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A Comparison of Carbon Stock Estimates and Projections for the Northeastern United States

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We conducted a comparison of carbon stock estimates produced by three different methods using regional data from the USDA Forest Service Forest Inventory and Analysis (FIA). Two methods incorporated by the Forest Vegetation Simulator (FVS) were compared to each other and to the current FIA component ratio method. We also examined the uncalibrated performance of FVS growth simulations for predicting net carbon accumulation in live trees. In general, the three carbon stock estimation approaches do not produce estimates that are either equivalent or are simply convertible. A strong spatial pattern of relationships between estimates was associated with regional variation in stand top height. Uncalibrated growth projections gave downwardly biased results that were also poorly correlated with observed carbon accumulation rates, yielding little improvement in root mean square error over the use of a simple regional average. These results reinforce the need for managers and scientists to be careful in choosing methods and reporting carbon stock estimates and to use appropriate model calibration methods in projecting future carbon accumulation.
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Keywords: biomass; carbon markets; growth and yield; model validation

Document Type: Research Article

Publication date: 2014-04-01

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    Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

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    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
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