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Monitoring post‐release dispersal of reintroduced wildlife informs management strategies to improve outcomes. In previous Swift fox (Vulpes velox) reintroductions, post‐release movements corresponded with survival and have been a metric for success of release strategies, but settlement patterns and resource selection by individuals from different source locations have not been compared. We fit piecewise regression models and resource selection functions to Global Positioning System collar data from Swift fox translocated to the Fort Belknap Reservation from Colorado and Wyoming. We found that 76% of studied Swift fox settled, most within 20 km of their release site. Contrary to our predictions, rates of settlement, distance and time to settlement, and resource selection did not differ by cohort or release strategy. Where Swift fox settled, we observed consistent selection of areas with high percentage cover by grass, low terrain ruggedness, intermediate clay soil content, and high Black‐tailed prairie dog suitability. Collectively, our study suggests that Swift fox are adaptable to a range of conditions within grassland ecosystems when high quality habitat is available and when pre‐release husbandry protocols are followed. However, we observed variability in post‐release behavior unexplained by the factors we assessed, possibly attributable to individual personality differences that are well documented in small canids. Swift fox are the most intensively reintroduced canid in the world, and our study highlights how science‐based advances in reintroduction practices can enhance success over time. These advances are particularly effective on Indigenous Peoples' Land, where high ecological and social suitability is present for large‐scale restoration initiatives. 

Abstract Accurately quantifying species’ area requirements is a prerequisite for effective area‐based conservation. This typically involves collecting tracking data on species of interest and then conducting home‐range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home‐range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross‐validation to quantify bias in empirical home‐range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation‐induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home‐range estimates. As a correction, we tested whether data thinning or autocorrelation‐informed home‐range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation‐informed home‐range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.