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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MDPI AG
2025-06-01
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| Series: | Agriculture |
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| author | Xiaorui Zhang Haiwen Wang Tingting Dai |
| author_facet | Xiaorui Zhang Haiwen Wang Tingting Dai |
| author_sort | Xiaorui Zhang |
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| description | <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. |
| format | Article |
| id | doaj-art-ace9075451ed4b10bc5607356ddf18c4 |
| institution | OA Journals |
| issn | 2077-0472 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Agriculture |
| spelling | doaj-art-ace9075451ed4b10bc5607356ddf18c42025-08-20T02:35:53ZengMDPI AGAgriculture2077-04722025-06-011513141110.3390/agriculture15131411Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche ModelXiaorui Zhang0Haiwen Wang1Tingting Dai2Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, ChinaCo-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, ChinaCo-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China<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.https://www.mdpi.com/2077-0472/15/13/1411potential suitable areapredictionclimate variablesoil variablecentroid |
| spellingShingle | Xiaorui Zhang Haiwen Wang Tingting Dai Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model Agriculture potential suitable area prediction climate variable soil variable centroid |
| title | Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model |
| title_full | Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model |
| title_fullStr | Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model |
| title_full_unstemmed | Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model |
| title_short | Predicting the Potential Geographic Distribution of <i>Phytophthora cinnamomi</i> in China Using a MaxEnt-Based Ecological Niche Model |
| title_sort | predicting the potential geographic distribution of i phytophthora cinnamomi i in china using a maxent based ecological niche model |
| topic | potential suitable area prediction climate variable soil variable centroid |
| url | https://www.mdpi.com/2077-0472/15/13/1411 |
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