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OPerational ECology
Ecosystem forecast products to enhance marine GMES applications
DG SPACE
Collaborative Project - small or medium-scale focused research project
Project Number: 283291
Deliverable No: D4.3
Date:
Title:
Workpackage:
4/11/2013
Contract delivery due date
Assessment of seasonal predictability for indicators of higher trophic levels in all
4 regions
Lead Partner for HCMR
Deliverable
Author(s):
Dissemination level (PU=public, RE=restricted, CO=confidential)
Report Status (DR = Draft, FI = FINAL)
Acknowledgements
The research leading to these results has received funding from the
European Community’s Seventh Framework Programme (FP7/20072013) under Grant Agreement No. 283291 for the project Operational
Ecology: ecosystem forecast products to enhance marine GMES
applications (OPEC)
OPEC Overview
“OPEC provides an enhanced capability to predict indicators of good environmental status
in European regional Seas“
The OPEC project (Operational Ecology) will help develop and evaluate ecosystem forecast
tools to help assess and manage the risks posed by human activities on the marine
environment, thus improving the ability to predict the “health” of European marine
ecosystems. The programme will focus on four European regional seas (North-East
Atlantic, Baltic, Mediterranean and Black Seas) and plans to implement a prototype
ecological Marine Forecast System, which will include hydrodynamics, lower and higher
trophic levels (plankton to fish) and biological data assimilation.
Products and services generated by OPEC will provide tools and information for
environmental managers, policymakers and other related industries, laying the
foundations for the next generation of operational ecological products and identification
of knowledge / data gaps.
OPEC will use the EU’s Global Monitoring for Environment and Security Marine Service as a
framework and feed directly into the research and development of innovative global
monitoring products or applications. This in turn will advise policies such as the European
Marine Strategy Framework Directive and Common Fisheries Policy, as well as the
continued monitoring of climate change and assessments of mitigation and adaptation
strategies.
www.marineopec.eu
Executive Summary
The main goal of this activity is to explore the predictability in time and space scales
for the HTL. This will provide significant information on how well the model skill
matches the timescales required by the marine resource managers. Five model
systems have been assessed; 2 in the Mediterranean, 1 in the NE. Atlantic, 1 in the
Black Sea and 1 in the Baltic Sea.
Relevance to Policy
To explore the potential predictability of the seasonal forecast, with a view of
defining operational services in the future for food web and commercial fish
descriptors is one of the core actions in the WP4.
Main Body
Introduction: A primary objective of OPEC is to explore the predictability at higher
trophic level, considering that the higher trophic level might exhibit much long time
scales than the lower trophic level. The predictability of a model is influenced by a
number of factors: initial conditions, the quality of external forcing functions (e.g.
meteorological forcing, open boundary conditions, freshwater and nutrient inputs)
and model process descriptions and parameterizations.
Core Activity:
Baltic
Description of the seasonal simulation experiment
Results
Summary of seasonal forecast experiment and lessons learnt
NW Atlantic
Description of the seasonal simulation experiment
Results:
Summary of seasonal forecast experiment and lessons learnt
Mediterranean/HCMR
The coupled hydrodynamic/biogeochemical model (POM-ERSEM) and the fulllife cycle anchovy model, along with the model setup (initial conditions, river inputs,
open boundary conditions) are described in deliverable D2.4 (www.marineopec.eu/downloads/OPEC_D2.4.pdf). The atmospheric forcing for the hindcast
simulation and seasonal forecast experiments was obtained from the regional
climate model HIRHAM5 simulation, provided by DMI (see D2.2 www.marineopec.eu/documents/deliverables/D2.2.pdf).
1. HTL sensitivity to atmospheric forcing
The atmospheric ensemble member forecast procedure, described in D4.2 was
implemented in the N. Aegean, in order to examine the response of the fish
(anchovy) biomass and distribution to the perturbation of the atmospheric forcing.
In Figure 1, the evolution of the anchovy biomass is shown for the different
ensemble members over the simulation period (3 years). The anchovy weight, as
well as zooplankton and temperature for different members are also shown in Figure
2. In the beginning of the simulation, the spread of the members is relatively small
both in terms of biomass and weight, since the members have the same initial
conditions. The spread in the adult anchovy biomass is small in the first year of the
simulation but is increasing in consequent years, as different numbers of early life
stages (egg production, larvae, juveniles) within members affect the next year
recruitment.
The anchovy weight is also significantly affected by zooplankton and temperature
that show an increased spread after the first year. The anchovy and egg abundance
distributions (Figures 3-4) in the perturbed members are similar to those of the
reference (unperturbed) simulation, as the fish main habitat is found in the coastal
river influenced areas. Although the spread of the temperature members in the second
year (1996) exhibit a noticeable spread the ecology in the coastal areas is mainly
driven by the coastal processes such as mixing and transport and the availability of
food which as written in [Tsiaras et al., 2012; Tsiaras et al., 2014] it is significantly
affected by the riverine inputs. In other words the effect of the temperature spread or
variability is masked.
In order to quantify the anchovy response to the ensemble members variability in
the low trophic level (zooplankton, temperature) that is related to the perturbation
of the atmospheric forcing, the members standard deviation has been normalized
(STD/members mean) for all different variables, as shown in Figure 5. Taking the
ratio between the anchovy biomass and zooplankton normalized STD (Figure 6), it
appears that zooplankton variability results in an about two times amplified
variability in the anchovy biomass. This amplification is rather interesting considering
that sensitivity experiments have shown that the general trend within the lower
trophic levels, is a dampening effect of the perturbation with increasing trophic level.
A quick explanation is that as mentioned above the anchovy biomass is
synergistically affected by the spread in the Temperature and in zooplankton.
Further studies will explore the role of each variable.
Summary of seasonal forecast experiment and lessons learnt
Developments in this area, sustained by improvements in data assimilation and
numerical modeling should further increase the value of the ensemble prediction
and promote its use in the small pelagic fish modeling. The use of ensemble methods
in the simulation of small pelagic fish will further convince users that ensemble
predictions are extremely valuable because they not only offer an estimate of the
most probable future state of a system but they also provide an estimate of the
range of possible future outcomes.
Figure 1: Anchovy adult, juvenile, late larvae biomass and daily egg production,
simulated by the ensemble members (red line) and the reference (un-perturbed)
simulation.
Figure 2: Anchovy weight for different stages (top) and average zooplankton (middle)
and temperature (bottom) at the adults location, simulated by the ensemble
members (red line) and the reference (un-perturbed) simulation.
Figure 3: Anchovy adult biomass distribution, simulated by the reference (unperturbed) simulation (top left) and the mean of the ensemble members (top right)
and ensemble members biomass STD (bottom).
Figure 4: Egg abundance distribution, simulated by the reference (un-perturbed)
simulation (top left) and the mean of the ensemble members (top right) and
ensemble member’s biomass STD (bottom).
Figure 5: Ensemble members normalized standard deviation (STD/members mean)
for adults (blue line), larvae (red line), Juveniles (green line), egg production (black
line), temperature (magenta line) and zooplankton (cyan line).
Figure 6: Ratio of members normalized STD (see Fig. 5) for anchovy adult biomass
over zooplankton.
References
Tsiaras, K. P., V. H. Kourafalou, D. E. Raitsos, G. Triantafyllou, G. Petihakis, and G.
Korres (2012), Inter-annual productivity variability in the North Aegean Sea:
Influence of thermohaline circulation during the Eastern Mediterranean Transient,
Journal of Marine Systems, 96-97, 72-81, doi:Doi 10.1016/J.Jmarsys.2012.02.003.
Tsiaras, K. P., G. Petihakis, V. H. Kourafalou, and G. Triantafyllou (2014), Impact of
the river nutrient load variability on the North Aegean ecosystem functioning over the
last decades, Journal of Sea Research, 86, 97-109, doi:Doi
10.1016/J.Seares.2013.11.007.
Mediterranean/OGS
Description of the seasonal simulation experiment
Results
Summary of seasonal forecast experiment and lessons learnt
Black Sea
Description of the seasonal simulation experiment
Results
Summary of seasonal forecast experiment and lessons learnt
Discussion and conclusion: summary of results across regions – any obvious pros
and cons of the different regional systems.