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Application Form MariFish Joint Call

MariFish Application form of 90

MariFish Joint Call

APPLICATION FORM for a transnational research project

For more information and guidance about completing and submitting applications see the Applicants’ Guide or contact the MariFish Call Secretariat ([email protected]).

Project Title (Acronym)

REPROdUCE: understanding REcruitment PROcesses Using Coupled biophysical models of the

pelagic Ecosystem.

This application is submitted under the topic area (please tick one): Stock – recruitment relationships with process understanding By-catches and discards Biological interaction between species Environmental impact of fisheries Economic indicators

1. Administrative Details

Applicant / Coordinator – Partner 1

Organisation Instituto Español de Oceanografía - IEO

Name of Contact

(incl. Title) Dr. Miguel Bernal Gender Male

Job Title Scientist (Investigador A4) Age 36

Postal Address Centro Oceanográfico de Cádiz Muelle de Levante (Puerto Pesquero) Aula del Mar, 11106 Cádiz. Apdo. 2609, SPAIN

E-mail [email protected]

Phone +34 956 261 333 (permanent) +1 732 932 3692 (current number)



Applicant – Partner 2

Organisation Hellenic Centre for Marine Research (HCMR)

Name of Contact

(incl. Title) Dr. Stylianos Somarakis Gender Male

Job Title Principal Researcher Age 41

Postal Address

Hellenic Centre for Marine Research Institute of Marine Biological Resources Former US base at Gournes P.O. Box 2214 Heraklion 71003 Crete, Greece


Phone +30 2810 337832


Organisation Institut français de recherche pour l'exploitation de la mer (IFREMER)

Name of Contact

(incl. Title) Dr Pierre Petitgas Gender Male

Job Title Researcher Age 46

Postal Address IFREMER, rue de l’Île d’Yeu, BP 21105, 44311 cdx 03, Nantes, France


Phone +33 (0)240 37 41 63


Organisation Centro Tecnológico de Investigación Marina y Alimentaria (AZTI)

Name of Contact

(incl. Title) Dr. Xabier Irigoien Gender Male

Job Title Section Head Age 42

Postal Address Herrera Kaia z/g, 20110 Pasaia, Spain


Phone 943004800




Organisation Instituto Portugues das Pescas e do Mar (IPIMAR)

Name of Contact

(incl. Title) Dr. Georgios Stratoudakis Gender Male

Job Title Senior Researcher, Reseearch Unit coordinator Age 38

Postal Address INRB/IPIMAR; Avenida de Brasilia s/n, 1449-006, Lisboa, Portugal


Phone 00351 213027099



2. Short Project Description

Project Title (Acronym)

REPROdUCE: understanding REcruitment PROcesses Using Coupled biophysical models of the pelagic Ecosystem.

Project duration 01/09/09 – 01/08/12

Project Aims

REPROdUCE will identify the main processes determining recruitment strength of two key southern European pelagic species (sardine and anchovy), and provide recruitment models that integrate information from the stock abundance, structure and distribution together with environmental data.

REPROdUCE focus on two case studies with large differences in their ecological characteristics and human exploitation patterns, the Bay of Biscay (Atlantic case study) and the North Aegean Sea (Mediterranean case study), and analyses the recruitment of small pelagic fish in relation to the state of the population (demography, structure and biomass – internal mechanisms) and the overall pelagic ecosystem, including human exploitation (habitat suitability, food availability and predation rates - external mechanisms). The project will build from available but scattered knowledge of processes and interactions working at different trophic levels of the pelagic ecosystem, integrating it into a full life cycle pelagic ecosystem model, centred on the role of small pelagic fish as key forage species of these ecosystems. Once developed, the ecosystem models will be used to tackle the main objectives of this project, by applying them to answer the following questions:

1- What are the main mechanisms driving recruitment (internal vs external mechanisms) and what are the links between those mechanisms?

2- Which of these mechanisms can be responsible for prolonged reduction of reproductive potential in sardines and anchovies, and what is the effect of the reduction in reproductive potential in population recovery rates?

3- Are the recruitment drivers identified coherent with current general ecological hypothesis on population expansion-contraction for small pelagic fish?

Project Objectives

•••• To develop conceptual models of the different trophic levels of the pelagic ecosystem for the project case studies.

•••• To develop and validate numerical integrated ecosystem models of the full-life cycle of sardine and anchovy within the pelagic ecosystem

•••• To identify the main recruitment drivers and their relative influence for small pelagic fish in the two case studies of the project.

•••• To develop recruitment based fishery indicators that allow to improve the short and medium-to-long term management of these stocks



Project Summary

Understanding the mechanisms that drive the recruitment process, i.e. the appearance of a new generation of individuals in a fish stock, remains one of the most challenging questions in fishery science. The ability to manage the human pressure on a fish stock, especially for small pelagic fish, largely depends on the ability to predict the abundance of new individuals entering the stock, as well as the effect that human pressure has on this process. However, the different biological processes that affect the abundance of recruits show a large and largely not understood variability in space and time. For the case of small pelagic fish, the difficulty in predicting recruitment strength increases, as a result of higher reproductive potential, larger mortality rates and a large dependence of both reproductive and mortality rates on environmental conditions.

Classical stock-recruitment or stock-recruitment-environment analysis fail to achieve acceptable predictive power levels, and provide little insight into the mechanism that generates recruitment variability. Reasons for this failure relate to the use of integrated or average quantities (i.e. biomass, recruitment, oceanographic indices) over large spatial and temporal scales, and the lack of underlying mechanistic hypothesis. A recent and promising alternative to these analyses is to use numerical models that allow simulating both the population dynamics and the surrounding environment, and test available and new hypothesis on stock-recruitment-environment relationships.

The objective of REPROdUCE is to develop and ensemble a battery of realistic simulation models of small pelagic fish full life cycle in two different ecosystems, to use these models to understand the main mechanism and drivers of the recruitment process, and to explore management scenarios and develop fishery indicators to assist in management decisions. The chosen case studies and key species are sardine and anchovy in the Bay of Biscay, and anchovy in the Aegean Sea.

The models will be developed in a modular approach, building up from existing knowledge and integrating models of ocean dynamics, nutrient and lower trophic levels, pelagic fish community, and, where possible, top-predators induced mortality. A variety of approaches, from detailed individual based models to habitat models, will be applied in each case study, and resulting models will be ensembled to provide a comprehensive description of the full life cycle of the species of interest. Additional work to develop and integrate the different modules from the existing knowledge is expected, in terms of model development and improvement of the empirical estimates of initial conditions and fluxes among model components. Also a large effort in the validation of the different components of the model, and the final model itself, will be required before the model is used to analyse the recruitment process. REPROdUCE will cope with the extra requirements using the extensive database and expertise available within the project consortium, and when required, designing extra field work to be carried out by the partners of the consortium within each national sampling plan. For the specific case of the Aegean Sea, where information on temporal patterns of anchovy spawning is lacking, ad hoc sampling surveys will be carried out to cover an entire spawning period of the species during the first year of the project. These surveys are expected to complement the available data, and to provide empirical information which can be used for model validation in this case study.

Once the life cycle models are built and validated, they will be used to generate hypothesis on the main potential drivers of recruitment strength and a series of contrasting simulation scenarios will be devised to test their relative influence. A series of assessment questions relevant to the management of each of the target stocks will be evaluated using the knowledge acquired through the project, and the developed life cycle models will be used to produce indices of recruitment strength to assist both in short- and medium- to long-term management.



Relevance to fishery management Recruitment strength is a key variable to manage the fluctuating stocks of sardine and anchovy in the two case studies of REPROdUCE. Anchovy in the Bay of Biscay is currently passing through a continued period of reduced recruitment potential, while sardine recruitment in this area shows a general low recruitment phase with periodic recruitment peaks. Management of anchovy in the area aims to keep biomass above a minimum biomass, but total allowable catches are set before direct surveys of recruitment are available, and are therefore based on assumptions. Both environmental and survey based juvenile abundance indexes have been proposed to provide estimators of recruitment, but are not currently used due to low predictive power (the former) or to short time series and unknown mechanisms linking juvenile abundance and recruitment (the later). Sardine in the Bay of Biscay is not managed as a unit, as the sardine stock currently under ICES management only includes the Iberian peninsula, and not the Armorican Shelf. However, the Armorican shelf is known to be a main recruitment area for sardine, and links between this shelf and the Cantabrian coast (North of Spain) are known to exist.

In the North Aegean Sea, the assessment of the anchovy stock started recently and it is evident that stock size is primarily driven by the strength of annual recruitment. Current management is however static and based on technical measures (mainly closed seasons and areas). A management Plan for the purse seine fisheries in Greece has been developed recently, in which the stock will be monitored routinely and managed adaptively in the future, e.g., effort and/or catch limits will be set annually based on stock status and recruitment predictions.

REPROdUCE has identified the following management questions to be tackled during the project:

Bay of Biscay

• Anchovy is currently under a situation defined as reduced reproductive potential and is not able to recover to previous levels of biomass. Can we identify which are the mechanisms that explain that the actual distribution/biomass is not able to produce enough recruits to return to previous biomass levels? • In good years, sardine egg production in northern Spain rise to similar levels than the ones found in the Armorican shelf, but recruitment in the former area is minimal in comparison with that in the later area. Can we explain why?

Aegean Sea.

• Management in the Mediterranean is based on technical measures and there are no quotas enforced. In the Aegean Sea, measures such as a 2.5 winter closed period for the purse seiners and several closed areas in coastal waters have been implemented since the early 60´s, without scientific support and assessment of their effectiveness. REPROdUCE will assess whether these areas and seasons are important for reproductive success and provide the knowledge required for the design of such closed areas and seasons.

Responses to these questions will improve both short term and medium to long term management of the target stocks. On the long term, understanding the mechanism by which a stock remains in a phase of low abundance will allow to devise measures to reduce the probability of these events and minimize the stock recovery time, with minimum social impacts. Also, assessing the efficiency of different management measures (spatial or temporal closures, reduced fishing effort, etc) under different environmental scenarios will allow devising more efficient long term management plans. In relation to short term management, REPRODUCE will evaluate the probability of obtaining different recruitment levels given current stock and environmental conditions, in order to improve the short term management of the stocks.

The development of recruitment indicators both for short and long term management will allow to establish more flexible management procedures for these stocks, like a two level management procedure in which the management of the stock adapts to periods of low or high stock biomass.



3. Detailed Project Description

Overview of Work Packages

General overview:

REPROdUCE is organised in two case studies, six Work Packages and a general management WP. WP’s are given a central role in the project, while case studies are used to provide contrast in the characteristics and responses of stock-recruitment relationships in different pelagic ecosystems. Although the main objective of the project is to analyse processes and drivers of small pelagic fish recruitment, the work packages cover a large portion of the pelagic ecosystem, as realistic models of the ecosystem are required to simulate and test hypothesis related to recruitment. A list of REPROdUCE WP’s is included in the table below:

Work Packages (WP)

No. of WP

Title

1 Hydrodynamic and lower trophic level models

2 Juvenile and adults: life cycle, within population diversity, habitat occupation, migration, growth, fecundity and mortality.

3 Models of early life stages dispersion and survival

4 Pelagic ecosystem model set-up and assemblage of model modules

5 Model validation, recruitment simulation scenarios and assessment of recruitment drivers

6 Synthesis and building of recruitment strength indicators

7 Project management

REPROdUCE scientific WP’s (i.e. WP 1 to 6) can be classified in two kinds of WP;

• WP 01, 02 and 03 are organised hierarchically, in a reductionist approach, to provide the required bricks to build-up a hydrodynamic biogeophysical coupled model of the life cycle of sardine and anchovy within the pelagic ecosystem.

• WP’s 04 to 06 are holistic WP’s in which the analysis of stock-recruitment relationships is carried out in the framework of interrelations of the whole pelagic ecosystem.

A large body of bibliography, data and general information on WP01 to 03 is already available through other recent and ongoing projects (see Organisation Roles, Expertise and Experience section) below for a list of project synergies), but has not been integrated in ecosystem models with full life cycle support. WP01 to 03 will therefore build up from existing knowledge, but with the aim to develop the modules required to obtain the ecosystem models which will be necessary to achieve the objectives of REPROdUCE. The main ecosystem model building and validation process, as well as its use to assess the influence of different drivers in the strength of recruitment, is carried out in WPs 04 to 06

A simplified view of the pelagic ecosystem and the organisation of REPROdUCE WP’s are shown in Figure 1. Small pelagic fish as sardine and anchovy (also known as “forage fish”) occupy intermediate trophic levels, in which a few species with a large biomass are



responsible to the energy flow from lower to upper trophic levels. These species and their relation with lower and upper trophic levels will be the focus of this project. The analysis of life cycles of sardine and anchovy has been separated into two WPs, WP02 (juvenile and adults) and WP03 (early life stages). The main reason for this is that early life stages are controlled by different processes as well as physiological and ecological rates. Passive early life stages are characterised by several orders of magnitude higher abundances and growth and mortality rates than active juvenile and adult stages. Survival and growth is therefore a main issue in the early life stages, while behaviour and reproductive capacity becomes a main issue in later stages. Coordination among these WPs will be ensured by close collaboration among the participant researchers, organisation of common meetings to develop common conceptual and operative models, and the general supervision of WP04.

Lower (Clima) and upper (Top predators) levels of the ecosystem diagram are not analysed through specific WP, but are included in the holistic WP’s. The required working models of ocean dynamics in relation to climate are already available for the case studies included in REPROdUCE (see Organisation Roles, Expertise and Experience section), and will be incorporated in the REPROdUCE ecosystem model within WP04 to 06. Inputs on top predator control on the small pelagic fish community and potential impact on their stock-recruitment relationship are also expected from other ongoing EU and national projects (Organisation Roles, Expertise and Experience section), and will be incorporated in the model building WP’s.

The flow of information between WP’s and towards the project synthesis WP is crucial for the REPROdUCE success. Therefore, the project structure relies on four coordination levels (see Figure 2): 1) WP04 coordinates the overall development of the modules required to build the final ecosystem model at three different levels; the construction of the conceptual models, the implementation of numerical models and the coupling of the different modules. WP04 also coordinates with WP05 to implement the required simulation scenarios for validation and for hypothesis testing on driver intensity. 2) WP05 coordinates the validation of the different modules and the ecosystem model, as well as data requirement for the validation and the design of simulation scenarios. 3) WP06 is the responsible for gathering all information obtained on recruitment drivers, from conceptual models of the different modules to the results of the alternative simulations carried out from the ecosystem model, and for the synthesis of the project results. 4) On top of the other WPs, the management WP (WP07) is the responsible of providing the necessary communication tools (WIKI web page, meetings, online meetings, etc.), make sure milestones are met and information is exchanged between REPROdUCE partners and WPs, and provide a link with the MARIFISH secretariat.

A variety of methodological approaches will be used within each WP. A list of available models and methods to build the different steps of a full life cycle pelagic ecosystem model is described in each of the WP. An important characteristic of REPROdUCE is the comparative approach between intrinsically deterministic Individual Based Models and probabilistic habitat characterisation methods. The use of probabilistic habitat-based ecosystem models is novel to the area, and the combination of both approaches is expected to provide further insight into the ecosystem in general, and into the processes that drive recruitment strength in particular.



WP 04, 05 & 06

WP03

WP02

Habitat

Spawning habitat

WP01

Small Pelagic Fish

Life patterns

Adult habitat

Clima

Ocean

Lower trophic

levels

Top predators

Potential Realised

Successful

Growth Migration

Reproduction

Figure 1: Simplified schematic diagram of the pelagic ecosystem and overimposed organisation of REPROdUCE Work Packages.



WP01 Conceptual

NPZ model

Numerical

module

Model

Validation

WP02Conceptual

Population

model

Numerical

module

Model

Validation

WP03 Conceptual

ELS model

Numerical

module

Model

Validation

Full life

cycle

module

Ecosystem

model

WP04

WP05Model validation &

design of simulation

scenarios

Coupling of ecosystem

modules

Conectivity of

numerical

modules

Coherence of

conceptual

models

Realistic scenario

Model validation

Alternative scenarios

Recruitment strength

indicators

Model simulation

Coordination

of module

validation

WP06Synthesis and building

of recruitment index

Potential

recruitment driversDriver intensity

Acquisition of extra

data for model

validation

Figure 2: REPROdUCE schematic workflow diagram and coordination between Work Packages. NPZ refers to Nutrient Phytoplankton Zooplankton models, and ELS refers to Early Life Stages model



Work Package Description:

WP01 : Hydrodynamic and lower trophic level models

• Work package Objectives

- To develop and validate an operative coupled physical-biogeochemical model (Nutrient, Phytoplankton, Zooplankton and Detritus model: NPZD type) with suitable components for a coupling to fish different life stages.

• Participants

AZTI (coordinator: Xabier Irigoien), IEO, IFREMER, HCMR

Participant name IEO HCMR IFREMER AZTI IPIMAR

Person-months per participant 23 8 15 10 --

• Programme of work

Lower trophic levels are directly controlled by geochemical nutrient cycles and ocean-climate conditions, and control the amount of energy available to upper trophic levels at the same time. Since the early 90’s a number of mass-balance models linking nutrients to phytoplankton and zooplankton biomass, modulated by simple environmental indices (light, temperature) have been developed (Fasham, 1993). After the outcome of hydrodynamic models at different scales and levels of precision (e.g. POM, Blumberg and Mellor, 1983; HAMSOM, Backhaus, 1985), coupling lower trophic level dynamic models with spatial explicit hydrodynamic models of the ocean has been a top priority to understand the dynamics of both coastal and open ocean ecosystems. A number of successful applications of coupled physical - nutrient-zooplankton-phytoplankton-detritus (NPZD) models are currently available (e.g. Allen et al. 2001, see a review in Werner et al. 2006). Hydrodynamic models of high spatial and temporal resolution have been applied to the Bay of Biscay by Ifremer, IEO and AZTI: models MARS (e.g. Lazure et al. 2009), ROMS (e.g. Otero et al. 2008a; Ferrer et al. 2009) and OPA (Friocourt et al. 2008a,b). Lower trophic models coupled to 3D hydrodynamic models have also been configured in the Bay of Biscay (e.g. Siddorn et al. 2007; Huret et al. 2007). In the Aegan Sea, the POM and ERSEM models have been elaborated within a series of large operational programs of HCMR (e.g. Korres and Lascaratos 2003; Ahumada and Cruzado, 2007)) and are currently fully implemented. Involved institutions have devoted effort to development of predictive models for operational purposes and daily results are or have been posted on web sites, e.g. Previmer Web: http://www.previmer.org/previsions/temperature_et_salinite and AZTI web of predictions: http://www.azti.es/impres/.

Work Package 1 will review the available data and knowledge on the lower trophic levels in the case study areas, develop a conceptual model which represents the main groups and processes affecting the nutrient and lower trophic levels within each ecosystem, and assemble an operative NPZD model to simulate the dynamic of these components of the ecosystem. The outputs of the model, including direct (temperature, salinity, food availability and composition) and indirect (vorticity, turbulence, fronts, stratification) hydrodynamic and biological variables, will be used as bottom-up forcing affecting fish physiology and behaviour.



These drivers will be integrated in habitat and individual based models within WP 02 and 03 (see WP02 and 03 descriptions). Interactions between lower trophic levels models developed in WP01 and forage fish life cycle models developed in WP02 and 03 will be ensured by the WP on general model construction (WP04).

Action 1: Review of literature, identification of available models in each case study

The different available coupled hydrodynamic-NPZD models will be reviewed, as well as a list of relevant environmental and biological variables for both case studies. The potential effect of physical variables in lower trophic levels (e.g. circulation, temperature, food conditions, vorticity, stratification, etc.) as well as the possible propagation of these effects in the trophic web will be discussed based on existing hypothesis.

Lack of data necessary for the calibration and validation of models will be assessed in order to evaluate uncertainties (Action 3). Similar or complementary approaches developed in other regions will also be reviewed. Based on these reviews, development and implementation of the lower trophic levels will be performed in Actions 2 and 3.

Associated deliverables:

- D1.1: Review of potential bottom-up forcing (climate-ocean and lower trophic levels) of intermediate trophic levels, in coordination with WP02, and 03

- D1.2: Review of available hydrodynamic-NPZD models for both case studies, and of available and lacking data or information necessary for validation and good representation of key processes identified in D1.1.

Action 2: Update of the different modules of the existing lower trophic levels models, taking into account the requirements of wp2 and wp3

Based on the reviews of Action 1, the existing conceptual NPZD models will be revisited, the adequacy of each of them to each case study will be evaluated, and either one of the existing conceptual models will be adopted, or a new NPZD model will be developed, including the main elements and forcing functions in both case study ecosystems. Food availability and condition play an important role in fish physiological and behavioural models, while at the same time forage fish predation rates plays an important role in the dynamic of lower trophic levels. Therefore the conceptual model will be developed in close coordination with WP02 and WP03 (coordination ensured by WP04 and a dedicated meeting for the development of conceptual models for each module).

Simulated primary production is often used as a proxy for food conditions, as it has been validated in a larger number of lower trophic levels models than secondary production, and it is therefore believed to be more reliable. Requirements to use zooplankton as the “currency” (food availability) between NPZD models and forage fish will be evaluated, and implemented in the conceptual and numerical models (see Action 3 below). Thus, a special effort will be performed to develop size-based modules of phytoplankton and zooplankton, in order to link them with fish models.


- D1.3: Adoption of a conceptual NPZD model with main climate forcing and main energy flow to intermediate trophic levels representation for both case studies

- D1.4: Report on adaptation needed in present hydrodynamic-NPZD models to correctly transfer energy to different stages of key forage fish species in both case studies



Action 3: Models implementations and comparison between the case studies, check model sensitivity to assumptions, and identify model uncertainties

Once the conceptual model of each case study is developed, the capability of existing NPZD models to implement all the model compartments and functional relations will be evaluated. Based on the available models coherent with the conceptual models for each case study, an operative NPZD model will be assembled, in coordination with WP02, 03 and 04. The models used for each case study should be comparable in terms of atmospheric and hydrologic forcings, space and time scales and conception. Especially, the importance of the mesoscale processes will be taken into account.

A validation effort will be performed in terms of hydrodynamic processes and lower trophic levels variables (especially primary and secondary productions). The validation of most of existing hydrodynamic-NPZD models is already ongoing for projects outside REPROdUCE. The WP01 will check that the hydrodynamic-NPZD models’ outputs will be reliable in order to be used in WP02 and WP03.

Hindcast runs of coupled hydrodynamic-lower trophic levels models will be performed on years when data sets are available to assess the reliability of the outputs. A series of validation criteria will be developed in coordination with WP05. Potential validation criteria include nutrients and chlorophyll concentration, as well as zooplankton fractionated dry weight, For each case study, a short series of hindcast runs will be compared with the validation criteria, and model adjustments will be made if required.


- D1.5: Report on the consistency of available numerical models with the conceptual models for each of the case studies, and comparability of the available models in terms of forcings, scales and conception.

- D1.6: Simulated forcing fields for “offline” (i.e. non-interactive one way coupling; fish prey on NPZD models, but NPZD models are not subsequentially updated) WP02 and WP03

- D1.7: Report on potential validation criteria for lower trophic level models, as well as initial validation tests, in coordination with WP05

• List of WP01 Deliverables

Deliverable Institute responsible

Deliverable Date

D1.1: Review of potential bottom-up forcing (climate-ocean and lower trophic levels) of intermediate trophic levels, in coordination with WP02, and 03

AZTI Month 06

D1.2: Review of available hydrodynamic-NPZD models for both case studies, and of available and lacking data or information necessary for validation and good representation of key processes identified in D1.1

IEO Month 06



Deliverable (cont.) Institute responsible

Deliverable Date

D1.3: Adoption of a conceptual NPZD model with main climate forcing and main energy flow to intermediate trophic levels representation for both case studies

AZTI Month 08

D1.4: Report on adaptation needed in present hydrodynamic-NPZD models to correctly transfer energy to different stages of key forage fish species in both case studies

IFREMER Month 10

D1.5: Report on the consistency of available numerical models with the conceptual models for each of the case studies, and comparability of the available models in terms of forcings, scales and conception.

IEO Month 11

D1.6: Simulated forcing fields for “offline” (i.e. non-interactive one way coupling; fish prey on NPZD models, but NPZD models are not subsequentially updated) WP02 and WP03

AZTI Month 15

D1.7: Report on potential validation criteria for lower trophic level models, as well as initial validation tests, in coordination with WP05

HCMR Month 20

• Milestones

Milestone number

Short description WPs involved

Expected Date

Verification

M3 Conceptual models Workshop ALL Month 6 Workshop held M4 Report on conceptual models for all

modules and overall REPROdUCE conceptual model

4(coord) ALL

Month 8 Report produced

M5 Annual meeting: adoption of numerial models for each module

ALL Month 11 Meeting held: Models adopted

M6 Completion of initial un-coupled simulations for all modules

1-3 Month 18 Demonstration simulations available

M7 Report on validation indexes for all modules

5(coord) ALL

Month 20 Report available to all modules

M8 Annual meeting + workshop on coupling the different modules

ALL Month 21 Meeting held: Workshop made

M9 Report on module validation results 5(coord) ALL

Month 24 Report available



WP02: Juvenile and adults: life cycle, within population diversity, habitat occupation, migration, growth, fecundity and mortality

• Objectives

- To identify main processes that affect non-pasive phases of sardine and anchovy in both case studies and to develop a spatially explicit full life cycle model of these species in relation to the environment, in coordination with WPs 01, 03 and 04.

• Participants

IFREMER (coordinator: Pierre Petitgas), HCMR, IEO, IPIMAR, AZTI


Person-months per participant 23 33 19 1 6


Full life cycle models coupled with lower trophic levels and hydrodynamic models have recently attracted large attention from the scientific community, as they are one of the main tools to understand the effect of variable and changing climate (see for example recent reviews in Werner et al., 2001; Travers et al., 2007; Checkley et al., 2009). Simulation of the full life cycle has also recently become a fundamental tool to understand the mechanisms that govern the stock-environmental-recruitment relationship (e.g., ICES, 2008; Checkley et al., 2009). A few implementation of Individual Based Models (IBM) of the full life cycle of fish are already available in different parts of the world (e.g. Megrey et al., 2007). Another promising field is the use of population and/or habitat based spatially explicit full life cycle models (e.g., Christensen et al., 2009; Ruiz et al., 2009), where the abundance and distribution of adults and offspring’s are modelled in relation to the environment and other predator and prey species. In the two Case Studies of REPROdUCE, different implementations of both IBM full life cycle models (Pecquerie, 2007) and models of different kind of habitats - potential, realised and successful - (Bellier et al., 2007; Bernal et al., 2007; Planque et al., 2007 for the Case study of the Bay of Biscay; Somarakis and Nikolioudakis, 2007 for the Aegean Sea) have been recently published. However, none of these models focused on understanding the recruitment drivers.

Life cycle models for sardine and anchovy for the two case studies of REPROdUCE will be developed between WP02 and 03, and coupled with NPZD models in WP04. WP02 will focus on the non-planktonic parts of the life cycle (juveniles and adults) and their effects on recruitment success. WP02 will develop a suite of models for a list of processes in these life stages. The models will be spatially-explicit and forced by fields that are outputs of lower trophic and hydrodynamic models as well as fields of predator or competitor species. Two complementary approaches will be developed. Habitat models will be developed for each of the life stages, and spatialised population dynamics will be embed within the habitat models using different ecological hypothesis on the use of potential habitat in relation to population abundance (i.e. McCall, 1990; Bakun, 1996; Petitgas et al., 2006). These models will be able to track spatiotemporal dynamics of abundance and recruitment potential, but will not take into account within population diversity. Another approach will be the development of IBM models for juveniles and adults that include bioenergetics, contingent diversity, fish movement and interaction between congeners. IBMs will allow to later investigate the effect of particular life histories in space and time on the reproductive potential.



While IBMs track the processes affecting individual life histories and thus have the potential to provide insight on the mechanisms and interactions driving recruitment, they require complex parameterisation. Habitat and population dynamics models (e.g. Christensen et al., 2009) attempt a compromise between a required level of detail and model complexity. Together, the use of both IBMs and habitat based models are expected to provide a better chance of defining the complexity/understanding required to address medium to long term trends of stock-recruitment links.

Action 1: Review of knowledge, data available and definition of conceptual models for the case studies

The different models and approaches to integrate the full life cycle will be reviewed. A list of processes during juvenile and adult stages will be reviewed, which can potentially affect the spawning initial conditions for the eggs and larvae IBMs. Available data on the main case study pelagic species will be reviewed that are relative to abundance, distribution, behaviour, spawning, growth, mortality as well on the species physiology and trophic level. The data will be assembled for the project purpose to evidence sensitive stages/conditions. Based on these reviews, conceptual models will be defined in each case study. In coordination with WP05 (actions 01 and 02), lack of knowledge will be identified and plans for acquisition of missing data required for the parametrization, calibration and validation of models (e.g., isotopes, energy density, seasonal patterns) will be devised.


- D2.1: A list of processes that are potentially influential on the initial conditions for larvae life IBMs and recommendations for model building.

Action 2: Habitat modelling

Two approaches will be developed, one statistical that captures the dynamics in space and time of population abundance and the other individual-based and determistic that formulates physiological conditions and behaviour. The predicted distributions will be made variable in time by updating the forcing fields. The statistical approach will make use of a variety of methods (e.g., GLMs, GAMs, EOFs, geostatistics). Fish spatial distributions will be modelled as a response to lower trophic model outputs, predators or other competing species as available, and population internal characteristics (e.g., demography, biomass). Multinomial models will be used to describe multispecies habitat preferences for the whole pelagic community, using acoustic and fishery independent sampling hauls. The individual-based approach to habitat mapping will make use of bioenergetic models (developed in action 3) to estimate the suitability of temperature and food conditions (output series of the lower trophic models) for growth and reproduction. The use here of bioenergetic models is to identify at each time the areas of potential suitability/unstuitability in the maps of environmental conditions.

In both approaches, hindcast runs of lower trophic models as produced by WP1 will be used to estimate historical long-term series of habitats. From these, critical conditions will be identified that affect spawning windows (location, timing, duration, etc.) as well as fecundity.


- D2.2: A report on the procedures and the resulting seasonal maps of potential, suitable and unsuitable habitats, for juveniles and adults of the target species in the case studies.



- D2.3: A report on multinomial habitat models and their potential to provide probabilistic habitat and abundance distribution.

- D2.4: A report on the identification of critical conditions that potentially affect spawning windows (location, timing, duration) as well as fecundity.

Action 3: individual-based modelling of growth, fecundity and mortality

Bioenergetics models will be developed to predict individual growth and reproduction as a function of time series of food and temperature (and individual fish state initial condition). These will be useful to map potential suitability of habitats. Options to formulate the effect of competing species and predators on growth will be considered. For that distributions of all pelagic species and predators will be useful.


- D2.5: A description of validated bioenergetic models for the species in the different case studies that predict growth and reproduction.

Action 4: Individual-based modelling of migration

Size-dependent and/or energy-dependent fish movement (migration) will be modelled explicitally or constrained. In this work, seasonal maps of habitats and vertical behaviour will be useful. Seasonal information from scientific surveys, commercial activity or sentinel surveys will be used for validation.


- D2.6: A list of rules that define at each time step how the fish is displaced and propositions to implement them.

Action 5: Population level representation and identification of validation criteria for juvenile and adult modules

Building on the maps of habitats for juveniles and adults generated by the habitat models, multi-site spatialised population models will be developed (e.g., matrix models) and parameterized. Options on how to spatialize growth and mortality will be considered.

In the IBM approach, within population diversity will be modelled and different options considered. One of them is to consider contingents with different characteristics in terms of physiology, displacement and spatial memory. Options on how to model the interaction between individuals or/and species will be developed so as to model at population level density-dependent habitat selection as well as conservatism/innovation of migration routes. Different scenarios for the population states and the individual states will be defined. In both approaches, connexion of the models with IBM larvae models will be necessary to close the life cycle.

A series of validation criteria will be developed in coordination with WP05, both common to IBM or habitat based models (i.e. population abundance and distribution) and specific to the different models (i.e. migration rates or occupation of potential habitat)


- D2.7: The description of options to spatialize growth and mortality parameters.

- D2.8: The description of the developed procedures to model within population diversity with IBMs; propositions on how to integrate individual histories at population level.



• List of WP02 deliverables


Deliverable Date

D2.1: A list of processes that are potentially influential on the initial conditions for larvae life IBMs and recommendations for model building.

IFREMER Month 08

D2.2: A report on the procedures and the resulting seasonal maps of potential, suitable and unsuitable habitats, for juveniles and adults of the target species in the case studies.

IFREMER Month 22

D2.3: A report on multinomial habitat models and their potential to provide probabilistic habitat and abundance distribution.

IEO Month 22

D2.4: A report on the identification of critical conditions that potentially affect spawning windows (location, timing, duration) as well as fecundity.

IFREMER Month 22

D2.5: A description of validated bioenergetic models for the species in the different case studies that predict growth and reproduction.

IFREMER Month 24

D2.6: A list of rules that define at each time step how the fish is displaced and propositions to implement them.

IFREMER Month 24

D2.7: The description of options to spatialize growth and mortality parameters.

IFREMER Month 24

D2.8: The description of the developed procedures to model within population diversity with IBMs; propositions on how to integrate individual histories at population level.

IFREMER Month 24

• WP02 related milestones

Milestone number


Expected Date

Verification



4(coord) ALL








(cont.) Milestone number


Expected Date

Verification


5(coord) ALL








WP 03: Models of early life stages dispersion and survival

•Objectives

- To identify main processes that affect passive, early life stages of sardine and anchovy in both case studies and to develop a spatially explicit full life cycle model of these species in relation to the environment in coordination with WPs 01, 02 and 04.

•Participants

IFREMER (coordinator: Martin Huret), HCMR, IEO, AZTI



4- Programme of work

Recruitment success is multicriteria and builds on many small scale processes occurring during a long period of time (several months) over large areas (geographical distribution area of populations) and involving large numbers of individuals (~1012). The early life stage has long been recognised as a critical period (Hjort, 1914) and much work has been dedicated to understanding the mechanisms of larval drift and survival and their modelling using Individual-Based Models (IBMs: Miller, 2007). Yet, the initial conditions for the eggs (spawning location and timing, amount of reserves, amount of eggs) constitute a lack of knowledge which is determinant for the predictability of the larvae IBMs (Gallego et al., 2007). Therefore, it is important to consider the critical period of the early life stage into a larger understanding of the many controls at all stages of the life cycle (juvenile survival in winter, growth and fecundity of adults, habitat occupation and migrations).

Work Package 3 will focus on early life stages (from egg to early juvenile), and their key role in the recruitment process, will link with WP02 to build up a full life cycle model of sardine and anchovy in the Bay of Biscay, and anchovy in the Aegean Sea, and with WP01 and WP04 to couple the full life cycle model with lower trophic levels and hydrodynamic models. The main reason for the separation between WP02 and WP03 is the direct dependency of the planktonic stages on the hydrodynamics, leading to a necessary coupling with circulation model for advection of individuals. Another reason is that numbers and rates of processes related to these stages are orders of magnitude higher than later in the life cycle. As an example, larvae IBMs need lower trophic levels forcing at the resolution of lower trophic models (i.e. few minutes) whereas daily or weekly forcing will be sufficient for adult habitat models. Thus specific modelling approaches with specific spatial and temporal resolutions are employed to tackle this part of the life cycle.

Development within REPROdUCE will build on recently developed IBM modules in each case study. For anchovy in the Bay of Biscay, an IBM was build simulating growth and mortality (Allain et al. 2003; Allain et al. 2007a) from larval and juvenile otolith daily rings analysis. The model was coupled to the hydrodynamic model MARS3D to investigate effects of different years environment forcing and spawning distribution (Allain et al. 2007b). In parallel a model of egg vertical distribution was validated on several species, among them anchovy (Petitgas et al., 2006). For the Aegean Sea, an off-line IBM tool has been recently developed within the EU SARDONE project. Individual groups of eggs and larvae are released as Lagrangian particles and this tool is off-line coupled with models providing physical and biological factors (such as velocity field, temperature and salinity from the POM hydrodynamic model, and biological



parameters, such as zooplankton, from the ERSEM biogeochemical model).

The previous studies are still under development progress to integrate better parameterization of several processes. These new developments will be realized in part within REPROdUCE, and will take advantage of recent new field surveys in the Bay of Biscay (Ifremer ECLAIR early life stages survey in 2008, surveys related to the Spanish program ECOANCHOA), as well as planned surveys on early life stages in the North Aegean Sea. Process to be considered and improved correspond to those known as poorly constrained by the community (Gallego et al. 2007) ; they relate to small scale physical processes (turbulence) impacting transport and feeding, vertical migration behaviour at different larval stages, feeding on specific prey fields, predation and mortality. Also models will consider time and space species interactions and will need for those biomass fields of species of interest as predator fields. Role of intraguild predation between anchovy and sardine at early life stages on recruitment will then be investigated.

Action 1: Review of data available and process knowledge acquired so far on behaviour, growth and mortality for early life stages of key species in both case studies.

A consequent amount of data has been collected in both case studies (gut content, energy density, growth rates from otolith daily rings, vertical distribution...see available data to the project in case study descriptions). These data use will first be reviewed and further analysed when necessary in view of process implementation in models.

Lacking information will be identified. For specific processes complementary efforts of data collection at sea and analysis may be necessary. For example, feeding at different sizes of larvae would be more accurately described using stable isotopes.

A specific effort will be done on mortality. A review of different means of assessing this information from indirect measurements will be investigated (e.g. differential growth curve between larvae and juveniles, successive larvae sampling), together with the possibility to improve our knowledge on this process in our case studies. Knowledge from other similar systems with similar species will also be gathered in order to fill gaps of information when data collect is not possible in our case studies.


- D3.1: Report on literature review on process knowledge (feeding, egg development rates, growth, mortality, behaviour) for anchovy and sardine of both case studies.

- D3.2: Report on lacking information and solution/hypothesis to fill these knowledge gaps.

Action 2: Definition of a conceptual model for each case study, comparison between the case studies and with other areas.

Based on the process knowledge of each species within each case study, a conceptual model of the all life cycle of both pelagic species within their ecosystem will be proposed.

The conceptual model will comprise:

a) A spatial dimension related to the spawning habitat definition and with a transport sketch of passive propagules.

b) An interaction with lower trophic levels (with size/stage dependent food consumption of larvae).



c) An interaction between pelagic species of interest (i.e. is there an intraguild predation on eggs/larvae? A spatial/temporal overlap of different species at different development stages?)

This conceptual model will give insights on the variability imposed by climate and bottom-up forcing variability, and how the response may transfer to early life stages.

It will sketch existing hypothesis about main drivers of the recruitment (on our case studies or other systems) to the different components of the model through detailed qualitative processes.


- D3.3: Conceptual models for each case study and species, including an accurate an qualitative summary of the main processes and model stages for the early life stages

- D3.4: Identification of the main forcing functions in the conceptual model potentially responsible for recruitment variability.

Action 3: State of the art, identification of available models representing fish early life stages in each case study and lacking important processes.

Models developed so far in each case study will be presented and pros/cons detailed. These are up to now Individual Based Models. Limitations of these models will be identified, with respect to important processes identified in action 1 and conceptualised in action 2. Likely, complementary developments will be needed, and will concern vertical behaviour of larvae, feeding on specific prey sizes instead of an actual bulk phytoplankton or zooplankton biomass, for which new development in WP1 are proposed (see WP1 description), and mortality.

Focusing on the biology, recent developments of bioenergetic models will also be reviewed. First attempts have been done in our case studies. For the northern Aegean Sea a bioenergetic model reproduces the growth of the E. encrasicolus (larvae+juveniles+adults) in a one-way linked configuration with the lower trophic level ecosystem model. In the Bay of Biscay, a bioenergetic model has been implemented to follow growth of larvae to the juvenile stage, with temperature and prey fields provided by the lower trophic level model. These new developments need to be dynamically linked to current operational IBMs.

Distinction will be made between process study models, generally focusing on the individual scale response, and population response potentially allowing a quantification of the recruitment process. Methodologies allowing the scale transfer from individual to population, with conservation the individual variability, will be investigated.

The choice of model will be done in projection of a future coupling to build up an ecosystem model in WP4, and in relation to its ability to answer the question on main drivers for recruitment.


- D3.5: Report on state of the art on available numerical early life stages models, with special stress on whether the models include main processes identified in the conceptual models developed in Action 3 above, and their respective advances towards building a full life cycle ecosystem model.



Action 4: Implementation of a battery of numerical models which adequately represent the conceptual model in each case study and species, check model sensitivity to assumptions, and identify model uncertainties.

Existing numerical models reported in Action 3 above which are considered appropriate representations of the conceptual models developed in Action 2 will be implemented. Whenever possible, different model approaches will be integrated as unique implementations, or else a series of complementary models will be implemented, in order to maintain a comprehensive modelling representation of the early life stages. New process identified as being necessary will be implemented in actual modules. Only those models that can be coupled with later life stages (juveniles and adults) and with the lower trophic level models developed in WP01 will be put forward as potential models to simulate early life stages of the species of interest.

Model will be run on years when consequent data is available to test its efficiency in representing the conceptual model, look at sensitivity to assumptions on unknown processes (mortality being the major one), and identify where major model uncertainties remain. A series of validation criteria will be developed in coordination with WP02 and WP05, and retained early life stages will be validated against those criteria using statistical analysis. Potential validation criteria include spatial distribution of eggs and larvae, spatially explicit larvae growth, overall larval survival and recruitment time series.


- D3.6: Report presenting comparative model runs between retained ELS models for selected years and lower trophic level distribution and abundance fields.

- D3.7: Definition of ELS validation criteria in coordination with WP02 and WP05 and report of initial module validation.

•List of WP03 Deliverables


Deliverable Date

D3.1: Report on literature review on process knowledge (feeding, egg development rates, growth, mortality, behaviour) for anchovy and sardine of both case studies.

IFREMER Month 06

D3.2: Report on lacking information and solution/hypothesis to fill these knowledge gaps.

HCMR Month 06

D3.3: Conceptual models for each case study and species, including an accurate an qualitative summary of the main processes and model stages for the early life stages

IFREMER Month 08

D3.4: Identification of the main forcing functions in the conceptual model potentially responsible for recruitment variability.

IEO Month 08



Deliverable (cont.) Institute responsible

Deliverable Date

D3.5: Report on state of the art on available numerical early life stages models, with special stress on whether the models include main processes identified in the conceptual models developed in Action 3 above, and their respective advances towards building a full life cycle ecosystem model.

HCMR Month 11

D3.6: Report presenting comparative model runs between retained ELS models for selected years and lower trophic level distribution and abundance fields.

IFREMER Month 18

D3.7: Definition of ELS validation criteria in coordination with WP02 and WP05 and report of initial module validation.

HCMR Month 24

•••• WP03 related milestones

Milestone number


Expected Date

Verification



4(coord) ALL







5(coord) ALL








WP 04: Pelagic ecosystem model set-up and assemblage of model modules

• Objectives

- Coordinate the development of WP01 to WP03 conceptual and numerical modules

- Develop model implementations for sardine and anchovy in the Bay of Biscay and the Aegean Seas using full life cycle coupled physical-biogeochemical models.

- Implement different climate and fishing pressure scenarios devised in WP05 to test the relative influence of the different drivers of recruitment strength

• Participants:

IEO (IEO + IMCS; coordinator Enrique Curtchitser), HCMR, AZTI, IFREMER




End-to-end models which couple hydrodynamic, lower trophic level and full fish life cycle models are rapidly developing and are expected to provide some of the required tools to improve the understanding of marine ecosystems (Hannah, 2007; Travers et al., 2007; Lett et al., 2009). Yet, many difficulties remain, such as finding validation data, determining the appropriate model complexity level to achieve certain goals and the need to integrate a variety of scientists, from physics to biologist and from modelers to observationalist (Hannah, 2007). Different examples of hydrodynamic models coupled to lower trophic levels, larvae models or fish dynamics models, both worldwide and in the two Case Studies covered by REPROdUCE are presented in WP01, 03 and 02 respectively.

The main task for WP04 is to coordinate the implementation of the conceptual and numerical models described in WP 01-03. This is a critical task for the success of any inter-comparison that can be achieved between the models, and the use of model output for the building of recruitment indices. In particular, WP 04 focuses on the implementation and evaluation of a coupled physical/biological ecosystem models. The physical models are three-dimensional hydrodynamic models and the biological models are full life cycle models for sardine and anchovy in the Bay of Biscay and anchovy in the Aegean Sea. In order to achieve this, WP04 will coordinate the sequential steps in building the different modules of the final ecosystem model, from the original development of conceptual models of WP’s 01 to 03 to the development of the numerical implementations of these models. Once coherent models are built, they will be coupled together, and the resulting model will be used to analyse the effects of the recruitment drivers identified in WP02 and 03. Also, simulation scenarios devised in WP05 to quantify the relative influence of the main drivers, as well as alternative management scenarios, will be coded into the model within WP04.

A variety of approaches and modelling techniques, especially the use of both Individual Based Models and population/habitat based models will be used in WP01 to 03. One of the scopes of WP04 is to coordinate the coupling of the different models used, to evaluate the strengths and weakness of the different approaches and to ensemble the results in order to take advance of the different perspective of the ecosystem given by the different approaches.



Action 1: Evaluate and inter-compare (physical) model implementations both in the Bay of Biscay and the Aegean Sea, in coordination with WP01 and design a strategy for integration of the different ecosystem modules with the physical model.

As part of this effort, a consistent set of metrics will be applied to the various model components in order to evaluate their relative skill in a given region. This will be done in close collaboration with WP 05 which is tasked with designing a strategy for an overall coupled model validation. Communication between WPs will be achieved making use of online facilities provided by WP07 (WIKI, weminars, videoconference, etc.), designing specific protocols to facilitate interchange of information related to the different tables (common tables, documents, etc), as well as physical meetings as detailed in the milestones list.


- D4.1: Review of available full life cycle models for small pelagics; pros and cons and applicability to the case studies and species analysed in REPROdUCE of the different approaches.

- D4.2: Design of a road map to obtain modules which describe the different main elements of the ecosystem that can be later coupled together (communication with the other WPs)

Action 2: Compile data requirements for the ecosystem modules, and identify possible additional requirements for coupled models in coordination with WP05; design a strategy when data is not available (e.g., for predictions use a super-ensemble approach).


- D5.3 (coordinated by WP05): Coordination with WP05 to report data requirements and plans for obtaining the data

Action 3: Couple the ecosystem physical to the sardine and anchovy models in the two regions of interest.

This is the most time-demanding action item of WP 04. The coupling between the lower- and higher-trophic level models will require a strategy for the feedbacks that develop when fish eat zooplankton. In particular, if the fish are represented as IBM’s and the zooplankton as (Eulerian) biomass concentrations. We will need to test various numerical strategies to ensure both model stability and skill. Also, spatially explicit mortality fields for the target species will be implemented, taking into account both natural and fishing mortality.


- D4.3: Implement a coupled physical-ecosystem model (spatially explicit, full life cycle) in the two regions of interest.



Action 4: Evaluate model sensitivity to uncertainty in the forcing functions.

Computing model uncertainty is a crucial step towards developing useful models for management. As part of this action item we will evaluate model sensitivity to perturbations in the external forcing functions such as sea surface temperature, fresh water fluxes, etc.


- D4.4: Evaluation of the coupled model uncertainties and sensitivities.



Deliverable Date

D4.1: Review of available full life cycle models for small pelagics; pros and cons and applicability to the case studies and species analysed in REPROdUCE of the different approaches.

IEO Month 06

D4.2: Design of a road map to obtain modules which describe the different main elements of the ecosystem that can be later coupled together (communication with the other WPs)

IEO Month 06

D4.3: Implement a coupled physical-ecosystem model (spatially explicit, full life cycle) in the two regions of interest.

IEO Month 25

D4.4: Evaluation of the coupled model uncertainties and sensitivities.

HCMR Month 33

• WP04 related Milestones

Milestone number


Expected Date

Verification



4(coord) ALL






M10 Online meeting on identification of simulation scenarios and required

validation data

5,6(coord.) ALL

Month 27 Online meeting held



WP 05: Model validation, recruitment simulation scenarios and assessment of recruitment drivers

• Objectives - Coordinate the development of validation criteria for the different modules (WP01 to

03) and for the ecosystem full life cycle model (WP04), - Coordinate the actions to obtain required data (existing or to be gathered by dedicated

observations/surveys) to perform the validation of the different modules and the final ecosystem model. For the specific case of the Aegean Sea this objective include to perform a series of ad hoc sampling surveys to cover an entire spawning period of the species during the first year of the project

- To identify potential stock-related (abundance, structure and demography) and environmental (habitat suitability, food availability and predation rates) recruitment drivers in each case study, gathering information obtained from the conceptual models developed in WP01 to 03 and from published or on-going research

- To identify a series of simulation scenarios which allows to; 1) validate the ecosystem model developed in WP04 (realistic scenario) and 2) to infer recruitment variability at different levels of the potential recruitment drivers (alternative contrasting scenarios),

- To analyse model outputs under the realistic and alternative scenarios in order to 1) validate the ecosystem model, and 2) assess and rank the influence of the different stock and environmentally related recruitment drivers in each case study

• Participants:

HCMR (coordinator: Stelios Somarakis), IEO, IFREMER, IPIMAR, AZTI


Person-months per participant 13 14 5 1 2


Model validation should be one of the main requirements to evaluate the quality of any scientific work that requires a modelling approach (Arhonditsis and Brett, 2004; Travers et al., 2007). However, validating complex and coupled models is not a straightforward task and comprehensive validation is overlooked in many ecosystem models (Arhonditsis et al., 2008). Simulating realistic scenarios which allow the validation of the outputs versus some experimental observations becomes an issue for complex coupled models, and finding adequate criteria to assess when outputs and experimental data are similar requires careful attention (Radach and Moll, 2006). If uncertainties in initial parameters or forcing functions of the model exist, model robustness can also be assessed by simulation over a range of initial conditions or forcing functions (Travers et al., 2007). Also, once a model has been validated and is considered an appropriate representation for a specific purpose, simulation under alternative scenarios provides a way to analyse the effect of different variables (drivers) in the outputs.

REPROdUCE will deal with these issues with a dedicated WP (WP05), in which the validation of the different modules and the final model will be coordinated, and simulation scenarios required to evaluate the intensity of potential recruitment drivers will be designed. Decisions on adequate validation criteria for the individual modules and for the final full model will be coordinated by WP05, and data requirements for the validation process will be overseen. Specific surveys to improve the temporal coverage of variables of interest in the AS case study



are already planned within REPROdUCE, and when identified, data requirements which are not available within either the BoB or the AS case study will be dealt with by ad-hoc experimental/sampling designs, to be carried out by the REPROdUCE partners. Realistic scenarios for the full model validation, together with alternative simulation scenarios that allow to test the intensity of different drivers will be designed in close coordination with the design of the conceptual models for WP01 to 04

Action 1: Coordination of WPs 01 to 04 in order to develop coherent model validation criteria and to identify data requirements.

WP05 will coordinate the definition of validation criteria for WPs 01 to 04, including definition of which model outputs will be used, data requirements and the criteria to evaluate similarity between outputs and experimental data/observations. When possible, validation for each module will focus on the main compartments that link with other modules, making sure the overall model “currency” (i.e. the quantity that is interchanged between modules) variable is validated.


- D5.1: report on model validation criteria for each module, and guidelines for the validation of the ecosystem full life cycle model.

- D5.2: report on data requirements for the validation of each module, and availability of those data from partner’s or external databases or alternative ways to obtain the required data (including request from ad-hoc surveys or experiences from partners and to the DCR).

- D5.3: report on ecosystem model validation criteria, once the coupled model is developed and in agreement with the guidelines reported in deliverable D5.1.

Action 2: Data collection for model validation

In this action, lack of data required for the parameterization, calibration and validation of models identified in WP02 and WP04 (e.g., stage specific vertical distribution behaviour, prey sizes, energy densities, predation rates, seasonal patterns), and reported in Action 1 of this WP will be acquired by mean of ad hoc observations and sampling at sea during routine (DCR) surveys and analysis of all relevant data, including those available from past surveys.

In the northern Aegean Sea, where there is compete lack of observations on seasonal patterns of spawning and adult distribution, ad hoc acoustic and ichthyoplankton surveys will be conducted that will cover an entire spawning season over the main spawning ground (Thracian Sea), in order to validate distribution maps predicted by the habitat models and the larval IBMs and collect information on unknown parameters.


- D5.4: Survey plan for the Aegean Sea surveys and ad-hoc surveys among partners

Action 3: Identification of potential recruitment drivers and potential correlation among them

Based on the conceptual models developed in WPs 01 to 03 and on published and ongoing research (See Organisation Roles, Expertise and Experience section), stock recruitment relationships will be revisited and potential drivers of recruitment for each of the studied stock will be reviewed (Stock biomass, stock distribution, demography, climate-related drivers –



fresh water inputs, stratification, upwelling etc). Drivers of recruitment will be ranked preliminary in terms of their importance for recruitment variability and the links among them will be identified where possible. Alternative mechanisms determining recruitment will be conceptually proposed and will be subsequently used to identify proper scenarios to test and compare with model predictions.


- D5.5: Online meeting for gathering information on potential drivers identified in each module conceptual model

- D5.6: Report on summary of potential drivers and their a priori influence on recruitment, from information gathered in the online meeting and from previous ecological hypothesis and on-going related projects.

Action 4: Design of contrasting scenarios to validate the model and test hypothesis related to the main recruitment drivers.

This action involves designing the simulations that will be implemented in the ecosystem model, in order to 1) validate the model, following the criteria developed in Action 1 and 2 above, and 2) investigate the relative influence of the different recruitment drivers identified in Action 3 above. The time horizon for the different simulations will be decided as well as the initial conditions and forcing functions.

For the model validation, a realistic scenario will be defined and a time framework which allows comparing model output to available observations in agreement with the validation protocol developed in Action 1. A realistic scenario includes realistic initial conditions for each module (nutrients, phytoplankton and zooplankton concentration in each of the required size or taxonomic group, fish biomass and distribution, etc.), realistic climate and hydrodynamic forcing (winds, currents on the boundary, river outflow, etc.) and realistic biological parameters. A comprehensive list of the initial conditions and forcing functions required for the realistic simulation will be reported, and will be used to implement the “base-case” simulation scenario in WP04.

For the alternative simulations, extreme conditions on any given potential recruitment driver identified in Action 3 above will be designed (e.g. continued low river inflow levels due to periods of low rainfall versus continued high river inflow levels due to periods of large rainfall). A specific set of simulation scenarios will deal with specific management options for each case study (e.g. no fishing mortality in given periods due to temporal bans, lower fishing mortality for biomass below a given value, etc.). The characteristics of each scenario will be detailed and passed to WP04 for their implementation.


- D5.7: A detailed description of the initial conditions and forcing functions to be used to generate a realistic simulation scenario (base-case), which will be used for model validation and prediction purposes.

- D5.8: A detailed list of alternative simulation scenarios and their related hypothesis (e.g. rainfall and river inflow have an effect in recruitment strength), together with the suggested list of changes in initial conditions or forcing function in relation to the base-case.



Action 5: Perform model validation and evaluate the influence of the different drivers, in coordination with WP04

Once the simulations designed in Action 4 above are implemented in the model within WP04 and a set of model runs is obtained, an assessment of model validity, based on the criteria developed in Action 1, as well as an assessment of the relative influence of the different recruitment drivers will be produced.


- D5.9: Report on model validation

- D5.10: Report on the relative influence and possible links between the different recruitment drivers.



Deliverable Date

D5.1: report on model validation criteria for each module, and guidelines for the validation of the ecosystem full life cycle model.

HCMR Month 20

D5.2: report on data requirements for the validation of each module, and availability of those data from partner’s or external databases or alternative ways to obtain the required data (including request from ad-hoc surveys or experiences from partners and to the DCR).

HCMR Month 20

D5.3: report on ecosystem model validation criteria, once the coupled model is developed and in agreement with the guidelines reported in deliverable D5.1.

HCMR Month 26

D5.4: Survey plan for the Aegean Sea surveys and ad-hoc surveys among partners

HCMR Month 20

D5.5: Online meeting for gathering information on potential drivers identified in each module conceptual model

IEO Month 27

D5.6: Report on summary of potential drivers and their a priori influence on recruitment, from information gathered in the online meeting and from previous ecological hypothesis and on-going related projects.

IEO Month 30

D5.7: A detailed description of the initial conditions and forcing functions to be used to generate a realistic simulation scenario (base-case), which will be used for model validation and prediction purposes.

IFREMER Month 30



Deliverable (cont) Institute responsible

Deliverable Date

D5.8: A detailed list of alternative simulation scenarios and their related hypothesis (e.g. rainfall and river inflow have an effect in recruitment strength), together with the suggested list of changes in initial conditions or forcing function in relation to the base-case.

IEO Month 30

D5.9: Report on model validation HCMR Month 32

D5.10: Report on the relative influence and possible links between the different recruitment drivers.

IFREMER Month 32

• WP05 related milestones Milestone number


Expected Date

Verification


5(coord) ALL





validation data

5,6(coord.) ALL


M11 Final meeting: development of recruitment index and responsibilities

and deadlines for the final report

ALL Month 34 Meeting held

M12 Final report ALL Month 36 Report sent



WP 06: Synthesis and building of recruitment strength indicators

a) Objectives

- To synthesize the project results and deliver a recruitment model that can be used as a fishery indicator

b) Participants: IEO (coordinator: Miguel Bernal), HCMR, IFREMER, AZTI, IPIMAR


Person-months per participant 18 4.5 4 1 1


WP06 will synthesize REPROdUCE achievements and use the results obtained in the project to provide a recruitment-based fishery indicator. In order to do that, achievements from the different WPs will be gathered together, using the coordination of WPs 04 and 05, and reporting milestones of the different WPs. The synthesis WP will address the scientific questions posed at the onset of the project;

1- What are the main mechanisms driving recruitment (internal vs external mechanisms) and what are the links between those mechanisms?

2- Which of these mechanisms can be responsible for prolonged reduction of reproductive potential in sardines and anchovies, and what is the effect of the reduction in reproductive potential in population recovery rates?

3- Are the recruitment drivers identified coherent with current general ecological hypothesis on population expansion-contraction for small pelagic fish?

As well as the case study related management questions:

Bay of Biscay

4- Anchovy is currently under a situation defined as reduced reproductive potential and is not able to recover to previous levels of biomass. Can we identify which are the mechanisms that explain that the actual distribution/biomass is not able to produce enough recruits to return to previous biomass levels?

5- In good years, sardine egg production in northern Spain rise to similar levels than the ones found in the Armorican shelf, but recruitment in the former area is minimal in comparison with that in the later area. Can we explain why?

Aegean Sea.

6- Management in the Mediterranean is based mainly on technical measures and there are no quotas enforced. In the Aegean Sea, measures, such as a 2.5 winter closed period for the purse seiners and several closed areas in coastal waters have been implemented since the early 60´s, without scientific support and assessment of their effectiveness. REPROdUCE will assess whether these areas and seasons are important for reproductive success and provide the knowledge required for the design of such closed areas and seasons.



Information on these questions gathered in the different WPs will be synthesize under the umbrella of WP06, and presented in the final REPROdUCE report. Also, the information on recruitment drivers collected in WPs 01 to 03, coordinated in WP04 and assessed in WPs 04 and 05 will be used to provide a stock environmentally explicit recruitment-based fishery indicator. Mechanism of recruitment success and failure will be detailed and presented in assessment and management forums. The full life cycle ecosystem model developed in WP04 will be provided as a tool to improve both short term and medium to long term management. The potential for including the environmentally explicit recruitment-based fishery indicator, as well as simulations from the full life cycle model in routine management of the different stocks included in the project will be evaluated in agreement with the adequate scientific and management forums (ICES and CIESM WG, STECF WG, RACs, etc). Shared membership of REPROdUCE partners with those forums will maximize dissemination and discussion of the results of the project and applicability to stock management.



Deliverable Date

D6.1: Final report, including a detailed list of recruitment strength indicators. The final full life cycle model, with the potential to predict recruitment under a variety of scenarios will be make available.

ALL (coord IEO)

Month 36



Expected Date

Verification







WP 07: Project management

c) Objectives - Oversee communication among WP leaders and project coordinator, and provide

support for internal (among partners) or external (between partners and the MARIFISH secretariat) questions on legal, financial or related matters,

- Ensuring that project objectives are achieved and deliveries are completed within the agreed timescale and within the costs estimated.

- Ensuring dissemination of results is made in accordance to the dissemination plans, and required reports are submitted to the MARIFISH secretariat

d) Participants: IEO (coordinator:Cristobal Suanzes), HCMR, IFREMER, AZTI, IPIMAR


The Project Management WP will be coordinated by the project coordinator (M. Bernal) and the project manager (C. Suanzes), and will include all WP and Case Study coordinators (see Table below)

Work Packages and Case Study coordinators included in the project management structure.

Task Description Responsible

WP01 Hydrodynamic and lower trophic level models X. Irigoien

M. Chifflet

WP02 Juvenile and adults: life cycle, within population diversity, habitat occupation, migration, growth, fecundity and mortality.

P. Petitgas

WP03 Models of early life stages dispersion and survival M. Huret

WP04 Pelagic ecosystem model set-up and assemblage of model modules

E. Curchitser

WP05 Model validation, recruitment simulation scenarios and assessment of recruitment drivers

S. Somarakis

WP06 Synthesis and building of recruitment strength indicators M. Bernal

WP07 Project management C. Suanzes

BoB CS Bay of Biscay Case Study E. Nogueira

AS CS Aegean Sea Case Study S. Somarakis

WP7 is a key component to building the project as a network of a coherent group of organizations to integrate research related activities. The main task of the Project Management WP is to provide required support to ensure that the desired level of communication among partners, WP and case studies takes place during the project life span. Also, the WP project management will make sure that deliverables, milestones, reporting events and dissemination of results are carried out in a timely manner, in accordance with the project chronogram.



Action 1: Co-ordinate and manage all aspects of the technical and contract management components of the project. This will include the legal, contractual, financial and administrative management of the consortium. within the Partners and with the MARIFISH secretariat

Action 2: Establish and maintain an interactive web-page (WIKI) for the project to facilitate communication, stimulate debate, act as an information centre, provide archive base for all reports and other output. Provide training if needed to all the partners to maximise WIKI use.

Action 3: Organisation of start up, annual and final meetings, workshops and meetings with media and social agents and other workshops

Action 4: Preparation of project reports (midterm and final report) to summarize what has been achieved



Deliverable Date

D 7.1. Signed Contract ALL (IEO coord)

Month 0

D 7.2. WIKI Web page IEO Month 2 D7.3: Dissemination of conceptual models to fishery scientist, policymakers and stakeholders

IEO Month 9

D 7.4. Midterm progress report ALL (IEO coord)

Month 13

D 7.5. Minutes and reports of workshops and follow up meetings ALL (IEO coord)

Months 1, 13, 25

D 7.6: Dissemination of influence of recruitment drivers to fishery scientist, policymakers and stakeholders

IEO Month 33

D 6.1: Final report in coordination with WP06 ALL (IEO coord)

Month 36



Expected Date

Verification

M1 Consortium and Marifish Secretariat contract signed

7 Month 0 Contract signed and project start

M2 Start-up meeting ALL Month 1 Meeting held M3 Conceptual models Workshop ALL Month 6 Workshop held M5 Annual meeting: adoption of numerial

models for each module ALL Month 11 Meeting held:

Models adopted M8 Annual meeting + workshop on

coupling the different modules ALL Month 21 Meeting held:

Workshop made M10 Online meeting on identification of

simulation scenarios and required validation data

5,6(coord.) ALL








Case Study Description: Bay of Biscay (BoB)

General description

The Bay of Biscay is an open oceanic bay located in the eastern North Atlantic, between 43.5° and 48.5° N and 8.5° and 1.5° W (Figure BoB-1). The southern part is oriented W-E along the Northern Spanish coast while the eastern part is oriented S-N along the French coast. The continental shelf in the French sector of the Bay of Biscay is between 150-180 km wide at the northern extreme (Armorican shelf), becoming narrower, about 50-km width, towards the southern part (Aquitaine shelf). Contrastingly, the continental shelf in the Spanish sector (Cantabrian Sea) is extremely narrow, with a mean width between 30-40 km.

Figure BoB-1. Bathymetry and main geographic areas in the bay of Biscay (Koutsikopoulus and Le Cann 1996)

Figure BoB-2. Scheme of the main oceanographic processes in the Bay of Biscay (OSPAR 2000, from Koutsikopoulus and Le Cann 1996)

Hydrography and circulation

The Bay of Biscay lies in the inter-gyre region that separates the major oceanic gyres of the North Atlantic: the sub-polar, extending approximately between 45°-65°N and driven by the Icelandic low pressure system, and the sub-tropical, between 10°-40°N and forced by the anticyclonic atmospheric circulation around the Azores high pressure cell (Pollard et al. 1996). Both the geographical configuration of the area, and the effect of different general circulation and local conditions create a large spatial and temporal heterogeny in hydrodynamic features (Figure BoB-2).

Hydrodynamic processes in the Bay of Biscay also show a strong seasonal and medium-term varying character, influencing the distribution and variability of the different abiotic and biotic ecosystem components at regional and mesoscale levels (OSPAR 2000, from Koutsikopoulus and Le Cann 1996). In the last years, hydrodynamic models of high spatial and temporal resolution have been applied to different zones of the Bay of Biscay by Ifremer, IEO and AZTI: models MARS (e.g. Lazure et al. 2009), ROMS (e.g. Otero et al. 2008a; Ferrer et al. 2009) and OPA (Friocourt et al. 2008a, b). Some of these models have focused on specific processes, such as the dynamics of the IPC (Friocourt et al. 2008a, b) or river plumes (Otero et al. 2008b). These institutions have devoted effort to development of predictive models for operational purposes and daily results are available online:

http://www.previmer.org/previsions/temperature_et_salinite).



Lower trophic levels

There is a relatively ample body of research concerning the spatial and temporal variability of plankton components in the Bay of Biscay. In the last years, these studies have covered various aspects of the dynamics, distribution and processes of the different lower trophic level components, at a wide range of temporal and spatial scales, from picoplancton (Calvo-Díaz et al. 2004; Morán 2007; Calvo-Díaz et al. 2008), nanoplankton (Granda and Anadón 2008), phytoplankton (Rodriguez et al. 2003; Lunven et al. 2005; Labry et al. 2005; Guillaud et al. 2008; Álvarez et al. 2009), meso-zooplankton (Isla et al. 2004; Ceballos and Álvarez-Marques 2006; Valdés et al. 2007; Cabal et al. 2008; Irigoien et al. 2009) to ichthyoplankton (González-Quirós et al. 2004; Rodríguez 2008). However, few of these studies have covered more than one functional group, as has being done for instances by Fernández et al. (2004) for phytoplankton and meso-zooplankton or Zarauz et al. (2007) for nano-, micro- and meso-zooplankton. Modelling studies are relatively scarce, being most of them of empirical, based on the use of generalized additive models (GAM) (e.g. Zarauz et al. 2008), time series analysis (e.g. Stenseth et al. 2006) or inverse modelling techniques (Marquis et al. 2007). Lower trophic models coupled to 3D hydrodynamic models have been configured for these area and ran in regional domains (e.g. Aita et al. 2007, Siddorn et al. 2007, Powell et al. 2006; Huret et al. 2007) and can be very useful to gain information on the temporal and spatial variability of food supply to higher trophic levels.

Pelagic stocks

The main pelagic species in the Bay of Biscay are sardine and anchovy (small pelagic) and mackerel and horse mackerel (middle-size pelagic), which together with species more common to temperate and subtropical waters, such as chub mackerel (S. colias), Mediterranean horse mackerel (T. mediterraneus), sprat (Sprattus sprattus) and blue jack mackerel (T. picturatus) conforms the pelagic fish community in the area.

Anchovy

The distribution of anchovy (Engraulis encrasicolus) in Atlantic European waters is nowadays concentrated in two well defined areas: the Bay of Biscay and the Gulf of Cádiz (Uriarte et al. 1996; ICES 2008a) (Figure BoB-3). Some residual coastal populations exist also along the western Iberian coast, English Channel, Celtic Sea and North Sea (Beare et al. 2004; ICES 2007a). Anchovy populations in the northern areas seem to have increased in recent years (Beare et al. 2004; ICES 2004). Despite its known fluctuations in distribution and abundance along the Atlantic European waters, even in the current low abundance situation in the Bay of Biscay, this area and the Gulf of Cádiz continue to be regarded as the main nuclei for Atlanto-European anchovy (ICES 2008a).

(a) (b)

Figure BoB-3. Anchovy. (a) Number of anchovy eggs per m3 observed by CUFES and (b) Acoustic energies (sA in m2/nm2) attributed to anchovy (ICES 2008)



Anchovy in the Bay of Biscay may grow to >20 cm and live span rarely goes beyond three years. It forms small schools located between 5 and 15 metres above the bottom during the day (Massé 1996), although change in the schooling pattern of anchovy have been described since the beginning of the 2000s (ICES 2008a). It is a serial spawner (several spawns per year) and reproduces in spring. The spawning area is located southward of 47° N and eastward of 5° W. Most spawning takes place over the continental shelf in areas influenced by the river plumes of the Gironde, Adour and Cantabrian rivers (Motos et al. 1996). However, recent studies have suggested that anchovy in the Bay of Biscay may recruit partially offshore (Irigoien et al. 2007). However it is no clear to what extent individuals recruited off the shelf contribute to the total population (Irigoien et al. 2008), partly because modelling studies have shown that off-shelf waters do not fulfil the conditions for larvae survival (Allain et al. 2007 a, b). As spring and summer progresses, anchovy migrates from the interior of the Bay of Biscay towards the north along the French coast and towards the east along the Cantabrian Sea, where spends the autumn. In winter migrates in the opposite direction towards the east and southeast of the Bay of Biscay (Prouzet et al. 1994). It has a high and very variable natural mortality. Mesoscale processes in relation to the vertical structure of the water column (stratification, upwelling and river plume extent) appear to have a great influence on the survival of larvae (Allain et al. 2001). However they may only act as limiting factors (Planque and Buffaz, 2008), and the mechanisms through which these physical processes affect recruitment are still to be better understood

Since 2002, the recruitment of Bay of Biscay anchovy has been among the lowest of the time series, with a series of two (2002 and 2003) and four (2005-2008) consecutive recruitment failures, this later series being the largest series of consecutive recruitment failures since anchovy assessment started (ICES 2008a). As all short lived species, anchovy stock is very dependent on recruitment, and therefore these recruitment failures lead to the low biomass levels observed in recent years. Environmental shifts, fishing pressure, or a combination of both, have been often reported as the causes of consecutive recruitment failures and their associated crisis (Freon et al. 2005). A reduction of the distribution of anchovy in the Bay of Biscay has been observed both in the acoustic and egg production survey (ICES, 2007a) and changes in the school composition have also been described (Masse and Gerlotto 2003). The anchovy population has disappeared from the Spanish coast and spawning grounds have been lost (ICES 2004). Based on circulation models, larval drift reveals that the larvae born in the French spawning grounds move towards Spanish coasts but fail to re-colonize there (Vaz and Petitgas 2002).

In the last years the spatial distribution of anchovy eggs in spring has expanded northward compared with the distribution of the anchovy eggs in the 60’s and 70’s (Bellier et al., 2007). According to previous studies (Motos et al., 1996; Uriarte et al., 1996), anchovy populations appear to have density-dependent strategies of spawning area selection. Different hypotheses have been suggested to explain interannual and long-term variations in anchovy abundance which are often attributed to important variability in recruitment levels, and are ultimately linked to variations in ocean processes. Changes in global and local environmental indexes have also been described for the Bay of Biscay, such as North Atlantic Oscillation index and Polar Eurasia and East Atlantic patterns (ICES, 2007b) and upwelling and stratification index (Borja et al. 1998; Alain et al. 2001; Huret and Petitgas 2007).

Sardine

European sardine (Sardina pilchardus) is found from Mauritania and Senegal to the North Sea, being also present in the Black Sea. This wide geographical range implies that the species is able to sustain wide ranges of both temperature and salinity. Recent studies by



Bernal (2008) have also shown a wide temperature tolerance (12-17°C) for sardine spawning habitat and distribution.

(a) (b)

Figure BoB 4. Sardine. (a) Number of sardine eggs per m3 observed by CUFES and (b) Acoustic energies (sA in m2/nm2) attributed to sardine during PELAGO, PELACUS

and PELGAS surveys in spring 2008 (ICES WGACEGG 2008)

Sardine in the western Iberia area seem to have a more coastal distribution than sardine in the northern Bay of Biscay probably due to the differences in shelf dimensions (Figure BoB 4). Over the French shelf, juveniles are found mainly concentrated all along the French coast mixed with anchovy and sprat in areas influenced by river plumes while adult sardine tend to be seen offshore in big schools at the surface.

Sardine in the Bay of Biscay can reach up to 25 cm in length and more than ten years of age. It forms large schools usually close to the coast and up to around 50 m depth from the sea surface to the bottom, whereas dense schools appear usually at the surface more offshore until the shelf-break. It is a serial spawner. In general, the spawning peak appears in spring, although there is a second peak in autumn (Solá et al. 1992). These two peaks may correspond to the existence of sympatric (or parapatric) spring and autumn sardines (Wyatt and Porteiro 2002), although no conclusive evidence has been found. The concept of metapopulation for the sardine resident in the Bay of Biscay may help to explain the significant variations in abundance which has taken place, especially in the southeast of the region in the last decade (Carrera and Porteiro 2003). The decrease in sardine recruitment has been related to global warming (Lavín et al. 1997; Cabanas and Porteiro 1998; Guisande et al. 2001; Valdés and Lavín 2002; Wyatt and Porteiro 2002) and this hypothesis is currently under investigation. A significant part of the biomass is present in the Northern Bay of Biscay (along the Brittany coast and offshore) in spring and summer, migrating at least for a part of it toward the western Channel and Celtic sea. This part of the population may show a similar evolution (2004 year class for instance) than the southern part whereas a different level of recruitment may sometime appear as in 2008 when the recruitment (2007 year class) was poor in the south but significant in the North (ICES, 2008b).

Some alternation between sardine and anchovy has been detected (Bode et al., 2006). Increase of sardine biomass off the Iberian Peninsula, as well as some signals of increase in the Armorican shelf has also been observed, although the acoustic data on the abundance of sardine in this later area does not show a stable trend (ICES, 2008a).



Case study: North Aegean Sea (NAS) - Anchovy

The Aegean Sea, like the rest of the eastern Mediterranean, is an area of low nutrient concentration, plankton biomass and production (Stergiou et al. 1997). However, its northern part (NAS), influenced by Black Sea waters (BSW) and the presence of a series of large rivers (e.g., Pinios, Aliakmon, Strymon, Nestos rivers, see Fig. 1), is relatively more productive than the highly oligotrophic southern part (Stergiou et al. 1997, Siokou-Frangou et al. 2002, Isari et al. 2006). The NAS has a wide continental shelf and constitutes one of the most important fishing grounds in the eastern Mediterranean, especially for small pelagic fish (Stergiou et al., 1997, Somarakis et al., 2006). The outflow of Black Sea water (salinity <30) from the Dardanelles enhances local productivity and its advection in the NAS induces high hydrological and biological complexity (Isari et al. 2006, 2007).

The NAS is inhabited by one of the largest anchovy stock is the Mediterranean which is mainly exploited by the Greek purse seine fleet (Somarakis et al. 2004; 2006). Despite the importance of small pelagic fish for Greece (~30% of total Greek landings), monitoring of their fisheries and assessment of the stocks has been initiated recently (2003), within the framework of the Greek National Program (EC-Data Collection Regulation -DCR). Since 2003, annual acoustic surveys targeting anchovy and sardine coupled with concurrent DEPM surveys for anchovy have been carried out in June (Table 1). These have provided biomass inputs for the assessment of the stocks using the Intergated Catch-at-Age analysis (Somarakis et al. 2007; Giannoulaki et al. 2007).

In the Mediterranean Sea, management of small pelagics is based on technical measures and no landing limits are currently set. In the Aegean Sea, measures, such as a 2.5 winter closed period for the purse seiners and several closed areas in coastal waters have been implemented since the early 60’s, without any scientific justification and assessment of their effectiveness. Research needs include the identification and characterization of nursery grounds and the understanding of the links between spawning and nursery areas (Somarakis et al. 2007; Somarakis and Nikolioudakis 2007).

Recent research projects in the Aegean Sea have focused, among others, on a primary understanding of factors that might affect recruitment of small pelagic fish in the northern Aegean Sea. Early national and European projects (ANCHOVY: Evaluation of the anchovy stocks in the Aegean Sea, DG XIV-1/MED/91/011 and EPET: Development of the Greek fisheries, EPET 125, II/94. Ministry of Research and Technology, Greece) provided the first information on patterns of anchovy egg and larval distributions as well as on growth and mortality of anchovy larvae (1993-1996, e.g., Somarakis and Nikolioudakis 2007). In later years, the project ANREC (Association of Physical and Biological processes acting on Recruitment and Post-Recruitment stages of Anchovy, QLRT-2001-01216) provided data on anchovy growth and feeding in the Thracian Sea during the larval and juvenile stages. The characterization of small pelagic fish habitats (spawning, nursery and adult habitats) based on satellite environmental information (e.g., Schismenou et al., 2008; Giannoulaki et al. 2008) was one of the main objectives of the project Envi-EFH (Environmental Approach to Essential Fish Habitat Designation. FP6-22466). Finally, the ongoing project SARDONE (Improving assessment and management of small pelagic species in the Mediterranean, FP6-44294) is expected to provide detailed information on growth and mortality of anchovy and sardine during the late-larval and juvenile stages as well as on characteristics of the juvenile habitats. Furthermore, an IBM tool is being developed within SARDONE (by which individual groups of eggs and larvae are released as Langrangian particles), which is now off-line coupled with models providing physical and biological factors (such as velocity field, temperature and salinity from the POM hydrodynamic model, and biological parameters, such as zooplankton, from the ERSEM biogeochemical model).



The POM and ERSEM models have been elaborated within a series of large operational programs of HCMR (POSEIDON & POSEIDON II) and are currently fully implemented. The hydrodynamic model is based on the Princeton Ocean Model (POM) (Blumberg and Mellor, 1983), which is a widely used model that has been previously applied to the Mediterranean area in numerous studies both at basin, regional and local scales (Drakopoulos and Lascaratos 1997; Zavatarelli and Mellor 1995; Lascaratos and Nittis 1998; Korres and Lascaratos 2003; Ahumada and Cruzado, 2007). POM is a primitive equation model that has a bottom – following vertical sigma coordinate system, a free surface and a split mode time step. Horizontal diffusion is calculated following a Smagorinsky formulation (Mellor and Blumberg, 1985), while the vertical eddy viscosity / diffusivity coefficients are computed according to the Mellor-Yamada 2.5 turbulence closure scheme (Mellor and Yamada, 1982). A second order conservative upstream advection scheme (Lin et al., 1994) is used for the biological tracers.

The biogeochemical model is based on the European Regional Seas Ecosystem Model (ERSEM) (Baretta et al., 1995; Petihakis et al. 2002; Allen et al., 2007; Blackford et al., 2004). Although the model was originally developed for the North Sea ecosystem, due to its generic character, it was soon applied in a range of different environments including the Mediterranean (Vichi et al., 1998, Zavaterelli et al., 2000, Petihakis et al., 1999, Petihakis et al., 2002, Petihakis et al., 2007, Triantafyllou et al., 2003, Triantafyllou et al., 2000, Triantafyllou et al., 2001). ERSEM uses a “functional” group approach to describe the ecosystem, where the biota are grouped together according to their trophic level (subdivided according to size classes or feeding methods). The biological functional group dynamics are described by both physiological (ingestion, respiration, excretion, egestion etc.) and population (growth, migration, mortality) processes. Carbon dynamics are coupled to chemical dynamics of nitrogen, phosphate, silicate and oxygen. The pelagic state variables include 4 groups of phytoplankton (diatoms, nanoplankton, picoplankton, dinoflagellates), 3 groups of zooplankton (heterotrophic flagellates, microzooplankton, mesozooplankton), bacteria, dissolved organic matter and particulate organic matter. Each group has dynamically varying C/N/P ratios and is represented by their carbon, nitrogen, phosphorus and in the case of diatoms silicon, components.

The coupling of hydrographic and ecosystem models with habitat models and IBMs in the Aegean Sea is expected to provide new insights into the mechanisms that control spawning and recruitment success of anchovy in this hydrologically and biologically complex system. Because most data and information in this basin comes from surveys carried out during the peak of the spawning season of anchovy (June, see Table below) there is a particular need to support the modelling workpackages of the project with ad hoc field sampling surveys covering the entire spawning period. The objective of these surveys will be to validate models and to get better insight into the temporal (seasonal) dimension of recruitment.

Data from surveys covering the entire northern Aegean Sea and available for analysis in REPROdUCE. All surveys have been carried out in June (peak anchovy spawning period). Type of data Source Year Project

Anchovy egg abundance

DEPM surveys 2003-2006, 2008 National (DCR)

Anchovy and sardine abundance

Acoustic surveys 2003-2006, 2008 National (DCR)

Anchovy egg and larval abundance

Bongo-net plankton surveys

1995-1996, 2003-2006

EPET, National (DCR)



Fig. NAS-1. Map of the Northern Aegean Sea with bathymetry.



List of WP deliverables Deliverable Institute

responsible Deliverable Date

D1.1: Review of potential bottom-up forcing (climate-ocean and lower trophic levels) of intermediate trophic levels, in coordination with WP02, and 03

AZTI Month 06

D1.2: Review of available hydrodynamic-NPZD models for both case studies, and of available and lacking data or information necessary for validation and good representation of key processes identified in D1.1

IEO Month 06

D1.3: Adoption of a conceptual NPZD model with main climate forcing and main energy flow to intermediate trophic levels representation for both case studies

AZTI Month 08

D1.4: Report on adaptation needed in present hydrodynamic-NPZD models to correctly transfer energy to different stages of key forage fish species in both case studies

IFREMER Month 10

D1.5: Report on the consistency of available numerical models with the conceptual models for each of the case studies, and comparability of the available models in terms of forcings, scales and conception.

IEO Month 11

D1.6: Simulated forcing fields for “offline” (i.e. non-interactive one way coupling; fish prey on NPZD models, but NPZD models are not subsequentially updated) WP02 and WP03

AZTI Month 15

D1.7: Report on potential validation criteria for lower trophic level models, as well as initial validation tests, in coordination with WP05

HCMR Month 20

D2.1: A list of processes that are potentially influential on the initial conditions for larvae life IBMs and recommendations for model building.

IFREMER Month 08

D2.2: A report on the procedures and the resulting seasonal maps of potential, suitable and unsuitable habitats, for juveniles and adults of the target species in the case studies.

IFREMER Month 22

D2.3: A report on multinomial habitat models and their potential to provide probabilistic habitat and abundance distribution.

IEO Month 22

D2.4: A report on the identification of critical conditions that potentially affect spawning windows (location, timing, duration) as well as fecundity.

IFREMER Month 22

D2.5: A description of validated bioenergetic models for the species in the different case studies that predict growth and reproduction.

IFREMER Month 24

D2.6: A list of rules that define at each time step how the fish is displaced and propositions to implement them.

IFREMER Month 24

D2.7: The description of options to spatialize growth and mortality parameters.

IFREMER Month 24

D2.8: The description of the developed procedures to model within population diversity with IBMs; propositions on how to integrate individual histories at population level.

IFREMER Month 24

D3.1: Report on literature review on process knowledge (feeding, egg development rates, growth, mortality, behaviour) for anchovy and sardine of both case studies.

IFREMER Month 06

D3.2: Report on lacking information and solution/hypothesis to fill these knowledge gaps.

HCMR Month 06

D3.3: Conceptual models for each case study and species, including an accurate an qualitative summary of the main processes and model stages for the early life stages

IFREMER Month 08

D3.4: Identification of the main forcing functions in the conceptual model potentially responsible for recruitment variability.

IEO Month 08

D3.5: Report on state of the art on available numerical early life stages models, with special stress on whether the models include main processes identified in the conceptual models developed in Action 3 above, and their respective advances towards building a full life cycle ecosystem model.

HCMR Month 11

D3.6: Report presenting comparative model runs between retained ELS models for selected years and lower trophic level distribution and abundance fields.

IFREMER Month 18

D3.7: Definition of ELS validation criteria in coordination with WP02 and WP05 and report of initial module validation.

HCMR Month 24

D4.1: Review of available full life cycle models for small pelagics; pros and IEO Month 06



cons and applicability to the case studies and species analysed in REPROdUCE of the different approaches. D4.2: Design of a road map to obtain modules which describe the different main elements of the ecosystem that can be later coupled together (communication with the other WPs)

IEO (IMCS) Month 06

D4.3: Implement a coupled physical-ecosystem model (spatially explicit, full life cycle) in the two regions of interest.

IEO (IMCS) Month 25

D4.4: Evaluation of the coupled model uncertainties and sensitivities. HCMR Month 33 D5.1: report on model validation criteria for each module, and guidelines for the validation of the ecosystem full life cycle model. HCMR

Month 20

D5.2: report on data requirements for the validation of each module, and availability of those data from partner’s or external databases or alternative ways to obtain the required data (including request from ad-hoc surveys or experiences from partners and to the DCR).

HCMR Month 20

D5.3: report on ecosystem model validation criteria, once the coupled model is developed and in agreement with the guidelines reported in deliverable D5.1.

HCMR Month 26

D5.4: Survey plan for the Aegean Sea surveys and ad-hoc surveys among partners HCMR

Month 20

D5.5: Online meeting for gathering information on potential drivers identified in each module conceptual model IEO

Month 27

D5.6: Report on summary of potential drivers and their a priori influence on recruitment, from information gathered in the online meeting and from previous ecological hypothesis and on-going related projects.

IEO Month 30

D5.7: A detailed description of the initial conditions and forcing functions to be used to generate a realistic simulation scenario (base-case), which will be used for model validation and prediction purposes.

IFREMER Month 30

D5.8: A detailed list of alternative simulation scenarios and their related hypothesis (e.g. rainfall and river inflow have an effect in recruitment strength), together with the suggested list of changes in initial conditions or forcing function in relation to the base-case.

IEO Month 30

D5.9: Report on model validation HCMR

Month 32

D5.10: Report on the relative influence and possible links between the different recruitment drivers. IFREMER

Month 32

D6.1: Final report, including a detailed list of recruitment strength indicators. The final full life cycle model, with the potential to predict recruitment under a variety of scenarios will be make available.

ALL (IEO coord)

Month 36

D 7.1. Signed Contract ALL (IEO coord)

Month 0

D 7.2. WIKI Web page IEO Month 2 D 7.3. Midterm progress report ALL

(IEO coord) Month 13

D 7.4. Minutes and reports of workshops and follow up meetings ALL (IEO coord)

Months 1, 13, and 25



List of REPROdUCE milestones Milestone number


Expected Date

Verification

M1 Consortium and Marifish Secretariat contract signed

7 Month 0 Contract signed and project start

M2 Start-up meeting ALL Month 1 Meeting held M3 Conceptual models Workshop ALL Month 6 Workshop held M4 Report on conceptual models for all


4(coord) ALL







5(coord) ALL







validation data

5,6(coord.) ALL








Time Schedule and visual scheme of milestones and deliverables

0 6 12 18 24 30 36

Action 1.1

Action 1.2

Action 1.3

Action 2.1

Action 2.2

Action 2.3

Action 2.4

Action 2.5

Action 3.1

Action 3.2

Action 3.3

Action 3.4

Action 4.1

Action 4.2

Action 4.4

Action 5.1

Action 5.2

Action 5.3

Action 5.4

Action 5.5

Action 6.1

Action 7

WP01

WP02

WP03

WP04

WP05

WP06

WP07

M2

M3

M5M4 M6 M7 + M8

M9

M10

M11 M12

D1.1 + D1.2

D1.3 + D1.4

D1.5-1.7

D2.1

D2.2 – 2.4

D2.5

D2.6

D2.7 + D2.8

D3.1 + D3.2

D3.4

D3.5

D3.6 + D3.7

D4.1 + D4.2

D4.3

D4.4

D5.1– 5.3

D5.4

D5.5 + D5.6

D5.7 + D5.8

D5.9 + D5.10

D6.1

D7.1+ D7.2 D7.3+ D7.4



Organisation Roles, Expertise and Experience

REPROdUCE Consortium.

One of the strengths of REPROdUCE is its partnership, which combines expertise on pelagic ecology, assessment of pelagic fish and the availability of the most extensive databases related to the pelagic ecosystem in the two case studies included in the project. The project consortium includes six institutes from 5 different countries, Spain, Greece, France, Portugal and the United States of America (see below for a detailed description of each institution). Four of the partners (IEO - Spain, HCMR - Greece, IFREMER – France, and AZTI - Spain) are eligible to be funded within the rules of the MARIFISH call for proposal for transnational projects. IPIMAR (Portugal) cannot be funded within MARIFISH as Portugal does not contribute to the virtual common pot, but can participate in the call without an associated budget, as an official member of the MARIFISH ERA-NET. Funds for the participation of IPIMAR within REPROdUCE are secured through the Institute internal budget, and additional funds to support the activities carried out in REPROdUCE will be seek taking advantage of the umbrella of this project. The University of Rutgers (US), through the Ocean Modelling group of the Institute for Marine and Coastal Sciences (IMCS), will also take an active role in REPROdUCE, through a subcontract from IEO.

With this partnership, REPROdUCE combines local expertise on both the pelagic ecosystem and the state of the art of modelling techniques applied to analyse them, and an external expert on the development and implementation of biophysical coupled models worldwide. This structure will maximise the probability of success of the project, by combining the required knowledge of the local characteristics and the requirements to develop the recruitment based fishery indicators which will be useful for each specific stock, with the expertise of development and applying biogeophysical models to a variety of ecosystems worldwide. The REPROdUCE consortium also contains the required multidisciplinary composition, including physicist, marine biologist and fishery scientist.

Two characteristics of the REPROdUCE consortium which generate an additional added value to the project are the links between a European consortium and a well known expert and reference in the field in the United States, and the links between the Atlantic and Mediterranean European waters. The link with US provides the opportunity to import expertise into an European consortium and provide training in an innovative field. The link between the Atlantic and Mediterranean areas generates an important flow of information and expertise between two European areas generally isolated in terms of fishery research and assessment procedures.

Table 1 summarises the dedication in man months for the different partners in the different WPs. Tables 2 and 3 summarises the available data and expertise within the REPROdUCE consortium, and Table 4 summarises the synergies between REPROdUCE and ongoing global, European and local projects. Expertise in ecosystem modelling covers the whole spectrum required by REPROdUCE, from hydrodynamic to fish models, while the REPROdUCE partnership combined database provides the best available database for the analysed case studies. Synergies with other global, European and local projects is large, and actions to maximize the exploitation of shared questions and research will be undertaken by the REPROdUCE partnership. Both shared membership to other ongoing projects and the identification of clear links between projects will help integrate research from different projects and improve the REPROdUCE end product.

A brief description of the relevant characteristics for each REPROdUCE partner including the expertise of the main researchers involved in the project is included in the next section, and curriculum vitae’s of all WP leaders and case study coordinators are attached to this proposal.



Table 1: Summary of the participation in man months of the different partners of REPROdUCE in the different WPs.

Participant name IEO HCMR IFREMER AZTI IPIMAR TOTAL WP01 23 8 15 10 -- 56 WP02 23 33 19 1 6 82 WP03 12 12 12 1 -- 37 WP04 19 16 4 5 -- 44 WP05 13 14 5 1 2 35 WP06 18 4.5 4 1 1 28.5 WP07 10 1.5 1 1 -- 13.5 TOTAL 118 89 60 20 9 296



Table 2: Experience of the different partners of the REPROdUCE consortium in relation to the modules included in the project. *IPIMAR participation in REPROdUCE is not ascribed to any Case Study, but else provides expertise in sardine biology, distribution and live cycles. Numbers after the NPZD letters indicate the number of compartments in the NPZD model

Institutes Case Study

Hydrodynamic model

NPZ Model ELS model Fish model

IEO Bay of Biscay

ROMS (Regional Ocean Modelling System)

NEMURO and BIOPHASAM

- Initial conditions (spawning habitat) (sardine) - Larval growth (anchovy)

- Potential and Realised spawning habitat (sardine)

HCMR Northern

Aegean Sea POM (Princeton Ocean

Model)

ERSEM (European Regional Seas

Ecosystem model)

- IBM models of egg and larval drift -Anchovy bioenergetics model

- Potential and Realised spawning habitat (sardine and anchovy)

IFREMER Bay of Biscay

MARS3D ECO-MARS3D N3-P3-Z2-D3

- IBM models of egg and larvae drift, growth and survival, succesful spawning hábitats and time windows with IBM

- Potential, Realised and Suitable habitats (sardine and anchovy) - Unfavourable habitats for juveniles and seasonal migration patterns

AZTI Bay of Biscay

ROMS N2 - P2 - Z2 - D2 - Larval growth (anchovy)

- Potential and realized spawning habitat (anchovy)

IPIMAR --* Local ROMS applications --

Passive particle tracking

- Potential and Realised spawning habitat (sardine)



Table 3: Summary of available data from the REPROdUCE consortium in relation to the modules included in the project. IPIMAR does not provide direct data, although provides general data and knowledge on sardine biology, distribution and live cycles. F = fluor, C = carbon concentration. Chl = Chlorophyll concentration, PP=primary production, SFB=Size-fractionated Biomass, SS = size structure, T = taxonomy available, DW = dry weight, CUFES = surface egg abundance sampler, NET = vertical profiles for egg abundance, PC = Pelagic community of fish, OG = otolith growth, Juv = juveniles.

Institutes Case Study

Hydrology data

Nutrients Phytoplankton Zooplankton Early Life Stages

Juveniles and Adults

IEO Bay of Biscay

Spring surveys: CTD >1987 Autumn surveys: CTD >2006 Time-series1: CTD: >1992

Spring surveys: Concentration >2008 Autumn surveys: C >2006 Time series: C >2000

Spring surveys: taxa concentration, F and Chl >2000 PP some years Autumn surveys: F, T and Chl >2006 Time series: F, >1992 T and Chl >2000

Spring surveys: SFB and SS >2000; T some years Process studies some years Autumn surveys: SFB and SS >2006 Time-series: SFB and SS >2000

Spring surveys: CUFES >2000 NET >1988 Autumn surveys: CUFES >2006 Time series: T and abundance some years

Spring surveys: - Adult abundance, distribution and PC >2000 Autumn surveys: - Same as above + Juv. >2006 - OG adults and Juv.

HCMR Northern Aegean

Sea

CTD: 2003 - 2006, 2008 Fisheries direct surveys

Concentration (>20years)

Chla, and functional group concentrations (>20 years)

-Abundance and biomass, T (>20 years). -DW (2003 - 2006, 2008)

- NET (2003 - 2006, 2008) - Larval abundance by size class (2003 - 2006, 2008) - OG Larvae (1994-1996)

- Adult abundance and distribution (2003 - 2006, 2008) -OG Late larvae and Juv. (2007-2008)

IFREMER Bay of Biscay

CTD: >2008 Buoys: 2008

Concentracion >2008

Size and taxa concentration >2008

T, SFB, LOPC (2004 – 2007)

- CUFES >2008 - NET (2007-2008) - OG Larvae (1999, 2004, 2008) - Larvae vert. distr. (2008)

- Adult abundance, distribution and PC >2008 - Juv. abundance and distribution (2003, 2005); - OG adults and juveniles

AZTI Bay of Biscay

CTD: 1998-2008 Buoys: 2001-2008

2000-2006 Chl a: 1998- 2008 - Large groups, size and abundance 1998-2008

- Eggs: Integrated (1998 – 2008), - Larvae: 2004-2008

- Adult distribution (2000 – 2008) - Juv. abundance and distribution (2004-2008)



Table 4: Summary of project synergies between REPROdUCE and global, European and local ongoing projects

PROJECT NAME SUMMARY OF MAIN SYNERGIES LINKS WITH REPROdUCE

GLOBAL GLOBEC-IMBER:

Integrated Marine Biogeochemistry and Ecosystem Research

Continuation of GLOBEC-SPACC research; understand the links between small pelagic fish, biogeochemical cycles and Climate,

Shared membership and strong participation. Expected presence in IMBER symposiums and workshops

QUEST-Fish: Quantifying and understanding the Earth System

Understanding how climate change would affect the potential production for global fisheries resources in the future

Results on North European Large Marine Ecosystem will be compared with results in the Bay of Biscay

EUROPEAN

CLIMAFISH: MARIFISH “Influence of Climate in small pelagic fish biology, distribution and population dynamics”

Combined climate and human effects on small pelagic fish

Shared membership and strong links. REPROdUCE is expected to provide information on one of CLIMAFISH main research lines

MEECE: Marine Ecosystem Evolution in a Changing Environment

Coupled ecosystem models (end-to-end models), applied to understand population drivers and the effect of variable clima in marine

Shared membership Expected interchange of modeling skills

ECOOP: European coastal-shelf area operational observing and forecasting system.

Development and standardization of operational tools to provide predictive potential to hydrodynamic models

An important amount of information for hydrodynamic model set-up and validation is coordinated within ECOOP

UNCOVER: Understanding the mechanisms of stock recovery

Analysis of impact of fisheries and environment processes on stock structure and recruitment dynamics. Evaluation of strategies for rebuilding.

Shared membership Common model modules Results on impact of exogeneous processes on reproductive potential and recruitment dynamics

RECLAIM: Resolving CLimAte Impact on fish stocks

Analysis of long-term time series of environment and fish, and identification of main processes of climate impact on fish stocks. Modelling of these processes and 'What if' scenarios based on future projections of climate change

Shared membership Results on processes of environment variability impact on fish distribution and abundance Common model modules

FRESH: Fish reproduction and fisheries

Analysis of the influence of reproductive potential in stock fluctuation and fishery assessment

Shared membership. Combined workshops expected, possibility to use FRESH as a framework for training on REPROdUCE final model

FACTS (submitted): Forage fish Interactions

Analysis of the pelagic ecosystem focusing on forage fish, aiming to analyse trophic relationship among forage fish and between them and the rest of the pelagic food web.

Shared membership, includes the Bay of Biscay as a case study. Expected interactions in relation to ecosystem modeling. Expected input on the mortality rates of forage fish from top predators



Table 4 (cont.): Summary of project synergies between REPROdUCE and global, European and local ongoing projects

PROJECT NAME SUMMARY OF MAIN SYNERGIES LINKS WITH REPROdUCE

BoB

ECOANCHOA:

Analysis of trophic interactions among pelagic species and with the rest of the pelagic ecosystem, in order to understand biomass fluctuations in Bay of Biscay anchovy

Shared membership. ECOANCHOA is expected to provide information on trophic interactions in the Bay of Biscay, and mechanism that control carrying capacity and long term fluctuations of biomass

REFORZA:

Observation and modeling of the effects of circulation on plankton distribution at the spring transition

Analysis of observed phytoplancton and larvae distribution during PELACUS cruise through high resolution hydrodynamic modelling

RAIA:

Deployment of a coastal observing and forecasting system in the coastal region in N Portugal and NW Spain (Galicia)

Application of a forecast circulation model for NW Spain shelf and slope. Development of a coupled biogeochemical model

LP_PELNOR (submitted): Long-term variability in the pelagic ecosystem of the North Iberian shelf

Collection, re-analysis and collation in a common database of physical and biological data (from plankton to top predators) of the pelagic ecosystem of the southern BoB shelf

Shared membership. Provision of raw and elaborated information for the development and validation of the modeling tools planned to be delivered by REPROdUCE

AS

SESAME: Southern European Seas: Assessing and Modelling Ecosystem changes (Mediterranean and Black Sea)

Mathematical models validated and upgraded using existing and new observations are being used to predict ecosystem responses to changes in climate and anthropogenic forcing. SESAME will also study the effect of the ecosystem variability on key goods and services, including fisheries

Shared membership. Ecosystem model validation for the Aegean Sea. An initial bioenergetics anchovy model is available from WP5 of SESAME.

SARDONE: Improving assessment and management of small pelagic species in the Mediterranean

Understanding the ecology of the early life history stages of small pelagic fish. Habitat modeling of adult and juvenile stages.

Shared membership. Diet, otolith and ecosystem data (e.g., nutrients, phytoplankton, micro- and meso-zooplankton) for calibration of fish-ecosystem models. Development of an IBM tool to study egg and larval drift. Statistical modeling of adult and juvenile stages.

ANREC: Association of Physical and Biological processes acting on Recruitment and Post-Recruitment stages of Anchovy

Understanding the ecology of the early life history and adult stages of anchovy.

Shared membership. Diet, otolith and ecosystem data (e.g., nutrients, phytoplankton, micro- and meso-zooplankton) for calibration of fish-ecosystem models.

Envi-EFH: Environmental Approach to Essential Fish Habitat Designation

Habitat modeling of small pelagic fish Shared membership. Statistical modeling of spawning, juvenile and adult habitats of small pelagic fish .



REPROdUCE Individual partners:

PARTNER 01: IEO - Spanish Oceanographic Institute (Spain) (COORDINATOR)

The Institute: The Instituto Español de Oceanografìa (IEO) is a public research organisation founded in 1914 and involved in multidisciplinary marine research. IEO is responsible for providing the scientific basis for the management of marine living resources exploited by the Spanish fishing fleets, as well as advice on issues related to marine biology, oceanography, marine pollution and aquaculture. The Institute headquarters are located in Madrid but has eight coastal laboratories, five aquaculture plants and several research vessels. The current staff includes about 500 people, half of which are qualified scientists. Within REPROdUCE, IEO as the project coordinator will have the University of Rutgers as a subcontract (see below)

The participants:

The IEO participates in REPROdUCE with a total of 13 researchers and one devoted research contract (a total of 119 man months). The IEO team includes fishery scientist, biologist and ecologist, experts in sardine and anchovy assessment, biology and ecology, physics experts in hydrodynamical modeling, and plankton ecologist specialist in phytoplankton, zooplankton and fish early life stages. IEO will also request a contract to implement models of lowe trophic levels. A brief description of the IEO team is included below

Dr. Miguel Bernal [24 months] (attached CV) is a quantitative biologist, specialist in early life stages modeling and fishery independent estimates of Stock abundance and distribution. He is the general coordinator of REPROdUCE and will be participating in WP 02, 04, 05 and 06. M. Bernal experience on management in multinational consortiums includes participation in 5 different EU projects, either as a researcher, WP leader and Institute coordinator. He has also been the responsible for a review of the assessment of South Australian sardine stock, and an external consultant in the assessment of sardine, anchovy and horse mackerel stocks in Chilean waters. M. Bernal has also been chairing the ICES WG on the acoustic and daily egg production based assessment of Atlanto-European sardine and anchovy, and is the coordinator of the spring pelagic survey program in Northern Spanish waters. He is currently chairing the recently establish MARIFISH WP07 research program on the effects of climate in small pelagic fish (CLIMAFISH), and has recently been nominated as the co-chairman of the ICES Annual Science conference Theme Session F “How does fishing alter marine populations' and ecosystems' sensitivity to climate?”. M. Bernal has published a total of 13 manuscripts in peer-reviewed journals and books, and more than 50 working documents.

Dr. Manuel Ruiz Villarreal [12 months] is a physicist with more than 10 years experience in ocean numerical modeling and turbulence. He has developed several aspects of hydrodynamical models for a number of 3d baroclinic models (MOHID, GETM, ROMS) and has participated in the development of the General Ocean Turbulence Model (GOTM). He has leaded and participated in several projects dealing with hydrodynamics and modeling of ocean and estuarine areas north and northwest of the Iberian Peninsula at scales suitable for studying the impact of circulation on plankton and larvae. Dr. Enrique Nogueira [10 months] (attached CV), is a specialist on low trophic levels and hydrodynamic features affecting the pelagic community, as well as early life stages of anchovy and forage fish recruitment. Dr. A. Bode [6 months] and Dr. Manuel Varela [5 months] are also specialist in environmental effects on low trophic levels, as well as analysis of trophic behavior. Ana Lago de Lanzós [4 months] is an expert in pelagic fish early life stages, including sardine and anchovy egg spatial distribution, development and mortality rates. Dr Begoña Villamor [6 months] and Dr. Pablo Abaunza [2 months] are specialist on the biology and dynamics of exploited marine



species, mainly pelagic species, with special emphasis on anchovies mackerel and horse mackerel. They are the responsible for the analysis of biology and assessments of all pelagic species analysed in the Spanish surveys within the ICES area, and are both members of the relevant ICES WGs on biology and assessment of these species. They have extensive experience in national and European projects, both as research members and in coordination responsibilities. Dr. Magdalena Iglesias [5 months] is an expert in the use of acoustic methods for the direct estimation of pelagic fish distribution and abundance, and is the responsible within the IEO for the acoustic based estimation of the abundance of main pelagic species in both the Atlantic and Mediterranean region sampled by the IEO. Dr. Ignacio Olaso [4 months] is a well known specialist in trophic relationship between different demersal and pelagic species, and has an extensive database of stomach contents of different pelagic and demersal species. Dr. Rafael Gonzalez-Quiros [8 months] is an specialist in early life stages ecology, as well as assessment and modeling of pelagic species. Dr. Isabel Riveiro [6 months] is also an specialist in early life stages for pelagic fish, and is also the responsible of the IEO project ECOPEL (ecology of the pelagic community). Cristobal Suanzes [9 months] is the responsible of the management of different aspects of the MARIFISH ERA-NET and will be the responsible of the management of the REPROdUCE project.

IEO involvement within REPROdUCE

The IEO team will be involved in all WPs (see Table 1 under the REPROdUCE consortium section), with the following main task:

WP1 Hydrodynamic and lower trophic level models:

IEO will hire a dedicated scientist to implement a battery of lower trophic level models within the ROMs hydrodynamic model already applied by IEO scientist. The IEO team will be responsible for reviewing available NPZD models, as well as reporting adequacy of the available models to implement the decided lower trophic level conceptual model [deliverables D1.1 and D1.5]

WP2 Juvenile and adults:

Within WP02, IEO will be responsible of the development and implementation of habitat models for sardine and anchovy in the Bay of Biscay case study, for the description of how to communicate the different modules of the life cycle model, and for the definition of the validation criteria for the population module, in coordination with WP05 [deliverables D2.4, D2.10 and D2.12]

WP3 Models of early life stages dispersion and survival:

Implication of IEO in WP03 will be lower than in the rest of the WPs, and the main task within this WP will be to provide published information and data about distribution and abundance of eggs and larvae of the target species, and to coordinate the identification of main forcing functions in the developed conceptual Early Life Stages model which can act as recruitment drivers [deliverable D3.4].

WP4 Pelagic ecosystem model set-up and assemblage of model modules:

IEO will have an active participation in WP04, both from the direct work of IEO staff and in coordination with the subcontracted party IMCS (see below for a description of IMCS work). Participation in this WP includes review of existing coupled models, and work in coordination with the WP leader to couple the different modules created in WPs 01 to 03 [deliverable 4.1].



WP5 Validation, simulation scenarios and assessment of recruitment drivers:

IEO will take active part in the validation of the different modules and the final ecosystem model, following up the gathering of information on potential drivers from the conceptual models of WP01-03, and coordinating the list of alternative simulations to test the hypothesis of the effect of the different potential recruitment drivers [deliverables D5.5, D5.6 and D5.8]

WP6 Synthesis and building of recruitment strength indicators:

IEO will have the coordination responsibility for the synthesis of the project, as well as for building the recruitment strength indicators and coordinating the preparation of the final report [deliverable 6.1]

WP07 Project management

IEO will also have the coordination responsibility of WP07, in which it will be responsible for providing the required tools to enhance communication among partners and with the MARIFISH secretariat and other interested parties [deliverables 7.1 – 7.4].

Selected related papers:

Álvarez E., Nogueira E., Acuña J.L., López-Álvarez M., Sostres J. 2009. Short-term dynamics of late-winter phytioplankton blooms in a températe ecosystem (Central Cantabrian Sea, Southern Bay of Biscay). Journal of Plankton Resrach (in press).

Bernal, M., Stratoudakis, Y., Coombs, S., Angelico, M., de Lanzos, A., Porteiro, C., Sagarminaga, Y., Santos, M., Uriarte, A., Cunha, E., Valdes, L. and Borchers, D., 2007. Sardine spawning off the European Atlantic coast: Characterization of and spatio-temporal variability in spawning habitat. Progress in Oceanography, 74:210-227.

Bode, A., Alvarez-Ossorio, M.T., Cunha, M.E., Garrido, S., Peleteiro, J.B., Porteiro, C., Valdes, L. and Varela, M., 2007. Stable nitrogen isotope studies of the pelagic food web on the Atlantic shelf of the Iberian Peninsula. Progress in Oceanography, 74:115-131.

Nogueira, E., Gonzalez-Nuevo, G., Bode, A., Varela, M., Moran, X.A.G. and Valdes, L., 2004. Comparison of biomass and size spectra derived from optical plankton counter data and net samples: application to the assessment of mesoplankton distribution along the Northwest and North Iberian Shelf. Ices Journal of Marine Science, 61:508-517.

Olaso, T., Gutierrez, J.L., Villamor, B., Carrera, P., Valdes, L. and Abaunza, P., 2005. Seasonal changes in the north-eastern Atlantic mackerel diet (Scomber scombrus) in the north of Spain (ICES Division VIIIc). Journal of the Marine Biological Association of the United Kingdom, 85:415-418.

Otero, P., Ruiz-Villarreal, M. and Peliz, Á., 2008. Variability of river plumes off NorthWest Iberia in response to wind events. Journal of Marine Systems 72, 238-255.

Uriarte, A., Prouzet, P., and B. Villamor, 1996. Bay of Biscay and Ibero Atlantic Anchovy populations and their fisheries. SCI. MAR., 60 (Supl.2): 237-255.

Varela, M.M., Bode, A., Moran, X.A.G. and Valencia, J., 2006. Dissolved organic nitrogen release and bacterial activity in the upper layers of the Atlantic Ocean. Microbial Ecology, 51:487-500.

Villamor, B., Bernal, M. and Hernandez, C., 2004. Models describing mackerel (Scomber scombrus) early life growth in the North and Northwest of the Iberian Peninsula in 2000. Scientia Marina, 68:571-583.



IEO subcontract: Institute of Marine and Coastal Sciences (IMCS), University of Rutgers, United States of America.

Apart from its direct participation on REPROdUCE, IEO will dedicate part of the REPROdUCE funds to subcontract the Ocean Modeling Group, a research group within the Institute of Marine and Coastal Sciences, of the University of Rutgers in New Jersey (United States of America).

The Rutgers University Ocean Modeling Group co-develops the Regional Ocean Modeling System (ROMS), a hydrodynamic model in widespread use globally for studies of estuarine, coastal, continental shelf, mesoscale and basin-scale processes. The group also hosts the http://myroms.org portal that maintains the ROMS source code and provides training and instructional resources for a collaborative community of over 1200 users world-wide.

Application modules coupled to ROMS include biogeochemical models of varying complexity, from a 4-variable (nutrient/phytoplankton/zooplankton/detritus) NPZD model designed for ecological data assimilation, through incorporation of carbon cycling, dissolved oxygen and predatory zooplankton, up to a 60-variable model encompassing multiple chemical elements, phytoplankton functional groups, and pigments that simulates bio-optics in coastal waters.

Studies utilizing ROMS have already simulated nutrient, carbon, and oxygen cycling, primary production, shelf-wide sediment transport, the dispersal of natural and polluted terrestrial runoff, and shelf/deep- ocean exchange.

Individual Based Models (IBM) of higher trophic level organisms complement these ecosystem models. ROMS can run fully coupled to community surface wind wave (SWAN) and mesoscale Weather Research and Forecasting (WRF) models, supports 2-way nested and composite domains, and has an Earth System Modeling Framework (ESMF) interface.

The participation of IMCS in REPROdUCE will focus on the coordination of the implementation of the coupled biogeochemical full life cycle ecosystem model of sardine and anchovy in both case studies. The main person involved from the Ocean Modeling Group at IMCS will be Enrique Curthitser [3 months] (attached CV), an specialist in hydrodynamic models and biophysical coupling of different ecosystem modules.

Selected publications:

Di Lorenzo, E., N. Schneider, K.M. Cobb, K. Chhak, P.J. Franks, A.J. Miller, J.C. McWilliams, S.J. Bograd, H. Arango, E.N. Curchitser, T.M. Powell and P. Rivere, 2008. North Pacific Gyre Oscillation links ocean climate and ecosystem change. Geophys. Res. Lett., 35, L08607,doi:10.1029/2007GL032838.

Powell, T, C. Lewis, E.N. Curchitser, D.B. Haidvogel, A.J. Hermann and E.L Dobbins, 2006.Results from a three-dimensional, nested biological-physical model of the California Current System and comparisons with statistics from satellite imagery. J. Geophys. Res., 111, C07018,doi:10.1029/2004JC002506

Curchitser, E.N., D.B. Haidvogel, A.J. Hermann, E. Dobbins, T.M. Powell and A. Kaplan, 2005.Multi-scale modeling of the North Pacific Ocean: Assessment of simulated basin-scale Variability(1996-2003). J. Gophys. Res., 110, C11021, doi:101029/2005JC002902.

Haidvogel, D.B., E.N. Curchitser, M. Iskandarani, R. Hughes, and M. Taylor, 1997. Global modeling of the ocean and atmosphere using the spectral element method. Atmo.-Oce. Vol XXXV, No. 1.



PARTNER 02: HCMR – Hellenic Centre for Marine Research (Greece)

The Institute: The Hellenic Centre for Marine Research (HCMR) is a governmental research organization operating under the auspices of the General Secretariat of Research and Technology (Ministry of Development). It has the mandate to promote basic research in all fields of aquatic environment and to deliver comprehensive scientific and technical support to the public. It was formed by the merging between the National Centre for Marine Research (NCMR) and the Institute of Marine Biology of Crete (IMBC) and it is now composed by the following five Institutes: Oceanography, Marine Biological Resources, Inland Waters, Aquaculture, Marine Biology & Genetics. The scientific personnel numbers 200 researchers and 90 technicians while 55 people support its administration. HCMR operates the 62m R/V Aegaeo, the 27m R/V Filia and the manned submersible THETIS with a total crew of 34 persons as well as two aquariums in Crete and Rhode Islands.

The contributions to the project will be provided by staff of the Institute of Marine Biological Resources and the Institute of Oceanography which will work closely together. Hydrodynamic and ecosystem models fully implemented within the POSEIDON framework by staff of the Institute of Oceanography (see below) and data on small pelagic fish collected by the fisheries surveys carried out by the Institute of Marine Biological Resources will form the basis for the development of project actions in the northern Aegean Sea (Mediterranean case study).

Institute of Marine Biological Resources (IMBR)

The IMBR is a major fisheries Institute of the Mediterranean Sea specialized in numerous aspects of Marine Fisheries Ecology and Management. It is the Institution responsible for the collection and management of fisheries data in Greece, for carrying out the direct surveys, including acoustic and egg production (DEPM) surveys for small pelagic fish and for producing assessments of the stocks. Its personnel have a long experience in research related to small pelagic fish, including habitat mapping, ecology of the early life stages, adult reproduction, feeding and growth. Recent projects of IMBR focusing on small pelagic fish include SARDONE (Improving assessment and management of small pelagic species in the Mediterranean. FP6-44294), Envi-EFH (Environmental Approach to Essential Fish Habitat Designation. FP6-22466) and SMALL PELAGIC (Improvement of in year management of small pelagic fish in Aegean Sea. FISH/2004/03-35).

Institute of Oceanography (IO)

Within the last 20 years the IO has contributed to a large number of international research projects, carried out in several regions of the Mediterranean and the Black Seas, such as: POEM, METROMED, KEYCOP, PELAGOS, OTRANTO, CINCS, MATER, THETIS, ANAXIMANDER, HERMES, MEDATLAS, MARSAIS, DANUBES, INTERPOL, BIMS, EDIOS, ESONET NoE, SESAME, etc. At the same time it participates in large international initiatives such as GLOBEC and GOOS and supports actively the efforts of IOC. Since 1996, HCMR is a member of EuroGOOS and contributes by (a) developing a national capacity in operational monitoring and forecasting through the POSEIDON project, and (b) participating in various EU funded research projects for the development of a European capacity in Operational Oceanography [e.g. MFS-PP (1999-2001), MAMA (2002-2004), Ferry-Box (2002-2005), MERSEA-Strand1 (2003-2004) and MFSTEP (2003-2005)]. The POSEIDON system was implemented during 1997-2000 following a 14Meuro investment of EFTA and the Hellenic Ministry of Economy and since the beginning of 2000 it provides operationally information and forecasts for meteorological conditions, sea-state, currents, hydrological structure and water quality in the Eastern Mediterranean. During the second phase of its implementation, the system has been updated to incorporate the latest technological advances in ocean monitoring, numerical modelling and remote sensing.



The participants::

Mr Stylianos Somarakis is a Senior Researcher of IMBR-HCMR . He has a PhD (1999) and MSc (1991) in Fisheries Ecology from the University of Crete. He was a Lecturer in the Biology Department of the University of Patras (2002-2006) and Assistant Professor in the Biology Department of the University of Crete in 2007. During the last 16 years he has participated/coordinated in more than 16 National and European projects in the field of fisheries ecology and management and has published more than 50 articles in peer reviewed journals. He is an expert in ichthyoplankton, larval fish ecology and fish reproduction with long experience in European anchovy and sardine. He is currently co-leading the Working Group on fish reproductive potential of the pan-European COST Action: “Fish Reproduction and Fisheries”. He is chairman of the working group on small pelagics of the General Fisheries Council for the Mediterranean (GFCM-Scientific Advisory Committee) and member of the Scientific Technical and Economic Committee for Fisheries (DG FISH). He is Contributing Editor of the Journal ‘Marine Ecology Progress Series’.

Mr George N. Triantafyllou is a Research Director of the IO-HCMR. He has a Ph.D. (1990) in Oceanography from the Aristotle University of Thessaloniki, after his M.Sc. (1988) in Oceanography and his B.Sc. (1982) in Mathematics from the University of Athens. He was faculty / academic staff (1992-1994) at the University of Wisconsin-Milwaukee, Dept. of Geosciences teaching Dynamic Meteorology courses to postgraduate and undergraduate students, and conducting research in Geophysical Fluid Dynamics and Non-linear Dynamics. Since 1995, joining HCMR, he has been involved either as researcher, principal investigator or major partner in EU and national projects some of which follow: MATER-MAST II (CT96-0051/1996-1999), THETIS (EU-ESPRIT F0069/1998-2001), MFSPP (MAS 3-CT98-0171/1998-2001), MEDNET (MAS3-CT98-0189/1999-2001), COST-IMPACT (Q5RS-2001-00993/2001-2003), MFSTEP (EVK3-2001-00174/2003-2005), INSEA (SST4-CT-2005-012336/2006-2008), ECOOP (EU/FP6, 2007-2013), SESAME (EU/FP6, 2006-2010), SARDONE (EU/FP6, 2007-2009). Currently he is participating in numerous projects conducting research in ecosystem modelling and data assimilation. His research interests include the development and application of numerical mathematical models and management tools, data analysis, data assimilation, nonlinear dynamics, nonlinear prediction, climate dynamics, ecosystem dynamics. He has a list of 53 publications in peer-review journals.

Ms Marianna Giannoulaki, holds a Masters degree in Marine Biology and a PhD degree in Fisheries Ecology (2003). In the last 5 years, she has been participating in several national and European funded projects on small pelagic fish (anchovy and sardine). Her work focuses on fish population dynamics and stock assessment, fisheries acoustics, spatial modeling, spatial indices, application of geostatistics in Fisheries, application of Generalised Additive Models in Fisheries Ecology, species-environment relationships, essential fish habitat of small pelagics as well as ecosystem based modeling. Currently, she holds a position of Assistant Researcher in the Institute of Marine Biological Resources of HCMR.

Mr Athanassios Machias holds a Masters degree in Marine Biology and a PhD degree in Fisheries acoustics (1994). Currently, he holds a position of Research Director in IMBR-HCMR and he is coordinating the hydroacoustic team of the Institute. In the last 12 years, he has participated/coordinated in numerous national and European projects on fisheries biology and assessment of small pelagic fishes (anchovy and sardine). His main fields of interest are fisheries acoustics, fisheries biology (age & growth, feeding), spatial modeling, species-environment relationships and marine ecosystem management.

Ms Anna I. Pollani is a systems analyst/programmer at the Institute of Oceanography HCMR since 1997, having prior professional experience of more than 15 years. She has active



participation in several EU research projects of the Institute of Oceanography (FIGIS, THETIS, MFSPP, MFSTEP, COST-IMPACT, INSEA, AQUAPLANNER, etc) and other environmental impact studies of national projects, skilled in the area of developing and applying numerical models and management tools on the marine environment.

Mr George I. Petihakis is an associate researcher of the Institute of Oceanography, HCMR. He got an M.Sc. (1989) in Applied Fish Biology from the Polytechnic South West (Plymouth) after completed his B.Sc. (1988) in Ecology from the Royal Holloway and Bedford new College University of London. His Ph.D. (2004) is on «Hydrodynamic and Ecological Simulation of the Ecosystem of Pagasitikos» from the University of Thessaly. He is conducting research in Marine Dynamics and Ecosystem Modeling. Since 1995, joining HCMR, he is participating in national and EU research projects, mainly in the field of ecological modelling.

Mr Konstantinos Tsiaras is a research scientist of the Institute of Oceanography HCMR. He has active participation in several multi-disciplinary European projects, such as DANUBS, MFSTEP, POSEIDON-II, SESAME, and in national projects as well. His scientific interests focus on numerical modeling of biogeochemical processes and hydrodynamics.

Mr Gerasimos Korres is an associate researcher of the Institute of Oceanography since January 2003. He has a B.Sc in Physics (1989), an M.Sc in Oceanography (1992) and a Ph.D in Physical Oceanography (1996) from the University of Athens. He has been involved in a large number of EU research projects and in national projects as well. Recently, he participated in the FP4/MFSPP and FP5/MFSTEP projects, with contribution to forecasting of the Eastern Mediterranean general circulation and in the FP4/FERRYBOX project, with contribution to developing data assimilation methods for the POSEIDON forecast system. His main interests are in the field of hydrodynamic numerical modeling/forecasting, wave modelling, data assimilation in hydrodynamic/wave models and air-sea interaction processes.

Mr Vasilis Valavanis is an environmental biologist and a GIS/RS scientist with extensive work on ocean-process and marine habitat mapping based on surveyed and remotely-sensed data and environmental habitat descriptors derived through species life history data. He coordinated and participated in a variety of EC-funded research on habitat modeling and fisheries-environment interactions (e.g. FAIR-FIGIS, FP4-ABDMAP,FAIR-CEPHVAR, FP5-MAMA, FP5-CEPHSTOCK, FP6-EnviEFH, FP7-U@MareNostrum).

Mr Stelios Katsanevakis is an assistant researcher in IMBR-HCMR. He holds a PhD in Biological Oceanography and his research work focuses on population dynamics, estimating abundance and monitoring of marine populations, spatial modelling, information theory, and conservation. He has participated in several national and EU-funded projects. Author/coauthor of 27 papers in international journals, 23 contributions in national and international congresses, and 3 book chapters.

Selected publications: Politikos D.V., Triantafyllou G., Petihakis G., Somarakis S., Ito S-I., Megrey B.A., Tsiaras K.P., submitted. Linking

a lower trophic level ecosystem model with a bioenergetics model for European anchovy (Engraulis encrasicolus).

Tsiaras K. P., Kourafalou V.H., Davidov A. and Staneva J., 2008. A three-dimensional coupled model of the western Black Sea plankton dynamics: Seasonal variability and comparison to SeaWiFS data. Journal of Geophysical Research C: Oceans 113 (7), art. no. C07007

Giannoulaki M., Valavanis D.V., Palialexis A., Tsagarakis K., Machias A., Somarakis S., Papaconstantinou C., 2008. Modeling the presence of anchovy Engraulis encrasicolus in the Aegean Sea during early summer, based on satellite environmental data. Hydrobiologia 612: 225–240



Schismenou E., Giannoulaki M., Valavanis V.D., Somarakis S., 2008. Modeling and predicting potential spawning habitat of anchovy (Engraulis encrasicolus) and round sardinella (Sardinella aurita) based on satellite environmental information. Hydrobiologia 612: 201-214

Korres G., Hoteit I., Triantafyllou G., 2007. Data assimilation into a Princeton Ocean model of the Mediterranean Sea using advanced Kalman filters. Journal of Marine Systems 65: 84-104

Kourafalou V., Tsiaras K., 2007. A nested circulation model for the North Aegean Sea. Ocean Science, 3: 1-16 Triantafyllou G., Korres G., Hoteit I., Petihakis G., Banks A.C., 2007. Assimilation of ocean colour data into a

Biochemical Flux Model of the Eastern Mediterranean Sea. Ocean Science 3: 397- 410 Somarakis S., Nikolioudakis N., 2007. Oceanographic habitat, growth and mortality of larval anchovy (Engraulis

encrasicolous) in the northern Aegean Sea (eastern Mediterranean). Marine Biology 152: 1143-1158 Mantzouni I., Somarakis S., Moutopoulos D.K., Kallianiotis A., Koutsikopoulos C., 2007. Periodic, spatially

structured matrix model for the study of anchovy (Engraulis encrasicolus) population dynamics in the N. Aegean Sea (E. Mediterranean). Ecological Modelling 208: 367-377

Giannoulaki M., Machias A., Koutsikopoulos C., Somarakis S., 2006. The effect of coastal topography on the spatial structure of anchovy and sardine. ICES Journal of Marine Science, vol. 63: 650-662

Somarakis S., Ganias K., Siapatis A., Koutsikopoulos C., Machias A., Papaconstantinou C., 2006. Spawning habitat and daily egg production of sardine in the eastern Mediterranean. Fisheries Oceanography 15: 281-292

Triantafyllou G., Hoteit I., Korres G., Petihakis G., 2005. Ecosystem modeling and data assimilation of physical-biogeochemical processes in shelf and regional areas of the Mediterranean Sea. App. Num. Anal. Comp. Math. 2: 262-280

Petihakis G., Triantafyllou G., Pollani A., Koliou A., Theodorou A., 2004. Field data analysis and application of a complex water column biogeo-chemical model in different areas of a semi-enclosed basin: Towards the development of an ecosystem management tool. Marine Environmental Research 59: 493-518

Somarakis S., Palomera I., Garcia A., Quintanilla L., Koutsikopoulos C., Uriarte A., Motos L., 2004. Daily egg production of anchovy in European waters. ICES Journal of Marine Science 61: 944-958

Triantafyllou G., Hoteit I., Petihakis G., 2003. A singular evolutive interpolated Kalman filter for efficient data assimilation in a 3D complex physical-biogeochemical model of the Cretan Sea. Journal of Marine Systems 40-41: 213-231

Triantafyllou G., Korres G., Petihakis G., Pollani A., Lascaratos A., 2003. Assessing the phenomenology of the Cretan Sea shelf area using coupling modelling techniques. Annales Geophysicae 21: 237-250

Petihakis G., Triantafyllou G., Allen J.I., Hoteit I., Dounas C., 2002. Modelling the spatial and temporal variability of the Cretan Sea ecosystem. Journal of Marine Systems 36: 173-196

Valavanis V.D., 2002. Geographic Information Systems in Oceanography and Fisheries. Taylor & Francis, London, 240pp.



PARTNER 03: IFREMER- Institut Français de Recherche pour l'Exploitation de la MER (France)

The institute : Ifremer is a public body created in 1984, and is the only French research organisation with an entirely maritime remit. It operates under the joint auspices of three Ministries: Higher Education and Research, Agriculture and Fisheries, and Ecology, Sustainable development and Infrastructure.

Being involved in all marine science and technology domains, Ifremer has the capability of solving different problems with an integrated approach. Ifremer's scope of action can be divided into four main areas, each of them including different topics as described hereunder:

1. Understanding, assessing, developing and managing ocean resources (knowledge and exploration of the deep sea; contribution to the exploitation of offshore oil; understanding ocean circulation in relation with the global change; sustainable management of fishery resources; optimisation and development of aquaculture production)

2. Improving knowledge, protection and restoration methods for the marine environment

3. Production and management of equipment of national interest

4. Helping the socio-economic development of the maritime world

The participants:

EMH (Nantes): The laboratory on ecology and modelling for fisheries is involved in research on ecosystems with fishery interests, to help defining conditions for long-term exploitation of marine resources and associated ecosystems. Mathematic and statistic methods are developed for these objectives, in addition to direct observations at sea.

Dr Pierre Petitgas [12 months] is a specialist of mapping spatial distributions of pelagic fish populations and their spatial relationships with abiotic and biotic environments. He has developed methods for analyzing spatial aggregation patterns. Within the EU project Fisboat he has developed monitoring schemes for spatial indicators derived from surveys and also from operational oceanography products. He has coordinated 2 EU projects and was involved in 4 others. He chaired the ICES Living Resources Committee and 3 ICES expert groups. At national level, he coordinated the pelagic component of the Bay of Biscay national program PNEC-Gascogne. He is involved in the Biscay spring pelagic ecosystem survey series and in the across compartment analysis with other teams at regional scale. He coordinates Ifremer's participation to the running EU project RECLAIM.

Dr Martin Huret [12 months], PhD in physical and biological oceanography, is working on the modelling of the dynamics of marine systems, with focus on physical and biological interactions. He was first involved in primary production modelling with coupled physical-biogeochemical models, focusing on the parameter optimisation from ocean color satellite data. He is since 2007 at Ifremer, involved in fisheries oceanography activities with connection to operational oceanography, with a focus on ichtyoplankton transport and survival and their coupling with lower trophic level models. Within the EU project RECLAIM he coordinated a long term hindcast run of a coupled physical-biogeochemical model and climate projection scenarios, and their use as forcing conditions to fish IBM and habitat models. He coordinates Ifremer's participation to the running EU project UNCOVER.

Jacques Massé [4 months] is in charge of Ifremer pelagic acoustic assessment surveys in the Bay of Biscay since 1988 (now funded by the EU under the DCR), and is mainly working on fisheries acoustics and the ecology of pelagic fish. He has participated in the development



of Image Analysis software for real time echotrace recognition and characterization (MOVIES). He has participated in four EU projects dealing with the improvement of stock assessments by direct methods and with the spatial distribution and aggregation patterns of fish schools. He coordinated with F. Gerlotto the symposium on acoustics in fisheries and aquatic ecology in Montpellier (June 2002).

DYNECO (Brest): The laboratory develops research activities to study coastal ocean ecosystems. Different tools, methods and observation systems support this research, from simple hydrodynamic to 3D coupled physical-biological-sediment model, and from in-situ data to remote sensing processed images. Within REPROdUCE, Marc Sourisseau will be involved and give support in the modelling activity of WP1. Dr. Marc Sourisseau [2months] specialist in lower trophic levels modelling for responsible for the operational coupled physical-biogeochemicel model at Ifremer will be involved and provide his expertise in the modelling activity of WP1.

IFREMER involvement within REPROdUCE

IFREMER will be contributing to all WPs, especially in relation to the Bay of Biscay case study, but also in the development of general methods and theories for modelling the pelagic ecosystem and understanding sardine and anchovy recruitment process.

WP1 Hydrodynamic and lower trophic level models:

Ifremer will provide its actual modelling expertise on lower trophic levels. A new hindcast simulation with new improvements of the model (ECO-MARS3D) is expected within the project. This hindcast will form the basis for environment variables to be transferred to WP4, with selected years to be run as validation years or scenarios. New developments of the biological model will mainly concern the size structure of zooplankton, to better fit needs of the WP2 and WP3 models in terms of prey fields. A postdoctoral fellow will be hired [18 months] at Ifremer to insure this model development task using historical data (at Ifremer and Université of La Rochelle) on zooplankton taxonomy, dry weight and size spectrum.

WP2 Juvenile and adults:

Ifremer will apply and test a set of mapping tools (GAM, EOF, geostatistics) for modelling the habitats of juvenile and adult fish in relation to environment and fish abundance. Also, to better define successfulness of habitats, especially for juveniles, and unfavourable habitats, especially for adult migrations, IBM models integrating bioenergetic formulations will be applied. Last, competitor and predator fields will be constrained by abundance fields of sardine/anchovy parallel life cycle model and also by other pelagic species spatial mapping or top predators. The latter process will take advantage of a collaboration with specialists at Université of La Rochelle in the frame of a french funding (ANR).The collaboration with University of La Rochelle will also allow to acquire data for model construction and validation (isotopes for branching correctly the fish in the ecosystem and energy density for validating bioenergetic models).

WP3 Models of early life stages dispersion and survival:

Ifremer will continue developments on the IBM model of early life stages of anchovy. This model will for the first time be applied to sardine with necessary adaptation. New developments will focus on the coupling to the improved lower trophic level model (as described above) for growth, and on the implementation of processes for which new knowledge has been gathered on recent surveys. Also we will test the possibility of coupling of the actual IBM to a bioenergetic model already applied in a simple configuration. Collaboration with University of La Rochelle will be helpful in doing so, in particular in correctly defining the appropriate food of the larvae using isotopes and gut contents.



WP4 Pelagic ecosystem model set-up and assemblage of model modules:

Ifremer will actively participate in the coupling of the different modules developped in WP1-3.

WP5 Validation, simulation scenarios and assessment of recruitment drivers:

Ifremer will take part of the overall validation process, and run simulation scenarios.

WP6 Synthesis and building of recruitment strength indicators:

Ifremer will investigate how process-based models can be beneficial for defining appropriate indicators for monitoring purposes.

Summary of Man-Month involvement:

WP1: 15 months WP2: 20 months WP3: 12 months WP4: 4 months WP5: 5 months

WP6: 4 months

Selected publications: Allain, G., Petitgas, P., Grellier, P. and Lazure, P. 2003. The selection process from larval to juvenile stages of

anchovy (Engraulis encrasicolus) in the bay of Biscay investigated by lagrangian simulations and comparative otolith growth. Fisheries Oceanography, 12: 407-418.

Allain G., Petitgas P., Lazure P. 2007a. The influence of environment and spawning distribution on the survival of anchovy (Engraulis encrasicolus) larvae in the Bay of Biscay (NE Atlantic) investigated by biophysical simulations. Fisheries Oceanography 16, 506-514.

Allain G., Petitgas P., Lazure P., Grellier P. 2007b. Biophysical modeling of larval drift, growth and survival for the prediction of anchovy (Engraulis encrasicolus) recruitment in the Bay of Biscay (NE Atlantic). Fisheries Oceanography 16, 489-505.

Bellier, E., Planque, B. and Petitgas, P., 2007. Historical fluctuations of spawning area of anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) in the Bay of Biscay during 1967-73 end 2000-2004. Fish. Oceanogr., 16(1): 1-15.

Dubreuil, J. and Petitgas, P. 2009. Energy density of anchovy Engraulis encrasicolus in the Bay of Biscay. Journal of Fish Biology. 74(3):521-534.

Gallego, A., North, E. and Petitgas, P. 2007. Advances in modelling physical–biological interactions in fish early life history. Marine Ecology Progress Series, 347: 121–126.

Goarant, A., Petitgas, P. and Bourriau, P. 2007. Anchovy (Engraulis encrasicolus) egg density measurements in the Bay of Biscay: evidence for the spatial variation in egg density with sea surface salinity. Marine Biology, 151: 1907-1915.

Huret M., C. Struski, F. Léger, P. Petitgas, P. Lazure and M. Sourisseau. 2009. Modélisation couplée physique-biogéochimie du golfe de Gascogne sur la période 1971-2007. R.INT.DOP/EMH/2009-01. In French.

Huret M., J. A. Runge et C. Chen. 2007. Dispersal modeling of fish early life stages : Sensitivity with application to Atlantic cod in the Western Gulf of Maine. A modeling sensitivity study. Marine Ecology Progress Series, 347, 261-274.

Huret M., F. Gohin, D. Delmas, M. Lunven and V. Garçon. 2007. Use of SeaWiFS data for improving the simulation of winter to spring phytoplankton production in the Bay of Biscay. Journal of Marine Systems, 65, 509-531.

Lazure P., Dumas F. 2008. An external-internal mode coupling for a 3D hydrodynamical model for applications at regional scale (MARS). Advances in Water Resources. 31: 233-250.

Lazure P., Garnier V., Dumas F., Herry C., Chifflet M., 2009. Development of a hydrodynamic model of the Bay of Biscay. Validation of hydrology. Continental Shelf Research, accepted.

Pecquerie L., P. Petitgas, M. Huret and A. Ménesguen. 2005. Modelling anchovy growth according to environmental conditions. ICES CM 2005/O:21.

Pecquerie L., M. Huret, P. Petitgas and A. Ménesguen. 2004. Use of coupled circulation and ecosystem NPZ models to characterise food conditions of anchovy in the Bay of Biscay. ICES CM 2004/P:33.

Petitgas, P. 2008. Fish Habitat Mapping with Empirical Orthogonal Functions. ICES CM 2008/M:07 Petitgas, P. 2009. Geostatistics and their applications to fisheries survey data: a history of ideas, 1990–2007.

Computers in Fisheries Research. B. Megrey and E. Moksness, Springer Netherlands: 191-224. Petitgas, P., Beillois, P., Massé, J., and Grellier, P. 2004. On the importance of adults in maintaining population

habitat occupation of recruits as deduced from observed schooling behaviour of age-0 anchovy in the Bay of Biscay. ICES CM 2004/J:13.

Petitgas, P., Magri, S. and Lazure, P., 2006. One-dimensional biophysical modelling of fish egg vertical distributions in shelf seas. Fish. Oceanogr., 15(5): 413-428.



Petitgas, P., Massé, J., Bourriau, P., Beillois, P., Bergeron, J.P., Delmas, D., Herbland, A., Koueta, N., Froidefond, J.M. and Santos, E., 2006. Hydro-plankton characteristics and their relationship with sardine and anchovy distributions on the French shelf of the Bay of Biscay. Sci. Mar., 70(S1): 161-172.

Planque B. and Buffaz L. 2008. Quantile regression models for fish recruitment-environment relationships: four case studies. Marine Ecology Progress Series. 357:213-223.

Planque, B., Bellier, E. and Lazure, P., 2007. Modelling potential spawning habitat of sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus) in the Bay of Biscay. Fish. Oceanogr., 16(1): 16-30.

Marquis, E., Petitgas, P., Niquil, N. and Dupuy, C. 2006. Influence of the small pelagic fish on the structure and functioning of the planktonic food web on the continental shelf of the Bay of Biscay. ICES CM 2006/F:09.

Massé, J. and Gerlotto, F., 2003. The three dimensional morphology and internal structure of Clupeid schools as observed using vertical scanning multibeam sonar. Aquatic Living Resources, 16:9.

Sourisseau, M., and F. Carlotti (2006), Spatial distribution of zooplankton size spectra on the French continental shelf of the Bay of Biscay during spring 2000 and 2001, J. Geophys. Res., 111, C05S09, doi:10.1029/2005JC003063.

Associated french partnership:

To be able to fulfil the commitments of IFREMER in different tasks of REPROdUCE, some additional funds will be requested at ANR (National Research Agency). The additional funds are included in the IFREMER budget section (other costs).

These additional funds will also enable collaboration with other French research teams bringing additional expertise to the project. These additional partners for the French part of MARIFISH will be Université de la Rochelle with CRMM (Centre de Recherche sur les Mammifères Marins), specialized in top predators (birds, marine mammals) research activities. They will help defining predator fields’ variability on anchovy and sardine and trophic interaction through stable isotopes analysis. They will also provide energy density estimates of small pelagic fish on a seasonal basis to validate/calibrate bioenergetic models. CRELA (Centre de Recherche sur les Ecosystèmes Littoraux Anthropisés), also from Université de la Rochelle will supply lower trophic level data and expertise for modelling activity in WP1 (stable isotopes to model the trophic linkeage of fish larvae).

Key personnel and recent publications for additional french partnership:

Prof. Vincent Ridoux (CRMM, Univ-La Rochelle). He is professor at the University of La Rochelle. He works on ecology and conservation of pelagic top predators, with a focus on marine mammals. He has extensive experience of large scientific projects and the management of groups of scientists. He participated in 13 national and international research projects, including European projects and has published 55 papers in international journals. He is currently expert for the ministry in charge of the environment, for the ministry of foreign affairs, for the International Whaling Commission, for Agency for marine Protected Areas.

Dr. Christine Dupuy (CRELA, Univ-La Rochelle). She is Associate Professor at University of La Rochelle, specialist of protozoa and microbial pathways from bacteria and phytoplankton to meso-zooplankton. She is collaborating with Ifremer teams on the reltionships between zooplankton and anchovy larvae. She has directed several thesis on the pelagic microzooplankton and micribial production in the Bay of Biscay. She is presently coordinator of a national project on microbial films in tidal flats.

Barnes C., Bethea D.M., Brodeur R.D., Spitz J., Ridoux V., Pusineri C., Chase B.C., Hunsicker M.E., Juanes F., Conover D.O., Kellermann A., Lancaster J., Ménard F., Bard F.-X., Munk P., Pinnegar J.K., Scharf F.S., Rountree R.A., Stergiou K.I., Sassa C., Sabates A. and Jennings S., 2008. Predator and prey body sizes in marine food webs. Ecology, 89(3): 881.

Dupuy, C., Ryckaert, M., Le Gall, S. et al. 2007. Seasonal variations in planktonic community structure and production in an atlantic coastal pond: The importance of nanoflagellates. Microbial Ecology, 53: 537-548.

Lahaye V., Bustamante P., Spitz, J., Das K., Meynier, L., Magnin V., Dabin W. and Caurant F., 2005. Long-term preferences of common dolphins (Delphinus delphis) in the Bay of Biscay using cadmium (Cd) as a metallic tracer. Marine Ecology Progress Series, 305: 275-285.

Marquis E., N. Niquil, D. Delmas, H.J. Hartmann, D. Bonnet, F. Carlotti, A. Herbland, C. Labry, B. Sautour, P. Laborde, A. Vézina and C. Dupuy 2007. Inverse analysis of the planktonic food web dynamics related to



phytoplankton bloom development on the continental shelf of the Bay of Biscay, French coast. Estuarine and Coastal Shelf Science 73, 223-235.

Meynier L., Pusineri C., Spitz J., Santos M.B., Pierce G.J. and Ridoux V., 2008. Intraspecific dietary variation in the short-beaked common dolphin Delphinus delphis in the Bay of Biscay: importance of fat fish. Marine Ecology Progress Series, 354: 277-287.

Pascal, P.-Y., Dupuy, C., Richard, P. et al. 2008. Bacterivory in the common foraminifer Ammonia tepida: Isotope tracer experiment and the controlling factors. J. Exp. Mar. Biol. Ecol., 359: 55-61.

Spitz J, Rousseau Y. and Ridoux V. 2006. Diet overlap between harbour porpoise and bottlenose dolphin: an argument in favour of interference competition for food ? Estuarine, Coastal and Shelf Science, 70: 259-270.

Spitz J., Richard E., Meynier L., Pusineri C. and Ridoux V., 2006. Dietary plasticity of the oceanic striped dolphin, Stenella coeruleoalba, in the neritic Bay of Biscay.Journal of Sea Research, 55: 309-320.

PARTNER 04: AZTI – tecnalia (SPAIN)

The institute AZTI (www.azti.es) is a private non-for-profit research organization. AZTI belongs to the recently created research corporation called TECNALIA that has become the fifth EU private research organization in size. The Marine Research Unit of AZTI has a long experience in oceanographic studies and, particularly in the fields of fisheries, ecology and hydrodynamics. During the last 5 years the Marine Research Unit has been involved in more than 24 EU projects, published 91 reviewed articles, including a book dedicated to the Oceanography of the Basque Country. AZTI has been an active participant in various EU-funded projects related to the Bay of Biscay and in particular to small pelagics as anchovy and sardine or to mackerel and horse mackerel.

The participants:

Dr. Xabier Irigoien is expert on plankton ecology and ecosystem functioning. His research is focused on basic laws controlling ecosystem dynamics. He is leader of the Marie Curie EST METAOCEANS and WP leader in the VII framework project MEECE. He will participate leading WP1 and collaborate in WP4.

Dr. Marina Chifflet is expert on ecosystem modeling. Her research focuses on the impact of human activities and climate variability on the ecosystem productivity and size structure. She will participate on WP1 and 4.

Leire Ibaibarriaga is expert on fish population dynamics, fisheries modeling and fisheries management. She will participate in WP4.

Dr. Unai Cotano is expert on fish larvae ecology. His research is oriented to the understanding of factors controlling fish larval growth and mortality. He will contribute to WP2 and 3 through the analysis of existing data.

AZTI involvement within REPROdUCE

WP1 Hydrodynamic and lower trophic level models (AZTI: 10 months)

AZTI will provide its actual modelling expertise on coupled hydrodynamic - lower trophic levels models. A new hindcast simulation with the model ROMS coupled to a lower trophic levels model will be performed. This hindcast will provide the environment variables to be transferred to WP2 and 3, and then assembled with in WP4. Hindcast runs will be performed on years when data sets are available.

WP2 Juvenile and adults (AZTI: 1 month):

AZTI will work in the development of the anchovy-sardine modules for the ROMS-NPD-APECOSM model (see below).

WP3 Models of early life stages dispersion and survival (AZTI: 1 month)



AZTI will include the early life stage IBM of anchovy in ROMS-N2P2Z2D2 (or in the AZTI Lagrangian model).

WP4 Pelagic ecosystem model set-up and assemblage of model modules (AZTI: 5 months)

In collaboration with IRD, AZTI will implement the end-to-end ROMS-NPD-APECOSM model in the Bay of Biscay, with special modules of anchovy and sardine.

WP5 Validation, simulation scenarios and assessment of recruitment drivers (AZTI: 1 month)

AZTI will take part of the overall validation process.

WP6 Synthesis and building of recruitment strength indicators (AZTI: 1 month)

Selected publications: Irigoien, X., Ø. Fiksen, et al.. 2007 Could Biscay Bay Anchovy recruit through a spatial loophole? Prog.

Oceanogr. 74: 132-148 Cotano U., et al (2008) Distribution, growth and survival of anchovy larvae (Engraulis encrasicolus L.) in relation

to hydrodynamic and trophic environment in the Bay of Biscay. J. Plank. Res. 30: 467-481. Uriarte A. P. Prouzet, B. Villamor 1996: Bay of Biscay and Ibero atlantic anchovy populations and their fisheries.

Sci. Mar. 60 (Supl.2): 237-255 Ibaibarriaga, L., C. Fernández, A. Uriarte and B. A. Roel. (2008). A two-stage biomass dynamic model for Bay of

Biscay anchovy: a Bayesian approach. ICES Journal of Marine Science 65: 191–205

PARTNER 05: INRB/IPIMAR - Instituto Nacional de Recursos Biologicos (Portugal)

The institutue: IPIMAR is the governmental research organisation in Portugal in the area of fisheries and marine resources, integrated in the National Institute for Biological resources (INRB) of the Ministry of Agriculture, Rural Development and Fisheries. IPIMAR aims to promote and support a sustainable and competitive fishing industry and aquaculture, to manage fish stocks to maintain maximum sustainable exploitation, to contribute for the protection of marine environment, and to monitor and upgrade the quality of fishery and aquaculture products. IPIMAR has about 180 researchers and technicians with permanent positions distributed in four Research Units (Marine Resources and Sustainability, Aquatic Environment and Biodiversity, Aquaculture and Fish Products), and 60 graduate students. The Institute is responsible for providing the scientific recommendations for the assessment of the commercial marine stocks to the European Community and is the national delegate institution at ICES. The Institute has three research vessels aimed at providing information on the state of the living marine resources. IPIMAR undertakes a wide range of research projects and monitoring activities financed by the Ministry of Agriculture, National Research Council, European Community and Public and Private Companies. The IPIMAR has an annual science budget of 12 million euros.

The participants:

Alexandra Silva [1.5 months]: Fisheries biologist, with in MSc in BioStatistics (Technical University of Lisbon, 2000) and a PhD in Fisheries Stock Assessment (University of Algarve, 2007); Since 1997 researcher at IPIMAR, responsible for sardine stock assessment and biological research and since 2008 senior scientist within the Fisheries Resources and Sustainability Research Unit. Has participated in several national and international research projects related to small pelagic fish biology, ecology and populations dynamics, including the coordination of a workpackage within the FP5 EU Project Sardine dynamics and stock structure in the north-east Atlantic (SARDYN). Currently supervising the post-doctorate activities of Cristina Nunes.



Cristina Nunes [3 months]: Zoologist, with a MSc in Marine Sciences (Free University of Brussels Belgium, 2001) and a PhD in Reproduction and Development of Marine Organisms (Free University of Brussels Belgium, 2005); Since 2002, PhD and post-doctoral scholarship holder at IPIMAR, within the Fisheries Resources and Sustainability Research Unit. Main areas of activity: biology of reproduction of the Iberian sardine, Daily Egg Production Method (DEPM) applied to the Iberian sardine for stock assessment.

Juan Zwolinski [3 months]: Fisheries biologist, with a MSc in BioStatistics (Technical University of Lisbon, 2003) and a PhD in Fisheries Acoustics devoted to the estimation of abundance and ecology studies of sardine off the Portuguese coast (University of Aveiro / IPIMAR, 2008). Main areas of activity: fisheries acoustics, estimation of pelagic fish distribution and abundance, spatial modelling, niche characterisation and habitat mapping.

Yorgos Stratoudakis [1.5 months]: Fisheries biologist, with an MSc in Fisheries Biology and Management (University of Bangor UK, 1993), a PhD in Fisheries Science (FRS Marine Laboratory and University of Aberdeen UK, 1997) and post-Doctoral experience at the University of St Andrews (UK, 1998) and IPIMAR (Portugal, 2000); Since 2001 senior researcher at IPIMAR, responsible for small pelagic fish research and since 2008 head of the Fisheries Resources and Sustainability Research Unit. Has participated in several national and international research projects related to small pelagic fish biology, ecology and populations dynamics, including the coordination of the FP5 EU Project Sardine dynamics and stock structure in the north-east Atlantic (SARDYN). Currently supervising the post-doctorate activities of Juan Zwolinski.

IPIMAR involvement within REPROdUCE

The main IPIMAR contribution to REPROdUCE will be through the development of two post-doctorate research projects and the extension of an Msc project related to WP2 and WP5 of the candidature, while some contribution will be provided in the synthesis of WP6 by scientists with experience in sardine life history, dynamics and assessment.

The first contribution (post-doctorate project on Reproductive potential in an indeterminate batch-spawning fish, the Atlanto-Iberian sardine), aims to estimate sardine annual population fecundity as an alternative indicator of the reproductive potential, to examine how demographic structure (size/age composition) and maternal condition (body energy reserves) can affect this annual population fecundity, and to re-evaluate the stock-recruit relationship of the Atlanto-Iberian stock. In the context of the REPROdUCE objectives, it could thus provide:

1) An evaluation of the seasonal variation of reproductive parameters (batch fecundity, spawning fraction)

2) Relationships between reproductive parameters (duration of spawning season, batch fecundity, spawning fraction) and fish length/age and condition indices (condition factor, hepatosomatic index)

3) Estimates of sardine annual population fecundities, using abundance data (SSB-at-length) from acoustic surveys

4) An evaluation of the sardine reproductive cost (i.e. the energy needed to produce the annual population fecundity per length class) and the fraction of which relies on the energy stored prior to spawning season

5) A comparison between annual population fecundities (as indicators of the population reproductive potential) and the corresponding abundances of recruits (age-1 sardines, estimated from the acoustic surveys).



The second contribution (post-doctorate project on small pelagic distribution, abundance and habtiat charactristics), will be in WP2, mainly in actions 1 (review of knowledge, data available and definition of conceptual models for the case studies) and 2 (Habitat Modelling). For action 1 this study will be able to provide insight on the variables that are, up to the moment, the most likely candidates to be used to in the building of a probabilistic habitat model for adult sardines off western and southern Iberia. For action 2, the study will provide maps of presence and abundance of sardine and the remaining important pelagic species from data collected on the annual acoustic surveys from the Spring 2008 onwards. In the case of sardine, the maps can be disaggregated by length, age or maturity stage. Indices of habitat and niche overlap between sardine and other pelagic species could be constructed from trawl data.

The third contribution will be through the recently concluded MSc study “Modelling sardine growth in two oceanographically distinct areas of the Portuguese coast”. This study will be further developed to provide information on the biological (reproduction, feeding, population abundance) and environmental factors (SST) influencing sardine annual and seasonal growth (off north and south Portugal). In the context of REPROdUCE (WP2, actions 1, 3) it may provide information on:

- Seasonal patterns of growth and relationship with temperature cycles and reproductive investment

- Regional variability of seasonal and annual growth

- Density-dependent effects on growth

Some contribution to WP05 (not very clear which actions yet) from on-going work on sardine stock assessment and management strategies, namely from the exploration of stock- recruitment models incorporating auto-correlation and spatial variability.

Selected publications:

Silva A, Skagen D, Carrera P, Massé J, Santos MB, Uriarte A, Marques V, Bellois P, Pestana G, Porteiro C, Stratoudakis Y (2009) Geographic variability in sardine (Sardina pilchardus, Walb.) dynamics in the Iberia-Biscay region. ICES Journal of Marine Science (in press)

Ganias K., C. Nunes, & Y. Stratoudakis (2008). Use of late ovarian atresia in describing spawning history of sardine, Sardina pilchardus. Journal of Sea Research 60: 297-302

Oliveira PB, Stratoudakis Y (2008) Meso-scale advection off the Iberian and the northern African Atlantic coasts: potential implications for sardine recruitment and population structure. Remote Sensing of Environment 112: 3376-3387

Silva A, Carrera P, Massé J, Uriarte A, Santos MB, Oliveira PB, Soares E, Porteiro C, Stratoudakis Y (2008) Geographic variability of sardine growth across the northeastern Atlantic and the Mediterranean Sea. Fisheries Research 90: 56-69

Ganias K., Nunes C. & Y. Stratoudakis (2007). Degeneration of sardine postovulatory follicles: tructural changes and factors affecting resorption. Fishery Bulletin 105(1): 131-139

Zwolinski, J., Mason, E,. Oliveira, P., Stratoudakis, Y. (2006) Fine-scale distribution of sardine

(Sardina pilchardus) eggs and adults during a spawning event. Journal of Sea Research 56: 394-

404



Dissemination and Exploitation

All participants within REPROdUCE are aware of the importance of maximizing the dissemination of the project advances and results, both within the scientific community and within the social agents responsible for linking scientific advances with fisheries management. In order to achieve this, the REPROdUCE consortium will take the following actions, coordinated by the management Work Package and in agreement with all project participants:

1. Establishment of the project interactive web page (WIKI) in the first 2 months of the project

The REPROdUCE WIKI will act as forum for communication between members, but will also provide direct information on the project progress and on results which can be of use to social agents. In order to do that, the WIKI will host regular reports on project achievements, written in clear non-scientific language, in which the implications of the results obtained, together with their applicability to the case studies included in the project, will be clearly stated. The WIKI will also host discussion forums to allow feedback from scientist, managers and fishers. REPROdUCE will also make use of other online tools like weminars (seminars online), videoconferences and online sharing of didactic material. Dissemination of the WIKI and the online material will be coordinated by the project management Work Package, assisted by all REPROdUCE partners. Shared membership of the REPROdUCE partners with assessment working groups and regional advisory committees (RACs) will provide forums to discuss project advances, and advertise REPROdUCE online communications tools among a large scientific and social community.

2. Publications in scientific journals and participation in scientific symposia and conferences

Main results from the scientific work carried out in the different REPROdUCE work packages will be sent for publication in peer-review journals. Technical and ecological papers of both specific aspects of the REPROdUCE modules and on the general characteristics of the pelagic ecosystem are expected. Coordination between project modules and the existence of two case studies with different ecological characteristics provides an adequate framework for producing integrated manuscripts, which can be of interest to a broad scientific community. Tight links between the project partners and the ICES and the MARIFISH community also provide the potential for specific symposium and theme sessions in science conferences to be suggested and chaired by REPROdUCE members.

3. Organization of media events and meetings with social agents

Apart from online communication with media and social agents, REPROdUCE will also organize meetings with local media and the social agents (policymakers and stakeholders). These meetings will be carried out at least on an annual basis in each case study and on more general forums at least once in the project lifetime. Local meetings with case study media and social agents will be organized taking advantage of existing links, like annual stakeholders and fishers meetings with the scientific community. Also, in the Bay of Biscay events like the participation of fishers in coordinated surveys with the different institutes involved (IEO, IFREMER and AZTI) will be used to discus project advances.

There are no problematic issues foreseen dealing with intellectual property rights (IPR) within REPROdUCE. All knowledge and the tools generated in this project will become publicly available at the end of the project. Partners will retain intellectual property rights to any background knowledge that they have mobilised for the use of the project.

The transnational Scientific Report of the project should be made available on the MariFish website 6 months after project ends (or as soon as possible).

We have read and will conform to the MariFish IPR statements and dissemination of results details in the Applicants’ Guide.



Risk Identifier

The objectives of REPROdUCE rely on obtaining adequate models of the different modules of the pelagic ecosystem, in order to advance in the understanding of the mechanisms and drivers that affect recruitment. Main potential risks of the project are not being able to obtain models of the required level of accuracy, failures at the time of coupling the different modules together or failures in having the adequate data to perform the required validation of the different parts of the model. In this section, the main potential risks which can affect achieving any of the main milestones of the project are identified, and a contingency plan to minimize that risk or to overcome it is detailed Milestone Risk Contingency plan Report on conceptual models for all modules and overall REPROdUCE conceptual model

Conceptual models are not good representations of the ecosystem or are not coherent among modules

Previous conceptual models of the different modules of the ecosystem exist. In case problems appear when adapting previous models to the requirements of REPROdUCE, consortium expertise should allow to overcome problems in the identification of appropriate conceptual models

Completion of initial un-coupled simulations for all modules

Numerical models do not work or produce results which are not coherent with previous knowledge

Numerical models of some of the modules have already been tested and validated. For the new modules, initial attempts of numerical modules have already been produced, in some cases by some of the partners of REPROdUCE

Coupling of the different modules

Modules are not compatible either numerically or in terms of abundance levels of the main compartments

REPROdUCE will deal with coupling difficulties with specific meetings and workshops and counting on the experience of the IMCS Ocean Modelling Group coordination. If unexpected problems appear, REPROdUCE will seek further support from expert groups

Generation of simulation scenarios and model validation

Validation data is not available or simulation scenarios cannot be implemented in the model

A dedicated WP (WP05) will continuosly assess if the required data for validation of the different modules and of the general ecosystem model is available. In case of lack of data, the REPROdUCE consortium may make use of any of their routine surveys to include some ad-hoc sampling/experience to obtain missing data. Implementation of simulation scenarios will be carried out under the supervision of two WP and adequate expertise can be dedicated to the issue if difficulties appear.



4. Resources

Summary of Budget Requested (Euros)

IEO HCMR IFREMER AZTI

Staff Costs 564939 207137 441600 82160

Travel & Subsistence

12000 56400 36000 10000

Consumables 2526 6000 32000 9400

Other Costs 40000 109500 130000 10000

Overheads 0 18952 278208 48474

Total Costs 619465 397989 917808 160034

Own funding contribution a

489465 0 524808 80034

National b funding

requested

130000 397989 100000 (1) 293000 (2)

80000

Total funding requested

707989

(Use as many columns as necessary) a If applicable b Check the maximum national funding possible (see Table 3 and Annex 3 of the Applicants Guide); in

the virtual common pot, each national funding organisation only funds its own national researchers in any successful collaborative proposal according to its funding rules. (1): Contribution requrested from MariFish (2): Contribution agreed with French national funding body in case the project is approved.



Summary of Budget Requested (Euros) distributed on budget years

2009-2010 2010-2011 2011-2012

Staff Costs 517879 439919 338039

Travel & Subsistence

161800 137800 138800

Consumables 33842 8842 7242

Other Costs 262500 13000 14000

Overheads 173995 117935 53705

Total Costs 1042016 608496 444785

Own funding contribution a

600654 618119 495000

National b funding

requested

401088 155148 151753

Total funding requested

707989

(Use as many columns as necessary) a If applicable b Check the maximum national funding possible (see Table 3 and Annex 3 of the Applicants Guide); in

the virtual common pot, each national funding organisation only funds its own national researchers in any successful collaborative proposal according to its funding rules. * IFREMER is also asking for 130000 Eur (2009-2010), 83000 Eur (2010-2011) and 80000 Eur (2011-2012) from the French national funding body (cost not included in this table)



Sub-Tables

Staff Costs (Euros c)

Staff Role d Staff Name Period

on project (days)

Salary Cost / Day

Other employment costs (e.g. employers pension

contribution)

Total staff costs to

the project

IEO Permanent Miguel Bernal 480 242,3 0,0 116.323

Permanent Manuel Ruiz Villarreal 240 242,3 0,0 58.152

Permanent Enrique Nogueira 200 242,3 0,0 48.460

Permanent Cristobal Suanzes 180 242,3 0,0 43.614

Permanent Rafael Gonzalez-Quiros

160 242,3 0,0 38.768

Permanent Antonio Bode 120 242,3 0,0 29.076

Permanent Begoña Villamor 120 242,3 0,0 29.076

Permanent Isabel Riveiro 120 242,3 0,0 29.076

Permanent Manuel Varela 100 242,3 0,0 24.230

Permanent Magdalena Iglesias 100 242,3 0,0 24.230

Permanent Ignacio Olaso 80 242,3 0,0 19.384

Permanent Ana Lago de Lanzós 80 242,3 0,0 19.384

Permanent Pablo Abaunza 40 242,3 0,0 9.692

Temporary employed

Researcher 360 209,7 0,0 75.474

HCMR Permanent Korres M. 117,5 84,39 26,51 13.031

Permanent Petihakis G. 160 91,64 21,24 18.061

Permanent Pollani A. 210 60,68 16,31 16.168

Permanent Triantafyllou G. 167,5 112,35 26,76 23.301

Permanent Tsiaras K. 210 58,60 15,32 15.523

Temporally employed

Politikos D. 600 54,80 15,20 42.000

Permanent Somarakis S. 180 95,86 22,22 21.254

Permanent Giannoulaki M. 180 82,95 19,23 18.392

Permanent Machias A. 90 129,89 26,76 14.099

Permanent Valavanis V. 120 66,24 17,46 10.044

Permanent Katsanevakis S. 180 70,30 14,50 15.264

IFREMER Permanent Pierre Petitgas 260,0 378,9 216,0 9.8534

Permanent Martin Huret

260,4 378,9 216,0 9.8670

Permanent Jacques Massé 86,8 378,9 216,0 3.2890



Permanent Marc Sourisseau 43,4 378,9 216,0 16.445

Temporary PostDoc fellow 390,6 299,6 170,8 11.7036

Temporary Researcher 260,4 299,6 170,8 78.024

AZTI Section Coordinator

Xabier Irigoien 60 296 0 17.760

Researcher Marina Chifflet 125 280 0 35.000

Researcher Leire Ibaibarriaga 105 280 0 29.400

Total 6187 1.295.835

c For researchers in countries which do not have the Euro as their national currency, see guidance in

‘Applicants Guide’, Annex 1 d Role: in order of prominence. State whether staff are permanent or temporarily employed for the

project.

Travel and Subsistence e (Euros) Proposed journey/activity and justification Cost

IEO 4 travels (annual meeting + one workshop per year; 2 persons each) x 3 years x 1000 Eur

12000

HCMR 4 persons x 2 trips/year x 3 years x 1350 euro 32400 HCMR 6 persons x 50 days x 80 euro (field sampling) 24000 IFREMER 6 travels x 3 years x 2000 36000 AZTI Two coordination workshops and an international

meeting per year 10000

e if applicable

Consumables (Euros)

Consumables required and brief justification, as appropriate

Cost

IEO Office supplies and requirements for WIKI setup (annual fee)

2526

HCMR Printer consumables - CD disks 3000 HCMR Nets, jars, fixatives for plankton collection 3000 IFREMER 3 PCs x 2000

3 software licence x 2000 8 surdrift buoys x 2500

32000

AZTI Small equipment for the lab and articles printing costs

9400



Other Costs (Euros) Please list any other costs including a brief

justification, as appropriate Cost

IEO Subcontract of the IMCS (USA), responsible for the coordination of WP04. Total cost includes 12000 Eur in travel (2 travels * 3 years * 2000 Eur), 4000 Eur in specialised computer to run coupled models, 3000 consumibles (1000 year in office supplies), 19000 in salary of Enrique Curchitser (40 days)

40000

HCMR 2 laptops, 1 PC, 1 printer 9500 HCMR Research vessel hire 100000 IFREMER Incitement budget for Univ La Rochelle :

salary for contracted research fellow; measurements of energy density of fish; stable isotopes on fish and larvae; predator fields

130000

AZTI Two workstations to run models (5000 € each) 10000

Overheads Costs (Euros) f Overheads rate (%)

f Costs

IEO 0 0 HCMR 5 18952 IFREMER 63 278208 AZTI 59 48474

f as specified in national rules



ANNEXES:

A1. Letters of intent from REPROdUCE partners

A2. Bibliography

A3. CVs of WP leaders, case study coordinators and IPIMAR leader scientist (Attached to the proposal)



ATT: Instituto Español de Oceanografía Miguel Bernal Centro Oceanográfico de Cádiz

Muelle de Levante (Puerto Pesquero)

Aula del Mar, 11106 Cádiz. Apdo. 2609.

Spain

20 February 2009

Re: Letter of Intent; MARIFISH Call for research project proposals on fisheries

management indicators; Stock – recruitment relationships with process understanding

Dear Co-ordinator,

We hereby express our firm intent to participate as a subcontracted entity in the proposed MARIFISH project: REPROdUCE: Understanding REcruitment PROcesses Using

Coupled biophysical models of the pelagic Ecosystem coordinated by the Spanish Oceanographic Institute (IEO), represented by the Research Scientist: Dr Miguel Bernal.

With this letter of intent we agree and assure that: • The Institute of Marine and Coastal Sciences (IMCS), wants to participate in the project, as a subcontract of the Spanish Oceanographic Institute (IEO), with Enrique Curchitser as its participant scientist; • The Project-Co-ordinator is authorised to submit the proposal on our behalf and we, as subcontract member of the consortium, will support all necessary activities and documents in due time for successful proposal preparation.

Best regards,

Francisco Werner

Institute of Marine and Coastal Sciences Rutgers, The State University of New Jersey 71 Dudley Road New Brunswick, NJ 08901-8521

http://marine.rutgers.edu 732-932-6555

Fax: 732-932-8578



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Ahumada, M.A. and Cruzado, A., 2007. Modeling of the circulation in the Northwestern Mediterranean Sea with the Princeton Ocean Model. Ocean Science, 3(1): 77-89.

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Allain G., Petitgas P., Lazure P. 2007a. The influence of environment and spawning distribution on the survival of anchovy (Engraulis encrasicolus) larvae in the Bay of Biscay (NE Atlantic) investigated by biophysical simulations. Fisheries Oceanography 16, 506-514.

Allain G., Petitgas P., Lazure P., Grellier P. 2007b. Biophysical modeling of larval drift, growth and survival for the prediction of anchovy (Engraulis encrasicolus) recruitment in the Bay of Biscay (NE Atlantic). Fisheries Oceanography 16, 489-505.

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