Over the years, we have at CEES developed annual matrix models (Caswell, 2001) for 11 stocks (3 Atlantic cod Gadus morhua (from 1946-), 1 herring (1950-), 1 Capelin Mallotus villosus (1974-), 1 NEA haddock (1950-), 2 Alaska pollock Gadus chalcogrammus (1961-), 3 European hake Merluccius merluccius (1978-), and 1 Polar cod Boreogadus saida (1946-) (Durant et al., 2013; Durant and Hjermann, 2017)). Using these matrices we have explored the effect of fishing, age structure and climate of fish population.
Here we will focus on the Northeast Arctic cod in the Barents Sea (“Skrei”). The catch of cod in 2020 was estimated to be ca 738 204 tonnes making it the largest Atlantic cod fishery in the world (ICES, 2021). The Northeast Arctic cod is co-managed by Norway and Russia (Jakobsen and Ozhigin, 2011). Cod currently matures at ten years of age (Ottersen and Holt, 2022) and migrates out of the Barents Sea to spawn along the Norwegian coast around the Lofoten from March to May (Jakobsen and Ozhigin, 2011). Eggs and larvae are carried by currents into the southern Barents Sea and south and west of Svalbard where the larvae settle towards the bottom at the age of approximately five months (Durant et al., 2021).
For this Master thesis, we will specifically calculate the annual transient realized population growth rate (the logarithm of the first eigenvector of the annual matrix)(Koons et al., 2005) on the Northeast Artic cod data. The resulting population growths will then be used as dependent variables in statistical models to explore the effect of a different variables (Fishery mortality, Sea Temperature, Ice coverage, population structure, Capelin Mallotus villosus abundance…). Eventually, we will run scenarios by modifying the fishing pressure (by changing S, see Fig. 1), the reproductive success (by changing R), and/or the population structure (e.g., by changing the maturation age thus R) and subsequently conduct a generalized analysis using e.g. mixed effect models (Durant et al., 2013; Durant and Hjermann, 2017).
To sum up, we would like to redo and improve some of the analyses of (Durant et al., 2013; Durant and Hjermann, 2017).
Objectives of the Master thesis:
"The effect of Age-structure, harvesting and climate effects on population growth of Northeast Arctic cod in the Barents Sea."
What we know:
We have a lot of information on the biology, change of population dynamics and trophic interaction of the cod in the Barents Sea.
What we have:
The necessary data for the study are made freely available by the International Council for the Exploration of the Sea (ICES, 2021).
What will the student do:
Using advanced statistical modelling (Matrix modeling and Generalized Additive Model) the student will examine the effect of external stressors on the population dynamics. This master requires computer work and we look for a student comfortable using R language and with good statistical competences. We expect the student to become familiar with the content of the book of Caswell (Caswell, 2001).
What we look at:
- Annual transient realized population growth rate (the logarithm of the first eigenvector of the annual matrix)(Koons et al., 2005) on the Northeast Artic cod.
- Effect of different explanatory variables on the population growth change.
- If possible, Scenarios applied to the results.
What will the student learn:
With this thesis the student will get an intrinsic knowledge of cod biology and of the Norwegian-Barents Sea ecosystem and its trophic interactions. The student will get a hands-on experience and supervision on the use of a versatile programming software (R-core) and advanced statistical modelling. Those are common tools used to solve ecological questions across topics. We expect the master thesis to be publishable in a good international journal.
Working environment
The Master work will be conducted within the Marine Ecology Group at the Centre for Ecological and Evolutionary Synthesis of the Department of Biosciences (http://bit.ly/1psRR6n). The marine group is a multidisciplinary group that bring together ca 10 researchers, PhD and Master Students working on the domains of ecology and statistic. It has shown over a decade competence in answering ecological questions around climate change and marine productivity through statistical analysis and interdisciplinary collaborations.
The Master will be able to train in a friendly environment her presentation skills at the monthly marine meetings.
Period
September 2023 – September 2025
Supervisor
Jo?l Durant (CEES/IBV University of Oslo)
References
Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation, 2nd edn, Sinauer Associates, Sunderland, MA.
Durant, J. M., Hidalgo, M., Rouyer, T., Hjermann, D. ?., Ciannelli, L., Eikeset, A. M., Yaragina, N., et al. 2013. Population growth across heterogeneous environments: effects of harvesting and age structure. Marine Ecology Progress Series, 480: 277-287.
Durant, J. M., and Hjermann, D. ?. 2017. Age-structure, harvesting and climate effects on population growth of Arcto-boreal fish stocks. Marine Ecology Progress Series, 577: 177-188.
Durant, J. M., Yaragina, N., and Stige, L. C. 2021. The role of spatial distribution for growth and survival of juvenile cod Gadus morhua in the Barents Sea. ICES Journal of Marine Science, 78: 2700-2708.
ICES 2021. Arctic Fisheries Working Group (AFWG). ICES Scientific Reports, 3: 817 pp.
Jakobsen, T., and Ozhigin, V. K. 2011. The Barents Sea: Ecosystem, Resources, Management. Half a century of Russian - Norwegian cooperation. p. 825. Tapir Academic Press, Trondheim, Norway.
Koons, D. N., Grand, J. B., Zinner, B., and Rockwell, R. F. 2005. Transient population dynamics: Relations to life history and initial population state. Ecological Modelling, 185: 283-297.
Ottersen, G., and Holt, R. E. 2022. Long-term variability in spawning stock age structure influences climate–recruitment link for Barents Sea cod. Fisheries Oceanography, 32: 91-105.
Figure 1 Matrix model Nt+1 = At · Nt (change of abundance from year t to year t+1), with Ra,t the contribution of each age-class a to the recruitment at year t and with Sa-a-1,t the survival between age-a at year t and age a-1 at year t. The age index a varies between 1 and amax, the older age-class in the population
