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1 March 2013 Seasonal and daily activity patterns of free-living Eurasian lynx Lynx lynx in relation to availability of kills
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Abstract

Activity patterns of predators are influenced by several factors including season and temperature as well as the availability of prey species. We investigated the activity of six free-living Eurasian lynx Lynx lynx (four males and two females without kittens) in the Bohemian Forest along the border between Germany and the Czech Republic. The lynx were tagged with GPS-collars with acceleration sensors in 2005, 2010 and 2011. Activity was measured every 5 minutes on 1,360 days (403,467 measurements) to detect circadian activity patterns. All lynx were predominantly crepuscular, with an average activity of 8.9 hours/day and with the lowest activity at midday. The activity patterns of male and female lynx did not differ significantly. With each 10°C increase in the mean air temperature per day, the lynx decreased their daily activity by 30 minutes. In winter, activity was concentrated at dusk. We also investigated whether lynx activity was influenced by the availability of freshly killed roe deer Capreolus capreolus, red deer Cervus elaphus or European hare Lepus europaeus. We compared the activity data of 357 days with a kill (109 recorded kills) and 316 days without a kill and calculated generalised additive mixed models. On days with a kill, the lynx were 3.3 hours/ day less active than on days without a kill. The activity on consecutive days with a killed prey did not differ. The pattern of activity on days with a kill differed little from the pattern of activity on days without a kill.

Many factors affect the activity of animals, including the sex and reproductive status of the animal (Schmidt 1999, Kolbe & Squires 2007) and environmental factors such as temperature (Beltran & Delibes 1994), light (Nielsen 1983) and season (Manfredi et al. 2011). For many carnivores, including wild felids, other important factors are the availability and activity of prey species (Ferguson et al. 1988, Beier et al. 1995). For example, Iriomote cats Prionailurus iriomotensis (Schmidt et al. 2009), jaguars Panthera onca and pumas Puma concolor (Harmsen et al. 2011) synchronise their activity peaks with those of their prey. The avoidance of humans can also influence the behaviour as it has been shown for snow leopards Uncia uncia (Wolf & Ale 2009) and wolves Canis lupus (Theuerkauf et al. 2003).

The Eurasian lynx Lynx lynx mainly hunts ungulates and generally chooses prey species which are slightly larger than itself and most common in a certain area (Jedrzejewski et al. 1993, Sunquist & Sunquist 2002, Breitenmoser & Breitenmoser-Würsten 2008). In the Bohemian Forest, roe deer Capreolus capreolus is the main prey of the lynx (Heurich et al. 2012). Other prey include red deer Cervus elaphus, especially calves, yearlings and females, as well as birds and small mammals (Fejklová 2002).

How lynx activity changes after having made a kill has not yet been studied in detail. A large kill provides enough food for several days (Okarma et al. 1997). During these days the need to hunt may stop or is at least reduced, and the lynx can spend longer time eating or performing other activities. Bernhart's (1990) and Reinhardt & Halle's (1999) observations on two and one lynx, respectively, support this hypothesis, showing that the lynx were less active on days when a killed prey was available. In a third study, Schmidt (1999) found that the activity of the lynx is lowest on the first day after the kill and increases gradually as the available meat decreases.

Former activity studies on large felids mainly focused on animal movements, recorded by radio-tracking (Bernhart 1990, Odden & Wegge 2005, Schmidt et al. 2009), camera trapping (Kolowski & Alonso 2010, Harmsen et al. 2011), or by only analysing indirect signs such as footprints or faeces (Saunders 1963, Wolf & Ale 2009). Reinhardt & Halle (1999) and Schmidt (1999) used activity sensors, which were not limited to only one type of activity, but were able to detect every possible action of an animal except resting or sleeping. Nonetheless, in the 1990s the sensors in radio-collars could only provide a relatively small amount of data. Nowadays, the new generation of GPS-collars include acceleration sensors, which detect the activity of an animal on a finer scale and allow collection of a large amount of data (Löttker et al. 2009). Gervasi et al. (2006) found good correspondence between sensor-measured and observed activity on brown bears Ursus arctos. This method is especially useful to investigate the behaviour of cryptic, mainly night active, forest living species occurring at low densities such as the Eurasian lynx, which can rarely, if at all, be directly observed (Altmann 1974).

We studied the behaviour of free-living Eurasian lynx in the Bohemian Forest using GPS-collars with acceleration sensors. We investigated the daily activity patterns, their seasonal changes, the influence of ambient temperature and sex of the lynx on activity, and whether the activity changes on days after successful hunting of prey.

Material and methods

Study area

The Bohemian Forest represents a forested mountain range along the border between Bavaria (Germany) and the southwestern part of the Czech Republic. The core area of our study was located in two contiguous protected areas, the Bavarian Forest National Park (240 km2; 49°3‘19″N, 13°12‘9″E) and the Šumava National Park (690 km2; 49°7‘0″N, 13°36‘0″E). Data were also collected from the adjacent Bavarian Forest Natural Park (3,007 km2) and the Bohemian Forest Protected Landscape Area (1,000 km2). Together, the four parks form the largest strictly protected continuous forest expanse in Central Europe, the so-called Bohemian Forest Ecosystem. Compared to elsewhere in Europe, the human population density is very low; < 2 inhabitants/km2 in the core area and at the margins (outside the national parks) approximately 70 inhabitants/km2 in Germany and < 30 inhabitants/km2 in the Czech Republic. The elevation ranges from 600 to 1,453 m a.s.l., with an average annual temperature of 6.5°C at lower elevations and 3.0°C at higher elevations. The mean annual precipitation is between 830 and 2,230 mm. Snow cover persists for 7-8 mo