technical report no. 45
national carbon
accounting system
Review of C:N Ratios in
Vegetation, Litter and
Soil Under Australian
Native Forests and
Plantations
Peter Snowdon, Phil Ryan and John Raison
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REVIEW OF C:N RATIOS IN VEGETATION,
LITTER AND SOIL UNDER AUSTRALIAN
NATIVE FORESTS AND PLANTATIONS
Peter Snowdon, Phil Ryan and John Raison
CSIRO Forestry and Forest Products
National Carbon Accounting System Technical Report No. 45
March 2005
Printed in Australia for the Australian Greenhouse Office in the Department of the
Environment and Heritage
© Commonwealth of Australia 2005
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March 2005
Department of the Environment and Heritage Cataloguing-in-Publication
Snowdon, Peter.
Review of C:N ratios in vegetation, litter and soil under Australian native forests and
plantations / Peter Snowdon, Phil Ryan and John Raison
p. cm.
(National Carbon Accounting System Technical Report; No. 45)
ISSN: 1442 6838
1. Forest soils-Carbon content-Australia-Analysis. 2. Forest soils-Nitrogen contentAustralia-Analysis. 3. Forest biomass-Australia-Analysis. I. Ryan, Philip J. II. Raison, R.
John (Robert John) III. Australian Greenhouse Office. IV. Series
363.73874’0994-ddc22
631.417’0994-dc22
ii
Australian Greenhouse Office
EXECUTIVE SUMMARY
1.
ANALYTICAL CONSIDERATIONS
Modern instrumental methods for analysing
carbon concentrations [C] and nitrogen
concentrations [N] in organic materials are
fast and accurate. Until recently, analysis of
plant material for [C] was less common, and
in many cases a [C] of 50% was assumed.
Various plant tissues probably vary in [C]
from 45-55% although some reported values
lie slightly outside this range.
2.
Soil organic [C] has often been estimated
indirectly by wet digestion (Walkley-Black
method 1934). Conversion to [C] requires
a correction factor to account for variable
oxidation in different soils, but this correction
factor is not always known. Loss on ignition
has also been used to estimate soil organic
matter but this method needs local calibration
because several soil factors can influence the
results. Dry combustion methods measure
[C] directly but can include unwanted
components such as charcoal. Analyses for
total soil [N] are straightforward, provided
that digestion of organic N is complete.
3.
With all methods, analytical variation in
results can occur both within and between
laboratories. Coefficients of variation for the
analysis of plant materials are generally less
than 6% for both [C] and [N], but analyses
of soils are much more variable, being in the
range 13–22%.
5.
6.
Available soil C:N ratio data have some
major limitations due to differences in the
size fraction analysed, chemical analytical
methodology, and errors due to calculation of
C:N ratios from mean [C] and [N]. For plant
materials the [C] is rarely measured, and a [C]
of 50% is often assumed when calculating C:N.
C:N RATIOS IN VEGETATION,
LITTERFALL AND LITTER ON
THE FOREST FLOOR
Above-ground standing biomass consists of
a woody component (wood, bark, branches)
which is persistent through time, and
foliage for which individual components
generally persist for only a few years or
less. A limited number of estimates of the C:
N ratios of these components are available
from biomass studies. Specific studies of
tissues such as sapwood, heartwood, bark
and foliage exist but the samples often may
not be representative because they fail to
adequately account for variation within the
component. The C:N ratio of foliage is much
lower (19-66) than that of wood (250-2500)
or other components. Nevertheless, in young
stands more than 60% of the N held in the
above-ground biomass occurs in the foliage. In
mature stands this proportion can fall to 50%.
C:N ratios are usually lower in tissues from
N-fixing species than comparable tissues from
non-N-fixing species.
7.
Little information is available on the C:N
ratios in roots. The ratios in woody roots are
similar to those in above-ground components
of similar size. Fine roots (variously defined)
have been reported to have C:N ratios in the
range 23-226 with a mean of 53.
8.
The majority of species occurring in native
forests or plantations withdraw (retranslocate)
up to 50% of foliar N content prior to leaf
shed, but overstorey species from subtropical
rainforests may withdraw little N. In
plantations the [N] in leaf-fall tends to increase
National Carbon Accounting System Technical Report
iii
4.
Particular attention must be paid to the
representativeness of what is sampled for
analysis. For example, whole canopies are
rarely sampled in forests. Some samples such
as litter and roots may need special treatment
to avoid the influence of soil contamination on
analytical results. The past tendency to only
analyse the soil fine earth fraction means that
most of the reported C:N ratios underestimate
the actual whole soil C:N ratio.
with the quantity of leaves shed (indicative of
N availability and stand productivity).
The quantity of litterfall tends to increase with
stand age, and in eucalypt-dominated native
forests the proportion of leaves decreases
from more than 90% in young stands to about
20% in old stands. C:N ratios increase as the
proportion of woody material increases. In
native eucalypt forests the range in C:N in
total litterfall has been observed to be between
64 and 112.
9.
10.
The C:N ratios in forest floor litter vary
between components with leaf < fine woody
< coarse woody material. For example, the
average values in eucalypt woodland systems
are 59, 115, and 379, respectively, for these
components. In ecosystems with a high
proportion of N-fixing species, C:N ratios are
lower than in other systems. Studies of litter
decomposition indicate that while biomass of
individual decaying components decreases
with time, their N content can increase,
decrease or fluctuate depending on litter
quality and environmental conditions.
Forest operations such as pruning, thinning
and harvesting affect nutrient cycles by
either removing nutrients from the site or
by returning components to the forest floor.
Different options for fire management can
have marked effects on the quantities of C and
N lost from the ecosystem.
C:N RATIOS IN SOILS
11.
iv
C:N ratios in Australian forest soils are highly
variable, but some generalisations can be made.
Earlier reviews have identified that climate,
especially rainfall and temperature, are the
most important factors affecting soil C and
N stocks. Phosphorus (P) content of the soil
parent material, degree of weathering, and
topographical influences are also important.
Vegetation cover influences both the amount
and quality (C:N ratio) of soil organic matter.
12.
Eucalypt forests generally have high (21–33)
C:N ratios in surface soils whereas ecosystems
dominated by other genera tend to have lower
ratios. Pine plantations have higher ratios
than eucalypt plantations. The latter reflects
the influence of eucalypt plantings on expasture (lower C:N ratio) compared with pine
predominantly on ex-native forest soils.
13.
Conifer plantation soils usually have higher
C:N ratios than their paired native forest site
but the reverse is observed in litter layers.
Fertilisation with P, which increases stand
growth, can increase soil and litter C:N ratios
in pine plantations growing on poor sites.
However, fertilisation with NP fertiliser has
had either no to mixed effects on soil C:N
ratios. Harvesting plantations or native forests
has produced either no impact or caused a
minor decrease in soil C:N ratios. Similarly,
fire seems to not affect C:N ratios, although
the separation of the effects of C contained in
inert charcoal has not been attempted.
14.
Certain extreme environmental conditions
will produce extreme C:N ratios. Saturated
anaerobic conditions, cold temperatures, and
strongly leaching conditions can result in very
high C:N ratios, while high temperatures and
low rainfall can produce very low C:N ratios.
15.
Further collection of soil C:N data, together
with ancillary data on geographicalposition, soil P, exchangeable Al, pH and size
fraction, would enable the testing of several
hypotheses on the importance of climate and
other environmental/pedogenic factors in
affecting forest soil C:N ratios. Collating good
geographical-position data for locations where
there is existing C:N data would be costeffective in enabling the use of continental
scale spatial modelling to examine the effects
of rainfall, temperature and/or evaporation,
and other factors on soil C:N ratios.
Australian Greenhouse Office
TABLE OF CONTENTS
Page No.
Executive Summary
iii
1. Introduction
1
2. Methods for Estimating C:N Ratios
1
2.1
2.2
Organic Materials
1
2.1.1
Carbon
1
2.1.2
Nitrogen
3
2.1.3
Approximate C:N Ratios
3
2.1.4
Special Precautions Needed During Chemical Analysis
3
2.1.5
Estimation of Nitrogen from Satellite Imagery
4
Soils
2.2.1
2.3
4
Carbon
4
Sampling and Methodological Limitations
5
2.3.1
Vegetation, Litterfall and Forest Floor Litter
5
2.3.2
Soils
5
2.3.3
2.3.2.1
What Soil is Being Sampled and Analysed?
5
2.3.2.2
Variation with Depth
6
2.3.2.3
Variation with Space and Time
6
Published Versus Calculated C:N Values
3. Vegetation
3.1
3.2
3.3
6
7
Nitrogen Content and C:N Ratios
7
3.1.1
Woody Biomass
7
3.1.2
Foliage
3.1.3
Roots
9
11
Nitrogen Changes in Leaves and Litter
13
3.2.1
Litterfall
13
3.2.2
Litter on the Forest Floor
15
3.2.3
Litter Decomposition
Effects of Forest Operations on C:N Ratios
4. Soil and Coarse Woody Debris
16
19
20
4.1
Previous Reviews
20
4.2
Nature of Current Review
20
4.3
Effects of Forest Vegetation
23
4.4
4.3.1
Summary of Soil and Litter Differences
23
4.3.2
Native Forests
23
4.3.3
Plantations
24
4.3.4
Paired Plots: Conifer Plantations Versus Native Eucalypt Forests or Pastures
24
4.3.5
Paired Plots: Eucalypt Plantations Versus Native Eucalypt Forests or Pastures
26
4.3.6
‘Latitude’ Effects – State Summaries for Eucalypt Forests
27
Effects of Environmental Factors
27
4.4.1
Climate
27
4.4.2
Parent Material
28
National Carbon Accounting System Technical Report
v
TABLE OF CONTENTS
continued
Page No.
4.4.3
4.5
4.6
Terrain
28
Pedogenic Factors
29
4.5.1
Time (weathering, leaching)
29
4.5.2
Morphology (soil type)
29
4.5.3
Exchangeable Al
30
4.5.4
Size Fraction
30
Forest Management (Disturbance) Effects
30
4.6.1
Site Establishment
30
4.6.2
Fertilisation
30
4.6.3
Weed Control
31
4.6.4
Harvesting/Thinning
31
4.6.5
Fire
31
4.7
Sources of Unpublished Forest Soil Chemical Data
32
4.8
Summary
33
4.9
References for Database and Report
34
Appendix 1.
Measured [C] and [N] and C:N ratios in various components of forest species.
ha-1)
ha-1)
47
Appendix 2.
and nitrogen content (kg
of foliage and total above-ground
Biomass (t
biomass in various native forest and plantation ecosystems.
50
Appendix 3.
Biomass (kg ha-1) and nitrogen content (kg ha-1) of leaves and total litterfall
for a range of native and plantation forests.
52
Appendix 4.
Biomass (t ha-1), nitrogen content (kg ha-1) and concentration (% ODW)
and C:N ratios of litter in various ecosystems.
54
Appendix 5.
Database structure (CNsoils.mdb). The database is held with the NCAS of
the AGO, Canberra.
56
LIST OF FIGURES
Figure 1.
Proportion of total above-ground biomass N content contained in the foliage of
native forests and plantations.
Figure 2.
Average [N] (% ODW) in above-ground woody biomass (wood, bark and branches)
of various native forests and plantations (data included in Appendix 2).
10
Figure 3.
Relationship between nitrogen concentrations [N] and total leaf-fall in native and
plantation grown eucalypts. (For data see Appendix 3).
14
Figure 4.
Proportion of total litterfall present as leaf material in native forests and plantations
(For data see Appendix 3).
15
Figure 5.
Surface soil C:N ratios categorised by the Australian Great Soil Group, and Australian
States. Medians, interquartile ranges and sample size are presented.
21
Figure 6.
A pruned tree regression for predicting surface soil C:N ratios across Bago-Maragle
State Forests. Variables are AI, mean annual temperature (MAT), RELIEF (range of
elevation within a 300 m radius area). Values within ellipses are the predicted
C:N means for that branch of the tree regression.
29
vi
7
Australian Greenhouse Office
LIST OF TABLES
Table 1.
Range of carbon and nitrogen concentrations, and C:N ratios in tissues from
15 species of eucalypts (Gifford 2000a).
1
Table 2.
Carbon concentrations in roots of various sizes from three species (Parrotta 1999).
2
Table 3.
Carbon content of wood calculated from extractive analysis data (from Mathews 1993).
2
Table 4.
Estimated carbon content of tissues with different lignin contents, assuming the carbon
content of lignin to be 65% and 45% for other components.
2
Table 5.
Variation in the determination of [C] and [N] and in samples of soil and plant materials
analysed by different laboratories. Data from Johnstone et al. (2000, 2001).
4
Table 6.
Averages and coefficients of variation for C (Walkley-Black) to N ratios based on
results from ten laboratories.
5
Table 7.
[N] (% ODW) in bark, sapwood and heartwood of various native forest species.
8
Table 8.
[N] (% ODW) in bark and stemwood determined in biomass studies of various
native forest species.
9
Table 9.
[N] (% ODW) in the youngest mature leaves of plantation trees >5 years old, and
free from effects of deficiency or toxicity (based on Boardman et al. 1997).
11
Table 10.
Nitrogen concentration [N] of N-fixing and non-N-fixing species in native stands
and plantations grown on comparable sites.
12
Table 11.
Foliar nitrogen concentration [N] (% ODW) derived from biomass studies of native
forests and selected plantations species.
12
Table 12.
Nitrogen concentration [N] (% ODW) and C:N ratios of fine roots for various species.
13
Table 13.
Nitrogen concentrations [N] (% ODW) in litterfall from various forest and
plantation ecosystems.
16
Table 14.
Average nitrogen concentration [N] (% ODW) and C:N ratios in litter from various
native forest and plantation ecosystems.
17
Table 15.
Concentration of carbon [C] and nitrogen [N] (% ODW), and C:N ratios in leaf litter,
woody litter and CWD from various woodland ecosystems in Queensland
(data from Harms and Dalal 2003).
18
Table 16.
C:N ratios in surface soil layers for various forest ecosystems. Calculated values are
derived from the database summaries derived from individual data.
22
Table 17.
C:N ratios for surface litter layers in various ecosystems.
23
Table 18.
C:N ratios for coarse woody debris in various ecosystems.
24
Table 19.
Soil C:N ratios from paired plot comparison of conifer plantations with adjacent
native forest.
25
Table 20.
Litter C:N ratios for paired plot comparison of conifer plantations with adjacent
native forest.
25
Table 21.
CSIRO FFP and QFRI (FWPRDC, 2004) forest floor and whole soil C:N ratios.
26
Table 22.
Soil C:N ratios for paired plot comparison of eucalypt plantations with either
adjacent native forest or pasture (Aggangan et al. 1998).
27
Table 23.
Variation in C:N ratios of surface soils for eucalypt forests grouped by State.
27
Table 24.
Custodians of available forest soil, litter and CWD chemical data.
32
National Carbon Accounting System Technical Report
vii
viii
Australian Greenhouse Office
1. INTRODUCTION
The cycling of Carbon (C) and Nitrogen (N) are
closely linked in biological systems. The C:N ratio
in vegetation, litter and soils can provide insights
into cycling processes, rates of turnover of pools,
stocks of C and N in ecosystem components, and
likely responses of the N cycle after ecosystem
perturbation. Models of C and N cycling in
terrestrial ecosystems (e.g. the Century model
and its variations) often utilise the C:N ratio of
pools as the primary model structure.
The Australian Greenhouse Office (AGO) is
currently developing and calibrating the FullCAM
model to enable estimation of the N dynamics and
non-CO2 (mainly nitrous oxide) flux in Australian
land systems.
The purpose of this review was to synthesize
existing information on the C:N ratio of ecosystem
components (vegetation, litter and soil) in Australian
forests. This is an input to calibration of a model of
the N cycle in Australian forests, and to generating
data which will enable the model to be run spatially.
2. METHODS FOR ESTIMATING C:N RATIOS
2.1
ORGANIC MATERIALS
2.1.1 Carbon
Carbon concentrations, [C], in organic materials
are determined in modern laboratories by dry
combustion methods where C (as CO2) is detected
by infra-red absorption measurement (e.g. LECO
CN analyzer), or where C is measured by mass
spectrometry (e.g. Europa Elemental Analyzer).
[C] in eucalypt tissues can vary in the range 38–56%
C (Table 1). Generally there is a relatively small
range of values with the coefficients of variation for
different tissues across different tree species, being in
the range 2.5 to 7.5% Gifford 2000a). This is similar
to differences (1.1–6.9%) found between trees of the
same species. Differences in values can be ascribed
to different proportions of C-containing compounds
such as lignin, cellulose and carbohydrates, and to
variations in mineral ash content (see Table 1).
Table 1. Range of carbon and nitrogen
concentrations, and C:N ratios in tissues from
15 species of eucalypts (Gifford 2000a).
Tissue
C%
N%
C:N
Green leaf
50.0 – 55.4
0.84 – 1.99
28 – 65
1-year-old twig
46.3 – 52.0
0.41 – 0.88
56 – 131
Branch
42.7 – 48.3
0.27 – 0.46
103 – 194
Bark
37.8 – 50.8
0.28 – 1.32
38 – 185
Sapwood
39.6 – 51.1
0.08 – 0.44
124 – 642
Heartwood
48.4 – 54.1
0.07 – 0.24
402 – 733
Leaf litter
51.5 – 55.6
0.40 – 2.08
27 – 146
Total Range
37.8 – 55.6
0.07 – 2.08
27 – 642
The [C] of woody roots have been examined by
Gifford (2000b). Individual analyses ranged from
43.8% C to 53.1% C with species averages ranging
from 46.7% C to 51.2% C. There was no trend
between C and root diameter but concentrations in
roots were similar to those in sapwood. The average
National Carbon Accounting System Technical Report
1
value was about 49% C. Parrotta (1999) found lower
values than these in three plantation species grown
in Puerto Rico (Table 2).
Table 2. Carbon concentrations in roots of various
sizes from three species (Parrotta 1999).
Species
< 0.2 cm
0.2-1.0 cm
> 1.0 cm
Casuarina equisetifolia
40.8
45.0
45.5
Eucalyptus robusta
39.7
44.2
44.2
Leucaena leucocephala
29.4
45.1
43.2
Older methods of assessment of [C] were based
on the analysis of constituent compounds whose
[C] were known or from the results of destructive
distillation data (Table 3, Mathews 1993).
Calculations in the latter method are complicated
by the fact that the C content of the residual charcoal
can be significantly less than 100% C. Results
with charcoal containing about 82% C are usually
expected. The [C] of cellulose and lignin are well
established at 44.4% and 66.7%, respectively. A value
of 45% has been assumed for hemi-celluloses. Minor
extractives have [C] in the range 40–94%. There are
only a few published values for Australian species
derived using extractive analysis (Table 3). Data from
Bland (1985a) can be used to estimate [C] of
E. regnans wood in the range 61 to 65%.
Table 3. Carbon content of wood calculated from
extractive analysis data (from Mathews 1993).
Component
Eucalyptus
sp.
Blue
gum
River red
gum
Black
wattle
Ash
0.24
0.3
1.7
0.9
Cellulose
47.9
51.3
45.0
42.9
Hemi-cellulose
32.2
22.3
19.2
33.6
Lignin
25.1
21.9
31.3
20.8
Other organics
1.9
1.3
2.8
1.8
Estimated [C]
49.7
49.3
50.7
48.8
2
Thorough examination of the chemical composition
of wood from only about a dozen eucalypt species
has been made (Bland 1985b). Acid insoluble lignin
of 11 southern species was in the range 19.9 to 22.7%.
However, examination of four species sampled from
Papua New Guinea to Tasmania clearly indicates a
trend for lignin content to decrease from about 32%
in the north to about 22% in the south (Kawamura
and Bland 1967). Within stems, lignin decreases from
the sapwood to outer heartwood and then increases
towards the pith (Bland 1985b).
Studies on the foliage of eucalypt overstorey and
dicotyledonous understorey species from Australian
Mediterranean-climate communities indicates that
lignin content falls from about 18% to 10% as foliar
P concentrations increase (Specht and Rundel 1990).
Leaves of acacias can have higher lignin contents
(31-34%) than eucalypts (22-25%) (Bernhard-Reversat
1993; Wedderburn and Carter 1999). Carbon
concentrations would be expected to behave in
a parallel fashion because [C] depends on lignin
content (see Table 4).
Table 4. Estimated carbon content of tissues with
different lignin contents, assuming the carbon
content of lignin to be 65% and 45% for other
components.
Lignin%
Estimated [C]
Lignin%
Estimated [C]
10
47
35
52
15
48
40
53
20
49
45
54
25
50
50
55
30
51
55
56
Small variations in [C] can also occur due to fertiliser
addition, or to age effects. For example, the average
foliar [C] in three fertiliser experiments with Pinus
radiata in the Moss Vale district was 50.4% C
(Snowdon unpublished data). The concentrations
were slightly greater by 0.67% C in one-year-old
Australian Greenhouse Office
needles compared to current foliage. Amelioration of
P deficiency reduced [C] by only 0.2%. These effects
are sufficiently small to be ignored in calculations of
C:N ratios.
2.1.2 Nitrogen
Nitrogen concentrations [N] are often determined
simultaneously with C by dry combustion methods.
Here N2 can be measured by thermal conductivity
(e.g. Leco CN analyzer), or N measured by mass
spectrometry (e.g. Europa Elemental Analyzer).
Until these methods became readily available, N was
extracted by wet combustion (e.g. Kjeldahl method),
which was followed by distillation of ammonia then
titration of the distillate. Since the 1960s colorimetric
determination of ammonium in the digest or in the
distillate have been the most common procedures.
The Kjeldahl method does not quantitatively
convert nitrate and some aromatic compounds
to ammonium, but this deficiency is usually
inconsequential for most soils and plant materials.
In comparison with [C] which is relatively stable, the
[N] in biomass tissues can range over two orders of
magnitude (see Table 1). Furthermore, there can be a
wide range of values within tissue types depending
on species and growing conditions. Gifford (2000a)
found that the coefficients of variation for different
tissues to be in the range 28 to 51%. A similar range
was observed for the coefficients of variation for
C:N ratios.
2.1.3 Approximate C:N Ratios
Reports of [N] are far more common that those
for [C]. It is often assumed that [C] cover a small
range and that it is reasonable to estimate C:N
ratios for modelling purposes by assuming a [C] of
about 50%. Data such as that in Table 1 show that a
significant range in [C] occurs. The veracity of the
assumption depends heavily on the lignin content of
the material. For each 5% increase in lignin content
the [C] is expected to increase by 1% (Table 4). Thus,
when lignin content is known an estimate of [C] can
be made.
Wherever possible C:N ratios based on measured
[C] have been used in this report. However, in
many cases for plant material only [N] have been
available so C:N ratios have been calculated on the
assumption that [C] was 50%. Gifford (2000a,b)
has measured [C], [N] and C:N in a number of
tissues from Australian forest and plantation
species. Additional data are presented in Appendix 1
and Table 15.
2.1.4 Special Precautions Needed
During Chemical Analysis
Special precautions are needed when analysing
materials such as litter and roots which may be
contaminated with soil particles. These contaminants
have a much higher specific gravity than organic
materials and much lower concentrations of C
and N. Their presence will increase the apparent
weight of the sample with the consequence that the
[C] and [N] may be significantly underestimated.
Washing roots can result in leaching losses of
N and other nutrients. In order to infer correct
nutrient concentrations in fine roots they should
be dried as soon as possible after sampling with a
minimal exposure to wet conditions. Corrections
need to be made to the analytical results to account
for the quantity of adhering soil and its nutrient
concentration (Misra 1994). Soil contamination
in root and litter samples is usually determined
from the residual ash and soil particles remaining
after dry combustion of the sample. Results are
usually reported on an ash free basis, in contrast to
components of the above-ground biomass which
retains the generally small ash content.
The ash content of other materials can have small
effects on the estimation of [C] and [N]. For example,
the ash content of heartwoods only varies between
0.1% and 1.0%. Sapwood ash contents are generally
higher than heartwood of the same species but less
than the bark. Decorticating barks of eucalypts can
have much higher ash contents (6.0–12.6% ash)
than those species with fibrous barks (0.5–1.3%
ash), while species with persistent bark hold an
intermediate position (Lambert 1981).
National Carbon Accounting System Technical Report
3
2.1.5 Estimation of Nitrogen
from Satellite Imagery
It is feasible to calibrate spectra in the range 400
to 2500 nm obtained by near infra-red reflectance
spectrometry (NIRS) to obtain estimates of foliar
concentrations of C, N, chlorophyll, lignin and
cellulose. (Bolster et al. 1996; Yoder and PettigrewCrosby 1995; Gillon et al. 1999). The technique has
been applied to eucalypt foliage for the estimation
of N, tannins and phenolics (McIlwee et al. 2001).
This technique opens the way for estimation of foliar
[N] and other components from airborne (Boegh
et al. 2002) and satellite remote sensing data.
2.2
SOILS
2.2.1 Carbon
Interest in soil C per se is a relatively recent
phenomenon. In the past, there was more interest
in determining the amount of soil organic matter
(SOM) as a surrogate for fertility. Thus most of
the few Australian forest soil chemical methods
texts (Lambert 1976, Hefferman 1985) specified the
use of the Walkley and Black (1934) procedure for
determination of soil C based on wet oxidation of
soil by a dichromate-sulphuric acid mixture. This
reaction is incomplete in digesting all organic matter
if no external heat is added, so a correction factor is
typically used to estimate the total organic-C. This
factor is often assumed to be 1.3. Another factor
was used to translate the total organic-C to organic
matter. This latter factor varies but Lambert (1976)
specified 1.72.
Some laboratories that produced Walkley-Black
values did not use the 1.3 correction factor. But when
it is used there can be a reasonable relationship
with total organic C determined by dry combustion
techniques (Little et al. 1962, Lowther et al. 1990,
Wang et al. 1996). This relationship was recently
tested in an exhaustive analysis of several Australian
laboratories by Skjemstad et al. (2000).
Table 5. Variation in the determination of [C] and [N] and in samples of soil and plant materials
analysed by different laboratories. Data from Johnstone et al. (2000, 2001).
Sample
C%
CV % for
carbon analyses
No. of
laboratories
N%
CV % for
nitrogen analyses
No. of
laboratories
110
1.30
21
20
0.095
16.04
17
111
1.06
13
20
0.115
16.09
17
112
1.41
22
20
0.090
20.95
17
113
1.86
20
20
0.108
19.34
17
114
1.75
18
20
0.178
17.48
17
115
2.87
13
20
0.253
18.37
17
Tobacco leaves
39.2
3.36
20
1.95
9.01
39A
Instant potato 1
44.1
4.84
20
1.49
4.70
39A
Instant potato 2
41.5
1.44
20
1.11
5.55
39A
E. nitens leaves
54.2B
3.30B
20
1.44
5.21
39A
Mixed pasture
44.5
2.98
20
2.26
5.89
39A
Wheat flour
44.4
7.29
20
2.47
4.81
39AB
Soils
Plant materials
A Results for laboratories 92 and 93 omitted.
B Results for laboratory 72 corrected.
4
Australian Greenhouse Office
The other cheap analytic method for determining
soil C and organic matter is Loss on Ignition (LOI).
This procedure does require local calibration because
soil factors other than organic C can affect the LOI.
Examples of the use of calibrated LOI-C estimates
are given by Ellis and Pennington (1989), Lowther
et al. (1990) and Carlyle (1995).
In recent times, the preferred soil C analysis
procedure has been the dry combustion or induction
furnace (often referred to as LECO ovens) procedure
(Rayment and Higginson 1992). This procedure
directly measures total soil C and is the preferred
methodology for soil C accounting (McKenzie
et al. 2000). The only complication occurs if the soil is
calcareous (or carbonaceous) because the induction
furnace will measure all C; (organic and inorganic).
Procedures for calcareous soils are detailed in
McKenzie et al. (2000).
The published data are more variable in the
methodology for analysing soil organic C than
for soil total N. For soil C, there has been a move
from Walkley-Black methods to induction furnace
(LECO). Skjemstad et al. (2000) provide an analysis
of the correction factors applied to provide
comparable data between methods.
Organic [C] in soils are commonly highest in
surface soils. They can range from 0 to 15% C but
in Australian soils are commonly < 5% C.
Table 6. Averages and coefficients of variation for
C (Walkley-Black) to N ratios based on results from
ten laboratories.
Sample
C:N ratio
CV%
110
13.2
12.5
111
9.4
16.0
112
16.8
24.7
113
17.2
16.6
114
10.0
16.0
115
11.4
9.0
2.3
SAMPLING AND METHODOLOGICAL
LIMITATIONS
2.3.1 Vegetation, Litterfall and
Forest Floor Litter
The main issue of sampling and methodological
limitations relates to the representativeness of
samples. Invariably a sample consists of a very small
part of the whole, and may not be representative
unless a well-designed sampling scheme has been
applied. Quite often the available data are from
a study designed for some other purpose, with
the consequence that the results may be biased by
design considerations used for the study from which
the data were obtained (compared to those which
may have been obtained by an appropriate sampling
design). Sampling problems such as these arise at the
tissue, tree and ecosystem levels of organisation.
2.3.2 Soils
2.3.2.1
What Soil is Being Sampled
and Analysed?
Soil chemical data for total organic C and N will
depend on what component of soil is being analysed.
Traditionally the analytical component has been the
‘fine earth fraction’ (material that has passed through
a 2 mm mesh sieve). The amount of >2 mm fraction
and what was done with it is often not stated. This is
important for forest soils where this ‘gravel’ fraction
often contains organic components such as roots,
woody debris, charcoal, insect and macro-fauna
carcasses, etc. The philosophical problems associated
with definitions of soil and non-soil in relation to soil
C have been discussed in detail by McKenzie et al.
(2000) and the same arguments are valid for soil N.
Some authors have used the <5 mm fraction
(e.g. Falkiner et al. 1993, Romanya et al. 1994). Other
authors have analysed the whole soil sample. While
this is the preferred approach for carbon accounting
purposes (McKenzie et al. 2000) there are operational
difficulties for very gravely/rocky soils. The whole
problem of ‘representativeness’ of the soil sampling
procedure is rarely tested (see Gillman et al. 1985) for
National Carbon Accounting System Technical Report
5
an exceptional case. McKenzie et al (2000)
also discussed this in detail and it is not discussed
further here.
In summary, most of the published data for forest
soil C:N ratios are not for the whole soil sample
but for a component, usually the fine earth fraction.
The implications of this bias will be discussed
further below.
2.3.2.2 Variation with Depth
Both [C] and [N] vary dramatically from the soil
surface (as coarse woody debris (CWD) and surface
litter) through organic-rich O and A horizons to
organic-poor subsoils. While the variation in soil
C:N ratio is less dramatic than its light components
it is still important to compare C:N ratios from
similar soil depths.
2.3.3
Published versus
Calculated C:N Values
Some papers present C:N values in their tables while
others only present [C] and [N] data. When C:N
ratios are calculated from published averages for
[C] and [N] different C:N values from those given in
the same publication may be obtained. This occurs
because the ratio of means is not equal to the mean
of ratios. The difference is related to the variances
of both components and the degree of correlation
between them. The biggest errors produced by this
process occur where the class has wide variation or
has non-normal distribution.
Here we report means of C:N ratios wherever data
for individual estimates have been available.
An important limitation to the reliability of C:N
ratio data comes where either soil [C] or [N] are
reaching their individual detection limits. At these
low concentrations, the ratio can become erratic and
meaningless. Such situations occur in subsoils and
will be discussed further below.
2.3.2.3 Variation with Space and Time
Most studies reported in the literature have
avoided the problems of spatial variation by
bulking samples, by using randomised block
designs, or by simply ignoring it. Temporal variation
in C:N ratios have received little attention because
the total soil C and N pools are seen to be much
larger than the labile pools. This may not be valid
where there is significant site disturbance such as
under afforestation and deforestation. The effects of
various stochastic disturbances such as fire, drought,
harvest etc. on soil C:N ratios may also be important
and are discussed further below.
6
Australian Greenhouse Office
3. VEGETATION
3.1
NITROGEN CONTENT AND C:N RATIOS
3.1.1 Woody Biomass
In seedlings most of the above-ground biomass is
present as foliage. As woody ecosystems mature the
proportion of woody tissue increases. Consequently,
the N content of the above-ground biomass in
mature systems is largely determined by its
concentration in woody tissues. The proportion of
N in foliage falls from more than 60% in young
stands to less than 10% in mature stands
(Figure 1). The degree to which this occurs is
species dependent. At Puruki in New Zealand a
chronosequence of biomass studies indicated that the
proportion of N held in the foliage fell linearly from
0.627 at a rate of –0.032 for each 100 kg N in the total
above-ground biomass (Beets and Pollock 1987).
The [N] in bark, sapwood and heartwood from
a number of eucalypt and other species in native
forests are given in Table 7. Heartwood [N] is
usually lower than sapwood [N], while bark usually
has the highest [N]. Consistent differences between
the results obtained for eucalypt bark by Lambert
(1981) and Gifford (2000a) may be due to differences
in species sampled and experimental techniques.
Average [N] in sapwood and heartwood from
eucalypts are little different from those of rainforest
species. Table 8 summarises published data for
bark and stemwood [N] for native eucalypt and
other genera of woody plants examined in biomass
studies. Figure 2 illustrates that C:N in the woody
component (wood, bark and branches) of
above-ground biomass tends to decline as total
biomass increases.
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Figure 1. Proportion of total above-ground biomass N content contained in the foliage of native
forests and plantations.
National Carbon Accounting System Technical Report
7
Table 7. [N] (% ODW) in bark, sapwood and heartwood of various native forest species.
Species
Bark
Sapwood
Heartwood
No. of samples
E. bicostataB
1.32
0.29
0.08
E. bridgesianaB
0.47
0.08
0.12
E. camaldulensisB
0.44
0.26
0.12
E. cypellocarpaB
0.90
0.28
0.07
E. dalrympleanaA
0.20
0.36
0.14
E. dalrympleanaB
0.33
0.26
0.24
E. divesA
0.11
0.12
0.09
E. divesB
0.92
0.10
0.14
E. fastigataB
0.53
0.13
0.07
E. grandisA
0.24
0.31
0.15
1
E. laevopineaA
0.31
0.19
0.11
1
E. macrorhynchaB
4
2
0.28
0.23
0.10
E.
maculataA
0.27
0.18
0.10
1
E.
maculosaA
0.20
0.22
0.10
1
E.
manniferaB
0.30
0.10
0.07
E.
melliodoraB
0.65
0.44
0.10
E.
obliquaD
0.23
0.10
0.04
E.
paucifloraB
0.45
0.39
0.13
E.
polyanthemosB
0.36
0.15
0.10
E.
populneaB
0.92
0.24
0.13
E.
radiataA
0.29
0.27
0.19
E.
radiataB
0.57
0.13
0.11
E.
rossiiA
0.15
0.16
0.08
3
E.
rubidaA
0.46
0.31
0.13
2
E.
salignaA
0.30
0.20
0.12
1
E.
sieberiA
0.18
0.11
0.07
1
E.
viminalisA
0.27
0.20
0.09
1
E.
viminalisB
0.55
0.14
0.11
Mean for Lambert
0.25
0.22
0.11
12
Mean for Gifford
0.60
0.21
0.11
15
A. decurrensB
0.93
0.16
0.21
1.71
0.26
0.16
0.30
0.10
0.08
0.89
0.28
0.15
0.27
0.17
0.14
1
0.62
0.19
0.14
4
A.
melanoxylonB
Calduvia
Callitris
paniculosaC
spB.
Ceratopetalum
apetalumA
Cryptocarya erythroxylonC
8
2
5
5
Australian Greenhouse Office
Species
C.
obovata C
Bark
Sapwood
Heartwood
No. of samples
0.90
0.32
-
1
Doryphora
sassafras C
1.08
0.29
0.23
5
Dysoxylum
fraserianum C
2.37
0.20
0.17
3
1.32
0.30
-
4
Euodia
micrococca C
Exocarpus
cupressiformis B
0.62
0.22
0.25
australis C
0.70
0.23
0.27
1
Geissois
benthamii C
0.29
0.11
0.09
6
Heritiera
actinophylla C
0.60
0.24
0.13
4
0.70
0.21
0.22
4
1.04
0.19
-
4
Orites excelsa C
0.20
0.08
0.04
4
Sloanea woollsii C
0.34
0.08
-
3
Tristania conferta A
0.31
0.21
0.19
4
Mean for rainforest species
0.77
0.19
0.15
14
Flindersia
H.
trifoliata C
Neolitsea
reticulata C
A Data from Lambert (1981)
B Data from Gifford (2000a&b)
C Data from Lambert et al. (1983)
D Data from Baker and Attiwill (1985)
Table 8. [N] (% ODW) in bark and stemwood
determined in biomass studies of various
native forest species.
Species
Bark
Stemwood
Reference
Acacia sp.
0.62
0.16
Feller (1980)
Banksia aemula
0.20
0.10
Westman and
Rogers (1977)
Eucalyptus.
calophylla
0.17
0.067
Hingston
et al. (1979)
0.175
0.047
Hingston
et al. (1979)
E. dives
0.46
0.15
Feller (1980)
E. obliqua
0.16
0.08
Feller (1980)
E. regnans
0.13
0.02
Feller (1980)
E. signata
0.26
0.21
Westman and
Rogers (1977)
E. umbra
0.31
0.20
Westman and
Rogers (1977)
E. diversicolor
Jefferys (1999) made a detailed study of the
distribution of N in stems of Pinus radiata and its
relationship with N in foliage and litterfall. The
average concentration of N in stemwood declined
asymptotically with age from about 0.7% in oneyear-old stands to about 0.03% in stands older than
20 years. Concentrations in individual stemwood
rings are highly dynamic. Highest concentrations
(~0.3% N) are found in sapwood rings at the end of
their first growing season. As the rings mature, N is
retranslocated so that heartwood rings may contain
only 0.02% N. As a consequence of the withdrawal
process the average whole stemwood [N] was not
well correlated (r=0.37) with whole-crown [N]. There
was a stronger relationship (r=0.88) between [N] in
1-year-old stemwood and whole-crown foliage [N].
3.1.2 Foliage
In green plant material about 85% of the N content
is present as proteins, 10% as nucleic acid and 5%
in soluble forms such as amino acids, amides and
amines. The major proportion of the protein occurs
as enzymes but there are also structural proteins,
which occur mainly in biological membranes, and
National Carbon Accounting System Technical Report
9
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Figure 2. Average [N] (% ODW) in above-ground woody biomass (wood, bark and branches) of various
native forests and plantations (data included in Appendix 2).
storage proteins. Protein in older leaves can be
hydrolysed to amino acids that are redistributed to
newly developing tissues. Proteolysis results in a
collapse of the chloroplasts and, hence, the yellowing
of older leaves which is an indication of senescence
or the first symptom of inadequate N nutrition.
N is a key element required for leaf production
and, hence, for controlling growth rates.
Leaf age is an important factor affecting concentrations
of nutrients in foliage because the concentrations of
mobile nutrients such as N tend to decline with age
(e.g. Lamb 1976). Seasonal fluctuations in nutrient
concentrations also occur (Lamb 1976; Schönau 1981;
Bell and Ward 1984; Knight 1988). In plantation
trees the foliar concentrations of nutrients are often
used as an aid for assessing the presence of nutrient
deficiencies or the need for fertiliser applications.
In view of the variation in nutrient concentrations
due to leaf age and other factors it is important to
standardise methods of foliar sampling and their
10
timing. The concentration of nutrients in the youngest
fully expanded leaves is often used to diagnose
nutrient status.
Boardman et al. (1997) have compiled a database
of nutrient concentrations in plantation species
(Table 9) while foliar [N] data on about 50 trees and
shrubs from sub-tropical rainforest in New South
Wales have been collected (Lambert et al. 1983;
Lambert and Turner 1986). Fensham and Bowman
(1995) have tabulated data for 11 Northern Territory
species found in monsoon rainforest and savanna.
Specht and Rundel (1990) have characterised foliar [N]
for species in 16 Mediterranean-climate ecosystems.
Data such as these can be used to estimate an upper
limit for [N] in tree canopies. Data from [N] in litter
fall (see below) can be used to estimate a lower limit
for [N]. In Pinus radiata average whole crown [N] is
about 88% of that in the annual one-year-old cohort
on the 3-year-old whorl (Jefferys 1999).
Australian Greenhouse Office
Table 9. [N] (% ODW) in the youngest mature
leaves of plantation trees >5 years old, and free
from effects of deficiency or toxicity (based on
Boardman et al. 1997).
Species
Nitrogen
C:N
Acacia dealbata
2.4 – 3.9
13 – 21
1.35
37
1.4 – 2.6
19 – 36
1.98
25
Ceratopetalum apetalum
0.6 – 1.2
42 – 83
Eucalyptus camaldulensis
1.5 – 2.1
24 – 33
E. delegatensis
1.4 – 1.9
26 – 36
E. diversicolor
1.1 – 1.3
38 – 45
E. dunnii
1.8 – 2.8
18 – 28
E. fastigata
2.0 – 2.3
22 – 25
E. globulus
1.2 – 1.9
6 – 42
E. grandis
1.0 – 1.6
31 – 50
E. maculata
1.4 – 2.4
21 – 36
E. microcorys
0.8 – 1.5
33 – 63
E. nitens
1.3 – 2.2
23 – 29
E. occidentalis
1.5 – 1.9
26 – 33
E. pilularis
0.9 – 1.3
38 – 56
E. regnans
1.6 – 1.9
26 – 31
E. saligna
0.9 – 2.1
24 – 56
E. tereticornis
1.0 – 1.6
31 – 50
Lophostemon confertus
1.1 – 1.4
36 – 45
Pinus canariensis
1.2 – 2.1
24 – 42
P. pinaster
0.6 – 0.9
56 – 83
P. radiata
1.2 – 2.0
25 – 42
Araucaria cunninghamii
A. heterophylla
Casuarina glauca
Even though N is a key element required for leaf
production and for controlling growth rates the
[N] in foliage is not necessarily a good indicator
of forest productivity. Low foliar [N] can indicate
N deficiency which is usually associated with low
productivity. In N-deficient pines and eucalypts,
[N] in foliage is commonly less than 1%. Single
applications of N fertiliser can result in short-term
increases in foliar [N] but within a few years they
decline to pre-fertilisation levels (Crane and Banks
1992). In general, forest stands respond to fertiliser
by producing more foliage having an adequate [N].
Productivity is better related to total canopy nitrogen
content. This is rarely measured but since leaf area
index is closely related to canopy mass a suitable
index for canopy N content could be the product of
leaf area index and foliar [N].
Specht and Rundel (1990) have shown that there
is a close positive relationship between [N] and
[P] of overstorey and understorey species in
Mediterranean-climate communities. P is often
seen as the key element limiting the development
of many Australian ecosystems (e.g. Polglase and
Attiwill 1992). P availability has a major impact on
N fixing systems. N fixing species such as Acacia
have an important role in N balance and cycling in
forest ecosystems (Adams and Attiwill 1984).
N fixing species have higher foliar [N] than nonfixing species grown on comparable sites (Table 10).
These differences persist through senescence so that
higher [N] are maintained in leaf-fall. In natural
and man-made mixed species stands, the presence
of N-fixing species make an important contribution
to [N] and C:N ratios in the litter.
[N] in the whole crown can sometimes be estimated
from mass and N content data in biomass studies.
Few data are available for native forests but more
data are available from local and overseas studies in
plantations species (Table 11).
3.1.3 Roots
Relatively little information is available for the
quantity and nutrient content of root systems due
to sampling difficulties. There are also difficulties
in obtaining precise chemical analyses due to soil
contamination (Misra 1994). [N] in fine roots tend
to be similar to concentrations found in foliage
(Table 12) but there is little evidence that N is
redistributed before the roots die (Nambiar 1987).
As roots become increasingly woody their [N]
drops until in the largest roots and root bole they
are similar to those in stemwood. Gifford (2000b)
presents data for the [N] and [C] in woody roots of a
number of Australian species.
National Carbon Accounting System Technical Report
11
Table 10. Nitrogen concentration [N] of N-fixing and non-N-fixing species in native stands and plantations
grown on comparable sites.
Non-N-fixing species
N%
N-fixing species
N%
Reference
E. diversicolor
1.10
Bossiaea sp.
2.73
Malajczuk and Grove (1977)
E. marginata
0.84
Acacia sp.
2.15
Malajczuk and Grove (1977)
E. regnans
1.35
A. sp.
2.50
Feller (1980)
E. miniata
1.23
A. aulacocarpa
1.61
Fensham and Bowman (1995)
E. tetradonta
0.94
A. aulacocarpa
1.61
Fensham and Bowman (1995)
E. confertiflora
1.25
A. aulacocarpa
1.61
Fensham and Bowman (1995)
E. regnans
1.62
A. dealbata
3.55
Frederick et al. (1985)
E. spp.
0.78
A. decurrens
1.50
Ward and Koch (1996)
E. globulus
1.00
A. mearnsii
2.51
Khanna (1997)
Pinus caribaea
1.10
A. auriculiformis
2.32
Osman et al. (1992)
P. radiata
1.65
A. dealbata
3.55
Frederick et al. (1985)
E. globulus
0.36
A. mearnsii
0.96
Khanna (1997)
E. nitens
0.66
A. melanoxylon
1.77
Wedderburn and Carter (1999)
E. tereticornis
0.85
A. auriculiformis
1.84
Swamy and Proctor (1997)
E. hybrid PF1
0.65
A. mangium
1.62
Bernhard-Reversat (1993)
E. hybrid HS2
0.67
A. auriculiformis
1.51
Bernhard-Reversat (1993)
Green foliage
Senescent foliage / leaf-fall
Table 11. Foliar nitrogen concentration [N] (% ODW) derived from biomass studies of native forests and
selected plantations species.
Ecosystem
Average
Minimum [N]
Maximum [N]
Average foliage C:N
No. of studies
E. diversicolor-E. calophylla A
0.76
66
1
E. diversicolor A
1.11
45
1
E. marginata B
1.04
48
1
E. obliqua D
1.36
37
1
1.31
38
1
0.69
72
1
E.
obliqua D
E. obliqua - E.
E.
dives C
regnans C
1.50
33
1
rubida E
1.07
47
1
Eucalypt plantation
1.46
0.59
1.84
37
21
P. radiata plantation
1.36
1.13
1.65
37
6
Acacia plantation
2.68
2.42
3.55
19
6
E. dives/E.
A Hingston et al. (1979); B Hingston et al. (1981); C Feller (1981); D Baker and Attiwill (1985); E Turner and Lambert (1988).
12
Australian Greenhouse Office
Table 12. Nitrogen concentration [N] (% ODW) and C:N ratios of fine roots for various species.
Ecosystem
Size
Root N%
Root C:N
Reference
Casuarina equisetifolia
< 2 mm
0.77
53A
Parrotta (1999)
Eucalyptus grandis
< 3 mm
0.62
80
Goncalves et al. (1998)
E. nitens
< 3 mm
2.17
23
Misra (1994)
E. populnea
< 2 mm
0.55
79A
Gifford (2000b)
E. robusta
< 2 mm
0.62
64A
Parrotta (1999)
Leucaena leucocephala
< 2 mm
0.13
226A
Parrotta (1999)
Pinus radiata
< 2 mm
0.54
89A
Gifford (2000b)
P radiata
< 0.5 mm live
1.18
42
Nambiar (1987)
P. radiata
< 0.5 mm live
1.24
40
Nambiar (1987)
P. radiata
< 0.5 mm dead
1.26
40
Nambiar (1987)
P. radiata
< 0.5 mm dead
1.32
38
Nambiar (1987)
A [C] measured on sample, otherwise assumed to be 50% C.
3.2
N CHANGES IN LEAVES AND LITTER
3.2.1 Litterfall
Litterfall consists predominantly of senescent
foliage and twigs but there are a variety of other
components (e.g. see Rogers and Westman 1977).
These include young foliage dislodged by wind
or grazing damage, foliage shed after fire damage,
reproductive organs, bark, branches, insect frass,
kino etc. Each is characterised by its own typical
[N] and C:N ratio. For example, the [N] in scorched
foliage shed after fire is closer to that of green foliage
than to senescent foliage (O’Connell 1977). Litterfall
is estimated by using collection traps. Accuracy of
estimates of litterfall depends upon trap size and
distribution. Usually, the small components such
as leaves and twigs are well estimated but the
smallest components such as pollen, seed and insect
frass may pass through the mesh used in the traps
while large components such as branches, cones
and fronds will not be well sampled by trapping.
Separate techniques are required for accurate
estimation of the fall of large components. Litter
traps are often cleared infrequently, e.g. at monthly
intervals. This allows leaching and decomposition
losses of some components to occur before
collection. This can be particularly important in hot,
wet environments. Thus, estimates of biomass and
nutrient content of litterfall should be considered as
minimal values.
Nutrient redistribution, particularly during the
process of leaf senescence, is considered to be an
important process in the nutrition of forest species.
It is seen as an important adaptation for colonisation
and survival on nutrient poor soils. Eucalypts
(Rogers and Westman 1977; O’Connell et al. 1978;
O’Connell and Menage 1982; Turner and Lambert
1988; Lambert and Turner 1989; Polglase and Attiwill
1992), Pinus radiata (Fife and Nambiar 1984; Beets
and Pollock 1987; Crane and Banks 1992), mangroves
(Woodroffe et al. 1988), and Araucaria cunninghamii
(Bubb et al. 1998a&b) can redistribute 50% or more of
their foliage nitrogen content prior to leaf fall. Acacia
mearnsii (Khanna 1997) also retranslocates 50% of
its foliar nitrogen during senescence, but smaller
amounts may be withdrawn from some leguminous
understorey species (O’Connell and Menage 1982).
In eucalypt seedlings the degree of withdrawal may
be greater at low plant N status (Wendler et al. 1995).
Within subtropical rainforest species, retranslocation
of nutrients prior to abscission of foliage seems to be
low for most overstorey species (Lambert and Turner
1989), but there are important exceptions including
National Carbon Accounting System Technical Report
13
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ä
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Figure 3. Relationship between nitrogen concentration [N] and total leaf-fall in native and plantation grown
eucalypts (Circled points are swamp-grown E. camaldulensis) (For data see Appendix 3).
short-lived species that invade after soil disturbance.
Withdrawal of N prior to leaf shed from species
growing in monsoon rainforest and savanna in the
Northern Territory has been estimated to be in the
range 19–54% (Fensham and Bowman 1995).
[N] in needle litterfall from Pinus radiata can be
highly correlated with average [N] in whole-crown
foliage (Jeffreys 1999). Under irrigated conditions
needle litterfall [N] can also be closely related to
growth rate (Khanna 1994), but this was not the
case for non-irrigated stands (Raison and Myers,
1992). A survey of published literature indicates
that in plantation grown eucalypts the leaf-fall [N]
increases with the quantity of leaf-fall (Figure 3).
Sites with high natural fertility and good rainfall
are often chosen for eucalypt plantations. It is likely
that the relationship shown in Figure 3 may indicate
that greater leaf-fall and higher [N] are obtained as
site fertility and water availability improves. The
relationship is less certain for native forests which
14
includes data for species grown in woodlands and
other situations as well as data for closed forests.
The quantity of litterfall tends to increase with
stand age. In eucalypt-dominated native forests
the proportion of leaf material in litterfall tends
to decrease from more than 90% to about 20%
as the total mass of litterfall increases (Figure 4).
This relationship is imprecise because of different
categories (branch size) included in total litterfall,
and presumably due to species composition of the
stands. The relationship is uncertain in eucalypt
plantations where spacing and the degree of selfpruning in different species would be important,
and stands are harvested whilst relatively young.
The increasing proportion of woody material in
litterfall results in a lower average [N].
The average [N] in litterfall from broad classes
of native forests and plantations are shown in
Table 13. High [N] is found in litterfall from tropical
rainforests, adding to evidence that many rainforest
Australian Greenhouse Office
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ä
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*ˆ˜ÕÃÊÀ>`ˆ>Ì>
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Figure 4. Proportion of total litterfall present as leaf material in native forests and plantations
(For data see Appendix 3).
3.2.2 Litter on the Forest Floor
In many Australian ecosystems wildfire or managed
fires can result in the removal of all or part of the
litter layer. As a consequence considerable amounts
of N can be lost by volatilisation, or by erosion of
ash or soil by wind and water (Hamilton et al. 1991;
Raison et al. 1993). Losses due to low-intensity fire
can be in the range 30–200 kg ha-1 depending on
In a mature undisturbed forest the amount of litter
that accumulates on the forest floor depends upon
the equilibrium between litterfall and the rate of litter
breakdown. The quantity of litter may be difficult
to determine due to spatial heterogeneity in the
distribution of different components and the degree
to which un-decomposed fragments are incorporated
into the upper mineral soil (Richards and Charley
1977). These, and differences in [N] between different
components, lead to inaccurate estimates of the
quantity of N stored in the litter layer and hence
C:N ratios.
forest productivity. Greater losses can occur due to
burning of the understorey vegetation. There is a
rapid re-accumulation of litter biomass during the
initial five years after burning. The N content of litter
would follow a similar pattern but recovery of lost
N by the ecosystem takes longer. Several studies
have shown that inter-fire periods of about 10 years
would be required to allow natural processes to
replace lost N. Frequent low intensity fires can result
in lowered mass and rate of N cycling through
litterfall with the consequence of declining tree and
ecosystem productivity (Raison et al. 1993).
species withdraw little N prior to leaf abscission.
Litterfall in natural eucalypt forests averages
0.65% N. Higher concentrations are found in
plantation grown eucalypts and pines while highest
concentrations are found in Acacia plantations.
National Carbon Accounting System Technical Report
15
Table 13. Nitrogen concentrations [N] (% ODW) in litterfall from various forest and plantation ecosystems.
Ecosystem
Average [N]
Minimum [N]
Maximum [N]
Average C:N
n
Tropical rainforest
1.20
0.92
1.92
43
9
Eucalypt, coastal NSW/Qld
0.59
0.30
0.94
100
7
Eucalypt, alpine NSW/Vic
0.47
0.34
0.64
112
6
Eucalypt, eastern Victoria
0.77
0.48
1.13
64
15
Eucalypt, Tasmania
0.49
0.39
0.60
105
5
Eucalypt, Western Australia
0.74
0.61
0.88
68
5
Eucalypt, woodland
0.67
0.47
0.89
78
4
Eucalypt plantation
0.81
0.40
1.32
67
13
P. radiata plantation
0.76
0.25
1.08
91
6
Acacia plantation
1.81
1.17
2.24
30
7
The average [N] in forest floor litter from native
eucalypt forests is about 0.62% N (Table 14,
Appendix 4). Variations about this value probably
depend on variations in sampling technique, species
composition, stand age, and site factors. Somewhat
higher (0.71% N) values are observed in eucalypt
plantations. These stands would generally be
younger and thus contain less woody litter than the
native forests studied, would be on sites selected for
good fertility, and may have received applications of
fertiliser. Higher [N] are usually found in litter from
forests and plantations dominated by non-eucalypt
species.
The quantity and nutrient content of eucalypt litter
can be affected by fertiliser applications (O’Connell
1994). In P. radiata the quantity of accumulated litter
(but not [N]) in second rotation stands can be higher
than in first rotation stands if fire is not used during
the inter-rotational period (Carey et al.1982).
Harms and Dalal (2003) have examined the C:N
ratios in leaf and woody litter, and coarse woody
debris from Queensland woodlands (Table 15).
Compared to eucalypt dominated woodlands,
Acacia dominated ones tend to have slightly lower
[C] in litter components and substantially higher
[N] in all components so that C:N ratios are
substantially lower.
16
3.2.3 Litter Decomposition
Decomposition is a general term used to describe
the interrelated processes by which organic matter is
broken down to CO2 and humus with a simultaneous
release of nutrients. These processes are essential for
recycling of C and nutrients. Decomposition often
begins with macrofauna physically breaking down
the particle-size of organic matter and predigesting
organic materials. Action by microorganisms results
in the progressive breakdown of organic matter.
This continuum of processes releases CO2 and
nutrients along the way.
The rate of decomposition is dependent on litter
quality and environmental conditions. Litter
quality factors important to decomposition and
mineralisation include: composition of organic
matter (C fractions such as extractables, cellulose,
hemicellulose, lignin), concentrations of
polyphenols (including tannins), and nutrient
content (e.g. C:N ratio, lignin:nitrogen ratio).
Litter with higher concentrations of nutrients and
lower concentrations of lignin and polyphenols will
decompose more rapidly and net mineralisation
begins earlier. Availability of nutrients from other soil
pools also enhances decomposition rates if nutrient
concentrations are low in litter.
Australian Greenhouse Office
Table 14. Average nitrogen concentration [N] (% ODW) and C:N ratios in litter from various native forest
and plantation ecosystems.
Ecosystem
Mean [N]
Minimum [N]
Maximum [N]
Mean C:N
n
73
10
Eucalypt – southern Qld
0.74
Eucalypt – coastal NSW/Qld
0.63
0.36
0.78
86
5
Eucalypt – inland NSW
0.42
0.30
0.63
132
3
Eucalypt – alpine NSW/Vic
0.65
0.52
0.94
79
10
Eucalypt – eastern Vic
0.60
0.35
1.01
94
12
Eucalypt – Tas
0.56
0.41
0.72
92
6
Eucalypt – southeast SA
0.68
77
10
Eucalypt – southwest WA
0.67
80
4
Acacia harpophylla – Qld
0.49
103
1
Araucaria rainforest – PNG
1.92
26
1
Montane rainforest – PNG
1.38
36
1
Nothofagus moorei – NSW
1.36
37
1
Cool temperate rainforest – Tas
0.72
69
1
Eucalypt plantation
0.71
84
6
Southern pines – Qld
0.66
82
10
P. radiata – southeast SA
0.84
63
10
P. radiata other locations
1.03
51
10
Acacia dealbata plantation
2.17
23
1
Soil temperature and moisture content are very
important factors affecting decomposition rates.
At favourable moisture conditions, increasing
temperature results in an exponential increase in
decomposition rates (Q10 of approx 2). At a constant
temperature, moisture content shows a parabolic
affect on decomposition rates with a maximum rate
at intermediate levels of moisture. High moisture
content can limit gas exchange leading to low
oxygen concentrations and potentially anaerobic
conditions. At low moisture content, a lack of
water limits microbial metabolism. In addition to
temperature and moisture conditions, soil acidity
extremes (pH <4 or >9) may severely reduce
decomposition rates.
The commonly used method to study litter
decomposition is to place senescent or litterfall
components in mesh bags in contact with the
0.46
0.85
0.27
0.95
0.63
1.43
litter layer and then to record changes in biomass
and nutrient content. Measurements over time on
components of the intact litter layer can also be
made. While biomass decreases with time, total
nutrient content can increase, decrease or fluctuate
according to the balance of gains and losses of
nutrients by the decaying litter components. As a
consequence of changes in mass and N content,
the [N] and C:N change markedly with time. Baker
and Attiwill (1985) found that total N in P. radiata
needle litter increased above initial quantities over
the initial two years of decay. [N] increased from
0.47% N to 0.76% N after one year and to 1.10%
N after two years. In two New Zealand studies,
concentrations reached about 1.45% N after four
years (Will et al. 1983) or 1.25% N after 5 years
(Will 1967). Foliar litter from E. obliqua (Baker
and Attiwill 1985) showed an increase in [N] from
0.49% N to 0.86% N after one year and to 1.10% N
National Carbon Accounting System Technical Report
17
Table 15. Concentrations of carbon [C] and nitrogen [N] (% ODW), and C:N ratios in leaf litter, woody litter
and CWD from various woodland ecosystems in Queensland (data from Harms and Dalal 2003).
Ecosystem
Analysis
Mean
Minimum
Maximum
No.
[C]
42.5
36.3
45.9
9
[N]
1.42
0.89
1.77
9
C:N
31
24
48
9
[C]
40.1
36.9
43.2
2
[N]
1.62
1.49
1.74
2
C:N
25
21
29
2
[C]
47.0
45.9
48.1
2
[N]
1.07
0.87
1.26
2
Leaf litter
Acacia systems
Casuarina systems
Callitris systems
Eucalyptus systems
C:N
46
36
55
2
[C]
46.6
42.2
49.4
18
[N]
0.83
0.47
1.10
18
C:N
59
43
95
18
[C]
41.2
33.3
44.4
9
[N]
0.94
0.68
1.30
9
C:N
46
30
61
9
[C]
42.1
-
-
1
[N]
0.98
-
-
1
C:N
43
-
-
1
[C]
43.1
41.7
44.4
2
[N]
0.52
0.51
0.53
2
Woody litter
Acacia systems
Casuarina systems
Callitris systems
Eucalyptus systems
C:N
83
81
84
2
[C]
44.6
33.3
50.0
18
[N]
0.39
0.33
0.44
18
C:N
115
78
151
18
[C]
48.6
46.4
51.0
10
[N]
0.236
0.171
0.332
10
C:N
213
154
291
10
[C]
49.1
47.5
50.6
2
[N]
0.217
0.208
0.226
2
C:N
226
224
228
2
[C]
47.5
46.9
48.1
2
[N]
0.217
0.214
0.220
2
Coarse woody debris
Acacia systems
Casuarina systems
Callitris systems
Eucalyptus systems
18
C:N
219
213
225
2
[C]
48.7
45.0
52.2
19
[N]
0.152
0.090
0.387
18
C:N
379
127
547
18
Australian Greenhouse Office
after two years. Application of fertilisers can alter the
rate of loss of organic matter and the gain or loss of
nutrients (Will et al. 1983; O’Connell 1994).
Models have been developed to describe the
pattern of C and N change during litter
decomposition. The forest floor contains litter in
various stages of decay with differing chemical
composition. The data summarised in Tables 14 and
15 integrate these differences at the site level, and
provide broad constraints on the models.
The option taken will depend upon the amount and
type of slash, the requirement of site preparation
for subsequent seedling establishment, and likely
effects on future site productivity. On podzolised
sands, soil C and N dynamics are very sensitive to
management operations that influence organic inputs,
decomposition or both. Weeds help to maintain
organic C and N reserves after clearfelling as does the
retention of above-ground logging residues. Long-term
reductions in soil C can occur after scalping of the site
during windrowing or the use of high intensity fires.
3.3
EFFECTS OF FOREST
OPERATIONS ON C:N RATIOS
Pruning, thinning and clear felling operations
disrupt the nutrient cycle by removing a significant
amount of nutrients from the site in harvested
products, and by returning crown and other
components of the biomass to the forest floor.
It is estimated that, depending on stand conditions, a
clearcut operation in a P. radiata forest would return
178 – 365 kg N ha-1 in logging residue, including
foliage, branches and stem wastage (Birk 1993).
Similar quantities are expected when felling native
eucalypt forests (Stewart and Flinn 1985; Hopmans
et al. 1993). The [N] in slash is much higher than
comparable components of litterfall. Nevertheless,
release of N by leaching or decomposition may be
slow. For example, only 16% of the N was released
from P. radiata needle slash during the first year
(Baker et al. 1989). If the slash is burnt a significant
quantity of contained N is lost to the atmosphere
(see Flinn et al. 1979; Raison et al. 1993a).
The main management options for slash after
harvesting include:
1.
broadcast burning;
2.
windrowing without burning;
3.
windrowing followed by burning;
4.
slash retention on the site with partial
incorporation into the soil (e.g. chopper
rolling); and
5.
slash retention with spot cultivation.
National Carbon Accounting System Technical Report
19
4. SOIL AND COARSE WOODY DEBRIS
Any review of the published C:N ratios for Australian
forest soils requires some comment on the assumptions
and methodological idiosyncrasies that can affect
the data and its interpretation. Methodological
considerations have been presented in Section 2.
4.1 PREVIOUS REVIEWS
There have been very few reviews of C:N ratios in
Australian soils, and none specifically for forest soils.
Hosking (1935) presented an early review (not cited).
Spain et al. (1983) produced a good overview of SOM
for Australian soils with some specific comments
about C:N ratios which are summarised below.
Spain concluded that:
•
•
Climate, especially rainfall and temperature,
was the most important factor affecting SOM
levels in soils. The effects on C and N are
not similar, and the relationship with climate
factors varied between temperate and tropical
environments.
Soil parent material P content, and its degree
of weathering, affected SOM content.
•
Vegetation influences both the amount and
quality (C:N ratio) of SOM.
•
Topography influences SOM via slope, aspect
and drainage. Impeded drainage can result in
formation of peat.
•
SOM generally decreases dramatically with
depth, although there are some soils where
organic matter accumulates in the B horizons
(Spodosols and some Sodosols).
Spain et al. (1983) went on to analyse a dataset
comprising C:N ratios for 3652 A1 horizons from
across Australia. They classified the variation in
SOM and C:N ratios to Great Soil Group (Stace et al.
1968). Two key figures from Spain et al. (1983) are
reproduced in Figure 5.
20
Some of the results include:
•
The C:N ratios were more normally distributed
within the soil types than were either of the
component (C or N) concentrations.
•
There was a considerable range in C:N ratios
within each of the soil groups.
•
Bias may have resulted due to the effect
of fixed ammonium (exchangeable and
extractable).
•
Nearly half of the great groups have a median
C:N ratio >15.
•
Three groups; podzols and humus podzols,
lateritic podzolics and yellow podzolics, have
median values >20.
•
Analysis by region showed that C and N
median values increased with latitude while
C:N values decreased with latitude with the
exception of WA and Tasmania.
•
The impact of vegetation is still poorly
understood.
The above analyses focussed on soils with a varying
history of agricultural use, and included very little
data for natural forests or plantations. The current
review addresses these gaps.
4.2 NATURE OF CURRENT REVIEW
This review has captured forest soil C:N ratio data.
Where available, supporting data for forest floor
(surface litter) and CWD were included. In many
cases, the publications only present concentrations
of soil organic C and total N. In other cases only C:N
summary data are presented.
All references are lodged in a Procite 5 database.
Another MS ACCESS database (CNsoils.mdb) was
constructed for recording C:N ratios and relevant
associated data. This latter database structure is
presented in Appendix 5. This review of literature
is not exhaustive; whilst some 70 publications have
been included, there are probably another 70+ that
could have useful data but which have not been
Australian Greenhouse Office
Podzols and humus podzols
Lateritic podzolic soils
Yellow podzolic soils
Earthy sands
Grey-brown podzolic soils
Siliceous sands
Red earths
Alpine humus soils
Non-calcic brown soils
Red podzolic soils
Yellow earths, grey earths
Soloths
Gleyed podzolic soils
Xanthozems
Black earths
Euchozerns
Solonetz, solodized-solonetz & solodic soils
Prairie soils
Krasnozems
Red-brown earths
Humic gleys
Terra rossa soils
Calcareous sands
Grey, brown and red clays
Rendzinas
Solonized brown soils
Sodic red-brown earths
Grey, brown and red clays (brigalow)
Desert loams
51
52
118
53
18
72
290
18
65
138
146
105
42
24
193
66
415
88
97
60
29
27
13
508
28
58
139
129
27
0
10
15
20
25
35
30
40
Carbon:Nitrogen ratio
86
Northern Territory
657
Northern Queensland
1211
Southern Queensland
224
New South Wales
384
Victoria
149
South Australia
162
Western Australia
142
Tasmania
10
14
18
22
26
30
Carbon:Nitrogen ratio
Figure 5. Surface soil C:N ratios categorised by the Australian Great Soil Group, and Australian States.
Medians, interquartile ranges and sample size are presented.
National Carbon Accounting System Technical Report
21
Table 16. C:N ratios in surface soil layers for various forest ecosystems. Calculated values are derived from
the database summaries derived from individual data.
Ecosystem
Published soil C:N ratios
Calculated soil C:N ratios
n
Mean
Min
Max
n
Mean
Min
Max
Sclerophyll
16
32.6
20.7
54.4
16
31.7
21.0
49.5
Dry sclerophyll
22
32.4
18.4
59.8
91
32.6
3.0
59.6
Sub-alpine forest
5
29.6
26.8
33.8
8
28.7
17.0
33.8
Wet sclerophyll
7
27.0
16.5
36.5
39
20.7
11.9
36.5
Monsoon forest
0
1
8.7
8.7
8.7
Sclero-rf ecotone
0
1
12.2
12.2
12.2
Native forest
Mixed forest
10
27.9
16.9
39.0
19
28.0
16.1
58.9
Rainforest
5
24.6
13.7
39.5
14
18.2
11.9
39.1
Warm temp rainforest
0
1
24.3
24.3
24.3
Swamp-forest
0
1
21.0
21.0
21.0
Woodland
0
2
33.6
24.8
42.4
Mixed eucalypt woodland
7
23.3
16.0
32.1
7
22.9
15.8
31.7
Mulga woodland
3
23.6
23.3
24.1
3
23.8
23.1
24.1
Open woodland
0
2
13.8
12.9
14.6
Box woodland
6
17.5
12.8
28.3
6
18.1
12.7
28.3
Ironbark woodland
8
22.4
15.3
30.7
8
21.1
15.3
29.5
Savanna
0
1
13.7
13.7
13.7
Mallee
0
6
50.9
30.3
86.9
Brigalow
3
11.6
11.4
11.9
3
11.5
11.3
11.7
Brigalow/Belah
9
16.7
13.8
27.4
9
16.4
13.9
27.7
Leptospermum
1
22.3
22.3
22.3
1
22.3
22.3
22.3
Acacia
1
23.6
23.6
23.6
1
23.7
23.7
23.7
Conifer plantation
44
29.5
14.3
67.0
74
31.2
12.7
121.7
Eucalypt plantation
12
17.6
11.0
28.5
24
19.4
12.7
35.2
0
3
13.3
12.1
14.7
Mangrove
0
1
6.2
6.2
6.2
Sedgeland-heathland*
0
2
559.0
38.0
1080.0
Heathland
0
16
24.9
10.5
60.0
Shrubland
0
5
24.2
15.0
40.5
Grassland
1
17.0
17.0
17.0
1
17.1
17.1
17.1
Pasture
3
12.2
11.4
13.1
6
13.7
11.4
19.7
No class
16
31.6
14.5
54.0
16
31.4
14.4
54.5
Woodlands
Plantations
Hoop pine plantation
Other
* Surface layers are O horizons (peat) from Tasmania.
22
Australian Greenhouse Office
Table 17. C:N ratios for surface litter layers in various ecosystems.
Ecosystem
Published C:N ratios
n
Mean
Min
Calculated C:N ratios
Max
n
Mean
Min
Max
11
88.8
58.4
148.0
6
71.9
56.8
90.0
Native forest
Dry sclerophyll
0
Sub-alpine forest
5
Wet sclerophyll
0
6
98.7
60.9
127.4
Mixed eucalypt woodland
0
7
61.6
36.8
94.0
Mulga woodland
0
3
27.6
25.6
29.1
Box woodland
0
6
56.5
43.7
95.5
Ironbark woodland
0
8
64.7
51.2
79.0
Brigalow/Belah
0
9
33.4
21.4
49.7
30
57.1
31.6
90.9
1
184.8
184.8
184.8
68.5
52.2
77.9
Woodlands
Plantations
Conifer plantation
5
Eucalypt plantation
0
46.2
43.6
included due to lack of access within the time
available for the review. References examined were
dominated by publications from the last 20 years
because of primary use of digital library search
engines.
The following sections discuss summary information
from the CN soils database.
4.3
49.7
4.3.2 Native Forests
There is a great deal of variation in surface soil
C:N ratios (Table 16) within the various native forest
types. However, there are some general trends in
mean C:N ratios:
•
Eucalypt forests (dry to wet sclerophyll and
alpine forests) have generally high values
(21-33).
•
Rainforests (except for warm temperate) have
low values (~18).
•
Non eucalypt woodlands (Acacia,
Leptospermum, etc) tend to be lower than
eucalypt woodlands (12-28 vs 18-51) probably
due to the N-fixing effect of acacias.
•
Tropical woodlands, savanna and monsoon
forest (deciduous) values are low (9-14).
•
There are certain native vegetation types
where SOM accumulates and these have very
high ratios due to presence of peat (P) or O
horizons.
EFFECTS OF FOREST VEGETATION
4.3.1 Summary of Soil and Litter Differences
Table 16 lists the surface soil C:N ratios classified
by forest ecosystem. The ecosystem classes are
somewhat arbitrary based on terms used in the
literature, and/or other well-accepted terms such as
dry/wet sclerophyll. The main aim was to separate
the main eucalypt forest types from the rainforests.
Tables 17 and 18 provide similar ecosystem
summaries for surface litter and CWD. These tables
complement Tables 14 and 15 presented earlier.
National Carbon Accounting System Technical Report
23
Surface litter C:N ratios (Tables 14, 15 and 17) in
eucalypt forests vary from about 70 to 130. For
woodlands (Queensland paired plot study, Harms and
Dalal, 2003) values are less, ranging from about 30-65.
CWD C:N ratio data are vary rare (Tables 15 and
18). The data presented here comes from Harms
and Dalal (2003) for Queensland woodlands, with
mean values ranging from 175-352, with the lower
values for the non-eucalypt woodlands (mulga and
brigalow/belah).
Table 18. C:N ratios for coarse woody debris in
various ecosystems.
Ecosystem
Biomass
Calculated soil C:N ratios
t/ha
n
Mean
Min
Max
130.0
1
802.5
802.5
802.5
Mixed euc. woodland
3.1
7
339.7
213.1
541.9
Mulga woodland
2.4
3
175.0
153.5
190.7
Box woodland
4.1
6
353.8
127.5
546.7
Ironbark woodland
1.4
8
351.6
56.4
496.0
14.4
9
228.9
174.5
290.8
Native forests
Dry sclerophyll
Woodlands
Brigalow/Belah
4.3.3 Plantations
Table 16 has 3 classes of plantations; conifer, eucalypt
and Hoop pine. Conifer plantations (P. radiata,
P. elliottii, P. caribaea and Pseudotsuga menziesii) are the
most variable and have the highest C:N ratio mean
(31) in surface soils. Eucalypt plantations values are
lower (19) but this also reflects the effect of plantings
on ex (and often improved)-pasture soils. The Hoop
pine plantations have the lowest values (13) but
there are only few data for these forests.
Surface litter C:N ratios (Tables 14 and 17) for conifer
plantations are lower than those for native forests,
and similar to those in woodlands. There is very
limited data for eucalypt plantations. There were no
CWD C:N ratios available for any plantations.
24
4.3.4 Paired Plots: Conifer Plantations versus
Native Eucalypt Forests or Pastures
There were a number of studies in the 1980-90s
that investigated the effects on soils of converting
mainly native eucalypt forest to conifer plantation.
These paired plot studies were distributed across
SE Australia (Turner and Kelly 1977, Hopmans
et al. 1980, Turner and Kelly 1985, Turner and
Lambert 1988). Recent interest in soil C as an index
of sustainable forest management (CSIRO FFP and
QFRI 2003) or for soil C accounting (AGO pairedplot studies) has created new data on the effects
of forestation, on conversion of native forest to
plantation, on SOM and C:N ratios.
Tables 19 and 20 summarise soil and litter data for
a number of these paired plot studies including
comparison of conifer plantations with either
adjacent native forest or pasture.
In most cases, conifer plantation soil in paired plot
studies had the highest C:N ratios, especially in the
surface soil layers. However, for litter layers the
reverse is observed. Conifer plantation litter
C:N (42-91) was lower than for native forest (57-108).
The absolute C:N ratios for either native forest or
plantation however, vary markedly from location
to location.
The results from recent detailed analyses by CSIRO
FFP and QFRI (FWPRDC, 2004) challenge the
conclusions from previous studies (Table 21). The
recent work measured organic C both in fine earth
and coarse soil fractions, as well as that in the forest
floor. They found that:
•
‘There is a significant difference in the size
fractions of organic matter between native
forest and pine. The >2 mm fraction accounted
for a larger proportion of site organic matter,
C, and N under pine (32–40%) than native
forest (17–29%), so restricting analysis to the
<2 mm fraction would lead to the incorrect
conclusion that these properties were lower
under pine’.
Australian Greenhouse Office
Table 19. Soil C:N ratios from paired plot comparison of conifer plantations with adjacent native forest.
No
4
5
Reference
Location
Layer
Native forest
Plantation
Turner and Kelly (1977)
(Douglas fir)
Bago SF
NSW
1
2
3
29.4
25.2
23.3
40.1
34.4
20.3
Bago SF
NSW
1
2
3
4
5
6
7
41.6
19.8
33.8
25.3
17.2
15.9
7.6
24.8
19.7
20.3
17.0
19.9
48.3
12.8
Lidsdale SF
NSW
1
2
20.5
14.3
29.2
16.6
Nundle SF
1
2
21.7
28.1
20.7
24.3
Wee Jasper
NSW
1
2
25.4
27.1
35.3
29.7
Billapaloola
NSW
1
2
29.1
28.0
37.5
44.1
Rennick, Vic
1
30.8
31.2
Turner and Lambert (1988)
(Pinus radiata)
NSW
6
52
•
Turner and Kelly (1985)
(Pinus radiata)
Hopmans et al. (1980)
(Pinus radiata)
‘The forest floor under pine contained a greater
quantity of organic matter and nutrients than
under native forest, and these represented
a greater proportion of the organic matter
and nutrients contained in the forest floor +
mineral soil. Restricting analysis to mineral
soil would lead to incorrect conclusions
about the effect of land management on
these properties.’
•
Adjacent pasture sites all had much lower
C:N ratios (13-20) reflecting the influence
of pasture improvement practices (legumes
and fertilisation).
Table 20. Litter C:N ratios for paired plot comparison of conifer plantations with adjacent native forest
No
Reference
Component
Native Forest
Plantation
4
Turner and Kelly (1977)
Bago SF
Total litter
67.6
43.9
6
Turner and Kelly (1985)
Wee Jasper
Stick
Bark
Leaf/needle
Fine
Understorey
Total litter
258.5
165.7
90.2
90.3
78.3
108.0
212.2
Billapaloola
Total litter
105.5
80.5
Bago SF
Total litter
Total litter
Total litter
Total litter
Total litter
74.1
73.5
68.7
68.3
56.8
49.6
48.0
43.4
42.1
48.2
69
En Chee (1999)
National Carbon Accounting System Technical Report
11.8
83.9
90.9
25
Table 21. CSIRO FFP and QFRI (FWPRDC, 2004) forest floor and whole soil C:N ratios.
Location
Soil Depth (m)
Native Forest
Plantation
0 – 0.075
0.075 - 0.15
0.15 – 0.30
E. baxteri
63.2
32.1
41.9
45.3
P. radiata
76.8
39.3
46.7
49.4
Green Triangle
Litter
Soil
Litter
Soil
SE Queensland
E. racemosa
Litter
Soil
Litter
Soil
0 – 0.075
0.075 - 0.15
0.15 – 0.30
73.3
25.5
24.6
26.4
P. elliottii/
P. caribaea
82.2
27.8
27.1
25.5
0 – 0.075
0.075 - 0.15
0.15 – 0.30
69.3
20.6
20.8
22.5
70.7
23.4
23.5
23.5
Even though the inclusion of the >2 mm fraction has
an important impact on the absolute amounts of soil
C and N, this coarse component (mostly charcoal
and woody debris) has higher C:N ratios than its
fine earth component so its inclusion in a whole soil
analysis tends to increase the C:N ratio. C:N ratios
for both the Green Triangle and SE Queensland
sites are highest under plantation, lower under
native forest, and lowest under pasture (Table 2).
Litter C:N ratios are about double the soil values
(63-82) however, in contrast to Table 20, litter under
plantation had higher C:N ratios than litter under
native forests.
Turner and Lambert (1988) reviewed a number of
studies examining the effect of converting native
forest to pine plantation on soils and concluded:
‘The results of the study are generally consistent with
similar studies, showing a decline in soil nitrogen
and organic matter content after planting with
P. radiata. Soils at the lower end of the fertility range
may be subject to accelerated nutrient depletion
under pine.’ This would explain the higher C:N
ratios under pine on low fertility sites compared to
26
52.0
33.0
41.2
48.2
0 – 0.075
0.075 - 0.15
0.15 – 0.30
Pasture
12.9
17.0
19.1
51.0
19.7
19.7
19.9
adjacent eucalypt forest, and why both the C:N ratios
and the land use differences decrease as site fertility
increases. However, there are still only limited
studies of the effects of conversion on soil C and N
stocks and the mechanisms underpinning changes
are not well understood. Broadscale generalisations
are thus risky.
4.3.5 Paired Plots: Eucalypt Plantations versus
Native Eucalypt Forests or Pastures
There are limited paired plot studies for eucalypt
plantations. Aggangan et al. (1998) present detailed
soil data for E. globulus plantations in SW WA
(Table 22). Establishing E. globulus plantations
on either ex-native forest or ex-pasture sites did
not produce any major change in C:N ratios. On
ex-native forests C:N ratios were high and similar
to the Jarrah native forest (25-38). On ex-pasture
sites the C:N ratios were much lower and possibly
slightly increased compared with adjacent pasture
(14-21).
Australian Greenhouse Office
Table 22. Soil C:N ratios for paired plot comparison
of eucalypt plantations with either adjacent native
forest or pasture (Aggangan et al. 1998).
Location
Layer
Native forest
Plantation
Augusta,
WA
1
2
3
4
35.9
28.4
25.5
37.3
35.2
35.8
36.0
34.4
1
2
3
4
Pasture
15.6
18.0
20.6
16.2
14.1
13.7
16.1
15.9
Wang et al. (1996) surveyed 27, first rotation
E. globulus plantation sites in Tasmania that were
either established on ex-pine or ex-native forest sites.
These authors found that the C:N ratio in the ex-pine
group (23.6) was higher than ratios in other groups
(13.1-15.6). The C:N ratio was negatively correlated
with total N and anaerobically mineralisable N.
The results in Table 23 are difficult to interpret.
Surface soil C:N ratio does seem to increase initially
going south from Qld to NSW, ACT and to Vic
(at least for dry sclerophyll forest where the data are
large) but then values decrease in Tas. This trend in
soil C:N ratios by State is different to that found by
Spain et al. (1983) (see Figure 5). They showed values
decreasing from north to south (except for Tasmania
which increased). The trend is less obvious in the
wet sclerophyll forests, so the dry sclerophyll trend
may reflect other environmental factors (rainfall,
evaporation, temperature, soil fertility), and not just
latitudinal change.
A true test of this hypothesis would be facilitated
if there were geographical-positions (latitude,
longitudes) for the majority of the sites in the
database. Unfortunately the literature is inconsistent
in recording this, although it could be pursued
further with the authors.
4.4
4.3.6 ‘Latitude’ effects – State Summaries
for Eucalypt Forests
4.4.1 Climate
Spain et al. (1983) claimed that there was a
‘latitudinal’ effect on SOM concentration beyond that
explained by rainfall or temperature (see Figure 5).
An attempt to discern such an effect for surface soil
C:N ratios is presented in Table 23, where values for
native eucalypt forest ecosystems are classified by
the State where the soil data were collected.
Table 23. Variation in C:N ratios of surface soils for
eucalypt forests grouped by State.
State Total Sclerophyll
Qld
21.6
NSW 29.2
Dry SubWet Mixed
sclerophyll alpine sclerophyll forest
21.6
31.7
29.1
ACT
32.0
32.5
WA
38.2
41.2
SA
32.1
32.1
Vic
31.7
40.8
Tas
25.4
27.4
23.2
30.4
35.1
21.3
17.0
15.6
20.3
EFFECTS OF ENVIRONMENTAL
FACTORS
28.0
Climatic factors have been flagged in the past
as critical in determining soil C density at a global
scale (Post et al. 1982) and at the Australian scale
(Spain et al. 1983). At a regional scale (50,000 ha
of Bago-Maragle State Forest), Ryan et al. (2000)
produced spatial soil models predicting soil C
density over a sub-alpine forest area. In these models,
a climatic attribute (Prescott Index; a PrecipitationEvaporation ratio) explained most variation in forest
soil C density to 1 m. Other authors have stressed the
importance of precipitation and temperature (Jenny
1980, Post et al. 1982, Spain et al. 1983). However,
there is not a clear logic as to how these factors
would affect C:N ratios.
The effect of climatic factors on soil C:N ratios at
an Australian scale could be best tested by utilising
the ESOCLIM GIS surfaces and all available soil
C:N data that had reasonable geographical-positions.
This could be achieved with further data mining and
interaction with the data owners.
National Carbon Accounting System Technical Report
27
Rainfall
The main problem in testing the effect of
precipitation on soil C:N ratios in native forests is
that the forests have changed species composition
and structure with increasing rainfall. So the data in
Table 16 also reflect a rainfall gradient; rainforests
receive more rainfall than dry sclerophyll forests
and their soil C:N ratios are lower. But is that due to
the rainfall or to the chemistry and quantity of the
different forest litter?
Gillman (1976) studied 24 red basaltic soils under
eucalypt forest or rainforest in Far North Queensland.
Soil C was positively correlated with rainfall
in eucalypt forests, but negatively correlated in
rainforests. Rainforest surface soil C:N ratio
varied from 13.8-14.3, while eucalypt forest soil
C:N decreased from 18.6 to 12.3. Sites with the same
rainfall but different vegetation showed a greater C:N
in eucalypt soils (rainforest 15 versus eucalypt 18-20).
Temperature
No studies have addressed the effect of temperature
on soil C:N ratios directly, however at low
temperatures where SOM accumulates forming thick
O horizons, and sometimes peat, C:N ratios can
increase dramatically. This is seen in the figure
of Spain et al. (1983) (Figure 5) comparing
C:N data by Great Soil Group. The highest C:N
values are for Alpine Humus soils (coldest) and the
lowest for Desert Loams (hottest).
Spain (1990) showed that [C] and [N] of rainforest
soils with basalt, granitic and acid volcanic parent
materials had an inverse relationship with mean
annual temperature but the author did not test
whether the same relationship existed for the
C:N ratios.
Evaporation
Bale and Charley (1994) produced an interesting
study in native forests of the New England
Tablelands that tested the effect of net radiation/
evaporation on forest soil properties. They measured
a series of plots located along ridgelines with either
28
a NW-SE or NE-SW orientation. Unfortunately all
their data are presented as Figures, but there was no
relationship between aspect and soil C:N ratio.
4.4.2 Parent Material
The effect of parent material on forest soil properties
has been investigated extensively. Kelly and Turner
(1978) studied soils with different parent materials in
the Eden region, and found a trend in C:N ratio from
28 to 46 that reflected parent materials indicative of
declining soil fertility.
Laffan et al. (1998) studied soils on sandstone, granite
and dolerite under dry or wet forests in Tasmania.
C:N ratios range from 9-50 (dry forest) to 31-33 (wet
forest) but there were no obvious parent material
effects.
Spain (1990) studied surface soils from 72 rainforest
sites from NE Qld on different parent materials.
Unfortunately only summary data are reported
but a large database is available. The C:N ratio did
not differ significantly between parent material
groupings. However, the C:N ratio increased
significantly with soil C content in all parent material
groupings except those of metamorphic rock origin.
4.4.3 Terrain
Most forest soil data come from forest plots or soil
pits. There are few studies that have looked at how
either soil C, N or C:N vary across the landscape
in single parent materials. Thus there is little
information on the effect of terrain.
Spain (1990) concluded after a study of 72 rainforest
sites from NE Qld, that topography plays a role,
particularly through its control on drainage, as
shown by the high organic matter content of some
of the soils on poorly drained sites. Similarly, the
shallow soils low in organic matter, formed on
granitic parent materials at ridge-top sites, reflect
their location in the landscape.
An unpublished study that modelled surface soil C:
N ratios across the Bago-Maragle forest found that
unlike soil carbon density, C:N ratios were poorly
Australian Greenhouse Office
predicted by climatic attributes. The best predictors
were terrain attributes, specifically ‘Aggradation
Index’ (AI) (also called Compound Topographic
Index, CTI). Basically this means that soils on upper
slopes (low AI) had lower C:N ratios than soils on
lower slopes and depressions (high AI). The tree
regression is shown in Figure 6 but it explains only a
small fraction of the variation in C:N across 50,000 ha
of sub-alpine forests.
4.5
PEDOGENIC FACTORS
between soil C and ‘free’ Fe-oxides (dithioniteextractable) but there was no examination as to
the impact of this on C:N ratios.
Some soils with the most extreme C:N ratios (both
high and low or non-existent) are Podosols that have
experienced extreme leaching of soluble organics
and Fe (podzolisation) and re-deposition in the B
horizons. Both the A horizon and B2h horizons can
have very high C:N ratios of >100 (Grant et al. 1995).
4.5.2 Morphology (soil type)
4.5.1 Time (weathering, leaching)
Very young soils have little organic matter, so C:N
ratios can be highly variable.
Increased weathering can increased the sesquioxides
(Fe and Al) in the soil and both these elements have
interaction with soil C. Relationships between soil C,
C:N ratios and exchangeable Al have already been
discussed. Gillman (1976) and Spain (1990) showed
that for basaltic soils there is a negative relationship
Highly weathered/leached Podosols can have thick
accumulation of organic matter in O or A horizons.
C:N ratios of these layers can be very high (see
sedgeland/heathland in Table 16 with a mean C:N
of 560). Another distinctive Podosol at the Cabbage
Tree site near Orbost has been measured by a
number of authors with a C:N of 50 (Romanya
et al. 1994, Connell et al. 1995, Serrasolsas and
Khanna 1995).
27.3
AI < 5.7
33.1
26.4
MAT < 8.9
44.2
RELIEF < 25
28.9
19.1
26.9
Figure 6. A pruned tree regression for predicting surface soil C:N ratios across Bago-Maragle State
Forests. Variables are AI, mean annual temperature (MAT), RELIEF (range of elevation within a 300 m radius
area). Values within ellipses are the predicted C:N means for that branch of the tree regression.
National Carbon Accounting System Technical Report
29
4.5.3 Exchangeable Al
Exchangeable Al has been flagged by a number of
authors as an important factor in SOM dynamics
and decomposition. Turner and Kelly (1981) and
Kelly et al. (1983) found high soil exchangeable Al
under Coachwood (Ceratopetalum apetalum) warm
temperate rainforest because Coachwood is an Al
accumulator. These rainforest soils also had higher
C:N ratios than other sub-tropical rainforest soils.
Khanna et al. (1986) investigated forest soil exchange
properties under sub-alpine eucalypt forests in the
Cotter Catchment ACT, and concluded that the high
C:N ratios (range 20-39) reflected the stable nature of
organic matter, and was probably due to presence of
high amounts of exchangeable Al.
The importance of exchangeable Al in affecting soil
C:N ratios still requires definitive testing. An
expanded soils database including other chemical
related data where available could facilitate this
process.
4.5.4 Size Fraction
The importance of the >2 mm size fraction in
accounting for forest soil C and N has been stressed
in the past by Smethurst and Nambiar (1995) and
subsequent workers in the Green Triangle region of
South Australia. Results from Bauhus et al. (2002a
and 2000b), CSIRO FFP and QFRI (FWPRDC 2004),
Harms and Dalal (2003), Murphy et al. (2003), and
Griffin et al. (2003) have endorsed the procedures
specified by McKenzie et al. (2000) for determining
C (and N) on the whole soil sample, including the
coarse fragment fraction, plus the surface litter
and CWD. Griffin et al. (2003) found that there
were significant [C] and [N] in the mineral coarse
fragments. Bauhus et al. (2002a) concluded:
‘The fractions greater than 2 mm, which are
traditionally discarded for soil chemical analysis
because they contribute little to the soil volume,
can form a significant fraction of total C. Fire
disturbances, which produce substantial amounts
of charcoal of particle sizes >2 mm, are an inherent
30
part of the ecological dynamics in native eucalypt
forests. Fragmented rocks and mineral aggregates
(>2 mm) contributed between 1.3% and 11.4% to soil
C in this study (Table 2). This fraction as well as the
plant residues incorporated in soil should therefore
be included in determinations of total C in soil
profiles’.
4.6
FOREST MANAGEMENT
(DISTURBANCE) EFFECTS
4.6.1 Site Establishment
Attiwill et al. (1985) studied the effects of mounding
on podzol soil properties in a P. radiata plantation
at Glencoe, East Gippsland, Victoria. A series
of mounds produced by a ‘Rome’ plough were
excavated, normal to the mound, and soils sampled
and analysed. The mean soil C:N ratio across
mounded and unmounded sites was 20.6 and
that of the mounded areas was 18.6. This was not
considered a significant change.
4.6.2 Fertilisation
Turner and Lambert (1986b) investigated the fate
of P fertiliser applied to a P. radiata plantation in
Belanglo State Forest. They found litter C:N ratios
increased from 61 to 90 after addition of 75 kg P per
ha. Soil C:N ratios seemed to increase with added P.
CSIRO FFP and QFRI (FWPRDC 2004) resampled a
number of established fertiliser trials on low fertility
sites in NSW. All the soils had quartzose sandstone
as their parent material. The main fertiliser treatment
had been P (although an NP factorial occurred at
one site) and this treatment had produced significant
growth responses. The authors state:
‘For Penrose NP and Woodburn sites, addition
of P caused large increases in C:N ratio of the
non-charcoal fraction of organic matter ... The
increase was particularly large for Woodburn
(40%) and clearly has implications for cycling and
mineralisation of N in organic matter. For example,
it might be expected that such large increased C:N
ratios would decrease net mineralisation of N.’
Australian Greenhouse Office
In contrast to the P fertiliser effect on low fertility
soils in NSW, Neilsen et al. (1992) reported on a
P. radiata N fertiliser trial in Tasmania and found
that:
‘There was no increase in organic carbon in the
surface soil, with the result that the C/N ratio was
reduced from a very high 28 to 17.’
Judd et al. (1996) and Hooda and Weston (1999) have
established and reported on a series of standard NP
establishment fertiliser trials in E. globulus plantations
at three sites in east Gippsland. They found surface
soil C:N ratios decreased by site, and that this was
inversely proportional to plantation productivity and
litter P concentrations. The Glencoe site is a deep
infertile sand that was also studied by Attiwill et al.
(1985). No treatment effects on soil C:N ratio could be
determined from the data in the papers.
4.6.3 Weed Control
Smethurst and Nambiar (1995) reported on a
P. radiata weed control experiment in the Green
Triangle. These authors analysed the whole soil and
found that weed free areas had lower C:N ratios.
‘Between 0 and 42 months, the C:N ratio calculated
for the unsieved soil decreased from 38.4 to 31.3 and
was associated with decreases in both the less than
2 mm and greater than 2 mm fractions’
These authors however found that this decrease in
C:N did not alter a 55% decrease in N mineralisation
in the weed-free treatments.
4.6.4 Harvesting/thinning
Gillman et al. (1985) reported on the effects of
logging on rainforest soils at a series of intervals
post harvest (+1, +2, and +4 yrs). Before logging the
surface soil mean C:N was 13.9. There was no effect
of logging or time since logging on soil C:N, with
values ranging between 11.4 and 16.2.
In Tasmania, Ellis et al. (1982) studied two native
forest stands that were logged and burned. Soil
surface C:N ratios varied from 27-38. No effects of
logging or burning were found.
‘Mean concentration of both C and N for burned
coupes were lower than those for the uncut control,
although the C:N ratios did not differ. In dry
sclerophyll forest, soils from all three coupes were
very similar in content of organic C and total N.’
A similar post logging and burning study in
Tasmanian mixed forests by Ellis and Graley (1983)
found that soil C:N ratios ranged from 50-27 and
there was a slight decrease in 0-0.02 m soil C:N after
logging but fire produced no further change.
Still in Tasmania, Pennington et al. (2001) investigated
the effects of harvesting native forest at the Warra
LTR site. They found soil total C and N decreased
significantly after logging and burning in the surface
0-0.05 m but the C:N ratio decreased only from 26 to
25 (not statistically significant).
Carlyle et al. (1998) investigated radiata pine postharvest soils at 9 sites across SA, Vic, and Tas and
found litter C:N ratios ranged from 32-51, and soil
C:N ratios ranged from 13-60 with two of the highest
C:N sites having been windrowed.
In general, forest harvesting does not seem to
produce much change in soil C:N ratios, even
though soil [C] and [N] are altered.
4.6.5 Fire
There have been a number of investigations on
the effect of forest fire on soil C and N.
Grove et al. (1986) working in Jarrah forest near
Dwellingup investigated the effect of fire on four
forest soils types. Surface soil C:N ratios before fire
varied from 33-53 and mean C:N decreased from
42 to 38 after the fire (no test on the significance of
this decrease was made).
Bauhus et al. (1993) developed experiments to test
the effect of fire on C and N processes in forest soils.
Soils came from the Cabbage Tree SSP site in East
Gippsland with unburnt and ashbed areas sampled.
Soil C:N ratios varied from 30-41 while surface soil
C:N decreased slightly in ash-bed samples.
National Carbon Accounting System Technical Report
31
Table 24. Custodians of available forest soil, litter and CWD chemical data.
State
Qld
NSW
ACT
Vic
Tas
SA
WA
Custodian
Organisation
John Simpson
QFRI
Mike Grundy
DNRM
Xu Zhihong
QDPI
Alistair Spain
CSIRO LW
Kelvin Montagu/Annette Cowie
SFNSW
Brian Murphy
DLWC
John Raison (coordinator for FFP)
CSIRO FFP
Roger Gifford
CSIRO PI
Brendan Mackey
ANU
Juergen Bauhus
ANU (now Univ.Freiburg)
Peter Hopmans
DSE
Chris Weston
UMelb
Mark Imhoff
DPI
Philip Smethurst
CSIRO FFP
Phillip Pennington
CSIRO FFP
Bill Neilsen
Forestry TAS
Mike Laffan
Forestry TAS
Clive Carlyle
CSIRO FFP
Don Mcquire
Forestry SA
Tim Grove
CSIRO FFP
Richard Harper
FPC
Ted Griffin
AgWA
Pauline Grierson
UWA
NT
Further work at this site by Romanya et al. (1994)
confirmed little effect of fire on soil C:N ratio.
The general response of these eucalypt forest soils
to fire can be significant in terms of losses of C and
N, however there is little evidence that C:N ratios
change significantly, even in ashbeds.
SOURCES OF UNPUBLISHED
FOREST SOIL CHEMICAL DATA
This review has only mined data from a fraction
of the papers that have forest soil and litter C and
N concentrations. Some of the papers only present
summary data (e.g. Connell et al. 1995) although the
full data set exists (M. Connell, CSIRO pers comm.).
There are also a large amount of unpublished data
available from various custodians. These custodians
and their organisations are listed above (Table 24).
Any future use of these data will be facilitated by
collection of some key ancillary data (see Appendix
5 for database field list) of which the following are
very important:
4.7
32
1.
Geographical-position of soil/litter/CWD
collection site in latitude, longitude and
datum (AGD66, WGS84 or GDA94) or AMG/
MGA zone, eastings and northings. This
geo-position would enable environmental
modelling at continental scales.
Australian Greenhouse Office
2.
Soil specimen size fraction: whether the
specimen analysed was whole soil or some
fraction (eg. <2mm fine earth).
3.
Analytical method for C and N determination.
4.
Associated chemistry; total P, exchangeable Al,
CEC and pH.
4.8
•
•
SUMMARY
Data on C:N ratios in forest soils, surface
litter and CWD have been collated from a
fraction of the available Australian published
literature. There is still a lot more information
that could be captured (at least another 100
papers, although some are difficult to obtain,
plus theses and other grey literature).
Available soil C:N ratio data have some
major limitations due to differences in the
size fraction analysed, chemical analytical
methodology, and errors due to calculation
of C:N ratios from mean [C] and [N].
•
The past tendency to only analyse the fine
earth fraction means that most of the reported
C:N ratios underestimate the actual whole soil
C:N ratio.
•
Relative ranking of C:N ratios are CWD
(175-800) > surface litter (28-185) > soil (6-51).
•
Soil C:N ratios in Australian forest soils are
highly variable but some general points can
be made.
•
•
Conifer plantation soils have C:N values
similar to dry sclerophyll forest (31) but
when compared to adjacent native forests,
the plantations usually have a higher soil
C:N. This difference decreases as the site
fertility increases.
•
Eucalypt plantation C:N ratios tend to be less
that those of conifer plantations, but this may
only reflect the fact that the majority of these
former plantations have been established on
ex-agricultural soils.
•
Fertilisation with P can increase soil and
litter C:N ratios in pine plantation sites of
low fertility. However, fertilisation with NP
fertiliser has had either no to mixed effects
on soil C:N ratios.
•
Harvesting plantations or native forests has
produced either no impact or a minor decrease
in soil C:N. Similarly, fire seems not to affect
C:N ratios.
•
Certain extreme environmental conditions
will produce extreme C:N ratios. Conditions
leading to very high values include saturated
anaerobic conditions, cold temperatures and,
strongly leaching conditions; while high
temperatures and low rainfall can produce
very low C:N ratios.
•
Further collection of C:N data, together
with ancillary data on geo-position, soil P,
exchangeable Al, pH and the size fraction
of the soil would allow exploration of the
effects of climate and other environmental/
pedogenic factors on forest soil C:N. Collating
good geo-position data for existing C:N data
would allow the use of continental-scale
spatial modelling to test the importance of
rainfall, temperature and/or evaporation on
C:N ratios.
Major forest ecosystems have a range of
surface soil C:N ratios that roughly follow
a fertility gradient (although it is difficult
to disassociate precipitation or temperature
effects). Rainforests have the lowest C:N ratios
(<20) while dry sclerophyll eucalypt forest
have values of about 30. Woodlands and
especially Acacia (N-fixing) woodlands have
values from 12-25 although mallee systems
can have high values (51).
National Carbon Accounting System Technical Report
33
4.9
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New South Wales. Forest Ecology and Management 6,
p155-168.
Turner J. and Lambert M.J. (1986a). Effects of forest
harvesting nutrient removals on soil nutrient
reserves. Oecologia 70, p140-148.
Turner J. and Lambert M.J. (1986b). Fate of applied
nutrients in a long-term superphosphate trial in
Pinus radiata. Plant and Soil 93, p373-382.
Turner J. and Lambert M.J. (1988). Soil properties as
affected by Pinus radiata plantations. New Zealand
Journal of Forestry Science 18, p77-91.
Turton S.M. and Sexton G.J. (1996). Environmental
gradients across four rainforest-open forest
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Journal of Ecology 21, p245-254.
Turvey N.D., Rudra A.B. and Turner J. (1986).
Characteristics of soil and productivity of Pinus
radiata (D.Don) in New South Wales. I. Relative
importance of soil physical and chemical parameters.
Australian Journal of Soil Research 24, p95-102.
Turvey N.D. and Smethurst P.J. (1994). Nutrient
concentrations in foliage, litter and soil in relation to
wood production of 7- to 15-year-old Pinus radiata in
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p157-164.
Vitousek P.M. (1984). Litterfall, nutrient cycling, and
nutrient limitation in tropical forests. Ecology 65,
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National Carbon Accounting System Technical Report
45
Wang X.J., Smethurst P. J. and Herbert A.M. (1996a).
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Nitrogen mineralisation indices in ferrosols under
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Nitrogen fluxes in surface soils of 1-2-year-old
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Journal of Ecology 21, p309-315.
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52, p44-52.
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Wedderburn M.E. and Carter J. (1999). Litter
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in a macrotidal embayment, Darwin harbour, NT,
Australia. Estuarine, Coastal and Shelf Science 26,
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(1992). Effect of annual weeds on water and
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plantation. Forest Ecology and Management 48,
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nitrogen concentration of fine roots in forest
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Forest Science 37, p374-382.
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Predicting nitrogen and chlorophyll content and
concentrations from reflectance spectra (400-2500
nm) at leaf and canopy scales. Remote Sensing of the
Environment 53, p199-211.
Wendler R., Carvalho P.O., Pereira J.S. and Millard
P. (1995). Role of nitrogen remobilization from old
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and structure of a subtropical eucalypt forest. North
Stradbroke Island. Australian Journal Botany 25,
p171-191.
46
Australian Greenhouse Office
APPENDICES
APPENDIX 1
Study No.
MEASURED [C] AND [N] AND C:N RATIOS IN VARIOUS COMPONENTS OF FOREST SPECIES
Species
Component
C mg/g
N mg/g
C:N
1
Casuarina equisetifolia
Leaves
438
18.1
24
1
C. equisetifolia
Litter (A0)
436
12.5
35
1
C. equisetifolia
Litterfall
454
12.5
36
1
C. equisetifolia
Roots < 0.2 cm diam.
408
7.7
53
1
C. equisetifolia
Roots > 1.0 cm diam.
455
3.7
123
1
C. equisetifolia
Roots 0.2-1.0 cm diam.
450
7.2
63
1
C. equisetifolia
Stem branch < 2.5 cm
458
6.1
75
1
C. equisetifolia
Stem branch > 2.5 cm
461
3.6
128
1
C. equisetifolia
Total above-ground biomass
458
5.6
82
1
Eucalyptus robusta
Leaves
444
15.1
29
1
E. robusta
Litter (A0)
427
7.0
61
1
E. robusta
Litterfall
449
7.9
57
1
E. robusta
Roots < 0.2 cm diam.
397
6.2
64
1
E. robusta
Roots > 1.0 cm diam.
442
4.8
92
1
E. robusta
Roots 0.2-1.0 cm diam.
442
4.6
96
1
E. robusta
Stem branch < 2.5 cm
549
4.9
112
1
E. robusta
Stem branch > 2.5 cm
462
3.0
154
1
E. robusta
Total above-ground biomass
469
4.5
104
1
Leucaena leucocephala
Leaves
416
33.2
13
1
L. leucocephala
Litter (A0)
393
15.7
25
1
L. leucocephala
Litterfall
442
20.4
22
1
L. leucocephala
Roots < 0.2 cm diam.
294
1.3
226
1
L. leucocephala
Roots > 1.0 cm diam.
432
15.5
28
1
L. leucocephala
Roots 0.2-1.0 cm diam.
451
13.3
34
1
L. leucocephala
Stem branch < 2.5 cm
439
13.3
33
1
L. leucocephala
Stem branch > 2.5 cm
454
8.1
56
1
L. leucocephala
Total above-ground biomass
451
9.3
48
2
E. cladocalyx
Leaves
489
12.3
41
3
E. amygdalina
Immature leaves
521
13.0
40
3
E. amygdalina
Immature leaves, coppice
506
18.0
28
3
E. globulus
Immature leaves
476
15.0
32
3
E. globulus
Immature leaves, coppice
533
26.0
21
3
E. globulus
Immature leaves, coppice (fire)
508
31.0
16
3
E. obliqua
Immature leaves
558
15.0
37
3
E. obliqua
Immature leaves, coppice
510
22.0
23
3
E. obliqua
Immature leaves, coppice (fire)
532
22.0
24
National Carbon Accounting System Technical Report
47
APPENDIX 1
MEASURED [C] AND [N] AND C:N RATIOS IN VARIOUS COMPONENTS OF FOREST
SPECIES continued
Study No.
Species
Component
C mg/g
N mg/g
C:N
3
E. ovata
Immature leaves
522
18.0
29
3
E. ovata
Immature leaves, coppice
512
17.0
30
3
E. ovata
Immature leaves, coppice (fire)
514
24.0
21
3
E. pulchella
Immature leaves
520
16.0
33
3
E. pulchella
Immature leaves, coppice
510
25.0
20
3
E. pulchella
Immature leaves, coppice (fire)
434
24.0
18
3
E. tenuiramis
Immature leaves
542
19.0
29
3
E. tenuiramis
Immature leaves, coppice
537
27.0
20
3
E. viminalis
Immature leaves
520
20.0
26
3
E. viminalis
Immature leaves, coppice
478
26.0
18
3
E. viminalis
Immature leaves, coppice (fire)
515
23.0
22
4
Pinus radiata
Needles, C+0
504
13.0
39
4
P. radiata
Needles, C+0
498
13.1
38
4
P. radiata
Needles, C+0
501
13.2
38
4
P. radiata
Needles, C+0
500
12.2
41
4
P. radiata
Needles, C+0
504
13.1
38
4
P. radiata
Needles, C+0
501
13.1
38
4
P. radiata
Needles, C+0
500
12.1
41
4
P. radiata
Needles, C+1
510
13.0
39
4
P. radiata
Needles, C+1
506
11.3
45
4
P. radiata
Needles, C+1
507
12.3
41
4
P. radiata
Needles, C+1
507
11. 8
43
4
P. radiata
Needles, C+1
506
13.1
39
4
P. radiata
Needles, C+1
507
10.5
48
4
P. radiata
Needles, C+1
509
10.2
50
5
P. radiata
Bark
533
3.9
175
5
P. radiata
Branch
514
1.6
354
5
P. radiata
Deepwood
541
0.9
651
5
P. radiata
Litter
535
6.2
102
5
P. radiata
Needles
511
11.8
44
5
P. radiata
Sapwwod
490
1.3
457
5
P. radiata
Twigs, 1yr
518
3.3
186
6
Melaleuca quinquenervia
Litter < 5 mm
491
14.3
34
6
M. quinquenervia
Litter < 5 mm
414
12.6
33
6
M. quinquenervia
Litter < 5 mm
417
12.0
35
6
M. quinquenervia
Litter < 5 mm
480
14.0
34
6
M. quinquenervia
Litter < 5 mm
417
11.9
35
48
Australian Greenhouse Office
Study No.
Species
Component
C mg/g
N mg/g
C:N
6
M. quinquenervia
Litter < 5 mm
407
12.0
34
6
M. quinquenervia
Litter > 5 mm
548
9.8
56
6
M. quinquenervia
Litter > 5 mm
539
9.7
56
6
M. quinquenervia
Litter > 5 mm
562
8.3
68
6
M. quinquenervia
Litter > 5 mm
544
9.0
60
6
M. quinquenervia
Litter > 5 mm
546
7.4
74
6
M. quinquenervia
Litter > 5 mm
540
7.6
71
7
Acacia melanoxylon
Leaf litterfall
476
17.7
27
7
Alnus glutinosa
Leaf litterfall
462
24.3
19
7
E. nitens
Leaf litterfall
513
6.6
78
7
Quercus rubra
Leaf litterfall
492
7.1
69
8
Albizia falcataria
Leaf litterfall
500
23.5
21
8
A. falcataria
Leaf litterfall
510
23.0
22
8
E. saligna
Leaf litterfall
530
8.9
60
8
E. saligna
Leaf litterfall
540
8.7
62
9
E. nitens
Leaves
524
13.9
38
10
P. radiata
Needles
513
13.0
39
11
Acacia various
Coarse woody debris
486
2.4
213
11
E. various
Coarse woody debris
487
1.5
379
12
E.s various
Forest floor
539
0.7
73
12
E. various
Forest floor
522
0.7
77
12
P. radiata
Litter
531
0.8
63
12
Pine, southern
Litter
544
0.7
82
References
1
Parrotta (1999)
7
Wedderburn and Carter (1999)
2
Gleadow (1999)
8
Brinkley et al. (1992)
3
Steinbauer et al. (1998)
9
Johnstone et al. (2001)
4
Snowdon (unpub.)
10 Snowdon, unpublished data
5
Gifford (2000a&b)
11 Harms and Dalal (2003)
6
Greenway (1994)
12 CSIRO/QFRI (2003)
National Carbon Accounting System Technical Report
49
APPENDIX 2
BIOMASS (T HA-1) AND NITROGEN CONTENT (KG HA-1) OF FOLIAGE AND TOTAL
ABOVE-GROUND BIOMASS IN VARIOUS NATIVE (N) FOREST AND PLANTATION
(P) ECOSYSTEMS
Ecosystem
Type
Foliage
biomass
Foliage
N
Above-ground
living
biomass
Aboveground N
Reference
Eucalyptus diversicolor/ E.
N
8.9
67.8
284
333
Hingston et al. (1979)
E. obliqua - E. dives
N
3.9
27.0
373
426
Feller (1980)
E. regnans
N
3.0
45.0
654
399
Feller (1980)
E. diversicolor
N
4.5
50.0
225
189
Hingston et al. (1979)
E. marginata
N
5.8
60.3
262
321
Hingston et al. (1980)
E. obliqua
N
6.1
83.2
401
372
Baker and Attiwill (1985)
E. obliqua
N
8.1
106.0
255
335
Baker and Attiwill (1985)
E. dives / E. rubida
N
2.2
23.6
71
116
Turner and Lambert (1988)
E. sieberi etc.
N
5.6
54.0
325
317
Hopmans et al. (1993)
E. radiata -E. dalrympleana
N
4.7
72.9
104
302
Turner (1980)
Acacia auriculiformis
P
9.0
221.4
326
958
Kumar et al. (1998)
A. auriculiformis
P
7.0
168.0
76
528
Osman et al. (1992)
A. auriculiformis
P
6.0
145.0
51
363
Osman et al. (1992)
A. auriculiformis
P
7.6
204.0
128
719
Bernhard-Reversat et al. (1993)
A. dealbata
P
6.4
227.0
182
1006
Frederick et al. (1985)
A. mangium
P
7.6
193.0
117
628
Bernhard-Reversat et al. (1993)
E. camaldulensis
P
5.0
69.0
45
149
Hunter (2001)
E. globulus
P
4.0
40.0
31
69
Cromer et al. (1980)
E. globulus
P
6.6
70.4
83
153
Cromer et al. (1980)
E. grandis
P
6.2
90.0
394
435
Turner and Lambert (1983)
E. grandis
P
3.1
49.0
123
246
Turner and Lambert (1983)
E. grandis
P
5.0
82.9
176
331
Turner and Lambert (1983)
E. grandis
P
8.6
142.0
274
549
Turner and Lambert (1983)
E. grandis
P
6.7
106.4
45
185
Hunter 2001)
E. grandis
P
3.2
57.3
188
617
Moraes Goncalves et al. (1998)
E. ‘hybrid’
P
9.6
56.3
116
214
Laclau et al. (1999)
E. nitens
P
9.4
173.0
82
332
Madgwick, et al. (1981)
E. regnans
P
8.7
141.0
172
340
Frederick et al. (1985)
E. fastigata
P
10.6
190.0
62
319
Madgwick, et al. (1981)
P (mine spoil)
6.0
51.1
58
128
Ward and Koch (1996)
E. saligna
P
5.7
91.0
130
241
Frederick et al. (1985b)
E. tereticornis
P
2.1
38.9
64
179
Sankaran (1998)
E. grandis
P
2.7
46.5
149
286
Bellote et al. (1980)
E. hybrid
P
4.2
63.2
91
431
Kushalpa (1993)
E. calophylla - E. resinifera
50
Australian Greenhouse Office
Ecosystem
Type
Foliage
biomass
Foliage
N
Above-ground
living
biomass
Aboveground N
Reference
E. globulus
P
5.0
61.0
50
112
Bennett et al. (1997)
E. globulus
P
4.0
46.8
45
93
Bennett et al. (1997)
E. globulus
P
4.0
46.0
43
87
Bennett et al. (1997)
E. grandis
P
5.6
85.4
275
486
Tandon et al. (1988)
P. radiata
P
7.2
84.0
160
196
Turner and Lambert (1988)
P. radiata
P
9.2
152.0
104
342
Frederick et al. (1985)
P. radiata
P
12.0
136.0
278
301
Baker and Attiwill (1985)
P. radiata
P
14.9
186.0
262
381
Baker and Attiwill (1985)
P. radiata
P
8.3
109.2
254
327
Birk (1993)
P. radiata
P
10.0
146.4
320
418
Birk (1993)
P. radiata
P
15.5
212.1
353
564
Birk (1993)
National Carbon Accounting System Technical Report
51
APPENDIX 3.
BIOMASS (KG HA-1) AND NITROGEN CONTENT (KG HA-1) OF LEAVES AND TOTAL
LITTERFALL FOR A RANGE OF NATIVE (N) AND PLANTATION (P) FORESTS
Ecosystem
Type
Leaf
Litterfall
Leaf
Litterfall
N
Total
Litterfall
kg ha-1
Total
Litterfall
N kg ha-1
Reference
E. regnans
P
5600
51.0
8100
61.0
Frederick et al. (1985)
E. pauciflora
N
2260
10.4
3920
19.5
Adams and Attiwill (1986b)
E. delegatensis
N
2620
15.8
6570
42.3
Adams and Attiwill (1986b)
E. regnans
N
2540
13.5
6770
40.8
Adams and Attiwill (1986b)
E. regnans
N
4200
34.4
7550
55.8
Adams and Attiwill (1986b)
E. obliqua
N
1960
10.6
5080
24.2
Adams and Attiwill (1986b)
E. obliqua
N
1940
10.9
4110
22.5
Adams and Attiwill (1986b)
E. sideroxylon
N
1530
12.6
2780
22.6
Adams and Attiwill (1986b)
E. microcarpa
N
1550
12.2
2800
22.3
Adams and Attiwill (1986b)
Acacia dealbata
P
4500
105.0
7000
139.0
Frederick et al. (1985)
Pinus radiata
P
6000
66.0
6200
68.0
Frederick et al. (1985)
P. radiata 1
P
2689
18.1
3583
24.0
Baker (1983)
P. radiata 2
P
2841
13.7
3859
20.8
Baker (1983)
P. radiata 3
P
1922
9.8
2582
14.2
Baker (1983)
P. radiata 4
P
2689
18.9
3345
23.8
Baker (1983)
P. radiata 5
P
3043
16.2
3752
22.0
Baker (1983)
E. obliqua 1
P
2463
17.7
5183
30.2
Baker (1983)
E. obliqua 2
P
2429
17.5
3884
24.1
Baker (1983)
E. regnans
P
2465
19.1
6862
46.4
Baker (1983)
E. sieberi
P
2570
13.6
5369
21.4
Baker (1983)
E. amygdalina
N
1100
4.6
1950
8.5
Adams and Attiwill (1991)
E. obliqua
N
2500
11.9
4320
19.5
Adams and Attiwill (1991)
E. obliqua - E. regnans
N
2270
10.8
5340
32.1
Adams and Attiwill (1991)
Atherosperma - Nothofagus
N
2400
16.6
4340
27.1
Adams and Attiwill (1991)
E. obliqua - E. amygdalina
N
2270
9.8
3740
21.4
Adams and Attiwill (1991)
E. obliqua
N
2080
7.9
3480
13.5
Adams and Attiwill (1991)
E. regnans
N
2610
23.0
4900
55.6
Polglase and Attiwill (1992)
E. regnans
N
2350
18.6
4850
53.1
Polglase and Attiwill (1992)
E. regnans
N
2600
19.0
5950
50.0
Polglase and Attiwill (1992)
E. regnans
N
2570
17.2
5790
38.1
Polglase and Attiwill (1992)
E. regnans
N
2870
22.6
8270
65.7
Polglase and Attiwill (1992)
E. regnans
N
2680
22.2
9410
83.5
Polglase and Attiwill (1992)
E. regnans
N
2750
20.4
8620
67.7
Polglase and Attiwill (1992)
E. regnans
N
2737
23.9
6606
43.5
Ashton (1975)
E. obliqua - E. baxteri
N
1900
8.7
2330
9.8
Lee and Correll (1978)
Melaleuca cuticularis
N
1600
12.6
4300
33.6
Congdon (1979)
52
Australian Greenhouse Office
Ecosystem
Type
Leaf
Litterfall
Leaf
Litterfall
N
Total
Litterfall
kg ha-1
Total
Litterfall
N kg ha-1
Reference
E. gummifera - Angophora costata
N
2970
22.3
5400
40.5
Lamb (1985)
E. botryoides - A. floribunda
N
4247
39.9
7450
70.0
Lamb (1985)
E. crebra
W
930
6.2
1270
7.8
McIvor (2001)
E. drepanophylla
W
300
2.3
720
5.2
McIvor (2001)
E. diversicolor
N
1000
7.2
1130
8.6
O’Connell and Menage (1982)
E. diversicolor
N
1640
9.1
3700
32.5
O’Connell and Menage (1982)
E. diversicolor
N
2140
12.3
4460
33.8
O’Connell and Menage (1982)
E. diversicolor
N
2700
16.3
7150
49.3
O’Connell and Menage (1982)
E. diversicolor
N
2230
11.0
9450
58.1
O’Connell and Menage (1982)
E. brookerana
P
7660
83.3
7860
84.9
Guo and Sims (1999)
E. brookerana
P
9970
118.4
10300
121.2
Guo and Sims (1999)
E. brookerana
P
9900
134.6
10650
140.7
Guo and Sims (1999)
A. auriculiformis
P
12570
231.0
17500
297.0
Swamy and Proctor (1997)
E. tereticornis
P
4170
35.5
8620
67.7
Swamy and Proctor (1997)
E. globulus
P
3402
28.0
8492
58.0
George and Varghese (1990)
A. mearnsii
P
4482
97.7
9041
192.9
Watanabe et al. (1980)
A. mearnsii
P
4251
92.7
9701
197.4
Watanabe et al. (1980)
E. tereticornis
P
6035
57.3
8313
66.3
Hosur et al. (1997)
E. tereticornis
P
3920
39.6
5515
53.6
Hosur et al. (1997)
Wet tropical rainforest
N
4173
45.9
5626
60.2
Herbohn and Congdon (1998)
Wet tropical rainforest
N
4017
47.4
5517
64.0
Herbohn and Congdon (1998)
Wet tropical rainforest
N
3743
37.8
5644
58.7
Herbohn and Congdon (1998)
National Carbon Accounting System Technical Report
53
APPENDIX 4.
BIOMASS (T HA-1), NITROGEN CONTENT (KG HA-1) AND CONCENTRATION (% ODW)
AND C:N RATIOS OF LITTER IN VARIOUS ECOSYSTEMS
Ecosystem
Type
Litter
biomass
Litter N
content
Average
Litter [N]
C:N
Reference
Acacia harpophylla
N
14.3
163.2
1.14
44
Moore et al. (1967)
Araucaria - Pouteria rainforest
N
8.8
168.2
1.92
26
Enright (1979)
Cool temperate rainforest
N
14.3
102.9
0.72
69
Adams and Attiwill (1991)
E. andrewsii +
N
12.4
91.9
0.74
67
Richards and Charley (1977)
E. delegatensis
N
17.8
125.0
0.70
71
Meakins (1966 (see Bevege 1978)
E. delegatensis
N
22.7
120.0
0.53
95
Raison et al. (1986)
E. delegatensis
N
37.2
257.0
0.69
72
Park (1975) (see Bevege 1978)
E. diversicolor
N
27.3
224.0
0.82
61
Hingston et al. (1979)
E. dives
N
14.5
75.0
0.52
97
Raison et al. (1986)
E. fastigata
N
27.0
216.0
0.80
63
Meakins (1966 (see Bevege 1978)
E. fastigata
N
18.1
109.0
0.60
83
Meakins (1966 (see Bevege 1978)
E. marginata
N
11.1
51.0
0.46
109
Hingston et al. (1980)
E. obliqua
N
11.2
86.8
0.78
65
Baker and Attiwill (1985)
E. obliqua
N
9.5
50.9
0.54
93
Baker and Attiwill (1985)
E. obliqua +
N
4.5
33.5
0.74
67
Richards and Charley (1977)
E. pauciflora
N
17.4
101.0
0.58
86
Raison et al. (1986)
E. pauciflora
N
34.2
323.0
0.94
53
Park (1975) (see Bevege 1978)
E. pilularis
N
15.0
87.0
0.58
86
Bevege (1978)
E. pilularis
N
15.3
105.0
0.69
73
Bevege (1978)
E. piperita
N
6.3
12.0
0.19
261
Hannon 1958 (see Bevege 1978)
E. robertsonii
N
9.2
55.0
0.60
84
Meakins 1966 (see Bevege 1978)
E. signata/ E. umbra
N
27.0
194.9
0.72
69
Rogers and Westman (1977)
E. agglomerata-E. muelleriana
N
16.8
58.0
0.35
145
Hopmans et al. (1993)
E. amygdalina
N
10.3
53.5
0.52
96
Adams and Attiwill (1991)
E. delegatensis
N
51.5
286.0
0.56
90
Adams and Attiwill (1986)
E. diversicolor
N
9.1
78.0
0.85
59
O’Connell (1994)
E. diversicolor/ E.
N
19.5
105.0
0.54
93
Hingston et al. (1979)
E. dives/ E.rubida
N
13.5
45.6
0.34
148
Turner and Lambert (1988)
E. microcarpa
N
12.5
106.9
0.86
58
Adams and Attiwill (1986b)
E. obliqua
N
13.7
66.8
0.49
103
Adams and Attiwill (1991)
E. obliqua
N
11.6
70.6
0.61
82
Adams and Attiwill (1986b)
E. obliqua
N
20.0
82.3
0.41
121
Adams and Attiwill (1991)
E. obliqua
N
18.0
96.8
0.54
93
Adams and Attiwill (1986b)
E. obliqua - E. amygdalina
N
12.9
79.4
0.62
81
Adams and Attiwill (1991)
E. obliqua - E. dives
N
13.1
132.0
1.01
50
Feller (1980)
E. obliqua - E. regnans
N
24.6
174.0
0.71
71
Adams and Attiwill (1991)
E. pauciflora
N
16.5
64.9
0.39
127
Adams and Attiwill (1986b)
54
Australian Greenhouse Office
Ecosystem
Type
Litter
biomass
Litter N
content
Average
Litter [N]
C:N
Reference
E. pilularis
N
16.1
58.0
0.36
139
Applegate (1982)
E. regnans
N
47.5
394.0
0.83
60
Feller (1980)
E. regnans
N
33.7
140.2
0.42
120
Adams and Attiwill (1986b)
E. regnans
N
21.8
112.1
0.51
97
Adams and Attiwill (1986b)
E. sieberi-E. obliqua
N
12.0
36.0
0.30
167
Turner and Lambert (1986b)
E. sideroxylon
N
14.6
92.3
0.63
79
Adams and Attiwill (1986b)
E. sieberi etc.
N
16.8
58.0
0.35
145
Hopmans et al. (1993)
Montane rainforest
N
7.7
106.0
1.38
36
Edwards and Grubb (1977);
Grubb and Edwards (1982)
Nothofagus moorei
N
8.1
110.1
1.36
37
Richards and Charley (1977)
Acacia dealbata
P
25.8
560.0
2.17
23
Frederick et al. (1985)
E. grandis
P
17.4
47.0
0.27
185
Turner and Lambert (1983)
E. grandis
P
23.7
187.2
0.79
63
Moraes Goncalves et al. (1998)
E. ‘hybrid’
P
11.4
81.0
0.71
70
Laclau et al. (1999)
E. regnans
P
9.2
87.0
0.95
53
Frederick et al. (1985)
E. saligna
P
19.2
140.0
0.73
69
Frederick et al. (1985b)
P. radiata
P
11.7
102.0
0.87
57
Birk (1993)
P. radiata
P
13.9
136.0
0.98
51
Birk (1993)
P. radiata
P
20.9
171.0
0.82
61
Birk (1993)
P. radiata
P
18.9
271.0
1.43
35
Frederick et al. (1985)
P. radiata
P
15.7
182.0
1.16
43
Baker and Attiwill (1985)
P. radiata
P
15.2
195.0
1.28
39
Baker and Attiwill (1985)
P. radiata
P
29.2
289.4
0.99
50
Ouro et al. (2001)
P. radiata
P
20.7
258.0
1.25
40
Carey et al. (1982)
P. radiata
P
8.9
82.2
0.92
54
Turvey and Smethurst (1994)
P. radiata
P
14.0
87.7
0.63
80
Turner and Lambert (1988)
19.84
19.8
124.0
80
Turner (1980)
E. radiata - E. dalrympleana
National Carbon Accounting System Technical Report
55
APPENDIX 5.
DATABASE STRUCTURE (CNSOILS.MDB). THE DATABASE IS WITH THE NCAS OF THE
AGO, CANBERRA.
Table
Field
Description
Papers
P_no
Sequential number - KEY field
Reference
Paper short reference
Organisation
Primary organisation from which the paper originated
Location
State where that organisation was based
Comments1
Sites
S_no
Sequential number for each class/site for which soil C,
N or C:N were measured – KEY field
Location
Site location
State
Site State
Soil PM
Soil parent material
Lat_agd66
Latitude in decimal degrees- AGD66 datum
Long_agd66
Longitude in decimal degrees- AGD66 datum
Elev_m
Elevation (m)
MAR_mm
Mean annual rainfall (mm)
Ecosystem
Ecosystem where soil was sampled
Species
Main forest species
Treat_Dist
Forest treatment or disturbance type
Stand_age
Forest stand age (yrs)
Comments2
Layers
56
L_no
Sequential soil layer number – KEY field
No_sam
Number of soil specimens included in summary
Sam_date
Sample data (yr)
U_Depth
Upper soil layer depth (m)
L_Depth
Lower soil layer depth (m)
F_no
Sequential soil fraction number within layer – KEY field
Fraction
Soil fraction (whole soil, ws; < 2mm etc.)
Wgt%
Fraction weight (% of whole soil)
Biomass
Organic matter biomass (t ha-1)
OM%
Soil organic matter (%)
OM_sd
Soil organic matter standard deviation
WB_C_corr
Walkley-Black correction soil C
Total_C
Total soil C (%)
C_sd
Total soil C standard deviation
Method_C
Method for Total C or OM
Total_N
Total soil N (%)
N_sd
Total soil N standard deviation
Method_N
Method for Total C or OM
Total_P
Total soil P (ppm)
Australian Greenhouse Office
Table
Field
Description
Layers
C:Np
C:N ratio from published paper
C:Nc
C:N ratio calculated from published paper
Comments3
Litter
No_sam
Cover%
Litter cover percentage
F_no
Sequential litter fraction number
Component
Litter fraction/component
Biomass-tha
Organic matter biomass (t ha-1)
BN_sd
Biomass standard deviation
Total_C
Total litter C (%)
C_sd
Total litter C standard deviation
Method_C
Method for Total C
Total_N
Total litter N (%)
N_sd
Total litter N standard deviation
Method_N
Method for Total C or OM
Total_P
Total litter P (ppm)
Cmass_kgha
Litter C mass (kg ha-1)
Nmass_kgha
Litter N mass (kg ha-1)
C:Np
C:N ratio from published paper
C:Nc
C:N ratio calculated from published paper
Comments4
CWD
Vad_m3ha
Adjusted CWD volume (m3 ha-1)
D_kgm3
CWD density (kg m3)
Biomass-tha
CWD biomass (t ha-1)
BN_sd
Biomass standard deviation
Total_C
Total CWD C (%)
C_sd
Total CWD C standard deviation
Method_C
Method for Total C
Total_N
Total CWD N (%)
N_sd
Total CWD N standard deviation
Method_N
Method for Total C
Total_P
Total CWD P (ppm)
Cmass_kgha
CWD C mass (kg ha-1)
Nmass_kgha
CWD N mass (kg ha-1)
C:Np
C:N ratio from published paper
C:Nc
C:N ratio calculated from published paper
Comments5
National Carbon Accounting System Technical Report
57
58
Australian Greenhouse Office
National Carbon Accounting System Technical Report
59
60
Australian Greenhouse Office
Publications
Series 1
Sets the framework for development of the National Carbon Accounting System
(NCAS) and documents initial NCAS-related technical activities.
Series 2
Provides targeted technical information aimed at improving carbon accounting
for Australian land based systems.
Series 3
Details protocols for biomass estimation and the development of integrated carbon
accounting models for Australia. Of particular note is:
28.
The FullCAM Carbon Accounting Model: Development, Calibration
and Implementation for the National Carbon Accounting System.
Series 4
Provides an integrated analysis of soil carbon estimation and modelling for
the NCAS, incorporating data from paired site sampling in NSW, Qld and WA.
A preliminary assessment of nitrous oxide emissions from Australian agriculture
is also included.
Series 5
Provides details on the improvement and verification of land cover change
analyses, calibration of the FullCAM model and impacts of tillage on
soil carbon.
Series 6
Includes:
45.
Review of C:N Ratios in Vegetation, Litter and Soil Under Australian
Native Forests and Plantations.
46.
Update on the National Carbon Accounting System Continuous
Improvement and Verification Methodology.
accounting and forecasting capability for human-induced sources and
sinks of greenhouse gas emissions from Australian land based
systems. It will provide a basis for assessing Australia’s progress
towards meeting its international emissions commitments.
technical report no. 45
The National Carbon Accounting System provides a complete
Review of C:N Ratios in Vegetation, Litter and Soil
Under Australian Native Forests and Plantations
http://www.greenhouse.gov.au