浙江农林大学学报2025，Vol.42Issue(6)：1122-1131,10.DOI:10.11833/j.issn.2095-0756.20240512
2种异速生物量模型精度评估
Accuracy evaluation of 2 allometric biomass models
摘要
Abstract
[Objective]The objective is to study the 2 basic models for estimating forest biomass:constant allometric ratio(CAR)model and variable allometric ratio(VAR)model,and compare the prediction accuracy(P)of the models,so as to provide reliable theoretical and technical support for forest biomass monitoring.[Method]Based on the biomass survey data of 50 Larix gmelinii trees in 18 fixed sample plots of Pangu Forest Farm in Daxing'an Mountains,a nonlinear seemingly uncorrelated regression method was used to construct the additive biomass models of CAR and VAR and to compare and evaluate the univariate and binary models of the 2 model forms.[Result](1)In the univariate model,the total biomass of the CAR model and the adjusted coefficient of determination(R2a)of each component biomass model were both greater than those of the VAR model,with an average increase of about 0.003.In the binary model,the CAR model also had a larger R2a.(2)From the model test index,the prediction accuracy of the 2 models in the univariate model was greater than 97.6%,and the prediction accuracy of the CAR model was higher.The prediction accuracy of the binary model was greater than 96.9%,and the prediction accuracy of the CAR model was higher.(3)There was a correlation between the size of stand diameter class and the goodness of fit of the model,and the model was generally more suitable for smaller diameter stands.[Conclusion]In both the univariate and binary models of total biomass and component biomass of trees,the CAR model has better fitting and model testing indexes than the VAR model,and the CAR model has better fitting and prediction effects on forest biomass.The fitting effect of small-diameter trees is better than that of large diameter trees.In general,the CAR model is not only simpler in form,but also performs better in fitting effect and estimation accuracy,which can provide a theoretical basis for estimating the biomass of L.gmelinii in Daxing'an Mountains.[Ch,5 fig.5 tab.31 ref.].关键词
兴安落叶松/恒定异速生长比(CAR)模型/可变异速生长比(VAR模型)/单木生物量Key words
Larix gmelinii/constant allometric ratio(CAR)model/variable allometric ratio(VAR)model/single tree biomass分类
农业科技引用本文复制引用
WANG Yi,MEI Xuesong,YUAN Ye,ZHU Wancai,DONG Lingbo..2种异速生物量模型精度评估[J].浙江农林大学学报,2025,42(6):1122-1131,10.基金项目
国家重点研发计划项目(2022YFD2200502) （2022YFD2200502）
黑龙江省省属科研院所科研业务费(CZKYF2024-1-B013,CZKYF2020-1-C031) （CZKYF2024-1-B013,CZKYF2020-1-C031）
