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The role of mate competition in speciation and divergence: a systematic review.

Alycia C R LackeyElizabeth S C ScordatoJason KeagyRobin M TinghitellaRobert J P Heathcote
Published in: Journal of evolutionary biology (2024)
Competition for mates can play a critical role in determining reproductive success, shaping phenotypic variation within populations, and influencing divergence. Yet, studies of the role of sexual selection in divergence and speciation have focused disproportionately on mate choice. Here, we synthesize the literature on how mate competition may contribute to speciation and integrate concepts from work on sexual selection within populations - mating systems, ecology, and mate choice. Using this synthesis, we generate testable predictions for how mate competition may contribute to divergence. Then, we identify the extent of existing support for these predictions in the literature with a systematic review of the consequences of mate competition for population divergence across a range of evolutionary, ecological, and geographic contexts. We broadly evaluate current evidence, identify gaps in available data and hypotheses that need testing, and outline promising directions for future work. A major finding is that mate competition may commonly facilitate further divergence after initial divergence has occurred, e.g., upon secondary contact and between allopatric populations. Importantly, current hypotheses for how mate competition contributes to divergence do not fully explain observed patterns. While results from many studies fit predictions of negative frequency dependent selection, agonistic character displacement, and ecological selection, results from ~30% studies did not fit existing conceptual models. This review identifies future research aims for scenarios in which mate competition is likely important but has been understudied, including how ecological context and interactions between mate choice and mate competition can facilitate or hinder divergence and speciation.
Keyphrases
  • climate change
  • systematic review
  • mental health
  • genome wide
  • machine learning
  • human health
  • risk assessment
  • artificial intelligence
  • decision making
  • genetic diversity