Abstract
Pathogen and parasite infections are increasingly recognized as powerful drivers of animal movement, including migration. Yet, infection-related migration benefits can result from a combination of environmental and/or social conditions, which can be difficult to disentangle. Here, we focus on two infection-related mechanisms that can favour migration: moving to escape versus recover from infection. By directly comparing the evolution of migration in response to each mechanism, we can evaluate the likely importance of changing abiotic conditions (linked to migratory recovery) with changing social conditions (linked to migratory escape) in terms of infection-driven migration. We built a mathematical model and analysed it using numerically simulated adaptive dynamics to determine when migration should evolve for each migratory recovery and social migratory escape. We found that a higher fraction of the population migrated under migratory recovery than under social migratory escape. We also found that two distinct migratory strategies (e.g. some individuals always migrate and others only occasionally migrate) sometimes coexisted within populations with social migratory escape, but never with migratory recovery. Our results suggest that migratory recovery is more likely to promote the evolution of migratory behaviour, rather than escape from infected conspecifics (social migratory escape).
Original language | English (US) |
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Pages (from-to) | 1448-1457 |
Number of pages | 10 |
Journal | Journal of Animal Ecology |
Volume | 89 |
Issue number | 6 |
DOIs | |
State | Published - Jun 1 2020 |
Bibliographical note
Funding Information:We thank Dave Daversa, Paul Hurtado, anonymous reviewers and the Associate Editor for helpful comments. We also thank anonymous reviewer 1 on Shaw and Binning (2016) for encouraging us to tease apart the relative impacts of recovery and escape. This material is based in part upon work supported by the National Science Foundation under grant no. DEB-1654609. S.A.B. is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Research Chair program. We acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper (http://www.msi.umn.edu).
Funding Information:
We thank Dave Daversa, Paul Hurtado, anonymous reviewers and the Associate Editor for helpful comments. We also thank anonymous reviewer 1 on Shaw and Binning ( 2016 ) for encouraging us to tease apart the relative impacts of recovery and escape. This material is based in part upon work supported by the National Science Foundation under grant no. DEB‐1654609. S.A.B. is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Research Chair program. We acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing resources that contributed to the research results reported within this paper ( http://www.msi.umn.edu ).
Publisher Copyright:
© 2020 British Ecological Society
Keywords
- disease ecology
- environmental gradient
- evolutionarily stable strategy
- host–parasite interaction
- mathematical model
- movement ecology
- pathogen infection