Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

Disentangling effects of dispersal, environment and anthropogenic barriers on functional connectivity in aquatic systems

Disentangling the roles of structural landscape factors and animal movement behaviour can present challenges for practitioners managing landscapes to maintain functional connectivity and achieve conservation goals. We used a landscape genetics approach to combine robust demographic, behavioural and genetic datasets with spatially explicit simulations to evaluate the effects of anthropogenic barriers (dams, culverts) and natural landscape resistance (gradient, elevation) affecting dispersal behaviour, genetic connectivity and genetic structure in a resident population of Westslope Cutthroat Trout (Oncorhynchus clarkii lewisi). Analyses based on 10 years of sampling effort revealed a pattern of restricted dispersal, and population genetics identified discrete population clusters between distal tributaries and the mainstem stream and no structure within the mainstem stream. Demogenetic simulations demonstrated that, for this population, the effects of existing anthropogenic barriers on population structure are redundant with effects of restricted dispersal associated with the underlying environmental resistance. Our approach provides an example of how extensive field sampling combined with landscape genetics can be incorporated into spatially explicit simulation modelling to explore how, together, movement ecology and landscape resistance can be used to inform decisions around restoration and connectivity.

Effects of landscape, resource use, and body size on genetic structure in bee populations

Quantifying genetic structure and levels of genetic variation are fundamentally important to predicting the ability of populations to persist in human-altered landscapes and adapt to future environmental changes. Genetic structure reflects the dispersal of individuals over generations, which can be mediated by species-level traits or environmental factors. Dispersal distances are commonly positively associated with body size and negatively associated with the amount of degraded habitat between sites, motivating the investigation of these potential drivers of dispersal concomitantly. We quantified genetic structure and genetic variability within populations of seven bee species from the genus Euglossa across fragmented landscapes. We genotyped bees at SNP loci and tested the following predictions: (1) deforested areas restrict gene flow; (2) larger species have lower genetic structure; (3) species with greater resource specialization have higher genetic structure; and (4) sites surrounded by more intact habitat have higher genetic diversity. Contrasting with previous work on bees, we found no associations between body size and genetic structure. Genetic structure was higher for species with greater resource specialization, and the amount of intact habitat between or surrounding sites was positively associated with parameters reflecting gene flow and genetic diversity. These results challenge the dominant paradigm that individuals of larger species disperse farther, and they suggest that landscape and resource requirements are important factors mediating dispersal.

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.

Corridor-based approach with spatial cross-validation reveals scale-dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity

Understanding how human infrastructure and other landscape attributes affect genetic differentiation in animals is an important step for identifying and maintaining dispersal corridors for these species. We built upon recent advances in the field of landscape genetics by using an individual-based and multiscale approach to predict landscape-level genetic connectivity for grizzly bears (Ursus arctos) across ~100,000 km2 in Canada's southern Rocky Mountains. We used a genetic dataset with 1156 unique individuals genotyped at nine microsatellite loci to identify landscape characteristics that influence grizzly bear gene flow at multiple spatial scales and map predicted genetic connectivity through a matrix of rugged terrain, large protected areas, highways and a growing human footprint. Our corridor-based modelling approach used a machine learning algorithm that objectively parameterized landscape resistance, incorporated spatial cross validation and variable selection and explicitly accounted for isolation by distance. This approach avoided overfitting, discarded variables that did not improve model performance across withheld test datasets and spatial predictive capacity compared to random cross-validation. We found that across all spatial scales, geographic distance explained more variation in genetic differentiation in grizzly bears than landscape variables. Human footprint inhibited connectivity across all spatial scales, while open canopies inhibited connectivity at the broadest spatial scale. Our results highlight the negative effect of human footprint on genetic connectivity, provide strong evidence for using spatial cross-validation in landscape genetics analyses and show that multiscale analyses provide additional information on how landscape variables affect genetic differentiation.

Landscape resistance index aiming at functional forest connectivity

Resistance models may quantify the ability of the landscape to impede species' movement and represent suitable habitats. Moreover, the performance of resistance models parameterized by land-use/land cover attributes evidence that the integrity of the environments subject to urban sprawl is poorly understood. In this sense, the study assumed we could identify the forest functional connectivity in a landscape considering the disparity in the landscape mosaic. In this context, we sought to develop a landscape resistance index through structural equation modeling (SEM), supported by the criteria of heat emission, biomass, and anthropogenic barriers, obtained by remote sensing, called observed variables. The landscape studied in the Green Belt Biosphere Reserve of São Paulo has significant remnants of the Atlantic Forest, a biodiversity hotspot. However, our results indicated criteria variability in the landscape modeled through the SEM, obtaining a significant adjustment of the landscape resistance index, with comparative fit index (CFI) of 1.00 and root mean square error of approximation (RMSEA) of 0.00. The index reflects the resistance levels of the land use/land cover, expressed by the class interval, ranging from 0% (1.73) to 100% (493.88), with the highest values associated with the anthropized uses and forest isolation. Thus, our index based on environmental attributes reflects the structure of functional forest connectivity and offers a framework to design forest corridors across landscapes.

An evaluation of isolation by distance and isolation by resistance on genetic structure of the Persian squirrel (Sciurus anomalus) in the Zagros forests of Iran

For the conservation of wild species, it is important to understand how landscape change and land management can affect gene flow and movement. Landscape genetic analyses provide a powerful approach to infer effects of various landscape factors on gene flow, thereby informing conservation actions. The Persian squirrel is a keystone species in the woodlands and oak forests of Western Asia, where it has experienced recent habitat loss and fragmentation. We conducted landscape genetic analyses of individuals sampled in the northern Zagros Mountains of Iran (provinces of Kurdistan, Kermanshah, and Ilam), focusing on the evaluation of isolation by distance (IBD) and isolation by resistance (IBR), using 16 microsatellite markers. The roles of geographical distance and landscape features including roads, rivers, developed areas, farming and agriculture, forests, lakes, plantation forests, rangelands, shrublands, and rocky areas of varying canopy cover, and swamp margins on genetic structure were quantified using individual-based approaches and resistance surface modeling. We found a significant pattern of IBD but only weak support for an effect of forest cover on genetic structure and gene flow. It seems that geographical distance is an important factor limiting the dispersal of the Persian squirrel in this region. The results of the current study inform ongoing conservation programs for the Persian squirrel in the Zagros oak forest.

Predicting Environmental and Ecological Drivers of Human Population Structure

Landscape, climate, and culture can all structure human populations, but few existing methods are designed to simultaneously disentangle among a large number of variables in explaining genetic patterns. We developed a machine learning method for identifying the variables which best explain migration rates, as measured by the coalescent-based program MAPS that uses shared identical by descent tracts to infer spatial migration across a region of interest. We applied our method to 30 human populations in eastern Africa with high-density single nucleotide polymorphism array data. The remarkable diversity of ethnicities, languages, and environments in this region offers a unique opportunity to explore the variables that shape migration and genetic structure. We explored more than 20 spatial variables relating to landscape, climate, and presence of tsetse flies. The full model explained ∼40% of the variance in migration rate over the past 56 generations. Precipitation, minimum temperature of the coldest month, and elevation were the variables with the highest impact. Among the three groups of tsetse flies, the most impactful was fusca which transmits livestock trypanosomiasis. We also tested for adaptation to high elevation among Ethiopian populations. We did not identify well-known genes related to high elevation, but we did find signatures of positive selection related to metabolism and disease. We conclude that the environment has influenced the migration and adaptation of human populations in eastern Africa; the remaining variance in structure is likely due in part to cultural or other factors not captured in our model.

Estimating resistance surfaces using gradient forest and allelic frequencies

Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity methods that use link-based methods traditionally rely on relating pairwise genetic distance between individuals or demes to their landscape distance (e.g., geographic distance, cost distance). In this study, we present an alternative to conventional statistical approaches to refine cost surfaces by adapting the gradient forest approach to produce a resistance surface. Used in community ecology, gradient forest is an extension of random forest, and has been implemented in genomic studies to model species genetic offset under future climatic scenarios. By design, this adapted method, resGF, has the ability to handle multiple environmental predicators and is not subjected to traditional assumptions of linear models such as independence, normality and linearity. Using genetic simulations, resistance Gradient Forest (resGF) performance was compared to other published methods (maximum likelihood population effects model, random forest-based least-cost transect analysis and species distribution model). In univariate scenarios, resGF was able to distinguish the true surface contributing to genetic diversity among competing surfaces better than the compared methods. In multivariate scenarios, the gradient forest approach performed similarly to the other random forest-based approach using least-cost transect analysis but outperformed MLPE-based methods. Additionally, two worked examples are provided using two previously published data sets. This machine learning algorithm has the potential to improve our understanding of landscape connectivity and inform long-term biodiversity conservation strategies.

Generalist nematodes dominate the nemabiome of roe deer in sympatry with sheep at a regional level

The growth of livestock farming and the recent expansion of wild ungulate populations in Europe favor opportunities for direct and/or indirect cross-transmission of pathogens. Comparatively few studies have investigated the epidemiology of gastro-intestinal nematode parasites, an ubiquitous and important community of parasites of ungulates, at the wildlife/livestock interface. In this study, we aimed to assess the influence of livestock proximity on the gastrointestinal nematode community of roe deer in a rural landscape located in southern France. Using ITS-2 rDNA nemabiome metabarcoding on fecal larvae, we analysed the gastrointestinal nematode communities of roe deer and sheep. In addition, we investigated Haemonchus contortus nad4 mtDNA diversity to specifically test parasite circulation among domestic and wild host populations. The dominant gastrointestinal nematode species found in both the roe deer and sheep were generalist species commonly found in small ruminant livestock (e.g. H. contortus), whereas the more specialised wild cervid nematode species (e.g. Ostertagia leptospicularis) were only present at low frequencies. This is in marked contrast with previous studies that found the nemabiomes of wild cervid populations to be dominated by cervid specialist nematode species. In addition, the lack of genetic structure of the nad4 mtDNA of H. contortus populations between host species suggests circulation of gastrointestinal nematodes between roe deer and sheep. The risk of contact with livestock only has a small influence on the nemabiome of roe deer, suggesting the parasite population of roe deer has been displaced by generalist livestock parasites due to many decades of sheep farming, not only for deer grazing close to pastures, but also at a larger regional scale. We also observed some seasonal variation in the nemabiome composition of roe deer. Overall, our results demonstrate significant exchange of gastrointestinal nematodes between domestic and wild ungulates, with generalist species spilling over from domestic ungulates dominating wild cervid parasite communities.

Habitat-linked genetic variation supports microgeographic adaptive divergence in an island-endemic bird species

We investigated the potential mechanisms driving habitat-linked genetic divergence within a bird species endemic to a single 250 km² island. The island scrub-jay (Aphelocoma insularis) exhibits microgeographic divergence in bill morphology across pine-oak ecotones on Santa Cruz Island, California (USA) similar to adaptive differences described in mainland congeners over much larger geographic scales. To test whether individuals exhibit genetic differentiation related to habitat type and divergence in bill length, we genotyped over 3,000 single nucleotide polymorphisms (SNPs) in 123 adult island scrub-jay males from across Santa Cruz Island using restriction site-associated DNA sequencing (RADseq). Neutral landscape genomic analyses revealed that genome-wide genetic differentiation was primarily related to geographic distance and differences in habitat composition. We also found 168 putatively adaptive loci associated with habitat type using multivariate redundancy analysis (RDA) while controlling for spatial effects. Finally, two genome-wide association analyses revealed a polygenic basis to variation in bill length with multiple loci detected in or near genes known to affect bill morphology in other birds. Our findings support the hypothesis that divergent selection at microgeographic scales can cause adaptive divergence in the presence of ongoing gene flow.

Contrasting environmental drivers of genetic and phenotypic divergence in an Andean poison frog (Epipedobates anthonyi)

Phenotypic and genetic divergence are shaped by the homogenizing effects of gene flow and the differentiating processes of genetic drift and local adaptation. Herein, we examined the mechanisms that underlie phenotypic (size and color) and genetic divergence in 35 populations (535 individuals) of the poison frog Epipedobates anthonyi along four elevational gradients (0-1800 m asl) in the Ecuadorian Andes. We found phenotypic divergence in size and color despite relatively low genetic divergence at neutral microsatellite loci. Genetic and phenotypic divergence were both explained by landscape resistance between sites (isolation-by-resistance, IBR), likely due to a cold and dry mountain ridge between the northern and southern elevational transects that limits dispersal and separates two color morphs. Moreover, environmental differences among sites also explained genetic and phenotypic divergence, suggesting isolation-by-environment (IBE). When northern and southern transects were analyzed separately, genetic divergence was predicted either by distance (isolation-by-distance, IBD; northern) or environmental resistance between sites (IBR; southern). In contrast, phenotypic divergence was primarily explained by environmental differences among sites, supporting the IBE hypothesis. These results indicate that although distance and geographic barriers are important drivers of population divergence, environmental variation has a two-fold effect on population divergence. On the one hand, landscape resistance between sites reduces gene flow (IBR), while on the other hand, environmental differences among sites exert divergent selective pressures on phenotypic traits (IBE). Our work highlights the importance of studying both genetic and phenotypic divergence to better understand the processes of population divergence and speciation along ecological gradients.

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.

Semi-quantitative metabarcoding reveals how climate shapes arthropod community assembly along elevation gradients on Hawaii Island

Spatial variation in climatic conditions along elevation gradients provides an important backdrop by which communities assemble and diversify. Lowland habitats tend to be connected through time, whereas highlands can be continuously or periodically isolated, conditions that have been hypothesized to promote high levels of species endemism. This tendency is expected to be accentuated among taxa that show niche conservatism within a given climatic envelope. While species distribution modeling approaches have allowed extensive exploration of niche conservatism among target taxa, a broad understanding of the phenomenon requires sampling of entire communities. Species-rich groups such as arthropods are ideal case studies for understanding ecological and biodiversity dynamics along elevational gradients given their important functional role in many ecosystems, but community-level studies have been limited due to their tremendous diversity. Here, we develop a novel semi-quantitative metabarcoding approach that combines specimen counts and size-sorting to characterize arthropod community-level diversity patterns along elevational transects on two different volcanoes of the island of Hawai'i. We found that arthropod communities between the two transects became increasingly distinct compositionally at higher elevations. Resistance surface approaches suggest that climatic differences between sampling localities are an important driver in shaping beta-diversity patterns, though the relative importance of climate varies across taxonomic groups. Nevertheless, the climatic niche position of OTUs between transects was highly correlated, suggesting that climatic filters shape the colonization between adjacent volcanoes. Taken together, our results highlight climatic niche conservatism as an important factor shaping ecological assembly along elevational gradients and suggest topographic complexity as an important driver of diversification.

What we talk about when we talk about colors

Do we talk about some colors more often than others? And do the colors we communicate about most frequently vary across cultures? A classic finding shows that languages around the world partition colors into words in remarkably similar, although not identical, ways. The biology of human color perception helps explain similar color vocabularies across languages, but less is known about how often speakers need to reference different colors. The inference method we develop reveals extensive variation in communicative needs across colors, and a diversity in needs across 130 languages, which helps explain variation in their color vocabularies. Our results open the door to studying cross-cultural variation in demands on different colors, and factors that drive color demands in linguistic communities.

Names for colors vary widely across languages, but color categories are remarkably consistent. Shared mechanisms of color perception help explain consistent partitions of visible light into discrete color vocabularies. But the mappings from colors to words are not identical across languages, which may reflect communicative needs—how often speakers must refer to objects of different color. Here we quantify the communicative needs of colors in 130 different languages by developing an inference algorithm for this problem. We find that communicative needs are not uniform: Some regions of color space exhibit 30-fold greater demand for communication than other regions. The regions of greatest demand correlate with the colors of salient objects, including ripe fruits in primate diets. Our analysis also reveals a hidden diversity in the communicative needs of colors across different languages, which is partly explained by differences in geographic location and the local biogeography of linguistic communities. Accounting for language-specific, nonuniform communicative needs improves predictions for how a language maps colors to words, and how these mappings vary across languages. Our account closes an important gap in the compression theory of color naming, while opening directions to study cross-cultural variation in the need to communicate different colors and its impact on the cultural evolution of color categories.

Genetic imprints of Brosimum alicastrum Sw. in Mexico

PREMISE

The mechanisms generating the geographical distributions of genetic diversity are a central theme in evolutionary biology. The amount of genetic diversity and its distribution are controlled by several factors, including dispersal abilities, physical barriers, and environmental and climatic changes. We investigated the patterns of genetic diversity and differentiation among populations of the widespread species Brosimum alicastrum in Mexico.

METHODS

Using nuclear DNA microsatellite data, we tested whether the genetic structure of B. alicastrum was associated with the roles of the Trans-Mexican Volcanic Belt and the Isthmus of Tehuantepec as geographical barriers to gene flow and to infer the role of past events in the genetic diversity patterns. We further used a maximum-likelihood population-effects mixed model (MLPE) to identify the main factor affecting population differentiation in B. alicastrum.

RESULTS

Our results suggested that Mexican B. alicastrum is well differentiated into three main lineages. Patterns of the genetic structure at a finer scale did not fully correspond to the current geographical barriers to gene flow. According to the MLPE mixed model, isolation by distance is the best model for explaining the genetic differentiation of B. alicastrum in Mexico.

CONCLUSIONS

We propose that the differentiation patterns might reflect (1) an ancient differentiation that occurred in Central and South America, (2) the effects of past climatic changes, and (3) the functions of some physical barriers to gene flow. This study provides insights into the possible mechanisms underlying the geographic genetic variation of B. alicastrum along a moisture gradient in tropical lowland forests.

The effect of sampling density and study area size on landscape genetics inferences for the Mississippi slimy salamander (Plethodon mississippi)

In landscape genetics, it is largely unknown how choices regarding sampling density and study area size impact inferences upon which habitat features impede vs. facilitate gene flow. While it is recommended that sampling locations be spaced no further apart than the average individual's dispersal distance, for low-mobility species, this could lead to a challenging number of sampling locations, or an unrepresentative study area. We assessed the effects of sampling density and study area size on landscape genetic inferences for a dispersal-limited amphibian, Plethodon mississippi, via analysis of nested datasets. Microsatellite-based genetic distances among individuals were divided into three datasets representing sparse sampling across a large study area, dense sampling across a small study area, or sparse sampling across the same small study area. These datasets were a proxy for gene flow (i.e., the response variable) in maximum-likelihood population effects models that assessed the nature and strength of their relationship with each of five land-use classes (i.e., potential predictor variables). Comparisons of outcomes were based on the rank order of effect, sign of effect (i.e., gene flow resistance vs. facilitation), spatial scale of effect, and functional relationship with gene flow. The best-fit model for each dataset had the same sign of effect for hardwood forests, manmade structures, and pine forests, indicating the impacts of these land-use classes on dispersal and gene flow in P. mississippi are robust to sampling scheme. Contrasting sampling densities led to a different inferred functional relationship between agricultural areas and gene flow. Study area size appeared to influence the scale of effect of manmade structures and the sign of effect of pine forests. Our findings provided evidence for an influence of sampling density, study area size, and sampling effort upon inferences. Accordingly, we recommend iterative subsampling of empirical datasets and continued investigation into the sensitivities of landscape genetic analyses using simulations.

Evolutionary stability, landscape heterogeneity, and human land-usage shape population genetic connectivity in the Cape Floristic Region biodiversity hotspot

As human-induced change eliminates natural habitats, it impacts genetic diversity and population connectivity for local biodiversity. The South African Cape Floristic Region (CFR) is the most diverse extratropical area for plant biodiversity, and much of its habitat is protected as a UNESCO World Heritage site. There has long been great interest in explaining the underlying factors driving this unique diversity, especially as much of the CFR is endangered by urbanization and other anthropogenic activity. Here, we use a population and landscape genetic analysis of SNP data from the CFR endemic plant Leucadendron salignum or "common sunshine conebush" as a model to address the evolutionary and environmental factors shaping the vast CFR diversity. We found that high population structure, along with relatively deeper and older genealogies, is characteristic of the southwestern CFR, whereas low population structure and more recent lineage coalescence depict the eastern CFR. Population network analyses show genetic connectivity is facilitated in areas of lower elevation and higher seasonal precipitation. These population genetic signatures corroborate CFR species-level patterns consistent with high Pleistocene biome stability and landscape heterogeneity in the southwest, but with coincident instability in the east. Finally, we also find evidence of human land-usage as a significant gene flow barrier, especially in severely threatened lowlands where genetic connectivity has been historically the highest. These results help identify areas where conservation plans can prioritize protecting high genetic diversity threatened by contemporary human activities within this unique cultural UNESCO site.

Canada lynx (Lynx canadensis) gene flow across a mountain transition zone in western North America

Mountain ecotones have the potential to cause multiple patterns in divergence, from simple barrier effects to more fundamental ecological divergence. Most work in mountain ecotones in North America has focused on reinforcement between refugial populations, making prediction of how mountains impact species that are not restricted to separate glacial refugia remains difficult. This study focused on the Canada lynx (Lynx canadensis Kerr, 1792), a highly mobile felid considered to be a habitat and dietary specialist. Specifically, we used 14 microsatellite loci and landscape genetic tools to investigate if the Rocky Mountains and associated climatic transitions influence lynx genetic differentiation in western North America. Although lynx exhibited high gene flow across the region, analyses detected structuring of neutral genetic variation across our study area. Gene flow for lynx most strongly related to temperature and elevation compared with other landscape variables (terrain roughness, percent forest cover, and habitat suitability index) and geographic distance alone. Overall, genetic structure in lynx is most consistent with barrier effects created by the Rocky Mountains rather than ecological divergence. Furthermore, warmer temperatures had a measurable impact on gene flow, which suggests connectivity may further decrease in peripheral or fragmented populations as climate warms.

Bacterial epibiont communities of panmictic Antarctic krill are spatially structured

Antarctic krill (Euphausia superba) are amongst the most abundant animals on Earth, with a circumpolar distribution in the Southern Ocean. Genetic and genomic studies have failed to detect any population structure for the species, suggesting a single panmictic population. However, the hyper-abundance of krill slows the rate of genetic differentiation, masking potential underlying structure. Here we use high-throughput sequencing of bacterial 16S rRNA genes to show that krill bacterial epibiont communities exhibit spatial structuring, driven mainly by distance rather than environmental factors, especially for strongly krill-associated bacteria. Estimating the ecological processes driving bacterial community turnover indicated this was driven by bacterial dispersal limitation increasing with geographic distance. Furthermore, divergent epibiont communities generated from a single krill swarm split between aquarium tanks under near-identical conditions suggests physical isolation in itself can cause krill-associated bacterial communities to diverge. Our findings show that Antarctic krill-associated bacterial communities are geographically structured, in direct contrast with the lack of structure observed for krill genetic and genomic data.

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.

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.

Small-scale population divergence is driven by local larval environment in a temperate amphibian

Genomic variation within and among populations is shaped by the interplay between natural selection and the effects of genetic drift and gene flow. Adaptive divergence can be found in small-scale natural systems even when population sizes are small, and the potential for gene flow is high, suggesting that local environments exert selection pressures strong enough to counteract the opposing effects of drift and gene flow. Here, we investigated genomic differentiation in nine moor frog (Rana arvalis) populations in a small-scale network of local wetlands using 16,707 ddRAD-seq SNPs, relating levels of differentiation with local environments, as well as with properties of the surrounding landscape. We characterized population structure and differentiation, and partitioned the effects of geographic distance, local larval environment, and landscape features on total genomic variation. We also conducted gene-environment association studies using univariate and multivariate approaches. We found small-scale population structure corresponding to 6-8 clusters. Local larval environment was the most influential component explaining 2.3% of the total genetic variation followed by landscape features (1.8%) and geographic distance (0.8%), indicative of isolation-by-environment, -by-landscape, and -by-distance, respectively. We identified 1000 potential candidate SNPs putatively under divergent selection mediated by the local larval environment. The candidate SNPs were involved in, among other biological functions, immune system function and development. Our results suggest that small-scale environmental differences can exert selection pressures strong enough to counteract homogenizing effects of gene flow and drift in this small-scale system, leading to observable population differentiation.

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.

Speed and directedness predict colonization sequence post-disturbance

Foundational ecological models characterize dispersal with two behavioral traits, speed and directional bias. We hypothesized that these two traits can predict the order of colonization by fishes in a heterogenous landscape. Colonization patterns following hydrological disturbance were documented from a 20-year multi-site time series of marsh fish, and we evaluated the ability of a two-parameter model to predict these patterns. The maximum aerobic swimming speed (U_CRIT) for six coexisting fish species were estimated using endurance tests; field estimates of directedness and swimming speed were previously documented using encounter samplers. We incorporated interspecific variation in speed, direction, and density into several Agent Based Models to simulate dispersal following disturbance. Six virtual "species" with varying levels of directedness, "swam" in an artificial environment to reach a refuge habitat. The time of first arrival for each species was saved at the end of each run and used to calculate the probability of arrival order. Our simulated results generated predictions on order of arrival consistent with observed colonization patterns in our long-term dataset. Swim tunnel results revealed that fast (high U_CRIT) estimates were characteristic of early colonizing species; whereas, slow (low U_CRIT) estimates were characteristic of late colonizing species. Directional bias better predicted order of arrival than speed and was robust to inter-specific variation in density. This study demonstrated that two parameters were adequate to predict the order of species colonization in a complex landscape. These results support the use of relatively simple trait-based models to generate realistic community assembly dynamics.

Alternative Quantifications of Landscape Complementation to Model Gene Flow in Banded Longhorn Beetles [Typocerus v. velutinus (Olivier)]

Rapid progression of human socio-economic activities has altered the structure and function of natural landscapes. Species that rely on multiple, complementary habitat types (i.e., landscape complementation) to complete their life cycle may be especially at risk. However, such landscape complementation has received little attention in the context of landscape connectivity modeling. A previous study on flower longhorn beetles (Cerambycidae: Lepturinae) integrated landscape complementation into a continuous habitat suitability 'surface', which was then used to quantify landscape connectivity between pairs of sampling sites using gradient-surface metrics. This connectivity model was validated with molecular genetic data collected for the banded longhorn beetle (Typocerus v. velutinus) in Indiana, United States. However, this approach has not been compared to alternative models in a landscape genetics context. Here, we used a discrete land use/land cover map to calculate landscape metrics related to landscape complementation based on a patch mosaic model (PMM) as an alternative to the previously published, continuous habitat suitability model (HSM). We evaluated the HSM surface with gradient surface metrics (GSM) and with two resistance-based models (RBM) based on least cost path (LCP) and commute distance (CD), in addition to an isolation-by-distance (IBD) model based on Euclidean distance. We compared the ability of these competing models of connectivity to explain pairwise genetic distances (R ST) previously calculated from ten microsatellite genotypes of 454 beetles collected from 17 sites across Indiana, United States. Model selection with maximum likelihood population effects (MLPE) models found that GSM were most effective at explaining pairwise genetic distances as a proxy for gene flow across the landscape, followed by the landscape metrics calculated from the PMM, whereas the LCP model performed worse than both the CD and the isolation by distance model. We argue that the analysis of a continuous HSM with GSM might perform better because of their combined ability to effectively represent and quantify the continuous degree of landscape complementation (i.e., availability of complementary habitats in vicinity) found at and in-between sites, on which these beetles depend. Our findings may inform future studies that seek to model habitat connectivity in complex heterogeneous landscapes as natural habitats continue to become more fragmented in the Anthropocene.

Fine-scale habitat heterogeneity and vole runways influence seed dispersal in Plagiobothrys nothofulvus

PREMISE

Seed dispersal allows plants to colonize new sites and contributes to gene flow among populations. Despite its fundamental importance to ecological and evolutionary processes, our understanding of seed dispersal is limited due to the difficulty of directly observing dispersal events. This is particularly true for the majority of plant species that are considered to have gravity as their primary dispersal mechanism. The potential for long-distance movement of gravity-dispersed seeds by secondary dispersal vectors is rarely evaluated.

METHODS

We employ whole-genome assays of maternally inherited cpDNA in Plagiobothrys nothofulvus to resolve patterns of genetic variation due to effective (realized) seed dispersal within a 16 hectare prairie that is characterized by a mosaic of habitat types. We evaluate the effects of microgeographic landscape features extracted from micro-UAV aerial surveys on patterns of seed dispersal using landscape genetics methods.

RESULTS

We found evidence of high resistance to seed-mediated gene flow (effective dispersal) within patches of Plagiobothrys nothofulvus, and strong genetic structure over distances of less than 20 m. Geographic distance was a poor predictor of dispersal distance, while landscape features had stronger influences on patterns of dispersal (distance and direction of seed movement). Patterns of dispersal were best predicted by the combined distribution of flower patches, habitat type, and the network of vole runways, with the latter explaining the largest proportion of variation in the model.

CONCLUSIONS

Our results suggest that primary dispersal occurs mostly within microhabitats and infrequent secondary dispersal may occur over longer distances due to the activity of small mammals and other vertebrates.

The evolution of polymorphism in the warning coloration of the Amazonian poison frog Adelphobates galactonotus

While intraspecific variation in aposematic signals can be selected for by different predatory responses, their evolution is also contingent on other processes shaping genetic variation. We evaluate the relative contributions of selection, geographic isolation, and random genetic drift to the evolution of aposematic color polymorphism in the poison frog Adelphobates galactonotus, distributed throughout eastern Brazilian Amazonia. Dorsal coloration was measured for 111 individuals and genetic data were obtained from 220 individuals at two mitochondrial genes (mtDNA) and 7963 Single Nucleotide Polymorphisms (SNPs). Four color categories were described (brown, blue, yellow, orange) and our models of frog and bird visual systems indicated that each color was distinguishable for these taxa. Using outlier and correlative analyses we found no compelling genetic evidence for color being under divergent selection. A time-calibrated mtDNA tree suggests that the present distribution of dorsal coloration resulted from processes occurring during the Pleistocene. Separate phylogenies based on SNPs and mtDNA resolved the same well supported clades, each containing different colored populations. Ancestral character state analysis provided some evidence for evolutionary transitions in color type. Genetic structure was more strongly associated with geographic features, than color category, suggesting that the distribution of color is explained by localized processes. Evidence for geographic isolation together with estimates of low effective population size implicates drift as playing a key role in color diversification. Our results highlight the relevance of considering the neutral processes involved with the evolution of traits with important fitness consequences.

Multiscale landscape genetics of American marten at their southern range periphery

American marten (Martes americana) are a conservation priority in many forested regions of North America. Populations are fragmented at the southern edge of their distribution due to suboptimal habitat conditions. Facilitating gene flow may improve population resilience through genetic and demographic rescue. We used a multiscale approach to estimate the relationship between genetic connectivity and landscape characteristics among individuals at three scales in the northeastern United States: regional, subregional, and local. We integrated multiple modeling techniques and identified top models based on consensus. Top models were used to parameterize resistance surfaces at each scale, and circuit theory was used to identify potential movement corridors. Regional gene flow was affected by forest cover, elevation, developed land cover, and slope. At subregional and local scales, the effects were site specific and included subsets of temperature, elevation, developed land cover, and slope. Developed land cover significantly affected gene flow at each scale. At finer scales, lack of variance in forest cover may have limited the ability to detect a relationship with gene flow. The effect of slope on gene flow was positive or negative, depending on the site examined. Occupancy probability was a relatively poor predictor, and we caution its use as a proxy for landscape resistance. Our results underscore the importance of replication and multiscale approaches in landscape genetics. Climate warming and landscape conversion may reduce the genetic connectivity of marten populations in the northeastern United States, and represent the primary challenges to marten conservation at the southern periphery of their range.

Urbanization reduces genetic connectivity in bobcats (Lynx rufus) at both intra- and interpopulation spatial scales

Urbanization is a major factor driving habitat fragmentation and connectivity loss in wildlife. However, the impacts of urbanization on connectivity can vary among species and even populations due to differences in local landscape characteristics, and our ability to detect these relationships may depend on the spatial scale at which they are measured. Bobcats (Lynx rufus) are relatively sensitive to urbanization and the status of bobcat populations is an important indicator of connectivity in urban coastal southern California. We genotyped 271 bobcats at 13,520 SNP loci to conduct a replicated landscape resistance analysis in five genetically distinct populations. We tested urban and natural factors potentially influencing individual connectivity in each population separately, as well as study-wide. Overall, landscape genomic effects were most frequently detected at the study-wide spatial scale, with urban land cover (measured as impervious surface) having negative effects and topographic roughness having positive effects on gene flow. The negative effect of urban land cover on connectivity was also evident when populations were analyzed separately despite varying substantially in spatial area and the proportion of urban development, confirming a pervasive impact of urbanization largely independent of spatial scale. The effect of urban development was strongest in one population where stream habitat had been lost to development, suggesting that riparian corridors may help mitigate reduced connectivity in urbanizing areas. Our results demonstrate the importance of replicating landscape genetic analyses across populations and considering how landscape genetic effects may vary with spatial scale and local landscape structure.

Urbanization impacts apex predator gene flow but not genetic diversity across an urban-rural divide

Apex predators are important indicators of intact natural ecosystems. They are also sensitive to urbanization because they require broad home ranges and extensive contiguous habitat to support their prey base. Pumas (Puma concolor) can persist near human developed areas, but urbanization may be detrimental to their movement ecology, population structure, and genetic diversity. To investigate potential effects of urbanization in population connectivity of pumas, we performed a landscape genomics study of 130 pumas on the rural Western Slope and more urbanized Front Range of Colorado, USA. Over 12,000 single nucleotide polymorphisms (SNPs) were genotyped using double-digest, restriction site-associated DNA sequencing (ddRADseq). We investigated patterns of gene flow and genetic diversity, and tested for correlations between key landscape variables and genetic distance to assess the effects of urbanization and other landscape factors on gene flow. Levels of genetic diversity were similar for the Western Slope and Front Range, but effective population sizes were smaller, genetic distances were higher, and there was more admixture in the more urbanized Front Range. Forest cover was strongly positively associated with puma gene flow on the Western Slope, while impervious surfaces restricted gene flow and more open, natural habitats enhanced gene flow on the Front Range. Landscape genomic analyses revealed differences in puma movement and gene flow patterns in rural versus urban settings. Our results highlight the utility of dense, genome-scale markers to document subtle impacts of urbanization on a wide-ranging carnivore living near a large urban center.

Additive effects of connectivity provided by different habitat types drive plant assembly

How connectivity affects plant assemblages is a central issue in landscape ecology. So far, empirical studies have produced contradictory results, possibly because studies: (1) inaccurately assess connectivity by prioritizing the respective effect of the type of habitat on plant assemblages and (2) omit the range of possible plant responses to connectivity depending on dispersal vectors. We focused on three dominant habitat types in agricultural landscapes (woodland, grassland and cropland), and analysed the effect of connectivity on herbaceous plant assemblage similarity for three primary dispersal modes (animal-dispersed, wind-dispersed and unassisted). Using circuit theory, we measured connectivity provided by woodland, grassland and cropland habitats independently. The similarity of plant assemblages was evaluated relative to the random expectation based on the regional pool. Overall, plant assemblage similarity in woodlands and temporary grasslands was dependent on connectivity, but not in wheat croplands. Only animal-dispersed species responded to connectivity. The similarity of animal-dispersed assemblages in woodlands was increased by the connectivity provided by woodland habitats, but was reduced by cropland habitats, whereas in temporary grasslands, similarity was increased by the connectivity provided by cropland habitats. Our results suggest that animal-dispersed species supplement their dispersal pathways, thus improving our knowledge of plant assembly rules in fragmented landscapes.

Landscape genetic inferences vary with sampling scenario for a pond-breeding amphibian

A critical decision in landscape genetic studies is whether to use individuals or populations as the sampling unit. This decision affects the time and cost of sampling and may affect ecological inference. We analyzed 334 Columbia spotted frogs at 8 microsatellite loci across 40 sites in northern Idaho to determine how inferences from landscape genetic analyses would vary with sampling design. At all sites, we compared a proportion available sampling scheme (PASS), in which all samples were used, to resampled datasets of 2-11 individuals. Additionally, we compared a population sampling scheme (PSS) to an individual sampling scheme (ISS) at 18 sites with sufficient sample size. We applied an information theoretic approach with both restricted maximum likelihood and maximum likelihood estimation to evaluate competing landscape resistance hypotheses. We found that PSS supported low-density forest when restricted maximum likelihood was used, but a combination model of most variables when maximum likelihood was used. We also saw variations when AIC was used compared to BIC. ISS supported this model as well as additional models when testing hypotheses of land cover types that create the greatest resistance to gene flow for Columbia spotted frogs. Increased sampling density and study extent, seen by comparing PSS to PASS, showed a change in model support. As number of individuals increased, model support converged at 7-9 individuals for ISS to PSS. ISS may be useful to increase study extent and sampling density, but may lack power to provide strong support for the correct model with microsatellite datasets. Our results highlight the importance of additional research on sampling design effects on landscape genetics inference.

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.

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

Functional connectivity, quantified using landscape genetics, can inform conservation through the identification of factors linking genetic structure to landscape mechanisms. We used breeding habitat metrics, landscape attributes, and indices of grouse abundance, to compare fit between structural connectivity and genetic differentiation within five long-established Sage-Grouse Management Zones (MZ) I-V using microsatellite genotypes from 6,844 greater sage-grouse (Centrocercus urophasianus) collected across their 10.7 million-km2 range. We estimated structural connectivity using a circuit theory-based approach where we built resistance surfaces using thresholds dividing the landscape into "habitat" and "nonhabitat" and nodes were clusters of sage-grouse leks (where feather samples were collected using noninvasive techniques). As hypothesized, MZ-specific habitat metrics were the best predictors of differentiation. To our surprise, inclusion of grouse abundance-corrected indices did not greatly improve model fit in most MZs. Functional connectivity of breeding habitat was reduced when probability of lek occurrence dropped below 0.25 (MZs I, IV) and 0.5 (II), thresholds lower than those previously identified as required for the formation of breeding leks, which suggests that individuals are willing to travel through undesirable habitat. The individual MZ landscape results suggested terrain roughness and steepness shaped functional connectivity across all MZs. Across respective MZs, sagebrush availability (<10%-30%; II, IV, V), tree canopy cover (>10%; I, II, IV), and cultivation (>25%; I, II, IV, V) each reduced movement beyond their respective thresholds. Model validations confirmed variation in predictive ability across MZs with top resistance surfaces better predicting gene flow than geographic distance alone, especially in cases of low and high differentiation among lek groups. The resultant resistance maps we produced spatially depict the strength and redundancy of range-wide gene flow and can help direct conservation actions to maintain and restore functional connectivity for sage-grouse.

Landscape limits gene flow and drives population structure in Agassiz's desert tortoise (Gopherus agassizii)

Distance, environmental heterogeneity and local adaptation can strongly influence population structure and connectivity. Understanding how these factors shape the genomic landscape of threatened species is a major goal in conservation genomics and wildlife management. Herein, we use thousands (6,859) of single nucleotide polymorphism markers and spatial data from hundreds of individuals (n = 646) to re-evaluate the population structure of Agassiz's desert tortoise (Gopherus agassizii). Analyses resolve from 4 to 8 spatially well-defined clusters across the range. Western, central, and southern populations within the Western Mojave recovery unit are consistent throughout, while analyses sometimes merge other recovery units depending on the level of clustering. Causal modeling consistently associates genetic connectivity with least-cost distance, based on multiple landscape features associated with tortoise habitat, better than geographic distance. Some features include elevation, soil depth, rock volume, precipitation, and vegetation coverage, suggesting that physical, climatic, and biotic landscape features have played a strong evolutionary role restricting gene flow between populations. Further, 12 highly differentiated outlier loci have associated functions that may be involved with neurogenesis, wound healing, lipid metabolism, and possibly vitellogenesis. Together, these findings have important implications for recovery programs, such as translocations, population augmentation, reproduction in captivity and the identification of ecologically important genes, opening new venues for conservation genomics in desert tortoises.

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.

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.

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.