ISOLATION BY RESISTANCE

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.

Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns

The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.

Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment

The conservation field is experiencing a rapid increase in the amount, variety, and quality of spatial data that can help us understand species movement and landscape connectivity patterns. As interest grows in more dynamic representations of movement potential, modelers are often limited by the capacity of their analytic tools to handle these datasets. Technology developments in software and high-performance computing are rapidly emerging in many fields, but uptake within conservation may lag, as our tools or our choice of computing language can constrain our ability to keep pace. We recently updated Circuitscape, a widely used connectivity analysis tool developed by Brad McRae and Viral Shah, by implementing it in Julia, a high-performance computing language. In this initial re-code (Circuitscape 5.0) and later updates, we improved computational efficiency and parallelism, achieving major speed improvements, and enabling assessments across larger extents or with higher resolution data. Here, we reflect on the benefits to conservation of strengthening collaborations with computer scientists, and extract examples from a collection of 572 Circuitscape applications to illustrate how through a decade of repeated investment in the software, applications have been many, varied, and increasingly dynamic. Beyond empowering continued innovations in dynamic connectivity, we expect that faster run times will play an important role in facilitating co-production of connectivity assessments with stakeholders, increasing the likelihood that connectivity science will be incorporated in land use decisions.

Up in the air: Threats to Afromontane biodiversity from climate change and habitat loss revealed by genetic monitoring of the Ethiopian Highlands bat

While climate change is recognized as a major future threat to biodiversity, most species are currently threatened by extensive human-induced habitat loss, fragmentation and degradation. Tropical high-altitude alpine and montane forest ecosystems and their biodiversity are particularly sensitive to temperature increases under climate change, but they are also subject to accelerated pressures from land conversion and degradation due to a growing human population. We studied the combined effects of anthropogenic land-use change, past and future climate changes and mountain range isolation on the endemic Ethiopian Highlands long-eared bat, Plecotus balensis, an understudied bat that is restricted to the remnant natural high-altitude Afroalpine and Afromontane habitats. We integrated ecological niche modelling, landscape genetics and model-based inference to assess the genetic, geographic and demographic impacts of past and recent environmental changes. We show that mountain range isolation and historic climates shaped population structure and patterns of genetic variation, but recent anthropogenic land-use change and habitat degradation are associated with a severe population decline and loss of genetic diversity. Models predict that the suitable niche of this bat has been progressively shrinking since the last glaciation period. This study highlights threats to Afroalpine and Afromontane biodiversity, squeezed to higher altitudes under climate change while losing genetic diversity and suffering population declines due to anthropogenic land-use change. We conclude that the conservation of tropical montane biodiversity requires a holistic approach, using genetic, ecological and geographic information to understand the effects of environmental changes across temporal scales and simultaneously addressing the impacts of multiple threats.

Flightlessness in insects enhances diversification and determines assemblage structure across whole communities

Dispersal limitation has been recurrently suggested to shape both macroecological patterns and microevolutionary processes within invertebrates. However, because of potential interactions among biological, environmental, temporal, and spatial variables, causal links among flight-related traits, diversification and spatial patterns of community assembly remain elusive. Integrating genetic variation within species across whole insect assemblages, within a simplified spatial and environmental framework, can be used to reduce the impact of these potentially confounding variables. Here, we used standardized sampling and mitochondrial DNA sequencing for a whole-community characterization of the beetle fauna inhabiting a singular forested habitat (laurel forest) within an oceanic archipelago setting (Canary Islands). The spatial structure of species assemblages together with species-level genetic diversity was compared at the archipelago and island scales for 104 winged and 110 wingless beetle lineages. We found that wingless beetle lineages have: (i) smaller range sizes at the archipelago scale, (ii) lower representation in younger island communities, (iii) stronger population genetic structure, and (iv) greater spatial structuring of species assemblages between and within islands. Our results reveal that dispersal limitation is a fundamental trait driving diversity patterns at multiple hierarchical levels by promoting spatial diversification and affecting the spatial configuration of entire assemblages at both island and archipelago scales.

High dispersal capacity of Culicoides obsoletus (Diptera: Ceratopogonidae), vector of bluetongue and Schmallenberg viruses, revealed by landscape genetic analyses

BACKGROUND

In the last two decades, recurrent epizootics of bluetongue virus and Schmallenberg virus have been reported in the western Palearctic region. These viruses affect domestic cattle, sheep, goats and wild ruminants and are transmitted by native hematophagous midges of the genus Culicoides (Diptera: Ceratopogonidae). Culicoides dispersal is known to be stratified, i.e. due to a combination of dispersal processes occurring actively at short distances and passively or semi-actively at long distances, allowing individuals to jump hundreds of kilometers.

METHODS

Here, we aim to identify the environmental factors that promote or limit gene flow of Culicoides obsoletus, an abundant and widespread vector species in Europe, using an innovative framework integrating spatial, population genetics and statistical approaches. A total of 348 individuals were sampled in 46 sites in France and were genotyped using 13 newly designed microsatellite markers.

RESULTS

We found low genetic differentiation and a weak population structure for C. obsoletus across the country. Using three complementary inter-individual genetic distances, we did not detect any significant isolation by distance, but did detect significant anisotropic isolation by distance on a north-south axis. We employed a multiple regression on distance matrices approach to investigate the correlation between genetic and environmental distances. Among all the environmental factors that were tested, only cattle density seems to have an impact on C. obsoletus gene flow.

CONCLUSIONS

The high dispersal capacity of C. obsoletus over land found in the present study calls for a re-evaluation of the impact of Culicoides on virus dispersal, and highlights the urgent need to better integrate molecular, spatial and statistical information to guide vector-borne disease control.

Analysing landscape effects on dispersal networks and gene flow with genetic graphs

Graph-theoretic approaches have relevant applications in landscape genetic analyses. When species form populations in discrete habitat patches, genetic graphs can be used (a) to identify direct dispersal paths followed by propagules or (b) to quantify landscape effects on multi-generational gene flow. However, the influence of their construction parameters remains to be explored. Using a simulation approach, we constructed genetic graphs using several pruning methods (geographical distance thresholds, topological constraints, statistical inference) and genetic distances to weight graph links (F_ST , D_PS , Euclidean genetic distances). We then compared the capacity of these different graphs to (a) identify the precise topology of the dispersal network and (b) to infer landscape resistance to gene flow from the relationship between cost-distances and genetic distances. Although not always clear-cut, our results showed that methods based on geographical distance thresholds seem to better identify dispersal networks in most cases. More interestingly, our study demonstrates that a sub-selection of pairwise distances through graph pruning (thereby reducing the number of data points) can counter-intuitively lead to improved inferences of landscape effects on dispersal. Finally, we showed that genetic distances such as the D_PS or Euclidean genetic distances should be preferred over the F_ST for landscape effect inference as they respond faster to landscape changes.

Idiosyncratic responses to drivers of genetic differentiation in the complex landscapes of Isthmian Central America

Isthmian Central America (ICA) is one of the most biodiverse regions in the world, hosting an exceptionally high number of species per unit area. ICA was formed <25 million years ago and, consequently, its biotic assemblage is relatively young and derived from both colonization and in situ diversification. Despite intensive taxonomic work on the local fauna, the potential forces driving genetic divergences and ultimately speciation in ICA remain poorly studied. Here, we used a landscape genetics approach to test whether isolation by distance, topography, habitat suitability, or environment drive the genetic diversity of the regional frog assemblage. To this end, we combined data on landscape features and mitochondrial DNA sequence variation for nine codistributed amphibian species with disparate life histories. In five species, we found that at least one of the factors tested explained patterns of genetic divergence. However, rather than finding a general pattern, our results revealed idiosyncratic responses to historical and ecological processes, indicating that intrinsic life-history characteristics may determine the effect of different drivers of isolation on genetic divergence in ICA. Our work also suggests that the convergence of several factors promoting isolation among populations over a heterogeneous landscape might maximize genetic differentiation, despite short geographical distances. In conclusion, abiotic factors and geographical features have differentially affected the genetic diversity across the regional frog assemblage. Much more complex models (i.e., considering multiple drivers), beyond simple vicariance of Caribbean and Pacific lineages, are needed to better understand the evolutionary history of ICA's diverse biotas.

Type and intensity of surrounding human land use, not local environment, shape genetic structure of a native grassland plant

Landscape heterogeneity can shape genetic structure and functional connectivity of populations. When this heterogeneity imposes variable costs of moving across the landscape, populations can be structured according to a pattern of "isolation by resistance" (IBR). At the same time, divergent local environmental filters can limit gene flow, creating an alternative pattern of "isolation by environment" (IBE). Here, we evaluate IBR and IBE in the insect-pollinated, biennial plant Sabatia angularis (L.) Pursh (Gentianaceae) across serpentine grasslands in the fragmented landscape of SE Pennsylvania, USA using ~4500 neutral SNP loci. Specifically, we test the extent to which radical alteration of the landscape matrix by humans has fundamentally altered the cost of movement, imprinting a pattern of IBR dictated by land use type and intensity, and the potential for IBE in relation to a gradient of heavy metal concentrations found in serpentine soil. We reveal a strong signal of IBR and a weak signal of IBE across sites, indicating the greater importance of the landscape matrix in shaping genetic structure of S. angularis populations in the study region. Based on Circuitscape and least cost path approaches, we find that both low- and high-intensity urbanization resist gene flow by orders of magnitude greater than "natural" habitats, although resistance to low-intensity urbanization weakens at larger spatial scales. While cropland presents a substantially lower barrier than urban development, cumulative human land use surrounding populations predicts within-population genetic diversity and inbreeding in S. angularis. Our results emphasize the role of forest buffers and corridors in facilitating gene flow between serpentine grassland patches and averting local extinction of plant populations.

Host relatedness and landscape connectivity shape pathogen spread in the puma, a large secretive carnivore

Urban expansion can fundamentally alter wildlife movement and gene flow, but how urbanization alters pathogen spread is poorly understood. Here, we combine high resolution host and viral genomic data with landscape variables to examine the context of viral spread in puma (Puma concolor) from two contrasting regions: one bounded by the wildland urban interface (WUI) and one unbounded with minimal anthropogenic development (UB). We found landscape variables and host gene flow explained significant amounts of variation of feline immunodeficiency virus (FIV) spread in the WUI, but not in the unbounded region. The most important predictors of viral spread also differed; host spatial proximity, host relatedness, and mountain ranges played a role in FIV spread in the WUI, whereas roads might have facilitated viral spread in the unbounded region. Our research demonstrates how anthropogenic landscapes can alter pathogen spread, providing a more nuanced understanding of host-pathogen relationships to inform disease ecology in free-ranging species.

Harnessing landscape genomics to identify future climate resilient genotypes in a desert annual

Local adaptation features critically in shaping species responses to changing environments, complicating efforts to revegetate degraded areas. Rapid climate change poses an additional challenge that could reduce fitness of even locally sourced seeds in restoration. Predictive restoration strategies that apply seeds with favourable adaptations to future climate may promote long-term resilience. Landscape genomics is increasingly used to assess spatial patterns in local adaption and may represent a cost-efficient approach for identifying future-adapted genotypes. To demonstrate such an approach, we genotyped 760 plants from 64 Mojave Desert populations of the desert annual Plantago ovata. Genome scans on 5,960 SNPs identified 184 potentially adaptive loci related to climate and satellite vegetation metrics. Causal modelling indicated that variation in potentially adaptive loci was not confounded by isolation by distance or isolation by habitat resistance. A generalized dissimilarity model (GDM) attributed spatial turnover in potentially adaptive loci to temperature, precipitation and NDVI amplitude, a measure of vegetation green-up potential. By integrating a species distribution model (SDM), we find evidence that summer maximum temperature may both constrain the range of P. ovata and drive adaptive divergence in populations exposed to higher temperatures. Within the species' current range, warm-adapted genotypes are predicted to experience a fivefold expansion in climate niche by midcentury and could harbour key adaptations to cope with future climate. We recommend eight seed transfer zones and project each zone into its relative position in future climate. Prioritizing seed collection efforts on genotypes with expanding future habitat represents a promising strategy for restoration practitioners to address rapidly changing climates.

Genetic structure across urban and agricultural landscapes reveals evidence of resource specialization and philopatry in the Eastern carpenter bee, Xylocopa virginica L

Human activity continues to impact global ecosystems, often by altering the habitat suitability, persistence, and movement of native species. It is thus critical to examine the population genetic structure of key ecosystemservice providers across human-altered landscapes to provide insight into the forces that limit wildlife persistence and movement across multiple spatial scales. While some studies have documented declines of bee pollinators as a result of human-mediated habitat alteration, others suggest that some bee species may benefit from altered land use due to increased food or nesting resource availability; however, detailed population and dispersal studies have been lacking. We investigated the population genetic structure of the Eastern carpenter bee, Xylocopa virginica, across 14 sites spanning more than 450 km, including dense urban areas and intensive agricultural habitat. X. virginica is a large bee which constructs nests in natural and human-associated wooden substrates, and is hypothesized to disperse broadly across urbanizing areas. Using 10 microsatellite loci, we detected significant genetic isolation by geographic distance and significant isolation by land use, where urban and cultivated landscapes were most conducive to gene flow. This is one of the first population genetic analyses to provide evidence of enhanced insect dispersal in human-altered areas as compared to semi-natural landscapes. We found moderate levels of regional-scale population structure across the study system (G'ST = 0.146) and substantial co-ancestry between the sampling regions, where co-ancestry patterns align with major human transportation corridors, suggesting that human-mediated movement may be influencing regional dispersal processes. Additionally, we found a signature of strong site-level philopatry where our analyses revealed significant levels of high genetic relatedness at very fine scales (<1 km), surprising given X. virginica's large body size. These results provide unique genetic evidence that insects can simultaneously exhibit substantial regional dispersal as well as high local nesting fidelity in landscapes dominated by human activity.

Phylogeographic Approaches to Characterize the Emergence of Plant Pathogens

Phylogeography combines geographic information with phylogenetic and population genomic approaches to infer the evolutionary history of a species or population in a geographic context. This approach has been instrumental in understanding the emergence, spread, and evolution of a range of plant pathogens. In particular, phylogeography can address questions about where a pathogen originated, whether it is native or introduced, and when and how often introductions occurred. We review the theory, methods, and approaches underpinning phylogeographic inference and highlight applications providing novel insights into the emergence and spread of select pathogens. We hope that this review will be useful in assessing the power, pitfalls, and opportunities presented by various phylogeographic approaches.

Spatial genetic structure and landscape connectivity in black bears: Investigating the significance of using different land cover datasets and classifications in landscape genetics analyses

Landscape genetic analyses allow detection of fine-scale spatial genetic structure (SGS) and quantification of effects of landscape features on gene flow and connectivity. Typically, analyses require generation of resistance surfaces. These surfaces characteristically take the form of a grid with cells that are coded to represent the degree to which landscape or environmental features promote or inhibit animal movement. How accurately resistance surfaces predict association between the landscape and movement is determined in large part by (a) the landscape features used, (b) the resistance values assigned to features, and (c) how accurately resistance surfaces represent landscape permeability. Our objective was to evaluate the performance of resistance surfaces generated using two publicly available land cover datasets that varied in how accurately they represent the actual landscape. We genotyped 365 individuals from a large black bear population (Ursus americanus) in the Northern Lower Peninsula (NLP) of Michigan, USA at 12 microsatellite loci, and evaluated the relationship between gene flow and landscape features using two different land cover datasets. We investigated the relative importance of land cover classification and accuracy on landscape resistance model performance. We detected local spatial genetic structure in Michigan's NLP black bears and found roads and land cover were significantly correlated with genetic distance. We observed similarities in model performance when different land cover datasets were used despite 21% dissimilarity in classification between the two land cover datasets. However, we did find the performance of land cover models to predict genetic distance was dependent on the way the land cover was defined. Models in which land cover was finely defined (i.e., eight land cover classes) outperformed models where land cover was defined more coarsely (i.e., habitat/non-habitat or forest/non-forest). Our results show that landscape genetic researchers should carefully consider how land cover classification changes inference in landscape genetic studies.

Connectivity assessment and prioritization of urban grasslands as a helpful tool for effective management of urban ecosystem services

Urban grasslands are usually managed as short-cut lawns and have limited biodiversity. Urban grasslands with low-intensity management are species rich and can perform numerous ecosystem services, but they are not accepted by citizens everywhere. Further, increasing and/or maintaining a relatively high level of plant species richness in an urban environment is limited by restricted plant dispersal. In this study, we examined the connectivity of urban grasslands and prioritized the grassland patches with regard to their role in connectivity in an urban landscape. We used high-resolution data from a land use system to map grassland patches in Wrocław city, Silesia, southwest Poland, Central Europe, and applied a graph theory approach to assess their connectivity and prioritization. We next constructed a model for several dispersal distance thresholds (2, 20, 44, 100, and 1000 m), reflecting plants with differing dispersal potential. Our results revealed low connectivity of urban grassland patches, especially for plants with low dispersal ability (2–20 m). The priority of patches was correlated with their area for all dispersal distance thresholds. Most of the large patches important to overall connectivity were located in urban peripheries, while in the city center, connectivity was more restricted and grassland area per capita was the lowest. The presence of a river created a corridor, allowing plants to migrate along watercourse, but it also created a barrier dividing the system. The results suggest that increasing the plant species richness in urban grasslands in the city center requires seed addition.

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.

Different landscape effects on the genetic structure of two broadly distributed woody legumes, Acacia salicina and A. stenophylla (Fabaceae)

Restoring degraded landscapes has primarily focused on re-establishing native plant communities. However, little is known with respect to the diversity and distribution of most key revegetation species or the environmental and anthropogenic factors that may affect their demography and genetic structure. In this study, we investigated the genetic structure of two widespread Australian legume species (Acacia salicina and Acacia stenophylla) in the Murray-Darling Basin (MDB), a large agriculturally utilized region in Australia, and assessed the impact of landscape structure on genetic differentiation. We used AFLP genetic data and sampled a total of 28 A. salicina and 30 A. stenophylla sampling locations across southeastern Australia. We specifically evaluated the importance of four landscape features: forest cover, land cover, water stream cover, and elevation. We found that both species had high genetic diversity (mean percentage of polymorphic loci, 55.1% for A. salicina versus. 64.3% for A. stenophylla) and differentiation among local sampling locations (A. salicina: ΦPT = 0.301, 30%; A. stenophylla: ΦPT = 0.235, 23%). Population structure analysis showed that both species had high levels of structure (6 clusters each) and admixture in some sampling locations, particularly A. stenophylla. Although both species have a similar geographic range, the drivers of genetic connectivity for each species were very different. Genetic variation in A. salicina seems to be mainly driven by geographic distance, while for A. stenophylla, land cover appears to be the most important factor. This suggests that for the latter species, gene flow among populations is affected by habitat fragmentation. We conclude that these largely co-occurring species require different management actions to maintain population connectivity. We recommend active management of A. stenophylla in the MDB to improve gene flow in the adversity of increasing disturbances (e.g., droughts) driven by climate change and anthropogenic factors.

Quantifying the individual impact of artificial barriers in freshwaters: A standardized and absolute genetic index of fragmentation

Fragmentation by artificial barriers is an important threat to freshwater biodiversity. Mitigating the negative aftermaths of fragmentation is of crucial importance, and it is now essential for environmental managers to benefit from a precise estimate of the individual impact of weirs and dams on river connectivity. Although the indirect monitoring of fragmentation using molecular data constitutes a promising approach, it is plagued with several constraints preventing a standardized quantification of barrier effects. Indeed, observed levels of genetic differentiation GD depend on both the age of the obstacle and the effective size of the populations it separates, making comparisons of the actual barrier effect of different obstacles difficult. Here, we developed a standardized genetic index of fragmentation (F INDEX), allowing an absolute and independent assessment of the individual effects of obstacles on connectivity. The F INDEX is the standardized ratio between the observed GD between pairs of populations located on either side of an obstacle and the GD expected if this obstacle completely prevented gene flow. The expected GD is calculated from simulations taking into account two parameters: the number of generations since barrier creation and the expected heterozygosity of the populations, a proxy for effective population size. Using both simulated and empirical datasets, we explored the validity and the limits of the F INDEX. We demonstrated that it allows quantifying effects of fragmentation only from a few generations after barrier creation and provides valid comparisons among obstacles of different ages and populations (or species) of different effective sizes. The F INDEX requires a minimum amount of fieldwork and genotypic data and solves some of the difficulties inherent to the study of artificial fragmentation in rivers and potentially in other ecosystems. This makes the F INDEX promising to support the management of freshwater species affected by barriers, notably for planning and evaluating restoration programs.

Epidemiological hypothesis testing using a phylogeographic and phylodynamic framework

Computational analyses of pathogen genomes are increasingly used to unravel the dispersal history and transmission dynamics of epidemics. Here, we show how to go beyond historical reconstructions and use spatially-explicit phylogeographic and phylodynamic approaches to formally test epidemiological hypotheses. We illustrate our approach by focusing on the West Nile virus (WNV) spread in North America that has substantially impacted public, veterinary, and wildlife health. We apply an analytical workflow to a comprehensive WNV genome collection to test the impact of environmental factors on the dispersal of viral lineages and on viral population genetic diversity through time. We find that WNV lineages tend to disperse faster in areas with higher temperatures and we identify temporal variation in temperature as a main predictor of viral genetic diversity through time. By contrasting inference with simulation, we find no evidence for viral lineages to preferentially circulate within the same migratory bird flyway, suggesting a substantial role for non-migratory birds or mosquito dispersal along the longitudinal gradient.

Channel network structure determines genetic connectivity of landward-seaward Avicennia marina populations in a tropical bay

Mangrove ecosystems along the East African coast are often characterized by a disjunct zonation pattern of seaward and landward Avicennia marina trees. This disjunct zonation may be maintained through different positions in the tidal frame, yielding different dispersal settings. The spatial configuration of the landscape and coastal processes such as tides and waves is expected to largely influence the extent of propagule transport and subsequent regeneration. We hypothesized that landward sites would keep a stronger genetic structure over short distances in comparison with enhanced gene flow among regularly flooded seaward fringes. We tested this hypothesis from densely vegetated A. marina transects of a well-documented mangrove system (Gazi Bay, Kenya) and estimated local gene flow and kinship-based fine-scale genetic structure. Ten polymorphic microsatellite markers in 457 A. marina trees revealed no overall significant difference in levels of allele or gene diversities between sites that differ in hydrological proximity. Genetic structure and connectivity of A. marina populations however indicated an overall effect of geographic distance and revealed a pronounced distinction between channels and topographic setting. Migration models allowed to infer gene flow directionality among channels, and indicated a bidirectional steppingstone between seaward and nearest located landward stands. Admixed gene pools without any fine-scale structure were found within the wider and more exposed Kidogoweni channel, suggesting open systems. Elevated kinship values and structure over 5 to 20 m distance were only detected in two distant landward and seaward transects near the mouth of the Mkurumuji River, indicating local retention and establishment. Overall, our findings show that patterns of A. marina connectivity are explained by hydrological proximity, channel network structure, and hydrokinetic energy, rather than just their positioning as disjunct landward or seaward zones.

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.

Hidden Markov Models reveal a clear human footprint on the movements of highly mobile African wild dogs

Large carnivores have experienced considerable range contraction, increasing the importance of movement across human-altered landscapes between small, isolated populations. African wild dogs (Lycaon pictus) are exceptionally wide-ranging, and recolonization is an important element of their persistence at broad scales. The competition-movement-connection hypothesis suggests that adaptations to move through areas that are unfavorable due to dominant competitors might promote the ability of subordinate competitors (like wild dogs) to move through areas that are unfavorable due to humans. Here, we used hidden Markov models to test how wild dog movements were affected by the Human Footprint Index in areas inside and outside of South Luangwa National Park. Movements were faster and more directed when outside the National Park, but slowed where the human footprint was stronger. Our results can be directly and quantitatively applied to connectivity planning, and we use them to identify ways to better understand differences between species in recent loss of connectivity.

The differential genetic signatures related to climatic landscapes for jaguars and pumas on a continental scale

Modern and paleoclimate changes may have altered species dynamics by shifting species' niche suitability over space and time. We analyze whether the current genetic structure and isolation of the two large American felids, jaguar (Panthera onca) and puma (Puma concolor), are mediated by changes in climatic suitability and connection routes over modern and paleoclimatic landscapes. We estimate species distribution under 5 climatic landscapes (modern, Holocene, last maximum glaciations [LMG], average suitability, and climatic instability) and correlate them with individuals' genetic isolation through causal modeling on a resemblance matrix. Both species exhibit genetic isolation patterns correlated with LMG climatic suitability, suggesting that these areas may have worked as "allele refuges." However, the jaguar showed higher vulnerability to climate changes, responding to modern climatic suitability and connection routes, whereas the puma showed a continuous and gradual transition of genetic variation. Despite differential responsiveness to climate change, both species are subjected to the climatic effects on genetic configuration, which may make them susceptible to future climatic changes, since these are progressing faster and with higher intensity than changes in the paleoclimate. Thus, the effects of climatic changes should be considered in the design of conservation strategies to ensure evolutionary and demographic processes mediated by gene flow for both species.

A novel quantitative framework for riverscape genetics

Riverscape genetics, which applies concepts in landscape genetics to riverine ecosystems, lack appropriate quantitative methods that address the spatial autocorrelation structure of linear stream networks and account for bidirectional geneflow. To address these challenges, we present a general framework for the design and analysis of riverscape genetic studies. Our framework starts with the estimation of pairwise genetic distance at sample sites and the development of a spatially structured ecological network (SSEN) on which riverscape covariates are measured. We then introduce the novel bidirectional geneflow in riverscapes (BGR) model that uses principles of isolation-by-resistance to quantify the effects of environmental covariates on genetic connectivity, with spatial covariance defined using simultaneous autoregressive models on the SSEN and the generalized Wishart distribution to model pairwise distance matrices arising through a random walk model of geneflow. We highlight the utility of this framework in an analysis of riverscape genetics for brook trout (Salvelinus fontinalis) in north central Pennsylvania, USA. Using the fixation index (F_ST ) as the measure of genetic distance, we estimated the effects of 12 riverscape covariates on geneflow by evaluating the relative support of eight competing BGR models. We then compared the performance of the top-ranked BGR model to results obtained from comparable analyses using multiple regression on distance matrices (MRM) and the program STRUCTURE. We found that the BGR model had more power to detect covariate effects, particularly for variables that were only partial barriers to geneflow and/or uncommon in the riverscape, making it more informative for assessing patterns of population connectivity and identifying threats to species conservation. This case study highlights the utility of our modeling framework over other quantitative methods in riverscape genetics, particularly the ability to rigorously test hypotheses about factors that influence geneflow and probabilistically estimate the effect of riverscape covariates, including stream flow direction. This framework is flexible across taxa and riverine networks, is easily executable, and provides intuitive results that can be used to investigate the likely outcomes of current and future management scenarios.

Genomic insights into adaptation to heterogeneous environments for the ancient relictual Circaeaster agrestis (Circaeasteraceae, Ranunculales)

Investigating the interaction between environmental heterogeneity and local adaptation is critical for understanding the evolutionary history of a species, providing the premise for studying the response of organisms to rapid climate change. However, for most species how exactly the spatial heterogeneity promotes population divergence and how genomic variations contribute to adaptive evolution remain poorly understood. We examine the contributions of geographical and environmental variables to population divergence of the relictual, alpine herb Circaeaster agrestis, as well as the genetic basis of local adaptation using RAD-seq and plastome data. We detected significant genetic structure with an extraordinary disequilibrium of genetic diversity among regions, and signals of isolation-by-distance along with isolation-by-resistance. The populations were estimated to begin diverging in the late Miocene, along with a possible ancestral distribution of the Hengduan Mountains and adjacent regions. Both environmental gradient and redundancy analyses revealed significant association between genetic variation and temperature variables. Genome-environment association analyses identified 16 putatively adaptive loci related mainly to biotic and abiotic stress resistance. Our genome-wide data provide new insights into the important role of environmental heterogeneity in shaping genetic structure, and access the footprints of local adaptation in an ancient relictual species, informing future conservation efforts.

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.

Comparative landscape genetics reveals differential effects of environment on host and pathogen genetic structure in Tasmanian devils (Sarcophilus harrisii) and their transmissible tumour

Genetic structure in host species is often used to predict disease spread. However, host and pathogen genetic variation may be incongruent. Understanding landscape factors that have either concordant or divergent influence on host and pathogen genetic structure is crucial for wildlife disease management. Devil facial tumour disease (DFTD) was first observed in 1996 and has spread throughout almost the entire Tasmanian devil geographic range, causing dramatic population declines. Whereas DFTD is predominantly spread via biting among adults, devils typically disperse as juveniles, which experience low DFTD prevalence. Thus, we predicted little association between devil and tumour population structure and that environmental factors influencing gene flow differ between devils and tumours. We employed a comparative landscape genetics framework to test the influence of environmental factors on patterns of isolation by resistance (IBR) and isolation by environment (IBE) in devils and DFTD. Although we found evidence for broad-scale costructuring between devils and tumours, we found no relationship between host and tumour individual genetic distances. Further, the factors driving the spatial distribution of genetic variation differed for each. Devils exhibited a strong IBR pattern driven by major roads, with no evidence of IBE. By contrast, tumours showed little evidence for IBR and a weak IBE pattern with respect to elevation in one of two tumour clusters we identify herein. Our results warrant caution when inferring pathogen spread using host population genetic structure and suggest that reliance on environmental barriers to host connectivity may be ineffective for managing the spread of wildlife diseases. Our findings demonstrate the utility of comparative landscape genetics for identifying differential factors driving host dispersal and pathogen transmission.

Effects of cost surface uncertainty on current density estimates from circuit theory

Background

Conservation practitioners are often interested in developing land use plans that increase landscape connectivity, which is defined as the degree to which the landscape facilitates or impedes movement among resource patches. Landscape connectivity is often estimated with a cost surface that indicates the varying costs experienced by an organism in moving across a landscape. True, or absolute costs are rarely known however, and therefore assigning costs to different landscape elements is often a challenge in creating cost surface maps. As such, we consider it important to understand the sensitivity of connectivity estimates to uncertainty in cost estimates.

Methods

We used simulated landscapes to test the sensitivity of current density estimates from circuit theory to varying relative cost values, fragmentation, and number of cost classes (i.e., thematic resolution). Current density is proportional to the probability of use during a random walk. Using Circuitscape software, we simulated electrical current between pairs of nodes to create current density maps. We then measured the correlation of the current density values across scenarios.

Results

In general, we found that cost values were highly correlated across scenarios with different cost weights (mean correlation ranged from 0.87 to 0.92). Changing the spatial configuration of landscape elements by varying the degree of fragmentation reduced correlation in current density across maps. We also found that correlations were more variable when the range of cost values in a map was high.

Discussion

The low sensitivity of current density estimates to relative cost weights suggests that the measure may be reliable for land use applications even when there is uncertainty about absolute cost values, provided that the user has the costs correctly ranked. This finding should facilitate the use of cost surfaces by conservation practitioners interested in estimating connectivity and planning linkages and corridors.

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.

Genotyping-in-Thousands by sequencing reveals marked population structure in Western Rattlesnakes to inform conservation status

Delineation of units below the species level is critical for prioritizing conservation actions for species at-risk. Genetic studies play an important role in characterizing patterns of population connectivity and diversity to inform the designation of conservation units, especially for populations that are geographically isolated. The northernmost range margin of Western Rattlesnakes (Crotalus oreganus) occurs in British Columbia, Canada, where it is federally classified as threatened and restricted to five geographic regions. In these areas, Western Rattlesnakes hibernate (den) communally, raising questions about connectivity within and between den complexes. At present, Western Rattlesnake conservation efforts are hindered by a complete lack of information on genetic structure and degree of isolation at multiple scales, from the den to the regional level. To fill this knowledge gap, we used Genotyping-in-Thousands by sequencing (GT-seq) to genotype an optimized panel of 362 single nucleotide polymorphisms (SNPs) from individual samples (n = 461) collected across the snake's distribution in western Canada and neighboring Washington (USA). Hierarchical STRUCTURE analyses found evidence for population structure within and among the five geographic regions in BC, as well as in Washington. Within these regions, 11 genetically distinct complexes of dens were identified, with some regions having multiple complexes. No significant pattern of isolation-by-distance and generally low levels of migration were detected among den complexes across regions. Additionally, snakes within dens generally were more related than those among den complexes within a region, indicating limited movement. Overall, our results suggest that the single, recognized designatable unit for Western Rattlesnakes in Canada should be re-assessed to proactively focus conservation efforts on preserving total genetic variation detected range-wide. More broadly, our study demonstrates a novel application of GT-seq for investigating patterns of diversity in wild populations at multiple scales to better inform conservation management.

Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana

BACKGROUND

Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation-isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)-in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1772 individuals from 278 populations distributed across the Iberian Peninsula.

RESULTS

IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana.

CONCLUSIONS

Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.

Range-wide genetic structure in the thorn-tailed rayadito suggests limited gene flow towards peripheral populations

Understanding the population genetic consequences of habitat heterogeneity requires assessing whether patterns of gene flow correspond to landscape configuration. Studies of the genetic structure of populations are still scarce for Neotropical forest birds. We assessed range-wide genetic structure and contemporary gene flow in the thorn-tailed rayadito (Aphrastura spinicauda), a passerine bird inhabiting the temperate forests of South America. We used 12 microsatellite loci to genotype 582 individuals from eight localities across a large latitudinal range (30°S–56°S). Using population structure metrics, multivariate analyses, clustering algorithms, and Bayesian methods, we found evidence for moderately low regional genetic structure and reduced gene flow towards the range margins. Genetic differentiation increased with geographic distance, particularly in the southern part of the species’ distribution where forests are continuously distributed. Populations in the north seem to experience limited gene flow likely due to forest discontinuity, and may comprise a demographically independent unit. The southernmost population, on the other hand, is genetically depauperate and different from all other populations. Different analytical approaches support the presence of three to five genetic clusters. We hypothesize that the genetic structure of the species follows a hierarchical clustered pattern.

The effect of landscape on functional connectivity and shell shape in the land snail Humboldtiana durangoensis

The populations of Humboldtiana durangoensis have experienced a drastic reduction in the effective population size; in addition, the species is threatened by anthropogenic activities. For the aforementioned, landscape genetics will serve as a tool to define the potential evolutionarily significant units (ESU) for this species. To complete our objective, we evaluated the effect of cover vegetation and climate on the functional connectivity of the species from the last glacial maximum (LGM) to the present as well as the effect of climate on shell shape. Partial Mantel tests, distance-based redundance analysis and a Bayesian framework were used to evaluate connectivity. On the other hand, geometric morphometrics, phylogenetic principal component analysis and redundancy analysis were used for the analysis of shell shape. Our results suggest that the suitable areas have been decreasing since the LGM; also, vegetation cover rather than climate has influenced the genetic connectivity among land snail populations, although temperature had a high influence on shell shape in this species. In conclusion, vegetation cover was the main factor that determined the functional connectivity for the land snail; however, local selective pressures led to different phenotypes in shell shape that allowed us to postulate that each one of the previously defined genetic groups must be considered as a different ESU.

Going with the flow: analysis of population structure reveals high gene flow shaping invasion pattern and inducing range expansion of Mikania micrantha in Asia

BACKGROUND AND AIMS

Mikania micrantha, a climbing perennial weed of the family Asteraceae, is native to Latin America and is highly invasive in the tropical belt of Asia, Oceania and Australia. This study was framed to investigate the population structure of M. micrantha at a large spatial scale in Asia and to identify how introduction history, evolutionary forces and landscape features influenced the genetic pattern of the species in this region.

METHODS

We assessed the genetic diversity and structure of 1052 individuals from 46 populations for 12 microsatellite loci. The spatial pattern of genetic variation was investigated by estimating the relationship between genetic distance and geographical, climatic and landscape resistances hypothesized to influence gene flow between populations.

KEY RESULTS

We found high genetic diversity of M. micrantha in this region, as compared with the genetic diversity parameters of other invasive species. Spatial and non-spatial clustering algorithms identified the presence of multiple genetic clusters and admixture between populations. Most of the populations showed heterozygote deficiency, primarily due to inbreeding, and the founder populations showed evidence of a genetic bottleneck. Persistent gene flow throughout the invasive range caused low genetic differentiation among populations and provided beneficial genetic variation to the marginal populations in a heterogeneous environment. Environmental suitability was found to buffer the detrimental effects of inbreeding at the leading edge of range expansion. Both linear and non-linear regression models demonstrated a weak relationship between genetic distance and geographical distance, as well as bioclimatic variables and environmental resistance surfaces.

CONCLUSIONS

These findings provide evidence that extensive gene flow and admixture between populations have influenced the current genetic pattern of M. micrantha in this region. High gene flow across the invaded landscape may facilitate adaptation, establishment and long-term persistence of the population, thereby indicating the range expansion ability of the species.

Genotyping-by-sequencing and ecological niche modeling illuminate phylogeography, admixture, and Pleistocene range dynamics in quaking aspen (Populus tremuloides)

Populus tremuloides is the widest-ranging tree species in North America and an ecologically important component of mesic forest ecosystems displaced by the Pleistocene glaciations. Using phylogeographic analyses of genome-wide SNPs (34,796 SNPs, 183 individuals) and ecological niche modeling, we inferred population structure, ploidy levels, admixture, and Pleistocene range dynamics of P. tremuloides, and tested several historical biogeographical hypotheses. We found three genetic lineages located mainly in coastal-Cascades (cluster 1), east-slope Cascades-Sierra Nevadas-Northern Rockies (cluster 2), and U.S. Rocky Mountains through southern Canadian (cluster 3) regions of the P. tremuloides range, with tree graph relationships of the form ((cluster 1, cluster 2), cluster 3). Populations consisted mainly of diploids (86%) but also small numbers of triploids (12%) and tetraploids (1%), and ploidy did not adversely affect our genetic inferences. The main vector of admixture was from cluster 3 into cluster 2, with the admixture zone trending northwest through the Rocky Mountains along a recognized phenotypic cline (Utah to Idaho). Clusters 1 and 2 provided strong support for the "stable-edge hypothesis" that unglaciated southwestern populations persisted in situ since the last glaciation. By contrast, despite a lack of clinal genetic variation, cluster 3 exhibited "trailing-edge" dynamics from niche suitability predictions signifying complete northward postglacial expansion. Results were also consistent with the "inland dispersal hypothesis" predicting postglacial assembly of Pacific Northwestern forest ecosystems, but rejected the hypothesis that Pacific-coastal populations were colonized during outburst flooding from glacial Lake Missoula. Overall, congruent patterns between our phylogeographic and ecological niche modeling results and fossil pollen data demonstrate complex mixtures of stable-edge, refugial locations, and postglacial expansion within P. tremuloides. These findings confirm and refine previous genetic studies, while strongly supporting a distinct Pacific-coastal genetic lineage of quaking aspen.

Rattus population genomics across the Haida Gwaii archipelago provides a framework for guiding invasive species management

Invasive species have led to precipitous declines in biodiversity, especially in island systems. Brown (Rattus norvegicus) and black rats (R. rattus) are among the most invasive animals on the planet, with eradication being the primary tool for established island populations. The need for increased research for defining eradication units and monitoring outcomes has been highlighted as a means to maximize success. Haida Gwaii is an archipelago ~100 km off the northern coast of British Columbia, Canada, that hosts globally significant breeding populations of seabirds that are at risk due to invasive rats. Here, we paired sampling of brown (n = 287) and black (n = 291) rats across the Haida Gwaii archipelago with genotyping by sequencing (10,770-27,686 SNPs) to investigate patterns of population connectivity and infer levels/direction of gene flow among invasive rat populations in Haida Gwaii. We reconstructed three regional clusters for both species (north, central and south), with proximate populations within regions being largely more related than those that were more distant, consistent with predictions from island biogeography theory. Population assignment of recently detected individuals post-eradication on Faraday, Murchison and the Bischof Islands revealed all were re-invaders from Lyell Island, rather than being on-island survivors. Based on these results, we identified six eradication units constituting single or clusters of islands that would limit the potential for reinvasion, some of which will need to be combined with biosecurity measures. Overall, our results highlight the importance of targeted research prior to conducting eradications and demonstrate a framework for applying population genomics for guiding invasive species management in island systems.

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.

Research on recognition and protection of ecological security patterns based on circuit theory: a case study of Jinan City

Accelerated urbanization and population growth have resulted in the loss of ecological land and biodiversity, accompanied by the degradation of ecosystem services. Identifying and improving existing ecological security patterns are of great significance for maintaining the sustainable development of cities. In this study, Jinan, the capital of China's Shandong Province, was used as a case study area. Based on three ecosystem services, namely, soil conservation, water conservation and carbon fixation, ecological sources were determined. Furthermore, a resistance surface was constructed based on biodiversity. On these bases, the circuit theory concept of random walks was applied to simulate ecosystem processes in a heterogeneous landscape and identify ecological corridors, pinch points and barriers. A total of 25 ecological sources, 48 ecological corridors and 19 pinch points were identified, and restoration areas were delimited to three levels. These elements together constituted the ecological security patterns. Specifically, the ecological sources were mainly distributed in southern Jinan and were covered mostly with forest land. The ecological corridors were located mainly in the eastern and southwestern plains below the southern mountainous areas and were covered mostly with cropland. Furthermore, the eastern corridors were much longer than the southwestern corridors. Pinch points were distributed mostly along rivers or around large-scale construction land. Barriers were distributed mainly in Zhangqiu District and northern Licheng District. Based on these findings, hierarchical restoration areas were delimited. Differentiated development contradictions in restoration areas were discussed, and corresponding ecological protection measures were proposed. An ecological security optimization pattern of "one center, two wings, and two belts" was finally proposed to provide planning strategies for decision-makers.

Sea ice loss increases genetic isolation in a high Arctic ungulate metapopulation

Sea ice loss may have dramatic consequences for population connectivity, extinction-colonization dynamics, and even the persistence of Arctic species subject to climate change. This is of particular concern in face of additional anthropogenic stressors, such as overexploitation. In this study, we assess the population-genetic implications of diminishing sea ice cover in the endemic, high Arctic Svalbard reindeer (Rangifer tarandus platyrhynchus) by analyzing the interactive effects of landscape barriers and reintroductions (following harvest-induced extirpations) on their metapopulation genetic structure. We genotyped 411 wild reindeer from 25 sampling sites throughout the entire subspecies' range at 19 microsatellite loci. Bayesian clustering analysis showed a genetic structure composed of eight populations, of which two were admixed. Overall population genetic differentiation was high (mean F_ST  = 0.21). Genetic diversity was low (allelic richness [AR] = 2.07-2.58; observed heterozygosity = 0.23-0.43) and declined toward the outer distribution range, where populations showed significant levels of inbreeding. Coalescent estimates of effective population sizes and migration rates revealed strong evolutionary source-sink dynamics with the central population as the main source. The population genetic structure was best explained by a landscape genetics model combining strong isolation by glaciers and open water, and high connectivity by dispersal across winter sea ice. However, the observed patterns of natural isolation were strongly modified by the signature of past harvest-induced extirpations, subsequent reintroductions, and recent lack of sea ice. These results suggest that past and current anthropogenic drivers of metapopulation dynamics may have interactive effects on large-scale ecological and evolutionary processes. Continued loss of sea ice as a dispersal corridor within and between island systems is expected to increase the genetic isolation of populations, and thus threaten the evolutionary potential and persistence of Arctic wildlife.

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.

Population genetics of the wolverine in Finland: the road to recovery?

After decades, even centuries of persecution, large carnivore populations are widely recovering in Europe. Considering the recent recovery of the wolverine (Gulo gulo) in Finland, our aim was to evaluate genetic variation using 14 microsatellites and mtDNA control region (579 bp) in order (1) to determine whether the species is represented by a single genetic population within Finland, (2) to quantify the genetic diversity, and (3) to estimate the effective population size. We found two major genetic clusters divided between eastern and northern Finland based on microsatellites (FST = 0.100) but also a significant pattern of isolation by distance. Wolverines in western Finland had a genetic signature similar to the northern cluster, which can be explained by former translocations of wolverines from northern to western Finland. For both main clusters, most estimates of the effective population size Ne were below 50. Nevertheless, the genetic diversity was higher in the eastern cluster (HE = 0.57, AR = 4.0, AP = 0.3) than in the northern cluster (HE = 0.49, AR = 3.7, AP = 0.1). Migration between the clusters was low. Two mtDNA haplotypes were found: one common and identical to Scandinavian wolverines; the other rare and not previously detected. The rare haplotype was more prominent in the eastern genetic cluster. Combining all available data, we infer that the genetic population structure within Finland is shaped by a recent bottleneck, isolation by distance, human-aided translocations and postglacial recolonization routes.