归一化差异植被指数
植被(病理学)
环境科学
背景(考古学)
蒸汽压差
增强植被指数
叶面积指数
大气科学
空间变异性
降水
自然地理学
气候学
地理
生态学
植被指数
地质学
蒸腾作用
气象学
生物
医学
植物
统计
病理
考古
光合作用
数学
作者
Huanhuan Liu,Yue Liu,Yu Chen,Mengen Fan,Yin Chen,Chengcheng Gang,Yongfa You,Zhuonan Wang
标识
DOI:10.1016/j.agrformet.2023.109327
摘要
The prominent role of drylands in the global ecosystem calls for a deeper understanding of the responses of dryland vegetation to ongoing environmental drivers in the context of global climate change. Here, we first investigated the spatial and temporal trends of global dryland vegetation based on multiple satellite- and model-based indices, including the normalized difference vegetation index (NDVI), leaf area index (LAI), vegetation optical depth (VOD), and gross primary productivity (GPP) during 1988–2018. Then, the impacts of a set of environmental drivers (i.e. mean annual precipitation (MAP), mean annual temperature (MAT), soil moisture (SM), and vapor pressure deficit (VPD)) on vegetation dynamics were quantified using partial correlation analysis and structural equation model. All four indices increased strongly before 2000 but slowed afterward. The variation in dryland vegetation was more related to SM anomaly in comparison with other environmental drivers. The variation induced by SM was amplified by high VOD in some continents. Furthermore, MAT contributed similarly as SM to vegetation dynamics in North America. The four vegetation indices exhibited divergent responses to environmental drivers due to their characteristics. At the continental scale, NDVI was only relevant to variation in VPD in North America. In contrast to NDVI, LAI, and VOD, GPP was more closely associated with the variation in SM and VPD. Roughly half of the GPP variation was attributable to the combination of SM and MAT in North America and Australia, whereas they have low predictive power (∼30%) in Eurasia, Africa, and South America. SM was closely linked to the vegetation changes in grasslands and shrublands; however, this impact varied among the continents. Our results advance the current understanding of dryland vegetation dynamics and shed new light on improving dryland carbon flux simulation by fully considering the role of soil moisture.
科研通智能强力驱动
Strongly Powered by AbleSci AI