Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that within‐pond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes.     

Comparative landscape genetics of pond‐breeding amphibians in Mediterranean temporal wetlands: The positive role of structural heterogeneity in promoting gene flow

Comparative landscape genetics studies can provide key information to implement cost‐effective conservation measures favouring a broad set of taxa. These studies are scarce, particularly in Mediterranean areas, which include diverse but threatened biological communities. Here, we focus on Mediterranean wetlands in central Iberia and perform a multi‐level, comparative study of two endemic pond‐breeding amphibians, a salamander (Pleurodeles waltl) and a toad (Pelobates cultripes). We genotyped 411 salamanders from 20 populations and 306 toads from 16 populations at 18 and 16 microsatellite loci, respectively, and identified major factors associated with population connectivity through the analysis of three sets of variables potentially affecting gene flow at increasingly finer levels of spatial resolution. Topographic, land use/cover, and remotely sensed vegetation/moisture indices were used to derive optimized resistance surfaces for the two species. We found contrasting patterns of genetic structure, with stronger, finer scale genetic differentiation in Pleurodeles waltl, and notable differences in the role of fine‐scale patterns of heterogeneity in vegetation cover and water content in shaping patterns of regional genetic structure in the two species. Overall, our results suggest a positive role of structural heterogeneity in population connectivity in pond‐breeding amphibians, with habitat patches of Mediterranean scrubland and open oak woodlands (“dehesas”) facilitating gene flow. Our study highlights the usefulness of remotely sensed continuous variables of land cover, vegetation and water content (e.g., NDVI, NDMI) in conservation‐oriented studies aimed at identifying major drivers of population connectivity.     

Multiscale resistant kernel surfaces derived from inferred gene flow: An application with vernal pool breeding salamanders

The importance of assessing spatial data at multiple scales when modelling species–environment relationships has been highlighted by several empirical studies. However, no landscape genetics studies have optimized landscape resistance surfaces by evaluating relevant spatial predictors at multiple spatial scales. Here, we model multiscale/layer landscape resistance surfaces to estimate resistance to inferred gene flow for two vernal pool breeding salamander species, spotted (Ambystoma maculatum) and marbled (A. opacum) salamanders. Multiscale resistance surface models outperformed spatial layers modelled at their original spatial scale. A resistance surface with forest land cover at a 500‐m Gaussian kernel bandwidth and normalized vegetation index at a 100‐m Gaussian kernel bandwidth was the top optimized resistance surface for A. maculatum, while a resistance surface with traffic rate and topographic curvature, both at a 500‐m Gaussian kernel bandwidth, was the top optimized resistance surface for A. opacum. Species‐specific resistant kernels were fit at all vernal pools in our study area with the optimized multiscale/layer resistance surface controlling kernel spread. Vernal pools were then evaluated and scored based on surrounding upland habitat (local score) and connectivity with other vernal pools on the landscape, with resistant kernels driving vernal pool connectivity scores. As expected, vernal pools that scored highest were in areas within forested habitats and with high vernal pool densities and low species‐specific landscape resistance. Our findings highlight the success of using a novel analytical approach in a multiscale framework with applications beyond vernal pool amphibian conservation.     

The influence of breeding phenology on the genetic structure of four pond‐breeding salamanders

Understanding metapopulation dynamics requires knowledge about local population dynamics and movement in both space and time. Most genetic metapopulation studies use one or two study species across the same landscape to infer population dynamics; however, using multiple co‐occurring species allows for testing of hypotheses related to different life history strategies. We used genetic data to study dispersal, as measured by gene flow, in three ambystomatid salamanders (Ambystoma annulatum , A. maculatum , and A. opacum ) and the Central Newt (Notophthalmus viridescens louisianensis ) on the same landscape in Missouri, USA . While all four salamander species are forest dependent organisms that require fishless ponds to reproduce, they differ in breeding phenology and spatial distribution on the landscape. We use these differences in life history and distribution to address the following questions: (1) Are there species‐level differences in the observed patterns of genetic diversity and genetic structure? and (2) Is dispersal influenced by landscape resistance? We detected two genetic clusters in A. annulatum and A. opacum on our landscape; both species breed in the fall and larvae overwinter in ponds. In contrast, no structure was evident in A. maculatum and N. v. louisianensis , species that breed during the spring. Tests for isolation by distance were significant for the three ambystomatids but not for N. v. louisianensis . Landscape resistance also contributed to genetic differentiation for all four species. Our results suggest species‐level differences in dispersal ability and breeding phenology are driving observed patterns of genetic differentiation. From an evolutionary standpoint, the observed differences in dispersal distances and genetic structure between fall breeding and spring breeding species may be a result of the trade‐off between larval period length and size at metamorphosis which in turn may influence the long‐term viability of the metapopulation. Thus, it is important to consider life history differences among closely related and ecologically similar species when making management decisions.     

Estimating occupancy dynamics for large‐scale monitoring networks: amphibian breeding occupancy across protected areas in the northeast United States

Regional monitoring strategies frequently employ a nested sampling design where a finite set of study areas from throughout a region are selected and intensive sampling occurs within a subset of sites within the individual study areas. This sampling protocol naturally lends itself to a hierarchical analysis to account for dependence among subsamples. Implementing such an analysis using a classic likelihood framework is computationally challenging when accounting for detection errors in species occurrence models. Bayesian methods offer an alternative approach for fitting models that readily allows for spatial structure to be incorporated. We demonstrate a general approach for estimating occupancy when data come from a nested sampling design. We analyzed data from a regional monitoring program of wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in vernal pools using static and dynamic occupancy models. We analyzed observations from 2004 to 2013 that were collected within 14 protected areas located throughout the northeast United States. We use the data set to estimate trends in occupancy at both the regional and individual protected area levels. We show that occupancy at the regional level was relatively stable for both species. However, substantial variation occurred among study areas, with some populations declining and some increasing for both species. In addition, When the hierarchical study design is not accounted for, one would conclude stronger support for latitudinal gradient in trends than when using our approach that accounts for the nested design. In contrast to the model that does not account for nesting, the nested model did not include an effect of latitude in the 95% credible interval. These results shed light on the range‐level population status of these pond‐breeding amphibians, and our approach provides a framework that can be used to examine drivers of local and regional occurrence dynamics.     

Using simulations to evaluate Mantel‐based methods for assessing landscape resistance to gene flow

Mantel‐based tests have been the primary analytical methods for understanding how landscape features influence observed spatial genetic structure. Simulation studies examining Mantel‐based approaches have highlighted major challenges associated with the use of such tests and fueled debate on when the Mantel test is appropriate for landscape genetics studies. We aim to provide some clarity in this debate using spatially explicit, individual‐based, genetic simulations to examine the effects of the following on the performance of Mantel‐based methods: (1) landscape configuration, (2) spatial genetic nonequilibrium, (3) nonlinear relationships between genetic and cost distances, and (4) correlation among cost distances derived from competing resistance models. Under most conditions, Mantel‐based methods performed poorly. Causal modeling identified the true model only 22% of the time. Using relative support and simple Mantel r values boosted performance to approximately 50%. Across all methods, performance increased when landscapes were more fragmented, spatial genetic equilibrium was reached, and the relationship between cost distance and genetic distance was linearized. Performance depended on cost distance correlations among resistance models rather than cell‐wise resistance correlations. Given these results, we suggest that the use of Mantel tests with linearized relationships is appropriate for discriminating among resistance models that have cost distance correlations <0.85 with each other for causal modeling, or <0.95 for relative support or simple Mantel r. Because most alternative parameterizations of resistance for the same landscape variable will result in highly correlated cost distances, the use of Mantel test‐based methods to fine‐tune resistance values will often not be effective.     

Habitat predictors of genetic diversity for two sympatric wetland‐breeding amphibian species

Population genetic diversity is widely accepted as important to the conservation and management of wildlife. However, habitat features may differentially affect evolutionary processes that facilitate population genetic diversity among sympatric species. We measured genetic diversity for two pond‐breeding amphibian species (Dwarf salamanders, Eurycea quadridigitata; and Southern Leopard frogs, Lithobates sphenocephalus) to understand how habitat characteristics and spatial scale affect genetic diversity across a landscape. Samples were collected from wetlands on a longleaf pine reserve in Georgia. We genotyped microsatellite loci for both species to assess population structures and determine which habitat features were most closely associated with observed heterozygosity and rarefied allelic richness. Both species exhibited significant population genetic structure; however, structure in Southern Leopard frogs was driven primarily by one outlier site. Dwarf salamander allelic richness was greater at sites with less surrounding road area within 0.5 km and more wetland area within 1.0 and 2.5 km, and heterozygosity was greater at sites with more wetland area within 0.5 km. In contrast, neither measure of Southern Leopard frog genetic diversity was associated with any habitat features at any scale we evaluated. Genetic diversity in the Dwarf salamander was strongly associated with land cover variables up to 2.5 km away from breeding wetlands, and/or results suggest that minimizing roads in wetland buffers may be beneficial to the maintenance of population genetic diversity. This study suggests that patterns of genetic differentiation and genetic diversity have associations with different habitat features across different spatial scales for two syntopic pond‐breeding amphibian species.     

A Test of Local Enhancement in Amphibians

Local enhancement is an underexplored social learning mechanism that is often observed in organisms that live in groups. This mechanism occurs when individuals are attracted to areas where conspecifics have previously been, but which are not present when the animal actually moves into the area. We tested for local enhancement in wood frog tadpoles (Lithobates sylvatica) and spotted salamander larvae (Ambystoma maculatum) in three experiments that exposed individuals to one side of a test chamber which was empty and another that contained a group of three conspecifics. Side preference of the focal individual was recorded once the conspecifics were removed. Tadpoles showed a clear preference for moving to areas where a group of tadpoles had previously been located. Conversely, this preference was not observed in salamander larvae. In addition, salamander larvae took significantly more time to initially choose a side. These results indicate that tadpoles exhibit local enhancement, whereas aquatic salamander larvae do not. This difference in social learning could be largely due to differences in aquatic ecology between tadpoles and salamander larvae.     

The effects of different cold‐temperature regimes on development,growth, and susceptibility to an abiotic and biotic stressor

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The influence of landscape on gene flow in the eastern massasauga rattlesnake (Sistrurus c. catenatus): insight from computer simulations

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation‐by‐distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation‐by‐distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long‐standing natural features (e.g. water bodies) co‐exist on the landscape.     

Contemporary human‐altered landscapes and oceanic barriers reduce bumble bee gene flow

Much of the world's terrestrial landscapes are being altered by humans in the form of agriculture, urbanization and pastoral systems, with major implications for biodiversity. Bumble bees are one of the most effective pollinators in both natural and cultivated landscapes, but are often the first to be extirpated in human‐altered habitats. Yet, little is known about the role of natural and human‐altered habitats in promoting or limiting bumble bee gene flow. In this study, I closely examine the genetic structure of the yellow‐faced bumble bee, Bombus vosnesenskii, across the southwestern US coast and find strong evidence that natural oceanic barriers, as well as contemporary human‐altered habitats, limit bee gene flow. Heterozygosity and allelic richness were lower in island populations, while private allelic richness was higher in island populations compared to mainland populations. Genetic differentiation, measured for three indices across the 1000 km study region, was significantly greater than the null expectation (F_ST = 0.041, F’_ST = 0.044 and D_est = 0.155) and correlated with geographic distance. Furthermore, genetic differentiation patterns were most strongly correlated with contemporary (2011) not past (2006, 2001) resistance maps calibrated for high dispersal limitation over oceans, impervious habitat and croplands. Despite the incorporation of dramatic elevation gradients, the analyses reveal that oceans and contemporary human land use, not mountains, are the primary dispersal barriers for B. vosnesenskii gene flow. These findings reinforce the importance of maintaining corridors of suitable habitat across the distribution range of native pollinators to promote their persistence and safeguard their ability to provide essential pollination services.     

Beyond the landscape: Resistance modelling infers physical and behavioural gene flow barriers to a mobile carnivore across a metropolitan area

Urbanization affects key aspects of wildlife ecology. Dispersal in urban wildlife species may be impacted by geographical barriers but also by a species’ inherent behavioural variability. There are no functional connectivity analyses using continuous individual‐based sampling across an urban‐rural continuum that would allow a thorough assessment of the relative importance of physical and behavioural dispersal barriers. We used 16 microsatellite loci to genotype 374 red foxes (Vulpes vulpes) from the city of Berlin and surrounding rural regions in Brandenburg in order to study genetic structure and dispersal behaviour of a mobile carnivore across the urban‐rural landscape. We assessed functional connectivity by applying an individual‐based landscape genetic optimization procedure. Three commonly used genetic distance measures yielded different model selection results, with only the results of an eigenvector‐based multivariate analysis reasonably explaining genetic differentiation patterns. Genetic clustering methods and landscape resistance modelling supported the presence of an urban population with reduced dispersal across the city border. Artificial structures (railways, motorways) served as main dispersal corridors within the cityscape, yet urban foxes avoided densely built‐up areas. We show that despite their ubiquitous presence in urban areas, their mobility and behavioural plasticity, foxes were affected in their dispersal by anthropogenic presence. Distinguishing between man‐made structures and sites of human activity, rather than between natural and artificial structures, is thus essential for better understanding urban fox dispersal. This differentiation may also help to understand dispersal of other urban wildlife and to predict how behaviour can shape population genetic structure beyond physical barriers.     

Landscape effects on gene flow for a climate‐sensitive montane species,the American pika

Climate change is arguably the greatest challenge to conservation of our time. Most vulnerability assessments rely on past and current species distributions to predict future persistence but ignore species' abilities to disperse through landscapes, which may be particularly important in fragmented habitats and crucial for long‐term persistence in changing environments. Landscape genetic approaches explore the interactions between landscape features and gene flow and can clarify how organisms move among suitable habitats, but have suffered from methodological uncertainties. We used a landscape genetic approach to determine how landscape and climate‐related features influence gene flow for American pikas (Ochotona princeps) in Crater Lake National Park. Pikas are heat intolerant and restricted to cool microclimates; thus, range contractions have been predicted as climate changes. We evaluated the correlation between landscape variables and genetic distance using partial Mantel tests in a causal modelling framework, and used spatially explicit simulations to evaluate methods of model optimization including a novel approach based on relative support and reciprocal causal modelling. We found that gene flow was primarily restricted by topographic relief, water and west‐facing aspects, suggesting that physical restrictions related to small body size and mode of locomotion, as well as exposure to relatively high temperatures, limit pika dispersal in this alpine habitat. Our model optimization successfully identified landscape features influencing resistance in the simulated data for this landscape, but underestimated the magnitude of resistance. This is the first landscape genetic study to address the fundamental question of what limits dispersal and gene flow in the American pika.     

Seed dispersal and realized gene flow of two forest orchids in a fragmented landscape

• Species with vast production of dust‐like windborne seeds, such as orchids, should not be limited by seed dispersal. This paradigm, however, does not fit recent studies showing that many sites suitable for orchids are unoccupied and most seeds land close to their maternal plant. To explore this issue, we studied seed dispersal and gene flow of two forest orchid species, Epipactis atrorubens and Cephalanthera rubra, growing in a fragmented landscape of forested limestone hills in southwest Bohemia, Czech Republic.
• We used a combination of seed trapping and plant genotyping methods (microsatellite DNA markers) to quantify short‐ and long‐distance dispersal, respectively. In addition, seed production of both species was estimated.
• We found that most seeds landed very close to maternal plants (95% of captured seeds were within 7.2 m) in both species, and dispersal distance was influenced by forest type in E. atrorubens. In addition, C. rubra showed clonal reproduction (20% of plants were of clonal origin) and very low fruiting success (only 1.6% of plants were fruiting) in comparison with E. atrorubens (25.7%). Gene flow was frequent up to 2 km in C. rubra and up to 125 km in E. atrorubens, and we detected a relatively high dispersal rate among regions in both species.
• Although both species occupy similar habitats and have similar seed dispersal abilities, C. rubra is notably rarer in the study area. Considerably low fruiting success in this species likely limits its gene flow to longer distances and designates it more sensitive to habitat loss and fragmentation.

     

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place‐based approach

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species’ niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species’ niches, resulting in predictions that are generally limited to climate‐occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place‐based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence–absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981–2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local‐scale differences in the realized niche of the American pika. This variation resulted in diverse and – in some cases – highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place‐based approach to species distribution modeling that includes fine‐scale factors when assessing current and future climate impacts on species’ distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.     

Functional connectivity and home range inferred at a microgeographic landscape genetics scale in a desert‐dwelling rodent

Gene flow in animals is limited or facilitated by different features within the landscape matrix they inhabit. The landscape representation in landscape genetics (LG) is traditionally modeled as resistance surfaces (RS), where novel optimization approaches are needed for assigning resistance values that adequately avoid subjectivity. Also, desert ecosystems and mammals are scarcely represented in LG studies. We addressed these issues by evaluating, at a microgeographic scale, the effect of landscape features on functional connectivity of the desert‐dwelling Dipodomys merriami. We characterized genetic diversity and structure with microsatellites loci, estimated home ranges and movement of individuals using telemetry—one of the first with rodents, generated a set of individual and composite environmental surfaces based on hypotheses of variables influencing movement, and assessed how these variables relate to individual‐based gene flow. Genetic diversity and structure results evidenced a family‐induced pattern driven by first‐order‐related individuals, notably determining landscape genetic inferences. The vegetation cover and soil resistance optimized surface (NDVI) were the best‐supported model and a significant predictor of individual genetic distance, followed by humidity and NDVI+humidity. Based on an accurate definition of thematic resolution, we also showed that vegetation is better represented as continuously (vs. categorically) distributed. Hence, with a nonsubjective optimization framework for RS and telemetry, we were able to describe that vegetation cover, soil texture, and climatic variables influence D. merriami's functional connectivity at a microgeographic scale, patterns we could further explain based on the home range, habitat use, and activity observed between sexes. We describe the relationship between environmental features and some aspects of D. merriami‘s behavior and physiology.     

Both landscape and local factors influence plant and hexapod communities of industrial water‐abstraction sites

1. At the landscape level, intensification of agriculture, fragmentation, and destruction of natural habitats are major causes of biodiversity loss that can be mitigated at small spatial scales. However, the complex relationships between human activities, landscapes, and biodiversity are poorly known. Yet, this knowledge could help private stakeholders managing seminatural areas to play a positive role in biodiversity conservation.
2. We investigated how water‐abstraction sites could sustain species diversity in vascular‐plant communities and two taxonomic groups of insect communities in a fragmented agricultural landscape.
3. Landscape‐scale variables (connectivity indices and surrounding levels of herbicide use), as well as site‐specific variables (soil type for vascular plants, floral availability for Rhopalocera, and low herbaceous cover for Orthoptera), were correlated to structural and functional metrics of species community diversity for these taxonomic groups, measured on 35 industrial sites in the Ile‐de‐France region in 2018–2019.
4. Rhopalocera and Orthoptera consisted essentially of species with a high degree of dispersal and low specialization, able to reach the habitat patches of the fragmented landscape of the study area. Sandy soil harbored more diverse vascular‐plant communities. Plant diversity was correlated to a greater abundance of Rhopalocera and a lower richness of Orthoptera.
5. Increasing landscape connectivity was related to higher abundance of plants and Rhopalocera, and a higher evenness index for Orthoptera communities. Higher levels of herbicide use were related to a decrease in the biodiversity of plants and Rhopalocera abundance. High levels of herbicide favored high‐dispersal generalist plants, while high levels of connectivity favored low‐dispersal plants. Specialist Orthoptera species were associated with low herbaceous cover and connectivity.
6. Water‐abstraction sites are valuable seminatural habitats for biodiversity. Changing intensive agricultural practices in surrounding areas would better contribute to conserving and restoring biodiversity on these sites.

     

Dealing with uncertainty in landscape genetic resistance models: a case of three co‐occurring marsupials

Landscape genetics lacks explicit methods for dealing with the uncertainty in landscape resistance estimation, which is particularly problematic when sample sizes of individuals are small. Unless uncertainty can be quantified, valuable but small data sets may be rendered unusable for conservation purposes. We offer a method to quantify uncertainty in landscape resistance estimates using multimodel inference as an improvement over single model‐based inference. We illustrate the approach empirically using co‐occurring, woodland‐preferring Australian marsupials within a common study area: two arboreal gliders (Petaurus breviceps, and Petaurus norfolcensis) and one ground‐dwelling antechinus (Antechinus flavipes). First, we use maximum‐likelihood and a bootstrap procedure to identify the best‐supported isolation‐by‐resistance model out of 56 models defined by linear and non‐linear resistance functions. We then quantify uncertainty in resistance estimates by examining parameter selection probabilities from the bootstrapped data. The selection probabilities provide estimates of uncertainty in the parameters that drive the relationships between landscape features and resistance. We then validate our method for quantifying uncertainty using simulated genetic and landscape data showing that for most parameter combinations it provides sensible estimates of uncertainty. We conclude that small data sets can be informative in landscape genetic analyses provided uncertainty can be explicitly quantified. Being explicit about uncertainty in landscape genetic models will make results more interpretable and useful for conservation decision‐making, where dealing with uncertainty is critical.     

Landscape‐scale deforestation decreases gene flow distance of a keystone tropical palm,Euterpe edulis Mart (Arecaceae)

Habitat loss represents one of the main threats to tropical forests, which have reached extremely high rates of species extinction. Forest loss negatively impacts biodiversity, affecting ecological (e.g., seed dispersal) and genetic (e.g., genetic diversity and structure) processes. Therefore, understanding how deforestation influences genetic resources is strategic for conservation. Our aim was to empirically evaluate the effects of landscape‐scale forest reduction on the spatial genetic structure and gene flow of Euterpe edulis Mart (Arecaceae), a palm tree considered a keystone resource for many vertebrate species. This study was carried out in nine forest remnants in the Atlantic Forest, northeastern Brazil, located in landscapes within a gradient of forest cover (19–83%). We collected leaves of 246 adults and 271 seedlings and performed genotyping using microsatellite markers. Our results showed that the palm populations had low spatial genetic structure, indicating that forest reduction did not influence this genetic parameter for neither seedlings nor adults. However, forest loss decreased the gene flow distance, which may negatively affect the genetic diversity of future generations by increasing the risk of local extinction of this keystone palm. For efficient strategies of genetic variability conservation and maintenance of gene flow in E. edulis, we recommend the maintenance of landscapes with intermediary to high levels of forest cover, that is, forest cover above 40%.     

Interspecific interactions influence contrasting spatial genetic structures in two closely related damselfly species

Spatial genetic structure (SGS) is largely determined by colonization history, landscape and ecological characteristics of the species. Therefore, sympatric and ecologically similar species are expected to exhibit similar SGSs, potentially enabling prediction of the SGS of one species from that of another. On the other hand, due to interspecific interactions, ecologically similar species could have different SGSs. We explored the SGSs of the closely related Calopteryx splendens and Calopteryx virgo within Finland and related the genetic patterns to characteristics of the sampling localities. We observed different SGSs for the two species. Genetic differentiation even within short distances in C. splendens suggests genetic drift as an important driver. However, we also observed indication of previous gene flow (revealed by a negative relationship between genetic differentiation and increasing potential connectivity of the landscape). Interestingly, genetic diversity of C. splendens was negatively related to density of C. virgo, suggesting that interspecific interactions influence the SGS of C. splendens. In contrast, genetic differentiation between C. virgo subpopulations was low and only exhibited relationships with latitude, pointing to high gene flow, colonization history and range margin effects as the drivers of SGS. The different SGSs of the two ecologically similar species caution indirect inferences of SGS based on ecologically similar surrogate species.