A Synoptic View of Carbon and Oxygen Dynamics in European Regional Seas: an Approach Coupling Modelled and Satellite Datasets - Part A: Conceptual Model and Sensitivity Analysis

A major work package of the JRC/IES FP6 Action 2121 ECOMAR is related to the further development and validation of ecological indices and the development of value added products of state and process of coastal and marine ecosystems in European regional seas. In this context a specific task is to develop, apply and validate a model for the quantification of oxygen and carbon cycles in shallow coastal waters exposed or sensitive to eutrophication. This model should be used for a more accurate quantification of oxygen depletion risk at a pan-European level. In this report the development of an accurate model for oxygen and carbon cycles in shelf and eutrophicated areas is presented. Following the recent development of eutrophication indices for coastal and marine areas, OXYRISK and PSA, and several recent attempts to implement a thorough but simple coupled benthic/pelagic model, the new model is applied in highly eutrophicated and sensitive coastal areas of the European seas. A new approach is proposed coupling a 3D hydrodynamic and a 1D ecosystem model, supplied with primary production data derived from satellite remote sensing. This approach allows getting a synoptic view in time and space of carbon and dissolved oxygen concentrations for different basins. A first application of the model is made for the Baltic Sea. The biogeochemical sub-model includes coupled benthic/pelagic processes specifically addressing oxygen quantification in the sediment, as in the benthic and upper layers of the water column. This ecosystem model will be gradually developed further from a simple (POC)/(DO) model into a NPZD/sediment model, while being fully coupled with the hydrodynamic model for advection and diffusion processes. The model will be validated along with its application as an eutrophication assessment tool for European seas.JRC.H.5-Rural, water and ecosystem resource

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

DESIMA Future Developments

Abstract not availableJRC.(SAI)-Space Application Institut

Numerical Verification Exercises with Different Computer Models for Simulating Sea Circulation Pattern. The Vertical Diffusion of Momentum in a Forced Barotropic Sea

Abstract not availableNA-NOT AVAILABL

Distributed Information System Supporting Integrated Coastal Zone Management.

Abstract not availableJRC.(SAI)-Space Application Institut

"Variable" Von Karman's Constant as a Parameter of Sediment Stratification.

Abstract not availableJRC.(SAI)-Space Application Institut

Model Phase Portraits of a Sediment-Stratified Oceanic Bottom Layer.

Abstract not availableJRC.(SAI)-Space Application Institut

User Requirements and Information Definition for a Virtual Coastal and Marine Data Warehouse.

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra

Comparison of Two Ocean Numerical Models: HAMSON and ISPRAMIX for the North Sea Dynamics Simulations

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra

DESIMA.

Coastal zones are key areas regarding human activities and their environmental impact. The DESIMA (Decision Support for integrated coastal zone Management) project aims to support Coastal Zone Management applications through an improved integration and use of various information sources and information providing tool. This project is carried out by the Marine Environment of the Joint Research Centre of the european Commission. DESIMA supports the harminisation and standardisation efforts on a European level in the field of coastal information systems.JRC.(SAI)-Space Application Institut