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具有空间显式的复合种群扩散的概率方法。

A probabilistic approach to dispersal in spatially explicit meta-populations.

机构信息

Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamnn 310, 12587, Berlin, Germany.

Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), 14195, Berlin, Germany.

出版信息

Sci Rep. 2020 Dec 17;10(1):22234. doi: 10.1038/s41598-020-79162-9.

Abstract

Meta-population and -community models have extended our understanding regarding the influence of habitat distribution, local patch dynamics, and dispersal on species distribution patterns. Currently, theoretical insights on spatial distribution patterns are limited by the dominant use of deterministic approaches for modeling species dispersal. In this work, we introduce a probabilistic, network-based framework to describe species dispersal by considering inter-patch connections as network-determined probabilistic events. We highlight important differences between a deterministic approach and our dispersal formalism. Exemplified for a meta-population, our results indicate that the proposed scheme provides a realistic relationship between dispersal rate and extinction thresholds. Furthermore, it enables us to investigate the influence of patch density on meta-population persistence and provides insight on the effects of probabilistic dispersal events on species persistence. Importantly, our formalism makes it possible to capture the transient nature of inter-patch connections, and can thereby provide short term predictions on species distribution, which might be highly relevant for projections on how climate and land use changes influence species distribution patterns.

摘要

元种群和元社区模型扩展了我们对栖息地分布、局部斑块动态和扩散对物种分布模式的影响的理解。目前,空间分布模式的理论观点受到用于模拟物种扩散的确定性方法的主导的限制。在这项工作中,我们通过将斑块间的连接视为由网络决定的概率事件,引入了一个基于网络的概率框架来描述物种的扩散。我们强调了确定性方法和我们的扩散形式主义之间的重要区别。对于一个元种群来说,我们的结果表明,所提出的方案提供了扩散率和灭绝阈值之间的现实关系。此外,它使我们能够研究斑块密度对元种群持久性的影响,并深入了解概率扩散事件对物种持久性的影响。重要的是,我们的形式主义使得捕捉斑块间连接的瞬态性质成为可能,从而可以对物种分布进行短期预测,这对于预测气候和土地利用变化如何影响物种分布模式可能非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2570/7747636/bb4919ff3269/41598_2020_79162_Fig1_HTML.jpg

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