首页|Prediction of the Potential Suitable Habitat for Xanthoceras Sorbifolium Bunge Based on MaxEnt Model

Prediction of the Potential Suitable Habitat for Xanthoceras Sorbifolium Bunge Based on MaxEnt Model

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This study integrates MaxEnt ecological niche model with ArcGIS technology to predict the potential suitable habitat for Xanthoceras sorbifolium Bunge in China, based on accurate and effective geographic distribution data. 3 environmental factors, including climate, topography, and soil (comprising 26 environmental variables), were employed to predict the potential suitable habitats for X. sorbifolium, classify the suitable habitats, and assess its adaptability. The results indicate that the potential suitable distribution areas for X. sorbifolium in China can be categorized into high, medium, and low suitable habitats, covering an area of 189.44×10~4 km~2, 162.05×10~4 km~2, and 252.87×10~4 km~2, respectively. These areas account for 19.73%, 16.88%, and 26.34% of China's total land area. The primary environmental factors influencing the distribution of X. sorbifolium. ranked from most to least influential, include annual precipitation, soil pH. average temperature of the coldest quarter, elevation, isothermality, precipitation coefficient of variation, soil organic carbon content, clay mass fraction, percentage of gravel volume, sand content, soil capacity, and maximum temperature of the warmest month. The results of this study provide a scientific basis for the selection and production planning layout of X. sorbifolium ecological cultivation bases.

Xanthoceras sorbifolium BungeMaxEnt modelEnvironmental factorsPotential suitable habitatSuitability assessment

Dawei Zhang、Shicui Fu、Zhonghui Zhang、Zimo Wang、Lu Liu、Fan Yang、Jingqi Yuan、Zhongliang Yu

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Jilin Provincial Academy of Forestry Sciences (Jilin Province Forestry Biological Control Center Station), Changchun, Jilin, 130033, China

Institute of Forestry Inventory and Planning of Jilin Province, Changchun, Jilin, 130000, China

International Conference on Remote Sensing, Mapping, and Image Processing

Xiamen(CN)

International Conference on Remote Sensing, Mapping, and Image Processing

131671P.1-131671P.9

2024