COS 87-9
An examination of dead wood carbon stock estimates to varying estimation procedures using the U.S. national forest inventory

Thursday, August 8, 2013: 10:50 AM
L100C, Minneapolis Convention Center
Grant M. Domke, USDA Forest Service, Northern Research Station, St. Paul, MN
Christopher W. Woodall, Northern Research Station, USDA Forest Service, Saint Paul, MN
Mark E. Harmon, Forest Ecosystems and Society, Oregon State University, Corvallis, OR
Andrew N. Gray, USDA Forest Service, Pacific Northwest Research Station, OR
Becky Fasth, Forest Science, Oregon State University, Corvallis, OR
Background/Question/Methods

Over the last several decades, downed dead wood (DDW) in forests has emerged as an important component in ecosystem structure and function. Renewed interest in utilizing forest biomass for energy has further elevated the profile of DDW and the contribution of this component to the carbon cycle. In the US, the national forest inventory conducted by the USDA Forest Service, Forest Inventory and Analysis (FIA) program has been consistently measuring DDW since 2001. Recently, purely model-based estimates of DDW carbon stocks were replaced in the FIA inventory with field-based estimates which rely on a general volume model, genera-specific density reduction factors by decay class, and a single carbon concentration constant. The objectives of this study were to examine the inputs and procedures employed to estimate DDW carbon stocks at the plot and population in the FIA program and evaluate alternative volume models, density reduction factors, and carbon concentration constants and associated uncertainties using sensitivity analysis. 

Results/Conclusions

Data for this study were taken entirely from the FIA plot network in the state of Oregon. A total of 4,859 observations were used from the most recent 10-year inventory cycle (2001-2010). Preliminary analyses examining just the differences between broad density reduction factors and carbon concentration constants versus genera-specific values resulted in substantial differences in per-unit-area and state level estimates of DDW biomass/C stocks. The preliminary results illustrate the complexities in measuring and modeling DDW dynamics in forest ecosystems and estimating DDW biomass/C across multiple spatial scales. Utilizing FIA data to assess alternative estimation methods and inputs was a convenient mechanism for assessing the local, regional, and national implications of emerging research on forest and tree attributes. Future analyses will incorporate alternative volume equations by DDW decay class and estimates will be evaluated across multiple spatial scales.