Environment-to-phenotype mapping and adaptation strategies in varying environments.
evolutionary theory
fluctuating environments
phenotypic plasticity
population dynamics
survival strategies
Journal
Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876
Informations de publication
Date de publication:
09 07 2019
09 07 2019
Historique:
pubmed:
22
6
2019
medline:
27
3
2020
entrez:
22
6
2019
Statut:
ppublish
Résumé
Biological organisms exhibit diverse strategies for adapting to varying environments. For example, a population of organisms may express the same phenotype in all environments ("unvarying strategy") or follow environmental cues and express alternative phenotypes to match the environment ("tracking strategy"), or diversify into coexisting phenotypes to cope with environmental uncertainty ("bet-hedging strategy"). We introduce a general framework for studying how organisms respond to environmental variations, which models an adaptation strategy by an abstract mapping from environmental cues to phenotypic traits. Depending on the accuracy of environmental cues and the strength of natural selection, we find different adaptation strategies represented by mappings that maximize the long-term growth rate of a population. The previously studied strategies emerge as special cases of our model: The tracking strategy is favorable when environmental cues are accurate, whereas when cues are noisy, organisms can either use an unvarying strategy or, remarkably, use the uninformative cue as a source of randomness to bet hedge. Our model of the environment-to-phenotype mapping is based on a network with hidden units; the performance of the strategies is shown to rely on having a high-dimensional internal representation, which can even be random.
Identifiants
pubmed: 31221749
pii: 1903232116
doi: 10.1073/pnas.1903232116
pmc: PMC6628789
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
13847-13855Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
Références
J Hered. 2016 Jan;107(1):25-41
pubmed: 26297912
Am Nat. 2013 Sep;182(3):313-27
pubmed: 23933723
Ecol Lett. 2016 Oct;19(10):1209-18
pubmed: 27515951
Proc Biol Sci. 2011 Jun 7;278(1712):1601-9
pubmed: 21411456
Science. 2006 Feb 3;311(5761):650-2
pubmed: 16456077
Philos Trans R Soc Lond B Biol Sci. 2010 Feb 27;365(1540):557-66
pubmed: 20083632
Trends Ecol Evol. 1998 Feb 1;13(2):77-81
pubmed: 21238209
Am Nat. 2007 Jan;169(1):38-46
pubmed: 17206583
Curr Opin Microbiol. 2015 Jun;25:67-72
pubmed: 26025019
Cell Host Microbe. 2013 Jun 12;13(6):632-42
pubmed: 23768488
Proc Natl Acad Sci U S A. 2009 Jun 2;106(22):8841-6
pubmed: 19470486
Biotechnol Bioeng. 2003 Dec 30;84(7):783-94
pubmed: 14708119
Science. 2004 Sep 10;305(5690):1622-5
pubmed: 15308767
PLoS Comput Biol. 2015 Mar 23;11(3):e1004055
pubmed: 25798588
J R Soc Interface. 2017 Jul;14(132):
pubmed: 28679667
Nature. 2017 Mar 15;543(7645):337-345
pubmed: 28300110
Phys Rev E. 2017 Sep;96(3-1):032412
pubmed: 29346942
Proc Natl Acad Sci U S A. 2018 Dec 11;115(50):12745-12750
pubmed: 30478048
Neuron. 2014 Sep 3;83(5):1213-26
pubmed: 25155954
Science. 2012 Jun 1;336(6085):1157-60
pubmed: 22539553
J Theor Biol. 1967 Jul;16(1):1-14
pubmed: 6035758
J Theor Biol. 1966 Sep;12(1):119-29
pubmed: 6015423
Evolution. 2017 Apr;71(4):859-871
pubmed: 28213964
Ecology. 2007 May;88(5):1086-90
pubmed: 17536393
Nature. 2009 Nov 5;462(7269):90-3
pubmed: 19890329
Science. 2005 Sep 23;309(5743):2075-8
pubmed: 16123265
Front Comput Neurosci. 2022 Aug 08;16:917786
pubmed: 36003684
Theor Popul Biol. 2007 Dec;72(4):560-75
pubmed: 17915273
Proc Biol Sci. 2011 Sep 22;278(1719):2705-13
pubmed: 21676977
Genetica. 1991;84(1):5-11
pubmed: 1874440