森林工程2025，Vol.41Issue(5)：871-882,12.DOI:10.7525/j.issn.1006-8023.2025.05.001
帽儿山天然林进界模型及影响因素分析
Analysis of the Ingrowth Model and Influencing Factors for the Natural Forests of Maoer Mountain
摘要
Abstract
Forest stand ingrowth is a critical component of the dynamic growth process of forest stands,essential for maintaining biodiversity and community structure stability in forest resources.Based on data from 61 plots established at the Maoer Mountain Experimental Forest Farm,this study considered factors such as stand characteristics and biodiver-sity.Through Kendall-Tau-b correlation coefficient analysis and selection of the most suitable variables considering mul-ticollinearity among variables,models for ingrowth were constructed using Poisson,negative binomial(NB),zero-in-flated,and Hurdle models.The contribution rate of variables was analyzed using hierarchical partitioning to identify key factors influencing the ingrowth model.The results showed that stand density(K),arithmetic mean diameter at breast height(d),Simpson's index,and mean stand height(MH)were significant factors affecting the number of ingrowth trees per hectare(Nn).Comparing models using AIC,BIC,and Loglike criteria,it was found that ZINB and HNB sig-nificantly outperformed other models.The Vuong test further revealed that the negative binomial models and their com-posite models(ZINB,HNB)performed better than Poisson models and their composites(ZIP,HP)in fitting the in-growth quantity of natural forests in Maoer Mountain,with the ZINB model slightly outperforming the HNB model.There-fore,the ZINB model was the optimal model for fitting the ingrowth quantity of natural forest stands in Maoer Mountain,a conclusion also supported by ten-fold cross-validation.Additionally,hierarchical partitioning analysis indicated that the Simpson's index and mean stand height(MH)contributed most to the count and zero parts,respectively,of the opti-mal ingrowth model(ZINB).The natural forest ingrowth model constructed by this research has a certain statistical reli-ability and can be used for ingrowth prediction in the Maoer Mountain area,providing a scientific basis for local natural forest regeneration management.关键词
进界/Kendall-Tau-b/零膨胀模型/Hurdle模型/层次分割Key words
Ingrowth/Kendall-Tau-b/zero-inflated model/Hurdle model/hierarchical partitioning分类
农业科技引用本文复制引用
刘佳琦,董利虎,苗铮..帽儿山天然林进界模型及影响因素分析[J].森林工程,2025,41(5):871-882,12.基金项目
"十四五"国家重点研发计划项目(2022YFD2201000) （2022YFD2201000）
国家自然科学基金面上项目(31971649). （31971649）
