Yang Chen , Long Ma , Xixi Wang , Tingxi Liu , Zixu Qiao
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引用次数: 0
Abstract
Desertification remains a critical global ecological and environmental challenge that threatens sustainable development. Although our understanding of desertification dynamics and their underlying drivers has improved, continued research is needed due to the region-specific nature of these processes. This study focuses on the Western Inner Mongolia Plateau in China as a case study to examine the evolution of desertification and its driving factors using a multifaceted approach, including the Mediterranean Desertification and Land Use (MEDALUS) model. Results show that the desertification sensitivity index (DSI) across the plateau ranged from 1.12 in prairie regions to 1.87 in desert areas, with a spatial gradient decreasing from west to east. Overall, the DSI exhibited a declining trend over the study period, though some areas showed localized degradation. Between 2001 and 2020, the DSI decreased across approximately 64 % of the plateau, with approximately 23 % (primarily desert regions) experiencing a significant reduction. In contrast, 36 % of the area, particularly the southeastern grasslands, saw an increase in DSI. Among the examined factors, seven—precipitation, normalized difference vegetation index (NDVI), leaf area index(LAI), drought resistance, erosion protection, fire risk, and land-use intensity—demonstrated high explanatory power greater than 0.6, highlighting their significant positive or negative impact on desertification. Additional factors such as temperature, sunshine duration, and potential evapotranspiration also influenced desertification, albeit to a lesser extent. Notably, interactions among these variables played a crucial role in shaping desertification trends. Addressing desertification, therefore, requires integrated strategies that account for the complex interplay of soil, climate, vegetation, and land management.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.