Inferring landscape effects on gene flow: a new model selection framework

Conservation genomics of an endangered montane amphibian reveals low population structure, low genomic diversity and selection pressure from disease

Wildlife diseases are a major global threat to biodiversity. Boreal toads (Anaxyrus [Bufo] boreas) are a state-endangered species in the southern Rocky Mountains of Colorado and New Mexico, and a species of concern in Wyoming, largely due to lethal skin infections caused by the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd). We performed conservation and landscape genomic analyses using single nucleotide polymorphisms from double-digest, restriction site-associated DNA sequencing in combination with the development of the first boreal toad (and first North American toad) reference genome to investigate population structure, genomic diversity, landscape connectivity and adaptive divergence. Genomic diversity (π = 0.00034-0.00040) and effective population sizes (Ne = 8.9-38.4) were low, likely due to post-Pleistocene founder effects and Bd-related population crashes over the last three decades. Population structure was also low, likely due to formerly high connectivity among a higher density of geographically proximate populations. Boreal toad gene flow was facilitated by low precipitation, cold minimum temperatures, less tree canopy, low heat load and less urbanization. We found >8X more putatively adaptive loci related to Bd intensity than to all other environmental factors combined, and evidence for genes under selection related to immune response, heart development and regulation and skin function. These data suggest boreal toads in habitats with Bd have experienced stronger selection pressure from disease than from other, broad-scale environmental variations. These findings can be used by managers to conserve and recover the species through actions including reintroduction and supplementation of populations that have declined due to Bd.

Inferring landscape resistance to gene flow when genetic drift is spatially heterogeneous

In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the 'true' cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the 'true' costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the 'true' scenario (cost distance Mantel correlations), but this 'true' scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the 'true' scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.

Inferring population connectivity in eastern massasauga rattlesnakes (Sistrurus catenatus) using landscape genetics

Assessing the environmental factors that influence the ability of a threatened species to move through a landscape can be used to identify conservation actions that connect isolated populations. However, direct observations of species' movement are often limited, making the development of alternate approaches necessary. Here we use landscape genetic analyses to assess the impact of landscape features on the movement of individuals between local populations of a threatened snake, the eastern massasauga rattlesnake (Sistrurus catenatus). We linked connectivity data with habitat information from two landscapes of similar size: a large region of unfragmented habitat and a previously studied fragmented landscape consisting of isolated patches of habitat. We used this analysis to identify features of the landscape where modification or acquisition would enhance population connectivity in the fragmented region. We found evidence that current connectivity was impacted by both contemporary land-cover features, especially roads, and inherent landscape features such as elevation. Next, we derived estimates of expected movement ability using a recently developed pedigree-based approach and least-cost paths through the unfragmented landscape. We then used our pedigree and resistance map to estimate resistance polygons of the potential extent for S. catenatus movement in the fragmented landscape. These polygons identify possible sites for future corridors connecting currently isolated populations in this landscape by linking the impact of future habitat modification or land acquisition to dispersal ability in this species. Overall, our study shows how modeling landscape resistance across differently fragmented landscapes can identify habitat features that affect contemporary movement in threatened species in fragmented landscapes and how this information can be used to guide mitigation actions whose goal is to connect isolated populations.

Fencing Can Alter Gene Flow of Asian Elephant Populations within Protected Areas

The Asian elephant is mostly confined to mountainous ranges and therefore risks population fragmentation if hard protected area (PA) boundaries near steep slopes prevent movement. We tested whether elephant gene flow is (i) controlled by slope and (ii) affected by the interplay between barriers and slope. We used 176 unique genotypes obtained non-invasively from fresh elephant dung to assess individual-by-individual genetic distance across the Western Ghats of India, a biodiversity hotspot. To assess landscape distance, 36 resistance models were produced by transforming a slope raster. Core areas and corridors were calculated from the raster that provided the best correlation between the genetic and distance matrices. The influence of the closure of PAs on gene flow was examined for one region, the Nilgiri Biosphere Reserve. The best resistance raster obtained by transforming the slope occupancy model was better than Euclidean distance for explaining genetic distance, indicating that slope partially controls gene flow. Fencing elephant PAs on hilly terrain reduces core areas and disrupts corridors. Consequently, hard PA boundaries abutting slopes can fragment elephant populations, but this can be ameliorated by protecting the adjacent flatter terrain.

Landscape genetics of a sub-alpine toad: climate change predicted to induce upward range shifts via asymmetrical migration corridors

Climate change is expected to have a major hydrological impact on the core breeding habitat and migration corridors of many amphibians in the twenty-first century. The Yosemite toad (Anaxyrus canorus) is a species of meadow-specializing amphibian endemic to the high-elevation Sierra Nevada Mountains of California. Despite living entirely on federal lands, it has recently faced severe extirpations, yet our understanding of climatic influences on population connectivity is limited. In this study, we used a previously published double-digest RADseq dataset along with numerous remotely sensed habitat features in a landscape genetics framework to answer two primary questions in Yosemite National Park: (1) Which fine-scale climate, topographic, soil, and vegetation features most facilitate meadow connectivity? (2) How is climate change predicted to influence both the magnitude and net asymmetry of genetic migration? We developed an approach for simultaneously modeling multiple toad migration paths, akin to circuit theory, except raw environmental features can be separately considered. Our workflow identified the most likely migration corridors between meadows and used the unique cubist machine learning approach to fit and forecast environmental models of connectivity. We identified the permuted modeling importance of numerous snowpack-related features, such as runoff and groundwater recharge. Our results highlight the importance of considering phylogeographic structure, and asymmetrical migration in landscape genetics. We predict an upward elevational shift for this already high-elevation species, as measured by the net vector of anticipated genetic movement, and a north-eastward shift in species distribution via the network of genetic migration corridors across the park.

Absence of genetic isolation across highly fragmented landscape in the ant Temnothorax nigriceps

BACKGROUND

Human activities, including changes in agricultural landscapes, often impact biodiversity through habitat fragmentation. This potentially reduces genetic exchange between previously connected populations. Using a combination of nuclear and mitochondrial markers, we investigated (i) genetic diversity and population structure at multiple spatial scales and (ii) colony genetic structure and queen mating frequency in the ant species Temnothorax nigriceps in a highly anthropized environment.

RESULTS

Although the results highlighted genetic structure on a European spatial scale, they did not reveal an impact of fragmentation on a regional scale, and we did not observe any genetic population structure on a regional scale. Across all populations, regardless of their geographical location, colony structure suggested monogyny (a single queen per colony) and monandry (single mating). However, nestmates were more related than expected, indicating that large-scale dispersal does not fully prevent genetic isolation.

CONCLUSIONS

Despite living in fragmented patches of habitat, populations of Temnothorax nigriceps are apparently genetically not isolated at a regional scale. However, large-scale dispersal alone does not prevent genetic isolation. The ecological requirements of T. nigriceps may explain their resilience to habitat fragmentation by allowing them to survive in very small patches of suitable habitat. The deeper investigation of the diversity of functional habitats for this species should allow to appreciate better the mechanisms permitting this species to overcome the negative impacts of fragmentation.

Parthenogenesis without costs in a grasshopper with hybrid origins

The rarity of parthenogenetic species is typically attributed to the reduced genetic variability that accompanies the absence of sex, yet natural parthenogens can be surprisingly successful. Ecological success is often proposed to derive from hybridization through enhanced genetic diversity from repetitive origins or enhanced phenotypic breadth from heterosis. Here, we tested and rejected both hypotheses in a classic parthenogen, the diploid grasshopper Warramaba virgo. Genetic data revealed a single hybrid mating origin at least 0.25 million years ago, and comparative analyses of 14 physiological and life history traits showed no evidence for altered fitness relative to its sexual progenitors. Our findings imply that the rarity of parthenogenesis is due to constraints on origin rather than to rapid extinction.

Scale-dependent influence of the sagebrush community on genetic connectivity of the sagebrush obligate Gunnison sage-grouse

Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk. Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision‐making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage‐grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations. Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage‐grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.

Fine-scale genome-wide signature of Pleistocene glaciation in Thitarodes moths (Lepidoptera: Hepialidae), host of Ophiocordyceps fungus in the Hengduan Mountains

The Hengduan Mountains region is a biodiversity hotspot known for its topologically complex, deep valleys and high mountains. While landscape and glacial refugia have been evoked to explain patterns of inter-species divergence, the accumulation of intra-species (i.e. population level) genetic divergence across the mountain-valley landscape in this region has received less attention. We used genome-wide restriction site-associated DNA sequencing (RADseq) to reveal signatures of Pleistocene glaciation in populations of Thitarodes shambalaensis (Lepidoptera: Hepialidae), the host moth of parasitic Ophiocordyceps sinensis (Hypocreales: Ophiocordycipitaceae) or "caterpillar fungus" endemic to the glacier of eastern Mt. Gongga. We used moraine history along the glacier valleys to model the distribution and environmental barriers to gene flow across populations of T. shambalaensis. We found that moth populations separated by less than 10 km exhibited valley-based population genetic clustering and isolation-by-distance (IBD), while gene flow among populations was best explained by models using information about their distributions at the local last glacial maximum (LGM_L , 58 kya), not their contemporary distribution. Maximum likelihood lineage history among populations, and among subpopulations as little as 500 meters apart, recapitulated glaciation history across the landscape. We also found signals of isolated population expansion following the retreat of LGM_L glaciers. These results reveal the fine-scale, long-term historical influence of landscape and glaciation on the genetic structuring of populations of an endangered and economically important insect species. Similar mechanisms, given enough time and continued isolation, could explain the contribution of glacier refugia to the generation of species diversity among the Hengduan Mountains.

Assessment of drivers of spatial genetic variation of a ground-dwelling bird species and its implications for conservation

In modern wildlife ecology, spatial population genetic methods are becoming increasingly applied. Especially for animal species in fragmented landscapes, preservation of gene flow becomes a high priority target in order to restore genetic diversity and prevent local extinction. Within Central Europe, the Alps represent the core distribution area of the black grouse, Lyrurus tetrix. At its easternmost Alpine range, events of subpopulation extinction have already been documented in the past decades. Molecular data combined with spatial analyses can help to assess landscape effects on genetic variation and therefore can be informative for conservation management. Here, we addressed whether the genetic pattern of the easternmost Alpine black grouse metapopulation system is driven by isolation by distance or isolation by resistance. Correlative ecological niche modeling was used to assess geographic distances and landscape resistances. We then applied regression-based approaches combined with population genetic analyses based on microsatellite data to disentangle effects of isolation by distance and isolation by resistance among individuals and subpopulations. Although population genetic analyses revealed overall low levels of genetic differentiation, the ecological niche modeling showed subpopulations to be clearly delimited by habitat structures. Spatial genetic variation could be attributed to effects of isolation by distance among individuals and isolation by resistance among subpopulations, yet unknown effects might factor in. The easternmost subpopulation was the most differentiated, and at the same time, immigration was not detected; hence, its long-term survival might be threatened. Our study provides valuable insights into the spatial genetic variation of this small-scale metapopulation system of Alpine black grouse.

Evidence of spatial genetic structure in a snow leopard population from Gansu, China

Understanding the spatial structure of genetic diversity provides insights into a populations' genetic status and enables assessment of its capacity to counteract the effects of genetic drift. Such knowledge is particularly scarce for the snow leopard, a conservation flagship species of Central Asia mountains. Focusing on a snow leopard population in the Qilian mountains of Gansu Province, China, we characterised the spatial genetic patterns by incorporating spatially explicit indices of diversity and multivariate analyses, based on different inertia levels of Principal Component Analysis (PCA). We compared two datasets differing in the number of loci and individuals. We found that genetic patterns were significantly spatially structured and were characterised by a broad geographical division coupled with a fine-scale cline of differentiation. Genetic admixture was detected in two adjoining core areas characterised by higher effective population size and allelic diversity, compared to peripheral localities. The power to detect significant spatial relationships depended primarily on the number of loci, and secondarily on the number of PCA axes. Spatial patterns and indices of diversity highlighted the cryptic structure of snow leopard genetic diversity, likely driven by its ability to disperse over large distances. In combination, the species' low allelic richness and large dispersal ability result in weak genetic differentiation related to major geographical features and isolation by distance. This study illustrates how cryptic genetic patterns can be investigated and analysed at a fine spatial scale, providing insights into the spatially variable isolation effects of both geographic distance and landscape resistance.

Genetic connectivity of two marine gastropods in the Mediterranean Sea: seascape genetics reveals species-specific oceanographic drivers of gene flow

Oceanographic features such as currents, waves, temperature and salinity, together with life history traits, control patterns and rates of gene flow and contribute to shaping the population genetic structure of marine organisms. Seascape genetics is an emerging discipline that adopts a spatially explicit approach to examine biotic and abiotic factors that drive gene flow in marine environments. In this study, we examined factors that contribute to genetic differentiation in two coastal Mediterranean gastropods whose geographical ranges overlap but which inhabit different environments. The two species differ in several life history traits and in their dispersal capabilities. Genetic differentiation was relatively low for the trochid species Gibbula divaricata (F_ST  =0.059), and high for the vermetid species Dendropoma lebeche (F_ST  =0.410). Salinity emerged as the most important variable explaining the genetic structure of both species; sea surface temperature was also important for G. divaricata. For the more sessile D. lebeche, the coastline was predicted to provide important pathways for stepping-stone connectivity and gene flow. Our results provide a greater understanding of the factors influencing marine population connectivity, which may be useful to guide marine conservation and management in the Mediterranean.

Multiscale assessment of functional connectivity: Landscape genetics of eastern indigo snakes in an anthropogenically fragmented landscape in central Florida

Landscape features can strongly influence gene flow and the strength and direction of these effects may vary across spatial scales. However, few studies have evaluated methodological approaches for selecting spatial scales in landscape genetics analyses, in part because of computational challenges associated with optimizing landscape resistance surfaces (LRS). We used the federally threatened eastern indigo snake (Drymarchon couperi) in central Florida as a case study with which to compare the importance of landscape features and their scales of effect in influencing gene flow. We used genetic algorithms (ResistanceGA) to empirically optimize LRS using categorical land cover surfaces, multiscale resource selection surfaces (RSS), and four combinations of landscape covariates measured at multiple spatial scales (multisurface multiscale LRS). We compared LRS where scale was selected using pseudo- and full optimization. Multisurface multiscale LRS received more empirical support than LRS optimized from categorical land cover surfaces or RSS. Multiscale LRS with scale selected using full optimization generally outperformed those with scale selected using pseudo-optimization. Multiscale LRS with large spatial scales (1200-1800 m) received the most empirical support. Our results highlight the importance of considering landscape features across multiple spatial scales in landscape genetic analyses, particularly broad scales relative to species movement potential. Different effects of scale on home range-level movements and dispersal could explain weak associations between habitat suitability and gene flow in other studies. Our results also demonstrate the importance of large tracts of undeveloped upland habitat with heterogenous vegetation communities and low urbanization for promoting indigo snake connectivity.

Spatio-temporal variation in environmental features predicts the distribution and abundance of Ixodes scapularis

Many species have experienced dramatic changes in both geographic range and population sizes in recent history. Increases in the geographic range or population size of disease vectors have public health relevance as these increases often precipitate the emergence of infectious diseases in human populations. Accurately identifying environmental factors affecting the biogeographic patterns of vector species is a long-standing analytical challenge, stemming from a paucity of data capturing periods of rapid changes in vector demographics. We systematically investigated the occurrence and abundance of nymphal Ixodes scapularis ticks at 532 sampling locations throughout New York State (NY), USA, between 2008 and 2018, a time frame that encompasses the emergence of diseases vectored by these ticks. Analyses of these field-collected data demonstrated a range expansion into northern and western NY during the last decade. Nymphal abundances increased in newly colonised areas, while remaining stable in areas with long-standing populations over the last decade. These trends in the geographic range and abundance of nymphs correspond to both the geographic expansion of human Lyme disease cases and increases in incidence rates. Analytic models fitted to these data incorporating time, space, and environmental factors, accurately identified drivers of the observed changes in nymphal occurrence and abundance. These models accounted for the spatial and temporal variation in the occurrence and abundance of nymphs and can accurately predict nymphal population patterns in future years. Forecasting disease risk at fine spatial scales prior to the transmission season can influence both public health mitigation strategies and individual behaviours, potentially impacting tick-borne disease risk and subsequently human disease incidence.

The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.

Landscape Genetics of Plants: Challenges and Opportunities

Dispersal is one of the most important but least understood processes in plant ecology and evolutionary biology. Dispersal of seeds maintains and establishes populations, and pollen and seed dispersal are responsible for gene flow within and among populations. Traditional views of dispersal and gene flow assume models that are governed solely by geographic distance and do not account for variation in dispersal vector behavior in response to heterogenous landscapes. Landscape genetics integrates population genetics with Geographic Information Systems (GIS) to evaluate the effects of landscape features on gene flow patterns (effective dispersal). Surprisingly, relatively few landscape genetic studies have been conducted on plants. Plants present advantages because their populations are stationary, allowing more reliable estimates of the effects of landscape features on effective dispersal rates. On the other hand, plant dispersal is intrinsically complex because it depends on the habitat preferences of the plant and its pollen and seed dispersal vectors. We discuss strategies to assess the separate contributions of pollen and seed movement to effective dispersal and to delineate the effects of plant habitat quality from those of landscape features that affect vector behavior. Preliminary analyses of seed dispersal for three species indicate that isolation by landscape resistance is a better predictor of the rates and patterns of dispersal than geographic distance. Rates of effective dispersal are lower in areas of high plant habitat quality, which may be due to the effects of the shape of the dispersal kernel or to movement behaviors of biotic vectors. Landscape genetic studies in plants have the potential to provide novel insights into the process of gene flow among populations and to improve our understanding of the behavior of biotic and abiotic dispersal vectors in response to heterogeneous landscapes.

The effect of gene flow from unsampled demes in landscape genetic analysis

An assumption of correlative landscape genetic methods is that genetic differentiation at neutral markers arises solely from the degree to which the intervening landscape between individuals or populations resists gene flow. However, this assumption is violated when gene flow occurs into the sampled population from an unsampled, differentiated deme. This may happen when sampling within only a portion of a population's extent or when closely related species hybridize with the sampled population. In both cases, violation of the modelling assumptions has the potential to reduce landscape genetic model selection accuracy and result in poor inferences. We used individual-based population genetic simulations in complex landscapes within a model selection framework to explore the potential confounding effect of gene flow from unsampled demes. We hypothesized that as gene flow from outside the sampling extent increased, model selection accuracy would decrease due to the formation of a hybrid zone where allele frequencies were perturbed in a way that was not correlated with effective distances between sampled individuals. Surprisingly, we found this expectation was unfounded, because the reduced accuracy due to admixture was counteracted by an increase in allelic diversity as alleles spread from the unsampled deme into the sampled population. These new alleles increased the power to detect landscape genetic relationships and even slightly improving model selection accuracy overall. This is a reassuring result, suggesting that sampling the full extent of a population or related species that may hybridize may be unnecessary, as long as other well-established sampling requirements are met.

The Influence of Environmental Variation on the Genetic Structure of a Poison Frog Distributed Across Continuous Amazonian Rainforest

Biogeographic barriers such as rivers have been shown to shape spatial patterns of biodiversity in the Amazon basin, yet relatively little is known about the distribution of genetic variation across continuous rainforest. Here, we characterize the genetic structure of the brilliant-thighed poison frog (Allobates femoralis) across an 880-km-long transect along the Purus-Madeira interfluve south of the Amazon river, based on 64 individuals genotyped at 7609 single-nucleotide polymorphism (SNP) loci. A population tree and clustering analyses revealed 4 distinct genetic groups, one of which was strongly divergent. These genetic groups were concomitant with femoral spot coloration differences, which was intermediate within a zone of admixture between two of the groups. The location of these genetic groups did not consistently correspond to current ecological transitions between major forest types. A multimodel approach to quantify the relative influence of isolation-by-geographic distance (IBD) and isolation-by-environmental resistance (IBR) nevertheless revealed that, in addition to a strong signal of IBD, spatial genetic differentiation was explained by IBR primarily linked to dry season intensity (r2 = 8.4%) and canopy cover (r2 = 6.4%). We show significant phylogenetic divergence in the absence of obvious biogeographical barriers and that finer-scaled measures of genetic structure are associated with environmental variables also known to predict the density of A. femoralis.

Gene flow and climate-associated genetic variation in a vagile habitat specialist

Previous work in landscape genetics suggests that geographic isolation is of greater importance to genetic divergence than variation in environmental conditions. This is intuitive when configurations of suitable habitat are a dominant factor limiting dispersal and gene flow, but has not been thoroughly examined for habitat specialists with strong dispersal capability. Here, we evaluate the effects of geographic and environmental isolation on genetic divergence for a vagile invertebrate with high habitat specificity and a discrete dispersal life stage: Dod's Old World swallowtail butterfly, Papilio machaon dodi. In Canada, P. m. dodi are generally restricted to eroding habitat along major river valleys where their larval host plant occurs. A series of causal and linear mixed effects models indicate that divergence of genome-wide single nucleotide polymorphisms is best explained by a combination of environmental isolation (variation in summer temperatures) and geographic isolation (Euclidean distance). Interestingly, least-cost path and circuit distances through a resistance surface parameterized as the inverse of habitat suitability were not supported. This suggests that, although habitat associations of many butterflies are specific due to reproductive requirements, habitat suitability and landscape permeability are not equivalent concepts due to considerable adult vagility. We infer that divergent selection related to variation in summer temperatures has produced two genetic clusters within P. m. dodi, differing in voltinism and diapause propensity. Within the next century, temperatures are predicted to rise by amounts greater than the present-day difference between regions of the genetic clusters, potentially affecting the persistence of the northern cluster under continued climate change.

Landscape genetics of wolverines (Gulo gulo): scale-dependent effects of bioclimatic, topographic, and anthropogenic variables

Climate change can have particularly severe consequences for high-elevation species that are well-adapted to long-lasting snow conditions within their habitats. One such species is the wolverine, Gulo gulo, with several studies showing a strong, year-round association of the species with the area defined by persistent spring snow cover. This bioclimatic niche also predicts successful dispersal paths for wolverines in the contiguous United States, where the species shows low levels of genetic exchange and low effective population size. Here, we assess the influence of additional climatic, vegetative, topographic, and anthropogenic, variables on wolverine genetic structure in this region using a multivariate, multiscale, landscape genetic approach. This approach allows us to detect landscape-genetic relationships both due to typical, small-scale genetic exchange within habitat, as well as exceptional, long-distance dispersal among habitats. Results suggest that a combination of snow depth, terrain ruggedness, and housing density, best predict gene flow in wolverines, and that the relative importance of variables is scale-dependent. Environmental variables (i.e., isolation-by-resistance, IBR) were responsible for 79% of the explained variation at small scales (i.e., up to ~230 km), and 65% at broad scales (i.e., beyond ~420 km). In contrast, a null model based on only space (i.e., isolation-by-distance, IBD) accounted only for 17% and 11% of the variation at small and broad scales, respectively. Snow depth was the most important variable for predicting genetic structures overall, and at small scales, where it contributed 43% to the variance explained. At broad spatial scales, housing density and terrain ruggedness were most important with contributions to explained variation of 55% and 25%, respectively. While the small-scale analysis most likely captures gene flow within typical wolverine habitat complexes, the broad-scale analysis reflects long-distance dispersal across areas not typically inhabited by wolverines. These findings help to refine our understanding of the processes shaping wolverine genetic structure, which is important for maintaining and improving functional connectivity among remaining wolverine populations.

Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape

Red deer (Cervus elaphus) throughout central Europe are influenced by different anthropogenic activities including habitat fragmentation, selective hunting and translocations. This has substantial impacts on genetic diversity and the long-term conservation of local populations of this species. Here we use genetic samples from 480 red deer individuals to assess genetic diversity and differentiation of the 12 administrative management units located in Schleswig Holstein, the northernmost federal state in Germany. We applied multiple analytical approaches and show that the history of local populations (i.e., translocations, culling of individuals outside of designated red deer zones, anthropogenic infrastructures) potentially has led to low levels of genetic diversity. Mean expected heterozygosity was below 0.6 and we observed on average 4.2 alleles across 12 microsatellite loci. Effective population sizes below the recommended level of 50 were estimated for multiple local populations. Our estimates of genetic structure and gene flow show that red deer in northern Germany are best described as a complex network of asymmetrically connected subpopulations, with high genetic exchange among some local populations and reduced connectivity of others. Genetic diversity was also correlated with population densities of neighboring management units. Based on these findings, we suggest that connectivity among existing management units should be considered in the practical management of the species, which means that some administrative management units should be managed together, while the effective isolation of other units needs to be mitigated.

Landscape management of the mahogany glider (Petaurus gracilis) across its distribution: subpopulations and corridor priorities

Key threatening processes to biodiversity include habitat loss and fragmentation, with populations restricted to small fragments of habitat being more prone to extinction. The mahogany glider (Petaurus gracilis) is endemic to sclerophyll woodland forests between Tully and Ingham in north Queensland and is one of Australia’s most endangered arboreal mammals due to these processes. The aim of this study was to identify the degree of habitat fragmentation of the remaining remnant vegetation of the mahogany glider, identify subpopulations within its distribution and identify key wildlife corridors for restoration to facilitate the movement of this species within and between subpopulations. Ten glider subpopulations, spread over 998 habitat fragments, were identified, of which only five subpopulations may currently be considered to be viable. To assist in providing habitat connectivity between and within the subpopulations, 55 corridors were identified for restoration that had an average length of 8.25 km. The average number of gaps greater than 30 m was 3.4 per corridor, with the average length of these gaps being 523 m. This study confirmed a high degree of habitat fragmentation across the distribution of the mahogany glider and highlighted the need to strengthen the remaining subpopulations by restoring habitat connectivity between the remaining habitat fragments.

Anthropogenic pressures drive population genetic structuring across a Critically Endangered lemur species range

In recent decades Madagascar has experienced significant habitat loss and modification, with minimal understanding of how human land use practices have impacted the evolution of its flora and fauna. In light of ongoing and intensifying anthropogenic pressures, we seek new insight into mechanisms driving genetic variability on this island, using a Critically Endangered lemur species, the black-and-white ruffed lemur (Varecia variegata), as a test case. Here, we examine the relative influence of natural and anthropogenic landscape features that we predict will impose barriers to dispersal and promote genetic structuring across the species range. Using circuit theory, we model functional connectivity among 18 sampling localities using population-based genetic distance (FST). We optimized resistance surfaces using genetic algorithms and assessed their performance using maximum-likelihood population-effects mixed models. The best supported resistance model was a composite surface that included two anthropogenic features, habitat cover and distance to villages, suggesting that rapid land cover modification by humans has driven change in the genetic structure of wild lemurs. Primary conservation priority should be placed on mitigating further forest loss and connecting regions identified as having low dispersal potential to prevent further loss of genetic diversity and promote the survival of other moist forest specialists.

Assessment of a large number of empirical plant species niche models by elicitation of knowledge from two national experts

Quantitative models play an increasing role in exploring the impact of global change on biodiversity. To win credibility and trust, they need validating. We show how expert knowledge can be used to assess a large number of empirical species niche models constructed for the British vascular plant and bryophyte flora. Key outcomes were (a) scored assessments of each modeled species and niche axis combination, (b) guidance on models needing further development, (c) exploration of the trade-off between presenting more complex model summaries, which could lead to more thorough validation, versus the longer time these take to evaluate, (d) quantification of the internal consistency of expert opinion based on comparison of assessment scores made on a random subset of models evaluated by both experts. Overall, the experts assessed 39% of species and niche axis combinations to be "poor" and 61% to show a degree of reliability split between "moderate" (30%), "good" (25%), and "excellent" (6%). The two experts agreed in only 43% of cases, reaching greater consensus about poorer models and disagreeing most about models rated as better by either expert. This low agreement rate suggests that a greater number of experts is required to produce reliable assessments and to more fully understand the reasons underlying lack of consensus. While area under curve (AUC) statistics showed generally very good ability of the models to predict random hold-out samples of the data, there was no correspondence between these and the scores given by the experts and no apparent correlation between AUC and species prevalence. Crowd-sourcing further assessments by allowing web-based access to model fits is an obvious next step. To this end, we developed an online application for inspecting and evaluating the fit of each niche surface to its training data.

Generalist dispersal and gene flow of an endangered keystone specialist (Dipodomys ingens)

Movement ecology and dispersal capabilities inherently drive genetic structure across landscapes. Through understanding dispersal and gene flow of giant kangaroo rats (Dipodomys ingens), conservation efforts can be focused, and we can further understand how genetic structure persists in this highly endemic small mammal. Here, we genetically identify parent–offspring and sibship relationships among 239 giant kangaroo rats using 15 microsatellites in the northern part of the species range and describe the individual genetic-spatial variation using a Moran eigenvector map (MEM). We further employ two landscape genetic analyses (isolation by resistance [IBR] and least cost paths [LCPs]) and two individual-based genetic metrics (Dps and a codominant marker distance from GenAlEx) to determine landscape factors (precipitation, slope, vegetation community, and roads) that influence gene flow. We found 19 pairs of related individuals, of which 18 were less than 250 m apart, but one sibling pair was 5.52 km apart, suggesting greater dispersal capabilities than previously noted. We found hierarchal spatial genetic structure using a MEM, with 3–4 genetically similar regions and two genetically similar subregions. Finally, we found low correlative strength between landscape features and gene flow. IBR consistently outperformed LCPs, and there was evidence that regions with 250–350 mm of precipitation and slope ≤ 5° promoted connectivity. We recommend that managers focus on habitat protection rather than corridor maintenance, with the caveat that anthropogenic factors were minimally considered in this study.

Inferring fine-scale spatial structure of the brown bear (Ursus arctos) population in the Carpathians prior to infrastructure development

Landscape genetics is increasingly being used in landscape planning for biodiversity conservation by assessing habitat connectivity and identifying landscape barriers, using intraspecific genetic data and quantification of landscape heterogeneity to statistically test the link between genetic variation and landscape variability. In this study we used genetic data to understand how landscape features and environmental factors influence demographic connectedness in Europe’s largest brown bear population and to assist in mitigating planned infrastructure development in Romania. Model-based clustering inferred one large and continuous bear population across the Carpathians suggesting that suitable bear habitat has not become sufficiently fragmented to restrict movement of individuals. However, at a finer scale, large rivers, often located alongside large roads with heavy traffic, were found to restrict gene flow significantly, while eastern facing slopes promoted genetic exchange. Since the proposed highway infrastructure development threatens to fragment regions of the Carpathians where brown bears occur, we develop a decision support tool based on models that assess the landscape configuration needed for brown bear conservation using wildlife corridor parameters. Critical brown bear corridors were identified through spatial mapping and connectivity models, which may be negatively influenced by infrastructure development and which therefore require mitigation. We recommend that current and proposed infrastructure developments incorporate these findings into their design and where possible avoid construction measures that may further fragment Romania’s brown bear population or include mitigation measures where alternative routes are not feasible.

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.

Everything you always wanted to know about gene flow in tropical landscapes (but were afraid to ask)

The bulk of the world’s biodiversity is found in tropical regions, which are increasingly threatened by the human-led degradation of natural habitats. Yet, little is known about tropical biodiversity responses to habitat loss and fragmentation. Here we review all available literature assessing landscape effects on gene flow in tropical species, aiming to help unravel the factors underpinning functional connectivity in the tropics. We map and classify studies by focus species, the molecular markers employed, statistical approaches to assess landscape effects on gene flow, and the evaluated landscape and environmental variables. We then compare qualitatively and quantitatively landscape effects on gene flow across species and units of analysis. We found 69 articles assessing landscape effects on gene flow in tropical organisms, most of which were published in the last five years, were concentrated in the Americas, and focused on amphibians or mammals. Most studies employed population-level approaches, microsatellites were the preferred type of markers, and Mantel and partial Mantel tests the most common statistical approaches used. While elevation, land cover and forest cover were the most common gene flow predictors assessed, habitat suitability was found to be a common predictor of gene flow. A third of all surveyed studies explicitly assessed the effect of habitat degradation, but only 14 of these detected a reduced gene flow with increasing habitat loss. Elevation was responsible for most significant microsatellite-based isolation by resistance effects and a single study reported significant isolation by non-forested areas in an ant. Our study reveals important knowledge gaps on the study of landscape effects on gene flow in tropical organisms, and provides useful guidelines on how to fill them.

Simulating impacts of rapid forest loss on population size, connectivity and genetic diversity of Sunda clouded leopards (Neofelis diardi) in Borneo

Habitat loss is the greatest threat to biodiversity in Borneo, and to anticipate and combat its effects it is important to predict the pattern of loss and its consequences. Borneo is a region of extremely high biodiversity from which forest is being lost faster than in any other. The little-known Sunda clouded leopard (Neofelis diardi) is the top predator in Borneo and is likely to depend critically on habitat connectivity that is currently being rapidly lost to deforestation. We modeled the effects of landscape fragmentation on population size, genetic diversity and population connectivity for the Sunda clouded leopard across the entirety of Borneo. We modelled the impacts of land use change between the years 2000, 2010 and projected forwards to 2020. We found substantial reductions across all metrics between 2000 and 2010: the proportion of landscape connected by dispersal fell by approximately 12.5% and the largest patch size declined by around 15.1%, leading to a predicted 11.4% decline in clouded leopard numbers. We also predict that these trends will accelerate greatly towards 2020, with the percentage of the landscape being connected by dispersal falling by about 57.8%, the largest patch size falling by around 62.8% and the predicted clouded leopard population falling by 62.5% between 2010 and 2020. We predicted that these large declines in clouded leopard population size and connectivity will also substantially reduce the genetic diversity of the remaining clouded leopard population.

Habitat Fragmentation Reduces Genetic Diversity and Connectivity of the Mexican Spotted Owl: A Simulation Study Using Empirical Resistance Models

We evaluated how differences between two empirical resistance models for the same geographic area affected predictions of gene flow processes and genetic diversity for the Mexican spotted owl (Strix occidentalis lucida). The two resistance models represented the landscape under low- and high-fragmentation parameters. Under low fragmentation, the landscape had larger but highly concentrated habitat patches, whereas under high fragmentation, the landscape had smaller habitat patches that scattered across a broader area. Overall habitat amount differed little between resistance models. We tested eight scenarios reflecting a factorial design of three factors: resistance model (low vs. high fragmentation), isolation hypothesis (isolation-by-distance, IBD, vs. isolation-by-resistance, IBR), and dispersal limit of species (200 km vs. 300 km). Higher dispersal limit generally had a positive but small influence on genetic diversity. Genetic distance increased with both geographic distance and landscape resistance, but landscape resistance displayed a stronger influence. Connectivity was positively related to genetic diversity under IBR but was less important under IBD. Fragmentation had a strong negative influence on the spatial patterns of genetic diversity and effective population size (Ns). Despite habitats being more concentrated and less widely distributed, the low-fragmentation landscape had greater genetic diversity than the high-fragmentation landscape, suggesting that highly concentrated but larger habitat patches may provide a genetic refuge for the Mexican spotted owl.

Admixture of hybrid swarms of native and introduced lizards in cities is determined by the cityscape structure and invasion history

Introductions of non-native lineages increase opportunities for hybridization. Non-native lineages of the common wall lizard, Podarcis muralis, are frequently introduced in cities where they hybridize with native populations. We aimed at unravelling the invasion history and admixture of native and non-native wall lizards in four German cities using citywide, comprehensive sampling. We barcoded and genotyped 826 lizards and tested if gene flow in populations composed of admixed native and introduced lineages is facilitated by similar environmental factors to those in native populations by comparing fine-scale landscape genetic patterns. In cities with non-native lineages, lizards commonly occurred in numerous clusters of hybrid swarms, which showed variable lineage composition, consisting of up to four distinct evolutionary lineages. Hybrid swarms held vast genetic diversity and showed recent admixture with other hybrid swarms. Landscape genetic analyses showed differential effects of cityscape structures across cities, but identified water bodies as strong barriers to gene flow in both native and admixed populations. By contrast, railway tracks facilitated gene flow of admixed populations only. Our study shows that cities represent unique settings for hybridization, caused by multiple introductions of non-native taxa. Cityscape structure and invasion histories of cities will determine future evolutionary pathways at these novel hybrid zones.

Spatio-temporal ecology of sympatric felids on Borneo. Evidence for resource partitioning?

Niche differentiation, the partitioning of resources along one or more axes of a species' niche hyper-volume, is widely recognised as an important mechanism for sympatric species to reduce interspecific competition and predation risk, and thus facilitate co-existence. Resource partitioning may be facilitated by behavioural differentiation along three main niche dimensions: habitat, food and time. In this study, we investigate the extent to which these mechanisms can explain the coexistence of an assemblage of five sympatric felids in Borneo. Using multi-scale logistic regression, we show that Bornean felids exhibit differences in both their broad and fine-scale habitat use. We calculate temporal activity patterns and overlap between these species, and present evidence for temporal separation within this felid guild. Lastly, we conducted an all-subsets logistic regression to predict the occurrence of each felid species as a function of the co-occurrence of a large number of other species and showed that Bornean felids co-occurred with a range of other species, some of which could be candidate prey. Our study reveals apparent resource partitioning within the Bornean felid assemblage, operating along all three niche dimension axes. These results provide new insights into the ecology of these species and the broader community in which they live and also provide important information for conservation planning for this guild of predators.