详细信息
基于混合效应模型及生存分析方法的落叶松云冷杉林单木生存模型研究 被引量:2
Study on single tree survival model of mixed stands of Larix olgensis,Abies nephrolepis and Picea jazoensis based on mixed effect model and survival analysis method
文献类型:期刊文献
中文题名:基于混合效应模型及生存分析方法的落叶松云冷杉林单木生存模型研究
英文题名:Study on single tree survival model of mixed stands of Larix olgensis,Abies nephrolepis and Picea jazoensis based on mixed effect model and survival analysis method
第一作者:李春明
机构:[1]中国林业科学研究院资源信息研究所,国家林业和草原局森林经营与生长模拟重点实验室,北京100091;[2]长白山森工集团有限公司汪清林业分公司,吉林汪清133200
年份:2022
卷号:44
期号:1
起止页码:1-8
中文期刊名:北京林业大学学报
外文期刊名:Journal of Beijing Forestry University
收录:CSTPCD;;北大核心:【北大核心2020】;CSCD:【CSCD2021_2022】;
基金:国家自然科学基金面上项目(31870624)。
语种:中文
中文关键词:混合效应模型;生存分析方法;随机效应;生存时间;落叶松云冷杉林
外文关键词:mixed effect model;survival analysis method;random effect;survival time;mixed stands of Larix olgensis,Abies nephrolepis and Picea jazoensis
分类号:S791.22
摘要:【目的】准确预测林木的生存和枯损是森林生长收获模型系统中十分重要的组成部分。构建基于混合效应模型和生存分析方法相结合的林木生存模型,能够提高林木枯损模型的精度。【方法】以吉林省汪清林业局20块落叶松云冷杉林样地数据为例,基于生存分析方法中常用的6个时间参数分布回归模型(指数分布、Weibull分布、对数正态分布、对数Logistic分布、Gompertz分布及Gamma分布),把林分因子和立地因子作为协变量加入到模型中去,构建林木生存模型。并在此基础上考虑样地的随机效应,并与传统模型的模拟效果进行比较。【结果】研究结果表明,随着单木初始胸径的增加,其枯损的风险降低,生存率提高;随着单木大于对象木断面积值的增加,其枯损的风险增加,生存率降低;随着林分密度的增加,林木枯损的概率增加,生存率降低;立地因子对林木的生存没有显著影响;6个参数分布回归模型中,Weibull分布的模拟精度最高。与固定效应模型相比,Weibull分布模型在考虑样地水平随机效应后,模型的模拟精度获得明显的提高,并且达到极显著程度。【结论】在森林经营中,要提高林木的生存率,需采取科学合理的经营方法和经营时间,避免使林分的密度过大。
[Objective]Accurate prediction of tree mortality is a very important part of forest growth and yield model system.Constructing a tree survival model based on mixed effect model and survival analysis method can improve the precision of tree mortality model.[Method]Taking the data of 20 sample plots of mixed stands of Larix olgensis,Abies nephrolepis and Picea jazoensis in Wangqing Forestry Bureau of Jilin Province,northeastern China as the example,the tree mortality and survival model was constructed based on 6 parameter distribution models of survival analysis method(exponential distribution,Weibull distribution,log-normal distribution,log-Logistic distribution,Gompertz distribution,Gamma distribution),stand factor and site factor were added into the model as covariates.The sample plot’s random effect was considered and compared with the simulation effect of the traditional model.[Result]With the increase of initial DBH,the risk of tree mortality decreased and the survival rate increased;with the increase of BAL,the risk of mortality increased and the survival rate decreased;with the increase of stand density per hectare,the probability of tree mortality increased and the survival rate decreased;the good-fitness of Weibull distribution model was the best;compared with the fixed effect model,the simulation accuracy of Weibull distribution model was greatly improved after considering the sample plot’s random effect,and reached a very significant degree.[Conclusion]In forest management,if we want to improve the survival rate of trees,we should adopt scientific and reasonable management methods and management time to avoid excessive stand density.
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