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首页> 外文期刊>Journal of Molluscan Studies >Habitat suitability modelling of four terrestrial slug species in the Iberian Peninsula (Arionidae: Geomalacus species)
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Habitat suitability modelling of four terrestrial slug species in the Iberian Peninsula (Arionidae: Geomalacus species)

机译:伊比利亚半岛上四种陆生species的栖息地适宜性模拟(Arionidae:Geomalacus种)

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摘要

Ecological niche modelling (ENM) determines habitat suitability of species by relating records of occurrence to environmental variables. Here, we investigated habitat suitability of four terrestrial slugs of the genus Geomalacus from the Iberian Peninsula using ENM. The potential distribution of these species was estimated using maximum entropy modelling. For this we used published presence records, together with observations from our fieldwork, and 10 layers of environmental variables in a crossvalidation design using ` minimum predicted area' as a measure of success. For each species, the models predicted distributions with high accuracy, while restricting predictions to minimum areas. Precipitation, and to a lesser extent temperature, were the most important variables to predict the distributions of the four species. We then compared the predicted distributions with the currently known distributions. For G. anguiformis and G. maculosus the predicted distributions included the known distributions, but also nearby mountain areas where these species have not previously been found. For G. malagensis and G. oliveirae the models predicted much wider distributions. Subsequent dedicated fieldwork could not confirm the presence of G. oliveirae in the newly predicted areas. Conversely, G. malagensis was found at five new and distant localities, including areas in Portugal where the species has not previously been recorded.
机译:生态位建模(ENM)通过将发生的记录与环境变量相关联来确定物种的栖息地适宜性。在这里,我们使用ENM调查了来自伊比利亚半岛的Geomalacus属的四个陆地的生境适应性。这些物种的潜在分布是使用最大熵模型估算的。为此,我们使用了公开的在场记录,以及我们实地考察的观察结果,以及在交叉验证设计中使用“最小预测面积”作为成功度量的10层环境变量。对于每个物种,模型都可以高精度预测分布,同时将预测范围限制在最小范围内。降水和较小的温度是预测这四个物种分布的最重要变量。然后,我们将预测分布与当前已知分布进行了比较。对于G. anguiformis和G. maculosus,预测的分布包括已知分布,但也包括先前未发现这些物种的附近山区。对于马拉加G. oliveirae和G. oliveirae,模型预测的分布范围更广。随后的专职野外调查无法确认在新预测的地区是否存在油橄榄。相反,在五个新的和遥远的地方发现了马拉加乳杆菌,包括葡萄牙以前从未记录过该物种的地区。

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