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.
The Eurasian lynx is of special conservation concern based on the European Union's Habitat Directive and its populations need to be maintained or restored at favourable conservation status. To ...evaluate lynx population status, appropriate monitoring needs to be in place. We modelled the distribution dynamics of lynx in the Alps (200 000 km2) during 1994–2014 at a resolution of 100 km2. Lynx distribution and detection probability varied by year, country, forest cover, elevation and distance to the nearest release site. Occupancy of neighbouring quadrats had a strong positive effect on colonization and persistence rates. Our analyses demonstrate the importance of accounting for imperfect detection: the raw data underestimated the lynx range by 55% on average, depending on country and winter. Over the past 20 years the Alpine lynx range has expanded at an average rate of 4% per year, which was partly due to the lynx translocations to new areas. Our approach to large‐scale distribution modelling and analysing trends using site occupancy models can be applied retrospectively and is useful in many cases where a network of trained people is established to report the presence of target species, for example, in Europe where member states of the European Union have to report conservation status of species of community interest. Hence, dynamic occupancy models are an appealing framework for inference about the large‐scale range dynamics based on opportunistic data and a useful tool for large‐scale management and conservation programmes.
We analysed range dynamics of a reintroduced large carnivore, the Eurasian lynx, in the Alps (200 000 km2) over 20 years, combining a cutting edge occupancy model with citizen science. Lynx distribution and detection probability varied by distance to the nearest release site, year, forest cover, elevation and country. Occupancy of neighbouring quadrats had a strong positive effect on colonization and persistence rates. Our analyses demonstrate the importance of accounting for imperfect detection: the raw data underestimated the lynx range by 55% on average. Over the past 20 years the Alpine lynx range expanded at an average rate of 4% per year, which was partly due to the lynx translocations to new areas. Our approach to large‐scale distribution modelling and analysing trends using site occupancy models can be applied retrospectively and is useful in many cases where a network of trained people is established to report the presence of target species.
Inferring the distribution and abundance of a species from field records must deal with false‐negative and false‐positive errors. False‐negative errors occur if a species present goes undetected, ...while false‐positive errors are typically a consequence of species misidentification. False‐positive observations in studies of rare species may cause an overestimation of the distribution or abundance of the species and distort trend indices. We illustrate this issue with the monitoring of the Eurasian lynx in the Alps. We developed a three‐level classification of field records according to their reliability as inferred from whether they were validated or not. The first category (C1) represents ‘hard fact’ data (e.g. dead lynx); the second category (C2) includes confirmed data (e.g. tracks verified by an expert); and the third category (C3) are unconfirmed data (e.g. any kind of direct visual observation). For lynx, which is a comparatively well‐known species in the Alps, we use site‐occupancy modelling to estimate its distribution and show that the inferred lynx distribution is highly sensitive to presence sign category: it is larger if based on C3 records compared with the more reliable C1 and C2 records. We believe that the reason for this is a fairly high frequency of false‐positive errors among C3 records. This suggests that distribution records for many lesser‐known species may be similarly unreliable, because they are mostly or exclusively based on unconfirmed and thus soft data. Nevertheless, such soft data form a considerable part of species assessments as presented, for example in the International Union for Conservation of Nature Red List. However, C3 records can often not be discarded because they may be the only information available. When inferring the distribution of rare carnivores, especially for species with an expanding or shrinking range, we recommend a rigorous discrimination between fully reliable and un‐ or only partly reliable data, in order to identify possible methodological problems in the distribution maps related to false‐positive records.
1. Hares are considered to be a valuable game species in most European countries. Hunting needs to be sustainable and sound management of hare populations requires some knowledge of the species' ...demographic variability, especially regarding the breeding output, which is highly time- and space-dependent and may govern the population size and exploitability. 2. Using shooting bag analysis and placental scar counts, mean fecundity and leveret survival were estimated at four study sites with contrasting hare numbers and density trends. These demographic parameters, harvest rates and adult natural survival rates (from the literature) were incorporated into a matrix projection model to analyse the population growth rate (λ) sensitivity and to derive indices of sustainable harvest rate (ISHR, i.e. rates compatible with λ ≥ 1). 3. The age structure comprised 48-69% young; fecundity varied between 12.2 and 15.0 leverets per breeding female; and 85-100% of adult females bred. These data combined gave a birth-to-autumn leveret survival index of 0.14-0.29 and, when loaded into the matrix model, resulted in simulated λs that matched the density changes observed in the study areas. The model structure, although simple, accounted for most of the relevant biological information. 4. ISHR was 30% when derived iteratively as a function of mean values of those parameters with largest elasticities (leveret survival and doe fecundity). When environmental and demographic stochasticity were included in the model, the proportion of endangered trajectories where the density threshold was < 1 km2over 50 km2varied sharply, with small changes in harvest rate or initial population size. Small populations could only sustain ≤ 20% harvest rates. 5. Demographic parameters derived from killed animals during year t can be used a posteriori to understand the species' dynamics and as a baseline to modulate the shooting scheme in year t + 1. An actual sustainable shooting scheme would require an additional real-time local process that, automatically, would take all sources of change in numbers into account. A two-stage management strategy (e.g. first computing a catch-effort estimator of population size based on numbers killed very early in the shooting period, then defining flexible harvest quotas) would help managers to cope with the unpredictable dynamics of the species and resulting fluctuations in hare numbers. 6. Synthesis and applications. The results of this exploratory study suggest that sustainable shooting of hares is possible provided some local data about their dynamics are available and slightly conservative quotas are used. Modelling approaches have potential in assessing the latter, but also as a check on the coherence of the estimates of the former (comparison of observed and modelled λ).
Dispersal is a fundamental process with wide-ranging evolutionary and management consequences. To date, natal dispersal has never been described for the polygynous-promiscuous European hare Lepus ...europaeus. Using telemetry, we investigated the natal dispersal pattern in two zones that differed in hunting pressure and hare density. We quantified both the natal dispersal rates and distances using 84 juvenile hares. We tested for the influence of several factors (age, sex, density and period of the year) on these two variables. Overall, the mean dispersal rate was 43% and the median natal dispersal distances were 209 m for philopatric hares and 1615 m for dispersers. The maximum distance moved was 17.35 km. Natal dispersal rates were higher in the hunting zone with less density for both males and females, but males dispersed more frequently than females in the two zones although females moved over longer distances. Natal dispersal occurred preferentially between 4 and 6 months of age. This very fine description of the natal dispersal pattern allowed us to make inferences about both the evolutionary and proximate causes of natal dispersal. We also advocate that more attention should be paid to dispersal in studies on hare dynamics and on the conception of hare management, because dispersal seems to be more common than previously thought.
1. Age- and sex-dependent survival rates of European hare, Lepus europaeus, were estimated for a declining population living in intensive large-scale farming conditions in northeastern France. During ...the period 1990-92, a capture-mark-recapture design was used to obtain robust survival rate estimations. 2. The best fit was obtained with survival rates estimated separately for adults and yearlings. Sex dependence was added only in yearlings (φmale yearling=0·471, φfemale yearling=0·237, φadult=0·507 whatever the sex). 3. These estimates and fecundity data obtained from hunting bag analysis and the literature were incorporated into a Leslie Matrix model in order to determine the sensitivity of the population growth rate (λ) to variations of the different demographic parameters. 4. Contrary to that of a population with a higher annual recruitment, the growth rate of the population studied (λ = 0·80), whose annual recruitment was weak, was more sensitive to maintenance than to recruitment variations.
Abstract Inferring the distribution and abundance of a species from field records must deal with false‐negative and false‐positive errors. False‐negative errors occur if a species present goes ...undetected, while false‐positive errors are typically a consequence of species misidentification. False‐positive observations in studies of rare species may cause an overestimation of the distribution or abundance of the species and distort trend indices. We illustrate this issue with the monitoring of the E urasian lynx in the A lps. We developed a three‐level classification of field records according to their reliability as inferred from whether they were validated or not. The first category ( C 1) represents ‘hard fact’ data (e.g. dead lynx); the second category ( C 2) includes confirmed data (e.g. tracks verified by an expert); and the third category ( C 3) are unconfirmed data (e.g. any kind of direct visual observation). For lynx, which is a comparatively well‐known species in the A lps, we use site‐occupancy modelling to estimate its distribution and show that the inferred lynx distribution is highly sensitive to presence sign category: it is larger if based on C 3 records compared with the more reliable C 1 and C 2 records. We believe that the reason for this is a fairly high frequency of false‐positive errors among C 3 records. This suggests that distribution records for many lesser‐known species may be similarly unreliable, because they are mostly or exclusively based on unconfirmed and thus soft data. Nevertheless, such soft data form a considerable part of species assessments as presented, for example in the I nternational U nion for C onservation of N ature R ed L ist. However, C 3 records can often not be discarded because they may be the only information available. When inferring the distribution of rare carnivores, especially for species with an expanding or shrinking range, we recommend a rigorous discrimination between fully reliable and un‐ or only partly reliable data, in order to identify possible methodological problems in the distribution maps related to false‐positive records.
Survival in the brown hare (Lepus europaeus) is poorly documented because only life tables and other nonrobust methods have been used to estimate constant annual survival rates. We used recent ...developments in mark-recapture analysis to model survival patterns in a Danish hare population monitored from 1957 to 1970. Goodness-of-fit tests revealed that the Cormack-Jolly-Seber (CJS) model was an adequate starting point for adults, and age-dependence was considered in modeling survival of yearlings. We found no differences in annual survival rates (φ) from 1957 to 1967 in adults, but males survived better than females ($\phi _{\text{males}}$= 0.55, 95% CI = 0.50-0.61;$\phi _{\text{females}}$= 0.50, 95% CI = 0.44-0.56). Yearling survival rates were time dependent and varied with winter severity, sex, and mass. Indeed, body mass strongly influenced the survival of yearling hares: larger animals (≥3 kg) had higher survival rates than smaller animals, in both males and females (φ = 0.40-0.68 for heavy males and φ = 0.20-0.44 for lighter males; φ = 0.31-0.52 for heavy females and φ = 0.22-0.40 for lighter females). These variations in survival rates were parallel between body mass classes over time (modeled as a function of winter temperature) within each sex.
We present a method to improve detection and aging of placental scars in the European hare (Lepus europaeus), along with its calibration on hand-reared does. The fecundity of these females was first ...established by a breeder counting the number of leverets delivered in each litter (reference values). The does were euthanized at the end of the breeding season, and their uteri were collected and stained. Two observers counted placental scars and grouped them by litter (estimated values) according to minimum differences in the following variables: 1) depth and 2) color of the crater at the implantation site, 3) sharpness of its outlines, 4) abundance and 5) color of macrophages, 6) size and 7) color of the antimesometrial depression. Atypical scars, possibly due to resorption of embryos, were not included in the estimated number of leverets delivered. A strong relation was found between the age of scars and categories of variables using a factorial correspondence analysis. Estimated values of fecundity and the number of litters were highly correlated with the reference values (r2=0.84 and 0.70, respectively). However, we slightly underestimated the variance in the frequency distribution of litter sizes as compared to the reference distribution. The method is therefore robust for estimating mean values of breeding parameters within a population. With adequate adult survival rates, it can also be used to compute an indirect index of survival of leverets by comparing mean number of leverets produced per female to age structure of the population in the autumn harvest.
PDF
