Behaviour of badgers (Meles meles) in farm buildings: Opportunities forthe transmission of Mycobacterium bovis to cattle?

Bryony A. Tolhurst a,*, Richard J. Delahay b, Neil J. Walker b, Alastair I. Ward b, Timothy J. Roper a

a Department of Biology and Environmental Science, University of Sussex, Brighton BN1 9QG, UKb Central Science Laboratory, Sand Hutton, York YO41 1LZ, UK

Applied Animal Behaviour Science 117 (2009) 103–113

A R T I C L E I N F O

Article history:

Accepted 23 October 2008

Available online 30 December 2008

Keywords:

Badger

Farm buildings

Foraging behaviour

Ranging behaviour

Bovine tuberculosis

Disease transmission

A B S T R A C T

Eurasian badgers (Meles meles) are implicated in the transmission of bovine tuberculosis

(Mycobacterium bovis) to cattle. Here we investigate potential spatio-temporal foci of

opportunities for contact between badgers and cattle in farm buildings. We discuss the

relative occurrence of different badger behaviours and their potential for facilitating

disease transmission, and examine correlates of building use by badgers including

availability of specific farm-based resources, badger demography, and environmental

variables. In addition, we investigate seasonal variation in home range structure with

respect to farm building use. Badger activity and ranging behaviour were monitored

intensively on six cattle farms throughout the year between July 2003 and June 2005 using

remote surveillance, radio-tracking and faecal analysis. Badgers foraged in buildings,

exhibited close, investigative ‘nose-to-nose’ contact with housed cattle and excreted/scent

marked on and around feed. A negative correlation was observed between frequency of

visits and 24 h rainfall and a positive correlation with minimum temperature. Badgers

visited feed stores most intensively and selected cattle ‘cake’ over other available food

types. A peak in visits was detected in spring and summer, and male badgers were more

likely to visit buildings than females. Management prescriptions for disease prevention

centre on reducing opportunities for direct or indirect contact between badgers and

housed cattle. It is thus recommended that effort to exclude badgers from buildings should

focus on feed stores and cattle housing during spring and summer in warm, dry weather.

� 2008 Elsevier B.V. All rights reserved.

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1. Introduction

Bovine tuberculosis (bTB) in cattle, caused by thebacterium Mycobacterium bovis is regarded as one of theUK’s most serious animal health problems (House ofCommons, 2008). The Eurasian badger (Meles meles L.) issusceptible to bTB infection and is a wildlife reservoir of M.

bovis. There is compelling evidence to suggest that

* Corresponding author. Present address: School of Pharmacy and

Biomolecular Sciences, University of Brighton, Cockcroft Building, Lewes

Road, Brighton BN2 4GJ, Sussex, UK. Tel.: +44 1273 644 794;

fax: +44 1273 679 333.

E-mail address: b.a.tolhurst@brighton.ac.uk (B.A. Tolhurst).

0168-1591/$ – see front matter � 2008 Elsevier B.V. All rights reserved.

doi:10.1016/j.applanim.2008.10.009

transmission occurs between badgers and cattle (Krebset al., 1997; Donnelly et al., 2006) but the precisemechanism remains unknown.

Infection may occur via direct contact or indirectly whencattle graze on grass contaminated by badger urine or faeces(e.g., Benham and Broom, 1989, 1991; Brown et al., 1993;Hutchings and Harris, 1999) or investigate contaminatedland in the vicinity of badger setts (e.g., Sleeman andMulcahy, 1993; Courtenay et al., 2006). Transmission as aresult of direct contact has received relatively little attentionin the scientific literature because field observations suggestthat badgers avoid grazing cattle (Benham and Broom, 1989;Benham, 1993). Anecdotal observations (Muirhead et al.,1974; Cheeseman and Mallinson, 1981; Sleeman and

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113104

Mulcahy, 1993) and systematic evidence (Garnett et al.,2002a, 2002b; Roper etal., 2003; Tolhurst,2006) suggest thatbadgers regularly forage in farm buildings such as feed storesand cattle sheds, where they consume and contaminate feedand may come into direct contact with cattle. Considerationofthesepossibilities isembodiedinrecentrecommendationsas tothe role that farm bio-security measures can play as partof the UK’s bTB control strategy (Independent ScientificGroup, 2007; Department for Environment Food and RuralAffairs, 2007).

Detailed information on the behaviour of badgers inrelation to farm buildings may help in the development offarm husbandry practices that minimise disease transmis-sion risks. Garnett et al. (2002a, b) demonstrated thatbadger foraging activity in buildings peaked in July andwas negatively correlated with total rainfall in thepreceding 24 h. However the study was conducted attwo farms only and data were collected solely during partof the year (March to October). Hence, the extent to whichsuch activity is representative of cattle farms in the region,and the degree to which badgers visit farm buildings in thewinter, remain unknown. Seasonal shifts in badger homeranges in relation to farm use were not quantified.Moreover, direct information on the frequency of occur-rence of different farm foods in badger diet and the relativefrequency of potentially high-risk behaviours in a range ofbuilding types, was absent.

The current study aims to further quantify badgerbehaviour in farm buildings and investigate environmentalcorrelates of farm visits, in order to identify spatio-temporal foci of bTB infection risk. The objectives were: (a)to test for year-round weather-related and seasonalvariation in the intensity of badger use of farm buildings;(b) to test for variation in badger home range structureover time in relation to use of buildings; (c) to investigatedifferences in the frequency of badger visits to differentfarm building types; (d) to explore differences in theexploitation of different types of food; (e) to quantifybehaviours considered to potentially incur infection risk;and (f) to examine demographic correlates of building useby badgers, such as sex-related differences.

2. Materials and methods

2.1. Study sites

The study area comprised six farms in the south-west of England

where badger population density and the incidence of bovine tubercu-

losis in cattle were high. The habitat consisted of a mixture of deciduous

woodland, permanent pasture, farm buildings, houses and gardens, and

pockets of arable land, including maize and cabbage fields. The farms

were situated between 800 m and 48 km apart and were divided equally

into beef and dairy herds. Some variation in cattle husbandry was

observed, for example what cattle were fed, where they were kept,

and when. At all three dairy farms, and one beef farm, cattle were fed

in buildings throughout the year, and additionally some cattle, such as

bulls and very young or sick calves, were housed during all seasons. At one

of the remaining beef farms, cattle were permanently at pasture from

April to September, with the occasional exception of young calves or sick

animals and at the other, a bull was housed throughout the summer. The

farms exhibited consistently poor bio-security measures with one excep-

tion, where some systematic procedures were put in place to exclude

wildlife (for a full description of husbandry practices see Tolhurst, 2006;

see below for details of cattle feed types available).

At each farm, the study site was designated as the farm buildings plus

surrounding farmland extending to a distance of 500 m in every direction,

creating a circle with an area slightly smaller than 100 ha (1 km2). This is

broadly consistent with the size of the largest reported badger territory in

the south-west of England (Krebs et al., 1997) and was consequently

considered to be likely to encompass the home ranges of all badgers

potentially visiting each farm.

2.2. Territory delineation and live-trapping of badgers

The extent to which badger social group territories overlapped with

farm buildings was identified at each study site using bait marking

(Delahay et al., 2000). A mixture of peanuts conspicuously coloured

indigestible plastic pellets and golden syrup was fed, once a day, at

potential main setts within the 500 m circle at all study sites. The mix

was deposited in up to 10 different ‘bait points’ around and within 15 m of

the outer holes, created by making a small depression in the ground with

the heel of the foot and covered with stones to prevent non-target uptake.

This process was undertaken during spring 2003 for 10 consecutive days.

During feeding and for a three-week period thereafter, all latrines were

searched for ‘returns’ (scats containing beads) in a systematic survey

radiating from each baited sett following badger paths. Returns recovered

in farm buildings and yards were traced back to the sett at which the

colour had been fed, and were assumed to be within the territory of the

corresponding social group. Cage traps baited with peanuts (see Cheese-

man and Mallinson, 1979) were then used to capture badgers at the main

setts of social groups whose territories included farm buildings. Trapping

occurred approximately four times per year, from June 2003 to June 2005,

with a closed season between early February and mid May each year to

avoid catching females with dependant cubs. Captured badgers were

transferred under Home Office licence to a sampling facility, where they

were anaesthetised using a mixture of ketamine hydrochloride, butor-

phanol tartrate and medetomedine (De Leeuw et al., 2004). Each indivi-

dual was tattooed at first capture for identification, sexed and weighed

(Clifton-Hadley et al., 1993). All badgers, except for cubs weighing less

than 2 kg, were fur-clipped (Stewart and Macdonald, 1997) to provide a

unique mark that would allow identification by remote surveillance and

direct observation. A total of 50 badgers was captured from six different

social groups, of which 39 were fur-clipped, and 17 (comprising 11

females and 6 males), fitted with split rawhide leather radio-collars

(Cheeseman and Mallinson, 1979). Each collar weighed <1.5% of the

average adult badger body weight, which is considerably less than the

stipulated welfare criterion of 3% (Brander and Cochran, 1971; Cochran,

1980). Initial selection of individuals for radio-collaring was based on

acquiring equal numbers of each sex, however low capture success in the

second year of the study resulted in all adults being collared, excluding

those with neck injuries or abnormalities. Exact numbers of animals in

each social group were unknown, however badger social groups at nearby

locations have been recorded to reach 30 individuals, and average 12

(Tuyttens et al., 2000). Based on these figures and the number of indi-

viduals fur-clipped (Table 1), it is estimated that a mean% of 54 � 8.5

badgers per social group were individually marked in this way.

2.3. Weather and season

Site-specific daily rainfall data (mm) were collected using rain gauges

(Wirefree Rain Monitor, Alana Ecology, Shropshire, UK) downloaded

weekly, and temperature (8C) dataloggers (Tinytag Plus, Alana Ecology,

Shropshire, UK) downloaded every three months. These data were vali-

dated by hourly weather data: rainfall (mm) and maximum and mini-

mum temperature (8C) provided by a local weather station (Nailsworth

Weather Station, Nailsworth, Gloucestershire, UK). Based on changes in

photoperiod, the seasons were defined as winter (January, February and

March), spring (April, May and June), summer (July, August and Septem-

ber), and autumn (October, November and December).

2.4. Remote surveillance

Video surveillance equipment and still cameras with motion sensors

were deployed at the six farms between October 2003 and June 2005 for

10 nights per month, in order to record badger visits to farm buildings.

Video ‘installations’ (Highview Electronics, Mitcheldean, Gloucestershire,

UK) consisted of a watertight plastic case containing a time-lapse Sony

VCR, timer, compartment and terminals for one 12 V dry fit lead acid

battery, and a video camera mounted with an infrared LED array. Still

cameras (TRAILMASTER, Goodson and Associates, Inc., 10614 Widmer,

Table 1

Number of fur-clipped and radio-collared badgers per social group, percentage of fur-clips detected by remote surveillance, and number of times detected

throughout the study.

Social

group

Number of

fur-clipped

badgers

Number of

radio-tracked

badgers

Number of

fur-clips detected

by remote surveillance

Percentage of fur-clips

detected by remote

surveillance

Number of repeat

visits by fur-clipped

individuals

1 12 4 2 17 11, 6

2 4 1 1 25 19

3 12 7 4 33 1, 6, 2, 3

4 4 2 2 50 1, 1

5 5 3 2 40 2, 5

6 2 0 0 0 0

Total 39 17 11 28 � 7* 5 � 2**

* Denotes mean (�S.E.) percentage of fur-clipped badgers detected (‘total’ percentage being redundant in this context).** Denotes mean (�S.E.) number of repeat visits by individuals.

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113 105

Lenexa, Kansas, 66215, USA) were triggered by both active infrared (AIR)

sensors (two aligned units emit a beam of infrared light which is triggered

when an object crosses) and passive infrared (PIR) sensors (one unit

detects changes in infrared light emitted by animate moving objects). A

total of 12 video installations and 13 still cameras were deployed, rotated

between the six farms to obtain equal coverage of a sample of each type of

facility during each season. Video cameras were positioned at the

entrance of facilities to record the entire inside of feed stores, silage

clamps and cattle housing. Footage of farmyards was recorded inciden-

tally, as views of the entire inside of a building, and deployment of

cameras out-of-reach of cattle often necessitated installation of a camera

to simultaneously record a section of surrounding farmyard. Where

badgers were detected in the farmyard but were not observed to enter

the building, farmyard use was recorded. Still cameras were positioned to

capture images of the entrance to facilities only, as we were not able to

observe badger resource use using this method, moreover the range of

view was restricted comparative to video, and entrances generally small

enough to adequately monitor.

Each remote surveillance sampling session, recorded concurrently at

different facilities on the same night, was termed a ‘camera night’. Remote

installations were programmed to record between sunset and sunrise

throughout the year and settings were adjusted to incorporate changes in

hours of daylight. Unforeseen circumstances (for example loss of battery

power or disturbance caused by cattle chewing cables or knocking over

tripods) occasionally reduced the number of hours recorded to less than

the entire night. Hence length of camera night was noted throughout the

study period and was observed to vary between 3 and 14 h.

Feed types available within the facilities were noted immediately

prior to each camera night. Video footage was analysed in terms of when

individual badgers entered and exited a building; designated a ‘visit’, and

what they were doing. Image clarity permitted behavioural observations,

including what resources, if any were exploited, even if there were several

different food types visible within the view.

Numbers of badger ‘visits’, badgers visiting and duration of visits

were analysed as three separate response variables: (i) total frequency of

visits by badgers per camera night (potentially including repeat visits by

the same individuals; (ii) mean duration of badger visits (in minutes) per

Table 2

Ethogram of behaviours exhibited by badgers from video footage.

Activity Code Description

Feeding (farm food) 1 Farm foods see

Foraging 2 Sniffing the air

searching groun

Excreting or scent-marking 3 Seen lifting tail

Moving through 4 Passes through

Auto-grooming 5 Application of t

Intra-specific aggressive behaviour 6 Conspecifics ch

aggressive phys

Interacting with cattle 7 Interactions ch

whereby anima

Interacting with cattle; nose-to-nose contact 8 Interactions ch

whereby the no

camera night and; (iii) maximum number of badgers in view per camera

night (the maximum number of badgers visible for the duration of each

visit). The latter variable was used as a proxy because accurate calculation

of number of individual badgers visiting per camera night was prevented

by a low rate of detection of fur-clips on the video footage (mean% 28 � 7;

Table 1). Possible explanations include rapid fur re-growth, and few badgers

captured proportional to group size. At least one repeat visit was recorded

for all 11 fur-clipped individuals that were detected (Table 1), suggesting

that exploitation of farm resources represents habitual rather than occa-

sional behaviour.

Seasonal effects were investigated using Generalized Linear Model-

ling (GLM) where all three response variables were modelled with a

Poisson distribution and regressed against the categorical variable ‘sea-

son’ (GenStat for Windows Edition 8.1.0.152, VSN International Ltd.,

Hemel Hempstead, UK). Any effect of year and differences between

individual farms were controlled for via inclusion in the model.

The relationship between rainfall, temperature and response variable

(i) (number of visits by badgers per camera night) was investigated using

Generalized Linear Modelling (GLM) where the response was modelled

with a negative binomial distribution. Maximum temperature was

removed from the analysis on the basis of collinearity with minimum

temperature, the latter being considered more biologically relevant

because badgers are nocturnal and the lowest temperatures tend to occur

at night.

To standardise interpretation of the rate of badger visits across

camera nights of varying length, the variable ‘number of hours per camera

night’ was entered into the model as a log-transformed offset. In analyses

where over-dispersion was present in the response (taken to be when

residual mean deviance >2) inference was based on an F-test with

residual mean deviance used as the denominator. Otherwise, change in

deviance was used, referenced against a chi-squared distribution on the

corresponding number of degrees of freedom.

Relative frequencies of badger behaviours and visits to different farm

facilities and feed types were compared using one-way ANOVA (Minitab

15 Statistical Software) after the response variables were converted to

proportions and arcsine transformed. An ethogram was constructed

(Table 2) from which five types of behaviour were selected for analysis:

n going in mouth/chewing observed.

or substrate/moving around in exploratory manner,

d, etc. Can include scent communication.

and squatting onto substrate.

facility or enters and exits view without exhibiting any other behaviour

ongue or paws to parts of body in repetitive movements. Shakes body.

asing/squaring up to each other and ruffling up fur. Engaging in

ical contact such as biting of other animals rump and neck.

aracterized by investigative exploration by either species of the other,

ls came within 2 m of each other.

aracterized by investigative exploration by either species of the other,

ses of both animals came within 10 cm (termed ‘nose-to-nose’ contact)

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113106

feeding, foraging, interacting with cattle, interacting with cattle (nose-to-

nose contact) and excreting/scent marking (it was not always possible to

distinguish between defaecating, urinating and caudal or anal scent gland

marking). The selection was based on the high frequency of occurrence of

the former two behaviours and the high potential relative risk of bTB

cross-infection associated with the latter three.

2.5. Radio-tracking

A total of seventeen adult badgers were radio-tracked between July

2003 and June 2005. Ten of these were tracked for up to one year each for

eight nights per month in repeated sequences of half-night sessions, in

order to monitor their movement patterns and behaviour, and a further

seven were tracked throughout spring 2005 to supplement data for this

season. Triangulated radio-fixes were obtained from two vantage points

and, where possible, badgers were located visually using a generation 2+

night-vision monocular. A minimum inter-fix interval of 30 min was

chosen, because all study animals at one site could be located easily

and each could comfortably traverse an average home range within this

time, thus reducing the extent to which the data were temporally auto-

correlated (Doncaster and Macdonald, 1997; Salvatori et al., 1999).

Logistic regression was used to investigate differences in the fre-

quency of radio-fixes located in buildings according to season and sex of

badgers. A binomially distributed response variable (fix in buildings = 1,

fix elsewhere = 0) was regressed against the categorical variables ‘season’,

and ‘sex’ (GenStat for Windows Edition 8.1.0.152, VSN International Ltd.,

Hemel Hempstead, UK). Home ranges encompassing 95% of radio-fixes

(considered to represent the outer home range boundary, excluding

outlying locations: Kenward, 1987) and core activity areas were gener-

ated for each of the 11 female and 6 male badgers, for each season using

minimum convex polygons (MCP) and kernel estimators (ArcView GIS

3.2, ESRI, Redlands, California and Ranges6 1.2, Anatrack Ltd., Wareham,

Dorset, UK). Both techniques were used so as to allow comparison with

other studies whilst accurately quantifying the internal structure of

badger home ranges. Fixed kernels and a smoothing factor (h) selected

by visual assessment were used for each of the 17 animals based on the

raw distribution of fixes (e.g., Pope et al., 2004). The analysis was

standardised by using the median value of h for every animal (Kenward,

2001). Utilization plots were generated to identify the percentage of fixes

that defined the core area, using an inflection point determined by eye

(Harris et al., 1990; Kenward and Hodder, 1996). Linear regression was

used to investigate seasonal variation in home range and core area size

overlapping the farm buildings at each site.

2.6. Dietary analysis

Dietary investigation of scats to determine the relative frequency

with which badgers exploited the different types of feed derived from

farm buildings was carried out at a sub-sample of three of the study

farms; time and labour constraints preventing scat collection and analysis

at all sites. The three farms were selected on the basis of the consistent

availability of the same feed types throughout the year. Feed types

included maize and grass silage, cattle ‘cake’ (a pelleted meal consisting

of items such as wheat, palm kernel, maize gluten, rapeseed extract,

sunflower extract, molasses and vegetable oils) and ‘concentrates’, con-

taining similar ingredients to cake but excluding molasses and vegetable

oils as binding agents. A sample of 20 scats was collected from each of the

three sites once per season, between July 2003 and June 2005, at latrines

within 5 m of each badger sett and, where present, inside farm buildings.

Scats were stored frozen and subsequently defrosted in 70% alcohol and

separated into fractions using graded sieves. Each macro-fraction was

then placed in a petri dish and viewed under 10� magnification using a

binocular light microscope, in order to separate and identify food items.

Table 3

Modes of accessibility scores for each facility type at different times of year. W

Facility type Mode of scores

W SP SU AU

Feed store 2 2 2 2

Cattle housing 3 4 4 3

Farmyard 5 5 5 5

Silage clamp 3 3 3 3

Dietary components were quantified using the frequency of occurrence

method (Skoog, 1970), expressed as a percentage of the total number of

samples (Zabala and Zuberogoitia, 2003). Farm-derived foods were iden-

tified using a feeding trial reference collection (see Tolhurst, 2006)

consisting of samples collected from the three study farms, and food

availability information provided from study-site surveys (see below).

Frequency of occurrence of different types of farm-derived food was

compared using one-way ANOVA (Minitab 15 Statistical Software) after

the response variable was converted to proportions and arcsine trans-

formed

2.7. Study-site surveys

A survey of each study site was carried out by one observer once per

season, between July 2003 and June 2005, where anthropogenic food

resources potentially available to badgers were recorded. In addition, the

potential accessibility of stored feed to badgers was assessed using

ranked scores from 1 to 5 as follows: 1 = inaccessible; 2 = fairly inacces-

sible; 3 = moderately accessible; 4 = little effort needed to gain access;

and 5 = freely accessible.

3. Results

3.1. Study-site surveys: resource availability in farm

buildings and surrounding land

Food available on the study farms included standingcrops, cereals in pheasant feeders and troughs on pasture,and stored cattle feed in buildings and yards. Five broadclasses of stored feed were identified: silage, cereal grains,concentrated feeds (cattle ‘cake’ and ‘concentrates’),‘straights’ (un-combined feeds), and hay and straw.Farm-building facilities were broadly divided into fourcategories: feed stores, cattle housing, farmyards andsilage clamps. There was little seasonal or inter-annualvariation in perceived accessibility to badgers of thesefacility types (see Table 3).

3.2. Weather-related variation

A negative association was found between rainfall inthe 24 h preceding each period of remote surveillance andthe frequency of badger visits to farm buildings and yards(GLM, F1,317 = 5.62, p < 0.05), and a positive associationbetween minimum temperature and frequency of visits(GLM, F1,317 = 25.33, p < 0.001). An interaction between24 h rainfall and minimum temperature (GLM,F1,316 = 28.16, p < 0.001 indicated that the effect of rainfallon badger visits to farms varied according to temperature.

3.3. Seasonal variation

Remote surveillance showed seasonal variation in thefrequency of badger visits to farm buildings and yards(GLM, change in deviance = 72.37, d.f. = 3, p < 0.001), the

= winter; SP = spring; SU = summer; AU = autumn.

Accessibility

Fairly inaccessible

Access possible with effort/little effort needed to gain access

Freely accessible

Access possible with effort

Fig. 1. (a) Mean number of badger visits to farms during each season; (b) mean maximum number of badgers in view during each season; and (c) mean

duration, in minutes, of badger visits per season. All data � S.E. and pooled across farms and years. Bars with a different letter denote seasons that were

significantly different from each other (GLM, z tests, p < 0.05).

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113 107

maximum number of badgers present during each visit(GLM, change in deviance = 44.21, d.f. = 3, p < 0.001) andthe duration of visits (GLM, F3,939 = 14.20, p < 0.001). Apeak in the former two variables was detected duringspring (April, May and June) and in the latter duringsummer (July, August and September)(see Fig. 1).Between-farm (GLM, change in deviance = 40.43, d.f. = 3,p < 0.001) and annual (GLM, change in deviance = 54.57,d.f. = 3, p < 0.001) variation was also detected. An inter-

action between season and farm (GLM, change indeviance = 5.67, d.f. = 15, p < 0.001) suggested that seaso-nal differences were not consistent across farms.

The frequency of badger radio-fixes located in farmbuildings differed between seasons (GLM, change indeviance = 16.38, d.f. = 3, p < 0.001). Badgers were morefrequently located in buildings during spring than in allother seasons and more in summer than in autumn orwinter (Table 4). In addition, there was seasonal variation

Table 4

Comparison of means tests for GLM analysis of radio-tracking data. The parameter estimate (Est.), z-statistic and p-value are shown for each combination of

explanatory levels, indicating the direction of the relationship between the 1st season and the 2nd on each row.

Season Frequency of radio-fixes in farm buildings Overlap between core areas and farm buildings

Est. z p Est. z p

Spring v summer 1.140 2.22 <0.05 1.230 1.16 NS

Spring v autumn 2.796 3.59 <0.001 3.420 2.28 <0.05

Spring v winter 3.220 3.14 <0.05 2.830 2.02 <0.05

Summer v autumn 1.656 2.06 <0.05 1.670 1.25 NS

Summer v winter 2.080 2.86 <0.05 1.520 1.12 NS

Fig. 2. (a) 95% kernel isopleth and (b) 100% minimum convex polygon home ranges for a male badger during autumn (dark grey), winter (black), spring (light

grey) and summer (black and white hatched). The extent of the farm-building complex (LH bottom corner) is denoted by a black border and the position of

the main sett by a black asterisk.

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113108

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113 109

in the overlap between badger home ranges and farmbuildings and yards (GLM, change in deviance = 3.06,d.f. = 3, p < 0.05) (Fig. 2). Badger core areas were morelikely to overlap with farm buildings during spring thanduring autumn or winter (see Table 4).

3.4. Frequency of badger visits to different farm facility types

Badgers visited all four types of facility and variationwas detected in the frequency of visits to each (one-wayANOVA, F3,16 = 3.47, p < 0.05). Visits to feed stores weremore frequent than to any other facility type, followed (indescending order) by cattle housing, farmyards and silageclamps (Fig. 3).

3.5. Food types exploited

Five different types of farm-derived food were observedin badger scats: cattle ‘cake’ or concentrated feed (it was

Fig. 3. Proportions of badger visits to different farm facilities � S.E. (data pooled a

denote facility types that were significantly different from each other (p < 0.05) (

Fig. 4. Proportions of different food types in badger scats containing farm-deriv

percentages. Bars with a different letter denote proportions of food types that

comparisons of means tests).

not possible to distinguish between these two), rolledbarley grains, wheat grains, wheat silage and maize silage.Variation was detected in the frequency of occurrence ofthe five food types (one-way ANOVA, F4,15 = 19.47,p < 0.001), with greater numbers of scats containing cattle‘cake’ or concentrates than all others, followed indescending order by barley, wheat, maize silage andwheat silage (Fig. 4). Remote surveillance revealed badgervisits to facilities containing five different types of farm-derived food: cattle ‘cake’, maize silage, wheat grains,cattle ‘cake’ mixed with maize silage, and grass silagemixed with maize silage. Variation that approachedsignificance was detected in the frequency with whichbadgers visited facilities containing the different foodtypes (one-way ANOVA, F4,15 = 3.06, p = 0.05), with morefrequent visits to those containing cattle ‘cake’ than allother types of farm-derived food (one-way ANOVA,comparisons of means tests, p always <0.05), followedby (in descending order) cattle ‘cake’ mixed with maize

cross farms and years) expressed as percentages. Bars with a different letter

one-way ANOVA, comparisons of means tests).

ed foods � S.E. (data pooled across farms, seasons and years) expressed as

were significantly different from each other (p < 0.05) (one-way ANOVA,

Fig. 5. Proportions of different behaviours recorded during badger visits to farm buildings � S.E. (data pooled across farms and years) expressed as

percentages. Bars with a different letter denote behaviours that were significantly different from each other (p < 0.05) (one-way ANOVA, comparisons of means

tests).

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113110

silage, maize silage, wheat/maize silage mixed with grasssilage, and hay.

3.6. Badger behaviour

The frequency of occurrence of the five behavioursvaried (one-way ANOVA, F4,15 = 6.23, p < 0.05) withfeeding occurring more frequently than all other beha-viours (Fig. 5). All of the observed ‘nose-to-nose’ contacts(N = 31) occurred in cattle housing, whereas 69.2 % ofbadger excretions/scent markings (N = 17) occurred in feedstores and 15.4% occurred in each of silage clamps andcattle housing.

A sex difference was demonstrated in the frequency ofradio-locations in buildings (GLM, change in deviance =18.01, d.f. = 1, p < 0.001) and in the overlap between coreactivity areas and farm buildings (GLM, change indeviance = 3.98, d.f. = 1, p < 0.05). Male badgers werelocated in buildings more frequently than females(comparison of means tests, parameter estimate = 3.790,z = 3.30, p < 0.001) and their core areas were more likely tocontain farm buildings (comparison of means tests,parameter estimate = 3.220, z = 2.54, p < 0.05).

4. Discussion

Our results, taken from a larger sample of farms, andincorporating year-round effects, confirm the findings ofGarnett et al. (2002a, b) in that frequency of badger visits tofarms was negatively correlated with 24 h rainfall. Weinvestigated this relationship in more detail and found aninteraction between rainfall and minimum temperature,which suggests that increasing temperature may result in acorresponding increase in badger visits to farms, providedthat rainfall is low. Anecdotal observations during radio-tracking sessions were consistent with this hypothesis:badgers were observed to forage on pasture on warm, rainynights and in farm buildings and yards on warm dry nights.Earthworms dominate the diet of badgers in Britain (Kruuket al., 1979; Kruuk and Parish, 1981) and the speciesfavoured by badgers (Lumbricus terrestris and rubellus) are

most commonly found under pasture where they forage onthe surface at temperatures above 2 8C following recentrainfall (Satchell, 1967). Conversely, when the weather isdry or very cold, worms retreat deep underground and arenot accessible to badgers, forcing them to seek alternativefood sources. Badgers may be more active at highertemperatures per se, but it is likely that rainfall influencesthe direction of activity, i.e., towards buildings or to otherparts of the home range.

In our study the frequency of visits and number ofbadgers visiting peaked in spring, but visits lasted longerin summer and were also more likely to occur in summerthan in winter or autumn. Such seasonal variation wasunlikely to have been driven by changes in the availabilityof farm-derived foods, which was shown to vary littlethroughout the year. It is more likely that differential useof farm buildings at different times of year reflectschanges in badger body weight, energy requirementsand activity levels. Seasonal fluctuations in badger bodyweight have been noted by several authors (Neal, 1977;Kruuk, 1989; Rogers et al., 1997) and linked to bothnutritive status (Hanks, 1981) and other factors such asday-length and temperature (Kruuk and Parish, 1983).Given the predominance of earthworms in badger diet(Kruuk and Parish, 1981) and the positive correlationbetween earthworm biomass and both badger bodyweight (Kruuk and Parish, 1985) and population size(Kruuk and Parish, 1982), seasonal fluctuations in rainfallmight be expected to influence nutritive status, througheffects on earthworm availability. Hence the availabilityof farm-derived foods during periods when earthwormsare scarce may provide badgers with an importantalternative source of nutrition.

Most visits to farm buildings by badgers were recordedin feed stores, which reflects the main purpose of the visits,i.e., to obtain food (Garnett et al., 2002a, 2002b). Resourcesare likely to be more accessible and more attractive tobadgers when taken from feed stores, partly because of theabsence of cattle, although studies documenting theresponse of badgers to cattle (on pasture) are equivocaland report both habituation (Kruuk, 1989; Brown et al.,

B.A. Tolhurst et al. / Applied Animal Behaviour Science 117 (2009) 103–113 111

1993) and avoidance (Benham and Broom, 1989; Sleemanand Mulcahy, 1993).

The high frequency of occurrence of cattle cake/concentrates and barley in badger scats relative to foragefeeds is consistent with the findings of Benham (1985,1993), who detected a preference by badgers for cattle cakeand barley in feed choice experiments, and Garnett et al.(2002a, b) who identified cattle cake to be the targetedresource in over 55% of badger visits to farm buildings.Evidence from remote surveillance from the present studyalso indicated disproportionate selection of facilitiescontaining cattle ‘cake’ mixed with maize silage. Thisfinding is potentially important, given that this combina-tion is likely to be available only in cattle housing whererisks of contact between badgers and cattle may be high.

The higher frequency of farm visits by male badgers inthe present study could potentially be linked to socialdominance or differences in energy requirements or homerange size. There is no evidence of interference competi-tion based on a sex-related linear dominance hierarchy inthe Eurasian badger (Macdonald et al., 2002) and onlyminimal aggression was observed between feeding indi-viduals in the present study (aggressive behaviour wasrecorded from less than 3% of badger visits to buildings).Males might however visit buildings more frequently as adirect consequence of their home ranges encompassing alarger area (Neal and Cheeseman, 1996), but in our studythis explanation is unlikely given that at all study sitesmain setts were present within four hundred metres of thefarm buildings, which would have been incorporated in thehome ranges of both sexes. Hence, the most plausiblehypothesis explaining the observed sex-related variationin visits to farm buildings may relate to differences inenergy budgets, although no data currently exists tosupport this.

Transmission of bovine tuberculosis during badgerforaging visits to farm buildings and yards could poten-tially occur through the respiratory route as a consequenceof the ‘nose-to-nose’ contact described. Aerosol infection ismore likely to occur in buildings than on pasture (Ministryof Agriculture, Fisheries and Food, 2000) and the survival ofairborne microorganisms is aided by the dark, humidconditions of cattle housing, particularly if intensively-stocked and poorly ventilated (Robertson, 2000). Inaddition, in the present study, farm workers were observedto collect feed from feed stores and silage clamps at leasttwice a day, all of which was mixed and fed immediately tohoused cattle. Hence, any badger excreta deposited in feedstores and silage clamps was likely to be transferred totroughs or the floor of cattle housing within 24 h of beingdeposited. Any remaining excreta, particularly if incorpo-rated into feed, could remain infective for long periods,given that M. bovis persists in conditions of limitedexposure to ultraviolet light (Wray, 1975; Wilesmith,1991; King, 1997). Subsequent transmission of infection tocattle could potentially occur by ingestion during unse-lective feeding (Central Science Laboratory, 2006), byeructation and inhalation into the lungs, or inhaled directlyinto the respiratory system via the explosive snortingassociated with cattle exploratory behaviour of novel fooditems.

Knowledge gaps emerging from this study include alack of empirical data on the likelihood of transmission pergiven contact between badgers and cattle, and thepersistence of M. bovis in different types of excreta inbuildings.

Furthermore, annual and between-farm variation inbadger use of buildings indicates that management advicefor preventing access to farms by badgers may be mosteffective if ‘‘tailor-made’’ for individual farms rather thanbroad-based prescriptions. Differing husbandry practicesbetween farms, individual differences in badger behaviourand yearly changes in rainfall are potential sources ofvariation.

Potential measures to exclude badgers from housingand feed stores range from exclusion methods such aselectric fencing (see Tolhurst et al., 2008) and simpleprocedures such as closing the doors of feed sheds atnight (Department for Environment Food and RuralAffairs, 2007), to improved ‘‘housekeeping’’, for exampleclearing away spilled cattle cake from beneath silo bins.The extent to which the six farms represent the situationthroughout bovine tuberculosis ‘‘hotspots’’ however, isunknown.

5. Conclusion

In this study we identify spatio-temporal foci ofpotential bTB transmission arising from the habitual useof farm buildings by badgers. Badgers were most likely tovisit feed stores containing cattle cake in spring andsummer on warm, dry nights, and to exhibit ‘nose-to-nose’contact with cattle in housing. Common-sense measures toprevent contact between badgers and cattle are recom-mended.

Acknowledgements

This study forms part of a DPhil project by the firstauthor, funded by DEFRA (Division of Animal Health),under contract SE3029. We thank the farmers and land-owners; Irvine Carter, John Jones, Martin Wooldridge, JanRowe, Alan Smith, and Burt Mayo for their cooperation andassistance. We are also indebted to Ivan Judd at theNailsworth weather station for supplying rainfall andtemperature data. Finally, we are especially grateful to thefield staff at the Central Science Laboratory researchstation, Woodchester Park, for their expertise in trappingand handling badgers, in particular Paul Spyvee, SarahBoxall and Chris Hanks, without whom the study wouldnot have been possible.

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