2The copepods Calanus finmarchicus and C. helgolandicus co-exist in the North Sea, 3 but their spatial distribution and phenology are very different. Long-term changes in their 4 distributions seem to occur due to climate change resulting in a northward extension of C. 5 helgolandicus and a decline of C. finmarchicus in this region. The aim of this study is to use life-6 stage structured models of the two Calanus species embedded in a 3D coupled hydrodynamic-7 biogeochemical model to investigate how the biogeography of C. finmarchicus and C. scenario suggest that in a warmer future, C. finmarchicus is likely to decline and C. 21 helgolandicus abundance will probably continue to increase in some areas. 22 23
Abstract. First results of a coupled modelling and forecasting system for fisheries on habitat-bound stocks are being presented. The system consists currently of three mathematically, fundamentally different model subsystems coupled offline: POLCOMS providing the physical environment implemented in the domain of the north-west European shelf, the SPAM model which describes sandeel stocks in the North Sea, and the third component, the SLAM model, which connects POLCOMS and SPAM by computing the physicalbiological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the basis of hindcast data.The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin-scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeel stocks are currently exploited close to the maximum sustainable yield, even though periodic overfishing seems to have occurred, but large uncertainty is associated with determining stock maximum sustainable yield due to stock inherent dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2-6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable.
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