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Over the past few decades, the use of camera‐traps has revolutionized our ability to monitor populations of wild terrestrial mammals. While methods to estimate abundance from individually‐identifiable animals are well‐established, they are mostly restricted to species with clear natural markings or else necessitate invasive and often costly animal tagging campaigns. Estimating abundance or density from unmarked animals remains challenging. Several models recently developed to deal with this issue are promising, but are not widely used by field ecologists. Here, we developed a framework for applying the Space‐To‐Event (STE) model—originally designed to be used with time‐lapse images—on motion‐triggered camera‐trap data. Our approach involves performing bootstrap resampling on the photographic dataset to generate multiple datasets that are then used as input to the STE model. We tested our approach on 29 datasets, including 17 ungulate species from eight sites, in six different countries and various ecosystems. Then, we conducted a regression analysis to evaluate how variations in ecological and sampling conditions across studies affected the bias and precision of our STE density estimates. Our study shows that with a bootstrap resampling approach and information on animal activity and effective detection distances to animals, the STE model can be used to analyze motion‐trigger datasets and provide population density estimates that are similar to those from other methods. We found that measuring the camera viewshed was critical to prevent major negative biases in density estimates. Moreover, using a 1‐s sampling window was important to avoid the positive bias that results from violating the instantaneous‐sampling assumption. We found that precision increased with greater sampling effort and higher density populations. Based on these results, we highlight several issues from past studies that have applied the original timelapse‐based STE to motion‐trigger datasets, issues that our bootstrap resampling approach addresses. We caution that the STE model, whether applied to timelapse or motion‐triggered datasets, relies on strict assumptions. Any violations of these assumptions, such as non‐instantaneous sampling or the application of angle and distance of detection provided by the camera manufacturer, can cause biases in multiple directions that may be difficult to differentiate. [ABSTRACT FROM AUTHOR]

Summary: Wind energy is a source of collision fatalities for birds and bats. To evaluate the risk that wind power development projects might pose to the conservation of protected species, it is essential to quantify the impact of collisions on the dynamics of wild populations. To address this challenge, two approaches are primarily employed: potential biological removal (PBR) and population projection analysis (PPA). PBR is a decision rule designed to calculate a sustainable fatality limit for a given population, whereas PPA relies on simulation-based modelling to forecast a population's future trajectory under various scenarios. In the context of environmental impact assessments (EIAs), we argue that PPA offers a more suitable method than PBR for evaluating population-level impacts resulting from collisions with wind turbines. Unlike PBR, PPA can be focused on a single source of disturbance, aligning with the perspective of the EIA process. By contrast, PBR necessarily adopts a population-centred perspective and is therefore only relevant when considering all sources of mortality that jointly affect a population. Furthermore, robust utilization of the PBR approach requires the definition of quantitative conservation objectives and the implementation of a comprehensive management strategy evaluation, neither of which is ever undertaken within the context of an EIA. [ABSTRACT FROM AUTHOR]

Interventions of the host–pathogen dynamics provide strong tests of relationships, yet they are still rarely applied across multiple populations. After American bullfrogs (Rana catesbeiana) invaded a wildlife refuge where federally threatened Chiricahua leopard frogs (R. chiricahuensis) were reintroduced 12 years prior, managers launched a landscape‐scale eradication effort to help ensure continued recovery of the native species. We used a before‐after‐control‐impact design and environmental DNA sampling of 19 eradication sites and 18 control sites between fall 2016 and winter 2020–2021 to measure community‐level responses to bullfrog eradication, including for two pathogens. Dynamic occupancy models revealed successful eradication from 94% of treatment sites. Native amphibians did not respond to bullfrog eradication, but the pathogens amphibian chytrid fungus (Batrachochytrium dendrobatidis) and ranaviruses were coextirpated with bullfrogs. Our spatially replicated experimental approach provides strong evidence that management of invasive species can simultaneously reduce predation and disease risk for imperiled species. [ABSTRACT FROM AUTHOR]

The endangered mountain yellow‐legged frog (Rana muscosa) has been reduced to <10 isolated populations in the wild. Due to frequent catastrophic events (floods, droughts, wildfires), the recent dynamics of these populations have been erratic, making the future of the species highly uncertain. In 2018, a recovery plan was developed to improve the species status by reducing the impacts of various threats (predation, disease, habitat destruction), as well as reinforcing wild populations through the reintroduction of captive‐bred frogs. The short‐term goal stated in this plan was to reach a minimum of 20 populations of 50 adults each (hereafter, the 20/50 target), before the species can be considered for downlisting from the U.S. Endangered Species Act. However, there is no guarantee that this 20/50 target will be sufficient to ensure the species persistence in the long run. Using 19 years of mark‐recapture data, we estimated populations' demographic trends and assessed the viability of R. muscosa from a starting state of 20 populations of 50 adults each (i.e., the downlisting criteria). Our results reveal that, from this 20/50 state, the species has high chances of persistence only at a short time horizon (50 years). Moreover, >80% of populations would be extinct 50 years later. Therefore, the species will not be able to persist without implementation of the reintroduction program. We found that it is more important to increase the number of suitable sites occupied by R. muscosa than to simply reinforce or augment existing populations. Expanding the current distribution by establishing new populations at suitable sites, even after the "20 populations" mark has been reached, would increase the likelihood of the species' persistence in the longer term. [ABSTRACT FROM AUTHOR]

Many aquatic species in the arid USA-Mexico borderlands region are imperiled, but limited information on distributions and threats often hinders management. To provide information on the distribution of the Western Tiger Salamander (Ambystoma mavortium), including the USA-federally endangered Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi), we used traditional (seines, dip-nets) and modern (environmental DNA [eDNA]) methods to sample 91 waterbodies in northern Sonora, Mexico, during 2015-2018. The endemic Sonoran Tiger Salamander is threatened by introgressive hybridization and potential replacement by another sub-species of the Western Tiger Salamander, the non-native Barred Tiger Salamander (A. m. mavortium). Based on occupancy models that accounted for imperfect detection, eDNA sampling provided a similar detection probability (0.82 [95% CI: 0.56-0.94]) as seining (0.83 [0.46-0.96]) and much higher detection than dip-netting (0.09 [0.02-0.23]). Volume of water filtered had little effect on detection, possibly because turbid sites had greater densities of salamanders. Salamanders were estimated to occur at 51 sites in 3 river drainages in Sonora. These results indicate tiger salamanders are much more widespread in northern Sonora than previously documented, perhaps aided by changes in land and water management practices. However, because the two subspecies of salamanders cannot be reliably distinguished based on morphology or eDNA methods that are based on mitochondrial DNA, we are uncertain if we detected only native genotypes or if we documented recent invasion of the area by the non-native sub-species. Thus, there is an urgent need for methods to reliably distinguish the subspecies so managers can identify appropriate interventions. [ABSTRACT FROM AUTHOR]

Density‐dependence effects acting on fecundity can be explained by two competing hypotheses. The individual adjustment hypothesis (IAH) states that, as population density increases, interference among individuals negatively affects their breeding performance. The second hypothesis, the habitat heterogeneity hypothesis (HHH), proposes that, as more individuals occupy the space available, lower quality habitats are increasingly used, causing average population fecundity to decline. In territorial species, it is often predicted that interference mechanisms (IAH) should be of less importance than spatial heterogeneity (HHH). Here, we test this prediction in Golden Eagles, using 35 years of reproduction monitoring data from a population that has been recolonizing the grounds of a French National Park (Ecrins) in the Alps. During the study period, the Eagle population increased from c. 11 to 41 territorial pairs, providing a good opportunity to explicitly assess fecundity across a gradient of densities. Under the IAH, we expect the fecundity of all territories to diminish as density rises. Under strict HHH, older territories should maintain higher fecundity across time, and a positive relationship between fecundity and the seniority of a territory should be observed. A density‐dependent pattern was clearly detected at the population level. At the territory level, the decrease of fecundity was strongly related to population size but not to territory seniority. Fecundity decreased similarly in all territories, suggesting that the IAH better explains the observed pattern. Two alternative mechanisms, related to the IAH, could be at play in this population: (1) negative interference by neighbours and non‐territorial Eagles and (2) the contraction of individual territories over time. Our results provide new insights into density dependence in territorial raptors, suggesting that, in addition to habitat heterogeneity, interference mechanisms might actually also play an important role. [ABSTRACT FROM AUTHOR]

As large carnivores recover throughout Europe, their distribution needs to be studied to determine their conservation status and assess the potential for human‐carnivore conflicts. However, efficient monitoring of many large carnivore species is challenging due to their rarity, elusive behavior, and large home ranges. Their monitoring can include opportunistic sightings from citizens in addition to designed surveys. Two types of detection errors may occur in such monitoring schemes: false negatives and false positives. False‐negative detections can be accounted for in species distribution models (SDMs) that deal with imperfect detection. False‐positive detections, due to species misidentification, have rarely been accounted for in SDMs. Generally, researchers use ad hoc data‐filtering methods to discard ambiguous observations prior to analysis. These practices may discard valuable ecological information on the distribution of a species. We investigated the costs and benefits of including data types that may include false positives rather than discarding them for SDMs of large carnivores. We used a dynamic occupancy model that simultaneously accounts for false negatives and positives to jointly analyze data that included both unambiguous detections and ambiguous detections. We used simulations to compare the performances of our model with a model fitted on unambiguous data only. We tested the 2 models in 4 scenarios in which parameters that control false‐positive detections and true detections varied. We applied our model to data from the monitoring of the Eurasian lynx (Lynx lynx) in the European Alps. The addition of ambiguous detections increased the precision of parameter estimates. For the Eurasian lynx, incorporating ambiguous detections produced more precise estimates of the ecological parameters and revealed additional occupied sites in areas where the species is likely expanding. Overall, we found that ambiguous data should be considered when studying the distribution of large carnivores through the use of dynamic occupancy models that account for misidentification. Article impact statement: Use of ambiguous detections can improve understanding of large‐carnivore distribution dynamics. [ABSTRACT FROM AUTHOR]

Rapid environmental change in highly biodiverse tropical regions demands efficient biomonitoring programmes. While existing metrics of species diversity and community composition rely on encounter‐based survey data, eDNA recently emerged as alternative approach. Costs and ecological value of eDNA‐based methods have rarely been evaluated in tropical regions, where high species richness is accompanied by high functional diversity (e.g., the use of different microhabitats by different species and life stages). We first tested whether estimation of tropical frogs' community structure derived from eDNA data is compatible with expert field assessments. Next, we evaluated whether eDNA is a financially viable solution for biodiversity monitoring in tropical regions. We applied eDNA metabarcoding to investigate frog species occurrence in five ponds in the Chiquitano dry forest region in Bolivia and compared our data with a simultaneous visual and audio encounter survey (VAES). We found that taxon lists and community structure generated with eDNA and VAES correspond closely, and most deviations are attributable to different species' life histories. Cost efficiency of eDNA surveys was mostly influenced by the richness of local fauna and the number of surveyed sites: VAES may be less costly in low‐diversity regions, but eDNA quickly becomes more cost‐efficient in high‐diversity regions with many sites sampled. The results highlight that eDNA is suitable for large‐scale biodiversity surveys in high‐diversity areas if life history is considered, and certain precautions in sampling, genetic analyses and data interpretation are taken. We anticipate that spatially extensive, standardized eDNA biodiversity surveys will quickly emerge in the future. [ABSTRACT FROM AUTHOR]

Abstract: In occupancy studies, species misidentification can lead to false‐positive detections, which can cause severe estimator biases. Currently, all models that account for false‐positive errors only consider omnibus sources of false detections and are limited to single‐species occupancy. However, false detections for a given species often occur because of the misidentification with another, closely related species. To exploit this explicit source of false‐positive detection error, we develop a two‐species occupancy model that accounts for misidentifications between two species of interest. As with other false‐positive models, identifiability is greatly improved by the availability of unambiguous detections at a subset of site x occasions. Here, we consider the case where some of the field observations can be confirmed using laboratory or other independent identification methods (“confirmatory data”). We performed three simulation studies to (1) assess the model's performance under various realistic scenarios, (2) investigate the influence of the proportion of confirmatory data on estimator accuracy and (3) compare the performance of this two‐species model with that of the single‐species false‐positive model. The model shows good performance under all scenarios, even when only small proportions of detections are confirmed (e.g. 5%). It also clearly outperforms the single‐species model. We illustrate application of this model using a 4‐year dataset on two sympatric species of lungless salamanders: the US federally endangered Shenandoah salamander Plethodon shenandoah, and its presumed competitor, the red‐backed salamander Plethodon cinereus. Occupancy of red‐backed salamanders appeared very stable across the 4 years of study, whereas the Shenandoah salamander displayed substantial turnover in occupancy of forest habitats among years. Given the extent of species misidentification issues in occupancy studies, this modelling approach should help improve the reliability of estimates of species distribution, which is the goal of many studies and monitoring programmes. Further developments, to account for different forms of state uncertainty, can be readily undertaken under our general approach. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems. [ABSTRACT FROM AUTHOR]

Abstract: The development and use of automated species detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide cost‐ and time‐effective means to process information‐rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors. We developed a hierarchical modelling framework for estimating species occupancy from automated species detection data. We explore design and optimization of data post‐processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false‐positive errors and utilizes information about both occurrence and abundance of detections to improve estimation. Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders. When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post‐validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post‐validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated. Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programmes. [ABSTRACT FROM AUTHOR]

N-mixture models have become a popular method for estimating abundance of free-ranging animals that are not marked or identified individually. These models have been used on count data for single species that can be identified with certainty. However, co-occurring species often look similar during one or more life stages, making it difficult to assign species for all recorded captures. This uncertainty creates problems for estimating species-specific abundance, and it can often limit life stages to which we can make inference., We present a new extension of N-mixture models that accounts for species uncertainty. In addition to estimating site-specific abundances and detection probabilities, this model allows estimating probability of correct assignment of species identity. We implement this hierarchical model in a Bayesian framework and provide all code for running the model in BUGS language programs., We present an application of the model on count data from two sympatric freshwater fishes, the brook stickleback ( Culaea inconstans) and the ninespine stickleback ( Pungitius pungitius), and illustrate implementation of covariate effects (habitat characteristics). In addition, we used a simulation study to validate the model and illustrate potential sample size issues. We also compared, for both real and simulated data, estimates provided by our model to those obtained by a simple N-mixture model when captures of unknown species identification were discarded. In the latter case, abundance estimates appeared highly biased and very imprecise, while our new model provided unbiased estimates with higher precision., This extension of the N-mixture model should be useful for a wide variety of studies and taxa, as species uncertainty is a common issue. It should notably help improve investigation of abundance and vital rate characteristics of organisms' early life stages, which are sometimes more difficult to identify than adults. [ABSTRACT FROM AUTHOR]

The article reports on the geographical distribution of Tiger Salamanders, Ambystoma mavortium stebbinsi species in Sonora, Mexico. Topics discussed include loss of natural wetland habitats, inbreeding caused by small population sizes and limited gene flow and lack of information on the distribution of Tiger Salamanders in Sonora , Mexico that poses challenges to conservation planning.

Before making dispersal decisions, many species are known to gather social information by prospecting potential future breeding sites, especially when they have failed breeding. So far, the role of current breeding performance on the occurrence of prospecting movements has mainly been studied at limited spatial scales, because of difficulties in tracking free-ranging, fast-moving individuals between distant breeding patches. Little information is thus available on individual behaviour and the spatial extent of prospecting movements in response to breeding failure. To address this issue, black-legged kittiwakes which breeding success was manipulated were tracked with GPS at the end of incubation in two Norwegian colonies. Crucially, and as predicted, prospecting visits to other breeding colonies were recorded in 33% of artificially-failed breeders, but never in successful ones. They occurred at large (40 km) as well as local spatial scales (1 km). Time-budgets of successful and failed breeders differed significantly in terms of trip duration, but also foraging, resting and nesting propensities. These results provide important elements to assess trade-offs between prospecting and other activities. They show that a substantial proportion of failed breeders prospect as early as within a week after failure at the egg stage and suggest that these individuals assess their options of future reproduction by prospecting alternative areas, although dispersal decisions may also involve more complex behavioural processes. Because they link breeding colonies situated tens of kilometres apart, prospecting movements may have critical implications for the dynamics of subdivided populations. [ABSTRACT FROM AUTHOR]

With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology., We present a multi-season extension of the staggered-entry occupancy model of Kendall et al. (2013, Ecology, 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics., We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities., Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change. [ABSTRACT FROM AUTHOR]

The investigation of individual heterogeneity in vital rates has recently received growing attention among population ecologists. Individual heterogeneity in wild animal populations has been accounted for and quantified by including individually varying effects in models for mark-recapture data, but the real need for underlying individual effects to account for observed levels of individual variation has recently been questioned by the work of Tuljapurkar et al. (Ecology Letters, 12, 93, 2009) on dynamic heterogeneity. Model-selection approaches based on information criteria or Bayes factors have been used to address this question. Here, we suggest that, in addition to model-selection, model-checking methods can provide additional important insights to tackle this issue, as they allow one to evaluate a model's misfit in terms of ecologically meaningful measures. Specifically, we propose the use of posterior predictive checks to explicitly assess discrepancies between a model and the data, and we explain how to incorporate model checking into the inferential process used to assess the practical implications of ignoring individual heterogeneity. Posterior predictive checking is a straightforward and flexible approach for performing model checks in a Bayesian framework that is based on comparisons of observed data to model-generated replications of the data, where parameter uncertainty is incorporated through use of the posterior distribution. If discrepancy measures are chosen carefully and are relevant to the scientific context, posterior predictive checks can provide important information allowing for more efficient model refinement. We illustrate this approach using analyses of vital rates with long-term mark-recapture data for Weddell seals and emphasize its utility for identifying shortfalls or successes of a model at representing a biological process or pattern of interest. [ABSTRACT FROM AUTHOR]

Prospecting allows individuals to gather information on the local quality of potential future breeding sites. In a variable and heterogeneous environment, it plays a major role in breeding habitat selection and potentially helps individuals make optimal dispersal decisions. Although prospecting movements, involving visits to other breeding sites, have been observed in many species at relatively fine spatial scales, little is known about their occurrence at larger scales. Furthermore, the adaptive value of dispersal strategies in response to environmental changes remains poorly investigated., Here, our main objective is to highlight in what ways tracking devices could constitute powerful tools to study prospecting behaviour at various spatial scales. First, we stress the importance of considering prospecting movements involved in breeding habitat selection and we detail the type of data that can be collected. Then, we review the advantages and constraints associated with the use of tracking devices in this context, and we suggest new perspectives to investigate the behavioural strategies adopted by individuals during breeding habitat selection processes and dispersal decisions., The rapid development of new powerful electronic tools for tracking individual behaviour thus opens a wide range of opportunities. More specifically, it may allow a more thorough understanding of the role of scale-dependent dispersal behaviour in population responses to environmental changes. [ABSTRACT FROM AUTHOR]

Understanding the additive or interactive threats of habitat transformation and invasive species is critical for conservation, especially where climate change is expected to increase the severity or frequency of drought. In the arid southwestern USA, this combination of stressors has caused widespread declines of native aquatic and semi-aquatic species. Achieving resilience to drought and other effects of climate change may depend upon continued management, so understanding the combined effects of stressors is important. We used Bayesian hierarchical models fitted with 10-years of pond-based monitoring surveys for the federally-endangered Sonoran Tiger Salamander ( Ambystoma mavortium stebbinsi ) and invasive predators (fishes and American Bullfrogs, Lithobates catesbeianus ) that threaten native species. We estimated trends in occupancy of salamanders and invasive predators while accounting for hydrological dynamics of ponds, then used a two-species interaction model to directly estimate how invasive predators affected salamander occupancy. We also tested a conceptual model that predicted that drought, by limiting the distribution of invasive predators, could ultimately benefit native species. Even though occupancy of invasive predators was stationary and their presence in a pond reduced the probability of salamander presence by 23%, occupancy of Sonoran Tiger Salamanders increased, annually, by 2.2%. Occupancy of salamanders and invasive predators both declined dramatically following the 5th consecutive year of drought. Salamander occupancy recovered quickly after return to non-drought conditions, while occupancy of invasive predators remained suppressed. Models that incorporated three time-lagged periods (1 to 4 years) of local moisture conditions confirmed that salamanders and invasive predators responded differently to drought, reflecting how life-history strategies shape responses to disturbances. The positive 10-year trend in salamander occupancy and their rapid recovery after drought provided partial support for the hypothesis of drought-mediated coexistence with invasive predators. These results also suggest management opportunities for conservation of the Sonoran Tiger Salamander and other imperiled organisms in human-transformed landscapes. [ABSTRACT FROM AUTHOR]

Two approaches have been classically used in disease ecology to estimate epidemiological parameters from field studies: cross-sectional sampling from unmarked individuals and longitudinal capture-recapture setups, which generally involve more limited numbers of marked individuals due to cost and logistical constraints. Although the benefits of longitudinal setups are increasingly acknowledged in the disease ecology community, cross-sectional data remain largely overrepresented in the literature, probably because of the inherent costs of longitudinal surveys. In this context, we used simulated data to compare the performances of cross-sectional and longitudinal designs to estimate the force of infection (i.e., the rate at which susceptible individuals become infected). Then, inspired from recent method developments in quantitative ecology, we explore the benefits of integrating both cross-sectional (seroprevalences) and longitudinal (individuals histories) data sets. In doing so, we investigate the effects of host species life history, antibody persistence, and degree of a priori knowledge and uncertainty on demographic and epidemiological parameters, as those are expected to affect in different ways the level of inference possible from the data. Our results highlight how those elements are important to consider in determining optimal sampling designs. In the case of long-lived species exposed to infectious agents resulting in persistent antibody responses, integrated designs are especially valuable as they benefit from the performances of longitudinal designs even with relatively small longitudinal sample sizes. As an illustration, we apply this approach to a combination of empirical and simulated data inspired from a case of bats exposed to a rabies virus. Overall, this work highlights that serology field studies could greatly benefit from the opportunity of integrating cross-sectional and longitudinal designs., (© 2019 by the Ecological Society of America.)

As large carnivores recover throughout Europe, their distribution needs to be studied to determine their conservation status and assess the potential for human-carnivore conflicts. However, efficient monitoring of many large carnivore species is challenging due to their rarity, elusive behavior, and large home ranges. Their monitoring can include opportunistic sightings from citizens in addition to designed surveys. Two types of detection errors may occur in such monitoring schemes: false negatives and false positives. False-negative detections can be accounted for in species distribution models (SDMs) that deal with imperfect detection. False-positive detections, due to species misidentification, have rarely been accounted for in SDMs. Generally, researchers use ad hoc data-filtering methods to discard ambiguous observations prior to analysis. These practices may discard valuable ecological information on the distribution of a species. We investigated the costs and benefits of including data types that may include false positives rather than discarding them for SDMs of large carnivores. We used a dynamic occupancy model that simultaneously accounts for false negatives and positives to jointly analyze data that included both unambiguous detections and ambiguous detections. We used simulations to compare the performances of our model with a model fitted on unambiguous data only. We tested the 2 models in 4 scenarios in which parameters that control false-positive detections and true detections varied. We applied our model to data from the monitoring of the Eurasian lynx (Lynx lynx) in the European Alps. The addition of ambiguous detections increased the precision of parameter estimates. For the Eurasian lynx, incorporating ambiguous detections produced more precise estimates of the ecological parameters and revealed additional occupied sites in areas where the species is likely expanding. Overall, we found that ambiguous data should be considered when studying the distribution of large carnivores through the use of dynamic occupancy models that account for misidentification., (© 2018 Society for Conservation Biology.)

Since amphibian declines were first proposed as a global phenomenon over a quarter century ago, the conservation community has made little progress in halting or reversing these trends. The early search for a "smoking gun" was replaced with the expectation that declines are caused by multiple drivers. While field observations and experiments have identified factors leading to increased local extinction risk, evidence for effects of these drivers is lacking at large spatial scales. Here, we use observations of 389 time-series of 83 species and complexes from 61 study areas across North America to test the effects of 4 of the major hypothesized drivers of declines. While we find that local amphibian populations are being lost from metapopulations at an average rate of 3.79% per year, these declines are not related to any particular threat at the continental scale; likewise the effect of each stressor is variable at regional scales. This result - that exposure to threats varies spatially, and populations vary in their response - provides little generality in the development of conservation strategies. Greater emphasis on local solutions to this globally shared phenomenon is needed.