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Wolf activity varies considerably among differentstudies that explained activity patterns by factors suchas human activity, breeding status or prey availability(Fancy and Ballard 1995; Vila` et al. 1995; Ciucci et al.1997; Theuerkauf et al. 2003; Kusak et al. 2005; Chavezand Gese 2006; Theuerkauf et al. 2007). However, it islikely that the high variability of wolf activity patterns isa result of their ability to react to various environmentalconditions (Packard 2003). Activity of individual wolvesmay also vary among days, switching from being diurnalto nocturnal. The purpose of our study was to examinethe variability of wolf activity between days and seasonsand to determine the most important factors thatinfluence activity in the Bieszczady Mountains, Poland.The study was conducted in the Bieszczady Moun-tains (Polish Carpathians) over an area of about1000km
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SHORT COMMUNICATION
Daily and seasonal variation in wolf activity in the Bieszczady Mountains,
SE Poland
Julia Eggermann
a
, Roman Gula
b
, Bartosz Pirga
b
,Jo
¨rn Theuerkauf
b,
,
Hiroshi Tsunoda
c,1
, Barbara Brzezowska
d
, Sophie Rouys
e
, Stephan Radler
f
a
Faculty of Biology and Biotechnology, Ruhr University Bochum, Universita
¨tsstr. 150, 44801 Bochum, Germany
b
Museum and Institute of Zoology, Polish Academy of Sciences, Wilcza 64, 00-679 Warsaw, Poland
c
Wildlife Conservation Laboratory, Graduate School of Agriculture, Tokyo University of Agriculture and Technology,
3-5-8 Saiwai-cho, Fuchu-shi, Tokyo 183-8509, Japan
d
Department of Animal Ecology, Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7,
30-387 Krako
´w, Poland
e
Conservation Research New Caledonia, BP 25 49, 98846 Noumea, New Caledonia
f
University of Applied Forest Sciences Rottenburg, Schadenweilerhof, 72108 Rottenburg, Germany
Received 9 January 2008; accepted 30 May 2008
Keywords: Activity pattern; Canis lupus; Distance travelled; Movements; Poland
Wolf activity varies considerably among different
studies that explained activity patterns by factors such
as human activity, breeding status or prey availability
(Fancy and Ballard 1995;Vila
`et al. 1995;Ciucci et al.
1997;Theuerkauf et al. 2003;Kusak et al. 2005;Chavez
and Gese 2006;Theuerkauf et al. 2007). However, it is
likely that the high variability of wolf activity patterns is
a result of their ability to react to various environmental
conditions (Packard 2003). Activity of individual wolves
may also vary among days, switching from being diurnal
to nocturnal. The purpose of our study was to examine
the variability of wolf activity between days and seasons
and to determine the most important factors that
influence activity in the Bieszczady Mountains, Poland.
The study was conducted in the Bieszczady Moun-
tains (Polish Carpathians) over an area of about
1000 km
2
(491190–491500N, 221150–221450E). Roughly,
60% of the area is covered with forest. The remaining
parts are fields, meadows or villages. Human population
density in the region is 44 inhabitants per km
2
(local
administration data of 2004), and road density is
0.64 km/km
2
. Red deer (Cervus elaphus), roe deer
(Capreolus capreolus) and wild boar (Sus scrofa) are
the major preys of wolves inhabiting the area (Gula
2004, 2008). The mean temperature is 14 1C in summer
and 31C in winter, with annual precipitations of
800–1200 mm. Snow cover lasts for 90–140 days, with an
average depth of 10–40 cm.
We caught three wolves with Belisle foot snares.
Capture and handling of wolves was done according to a
procedure approved by the Ethical Commission of the
Polish Ministry of Science and Higher Education.
During 78 continuous 24-h sessions, we radio-tracked
a breeding female (4224 locations during 44 radio-
tracking days from March 2002 to October 2004),
ARTICLE IN PRESS
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1616-5047/$ - see front matter r2008 Deutsche Gesellschaft fu
¨rSa
¨ugetierkunde. Published by Elsevier GmbH. All rights reserved.
doi:10.1016/j.mambio.2008.05.010 Mamm. biol. 74 (2009) 159–163
Corresponding author
E-mail address: jtheuer@miiz.waw.pl (J. Theuerkauf).
1
Present address: Laboratory of Water Resource Planning, United
Graduate School of Agriculture, Tokyo University of Agriculture and
Technology, Saiwai-cho 3-5-8, Fuchu, Tokyo 183-8509, Japan.
a non-breeding female (480 locations during 5 days from
September 2005 to May 2006) and a breeding male wolf
(2688 locations during 28 days from June 2003 to
July 2006) of three different established packs. We
assessed the breeding and pack status of wolves based
on snow-tracking, howling surveys, radio-tracking and
den searching as described in Tsunoda et al. (2008)
and Gula (2008). We located wolves by VHF ground
telemetry and triangulation, as described in Theuerkauf
and J˛edzejewski (2002), with a location accuracy of
about 250 m (Theuerkauf et al. 2007). We estimated
distances travelled as straight line distances between
consecutive radio-tracking locations taken at 15-min
intervals (always 96 locations per day). To estimate the
proportion of time active, we assigned a value of 1 when
wolves were active and locations changed; a value of 0
when wolves were not active and locations did not
change; and a value of 0.5 when wolves were either
active or locations changed (as described in Theuerkauf
and J˛edzejewski 2002). We eliminated auto-correlation
among consecutive activity estimates or radio-locations
by calculating one value of the time spent active or
distance travelled for each hour (as described in
Theuerkauf et al. 2007). We then calculated the
coefficient of variance (CV) of each hour as variation
among the radio-tracking sessions. A single radio-
tracking day is therefore the sample unit. We subdivided
the year into four periods: winter from November to
February, spring as March and April, summer from
May to August and autumn as September and October.
Periods of the day were dawn (sunrise 71 h), day (1 h
after sunrise to 1 h before sunset), dusk (sunset 71h)
and night (1 h after sunset to 1 h before sunrise). Activity
and inactivity bouts were periods of uninterrupted
activity or inactivity. To estimate nocturnality (propor-
tion of activity at night compared with the whole day)
during different seasons, we used Ivlev’s electivity index
(Jacobs 1974)
nocturnality index ¼ðpnpdÞðpnþpd2pnpdÞ1,
with p
n
being the percentage of time a wolf was active at
night (from sunset to sunrise) and p
d
the percentage of
time active in the day (from sunrise to sunset). The
nocturnality index can range from +1 (totally noctur-
nal) to 1 (totally diurnal). To measure the daily range
and its variation between four seasons, we used 100%
minimum convex polygons (MCP) for each of the 24-h
monitoring sessions (96 consecutive radio-locations for
each day) and subsequently calculated mean values for
each season.
Daily patterns of the mean time spent active and the
CV of activity of the breeding female and the breeding
male were similar. The activity and CV patterns of the
non-breeding female were highly variable, likely caused
by the small sample size (n¼5 days). Wolves were
active on average at 3272% [95% confidence interval
ARTICLE IN PRESS
0
20
40
60
80
100
0 6 12 18 24
0
20
40
60
80
100
0 6 12 18 24
TIME ACTIVE [%]
0
20
40
60
80
100
0 6 12 18 24
HOUR OF DAY
Fig. 1. Daily pattern of mean time spent active per hour
(shaded area) and coefficients of variance (bold continuous
line) with CI of a breeding female (A, n¼44 days), a breeding
male (B, n¼28) and a non-breeding female (C, n¼5) wolf,
radio-tracked in the Bieszczady Mountains (SE Poland)
between 2002 and 2006. The grey line indicates the daily mean
of time active. The horizontal bar indicates length and
variation of night (black), dawn and dusk (grey) and day
(white).
J. Eggermann et al. / Mamm. biol. 74 (2009) 159–163160
(CI), n¼78 days] of all radio-locations, with a main
peak of activity at dawn (Fig. 1). The CV was lowest in
the early morning hours and subsequently increased.
Wolves were more active, moved more often and
travelled greater distances at dawn than at other times
of the day (U-test, n¼78, all po0.001; Table 1).
Activity bouts were longer at night and dawn (U-test,
n¼78, p¼0.022), whereas bouts of inactivity lasted
longer in the day and at sunset; these differences were,
however, not significant (Table 1). The daily patterns
of mean distances travelled did not vary among the
four seasons (ANOVA two-way interactions, p¼0.240;
Fig. 2). Although the patterns followed the timing
of sunrise and sunset, the activity peak was highest
in winter and lowest in summer. Wolves travelled the
furthest in the early morning (03:00–06:00 h) and the
least around noon (10:00–16:00 h) in all seasons (Fig. 2).
The average distance travelled per hour was the shortest
in summer (Table 1) and differed from other seasons
(spring/autumn: U-test, n¼67, p¼0.022; winter:
n¼40, p¼0.003), while there were no significant
differences among the other seasons (spring, autumn
and winter). The lengths of active or inactive bouts did
not vary much among seasons (Table 1). In summer, the
wolves tended towards diurnal activity, but were more
nocturnal in other seasons. The CIs were, however, large
and all of them included the value zero. The mean daily
MCP was smallest in summer and largest in autumn and
winter (Table 1).
Wolves in our study area had a crepuscular activity
pattern with a distinct peak around dawn, but their
activity was highly variable. The only part of the day
when variance was low and thus activity more pre-
dictable was the early morning, which might be related
to hunting. Theuerkauf et al. (2003) showed that wolves
hunt mainly around dawn and dusk in Eastern Poland,
which coincided with peaks in activity and movement.
In Minnesota, wolves were the most active at night and
dawn, when they hunted for deer and moose (Chavez
and Gese 2006). Our results are in keeping with those
of Fancy and Ballard (1995) who found that wolves
generally have distinct patterns of activity, but that their
activity is highly flexible and may be adapted to various
environmental conditions. The reason for a lower
mobility during summer is denning, when wolf activity
concentrates on the den site and the breeding female
does not move far from the den (Harrington and Mech
1982;Ballard et al. 1991;Schmidt et al. 2008;Tsunoda
et al. 2008). Our results about daily ranges calculated by
daily MCPs support this idea. Although the sample size
in our study was small, we conclude that apart from the
times when they are hunting, wolf activity and distance
travelled are highly variable, which reflects the plasticity
of their behaviour.
Acknowledgements
This study was a part of the Bieszczady Wolf Project
funded by the Polish National Committee for Scientific
Research (KBN 6P04F 006), budget of the Museum and
Institute of Zoology, PAS, and financially supported by
ARTICLE IN PRESS
Table 1. Means (with 95% confidence intervals) of the time spent active, time moving, distance travelled, length of activity bouts,
nocturnality index and daily range (MCP) at different periods of the year and different times of the day of three wolves (n¼78 days)
radio-tracked in the Bieszczady Mountains (SE Poland) between 2002 and 2006
Time active
(%)
Time moving
(%)
Distance travelled
(km/h)
Active bout
length (h)
Inactive bout
length (h)
Nocturnality
index
Daily range
(km
2
)
Winter
(n¼11)
34.474.7 25.074.5 0.6870.15 1.670.5 1.570.4 0.1270.25 13.977.0
Spring
(n¼19)
32.876.0 23.076.1 0.5770.15 1.370.3 1.570.3 0.1370.24 9.174.4
Summer
(n¼29)
29.074.3 19.174.7 0.4070.15 1.270.3 1.770.3 0.1170.18 4.872.0
Autumn
(n¼19)
32.574.6 23.974.5 0.6170.27 1.270.3 1.870.3 0.1370.24 14.877.9
Dawn
(n¼78)
46.175.4 35.075.7 0.8970.18 1.770.4 1.570.4
Day
(n¼78)
27.173.3 17.773.0 0.3770.06 0.870.1 1.670.3
Dusk
(n¼78)
25.974.5 16.074.0 0.3870.11 1.370.4 2.070.5
Night
(n¼78)
30.275.5 22.275.1 0.5870.16 1.870.5 2.270.5
J. Eggermann et al. / Mamm. biol. 74 (2009) 159–163 161
scholarships of the German Academic Exchange Service
(to J.E.), the German Donors’ Association for the
Promotion of Sciences and Humanities (to J.T.) and
the Japan Student Services Organization (to H.T.).
We thank L. Aubry, M. Barreteau, M. Carruthers,
M. Diemert, S. Drevet, M. Januszczak, S. Kiener,
K. Lahongre, M. Le Peutrec, K. Mayer, N. Schmidt,
M.-C. Schultz, M. Skuban and W. Schwimmer for their
help during the fieldwork.
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0
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0.5
1
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0
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... To determine variations in daytime activity with respect to night activity for each of the subjects, the non-parametric Wilcoxon sign-ranked test was applied. To estimate the nocturnal activity during the months of the year, the rate of nocturnal proposed by Eggermann et al. (2009) was modified because in our work we were unable to determine the time that the study subjects were active during the day and night. Therefore the total amount of day and night activity of the study subjects was used instead. ...
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