Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model

<i>Phytophthora cinnamomi</i> is a globally distributed plant-pathogenic oomycete that threatens economically important crops, including <i>Lauraceae</i>, <i>Bromeliaceae</i>, <i>Fabaceae</i>, and <i>Solanaceae</i>. Utilizing species occurr...

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Bibliographic Details
Main Authors: Xiaorui Zhang, Haiwen Wang, Tingting Dai
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Agriculture
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Online Access:https://www.mdpi.com/2077-0472/15/13/1411
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Summary:<i>Phytophthora cinnamomi</i> is a globally distributed plant-pathogenic oomycete that threatens economically important crops, including <i>Lauraceae</i>, <i>Bromeliaceae</i>, <i>Fabaceae</i>, and <i>Solanaceae</i>. Utilizing species occurrence records and 35 environmental variables (|R| < 0.8), we employed the MaxEnt model and ArcGIS spatial analysis to systematically predict the potential geographical distribution of <i>P. cinnamomi</i> under current (1970–2000) and future (2030S, 2050S, 2070S, 2090S) climate scenarios across three Shared Socioeconomic Pathways (SSPs). The results indicate that currently suitable habitats cover the majority of China’s provinces (>50% of their areas), with only sporadic low-suitability zones in Qinghai, Tibet, and Xinjiang. The most influential environmental variables were the mean diurnal temperature range, mean temperature of the warmest quarter, annual precipitation, precipitation of the driest month, and elevation. Under future climate scenarios, new suitable habitats emerged in high-latitude regions, while the highly suitable area expanded significantly, with the distribution centroid shifting northeastward. This study employs predictive modeling to elucidate the future distribution patterns of <i>P. cinnamomi</i> in China, providing a theoretical foundation for establishing a regional-scale disease early warning system and formulating ecological management strategies.
ISSN:2077-0472