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      Guidance on estimation of abundance and density of wild carnivore population:methods, challenges, possibilities

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          Status and ecological effects of the world's largest carnivores.

          Large carnivores face serious threats and are experiencing massive declines in their populations and geographic ranges around the world. We highlight how these threats have affected the conservation status and ecological functioning of the 31 largest mammalian carnivores on Earth. Consistent with theory, empirical studies increasingly show that large carnivores have substantial effects on the structure and function of diverse ecosystems. Significant cascading trophic interactions, mediated by their prey or sympatric mesopredators, arise when some of these carnivores are extirpated from or repatriated to ecosystems. Unexpected effects of trophic cascades on various taxa and processes include changes to bird, mammal, invertebrate, and herpetofauna abundance or richness; subsidies to scavengers; altered disease dynamics; carbon sequestration; modified stream morphology; and crop damage. Promoting tolerance and coexistence with large carnivores is a crucial societal challenge that will ultimately determine the fate of Earth's largest carnivores and all that depends upon them, including humans.
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            Recovery of large carnivores in Europe's modern human-dominated landscapes.

            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. Copyright © 2014, American Association for the Advancement of Science.
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              Spatially explicit maximum likelihood methods for capture-recapture studies.

              Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore straightforward. Additional (nonspatial) variation in capture probability may be modeled as in conventional capture-recapture. The method is tested by simulation, using a model in which capture probability depends only on location relative to traps. Point estimators are found to be unbiased and standard error estimators almost unbiased. The method is used to estimate the density of Red-eyed Vireos (Vireo olivaceus) from mist-netting data from the Patuxent Research Refuge, Maryland, U.S.A. Estimates agree well with those from an existing spatially explicit method based on inverse prediction. A variety of additional spatially explicit models are fitted; these include models with temporal stratification, behavioral response, and heterogeneous animal home ranges.

                Author and article information

                Journal
                EFSA Supporting Publications
                EFS3
                EFSA Supporting Publications
                Wiley
                23978325
                23978325
                November 2020
                November 2020
                : 17
                : 11
                Affiliations
                [1 ]Polish Academy of Sciences Poland
                [2 ]Czech University of Life Sciences, Kamycka 129, 16500
                [3 ]Instituto de Investigación en Recursos Cinegéticos IREC (CSIC‐UCLM-JCCM) Ronda de Toledo s/n, 13005 Ciudad Real Spain
                [4 ]University of Sassari Italy
                [5 ]Polish Academy of Sciences Spain
                [6 ]Instituto de Biología de la Conservación Spain
                [7 ]University of Veterinary Medicine Hannover, Bischofsholer Damm 15, 30173, Hannover Germany
                [8 ]Eberswalde University for Sustainable environment, Alfred‐Möller‐Straße 1, 16225 Eberswalde Germany
                [9 ]Wildlife Management Department, 1797, 10 St. Kl. Ochridski Blvd Sofia Bulgaria
                Article
                10.2903/sp.efsa.2020.EN-1947
                e59ac4b3-5495-4c70-b1a7-cc26911c53b1
                © 2020
                History

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