Abstract
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.
| Original language | English |
|---|---|
| Article number | 109327 |
| Journal | Agricultural and Forest Meteorology |
| Volume | 331 |
| DOIs | |
| State | Published - Mar 15 2023 |
| Externally published | Yes |
Funding
This work was supported by the National Natural Science Foundation of China ( 31602004 ), the Natural Science Foundation of Shaanxi Province ( 2021JQ-171 ), the CAS “Light of West China” program ( XAB2016B05 ), and the Key Laboratory of Disaster Prevention and Mitigation of Qinghai Province ( QFZ-2021-Z06 ).
Keywords
- Dryland vegetation
- Soil moisture
- Structural equation model (SEM)
- Vapor pressure deficit (VPD)
- Vegetation indices