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

doi:10.1016/j.jia.2022.12.004

Journal of Integrative Agriculture

2023, Vol. 22

Issue (9): 2783-2795 DOI: 10.1016/j.jia.2022.12.004

Plant Protection

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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

ZHAO Hao-xiang^1*, XIAN Xiao-qing^1*, GUO Jian-yang¹, YANG Nian-wan^{1, 2}, ZHANG Yan-ping³, CHEN Bao-xiong³, HUANG Hong-kun³, LIU Wan-xue^1#

¹ State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Science, Beijing 100193, P.R.China
² Western Agricultural Research Center, Chinese Academy of Agricultural Sciences, Changji 831100, P.R.China
³ Rural Energy and Environment Agency, Ministry of Agriculture and Rural Affairs, Beijing 100193, P.R.China

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摘要

外来入侵蚂蚁是世界范围内最具侵略性、竞争性和广泛的外来入侵物种之一。小火蚁Wasmannia auropunctata是太平洋地区最具威胁性的外来入侵蚂蚁，被列入 "世界100种恶性外来入侵物种"，已经在全世界许多国家和岛屿上建立了种群。最近在我国东南地区发现了小火蚁的野生种群，对我国的农业、经济、环境、和公共健康构成了巨大的潜在威胁。识别小火蚁在我国的潜在地理分布可以明确可能面临入侵风险的地区。因此，我们根据小火蚁的全球分布记录和生物气候变量，利用集合模型预测了气候变化下其在我国的地理分布格局。我们的研究结果表明，在八个物种分布模型中，ANN、FDA、GBM和RF比CTA、GLM、SRE和MaxEnt更准确。ANN、FDA、GBM和RF的平均TSS值分别为0.820、0.810、0.843和0.857，平均AUC值分别为0.946、0.954、0.968和0.979。集合模型的平均TSS和AUC值分别为0.882和0.972，表明集合模型的预测结果比用单一模型的预测结果更可靠。在现代和未来气候条件下，小火蚁在我国的潜在地理分布主要位于南部地区。在气候变化情景下，小火蚁的地理分布有着向高纬度地区转移的趋势。小火蚁在我国的地理分布格局主要受温度变量影响，温度年较差（bio7）和最热季度平均温度（bio10）是影响小火蚁地理分布的重要环境变量。小火蚁在我国南部地区有着广泛的潜在入侵风险区域，因制定小火蚁在我国南方地区的的早期预警、监测、预防和控制策略。

Abstract

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.

Keywords: invasive alien ants potential geographical distribution Wasmannia auropunctata climate change Ensemble model

Received: 18 August 2022 Accepted: 28 October 2022

Fund:

This work was supported by the National Key R&D Program of China (2021YFC2600400), the Technology Innovation Program of the Chinese Academy of Agricultural Sciences (caascx-2017-2022-IAS), and the Key R&D Program of Yunnan Province, China (202103AF140007)

About author: ZHAO Hao-xiang, E-mail: zhao834323482@163.com; XIAN Xiao-qing, E-mail: xianxiaoqing@caas.cn; #Correspondence LIU Wan-xue, E-mail: liuwanxue@caas.cn * These authors contributed equally to this study.

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	ZHAO Hao-xiang
	XIAN Xiao-qing
	GUO Jian-yang
	YANG Nian-wan
	ZHANG Yan-ping
	CHEN Bao-xiong
	HUANG Hong-kun
	LIU Wan-xue

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ZHAO Hao-xiang, XIAN Xiao-qing, GUO Jian-yang, YANG Nian-wan, ZHANG Yan-ping, CHEN Bao-xiong, HUANG Hong-kun, LIU Wan-xue. 2023. 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 . Journal of Integrative Agriculture, 22(9): 2783-2795.

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