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Quantifying the reliability of dispersal paths in connectivity networks

机译：量化连接网络中分散路径的可靠性

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摘要

Many biological systems, from fragmented landscapes to host populations, can be represented as networks of connected habitat patches. Links between patches in these connectivity networks can represent equally diverse processes, from individuals moving through the landscape to pathogen transmissions or successive colonization events in metapopulations. Any of these processes can be characterized as stochastic, with functional links among patches that exist with various levels of certainty. This stochasticity then needs to be reflected in the algorithms that aim to predict the dispersal routes in these networks. Here we adapt the concept of reliability to characterize the likelihood that a specific path will be used for dispersal in a probabilistic connectivity network. The most reliable of the paths that connect two patches will then identify the most likely sequence of intermediate steps between these patches. Path reliability will be sensitive to targeted disruptions of individual links that form the path, and this can then be used to plan the interventions aimed at either preserving or disrupting the dispersal along that path. The proposed approach is general, and can be used to identify the most likely dispersal routes in various contexts, such as predicting patterns of migrations, colonizations, invasions and epidemics.
机译：从分散的景观到宿主种群，许多生物系统都可以表示为相互连接的栖息地斑块的网络。这些连通性网络中的斑块之间的链接可以代表同样多样的过程，从遍历景观的个体到病原体传播或后继种群中的定居事件。这些过程中的任何一个都可以被描述为随机的，其中补丁之间的功能链接具有各种确定性。然后，需要在旨在预测这些网络中扩散路径的算法中反映这种随机性。在这里，我们采用可靠性的概念来描述在概率连接网络中使用特定路径进行分散的可能性。连接两个补丁的路径中最可靠的路径将确定这些补丁之间最可能的中间步骤顺序。路径可靠性将对形成路径的各个链接的定向破坏敏感，然后可以用于计划旨在保留或破坏沿该路径的分散的干预措施。所提出的方法是通用的，可用于识别各种情况下最可能的扩散途径，例如预测迁移，定居，入侵和流行的模式。

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