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Predictable and Divergent Change in the Multivariate P Matrix during Parallel Adaptation
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Environmental and Life Sciences (from 2013).ORCID iD: 0000-0001-9587-8665
University of Connecticut, USA.
Loyola University Chicago, USA.
2024 (English)In: American Naturalist, ISSN 0003-0147, E-ISSN 1537-5323, Vol. 204, no 1, p. 15-29Article in journal (Refereed) Published
Abstract [en]

Adaptation to replicated environmental conditions can be remarkably predictable, suggesting that parallel evolution may be a common feature of adaptive radiation. An open question, however, is how phenotypic variation itself evolves during repeated adaptation. Here, we use a dataset of morphological measurements from 35 populations of threespine stickleback, consisting of 16 parapatric lake-stream pairs and three marine populations, to understand how phenotypic variation has evolved during transitions from marine to freshwater environments and during subsequent diversification across the lake-stream boundary. We find statistical support for divergent phenotypic covariance (P) across populations, with most diversification of P occurring among freshwater populations. Despite a close correspon-dence between within-population phenotypic variation and among-population divergence, we find that variation in P is unrelated to total variation in population means across the set of populations. For lake-stream pairs, we find that theoretical predictions for microevolutionary change can explain more than 30% of divergence in P matrices across the habitat boundary. Together, our results indicate that divergence in variance structure occurs primarily in dimensions of trait space with low phenotypic integration, correlated with disparate lake and stream environments. Our findings illustrate how conserved and divergent features of multivariate variation can underlie adaptive radiation.

Place, publisher, year, edition, pages
2024. Vol. 204, no 1, p. 15-29
Keywords [en]
covariance tensor, Gasterosteus aculeatus, genetic lines of least resistance, parallel evolution, quantitative genetics
National Category
Evolutionary Biology Ecology
Research subject
Biology
Identifiers
URN: urn:nbn:se:kau:diva-103849DOI: 10.1086/730261ISI: 001225502900001PubMedID: 38857340Scopus ID: 2-s2.0-85195623302OAI: oai:DiVA.org:kau-103849DiVA, id: diva2:1949902
Available from: 2025-04-03 Created: 2025-04-03 Last updated: 2026-02-12Bibliographically approved

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De Lisle, Stephen P.

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