A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Evolutionary branching of dispersal strategies in structured metapopulations
Tekijät: Parvinen K
Kustantaja: SPRINGER-VERLAG
Julkaisuvuosi: 2002
Journal: Journal of Mathematical Biology
Tietokannassa oleva lehden nimi: JOURNAL OF MATHEMATICAL BIOLOGY
Lehden akronyymi: J MATH BIOL
Vuosikerta: 45
Numero: 2
Aloitussivu: 106
Lopetussivu: 124
Sivujen määrä: 19
ISSN: 0303-6812
DOI: https://doi.org/10.1007/s002850200150
Tiivistelmä
Dispersal polymorphism and evolutionary branching of dispersal strategies has been found in several metapopulation models. The mechanism behind those findings has been temporal variation caused by cyclic or chaotic local dynamics, or temporally and spatially varying carrying capacities. We present a new mechanism: spatial heterogeneity in the sense of different patch types with sufficient proportions, and temporal variation caused by catastrophes. The model where this occurs is a generalization of the model by Gyllenberg and Metz (2001). Their model is a size-structured metapopulation model with infinitely many identical patches. We present a generalized version of their metapopulation model allowing for different types of patches. In structured population models, defining and computing fitness in polymorphic situations is, in general, difficult. We present an efficient method, which can be applied also to other structured population or metapopulation models.
Dispersal polymorphism and evolutionary branching of dispersal strategies has been found in several metapopulation models. The mechanism behind those findings has been temporal variation caused by cyclic or chaotic local dynamics, or temporally and spatially varying carrying capacities. We present a new mechanism: spatial heterogeneity in the sense of different patch types with sufficient proportions, and temporal variation caused by catastrophes. The model where this occurs is a generalization of the model by Gyllenberg and Metz (2001). Their model is a size-structured metapopulation model with infinitely many identical patches. We present a generalized version of their metapopulation model allowing for different types of patches. In structured population models, defining and computing fitness in polymorphic situations is, in general, difficult. We present an efficient method, which can be applied also to other structured population or metapopulation models.
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