A standardized protocol for assessing the performance of automatic detection systems used in onshore wind power plants to reduce avian mortality.

While wind power plants are an important contribution to the production of renewable energy to limit climate change, collision mortality from turbines is a danger for birds, including many protected species. To try to mitigate collision risks, automatic detection systems (ADSs) can be deployed on wind power plants; these work by detecting incoming birds using a detection/classification process and triggering a specific reaction (scaring off the bird or shutting down the turbine). Nonetheless, bird fatalities still occur at ADS-equipped wind power plants, which raises the question of the performance of these tools. To date, the lack of a transparent, peer-reviewed experimental process to compare the performance of types of ADS has meant there is no robust protocol to assess these systems. With the aim of filling this gap, we developed two standardized protocols that provide objective and unbiased assessments of the performance of different types of ADS, based on their probability of detecting/classifying birds at risk of collision. Both protocols rely on precise 3D tracking of wild birds by human observers using a laser rangefinder, and the comparison of these tracks with those detected and recorded by an ADS. The first protocol evaluates a system's general performance, generating comparable data for all types of ADS. In this protocol, detection/classification probability is estimated conditional on several abiotic and biotic environmental factors such as bird size, distance from the target, the flight angle and azimuth of the bird, as well as weather conditions. The second protocol aims to verify that the performance of an ADS installed on a given wind power plant complies with its regulatory requirements. In this protocol, detection/classification probability is specifically estimated for a given target species at a given regulatory detection distance. This protocol also estimates the proportion of time an ADS is functional on site over a year, and the proportion of reaction orders successfully operated by wind turbines. These protocols have been field-tested and made publicly available for use by government agencies and wind power plant operators.

EolPop, a R-shiny tool for quantifying the demographic impact of species exposed to fatalities: Application to bird collisions with wind turbines.

Quantifying the demographic impact of anthropogenic fatalities on animal populations is a key component of wildlife conservation. However, such quantification remains rare in environmental impact assessments (EIA) of large-infrastructure projects, partly because of the complexity of implementing demographic models. Providing user-friendly demographic tools is thus an important step to fill this gap. We developed an application called EolPop to run demographic simulations and assess population-level impacts of fatalities. This tool, freely available online, is easy to use and requires minimal input data from the user. As an output, it provides an estimate, with associated uncertainty, of the relative deficit in population size at a given time horizon. Because this impact metric is relative to a baseline scenario without fatalities, it is robust to uncertainties. We showcase the tool using examples on two species that are affected by collisions with wind turbines: Lesser kestrel (Falco naumanni) and Eurasian skylark (Alauda arvensis). After 30 years, the kestrel's population is expected to suffer a deficit of ca. 48%. In contrast, the impact on skylarks, which are already declining in France, is estimated to be fairly low (ca. 7%). EolPop aims at providing a robust quantification of the relative impact of fatalities. This tool was originally built for windfarm EIA, with a focus on birds, but it can be used to assess the demographic consequences of any type of fatalities on any species.

Next-generation serology: integrating cross-sectional and capture-recapture approaches to infer disease dynamics.

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.

Use of ambiguous detections to improve estimates from species distribution models.

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.

Accuracy, limitations and cost efficiency of eDNA-based community survey in tropical frogs.

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.

An analytical framework for estimating aquatic species density from environmental DNA.

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.

Migration, Prospecting, Dispersal? What Host Movement Matters for Infectious Agent Circulation?

Spatial disease ecology is emerging as a new field that requires the integration of complementary approaches to address how the distribution and movements of hosts and parasites may condition the dynamics of their interactions. In this context, migration, the seasonal movement of animals to different zones of their distribution, is assumed to play a key role in the broad scale circulation of parasites and pathogens. Nevertheless, migration is not the only type of host movement that can influence the spatial ecology, evolution, and epidemiology of infectious diseases. Dispersal, the movement of individuals between the location where they were born or bred to a location where they breed, has attracted attention as another important type of movement for the spatial dynamics of infectious diseases. Host dispersal has notably been identified as a key factor for the evolution of host-parasite interactions as it implies gene flow among local host populations and thus can alter patterns of coevolution with infectious agents across spatial scales. However, not all movements between host populations lead to dispersal per se. One type of host movement that has been neglected, but that may also play a role in parasite spread is prospecting, i.e., movements targeted at selecting and securing new habitat for future breeding. Prospecting movements, which have been studied in detail in certain social species, could result in the dispersal of infectious agents among different host populations without necessarily involving host dispersal. In this article, we outline how these various types of host movements might influence the circulation of infectious disease agents and discuss methodological approaches that could be used to assess their importance. We specifically focus on examples from work on colonial seabirds, ticks, and tick-borne infectious agents. These are convenient biological models because they are strongly spatially structured and involve relatively simple communities of interacting species. Overall, this review emphasizes that explicit consideration of the behavioral and population ecology of hosts and parasites is required to disentangle the relative roles of different types of movement for the spread of infectious diseases.

Quantitative evidence for the effects of multiple drivers on continental-scale amphibian declines.

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.

Modeling false positive detections in species occurrence data under different study designs.

The occurrence of false positive detections in presence-absence data, even when they occur infrequently, can lead to severe bias when estimating species occupancy patterns. Building upon previous efforts to account for this source of observational error, we established a general framework to model false positives in occupancy studies and extend existing modeling approaches to encompass a broader range of sampling designs. Specifically, we identified three common sampling designs that are likely to cover most scenarios encountered by researchers. The different designs all included ambiguous detections, as well as some known-truth data, but their modeling differed in the level of the model hierarchy at which the known-truth information was incorporated (site level or observation level). For each model, we provide the likelihood, as well as R and BUGS code needed for implementation. We also establish a clear terminology and provide guidance to help choosing the most appropriate design and modeling approach.

Female Weddell seals show flexible strategies of colony attendance related to varying environmental conditions.

Many animal life cycles involve movements among different habitats to fulfill varying resource demands. There are inherent costs associated with such movements, and the decision to leave or stay at a given location ought to be motivated by the benefits associated with potential target habitats. Because movement patterns, especially those associated with reproduction, can have important implications for the success (survival, reproduction) of individual animals, and therefore a population's dynamics, it is important to identify and understand their sources of variation (environmental and individual). Here, using a mark-recapture, multistate modeling approach, we investigated a set of a priori hypotheses regarding sources and patterns of variation in breeding-colony attendance for Weddell seal (Leptonychotes weddellii) females on sabbatical from pup production. For such females, colony attendance might be motivated by predation avoidance and positive social interactions related to reproduction, but some costs, such as reduced foraging opportunities or aggressive interactions with conspecifics, might also exist. We expected these benefits and costs to vary with a female's condition and the environment. Results revealed that the probability of being absent from colonies was higher (1) in years when the extent of local sea ice was larger, (2) for the youngest and oldest individuals, and (3) for females with less reproductive experience. We also found substantial levels of residual individual heterogeneity in these rates. Based on our a priori predictions, we postulate that the decision to attend breeding colonies or not is directly influenced by an individual's physiological condition, as well as by the ice-covered distance to good foraging areas, availability of predator-free haul-out sites, and the level of negative interactions with conspecifics inside colonies. Our results support the idea that in iteroparous species, and colonial animals in particular, seasonal and temporary movements from/to reproductive sites represent flexible behavioral strategies that can play an important role in coping with environmental variability.

Use of posterior predictive checks as an inferential tool for investigating individual heterogeneity in animal population vital rates.

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. We show how posterior predictive checks can be used to strengthen inferences in ecological studies. We demonstrate the application of this method on analyses dealing with the question of individual reproductive heterogeneity in a population of Antarctic pinnipeds.

An evolutionary perspective on reproductive individual heterogeneity in a marine vertebrate.

Although the quantification of individual heterogeneity in wild populations' vital rates has recently attracted growing interest among ecologists, the investigation of its evolutionary consequences remains limited, mainly because of the difficulties in assessing fitness and heritability from field studies on free-ranging animals. In the presence of individual variability, evaluation of fitness consequences can notably be complicated by the existence of trade-offs among different vital rates. In this study, to further assess the evolutionary significance of previously quantified levels of individual heterogeneity in female Weddell seal (Leptonychotes weddellii Lesson) reproductive rates (Chambert et al. ), we investigated how several life-history characteristics of female offspring were related to their mother's reproductive rate, as well as to other maternal traits (age and experience) and environmental conditions at birth. The probability and age of first reproduction (recruitment) of female offspring was not related to their mother's reproductive rate, suggesting the absence of a maternal trade-off between the number and quality of offspring a female produces. Evidence of a positive, but relatively weak, relationship between the reproductive rates of a mother and her female offspring was found, suggesting some degree of heritability in this trait. Using a simulation approach based on these statistical findings, we showed that substantial differences in the number of grandchildren, produced through female progeny, can be expected among females with different reproductive rates. Despite the presence of substantial stochastic variability, due to environmental fluctuations and other unidentified mechanisms, and in the light of the fact that the metrics obtained do not provide a full measure of real fitness, our results do suggest that the individual reproductive variability found in female Weddell seals could potentially have important fitness consequences.

Estimating transitions between states using measurements with imperfect detection: application to serological data.

Classifying the states of an individual and quantifying transitions between states are crucial while modeling animal behavior, movement, and physiologic status. When these states are hidden or imperfectly known, it is particularly convenient to relate them to appropriate quantitative measurements taken on the individual. This task is, however, challenging when quantitative measurements are not available at each sampling occasion. For capture-recapture data, various ways of incorporating such non-discrete information have been used, but they are either ad hoc and/or use a fraction of the available information by relying on a priori thresholds to assign individual states. Here we propose assigning discrete states based on a continuous measurement, and then modeled survival and transition probabilities based on these assignments. The main advantage of this new approach is that a more informative use of the non-discrete information is done. As an illustrative working example, we applied this approach to eco-epidemiological data collected across a series of years in which individuals of a long-lived seabird, the Black-legged Kittiwake (Rissa tridactyla), could either be visually detected or physically recaptured and blood sampled for subsequent immunological analyses. We discuss how this approach opens many perspectives in eco-epidemiology, but also more broadly, in population ecology.

Individual heterogeneity in reproductive rates and cost of reproduction in a long-lived vertebrate.

Individual variation in reproductive success is a key feature of evolution, but also has important implications for predicting population responses to variable environments. Although such individual variation in reproductive outcomes has been reported in numerous studies, most analyses to date have not considered whether these realized differences were due to latent individual heterogeneity in reproduction or merely random chance causing different outcomes among like individuals. Furthermore, latent heterogeneity in fitness components might be expressed differently in contrasted environmental conditions, an issue that has only rarely been investigated. Here, we assessed (i) the potential existence of latent individual heterogeneity and (ii) the nature of its expression (fixed vs. variable) in a population of female Weddell seals (Leptonychotes weddellii), using a hierarchical modeling approach on a 30-year mark-recapture data set consisting of 954 individual encounter histories. We found strong support for the existence of latent individual heterogeneity in the population, with "robust" individuals expected to produce twice as many pups as "frail" individuals. Moreover, the expression of individual heterogeneity appeared consistent, with only mild evidence that it might be amplified when environmental conditions are severe. Finally, the explicit modeling of individual heterogeneity allowed us to detect a substantial cost of reproduction that was not evidenced when the heterogeneity was ignored.

Environmental extremes versus ecological extremes: impact of a massive iceberg on the population dynamics of a high-level Antarctic marine predator.

Extreme events have been suggested to play a disproportionate role in shaping ecological processes, but our understanding of the types of environmental conditions that elicit extreme consequences in natural ecosystems is limited. Here, we investigated the impact of a massive iceberg on the dynamics of a population of Weddell seals. Reproductive rates of females were reduced, but survival appeared unaffected. We also found suggestive evidence for a prolonged shift towards higher variability in reproductive rates. The annual number of females attending colonies showed unusual swings during the iceberg period, a pattern that was apparently the consequence of changes in sea-ice conditions. In contrast to the dramatic effects that were recorded in nearby populations of emperor penguins, our results suggest that this unusual environmental event did not have an extreme impact on the population of seals in the short-term, as they managed to avoid survival costs and were able to rapidly re-achieve high levels of reproduction by the end of the perturbation. Nevertheless, population projections suggest that even this modest impact on reproductive rates could negatively affect the population in the long run if such events were to occur more frequently, as is predicted by models of climate change.

Exposure of black-legged kittiwakes to Lyme disease spirochetes: dynamics of the immune status of adult hosts and effects on their survival.

1. Despite a growing interest in wildlife disease ecology, there is a surprising lack of knowledge about the exposure dynamics of individual animals to naturally circulating infectious agents and the impact of such agents on host life-history traits. 2. The exploration of these questions requires detailed longitudinal data on individual animals that can be captured multiple times during their life but also requires being able to account for several sources of uncertainty, notably the partial observation or recapture of individuals at each sampling occasion. 3. We use a multi-year dataset to (i) assess the potential effect of exposure to the tick-borne agent of Lyme disease, Borrelia burgdorferi sensu lato (Bbsl), on adult apparent survival for one of its natural long-lived hosts, the Black-legged kittiwake (Rissa tridactyla), and (ii) investigate the temporal dynamics of individual immunological status in kittiwakes to infer the rate of new exposure and the persistence of the immune response. Using a multi-event modelling approach, potential uncertainties arising from partial observations were explicitly taken into account. 4. The potential impact of Bbsl on kittiwake survival was also evaluated via an experimental approach: the apparent survival of a group of breeding birds treated with an antibiotic was compared with that of a control group. 5. No impact of exposure to Bbsl was detected on adult survival in kittiwakes, in either observational or experimental data. 6. An annual seroconversion rate (from negative to positive) of 1·5% was estimated, but once an individual became seropositive, it remained so with a probability of 1, suggesting that detectable levels of anti-Bbsl antibodies persist for multiple years. 7. These results, in combination with knowledge on patterns of exposure to the tick vector of Bbsl, provide important information for understanding the spatio-temporal nature of the interaction between this host and several of its parasites. Furthermore, our analyses highlight the utility of capture-mark-recapture approaches handling state uncertainty for disease ecology studies.

Evaluating the demographic buffering hypothesis with vital rates estimated for Weddell seals from 30 years of mark-recapture data.

1. Life-history theory predicts that those vital rates that make larger contributions to population growth rate ought to be more strongly buffered against environmental variability than are those that are less important. Despite the importance of the theory for predicting demographic responses to changes in the environment, it is not yet known how pervasive demographic buffering is in animal populations because the validity of most existing studies has been called into question because of methodological deficiencies. 2. We tested for demographic buffering in the southern-most breeding mammal population in the world using data collected from 5558 known-age female Weddell seals over 30 years. We first estimated all vital rates simultaneously with mark-recapture analysis and then estimated process variance and covariance in those rates using a hierarchical Bayesian approach. We next calculated the population growth rate's sensitivity to changes in each of the vital rates and tested for evidence of demographic buffering by comparing properly scaled values of sensitivity and process variance in vital rates. 3. We found evidence of positive process covariance between vital rates, which indicates that all vital rates are affected in the same direction by changes in annual environment. Despite the positive correlations, we found strong evidence that demographic buffering occurred through reductions in variation in the vital rates to which population growth rate was most sensitive. Process variation in vital rates was inversely related to sensitivity measures such that variation was greatest in breeding probabilities, intermediate for survival rates of young animals and lowest for survival rates of older animals. 4. Our work contributes to a small but growing set of studies that have used rigorous methods on long-term, detailed data to investigate demographic responses to environmental variation. The information from these studies improves our understanding of life-history evolution in stochastic environments and provides useful information for predicting population responses to future environmental change. Our results for an Antarctic apex predator also provide useful baselines from a marine ecosystem when its top- and middle-trophic levels were not substantially impacted by human activity.