Genetic and phenotypic population divergence on a microgeographic scale in brown trout

Salmonid populations of many rivers are rapidly declining. One possible explanation is that habitat fragmentation increases genetic drift and reduces the populations' potential to adapt to changing environmental conditions. We measured the genetic and eco-morphological diversity of brown trout (Salmo trutta) in a Swiss stream system, using multivariate statistics and Bayesian clustering. We found large genetic and phenotypic variation within only 40 km of stream length. Eighty-eight percent of all pairwise F(ST) comparisons and 50% of the population comparisons in body shape were significant. High success rates of population assignment tests confirmed the distinctiveness of populations in both genotype and phenotype. Spatial analysis revealed that divergence increased with waterway distance, the number of weirs, and stretches of poor habitat between sampling locations, but effects of isolation-by-distance and habitat fragmentation could not be fully disentangled. Stocking intensity varied between streams but did not appear to erode genetic diversity within populations. A lack of association between phenotypic and genetic divergence points to a role of local adaptation or phenotypically plastic responses to habitat heterogeneity. Indeed, body shape could be largely explained by topographic stream slope, and variation in overall phenotype matched the flow regimes of the respective habitats.     

Are populations like a circuit? Comparing isolation by resistance to a new coalescent‐based method

A number of methods commonly used in landscape genetics use an analogy to electrical resistance on a network to describe and fit barriers to movement across the landscape using genetic distance data. These are motivated by a mathematical equivalence between electrical resistance between two nodes of a network and the ‘commute time’, which is the mean time for a random walk on that network to leave one node, visit the other, and return. However, genetic data are more accurately modelled by a different quantity, the coalescence time. Here, we describe the differences between resistance distance and coalescence time, and explore the consequences for inference. We implemented a Bayesian method to infer effective movement rates and population sizes under both these models, and found that inference using commute times could produce misleading results in the presence of biased gene flow. We then used forwards‐time simulation with continuous geography to demonstrate that coalescence‐based inference remains more accurate than resistance‐based methods on realistic data, but difficulties highlight the need for methods that explicitly model continuous, heterogeneous geography.     

Natural and anthropogenic determinants of genetic structure in the largest remaining population of the endangered golden-brown mouse lemur, Microcebus ravelobensis

Genetic differentiation between natural populations is best understood as a result of both natural and anthropogenic factors. Genetic studies on large populations still living under relatively undisturbed conditions are extremely valuable to disentangle these influences. The effect of three natural (geographic distance, landscape, dispersal) factors and two anthropogenic factors (road, savannah) on gene flow was analyzed in the largest remaining forest region in the range of the endangered golden-brown mouse lemur in Madagascar. A total of 187 individuals from 12 sites were sampled and genotyped at eight polymorphic microsatellite loci. All sites exhibited similar levels of genetic variation. The level of genetic differentiation was low to moderate with pairwise F(ST) values ranging from -0.002 to 0.12, but most were significant and all sites exhibited high self-assignment rates. A spatial autocorrelation analysis was performed at two geographic scales revealing a pattern of isolation-by-distance and suggesting that no clear differences exist between male and female local dispersal. Two Bayesian approaches revealed that a stretch of savannah represented a significant barrier to movement, whereas the influence of the road on gene flow was less clear. Finally, we found that landscape characteristics, in particular altitude, play a role in the functional connectivity of the sites. The study underlines the importance of studies in relatively undisturbed conditions for the interpretation of population genetics data in fragmented environments. The results are discussed in terms of their conservation relevance for forest-dwelling animals such as most primate species.     

Relationships between migration rates and landscape resistance assessed using individual-based simulations

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic structure. We used classical Wright-Fisher models and spatially explicit, individual-based, landscape genetic models to simulate gene flow via dispersal and mating in a series of landscapes representing two patches of habitat separated by a barrier. We developed a mathematical formula that predicts the relationship between barrier strength (i.e., permeability) and the migration rate (m) across the barrier, thereby linking spatially explicit landscape genetics to classical population genetics theory. We then assessed the reliability of the function by obtaining population genetics parameters (m, F(ST) ) using simulations for both spatially explicit and Wright-Fisher simulation models for a range of gene flow rates. Next, we show that relaxing some of the assumptions of the Wright-Fisher model can substantially change population substructure (i.e., F(ST) ). For example, isolation by distance among individuals on each side of a barrier maintains an F(ST) of ～0.20 regardless of migration rate across the barrier, whereas panmixia on each side of the barrier results in an F(ST) that changes with m as predicted by classical population genetics theory. We suggest that individual-based, spatially explicit modelling provides a general framework to investigate how interactions between movement and landscape resistance drive population genetic patterns and connectivity across complex landscapes.     

In-stream and overland dispersal across a river network influences gene flow in a freshwater insect, Calopteryx splendens

Gene flow in riverine species is constrained by the dendritic (branching) structure of the river network. Spatial genetic structure (SGS) of freshwater insects is particularly influenced by catchment characteristics and land use in the surroundings of the river. Gene flow also depends on the life cycle of organisms. Aquatic larvae mainly drift downstream whereas flying adults can disperse actively overland and along watercourses. In-stream movements can generate isolation by distance (IBD) at a local scale and differentiation between subcatchments. However, these patterns can be disrupted by overland dispersal. We studied SGS across the Loire River in the damselfly Calopteryx splendens which is able to disperse along and between watercourses. Our sampling design allowed us to test for overland dispersal effects on genetic differentiation between watercourses. Amplified fragment length polymorphism markers revealed high genetic differentiation at the catchment scale but the genetic structure did not reflect the geographical structure of sampling sites. We observed IBD patterns when considering the distance following the watercourse but also the Euclidean distance, i.e. the shortest distance, between pairs of sites. Altogether, our results support the hypothesis of overland dispersal between watercourses. From a conservation perspective, attention should be paid to the actual pathways of gene flow across complex landscapes such as river networks.     

Isolation by distance,resistance and/or clusters? Lessons learned from a forest‐dwelling carnivore inhabiting a heterogeneous landscape

Landscape genetics provides a valuable framework to understand how landscape features influence gene flow and to disentangle the factors that lead to discrete and/or clinal population structure. Here, we attempt to differentiate between these processes in a forest‐dwelling small carnivore [European pine marten (Martes martes)]. Specifically, we used complementary analytical approaches to quantify the spatially explicit genetic structure and diversity and analyse patterns of gene flow for 140 individuals genotyped at 15 microsatellite loci. We first used spatially explicit and nonspatial Bayesian clustering algorithms to partition the sample into discrete clusters and evaluate hypotheses of ‘isolation by barriers’ (IBB). We further characterized the relationships between genetic distance and geographical (‘isolation by distance’, IBD) and ecological distances (‘isolation by resistance’, IBR) obtained from optimized landscape models. Using a reciprocal causal modelling approach, we competed the IBD, IBR and IBB hypotheses with each other to unravel factors driving population genetic structure. Additionally, we further assessed spatially explicit indices of genetic diversity using sGD across potentially overlapping genetic neighbourhoods that matched the inferred population structure. Our results revealed a complex spatial genetic cline that appears to be driven jointly by IBD and partial barriers to gene flow (IBB) associated with poor habitat and interspecific competition. Habitat loss and fragmentation, in synergy with past overharvesting and possible interspecific competition with sympatric stone marten (Martes foina), are likely the main factors responsible for the spatial genetic structure we observed. These results emphasize the need for a more thorough evaluation of discrete and clinal hypotheses governing gene flow in landscape genetic studies, and the potential influence of different limiting factors affecting genetic structure at different spatial scales.     

Small-Scale Fragmentation Effects on Local Genetic Diversity in Two Phyllostomid Bats with Different Dispersal Abilities in Panama

Habitat fragmentation is one of the greatest threats to biodiversity. Despite their importance for conservation, the genetic consequences of small-scale habitat fragmentation for bat populations are largely unknown. In this study, we linked genetic with ecological and demographic data to assess the effects of habitat fragmentation on two species of phyllostomid bats ( Uroderma bilobatum and Carollia perspicillata ) that differ in their dispersal abilities and demographic response to fragmentation. We hypothesized that population differentiation and the effect of habitat fragmentation on levels of genetic diversity will be a function of the species' mobility. We sequenced mtDNA from 232 bats caught on 11 islands in Gatún Lake, Panamá, isolated from the mainland for ca 90 yr, and in adjacent, continuous forest on the mainland. Populations of both species showed significant genetic differentiation ( F _ST). Consistent with our prediction, population subdivision was lower in the highly mobile U. bilobatum ( F _ST= 0.01) compared to the less vagile C. perspicillata ( F _ST= 0.06), and only the latter species showed a pattern indicative of isolation by distance and, in addition, an effect of fragmentation. Genetic erosion as a result of fragmentation was also only detectable in the less mobile species, C. perspicillata , where haplotype diversity was lower in island compared to mainland populations. Our results suggest that some Neotropical bat species are prone to loss of genetic variation in response to anthropogenic small-scale habitat fragmentation. In this context, our findings point toward mobility as a good predictor of a species' vulnerability to fragmentation and altered population genetic structure.