Home range size is one of the most fundamental ecological parameters that can be described 36 for any given species and can be viewed as a trade-off between resource access and energetic 37 costs. The minimum size of an animal's home range is fundamentally determined by the 38 ability to obtain enough food resources for survival and to secure successful reproduction 39 (Burt 1943) but the actual use of space is influenced by a far more complex array of factors. We used location data on wolves monitored within the on-going Scandinavian Wolf Research wolves within a specific pack may have changed between years but the approximate estimates. An effect of pack size on home range size was mainly observed when using kernel 380 estimates, where range size decreased with increasing number of wolves in a pack (Table 3). but not for OREP, is likely an effect of these roads functioning as a "natural" barrier for wolf 399 home movements which is not used but still included in MCP ranges. (Fig. 4) (non-ungulate) prey species that we were not able to measure. Although there is no evidence 472 that these non-ungulate species constitute major parts of wolf diet, they may have more subtle 473 influences in some key periods or on larger scale movement patterns. 474The Scandinavian wolf population has constantly increased during the years of the study 475 and an effect of population density on home range size was expected but not observed. The limiting effect on space use. The inverse effect of density may however be masked by some of 485 the smallest home ranges being isolated from the main population's distribution (Fig. 1)
1. Understanding the role of predation in shaping the dynamics of animal communities is a fundamental issue in ecological research. Nevertheless, the complex nature of predator–prey interactions often prevents researchers from modelling them explicitly.2. By using periodic Leslie–Usher matrices and a simulation approach together with parameters obtained from long-term field projects, we reconstructed the underlying mechanisms of predator–prey demographic interactions and compared the dynamics of the roe deer–red fox–Eurasian lynx–human harvest system with those of the moose–brown bear–gray wolf–human harvest system in the boreal forest ecosystem of the southern Scandinavian Peninsula.3. The functional relationship of both roe deer and moose λ to changes in predation rates from the four predators was remarkably different. Lynx had the strongest impact among the four predators, whereas predation rates by wolves, red foxes, or brown bears generated minor variations in prey population λ. Elasticity values of lynx, wolf, fox and bear predation rates were −0·157, −0·056, −0·031 and −0·006, respectively, but varied with both predator and prey densities.4. Differences in predation impact were only partially related to differences in kill or predation rates, but were rather a result of different distribution of predation events among prey age classes. Therefore, the age composition of killed individuals emerged as the main underlying factor determining the overall per capita impact of predation.5. Our results confirm the complex nature of predator–prey interactions in large terrestrial mammals, by showing that different carnivores preying on the same prey species can exert a dramatically different demographic impact, even in the same ecological context, as a direct consequence of their predation patterns. Similar applications of this analytical framework in other geographical and ecological contexts are needed, but a more general evaluation of the subject is also required, aimed to assess, on a broader systematic and ecological range, what specific traits of a carnivore are most related to its potential impact on prey species.
Abstract. Recolonizing carnivores can have a large impact on the status of wild ungulates, which have often modified their behavior in the absence of predation. Therefore, understanding the dynamics of reestablished predator-prey systems is crucial to predict their potential ecosystem effects. We decomposed the spatial structure of predation by recolonizing wolves (Canis lupus) on two sympatric ungulates, moose (Alces alces) and roe deer (Capreolus capreolus), in Scandinavia during a 10-year study. We monitored 18 wolves with GPS collars, distributed over 12 territories, and collected records from predation events. By using conditional logistic regression, we assessed the contributions of three main factors, the utilization patterns of each wolf territory, the spatial distribution of both prey species, and fine-scale landscape structure, in determining the spatial structure of moose and roe deer predation risk. The reestablished predator-prey system showed a remarkable spatial variation in kill occurrence at the intra-territorial level, with kill probabilities varying by several orders of magnitude inside the same territory. Variation in predation risk was evident also when a spatially homogeneous probability for a wolf to encounter a prey was simulated. Even inside the same territory, with the same landscape structure, and when exposed to predation by the same wolves, the two prey species experienced an opposite spatial distribution of predation risk. In particular, increased predation risk for moose was associated with open areas, especially clearcuts and young forest stands, whereas risk was lowered for roe deer in the same habitat types. Thus, fine-scale landscape structure can generate contrasting predation risk patterns in sympatric ungulates, so that they can experience large differences in the spatial distribution of risk and refuge areas when exposed to predation by a recolonizing predator. Territories with an earlier recolonization were not associated with a lower hunting success for wolves. Such constant efficiency in wolf predation during the recolonization process is in line with previous findings about the naı¨ve nature of Scandinavian moose to wolf predation. This, together with the human-dominated nature of the Scandinavian ecosystem, seems to limit the possibility for wolves to have large ecosystem effects and to establish a behaviorally mediated trophic cascade in Scandinavia.
Measuring activity levels in animals provides important information about their behavioral ecology and may be a relevant factor in management and conservation. We tested an individual-based method to discriminate active and passive behaviors on brown bears (Ursus arctos), using a dual-axis motion sensor mounted on Global Positioning System-Global System for Mobile Communications (GPS-GSM) collars. The method takes into account individual variation in activity levels and does not require further calibration. We validated the method through direct observations of captive bears and an extensive survey of wild bear signs in the boreal forest of central Sweden. We found good correspondence between sensor-measured and observed activity on captive bears. Analysis of wild bear signs at GPS locations and its comparison with the collar-based activity status confirmed the possibility of successfully applying the method to study brown bear activity patterns in the wild. The method provided 94.3% correct activity classification on captive bears and about 78.2% on wild bears. We tested the possibility of using this technique to measure increasing levels of activity by analyzing the correlation between the collar-derived numeric activity and the intensity of bear movement. At a broader scale (active vs. passive), the sensor-measured value provided information on the degree of activity, but no correlation was evident at a finer scale (specific behaviors). We suggest that using more sensors in different regions of a bear's body could overcome this difficulty and improve our knowledge of animal behavior in the wild, through remote monitoring of activity levels. We conclude that this method can be useful in the study of behavioral ecology of a wide range of animals, especially species that are difficult to observe or move great distances. (WILDLIFE SOCIETY BULLETIN 34(5):1314-1319 2006)
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