文献类型：期刊文献

中文题名：基于立地混合效应的湖南丘陵平原区杉木多形立地指数模型研究

英文题名：Polymorphic Site-Index Model with Site Mixed Effects for Chinese fir Plantations in Hunan Hilly Plains

作者：宋争[1] 黄朗[2] 胡松[2] 张雄清[3] 朱光玉[2]

第一作者：宋争

机构：[1]中国林业科学研究院林业科技信息研究所,北京100091;[2]中南林业科技大学林学院,湖南长沙410004;[3]中国林业科学研究院林业研究所,北京100091

年份：2022

卷号：35

期号：5

起止页码：172-179

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2021_2022】；

基金：国家林草局青拔项目(2019132605)。

语种：中文

中文关键词：杉木;立地效应;立地指数模型;混合效应模型

外文关键词：Chinese fir;site effect;site index model;mixed effects model

分类号：S758

摘要：[目的]研究林分立地因子对立地指数的影响,构建含立地混合效应的立地指数模型,以解决区域性立地指数模型精度低的问题。[方法]基于湖南丘陵平原地区360组杉木平均优势木高-年龄数据,利用数量化方法Ⅰ对影响林分优势高生长的立地因子进行显著性分析,并选取P<0.05的立地因子作为主导因子;采用8种常用的立地指数方程进行基础模型选择,以主导立地因子及其组合作随机效应,确定包含立地效应的立地指数模型。运用AIC、BIC、Log-likelihood和R^(2)等4个评价指标比较不同组合类型的模拟精度,选取最优随机效应组合。采用K-means聚类划分立地类型组,以解决复杂立地类型的模型应用问题。[结果]1)基于数量化方法Ⅰ的显著性分析结果显示:对林分优势高具有显著影响的立地因子有海拔、坡度、坡向与土壤类型,其显著性顺序为土壤类型>海拔>坡向>坡度。2)10个候选基础模型的拟合精度均较低(R^(2)=0.4243~0.5644),本研究选取M4(R^(2)=0.5644)作为构建多形立地指数曲线的基础模型。3)将不同立地因子及其组合作随机效应构建非线性混合模型,确定系数R^(2)从0.4243~0.5644提高到0.5655~0.8089,模型拟合精度的高低与主导立地因子的显著性紧密相关,其中含立地类型的混合模型模拟精度最高(R^(2)=0.8089)。4)以确定系数≥0.99为聚类精度标准,将研究区立地类型划分为11个立地类型组,含立地类型组的混合模型在便于应用的同时,提高了建模精度(R^(2)=0.8117)。[结论]含立地随机效应的立地指数曲线模型可以显著提高区域复杂立地类型的立地建模精度。
[Objective]To improve regional site index model,the site index model with the random effects of site factors was developed.[Method]Based on the 360 samples with dominant height-age of Chinese fir in the hilly and plain area of Hunan Province,the quantification method I was used to select the site factors affecting the dominant height growth(P<0.05).The 8 commonly used models were used to develop the basic site index model,as well as the models considering the random effects of site factors and their combinations.The evaluation statistics including AIC,BIC,Log-likelihood and R^(2)were used to select the optimal random effect model.In addition,K-means clustering was used to divide site type groups for model applications.[Results]1)The site factors including altitude,slope,aspect and soil type had significant impact on dominant height growth based on the quantitative method I.And soil type was the most important factor,following by altitude,slope aspect,and Slope.2)The fitting accuracy of the 8 candidate basic models was low(R^(2)=0.4243~0.5644).M4(R^(2)=0.5644)was selected the best basic model for developing the polymorphic site index curve.3)Considering the influence of the site effect on the site index,the nonlinear mixed effects models with different site factors and their combination of random effects were developed.The mixed effects model with the random effects of site type performed the best(R^(2)=0.8089).4)The site types were divided into 11 site groups.The mixed model containing the site type groups improved the modeling accuracy(R^(2)=0.8117).[Conclusion]The site index model with site mixed effect can significantly improve the site modeling accuracy of regional complex site types,and provide a reference and basis for regional forest site quality evaluation.