Search

Abstract Harvest data have the potential to be used as an abundance index due to its widespread availability and long‐term collection across large geographical areas. However, challenges such as the lack of hunting effort information, varying data resolutions and reporting biases hinder its direct use as an abundance proxy. Here, we present the game target‐group, a statistical approach based on a thinned inhomogeneous Poisson point process, to estimate animal abundance at fine‐scale resolution from hunting data. We employ a Bayesian hierarchical framework to borrow information from harvest data on related species to overcome issues due to the lack of hunting management information. We conducted a simulation study to explore model performance and parameter identifiability under different scenarios (sample size, species catchability/abundance and unmodelled heterogeneity) and assessed the method on a real case study with four species in central Spain. The simulation study confirmed that with a large enough sample size (n > 5000), high catchability and lack of unmodelled heterogeneity in the abundance process, the model was able to obtain unbiased estimations for total abundance parameters. In the case study, our model successfully captured species‐habitat relationships and produced reliable estimates of total abundance at regional scale. Internal validation with independent test data and external validation with fieldwork data confirmed the model's ability to predict hunting yields and estimate species total abundance accurately. Our approach provides a flexible and valuable tool for large‐scale monitoring programs relying on harvest data with potential applications in wildlife management and conservation. However, the method should be applied with caution when there is unmodelled heterogeneity, low catchability or the sample size is small (

Transports of people and goods contribute to the ongoing 6th mass extinction of species. They impact species viability by reducing the availability of suitable habitat, by limiting connectivity between suitable patches, and by increasing direct mortality due to collisions with vehicles. Not only does it represent a threat for some species conservation capabilities, but animal vehicle collisions (AVC) is also a threat for human safety and security in transport and has a massive cost for transport infrastructure (TI) managers and users. Using the opportunities offered by the increasing number of sensors embedded into TI and the development of their digital twins, we developed a framework aiming at managing AVC by mapping the collision risk between trains and ungulates (roe deer and wild boar) thanks to the deployment of a camera trap network. The proposed framework uses population dynamic simulations to identify collision hotspots and assist with the design of sensors deployment. Once sensors are deployed, the data collected, here photos, are processed through deep learning to detect and identify species at the TI vicinity. Then, the processed data are fed to an abundance model able to map species relative abundance around the TI as a proxy of the collision risk. We implement the framework on an actual section of railway in south-western France benefiting from a mitigation and monitoring strategy. The implementation thus highlighted the technical and fundamental requirements to effectively mainstream biodiversity concerns in the TI digital twins. This would contribute to the AVC management in autonomous vehicles thanks to connected TI.

Abstract Occupancy models were originally developed to better understand species distribution while accounting for imperfect detection. Because species distribution is not only shaped by habitat quality but also by the ability of individuals to reach suitable habitats, spatial dynamic occupancy models have been proposed to extend the original framework by defining that site colonisation was a function of the Euclidean distance to occupied sites. However, not all sites in the landscape are equally accessible due to the presence of barriers, that of corridors, etc. To account for connectivity between sites, the Euclidean distance has recently been replaced by a least‐cost path distance, which explicitly accounts for landscape resistance, but assumes that individuals will follow the optimal route. To relax this assumption, we first developed a new spatial occupancy model that incorporates commute‐time distance derived from circuit theory to model accessibility across sites. This distance has the advantage of modelling movement as a random walk and accounting for the fact that colonisation could be achieved from multiple paths. Our approach allows for the explicit estimation of landscape connectivity from detection/non‐detection data and a direct measure of connectivity uncertainty. We implemented the model in the Bayesian framework using the nimble R package, which allows useful R connectivity functions to be called from within the model. Second, we carried out a simulation study to assess the performance of our model by considering four scenarios depicting an increasing level of landscape resistance. Third, to illustrate our new approach, we studied the recolonisation of two carnivores in France. We quantified the degree to which rivers facilitate Eurasian otter (Lutra lutra) colonisation and highways impede Eurasian lynx (Lynx lynx) colonisation. Overall, spatial occupancy models provide a flexible framework to accommodate any distance metric designed to align with species dispersal ecology.

Ungulate populations can exhibit various growth patterns, which are influenced by factors such as predation and resource availability. Favourable environments can lead to irruptive growth, resulting in resource depletion. However, additional pressures from predation, and hunting can potentially impact population development leading to declines or even local extinctions. This study uses simulation models to explore the potential impact of multiple mortality sources on roe deer populations. We develop an age-structured, two-sex demographic matrix model for roe deer, which we parameterise with empirical demographic estimates obtained from published studies in Norway. We develop scenarios to assess the influence of mortality sources such as hunting, predation by lynx and red foxes, and environmental stochasticity on roe deer population dynamics. When simulating favourable environments without predation, roe deer populations tended to erupt due to the species' rapid reproductive capacity. However, additional sources of mortality, such as predation or harvest, lead to severe population declines, and even to quasi-extinction, especially when occurring in combination. Environmental stochasticity such as periodic severe winters with heavy snowfall reduces the growth rate and population densities even further. On the other hand, accounting for some form of spatial heterogeneity through immigration and refuges stabilised populations, with a reduced risk of quasi-extinction. Our results provide meaningful insights into the properties of this system allow implications for the management and identify areas where further exploration is needed.

Abstract Emotions are short, intuitive mental processes that are important components of people's cognitions. They can influence attitudes (i.e. positive or negative evaluations of objects), and they are involved in decision‐making processes. In the context of human‐wildlife coexistence, mostly emotional dispositions have been studied (i.e. people's decontextualized, stable tendencies to react in a certain way towards wildlife), in contrast to emotional states (i.e. quick reactions elicited in specific contexts), which have been overlooked. This limits our understanding of emotional states and the role of emotional diversity in shaping attitudes towards wildlife species. Here, we quantified emotional states elicited by context‐specific wolf encounters featured in a set of YouTube videos. We conducted a social survey in rural populations of 24 randomly selected cities in France (n = 795) to (i) quantify emotional diversity and (ii) test the relationship between emotional states and attitudes towards wolves, accounting for individual and regional factors. We found that emotional states that were most expressed across the six contexts of encounter were surprise, interest and fear, in this order. Emotional diversity was highly context‐specific, with significantly different emotional identity, dispersion and extremization across the six contexts of encounters. Most variance in attitudes was explained by emotional factors alone (28%) and the best model including all three groups of predictors (emotional, individual and regional factors) explained 57% of the variance. The strongest effects of emotional states on attitudes were those of anger and joy. Fear had only half the effect of joy on attitudes. Synthesis and applications: Our results highlight the importance and context‐specificity of emotional diversity for human‐carnivore coexistence. Complementary to previous studies focusing on single emotions and on decontextualized emotional dispositions, quantifying diverse, context‐dependent emotional states can be helpful to improve decision‐making in three different ways: (i) address relevant contexts triggering anger, which is a feeling rooted in perceived injustice, (ii) reduce emotional biases involving fear of carnivores given the extremely low probability of risks to human life and (iii) promote positive emotions like joy to better reflect costs and benefits of sharing landscapes with large carnivores. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Biodiversity monitoring is undergoing a revolution, with fauna observation data being increasingly gathered continuously over extended periods, through sensors like camera traps and acoustic recorders, or via opportunistic observations. These data are often analysed with discrete‐time ecological models, requiring the transformation of continuously collected data into arbitrarily chosen, non‐independent discrete‐time intervals. To overcome this issue, ecologists are increasingly turning to the existing continuous‐time models in the literature. Closer to the real detection process, they are lesser known than discrete‐time models, not always easily accessible and can be more complex. Focusing on occupancy models, a type of species distribution models, we asked ourselves: Should we dedicate time and effort to learning and using these continuous‐time models, or can we go on using discrete‐time models? We conducted a comparative simulation study using data generated within a continuous‐time framework. We assessed the performance of five static occupancy models with varying detection processes: discrete detection/non‐detection process, discrete count process, continuous‐time Poisson process and two types of modulated Poisson processes. Our goal was to assess their abilities to estimate occupancy probability with continuously collected data. We applied all models to empirical lynx data as an illustrative example. In scenarios with easily detectable animals, we found that all models accurately estimated occupancy. All models reached their limits with highly elusive animals. Variation in discretisation intervals had minimal impact on the discrete models' capacity to estimate occupancy accurately. Our study underscores that opting for continuous‐time models with an increased number of parameters, aiming to get closer to the sensor detection process, may not offer substantial advantages over simpler models when the sole aim is to accurately estimate occupancy. Model choice can thus be driven by practical considerations such as data availability or implementation time. However, occupancy models can encompass goals beyond estimating occupancy probability. Continuous‐time models, particularly those considering temporal variations in detection, can offer valuable insights into specific species behaviour and broader ecological inquiries. We hope that our findings offer valuable guidance for researchers and practitioners working with continuously collected data in wildlife monitoring and modelling.

Abstract Social networks are tied to population dynamics; interactions are driven by population density and demographic structure, while social relationships can be key determinants of survival and reproductive success. However, difficulties integrating models used in demography and network analysis have limited research at this interface. We introduce the R package genNetDem for simulating integrated network–demographic datasets. It can be used to create longitudinal social network and/or capture–recapture datasets with known properties. It incorporates the ability to generate populations and their social networks, generate grouping events using these networks, simulate social network effects on individual survival, and flexibly sample these longitudinal datasets of social associations. By generating co‐capture data with known statistical relationships, it provides functionality for methodological research. We demonstrate its use with case studies testing how imputation and sampling design influence the success of adding network traits to conventional Cormack–Jolly–Seber (CJS) models. We show that incorporating social network effects into CJS models generates qualitatively accurate results, but with downward‐biased parameter estimates when network position influences survival. Biases are greater when fewer interactions are sampled or fewer individuals observed in each interaction. While our results indicate the potential of incorporating social effects within demographic models, they show that imputing missing network measures alone is insufficient to accurately estimate social effects on survival, pointing to the importance of incorporating network imputation approaches. genNetDem provides a flexible tool to aid these methodological advancements and help researchers testing other sampling considerations in social network studies.

Abstract To document and halt biodiversity loss, monitoring, quantifying trends and assessing management and conservation strategies on wildlife populations and communities are crucial steps. With increasing technological innovations, more and more data are collected and new quantitative methods are constantly developed. These rapid developments come with an increasing need for analytical skills, which are hardly accessible to managers. On the other hand, researchers spend more and more time on research grant applications and administrative tasks, which leaves fewer opportunities for knowledge transfer. This situation tends to increase the gap between researchers and managers. Here, we illustrate how to fill this gap by presenting two long‐term collaborations between a research unit—Centre for Functional and Evolutionary Ecology; CEFE—and a national agency—French Biodiversity Agency; OFB. The first example is a collaboration providing statistical support to national parks for the design and implementation of scientific monitoring protocols. It relies on the recruitment of a research engineer funded by OFB and physically based at CEFE, who works closely with OFB and managers. The second example is a collaboration on the management of large carnivores. For more than 10 years, it has involved several PhD students and post‐doctoral fellows co‐supervised by CEFE and OFB, and has recently resulted in the recruitment of a permanent OFB researcher who works half‐time at CEFE and half‐time at OFB. These case studies illustrate the modalities of collaborative work between public institutions acting at different levels of biodiversity conservation for the co‐construction of research agendas and the exchange of knowledge. These collaborations also bring out some challenges. Inter‐knowledge and mutual learning remain difficult at scales larger than that of the teams concerned. The staff working at this interface needs to possess good listening skills, respect all partners' needs and demonstrate flexibility. Knowledge exchanges require time, thus reducing productivity according to quantitative metrics such as scientific publications or institutional reports. These collaborations can therefore be difficult to assume socially, and remain tenuous because they rely on a good understanding of the differences in governance of the various partners. Based on our experience, success is favoured by long‐term and close relationships, and by co‐construction of projects at early stage. Sharing a space (i.e. office or building) facilitates face‐to‐face interactions during planned work sessions and casual meetings that build up a shared scientific culture and mutual trust.

Abstract Few empirical studies have described social‐ecological systems (SESs) in transition. Some studies focused on external drivers that impact the SES and communities' responses to adapt to changes, including economic, land and conservation policies. Others have considered the effect of social and cultural changes on communities' capacity to sustain their activities. While sociocultural changes are increasingly common through globalization and world‐wide economic development, there is an urgent need to better understand and document how these changes affect individual and community agency to adapt or transform a system that is facing a combination of powerful internal and external forces. The human–Asian elephant relationship appears particularly illustrative of a complex SES because of the dual status of the elephant being wild or under human care, and the entanglement of ecological, cultural, social and economic dimensions. The ongoing and rapid political, socio‐economic and environmental changes occurring in Laos for the last decades have strongly affected this relationship. We conducted an ethnological survey to assess how the SES has evolved in Laos and its consequences for human‐wild‐captive elephant interactions and elephant handling practices. We show that in the 1990s, the SES was based on the principles of common access to natural resources and social control over nature and spirits, and led to a form of elephant handling with close interactions between captive and wild elephants. Husbandry practices then could be likened to pastoralism as a mode of production associated with a mode of relation close to seasonal freedom. Since the turn of the present century, the commodification of nature and of increasingly divided access to natural resources led eventually to the segregation of wild elephants and captivity of their working conspecifics. With the intensification of workload, owners switched to a ranching‐like economy, based on the accumulation of monetary capital from the employment of elephants in logging or tourism. We discuss how the combination of external drivers, such as economic liberalization, land and conservation policies, and internal drivers linked to sociocultural changes could affect a SES in transition, leading to a fading interest of the new generation in their family heritage. A free Plain Language Summary can be found within the Supporting Information of this article.

Abstract Optimizing the effect of management practices on weed population dynamics is challenging due to the difficulties in inferring demographic parameters in seed banks and their response to disturbance. Here, we used a long‐term plant survey between 2006 and 2012 in 46 French vineyards and quantified the effects of management practices (tillage, mowing, and herbicide) on colonization, germination, and seed survival of 30 weed species in relation to their seed mass. To do so, we used a recent statistical approach to reliably estimate demographic parameters for plant populations with a seed bank using time series of presence–absence data, which we extended to account for interspecies variation in the effects of management practices on demographic parameters. Our main finding was that when the level of disturbance increased (i.e., in plots with a higher number of herbicides, tillage, or mowing treatments), colonization success and survival in large‐seeded species increased faster than in small‐seeded species. High disturbance through tillage increased survival in the seed bank of species with high seed mass. The application of herbicides increased germination, survival, and colonization probabilities of species with high seed mass. Mowing, representing habitats more competitive for light, increased the survival of species with high seed mass. Overall, the strong relationships between the effects of management practices and seed mass provide an indicator for predicting the dynamics of weed communities under disturbance.

Reproductive senescence is ubiquitous in mammals. However, patterns of senescence vary across reproductive traits, even within populations, perhaps because of differences in selection pressures, physiological constraints, and responses to environmental conditions. We investigated reproductive senescence in wild female polar bears (Ursus maritimus), using 31 years of capture-recapture data from the Svalbard area. We studied the influence of environmental conditions on age-specific litter production and litter size using generalized linear mixed models. Further, using a capture-recapture model that handles the dependency between vital rates of individuals belonging to the same family unit, we assessed maternal-age-related changes in first year cub and litter survival. We provide clear evidence for reproductive senescence in female polar bears. Litter production and litter size peaked in middle-aged females and declined sharply afterward. By contrast cub and litter survival did not decline after prime age. We found no evidence of terminal investment. The reproductive output of all females was affected by sea-ice conditions during the previous year and the Arctic Oscillation, with some effects differing greatly between age groups. Old females were affected the most by environmental conditions. Our results suggest that the decline in reproductive output is a combination of fertility and body-condition senescence, with a weak contribution of maternal-effect senescence, possibly due to benefits of experience. Further, as predicted by evolutionary theory, senescence appears to be a consequence of failures in early stages of the reproductive cycle rather than in late stages, and environmental variation affected old females more than prime-aged females. Our study emphasizes the need to study several reproductive traits and account for environmental variation when investigating reproductive senescence. Differences in senescence patterns across reproductive traits should be interpreted in light of evolutionary theory and while considering underlying physiological drivers.

Abstract In species providing extended parental care, one or both parents care for altricial young over a period including more than one breeding season. We expect large parental investment and long‐term dependency within family units to cause high variability in life trajectories among individuals with complex consequences at the population level. So far, models for estimating demographic parameters in free‐ranging animal populations mostly ignore extended parental care, thereby limiting our understanding of its consequences on parents and offspring life histories. We designed a capture–recapture multievent model for studying the demography of species providing extended parental care. It handles statistical multiple‐year dependency among individual demographic parameters grouped within family units, variable litter size, and uncertainty on the timing at offspring independence. It allows for the evaluation of trade‐offs among demographic parameters, the influence of past reproductive history on the caring parent's survival status, breeding probability, and litter size probability, while accounting for imperfect detection of family units. We assess the model performance using simulated data and illustrate its use with a long‐term dataset collected on the Svalbard polar bears (Ursus maritimus). Our model performed well in terms of bias and mean square error and in estimating demographic parameters in all simulated scenarios, both when offspring departure probability from the family unit occurred at a constant rate or varied during the field season depending on the date of capture. For the polar bear case study, we provide estimates of adult and dependent offspring survival rates, breeding probability, and litter size probability. Results showed that the outcome of the previous reproduction influenced breeding probability. Overall, our results show the importance of accounting for i) the multiple‐year statistical dependency within family units, ii) uncertainty on the timing at offspring independence, and iii) past reproductive history of the caring parent. If ignored, estimates obtained for breeding probability, litter size, and survival can be biased. This is of interest in terms of conservation because species providing extended parental care are often long‐living mammals vulnerable or threatened with extinction.

In an era of increasing human pressure on nature, understanding the spatiotemporal patterns of wildlife relative to human disturbance can inform conservation efforts, especially for large carnivores. We examined the temporal activity and spatial patterns of wolves and eight sympatric mammals at 71 camera trap stations in Greece. Grey wolves temporally overlapped the most with wild boars (Δ = 0.84) and medium-sized mammals (Δ > 0.75), moderately with brown bears (Δ = 0.70), and least with roe deer (Δ = 0.46). All wild mammals were mainly nocturnal and exhibited low temporal overlap with human disturbance (humans, vehicles, livestock, and dogs; Δ = 0.18–0.36), apart from roe deer, which were more diurnal (Δ = 0.80). Six out of nine species increased their nocturnality at sites of high human disturbance, particularly roe deer and wolves. The detection of wolves was negatively associated with paved roads, the detection of roe deer was negatively associated with human disturbance, and the detection of wild boars was negatively associated with dogs. The detection of bears, boars, and foxes increased closer to settlements. Our study has applied implications for wolf conservation and human–wildlife coexistence.

Sharing space with large carnivores on a human-dominated continent like Europe results in multiple conflictful interactions with human interests, of which depredation on livestock is the most widespread. We conducted an analysis of the impact by all four European large carnivores on sheep farming in 10 European countries, during the period 2010–2015. We ran a hierarchical Simultaneous Autoregressive model, to assess the influence of several ecological factors on the reported depredation levels. About 35,000 (SD = 4110) sheep kills were compensated in the ten countries as caused by large carnivores annually, representing 0.5% of the total sheep stock. Of them, 45% were recognized as killed by wolves, 24% by wolverines, 19% by lynx and 12% by bears. We found a positive relationship between wolf distribution and the number of compensated sheep, but not for the other three species. Depredation levels were lower in the areas where large carnivore presence has been continuous compared to areas where they disappeared and returned in the last 50 years. Our study shows that a few large carnivores can produce high damage, when the contribution of environmental, social, and economic systems predisposes for it, whereas large populations can produce a limited impact when the same components of the system reduce the probability that depredations occur. Time of coexistence plays in favour of a progressive reduction in the associated costs, provided that the responsible agencies focus their attention both on compensation and co-adaptation.

Abstract Obtaining estimates of animal population density is a key step in providing sound conservation and management strategies for wildlife. For many large carnivores however, estimating density is difficult because these species are elusive and wide‐ranging. Here, we focus on providing the first density estimates of the Eurasian lynx (Lynx lynx) in the French Jura and Vosges mountains. We sampled a total of 413 camera trapping sites (with two cameras per site) between January 2011 and April 2016 in seven study areas across seven counties of the French Jura and Vosges mountains. We obtained 592 lynx detections over 19,035 trap days in the Jura mountains and 0 detection over 6,804 trap days in the Vosges mountains. Based on coat patterns, we identified a total number of 92 unique individuals from photographs, including 16 females, 13 males, and 63 individuals of unknown sex. Using spatial capture–recapture (SCR) models, we estimated abundance in the study areas between 5 (SE = 0.1) and 29 (0.2) lynx and density between 0.24 (SE = 0.02) and 0.91 (SE = 0.03) lynx per 100 km2. We also provide a comparison with nonspatial density estimates and discuss the observed discrepancies. Our study is yet another example of the advantage of combining SCR methods and noninvasive sampling techniques to estimate density for elusive and wide‐ranging species, like large carnivores. While the estimated densities in the French Jura mountains are comparable to other lynx populations in Europe, the fact that we detected no lynx in the Vosges mountains is alarming. Connectivity should be encouraged between the French Jura mountains, the Vosges mountains, and the Palatinate Forest in Germany where a reintroduction program is currently ongoing. Our density estimates will help in setting a baseline conservation status for the lynx population in France.

Abstract To successfully perform their long‐distance migrations, migratory birds require sites along their migratory routes to rest and refuel. Monitoring the use of so‐called stopover and staging sites provides insights into (a) the timing of migration and (b) the importance of a site for migratory bird populations. A recently developed Bayesian superpopulation model that integrates mark–recapture data and ring density data enabled the estimation of stopover timing, duration, and population size. Yet, this model did not account for heterogeneity in encounter (p) and staying (ϕ) probabilities. Here we extended the integrated superpopulation model by implementing finite mixtures to account for heterogeneity in p and ϕ. We used simulations and real data (from 2009–2016) on red knots Calidris canutus, mostly of the subspecies piersmai, staging in Bohai Bay, China, during spring migration to (a) show the importance of accounting for heterogeneity in encounter and staying probabilities to get unbiased estimates of stopover timing, duration, and numbers of migratory birds at staging sites and (b) get accurate stopover parameter estimates for a migratory bird species at a key staging site that is threatened by habitat destruction. Our simulations confirmed that heterogeneity in p affected stopover parameter estimates more than heterogeneity in ϕ, especially when most birds had low p. Bias was particularly severe when most birds had both low ϕ and p. Bias was largest for population size, intermediate for stopover duration and negligible for stopover timing. A total of 50,000–100,000 red knots were estimated to annually stop for 5–9 days in Bohai Bay between 10 and 30 May. This shows the key importance of this staging site for this declining species. There were no clear changes in stopover parameters over time, although stopover population size was substantially lower in 2016 than in preceding years. Our study shows the importance of accounting for heterogeneity in both encounter and staying probabilities for accurately estimating stopover duration and population size and provides an appropriate modeling framework.

Traffic hijacking over the Internet has become a frequent incident over the last two decades. From minor inconveniences for casual users to massive leaks of governmental data, these events cover an unprecedently large spectrum. Many hijackings are presumed to be caused by unfortunate routing mistakes, but a well-organized attacker could set up a long-term stealthy relay, accessing critical traffic metadata, despite suitable encryption schemes. While many studies focus on the mitigation of known attacks, we choose to design a complete detection method regardless of the attacker’s strategy. We propose a two-party cryptographic protocol for detecting traffic hijacking over the Internet. Our proposal relies on a distance-bounding mechanism that performs interactive authentication with a “Challenge–Response” exchange, and measures the round-trip time of packets to decide whether an attack is ongoing. Our construction is supported by worldwide experiments on communication time between multiple nodes, allowing us to both demonstrate its applicability and evaluate its performance. Over the course of this paper, we demonstrate our protocol to be efficient—itrequires only two cryptographic operations per execution inducing negligible workload for users and very few loss of throughput, scalable—no software updates are required for intermediate network nodes, routing protocol independent—this means that any future update of the route selection process will not induce changes on our scheme, and network friendly—the added volume of transiting data is only about 1.5%.

Abstract The estimation of population size remains one of the primary goals and challenges in ecology and provides a basis for debate and policy in wildlife management. Despite the development of efficient noninvasive sampling methods and robust statistical tools to estimate abundance, the maintenance of field sampling is still subject to economic and logistic constraints. These can result in intentional or unintentional interruptions in sampling and cause gaps in data time series, posing a challenge to abundance estimation, and ultimately conservation and management decisions. We applied an open population spatial capture–recapture (OPSCR) model to simulations and a real‐life case study to test the reliability of abundance inference to interruptions in data collection. Using individual detections occurring over consecutive sampling occasions, OPSCR models allow the estimation of abundance while accounting for lack of demographic and geographic closure between occasions. First, we simulated sampling data with interruptions in field sampling of different lengths and timing and checked the performance of an OPSCR model in deriving abundance for species with slow and intermediate life‐history strategies. Next, we introduced artificial sampling interruptions of various magnitudes and timing to a five‐year noninvasive monitoring data set of wolverines (Gulo gulo) in Norway and quantified the consequences for OPSCR model predictions. Inferences from OPSCR models were reliable even with temporal interruptions in monitoring. Interruption did not cause systematic bias, but increased uncertainty. Interruptions occurring at occasions near the beginning and the end of the sampling period caused higher uncertainty. The loss in precision was more severe for species with a faster life‐history strategy. OPSCR allows monitoring studies to provide contiguous abundance estimates to managers, stakeholders, and policy makers even when data are noncontiguous. OPSCR models do not only help cope with unintentional interruptions during sampling but also offer opportunities for using intentional sampling interruptions during the design of cost‐effective population surveys.

Abstract Breeding dispersal is a key process of population structure and dynamics and is often triggered by an individual's breeding failure. In both colonial and territorial birds, reproductive success of conspecifics (RSc) can also lead individuals to change breeding sites after a failure on a site. Yet, few studies have simultaneously investigated the independent contribution of individual reproductive success (RSi) and of RSc on dispersal decision. Here, we develop a modeling framework to disentangle the effects of RSi and RSc on demographic parameters, while accounting for imperfect individual detection and other confounding factors such as age or dispersal behavior in the previous year. Using a 10‐year capture–recapture dataset composed of 1,595 banded tree swallows, we assessed the effects of nonmanipulated RSi and RSc on female breeding dispersal in this semicolonial passerine. Dispersal was strongly driven by RSi, but not by RSc. Unsuccessful females were 9.5–2.5 times more likely to disperse than successful ones, depending if they had dispersed or not in the previous year, respectively. Unsuccessful females were also three times less likely to be detected than successful ones. Contrary to theoretical and empirical studies, RSc did not drive the decision to disperse but influenced the selection of the following breeding site once dispersal had been initiated. Because detection of individuals was driven by RSi, which was positively correlated to RSc, assuming a perfect detection as in previous studies may have lead us to conclude that RSc affected dispersal patterns, yet our approach corrected for this bias. Overall, our results suggest that the value and use of RSc as public information to guide dispersal decisions are likely dictated by multiple ecological determinants, such as landscape structure and extent, if this cue is indeed used.

Anthropogenic hybridization is widely perceived as a threat to the conservation of biodiversity. Nevertheless, to date, relevant policy and management interventions are unresolved and highly convoluted. While this is due to the inherent complexity of the issue, we hereby hypothesize that a lack of agreement concerning management goals and approaches, within the scientific community, may explain the lack of social awareness on this phenomenon, and the absence of effective pressure on decision-makers. By focusing on wolf x dog hybridization in Europe, we hereby (a) assess the state of the art of issues on wolf x dog hybridization within the scientific community, (b) assess the conceptual bases for different viewpoints, and (c) provide a conceptual framework aiming at reducing the disagreements. We adopted the Delphi technique, involving a three-round iterative survey addressed to a selected sample of experts who published at Web of Science listed journals, in the last 10 years on wolf x dog hybridization and related topics. Consensus was reached that admixed individuals should always be defined according to their genetic profile, and that a reference threshold for admixture (i.e., q-value in assignment tests) should be formally adopted for their identification. To mitigate hybridization, experts agreed on adopting preventive, proactive and, when concerning small and recovering wolf populations, reactive interventions. Overall, experts' consensus waned as the issues addressed became increasingly practical, including the adoption of lethal removal. We suggest three non-mutually exclusive explanations for this trend: (i) value-laden viewpoints increasingly emerge when addressing practical issues, and are particularly diverging between experts with different disciplinary backgrounds (e.g., ecologists, geneticists); (ii) some experts prefer avoiding the risk of potentially giving carte blanche to wolf opponents to (illegally) remove wolves, based on the wolf x dog hybridization issue; (iii) room for subjective interpretation and opinions result from the paucity of data on the effectiveness of different management interventions. These results have management implications and reveal gaps in the knowledge on a wide spectrum of issues related not only to the management of anthropogenic hybridization, but also to the role of ethical values and real-world management concerns in the scientific debate.

Estimating eco-epidemiological parameters in free-ranging populations can be challenging. As known individuals may be undetected during a field session, or their health status uncertain, the collected data are typically “imperfect”. Multi-event capture-mark-recapture (MECMR) models constitute a substantial methodological advance by accounting for such imperfect data. In these models, animals can be “undetected” or “detected” at each time step. Detected animals can be assigned an infection state, such as “susceptible” (S), “infected” (I), or “recovered” (R), or an “unknown” (U) state, when for instance no biological sample could be collected. There may be heterogeneity in the assignment of infection states, depending on the manifestation of the disease in the host or the diagnostic method. For example, if obtaining the samples needed to prove viral infection in a detected animal is difficult, this can result in a low chance of assigning the I state. Currently, it is unknown how much uncertainty MECMR models can tolerate to provide reliable estimates of eco-epidemiological parameters and whether these parameters are sensitive to heterogeneity in the assignment of infection states. We used simulations to assess how estimates of the survival probability of individuals in different infection states and the probabilities of infection and recovery responded to (1) increasing infection state uncertainty (i.e., the proportion of U) from 20 to 90%, and (2) heterogeneity in the probability of assigning infection states. We simulated data, mimicking a highly virulent disease, and used SIR-MECMR models to quantify bias and precision. For most parameter estimates, bias increased and precision decreased gradually with state uncertainty. The probabilities of survival of I and R individuals and of detection of R individuals were very robust to increasing state uncertainty. In contrast, the probabilities of survival and detection of S individuals, and the infection and recovery probabilities showed high biases and low precisions when state uncertainty was >50%, particularly when the assignment of the S state was reduced. Considering this specific disease scenario, SIR-MECMR models are globally robust to state uncertainty and heterogeneity in state assignment, but the previously mentioned parameter estimates should be carefully interpreted if the proportion of U is high.

This study describes two longitudinal serological surveys of European Bat Lyssavirus type 1 (EBLV-1) antibodies in serotine bat (Eptesicus serotinus) maternity colonies located in the North-East of France. This species is currently considered as the main EBLV-1 reservoir. Multievent capture-recapture models were used to determine the factors influencing bat rabies transmission as this method accounts for imperfect detection and uncertainty in disease states. Considering the period of study, analyses revealed that survival and recapture probabilities were not affected by the serological status of individuals, confirming the capacity of bats to be exposed to lyssaviruses without dying. Five bats have been found with EBLV-1 RNA in the saliva at the start of the study, suggesting they were caught during virus excretion period. Among these bats, one was interestingly recaptured one year later and harbored a seropositive status. Along the survey, some others bats have been observed to both seroconvert (i.e. move from a negative to a positive serological status) and serorevert (i.e. move from a positive to a negative serological status). Peak of seroprevalence reached 34% and 70% in site A and B respectively. On one of the 2 sites, global decrease of seroprevalence was observed all along the study period nuanced by oscillation intervals of approximately 2-3 years supporting the oscillation infection dynamics hypothesized during a previous EBLV-1 study in a Myotis myotis colony. Seroprevalence were affected by significantly higher seroprevalence in summer than in spring. The maximum time observed between successive positive serological statuses of a bat demonstrated the potential persistence of neutralizing antibodies for at least 4 years. At last, EBLV-1 serological status transitions have been shown driven by age category with higher seroreversion frequencies in adults than in juvenile. Juveniles and female adults seemed indeed acting as distinct drivers of the rabies virus dynamics, hypothesis have been addressed but their exact role in the EBLV-1 transmission still need to be specified.

Abstract Theory recognizes that a treatment of the detection process is required to avoid producing biased estimates of population rate of change. Still, one of three monitoring programmes on animal or plant populations is focused on simply counting individuals or other fixed visible structures, such as natal dens, nests, tree cavities. This type of monitoring design poses concerns about the possibility to respect the assumption of constant detection, as the information acquired in a given year about the spatial distribution of reproductive sites can provide a higher chance to detect the species in subsequent years. We developed an individual‐based simulation model, which evaluates how the accumulation of knowledge about the spatial distribution of a population process can affect the accuracy of population growth rate estimates, when using simple count‐based indices. Then, we assessed the relative importance of each parameter in affecting monitoring performance. We also present the case of wolverines (Gulo gulo) in southern Scandinavia as an example of a monitoring system with an intrinsic tendency to accumulate knowledge and increase detectability. When the occupation of a nest or den is temporally autocorrelated, the monitoring system is prone to increase its knowledge with time. This happens also when there is no intensification in monitoring effort and no change in the monitoring conditions. Such accumulated knowledge is likely to increase detection probability with time and can produce severe bias in the estimation of the rate and direction of population change over time. We recommend that a systematic sampling of the population process under study and an explicit treatment of the underlying detection process should be implemented whenever economic and logistical constraints permit, as failure to include detection probability in the estimation of population growth rate can lead to serious bias and severe consequences for management and conservation.

While the Mediterranean Sea has been designated as a Global Biodiversity Hotspot, assessments of cetacean population abundance are lacking for large portions of the region, particularly in the southern and eastern basins. The challenges and costs of obtaining the necessary data often result in absent or poor abundance information. We applied capture-recapture models to estimate abundance, survival and temporary emigration of odontocete populations within a 2,400 km2 semi-enclosed Mediterranean bay, the Gulf of Corinth. Boat surveys were conducted in 2011-2015 to collect photo-identification data on striped dolphins Stenella coeruleoalba, short-beaked common dolphins Delphinus delphis (always found together with striped dolphins in mixed groups) and common bottlenose dolphins Tursiops truncatus, totaling 1,873 h of tracking. After grading images for quality and marking distinctiveness, 23,995 high-quality photos were included in a striped and common dolphin catalog, and 2,472 in a bottlenose dolphin catalog. The proportions of striped and common dolphins were calculated from the photographic sample and used to scale capture-recapture estimates. Best-fitting robust design capture-recapture models denoted no temporary emigration between years for striped and common dolphins, and random temporary emigration for bottlenose dolphins, suggesting different residency patterns in agreement with previous studies. Average estimated abundance over the five years was 1,331 (95% CI 1,122-1,578) striped dolphins, 22 (16-32) common dolphins, 55 (36-84) "intermediate" animals (potential striped x common dolphin hybrids) and 38 (32-46) bottlenose dolphins. Apparent survival was constant for striped, common and intermediate dolphins (0.94, 95% CI 0.92-0.96) and year-dependent for bottlenose dolphins (an average of 0.85, 95% CI 0.76-0.95). Our work underlines the importance of long-term monitoring to contribute reliable baseline information that can help assess the conservation status of wildlife populations.

Seabirds are affected by changes in the marine ecosystem. The influence of climatic factors on marine food webs can be reflected in long-term seabird population changes. We modelled the survival and recruitment of the Mediterranean storm petrel (Hydrobates pelagicus melitensis) using a 21-year mark-recapture dataset involving almost 5000 birds. We demonstrated a strong influence of prebreeding climatic conditions on recruitment age and of rainfall and breeding period conditions on juvenile survival. The results suggest that the juvenile survival rate of the Mediterranean subspecies may not be negatively affected by the predicted features of climate change, i.e., warmer summers and lower rainfall. Based on considerations of winter conditions in different parts of the Mediterranean, we were able to draw inferences about the wintering areas of the species for the first time.

BackgroundData collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation.Methodology/principal findingsThe aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength.Conclusion/significanceThe state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Great apes are threatened with extinction, but precise information about the distribution and size of most populations is currently lacking. We conducted orangutan nest counts in the Malaysian state of Sabah (North Borneo), using a combination of ground and helicopter surveys, and provided a way to estimate the current distribution and size of the populations living throughout the entire state. We show that the number of nests detected during aerial surveys is directly related to the estimated true animal density and that a helicopter is an efficient tool to provide robust estimates of orangutan numbers. Our results reveal that with a total estimated population size of about 11,000 individuals, Sabah is one of the main strongholds for orangutans in North Borneo. More than 60% of orangutans living in the state occur outside protected areas, in production forests that have been through several rounds of logging extraction and are still exploited for timber. The role of exploited forests clearly merits further investigation for orangutan conservation in Sabah.

We assessed spatial and temporal variation in reporting probability of banded Greater Snow Geese (Chen caerulescens atlantica) shot by hunters in eastern North America and evaluated potential residual biases in kill rate estimation. Adult Greater Snow Geese were marked with reward (value: US$10, $20, $30, $50, and $100) and standard bands ($0, control) in the Canadian Arctic from 2003 to 2005. We used a spatially explicit multinomial model based on 200 direct recoveries from 4256 banded geese to estimate reporting rate and harvest rate. We found that reporting rate for standard bands varied over time whereas harvest rate was higher in Canada than in the U.S. The reporting probability increased from 0.40 ± 0.11 in the first year of the study to 0.82 ± 0.14 and 0.84 ± 0.13 the second and third years, respectively. Overall, these reporting rates are higher than two previous estimates for this population, which leads to lower estimates of kill rate. However, the large annual differences in reporting rates found in this study lead to uncertainty in the estimation of kill rate. We suggest that the increase in reporting rate in the last two year of the study may be due to the dissemination of information among hunters regarding the presence of reward bands on birds, resulting in increased reporting rate for all bands. This raises issues about the need to adequately inform the public in such large-scale studies to avoid undesirable temporal trends over the course of the study.