Modelling ecosystem adaptation and dangerous rates of global warming.

adaptation climate change ecology evolution lifetime modelling

Journal

Emerging topics in life sciences
ISSN: 2397-8554
Titre abrégé: Emerg Top Life Sci
Pays: England
ID NLM: 101706399

Informations de publication

Date de publication:
10 May 2019
Historique:
received: 31 01 2019
revised: 28 03 2019
accepted: 05 04 2019
entrez: 1 2 2021
pubmed: 10 5 2019
medline: 10 5 2019
Statut: ppublish

Résumé

We are in a period of relatively rapid climate change. This poses challenges for individual species and threatens the ecosystem services that humanity relies upon. Temperature is a key stressor. In a warming climate, individual organisms may be able to shift their thermal optima through phenotypic plasticity. However, such plasticity is unlikely to be sufficient over the coming centuries. Resilience to warming will also depend on how fast the distribution of traits that define a species can adapt through other methods, in particular through redistribution of the abundance of variants within the population and through genetic evolution. In this paper, we use a simple theoretical 'trait diffusion' model to explore how the resilience of a given species to climate change depends on the initial trait diversity (biodiversity), the trait diffusion rate (mutation rate), and the lifetime of the organism. We estimate theoretical dangerous rates of continuous global warming that would exceed the ability of a species to adapt through trait diffusion, and therefore lead to a collapse in the overall productivity of the species. As the rate of adaptation through intraspecies competition and genetic evolution decreases with species lifetime, we find critical rates of change that also depend fundamentally on lifetime. Dangerous rates of warming vary from 1°C per lifetime (at low trait diffusion rate) to 8°C per lifetime (at high trait diffusion rate). We conclude that rapid climate change is liable to favour short-lived organisms (e.g. microbes) rather than longer-lived organisms (e.g. trees).

Identifiants

pubmed: 33523155
pii: 219722
doi: 10.1042/ETLS20180113
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

221-231

Informations de copyright

© 2019 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society and the Royal Society of Biology.

Auteurs

Rebecca Millington (R)

College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, U.K.
Marine Spatial Ecology Lab, School of Biological Sciences, The University of Queensland, Queensland, Australia.

Peter M Cox (PM)

College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, U.K.

Jonathan R Moore (JR)

College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, U.K.

Gabriel Yvon-Durocher (G)

Environment and Sustainability Institute, University of Exeter, Penryn, U.K.

Classifications MeSH