1. Research Article
The Effect of Anthropogenic Resources
on the Space-Use Patterns of Golden Jackals
GUY ROTEM, Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet
Ben-Gurion 84990, Israel
HAIM BERGER, Mitrani Department of Desert Ecology, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben-Gurion 84990,
Israel
RONI KING, Science Division, Nature and Parks Authority, Jerusalem, Israel
PUA BAR (KUTIEL), Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Sede Boqer Campus,
Midreshet Ben-Gurion 84990, Israel
DAVID SALTZ,1
Mitrani Department of Desert Ecology, the Jacob Blaustein Institutes for Desert Research, Ben Gurion University of the Negev, Sede
Boqer Campus, 84990, Israel, and Science Division, Nature and Parks Authority, Jerusalem, Israel
ABSTRACT We studied the influence of agricultural villages on space-use patterns of golden jackals (Canis aureus Linnaeus) in the
Mediterranean region of Israel. Villages in our research area attract jackals due to poor sanitation conditions in and around villages. As resources in
these villages are abundant and predictable, we expected that space-use patterns of jackals near those villages, including home-range characteristics
and movement paths, would differ from those of jackals inhabiting more natural areas. Using radio-locations from 16 individuals (8 near villages
and 8 from more natural areas), we found that mean home-range size of jackals close to villages was 6.6 Æ 4.5 km2
, smaller than mean home-
range size of jackals in more natural areas (21.2 Æ 9.3 km2
, P ¼ 0.001). Similarly, core area size of jackals near villages was 1.2 Æ 0.92 km2
,
compared to 3.5 Æ 1.6 km2
for individuals inhabiting more natural areas (P ¼ 0.004). The core area/home-range ratio was greater for jackals
near villages than for those occupying more natural areas (0.122 Æ 0.045 vs. 0.095 Æ 0.037, respectively, P ¼ 0.004). Jackals moved little during
the day, with day ranges smaller for jackals near villages than away from them (1.65 Æ 0.67 vs. 7.5 Æ 5.6 km2
, respectively, P ¼ 0.028).
However, jackals near villages moved as much at night as did jackals in more natural areas, although movement was in a less directional manner.
Changes in distribution and predictability of resources due to anthropogenic activity affect not only the home-range size of jackals, but also how
they utilize and move through space. ß 2011 The Wildlife Society.
KEY WORDS anthropogenic, Canis aureus, food, home range, jackal, movement persistence, utilization distribution.
Daily movement patterns of predators are influenced by
presence and activity of humans or livestock (e.g., sheep,
goats, dogs) in natural habitats (Zielinski 1988, Theuerkauf
et al. 2001, Grassman et al. 2005). Within agricultural areas,
anthropogenic resources exert strong influences on space-use
patterns of wild animals, especially omnivorous canids such
as red foxes (Vulpes vulpes; Contesse et al. 2004), coyotes
(Canis latrans; Fedriani et al. 2001, Atwood et al. 2004), and
jackals (Giannatos 2004). Influences include changes in
home-range size, movement patterns (Fedriani et al. 2001,
Admasu et al. 2004, Kusak et al. 2005), and other aspects of
space utilization (Posillico et al. 1995, Savard et al. 2000,
Riley et al. 2003, Pascale et al. 2004, Baghli and Verhagen
2005). Consistent with optimal foraging theory, in any area
where food availability increases, there is a corresponding
decrease in the extent of foraging-related movement and
home range size (Stephens and Krebs 1986, Coman et al.
1991, Fedriani et al. 2001, Admasu et al. 2004). Accordingly,
studies on canids have shown that near human concen-
trations, home ranges (as defined by Burt 1943) are small
in comparison to home ranges in more pristine areas (red
foxes: Coman et al. 1991; coyotes: Grinder and Krausman
2001, raccoon dogs [Nycterutes procyonoises]: Saeki et al.
2007). However, generally these studies did not address
impacts of abundant anthropogenic resources on the finer
aspects of movement (Nathan et al. 2008) such as utilization
distribution (Horne et al. 2007) and individual path charac-
teristics (e.g., tortuosity, Whittington et al. 2004) stemming
from the changes in distribution and predictability of
resources.
We studied space-use patterns of golden jackals (Canis
aureus Linnaeus) as a function of proximity to agricultural
communities that provided concentrated and predictable
resources, in the form of fruit orchards and human waste,
to jackals (e.g., poultry carcases, Yom-Tov 1995, Dolev
2006, Bino et al. 2011). Golden jackals are medium-sized
predators (approx. 8.8 kg and 7.3 kg body mass for ad M and
ad F, respectively) that are omnivorous habitat generalists
and opportunistic foragers with a variable diet (Yom-Tov
1995, Kaunda and Skinner 2003). The golden jackal is native
to Israel and has become overabundant in the past 2 decades,
presumably due to anthropogenic resources and poor sani-
tation in and around built areas. Consequently, the species
presents a threat to biodiversity by preying on the native
fauna, but the extent of this threat is unknown. Although
common, and in many areas overabundant and a major host
for rabies, knowledge about behavior and ecology of golden
jackals is limited, and no studies have addressed the impact of
anthropogenic resources on the ecology (including spatial
behavior and densities) of the species.
We focused on 3 aspects of jackal movements: home-range
size, utilization distribution (White and Garrott 1990),
Received: 17 August 2009; Accepted: 5 May 2010
1
E-mail: dsaltz@bgu.ac.il
Journal of Wildlife Management 75(1):132–136; 2011; DOI: 10.1002/jwmg.9
132 The Journal of Wildlife Management 75(1)

2. and individual path characteristics. We hypothesized that
agricultural villages provided a rich, concentrated source of
food for jackals (Yom-Tov 1995, Dolev 2006, Bino 2007),
and would influence spatial dynamics of nearby jackals. From
this general hypothesis, we derived the following predictions:
1) nighttime and daily home-range size and core area size
of jackals close to villages would be smaller than those of
jackals inhabiting more pristine areas further away from
those villages, 2) because resource distribution near villages
would be less patchy relative to the movement scale of jackals,
utilization distribution of jackals near villages would be more
uniform over space with only one core area, whereas space use
of jackals in lesser developed areas would be more variable
and with several core areas, and 3) jackals in pristine areas
would travel longer distances to hunting grounds, with
higher speed and more directional movement, compared
to jackals with home ranges closer to villages.
STUDY AREA
We conducted our study in Britannia Park (Fig. 1), a 40 km2
area located at the foothills of the Judean hills in central Israel
(318380
2900
N, 348540
1200
E) approximately 30 km south-west
of Jerusalem. The park encompassed low rolling hills with
both planted forests dominated by oak (Quercus calliprinos)
and wild Palestine cashew (Pistacia palaestina), and
Mediterranean Maqui dominated by 2 communities: 1)
Palestine buckthorn (Rhamnus palaestinus) and 2) Carob
(Ceratonia siliqua) and mastic tree (Pistacia lenticus)
(Alon 1984). The park was bounded by agricultural villages
that economically relied on fruit orchards, vineyards, and
poultry farms. The climate was Mediterranean with mean
annual rainfall averaging 490 mm/year with, on average,
51 rain days/year. Temperatures ranged from 138C in winter
(Dec–Feb) to 258C in summer (Jun–Aug).
METHODS
We used padded leg traps to trap and collar mounted
transmitters to radio-tag jackals. We opened traps 1 hr
before sunset and closed them 1 hr after sunrise to avoid
trapping other species. We opened traps for 868 nights
between 2002 and 2006, with !3 traps each night.
We caught and radio-tagged 86 jackals, however only 16
provided sufficient data for home range analysis. No jackals
were injured or recaptured during our study.
We used radio-location by triangulation (White and
Garrott 1990) to track radio-collared jackals. We triangu-
lated from predetermined locations with known coordinates
and good coverage that provided a good intersection angle
(308) between bearings (Saltz 1994). To calculate radio-
location error we placed a radio tag at a random location in
the study area and estimated each location by triangulation
using receiving sites we regularly used for that specific
area. We then returned to the site and determined its true
coordinates using a Global Positioning System (GPS). We
repeated this process for 30 locations and used the average
displacement of the estimated location from the true location
as a measure of radio-location error.
We located animals by radio-telemetric triangulation using
2 types of tracking techniques and consequent analyses. The
first technique focused on obtaining data for home-range and
utilization-distribution analyses. For this type of analysis, we
obtained a 1 nightly location/individual every 24 hr
to avoid autocorrelation between relocations (White and
Garrott 1990). We then used an ArcView 3.1 Kernel
algorithm (Blundell et al. 2001) to calculate home range,
core area, and daytime activity area. For home range and core
area analyses, we used only individuals for which we had at
least 30 nightly relocations (the minimum recommended
number for estimating a home range, Kernohan et al.
2001). For daytime home-range area, we used a minimum
of 15 relocations, but tested whether the number of reloca-
tions impacted daytime home range estimation by randomly
selecting a subset of 15 relocations from each individual and
recalculating the home range. We then regressed the pro-
portion of change in area from the original home range (with
all data points) on the proportion of points included in the
subset relative to the total number of points.
We defined the home range as the area within 90%
isopleths and the core as the area within 50% isopleths
(Borger et al. 2006) using night relocations only. We defined
the daytime activity area as 90% isopleths calculated from
daytime locations. For daytime activity we obtained only one
daily location/individual every 24 hr. We used the ratio of
the nighttime core area (50% isopleths) to the nighttime
home-range area (90% isopleth) as an index of utilization
distribution (Horne et al. 2007), where higher ratios reflect a
more uniform use of space and lower ratios reflect an affinity
to specific areas within the home range. We then divided
jackals post hoc into 2 groups, Close and Far from the nearest
agricultural village borderline based on whether the core area
included part of a village (Close) or not (Far). Far animals
may have occasionally frequented villages. We delineated
Figure 1. Study area location within Israel (left), and a aerial photograph of
the Britania Park study area in the Mediterranean region, Israel (right)
depicting the topography and agricultural villages (white lettering), where
we studied jackals in 2006.
Rotem et al. Movement Patterns of Jackals 133

3. the village borderline as the line forming a convex polygon
connecting the outer buildings of each village. Based on this
definition, we used t-tests to compare the home-range size,
core area size, number of core areas, and the core area/home
range ratio of the 2 groups. We used the proximity of the
home range to villages as a class predictor (rather than
continuous) with 2 levels because we expected jackals to have
1 of 2 behaviors: 1) commensal individuals depending on
resources in the immediate surroundings of the village, or 2)
individuals relying on natural prey further away from the
village and venturing into the village only when resources
were scarce, to avoid territorial confrontations.
We employed the second-tracking technique to elucidate
individual nightly movement paths by continuously tracking
an individual throughout the night, obtaining one location
every hour from sunset to sunrise. We tracked 6 jackals
(a subset of the 16 jackals tracked for the home-range analysis
above): 3 near villages (Close) and 3 in lesser-disturbed habitat
away from villages (Far). We tracked each individual for 2
nights during the period April–September 2006. One of
the 2 nights was moonlit (3/4 full moon) and the other
was dark (1/4 moon). From these data, we obtained total
distance traveled at night, calculated as the sum of all
trajectories between relocations (synonymous with speed
because time between relocations was fixed). Turning angle
was the smaller angle between 3 relocations, and we calcu-
lated persistence of movement (inverse of path tortuosity) per
night as the total distance moved per jackal per night divided
by the sum of the turning angles (8; where 08 ¼ straight and
1808 ¼ turning back) per night. We also calculated average
turning angle/night. We used a 2-way factorial analysis of
variance (ANOVA; Close vs. Far and moonlit vs. dark
nights), after testing for normality, to compare total distance
traveled per night and mean nightly turning angles.
RESULTS
Mean location error was 148 Æ 48 m. We obtained
751 nighttime relocations for home range analyses from
16 individuals between 2002 and 2006, with !30 reloca-
tions/individual. The home range core of 8 individuals
included all or part of a village and we consequently
categorized those 8 individuals as Close and the remaining
8 individuals as Far. Only 3 (1%) of all Far jackal reloca-
tions were within a village. Furthermore, the proportion
of home range area within village boundaries ranged from
approximately 0.1–0.8 for Close jackals as opposed to
0.01–0.06 for Far jackals (Table 1). Thus, there is a clear
dichotomy between the 2 groups, which would be further
enhanced if we considered the proportion of the home-range
volume within village boundaries (as village boundaries
covered the core of Close animals’ home range).
We calculated daytime area of activity from 460 relocations
for 13 of the 16 jackals for which we had !30 locations.
Number of daytime relocations ranged from 15 to 40/animal
and we found no correlation between daytime activity area
size and number of relocations (adjusted R2
¼ À0.03,
P ¼ 0.43). Mean nighttime home-range size of Close jackals
was smaller than that of Far jackals (6.6 Æ 4.5 km2
vs.
21.2 Æ 9.3, respectively). Similarly, core area size of Close
jackals was smaller (1.2 Æ 0.92 km2
vs. 3.5 Æ 1.6 km2
,
respectively, P ¼ 0.004). Core area/home-range ratio was
greater for Close jackals than for Far jackals (0.122 Æ 0.045
vs. 0.095 Æ 0.037, respectively; mean ratios before trans-
formation, P ¼ 0.004 after ArcSin transformation) with
no difference between the groups in number of core areas/
home range (average of 1.25 vs. 1.5, respectively, P ¼ 0.422,
Wilcoxon matched pairs test). All jackals moved little during
the day, with daytime ranges smaller for Close jackals than
Far jackals (1.65 Æ 0.67 km2
vs. 7.5 Æ 5.6 km2
, respect-
ively, P ¼ 0.028).
We found no difference (P 0.05) in total distance trav-
eled per night between Close and Far jackals and moonlit
versus dark nights. The interaction between distance moved
and moon condition was insignificant as well. Jackals close to
villages moved approximately 9.4 Æ 3.35 km/night com-
pared to 9.5 Æ 1.69 km/night for individuals in more
natural areas. Total distance moved on dark nights was
9.93 Æ 2.15 km versus 9.01 Æ 2.99 km on moonlit nights.
Similarly, we found no effect of the same predictors on
turning angles (tortuosity).
Both moon phase (i.e., moonlight vs. dark night) and
proximity to the villages (i.e., Close vs. Far) had no signifi-
cant effect on persistency, but the interaction distance Â
moon phase was significant (F ¼ 7.2558, P ¼ 0.0273),
resulting from Far jackals moving more persistently on dark
nights than on moonlit nights, whereas Close jackals exhib-
ited intermediate persistance under both moon conditions
(P ¼ 0.031, Tukey’s Honestly Significant Difference post
hoc test, Fig. 2).
DISCUSSION
Proximity to agricultural villages did not only cause
shrinkage in jackals’ home-range size and a more uniform
Table 1. Kernel method home range (90% isopleth) and core sizes (50%
isopleth) of jackals that are either Close or Far from agricultural villages in
Britania Park, Mediterranean region, Israel, 2002–2006.
Distance
group
category
Home
range (ha)
Core
area (ha)
Core overlap
with village
Proportion of
home range
within village
boundaries
Far 16.88 2.20 No 0.01
13.92 2.06 No 0.06
11.91 1.13 No 0.01
25.67 3.93 No 0.02
32.47 5.17 No 0.03
10.23 2.96 No 0.02
34.26 5.43 No 0.01
24.62 5.33 No 0.06
Close 2.63 0.58 Yes 0.13
16.67 3.40 Yes 0.09
3.07 0.91 Yes 0.15
7.85 1.32 Yes 0.13
3.99 1.00 Yes 0.50
4.85 0.44 Yes 0.41
6.33 1.17 Yes 0.29
7.47 1.32 Yes 0.24
134 The Journal of Wildlife Management 75(1)

4. utilization distribution, but it also appeared to impact the
foraging strategy as a whole, as reflected in the less persistent
movement trajectories associated with a loss of response
to moon phase. Smaller home ranges and a more uniform
utilization distribution in response to anthropogenic resour-
ces have been previously documented in other predators
(Belcher and Darrant 2004, Silva and Talamoni 2004,
Bradley et al. 2005, Kusak et al. 2005, Parra 2006).
Although not tested by perturbation, it is safe to assume
that in our study these patterns resulted from increased
availability and predictability of resources in time and space
in and around villages, including fruits from the orchards,
household trash, and poultry carcasses, and a uniform distri-
bution of these resources at the relevant scale (Sutherland
1997, Atkinson et al. 2002, Valenzuela and MecDonald
2002, Admasu et al. 2004, Silva and Talamoni 2004).
Interestingly, jackals near villages moved as much at night
as jackals in more pristine areas, although in a less directional
manner, suggesting a small-scale search pattern rather
than extended directional journeys to hunting grounds, as
reflected in the high persistence of direction in Far jackals
during moonlit nights. Close jackals’ loss of response to
moonlight is of special interest as the increased movement
during moonlit nights reflects an adaptive response of
predators that rely on vision for hunting. Potential prey,
such as small mammals and reptiles, are less active during
moonlit nights due to increased risk of predation (Kotler and
Brown 1988). According to the predation-risk allocation
hypothesis (Lima and Bednekoff 1999) these responses of
potential prey should influence predator movement patterns.
Furthermore, because many nocturnal mammalian predators
rely on vision during the final stages of the hunt, moonlight
may be important (Kavanau and Ramos 1975). However,
to date, only few studies have addressed the impact of
moonlight on the activity of canid predators (Sa´bato et al.
2006). In our study, moonlit nights did not induce any
changes in space-use patterns of Close jackals suggesting a
change in their foraging behavior strategy. Although there
is no direct evidence, our finding support the notion that
Close jackals spend little time stalking prey. The response to
moonlight in predators is a plastic learned behavior, which
is abandoned when resources become readily available
and constant over time but may be re-acquired if conditions
change.
MANAGEMENT IMPLICATIONS
Overabundant predators may depress prey densities and
alter community structure (Garrott et al. 1993, Ritchie
and Johnson 2009). The loss of response to the lunar
cycle suggests that when overabundance is the result of
anthropogenically supplied resources that are rich and
predictable in time and space, omnivorous predators (e.g.,
jackals) may shift their foraging strategy from hunting to
scavenging. The impact of this process will be functionally
similar to predator extinction in a top-down situation,
altering prey community structure and possibly driving
the extinction of species at lower trophic levels due to com-
petitive exclusion (Schmitz et al. 2000). Culling, in this case,
will not provide an appropriate solution, as it is not expected
to alter the feeding behavior of the commensal jackals.
The only viable management in this situation is sanitation
that will minimize scavenging opportunities and force the
jackals to hunt (Bino et al. 2011).
ACKNOWLEDGMENTS
We thank 2 anonymous reviewers for providing constructive
criticism. Our study would not have been possible without
the field assistance of H. Grushka, A. Sereth, O. Alnekave,
and S. Aharon. Our study was funded by the Jewish National
Fund and The Israel Nature and Parks Authority (INPA).
We thank the INPA rangers for their help, especially Y.
Gendler and I. Shefman. This is publication number 691 of
the Mitrani Department of Desert Ecology.
LITERATURE CITED
Admasu, E., S. J. Thirgood, A. Bekele, and M. K. Laurenson. 2004. Spatial
ecology of Golden Jackal in the Ethiopian Highlands. African Journal of
Ecology 42:144–152.
Alon A. editor. 1984. Plants and animals of the land of Israel. Ministry of
Defence Publishing House and The Society for Protection of Nature
Israel, Ramat-Gan, Israel [in Hebrew].
Atkinson, R. P. D., C. J. Rhodes, D. W. Macdonald, and R. M. Anderson.
2002. Scale-free dynamics in the movement patterns of Jackals. Oikos
98:134–140.
Atwood, T. C., H. P. Weeks, and T. M. Gehring. 2004. Spatial ecology of
coyotes along a suburban-to-rural gradient. Journal of Wildlife
Management 68:1000–1009.
Baghli, A., and R. Verhagen. 2005. Activity patterns and use of resting sites
by polecats in an endangered population. Mammalia 69:211–222.
Belcher, C. A., and J. P. Darrant. 2004. Home range and spatial organization
of the marsupial carnivore, Dasyurus maculates maculates (Marsupialia
Dasyuridae) in South-Eastern Australia. Journal of Zoology 262:271–280.
Bino, G. 2007. Spatial and numerical responses of Golden Jackals (Canis
aureus) and red foxes (Vulpes vulpes) to resource manipulation. Thesis,
Hebrew University of Jerusalem, Jerusalem, Israel.
Figure 2. Movement persistency, defined as the ratio between total distance
traveled per night divided by the sum of all turning angles (8) during the
specific night, of jackals in Britania Park, Mediterranean region, Israel, from
April to December 2006. Far and Close classify the jackals based on the
distance of their home range from the nearest agricultural village.
Rotem et al. Movement Patterns of Jackals 135

5. Bino, G., A. Dolev, D. Yosha, A. Guter, U. Saltz, and S. Kark. 2011. Abrupt
spatial and numerical responses of overabundant foxes to a reduction in
anthropogenic resources. Journal of Applied Ecology, In Press.
Blundell, G. M., J. A. K. Maier, and E. M. Debevec. 2001. Linear home
ranges: effects of smoothing, sample size, and autocorrelation on Kernel
estimates. Ecological Monographs 71:489–496.
Borger, L., N. Franconi, G. D. Michele, A. Gantz, F. Meschi, A. Manica, S.
Lovari, and T. Coulson. 2006. Effects of sampling regime on the mean and
variance of home range size estimates. Journal of Animal Ecology
75:1393–1405.
Bradley, E. H., D. H. Pletscher, B. E. Bangs, K. E. Kunkel, D. W. Smith, C.
Mack, T. J. Meier, J. A. Fontaine, C. C. Niemeyer, and D. J. Michael.
2005. Evaluating Wolf translocation as a nonlethal method to reduce
livestock conflicts in the Northwestern United States. Conservation
Biology 19:1498–1508.
Burt, W. H. 1943. Territoriality and home range concepts as applied to
mammals. Journal of Mammology 24:346–352.
Coman, B. J., J. Robinson, and C. Beaumont. 1991. Home range, dispersal
and density of Red Foxes (Vulpes vulpes L.) in central Victoria. Wildlife
Research 18:215–223.
Contesse, P., D. Hegglin, S. Gloor, F. Bontadina, and P. Deplazes. 2004.
The diet of urban foxes (Vulpes vulpes) and the availability of anthropo-
genic food in the city of Zurich, Switzerland. Mammalian Biology 69:
81–95.
Dolev, A. 2006. Modeling the spatial dynamics of rabies in canid vectors
using a realistic landscape: a tool for optimizing the spatial scattering of
oral rabies vaccination. Dissertation, Ben-Gurion University of the Negev,
Beer-Sheva,Israel. [In Hebrew.].
Fedriani, J. M., T. K. Fuller, and R. M. Sauvajot. 2001. Does availability of
anthropogenic food enhance densities of omnivorous mammals? An
example with coyotes in southern California. Ecography 24:325–331.
Garrott, R. A., P. J. White, and C. A. Vanderbilt White. 1993.
Overabundance: an issue for conservation biologists? Conservation
Biology 7:946–949.
Giannatos, G. 2004. Conservation action plan for the golden jackal Canis
aureus Linnaeus in Greece. hhttp://www.panda.orgi Accessed 7 Mar
2006.
Grassman, L. I. J., M. E. Tewes, N. J. Silvy, and K. Kreetiyutanont. 2005.
Spatial organization and diet of the leopard cat (Prionailurus bengalensis) in
north-central Thailand. Journal of Zoology 266:45–54.
Grinder, M. I., and P. R. Krausman. 2001. Home range, habitat use, and
nocturnal activity of coyotes in an urban environment. Journal of Wildlife
Management 65:887–898.
Horne, J. S., E. O. Garton, S. M. Krone, and J. S. Lewis. 2007. Analyzing
animal movements using Brownian bridges. Ecology 88:2354–2363.
Kaunda, S. K. K., and J. D. Skinner. 2003. Black-backed diet at Mokolodi
nature reserve Botswana. African Journal of Ecology 41:39–46.
Kavanau, J. L., and J. Ramos. 1975. Influence of light on activity and phasing
of carnivores. American Naturalist 109:391–418.
Kernohan, B. J., R. A. Gitzen, and J. J. Millspaugh. 2001. Analysis of animal
space use and movements. Pages 125–166 in J. J. Millspaugh and J. M.
Marzluff, editors. Radio tracking and animal populations. Academic Press,
San Diego, California, USA.
Kotler, B. P., and J. S. Brown. 1988. Environmental heterogeneity and the
coexistence of desert rodents. Annual Review of Ecology and Systematics
19:281–307.
Kusak, J., A. M. Skrbinsek, and D. Huber. 2005. Home range, movements
and activity of wolves (Canis lupus) in the Dalmatian part of Dinarids,
Croatia. Europe Journal of Wildlife Research 51:254–262.
Lima, S. L., and P. A. Bednekoff. 1999. Temporal variation in danger drives
antipredator behavior: the predation risk allocation hypothesis. American
Naturalist 153:649–659.
Nathan, R., W. M. Getz, E. Revilla, M. L. Holyoak, R. Kadmon, D. Saltz,
and P. E. Smouse. 2008. Moving forward with movement ecology: a
proposed unifying paradigm to study movements of organisms.
Proceedings of the National Academy of Sciences of the United States
of America 105:19052–19059.
Parra, G. J. 2006. Resource partitioning in sympatric delphinids: space use
and habitat preferences of Australian snubfin and Indo-Pacific humpback
dolphins. Journal of Animal Ecology 75:862–874.
Pascale, C. D., S. G. Hegglin, F. Bontadina, and P. Deplazes. 2004. The
diet of urban foxes (Vulpes vulpes) and the availability of anthropogenic
food in the city of Zurich, Switzerland. Mammalian Biology 69:81–95.
Posillico, M., P. Serafini, and S. Lovari. 1995. Activity patterns of the Stone
Marten Martes foina Erxleben 1777, in relation to some environmental
factors. Hystrix 7:79–97.
Redecker B. P. Finck, W. Hardtle, U. Riecken, E. Schroder, editors. 2002.
Pasture landscape and nature conservation. Springer, New York, New
York, USA.
Riley, S. D., R. M. Sauvajot, T. K. Fuller, E. C. York, D. A. Kamradt, C.
Bromley, and R. K. Wayne. 2003. Effects of urbanization and habitat
fragmentation on Bobcat and Coyotes in Southern California.
Conservation Biology 17:566–576.
Ritchie, E. G., and C. M. Johnson. 2009. Predator interactions, mesopre-
dator release and biodiversity conservation. Ecology Letters 12:982–
998.
Sa´bato, M. A. L., L. F. Bandeira de Melo, E. M. Vaz Magni, R. J. Young,
and C. M. Coelho. 2006. A note on the effect of the full moon on the
activity of wild maned wolves, Chrysocyon brachyurus. Behavioural
Processes 73:228–230.
Saeki, M., P.J. Johnson, and U.W. Macdonald. 2007. Movements and
habitat selection of raccoon dogs (Nyctereutes procyonoides) in a mosaic
landscape. Journal of Mammalogy 88:1098–1111.
Saltz, D. 1994. Reporting error measures in radio location by triangu-
lation—a review. Journal of Wildlife Management 58:181–184.
Savard, J. J., P. Clergeau, and G. Mennechez. 2000. Biodiversity concepts
and urban ecosystems. Landscape and Urban Planning 48:131–142.
Schmitz, O. J., P. A. Hamba¨ck, and A. P. Beckerman. 2000. Trophic
cascades in terrestrial systems: a review of the effects of carnivore removals
on plants. The American Naturalist 155:141–153.
Silva, J. D. A., and S. A. Talamoni. 2004. Core area and center of activity of
manned wolves, Chrysocyon brachyurus (llliger) (Mammalia, Canidae),
submitted to supplemental feeding Revista Brasileira. Zoologia 21:391–
395.
Stephens, D. W., and J. R. Krebs. 1986. Foraging theory. Princeton
University Press, New Jersey, USA.
Sutherland, W. J. 1997. From individual behaviour to population ecology.
Oxford University Press, Oxford, United Kingdom.
Theuerkauf, J., W. Jedrzejewski, K. Schmidt, and R. Gula. 2001. Impact of
human activity on daytime movement patterns of wolves, Canis lupus, in
the Bialowieza Forest, Poland. Pages 206–209 in R. Field, R. J. Warren ,
H. Okarma , and P. R. Sievert , editors. Wildlife, land and people:
priorities for the 21st century. The Wildlife Society, Bethesda,
Maryland, USA.
Valenzuela, D., and D. E. MecDonald. 2002. Home range use by White-
nosed coatis (Nasua narica): limited water and a test of the resource
dispersion hypothesis. Journal of Zoology 258:247–256.
White, G. C., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking
data. Academic Press, San Diego, California, USA.
Whittington, J., C. C. St. Clair, and G. Mercer. 2004. Path tortuosity and
the permeability of roads and trails to wolf movement. Ecology and
Society 9:4. hhttp://www.ecologyandsociety.org/vol9/iss1/art4/i Accessed
23 Jan 2008.
Yom-Tov, Y. 1995. Cattle predation by the Golden jackal Canis aureus in
the Golan Heights, Israel. Biological Conservation 73:19–22.
Zielinski, W. J. 1988. The influence of daytime variation in foraging cost on
the activity of small carnivores. Animal Behavior 36:239–249.
Associate Editor: Bret A. Collier.
136 The Journal of Wildlife Management 75(1)