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Pattern formation triggered by rare events: lessons from the spread of rabies.

机译:罕见事件触发的模式形成:狂犬病传播的教训。

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摘要

Understanding of large-scale spatial pattern formation is a key to successful management in ecology and epidemiology. Neighbourhood interactions between local units are known to contribute to large-scale patterns, but how much do they contribute and what is the role of regional interactions caused by long-distance processes? How much long-distance dispersal do we need to explain the patterns that we observe in nature? There seems to be no way to answer these questions empirically. Therefore, we present a modelling approach that is a combination of a grid-based model describing local interactions and an individual-based model describing dispersal. Applying our approach to the spread of rabies, we show that in addition to local rabies dynamics, one long-distance infection per 14000 km2 per year is sufficient to reproduce the wave-like spread of this disease. We conclude that even rare ecological events that couple local dynamics on a regional scale may have profound impacts on large-scale patterns and, in turn, dynamics. Furthermore, the following results emerge: (i) Both neighbourhood infection and long-distance infection are needed to generate the wave-like dispersal pattern of rabies; (ii) randomly walking rabid foxes are not sufficient to generate the wave pattern; and (iii) on a scale of less than 100 km x 100 km, temporal oscillations emerge that are independent from long-distance dispersal.
机译:了解大规模空间格局的形成是生态学和流行病学成功管理的关键。众所周知,地方单位之间的邻里互动会促成大规模模式,但它们会贡献多少呢?长距离过程所引起的区域互动又起什么作用?我们需要多少距离散布来解释我们在自然界中观察到的模式?似乎没有办法凭经验回答这些问题。因此,我们提出了一种建模方法,该方法是描述局部相互作用的基于网格的模型和描述分散性的基于个人的模型的组合。将我们的方法应用于狂犬病的传播,我们发现,除了当地的狂犬病动态外,每年每14000 km2一次远距离感染就足以重现这种疾病的波状传播。我们得出的结论是,即使是罕见的生态事件,在区域范围内将局部动力学耦合在一起,也可能对大规模模式以及动力学产生深远影响。此外,得出以下结果:(i)产生狂犬病的波状传播模式既需要邻里感染又需要远距离感染; (ii)随机行走的狂犬病狐狸不足以产生波浪状; (iii)在小于100 km x 100 km的范围内,出现了与长距离分散无关的时间振荡。

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