Movement ecology and conservation : the case of African vultures

The movements of critically endangered vultures, equipped with satellite-based tracking devices in Namibia, were inspected using Generalized Additive Models. Models incorporated spatially adaptive (1D and 2D) smooths via the Spatially Adaptive Local Smoothing Algorithm (SALSA) and Complex REgion Spatial Smoother (CReSS) method. The correlated nature of geo-location data was address via robust standard errors. The results of this thorough and integrative study of movement ecology have an unprecedented level of detail, far exceeding what is available in the literature. Namely, vultures were seen throughout Namibia and its five neighbouring countries with three individuals visiting locations farther than 1,000 km from where they were initially seen. Large variability was found both within and between birds. Differences were perceived in four daily movement properties, even though temporal differences were only captured for daily distance travelled (monthly) and daily maximum displacement (seasonally). There was noticeable variation in the size of the areas each bird used from month to month, often showing very little spatial overlap. Home ranges varied greatly; one bird expanded its monthly home range as much as nineteen times its smaller size. Contrastingly, core areas remained sometimes constant. Home ranges were three to five times larger than the respective core areas, clearly indicating a non-uniform use of the environment. The extensive study area (2.3 million sq.km) was characterised using habitat features, climate conditions and indices of human presence. Vegetation index, minimum distance to river and minimum distance to road were consistently important in explaining the probability of bird presence. Nonetheless, each vulture used its environment in its own way. These novel findings support trans-frontier conservation measures, represent crucial support to revise the geographic extent of existing conservation actions and constitute the basis to predict the risk of exposure of vultures to lethal threats or to assess changes under Climate Change scenarios."This work was supported by the Fundação para a Ciência e Tecnologia (Portugal) [grant number PD/BD/113551/2015] and the European Social Fund under the III European Community Support Framework.