Invasive species have a massive impact on their environment and predicting geographical zones at risk of invasion is paramount to the control of further invasions. Invasive anurans are particularly detrimental to native amphibian species, other vertebrates, and even aquaculture through competition, predation, disease transmission, toxicity, or a combination of these. Four species have been designated as the worst anuran invaders worldwide: Duttaphrynus melanostictus, Rhinella marina, Lithobates catesbeianus and Xenopus laevis. In this study, we modelled global habitat suitability for all four species using ecological niche factor analysis (ENFA) to predict the most susceptible areas to invasion. Models showed suitable climatic conditions for all four species expanded beyond their current native and invasive ranges. Tropical, subtropical, and island biomes around the world were among the areas with the highest ENFA suitability for all four species. Further, marginality statistics indicate niche expansion in D. melanostictus, and generalism in the three other species. As only climatic variables were used in the modelling, these results show the ultimate distributions if all landscape conditions are met without significant barriers to invasion.

外来入侵物种对其环境造成巨大影响，预测有入侵风险的地理区域对于控制进一步入侵至关重要。通过竞争，捕食，疾病传播，毒性或这些因素的组合，侵入性无氧物种对本地两栖动物物种，其他脊椎动物甚至水产养殖尤其有害。四种物种被指定为全球最严重的无色动物入侵者：Duttaphrynus melanostictus，Rhinella marina，Lithobates catesbeianus和Xenopus laevis。在这项研究中，我们使用生态位因子分析（ENFA）对所有四个物种的全球栖息地适宜性进行了建模，以预测最容易受到侵袭的区域。模型显示，所有四个物种的气候条件都超出了其当前的自然和入侵范围。全世界的热带，亚热带和岛屿生物群落都是ENFA对所有四个物种的适应性最高的地区。此外，边际统计数据表明，D。melanostictus的生态位扩展，而其他三个物种的通才。由于仅在模型中使用了气候变量，因此，如果满足所有景观条件而没有明显的入侵障碍，则这些结果将显示最终分布。