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MEDINA Overall objectives:

The MEDINA e-Infrastructure: enhancing ongoing monitoring and assessment of marine ecosystems in North Africa Roberto Pastres, Ca’ Foscari University of Venice pastres@unive.it medinaproject@unive.it. MEDINA Overall objectives:

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MEDINA Overall objectives:

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  1. The MEDINA e-Infrastructure: enhancing ongoing monitoring and assessment of marine ecosystems in North AfricaRoberto Pastres, Ca’ Foscari University of Venicepastres@unive.itmedinaproject@unive.it

  2. MEDINA Overall objectives: -To contribute to the assessment of coastal ecosystem status in North African countries; -To enhance the monitoring capacity in the region. -To feedback MEDINA’s scientific contribution within the EU regulatory framework. -To ensure the optimal exploitation of the GEOSS Common Infrastructure (GCI) in supporting on going monitoring&assessment

  3. MEDINA’s key features: • Driver-Pressure-State-Impact-Responseconceptualframeworkforon-goingmonitoring and assessment. • Useofmodels (biogeochemical, SpeciesDistribution, Food Web etc ….) forrelatingDrivers/Pressuresto State/Impacts. • Fusionofremotely-sensed and in-situobservation, throughmodelling, formonitoringoptimization.

  4. Monitoring is entrusted to several institutions! Morocco

  5. The MEDINA e-Infrastructure is building a bridge between the National Monitoring Capacity and the resources made available by the GCI.

  6. What is the MEDINA e-Infrastructure? • Infrastructure that supports access to geographic interoperable spatial information. • Distributed geographic database, based on standardized protocols, to ensure interoperability. • A tool to disseminate Medina products.

  7. Main features and components of the MeI FEATURE (i.e. what?) DISCOVERY VISUALIZATION DELIVERY DATA ACCESS COMPONENT (i.e. how?) CATALOG MAP SERVICES (WMS), ONLINE VIEWER, MAP SERVICES (WFS, WCS)

  8. MeI conceptual model

  9. MeI: stage ofdevelopment The basic structure of the reference catalogue for the Medina e-Infrastructure (MeI) has been defined; The MeI is operational and is being populated ; Pilot cases: an Architecture Implementation Pilot has been developed (Species Distribution Model for Posidonia oceanica): see video.

  10. http://www.medinageoportal.eu/ The Medina e‐Infrastructure viewer is designed to improve visualisation and analysis of spatial data through tools such as: zoom in and out, pre‐defined selection of areas, a tool for adjust layers transparency.

  11. The GEOSS searching tool allows the user to look for specific environmental topics among the GEOSS Data Catalogue and the Medina catalogue, thereby assuring the exploitation of the GEOSS GCI resources.

  12. The MeI data catalogue groups the indicators within three categories: Ecological Objectives and DPSIR, Modelling Outputs and Earth Observations

  13. MEDINA contribution to the implementation of UNEP-MAP EcAp

  14. Progress towards ECAP entails important challenges for all Mediterranean countries: The approach is complex and a huge monitoring effort is required to assess the ecosystem status in relation to GES for all the 11 EcOs. MEDINA will focus on 3 EcOs that are relevant for the area and can be addressed (fully or partially) by remotely sensed EO and modelling : EcO1 Biodiversity EcO5 Eutrophication EcO9 Contaminant

  15. MEDINA contribution to the implementation of UNEP-MAP EcAp

  16. Oceanic fronts as “deep sea habitat in EcAp” : dynamic boundaries between water mass with a larger-than-average horizontal gradient in property like temperature, colour, salinity or turbidity

  17. AIP6: DEVELOPMENT OF A POSIDONIA DISTRIBUTION MODEL (PoSDM) AVAILABLE THROUGH GEOSS COMMON INFRASTRUCTURE (GCI) DM Posidonia oceanica

  18. Why a Posidonia DM? Species Distribution Model (or Habitat Suitability Model, HSM) are often used to integrate or extrapolate sparse occurrence data (Elith & Leathwick, 2009). The application of the Posidonia DM provides an estimate of the potential extension of the Posidonia habitat, thus allowing the estimation of one key UNEP-MAP operational objective and related indicators, namely, OO 1.4 (Key coastal and marine habitats are not being lost)

  19. GEOSS BROKER: http://www.eurogeoss-broker.eu/

  20. PoDM - Posidonia oceanica distribution model - Development Tuscany Balearic Island Campania Apulia 3) Calibration sites Calabria Model calibration (Binomial Generalized Additive Model) Data coupling (Inputs) P. oceanica presence Kd; Euphotic depth; Chl; CDM (EMIS EOs) SST(Aqua-MODIS) PAR (SeaWiFS) Bathymetry (GEBCO) Posidonia Effects on P. oceanica probability of presence Kd Chl …

  21. PoDM – 4) Model Testing Pilot Case Gulf of Gabes (Tunisia) Input data Model Prediction (probability of presence) Bathymetry (m) Par (Einstein m-2 day-1) Chlorophyll –a (g m-2) Light coef. Extinction (m-1) SST(°C) Sea-truth distribution (Zaouali, 1993)

  22. 5) Implementation of the model on the basis of raster files showing the environmental variables for the entire Mediterranean region.

  23. Next steps - The MeI will be populated with the results of the regional ecosystem assessement and those concerning five test areas (Pilot Cases) -The MeI will be presented to monitoring agencies and stakeholders at four National workshops, to be held in Algeria, Egypt, Morocco and Tunisia in May-June 2014. Meetings will be focused on EcAp implementation.

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