Identifying priority conservation areas for recovering large carnivores using citizen science data

Understanding the processes related to wildlife recoveries is not only essential in solving human - wildlife conflicts, but also for identifying priority conservation areas and in turn, for effective conservation planning. We used data from a large citizen science program to study the spatial processes related to the demographic and genetic recovery of brown bears in Greece and to identify new areas for their conservation. This was achieved by visually comparing our data with an estimation of the past distribution of brown bears in Greece and by using a Point Process Model to model habitat suitability, and then comparing our results with the current distribution of brown bear records and with that of protected areas. Our results indicate that in the last 15 years bears may have increased their range by as much as 100%, by occupying mainly anthropogenic landscapes and areas with suitable habitat that are currently not legally protected, thus creating a new conservation reality for the species in Greece. This development dictates the re-evaluation of the national management and conservation priorities for brown bears in Greece by focusing in establishing new protected areas that will safeguard their recovery. Our conservation approach is a swift and cheap way of identifying priority conservation areas, while gaining important insights on the spatial processes associated with population recoveries. It will help prioritize conservation actions for brown bears in Greece and may serve as a model conservation approach to countries facing financial and logistic constraints in the monitoring of local biodiversity or facing challenges in managing rapid population recoveries. Our conservation approach appeared also to be better suited to identifying priority areas for conservation in areas with recovering wildlife populations and may therefore be used as an \"early-warning\" conservation system.