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- Materials and methods
The management of European badgers Meles meles L. is of great concern in the British Isles, where this species is implicated in the transmission of bovine tuberculosis (TB) to cattle (Krebs et al. 1997; Eves 1999). Bovine TB, caused by the bacterium Mycobacterium bovis, is a zoonotic disease of cattle that has been increasing in incidence since the 1980s (Krebs et al. 1997).
Over the last 30 years, policies to control cattle TB in Britain have included two main components. The first component is intended to detect infection in cattle and prevent spread to other herds, and involves regular testing of cattle, with slaughter of any animals showing evidence of possible infection, as well as temporary movement restrictions on affected herds. Cattle control measures similar to these have successfully eradicated TB in much of the developed world. Control has been more difficult to achieve, however, where wildlife populations are persistently infected (Morris, Pfeiffer & Jackson 1994). Hence, the second component of British TB control policy has involved various forms of badger culling, intended to reduce the risk of transmission to cattle in high-risk areas (Zuckerman 1980; Dunnet, Jones & McInerney 1986; Krebs et al. 1997). Badgers and their dens (setts) are protected by national legislation and, since the 1970s, all badger culling carried out for disease control purposes has been performed by government staff.
Although various forms of badger culling have formed a component of British TB policy since 1973 (Krebs et al. 1997), their effectiveness as control measures appears variable. Virtual elimination of badgers from several localities in the British Isles has been linked to declines in the incidence of TB in cattle (Clifton-Hadley et al. 1995; Eves 1999; Griffin et al. 2005). Spatial associations between patterns of M. bovis infection in cattle and badgers indicate that transmission occurs between the two species at a local scale (Woodroffe et al. 2005), suggesting that more localized culling of badgers could also be expected to control cattle TB. However, analysis of data from a large-scale randomized, replicated and controlled field experiment (the Randomized Badger Culling Trial, RBCT) recently showed that the incidence of TB in cattle was higher in areas subjected to localized badger culling, similar to the form of culling implemented as past policy in much of Britain and Ireland, than in nearby areas where no experimental culling occurred (Donnelly et al. 2003; Le Fevre et al. 2005). The British government suspended experimental localized badger culling in 2003, because its failure to reduce the incidence of cattle TB on the time-scale tested indicated that this approach could be expected to contribute little to improved control (Donnelly et al. 2003; Bourne et al. 2005). Subsequently, however, similar management approaches have been included in policy proposals put forward by lobby groups (British Veterinary Association 2005; Gallagher et al. 2005; National Farmers’ Union 2005). A better understanding of the mechanisms underlying the link between badger culling and TB in cattle is vital to determine whether culling can be expected to contribute more effectively to TB control, or whether other management actions (e.g. badger vaccination, fertility control or improved cattle controls; White & Harris 1995; Swinton et al. 1997) might be more effective.
One explanation for the possibly detrimental effect of localized badger culling is that the consequent disruption of badger spatial organization might influence TB transmission, either among badgers or from badgers to cattle (Swinton et al. 1997; Tuyttens et al. 2000; Tuyttens & Macdonald 2000; Donnelly et al. 2003). Frequent movement of badgers between social groups has been associated with increased transmission of TB within a badger population (Rogers et al. 1998), and such movements are known to occur more frequently in low density badger populations, such as those suppressed by culling (Woodroffe, Macdonald & da Silva 1995). Hence, reduction of population density may reduce contact rates between badgers to a lesser extent than expected (Barlow 1996), and could even increase them (Swinton et al. 1997), potentially increasing TB prevalence in the badger population. In addition, badger culling has been linked to increases in the extent of badger ranging behaviour (Cheeseman et al. 1993; O’Corry-Crowe et al. 1996; Tuyttens et al. 2000), raising the possibility that individual badgers in populations subject to control may come into contact with a larger number of cattle herds and, if infected, could potentially trigger a larger number of infections in cattle. In TB-infected badger populations, either or both of these processes could increase the risk of transmission from badgers to cattle. Importantly, such ‘perturbation’ mechanisms may interact with simpler effects of reduced badger population density to produce TB dynamics that are strongly non-linear. Hence, they could reconcile the apparently contradictory findings that elimination of badgers appears to contribute to the control of cattle TB (Clifton-Hadley et al. 1995; Eves 1999; Griffin et al. 2005), while localized culling may have little effect or even increase TB risks to cattle (Donnelly et al. 2003).
An alternative, somewhat simpler, explanation for the apparently detrimental effects of localized culling is that experimental control areas could have been compromised (Godfray et al. 2004). Specifically, if landowners in areas randomly allocated to receive no officially sanctioned culling were, in fact, culling badgers illegally, then badger density might be lower in these areas than in those that received localized culling. If this was the case, it could explain why legal, government-implemented, culling appears to be less effective at controlling cattle TB than no (legal) culling at all.
Only limited information is available to evaluate the hypothesis that culling prompts perturbation of badger spatial organization in ways that might influence TB dynamics. Past studies have included before and after comparisons at single sites in response to localized culling (Cheeseman et al. 1993; O’Corry-Crowe et al. 1996; Tuyttens et al. 2000) as well as extrapolation of patterns from an undisturbed population (Rogers et al. 1998). Only one study has simultaneously compared two sites with and without localized culling (P. Riordan, D.W. Macdonald, R.J. Delahay, C.L. Cheeseman, K.M. Service, E. Fordham & B.J. Harmsen, unpublished data). Hence, the only studies of the effects of localized culling, similar to that implemented in the RBCT, document one-off changes in badger spatial organization, which might be because of site-specific factors. Given the need to understand the importance, if any (Bourne et al. 2004; Godfray et al. 2004), of social perturbation in influencing TB dynamics and, hence, the expected efficacy of measures such as badger vaccination in comparison with culling, there is a clear need for replicated studies that investigate general patterns of change in badger spatial organization in response to culling. To evaluate the hypothesis that culling may disrupt badger spatial organization, we compared the activity and spatial organization of badgers in 13 study areas exposed to different levels of culling.
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- Materials and methods
Our data indicate that culling influenced both the activity and spatial organization of badgers. The numbers of latrine pits containing colour-marked faeces, the distance between these bait returns and their original setts, and patterns of overlap between mapped home ranges were all related to the culling treatments applied. Importantly, and in contrast with previous studies, consistent differences between treatments were detected across multiple study areas with substantially different culling histories, indicating that they probably represent general patterns.
The number of latrine pits found to contain colour-marked faeces (bait returns) is not usually used as a measure of badger abundance (Delahay et al. 2000). However, both the number of latrines encountered away from setts (Tuyttens et al. 2001) and the number of faecal deposits encountered at setts in spring (Wilson et al. 2003) have been found to correlate with local badger density, suggesting that the numbers of bait returns might reasonably be expected to give an approximate index of badger numbers. Hutchings, Service & Harris (2002) suggested that badgers living at low densities may be less likely to defecate in latrines, potentially reducing the detectability of bait returns. This offers an alternative mechanism whereby the number of bait returns per sett might be lower at lower badger densities, but does not undermine the plausibility of a link between bait returns and badger abundance.
If the number of bait returns per sett does give an approximate index of badger numbers, then our findings indicate that, as expected, badger densities are suppressed by culling. This effect was greatest in proactive areas, but Fig. 2a shows that bait returns were also markedly lower in reactive areas than in areas not subjected to experimental culling. This argues against the hypothesis that the apparently negative effects of reactive culling on cattle TB might have been caused by widespread illegal culling of badgers in experimental control areas (Godfray et al. 2004). While these data indicate that reactive culling influenced badger activity over a scale of several square kilometres, analyses revealed no effect of particular setts’ exposure to reactive culling at a more local scale. Failure to detect such an effect could result from the low power of the analyses performed on data from within reactive areas, but could also reflect changes in the distribution of badger activity post-cull, dissipating localized effects over larger areas.
Bait returns suggest a reduced level of badger activity inside proactive culling areas, but badger populations appear to have persisted nevertheless, with a proportion of setts showing high levels of activity (Fig. 1). The persistence of highly active setts deep inside proactive culling areas relates to a variety of factors, including lack of landowner consent for culling and disruption of culls by animal rights activists.
While the number of bait returns per sett probably gives only an approximate index of local badger density, this measure suggests that culling may influence badger populations beyond the area actually culled. Overall, the average number of bait returns recovered per sett outside proactive areas was comparable with that recorded in no-culling areas (Fig. 2a). However, this measure declined with increasing proximity to the boundary of the culling area (Fig. 3a). Taken together, these results suggest that, in contrast with findings from more wide-ranging species (Woodroffe & Frank 2005), culling probably does not have a major impact upon the density of badgers in adjoining areas (consistent with Kruuk & Macdonald's 1985 portrayal of badgers as a ‘contractionist’ species that rarely expands its home ranges to occupy vacant space) but does have a small, measurable, effect on badger density and possibly an important effect on local population dynamics.
The distances moved by badgers, measured as the median distance between a bait return and its sett of origin, also varied in response to culling (Fig. 2b). While the spatial distribution of bait returns has been shown to give a good approximation to the location of territory boundaries in high-density populations (Kruuk 1978; Delahay et al. 2000), it is known to be a less reliable indicator of badger spatial organization in low-density populations (Kruuk & Parish 1982; Delahay et al. 2000). It is important to bear in mind that badgers use defecation for scent marking not just for excretion. Hence, while the distribution of bait returns might change (or not) in response to culling-induced changes in territorial organization, this does not necessarily demonstrate that movement patterns have (or have not) changed. If badgers move through an area, but do not defecate there, those movements will not be detected by this method. Interestingly, Tuyttens et al. (2000) found temporal changes in the distribution of bait returns that they attributed to the effects of culling, but could detect no changes in the movements of individual radio-collared badgers.
Despite these caveats, the evidence strongly suggests that badgers’ spatial organization was influenced by culling. Hence, our results uphold the findings of previous, less extensive, studies showing that culling prompts wide-ranging behaviour (Cheeseman et al. 1993; O’Corry-Crowe et al. 1996; Tuyttens et al. 2000). Moreover, the data presented in Fig. 3b suggest that the effects of culling on badger movement patterns might not be confined to the area actually culled. Outside proactive culling areas, the median distance to bait returns was greatest for setts in sectors closest to the boundary of the culling area. Hence, any consequences of badger movement patterns for TB transmission might also extend beyond the boundaries of the culling area.
The probability of contact between badgers, and between badgers and cattle, will be influenced by both the density of badgers and the extent of their movements. Bait returns suggested that, inside proactive culling areas, badger abundance was markedly reduced (suggesting lower probabilities of contact) but ranging behaviour increased (suggesting higher probabilities of contact). Not surprisingly, badger abundance appears to have been reduced to a lesser extent in reactive culling areas, but ranging behaviour was also somewhat elevated. Whether the combined effects of reduced density and more extensive movements could generate badger–cattle contact probabilities higher than those occurring in survey-only areas depends upon whether badger density or movement has the greatest influence on contact rates; this is unknown, although simple models might help to characterize the patterns. Nevertheless, these patterns do provide a possible biological mechanism that may explain the apparently greater incidence of cattle TB in reactive culling areas, despite reduced badger density. The plausibility of this argument depends in part on the time it would take for badger culling to generate additional cases of TB in cattle (Godfray et al. 2004). Behavioural data show that local reductions in badger density cause badgers to alter their ranging behaviour within a few days or weeks (Cheeseman et al. 1993; Roper & Lüps 1993; Woodroffe et al. 1995). suggesting that badger-cattle contact rates would change rapidly after culling. The time taken for these contacts to lead to new infections in cattle is unknown but presumably variable. Following infection, cattle become responsive to the tuberculin test after about three weeks (C. Howard, Institute for Animal Health, personal communication, cited in Le Fevre et al. (2005)). Hence, if badgers can infect susceptible cattle rapidly on contact, increased cattle incidence would be detectable 2–3 months after badger culling. Alternatively (or additionally), expanded badger movements might influence cattle TB incidence through greater transmission among badgers, with consequently higher prevalence, ultimately causing greater transmission to cattle (Swinton et al. 1997; Tuyttens et al. 2000). In this scenario, however, new infections in cattle would appear more slowly because an additional (badger-badger) transmission stage would be involved. To summarise, the patterns we observed could plausibly explain the apparently greater incidence of cattle TB in reactive culling areas, on the timescale at which it was detected. However, as reactive culling selectively removes badgers that are spatially associated with infected cattle and hence more likely to be infected themselves (Woodroffe et al. 2005), rates of contact with infectious badgers might not follow the same pattern as contacts with badgers in general. Hence, while our findings are consistent with the hypothesis that reactive culling may have influenced TB risks to cattle through perturbation of badger spatial organization, they do not provide a conclusive test of this hypothesis.
If localized culling does indeed influence contact rates between badgers and cattle in the manner that we hypothesize, this may have implications for the effectiveness of culling carried out on a larger spatial scale, as in the proactive treatment of the RBCT and in a similar study recently completed in Ireland (Griffin et al. 2005). Inside proactive culling areas, badger densities are substantially reduced, potentially countering effects of increased movement on contact rates with cattle. Hence, detrimental effects of badger culling on cattle TB incidence could be smaller than in reactive areas, or even non-existent. However, on the edges of proactive culling areas, including adjoining areas not subjected to culling, badger densities are less depressed but movements do appear to be increased. Therefore, if contact rates with badgers influence TB risks for cattle, these areas might be expected to experience elevated risks.
In conclusion, our results suggest that culling can profoundly affect both the density and the ranging behaviour of badgers, and this has possible implications for the transmission of M. bovis to cattle. Bait-marking data provide no support for the suggestion that illegal culling in experimental control areas might explain why the incidence of cattle TB is lower in these areas than in nearby areas subjected to localized badger culling. The data do, however, indicate that badgers in and around areas subject to culling range more widely than those in undisturbed populations, potentially increasing their contact rates both with cattle and other badgers. This is consistent with the observation that culling strategies that remove only a small proportion of local badger populations, such as the ‘interim strategy’ that operated from 1986 to 1998, and the reactive culling treatment of the RBCT, appear either ineffective or counter-productive (Krebs et al. 1997; Donnelly et al. 2003; Le Fevre et al. 2005). These findings may help to design more effective management policies, and should be taken into account in determining what role badger culling should play in future strategies to control cattle TB.