Assessment of Potential
Productivity of Tree Species in
China, Mongolia and the Former
Soviet Union: Methodology and
Results
Fischer, G., van Velthuizen, H.T. and Prieler, S.
IIASA Interim Report
March 2001
Fischer G, van Velthuizen HT, and Prieler S (2001) Assessment of Potential Productivity of Tree Species in China, Mongolia
and the Former Soviet Union: Methodology and Results. IIASA Interim Report. IR-01-015, IIASA, Laxenburg, Austria
Copyright © 2001 by the author(s). http://pure.iiasa.ac.at/6505/
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IR-01-015
Assessment of Potential Productivity of Tree Species
in China, Mongolia and the Former Soviet Union:
Methodology and Results
Günther Fischer ([email protected])
Harrij van Velthuizen ([email protected])
Sylvia Prieler ([email protected])
Approved by
Arne Jemelöv ([email protected])
Acting Director, IIASA
March, 2001
Interim Reports on work of the International Institute for Applied Systems Analysis receive only
limited review. Views or opinions expressed herein do not necessarily represent those of the
Institute, its National Member Organizations, or other organizations supporting the work.
Contents
Abstract
vi
Acknowledgements
vii
About the Authors
viii
Chapter 1
Approach for the Assessment of Tree Species Productivity
1
1.1
1.2
1.3
1
1
2
Background
Ecological approach
This report
Chapter 2
Methodology Overview
3
Chapter 3
Land Resources Database
6
3.1
3.2
3.3
3.4
Chapter 4
Chapter 5
Chapter 6
Climate resources
3.1.1
Moisture regimes
3.1.2
Thermal regimes
3.1.3
Aspect and terrain slope effects on micro-climate
Soil and terrain resources
Seasonal wet sites
Land cover and accessibility
6
6
7
8
8
9
10
Potential Productivity Analysis
11
4.1
4.2
4.3
4.4
4.5
4.6
11
13
19
31
32
35
Land utilization types
Ecological requirements
Biomass increment calculation
Climatic related productivity constraints
Soil and terrain suitability analysis
Suitability analysis of seasonal wet sites
Preliminary Results of Potential Forest Production Assessment
37
5.1
5.2
5.3
5.4
38
39
41
42
Assessment scenarios
Results for biomass plantation forestry
Results for traditional production forestry
Results for conservation forestry
43
Concluding Remarks
45
References
ii
Figures
Figure 1
Figure 2
Figure 3
Conceptual framework of methodology.
2
Productivity assessment for tree species.
3
Relationship between leaf area index (LAI) and maximum growth rate as
a fraction of the maximum growth rate at LAI of 5.
27
Plates
Plate 1
Plate 2
Plate 3
Plate 4
Plate 5
Plate 6
Plate 7
Plate 8
Plate 9
Plate 10
Plate 11
Plate 12
Plate 13
Plate 14
Plate 15
Plate 16
Plate 17
Plate 18
Plate 19
Plate 20
Plate 21
Plate 22
Plate 23
Length of growing periods.
50
Thermal climates.
51
Mean temperatures of coldest month.
52
Mean temperatures of warmest month.
53
Minimum temperatures of the coldest month.
54
Temperature growing periods (LGP t=5 ).
55
Frost-free periods (LGP t=10 ).
56
Temperature sums (t > 5o C).
57
o
Temperature sums (t > 10 C).
58
Zones with accessibility to roads and railroads.
59
Agriculture and forest land.
60
Aridity index map.
61
States of the FSU and Oblasts within Russia Administrative areas of
FSU.
62
Provinces of China.
63
Productivity of Salix viminalis (t/ha biomass yield).
64
Productivity of Salix viminalis in accessible areas, excluding cultivated
and urban areas (t/ha biomass yield).
65
Suitability index for biomass plantation forestry (excluding cultivated
and urban areas).
66
Suitability index for biomass plantation forestry of current forest areas. 67
Suitability index for biomass plantation forestry in accessible areas
(excluding cultivated and urban areas).
68
Suitability index for traditional production forestry (excluding cultivated
and urban areas).
69
Suitability index for traditional production forestry of current forest
areas.
70
Suitability index for traditional production forestry of accessible areas
currently forested.
71
Suitability index for conservation forestry (excluding cultivated and
urban areas).
72
Tables
Table 1
Table 2
Table 3
Table 4
Table 5
Soil moisture storage capacity classes derived for FAO soil units and soil
depth/volume limiting soil phases
6
Thermal Climates
7
List of attributes derived from WISE soil profile database
8
Default slope classes
9
Post-winter period of water-logging due to snowmelt
10
iii
Table 6
Table 7
Table 8
Table 9
Table 10
Table 11
Table 12
Table 13
Table 14
Table 15
Table 16
Table 17
Table 18
Table 19
Table 20
Table 21
Table 22
Table 23
Conservation forestry LUTs
12
Traditional forestry LUTs
12
Biomass forestry LUTs
13
Climatic requirements
15
Soil requirements
20
Rotation and productivity characteristics
23
Relationships between temperature and rate of photosynthesis (Pm in kg
CH2 O ha-1 hr-1) for adaptability/productivity groups of boreal and
temperate tree species
25
Growth periods of deciduous tree species
26
Assumed forest fire intervals for conservation forestry. LUTs
31
Terrain-slope ratings (Fm > 1300)
34
LGP suitability ratings for water collecting sites: Group II tree species 35
LGP suitability ratings for water collecting sites: Group III tree species 36
LGP suitability ratings for water collecting sites: Group IV tree species 36
Suitability classification for conservation forestry
37
Very suitable and suitable areas for biomass plantation with willow
(Salix viminalis)
40
Very suitable and suitable areas for biomass plantation forestry
41
Very suitable and suitable areas for traditional production forestry
42
Areas suitable for conservation forestry
43
Appendixes
Appendix 1
Administrative Divisions
Table A1
List of States of the FSU, Oblasts of Russia.
Appendix II Potential Productivity for Forestry - Scenario results.
Salix viminalis:
Table A2
Table A3
Table A4
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Biomass plantation forestry:
Table A5
Table A6
Table A7
Table A8
Table A9
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Accessible areas currently under forest.
All areas, excluding cultivated areas, urban areas and areas currently
under forest.
Traditional production forestry:
Table A10
Table A11
Table A12
Table A13
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Accessible areas currently under forest.
iv
73
74
Table A14
All areas, excluding cultivated areas, urban areas and areas currently
under forest.
Conservation forestry:
Table A15
Table A16
Table A17
All areas.
All areas, excluding cultivated and urban areas.
All areas, excluding cultivated areas, urban areas and areas currently
under forest.
Appendix III Potential Productivity for Forestry - Scenario results.
Table A18
Table A19
107
FAO '90 soil unit ratings for tree species in boreal, temperate and
subtropical climates
FAO '90 soil phase ratings for tree species in boreal, temperate and
subtropical climates
DISCLAIMERS
Any part of this tree species productivity model and model parameters may be modified
in the light of new or improved knowledge and/or new objectives. The model is
expected to be expanded and refined with use.
The designations employed and the presentation of the material in this document do not
imply the expression of any opinion whatsoever on the part of IIASA concerning the
legal status of any sea area or concerning the legal status of any country, territory, city
or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.
v
Abstract
Over the past twenty years, the term agro-ecological zones methodology (AEZ) has
become widely used for global regional and national assessments of agricultural
potentials. The AEZ methodologies and procedures have recently been extended and
newly implemented to make use of the latest digital geographical databases, and to cope
with the specific characteristics of seasonal temperate and boreal climates.
This report presents details of a companion model of AEZ that enables assessments of
potential productivity of forest tree species. It is referred to as FAEZ.
The FAEZ methodology follows an environmental approach; it provides a standardized
framework for the characterization of climate, soil and terrain conditions relevant to
forest production and it uses environmental matching procedures to identify limitations
of prevailing climate, soil and terrain for a range of tree species and assumed
management objectives.
The model for the estimation of biomass increments is based on two well established
and robust models: the Chapman-Richard biomass increment model, and the AEZ
potential biomass model.
FAEZ includes an inventory of ecological adaptability characteristics as well as an
inventory of specific ecological and environmental requirements for 52 boreal and
temperate forest tree species. The natural resources inventory is based on the up-to-date
LUC-GIS database of climate, soil, terrain and vegetation covering China, Mongolia
and former Soviet Union.
Results of potential productivity for tree species in North, Central and East Asia are
presented under three different sets of assumptions of forest resources management and
exploitation, namely: conservation forestry, traditional production forestry and biomass
plantation forestry.
vi
Acknowledgments
This study is a first systematic ecological assessment of land productivity for boreal and
temperate tree species for a large area. It covers the territory of China, Mongolia and the
States of the Former Soviet Union. The study builds on methodologies and procedures
developed by IIASA and FAO for its recently completed Global Agro-Ecological Zones
2000 study. This current study, specifically for boreal and temperate tree species, would
not have been carried out at this time without the financial support provided by the New
Energy and Industrial Technology Development Organization(NEDO), (IIASAContract 99-148, NEDO, Paris, France), and the Netherlands Organization for Scientific
Research (NWO), (IIASA Contract 00-140 -- NWO, The Netherlands) and without
intellectual support and the facilities made available by IIASA's Land Use Change
(LUC) project.
Further we wish to express our gratitude to Mr. Otto Vaessen jr., student of Larenstein
University of Professional Education in Velp, The Netherlands for assistance with data
collection and to Ms. Cynthia Enzlberger-Vaughan for editing the report.
vii
About the Authors
Günther Fischer is the leader of a major research project at IIASA on Modeling Land Use
and Land Cover Changes in Europe and Northern Asia (LUC). A primary research
objective of this project is the development of a GIS-based modelling framework, which
combines economic theory and advanced mathematical methods with biophysical land
evaluation approaches to model spatial and dynamic aspects of land-resources use. He was
a member of the IGBP-HDP Core Project Planning Committee on Land-Use and LandCover Change (LUCC), and is a co-author of the LUCC Science Plan. He serves on the
Scientific Steering Committee of the joint LUCC Core Project/Programme of the IGBPIHDP, and leads the LUCC Focus 3 office at IIASA.
Harrij van Velthuizen has over twenty years experience in applied land resources
ecology. He was a member of the working group that developed FAO's Agro-Ecological
Zones (AEZ) methodology. As senior consultant and chief technical advisor, van
Velthuizen has been working for projects on agro-ecological assessments for
agricultural development planning in countries in Asia, Africa and South America.
Since 1995, van Velthuizen has been working closely with the IIASA-Land Use Change
Project on enhancement of the AEZ methodologies and various applications for the
Former Soviet Union, China, Bangladesh, Kenya and Nigeria and at the global level.
Recently he has also been serving as land resources ecologist in a FAO/UNDP project
concerned with Utilization of Agro-ecological Zones Databases at the Bangladesh
Agricultural Research Council, and as an advisor on agro-ecological zoning in a
DANIDA/World Bank project on Environmental Information Systems Development in
Ghana.
Sylvia Prieler is a Research Scholar and Geographic Information Systems (GIS) expert
with the Land-Use Change (LUC) Project at IIASA. In 1994 she obtained her Master's
degree in landscape planning and ecology at the University of Agricultural Sciences,
Vienna. She studied at the University of Manchester for a year in 1993, where she wrote
her dissertation on Environmental Assessment - Assessing Impacts on Terrestrial
Ecology and on the Landscape in the British context.
In 1994 Ms. Prieler joined the IIASA project on "Regional Material Balance
Approaches to Long-Term Environmental Policy Planning". In 1997 she joined the
IIASA LUC project as a GIS expert. She maintains the large LUC Arc/Info GIS
databases, and handles many requests for GIS-related services both from the LUC
researchers and outside collaborators. In addition, Ms. Prieler is working on specific
LUC research tasks with regard to climatic variability in China and its impact on
agricultural production potential.
viii
Assessment of Potential Productivity of Tree Species
in China, Mongolia and the Former Soviet Union:
Methodology and Results
Günther Fischer, Harrij van Velthuizen, and Sylvia Prieler
Chapter 1
1.1
Approach for the Assessment of Tree Species Productivity
Background
Why do particular trees grow where they do? How do they cope with their environment? How do they
respond to change? How productive are they – or could they become? These questions can only be answered if we know how trees and forests function from eco-physiological and environmental perspectives, and the way environmental factors and management (e.g. drought, competition, fertilization,
thinning) affect growth and partitioning.
Research in forestry has traditionally been empirical – treatments are applied and results are observed,
usually over periods of years (Landsberg, 1986). Forest yield predictions are traditionally based on the
site-index method and growth site correlation. The site-index estimation is made on the basis of the
height of the dominant and co-dominant trees of a fully stocked and evenly aged stand. The index is
estimated for permanent sample plots, which are normally established on sites with varying environmental conditions. Growth-site correlations are based on such sample plots, laid in a substantial number of stands that are well distributed over a range of environments found within an area, and are
measured repeatedly over a period of time to obtain growth data. In each of the sample plots, values of
land characteristics thought likely to affect tree growth are recorded. In this way, simple or multiple
correlations can be established between growth and site factors. Site factors, significantly related to
growth, are subsequently surveyed for other parts of the area for which no direct growth data is available, thus enabling yield predictions to be made for the entire study area. These techniques are empir ical instruments and do not employ information on tree and forest ecologies.
With an increased emphasis on multiple use forestry, plantation forestry, community forestry, agroforestry, and more recently on forests as renewable energy sources and the role of forests in global
CO2 balances, the scope of quantitative land evaluation for forestry is widening. In land evaluation, the
definition of land qualities is generally dictated by the sophistication of the ecological characterization
embodied in the land resources inventory. Also, the formulation of land use requirements, in terms of
land qualities, depends on the knowledge concerning the processes that govern the growth of trees and
forests, and how those processes are affected by the prevailing environmental conditions.
1.2
Ecological Approach
Quantitative and semi-quantitative land evaluation methods in particular the FAO/IIASA AgroEcological Zones (AEZ) approach for crop productivity assessment, have been adapted for the development of a companion model that assesses potential productivity of forest tree species, referred to as
FAEZ.
Similar to AEZ, the FAEZ methodology follows an environmental approach; it provides a standardized framework for the characterization of climate, soil and terrain conditions relevant to forest production and it uses environmental matching procedures to identify land use specific limitations of prevailing climate, soil and terrain resources, for assumed management objectives.
In its simplest form, FAEZ contains three basic elements as sketched in Figure 1 below:
(i)
Selected production systems with defined management objectives and species-specific environmental requirements and adaptability characteristics. These are termed Land Utilization Types;
(ii)
Geo-referenced climate, soil, terrain and land cover data which are combined into a land resources database, and
(iii)
Procedures for the calculation of potential biomass increments, and procedures for matching
forest species environmental requirements with the respective environmental characteristics
contained in the land resources database.
1.3
This Report
This report presents the FAEZ methodology and results of potential productivity for tree species in
North, Central and East Asia under different assumptions of forest resources management and explo itation, namely: conservation forestry, traditional production forestry and biomass plantation forestry.
LAND
(CLIMATE, SOIL AND
TERRAIN DATA)
LAND USE
DATA
LAND UTILIZATION
TYPES
(LUT)
DATA ANALYSIS
TREE SPECIES/LUT
REQUIREMENTS
LAND RESOURCES
DATABASE
BIOMASS
CALCULATION
----------------------------
MATCHING
OF LUT REQUIREMENTS
WITH LAND
RESOURCES
TREE SPECIES
PRODUCTIVITY
Figure 1
Conceptual framework of methodology
The report includes an inventory of ecological adaptability characteristics as well as an inventory of
specific climate, soil and terrain requirements for 52 boreal and temperate forest tree species. It also
provides the same details of the LUC-GIS database of climate, soil, terrain and vegetation covering
China, Mongolia and former Soviet Union, which constitute the 'backbone' of the study.
2
Chapter 2
Methodology Overview
Figure 2 presents a schematic overview of the flow and integration as implemented. The figure is explained in Box 1.
The FAEZ procedures are implemented to operate on a GIS grid-cell database. For each grid-cell, first
a climatic analysis is performed to derive climatic indicators relevant for matching climate conditions
with thermal requirements of tree species. Then, for LUTs passing this thermal screen, a soil moisture
balance is calculated and average annual biomass increments are estimated. Subsequently, these are
adjusted for limitations due to soil and terrain conditions. The results are stored in a grid-cell LUT
database, as input to scenario analysis, mapping and tabulation.
GIS
Forest Land
Utilization Types
(Forest/LUT)
Soils
Climate
Database
Climate Change
Scenarios
Elevation (DEM)
Physiography
Land cover
∆ P, ∆ T, ∆ Rad, ∆ CO2
Tree species/LUT Catalogue
Ecological Requirements
Biomass Parameters
Partitioning Coefficients
Tree species distribution
Infrastructure/Settlements
Admin. Boundaries
Climate Analysis
ETm, ETa, LGP, TR
Calculator
Land Resources
Database
Biomass Calculator
Climatic and
Edaphic
Matching
Procedures
Tree species/LUT
Productivity
Database
Multiple-Criteria Analysis
Soil Association
Composition
Database
Forest Landuse Scenarios
Forest Land Use
Options
Figure 2
Productivity Assessment for Tree Species
3
Box 1
Forest Land UtilizationTypes (LUT)
The forest land utilization types include definitions and descriptions of 52 tree species. The LUT attributes include characteristics of the tree species and information on management practices, inputs and utilization of
produce. The LUTs have been defined for three management objectives, i.e., conservation forestry, traditional
production forestry and biomass plantation forestry.
Tree species/LUT catalogue
The tree species catalogue database provides a quantified description of LUTs including crop adaptability
characteristics such as: rotation length, vegetation period, photosynthetic pathway, photosynthesis temperature
relationships, maximum leaf area index, partitioning coefficients, and parameters describing ecological requirements.
Climate database
The climate database with a 5 km grid-cell size contains long-term averages of monthly mean climate parameters. For China the climatic database was expanded with historical data on precipitation and temperatures
for the period 1958-1997.
Climate scenarios (not implemented for this initial study)
FAEZ has been set up to allow application of climate sensitivity tests and GCM based climate scenarios.
Land characteristics (GIS)
Soils, elevation (DEM), physiography, vegetation zones, present land use/cover and administrative div isions are kept as individual layers in the geographical information system:
•
Soil and terrain data, from the Soil and Physiography database for North and Central Asia. (FAO/IIASA
1999), covering China, Mongolia, and the territory of the former Soviet Union
•
Elevation data, from the GTOPO30 data set (EROS Data Center, 1998). Altitude differences of neighboring grid-cells were applied to compile a terrain slope/aspect distribution database in terms of seven average slope range classes.
•
Land cover data was derived for China, from the 1:1,000.000 Land Use map of China (Wu Chuanjun,
1991); for the FSU from the IIASA/LUC Agricultural Regionalization and Land Categories databases
(Stolbovoi at al., 1997a, b), and for Mongolia from the Vegetation Distribution Inventory for Mongolia
(Sitch and van Minnen, 1996).
•
Infrastructure information has been derived from the Digital Chart of the World (DCW, 1993). It has been
used to create an accessibility inventory for the territory of China, Mongolia and the FSU.
•
Tree species distribution in China, derived from the Vegetation map of China, Institute of Botany, Chinese Academy of Sciences in Beijing. For the FSU, from the IIASA/LUC Vegetation database
http://www.iiasa.ac.at/Research/LUC/GIS
Soil association composition database
The soil association composition database contains occurrences of soil units, soil phases, textures and terrain slope classes.
Land resources database (GIS)
The land resources database includes layers of the digital soil map of North and Central Asia, the slope
distribution database, land cover layers, infrastructure and administrative areas and associated attribute databases.
Climate data analysis (ETo, ETa, LGP and TR calculation)
From basic climatic data, monthly reference evapotranspiration (ETo) is calculated according to Penman
Monteith. A water-balance model provides estimations of actual evapotranspiration (ETa) and length of growing
period (LGP). Temperature and elevation/aspect data are used for the characterization of thermal regimes (TR) as
follows:
•
Thermal climates, representing major latitudinal climatic zones;
•
Winter and summer temperatures and extreme temperatures;
•
Temperature growing periods (LGPt ), and
4
•
Accumulated temperatures.
Tree species/LUT thermal requirements
Temperature requirements of individual tree species are matched with temperature regimes prevailing in
individual grid-cells. For grid-cells with an optimum or sub-optimum match, biomass increment calculations are
performed.
Biomass increment calculation
The FAEZ methodology for the calculation of potential biomass is based on the Chapman-Richard bio mass increment model and the eco-physiological biomass and yield model of Kassam. It provides temperature
and radiation limited biomass increments of individual tree species.
Climatic suitability
Climatic constraints cause direct or indirect losses in the biomass increment. Climatic constraints1 are influenced by the following conditions:
•
•
•
•
•
The variability and degree of water-stress during the growing period;
Constraints indirectly related to climatic conditions (e.g., pests, diseases and invasion of unwanted species
or weeds);
The climatic factors which effect the efficiency of forestry operations and costs of production;
The risk of occurrence of late and early frost, and
The risk of forest fire (for conservation forestry).
The climatic constraints for individual tree species - by management objective – have been specified according to the prevailing temperature and moisture regimes.
Soil and terrain suitability
The edaphic suitability assessment is based on matching of soil and terrain requirements of tree species
with prevailing soil and terrain conditions. These are management/input specific.
Tree species/LUT productivity database
The results of the matching of tree species/LUT-specific environmental requirements with prevailing climate, soil and terrain conditions is combined with quantified biomass increments. This data is stored in the tree
species/LUT productivity database by grid-cell.
Forest Land Use Scenarios/Multiple criteria analysis (not implemented for this initial study)
Forest land-use scenarios are formulated on the basis of actual and desired land-use. These scenarios and
the potential productivity for the Forest LUTs serve as input in the multiple criteria analysis tool, which in turn
provides selection of individual grid-cells feasible for forest land-use alternatives.
1
At this stage of the methodology development, constraints indirectly related to climatic conditions such as pests, diseases, invasion of unwanted species or weeds and workability, have not been taken into account.
5
Chapter 3
Land Resources Database
The FAEZ methodology for the productivity assessments of forest species provides a framework for
establishing a spatial inventory and database of land resources. The land resources inventory (LRI) includes components of climate, soils, landform, current land cover and accessibility. The individual LRI
components are selected, defined and classified in a manner that is as much as possible matching
available specific ations of ecological requirements of tree species.
The climatic resources inventory is based on the Leemans and Cramer climate database (Leemans and
Cramer, 1991), which was enhanced in IIASA/LUC with the help of the Potsdam Institute for Climate
Impact Research (PIK). The database offers a spatial resolution of 5 km and contains monthly climate
averages which allow quantification of each 5 km grid-cell in terms of thermal climates, summer-,
winter- and extreme temperatures, temperature sums, various types of length of growing periods,
moisture deficits and surpluses, etc.
The Soil and Physiography database for North and Central Asia (FAO/IIASA, 1999), covering China,
Mongolia, and the territory of the former Soviet Union was used. This digital soil map presents soil
associations in grid-cells of 5-km resolution. The composition of soil associations is described in terms
of percentage occurrence of soil units, soil phases and textures.
Terrain slopes were derived from the GTOPO30 digital elevation data. From this DEM also a terrainslope distribution database was compiled.
3.1
Climate Resources
3.1.1 Moisture regimes
Monthly totals of reference evapotranspiration (ET0 ) are calculated for each grid-cell. A water-balance
model, comparing moisture supply from rainfall/snow and storage in soils with potential evapotranspiration provides estimations of actual evapotranspiration (ETa).
A general characterization of moisture conditions is achieved through the concept of length of growing
period (LGP), i.e., the period during the year when both moisture availability and temperatures are
adequate for plant growth.
The growing period continues beyond the rainy season because of moisture stored in the soil profile.
The amount of soil moisture stored in the soil profile, and available to plants varies with depth of the
soil profile, the soil physical characteristics, and the rooting pattern of the plant. Depletion of soil
moisture reserves causes the actual evapotranspiration to fall short of the potential rate. Soil moisture
storage capacity of soils (Smax) depends on soil physical and chemical characteristics, but above all on
effective soil depth or volume (Fisher et al., 2000). For tree species the maximum effective rooting
depth has been assumed to range between 0.5 m and 2 m.
The Smax values presented in Table 1 were used to set limits to available soil moisture, enabling calculation of possible extension of the growing period beyond the end of the rainy season by soil unit,
soil texture class, and soil phase. Plate 1 presents length of growing period zones in map form.
Table 1
Soil moisture storage capacity classes derived for FAO soil units and soil
depth/volume limiting soil phases
Class
Smax
(mm)
1
2
3
4
5
6
225 mm
185 mm
150 mm
115 mm
50 mm
15 mm
Soils with Lithic Phase
(mm)
50 mm
40 mm
35 mm
25 mm
15 mm
n.a.
Soils with Petroferric
and Duripan
115/50 mm
90/40 mm
75/35 mm
55/25 mm
35/15 mm
n.a.
6
Soils with Skeletic and Rudic Phases
(Revised Le gend ’90)
115 mm
90 mm
75 mm
55 mm
25 mm
n.a.
3.1.2 Thermal regimes
Thermal regimes are quantified for each grid-cell in terms of four types of attributes, namely :
•
Thermal climates, representing major latitudinal climatic zones;
•
Winter and summer temperatures;
•
Temperature growing periods (LGP t ), and
•
Temperature sums
Thermal Climates
The thermal climates are obtained through classifying of monthly temperatures corrected to sea level
(with an assumed lapse rate: 0.55°C/100m). The temperate and boreal belts have been subdivided according to continentality into three classes, namely: oceanic, sub-continental and continental. The subtropics have been subdivided into a summer and winter-rainfall type. Table 2 presents the thermal climate classification used for sub-tropical, temperate and boreal zones. The geographic distribution of
the thermal climates is presented in Plate 2.
Table 2
Thermal climates
Thermal climate classification
Subtropics: One or more months with monthly mean
Subtropics Summer Rainfall
temperatures, corrected to sea level, below 18oC but
Northern hemisphere: rainfall in April - September ≥
above 5oC
rainfall in October - March
Southern hemisphere: rainfall in October - March ≥
rainfall in April - September
Subtropics Winter rainfall
Northern hemisphere: rainfall in October - March ≥
rainfall in April - September
Southern hemisphere: rainfall in April - September ≥
rainfall in October - March
Temperate: At least one month with monthly mean temOceanic Temperate: Seasonality less than 20°C*
peratures, corrected to sea level, below 5°C and four or
Sub-continental Temperate: Seasonality 20-35°C*
more months above 10°C
Continental Temperate: Seasonality more than 35°C*
Boreal: At least one month with monthly mean temOceanic Boreal: Seasonality less than 20°C*
peratures, corrected to sea level, below 5°C and more
Sub-continental Boreal: Seasonality 20-35°C*
than one but less than four months above 10°C
Continental Boreal: Seasonality more than 35°C*
Polar/Arctic: All months with monthly mean temperatures, corrected to sea level, below 10°C
*
Seasonality refers to the difference in mean temperature of the warmest and coldest month, respectively.
Winter and summer temperatures
Mean temperatures of the warmest and coldest months as well as minimum temperatures of the coldest
month were determined. Plate 3, 4 and 5 present the respective isotherm maps.
Temperature growing periods and temperature sums
In addition to thermal climates and temperature extremes, temperature growing periods (LGP t ) have
been calculated. For instance LGPt=5 of 5°C, i.e., the number of days when mean daily temperature
exceeds 5°C, represents the period with temperatures suitable for plant growth. Similarly LGP t=10 of
10°C approximates the frost-free period. Lengths, beginning and ending dates of such periods are calculated for each grid-cell and are stored in the attribute database. Plate 6 and 7 present respectively
maps of temperature growing periods (LGP t=5) and frost-free periods (LGP t=10). Accumulated temperatures have been calculated for base temperatures of 0, 5 and 10o C. Plate 8 and 9 present maps of
temperature sums with base temperatures of respectively 5 and 10°C.
7
3.1.3 Aspect and terrain-slope effects on micro-climate
Many studies have shown how micro-climate and forest responses differ on north and south facing
slopes. The solar geometry calculations provide a means for computing incident solar radiation to any
combination of slope aspects each day of the year (Garnier and Ohmura, 1968 and Swift, 1976). From
differences in computed solar radiation aspect related temperature differences can be inferred. For instance a south facing slope would be 1-2o C warmer than flat terrain. A north facing slope however
might be 1-2o C cooler than flat terrain. On south facing slopes snow may melt 1-2 months earlier than
adjacent north facing slopes of the same elevation.
The terrain slopes data derived from GTOP030 also provide information on aspect. With the help of
procedures described by Warring and Running (1998), effects of slope/aspect combinations can be
used to modify attributes of the climate database (including solar radiation, temperature, evapotranspiration and growing period parameters). Thus, the forest productivity assessment, in particular in high
latitude zones, can take account of micro-climatic effects of prevailing aspect and terrain slope combinations.
3.2
Soil and Terrain Resources
The source of soil information used is the Soil and Physiography database for North and Central Asia
(FAO/IIASA 1999), covering China, Mongolia, and territory of the former Soviet Union. This digital
soil map presents soil associations in grid-cells of 5-km resolution. The composition of soil associations is described in terms of percentage occurrence of soil units, soil phases and textures. Therefore,
each 5 km grid-cell is considered as consisting of several land units.
The soil units, classified according to the revised legend of the FAO/Unesco Soil Map of the World
(FAO/Unesco/ISRIC, 1990), are defined in terms of measurable and observable properties of the soil
itself. Many of these properties are relevant to the use and production potential of soils. Through linkage with the World Inventory of Soil Emissions Potential (WISE) soil profile database (Batjes et. al.,
1997) statistics on physical and chemical soil attributes by 'FAO’90' soil unit/topsoil texture combinations were derived for matching soil requirements of the tree species with soil characteristics (Table 3).
Table 3
List of soil attributes derived from WISE soil profile database
Profile identifiers
FAO-Unesco soil unit (1990 Legend)
Topsoil textural class
Attributes (for topsoil and subsoil)
Organic carbon
pH(H2 O)
Sum of exchangeable Ca, Mg, Na and K (TEB) ◊
Ratio of exchangeable Ca/Mg ◊
Ratio of exchangeable (Ca+Mg)/K ◊
Effective CEC †
CECsoil
CECclay ◊
Base saturation (as %)
CaCO3 content
Gypsum content
Exch. sodium percentage (ESP) ◊
Bulk density
Total porosity (as derived from bulk density) ◊
% sand
% silt
% clay
Available Water Capacity (AWC1 ; from pF 2.0 to pF 4.2)
Available Water Capacity (AWC2 ; from pF 2.5 to pF 4.2)
◊
†
Calculated from other measured soil properties.
ECEC is defined as sum of exchangeable [Ca+Mg+K+Na]+ exchangeable [H+Al], after Van Reeuwijk (1993).
8
Two sources of geo-referenced terrain slopes are available for use: (i) terrain slopes indicated in the
mapping unit expansion tables of the digital soil map, and (ii) terrain slopes derived from GTOPO30
data (EROS Data Center, 1998). The latter terrain-slope database has been generated with a rule-based
algorithm to calculate slope distributions in terms of seven slope classes per 5 km grid-cell, based on
neighborhood relationships among grid-cells in the 30 arc-second GTOPO30 database (Fischer et al.
2000).
Terrain slopes indicated in the digital soil map distinguish three broad slope classes as follows:
Class a:
Class b:
Class c:
level to undulating, dominant slopes ranging between 0 and 8 percent;
rolling to hilly, dominant slopes ranging between 8 and 30 percent;
steeply dissected to mountainous, dominant slopes over 30 percent.
The terrain slopes of the digital soil map apply to the dominant soil unit of a soil association mapping
unit. Where two slopes are indicated for a mapping unit (i.e., a/b or b/c), they apply each to 50 percent
of the extent of the dominant soil unit. For all associated and included soils, default slope classes (Table 4) are assigned to the individual soil units (FAO, 1978-81) as follows:
Table 4
Default slope classes
Default slope class
a
a/b
b
b/c
Soil Units in FAO’90
Fluvisols, Gleysols, Histosols, Planosols, Solonchaks, Solonetz and Vertisols
Arenosols, Anthrosols, Chernozems, Ferralsols, Greyzems, Gypsisols, Kastanozems,
Luvisols, Lixisols, Podzoluvisols, Phaeozems, Plinthosols, and Podzols
Acrisols, Alisols, Calcisols, Cambisols, Nitisols and Regosols
Andosols, and Lepthosols
The slope classes of the digital soil map are very broad and do not reflect the information contained in
recent digital data sets. Hence, the above broad slope classes have been refined on the basis of know ledge about soil unit-slope relationships and information derived from GTOPO30. Slopes derived from
the 30 arc-second DEM were allocated to soil units occurring within individual soil associations
(Fisher et al., 2000).
3.3
Seasonal Wet Sites
High groundwater levels, water-logging and flooding affect the distribution of tree species. These soil
wetness conditions are restricted mainly to floodplain areas, water collecting sites and in some cases
also to poorly drained flat terrain. Excessive soil wetness conditions are usually due to internal soil
drainage characteristics or prolonged frozen condition of soils. In particular in continental temperate
and boreal zones, poorly drained or frozen soils in flat terrain frequently become submerged or wate rlogged in early spring as a result of water accumulation from snowmelt.
Fluvisols and Gleysols
The flooding attributes of Fluvisols are generally controlled by external factors such as a river’s flood
regime which in turn is influenced by hydrological features of the catchment area and catchment/site
relations, rather than by the amount of 'on site' precipitation. The flooding regime in arid and semi-arid
zones is often erratic. In some years severe flash floods may occur, while in other years no floods may
occur at all. In sub-humid and humid zones flooding is more regular but duration and depth of flooding
may vary widely from year to year.
Gleysols are not directly affected by river flooding. These soils are however frequently situated in lowlying water collecting sites and when not artificially drained, Gleysols may be subject to water-logging
or even inundation as a result of combinations of high groundwater tables and ponding rainwater. In
sub-humid and humid areas Gleysols often remain wet for extensive periods, rendering them unsuitable for tree species sensitive to water-logging.
On the other hand, certain trees species which are tolerant to flooding, water-logging and high
groundwater tables may perform well on residual soil moisture available on both, Fluvisols and
Gleysols. Therefore, the separate suitability classification for water collecting sites does account for
9
specific tolerances to excess moisture (high groundwater tables, water-logging and flooding/inundation). Gleysols are mostly but not necessarily subjected to water-logging and inundation, as
are the 'natural Fluvisols'. Therefore, Gleysols with terrain-slopes of less than 2% in the model are
handled as Fluvisols.
Excess water due to snowmelt
Excessive wetness might however also occur in other soils. For example, in continental temperate and
boreal areas, as result of snowmelt at the end of the winter period, large tracts of land tend to become
waterlogged or ponded with water. Especially flat terrain with poorly drained soils may be affected by
substantial periods of wet conditions (Fischer et al., 2000). Depending on the amount of excess moisture from melted snow, the following assumptions were made for the period of waterlogged conditions 2 (Table 5).
Table 5
Post-winter period of water-logging due to snowmelt
Excess moisture from
snowmelt (mm)
40
80
120
180
240
Length of period of water-logging (days)
Very poorly drained soils
Poorly/imperfectly drained soils
0
0
5
0
15
10
30
20
45
30
Note: Drainage classes are according to the FAO Guidelines for Soil Description. (FAO, 1990)
3.4
Land Cover and Accessibility
Prior to the actual productivity assessments, current occurrence of cultivated areas and forested areas
and accessibility to infrastructure was inventoried and integrated in the basic land resources database.
From data available in the IIASA LUC project, a GIS3 coverage of agriculture and forest land for the
territory of China, Mongolia and the former Soviet Union was compiled (Plate 12). This coverage has
been used to mask or select areas, that are in use for cultivation, are under forest, or are under other
permanent uses such as urban areas, mining areas etc.
Infrastructure information of the Digital Chart of the World (DCW, 1993) has been used to create an
accessibility inventory for the territory of China, Mongolia and the FSU. With standard GIS procedures buffer zones4 of 10 km around roads and railways were established, i.e., 5 km on each side (Plate
11). The coverage of buffer zones subsequently was converted into a 5km grid, which in turn served as
a proxy for accessibility.
2
3
4
Periods of excessive rainfall may also lead to widespread waterlogging or even ponding during the vegetation period
of trees. Therefore, levels of accumulated excess rainfall have been treated in a similar manner as wetness originating
from snowmelt after the winter period.
The map showing cultivated areas and forested areas has been compiled from the land categories inventory of the
FSU (Stolbovoi et al. 1997a), the 1:1,000,000 land use map of China (Wu Chuanjun, 1994) and Vegetation Distribution for Mongolia (Sitch and van Minnen, 1996). These three data sets were combined, a reclassification was applied
featuring agriculture and forest, and was transferred to the 5km grid.
It has been assumed that a distance of 5km to nearest road or railway would facilitate sufficiently the accessibility
required for forest management and logging operations.
10
Chapter 4
4.1
Potential Productivity Analysis
Land Utilization Types
The suitability of land for trees relates to the performance of the forestry system, which involves two
components, the land unit and land utilization type. Land utilization types (LUTs) must be defined before the assessment of the suitability of land. Different LUTs have different requirements for land
quality. If the quality of a land unit matches the land use requirement of a defined LUT, its suitability
is high. Furthermore, selection and definition of LUTs guides the selection of land characteristics to be
represented in the land resources inventory. These characteristics are then used as evaluation criteria in
the suitability analysis (FAO, 1984).
In this study, covering boreal, temperate and subtropical part of China, Mongolia and the former Soviet Union, the data used for the definition of LUT includes tree species characteristics such as: rotation height, rotation length, achieved maximum production levels, temperature dependent rates of
photosynthesis, partitioning coefficients, moisture stress related yield reduction coefficients, wood
density coefficients, and CO2 sequestration capacities. Further, parameters are included which describe
ecological requirements of the individual tree species regarding radiation regimes, thermal regimes,
moisture regimes and regarding soil and terrain conditions.
Three kinds of forest resources management and exploitation are assumed. The first type has as management objectives, nature conservation, bio-diversity preservation and limited selective extraction of
individual trees, and/or environmental protection objectives such as stabilization of steep slopes, dunes
or shifting sand and windbreaks/dust filters. This type is referred to as 'conservation forestry'. The second type reflects traditional forestry, with main management objectives being maximizing quality and
quantity of timber/wood/pulp production. This type is referred to as 'traditional production forestry'.
The third type captures the fully mechanized bio-fuel and pulpwood production for energy generation
and industrial application of pulpwood. This type is characterized by short rotations of single stem or
coppice systems and is referred to as 'biomass plantation forestry'.
The LUT data compiled for this study comprises 36 deciduous tree species, 14 coniferous species and
2 deciduous coniferous species (larches).
Conservation forestry
This forestry type consists of mixed forest with multi-aged stands. The management is focused on
preservation of a diversified ecosystem; it includes some basic measures for fire protection and extraction of selected dominant and co-dominant trees. Invasion of exotic species as well as occurrences of
pests and diseases are monitored and minimized. Stands are generally tending towards climax conditions. Extraction takes place at sub-optimum rotation lengths, generally mature or over-mature individual trees.
Under unprotected conditions in arid and semi-arid environments (aridity index5 of vegetation period
P/PET < 0.5), forest fires occur at intervals as short as 15 years to about 60 years. These zones are
dominated by fire-susceptible light coniferous tree species (such as larch and pine) and some smallleaved species (such as Betula papyrifera). In moderately dry boreal, temperate and subtropical-winter
rainfall zones (aridity index 0.5 - 1.0), characterized by a mix of mainly dark and light coniferous tree
species and some broad-leaved species, forest fire intervals occur roughly between 75 and 150 years.
In sub-humid and humid zones (including subtropics with summer rainfall) dominated by broadleaved
and dark coniferous forest species, occurrences of forest fires are rare (adapted from Shvidenko and
Nilsson, 1995). The size of areas affected by individual forest fires in the majority of the incidents is
typical less than 5 ha, but in extreme cases in particular in dry boreal environments fires may cover areas as large as 50,000–200,000 ha (Payette, 1992). It has been assumed that the conservation forest
LUTs are affected by fire hazards at regular intervals (see Section 4.4).
5
Plate 12 presents the aridity index map (P/PET) covering China, Mongolia and the FSU
11
The LUT attributes listed in Table 6 form the basis for the tree species suitability assessment for conservation forestry.
Table 6
Conservation forestry LUTs
LUT Attributes
Tree species considered
Produce
Management objectives
Capital Intensity
Labour Intensity
Power source
Technology
Productivity
Environmental hazards
Environmental benefits
Infrastructure requirement
Scale of operation
Conservation Forestry
Birch, Poplar, Willow, Oak, Beech, Hornbeam, Ash, Alder, Lime, Maple, Robinia,
Chestnut, Walnut, Larch, Spruce, Pine and Fir.
Wood for various purposes
Land conservation: Sand dune fixing, slope stabilization, wind break, pollution/dust filters, soil improvement; pest, disease and fire control measures; limited tree extraction.
Low
Low; nature conservation personnel
n.a.
No fertilizer; self-seeding; limited pest, disease control, no fire prevention measures
Low
It is assumed that natural fires occur at intervals 15-60 years in dry boreal zones and at
intervals between 75 and 150 years in moderately dry boreal, temperate and subtropical
zones. No fire protection measures are assumed.
Stable forest eco-systems: preservation of bio-diversity; carbon dioxide sequestration in
stem-wood, roots and soil.
Access to research information.
Limited operations at small scales
Traditional production forestry
This type involves the control of forest composition, establishment and growth. Traditional planting/regeneration and harvest methods – clear-felling, seed-tree and shelter-wood in even-age management - are used for the planting/regeneration and subsequent growth of commercially important tree
species. Harvest at age of maximum yield (optimum rotation length).
In the productivity assessment for traditional forestry, adequate measures and management are assumed which would prevent from production loss due to natural uncontrolled forest fires. Table 7 presents the main LUT attributes for traditional production forestry.
Table 7
Traditional production forestry LUTs
LUT Attributes
Tree species considered
Produce
Management objectives
Capital Intensity
Labour Intensity
Power source
Technology
Productivity
Environmental hazards
Environmental benefits
Infrastructure requirement
Scale of operation
Traditional Production Forestry
Birch, Poplar, Oak, Beech, Robinia, Larch, Spruce, Pine and Fir.
Timber/pulp
Commercial timber and pulp production: pure equal-aged stands; optimum rotation lengths;
maximization of high quality timber production; clear fell and other clearing systems.
High
Medium; planting/seeding, maintenance and clearing
Mechanized
Good planting material; mechanized planting; start-off fertilizer; proper thinning; pest, disease and erosion control; mechanized clear felling and full fire prevention measures (which
may occupy up to 10% of the forest production area).
High
Soil erosion and nutrient leaching hazards; pest and diseases ; natural fire hazards are assumed minimized through adequate protection measures.
Carbon dioxide sequestration in stem wood, roots and soil
Adequate market accessibility; access to research information and advisory services.
Large enterprises
12
Biomass plantation forestry
This special type of forestry is concerned with maximization of wood biomass output per hectare for
energy production 6 from bio-fuel and for the pulp and paper industry. Highly productive pioneer species are grown as monoculture plantations in short rotations. In this assessment only a short duration
rotation coppice (SRC) system with willow (e.g., Salix viminalis) and short duration rotation single
stem (SRSS) systems with suitable poplar, alder and ash species are considered. It is assumed that for
the SRC system the first harvest takes place after five years and subsequently every three years up to
an age of 20-25 years and for SRSS systems 7-10 year rotations apply. Fertilization, annual weeding
and mechanical harvesting are assumed. The density of SRC systems is assumed 2500 surviving stools
per hectare (Leave area index = 4). Further, it is assumed that optimum harvest periods are selected
and that all harvested biomass is utilized. Table 8 presents main LUT attributes for biomass plantationforestry.
Table 8
Biomass plantation forestry LUTs
LUT Attributes
Biomass Plantation Forestry
Tree species considered
Produce
Selected Poplar, Alder, Ash and Willow species.
Bio-fuel/pulp
Management objectives
Commercial bio-fuel and pulp production; plantations of fast growing willow in short duration rotation coppice systems and Poplar, Alder and Ash species in short duration single
stem rotations; maximizing above ground biomass yields; felling systems with “harvesters”.
Capital Intensity
High
Labor Intensity
Low; mainly control of pest, disease and invasion of unwanted species.
Power source
Technology
Highly mechanized
Selected fully treated planting material; fully mechanized planting or coppicing; adequate
use of fertilizer, pesticides; fully mechanized planting and clear felling and where required
full fire prevention measures (which may occupy up to 10% of the biomass plantation area).
Productivity
Very High
Environmental hazards
Environmental benefits
Pollution due to fertilization, use of pesticides and chemical weed control.
Potential for groundwater quality improvement, e.g., through nitrate extraction by coppice
tree crops; carbon dioxide sequestration in roots and soil.
Infrastructure requirement
Adequate pulp/paper industry and/or bio-energy production units or pellet/bricket production
industry readily accessible. High level of advisory services and application of research findings.
Medium and large enterprises
Scale of operation
4.2
Ecological Requirements
The ecological requirements of the 52 selected tree species are presented in two parts, namely (a)
quantified climate requirements and (b) semi-quantified soil requirements. Main sources used are:
Song Zhaomin and Meng Ping (1993); Chartier (Ed.) (1995); Shugart (Ed.) (1992); Kruessmann
(1972); Schmidt-Vogt. (1987); Schuett et al. (1999); Jansen et al. (1995), and Shvidenko et al.,
(1996a, b).
As part of the climatic suitability analysis, temperature requirements of tree species are matched with
actual temperature regimes in grid-cells. When the temperature characteristics in a particular grid-cell
6
Several tree species are currently used for forest biomass production systems. Examples apart from willow include:
poplar, eucalyptus, black locust and selected conifers. These species are used in either short rotation coppice systems
or in short rotation single stem systems. In boreal and temperate environments mainly willow and to some extent
poplar systems are used. The short rotation willow, apart from production of biomass is also being used for purification (nitrate reduction) of groundwater (Perttu and Aronsson, 1995).
It is envisaged to compare potential productivity and energy efficiency of forests biomass production systems with
energy crops, such as: rape, sunflower, sugar beet, sweet sorghum, wheat, cystle (Cynara cardunculu) and a C4 perennial grass (Miscanthus sinensis giganteus). Recent research with this C4 grass has shown that per annum dry matter
yields of 20-25 t/ha are achievable.
13
match tree species temperature requirements in optimum or sub-optimum fashion, then this tree species is considered in the biomass increment calculations.
Thermal suitability is assessed through matching thermal requirements of individual tree species/LUTs
with average thermal conditions in a particular grid-cell. The thermal conditions considered are; mean
temperatures of the coldest and the warmest month, length of frost-free period, length of vegetation
period, length of dormancy period and temperature sums during vegetation and frost-free period (Table 9). In case all conditions are met in an optimum fashion, the rating is S1 (optimal conditions). In
case one or more conditions only meet range conditions, the rating is S2 (sub-optimal conditions).
When one or more conditions fall outside the range conditions, the rating of that particular cell is not
suitable.
The moisture suitability analysis is essentially based on the comparison of tree species specific drought
tolerances with the moisture conditions during the respective vegetation period. For each of the tree
species two thresholds have been set, one between optimum and sub-optimum conditions for growth
(parameter κ) and one between sub-optimum growth and not suitable conditions (parameter λ). Further
it is assumed that with increasingly dry conditions spacing of trees becomes wider. Therefore in such
conditions gradually lower than optimum LAI values (parameter µ) are assumed see Table 11.
Climatic requirements of tree species were expressed in optimum, range and not suitable conditions as
presented in Table 9 and include the following parameters:
(i)
(ii)
(iii)
(iv)
(v)
(vi)
(vii)
Mean temperatures of the coldest and the warmest month;
Minimum temperatures of the coldest month;
Frost-free period (days with mean temperature > 10o C);
Periods of biological activity (days with Tmean > 5o C);
Dormancy periods;
Accumulated temperatures (base temperatures of 5o C and 10o C);
Length of growing periods (days);
Sources:
Barnes et al., (1998); Burschel and Huss, (1997); Chartier et al., (1995); Chen, (1999);
IIASA-LUC (1998a, b, c); Jansen et al., (1995); (1968), Kassam, (1977); Köstler et al.,
(1968), Krüssmann. (1972, 1983); Mitscherlich, (1975); Nikolov and Helmisaari, (1992);
Perttu and Aronsson, (1995); Schmidt-Vogt, (1987); Schmidt, (1987, 1989); Schober,
(1975); Schuett (1999) Shugart, (1992); Shvidenko et al., (1996a, b); Stolbovoi et al.,
(1997a); Woods and Hall, (1994).
All climatic parameters have been estimated/verified by overlaying species distribution maps and climatic maps.
.
14
Table 9
Climatic requirements
OPTIMUM CONDITIONS
Temperate and Boreal Deciduous Tree Species
Birch
Poplar
Willow
Oak
Beech
Hornbeam
Ash
Alder
Lime
Maple
Locust
Chestnut
Walnut
7
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula platypphylla
Betula papyrifera
Populus nigra
Populus euramericana cv rob.
Populus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Salix alba
Salix viminalis
Quercus robur
Quercus petracea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Fagus sylvatica
Carpinus betulus
Fraxinus excelsior
Fraxinus mandshurica
Alnus glutinosa
Tilia cordata
Acer plantanoides
Acer campestre
Acer campbellii
Robinia pseudoacacia
Castanea sativa
Junglans regia
Tmean
Jan
(o C)
Tmean
July
(o C)
Tmin
Jan
(o C)
LGPT
10 o C
(days)7
LGPT
5 oC
(days)
Dormancy
break
(days)
Tsum
10 o C
(ddays)
Tsum
5 oC
(ddays
)
>-40
>-40
>-40
>-40
>-30
>-28
>-30
>-30
>-30
>-35
>-35
>-35
>-15
>-20
>-30
>-30
>-20
>-5
>-10
>0
>-20
>-10
>-10
>-30
>-5
>-20
>-8
>-30
>-20
>-25
>-20
>-8
>-15
>-10
>0
>-20
12-20
14-20
12-16
12-16
14-23
14-23
15-30
15-30
17-30
16-26
15-26
15-26
17-26
20-30
16-28
16-28
15-27
15-28
16-24
20-32
16-27
20-27
20-27
16-20
16-22
16-25
18-25
16-24
16-24
14-22
16-24
18-24
15-24
16-27
16-22
16-24
-55
-50
-50
-55
-40
-40
-35
-35
-35
-45
-45
-45
-20
-25
-35
-35
-25
-10
-15
-5
-25
-15
-15
-35
-10
-25
-15
-35
-25
-30
-30
-15
-20
-15
-1
-25
>75
>90
>90
>75
>90
>90
>120
>120
>135
>90
>90
>90
>135
>135
>120
>120
>150
>165
>165
>180
>150
>180
>180
>120
>165
>150
>150
>150
>150
>135
>150
>150
>135
>165
>180
>150
>120
>135
>135
>120
>135
>135
>150
>150
>165
>120
>135
>135
>165
>165
>150
>150
>180
>210
>210
>240
>180
>225
>225
>135
>210
>180
>180
>180
>180
>165
>180
>180
>165
>225
>225
>180
>105
>90
>90
>105
>90
>90
>30
>30
>30
>75
>60
>60
>30
>30
>30
>30
0
0
>45
>30
0
>45
>45
>150
>60
0
0
0
0
0
0
0
0
0
>60
0
>1000
>1200
>1200
>1000
>1200
>1200
>2400
>2400
>3000
>1600
>1800
>1800
>3000
>3000
>1800
>1800
>2000
>2100
>2100
>3000
>2000
>3000
>3000
>1800
>2200
>2200
>2000
>2000
>2000
>1800
>2000
>2000
>2000
>2300
>2500
>2200
>1400
>1600
>1600
>1400
>1600
>1600
>2800
>2800
>3400
>2000
>2200
>2200
>3400
>3400
>2200
>2200
>2400
>2500
>2500
>3400
>2400
>3400
>3500
>2100
>2750
>2600
>2500
>2500
>2400
>2200
>2400
>2500
>2400
>2750
>3000
>2600
LGP
(days)
>120
>135
>135
>120
>135
>135
>135
>135
>150
>120
>135
>135
>150
>150
>135
>135
>150
>150
>180
>180
>150
>180
>150
>120
>180
>150
>165
>165
>165
>135
>150
>150
>150
>135
>195
>150
All temperate and boreal deciduous tree species are confined to areas with winter temperatures at least for some time below 10oC. For optimum levels LGPT10 < 330 days has been used as cut off.
15
OPTIMUM CONDITIONS
Deciduous Coniferous Trees
Larch
Larix gmelinii
Larix sibirica
Tmean
Jan
(o C)
Tmean
July
(o C)
Tmin
Jan
(o C)
LGPT
10 o C
(days)
LGPT
5 oC
(days)
Dormancy
break.
(days)
Tsum
10 o C
(ddays)
Tsum
5 oC
(ddays
)
> -45
> -40
12-20
12-20
-55
-45
>75
>75
>120
>120
>165
>165
>950
>1000
>1300
>1400
LGP
(days)
>120
>120
OPTIMUM CONDITIONS
Coniferous Trees
Spruce
Pine
Fir
Picea abies
Picea asperata
Picea ajanensiss
Picea obovata
Picea koreaiensis
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Abies alba
Abies sibirica
Cunninghamia lanceolata
Tmean
Jan
(o C)
Tmean
July
(o C)
Tmin
Jan
(o C)
LGPT
10 o C
(days)
LGPT
5 oC
(days)
Dormancy
break.
(days)
Tsum
10 o C
(ddays
)
Tsum
5 oC
(ddays)
(days)
>-20
>-16
>-30
>-35
>-20
>-35
>-35
>-13
>0
>0
>-20
> -5
> -40
>4
14-18
14-18
14-18
13-18
14-18
14-20
14-23
18-24
24-28
16-22
14-18
16-20
14-20
24-28
-25
-20
-35
-40
-30
-50
-50
-22
-5
-5
-30
-20
-45
-10
>105
>90
>90
>75
>120
>75
>75
>165
>240
>195
>120
>135
>75
>255
>135
>150
>135
>120
>135
>120
>120
>180
>270
>240
>150
>180
>120
>300
>105
>135
>165
>195
>165
>180
>90
>135
0
0
>165
>120
>165
0
>1150
<1100
>1150
>1000
>1150
>900
>1000
>2500
>4000
>4000
>1150
>2200
>950
>4000
>1600
>1400
>1500
>1350
>1600
>1400
>1400
>3000
>4500
>4500
>1600
>2750
>1400
>4500
>135
>150
>135
>120
>150
>120
>120
>165
>240
>180
>135
>165
>120
>270
16
LGP
Table 9
Continued
RANGE CONDITIONS
Temperate and Boreal Deciduous Tree Species
Birch
Poplar
Willow
Oak
Beech
Hornbeam
Ash
Alder
Lime
Maple
Locust
Chestnut
Walnut
8
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula platyphylla
Betula papyrifera
Populus nigra
Populus euramericana cv rob.
Populus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Salix alba
Salix viminalis
Quercus robur
Quercus petracea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Fagus sylvatica
Carpinus betulus
Fraxinus excelsior
Fraxinus mandshurica
Alnus glutinosa
Tilia cordata
Acer plantanoides
Acer campestre
Acer campbellii
Robinia pseudoacacia
Castanea sativa
Junglans regia
Tmean
Jan
(o C)
Tmean
July
(o C)
Tmin
Jan
(o C)
LGPT
10 o C
(days)8
LGPT
5 oC
(days)
Dormancy
break
(days)
Tsum
10 o C
(ddays
)
Tsum
5 oC
(ddays)
LGP
(days)
>-45
>-45
> -45
>-45
>-35
>-33
>-35
>-35
>-35
>-45
>-40
>-40
>-20
>-30
> -35
> -35
>-25
>-7
>-12
>-2
>-25
>-12
>-12
>-35
>-7
>-25
> -15
>-35
>-25
>-30
>-25
>-13
>-20
>-12
>-1
>-15
10-23
12-23
10-18
10-18
12-26
12-26
14-33
12-33
16-33
13-28
13-28
13-28
16-33
18-33
15-30
15-30
14-29
14-30
15-26
18-34
15-29
18-29
18-29
14-22
14-25
14-30
16-30
15-27
14-26
16-26
14-25
16-25
13-26
14-30
14-26
14-26
-60
-55
-55
-60
-45
-45
-40
-40
-40
-55
-55
-55
-25
-30
-40
-40
-30
-12
-20
-10
-30
-20
-20
-40
-12
-30
-25
-40
-30
-35
-35
-18
-25
-18
-3
-30
>60
>75
>75
>60
>75
>75
>105
>105
>120
>75
>75
>75
>120
>120
>105
>105
>120
>150
>150
>165
>135
>165
>165
>105
>150
>135
>135
>135
>135
>135
>120
>120
>120
>150
>165
>135
>105
>120
>120
>105
>120
>120
>135
>135
>150
>105
>120
>120
>150
>150
>135
>135
>150
>195
>195
>225
>165
>210
>210
>120
>195
>165
>165
>165
>165
>165
>150
>150
>150
>210
>210
>165
>90
>75
>75
>90
>75
>75
0
0
0
>60
>45
>45
0
0
0
0
0
0
>30
0
0
>30
>30
>135
>45
0
0
0
0
0
0
0
0
0
>30
0
>850
>1000
>1000
>850
>1000
>1000
>2200
>2200
>2300
>1300
>1500
>1500
>2700
>2700
>1500
>1500
>1800
>1900
>1900
>2800
>1800
>2800
>2800
>1600
>1900
>2000
>1800
>1800
>1800
>1600
>1800
>1800
>1800
>2100
>2300
>2000
>1100
>1250
>1250
>1100
>1250
>1250
>2600
>2600
>2800
>1800
>1900
>1900
>3100
>3100
>1900
>1900
>2200
>2350
>2400
>3200
>2200
>3200
>3300
>1900
>2400
>2400
>2250
>2250
>2200
>2000
>2200
>2200
>2200
>2500
>2800
>2400
>105
>120
>120
>105
>120
>120
>120
>120
>135
>105
>120
>120
>135
>135
>120
>120
>135
>135
>180
>180
>150
>180
>150
>105
>165
>135
>150
>150
>150
>135
>135
>135
>135
>120
>180
>135
All temperate and boreal deciduous tree species are confined to areas with winter temperatures at least for some time below 10oC. For range levels LGPT10 > 360 days has been used as cut off.
17
RANGE CONDITIONS
Deciduous Coniferous Trees
Larch
Larix gmelinii
Larix sibirica
Tmean
Jan
(o C)
Tmean
July
(o C)
Tmin
Jan
(o C)
LGPT
10 o C
(days)
LGPT
5 oC
(days)
Dormancy
break.
(days)
Tsum
10 o C
(ddays
)
Tsum
5 oC
(ddays)
LGP
(days)
>-50
>-45
11-23
11-23
-60
-50
>60
>60
>105
>105
>135
>135
>800
>850
>1000
>1100
>105
>105
LGP
RANGE CONDITIONS
Coniferous Trees
Spruce
Pine
Fir
Picea abies
Picea asperata
Picea ajanensiss
Picea obovata
Picea koreaiensis
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Abies alba
Abies sibirica
Cunninghamia lanceolata
Tmean
Jan
(o C)
Tmean
July
(o C)
Tmin
Jan
(o C)
LGPT
10 o C
(days)
LGPT
5 oC
(days)
Dormancy
break.
(days)
Tsum
10 o C
(ddays
)
Tsum
5 oC
(ddays)
(days)
>-25
>-18
>-35
>-40
>-25
>-45
>-45
>-15
>-2
>-3
>-25
>-8
>-45
>0
12-20
12-20
12-20
12-19
12-20
12-23
12-25
16-26
22-30
15-24
12-21
14-23
12-23
22-30
-30
-22
-40
-45
-35
-60
-60
-25
-8
-8
-35
-25
>-50
>-15
>90
>75
>75
>60
>105
>60
>60
>150
>210
>180
>105
>120
>60
>240
>120
>135
>120
>105
>120
>105
>105
>165
>240
>225
>135
>165
>105
>270
>90
>120
>150
>180
>150
>165
>60
>120
0
0
>150
>90
>150
0
>1050
<1050
>1000
>900
>1050
>800
>850
>2300
>3750
>3750
>1050
>2000
>850
>3750
>1250
>1300
>1200
>1150
>1250
>1150
>1100
>2800
>4000
>4000
>1250
>2500
>1100
>4250
>120
>135
>120
>105
>135
>105
>105
>150
>210
>165
>120
>150
>105
>240
18
The soil suitability assessment is based on the comparison of soil requirements of tree species and
prevailing soil conditions. The soil assessment also reflects constraints imposed by landform and
other features that do not directly form a part of the soil but may have a significant influence on the
use that can be made of the soil. Distinction is made between internal soil requirements of crop/LUTs,
e.g., soil moisture regime, soil fertility, effective soil depth for root development, and other physical
and chemical soil properties, and external requirements related to, e.g., soil slope, occurrence of
flooding, and soil accessibility.
In order to safeguard that production be achievable on a sustainable basis, a terrain-slope suitability
classification is applied which not only concerns workability and accessibility but also prevents intolerable levels of topsoil erosion and fertility loss. Depending on prevailing rainfall aggressivity, upper
limits have been set to slope gradients for traditional production forestry and biomass forestry. Beyond these slope gradients land has been classified not suitable for tree production under these management objectives.
A number of soil characteristics affecting growth and production of tree species have been classified
in terms of optimum, range and not suitable conditions for the 52 forest tree species considered (Table
10), including the following:
(i)
(ii)
(iii)
(iv)
(v)
(vi)
(vii)
(viii)
4.3
Soil fertility;
Soil texture and structure;
Soil internal drainage;
Soil depth;
Soil reaction;
Soil stoniness;
Soil salinity, and
Water-logging/flooding conditions.
Biomass Increment Calculation
The AEZ methodology for the calculation of potential biomass is based on two well established and
robust models: the Chapman-Richard biomass increment model (e.g., see Nilsson, 1983), and a potential biomass model adapted from Kassam (1977) and Kassam et al. (1991). Details of the calculation procedures are presented below.
A generalized function for forest stand development
Many practical applications in forestry employ a biomass increment model suggested by ChapmanRichard, expressing stand development in terms of relative yield over relative age. The generalized
function is of the form:
y ( r ) = α ⋅ (1 − β − r ) γ
r =t/R
(1)
B( r ) = y ( r ) ⋅ B*
where:
R…
t…
r…
y…
B(r) …
B* …
α, β, γ
9
optimum rotation length9
age of stand
relative age, i.e., age expressed relative to optimum rotation length
relative yield, i.e., yield relative to biomass at age of maximum volume production
biomass at relative age r
biomass at age of maximum volume production
parameters of Chapman-Richard function
Rotation length is taken as the age at 'maximum volume production', and is the point in time when annual increment
is equal to the mean increment over the total period since establishment.
19
Table 10
Soil requirements
Deciduous Trees
Birch
Poplar
Willow
Oak
Beech
Hornbeam
Ash
Alder
Lime
Maple
Black locust
Chestnut
Walnut
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula platyphylla
Betula papyrifera
Populus nigra
Populus euramericana cv rob.
Populus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Salix alba
Salix viminalis
Quercus robur
Quercus petracea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Fagus sylvatica
Carpinus betulus
Fraxinus excelsior
Fraxinus mandshurica
Alnus glutinosa
Tilia cordata
Acer plantanoides
Acer campestre
Acer campbellii
Robinia pseudoacacia
Castanea sativa
Junglans regia
Fertility
low
low
low
low
low
low
high
high
high
med./high
med./high
med./high
high
high
high
high
medium
medium
medium
medium
medium
medium
medium
medium
medium
medium
high
high
high
medium
med./high
med./high
med./high
medium
med/high
med/high
Texture/Structure
Optimum
9-16
10-16
10-16
9-16
10-16
10-16
9-15
9-15
9-16
9-16
9-16
9-16
9-15
9-15
9-16
9-16
9-15
9-16
9-15
9-15
9-15
9-16
9-16
9-15
9-15
9-15
9-15
9-15
9-15
9-15
9-16
9-16
9-16
9-16
9-15
9-16
Range
6-19
9-20
9-20
6-19
9-19
9-19
5-19
5-19
6-19
6-19
6-19
6-19
5-19
5-19
5-20
5-20
5-19
5-20
5-19
5-19
6-17
6-19
6-19
5-19
6-16
5-17
6-17
6-17
5-19
6-17
6-19
6-19
6-19
5-19
6-16
5-19
Drainage
Optimum
W-I
W-MW
W-MW
W-I
W-MW
W-MW
W-MW
W-MW
W-MW
W-MW
W-MW
W-MW
W-MW
W-MW
W-I
W-I
W-I
W-MW
W-MW
W-I
W-MW
W-MW
W-MW
W-I
W
W-MW
W-I
W-I
W-I
W-MW
W-MW
W-MW
W-MW
W-MW
W
W
20
Range
SE-VP
E-I
E-I
SE-P
SE-I
SE-P
SE-P
SE-P
SE-I
SE-I
SE-I
SE-I
SE-P
SE-P
SE-VP
SE-VP
SE-P
E-I
E-I
SE-P
SE-I
SE-I
SE-I
SE-P
SE-MW
SE-I
SE-P
SE-P
SE-VP
SE-I
SE-I
SE-I
SE-I
SE-I
SE-MW
SE-MW
Depth (cm)
Optimum
>100
>100
>100
>100
>100
>100
>150
>150
>150
>150
>150
>150
>150
>150
>100
>100
>100
>100
>150
>100
>100
>100
>100
>100
>150
>100
>100
>100
>100
>150
>100
>100
>100
>150
>150
>150
Marginal
>30
>50
>50
>30
>50
>50
>75
>75
>75
>75
>75
>75
>75
>75
>50
>50
>50
>50
>75
>50
>50
>50
>50
>50
>75
>50
>30
>30
>30
>75
>50
>50
>50
>50
>75
>75
Reaction (pH)
Optimum
4.5-7.5
4.5-7.0
4.5-7.0
4.5-7.5
4.5-7.5
4.5-7.5
6.5-7.5
6.5-7.5
6.0-7.0
6.0-7.0
6.0-7.0
6.0-7.0
6.5-7.5
6.5-7.5
5.0-7.5
5.0-7.5
5.5-7.5
5.0-7.0
5.5-7.5
6.0-8.0
5.5-7.5
5.5-7.5
5.5-7.5
5.5-7.5
5.5-7.5
5.0-7.0
5.8-7.5
5.8-7.5
5.0-7.0
5.0-7.5
5.0-7.0
5.5-7.5
5.5-7.5
5.5-7.5
5.0-7.0
6.5-7.5
Range
4.0-8.0
4.0-8.0
4.0-8.0
4.0-8.0
4.0-8.0
4.0-8.0
5.5-8.5
5.5-8.5
5.5-8.5
5.5-8.5
5.5-8.5
5.5-8.5
5.5-8.5
5.5-8.5
4.5-8.5
4.5-8.5
4.5-8.5
4.0-8.0
4.5-8.5
5.0-8.5
4.5-8.0
4.5-8.0
4.5-8.0
4.5-8.5
5.0-8.5
4.0-8.5
4.5-8.5
4.5-8.4
4.5-8.5
4.5-8.5
4.0-8.5
4.0-8.5
4.0-8.5
5.0-8.5
4.0-8.0
5.5-8.5
Water-logging/ Flooding
Optimum
F1
F0
F0
F0/F1
F0
F0
F1
F1
F0/F1
F0
F0/F1
F0/F1
F0/F1
F0/F1
F1
F1
F0/F1
F0
F0
F0
F0
F0
F0
F0
F0
F0
F0/F1
F0/F1
F0/F1
F0
F0/F1
F0/F1
F0/F1
F0
F0
F0
Marginal
F1/F2
F0/F1
F0/F1
F1
F0/F1
F0/F1
F1/F2
F1/F2
F1/F2
F0/F1
F1/F2
F1/F2
F1
F1
F2
F2
F1
F0
F0
F0/F1
F0/F1
F0/F1
F0/F1
F0/F1
F0
F0/F1
F1/F2
F1/F2
F1/F2
F0/F1
F1
F1
F1
F0
F0
F0
Deciduous Coniferous Trees
Larch
Fertility
low
low/med
Larix gmelinii
Larix sibirica
Fertility
Coniferous Trees
Spruce
Pine
Fir
medium
medium
medium
medium
medium
low/med.
low
low/med.
low/med.
low/med.
low/med.
medium
medium
medium
Picea abies
Picea asperata
Picea ajanensiss
Picea obovata
Picea koreaiensis
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Abies alba
Abies sibirica
Cunninghamia lanceolata
TEXTURE/STRUCTURE
symbol
massive clay
massive silty clay
very fine clay, vertisol structure
very fine clay, blocky structure
clay, vertisol structure
clay, blocky structure
silty clay, blocky structure
clay, oxisol structure
silty clay loam
clay loam
silt
Cm
SiCm
C+60,v
C+60,s
C-60,v
C-60,s
SiCs
Co
SiCL
CL
Si
Texture/Structure
Optimum
9-16
9-16
Range
6-20
6-19
Optimum
W-MW
W-MW
Texture/Structure
Optimum
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
9-16
Range
6-19
6-19
6-19
6-19
6-19
5-20
6-21
6-19
6-19
6-19
6-20
5-18
6-19
6-19
code TEXTURE/STRUCTURE
1
2
3
4
5
6
7
8
9
10
11
Drainage
Depth (cm)
Range
SE-I
SE-I
Drainage
Optimum
W-MW
W-MW
W-MW
W-MW
W-MW
W-MW
W-I
W-MW
W
W-MW
W-MW
W-MW
W
W
Range
SE-I
SE-I
SE-I
SE-I
SE-I
SE-P
E-P
SE-I
SE-MW
SE-I
SE-I
SE-P
SE-I
SE-I
code
SiL
SC
L
SCL
SL
LfS
LS
LcS
fS
S
cS
12
13
14
15
16
17
18
19
20
21
22
21
Marginal
>30
>50
Depth (cm)
symbol
silt loam
sandy clay
loam
sandy clay loam
sandy loam
loamy fine sand
loamy sand
loamy coarse sand
fine sand
sand
coarse sand
Optimum
>75
>100
Optimum
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>100
>150
>150
>100
Marginal
>50
>50
>50
>50
>50
>30
>30
>30
>30
>30
>30
>75
>75
>30
Reaction (pH)
Optimum
5.0-7.5
5.0-7.0
Range
4.5-8.5
4.5-8.0
Reaction (pH)
Optimum
4.5-6.0
4.5-6.0
4.5-6.0
4.5-6.0
4.5-6.0
5.0-6.0
5.0-6.5
5.0-6.5
5.0-6.5
5.0-6.5
5.0-6.5
4.5-7.5
4.5-7.0
4.5-7.0
Range
4.0-7.5
4.0-7.5
4.0-7.5
4.0-7.5
4.0-7.5
4.0-8.0
4.0-8.5
4.0-8.5
4.0-8.5
4.0-8.5
4.0-8.5
4.0-8.5
4.0-8.0
4.0-9.0
DRAINAGE
Excessively drained
Somewhat excessively drained
Well
Moderately well drained
Imperfectly drained
Poorly drained
Very poorly drained
Waterlogging/ Flooding
Optimum
F1
F0/F1
Marginal
F1/F2
F1/F2
Waterlogging/ Flooding
Optimum
F0
F0
F0
F0
F0
F0/F1
F1
F0
F0
F0
F0/F1
F0
F0
F0
Marginal
F0
F0
F0
F0
F0
F1
F1/F2
F0/F1
F0/F1
F0/F1
F1
F0/F1
F0/F1
F0/F1
Symbol
E
SE
W
MW
I
P
VP
WATERLOGGING/FLOODING
No flooding/waterlogging
Occasional floods/waterlogging (short periods)
Frequent floods/waterlogging (longer periods)
F0
F1
F2
According to the definitions of y, r, and R, the following conditions must hold:
y ( 0) = 0
y (1) = 1
dy
=1
dr r =1
(2)
To fully specify the function, an additional condition is needed. Usually the relative standing biomass
at 50% percent of the rotation length, i.e., y(0.5), is estimated at 38%, and this condition can be used
to obtain the parameter values of the function. The tabulation below shows parameter values and derived properties of the Chapman-Richard function using a range of values for y (0.5):
α
1.5052
1.5644
1.6416
1.7471
1.9014
y(0.5)
0.34
0.36
0.38
0.40
0.42
β
10.189
8.0876
6.3581
4.9385
3.7781
γ
3.9585
3.3907
2.8967
2.4661
2.0900
r*
0.5927
0.5840
0.5749
0.5651
0.5546
y(r*)
0.4753
0.4782
0.4813
0.4845
0.4878
ax
1.4764
1.4182
1.3601
1.3018
1.2431
In the above, r* denotes the relative age at which the maximum growth occurs, and a x the relative increment at the age of maximum growth,
ax =
dy
dr
(3)
r= r*
The rate of relative biomass increment a(r) at relative age r can be derived from (1):
a (r) =
dy
= α ⋅ γ ⋅ ln( β ) ⋅ β −r ⋅ (1 − β −r ) γ −1
dr
(4)
In order to calculate biomass at age of maximum volume production B* , we integrate the rate of net
biomass production b n (t) over the entire rotation R:
R
R
B* = ∫ bn (t ) ⋅ dt = (bn ( r * ) / a x ) ⋅ ∫ a (t / R) ⋅ dt ≈ R ⋅ N ⋅ bnx / a x
0
(5)
0
where N denotes the length of the annual vegetation period (in days) and b nx the daily rate of biomass
production at the age of maximum growth t * = r * ⋅ R (averaged for that year). Following the ecophysiological principles of Kassam (1977) and Kassam et al. (1991), we calculate b nx as the difference of maximum rate of gross biomass production b gm and respiration losses sm,
b nx = bgm - sm
(6)
Maximum rate of gross biomass production
The maximum rate of gross biomass production (b gm) is related to the maximum net rate of CO2 exchange of leaves (Pm), which is dependent on temperature, and the level of atmospheric CO2 concentration. For estimating biomass production, relationships between temperature and rate of photosynthesis of forest tree species have been established. The forest tree species in subtropical, temperate
and boreal climates considered in the study have the C3 photosynthesis pathway, and rates of maximum photosynthesis (Pm) are in the range 5 – 20 kg CH2 O ha-1 hr-1 (Landsberg, 1986).
Species are classified according to productivity into three classes, namely class I: Pm = 5-10 kg CH2 O
ha-1 hr-1; class II: Pm = 10-15 kg CH2 O ha-1 hr-1; and class III: Pm = 15-20 kg CH2 O ha -1 hr-1. These
classes of photosynthesis rates correspond to mean annual total biomass increments (including foliage, stem and roots) of < 10 t/ha, 10-15 t/ha and > 15 t/ha dry weight respectively, or annual wood
22
Table 11
Rotation and productivity characteristics
Tree Species
Birch
Poplar
Willow
Oak
Beech
Hornbeam
Ash
Alder
Lime
10
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula platyphylla
Betula papyrifera
Populus nigra
Populus euramericana
Populus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Salix alba
Salix viminalis(SRC)
Quercus robur
Quercus petraea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Fagus sylvatica
Carpinus betulus
Fraxinus excelsior
Fraxinus mandshurica
Alnus glutinosa
Tilia cordata
Rotation
Height
(m)
32
30
20
25
20
30
35
35
30
30
30
30
30
30
35
8
30
35
25
20
35
12
25
30
36
27
30
30
23
30
Length
(years)
65
65
65
65
65
65
25
25
25
30
30
30
25
25
40
3-5/25
75
75
45
40
70
35
70
75
85
70
40
40
60
65
Production
(m3/ha/yr)
7.0
7.5
6.0
5.0
6.0
7.0
31.0
31.0
26.0
26.0
26.0
26.0
26.0
26.0
27.0
27.0
9.0
9.0
9.3
9.0
12.0
7.2
9.0
9.0
12.0
11.0
10.0
10.0
12.0
11.0
Density
(g/cm3)
Dry Weight
(t/ha)
Class
LAI
Drought Tolerance Parameters 10
ETa/ETo*100
Class
κ
λ
µ
0.61
0.61
0.61
0.61
0.61
0.61
0.34
0.34
0.39
0.39
0.39
0.39
0.39
0.39
0.41
0.41
0.85
0.65
0.70
0.65
0.85
0.70
0.65
0.85
0.68
0.78
0.65
0.65
0.55
0.54
4.3
4.6
3.7
3.1
3.7
4.3
10.5
10.5
10.1
10.1
10.1
10.1
10.1
10.1
11.1
11.1
7.7
5.9
6.5
5.9
9.9
5.0
5.9
7.7
8.2
8.6
6.5
6.5
6.6
5.9
I
I
I
I
I
I
III
III
III
III
III
III
III
III
III
III
II
II
II
II
II
II
II
II
II
II
II
II
II
II
3.0
3.0
3.0
3.0
3.0
3.0
4.0
4.0
4.0
4.0
4.0
4.0
4.0
4.0
4.0
4.0
4.5
4.5
5.0
4.5
4.5
4.5
4.5
4.5
5.5
5.0
5.0
5.0
5.0
5.0
95
85
85
95
85
85
90
90
90
90
90
90
90
90
95
95
85
85
90
85
85
85
85
85
95
90
95
95
95
95
85
65
65
85
65
65
80
80
80
80
80
80
80
80
85
85
65
65
80
65
65
65
65
65
85
80
85
85
85
85
50
50
50
50
50
50
50
50
50
50
50
50
50
50
65
65
50
50
50
50
50
50
50
50
50
50
65
65
65
50
C
A
A
C
A
A
B
B
B
B
B
B
B
B
D
D
A
A
B
A
A
A
A
A
C
B
D
D
D
C
ET a /ET o thresholds are as follows: κ represents the threshold value above which full biomass increments are assumed; λ represents the threshold below which zero biomass
increments are assumed; µrepresents the relative LAI at λ (LAI at κ is assumed 100%). Class A-D represent different combinations of κ, λ and µ.
23
Tree Species
Acer
Black locust
Chestnut
Walnut
Larch
Spruce
Pine
Fir
Class I:
Class II:
Class III:
Partitioning:
Rotation
Acer plantanoides
Acer campestre
Acer campbellii
Robinia pseudoacacia
Castanea sativa
Junglans regia
Larix gmelinii
Larix sibirica
Picea abies
Picea asperata
Picea ajanensiss
Picea obovata
Picea koreaiensis
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Abies alba
Abies sibirica
Cunninghamia lanceolata
Height
(m)
30
15
20
25
30
30
25
27
40
25
30
30
30
30
35
25
24
15
25
40
30
30
Length
(years)
40
40
40
40
80
100
75
75
60
60
60
60
60
60
55
55
60
60
40
90
90
90
Production
(m3/ha/yr)
8.0
8.0
8.0
12.0
11.4.
8.0
8.2
13.0
26.0
21.0
26.0
26.0
26.0
10.5
12.0
9.0
9.0
6.0
12.0
26.0
21.0
21.0
< 6.0 t/ha stem + branch wood biomass or < 10.0 t/ha total biomass
6.0-9.0 t/ha stem + branch wood biomass or 10.0 –15.0 t/ha total biomass
> 9..0 t/ha stem + branch wood biomass or > 15.0 t/ha total biomass
Soil/LGP rating
VS:
S/MS:
mS:
Density
(g/cm3)
Dry Weight
(t/ha)
Class
LAI
Drought Tolerance Parameters
ETa/ETo*100
Class
κ
λ
µ
0.67
0.67
0.59
0.73
0.63
0.64
0.65
0.65
0.44
0.44
0.44
0.44
0.44
0.51
0.51
0.43
0.43
0.43
0.44
0.45
0.47
0.40
5.4
5.4
4.7
8.8
7.2
5.1
5.3
8.5
11.4
9.2
11.4
11.4
11.4
5.4
6.1
3.8
3.8
2.6
5.3
11.7
9.9
8.4
II
II
I
II
II
II
II
II
III
II
III
III
III
II
II
I
I
I
I
III
II
II
5.0
5.0
5.0
3.5
5.0
5.0
3.0
3.5
6.0
6.0
6.0
6.0
6.0
3.5
3.5
3.5
3.5
3.5
3.5
6.0
6.0
5.0
95
95
95
85
90
90
85
85
95
95
95
95
95
90
85
90
90
90
90
90
95
95
≈ Pm = 5-10 kg CH2 O ha-1hr -1
≈ Pm = 10-15 kg CH2 O ha-1 hr -1
≈ Pm = >15 kg CH2 O ha-1hr -1
Stem+branch wood/leaves/roots = 60/20/20
Stem+branch wood/leaves/roots = 50/20/30
Stem+branch wood/leaves/roots = 40/20/40
24
85
85
85
65
80
80
65
65
85
85
85
85
85
85
65
80
80
80
80
80
85
85
50
50
50
50
50
50
50
50
65
65
65
65
65
50
50
50
50
50
50
50
50
65
C
C
C
A
B
B
A
A
D
D
D
D
D
B
A
B
B
B
B
B
C
D
biomass increments (stem and branch wood) of < 6 t/ha, 6-9 t/ha, and > 9 t/ha dry weight respectively.
Table 11 presents rotation and productivity characteristics of selected deciduous and coniferous tree
species (Jansen et al., 1995).
For Pm = 20 kg ha -1 hr-1 and a maximum leaf area index LAI = 5, b gm is calculated from the equation:
(7)
b gm = F x bo + (1 - F) bc
where:
F=
the fraction of the daytime the sky is clouded, F = (Ac - 0.5 Rg ) / (0.8 Ac), where Ac (or
PAR) is the maximum active incoming short-wave radiation on clear days (de Wit,
1965), and Rg is incoming short-wave radiation (both are measured in cal cm-2 day-1)
b o = gross dry matter production rate of a standard crop for a given location and time of the
year on a completely overcast day, (kg ha -1 day-1) (de Wit, 1965)
b c = gross dry matter production rate of a standard crop for a given location and time of the
year on a perfectly clear day, (kg ha -1 day-1) (de Wit, 1965).
For values of Pm less than 20 kg ha -1 hr-1, b gm is then calculated according to:
(8)
b gm = F (0.5 +0.025 Pm) bo + (1 - F) (0.05 Pm) b c
Relationships between temperature and rate of photosynthesis (kg CH2 O ha -1 hr-1) for deciduous, coniferous and deciduous coniferous (larches) tree species by productivity classes are presented in Table
12. Table 13 shows estimated relationships between temperature regime and growth period for deciduous trees and larches.
Table 12
Relationships between temperature and rate of photosynthesis (Pm in kg
CH2 O ha-1 hr-1) for adaptability/productivity groups of boreal and te mperate tree species
Day-time Air Temperature (oC)
Adaptability/Productivity Class
-5
0
5
10
15
20
25
30
35
40
0
0
0
0
0
0
0*
0*
0*
4.5
7.5
12.5
6.0
10.0
15.0
7.5
12.5
17.5
6.0
10.0
15.0
3.0
5.0
7.5
0.75
1.5
2.5
0
0
0
0
0
0
0
0
0
0*
0*
0*
4.5
7.5
12.5
6.0
10.0
15.0
7.5
12.5
17.5
6.0
10.0
15.0
3.0
5.0
7.5
0.75
1.5
2.5
0
0
0
0.5
1.0
1.5
1.0
2.0
3.0
2.0
4.0
6.0
4.5
7.5
12.5
6.0
10.0
15.0
7.5
12.5
17.5
6.0
10.0
15.0
3.0
5.0
7.5
0.75
1.5
2.5
0
0
0
0
0
0
0
0
0
0.75
1.5
2.5
4.5
7.5
12.5
6.0
10.0
15.0
7.5
12.5
17.5
6.0
10.0
15.0
3.0
5.0
7.5
0.75
1.5
2.5
0
0
0
Deciduous Trees
I
II
III
Pm (max): 5-10 kg ha-1 hr -1
Pm (max): 10-15 kg ha-1hr -1
Pm (max): 15-25 kg ha-1hr -1
Deciduous Coniferous Trees
I
II
III
Pm (max): 5-10 kg ha-1 hr -1
Pm (max): 10-15 kg ha-1hr -1
Pm (max): 15-25 kg ha-1hr -1
ConiferousTrees (clear days)
I
II
III
Pm (max): 5-10 kg ha-1 hr -1
Pm (max): 10-15 kg ha-1hr -1
Pm (max): 15-25 kg ha-1hr -1
ConiferousTrees (overcast days)
I
II
III
Pm (max): 5-10 kg ha-1 hr -1
Pm (max): 10-15 kg ha-1hr -1
Pm (max): 15-25 kg ha-1hr -1
* no leave/needle photosynthesis
25
Table 13
Growth periods for deciduous tree species
Growth Period11
Tree Species
Start Conditions12
Birch
Poplar
Willow
Oak
Beech
Hornbeam
Ash
Alder
Lime
Acer
Black locust
Chestnut
Walnut
Larch
III
III
III
III
III
III
II
II
I
I
II
II
II
II
I
I
V
V
V
V
V
V
V
V
IV
IV
III
IV
III
V
V
V
V
V
V
V
II
II
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula platyphylla
Betula papyrifera
Populus nigra
Populus euramericana cv rob.
Populus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Salix alba
Salix viminalis
Quercus robur
Quercus petracea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Fagus sylvatica,,
Carpinus betulus
Fraxinus excelsior
Fraxinus mandshurica
Alnus glutinosa
Tilia cordata
Acer plantanoides
Acer campestre
Acer campbellii
Robinia pseudoacacia
Castanea sativa
Junglans regia
Larix gmelinii
Larix sibirica
Σ t=5 > 450
Σ t=5 > 450
Σ t=5 > 450
Σ t=5 > 450
Σ t=5 > 450
Σ t=5 > 450
Σ t=5 > 400
Σ t=5 > 400
Σ t=5 > 350
Σ t=5 > 350
Σ t=5 > 400
Σ t=5 > 400
Σ t=5 > 400
Σ t=5 > 400
Σ t=5 > 350
Σ t=5 > 350
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 550
Σ t=5 > 550
Σ t=5 > 450
Σ t=5 > 550
Σ t=5 > 450
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 650
Σ t=5 > 400
Σ t=5 > 400
End Conditions
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Tmean <10oC
Maximum growth rate at actual LAI
The maximum rate of gross biomass production (b gm) refers to a reference LAI of 5. When actual
LAI deviates, adjustment of b gm is achieved by means of a correction factor L, which equals the ratio
of b gm at actual LAI to b gm at LAI of 5. As shown in Figure 3, the effect of LAI on bgm is small
when LAI is larger than 5 and a near complete ground cover or light interception is achieved.
11
Based on calculations for Bologna (Italy), Vienna (Austria), De Bilt (Netherlands), Stockholm (Sweden), Moscow
(Russia), and Kiruna (Sweden).
12
Species-specific thresholds for meeting phenological requirements for bud burst and flushing have been related to
temperature sums for mean temperatures exceeding 5oC (Barnes et al., 1998).
26
Adjustment factor L
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0
2
4
6
8
Leaf Area Index (LAI)
Figure 3
Relationship between leaf area index (LAI) and maximum growth rate as
a fraction of the maximum growth rate at LAI of 5
The LAI of individual tree species/LUTs has been adjusted when moisture stress thresholds are exceeded (Table 11). In case (e = ETa/ETo*100 ) falls short of the species specific drought tolerance parameter κ, but is not less than parameter λ, the leaf area index has been adjusted proportionately to the
values between 100% and minimum value µ corresponding to position of e with regard to drought tolerance parameters κ and λ. In case e falls short of λ then zero biomass increment (not suitable) is assumed. The adjusted LAI has been calculated as follows:
LAI adj
 LAI

κ−e
 e−λ
=  LAI 
+µ⋅

κ − λ
κ−λ

 not suitable
e≥ κ
α ≥e≥ λ
(9)
e<λ
where:
e = ETa/ETo*100
Respiration losses
To calculate the maximum rate of net biomass production (b nx), the maximum rate of gross biomass
production (b gm) and the rate of respiration (sm) are required. Here, growth respiration is considered
a linear function of the rate of gross biomass production (McCree, 1974), and maintenance respiration
a linear function of net biomass that has already been accumulated (Bm). When the rate of gross biomass production is b gm, the respiration rate sm is:
(10)
sm = k bgm + c Bm
where k and c are the proportionality constants for growth respiration and maintenance respiration respectively, and Bm is the net biomass accumulated at the time of maximum rate of net biomass production. For both legume and non-legume species k equals 0.28. However, c is temperature dependent
o
and differs for the two species groups. At 30 C, factor C30 for a legume species equals 0.0283 and for
a non-legume species 0.0108. The temperature dependence of Ct for both species groups is modeled
with a quadratic function:
2
(11)
Ct = C30 (0.044+0.0019 T+0.0010 T ).
27
Net average annual biomass increment
In order to characterize land productivity, we calculate average annual biomass increments achievable
in the longer term. Net average annual biomass increment (Ba ) is obtained from (5),
Ba = B * / R = N ⋅ bnx / a x
(12)
In our simulations it is assumed that the standing biomass at 50% rotation length is 38% of the standing biomass at 100% of the optimum rotation length. In this case, the Chapman-Richard function implies that the maximum rate of biomass increase occurs at a relative age r* = 0.575, that the relative
yield y(r* ) at relative age r* equals y(r* ) = 0.481, and that the maximum relative biomass increase
a(r*) = a x =1.360.
Using (6), (9) and (10) and the parameter values presented above, we calculate the average net biomass production Ba :
Ba = ((1 − k ) ⋅ bgm ⋅ L ⋅ N / a x ) /(1 + N ⋅ y ( r * ) ⋅ C t / a x )
(13)
and inserting parameter values we obtain,
Ba = (0.529 ⋅ bgm ⋅ L ⋅ N ) /(1 + N ⋅ 0.354 ⋅ Ct )
(14)
where, as before:
bgm
L
N
= maximum rate of gross biomass production at leaf area index (LAI) of 5 (kg CH2O ha -1day-1)
= Maximum growth ratio, equal to the ratio of bgm at actual LAI to bgm at LAI of 5.
= Length of growth period during the year (days)
Ct
= Maintenance respiration
Partitioning of biomass
Potential average annual constraint-free wood biomass increment13 (Bw) is calculated from Ba using
the equation:
(15)
Bw = Hiwood x Ba
where:
Hiwood = harvest index, i.e., proportion of the net biomass of the species that is stem and branch
wood (or in case of coppice systems shoots and twigs).
The partitioning coefficients (wood, branches, twigs and foliage, and roots) are species-specific and
are also closely related to soil water availability and fertilization. Reference values for stem wood and
branches equal 0.6, for twigs and foliage 0.2 and 0.2 for roots. With fertilization and irrigation the
harvest index for wood biomass may increase at the expense of root biomass.
Thus, climate and tree species characteristics that apply in the computation of net biomass increments
are: (a) heat and radiation regime over the vegetation period, (b) adaptability/productivity classes to
determine applicable rates of photosynthesis, P m, (c) length of vegetation period, (d) maximum leaf
area index, and (e) partitioning coefficients.
13
Similarly annual potential root biomass increment and annual foliage can be calculated by using the appropriate harvest indexes, Hiroots and Hitwigs and foliage , or in case of short rotation coppice systems Hishoots and twigs
28
Moisture limited biomass increments
The calculation of moisture limited biomass increments uses the procedures described in FAO (1992)
and FAO (1998), known as the CROPWAT method. In this approach, the species-specific potential
c
evapotranspiration ETo is related to reference evapotranspiration ETo as,
EToc = k c x ETo
(16)
where k c is calculated from a piecewise linear function as sketched below:
kc
k2 c
1.0
k3
0.5
c
k1 c
d1
d2
d3
d4
crop cycle
The function is parameterized by means of seven parameters. Four coefficients, d1, …, d4, relate to
the characteristics of the seasonal leaf area development for deciduous tree species, denoting the
length (in days) of four development stages, namely, leaf flushing, early stage, mid season stage, and
late-season stage. Another three parameters, k 1c , k 2 c and k 3c , define relationship (16) for the individual stages. For non-deciduous tree species parameter k2c is used for the total period in which photosynthesis is possible.
Let D1 , …, D4 denote the days belonging to each of the four development stages,
D1 = { j 1 ≤ j ≤ d 1} ,
D2 = { j d 1 < j ≤ d 1 + d 2} ,
D3 = { j d1 + d 2 < j ≤ d 1 + d 2 + d 3} , and
D4 = { j d 1 + d 2 + d 3 < j ≤ d 1 + d 2 + d 3 + d 4} ,
then the value of k c for a particular day j is defined by piecewise linear functions:
 k1c

c
c
 k1c + ( j − d 1) ⋅ k 2 − k1

d2
k cj =  c
k 2
 c
k3c − k 2c
 k 2 + ( j − ( d 1 + d 2 + d 3)) ⋅

d4
29
j ∈ D1
j ∈ D2
j ∈ D3
j ∈ D4
(17)
Using (16) and (17), species-specific potential evapotranspiration over the four leaf area development
c
stages, TETokc , and the entire vegetation period, TETo can be calculated:
TETokc =
∑k
j∈Dk
c
j
⋅ ETo j
k = 1, …,4
(18)
d 0 = d1 + d 2 + d 3 + d 4
d0
(19)
TEToc = ∑ k cj ⋅ ETo j
j =1
Similarly, applying a species-specific soil water balance, actual evapotranspiration is calc ulated:
TETack =
∑ ETa
j∈Dk
c
j
k = 1, …,4
(20)
d0
TETac = ∑ ETa cj
(21)
j =1
where ETa c is determined according to:
W jc+1 = min (W jc + Pj − ETa cj , Sa )
(22)
ETo cj
ETa = 
ρ j ⋅ETocj
(23)
c
j
if ( W jc + Pj )⋅d ≥ Sa⋅d ⋅( 1 − p cj )
else
with,
ρj =
ETa cj
ETocj
=
W jc + Pj
(24)
Sa⋅(1 − p cj )
p cj
number of day in year
available soil moisture holding capacity (mm/m)
rooting depth (m)
soil water depletion fraction below which ETa < ETo
ρj
actual evapotranspiration proportionality factor.
j
Sa
d
Sa and d are defined by the respective values of the soil units in individual grid-cells. The computation of water-limited biomass increment Bl is now easily obtained, following FAO (1979, 1992 and
1998):
1−
Bl
ETa c
= k y ⋅ (1 −
)
Ba
ETo c
(25)
We evaluate (25) in two variants, first over the entire vegetation period and then according to individual growth stages. The more severe of the two conditions determines Bl . The respective reduction
multipliers f 0 and f1 are defined by,
f 0 = 1 − k 0y ⋅ (1 −
TETac
)
TEToc
(26)
and
30
4
f 1 = ∏ (1 − k ky ⋅ (1 −
k =1
TETakc
))
TETokc
(27)
y
where the coefficient expressing the sensitivity of biomass increment to moisture deficit, k , are
based on FAO (1992 and 1998).
Applying (26) and (27) to potential biomass increment from (15), we obtain the final results,
Bl = min( f 0 , f 1 ) ⋅ Ba
4.4
(28)
Climate related Productivity Constraints
Climatic constraints may cause direct or indirect losses of biomass increments. These constraints are
influenced by the following conditions:
•
Constraints indirectly related to climatic conditions such as pests, diseases and invasion of unwanted species or weeds;
•
Climatic factors which affect the efficiency of forestry operations and costs of production,
•
Occurrence of late and early frost, and
•
Forest fires.
The climatic constraints for individual tree species by management objective are specified for the
temperature and moisture regimes in each grid-cell. In particular the climatic constraints are linked to:
(i) length of thermal growing period (LGP t=5 ), (ii) length of frost-free period (LGP t=10), (iii) accumulated temperatures, (iv) length of moisture growing period (LGP), and (v) seasonal wetness.
Frost risks
Frost risks are accounted for in matching the early and late frost tolerance/sensitivity of individual tree
species with prevailing periods during which mean daily temperatures exceed 10o C. These periods are
assumed to represent, by and large, the frost-free periods (Table 9).
Forest fire risks
Forests fire risk has been assumed to be related to the following main factors: (i) climate conditions
(aridity and wind), forest species susceptibility to fire, and (iii) forest fire prevention measures (access
roads and fire protection barriers). Forest species may be listed in decreasing order of firesusceptibility as follows: (1) light coniferous species, (2) dark coniferous species and (3) broad-leaved
species.
Table 14 presents the assumptions we have made for forest fire intervals for unprotected forest resources of respectively broad-leaved, dark coniferous and light coniferous tree species under three
distinct aridity conditions (see also Section 4.1, conservation forestry and Plate 12, Aridity Index).
The tentative forest fire intervals presented in Table 14 are applied only for the suitability analysis of
conservation forest LUTs. Traditional production forest and biomass plantation forest LUTs are assumed to require full fire protection by means of access roads and fire protection barriers. These
measures, however, may take away between 5 and 10 % of potentially productive forest areas.
Table 14
Assumed forest fire intervals for conservation forestry LUTs
Dominantly broadleaved forest
Dominantly dark coniferous forests
Dominantly light coniferous forests
< 0.5
n.a.
n.a
25 years
31
Aridity Index Period (P/PET)
0.5-1.0
>1.0
>150 years
>150 years
100 years
>150 years
50 years
>150 years
Indirect climatic constraints
At this stage of the model development, it has not been possible to implement in the climatic suitability assessment other climatically driven constraints such as pests and diseases, invasion of unwanted
species or weeds, and limitations of workability and accessibility (due to excessive wetness), which
may very well reduce annual biomass increments.
4.5
Soil and Terrain Suitability Analysis
Soil suitability
From the basic soil requirements of forest tree species, a number of soil characteristics have been established which relate to growth and biomass production. For the 52 forest tree species considered,
optimal, sub-optimal and marginal/unsuitable levels of these soil characteristics have been established
(Table 10).
Beyond critical ranges, tree species cannot be expected to grow satisfactorily and produce biomass.
Soil suitability classifications are based on knowledge of requirements, prevailing soil conditions, and
applied management. In other words, soil suitability classifications describe in broad terms to what
extent soil conditions match tree species requirements under defined input and management circumstances.
Specifically for soil suitability evaluation purposes, a range of quantitative and qualitative attributes
have been identified as being required for soil suitability assessments as follows:
(i)
Information that can be inferred from the soil units of legends of the soil maps. This includes: soil drainage, soil depth, gravel content, electrical conductivity, exchangeable sodium percentage, calcium carbonate content and gypsum content.
(ii)
Other attributes require quantitative data and are to be derived from soil profile databases.
(see Section 3.2).
In Appendix III soil unit and soil phase suitability ratings are proposed for the 52 tree species considered. Two sets of ratings have been compiled. One set for natural soil conditions, excluding consideration of any inputs or specific soil management. This set of ratings has been used for the soil suitability assessment regarding conservation forestry LUTs (see Table 6). A second set of ratings was
applied for traditional production forest and biomass plantation forestry LUTs (see Tables 7 and 8).
These latter ratings assume inputs in terms of nutrients and specific management, in particular, in
support of juvenile growth. The ratings presented for soil units and soil phases in Appendix III are the
following:
S1
S2
S1/S2
S1/N
S2/N
N
(1)
(2)
(3)
(4)
(5)
(6)
Optimal conditions
Sub-optimal conditions
50% optimal and 50% sub-optimal conditions
50% optimal and 50% not suitable conditions
50% sub-optimal and 50% not suitable conditions
Not suitable conditions
Terrain suitability
Sustainable forest production on sloping land is concerned with the prevention of erosion of topsoil
and decline of fertility. Usually this is achieved by combining special forest management and soil
conservation measures. Slopes with tree stands that are providing inadequate soil protection and without sufficient soil conservation measures, may cause a considerable risk of accelerated soil erosion. In
the short term such situation may lead to production losses due to erosion of topsoil. In the long term,
this may result in truncation of the soil profile and consequently reduction of natural soil fertility and
of available soil moisture.
32
The terrain-slope suitability rating used in the FAEZ model captures the factors described above,
which influence production and sustainability. This is achieved through: (i) defining for the various
forest/LUTs permissible slope ranges by setting maximum slope limits; (ii) for slopes within the permissible limits, accounting for likely yield reduction due to loss of topsoil, and (iii) distinguishing
among forestry practices ranging from manual to highly mechanized management.
Ceteris paribus, i.e., under similar forest cover, soil erodibility and forestry and soil management, soil
erosion hazards largely depend on amount and intensity of rainfall. Data on rainfall amount is available on a monthly basis in the 0.5 degree lat/long climate databases.
To account for clearly existing differences in both amount and within-year distribution of rainfall, use
has been made of the modified Fournier index (Fm), which reflects the combined effect of rainfall
amount and distribution (FAO/UNEP, 1977), as follows:
Fm = 12
12
∑
i =1
pi 2
Pann
where:
p i = precipitation of month i
Pann = total annual precipitation
When precipitation is equally distributed during the year, i.e., in each month one-twelfth of the annual
amount is received, then the value of Fm is equal to Pann. On the other extreme, when all precipitation is received within one month, the value of Fm amounts to twelve times Pann. Hence, Fm is sensitive to both total amount and distribution of rainfall and is limited to the range of Pann ≤ Fm ≤ 12
Pann. The Fm index has been calculated for all 0.5 degree grid-cells of the climatic inventory. The
results have been grouped in six classes, namely: Fm < 1300, 1300-1800, 1800-2200, 2200-2500,
2500-2700, and Fm > 2700.
Slope ratings are defined for the seven slope range classes used in the land resources database,
namely: 0-2% flat, 2-5% gently sloping, 5-8 % undulating, 8-16% rolling, 16-30% hilly, 30-45%
steep, and > 45% very steep. Three suitability-rating classes are employed:
S1
S2
N
Optimal conditions
Sub-optimal conditions
Not suitable conditions
Table 15 presents percentage distributions of terrain-slope ratings for the three forest management
types (conservation forestry, traditional production forestry and biomass forestry) for six class ranges
of the modified Fournier index Fm (Fm < 1300; 1300-1800; 1800-2200; 2200-2500; 2500-2700 and
>2700).
.
33
Table 15
Terrain-slope ratings (Fm <1300)
Slope Gradient Classes
Suitability Distribution (%)
Conservation Forestry
Traditional Production Forestry
Biomass Forestry
0-2 %
S1
100
100
100
S2
2-5%
N
S1
100
100
100
S2
5-8%
N
S1
100
100
75
S2
8-16%
N
S1
100
100
25
16-30%
S2
N
50
50
S1
100
50
S2
30-45%
N
S1
100
50
> 45%
S2
N
50
50
100
100
S1
100
N
N
100
100
(Fm: 1300-1800)
Slope Gradient Classes
Suitability Distribution (%)
Conservation Forestry
Traditional Production Forestry
Biomass Forestry
0-2 %
S1
100
100
100
S2
2-5%
N
S1
100
100
100
S2
5-8%
N
S1
100
100
75
S2
8-16%
N
S1
100
100
25
16-30%
S2
N
50
50
S1
100
50
S2
30-45%
N
S1
100
50
> 45%
S2
N
50
50
100
100
S1
100
N
N
100
100
(Fm: 1800-2200)
Slope Gradient Classes
Suitability Distribution (%)
Conservation Forestry
Traditional Production Forestry
Biomass Forestry
0-2 %
S1
100
100
100
S2
2-5%
N
S1
100
100
100
S2
5-8%
N
S1
100
100
75
S2
8-16%
N
S1
100
100
16-30%
S2
N
25
25
75
5-8%
8-16%
S1
100
50
S2
30-45%
N
S1
100
50
> 45%
S2
N
25
75
100
100
S1
100
N
N
100
100
(Fm: 2200-2500)
Slope Gradient Classes
Suitability Distribution (%)
Conservation Forestry
Traditional Production Forestry
Biomass Forestry
0-2 %
S1
100
100
100
S2
2-5%
N
S1
100
100
100
S2
N
S1
100
100
75
S2
N
S1
100
100
25
16-30%
S2
N
25
75
S1
100
50
S2
30-45%
N
S1
100
50
> 45%
S2
N
25
75
100
100
S1
100
N
N
100
100
(Fm: 2500-2700)
Slope Gradient Classes
Suitability Distribution (%)
Conservation Forestry
Traditional Production Forestry
Biomass Forestry
0-2 %
S1
100
100
100
S2
2-5%
N
S1
100
100
100
S2
5-8%
N
S1
100
100
50
S2
8-16%
N
S1
100
75
S2
16-30%
N
25
50
S1
100
25
S2
30-45%
N
S1
100
S2
75
100
> 45%
N
S1
100
N
100
100
100
N
100
100
(Fm >2700)
Slope Gradient Classes
Suitability Distribution (%)
Conservation Forestry
Traditional Production Fo restry
Biomass Forestry
0-2 %
S1
100
100
100
S2
2-5%
N
S1
100
100
100
S2
5-8%
N
S1
100
100
50
S2
8-16%
N
50
S1
100
75
S2
16-30%
N
25
100
34
S1
100
25
S2
30-45%
N
75
100
S1
100
S2
> 45%
N
100
100
S1
100
N
N
100
100
4.6
Suitability Analysis of Seasonal Wet Sites
For assessing the suitability of wetness prone soils, the tree species have been grouped according their
tolerance to excess moisture and resulting poor oxygen supply to rooting systems (Shugart et al.,
1992):
Group I
Group II
Group III
Group IV
Tree species not tolerant to wetness
Tree species somewhat tolerant to wetness
Tree species tolerant to wetness
Tree species requiring wet conditions
Group I:
Fagus sylvatica, Quercus petracea, Q. rubra, Robinia pseudoacacia, Castanea sativa,
Junglans regia, Picea abies, P. asperata, P. ajanensis, P. obovata and P. koreaiensis
are not tolerant to wetness and cannot be grown on seasonal wet soils. All Fluvisols,
Gleysols and sites affected by water-logging (Table 5) due to snowmelt are considered not suitable (N).
Group II:
Betula tortuosa, Populus tomentosa, P. euphraetica, Quercus robur, Acer plantanoides, A. campestre, A. campbellii,, Pinus sibirica, P. koreaiensis and to some extent
Betula pendula, B. verrucosa, B. platyphylla, B. papyrifera, Populus termula, Quercus lanuginose, Q. cerris, Q. acutissima, Q. variablis, Q. mongolica, Carpinus betulus,Tilia cordata, Pinus tabulaeformis,P. massoniana, P. yunnanensis, Abies alba, A.
sibirica and Cunnninghamia lanceolata are somewhat tolerant to wetness and benefit
to some extent from high groundwater tables and extra residual moisture available in
Fluvisols and Gleysols. In water collecting sites with less than 30 days LGP, it is assumed there is on the average insufficient water to grow successfully trees, especially
since the contribution from rainfall is also almost non-existent. At LGPs longer than
120 days trees will grow irrespective additional water. It has been assumed that the
Fluvisols/Gleysols are too wet in LGPs over 300 days. Table 16 presents suitability
classes for the Group II tree species by length of growing period, accounting for differences in amounts of residual moisture and in periods with water-logging and inundation. Water-logging and inundation affect different parts of Fluvisols and Gleysols
differently. Higher parts are much less affected than the lower parts. Areas affected by
prolonged water-logging of more than 10 days as result of water from snowmelt (Table 5) are considered not suitable (N) for Group II tree species. Areas affected between 5 and 10 days are rated sub-optimal (S2).
Table 16
LGP suitability ratings for water collecting sites: Group II tree species
Suitability
class
Distribution of suitability classes (%) for water-collecting sites by LGP class
0
129
3059
6089
VS
33
mS
33
33
34
34
Group III:
120149
150179
180209
210239
33
33
33
33
33
33
33
33
33
33
33
S
MS
NS
90119
100
100
240269
270299
300329
330364
365-
365+
100
100
100
100
33
34
34
34
34
34
33
33
33
34
34
Populus alba, P. basamiferas, P. maximowiczii, Fraxinus excelsior , F. mandshurica,
Alnus glutinosa, Larix sibirica and surely Betula pubescens, Populus nigra, P.
euramericana, Larix gmelinii and Pinus sylvestris are relatively tolerant to wet conditions. These species tolerate prolonged periods of water-logging and some inundation.
Table 17 presents suitability classes for the Group III tree species by length of growing period, accounting for differences in amounts of residual moisture and for periods
with waterlogging and inundation. Areas affected by snowmelt water are rated as
35
follows for Group III tree species. Water-logging periods of less than 10 days are considered to pose no constraint (S1) to growth of Group III tree species; periods between 10 and 30 days are considered sub-optimal (S2), and periods of more than 30
days not suitable (N).
Table 17
Suitability
class
LGP suitability ratings for water collecting sites: Group III tree species
Distribution of suitability classes (%) for water-collecting sites by LGP class
0
129
3059
6089
VS
120149
150179
180209
210239
240269
270299
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
S
33
MS
mS
NS
90119
100
33
33
33
67
34
34
300329
330364
365-
365+
100
100
33
34
34
34
34
34
34
34
33
33
33
34
34
Group IV:
Willows, Salix alba and especially Salix viminalis, are adapted to wet conditions and
tolerate prolonged periods of water-logging and inundation. Long periods of waterlogging and/or inundation affect growth. Table 18 presents suitability classes for these
tree species by length of growing period.
Table 18
LGP suitability ratings for water collecting sites : Group IV tree species
Suitability
class
Distribution of suitability classes (%) for water-collecting sites by LGP class
0
129
3059
6089
90119
120149
150179
180209
210239
240269
270299
300329
330364
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
33
34
34
34
34
34
34
34
34
34
33
33
34
33
VS
S
MS
33
33
mS
33
34
NS
100
100
34
365-
365+
34
36
Chapter 5
Preliminary Results of Potential Forest Productivity Assessment
This section describes preliminary results 14 of the FAEZ tree species productivity assessment. The
study covers the territory of China, Mongolia and the former Soviet Union (FSU).
Estimations of land suitability/productivity were made involving 52 different tree species and for
three assumed management objectives. For biomass plantation forestry and traditional production forestry, results are expressed in terms of annual biomass increments over optimum rotation periods for
the best producing species. For conservation forestry only land suitability was determined. The basic
six suitability classes used in the presentation of the results reflect the performance of the best adapted
species in each land unit as follows:
Table 19
Suitability classification for conservation forestry
Symbol
VS
S
MS
mS
VmS
NS
Description
Percentage of maximum attainable annual
growth for best adapted species
80-100
60-80
40-60
20-40
5-20
<5
Very Suitable
Suitable
Moderately Suitable
Marginally Suitable
Very Marginally Suitable
Not Suitable
The suitability/productivity assessments were carried out for 5 km grid-cells, by matching climate
characteristics, calculating gross biomass increments, and subsequently, by matching soil and terrain
characteristics of each grid-cell with ecological requirements of each considered tree species by management objective. The results were stored in a large database, containing a distribution of land suitability classes and attainable annual biomass increments by 5 km grid-cell for each of the 52 tree species.
For each grid-cell suitability results are also represented by a suitability index SI, reflecting the suitability make-up of a grid-cell in accordance with the definition of suitability classes, namely as:
SI = VS*0.9 + S*0.7 + MS*0.5 + mS*0.3 + VmS*0.1.
The grid-cell results have subsequently been aggregated by province for China, by individual state of
the FSU (for Russia by oblast) and for Mongolia. Table A-1 in Appendix I presents a list of codes and
names of the States of the FSU and the oblasts of Russia. (Plate 13 shows a map of the FSU15 and
Plate 14 of China with the boundaries of the various administrative divisions 16).
Depending on management objectives different sub-sets of the 52 tree species were considered as
follows:
(i)
(ii)
(iii)
14
15
16
Biomass plantation forestry - Poplar, Alder, Ash and Willow species.
Traditional production forestry - Birch, Poplar, Oak, Beech, Robinia, Larch,
Spruce, Pine and Fir species.
Conservation forest - all 52 species.
This is the first systematic forest p roductivity potential assessment in its kind and before publishing final results,
substantial verification and validation of methodology and calculation procedures is required (see also disclaimer).
The codes in Table A-1 correspond with the codes used in Plate 13.
It should be noted that until recently Chengquing Province was a part of Sichuan Province. The results presented for
the Sichuan Province include the territory of the new Province Chengquing.
37
From various data available in the IIASA LUC project, a GIS17 coverage of agriculture and forest land
in China, Mongolia and the States of the Former Soviet Union was compiled (Plate 12). This coverage
was used to mask or select areas that are in use for cultivation, under forest or under other permanent
use such as urban areas.
Also, a layer has been created to reflect accessibility18 . It records the presence of roads and railroads
and marks grid-cells as accessible, that fall at least partly within a 10 km buffer zone around roads and
railroads (Plate 11). This coverage was used to mask non-accessible areas (see Section 3.4)
5.1
Assessment Scenarios
To demonstrate and test the application of FAEZ, a productivity analysis for the territory of China,
Mongolia and the former Soviet Union has been carried out for seven scenarios, according to the following assumptions:
Scenario 1:
All land is assessed for biomass plantation, traditional and conservation forestry
LUTs regardless accessibility or other current uses.
Scenario 2:
All accessible land is assessed for both biomass plantation and traditional production
forestry LUTs.
Scenario 3:
As in scenario 1, excluding grid-cells classified as dominantly cultivated land and
urban areas.
Scenario 4:
As in scenario 1, only for areas classified as currently under forest.
Scenario 5:
As in scenario 2, excluding cultivated land and urban areas.
Scenario 6:
As in scenario 2, only for areas currently under forest.
Scenario 7:
As in scenario 3, excluding areas currently under forest.
Results aggregated by administrative units are presented in tabular form in the Appendix II. The results are organized by major LUTs: (i) Biomass plantation forestry (results have been provided separately for Willow (Salix viminalis) alone, and for the biomass plantation forestry species combined);
(ii) Traditional production forestry (results for the traditional forestry species combined), and (iii)
Conservation forestry (results for the conservation forestry species combined). Selected results as
provided in the Appendix II are listed below:
Salix viminalis:
Table A2
Table A3
Table A4
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Biomass plantation forestry:
Table A5
Table A6
Table A7
17
18
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
The map showing cultivated areas and forested areas has been compiled from the land categories and the agricultural
regionalization inventories of the FSU (Stolbovoi et al., 1997a, 1997b), the 1:1,000,000 land use map of China (Wu
Chuanjun, 1991) and Vegetation Distribution for Mongolia (Sitch and van Minnen, 1996). These three inventories
were combined, a reclassification was applied featuring areas with dominantly agriculture and forest, and was transferred to the 5km grid.
Based on existing infrastructure information of the Digital Chart of the World (DCW, 1993), an accessibility inventory has been created for the territory of the FSU, China and Mongolia. Standard GIS procedures were used to create
buffer zones of 10 km around the roads and railways, i.e., 5 km on each side. The buffer coverage was then transferred to a 5 km grid, which in turn was used in this study as mask for accessibility.
38
Table A8
Table A9
Accessible areas currently under forest.
All areas, excluding cultivated areas, urban areas and areas currently under forest.
Traditional production forestry:
Table A10
Table A11
Table A12
Table A13
Table A14
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Accessible areas currently under forest.
All areas, excluding cultivated areas, urban areas and areas currently under forest.
Conservation forestry:
Table A15
Table A16
Table A17
All areas.
All areas, excluding cultivated and urban areas.
All areas, excluding cultivated areas, urban areas and areas currently under forest.
The individual tables of Appendix II are organized as follows: The first data column (Total area) records how much land is assessed, given the scenario restrictions. For example, in Mongolia under scenario 1 (considering all the land) the total is 156,198 thousand hectares; under Scenario 2 (land that is
accessible by road or railroad) the total is 63,130 thousand hectares; under Scenario 3 (land, excluding
cultivated and urban areas) the total is 154,858 thousand hectares, under Scenario 4 (land currently
under forest) the total is 7,058 thousand hectares, under Scenario 5 (land that is accessible by road or
railroad, excluding cultivated and urban areas) the total is 62,805 thousand hectares, under Scenario 6
(land that is accessible by road or railroad and is currently under forest) the total is 1,163 thousand
hectares, and finally under Scenario 7 (land that is neither under forest, nor cultivated or urban) the
total is 147,800 thousand hectares.
The next group of nine columns presents extents of land variously suitable for tree growth (see for
definition of the suitability classes Table 19). In the case of biomass plantation forestry and traditional
forestry LUTs a further eight columns follow, presenting production (total annual biomass increments
by suitability classes). Finally a last group of eight columns presents per hectare production following
the same logic.
5.2
Results for Biomass Plantation Forestry
Table 20 provides extents of prime land for Willow considering respectively: all land, all accessible
land, and all accessible land with the exclusion of cultivated and urban areas.
Results for Willow, which is assumed to be grown in short rotation coppice system (SRCS) with
rather specific environmental requirements for growth and management, indicate that prime land
(VS+S) is quite rare. Some areas exist in mainly the Baltic States, Byelorussia, Ukraine, and Russia.
A rather large area is found in China. However, as can be seen in Table 20, when only areas are considered that are accessible and when excluding cultivated and urban areas, then in China, only less
than 3 million hectares remain from approximate 12 million hectares of potential prime willow land.
Examples of selected results for Willow (Salix viminalis ) are presented in map-form as follows:
Plate 15
Productivity of Salix viminalis (t/ha biomass yield).
Plate 16
Productivity of Salix viminalis in accessible areas, excluding cultivated and urban areas (t/ha biomass yield).
Table 21 presents results in the same format as Table 20, but now combined for all biomass plantation
species considered (Poplar, Alder, Ash and Willow species). The pattern observed with the Willow
only, remains in tact. Major tracts of potential prime land are found in Byelorussia, the Ukraina, Russia. The largest extents are found in China. However, when we confine to accessible areas and take
away cultivated and urban areas, the extents generally reduce approximately three quarters. From this
study it appears that seven of the countries investigated have virtually no potential prime land at all
39
for biomass plantation forestry. These countries are: Mongolia, Armenia, Azerbeijan, Kazakstan, Kirghiztan, Tajik istan and Turkmenistan.
Examples of selected results for the biomass plantation species combined are presented in map-form
as follows:
Plate 17
Plate 18
Plate 19
Table 20
Suitability index for biomass plantation forestry (excluding cultivated and urban areas).
Suitability index for biomass plantation forestry of current forest areas.
Suitability index for biomass plantation forestry in accessible areas (excluding cult ivated and urban areas).
Very suitable and suitable areas for biomass plantation with Willow (Salix
viminalis)
Total
area
(1)
(000ha)
Mongolia
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Russia
Russia West of Urals
Russia East of Urals
China
VS+S
Total areas
(2)
(000ha) % of (1)
Accessible areas
(3)
(000ha) % of (1)
VS+S
Accessible areas
VS+S
Accessible areas, e xcluding cultivated
(4)
land and urban areas
(000 ha) % of (3)
(000 ha)
% of (4)
156,198
0
0
63,130
40
0
0
0
-
2,690
0
0
2,025
75
0
0
0
-
7,868
0
0
6,095
77
0
0
0
20,348
640
3
17,955
88
549
3
184
34
3,938
137
3
3,365
73
112
3
74
66
6,523
6
0
4,763
73
6
0
1
17
268,445
1
0
165,068
61
1
0
1
100
-
19,548
0
0
10,428
53
0
0
0
-
6,313
284
4
5,573
88
245
4
91
37
6,420
582
9
6,018
94
543
9
176
32
3,000
16
1
2,848
95
15
1
1
7
9,013
0
0
4,775
53
0
0
0
-
45,390
0
0
22,535
50
0
0
0
-
57,570
634
1
51,955
90
573
1
77
13
1,674,521
3,014
0
503,616
30
2.274
0
704
31
389,947
1,353
0
244,894
63
1,173
0
158
13
1,284,574
1,661
0
258,722
20
1,101
0
546
50
937,041
12,421
1
416,566
44
8,408
2
2,950
35
40
Table 21
Very suitable and suitable areas for biomass plantation Forestry
Total
area
(1)
(000ha)
Mongolia
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Russia
Russia West of Urals
Russia East of Urals
China
5.3
VS+S
Total areas
(2)
(000ha) % of (1)
Accessible areas
(3)
(000ha) % of (1)
VS+S
Accessible areas
VS+S
Accessible areas, e xcluding cultivated
(4)
land and urban areas
(000 ha) % of (3)
(000 ha)
% of (4)
156,198
0
0
63,130
40
0
0
0
-
2,690
0
0
2,025
75
0
0
0
-
7,868
0
0
6,095
77
0
0
0
20,348
6,048
30
17,955
88
5,375
30
1,589
30
3,938
567
14
3,365
73
525
16
199
38
6,523
114
2
4,763
73
97
2
12
12
268,445
5
0
165,068
61
4
0
3
75
-
19,548
0
0
10,428
53
0
0
0
6,313
831
13
5,573
88
712
13
192
29
-
6,420
1893
29
6,018
94
1,757
29
876
50
3,000
190
6
2,848
95
182
6
14
8
9,013
0
0
4,775
53
0
0
0
-
45,390
0
0
22,535
50
0
0
0
57,570
8,732
15
51,955
90
7,973
15
816
-
1,674,521
23,110
1
503,616
30
18,488
4
6259
3
389,947
17,483
4
244,894
63
14,622
6
4515
31
1,284,574
5,627
0
258,722
20
3,866
1
1744
45
937,041
39,729
4
416,566
44
27,362
7
10,415
38
10
Results for Traditional Production Forestry
Table 22 provides extents of prime land for traditional production forestry. To enable easy comparisons of results, Table 22 addresses the same categories as were provided for biomass plantation forestry in the Table 20 and 21, namely: all land, all accessible land and all accessible land with the exclusion of cultivated and urban land.
The results presented are based on all species considered for traditional production forestry combined,
i.e., Birch, Poplar, Oak, Beech, Robinia ; Larch, Spruce, Pine and Fir species. The relatively wide environmental tolerances of especially Pine, Spruce, Birch and Larch is the foremost reason for the large
areas of prime land that we have estimated, about four times more than for the biomass plantation
species. The slope limitations imposed for fully mechanized planting and harvesting assumed for the
biomass plantation LUTs explains another part of the differences found. Countries with over one million hectares of potential prime land which is accessible and not already used for cultivation or urban
purposes are: Byelorussia (more than 3 million), Lithuania (more than 1.4 million), Ukraine (more
than 1.8 million), Russia (more than 68 million) and China (more than 46 million hectares).
Examples of selected results for the traditional production forestry species combined are presented in
map-form as follows:
Plate 20
Plate 21
Plate 22
Suitability index for traditional production forestry (excluding cultivated and urban
areas).
Suitability index for traditional production forestry of current forest areas.
Suitability index for traditional production forestry of accessible areas currently
forested.
41
Table 22
Very suitable and suitable areas for traditional production forestry
Total
area
(1)
(000ha)
Mongolia
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Russia
Russia West of Urals
Russia East of Urals
China
5.4
VS+S
Total areas
(2)
(000ha) % of (1)
Accessible areas
(3)
(000ha) % of (1)
VS+S
Accessible areas
VS+S
Accessible areas, e xcluding cultivated
(4)
land and urban areas
(000 ha) % of (3)
(000 ha)
% of (4)
156,198
96
0
63,130
40
9
0
9
100
2,690
53
2
2,025
75
47
2
39
87
7,868
63
1
6,095
77
49
1
45
92
20,348
10,413
51
17,955
88
9,261
52
3,047
33
3,938
1,735
44
3,365
73
1,543
46
547
37
6,523
404
6
4,763
73
351
7
91
26
268,445
814
0
165,068
61
495
0
385
79
19,548
53
0
10,428
53
43
0
28
65
6,313
2,226
35
5,573
88
1,951
35
609
31
6,420
2,900
45
6,018
94
2,719
45
1,479
54
3,000
805
27
2,848
95
778
27
26
3
9,013
0
0
4,775
53
0
0
0
-
45,390
0
0
22,535
50
0
0
0
57,570
20,665
36
51,955
90
18,794
36
1,827
10
-
1,674,521
204,248
12
503,616
30
123,126
24
68,967
56
389,947
113,377
29
244,894
63
84,497
35
40,271
48
1,284,574
90,871
7
258,722
20
38,629
15
28,696
74
937,041
129,701
14
416,566
44
80,347
19
46,120
57
Results for Conservation Forestry
For the assessment of suitability for conservation forestry all 52 species considered in this study are
used. The selection of tree species is based on criteria other then biomass production, as used for biomass plantation and traditional production forestry. For conservation forestry, the tree species with the
best ecological adaptation (highest suitability index) has been selected irrespective of its productivity.
The results are presented by suitability class (Appendix II Table A15-17 and Table 23).
Table 23 provides results in terms of extents of land that is at minimum marginally suitable for at least
one species. The results are presented for (i) all areas; all areas, but excluding cultivated and urban areas, and (iii) all areas excluding cultivated and urban areas and areas currently already under forest.
The fact, that no slope limitations are imposed when assessing suitability for conservation forestry, a
large number of species spanning a wide range of ecological adaptability are considered, and all land
with at least marginal suitability is reported, resulted in large extents of suitable land in the majority
of countries investigated. Very large shares of potential suitable land (more than 70% of total area)
were found in Byelorussia, the Baltic states, Moldavia and the Ukraine. Low shares (less than 10 %)
were found in Mongolia, Kazakstan, Tajikistan, and Turkmenistan. When discounting land in cult ivated or urban use or already under forest, then the highest shares (as percentage of total land) of land
potentially suitable for conservation forest are found, in Armenia (16%), Azerbeijan (10%), Lithuania
(21%) and China (11%). In absolute terms, the largest areas are found in the biggest countries, namely
in Russia, more than 81 million, in particular in Russia east of the Urals with more than 65 million,
and in China almost 100 million hectares.
An example in map form of suitability results for conservation forestry is presented in Plate 23: Suitability index for conservation forestry (excluding cultivated and urban areas).
42
Table 23
Areas suitable for conservation forestry
Total area
(1)
Mongolia
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Russia
Russia West of Urals
Russia East of Urals
China
Chapter 6
VS+S+MS+mS
Total area
(000ha)
(000ha)
156,198
8,843
% of (1))
6
2,690
688
7,868
1,495
20,348
3,938
VS+S+MS+mS
VS+S+MS+mS
Excluding cultivated and Excluding cultivated land,
urban areas
urban areas and areas currently under forest
(000 ha)
% of (1))
(000 ha)
% of (1))
8,774
6
8,074
5
26
499
19
429
16
19
1,110
14
783
10
19,061
94
7,014
34
1490
7
2,742
70
1,069
27
261
7
6,523
2,067
32
1,191
18
511
8
268,445
22,058
8
10,982
4
9,616
4
19,548
2,191
11
1,330
7
1,009
5
6,313
5,708
90
2,056
33
198
3
6,420
5,853
91
2,986
47
1,365
21
3,000
2,596
86
89
3
6
0
9,013
762
8
511
6
8
0
45,390
31
0
26
0
8
0
57,570
45,761
79
4,907
9
530
1
1,674,521
518,789
31
387,013
23
81,613
5
389,947
240,535
62
1239,849
36
16,289
4
1,284,574
278,245
22
247,164
19
65,324
5
937,041
374,584
40
248,019
26
99,412
11
Concluding Remarks
This study confirms in quantitative manner the uneven distribution of potentials for tree growth and
therefore to a large extent also the uneven distribution of the production potentials of renewable forest
biomass resources within China, Mongolia and the FSU. The results indicate that the concentration of
potential areas for the production of woody biomass is mainly located in the European part of the FSU
and China.
The results obtained through this exercise, in absolute terms, should be treated in a conservative manner at appropriate aggregation levels, which are commensurate with the resolution of basic data and
the scale of the study. Relative results, i.e., the comparison of absolute results at sub-national level in
China and the FSU, are likely more robust, when noting that for the entire study area procedures and
data were uniformly applied.
The study revealed that in order to obtain a more complete picture of potentials for forest production
in particular of China, additional tree species should be included. In particular, species should be included that are specifically adapted to warm sub-tropical climate prevailing in Southeast China. It is
expected that the FAEZ procedures and model parameters will be benefiting from scrutiny with
further use.
Limitations
The FAEZ results presented are based on 5 km resolution environmental data sets of North, Central
and East Asia. While representing the most recent data compilations for this territory, the quality and
reliability of these datasets is known to be uneven across the region.
Also silvicultural data, such as data on environmental requirements of individual tree species, contain
assumptions and generalizations necessary for the scale of the study. In particular, further work is required to quantify occurrence and severity of constraints indirectly related to climate conditions that
43
adversely affect growth and productivity of tree species. These constraints include impacts due to
pests, diseases, invasion of unwanted species or weeds, workability, and forest fires.
Various types of land degradation may very well affect forest suitability and productivity. Land degradation information could not be considered in the present FAEZ assessment. In a future version soil
degradation data available in the LUC-GIS database for North, Central and East Asia will be reviewed
for use in FAEZ.
For the above reasons the results obtained from this first implementation of FAEZ should be treated in
a conservative manner at appropriate aggregation levels, which are commensurate with the resolution
of underlying basic data and the scale of the study.
Next steps
The compatibility of the FAEZ approach with the methods for agriculture (AEZ) allows for consistent
integration of agriculture and forest sector assessments. It provides key inputs in region specific applications of the IIASA/FAO multi-criteria model analysis (MCMA) tool which is targeted to provide
better assistance for decision making for rural development planning at national and regional levels.
Applications using the North, Central and East Asian LUC-GIS data sets have been started. With the
already initiated integration of pan-European data sets, also further FAEZ/AEZ/MCMA applications
are becoming possible. For Europe the LUC project focus will be initially on countries envisaged for
the EU eastward enlargement.
44
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47
PLATES
Plate 1
Length of growing periods.
Plate 2
Thermal climates.
Plate 3
Mean temperatures of coldest month.
Plate 4
Mean temperatures of warmest month.
Plate 5
Mean minimum temperatures of coldest month.
Plate 6
Temperature growing periods (LGP t=5 ).
Plate 7
Frost-free periods (LGP t=10).
Plate 8
Temperature sums (t > 5o C).
Plate 9
Temperature sums (t > 10o C).
Plate 10
Zones with accessibility to roads and railroads.
Plate 11
Agriculture and forest land.
Plate 12
Aridity index.
Plate 13
States of the FSU and Oblasts within Russia Administrative areas of FSU.
Plate 14
Provinces of China.
Plate 15
Productivity of Salix viminalis (t/ha biomass yield).
Plate 16
Productivity of Salix viminalis in accessible areas, excluding cultivated and urban areas (t/ha biomass yield).
Plate 17
Suitability index for biomass plantation forestry (excluding cultivated and urban areas).
Plate 18
Suitability index for biomass plantation forestry of current forest areas.
Plate 19
Suitability index for biomass plantation forestry in accessible areas (excluding cult ivated and urban areas).
Plate 20
Suitability index for traditional production forestry (excluding cultivated and urban
areas).
Plate 21
Suitability index for traditional production forestry of current forest areas.
Plate 22
Suitability index for traditional production forestry of accessible current forest areas.
Plate 23
Suitability index for conservation forestry (excluding cultivated and urban areas).
49
Plate 1
Length of growing period
50
Plate 2
Thermal climates
51
Plate 3
Mean temperatures of coldest month
52
Plate 4
Mean temperatures of warmest month
53
Plate 5
Mean minimum temperatures of coldest month
54
Plate 6
Temperature growing periods (LGPt=5)
55
Plate 7
Frost-free periods (LGPt=10)
56
Plate 8
Accumulated temperature s (t > 5o C)
57
Plate 9
Accumulated temperatures (t > 10o C)
58
Plate 10
Zones with accessibility to roads and railroads
59
Plate 11 Agriculture and forest land
60
Plate 12
Aridity index
61
Plate 13
States of the FSU and Oblasts within Rusia
62
Plate 14 Provinces of China
63
Plate 15
Productivity of Salix viminalis (t/ha biomass yield)
64
Plate 16 Productivity of Salix viminalis in accessible areas, excluding cultivated and urban areas (t/ha biomass yield)
65
Plate 17
Suitability index for biomass plantation forestry (excluding cultivated and urban areas)
66
Plate 18
Suitability index for biomass plantation forestry of current forest areas
67
Plate 19
Suitability index for biomass plantation forestry in accessible areas (excluding cultivated and urban areas)
68
Plate 20
Suitability index for traditional production forestry (excluding cultivated and urban areas)
69
Plate 21
Suitability index for traditional production forestry of current forest areas
70
Plate 22
Suitability index for traditional production forestry of accessible current forest areas
71
Plate 23
Suitability index for conservation forestry in non-cultivated areas
72
APPENDIX I
Table A-1
List of States of the FSU and Oblasts of Russia, respectively west and east of the
Urals
Code States of the FSU (excluding Russia)
11
12
13
14
15
16
17
18
19
20
21
22
23
Code
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Oblasts in Russia (West of the Urals)
Krasnodar Kray
Stavropol Kray
Arkhangelsk oblast
Astrakhan oblast
Belgorod oblast
Bryansk oblast
Vladimir oblast
Volgograd oblast
Vologda oblast
Voronezh oblast
Nizhni Novgorod oblast
Nenets a.okr.
Ivanovo oblast
Kaliningrad oblast
Tver oblast
Kaluga oblast
Kirov oblast
Kostroma oblast
Samara oblast
Kursk oblast
Komi-Permyak a.okr.
Leningrad oblast
Lipetsk oblast
Moscow oblast
Murmansk oblast
Novgorod oblast
Orenburg oblast
Oryel oblast
Penza oblast
Perm oblast
Pskov oblast
Rostov oblast
Ryazan oblast
Saratov oblast
Smolensk oblast
Tambov oblast
Tula oblast
Ulyanovsk oblast
Yaroslavl oblast
Adigei Republic
Bashkortostan Republic
Extents
(000 ha)
2690
7868
20348
3938
6523
268445
19548
6313
6420
3000
9013
45390
57570
457066
Code
182
183
185
186
187
188
189
190
191
192
194
196
197
Code
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
176
181
193
195
198
7620
6635
38190
4598
2665
3483
2925
11265
14628
5195
7515
16858
2270
1240
8395
2963
11930
6000
5118
3020
3280
7500
2410
4665
13960
5450
12418
2458
4320
12715
5568
10133
3935
10375
4943
3435
2553
3690
3260
775
14435
Oblasts in Russia (West of the Urals)
Daghestn Republic
Kabardino-Balkarian Republic
Kalmyk-Khalm-Tangch Republic
Karelia Republic
Komi Republic
Mari-El Republic
Mordovian SSR
North-Ossetian SSR
Karachai-Cherkess Republic
Tatarstan Republic
Udmurt Republic
Checheno-Ingush Republic
Chuvash Republic
West of URAL Total
Oblasts in Russia (East of the Urals)
Altai Kray
Gorno-Altai Republic
Krasnoyarsk Kray
Primorski Kray
Taymyr a.okr.
Khabarovsk Kray
Amur oblast
Evenk a.okr
Yevrey (Jewish) a.oblast
Irkutsk oblast
Ust-Orda Buryat a.okr.
Kamchatka oblast
Koryak a.okr.
Kemerovo oblast
Chukchi a.okr.
Kurgan oblast
Magadan oblast
Novosibirsk oblast
Omsk oblast
Sakhalin oblast
Sverdlovsk oblast
Aga-Buryat a.okr.
Tomsk oblast
Tyumen oblast
Khanty-Mansi a.okr.
Yamalo-Nenets a.okr.
Chelyabinsk oblast
Chita oblast
Buryat Republic
Tuva Republic
Chita oblast
Buryat Republic
Tuva Republic
Khakass Republic
Sakha (Yakutia) Republic
Russia East of Urals
16653
9385
71140
16338
82285
77545
36283
75673
3700
76270
2178
17045
28903
9500
70770
7110
45830
17673
13980
8095
19273
1970
31145
15860
53163
66588
8763
41493
33533
17035
6120
303275
9750
3595
241375
1284574
Russia
1674521
Other States of the FSU
457066
2131587
FSU
73
Extents
(000 ha)
5033
1238
7510
18253
41370
2365
2590
778
1468
6663
4150
1930
1808
389947
APPENDIX II
Potential Productivity for Forestry - Scenario results.
Salix viminalis:
Table A2
Table A3
Table A4
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Biomass plantation forestry:
Table A5
Table A6
Table A7
Table A8
Table A9
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Accessible areas currently under forest.
All areas, excluding cultivated areas, urban areas and areas currently under forest.
Traditional production forestry:
Table A10
Table A11
Table A12
Table A13
Table A14
All areas.
Accessible areas.
Accessible areas, excluding cultivated and urban areas.
Accessible areas currently under forest..
All areas, excluding cultivated areas, urban areas and areas currently under forest.
Conservation forestry:
Table A15
Table A16
Table A17
All areas.
All areas, excluding cultivated and urban areas.
All areas, excluding cultivated areas, urban areas and areas currently under forest.
74
APPENDIX II
Table A2 PRODUCTION POTENTIALS FOR BIOMASS PLANTATIONS WITH WILLOW ( Salix viminalis ) - ALL AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
156198
0
0
0
0
0
0
0
78
156119
2690
7868
20348
3938
6523
268445
19548
6313
6420
3000
9013
45390
57570
0
0
640
137
6
1
0
284
582
16
0
0
634
0
0
2410
598
62
6
0
1038
1288
54
2
0
3059
0
320
3240
938
141
1907
85
1860
2070
93
23
1
5095
457066
2300
8517
Krasnodar Kray
12
7620
Stavropol Kray
12
6635
Arkhangelsk oblast
12
38190
Astrakhan oblast
12
4598
Belgorod oblast
12
2665
Bryansk oblast
12
3483
Vladimir oblast
12
2925
Volgograd oblast
12
11265
Vologda oblast
12
14628
Voronezh oblast
12
5195
Nizhni Novgorod oblast 12
7515
Nenets a.okr.
12
16858
Ivanovo oblast
12
2270
Kaliningrad oblast
12
1240
Tver oblast
12
8395
Kaluga oblast
12
2963
Kirov oblast
12
11930
Kostroma oblast
12
6000
Samara oblast
12
5118
Kursk oblast
12
3020
Komi-Permyak a.okr. 12
3280
Leningrad oblast
12
7500
Lipetsk oblast
12
2410
Moscow oblast
12
4665
Murmansk oblast
12
13960
Novgorod oblast
12
5450
Orenburg oblast
12
12418
Oryel oblast
12
2458
Penza oblast
12
4320
Perm oblast
12
12715
Pskov oblast
12
5568
Rostov oblast
12
10133
Ryazan oblast
12
3935
Saratov oblast
12
10375
Smolensk oblast
12
4943
Tambov oblast
12
3435
Tula oblast
12
2553
Ulyanovsk oblast
12
3690
Yaroslavl oblast
12
3260
Adigei Republic
12
775
Bashkortostan Republic 12
14435
Daghestn Republic
12
5033
Kabardino-Balkarian Republic
12
1238
Kalmyk-Khalm-Tangch Republic
12
7510
Karelia Republic
12
18253
Komi Republic
12
41370
Mari-El Republic
12
2365
Mordovian SSR
12
2590
North-Ossetian SSR
12
778
Karachai-Cherkess Republic
12
1468
Tatarstan Republic
12
6663
Udmurt Republic
12
4150
Checheno-Ingush Republic
12
1930
Chuvash Republic
12
1808
Altai Kray
12
16653
26
1
0
0
3
0
0
0
0
0
50
0
0
29
16
0
0
0
0
231
0
0
159
0
0
0
0
263
0
0
16
0
166
0
0
14
226
0
2
2
0
1
12
0
0
0
24
44
37
20
0
0
11
0
698
42
4
0
0
9
127
186
0
220
0
611
0
38
198
271
175
65
73
0
794
0
70
337
348
0
425
0
793
0
53
304
0
915
0
0
29
562
0
94
10
263
3
18
0
0
0
71
145
39
27
91
101
13
6
1532
FSU REPUBLICS
Average annual biomass increments (000tons) ---------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
0
0
1
0
0
0
1
250
0
0
0
0
1
0
0
0
0
1
0
0
12
0
0
640
137
5
1
0
284
582
15
0
0
622
0
0
1770
461
56
5
0
754
706
38
2
0
2425
0
320
830
340
79
1901
85
822
782
39
21
1
2036
0
706
393
186
85
3428
103
273
260
42
55
1
541
2690
6274
16715
2814
6297
263111
19359
4180
4090
2865
8935
45388
51930
0
0
9391
1670
92
11
0
3669
7853
212
0
0
9292
0
0
28141
5947
696
53
0
10957
14766
587
16
0
35231
0
2221
33345
7987
1233
9723
450
15621
19376
836
139
7
48529
0
0
0
0
12
0
0
0
0
19
0
0
199
0
0
9391
1670
80
11
0
3669
7853
193
0
0
9093
0
0
18750
4277
604
42
0
7288
6913
375
16
0
25939
0
2221
5204
2040
537
9670
450
4664
4610
249
123
7
13298
0
1638
806
410
196
5881
182
558
524
95
110
3
1201
15773
14
2286
6217
7256
6073
434648
32190
96394
139467
230
31960
64204
43073
11604
651
5
152
0
223
367
233
16
1768
858
929
0
46
368
766
361
343
380
154
1195
142
1050
837
470
0
751
88
1090
618
467
738
196
1202
88
0
1306
699
141
378
199
1377
33
36
0
79
35
130
397
48
28
687
292
75
24
2949
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
14
6
0
0
2
0
0
14
1
0
0
3
0
0
0
0
0
50
0
0
29
16
0
0
0
0
231
0
0
159
0
0
0
0
263
0
0
16
0
166
0
0
14
226
0
2
2
0
1
10
0
0
0
24
44
23
14
0
0
9
0
698
16
3
0
0
6
127
186
0
220
0
561
0
38
169
255
175
65
73
0
563
0
70
178
348
0
425
0
530
0
53
288
0
749
0
0
15
336
0
92
8
263
2
6
0
0
0
47
101
2
7
91
101
2
6
834
609
1
152
0
214
240
47
16
1548
858
318
0
8
170
495
186
278
307
154
401
142
980
500
122
0
326
88
297
618
414
434
196
287
88
0
1277
137
141
284
189
1114
30
18
0
79
35
59
252
9
1
596
191
62
18
1417
298
15
25
0
369
86
0
9
144
301
66
0
0
18
44
0
210
67
322
224
31
643
213
0
0
212
219
7
918
221
114
117
17
154
27
375
0
573
17
58
1421
48
17
0
39
3
35
323
8
1
558
42
50
96
529
6665
6615
37993
4597
2073
3029
2692
11240
12715
4036
6520
16837
2225
855
7585
2602
11376
5554
4641
1600
3107
5806
1360
4195
13960
4488
12110
1361
2784
12027
4716
9819
2716
10132
4916
1753
1853
2976
2864
519
11636
4944
1184
7510
18126
41332
2200
1869
722
1439
5418
3815
1805
1688
13175
408
10
0
0
36
0
0
0
0
0
679
0
0
417
201
0
3
0
0
3096
0
0
2060
0
0
0
0
3658
0
0
207
0
2124
0
0
172
3179
0
29
28
4
14
170
0
0
0
333
542
542
276
0
0
158
0
8894
565
41
0
0
91
1293
1754
0
1910
0
6016
0
349
2169
2574
1721
688
684
0
8556
0
613
3754
3335
0
3960
0
8991
0
506
2868
0
9442
0
0
334
6550
0
870
103
2452
38
235
0
0
0
852
1601
565
345
943
932
182
67
16952
5038
47
776
0
1411
2775
2014
95
10214
5307
7876
0
392
3221
5337
2832
2215
2404
904
10928
746
5756
6706
4038
0
5784
460
10803
3540
2813
5222
1200
11109
528
0
7881
7372
819
2430
1489
8560
212
351
0
390
179
1227
3092
621
352
4308
1993
590
175
24546
212
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
36
0
0
0
0
0
234
95
0
0
35
0
0
196
10
0
0
36
0
0
0
0
0
679
0
0
417
201
0
3
0
0
3096
0
0
2060
0
0
0
0
3658
0
0
207
0
2124
0
0
172
3179
0
29
28
4
12
134
0
0
0
333
542
308
181
0
0
123
0
8894
157
31
0
0
55
1293
1754
0
1910
0
5337
0
349
1752
2373
1721
685
684
0
5460
0
613
1694
3335
0
3960
0
5333
0
506
2661
0
7318
0
0
162
3371
0
841
75
2448
24
65
0
0
0
519
1059
23
69
943
932
24
67
8058
4473
6
776
0
1320
1482
260
95
8304
5307
1860
0
43
1052
2763
1111
1527
1720
904
2372
746
5143
2952
703
0
1824
460
1812
3540
2307
2354
1200
1667
528
0
7547
822
819
1560
1386
6108
174
116
0
390
179
375
1491
56
7
3365
1061
408
108
7594
730
34
42
0
756
181
0
17
319
617
135
0
0
37
95
0
408
125
597
444
65
1148
415
0
0
404
382
14
1751
461
211
260
34
306
54
738
0
1086
33
142
2579
96
38
0
80
5
78
612
18
3
1032
94
110
183
1095
Average annual biomass yield (kg/ha) -----------------------------VS
S
MS
mS
vmS
VS+S VS...MS VS...mS
0
0
1000
0
0
0
7026
3208
0
0
14673
12190
15333
11000
0
12919
13493
13250
0
0
14656
0
0
11677
9945
11226
8833
0
10556
11464
10870
8000
0
11517
0
6941
10292
8515
8745
5099
5294
8398
9360
8989
6043
7000
9525
13996
11318
15692
10000
0
0
12000
0
0
0
0
0
13580
0
0
14379
12563
0
3000
0
0
13403
0
0
12956
0
0
0
0
13909
0
0
12938
0
12795
0
0
12286
14066
0
14500
14000
4000
14000
14167
0
0
0
13875
12318
14649
13800
0
0
14364
0
12742
13452
10250
0
0
10111
10181
9430
0
8682
0
9846
0
9184
10955
9498
9834
10585
9370
0
10776
0
8757
11139
9583
0
9318
0
11338
0
9547
9434
0
10319
0
0
11517
11655
0
9255
10300
9323
12667
13056
0
0
0
12000
11041
14487
12778
10363
9228
14000
11167
11065
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used (short rotation coppice systems): VS conditions: shoots+twigs+leaves/stool+roots, 60/40; S and MS: 50/50; mS and VmS: 40/60
0
0
0
0
18634
0
0
0
0
16027
0
0
16049
0
0
14673
12206
15275
12247
0
12939
13482
13180
0
0
14607
0
9602
10595
9275
10802
9098
0
9665
9794
9946
8024
0
10697
0
6945
6271
5999
6764
5088
5265
5676
5898
6424
5829
6446
6531
0
2319
2050
2203
2317
1716
1773
2041
2018
2259
2009
2131
2219
8842
16429
13981
10327
5936
1911
7739
9400
5105
0
6327
7561
8644
5938
5777
6185
8478
0
8522
8753
6967
7845
6458
6326
5870
9145
5254
5482
8012
8591
0
7702
5227
9911
5728
6024
7076
6122
9242
6000
0
6034
10546
5809
6429
7482
6216
6424
9750
0
4937
5114
9438
7788
12938
12571
6271
6825
7867
7292
8323
18305
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17097
16679
0
0
0
0
0
17125
16764
0
0
17115
0
0
14278
14653
0
0
12429
0
0
0
0
0
13653
0
0
14354
12440
0
13358
0
0
13391
0
0
12965
0
0
0
0
13885
0
0
12873
0
12772
0
0
12165
14087
0
12453
13766
12341
14108
13326
0
0
0
13787
12277
13405
13271
0
0
13792
0
12751
10047
10265
0
0
8884
10151
9442
0
8681
0
9513
0
9281
10386
9298
9849
10520
9419
0
9691
0
8727
9504
9585
0
9326
0
10070
0
9630
9256
0
9766
0
0
10912
10024
0
9112
10003
9297
10348
10766
0
0
0
11020
10435
10812
10637
10327
9229
10770
12190
9664
7345
6298
5101
0
6170
6181
5500
5892
5364
6188
5844
0
5604
6207
5585
5973
5482
5611
5861
5913
5253
5248
5900
5779
0
5594
5235
6107
5728
5568
5428
6107
5816
5980
0
5907
5984
5809
5491
7341
5483
5721
6551
0
4927
5124
6380
5907
6478
6258
5649
5549
6578
6138
5359
2453
2201
1703
0
2049
2098
0
1818
2212
2046
2040
0
0
2065
2176
0
1944
1876
1853
1985
2078
1785
1951
1869
0
1907
1743
1950
1907
2087
1855
2228
2011
1978
2004
1968
0
1895
1940
2459
1815
2018
2187
0
2015
1686
2247
1892
2160
2061
1850
2207
2191
1905
2068
APPENDIX II
Table A2 PRODUCTION POTENTIALS FOR BIOMASS PLANTATIONS WITH WILLOW ( Salix viminalis ) - ALL AREAS
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Gorno-Altai Republic
12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
9385
0
3
44
0
0
3
41
21
9320
71140
31
202
1200
0
31
171
998
1022
68918
16338
111
359
720
0
111
248
361
177
15441
82285
0
0
0
0
0
0
0
0
82285
77545
95
693
1305
0
95
598
612
530
75703
36283
202
1168
3459
0
202
966
2291
1708
31116
75673
0
0
0
0
0
0
0
0
75672
3700
334
732
984
0
334
398
252
72
2645
76270
0
0
8
0
0
0
8
13
76250
2178
0
0
0
0
0
0
0
0
2177
17045
0
0
0
0
0
0
0
0
17022
28903
0
0
0
0
0
0
0
0
28902
9500
0
25
413
0
0
25
388
309
8778
70770
0
0
0
0
0
0
0
0
70745
7110
35
273
1228
0
35
238
955
913
4968
45830
0
0
0
0
0
0
0
0
45830
17673
53
1024
3433
0
53
971
2409
1333
12907
13980
0
26
2470
0
0
26
2444
751
10759
8095
0
0
3
0
0
0
3
15
7984
19273
16
872
2599
0
16
856
1727
595
16078
1970
0
0
0
0
0
0
0
8
1962
31145
0
143
1910
0
0
143
1767
856
28379
15860
0
216
2999
0
0
216
2783
1415
11446
53163
0
0
461
0
0
0
461
272
52429
66588
0
0
0
0
0
0
0
0
66580
8763
81
336
738
0
81
255
402
1066
6959
41493
0
0
0
0
0
0
0
130
41362
33533
0
0
1
0
0
0
1
22
33509
17035
0
0
0
0
0
0
0
9
17026
6120
5
20
55
0
5
15
35
17
6048
303275
0
0
0
0
0
0
0
0
303257
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
389947
1284574
1674521
1353
1661
3014
7530
7624
15154
22516
26979
49495
36
0
36
1317
1661
2978
6177
5963
12140
14986
19355
34341
8755
11783
20538
358600
1245632
1604232
18346
21954
40300
77949
78049
155998
164532
183406
347938
614
0
614
17732
21954
39686
59603
56095
115698
86583
105357
191940
16969
25688
42657
13559
13217
13371
10352
10237
10294
1640
1125
18480
15783
14798
16295
13863
19145
44848
413
9290
9250
13783
16663
18168
21050
11995
16385
23425
2840
56143
17725
37325
115468
20900
40580
5038
163355
119045
72183
40
0
0
0
1
228
1606
105
8
173
228
3376
523
2324
243
1174
1047
66
168
138
0
498
418
92
0
1
0
0
0
4
0
0
0
0
1
6
468
2721
218
38
535
346
5233
983
3929
801
2186
2519
193
353
545
0
1212
1076
203
1
7
4
0
0
11
0
0
48
228
1681
179
2099
4207
678
625
1577
346
5543
1168
4478
1291
2369
3259
309
495
767
0
1581
1094
225
145
82
31
78
1
15
1
0
0
0
0
0
15
535
10
0
0
114
1573
171
976
2
461
129
1
0
0
0
97
13
3
0
0
0
0
0
0
0
0
0
0
0
1
213
1071
95
8
173
114
1803
352
1348
241
713
918
65
168
138
0
401
405
89
0
1
0
0
0
4
0
0
0
0
1
5
240
1115
113
30
362
118
1857
460
1605
558
1012
1472
127
185
407
0
714
658
111
1
6
4
0
0
7
0
0
48
228
1680
173
1631
1486
460
587
1042
0
310
185
549
490
183
740
116
142
222
0
369
18
22
144
75
27
78
1
4
1
0
52
247
1768
575
1693
1153
462
136
204
0
100
43
97
182
16
92
36
30
86
0
181
0
40
192
552
85
109
4
3
4
0
1540
650
15031
15029
11006
10934
12722
18384
43067
67
3525
8040
9207
15189
15782
17700
11649
15861
22573
2840
54381
16630
37061
115130
20267
40464
4850
163350
119027
72177
40
0
0
2
13
3610
25467
1568
114
2472
3729
53869
8079
37620
3367
18334
15268
912
2204
1823
0
7738
6285
1348
0
13
4
0
0
57
0
0
0
0
9
57
6322
37185
2774
385
6211
4931
72656
12687
54203
8871
28381
29950
2177
4001
6094
0
15445
13313
2501
12
70
44
0
0
128
0
0
311
1512
11371
1147
17484
47122
5775
3721
11949
4933
74695
13802
57728
11777
29454
34332
2882
4841
7538
0
17886
13433
2649
819
564
198
400
4
153
4
0
0
0
0
0
269
9731
179
0
0
2095
28350
3126
18017
34
8302
2306
23
0
0
0
1860
246
49
0
0
0
0
0
2
0
0
0
0
2
13
3341
15736
1389
114
2472
1634
25519
4953
19603
3333
10032
12962
889
2204
1823
0
5878
6039
1299
0
13
4
0
0
55
0
0
0
0
7
44
2712
11718
1206
271
3739
1202
18787
4608
16583
5504
10047
14682
1265
1797
4271
0
7707
7028
1153
12
57
40
0
0
71
0
0
311
1512
11362
1090
11162
9937
3001
3336
5738
2
2039
1115
3525
2906
1073
4382
705
840
1444
0
2441
120
148
807
494
154
400
4
25
4
0
113
545
3983
1283
3848
2590
1001
261
432
0
226
89
218
359
31
180
79
67
190
0
405
0
92
403
1266
165
184
7
6
10
0
0
0
2000
13000
15833
15857
14933
14250
14289
16355
15956
15447
16188
13856
15617
14583
13818
13119
13210
0
15538
15036
14652
0
13000
4000
0
0
14250
0
0
0
0
9000
9500
13509
13666
12725
10132
11609
14251
13884
12906
13796
11075
12983
11890
11280
11334
11182
0
12743
12373
12320
12000
10000
11000
0
0
11636
0
0
6479
6632
6764
6408
8330
11201
8518
5954
7577
14257
13476
11817
12891
9122
12433
10535
9327
9780
9828
0
11313
12279
11773
5648
6878
6387
5128
4000
10200
4000
0
937041
12421
23589
34600
4100
8321
11168
11011
8142
894173
193896
308407
378484
74589
119307
114511
70077
18033
15610
13074
10939
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
LC
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Average annual biomass increments (000tons) ---------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
6
33
245
0
6
27
212
36
378
1806
7381
0
378
1428
5575
2222
1615
4134
6346
0
1615
2519
2212
376
0
0
0
0
0
0
0
0
1260
7370
11293
0
1260
6110
3923
1268
2766
11846
24359
0
2766
9080
12513
3169
0
0
0
0
0
0
0
0
4676
8662
10142
0
4676
3986
1480
139
0
0
57
0
0
0
57
33
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
205
2150
0
0
205
1945
642
0
0
0
0
0
0
0
0
440
2807
7838
0
440
2367
5031
1533
0
0
0
0
0
0
0
0
653
9392
23239
0
653
8739
13847
2935
0
221
12754
0
0
221
12533
2080
0
0
23
0
0
0
23
35
204
7935
17281
0
204
7731
9346
1132
0
0
0
0
0
0
0
24
0
1167
10921
0
0
1167
9754
2025
0
1922
16391
0
0
1922
14469
3902
0
0
2364
0
0
0
2364
696
0
0
0
0
0
0
0
0
1001
3408
5679
0
1001
2407
2271
1796
0
0
3
0
0
0
3
413
0
0
7
0
0
0
7
70
0
0
0
0
0
0
0
29
61
189
387
0
61
128
198
38
0
0
0
0
0
0
0
0
Average annual biomass yield (kg/ha) -----------------------------VS
S
MS
mS
vmS
VS+S VS...MS VS...mS
6000 11000
5568
0 12447
8975
5171
1718
12194
8941
6151
0 12036
8347
5588
2175
14550 11515
8814
0 14590 10170
6124
2123
0
0
0
0
0
0
0
0
13263 10635
8654
0 13221 10222
6415
2392
13693 10142
7042
0 13694
9396
5462
1856
0
0
0
0
0
0
0
0
14000 11833 10307
0 14004 10008
5879
1942
0
0
7125
0
0
0
7570
2601
0
0
0
0
0
0
0
2980
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
8200
5206
0
0
8178
5017
2077
0
0
0
0
0
0
0
0
12571 10282
6383
0 12435
9941
5270
1679
0
0
0
0
0
0
0
0
12321
9172
6769
0 12216
9004
5748
2202
0
8500
5164
0
0
8516
5128
2769
0
0
7667
0
0
0
7059
2315
12750
9100
6649
0 12535
9031
5411
1903
0
0
0
0
0
0
0
3172
0
8161
5718
0
0
8144
5520
2366
0
8898
5465
0
0
8895
5200
2757
0
0
5128
0
0
0
5132
2555
0
0
0
0
0
0
0
0
12358 10143
7695
0 12385
9425
5653
1685
0
0
3000
0
0
0
7545
3181
0
0
7000
0
0
0
7601
3112
0
0
0
0
0
0
0
3315
12200
9450
7036
0 12145
8491
5612
2329
0
0
0
0
0
0
0
0
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used (short rotation coppice systems): VS conditions: shoots+twigs+leaves/stool+roots, 60/40; S and MS: 50/50; mS and VmS: 40/60
7307 17056
6798 #DIV/0!
7030 17056
13464
13217
13326
9649
9407
9530
5778
5443
5589
1938
2180
2077
0
0
0
0
17762
18190
17845
0
0
18409
18028
18242
18458
18484
18002
17941
17043
0
0
0
19143
19065
18500
0
0
0
0
0
17020
0
0
0
0
13300
12967
15720
14686
14660
13800
14328
14317
14151
14086
14543
13821
14068
14115
13579
13146
13222
0
14669
14918
14560
0
13849
13276
0
0
14020
0
0
0
0
9764
9451
11287
10511
10636
9146
10322
10226
10117
10018
10331
9862
9923
9977
9971
9731
10495
0
10797
10675
10412
10015
9946
9838
9021
8375
10048
0
0
6492
6617
6762
6305
6843
6688
6518
5684
5507
6103
6580
6038
6416
5926
5867
5919
6073
5918
6515
0
6621
6500
6719
5594
6600
5743
5116
4807
6076
5391
0
2164
2206
2254
2231
2274
2246
2169
1919
2119
0
2268
2094
2248
1979
1944
1966
2195
2241
2206
0
2229
2179
2312
2100
2295
1933
1691
1716
2230
2208
0
18192
14338
10253
6364
2215
APPENDIX II
Table A3 PRODUCTION POTENTIALS FOR BIOMASS PLANTATIONS WITH WILLOW ( Salix viminalis ) - ACCESSIBLE AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
63130
0
0
0
0
0
0
0
46
63084
0
0
1
0
0
0
1
146
2025
6095
17955
3365
4763
165068
10428
5573
6018
2848
4775
22535
51955
0
0
549
112
6
1
0
245
543
15
0
0
573
0
0
2011
495
52
4
0
910
1199
51
2
0
2747
0
230
2741
779
115
1263
75
1650
1944
88
21
1
4558
0
0
0
0
1
0
0
0
0
1
0
0
12
0
0
549
112
5
1
0
245
543
14
0
0
561
0
0
1462
383
46
3
0
665
656
36
2
0
2174
0
230
730
284
63
1259
75
740
745
37
19
1
1811
0
524
341
151
65
2375
93
243
249
39
49
1
476
2025
4848
14873
2434
4582
161429
10260
3679
3824
2720
4706
22533
46921
0
0
8036
1370
85
9
0
3165
7321
203
0
0
8375
0
0
23504
4912
578
38
0
9578
13745
559
12
0
31607
0
1581
28069
6609
1005
6437
393
13768
18136
799
122
6
43432
303403
2044
7471
13465
14
2030
5427
5994
4606
284834
28564
84533
Krasnodar Kray
12
6715
Stavropol Kray
12
5428
Arkhangelsk oblast
12
14210
Astrakhan oblast
12
2923
Belgorod oblast
12
2248
Bryansk oblast
12
3095
Vladimir oblast
12
2510
Volgograd oblast
12
9108
Vologda oblast
12
9155
Voronezh oblast
12
4550
Nizhni Novgorod oblast12
6403
Nenets a.okr.
12
2583
Ivanovo oblast
12
1875
Kaliningrad oblast
12
1183
Tver oblast
12
6128
Kaluga oblast
12
2445
Kirov oblast
12
8750
Kostroma oblast
12
4263
Samara oblast
12
4408
Kursk oblast
12
2623
Komi-Permyak a.okr. 12
2220
Leningrad oblast
12
5678
Lipetsk oblast
12
2140
Moscow oblast
12
4130
Murmansk oblast
12
4110
Novgorod oblast
12
3935
Orenburg oblast
12
8305
Oryel oblast
12
2018
Penza oblast
12
3893
Perm oblast
12
8423
Pskov oblast
12
4508
Rostov oblast
12
8245
Ryazan oblast
12
3453
Saratov oblast
12
8433
Smolensk oblast
12
4113
Tambov oblast
12
2905
Tula oblast
12
2283
Ulyanovsk oblast
12
3218
Yaroslavl oblast
12
2350
Adigei Republic
12
605
Bashkortostan Republic12
8983
Daghestn Republic
12
3843
Kabardino-Balkarian Republic
12
898
Kalmyk-Khalm-Tangch 12
Republic4735
Karelia Republic
12
9165
Komi Republic
12
14183
Mari-El Republic
12
1575
Mordovian SSR
12
2315
North-Ossetian SSR 12
608
Karachai-Cherkess Republic
12
1085
Tatarstan Republic
12
5278
Udmurt Republic
12
3425
Checheno-Ingush Republic
12
1555
25
1
0
0
3
0
0
0
0
0
41
0
0
25
10
0
0
0
0
201
0
0
140
0
0
0
0
222
0
0
12
0
150
0
0
5
201
0
2
2
0
1
10
0
0
0
18
42
35
17
0
0
10
40
4
0
0
9
116
165
0
137
0
542
0
25
185
189
151
46
38
0
699
0
49
296
322
0
288
0
663
0
43
235
0
810
0
0
16
500
0
74
9
190
3
16
0
0
0
50
136
37
21
70
84
12
589
5
94
0
194
334
207
15
1019
772
827
0
31
343
532
310
251
258
144
1057
101
741
740
433
0
515
60
901
550
308
596
151
1070
79
0
1110
624
121
263
189
969
31
33
0
59
19
88
362
46
22
536
239
74
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
13
5
0
0
2
13
1
0
0
3
0
0
0
0
0
41
0
0
25
10
0
0
0
0
201
0
0
140
0
0
0
0
222
0
0
12
0
150
0
0
5
201
0
2
2
0
1
8
0
0
0
18
42
22
12
0
0
8
15
3
0
0
6
116
165
0
137
0
501
0
25
160
179
151
46
38
0
498
0
49
156
322
0
288
0
441
0
43
223
0
660
0
0
11
299
0
72
7
190
2
6
0
0
0
32
94
2
4
70
84
2
549
1
94
0
185
218
42
15
882
772
285
0
6
158
343
159
205
220
144
358
101
692
444
111
0
227
60
238
550
265
361
151
260
79
0
1094
124
121
189
180
779
28
17
0
59
19
38
226
9
1
466
155
62
259
13
16
0
314
74
0
9
75
269
57
0
0
17
30
0
148
42
292
196
25
459
187
0
0
164
142
5
830
168
103
88
16
137
24
318
0
504
13
56
967
43
17
0
29
2
19
289
8
0
427
39
50
5862
5410
14085
2922
1739
2686
2303
9084
8061
3509
5519
2582
1844
824
5566
2135
8351
3962
3971
1370
2093
4478
1213
3697
4110
3257
8102
1111
2512
7947
3808
8006
2366
8217
4089
1477
1659
2592
2073
360
7046
3762
848
4735
9074
14161
1469
1664
554
1062
4315
3147
1432
403
9
0
0
36
0
0
0
0
0
556
0
0
360
126
0
2
0
0
2693
0
0
1805
0
0
0
0
3072
0
0
151
0
1917
0
0
59
2831
0
24
26
3
13
141
0
0
0
254
511
516
255
0
0
132
553
36
0
0
91
1176
1563
0
1190
0
5316
0
231
2017
1785
1487
491
359
0
7523
0
426
3289
3088
0
2667
0
7506
0
413
2211
0
8357
0
0
181
5827
0
684
97
1768
30
201
0
0
0
598
1494
537
298
714
780
155
FSU REPUBLICS
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
0
0 1000
0
0
0 6961 3206
0
0
0
0
11
0
0
0
0
19
0
0
198
0
0
8036
1370
74
9
0
3165
7321
184
0
0
8177
0
0
15468
3542
493
29
0
6413
6424
356
12
0
23232
0
1581
4565
1697
427
6399
393
4190
4391
240
110
6
11825
0
1212
699
334
151
4076
165
495
502
88
98
2
1058
120357
228
28336
55969
35824
8880
13975 11315
4585
41
479
0
1231
2526
1791
89
5895
4777
6982
0
264
2995
3704
2436
1612
1592
844
9640
534
4062
5910
3728
0
3924
316
8958
3154
1899
4174
928
9868
474
0
6650
6567
705
1725
1417
6046
188
313
0
291
98
837
2831
593
302
3347
1643
562
212
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
30
0
0
0
0
0
227
91
0
0
28
191
9
0
0
36
0
0
0
0
0
556
0
0
360
126
0
2
0
0
2693
0
0
1805
0
0
0
0
3072
0
0
151
0
1917
0
0
59
2831
0
24
26
3
11
111
0
0
0
254
511
289
164
0
0
104
150
27
0
0
55
1176
1563
0
1190
0
4760
0
231
1657
1659
1487
489
359
0
4830
0
426
1484
3088
0
2667
0
4434
0
413
2060
0
6440
0
0
122
2996
0
660
71
1765
17
60
0
0
0
344
983
21
43
714
780
23
4032
5
479
0
1140
1350
228
89
4705
4777
1666
0
33
978
1919
949
1121
1233
844
2117
534
3636
2621
640
0
1257
316
1452
3154
1486
1963
928
1511
474
0
6469
740
705
1041
1320
4278
158
112
0
291
98
239
1337
56
4
2633
863
407
637
29
28
0
644
156
0
16
163
552
115
0
0
34
65
0
288
80
540
388
52
819
364
0
0
308
248
10
1583
345
191
195
32
270
47
626
0
957
26
138
1758
86
37
0
57
4
43
547
18
1
790
86
109
16120
9000
0
0
12000
0
0
0
0
0
13561
0
0
14400
12600
0
2000
0
0
13398
0
0
12893
0
0
0
0
13838
0
0
12583
0
12780
0
0
11800
14085
0
12000
13000
3000
13000
14100
0
0
0
14111
12167
14743
15000
0
0
13200
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used (short rotation coppice systems): VS conditions: 60/40; S and MS: 50/50; mS and VmS: 40/60.
0
0
14638
12232
14167
9000
0
12918
13483
13533
0
0
14616
0
0
0
0
0
0 6874
0
0 9602
11688 10240
0 14646 10577
9923 8484
0 12190 9239
11115 8739 18529 15248 10657
9500 5097
0 12217 8967
0 5240
0
0
0
10525 8344
0 12903 9644
11464 9329
0 13485 9793
10961 9080 16028 13205 9971
6000 5810
0
0 8023
0 6000
0
0
0
11506 9529 16049 14579 10688
0
6867
6256
5982
6757
5084
5251
5660
5894
6425
5850
6455
6528
0
2313
2050
2205
2320
1716
1771
2033
2014
2258
2008
2130
2222
8939 16286 13959 10313
5977
1928
13825 7784 18305 14301 10068
9000 8200
0 14583 10235
0 5096
0
0
0
0
0
0
0
0
10111 6345
0 12429 8884
10138 7563
0
0 10144
9473 8652
0
0 9451
0 5933
0
0
0
8686 5785
0
0 8671
0 6188
0
0
0
9808 8443
0 13577 9505
0
0
0
0
0
9240 8516
0
0 9285
10903 8732
0 14341 10386
9444 6962
0 12427 9292
9848 7858
0
0 9847
10674 6422
0 13279 10541
9447 6171
0
0 9445
0 5861
0
0
0
10763 9120
0 13395 9698
0 5287
0
0
0
8694 5482
0
0 8719
11111 7986
0 12925 9503
9590 8610
0
0 9594
0
0
0
0
0
9260 7619
0
0 9275
0 5267
0
0
0
11321 9942
0 13820 10050
0 5735
0
0
0
9605 6166
0
0 9604
9409 7003
0 12815 9254
0 6146
0
0
0
10317 9222
0 12766 9757
0 6000
0
0
0
0
0
0
0
0
11313 5991
0 12075 10993
11654 10524
0 14087 10024
0 5826
0
0
0
9243 6559
0 12453 9125
10778 7497
0 13724 9997
9305 6239
0 12352 9265
10000 6065 17097 14048 10296
12563 9485 16646 13347 10782
0
0
0
0
0
0 4932
0
0
0
0 5158
0
0
0
11960 9511
0 13767 10896
10985 7820
0 12288 10425
14514 12891 17137 13430 10791
14190 13727 16785 13226 10588
10200 6244
0
0 10223
9286 6874
0
0 9274
12917 7595 17181 13875 10783
7349
6335
5094
0
6169
6178
5505
5897
5337
6189
5840
0
5595
6209
5586
5972
5475
5612
5861
5913
5267
5252
5902
5780
0
5551
5224
6106
5731
5617
5431
6136
5814
5977
0
5913
5982
5810
5507
7337
5494
5651
6556
0
4908
5117
6367
5918
6478
6193
5654
5578
6578
2456
2195
1703
0
2050
2103
0
1823
2160
2047
2032
0
0
2066
2182
0
1949
1879
1847
1984
2064
1786
1951
1869
0
1879
1744
1950
1908
2059
1848
2227
2014
1977
2005
1970
0
1897
1959
2459
1818
1997
2187
0
1954
1689
2286
1893
2160
2072
1851
2195
2191
APPENDIX II
Table A3 PRODUCTION POTENTIALS FOR BIOMASS PLANTATIONS WITH WILLOW ( Salix viminalis ) - ACCESSIBLE AREAS
ADM REG NAME
197
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Chuvash Republic
12
Altai Kray
12
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
1678
0
5
21
0
0
5
16
92
1565
0
57
156
0
0
57
99
174
11538
486
1036
2075
0
486
550
1039
342
9120
6202
11601
17158
0
6202
5399
5557
684
2693
0
3
36
0
0
3
33
16
2640
6
33
203
0
6
27
170
28
16560
26
157
819
0
26
131
662
687
15055
309
1404
5094
0
309
1095
3690
1502
7290
68
229
453
0
68
161
224
93
6744
988
2625
3996
0
988
1637
1371
199
2848
0
0
0
0
0
0
0
0
2847
0
0
0
0
0
0
0
0
9013
45
250
429
0
45
205
179
76
8505
601
2600
3671
0
601
1999
1071
169
9438
142
630
1543
0
142
488
913
653
7241
1951
6659
11796
0
1951
4708
5137
1245
6140
0
0
0
0
0
0
0
0
6140
0
0
0
0
0
0
0
0
1545
189
408
534
0
189
219
126
29
982
2651
4839
5575
0
2651
2188
736
54
17280
0
0
7
0
0
0
7
12
17261
0
0
54
0
0
0
54
32
1180
0
0
0
0
0
0
0
0
1180
0
0
0
0
0
0
0
0
3853
0
0
0
0
0
0
0
0
3852
0
0
0
0
0
0
0
0
5013
0
0
0
0
0
0
0
0
5012
0
0
0
0
0
0
0
0
5290
0
15
280
0
0
15
265
210
4800
0
121
1454
0
0
121
1333
446
8158
0
0
0
0
0
0
0
0
8155
0
0
0
0
0
0
0
0
5195
30
217
940
0
30
187
723
680
3575
368
2226
6026
0
368
1858
3800
1142
9245
0
0
0
0
0
0
0
0
9245
0
0
0
0
0
0
0
0
9910
32
678
1691
0
32
646
1013
732
7487
387
6195
12056
0
387
5808
5861
1542
8545
0
17
1549
0
0
17
1532
582
6413
0
147
8047
0
0
147
7900
1626
4795
0
0
3
0
0
0
3
13
4776
0
0
22
0
0
0
22
31
12618
16
665
1813
0
16
649
1148
444
10361
204
6060
12344
0
204
5856
6284
844
663
0
0
0
0
0
0
0
4
658
0
0
0
0
0
0
0
13
7415
0
55
795
0
0
55
740
474
6146
0
447
4638
0
0
447
4191
1096
7043
0
118
872
0
0
118
754
755
5416
0
1059
5140
0
0
1059
4081
2130
6830
0
0
34
0
0
0
34
51
6745
0
0
202
0
0
0
202
132
2680
0
0
0
0
0
0
0
0
2680
0
0
0
0
0
0
0
0
6338
62
270
580
0
62
208
310
781
4977
765
2731
4486
0
765
1966
1755
1318
7850
0
0
0
0
0
0
0
93
7757
0
0
0
0
0
0
0
298
6650
0
0
1
0
0
0
1
16
6633
0
0
6
0
0
0
6
50
5043
0
0
0
0
0
0
0
7
5035
0
0
0
0
0
0
0
24
3093
5
18
50
0
5
13
32
14
3029
61
175
353
0
61
114
178
32
46970
0
0
0
0
0
0
0
0
46970
0
0
0
0
0
0
0
0
244894
258722
503616
1173
1101
2274
6275
4766
11041
18033
14504
32537
34
0
34
1139
1101
2240
5102
3665
8767
11758
9738
21496
7032
6764
13796
219786
237437
457223
15895
14493
30388
65196
48922
114118
133683
102321
236004
590
0
590
15305
14493
29798
49301
34429
83730
68487
53399
121886
13656
14637
28293
1385
863
13455
8953
10518
10775
11258
14803
26983
370
5798
5938
9145
10700
9940
11740
8395
12815
15593
700
26720
8415
23453
56150
8803
15968
2450
32755
29875
21850
0
0
0
0
0
167
1239
98
8
90
206
2175
380
1710
141
749
612
52
132
86
0
343
230
61
0
0
0
0
0
1
0
0
0
0
0
1
341
2095
203
35
294
312
3385
707
2883
515
1368
1582
147
273
356
0
816
595
124
0
2
2
0
0
3
0
0
40
180
1302
123
1499
3244
605
502
1021
312
3620
841
3311
830
1489
2115
233
380
511
0
1072
607
140
116
47
17
37
0
4
1
0
0
0
0
0
12
417
10
0
0
103
1003
123
709
1
289
41
1
0
0
0
79
8
3
0
0
0
0
0
0
0
0
0
0
0
0
155
822
88
8
90
103
1172
257
1001
140
460
571
51
132
86
0
264
222
58
0
0
0
0
0
1
0
0
0
0
0
1
174
856
105
27
204
106
1210
327
1173
374
619
970
95
141
270
0
473
365
63
0
2
2
0
0
2
0
0
40
180
1302
122
1158
1149
402
467
727
0
235
134
428
315
121
533
86
107
155
0
256
12
16
116
45
15
37
0
1
1
0
43
194
1365
442
1192
907
401
104
139
0
80
37
76
127
10
65
29
22
61
0
122
0
33
136
457
47
48
2
1
3
0
1302
488
10787
8386
7826
6625
10251
14196
25822
57
2094
5061
5758
9743
8441
9560
8132
12413
15021
700
25526
7808
23279
55898
8298
15903
2365
32753
29870
21846
0
0
0
1
4
2644
19631
1465
114
1286
3376
34731
5862
27656
1957
11665
8798
711
1731
1139
0
5415
3473
887
0
3
3
0
0
14
0
0
0
0
5
18
4604
28613
2587
363
3396
4464
47006
9138
39797
5641
17803
18458
1659
3101
3994
0
10521
7377
1545
2
24
25
0
0
30
0
0
257
1191
8814
787
12534
36296
5211
3034
7369
4466
48567
9948
42557
7503
18512
21609
2185
3733
5003
0
12213
7453
1652
639
322
113
192
2
38
3
0
0
0
0
0
212
7580
170
0
0
1897
18092
2252
13075
22
5204
738
22
0
0
0
1516
158
47
0
0
0
0
0
2
0
0
0
0
1
4
2432
12051
1295
114
1286
1479
16639
3610
14581
1935
6461
8060
689
1731
1139
0
3899
3315
840
0
3
3
0
0
12
0
0
0
0
4
14
1960
8982
1122
249
2110
1088
12275
3276
12141
3684
6138
9660
948
1370
2855
0
5106
3904
658
2
21
22
0
0
16
0
0
257
1191
8809
769
7930
7683
2624
2671
3973
2
1561
810
2760
1862
709
3151
526
632
1009
0
1692
76
107
637
298
88
192
2
8
3
0
93
428
3078
990
2712
2037
870
200
294
0
182
77
171
251
20
129
63
50
135
0
270
0
77
276
1051
93
82
3
2
7
0
416566
8480
16039
24199
2799
5681
7559
8160
6143
386209
132566
210171
262203
50987
81579
77605
52032
13641
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used (short rotation coppice systems): VS conditions: 60/40; S and MS: 50/50; mS and VmS: 40/60.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
0 11400 7429
0
0 12194 6093 1901
12761 11198 8269
0 12754 9809 5346 2003
6000 11000 5639
0 12447 8975 5198 1727
11885 8943 6220
0 12043 8384 5578 2186
14529 11463 8821
0 14439 10165 6134 2143
0
0
0
0
0
0
0
0
13356 10400 8557
0 13375 9735 5984 2229
13739 10570 7645
0 13744 9639 5624 1906
0
0
0
0
0
0
0
0
14026 11860 10440
0 14051 9995 5844 1866
0
0 7714
0
0
0 7559 2599
0
0
0
0
0
0
0 2980
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 8067 5193
0
0 8152 5028 2118
0
0
0
0
0
0
0
0
12267 10258 6411
0 12434 9941 5252 1680
0
0
0
0
0
0
0
0
12094 9137 7130
0 12210 8985 5784 2107
0 8647 5195
0
0 8497 5155 2794
0
0 7333
0
0
0 7051 2303
12750 9113 6809
0 12535 9024 5475 1903
0
0
0
0
0
0
0 3162
0 8127 5834
0
0 8144 5665 2312
0 8975 5894
0
0 9011 5413 2822
0
0 5941
0
0
0 5890 2599
0
0
0
0
0
0
0
0
12339 10115 7734
0 12409 9453 5652 1688
0
0
0
0
0
0 7090 3195
0
0 6000
0
0
0 7646 3114
0
0
0
0
0
0
0 3300
12200 9722 7060
0 12145 8501 5646 2362
0
0
0
0
0
0
0
0
13551 10390
13163 10265
13363 10336
9663
9394
9551
5825
5484
5670
1942
2164
2051
0
0
9959
9611
11260
10493
10678
9154
10363
10228
10148
10026
10352
9849
9918
9958
9970
9741
10576
0
10802
10706
10387
9363
10219
9876
0
0
10093
0
0
6489
6614
6764
6292
6847
6689
6522
5720
5461
6104
6632
6055
6443
5919
5863
5912
6079
5917
6514
0
6598
6470
6803
5496
6588
5833
5162
4957
6152
5324
0
2163
2205
2254
2237
2275
2247
2168
1928
2117
0
2269
2105
2251
1979
1943
1971
2196
2236
2207
0
2217
0
2309
2032
2300
1964
1699
1726
2254
2227
0
15633 13104 10835 18216 14360 10267
6376
2221
0
0
1000
4000
15832
15844
14949
14250
14289
16388
15968
15426
16173
13879
15574
14376
13673
13114
13244
0
15787
15100
14541
0
3000
3000
0
0
14000
0
0
0
0
5000
18000
13501
13658
12744
10371
11551
14308
13887
12925
13804
10953
13014
11668
11286
11359
11219
0
12893
12398
12460
2000
12000
12500
0
0
10000
0
0
7413 17353 13437
7055 #DIV/0! 13163
7253 17353 13303
6425
6617
6770
6398
8362
11189
8613
6044
7217
14314
13416
11829
12853
9040
12433
10217
9378
9824
9791
0
11393
12278
11800
5509
6851
6647
5189
2000
9500
3000
0
0
0
0
0
17757
18174
17840
0
0
18413
18030
18256
18448
18415
18003
17959
17056
0
0
0
19149
19065
18569
0
0
0
0
0
17020
0
0
0
0
13295
13114
15649
14658
14723
13800
14247
14320
14191
14074
14566
13799
14054
14124
13533
13132
13289
0
14755
14939
14480
0
14077
13383
0
0
13735
0
0
APPENDIX II
Table A4 PRODUCTION POTENTIALS FOR BIOMASS PLANTATIONS WITH WILLOW ( Salix viminalis ) - ACCESSIBLE AREAS, EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
62805
0
0
0
0
0
0
0
46
62759
1448
4205
6503
1303
3013
134203
8128
1875
3013
93
3495
20363
5253
0
0
184
74
1
1
0
91
176
1
0
0
77
0
0
866
240
16
4
0
310
396
2
1
0
407
0
123
1130
357
35
410
16
534
795
3
10
1
603
192895
605
2242
Krasnodar Kray
12
1820
Stavropol Kray
12
805
Arkhangelsk oblast
12
13708
Astrakhan oblast
12
2853
Belgorod oblast
12
73
Bryansk oblast
12
638
Vladimir oblast
12
1008
Volgograd oblast
12
1703
Vologda oblast
12
7900
Voronezh oblast
12
473
Nizhni Novgorod oblast12
3318
Nenets a.okr.
12
2583
Ivanovo oblast
12
848
Kaliningrad oblast
12
145
Tver oblast
12
2598
Kaluga oblast
12
1038
Kirov oblast
12
5758
Kostroma oblast
12
3273
Samara oblast
12
370
Kursk oblast
12
80
Komi-Permyak a.okr. 12
1838
Leningrad oblast
12
4743
Lipetsk oblast
12
80
Moscow oblast
12
2008
Murmansk oblast
12
3965
Novgorod oblast
12
3273
Orenburg oblast
12
1840
Oryel oblast
12
53
Penza oblast
12
575
Perm oblast
12
5435
Pskov oblast
12
2258
Rostov oblast
12
313
Ryazan oblast
12
1050
Saratov oblast
12
845
Smolensk oblast
12
563
Tambov oblast
12
255
Tula oblast
12
213
Ulyanovsk oblast
12
780
Yaroslavl oblast
12
850
Adigei Republic
12
225
Bashkortostan Republic12
3123
Daghestn Republic
12
3370
Kabardino-Balkarian Republic
12
555
Kalmyk-Khalm-Tangch Republic
12
3825
Karelia Republic
12
8518
Komi Republic
12
14183
Mari-El Republic
12
943
Mordovian SSR
12
593
North-Ossetian SSR 12
405
Karachai-Cherkess Republic
12
895
Tatarstan Republic
12
540
Udmurt Republic
12
1400
Checheno-Ingush Republic
12
1028
Chuvash Republic
12
643
Altai Kray
12
6125
14
1
0
0
0
0
0
0
0
0
29
0
0
9
2
0
0
0
0
7
0
0
3
0
0
0
0
2
0
0
5
0
0
0
0
0
1
0
1
2
0
1
10
0
0
0
14
12
21
14
0
0
10
0
170
26
4
0
0
0
3
86
0
101
0
153
0
6
36
58
12
30
23
0
26
0
39
6
134
0
238
0
8
0
16
126
0
161
0
0
0
9
0
20
9
23
3
16
0
0
0
38
32
22
18
3
16
12
2
434
FSU REPUBLICS
Average annual biomass increments (000tons) ---------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
0
0
1
0
0
0
1
146
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
184
74
1
1
0
91
176
1
0
0
76
0
0
682
166
15
3
0
219
220
1
1
0
330
0
123
264
117
19
406
16
224
399
1
9
1
196
0
242
65
82
21
920
15
74
144
2
18
1
30
1447
3472
5307
864
2957
132872
8096
1267
2074
88
3468
20361
4619
0
0
2693
896
10
9
0
1187
2372
10
0
0
1154
0
0
9951
2442
170
37
0
3301
4521
23
5
0
4733
0
834
11613
3148
305
2109
83
4573
6869
32
54
6
6008
0
0
0
0
2
0
0
0
0
0
0
0
21
0
0
2693
896
8
9
0
1187
2372
10
0
0
1133
0
0
7258
1546
160
28
0
2114
2149
13
5
0
3579
0
834
1662
706
135
2072
83
1272
2348
9
49
6
1275
0
549
135
176
50
1578
28
152
287
4
36
2
65
4017
1
604
1637
1775
1614
186892
8331
25183
104
4
77
0
5
43
96
0
839
59
205
0
8
60
192
63
202
191
21
36
87
652
15
153
0
432
1
16
43
155
405
0
186
6
0
51
19
30
83
13
98
24
16
0
52
19
66
62
24
19
54
39
18
11
1043
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
9
4
0
0
2
0
0
8
1
0
0
0
0
0
0
0
0
29
0
0
9
2
0
0
0
0
7
0
0
3
0
0
0
0
2
0
0
5
0
0
0
0
0
1
0
1
2
0
1
8
0
0
0
14
12
12
10
0
0
8
0
170
12
3
0
0
0
3
86
0
101
0
124
0
6
27
56
12
30
23
0
19
0
39
3
134
0
238
0
6
0
16
121
0
161
0
0
0
8
0
19
7
23
2
6
0
0
0
24
20
1
4
3
16
2
2
264
78
0
77
0
5
40
10
0
738
59
52
0
2
24
134
51
172
168
21
10
87
613
9
19
0
194
1
8
43
139
279
0
25
6
0
51
10
30
63
4
75
21
0
0
52
19
28
30
2
1
51
23
6
9
609
82
3
14
0
10
2
0
0
56
19
10
0
0
2
6
0
95
38
52
1
25
362
3
0
0
147
2
0
99
73
90
0
0
10
2
17
0
134
2
2
110
32
0
0
26
2
14
38
2
0
35
10
8
31
224
1634
799
13602
2852
57
592
912
1702
7004
394
3102
2582
840
84
2400
975
5460
3044
297
43
1725
3728
62
1854
3965
2694
1837
35
433
5208
1763
312
863
830
560
186
194
616
766
210
2914
3307
539
3825
8437
14161
863
492
378
876
452
1351
1002
601
4858
229
9
0
0
0
0
0
0
0
0
395
0
0
125
24
0
0
0
0
88
0
0
38
0
0
0
0
35
0
0
63
0
0
0
0
0
9
0
7
26
0
13
141
0
0
0
190
153
318
195
0
0
132
0
2177
347
35
0
0
0
34
821
0
874
0
1595
0
52
402
542
122
313
216
0
275
0
345
70
1285
0
2189
0
100
0
152
1173
0
1577
0
0
0
84
0
178
97
216
30
201
0
0
0
457
349
324
237
28
164
155
26
4821
35634
23
8308
16852
10451
3062
906
36
390
0
33
284
876
0
4791
372
1906
0
61
547
1281
426
1239
1154
123
336
461
3561
122
1395
0
3254
4
150
245
934
2673
3
1722
35
0
300
144
174
522
122
627
150
204
0
255
98
635
527
339
241
316
300
195
79
8114
111
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
30
0
0
0
0
0
153
65
0
0
28
0
0
118
9
0
0
0
0
0
0
0
0
395
0
0
125
24
0
0
0
0
88
0
0
38
0
0
0
0
35
0
0
63
0
0
0
0
0
9
0
7
26
0
11
111
0
0
0
190
153
165
130
0
0
104
0
2177
118
26
0
0
0
34
821
0
874
0
1200
0
52
277
518
122
313
216
0
187
0
345
32
1285
0
2189
0
65
0
152
1110
0
1577
0
0
0
75
0
171
71
216
17
60
0
0
0
267
196
6
42
28
164
23
26
2644
559
1
390
0
33
250
55
0
3917
372
311
0
9
145
739
304
926
938
123
61
461
3216
52
110
0
1065
4
50
245
782
1500
3
145
35
0
300
60
174
344
25
411
120
3
0
255
98
178
178
15
4
288
136
40
53
3293
201
7
23
0
20
4
0
0
120
40
21
0
0
4
12
0
184
71
93
2
52
646
6
0
0
272
3
0
188
164
165
0
1
19
4
34
0
252
3
6
200
65
1
0
50
4
32
71
5
1
64
22
19
59
442
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
0
0
1000
0
0
0
6961
3205
0
0
14636
12108
10000
9000
0
13044
13477
10000
0
0
14987
0
0
0
0
0
0
6780
0
0
9602
11491 10277
0 14667 10643
10175
8818
0 12130
9324
10625
8714 19111 14041 10982
9250
5144
0 12215
8977
0
5188
0
0
0
10648
8564
0 13022
9665
11417
8640
0 13471
9781
11500 10667 16377 15410 11041
5000
5400
0
0
8039
0
6000
0
0
0
11629
9964 15931 14931 10843
13770 11232
16357
9000
0
0
0
0
0
0
0
0
13621
0
0
13889
12000
0
0
0
0
12571
0
0
12667
0
0
0
0
17500
0
0
12600
0
0
0
0
0
9000
0
7000
13000
0
13000
14100
0
0
0
13571
12750
15143
13929
0
0
13200
0
12806
13346
8750
0
0
0
11333
9547
0
8653
0
10425
0
8667
11167
9345
10167
10433
9391
0
10577
0
8846
11667
9590
0
9197
0
12500
0
9500
9310
0
9795
0
0
0
9333
0
8900
10778
9391
10000
12563
0
0
0
12026
10906
14727
13167
9333
10250
12917
13000
11108
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used (short rotation coppice systems): VS conditions: shoots+twigs+leaves/stool+roots, 60/40; S and MS: 50/50; mS and VmS: 40/60.
8871 23000 13755 10294
8712
9000
5065
0
6600
6605
9125
0
5710
6305
9298
0
7625
9117
6672
6762
6134
6042
5857
9333
5299
5462
8133
9118
0
7532
4000
9375
5698
6026
6600
3000
9258
5833
0
5882
7579
5800
6289
9385
6398
6250
12750
0
4904
5158
9621
8500
14125
12684
5852
7692
10833
7182
7779
19613
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17097
16646
0
0
0
0
0
17124
16753
0
0
17181
0
0
14655
14583
0
0
0
0
0
0
0
0
13649
0
0
14316
12408
0
0
0
0
13409
0
0
13147
0
0
0
0
14258
0
0
12699
0
0
0
0
0
13760
0
12464
13724
0
14048
13347
0
0
0
13768
12250
13315
13263
0
0
13875
0
12832
9996
10271
0
0
0
10327
9544
0
8630
0
9708
0
9415
10314
9186
9874
10337
9296
0
9774
0
8734
9340
9595
0
9213
0
10155
0
9704
9162
0
9795
0
0
0
9929
0
9012
9997
9331
10308
10782
0
0
0
10918
9813
10655
10582
11011
10030
10783
12181
10001
0
6777
6288
6039
6931
5099
5287
5689
5881
6648
5674
6455
6497
0
2270
2059
2136
2360
1714
1831
2049
1995
2283
2021
2130
2188
5888
1897
7165
6144
5093
0
6159
6201
5544
0
5309
6256
5929
0
5627
6170
5532
6015
5387
5594
5819
5946
5283
5246
5791
5716
0
5494
5011
6087
5704
5644
5383
6197
5772
6016
0
5830
6013
5759
5456
6543
5480
5688
6353
0
4908
5117
6422
5867
6468
6193
5686
5898
6534
6010
5409
2439
2231
1702
0
2048
2112
0
0
2122
2072
2034
0
0
2062
2211
0
1936
1857
1777
2003
2064
1786
1932
1860
0
1850
1641
0
1901
2254
1828
2061
2359
1988
1997
1953
0
1888
1903
2451
1811
2001
2178
0
1895
1689
2327
1893
2158
2017
1827
2246
2202
1908
1972
APPENDIX II
Table A4 PRODUCTION POTENTIALS FOR BIOMASS PLANTATIONS WITH WILLOW ( Salix viminalis ) - ACCESSIBLE AREAS, EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
2668
0
3
36
0
0
3
33
16
2615
13728
19
78
433
0
19
59
355
393
12902
6520
59
205
412
0
59
146
207
87
6021
2825
0
0
0
0
0
0
0
0
2825
8873
40
216
386
0
40
176
170
74
8409
8108
78
423
1190
0
78
345
767
591
6327
6128
0
0
0
0
0
0
0
0
6127
1450
163
354
471
0
163
191
117
29
949
16035
0
0
7
0
0
0
7
10
16018
693
0
0
0
0
0
0
0
0
692
3853
0
0
0
0
0
0
0
0
3852
5010
0
0
0
0
0
0
0
0
5010
3498
0
3
134
0
0
3
131
107
3256
8158
0
0
0
0
0
0
0
0
8155
2403
2
26
321
0
2
24
295
317
1765
9245
0
0
0
0
0
0
0
0
9245
6220
4
180
739
0
4
176
559
473
5008
5035
0
16
396
0
0
16
380
412
4228
4760
0
0
3
0
0
0
3
13
4741
10428
1
323
1085
0
1
322
762
293
9049
630
0
0
0
0
0
0
0
4
626
6968
0
48
717
0
0
48
669
415
5836
4585
0
67
651
0
0
67
584
467
3468
6780
0
0
31
0
0
0
31
50
6700
2678
0
0
0
0
0
0
0
0
2677
2578
10
45
100
0
10
35
55
165
2312
7260
0
0
0
0
0
0
0
80
7180
6045
0
0
0
0
0
0
0
10
6035
4778
0
0
0
0
0
0
0
6
4772
2370
0
3
20
0
0
3
17
7
2344
46870
0
0
0
0
0
0
0
0
46870
Average annual biomass increments (000tons) ---------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
6
33
202
0
6
27
169
28
224
730
2737
0
224
506
2007
847
847
2323
3588
0
847
1476
1265
188
0
0
0
0
0
0
0
0
536
2258
3277
0
536
1722
1019
165
1069
4332
8574
0
1069
3263
4242
1110
0
0
0
0
0
0
0
0
2281
4181
4863
0
2281
1900
682
54
0
0
51
0
0
0
51
27
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
28
674
0
0
28
646
210
0
0
0
0
0
0
0
0
26
258
1752
0
26
232
1494
529
0
0
0
0
0
0
0
0
46
1633
5063
0
46
1587
3430
1037
0
132
2357
0
0
132
2225
1120
0
0
22
0
0
0
22
31
9
2894
7030
0
9
2885
4136
566
0
0
0
0
0
0
0
12
0
388
4162
0
0
388
3774
961
0
583
3739
0
0
583
3156
1333
0
0
180
0
0
0
180
129
0
0
0
0
0
0
0
0
123
499
811
0
123
376
312
276
0
0
0
0
0
0
0
256
0
0
1
0
0
0
1
33
0
0
0
0
0
0
0
19
0
28
109
0
0
28
81
15
0
0
0
0
0
0
0
0
122175
223305
345480
158
546
704
1515
2424
3939
5054
8175
13229
23
0
23
135
546
681
1357
1878
3235
3539
5751
9290
1666
4243
5909
115414
210872
326286
2190
7344
9534
15065
25121
40186
34548
57306
91854
389
0
389
1801
7344
9145
12875
17777
30652
19483
32185
51668
3210
9388
12598
705
70
5220
3418
1513
4635
3945
7378
15713
0
583
3165
4535
7530
7245
9118
6195
7700
11093
475
15890
5543
20278
48138
5088
11770
1600
28288
29138
20918
0
0
0
0
0
8
501
3
0
34
0
105
33
952
54
495
348
37
96
56
0
47
134
46
0
0
0
0
0
1
0
0
0
0
0
1
20
856
5
7
108
0
170
77
1565
234
865
998
103
200
236
0
108
360
92
0
2
2
0
0
3
0
0
0
1
39
7
181
1246
40
73
268
0
200
108
1800
385
937
1362
162
280
337
0
124
369
102
62
41
10
37
0
4
0
0
0
0
0
0
0
158
0
0
0
0
43
2
393
1
185
7
1
0
0
0
2
6
1
0
0
0
0
0
0
0
0
0
0
0
0
8
343
3
0
34
0
62
31
559
53
310
341
36
96
56
0
45
128
45
0
0
0
0
0
1
0
0
0
0
0
1
12
355
2
7
74
0
65
44
613
180
370
650
66
104
180
0
61
226
46
0
2
2
0
0
2
0
0
0
1
39
6
161
390
35
66
160
0
30
31
235
151
72
364
59
80
101
0
16
9
10
62
39
8
37
0
1
0
0
0
1
40
40
173
260
45
13
47
0
15
6
59
69
2
45
18
16
39
0
11
0
25
65
25
17
45
1
1
1
0
705
69
5141
3370
1159
3129
3860
7292
15398
0
367
3052
2676
7076
6306
7709
6014
7404
10716
475
15755
5173
20151
48010
5022
11743
1519
28286
29133
20916
0
0
0
1
4
114
7894
35
0
473
0
1669
466
15381
753
7686
4977
511
1264
741
0
693
2022
660
0
3
2
0
0
14
0
0
0
0
5
16
236
11634
56
59
1225
0
2342
903
21771
2535
11369
11481
1172
2269
2634
0
1338
4437
1133
2
20
19
0
0
30
0
0
0
5
267
54
1334
14258
282
415
2097
0
2543
1090
23331
3431
11794
13639
1533
2743
3294
0
1443
4493
1203
352
279
64
189
1
38
1
0
0
0
0
0
0
2847
0
0
0
0
779
39
7214
16
3330
127
19
0
0
0
42
120
14
0
0
0
0
0
2
0
0
0
0
1
4
114
5047
35
0
473
0
890
427
8167
737
4356
4850
492
1264
741
0
651
1902
646
0
3
2
0
0
12
0
0
0
0
4
12
122
3740
21
59
752
0
673
437
6390
1782
3683
6504
661
1005
1893
0
645
2415
473
2
17
17
0
0
16
0
0
0
5
262
38
1098
2624
226
356
872
0
201
187
1560
896
425
2158
361
474
660
0
105
56
70
350
259
45
189
1
8
1
0
0
2
91
91
394
586
97
25
117
0
35
13
135
137
5
90
39
35
86
0
24
0
58
146
55
33
76
2
2
3
0
286887
2950
6012
8175
799
2151
3062
2163
1079
277626
45363
76686
90173
14549
30814
31323
13487
2377
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
6000 11000
5611
0 12447
8975
5196
1726
11789
9359
6321
0 12015
8552
5656
2157
14356 11332
8709
0 14381 10126
6119
2146
0
0
0
0
0
0
0
0
13400 10454
8490
0 13392
9764
5983
2225
13705 10241
7205
0 13773
9463
5531
1877
0
0
0
0
0
0
0
0
13994 11811 10325
0 13975
9938
5815
1863
0
0
7286
0
0
0
7588
2628
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
9333
5030
0
0
8136
4946
1961
0
0
0
0
0
0
0
0
13000
9923
5458
0 12600
9806
5066
1669
0
0
0
0
0
0
0
0
11500
9072
6851
0 12147
8993
6138
2194
0
8250
5952
0
0
8498
5862
2722
0
0
7333
0
0
0
7051
2303
9000
8960
6479
0 11896
8966
5427
1931
0
0
0
0
0
0
0
3157
0
8083
5805
0
0
8121
5643
2315
0
8701
5743
0
0
8743
5404
2858
0
0
5806
0
0
0
5866
2597
0
0
0
0
0
0
0
0
12300 11089
8110
0 12303 10613
5667
1677
0
0
0
0
0
0
7090
3202
0
0
1000
0
0
0
7548
3162
0
0
0
0
0
0
0
3300
0
9333
5450
0
0
9231
4888
2128
0
0
0
0
0
0
0
0
13861
9944
13451 10363
13543 10202
9488
9466
9475
5505
5596
5562
1927
2213
2132
0
0
9959
9583
10581
10545
10263
9012
10127
0
10349
10046
10429
9884
9957
10000
9982
9702
10510
0
10617
10667
10321
9363
10192
9894
0
0
10093
0
0
0
6742
6785
6358
6826
6724
6532
5428
5448
0
6794
6073
6637
5944
5876
5932
6075
5901
6508
0
6670
6485
6774
5621
6557
5824
5169
5275
6152
5522
0
0
2247
2262
2259
2277
2254
2151
1870
2505
0
2272
2096
2278
1991
1946
1975
2201
2228
2198
0
2254
0
2309
2253
2239
1933
1704
1815
2254
1891
0
15377 12755 11030 18209 14325 10230
6235
2203
0
0
1000
4000
14250
15756
11667
0
13912
0
15895
14121
16157
13944
15527
14302
13811
13167
13232
0
14745
15090
14348
0
3000
2000
0
0
14000
0
0
0
0
5000
16000
11800
13591
11200
8429
11343
0
13776
11727
13911
10833
13143
11504
11379
11345
11161
0
12389
12325
12315
2000
10000
9500
0
0
10000
0
0
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used (short rotation coppice systems): VS conditions: shoots+twigs+leaves/stool+roots, 60/40; S and MS: 50/50; mS and VmS: 40/60.
6836 16913 13341
7010 #DIV/0! 13451
6943 16913 13429
0
5000
6846
7714
7370
11443
7050
5685
7825
0
12715
10093
12962
8912
12587
10014
9463
9796
9774
0
11637
12176
11794
5677
6805
6400
5108
1000
9500
1000
0
0
0
0
0
0
18056
0
0
0
0
17967
18456
18356
18424
18011
18019
17046
0
0
0
19189
19077
17540
0
0
0
0
0
17020
0
0
0
0
13295
13287
14878
14718
13468
12582
13998
0
14435
14000
14606
13822
14062
14201
13607
13120
13132
0
14444
14878
14456
0
14056
13337
0
0
13735
0
0
APPENDIX II
Table A5 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ALL AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha)-------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
156198
0
0
54
0
0
0
54
191
155953
Average annual biomass increments (000tons)----------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
0
0
235
0
0
0
235
510
2690
7868
20348
3938
6523
268445
19548
6313
6420
3000
9013
45390
57570
0
0
6048
567
114
5
0
831
1893
190
0
0
8732
0
0
14103
1362
191
35
4
2679
3646
276
5
0
16809
2
520
15879
1974
291
7645
198
4480
4431
394
56
9
22853
0
0
0
0
62
0
0
0
0
77
0
0
1215
0
0
6048
567
52
5
0
831
1893
113
0
0
7517
0
0
8055
795
77
30
4
1848
1753
86
5
0
8077
2
520
1776
612
100
7610
194
1801
785
118
51
9
6044
27
780
505
213
116
7285
167
429
506
257
79
7
4315
2661
6000
3964
1751
6115
253515
19182
1403
1484
2350
8878
45374
30398
0
0
87097
7056
1805
64
0
10950
25982
2706
0
0
121860
0
3
171363
14445
2618
341
35
28221
43089
3545
37
0
207474
11
3584
182486
17821
3261
39862
1309
38357
47735
4332
323
56
248112
0
0
0
0
1088
0
0
0
0
1240
0
0
19477
0
0
87097
7056
717
64
0
10950
25982
1466
0
0
102383
0
3
84266
7389
813
277
35
17271
17107
839
37
0
85614
11
3581
11123
3376
643
39521
1274
10136
4646
787
286
56
40638
50
1812
1035
455
254
12653
350
857
1015
588
154
15
9676
457066
18380
39110
58732
1354
17026
20730
19622
14686
383075
257520
471171
587249
21805
235715
213651
116078
28914
Krasnodar Kray
12
7620
Stavropol Kray
12
6635
Arkhangelsk oblast
12
38190
Astrakhan oblast
12
4598
Belgorod oblast
12
2665
Bryansk oblast
12
3483
Vladimir oblast
12
2925
Volgograd oblast
12
11265
Vologda oblast
12
14628
Voronezh oblast
12
5195
Nizhni Novgorod oblast12
7515
Nenets a.okr.
12
16858
Ivanovo oblast
12
2270
Kaliningrad oblast
12
1240
Tver oblast
12
8395
Kaluga oblast
12
2963
Kirov oblast
12
11930
Kostroma oblast
12
6000
Samara oblast
12
5118
Kursk oblast
12
3020
Komi-Permyak a.okr. 12
3280
Leningrad oblast
12
7500
Lipetsk oblast
12
2410
Moscow oblast
12
4665
Murmansk oblast
12
13960
Novgorod oblast
12
5450
Orenburg oblast
12
12418
Oryel oblast
12
2458
Penza oblast
12
4320
Perm oblast
12
12715
Pskov oblast
12
5568
Rostov oblast
12
10133
Ryazan oblast
12
3935
Saratov oblast
12
10375
Smolensk oblast
12
4943
Tambov oblast
12
3435
Tula oblast
12
2553
Ulyanovsk oblast
12
3690
Yaroslavl oblast
12
3260
Adigei Republic
12
775
Bashkortostan Republic12
14435
Daghestn Republic
12
5033
Kabardino-Balkarian Republic
12
1238
Kalmyk-Khalm-Tangch Republic
12
7510
Karelia Republic
12
18253
Komi Republic
12
41370
Mari-El Republic
12
2365
Mordovian SSR
12
2590
North-Ossetian SSR 12
778
Karachai-Cherkess Republic
12
1468
Tatarstan Republic
12
6663
Udmurt Republic
12
4150
Checheno-Ingush Republic
12
1930
Chuvash Republic
12
1808
Altai Kray
12
16653
67
2
0
0
43
653
270
0
0
6
878
0
1016
541
871
752
602
113
0
636
0
162
431
1290
0
909
0
572
15
184
1525
1
1015
0
2330
71
733
0
477
13
318
2
32
0
0
0
158
228
112
23
155
220
23
34
1260
101
7
386
0
114
2406
1858
0
3057
33
4394
0
1859
808
4235
1885
2630
1694
0
1430
474
1071
913
2832
0
3053
0
1375
175
1587
3455
2
2775
0
3746
352
1568
7
1873
24
1236
5
50
0
80
429
724
788
128
29
425
1341
29
129
2580
3623
1479
2152
0
439
2894
2188
266
8810
977
5204
0
1963
978
6878
2158
5742
4215
377
1754
1237
3476
1339
3560
0
4431
160
1541
1060
3583
4142
2058
3054
561
3826
1598
1671
196
2723
229
2732
149
235
162
316
838
1086
1200
187
56
1163
2155
327
222
5356
21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
5
0
0
0
0
0
42
6
0
0
6
0
0
46
2
0
0
43
653
270
0
0
6
878
0
1016
541
871
752
602
113
0
636
0
162
431
1290
0
909
0
572
15
184
1525
1
1015
0
2330
71
733
0
477
11
318
2
27
0
0
0
158
228
70
17
155
220
17
34
1260
34
5
386
0
71
1753
1588
0
3057
27
3516
0
843
267
3364
1133
2028
1581
0
794
474
909
482
1542
0
2144
0
803
160
1403
1930
1
1760
0
1416
281
835
7
1396
11
918
3
18
0
80
429
566
560
16
6
270
1121
6
95
1320
3522
1472
1766
0
325
488
330
266
5753
944
810
0
104
170
2643
273
3112
2521
377
324
763
2405
426
728
0
1378
160
166
885
1996
687
2056
279
561
80
1246
103
189
850
205
1496
144
185
162
236
409
362
412
59
27
738
814
298
93
2776
1154
877
1682
0
349
53
255
485
1086
808
264
0
58
18
182
50
2022
514
720
79
526
1611
230
60
0
234
435
10
1151
672
109
1708
46
808
126
783
0
781
48
97
1360
110
94
38
505
914
336
211
23
36
948
185
153
278
1601
2836
4279
34336
4597
1878
535
483
10514
4733
3410
2046
16837
249
243
1335
754
4167
1271
4021
1187
1517
2412
841
1045
13960
785
11823
907
2109
8461
1316
6366
834
9005
990
1055
881
2712
489
450
10344
4764
910
7310
17424
39619
942
1178
567
1375
4552
1811
1450
1308
9696
1038
32
0
0
541
9472
3485
0
0
70
11729
0
13170
7833
10994
10091
7769
1446
0
8802
0
1988
5747
16895
0
11486
0
8228
172
2261
19783
10
13889
0
30757
891
10188
0
5986
180
3959
33
424
0
0
0
2010
2891
1670
332
1872
2770
323
434
15845
1371
77
3132
0
1207
27680
18690
0
26600
350
45871
0
21063
10599
41842
21170
26015
15999
0
16645
3978
9726
10485
31419
0
30914
0
16452
1862
14663
37656
16
31128
0
44087
3822
18498
75
18705
294
12580
66
594
0
639
3511
7493
8226
1831
395
4515
12912
382
1329
28121
26531
9707
11814
0
3210
30723
20567
1303
56463
6179
50609
0
21651
11657
56353
22796
42964
30129
2117
18566
8009
22283
13036
35466
0
38395
809
17463
7021
25500
41463
13152
32763
2848
44547
11276
19115
1179
23365
1790
21144
948
1801
911
1840
5567
9757
10751
2212
576
8880
17448
2269
1883
42738
395
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
33
0
5
78
0
0
0
0
0
719
108
0
0
102
0
0
643
29
0
0
541
9472
3485
0
0
70
11729
0
13170
7833
10994
10091
7769
1446
0
8802
0
1988
5747
16895
0
11486
0
8228
172
2261
19783
10
13889
0
30757
891
10188
0
5986
147
3959
28
346
0
0
0
2010
2891
951
224
1872
2770
221
434
15845
333
45
3132
0
666
18208
15205
0
26600
280
34142
0
7893
2766
30848
11079
18246
14553
0
7843
3978
7738
4738
14524
0
19428
0
8224
1690
12402
17873
6
17239
0
13330
2931
8310
75
12719
114
8621
33
170
0
639
3511
5483
5335
161
63
2643
10142
59
895
12276
25160
9630
8682
0
2003
3043
1877
1303
29863
5829
4738
0
588
1058
14511
1626
16949
14130
2117
1921
4031
12557
2551
4047
0
7481
809
1011
5159
10837
3807
13136
1635
2848
460
7454
617
1104
4660
1496
8564
882
1207
911
1201
2056
2264
2525
381
181
4365
4536
1887
554
14617
2760
1920
2771
0
720
110
481
853
1933
1657
505
0
109
37
346
98
3565
960
1340
153
893
2967
451
112
0
444
718
20
2214
1256
204
3600
98
1534
241
1554
0
1500
91
240
2503
237
206
75
900
1524
700
423
49
80
1790
378
334
546
2990
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha)--------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
0
0
4352
0
0
0
4390
2675
0
0
14401
12444
15833
12800
0
13177
13725
14242
0
0
13956
0
3000
12151
10606
13707
9743
8750
10534
11818
12844
7400
0
12343
14011 12047
15493
16000
0
0
12581
14505
12907
0
0
11667
13359
0
12963
14479
12622
13419
12905
12796
0
13840
0
12272
13334
13097
0
12636
0
14385
11467
12288
12972
10000
13684
0
13200
12549
13899
0
12549
13846
12450
16500
13250
0
0
0
12722
12680
14911
14435
12077
12591
14043
12765
12575
13574
11000
8114
0
10588
11505
10059
0
8701
10606
10439
0
11330
13118
9880
11231
9892
9445
0
11640
8392
9081
11484
11094
0
10126
0
11965
10640
9239
10899
8000
11217
0
11769
10858
11797
10714
9987
12250
10178
13200
11880
0
7988
8184
10349
10439
14305
13621
10624
9629
13172
10302
10900
5500
0
0
0
6892
0 12452
9047
11492
0 14401 10461
9028
0 12444
9295
11206 17540 13841 10492
5214
0 12661
9322
6611
0
0
9246
8562
0 13172
9347
10773
0 13726
9760
10995 16200 13033
9760
5768
0
0
8098
6222
0
0
0
10857 16033 13619 10599
9999 16104 13844 10306
7323
6563
5490
0
7312
10616
9400
4898
6409
6324
9725
0
11030
11919
8193
10563
7482
7148
5615
10585
6475
6411
9736
9962
0
8665
5056
11332
6624
7117
10010
6391
10728
5077
11643
7056
11439
6015
8581
7817
7739
6362
7664
5623
5823
6643
8984
8959
11829
10286
7635
8097
6939
8482
7979
18445
15904
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17694
0
16963
16565
0
0
0
0
0
17143
16652
0
0
16811
0
0
13947
13155
0
0
12523
14496
12909
0
0
11749
13352
0
12966
14479
12616
13428
12912
12787
0
13847
0
12252
13332
13096
0
12629
0
14396
11707
12291
12971
13689
13680
0
13201
12634
13891
0
12548
14020
12461
13509
13003
0
0
0
12761
12663
13590
13044
12086
12609
13297
12849
12576
9928
9907
8124
0
9383
10384
9578
0
8702
10307
9709
0
9364
10361
9169
9779
8998
9208
0
9873
8385
8513
9822
9420
0
9062
0
10242
10533
8840
9261
9778
9794
0
9415
10437
9953
10221
9112
10096
9395
9897
9686
0
8006
8191
9680
9522
9912
10031
9781
9049
10217
9417
9298
6099
6890
6263
5518
6456
5193
6561
5627
5921
6688
5613
6427
6723
1861
2323
2051
2143
2185
1737
2093
1995
2005
2290
1955
2042
2242
5916
1969
7145
6540
4915
0
6168
6237
5690
4896
5191
6177
5851
0
5635
6207
5490
5952
5447
5604
5613
5937
5285
5220
5984
5557
0
5430
5054
6091
5831
5430
5540
6387
5853
5075
5714
5983
5981
5838
5485
7311
5725
6109
6543
5615
5088
5032
6245
6130
6413
6686
5914
5573
6333
5984
5266
2391
2191
1648
0
2064
2078
1889
1759
1781
2050
1912
0
1866
2065
1905
1939
1763
1868
1862
1943
1698
1841
1967
1875
0
1895
1653
1917
1924
1870
1868
2108
2132
1898
1904
1986
1596
1920
1889
2469
1840
2145
2191
1965
1782
1668
2081
2000
2153
2239
1889
2046
2174
1960
1868
APPENDIX II
Table A5 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ALL AREAS
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
Total
Suitable Areas (000ha)-------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
9385
1
19
62
0
1
18
43
16
9306
71140
58
883
2818
0
58
825
1935
2189
66132
16338
182
666
1600
5
177
484
934
361
14376
82285
0
0
0
0
0
0
0
0
82285
77545
316
1696
2624
0
316
1380
928
1060
73855
36283
1041
2460
5533
0
1041
1419
3073
2471
28279
75673
0
0
0
0
0
0
0
0
75672
3700
491
1248
1544
0
491
757
296
94
2061
76270
0
0
117
0
0
0
117
227
75926
2178
0
0
1
0
0
0
1
6
2170
17045
0
0
0
0
0
0
0
0
17022
28903
0
0
0
0
0
0
0
0
28902
9500
0
462
1289
0
0
462
827
405
7806
70770
0
0
0
0
0
0
0
0
70745
7110
175
579
1602
0
175
404
1023
801
4707
45830
0
0
0
0
0
0
0
0
45830
17673
937
2395
5777
0
937
1458
3382
1431
10465
13980
8
470
5675
0
8
462
5205
1234
7069
8095
0
5
17
0
0
5
12
30
7956
19273
764
3734
8183
0
764
2970
4449
1067
10022
1970
0
0
6
0
0
0
6
39
1925
31145
4
1355
5405
0
4
1351
4050
2575
23165
15860
112
775
5659
0
112
663
4884
1842
8359
53163
0
426
1432
0
0
426
1006
839
50892
66588
0
0
0
0
0
0
0
0
66580
8763
269
640
1247
0
269
371
607
1263
6252
41493
0
0
81
0
0
0
81
222
41189
33533
0
0
32
0
0
0
32
120
33381
17035
0
0
12
0
0
0
12
14
17009
6120
9
108
299
0
9
99
191
201
5620
303275
0
0
0
0
0
0
0
0
303257
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
389947
1284574
1674521
17483
5627
23110
57572
20501
78073
103370
56371
159741
82
5
87
17401
5622
23023
40089
14874
54963
45798
35870
81668
1640
1125
18480
15783
14798
16295
13863
19145
44848
413
9290
9250
13783
16663
18168
21050
11995
16385
23425
2840
56143
17725
37325
115468
20900
40580
5038
163355
119045
72183
40
0
0
2
19
878
4056
1473
1787
4537
267
5320
1049
5525
2282
5040
3006
78
319
571
0
1793
770
645
105
156
17
0
0
34
0
0
1
0
10
49
1547
5763
2012
3018
9806
385
7405
1641
7975
3195
6627
4428
213
570
1157
0
4348
1730
1016
517
332
63
0
1
52
0
0
202
270
2735
697
4100
7345
3211
5756
15317
385
7679
1869
8597
3766
6818
5126
333
727
1432
0
5648
1800
1207
2549
1040
181
129
23
108
4
0
0
0
0
3
270
1418
454
430
163
151
2500
326
1980
1105
2239
1224
5
70
116
0
194
77
127
0
8
1
0
0
9
0
0
0
0
2
16
608
2638
1019
1357
4374
116
2820
723
3545
1177
2801
1782
73
249
455
0
1599
693
518
105
148
16
0
0
25
0
0
1
0
8
30
669
1707
539
1231
5269
118
2085
592
2450
913
1587
1422
135
251
586
0
2555
960
371
412
176
46
0
1
18
0
0
201
270
2725
648
2553
1582
1199
2738
5511
0
274
228
622
571
191
698
120
157
275
0
1300
70
191
2032
708
118
129
22
56
4
0
237
267
2856
1083
2459
1222
1123
1093
1672
0
73
42
61
230
16
107
38
35
96
0
197
0
202
3794
714
238
198
72
32
16
0
1201
588
12888
14002
8239
7728
9529
12296
27858
28
1415
7339
5125
12667
11334
15816
11623
15623
21897
2840
50298
15924
35916
109124
19146
40161
4710
163260
118905
72162
40
2
0
32
268
13382
63478
21601
25223
64594
4436
85240
16098
87550
36873
79888
47305
1080
4558
8244
0
27044
11830
9874
1283
2250
231
1
1
531
0
0
937041
39729
63861
89054
12870
26859
24132
25193
18173
829682
612897
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
LC
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
25282
261223
20108 1207911
45390 1469134
Average annual biomass increments (000tons)----------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
18
175
403
0
18
157
228
27
696
7659
19138
0
696
6963
11479
5195
2614
7602
13411
87
2527
4988
5809
739
0
0
0
0
0
0
0
0
4218
17375
22935
0
4218
13157
5560
2353
14043
27576
44161
0
14043
13533
16585
4490
0
0
0
0
0
0
0
0
6883
14366
16100
0
6883
7483
1734
181
0
0
786
0
0
0
786
553
0
0
9
0
0
0
9
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3763
8171
0
0
3763
4408
853
0
0
0
0
0
0
0
0
2162
6175
11572
0
2162
4013
5397
1355
0
0
0
0
0
0
0
0
11307
25682
42863
0
11307
14375
17181
2965
98
4584
30108
0
98
4486
25524
2445
0
44
108
0
0
44
64
70
9267
35089
58479
0
9267
25822
23390
1946
0
0
24
0
0
0
24
73
42
11777
35349
0
42
11735
23572
5955
1334
7652
33042
0
1334
6318
25390
4287
0
3466
8976
0
0
3466
5510
2029
0
0
0
0
0
0
0
0
3359
6790
10076
0
3359
3431
3286
2131
0
1
367
0
0
1
366
515
0
0
197
0
0
0
197
313
0
0
54
0
0
0
54
37
111
959
2031
0
111
848
1072
375
0
0
0
0
0
0
0
0
231651
71997
303648
606564
868806
208856
401098
815420 1269904
1443
87
1530
230208
71910
302118
374913
136859
511772
262242
192242
454484
48200
41892
90092
1318
1786
17989
4865
37969
91814
34814
52640
148090
5640
108216
23401
116689
49493
96968
65840
3170
7958
16215
0
63359
22456
14929
15518
8850
1376
787
124
986
22
0
0
0
2
51
4721
25559
7717
6922
2540
2782
45074
5904
36636
20186
40409
21998
86
1219
1980
0
3673
1481
2341
0
144
24
0
0
170
0
0
2
0
30
217
8661
37919
13884
18301
62054
1654
40166
10194
50914
16687
39479
25307
994
3339
6264
0
23371
10349
7533
1283
2106
207
1
1
361
0
0
5
0
78
280
7058
17889
5400
12264
52734
1202
21188
5928
25218
9195
15954
14376
1356
2464
6173
0
27678
10187
3794
3713
1773
443
3
13
178
0
0
1311
1786
17879
4317
17529
10447
7813
15153
30762
2
1788
1375
3921
3425
1126
4159
734
936
1798
0
8637
439
1261
10522
4827
702
783
110
277
22
0
515
590
6263
2395
5655
2761
2434
1940
2953
0
175
89
139
441
31
207
84
77
213
0
439
1
463
7243
1625
470
394
132
57
33
0
859441 1013282
231619
381278
246544
153841
37819
7
0
110
548
20440
81367
27001
37487
117328
5638
106428
22026
112768
46068
95842
61681
2436
7022
14417
0
54722
22017
13668
4996
4023
674
4
14
709
0
0
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha)--------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
18000
9211
6500
0 12446
8624
5266
1710
12000
8674
6791
0 11921
8438
5931
2373
14363 11414
8382 16003 14319 10307
6216
2047
0
0
0
0
0
0
0
0
13348 10245
8740
0 13360
9537
5991
2220
13490 11210
7981
0 13493
9535
5398
1817
0
0
0
0
0
0
0
0
14018 11511 10427
0 14009
9881
5858
1921
0
0
6718
0
0
0
6694
2439
0
0
9000
0
0
0
6013
2600
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
8145
6339
0
0
8141
5330
2105
0
0
0
0
0
0
0
0
12354 10665
7223
0 12334
9938
5275
1691
0
0
0
0
0
0
0
0
12067 10723
7420
0 12068
9857
5081
2073
12250
9753
5305
0 11631
9702
4903
1981
0
8800
6353
0
0
9207
5462
2305
12130
9397
7146
0 12132
8695
5257
1823
0
0
4000
0
0
0
4288
1874
10500
8692
6540
0 11665
8685
5820
2313
11911
9874
5839
0 11905
9530
5198
2327
0
8136
6268
0
0
8128
5478
2419
0
0
0
0
0
0
0
0
12487 10609
8080
0 12471
9257
5410
1686
0
1000
4531
0
0
8449
4488
2320
0
0
6156
0
0
0
6172
2614
0
0
4500
0
0
0
4471
2670
12333
8880
6793
0 11976
8554
5617
1868
0
0
0
0
0
0
0
0
13250 10536
12795 10188
13139 10444
9352
9201
9311
5726
5359
5565
1906
2083
1985
9485
0
9468
9468
10555
10478
10025
9967
10008
10226
10161
10019
10294
10075
10055
10107
10016
9810
10539
0
10833
10615
10227
9008
10059
9589
8964
9222
9786
0
0
6510
6622
6561
6660
6867
6604
6517
5534
5582
6122
6516
6041
6308
5994
5884
5955
6104
5952
6539
0
6644
6238
6610
5177
6823
5952
6061
5125
4971
5227
0
2173
2206
2193
2211
2300
2259
2167
1776
1766
0
2392
2094
2269
1919
1944
1932
2191
2209
2207
0
2230
2194
2290
1909
2277
1975
1987
1829
1819
2047
0
15427 13458 11378 17997 14196 10216
6106
2081
2000
0
16000
14105
15241
15650
14665
14115
14237
16614
16023
15346
15846
16158
15851
15737
13846
14288
14438
0
15083
15364
15309
12219
14423
13588
1000
1000
15618
0
0
7000
0
11000
11184
13213
14119
13420
12421
11965
14644
14372
13422
14140
14419
14462
13930
11437
12319
12461
0
12586
12727
13453
9663
12117
10698
4000
14000
13635
0
0
8405 17598 13230
7115 17400 12791
7950 17586 13122
6525
6615
6577
6980
9261
12500
10842
9145
9668
14649
14092
12521
13573
13142
14222
12844
9520
10946
11323
0
11218
12476
12369
6088
8510
7602
6101
5391
9130
5500
0
16056
0
16089
16928
17459
18030
17014
16091
15570
18378
18029
18104
18499
18269
18047
17973
16661
17436
17030
0
18963
19339
18484
0
17957
16754
0
0
18709
0
0
13330
0
13197
13178
14255
14373
13624
13483
14188
14316
14245
14097
14362
14179
14097
14204
13640
13394
13772
0
14613
14924
14544
12169
14201
13317
12277
12150
14376
0
0
APPENDIX II
Table A6 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ACCESSIBLE AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
63130
0
0
34
0
0
0
34
97
63000
0
0
147
0
0
0
147
276
2025
6095
17955
3365
4763
165068
10428
5573
6018
2848
4775
22535
51955
0
0
5375
525
97
4
0
712
1757
182
0
0
7973
0
0
12434
1212
163
23
3
2348
3408
264
3
0
15142
2
382
14001
1729
245
5149
172
3938
4151
375
47
7
20602
0
0
0
0
52
0
0
0
0
73
0
0
1141
0
0
5375
525
45
4
0
712
1757
109
0
0
6832
0
0
7059
687
66
19
3
1636
1651
82
3
0
7169
2
382
1567
517
82
5126
169
1590
743
111
44
7
5460
26
587
449
176
93
4977
150
381
475
242
68
6
3947
1997
4633
3504
1460
4425
154943
10106
1254
1391
2230
4660
22523
27407
0
0
77379
6534
1536
46
0
9365
24113
2608
0
0
111172
0
1
151127
12900
2218
219
27
24631
40227
3408
28
0
187047
10
2607
160928
15745
2742
26817
1135
33565
44623
4149
275
42
223784
0
0
0
0
917
0
0
0
0
1185
0
0
18294
0
0
77379
6534
619
46
0
9365
24113
1423
0
0
92878
0
1
73748
6366
682
173
27
15266
16114
800
28
0
75875
303403
16625
35000
50800
1266
15359
18375
15800
11577
240533
232753
421833
516422
20396
212357
Krasnodar Kray
12
6715
Stavropol Kray
12
5428
Arkhangelsk oblast
12
14210
Astrakhan oblast
12
2923
Belgorod oblast
12
2248
Bryansk oblast
12
3095
Vladimir oblast
12
2510
Volgograd oblast
12
9108
Vologda oblast
12
9155
Voronezh oblast
12
4550
Nizhni Novgorod oblast12
6403
Nenets a.okr.
12
2583
Ivanovo oblast
12
1875
Kaliningrad oblast
12
1183
Tver oblast
12
6128
Kaluga oblast
12
2445
Kirov oblast
12
8750
Kostroma oblast
12
4263
Samara oblast
12
4408
Kursk oblast
12
2623
Komi-Permyak a.okr. 12
2220
Leningrad oblast
12
5678
Lipetsk oblast
12
2140
Moscow oblast
12
4130
Murmansk oblast
12
4110
Novgorod oblast
12
3935
Orenburg oblast
12
8305
Oryel oblast
12
2018
Penza oblast
12
3893
Perm oblast
12
8423
Pskov oblast
12
4508
Rostov oblast
12
8245
Ryazan oblast
12
3453
Saratov oblast
12
8433
Smolensk oblast
12
4113
Tambov oblast
12
2905
Tula oblast
12
2283
Ulyanovsk oblast
12
3218
Yaroslavl oblast
12
2350
Adigei Republic
12
605
Bashkortostan Republic12
8983
Daghestn Republic
12
3843
Kabardino-Balkarian Republic
12
898
Kalmyk-Khalm-Tangch 12
Republic4735
Karelia Republic
12
9165
Komi Republic
12
14183
Mari-El Republic
12
1575
Mordovian SSR
12
2315
North-Ossetian SSR 12
608
Karachai-Cherkess Republic
12
1085
Tatarstan Republic
12
5278
Udmurt Republic
12
3425
Checheno-Ingush Republic
12
1555
64
2
0
0
39
557
223
0
0
5
772
0
833
519
657
617
462
67
0
561
0
124
378
1163
0
685
0
477
10
150
1273
1
906
0
1935
47
657
0
395
12
219
2
29
0
0
0
114
208
109
21
94
185
21
94
6
196
0
101
2129
1598
0
2048
31
3720
0
1542
771
3128
1565
1934
1160
0
1261
301
793
805
2543
0
2206
0
1138
144
1194
2852
2
2432
0
3107
284
1403
7
1364
22
847
4
46
0
60
147
525
712
125
25
286
1100
27
3245
1178
1331
0
379
2570
1884
223
5564
873
4396
0
1629
929
5021
1795
4144
2968
343
1545
825
2622
1187
3148
0
3188
117
1272
934
2602
3419
1698
2676
495
3169
1350
1498
171
1947
215
1869
142
221
148
235
321
753
1082
184
50
891
1765
305
21
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
4
0
0
0
0
0
41
6
0
0
6
43
2
0
0
39
557
223
0
0
5
772
0
833
519
657
617
462
67
0
561
0
124
378
1163
0
685
0
477
10
150
1273
1
906
0
1935
47
657
0
395
10
219
2
25
0
0
0
114
208
68
15
94
185
15
30
4
196
0
62
1572
1375
0
2048
26
2948
0
709
252
2471
948
1472
1093
0
700
301
669
427
1380
0
1521
0
661
134
1044
1579
1
1526
0
1172
237
746
7
969
10
628
2
17
0
60
147
411
504
16
4
192
915
6
3151
1172
1135
0
278
441
286
223
3516
842
676
0
87
158
1893
230
2210
1808
343
284
524
1829
382
605
0
982
117
134
790
1408
567
1696
244
495
62
1066
95
164
583
193
1022
138
175
148
175
174
228
370
59
25
605
665
278
1029
747
1074
0
295
47
217
411
664
703
214
0
50
17
127
38
1513
365
644
64
398
1239
207
51
0
174
297
9
1043
478
96
1413
40
703
109
660
0
691
40
93
911
103
88
35
373
579
203
180
23
31
781
166
147
2436
3503
11790
2922
1572
479
409
8473
2928
2974
1791
2582
196
236
980
612
3093
930
3420
1013
997
1817
746
931
4110
572
7891
736
1916
5343
993
5135
736
7235
834
895
785
2356
363
297
6203
3590
588
4552
8554
13282
619
1053
399
1004
3606
1494
1104
991
27
0
0
495
8080
2888
0
0
59
10302
0
10796
7519
8284
8291
5969
850
0
7771
0
1520
5040
15259
0
8650
0
6864
120
1841
16513
10
12398
0
25551
598
9130
0
4958
172
2732
27
394
0
0
0
1445
2642
1638
300
1138
2336
287
1291
71
1597
0
1080
24397
16072
0
17772
332
38941
0
17445
10130
30939
17567
19222
10901
0
14678
2546
7235
9236
28274
0
22416
0
13633
1528
11080
31140
16
27355
0
36588
3075
16549
70
13792
273
8662
51
559
0
481
1212
5415
7434
1798
342
3006
10633
345
23810
7753
7182
0
2795
27145
17703
1098
36017
5545
42902
0
17938
11113
41332
18936
31255
21040
1939
16365
5334
16792
11517
31642
0
27740
588
14448
6132
18730
34276
10877
28787
2512
36944
9457
17115
1029
16996
1686
14526
895
1705
833
1370
2094
6840
9692
2179
510
6552
14350
2124
387
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
31
0
4
72
0
0
0
0
0
709
103
0
0
93
604
25
0
0
495
8080
2888
0
0
59
10302
0
10796
7519
8284
8291
5969
850
0
7771
0
1520
5040
15259
0
8650
0
6864
120
1841
16513
10
12398
0
25551
598
9130
0
4958
141
2732
23
322
0
0
0
1445
2642
929
197
1138
2336
194
FSU REPUBLICS
10
2606
9801
2845
524
26598
1108
8934
4396
741
247
42
36737
49
1361
920
376
200
8694
313
757
950
554
133
11
8858
189080
94589
23176
300
44
1597
0
585
16317
13184
0
17772
273
28639
0
6649
2611
22655
9276
13253
10051
0
6907
2546
5715
4196
13015
0
13766
0
6769
1408
9239
14627
6
14957
0
11037
2477
7419
70
8834
101
5930
24
165
0
481
1212
3970
4792
160
42
1868
8297
58
22519
7682
5585
0
1715
2748
1631
1098
18245
5213
3961
0
493
983
10393
1369
12033
10139
1939
1687
2788
9557
2281
3368
0
5324
588
815
4604
7650
3136
10861
1432
2512
356
6382
566
959
3204
1413
5864
844
1146
833
889
882
1425
2258
381
168
3546
3717
1779
2461
1639
1770
0
609
97
410
728
1170
1444
410
0
93
34
241
74
2665
683
1203
125
678
2287
407
95
0
325
489
18
2004
891
178
2990
85
1331
207
1311
0
1326
75
231
1674
220
193
69
669
963
425
358
49
69
1470
340
321
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
0
0 4324
0
0
0 4380 2851
0
0
14396
12446
15835
11500
0
13153
13724
14330
0
0
13944
0
1000
12154
10644
13607
9522
9000
10490
11804
12909
9333
0
12353
5000
0
0
0
6825
0
0 9297
11494
0 14395 10447
9106
0 12450 9266
11192 17597 13874 10369
5208
0 12717 9333
6599
0
0 9213
8523
0 13159 9331
10750
0 13720 9757
11064 16204 13033 9768
5851
0
0 8086
6000
0
0
0
10862 16037 13595 10584
6081
6816
6253
5503
6395
5189
6540
5618
5918
6688
5643
6429
6728
1857
2317
2049
2136
2158
1747
2092
1989
2002
2288
1960
2033
2244
14000 12052 10166 16111 13826 10290
5987
2002
15484
13500
0
0
12692
14506
12951
0
0
11800
13345
0
12960
14487
12609
13438
12920
12687
0
13852
0
12258
13333
13120
0
12628
0
14390
12000
12273
12972
10000
13684
0
13205
12723
13896
0
12552
14333
12475
13500
13586
0
0
0
12675
12702
15028
14286
12106
12627
13667
7147
6556
4921
0
6165
6235
5697
4915
5189
6189
5856
0
5639
6210
5491
5956
5445
5609
5652
5933
5325
5226
5976
5569
0
5419
5038
6086
5826
5433
5534
6405
5861
5078
5719
5989
5980
5843
5493
7319
5740
6125
6543
5632
5083
5069
6261
6108
6413
6702
5861
5594
6408
2392
2195
1648
0
2063
2080
1891
1770
1763
2056
1916
0
1868
2066
1905
1940
1761
1869
1867
1933
1704
1845
1967
1883
0
1871
1647
1919
1921
1864
1858
2116
2123
1894
1905
1987
1592
1919
1895
2469
1838
2139
2191
1977
1791
1662
2090
1996
2153
2243
1882
2042
2180
13734
11833
8148
0
10693
11459
10058
0
8678
10710
10468
0
11313
13139
9891
11225
9939
9397
0
11640
8458
9124
11473
11118
0
10161
0
11980
10611
9280
10919
8000
11248
0
11776
10827
11795
10000
10111
12409
10227
12750
12152
0
8017
8245
10314
10441
14384
13680
10510
9666
12778
7337
6581
5396
0
7375
10562
9396
4924
6473
6352
9759
0
11012
11962
8232
10549
7542
7089
5653
10592
6465
6404
9703
10051
0
8701
5026
11358
6565
7198
10025
6406
10757
5075
11658
7005
11425
6018
8729
7842
7772
6303
7715
5628
5830
6523
9084
8957
11842
10200
7354
8130
6964
18476
16209
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17641
0
16957
16544
0
0
0
0
0
17151
16684
0
0
16820
13984
13296
0
0
12571
14508
12924
0
0
11742
13336
0
12963
14480
12615
13435
12927
12731
0
13839
0
12264
13336
13117
0
12620
0
14377
11672
12296
12970
13689
13688
0
13201
12596
13889
0
12551
14020
12473
13487
12990
0
0
0
12711
12683
13607
13041
12110
12617
13324
9959
9911
8148
0
9369
10381
9591
0
8679
10369
9713
0
9375
10361
9168
9790
9005
9195
0
9870
8462
8550
9821
9433
0
9048
0
10236
10545
8852
9262
9778
9799
0
9416
10456
9951
10225
9115
10102
9438
9813
9672
0
7992
8220
9656
9505
9905
9898
9751
9069
10216
APPENDIX II
Table A6 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ACCESSIBLE AREAS
ADM REG NAME
197
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Chuvash Republic
12
Altai Kray
12
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
1678
29
115
200
0
29
86
85
263
1216
370
1181
1693
0
370
811
512
515
11538
860
1722
3816
0
860
862
2094
1203
6519
10843
18909
29931
0
10843
8066
11022
2255
2693
1
17
49
0
1
16
32
9
2634
18
153
321
0
18
135
168
16
16560
50
596
1677
0
50
546
1081
945
13938
595
5243
11529
0
595
4648
6286
2190
7290
121
453
1087
5
116
332
634
226
5978
1727
5140
9080
76
1651
3413
3940
468
2848
0
0
0
0
0
0
0
0
2847
0
0
0
0
0
0
0
0
9013
177
567
859
0
177
390
292
207
7945
2393
6096
7785
0
2393
3703
1689
431
9438
752
1522
2709
0
752
770
1187
941
5787
10222
17674
24234
0
10222
7452
6560
1745
6140
0
0
0
0
0
0
0
0
6140
0
0
0
0
0
0
0
0
1545
271
649
795
0
271
378
146
40
711
3810
7558
8409
0
3810
3748
851
74
17280
0
0
80
0
0
0
80
161
17039
0
0
547
0
0
0
547
396
1180
0
0
1
0
0
0
1
4
1175
0
0
7
0
0
0
7
10
3853
0
0
0
0
0
0
0
0
3852
0
0
0
0
0
0
0
0
5013
0
0
0
0
0
0
0
0
5012
0
0
0
0
0
0
0
0
5290
0
260
778
0
0
260
518
261
4251
0
2123
4875
0
0
2123
2752
557
8158
0
0
0
0
0
0
0
0
8155
0
0
0
0
0
0
0
0
5195
138
450
1206
0
138
312
756
596
3392
1698
4797
8786
0
1698
3099
3989
1009
9245
0
0
0
0
0
0
0
0
9245
0
0
0
0
0
0
0
0
9910
617
1513
3072
0
617
896
1559
779
6059
7440
16173
24115
0
7440
8733
7942
1542
8545
5
315
3600
0
5
310
3285
722
4223
61
3093
19196
0
61
3032
16103
1484
4795
0
4
14
0
0
4
10
27
4751
0
40
97
0
0
40
57
63
12618
589
2639
5730
0
589
2050
3091
799
6088
7144
25142
41494
0
7144
17998
16352
1453
663
0
0
3
0
0
0
3
18
642
0
0
12
0
0
0
12
34
7415
4
773
2288
0
4
769
1515
928
4199
42
6735
15575
0
42
6693
8840
2127
7043
59
450
2323
0
59
391
1873
810
3909
711
4426
14288
0
711
3715
9862
1834
6830
0
123
289
0
0
123
166
164
6377
0
998
1988
0
0
998
990
389
2680
0
0
0
0
0
0
0
0
2680
0
0
0
0
0
0
0
0
6338
214
509
974
0
214
295
465
920
4443
2671
5412
7938
0
2671
2741
2526
1554
7850
0
0
61
0
0
0
61
139
7651
0
0
266
0
0
0
266
318
6650
0
0
23
0
0
0
23
86
6541
0
0
142
0
0
0
142
224
5043
0
0
11
0
0
0
11
12
5020
0
0
48
0
0
0
48
31
3093
8
98
247
0
8
90
149
160
2685
100
871
1707
0
100
771
836
297
46970
0
0
0
0
0
0
0
0
46970
0
0
0
0
0
0
0
0
244894
258722
503616
14622
3866
18488
45900
12660
58560
80716
31692
112408
80
5
85
14542
3861
18403
31278
8794
40072
34816
19032
53848
19843
10157
30000
144291
216858
361149
194255
49475
243730
488360
130583
618943
689833
232370
922203
1401
76
1477
192854
49399
242253
294105
81108
375213
201473
101787
303260
38119
20501
58620
1385
863
13455
8953
10518
10775
11258
14803
26983
370
5798
5938
9145
10700
9940
11740
8395
12815
15593
700
26720
8415
23453
56150
8803
15968
2450
32755
29875
21850
0
0
0
1
12
684
3059
1267
1641
3003
238
3395
765
3838
1599
3300
1759
61
254
328
0
1121
434
443
24
113
11
0
0
12
0
0
0
0
6
28
1169
4345
1741
2694
6319
344
4753
1177
5565
2224
4335
2682
163
447
728
0
2733
961
691
131
215
40
0
1
19
0
0
179
216
2164
530
3055
5574
2767
4813
9944
344
4958
1343
6044
2592
4461
3184
253
566
923
0
3557
995
828
1448
771
115
56
13
64
4
0
0
0
0
2
216
1051
394
405
131
134
1555
239
1366
770
1406
567
4
57
52
0
120
46
90
0
5
1
0
0
2
0
0
0
0
1
10
468
2008
873
1236
2872
104
1840
526
2472
829
1894
1192
57
197
276
0
1001
388
353
24
108
10
0
0
10
0
0
0
0
5
16
485
1286
474
1053
3316
106
1358
412
1727
625
1035
923
102
193
400
0
1612
527
248
107
102
29
0
1
7
0
0
179
216
2158
502
1886
1229
1026
2119
3625
0
205
166
479
368
126
502
90
119
195
0
824
34
137
1317
556
75
56
12
45
4
0
214
211
2266
822
1797
949
976
856
1111
0
60
36
45
172
10
77
31
26
69
0
131
0
152
2500
517
145
86
33
24
13
0
992
435
9023
7600
5665
4252
7514
9135
15927
25
776
4559
3057
7936
5469
8479
8111
12223
14600
700
23032
7420
22473
52202
7515
15707
2307
32709
29786
21833
0
1
0
20
169
10397
47796
18624
23219
42771
3953
54310
11719
60742
25805
52084
27105
849
3635
4717
0
16892
6677
6772
290
1625
142
1
1
174
0
0
4
0
69
323
15515
61276
23384
33710
76254
5041
68163
15856
78554
32102
62487
36431
1870
5533
8958
0
34325
12290
9309
1258
2652
424
3
13
240
0
0
1173
1430
14214
3665
28474
69389
30069
45466
96425
5043
69512
16860
81587
34306
63228
39420
2419
6244
10234
0
39799
12504
10215
7968
6465
881
351
78
458
19
0
0
0
1
34
3772
18941
6700
6518
2035
2457
28030
4310
25243
14068
25394
10195
75
991
896
0
2292
888
1654
0
82
12
0
0
40
0
0
1
0
19
135
6625
28855
11924
16701
40736
1496
26280
7409
35499
11737
26690
16910
774
2644
3821
0
14600
5789
5118
290
1543
130
1
1
134
0
0
3
0
49
154
5118
13480
4760
10491
33483
1088
13853
4137
17812
6297
10403
9326
1021
1898
4241
0
17433
5613
2537
968
1027
282
2
12
66
0
0
1169
1430
14145
3342
12959
8113
6685
11756
20171
2
1349
1004
3033
2204
741
2989
549
711
1276
0
5474
214
906
6710
3813
457
348
65
218
19
464
466
4967
1821
4138
2142
2114
1525
1952
0
145
76
104
329
20
149
67
58
153
0
291
0
349
4640
1185
289
172
62
43
27
0
416566
27362
43511
61761
8613
18749
16149
18250
13329
341462
420490
586044
697896
154628
265862
165554
111852
27748
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
12759 10270 8465
0 12903 9470 6019 1962
12608 10981 7844
0 12609 9354 5264 1875
18000 9000 6551
0 12446 8661 5319 1720
11900 8797 6875
0 11911 8514 5813 2318
14273 11347 8353 15996 14245 10294 6216 2072
0
0
0
0
0
0
0
0
13520 10751 9063
0 13550 9489 5791 2088
13593 11612 8946
0 13595 9676 5527 1853
0
0
0
0
0
0
0
0
14059 11646 10577
0 14069 9918 5839 1863
0
0 6838
0
0
0 6872 2462
0
0 7000
0
0
0 5788 2654
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 8165 6266
0
0 8164 5314 2134
0
0
0
0
0
0
0
0
12304 10660 7285
0 12338 9926 5273 1692
0
0
0
0
0
0
0
0
12058 10689 7850
0 12054 9750 5093 1979
12200 9819 5332
0 11623 9767 4903 2056
0 10000 6929
0
0 9269 5518 2315
12129 9527 7242
0 12137 8778 5290 1819
0
0 4000
0
0
0 4279 1920
10500 8713 6807
0 11665 8701 5836 2292
12051 9836 6151
0 12006 9508 5264 2264
0 8114 6879
0
0 8128 5955 2376
0
0
0
0
0
0
0
0
12481 10633 8150
0 12470 9277 5432 1690
0
0 4361
0
0
0 4384 2295
0
0 6174
0
0
0 6118 2607
0
0 4364
0
0
0 4457 2639
12500 8888 6911
0 11995 8554 5609 1861
0
0
0
0
0
0
0
0
13285 10640
12797 10315
13183 10569
9403
9223
9363
5787
5348
5632
1921
2018
1954
9518
0
9531
9481
10554
10481
10043
9962
10096
10229
10203
10039
10317
10076
10053
10108
10010
9838
10603
0
10816
10648
10248
9078
10104
9618
9055
9167
9044
0
0
6513
6619
6553
6654
6873
6600
6518
5549
5565
6123
6569
6058
6334
5992
5881
5949
6109
5962
6536
0
6640
6286
6628
5094
6858
6057
6166
5445
4828
5170
0
2174
2205
2192
2215
2302
2258
2166
1782
1756
0
2394
2106
2290
1913
1943
1939
2192
2203
2207
0
2221
2137
2294
1856
2292
1988
1996
1880
1760
2052
0
15368 13469 11300 17953 14180 10252
6129
2082
1000
0
20000
14083
15200
15625
14699
14149
14243
16609
15997
15319
15826
16138
15783
15409
13918
14311
14381
0
15069
15385
15287
12083
14381
12909
1000
1000
14500
0
0
4000
0
11500
11536
13272
14103
13431
12513
12067
14654
14341
13472
14116
14434
14415
13584
11472
12378
12305
0
12559
12789
13472
9603
12335
10600
3000
13000
12632
0
0
8546 17513 13262
7332 15200 12794
8204 17376 13164
6553
6620
6568
6915
9320
12449
10867
9446
9697
14660
14020
12554
13499
13235
14174
12381
9561
11032
11088
0
11189
12567
12337
5503
8385
7661
6268
6000
7156
4750
0
16056
0
16051
16913
17455
18027
16983
16091
15575
18384
18024
18059
18483
18261
18056
17982
16694
17476
17117
0
19131
19433
18298
0
18214
16864
0
0
17862
0
0
13888
0
13203
13154
14152
14367
13651
13515
14185
14319
14283
14091
14360
14164
14094
14187
13589
13420
13866
0
14582
14932
14513
12065
14291
13390
12277
12150
13968
0
0
APPENDIX II
Table A7 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ACCESSIBLE AREAS, EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
62805
0
0
33
0
0
0
33
97
62675
0
0
147
0
0
0
147
276
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
0
0 4455
0
0
0 4380 2852
1448
4205
6503
1303
3013
134203
8128
1875
3013
93
3495
20363
5253
0
0
1589
199
12
3
0
192
876
14
0
0
816
0
0
4376
475
31
21
2
704
1719
15
2
0
2230
1
202
4974
690
55
1908
41
1356
2101
18
19
6
2665
0
0
0
0
9
0
0
0
0
10
0
0
76
0
0
1589
199
3
3
0
192
876
4
0
0
740
0
0
2787
276
19
18
2
512
843
1
2
0
1414
1
202
598
215
24
1887
39
652
382
3
17
6
435
12
273
147
89
29
2091
30
118
275
9
20
4
117
1434
3363
1382
524
2928
130204
8056
401
637
66
3455
20352
2470
0
0
22964
2462
206
42
0
2507
12012
204
0
0
11870
0
0
52317
5023
405
208
18
7293
20234
219
17
0
27156
9
1354
56092
6221
560
10020
271
10936
22488
239
110
40
29978
0
0
0
0
159
0
0
0
0
154
0
0
1219
0
0
22964
2462
47
42
0
2507
12012
50
0
0
10651
0
0
29353
2561
199
166
18
4786
8222
15
17
0
15286
9
1354
3775
1198
155
9812
253
3643
2254
20
93
40
2822
23
620
304
186
65
3677
61
232
547
20
40
9
255
192895
3701
9575
14036
95
3606
5874
4461
3214
175272
52267
112890
138318
1532
50735
60623
25428
6039
14122 11790
Krasnodar Kray
12
1820
Stavropol Kray
12
805
Arkhangelsk oblast
12
13708
Astrakhan oblast
12
2853
Belgorod oblast
12
73
Bryansk oblast
12
638
Vladimir oblast
12
1008
Volgograd oblast
12
1703
Vologda oblast
12
7900
Voronezh oblast
12
473
Nizhni Novgorod oblast12
3318
Nenets a.okr.
12
2583
Ivanovo oblast
12
848
Kaliningrad oblast
12
145
Tver oblast
12
2598
Kaluga oblast
12
1038
Kirov oblast
12
5758
Kostroma oblast
12
3273
Samara oblast
12
370
Kursk oblast
12
80
Komi-Permyak a.okr. 12
1838
Leningrad oblast
12
4743
Lipetsk oblast
12
80
Moscow oblast
12
2008
Murmansk oblast
12
3965
Novgorod oblast
12
3273
Orenburg oblast
12
1840
Oryel oblast
12
53
Penza oblast
12
575
Perm oblast
12
5435
Pskov oblast
12
2258
Rostov oblast
12
313
Ryazan oblast
12
1050
Saratov oblast
12
845
Smolensk oblast
12
563
Tambov oblast
12
255
Tula oblast
12
213
Ulyanovsk oblast
12
780
Yaroslavl oblast
12
850
Adigei Republic
12
225
Bashkortostan Republic12
3123
Daghestn Republic
12
3370
Kabardino-Balkarian Republic
12
555
Kalmyk-Khalm-Tangch 12
Republic3825
Karelia Republic
12
8518
Komi Republic
12
14183
Mari-El Republic
12
943
Mordovian SSR
12
593
North-Ossetian SSR 12
405
Karachai-Cherkess Republic
12
895
Tatarstan Republic
12
540
Udmurt Republic
12
1400
Checheno-Ingush Republic
12
1028
44
1
0
0
1
32
75
0
0
0
348
0
373
56
371
253
140
42
0
17
0
115
10
521
0
562
0
7
0
41
631
0
101
0
249
2
61
0
140
11
26
2
24
0
0
0
53
43
40
17
4
77
20
69
3
188
0
2
451
644
0
1689
0
2026
0
708
96
1357
655
968
857
0
39
202
705
19
1231
0
1800
0
27
12
485
1496
0
677
0
427
24
129
1
511
19
125
4
30
0
53
147
345
233
47
20
14
451
25
254
27
1213
0
10
558
770
7
4785
64
2450
0
747
120
2129
759
2481
2333
26
47
588
2302
26
1548
0
2638
1
34
90
1236
1862
21
760
9
446
86
136
42
718
25
287
104
36
0
205
321
527
308
67
22
85
749
104
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
4
0
0
0
0
0
16
5
0
0
6
32
1
0
0
1
32
75
0
0
0
348
0
373
56
371
253
140
42
0
17
0
115
10
521
0
562
0
7
0
41
631
0
101
0
249
2
61
0
140
9
26
2
20
0
0
0
53
43
24
12
4
77
14
25
2
188
0
1
419
569
0
1689
0
1678
0
335
40
986
402
828
815
0
22
202
590
9
710
0
1238
0
20
12
444
865
0
576
0
178
22
68
1
371
8
99
2
6
0
53
147
292
190
7
3
10
374
5
185
24
1025
0
8
107
126
7
3096
64
424
0
39
24
772
104
1513
1476
26
8
386
1597
7
317
0
838
1
7
78
751
366
21
83
9
19
62
7
41
207
6
162
100
6
0
152
174
182
75
20
2
71
298
79
113
28
1006
0
11
2
89
5
589
79
165
0
18
2
44
15
1258
305
68
1
388
1037
20
33
0
149
3
0
143
341
64
20
26
30
12
87
0
176
5
7
154
73
5
0
347
579
119
33
8
2
84
99
47
1452
750
11473
2852
52
78
148
1691
2526
329
703
2582
83
23
424
264
2020
635
275
33
861
1404
34
427
3965
485
1836
18
342
3858
332
271
263
807
105
82
77
561
127
193
2682
3185
515
3825
7963
13282
297
253
330
871
370
552
876
674
20
0
0
9
465
979
0
0
0
4632
0
4849
812
4699
3367
1796
531
0
236
0
1408
129
6827
0
7082
0
94
0
500
8154
0
1394
0
3262
23
821
0
1753
153
322
27
333
0
0
0
680
547
587
232
52
970
285
925
41
1534
0
19
4789
6438
0
14614
0
20969
0
8002
1222
13699
7290
9088
7987
0
453
1700
6442
218
13525
0
18271
0
300
131
4379
16115
0
7022
0
4924
243
1480
8
5117
237
1226
51
391
0
424
1212
3505
2299
657
265
147
4353
338
2236
190
6578
0
69
5450
7156
34
30655
403
23446
0
8222
1368
17925
7910
17213
16261
153
500
3744
14778
260
15284
0
22797
5
346
574
8462
18125
125
7508
50
5033
607
1523
246
6249
275
2141
653
428
0
1199
2094
4646
2731
786
279
551
6020
832
231
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
31
0
4
72
0
0
0
0
0
269
76
0
0
93
443
18
0
0
9
465
979
0
0
0
4632
0
4849
812
4699
3367
1796
531
0
236
0
1408
129
6827
0
7082
0
94
0
500
8154
0
1394
0
3262
23
821
0
1753
122
322
23
261
0
0
0
680
547
318
156
52
970
192
251
21
1534
0
10
4324
5459
0
14614
0
16337
0
3153
410
9000
3923
7292
7456
0
217
1700
5034
89
6698
0
11189
0
206
131
3879
7961
0
5628
0
1662
220
659
8
3364
84
904
24
58
0
424
1212
2825
1752
70
33
95
3383
53
1311
149
5044
0
50
661
718
34
16041
403
2477
0
220
146
4226
620
8125
8274
153
47
2044
8336
42
1759
0
4526
5
46
443
4083
2010
125
486
50
109
364
43
238
1132
38
915
602
37
0
775
882
1141
432
129
14
404
1667
494
273
63
1657
0
22
4
169
8
1029
164
313
0
33
4
82
29
2183
568
129
2
658
1911
39
62
0
275
5
0
273
634
117
37
56
58
22
171
0
337
8
17
275
157
10
0
615
963
260
65
17
4
158
200
102
15318
20000
0
0
9000
14531
13053
0
0
0
13310
0
13000
14500
12666
13308
12829
12643
0
13882
0
12243
12900
13104
0
12601
0
13429
0
12195
12922
0
13802
0
13100
11500
13459
0
12521
13909
12385
13500
13875
0
0
0
12830
12721
14675
13647
13000
12597
14250
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
0
0
14452
12372
17167
14000
0
13057
13712
14571
0
0
14547
0
0
11955
10575
13065
9905
9000
10359
11771
14600
8500
0
12178
13406
13667
8160
0
9500
10619
9997
0
8652
0
10350
0
11302
12729
10095
11130
9388
9320
0
11615
8416
9138
11474
10987
0
10151
0
11111
10917
9029
10772
0
10372
0
11532
10125
11473
8000
10014
12474
9808
12750
13033
0
8000
8245
10159
9867
13979
13250
10500
9652
13520
9000
0
0
0
6703
0
0 8747
11277
0 14455 10533
9016
0 12366 9296
10182 17423 13725 10645
5252
0 12727 9351
6610
0
0 9297
8065
0 13065 9346
10703
0 13717 9756
13278 16161 13481 10511
5789
0
0 8105
6667
0
0
0
11249 15954 14403 10808
9855 16126 14070 10321
8803
7037
5423
0
6900
9767
9294
4857
6406
6297
9570
0
11007
11400
8419
10422
6938
6970
5885
10638
6367
6420
10000
9873
0
8642
5000
10176
6378
6846
9734
5952
9879
5556
11285
7058
11199
5857
8703
11000
7460
6279
11889
0
5849
6523
8816
8867
11731
12682
6482
8037
8000
18921
16209
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17641
0
16957
16547
0
0
0
0
0
17022
16620
0
0
16820
13898
13342
0
0
12837
14519
13076
0
0
0
13328
0
13009
14509
12664
13297
12875
12712
0
14162
0
12274
13470
13106
0
12604
0
14491
0
12282
12933
0
13739
0
13095
12160
13547
0
12548
13932
12593
13487
13037
0
0
0
12956
12853
13459
13030
12225
12639
13331
9862
10450
8147
0
9348
10328
9596
0
8652
0
9737
0
9408
10314
9124
9768
8811
9144
0
10079
8420
8536
9927
9437
0
9036
0
10208
10807
8735
9204
0
9769
0
9360
10056
9752
10024
9067
10012
9178
9817
9940
0
7971
8220
9684
9237
9910
10018
9382
9057
10230
6168
6704
6308
5560
6487
5200
6474
5584
5899
6841
5383
6467
6489
1905
2273
2069
2091
2227
1759
2016
1970
1989
2288
1969
2064
2178
5700
1879
7091
6287
4920
0
6152
6199
5677
4790
5181
6249
5849
0
5645
6170
5473
5967
5371
5606
5773
5947
5292
5221
5774
5541
0
5403
5195
6082
5702
5435
5494
5841
5827
5853
5667
5844
6024
5765
5455
6161
5638
6050
6534
0
5096
5069
6266
5790
6408
6369
5720
5592
6226
2406
2248
1647
0
2050
2053
1888
1760
1748
2071
1892
0
1863
2063
1865
1933
1736
1866
1902
2069
1695
1842
1967
1899
0
1845
1717
0
1911
1859
1834
1840
2145
1965
1883
1969
1575
1909
1881
2439
1789
2132
2199
0
1776
1662
2174
1985
2146
2245
1870
2018
2172
APPENDIX II
Table A7 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ACCESSIBLE AREAS, EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
197
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Chuvash Republic
12
Altai Kray
12
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
643
5
29
66
0
5
24
37
135
441
65
298
508
0
65
233
210
270
6125
339
761
1787
0
339
422
1026
712
3626
4278
8243
13705
0
4278
3965
5462
1366
2668
1
16
48
0
1
15
32
9
2610
18
152
320
0
18
134
168
16
13728
35
378
1016
0
35
343
638
657
12055
415
3336
7135
0
415
2921
3799
1537
6520
105
373
831
5
100
268
458
168
5521
1489
4228
7049
76
1413
2739
2821
346
2825
0
0
0
0
0
0
0
0
2825
0
0
0
0
0
0
0
0
8873
165
505
783
0
165
340
278
202
7885
2235
5460
7071
0
2235
3225
1611
421
8108
323
813
1823
0
323
490
1010
850
5435
4382
9088
14589
0
4382
4706
5501
1553
6128
0
0
0
0
0
0
0
0
6127
0
0
0
0
0
0
0
0
1450
233
575
712
0
233
342
137
40
698
3266
6646
7439
0
3266
3380
793
74
16035
0
0
64
0
0
0
64
134
15837
0
0
450
0
0
0
450
330
693
0
0
1
0
0
0
1
0
691
0
0
4
0
0
0
4
1
3853
0
0
0
0
0
0
0
0
3852
0
0
0
0
0
0
0
0
5010
0
0
0
0
0
0
0
0
5010
0
0
0
0
0
0
0
0
3498
0
204
545
0
0
204
341
177
2776
0
1663
3453
0
0
1663
1790
362
8158
0
0
0
0
0
0
0
0
8155
0
0
0
0
0
0
0
0
2403
20
76
442
0
20
56
366
296
1664
249
795
2653
0
249
546
1858
497
9245
0
0
0
0
0
0
0
0
9245
0
0
0
0
0
0
0
0
6220
156
692
1613
0
156
536
921
532
4075
1864
7328
12037
0
1864
5464
4709
1097
5035
5
286
1647
0
5
281
1361
501
2887
61
2810
9507
0
61
2749
6697
1072
4760
0
4
14
0
0
4
10
27
4716
0
40
97
0
0
40
57
63
10428
284
1929
4442
0
284
1645
2513
672
5313
3419
17731
30939
0
3419
14312
13208
1217
630
0
0
2
0
0
0
2
15
612
0
0
11
0
0
0
11
30
6968
2
696
2138
0
2
694
1442
838
3992
21
5978
14431
0
21
5957
8453
1910
4585
32
304
1675
0
32
272
1371
506
2403
388
2962
10132
0
388
2574
7170
1150
6780
0
116
275
0
0
116
159
161
6344
0
947
1898
0
0
947
951
383
2678
0
0
0
0
0
0
0
0
2677
0
0
0
0
0
0
0
0
2578
43
89
194
0
43
46
105
269
2115
534
951
1510
0
534
417
559
454
7260
0
0
56
0
0
0
56
116
7088
0
0
246
0
0
0
246
263
6045
0
0
11
0
0
0
11
62
5971
0
0
62
0
0
0
62
166
4778
0
0
9
0
0
0
9
10
4759
0
0
41
0
0
0
41
25
2370
1
34
119
0
1
33
85
91
2159
12
298
782
0
12
286
484
170
46870
0
0
0
0
0
0
0
0
46870
0
0
0
0
0
0
0
0
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
13000 10276 7697
0 13090 9640 5602 2003
12619 10832 7669
0 12634 9394 5323 1917
18000 9500 6667
0 12446 8660 5319 1720
11857 8825 7023
0 11901 8518 5956 2341
14181 11335 8483 15996 14153 10227 6161 2057
0
0
0
0
0
0
0
0
13545 10812 9031
0 13562 9488 5788 2089
13567 11178 8003
0 13556 9612 5447 1828
0
0
0
0
0
0
0
0
14017 11558 10448
0 13993 9869 5812 1861
0
0 7031
0
0
0 6994 2466
0
0 4000
0
0
0 5640 2128
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 8152 6336
0
0 8157 5252 2047
0
0
0
0
0
0
0
0
12450 10461 6002
0 12196 9701 5082 1680
0
0
0
0
0
0
0
0
11949 10590 7462
0 11968 10195 5113 2062
12200 9825 5772
0 11623 9801 4920 2140
0 10000 6929
0
0 9269 5518 2315
12039 9192 6965
0 12034 8699 5257 1811
0
0 5500
0
0
0 4278 1990
10500 8589 6750
0 11680 8580 5861 2281
12125 9743 6049
0 11941 9449 5229 2273
0 8164 6902
0
0 8135 5973 2381
0
0
0
0
0
0
0
0
12419 10685 7784
0 12501 9065 5318 1690
0
0 4393
0
0
0 4391 2267
0
0 5636
0
0
0 5512 2659
0
0 4556
0
0
0 4453 2577
12000 8765 6571
0 11743 8616 5671 1862
0
0
0
0
0
0
0
0
122175
223305
345480
4515
1744
6259
19040
7851
26891
34229
20247
54476
45
5
50
4470
1739
6209
14525
6107
20632
15189
12396
27585
8024
7045
15069
79883
195993
275876
58769
22631
81400
192348
78656
271004
274628
145561
420189
778
76
854
57991
22555
80546
133579
56025
189604
82280
66905
149185
14508
14503
29011
705
70
5220
3418
1513
4635
3945
7378
15713
0
583
3165
4535
7530
7245
9118
6195
7700
11093
475
15890
5543
20278
48138
5088
11770
1600
28288
29138
20918
0
0
0
1
6
65
1596
226
434
1108
0
225
77
1549
796
2066
989
44
164
244
0
184
265
305
22
29
8
0
0
12
0
0
0
0
5
14
123
2211
273
855
2669
0
321
138
2348
1141
2769
1629
116
299
511
0
358
594
478
116
75
26
0
1
17
0
0
14
2
217
60
288
2585
380
1531
4317
0
346
180
2587
1328
2844
1976
178
386
635
0
399
611
569
923
159
58
49
11
50
2
0
0
0
0
1
20
517
57
94
51
0
84
16
539
353
845
263
3
27
41
0
13
29
59
0
3
1
0
0
2
0
0
0
0
1
5
45
1079
169
340
1057
0
141
61
1010
443
1221
726
41
137
203
0
171
236
246
22
26
7
0
0
10
0
0
0
0
4
8
58
615
47
421
1561
0
96
61
799
345
703
640
72
135
267
0
174
329
173
94
46
18
0
1
5
0
0
14
2
212
46
165
374
107
676
1648
0
25
42
239
187
75
347
62
87
124
0
41
17
91
807
84
32
49
10
33
2
0
30
2
333
115
209
214
191
281
464
0
8
6
32
87
2
51
19
17
44
0
18
0
115
1623
79
57
67
27
20
7
0
661
66
4670
3242
1015
1836
3374
5566
10932
0
228
2978
1917
6114
4399
7090
5998
7298
10414
475
15473
4931
19593
45592
4850
11656
1483
28249
29067
20909
0
1
0
18
87
972
24739
3212
6053
15605
0
3525
1149
24405
12722
32477
15019
617
2295
3508
0
2742
4070
4654
264
418
98
1
1
174
0
0
4
0
61
165
1602
31189
3668
10208
31068
0
4520
1768
32727
16209
39556
21511
1334
3610
6322
0
4588
7562
6414
1113
880
268
3
13
226
0
0
95
10
1377
466
2728
33653
4372
13830
40042
0
4688
2022
34284
17335
39998
23584
1711
4129
7133
0
4863
7670
7011
5247
1440
459
310
66
387
11
0
0
0
1
20
352
9273
978
1509
787
0
1507
284
9907
6448
15262
4740
57
471
710
0
241
564
1098
0
53
11
0
0
40
0
0
1
0
17
67
620
15466
2234
4544
14818
0
2018
865
14498
6274
17215
10279
560
1824
2798
0
2501
3506
3556
264
365
87
1
1
134
0
0
3
0
43
78
630
6450
456
4155
15463
0
995
619
8322
3487
7079
6492
717
1315
2814
0
1846
3492
1760
849
462
170
2
12
52
0
0
91
10
1316
301
1126
2464
704
3622
8974
0
168
254
1557
1126
442
2073
377
519
811
0
275
108
597
4134
560
191
307
53
161
11
0
66
5
697
255
482
489
413
468
785
0
19
13
76
169
5
100
42
38
97
0
40
0
264
3121
176
113
136
51
35
14
0
1000
0
18000
14500
14954
15501
14212
13947
14084
0
15667
14922
15755
15982
15720
15186
14023
13994
14377
0
14902
15358
15259
12000
14414
12250
1000
1000
14500
0
0
286887
10415
17087
22685
3018
7397
6672
5598
4118
260076
158826
226589
258921
54313
104513
67763
32332
8169
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
13016 10102
12976 10019
13005 10078
9196
9174
9190
5417
5397
5408
1808
2059
1925
9610
0
9511
9395
10889
10480
9718
9880
9905
0
10339
10078
10420
10109
10068
10140
10021
9773
10548
0
10597
10607
10192
9006
10035
9553
9055
9167
9417
0
0
6578
6674
6206
6535
6834
6594
6557
5359
5446
0
6629
6075
6527
6029
5893
5972
6110
5940
6532
0
6642
6292
6568
5122
6679
5948
6231
5354
4864
5196
0
2193
2224
2096
2216
2307
2281
2164
1664
1691
0
2302
2094
2389
1928
1946
1956
2195
2216
2200
0
2261
2137
2287
1923
2232
1988
2026
1879
1750
1953
0
15250 13261 11414 17996 14129 10156
5776
1984
4000
0
12200
11786
13024
14106
13436
11939
11640
0
14081
12812
13938
14206
14285
13205
11500
12074
12372
0
12816
12731
13418
9595
11733
10308
3000
13000
13294
0
0
8023 17289 12973
7189 15200 12970
7713 17080 12972
6786
5000
6346
7767
9472
13019
11505
9033
9275
0
13549
11233
13252
13053
14064
11935
9612
10697
11233
0
12188
12553
12322
5685
9057
7914
6327
6000
7740
5500
0
16056
0
16051
16856
17342
17935
17051
16073
15579
0
17933
17717
18369
18251
18060
17999
16613
17541
17175
0
18984
19375
18465
0
18129
17084
0
0
17862
0
0
13888
0
13171
13047
13748
14335
13219
13366
14020
0
14343
14067
14359
14160
14103
14165
13645
13361
13817
0
14597
14846
14465
12084
14169
13272
12277
12150
13968
0
0
APPENDIX II
Table A8 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ACCESSIBLE AREAS CURRENTLY UNDER FOREST
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
1163
0
0
0
0
0
0
0
0
1162
0
0
0
0
0
0
0
0
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
0
0
0
0
0
0 4228 1861
135
698
5098
975
1995
4208
2290
1748
1605
85
2640
1198
4743
0
0
1405
145
3
0
0
154
561
12
0
0
727
0
0
3487
324
7
1
0
631
945
13
2
0
1988
0
9
3940
507
15
48
2
1261
1113
15
18
1
2369
0
0
0
0
1
0
0
0
0
9
0
0
67
0
0
1405
145
2
0
0
154
561
3
0
0
660
0
0
2082
179
4
1
0
477
384
1
2
0
1261
0
9
453
183
8
47
2
630
168
2
16
1
381
0
11
126
68
8
114
4
109
157
8
19
3
98
135
578
1031
400
1971
4045
2284
377
335
62
2603
1194
2275
0
0
20235
1813
49
0
0
2003
7731
182
0
0
10645
0
0
42039
3477
90
13
0
6455
11491
190
17
0
24314
0
60
44883
4469
139
258
10
9970
12478
206
103
4
26781
0
0
0
0
21
0
0
0
0
142
0
0
1071
0
0
20235
1813
28
0
0
2003
7731
40
0
0
9574
0
0
21804
1664
41
13
0
4452
3760
8
17
0
13669
0
60
2844
992
49
245
10
3515
987
16
86
4
2467
0
27
260
136
18
200
7
215
311
17
37
6
211
27418
3007
7398
9298
77
2930
4391
1900
725
17290
42658
88086
99361
1234
41424
45428
11275
1445
14186 11907 10686 16026 14138 10346
5934
1993
Krasnodar Kray
12
1335
Stavropol Kray
12
20
Arkhangelsk oblast
12
11643
Astrakhan oblast
12
48
Belgorod oblast
12
73
Bryansk oblast
12
638
Vladimir oblast
12
995
Volgograd oblast
12
203
Vologda oblast
12
7190
Voronezh oblast
12
245
Nizhni Novgorod oblast12
3093
Nenets a.okr.
12
255
Ivanovo oblast
12
823
Kaliningrad oblast
12
115
Tver oblast
12
2510
Kaluga oblast
12
980
Kirov oblast
12
5580
Kostroma oblast
12
3073
Samara oblast
12
365
Kursk oblast
12
80
Komi-Permyak a.okr. 12
1720
Leningrad oblast
12
4215
Lipetsk oblast
12
80
Moscow oblast
12
1835
Murmansk oblast
12
2660
Novgorod oblast
12
3133
Orenburg oblast
12
53
Oryel oblast
12
53
Penza oblast
12
575
Perm oblast
12
5190
Pskov oblast
12
2053
Rostov oblast
12
18
Ryazan oblast
12
730
Saratov oblast
12
375
Smolensk oblast
12
563
Tambov oblast
12
255
Tula oblast
12
200
Ulyanovsk oblast
12
763
Yaroslavl oblast
12
783
Adigei Republic
12
153
Bashkortostan Republic12
2568
Daghestn Republic
12
240
Kabardino-Balkarian Republic
12
165
Kalmyk-Khalm-Tangch 12
Republic 3
Karelia Republic
12
6885
Komi Republic
12
10830
Mari-El Republic
12
878
Mordovian SSR
12
478
North-Ossetian SSR 12
135
Karachai-Cherkess Republic
12
473
Tatarstan Republic
12
533
Udmurt Republic
12
1400
Checheno-Ingush Republic
12
330
23
0
0
0
1
32
73
0
0
0
345
0
371
48
355
240
140
37
0
17
0
112
10
470
0
536
0
7
0
41
586
0
72
0
249
2
57
0
125
6
25
0
15
0
0
0
49
31
12
11
4
77
6
41
0
168
0
2
451
633
0
1585
0
1894
0
687
74
1310
625
961
810
0
39
192
636
19
1119
0
1691
0
27
12
466
1353
0
479
0
427
24
120
1
469
11
121
0
20
0
53
110
302
168
12
12
14
451
7
106
6
1161
0
10
558
758
7
4304
37
2290
0
723
90
2055
727
2432
2191
26
47
550
2004
26
1421
0
2508
1
34
90
1174
1684
2
539
8
446
86
127
42
664
15
273
6
24
0
195
255
469
234
23
13
84
749
14
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
3
0
0
0
0
0
3
3
0
0
1
15
0
0
0
1
32
73
0
0
0
345
0
371
48
355
240
140
37
0
17
0
112
10
470
0
536
0
7
0
41
586
0
72
0
249
2
57
0
125
5
25
0
12
0
0
0
49
31
9
8
4
77
5
18
0
168
0
1
419
560
0
1585
0
1549
0
316
26
955
385
821
773
0
22
192
524
9
649
0
1155
0
20
12
425
767
0
407
0
178
22
63
1
344
5
96
0
5
0
53
110
253
137
0
1
10
374
1
65
6
993
0
8
107
125
7
2719
37
396
0
36
16
745
102
1471
1381
26
8
358
1368
7
302
0
817
1
7
78
708
331
2
60
8
19
62
7
41
195
4
152
6
4
0
142
145
167
66
11
1
70
298
7
48
1
801
0
11
2
89
5
517
51
142
0
17
2
41
14
1202
286
68
1
345
897
20
29
0
141
3
0
143
293
54
4
20
27
12
87
0
175
4
6
126
7
4
0
322
508
119
32
3
0
83
99
10
1181
13
9673
47
52
78
148
191
2369
157
662
255
82
22
413
238
1947
596
271
33
824
1314
34
385
2660
483
49
18
342
3723
315
12
171
341
105
82
72
546
115
132
2168
228
138
2
6369
10068
289
210
109
459
365
552
307
361
0
0
0
9
465
959
0
0
0
4591
0
4826
702
4500
3190
1797
476
0
236
0
1369
129
6139
0
6750
0
94
0
505
7581
0
994
0
3262
23
774
0
1563
77
318
1
199
0
0
0
636
402
173
163
52
970
80
544
0
1369
0
19
4789
6336
0
13722
0
19674
0
7801
977
13211
6954
9031
7545
0
453
1619
5842
218
12246
0
17182
0
300
131
4234
14650
0
4966
0
4924
243
1393
8
4681
129
1201
1
250
0
419
909
3076
1669
174
176
146
4353
85
998
38
6252
0
69
5450
7044
34
27801
229
21989
0
8005
1078
17289
7566
16947
15278
153
500
3514
12996
260
13922
0
21596
5
346
574
8073
16471
12
5314
46
5033
607
1436
246
5747
156
2060
39
276
0
1144
1643
4129
2053
242
180
544
6020
133
151
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
12
0
0
44
0
0
0
0
0
52
54
0
0
19
210
0
0
0
9
465
959
0
0
0
4591
0
4826
702
4500
3190
1797
476
0
236
0
1369
129
6139
0
6750
0
94
0
505
7581
0
994
0
3262
23
774
0
1563
65
318
1
155
0
0
0
636
402
121
109
52
970
61
183
0
1369
0
10
4324
5377
0
13722
0
15083
0
2975
275
8711
3764
7234
7069
0
217
1619
4473
89
6107
0
10432
0
206
131
3729
7069
0
3972
0
1662
220
619
8
3118
52
883
0
51
0
419
909
2440
1267
1
13
94
3383
5
454
38
4883
0
50
661
708
34
14079
229
2315
0
204
101
4078
612
7916
7733
153
47
1895
7154
42
1676
0
4414
5
46
443
3839
1821
12
348
46
109
364
43
238
1066
27
859
38
26
0
725
734
1053
384
68
4
398
1667
48
117
2
1321
0
22
4
167
8
904
106
268
0
31
4
77
28
2090
533
129
2
583
1657
39
55
0
260
5
0
273
547
100
9
43
53
22
171
0
334
8
15
225
15
8
0
575
845
260
64
7
0
156
200
22
15696
0
0
0
9000
14531
13137
0
0
0
13307
0
13008
14625
12676
13292
12836
12865
0
13882
0
12223
12900
13062
0
12593
0
13429
0
12317
12937
0
13806
0
13100
11500
13579
0
12504
12833
12720
1000
13267
0
0
0
12980
12968
14417
14818
13000
12597
13333
7030
6390
4918
0
6152
6199
5676
4790
5178
6276
5851
0
5642
6201
5471
5969
5383
5601
5773
5947
5290
5228
5774
5546
0
5402
5195
6082
5702
5422
5504
6532
5815
6002
5667
5844
6024
5765
5459
6316
5637
6747
6604
0
5116
5073
6298
5795
6397
5860
5725
5592
6606
2431
2169
1648
0
2050
2053
1888
1760
1748
2062
1894
0
1861
2068
1866
1933
1739
1865
1904
2069
1689
1847
1967
1878
0
1846
1717
0
1911
1869
1834
2177
2161
2011
1883
1969
1575
1913
1884
2488
1794
2218
2207
0
1789
1664
2174
1978
2141
1870
1871
2018
2225
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
0
0
14402
12503
16333
0
0
13006
13781
15167
0
0
14642
0
0
12056
10731
12857
13000
0
10230
12160
14615
8500
0
12230
13268
0
8149
0
9500
10619
10009
0
8657
0
10388
0
11355
13203
10085
11126
9398
9315
0
11615
8432
9186
11474
10944
0
10161
0
11111
10917
9086
10828
0
10367
0
11532
10125
11608
8000
9981
11727
9926
1000
12500
0
7906
8264
10185
9935
14500
14667
10429
9652
12143
0
0
0
0
6667
0
0 8717
11392
0 14397 10474
8815
0 12468 9283
9267 18057 13956 9797
5375
0 12906 8937
5000
0
0
0
7906
0 12992 9336
11211
0 13780 9781
13733 16123 12881 10077
5722
0
0 8105
4000
0
0
0
11305 15963 14504 10839
9415
6333
5385
0
6900
9767
9293
4857
6459
6189
9602
0
11072
11978
8413
10407
6968
6973
5885
10638
6389
6485
10000
9797
0
8611
5000
10176
6378
6876
9781
6000
9859
5750
11285
7058
11307
5857
8655
10400
7546
6500
11500
0
5867
6443
8804
8774
10522
13846
6476
8037
9500
19591
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17624
0
0
16608
0
0
0
0
0
17058
16622
0
0
17156
14259
0
0
0
12837
14519
13069
0
0
0
13322
0
13007
14541
12662
13290
12875
12726
0
14162
0
12277
13470
13064
0
12599
0
14491
0
12280
12945
0
13747
0
13095
12160
13558
0
12548
14030
12600
12360
13149
0
0
0
12895
12793
13204
12996
12225
12639
13399
9973
0
8138
0
9348
10328
9596
0
8657
0
9738
0
9401
10386
9121
9775
8815
9147
0
10079
8417
8540
9927
9414
0
9030
0
10208
10807
8765
9218
0
9752
0
9360
10056
9764
10024
9070
10081
9196
0
9863
0
7974
8268
9658
9224
10691
9979
9385
9057
10135
0
6968
6272
5425
6217
5222
5349
5577
5887
6886
5367
6075
6471
1914
2433
2057
2015
2139
1749
1898
1964
1981
2290
1978
2016
2159
APPENDIX II
Table A8 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - ACCESSIBLE AREAS CURRENTLY UNDER FOREST
ADM REG NAME
197
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Chuvash Republic
12
Altai Kray
12
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
643
5
29
66
0
5
24
37
135
441
65
298
508
0
65
233
210
270
2920
175
386
728
0
175
211
342
401
1791
2193
4198
6076
0
2193
2005
1878
790
1693
0
11
40
0
0
11
29
9
1645
0
91
243
0
0
91
152
15
12555
17
259
729
0
17
242
470
544
11282
197
2225
5034
0
197
2028
2809
1270
5300
48
191
434
5
43
143
243
116
4750
682
2152
3648
73
609
1470
1496
239
988
0
0
0
0
0
0
0
0
987
0
0
0
0
0
0
0
0
6658
109
290
456
0
109
181
166
132
6067
1473
3181
4131
0
1473
1708
950
267
6083
72
338
1041
0
72
266
703
628
4413
962
3471
7235
0
962
2509
3764
1126
5605
0
0
0
0
0
0
0
0
5605
0
0
0
0
0
0
0
0
750
99
213
266
0
99
114
53
25
459
1396
2531
2839
0
1396
1135
308
46
14285
0
0
56
0
0
0
56
120
14109
0
0
394
0
0
0
394
299
413
0
0
0
0
0
0
0
0
412
0
0
0
0
0
0
0
0
2035
0
0
0
0
0
0
0
0
2035
0
0
0
0
0
0
0
0
873
0
0
0
0
0
0
0
0
872
0
0
0
0
0
0
0
0
2875
0
192
523
0
0
192
331
172
2181
0
1562
3300
0
0
1562
1738
353
2220
0
0
0
0
0
0
0
0
2220
0
0
0
0
0
0
0
0
483
16
40
93
0
16
24
53
43
347
193
426
710
0
193
233
284
74
2635
0
0
0
0
0
0
0
0
2635
0
0
0
0
0
0
0
0
1660
59
252
572
0
59
193
320
202
886
712
2600
4287
0
712
1888
1687
434
1958
2
140
642
0
2
138
502
265
1051
24
1436
3935
0
24
1412
2499
545
4178
0
4
14
0
0
4
10
27
4134
0
40
96
0
0
40
56
62
9003
271
1620
3695
0
271
1349
2075
565
4743
3260
14931
25834
0
3260
11671
10903
1008
155
0
0
0
0
0
0
0
1
154
0
0
1
0
0
0
1
3
4765
1
467
1450
0
1
466
983
578
2737
14
3914
9692
0
14
3900
5778
1321
1593
20
83
529
0
20
63
446
214
850
237
848
3242
0
237
611
2394
480
4878
0
99
201
0
0
99
102
68
4608
0
805
1397
0
0
805
592
152
1173
0
0
0
0
0
0
0
0
1172
0
0
0
0
0
0
0
0
1520
8
37
115
0
8
29
78
53
1352
96
356
762
0
96
260
406
90
3128
0
0
4
0
0
0
4
18
3106
0
0
20
0
0
0
20
45
3718
0
0
4
0
0
0
4
20
3693
0
0
27
0
0
0
27
49
2858
0
0
8
0
0
0
8
8
2842
0
0
36
0
0
0
36
19
1603
0
5
16
0
0
5
11
12
1575
0
41
114
0
0
41
73
24
33823
0
0
0
0
0
0
0
0
33822
0
0
0
0
0
0
0
0
90232
144384
234616
4190
897
5087
17625
4627
22252
31354
11616
42970
19
5
24
4171
892
5063
13435
3730
17165
13729
6989
20718
7006
4221
11227
51856
128535
180391
54431
11439
65870
177948
44808
222756
252045
83053
335098
332
73
405
54099
11366
65465
123517
33369
156886
74097
38245
112342
12634
8711
21345
158
18
938
695
1170
4095
2870
5498
10550
0
395
2828
3683
4348
4985
6900
5803
6030
6103
260
4970
2490
12718
5360
1453
770
23
713
2808
248
0
0
0
0
0
43
1566
199
363
473
0
160
70
1502
298
1841
766
43
116
67
0
127
122
127
13
8
1
0
0
11
0
0
0
0
1
2
93
2160
240
729
1444
0
233
125
2261
479
2431
1265
112
210
167
0
255
261
197
63
23
4
0
0
15
0
0
5
0
40
11
232
2492
293
936
2114
0
255
160
2480
589
2496
1562
171
270
224
0
293
266
248
155
33
6
0
0
19
0
0
0
0
0
0
12
512
51
87
43
0
50
15
532
109
782
195
3
19
8
0
8
13
26
0
1
0
0
0
2
0
0
0
0
0
0
31
1054
148
276
430
0
110
55
970
189
1059
571
40
97
59
0
119
109
101
13
7
1
0
0
9
0
0
0
0
1
2
50
594
41
366
971
0
73
55
759
181
590
499
69
94
100
0
128
139
70
50
15
3
0
0
4
0
0
5
0
39
9
139
332
53
207
670
0
22
35
219
110
65
297
59
60
57
0
38
5
51
92
10
2
0
0
4
0
0
10
1
55
23
179
153
98
24
109
0
8
6
31
49
2
40
18
11
23
0
15
0
74
137
13
5
1
0
2
0
0
142
16
843
660
760
1450
2479
4537
8326
0
132
2662
1172
3710
2487
5298
5613
5748
5856
260
4662
2222
12396
5069
1407
759
22
711
2787
247
0
0
0
3
7
619
24306
2837
5100
6645
0
2475
1033
23687
4644
29030
11585
597
1638
968
0
1894
1860
1947
159
114
22
1
1
155
0
0
1
0
10
25
1163
30542
3232
8711
16225
0
3234
1583
31603
6471
34959
16645
1287
2557
2036
0
3256
3325
2649
592
262
50
2
5
196
0
0
35
3
271
85
2112
32733
3580
9953
20112
0
3381
1799
33044
7138
35344
18416
1649
2913
2405
0
3510
3361
2983
1081
322
60
4
7
220
0
0
0
0
0
1
202
9190
872
1404
676
0
899
263
9763
1974
14110
3507
56
339
135
0
154
255
482
0
13
3
0
0
33
0
0
0
0
3
6
417
15116
1965
3696
5969
0
1576
770
13924
2670
14920
8078
541
1299
833
0
1740
1605
1465
159
101
19
1
1
122
0
0
1
0
7
18
544
6236
395
3611
9580
0
759
550
7916
1827
5929
5060
690
919
1068
0
1362
1465
702
433
148
28
1
4
41
0
0
34
3
261
60
949
2191
348
1242
3887
0
147
216
1441
667
385
1771
362
356
369
0
254
36
334
489
60
10
2
2
24
0
0
23
2
123
51
412
352
215
43
199
0
19
12
75
96
4
79
40
25
50
0
34
0
168
257
29
10
1
0
4
0
0
98880
7916
12770
15350
2468
5448
4854
2580
1087
82433
121327
170621
186521
44331
76996
49294
15900
2323
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
13000 10276 7697
0 13090 9640 5602 2003
12531 10876 8346
0 12544 9508 5500 1968
0 8273 6075
0 12474 8581 5307 1718
11588 8591 6905
0 11923 8366 5978 2334
14208 11267 8406 16004 14177 10286 6151 2055
0
0
0
0
0
0
0
0
13514 10969 9059
0 13531 9459 5711 2022
13361 10269 6950
0 13320 9416 5352 1792
0
0
0
0
0
0
0
0
14101 11883 10673
0 14068 9974 5778 1844
0
0 7036
0
0
0 7045 2482
0
0
0
0
0
0
0 2698
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 8135 6310
0
0 8130 5257 2058
0
0
0
0
0
0
0
0
12063 10650 7634
0 12166 9694 5403 1734
0
0
0
0
0
0
0
0
12068 10317 7495
0 12092 9786 5272 2148
12000 10257 6129
0 11603 10213 4980 2057
0 10000 6857
0
0 9269 5512 2313
12030 9217 6992
0 12037 8651 5255 1785
0
0 1000
0
0
0 4296 2521
14000 8381 6684
0 11692 8364 5876 2286
11850 10217 6129
0 12054 9633 5371 2246
0 8131 6950
0
0 8130 5804 2215
0
0
0
0
0
0
0
0
12000 9622 6626
0 12411 8941 5229 1698
0
0 5000
0
0
0 5005 2537
0
0 6750
0
0
0 6038 2486
0
0 4500
0
0
0 4449 2508
0 8200 7125
0
0 8315 6351 2110
0
0
0
0
0
0
0
0
12991 10096
12753 9684
12949 10011
9194
8946
9140
5397
5472
5422
1803
2064
1901
9347
0
9677
9406
10931
10504
9685
9877
9869
0
10392
10087
10432
10104
10054
10132
10020
9743
10635
0
10678
10524
10069
8748
9923
9495
8717
9075
9792
0
0
6513
6639
6729
6390
6830
6590
6595
5986
5803
0
6620
6096
6573
6038
5883
5972
6111
5931
6433
0
6683
6493
6543
5335
6260
6092
6269
6252
6122
0
0
2175
2215
2236
2175
2311
2302
2195
1769
1825
0
2306
2106
2396
1963
1949
1965
2193
2232
2207
0
2267
2137
2282
1874
2228
2057
2118
1977
2160
2554
0
15327 13361 12151 17962 14133 10155
6163
2137
0
0
3000
7000
14395
15521
14256
14050
14049
0
15469
14757
15770
15584
15769
15124
13884
14121
14448
0
14913
15246
15331
12231
14250
22000
1000
1000
14091
0
0
1000
0
10000
12500
12505
14140
13467
11949
11236
0
13880
12664
13977
13509
14381
13158
11491
12176
12192
0
12769
12739
13447
9397
11391
12500
2000
5000
13067
0
0
8039 17474 12970
7150 14600 12742
7798 16875 12930
7000
3000
6775
7727
9103
13135
12218
10634
9514
0
13259
11244
13324
12119
14160
11790
9643
10789
10737
0
11980
12635
12028
6974
9758
10000
4000
7000
11579
0
0
16056
0
0
17484
17286
17935
17099
16076
15569
0
17906
17677
18366
18181
18044
17999
16607
17455
17976
0
19066
18997
18626
0
17258
17506
0
0
17776
0
0
13452
0
13069
13241
13555
14347
13258
13379
13874
0
14386
14040
14362
14123
14092
14153
13637
13403
14238
0
14564
14681
14539
12053
13839
13118
12204
12150
13933
0
0
APPENDIX II
Table A9 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - EXCLUDING CULTIVATED AREAS, URBAN AREAS AND AREAS CURRENTLY UNDER FOREST
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
147800
0
0
53
0
0
0
53
190
147557
Average annual biomass increments (000tons) --------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
0
0
235
0
0
0
235
508
1788
4578
1680
370
1515
214330
12170
210
1463
10
2655
40375
640
0
0
209
58
12
5
0
60
336
2
0
0
109
0
0
1068
165
34
30
2
115
807
3
0
0
294
2
285
1244
207
58
2659
40
152
1027
5
2
8
375
0
0
0
0
10
0
0
0
0
1
0
0
11
0
0
209
58
2
5
0
60
336
1
0
0
98
0
0
859
107
22
25
2
55
471
1
0
0
185
2
285
176
42
24
2629
38
37
220
2
2
8
81
12
390
24
26
30
2798
28
17
124
2
5
2
26
1774
3595
412
137
1427
208873
12102
41
311
4
2648
40366
238
0
0
3124
701
207
60
0
805
4580
22
0
0
1521
0
0
12327
1701
449
298
18
1325
9169
29
0
0
3477
10
1957
13458
1959
611
13966
266
1540
10467
44
14
49
4019
0
0
0
0
179
0
0
0
0
12
0
0
181
0
0
3124
701
28
60
0
805
4580
10
0
0
1340
0
0
9203
1000
242
238
18
520
4589
7
0
0
1956
10
1957
1131
258
162
13668
248
215
1298
15
14
49
542
24
895
52
60
69
4897
57
34
248
4
9
4
60
281784
791
2518
6064
22
769
1727
3546
3484
271928
11020
28793
48360
372
10648
17773
19567
6413
Krasnodar Kray
12
625
Stavropol Kray
12
965
Arkhangelsk oblast
12
11818
Astrakhan oblast
12
4380
Belgorod oblast
12
0
Bryansk oblast
12
0
Vladimir oblast
12
13
Volgograd oblast
12
1890
Vologda oblast
12
1253
Voronezh oblast
12
258
Nizhni Novgorod oblast12
298
Nenets a.okr.
12
15018
Ivanovo oblast
12
25
Kaliningrad oblast
12
30
Tver oblast
12
118
Kaluga oblast
12
65
Kirov oblast
12
235
Kostroma oblast
12
253
Samara oblast
12
5
Kursk oblast
12
0
Komi-Permyak a.okr. 12
170
Leningrad oblast
12
800
Lipetsk oblast
12
0
Moscow oblast
12
193
Murmansk oblast
12
6555
Novgorod oblast
12
233
Orenburg oblast
12
2480
Oryel oblast
12
0
Penza oblast
12
0
Perm oblast
12
325
Pskov oblast
12
265
Rostov oblast
12
453
Ryazan oblast
12
405
Saratov oblast
12
615
Smolensk oblast
12
0
Tambov oblast
12
0
Tula oblast
12
13
Ulyanovsk oblast
12
18
Yaroslavl oblast
12
83
Adigei Republic
12
103
Bashkortostan Republic12
808
Daghestn Republic
12
4188
Kabardino-Balkarian Republic
12
663
Kalmyk-Khalm-Tangch Republic
12
6183
Karelia Republic
12
3005
Komi Republic
12
8200
Mari-El Republic
12
100
Mordovian SSR
12
125
North-Ossetian SSR 12
378
Karachai-Cherkess Republic
12
623
Tatarstan Republic
12
8
Udmurt Republic
12
3
Checheno-Ingush Republic
12
960
Chuvash Republic
12
0
Altai Kray
12
4503
24
2
0
0
0
0
2
0
0
0
3
0
2
8
19
14
0
6
0
0
0
8
0
55
0
47
0
0
0
0
58
0
35
0
0
0
4
0
18
6
1
2
10
0
0
0
5
11
28
5
0
0
16
0
238
33
4
33
0
0
0
11
0
157
0
179
0
21
21
61
32
11
60
0
0
15
99
0
122
0
186
0
0
0
23
195
0
259
0
0
0
8
0
50
9
4
5
11
0
1
50
61
69
35
8
0
0
21
0
574
174
25
89
0
0
0
13
0
842
32
217
0
24
28
97
33
65
182
0
0
63
466
0
144
0
216
0
0
0
87
234
27
290
1
0
0
8
0
64
11
18
105
13
0
14
89
83
78
44
10
1
1
108
0
1446
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
2
0
0
0
0
0
13
1
0
0
5
0
0
19
2
0
0
0
0
2
0
0
0
3
0
2
8
19
14
0
6
0
0
0
8
0
55
0
47
0
0
0
0
58
0
35
0
0
0
4
0
18
5
1
2
8
0
0
0
5
11
15
4
0
0
11
0
238
9
2
33
0
0
0
9
0
157
0
176
0
19
13
42
18
11
54
0
0
15
91
0
67
0
139
0
0
0
23
137
0
224
0
0
0
4
0
32
3
3
3
1
0
1
50
56
58
7
3
0
0
5
0
336
141
21
56
0
0
0
2
0
685
32
38
0
3
7
36
1
54
122
0
0
48
367
0
22
0
30
0
0
0
64
39
27
31
1
0
0
0
0
14
2
14
100
2
0
13
39
22
9
9
2
1
1
87
0
872
78
33
308
0
0
0
1
0
129
35
29
0
1
0
4
1
78
25
0
0
56
194
0
4
0
11
4
0
0
63
10
25
7
3
0
0
0
2
0
1
46
73
2
0
37
111
1
1
4
2
1
0
40
0
395
373
907
11407
4380
0
0
0
1890
282
191
51
14997
1
1
17
30
92
46
5
0
52
141
0
45
6555
4
2476
0
0
175
20
400
108
611
0
0
5
16
19
90
743
4001
647
6182
2947
7999
16
46
329
609
5
1
813
0
2661
347
25
0
0
0
0
20
0
0
0
48
0
24
110
244
194
0
76
0
0
0
92
0
737
0
602
0
0
0
0
747
0
475
0
0
0
47
0
223
85
12
29
138
0
0
0
70
145
419
81
0
0
221
0
3010
429
46
271
0
0
0
103
0
1351
0
1759
0
203
245
628
372
88
569
0
0
124
863
0
1387
0
1872
0
0
0
188
1995
0
2673
0
0
0
86
0
511
120
42
61
147
0
5
408
627
683
488
112
1
4
269
0
6124
1433
178
550
0
0
0
113
0
4915
193
1980
0
219
290
828
380
357
1259
0
0
377
2769
0
1506
0
2037
1
0
0
542
2206
150
2857
4
0
0
86
0
586
130
122
661
162
0
69
606
755
736
548
126
7
9
790
0
10692
86
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
21
0
4
29
0
0
0
0
0
219
24
0
0
77
0
0
261
22
0
0
0
0
20
0
0
0
48
0
24
110
244
194
0
76
0
0
0
92
0
737
0
602
0
0
0
0
747
0
475
0
0
0
47
0
223
64
12
25
109
0
0
0
70
145
200
57
0
0
144
0
3010
82
21
271
0
0
0
83
0
1351
0
1711
0
179
135
384
178
88
493
0
0
124
771
0
650
0
1270
0
0
0
188
1248
0
2198
0
0
0
39
0
288
35
30
32
9
0
5
408
557
538
69
31
1
4
48
0
3114
1004
132
279
0
0
0
10
0
3564
193
221
0
16
45
200
8
269
690
0
0
253
1906
0
119
0
165
1
0
0
354
211
150
184
4
0
0
0
0
75
10
80
600
15
0
64
198
128
53
60
14
6
5
521
0
4568
187
75
506
0
0
0
1
0
226
71
54
0
1
1
8
1
131
47
1
0
97
349
0
8
0
20
5
0
0
113
19
42
14
5
0
0
0
3
0
2
81
156
4
0
61
180
2
2
10
5
2
0
85
0
729
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be assumed: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
0
0
4434
0
0
0
4390
2677
0
0
14947
12086
17250
12000
0
13417
13631
11000
0
0
13954
0
0
11542
10309
13206
9933
9000
11522
11362
9667
0
0
11827
13932 11435
14458
12500
0
0
0
0
10000
0
0
0
16000
0
12000
13750
12842
13857
0
12667
0
0
0
11500
0
13400
0
12809
0
0
0
0
12879
0
13571
0
0
0
11750
0
12389
14167
12000
14500
13800
0
0
0
14000
13182
14964
16200
0
0
13813
0
12647
13000
11500
8212
0
0
0
9364
0
8605
0
9827
0
9667
11667
10295
11625
8000
9483
0
0
8267
8717
0
11369
0
10065
0
0
0
8174
10231
0
10320
0
0
0
10750
0
10220
13333
10500
12200
13364
0
5000
8160
10279
9899
13943
14000
1000
4000
12810
0
10669
5000
0
0
0
6867
0
0
8791
10818
0 14920 10716
9464
0 12092
9324
10534 17143 13212 11173
5252
0 12659
9368
6650
0
0
9297
10132
0 13386
9495
10192
0 13620
9736
8800 16649 16650 11117
7000
0
0
0
6125
0
0
0
10717 15892 13619 10582
6180
6857
6428
6186
6769
5199
6536
5824
5912
6916
5590
6500
6730
7975 16909 13847 10291
5518
1841
7128
6324
4942
0
0
0
5752
0
5205
6083
5827
0
5689
6102
5545
5811
5001
5667
0
0
5278
5197
0
5445
0
5437
4024
0
0
5517
5397
5509
5863
4662
0
0
0
0
5387
5787
5810
5991
6351
0
4859
5012
5956
5717
6421
6531
5427
5168
5968
0
5236
2389
2255
1642
0
0
0
1917
0
1752
2045
1876
0
1901
2035
1959
1936
1677
1883
1532
0
1741
1801
0
2053
0
1826
1330
0
0
1796
1833
1705
2102
1560
0
0
0
1528
1821
2149
1771
2133
2174
0
1649
1623
2134
2314
2151
2218
1806
0
2136
0
1844
8236
7120
6180
0
0
0
8692
0
5837
6031
9124
0
9125
10357
8536
11515
5492
6918
0
0
5984
5942
0
10458
0
9431
1000
0
0
6230
9427
5556
9852
4000
0
0
10750
0
9156
11818
6778
6295
12462
0
4929
6809
9096
9436
12455
12600
7000
9000
7315
0
7394
17750
15904
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
17733
0
16946
16449
0
0
0
0
0
17003
16574
0
0
16698
0
0
13564
13148
0
0
0
0
13421
0
0
0
13948
0
13284
14311
12716
13421
0
12615
0
0
0
12162
0
13493
0
12726
0
0
0
0
12797
0
13737
0
0
0
13373
0
12535
13864
12606
13562
12861
0
0
0
13938
13025
13603
13090
0
0
13242
0
12672
9561
10424
8188
0
0
0
9586
0
8618
0
9705
0
9521
10171
9235
9601
8426
9152
0
0
8446
8502
0
9669
0
9125
0
0
0
8118
9102
0
9809
0
0
0
9566
0
9008
9921
8636
9886
10393
0
7740
8098
9866
9255
9901
10028
9069
8615
10237
0
9262
1913
2297
2144
2303
2296
1750
2028
2061
2001
2290
1866
2161
2285
APPENDIX II
Table A9 PRODUCTION POTENTIALS FOR BIOMASS PLANTATION FORESTRY SPECIES - EXCLUDING CULTIVATED AREAS, URBAN AREAS AND AREAS CURRENTLY UNDER FOREST
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
231
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
13
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Shanghai
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
4118
1
6
9
0
1
5
3
1
4107
5383
20
158
456
0
20
138
298
183
4744
1490
76
222
487
0
76
146
265
63
940
71523
0
0
0
0
0
0
0
0
71522
18580
147
1073
1543
0
147
926
470
582
16456
6033
322
680
1416
0
322
358
736
508
4109
9323
0
0
0
0
0
0
0
0
9322
1318
218
652
808
0
218
434
156
30
479
8388
0
0
21
0
0
0
21
24
8343
350
0
0
1
0
0
0
1
0
349
9120
0
0
0
0
0
0
0
0
9097
25808
0
0
0
0
0
0
0
0
25807
925
0
15
33
0
0
15
18
8
885
60873
0
0
0
0
0
0
0
0
60847
2543
9
46
444
0
9
37
398
319
1781
31205
0
0
0
0
0
0
0
0
31205
8383
171
749
2300
0
171
578
1551
648
5434
5148
6
215
1722
0
6
209
1507
372
3054
973
0
0
0
0
0
0
0
0
964
2898
25
616
1503
0
25
591
887
183
1212
1038
0
0
4
0
0
0
4
30
1004
10153
1
356
1717
0
1
355
1361
619
7816
7145
36
421
3027
0
36
385
2606
720
3398
20210
0
101
656
0
0
101
555
520
19034
41490
0
0
0
0
0
0
0
0
41482
1518
42
62
99
0
42
20
37
287
1132
11328
0
0
63
0
0
0
63
137
11127
10333
0
0
10
0
0
0
10
58
10264
5498
0
0
1
0
0
0
1
2
5494
1360
1
32
128
0
1
31
96
100
1131
107800
0
0
0
0
0
0
0
0
107782
Average annual biomass increments (000tons) --------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
18
61
78
0
18
43
17
2
240
1458
3220
0
240
1218
1762
429
1080
2565
4203
3
1077
1485
1638
130
0
0
0
0
0
0
0
0
1951
10791
13685
0
1951
8840
2894
1358
4350
7829
11841
0
4350
3479
4012
940
0
0
0
0
0
0
0
0
3039
7308
8229
0
3039
4269
921
62
0
0
127
0
0
0
127
53
0
0
4
0
0
0
4
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
127
216
0
0
127
89
14
0
0
0
0
0
0
0
0
108
461
2456
0
108
353
1995
531
0
0
0
0
0
0
0
0
2031
8084
15889
0
2031
6053
7805
1364
71
2047
9410
0
71
1976
7363
801
0
0
0
0
0
0
0
1
297
5407
10008
0
297
5110
4601
349
0
0
18
0
0
0
18
56
7
3255
10956
0
7
3248
7701
1420
423
4052
17419
0
423
3629
13367
1698
0
819
3789
0
0
819
2970
1289
0
0
0
0
0
0
0
0
524
707
912
0
524
183
205
484
0
0
274
0
0
0
274
307
0
0
53
0
0
0
53
160
0
0
5
0
0
0
5
6
12
286
815
0
12
274
529
183
0
0
0
0
0
0
0
0
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
18000 10167
8667
0 12446
8831
5367
1807
12000
9228
7061
0 11896
8834
5910
2349
14175 11544
8627 15826 14091 10163
6187
2060
0
0
0
0
0
0
0
0
13272 10057
8869
0 13308
9551
6157
2333
13509 11513
8362
0 13530
9727
5455
1849
0
0
0
0
0
0
0
0
13940 11209 10184
0 13941
9832
5903
2043
0
0
6048
0
0
0
6100
2233
0
0
4000
0
0
0
5726
1932
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
8467
6545
0
0
8583
5081
1683
0
0
0
0
0
0
0
0
12000 10022
5532
0 12346
9657
5017
1668
0
0
0
0
0
0
0
0
11877 10793
6908
0 11869 10469
5032
2106
11833
9521
5465
0 11643
9473
4884
2154
0
0
0
0
0 10655
7072
2488
11880
8778
6659
0 12078
8641
5187
1908
0
0
4500
0
0
0
4275
1864
7000
9143
6381
0 11656
9138
5659
2293
11750
9625
5755
0 11743
9415
5130
2359
0
8109
5776
0
0
8103
5347
2480
0
0
0
0
0
0
0
0
12476 11403
9212
0 12537
9231
5503
1687
0
0
4349
0
0
0
4353
2237
0
0
5300
0
0
0
5390
2739
0
0
5000
0
0
0
4480
2814
12000
8938
6367
0 11743
8694
5497
1819
0
0
0
0
0
0
0
0
75204
496758
571962
389
1313
1702
1854
5978
7832
3996
17894
21890
27
0
27
362
1313
1675
1465
4665
6130
2142
11916
14058
1420
5789
7209
69725
472982
542707
5211
17161
22372
18730
61381
80111
30537
124299
154836
463
3
466
4748
17158
21906
13519
44220
57739
11807
62918
74725
2575
12367
14942
673
78
6618
6105
515
1193
1468
2573
9320
0
275
500
1465
4710
5280
4623
540
2330
0
848
24765
6493
11850
90058
9673
31640
3505
153305
106460
69645
10
0
0
2
11
28
64
34
84
1190
0
103
10
79
684
357
349
2
62
335
0
127
273
239
40
34
9
0
0
1
0
0
0
0
8
25
38
106
44
150
2322
0
139
19
141
910
558
583
5
116
601
0
217
632
389
188
93
32
0
1
3
0
0
9
3
241
86
69
157
125
816
3871
0
142
26
168
1018
573
655
8
152
698
0
227
659
442
1269
218
84
116
20
37
2
0
0
0
0
2
10
13
8
7
8
0
56
2
15
336
95
98
0
11
84
0
24
27
42
0
3
1
0
0
0
0
0
0
0
2
9
18
51
26
77
1182
0
47
8
64
348
262
251
2
51
251
0
103
246
197
40
31
8
0
0
1
0
0
0
0
6
14
10
42
10
66
1132
0
36
9
62
226
201
234
3
54
266
0
90
359
150
148
59
23
0
1
2
0
0
9
3
233
61
31
51
81
666
1549
0
3
7
27
108
15
72
3
36
97
0
10
27
53
1081
125
52
116
19
34
2
0
21
3
369
165
36
74
116
344
547
0
0
1
1
51
2
15
1
8
29
0
5
0
56
2301
138
102
162
65
22
9
0
642
72
6008
5855
410
960
1226
1412
4902
0
132
473
1297
3641
4705
3953
531
2171
0
847
24533
5833
11351
86489
9316
31454
3227
153220
106401
69633
10
1
0
23
145
425
957
457
1140
16929
0
1669
144
1191
11085
5458
5340
26
869
4813
0
1937
4212
3629
483
505
115
0
0
23
0
0
5
0
81
272
528
1373
559
1797
28129
0
2037
230
1821
13372
7503
7727
59
1395
7598
0
2876
8025
5167
1835
1095
339
1
9
39
0
0
64
20
1500
669
740
1711
1094
5194
36328
0
2060
274
1983
14024
7595
8157
77
1609
8243
0
2938
8194
5514
7412
1933
645
706
104
198
13
0
0
0
1
31
175
241
127
115
126
0
1009
31
273
6149
1733
1769
1
190
1418
0
441
531
774
0
60
13
0
0
8
0
0
1
0
22
114
250
716
330
1025
16803
0
660
113
918
4936
3725
3571
25
679
3395
0
1496
3681
2855
483
445
102
0
0
15
0
0
4
0
58
127
103
416
102
657
11200
0
368
86
630
2287
2045
2387
33
526
2785
0
939
3813
1538
1352
590
224
1
9
16
0
0
59
20
1419
397
212
338
535
3397
8199
0
23
44
162
652
92
430
18
214
645
0
62
169
347
5577
838
306
705
95
159
13
0
46
6
764
366
82
166
249
568
913
0
1
2
1
96
3
29
2
17
64
0
11
0
128
4574
306
200
326
119
38
18
0
1000
0
11500
13182
15179
14953
13441
13571
14226
0
16204
14400
15076
16206
15289
15301
13000
14016
14367
0
15252
15429
15184
12075
14853
12778
0
0
23000
0
0
556518
4117
7320
11891
842
3275
3203
4571
4643
540704
61576
93872
118999
15216
46360
32296
25127
9095
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be assumed: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
13396 10102
13068 10267
13143 10228
9228
9479
9419
5512
5280
5315
1813
2136
2073
9652
0
9446
9406
10473
9868
9806
9900
9898
0
10114
10024
10181
10120
10178
10199
10098
9820
10455
0
10451
10620
10262
9160
10067
9543
8930
9291
8664
0
0
6611
6681
6095
6514
6841
6588
6563
5102
5292
0
6626
5973
6016
6024
5973
6002
6140
5958
6622
0
6310
6154
6536
5160
6687
5827
6093
5016
4746
5266
0
2202
2231
2072
2215
2281
2232
2146
1654
1669
0
2204
2004
1958
1884
1929
1901
2248
2184
2198
0
2219
1851
2291
1988
2216
1964
2007
1824
1742
1958
0
14957 12824 10007 18071 14156 10083
5497
1959
5000
0
10125
10880
13895
12953
12705
11980
12114
0
14655
12105
12915
14695
13446
13254
11800
12026
12642
0
13253
12698
13283
9761
11774
10594
1000
9000
13000
0
0
7642 17148 13116
6946 15826 13068
7073 17139 13078
7111
6667
6224
7779
10725
10898
8752
6365
9385
0
14507
10538
11804
13776
13255
12453
9625
10586
11809
0
12943
12434
12475
5841
8867
7679
6086
5200
5351
6500
0
0
0
15890
16865
17425
18015
16640
16022
15638
0
17987
18282
18504
18285
18224
18019
16920
17519
16901
0
18033
19585
18346
0
18348
16708
0
0
18432
0
0
13636
0
13178
13092
14062
13904
12919
13247
14220
0
14134
14278
14297
14195
14220
14234
14071
13243
13550
0
14566
14971
14456
12203
14223
13207
12375
0
14368
0
0
APPENDIX II
Table A10 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - ALL AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
156198
96
650
5229
8
88
554
4579
5638
145330
Average annual biomass increments (000tons) -------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
1027
4619
23866
132
895
3592
19247
8173
2690
7868
20348
3938
6523
268445
19548
6313
6420
3000
9013
45390
57570
53
63
10413
1735
404
814
53
2226
2900
805
0
0
20665
191
187
18076
2274
692
5280
320
5111
5226
1982
32
0
37624
360
771
18656
2343
984
19957
1036
5488
5490
2476
343
22
44361
0
0
1799
21
187
92
3
243
214
112
0
0
4756
53
63
8614
1714
217
722
50
1983
2686
693
0
0
15909
138
124
7663
539
288
4466
267
2885
2326
1177
32
0
16959
169
584
580
69
292
14677
716
377
264
494
311
22
6737
117
1244
0
6
325
4837
565
5
0
199
403
61
6155
2213
5285
1692
1588
5213
243652
17947
821
929
325
8267
45307
7052
542
713
147391
21485
6869
8305
561
28869
41296
10947
0
0
300582
1455
1615
232047
26260
9720
44572
2480
55548
64719
21993
256
0
473885
2093
5413
235731
26553
11526
117061
6087
57707
66467
25154
1895
139
516445
0
6
25579
291
3844
1206
52
3440
3118
1816
0
0
82535
542
707
121812
21194
3025
7099
509
25429
38178
9131
0
0
218047
913
902
84656
4775
2851
36267
1919
26679
23423
11046
256
0
173303
638
3798
3684
293
1806
72489
3607
2159
1748
3161
1639
139
42560
165
2744
0
7
722
7856
952
7
1
429
789
124
13553
457066
40131
76995
102287
7427
32704
36864
25292
13917
340291
567560
934550 1072271
121887
445673
366990
137721
27349
Krasnodar Kray
12
7620
Stavropol Kray
12
6635
Arkhangelsk oblast
12
38190
Astrakhan oblast
12
4598
Belgorod oblast
12
2665
Bryansk oblast
12
3483
Vladimir oblast
12
2925
Volgograd oblast
12
11265
Vologda oblast
12
14628
Voronezh oblast
12
5195
Nizhni Novgorod oblast12
7515
Nenets a.okr.
12
16858
Ivanovo oblast
12
2270
Kaliningrad oblast
12
1240
Tver oblast
12
8395
Kaluga oblast
12
2963
Kirov oblast
12
11930
Kostroma oblast
12
6000
Samara oblast
12
5118
Kursk oblast
12
3020
Komi-Permyak a.okr. 12
3280
Leningrad oblast
12
7500
Lipetsk oblast
12
2410
Moscow oblast
12
4665
Murmansk oblast
12
13960
Novgorod oblast
12
5450
Orenburg oblast
12
12418
Oryel oblast
12
2458
Penza oblast
12
4320
Perm oblast
12
12715
Pskov oblast
12
5568
Rostov oblast
12
10133
Ryazan oblast
12
3935
Saratov oblast
12
10375
Smolensk oblast
12
4943
Tambov oblast
12
3435
Tula oblast
12
2553
Ulyanovsk oblast
12
3690
Yaroslavl oblast
12
3260
Adigei Republic
12
775
Bashkortostan Republic12
14435
Daghestn Republic
12
5033
Kabardino-Balkarian Republic
12
1238
Kalmyk-Khalm-Tangch Republic
12
7510
Karelia Republic
12
18253
Komi Republic
12
41370
Mari-El Republic
12
2365
Mordovian SSR
12
2590
North-Ossetian SSR 12
778
Karachai-Cherkess Republic
12
1468
Tatarstan Republic
12
6663
Udmurt Republic
12
4150
Checheno-Ingush Republic
12
1930
Chuvash Republic
12
1808
Altai Kray
12
16653
934
202
7175
0
385
2836
1352
0
9568
333
3760
0
1839
744
6947
2235
6322
4093
466
1724
2045
2520
1601
3615
11
3614
215
1882
2347
7867
3297
240
2814
58
4353
1627
2307
431
2943
233
4401
102
215
0
1768
4193
839
1652
261
179
1635
2583
231
383
4412
1885
745
19021
0
1488
3399
2812
0
11910
1221
7238
10
2248
914
7794
2896
11114
5719
746
2684
3040
6015
2230
4394
85
4758
497
2440
3057
9909
4650
486
3831
439
4656
2662
2530
1042
3064
445
7812
203
480
0
8553
15677
1867
2279
303
431
3546
3829
456
985
7984
4324
3186
24637
0
1644
3429
2871
568
12538
2091
7387
309
2261
989
7912
2934
11569
5849
2033
2714
3128
6306
2351
4537
484
4812
1212
2454
3983
10428
4722
4322
3934
1688
4692
2959
2553
2300
3066
480
9920
651
620
171
11568
24599
2157
2508
388
486
5061
3896
947
1321
10881
98
11
1263
0
80
1064
139
0
1942
61
436
0
78
48
841
129
1268
494
0
298
995
915
376
297
0
412
0
160
8
2446
84
1
561
0
33
340
147
0
129
18
395
19
48
0
449
1805
14
216
94
52
0
414
41
15
1051
836
191
5912
0
305
1772
1213
0
7626
272
3324
0
1761
696
6106
2106
5054
3599
466
1426
1050
1605
1225
3318
11
3202
215
1722
2339
5421
3213
239
2253
58
4320
1287
2160
431
2814
215
4006
83
167
0
1319
2388
825
1436
167
127
1635
2169
190
368
3361
951
543
11846
0
1103
563
1460
0
2342
888
3478
10
409
170
847
661
4792
1626
280
960
995
3495
629
779
74
1144
282
558
710
2042
1353
246
1017
381
303
1035
223
611
121
212
3411
101
265
0
6785
11484
1028
627
42
252
1911
1246
225
602
3572
2439
2441
5616
0
156
30
59
568
628
870
149
299
13
75
118
38
455
130
1287
30
88
291
121
143
399
54
715
14
926
519
72
3836
103
1249
36
297
23
1258
2
35
2108
448
140
171
3015
8922
290
229
85
55
1515
67
491
336
2897
1550
709
1890
0
387
0
0
900
40
2473
0
173
0
0
0
0
37
0
705
32
0
75
54
0
805
0
324
0
252
58
0
1728
0
1660
0
439
0
590
0
7
1073
275
5
61
1915
5049
20
49
2
12
569
0
67
383
502
1739
2740
11643
4597
634
54
54
9797
2049
629
128
16355
10
250
483
29
325
150
2379
275
151
1119
4
128
12671
638
10882
3
85
2229
845
4083
0
7027
251
36
0
801
194
288
3442
4099
612
7278
4763
11721
188
32
386
969
1033
253
917
105
5271
12945
2283
98316
0
4175
34211
17192
0
132326
3495
46264
0
26266
11404
98389
31306
85168
57413
4516
21668
30284
35762
20823
51370
118
50163
2119
25019
25840
111537
47016
2588
34653
551
66018
18130
32863
4170
41899
3219
51219
1305
3297
0
23597
60239
10066
19731
4463
2975
18124
33515
3345
4383
53289
21930
7210
199001
0
14854
40258
30069
0
154034
12161
77813
61
29936
13330
106416
37880
126860
73006
6317
32183
39245
67725
27074
58346
565
61026
4124
30504
31329
129833
59577
5042
43806
3658
69217
27424
35029
7956
43069
5574
78191
2285
6140
0
82619
156813
18350
25199
4956
5615
32830
44551
5722
9129
82472
1847
169
21817
0
1034
13995
1992
0
30871
773
5450
0
1111
616
11740
1705
20451
8702
0
3846
16667
15457
4698
4244
0
5914
0
2110
101
40468
1204
8
6825
0
488
3553
2407
0
1797
274
6271
289
901
0
7674
30796
171
2701
1754
1070
0
6786
722
178
15002
11098
2114
76499
0
3141
20216
15200
0
101455
2722
40814
0
25155
10788
86649
29601
64717
48711
4516
17822
13617
20305
16125
47126
118
44249
2119
22909
25739
71069
45812
2580
27828
551
65530
14577
30456
4170
40102
2945
44948
1016
2396
0
15923
29443
9895
17030
2709
1905
18124
26729
2623
4205
38287
8985
4927
100685
0
10679
6047
12877
0
21708
8666
31549
61
3670
1926
8027
6574
41692
15593
1801
10515
8961
31963
6251
6976
447
10863
2005
5485
5489
18296
12561
2454
9153
3107
3199
9294
2166
3786
1170
2355
26972
980
2843
0
59022
96574
8284
5468
493
2640
14706
11036
2377
4746
29183
16847
14857
25449
0
821
191
322
2767
2873
4785
913
1087
65
494
621
224
2281
623
6222
185
455
1330
659
714
1522
263
3130
103
5719
2689
452
23717
609
6267
260
1937
153
5336
12
230
9427
2872
871
939
14521
42198
1278
1278
518
336
6559
365
2983
1307
14177
3615
1436
2352
0
798
0
0
1608
42
5056
0
193
0
0
0
0
49
0
1229
57
0
79
105
0
1057
0
442
1
392
71
0
3671
0
3137
0
867
0
824
0
16
1522
572
9
123
3293
7623
32
46
4
24
837
0
127
635
812
FSU REPUBLICS
38777
22067
224450
0
15675
40449
30391
2767
156907
16946
78726
1148
30001
13824
107037
38104
129141
73629
12539
32368
39700
69055
27733
59060
2087
61289
7254
30607
37048
132522
60029
28759
44415
9925
69477
29361
35182
13292
43081
5804
87618
5157
7011
939
97140
199011
19628
26477
5474
5951
39389
44916
8705
10436
96649
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
10698
7106
4564 16073 10168
6483
4203
1450
10226
11317
14155
12383
17002
10203
10585
12969
14240
13599
0
0
14545
7618
8636
12837
11548
14046
8442
7750
10868
12384
11096
8000
0
12595
5814
7021
12636
11333
11713
5866
5875
10515
12107
10159
5525
6318
11642
0
13864
14216
13899
20564
13157
18465
14178
14549
16189
0
0
17353
10158
6595
11213
7292
14142 11048
12363
8862
13918
9901
9832
8120
10145
7187
12826
9249
14213 10070
13178
9386
0
8137
0
0
13706 10219
14143 12138 10483 16411 13627
13860
11302
13703
0
10844
12063
12716
0
13830
10495
12304
0
14283
15328
14163
14007
13472
14027
9691
12568
14809
14191
13006
14210
10727
13880
9856
13294
11010
14178
14260
10783
12314
9500
15166
11143
14245
9675
14237
13815
11638
12794
15335
0
13347
14367
11998
11944
17100
16620
11085
12975
14481
11444
12078
11634
9678
10462
0
9983
11844
10693
0
12933
9960
10751
6100
13317
14584
13654
13080
11414
12766
8468
11991
12910
11259
12141
13279
6647
12826
8298
12502
10248
13103
12812
10374
11435
8333
14866
10302
13845
7635
14056
12526
10009
11256
12792
0
9660
10003
9829
11057
16356
13028
9258
11635
12548
9268
10330
8968
6926
9110
0
9535
11796
10586
4871
12515
8104
10657
3715
13269
13978
13528
12987
11163
12588
6168
11926
12692
10951
11796
13017
4312
12737
5985
12472
9302
12708
12713
6654
11290
5880
14808
9923
13781
5779
14051
12092
8832
7922
11308
5491
8397
8090
9100
10557
14108
12245
7783
11529
9192
7900
8882
18938
14743
17276
0
12961
13151
14362
0
15893
12572
12509
0
14261
12793
13955
13258
16132
17598
0
12912
16749
16894
12483
14286
0
14343
0
13173
12538
16542
14257
13501
12155
0
14767
10439
16425
0
13936
14867
15873
15592
18724
0
17098
17060
12267
12517
18651
20409
0
16387
17703
12256
14275
13281
11064
12939
0
10307
11409
12528
0
13303
9992
12278
0
14288
15489
14190
14053
12806
13535
9697
12501
12964
12648
13162
14202
10599
13820
9875
13301
11002
13110
14260
10780
12352
9514
15170
11323
14103
9684
14251
13717
11220
12277
14330
0
12075
12329
11995
11856
16200
14964
11086
12323
13828
11438
11393
3783
6503
6346
4247
6189
4939
5041
5726
6626
6400
5274
6192
6317
1414
2207
1836
1132
2221
1624
1685
1567
1792
2153
1956
2046
2202
9955
5445
1965
9446
9072
8499
0
9684
10748
8821
0
9269
9754
9071
5979
8981
11301
9482
9942
8700
9589
6421
10948
9002
9146
9930
8958
6069
9499
7109
9838
7727
8961
9284
9976
8997
8148
10544
8975
9696
6199
9674
11119
7907
9681
10733
0
8698
8409
8058
8715
11627
10478
7696
8854
10574
7885
8170
6907
6086
4531
0
5256
6437
5416
4872
4578
5498
6110
3640
5133
6595
5260
5967
5012
4790
4835
6249
5191
4571
5442
5003
3813
4901
4374
7497
6178
5179
6246
6183
5894
5018
7280
6524
6657
4242
5141
6586
4473
6405
6205
5481
4816
4730
4403
5571
6076
6150
4329
5446
6081
3893
4894
2333
2026
1245
0
2060
732
0
1787
1065
2044
2035
1113
0
0
1738
0
1338
1071
1743
1790
1734
1049
1953
0
1314
1052
1366
1961
1559
1232
0
2124
918
1889
0
1976
0
1396
1701
2271
1418
2081
1875
2023
1720
1510
1608
927
2073
1979
1472
892
1894
1656
1619
APPENDIX II
Table A10 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - ALL AREAS
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
9385
424
698
987
85
339
274
289
178
8221
71140
14263
26294
33801
1820
12443
12031
7507
5666
31673
16338
812
2489
4109
182
630
1677
1620
1411
10817
82285
0
0
0
0
0
0
0
0
82285
77545
3368
7526
13225
209
3159
4158
5699
5535
58777
36283
7656
11900
17451
1310
6346
4244
5551
3640
15192
75673
5
285
776
0
5
280
491
3116
71780
3700
1025
1512
1944
189
836
487
432
179
1576
76270
5183
11610
19239
52
5131
6427
7629
9058
47973
2178
163
478
817
4
159
315
339
89
1272
17045
14
655
2238
0
14
641
1583
688
14097
28903
0
106
375
0
0
106
269
1027
27501
9500
3251
4780
5728
609
2642
1529
948
763
3009
70770
0
0
0
0
0
0
0
0
70745
7110
1141
2746
3777
0
1141
1605
1031
548
2786
45830
0
14
788
0
0
14
774
971
44071
17673
4823
8223
10056
441
4382
3400
1833
759
6858
13980
2544
4996
8959
50
2494
2452
3963
716
4306
8095
401
1379
2553
0
401
978
1174
371
5079
19273
11247
13541
14567
2294
8953
2294
1026
164
4542
1970
1
47
551
0
1
46
504
364
1055
31145
12538
20290
23730
996
11542
7752
3440
255
7160
15860
6649
10125
11624
271
6378
3476
1499
547
3690
53163
7884
18557
28595
508
7376
10673
10038
2810
21758
66588
3
994
5413
0
3
991
4419
9713
51455
8763
1546
2866
4086
185
1361
1320
1220
1318
3359
41493
150
1338
6939
0
150
1188
5601
7183
27371
33533
192
1302
3348
7
185
1110
2046
4879
25305
17035
29
294
1275
0
29
265
981
1161
14599
6120
812
1646
2489
97
715
834
843
281
3350
303275
335
2595
9193
0
335
2260
6598
13944
280120
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
389947
1284574
1674521
113377
90871
204248
190495
167270
357765
233949
249514
483463
18734
10360
29094
94643
80511
175154
77118
76399
153517
43454
82244
125698
1640
1125
18480
15783
14798
16295
13863
19145
44848
413
9290
9250
13783
16663
18168
21050
11995
16385
23425
2840
56143
17725
37325
115468
20900
40580
5038
163355
119045
72183
40
124
1
1722
1175
2761
5242
5539
7179
23333
133
3088
2084
5761
6560
8153
6962
1040
3215
6783
254
8321
6669
10034
7666
2876
1766
53
202
934
71
0
559
189
5257
3347
5569
8039
8396
10848
31468
200
5622
3451
8565
8734
11074
9754
2823
5659
11806
809
15387
10450
12739
13495
5180
3363
169
537
1457
251
1
899
344
9629
6426
7154
9601
10318
13664
36390
267
5991
3895
8754
9466
11417
10374
3439
6265
12817
1288
17258
11170
14145
27397
6601
5288
1069
1437
1821
1166
2
2
0
221
166
60
921
1961
2401
7318
47
1081
362
1447
1739
1194
1081
24
680
1857
43
1341
1029
3808
1502
288
460
6
55
318
4
0
122
1
1501
1009
2701
4321
3578
4778
16015
86
2007
1722
4314
4821
6959
5881
1016
2535
4926
211
6980
5640
6226
6164
2588
1306
47
147
616
67
0
435
188
3535
2172
2808
2797
2857
3669
8135
67
2534
1367
2804
2174
2921
2792
1783
2444
5023
555
7066
3781
2705
5829
2304
1597
116
335
523
180
1
340
155
4372
3079
1585
1562
1922
2816
4922
67
369
444
189
732
343
620
616
606
1011
479
1871
720
1406
13902
1421
1925
900
900
364
915
1
25
163
1425
2666
434
459
1093
746
1729
0
10
46
18
173
0
151
125
112
291
288
220
1
1050
5345
812
686
210
557
178
513
0
717
618
7426
6689
7209
6236
2451
4734
6729
145
3167
5310
5011
7024
6751
10525
8432
10008
10316
1265
38665
6554
22130
82725
13488
34605
3759
161362
117047
70504
37
937041
129701
205198
255752
31416
98285
75497
50554
19526
661639
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
LC
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
24368
131553
77836
957053
102204 1088606
Average annual biomass increments (000tons) -------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
4647
6662
7923
1152
3495
2015
1261
251
166263
259863
297361
24729
141534
93600
37498
8804
9974
21550
29062
2609
7365
11576
7512
2510
0
0
0
0
0
0
0
0
37803
69378
94819
3045
34758
31575
25441
8093
83439
117977
143550
16471
66968
34538
25573
5382
55
2115
3889
0
55
2060
1774
4041
13043
16533
18760
2506
10537
3490
2227
316
60383
108574
141938
590
59793
48191
33364
13721
1618
3978
5328
45
1573
2360
1350
122
127
5615
13344
0
127
5488
7729
1066
0
733
1714
0
0
733
981
1144
37436
48782
52798
7897
29539
11346
4016
1231
0
0
0
0
0
0
0
0
12266
24786
29844
0
12266
12520
5058
881
0
103
3560
0
0
103
3457
1301
55212
82953
91906
5968
49244
27741
8953
1255
29662
50432
69202
667
28995
20770
18770
1213
4975
12631
18865
0
4975
7656
6234
630
143652
162081
166728
35838
107814
18429
4647
243
8
272
2200
0
8
264
1928
508
146757
210286
228180
13701
133056
63529
17894
374
71305
98059
105269
3687
67618
26754
7210
866
95007
182422
233572
7657
87350
87415
51150
5064
26
7228
30648
0
26
7202
23420
17735
17861
27843
32640
2760
15101
9982
4797
1996
1613
9826
33423
3
1610
8213
23597
10505
2104
10430
19325
99
2005
8326
8895
7382
310
2205
6304
0
310
1895
4099
1634
8596
14756
18386
1239
7357
6160
3630
384
3610
20620
49341
0
3610
17010
28721
19567
1527738 2205842 2428478
1061041 1661165 2046528
2588779 3867007 4475006
1819
10
19011
14291
43853
82960
82253
97235
290819
2100
50970
29721
90162
97979
124037
102385
14454
46169
108207
3106
124304
99243
180554
89769
42230
24728
588
2505
15090
614
3
6502
2230
52507
35644
78520
115959
113151
134484
364795
2780
76644
43525
118890
119869
154164
129897
31672
67977
155793
7461
198423
136772
207062
133185
65297
39865
1520
5031
19201
1947
17
8498
3287
78874
54265
89181
125507
123739
148854
391420
3191
79077
46163
120145
124315
156213
133440
35325
71191
161856
9619
210029
140715
214026
200931
74146
50368
6217
9822
20824
6311
22
1881169 2620784 2897571
291647 1236091
678104
145665
915376
600124
437312 2151467 1278228
27
0
2262
2264
1081
16796
31610
34280
99875
866
19627
6024
26329
31714
21526
19499
421
12473
37304
672
25037
19318
83284
23323
5255
8186
92
900
6434
33
0
222636
385363
607999
41944
119031
160975
1792
10
16749
12027
42772
66164
50643
62955
190944
1234
31343
23697
63833
66265
102511
82886
14033
33696
70903
2434
99267
79925
97270
66446
36975
16542
496
1605
8656
581
3
4683
2220
33496
21353
34667
32999
30898
37249
73976
680
25674
13804
28728
21890
30127
27512
17218
21808
47586
4355
74119
37529
26508
43416
23067
15137
932
2526
4111
1333
14
1996
1057
26367
18621
10661
9548
10588
14370
26625
411
2433
2638
1255
4446
2049
3543
3653
3214
6063
2158
11606
3943
6964
67746
8849
10503
4697
4791
1623
4364
5
42
345
3145
5849
918
1024
2288
1202
2927
0
25
89
47
317
0
275
244
191
584
413
445
2
1693
8813
1822
1243
348
947
280
847
1
536512 1344657
739615
276787
36366
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
10960
9544
8027 13600 10324
7356
4368
1411
11657
9883
8797 13588 11374
7780
4995
1554
12283
8658
7073 14322 11689
6903
4637
1779
0
0
0
0
0
0
0
0
11224
9218
7170 14574 11002
7594
4464
1462
10899
9914
8226 12578 10553
8137
4607
1479
11000
7421
5012
0 10912
7363
3611
1297
12725 10935
9650 13227 12606
7165
5154
1762
11650
9352
7378 11289 11654
7498
4373
1515
9926
8322
6521 10956
9924
7481
3988
1373
9071
8573
5962
0
9293
8564
4882
1550
0
6915
4571
0
0
6915
3652
1114
11515 10205
9218 12971 11182
7420
4237
1614
0
0
0
0
0
0
0
0
10750
9026
7902
0 10748
7802
4908
1610
0
7357
4518
0
0
7148
4468
1340
11448 10088
9139 13548 11238
8158
4885
1654
11660 10094
7724 13333 11627
8472
4736
1693
12406
9160
7389
0 12404
7828
5312
1698
12772 11970 11446 15625 12043
8032
4531
1477
8000
5787
3993
0 10828
5806
3822
1396
11705 10364
9616 13759 11528
8195
5202
1468
10724
9685
9056 13625 10602
7697
4810
1584
12051
9830
8168 15076 11843
8190
5096
1802
8667
7272
5662
0 10441
7269
5300
1826
11553
9715
7988 14956 11096
7564
3930
1514
10753
7344
4817 10191 10738
6916
4213
1463
10958
8011
5772 14585 10809
7501
4347
1513
10690
7500
4944
0 10737
7152
4178
1408
10586
8965
7387 12719 10285
7386
4308
1367
10776
7946
5367
0 10791
7526
4353
1403
13475 11580 10380 15568 13061
11676
9931
8202 14060 11370
12675 10809
9256 15031 12283
8793
7855
8326
5123
4686
4837
1721
1529
1575
14715
15571
11161
11918
15835
15313
14153
13175
11923
14271
15618
13758
14797
13745
14731
14094
13817
13295
14392
11531
14222
14171
15624
10779
14290
12666
10606
10940
14061
8612
14652
10772
11812
9477
9831
12347
11798
10816
10154
9093
10172
10132
10101
10245
10071
10313
9855
9658
8923
9474
7849
10490
9925
9798
7448
10012
9476
8053
7550
7864
7424
9684
5876
6827
6030
6047
6727
6113
5509
5104
5410
6156
6596
5939
6638
6077
5976
5717
5932
5299
5996
4505
6204
5477
4954
4873
6228
5456
5217
5322
4456
4770
5797
1654
2108
2207
2194
2114
2231
2093
1611
1693
0
2574
1950
2556
1833
1967
1819
1952
1701
2007
1435
2022
2158
1612
1649
2245
1812
1655
1700
1579
1650
1906
14504 12772 11330 17078 13681
9797
5475
1862
14669
10000
11040
12163
15883
15826
14850
13544
12464
15789
16506
14262
15650
14936
15214
14706
13898
14360
15953
12228
14939
14881
17994
11710
14684
14002
11094
12401
16156
8648
3000
11631
11799
9988
10650
14099
14425
13477
12397
11593
13900
13633
12612
13881
13724
13921
13317
11219
12012
13196
9222
12895
13088
16254
9869
12606
11854
8994
9369
13178
7757
17000
9453
9555
8191
8445
12466
13072
11993
10894
10756
11951
13199
11852
13725
13133
13682
12863
10272
11363
12628
7468
12170
12598
15131
7334
11233
9525
5816
6835
11435
5413
11000
15020
0
10219
13601
17892
18242
16115
14275
13649
18324
18150
16661
18199
18235
18033
18037
17596
18352
20085
15803
18674
18778
21870
15532
18239
17781
16261
16385
20240
9336
0
APPENDIX II
Table A11 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - ACCESSIBLE AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
63130
9
180
1864
1
8
171
1684
2063
59202
107
1173
8360
19
88
1066
7187
3128
2025
6095
17955
3365
4763
165068
10428
5573
6018
2848
4775
22535
51955
47
49
9261
1543
351
495
43
1951
2719
778
0
0
18794
169
147
16011
2015
600
3439
243
4495
4901
1902
23
0
34066
317
583
16521
2071
832
13369
813
4830
5151
2358
252
17
40172
0
0
1539
17
161
50
1
210
205
109
0
0
4337
47
49
7722
1526
190
445
42
1741
2514
669
0
0
14457
122
98
6750
472
249
2944
200
2544
2182
1124
23
0
15272
148
436
510
56
232
9930
570
335
250
456
229
17
6106
100
970
0
4
249
3235
453
5
0
187
303
42
5619
1609
4049
1434
1289
3682
148464
9160
738
867
303
4220
22476
6163
475
553
131196
19312
5968
4993
457
25315
38698
10585
0
0
273206
1280
1268
205862
23507
8441
29070
1900
48821
60645
21155
188
0
429067
1829
4072
209099
23745
9879
78215
4840
50728
62304
24078
1406
103
467786
0
5
21880
236
3320
636
27
2982
2980
1758
0
0
75165
475
548
109316
19076
2648
4357
430
22333
35718
8827
0
0
198041
805
715
74666
4195
2473
24077
1443
23506
21947
10570
188
0
155861
549
2804
3237
238
1438
49145
2940
1907
1659
2923
1218
103
38719
141
2142
0
5
549
5315
776
7
1
402
595
86
12384
303403
36031
68011
87286
6629
29402
31980
19275
11167
204454
510758
831204
938084
108989
401769
320446
106880
22403
Krasnodar Kray
12
6715
Stavropol Kray
12
5428
Arkhangelsk oblast
12
14210
Astrakhan oblast
12
2923
Belgorod oblast
12
2248
Bryansk oblast
12
3095
Vladimir oblast
12
2510
Volgograd oblast
12
9108
Vologda oblast
12
9155
Voronezh oblast
12
4550
Nizhni Novgorod oblast12
6403
Nenets a.okr.
12
2583
Ivanovo oblast
12
1875
Kaliningrad oblast
12
1183
Tver oblast
12
6128
Kaluga oblast
12
2445
Kirov oblast
12
8750
Kostroma oblast
12
4263
Samara oblast
12
4408
Kursk oblast
12
2623
Komi-Permyak a.okr. 12
2220
Leningrad oblast
12
5678
Lipetsk oblast
12
2140
Moscow oblast
12
4130
Murmansk oblast
12
4110
Novgorod oblast
12
3935
Orenburg oblast
12
8305
Oryel oblast
12
2018
Penza oblast
12
3893
Perm oblast
12
8423
Pskov oblast
12
4508
Rostov oblast
12
8245
Ryazan oblast
12
3453
Saratov oblast
12
8433
Smolensk oblast
12
4113
Tambov oblast
12
2905
Tula oblast
12
2283
Ulyanovsk oblast
12
3218
Yaroslavl oblast
12
2350
Adigei Republic
12
605
Bashkortostan Republic12
8983
Daghestn Republic
12
3843
Kabardino-Balkarian Republic
12
898
Kalmyk-Khalm-Tangch 12
Republic4735
Karelia Republic
12
9165
Komi Republic
12
14183
Mari-El Republic
12
1575
Mordovian SSR
12
2315
North-Ossetian SSR 12
608
Karachai-Cherkess Republic
12
1085
Tatarstan Republic
12
5278
Udmurt Republic
12
3425
Checheno-Ingush Republic
12
1555
873
181
3950
0
332
2514
1149
0
6169
305
3229
0
1501
711
5096
1845
4594
2918
428
1509
1339
1808
1419
3233
1
2630
127
1542
2098
5515
2737
197
2472
53
3612
1354
2065
374
2123
214
2954
75
186
0
1091
1600
567
1483
239
146
1293
2094
197
1723
662
10047
0
1259
3024
2409
0
7648
1074
6185
2
1858
880
5704
2389
8139
4072
647
2339
2055
4526
1982
3897
7
3467
306
2003
2727
6988
3860
410
3362
381
3870
2237
2262
923
2224
414
5143
155
422
0
5218
6811
1253
2033
274
357
2794
3162
404
3898
2645
12066
0
1387
3051
2462
478
8044
1832
6307
33
1869
946
5789
2419
8489
4153
1785
2362
2117
4771
2091
4020
141
3506
813
2013
3588
7311
3916
3568
3452
1477
3901
2487
2283
2045
2226
445
6378
549
550
155
7010
9925
1434
2243
359
393
4027
3221
861
89
9
587
0
71
937
123
0
1275
59
379
0
65
46
596
113
919
356
0
267
614
592
323
282
0
293
0
130
7
1692
64
1
483
0
24
275
134
0
96
15
248
13
42
0
294
620
7
194
86
43
0
307
37
784
172
3363
0
261
1577
1026
0
4894
246
2850
0
1436
665
4500
1732
3675
2562
428
1242
725
1216
1096
2951
1
2337
127
1412
2091
3823
2673
196
1989
53
3588
1079
1931
374
2027
199
2706
62
144
0
797
980
560
1289
153
103
1293
1787
160
850
481
6097
0
927
510
1260
0
1479
769
2956
2
357
169
608
544
3545
1154
219
830
716
2718
563
664
6
837
179
461
629
1473
1123
213
890
328
258
883
197
549
101
200
2189
80
236
0
4127
5211
686
550
35
211
1501
1068
207
2175
1983
2019
0
128
27
53
478
396
758
122
31
11
66
85
30
350
81
1138
23
62
245
109
123
134
39
507
10
861
323
56
3158
90
1096
31
250
21
1122
2
31
1235
394
128
155
1792
3114
181
210
85
36
1233
59
457
1387
608
589
0
328
0
0
771
31
2173
0
12
0
0
0
0
27
0
620
25
0
68
47
0
379
0
221
0
226
23
0
1459
0
1426
0
387
0
541
0
6
595
230
3
57
800
1270
12
45
2
7
487
0
62
1425
2175
1540
2922
532
44
49
7859
1080
546
94
2537
6
238
338
25
234
110
2003
235
102
838
2
110
3590
428
7270
3
79
1089
591
3218
0
5529
211
32
0
631
124
154
2010
3056
345
4523
1352
2988
129
27
246
684
763
204
631
12113
2036
54082
0
3616
30279
14549
0
85733
3202
39791
0
21371
10900
72260
25748
61874
41020
4157
18964
19752
25466
18403
45852
12
36529
1253
20575
23061
78036
39161
2136
30508
509
54816
15045
29423
3618
30238
2947
34220
962
2853
0
14569
22676
6803
17731
4073
2517
14176
26845
2855
20082
6440
106385
0
12608
35769
25632
0
99495
10648
66602
11
24559
12803
78015
31138
92755
52096
5594
27994
26244
50460
23985
51813
52
44476
2552
25113
27892
91225
49604
4249
38530
3194
57538
23010
31334
7018
31220
5172
51629
1738
5401
0
50558
66715
12352
22527
4478
4731
25708
36284
5056
35099
18481
115643
0
13282
35941
25916
2338
101340
14831
67362
121
24615
13239
78463
31317
94514
52480
11184
28139
26574
51592
24581
52421
564
44669
4790
25189
33180
92930
49955
23869
39060
8695
57762
24634
31472
11760
31231
5377
57212
4270
6193
854
58946
82099
13150
23700
4992
4957
31062
36604
7854
1701
128
10172
0
926
12299
1766
0
20293
742
4739
0
927
583
8314
1500
14770
6353
0
3453
10296
9966
4021
4031
0
4226
0
1712
90
28085
917
8
5854
0
350
2850
2229
0
1335
225
3917
197
787
0
5053
10580
90
2424
1592
937
0
4979
650
10412
1908
43910
0
2690
17980
12783
0
65440
2460
35052
0
20444
10317
63946
24248
47104
34667
4157
15511
9456
15500
14382
41821
12
32303
1253
18863
22971
49951
38244
2128
24654
509
54466
12195
27194
3618
28903
2722
30303
765
2066
0
9516
12096
6713
15307
2481
1580
14176
21866
2205
7969
4404
52303
0
8992
5490
11083
0
13762
7446
26811
11
3188
1903
5755
5390
30881
11076
1437
9030
6492
24994
5582
5961
40
7947
1299
4538
4831
13189
10443
2113
8022
2685
2722
7965
1911
3400
982
2225
17409
776
2548
0
35989
44039
5549
4796
405
2214
11532
9439
2201
15017
12041
9258
0
674
172
284
2338
1845
4183
760
110
56
436
448
179
1759
384
5590
145
330
1132
596
608
512
193
2238
76
5288
1705
351
19620
530
5501
224
1624
138
4742
11
205
5583
2532
792
854
8388
15384
798
1173
514
226
5354
320
2798
3233
1230
729
0
677
0
0
1383
33
4441
0
12
0
0
0
0
37
0
1093
44
0
72
92
0
492
0
305
1
347
26
0
3115
0
2692
0
765
0
757
0
13
835
474
5
115
1387
2050
19
42
4
13
717
0
118
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
11889 6517 4485 16456 10387 6245 4267 1516
10106
11286
14167
12516
17003
10087
10628
12975
14232
13605
0
0
14537
7574
8626
12858
11666
14068
8453
7819
10861
12374
11123
8174
0
12595
5770
6985
12657
11465
11874
5850
5953
10503
12096
10211
5579
6059
11645
0
13868
14221
13935
20598
12730
18657
14172
14566
16190
0
0
17329
10166 6614
11064 7319
14156 11062
12498 8883
13918 9942
9800 8180
10117 7228
12826 9240
14206 10059
13202 9400
0 8135
0
0
13698 10206
3718
6431
6348
4280
6209
4949
5153
5698
6646
6407
5323
6174
6341
1411
2209
1852
1080
2208
1643
1712
1567
1779
2154
1961
2040
2204
14176 12222 10747 16441 13665 10020
5545
2006
13875
11249
13692
0
10892
12044
12662
0
13897
10498
12323
0
14238
15331
14180
13956
13468
14058
9713
12567
14751
14085
12969
14182
12000
13889
9866
13343
10992
14150
14308
10843
12341
9604
15176
11112
14248
9674
14243
13771
11584
12827
15339
0
13354
14173
11998
11956
17042
17240
10964
12820
14492
6903
6071
4585
0
5254
6439
5397
4889
4658
5520
6211
3551
5181
6597
5279
5944
5032
4729
4913
6232
5322
4621
5460
4921
3810
4899
4412
7446
6145
5274
6222
6212
5883
5018
7225
6504
6670
4224
5147
6541
4520
6419
6208
5510
4680
4941
4399
5593
6073
6181
4343
5451
6119
2331
2022
1238
0
2061
732
0
1795
1073
2044
2035
1005
0
0
1644
0
1351
1459
1762
1752
1850
1057
1951
0
1298
1054
1379
1961
1539
1155
0
2134
927
1889
0
1977
0
1398
1626
2274
1403
2058
1878
2026
1733
1614
1548
922
2079
1941
1472
867
1909
11655
9728
10589
0
10014
11828
10640
0
13009
9914
10768
5500
13218
14549
13677
13034
11396
12794
8646
11968
12771
11149
12101
13296
7429
12828
8340
12538
10228
13055
12851
10363
11460
8383
14868
10286
13852
7603
14038
12493
10039
11213
12799
0
9689
9795
9858
11081
16343
13252
9201
11475
12515
9004
6987
9584
0
9576
11780
10526
4891
12598
8096
10681
3667
13170
13995
13554
12946
11134
12637
6266
11913
12553
10814
11756
13040
4000
12741
5892
12513
9247
12711
12757
6690
11315
5887
14807
9905
13785
5751
14030
12083
8970
7778
11260
5510
8409
8272
9170
10566
13905
12613
7713
11364
9122
19114
14848
17317
0
12970
13123
14367
0
15913
12567
12488
0
14262
12795
13955
13250
16079
17846
0
12922
16767
16823
12464
14295
0
14402
0
13138
12529
16603
14257
13501
12129
0
14689
10375
16588
0
13948
14893
15819
15682
18653
0
17178
17061
12246
12519
18476
21572
0
16203
17465
13281
11115
13056
0
10314
11401
12463
0
13372
9988
12300
0
14238
15521
14209
14001
12816
13533
9705
12487
13034
12749
13128
14172
10588
13821
9883
13359
10987
13066
14308
10866
12393
9510
15179
11304
14087
9666
14261
13670
11198
12404
14334
0
11944
12344
11997
11872
16187
15274
10961
12236
13772
9379
9161
8579
0
9703
10756
8799
0
9303
9688
9069
5941
8918
11289
9462
9901
8711
9600
6577
10879
9068
9195
9913
8981
6544
9493
7241
9838
7680
8956
9301
9932
9009
8180
10536
9021
9706
6198
9678
11139
7953
9680
10781
0
8719
8451
8088
8724
11531
10485
7682
8838
10613
APPENDIX II
Table A11 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - ACCESSIBLE AREAS
ADM REG NAME
197
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Chuvash Republic
12
Altai Kray
12
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
1678
355
915
1223
13
342
560
308
357
96
4074
8498
9700
163
3911
4424
1202
592
11538
2831
5421
7500
570
2261
2590
2079
357
3680
34068
55250
65483
8126
25942
21182
10233
583
2693
236
375
540
54
182
139
165
96
2056
2643
3674
4403
747
1896
1031
729
136
16560
5408
9155
10887
1015
4393
3747
1732
882
4790
60780
89313
97874
13365
47415
28533
8561
1399
7290
614
1776
2493
144
470
1162
717
684
4112
7535
15690
19077
2060
5475
8155
3387
1287
2848
0
0
0
0
0
0
0
0
2847
0
0
0
0
0
0
0
0
9013
677
1633
2497
31
646
956
864
701
5812
7830
15131
19062
386
7444
7301
3931
1019
9438
2722
4256
6030
698
2024
1534
1774
564
2844
31122
43841
52429
8771
22351
12719
8588
883
6140
1
9
34
0
1
8
25
197
5909
7
65
173
0
7
58
108
256
1545
532
738
922
110
422
206
184
41
582
6712
8176
9142
1419
5293
1464
966
72
17280
2742
5472
7404
42
2700
2730
1932
1480
8394
31465
51898
60525
482
30983
20433
8627
2267
1180
89
303
520
2
87
214
217
64
597
857
2455
3305
26
831
1598
850
90
3853
6
329
1056
0
6
323
727
260
2537
52
2844
6391
0
52
2792
3547
402
5013
0
36
129
0
0
36
93
279
4604
0
249
617
0
0
249
368
318
5290
1822
2608
3206
374
1448
786
598
571
1514
21065
26892
29423
4852
16213
5827
2531
933
8158
0
0
0
0
0
0
0
0
8155
0
0
0
0
0
0
0
0
5195
913
2087
2816
0
913
1174
729
390
1988
9828
18978
22540
0
9828
9150
3562
628
9245
0
6
179
0
0
6
173
322
8744
0
42
935
0
0
42
893
429
9910
2322
4333
5490
298
2024
2011
1157
529
3892
26954
43470
49122
4073
22881
16516
5652
875
8545
995
2399
5242
30
965
1404
2843
531
2772
11691
23485
37016
408
11283
11794
13531
909
4795
329
979
1712
0
329
650
733
246
2834
4080
9144
12984
0
4080
5064
3840
424
12618
7921
9631
10296
1723
6198
1710
665
42
2279
102482 116218 119262
27102
75380
13736
3044
67
663
0
14
160
0
0
14
146
120
382
0
81
633
0
0
81
552
167
7415
3301
4949
5733
367
2934
1648
784
119
1563
38493
52054
56089
4943
33550
13561
4035
207
7043
1981
3911
4682
88
1893
1930
771
381
1979
20355
35373
39121
1243
19112
15018
3748
608
6830
1188
2357
3360
62
1126
1169
1003
258
3212
14546
24261
29417
915
13631
9715
5156
459
2680
0
38
166
0
0
38
128
335
2179
0
274
946
0
0
274
672
594
6338
1184
2132
2994
141
1043
948
862
953
2390
13641
20824
24222
2086
11555
7183
3398
1446
7850
52
590
1618
0
52
538
1028
1045
5187
526
4155
8540
2
524
3629
4385
1476
6650
93
574
1346
1
92
481
772
1048
4256
1015
4585
7951
14
1001
3570
3366
1589
5043
10
152
717
0
10
142
565
552
3774
104
1125
3508
0
104
1021
2383
792
3093
591
1185
1691
81
510
594
506
151
1251
6242
10630
12829
1030
5212
4388
2199
208
46970
69
737
2524
0
69
668
1787
2560
41886
727
5637
13103
0
727
4910
7466
3439
244894
258722
503616
84497
38629
123126
136903
68185
205088
164514
93944
258458
12820
5831
18651
71677
32798
104475
52406
29556
81962
27611
25759
53370
15281
15758
31039
65047
149001
214048
1385
863
13455
8953
10518
10775
11258
14803
26983
370
5798
5938
9145
10700
9940
11740
8395
12815
15593
700
26720
8415
23453
56150
8803
15968
2450
32755
29875
21850
0
99
1
1087
510
2049
3461
4462
5980
13741
119
1986
1457
3820
4523
4956
4279
735
2542
4539
37
4349
3276
6516
3113
1328
948
30
116
239
49
0
478
149
3641
1635
4099
5456
6773
8835
18609
176
3603
2363
5757
5900
6527
5731
2022
4481
8335
172
8264
5106
8229
5754
2523
1886
70
246
418
154
0
785
270
7075
3609
5227
6656
8391
10920
21713
238
3885
2678
5889
6352
6691
6032
2503
4986
9089
310
9420
5484
9237
13545
3253
2807
446
544
574
872
0
1
0
125
73
39
616
1547
1993
4562
41
672
284
1045
1260
719
687
23
529
1105
6
585
527
2605
607
155
205
5
34
77
2
0
98
1
962
437
2010
2845
2915
3987
9179
78
1314
1173
2775
3263
4237
3592
712
2013
3434
31
3764
2749
3911
2506
1173
743
25
82
162
47
0
379
148
2554
1125
2050
1995
2311
2855
4868
57
1617
906
1937
1377
1571
1452
1287
1939
3796
135
3915
1830
1713
2641
1195
938
40
130
179
105
0
307
121
3434
1974
1128
1200
1618
2085
3104
62
282
315
132
452
164
301
481
505
754
138
1156
378
1008
7791
730
921
376
298
156
718
0
24
122
1082
1819
280
323
931
525
1191
0
8
34
16
134
0
110
100
101
227
94
155
1
815
2863
553
315
95
212
100
415
0
576
470
5298
3525
5011
3795
1935
3357
4078
131
1902
3225
3240
4214
3249
5598
5792
7729
6276
296
17145
2930
13400
39742
4996
12845
1909
32000
29201
20564
0
416566
80347
127392
159481
20129
60218
47045
32089
12645
244429
1133389 1598982 1746203
454820 685814 806122
1588209 2284796 2552325
1445
10
11781
6251
32490
54631
66413
81215
170363
1869
32825
20915
59783
67783
75292
62859
10204
36314
70262
460
64296
48924
119886
34229
19682
12903
345
1458
3503
419
0
5508
1764
35651
17327
57817
78384
91667
110323
214584
2447
49281
30128
79585
81693
91492
77187
22601
53442
105870
1535
105383
67036
136939
52826
31673
21953
642
2455
4687
1179
0
196230 937159
82050 372770
278280 1309929
465593
230994
696587
147221
120308
267529
27960
23962
51922
7313
2597
56228
29071
65346
85686
100575
120916
231244
2831
51144
32008
80466
84425
92503
78927
25439
56074
110349
2163
112603
69095
141928
90709
36437
27032
2592
4047
5352
4569
0
20
0
1244
1017
697
11230
24994
28542
61174
749
12211
4782
19038
23002
12943
12393
402
9699
21497
90
10836
9775
57607
9068
2847
3485
79
551
1448
18
0
1425
10
10537
5234
31793
43401
41419
52673
109189
1120
20614
16133
40745
44781
62349
50466
9802
26615
48765
370
53460
39149
62279
25161
16835
9418
266
907
2055
401
0
4063
1754
23870
11076
25327
23753
25254
29108
44221
578
16456
9213
19802
13910
16200
14328
12397
17128
35608
1075
41087
18112
17053
18597
11991
9050
297
997
1184
760
0
1805
833
20577
11744
7529
7302
8908
10593
16660
384
1863
1880
881
2732
1011
1740
2838
2632
4479
628
7220
2059
4989
37883
4764
5079
1950
1592
665
3390
39
266
2384
4015
592
724
1949
855
2008
0
20
68
41
244
0
198
195
171
450
137
319
2
1317
4663
1251
572
156
367
148
696
0
1168810 1633059 1809669
341438
827372
464249
176610
23847
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
11476 9287 7931 12237 11423 7896 3903 1657
12034 10192 8731 14245 11474 8180 4922 1632
11199 9797 8154 13800 10424 7425 4416 1410
11239 9756 8990 13174 10793 7615 4941 1586
12272 8834 7652 14292 11640 7016 4722 1881
0
0
0
0
0
0
0
0
11566 9266 7634 12611 11515 7639 4549 1454
11434 10301 8695 12571 11045 8290 4840 1567
7000 7222 5088
0 10908 6966 4282 1298
12617 11079 9915 12944 12550 7096 5251 1748
11475 9484 8175 11387 11474 7483 4465 1532
9629 8102 6356 11122 9602 7477 3914 1418
8667 8644 6052
0 9412 8652 4876 1545
0 6917 4783
0
0 6904 3936 1142
11561 10311 9177 12985 11199 7415 4232 1634
0
0
0
0
0
0
0
0
10765 9093 8004
0 10764 7793 4883 1607
0 7000 5223
0
0 7186 5151 1329
11608 10032 8948 13681 11303 8214 4886 1655
11750 9789 7061 13578 11697 8401 4759 1711
12401 9340 7584
0 12406 7786 5238 1722
12938 12067 11583 15733 12161 8031 4577 1581
0 5786 3956
0
0 5885 3770 1387
11661 10518 9784 13483 11436 8228 5144 1737
10275 9044 8356 14119 10097 7779 4863 1596
12244 10293 8755 14786 12104 8311 5141 1782
0 7211 5699
0
0 7288 5245 1774
11521 9767 8090 14762 11078 7577 3942 1517
10115 7042 5278 9946 10105 6742 4266 1412
10914 7988 5907 15405 10901 7425 4358 1515
10400 7401 4893
0 10396 7194 4221 1436
10562 8970 7587 12712 10221 7393 4344 1383
10536 7649 5191
0 10548 7353 4177 1343
13413 11680 10614 15307 13075
11774 10058 8581 14071 11366
12899 11141 9875 14920 12538
8884
7815
8499
5332
4671
5013
1830
1521
1673
14609
15571
10957
11986
15821
15254
14211
13210
11895
14279
15693
13757
14684
13725
14715
14050
13770
13224
14201
11749
14204
14242
15923
10041
14353
12670
10725
11081
12725
8602
0
10716
11842
9346
9849
12354
11904
10927
10196
9085
10176
10174
10164
10223
10101
10312
9869
9633
8835
9380
7959
10494
9897
9956
7041
10034
9645
7344
7690
6610
7232
0
5885
6855
5992
5950
6676
6085
5505
5080
5367
6155
6611
5977
6695
6040
6161
5781
5898
5215
5937
4566
6243
5443
4948
4863
6529
5514
5191
5341
4272
4725
0
1650
2182
2203
2207
2112
2241
2093
1627
1685
0
2579
1962
2548
1826
1945
1812
1949
1703
1981
1460
2061
2158
1615
1629
2263
1819
1637
1731
1482
1680
0
14547 12819 11347 16962 13740
9868
5504
1886
14596
10000
10838
12257
15857
15785
14884
13581
12398
15706
16528
14355
15650
14986
15192
14690
13883
14286
15480
12432
14784
14934
18399
10996
14821
13611
11500
12569
14657
8551
0
11523
11839
9792
10598
14105
14367
13534
12487
11531
13903
13678
12750
13824
13846
14017
13468
11178
11926
12702
8924
12752
13129
16641
9181
12554
11640
9171
9980
11213
7656
0
9316
9619
7947
8055
12502
12873
11986
11073
10650
11895
13164
11952
13664
13291
13825
13085
10163
11246
12141
6977
11954
12599
15365
6697
11201
9630
5812
7439
9324
5240
0
15139
0
9986
13842
17860
18219
16152
14323
13409
18332
18163
16823
18212
18250
18010
18027
17476
18322
19462
16065
18527
18562
22115
14938
18309
16981
16179
16315
18741
9331
0
APPENDIX II
Table A12 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - ACCESSIBLE AREAS, EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
62805
9
180
1857
1
8
171
1677
2042
58906
107
1173
8329
19
88
1066
7156
3102
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
11889 6517 4485 16456 10387 6245 4267 1519
1448
4205
6503
1303
3013
134203
8128
1875
3013
93
3495
20363
5253
39
45
3017
574
91
385
28
609
1479
26
0
0
1827
113
115
5716
772
197
1917
125
1558
2573
55
18
0
3454
202
358
5878
805
321
6245
343
1700
2698
75
154
14
3943
0
0
537
7
19
41
1
59
121
3
0
0
434
39
45
2480
567
72
344
27
550
1358
23
0
0
1393
74
70
2699
198
106
1532
97
949
1094
29
18
0
1627
89
243
162
33
124
4328
218
142
125
20
136
14
489
60
532
0
4
132
1765
229
2
0
9
154
37
62
1185
2948
624
493
2560
126193
7555
172
314
8
3188
20312
1248
402
506
41984
6992
1281
3910
302
7619
21255
364
0
0
27236
901
989
71280
8717
2288
16332
971
16358
32242
630
144
0
45309
1243
2489
72260
8854
3043
37567
1935
17151
33082
761
853
87
47875
0
3
7503
95
348
529
27
840
1766
53
0
0
7357
402
503
34481
6897
933
3381
275
6779
19489
311
0
0
19879
499
483
29296
1725
1007
12422
669
8739
10987
266
144
0
18073
342
1500
980
137
755
21235
964
793
840
131
709
87
2566
84
1151
0
4
295
2811
350
3
0
19
302
76
133
192895
8120
16613
22736
1222
6898
8493
6123
2986
166800
111851
196161
227200
18521
93330
84310
31039
5228
13775 11808
Krasnodar Kray
12
1820
Stavropol Kray
12
805
Arkhangelsk oblast
12
13708
Astrakhan oblast
12
2853
Belgorod oblast
12
73
Bryansk oblast
12
638
Vladimir oblast
12
1008
Volgograd oblast
12
1703
Vologda oblast
12
7900
Voronezh oblast
12
473
Nizhni Novgorod oblast12
3318
Nenets a.okr.
12
2583
Ivanovo oblast
12
848
Kaliningrad oblast
12
145
Tver oblast
12
2598
Kaluga oblast
12
1038
Kirov oblast
12
5758
Kostroma oblast
12
3273
Samara oblast
12
370
Kursk oblast
12
80
Komi-Permyak a.okr. 12
1838
Leningrad oblast
12
4743
Lipetsk oblast
12
80
Moscow oblast
12
2008
Murmansk oblast
12
3965
Novgorod oblast
12
3273
Orenburg oblast
12
1840
Oryel oblast
12
53
Penza oblast
12
575
Perm oblast
12
5435
Pskov oblast
12
2258
Rostov oblast
12
313
Ryazan oblast
12
1050
Saratov oblast
12
845
Smolensk oblast
12
563
Tambov oblast
12
255
Tula oblast
12
213
Ulyanovsk oblast
12
780
Yaroslavl oblast
12
850
Adigei Republic
12
225
Bashkortostan Republic12
3123
Daghestn Republic
12
3370
Kabardino-Balkarian Republic
12
555
Kalmyk-Khalm-Tangch 12
Republic3825
Karelia Republic
12
8518
Komi Republic
12
14183
Mari-El Republic
12
943
Mordovian SSR
12
593
North-Ossetian SSR 12
405
Karachai-Cherkess Republic
12
895
Tatarstan Republic
12
540
Udmurt Republic
12
1400
Checheno-Ingush Republic
12
1028
354
51
3706
0
7
573
428
0
5368
3
1525
0
683
75
2184
807
2811
2202
81
48
1003
1587
33
1553
1
2236
2
41
243
3331
1392
0
575
0
509
132
188
86
799
69
467
71
137
0
994
1600
373
346
109
111
145
880
176
567
164
9635
0
40
632
953
0
6699
50
3175
2
840
93
2423
1019
5375
3174
105
70
1703
3914
58
1891
7
2910
6
51
384
4332
2054
0
995
18
535
227
208
232
811
105
972
147
199
0
4961
6811
794
522
131
199
292
1300
300
738
224
11603
0
46
635
980
10
7061
147
3243
33
847
106
2451
1031
5578
3234
174
71
1764
4103
79
1955
134
2941
18
52
521
4587
2071
52
1050
50
538
246
212
540
811
119
1548
445
212
0
6703
9925
865
575
167
223
433
1318
455
63
7
571
0
1
223
44
0
1124
0
86
0
26
4
304
45
693
326
0
5
461
540
8
145
0
252
0
7
6
1064
42
0
171
0
1
28
14
0
19
3
80
13
40
0
275
620
3
85
32
33
0
137
37
291
44
3135
0
6
350
384
0
4244
3
1439
0
657
71
1880
762
2118
1876
81
43
542
1047
25
1408
1
1984
2
34
237
2267
1350
0
404
0
508
104
174
86
780
66
387
58
97
0
719
980
370
261
77
78
145
743
139
213
113
5929
0
33
59
525
0
1331
47
1650
2
157
18
239
212
2564
972
24
22
700
2327
25
338
6
674
4
10
141
1001
662
0
420
18
26
95
20
146
12
36
505
76
62
0
3967
5211
421
176
22
88
147
420
124
171
60
1968
0
6
3
27
10
362
97
68
31
7
13
28
12
203
60
69
1
61
189
21
64
127
31
12
1
137
255
17
52
55
32
3
19
4
308
0
14
576
298
13
0
1742
3114
71
53
36
24
141
18
155
58
13
585
0
7
0
0
9
29
255
0
12
0
0
0
0
11
0
65
1
0
37
1
0
366
0
6
0
35
21
0
13
0
66
0
8
0
115
0
4
369
180
2
0
790
1270
5
12
1
7
51
0
21
1024
568
1505
2852
19
3
28
1684
810
70
74
2537
1
38
146
6
167
39
130
7
75
602
0
53
3465
331
1817
0
19
826
187
247
0
729
24
0
0
125
38
101
1206
2738
341
3825
1022
2988
72
6
238
665
55
82
551
5663
660
50772
0
79
6561
5318
0
74799
29
19088
0
9737
1139
30942
11246
38912
31032
795
619
14702
22479
430
22118
12
31018
16
497
2651
47580
19810
0
6428
0
7695
1496
2819
848
11434
1089
5565
916
2215
0
13328
22676
4490
4071
1895
1907
1553
11245
2623
7945
1738
101574
0
416
7136
9965
0
87177
525
33794
11
11148
1348
33226
13341
61237
40338
954
846
21043
43980
648
25131
52
37372
43
590
3653
56599
25855
0
10133
154
7969
2306
3015
1686
11555
1479
9262
1652
2876
0
47919
66715
7917
5537
2143
2862
2637
14962
3980
9140
2100
110598
0
450
7153
10111
46
88871
1066
34189
121
11183
1436
33372
13415
62348
40611
1254
856
21364
44864
767
25464
536
37526
97
595
4354
57944
25955
286
10455
323
7996
2424
3037
2967
11556
1584
11687
3553
2952
0
56085
82099
8231
5810
2364
3002
3245
15061
4921
1296
106
9878
0
16
2849
634
0
17980
0
1094
0
372
57
4240
575
11554
5914
0
73
7716
9112
93
2072
0
3634
0
98
73
17671
594
0
2152
0
20
310
260
0
270
72
1237
196
759
0
4714
10580
41
1062
634
704
0
2186
650
4367
554
40894
0
63
3712
4684
0
56819
29
17994
0
9365
1082
26702
10671
27358
25118
795
546
6986
13367
337
20046
12
27384
16
399
2578
29909
19216
0
4276
0
7675
1186
2559
848
11164
1017
4328
720
1456
0
8614
12096
4449
3009
1261
1203
1553
9059
1973
2282
1078
50802
0
337
575
4647
0
12378
496
14706
11
1411
209
2284
2095
22325
9306
159
227
6341
21501
218
3013
40
6354
27
93
1002
9019
6045
0
3705
154
274
810
196
838
121
390
3697
736
661
0
34591
44039
3427
1466
248
955
1084
3717
1357
1195
362
9024
0
34
17
146
46
1694
541
395
110
35
88
146
74
1111
273
300
10
321
884
119
333
484
154
54
5
701
1345
100
286
322
169
27
118
22
1281
1
105
2425
1901
76
0
8166
15384
314
273
221
140
608
99
941
131
24
725
0
15
0
0
16
31
515
0
12
0
0
0
0
14
0
112
2
0
39
1
0
476
0
8
0
46
25
0
26
0
126
0
15
0
148
0
10
529
372
4
0
1373
2050
7
11
1
13
79
0
40
15997
12941
13700
0
11286
11450
12425
0
13934
9667
12517
0
14256
15187
14168
13936
13843
14093
9815
12896
14658
14164
13030
14242
12000
13872
8000
12122
10909
14284
14231
0
11179
0
15118
11333
14995
9860
14310
15783
11916
12901
16168
0
13408
14173
12038
11766
17385
17180
10710
12778
14903
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
10308
11244
13916
12181
14077
10156
10786
12511
14371
14000
0
0
14907
7973
8600
12470
11291
11614
8520
7768
10499
12531
11455
8000
0
13118
14012
10598
10542
0
10400
11291
10456
0
13013
10500
10644
5500
13271
14495
13713
13092
11393
12709
9086
12086
12356
11237
11172
13290
7429
12843
7167
11569
9513
13065
12588
0
10184
8556
14895
10159
14495
7267
14248
14086
9529
11238
14452
0
9659
9795
9971
10607
16359
14382
9031
11509
13267
6153
6953
12293
10999
9480
6016
5641
10089
12262
10147
5539
6214
12142
0
13888
13960
13609
18585
12752
18657
14135
14621
16076
0
0
16951
10225 6714
11123 6945
13904 10853
12154 8705
12881 9498
9832 8110
10036 6918
12321 9207
14348 10042
13744 9238
0 8149
0
0
14273 11108
9993 15156 13530
12385
9375
9532
0
9783
11265
10317
4600
12586
7252
10542
3667
13203
13547
13616
13012
11177
12558
7207
12056
12111
10934
9709
13025
4000
12760
5389
11442
8357
12632
12533
5500
9957
6460
14862
9854
14325
5494
14249
13311
7550
7984
13925
0
8367
8272
9516
10104
14156
13462
7494
11427
10815
20605
15368
17305
0
13074
12761
14441
0
16004
0
12648
0
14288
12727
13946
12663
16663
18152
0
14068
16744
16863
12358
14260
0
14449
0
13029
12523
16604
14200
0
12592
0
15190
11084
18108
0
13933
21025
15553
15690
18902
0
17151
17061
12240
12520
19764
21122
0
15996
17465
15031
12455
13046
0
10785
10610
12189
0
13387
9473
12506
0
14263
15231
14201
13999
12914
13391
9790
12624
12900
12768
13213
14241
10591
13803
9663
11726
10885
13194
14236
0
10573
0
15100
11368
14691
9878
14314
15319
11172
12510
14966
0
11975
12344
12025
11540
16384
15422
10717
12197
14202
3849
6176
6059
4124
6113
4906
4417
5577
6714
6417
5225
6251
5249
1389
2164
2026
1081
2234
1593
1527
1392
1885
2107
1963
2051
2135
9927
5069
1751
10694
9551
8569
0
10339
9803
8854
0
9301
10452
8910
5941
8962
11496
9555
9892
8707
9570
6588
10105
9065
9242
8582
8909
6544
9426
7315
9359
7125
9006
9125
0
8828
8723
10557
8496
9582
5738
9743
10853
7322
9670
10662
0
8721
8451
8133
8321
11525
10830
7357
8844
10955
6989
6027
4586
0
5296
6539
5467
4790
4672
5550
5827
3551
5244
6580
5197
5982
5469
4571
4329
7116
5298
4673
5685
5228
3820
4909
4673
6865
5107
5281
5906
5451
5867
5222
8468
6100
6131
4157
5035
7518
4209
6376
6042
0
4688
4941
4429
5155
6113
5787
4299
5371
6058
2245
1883
1238
0
2051
0
0
1731
1076
2022
0
1005
0
0
2446
0
1245
1522
1716
1906
1850
1042
2073
0
1298
1057
1295
0
1319
1165
0
2030
920
1918
0
1925
0
1285
2447
2467
1435
2067
1878
0
1739
1614
1468
865
2003
1941
1551
924
1906
APPENDIX II
Table A12 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - ACCESSIBLE AREAS, EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
197
101
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Chuvash Republic
12
Altai Kray
12
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Average annual biomass increments (000tons) --------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
643
176
441
523
7
169
265
82
95
25
2085
4188
4498
83
2002
2103
310
159
6125
1475
3067
4025
304
1171
1592
958
253
1847
17474
30268
34952
4392
13082
12794
4684
414
2668
235
373
532
54
181
138
159
87
2048
2629
3656
4360
742
1887
1027
704
120
13728
3865
6961
8522
447
3418
3096
1561
858
4348
43831
67418
75109
6079
37752
23587
7691
1361
6520
486
1367
1963
122
364
881
596
668
3889
6085
12534
15432
1763
4322
6449
2898
1256
2825
0
0
0
0
0
0
0
0
2825
0
0
0
0
0
0
0
0
8873
644
1549
2401
30
614
905
852
699
5770
7422
14341
18214
375
7047
6919
3873
1017
8108
2085
3449
5036
398
1687
1364
1587
559
2512
23064
34371
41954
4970
18094
11307
7583
875
6128
1
9
34
0
1
8
25
197
5896
7
65
173
0
7
58
108
256
1450
459
663
839
88
371
204
176
41
570
5787
7235
8152
1143
4644
1448
917
71
16035
2472
4800
6642
37
2435
2328
1842
1454
7939
28680
46091
54319
425
28255
17411
8228
2227
693
41
117
252
1
40
76
135
43
398
412
993
1514
16
396
581
521
59
3853
6
329
1056
0
6
323
727
260
2537
52
2844
6391
0
52
2792
3547
402
5010
0
36
129
0
0
36
93
279
4602
0
249
617
0
0
249
368
318
3498
1405
2060
2445
257
1148
655
385
214
839
16440
21277
22954
3343
13097
4837
1677
338
8158
0
0
0
0
0
0
0
0
8155
0
0
0
0
0
0
0
0
2403
219
823
1211
0
219
604
388
233
959
2323
6993
8874
0
2323
4670
1881
370
9245
0
6
179
0
0
6
173
322
8744
0
42
935
0
0
42
893
429
6220
1179
2676
3282
161
1018
1497
606
165
2773
13378
25647
28599
2167
11211
12269
2952
268
5035
864
2029
2949
27
837
1165
920
197
1889
10256
20066
24382
369
9887
9810
4316
340
4760
324
966
1695
0
324
642
729
246
2815
4028
9031
12854
0
4028
5003
3823
424
10428
6302
7597
8185
1379
4923
1295
588
42
2201
82205
92474
95140
21857
60348
10269
2666
67
630
0
13
149
0
0
13
136
115
366
0
76
588
0
0
76
512
160
6968
3104
4652
5405
320
2784
1548
753
93
1469
36118
48858
52709
4298
31820
12740
3851
161
4585
1500
2724
3177
70
1430
1224
453
227
1181
15426
24968
27178
995
14431
9542
2210
359
6780
1170
2330
3329
60
1110
1160
999
257
3194
14323
23966
29102
895
13428
9643
5136
459
2678
0
38
166
0
0
38
128
335
2177
0
274
946
0
0
274
672
594
2578
314
624
1020
53
261
310
396
392
1164
3844
5986
7516
851
2993
2142
1530
601
7260
51
519
1457
0
51
468
938
983
4819
517
3694
7707
2
515
3177
4013
1385
6045
66
489
1132
1
65
423
643
959
3955
716
3876
6666
14
702
3160
2790
1454
4778
10
137
628
0
10
127
491
492
3658
104
1016
3078
0
104
912
2062
702
2370
350
711
1142
35
315
361
431
136
1092
3738
6410
8248
438
3300
2672
1838
185
46870
69
737
2521
0
69
668
1784
2556
41793
727
5636
13096
0
727
4909
7460
3434
122175
223305
345480
40271
28696
68967
72526
51851
124377
83447
71503
154950
7645
3844
11489
32626
24852
57478
32255
23155
55410
10921
19652
30573
4520
13362
17882
34161
138424
172585
555082 838632 891922
339586 520355 611759
894668 1358987 1503681
705
70
5220
3418
1513
4635
3945
7378
15713
0
583
3165
4535
7530
7245
9118
6195
7700
11093
475
15890
5543
20278
48138
5088
11770
1600
28288
29138
20918
0
78
1
877
304
223
1908
1768
2649
7444
0
222
535
1762
2941
3471
3055
554
1580
3349
29
1247
2116
5329
2820
874
606
19
101
225
33
0
250
7
2252
827
484
2490
2496
4172
10527
0
325
1007
2792
3975
4674
4200
1464
2677
5761
107
2021
3336
6730
5108
1381
1124
43
227
386
113
0
361
11
3359
1339
645
2874
2953
5250
12558
0
360
1120
2880
4236
4814
4424
1793
2942
6288
212
2224
3594
7581
10913
1650
1623
301
510
520
678
0
1
0
104
46
5
229
724
1091
2469
0
20
73
554
755
447
439
9
349
900
5
296
360
2101
593
113
144
5
23
74
2
0
77
1
773
258
218
1679
1044
1558
4975
0
202
462
1208
2186
3024
2616
545
1231
2449
24
951
1756
3228
2227
761
462
14
78
151
31
0
172
6
1375
523
261
582
728
1523
3083
0
103
472
1030
1034
1203
1145
910
1097
2412
78
774
1220
1401
2288
507
518
24
126
161
80
0
111
4
1107
512
161
384
457
1078
2031
0
35
113
88
261
140
224
329
265
527
105
203
258
851
5805
269
499
258
283
134
565
0
17
2
192
567
30
100
244
194
515
0
1
18
16
73
0
71
63
42
143
71
27
0
684
2090
81
170
61
208
89
334
0
326
57
1668
1511
837
1661
747
1933
2639
0
222
2026
1639
3221
2430
4622
4339
4716
4663
193
13638
1949
12011
35134
3357
9978
1238
27569
28529
19906
0
1155
10
9673
3771
3489
29716
25908
35312
92500
0
3460
7453
27481
43680
52628
44663
7681
22846
52660
356
19457
31853
98036
31895
12999
8653
236
1239
3391
283
0
2846
69
21624
9006
7085
36356
33293
51043
121196
0
4540
12119
37988
54191
65104
55963
16473
32739
75455
965
27434
43987
111800
48267
18042
13565
409
2206
4469
863
0
286887
46120
70956
88013
11931
34189
24836
17057
6103
192759
672484
909097
123631
55134
178765
431451
284452
715903
283550
180769
464319
53290
91404
144694
7155
20106
27261
3471
90
28078
12124
7977
38888
35774
56763
132115
0
4773
12771
38586
55773
65965
57202
18420
34217
78617
1435
28618
45393
115925
76609
19610
16289
1752
3716
5042
3467
0
20
0
1058
629
86
4158
11528
15223
33390
0
369
1134
9950
13772
8039
7923
167
6463
17690
74
5711
6742
46683
8941
2079
2558
79
376
1416
18
0
1135
10
8615
3142
3403
25558
14380
20089
59110
0
3091
6319
17531
29908
44589
36740
7514
16383
34970
282
13746
25111
51353
22954
10920
6095
157
863
1975
265
0
1691
59
11951
5235
3596
6640
7385
15731
28696
0
1080
4666
10507
10511
12476
11300
8792
9893
22795
609
7977
12134
13764
16372
5043
4912
173
967
1078
580
0
625
21
6454
3118
892
2532
2481
5720
10919
0
233
652
598
1582
861
1239
1947
1478
3162
470
1184
1406
4125
28342
1568
2724
1343
1510
573
2604
0
28
4
393
1247
71
214
474
315
855
0
1
34
41
132
0
131
122
73
283
102
43
1
1082
3411
180
305
101
360
135
534
0
999460
206276
466208
236613
90363
10672
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS
S
MS
mS
vmS
VS+SVS...MSVS...mS
11847 9497 8600 12444 11876 7931 3763 1680
11847 9869 8684 14440 11169 8039 4891 1635
11187 9802 8195 13798 10423 7423 4413 1384
11340 9685 8814 13592 11046 7619 4928 1587
12521 9169 7861 14467 11877 7316 4861 1880
0
0
0
0
0
0
0
0
11525 9258 7586 12570 11469 7649 4545 1454
11062 9965 8331 12472 10728 8288 4777 1566
7000 7222 5088
0 10908 6966 4282 1298
12608 10913 9716 12918 12529 7088 5213 1744
11602 9602 8178 11485 11606 7478 4468 1531
10049 8487 6008 11026 9955 7683 3851 1396
8667 8644 6052
0 9412 8652 4876 1545
0 6917 4783
0
0 6904 3938 1142
11701 10329 9388 12991 11410 7388 4361 1581
0
0
0
0
0
0
0
0
10607 8497 7328
0 10612 7734 4844 1592
0 7000 5223
0
0 7186 5151 1329
11347 9584 8714 13429 11007 8196 4873 1630
11870 9890 8268 13574 11814 8419 4691 1725
12432 9349 7583
0 12416 7791 5242 1722
13044 12172 11624 15850 12259 7929 4536 1582
0 5846 3946
0
0 5970 3752 1392
11636 10503 9752 13442 11428 8228 5114 1727
10284 9166 8555 14218 10093 7793 4877 1584
12242 10286 8742 14842 12100 8312 5144 1782
0 7211 5699
0
0 7288 5245 1774
12242 9593 7369 16014 11445 6904 3859 1532
10137 7118 5290 9946 10135 6786 4276 1409
10848 7926 5889 15405 10882 7468 4342 1516
10400 7416 4901
0 10458 7186 4202 1427
10680 9015 7222 12641 10479 7397 4263 1361
10536 7647 5195
0 10548 7353 4181 1343
13784 11563 10688 16171 13224
11834 10036 8556 14343 11446
12972 10926 9704 15560 12455
8791
7807
8380
4880
4651
4733
1583
1505
1524
14710
15571
11138
12170
15585
15222
13777
12897
11882
0
15319
13672
14515
13682
14745
14045
13775
13312
14279
11712
14447
14303
15908
10306
14349
13183
11537
11028
13116
8590
0
9812
9706
8692
10005
13760
11416
10143
10329
9308
0
10501
9879
10204
10161
10368
9866
9666
9016
9452
7847
10302
9946
9822
7156
9940
9491
7225
7651
6693
7244
0
5630
5706
5828
6088
5551
6588
5427
5304
5376
0
6570
5754
6767
6068
6146
5524
5923
5572
6001
4472
5848
5456
4847
4882
5837
5463
5196
5342
4267
4610
0
1670
2032
2052
2199
2392
2142
1943
1622
1659
0
2387
1888
2548
1809
1949
1831
1942
1762
1985
1447
1588
2196
1580
1632
2211
1796
1658
1732
1510
1599
0
14581 12812 11356 17289 13636
9527
5298
1749
14808
10000
11030
12405
15646
15574
14654
13330
12426
0
15586
13931
15596
14852
15162
14620
13865
14459
15724
12276
15603
15053
18397
11310
14873
14279
12421
12267
15071
8576
0
11384
9857
9602
10890
14638
14601
13339
12235
11513
0
13969
12035
13606
13633
13929
13325
11252
12230
13098
9019
13574
13186
16612
9449
13064
12069
9512
9718
11578
7637
0
9615
8182
8359
9055
12367
13531
12114
10812
10520
0
13258
11403
13398
13166
13703
12930
10273
11631
12503
6769
12868
12630
15292
7020
11885
10036
5821
7286
9696
5114
0
15139
0
10148
13816
17718
18131
15914
13946
13525
0
18182
15477
17968
18239
17972
18054
18152
18508
19659
15944
19262
18708
22214
15069
18460
17822
16179
16052
19215
9331
0
APPENDIX II
Table A13 PRODUCTION POTENTIALS FOR TRADITIOONAL PRODUCTION FORESTRY SPECIES - ACCESSIBLE AREAS CURRENTLY UNDER FOREST
ADM REG NAME
2
11
12
13
14
15
16
17
18
19
20
21
22
23
LC
4 Mongolia
12
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
1163
0
9
50
0
0
9
41
99
1013
Average annual biomass increments (000tons) ---------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
0
61
241
0
0
61
180
132
135
698
5098
975
1995
4208
2290
1748
1605
85
2640
1198
4743
7
19
2527
417
42
56
0
553
820
25
0
0
1605
13
41
4565
592
82
306
15
1450
1369
51
18
0
3085
20
78
4664
621
151
594
60
1585
1438
71
151
8
3530
0
0
432
7
11
3
0
49
30
3
0
0
382
7
19
2095
410
31
53
0
504
790
22
0
0
1223
6
22
2038
175
40
250
15
897
549
26
18
0
1480
7
37
99
29
69
288
45
135
69
20
133
8
445
8
58
0
4
56
183
82
2
0
6
151
37
51
108
462
433
350
1789
3431
2148
161
167
8
2338
1153
1161
69
228
35440
5304
621
492
3
6850
12095
342
0
0
24070
103
366
57723
6820
1068
2406
111
15078
17793
585
144
0
40563
132
571
58344
6945
1519
3714
290
15829
18241
712
839
48
42850
0
3
6038
94
193
28
0
684
431
41
0
0
6528
69
225
29402
5210
428
464
3
6166
11664
301
0
0
17542
34
138
22283
1516
447
1914
108
8228
5698
243
144
0
16493
29
205
621
125
451
1308
179
751
448
127
695
48
2287
12
124
0
4
124
295
127
3
0
13
297
76
106
27418
6071
11587
12971
917
5154
5516
1384
638
13709
85514
142760
150034
14040
71474
57246
7274
103
2 Krasnodar Kray
12
1335
242
392
452
31
211
150
60
107
2 Stavropol Kray
12
20
0
2
11
0
0
2
9
111
2 Arkhangelsk oblast
12
11643
3413
8289
9915
533
2880
4876
1626
112
2 Astrakhan oblast
12
48
0
0
0
0
0
0
0
114
2 Belgorod oblast
12
73
7
40
46
1
6
33
6
115
2 Bryansk oblast
12
638
573
632
635
223
350
59
3
117
2 Vladimir oblast
12
995
425
942
969
43
382
517
27
118
2 Volgograd oblast
12
203
0
0
10
0
0
0
10
119
2 Vologda oblast
12
7190
4952
6130
6480
1043
3909
1178
350
120
2 Voronezh oblast
12
245
0
37
102
0
0
37
65
3093
1446
2967
3025
84
1362
1521
58
122
2 Nizhni Novgorod oblast12
123
2 Nenets a.okr.
12
255
0
2
25
0
0
2
23
124
2 Ivanovo oblast
12
823
670
815
822
25
645
145
7
127
2 Kaliningrad oblast
12
115
67
77
86
4
63
10
9
128
2 Tver oblast
12
2510
2116
2344
2371
291
1825
228
27
129
2 Kaluga oblast
12
980
759
963
974
45
714
204
11
133
2 Kirov oblast
12
5580
2718
5214
5404
662
2056
2496
190
134
2 Kostroma oblast
12
3073
2072
2980
3035
265
1807
908
55
136
2 Samara oblast
12
365
81
105
173
0
81
24
68
138
2 Kursk oblast
12
80
48
70
71
5
43
22
1
1720
950
1595
1651
444
506
645
56
139
2 Komi-Permyak a.okr. 12
141
2 Leningrad oblast
12
4215
1421
3471
3635
494
927
2050
164
142
2 Lipetsk oblast
12
80
33
58
79
8
25
25
21
146
2 Moscow oblast
12
1835
1426
1727
1782
114
1312
301
55
147
2 Murmansk oblast
12
2660
1
7
108
0
1
6
101
149
2 Novgorod oblast
12
3133
2157
2805
2836
243
1914
648
31
153
2 Orenburg oblast
12
53
2
6
18
0
2
4
12
154
2 Oryel oblast
12
53
41
51
52
7
34
10
1
156
2 Penza oblast
12
575
243
384
521
6
237
141
137
157
2 Perm oblast
12
5190
3226
4123
4364
1007
2219
897
241
158
2 Pskov oblast
12
2053
1290
1874
1885
33
1257
584
11
160
2 Rostov oblast
12
18
0
0
10
0
0
0
10
161
2 Ryazan oblast
12
730
420
689
730
120
300
269
41
163
2 Saratov oblast
12
375
0
18
42
0
0
18
24
166
2 Smolensk oblast
12
563
509
535
538
1
508
26
3
168
2 Tambov oblast
12
255
132
227
246
28
104
95
19
170
2 Tula oblast
12
200
177
197
200
14
163
20
3
173
2 Ulyanovsk oblast
12
763
86
232
537
0
86
146
305
178
2 Yaroslavl oblast
12
783
740
752
752
15
725
12
0
179
2 Adigei Republic
12
153
35
59
70
1
34
24
11
2568
435
894
1417
73
362
459
523
180
2 Bashkortostan Republic12
182
2 Daghestn Republic
12
240
7
18
43
1
6
11
25
183
2 Kabardino-Balkarian Republic
12
165
77
109
112
17
60
32
3
12
3
0
0
0
0
0
0
0
185
2 Kalmyk-Khalm-Tangch Republic
186
2 Karelia Republic
12
6885
840
3854
5299
267
573
3014
1445
187
2 Komi Republic
12
10830
1310
5528
8273
496
814
4218
2745
188
2 Mari-El Republic
12
878
346
739
809
3
343
393
70
189
2 Mordovian SSR
12
478
265
408
459
64
201
143
51
190
2 North-Ossetian SSR 12
135
54
67
82
14
40
13
15
12
473
58
107
117
20
38
49
10
191
2 Karachai-Cherkess Republic
192
2 Tatarstan Republic
12
533
141
287
428
0
141
146
141
194
2 Udmurt Republic
12
1400
880
1300
1318
137
743
420
18
12
330
77
127
135
14
63
50
8
196
2 Checheno-Ingush Republic
197
2 Chuvash Republic
12
643
176
441
523
7
169
265
82
101
3 Altai Kray
12
2920
811
1677
1992
146
665
866
315
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used:
VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
24
0
477
0
7
0
0
9
29
127
0
11
0
0
0
0
11
0
64
1
0
36
1
0
320
0
6
0
35
20
0
1
0
62
0
8
0
110
0
3
286
27
0
0
731
1054
5
12
0
4
51
0
4
95
139
858
9
1244
47
19
3
26
184
681
16
67
220
1
28
138
6
164
37
128
7
70
545
0
51
2231
296
30
0
19
806
167
7
0
272
24
0
0
116
30
79
864
172
53
2
856
1504
64
6
53
351
54
82
190
25
790
3689
0
46953
0
79
6561
5283
0
69578
0
18154
0
9582
1036
29986
10527
37622
29037
795
619
14016
20223
430
20449
11
30041
16
497
2651
46046
18434
0
4708
0
7695
1496
2643
848
10593
544
5325
77
1250
0
11452
18515
4156
3115
989
1064
1513
11245
1186
2085
9379
5272
19
88831
0
416
7136
9857
0
80488
409
31736
10
10891
1145
32159
12538
59336
37687
954
846
19856
39238
648
23126
51
36164
43
590
3653
54121
23804
0
7050
154
7969
2306
2831
1686
10708
808
8693
182
1598
0
37880
54049
7346
4310
1144
1616
2584
14962
1752
4188
16272
5686
71
96296
0
450
7153
10003
46
82128
768
32078
91
10926
1206
32301
12603
60377
37937
1251
856
20149
40001
767
23411
441
36317
97
595
4354
55381
23874
66
7291
285
7996
2424
2852
2955
10709
895
10899
348
1615
0
44486
67594
7655
4570
1231
1675
3188
15061
1803
4498
17761
624
0
9229
0
16
2849
618
0
16742
0
1066
0
355
57
4065
575
11063
4765
0
73
7457
8338
93
1639
0
3503
0
98
73
16711
467
0
1519
0
20
310
260
0
209
29
1184
10
333
0
4588
8438
41
804
311
445
0
2186
255
83
2068
3065
0
37724
0
63
3712
4665
0
52836
0
17088
0
9227
979
25921
9952
26559
24272
795
546
6559
11885
337
18810
11
26538
16
399
2578
29335
17967
0
3189
0
7675
1186
2383
848
10384
515
4141
67
917
0
6864
10077
4115
2311
678
619
1513
9059
931
2002
7311
1583
19
41878
0
337
575
4574
0
10910
409
13582
10
1309
109
2173
2011
21714
8650
159
227
5840
19015
218
2677
40
6123
27
93
1002
8075
5370
0
2342
154
274
810
188
838
115
264
3368
105
348
0
26428
35534
3190
1195
155
552
1071
3717
566
2103
6893
414
52
7465
0
34
17
146
46
1640
359
342
81
35
61
142
65
1041
250
297
10
293
763
119
285
390
153
54
5
701
1260
70
66
241
131
27
118
21
1269
1
87
2206
166
17
0
6606
13545
309
260
87
59
604
99
51
310
1489
FSU REPUBLICS
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
0
6778
4820
0
0
6871
4370
1337
9857
12000
14025
12719
14786
8786
3000
12387
14750
13680
0
0
14997
7923
8927
12645
11520
13024
7863
7400
10399
12997
11471
8000
0
13148
6221
6243
10935
8660
11126
7657
7021
9172
10375
9236
8149
0
11142
3910
5603
6272
4274
6575
4548
4011
5556
6525
6400
5218
6066
5134
1585
2141
2026
1082
2200
1612
1550
1392
1401
2047
1965
2051
2096
1181
14086 12321 11567 15311 13868 10378
5256
1851
51
1
599
0
15
0
0
16
31
260
0
11
0
0
0
0
14
0
110
2
0
37
1
0
420
0
8
0
46
24
0
1
0
121
0
15
0
141
0
9
426
58
0
0
1274
1693
7
11
1
8
79
0
10
159
224
15244
0
13757
0
11286
11450
12431
0
14050
0
12555
0
14301
15463
14171
13870
13842
14014
9815
12896
14754
14232
13030
14340
11000
13927
8000
12122
10909
14273
14290
0
11210
0
15118
11333
14932
9860
14315
15543
12241
11000
16234
0
13633
14134
12012
11755
18315
18345
10730
12778
15403
11847
11565
6912
6147
4591
0
5296
6539
5467
4790
4684
5550
5876
3565
5244
6663
5202
6005
5482
4535
4342
7116
5266
4659
5685
5134
3860
4908
4673
6865
5107
5230
6314
6509
5868
5554
8468
6100
6154
4166
5035
7717
4216
6595
5651
0
4572
4934
4413
5134
5968
5821
4292
5371
6385
3763
4719
2104
2080
1257
0
2051
0
0
1731
1076
2044
0
1024
0
0
2448
0
1245
1327
1724
1906
1851
1044
2073
0
1310
1057
1298
0
1319
1174
0
1837
912
1951
0
1925
0
1282
2457
2516
1487
2187
1923
0
1744
1607
1468
865
2109
1944
1551
924
2201
1680
1619
13449
9500
10717
0
10400
11291
10464
0
13130
11054
10696
5000
13363
14870
13720
13020
11380
12647
9086
12086
12449
11305
11172
13391
7286
12893
7167
11569
9513
13127
12702
0
10232
8556
14895
10159
14371
7267
14239
13695
9724
10111
14661
0
9829
9777
9940
10564
17075
15103
9003
11509
13795
9497
9703
6600
7321
12509
11184
10060
6253
4833
9987
12685
10028
5556
6000
12139
12580
6455
9712
0
9783
11265
10323
4600
12674
7529
10604
3640
13292
14023
13623
12939
11173
12500
7231
12056
12204
11004
9709
13137
4083
12806
5389
11442
8357
12690
12665
6600
9988
6786
14862
9854
14260
5503
14241
12786
7692
8093
14420
0
8395
8170
9462
9956
15012
14316
7449
11427
13356
8600
8916
0
13925
13971
13610
18070
8726
0
14084
14552
15923
0
0
17100
20138
0
17320
0
13074
12761
14437
0
16046
0
12653
0
14296
12727
13945
12663
16711
17963
0
14068
16796
16884
12358
14333
0
14421
0
13029
12523
16598
14186
0
12619
0
15190
11084
18108
0
13960
20912
16271
16674
19758
0
17159
17025
12240
12534
22653
22430
0
15996
18555
12444
14147
10689
12082
14033
12706
13971
8804
8795
12245
14762
13665
0
0
14341
14493
0
13099
0
10785
10610
12196
0
13517
0
12542
0
14308
15499
14204
13931
12915
13431
9790
12624
12975
12825
13213
14332
10592
13864
9663
11726
10885
13222
14290
0
10627
0
15100
11368
14649
9878
14316
15234
11431
11996
15299
0
11984
12380
12012
11473
16906
16284
10701
12197
14715
11876
11000
10559
7849
8588
0
10339
9803
8850
0
9261
10938
8930
5945
9002
11196
9526
9870
8699
9531
6588
10105
9051
9277
8582
8886
6544
9450
7315
9359
7125
8999
9193
0
8721
8723
10557
8496
9561
5738
9771
11104
7343
9909
10802
0
8769
8425
8125
8336
12130
11194
7347
8844
11312
7931
7964
APPENDIX II
Table A13 PRODUCTION POTENTIALS FOR TRADITIOONAL PRODUCTION FORESTRY SPECIES - ACCESSIBLE AREAS CURRENTLY UNDER FOREST
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) -------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
1693
202
322
455
43
159
120
133
53
1185
12555
3368
6188
7646
324
3044
2820
1458
852
4057
5300
378
930
1360
113
265
552
430
604
3337
988
0
0
0
0
0
0
0
0
987
6658
471
1069
1777
17
454
598
708
529
4348
6083
1370
2420
3629
183
1187
1050
1209
470
1983
5605
1
9
34
0
1
8
25
195
5376
750
211
293
378
42
169
82
85
34
339
14285
2361
4557
6235
35
2326
2196
1678
1335
6716
413
38
96
168
1
37
58
72
12
232
2035
6
219
731
0
6
213
512
198
1106
873
0
1
24
0
0
1
23
26
823
2875
1342
1972
2241
242
1100
630
269
94
540
2220
0
0
0
0
0
0
0
0
2220
483
65
300
366
0
65
235
66
9
107
2635
0
2
66
0
0
2
64
151
2418
1660
548
1118
1252
56
492
570
134
17
390
1958
455
1056
1372
4
451
601
316
5
581
4178
273
824
1502
0
273
551
678
240
2433
9003
5272
6409
6956
1146
4126
1137
547
41
2006
155
0
5
22
0
0
5
17
32
102
4765
2145
3287
3726
212
1933
1142
439
76
963
1593
500
1081
1240
42
458
581
159
48
304
4878
727
1614
2284
40
687
887
670
148
2445
1173
0
33
133
0
0
33
100
266
774
1520
233
463
731
52
181
230
268
101
687
3128
24
169
601
0
24
145
432
474
2052
3718
39
312
730
1
38
273
418
580
2407
2858
5
89
446
0
5
84
357
347
2064
1603
115
243
568
19
96
128
325
112
922
33823
50
629
2075
0
50
579
1446
2007
29741
Average annual biomass increments (000tons) ---------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
2237
3135
3738
590
1647
898
603
76
38238
59651
66783
4445
33793
21413
7132
1352
4703
8973
11128
1627
3076
4270
2155
1133
0
0
0
0
0
0
0
0
5302
9880
13121
207
5095
4578
3241
745
14604
23233
28897
2231
12373
8629
5664
727
7
65
173
0
7
58
108
253
2655
3260
3691
551
2104
605
431
59
27351
43739
51287
405
26946
16388
7548
2043
386
832
1131
16
370
446
299
15
52
1868
4394
0
52
1816
2526
297
0
8
101
0
0
8
93
30
15747
20409
21577
3138
12609
4662
1168
148
0
0
0
0
0
0
0
0
713
2442
2785
0
713
1729
343
15
0
16
354
0
0
16
338
195
6219
10727
11387
755
5464
4508
660
30
5330
10572
11974
49
5281
5242
1402
8
3425
7720
11266
0
3425
4295
3546
414
69231
78230
80695
18011
51220
8999
2465
65
0
30
85
0
0
30
55
44
24979
34378
36604
2814
22165
9399
2226
132
5505
10025
10831
623
4882
4520
806
71
8921
16312
19796
585
8336
7391
3484
253
0
237
765
0
0
237
528
469
2875
4394
5498
839
2036
1519
1104
163
273
1316
3194
2
271
1043
1878
687
426
2472
4296
14
412
2046
1824
867
53
658
2179
0
53
605
1521
504
1230
2135
3486
241
989
905
1351
148
530
4743
10847
0
530
4213
6104
2711
90232
144384
234616
37144
21010
58154
64690
37387
102077
73677
50740
124417
6903
2718
9621
30241
18292
48533
27546
16377
43923
8987
13353
22340
3631
9195
12826
12902
84435
97337
158
18
938
695
1170
4095
2870
5498
10550
0
395
2828
3683
4348
4985
6900
5803
6030
6103
260
4970
2490
12718
5360
1453
770
23
713
2808
248
0
18
1
169
75
161
1788
1476
2393
5322
0
161
485
1483
1457
2595
2350
526
1248
1472
18
790
895
3016
1582
325
131
6
8
151
0
0
60
5
396
212
384
2268
1984
3775
7741
0
238
914
2336
2060
3445
3193
1385
2083
2743
62
1307
1462
3852
2535
497
223
7
17
192
2
0
90
8
536
306
531
2589
2223
4302
8715
0
270
1009
2422
2219
3528
3347
1688
2275
3068
116
1441
1584
4422
3272
541
268
11
31
230
10
0
1
0
29
10
1
214
620
1027
1896
0
8
68
532
329
365
331
9
293
341
3
174
152
1219
407
39
25
3
3
56
0
0
17
1
140
65
160
1574
856
1366
3426
0
153
417
951
1128
2230
2019
517
955
1131
15
616
743
1797
1175
286
106
3
5
95
0
0
42
4
227
137
223
480
508
1382
2419
0
77
429
853
603
850
843
859
835
1271
44
517
567
836
953
172
92
1
9
41
2
0
30
3
140
94
147
321
239
527
974
0
32
95
86
159
83
154
303
192
325
54
134
122
570
737
44
45
4
14
38
8
0
4
1
37
101
10
68
116
21
98
0
0
15
16
29
0
49
55
32
95
35
18
0
436
487
21
6
2
8
14
2
0
63
9
365
288
628
1438
531
1174
1738
0
124
1803
1244
2099
1457
3504
4059
3723
2940
108
3511
905
7860
1601
891
496
8
674
2563
235
0
273
9
1832
979
2532
27870
21655
31962
65988
0
2496
6747
23532
21576
39429
34288
7287
18099
21917
234
12244
13480
54933
19308
4797
1991
88
100
2605
0
0
716
46
3828
2306
5683
33301
26808
46279
89019
0
3311
10992
32276
27739
48203
42681
15609
25588
33603
580
17580
19171
62815
26542
6460
2809
99
170
2967
18
0
98880
30102
45378
51052
8155
21947
15276
5674
1776
46039
438251
587199
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used:
VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
512814
754840
797710
250371
377732
439824
763185 1132572 1237534
111501
39211
150712
401313
211160
612473
242026
127361
369387
42870
62092
104962
5659
13878
19537
901
61
4674
2848
6478
35396
28098
49437
94657
0
3521
11538
32857
28715
48738
43540
17411
26649
35550
830
18386
19837
65565
30179
6704
3054
122
247
3161
61
0
15
0
306
142
27
3880
9881
14347
25667
0
139
1052
9654
5988
6558
5970
158
5449
6489
55
3372
2802
26803
6317
736
483
50
36
1165
0
0
258
9
1526
837
2505
23990
11774
17615
40321
0
2357
5695
13878
15588
32871
28318
7129
12650
15428
179
8872
10678
28130
12991
4061
1508
38
64
1440
0
0
443
37
1996
1327
3151
5431
5153
14317
23031
0
815
4245
8744
6163
8774
8393
8322
7489
11686
346
5336
5691
7882
7234
1663
818
11
70
362
18
0
185
15
846
542
795
2095
1290
3158
5638
0
210
546
581
976
535
859
1802
1061
1947
250
806
666
2750
3637
244
245
23
77
194
43
0
6
2
78
225
24
144
225
38
169
0
1
29
41
52
0
88
107
57
187
52
29
1
686
840
47
13
4
13
24
3
0
619215
137541
300710
148948
32016
3185
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
11074
9736
8215 13641 10384
7459
4545
1446
11353
9640
8734 13706 11101
7592
4893
1587
12442
9648
8182 14449 11622
7739
5008
1877
0
0
0
0
0
0
0
0
11257
9242
7384 11976 11234
7650
4576
1407
10660
9600
7963 12183 10427
8218
4684
1546
7000
7222
5088
0 10908
6958
4282
1299
12583 11126
9765 13006 12465
7395
5093
1738
11584
9598
8226 11523 11586
7463
4498
1530
10158
8667
6732 11026
9915
7722
4150
1277
8667
8530
6011
0
9405
8512
4933
1502
0
8000
4208
0
0
6754
4078
1185
11734 10349
9628 12973 11460
7401
4344
1573
0
0
0
0
0
0
0
0
10969
8140
7609
0 11040
7348
5174
1618
0
8000
5364
0
0
7216
5276
1297
11349
9595
9095 13414 11115
7904
4929
1688
11714 10011
8727 12120 11703
8722
4439
1724
12546
9369
7501
0 12528
7800
5229
1725
13132 12206 11601 15718 12414
7917
4506
1584
0
6000
3864
0
0
6010
3300
1378
11645 10459
9824 13258 11469
8231
5074
1737
11010
9274
8735 14911 10652
7775
5083
1461
12271 10107
8667 14804 12141
8329
5197
1704
0
7182
5752
0
0
7304
5288
1762
12339
9490
7521 16047 11253
6605
4120
1612
11375
7787
5314
9946 11065
7184
4348
1451
10923
7923
5885 15405 10844
7482
4360
1494
10600
7393
4886
0 10615
7183
4262
1450
10696
8786
6137 12546 10278
7085
4152
1323
10600
7541
5227
0 10594
7282
4221
1351
13806 11669 10827 16153 13270
11917 10103
8668 14426 11544
13124 11095
9947 15665 12620
8786
7777
8410
4770
4650
4698
1559
1509
1523
14873
15586
10887
12880
15611
15244
13763
12897
11768
0
15373
13670
14590
13822
14740
14023
13780
13245
13643
11686
14411
14369
15656
11058
14198
14164
11384
11808
15152
0
0
10449
9386
8807
9697
14115
11309
10137
10361
9523
0
10605
9889
10248
10214
10322
9958
9686
8971
9193
7887
10313
10037
9432
7592
9654
8909
8483
8008
8868
7688
0
6112
5616
6038
5776
5392
6526
5408
5987
5790
0
6501
5761
6796
6133
6416
5568
5944
5540
5987
4594
5996
5454
4820
4934
5579
5476
5329
5334
5127
5105
0
1704
1766
2130
2228
2502
2128
1946
1804
1731
0
2386
1881
2548
1802
1947
1804
1955
1768
1968
1491
1568
2196
1573
1727
2264
2146
1792
1664
1682
1479
0
14559 12940 12129 16866 13702
9750
5643
1793
15167
9000
10840
13053
15727
15587
14671
13356
12399
0
15503
13911
15868
14809
15194
14591
13854
14502
14889
13000
15499
15061
18214
12205
14760
15198
14667
12500
17252
0
0
11933
9200
9667
10877
14799
14683
13512
12259
11500
0
13912
12026
13817
13466
13992
13367
11270
12284
12250
9355
13451
13113
16307
10470
12998
12596
14143
10000
15453
9000
0
10011
7625
8720
9307
12200
13672
12640
11492
10861
0
13041
11435
13566
12941
13815
13009
10315
11714
11587
7155
12759
12523
14827
9223
12392
11396
11091
7968
13743
6100
0
15430
0
10511
13921
18377
18137
15925
13969
13541
0
18056
15407
18133
18202
17992
18060
18040
18587
19046
16032
19435
18378
21992
15513
18941
19395
16686
14129
20635
0
0
APPENDIX II
Table A14 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - EXCLUDING CULTIVATED AREAS, URBAN AREAS AND AREAS CURRENTLY UNDER FOREST
ADM REG NAME
2
LC
4 Mongolia
12
11
12
13
14
15
16
17
18
19
20
21
22
23
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
147800
81
569
4858
5
76
488
4289
4901
138043
Average annual biomass increments (000tons) --------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
829
3936
21943
77
752
3107
18007
7189
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
10235
6917
4517 16415
9925
6372
4199
1467
1788
4578
1680
370
1515
214330
12170
210
1463
10
2655
40375
640
37
32
584
177
59
558
31
90
690
2
0
0
267
117
89
1356
204
139
2478
143
180
1254
4
0
0
445
212
387
1435
209
209
8337
377
191
1312
6
7
8
510
0
0
131
0
8
72
3
17
93
1
0
0
66
37
32
453
177
51
486
28
73
597
1
0
0
201
80
57
772
27
80
1920
112
90
564
2
0
0
178
95
298
79
5
70
5859
234
11
58
2
7
8
65
64
638
0
0
104
2385
199
0
0
2
7
0
14
1512
3244
244
160
1201
203608
11594
19
151
2
2641
40367
115
375
335
7712
1894
777
5880
340
1206
9600
22
0
0
3867
913
735
15883
2139
1453
21477
1109
2101
15083
45
0
0
5793
1283
2666
16342
2156
1841
50198
2124
2164
15488
59
38
53
6220
0
1
1801
2
160
982
52
239
1357
12
0
0
1065
375
334
5911
1892
617
4898
288
967
8243
10
0
0
2802
538
400
8171
245
676
15597
769
895
5483
23
0
0
1926
370
1931
459
17
388
28721
1015
63
405
14
38
53
427
88
1389
0
0
236
3760
295
0
0
6
14
0
33
10135
10469
13205
10701
13169
10538
10968
13400
13913
11000
0
0
14483
281784
2527
6409
13200
391
2136
3882
6791
3413
264858
32008
66731
100632
5671
26337
34723
33901
5821
12666 10412
Krasnodar Kray
12
625
Stavropol Kray
12
965
Arkhangelsk oblast
12
11818
Astrakhan oblast
12
4380
Belgorod oblast
12
0
Bryansk oblast
12
0
Vladimir oblast
12
13
Volgograd oblast
12
1890
Vologda oblast
12
1253
Voronezh oblast
12
258
Nizhni Novgorod oblast12
298
Nenets a.okr.
12
15018
Ivanovo oblast
12
25
Kaliningrad oblast
12
30
Tver oblast
12
118
Kaluga oblast
12
65
Kirov oblast
12
235
Kostroma oblast
12
253
Samara oblast
12
5
Kursk oblast
12
0
Komi-Permyak a.okr. 12
170
Leningrad oblast
12
800
Lipetsk oblast
12
0
Moscow oblast
12
193
Murmansk oblast
12
6555
Novgorod oblast
12
233
Orenburg oblast
12
2480
Oryel oblast
12
0
Penza oblast
12
0
Perm oblast
12
325
Pskov oblast
12
265
Rostov oblast
12
453
Ryazan oblast
12
405
Saratov oblast
12
615
Smolensk oblast
12
0
Tambov oblast
12
0
Tula oblast
12
13
Ulyanovsk oblast
12
18
Yaroslavl oblast
12
83
Adigei Republic
12
103
Bashkortostan Republic12
808
Daghestn Republic
12
4188
Kabardino-Balkarian Republic
12
663
Kalmyk-Khalm-Tangch Republic
12
6183
Karelia Republic
12
3005
Komi Republic
12
8200
Mari-El Republic
12
100
Mordovian SSR
12
125
North-Ossetian SSR 12
378
Karachai-Cherkess Republic
12
623
Tatarstan Republic
12
8
Udmurt Republic
12
3
Checheno-Ingush Republic
12
960
Chuvash Republic
12
0
Altai Kray
12
4503
126
62
545
0
0
0
3
0
700
4
109
0
13
8
87
54
116
155
0
0
82
294
0
135
0
128
0
0
0
137
139
0
207
0
0
0
11
0
68
38
42
86
69
0
277
433
40
87
61
70
4
2
109
0
1043
203
197
2210
0
0
0
11
0
974
15
277
2
25
16
101
63
214
240
0
0
153
671
0
180
38
176
0
0
0
276
231
0
390
0
0
0
12
0
69
51
112
168
106
0
1885
1962
84
123
70
126
6
2
190
0
2026
336
264
3052
0
0
0
11
0
1000
58
289
95
25
20
103
65
231
247
1
0
160
701
0
190
166
176
2
0
0
295
237
64
406
9
0
0
12
4
69
54
191
489
121
0
2496
2891
87
125
92
149
7
2
360
0
2899
36
9
71
0
0
0
1
0
117
0
5
0
1
0
17
0
38
67
0
0
24
73
0
33
0
12
0
0
0
68
13
0
70
0
0
0
0
0
4
2
10
17
24
0
16
168
0
24
21
20
0
1
24
0
312
90
53
474
0
0
0
2
0
583
4
104
0
12
8
70
54
78
88
0
0
58
221
0
102
0
116
0
0
0
69
126
0
137
0
0
0
11
0
64
36
32
69
45
0
261
265
40
63
40
50
4
1
85
0
731
77
135
1665
0
0
0
8
0
274
11
168
2
12
8
14
9
98
85
0
0
71
377
0
45
38
48
0
0
0
139
92
0
183
0
0
0
1
0
1
13
70
82
37
0
1608
1529
44
36
9
56
2
0
81
0
983
133
67
842
0
0
0
0
0
26
43
12
93
0
4
2
2
17
7
1
0
7
30
0
10
128
0
2
0
0
19
6
64
16
9
0
0
0
4
0
3
79
321
15
0
611
929
3
2
22
23
1
0
170
0
873
37
15
272
0
0
0
0
0
0
139
0
38
0
0
0
0
0
0
1
0
0
2
0
0
140
0
7
0
0
2
0
14
0
4
0
0
0
5
0
1
121
192
3
0
175
558
0
0
0
5
0
0
21
0
156
252
686
8481
4380
0
0
2
1890
252
60
9
14865
0
10
14
0
4
6
3
0
10
97
0
2
6249
55
2471
0
0
29
28
374
0
602
0
0
0
9
13
47
496
3499
538
6182
327
4751
13
0
285
468
2
0
578
0
1447
2226
787
7094
0
0
0
34
0
8762
38
1286
0
156
103
1220
812
1583
2368
0
0
1046
3926
0
1779
0
1646
0
0
0
1947
1848
0
2300
0
0
0
175
0
978
613
319
1118
1076
0
3386
6102
490
1031
995
1066
40
35
1580
0
12887
3082
2053
21147
0
0
0
107
0
11358
131
2757
14
258
203
1363
907
2465
3217
0
0
1701
7279
0
2187
224
2080
0
0
0
3209
2637
0
3944
0
0
0
183
0
985
757
819
1905
1453
0
17177
18889
852
1326
1091
1652
53
35
2441
0
20882
4016
2453
24865
0
0
0
107
0
11465
368
2823
346
258
229
1374
917
2556
3251
3
0
1742
7421
0
2247
685
2082
7
0
0
3321
2667
327
4036
37
0
0
184
12
985
775
1142
3945
1544
0
20446
23315
866
1339
1226
1788
57
35
3449
0
25192
746
137
1205
0
0
0
15
0
1815
0
58
0
18
0
240
0
595
1271
0
0
362
1229
0
461
0
186
0
0
0
1129
188
0
878
0
0
0
0
0
61
54
77
267
443
0
269
2899
0
301
365
348
0
16
403
0
4596
1480
650
5889
0
0
0
19
0
6947
38
1228
0
138
103
980
812
988
1097
0
0
684
2697
0
1318
0
1460
0
0
0
818
1660
0
1422
0
0
0
175
0
917
559
242
851
633
0
3117
3203
490
730
630
718
40
19
1177
0
8291
856
1266
14053
0
0
0
73
0
2596
93
1471
14
102
100
143
95
882
849
0
0
655
3353
0
408
224
434
0
0
0
1262
789
0
1644
0
0
0
8
0
7
144
500
787
377
0
13791
12787
362
295
96
586
13
0
861
0
7995
934
400
3718
0
0
0
0
0
107
237
66
332
0
26
11
10
91
34
3
0
41
142
0
60
461
2
7
0
0
112
30
327
92
37
0
0
1
12
0
18
323
2040
91
0
3269
4426
14
13
135
136
4
0
1008
0
4310
88
27
315
0
0
0
0
0
0
277
0
41
0
0
0
0
0
0
2
0
0
2
0
0
169
0
9
0
0
2
0
28
0
6
0
0
0
7
0
2
150
398
6
0
292
875
0
0
1
11
0
0
37
0
257
FSU REPUBLICS
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
17667
12694
13017
0
0
0
11333
0
12517
9500
11798
0
12000
12875
14023
15037
13647
15277
0
0
12756
13354
0
13178
0
12859
0
0
0
14212
13295
0
11111
0
0
0
15909
0
14382
16132
7595
13000
15594
0
12224
14092
12250
11851
16311
15229
10000
17500
14495
0
12356
7803
8258
11713
10485
10453
8667
7755
11672
12028
11250
0
0
13018
15182
10421
9569
0
0
0
9727
0
11661
8733
9953
7000
10320
12688
13495
14397
11519
13404
0
0
11118
10848
0
12150
5895
11818
0
0
0
11627
11416
0
10113
0
0
0
15250
0
14275
14843
7313
11339
13708
0
9112
9627
10143
10780
15586
13111
8833
17500
12847
0
10307
6052
6889
11388
10316
8809
6021
5634
11330
11805
9833
5429
6625
12196
0
13782
13732
13463
19101
13568
18465
14365
14640
16649
0
0
16055
10094
6742
10439
7068
13047 10579
10702
8957
12117
8460
10071
8122
10138
6872
13163
9971
13815
9723
16650
9254
0
0
0
0
13935 10815
7624 14504 12330
11952
9292
8147
0
0
0
9727
0
11465
6345
9768
3642
10320
11450
13340
14108
11065
13162
3000
0
10888
10586
0
11826
4127
11830
3500
0
0
11258
11253
5109
9941
4111
0
0
15333
3000
14275
14352
5979
8067
12760
0
8192
8065
9954
10712
13326
12000
8143
17500
9581
0
8690
20913
15287
17050
0
0
0
14635
0
15467
0
12575
0
14130
0
13988
0
15670
18912
0
0
15360
16731
0
13996
0
15179
0
0
0
16634
14262
0
12531
0
0
0
0
0
13841
21824
7808
15533
18152
0
16820
17234
0
12474
17485
17789
0
18036
16827
0
14754
16466
12250
12418
0
0
0
10635
0
11918
9470
11836
0
11781
13078
14097
15019
12681
12460
0
0
11713
12216
0
12949
10485
12551
0
0
0
11920
13190
0
10398
0
0
0
15282
0
14290
15712
7516
12364
14084
0
11952
12077
12223
11654
15665
14345
11375
13928
13767
0
11335
3903
6471
5782
3295
5504
4902
4339
5946
6925
7059
5589
6484
6543
1374
2175
0
1587
2270
1577
1482
0
2143
2263
1859
0
2325
8945
4992
1706
11089
9349
8442
0
0
0
9102
0
9463
8479
8732
6006
8479
11843
10030
10404
8983
10005
0
0
9229
8905
0
9037
5905
9010
0
0
0
9093
8564
0
9008
0
0
0
10121
0
9238
10655
7096
9611
10286
0
8578
8363
8187
8221
10657
10407
8249
0
10622
0
8129
7023
5978
4416
0
0
0
0
0
4173
5442
5505
3584
0
6398
5016
5809
5263
4888
3373
0
5548
4680
0
5830
3595
4961
3041
0
0
6015
5148
5070
5874
4316
0
0
5773
3366
0
6632
4095
6346
6009
0
5354
4765
4973
5615
6208
5886
5651
1652
5920
0
4937
2348
1852
1156
0
0
0
0
0
941
1992
0
1087
0
0
2433
0
0
1337
1353
0
1833
981
0
0
1207
0
1262
0
0
963
0
1954
923
1418
0
0
0
1357
2427
2253
1240
2076
1859
0
1669
1567
1425
0
1858
2074
0
0
1787
0
1644
APPENDIX II
Table A14 PRODUCTION POTENTIALS FOR TRADITIONAL PRODUCTION FORESTRY SPECIES - EXCLUDING CULTIVATED AREAS, URBAN AREAS AND AREAS CURRENTLY UNDER FOREST
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr.
12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
231
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
13
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Shanghai
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
4118
43
67
107
12
31
24
40
52
3958
5383
1015
1889
2213
192
823
874
324
108
3061
1490
138
535
737
10
128
397
202
78
674
71523
0
0
0
0
0
0
0
0
71522
18580
1370
3011
4270
78
1292
1641
1259
797
13513
6033
1923
2635
3401
344
1579
712
766
427
2204
9323
0
13
21
0
0
13
8
78
9223
1318
398
656
822
70
328
258
166
16
481
8388
196
402
700
2
194
206
298
439
7249
350
3
22
101
0
3
19
79
35
214
9120
1
202
570
0
1
201
368
146
8381
25808
0
103
309
0
0
103
206
935
24564
925
109
153
307
21
88
44
154
150
468
60873
0
0
0
0
0
0
0
0
60847
2543
171
650
1096
0
171
479
446
285
1162
31205
0
8
507
0
0
8
499
426
30272
8383
1697
3292
4116
193
1504
1595
824
216
4051
5148
1099
2010
2860
37
1062
911
850
250
2038
973
60
211
282
0
60
151
71
21
661
2898
2048
2311
2383
354
1694
263
72
3
512
1038
0
20
300
0
0
20
280
184
554
10153
3887
6214
7499
249
3638
2327
1285
47
2607
7145
3328
4547
5145
118
3210
1219
598
272
1728
20210
3552
7511
11604
125
3427
3959
4093
1268
7338
41490
0
324
2155
0
0
324
1831
2722
36605
1518
96
230
405
1
95
134
175
406
706
11328
37
526
1690
0
37
489
1164
1397
8241
10333
46
361
798
0
46
315
437
951
8584
5498
9
77
288
0
9
68
211
241
4968
1360
323
650
802
16
307
327
152
37
521
107800
57
297
1222
0
57
240
925
2483
104078
Average annual biomass increments (000tons) --------------------------------------------VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
497
671
824
173
324
174
153
69
11700
18715
20426
2607
9093
7015
1711
159
1765
4354
5254
149
1616
2589
900
148
0
0
0
0
0
0
0
0
15421
27738
33171
1133
14288
12317
5433
1196
21207
27162
30901
4405
16802
5955
3739
631
3
103
135
0
3
100
32
98
5059
6834
7714
902
4157
1775
880
29
2411
4016
5212
20
2391
1605
1196
618
29
175
457
0
29
146
282
49
10
1813
3551
0
10
1803
1738
224
0
712
1455
0
0
712
743
1039
1173
1486
2161
276
897
313
675
237
0
0
0
0
0
0
0
0
1779
5597
7754
0
1779
3818
2157
453
0
57
2208
0
0
57
2151
591
18985
32228
36232
2546
16439
13243
4004
350
12845
20282
24337
510
12335
7437
4055
425
713
1899
2285
0
713
1186
386
26
24987
27116
27498
5695
19292
2129
382
3
0
114
1168
0
0
114
1054
255
45259
64153
70776
3410
41849
18894
6623
64
34691
44087
46836
1516
33175
9396
2749
439
42116
74285
94421
1877
40239
32169
20136
2345
2
2282
12157
0
2
2280
9875
4904
1123
2190
2781
12
1111
1067
591
610
358
3596
8450
0
358
3238
4854
1972
508
2902
4806
0
508
2394
1904
1452
97
586
1437
0
97
489
851
329
3468
5932
6625
205
3263
2464
693
56
615
2426
6430
0
615
1811
4004
3275
75204
496758
571962
4501
22649
27150
11629
40953
52582
15352
59609
74961
986
2134
3120
3515
20515
24030
7128
18304
25432
3723
18656
22379
1752
14626
16378
58039
422432
480471
59965
259708
319673
121941
404393
526334
140711
492654
633365
16036
30032
46068
43929
229676
273605
61976
144685
206661
18770
88261
107031
2745
22303
25048
673
78
6618
6105
515
1193
1468
2573
9320
0
275
500
1465
4710
5280
4623
540
2330
0
848
24765
6493
11850
90058
9673
31640
3505
153305
106460
69645
10
76
0
1154
620
94
336
393
309
4243
0
85
71
478
2077
1833
1293
39
469
2878
74
1102
2527
3392
2530
1152
904
26
160
129
53
0
228
6
2858
1530
144
527
710
482
5510
0
129
135
766
2720
2647
1938
107
829
4448
232
1685
3870
4276
5055
1928
1656
76
468
312
190
0
315
8
4219
2412
161
615
995
1244
7186
0
132
159
772
2865
2795
2111
140
922
4712
389
1814
4129
4670
13926
2539
2741
711
1294
459
894
0
0
0
141
91
8
39
133
71
1113
0
24
8
36
574
188
165
0
91
906
14
293
424
1221
392
114
264
2
27
32
4
0
76
0
1013
529
86
297
260
238
3130
0
61
63
442
1503
1645
1128
39
378
1972
60
809
2103
2171
2138
1038
640
24
133
97
49
0
152
6
1704
910
50
191
317
173
1267
0
44
64
288
643
814
645
68
360
1570
158
583
1343
884
2525
776
752
50
308
183
137
0
87
2
1361
882
17
88
285
762
1676
0
3
24
6
145
148
173
33
93
264
157
129
259
394
8871
611
1085
635
826
147
704
0
14
2
219
806
24
35
172
262
630
0
0
3
0
56
0
37
9
10
66
102
13
0
320
3039
161
425
139
515
98
409
0
343
67
2178
2888
330
543
300
1067
1504
0
143
338
693
1789
2485
2474
390
1398
0
355
22937
2363
6860
73093
6972
28474
2655
151495
105903
68343
9
1130
0
12949
7519
1477
5231
5709
4024
53039
0
1349
999
6905
30814
27755
18979
544
6793
47970
939
17433
37950
61786
27205
16998
12831
297
1888
1660
452
0
2612
60
28039
16591
2058
7439
8892
5743
63983
0
1795
1633
9796
37241
36237
25217
1186
10133
63429
2176
23478
51276
70756
45203
24842
19855
669
4208
2842
1457
3
3088
73
36034
22095
2192
8029
10466
9287
72506
0
1819
1769
9830
38109
37083
26140
1372
10670
65032
2868
24201
52698
72686
88316
28429
25718
3946
8617
3437
4733
4
5
0
1441
1240
146
713
2105
969
15201
0
430
129
530
10473
3417
2989
9
1643
18493
228
5551
8114
27280
5788
2047
4755
28
445
530
33
0
1125
0
11508
6279
1331
4518
3604
3055
37838
0
919
870
6375
20341
24338
15990
535
5150
29477
711
11882
29836
34506
21417
14951
8076
269
1443
1130
419
0
1482
60
15090
9072
581
2208
3183
1719
10944
0
446
634
2891
6427
8482
6238
642
3340
15459
1237
6045
13326
8970
17998
7844
7024
372
2320
1182
1005
3
476
13
7995
5504
134
590
1574
3544
8523
0
24
136
34
868
846
923
186
537
1603
692
723
1422
1930
43113
3587
5863
3277
4409
595
3276
1
23
5
450
1757
54
76
340
417
1036
0
0
6
0
103
0
67
17
18
136
143
22
0
508
4906
351
760
227
880
150
645
0
556518
28497
45462
65329
6375
22122
16965
19867
7566
488389
412625
568849
671247
114732
297893
156224
102398
13097
Note: Annual biomass increments and annual biomass yields refer to total biomass. The following partitioning may be used: VS conditions: stem+branchwood/twigs+leaves/roots, 60/20/20; S and MS: 50/20/30; mS and VmS: 40/20/40.
Average annual biomass yield (kg/ha) ------------------------------VS+SVS...MSVS...mS
VS
S
MS
mS
vmS
11558 10015
7701 14257 10488
7170
3850
1322
11527
9907
9230 13558 11052
8026
5286
1470
12790
8138
7129 14731 12642
6520
4449
1891
0
0
0
0
0
0
0
0
11256
9212
7768 14558 11057
7505
4315
1500
11028 10308
9086 12796 10641
8360
4879
1478
3000
7923
6429
0 10843
7614
3734
1258
12711 10418
9384 12911 12673
6878
5316
1836
12301
9990
7446 10768 12318
7782
4018
1409
9667
7955
4525
0 10655
7680
3560
1406
10000
8975
6230
0
9315
8958
4729
1528
0
6913
4709
0
0
6937
3612
1111
10761
9712
7039 13251 10168
7122
4379
1581
0
0
0
0
0
0
0
0
10404
8611
7075
0 10393
7968
4838
1591
0
7125
4355
0
0
7061
4309
1389
11187
9790
8803 13209 10933
8302
4861
1621
11688 10091
8509 13620 11615
8166
4771
1701
11883
9000
8103
0 11812
7839
5427
1204
12201 11733 11539 16104 11388
8096
5269
1263
0
5700
3893
0
0
5731
3764
1387
11644 10324
9438 13709 11502
8121
5153
1373
10424
9696
9103 12884 10335
7708
4601
1610
11857
9890
8137 14973 11742
8124
4920
1850
2000
7043
5641
0 10502
7032
5393
1802
11698
9522
6867 14062 11729
7941
3367
1502
9676
6837
5000
0
9765
6621
4169
1412
11043
8039
6023
0 11022
7607
4356
1528
10778
7610
4990
0 10625
7191
4031
1362
10737
9126
8261 12745 10611
7546
4561
1515
10789
8168
5262
0 10775
7560
4329
1319
13323 10486
11467
9875
11774 10010
8695
7905
8126
5042
4731
4783
1567
1525
1529
14787
14859
11360
11881
15500
15218
13868
12841
12088
0
15034
13754
14408
13534
14799
14173
13740
13624
14951
11809
14681
14188
15891
10018
14405
12622
11228
10871
11660
8587
14737
9742
9866
8854
9974
11588
11551
10041
9954
8639
0
10132
9888
10046
9998
10422
9668
9382
9276
9849
7820
10366
9922
10152
7129
10112
9346
7399
7538
6444
7363
9654
5487
6197
5872
6243
7653
6739
5514
4650
5086
0
7231
5679
5975
5974
5702
5337
5699
5766
6074
4397
5604
5489
4905
4860
5867
5403
5162
5335
4039
4651
5802
1663
2229
2053
2181
2300
2182
1978
1590
1645
0
2391
1915
2106
1819
1999
1810
1864
1721
2053
1398
1646
2088
1590
1614
2179
1789
1636
1708
1533
1578
1917
14480 12513 10275 17997 13466
9209
5154
1731
14868
0
11221
12127
15713
15568
14527
13023
12500
0
15871
14070
14446
14836
15142
14678
13949
14484
16668
12689
15819
15018
18215
10753
14755
14194
11423
11800
12868
8528
0
11456
10000
9811
10844
14292
14116
12524
11915
11612
0
13915
12096
12789
13692
13690
13012
11084
12223
14260
9379
13934
13250
16547
8942
12885
11990
8803
8991
9109
7668
3000
9166 16264 12498
8265 14073 11196
8449 14765 11386
9803
9125
8541
9160
13615
13055
10519
7465
10090
0
13780
11126
12733
13302
13268
12383
9800
11573
13801
7373
13341
12763
15564
6342
11197
9383
5550
6659
7488
5294
4000
14313
0
10203
13579
17753
18190
15807
13594
13652
0
18142
15711
14675
18258
18142
18085
20342
18147
20406
15938
18953
19129
22338
14750
17960
17979
15353
16235
16636
9336
0
APPENDIX II
Table A15 SUITABLE AREAS FOR CONSERVATION FORESTRY - ALL AREAS
ADM REG NAME
2
11
12
13
14
15
16
17
18
19
20
21
22
23
4 Mongolia
12
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
156198
200
2622
8843
18
182
2422
6221
6549 140806
2690
7868
20348
3938
6523
268445
19548
6313
6420
3000
9013
45390
57570
169
217
15798
1929
738
3853
171
2826
3505
1566
0
0
29877
472
704
18694
2393
1485
9596
1010
5508
5653
2398
86
0
41613
688
1495
19061
2742
2067
22058
2191
5708
5853
2596
762
31
45761
0
14
5742
440
374
559
30
773
1572
414
0
0
11343
169
203
10056
1489
364
3294
141
2053
1933
1152
0
0
18534
303
487
2896
464
747
5743
839
2682
2148
832
86
0
11736
216
791
367
349
582
12462
1181
200
200
198
676
31
4148
155
1646
13
120
593
4951
710
85
31
224
512
127
6864
1847
4159
1273
1075
3863
241435
16645
519
536
180
7738
45231
4942
457066
60649
89612
111013
21261
39388
28963
21401
16031
329443
Krasnodar Kray
12
7620
Stavropol Kray
12
6635
Arkhangelsk oblast
12
38190
Astrakhan oblast
12
4598
Belgorod oblast
12
2665
Bryansk oblast
12
3483
Vladimir oblast
12
2925
Volgograd oblast
12
11265
Vologda oblast
12
14628
Voronezh oblast
12
5195
Nizhni Novgorod oblast12
7515
Nenets a.okr.
12
16858
Ivanovo oblast
12
2270
Kaliningrad oblast
12
1240
Tver oblast
12
8395
Kaluga oblast
12
2963
Kirov oblast
12
11930
Kostroma oblast
12
6000
Samara oblast
12
5118
Kursk oblast
12
3020
Komi-Permyak a.okr. 12
3280
Leningrad oblast
12
7500
Lipetsk oblast
12
2410
Moscow oblast
12
4665
Murmansk oblast
12
13960
Novgorod oblast
12
5450
Orenburg oblast
12
12418
Oryel oblast
12
2458
Penza oblast
12
4320
Perm oblast
12
12715
Pskov oblast
12
5568
Rostov oblast
12
10133
Ryazan oblast
12
3935
Saratov oblast
12
10375
Smolensk oblast
12
4943
Tambov oblast
12
3435
Tula oblast
12
2553
Ulyanovsk oblast
12
3690
Yaroslavl oblast
12
3260
Adigei Republic
12
775
Bashkortostan Republic12
14435
Daghestn Republic
12
5033
Kabardino-Balkarian Republic
12
1238
Kalmyk-Khalm-Tangch 12
Republic7510
Karelia Republic
12
18253
Komi Republic
12
41370
Mari-El Republic
12
2365
Mordovian SSR
12
2590
North-Ossetian SSR 12
778
Karachai-Cherkess Republic
12
1468
Tatarstan Republic
12
6663
Udmurt Republic
12
4150
Checheno-Ingush Republic
12
1930
Chuvash Republic
12
1808
Altai Kray
12
16653
1362
480
7692
0
977
3315
1555
0
9938
676
4852
0
1862
765
7253
2525
7552
4324
539
2683
2061
3043
1989
4005
13
4098
310
2418
2749
8602
3419
361
3261
177
4368
2084
2534
495
2990
386
6688
196
424
0
2147
4784
1136
1891
317
388
2707
3375
441
644
6373
2408
1475
19696
0
1565
3429
2866
0
12127
1341
7356
15
2251
954
7933
2935
11211
5759
860
2691
3046
6125
2257
4445
89
5076
655
2454
3725
10284
4791
847
3886
529
4734
2788
2552
1593
3090
482
9372
411
628
0
9008
16384
1909
2469
383
524
4226
3890
671
1079
9812
4667
3330
24917
0
1715
3431
2908
583
12928
2157
7430
309
2260
1036
8173
2940
11601
5851
2164
2740
3157
6598
2354
4571
486
5228
1323
2454
4024
10613
4886
4499
3936
1720
4769
2963
2552
2445
3198
530
10807
1112
676
172
11853
25093
2191
2528
464
588
5195
3897
1164
1349
11393
379
105
1909
0
269
1336
288
0
3618
264
1596
0
779
366
3247
832
3172
1621
0
1331
1310
1321
1562
1703
0
1491
21
1435
1591
5326
1338
81
1704
0
2129
1304
1748
104
1440
154
2926
73
162
0
613
2135
260
1373
241
159
1287
1392
185
183
3428
983
375
5783
0
708
1979
1267
0
6320
412
3256
0
1083
399
4006
1693
4380
2703
539
1352
751
1722
427
2302
13
2607
289
983
1158
3276
2081
280
1557
177
2239
780
786
391
1550
232
3762
123
262
0
1534
2649
876
518
76
229
1420
1983
256
461
2945
1046
995
12004
0
588
114
1311
0
2189
665
2504
15
389
189
680
410
3659
1435
321
8
985
3082
268
440
76
978
345
36
976
1682
1372
486
625
352
366
704
18
1098
100
96
2684
215
204
0
6861
11600
773
578
66
136
1519
515
230
435
3439
2259
1855
5221
0
150
2
42
583
801
816
74
294
9
82
240
5
390
92
1304
49
111
473
97
126
397
152
668
0
299
329
95
3652
50
1191
35
175
0
852
108
48
1435
701
48
172
2845
8709
282
59
81
64
969
7
493
270
1581
1770
647
1742
0
481
0
0
945
248
2751
6
177
0
0
53
0
66
13
736
12
0
373
52
1
942
115
332
0
230
85
43
1719
0
1679
0
438
0
542
21
13
1087
558
41
61
1816
5070
36
42
31
72
553
13
120
415
492
1176
2658
11511
4597
470
51
17
9737
1452
288
79
16352
10
204
170
22
262
137
2216
267
123
528
4
94
12532
107
10763
3
66
2016
638
3915
0
6977
174
34
0
704
40
232
2540
3356
519
7277
4575
11207
138
20
283
807
915
240
647
44
4768
FSU REPUBLICS
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
LC
APPENDIX II
Table A15 SUITABLE AREAS FOR CONSERVATION FORESTRY - ALL AREAS
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
11
11
11
11
11
11
12
12
12
13
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
9385
805
2050
2229
108
697
1245
179
236
6920
71140
17169
29443
35569
4760
12409
12274
6126
6085
29485
16338
1118
3038
5214
334
784
1920
2176
2277
8847
82285
0
0
0
0
0
0
0
0
82285
77545
4712
8733
16880
898
3814
4021
8147
7809
52849
36283
9068
13302
20282
2440
6628
4234
6980
4631
11370
75673
5
372
888
0
5
367
516
3533
71251
3700
1189
1842
2211
607
582
653
369
436
1052
76270
7218
14469
22248
1324
5894
7251
7779
12324
41698
2178
234
660
867
40
194
426
207
55
1254
17045
100
1122
2880
0
100
1022
1758
676
13467
28903
0
112
399
0
0
112
287
1105
27399
9500
4386
5429
6377
1043
3343
1043
948
639
2483
70770
0
0
0
0
0
0
0
0
70745
7110
1600
2907
3780
521
1079
1307
873
564
2767
45830
0
24
934
0
0
24
910
1154
43742
17673
5423
8632
10062
2708
2715
3209
1430
880
6730
13980
3302
5265
8964
518
2784
1963
3699
721
4295
8095
743
1680
2758
5
738
937
1078
327
4918
19273
11885
13969
14649
5498
6387
2084
680
212
4412
1970
2
85
754
0
2
83
669
308
907
31145
14606
21195
23760
3644
10962
6589
2565
228
7157
15860
7486
10408
11635
1972
5514
2922
1227
578
3647
53163
10264
18913
28719
1271
8993
8649
9806
2870
21573
66588
20
1389
5425
0
20
1369
4036
9761
51393
8763
2130
3321
4408
741
1389
1191
1087
1226
3129
41493
316
2685
12052
1
315
2369
9367
9019
20420
33533
393
3753
6916
17
376
3360
3163
7630
18987
17035
107
1519
2836
0
107
1412
1317
1547
12652
6120
1427
2358
3143
223
1204
931
785
194
2782
303275
519
3407
10022
0
519
2888
6615
17029 276207
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
389947
1284574
1674521
132851
112600
245451
201274
191894
393168
240535
278254
518789
57863
32101
89964
74988
80499
155487
68423
79294
147717
39261
86360
125621
1640
1125
18480
15783
14798
16295
13863
19145
44848
413
9290
9250
13783
16663
18168
21050
11995
16385
23425
2840
56143
17725
37325
115468
20900
40580
5038
163355
119045
72183
40
567
32
5492
4060
4302
8121
7924
10224
29796
268
5967
8052
10363
12081
14944
16592
8176
8946
14365
406
22192
15884
21569
12288
8512
5170
151
688
4931
428
0
1007
236
9646
6841
6028
10241
10430
13564
36616
386
7879
9024
12888
13834
16366
18304
9844
10638
18651
1104
29588
16567
24627
21631
11152
7637
558
1616
5841
963
1
1250
349
12346
9082
7478
11638
11834
15507
39425
386
8100
9130
13168
14250
16377
18457
10204
11148
19531
1621
31081
16568
27781
33223
11750
9258
1388
3018
6944
2290
2
132
0
1505
1284
1367
2841
4073
4915
15520
134
2763
1412
3236
5343
4587
3249
319
2116
4051
57
5293
2298
8730
4364
1872
2006
45
216
1647
41
0
435
32
3987
2776
2935
5280
3851
5309
14276
134
3204
6640
7127
6738
10357
13343
7857
6830
10314
349
16899
13586
12839
7924
6640
3164
106
472
3284
387
0
440
204
4154
2781
1726
2120
2506
3340
6820
118
1912
972
2525
1753
1422
1712
1668
1692
4286
698
7396
683
3058
9343
2640
2467
407
928
910
535
1
243
113
2700
2241
1450
1397
1404
1943
2809
0
221
106
280
416
11
153
360
510
880
517
1493
1
3154
11592
598
1621
830
1402
1103
1327
1
1
241
2009
3488
1055
508
1070
729
1485
0
8
34
16
185
0
162
133
191
393
272
656
0
3940
4104
942
487
33
900
545
416
0
389
534
4125
3212
6266
4150
958
2909
3938
27
1059
85
600
2227
1792
2430
1658
5047
3502
947
24405
1157
5603
78141
8208
30835
3615
159437
111557
69476
37
937041
262491
333708
374584
85416
177075
71217
40876
24003
538326
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
LC
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
26147 123194
94546 911591
120693 1034785
APPENDIX II
Table A16 SUITABLE AREAS FOR CONSERVATION FORESTRY - EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
2
11
12
13
14
15
16
17
18
19
20
21
22
23
4 Mongolia
12
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
154858
200
2610
8774
18
182
2410
6164
6481 139602
1965
5588
7628
1508
4480
220903
16238
2220
3205
105
7423
42520
6305
138
199
5734
699
249
2468
84
981
1788
51
0
0
3667
353
608
6878
936
815
5543
747
1966
2915
80
62
0
4590
499
1110
7014
1069
1191
10982
1330
2056
2986
89
511
26
4907
0
13
1862
146
66
500
20
225
768
13
0
0
1343
138
186
3872
553
183
1968
64
756
1020
38
0
0
2324
215
409
1144
237
566
3075
663
985
1127
29
62
0
923
146
502
136
133
376
5439
583
90
71
9
449
26
317
110
998
11
68
387
2837
538
29
12
12
355
118
112
1356
3062
603
370
2902
207083
14370
135
208
3
6556
42376
1285
320088
16058
25493
33770
4956
11102
9435
8277
5587
280309
Krasnodar Kray
12
2158
Stavropol Kray
12
988
Arkhangelsk oblast
12
37453
Astrakhan oblast
12
4453
Belgorod oblast
12
80
Bryansk oblast
12
718
Vladimir oblast
12
1175
Volgograd oblast
12
2173
Vologda oblast
12
12483
Voronezh oblast
12
548
Nizhni Novgorod oblast12
4018
Nenets a.okr.
12
16818
Ivanovo oblast
12
1063
Kaliningrad oblast
12
160
Tver oblast
12
3450
Kaluga oblast
12
1240
Kirov oblast
12
7908
Kostroma oblast
12
4593
Samara oblast
12
445
Kursk oblast
12
90
Komi-Permyak a.okr. 12
2813
Leningrad oblast
12
6358
Lipetsk oblast
12
98
Moscow oblast
12
2270
Murmansk oblast
12
13535
Novgorod oblast
12
4568
Orenburg oblast
12
2623
Oryel oblast
12
63
Penza oblast
12
625
Perm oblast
12
8853
Pskov oblast
12
2750
Rostov oblast
12
475
Ryazan oblast
12
1253
Saratov oblast
12
1033
Smolensk oblast
12
748
Tambov oblast
12
328
Tula oblast
12
238
Ulyanovsk oblast
12
848
Yaroslavl oblast
12
1320
Adigei Republic
12
380
Bashkortostan Republic12
5880
Daghestn Republic
12
4543
Kabardino-Balkarian Republic
12
873
Kalmyk-Khalm-Tangch 12
Republic6185
Karelia Republic
12
14833
Komi Republic
12
41370
Mari-El Republic
12
1410
Mordovian SSR
12
673
North-Ossetian SSR 12
570
Karachai-Cherkess Republic
12
1255
Tatarstan Republic
12
678
Udmurt Republic
12
1678
Checheno-Ingush Republic
12
1383
Chuvash Republic
12
688
Altai Kray
12
9045
595
147
7292
0
31
680
602
0
8748
31
2130
0
864
91
3008
1051
4440
3269
102
80
1648
2695
45
1917
8
3515
7
61
310
5586
1735
0
844
12
679
190
234
114
1244
133
1450
187
248
0
1994
4784
695
434
167
243
271
1270
360
261
3500
854
255
19055
0
47
713
1141
0
10714
70
3886
15
1054
116
3271
1235
7469
4452
137
80
2617
5372
72
2164
84
4288
30
62
504
6803
2557
6
1219
26
721
299
238
404
1262
162
2600
374
286
0
8553
16384
1210
646
214
323
455
1576
526
494
5553
1055
293
24231
0
54
713
1166
23
11416
187
3946
308
1060
135
3369
1236
7673
4531
209
82
2718
5687
96
2232
452
4406
64
62
577
7057
2616
81
1252
55
726
317
238
631
1308
191
3637
987
316
0
11325
25093
1308
659
264
385
562
1580
715
565
6364
216
59
1858
0
13
271
101
0
3150
6
489
0
359
40
1311
375
1883
1224
0
35
1047
1221
33
835
0
1290
0
20
139
3610
659
0
263
0
332
100
105
32
615
49
416
70
101
0
571
2135
122
255
111
112
108
547
175
33
1593
379
88
5434
0
18
409
501
0
5598
25
1641
0
505
51
1697
676
2557
2045
102
45
601
1474
12
1082
8
2225
7
41
171
1976
1076
0
581
12
347
90
129
82
629
84
1034
117
147
0
1423
2649
573
179
56
131
163
723
185
228
1907
259
108
11763
0
16
33
539
0
1966
39
1756
15
190
25
263
184
3029
1183
35
0
969
2677
27
247
76
773
23
1
194
1217
822
6
375
14
42
109
4
290
18
29
1150
187
38
0
6559
11600
515
212
47
80
184
306
166
233
2053
201
38
5176
0
7
0
25
23
702
117
60
293
6
19
98
1
204
79
72
2
101
315
24
68
368
118
34
0
73
254
59
75
33
29
5
18
0
227
46
29
1037
613
30
0
2772
8709
98
13
50
62
107
4
189
71
811
241
14
1741
0
10
0
0
20
228
314
5
176
0
0
13
0
39
5
81
0
0
288
1
0
887
84
20
0
33
64
21
15
0
79
0
10
0
107
3
12
719
490
40
0
1784
5070
23
10
28
72
54
8
92
110
345
861
681
11460
4452
16
4
10
2130
838
47
67
16314
3
25
69
5
197
56
155
7
95
383
0
38
12196
78
2538
0
16
1731
113
379
0
899
21
1
0
109
10
176
1524
3057
517
6185
1716
11207
79
4
277
797
62
90
575
12
2337
FSU REPUBLICS
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
LC
APPENDIX II
Table A16 SUITABLE AREAS FOR CONSERVATION FORESTRY - EXCLUDING CULTIVATED AND URBAN AREAS
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
11
11
11
11
11
11
12
12
12
12
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
9330
802
2041
2213
107
695
1239
172
226
6891
67158
14756
26286
32302
3717
11039
11530
6016
6067
28788
15145
893
2358
4386
292
601
1465
2028
2260
8499
81188
0
0
0
0
0
0
0
0
81187
77168
4596
8521
16623
892
3704
3925
8102
7795
52742
34328
8205
12103
18838
2046
6159
3898
6735
4578
10911
75635
5
372
888
0
5
367
516
3533
71214
3590
1107
1748
2109
556
551
641
361
436
1045
71560
6661
13381
21073
1224
5437
6720
7692
12248
38239
1445
121
308
445
21
100
187
137
38
961
17018
100
1122
2877
0
100
1022
1755
676
13442
28898
0
112
398
0
0
112
286
1105
27394
7103
3736
4605
5237
814
2922
869
632
210
1654
70690
0
0
0
0
0
0
0
0
70665
3223
450
1161
1606
96
354
711
445
306
1311
45825
0
24
934
0
0
24
910
1154
43737
12435
3674
6208
7089
1432
2242
2534
881
324
5022
9258
3046
4731
5945
501
2545
1685
1214
256
3058
8045
735
1661
2734
5
730
926
1073
327
4892
16690
9819
11492
12164
4456
5363
1673
672
189
4337
1873
2
83
715
0
2
81
632
294
865
30583
14311
20800
23341
3538
10773
6489
2541
201
7040
12890
6737
8955
9856
1833
4904
2218
901
370
2664
53040
10224
18862
28659
1267
8957
8638
9797
2867
21515
66395
20
1389
5424
0
20
1369
4035
9759
51204
3685
698
1267
1769
248
450
569
502
447
1469
40300
293
2417
11612
1
292
2124
9195
8906
19782
32600
343
3589
6527
17
326
3246
2938
7503
18571
16665
106
1466
2663
0
106
1360
1197
1489
12513
5180
871
1652
2376
102
769
781
724
189
2616
302708
519
3406
9997
0
519
2887
6591
17004 275689
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
235212
1230696
1465908
66502
96330
162832
117095
167673
284768
139849
247164
387013
26496
24758
51254
40006
71572
111578
50593
71343
121936
22754
79491
102245
13011
91102
104113
82282
892254
974536
878
95
8108
7653
2360
7650
5388
10343
29720
0
830
5480
6878
12195
13748
16935
9233
10590
18013
2165
37043
11843
32713
104640
14298
33838
3550
156700
116778
70143
33
411
1
4515
2768
692
4257
3833
5407
20083
0
508
5180
5453
9169
11470
13397
6697
6893
11826
332
11199
10698
18462
11638
6594
3759
79
651
4794
304
0
660
14
6520
4091
815
5062
4538
7770
25229
0
616
5442
6457
10322
12426
14599
7845
7800
14679
843
12848
11156
21174
19723
8167
5423
267
1563
5626
692
1
755
19
7269
4718
1033
5519
4886
8637
26946
0
653
5457
6637
10462
12434
14696
8054
8068
15332
1268
13543
11157
24021
29102
8479
6515
937
2939
6681
1800
2
127
0
1348
921
214
1598
2057
2963
10472
0
208
693
1542
3732
3268
2074
253
1576
3401
52
3424
1575
7470
4289
1450
1574
40
184
1606
29
0
284
1
3167
1847
478
2659
1776
2444
9611
0
300
4487
3911
5437
8202
11323
6444
5317
8425
280
7775
9123
10992
7349
5144
2185
39
467
3188
275
0
249
13
2005
1323
123
805
705
2363
5146
0
108
262
1004
1153
956
1202
1148
907
2853
511
1649
458
2712
8085
1573
1664
188
912
832
388
1
95
5
749
627
218
457
348
867
1717
0
37
15
180
140
8
97
209
268
653
425
695
1
2847
9379
312
1092
670
1376
1055
1108
1
0
2
98
1404
52
161
312
273
615
0
1
7
16
112
0
116
74
109
254
230
339
0
3545
3118
212
347
23
891
526
338
0
122
74
741
1530
1274
1970
189
1434
2159
0
176
15
224
1622
1314
2123
1105
2412
2427
666
23159
686
5146
72420
5607
26976
2590
152870
109571
68004
31
749841
181070
222368
248019
58140
122930
41298
25651
13175
488637
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
LC
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
APPENDIX II
Table A 17 SUITABLE AREAS FOR CONSERVATION FORESTRY - EXCLUDING CULTIVATED AREAS, URBAN
AREAS AND AREAS CURRENTLY UNDER FOREST
ADM REG NAME
2
11
12
13
14
15
16
17
18
19
20
21
22
23
4 Mongolia
12
1
1
1
1
1
1
1
1
1
1
1
1
1
12
12
12
12
12
12
12
12
12
12
12
12
12
Armenia
Azerbaijan
Byelorussia
Estonia
Georgia
Kazakhstan
Kirghiztan
Latvia
Lithuania
Moldavia
Tajikistan
Turkmenistan
Ukraine
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
147800
158
2239
8074
11
147
2081
5835
5259 134466
1788
4578
1680
370
1515
214330
12170
210
1463
10
2655
40375
640
101
95
1149
178
126
1891
82
127
786
2
0
0
378
303
379
1427
220
393
4565
566
195
1348
5
0
0
494
429
783
1490
261
511
9616
1009
198
1365
6
8
8
530
0
0
301
22
29
414
19
40
336
1
0
0
146
101
95
848
156
97
1477
63
87
450
1
0
0
232
202
284
278
42
267
2674
484
68
562
3
0
0
116
126
404
63
41
118
5051
443
3
17
1
8
8
36
91
844
9
25
180
2536
287
2
7
3
7
1
16
1268
2643
180
84
824
202178
10874
10
89
1
2640
40366
94
281784
4915
9895
16214
1308
3607
4980
6319
4008
261251
Krasnodar Kray
12
625
Stavropol Kray
12
965
Arkhangelsk oblast
12
11818
Astrakhan oblast
12
4380
Belgorod oblast
12
0
Bryansk oblast
12
0
Vladimir oblast
12
13
Volgograd oblast
12
1890
Vologda oblast
12
1253
Voronezh oblast
12
258
Nizhni Novgorod oblast12
298
Nenets a.okr.
12
15018
Ivanovo oblast
12
25
Kaliningrad oblast
12
30
Tver oblast
12
118
Kaluga oblast
12
65
Kirov oblast
12
235
Kostroma oblast
12
253
Samara oblast
12
5
Kursk oblast
12
0
Komi-Permyak a.okr. 12
170
Leningrad oblast
12
800
Lipetsk oblast
12
0
Moscow oblast
12
193
Murmansk oblast
12
6555
Novgorod oblast
12
233
Orenburg oblast
12
2480
Oryel oblast
12
0
Penza oblast
12
0
Perm oblast
12
325
Pskov oblast
12
265
Rostov oblast
12
453
Ryazan oblast
12
405
Saratov oblast
12
615
Smolensk oblast
12
0
Tambov oblast
12
0
Tula oblast
12
13
Ulyanovsk oblast
12
18
Yaroslavl oblast
12
83
Adigei Republic
12
103
Bashkortostan Republic12
808
Daghestn Republic
12
4188
Kabardino-Balkarian Republic
12
663
Kalmyk-Khalm-Tangch 12
Republic6183
Karelia Republic
12
3005
Komi Republic
12
8200
Mari-El Republic
12
100
Mordovian SSR
12
125
North-Ossetian SSR 12
378
Karachai-Cherkess Republic
12
623
Tatarstan Republic
12
8
Udmurt Republic
12
3
Checheno-Ingush Republic
12
960
Chuvash Republic
12
0
Altai Kray
12
4503
195
147
636
0
0
0
9
0
772
5
115
0
13
13
90
61
123
166
0
0
82
393
0
162
0
161
0
0
0
153
154
0
276
0
0
0
13
0
69
55
88
160
109
0
354
485
45
87
74
116
6
3
194
0
1706
224
251
2261
0
0
0
12
0
981
18
285
3
25
21
105
65
215
240
0
0
153
682
0
183
38
222
0
0
0
285
246
0
398
0
0
0
13
0
71
56
162
325
137
0
1949
2116
85
124
99
164
6
3
290
0
2590
354
278
3064
0
0
0
13
0
1088
58
293
95
25
28
109
65
232
247
1
0
165
730
0
192
166
225
2
0
0
306
255
66
405
10
0
0
13
5
72
60
219
890
162
0
2510
2915
91
124
123
192
6
3
432
0
3081
92
59
177
0
0
0
1
0
242
0
8
0
1
4
37
26
57
82
0
0
37
152
0
62
0
36
0
0
0
91
47
0
78
0
0
0
6
0
34
25
21
62
43
0
21
202
5
52
61
55
4
2
111
0
848
103
88
459
0
0
0
8
0
530
5
107
0
12
9
53
35
66
84
0
0
45
241
0
100
0
125
0
0
0
62
107
0
198
0
0
0
7
0
35
30
67
98
66
0
333
283
40
35
13
61
2
1
83
0
858
29
104
1625
0
0
0
3
0
209
13
170
3
12
8
15
4
92
74
0
0
71
289
0
21
38
61
0
0
0
132
92
0
122
0
0
0
0
0
2
1
74
165
28
0
1595
1631
40
37
25
48
0
0
96
0
884
130
27
803
0
0
0
1
0
107
40
8
92
0
7
4
0
17
7
1
0
12
48
0
9
128
3
2
0
0
21
9
66
7
10
0
0
0
5
1
4
57
565
25
0
561
799
6
0
24
28
0
0
142
0
491
97
14
268
0
0
0
0
0
72
156
0
39
0
0
2
0
0
1
2
0
0
57
0
0
146
7
7
0
0
2
2
14
0
3
0
0
0
6
0
0
136
414
37
0
178
590
0
0
25
20
0
0
74
0
143
174
672
8473
4380
0
0
0
1890
92
42
5
14864
0
1
7
0
4
4
2
0
5
14
0
1
6243
1
2471
0
0
17
8
372
0
601
0
0
0
6
10
43
452
2876
465
6182
310
4695
8
0
229
411
2
0
454
0
1279
FSU REPUBLICS
103
107
111
112
114
115
117
118
119
120
122
123
124
127
128
129
133
134
136
138
139
141
142
146
147
149
153
154
156
157
158
160
161
163
166
168
170
173
178
179
180
182
183
185
186
187
188
189
190
191
192
194
196
197
101
LC
APPENDIX II
Table A 17 SUITABLE AREAS FOR CONSERVATION FORESTRY - EXCLUDING CULTIVATED AREAS, URBAN
AREAS AND AREAS CURRENTLY UNDER FOREST
ADM REG NAME
102
104
105
106
108
110
116
121
125
126
130
131
132
135
137
144
150
152
164
165
167
169
171
172
174
175
176
181
193
195
198
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
LC
Gorno-Altai Republic 12
Krasnoyarsk Kray
12
Primorski Kray
12
Taymyr a.okr.
12
Khabarovsk Kray
12
Amur oblast
12
Evenk a.okr
12
Yevrey (Jewish) a.oblast
12
Irkutsk oblast
12
Ust-Orda Buryat a.okr. 12
Kamchatka oblast
12
Koryak a.okr.
12
Kemerovo oblast
12
Chukchi a.okr.
12
Kurgan oblast
12
Magadan oblast
12
Novosibirsk oblast
12
Omsk oblast
12
Sakhalin oblast
12
Sverdlovsk oblast
12
Aga-Buryat a.okr.
12
Tomsk oblast
12
Tyumen oblast
12
Khanty-Mansi a.okr. 12
Yamalo-Nenets a.okr. 12
Chelyabinsk oblast
12
Chita oblast
12
Buryat Republic
12
Tuva Republic
12
Khakass Republic
12
Sakha (Yakutia) Republic
12
RUSSIA WEST
RUSSIA EAST
RUSSIA TOTAL
211
212
213
214
237
241
221
222
223
231
232
233
234
236
242
243
235
244
245
246
251
252
253
215
261
262
264
265
254
263
272
11
11
11
11
11
11
12
12
12
12
13
13
13
14
14
14
15
15
15
15
16
16
16
17
17
17
17
17
18
18
19
Beijing
Tianjin
Hebei
Shanxi
Shandong
Henan
Liaoning
Jilin
Heilongjiang
Shanghai
Jiangsu
Zhejiang
Anhui
Jiangxi
Hubei
Hunan
Fujian
Guangdong
Guangxi
Hainan
Sichuan
Guizhou
Yunnan
Nei Mongol
Shaanxi
Gansu
Ningxia
Xinjiang
Xizang
Qinghai
Hongkong
CHINA TOTAL
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
Total
Suitable Areas (000ha) ------------------------------------------------------------------------------------------------Extent
VS+S VS...MS VS...mS
VS
S
MS
mS
vmS
NS
4118
73
505
531
14
59
432
26
77
3510
5383
1143
2033
2252
393
750
890
219
123
3008
1490
172
637
836
39
133
465
199
156
498
71523
0
0
0
0
0
0
0
0
71522
18580
1718
3326
4563
342
1376
1608
1237
1238
12780
6033
2153
2831
3777
722
1431
678
946
606
1650
9323
0
16
26
0
0
16
10
78
9219
1318
422
800
941
203
219
378
141
34
342
8388
240
718
1026
47
193
478
308
847
6514
350
7
57
115
0
7
50
58
29
207
9120
23
303
725
0
23
280
422
185
8188
25808
0
108
320
0
0
108
212
1018
24469
925
161
178
365
23
138
17
187
135
425
60873
0
0
0
0
0
0
0
0
60847
2543
306
743
1098
53
253
437
355
289
1156
31205
0
12
580
0
0
12
568
522
30104
8383
2004
3435
4116
890
1114
1431
681
269
3997
5148
1392
2144
2863
303
1089
752
719
250
2034
973
103
247
291
0
103
144
44
23
651
2898
2113
2330
2383
950
1163
217
53
3
511
1038
0
35
377
0
0
35
342
178
482
10153
4322
6465
7502
870
3452
2143
1037
44
2606
7145
3643
4625
5151
959
2684
982
526
287
1707
20210
4702
7701
11633
445
4257
2999
3932
1308
7269
41490
3
470
2159
0
3
467
1689
2728
36596
1518
131
247
412
71
60
116
165
409
696
11328
95
1275
2832
0
95
1180
1557
1718
6778
10333
95
1557
2162
1
94
1462
605
1298
6873
5498
30
655
929
0
30
625
274
306
4263
1360
590
781
892
71
519
191
111
19
449
107800
68
490
1386
0
68
422
896
3205 103191
75204
496758
571962
5584
27415
32999
12513
47314
59827
16289
65324
81613
1993
7244
9237
3591
20171
23762
6929
19899
26828
3776
18010
21786
2369
17525
19894
56486
413821
470307
673
78
6618
6105
515
1193
1468
2573
9320
0
275
500
1465
4710
5280
4623
540
2330
7725
848
24765
6493
11850
90058
9673
31640
3505
153305
106460
69645
10
306
0
3653
2109
134
605
660
409
5090
0
130
452
1376
3742
4486
3732
318
1551
5589
112
4528
5934
7041
4421
3452
2690
66
578
679
298
0
492
7
5338
3169
172
734
992
523
6140
0
161
494
1433
4086
4792
3962
364
1798
6737
299
5088
6160
7855
9652
4524
4038
246
1385
1001
664
0
559
9
5960
3662
187
770
1196
1262
7502
0
164
499
1433
4144
4792
3977
393
1848
6941
460
5387
6160
8793
16697
4828
5062
896
2632
1458
1741
0
91
0
1044
689
64
231
310
183
2793
0
62
40
290
1864
1037
548
10
288
1862
17
1413
861
2692
1223
708
1096
30
152
295
29
0
215
0
2609
1420
70
374
350
226
2297
0
68
412
1086
1878
3449
3184
308
1263
3727
95
3115
5073
4349
3198
2744
1594
36
426
384
269
0
186
7
1685
1060
38
129
332
114
1050
0
31
42
57
344
306
230
46
247
1148
187
560
226
814
5231
1072
1348
180
807
322
366
0
67
2
622
493
15
36
204
739
1362
0
3
5
0
58
0
15
29
50
204
161
299
0
938
7045
304
1024
650
1247
457
1077
0
0
2
74
1140
31
43
162
266
592
0
0
0
0
51
0
37
12
17
56
100
145
0
1228
2284
129
318
23
791
252
334
0
112
66
583
1304
298
381
109
1044
1226
0
110
0
32
515
488
609
134
465
727
287
19233
332
1830
71076
4717
26259
2585
149882
104751
67570
9
564243
64141
82306
99412
19922
44219
18165
17106
8087
456734
APPENDIX III
Soil Suitability Ratings
Table A18
Table A19
Soil unit suitability ratings for tree species
Soil phase suitability ratings for tree species
107
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
AC
ACf
ACg
ACh
ACp
ACu
AL
ALf
ALg
ALh
ALj
ALp
ALu
AN
ANg
ANh
ANi
ANm
ANu
ANz
AR
ARa
ARb
ARc
ARg
ARh
ARl
ARo
AT
ATa
ATc
ATf
ATu
CH
CHg
CHh
CHk
CHl
CHw
CL
CLh
CLl
CLp
CM
CMc
CMd
CMe
CMg
CMi
CMo
CMu
CMv
CMx
FL
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
IL
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Units
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Input Level
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
001
4 4 4 4 4 4
6 6 2 2 2 2 2 2
2 4
2 2 2 6 2 2 2 2 2 2
6 6 6 2
2 6 6 2 2 6
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
002
4 4 4 4 4 4
4 4 6 6 6 6 4 4
6 4
6 2 6 6 2 2 2 6 6 6
4 4 4 6
4 4 4 4 6 4
2 2
6 6 6 6 6
2 2 2 2 2 2
2 2 2
003
4 4 4 4 4 4
6 6 6 4 6 6 6 6
2 2
6 4 4 6 6 6 6 6 4 6
6 6 6 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
004
4 4 4 4 4 4
6 6 2 2 2 2 6 6
2 4
2 2 2 6 2 2 2 2 2 2
6 6 6 2
2 6 6 2 2 6
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
005
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 6 6 6 6 6
6 6 6
006
4 4 4 4 4 4
6 6 2 2 2 2 6 6
2 4
2 2 2 6 2 2 2 2 2 2
6 6 6 2
2 6 6 2 2 6
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
007
1 1 1 1 1 1
2 2 2 2 2 2 2 2
1 4
3 3 3 2 3 3 3 3 2 3
6 6 6 3
2 2 2 2 3 6
1 1
3 3 3 3 3
1 1 1 1 1 1
1 1 1
008
2 2 2 2 2 2
6 6 6 6 6 6 6 6
2 4
6 2 6 6 2 2 2 6 6 6
4 4 4 6
4 4 4 4 6 6
2 2
6 6 6 6 6
2 2 2 2 2 2
2 2 2
009
2 6 6 3 6 6
2 2 6 4 6 6 6 6
2 2
6 4 4 6 6 6 6 6 4 6
6 6 6 6
6 6 6 6 4 4
3 3
4 4 4 4 4
2 3 2 6 2 2
3 2 2
010
1 1 1 1 1 1
2 2 2 2 2 2 2 2
1 4
3 3 3 2 3 3 3 3 2 3
6 6 6 3
2 6 6 2 3 6
3 3
3 3 3 3 3
1 1 1 1 1 1
3 3 3
011
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 2
4 4 4 4 4 4 4 4 4 4
6 6 6 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 4 4
012
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
013
1 1 1 1 1 1
6 6 2 2 2 2 6 6
1 4
2 2 2 2 2 2 2 2 2 2
6 6 6 2
2 6 6 2 2 6
1 1
2 2 2 2 2
1 1 1 1 1 1
1 1 1
014
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
015
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
016
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
017
6 6 6 6 4 4
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
018
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 6
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
019
1 1 1 1 1 1
2 2 1 1 1 1 2 2
1 4
1 1 1 1 1 1 1 1 1 1
3 3 3 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
020
4 6 6 4 6 6
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
4 4 4
021
6 2 2 6 2 2
2 2 2 2 2 2 2 2
2 4
2 2 2 2 6 2 2 2 4 2
2 2 2 2
2 2 2 2 2 4
3 2
6 6 6 6 6
2 3 2 2 2 3
6 2 2
022
6 2 2 6 2 2
6 6 6 6 6 6 6 6
2 4
6 2 6 6 6 2 2 6 4 6
6 6 6 6
6 6 6 6 6 4
3 2
6 6 6 6 6
2 3 2 2 2 3
6 2 2
023
2 3 3 2 3 3
2 2 2 2 2 2 2 2
3 4
2 2 2 2 6 2 2 2 4 2
2 2 2 2
2 2 2 2 2 4
3 2
6 6 6 6 6
2 3 2 2 2 3
6 2 2
024
6 2 2 6 2 2
2 2 2 2 2 2 2 2
2 4
2 2 2 2 6 2 2 2 4 2
2 2 2 2
2 2 2 2 2 4
4 4
4 4 4 4 4
2 2 2 2 2 2
6 6 2
025
2 6 6 2 6 6
6 6 6 4 6 6 6 6
2 2
6 4 4 6 4 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
026
2 3 3 2 3 3
2 2 2 2 2 2 2 2
3 4
2 2 2 2 6 2 2 2 4 2
2 2 2 2
2 2 2 2 2 4
3 2
6 6 6 6 6
2 3 2 2 2 2
6 2 2
027
3 1 1 3 1 1
2 2 2 2 2 2 2 2
3 4
3 3 3 3 2 3 3 3 4 2
2 2 2 2
2 2 2 2 2 4
3 3
6 6 6 6 6
3 3 3 3 3 3
2 3 3
028
4 4 4 4 4 4
4 4 6 6 6 6 4 4
6 4
6 2 6 4 6 2 2 6 4 6
6 6 6 6
6 6 6 4 6 4
2 6
4 4 4 4 4
2 2 2 2 2 2
6 2 2
029
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 6
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
030
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 6
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
031
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 2
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
032
1 1 1 1 1 1
2 2 1 1 1 1 2 2
1 6
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
033
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 6
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
034
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 4
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
2 2
2 2 2 2 2
1 1 1 1 1 1
2 2 2
035
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
036
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 4
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
2 2
2 2 2 2 2
1 1 1 1 1 1
2 2 2
037
6 6 6 6 6 6
6 6 6 6 6 6 6 6
2 4
2 2 2 2 6 6 6 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
2 2 2 2 2 2
2 4 2
038
2 2 2 2 2 2
3 3 3 3 3 3 3 3
2 4
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
6 6
4 4 4 4 4
2 2 2 2 2 2
6 6 6
039
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 4
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
040
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 4
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
041
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 4
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
042
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 4
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
043
6 2 2 6 2 2
6 6 6 6 6 6 6 6
6 4
2 2 2 2 2 2 2 2 6 2
2 2 2 2
2 2 2 2 2 6
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
044
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
045
3 3 3 3 3 3
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 3 1
4 4
4 4 4 4 4
2 3 3 3 3 3
3 6 3
046
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 3 3 1 1 3
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
047
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
048
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
049
2 6 6 2 6 6
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
050
2 2 2 2 2 2
6 6 6 6 6 6 6 6
2 4
6 6 6 4 6 6 6 6 6 6
4 4 4 6
6 6 6 4 6 6
2 2
6 6 6 6 6
2 2 2 2 2 2
2 2 2
051
1 1 1 1 1 1
2 2 1 1 1 1 2 2
1 6
1 1 1 1 1 1 1 1 1 1
3 3 3 1
1 3 3 1 1 3
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
052
6 4 4 6 4 4
6 6 6 6 6 6 6 6
6 4
6 6 6 6 4 4 4 6 4 6
6 6 6 6
6 6 6 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
053
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
054
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 4 4 1 1 1 1 1 4 1
1 1 1 1
1 1 1 1 4 4
1 1
4 4 4 4 4
1 1 1 4 1 1
1 1 1
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
FLc
FLd
FLe
FLm
FLs
FLt
FLu
FR
FRg
FRh
FRp
FRr
FRu
FRx
GL
GLa
GLd
GLe
GLi
GLk
GLm
GLt
GLu
GR
GRg
GRh
GY
GYh
GYk
GYl
GYp
HS
HSf
HSi
HSl
HSs
HSt
KS
KSh
KSk
KSl
KSy
LP
LPd
LPe
LPi
LPk
LPm
LPq
LPu
LV
LVa
LVf
LVg
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
IL
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Units
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Input Level
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
055
3 3 3 3 3 3
1 1 1 1 1 1 1 1
1 1
1 4 4 1 1 1 1 1 4 1
1 1 1 1
1 1 1 1 4 4
4 4
4 4 4 4 4
3 3 3 4 3 3
1 6 1
056
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 4 4 3 3 3 3 1 4 1
1 1 1 1
1 1 1 1 4 4
1 1
4 4 4 4 4
1 1 1 4 1 1
1 1 1
057
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 4 4 1 1 1 1 1 4 1
1 1 1 1
1 1 1 1 4 4
1 1
4 4 4 4 4
1 1 1 4 1 1
1 1 1
058
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 4 4 1 1 1 1 1 4 1
1 1 1 1
1 1 1 1 4 4
1 1
4 4 4 4 4
1 1 1 4 1 1
1 1 1
059
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
6 6 6 4 6 6
4 4 4
060
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
061
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 1
1 4 4 3 1 1 1 1 4 1
3 3 3 1
1 1 1 1 4 4
1 1
4 4 4 4 4
3 3 3 4 3 3
1 1 1
062
4 4 4 4 4 4
6 6 2 2 2 2 6 6
6 6
6 2 6 4 2 2 2 6 6 6
6 6 6 6
6 4 4 6 6 4
4 4
4 6 4 4 4
6 6 6 6 6 6
2 6 2
063
4 4 4 4 4 4
6 6 6 6 6 6 4 4
6 6
4 4 4 4 6 6 6 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
6 4 4
064
4 4 4 4 4 4
6 6 2 2 2 2 6 6
6 6
6 2 6 4 2 2 2 6 6 6
6 6 6 6
6 4 4 6 6 4
4 4
4 6 4 4 4
6 6 6 6 6 6
2 6 2
065
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
066
4 4 4 4 4 4
6 6 2 2 2 2 6 6
6 6
6 2 6 4 2 2 2 6 6 6
6 6 6 6
6 4 4 6 6 4
4 4
4 6 4 4 4
6 6 6 6 6 6
2 6 2
067
4 4 4 4 4 4
6 6 2 2 2 2 6 6
6 6
6 2 6 4 2 2 2 6 6 6
6 6 6 6
6 4 4 6 6 4
4 4
4 6 4 4 4
6 6 6 6 6 6
2 6 2
068
4 4 4 4 4 4
6 6 6 6 6 6 6 6
6 6
6 6 6 4 4 6 6 6 6 6
6 6 6 6
6 4 4 6 6 4
4 4
4 6 4 4 4
6 6 6 6 6 6
6 6 6
069
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
070
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 4 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
071
3 6 6 3 6 6
6 6 6 4 6 6 6 6
3 3
6 4 4 4 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
072
3 6 6 3 6 6
6 6 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
073
2 6 6 2 6 6
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
6 4
4 4 4 4 4
6 4 4 4 4 4
4 4 4
074
2 6 6 2 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 4 4 4 6 4 6
2 2 2 6
6 6 6 6 4 4
4 4
4 4 4 4 4
6 2 6 4 6 6
6 4 6
075
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
076
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
077
3 6 6 3 6 6
6 6 6 4 6 6 6 6
3 3
6 4 4 4 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
078
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
2 2
1 1 1 1 1
1 1 1 1 1 1
1 1 1
079
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
6 6 6
080
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
2 2
1 1 1 1 1
1 1 1 1 1 1
1 1 1
081
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
082
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
083
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
084
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
085
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
086
2 4 4 2 4 4
4 4 4 4 4 4 4 4
2 6
6 6 6 6 6 6 6 6 4 4
2 2 2 4
4 4 4 4 4 4
4 4
4 4 4 4 4
2 2 2 2 2 2
4 4 4
087
2 4 4 2 4 4
4 4 4 4 4 4 4 4
2 6
6 6 6 4 6 6 6 6 4 4
2 2 2 4
4 4 4 4 4 4
4 4
4 4 4 4 4
2 2 2 2 2 2
4 4 4
088
6 4 4 6 4 4
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
6 4
4 4 4 4 4
6 4 4 4 4 4
4 4 4
089
2 4 4 2 4 4
4 4 4 4 4 4 4 4
2 2
6 6 6 6 6 6 6 6 4 4
2 2 2 4
4 4 4 4 4 4
6 6
6 6 6 6 6
2 2 2 2 2 2
6 6 6
090
4 4 4 4 4 4
4 4 4 4 4 4 4 4
2 2
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
091
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
092
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
093
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
094
2 2 2 2 2 2
3 3 2 2 2 2 3 3
1 4
3 3 3 1 2 2 2 3 2 3
3 3 3 3
3 3 3 2 2 2
4 4
4 4 4 4 4
2 3 3 3 3 3
1 4 1
095
2 2 2 2 2 2
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 2 3
1 1 1 3
3 3 3 2 2 2
6 6
6 6 6 6 6
3 3 3 3 3 3
6 6 6
096
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
097
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
6 6 6 6 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
098
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
099
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
6 6 6 6 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
100
4 4 4 6 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
101
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
6 6 6 6 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
4 4
4 4 4 4 4
4 6 6 6 6 6
4 4 6
102
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
103
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
104
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
105
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
106
3 1 1 3 1 1
3 3 3 3 3 3 3 3
3 4
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
3 3
3 3 3 3 3
3 3 3 3 3 3
3 3 3
107
4 4 4 4 4 4
6 6 6 6 6 6 6 6
6 4
6 2 6 4 2 2 2 6 6 6
6 6 6 6
6 6 6 4 6 4
2 2
6 6 6 6 6
2 2 2 2 2 2
2 2 2
108
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
LVh
LVj
LVk
LVv
LVx
LX
LXa
LXf
LXg
LXh
LXj
LXp
NT
NTh
NTr
NTu
PD
PDd
PDe
PDg
PDi
PDj
PH
PHc
PHg
PHh
PHj
PHl
PL
PLd
PLe
PLi
PLm
PLu
PT
PTa
PTd
PTe
PTu
PZ
PZb
PZc
PZf
PZg
PZh
PZi
RG
RGc
RGd
RGe
RGi
RGu
RGy
SC
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
IL
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Units
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Input Level
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
109
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
110
2 6 6 2 6 6
2 2 6 4 6 6 6 6
3 6
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
4 4 4
111
3 2 2 3 2 2
1 1 1 1 1 1 1 1
1 4
1 1 1 1 2 2 2 1 2 1
1 1 1 1
1 1 1 1 2 2
6 6
4 4 4 4 4
2 3 3 3 3 3
1 6 1
112
2 6 6 2 6 6
2 2 6 6 6 6 2 2
2 4
6 6 6 6 4 4 4 6 4 6
6 6 6 6
6 6 6 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
113
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
114
1 1 1 1 1 1
3 3 3 3 3 3 3 3
1 4
1 1 1 1 1 1 1 1 3 1
3 3 3 1
1 1 1 3 3 3
1 1
3 3 3 3 3
1 1 1 1 1 1
1 1 1
115
3 1 1 3 1 1
3 3 3 3 3 3 3 3
3 4
3 3 3 3 3 3 3 3 2 3
2 2 2 3
3 2 2 2 2 2
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
116
4 4 4 4 4 4
6 6 6 6 6 6 6 6
4 4
6 2 6 4 2 2 2 6 6 6
4 4 4 6
6 6 6 4 6 4
2 2
6 6 6 6 6
2 2 2 2 2 2
2 2 2
117
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 2
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
118
1 1 1 1 1 1
3 3 3 3 3 3 3 3
1 4
1 1 1 1 1 1 1 1 3 3
3 3 3 3
3 2 2 3 3 3
1 1
3 3 3 3 3
1 1 1 1 1 1
1 1 1
119
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 6
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 2 2
4 4 4
120
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
121
4 4 4 4 4 4
3 3 1 1 1 1 3 3
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
122
4 4 4 4 4 4
3 3 1 1 1 1 3 3
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
123
4 4 4 4 4 4
1 1 1 1 1 1 1 1
1 4
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
124
4 4 4 4 4 4
3 3 1 1 1 1 3 3
1 6
1 1 1 3 1 1 1 1 3 1
3 3 3 1
1 1 1 3 3 3
3 3
3 3 3 3 3
1 1 1 1 1 1
3 3 3
125
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
126
1 1 1 1 1 1
2 2 2 2 2 2 2 2
1 4
1 1 1 3 1 1 1 1 3 1
1 1 1 1
1 1 1 1 3 3
1 1
3 3 3 3 3
1 1 1 1 1 1
1 1 1
127
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
128
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
129
2 6 6 2 6 6
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
130
2 6 6 2 6 6
6 6 6 4 6 6 6 6
2 6
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
4 4 4
131
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
132
2 2 2 2 2 2
1 1 3 3 3 3 1 1
2 4
1 1 1 1 1 1 1 1 2 2
3 3 3 2
3 3 3 2 2 2
6 6
2 2 2 2 2
1 1 1 1 1 1
6 6 6
133
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
134
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 4
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
135
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 6
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
4 4 4
136
1 1 1 1 1 1
2 2 2 2 2 2 2 2
1 4
1 1 1 1 1 1 1 1 2 2
3 3 3 3
3 3 3 2 2 2
2 2
2 2 2 2 2
1 1 1 1 1 1
1 2 1
137
2 6 6 2 6 6
6 6 6 6 6 6 6 6
2 4
6 6 6 6 6 6 6 6 4 2
2 2 2 6
6 6 6 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
138
2 6 6 2 6 6
6 6 6 6 6 6 6 6
2 4
6 6 6 6 6 6 6 6 4 2
2 2 2 6
6 6 6 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
139
2 6 6 2 6 6
2 2 6 6 6 6 6 6
2 4
6 6 6 6 6 6 6 6 4 2
2 2 2 6
6 6 6 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
140
6 4 4 6 4 4
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
141
2 6 6 2 6 6
6 6 6 6 6 6 6 6
2 6
6 6 6 6 6 6 6 6 4 2
2 2 2 6
6 6 6 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
142
2 6 6 2 6 6
6 6 6 6 6 6 6 6
2 4
6 6 6 6 6 6 6 6 4 2
2 2 2 6
6 6 6 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
143
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
144
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
145
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
146
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
147
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
148
2 3 3 2 3 3
2 2 2 2 2 2 2 2
2 4
2 3 2 6 2 3 3 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
149
2 3 3 2 3 3
2 2 2 2 2 2 2 2
2 4
2 3 2 6 2 3 3 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
150
3 3 3 3 3 3
2 2 2 2 2 2 2 2
2 4
2 3 2 6 2 3 3 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
151
2 6 6 2 6 6
4 4 6 6 6 6 4 4
6 4
6 2 6 4 4 2 2 6 4 6
4 4 4 6
4 4 4 4 4 4
6 6
6 6 6 6 6
2 2 2 2 2 2
6 6 6
152
2 6 6 2 6 6
6 6 4 4 4 4 4 4
2 2
6 4 4 4 4 6 6 6 4 6
6 6 6 6
4 6 6 6 4 4
4 4
4 4 4 4 4
6 2 6 4 6 6
6 4 4
153
2 3 3 2 3 3
2 2 2 2 2 2 2 2
2 4
2 3 2 6 2 3 3 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
154
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
155
1 1 1 1 1 1
3 3 3 3 3 3 3 3
1 4
1 1 1 1 3 1 1 1 2 1
1 1 1 1
1 1 1 1 1 2
1 3
1 1 1 1 1
3 1 3 3 3 1
3 1 1
156
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 4
1 1 1 1 3 1 1 1 2 1
1 1 1 1
1 1 1 1 2 2
4 4
4 4 4 4 4
2 3 2 2 2 3
3 4 1
157
1 1 1 1 1 1
2 2 2 2 2 2 2 2
1 4
1 1 1 3 3 1 1 1 2 1
1 1 1 1
1 3 3 1 1 2
1 3
1 1 1 1 1
3 1 3 3 3 1
3 1 1
158
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 4
1 1 1 1 3 1 1 1 2 1
1 1 1 1
1 1 1 1 1 2
1 3
1 1 1 1 1
3 1 3 3 3 1
3 1 1
159
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
160
1 1 1 1 1 1
2 2 3 3 3 3 2 2
1 4
1 1 1 3 3 1 1 1 2 1
3 3 3 1
3 3 3 3 2 2
1 3
2 2 2 2 2
3 1 3 3 3 1
3 1 1
161
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
162
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
SCg
SCh
SCl
SCk
SCm
SCn
SCy
SN
SNg
SNh
SNj
SNk
SNm
SNy
VR
VRd
VRe
VRk
VRy
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
163
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
164
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
165
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
166
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
167
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
168
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
169
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
170
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
171
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
172
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
173
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
174
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
175
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
176
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
177
6 6 6 6 6 6
2 2 6 6 6 6 2 2
2 4
6 6 6 6 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
178
6 6 6 6 6 6
6 6 6 6 6 6 6 6
6 4
6 6 6 4 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
179
6 6 6 6 6 6
2 2 6 6 6 6 2 2
2 4
6 6 6 6 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
180
4 4 4 4 4 4
2 2 6 6 6 6 2 2
2 4
6 6 6 6 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
4 6 6 6 6 6
6 4 4
181
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
AC
ACf
ACg
ACh
ACp
ACu
AL
ALf
ALg
ALh
ALj
ALp
ALu
AN
ANg
ANh
ANi
ANm
ANu
ANz
AR
ARa
ARb
ARc
ARg
ARh
ARl
ARo
AT
ATa
ATc
ATf
ATu
001
002
003
004
005
006
007
008
009
010
011
012
013
014
015
016
017
018
019
020
021
022
023
024
025
026
027
028
029
030
031
032
033
4
4
4
4
4
4
2
6
2
2
2
4
2
1
3
1
6
1
3
4
2
6
2
6
2
2
2
4
1
1
1
1
1
4
4
4
4
4
4
2
6
6
2
6
4
2
1
6
1
6
1
3
4
2
2
2
2
6
2
2
4
1
1
1
1
1
4
4
4
4
4
4
2
6
6
2
6
4
2
1
6
1
6
1
3
4
2
2
2
2
6
2
2
4
1
1
1
1
1
4
4
4
4
4
4
2
6
2
2
2
4
2
1
3
1
6
1
3
4
2
6
2
6
2
2
2
4
1
1
1
1
1
4
4
4
4
4
4
2
6
6
2
6
4
2
1
6
1
6
1
3
4
2
2
2
2
6
2
2
4
1
1
1
1
1
4
4
4
4
4
4
2
6
6
2
6
4
2
1
6
1
6
1
3
4
2
2
2
2
6
2
2
4
1
1
1
1
1
6
4
6
6
4
6
2
6
2
2
2
4
6
1
2
1
4
1
2
4
6
6
6
6
6
6
6
4
1
1
1
2
2
6
4
6
6
4
6
2
6
2
2
2
4
6
1
2
1
4
1
2
4
6
6
6
6
6
6
6
4
1
1
1
2
2
2
6
4
2
4
2
2
6
6
2
6
4
2
1
6
1
4
1
3
4
6
6
6
6
4
6
6
6
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
4
1
3
4
6
6
6
6
4
6
6
6
1
1
1
1
1
2
6
4
2
4
2
2
6
6
2
6
4
2
1
6
1
4
1
3
4
6
6
6
6
4
6
6
6
1
1
1
1
1
2
6
4
2
4
2
2
6
6
2
6
4
2
1
6
1
4
1
3
4
6
6
6
6
4
6
6
6
1
1
1
1
1
6
4
4
6
4
6
2
6
6
2
6
4
6
1
2
1
4
1
2
4
6
6
6
6
4
6
6
4
1
1
1
2
2
6
4
4
6
4
6
2
6
6
2
6
4
6
1
2
1
4
1
2
4
6
6
6
6
4
6
6
4
1
1
1
2
2
6
6
6
6
4
6
3
2
2
3
2
4
3
1
3
1
6
1
1
4
2
6
3
2
2
3
3
6
1
1
1
1
1
6
6
6
6
4
6
3
2
2
3
2
4
3
1
3
1
6
1
1
4
2
6
3
2
2
3
3
6
1
1
1
1
1
6
6
4
6
4
6
2
6
4
2
4
4
2
1
4
1
4
1
1
4
2
6
2
2
4
2
3
4
1
1
1
1
1
2
6
4
2
4
2
3
6
4
3
4
4
3
1
4
1
4
1
1
4
2
6
3
3
4
2
3
6
1
1
1
1
1
6
6
6
6
4
6
2
6
6
2
4
4
2
1
6
1
4
1
1
4
2
6
2
2
6
2
3
4
1
1
1
1
1
4
4
4
4
4
4
2
6
6
2
4
4
6
1
6
1
4
1
1
4
2
6
2
2
6
2
3
4
1
1
1
3
1
2
6
6
2
4
2
3
6
6
3
4
4
3
1
6
1
4
1
1
4
6
4
2
2
4
6
2
4
1
1
1
1
1
2
6
6
2
4
2
3
6
6
3
4
4
3
1
6
1
4
1
1
4
2
6
3
3
6
2
3
6
1
1
1
1
1
2
6
6
2
4
2
3
6
6
3
4
4
3
1
6
1
4
1
1
4
2
6
3
3
6
2
3
6
1
1
1
1
1
6
6
6
6
4
6
2
6
6
2
4
4
2
1
6
1
4
1
1
4
2
6
2
2
6
2
3
4
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
4
1
3
4
4
4
4
4
4
4
4
4
1
1
1
1
1
2
6
6
2
4
2
2
6
6
2
4
4
2
1
6
1
4
1
3
4
2
6
2
2
6
2
2
6
1
1
1
1
1
6
4
6
6
4
6
6
4
6
6
6
4
6
1
3
1
4
3
2
4
2
6
2
2
2
2
2
6
1
1
1
1
1
6
4
6
6
4
6
6
4
6
6
6
4
6
1
3
1
4
3
2
4
2
6
2
2
2
2
2
6
1
1
1
1
1
6
4
6
6
4
6
6
4
6
6
6
4
6
1
3
1
4
3
2
4
2
6
2
2
2
2
2
6
1
1
1
1
1
2
6
6
2
4
2
2
6
6
2
4
4
2
1
6
1
4
1
3
4
2
6
2
2
6
2
2
6
1
1
1
1
1
2
4
6
2
4
2
2
4
6
2
4
4
2
1
6
1
4
1
3
4
2
6
2
2
6
2
2
6
1
1
1
1
1
6
4
6
6
4
6
6
4
6
6
4
4
6
1
6
1
4
1
3
4
2
6
2
2
6
2
2
6
1
1
1
1
1
6
4
6
6
4
6
6
4
6
6
4
4
6
1
6
1
4
1
3
4
2
6
2
2
6
2
2
6
1
1
1
1
1
2
4
6
2
4
2
2
4
6
2
4
4
2
1
6
1
4
1
3
4
2
6
2
2
6
2
2
4
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
4
1
3
4
2
6
2
2
4
2
2
6
1
1
1
1
1
6
6
4
6
4
6
6
6
4
6
4
4
6
1
4
1
4
1
3
4
4
4
4
4
4
4
4
4
1
1
1
1
1
2
6
6
2
6
2
2
6
6
2
6
4
3
1
6
1
2
1
3
4
3
3
3
4
6
3
3
2
1
1
1
1
1
2
6
6
2
6
2
2
6
6
2
6
4
3
1
6
1
6
1
3
4
2
2
2
4
6
2
2
6
1
1
1
1
1
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
IL
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
FAO '90 Soil Units
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Input Level
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
4
1
3
4
6
6
6
4
4
6
6
4
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
4
1
3
4
6
6
6
4
4
6
6
4
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
6
1
3
4
6
6
6
4
4
6
6
4
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
6
1
3
4
6
6
6
4
4
6
6
4
1
1
1
1
1
2
6
4
2
4
2
2
6
4
2
4
4
2
1
4
1
4
1
3
4
6
6
6
4
4
6
6
4
1
1
1
1
1
2
6
2
2
6
2
3
6
6
3
6
4
3
1
2
1
6
1
3
4
2
2
2
6
6
2
3
2
1
1
1
1
1
2
6
3
2
6
2
3
6
2
3
2
4
3
1
3
1
4
1
3
4
3
3
3
2
2
3
3
2
1
1
1
1
1
2
6
2
2
6
2
3
6
6
3
6
4
3
1
2
1
4
1
3
4
2
2
2
2
6
2
3
2
1
1
1
1
1
2
6
6
2
6
2
3
6
4
3
4
4
3
1
6
1
4
1
3
4
2
2
2
2
4
2
3
2
1
1
1
1
1
2
6
2
2
6
2
3
6
6
3
6
4
3
1
2
1
4
1
3
4
2
2
2
2
6
2
3
2
1
1
1
1
1
2
6
2
2
6
2
3
6
6
3
6
4
3
1
2
1
4
1
3
4
3
3
3
2
6
3
3
2
1
1
1
1
1
2
6
2
2
6
2
2
6
2
2
4
4
3
1
2
1
4
1
3
4
6
6
6
6
6
6
6
6
1
1
1
1
1
2
6
6
2
6
2
2
6
6
2
4
4
3
1
6
1
4
1
3
4
2
2
2
6
6
2
2
6
1
1
1
1
1
2
6
6
2
6
2
2
6
6
2
4
4
3
1
6
1
4
1
3
4
2
2
2
2
6
2
2
6
1
1
1
1
1
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
CH
CHg
CHh
CHk
CHl
CHw
CL
CLh
CLl
CLp
CM
CMc
CMd
CMe
CMg
CMi
CMo
CMu
CMv
CMx
FL
FLc
FLd
FLe
FLm
FLs
FLt
FLu
FR
FRg
FRh
FRp
FRr
FRu
FRx
GL
GLa
GLd
GLe
GLi
GLk
GLm
GLt
GLu
GR
GRg
GRh
GY
GYh
GYk
GYl
GYp
HS
HSf
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
IL
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Units
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Input Level
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
034
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 3
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
2 2
2 2 2 2 2
1 1 1 1 1 1
2 2 2
035
3 6 6 3 6 6
2 2 6 4 6 6 6 6
2 2
4 4 6 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
2 6 6
036
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 3
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
2 2
2 2 2 2 2
1 1 1 1 1 1
2 2 2
037
6 6 6 6 6 6
6 6 6 6 6 6 6 6
2 2
6 6 6 6 6 6 6 6 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
2 2 2 2 2 2
2 4 2
038
2 2 2 2 2 2
3 3 3 3 3 3 3 3
2 2
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
6 6
4 4 4 4 4
2 2 2 2 2 2
6 6 6
039
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 3
3 3 3 3 3 3 3 3 3 3
3 3 3 3
3 3 3 3 3 3
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
040
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 2
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
041
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 2
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
042
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 2
2 2 2 2 2 2 2 2 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
043
2 2 2 2 2 2
6 6 6 6 6 6 6 6
6 6
2 2 2 2 2 2 2 2 6 2
2 2 2 2
2 2 2 2 2 6
4 4
4 4 4 4 4
6 2 2 2 2 2
2 4 2
044
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
045
3 3 3 3 3 3
3 3 3 3 3 3 3 3
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 3 1
4 4
4 4 4 4 4
2 3 3 3 3 3
1 6 1
046
3 3 3 3 3 3
2 2 2 2 2 2 2 2
3 3
3 3 3 2 3 3 3 3 3 3
3 3 3 3
3 2 2 3 3 2
3 3
3 3 3 3 3
3 3 3 3 3 3
3 3 3
047
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
048
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
049
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
050
2 2 2 2 2 2
6 6 6 6 6 6 6 6
2 2
6 6 6 4 6 6 6 6 6 6
4 4 4 6
6 6 6 4 6 6
6 6
6 6 6 6 6
2 2 2 2 2 2
6 6 6
051
3 3 3 3 3 3
2 2 2 2 2 2 2 2
3 3
3 3 3 3 3 3 3 3 3 3
2 2 2 3
3 2 2 3 3 2
3 3
3 3 3 3 3
3 3 3 3 3 3
3 3 3
052
6 4 4 6 4 4
2 2 6 6 6 6 2 2
6 6
6 6 6 6 4 4 4 6 4 6
6 6 6 6
6 6 6 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
053
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 1
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 3
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
054
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 4 4 1 1 1 1 1 4 1
1 1 1 1
1 1 1 1 4 4
1 1
4 4 4 4 4
1 1 1 4 1 1
1 1 1
055
3 3 3 3 3 3
3 3 3 3 3 3 3 3
1 1
1 4 4 1 3 3 3 1 4 1
1 1 1 1
1 1 1 1 4 4
4 4
4 4 4 4 4
3 1 1 4 1 1
1 6 1
056
2 2 2 2 2 2
2 2 2 2 2 2 2 2
3 3
1 4 4 3 3 3 3 1 4 3
3 3 3 3
3 3 3 3 4 4
3 3
4 4 4 4 4
3 3 3 4 3 3
3 3 3
057
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 4 4 1 1 1 1 1 4 1
1 1 1 1
1 1 1 1 4 4
1 1
4 4 4 4 4
1 1 1 4 1 1
1 1 1
058
3 3 3 3 3 3
3 3 3 3 3 3 3 3
1 1
1 4 4 1 1 1 1 1 4 3
3 3 3 3
3 3 3 3 4 4
3 3
4 4 4 4 4
3 3 3 4 3 3
3 3 3
059
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
6 6 6 4 6 6
4 4 4
060
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
061
3 3 3 3 3 3
2 2 2 2 2 2 2 2
3 3
3 4 4 3 3 3 3 3 4 3
2 2 2 3
3 3 3 3 4 4
3 3
4 4 4 4 4
3 3 3 4 3 3
3 3 3
062
4 4 4 4 4 4
6 6 2 2 2 2 6 6
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 2 4
2 4 2
063
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 6 4
6 4 4
064
4 4 4 4 4 4
6 6 2 2 2 2 6 6
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 2 4
2 4 2
065
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
066
4 4 4 4 4 4
6 6 2 2 2 2 6 6
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 2 4
2 4 2
067
4 4 4 4 4 4
6 6 2 2 2 2 6 6
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 2 4
2 4 2
068
4 4 4 4 4 4
6 6 6 6 6 6 6 6
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 6 4
6 4 6
069
2 4 4 2 4 4
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
070
2 4 4 2 4 4
2 2 6 4 6 6 6 6
3 3
6 4 4 4 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
071
6 4 4 6 4 4
6 6 6 4 6 6 6 6
2 2
6 4 4 4 6 6 6 6 4 6
6 6 6 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
072
2 4 4 2 4 4
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
073
6 4 4 6 4 4
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
6 4
4 4 4 4 4
6 4 4 4 4 4
4 4 4
074
2 4 4 2 4 4
2 2 6 4 6 6 6 6
3 3
6 4 4 6 4 4 4 6 4 6
2 2 2 6
6 6 6 6 4 4
4 4
4 4 4 4 4
4 6 6 4 6 6
6 4 6
075
2 4 4 2 4 4
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
076
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
077
2 4 4 2 4 4
6 6 6 4 6 6 6 6
2 2
6 4 4 4 4 4 4 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
6 6 6
078
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
079
2 6 6 2 6 6
6 6 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
2 6 6
080
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
081
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
082
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
083
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
084
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
085
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
086
2 4 4 2 4 4
4 4 4 4 4 4 4 4
2 2
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
4 4
4 4 4 4 4
2 2 2 2 2 2
4 4 4
087
2 4 4 2 4 4
4 4 4 4 4 4 4 4
2 2
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
4 4
4 4 4 4 4
2 2 2 2 2 2
4 4 4
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
HSi
HSl
HSs
HSt
KS
KSh
KSk
KSl
KSy
LP
LPd
LPe
LPi
LPk
LPm
LPq
LPu
LV
LVa
LVf
LVg
LVh
LVj
LVk
LVv
LVx
LX
LXa
LXf
LXg
LXh
LXj
LXp
NT
NTh
NTr
NTu
PD
PDd
PDe
PDg
PDi
PDj
PH
PHc
PHg
PHh
PHj
PHl
PL
PLd
PLe
PLi
PLm
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
IL
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Units
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Input Level
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
088
6 4 4 6 4 4
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
6 4
4 4 6 6 4
6 4 4 4 4 4
4 4 4
089
3 4 4 3 4 4
4 4 4 4 4 4 4 4
2 2
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
6 6 6 6 6
3 3 3 3 3 3
6 6 6
090
4 4 4 4 4 4
4 4 4 4 4 4 4 4
2 2
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
091
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
092
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
093
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
094
2 2 2 2 2 2
2 2 2 2 2 2 2 2
1 1
3 3 3 1 6 6 6 3 2 2
3 3 3 2
2 2 2 2 2 2
4 4
4 4 4 4 4
2 3 3 3 3 3
1 4 1
095
2 2 2 2 2 2
2 2 2 2 2 2 2 2
1 1
1 1 1 1 1 1 1 1 2 2
3 3 3 2
2 2 2 2 2 2
6 6
4 4 4 4 4
3 3 3 3 3 3
6 6 6
096
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
097
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
098
6 4 4 6 4 4
4 4 4 4 4 4 4 4
4 4
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
099
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
6 6 6 6 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
100
4 4 4 4 4 4
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
101
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
6 6 6 6 4 4 4 6 4 6
6 6 6 6
4 4 4 4 4 4
4 4
4 4 4 4 4
4 6 6 6 6 6
4 4 6
102
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
103
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
104
6 6 6 6 6 6
4 4 4 4 4 4 4 4
4 4
6 6 6 4 6 6 6 6 4 6
6 6 6 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
4 4 6
105
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
106
3 3 3 3 3 3
2 2 2 2 2 2 2 2
3 3
3 3 3 2 3 3 3 3 3 3
3 3 3 3
3 3 3 3 2 3
2 2
2 2 2 2 2
3 3 3 3 3 3
2 2 2
107
4 4 4 4 4 4
6 6 6 6 6 6 6 6
6 6
6 2 6 4 2 2 2 6 6 6
4 4 4 6
6 6 6 4 6 6
6 6
6 6 6 6 6
2 2 2 2 2 2
6 6 6
108
3 6 6 3 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
109
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 1
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
110
2 6 6 2 6 6
2 2 6 4 6 6 6 6
3 3
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
4 4 4
111
2 2 2 2 2 2
3 3 3 3 3 3 3 3
1 1
1 1 1 1 1 1 1 1 2 1
1 1 1 1
1 1 1 1 2 2
6 6
4 4 4 4 4
6 2 2 2 2 2
1 6 1
112
6 6 6 6 6 6
6 6 6 6 6 6 6 6
2 2
6 6 6 6 4 4 4 6 4 6
6 6 6 6
6 6 6 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
113
1 1 1 1 1 1
3 3 1 1 1 1 3 3
1 1
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 3
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
114
3 3 3 3 3 3
2 2 3 3 3 3 2 2
3 3
3 3 3 3 3 3 3 3 2 3
2 2 2 3
3 3 3 2 2 2
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
115
2 2 2 2 2 2
2 2 2 2 2 2 2 2
2 2
3 3 3 3 3 3 3 3 2 2
2 2 2 2
2 2 2 2 2 2
3 3
2 2 2 2 2
2 2 2 2 2 2
3 3 3
116
4 4 4 4 4 4
4 4 6 6 6 6 4 4
4 4
6 2 6 4 2 2 2 6 6 6
4 4 4 6
6 4 4 4 6 6
6 6
6 6 6 6 6
6 6 6 6 6 6
6 6 6
117
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 2
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 4 4 6 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
2 6 6
118
3 3 3 3 3 3
3 3 3 3 3 3 3 3
3 3
3 3 3 3 3 3 3 3 2 3
2 2 2 3
3 2 2 3 2 2
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
119
2 6 6 2 6 6
2 2 6 44 6 6 6 6
2 2
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 6 6 6
4 4 4
120
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
121
4 4 4 4 4 4
3 3 1 1 1 1 3 3
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
122
4 4 4 4 4 4
3 3 1 1 1 1 3 3
3 3
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
123
4 4 4 4 4 4
1 1 1 1 1 1 1 1
1 1
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
124
4 4 4 4 4 4
2 2 2 2 2 2 2 2
3 3
3 3 3 2 3 3 3 3 2 3
2 2 2 3
3 3 3 3 2 2
2 2
2 2 2 2 2
1 1 1 1 1 1
2 2 2
125
1 1 1 1 1 1
2 2 1 1 1 1 2 2
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
126
3 3 3 3 3 3
2 2 2 2 2 2 2 2
3 3
3 1 3 2 1 1 1 3 2 3
2 2 2 3
3 2 2 3 2 2
3 3
2 2 2 2 2
3 3 3 3 3 3
3 3 3
127
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
128
2 6 6 2 6 6
2 2 6 4 6 6 6 6
3 3
6 4 4 6 6 6 6 6 4 6
2 2 2 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
2 6 6
129
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
130
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 2
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
6 6
4 4 4 4 4
6 2 6 4 6 6
4 4 4
131
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 1 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
132
2 2 2 2 2 2
1 1 3 3 3 3 1 1
2 2
1 1 1 1 1 1 1 1 2 2
2 2 2 2
3 3 3 2 2 2
4 4
2 2 2 2 2
2 1 1 1 1 1
4 4 4
133
3 6 6 3 6 6
2 2 6 4 6 6 6 6
2 2
6 4 4 6 6 6 6 6 4 6
3 3 3 6
6 6 6 6 4 4
6 6
4 4 4 4 4
2 3 2 6 2 2
6 6 6
134
1 1 1 1 1 1
1 1 1 1 1 1 1 1
1 1
1 1 1 3 1 1 1 1 1 1
1 1 1 1
1 1 1 1 1 1
1 1
1 1 1 1 1
1 1 1 1 1 1
1 1 1
135
2 6 6 2 6 6
2 2 6 4 6 6 6 6
2 2
4 4 4 4 4 4 4 4 4 4
2 2 2 4
4 4 4 4 4 4
4 4
4 4 4 4 4
6 2 6 4 6 6
4 4 4
136
1 1 1 1 1 1
2 2 2 2 2 2 2 2
1 1
1 1 1 1 1 1 1 1 2 2
2 2 2 2
3 3 3 2 2 2
2 2
2 2 2 2 2
1 1 1 1 1 1
1 2 1
137
2 6 6 2 6 6
6 6 6 4 6 6 6 6
2 2
4 4 4 4 4 4 4 4 6 2
2 2 2 2
4 4 4 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
138
2 6 6 2 6 6
6 6 6 4 6 6 6 6
6 6
4 4 4 4 4 4 4 4 6 6
6 6 6 6
4 4 4 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 6
139
2 6 6 2 6 6
6 6 6 4 6 6 6 6
2 2
4 4 4 4 4 4 4 4 6 2
2 2 2 2
4 4 4 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
140
6 4 4 6 4 4
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
6 4
4 4 6 6 4
6 4 4 4 4 4
4 4 4
141
2 6 6 2 6 6
6 6 6 4 6 6 6 6
2 2
4 4 4 4 4 4 4 4 6 2
2 2 2 2
4 4 4 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
SU
PLu
PT
PTa
PTd
PTe
PTu
PZ
PZb
PZc
PZf
PZg
PZh
PZi
RG
RGc
RGd
RGe
RGi
RGu
RGy
SC
SCg
SCh
SCl
SCk
SCm
SCn
SCy
SN
SNg
SNh
SNj
SNk
SNm
SNy
VR
VRd
VRe
VRk
VRy
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
IL
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Units
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
SL
Input Level
Table A18 FAO '90 SOIL UNIT RATINGS FOR TREE SPECIES IN BOREAL, TEMPERATE AND SUBTROPICAL CLIMATES
SEQ Bi 1 2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
142
2 6 6 2 6 6
4 4 6 4 6 6 4 4
2 2
4 4 4 4 4 4 4 4 6 6
6 6 6 6
4 4 4 6 6 4
6 6
6 6 6 6 6
2 2 6 4 6 6
6 6 2
143
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
144
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
145
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
146
4 4 4 4 4 4
6 6 6 6 6 6 6 6
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
147
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
148
6 2 2 6 2 2
2 2 2 2 2 2 2 2
2 2
2 2 2 6 6 2 2 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
2 2 2 2 2 2
2 2 2
149
6 2 2 6 2 2
2 2 2 2 2 2 2 2
2 2
2 3 2 6 2 3 3 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
2 2 2 2 2 2
2 2 2
150
6 2 2 6 2 2
2 2 2 2 2 2 2 2
2 2
2 3 2 6 6 3 3 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
2 2 2 2 2 2
2 2 2
151
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
6 2 6 4 6 2 2 6 4 6
4 4 4 6
4 4 4 4 4 4
6 6
6 6 6 6 6
6 6 6 6 6 6
6 6 6
152
6 4 4 6 4 4
2 2 6 4 6 6 6 6
2 2
6 4 4 4 4 6 6 6 4 6
6 6 6 6
4 4 4 6 4 4
4 4
4 4 4 4 4
6 2 6 4 6 6
6 4 4
153
6 2 2 6 2 2
2 2 2 2 2 2 2 2
2 2
2 2 2 6 6 2 2 2 6 2
6 6 6 2
2 6 6 2 2 6
2 2
2 2 2 2 2
2 2 2 2 2 2
2 2 2
154
6 4 4 6 4 4
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 6
6 4 4 4 4 4
4 4 4
155
1 1 1 1 1 1
3 3 3 3 3 3 3 3
1 1
1 1 1 1 3 1 1 1 2 1
1 1 1 1
1 3 3 1 1 2
1 3
1 1 1 1 1
3 1 3 3 3 1
3 1 1
156
2 2 2 2 2 2
3 3 2 2 2 2 3 3
3 3
1 1 1 1 3 1 1 1 2 1
1 1 1 1
1 3 3 1 2 2
4 4
4 4 4 4 4
6 2 2 2 2 2
3 4 1
157
2 3 3 2 3 3
2 2 2 2 2 2 2 2
3 3
3 3 3 2 2 3 3 3 2 3
2 2 2 3
3 2 2 3 2 2
3 2
2 2 2 2 2
2 3 2 2 2 3
2 3 3
158
3 1 1 3 1 1
3 3 3 3 3 3 3 3
1 1
1 1 1 1 3 1 1 1 2 1
1 1 1 1
1 1 1 1 1 2
1 3
1 1 1 1 1
3 1 3 3 3 1
3 1 1
159
6 6 6 6 6 6
4 4 4 4 4 4 4 4
6 6
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
2 6
4 4 6 6 4
6 4 4 4 4 4
4 4 4
160
2 3 3 2 3 3
2 2 2 2 2 2 2 2
3 3
3 3 3 2 2 3 3 3 2 3
2 2 2 3
3 2 2 3 2 2
3 2
2 2 2 2 2
2 3 2 2 2 3
2 3 3
161
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
162
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
163
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
164
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
165
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
166
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
167
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
168
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
169
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
170
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
171
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
172
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
173
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
174
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
175
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
176
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
177
6 4 4 6 4 4
2 2 6 6 6 6 2 2
6 6
6 6 6 6 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
178
4 4 4 4 4 4
6 6 6 6 6 6 6 6
6 6
6 6 6 4 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
179
6 4 4 6 4 4
2 2 6 6 6 6 2 2
6 6
6 6 6 6 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
6 6 6 6 6 6
6 4 4
180
4 4 4 4 4 4
2 2 6 6 6 6 2 2
6 6
6 6 6 6 4 4 4 6 4 6
6 6 6 4
4 4 4 6 4 4
4 4
4 4 4 4 4
4 6 6 6 6 6
6 4 4
181
4 4 4 4 4 4
4 4 4 4 4 4 4 4
4 4
4 4 4 4 4 4 4 4 4 4
4 4 4 4
4 4 4 4 4 4
4 4
4 4 4 4 4
4 4 4 4 4 4
4 4 4
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
IL
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
SP
Anthraquic
Duripan
Fragipan
Gelundic
Gigai
Inundic
Lithic
Petroferric
Phreatic
Placic
Rudic
Salic
Skelectic
Sodic
Takyric
Yermic
Desert
Gobi
Cultivation
SEQ Bi 1
001
1
002
1
003
1
004
2
005
1
006
1
007
2
008
3
009
1
010
3
011
3
012
4
013
3
014
4
015
4
016
4
017
4
018
4
019
1
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
PH
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
H
H
H
Anthraquic
Duripan
Fragipan
Gelundic
Gigai
Inundic
Lithic
Petroferric
Phreatic
Placic
Rudic
Salic
Skelectic
Sodic
Takyric
Yermic
Desert
Gobi
Cultivation
001
002
003
004
005
006
007
008
009
010
011
012
013
014
015
016
017
018
019
3
3
1
2
3
1
2
3
1
3
3
4
3
4
4
4
4
4
1
Fir
Abies alba
Abies sibirica
Cunninghamia lanceolata
Pine
Pinus sibirica
Pinus sylvestris
Pinus tabulaeformis
Pinus massoniana
Pinus yunnanensis
Pinus koreaiensis
Spruce
Picea abies
Picea asperata
Picea ajanensis
Picea obovata
Picea koreaiensis
Black locust
Chestnut
Wallnut
Larch
Larix gmelinii
Larix sibirica
Alder
Lime
Maple
Acer plantanoides
Acer campestre
Acer campbelii
Beech
Hornbeam
Ash
Fraxinus excelsior
Fraxinus mandshurica
Oak
Quercus robur
Quercus petraeea
Quercus rubra
Quercus lanuginosa
Quercus cerris
Quercus acutissima
Quercus variablis
Quercus mongolica
Willow
Salix alba
Salix viminalis (plantation)
Poplar
Populus nigra
Populus euramericana
Polpulus alba
Populus tremula
Populus balsamiferas
Populus maximowiczii
Populus tomentosa
Populus euphraetica
Birch
Betula pubescens
Betula pendula
Betula verrucosa
Betula tortuosa
Betula Platypphylla
Betula papyrifera
FAO '90 Soil Phases
Input Level
Table A19 FAO '90 SOIL PHASE RATINGS FOR BOREAL, TEMPERATE AND SUBTROPICAL TREE SPECIES
2 3 4 5 6 Po 1 2 3 4 5 6 7 8 Wi 1 2 Oa 1 2 3 4 5 6 7 8 Be Ho As 1 2 Al Li Ma 1 2 3 Bl Ch Wa La 1 2 Sp 1 2 3 4 5 Pi 1 2 3 4 5 6 Fi 1 2 3
1
3
1
2
1
3
6
2
1
2
2
4
2
4
4
4
4
4
1
1
3
1
2
1
3
6
2
1
2
2
4
2
4
4
4
4
4
1
1
1
1
2
1
1
2
3
1
3
3
4
3
4
4
4
4
4
1
1
3
1
6
1
3
6
2
1
2
2
4
2
4
4
4
4
4
1
1
3
1
6
1
3
6
2
1
2
2
4
2
4
4
4
4
4
1
1
2
3
6
1
1
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
1
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
1
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
2
1
2
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
1
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
1
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
3
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
3
4
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
2
1
1
6
2
1
3
2
4
2
4
4
4
4
4
1
1
3
3
4
3
1
4
2
1
3
2
6
6
6
4
4
4
4
1
1
3
3
4
1
3
6
2
1
2
2
4
2
4
4
4
4
4
1
1
3
3
4
1
4
6
6
1
6
2
4
2
4
4
4
4
4
1
1
6
2
4
1
4
4
4
1
6
6
4
6
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
1
1
4
1
1
6
2
1
3
2
4
2
4
4
4
4
4
1
1
1
1
4
1
1
6
2
1
3
2
4
2
4
4
4
4
4
1
1
1
1
4
1
1
6
2
1
3
2
4
2
4
4
4
4
4
1
1
2
2
4
1
4
4
6
3
6
6
4
6
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
2
3
6
1
2
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
6
1
4
6
6
1
6
2
4
6
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
1
1
2
1
1
2
2
1
3
3
4
3
4
4
4
4
4
1
1
3
1
2
1
1
6
6
1
3
2
4
2
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
6
4
6
4
4
4
4
4
1
1
3
1
2
1
1
6
6
1
3
2
4
2
4
4
4
4
4
1
1
3
1
2
1
1
6
6
1
3
2
6
3
6
4
4
4
4
1
1
3
1
4
1
2
6
6
1
2
2
4
2
4
4
4
4
4
1
1
3
1
4
1
6
6
6
1
6
2
4
2
4
4
4
4
4
1
1
3
1
4
1
2
6
6
1
2
2
4
2
4
4
4
4
4
1
1
3
1
6
1
2
6
6
1
2
2
4
2
4
4
4
4
4
1
1
2
2
4
1
4
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
2
6
1
4
4
6
1
6
2
4
2
4
4
4
4
4
1
1
3
3
4
1
4
6
2
1
6
2
4
2
4
2
2
3
2
3
3
6
2
1
2
2
4
2
4
4
4
4
4
1
2
2
3
2
3
3
6
2
1
2
2
4
2
4
4
4
4
4
1
3
3
1
2
3
1
2
3
1
3
3
4
3
4
4
4
4
4
1
2
2
3
6
3
3
6
2
1
2
2
4
2
4
4
4
4
4
1
2
2
3
6
3
3
6
2
1
2
2
4
2
4
4
4
4
4
1
3
6
2
6
3
1
4
6
1
6
2
4
2
4
4
4
4
4
1
3
6
2
6
3
1
4
6
1
6
2
4
2
4
4
4
4
4
1
2
6
2
6
3
1
4
6
1
6
2
4
2
4
4
4
4
4
1
6
6
2
2
3
2
4
6
1
6
2
4
2
4
4
4
4
4
1
2
6
2
6
3
1
4
6
1
6
2
4
2
4
4
4
4
4
1
2
6
2
6
3
1
4
6
1
6
2
4
2
4
4
4
4
4
1
2
6
2
6
3
3
4
6
1
6
2
4
2
4
4
4
4
4
1
2
6
2
6
3
3
4
6
1
6
2
4
2
4
4
4
4
4
1
1
2
2
2
3
1
6
2
1
3
2
4
2
4
4
4
4
4
1
1
2
2
2
3
1
6
2
1
3
2
4
2
4
4
4
4
4
1
2
2
2
4
3
3
6
2
1
2
2
4
2
4
4
4
4
4
1
6
2
2
4
3
4
6
6
3
6
2
4
2
4
4
4
4
4
1
6
4
6
4
3
4
4
4
3
6
6
4
6
4
4
4
4
4
1
2
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
3
3
3
4
3
1
6
2
1
3
2
4
2
4
4
4
4
4
1
3
3
3
4
3
1
6
2
1
3
2
4
2
4
4
4
4
4
1
3
3
3
4
3
1
6
2
1
3
2
4
2
4
4
4
4
4
1
6
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
2
4
3
2
6
6
1
6
2
4
2
4
4
4
4
4
1
6
6
2
6
3
2
6
6
3
6
2
4
2
4
4
4
4
4
1
4
2
2
6
3
4
6
6
3
6
2
4
6
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
3
3
1
2
3
1
2
2
1
3
3
4
3
4
4
4
4
4
1
2
2
3
2
3
1
6
6
1
3
2
4
2
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
4
6
6
4
3
4
4
6
3
6
6
4
6
4
4
4
4
4
1
2
2
3
2
3
1
6
6
1
3
2
4
2
4
4
4
4
4
1
3
2
3
2
3
1
6
6
1
3
2
6
3
6
4
4
4
4
1
6
2
3
4
3
2
6
6
1
2
2
4
2
4
4
4
4
4
1
6
2
3
4
3
6
6
6
1
6
2
4
2
4
4
4
4
4
1
6
2
3
4
3
2
6
6
1
2
2
4
2
4
4
4
4
4
1
6
2
3
6
3
2
6
6
1
2
2
4
2
4
4
4
4
4
1
6
6
6
4
3
4
4
6
1
6
2
4
2
4
4
4
4
4
1
6
6
6
6
3
4
4
6
1
6
2
4
2
4
4
4
4
4
1
4
2
2
4
3
4
6
2
1
6
2
4
2
4
4
4
4
4
1
4
4
4
4
1