Identifying priority conservation areas for a recovering brown bear population in Greece using citizen science data

Abstract

Understanding the processes related to wildlife recoveries is not only essential in solving humanwildlife conflicts, but also for identifying priority conservation areas and in turn, for effective conservation planning. We used data from a citizen science program to study spatial aspects of the demographic and genetic recovery of brown bears in Greece and to identify new areas for their conservation. We visually compared our data with an estimation of the past distribution of brown bears in Greece and used a point process approach to model habitat suitability. We then compared 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 spatial aspects of population recovery. It will help prioritize conservation actions for brown bears in Greece and may serve as a model conservation approach to countries facing similar financial and logistic constraints in the monitoring of local biodiversity or facing challenges in managing rapid population recoveries. Our conservation approach appeared to be particularly suited to identifying priority areas for conservation in areas with recovering wildlife populations and may therefore be used as an 'early-warning' conservation system.

Ecological consequences of human depopulation of rural areas on wildlife: A unifying perspective

“…Most impacts are now caused indirectly via the development of the communication and energy supply infrastructure (Martínez-Abraín et al, 2009, but wildlife does not perceive that additive mortality such as direct predation by humans. The process of "refuge abandonment" will most likely force the development of new conservation policies (Martínez-Abraín et al, 2019b), and will increase the demand for improved maps of habitat suitability in relation to currently "empty" sites (Bonnet-LeBrun et al, 2019). This means that many presently unused, high-quality sites will become occupied in the future, as currently occupied sites are abandoned.…”

Reduced movement of wildlife in Mediterranean landscapes: a case study of brown bears in Greece

“…Bear habitat in Greece has been undergoing during the last decades a progressive rewilding as a consequence of rural abandonment. In addition, since the early 2000s encouraging signs of bear recovery have been recorded in the country, including an increase in population size (Karamanlidis et al , ), a range expansion (Bonnet Lebrun et al, ) and a genetic recovery (Karamanlidis et al , ). At the same time, human–bear conflicts have also been increasing (Karamanlidis et al , ), creating an urgent need for understanding this recovery and developing new, effective management and conservation measures that will safeguard the future of this bear population.…”

Uniform performance of mammal detection methods under contrasting environmental conditions in Mediterranean landscapes

“…Monitoring local occupancy and the regional distribution of wild mammals is essential to guide species management (Sarre et al 2012) and set conservation priorities (Kong et al 2017). Accurate knowledge of species occurrence (Thorn et al 2011, McCarthy et al 2015), together with methodological approaches that predict species response to fast drivers of global change (Araújo et al 2019, La Marca et al 2019), is fundamental to identify conservation priority areas (Bonnet‐Lebrun et al 2020). Monitoring programmes should quickly collect reliable data over large areas to produce successive distribution snapshots which require cost‐effective detection methods (Thorn et al 2010, Parry and Peres 2015).…”