Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

Huiling Tian; Jianhua Zhu; Xiao He; Xinyun Chen; Zunji Jian; Chenyu Li; Qiangxin Ou; Qi Li; Guosheng Huang; Changfu Liu; Wenfa Xiao

首页> 中文期刊> 《森林生态系统：英文版》 >Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

开具论文收录证明 >>

期刊封面封底目录下载 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Estimating the volume growth of forest ecosystems accurately is important for understanding carbon sequestration and achieving carbon neutrality goals.However,the key environmental factors affecting volume growth differ across various scales and plant functional types.This study was,therefore,conducted to estimate the volume growth of Larix and Quercus forests based on national-scale forestry inventory data in China and its influencing factors using random forest algorithms.The results showed that the model performances of volume growth in natural forests(R^(2)=0.65 for Larix and 0.66 for Quercus,respectively)were better than those in planted forests(R^(2)=0.44 for Larix and 0.40 for Quercus,respectively).In both natural and planted forests,the stand age showed a strong relative importance for volume growth(8.6%–66.2%),while the edaphic and climatic variables had a limited relative importance(<6.0%).The relationship between stand age and volume growth was unimodal in natural forests and linear increase in planted Quercus forests.And the specific locations(i.e.,altitude and aspect)of sampling plots exhibited high relative importance for volume growth in planted forests(4.1%–18.2%).Altitude positively affected volume growth in planted Larix forests but controlled volume growth negatively in planted Quercus forests.Similarly,the effects of other environmental factors on volume growth also differed in both stand origins(planted versus natural)and plant functional types(Larix versus Quercus).These results highlighted that the stand age was the most important predictor for volume growth and there were diverse effects of environmental factors on volume growth among stand origins and plant functional types.Our findings will provide a good framework for site-specific recommendations regarding the management practices necessary to maintain the volume growth in China's forest ecosystems.

著录项

来源
《森林生态系统：英文版》 |2022年第3期|396-406|共11页
作者
Huiling Tian; Jianhua Zhu; Xiao He; Xinyun Chen; Zunji Jian; Chenyu Li; Qiangxin Ou; Qi Li; Guosheng Huang; Changfu Liu; Wenfa Xiao;
展开▼
作者单位

Ecology and Nature Conservation Institute Academy of Forestry Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration;

Co-Innovation Center for Sustainable Forestry in Southern China Forestry University;

Institute of Forest Resource Information Techniques Academy of Forestry Laboratory of Forest Management and Growth Modeling Forestry and Grassland Administration;

Academy of Forest Inventory and Planning Forestry and Grassland Administration;

School of Forestry and Landscape Architecture Agricultural University;

展开▼
原文格式 PDF
正文语种 chi
中图分类文摘、索引;
关键词
Stand volume growth; Stand origin; Plant functional type; National forest inventory data; Random forest algorithms;

相似文献

中文文献
外文文献

1. Dynamic Optimization of E--commerce Logistics Network Based on Machine Learning Algorithms [A] . Chen Zou . 2020

Using machine learning algorithms to estimate stand volume growth of Larix and Quercus forests based on national-scale Forest Inventory data in China

摘要

著录项

相似文献

相关主题

期刊订阅