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Environmental DNA (eDNA) is being rapidly adopted as a tool to detect rare animals. Quantitative PCR (qPCR) using probe-based chemistries may represent a particularly powerful tool because of the method’s sensitivity, specificity, and potential to quantify target DNA. However, there has been little work understanding the performance of these assays in the presence of closely related, sympatric taxa. If related species cause any cross-amplification or interference, false positives and negatives may be generated. These errors can be disastrous if false positives lead to overestimate the abundance of an endangered species or if false negatives prevent detection of an invasive species. In this study we test factors that influence the specificity and sensitivity of TaqMan MGB assays using co-occurring, closely related brook trout (Salvelinus fontinalis) and bull trout (S. confluentus) as a case study. We found qPCR to be substantially more sensitive than traditional PCR, with a high probability of detection at concentrations as low as 0.5 target copies/µl. We also found that number and placement of base pair mismatches between the Taqman MGB assay and non-target templates was important to target specificity, and that specificity was most influenced by base pair mismatches in the primers, rather than in the probe. We found that insufficient specificity can result in both false positive and false negative results, particularly in the presence of abundant related species. Our results highlight the utility of qPCR as a highly sensitive eDNA tool, and underscore the importance of careful assay design.

The availability of spatially referenced environmental data and species occurrence records in online databases enable practitioners to easily generate species distribution models (SDMs) for a broad array of taxa. Such databases often include occurrence records of unknown reliability, yet little information is available on the influence of data quality on SDMs generated for rare, elusive, and cryptic species that are prone to misidentification in the field. We investigated this question for the fisher (Pekania pennanti), a forest carnivore of conservation concern in the Pacific States that is often confused with the more common Pacific marten (Martes caurina). Fisher occurrence records supported by physical evidence (verifiable records) were available from a limited area, whereas occurrence records of unknown quality (unscreened records) were available from throughout the fisher's historical range. We reserved 20% of the verifiable records to use as a test sample for both models and generated SDMs with each dataset using Maxent. The verifiable model performed substantially better than the unscreened model based on multiple metrics including AUCtest values (0.78 and 0.62, respectively), evaluation of training and test gains, and statistical tests of how well each model predicted test localities. In addition, the verifiable model was consistent with our knowledge of the fisher's habitat relations and potential distribution, whereas the unscreened model indicated a much broader area of high-quality habitat (indices > 0.5) that included large expanses of high-elevation habitat that fishers do not occupy. Because Pacific martens remain relatively common in upper elevation habitats in the Cascade Range and Sierra Nevada, the SDM based on unscreened records likely reflects primarily a conflation of marten and fisher habitat. Consequently, accurate identifications are far more important than the spatial extent of occurrence records for generating reliable SDMs for the fisher in this region. We strongly recommend that practitioners avoid using anecdotal occurrence records to build SDMs but, if such data are used, the validity of resulting models should be tested with verifiable occurrence records.

Environmental DNA (eDNA) sampling is a powerful tool for detecting invasive and native aquatic species. Often, species of conservation interest co-occur with other, closely related taxa. Here, we developed qPCR (quantitative PCR) markers which distinguish westslope cutthroat trout (Oncorhynchus clarkii lewsi), Yellowstone cutthroat trout (O. clarkii bouvieri), and rainbow trout (O. mykiss), which are of conservation interest both as native species and as invasive species across each other's native ranges. We found that local polymorphisms within westslope cutthroat trout and rainbow trout posed a challenge to designing assays that are generally applicable across the range of these widely-distributed species. Further, poorly-resolved taxonomies of Yellowstone cutthroat trout and Bonneville cutthroat trout (O. c. utah) prevented design of an assay that distinguishes these recognized taxa. The issues of intraspecific polymorphism and unresolved taxonomy for eDNA assay design addressed in this study are likely to be general problems for closely-related taxa. Prior to field application, we recommend that future studies sample populations and test assays more broadly than has been typical of published eDNA assays to date.

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 majority of environmental DNA (eDNA) assays for vertebrate species are based on commonly analyzed regions of the mitochondrial genome. However, the high degree of mitochondrial similarity between two species of charr (Salvelinus spp.), southern Dolly Varden (S. malma lordii) and bull trout (Salvelinus confluentus), precludes the development of a mitochondrial eDNA assay to distinguish them. Presented here is an eDNA assay to detect bull trout based on the first ribosomal internal transcribed spacer (ITSI), a nuclear marker. This assay successfully detects bull trout and avoids detecting Dolly Varden as well as brook trout (S. fontinalis), Arctic char (S. alpinus), and lake trout (S. namaycush). In addition, this assay was compared with an extensively used mitochondrial bull trout assay and it was found that the ITSI-based assay produced higher detectability. Our results suggest this assay should out-perform the published mtDNA assay across the range of bull trout, while the added specificity allows reliable bull trout detection in areas where bull trout co-occur with other charr such as Dolly Varden. While clearly a superior assay in this instance, basing assays on ITSI is not without problems. For vertebrates, there are fewer ITSI sequences available than commonly sequenced regions of the mitochondrial genome. Thus, the initial in silico screening of candidate assays must be preceded by much more extensive sampling and sequencing of sympatric or closely related taxa. Further, all copies of the internal transcribed spacers within an individual may not be identical, which can lead to complications. Lastly, the copy number for ITSI varies widely across taxa; the greater detectability associated with this assay cannot be assumed for other species.

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities. Los biólogos de la conservación reconocen que un sistema de áreas protegidas aisladas será necesario pero insuficiente para alcanzar los objetivos de la biodiversidad. Las estrategias actuales para conectar las áreas núcleos de conservación por medio de corredores consideran la ubicación óptima de estos con base en un solo objetivo de optimización: maximizar, comúnmente, el movimiento de una especie blanco a lo largo de una red de áreas protegidas. Mostramos que diseñar los corredores para una especie única con base solamente en un criterio ecológico lleva a enlazamientos extremadamente caros que son sub-óptimos para los objetivos de conectividad de especies múltiples. De manera similar, adquirir los enlazamientos menos caros lleva a soluciones ecológicamente pobres. Desarrollamos algoritmos para optimizarlos corredores para el uso de especies múltiples dado un presupuesto específico. Aplicamos nuestra estrategia en el oeste de Montana para demostrar cómo las soluciones pueden utilizarse para evaluar las compensaciones en la conectividad de dos especies con requerimientos de habitat diferentes, áreas nucleares diferentes y valores de conservación diferentes bajo presupuestos diferentes. Evaluamos los corredores que fueron óptimos para cada especie individualmente y para ambas especies en conjunto. Incorporar una restricción de presupuesto y optimizar en conjunto para ambas especies resultó en corredores que estuvieron próximos al potencial óptimo de movimiento de las especies individuales pero con ahorros sustanciales de gastos. Nuestra estrategia produjo corredores que estuvieron dentro del 14 % y el 11 % de la mejor conectividad posible entre corredores para los osos pardos (Ursus arctos) y los glotones (Gulo gulo), respectivamente, y ahorro el 75 % del costo. De igual manera, la optimización conjunta bajo un presupuesto combinado resultó en una conectividad mejorada para ambas especies en relación a la división del presupuesto en dos para optimizar para cada especie individualmente. Nuestros resultados demuestran la economía de escala y las complementariedades que los planeadores de la conservación pueden obtener al optimizar los diseños del corredor para financiar los costos y para los objetivos de conectividad de especies múltiples en conjunto. Creemos que nuestra estrategia puede facilitar la conservación de corredores al reducir los costos de adquisición y al permitir que los corredores derivados reflejen más cercanamente las prioridades de conservación.

Predicting population-level effects of landscape change depends on identifying factors that influence population connectivity in complex landscapes. However, most putative movement corridors and barriers have not been based on empirical data. In this study, we identify factors that influence connectivity by comparing patterns of genetic similarity among 146 black bears (Ursus americanus), sampled across a 3,000-km2 study area in northern Idaho, with 110 landscape-resistance hypotheses. Genetic similarities were based on the pairwise percentage dissimilarity among all individuals based on nine microsatellite loci (average expected heterozygosity = 0.79). Landscape-resistance hypotheses describe a range of potential relationships between movement cost and land cover, slope, elevation, roads, Euclidean distance, and a putative movement barrier. These hypotheses were divided into seven organizational models in which the influences of barriers, distance, and landscape features were statistically separated using partial Mantel tests. Only one of the competing organizational models was fully supported: patterns of genetic structure are primarily related to landscape gradients of land cover and elevation. The alternative landscape models, isolation by barriers and isolation by distance, are not supported. In this black bear population, gene flow is facilitated by contiguous forest cover at middle elevations.

The ability of populations to be connected across large landscapes via dispersal is critical to long-term viability for many species. One means to mitigate population isolation is the protection of movement corridors among habitat patches. Nevertheless, the utility of small, narrow, linear features as habitat corridors has been hotly debated. Here, we argue that analysis of movement across continuously resistant landscapes allows a shift to a broader consideration of how landscape patterns influence connectivity at scales relevant to conservation. We further argue that this change in scale and definition of the connectivity problem improves one's ability to find solutions and may help resolve long-standing disputes regarding scale and definition of movement corridors and their importance to population connectivity. We used a new method that combines empirically derived landscape-resistance maps and least-cost path analysis between multiple source and destination locations to assess habitat isolation and identify corridors and barriers to organism movement. Specifically, we used a genetically based landscape resistance model for American black bears ( Ursus americanus) to identify major movement corridors and barriers to population connectivity between Yellowstone National Park and the Canadian border. Even though western Montana and northern Idaho contain abundant public lands and the largest wilderness areas in the contiguous United States, moving from the Canadian border to Yellowstone Park along those paths indicated by modeled gene flow required bears to cross at least 6 potential barriers. Our methods are generic and can be applied to virtually any species for which reliable maps of landscape resistance can be developed.

Wolverines (Gulo gulo) are one of the rarest carnivores in the contiguous United States. Effective population sizes in Montana, Idaho, and Wyoming, where most of the wolverines in the contiguous United States exist, were calculated to be 35 (credible limits, 28-52) suggesting low abundance. Landscape features that influence wolverine population substructure and gene flow are largely unknown. Recent work has identified strong associations between areas with persistent spring snow and wolverine presence and range. We tested whether a dispersal model in which wolverines prefer to disperse through areas characterized by persistent spring snow cover produced least-cost paths among all individuals that correlated with genetic distance among individuals. Models simulating large preferences for dispersing within areas characterized by persistent spring snow explained the data better than a model based on Euclidean distance. Partial Mantel tests separating Euclidean distance from spring snow-cover-based effects indicated that Euclidean distance was not significant in describing patterns of genetic distance. Because these models indicated that successful dispersal paths followed areas characterized by spring snow cover, we used these understandings to derive empirically based least-cost corridor maps in the U.S. Rocky Mountains. These corridor maps largely explain previously published population subdivision patterns based on mitochondrial DNA and indicate that natural colonization of the southern Rocky Mountains by wolverines will be difficult but not impossible.

Anecdotal occurrence data (unverifiable observations of organisms or their sign) and inconclusive physical data are often used to assess the current and historical ranges of rare or elusive species. However, the use of such data for species conservation can lead to large errors of omission and commission, which can influence the allocation of limited funds and the efficacy of subsequent conservation efforts. We present three examples of biological misunderstandings, all of them with significant conservation implications, that resulted from the acceptance of anecdotal observations as empirical evidence. To avoid such errors, we recommend that a priori standards constrain the acceptance of occurrence data, with more stringent standards applied to the data for rare species. Because data standards are likely to be taxon specific, professional societies should develop specific evidentiary standards to use when assessing occurrence data for their taxa of interest.