摘要
净初级生产力(net primary production,NPP)是衡量生态系统碳循环的重要指标。文章基于MOD17A3HGF数据和气象数据,利用Theil-Sen Median趋势分析、重心模型和相关性分析等方法对云南省2011—2020年NPP时空变化特征和影响因素进行研究,并定量区分人类活动和气候变化对植被的影响。结果表明:2011—2020年云南省NPP在空间上呈自西向东、自南向北逐渐下降的分布特征,平均值为1025.22 gC·m^(-2)·a^(-1);高波动区主要分布在迪庆藏族自治州和怒江傈僳族自治州;NPP与气温显著相关区域主要分布在滇东地区,与降水显著相关区域主要分布在滇中和滇东北地区;影响研究区植被恢复的因子顺序为:气候变化>气候变化与人类活动共同作用>人类活动;影响研究区植被退化的因子顺序为:人类活动>气候变化与人类活动共同作用>气候变化。
Net primary production(NPP)serves as a crucial metric for assessing the carbon cycling within ecosystems.Based on MOD17A3HGF data and meteorological data,we use Theil-Sen Median trend analysis,centroid modeling and correlation analysis to analyze the spatiotemporal patterns and influencing factors of NPP in Yunnan province from 2011 to 2020.The results reveal that:from 2011 to 2020,NPP in Yunnan province displays a declining spatial distribution trend from west to east and from south to north,with an average value of 1025.22 gC·m^(-2)·a^(-1);the high fluctuation area is mainly distributed in Diqing Tibetan autonomous prefecture and Nujiang Lisu autonomous prefecture;the significant correlation between NPP and temperature is mainly distributed in eastern Yunnan,and the significant correlation between NPP and precipitation is mainly distributed in central and northeast Yunnan.The order of factors influencing vegetation recovery in the study area is:climate change>combined impact of climate change and human activities>human activities.In terms of vegetation degradation,the sequence of factors is:human activities>combined impact of climate change and human activities>climate change.
作者
郑洁茹
温兴平
王俊霖
赵一璐
曹毅
ZHENG Jieru;WEN Xingping;WANG Junlin;ZHAO Yilu;CAO Yi(Faculty of Land Resources Engineering,Kunming University of Science and Technology,Kunming 650093,China;Mineral Resources Prediction and Evaluation Engineering Laboratory of Yunnan Province,Kunming 650093,China)
出处
《遥感信息》
CSCD
北大核心
2024年第1期93-103,共11页
Remote Sensing Information
基金
国家自然科学基金(41101343)。
关键词
NPP
重心模型
时空变化
影响因素
人类活动
云南省
net primary production
center of gravity model
spatial-temporal variation
influencing factor
human activity
Yunnan province
