• End-user involvement to improve predictions and management of populations with complex dynamics and multiple drivers 

      Henden, John-André; Ims, Rolf Anker; Yoccoz, Nigel; Asbjørnsen, Einar Johannes; Stien, Audun; Mellard, Jarad Pope; Tveraa, Torkild; Marolla, Filippo; Jepsen, Jane Uhd (Peer reviewed; Journal article, 2020)
      Sustainable management of wildlife populations can be aided by building models that both identify current drivers of natural dynamics and provide near-term predictions of future states. We employed a Strategic Foresight ...
    • Harvest models of small populations of a large carnivore using Bayesian forecasting 

      Andrén, Henrik; Hobbs, N. Thompson; Aronsson, Malin; Brøseth, Henrik; Chapron, Guillaume; Linnell, John Durrus; Odden, John; Persson, Jens; Nilssen, Erlend B. (Peer reviewed; Journal article, 2019)
      Harvesting large carnivores can be a management tool for meeting politically set goals for their desired abundance. However, harvesting carnivores creates its own set of conflicts in both society and among conservation ...
    • Predicting kill sites of an apex predator from GPS data in different multi-prey systems 

      Oliveira, Teresa; Sanchez, David Carricondo; Mattisson, Jenny; Vogt, Kristina; Corradini, Andrea; Linnell, John Durrus; Odden, John; Heurich, Marco Dietmar; Rodríguez-Recio, Mariano; Krofel, Miha (Peer reviewed; Journal article, 2022)
      Kill rates are a central parameter to assess the impact of predation on prey species. An accurate estimation of kill rates requires a correct identification of kill sites, often achieved by field-checking GPS location ...
    • Rangifer management controls a climate-sensitive tundra state transition 

      Bråthen, Kari Anne; Ravolainen, Virve Tuulia; Stien, Audun; Tveraa, Torkild; Ims, Rolf Anker (Journal article; Peer reviewed, 2017)
      Rangifer (caribou/reindeer) management has been suggested to mitigate the temperature- driven transition of Arctic tundra into a shrubland state, yet how this happens is uncertain. Here we study this much focused ecosystem ...