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Recent advances in species distribution models (SDMs) associated with artificial intelligence (AI) and increased volumes of available data for model variables have allowed reliable evaluation of the potential distribution of any species. A reliable SDM requires suitable occurrence records and variables with optimal model structures. In this study, we developed three different machine learning-based SDMs [MaxEnt, random forest (RF), and multi-layer perceptron (MLP)] to predict the global potential distribution of two invasive ants under current and future climates. These SDMs showed that the potential distribution of Solenopsis invicta would be expanded by climatic change, whereas it would not significantly change for Anoplolepis gracilipes. The models were compared using model performance metrics, and the optimal model structure and spatial projection were selected. The MaxEnt exhibited high performance, while the MLP model exhibited low performance, with the largest variation by climate change. Random forest showed the smallest potential distribution area, but it was robust considering the number of occurrence records and changes in model variables. All the models showed reliable performance, but the difference in performance and projection size suggested that optimal model selection based on data availability, model variables, study objectives, or an ensemble approach was necessary to develop a comprehensive SDM to minimize modeling uncertainty. We expect that this study will help with the use of AI-based SDMs for the evaluation and risk assessment of invasive ant species.

We obtained 14,140 interception records of ants arriving in Australia between 1986 and 2010 to examine taxonomic and biogeographic patterns of invasion. We also evaluated how trade and transport data influenced interception rates, the identity of species being transported, the commerce most associated with the transport of ants, and which countries are the primary sources for ants arriving in Australia. The majority of ant interceptions, accounting for 48% of interceptions, were from Asia and Oceania. The top commodities associated with ant interceptions were: (1) Live trees, plants, cut flowers; (2) Wood and wood products; (3) Edible vegetables; and (4) Edible fruit and nuts. The best fitting model for predicting ant interceptions included volumes for these four commodities, as well as total trade value, transport volume, and geographic distance (with increased distance decreasing predicted ant interceptions). Intercepted ants identified to species consisted of a combination of species native to Australia, introduced species already established in Australia, and species not yet known to be established. 82% of interceptions identified to species level were of species already known to be established in Australia withParatrechina longicornishaving the most records. These data provide key biogeographic insight into the overlooked transport stage of the invasion process. Given the difficult nature of eradication, once an ant species is firmly established, focusing on early detection and quarantine is key for reducing the establishment of new invasions.

The recent discovery of multiple viruses in ants, along with the widespread infection of their hosts across geographic ranges, provides an excellent opportunity to test whether viral prevalence in the field is associated with the complexity of social interactions in the ant population. In this study, we examined whether the association exists between the field prevalence of a virus and the intercolonial aggression of its ant host, using the yellow crazy ant (Anoplolepis gracilipes) and its natural viral pathogen (TR44839 virus) as a model system. We delimitated the colony boundary and composition of A. gracilipes in a total of 12 study sites in Japan (Okinawa), Taiwan, and Malaysia (Penang), through intercolonial aggression assay. The spatial distribution and prevalence level of the virus was then mapped for each site. The virus occurred at a high prevalence in the surveyed colonies of Okinawa and Taiwan (100% infection rate across all sites), whereas virus prevalence was variable (30%–100%) or none (0%) at the sites in Penang. Coincidentally, colonies in Okinawa and Taiwan displayed a weak intercolonial boundary, as aggression between colonies is generally low or moderate. Contrastingly, sites in Penang were found to harbor a high proportion of mutually aggressive colonies, a pattern potentially indicative of complex colony composition. Our statistical analyses further confirmed the observed correlation, implying that intercolonial interactions likely contribute as one of the effective facilitators of/barriers to virus prevalence in the field population of this ant species.

Anoplolepis gracilipes (F. Smith, 1857) Plates 80���82 Specimens examined: Al-Wathba Wetland Reserve, 14.iii.2005, CAC. Distribution: An African species, the ���yellow crazy ant��� has been introduced into Australia and the Pacific Islands, causing a considerable loss of local biodiversity. New to the UAE., Published as part of Cedric A. Collingwood, Donat Agosti, Mostafa R. Sharaf & Antonius van Harten, 2011, Order Hymenoptera, family Formicidae, pp. 1-70 in Arthropod fauna of the UAE 4 on page 44, DOI: 10.5281/zenodo.1168586