The iMarine solutions in support to the ecosystem approach needs

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Information about The iMarine solutions in support to the ecosystem approach needs
Technology

Published on March 18, 2014

Author: iMarine283644

Source: slideshare.net

The iMarine solutions in support to the Ecosystem Approach needs iMarine data platform for collaborations, 7th March 2014, FAO (Rome) Marc Taconet (FAO) Approach needs iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

PART 1 - Serving policy frameworks facing BIG challenges – example of EAF Outline iMarine data platform for collaborations , 7th March 2014, FAO (Rome) PART 2 – iMarine solutions The power of an e-Infrastructure Synergies and efficiencies through Global collaborative communities

Serving policy framework facing BIG challenges – the EA • FAO • DG MARE • Eurostat • NEAFC • MEDDE/DOF • iMarine Board – the Community Governing body: – representatives of influential community partners – convey community requirements drivers of technology developments – stimulus - three EA policy challenges (Business Cases) Fisheries • IRD • ICES • IOC/OBIS • FIN • CRIA • VLIZ • T2/GENESI- DEC » BC1: Support to implementation of the EU Common Fishery Policy » BC2: Support to FAO’s deep seas fisheries programme » BC3: Support to regional tropical LME pelagic EAF community • The three iMarine Business Cases: BiodiversityEnvironment iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Data needs in the EA policy framework 2. Fine grained catch & effort for resources assessment, management of fishing quota, fishing impact assessments 1. Species niche modeling to monitor health and trends of the ecosystems Serving policy framework facing BIG challenges – the EA 4. Comprehensive species knowledge base to address impact of fishing on marine ecosystems 3. Mapping of sensitive or fragile habitats in need of special management (EBSAs or VMEs) iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

PART 2 – iMarine solutions The power of an e-Infrastructure Outline Synergies and efficiencies through Global collaborative communities iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Monitoring ecosystem health and trends requires baselines – Species predictive mapping Synergies and efficiencies through Global collaboration & CoP Ecological niche modelling Source: Kaschner et. al. (2006) iMarine data platform for collaborations , 7th March 2014, FAO (Rome) AQUAMAPS

Biodiversity models • Joint occurrence of n taxa Maintaining ecosystem health requires – Identification of Sensitive or fragile habitats Environmental enrichment of species occurrence data Synergies and efficiencies through Global collaboration & CoP Source: Coll et al. (2010) iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Enriched species occurrences Synergies and efficiencies through Global collaboration & CoP Environmental enrichment of species occurrence data Physical variables Environmental variables for each occurrence, selection of the most appropriate proxi data according to: -Time range - Z range (depth) iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Mapping of sensitive habitats is required for applying special management measures: – Aimed at reducing ecosystem impacts of Deep sea fishing on fragile ecosystems (VMEs assessments) Synergies and efficiencies through Global collaboration & CoP iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Management of scientific data collected on Board fishing vessels, e.g. sharks as by-catch species identified by Observers on Board tuna fishing vessels Isurus oxyrinchus (Shortfin mako - shark) Mapping of sensitive habitats is required for applying special management measures: – Aimed at reducing ecosystem impacts of Fishing on by-catch species Synergies and efficiencies through Global collaboration & CoP Source: IRD ECOSCOPE Source: OBIS / IRD ECOSCOPE Source: iMarine / AquaMaps iMarine data platform for collaborations , 7th March 2014, FAO (Rome) Modeling of species geographic distribution, • Application of Predictive mapping models, such as developed by Aquamaps

• Coarse resolution Atlantic herring catch statistics … Fisheries management and policy making requires – Assessing high seas resources vs. resources inside EEZs (UNGA) – Fish quotas allocation (RFMOs) Finer grained catch and effort data can be obtained through spatial reallocation process Synergies and efficiencies through Global collaboration & CoP SPREAD iMarine data platform for collaborations , 7th March 2014, FAO (Rome) … are re-allocated by EEZ based on the species distribution

Near-real-time management of high resolution fisheries operational data Synergies and efficiencies through Global collaboration & CoP Fishery control and surveillance, and adaptive fishery management, require : – Quota uptake monitoring, fishing impact assessment iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Access to MCS data by science VMS and e-LogBook data processing under confidentiality requirements Synergies and efficiencies through Global collaboration & CoP Fishery control and surveillance, and adaptive fishery management, require : – Quota uptake monitoring, fishing impact assessment iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

VALIDATION rules More integrated and higher quality catch / effort / biological occurrences data in coverage, timeliness, resolution and accuracy promote simplified, efficient and quality workflow across domains through: • common formats, harmonization support, validation rules Synergies and efficiencies through Global collaboration & CoP Flag State 1e-Logbooks, VMS (Fishing Activity Reports) Metadata Regional DataBase (FLUX)Reports) iMarine data platform for collaborations , 7th March 2014, FAO (Rome) HARMONISATION support Metadata Standards Flag State 2 (FishFrame) Scientific observations FLUX FishFrame SDMX DWC OGC Analytical processes

Synergies and efficiencies through Global collaboration & CoP Synergies – a case study • In fisheries monitoring, attention is brought to: – By-catch species – Species acting as indicators of fragile habitats (e.g. VME encounters) • Species identification guides are being developed at regional / national level – Local efforts would benefit from collated knowledge Chondrichthyes (class), Scombridae (family), Lutjanus spp (genus) Condrycthiens (vs. Chondrichthyes) P. notialis (vs. Penaeus notialis) Pomadasydés, Sparidae (Pageot), Penaeus sp, langouste, seiche Farfantepenaeus notialis (deprecated) vs. Penaeus notialis (official) • Issue: many species names are reported, with variations and errors iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Synergies – a case study: Taxa name matching / mapping – Names validation through cross-referencing with global taxonomic databases – Capturing mappings between local expressions and authority lists Cross-fertilization opportunities between fisheries sciences and bio-ecological sciences Synergies and efficiencies through Global collaboration & CoP Plus … Fisheries Linked Open Data (FLOD) – Organizing concepts and terms in comprehensive ontologies available as Linked Open Data Comprehensive knowledge bases on: – Species vernacular / multilingual names – broad range of species information • contributing to fill the gap of knowledge Results in … Plus … iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Species focused information disseminated through mobile Fisheries science will benefit from comprehensive knowledge bases integrating fishery and biodiversity data sources: Synergies and efficiencies through Global collaboration & CoP APPLIFISH disseminated through mobile applications, for use by anyone at consumer places – Requires capacity to integrate multiple / complementary sources – Efficiency will rely on broad knowledge base on species names, combined with GPS information of Mobile user iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

• Seamless access to fisheries information scattered among three Synergies and efficiencies through Global collaboration & CoP CHIMAERA: REGIONAL FISHERIES PORTAL FOR SOUTH-WEST INDIAN OCEAN Fisheries science will benefit from comprehensive knowledge bases integrating fishery and biodiversity data sources: information scattered among three distinct information systems – Requires capacity to integrate multiple / complementary sources iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Elements of synergies – Various Business Cases complement each other: – End-up building comprehensive toolkit required for entire flow from raw data collection to policy indicators – Data produced by A. are inputs to B. – all accessible from same environment – Tools are pooled and can be reused across different communities having similar needs, and enriched Synergies and efficiencies through Global collaboration & CoP communities having similar needs, and enriched – Data availability among disciplines enhance quality – Bridge MCS data with science (confidentiality requirements) Elements of efficiencies – Partner systems tend to specialize on their strength and delegate to others iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

CONCLUSION What are the ingredients of success Outline What are the ingredients of success iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Powerful technology Community governance Data access and sharing policies Conclusion – ingredients of success Data access and sharing policies Business model for Exploitation of the data infrastructure – Public centered Partnership business model iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Thanks for your attention Outline iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

Matching the technology offer with community needs A vision in support to EAF needs Fishery resource productivity Biodiversity and preservation Biodiversity and habitat preservation Social and economic goals values Objectives Policy maker Fishery manager Serving policy framework facing BIG challenges – the EA Indicators / Ref points Distribution of fishery activity Socio-economic communities Socio-economic structure of fishing communities Abundance levels fish stocks Distribution habitats Distribution of non-target species / habitats Fishery manager Scientist Data manager models Data repositories Statistician iMarine data platform for collaborations , 7th March 2014, FAO (Rome)

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