Combining In Situ and Remote-Sensing Data to Assess the Spatial Pattern and Changes of Major Grassland Types in Xinjiang, China, Under Climate Change Scenarios

Examining the long-term spatiotemporal distribution of grassland types and their transitions is crucial for better understanding regional and global changes. Most research in this field has examined the spatial distribution, temporal dynamics of grasslands, and their causes as a unified entity. This study predicted the distribution of nine major grassland types in Xinjiang under three climate change scenarios from 2041 to 2100 based on 1980s grassland maps, field data in 2023, and 28 factors. The total area of the nine grassland types showed a decreasing trend from 2041 to 2100. The lowland meadow (LM), temperate meadow steppe (TMS), temperate steppe desert (TSD), temperate desert steppe (TDS), and mountain meadow (MM) expanded, while significant declines occurred in alpine meadow (AM), alpine steppe (AS), temperate desert (TD), and temperate steppe (TS). Among cumulative contribution rate of the 28 factors examined in this study, NDVI, vegetation type, slope, elevation, soil_symbol, soil_ph, Bio1, Bio5, Bio8, Bio9, Bio10, Bio12, Bio13, Bio15, and Bio18 played important roles in most grassland types. LM, TD, and AS grassland were found to be more sensitive to E (environment), while AM, TDS, and TSD were more influenced by T (temperature). The distributions of MM and TMS are significantly influenced by the combined effects of all three categories of factors. For TS, the impacts of both temperature and environmental factors are substantial. These findings provided a robust foundation for conservation planning and the sustainable management of grassland ecosystems in temperate and alpine regions.