Summary 1.Spatially explicit Bayesian clustering techniques offer a powerful tool for ecology and wildlife management, as genetic divisions can be correlated with landscape features. We used these methods to analyse the genetic structure of a population of European wild boar Sus scrofa with the aim of identifying effective barriers for disease management units. However, it has been suggested that the methods could produce biased results when faced with deviations from random mating not caused by genetic discontinuities, such as isolation by distance (IBD). 2. We analysed a data set consisting of 697 wild boar multilocus genotypes using spatially explicit ( baps, geneland ) and non-explicit ( structure ) Bayesian methods. We also simulated and analysed data sets characterized by different degrees of IBD, with and without genetic discontinuities. 3. When analysing the empirical data set, different programs did not converge on the same clustering solution and some clusters were difficult to explain biologically. Results from the simulated data showed that IBD, also present in the empirical data set, could cause the Bayesian methods to overestimate genetic structure. Simulated barriers were identified correctly, but the programs superimposed further clusters at higher IBD levels. 4. It was not possible to ascertain with confidence whether the clustering solutions offered by the various programs were an accurate reflection of population genetic structure in our empirical data set or were artefacts created by the underlying IBD pattern. 5. Synthesis and applications : We show that Bayesian clustering methods can overestimate genetic structure when analysing an individual-based data set characterized by isolation by distance. This bias could lead to the erroneous delimitation of management or conservation units. Investigators should be critical and suspicious of clusters that cannot be explained biologically. Data sets should be tested for isolation by distance and conclusions should not be based on the output from just one method.

The joint analysis of spatial and genetic data is rapidly becoming the norm in population genetics. More and more studies explicitly describe and quantify the spatial organization of genetic variation and try to relate it to underlying ecological processes. As it has become increasingly difficult to keep abreast with the latest methodological developments, we review the statistical toolbox available to analyse population genetic data in a spatially explicit framework. We mostly focus on statistical concepts but also discuss practical aspects of the analytical methods, highlighting not only the potential of various approaches but also methodological pitfalls.

The potential link between badgers and bovine tuberculosis has made it vital to develop accurate techniques to census badgers. Here we investigate the potential of using genetic profiles obtained from faecal DNA as a basis for population size estimation. After trialling several methods we obtained a high amplification success rate (89%) by storing faeces in 70% ethanol and using the guanidine thiocyanate / silica method for extraction. Using 70% ethanol as a storage agent had the advantage of it being an antiseptic. In order to obtain reliable genotypes with fewer amplification reactions than the standard multiple-tubes approach, we devised a comparative approach in which genetic profiles were compared and replication directed at similar, but not identical, genotypes. This modified method achieved a reduction in polymerase chain reactions comparable with the maximumlikelihood model when just using reliability criteria, and was slightly better when using reliability criteria with the additional proviso that alleles must be observed twice to be considered reliable. Our comparative approach would be best suited for studies that include multiple faeces from each individual. We utilized our approach in a well-studied population of badgers from which individuals had been sampled and reliable genotypes obtained. In a study of 53 faeces sampled from three social groups over 10 days, we found that direct enumeration could not be used to estimate population size, but that the application of mark-recapture models has the potential to provide more accurate results.

In many European countries, the wild boar (Sus scrofa) is often associated with crop damage. In this study, we analyse data relating to 13,276 cases of wild boar damage to agricultural crops over a 10-year period in Luxembourg (an area of 2,586 km 2 in Western Europe). Results show that (1) damage is more severe in this area than in others; (2) damage to permanent grassland is far more frequent and more severe than damage to annual crops; (3) trichomatous crops such as barley are avoided; (4) damage is seasonally distributed according to type of crop; (5) damage is distributed spatially in a non-uniform manner; (6) damage intensity is significantly correlated with wild boar hunting bags, both over time and space. We suggest that wild boar management strategy should always take into account the issue of damage to agricultural crops. Our results imply that measures for preventing or reducing damage should be more targeted in time and space and that adjustments to cropping patterns should contribute towards a reduction of wild boar damage.

While motorways are often assumed to influence the movement behaviour of large mammals, there are surprisingly few studies that show an influence of these linear structures on the genetic make-up of wild ungulate populations. Here, we analyse the spatial genetic structure of red deer (Cervus elaphus) and wild boars (Sus scrofa) along a stretch of motorway in the Walloon part of Belgium. Altogether, 876 red deer were genotyped at 13 microsatellite loci, and 325 wild boars at 14 loci. In the case of the red deer, different genetic clustering tools identified two genetic subpopulations whose borders matched the motorway well. Conversely, no genetic structure was identified in the case of the wild boar. Analysis of isolation-by-distance patterns of pairs of individuals on the same side and on different sides of the motorway also suggested that the road was a barrier to red deer, but not to wild boar movement. While telemetry studies seem to confirm that red deer are more affected by motorways than wild boar, the red deer sample size was also much larger than that of the wild boars. We therefore repeated the analysis of genetic structure in the red deer with randomly sub-sampled data sets of decreasing size. The power to detect the genetic structure using clustering methods decreased with decreasing sample size.