ArticleJournal of the Royal Society, Interface2018
Variability in life-history switch points across and within populations explained by Adaptive Dynamics.
Article in Journal of the Royal Society, Interface, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Timing the initiation of sex: Delay mechanisms alter fitness outcomes in a rotifer population model.Journal of theoretical biology · 2026Article
- Timing the initiation of sex: delay mechanisms alter fitness outcomes in a rotifer population model.bioRxiv : the preprint server for biology · 2025Article
- Species-specific model to predict amphibian metamorphosis.Scientific reports · 2023Article
- Competition among small individuals hinders adaptive radiation despite ecological opportunity.Proceedings. Biological sciences · 2022Article
- Loss of consumers constrains phenotypic evolution in the resulting food web.Evolution letters · 2020Article
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Authors and funding
3 authors.
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Abstract
Understanding the factors that shape the timing of life-history switch points (SPs; e.g. hatching, metamorphosis and maturation) is a fundamental question in evolutionary ecology. Previous studies examining this question from a fitness optimization perspective have advanced our understanding of why the timing of life-history transitions may vary across populations and environments. However, in nature we also often observe variability among individuals within populations. Optimization theory, which typically predicts a single optimal SP under physiological and environmental constraints for a given environment, cannot explain this variability. Here, we re-examine the evolution of a single life-history SP between juvenile and adult stages from an Adaptive Dynamics (AD) perspective, which explicitly considers the feedback between the dynamics of population and the evolution of life-history strategy. The AD model, although simple in structure, exhibits a diverse range of evolutionary scenarios depending upon demographic and environmental conditions, including the loss of the juvenile stage, a single optimal SP, alternative optimal SPs depending on the initial phenotype, and sympatric coexistence of two SP phenotypes under disruptive selection. Such predictions are consistent with previous optimization approaches in predicting life-history SP variability across environments and between populations, and in addition they also explain within-population variability by sympatric disruptive selection. Thus, our model can be used as a theoretical tool for understanding life-history variability across environments and, especially, within species in the same environment.
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