Highly pathogenic avian influenza (HPAI) poses major conservation issues worldwide. In France, recurrent outbreaks of HPAI (H5) in wild birds have occurred since 2020, yet our understanding of the disease's dynamics have remained limited. By leveraging data from the national wildlife health surveillance network (SAGIR), we conducted a spatiotemporal analysis of the HPAI outbreaks in wild birds. Between 2016 and 2022, two different spatiotemporal patterns of the disease were observed in France: sporadic episodes of the virus in four episodes, forming either isolated cases or self-limited clusters at the maximum and epizootic circulation in 2022. During sporadic circulation episodes, observations were concentrated in well-defined spatiotemporal clusters with low prevalence. Those self-limited clusters, places where the density of positive events was substantially larger than in the rest of France, reflected three epidemiologic patterns: 1) recurrent clusters linked to migration and waterfowl habitats; 2) clusters involving synanthropic species in diverse areas and related to outbreaks in poultry farms; and 3) outbreaks in colonial bird species, observed once in 2020 and once in 2022, involving Red Knots (Calidris canutus) and Eurasian Griffon Vultures (Gyps fulvus), respectively. Beginning in summer 2022, the epizootic episode, characterized by a high prevalence along the northern French coasts, involved Northern Gannets (Morus bassanus) and Laridae. During this epizootic, cluster boundaries were far less well-defined. The ecology of the affected bird species and the characteristics of the circulating viral strains (often adapted to these species) may explain this new spatiotemporal dynamic compared with previously observed sporadic circulation, driven mainly through migration. Our study provides a better understanding of the dynamics of HPAI outbreaks in wild birds; nevertheless, knowledge gaps remain, and improved surveillance of HPAI in wild birds is still needed.

Long-term ecological monitoring is essential for tracking biodiversity trends and guiding conservation policy. However, these programs often experience changes in site coverage over time, through both the loss of existing sites and the addition of new ones. When this loss is non-random-corresponding to a "Missing Not At Random" (MNAR) mechanism, such as preferential abandonment of low-diversity or degraded sites-it can introduce substantial bias in population trend estimates. Although well documented in theory and simulations, this issue remains poorly supported by empirical evidence. Using 20 years of data from a national grassland bird monitoring program in France, we assessed whether site loss biased estimates of temporal change in hay meadow cover, grassland bird abundance, and species richness. Sites retained long-term exhibited higher initial values for all three variables, whereas early-abandoned sites started with lower hay meadow cover and biodiversity and experienced stronger declines, particularly in abundance. Between the first monitoring year and 2024, bird abundance declined by 19% at long-term sites but by more than 40% at early-abandoned ones. Our results reveal that well-preserved hay meadow sites were preferentially retained, while degraded sites were more likely to be abandoned. This selective process leads to systematic underestimation of national biodiversity trends when analyses rely only on long-term sites. To address this, we developed a simple correction method based on resampling of all initially monitored sites. This study provides one of the first empirical demonstrations and quantifications of MNAR bias in biodiversity monitoring. It highlights the need to explicitly account for site loss and selection effects when interpreting long-term trends and designing conservation strategies.

Diagnosing the cause of peracute death in wildlife is challenging, particularly when necropsy, histopathology, and ancillary testing yield nonspecific results. Biochemistry could provide pathophysiologic information on the death process that is unobtainable with morphologic methods. To evaluate the impact of postmortem delay on the quality of blood biochemical analysis, blood samples were collected from 20 wild boars (Sus scrofa) hunted in January 2018 in France. The body condition, age, and sex of each boar were recorded. Each animal was sampled once between the time of death and 6 h postmortem, with six boars sampled within the first hour, three boars sampled at each hour thereafter (hours 2-5), and two boars sampled at 6 h postmortem. Samples were promptly sent to the laboratory, centrifuged, and assessed for hemolysis before measurement of biochemical parameters using a wet chemistry analyzer. The first component from a principal component analysis was used as a quality index of the biochemical composition of the blood. This index strongly correlated positively with sodium and chloride and negatively with total proteins, alanine aminotransferase, fructosamine, and potassium. A segmented regression analysis indicated stability of blood quality for 2 h after death, followed by a linear decrease. Practically, blood samples drawn within 2 h after death maintained overall quality. This exploratory study should be expanded with evaluations of changes of individual metabolites over time.

Expanding populations of large herbivores compromise tree regeneration in many Northern Hemisphere forests. Browsing pressure vary spatially as large herbivores forage through the landscape, according to food availability. Intra-forest meadows attract red deer (Cervus elaphus L.) as they offer substantial food resources. However, the effect of intra-forest meadows on seedling browsing remains unexplored. Using a dataset of seedlings abundance and browsing observation from 2006 to 2024 in a study area of North-Eastern France, we modelled the browsing probability of silver fir (Abies alba Mill.), Norway spruce (Picea abies (L.) H. Karst), and beech (Fagus sylvatica L.) seedlings according to the distance to intra-forest meadows. We compared the current browsing level to simulated levels where seedlings would be distant from intra-forest meadows. We considered whether species availability, bramble availability, red deer abundance index, and forest fruits abundance index could influence the browsing of seedlings. We did not identify an effect of intra-forest meadows on the browsing probability of Norway spruce and beech. The proximity to intra-forest meadows reduced silver fir browsing probability when silver fir cover on the plot did not exceed 12.5% and when forest fruits were abundant on the study site. The browsing probability of silver fir was minimal at a distance of about 366 m (CI95% = 249 - 434 m) from intraforest meadows. The results of this case study indicate that proximity to intra-forest meadows could influence some tree species browsing intensity and spatial distribution but it does not consistently lower browsing pressure on forest regeneration.

Abstract Camera traps have been widely used in the past decade to monitor the abundance of unmarked animal populations. Most estimation methods rely either on the number of times animals pass through the detection zones, like random encounter models (REM), or on the number of capture occasions in a time‐lapse program when animals were seen on the pictures, like the instantaneous sampling (IS) approach. Yet, the ability of these two popular method classes to both reliably detect population trends and estimate population size has rarely been evaluated. We filled this gap by simulating a setup of either 100 or 25 camera traps randomly distributed on a 2600‐ha area (respectively ≈4 and 1 trap/km2), along with the movements of a fictional population of 300 roe deer (Capreolus capreolus). Simulations were informed by field data on habitat, habitat selection, and activity patterns of GPS‐monitored roe deer. Under idealized conditions (e.g., perfect knowledge of day range and visibility), both IS and REM provided unbiased population estimates, though uncertainty remained substantial (CV from 15% to 30% with 4 and 1 trap/km2, respectively). However, our results show that neglecting imperfect detectability leads to severe biases in absolute density estimation. Moreover, despite idealized conditions and large sampling efforts, a simulated 20% population decline over 5 years went undetected by both approaches in 65%–75% of simulations at high trap density and 80% at low trap density. Testing other sampling strategies to improve sensitivity either led to an unchanged population size estimation precision (stratified sampling) or to biased estimated trends (sampling only in high‐quality habitats). Simulating animals with a 10 times larger home range led to miss the decline less frequently (5%– 40% at high trap density, 33%–67% at low trap density). These results suggest that the key metric for camera trap use is the average number of different traps visited per animal, which in turn depends on trap density, home‐range size, and space use heterogeneity. We provide an R package allowing the reader to reproduce these simulations, and carry out their own simulations.

The use of camera traps to monitor unmarked animal populations has expanded during the last decade, leading to the development of several density estimation methods. This plethora of methods may be confusing for the newcomer to the field. Some methods, such as the random encounter model, require the knowledge of the mean travel speed of the animals, while others, such as camera trap distance sampling, do not rely on such assumptions. Different methods, like instantaneous sampling, camera trap distance sampling, and the association model, rely on similar types of data, but do not seem identical. In this article, I explore the relationships between different density estimators, including the random encounter model, the random encounter and staying time model, the time in front of camera approach, the time-to-event model, camera-trap distance sampling, the association model, and the space-to-event model. I show how these different estimators are related under two simplifying assumptions (perfect detectability, and animals moving as molecules in an ideal gas). I develop a map of mathematical relationships between these estimators. This framework helps readers understand how these methods are interconnected, providing a clearer conceptual foundation for selecting and implementing density estimation studies.

Although accounting for the sequential nature of the predation is useful to better understand predator-prey interactions, this approach has rarely been adopted in the context of large carnivore attacks on livestock. Here we developed a model of wolf (Canis lupus) predation that integrated its sequential nature and the effects of covariates. We used over 300 wolf observations obtained by thermal infrared cameras in hotspots of wolf predation on sheep in the French Alps to quantify the impact of the presence of livestock guarding dogs (LGDs), fencing and other environmental factors on the conditional probabilities of wolf approach and attack. Our data show that most often, only one or two wolves appear to be involved in predation on sheep, suggesting that the predator is unlikely to overwhelm the LGDs by sheer numbers. However, we detected no effect of LGDs or fencing on the predation sequence, possibly because observations of wolf behaviour were brief and subject to high variability among observers and years. Observers did not systematically record data and sometimes scored contradictory information. A posteriori power analysis revealed that the effects of LGDs or fencing would have been detected in our data if they halved and one-third the probability of approach and attack, respectively. We cannot draw general conclusions about the effectiveness of LGDs or fencing because our data were not random but collected in hotspots only. Nevertheless, our approach can be used to improve assessment of the effectiveness of preventive methods, a vital task for the conservation of large carnivores.

Usutu virus (USUV) was first isolated in Africa in 1959 and has since spread to and through Europe with a typical enzootic mosquito-bird cycle. In France, it was first detected in birds in 2015, but during summer 2018 the spread of USUV was particularly significant throughout the country, killing mainly common blackbirds (Turdus merula) and to a lesser extent great grey owls (Strix nebulosa), among other captive and non-captive wild bird species. Previous studies of USUV in France have focused on reconstructing pathways of introduction, but not on structural aspects of virus spread within the country. Data (RT-PCR of geolocated dead birds) on this 2018 outbreak were collected through both an event-based wildlife network named SAGIR and the health surveillance of the French-speaking Association of Zoo Veterinarians (AFVPZ). In addition, common blackbird populations could be monitored through another network (REZOP). Statistical analysis (spatial, temporal, spatiotemporal and environmental determinants) of the SAGIR and AFVPZ network data helped to highlight the early appearance of separate large clusters of USUV cases in mid-July 2018, the subsequent diffusion into smaller and secondary clusters at the end of August 2018, and a meanwhile enlargement of the first clusters with an increase in the number of cases. High human density (top 10.5% densest areas in France) and wetland concentration (top 19.3% most likely wetland areas) were significant factors in USUV case locations. Using generalised additive mixed models on REZOP data, we also highlighted the decline in common blackbird population trends in areas with medium and even more with high USUV pressure (areas defined based on SAGIR-AFVPZ data) following the 2018 outbreak (respectively −7.4% [−11.4; −3.9]95% and −15.7% [−16.2; −9.1]95%). A large area (radius ∼150 km) in the centre and centre-west of France, and smaller areas in the south-east, north and north-east of France (each with a radius ∼ 50 km) were particularly affected. We conclude on the importance to work with synergistic networks to assess infection spread in wild bird species, as well as the negative impact of an emerging arbovirus. The responsiveness of such a network system could be improved by automating alerts.

The Sylvatub system is a national surveillance program established in 2011 in France to monitor infections caused by Mycobacterium bovis, the main etiologic agent of bovine tuberculosis, in wild species.This participatory program, involving both national and local stakeholders, allowed us to monitor the progression of the infection in three badger populations in clusters covering between 3222 km 2 and 7698 km 2 from 2013 to 2019.In each cluster, badgers were trapped and tested for M. bovis.Our first aim was to describe the dynamics of the infection in these clusters.We developed a Bayesian model of prevalence accounting for the spatial structure of the cases, the imperfect and variable sensitivity of the diagnostic tests, and the correlation of the infection status of badgers in the same commune caused by local factors (e.g., social structure and proximity to infected farms).This model revealed that the prevalence increased with time in one cluster (Dordogne/Charentes), decreased in the second cluster (Burgundy), and remained stable in the third cluster (Bearn).In all the clusters, the infection was strongly spatially structured, whereas the mean correlation between the infection status of the animals trapped in the same commune was negligible.Our second aim was to develop indicators for monitoring M. bovis infection by stakeholders of the program.We used the model to estimate, in each cluster, (i) the mean prevalence level at mid-period, and (ii) the proportion of the badger population that became infected in one year.We then derived two indicators of these two key quantities from a much simpler regression model, and we showed how these two indicators could be easily used to monitor the infection in the three clusters.We showed with simulations that these two simpler indicators were good approximations of these key quantities.

AbstractLow levels of essential mineral elements such as cobalt, copper, and iron, in organisms reduce immune function, increasing the chances of parasitic infection. This phenomenon has been demonstrated widely in domestic animals but rarely in wildlife. In this study, we used data from 7‐ to 9‐month‐old roe deer (Capreolus capreolus), living in two different populations facing contrasting environmental conditions (Trois‐Fontaines and Chizé), to investigate whether the parasitic and immunological statuses could be related to essential element status. Between 2016 and 2019, we collected feces to measure parasite burdens (gastrointestinal and pulmonary nematodes), blood to measure immunological parameters (globulins and white blood cells), and hair to assess the concentration of 11 essential elements (calcium [Ca], chromium [Cr], cobalt [Co], copper [Cu], iron [Fe], magnesium [Mg], manganese [Mn], potassium [K], molybdenum [Mo], selenium [Se], and zinc [Zn]). The results showed first heterogeneity in the individual phenotypes of the two populations. Roe deer with low body mass had high concentrations of all the essential elements (in particular, Ca, Fe, Cu, K, and Mn), a high parasitic burden, and high concentrations of globulins. An association between high concentrations of essential elements and a high parasite burden was found at the two study sites despite markedly different environmental conditions. A relationship between essential element concentrations and immune parameters was also detected, with more basophils and globulins being associated with high concentrations of essential trace elements (i.e., Ca, Fe, Cu, and, to a lesser extent, Se, Cr, and Zn). These results suggest that young individuals with low body mass and high parasitism may select feeding resources rich in mineral elements, which may improve their ability to control the infestation and/or mitigate the negative consequences of parasites by maintaining immune system functions.

Botulism in wild birds is a widespread and potentially lethal disease raising major conservation issues. Botulism is also of public health concern. Due to the action of botulinum neurotoxins, mostly produced by Clostridium botulinum , botulism can affect wild birds, livestock, and humans. This study is part of a project aimed at improving our understanding of the pathogenesis of botulism in wild avifauna, which is still poorly understood. Indeed, the prevalence and dynamics of C. botulinum in the digestive tract or in bird tissue, whether as intermittent carriage related to environmental contamination or as part of the normal avian microbiota, is still unknown. In this study, we specifically addressed the presence of a healthy carrier status of wild birds, and its role in outbreaks. To answer this question, we monitored the estimated prevalence of C. botulinum in wild birds through samples from banded and swabbed birds as well as from hunted bird organs. Our results do not support the hypothesis of a healthy carriage outside of outbreaks, which raises the question of the bioavailability of the bacterium and toxin in the environment. Finally, the gene encoding botulinum neurotoxin type E was detected in keel muscle from a hunted bird, showing that recommendations on the consumption of wild bird meat are needed following a botulism outbreak.

AbstractThe Sylvatub system is a national surveillance program established in 2011 in France to monitor infections caused byMycobacterium bovis, the main etiologic agent of bovine tuberculosis, in wild species. This participatory program, involving both national and local stakeholders, allowed us to monitor the progression of the infection in three badger populations in clusters covering between 3222 km2and 7698 km2from 2013 to 2019. In each cluster, badgers were trapped and tested forM. bovis. Our first aim was to describe the dynamics of the infection in these clusters. We developed a Bayesian model of prevalence accounting for the spatial structure of the cases, the imperfect and variable sensitivity of the diagnostic tests, and the correlation of the infection status of badgers in the same commune caused by local factors (e.g., social structure and proximity to infected farms). This model revealed that the prevalence increased with time in one cluster (Dordogne/Charentes), decreased in the second cluster (Burgundy), and remained stable in the third cluster (Bearn). In all the clusters, the infection was strongly spatially structured, whereas the mean correlation between the infection status of the animals trapped in the same commune was negligible. Our second aim was to develop indicators for monitoringM. bovisinfection by stakeholders of the program. We used the model to estimate, in each cluster, (i) the mean prevalence level at mid-period, and (ii) the proportion of the badger population that became infected in one year. We then derived two indicators of these two key quantities from a much simpler regression model, and we showed how these two indicators could be easily used to monitor the infection in the three clusters. We showed with simulations that these two simpler indicators were good approximations of these key quantities.

Brucellosis due to Brucella melitensis affects domestic and wild ruminants, as well as other mammals, including humans. Despite France being officially free of bovine brucellosis since 2005, two human cases of Brucella melitensis infection in the French Alps in 2012 led to the discovery of one infected cattle herd and of one infected population of wild Alpine ibex (Capra ibex). In this review, we present the results of 10 years of research on the epidemiology of brucellosis in this population of Alpine ibex. We also discuss the insights brought by research and expert assessments on the efficacy of disease management strategies used to mitigate brucellosis in the French Alps.

Essential trace elements play an important role in the development of optimal immune responses, in particular to fight a parasitic infection, as it has been demonstrated many times in domestic animals, but rarely in wildlife. The aim of this study was to assess whether trace element concentrations could be a factor influencing parasitic infection and immune phenotype in roe deer (Capreolus capreolus) using factor analyses. From 2016 to 2019, we collected data on 7-9 months-old roe deer to assess 11 trace element concentrations (e.g. Ca, Co, Cr, Cu, Fe, K, Mg, Mn, Mo, Se, Zn) in hair, parasite burden (gastro-intestinal and pulmonary nematodes), and immunological parameters (globulines and white blood cells) in two French populations with different ecological contexts (Trois-Fontaines and Chizé). We showed a heterogeneity of individual phenotypes, with clear gradients opposing animals with low body mass, high concentrations of all trace elements (in particular Ca, Fe, Cu, K, and Mn), high parasitic burden and high concentrations of globulins to animals with the opposite characteristics. The association between high concentration in essential trace elements and high parasite burden was found at the two study sites despite markedly different environmental conditions. A relationship between trace element concentrations and immunological parameters was also identified, with more basophils and globulins associated to high concentrations of essential trace elements (i.e. Ca, Fe, Cu and to a lesser extent Se, Cr and Zn). These results suggest primarily that high parasite burden could predispose young individuals with low body mass to select a diet with a higher proportion of high trace element feed to minimize the infection. They suggest also that young roe deer with higher trace element concentrations will have a more reactive immune system.

La brucellose à Brucella melitensis touche les ruminants domestiques et sauvages, ainsi que d’autres mammifères, dont les humains. Bien que la France soit officiellement indemne depuis 2005, deux cas humains reportés en Haute-Savoie en 2012 ont conduit à la découverte de l’infection dans un élevage bovin et chez les bouquetins des Alpes (Capra ibex) du massif du Bargy. Nous présentons dans cette synthèse les principales découvertes de ces dix dernières années sur le système brucellose-bouquetins. Nous discuterons également de l’apport de la recherche et de l’expertise sur l’évaluation de l’efficacité des mesures de gestion sanitaire mises en place dans le massif du Bargy pour lutter contre la brucellose.

Abstract Assessing trends in the relative abundance of populations is a key yet complex issue for management and conservation. This is a major aim of many large‐scale censusing schemes such as the International Waterbird Count (IWC). However, owing to the lack of sampling strategy and standardization, such schemes likely suffer from biases due to spatial heterogeneity in sampling effort. Despite huge improvements of the statistical tools that allow tackling these statistical issues (e.g., GLMM, Bayesian inference), many conservationists still prefer to rely on stand‐alone turn‐key statistical tools, often violating the prerequisites put forward by the developers of these tools. Here, we propose a straightforward and flexible approach to tackle the typical statistical issues one can encounter when analyzing count data of monitoring schemes such as the IWC. We rely on IWC counts of the declining common pochard populations of the Northwest European flyway as a case study (period 2002–2012). To standardize the size of sampling units and mitigate spatial autocorrelation, we grouped sampling sites using a 75 × 75 km grid cells overlaid over the flyway of interest. Then, we used a hierarchical modeling approach, assessing population trends with random effects at two spatial scales (grid cells, and sites within grid cells) in order to derive spatialized values and to compute the average population trend at the whole flyway scale. Our approach allowed to tackle many statistical issues inherent to this type of analysis but often neglected, including spatial autocorrelation. Concerning the case study, our main findings are that: (1) the northwestern population of common pochards experienced a steep decline (4.9% per year over the 2002–2012 period); (2) the decline was more pronounced at high than low latitude (11.6% and 0.5% per year at 60° and 46° of latitude, respectively); and, (3) the decline was independent of the initial number of individuals in a given site (random across sites). Beyond the case study of the common pochard, our study provides a conceptual statistical framework for estimating and assessing potential drivers of population trends at various spatial scales.