comparison of the growth of cultured blue mussel Mytilus edulis by use of Dynamic Energy Budgets (DEB)

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Multi-site comparison of the growth of cultured blue mussel Mytilus edulis by use of Dynamic Energy Budgets (DEB) M.

Smaal CANO MOMA (AURORA) Context Culture of the blue mussel Mytilus edulis: A worldwide cultured species: 391 000 tonnes (in 2005)

bottom, ropes, rafts, poles) Mussel culture under contrasted environments, e.g.

1 Multi-site comparison of the growth of cultured blue mussel Mytilus edulis by use of Dynamic Energy Budgets (DEB) M. Alunno-Bruscia, C. Bacher, Ø. Strand, R. Rosland, P. Cranford, J. Grant, Aad C. Smaal CANO MOMA (AURORA) Context Culture of the blue mussel Mytilus edulis: A worldwide cultured species: tonnes (in 2005) 93% from EU (Spain, France, Holland) 207 millions Euro (source FAO FishStat) Several culture methods (e.g. bottom, ropes, rafts, poles) Mussel culture under contrasted environments, e.g. phytoplankton concentrations (1-12 µg L -1 ), SPM (1-100 mg L -1 ), temperature (1-22 C) differences in growth and reproduction of M. edulis among culture sites and over years (variability in yields) sustainability of the mussel culture is sensitive to environmental conditions 1

2 Objective Environmental variability (e.g. T C, food) Generic individual growth model? Explain & Predict Variability in M. edulis growth & reproduction Method: the individual bio-energetic model food assimilation faeces somatic maintenance κ Reserve (E) 1-κ maturity maintenance 3 state variables (3 ordinary differential equations) 2 forcing variables: T C, food growth Structure (V) development reproduction Reproduction Maturity buffer (E R ) 12 parameters for a full life cycle Outputs: length (or mass), number of eggs, energy per egg; elements (C, N, H, O) Offspring Conceptual scheme of the standard DEB model (Kooijman 2000) 2

Energy acquisition (in DEB theory) The energy ingestion rate: depends on temperature T (Arrhenius relationship) is surface-area area of the organism S=(δL) 2 =V 2/3 is related to food density through

modeling procedure Step 1: Conceptualisation 10 mathematical key-equations to describe the main physiological processes (Kooijman, 2000) 1 Step 2: Parameters estimation 15 parameter values estimated

3 Energy acquisition (in DEB theory) The energy ingestion rate: depends on temperature T (Arrhenius relationship) is surface-area area of the organism S=(δL) 2 =V 2/3 is related to food density through a Holling type II curve (Michaelis-Menten) {p X } Ingestion rate {p Xm } {p Xm }/2 For a given T Michaelis-Menten { p & X} = ( ){ p& Xm} X + X X For a given T K X k X (=food density) Method: the modeling procedure Step 1: Conceptualisation 10 mathematical key-equations to describe the main physiological processes (Kooijman, 2000) 1 Step 2: Parameters estimation 15 parameter values estimated for M. edulis 2 except X K (half saturation coefficient) calibrated for each simulation Rosland et al Step 3: Implementation Step 4: Test & simulations 4.1: Forcing 4.2: Validation Implementation of equations and numerical computing under a modelling software (Matlab) Temperature & food density (chlorophyll a) Observed shell length or dry flesh mass over time 3 4 3

Method: a multi-site approach Canada Norway 1

sites: Aiguillon Bay (6 years) Mont Saint Michel

4 Method: a multi-site approach Canada Norway 1 site: Tracadie Bay 2 years 3 sites: Toskasundet Austevoll Flødevigen (2 years) 20 data sets France 1 site: Oosterschelde 3 cohorts Holland 2 sites: Aiguillon Bay (6 years) Mont Saint Michel Bay (5 locations) Results: Norwegian sites Shell length (mm) 4

5 Results: Norwegian sites Dry flesh mass (g) X K = X K = X K (µg chl a L-1) X K = X K = Results: Aiguillon Bay (France) Shell length (mm) Data source: Ifremer LER/PC (S. Robert) 5

6 Results: Aiguillon Bay (France) ❿Dry flesh mass (g) X K = X K = X K = No spawning X K = X K = X K = Results: Mont Saint Michel Bay (France) Shell length (mm) Data source: Ifremer LER/B (J. Mazurié) 6

7 Results: Mont Saint Michel Bay (France) ❿Dry flesh mass (g) X K = X K = X K = X K = X K = Results: Tracadie Bay (Canada) X K = Shell length (mm) ❿Dry flesh mass (g) X K =

8 Results: Oosterschelde (Holland) Shell length (mm) Data source: IMARES Wageningen & RIKZ Results: Oosterschelde (Holland) Dry flesh mass (g) X K = X K = X K = Data source: IMARES Wageningen & RIKZ 8

9 Conclusion The mussel-deb model simulates rather properly shell length of M. edulis in different ecosystems: robustness of the model structure (energy for growth, reproduction, maintenance) one single set of parameters, except X K : µg Chl a L 1 ( ) X K depends on food quality and quantity, inorganic material, phenotypic plasticity (e.g. Crassostrea gigas, Perna canaliculus) a rough food quantifier: chlorophyll a but phytoplankton enumeration has been shown to explain and predict properly oyster (C. gigas) growth cultured in different sites (see Bourlès et al. poster 25) Conclusion Some discrepancies between observed vs simulated dry flesh mass are observed: Flødevigen, (NO): very low values for X K Chl a may not be the best food quantifyer Any other food sources (e.g. heterotrophic protists) than phytoplankton? Aiguillon Bay (FR): overestimation of growth in lean periods during fall and winter What about the food quality? Does the allocation of energy differ during prolonged lean periods? Tracadie Bay 1999 (CA): high value for X K, spawning not satisfying Only a few measured growth data (interpolation) Oosterschelde (NL): high values for X K for the 3 cohorts likely due to a problem of food depletion due to fouling of the mussel cages 9

10 Perspectives & related applications Further improvements and simulations are needed: 1/ testing other food quantifyers, e.g. phytoplankton composition (see C. gigas: Bourlès et al. 2009, poster AE09), carbon content, C:Chl a ratio (see C. gigas: Grangeré et al. 2009, AE09 -IMTA) phytoplankton data for Flødevigen, Aiguillon Bay (Tracadie Bay, Oosterschelde). 2/ lean periods : checking the maintenance costs ([p M ]) 3/ gametogenesis: revisiting its formalisation for M. edulis in DEB Coupling the mussel-deb model to: the FARM model: a GIS tool, AkvaVis: Rosland et al. (AE09 - this session) Hageberg et al. (AE09 -this session) ecosystem models: Maar et al. 2009, Mazurié et al. ICSR 2007 reconstruct trophic conditions: Flye Sainte Marie et al. (AE09 30; BlueDEB) More about DEB applications in aquatic species DEB codes for: mussel, oyster, cockle sea bass, hake, sole ( ) malunnob@ifremer.fr The AquaDEB project (Sept. 2009) Bourlès et al Grangeré et al Maar et al Ren 2009 Rosland et al

11 Thank you for your attention!!!!!! I WANT MUSSEL DATA!!!! Mussel growth data over time + Forcing data (T C, food) 11

Preparing a special issue in Journal of Sea Research in relation to the AquaDEB project, phase II

Preparing a special issue in Journal of Sea Research in relation to the AquaDEB project, phase II 1. Provisional list of publications deadline for final submission: 29 Oct. 2010 This 3 rd special issue