Monitoring the little fire ant, Wasmannia auropunctata (Roger 1863), in the early stage of its invasion in China: Predicting its geographical distribution pattern under climate change

文献类型： 外文期刊

第一作者： Zhao, Hao-xiang

作者： Zhao, Hao-xiang;Xian, Xiao-qing;Guo, Jian-yang;Yang, Nian-wan;Liu, Wan-xue;Yang, Nian-wan;Zhang, Yan-ping;Chen, Bao-xiong;Huang, Hong-kun

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关键词： invasive alien ants; potential geographical distribution; Wasmannia auropunctata; climate change; Ensemble model

期刊名称：JOURNAL OF INTEGRATIVE AGRICULTURE （ 影响因子：4.8； 五年影响因子：4.8 ）

ISSN： 2095-3119

年卷期： 2023 年 22 卷 9 期

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收录情况： SCI

摘要： Invasive alien ants (IAAs) are among the most aggressive, competitive, and widespread invasive alien species (IAS) worldwide. Wasmannia auropunctata, the greatest IAAs threat in the Pacific region and listed in "100 of the world's worst IAS", has established itself in many countries and on islands worldwide. Wild populations of W. auropunctata were recently reported in southeastern China, representing a tremendous potential threat to China's agricultural, economic, environmental, public health, and social well-being. Estimating the potential geographical distribution (PGD) of W. auropunctata in China can illustrate areas that may potentially face invasion risk. Therefore, based on the global distribution records of W. auropunctata and bioclimatic variables, we predicted the geographical distribution pattern of W. auropunctata in China under the effects of climate change using an ensemble model (EM). Our findings showed that artificial neural network (ANN), flexible discriminant analysis (FDA), gradient boosting model (GBM), Random Forest (RF) were more accurate than categorical regression tree analysis (CTA), generalized linear model (GLM), maximum entropy model (MaxEnt) and surface distance envelope (SRE). The mean TSS values of ANN, FDA, GBM, and RF were 0.820, 0.810, 0.843, and 0.857, respectively, and the mean AUC values were 0.946, 0.954, 0.968, and 0.979, respectively. The mean TSS and AUC values of EM were 0.882 and 0.972, respectively, indicating that the prediction results with EM were more reliable than those with the single model. The PGD of W. auropunctata in China is mainly located in southern China under current and future climate change. Under climate change, the PGD of W. auropunctata in China will expand to higher-latitude areas. The annual temperature range (bio7) and mean temperature of the warmest quarter (bio10) were the most significant variables affecting the PGD of W. auropunctata in China. The PGD of W. auropunctata in China was mainly attributed to temperature variables, such as the annual temperature range (bio7) and the mean temperature of the warmest quarter (bio10). The populations of W. auropunctata in southern China have broad potential invasion areas. Developing strategies for the early warning, monitoring, prevention, and control of W. auropunctata in southern China requires more attention.

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