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Spatial ecology of european badgers (Meles meles) in Mediterranean habitats of the north-eastern Iberian peninsula. I: home range size, spatial distribution and social organization

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Abstract

Although there are some radio-telemetry studies on badger spatial organization in sub-humid Mediterranean lowlands, cork oak woods and Atlantic highland forest (in the South, West and North of the Iberian Peninsula respectively), the present study is the first carried out in the Mediterranean forests of the NE Iberian Peninsula in the parks of Collserola and Montserrat, close to Barcelona. The home range of 13 adult badgers (6 males and 7 females) was examined with the aim of providing results to compare with previous studies in order to advance in the understanding of badger social organization with special regard to low density populations in Mediterranean environments. Mean home range size was 307.6 ha ± 96.4 (± SE) and 72.8 ha ± 15.1 for males and females respectively for MCP95 and 287.4 ± 79.1 and 85.1 ± 26.6 for FK95 with differences between Parks. In addition, the home ranges of Collserola males were over four times larger than those of females, while for Montserrat this Figure was 1.5. Moreover, badger groups were formed by one to three individuals in Collserola, and at least three individuals in Montserrat. This discrepancy points to a distinct social organization associated with differences in population densities (0.6 ind./km2 in Collserola and 1.9 ind./km2 in Montserrat) and landscape structure conditions. Our results suggest that the home range configuration of males is driven by female distribution in space.
INTRODUCTION
The European badger (Meles meles) shows large
intraspecific variation in social organization which is
understood to reflect ecological, demographic and behav-
ioral plasticity (Palphramand et al. 2007). Populations
throughout Europe present a two-order of magnitude vari-
ation in density, which parallels considerable variation in
social spacing. Population density varies from less than
one ind./km
2
in Poland (Kowalczyk et al. 2000) and the
South of Spain (Revilla & Palomares 2002), to over 38
ind./km
2
in some areas of Britain (Johnson et al. 2002). In
brief, low density populations are found at the northern
(e.g. Broseth et al. 1997) and southern (e.g. Revilla &
Palomares 2002) edges of its distribution range while
higher densities occur at medium latitudes, reaching a
maximum in the British Isles and Ireland (see review in
Johnson et al. 2002). In general terms, it seems that bad-
ger population density is higher in environments with
minor differences between seasonal characteristics (i.e.
temperature, rain, etc.) compared to more variable ones.
Associated with this, the spatial distribution of individu-
als within populations is highly variable. In low density
populations, groups are usually composed of one (Pigozzi
1987) to 3 individuals (Do Linh San et al. 2007a, Revilla
et al. 2001) and territory size reaches several square kilo-
meters, up to 25 km
2
(Kowalczyk et al. 2003). In contrast,
in high density populations, groups can include over 25
individuals, including several adults of both sexes (e.g.
Rogers et al. 1997) and territories rarely reach one square
kilometer, being as small as 0.14 km
2
(Cheeseman et al.
1981).
The badger has become a model in mammal socio-
biology because its plasticity in social organization has
been understood as a primitive level of sociality in carni-
vores (Woodroffe & Macdonald 1993). Sociality in bad-
gers does not seem to be a result of the benefits of coop-
erative activities, as these have rarely been detected, but
rather a result of a resource exploitation strategy. The
most persistent ecological theory for the evolution of spa-
tial groups is the Resource Dispersion Hypothesis (RDH;
Macdonald 1983). In brief, it asserts that, when resources
are patchily distributed in space and/or time, the smallest,
economically defensible territory able to support its pri-
mary holders would usually be rich enough to support
additional individuals with little or no cost to the primary
holders. Therefore, a benefit is not necessary for spatial
groups to develop, or benefits are considered almost neg-
ligible. Territoriality is supposed to be an adaptation for
the defence of a limiting resource (Woodroffe & Macdon-
ald 1993). Accordingly, different resources have been
proposed as the key factors driving badger territoriality,
VIE ET MILIEU - LIFE AND ENVIRONMENT, 2009, 59 (2): 227-236
SPATIAL ECOLOGY OF EUROPEAN BADGERS (MELES MELES)
IN MEDITERRANEAN HABITATS OF THE NORTH-EASTERN
IBERIAN PENINSULA. I: HOME RANGE SIZE, SPATIAL
DISTRIBUTION AND SOCIAL ORGANIZATION
G. MOLINA-VACAS
*
, V. BONET-ARBOLÍ, E. RAFART-PLAZA,
J. D. RODRÍGUEZ-TEIJEIRO
Animal Biology Department, Universitat de Barcelona, 645 Avenue Diagonal, 08028 Barcelona, Spain
* Corresponding author: guillemolina@ub.edu
ABSTRACT. Although there are some radio-telemetry studies on badger spatial organization
in sub-humid Mediterranean lowlands, cork oak woods and Atlantic highland forest (in the
South, West and North of the Iberian Peninsula respectively), the present study is the first car-
ried out in the Mediterranean forests of the NE Iberian Peninsula in the parks of Collserola and
Montserrat, close to Barcelona. The home range of 13 adult badgers (6 males and 7 females)
was examined with the aim of providing results to compare with previous studies in order to
advance in the understanding of badger social organization with special regard to low density
populations in Mediterranean environments. Mean home range size was 307.6 ha ± 96.4 (± SE)
and 72.8 ha ± 15.1 for males and females respectively for MCP95 and 287.4 ± 79.1 and 85.1 ±
26.6 for FK95 with differences between Parks. In addition, the home ranges of Collserola males
were over four times larger than those of females, while for Montserrat this figure was 1.5.
Moreover, badger groups were formed by one to three individuals in Collserola, and at least
three individuals in Montserrat. This discrepancy points to a distinct social organization associ-
ated with differences in population densities (0.6 ind./km
2
in Collserola and 1.9 ind./km
2
in
Montserrat) and landscape structure conditions. Our results suggest that the home range config-
uration of males is driven by female distribution in space.
EUROPEAN BADGER
IBERIAN PENINSULA
MEDITERRANEAN HABITATS
MELES MELES
SOCIAL ORGANIZATION
SPATIAL ECOLOGY
HOME RANGE SIZE
228 G. MOLINA-VACAS, V. BONET-ARBOLÍ, E. RAFART-PLAZA, J. D. RODRÍGUEZ-TEIJEIRO
Vie Milieu, 2009, 59 (2)
and their distribution would determine badger spatial
organization. In the original form, RDH focuses on food
dispersion as the main factor (Macdonald 1983). Don-
caster & Woodroffe (1993) argued that the distribution of
setts, which are considered a key resource for the species
(Roper 1993), rather than food, determines territory size
and shape, resulting in territories that are larger than need-
ed in relation to food abundance and, thus, allow more
individuals to stay (Sett Dispersion Hypothesis, SDH).
Finally, the Anti-kleptogamy Hypothesis (AKH; Roper et
al. 1986) proposes that the availability of breeding oppor-
tunities is the most important factor in male spatial distri-
bution. Accordingly, territoriality in males would have a
mate-guarding function, as also proposed by Revilla &
Palomares (2002).
In order to improve our understanding on badger socio-
spatial organization in low-density Mediterranean popu-
lations, and also in a global context, we studied the home
range size, group size and population density of two bad-
ger populations of the North-Eastern Iberian Peninsula by
means of radio-tracking, den-watching, and camera trap-
ping between 1997 and 2007. The specific objectives of
the present investigation were 1) to describe badger socio-
spatial organization in our study areas to assess which of
the above-mentioned explanatory hypotheses fits best
with the obtained results, and 2) to compare our data with
other European studies.
MATERIALS AND METHODS
Study areas: The Park of Collserola (41º27’N, 2º6’E) is an
85 km
2
natural space belonging to the Catalan Coastal Cordille-
ra, which spreads over about 100 km in a North-South direction,
parallel to the Mediterranean Sea, roughly 10 km away from the
coastline. This space is naturally separated from the rest of the
cordillera by the rivers Besòs to the NE and Llobregat to the
SW. Its south-eastern limit is formed by the city of Barcelona
and the rest of its perimeter is almost closed by a belt of cities
and highways except for two narrow corridors to the north. It is
basically composed of slates with some granite outcrops on the
northern side and calcareous outcrops to the south. Altitude
ranges from 50 to 512 m above sea level. Mean annual tempera-
ture and rainfall are 14ºC and 672 mm respectively, with wide
seasonal variations in both factors. Summer is usually the hot-
test and driest season, whereas spring and autumn are the wet-
test ones and winters are mild. The inner 80 % of the park sur-
face is covered by dense woodland, largely dominated by the
Aleppian pine (Pinus halepensis) and the holm oak (Quercus
ilex), with very dense undergrowth. At the periphery, vegetation
mostly consists of Mediterranean scrub patches, basically com-
posed of tree heath (Erica arborea) and rock rose (Cistus sp.).
These peripheral areas hold most of the small amount of agricul-
tural activity remaining inside Collserola (8 % of its area). Even
though some areas of Collserola can be classified as sub-urban
habitats, most of it retains the features of a wild natural space.
The second study area is located on the southern side of
Montserrat Mountain Natural Park and in its agricultural sur-
roundings (41º36’N, 1º48’E), 40 km NW of the city of Barcelo-
na (16 km apart from Collserola Park) with an area of over
50 km
2
. The Montserrat massif shows a particular relief with a
columnar appearance. It is formed basically by conglomerates
created by alluvial sedimentation. Large alluvial cones were
raised by Alpine tectonics which originated the Catalan Pre-
coastal Cordillera. Altitude ranges from 250 m to 1224 m. Cli-
mate is typically Mediterranean, similar to Collserola, but is
drier and hotter on the southern side. Wood and scrub are the
dominating vegetation types with the same species as in Collse-
rola Park. This vegetation alternates with croplands: olive crops
(Olea europaea), vineyards (Vitis sp.) and cereal crops. The two
populations live in similar habitats, however with the following
differences. Montserrat is less woody and more patchy and has a
higher proportion of fruit crops relative to cereal crops. In addi-
tion, these Parks have notable differences in connectivity levels
and human pressure. The badgers in Collserola and Montserrat
are considered as separated populations owing to the high level
of infrastructures that isolate Collserola from the rest of the sur-
rounding natural habitats.
Badger capture and tadio-telemetry: Trapping took place
between 1997 and 2006. Badgers were captured with padded leg
hold traps (Victor Soft Catch 1.5, Woodstream Corp Lititz, PA)
placed on well-used badger paths near setts or latrines, which is
the most effective method for capturing badgers in Mediterra-
nean landscapes (Bonet-Arbolí 2003, Loureiro et al. 2007,
Muñoz-Igualada et al. 2008, Rafart-Plaza 2005). Traps were
checked and defused every day at dawn to avoid trapping
domestic animals, and were activated again at dusk. All the Rec-
ommendations of the Animal Welfare Protocol of the European
Union were followed and no badger was injured during han-
dling. Badgers were anesthetized by intramuscular injections of
combinations of ketamine and xylazine hydrochloride (Kreeger
1997), diazepam or medetomidine (Palphramand et al. 2007).
Sex, body mass to the nearest 0.1 kg and morphometric mea-
surements were taken. We estimated the age of animals on the
basis of tooth wear, body mass and date of capture (Da Silva &
Macdonald 1989). Only adults were equipped with a radio-
transmitter (TW-5, Biotrack Ltd.). We used a portable VHF
receiver (R1000, Communications Specialists Inc.) and a hand-
held three element Yagi antenna (Biotrack Ltd.) for radio-track-
ing data collection. Locations were taken with the triangulation
method (White & Garrot 1990), as direct observation was
impossible in most badger ranges because of the dense under-
growth of the wood.
The radio-tracking protocol was established as follows. The
night (19h00-07h00, in solar time) was divided into four periods
of three hours each. Each radio-tracking session consisted of
one or two periods, during which we recorded as many locations
as possible. We recorded all bearings for each radiolocation
within a 10-minute interval to reduce error associated with bad-
ger movement and within 45-135º intervals for cross bearings.
Exceptions to this were the first night after the release of the ani-
SPATIAL ECOLOGY OF BADGERS IN NE IBERIAN PENINSULA 229
Vie Milieu, 2009, 59 (2)
mal and when a particular animal was difficult to find. In these
cases, radio-tracking took place for the whole night. Each indi-
vidual was followed for at least one session every ten days when
possible.
Space use analyses: Radio-tracking data and spatial estima-
tors were calculated with Range VII software (South et al.
2005). Thirteen out of the 15 monitored badgers had reached
home range stabilization according to the Incremental Area Plot
method (hereafter IAP; Harris et al. 1990), which represents the
accumulated area used with the increasing number of fixes.
Only active locations outside the sett (n = 640) of these 13 bad-
gers were used for the analyses. No major changes in the envi-
ronment were noted during the 10-year study period, so we ana-
lyzed all territories irrespective of the year during which data
were collected. To avoid problems in home range estimators
caused by unequal time intervals between locations we first ran-
domly deleted locations until they were at least one hour apart in
the same night-period (De Solla et al. 1999). When individual
home ranges overlapped with others simultaneously, a Multi-
Response Permutation Procedures test (MRPP, Biondini et al.
1988) was performed in order to test for significant differences
in space use. If significance was not reached, badgers were con-
sidered as members of the same group, the home range of which
was obtained by merging all fixes. In spite of criticism (Borger
et al. 2006), the Minimum Convex Polygon (hereafter MCP) is
the method employed most frequently in home range studies.
However, MCP requires a subjacent uniform distribution of
data, and it is therefore not necessarily optimal for comparing
data across studies. Otherwise, the Kernel method seems to be a
better index for home range description, but it also has the prob-
lem that the bandwidth selection method has a great influence
on the results, which prevents robust comparisons between stud-
ies (Laver & Kelly 2008). Thus, home ranges were estimated
using both methods in order to provide better comparability with
other studies: Minimum Convex Polygon with 95% of locations
(MCP95) and fixed kernel estimator (Worton 1989) with 95% of
the utilization distribution (FK95) as recommended by Laver &
Kelly (2008). For fixed kernel estimates an optimal smoothing
parameter was created for each home range (Kenward et al.
2001) by multiplying the smoothing parameter found by the
minimum square method (hcv) by a correcting factor (Worton
1995, Seaman & Powell 1996, De Solla et al. 1999). This factor
was searched, by trial and error, at 0.01 intervals starting from 1
hcv and was accepted when K95 was the smallest range that
allowed a single shape as a home range (avoiding unconnected
patches) as expected for territorial species like the badger
(Blundell et al. 2001, Borger et al. 2006, Hodder et al. 1998).
Comparisons between sexes and areas concerning mean values
of home range estimators (MCP and FK, Table I) were conduct-
ed with the Mann-Whitney test using SPSS 15 for Windows
(SPSS, Chicago, IL). We obtained similar results for both esti-
mators, so in the text we only show the results of FK to avoid
redundant data.
Group size and population density: Group size was estimated
in a systematic way for a wooded area of Collserola only, where-
as a coarser estimation was obtained for Montserrat. The proce-
dure for the calculation of group size was based on the simulta-
neous monitoring of all known setts in each home range on a
given night. Badgers were very suspicious and shy, and our pre-
vious experience showed that, in most cases, they would not
come out of a sett if humans were around. In addition, each indi-
vidual used between at least three and ten setts during their
tracking period (Bonet-Arbolí 2003), so a lot of people would
be required to simultaneously watch all setts at night. Therefore
sett monitoring was performed by sign surveys during two con-
secutive mornings in order to ascertain which setts had been
used by badgers on a given night and in a given range. The sett
watching procedure usually extends for three consecutive nights
in order to deal with the possibility of badgers occasionally
sleeping away from their usual setts. In our case, we decided to
perform the censuses over several non-consecutive nights in the
course of one year (07/1998-07/1999) in each territory because,
although a clear seasonal pattern of sett use exists in Collserola
(Bonet-Arbolí et al. 2005), badgers frequently, and unpredict-
ably, move away from their favorite setts for several consecutive
days within seasons. This monitoring schedule was also useful
to dilute the effect that transients visiting a given range for a few
days (particularly males, see results) would have on the overes-
timation of group size in such a low density population. There-
fore, results are given as the mean number of individual ± stan-
dard error across monitoring sessions, in each home range. Cen-
suses started when the limits of each monitored range had been
established by means of radio-tracking, and sometimes extended
beyond the death of the tracked individual.
The estimation of the number of badgers based on the num-
ber of active setts requires knowledge of all setts in a range.
Besides the discovery of new setts thanks to the radio-tracking
of badgers, a systematic survey (1992-1995) conducted in an
area (A) of approximately 400 ha before the beginning of the
trapping period allowed us to find several setts of interest for
that purpose, because A was later partially included in three
adjacent badger ranges. The area of A represented 65 % of the
home range of F5 + F6, 20 % of the home range of M7 and 96 %
of the home range of F9 (Fig. 1). Sett surveys are highly time-
consuming in Collserola owing to the roughness of the land-
scape and the thickness of the vegetation such that it would have
been impossible to complete the survey of each territory within
the study period. Therefore we used the number of setts (S)
found inside A during that previous survey to extrapolate the
total number of setts (S
tot
) in each range. All setts were visited
several times during the study period and those that were clearly
abandoned by badgers were discarded for the subsequent calcu-
lations. In order to take into account those setts that would have
gone unnoticed during the survey, together with those built since
then, we calculated the survey efficiency from the number of
setts that the tracked individuals used within A and which were
already known from the previous survey. This figure was 75 %
(i.e. in 1992-1995 we found three out of every four setts present
in the surveyed area of Collserola at the time of radio-tracking).
Therefore, S
to t
= [(S/0.75)/A(ha)] * K95(ha) + outliers.
230 G. MOLINA-VACAS, V. BONET-ARBOLÍ, E. RAFART-PLAZA, J. D. RODRÍGUEZ-TEIJEIRO
Vie Milieu, 2009, 59 (2)
Outliers were setts used by the tracked individuals that were
located outside home ranges and setts not used by the tracked
individuals and located outside home ranges at a similar dis-
tance (mean distance of outlier setts used by the tracked indi-
viduals to the border of the home range in question).
Thus, the total number of active setts on a given night (AS
tot
)
as extrapolated from the number of setts actually found active
(AS) is: AS
to t
= (AS/S)*S
tot
.
Finally, two additional factors are needed to estimate the
number of badgers based on the number of active setts: the sett
changing rate (i.e. the frequency with which badgers change
from one sett to another between two consecutive days) and sett
sharing frequency.
Concerning the sett changing rate, the use of the same sett
on two consecutive days by an individual results in one active
sett/badger whereas sett shifting would result in two active setts/
badger. With radio-tracking data and using 23 series of two con-
secutive days spread over the four seasons (of all individuals in
these three territories), the probability of returning to the same
sett was 0.48 and the probability of moving to another sett was
0.52. Therefore, we assumed 0.5 frequencies for each situation
and we thus obtained ¾ badgers/active sett, if AS
tot
> 1.
Sett sharing frequency was estimated by opportunistically
setting camera-traps at setts that seemed to be in use all around
the ranges of Collserola where the censuses took place. We
detected two badgers on only one occasion out of the nine sam-
pled nights (12.5 %). Given this low figure we assumed that
each active sett was occupied by a single badger on a given day.
In Montserrat, a camera trapping survey was carried out over
two periods: the first one during the trapping sessions in order to
confirm badger activity in setts, and the second one, one year
later, to detect and identify the maximum number of individuals
per group. 373 camera/night were placed near sett entrances,
badger paths and latrines, in the three territories (two of them
holding one radio-tagged badger and one holding two) as well
as in an adjacent control area without tagged animals but with
known badger activity (Area O). Each camera was in place for
an average of only 3.73 days at a given site, so results were con-
sidered together with those obtained by live-trapping and must
be considered with caution. The minimum number of recorded
Fig. 1. – a, Location of study areas in the Iberian Peninsula (Montserrat Mountain Park in the upper left corner and Collserola in the
bottom right corner). b, c, and d, represent the home ranges of all radio-tagged badgers based on MCP95 contours in the UTM refer-
ence system. a, Montserrat study area at a scale of 1:20,000; b, Southern side of Collserola study area (7 individuals) at a scale of
1:33,000, and c, Northern side of Collserola study area (2 individuals) at a scale of 1:21,000. Solid and broken lines represent males
and females respectively. Stippled areas represent wooded patches. Only individuals with Incremental Area Plot (the increase in the
accumulated used area when adding more fixes) stabilization are represented.
SPATIAL ECOLOGY OF BADGERS IN NE IBERIAN PENINSULA 231
Vie Milieu, 2009, 59 (2)
individuals in each home range was used as an estimator of
group size.
Population density was calculated on the basis of total
recorded individuals across groups, per study area, and two fig-
ures are presented, one considering only the area occupied by
ranges on the one hand and a wider area encompassing all rang-
es on the other.
RESULTS
We obtained sufficient data for 13 radio-tracked bad-
gers that had reached home range stabilization as judged
from the IAP (6 males and 7 females, Table I, 578 fixes,
mean = 44.46 ± 30.17, range 20-127). These were all of
the Montserrat individuals (2 males and 2 females) and 9
badgers from Collserola (4 males and 5 females). In terms
of home range size, in Collserola we found differences
between the sexes (FK95: m = 388.1 ± 72.8 ha, f = 95.2 ±
37,3 ha; U = 1, P = 0.027). Two females (F5 and F6) had
overlapping home ranges (MRPP test, δ = 0.809, P = 0.42,
F5 + F6 FK95 67.0 % for F5 and 79.4 % for F6, Fig. 1)
and were therefore considered as belonging to the same
group. The magnitude of the difference between the sexes
did not seem as high in Montserrat Mountain Park (FK95:
m = 85.9 ± 32.8 ha, f = 59.7 ± 2.3 ha), but the small sam-
ple size precludes statistical analysis. In Montserrat, the
home ranges of M2 and F4 overlapped almost completely
(MRPP test, δ = 0.809, P = 0.79, M2 + F4 FK95 over-
lap = 81.7 % for M2 and 75.7 % for F4, Fig. 1). However,
in spite of a small overlap between the ranges of M1 and
F3, the locations of these two individuals were signifi-
cantly separated in space (δ = 48.287, P < 0.001, M1 + F3
FK95 overlap = 8.8 % for M1 and 5.2 % for F3, Fig. 1).
Therefore, M2 and F4 were considered members of the
same group, whereas M1 and F3 belonged to separate
groups. According to home range size tests, we distin-
guished three badger groups for further analysis: Montser-
rat badgers, Collserola males and Collserola females.
There was a significant difference between these groups
(Kruskal-Wallis test, FK95: H = 6.89, df = 2, P = 0.032):
Collserola males have larger home ranges than Collserola
females (FK: U = 1, P = 0.032) and Montserrat badgers
(FK: U = 0, P = 0.028), whereas Collserola females and
Montserrat badgers have similar home range sizes (FK:
U = 10, P = 1). According to IAP functions, we found two
different patterns of home range exploitation. Females
and males M1, M2 (Montserrat) and M13 (Collserola)
gradually reached the maximum size of their ranges by
regularly moving across their home ranges, whereas the
Table I. – Location, radio-tracking period, cause of the end of tracking, number of radio locations, and home range size (ha). M Male,
F female.
*
Montserrat Mountain Natural Park,
Southern side of Collserola Park, and
#
Northern side of Collserola Park.
Badger ID
Tracking period
Cause Fixes
Home Range
DD.MM.YY MCP95 FK95
M1
*
18.12.99-02.01.01 Battery ran out 44 117.7 118.7
M2
*
07.02.00-17.10.00 Broken collar 29 63.8 53.1
F3
*
23.02.00-08.09.00 Battery ran out 22 57.5 62.0
F4
*
08.02.00-12.10.00 Battery ran out 24 53.9 57.3
F5
17.02.97-22.07.97 Death (unknown) 45 77.4 58.1
F6
17.02.97-03.03.99 Death (unknown) 85 57.8 49.0
M7
24.01.98-09.07.98 Death (poaching) 34 284.6 314.4
F8
05.02.99-03.05.99 Death (road-kill) 9 - -
F9
03.03.99-19.08.99 Broken collar 28 88.2 135.9
F10
23.03.00-14.01.01 Death (Poaching) 29 23.7 12.1
M11
11.11.03-04.12.03 Signal loss 4 - -
M12
16.06.04-13.06.05 Broken collar 52 450.3 501.4
M13
31.07.05-17.11.06 Battery ran out 39 227.0 219.0
F14
#
16.02.06-10.03.06 Broken collar 20 151.0 221.0
M15
#
02.12.06-23.07.07 End of eld work 127 702.2 517.7
Mean Montserrat males ± SE (n = 2) 37 ± 8 90.8 ± 27.0 85.9 ± 32.8
Mean Montserrat females ± SE (n = 2) 23 ± 1 55.7 ± 1.8 59.7 ± 2.3
Mean Collserola males ± SE (n = 4) 63 ± 22 416 ± 106.5 388.1 ± 72.8
Mean Collserola females ± SE (n = 5) 41 ± 12 79.6 ± 20.9 95.2 ± 37.3
Mean males ± SE (n = 6) 54 ± 15 307.6 ± 96.4 287.4 ± 79.1
Mean females ± SE (n = 7) 36 ± 9 72.8 ± 15.1 85.1 ± 26.6
232 G. MOLINA-VACAS, V. BONET-ARBOLÍ, E. RAFART-PLAZA, J. D. RODRÍGUEZ-TEIJEIRO
Vie Milieu, 2009, 59 (2)
remaining males (all of them belonging to Collserola) and
female F3 (Montserrat) increased their home range by
exploiting different areas at different times, which entails
a sharp rise in the IAP curve (Fig. 2).
Census and group size in the wooded area of Collserola
During the census period, one to three badgers were
detected in home range F5 + F6 (mean: 1.5 ± 0.3, n = 7
monitoring sessions); zero to two individuals were detect-
ed in home range M7 (1.8 ± 0.5, n = 4, M7 was not found
during one of the censuses) and one individual was detect-
ed in home range F9 in the two monitoring sessions car-
ried out (F9). In home range F5 + F6, the monitoring ses-
sions were carried out after the death of F5. Therefore,
while this home range was used by at least two females in
1997, the number of animals during the following two
years was normally one (F6), although we detected two
individuals on one occasion and three individuals on
another. In home range M7, the most frequent number of
badgers detected was two, while it is clear that F9 ranged
alone during its tracking period. Taking into account the
size of the home ranges, badger density in the wooded
part of Collserola during the study period was 1.6 ind./
km
2
(considering only the area occupied by the three ter-
ritories). Given that these territories were adjacent, the
density within the MCP100 drawn around all locations of
all individuals (720 ha) was 0.6 individuals/km
2
.
In Montserrat at least three badgers were detected in
home range M1 : M1 and two other non-tagged adults,
which could be distinguished by the different tonality of
their hair. In home range F3 we found a minimum of three
badgers as well: F3 and two subadults, which were prob-
ably her previous years offspring. Home range M2 + F4
also contained three animals: M2, F4 and one non-tagged
adult. Finally, in Area O we again identified a minimum
of three individuals (one adult, one sub-adult and one cub)
by camera trapping. So we obtained a minimum group
size of three individuals (adults and sub-adults) per home
range and a population density of 1.9 individuals/km
2
.
Ranging patterns
Males seem to range over larger areas than females in
Collserola. For example, M7 was caught in January 1998
and was consistently detected within the eastern half of
its home range (Fig. 1) and slept in dens within that part
of the home range. In April, it started to exploit the neigh-
boring female home range (F5 + F6) and slept in a den in
the overlap zone, while occasionally returning to its for-
mer range to forage and rest. In July it disappeared from
the study area, returning in October to the F5 + F6 home
range, when it was shot by a poacher. Similarly, individu-
al M12 was caught near a sett in June 2004, in the western
part of its home range and its signal was lost after release.
In August, it was found foraging and sleeping in the oppo-
site (eastern) corner of its home range, and in February
2005 it returned to the original home range inhabited by
at least one female (as judged from the presence of signs
made by cubs). Finally its collar was broken when it
moved to a new area in June 2006.
Although one-night excursions far away from the nor-
mal range were performed by several individuals in both
study areas, no such movements lasting for several weeks
were observed for the Montserrat individuals or Collsero-
la females. The high mobility of males is further illustrat-
ed by the fact that two males disappeared from the area in
which they were caught, shortly after release. One of them
was caught the same day at the same sett that F10 was
caught, the signal of its transmitter having been lost the
night of its release. Another one was caught inside the
home range of M12, 8 months before M12, and after a
few days of tracking, it disappeared. Although a failure in
the radio system cannot be ruled out, this never happened
to Montserrat individuals or Collserola females. Indeed,
the sole Collserola female for which we could not gather
enough data to calculate its home range was followed for
two months before it was killed by a car. This female was
consistently using the western third of the F5 + F6 home
range (when F6 was already dead) but it slept outside the
limits of this home range.
In Montserrat the three studied territories contained at
least three members, with at least one of them containing
individuals of both sexes (M2 + F4). In contrast, in Coll-
serola, F9 was solitary in its home range, as revealed by
the systematic census carried out. Several one-day visits
at all known setts in the small range of F10 suggested that
this female was living solitarily as well. On the other
hand, F6 sometimes shared its home range with one or,
occasionally, two additional individuals (one of them was
F5 in 1997), but the census revealed that it was sometimes
ranging alone.
DISCUSSION
For both study areas we found population density val-
ues close to those obtained for the South and West Iberian
Peninsula (Revilla & Palomares 2002, and Rosalino et al.
2004 respectively). These results are also comparable to
those obtained by Kowalczyk et al. (2000) in Bialowieza
Primeval Forest, and place our populations at the corre-
sponding low population density level of the sclerophyl-
lous Mediterranean dry forests (Virgós & Casanovas
1999) in contrast to badger populations inhabiting the
British Isles (Johnson et al. 2002). Along with the low
population densities, territories were large, particularly in
the case of Collserola males. Only badgers from Poland
and the south of the Iberian Peninsula (Revilla et al. 2001)
have larger home ranges than Collserola males at a lower
population density (Kowalczyk et al. 2003).
Even though the small sample size in Montserrat pre-
SPATIAL ECOLOGY OF BADGERS IN NE IBERIAN PENINSULA 233
Vie Milieu, 2009, 59 (2)
cludes statistical analysis, it is clear that the magnitude of
the difference between male and female home range sizes
is much greater in Collserola than in Montserrat (Table I):
Collserola males had a mean home range size over five
times that of females for MCP95 and over four times for
FK95, whereas for Montserrat this figure was less than
two for both estimators (Table I). In addition, for MCP95
the smallest male home range in Collserola (M13) was
1.5 times larger than the largest female home range (F9)
while in Montserrat the smallest male home range (M2)
Fig. 2. – Incremental Area Plot for MCP95 for individuals which reached the home range stabilization (M1 to M15). Same plotting was
conducted for FK95 with similar results (MRA= Maximum Range Area).
234 G. MOLINA-VACAS, V. BONET-ARBOLÍ, E. RAFART-PLAZA, J. D. RODRÍGUEZ-TEIJEIRO
Vie Milieu, 2009, 59 (2)
had a size comparable to that of females.
Similar, but less marked, tendencies for male home
ranges to be larger than those of females have been report-
ed for some other low density populations (Do Linh San
et al. 2007b, Kowalczyk et al. 2003). No such striking
differences in home range size between sexes have been
reported for any other European population (e.g. Bodin et
al. 2006, Palphramand et al. 2007, Kowalczyk et al. 2003,
Remonti et al. 2006). Nevertheless, the situation in Coll-
serola is similar to that of Hinode in the suburbs of Tokyo
where male badgers have territories three times larger
than females (Kaneko et al. 2006). This difference in
home range size is attained by males by exploiting differ-
ent areas of their territories at different times of the year
(as judged from IAP patterns). Therefore, all evidence
strongly suggests that males are more mobile than females
and exploit or occasionally visit different areas at differ-
ent times. In Montserrat, even though the sample size was
small, all evidence points to the fact that badgers form
classical mixed-sex groups of small size like other Euro-
pean low density populations. In Collserola, the basic ter-
ritorial unit seems to be a solitary female, which would be
the first animal to settle in an empty area based on the
richness in trophic resources (Tuyttens et al. 2000b, Tuyt-
tens et al. 2000a). It may subsequently associate with
other individuals under unknown conditions, probably
females, as suggested by the fact that the only two indi-
viduals tracked at the same time that completely over-
lapped their ranges were two females (F5 and F6). Assum-
ing that both sexes have similar overall metabolic require-
ments, and therefore the difference in home range size
can not be explained by differences in energetic needs,
the large difference in home range size in Collserola sug-
gests that females are the key resource in male spatial
organization, as predicted by the AKH (Neal & Cheese-
man 1996, Roper et al. 1986).
We found a notable difference in population density
between the two Parks (Collserola 0.6 individuals/km
2
,
Montserrat 1.9 individuals/km
2
), in spite of them having
similar habitat, weather and soil conditions. This may
reflect the fact that, even though there are few habitat dif-
ferences between Collserola and Montserrat when group-
ing habitats into main categories, Montserrat Park has a
higher proportion of fruit crops than cereals, which could
provide higher food availability. In addition, the Collse-
rola badger population is physically isolated from other
surrounding natural reserves and suffers a higher influx of
people than Montserrat, which means higher levels of
badger sett disturbance, poaching and road-kill risk. Nev-
ertheless, it has to be borne in mind that the systematic
census was carried out in a wooded part of Collserola and,
even though this is representative of 80 % of the Parks
area, several indications suggest that density may be high-
er in the agricultural periphery. For example, visual obser-
vations on one night revealed at least three badgers wan-
dering around a sett used by M12 in the agricultural
periphery of Collserola (G Molina-Vacas pers obs). This
suggests that group size in agricultural areas may be high-
er than in wooded areas. Given that territories were simi-
lar in size, density may be higher as well. In contrast, we
found a strikingly small home range in that agricultural
part of Collserola (the range of F10 was less than half the
size of the range of the other females) and its female
inhabitant was apparently living solitarily. Therefore, a
higher density could also be reached by the juxtaposition
of very small territories in the richest parts of the Park
(i.e. the agricultural ones, see Molina-Vacas et al., this
issue) inhabited by one, or a few females. More research
in the agricultural periphery of Collserola is needed in
order to ascertain which the prevailing mode is.
Although it was not the aim of the present paper to dis-
cuss territoriality in our populations, all indications sug-
gest that badgers of Montserrat and Collserola are indeed
territorial, as is the case for all the studied populations of
any density to date, with the possible exception of the
Bristol population (Harris 1984). First, the intrasexual
home range overlap is almost a case of all or nothing (c.f.
Fig. 1). Second, F9 and F6 were tracked simultaneously
for 2 months without trespassing over their common
range borders. Shortly after F6 died, after which its range
remained empty for some months, F9 made a two-night
excursion deep into the F5 + F6 range. Finally, a fight
between two unknown individuals was observed on the
border of the F5 + F6 range, which was marked with a
combination of visual (i.e. paths) and chemical (i.e.
latrines) signs (Bonet-Arbolí 2003).
At first glance, the spatial organization of badgers in
Collserola is similar to the typical mustelid spacing pat-
tern (Powell 1979), with the likelihood of females form-
ing groups, probably due to the greater tolerance between
females of this species compared to other mustelid spe-
cies (Woodroffe & Macdonald 1995). The pattern
observed in Collserola was first observed by Kruuk
(1978) in Wytham Woods. Kruuk observed that 45% of
the studied individuals belonged to a specific kind of
social group, which he named joint ranges, in which the
males’ ranges overlapped with those of females from dif-
ferent main setts.
We suggest that, at low densities, where females range
alone or in very small groups, males need to encompass
several female territories in order to increase their mating
opportunities, and this could be achieved at low risk for
males of encountering other aggressive males. This spa-
tial strategy in males is only achievable if female territo-
ries are not too large, which is the case in both study areas,
probably due to the existence of sufficient food resources.
Where home range richness is very low and females need
to have large territories to satisfy their nutritional needs
(Broseth et al.1997, Rodriguez et al. 1996, Revilla & Pal-
omares 2002) males would be unable to encompass more
than one female home range, thus giving rise to pairs as a
basic unit of social organization. In contrast, at high den-
SPATIAL ECOLOGY OF BADGERS IN NE IBERIAN PENINSULA 235
Vie Milieu, 2009, 59 (2)
sities, where several females cohabit, one home range is
enough to ensure a high number of mating opportunities,
and the probability of encountering aggressive neighbor-
ing males is high, so that it would be advantageous for a
male to be a permanent member of a multi-female group.
Ac k n o w l e d g e m e n t s . We thank Professor T J Roper and
three anonymous referees for their helpful comments that great-
ly improved an earlier version of the manuscript. We are grate-
ful to Collserola Park for financial support and Barcelona Zoo
veterinary services and Can Balasch Biological Station for their
veterinary and logistical support. VBA and ERP received fel-
lowships from the Generalitat de Catalunya during part of the
work. We also appreciate the help of A Barroso and the Montser-
rat Mountain Park guards for their help with the trapping and
radio-tracking tasks. Badgers were trapped and manipulated
with permission of the Departament de Medi Ambient i Habitat-
ge of the Catalan government, the ethical inter-universities com-
mission of Catalonia, the Parks’ authorities and the hunters’
associations. The English version of this manuscript has been
revised by R Rycroft from the UB’s Linguistic Advice Service.
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Received October 30, 2008
Accepted February 9, 2009
Associate Editor: E Magnanou
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: We provide a temporal overview (from 2012 to 2018) of the outcomes of tuberculosis (TB) in the cattle and badger populations in a hot-spot in Asturias (Atlantic Spain). We also study the badger’s spatial ecology from an epidemiological perspective in order to describe hazardous behavior in relation to TB transmission between cattle and badgers. Culture and single intradermal tuberculin test (SITT) were available for cattle as part of the National Program for the Eradication of TB. A field survey was also carried out in order to determine the paddocks and buildings used by each farm, and the information obtained was stored by using geographic information systems. Moreover, eighty-three badgers were submitted for necropsy and subsequent bacteriological studies. Ten badgers were also tracked, using global positioning system (GPS) collars. The prevalence of TB in cattle herds in the hot-spot increased from 2.2% in 2012 to 20% in 2016; it then declined to 0.0% in 2018. In contrast, the TB prevalence in badgers increased notably (from 5.55% in 2012–2015 to 10.64% in 2016–2018). Both cattle and badgers shared the same strain of Mycobacterium bovis. The collared badgers preferred paddocks used by TB-positive herds in spring and summer (when they were more active). The males occupied larger home ranges than the females (Khr95: males 149.78 ± 25.84 ha and females 73.37 ± 22.91 ha; Kcr50: males 29.83 ± 5.69 ha and females 13.59 ± 5.00 ha), and the home ranges were smaller in autumn and winter than in summer. The averages of the index of daily and maximum distances traveled by badgers were 1.88 ± (SD) 1.20 km and 1.99 ± 0.71 km, respectively. One of them presented a dispersive behavior with a maximum range of 18.3 km. The most preferred habitat was apple orchards in all seasons, with the exception of winter, in which they preferred pastures. Land uses and landscape structure, which have been linked with certain livestock-management practices, provide a scenario of great potential for badger–cattle interactions, thus enhancing the importance of the badgers’ ecology, which could potentially transmit TB back to cattle in the future.
... For example, a reduction in density may allow remaining individuals to spread out within the habitat [20,43]; if home range sizes remain the same, this should lead to a reduction in spatial overlap among conspecifics. Alternatively, reducing density may allow individuals to increase the sizes of their ranges [23,44], with the result that overlap among conspecifics remains the same even though animals are more widely distributed across the habitat. In contrast to these scenarios, however, members of our study population displayed few changes in patterns of space use following the flood. ...
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Identifying the factors that favor group living is central to studies of animal social behavior. One demographic parameter that is expected to substantially shape spatial and social relationships is population density. Specifically, high population densities may favor group living by constraining opportunities to live alone. In contrast, low densities may allow individuals to spread out within the habitat, leading to a reduction in the prevalence or size of social groups. Abrupt changes in density following natural catastrophic events provide important opportunities to evaluate the effects of population density on patterns of spatial and social organization. As part of long-term studies of the behavioral ecology of a population of highland tuco-tucos (Ctenomys opimus) at Monumento Natural Laguna de los Pozuelos, Jujuy Province, Argentina, we monitored the demographic and behavioral consequences of a flood that inundated our study site during December 2012. Unlike most species of Ctenomys studied to date, highland tuco-tucos are group living, meaning that multiple adults share burrow systems and nest sites. Despite a post-flood reduction in population density of ~75%, animals present on the study site during the 2013 breeding season continued to live in multi-adult social units (groups). No differences between pre- and post-flood home range sizes were detected and although between-unit spatial overlap was reduced in 2013, overlap within social units did not differ from that in pre-flood years. Animals assigned to the same social unit in 2013 had not lived together during 2012, indicating that post-flood groups were not simply the remnants of those present prior to the flood. Collectively, these findings indicate that group living in highland tuco-tucos is not driven by the density of conspecifics in the habitat. In addition to enhancing understanding of the adaptive bases for group living in Ctenomys, our analyses underscore the power of catastrophic events to generate insights into fundamental aspects of social behavior.
... These were 95% kernel utilisation distribution (KD95), and 95% Minimum Convex Polygons (MCP95) (cf. [27]). The home-ranges of each animal, calculated from GPS and 'GPS-corrected dead-reckoned data' data, for both MCP95 and KD95, were exported as polygon vector shapefiles, transferred into QGIS 3.6.3 ...
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Background Recent developments in both hardware and software of animal-borne data loggers now enable large amounts of data to be collected on both animal movement and behaviour. In particular, the combined use of tri-axial accelerometers, tri-axial magnetometers and GPS loggers enables animal tracks to be elucidated using a procedure of ‘dead-reckoning’. Although this approach was first suggested 30 years ago by Wilson et al. (1991), surprisingly few measurements have been made in free-ranging terrestrial animals. The current study examines movements, interactions with habitat features, and home-ranges calculated from just GPS data and also from dead-reckoned data in a model terrestrial mammal, the European badger (Meles meles). Methods Research was undertaken in farmland in Northern Ireland. Two badgers (one male, one female) were live-trapped and fitted with a GPS logger, a tri-axial accelerometer, and a tri-axial magnetometer. Thereafter, the badgers’ movement paths over 2 weeks were elucidated using just GPS data and GPS-enabled dead-reckoned data, respectively. Results Badgers travelled further using data from dead-reckoned calculations than using the data from only GPS data. Whilst once-hourly GPS data could only be represented by straight-line movements between sequential points, the sub-second resolution dead-reckoned tracks were more tortuous. Although there were no differences in Minimum Convex Polygon determinations between GPS- and dead-reckoned data, Kernel Utilisation Distribution determinations of home-range size were larger using the former method. This was because dead-reckoned data more accurately described the particular parts of landscape constituting most-visited core areas, effectively narrowing the calculation of habitat use. Finally, the dead-reckoned data showed badgers spent more time near to field margins and hedges than simple GPS data would suggest. Conclusion Significant differences emerge when analyses of habitat use and movements are compared between calculations made using just GPS data or GPS-enabled dead-reckoned data. In particular, use of dead-reckoned data showed that animals moved 2.2 times farther, had better-defined use of the habitat (revealing clear core areas), and made more use of certain habitats (field margins, hedges). Use of dead-reckoning to provide detailed accounts of animal movement and highlight the minutiae of interactions with the environment should be considered an important technique in the ecologist’s toolkit.
... Las áreas que se calculan a partir de imágenes satelitales o modelos espaciales siempre se desvían de la realidad, a menos que el relieve sea totalmente plano y ajustado a la superficie del geoide de referencia. Por ello, cuando se reportan áreas planimétricas se están ignorando las irregularidades del relieve lo que conlleva a que se produzcan resultados que subestiman las áreas reales (ej.: Broomhall et al. 2003;Admasu et al. 2004;Find'o y Chovancova 2004;Molina-Vacas et al. 2009;Simcharoen et al. 2008;Mattisson et al. 2011). En términos planimétricos, se asume que un kilómetro cuadrado de área representa la misma cantidad de superficie en una zona llana que en una montañosa, cuando no es realmente así. ...
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Spatial information, satellite products and their derivatives are important sources of environmental information. However, the accuracy of area and distance measurements is sacrificed by using planimetric projections and consciously ignoring relief irregularities, essential in ecological studies where the important estimate area is those perceived by organisms and the real surface of which resources density depend. In this paper, we assess differences in estimation of geographic areas accounting for or ignoring terrain topology, in ecological studies applications or distribution modeling, in Cuban archipelago. By using parcels and virtual species simulated distributions we assess the bias size in those estimations over a topological area derived from a digital elevation model, with 26.8m of spatial resolution. Underestimation bias can reach in Cuba up to 1598 m2 of differences, equivalent to 45% of error. Errors are higher in mountain regions. We probe that equally planimetric size parcels can reach differences up to 15%, depending on location and included proportions of relief types. Changes in potential distribution area estimates for virtual species present errors over 700 km2. If using relativized values, the error diminishes. More studies are in need on the methodological impact of this bias, mostly for its implications for ecological conclusions or on its potential influence in management decisions.
... But with regard of our species of interest (i.e., mesocarnivores), our results showed that these species are not easily detected by unbaited cameras, as almost all of them responded better to meat-and fish-baited cameras, with the exception of feral cats. Typically, unbaited cameras are placed on animal trails, but also in den entrances or latrines (Molina-Vacas et al. 2009;Oleaga et al. 2011;Curveira-Santos et al. 2017). In consequence, this sampling procedure would be highly subjective and should include a new random variable, i.e., the researcher experience. ...
Article
A wide variety of baits is used in camera trap studies, but few have been validated to obtain optimal and comparable results. The present study aimed to analyze the effectiveness of different baits commonly used in camera trap studies in the Iberian Peninsula. First, a bibliographic review was performed in order to identify the most common baits. Then, an intensive camera trap monitoring program was carried out with the identified baits. Finally, we estimate the effect of bait type on the average detection of several target and nontarget mammal species. Results show that chicken- and fish-baited cameras produced satisfactory results for targeted species. Chicken meat showed higher detection for badgers, stone martens, and common genets. Canned sardines in vegetable oil resulted an attractive bait for red foxes and feral dogs. Unbaited cameras, vegetable-based baits, or scats and urine as operational attractants resulted ineffective baits for mesocarnivores, with the exception of feral cats. A variety of baits has been used for mesocarnivore inventories or single-species studies in the Iberian Peninsula. In consequence, most of these inventories and studies cannot be fully compared. Moreover, as baits are not equally effective, diversity and abundance data could be underestimated and compromise the quality of the survey data. The present results highlight the need for standardized methods in camera trap studies to follow a replicable methodology in order to obtain feasible and comparable results among studies.
... The density of each road category was calculated through a moving window in the ESRI ArcGIS ® software package. We considered a window radius of 750 m, according to the average home range size of badgers (Balestrieri et al. 2016;Kauhala and Holmala 2011;Molina-Vacas et al. 2009;Gaughran et al. 2018). All the predictors were rasterized at a 40-m spatial resolution. ...
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Collisions between wildlife and vehicles represent the main conflict between infrastructures and ecosystems. Road mortality is the largest single cause of death for many vertebrates, representing a growing phenomenon of remarkable dimension. Most studies in road ecology investigated spatial roadkill patterns, showing that roadkill probability is often higher near optimal habitat for a large amount of species. Landscape connectivity has been less often considered in roadkill research, and only few studies considered habitat suitability and landscape connectivity at the same time. The purpose of the present study was to evaluate the relative importance of habitat suitability and landscape connectivity in determining roadkill risk for a habitat-generalist carnivore, namely, the Eurasian badger in the Abruzzo region (Central Italy). We collected occurrence data of living individuals from camera trapping and roadkill data of through a Citizen Science initiative. We used the occurrence data to produce a habitat suitability model (HSM) and a landscape connectivity model (LCM). Both HSM and LCM were then used as predictors in combination with road characteristics to fit a roadkill risk model. We found that landscape connectivity was more important than habitat suitability in determining roadkill risk for the Eurasian badger. Overall, the density of regional roads was the most important variable. Our finding highlighted how important is to consider landscape connectivity in planning mitigation measures aimed to preserve habitat-generalist species.
... In contrast, male home range size changes in relation to females, with males travelling greater distances when females have larger home ranges. Studies on badgers have also shown that the home range configuration of males can be driven by female distribution in space (Molina-Vacas et al., 2009). ...
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Despite enormous efforts, complete animal tuberculosis (TB) eradication has only been achieved in few regions. Epidemiological analyses are key to identify TB risk factors and set up targeted biosecurity measures. Here, we conducted an in-depth characterization of 84 extensive beef cattle farms from a high TB prevalence region in Western Spain, and assessed how farm management and wildlife presence on farms contribute to cattle TB risk. Twenty-six out of 84 variables were associated with cattle farm TB positivity. Farm management variables associated with TB positivity included older cattle, larger herd size, highly fragmented farm structure and greater connectivity between farms. TB-positive farms provided supplemental feed over a higher number of months, used calf feeders, and had higher number of waterholes. Detecting Eurasian wild boar (Sus scrofa), red fox (Vulpes vulpes), European badger (Meles meles), roe deer (Capreolus capreolus), or Egyptian mongoose (Herpestes ichneumon) on cattle farms was also associated with farm TB positivity. The best ordinal regression model indicated that in farms with a large herd size (> 167 animals) the odds of being positive or recurrently positive (versus negative) was 7.34 (95% CI = 2.43–23.51) times higher that of farms with small herd size. Further, for every additional host species detected in the farm premises, the odds of being TB-positive increased by 56%. We conclude that both cattle management and wildlife need to be targeted for successful TB control in grazing-based farming systems.
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A recent report shows that tooth wear in Eurasian badgers can be used to differentiate four age classes (Hancox, 1988). However, data from known-age badgers in Wytham Woods, Oxfordshire (UK), show that the tooth-wear criteria of Hancox cannot be used reliably to age badgers from that population. This discrepancy may arise because badgers living on different diets have markedly different rates of tooth wear. Since such differences in diet are quite common between populations, and since tooth wear can be sufficiently rapid that some yearling badgers have heavily worn teeth, we conclude that the technique is unlikely to be of general application.
Chapter
The statistical procedures that are most widely used in ecological population and community research belong to the family of parametric methods. Embedded in these procedures are assumptions about the normal distribution of the underlying population, homogeneity of variances and linear response patterns. One of the problems encountered in ecological and vegetation studies, however, is that these assumptions are very difficult, if not impossible, to meet. In addition, a very serious shortcoming of the most widely used statistical methods is the lack of congruence between the geometry of the data space, which is for the most part Euclidean, and the analysis space, which in the standard parametric tests and most of the nonparametric tests, is not Euclidean. In ecological and vegetation studies, the combination of a failure to meet model assumptions and a lack of congruence between the geometries of the data space and the analysis space can lead, as shown in this paper, to gross errors in data interpretation and hypothesis testing. A new and powerful statistical technique (MRPP) is presented in this paper which is free from assumptions about the underlying distribution model of the population under analysis, can easily handle nonlinear data structures and more importantly meets the congruence principle (a common geometry for both the data and analysis spaces). The theoretical formulations for MRPP and its randomized block design counterpart MRBP as well as their relationship to other statistical methods are outlined in the first part of a paper. This is followed by computer algorithms and programs needed for their implementation as well as a series of detailed examples which demonstrate major advantages of MRPP and MRBP over the currently most widely used statistical methods. Computer programs are available from the authors free of charge (send a blank diskette).
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Simulations are necessary to assess the performance of home-range estimators because the true distribution of empirical data is unknown, but we must question whether that performance applies to empirical data. Some studies have used empirically based simulations, randomly selecting subsets of data to evaluate estimator performance, but animals do not move randomly within a home range. We created an empirically based simulation using a behavioral model, generated a probability distribution from those data, and randomly selected locations from that distribution in a chronological sequence as the simulated individual moved through its home range. Thus, we examined the influence of temporal patterns of space use and determined the effects of smoothing, number of locations, and autocorrelation on kernel estimates. Additionally, home-range estimators were designed to evaluate species that use space with few restrictions, traveling almost anywhere on the landscape. Many species, however, confine their movements to a geographical feature that conforms to a relatively linear pattern. Consequently, conventional analysis techniques may overestimate home ranges. We used simulations based upon coastal river otters (Lontra canadensis), a species that primarily uses the aquatic-terrestrial interface, to evaluate the efficacy of fixed and adaptive kernel estimates with various smoothing parameters. Measures of shoreline length within contours from fixed kernel analyses and the reference smoothing parameter were best for estimates of 95% home ranges, because smoothing with least squares cross validation (LSCV) often resulted in inconsistent results, excessive fragmentation, and marked underestimates of linear home ranges. Core areas (50% density contours) were best defined with fixed kernel LSCV estimates. Fewer locations underestimated linear home ranges, and there was a subtle positive relation between home-range size and autocorrelation. Generally, as location numbers increased, autocorrelation increased, but differences from the "true" home range decreased. Results were similar for our simulations and empirical data from 13 river otters. Examination of empirical data revealed that data with high positive autocorrelation illustrated seasonal reproductive activities. Because autocorrelation does not negatively influence estimates of linear home ranges, assessment of independence between data points may be more appropriately viewed as a means to identify important behavioral information, rather than as a hindrance.
Article
1. We present data on the effects of female/female competition on the reproductive success of European badgers Meles meles in Britain. While a single, dominant female usually suppresses reproduction in other female group members, elsewhere up to four females may breed successfully in each group. 2. Across Britain, the mean number of breeding females per social group decreases in populations living at high latitudes, where food availability and population density are relatively low. Within our study population in southern England, the number of breeding females in each social group increased with the quality of the group territory. 3. In our study population, all females aged 3 years and older became pregnant, but a proportion of females lost their litters during gestation or around the time of birth. The proportion of females that lost their litters was higher in larger groups. However, mean litter size at weaning remained roughly constant despite variation in the number of females lactating, and preweaning cub mortality appeared to be low. Females tended to disperse away from very large groups, and may have increased their chances of breeding in this way. These results suggest that females competed for breeding status, but that there was little competition among females thereafter. 4. The characteristics of females that produced cubs successfully differed between the 2 years when this study was carried out. Only females in relatively good condition bred successfully following a very dry summer, when food availability was low. However, when food availability was high, following a wet summer, females were in better condition on average and breeding success appeared to be related to social status. We suggest that this reflected a difference in the structure of competition between the two years. 5. In contrast with the situation in other social carnivores, reproductive suppression in badgers appears to be a response to female/female competition for resources, rather than a need for co-operative care of the young. Although alloparental care occurred in at least one badger population, this population had the lowest, rather than the highest, level of reproductive suppression.
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Much discussion of the determinants of carnivore sociality has been dogged by its reliance on largely untestable hypotheses. Here we employ spatial analysis of published data on badger (Meles meles) setts and latrine sites from five study localities in Britain to test the idea that den locations can determine territory shape and size. Territorial boundary points were identified from latrines shared between two or more main setts. These were found to lie in close proximity to the hypothetical borders of a fixed-territory model constructed from Dirichlet tessellations around main setts. At three localities the fit was better than chance expectation, given by points scattered at random and repelled from main setts. These results suggest a functional interpretation of territorial behaviour, in terms of maximizing reproductive success by defending an established breeding den, which the conventional models of central-place foraging do not encompass. A test of the Dirichlet borders against a model of differential expansion suggested that occupants of some main setts could expand one or more borders to the detriment of neighbouring territories, probably in response to variations in food availability around the given den sites. The implications of these results are that (1) by defining territory size, suitable den sites for breeding and overwintering may impose an upper limit on the density of badger social units, and (2) the distribution of main setts may therefore influence the size of group that can be accommodated in the resulting territory. The question of why badgers are sociable therefore finds a reply with unexpected significance given to the location of dens. We suggest the model might be appropriate to other vertebrates for which an established den or nest site could represent a key resource to be costed in an energy currency in the animal's defence budget.
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(1) This paper presents information obtamed on the prevalence and distribution of tuberculosis in badgers from four areas in south-west England. One hundred and thirty-six badgers, representing twenty-four social groups, were removed for post-mortem exammation following outbreaks of tuberculosis in cattle. (2) Mean group size for each area varied little (4.8-7.6 individuals) but mean territory size varied considerably (22.0-74.7 ha). (3) The prevalence of tuberculosis varied greatly from 6.9% to 34.5% indicating spatial and/or temporal variations in prevalence in local populations.