Breeding decision in migratory population with stochastic and deterministic cost.

IF 1.4 4区 生物学 Q4 ECOLOGY
Yogesh Trivedi, François Massol, Anushaya Mohapatra
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引用次数: 0

Abstract

Breeding decisions in migratory animal populations involve a trade-off between returning to natal grounds and delaying reproduction. Partial migration, in which some individuals migrate while others remain resident, is common across species. Migrating individuals often face ecological challenges, such as predation and environmental unpredictability, imposing significant breeding costs that affect their reproductive choices. We developed a discrete-time population model that considers both migration and the option to skip breeding. Our analysis of a deterministic model with constant breeding costs shows that the evolutionarily stable strategy (ESS) is always to breed. However, when accounting for environmental stochasticity from catastrophic events like floods or droughts, our extended model reveals that high breeding costs during such events may favor skipping breeding, improving long-term population growth. Conversely, always breeding remains beneficial under low costs. Our findings highlight the adaptive significance of reproductive decisions in the context of migration and environmental variability.

具有随机和确定性代价的迁徙种群繁殖决策。
迁徙动物种群的繁殖决策涉及到返回出生地和推迟繁殖之间的权衡。部分迁移,即一些个体迁移而另一些个体留在原地,是跨物种的普遍现象。迁徙个体经常面临生态挑战,如捕食和环境的不可预测性,造成了巨大的繁殖成本,影响了它们的生殖选择。我们开发了一个离散时间种群模型,考虑了迁移和跳过繁殖的选择。我们对一个具有恒定繁殖成本的确定性模型进行了分析,结果表明进化稳定策略(ESS)始终是繁殖。然而,当考虑洪水或干旱等灾难性事件的环境随机性时,我们的扩展模型显示,在这些事件中,高繁殖成本可能有利于跳过繁殖,从而改善长期的种群增长。相反,在低成本的情况下,始终进行育种仍然是有益的。我们的研究结果强调了在迁移和环境变化的背景下生殖决策的适应性意义。
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
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
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.
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