Deliverables

/Deliverables

Library and tools for MareFrame

  https://github.com/mareframe

July 7th, 2017|

Deliverable 7.3 – Simulation based training tool for a DSS for EAFM

The MareFrame DST Training Tool is version 1.0. This means that all features are implemented and tested for bugs. Three example scenarios have been made and are available at the link provided in the user manual. New scenarios for each case-study are easily made. In addition, the software design of the training tool makes it

April 7th, 2017|

Deliverable 7.4 – Material in learning content management system

This report is a Deliverable of Work Package 7 (WP7 – Synthesis & training development) of the FP7 MareFrame research project. In this report we introduce tutor-web, the Learning Content Management System (LCMS) chosen to store MareFrame learning material, and subsequently outline the available content and explain where it can be downloaded from. Finally, we

December 31st, 2016|

Deliverable 7.2 – Analysed case studies with respect to project progress evaluation

This report is a deliverable of Work Package 7 (WP7 – Synthesis & training development) of the FP7 MareFrame research project. The report comprises two main parts. The first part presents a protocol for the comparison and evaluation of the ecosystem models that have been developed and applied within the MareFrame project. This is to

December 31st, 2016|

Deliverable 5.3 – Results of ecosystem modelling in case study areas

This report is a deliverable of Work Package 5 (WP5 – Apply new methods in case studies) of the FP7 MareFrame research project. It documents the application of a large number of ecosystem models into the different case studies with the ultimate goal to provide the quantitative information required by the decision support tools developed

December 31st, 2016|

Deliverable 4.7 – Atlantis model run for data-poor case study

This report is the 7th deliverable in WP4 and studies the performance of Ecopath with Ecosim (EwE) and Gadget in data-poor cases. The Atlantis model that was constructed for Icelandic waters was used as an operating model and data simulated from the model for data-poor scenarios. The simulated data was fed into EwE and Gadget

December 31st, 2016|

Deliverable 4.6 – Parameterisation part 4.Alternative model run for each case study which replicates the time series of the commercial fish species, GES, economic and social (EAFM) indicators

This report, deliverable 4.6 (D4.6), is a deliverable of Work Package 4 (WP4 – Ecosystem models and assessment models) of the FP7 MareFrame research project. The aim of the MareFrame project is to identify management strategies which will achieve Good Environmental Status (GES) by applying a minimum of two ecosystem models on each of eight

December 30th, 2016|

Deliverable 4.5 – Parameterisation part 3. Working model run for each case study which replicates the time series of the economic and social (EAFM) indicators

This report is a deliverable of work package 4 (WP4 – Ecosystem models and assessment models) of the FP7 MareFrame research project. The aim of the MareFrame project is to identify management strategies which will encompass the ecosystem approach to fisheries management. The generic strategy for the project is to apply a minimum of two

December 30th, 2016|

Deliverable 4.4 – Comparison of the performance of two EMs with known (simulated) data

This report is the 4th deliverable in WP4 and studies the performance of two models commonly used in this WP, Ecopath with Ecosim (EwE) and Gadget. An Atlantis model was constructed for Icelandic waters and used as an operating model, i.e. simulated data from Atlantis was fed into EwE and Gadget. Thus, Atlantis was considered

December 29th, 2016|

Deliverable 1.3 Fisheries Advice in relation to the CFP and MSFD

The debate on the Ecosystem Approach to Fisheries Management (EAFM) has shifted from definition of the concept towards implementation. In the European Union (EU) challenges and barriers coming from the scientific knowledge base and the institutional framework have been analysed elsewhere. However, in the current playing field other challenges have gone unnoticed. These relate to

December 28th, 2016|