On the evolution of conditional dispersal under environmental and demographic stochasticity
Author
Summary, in English
Questions: How will density-dependent and costly dispersal evolve in populations subject to local density regulation and environmental stochasticity? What type of density response will evolve, a strong threshold type response or a soft response gradually increasing dispersal?
Method: An individual-based model including density dependence, environmental fluctuations, and population variation was used to simulate evolution of dispersal behaviour.
Key assumptions and variables: Individuals can assess the instantaneous difference between habitat densities and base their dispersal behaviour thereon. However, future density and thus future quality of a chosen habitat patch remain uncertain due to behavioural variation and density fluctuations. Local density regulation was given by the Beverton-Holt map, affected by stochastic environmental forcing. An individual’s dispersal decision is a sigmoid function of the density ratio between patch densities. The half-saturation point and steepness of the dispersal
reaction norm were allowed to evolve.
Conclusions: Conditional dispersal evolves from a state of random behaviour, yet we do not observe threshold dispersal as the evolutionary endpoint (as found in previous models). Among a heterogeneous set of dispersal strategies, the most successful respond softly to density differences but require a large density advantage to trigger emigration. Although threshold dispersal might be evolutionarily stable, we propose that such an endpoint may not be attainable if the evolutionary trajectory becomes less affected by selection and more by drift. The variability in
dispersal behaviour within populations leads to unpredictability in the potential benefit of dispersal and hence may select for conservative emigration criteria. Other evolving life-history traits, such as phenological traits, subject to density- and frequency-dependent effects may show similar evolutionary patterns.
Method: An individual-based model including density dependence, environmental fluctuations, and population variation was used to simulate evolution of dispersal behaviour.
Key assumptions and variables: Individuals can assess the instantaneous difference between habitat densities and base their dispersal behaviour thereon. However, future density and thus future quality of a chosen habitat patch remain uncertain due to behavioural variation and density fluctuations. Local density regulation was given by the Beverton-Holt map, affected by stochastic environmental forcing. An individual’s dispersal decision is a sigmoid function of the density ratio between patch densities. The half-saturation point and steepness of the dispersal
reaction norm were allowed to evolve.
Conclusions: Conditional dispersal evolves from a state of random behaviour, yet we do not observe threshold dispersal as the evolutionary endpoint (as found in previous models). Among a heterogeneous set of dispersal strategies, the most successful respond softly to density differences but require a large density advantage to trigger emigration. Although threshold dispersal might be evolutionarily stable, we propose that such an endpoint may not be attainable if the evolutionary trajectory becomes less affected by selection and more by drift. The variability in
dispersal behaviour within populations leads to unpredictability in the potential benefit of dispersal and hence may select for conservative emigration criteria. Other evolving life-history traits, such as phenological traits, subject to density- and frequency-dependent effects may show similar evolutionary patterns.
Publishing year
2007
Language
English
Pages
663-673
Publication/Series
Evolutionary Ecology
Volume
9
Issue
4
Links
Document type
Journal article
Publisher
Springer
Topic
- Biological Sciences
Keywords
- conditional dispersal
- density dependence
- environmental noise
- evolutionary trajectory
- stochasticity
- individual-based
Status
Published
Research group
- Theoretical Population Ecology and Evolution Group
ISBN/ISSN/Other
- ISSN: 1573-8477