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外来入侵滑龟出现在意想不到的栖息地:是生态位转移还是研究预测指标的问题?

Alien invasive slider turtle in unpredicted habitat: a matter of niche shift or of predictors studied?

机构信息

Biogeography Department, Trier University, Trier, Germany.

出版信息

PLoS One. 2009 Nov 24;4(11):e7843. doi: 10.1371/journal.pone.0007843.

Abstract

BACKGROUND

Species Distribution Models (SDMs) aim on the characterization of a species' ecological niche and project it into geographic space. The result is a map of the species' potential distribution, which is, for instance, helpful to predict the capability of alien invasive species. With regard to alien invasive species, recently several authors observed a mismatch between potential distributions of native and invasive ranges derived from SDMs and, as an explanation, ecological niche shift during biological invasion has been suggested. We studied the physiologically well known Slider turtle from North America which today is widely distributed over the globe and address the issue of ecological niche shift versus choice of ecological predictors used for model building, i.e., by deriving SDMs using multiple sets of climatic predictor.

PRINCIPAL FINDINGS

In one SDM, predictors were used aiming to mirror the physiological limits of the Slider turtle. It was compared to numerous other models based on various sets of ecological predictors or predictors aiming at comprehensiveness. The SDM focusing on the study species' physiological limits depicts the target species' worldwide potential distribution better than any of the other approaches.

CONCLUSION

These results suggest that a natural history-driven understanding is crucial in developing statistical models of ecological niches (as SDMs) while "comprehensive" or "standard" sets of ecological predictors may be of limited use.

摘要

背景

物种分布模型(SDMs)旨在描述物种的生态位,并将其投射到地理空间中。其结果是物种潜在分布的地图,例如,有助于预测外来入侵物种的能力。关于外来入侵物种,最近有几位作者观察到 SDMs 得出的本地和入侵范围的潜在分布之间存在不匹配的情况,并提出了在生物入侵过程中生态位转移的解释。我们研究了生理上众所周知的北美滑龟,它现在广泛分布在全球各地,并解决了生态位转移与用于模型构建的生态预测因子选择之间的问题,即通过使用多组气候预测因子来推导 SDMs。

主要发现

在一个 SDM 中,使用预测因子来反映滑龟的生理极限。它与基于各种生态预测因子集或旨在全面性的预测因子的许多其他模型进行了比较。专注于研究物种生理极限的 SDM 比其他任何方法都更能准确地描绘出目标物种的全球潜在分布。

结论

这些结果表明,在开发生态位的统计模型(如 SDMs)时,基于自然历史的理解是至关重要的,而“全面”或“标准”的生态预测因子集可能用处有限。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/093d/2776975/0ad159c2ac49/pone.0007843.g001.jpg

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