Bradley, D. W., Molles, L. E., & Waas, J. R. (2013). Post-translocation assortative pairing and social implications for the conservation of an endangered songbird. Animal Conservation, published online 15 October 2013.
Permanent Research Commons link: http://hdl.handle.net/10289/8097
Animals translocated for conservation purposes may be sourced from multiple locations which may exhibit inter-site variability in reproductive behaviours. The influence that these differences may have on the propensity of pair formation, and the ultimate impact this may have on the success of the translocation, is unknown due to the low sample sizes of many translocations. We address this knowledge gap by collating an existing 18-year data set documenting multisource translocations of the endangered North Island Kōkako, Callaeas wilsoni, a duetting New Zealand species with known population-specific vocalizations. We found a strong, statistically significant tendency for Kōkako to pair assortatively with respect to source population (like with like) following release. Population-specific differences in sexually selected behaviours that are important in mate choice decisions, such as bird song, are likely the proximate explanation for such reproductive decisions. Accounting for the tendency to pair assortatively following translocation may be particularly important when managing highly vocal animals like Kōkako that produce vocal duets and cooperatively defend territories as mated pairs. Consequently, careful consideration of behavioural variation between translocated individuals should be made, which will appropriately inform decisions relating to release-cohort composition. Failure to consider such variation may negatively impact the success of a translocation as the effective population size of the founder group may be lower than intended. Our findings make an important contribution towards understanding the impact that behavioural variation can have on the conservation of endangered species, and highlight the value of combining long-term data from multiple sources.