The Allometry of Coarse Root Biomass: Log-Transformed Linear Regression or Nonlinear Regression?
作 者：Lai JS, Yang B, Lin DM, Kerkhoff AJ, Ma KP*
影响因子：3.73
刊物名称：PLoS One
出版年份：2013
卷：8 期：10 页码：e77007
论文摘要：
Precise estimation ofrootbiomassis important for understanding carbon stocks and dynamics in forests. Traditionally,biomassestimates are based on allometric scaling relationships between stem diameter andcoarserootbiomasscalculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-rootbiomassallometry. We then contrast model predictions by estimating standcoarserootbiomassbased on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict knownrootbiomassvalues measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-rootbiomassscaling models. More importantly, inappropriately using NLR leads to grossly inaccurate standbiomassestimates, especially for stands dominated by smaller trees.
