Recording ultrasonic echolocation calls of bats using bat-detectors is often used for wide-scale monitoring in studies on bat management and conservation. In Europe, the most important legal instrument for bat conservation is the Habitat Directive (43/92/EEC), which defines various levels of species (and habitat) protection for different bat species and/or genera. Thus for most management needs, the usefulness of bat-monitoring techniques depends on the possibility to determine to species/genus. We compared the discrimination performances of 4 statistical methods applied to identify bat species from their ultrasonic echolocation calls. In 3 different areas of northern Italy, we made recordings of 20 species of bat (60% of those occurring in Italy), 17 from the family Vespertilionidae and 3 from Rhinolophidae. Calls of bats identified to species level from morphological and genetic characters were time-expanded and recorded on release. We measured 7 variables from each call, and we developed classification models through both conventional tests (multiple discriminant analysis and cluster analysis) that were based on a classical statistical approach, and through 2 nonconventional classifiers (classification and regression trees, and neural networks) that relied on generalization and fuzzy reasoning. We compared the performance of the 4 techniques using the percentage of cases classified correctly in 5 classification trials at various taxonomic levels that were characterized by an increasingly difficult identification task: (1) family level (Rhinolophidae vs. Vespertilionidae), (2) species level within genus Rhinolophus, (3) genus level within Vespertilionidae, (4) species level within genus Myotis, and (5) all species. Multiple discriminant function analysis (DFA) correctly classified marginally more cases than artificial neural networks (ANN; 74-100% against 64-100%), especially at the species level (trial 4, species of genus Myotis; trial 5, all species). Both these techniques performed better than cluster analysis or classification and regression trees, the latter reaching only 56 and 41% in Myotis species and all species trials. Artificial neural networks do not yet seem to offer a major advantage over conventional multivariate methods (e.g., DFA) for identifying bat species from their ultrasonic echolocation calls. JOURNAL OF WILDLIFE MANAGEMENT 69(4):1601-1614; 2005

Populations on the limits of species' distribution can show different behavioral adaptations to strong ecological pressure than in the central part of the range. We investigated space use patterns of alpine mountain hare (Lepus timidus) at two areas on the southern edge of the species' range. We monitored 34 hares between 2005 and 2008, estimating home range size, overlap, and site fidelity, and compared our results with space use in Scottish and North-European populations. Home ranges of mountain hares did not differ between two study areas with different habitat types. Subadult animals used larger ranges than adults and both age groups reduced home range size in autumn, a period that might be critical for hares due to changes in diet and/or high energy expenditure during the previous breeding season. Home ranges in these alpine populations were smaller than in Scandinavian populations but within the range of populations in different habitat types in Scotland. Seasonal home ranges overlapped considerably, but differed among the sexes: male-female overlap was higher than same sex (male-male and female-female) spatial overlap. Seasonal shifts of home ranges were small, and site fidelity remained high over the seasons, suggesting that resource distribution remained constant throughout the year and that the knowledge of an intensively frequented area is an important element of habitat quality. We concluded that habitat structure and availability of mates interact in affecting mountain hare space use in alpine habitats.

Estimating density, age and sex structure of wild populations is a key objective in wildlife management. Live trapping is frequently used to collect data on populations of small and medium-sized mammals. Ideally, sampling mammal populations by live capturing of individuals provides a random and representative sample of the target population. Trapping data may, however, be biased. We used live-capture data from mountain hares Lepus timidus in Scotland to assess sampling bias between two different capture methods. We captured hares using baited cage traps and long nets on five study areas in the Scottish Highlands. After controlling for the effects of body size, individuals caught in traps were lighter than individuals caught using long nets, suggesting that the body condition of hares differed between the capture methods. This tendency may reflect an increased risk-taking of individuals in poorer body condition and less aversion to entering traps in order to benefit from eating bait. Overall, we caught more adult hares than juveniles and more female hares than males. Our results show that estimates of density and population structure of mountain hares using livecapture data could be affected by the capture method used. We suggest that live-capture studies employ more than one capture method and test for heterogeneity in capture probability to minimise potential bias and achieve reliable estimates of population parameters.

We investigated activity patterns and habitat use of 34 radio-tracked mountain hares (Lepus timidus) in the Italian Alps. We first showed that hares were nocturnal and that activity patterns changed seasonally in parallel with circadian rhythms. We predicted that day home ranges will include suitable resting (shelter) habitats, and night home ranges will primarily include suitable foraging habitats. A hare's night-range was larger than its day-range. On average, night and day ranges overlapped by 36%, suggesting that selective pressures affecting space use were, at least partly, different at night than day. Dwarf mountain-pine was the most preferred habitat in all seasons and was selected both for active behaviour (night) and resting (day) and hares avoided the most open habitats. Exploring the effects of season, time of day (day vs. night) and site, we found that habitat use by mountain hares did not differ between seasons or between the active (night) and resting (day) period of circadian cycle. Also, we found no effects of differences in landscape structure (habitat patchiness and heterogeneity) on the patterns of habitat selection. Hares always preferred the dense, forested habitats, which seemed to provide food resources as well as shelter from predators throughout the year