Spatial invasion of cooperative parasites

IF 1.2 4区生物学 Q4 ECOLOGY

Theoretical Population Biology Pub Date : 2024-07-09 DOI:10.1016/j.tpb.2024.07.001

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引用次数: 0

Abstract

In this paper we study invasion probabilities and invasion times of cooperative parasites spreading in spatially structured host populations. The spatial structure of the host population is given by a random geometric graph on ${[0, 1]}^{n}$ , $n \in N$ , with a Poisson $(N)$ -distributed number of vertices and in which vertices are connected over an edge when they have a distance of at most $r_{N}$ with $r_{N}$ of order $N^{(β - 1) / n}$ for some $0 < β < 1$ . At a host infection many parasites are generated and parasites move along edges to neighbouring hosts. We assume that parasites have to cooperate to infect hosts, in the sense that at least two parasites need to attack a host simultaneously. We find lower and upper bounds on the invasion probability of the parasites in terms of survival probabilities of branching processes with cooperation. Furthermore, we characterize the asymptotic invasion time.

An important ingredient of the proofs is a comparison with infection dynamics of cooperative parasites in host populations structured according to a complete graph, i.e. in well-mixed host populations. For these infection processes we can show that invasion probabilities are asymptotically equal to survival probabilities of branching processes with cooperation. Furthermore, we build on proof techniques developed in Brouard and Pokalyuk (2022), where an analogous invasion process has been studied for host populations structured according to a configuration model.

We substantiate our results with simulations.

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合作寄生虫的空间入侵。

本文研究了在空间结构宿主种群中传播的合作寄生虫的入侵概率和入侵时间。宿主种群的空间结构由[0,1]n, n∈N 上的随机几何图给出，图中顶点的数量是泊松（N）分布的，当顶点之间的距离最多为 rN 时，它们通过边相连，rN 的阶数为 N(β-1)/n，对于某个 0

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Theoretical Population Biology 生物-进化生物学

CiteScore

2.50

自引率

14.30%

发文量

审稿时长

6-12 weeks

期刊介绍： An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.