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

Published on Jul 5, 2019in Animal Conservation3.048
· DOI :10.1111/acv.12522
A.‐S. Bonnet‐Lebrun (University of Montpellier), Alexandros A. Karamanlidis16
Estimated H-index: 16
(NMBU: Norwegian University of Life Sciences)
+ 2 AuthorsOlivier Gimenez41
Estimated H-index: 41
(University of Montpellier)
  • References (38)
  • Citations (0)
📖 Papers frequently viewed together
4 Authors (Luca Santini, ..., Carlo Rondinini)
7 Citations
2 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
#1Alexandros A. Karamanlidis (NMBU: Norwegian University of Life Sciences)H-Index: 16
#2Tomaž Skrbinšek (University of Ljubljana)H-Index: 10
Last. Astrid Vik Stronen (AAU: Aalborg University)H-Index: 13
view all 8 authors...
Understanding the mechanisms and patterns involved in population recoveries is challenging and important in shaping conservation strategies. We used a recovering rear-edge population of brown bears at their southernmost European range in Greece as a case study (2007–2010) to explore the recovery genetics at a species’ distribution edge. We used 17 microsatellite and a mitochondrial markers to evaluate genetic structure, estimate effective population size and genetic diversity, and infer gene flo...
4 CitationsSource
#1Barnabas H. Daru (Harvard University)H-Index: 14
#2Daniel S. Park (Harvard University)H-Index: 14
Last. Charles C. Davis (Harvard University)H-Index: 44
view all 11 authors...
Summary Nonrandom collecting practices may bias conclusions drawn from analyses of herbarium records. Recent efforts to fully digitize and mobilize regional floras online offer a timely opportunity to assess commonalities and differences in herbarium sampling biases. We determined spatial, temporal, trait, phylogenetic, and collector biases in c. 5 million herbarium records, representing three of the most complete digitized floras of the world: Australia (AU), South Africa (SA), and New England,...
54 CitationsSource
#1Antoine Guisan (UNIL: University of Lausanne)H-Index: 72
#2Wilfried Thuiller (CNRS: Centre national de la recherche scientifique)H-Index: 99
Last. Niklaus E. ZimmermannH-Index: 7
view all 3 authors...
77 CitationsSource
#1Carlos Bautista (PAN: Polish Academy of Sciences)H-Index: 1
#2Javier Naves (CSIC: Spanish National Research Council)H-Index: 16
Last. Nuria Selva (PAN: Polish Academy of Sciences)H-Index: 21
view all 23 authors...
Summary Wildlife damage to human property threatens human–wildlife coexistence. Conflicts arising from wildlife damage in intensively managed landscapes often undermine conservation efforts, making damage mitigation and compensation of special concern for wildlife conservation. However, the mechanisms underlying the occurrence of damage and claims at large scales are still poorly understood. Here, we investigated the patterns of damage caused by brown bears Ursus arctos and its ecological and so...
27 CitationsSource
#1Antoine GuisanH-Index: 72
#2Wilfried ThuillerH-Index: 99
Last. Niklaus E. ZimmermannH-Index: 56
view all 3 authors...
90 CitationsSource
#1Jonas Geldmann (Wild Center)H-Index: 15
#2Jacob Heilmann-Clausen (Wild Center)H-Index: 21
Last. Anders P. Tøttrup (Wild Center)H-Index: 28
view all 8 authors...
Aim To understand how the integration of contextual spatial data on land cover and human infrastructure can help reduce spatial bias in sampling effort, and improve the utilization of citizen science-based species recording schemes. By comparing four different citizen science projects, we explore how the sampling design's complexity affects the role of these spatial biases. Location Denmark, Europe. Methods We used a point process model to estimate the effect of land cover and human infrastructu...
31 CitationsSource
#1Enrico Di Minin (UKZN: University of KwaZulu-Natal)H-Index: 19
#2Rob Slotow (UCL: University College London)H-Index: 43
Last. Atte Moilanen (UH: University of Helsinki)H-Index: 56
view all 9 authors...
Mammalian carnivores have suffered the biggest range contraction among all biodiversity and are particularly vulnerable to habitat loss and fragmentation. Therefore, we identified priority areas for the conservation of mammalian carnivores, while accounting for species-specific requirements for connectivity and expected agricultural and urban expansion. While prioritizing for carnivores only, we were also able to test their effectiveness as surrogates for 23,110 species of amphibians, birds, mam...
58 CitationsSource
#1Nefta-Eleftheria P. Votsi (A.U.Th.: Aristotle University of Thessaloniki)H-Index: 4
#2Maria Zomeni (Open University of Cyprus)H-Index: 4
Last. John D. Pantis (A.U.Th.: Aristotle University of Thessaloniki)H-Index: 29
view all 3 authors...
The wolf (Canis lupus) is used as a case study to rate Natura 2000 sites in Greece based on preferred wolf habitat characteristics and test whether the network is suitable for their conservation. Road density, agricultural area, site area, connectivity, food availability (i.e., presence of natural prey), and elevation in 237 sites are combined in a logistic regression model. The occurrence of the wolf’s natural prey was the most prevalent factor determining wolf presence, followed by agricultura...
12 CitationsSource
#1Alexandros A. Karamanlidis (NMBU: Norwegian University of Life Sciences)H-Index: 16
Last. Olivier Gimenez (University of Montpellier)H-Index: 41
view all 4 authors...
Abstract Reliable population and density estimates are the cornerstone of effective conservation and management planning, as conservation priorities often arise in relation to population numbers. Despite increased public interest and costly conservation programs limited information on brown bear (Ursus arctos, Linnaeus, 1758) abundance and density in Greece exists. We carried out systematic non-invasive genetic sampling using hair traps on power poles, as part of a capture-mark-recapture study d...
16 CitationsSource
Analyzing wildlife tracking data frequently involves the estimation of home ranges. However, home range studies frequently lack important analytical steps, or only insufficiently report results. This makes it difficult for other researchers to evaluate, compare, and reproduce results from published home-range studies. To facilitate more thorough home-range analyses and reporting of analytical details, we developed a package for the statistical software package R that offers a user-friendly platf...
41 CitationsSource
Cited By0