A standardized approach to empirically define reliable assignment thresholds and appropriate management categories in deeply introgressed populations.

Anthropogenic hybridization is recognized as a major threat to the long-term survival of natural populations. While identifying F1 hybrids might be simple, the detection of older admixed individuals is far from trivial and it is still debated whether they should be targets of management. Examples of anthropogenic hybridization have been described between wolves and domestic dogs, with numerous cases detected in the Italian wolf population. After selecting appropriate wild and domestic reference populations, we used empirical and simulated 39-autosomal microsatellite genotypes, Bayesian assignment and performance analyses to develop a workflow to detect different levels of wolf x dog admixture. Membership proportions to the wild cluster (q) and performance indexes identified two q-thresholds which allowed to efficiently classify the analysed genotypes into three assignment classes: pure (with no or negligible domestic ancestry), older admixed (with a marginal domestic ancestry) and recent admixed (with a clearly detectable domestic ancestry) animals. Based on their potential to spread domestic variants, such classes were used to define three corresponding management categories: operational pure, introgressed and operational hybrid individuals. Our multiple-criteria approach can help wildlife managers and decision makers in more efficiently targeting the available resources for the long-term conservation of species threatened by anthropogenic hybridization.