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Prediction of forest biomass and carbon is becoming important issues in the United States. However, estimating forest biomass and carbon is difficult and relies on empirically-derived regression equations. Based on recent findings from a national gap analysis and comprehensive assessment of the USDA Forest Service Forest Inventory and Analysis (USFS-FIA) component ratio method (CRM) for estimating both biomass and carbon using historical individual tree biomass data, alternative approaches for predicting forest biomass and carbon were evaluated. The different CRM approaches tested included: 1) development and use of a unified stem taper equation to estimate stem volume; 2) updated model forms and parameters for predicting biomass components; and 3) comparison of alternative wood density values. Overall, these modifications show the potential to improve estimates of forest biomass and carbon, but additional testing is required before implementation.

Estimation of national forest biomass and carbon in the United States is increasingly desirable for many reasons. Recent studies evaluated nationally-prominent (Domke et al. 2012) and regionally-prominent (Westfall 2012) biomass estimation methods and found significantly disparate results, instigating research into current estimation methods. However, assessing biomass estimation methods and developing new methods are difficult due to the requisite for independent empirical data. A national biomass estimation research project currently is acquiring the necessary data for improving biomass estimation.