Jenkins, Jennifer (University of Vermont, 590 Main Street, Burlington, VT, 05405; Phone: 802-656-2953; Email: jennifer.c.jenkins@uvm.edu)

A Comprehensive Database of Diameter-Based Biomass Regressions for North American Tree Species

J.C.Jenkins, D.C.Chojnacky, L.S.Heath, R.A.Birdsey

Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the published literature can be inconsistent and incomplete with respect to large-scale forest C estimation and few off-the-shelf resources have been available for allometric estimation of tree biomass. In this project, we used primary sources whenever possible to compile all available (2600+) diameter-based allometric regression equations for estimating total aboveground and component biomass, defined in dry weight terms, for tree species found in the United States. The database includes information on the numbers of trees sampled to develop each equation, the maximum and minimum dbh values over which the equation is valid, regression statistics as published by the original authors, and other information valuable for users of the equations. The compilation is published as a database and is available in both paper and electronic format (Jenkins, JC, DC Chojnacky, LS Heath, and RA Birdsey. 2004. Comprehensive Database of Diameter-based Biomass Regressions for Untied States Tree Species. Gen. Tech. Rep. NE-319. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. Also available at http://www.fs.fed.us/ne/global/. This database is the underlying source of material for our 2003 paper entitled “Consistent National-Scale Biomass Estimators for United States Tree Species” (Forest Science 49(1): 12-35). In addition to its value as a source for our generalized national-scale equations, we envision this database as a user-friendly and comprehensive resource for researchers and practitioners interested in quantifying standing stocks of biomass based on forest mensuration data.