Rees, M. orcid.org/0000-0001-8513-9906 and Ellner, S. (2019) Why so variable: can genetic variance in flowering thresholds be maintained by fluctuating selection? American Naturalist, 194 (1). ISSN 0003-0147
Abstract
We use integral projection models (IPMs) and individual-based simulations to study the evolution of genetic variance in two monocarpic plant systems. Previous approaches combining IPMs with an adaptive dynamics–style invasion analysis predicted that genetic variability in the size threshold for flowering will not be maintained, which conflicts with empirical evidence. We ask whether this discrepancy can be resolved by making more realistic assumptions about the underlying genetic architecture, assuming a multilocus quantitative trait in an outcrossing diploid species. To do this, we embed the infinitesimal model of quantitative genetics into an IPM for a size-structured cosexual plant species. The resulting IPM describes the joint dynamics of individual size and breeding value of the evolving trait. We apply this general framework to the monocarpic perennials Oenothera glazioviana and Carlina vulgaris. The evolution of heritable variation in threshold size is explored in both individual-based models (IBMs) and IPMs, using a mutation rate modifier approach. In the Oenothera model, where the environment is constant, there is selection against producing genetically variable offspring. In the Carlina model, where the environment varies between years, genetically variable offspring provide a selective advantage, allowing the maintenance of genetic variability. The contrasting predictions of adaptive dynamics and quantitative genetics models for the same system suggest that fluctuating selection may be more effective at maintaining genetic variation than previously thought.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 by The University of Chicago. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | genetic variance; adaptive dynamics; quantitative genetics; flowering threshold; integral projection model |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) > Department of Animal and Plant Sciences (Sheffield) |
Funding Information: | Funder Grant number NATURAL ENVIRONMENT RESEARCH COUNCIL NE/K014048/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Sep 2018 13:30 |
Last Modified: | 06 Jun 2020 00:39 |
Status: | Published |
Publisher: | University of Chicago Press |
Refereed: | Yes |
Identification Number: | 10.1086/703436 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:135752 |