Study on rare and endangered plants under climate: maxent modeling for identifying hot spots in northwest China

Background: Climate warming has caused substantial changes in temporal and spatial environmental patterns. The study on hot spots of rare endangered plants Northwest China under predicted climate change can provide a scientific reference for the restoration reconstruction those degraded habitats, as well improvement protection system China. Results: Based MaxEnt algorithm, 813 effective distribution records 11 factor variables China, this identified biodiversity hotspots change. results showed that: (1) prediction accuracy model is high, area curve (AUC) 0.876, total suitable potential geographical 137.96×104km2, mainly including Western Southwestern Xinjiang, Southern Gansu, parts Eastern Qinghai Province, Shaanxi Province; (2) altitude, temperature precipitation are main factors affecting China; (3) four scenarios future, with increase emission from low to high forcing, Xinjiang would have most obvious loss which occur Gansu provinces. Conclusion: Under scenario increasing forcing happens that occurs