Predator–prey density-dependent branching processes

IF 0.5 4区 数学 Q4 STATISTICS & PROBABILITY
C. Gutiérrez, C. Minuesa
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引用次数: 1

Abstract

Abstract Two density-dependent branching processes are considered to model predator–prey populations. For both models, preys are considered to be the main food supply of predators. Moreover, in each generation the number of individuals of each species is distributed according to a binomial distribution with size given by the species population size and probability of success depending on the density of preys per predator at the current generation. The difference between the two proposed processes lies in the food supply of preys. In the first one, we consider that preys have all the food they need at their disposal while in the second one, we assume that the natural resources of the environment are limited and therefore there exists a competition among preys for food supplies. Results on the fixation and extinction of both species as well as conditions for the coexistence are provided for the first model. On the event of coexistence of both populations and on the prey fixation event, the limiting growth rates are obtained. For the second model, we prove that the extinction of the entire system occurs almost surely. Finally, the evolution of both models over the generations and our analytical findings are illustrated by simulated examples.
捕食者-猎物密度相关的分支过程
摘要考虑了两个密度相关的分支过程来模拟捕食者-猎物种群。对于这两种模型,猎物都被认为是捕食者的主要食物来源。此外,在每一代中,每个物种的个体数量都是根据二项分布分布的,其大小由物种种群大小和成功概率决定,这取决于当前一代每个捕食者的猎物密度。这两种拟议过程的区别在于猎物的食物供应。在第一个例子中,我们认为猎物拥有它们所需的所有食物,而在第二个例子中我们认为环境的自然资源是有限的,因此猎物之间存在着食物供应的竞争。为第一个模型提供了关于两个物种的固定和灭绝以及共存条件的结果。在两个种群共存的情况下和在猎物固定的情况下,获得了极限生长率。对于第二个模型,我们证明了整个系统几乎肯定会灭绝。最后,通过模拟例子说明了这两个模型在几代人中的演变以及我们的分析结果。
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来源期刊
Stochastic Models
Stochastic Models 数学-统计学与概率论
CiteScore
1.30
自引率
14.30%
发文量
42
审稿时长
>12 weeks
期刊介绍: Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.
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