Modelling the dispersal of the two main hosts of the raccoon rabies variant in heterogeneous environments with landscape genetics

Abstract

Predicting the geographic spread of wildlife epidemics requires knowledge about the movement patterns of disease hosts or vectors. The field of landscape genetics provides valuable approaches to study dispersal indirectly, which in turn may be used to understand patterns of disease spread. Here, we applied landscape genetic analyses and spatially explicit models to identify the potential path of raccoon rabies spread in a mesocarnivore community. We used relatedness estimates derived from microsatellite genotypes of raccoons and striped skunks to investigate their dispersal patterns in a heterogeneous landscape composed predominantly of agricultural, forested and residential areas. Samples were collected in an area covering 22 000 km2 in southern Québec, where the raccoon rabies variant (RRV) was first detected in 2006. Multiple regressions on distance matrices revealed that genetic distance among male raccoons was strictly a function of geographic distance, while dispersal in female raccoons was significantly reduced by the presence of agricultural fields. In skunks, our results suggested that dispersal is increased in edge habitats between fields and forest fragments in both males and females. Resistance modelling allowed us to identify likely dispersal corridors used by these two rabies hosts, which may prove especially helpful for surveillance and control (e.g. oral vaccination) activities.

Modelling seasonal habitat suitability and connectivity for feral pigs in northern Australia: towards risk-based management of infectious animal diseases with wildlife hosts

“…Risk-based disease management requires better spatial knowledge of the links (dispersal paths or 'corridors') between populations (Riley 2007;Cowled & Garner 2008;Rioux Paquette et al 2014). Habitat connectivity models are well suited to deliver such knowledge, but have not been widely applied to investigate risk of disease spread (Kool et al 2013).…”

“…Further, recent technical developments have allowed computation of movement probabilities (i.e.' matrix connectivity') across large landscapes independent of habitat patches (Koen et al 2014;Pelletier et al 2014). …”

“…Third, we modelled matrix connectivity using the methodology developed by Pelletier et al (2014) for regional-scale applications of the circuit-theoretic approach (McRae et al 2008). Fourth, we estimated patch connectivity, by computing, for each habitat patch, the total area the patch is connected to via dispersal corridors.…”

“…Circuitscape computes the current density for each pixel, which can be interpreted as the probability of a species moving through that pixel via random walk theory (McRae et al 2008). We used a recent extension of Circuitscape described by Pelletier et al (2014), which models movement probabilities across entire landscapes rather than between nodes. It does not require delineated habitat patches (Moilanen 2011;Koen et al 2014) and overcomes computational limitations for regional scale applications (see Leonard et al 2016 for a high-performance computing solution).…”

“…This framework was suited to our study aims as it (a) modelled movement probabilities along all possible dispersal paths (which is indicative of disease spread risk) and (b) did not rely on strict distinctions between nodes (patches), edges Circuit-theoretic models can be computationally prohibitive when applied over large areas . We used a recent extension (Pelletier et al 2014) that models matrix connectivity (as 'omnidirectional current density') on buffered tiles. These can join to form arbitrarily large study areas (here 175 million pixels).…”