Detecting Wildlife Poaching: Identifying the Origin of Individuals with Bayesian Assignment Tests and Multilocus Genotypes

Abstract: Illegal harvesting is a serious threat to the persistence of many plant and animal taxa. The combination of highly polymorphic DNA markers and new statistical methods called “assignment tests” can potentially help detect and thereby reduce poaching. Assignment tests can identify the population of origin of individuals if populations are genetically differentiated. We evaluated the usefulness of two assignment tests to wildlife forensics by applying them to large empirical (microsatellite DNA) data sets from 10 species. We also conducted computer simulations to assess the influence of genetic polymorphism ( heterozygosity) and population differentiation (   FST ) on the performance of the tests. The fully Bayesian assignment test of Pritchard et al. (2000) performed better than the partially Bayesian exclusion test of Cornuet et al. (1999) , but the fully Bayesian method requires the assumption that the true population of origin was sampled. The median percentage of individuals correctly assigned for the 10 empirical data sets was 61% and 36% for the assignment and exclusion tests, respectively. Both the empirical and simulated data sets suggest that nearly all individuals can be assigned with high statistical certainty (99.9%) for two highly differentiated populations (    FST≈ 0.15–0.2) when 10 loci (  H> 0.6) and samples of 30–50 individuals are used per population. We recommend using both tests when the true population of origin might not have been sampled in the data set.

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