Visualizing the risk landscape to adaptively increase post-release survival of translocated Galliformes

Abstract

Translocation of captive-bred animals is a widely used conservation strategy to support the recovery of imperiled wild populations. Identifying which factors enhance or limit survival after release can be important in adapting translocation strategies, particularly for species with low survival rates after release from captivity. Many translocation programs track post-translocation survival, but few complete spatial-statistical assessments of mortality risk associated with release environments. Typically, few animals are released from captive breeding programs, limiting the sample size available for analyses. We aimed to create a workflow that used limited datasets to evaluate the influence of spatial conditions and other factors on mortality risk. Greater sage-grouse (Centrocercus urophasianus) are endangered in Canada and of conservation concern throughout their range in the United States. After the species declined precipitously in Canada, a captive breeding program was initiated with subsequent releases in Alberta and Saskatchewan. Despite success in captive breeding, mortality rates of released sage-grouse were high. We used GPS- and VHF-based locations of released sage-grouse to determine how spatial features influence mortality risk of sage-grouse after release from captivity. We implemented a multistep approach to quantify and map risk relative to the environmental features associated with mortality. We also assessed whether the movement behaviors of sage-grouse correspond with environmental risk factors by using a combination of survival models and integrated step-selection functions. Mortality of sage-grouse in Alberta was hastened in areas close to anthropogenic disturbance. Although birds in Alberta avoided areas of higher mortality risk, those in Saskatchewan did not, perhaps due to environmental and selection constraints. This multistep approach allowed us to utilize small sample sizes to assess key risk factors in the landscape. This process supports the adaptive modification of translocation plans and can similarly support other data-limited scientists and managers in assessing environmental mortality risk and defining conservation actions for endangered species.