Using a genetic network to parameterize a landscape resistance surface for fishers, Martes pennanti

Abstract

Knowledge of dispersal-related gene flow is important for addressing many basic and applied questions in ecology and evolution. We used landscape genetics to understand the recovery of a recently expanded population of fishers (Martes pennanti) in Ontario, Canada. An important focus of landscape genetics is modelling the effects of landscape features on gene flow. Most often resistance surfaces in landscape genetic studies are built a priori based upon nongenetic field data or expert opinion. The resistance surface that best fits genetic data is then selected and interpreted. Given inherent biases in using expert opinion or movement data to model gene flow, we sought an alternative approach. We used estimates of conditional genetic distance derived from a network of genetic connectivity to parameterize landscape resistance and build a final resistance surface based upon information-theoretic model selection and multi-model averaging. We sampled 657 fishers from 31 landscapes, genotyped them at 16 microsatellite loci, and modelled the effects of snow depth, road density, river density, and coniferous forest on gene flow. Our final model suggested that road density, river density, and snow depth impeded gene flow during the fisher population expansion demonstrating that both human impacts and seasonal habitat variation affect gene flow for fishers. Our approach to building landscape genetic resistance surfaces mitigates many of the problems and caveats associated with using either nongenetic field data or expert opinion to derive resistance surfaces.

Isolation of peripheral populations of Canada lynx (Lynx canadensis)

“…Despite the number of empirical tests, support for this hypothesis is mixed (Colwell 2000). Rivers have been shown to impede dispersal and gene flow of a diversity of terrestrial species, including reptiles (lizards: Lamborot et al 2003), birds (Hayes and Sewlal 2004;Voelker et al 2013), and mammals (mustelids: Garroway et al 2011;primates: Ayres and Clutton-Brock 1992;Peres et al 1996). There are also examples of rivers that do not act as barriers (Patton et al 1994;Fairley et al 2002;Lougheed et al 1999;Côté et al 2012).…”

Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species

“…To understand how landscape heterogeneity may impact genetic connectivity within a focal species, researchers typically utilize field studies (for example, habitat selection or occupancy) to develop landscape resistance models. This method of hypothesis development has been successful in landscape genetics, and multiple studies have shown that important landscape features in field studies such as land cover (Goldberg and Waits, 2010;Garroway et al, 2011), climatic conditions (Row et al, 2014) and anthropogenic barriers (Blanchong et al, 2008;Latch et al, 2011) also strongly influence gene flow. When field data corroborates correlations from landscape genetics (for example, avoided habitats also prevent gene flow; Shafer et al, 2012), meaningful conclusions about genetic connectivity can be drawn and used to develop sound conservation and management plans.…”

Evaluating the relationship between trapper harvest of American martens (Martes americana) and the quantity and spatial configuration of habitat in the boreal forests of Ontario, Canada

“…Because martens avoid crossing large open areas McCullough 1984, Gosse 2005), even frozen lakes and larger rivers may restrict the movement of martens across the landscape, functionally isolating patches of suitable habitat. Garroway et al (2011) identified river density as a factor impeding fisher (Martes pennanti Erxleben) gene flow in Ontario, and the potential for water bodies to act as barriers to marten movement was acknowledged in work by Broquet et al (2006b), where lakes were given high resistance values in friction maps developed for least-cost movement modelling. The greater proportion of high-resistance, non-forested areas in the matrix surrounding patches of suitable habitat in the western study region may have resulted in a stronger relationship between trapper success and patch size.…”