Predicting Polygonum capitatum distribution in China across climate scenarios using MaxEnt modeling

Abstract

Abstract Climate change affects the geographical distribution of species. Predicting the future potential areas suitable for certain species is of great significance for understanding their distribution characteristics and exerting their value. Based on the data of 276 effective distribution points of Polygonum capitatum and 20 ecological factors, the maximum entropy (MaxEnt) model and the ArcGIS software were employed to predict the areas suitable for P. capitatum growth, and the main environmental factors affecting the geographical distribution of this species were explored. Under the current climatic conditions, the areas highly suitable for P. capitatum are mainly distributed in southwestern China, with a small number of sites in coastal areas and most sites in Guizhou Province. Under different climate scenarios, the suitable areas were reduced to varying degrees. The dominant environmental variables affecting the distribution of P. capitatum were precipitation in the driest month, annual precipitation, and elevation, with a cumulative contribution rate of 84.1%. Against the background of a changing climate, the areas suitable for P. capitatum in China will be widely distributed in the southwestern region, with Guizhou Province and Yunnan Province as the main distribution areas; some sites will also be distributed throughout the southwest of Tibet Autonomous Region, the south of Sichuan Province, the north of Guangxi Autonomous Region, and the coastal area of Fujian Province. Optimal conditions for P. capitatum include a dry month precipitation range of 13.4 to 207.3 mm, elevations from 460.3 to 7214.3 m, and annual precipitation between 810 and 1575 mm. Given these insights, we recommend enhanced conservation efforts in current prime habitats and exploring potential cultivation in newly identified suitable regions to ensure the species’ preservation and sustainable use.

Keywords

• Polygonum capitatum
• MaxEnt model
• Climate change
• Habitat suitability
• Traditional Miao medicine