Since 2014, the Norwegian Institute for Nature Research has studied the migration patterns of sea trout in multiple catchments. Sea trout are marked with a PIT (passively integrated transponders) tags that record their movements out to sea and back to freshwater when they pass underwater antennas at river mouths. During their marine migrations, sea trout need to find food to maximize their growth, while also being exposed to multiple threats from parasites (e.g. salmon lice), predation (e.g. birds, large fish, marine mammals) and marine fishing. For many catchments, this results in only 25-40% of sea trout returning to freshwater each year.

Read more on the page "Gytebestander av laks og sjøørret" (in Norwegian)

Norway has several thousand sea trout populations, which are all influenced by human activity to some extent. As sea trout display several alternative life history strategies, and occupy a range of habitats with large natural fluctuations, it is not possible to collect information on critical life phases for every sea trout population. Here, a model-based approach provides the best solution for assessing population-level responses of sea trout to environmental changes and management actions. Our individual-based dynamic model for sea trout populations (IBTRUTTA; Hedger et al. 2021) provides realistic assessments of population-level responses to:

• consequences of reduced time and growth in the sea. For a given population, we can quantify changes in population size and distributions, and their reproductive potential under different levels of salmon lice pressure (Hedger et al. 2021; Diserud et al. 2020). 
• population-specific conservation goals. Spawning stock targets can be developed based on stock-recruitment relationships. 
• long-term effects of different management and harvesting strategies. 
• importance of smolt population characteristics for survival and growth (e.g. size, timing of emigration; Jensen et al. 2020). 

In order to build population-specific models, we examine life history parameters critical to population dynamics, and assess how they vary between population types, and in response to different human activities. Our long-term sea trout time-series, and national and international collaborations with other sea trout researchers are integral to our modelling activities. For instance, in conjunction with ICES working group WGTRUTTA, we coordinate data collection, fit stock-recruitment models over a large geographical and environmental scale, and quantify impacts on European sea trout populations. 

Hedger R, Diserud OH, Finstad B, Jensen AJ, Hendrichsen DK, Ugedal O, & Næsje TF. (2021). Modeling salmon lice effects on sea trout (Salmo trutta L.) population dynamics using an individual-based approach. Aquaculture Environment Interactions 13: 145-163 https://doi.org/10.3354/aei00397 

Diserud OH, Hedger R, Finstad B, Hendrichsen D, Jensen AJ, & Ugedal O. (2020). Salmon louse infestation in wild brown trout populations generates multi-modal mixture distributions. Aquaculture Environment Interactions 12:447-456. https://doi.org/10.3354/aei00374

Jensen AJ, Finstad B, Fiske P, Diserud OH, & Thorstad EB. (2020). Repeatable individual variation in migration timing in two anadromous salmonids and ecological consequences. Ecology & Evolution 10:11727–11738. https://doi.org/10.1002/ece3.6808