The impact of dormancy on evolutionary branching

IF 1.2 4区 生物学 Q4 ECOLOGY
Jochen Blath , Tobias Paul , András Tóbiás , Maite Wilke Berenguer
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引用次数: 0

Abstract

In this paper, we investigate the consequences of dormancy in the ‘rare mutation’ and ‘large population’ regime of stochastic adaptive dynamics. Starting from an individual-based micro-model, we first derive the Polymorphic Evolution Sequence of the population, based on a previous work by Baar and Bovier (2018). After passing to a second ‘small mutations’ limit, we arrive at the Canonical Equation of Adaptive Dynamics, and state a corresponding criterion for evolutionary branching, extending a previous result of Champagnat and Méléard (2011).

The criterion allows a quantitative and qualitative analysis of the effects of dormancy in the well-known model of Dieckmann and Doebeli (1999) for sympatric speciation. In fact, quite an intuitive picture emerges: Dormancy enlarges the parameter range for evolutionary branching, increases the carrying capacity and niche width of the post-branching sub-populations, and, depending on the model parameters, can either increase or decrease the ‘speed of adaptation’ of populations. Finally, dormancy increases diversity by increasing the genetic distance between subpopulations.

休眠对进化分支的影响
在本文中,我们研究了休眠在随机适应动力学的 "罕见突变 "和 "大种群 "机制中的后果。从基于个体的微观模型出发,我们首先在 Baar 和 Bovier(2018)之前的研究基础上推导出种群的多态进化序列。在达到第二个 "小突变 "极限后,我们得出了适应动态的典型方程,并阐述了相应的进化分支标准,扩展了 Champagnat 和 Méléard (2011) 之前的研究成果。该标准允许对 Dieckmann 和 Doebeli(1999 年)著名的同域物种演化模型中的休眠效应进行定量和定性分析。事实上,我们可以看到一幅相当直观的图景:休眠扩大了进化分支的参数范围,增加了分支后亚种群的承载能力和生态位宽度,而且根据模型参数的不同,可以提高或降低种群的 "适应速度"。最后,休眠会增加亚种群之间的遗传距离,从而提高多样性。
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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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