Spatiotemporal patterns and driving mechanisms of vegetation in a fragile ecotone: the case of desert steppe in Northern China

The desert steppe is an important transition zone in northern China with high ecological sensitivity. This study used long-term NDVI and climate datasets from 2001 to 2024 and combined trend analysis with a machine-learning-based attribution framework. This combination enables a clearer separation of long-term vegetation trends and the relative contributions of climatic factors and human activities estimated through a residual-based approach. We investigated the spatiotemporal dynamics of NDVI in the desert steppe ecotone, evaluated the persistence of observed vegetation trends under extrapolation, and quantified vegetation responses to climatic factors and human activities estimated using a residual-based approach. The results indicated clear spatial heterogeneity in vegetation distribution across the study area. NDVI demonstrated a significant long-term increasing trend, with an average annual growth rate of 0.004 yr−1. Spatially, 20.40% of the region experienced highly significant improvement, concentrated mainly in the central and southern areas, whereas 3.73% exhibited a declining trend with a scattered distribution. NDVI dynamics showed strong persistence, with more than 81.20% of the region expected to maintain the observed NDVI trend under trend extrapolation, while only a very small proportion (<5%) may continue to exhibit a downward trend. The attribution analysis suggested that climate and non-climatic factors both contributed to NDVI variation, with non-climatic factors showing a relatively larger contribution in some areas. Climatic drivers showed differentiated contributions, and vegetation responded most sensitively and positively to drought index and precipitation. Non-climatic factors showed a relatively stronger positive contribution, particularly in the northern subregion. This study provides a region-specific attribution framework for understanding vegetation dynamics in the desert steppe ecotone and may inform ecological restoration and sustainable management in arid regions.