Literature DB >> 23669536

A quantitative genetic model of r- and K-selection in a fluctuating population.

Steinar Engen1, Russell Lande, Bernt-Erik Saether.   

Abstract

We analyze a stochastic quantitative genetic model for the joint dynamics of population size N and evolution of a multidimensional mean phenotype (z) under density-dependent selection. This generalizes our previous theories of evolution in fluctuating environments to include density-dependent (but frequency-independent) selection on quantitative characters. We assume that appropriate constraints or trade-offs between fitness components exist to prevent unlimited increase of fitness. We also assume weak selection such that the expected rate of return to equilibrium is much slower for (z) than N. The mean phenotype evolves to a stationary distribution around an equilibrium point z(opt) that maximizes a simple function determined by ecological parameters governing the dynamics of population size. For any (z), the expected direction of phenotypic evolution is determined by the additive genetic covariance matrix G and the gradient of this function with respect to the mean phenotype. For the theta-logistic model of density dependence, evolution tends to maximize the expected value of N(θ).

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Year:  2013        PMID: 23669536     DOI: 10.1086/670257

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  11 in total

1.  Evidence for r- and K-selection in a wild bird population: a reciprocal link between ecology and evolution.

Authors:  Bernt-Erik Sæther; Marcel E Visser; Vidar Grøtan; Steinar Engen
Journal:  Proc Biol Sci       Date:  2016-04-27       Impact factor: 5.349

2.  Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations.

Authors:  Russell Lande; Steinar Engen; Bernt-Erik Sæther
Journal:  Proc Natl Acad Sci U S A       Date:  2017-10-10       Impact factor: 11.205

3.  Density-dependent selection and the maintenance of colour polymorphism in barn owls.

Authors:  Thomas Kvalnes; Bernt-Erik Sæther; Steinar Engen; Alexandre Roulin
Journal:  Proc Biol Sci       Date:  2022-06-01       Impact factor: 5.530

4.  Stochastic Evolutionary Demography under a Fluctuating Optimum Phenotype.

Authors:  Luis-Miguel Chevin; Olivier Cotto; Jaime Ashander
Journal:  Am Nat       Date:  2017-09-27       Impact factor: 3.926

5.  The influence of fluctuating population densities on evolutionary dynamics.

Authors:  Hanja Pisa; Joachim Hermisson; Jitka Polechová
Journal:  Evolution       Date:  2019-06-11       Impact factor: 3.694

6.  Phenotypic memory drives population growth and extinction risk in a noisy environment.

Authors:  Marie Rescan; Daphné Grulois; Enrique Ortega-Aboud; Luis-Miguel Chevin
Journal:  Nat Ecol Evol       Date:  2020-01-27       Impact factor: 15.460

7.  Detecting climate signals in populations across life histories.

Authors:  Stéphanie Jenouvrier; Matthew C Long; Christophe F D Coste; Marika Holland; Marlène Gamelon; Nigel G Yoccoz; Bernt-Erik Saether
Journal:  Glob Chang Biol       Date:  2022-01-14       Impact factor: 13.211

8.  Reconsideration of r/K Selection Theory Using Stochastic Control Theory and Nonlinear Structured Population Models.

Authors:  Ryo Oizumi; Toshikazu Kuniya; Yoichi Enatsu
Journal:  PLoS One       Date:  2016-06-23       Impact factor: 3.240

9.  Contrasting patterns of density-dependent selection at different life stages can create more than one fast-slow axis of life-history variation.

Authors:  Jonathan Wright; Erik Blystad Solbu; Steinar Engen
Journal:  Ecol Evol       Date:  2020-03-01       Impact factor: 2.912

10.  Correlated chromosomal periodicities according to the growth rate and gene expression.

Authors:  Liu Liu; Masaomi Kurokawa; Motoki Nagai; Shigeto Seno; Bei-Wen Ying
Journal:  Sci Rep       Date:  2020-09-23       Impact factor: 4.379

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