Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2025
Authors
Ramūnas Digaitis Greeley Beck Sune Tjalfe Thomsen Maria Fredriksson Emil Engelund ThybringAbstract
No abstract has been registered
Authors
Lathika Y. Hitige Rashmi N.J.K. Arachchi Nimal Ratnayake Miyuru Gunathilake Upaka RathnayakeAbstract
No abstract has been registered
Authors
Udara Senatilleke Ravindu Panditharathne Ruchiru D. Herath Dushyantha M. Aththanayake Randika K. Makubura Sajana Hemakumara Miyuru Gunathilake Hazi Md. Azamathulla Komali Kantamaneni Upaka RathnayakeAbstract
No abstract has been registered
Abstract
Reliable estimates of the size and composition of harvested populations over time are key to designing adequate population management plans, regardless of management objectives. In Norway, a national system for collecting and analysing hunter-reported data on red deer (Cervus elaphus) has been operational for about 20 years. The system was expected to provide population metrics that would substantially improve deer population management routines at the municipal level. This has proven to be challenging when using existing state-of-the-art estimation methodology. The main reasons are that the variation in the observation data is generally much larger than population abundance variability, and that one does not have a clear understanding of the stochastic process generating the observation data. Here, using hunter-reported observation data and harvest data from six Norwegian municipalities collected in the period 2007–2023, we show that a straightforward estimation methodology based on population modelling can produce robust abundance estimates despite frequent low quality of the observation data. Its major assets are that it does not involve strong assumptions about the stochastic processes underlying the observation process and that it does not involve assumptions about initial population size and structure in terms of prior statistical distributions. We anticipate that the method can be applied in several other population management contexts, and we think that the results offer fresh perspectives on to what extent noisy citizen-collected time series data can be used to inform management decisions.
Authors
Mohammad Tirgariseraji A. Pouyan Nejadhashemi Mahmood Sabouhi Sabouni Yaghoob Jafari Tomas Persson Alisher Mirzabaev Alireza Nikouei Kieron Moller Naser Shahnoushi ForoushaniAbstract
No abstract has been registered
Authors
Linn Fenna Groeneveld Oksana Bekkevold Trond Bergskås Martin Linkogel Cord Luellmann Marit AlmvikAbstract
No abstract has been registered
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Authors
Junbin Zhao Simon Weldon Alexandra Barthelmes Erin Swails Kristell Hergoualc’h Ülo Mander Chunjing Qiu John Connolly Whendee L. Silver David I. CampbellAbstract
No abstract has been registered
Abstract
No abstract has been registered