Abstract

Forest ecosystems are the largest terrestrial carbon sink on earth and their management has been recognized as a relatively cost-effective strategy for offsetting greenhouse gas emissions. Forest carbon stocks in the U.S. are estimated using data from the USDA Forest Service, Forest Inventory and Analysis (FIA) program. In an attempt to balance accuracy with consistency, the FIA program recently developed the component ratio method which utilizes regional volume models to replace the existing set of generalized allometric regression models used to estimate biomass and carbon stocks. This study describes the impact of the transition from the generalized allometric regression models to the component ratio method on the National Greenhouse Gas Inventory estimates by comparing estimates of carbon stocks from both approaches by common tree species and varying spatial scales (e.g., tree to national scale). Results for the 20 most abundant tree species in the 48 conterminous states of the U.S. suggest there is a significant difference in estimates of carbon stocks at the plot and national scales for the two estimation approaches. The component ratio method decreased estimates of national carbon stocks by an average of 16% for the species in the study. The observed reductions in carbon estimates can be attributed to incorporation of tree height as a predictor variable into species-specific volume models used to estimate tree biomass and carbon stocks. While the transition from the generalized allometric regression models to the component ratio method is procedural in nature, it may have important implications for national and global forest carbon sink estimates and the perception of the role forests play in mitigating the effects of atmospheric carbon dioxide. By combining regional accuracy with a nationally consistent approach, the component ratio method reflects a critical first step in aligning estimates of forest carbon stocks in the U.S.’s National Greenhouse Gas Inventory with estimates of tree volume in the FIA database.

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