Sex‐specific graphs: Relating group‐specific topology to demographic and landscape data

Abstract

Sex-specific genetic structure is a commonly observed pattern among vertebrate species. Facing differential selective pressures, individuals may adopt sex-specific life history traits that ultimately shape genetic variation among populations. Although differential dispersal dynamics are commonly detected in the literature, few studies have used genetic structure to investigate sex-specific functional connectivity. The recent use of graph theoretic approaches in landscape genetics has demonstrated network capacities to describe complex system behaviours where network topology represents genetic interaction among subunits. Here, we partition the overall genetic structure into sex-specific graphs, revealing different male and female dispersal dynamics of a fisher (Pekania [Martes] pennanti) metapopulation in southern Ontario. Our analyses based on network topologies supported the hypothesis of male-biased dispersal. Furthermore, we demonstrated that the effect of the landscape, identified at the population level, could be partitioned among sex-specific strata. We found that female connectivity was negatively correlated with snow depth, whereas connectivity among males was not. Our findings underscore the potential of conducting sex-specific analysis by identifying landscape elements or configuration that differentially promotes or impedes functional connectivity between sexes, revealing processes that may otherwise remain cryptic. We propose that the sex-specific graph approach would be applicable to other vagile species where differential sex-specific processes are expected to occur.

Habitat, Climate, and Fisher and Marten Distributions

“…The energy expenditure associated with animal movement through snow varies according to snow depth and the lift it provides, together with the speed of the individual's movements (Crête and Larivière 2003). Snow conditions particularly affect fisher dispersal (Raine 1983, Krohn et al 2005, Carr et al 2007b, Garroway et al 2011, Bertrand et al 2017) because they are larger and heavier than martens and exert greater foot loading (18.2-32.0 g/cm 2 vs. 9.1-12.2 g/cm 2 ). Compared to martens, movements of fishers tend to be more strongly constrained by deep, uncompacted snow Rego 1994, Krohn et al 2005).…”

Spatial familial networks to infer demographic structure of wild populations

“…Network analyses have been used in biological and ecological studies to quantify and explore the structure of populations across numerous taxa (Bertrand et al, 2017;Dyer & Nason, 2004;Fortuna et al, 2009), but to our knowledge, this is the first to combine genetically derived pedigree data with network analysis to infer familial structure of wild populations. Network analyses are powerful and flexible methods for investigating the complex networks of interconnections between individuals within and between populations (Wasserman & Faust, 1994).…”

“…Our network was highly connected as a result of the polygamous mating system of caribou and ability for long range dispersal. Although family groups can be identified within the network, presenting varied levels of dispersal, fitness, and cohesion, the removal of edges with high Network analyses are powerful methods to assist in wildlife conservation (Bertrand et al, 2017;Dyer & Nason, 2004;Fortuna et al, 2009), but most wild populations cannot be directly observed, and demographic networks cannot be constructed. By constructing a familial network based on genetically derived parent-offspring relationships, we calculated informative measures to draw a much finer picture of their individual fitness levels, pattern of demographic structure, and relative contribution of local areas to the larger population.…”

“…A larger number of analytical approaches have been developed to delineate populations and assess the extent and patterns of gene flow and dispersal (e.g., Galpern et al, 2014;Jombart et al, 2008;Pritchard, Stephens, & Donnelly, 2000). More recently, graph-theoretic approach has been used to assess population genetic structure (Dyer & Nason, 2004), investigate sex-specific dispersal processes and network structures in landscape genetics (Bertrand et al, 2017), and analyze spatial patterns of genetic variation across a species' range (Fortuna et al, 2009). In parallel, pedigree reconstructions have been done to inform on demographic parameters (Creel et al, 2003;Gobush et al, 2009;Lucena-Perez et al, 2018;McFarlane et al, 2018), yet network analyses and genetically derived pedigrees have been used as two separate methodological frameworks.…”

Landscape permeability and individual variation in a dispersal-linked gene jointly determine genetic structure in the Glanville fritillary butterfly

“…; Bertrand et al. ), to our knowledge, only two papers have integrated non‐sex related variation in dispersal traits: DiLeo et al. () found that individual variation in the number of flowers on dogwood trees influenced spatial patterns of gene flow beyond the effects of Euclidean distance; and McDevitt et al.…”