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We designed a participatory monitoring program for the capercaillie population in the French Pyrenees based on lek censuses conducted during the breeding season. This program was implemented by a consortium of stakeholders interested in the conservation of French galliforms. The program, carried out since 2010, relied on a dual frame sampling approach: The first sampled frame was the list of all known leks in the study area. We distinguished two types of known leks: leks known to be active before the onset of the program (with at least one cock detected since 2000) and leks with an indeterminate activity status at the time of the onset of the program. The monitoring program also accounted for the existence of leks that were unknown due mainly to incomplete expert knowledge. We therefore built a complementary area frame by discretizing the study area into a set of 4-km

International audience; For sustainable management of exploited populations, it is required to have good knowledge on temporal trends in population density to adapt the harvest. In this regard, hunting statistics are often collected routinely by government agencies and associations. These data are used to assess demographic trends through the development of indices, which are in turn used to manage exploited populations in a sustainable way. However, these population indices depend on features of the hunting process (e.g. hunting effort, hunting conditions, probability of catch). In this study, we show how to use hunting logs to assess demographic trends in exploited populations while accounting for the components of the hunting process. In particular, we developed a catch-effort model to study how the hunting effort leads to mortality rate – hunting pressure – within a given habitat type and during a given period. We illustrated the usefulness of this approach using exploited wild boar (Sus scrofa) populations as a case study. We used a large hunting logs dataset to perform our study, with several hundreds of thousands hunting events for more than 10 years in two French departments in France, including information about the number of hunters, of wild boars culled and the date of the hunt. We showed that catchability is a key parameter to assess hunting pressure at a given time and place. This parameter varies both within the hunting season and between habitat types. Once this variation in catchability was accounted for, our catch-effort model allowed us to obtain estimates of relative densities of wild boar populations over the study period at the management unit scale. Thus, catch-effort models are powerful tools to assess population density and to understand the underlying hunting process. Our study offers straightforward and reproducible conceptual framework that can be applied routinely by wildlife managers on exploited populations and practitioners from hunting statistics logs.

We develop a new statistical procedure to monitor relative species abundances and their respective preferences for different habitat types, using opportunistic data. Following Giraud et al. (Biometrics 72(2):649–658, 2015), we combine the opportunistic data with some standardized data in order to correct the bias inherent to the opportunistic data collection. Species observations are modeled by Poisson distributions whose parameters quantify species abundances and habitat preferences, and are estimated using Bayesian computations. Our main contributions are (i) to tackle the bias induced by habitat selection behaviors, (ii) to handle data where the habitat type associated to each observation is unknown, (iii) to estimate probabilities of selection of habitat for the species. As an illustration, we estimate common bird species habitat preferences and abundances in the region of Aquitaine (France).

Accurate flyway delineation is a prerequisite for effective conservation and management of migratory bird populations, yet such limits have so far mostly been set subjectively. We present a statistical method to infer population boundaries from the analysis of ring recoveries, using a Bayesian framework. The approach was applied to Eurasian teal Anas crecca ringed in Camargue, southern France, and Abberton Reservoir, Essex, eastern England. The results presented show the boundaries of the two teal flyways in western Europe, with a zone of overlap, broadly matching those previously defined. The percentage of teal switching flyways (abmigration rate) was 2.4–2.6%, greater in birds ringed as juveniles than as adults. Abmigrants ended up at sites within the other flyway where the density of local birds was lower than expected by chance, suggesting abmigration resulted from exploratory or aberrant behaviour. The methodology presented here can be used to infer flyway boundaries of any bird with an adequate ring-re-encounter dataset, which has crucial consequences for the evaluation of their trends in abundance and hence conservation status, and the management of sustainable harvests.

Wild boar populations have increased dramatically over the last decades throughout Europe and in France in particular. While hunting is considered the most efficient way to control game populations, many local conflicts persist after the hunting period due to remaining high densities of wild boar despite the large number of animals culled every year. Therefore, increasing the efficiency of hunting is a timely issue. Herein, we assessed how hunting effort can be measured, and we determined whether the hunting effort carried out by hunters explains the observed hunting pressure. We measured the characteristics and results of all hunts that occurred in the experimental forest of Châteauvillain-Arc-en-Barrois (Northeastern France), and we modelled the number of animals culled as a function of the hunting effort, measured by the number of beaters, hunters, and dogs, as well as the size of the hunting area. We also accounted for variables suspected to affect the hunting efficiency achieved with a given effort, such as time of day (AM/PM), the month during which hunting occurred. We found that more posted hunters, larger hunted areas, and hunts carried out early in the season, i.e. before February, increased the number of culled animals. Our model can be used by wildlife managers to adjust hunting effort in order to reach the hunting pressure expected to meet management objectives.

Aim Habitat quality and heterogeneity directly influence the distribution and abundance of organisms at different spatial scales. Determining the main environmental factors driving the variation in species abundance is crucial to understand the underlying ecological processes, and this is especially important for widely distributed species living in contrasting environments. However, the responses to environmental variation are usually described at relatively small spatial scales. Here, we studied the variation in abundance of a widely distributed mustelid, the European badger (Meles meles), across France. Location The whole metropolitan France. Methods We used (a) direct detections of 9,439 dead and living badgers, from 2006 to 2009, to estimate badger relative abundance in 703 small agricultural regions of metropolitan France and (b) a Bayesian modeling approach to identify the main environmental determinants influencing badger abundance. Results Despite a continuous distribution of badger in France, we found large variation in badger abundance between regions, explained by environmental factors. Among a set of 13 environmental variables, we demonstrated that badger abundance in lowlands (, We used direct detections of 9,439 badgers Meles meles, to estimate badger relative abundances in 703 small agricultural regions of metropolitan France and a Bayesian modeling approach to identify the main environmental determinants influencing badger abundances. Despite a continuous distribution of badger in this country, we demonstrated that badger abundances in lowlands were mostly driven by biotic factors such as potential food resources and forest fragmentation, while in mountainous areas, abiotic factors drove the variations in badger relative abundance. These results underline the importance of mapping the abundance of wildlife species based on environmental suitability and highlight the complexity of drivers influencing species abundance at large spatial scale.

The monitoring of the disease prevalence in a population is an essential component of its adaptive management. However, field data often lead to biased estimates. This is the case for brucellosis infection of ibex in the Bargy massif (France). A test-and-cull program is being carried out in this area to manage the infection: captured animals are euthanized when seropositive, and marked and released when seronegative. Because this mountainous species is difficult to capture, field workers tend to focus the capture effort on unmarked animals. Indeed, marked animals are less likely to be infected, as they were controlled and negative during previous years. As the proportion of marked animals in the population becomes large, captured animals can no longer be considered as an unbiased sample of the population. We designed an integrated Bayesian model to correct this bias, by estimating the seroprevalence in the population as the combination of the separate estimates of the seroprevalence among unmarked animals (estimated from the data) and marked animals (estimated with a catalytic infection model, to circumvent the scarcity of the data). As seroprevalence may not be the most responsive parameter to management actions, we also estimated the proportion of animals in the population with an active bacterial infection. The actual infection status of captured animals was thus inferred as a function of their age and their level of antibodies, using a model based on bacterial cultures carried out for a sample of animals. Focusing on the population of adult females in the core area of the massif, i.e. with the highest seroprevalence, this observational study shows that seroprevalence has been divided by two between 2013 (51%) and 2018 (21%). Moreover, the likely estimated proportion of actively infected females in the same population, though very imprecise, has decreased from a likely estimate of 34% to less than 15%, suggesting that the management actions have been effective in reducing infection prevalence.

Hunting, including drive hunts, can be considered as a predation process. Although drive hunts are spatially and temporally well defined, the scale at which the hunting risk triggers anti-predator responses of prey remains poorly documented. The present study aims at 1) characterizing the delayed movement responses of female red deer Cervus elaphus to hunters and 2) understanding the main environmental determinants modulating these post-disturbance responses at the individual level. We hypothesized that red deer alter their movement behaviour for several days after a drive hunt by increasing their speed and exploring more space. Then, we predicted that individuals close to the hunting area would exhibit stronger responses (i.e. higher speed and larger home range size) than individuals located further away. We also expected topographic obstacles and vegetation cover to reduce the magnitude of the post-disturbance responses. We used GPS data from a large dataset collected on 91 female red deer in the National Hunting and Wildlife Reserve of La Petite Pierre (France), between 2004 and 2018. Each year, drive hunts are conducted by about 43 hunters and 6 dogs, once a week from October to February. Our results suggest that, over a 72-h period after a drive hunt, female red deer could show two contrasting strategies: 1) flight-type movements (i.e. higher maximum speed) associated with more space explored due to a temporary avoidance of the disturbed area and 2) lower movements to avoid detection and contacts with hunters. These two delayed responses are situation-specific, depending on risk proximity, landscape features, hunting conditions and individual characteristics. This study highlights that ungulate management using a ‘hunting for fear’ approach may be adjusted considering spatial and temporal scales of the effects of drive hunts on red deer movement patterns.

Mute Swan Cygnus olor numbers have recently increased in a dramatic fashion in Western Europe and in North America, suggesting there could be potential consequences for the rest of the waterbird community. Breeding Mute Swan pairs may behave territorially towards other waterbirds, taking advantage of their larger size, and hence cause concern regarding their potential effects on waterbird communities. We studied how the within-site distributions of breeding Mute Swans and other waterbirds were related to each other, in order to assess if there is support to the assertion that breeding Mute Swans may affect the distribution of the other waterfowl within waterbodies. We mapped waterbird and swan distribution within fishponds during the Mute Swan breeding period. Relying on spatial point pattern analysis, our first finding is that breeding Mute Swans were located in the vicinity of the other waterbirds, using the same area within fishpond. Waterbirds do not completely desert the area used by breedi...

Sympatric populations of species with similar ecology are limited by competition for available resources. While quantifying niche overlap between species in interaction offers a useful description of coexistence patterns, the lack of correspondence between niche overlap and competition prevents any functional interpretation. Using an innovative approach for analysing spatial distributions of individuals from two sympatric species, we aim to fill the gap. We applied our models to data collected on sympatric females of roe deer and red deer. Using the null model approach commonly applied in community ecology, we tested in a first model for deviation from a random distribution of female roe deer in relation to female red deer. We took into account constraints generated by both the marked sedentary habits and habitat use (avoidance of mature forest) of roe deer in this null model. In a second null model, we removed the habitat constraints to avoid any lack of power of our tests. We then compared the overlap index calculated from roe deer and red deer locations with the distribution expected under each of these null models. As we failed to reject the null model in both cases, we tested a third null model simulating an identical distribution of roe deer and red deer home ranges and we rejected it. Our results show that the distribution of female roe deer does not depend on the distribution of female red deer, indicating an absence of competitive interactions between the deer species. This conclusion relies on the application of the null model approach, which provides a suitable way of performing a formal test of interspecific competition rooted in explicitly defined hypotheses, and could not have been reached using simple overlap indices as generally performed when assessing competitive interactions. We thus encourage scientists to apply this null model analysis to population ecology.

One of the main objectives of community ecology is to understand the conditions allowing species to coexist, which requires identifying how co-occurring species use and share space and resources. Species of the same trophic level, such as large herbivores, are of fundamental interest in that context because competition for resources is likely. Segregation in space or on some axes of the ecological niche are processes allowing coexistence, yet, both are seldom studied jointly. Based on annual spring censuses collected for 11 yr, we analysed the degree of overlap in spatial distribution among chamois Rupicapra rupicapra and mouflon Ovis gmelini musimon, 2 species of similar size that coexist on the same alpine pastures. We further investigated whether they differed in terms of habitat selection processes, and identified which environmental factors led to species being aggregated or segregated. The areas of intensive use for 2 species were more spatially aggregated than expected by chance. Habitat selection was studied using multivariate methods based on the niche concept, considering the presence of 1 species as an environmental variable for the other. Despite a large overlap in niches (88%), segregation was significant as chamois preferred meadows dominated by Sesleria and Carex sempervirens while mouflon selected meadows dominated by Carex ferruginea and avoided being close to areas affected by human activities. Importantly, habitat selection within each species was not affected by the presence of the other species. Coexistence between these 2 species and spatial overlap may be permitted because resource partitioning occurs at a fine temporal and/or spatial scale. We underscore that joint approaches of spatial and ecological processes are necessary to disclose the type of interaction (neutral, facilitation or competition) at play within a community.

An estimate of changes in a species' distribution range is a key variable in assessing its conservation status. It may be based on the direct detection of individuals, or on the use of indirect presence sign surveys. In both cases, the process requires one to switch from a point-based approach, where individuals/presence signs are located using a coordinate system, to an area-based one, each original point being replaced by a cell area unit (CAU), with a given shape and size. The estimated distribution range (EDR) is the spatial union of the CAUs over the area of interest. Based on wolf presence signs collected in France (1996- 2006), we analysed the influence of the shape and size of types of CAUs (circular area versus square grid mesh; 6, 25, 50 and 100 km 2 ) on the changes in EDR. EDR increased with time and a saturating phase was noticed by the end of the period. We assessed the effects of the year and the type of CAU on EDR using exploratory data analysis. Larger CAUs resulted logically in larger EDR values, whatever the CAU shape. For a given CAU size, contiguous square grids yielded larger EDR values than overlapping circular buffers. The effect of the interactions between the year and the type of CAU on EDR changes was evidenced using an auto-modelling method based on principal component analysis. Compared to smaller units, larger CAUs resulted in larger growth rates during the range increase phase, and in smaller rates during the saturating phase. A basic and descriptive conceptual model helped interpreting this pattern as a consequence of the character- istics of the colonisation process in the wolf population. We discuss the present results within the framework of conservation status assessment and management of the wolf population.

We use a new method called “product kernel estimator” to explore the spatial and temporal distribution of 9,114 recoveries of Teal (Anas crecca) ringed in Camargue, southern France, and recovered over the whole of Europe. This method allows exploration of the changes in time of the probability density to recover a ringed bird over a grid covering the study area. We thus identified two migration corridors for this species to the north and south of the Alps, whereas earlier analyses mostly suggested a southern route from Camargue, especially in spring. The northern route seems to be used to a greater extent in autumn than in spring, indicating a frequent abmigration (animals switching from one corridor to the other). Moreover, migration of the population seems faster in spring than in autumn. The simultaneous presence of Teal recoveries in many distinct geographical areas in spring is consistent with the idea that these ducks are not limited by their migratory speed in spring, nor do they wait until favorable environmental conditions before colonizing their breeding areas.

Fish ponds host a relatively important share of the breeding population of waterfowl in Europe. The objective of this study was to investigate the influence of fish-farming management on the distribution of dabbling and diving duck breeding, in 103 fishponds from four regions important for duck breeding in France. Duck breeding in fish ponds was apparently influenced by food resource and nesting site availability. Dabbling duck pair density was generally higher when invertebrates were abundant in macrophytes beds and when competition for food with carps Cyprinus carpio was potentially decreased by lower fish stock biomass. Diving duck pair abundance seemed to be negatively influenced by low invertebrates biomasses in pond sediment and by the absence of large reed beds at the edge of waterbodies. The difference between dabbling and diving ducks was also confirmed by a study of the variation in brood numbers standardized by pair numbers. This brood:pair ratio corresponded to a measure of nesting success and the possible attraction of fish ponds for some broods hatched in neighbouring waterbodies. Dabbling duck brood:pair ratio was lower in one of the study regions where most of meadow areas surrounding fish ponds have been transformed into cereal crops in the past few decades. Diving duck brood:pair ratio was positively linked to pond fertilization due to fish farming. Fish farming, therefore, influenced duck breeding by an interaction between carp density and fertilization. We hypothesize that fertilization increases zooplankton density, thereby decreasing the competition between carps and waterfowl for benthic prey.

Although it is widely accepted that populations vary in space and time, defining the spatial scale of population structure relevant for understanding temporal variation or for management and conservation purposes remains a challenge. We studied jointly temporal patterns of social and spatial structures in an introduced population of mouflon ( Ovis gmelini musimon (Schreber, 1782)) to define the temporal stability of these structures and to uncover the history of the colonization process. We expected social organization to remain stable between years, mouflon to stay sedentary, and colonization to have occurred through a diffusion process. We used yearly censuses performed between 1994 and 2004, and collected information in managers’ archives and newspapers reporting the presence of mouflon in different areas since its introduction in 1954 in the Bauges mountains, France. Mouflons were divided into male and nursery groups, whose number (1.88 ± 0.31 for males and 7.54 ± 0.58 for nurseries) and composition (7.05 ± 1.25 individuals in male groups; 13.6 ± 1.41 females, 8.11 ± 0.72 lambs, and 6.51 ± 0.65 males in the nurseries) remained stable over years. The spatial distribution of nursery groups was clustered in five areas, highly correlated between years (p < 0.001), suggesting that the same groups were observed in given areas every year and confirming the sedentary lifestyle of the species. The presence–absence data of the species since its introduction suggested a colonization by diffusion. We discuss the social and spatial structures of the population and the type of colonization process that could have led to this kind of structure.

We compared the body mass of adult rock ptarmigan Lagopus mutus shot in autumn in the French Pyrenees (Ariege), the French Alps (Hautes-Alpes) and the Italian Alps (Province of Verbania). Mean body mass of adults was greater in the Ariege than in the Hautes-Alpes both for cocks (466 vs 433 g) and hens (429 vs 406 g), with the body mass of Italian birds being intermediate (cocks 448 g, hens 418 g). The relatively large mass of rock ptarmigan in the Pyrenees contrasts with the geographic trends found in capercaillie Tetrao urogallus and grey partridge Perdix perdix in France. For the last two species, birds in the Pyrenees are smaller than those further north. The site differences that we observed in body mass of rock ptarmigan may be related to differences in availability of high quality foods, particularly ericaceous shrubs. However, at the continental scale within Europe, the body mass of rock ptarmigan appears to be greatest in northern latitudes.

Summary 1. Timing and synchrony of reproduction are regarded as crucially important factors for fitness in seasonal environments. Natural selection has probably favoured temperate and arctic female herbivores that match reproduction with onset of plant growth in spring. However, breeding synchrony may also be affected by variation in phenotypic quality of females in a population, because females in poor body condition have been found to delay ovulation and subsequent calving. 2. We compared breeding phenology, i.e. the timing and synchrony of rutting (roaring, sexual aggregation) and calving of red deer ( Cervus elaphus L.) in France (latitude: 49 ° N) and Norway (latitude: 63 ° N). We hypothesized (H 1 ) that calving and rutting were later at the site with latest onset of plant growth. 3. We further quantified overall environmental predictability as the sum of annual constancy and seasonality and tested three different (not mutually exclusive) hypotheses about breeding synchrony: (H 2a ) the population experiencing most seasonal plant phenology should show the highest breeding synchrony; (H 2b ) overall predictability of plant phenology should determine breeding synchrony; and (H 2c ) breeding should be more synchronized in the population with lowest female body weight variation within age classes because they ovulate more synchronously. 4. Calving and rutting, as well as onset of plant phenology, were later in Norway than in France, complying with the first hypothesis. Plant growth in spring was overall more predictable and also more seasonal in Norway than France. Hence we expected higher breeding synchrony in Norway than in France according to H 2a and H 2b . Variance in female body weight was slightly higher in France than in Norway, which should also cause more synchronized breeding in Norway than in France (H 2c ). Contrary to all predictions, variance in rutting and calving dates was around two times higher in Norway than in France. 5. We suggest two alternative explanations of breeding synchrony. A more variable topography in Norway can make optimal birth date more variable on a local scale than in France, thereby maintaining a higher genetic variance for calving date in Norwegian red deer. Further, population age structure may play a role, as ovulation varies according to female age. Clearly, processes of breeding synchrony are far more complex than previously realized.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]QUASARE; We estimated the spatial distribution of 6 Mustelidae species in France using the data collected by the French national hunting and wildlife agency under the "small carnivorous species logbooks" program. The 1500 national wildlife protection officers working for this agency spend 80% of their working time traveling in the spatial area in which they have authority. During their travels, they occasionally detect dead or living small and medium size carnivorous animals. Between 2002 and 2005, each car operated by this agency was equipped with a logbook in which officers recorded information about the detected animals (species, location, dead or alive, date). Thus, more than 30000 dead or living animals were detected during the study period. Because a large number of detected animals in a region could have been the result of a high sampling pressure there, we modeled the number of detected animals as a function of the sampling effort to allow for unbiased estimation of the species density. For dead animals -- mostly roadkill -- we supposed that the effort in a given region was proportional to the distance traveled by the officers. For living animals, we had no way to measure the sampling effort. We demonstrated that it was possible to use the whole dataset (dead and living animals) to estimate the following: (i) the relative density -- i.e., the density multiplied by an unknown constant -- of each species of interest across the different French agricultural regions, (ii) the sampling effort for living animals for each region, and (iii) the relative detection probability for various species of interest.

With the internet, a massive amount of information on species abundance can be collected by citizen science programs. However, these data are often difficult to use directly in statistical inference, as their collection is generally opportunistic, and the distribution of the sampling effort is often not known. In this article, we develop a general statistical framework to combine such "opportunistic data" with data collected using schemes characterized by a known sampling effort. Under some structural assumptions regarding the sampling effort and detectability, our approach makes it possible to estimate the relative abundance of several species in different sites. It can be implemented through a simple generalized linear model. We illustrate the framework with typical bird datasets from the Aquitaine region in south-western France. We show that, under some assumptions, our approach provides estimates that are more precise than the ones obtained from the dataset with a known sampling effort alone. When the opportunistic data are abundant, the gain in precision may be considerable, especially for rare species. We also show that estimates can be obtained even for species recorded only in the opportunistic scheme. Opportunistic data combined with a relatively small amount of data collected with a known effort may thus provide access to accurate and precise estimates of quantitative changes in relative abundance over space and/or time.

Wildlife diseases are often studied using hunting data. In such studies, inferences about diseases are often made by comparing raw disease prevalence levels, ignoring complications like stochasticity in recruitment. We carried out a field trial to study the effectiveness of oral vaccination of wild boar (Sus scrofa) against classical swine fever (CSF) in the Vosges mountains (Northeastern France) for 3 years (2008–2010). Since August 2004, hunters had carried out three vaccination sessions per year in spring, summer and autumn. During our study period, we determined whether each wild boar hunted in our study area was immunized or not against CSF. We used a Bayesian approach to model the changes in the proportion of vaccinated animals in the population of young animals (i.e., 12 months old). This approach allowed to disentangle the effects of the birth peaks (leading to a decrease) and of both the vaccination sessions and natural infection (leading to an increase) on this proportion. We thus inferred, at the individual level, the probability that a non-immunized animal became vaccinated after a particular session. There was a high between-year variability in the effectiveness of the vaccination: the observed patterns were similar in 2008 and 2010, but 2009 was characterized by an overall greater effectiveness of the vaccination. Within a particular year, the spring vaccination session was more effective than the autumn session, probably because of the higher food availability in autumn that render the vaccination places less attractive to the animals. The vaccination effectiveness was rather low in summer, except in 2009, probably because of higher age identification error this year. This model also highlighted an immunisation of animals occurring outside vaccination periods, which suggests either the presence of the CSF virus in our study area, or the consumption of the vaccine outside the vaccination sessions. Finally, we observed a high spatial variability of the probability of vaccination. The effectiveness of the vaccination was indeed strongly related to both the distribution of the forests and the distribution of the vaccination places in our study area. This study highlights an optimal vaccination effort of 1.25 places per km2 to maximize the proportion of immune wild boar in that area.

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

Traditional rangelands in many developing countries are currently being encroached by cultivation, driving some herders to illegally use protected areas for grazing their cattle. Since cattle are an exotic species in these ecosystems, they might have an impact on the local wild herbivore communities, notably through competition. We used point pattern statistics to characterise the spatial relationships between wild ungulate species and cattle herds within a protected area in west Africa undergoing seasonal intrusions by cattle. We predicted that the wild ungulate species that are ecologically and morphologically similar to cattle, in terms of body mass and diet, would be more sensitive to grass depletion by cattle and would be separated from cattle to a larger extent. The spatial distribution of browsing and mixed-feeding antelopes did not seem to be affected much by cattle presence, whereas most grazing species showed spatial separation from cattle. Interestingly, elephants also showed significant separation from cattle herds. We discuss the likely processes that may have contributed to the observed spatial patterns. The spatial displacement of certain wild species, including megaherbivores, affects the whole community structure and, thus, other components of the ecosystem.

International audience; In most previous studies of habitat selection, the use of a given habitat type is assumed to be directly proportional to its availability. However, the use and (or) the selection of a given habitat may be conditional on the availability of that habitat. We aim here to (i) identify the environmental variables involved in habitat selection, (ii) identify classes of individuals with similar patterns of habitat selection, and (iii) assess whether habitat use changes with changing availability of habitat types, within monthly home ranges of female western roe deer (Capreolus capreolus (L., 1758)). We found that some females adjust their habitat use according to the distribution of resources within habitats. Females with similar home ranges in terms of resource quantity and quality showed similar patterns of habitat selection. Differences in habitat use between 2 years with contrasting resource availability showed that temporal changes of environmental conditions influenced the pattern of habitat selection by female roe deer. Habitat selection also differed between periods of the life cycle likely because of contrasted energy requirements. This study shows that the relationship between habitat use by herbivores and habitat availability is nonproportional, and that the availability of resources influences use mostly at intermediate values.

Studies of animal movements have been popularized for many large and shy species by the increasing use of radio telemetry methods (VHF and GPS technologies). Data are collected with high sampling frequency, and consist of successive observations of the position of an individual animal. The statistical analysis of such data poses several problems due to the lack of independence of successive observations. However, the statistical description of the temporal autocorrelation between successive steps is rarely performed by ecologists studying the patterns of animals movements. The aim of this paper is to warn ecologists against the consequences of failing to consider this aspect. We discuss the various issues related to analyzing autocorrelated data, and show how the exploratory analysis of autocorrelation can both reveal important biological insights and help to improve the accuracy of movement models. We suggest some tools that can be used to measure, test, and adjust for temporal autocorrelation. A short ecological illustration is presented.

The Mahalanobis distances have been introduced in habitat selection studies for the estimation of environmental suitability maps (ESMs). The pixels of raster maps of a given area correspond to points in the multidimensional space defined by the mapped environmental variables (ecological space). The Mahalanobis distances measure the distances in this space between these points and the mean of the ecological niche (i.e., the hypothesized optimum for the species) regarding the structure of the niche. The map of these distances over the area of interest is an estimated ESM. Several authors recently noted that the use of a single optimum for the niche of a species may lead to biased predictions of animal occurrence. They proposed to use instead a minimum set of basic habitat requirements, found by partitioning the Mahalanobis distances into a restricted set of biologically meaningful axes. However, the statistical approach they proposed does not take into account the environmental conditions on the area where the niche was sampled (i.e., the environmental availability), and we show that including this availability is necessary. We used their approach as a basis to develop a new exploratory tool, the Mahalanobis distance factor analysis (MADIFA), which performs an additive partitioning of the Mahalanobis distances taking into account this availability. The basic habitat requirements of a species can be derived from the axes of the MADIFA. This method can also be used to compute ESMs using only this small number of basic requirements, therefore including only the biologically relevant information. We also prove that the MADIFA is complementary to the commonly used ecological-niche factor analysis (ENFA). We used the MADIFA method to analyze the niche of the chamois Rupicapra rupicapra in a mountainous area. This method adds to the existing set of tools for the description of the niche.

We propose here some refinements of the ecological-niche factor analysis (ENFA) to describe precisely one organism’s habitat selection. The ENFA is based on the concept of the ecological niche, and provides a measure of the realised niche within the available space from the computation of two parameters, the marginality and the specialization. By measuring the departure of the ecological niche from the average available habitat, the marginality identifies the preference of the individual, population, or species for specific conditions of the environment among the whole set of possibilities. The specialization appears as a consequence of the narrowness of the niche on some environmental variables. The ENFA is a factorial analysis that extracts one axis of marginality and several axes of specialization. We present here the use of biplots (i.e., the projection of both the pixels of the map and the environmental variables in the subspace extracted by the ENFA) as a way to identify the key-variables for management, assessing which habitat features are of prime importance and should be preserved or reinforced. With the help of this tool, we are now able to describe much more precisely the habitat selection of the organism under focus. In our application to the lynx in the Vosges mountains, based on sightings as well as other indices of lynx presence, we thus underlined a strong avoidance of agricultural areas by the lynx. We also highlighted the relative indifference of the lynx to the proximity of artificial areas and at the opposite, the sensitivity to the proximity of highways. The ENFA provides a suitable way to measure habitat use/selection under a large range of ecological contexts and should be used to define precisely the ecological niche and therefore identify the characteristics searched for by the organism under study.

We propose a new statistical framework for the exploratory analysis of the ecological niche, the "General niche-environment system factor analysis" (GNESFA). The data required for this analysis are (i) a table giving the values of the environmental variables in each environment unit (EU, e.g., the patches of habitat on a vector map), (ii) a set of weights measuring the availability of the EUs to the species (e.g., the proportion of the study area covered by a given patch), and (iii) a set of utilization weights describing the use of the EUs by the focal species (e.g., the proportion of detections of the species in each patch). Each row of the table corresponds to a point in the multidimensional space defined by the environmental variables, and each point is associated with two weights. The GNESFA searches the directions in this space where the two weight distributions differ the most, choosing one distribution as the reference, and the other one as the focus. The choice of the utilization as the reference corresponds to the MADIFA (Mahalanobis distances factor analysis), which identifies the directions on which the available EUs are in average the furthest from the optimum of the niche, allowing habitat suitability modelling. The choice of the availability as the reference corresponds to the FANTER (Factor analysis of the niche, taking the environment as the reference), which identifies the directions on which the niche is the furthest from the average environment (marginality) and those on which the niche is the narrowest compared with the environment (specialization). The commonly used ENFA (Ecological niche factor analysis) is at the middle point between the MADIFA and the FANTER, considering both distributions as the reference and the focus simultaneously. When used concurrently, these three analyses allow an extensive exploration of the system.

The development of methods to analyze habitat selection when resources are defined by several categories (e.g., vegetation types) is a topical issue in radio-tracking studies. The White and Garrott statistic, an extension of the widely used test of Neu et al., can be used to determine whether habitat selection is significant. As well, Manly's selection ratio, a particularly useful measure of resource selectivity by resource users, allows detection of the most strongly selected habitat types. However, when both the number of animals and types of habitat are large, the biologist often has to deal with an excessively large number of measures. In this paper we present a new method, the eigenanalysis of selection ratios, that generalizes these two common methods within the framework of eigenanalyses. This method undertakes an additive linear partitioning of the White and Garrott statistic, so that the difference between habitat use and availability is maximized on the first factorial axes. The eigenanalysis of selection ratios is therefore optimal in habitat selection studies. Although we primarily consider the case where the habitat availability is the same for all animals (design II), we also extend this analysis to the case where the habitat availability varies from one animal to another (design III). An application of this method is provided using radio-tracking data collected on 17 squirrels in five habitat types. The results indicate variability in habitat selection, with two groups of animals displaying two patterns of preference. This difference between the two groups is explained by the patch structure of the study area. Because this method is mainly exploratory, and therefore does not rely on any distributional assumption, we recommend its use in studies of habitat selection.

The practical analysis of space use and habitat selection by animals is often a problem due to the lack of well-designed programs. I present here the “adehabitat” package for the R software, which offers basic GIS (Geographic Information System) functions, methods to analyze radio-tracking data and habitat selection by wildlife, and interfaces with other R packages. These tools can be downloaded freely on the internet. Because the functions of this package can be combined with other functions of R, “adehabitat” provides a powerful environment for the analysis of the space and habitat use.

Two kinds of wildlife habitat studies can be distinguished in the literature: hindcasting and forecasting studies. Hindcasting studies aim to emphasize among a large set of habitat variables those that are of interest for the focus species, whereas forecasting studies are intended to predict habitat selection according to a small number of habitat variables for a given area. We provide here a new analytical tool which relies on the concept of ecological niche, the K-select analysis, for hindcasting studies of habitat selection by animals using radio-tracking data. Each habitat variable defines one dimension in the ecological space. For each animal, the difference between the vector of average available habitat conditions and the vector of average used conditions defines the marginality vector. Its size is proportional to the importance of habitat selection, and its direction indicates which variables are selected. By performing a non-centered principal component analysis of the table containing the coordinates of the marginality vectors of each animal (row) on the habitat variables (column), the K-select analysis returns a linear combination of habitat variables for which the average marginality is greatest. It is a synthesis of variables which contributes the most to the habitat selection. As with principal component analysis, the biological significance of the factorial axes is deduced from the loading of variables. An example is provided: habitat selection by wild boar is studied in a Mediterranean habitat using the K-select analysis. The numerous advantages of the analysis (a large number of variables that can be included, individual variability in habitat selection taken into account, a lack of too strict underlying hypotheses) make it a powerful approach in radio-tracking studies designed to identify habitat variables that are selected by animals.

The aim of this work was to assess the efficiency of dissuasive spreading of maize to reduce the level of wild boar damage to vines in a Mediterranean area (Puechabon, southern France). The 50 wine growers of Puechabon were all questioned about the annual losses caused by the wild boar in each vineyard of the study area between 1990 and 1992. We also studied the distribution of the damage on a smaller scale, by mapping the damaged vines within two vineyards. In summer 1993, we distributed 4.7 tons of maize in the woods , and then questioned the wine growers about the losses in each vineyard for 1993. During 1990–1992, on both large and small scales, the damage had a patchy distribution, with more patches of damage occurring close to the woods. Moreover, the later the vines ripened, the less frequent the damage. The severity of the damage was only affected by the distance of the vineyard from woods. In total, the wild boar consumed 20,049 kg of grapes each year between 1990–1992 (193 kg/ha), and 63% of the vineyards were damaged. In 1993, both the density and the compensation paid in the departement increased threefold. However, in our study area, both the proportion of damaged vineyards (36%) and the level of damage in the vineyards (151 kg/ha) were reduced, saving more than 60% in compensation. The dissuasive spreading of maize is therefore an efficient tool to reduce the level of damage to vineyards.

Damage caused by elephants was monitored in two woodland stands of Zakouma National Park (Chad) between February and March 1998. The Acacia seyal savanna was more severely damaged (29.8% of trees damaged of which 13.2% severely) than the Combretaceae savanna (26.5% of trees damaged of which only 4.2% severely). Nearly all severely damaged trees showed resprouts (respectively 86.8% and 88.5% in Combretaceae and A. seyal savannas). Both low damage rate and low mortality rate indicate that no serious ‘elephant problem’ occurred in Zakouma National Park. Elephants selected trees to damage according to species and height. Such selection also occurred for severe damage in A. seyal savanna, but only height affected severity of damage in Combretaceae savanna. In both savannas, the plots close to a water point were the most frequently damaged. In Combretaceae savanna, the distribution of damaged trees was clumped. On the other hand, spatial auto-correlation was not significant for the severity or the frequency of damage in A. seyal savanna. Neither tree density nor diversity of woody species affected the spatial patterns of damage or severe damage.

Heterogeneity of infectious disease transmission can be generated by individual differences in the frequency of contacts with susceptible individuals, in the ability to transmit the infectious agent or in the duration of infection, and by spatial variation in the distribution, density or movements of hosts. Identifying spatial and individual heterogeneity can help improving management strategies to eradicate or mitigate infectious diseases, by targeting the individuals or areas that are responsible for most transmissions. Individual-based models allow quantifying the respective role of these sources of heterogeneity by integrating potential mechanisms that generate heterogeneity and then by tracking transmissions caused by each infected individual. In this study, we provide an individual-based model of endemic brucellosis Brucella melitensis transmission in the population of Alpine ibex (Capra ibex) of the Bargy massif (France) by taking advantage of detailed information available on ibex population dynamics, behaviour, and habitat use, and on epidemiological surveys. This host-pathogen system is expected to be subject of both individual and spatial heterogeneity. We first estimated the transmission probabilities, hitherto unknown, of the two main transmission routes of the infection (i.e., exposure to infectious births/abortions and venereal transmission). Then, we quantified heterogeneity at both individual and spatial levels. We found that both transmission routes are not negligible to explain the data, and that there is a high amount of heterogeneity of the host-pathogen system at the individual level, with females generating around 90% of the new cases of brucellosis infection. Males transmit infection at a lesser extent but still play a non-negligible role because they move between subpopulations and thereby create opportunities for spreading the infection spatially by venereal transmission. Two particular socio-spatial units are hotspots of transmission, and act as sources of transmission for the other units. These results may have important implications for disease management strategies.