Evolutionarily stable movement strategies in reaction-diffusion models with edge behavior.
J Math Biol
; 80(1-2): 61-92, 2020 01.
Article
em En
| MEDLINE
| ID: mdl-30783745
ABSTRACT
Many types of organisms disperse through heterogeneous environments as part of their life histories. For various models of dispersal, including reaction-advection-diffusion models in continuously varying environments, it has been shown by pairwise invasibility analysis that dispersal strategies which generate an ideal free distribution are evolutionarily steady strategies (ESS, also known as evolutionarily stable strategies) and are neighborhood invader strategies (NIS). That is, populations using such strategies can both invade and resist invasion by populations using strategies that do not produce an ideal free distribution. (The ideal free distribution arises from the assumption that organisms inhabiting heterogeneous environments should move to maximize their fitness, which allows a mathematical characterization in terms of fitness equalization.) Classical reaction diffusion models assume that landscapes vary continuously. Landscape ecologists consider landscapes as mosaics of patches where individuals can make movement decisions at sharp interfaces between patches of different quality. We use a recent formulation of reaction-diffusion systems in patchy landscapes to study dispersal strategies by using methods inspired by evolutionary game theory and adaptive dynamics. Specifically, we use a version of pairwise invasibility analysis to show that in patchy environments, the behavioral strategy for movement at boundaries between different patch types that generates an ideal free distribution is both globally evolutionarily steady (ESS) and is a global neighborhood invader strategy (NIS).
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Evolução Biológica
/
Modelos Biológicos
Tipo de estudo:
Prognostic_studies
Limite:
Animals
Idioma:
En
Revista:
J Math Biol
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Canadá