Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum)

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation‐by‐distance and isolation‐by‐resistance models for this land snail, with an equal fit to least‐cost paths and circuit‐theory‐based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale‐dependent processes.     

Landscape characteristics influencing the genetic structure of greater sage‐grouse within the stronghold of their range: a holistic modeling approach

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high‐ and low‐quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage‐grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low‐quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33‐km‐diameter moving windows were preferred, suggesting small‐scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.     

Applying landscape genetics to the microbial world

Landscape genetics, which explicitly quantifies landscape effects on gene flow and adaptation, has largely focused on macroorganisms, with little attention given to microorganisms. This is despite overwhelming evidence that microorganisms exhibit spatial genetic structuring in relation to environmental variables. The increasing accessibility of genomic data has opened up the opportunity for landscape genetics to embrace the world of microorganisms, which may be thought of as ‘the invisible regulators’ of the macroecological world. Recent developments in bioinformatics and increased data accessibility have accelerated our ability to identify microbial taxa and characterize their genetic diversity. However, the influence of the landscape matrix and dynamic environmental factors on microorganism genetic dispersal and adaptation has been little explored. Also, because many microorganisms coinhabit or codisperse with macroorganisms, landscape genomic approaches may improve insights into how micro‐ and macroorganisms reciprocally interact to create spatial genetic structure. Conducting landscape genetic analyses on microorganisms requires that we accommodate shifts in spatial and temporal scales, presenting new conceptual and methodological challenges not yet explored in ‘macro’‐landscape genetics. We argue that there is much value to be gained for microbial ecologists from embracing landscape genetic approaches. We provide a case for integrating landscape genetic methods into microecological studies and discuss specific considerations associated with the novel challenges this brings. We anticipate that microorganism landscape genetic studies will provide new insights into both micro‐ and macroecological processes and expand our knowledge of species’ distributions, adaptive mechanisms and species’ interactions in changing environments.     

Landscape genetics identifies streams and drainage infrastructure as dispersal corridors for an endangered wetland bird

Anthropogenic alterations to landscape structure and composition can have significant impacts on biodiversity, potentially leading to species extinctions. Population‐level impacts of landscape change are mediated by animal behaviors, in particular dispersal behavior. Little is known about the dispersal habits of rails (Rallidae) due to their cryptic behavior and tendency to occupy densely vegetated habitats. The effects of landscape structure on the movement behavior of waterbirds in general are poorly studied due to their reputation for having high dispersal abilities. We used a landscape genetic approach to test hypotheses of landscape effects on dispersal behavior of the Hawaiian gallinule (Gallinula galeata sandvicensis), an endangered subspecies endemic to the Hawaiian Islands. We created a suite of alternative resistance surfaces representing biologically plausible a priori hypotheses of how gallinules might navigate the landscape matrix and ranked these surfaces by their ability to explain observed patterns in genetic distance among 12 populations on the island of O`ahu. We modeled effective distance among wetland locations on all surfaces using both cumulative least‐cost‐path and resistance‐distance approaches and evaluated relative model performance using Mantel tests, a causal modeling approach, and the mixed‐model maximum‐likelihood population‐effects framework. Across all genetic markers, simulation methods, and model comparison metrics, surfaces that treated linear water features like streams, ditches, and canals as corridors for gallinule movement outperformed all other models. This is the first landscape genetic study on the movement behavior of any waterbird species to our knowledge. Our results indicate that lotic water features, including drainage infrastructure previously thought to be of minimal habitat value, contribute to habitat connectivity in this listed subspecies.     

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.     

Individual dispersal,landscape connectivity and ecological networks

Connectivity is classically considered an emergent property of landscapes encapsulating individuals' flows across space. However, its operational use requires a precise understanding of why and how organisms disperse. Such movements, and hence landscape connectivity, will obviously vary according to both organism properties and landscape features. We review whether landscape connectivity estimates could gain in both precision and generality by incorporating three fundamental outcomes of dispersal theory. Firstly, dispersal is a multi‐causal process; its restriction to an ‘escape reaction’ to environmental unsuitability is an oversimplification, as dispersing individuals can leave excellent quality habitat patches or stay in poor‐quality habitats according to the relative costs and benefits of dispersal and philopatry. Secondly, species, populations and individuals do not always react similarly to those cues that trigger dispersal, which sometimes results in contrasting dispersal strategies. Finally, dispersal is a major component of fitness and is thus under strong selective pressures, which could generate rapid adaptations of dispersal strategies. Such evolutionary responses will entail spatiotemporal variation in landscape connectivity. We thus strongly recommend the use of genetic tools to: (i) assess gene flow intensity and direction among populations in a given landscape; and (ii) accurately estimate landscape features impacting gene flow, and hence landscape connectivity. Such approaches will provide the basic data for planning corridors or stepping stones aiming at (re)connecting local populations of a given species in a given landscape. This strategy is clearly species‐ and landscape‐specific. But we suggest that the ecological network in a given landscape could be designed by stacking up such linkages designed for several species living in different ecosystems. This procedure relies on the use of umbrella species that are representative of other species living in the same ecosystem.     

Variation in fine‐scale genetic structure and local dispersal patterns between peripheral populations of a South American passerine bird

The distribution of suitable habitat influences natal and breeding dispersal at small spatial scales, resulting in strong microgeographic genetic structure. Although environmental variation can promote interpopulation differences in dispersal behavior and local spatial patterns, the effects of distinct ecological conditions on within‐species variation in dispersal strategies and in fine‐scale genetic structure remain poorly understood. We studied local dispersal and fine‐scale genetic structure in the thorn‐tailed rayadito (Aphrastura spinicauda), a South American bird that breeds along a wide latitudinal gradient. We combine capture‐mark‐recapture data from eight breeding seasons and molecular genetics to compare two peripheral populations with contrasting environments in Chile: Navarino Island, a continuous and low density habitat, and Fray Jorge National Park, a fragmented, densely populated and more stressful environment. Natal dispersal showed no sex bias in Navarino but was female‐biased in the more dense population in Fray Jorge. In the latter, male movements were restricted, and some birds seemed to skip breeding in their first year, suggesting habitat saturation. Breeding dispersal was limited in both populations, with males being more philopatric than females. Spatial genetic autocorrelation analyzes using 13 polymorphic microsatellite loci confirmed the observed dispersal patterns: a fine‐scale genetic structure was only detectable for males in Fray Jorge for distances up to 450 m. Furthermore, two‐dimensional autocorrelation analyzes and estimates of genetic relatedness indicated that related males tended to be spatially clustered in this population. Our study shows evidence for context‐dependent variation in natal dispersal and corresponding local genetic structure in peripheral populations of this bird. It seems likely that the costs of dispersal are higher in the fragmented and higher density environment in Fray Jorge, particularly for males. The observed differences in microgeographic genetic structure for rayaditos might reflect the genetic consequences of population‐specific responses to contrasting environmental pressures near the range limits of its distribution.     

Watershed‐level brook trout genetic structuring: Evaluation and application of riverscape genetics models

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Landscape Effects on the Genetic Structure of the Ground Beetle Poecilus Versicolor STURM 1824

The impact of landscape structure on the genetic structure of an abundant and widespread carabid beetle Poecilus versicolor was analysed in a low mountain range (Lahn-Dill-Bergland, Germany) by means of RAPD-PCR. Habitat patch and landscape characteristics were included as independent variables into a GIS oriented correlative approach. Results indicated a high overall genetic diversity of the beetle population and suggest that the mobility of P. versicolor is much higher than previously thought. An equilibrium among migration and genetic drift has not been reached yet, therefore it is very likely that revealed differences in allele frequencies reflect current pattern of genetic diversity. Landscape characteristics at a scale of 1000 × 1000 m surrounding each study site significantly affected the genetic population structure of the carabid beetle, while it is only indirect affected by patch conditions. Opposite effects of grassland and arable land on genetic diversity demonstrated that grassland in the surrounding landscape facilitates dispersal, while arable land apparently decreases successful dispersal, but both factors increase population density on the study site. We conclude that the local population genetic structure of a widespread and highly mobile species as P. versicolor is strongly affected by the amount of suitable habitat in a landscape of large habitat proportion. The inclusion of landscape characteristics offers a powerful way for analysing effects on genetic diversity. Further studies on conservation genetics should incorporate a landscape perspective in order to assess the loss of local genetic diversity.     

Inferring landscape effects on dispersal from genetic distances: how far can we go?

Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.     

Landscape genetic analyses reveal cryptic population structure and putative selection gradients in a large-scale estuarine environment

Disentangling the relative contributions of selective and neutral processes underlying phenotypic and genetic variation under natural, environmental conditions remains a central challenge in evolutionary ecology. However, much of the variation that could be informative in this area of research is likely to be cryptic in nature; thus, the identification of wild populations suitable for study may be problematic. We use a landscape genetics approach to identify such populations of three-spined stickleback inhabiting the Saint Lawrence River estuary. We sampled 1865 adult fish over multiple years. Individuals were genotyped for nine microsatellite loci, and georeferenced multilocus data were used to infer population groupings, as well as locations of genetic discontinuities, under a Bayesian model framework ( geneland ). We modelled environmental data using nonparametric multiple regression to explain genetic differentiation as a function of spatio-ecological effects. Additionally, we used genotype data to estimate dispersal and gene flow to parameterize a simple model predicting adaptive vs. plastic divergence between demes. We demonstrate a bipartite division of the genetic landscape into freshwater and maritime zones, independent of geographical distance. Moreover, we show that the greatest proportion of genetic variation (31.5%) is explained by environmental differences. However, the potential for either adaptive or plastic divergence between demes is highly dependent upon the strength of migration and selection. Consequently, we highlight the utility of landscape genetics as a tool for hypothesis generation and experimental design, to identify focal populations and putative selection gradients, in order to distinguish between phenotypic plasticity and local adaptation.     

The number of breeders explains genetic connectivity in an endangered bird

Connectivity is central to ecology and evolution as it focuses on the movement of individuals or genes across landscapes. Genetic connectivity approaches aim to understand gene flow but often estimate it indirectly based on metrics of genetic differentiation, which can also be affected by other evolutionary forces such as genetic drift. Gene flow and genetic drift are driven by separate ecological mechanisms with potentially differing effects on genetic differentiation and interpretations of genetic connectivity. The ecological mechanisms contributing to gene flow and genetic drift are primarily effective dispersal, or movement followed by successful reproduction, and the number of breeders in a local population, N_b, respectively. Yet, rarely are these ecological mechanisms and genetic connectivity measured simultaneously across landscapes. We examine the roles of effective dispersal and N_b on genetic connectivity across the entire range of the endangered snail kite (Rostrhamus sociabilis plumbeus), between 2006–2015. We find that both N_b and effective dispersal are important predictors of genetic connectivity across this landscape, but that N_b has a 3 × stronger effect on genetic connectivity. Furthermore, N_b is positively correlated with heterozygosity and allelic richness within patches, suggesting a potentially important role of genetic drift, in addition to gene flow, on genetic connectivity. These results emphasize that conservation efforts should focus on not only between‐patch processes of movement but also within‐patch processes regarding habitat quality and local population size for increasing genetic connectivity.     

Immune gene variability influences roe deer natal dispersal

Dispersal is a key life‐history trait governing the response of individuals, populations and species to changing environmental conditions. In the context of global change, it is therefore essential to better understand the respective role of condition‐, phenotype‐ and genetic‐dependent drivers of dispersal behaviour. Although the importance of immune function and pathogen infestation in determining patterns of dispersal is increasingly recognised, no study to our knowledge has yet investigated the influence of immune gene variability on dispersal behaviour. Here, we filled this knowledge gap by assessing whether individual heterozygosity at five immune gene loci (one from the Major histocompatibility complex and four from encoding Toll‐like receptors) influences roe deer natal dispersal. We found that dispersal propensity was affected by immune gene diversity, suggesting potential pathogen‐mediated selection through over‐dominance. However, the direction of this effect differed between high and low quality individuals, suggesting that dispersal propensity is driven by two different mechanisms. In support of the condition‐dependent dispersal hypothesis, dispersal propensity increased with increasing body mass and, among high quality individuals only (standardized body mass > 18 kg), with increasing immune gene diversity. However, among poor quality individuals, we observed the opposite pattern such that dispersal propensity was higher for individuals with lower immune gene diversity. We suggest that these poor quality individuals expressed an emergency dispersal tactic in an attempt to escape a heavily infested environment associated with poor fitness prospects. Our results have potentially important consequences in terms of population genetics and demography, as well as host–pathogen evolution.     

Using neutral cline decay to estimate contemporary dispersal: a generic tool and its application to a major crop pathogen

Dispersal is a key parameter of adaptation, invasion and persistence. Yet standard population genetics inference methods hardly distinguish it from drift and many species cannot be studied by direct mark‐recapture methods. Here, we introduce a method using rates of change in cline shapes for neutral markers to estimate contemporary dispersal. We apply it to the devastating banana pest Mycosphaerella fijiensis, a wind‐dispersed fungus for which a secondary contact zone had previously been detected using landscape genetics tools. By tracking the spatio‐temporal frequency change of 15 microsatellite markers, we find that σ, the standard deviation of parent–offspring dispersal distances, is 1.2 km/generation^1/2. The analysis is further shown robust to a large range of dispersal kernels. We conclude that combining landscape genetics approaches to detect breaks in allelic frequencies with analyses of changes in neutral genetic clines offers a powerful way to obtain ecologically relevant estimates of dispersal in many species.     

On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system

Dispersal and natural selection are key evolutionary processes shaping the distribution of phenotypic and genetic diversity. For species inhabiting complex spatial environments however, it is unclear how the balance between gene flow and selection may be influenced by landscape heterogeneity and environmental variation. Here, we evaluated the effects of dendritic landscape structure and the selective forces of hydroclimatic variation on population genomic parameters for the Murray River rainbowfish, Melanotaenia fluviatilis across the Murray–Darling Basin, Australia. We genotyped 249 rainbowfish at 17,503 high‐quality SNP loci and integrated these with models of network connectivity and high‐resolution environmental data within a riverscape genomics framework. We tested competing models of gene flow before using multivariate genotype–environment association (GEA) analysis to test for signals of adaptive divergence associated with hydroclimatic variation. Patterns of neutral genetic variation were consistent with expectations based on the stream hierarchy model and M. fluviatilis’ moderate dispersal ability. Models incorporating dendritic network structure suggested that landscape heterogeneity is a more important factor determining connectivity and gene flow than waterway distance. Extending these results, we also introduce a novel approach to controlling for the unique effects of dendritic network structure in GEA analyses of populations of aquatic species. We identified 146 candidate loci potentially underlying a polygenic adaptive response to seasonal fluctuations in stream flow and variation in the relative timing of temperature and precipitation extremes. Our findings underscore an emerging predominant role for seasonal variation in hydroclimatic conditions driving local adaptation and are relevant for informing proactive conservation management.     

Matrix quality and disturbance frequency drive evolution of species behavior at habitat boundaries

Previous theoretical studies suggest that a species' landscape should influence the evolution of its dispersal characteristics, because landscape structure affects the costs and benefits of dispersal. However, these studies have not considered the evolution of boundary crossing, that is, the tendency of animals to cross from habitat to nonhabitat (“matrix”). It is important to understand this dispersal behavior, because of its effects on the probability of population persistence. Boundary‐crossing behavior drives the rate of interaction with matrix, and thus, it influences the rate of movement among populations and the risk of dispersal mortality. We used an individual‐based, spatially explicit model to simulate the evolution of boundary crossing in response to landscape structure. Our simulations predict higher evolved probabilities of boundary crossing in landscapes with more habitat, less fragmented habitat, higher‐quality matrix, and more frequent disturbances (i.e., fewer generations between local population extinction events). Unexpectedly, our simulations also suggest that matrix quality and disturbance frequency have much stronger effects on the evolution of boundary crossing than either habitat amount or habitat fragmentation. Our results suggest that boundary‐crossing responses are most affected by the costs of dispersal through matrix and the benefits of escaping local extinction events. Evolution of optimal behavior at habitat boundaries in response to the landscape may have implications for species in human‐altered landscapes, because this behavior may become suboptimal if the landscape changes faster than the species' evolutionary response to that change. Understanding how matrix quality and habitat disturbance drive evolution of behavior at boundaries, and how this in turn influences the extinction risk of species in human‐altered landscapes should help us identify species of conservation concern and target them for management.     

Landscape genetics in the subterranean rodent <Emphasis Type="Italic">Ctenomys</Emphasis> “<Emphasis Type="Italic">chasiquensis</Emphasis>” associated with highly disturbed habitats from the southeastern Pampas region,Argentina

Studies of genetic differentiation in fragmented environments help us to identify those landscape features that most affect gene flow and dispersal patterns. Particularly, the assessment of the relative significance of intrinsic biological and environmental factors affecting the genetic structure of populations becomes crucial. In this work, we assess the current dispersal patterns and population structure of Ctenomys “chasiquensis”, a vulnerable and endemic subterranean rodent distributed on a small area in Central Argentina, using 9 polymorphic microsatellite loci. We use landscape genetics approaches to assess the relationship between genetic connectivity among populations and environmental attributes. Our analyses show that populations of C. “chasiquensis” are moderately to highly structured at a regional level. This pattern is most likely the outcome of substantial gene flow on the more homogeneous sand dune habitat of the Northwest of its distributional range, in conjunction with an important degree of isolation of eastern and southwestern populations, where the optimal habitat is surrounded by a highly fragmented landscape. Landscape genetics analysis suggests that habitat quality and longitude were the environmental factors most strongly associated with genetic differentiation/uniqueness of populations. In conclusion, our results indicate an important genetic structure in this species, even at a small spatial scale, suggesting that contemporary habitat fragmentation increases population differentiation.     

Quantifying the lag time to detect barriers in landscape genetics

Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individual‐based simulations to examine the ability of an individual‐based statistic [Mantel’s r using the proportion of shared alleles’ statistic (Dps)] and population‐based statistic (F_ST) to detect barriers. We simulated a range of movement strategies including nearest neighbour dispersal, long‐distance dispersal and panmixia. The lag time for the signal of a new barrier to become established is short using Mantel’s r (1–15 generations). F_ST required approximately 200 generations to reach 50% of its equilibrium maximum, although G’_ST performed much like Mantel’s r. In strong contrast, F_ST and Mantel’s r perform similarly following the removal of a barrier formerly dividing a population. Also, given neighbour mating and very short‐distance dispersal strategies, historical discontinuities from more than 100 generations ago might still be detectable with either method. This suggests that historical events and landscapes could have long‐term effects that confound inferences about the impacts of current landscape features on gene flow for species with very little long‐distance dispersal. Nonetheless, populations of organisms with relatively large dispersal distances will lose the signal of a former barrier within less than 15 generations, suggesting that individual‐based landscape genetic approaches can improve our ability to measure effects of existing landscape features on genetic structure and connectivity.     

Landscape genetics of an endangered lemur (Propithecus tattersalli) within its entire fragmented range

Habitat fragmentation may strongly reduce individuals’ dispersal among resource patches and hence influence population distribution and persistence. We studied the impact of landscape heterogeneity on the dispersal of the golden‐crowned sifaka (Propithecus tattersalli), an endangered social lemur species living in a restricted and highly fragmented landscape. We combined spatial analysis and population genetics methods to describe population units and identify the environmental factors which best predict the rates and patterns of genetic differentiation within and between populations. We used non‐invasive methods to genotype 230 individuals at 13 microsatellites in all the main forest fragments of its entire distribution area. Our analyses suggest that the Manankolana River and geographical distance are the primary structuring factors, while a national road crossing the region does not seem to impede gene flow. Altogether, our results are in agreement with a limited influence of forest habitat connectivity on gene flow patterns (except for North of the species’ range), suggesting that dispersal is still possible today among most forest patches for this species. Within forest patches, we find that dispersal is mainly among neighbouring social groups, hence confirming previous behavioural observations.     

Mechanistic insights into landscape genetic structure of two tropical amphibians using field‐derived resistance surfaces

Conversion of forests to agriculture often fragments distributions of forest species and can disrupt gene flow. We examined effects of prevalent land uses on genetic connectivity of two amphibian species in northeastern Costa Rica. We incorporated data from field surveys and experiments to develop resistance surfaces that represent local mechanisms hypothesized to modify dispersal success of amphibians, such as habitat‐specific predation and desiccation risk. Because time lags can exist between forest conversion and genetic responses, we evaluated landscape effects using land‐cover data from different time periods. Populations of both species were structured at similar spatial scales but exhibited differing responses to landscape features. Litter frog population differentiation was significantly related to landscape resistances estimated from abundance and experiment data. Model support was highest for experiment‐derived surfaces that represented responses to microclimate variation. Litter frog genetic variation was best explained by contemporary landscape configuration, indicating rapid population response to land‐use change. Poison frog genetic structure was strongly associated with geographic isolation, which explained up to 45% of genetic variation, and long‐standing barriers, such as rivers and mountains. However, there was also partial support for abundance‐ and microclimate response‐derived resistances. Differences in species responses to landscape features may be explained by overriding effects of population size on patterns of differentiation for poison frogs, but not litter frogs. In addition, pastures are likely semi‐permeable to poison frog gene flow because the species is known to use pastures when remnant vegetation is present, but litter frogs do not. Ongoing reforestation efforts will probably increase connectivity in the region by increasing tree cover and reducing area of pastures.