西南林业大学学报2024，Vol.44Issue(5)：138-147,10.DOI:10.11929/j.swfu.202308032
湖北杉木人工林生物量及其可变密度预估模型研究
Biomass and Variable Density Prediction Model of Cunninghamia lanceolata Plantation in Hubei Province
摘要
Abstract
In order to study the biomass and the change law of Cunninghamia lanceolata plantation in Hubei province,the data of 190 standard plots and the biomass of 517 samples of plantations aged from 6 to 59 years were used.The biomass per unit area of each stand was calculated based on the established biomass estimation equation of single tree and the optimal biomass estimation equation of whole stand was constructed and selected based on the age of stand,site index and 7 different stand density indexes.The results showed that the average biomass of C.lanceolata plantation was 52.8893 kg.The goodness of fit of two-unit biomass equations with DBH and tree height as variables were 0.91,respectively,and it had higher goodness of fit and accuracy.The average biomass per unit area of the stands was 101.4923 t/hm2,which increased with the increase of the age of the stands.Based on the empirical equation of multiple regression technique,a total of 16 stand biomass prediction models with 7 stand density indexes and without density indexes were constructed.The model with the stand density in-dex including the number of standing trees and the size of trees achieved a better fitting effect than others.The Schumacher modified harvest model of the density index SDI had the highest accuracy,with R2 of 0.95,and the test accuracy of 97％.It had good applicability to estimating the biomass of Chinese fir in this region,and could provide reference and support for the management and quality improvement of its plantation.关键词
杉木/人工林/生物量/林分密度/林分模型Key words
Cunninghamia lanceolata/plantation/biomass/stand density index/stand model分类
农业科技引用本文复制引用
杜超群,袁慧,林虎,刘华,许业洲..湖北杉木人工林生物量及其可变密度预估模型研究[J].西南林业大学学报,2024,44(5):138-147,10.基金项目
国家重点研发项目子课题(2021YFD2201304)资助 （2021YFD2201304）
湖北省林业科技支撑项目([2022]LYKJ03)资助. （[2022]LYKJ03）
