V. vulpes is considered an invasive pest in Australia and threatens a variety of native biodiversity, kills livestock as well as potentially negatively impacting human health. Climate change is thought to have variable influences on species distribution patterns and may facilitate the spread of invasive species into new areas. Here we use EcoCommons to develop species distribution models for V. vulpes as well as its prey species O. cuniculus under current and future climate scenarios. Occurrence data was sourced from Atlas of Living Australia. The environmental layers for each model as well as the model algorithms were selected using case studies based on past research into both V. vulpes and O. cuniculus using species distribution modelling. Maxent, Generalized linear model (GLM), Boosted Regression Tree (BRT), Random forest (RF) and Bioclim were all of the model algorithms utilized. Models were configured and then distribution under current climate conditions were then mapped for both species, these results were then projected onto the years 2045 and 2085 using the Representative Concentration Pathway 4.5. All models performed well with no AUC score below 0.9. Results suggest that V. vulpes is largely predicted to reside in southern and southeastern regions including coastal areas of Australia as well as in small areas in the southwest with urban areas under considerable invasion threat. V. vulpes distribution was matched across most of its predicted suitable area with O. cuniculus. Urban areas were discussed as requiring more attention from management strategies due to the increasing confidence of foxes in urban areas. Recommendations were made to direct future attention towards modelling modelling biotic interactions, include a greater body of historical occurrence data as well as attempt to use more severe Representative Concentration Pathways. Nevertheless, this study represents as far as is know the first study using the new EcoCommons SDM platform to model V. vulpes distribution under climate change conditions.
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