Spatial shifts of marine stocks and the resilience of polar resource management (STOCHSHIFT)
About the project
STOCKSHIFT explores the resilience of Arctic and Antarctic marine-resource management institutions to large-scale spatial shifts of major marine stocks in the Barents Sea, the Norwegian Sea and the Southern Ocean. Climate change and other environmental factors are currently causing variability in the spatial distribution of fish stocks in Polar waters. In the Barents Sea, cod is expanding northeastwards, while in the Norwegian Sea significant changes in abundance, distribution and migration patterns can be observed in pelagic species such as mackerel. In the Southern Ocean, the combined effect of increasing temperatures with associated declines in sea ice, ocean acidification and changes in circulation is likely to affect the geographical distribution of krill.
These developments put established management regimes under pressure. In this truly interdisciplinary research endeavour, world-leading marine biologists, international lawyers and political scientists join efforts to study the resilience of Arctic and Antarctic marine resource management institutions to large-scale shifts of major marine stocks.
- How is climate change affecting distributional shifts of Polar fish stocks - are there any general patterns of movement, adaptability and recruitment?
- To what extent do shifts in migratory patterns influence the fit between the spatial scope of existing national and international management regimes and the fishing activities they seek to govern - and how will they influence the effectiveness of the regimes?
- How does continued effectiveness require adaptation within the complexes of institutions that co-govern commercial activities in Polar marine ecosystems?
Based on case studies from the Barents Sea, the Norwegian Sea and the Southern Ocean, a meta-analysis will be performed to synthesize the overall impact of climate, fisheries and species interaction. Finally, the project will explore how comparative case study analysis and agent-based modelling (ABM) can be combined to examine cross-regime responses to plausible ecosystem development trajectories.