摘要
为揭示羌塘草原2001—2020年植被时空变化格局及其影响因素,并预测气候变化条件下羌塘草原植被可能的变化趋势,本研究基于MODIS NDVI数据以及温度、降水和风速数据,探究了羌塘草原植被覆盖变化与气象因子的关系;利用随机森林、支持向量机和随机梯度下降回归3种机器学习算法建立NDVI预测模型,筛选模拟精度最优模型,进行多情景下植被变化模拟。结果表明:2001—2020年羌塘草原NDVI呈现轻微增加趋势,增长率为0.0003 a^(-1)。NDVI对温度的响应滞后3个月,降水滞后0~1个月,NDVI与风速呈负相关且无滞后。随机森林算法的模拟精度最高(Adjusted R^(2)=0.958)。未来植被覆盖度整体提升的情景是增温1.0℃、降水增加25%、风速降低25%。研究结果有助于预警植被退化问题,为气候变化背景下该区域植被生态保护提供科学依据。
This study aimed to reveal the spatiotemporal variations and the influencing factors of vegetation in the Qiangtang grassland during 2001-2020,and to predict the change trends of vegetation under climate change scenarios.Based on the data of MODIS NDVI,temperature,precipitation,and wind speed,we explored the relationship between vegetation changes and meteorological factors.Furthermore,NDVI prediction models were establish with three machine learning algorithms of random forest,support vector machine,and random gradient descent regression.The optimal model with the best simulation accuracy was selected to simulate vegetation changes under multiple scenarios.We found that NDVI of the Qiangtang grassland showed a slight increasing trend with a growth rate of 0.0003 a^(-1)from 2001 to 2020.The response of NDVI to temperature lagged by 3 months,precipitation lagged by 0-1 months.NDVI was negatively correlated with wind speed without lag.The random forest algorithm had the highest simulation accuracy(Adjusted R^(2)=0.958).The scenario for improvement of vegetation coverage in the future included 1.0℃increase in temperature,25%increase in precipitation,and 25%decrease in wind speed.This study contributed to early warning of vegetation degradation,which would help vegetation conservation under climate change.
作者
李彩琳
宋彦涛
张靖
乌云娜
孙磊
LI Cailin;SONG Yantao;ZHANG Jing;WU Yunna;SUN Lei(College of Environment and Bioresources,Dalian Minzu University,Dalian 116600,Liaoning,China;College of Animal Science,Xizang Agricultural and Animal Husbandry University,Nyingchi 860000,Tibet,China)
出处
《生态学杂志》
CAS
CSCD
北大核心
2024年第6期1664-1673,共10页
Chinese Journal of Ecology
基金
大连民族大学-西藏农牧学院联合基金项目(DLMZ-NMXY2021002)
国家民委中青年英才培养计划项目(2022)
中央高校基本科研业务费(2024)资助。
关键词
羌塘草原
归一化植被指数
随机森林
多情景模拟
Qiangtang grassland
normalized difference vegetation index
random forest
multi-scenario prediction
作者简介
李彩琳,女,1997年生,硕士研究生,主要研究方向为生态系统评估。E-mail:lcl8897156@foxmail.com;通信作者:宋彦涛,E-mail:songyantao@dlnu.edu.cn。
