Climate change and best forestry
practices.
Can we (ever) reach a consensus?
Dr. Harald Kvaalen
Norwegian Forest and Landscape Institute
Forests and forestry influence the climate in many ways
• Directly
–
–
–
–
–
–
Carbon storage in trees and soil
Radiation budget (albedo)
Distribution of heat
Cloud albedo
Rainfall
Runoff
• Indirectly
– Carbon storage in forest products
– Storage and substitution effects of forest products
Is it possible to find best practices when things are so complex?
• Yes if we know the magnitude of the major effects
• Some of them are hard to quantify
– Cloud albedo
• Substitution effects depends on how we use the products, and in the end, on politics
There are three main practices
• Conservation
– Store carbon but gives no industrial raw materials
– Is also influenced by human industrial society (SO2, NOx)
• Uneven aged forestry with selective logging
• Even aged forestry with clear cutting and planting
We cannot forget history!
• Norway has a very long logging history • Already during the iron age large areas of mountain forests deforestated
• Many forest areas have been harvested with diameter limit cutting many times over four to five centuries
• The worlds first national forest inventory (NFI) in the 1920’s give us valuable, but often forgotten facts
Forest condition in Buskerud county around 1920
Area
Forest condition
(ha)
Under utiliezed
Normaly logged
Over utilized
‘Luted’
Sum
M3 per ha
of spruce
Percent of
and pine
the area
7227
1.4
140
440985
57824
86.4
11.3
57
28
4108
0.8
13
510144
Barskogens tilstand og bestokning fra Tabell 41 og Tab 42
• Similar conditions in all other counties
• Large areas of the mountain region and Western Norway were completely deforstated
• Real pristine forest barely exist in Norway
• The present «old growth forest» is a legacy from four hundred years of selective logging
• Does it still matter?
Let’s take a closer look at the change in forest site index
Data from the National Forest Inventory
Modeled changes in SI
The differences are large indeed
Yield capacity (m3 ha-1)
14
Yield capacity regression line
12
Stand from 1880
Stand from 1980
10
8
6
4
2
0
6
8
11
14
17
20
Site index (H40 Tveite)
Example from stands on blueberry type and better sites with heat sum of 1000 day degrees
23
15
22
20
14
18
13
16
14
12
12
11
10
8
H40
Mean height
10
6
9
4
0
5
10
15
20
25
30
35
40
45
Diameter class (cm)
Data from NFI Oppland 1924 for spruce forest on the best sites
50
Mean height (meters)
H40 calculated from growth intercept
Diameter limit cutting is one important
cause of the low site index in old forest
If we study singel trees we often find
the same pattern
B o n ite t T re m y r i T ø rrd a l
20
T re 3
18
L in e æ r tre n d
Bonitet (H40)
16
14
12
10
8
6
1890
1905
1920
1935
1950
År
1965
1980
1995
Recent genetic improvement will add to this difference
Austre Slidre
600 masl
Site index (H40)
20
Ringebu
720 masl
SI from
veg. type
17
14
11
Local Orchard Local Orchard
Variety
SI from old
trees nearby
18
16
-1
-1
Current annual increment (m ha year )
Planted middel aged forests at high altitudes grows very well
3
14
12
10
8
6
1102 1020 masl
1103 1020 masl
G14 Braastad p8
G17 Braastad p8
G20 Braastad p8
4
2
0
0
20
40
60
80
Total age from seed (years)
100
The historical legacy still matters to estimation of site productivity
•
•
•
•
•
•
•
•
Past diameter limit cutting
Longer growing season in recent years
Cumulative increase in N‐supply
Decline in SO2 – increasing levels of nutrients?
CO2 fertilization?
Official figures from the old NFI plots are wrong
Models based on them are misleading (Klimakur)
Correct assessment of site productivity is an absolute necessity in any modeling work
Development of standing volume is dependent on SI and stand density
Asumptions:
No thinnings
Interest rate 2%
Price timber: 480 NOK
Price pulp: 240 NOK
800
Standing volume (m3 ha-1)
Models:
Gi: Fahlvik 2006
Ig: Andreassen et al 2009
Ho Tveite 1977
Mort: Eid & Øyen 2003
700
600
500
400
300
200
100
0
0
50
100
150
200
Total age from germination (years)
250
The development of stand volum Is similar to the C – stock in a chronosequence from Canada
(Taylor et al. 2014)
Mean V3 to rotation age(m3 ha-1)
Mean standing volume depends on
rotation length, stand density and SI
500
400
300
200
100
0
0
50
100
150
200
Rotation age (years)
250
A tree is more than the stem
Needles + dead needles (turnover rate 0.143)
Crown parts + dead cp (turnover rate 0.027) Roots + dead roots (turnover rate 0.027)
+ Necromass of dead trees calculated from Eid
and Øyen 2003
• Mean residence time of all dead parts 40 years > decomposition rate 0.025 (Frøberg et al. 2011)
•
•
•
•
-2
Carbon from decaying parts (kg m )
The speed of C accumulation in dead and decaying parts depends on stand density, SI, and the rate of decomposition
25
20
15
7 kg C in organic soil
that decompose
10
5
0
0
20
40
60
80
100
Rotation age (years)
120
Sum of old and new C (kg m-2)
C in soil will increase over rotations
even if we remove all harvest residues 220
200
180
160
140
120
100
80
60
40
20
0
50
100
150
200
Years from first cutting
250
Some weak parts
• Models do not start at the planting year
• Øyen (Norsk Skogbruk 9/2012) found that young planted forest now has much higher above ground biomass expansion factors than predicted by Marklund, whereas it was a bit lower in older plantations. – Christmas tree sized trees has a BEF about 4
• Carbon from trees via mycorrhiza is not included The C‐input to soil
from trees via mycorrhiza can be signficant even in young forest
(Wallander et al. 2010)
C‐input from trees through ECM can
be substantial i young forest
Neumann & Matzner 2013. Biomass of extramateria ectomycrrhizal mycelium
And fine roots in a young Norway spruce stand..‐
-2
Sum C biomass and org. soil (kg m )
Total C accumulation from planting
50
40
30
20
10
0
0
20
40
60
80
100
Rotation age (years)
120
-2
-1
Mean total C-accumulation (kg m year )
Mean C‐accumulation
0.6
0.5
0.4
0.3
0.2
0.1
0.0
0
20
40
60
80
100
Rotation age (years)
120
Adding 0.1 – 0.4 kg C from mycorrhiza and increase the BEF in young forest will change the picture a lot
Ståande volum >10 cm (m3 ha-1)
Then we can turn to the protected
forest at Oppkuven in Nordmarka
300
250
200
150
100
50
0
6
8
11
14
Bonitet H40
Data frå Rune Groven 2006: Stand structure and dynamics of old growth Picea abies forest in southeastern Norway
Mean standing volume over the rotation in even aged harvested forest is about the same as in protected forest
Rotation Mean V3 H40 length
even aged Oppkuven V3
11
121
116
140
14
99
173
275
17
86
277
The comparssion is totally dependent on that SI is correct and assumptions about rotation length
-2
C accumulation and subst effect (kg m )
Cutting and planting is better than protection after some years
30
20
10
0
-10
0
20
40
60
Rotation age (years)
80
Assuming substitution effect of 400 kg per m3 and that the old forest is at steady state C.
Even aged vs uneven aged
• Andreassen 1991: In uneven aged long term experminents the yield was ca 20 percent below the yield capacity.
• Calculation of the mean standing volume at some of these plots shows that it also is about 20 percent lower than for even aged forest
• C‐accumulation in other tree parts must be much higer if uneven aged is to beat even aged
• Recall the difficulties with SI asessment
Cum. dif. radiative forcing (MJ m-2)
Albedo: examples, spruce G11 and G17 vs cleared land
20000
0
-20000
-40000
-60000
Løken + 500 m
Tromsø
Løken G11
-80000
-100000
-120000
0
20
40
60
80
100
Time from planting
Model: (Bright et al. 2013), radiation and temp data: Bioforsk, radiation efficiency =2,
1 kg CO2 = 28.8 MJ.
Albedo
• If we can belive the models spruce is better than goat driven deforestation even in high altitude areas
• In costal areas albedo play little role and it will decline with global warming
• Including albedo requires very good models for the early carbon dynamics because of the cumulative difference
Conclusions
• Clearcutting and planting generally the best option – but there are exeptions
• We need much better models for early stand development and for the soil
• Forest tree breeding will continue and change the productivity – many models are outdated
• We need a much better understanding of the changes in site productivity
• If we get all this we may reach consensus ?