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An agent-based model of red colobus resources and disease dynamics implicates key resource sites as hot spots of disease transmission

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  • Bonnell, Tyler R.
  • Sengupta, Raja R.
  • Chapman, Colin A.
  • Goldberg, Tony L.

Abstract

The effect of anthropogenic landscape change on disease in wildlife populations represents a growing conservation and public health concern. Red colobus monkeys (Procolobus rufomitratus), an endangered primate species, are particularly susceptible to habitat alteration and have been the focus of a great deal of disease and ecological research as a result. To infer how landscape changes can affect host and parasite dynamics, a spatially explicit agent-based model is created to simulate movement and foraging of this primate, based on a resource landscape estimated from extensive plot-derived tree population data from Kibale National Park, Uganda. Changes to this resource landscape are used to simulate effects of anthropogenic forest change. With each change in the landscape, disease outcomes within the simulated red colobus population are monitored using a hypothetical microparasite with a directly transmitted life cycle. The model predicts an optimal distribution of resources which facilitates the spread of an infectious agent through the simulated population. The density of resource rich sites and the overall heterogeneity of the landscape are important factors contributing to this spread. The characteristics of this optimal distribution are similar to those of logged sections of forest adjacent to our study area.

Suggested Citation

  • Bonnell, Tyler R. & Sengupta, Raja R. & Chapman, Colin A. & Goldberg, Tony L., 2010. "An agent-based model of red colobus resources and disease dynamics implicates key resource sites as hot spots of disease transmission," Ecological Modelling, Elsevier, vol. 221(20), pages 2491-2500.
    • Handle: RePEc:eee:ecomod:v:221:y:2010:i:20:p:2491-2500
    DOI: 10.1016/j.ecolmodel.2010.07.020
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    References listed on IDEAS

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    1. Yoak, Andrew J. & Reece, John F. & Gehrt, Stanley D. & Hamilton, Ian M., 2016. "Optimizing free-roaming dog control programs using agent-based models," Ecological Modelling, Elsevier, vol. 341(C), pages 53-61.
    2. Dion, Elise & VanSchalkwyk, Louis & Lambin, Eric F., 2011. "The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation," Ecological Modelling, Elsevier, vol. 222(13), pages 2059-2072.
    3. Tardy, Olivia & Massé, Ariane & Pelletier, Fanie & Fortin, Daniel, 2018. "Interplay between contact risk, conspecific density, and landscape connectivity: An individual-based modeling framework," Ecological Modelling, Elsevier, vol. 373(C), pages 25-38.
    4. Nunn, Charles L. & Thrall, Peter H. & Kappeler, Peter M., 2014. "Shared resources and disease dynamics in spatially structured populations," Ecological Modelling, Elsevier, vol. 272(C), pages 198-207.
    5. Bonnell, Tyler R. & Ghai, Ria R. & Goldberg, Tony L. & Sengupta, Raja & Chapman, Colin A., 2016. "Spatial patterns of persistence for environmentally transmitted parasites: Effects of regional climate and local landscape," Ecological Modelling, Elsevier, vol. 338(C), pages 78-89.
    6. Perez, Liliana & Dragicevic, Suzana, 2012. "Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model," Ecological Modelling, Elsevier, vol. 231(C), pages 53-64.

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