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.     

Comparative landscape genetics reveals the evolution of viviparity reduces genetic connectivity in fire salamanders

Evolutionary changes in reproductive mode may affect co‐evolving traits, such as dispersal, although this subject remains largely underexplored. The shift from aquatic oviparous or larviparous reproduction to terrestrial viviparous reproduction in some amphibians entails skipping the aquatic larval stage and, thus, greater independence from water. Accordingly, amphibians exhibiting terrestrial viviparous reproduction may potentially disperse across a wider variety of suboptimal habitats and increase population connectivity in fragmented landscapes compared to aquatic‐breeding species. We investigated this hypothesis in the fire salamander (Salamandra salamandra), which exhibits both aquatic‐ (larviparity) and terrestrial‐breeding (viviparity) strategies. We genotyped 426 larviparous and 360 viviparous adult salamanders for 13 microsatellite loci and sequenced a mitochondrial marker for 133 larviparous and 119 viviparous individuals to compare population connectivity and landscape resistance to gene flow within a landscape genetics framework. Contrary to our predictions, viviparous populations exhibited greater differentiation and reduced genetic connectivity compared to larviparous populations. Landscape genetic analyses indicate viviparity may be partially responsible for this pattern, as water courses comprised a significant barrier only in viviparous salamanders, probably due to their fully terrestrial life cycle. Agricultural areas and, to a lesser extent, topography also decreased genetic connectivity in both larviparous and viviparous populations. This study is one of very few to explicitly demonstrate the evolution of a derived reproductive mode affects patterns of genetic connectivity. Our findings open avenues for future research to better understand the eco‐evolutionary implications underlying the emergence of terrestrial reproduction in amphibians.     

Landscape genetics of alpine Sierra Nevada salamanders reveal extreme population subdivision in space and time

Quantifying the influence of the landscape on the genetic structure of natural populations remains an important empirical challenge, particularly for poorly studied, ecologically cryptic species. We conducted an extensive microsatellite analysis to examine the population genetics of the southern long‐toed salamander (Ambystoma macrodactylum sigillatum) in a naturally complex landscape. Using spatially explicit modelling, we investigated the influence of the Sierra Nevada topography on potential dispersal corridors between sampled populations. Our results indicate very high‐genetic divergence among populations, high within‐deme relatedness, and little evidence of recent migration or population admixture. We also discovered unexpectedly high between‐year genetic differentiation (F_ST) for breeding sites, suggesting that breeding groups vary over localized space and time. While environmental factors associated with high‐elevation montane habitats apparently play an important role in shaping population differentiation, additional, species‐specific biological processes must also be operating to account for observed deviations from temporal, among‐year panmixia. Our study emphasizes the population‐level insights that can be gained from high‐density sampling in space and time, and the highly substructured population biology that may characterize amphibians in extreme montane habitats.     

Genetic structure of native ant supercolonies varies in space and time

Ant supercolonies are the largest cooperative units known in nature. They consist of networks of interconnected nests with hundreds of reproductive queens, where individuals move freely between nests, cooperate across nest boundaries and show little aggression towards non‐nestmates. The combination of high queen numbers and free mixing of workers, queens and brood between nests results in extremely low nestmate relatedness. In such low‐relatedness societies, cooperative worker behaviour appears maladaptive because it may aid random individuals instead of relatives. Here, we provide a comprehensive picture of genetic substructure in supercolonies of the native wood ant Formica aquilonia using traditional population genetic as well as network analysis methods. Specifically, we test for spatial and temporal variation in genetic structure of different classes of individuals within supercolonies and analyse the role of worker movement in determining supercolony genetic networks. We find that relatedness within supercolonies is low but positive when viewed on a population level, which may be due to limited dispersal of individuals and/or ecological factors such as nest site limitation and competition against conspecifics. Genetic structure of supercolonies varied with both sample class and sampling time point, which indicates that mobility of individuals varies according to both caste and season and suggests that generalizing has to be carried out with caution in studies of supercolonial species. Overall, our analysis provides novel evidence that native wood ant supercolonies exhibit fine‐scale genetic substructure, which may explain the maintenance of cooperation in these low‐relatedness societies.     

The advantages of going large: genome‐wide SNPs clarify the complex population history and systematics of the threatened western pond turtle

As the field of phylogeography has matured, it has become clear that analyses of one or a few genes may reveal more about the history of those genes than the populations and species that are the targets of study. To alleviate these concerns, the discipline has moved towards larger analyses of more individuals and more genes, although little attention has been paid to the qualitative or quantitative gains that such increases in scale and scope may yield. Here, we increase the number of individuals and markers by an order of magnitude over previously published work to comprehensively assess the phylogeographical history of a well‐studied declining species, the western pond turtle (Emys marmorata). We present a new analysis of 89 independent nuclear SNP markers and one mitochondrial gene sequence scored for rangewide sampling of >900 individuals, and compare these to smaller‐scale, rangewide genetic and morphological analyses. Our enlarged SNP data fundamentally revise our understanding of evolutionary history for this lineage. Our results indicate that the gains from greatly increasing both the number of markers and individuals are substantial and worth the effort, particularly for species of high conservation concern such as the pond turtle, where accurate assessments of population history are a prerequisite for effective management.     

Estimating the inbreeding level and genetic relatedness in an isolated population of critically endangered Sichuan taimen (Hucho Bleekeri) using genome‐wide SNP markers

Sichuan taimen (Hucho bleekeri) is critically endangered fish listed in The Red List of Threatened Species compiled by the International Union for Conservation of Nature (IUCN). Specific locus amplified fragment sequencing (SLAF‐seq)‐based genotyping was performed for Sichuan taimen with 43 yearling individuals from three locations in Taibai River (a tributary of Yangtze River) that has been sequestered from its access to the ocean for more than 30 years since late 1980s. Applying the inbreeding level and genetic relatedness estimation using 15,396 genome‐wide SNP markers, we found that the inbreeding level of this whole isolated population was at a low level (2.6 × 10^?3 ± 0.079), and the means of coancestry coefficients within and between the three sampling locations were all very low (close to 0), too. Genomic differentiation was negatively correlated with the geographical distances between the sampling locations (p < .001), and the 43 individuals could be considered as genetically independent two groups. The low levels of genomic inbreeding and relatedness indicated a relatively large number of sexually mature individuals were involved in reproduction in Taibai River. This study suggested a genomic‐relatedness‐guided breeding and conservation strategy for wild fish species without pedigree information records.     

Optimizing the trade‐off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual‐based sampling scheme

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, that is, the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population‐based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic data sets to investigate the efficiency of an individual‐based sampling scheme (ISS) in detecting isolation‐by‐distance and isolation‐by‐barrier patterns. Provided that pseudo‐replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of interindividual measures of genotypic dissimilarity may efficiently replace interpopulation measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.     

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

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

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.     

How many came home? Evaluating ex situ conservation of green turtles in the Cayman Islands

Ex situ management is an important conservation tool that allows the preservation of biological diversity outside natural habitats while supporting survival in the wild. Captive breeding followed by re‐introduction is a possible approach for endangered species conservation and preservation of genetic variability. The Cayman Turtle Centre Ltd was established in 1968 to market green turtle (Chelonia mydas) meat and other products and replenish wild populations, thought to be locally extirpated, through captive breeding. We evaluated the effects of this re‐introduction programmme using molecular markers (13 microsatellites, 800‐bp D‐loop and simple tandem repeat mitochondrial DNA sequences) from captive breeders (N = 257) and wild nesting females (N = 57) (sampling period: 2013–2015). We divided the captive breeders into three groups: founders (from the original stock), and then two subdivisions of F₁ individuals corresponding to two different management strategies, cohort 1995 (“C1995”) and multicohort F₁ (“MCF1”). Loss of genetic variability and increased relatedness was observed in the captive stock over time. We found no significant differences in diversity among captive and wild groups, and similar or higher levels of haplotype variability when compared to other natural populations. Using parentage and sibship assignment, we determined that 90% of the wild individuals were related to the captive stock. Our results suggest a strong impact of the re‐introduction programmme on the present recovery of the wild green turtle population nesting in the Cayman Islands. Moreover, genetic relatedness analyses of captive populations are necessary to improve future management actions to maintain genetic diversity in the long term and avoid inbreeding depression.     

Why sampling scheme matters: the effect of sampling scheme on landscape genetic results

There has been a recent trend in genetic studies of wild populations where researchers have changed their sampling schemes from sampling pre-defined populations to sampling individuals uniformly across landscapes. This reflects the fact that many species under study are continuously distributed rather than clumped into obvious “populations”. Once individual samples are collected, many landscape genetic studies use clustering algorithms and multilocus genetic data to group samples into subpopulations. After clusters are derived, landscape features that may be acting as barriers are examined and described. In theory, if populations were evenly sampled, this course of action should reliably identify population structure. However, genetic gradients and irregularly collected samples may impact the composition and location of clusters. We built genetic models where individual genotypes were either randomly distributed across a landscape or contained gradients created by neighbor mating for multiple generations. We investigated the influence of six different sampling protocols on population clustering using program STRUCTURE, the most commonly used model-based clustering method for multilocus genotype data. For models where individuals (and their alleles) were randomly distributed across a landscape, STRUCTURE correctly predicted that only one population was being sampled. However, when gradients created by neighbor mating existed, STRUCTURE detected multiple, but different numbers of clusters, depending on sampling protocols. We recommend testing for fine scale autocorrelation patterns prior to sample clustering, as the scale of the autocorrelation appears to influence the results. Further, we recommend that researchers pay attention to the impacts that sampling may have on subsequent population and landscape genetic results. The U.S. Government's right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.     

Population structure of Columbia spotted frogs (Rana luteiventris) is strongly affected by the landscape

Landscape features such as mountains, rivers, and ecological gradients may strongly affect patterns of dispersal and gene flow among populations and thereby shape population dynamics and evolutionary trajectories. The landscape may have a particularly strong effect on patterns of dispersal and gene flow in amphibians because amphibians are thought to have poor dispersal abilities. We examined genetic variation at six microsatellite loci in Columbia spotted frogs (Rana luteiventris) from 28 breeding ponds in western Montana and Idaho, USA, in order to investigate the effects of landscape structure on patterns of gene flow. We were particularly interested in addressing three questions: (i) do ridges act as barriers to gene flow? (ii) is gene flow restricted between low and high elevation ponds? (iii) does a pond equal a ‘randomly mating population’ (a deme)? We found that mountain ridges and elevational differences were associated with increased genetic differentiation among sites, suggesting that gene flow is restricted by ridges and elevation in this species. We also found that populations of Columbia spotted frogs generally include more than a single pond except for very isolated ponds. There was also evidence for surprisingly high levels of gene flow among low elevation sites separated by large distances. Moreover, genetic variation within populations was strongly negatively correlated with elevation, suggesting effective population sizes are much smaller at high elevation than at low elevation. Our results show that landscape features have a profound effect on patterns of genetic variation in Columbia spotted frogs.     

Comparing RADseq and microsatellites for estimating genetic diversity and relatedness — Implications for brown trout conservation

The conservation and management of endangered species requires information on their genetic diversity, relatedness and population structure. The main genetic markers applied for these questions are microsatellites and single nucleotide polymorphisms (SNPs), the latter of which remain the more resource demanding approach in most cases. Here, we compare the performance of two approaches, SNPs obtained by restriction‐site‐associated DNA sequencing (RADseq) and 16 DNA microsatellite loci, for estimating genetic diversity, relatedness and genetic differentiation of three, small, geographically close wild brown trout (Salmo trutta) populations and a regionally used hatchery strain. The genetic differentiation, quantified as F_ST, was similar when measured using 16 microsatellites and 4,876 SNPs. Based on both marker types, each brown trout population represented a distinct gene pool with a low level of interbreeding. Analysis of SNPs identified half‐ and full‐siblings with a higher probability than the analysis based on microsatellites, and SNPs outperformed microsatellites in estimating individual‐level multilocus heterozygosity. Overall, the results indicated that moderately polymorphic microsatellites and SNPs from RADseq agreed on estimates of population genetic structure in moderately diverged, small populations, but RADseq outperformed microsatellites for applications that required individual‐level genotype information, such as quantifying relatedness and individual‐level heterozygosity. The results can be applied to other small populations with low or moderate levels of genetic diversity.     

Genetic distinction between contiguous urban and rural multimammate mice in Tanzania despite gene flow

Special conditions are required for genetic differentiation to arise at a local geographical scale in the face of gene flow. The Natal multimammate mouse, Mastomys natalensis, is the most widely distributed and abundant rodent in sub‐Saharan Africa. A notorious agricultural pest and a natural host for many zoonotic diseases, it can live in close proximity to humans and appears to compete with other rodents for the synanthropic niche. We surveyed its population genetic structure across a 180‐km transect in central Tanzania along which the landscape varied between agricultural land in a rural setting and natural woody vegetation, rivers, roads and a city (Morogoro). We sampled M. natalensis across 10 localities and genotyped 15 microsatellite loci from 515 individuals. Hierarchical STRUCTURE analyses show a K‐invariant pattern distinguishing Morogoro suburbs (located in the centre of the transect) from nine surrounding rural localities. Landscape connectivity analyses in Circuitscape and comparison of rainfall patterns suggest that neither geographical isolation nor natural breeding asynchrony could explain the genetic differentiation of the urban population. Using the isolation‐with‐migration model implemented in IMa2, we inferred that a split between suburban and rural populations would have occurred recently (<150 years ago) with higher urban effective population density consistent with an urban source to rural sink of effective migration. The observed genetic differentiation of urban multimammate mice is striking given the uninterrupted distribution of the animal throughout the landscape and the high estimates of effective migration (2N_eM = 3.0 and 29.7), suggesting a strong selection gradient across the urban boundary.     

Landscape context influences the abundance of amphibians and the strength of their food web interactions in small ponds

Many species, including most amphibians, undergo an ontogenetic niche shift (ONS) from an aquatic larval stage to a terrestrial adult stage. We use the ratio of aquatic to terrestrial habitat in a landscape as a tool to understand the influence of landscape context on the population growth of ONS species. The aquatic to terrestrial ratio (ATR) of habitats can be viewed as an analog to the influence of resource ratios on the population growth of consumers and depends on the degree to which each habitat type limits the growth of a given population. Population growth rates of shorter‐lived species tend to be more limited by demographic rates in early (aquatic) life stages. As a result, increasing the ATR should lead to a higher total population size in the landscape (and higher densities in the terrestrial habitat), but have little influence on the density of individuals in any given aquatic habitat. Alternatively, population growth rates of longer‐lived species tend to be more limited by demographic rates in later (terrestrial) life stages and increasing the ATR should have little influence on the total population size in the landscape, but decrease the density of individuals in any given aquatic habitat. We show that among‐landscape variation in the breeding‐pond densities of three widespread amphibians with contrasting life histories is consistent with this framework. Within‐pond densities of Pseudacris crucifer, a species with short‐lived adults, were not influenced by ATR, whereas within‐pond densities of Hyla versicolor, a longer‐lived member of the same family (Hylidae), declined as ATR increased. Ambystoma maculatum, a long‐lived salamander, also had lower densities in ponds with higher ATR. Because A. maculatum larvae are important predators in ponds, we use structural equation modeling to show that landscape context (ATR) can moderate community structure via direct (amphibian abundances) and indirect (prey species richness) effects.     

swinger: a user‐friendly computer program to establish captive breeding groups that minimize relatedness without pedigree information

Captive breeding programmes are often a necessity for the continued persistence of a population or species. They typically have the goal of maintaining genetic diversity and minimizing inbreeding. However, most captive breeding programmes have been based on the assumption that the founding breeders are unrelated and outbred, even though in situ anthropogenic impacts often mean these founders may have high relatedness and substantial inbreeding. In addition, polygamous group‐breeding species in captivity often have uncertain pedigrees, making it difficult to select the group composition for subsequent breeding. Molecular‐based estimates of relatedness and inbreeding may instead be used to select breeding groups (≥two individuals) that minimize relatedness and filter out inbred individuals. swinger constructs breeding groups based on molecular estimates of relatedness and inbreeding. The number of possible combinations of breeding groups quickly becomes intractable by hand. swinger was designed to overcome this major issue in ex situ conservation biology. The user can specify parameters within swinger to reach breeding solutions that suit the mating system of the target species and available resources. We provide evidence of the efficiency of the software with an empirical example and using simulations. The only data required are a typical molecular marker data set, such as a microsatellite or SNP data set, from which estimates of inbreeding and pairwise relatedness may be obtained. Such molecular data sets are becoming easier to gather from non‐model organisms with next‐generation sequencing technology. swinger is an open‐source software with a user‐friendly interface and is available at http://www.molecularecology.flinders.edu.au/molecular-ecology-lab/software/swinger/swinger/ and https://github.com/Yuma248/Swinger .     

Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change

Landscape genetics seeks to determine the effect of landscape features on gene flow and genetic structure. Often, such analyses are intended to inform conservation and management. However, depending on the many factors that influence the time to reach equilibrium, genetic structure may more strongly represent past rather than contemporary landscapes. This well‐known lag between current demographic processes and population genetic structure often makes it challenging to interpret how contemporary landscapes and anthropogenic activity shape gene flow. Here, we review the theoretical framework for factors that influence time lags, summarize approaches to address this temporal disconnect in landscape genetic studies, and evaluate ways to make inferences about landscape change and its effects on species using genetic data alone or in combination with other data. Those approaches include comparing correlation of genetic structure with historical versus contemporary landscapes, using molecular markers with different rates of evolution, contrasting metrics of genetic structure and gene flow that reflect population genetic processes operating at different temporal scales, comparing historical and contemporary samples, combining genetic data with contemporary estimates of species distribution or movement, and controlling for phylogeographic history. We recommend using simulated data sets to explore time lags in genetic structure, and argue that time lags should be explicitly considered both when designing and interpreting landscape genetic studies. We conclude that the time lag problem can be exploited to strengthen inferences about recent landscape changes and to establish conservation baselines, particularly when genetic data are combined with other data.     

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.     

Pedigree analysis for the genetic management of group‐living species

Captive breeding programs are an important tool for the conservation of endangered species. These programs are commonly managed using pedigrees containing information about the history of each individual's family, such as breeding pairs and parentage. However, there are some species that are kept in groups where it is hard to distinguish between particular individuals within the group, making it very difficult to record any information at an individual level. Currently, software and methods commonly used for registering and analyzing pedigrees to help manage populations at an individual level are not adequate for managing these group‐living species. Therefore, there is a need to further develop these tools and methodologies for pedigree analysis to better manage group‐living species. PMx is a program used for the management of ex situ populations in zoos and aquariums. We adapted the pedigree analysis method implemented in PMx to analyze pedigrees (records of descendant lineages) of group‐living species. In addition, we developed a group pedigree data entry sheet and group2PMx, a converter program that enables group datasets to be imported into PMx. We show how pedigree analysis of a group‐living species can be used for population management using the studbook of the endangered Texas blind cave salamander Eurycea rathbuni. Such analyses of the pedigree of groups can improve the management of group‐living species in ex situ breeding programs. Firstly, it enables better management decisions based on more accurate genetic measures between groups, allowing for greater control of inbreeding. Secondly, it can improve the conditions in which group‐living species are held by adapting husbandry practices to better reflect conditions of these species living in the wild. The use of the spreadsheet and group2PMx extends the application of PMx_, allowing conservation managers and other institutions outside the zoo and aquarium community to easily import and analyze their pedigree data.     

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.