| Summary: | Background The Scandinavian wolf (Canis lupus) population is being monitored annually using non-invasive genetic sampling (NGS) and recovery of dead individuals. DNA extracted from faeces, urine, hair, and tissue is used to identify the species, sex, and individual from which each sample originated. These data have been compiled in the Scandinavian large carnivore database Rovbase 3.0 (www.rovbase.se). Approach Using the Bayesian open-population spatial capture-recapture (OPSCR) model developed by RovQuant (Bischof et al., 2019b, 2020), we estimated annual density and vital rates of the Scandinavian wolf population for nine seasons from 2012/13 to 2020/21. The OPSCR model accounts for individual movements, as well as imperfect and variable detection. Results The OPSCR model yielded annual density maps and both total and jurisdiction-specific population sizes for wolves from 2012/13 to 2020/21. The estimated number of wolves for October 1, 2020 (start of the 2020/21 monitoring season) was 460 individuals (CrI: 439 - 483), of which 371 (CrI: 351-392) were located in Sweden and 89 (CrI: 80-99) in Norway. In addition to annual density and jurisdiction-specific abundance estimates, we report estimates of survival, recruitment, and detection probabilities. Bakgrunn Den skandinaviske bestanden av ulv (Canis lupus) blir overvåket årlig ved bruk av ikke-invasiv genetisk prøveinnsamling (NGS) og gjenfunn av døde individer. DNA ekstrahert fra skit, urin, hår og vev brukes til å identifisere art, kjønn og individ for hver enkelt prøve. Denne informasjonen samles og ivaretas i den skandinaviske databasen for store rovdyr; Rovbase 3.0 (www.rovbase.se). Tilnærming Ved bruk av en Bayesiansk åpen romlig fangst-gjenfangst populasjons modell (OPSCR), utviklet av RovQuant (Bischof et al., 2019b, 2020), estimerte vi årlige tettheter og demografiske rater hos den skandinaviske ulvebestanden i ni sesonger fra 2012/13 til 2020/21. OPSCR modellen tar høyde for individers forflytninger, samt variabel oppdagbarhet. Resultater OPSCR ...
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