Ocean biogeochemistry is a novel standard component of fifth phase of the Coupled Model Intercomparison Project (CMIP5) experiments which project future climate change caused by anthropogenic emissions of greenhouse gases. Of particular interest here is the evolution of the oceanic sink of carbon and the oceanic contribution to the climate‐carbon cycle feedback loop. The Hamburg ocean carbon cycle model (HAMOCC), a component of the Max Planck Institute for Meteorology Earth system model (MPI‐ESM), is employed to address these challenges. In this paper we describe the version of HAMOCC used in the CMIP5 experiments (HAMOCC 5.2) and its implementation in the MPI‐ESM to provide a documentation and basis for future CMIP5‐related studies. Modeled present day distributions of biogeochemical variables calculated in two different horizontal resolutions compare fairly well with observations. Statistical metrics indicate that the model performs better at the ocean surface and worse in the ocean interior. There is a tendency for improvements in the higher resolution model configuration in representing deeper ocean variables; however, there is little to no improvement at the ocean surface. An experiment with interactive carbon cycle driven by emissions of CO2 produces a 25% higher variability in the oceanic carbon uptake over the historical period than the same model forced by prescribed atmospheric CO2 concentrations. Furthermore, a climate warming of 3.5 K projected at atmospheric CO2 concentration of four times the preindustrial value, reduced the atmosphere‐ocean CO2 flux by 1 GtC yr−1. Overall, the model shows consistent results in different configurations, being suitable for the type of simulations required within the CMIP5 experimental design.

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a b s t r a c tThe concept of co-location of marine areas receives an increased significance in the light of sustainable development in the already heavily used offshore marine realm. Within this study, different spatial colocation scenarios for the coupling of offshore aquacultures and wind farms are evaluated in order to support efficient and sustainable marine spatial management strategies. A Geographic Information System (GIS) and multi-criteria evaluation (MCE) techniques were combined to index suitable co-sites in the German exclusive economic zone of the North Sea. The MCE was based on criteria such as temperature, salinity or oxygen. In total, 13 possible aquaculture candidates (seaweed, bivalves, fish and crustaceans) were selected for the scenario configuration. The GIS modelling framework proved to be powerful in defining potential co-location sites. The aquaculture candidate oarweed (Laminaria digitata) revealed the highest suitability scores at 10-20 m depth from April to June, followed by haddock (Melanogrammus aeglefinus) at 20-30 m depth and dulse (Palmaria palmata) and Sea belt (Saccharina latissima) at 0-10 m depth between April and June. In summary, results showed several wind farms were de facto suitable sites for aquaculture since they exhibited high suitability scores for Integrated MultiTrophic Aquaculture (IMTA) systems combining fish species, bivalves and seaweeds. The present results illustrate how synergies may be realised between competing needs of both offshore wind energy and offshore IMTA in the German EEZ of the North Sea. This might offer guidance to stakeholders and assist decision-makers in determining the most suitable sites for pilot projects using IMTA techniques.

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Understanding of the processes affecting recruitment of commercially important fish species is one of the major challenges in fisheries science. Towards this aim, we investigated the relation between North Sea hydrography (temperature and salinity) and fish stock variables (recruitment, spawning stock biomass and pre-recruitment survival index) for 9 commercially important fishes using spatially-resolved cross-correlation analysis. We used high-resolution (0.2° × 0.2°) hydrographic data fields matching the maximal temporal extent of the fish population assessments (1948–2013). Our approach allowed for the identification of regions in the North Sea where environmental variables seem to be more influential on the fish stocks, as well as the regions of a lesser or nil influence. Our results confirmed previously demonstrated negative correlations between temperature and recruitment of cod and plaice and identified regions of the strongest correlations (German Bight for plaice and north-western North Sea for cod). We also revealed a positive correlation between herring spawning stock biomass and temperature in the Orkney-Shetland area, as well as a negative correlation between sole pre-recruitment survival index and temperature in the German Bight. A strong positive correlation between sprat stock variables and salinity in the central North Sea was also found. To our knowledge the results concerning correlations between North Sea hydrography and stocks’ dynamics of herring, sole and sprat are novel. The new information about spatial distribution of the correlation provides an additional help to identify mechanisms underlying these correlations. As an illustration of the utility of these results for fishery management, an example is provided that incorporates the identified environmental covariates in stock-recruitment models.