Statistical Methods for Identifying Wolf Kill Sites Using Global Positioning System Locations

Abstract: Accurate estimates of kill rates remain a key limitation to addressing many predator—prey questions. Past approaches for identifying kill sites of large predators, such as wolves (Canis lupus), have been limited primarily to areas with abundant winter snowfall and have required intensive ground-tracking or aerial monitoring. More recently, attempts have been made to identify clusters of locations obtained using Global Positioning System (GPS) collars on predators to identify kill sites. However, because decision rules used in determining clusters have not been consistent across studies, results are not necessarily comparable. We illustrate a space—time clustering approach to statistically define clusters of wolf GPS locations that might be wolf kill sites, and we then use binary and multinomial logistic regression to model the probability of a cluster being a non—kill site, kill site of small-bodied prey species, or kill site of a large-bodied prey species. We evaluated our approach using field visits of kills and assessed the accuracy of the models using an independent dataset. The cluster-scan approach identified 42–100% of wolf-killed prey, and top logistic regression models correctly classified 100% of kills of large-bodied prey species, but 40% of small-bodied prey species were classified as nonkills. Although knowledge of prey distribution and vulnerability may help refine this approach, identifying small-bodied prey species will likely remain problematic without intensive field efforts. We recommend that our approach be utilized with the understanding that variation in prey body size and handling time by wolves will likely have implications for the success of both the cluster scan and logistic regression components of the technique. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):798–807; 2008)     

Wolf Movement Patterns: a Key to Estimation of Kill Rate?

Abstract: To estimate wolf (Canis lupus) kill rates from fine-scale movement patterns, we followed adult wolves in 3 territories of the Scandinavian wolf population using Global Positioning Systems (GPS) during the winters of 2001–2003. The resulting 6 datasets of 62–84 study days gave a total of 8,747 hourly GPS positions. We visited clusters of positions in the field on average 8.8 days after positioning and found moose (Alces alces) killed by wolves during the study period on 74 (8%) of the 953 clusters. The number of positions and visits to a cluster, their interaction, and the proportion of afternoon positions were significant fixed effects in mixed logistic-regression models predicting the probability of a cluster containing a wolf-killed moose. The models, however, displayed a poor goodness-of-fit and were not a suitable tool for estimating kill rates from positioning data alone. They might be used to reduce fieldwork by excluding unlikely clusters, although the reduction was not substantial. We discuss proximate factors (i.e., human disturbance and access to prey) as well as ultimate factors (i.e., social organization, intra-guild dominance, and litter size) as potential causes of the observed high temporal and spatial variation in prey-handling. For similar future kill-rate studies, we recommend increasing field efforts and shortening positioning intervals.     

Encounter frequencies between GPS-collared wolves (Canis lupus) and moose (Alces alces) in a Scandinavian wolf territory

Over 6,000 GPS fixes from two wolves (Canis lupus) and 30,000 GPS fixes from five moose (Alces alces) in a wolf territory in southern Scandinavia were used to assess the static and dynamic interactions between predator and prey individuals. Our results showed that wolves were closer to some of the moose when inside their home ranges than expected if they had moved independently of each other, and we also found a higher number of close encounters (<500 m) than expected. This suggests that the wolves were actively seeking the individual moose within their territory. Furthermore, the wolves showed a preference for moving on gravel forest roads, which may be used as convenient travel routes when patrolling the territory and seeking areas where the moose are. However, due to the particularly large size of the wolf territory combined with relatively high moose densities, the wolves generally spent a very small proportion of their time inside the home range of each individual moose, and the frequency of encounters between the wolves and any particular moose was very low. We suggest that the high moose:wolf ratio in this large Scandinavian wolf territory compared to that typically occurring in North America, results in a relatively low encounter frequency and a low predation risk for individual moose, as the predation pressure is spread over a high number of prey individuals.     

Evaluating Global Positioning System Telemetry Techniques for Estimating Cougar Predation Parameters

ABSTRACT Using clusters of locations obtained from Global Positioning System (GPS) telemetry collars to identify predation events may allow more efficient estimation of behavioral predation parameters for the study and management of large carnivore predator-prey systems. Applications of field- and model-based GPS telemetry cluster techniques, however, have met with mixed success. To further evaluate and refine these techniques for cougars (Puma concolor), we used data from visits to 1,735 GPS telemetry clusters, 637 of which were locations where cougars killed prey >8 kg in a multi-prey system in west-central Alberta. We tested 1) whether clusters were reliably created at kill locations, 2) the ability of logistic regression models to identify kill occurrence (prey >8 kg) and multinomial regression models to identify the prey species at a kill cluster, and 3) the duration of monitoring required to accurately estimate kill rate and prey composition. We found that GPS collars programmed to attempt location fixes every 3 hours consistently identified locations where prey >8 kg were handled, and cluster creation was robust to GPS location acquisition failures (poor collar fix success). The logistic regression model was capable of estimating cougar kill rate with a mean 5-fold cross validation error of <10%, provided the appropriate probability cutoff distinguishing kill clusters from non-kill clusters was selected. Logistic models also can be used to direct visits to clusters, reducing field efforts by as much as 25%, while still locating >95% of all kills. The multinomial model overpredicted occurrence of primary prey (deer) in the diet and underpredicted consumption of alternate prey (e.g., elk and moose) by as much as 100%. We conclude that a purely model-based approach should be used cautiously and that field visitation is required to obtain reliable information on species, sex, age, or condition of prey. Ultimately, we recommend a combined approach that involves using models to direct field visitation when estimating behavioral predation parameters. Regardless of the monitoring approach, long continuous monitoring periods (i.e., >100 days of a 180-day period) were necessary to reduce bias and imprecision in kill rate and prey composition estimates.     

Ecological factors drive differentiation in wolves from British Columbia

Aim Limited population structure is predicted for vagile, generalist species, such as the grey wolf (Canis lupus L.). Our aims were to study how genetic variability of grey wolves was distributed in an area comprising different habitats that lay within the potential dispersal range of an individual and to make inferences about the impact of ecology on population structure. Location British Columbia, Canada – which is characterized by a continuum of biogeoclimatic zones across which grey wolves are distributed – and adjacent areas in both Canada and Alaska, United States. Methods We obtained mitochondrial DNA control region sequences from grey wolves from across the province and integrated our genetic results with data on phenotype, behaviour and ecology (distance, habitat and prey composition). We also compared the genetic diversity and differentiation of British Columbia grey wolves with those of other North American wolf populations. Results We found strong genetic differentiation between adjacent populations of grey wolves from coastal and inland British Columbia. We show that the most likely factor explaining this differentiation is habitat discontinuity between the coastal and interior regions of British Columbia, as opposed to geographic distance or physical barriers to dispersal. We hypothesize that dispersing grey wolves select habitats similar to the one in which they were reared, and that this differentiation is maintained largely through behavioural mechanisms. Main conclusions The identification of strong genetic structure on a scale within the dispersing capabilities of an individual suggests that ecological factors are driving wolf differentiation in British Columbia. Coastal wolves are highly distinct and representative of a unique ecosystem, whereas inland British Columbia grey wolves are more similar to adjacent populations of wolves located in Alaska, Alberta and Northwest Territories. Given their unique ecological, morphological, behavioural and genetic characteristics, grey wolves of coastal British Columbia should be considered an Evolutionary Significant Unit (ESU) and, consequently, warrant special conservation status. If ecology can drive differentiation in a highly mobile generalist such as the grey wolf, ecology probably drives differentiation in many other species as well.     

Comparative Patterns of Predation by Cougars and Recolonizing Wolves in Montana's Madison Range

Abstract: Numerous studies have documented how prey may use antipredator strategies to reduce the risk of predation from a single predator. However, when a recolonizing predator enters an already complex predator—prey system, specific antipredator behaviors may conflict and avoidance of one predator may enhance vulnerability to another. We studied the patterns of prey selection by recolonizing wolves (Canis lupus) and cougars (Puma concolor) in response to prey resource selection in the northern Madison Range, Montana, USA. Elk (Cervus elaphus) were the primary prey for wolves, and mule deer (Odocoileus hemionus) were the primary prey for cougars, but elk made up an increasingly greater proportion of cougar kills annually. Although both predators preyed disproportionately on male elk, wolves were most likely to prey on males in poor physical condition. Although we found that the predators partitioned hunting habitats, structural complexity at wolf kill sites increased over time, whereas complexity of cougar kill sites decreased. We concluded that shifts by prey to structurally complex refugia were attempts by formerly naïve prey to lessen predation risk from wolves; nevertheless, shifting to more structurally complex refugia might have made prey more vulnerable to cougars. After a change in predator exposure, use of refugia may represent a compromise to minimize overall risk. As agencies formulate management strategies relative to wolf recolonization, the potential for interactive predation effects (i.e., facilitation or antagonism) should be considered.     

Testing Global Positioning System Telemetry to Study Wolf Predation on Deer Fawns

ABSTRACT We conducted a pilot study to test the usefulness of Global Positioning System (GPS) collars for investigating wolf (Canis lupus) predation on white-tailed deer (Odocoileus virginianus) fawns. Using GPS collars with short location-attempt intervals on 5 wolves and 5 deer during summers 2002–2004 in northeastern Minnesota, USA, demonstrated how this approach could provide new insights into wolf hunting behavior of fawns. For example, a wolf traveled ≥1.5–3.0 km and spent 20–22 hours in the immediate vicinity of known fawn kill sites and ≥0.7 km and 8.3 hours at scavenging sites. Wolf travel paths indicated that wolves intentionally traveled into deer summer ranges, traveled ≥0.7–4.2 km in such ranges, and spent <1–22 hours per visit. Each pair of 3 GPS-collared wolf pack members were located together for ≤6% of potential locations. From GPS collar data, we estimated that each deer summer range in a pack territory containing 5 wolves ≥1 year old and hunting individually would be visited by a wolf on average every 3–5 days. This approach holds great potential for investigating summer hunting behavior of wolves in areas where direct observation is impractical or impossible.     

Effect of sociality and season on gray wolf (Canis lupus) foraging behavior: implications for estimating summer kill rate

Background

Understanding how kill rates vary among seasons is required to understand predation by vertebrate species living in temperate climates. Unfortunately, kill rates are only rarely estimated during summer.

Methodology/Principal Findings

For several wolf packs in Yellowstone National Park, we used pairs of collared wolves living in the same pack and the double-count method to estimate the probability of attendance (PA) for an individual wolf at a carcass. PA quantifies an important aspect of social foraging behavior (i.e., the cohesiveness of foraging). We used PA to estimate summer kill rates for packs containing GPS-collared wolves between 2004 and 2009. Estimated rates of daily prey acquisition (edible biomass per wolf) decreased from 8.4±0.9 kg (mean ± SE) in May to 4.1±0.4 kg in July. Failure to account for PA would have resulted in underestimating kill rate by 32%. PA was 0.72±0.05 for large ungulate prey and 0.46±0.04 for small ungulate prey. To assess seasonal differences in social foraging behavior, we also evaluated PA during winter for VHF-collared wolves between 1997 and 2009. During winter, PA was 0.95±0.01. PA was not influenced by prey size but was influenced by wolf age and pack size.

Conclusions/Significance

Our results demonstrate that seasonal patterns in the foraging behavior of social carnivores have important implications for understanding their social behavior and estimating kill rates. Synthesizing our findings with previous insights suggests that there is important seasonal variation in how and why social carnivores live in groups. Our findings are also important for applications of GPS collars to estimate kill rates. Specifically, because the factors affecting the PA of social carnivores likely differ between seasons, kill rates estimated through GPS collars should account for seasonal differences in social foraging behavior.     

Comparing Ground Telemetry and Global Positioning System Methods to Determine Cougar Kill Rates

ABSTRACT We assessed whether use of 2 methods, intensive very high frequency (VHF) radiotelemetry and Global Positioning System (GPS) cluster sampling, yielded similar estimates of cougar (Puma concolor) kill rates in Yellowstone National Park, 1998–2005. We additionally determined biases (underestimation or overestimation of rates) resulting from each method. We used modeling to evaluate what characteristics of clusters best predicted a kill versus no kill and further evaluated which predictor(s) minimized effort and the number of missed kills. We conducted 16 VHF ground predation sequences resulting in 37 kill intervals (KIs) and 21 GPS sequences resulting in 84 KIs on 6 solitary adult females, 4 maternal females, and 5 adult males. Kill rates (days/kill and biomass [kg] killed/day) did not differ between VHF and GPS predation sampling methods for maternal females, solitary adult females, and adult males. Sixteen of 142 (11.3%) kills detected via GPS clusters were missed through VHF ground-based sampling, and the kill rate was underestimated by an average of 5.2 (95% CI = 3.8–6.6) days/kill over all cougar social classes. Five of 142 (3.5%) kills identified by GPS cluster sampling were incorrectly identified as the focal individual's kill from scavenging, and the kill rate was overestimated within the adult male social class by an average of 5.8 (95% CI = 3.0–8.5) days/ungulate kill. The number of nights (locations between 2000 hours and 0500 hours) a cougar spent at a cluster was the most efficient variable at predicting predation, minimizing the missed kills, and minimizing number of extra clusters that needed to be searched. In Yellowstone National Park, where competing carnivores displaced cougars from their kills, it was necessary to search extra sites where a kill may not have been present to ensure we did not miss small, ungulate prey kills or kills with displacement. Using predictions from models to assign unvisited clusters as no kill, small prey kill, or large prey kill can bias downward the number of kills a cougar made and bias upward kills made by competitors that displace cougars or scavenge cougar kills. Our findings emphasize that field visitation is crucial in determining displacement and scavenging events that can result in biases when using GPS cluster methods in multicarnivore systems.     

Wolves,white‐tailed deer,and beaver: implications of seasonal prey switching for woodland caribou declines

Population increases of primary prey can negatively impact alternate prey populations via demographic and behavioural responses of a shared predator through apparent competition. Seasonal variation in prey selection patterns by predators also can affect secondary and incidental prey by reducing spatial separation. Global warming and landscape changes in Alberta's bitumen sands have resulted in prey enrichment, which is changing the large mammal predator–prey system and causing declines in woodland caribou Rangifer tarandus caribou populations. We assessed seasonal patterns of prey use and spatial selection by wolves Canis lupus in two woodland caribou ranges in northeastern Alberta, Canada, that have undergone prey enrichment following recent white‐tailed deer Odocoileus virginianus invasion. We determined whether risk of predation for caribou (incidental prey) and the proportion of wolf‐caused‐caribou mortalities varied with season. We found that wolves showed seasonal variation in primary prey use, with deer and beaver Castor canadensis being the most common prey items in wolf diet in winter and summer, respectively. These seasonal dietary patterns were reflected in seasonal wolf spatial resource selection and resulted in contrasting spatial relationships between wolves and caribou. During winter, wolf selection for areas used by deer maintained strong spatial separation between wolves and caribou, whereas wolf selection for areas used by beaver in summer increased the overlap with caribou. Changing patterns in wolf resource selection were reflected by caribou mortality patterns, with 76.2% of 42 adult female caribou mortalities occurring in summer. Understanding seasonal patterns of predation following prey enrichment in a multiprey system is essential when assessing the effect of predation on an incidental prey species. Our results support the conclusion that wolves are proximately responsible for woodland caribou population declines throughout much of their range.     

Food habits of the world's grey wolves

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Complex tactics in a dynamic large herbivore–carnivore spatiotemporal game

The spatiotemporal game between predators and prey is a fundamental process governing their distribution dynamics. Players may adopt different tactics as the associated costs and benefits change through time. Yet few studies have investigated the potentially simultaneous and dynamic nature of movement tactics used by both players. It is particularly unclear to what extent perceived predation risk mediates the fine‐scale distribution of large and dangerous prey, which are mostly driven by bottom–up, resource‐related processes. We built habitat use and movement models based on 10 years of monitoring GPS‐collared grey wolves Canis lupus and plains bison Bison bison bison in Prince Albert National Park, Canada, to investigate the predator–large prey game in a multi‐prey system. Bison did not underuse patches of high‐quality vegetation at any time during the seasonal cycle even though wolves were selectively patrolling these areas. Rather, in at least one season, bison engaged in complex tactics comprised of proactive responses to the long‐term distribution (risky places) and reactive responses to the immediate proximity (risky times) of their opponent. In summer–autumn, bison reduced the time spent in food‐rich patches as both the long‐term use and the immediate proximity of wolves increased. By demonstrating that wolf distribution triggers patch abandonment by bison, we provide a key element in support of the shell game hypothesis – where prey move constantly to avoid predators attempting to anticipate their location. In winter, a season of relatively high energetic stress, bison no longer abandoned food‐rich patches as predation risk increased, while no bison responses to wolves were observed in spring–summer. Our work demonstrates the highly dynamic and complex nature of the predator–large prey spatiotemporal game, a key trait‐mediated mechanism by which trophic interactions structure ecological communities.     

Underestimating the frequency,strength and cost of antipredator responses with data from GPS collars: an example with wolves and elk

Field studies that rely on fixes from GPS‐collared predators to identify encounters with prey will often underestimate the frequency and strength of antipredator responses. These underestimation biases have several mechanistic causes. (1) Step bias: The distance between successive GPS fixes can be large, and encounters that occur during these intervals go undetected. This bias will generally be strongest for cursorial hunters that can rapidly cover large distances (e.g., wolves and African wild dogs) and when the interval between GPS fixes is long relative to the duration of a hunt. Step bias is amplified as the path travelled between successive GPS fixes deviates from a straight line. (2) Scatter bias: Only a small fraction of the predators in a population typically carry GPS collars, and prey encounters with uncollared predators go undetected unless a collared group‐mate is present. This bias will generally be stronger for fission–fusion hunters (e.g., spotted hyenas, wolves, and lions) than for highly cohesive hunters (e.g., African wild dogs), particularly when their group sizes are large. Step bias and scatter bias both cause underestimation of the frequency of antipredator responses. (3) Strength bias: Observations of prey in the absence of GPS fix from a collared predator will generally include a mixture of cases in which predators were truly absent and cases in which predators were present but not detected, which causes underestimation of the strength of antipredator responses. We quantified these biases with data from wolves and African wild dogs and found that fixes from GPS collars at 3‐h intervals underestimated the frequency and strength of antipredator responses by a factor >10. We reexamined the results of a recent study of the nonconsumptive effects of wolves on elk in light of these results and confirmed that predation risk has strong effects on elk dynamics by reducing the pregnancy rate.     

Legal protection of wolves in Poland: implications for the status of the wolf population

Legal protection of wolves (Canis lupus) in Poland was implemented in 1998 after 23 years of management as a game species. Wolves occurring in Poland were interconnected with larger populations in the Carpathian Mountains and Belarus, Baltic States and Russia, stable in numbers, and were not considered endangered before the change in legal status affording protection from hunting. Parties calling for wolf protection wanted to stop killing of wolves because of their symbolic nature, but did not have particular management goals to achieve. The government did not accompany the change in legal status by management plan, and therefore, the ban on wolf hunting was weakly enforced. A wolf distribution monitoring demonstrated that wolf range had not expanded 9 years after the hunting ban was implemented, and no increase in wolf numbers was observed. This failure to recover may be explained by: (1) a significant (up to 35%) reduction in the wolves’ prey base 6 years before wolf hunting was stopped, (2) weak enforcement of the protection law, resulting in lack of poaching control of wolves, (3) probable increasing fragmentation and isolation of wolf habitat caused by rapid economic growth in Poland. Inconsistent application of current management policy toward wolves resulted in weak enforcement of regulations and promoted negative attitudes toward the species. To improve the status of wolves in Poland, I recommend a flexible wolf management planning framework that involves and addresses attitudes of hunters and sheep herders, includes a framework to promote strong law enforcement, and consistent, fair compensation for livestock killed by wolves.     

Summer kill rates and predation pattern in a wolf–moose system: can we rely on winter estimates?

So far the vast majority of studies on large carnivore predation, including kill rates and consumption, have been based on winter studies. Because large carnivores relying on ungulates as prey often show a preference for juveniles, kill rates may be both higher and more variable during the summer season than during the rest of the year leading to serious underestimates of the total annual predation rate. This study is the first to present detailed empirical data on kill rates and prey selection in a wolf–moose system during summer (June–September) as obtained by applying modern Global Positioning System-collar techniques on individual wolves (Canis lupus) in Scandinavia. Moose (Alces alces) was the dominant prey species both by number (74.4%) and biomass (95.6%); 89.9% of all moose killed were juveniles, representing 76.0% of the biomass consumed by wolves. Kill rate in terms of the kilogram biomass/kilogram wolf per day averaged 0.20 (range: 0.07–0.32) among wolf territories and was above, or well above, the daily minimum food requirements in most territories. The average number of days between moose kills across wolf territories and study periods was 1.71 days, but increased with time and size of growing moose calves during summer. Over the entire summer (June–September, 122 days), a group (from two to nine) of wolves killed a total of 66 (confidence interval 95%; 56–81) moose. Incorporation of body growth functions of moose calves and yearlings and wolf pups over the summer period showed that wolves adjusted their kill rate on moose, so the amount of biomass/kilogram wolf was relatively constant or increased. The kill rate was much higher (94–116%) than estimated from the winter period. As a consequence, projecting winter kill rates to obtain annual estimates of predation in similar predator–prey systems may result in a significant underestimation of the total number of prey killed. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Moose movement rates are altered by wolf presence in two ecosystems

Predators directly impact prey populations through lethal encounters, but understanding nonlethal, indirect effects is also critical because foraging animals often face trade‐offs between predator avoidance and energy intake. Quantifying these indirect effects can be difficult even when it is possible to monitor individuals that regularly interact. Our goal was to understand how movement and resource selection of a predator (wolves; Canis lupus) influence the movement behavior of a prey species (moose; Alces alces). We tested whether moose avoided areas with high predicted wolf resource use in two study areas with differing prey compositions, whether avoidance patterns varied seasonally, and whether daily activity budgets of moose and wolves aligned temporally. We deployed GPS collars on both species at two sites in northern Minnesota. We created seasonal resource selection functions (RSF) for wolves and modeled the relationship between moose first‐passage time (FPT), a method that discerns alterations in movement rates, and wolf RSF values. Larger FPT values suggest rest/foraging, whereas shorter FPT values indicate travel/fleeing. We found that the movements of moose and wolves peaked at similar times of day in both study areas. Moose FPTs were 45% lower in areas most selected for by wolves relative to those avoided. The relationship between wolf RSF and moose FPT was nonlinear and varied seasonally. Differences in FPT between low and high RSF values were greatest in winter (?82.1%) and spring (?57.6%) in northeastern Minnesota and similar for all seasons in the Voyageurs National Park ecosystem. In northeastern Minnesota, where moose comprise a larger percentage of wolf diet, the relationship between moose FPT and wolf RSF was more pronounced (ave. across seasons: ?60.1%) than the Voyageurs National Park ecosystem (?30.4%). These findings highlight the role wolves can play in determining moose behavior, whereby moose spend less time in areas with higher predicted likelihood of wolf resource selection.     

Spatial interactions between grey wolves and Eurasian lynx in Białowieża Primeval Forest, Poland

Various species of large predators are reported to influence each other through interference or exploitation competition that may affect demography and survival of the subordinate species. We analyzed spatial relationships between grey wolf (Canis lupus) and Eurasian lynx (Lynx lynx) in Białowieża Primeval Forest (BPF, eastern Poland) to determine how they partitioned the space. The wolves (n = 8) and lynx (n = 14) were radio-tracked in 1991–1999. Three wolves and seven lynx were radio-tracked simultaneously in 1994–1996. Territories of wolf packs and home ranges of lynx overlapped considerably (76% of wolf territories and 50% of lynx home ranges, on average). In three cases, their core areas were also overlapping. Wolf-lynx dyads with overlapping home ranges were simultaneously located at distances from 0 to 28 km from each other. We found neither avoidance nor attraction between wolves and lynx occupying the same areas. We concluded that in BPF, the two large predators coexist due to specialization on different preferred prey and heterogeneous habitat.     

Coexistence of wolves and humans in a densely populated region (Lower Saxony,Germany)

Since the first sporadic occurrences of grey wolves (Canis lupus) west of the Polish border in 1996, wolves have shown a rapid population recovery in Germany. Wolves are known to avoid people and wolf attacks on humans are very rare worldwide. However, the subjectively perceived threat is considerable, especially as food-conditioned habituation to humans occurs sporadically. Lower Saxony (Germany) has an exceedingly higher human population density than most other regions with territorial wolves; thus, the potential for human–wolf conflicts is higher. Using hunters’ wildlife survey data from 455 municipalities and two years (2014–2015) and data from the official wolf monitoring (557 confirmed wolf presences and 500 background points) collected between 2012–2015, grey wolf habitat selection was modelled using generalized additive models with respect to human population density, road density, forest cover and roe deer density. Moreover, we tested whether habitat use changed in response to human population and road density between 2012/2013 and 2014/2015.Wolves showed a preference for areas of low road density. Human population density was less important as a covariate in the model of the survey data. Areas with higher prey abundance (5–10 roe deer/km²) and areas with >20% forest cover were preferred wolf habitats. Wolves were mostly restricted to areas with the lowest road and human population densities. However, between the two time periods, avoidance of human density decreased significantly.Recolonization of Germany is still in its early stages and it is unclear where this process will halt. To-date authorities mainly concentrate on monitoring measures. However, to avoid conflict, recolonization will require more stringent management of wolf populations and an improved information strategy for rural populations.     

Genetic characterization of grey wolves (<Emphasis Type="Italic">Canis lupus</Emphasis> L. <Emphasis Type="Italic">1758</Emphasis>) from Bosnia and Herzegovina: implications for conservation

The grey wolves of Bosnia and Herzegovina form a subpopulation of the Dinaric-Balkan wolf population and represent one of Europe’s least studied wolf populations. Since the Dinaric-Balkan population is a valuable source of genetic diversity for neighboring populations, comprehensive assessments are warranted. We aimed to determine the genetic variability and structure of the grey wolf population from Bosnia and Herzegovina, as well as estimate levels of gene flow and inbreeding and evaluate genetic signals of a bottleneck. To do this, we analyzed the variability of eighteen microsatellite loci. We found moderately high genetic heterozygosity for wolves from Bosnia and Herzegovina, as described for other Dinaric-Balkan wolf populations. We reveal weak genetic structuring with two genetic clusters identified. Wolves from the eastern part of the region formed a relatively distinct cluster, whereas individuals in the second cluster overlapped quite considerably with admixed individuals. Despite the signal of genetic structure being weak, clustering of individuals from the eastern part of the country extended through all analyses. Thus, this cluster could be considered a separate management unit, perhaps requiring specific conservation attention.     

Diet of wolves <Emphasis Type="Italic">Canis lupus</Emphasis> returning to Hungary

At the end of the nineteenth century, the wolf Canis lupus was extinct in Hungary and in recent decades has returned to the northern highland area of the country. The diet of wolves living in groups in Aggteleki National Park was investigated using scat analysis (n = 81 scats) and prey remains (n = 31 carcasses). Throughout the year wolves (average, minimum two wolves per year) consumed mostly wild-living ungulates (mean percent of biomass consumed, B% 97.2%; relative frequency of occurrence, %O 74.0%). The wild boar Sus scrofa was the most common prey item found in wolf scat (%B 35.6%) and is also the most commonly occurring ungulate in the study areas. The second most commonly occurring prey item in wolf scat was red deer Cervus elaphus (B% 32.8%). Conversely, prey remain analyses revealed wild boar as the second most commonly utilised prey species (%O 16.1%) after red deer (%O 67.7%). The roe deer Capreolus capreolus that occurs at lower population densities was the third most commonly utilised prey species. The importance of low population density mouflon Ovis aries, livestock and other food types was low. The results are similar to those found in the northern part of the Carpathian Mountains.