Predicting evolution over multiple generations in deteriorating environments using evolutionarily explicit Integral Projection Models
Coulson, Tim ; Potter, Tomos and Felmy, Anja LU
(2021)
In Evolutionary Applications
14(10).
p.2490-2501
- Abstract
Human impacts on the natural world often generate environmental trends that can have detrimental effects on distributions of phenotypic traits. We do not have a good understanding of how deteriorating environments might impact evolutionary trajectories across multiple generations, even though effects of environmental trends are often significant in the statistical quantitative genetic analyses of phenotypic trait data that are used to estimate additive genetic (co)variances. These environmental trends capture reaction norms, where the same (average) genotype expresses different phenotypic trait values in different environments. Not incorporated into the predictive models typically parameterised from statistical analyses to predict... (More)
Human impacts on the natural world often generate environmental trends that can have detrimental effects on distributions of phenotypic traits. We do not have a good understanding of how deteriorating environments might impact evolutionary trajectories across multiple generations, even though effects of environmental trends are often significant in the statistical quantitative genetic analyses of phenotypic trait data that are used to estimate additive genetic (co)variances. These environmental trends capture reaction norms, where the same (average) genotype expresses different phenotypic trait values in different environments. Not incorporated into the predictive models typically parameterised from statistical analyses to predict evolution, such as the breeder's equation. We describe how these environmental effects can be incorporated into multi-generational, evolutionarily explicit, structured population models before exploring how these effects can influence evolutionary dynamics. The paper is primarily a description of the modelling approach, but we also show how incorporation into models of the types of environmental trends that human activity has generated can have considerable impacts on the evolutionary dynamics that are predicted.
(Less)
- author
- Coulson, Tim
; Potter, Tomos
and Felmy, Anja
LU
- publishing date
- 2021-10
- type
- Contribution to journal
- publication status
- published
- keywords
- additive genetic variance, covariance, environmental change, Integral Projection Models, selection
- in
- Evolutionary Applications
- volume
- 14
- issue
- 10
- pages
- 12 pages
- publisher
- Wiley-Blackwell
- external identifiers
-
- scopus:85111117906
- ISSN
- 1752-4563
- DOI
- 10.1111/eva.13272
- language
- English
- LU publication?
- no
- additional info
- Funding Information: Tom Potter is joint funded by NERC DTP and Lamb and Flag studentships at Oxford University, and Anja Felmy is funded by an Early Postdoc Mobility Fellowship from the Swiss National Science Foundation (P2EZP3_181775). We thank Dylan Childs and Joe Travis for helpful comments on an earlier version of the manuscript, and Jarrod Hadfield and two anonymous reviewers who provided extremely useful reviewer comments. Funding Information: Tom Potter is joint funded by NERC DTP and Lamb and Flag studentships at Oxford University, and Anja Felmy is funded by an Early Postdoc Mobility Fellowship from the Swiss National Science Foundation (P2EZP3_181775). We thank Dylan Childs and Joe Travis for helpful comments on an earlier version of the manuscript, and Jarrod Hadfield and two anonymous reviewers who provided extremely useful reviewer comments. Publisher Copyright: © 2021 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.
- id
- 46c20d4e-b4e6-4937-80b2-84adcc972157
- date added to LUP
- 2023-12-11 11:41:47
- date last changed
- 2023-12-15 16:49:14
@article{46c20d4e-b4e6-4937-80b2-84adcc972157,
abstract = {{<p>Human impacts on the natural world often generate environmental trends that can have detrimental effects on distributions of phenotypic traits. We do not have a good understanding of how deteriorating environments might impact evolutionary trajectories across multiple generations, even though effects of environmental trends are often significant in the statistical quantitative genetic analyses of phenotypic trait data that are used to estimate additive genetic (co)variances. These environmental trends capture reaction norms, where the same (average) genotype expresses different phenotypic trait values in different environments. Not incorporated into the predictive models typically parameterised from statistical analyses to predict evolution, such as the breeder's equation. We describe how these environmental effects can be incorporated into multi-generational, evolutionarily explicit, structured population models before exploring how these effects can influence evolutionary dynamics. The paper is primarily a description of the modelling approach, but we also show how incorporation into models of the types of environmental trends that human activity has generated can have considerable impacts on the evolutionary dynamics that are predicted.</p>}},
author = {{Coulson, Tim and Potter, Tomos and Felmy, Anja}},
issn = {{1752-4563}},
keywords = {{additive genetic variance; covariance; environmental change; Integral Projection Models; selection}},
language = {{eng}},
number = {{10}},
pages = {{2490--2501}},
publisher = {{Wiley-Blackwell}},
series = {{Evolutionary Applications}},
title = {{Predicting evolution over multiple generations in deteriorating environments using evolutionarily explicit Integral Projection Models}},
url = {{http://dx.doi.org/10.1111/eva.13272}},
doi = {{10.1111/eva.13272}},
volume = {{14}},
year = {{2021}},
}