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fitness costs of adaptation via phenotypic plasticity and maternal effects

Phenotypes are often environmentally dependent, which requires organisms to track environmental change. The challenge for organisms is to construct phenotypes using the most accurate environmental cue. Here, we use a quantitative genetic model of adaptation by additive genetic variance, within‐ and...

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Bibliographic Details
Published in:Functional ecology 2014-06, Vol.28 (3), p.693-701
Main Authors: Ezard, Thomas H. G, Prizak, Roshan, Hoyle, Rebecca B, Marshall, Dustin
Format: Article
Language:English
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Summary:Phenotypes are often environmentally dependent, which requires organisms to track environmental change. The challenge for organisms is to construct phenotypes using the most accurate environmental cue. Here, we use a quantitative genetic model of adaptation by additive genetic variance, within‐ and transgenerational plasticity via linear reaction norms and indirect genetic effects respectively. We show how the relative influence on the eventual phenotype of these components depends on the predictability of environmental change (fast or slow, sinusoidal or stochastic) and the developmental lag τ between when the environment is perceived and when selection acts. We then decompose expected mean fitness into three components (variance load, adaptation and fluctuation load) to study the fitness costs of within‐ and transgenerational plasticity. A strongly negative maternal effect coefficient m minimizes the variance load, but a strongly positive m minimises the fluctuation load. The adaptation term is maximized closer to zero, with positive or negative m preferred under different environmental scenarios. Phenotypic plasticity is higher when τ is shorter and when the environment changes frequently between seasonal extremes. Expected mean population fitness is highest away from highest observed levels of phenotypic plasticity. Within‐ and transgenerational plasticity act in concert to deliver well‐adapted phenotypes, which emphasizes the need to study both simultaneously when investigating phenotypic evolution.
ISSN:0269-8463
1365-2435
DOI:10.1111/1365-2435.12207