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• W4378348518 endingPage "458" @default.
• W4378348518 startingPage "458" @default.
• W4378348518 abstract "Climate change has a highly significant impact on the distribution of species. As the greenhouse effect intensifies each year, the distribution of organisms responds to this challenge in diverse ways. Therefore, climatic environmental variables are a key entry point for capturing the current and future distribution trends of pests. Frankliniella occidentalis is an invasive pest attested worldwide. Its damage is mainly divided into two aspects, including mechanical damage caused by its feeding and egg laying and the spread of tomato spotted wilt virus (TSWV). TSWV is the most dominant transmitted virulent disease. Moreover, F. occidentalis is the major vector for the transmission of this virus, which poses a grave threat to the yield and survival of our crops. In this study, the distribution pattern of this pest was explored using 19 bioclimatic variables based on the Maxent model. The results indicated that in the future, high-suitability areas of F. occidentalis will be widely distributed in 19 provinces of China, with Hebei, Henan, Shandong, Tianjin and Yunnan being the most abundant. Among the 19 bioclimatic variables, the five variables of annual mean temperature (Bio 1), temperature seasonality (standard deviation × 100) (Bio 4), min temperature of the coldest month (Bio 6), mean temperature of the driest quarter (Bio 9) and precipitation of the coldest quarter (Bio 19) were selected as the key environmental variables affecting the distribution of F. occidentalis. In summary, temperature and precipitation are vital factors for the study of the species’ distribution, and this study aims to provide new perspectives for the control of this pest in China." @default.
• W4378348518 created "2023-05-27" @default.
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• W4378348518 date "2023-05-12" @default.
• W4378348518 modified "2023-09-28" @default.
• W4378348518 title "Predicting the Current and Future Distributions of Frankliniella occidentalis (Pergande) Based on the MaxEnt Species Distribution Model" @default.
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• W4378348518 doi "https://doi.org/10.3390/insects14050458" @default.
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• W4378348518 hasPublicationYear "2023" @default.
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