cE3c - Centre for Ecology, Evolution and Environmental Changes / Azorean Biodiversity Group, Faculty of Agriculture and Environment, Department of Environmental Sciences and Engineering, University dos Azores, Azores, Portugal.
Department of Cellular Biology and Ecology, University of Santiago de Compostela, Santiago, Spain.
PLoS One. 2020 Aug 7;15(8):e0237216. doi: 10.1371/journal.pone.0237216. eCollection 2020.
The aims of this study were to predict the potential distribution of two introduced Mustelidae, Mustela nivalis and M. putorius in the Azores archipelago (Portugal), and evaluate the relative contribution of environmental factors from native and introduced ranges to predict species distribution ranges in oceanic islands. We developed two sets of Species Distribution Models using MaxEnt and distribution data from the native and introduced ranges of the species to project their potential distribution in the archipelago. We found differences in the predicted distributions for the models based on introduced and on native occurrences for both species, with different most important variables being selected. Climatic variables were most important for the introduced range models, while other groups of variables (i.e., human-disturbance) were included in the native-based models. Most of the islands of the Azorean archipelago were predicted to have suitable habitat for both species, even when not yet occupied. Our results showed that predicting the invaded range based on introduced range environmental conditions predicted a narrower range. These results highlight the difficulty to transfer models from native to introduced ranges across taxonomically related species, making it difficult to predict future invasions and range expansion.
本研究旨在预测两种已引入的鼬科动物，即雪貂（Mustela nivalis）和白鼬（M. putorius）在亚速尔群岛（葡萄牙）的潜在分布，并评估来自本土和引入范围的环境因素对预测海洋岛屿物种分布范围的相对贡献。我们使用 MaxEnt 开发了两套物种分布模型，并使用物种的本土和引入范围的数据来预测它们在群岛中的潜在分布。我们发现，对于这两个物种，基于引入和基于本土发生的模型的预测分布存在差异，选择了不同的最重要变量。对于引入范围模型，气候变量最为重要，而其他组的变量（如人类干扰）则包含在基于本土的模型中。亚速尔群岛的大多数岛屿都被预测为这两个物种的适宜栖息地，即使它们尚未被占据。我们的结果表明，基于引入范围的环境条件预测入侵范围会导致预测范围变窄。这些结果突出表明，在分类上相关的物种中，从本土范围向引入范围转移模型具有一定的难度，这使得预测未来的入侵和范围扩张变得困难。
