Translocation is a critical tool for wildlife management, but animals are most vulnerable immediately after release, making the timing of settlement and the factors influencing it key to improving outcomes. Methods for detecting settlement and evaluating resource selection vary widely, creating uncertainty about best practices. To address this, we evaluated seasonally corrected and uncorrected location data for predicting settlement, compared resource selection between seasonally and non-seasonally aligned controls, and applied a unified framework to bighorn sheep ( Ovis canadensis ) GPS data to identify settlement and assess changes in resource selection. In February 2015, we translocated 26 bighorn sheep (24 F, 2 M) from Alberta, Canada, to the Deadwood ecoregion, South Dakota, USA. We used a changepoint detection method to identify settlement in movement indices and applied resource selection functions (RSFs) and integrated step selection analyses (iSSAs) to assess selection at the range and step scales. Predicted settlement times did not differ between seasonally corrected and uncorrected datasets (Kruskal–Wallis χ 2 = 0.08, P = 0.77), though some discrepancies occurred. The longest settlement times coincided with the lambing season (∼33% of individuals), suggesting the lambing season may initiate settlement, thereby shortening the exploration period and mitigating risk. We observed minor differences between controls at the range scale and negligible differences at the step scale. Comparing the impact period to seasonally aligned controls using multi-scale resource selection analyses provided deeper insight into post-release behavior. We recommend routine use of seasonally aligned controls and standardized terminology to improve clarity and consistency across translocation studies. • Seasonally aligned controls account for potential confounding seasonal variation. • Multi-scale selection analyses yielded broader insights. • Lambing season may prompt settlement in reintroduced female bighorn sheep. • Bighorn sheep may reduce risk at the step when traversing risky areas. • We recommend adopting standardized terminology presented within this manuscript.
Stewart et al. (Thu,) studied this question.