%0 Journal Article %A ZHAO Hao-xiang %A XIAN Xiao-qing %A GUO Jian-yang %A YANG Nian-wan %A ZHANG Yan-ping %A CHEN Bao-xiong %A HUANG Hong-kun %A LIU Wan-xue %T 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  %D 2023 %R 10.1016/j.jia.2022.12.004 %J Journal of Integrative Agriculture %P 2783-2795 %V 22 %N 9 %X

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 Wauropunctata 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 Wauropunctata in China can illustrate areas that may potentially face invasion risk.  Therefore, based on the global distribution records of Wauropunctata and bioclimatic variables, we predicted the geographical distribution pattern of Wauropunctata 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 Wauropunctata in China is mainly located in southern China under current and future climate change.  Under climate change, the PGD of Wauropunctata 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 Wauropunctata in China.  The PGD of Wauropunctata 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 Wauropunctata in southern China have broad potential invasion areas.  Developing strategies for the early warning, monitoring, prevention, and control of Wauropunctata in southern China requires more attention.

%U https://www.chinaagrisci.com/Jwk_zgnykxen/EN/10.1016/j.jia.2022.12.004