Nebkhas are a unique biogeomorphological landform found across global drylands and coastal environments, providing crucial habitat for biodiversity and preventing land desertification. In this study, for the first time machine-learning based models were used to quantify the biogeomorphological niche of nebkhas and simulate the geographical distribution of Nitraria nebkhas in northern China under climate change. The results indicate that climate variables impact the growth of formative shrub species on nebkhas, while both climate, soil and geomorphological conditions, and their spatial configuration determine the probability of nebkha occurrence in northern China. Under medium and high greenhouse gas emission scenarios, the potential distribution of nebkhas in the study area is projected to shift northward but decrease in the south by the end of the century due to rising temperatures. Given the potential impact of nebkha field degradation on biodiversity and soil hydrological conditions, comprehensive land-use strategies should be designed to protect nebkhas and mitigate the impact of future climate change.
 

灌丛沙丘,机器学习,生物地貌格局,潜在分布,气候环境变化