Self-structuring in spatial evolutionary ecology. (bibtex)
by Lion S. & van Baalen M.
Abstract:
Spatial self-structuring has been a focus of recent interest among evolutionary ecologists. We review recent developments in the study of the interplay between spatial self-structuring and evolution. We first discuss the relative merits of the various theoretical approaches to spatial modelling in ecology. Second, we synthesize the main theoretical studies of the evolution of cooperation in spatially structured populations. We show that population viscosity is generally beneficial to cooperation, because cooperators can reap additional benefits from being clustered. A similar mechanism can explain the evolution of honest communication and of reduced virulence in host-parasite interactions. We also discuss some recent innovative empirical results that test these theories. Third, we show the relevance of these results to the general field of evolutionary ecology. An important conclusion is that kin selection is the main process that drives evolution of cooperation in viscous populations. Many results of kin selection theory can be recovered as emergent properties of spatial ecological dynamics. We discuss the implications of these results for the study of multilevel selection and evolutionary transitions. We conclude by sketching some perspectives for future research, with a particular emphasis on the topics of evolutionary branching, criticality, spatial fluctuations and experimental tests of theoretical predictions.
Reference:
Lion S. & van Baalen M. (2008) Self-structuring in spatial evolutionary ecology. Ecology Letters. 11(3): 277-295.
Bibtex Entry:
@Article{LionVanBaalen2008,
  Author         = {Lion, Sébastien and van Baalen, Minus},
  Title          = {Self-structuring in spatial evolutionary ecology.},
  Journal        = {Ecology Letters},
  doi            = {10.1111/j.1461-0248.2007.01132.x},
  Volume         = {11},
  Number         = {3},
  Pages          = {277-295},
  URL = {pub/LionVanBaalen2008.pdf},
  keywords       = {space, evolution of social traits, virulence, dispersal},  
  Abstract       = {Spatial self-structuring has been a focus of recent
                   interest among evolutionary ecologists. We review
                   recent developments in the study of the interplay
                   between spatial self-structuring and evolution. We
                   first discuss the relative merits of the various
                   theoretical approaches to spatial modelling in ecology.
                   Second, we synthesize the main theoretical studies of
                   the evolution of cooperation in spatially structured
                   populations. We show that population viscosity is
                   generally beneficial to cooperation, because
                   cooperators can reap additional benefits from being
                   clustered. A similar mechanism can explain the
                   evolution of honest communication and of reduced
                   virulence in host-parasite interactions. We also
                   discuss some recent innovative empirical results that
                   test these theories. Third, we show the relevance of
                   these results to the general field of evolutionary
                   ecology. An important conclusion is that kin selection
                   is the main process that drives evolution of
                   cooperation in viscous populations. Many results of kin
                   selection theory can be recovered as emergent
                   properties of spatial ecological dynamics. We discuss
                   the implications of these results for the study of
                   multilevel selection and evolutionary transitions. We
                   conclude by sketching some perspectives for future
                   research, with a particular emphasis on the topics of
                   evolutionary branching, criticality, spatial
                   fluctuations and experimental tests of theoretical
                   predictions.},
  year           = {2008}
}
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