Objective To predict the potential distribution of Euglandina rosea in China under current and future climatic conditions via an optimized maximum entropy (MaxEnt) model, and to provide a theoretical basis for the prevention and control of invasion of E. rosea in China. Methods The global occurrence records of E. rosea were collected and screened using ENMtool. Maxent 3.4.1 and GraphPad Prism 8 were used to screen environmental variables according to the contribution rate of environmental variables, the jackknife method, and the correlation analysis of variables. The "kuenm" package was run in R 4.0.4 software to calculate and adjust the model parameters by means of regularization multipliers and feature combinations. The optimized MaxEnt model was used to predict the potential distribution of E. rosea in China under current and future climate scenarios. ArcGIS 10.7 was used to process the results and map the images. Results A total of 780 E. rosea occurrence records were identified, and four environmental variables were used to construct the MaxEnt model. The area under the curve (AUC) of the model was 0.963. The most influential environmental factors on the distribution of E. rosea were precipitation of the driest quarter and the highest temperature in February. The MaxEnt model predicted that the current potential areas of E. rosea were distributed in the southeast of China, concentrated in Fujian province, Guangdong province, and central Guangxi Zhuang Autonomous Region. It would gradually expand northward to Hunan province, Jiangxi province, central Anhui province, eastern Hubei province, and some areas of Zhejiang province in the future. Conclusions E. rosea has potential distribution in China. With global warming, its potential habitat areas will gradually expand, while at lower latitudes in the southeast they will slightly shrink. As a result, the overall center of potential areas shifts northward.
YIN Ying-xuan, XU An-yuan, PAN Xiao-wen, HE Qing, WU Yin-juan, LI Xue-rong
. Predicting the potential distribution of Euglandina rosea in China using an optimized MaxEnt model[J]. Chinese Journal of Vector Biology and Control, 2023
, 34(2)
: 137
-144
.
DOI: 10.11853/j.issn.1003.8280.2023.02.002
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