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

作　　者：杜超群[1] 袁慧 林虎 刘华 许业洲[1] Du Chaoqun;Yuan Hui;Lin Hu;Liu Hua;Xu Yezhou(Hubei Academy of Forestry,Wuhan Hubei 430075,China;Taizishan Forest Farm Adminiatration Bureau,Jingshan Hubei 431822,China;Forest seed and seedling management Station of Hubei Forestry Bureau,Wuhan Hubei 430075,China)

机构地区：[1]湖北省林业科学研究院,湖北武汉430079 [2]湖北省太子山林场管理局,湖北京山431822 [3]湖北省林业局林木种苗管理总站,湖北武汉430079

出　　处：《西南林业大学学报（自然科学）》2024年第3期138-147,共10页Journal of Southwest Forestry University：Natural Sciences

基　　金：国家重点研发项目子课题(2021YFD2201304)资助;湖北省林业科技支撑项目([2022]LYKJ03)资助。

摘　　要：利用6~59年生杉木人工林190个标准地资料和517株样木生物量测定数据,以建立的单木生物量估算方程为基础推算出各林分单位面积生物量,并基于林龄、立地指数以及7种不同林分密度指标构建并选择最优的全林分生物量预估方程,研究湖北杉木人工林林分生物量及其变化规律。结果表明:该区域杉木人工林平均单株生物量为52.8893 kg,以胸径和树高为变量的二元单木生物量方程的拟合优度为0.91,其拟合优度和精度更高;林分平均单位面积生物量为101.4923 t/hm^(2),总体上呈随林龄增加而增大的趋势;基于多元回归技术的经验方程构建了含7个林分密度指标和不含密度指标共计16种林分生物量预估模型,包含林分立木株数和林木大小信息的林分密度指标的模型均达到了较理想的拟合效果,其中密度指数SDI的Schumacher修正收获模型精度最高,确定系数为0.95,检验精度为97%,对本区域杉木生物量估算具有较好的适用性,能为其人工林经营和质量提升提供参考与支持。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/hm^(2),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 index 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 

分 类 号：S722.83[农业科学—林木遗传育种]