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- W4311318708 abstract "The primary culprits of pine wilt disease (PWD), an epidemic forest disease that significantly endangers the human environment and the world’s forest resources, are pinewood nematodes (PWN, Bursaphelenchus xylophilus). The MaxEnt model has been used to predict and analyze the potential geographic spread of PWD in China under the effects of climate change and can serve as a foundation for high-efficiency monitoring, supervision, and prompt prevention and management. In this work, the MaxEnt model’s criteria settings were optimized using data from 646 PWD infestation sites and seven climate variables from the ENMeval data package. It simulated and forecasted how PWD may be distributed under present and future (the 2050s and 2070s) climatic circumstances, and the key climate factors influencing the disease were examined. The area under AUC (area under receiver operating characteristic (ROC) curve) is 0.940 under the parameters, demonstrating the accuracy of the simulation. Under the current climate conditions, the moderately and highly suitable habitats of PWD are distributed in Anhui, Jiangxi, Hubei, Hunan, Guangdong, Guangxi, Sichuan, and other provinces. The outcomes demonstrated that the fundamental climate variables influencing the PWD distribution were rainfall and temperature, specifically including maximum temperature of warmest month, mean temperature of driest quarter, coefficient of variation of precipitation seasonality, and precipitation of wettest quarter. The evaluation outcomes of the MaxEnt model revealed that the total and highly suitable areas of PWD will expand substantially by both 2050 and 2070, and the potential distribution of PWD will have a tendency to spread towards high altitudes and latitudes." @default.
- W4311318708 created "2022-12-25" @default.
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- W4311318708 date "2022-12-12" @default.
- W4311318708 modified "2023-10-14" @default.
- W4311318708 title "Predicting the Potential Distribution of Pine Wilt Disease in China under Climate Change" @default.
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- W4311318708 doi "https://doi.org/10.3390/insects13121147" @default.
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