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.     

Quantification and reduction of bias from sampling larvae to infer population and landscape genetic structure

A well-designed sampling scheme is critical for obtaining accurate results from population genetic studies. Larval samples contain only the genetic material of successful breeders, often of a single year, and may be biased towards particular families. To quantify the bias of using larval samples to infer population and landscape genetic structure and explore how this bias may be reduced using sibship analysis, we analysed eight microsatellite loci from 484 tissue samples of larvae and adults of Columbia spotted frogs (Rana luteiventris) and long-toed salamanders (Ambystoma macrodactylum) at nine breeding sites in north Idaho. Differences in allele frequencies between adult and larval samples were not detected after full-siblings were removed from the larval data set for Columbia spotted frogs; for long-toed salamanders, these differences remained at two out of four ponds. Data from Columbia spotted frog larvae indicated higher levels of differentiation among populations (median difference in F_ST = 0.020, P < 0.01), as predicted by population genetic theory, whereas data from larval samples of long-toed salamanders showed some evidence of lower levels of differentiation among populations (median difference in F_ST = 0.012, P = 0.06). For both species, removing all but one individual from each full-sibling family led to parameter estimates that were closer to those calculated from adult samples for both population and landscape genetic measures. Removal of full-siblings is likely to improve estimates of population genetic parameters; however, knowledge of the species’ breeding system is essential for understanding additional sources of bias when inferring population genetic structure from larval samples.     

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.     

The impact of anchored phylogenomics and taxon sampling on phylogenetic inference in narrow‐mouthed frogs (Anura,Microhylidae)

Despite considerable progress in unravelling the phylogenetic relationships of microhylid frogs, relationships among subfamilies remain largely unstable and many genera are not demonstrably monophyletic. Here, we used five alternative combinations of DNA sequence data (ranging from seven loci for 48 taxa to up to 73 loci for as many as 142 taxa) generated using the anchored phylogenomics sequencing method (66 loci, derived from conserved genome regions, for 48 taxa) and Sanger sequencing (seven loci for up to 142 taxa) to tackle this problem. We assess the effects of character sampling, taxon sampling, analytical methods and assumptions in phylogenetic inference of microhylid frogs. The phylogeny of microhylids shows high susceptibility to different analytical methods and datasets used for the analyses. Clades inferred from maximum‐likelihood are generally more stable across datasets than those inferred from parsimony. Parsimony trees inferred within a tree‐alignment framework are generally better resolved and better supported than those inferred within a similarity‐alignment framework, even under the same cost matrix (equally weighted) and same treatment of gaps (as a fifth nucleotide state). We discuss potential causes for these differences in resolution and clade stability among discovery operations. We also highlight the problem that commonly used algorithms for model‐based analyses do not explicitly model insertion and deletion events (i.e. gaps are treated as missing data). Our results corroborate the monophyly of Microhylidae and most currently recognized subfamilies but fail to provide support for relationships among subfamilies. Several taxonomic updates are provided, including naming of two new subfamilies, both monotypic.     

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

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

A note on the accuracy of PAC-likelihood inference with microsatellite data

Stephens and Donnelly have introduced a simple yet powerful importance sampling scheme for computing the likelihood in population genetic models. Fundamental to the method is an approximation to the conditional probability of the allelic type of an additional gene, given those currently in the sample. As noted by Li and Stephens, the product of these conditional probabilities for a sequence of draws that gives the frequency of allelic types in a sample is an approximation to the likelihood, and can be used directly in inference. The aim of this note is to demonstrate the high level of accuracy of "product of approximate conditionals" (PAC) likelihood when used with microsatellite data. Results obtained on simulated microsatellite data show that this strategy leads to a negligible bias over a wide range of the scaled mutation parameter theta. Furthermore, the sampling variance of likelihood estimates as well as the computation time are lower than that obtained with importance sampling on the whole range of theta. It follows that this approach represents an efficient substitute to IS algorithms in computer intensive (e.g. MCMC) inference methods in population genetics.     

Novel relationships among hyloid frogs inferred from 12S and 16S mitochondrial DNA sequences

Advanced frogs (Neobatrachia) are usually divided into two taxa, Ranoidea (the firmisternal frogs) and Hyloidea (all other neobatrachians). We investigated phylogenetic relationships among several groups of Hyloidea using 12S and 16S rRNA mitochondrial gene sequences and tested explicit relationships of certain problematic hyloid taxa using a sample of 93 neobatrachians. Parsimony, maximum likelihood, and Bayesian inference methods suggest that both the Ranoidea and Hyloidea are well-supported monophyletic groups. We reject three hypotheses using parametric bootstrap simulation: (1) Dendrobatidae lies within the Ranoidea; (2) The group containing Hylidae, Pseudidae, and Centrolenidae is monophyletic; and (3) Brachycephalus is part of Bufonidae.     

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.     

Identifying Priority Giant Anteater (Myrmecophaga tridactyla) Populations for Conservation in São Paulo State,Brazil

Habitat loss is the main threat to biodiversity conservation worldwide. Some species may be particularly susceptible to the effects of fragmentation and the isolation of populations. The impacts of human activity on wild animal populations may be understood through relationships between individual genetic data and spatial landscape variables, particularly when considering local population dynamics influenced by fragmented habitats. Thus, the objective of this study was to analyze the population structure and genetic diversity of the giant anteater (Myrmecophaga tridactyla) using an individual sampling scheme (ISS) on a regional geographic scale. Data were collected from 41 specimens from twenty different locations in São Paulo State, Brazil, and six polymorphic microsatellite loci were genotyped. Our results indicate that barriers to gene flow exist and have segregated individuals of the farther away areas into two spatially structured clusters. The populations were also found to have high genetic diversity. The experimental sampling approach used herein enabled an analysis of the population dynamics of the giant anteater on a regional scale, as well as the identification of priority populations for genetic resource conservation for this species. The results reflect the need for adequate management plans. The efficacy of the sampling scheme may vary based on the study model used, but we argue that the use of an ISS combined with suitable molecular markers and statistical methods may serve as an important tool for initial analyses of threatened or vulnerable species, particularly in anthropized regions where populations are small or hard to characterize.     

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.     

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.     

Hyperspectral Analysis of Columbia Spotted Frog Habitat

Abstract: Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96% (44 wetlands) correctly classified with the 2002 data and 89% (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74% (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72% (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats.     

Regional variation in drivers of connectivity for two frog species (Rana pretiosa and R. luteiventris) from the U.S. Pacific Northwest

Comparative landscape genetics has uncovered high levels of variability in which landscape factors affect connectivity among species and regions. However, the relative importance of species traits versus environmental variation for predicting landscape patterns of connectivity is unresolved. We provide evidence from a landscape genetics study of two sister taxa of frogs, the Oregon spotted frog (Rana pretiosa) and the Columbia spotted frog (Rana luteiventris) in Oregon and Idaho, USA. Rana pretiosa is relatively more dependent on moisture for dispersal than R. luteiventris, so if species traits influence connectivity, we predicted that connectivity among R. pretiosa populations would be more positively associated with moisture than R. luteiventris. However, if environmental differences are important drivers of gene flow, we predicted that connectivity would be more positively related to moisture in arid regions. We tested these predictions using eight microsatellite loci and gravity models in two R. pretiosa regions and four R. luteiventris regions (n = 1,168 frogs). In R. pretiosa, but not R. luteiventris, connectivity was positively related to mean annual precipitation, supporting our first prediction. In contrast, connectivity was not more positively related to moisture in more arid regions. Various temperature metrics were important predictors for both species and in all regions, but the directionality of their effects varied. Therefore, the pattern of variation in drivers of connectivity was consistent with predictions based on species traits rather than on environmental variation.     

Sampling-through-time in birth-death trees

I consider the constant rate birth-death process with incomplete sampling. I calculate the density of a given tree with sampled extant and extinct individuals.This density is essential for analyzing datasets which are sampled through time. Such datasets are common in virus epidemiology as viruses in infected individuals are sampled through time. Further, such datasets appear in phylogenetics when extant and extinct species data is available.I show how the derived tree density can be used (i) as a tree prior in a Bayesian method to reconstruct the evolutionary past of the sequence data on a calender-timescale, (ii) to infer the birth- and death-rates for a reconstructed evolutionary tree, and (iii) for simulating trees with a given number of sampled extant and extinct individuals which is essential for testing evolutionary hypotheses for the considered datasets.     

Distribution of the disease pathogen Batrachochytrium dendrobatidis in non‐epidemic amphibian communities of western Canada

Chytridiomycosis is an emerging infectious disease of amphibians caused by the waterborne pathogen Batrachochytrium dendrobatidis (Bd) and is responsible for the recent decline of species worldwide. Elucidating patterns in disease prevalence has proved challenging, as small‐scale studies to date have provided conflicting results. We present data on the prevalence of Bd (the proportion of individuals with Bd) collected from amphibians sampled throughout British Columbia. We had two different datasets: our original dataset includes 1129 individuals sampled in 103 sites representing 14 species. A second dataset has 839 individuals sampled in 19 sites representing 10 species. We use a Bayesian state‐space occupancy modelling approach to estimate the probability that an individual is Bd+ as a function of individual and site characteristics. Cross‐validation techniques and the original dataset were used to find the best model: this model includes species, life stage, and geographic location. Our results suggest that Bd prevalence is not strongly related to seasonality, latitude or site type. Within a species, Bd prevalence depended on life stage; the watershed in which a site occurs may also usefully predict prevalence. Overall observed infection prevalence was ～16%. Our best model accurately assigns Bd status to an individual ～ 42% of the time. Taking advantage of the Bayesian framework, we ran an analysis with the second dataset using estimates from the original model as prior values. We present posterior density distributions for those sites and species with narrow credible intervals, and show that sites tend to be either highly likely or highly unlikely to have individuals with Bd, while individuals of some stages of some species have an intermediate likelihood of being Bd‐positive. The Bayesian model using informed priors had increased accuracy rates in assigning Bd status to both individuals and groups of individuals.     

Molecules,morphology and minute hooded beetles: a phylogenetic study with implications for the evolution and classification of Corylophidae (Coleoptera: Cucujoidea)

Eight genes (nuclear: 18S, 28S, H3, CAD; mitochondrial: 12S, 16S, COI, COII) and morphology were used to infer the evolutionary history of Corylophidae, some of the smallest free‐living insects. The study included 36 corylophid exemplars, representing approximately 60% of the known generic diversity of the family and 16 cucujoid outgroup taxa. Multiple partitioning strategies, molecular datasets, combined datasets and different taxon sampling regimes using maximum likelihood and mixed‐model Bayesian inference were utilized to analyse these data. Most results were highly concordant across analyses. There was strong agreement across (i) partitioning strategies, (ii) maximum likelihood and Bayesian inference analyses of the molecular data, and (iii) Bayesian inference of the molecular data alone and Bayesian inference of the combined morphological and molecular data when all terminal taxa were included. When a strict taxon sampling protocol was employed so that only single generic exemplars were included, deep relationships were affected in the resulting phylogenetic hypotheses. Under such narrow sampling strategies, deep phylogenetic relationships were also sensitive to the choice of generic exemplars. Although it is often challenging to obtain single representatives for many taxa in higher‐level phylogenetic analyses, these results indicate the importance of using denser taxon sampling approaches even at the specific level for genera included in such studies. Molecular data alone support Anamorphinae (Endomychidae) strongly as the sister group of Corylophidae. In combined data analyses, Coccinellidae is recovered as the sister group to Corylophidae. In all analyses, Corylophidae and the subfamily Corylophinae are recovered as monophyletic. The monophyly of Periptyctinae was untested, as only a single species was included. All included corylophine tribes were recovered as monophyletic with the exception of Aenigmaticini; Aenigmaticum Matthews forms the sister group to Orthoperus Stephens and Stanus?lipiński et al. is recovered as the sister group of Sericoderus Stephens. Stanus tasmanicus?lipiński et al. is transferred to a new genus, Pseudostanus Robertson, ?lipiński & McHugh gen.n. incertae sedis. We propose a new tribe, Stanini Robertson, ?lipiński & McHugh trib.n. for Stanus bowesteadi?lipiński et al. and a new concept of Aenigmaticini sensu.n. to include only the nominate genus. Anatomical transitions associated with corylophid miniaturization are highlighted. Key phenotypic modifications and elevated rates of substitution in nuclear rRNA genes are evident in a subgroup of Corylophinae that includes the most diminutive species. Other taxonomic and evolutionary implications are discussed in light of the results.     

High dispersal in a frog species suggests that it is vulnerable to habitat fragmentation

Global losses of amphibian populations are a major conservation concern and their causes have generated substantial debate. Habitat fragmentation is considered one important cause of amphibian decline. However, if fragmentation is to be invoked as a mechanism of amphibian decline, it must first be established that dispersal is prevalent among contiguous amphibian populations using formal movement estimators. In contrast, if dispersal is naturally low in amphibians, fragmentation can be disregarded as a cause of amphibian declines and conservation efforts can be focused elsewhere. We examined dispersal rates in Columbia spotted frogs (Rana luteiventris) using capture-recapture analysis of over 10,000 frogs in combination with genetic analysis of microsatellite loci in replicate basins. We found that frogs had exceptionally high juvenile dispersal rates (up to 62% annually) over long distances (>5km), large elevation gains (>750m) and steep inclines (36 degrees incline over 2km) that were corroborated by genetic data showing high gene flow. These findings show that dispersal is an important life-history feature of some amphibians and suggest that habitat fragmentation is a serious threat to amphibian persistence.     

Population genetics suggests effectiveness of habitat connectivity measures for the European tree frog in Switzerland

1.  Governmental authorities in many countries financially support the implementation of habitat connectivity measures to enhance the exchange of individuals among fragmented populations. The evaluation of the effectiveness of such measures is crucial for future management directions and can be accomplished by using genetic methods.
2.  We retraced the population history of the European tree frog in two Swiss river valleys (Reuss and Thur), performed comprehensive population sampling to infer the genetic structure at 11 microsatellite markers, and used first-generation migrant assignment tests to evaluate the contemporary exchange of individuals.
3.  Compared with the Thur valley, the Reuss valley has lost almost double the number of breeding sites and exhibited a more pronounced genetic grouping. However, similar numbers of contemporary migrants were detected in both valleys. In the Reuss valley, 81% of the migration events occurred within the identified genetic groups, whereas in the Thur valley migration patterns were diffuse.
4.  Our results show that the connectivity measures implemented in the Reuss valley facilitated effective tree frog migration among breeding sites within distances up to 4 km. Nevertheless, the Reuss valley exhibited high genetic differentiation, which reflected the impact of barriers to tree frog movement such as the River Reuss. By contrast in the Thur valley, a larger number of breeding sites have been preserved and high admixture indicated exchange of individuals at distances up to 16 km.
5.   Synthesis and applications . We show that genetic methods can substantiate the effectiveness of connectivity measures taken in conservation management at the landscape scale. We urge responsible authorities from both river valleys to continue implementing connectivity measures and to create a dense network of breeding sites, as spatial gaps of 8 km are rarely traversed by tree frogs.     

Persistence at distributional edges: Columbia spotted frog habitat in the arid Great Basin,USA

A common challenge in the conservation of broadly distributed, yet imperiled species is understanding which factors facilitate persistence at distributional edges, locations where populations are often vulnerable to extirpation due to changes in climate, land use, or distributions of other species. For Columbia spotted frogs (Rana luteiventris) in the Great Basin (USA), a genetically distinct population segment of conservation concern, we approached this problem by examining (1) landscape‐scale habitat availability and distribution, (2) water body‐scale habitat associations, and (3) resource management‐identified threats to persistence. We found that areas with perennial aquatic habitat and suitable climate are extremely limited in the southern portion of the species’ range. Within these suitable areas, native and non‐native predators (trout and American bullfrogs [Lithobates catesbeianus]) are widespread and may further limit habitat availability in upper‐ and lower‐elevation areas, respectively. At the water body scale, spotted frog occupancy was associated with deeper sites containing abundant emergent vegetation and nontrout fish species. Streams with American beaver (Castor canadensis) frequently had these structural characteristics and were significantly more likely to be occupied than ponds, lakes, streams without beaver, or streams with inactive beaver ponds, highlighting the importance of active manipulation of stream environments by beaver. Native and non‐native trout reduced the likelihood of spotted frog occupancy, especially where emergent vegetation cover was sparse. Intensive livestock grazing, low aquatic connectivity, and ephemeral hydroperiods were also negatively associated with spotted frog occupancy. We conclude that persistence of this species at the arid end of its range has been largely facilitated by habitat stability (i.e., permanent hydroperiod), connectivity, predator‐free refugia, and a commensalistic interaction with an ecosystem engineer. Beaver‐induced changes to habitat quality, stability, and connectivity may increase spotted frog population resistance and resilience to seasonal drought, grazing, non‐native predators, and climate change, factors which threaten local or regional persistence.     

Bias and conflict in phylogenetic inference of myco-heterotrophic plants: a case study in Thismiaceae

Due to morphological reduction and absence of amplifiable plastid genes, the identification of photosynthetic relatives of heterotrophic plants is problematic. Although nuclear and mitochondrial gene sequences may offer a welcome alternative source of phylogenetic markers, the presence of rate heterogeneity in these genes may introduce bias/systematic error in phylogenetic analyses. We examine the phylogenetic position of Thismiaceae based on nuclear 18S rDNA and mitochondrial atpA DNA sequence data, as well as using parsimony, likelihood and Bayesian inference methods. Significant differences in evolutionary rates of these genes between closely related taxa lead to conflicting results: while parsimony analyses of 18S rDNA and combined data strongly support the monophyly of Thismiaceae, Bayesian inference, with and without a relaxed molecular clock, as well as the Swofford–Olsen–Waddell–Hillis (SOWH) test confidently reject this hypothesis. We show that rate heterogeneity in our data leads to long-branch attraction artifacts in parsimony analysis. However, using model-based inference methods the question of whether Thismiaceae are monophyletic remains elusive. On the one hand maximum likelihood nonparametric bootstrapping and parametric hypothesis tests fail to support a paraphyletic Thismiaceae, on the other hand Bayesian inference methods (both without and with a relaxed clock) significantly reject a monophyletic Thismiaceae. These results show that an adequate sampling, the use of rate homogeneous data, and the application of different inference methods are important factors for developing phylogenetic hypotheses of myco-heterotrophic plants. © The Willi Hennig Society 2009.