Landscape genetics of high mountain frog metapopulations

Abstract

Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between-site (landscape resistance) landscape characteristics and at-site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between-site and at-site landscape processes in metapopulations of Columbia spotted frogs (Rana luteiventris) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at-site landscape process) and resistance (e.g. between-site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at-site) and topographic complexity (between-site). Conversely, site productivity (as measured by heat load index, at-site) and growing season (as measured by frost-free period between-sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source-sink dynamics. In conclusion, gravity models provide a powerful new modelling approach for examining a wide range of both basic and applied questions in landscape genetics.

Quantifying functional connectivity: The role of breeding habitat, abundance, and landscape features on range‐wide gene flow in sage‐grouse

“…In our analysis, inclusion of abundance indices acted to decrease resistance around population centers and increase the resistance in areas with low abundance, but our approach could not test the effect of population size on the attractiveness of individual locations to dispersers. Thus, using models where local abundance can modify the number of dispersers into, or out of, a population (Murphy, Dezzani, Pilliod, & Storfer, 2010; Row, Oyler‐McCance, & Fedy, 2016), might provide more insight into the effects of abundance on differentiation. We only included abundance estimates of males during the breeding season, but it is possible that abundance during other seasons or estimates of effective population size may be of greater importance to functional connectivity.…”

Linking extinction–colonization dynamics to genetic structure in a salamander metapopulation

“…Predatory fish have negative effects on amphibian survival, abundance and distribution [62 -64], and wetlands with short hydroperiods can decrease adult survival and the probability of successful recruitment in A. tigrinum [32]. We predicted sites with predatory fish and short hydroperiod would be subject to strong genetic drift owing to low population size, bottlenecks or recurring founder events following extinction, which should all result in high local F ST [6,65]. Hydroperiod had a weak negative effect on F ST , suggesting that long hydroperiod may partly limit the effect of genetic drift.…”

Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change

“…We estimated inter‐individual GD, by calculating the ratio proportion of shared alleles (Dps, GD = (1 − Dps); Bowcock et al., 1994) for each pairwise combination of individuals using GenAlEx v. 6.0 (Peakall & Smouse, 2006). Dps is a commonly used individual‐based genetic distance measure in landscape genetic studies and has been shown to accurately reflect SGS and connectivity at small spatial scales (Murphy, Dezzani, Pilliod, & Storfer, 2010). …”