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Recovery from infection is more likely to favor the evolution of migration than social escape from infection

Citation

Shaw, Allison; Binning, Sandra (2020), Recovery from infection is more likely to favor the evolution of migration than social escape from infection, Dryad, Dataset, https://doi.org/10.5061/dryad.000000014

Abstract

1. 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.
2. Here, we focus on two infection-related mechanisms that can favor 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.
3. We built a mathematical model and analyzed it using numerically simulated adaptive dynamics to determine when migration should evolve for each migratory recovery and social migratory escape.
4. 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.
5. Our results suggest that migratory recovery is more likely to promote the evolution of migratory behavior, rather than escape from infected conspecifics (social migratory escape).

Usage Notes

README.txt: This text file contains readme and notes for all files.


files_runcode.zip: This zipped folder contains Matlab code (.m files) for running model simulations.


files_plotfigures.zip: This zipped folder contains Matlab code (.m files) and data (.mat files) for plotting the figures.

Funding

National Science Foundation, Award: DEB-1654609

Natural Sciences and Engineering Research Council of Canada

Canada Research Chairs