GREEN matrix UPloaded:
A new ecosystem variable for marine resources sector
Author: P. Lehodey ([email protected])
Date: 07/03/2016.
Version: v0
GREENUP
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GREENUP
The objective of GREENUP is to extent the CMEMS
products catalogue by developing a new product
covering a key ecosystem component at the mid-
trophic level, i.e., micronekton, to better address
the Marine Resources area of benefit.
Objective
Micronekton
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• Micronekton organisms at the intermediate trophic level (i.e.,
MTL: Mid-Trophic Level) are both prey of adult and predator of
eggs and larvae.
• Zooplankton are prey of larvae and juveniles of fish
• Zpk and MTL are two critical components of the system to
understand and predict habitats and behaviours of fish.
SURVIVING = Feeding + Avoiding predators + Avoiding unfavourable environment
Micronekton is central to understand fish behaviourMicronekton is central to understand fish behaviour
Zoopk
Micronk
eggs
larvae
REPRODUCING = Meeting congeners + Optimizing the survival rate of larvae (as above)
GREENUP
The missing link to the management of resources
Zooplankton and micronekton
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Davison et al (2013) estimated that migrant micronekton participate between <10% (mesotrophic) and >40 % (oligotrophic) of total carbon export in the Calcofi
region.
The biological
pump
GREENUP
Also a key component in the Carbon cycle (biological pump)
Micronekton: the missing link
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• No estimation about squids, deep shrimps, gelatinous organisms, …
• More recent studies based on acoustic suggest it is underestimated by one order of magnitude (at least).
• Only one global review of mesopelagic fish abundance to date, Gjosaeter and Kawaguchi (1980), based primarily on trawl surveys, and estimating
global biomass on the order of one billion tonnes.
Irigoien et al (2013)
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How to observe micronekton?
Source:
Rudy Kloser & Jock Young CSIRO,
Australia
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Kaardvelt et al (2012)
GREENUPHow to observe micronekton?
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Zooplankton: 1 functional group
Micronekton: 6 functional groups in 3 vertical layers; 3 groups with daily
vertical migrations
Dynamics: Time of Development linked to temperature (maturity = turn
over; mortality); Organisms drifiting with currents in their layers.
Forcing: Temperature, currents and Primary Production.
Parameters: 6 unknown parameters to define the energy transfer from PP
to functional groups. One optimization approach using acoustic data
References :
Lehodey et al 2010: Prog In Oceanog
Lehodey et a. 2015: ICES J.Mar. Sci.
GREENUPHow to model micronekton?
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Time of development in days (Log) of micronekton until age at
recruitment and maturity (tm) relatively to the ambiant water
temperature
Age at maturity:
797 d
255 d
88 d
199 d
64 d
22 d
Age at recruitment:
Dynamics:
Spatial dynamics:
Eulerian transport model = Density fluxes in each point of a grid according to advection (currents) + diffusion (accounting
for currents in vertical layers and the time spent in these layers)
GREENUPHow to model micronekton?
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Simulation
¼° deg x week
temperature & currents from MERCATOR-Ocean (+
corrections!)
& Satellite derived Primary prod.
Biomass distributions (2015) of epipelagic and
lower mesopelagic (non-migrant) biomass
GREENUPHow to model micronekton?
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GREENUPHow to evaluate micronekton?
Menkes C., Allain V. Rodier M., Gallois F., Lebourges-Dhaussy A., Hunt B., Smeti H., Pagano M., Josse E. Daroux A., Lehodey P., Senina I., Kestenare E., Lorrain A., and S. Nicol. (2015).
Seasonal oceanography from physics to micronekton in a south-west Pacific ecosystem. Deep Sea Research
Direct observation / comparison
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GREENUPHow to evaluate micronekton?
Parameters optimisation from data assimilation06-11-2005 Aus-NZ start lat-40.4317 end lat -40.689
Dep
th m
Longitude d.d150 152 154 156 158 160 162 164 166 168
0
200
400
600
800
1000
1200
150 152 154 156 158 160 162 164 166 168-95
-90
-85
-80
-75
-70
-65
mea
n S
v dB
Longitude d.d
10-80 m
80-400 m400-1000 m
Lehodey, P., Conchon, A., Senina, I., Domokos, R.,
Calmettes, B., Jouanno, J., Hernandez, O., and Kloser, R.
(2015) Optimization of a micronekton model with acoustic
data. – ICES Journal of Marine Science, 72(5): 1399-1412
Projects:
• OSMOSIS (ESA)
• Mycto3Dmap ( French ANR)
• MESOPP (H2020: EU-Australia)
• AtlantOS (H2020)
• AMORAD (French ANR)
One PhD: Anna Conchon
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GREENUPHow to evaluate micronekton?
Indirect observations
epipelagic MTL component
30 40 50 60 70 80 90 100 110 120 130 140 15050
45
40
35
30
25
Longitude (E)
Latit
ude
(S)
SBT tracking data (1998-2000) from S. Bestley (CSIRO)
Austral bluefin chase epipelagic prey in the subtropical
convergence
Elephant seals feed on deep forage, diving continuously between
400 and 1000 m !
Lower mesopelagic MTL component
GREENUPHow to evaluate micronekton?
Track of Seals leaving Kerguelen colony overimposed with micronekton (Thèse Lauriane Massardier,
Univ. Sofia Antipolis)
Indirect observations
GREENUPHow to evaluate micronekton?
Hernandez O., Lehodey P., Senina I., Echevin V., Ayon P., Bertrand A., Gaspar P., (2014).
Understanding mechanisms that control fish spawning and larval recruitment:
Parameter optimization of an Eulerian model (SEAPODYM-SP) with Peruvian anchovy
and sardine eggs and larvae data. Progress in Oceanography 123, 105-122.
Optimal parameterization of spawning
habitat based on eggs and larvae density
observations
Modeling
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GREENUPHow to evaluate micronekton?
Modeling
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Using directed movements along the gradient of habitat (temperature x
prey) + currentsUsing passive drift with currents only
Predicted distribution after one year of movements
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GREENUPProject overview
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GREENUPOrganization of the work
WP1: project coordination
Project management + Roadmap for a future transfer of the
R&D performed within this project
Management facilitated by proximity with Mercator-Ocean
and already well developed links
Only two other partners (well known)
Three project meetings: kick off, mid-term and final meeting
hosted in Toulouse (Mercator Ocean or CLS)
Participation to two CMEMS meetings and international
conferences to present the main results of studies and to
promote CMEMS.
=> Link with other project (MESOPP; ATLANTOS)
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GREENUPOrganization of the work
WP2: Prototype
- Atlantic forcing variables from C-MEMS
- Sensitivity of the MTL model to its forcing
(Feedback)
- Adding benthos group
- Improving parameterisation
- Hindcast simulations
Products Name Product Identifer
Physical
Global Ocean 1/12° Physics Analysis and Forecast
updated Daily
GLOBAL_ANALYSIS_FORECAST_PHYS_001_00
2
Global Ocean 1/4° Physics Analysis and Forecast
updated Daily
GLOBAL_ANALYSIS_FORECAST_PHYS_001_01
5
Global Ocean Physics Reanalysis GLORYS2V3 (1993-
2013)
GLOBAL_REANALYSIS_PHYS_001_009
Global Observed Ocean Physics Temperature Salinity
Heights and Currents Processing
GLOBAL_ANALYSIS_PHYS_001_016
Biogeochemical
Global Ocean Biogeochemistry Analysis and weekly
Forecast
GLOBAL_ANALYSIS_FORECAST_BIO_001_014
Global Ocean Biogeochemistry NON ASSIMILATIVE
Hindcast (PISCES) (1998-2013)
GLOBAL_REANALYSIS_BIO_001_018
Global Ocean Biogeochemistry NON ASSIMILATIVE
Hindcast (PELAGOS025) (1998-2013)
GLOBAL_REANALYSIS_BIO_001_019
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GREENUPOrganization of the work
WP3: Impact assessment
Two use cases:
-Atlantic mackerel
-Whales habitat
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GREENUPOrganization of the work
Left: Shifts in the observed spawning distribution of Mackerel between 2010 and 2013, as derived from Mackerel Egg Survey
observations. (M Payne, DTU Aqua, Unpublished data).
Right: Catch Per Unit Effort of juvenile mackerel at the age of zero in Oct-Dec 2005 and 2006. (from Jansen and Gislason, 2013)
Partner DTU-Aqua (Mark Payne)
Link to ICES stock assessment working group
Micronekton will be incorporated into existing forecast models for the distribution of
mackerel. These models use both near-real-time observations and forecasts of
environmental variables in an environmental-niche modelling framework to describe and
predict the distribution of this species: products updated on a regular basis (
www.fishforecasts.aqua.dtu.dk) and are being used to help design and implement
scientific surveys monitoring this fish population.
Model skill will be evaluated in the presence and absence of the micronekton product
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GREENUPOrganization of the work
Whales whatching is a valuable tourist
industry in Azores
Conservation measures require habitat
forecasting!
Partner Institute of Marine Research -
University of the Azores (IMAR-UAz),
Portugal
(Pedro Afonso; Mónica Almeida e Silva)
Link to a postdoctoral study (Frederic Van
Deperre)
Micronekton will help to predict local-scale habitats (e.g. General Additive Models and Maximum Entropy Models) and movements of marine top predators focusing on baleen whales. Data on whale
presence available from the European Ocean Biogeographic Information System (EurOBIS) at the ocean basin scale, and the Azorean Fisheries Observation Program (POPA) at the regional scale.
Performance will be evaluated by comparing predictive ability with that of models including only physical and biogeochemical variables
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Epipelagic layer
Upper
mesopelagic layer
Lower
mesopelagic layer
Noise
+++
++
+
+
++
++ ++
+
++
Observing System Simulation Experiments
$$$$$$$
Time series
Time
series
Transect
Bathymetry
< 1000m
GREENUPLink to other project
AtlantOS H2020
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GREENUPLink to other project
Mesopelagic Southern Ocean Prey and Predators
Participant no. Participant organization name Participant short
name
Country
1
(Coordinator)
Collecte Localisation Satellite CLS France
2 Antarctic Climate and Ecosystems Cooperative Research Center ACE-CRC Australia
3 Commonwealth Scientific and Industrial Research Organisation CSIRO Australia
4 Institute for Marine and Antarctic Studies - University of Tasmania IMAS Australia
5 British Antarctic Survey BAS United Kingdom
6 Université Pierre et Marie Curie UPMC France
7 Institute of Marine Research IMR Norway
8 University of St Andrews UA United Kingdom
9 Australian Antarctic division AAD Australia
Type of funding scheme: Coordination and support Action
Work Programme topic addressed: Call H2020-INT-INCO-2015
Total budget request: 1,061,689 Euros
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GREENUPPlanning and deliverables
Project Review: KO, Mid-term review, Final reviewQuaterly progress report
# Respon-sible Title Due
WP 1.1 CLS Kick-Off T0
WP 1.3 CLS Prototype Implementation T0+9
WP 1.3 CLS Products delivery T0+12
WP 1.2 CLS Mid-term Review T0+12
WP 3.3 DTU Impact Assessment feedbacks T0+21
WP 1.4 CLS Final Review T0+23
WP 1.4 CLS Roadmap for future implementation T0+24
List of milestones
# Respon-sible Nature Title Due
D1.0 CLS Report Quarterly progress reports
Every 3 months
from T0+3,
T0+21
D2.0 CLS Report Mid-term report T0+12
D3.0 CLS Report Final report T0+23
D4.0 CLS Report Roadmap for future implementation TO+24
List of deliverables