Interplay between contact risk, conspecific density, and landscape connectivity: An individual-based modeling framework

Interplay between contact risk, conspecific density, and landscape connectivity: An individual-based modeling framework. Tardy, O., Massé, A., Pelletier, F., & Fortin, D. Ecological Modelling, 373:25-38, 4, 2018.

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In many host-pathogen systems, pathogen transmission requires close contact between infectious and susceptible hosts. The contact rates among individuals depend upon how they move in the landscape because functional connectivity can affect interactions between individuals. Yet few studies have explored the interplay between contact rates, conspecific density, and functional connectivity. Using a spatially explicit individual-based model, we investigated how empirical movement rules translate into spatial patterns of contact rates among disease hosts in complex landscapes. We developed dynamic models of functional connectivity by characterizing movement behaviors of radio-collared raccoons, which are the main hosts of the raccoon rabies virus. On this basis, we simulated space-use dynamics of raccoons in virtual landscapes varying in conspecific density, forest availability, and landscape connectivity. We then characterized spatial patterns in the density of per capita contact rates of simulated raccoons. Radio-collared raccoons were more likely to choose large habitat patches that were reached by traveling along least-cost paths, and had relatively long residence times in anthropogenic areas, especially during daytime. These movement rules that were applied to simulated raccoons in virtual landscapes revealed three key patterns in contact rates. First, few simulated raccoons were responsible for most contacts between individuals, a pattern that emerged even though all simulated raccoons obeyed the same movement rules. Second, per capita contact rates increased linearly with individual density under most conditions, which indicates that raccoon rabies transmission should be density-dependent rather than frequency-dependent. Third, functional connectivity created a broad range of patterns in the density of per capita contact rates from decreasing to increasing values, depending upon the availability of land cover types. Overall, the contacts between hosts tended to occur at highest densities in forests, anthropogenic areas, and agricultural corridors. We show that complex patterns of contact rates can emerge from simple empirical movement rules and, therefore, can be key drivers of disease spread dynamics. The strong spatial heterogeneity observed in contact rates implies that the effectiveness of particular control interventions can strongly vary depending upon host density, landscape composition, and functional connectivity. This study provides key functional relationships for tailoring interventions to changes in local conditions.

@article{
 title = {Interplay between contact risk, conspecific density, and landscape connectivity: An individual-based modeling framework},
 type = {article},
 year = {2018},
 keywords = {Animal movement,Contact rate,Individual-based model,Infectious disease management,Landscape connectivity,Raccoon},
 pages = {25-38},
 volume = {373},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S0304380018300504},
 month = {4},
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 last_modified = {2020-02-04T21:30:48.804Z},
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 citation_key = {Tardy2018},
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 abstract = {In many host-pathogen systems, pathogen transmission requires close contact between infectious and susceptible hosts. The contact rates among individuals depend upon how they move in the landscape because functional connectivity can affect interactions between individuals. Yet few studies have explored the interplay between contact rates, conspecific density, and functional connectivity. Using a spatially explicit individual-based model, we investigated how empirical movement rules translate into spatial patterns of contact rates among disease hosts in complex landscapes. We developed dynamic models of functional connectivity by characterizing movement behaviors of radio-collared raccoons, which are the main hosts of the raccoon rabies virus. On this basis, we simulated space-use dynamics of raccoons in virtual landscapes varying in conspecific density, forest availability, and landscape connectivity. We then characterized spatial patterns in the density of per capita contact rates of simulated raccoons. Radio-collared raccoons were more likely to choose large habitat patches that were reached by traveling along least-cost paths, and had relatively long residence times in anthropogenic areas, especially during daytime. These movement rules that were applied to simulated raccoons in virtual landscapes revealed three key patterns in contact rates. First, few simulated raccoons were responsible for most contacts between individuals, a pattern that emerged even though all simulated raccoons obeyed the same movement rules. Second, per capita contact rates increased linearly with individual density under most conditions, which indicates that raccoon rabies transmission should be density-dependent rather than frequency-dependent. Third, functional connectivity created a broad range of patterns in the density of per capita contact rates from decreasing to increasing values, depending upon the availability of land cover types. Overall, the contacts between hosts tended to occur at highest densities in forests, anthropogenic areas, and agricultural corridors. We show that complex patterns of contact rates can emerge from simple empirical movement rules and, therefore, can be key drivers of disease spread dynamics. The strong spatial heterogeneity observed in contact rates implies that the effectiveness of particular control interventions can strongly vary depending upon host density, landscape composition, and functional connectivity. This study provides key functional relationships for tailoring interventions to changes in local conditions.},
 bibtype = {article},
 author = {Tardy, Olivia and Massé, Ariane and Pelletier, Fanie and Fortin, Daniel},
 doi = {10.1016/j.ecolmodel.2018.02.003},
 journal = {Ecological Modelling}
}

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