Spatio-temporal characteristics and driving mechanism of land degradation sensitivity in Northwest China

Sci Total Environ. 2024 Mar 25:918:170403. doi: 10.1016/j.scitotenv.2024.170403. Epub 2024 Feb 1.

Abstract

Northwest China has been experiencing severe land degradation for a long time due to various natural and social elements. Evaluating and analyzing the process of occurrence and driving mechanism of land degradation sensitivity in this area is crucial for enhancing the local ecological environment. In this study, 18 social and environmental elements were used to construct a land degradation sensitivity index (LDSI) evaluation system in the area from vegetation, climate, management, soil, and geomorphology five factors. The spatio-temporal characteristics of LDSI in Northwest China from 2000 to 2020 were evaluated on the basis of analyzing the developmental changes of each factor. Correlation analysis and multiscale geographical weighting regression (MGWR) were used to reveal the driving mechanism of land degradation sensitivity. The results indicated a high level of land degradation sensitivity in Northwest China, with >66 % of the area (190.96 × 104 km2) in the critical sensitive class from 2000 to 2020. But the land degradation sensitivity decreased in 18.52 % of the area (53.58 × 104 km2) from 2000 to 2020, the overall trend was weakening. The spatial distribution mainly showed stronger sensitivity in the northwest and weaker sensitivity in the southeast. By exploring the driving mechanism of land degradation sensitivity, it was found that vegetation and climate showed a strong correlation, with a correlation coefficient >0.8. Drought resistance played a strong role in the dynamic process of land degradation. The basic dynamic elements showed some spatial variability in land degradation in different regions. This study is of significance for land degradation prevention and sustainable development in Northwest China.

Keywords: Driving mechanism; Land degradation sensitivity; Multiscale geographical weighting regression; Northwest China; Spatial and temporal characteristics.