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Effect of Silvicultural Treatments on Carbon Storage
of Northern Hardwood Forests
Byung Bae Park
Introduction
Combustion of fossil fuels and other human activities are the primary
reasons for the increased concentration of atmospheric carbon dioxide,
which is likely to accelerate the rate of climate change. The Kyoto Protocol
calls for each country that ratifies the agreement to reduce greenhouse
gas emissions by specified targets below a 1990 baseline level during
the first commitment period, 2008 to 2012. The target for the United States
is a 7 percent reduction.
The role of forests in carbon sequestration is to transform atmospheric
carbon dioxide into organic matter. Many researchers have examined ways
to sequester more carbon in forests or to offset losses from these systems.
These include establishing new stands, reducing forest burning and deforestation,
and storing wood in durable products.
In New York State, forests cover 62 percent of the total land area, with
85 percent of forests in private ownership. Half of the forested area
is economically mature and the majority is not protected from timber harvesting.
But few have management plans that address carbon storage. The offset
credits associated with forest growth could change the economics of land
use and forest management in the region. Forest managers and landowners
need to be aware of the effects of alternate treatments on carbon storage
as well as economic products.
The effect of silvicultural activity on carbon storage has rarely been
studied. This study is a first step towards providing forest managers
and landowners with information on how silvicultural treatments affect
carbon storage in live trees, detritus, and harvested products.
Estimation of Carbon Storage in the Forest
In this study, carbon storage was estimated as the sum of three major
forest ecosystem components: live trees, detritus and harvested wood.
Although soil carbon storage is extremely large, it was ignored, assuming
that silvicultural treatments don't significantly affect carbon change.
We used existing data on the diameter and condition of live trees by tree
species in research plots. Three different forest types in northern hardwood
forests were investigated (Figure 1, 2, 3). Various
cutting practices, widely used in New York State for silvicultural treatments,
were simulated using SILVAH, a stand analysis, prescription, and management
simulator program for eastern hardwoods, developed by the United States
Department of Agriculture Forest Service. Tree growth following treatment
was also simulated by SILVAH. Changes over time in volume of harvested
wood and detritus after cutting were predicted using published rate loss
constants. The estimated volume of live trees, detritus and harvested
wood was added and converted to the amount of carbon stored.
Carbon Storage in Live Trees
The living parts of trees are a sink for carbon dioxide while the forest
is growing after silvicultural treatments.
Tree growth was simulated at each application of 50% thinning, 70% thinning,
50% selection cutting, 70% selection cutting and no cutting (Figure
4, 5, 6).
Carbon Storage in Harvested Wood
Harvested wood represents carbon stored in various wood products after
harvesting that have not yet oxidized back to carbon dioxide. They were
largely allocated to four groups based on stem diameter: poles, small
saw, medium saw and large saw. They are assumed to decay exponentially.
The average residence times of carbon in harvested wood were estimated
at 4, 13, 30 and 65 years for poles, small saw, medium saw and large saw.
Remaining volume was estimated by the following equation.
y = e(-tk)
where t is the number of years since the onset of decomposition of a given
material, k is the rate loss constant and y is the fraction of original
material remaining t years since the onset of decomposition.
Carbon Storage in Detritus
Carbon in detritus at the time of harvest was simulated by SILVAH. Detritus
was treated as four components: stem + bark, branches, foliage, and stumps
+ roots. The decomposition rates of these components were based on published
rate loss constants. Remaining detritus was estimated by the equation
above.
Method of Volume Converted into Carbon
Total estimated volume (cubic feet) was converted to the amount of carbon
storage (pounds) by a carbon conversion factor (18.65), which was calculated
as the density of wood (37.44 lbs/cubic foot) times percent carbon (0.498
%). The decomposition rate constants apply to the mass of detritus and
wood product pools, so our results are not sensitive to assumptions about
the density of these materials.
Total Carbon Storage after Silvicultural Practices
The three forest types differed in carbon storage. Carbon storage of the
original stands is 23 (Northern Hardwood), 36 (Allegheny Hardwood) and
41 tons/acre (Oak - Black cherry forest). Results of the simulations suggest
that tree cutting reduces total carbon storage compared to no cutting
(Figures 7, 8, 9), because the growth of residual
trees is less rapid than the decomposition of the detritus and harvested
wood products. Changes in carbon storage in each forest types are primarily
determined by the growth of live trees. The rate of accumulation of carbon
in live trees is greatest in the Allegheny Hardwood forest, where trees
typically have the fastest volume growth.
Among treatments, no cutting generally stores the greatest amount carbon.
However, the 70% selection cutting treatment increases carbon storage
slightly more than that of no cutting at about 40 years in Allegheny Hardwoods.
More research is needed to determine whether any silvicultural treatment
can store significantly more carbon than no treatment over the long term.
Contact Information and Links
Please feel free to contact us if you have any questions or comments.
Byung Bae Park
Email: ecobbp@hotmail.com
Dr.
Ruth D. Yanai
Email: rdyanai@mailbox.syr.edu
Homepage: http://www.esf.edu/course/rdyanai/home.htm
345 Illick Hall, One Forestry Drive
Syracuse, NY 13210-2788
(315) 470-6955
Links
The Kyoto Protocol
United Nations Framework Convention on Climate Change (UNFCCC)
www.unfccc.de/
SILVAH
www.fs.fed.us/ne/warren
Growth
and Yield Simulator
www.cof.orst.edu/cof/fr/research/organon
Figures 1- 3



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Figures 4-6
Figure #4

Figure #5

Figure #6

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Figures 7-9
Figure #7

Figure #8

Figure #9

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