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Abstract
The USDA Forest Service Forest Inventory and Analysis (FIA) program, as mandated by US Congressional legislation, provides statistically valid and unbiased estimates of forest characteristics across the United States and territories, which underlie a variety of analyses supporting ecological, economic, and policy needs across spatial scales. New allometric models have been implemented in the FIA program database based on a recent National Scale Volume and Biomass (NSVB) study for updated tree biomass and carbon estimates. Moreover, newer soil and litter carbon models with corresponding new estimates implemented in the FIA database, dependent on live tree biomass inputs. To understand effects of these updated models on forest carbon estimates, we compared estimates between previous and new (current) models. The most significant differences in total carbon (i.e., combined total carbon stock across various forest pools, including soil organic matter, litter, and live and dead tree biomass) were driven by larger estimates of soil organic carbon and smaller estimates of litter carbon. Overall, live tree merchantable volume, aboveground live biomass and carbon, and belowground live biomass estimates, were larger with the new models. Magnitude of differences varied by attribute, region, forest type, species, and tree sizes, as expected. Importantly, because previous models underestimated biomass in tops and limbs, there is now a higher estimated proportion of total tree biomass in these components and a lower proportion in the merchantable bole. We discuss some implications in the context of voluntary carbon accounting and forest carbon projects under the different registries and the potential influence of the new model system to timber market analyses and associated asset valuations.
Citation
Héctor I. R., Munro, H.L., Prisley, P.P., et al. Population estimate differences for forest biomass, merchantable volume, and carbon pools as a result of modeling system updates in the United States. ScienceDirect. 595: 12. 2965. https://doi.org/10.1016/j.foreco.2025.122965.