Abstract

Assessing which females have bred successfully is a central requirement in many ecological field studies, providing an estimate of the effective female population size. Researchers have applied teat measurements previously to assess whether females, in a variety of mammalian species, have bred; however, this technique has not been validated genetically. Furthermore, several analytical techniques are available to classify individuals, but their misclassification rates have not been compared. We used 22 microsatellite loci to assign maternity, with 95% confidence, within a high-density population of European badgers Meles meles, as plural and subterranean breeding means that maternity cannot be inferred from behavioural observations. The teat lengths and diameters of 136 females, measured May–July 1994–2005, from social groups in which all offspring were assigned a mother, were reliable indicators of recent breeding success. A Generalised Linear Mixed Model (GLMM) classified both breeding and non-breeding females with lower error rates than discriminant analyses and crude teat-size criteria. The GLMM model logit probability = −20 + 1.8 month + 1.6 mean teat length + 1.0 mean teat diameter can be applied quickly in the field to assess the probability with which a female badger should be assigned maternity. This is a low-cost measure which, after validation, could be used in other badger or mammalian populations to assess the breeding success of females. This may be a particularly useful welfare tool for veterinary practitioners, especially during badger culls.

Full Text
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