资源环境科技发展态势分析平台

Selected allometric equations and fitting strategies were evaluated for their predictive abilities for estimating above ground biomass for seven species of shrubs common to northeastern California. Size classes for woody biomass were categorized as 1-h fuels (0.1-0.6 cm), 10-h fuels (0.6-2.5 cm), 100-h fuels (2.57.6 cm), and 1000-h fuels (greater than 7.7 cm in diameter). Three fitting strategies were evaluated weighted nonlinear least squares regression (WNLS), seemingly unrelated regression (SUR), and multinomial log-linear regression (MLR) - to estimate individual shrub biomass as a function of crown area. The inclusion of the shrub height as a covariate did not increase the accuracy of prediction for all species. When MLR was used, on the average, RMSE values were reduced by 23.1% for the 1-h component, by 23.9% for the 10-h component, and by 45.6% for the leaf component for serviceberry when compared to SUR Based on the residual plots and cross-validation fit statistics, MLR is recommended for estimating AGB for seven major shrub species in California. The equation coefficients are documented for future use. (C) 2017 Elsevier B.V. All rights reserved.