文献类型：期刊文献

中文题名：不同气候区日本落叶松通用削度方程构建

英文题名：Construction of universal taper equation of Larix kaempferi in different climatic regions

作者：王溢琨[1] 贾炜玮[1] 陈东升[2] 李丹丹[1] 李泽霖[1]

第一作者：王溢琨

机构：[1]东北林业大学林学院/森林生态系统可持续经营教育部重点实验室,哈尔滨150040;[2]中国林业科学研究院林业研究所,北京100091

年份：2025

卷号：36

期号：1

起止页码：86-94

中文期刊名：应用生态学报

外文期刊名：Chinese Journal of Applied Ecology

收录：;北大核心:【北大核心2023】；

基金：国家重点研发计划项目(2023YFD2200801)资助。

语种：中文

中文关键词：日本落叶松;削度方程;气候响应模型;非线性混合效应模型

外文关键词：Larix kaempferi;taper equation;climate response model;nonlinear mixed-effects model

分类号：TP3

摘要：本研究以辽宁、湖北和甘肃3个地区的78块样地234株日本落叶松为对象,在林业研究中常用的6种削度方程中选取最优的1种作为基础模型,将样地的气候因子通过指数形式添加到其中,构建适用于不同气候区的基础模型、气候响应模型和非线性混合效应模型,研究了不同地区日本落叶松的干形指标,分析干形对气候变量的响应差异,并对比3种模型的拟合精度,选出最优的通用方程。结果表明:在6种常用的削度方程模型中,Kozak模型普适性最好,为最优基础模型;在最优基础模型中同时引入年平均温度和年平均降水量构建气候响应模型,因为综合考虑了不同气候因子对树木干形的影响,树干模型拟合精度有所提高。在气候响应模型中引入不同地区作为随机效应,构建非线性混合效应模型。根据各项模型评价指标和残差图,非线性混合效应模型在所构建的3种模型中拟合精度最高(R~2=0.9874),AIC(6426.04)和BIC(6512.88)值最小,均方根误差(RMSE)较基础模型和气候响应模型分别降低了4.9%和4.0%。因此,非线性混合效应模型可作为描述3个地区日本落叶松树木干形最优的通用削度方程。
Based on 234 Larix kaempferi tree samples from 78 sampling plots across three regions, including Liao-ning, Hubei, and Gansu provinces, we selected the optimal one among the six commonly used taper equations in forestry research to construct a basic model, a climate response model, and a nonlinear mixed-effects model suitable for different climatic regions with the climatic factors being added in an exponential form. We further investigated the stem form indices of L. kaempferi in different regions, analyzed the differences in stem form responses to climatic variables, and selected the optimal universal equation based on the fitting accuracy of the three models. The results showed that Kozak model had the best universality and was the optimal basic model. After simultaneously introducing annual average temperature and annual average precipitation into the optimal basic model to the climate response model, the fitting accuracy of the model was improved by considering the impact of various climatic factors on stem form. Additionally, when different regions were introduced into the nonlinear mixed-effects model as random factors, the fitting accuracy reached the highest(R~2=0.9874) among the three models with the lowest AIC(6426.04) and BIC(6512.88) values according to the evaluation indicators and residual plots. The root-mean-square error was reduced by 4.9% and 4.0% compared with the basic model and climate response model, respectively. Therefore, the nonlinear mixed-effects model could be the optimal universal taper equation for describing stem form of L. kaempferi in the three regions.