Antagonistic coevolution between quantitative and Mendelian traits

Yamamichi, Masato; Ellner, Stephen P.

doi:10.1098/rspb.2015.2926

Cited by 30 publications

(29 citation statements)

References 68 publications

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“…This study also showed that small population sizes resulted in lower standing genetic variation, due to inbreeding and/or genetic drift. Similar effects of population size have been shown in mathematical models (Gomulkiewicz & Houle, ; Uecker & Hermisson, ; Yamamichi & Ellner, ) and experiments (Bell & Gonzalez, ; Cameron, Plaistow, Mugabo, Piertney, & Benton, ; Gonzalez & Bell, ; Low‐Décarie et al, ).…”

Section: Introductionsupporting

confidence: 69%

The role of stressors in altering eco‐evolutionary dynamics

2019

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We review and synthesize evidence from the fields of ecology, evolutionary biology and population genetics to investigate how the presence of abiotic stress can affect the feedback between ecological and evolutionary dynamics. To obtain a better insight of how, and under what conditions, an abiotic stressor can influence eco‐evolutionary dynamics, we use a conceptual predator–prey model where the prey can rapidly evolve antipredator defences and stress resistance. We show how abiotic stress influences eco‐evolutionary dynamics by changing the pace and in some case the potential for evolutionary change and thus the evolution‐to‐ecology link. Whether and how the abiotic stress influences this link depends on the effect on population sizes, mutation rates, the presence of gene flow and the genetic architecture underlying the traits involved. Overall, we report ecological and population genetic mechanisms that have so far not been considered in studies on eco‐evolutionary dynamics and suggest future research directions and experiments to develop an understanding of the role of eco‐evolutionary dynamics in more complex ecological and evolutionary scenarios. A http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.13263/suppinfo is available for this article.

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Section: Introductionsupporting

confidence: 69%

The role of stressors in altering eco‐evolutionary dynamics

2019

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“…This makes gradient dynamic models a good starting point for studying eco-evolutionary dynamics. But, because they do not specify gene-level processes, they may not capture all possible dynamics (e.g., see Levin and Udovic 1977, Doebeli 1997, Yamamichi and Ellner 2016.…”

Section: Assumptions and Generality Of Model And Resultsmentioning

confidence: 99%

Genetic variation determines which feedbacks drive and alter predator–prey eco‐evolutionary cycles

Cortez

2018

Ecological Monographs

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Evolution can alter the ecological dynamics of communities, but the effects depend on the magnitudes of standing genetic variation in the evolving species. Using an eco‐coevolutionary predator–prey model, I identify how the magnitudes of prey and predator standing genetic variation determine when ecological, evolutionary, and eco‐evolutionary feedbacks influence system stability and the phase lags in predator–prey cycles. Here, feedbacks are defined by subsystems, i.e., the dynamics of a subset of the components of the whole system when the other components are held fixed; ecological (evolutionary) feedbacks involve the direct and indirect effects between population densities (species traits) and eco‐evolutionary feedbacks involve the direct and indirect effects between population densities and traits. When genetic variation is low in both species, ecological feedbacks and eco‐evolutionary feedbacks involving either the predator or the prey trait have the strongest effects on system stability, when genetic variation is high in one species, evolutionary and eco‐evolutionary feedbacks involving that species’ trait have the strongest effects, and, when genetic variation is high in both species, evolutionary feedbacks involving one or both traits and eco‐coevolutionary feedbacks involving both traits have the strongest effects. I present the biological conditions under which each feedback can destabilize the whole system and cause predator–prey cycles. Predator–prey cycles can also arise when all feedbacks are stabilizing. This counterintuitive outcome occurs when feedbacks involving many variables are more stabilizing than feedbacks involving fewer variables or vice versa. I also identify how the indirect effects of prey and predator density on the predator dynamics (mediated by evolutionary responses in one or both species) alter the phase lags in predator–prey cycles. I present conditions under which the trait‐mediated indirect effects introduce delays that cause the lag between prey and predator peaks to increase. This work explains and unifies empirical and theoretical studies on how predator–prey coevolution alters the dynamics of predator–prey systems and how those effects depend on the magnitudes of prey and predator standing genetic variation.

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“…This stabilizes allele fluctuations and enhances allele persistence under fluctuating selection (Figs. 1 and 2; see also Yamamichi and Ellner 2016 for antagonistic coevolution).…”

Section: Discussionmentioning

confidence: 99%

“…Time‐lagged NFDS is especially common in antagonistic coevolution in host–parasite or prey–predator interactions and is considered to be influential for balancing selection (Tellier and Brown ; Leffler et al. ; Yamamichi and Ellner ).…”

Section: Discussionmentioning

confidence: 99%

“…Not only stochastic environments, but also NFDS can cause allele fluctuations when the fitness function is nonlinear or time-lagged (e.g., Takahashi and Hori 1994;Tellier and Brown 2009;Takahashi and Kawata 2013). Time-lagged NFDS is especially common in antagonistic coevolution in host-parasite or prey-predator interactions and is considered to be influential for balancing selection (Tellier and Brown 2009;Leffler et al 2013;Yamamichi and Ellner 2016).…”

Section: Discussionmentioning

confidence: 99%

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Roles of maternal effects in maintaining genetic variation: Maternal storage effect

Yamamichi

Hoso

2016

Evolution

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Understanding the maintenance of genetic variation remains a central challenge in evolutionary biology. Recent empirical studies suggest the importance of temporally varying selection, as allele frequencies have been found to fluctuate substantially in the wild. However, previous theory suggests that the conditions for the maintenance of genetic variation under temporally fluctuating selection are quite restrictive. Using mathematical models, we demonstrate that maternal genetic effects, whereby maternal genotypes affect offspring phenotypes, can facilitate the maintenance of polymorphism in temporally varying environments. Maternal effects result in mismatches between genotypes and phenotypes, thereby buffering the influence of selection on allele frequency. This decreases the magnitude of allele-frequency fluctuations and creates conditions for the maintenance of variation when selection causes fluctuations. Therefore, maternal effects may result in a temporal storage effect ("maternal storage effect"). On the other hand, when selection does not cause fluctuations (e.g., linear negative frequency-dependent selection), maternal genetic effects moderate the relative importance of selection compared to genetic drift and promote stochastic allele extinction in finite populations. Thus, maternal effects can play an important role in the maintenance of polymorphism, but the direction of the effect depends on the nature of selection.

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Antagonistic coevolution between quantitative and Mendelian traits

Cited by 30 publications

References 68 publications

The role of stressors in altering eco‐evolutionary dynamics

The role of stressors in altering eco‐evolutionary dynamics

Genetic variation determines which feedbacks drive and alter predator–prey eco‐evolutionary cycles

Roles of maternal effects in maintaining genetic variation: Maternal storage effect

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