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)

Fis

he

rie

s

• 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:

Bio

div

ers

ity

En

vir

on

me

nt


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


Technology

The iMarine solutions in support to the ecosystem approach needs