Quantifying the contributions of climate change and human activities to grassland dynamics in southwest of China using a spatiotemporally varying residual method
Grasslands in southwestern China (SWC) are among the most fragile ecosystems globally, exhibiting high sensitivity to climate change (CC) and human activities (HA). Disentangling their relative contributions is essential for developing sustainable grassland management strategies. However, grasslands...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2484473 |
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| Summary: | Grasslands in southwestern China (SWC) are among the most fragile ecosystems globally, exhibiting high sensitivity to climate change (CC) and human activities (HA). Disentangling their relative contributions is essential for developing sustainable grassland management strategies. However, grasslands in humid regions have received limited attention, and their spatiotemporal dynamics and drivers remain poorly understood. We comprehensively investigate the spatiotemporal characteristics of grasslands in SWC and decode their dominant drivers using multiple vegetation indices (GPP, LAI, and NDVI) and the spatiotemporally varying residual method. Results indicate that grasslands in SWC have experienced significantly increasing trends in GPP, LAI, and NDVI during 1982–2018, with slopes of 1.28 gC/m2/yr (p < 0.05), 0.003 m2/m2/yr (p < 0.05), and 0.0008/yr (p < 0.001), respectively. The magnitude and trends of these indicators in the karst region were greater than those in the non-karst region. Our findings identify temperature as the dominant climatic factor influencing grassland changes and confirm HA contributing more to grassland dynamics than CC. This study is the first to focus on humid grasslands in a karst-dominated region and highlights their significance in global grassland studies. We provide a reproducible method for quantifying the drivers of global grassland dynamics, supporting decision-makers in formulating global grassland management policies. |
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| ISSN: | 1753-8947 1753-8955 |