DOI: 10.3390/f17070764 ISSN: 1999-4907

Maximum Entropy Modeling Predicts Factors Influencing Ecological Suitability of the Plant Trillium camschatcense in Northeast China

Hongtao Jin, Peng Ding, Diankun Shao, Su Yan, Qingru Yang, Hongyao Yu, Hongxin Li, Shuang Lu, Zhihui Luan, Yitong Wang

Trillium camschatcense, a plant renowned for its ecological and medicinal value, is predominantly found in the temperate forests of East Asia. However, its habitat is increasingly threatened from climate change, habitat fragmentation, and intensified human activities. In this study, the Maxent (Maximum Entropy) model was used to assess the current ecological suitability of T. camschatcense based on historical climate data (1970–2000), and further simulate its potential distribution shifts under multiple future climate change scenarios to predict long-term habitat variation trends across northeast China.All modeling and spatial mapping analyses were performed using MaxEnt and ArcGIS 10.8.1 software. Drawing upon 93 known distribution points and 26 pertinent environmental variables covering climate, soil, and elevation, we built species distribution models for both present and future periods to pinpoint the crucial environmental factors influencing its distribution. Our findings revealed that elevation, soil nitrogen content, seasonal temperatures, annual precipitation, mean temperature during the coldest quarter, and mean diurnal temperature range were the primary factors influencing the distribution of T. camschatcense. Notably, highly suitable habitats were predominantly concentrated in Baishan City and the southwestern region of Yanbian Korean Autonomous Prefecture in Jilin Province. This insight offers valuable scientific guidance for the conservation planning, sustainable utilization, and potential introduction and cultivation of T. camschatcense. Furthermore, targeted conservation strategies can help identify climate refugia and protect climatically stable habitats for the long-term persistence and resilience of the species under continuous global warming.

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