Prediction of Potential Forest Risk Areas for Phytopythium helicoides in China Under Climate Change Based on Maximum Entropy Modeling

Despite the growing threat of Pythium helicoides to forest plantations in China, a nationwide assessment of climatic suitability remains unavailable, limiting the development of preventive strategies. This study applied the Maximum Entropy model combined with geographic information system analysis to predict the potential distribution and suitable habitats of the pathogen across China. The model was constructed using occurrence records from the Global Biodiversity Information Facility and published literature, together with bioclimatic, topographic, and soil variables. Simulations were performed under current and future climate conditions throughout the twenty-first century across low, medium, and high emission scenarios. The model performed reliably, with Area Under the Curve values indicating favorable predictive accuracy across all periods. Habitat suitability was governed primarily by precipitation of the driest month, temperature annual range, and elevation. Under current conditions, highly suitable areas are concentrated in tropical and subtropical monsoon regions, particularly eastern Hainan and Taiwan. Under future scenarios, suitable habitats are projected to shift toward warm temperate regions while contracting overall, with plains, basin floors, and valleys retaining high suitability due to favorable moisture retention. Windward mountain slopes are generally unsuitable, although scattered medium-suitable habitats may form in lower-lying depressions with gentler slopes.

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Publication Details

Journal
Forests
Published
2026-05-21
DOI
https://doi.org/10.3390/f17050626
Primary Topic
Plant Pathogens and Resistance
Type
article
Field-Weighted Citation Impact
0.00

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article

Prediction of Potential Forest Risk Areas for Phytopythium helicoides in China Under Climate Change Based on Maximum Entropy Modeling

Yuzhe Kong, Chun Yang, Size Dai, Qing Chen et al.
Forests
Plant Pathogens and Resistance
article

Prediction of Potential Forest Risk Areas for Phytopythium helicoides in China Under Climate Change Based on Maximum Entropy Modeling

Yuzhe Kong, Chun Yang, Size Dai, Qing Chen, Tingting Dai, Binbin Jiao
article en

Abstract

Despite the growing threat of Pythium helicoides to forest plantations in China, a nationwide assessment of climatic suitability remains unavailable, limiting the development of preventive strategies. This study applied the Maximum Entropy model combined with geographic information system analysis to predict the potential distribution and suitable habitats of the pathogen across China. The model was constructed using occurrence records from the Global Biodiversity Information Facility and published literature, together with bioclimatic, topographic, and soil variables. Simulations were performed under current and future climate conditions throughout the twenty-first century across low, medium, and high emission scenarios. The model performed reliably, with Area Under the Curve values indicating favorable predictive accuracy across all periods. Habitat suitability was governed primarily by precipitation of the driest month, temperature annual range, and elevation. Under current conditions, highly suitable areas are concentrated in tropical and subtropical monsoon regions, particularly eastern Hainan and Taiwan. Under future scenarios, suitable habitats are projected to shift toward warm temperate regions while contracting overall, with plains, basin floors, and valleys retaining high suitability due to favorable moisture retention. Windward mountain slopes are generally unsuitable, although scattered medium-suitable habitats may form in lower-lying depressions with gentler slopes.

ForestsVol. 17(5)
Nanjing Forestry University (CN), Shanghai Customs College (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Priority Academic Program Development of Jiangsu Higher Education Institutions, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 7%
Plant Pathogens and Resistance
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