Kalle Parvinen: Evolution of dispersal in metapopulation models

Tid: Ti 2018-11-20 kl 14.00

Föreläsare: Kalle Parvinen, University of Turku

Plats: Seminar Hall Kuskvillan, Institut Mittag-Leffler

Invasion fitness is the long-term exponential growth rate of a rare mutant in the environment set by the resident. It is a key concept in adaptive dynamics, which is a general framework for studying evolution by natural selection in realistic population models. A mutant may invade if it has positive invasion fitness. Adaptive dynamics investigates long-term consequences of such invasions.
Metapopulation models describe population dynamics in fragmented landscapes. A metapopulation is thus a collection of local populations connected with dispersal. In metapopulation models the invasion fitness is often difficult to calculate. The metapopulation reproduction ratio introduced by Gyllenberg and Metz (2001) and Metz and Gyllenberg (2001) is often easier to calculate. Consider a single mutant disperser arriving in a patch. This mutant may reproduce and thus gain descendants in this patch, but this will not necessarily happen because of demographic stochasticity. As long as this mutant or at least one of its descendants is present in the local population, we call it a mutant colony. Again, because of demographic stochasticity or catastrophes, the mutant colony will eventually go extinct.
During its lifetime, some mutants will emigrate from this mutant colony to the disperser pool. Their average number is the metapopulation reproduction ratio Rm of the mutant. In other words, it is the expected number of successful dispersers produced by a typical mutant colony initiated by a single mutant disperser.
In this talk I will present general results about the evolution of dispersal in metapopulation models, and discuss general mechanisms selecting for/against dispersal, including temporal heterogeneity vs. constant environments, spatial heterogeneity, kin competition and direct cost of dispersal.

Tillhör: Institutionen för matematik
Senast ändrad: 2018-11-18