河北省北部华北落叶松人工林立地指数空间分布预测
更新日期:2021-06-08     浏览次数:243
核心提示:摘要【目的】探究河北省北部华北落叶松人工林立地生产力空间分布格局及其与环境因子的关系,为高效森林经营提供依据。【方法】基于研究区1179块森林资

摘要 【目的】探究河北省北部华北落叶松人工林立地生产力空间分布格局及其与环境因子的关系,为高效森林经营提供依据。【方法】基于研究区1179块森林资源二类调查小班数据,建立以地形、气候和土壤因子为辅助变量的多元线性回归(MLR)、随机森林(RF)、回归克里格(RK)和地理加权回归克里格(GWRK)模型。通过模型评价,选择最优模型预测研究区华北落叶松人工林立地指数(SI)空间分布,采用相关和偏相关分析方法分析SI分布格局与主要环境因子的关系。【结果】海拔、最干月降水、土壤全氮和全磷是影响研究区华北落叶松人工林立地生产力的主要因子;地统计学的2种模型(RK和GWRK)拟合优度相近且均显著高于MLR和RF模型,与全局回归的RK模型相比,局部回归的GWRK模型具有较高的R2(0.780)及较低的AIC(160.533)、RMSE(1.593 m)和MAE(1.113 m),为最优预测模型;不同立地生产力等级地区内SI对地形和土壤因子的变化表现更为敏感,对气候因子的变化反应较弱。【结论】海拔、最干月降水较高以及土壤氮磷含量适中的研究区西北部,是华北落叶松人工林适生区,而海拔、最干月降水较低以及土壤氮磷含量不平衡的东、南部,华北落叶松人工林的适应性较差,可通过造林活动或适当添加氮磷肥削弱环境因子对树木的不利影响。 【Objective】Exploring the spatial distribution of site productivity and analyzing its relationships with environmental factors for Larix principis-rupprechtii plantations are crucial for the effective forest management in the north area of Hebei Province.【Method】based on data from 1179 forest inventory plots distributed across this area,we established multiple linear regression(MLR),random forest(RF),regression Kriging(RK)and geographical weighted regression Kriging(GWRK)models with topographic,climate and soil factors.Through model evaluation,the optimal model was selected to predict the spatial distribution patterns of site index(SI)for L.principis-rupprechtii plantations.The relationships between the distribution pattern of SI and environmental factors were analyzed by correlation and partial correlation analysis.【Result】The major environmental factors influencing site productivity of L.principis-rupprechtii plantations in the study area included elevation(DEM),precipitation of the driest month(BIO14),total soil nitrogen and phosphorus(TN and TP).The values of goodness of fit of the two geostatistical models(RK and GWRK)were similar and both significantly higher than those of MLR and RF models.In contrast to RK model based on global regression,the GWRK model based on local regression had a higher fitting accuracy with R2=0.780,AIC=160.533,RMSE=1.593 m and MAE=1.113 m.The GWRK model based on local regression had a highly predictive power to predict SI of L.principis-rupprechtii plantations in the study area.SI was more sensitive to the variation of topographic and soil factors and less sensitive to the variation of the climate factors across regions with different site productivity classes.【Conclusion】The site with a high growth suitability for L.principis-rupprechtii might tend to occur in the northwest area with a higher elevation,relatively high BIO14 and suitable soil TN and TP contents.However,the site with a low growth suitability for L.principis-rupprechtii were found in the eastern and
作者 李文博 吕振刚 黄选瑞 张志东 Li Wenbo;LüZhengang;Huang Xuanrui;Zhang Zhidong(Hebei Province Key Laboratory of Forest Trees Germplasm Resources and Forest Protection College of Forestry,Agricultural University of Hebei,Baoding 071000;Henan Provincial Institute of Forest Inventory and Planning,Zhengzhou 451200;College of Resource and Environment,Huazhong Agricultural University,Wuhan 430070)
出处 《林业科学》 EI CAS CSCD 北大核心 2021年第3期79-89,共11页 Scientia Silvae Sinicae
基金 国家自然科学基金项目(32071795) 河北省自然科学基金项目(C2020204026) 国家重点研发计划(2017YFD0600403)。
关键词 立地指数 环境因子 地统计学 随机森林 华北落叶松 site index environmental factors geostatistics random forest Larix principis-rupprechtii