The iMarine solutions in support to the ecosystem approach needs

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
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

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
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)

PART 2 – iMarine solutions
The power of an e-Infrastructure
Outline
Synergies and efficiencies through Global
collaborative communities

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)
AQUAMAPS

Biodiversity models
• Joint occurrence of n taxa
Maintaining ecosystem health requires
– Identification of Sensitive or fragile habitats
Environmental
enrichment of species
occurrence data
Source: Coll et al. (2010)

Enriched species
occurrences
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)

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)

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
Source: IRD ECOSCOPE
Source: OBIS / IRD ECOSCOPE
Source: iMarine / AquaMaps
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
SPREAD
… are re-allocated
by EEZ based on
the species
distribution

Near-real-time management of high resolution fisheries operational data
Fishery control and surveillance, and adaptive fishery management, require :
– Quota uptake monitoring, fishing impact assessment

Access to MCS data by science
VMS and e-LogBook data processing under confidentiality requirements
Fishery control and surveillance, and adaptive fishery management, require :
– Quota uptake monitoring, fishing impact assessment

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
Flag
State 1e-Logbooks, VMS
(Fishing Activity
Reports)
Metadata
Regional
DataBase
(FLUX)Reports)
HARMONISATION
support
Metadata
Standards
Flag
State 2
(FishFrame)
Scientific
observations
FLUX
FishFrame
SDMX
DWC
OGC
Analytical
processes

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

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
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 …

Species focused information
disseminated through mobile
Fisheries science will benefit from comprehensive knowledge bases
integrating fishery and biodiversity data sources:
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

• Seamless access to fisheries
information scattered among three
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

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
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

CONCLUSION
What are the ingredients of success
Outline
What are the ingredients of success

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

Thanks for your attention
Outline

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
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

The iMarine solutions in support to the ecosystem approach needs

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