Data from: Host dispersal responses to resource supplementation determine pathogen spread in wildlife metapopulations
Becker, Daniel J.
Snedden, Celine E.
Hall, Richard J.
Published Jun 11, 2018 on Dryad.
Cite this dataset
Becker, Daniel J.; Snedden, Celine E.; Altizer, Sonia; Hall, Richard J. (2018). Data from: Host dispersal responses to resource supplementation determine pathogen spread in wildlife metapopulations [Dataset]. Dryad. https://doi.org/10.5061/dryad.44dr859
Many wildlife species occupy landscapes that vary in the distribution, abundance, and quality of food resources. Increasingly, urbanized and agricultural habitats provide supplemental food resources that can have profound consequences for host distributions, movement patterns, and pathogen exposure. Understanding how host and pathogen dispersal across landscapes is affected by the spatial extent of food-supplemented habitats is therefore important for predicting the consequences for pathogen spread and impacts on host occupancy. Here we develop a generalizable metapopulation model to understand how the relative abundance of provisioned habitats across the landscape, and host dispersal responses to provisioning and infection, influence patch occupancy by hosts and their pathogens. We find that pathogen invasion and landscape-level infection prevalence are greatest when provisioning increases patch attractiveness and disperser production and when infection has minimal costs on dispersal success. Alternatively, if provisioning promotes site fidelity or reduces disperser production, increasing the fraction of food-supplemented habitats can reduce landscape-scale infection prevalence and minimize disease-induced declines in host occupancy. This work highlights the importance of considering how resources and infection jointly influence host dispersal for predicting how changing resource distributions influence the spread of infectious diseases.
Becker et al 2018_AmNat_R code
R code for deriving threshold conditions, for numerically solving the differential equations, and for recreating key figures.
National Science Foundation, Award: DEB-1601052, DEB-1518611, DBI-1156707