Potential geographical distribution and environmental explanations of rare and endangered plant species through combined modelling: A case study of Northwest Yunnan, China

In recent decades, due to the effect of climate change and the interference of human activities, the species habitat index fallen 2%. Studying the geographical distribution pattern and predicting the potential geographical distribution of species are of great significance for developing scientific and effective biodiversity conservation strategies. The purpose of this research is to predict the potential geographical distribution of 25 rare and endangered plant species in Northwest Yunnan, China on the grid map with a resolution of 0.05° × 0.05° and analyze the explanation capabilities of various environmental factors on the potential geographical distribution patterns of these species, and explore the main restrictive environmental factors. Initially, we employed the ecological niche model MaxEnt to predict the potential geographical distribution of target species. Following that, we overlaid the potential geographical distribution of each species, and we obtained the potential geographical distribution pattern of species richness on the spatial scale of the ecological niche model with a resolution of 0.05° × 0.05°. Ultimately, we also adopted geographically weighted regression (GWR) model to investigate the explanation capabilities of various environmental parameters on the potential distribution patterns. The results showed that the average AUC value of each species was between 0.80 and 1.00, which indicated that the simulation precision of the MaxEnt model for each species was good or excellent. Besides, the potential distribution areas of these species were between 826.33 km2 and 44,963.53 km2. In addition, the average contribution values of the annual precipitation (Bio12), precipitation of coldest quarter (Bio19) and population density (Pop) were 25.92%, 15.86% and 17.95%, respectively. Moreover, the goodness of fit R2 and AIC value of the water model were 0.88 and 7,703.82, respectively, which indicated the water factor largely influenced the potential distribution of these species. The results of this study would be helpful for implementing long-term conservation and reintroduction for these species.