JERICO WP10: JRA Emerging technologies (Improve system components)

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JERICO WP10 JRAEmerging technologies(Improve
system components)
Glenn Nolan, Antoine Gremare
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(No Transcript)
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Partners involved
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WP10 Objectives

• To examine the extent to which existing
  technologies can be improved and/or adapted to
  the benefit of coastal operational oceanography
  and to document and test emerging technologies
  that will underpin future operational
  oceanographic systems in Europes coastal seas.
  The work package is sub-divided into tasks
  including
• 1. New tools and strategies for monitoring key
  biological compartments and processes
• 2. Development of new physico-chemical sensors.
• 3.Use of emerging profiling technologies for
  coastal seas.
• 4. Increased use of ships of opportunity in
  making coastal oceanographic measurements.
• 5. Best practices in coastal observatory
  implementation.

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Overview of tasks and sub-tasks
Task Description Sub-task Description Partners Partners Partners Partners Partners Partners Partners Partners Partners Partners Partners Partners Partners
        INSU NIOZ NIVA NERC SYKE SMHI HZG OGS IFREMER CSIC CNR CEFAS MI
10.1 Biological Compartments                            
10.2 Physical/Chem. Sensors 10.2.1 Contaminants                          
    10.2.2 Algal pigments                          
    10.2.3 Carbonate System                          
10.3 Emerging tech.                              
10.4 Fishing vessel/VOS                              
10.5 Ferrybox                              
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Key personnel
INSU Antoine OGS Rajesh
NIOZ Carlo IFREMER Yannick
NIVA Dominique CSIC Joaquin
NERC David CNR Michela
SYKE Jukka CEFAS Dave
SMHI Bengt MI Glenn
HZG Willi  MUMM Michael
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TASK 10.1

• DEVELOPMENTS OF NEW TOOLS AND STRATEGIES FOR THE
  MONITORING OF KEY BIOLOGICAL COMPARTMENTS AND
  PROCESSES
• (1) in situ video imaging of the water sediment
  interface using ROV or other mobile carriers to
  infer the abundance of supra-benthos
• (2) in situ sediment profile images to infer the
  ecological quality status of benthic habitats
  using either existing or newly developed indices,
  
• (3) in situ recorded videos by fixed cameras to
  assess the activity and growth of benthic
  organisms,
• (4) images derived from laboratory equipments
  designed to process and assess both phytoplankton
  (Flowcam, FlowCytoBot) and zooplankton (Zooscan).
• (INSU, NIOZ, NIVA)
• Demonstration survey

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TASK 10.1 DEVELOPMENTS OF NEW TOOLS FOR THE
MONITORING OF KEY BIOLOGICAL COMPARTMENTS AND
PROCESSES (INSU, NIOZ, NIVA)

• Coastal ecosystems are highly productive
• biodiversity hotspots (most of
  them)
• heterogeneous in space
• submitted to disturbances
  (man-induced, temporal instability)
• Stakeholders operating in coastal areas are
  highly interested in biological issues (some of
  them regarding the top of the food chain)
• They is a growing need for the assessment of
  ecosystem ecological quality at large spatial
  scale (from WFD to MSFD)
• From a technical standpoint, the current number
  of biological parameters that can be included in
  an operational network is extremely low
  (increasing the spatial and temporal frequency
  of Chl a measurements is probably necessary but
  certainly not
• enough when pretending to assess the
  ecological quality status of coastal ecosystems).
• Strong need to develop new tools

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TASK 10.1 DEVELOPMENTS OF NEW TOOLS

• In situ sediment profile images to infer the
  ecological quality status of benthic habitats
  using either existing or newly developed indices
• In situ video imaging of the water sediment
  interface using ROV or other mobile carriers to
  infer the abundance of suprabenthos
• In situ recorded videos by fixed cameras to
  assess the activity and growth of benthic
  organisms
• Images derived from laboratory equipments
  designed to process and assess both phytoplankton
  (Flowcam) and zooplankton (Zooscan).

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In situ sediment profile images Monitoring
growth - Based on segmentations of individual
images - Used to draw the water/sediment
interface, aRPD and biogenic structures - Works
automatically and semi automatically -
Challenge Extend the plasticity of the software
to make it applicable (automatically)in the
largest possible set of situations
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In situ video imaging of the water sediment
interface using mobile carriers - Based on
segmentations of individual images - Allow for
the identification and quantification of selected
species - Long term time series provide an
indirect assessment of growth - Already achieved
in the Mediterranean - Challenge Create an
interface allowing for the parametrization of
segmentation
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In situ recorded videos by fixed cameras
Monitoring activity and movements - Based on
the pixel by pixel comparison of successive
images - Threshold of detected changes
attributed to activity - Already achieved in the
laboratory - Challenge Transpose this to the
field (noise)
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In situ recorded videos by fixed cameras
Monitoring growth - Based on the pixel by pixel
comparison of successive images - Threshold of
detected changes attributed to activity - Long
term time series can provide an indirect
assesment of growth - Already achieved in the
laboratory - Challenge Achieve direct
assessment of growth in situ
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Images derived from laboratory equipments to
monitor end to end plankton community -
Semi-automatic recognition based on a large set
of biometric measu- ments
and a learning set (currently different
instruments and no integration) - Challenge
Develop an integrated suite of software for image
analysis, automatic recognition, predictions
validation and images and results management
for both Flowcam (protozoa) and Zooscan
(metazoa)
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DEMONSTRATION SURVEYS

• - Some of the developments of tools are dealing
  with the characterization of phytoplankton
  (including harmful species).
• - Other ones are dealing with the monitoring
  activity of macrobenthos
• A demonstration survey will combine these two
  inputs. It will be carried out at several
  contrasted site including an
• - oligotropic one (Villefranche),
• - second featuring important aquaculture
  activities potentially affected by
• harmful algal blooms (Arcachon)
• - a Baltic one (to be discussed)

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TASK 10.2

• DEVELOPMENTS OF PHYSICO-CHEMICAL SENSORS AND
  IMPLEMENTATION ON NEW PLATFORMS
• Subtask 10.2.1. Contaminants
• Subtask 10.2.2. Algal pigments
• Subtask 10.2.3. Carbonate system (adapt and
  deploy)
• (NIVA, NERC, SYKE, SMHI, HZG)

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TASK 10.3

• EMERGING TECHNOLOGY - PROFILING TECHNOLOGY,
  INTER-COMPARISON WITH MATURE TECHNOLOGY
• (1) MAMBO buoy, PAGODE profiling floats and
  ship-based CTD systems in the Northern Adriatic
  Sea, and
• (2) the EOL buoy and ship-based measurements in
  the Ligurian Sea,
• (3) profiling system in the Bay of Biscay (ocean
  exposed conditions) compare with those of two
  FerryBox lines
• (OGS, IFREMER, CSIC, MI, INSU, NIVA, NERC)
• Two case studies including glider and XBTs from
  Ferries

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TASK 10.4

• SHIPS OF OPPORTUNITY, NEXT GENERATION FISHING
  VESSELS PROBES
• (IFREMER, CNR, CEFAS, MI)
• Short workshop (field activity WP7??)

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TASK 10.5

• FERRYBOX DATA QUALITY CONTROL ALGORITHM (M6-M42)
• (NERC, NIVA, HZG)
• Review (no field activity)

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  Year 1 Year 2 Year 3 Year 4
MS22 12      
MS23   24    
MS24     26  
MS25     26  
MS26     30  
D10.1     36  
D10.2       42
D10.3       42
D10.4       42
Internal reporting 9 24 27 48
Project reporting   18 36  
Field activity        
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Deliverables WP10
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Milestones
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Next steps

• Include SPM satellite task (MUMM)
• Develop a short DoW for WP10
• Milestones, deliverables
• Timing of experiments
• Linkages to other WPs
• Resources