广西林业科学2025，Vol.54Issue(3)：287-293,7.DOI:10.19692/j.issn.1006-1126.20250306
广西钦州湾桐花树生物量模型构建与评价
Constructions and Evaluations for Biomass Models of Aegiceras corniculatum at Qinzhou Bay,Guangxi
摘要
Abstract
In order to rapidly and accurately estimate biomass of Aegiceras corniculatum at Qinzhou bay,Guangxi,stem,leaf,root,above-ground and total biomass were obtained by whole plant harvesting method,and power function and linear predictive models of various A.corniculatum biomass were established based on pre-dictive variables of basal diameter(D),tree height(H)and their derivatives,and fitting and predictive effects of models were evaluated.Results showed that in single-variable predictive models,stem,above-ground and total biomass had stronger correlations with H,and two models taking H as independent variable had higher coeffi-cients of determination(R2)and precision(P),lower mean relative errors(MRE)and relative root mean square errors(RRMSE),which indicated that H had better fitting effects to these biomass.In single-variable predictive models,fitting effect of D on leaf biomass was better than H.Fitting effects of combined-variable predictive models were better than single-variable predictive models.There were stronger correlations among DH2 and stem,root,above-ground and total biomass.Linear models of stem,root and total biomass taking DH2 as inde-pendent variable had the highest R2 and P,lower MRE and RRMSE in the same model,which showed the best fitting effects.Power function model of above-ground biomass taking DH2 as independent variable had the high-est R2 and P,lower MRE and RRMSE in the same model,which showed the best fitting effect.There was stron-ger correlation between DH and leaf biomass.Power function model of leaf biomass taking DH as independent variable had the highest R2 and P,the lowest MRE and RRMSE,which showed the best fitting effect.Combin-ing R2 and three evaluation indexes,the best predictive models of A.corniculatum stem,root and total biomass were linear models taking DH2 as independent variable,the best predictive model of A.corniculatum above-ground biomass was power function model taking DH2 as independent variable,and the best predictive model of A.corniculatum leaf biomass was power function model taking DH as independent variable.关键词
生物量/线性模型/幂函数模型/桐花树Key words
biomass/linear model/power function model/Aegiceras corniculatum分类
农业科技引用本文复制引用
欧芷阳,张继辉,庞世龙,韦海航,杨景竣,梁萍,刘秀..广西钦州湾桐花树生物量模型构建与评价[J].广西林业科学,2025,54(3):287-293,7.基金项目
广西重点研发计划项目(桂科AB23026057) （桂科AB23026057）
中央财政林业科技推广示范项目([2022]TG18号) （[2022]TG18号）
广西林业科技推广示范项目(2023GXLK07) （2023GXLK07）
