The conservation of large carnivores is a formidable challenge for biodiversity conservation. Using a data set on the past and current status of brown bears (Ursus arctos), Eurasian lynx (Lynx lynx), gray wolves (Canis lupus), and wolverines (Gulo gulo) in European countries, we show that roughly one-third of mainland Europe hosts at least one large carnivore species, with stable or increasing abundance in most cases in 21st-century records. The reasons for this overall conservation success include protective legislation, supportive public opinion, and a variety of practices making coexistence between large carnivores and people possible. The European situation reveals that large carnivores and people can share the same landscape.

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Inferring the distribution and abundance of a species from field records must deal with false-negative and false-positive errors. False-negative errors occur if a species present goes undetected, while false-positive errors are typically a consequence of species misidentification. False-positive observations in studies of rare species may cause an overestimation of the distribution or abundance of the species and distort trend indices. We illustrate this issue with the monitoring of the Eurasian lynx in the Alps. We developed a three-level classification of field records according to their reliability as inferred from whether they were validated or not. The first category (C1) represents 'hard fact' data (e.g. dead lynx); the second category (C2) includes confirmed data (e.g. tracks verified by an expert); and the third category (C3) are unconfirmed data (e.g. any kind of direct visual observation). For lynx, which is a comparatively well-known species in the Alps, we use site-occupancy modelling to estimate its distribution and show that the inferred lynx distribution is highly sensitive to presence sign category: it is larger if based on C3 records compared with the more reliable C1 and C2 records. We believe that the reason for this is a fairly high frequency of false-positive errors among C3 records. This suggests that distribution records for many lesser-known species may be similarly unreliable, because they are mostly or exclusively based on unconfirmed and thus soft data. Nevertheless, such soft data form a considerable part of species assessments as presented, for example in the International Union for Conservation of Nature Red List. However, C3 records can often not be discarded because they may be the only information available. When inferring the distribution of rare carnivores, especially for species with an expanding or shrinking range, we recommend a rigorous discrimination between fully reliable and unor only partly reliable data, in order to identify possible methodological problems in the distribution maps related to false-positive records. A. Molinari-Jobin et al. Monitoring in the presence of possible species misidentification Animal Conservation 15 (2012) 266-273 A. Molinari-Jobin et al. Monitoring in the presence of possible species misidentification Animal Conservation 15 (2012) 266-273

Analysis of global positioning system (GPS) location clusters (GLCs) is becoming increasingly popular in studies of carnivore ecology. While promising, this application of GPS technology is still poorly developed for most species. We applied this method to study predation and maternal behavior of the Eurasian lynx (Lynx lynx) in Dinaric Mountains. Low population densities, rugged terrain, dense vegetation, and administrative borders make studies of this endangered population using traditional methods and a limited budget very challenging. We used geographic information system (GIS) and linear mixed effects models to understand the movement of lynx during the consumption process and denning period and estimate lynx kill rates. 99% of kills were found at GLCs longer than 30 h and with minimum two locations within 300 m. We confirmed 86% of potential kills and all potential dens that were searched for in the field. High success in predicting kill and den sites showed that Eurasian lynx is a suitable species for application of the GLC analysis methods. Comparison of field-confirmed kills with model predictions showed the possibility for remote estimation of approximate kill 2 rates in Eurasian lynx. Movements of lynx were primarily affected by daytime period, time since the last kill/den translocation, lynx category and their interactions. Based on the empirical data we programmed simulations of lynx movements and elaborated recommendations for more efficient field procedures and study designs (GPS schedules) for future studies. We believe that our findings and approach will also benefit studies of other species with similar behavior.