期刊
AMERICAN NATURALIST
卷 200, 期 3, 页码 345-372出版社
UNIV CHICAGO PRESS
DOI: 10.1086/720439
关键词
quantitative genetics; adaptive dynamics; reproductive value; environmental feedbacks; timescales
资金
- Agence Nationale de la Recherche (ANR) JCJC grant [ANR-16-CE350012-01]
- ESB Cooperation Program, Graduate University for Advanced Studies, SOKENDAI
- [R01 GM122061-03]
- [NSF-DEB2011109]
In this study, the authors extended an oligomorphic approximation method to class-structured populations, which allows for the joint description of ecological variables and multimodal trait distributions. They also introduced a new approximation method using reproductive values to simplify eco-evolutionary dynamics. The effectiveness of this approach was illustrated using the case of two-habitat migration-selection models.
Our understanding of the evolution of quantitative traits in nature is still limited by the challenge of including realistic trait distributions in the context of frequency-dependent selection and ecological feedbacks. We extend to class-structured populations a recently introduced oligomorphic approximation, which bridges the gap between adaptive dynamics and quantitative genetics approaches and allows for the joint description of the dynamics of ecological variables and of the moments of multimodal trait distributions. Our theoretical framework allows us to analyze the dynamics of populations composed of several morphs and structured into distinct classes (e.g., age, size, habitats, infection status, and species). We also introduce a new approximation to simplify the eco-evolutionary dynamics using reproductive values. We illustrate the effectiveness of this approach by applying it to the important conceptual case of two-habitat migration-selection models. In particular, we show that our approach allows us to predict both the long-term evolutionary end points and the short-term transient dynamics of the eco-evolutionary process, including fast evolution regimes. We discuss the theoretical and practical implications of our results and sketch perspectives for future work.
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