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A Dynamic Energy Budget (DEB) model for simulation of growth and bioenergetics of blue mussels (Mytilus edulis) has been tested in three low seston sites in southern Norway. The observations comprise four datasets from laboratory experiments (physiological and biometrical mussel data) and three datasets from in situ growth experiments (biometrical mussel data). Additional in situ data from commercial farms in southern Norway were used for estimation of biometrical relationships in the mussels. Three DEB parameters (shape coefficient, half saturation coefficient, and somatic maintenance rate coefficient) were estimated from experimental data, and the estimated parameters were complemented with parameter values from literature to establish a basic parameter set. Model simulations based on the basic parameter set and site specific environmental forcing matched fairly well with observations, but the model was not successful in simulating growth at the extreme low seston regimes in the laboratory experiments in which the long period of negative growth caused negative reproductive mass. Sensitivity analysis indicated that the model was moderately sensitive to changes in the parameter and initial conditions. The results show the robust properties of the DEB model as it manages to simulate mussel growth in several independent datasets from a common basic parameter set. However, the results also demonstrate limitations of Chl a as a food proxy for blue mussels and limitations of the DEB model to simulate long term starvation. Future work should aim at establishing better food proxies and improving the model formulations of the processes involved in food ingestion and assimilation. The current DEB model should also be elaborated to allow shrinking in the structural tissue in order to produce more realistic growth simulations during long periods of starvation.

A spatially explicit coupled hydrodynamic-biogeochemical model was developed to study a coastal ecosystem under the combined effects of mussel aquaculture, nutrient loading and climate change. The model was applied to St Peter's Bay (SPB), Prince Edward Island, Eastern Canada. Approximately 40 % of the SPB area is dedicated to mussel (Mytilus edulis) longline culture. Results indicate that the two main food sources for mussels, phytoplankton and organic detritus, are most depleted in the central part of the embayment. Results also suggest that the system is near its ultimate capacity, a state where the energy cycle is restricted to nitrogen-phytoplankton-detritus-mussels with few resources left to be transferred to higher trophic levels. Annually, mussel meat harvesting extracts nitrogen (N) resources equivalent to 42 % of river inputs or 46.5 % of the net phytoplankton primary production. Under such extractive pressure, the phytoplankton biomass is being curtailed to 1980's levels when aquaculture was not yet developed and N loading was half the present level. Current mussel stocks also decrease bayscale sedimentation rates by 14 %. Finally, a climate change scenario (year 2050) predicted a 30 % increase in mussel production, largely driven by more efficient utilization of the phytoplankton spring bloom. However, the predicted elevated summer temperatures (> 25 A degrees C) may also have deleterious physiological effects on mussels and possibly increase summer mortality levels. In conclusion, cultivated bivalves may play an important role in remediating the negative impacts of landderived nutrient loading. Climate change may lead to increases in production and ecological carrying capacity as long as the cultivated species can tolerate warmer summer conditions.

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The simulations demonstrate spatial growth patterns at longlines under environmental settings and farm configurations where flow reduction and seston depletion have significant impacts on individual mussel growth. Longline spacing has a strong impact on the spatial distribution of individual growth, and the spacing is characterised by a threshold value. Below the threshold growth reduction and spatial growth variability increase rapidly as a consequence of reduced water flow and seston supply rate, but increased filtration due to higher mussel densities also contributes to the growth reduction. The spacing threshold is moderated by other farm configuration factors and environmental conditions. Comparisons with seston depletion reported from other farm sites show that the model simulations are within observed ranges. A demonstration is provided on how the model can guide farm configuration with the aim of optimising total farm biomass and individual mussel quality (shell length, flesh mass, spatial flesh mass variability) under different environmental settings. The model has a potential as a decision support tool in mussel farm management and will be incorporated into a GIS-based toolbox for spatial aquaculture planning and management. Research highlights ► New model for flow reduction, seston depletion and mussel growth in longline farms. ► Integration of processes at the level of individual mussels and at the farm level. ► Mussel size and condition depend on farm configuration and environment. ► Spacing between longlines is the most influential farm parameter on mussel growth. ► The effects of farm configuration are moderated by environmental conditions.

A comparison of Scope For Growth (SFG) and Dynamic Energy Budget (DEB) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 2 Abstract 17Growth of Mytilus edulis was modelled using individual based models following both 18 Scope For Growth (SFG) and Dynamic Energy Budget (DEB) approaches. These models 19 were parameterized using independent studies and calibrated for each dataset by adjusting 20 the half-saturation coefficient of the food ingestion function term, X K , a common 21 parameter in both approaches related to feeding behaviour. Auto-calibration was carried 22 out using an optimization tool, which provides an objective way of tuning the model. 23Both approaches yielded similar performance, suggesting that although the basis for 24 constructing the models is different, both can successfully reproduce M. edulis growth. 25The good performance of both models in different environments achieved by adjusting a 26 single parameter, X K , highlight the potential of these models for (1) producing 27 prospective analysis of mussel growth and (2) investigating mussel feeding response in 28 different ecosystems. Finally, we emphasize that the convergence of two different 29 modelling approaches via calibration of X K , indicates the importance of the feeding 30 behaviour and local trophic conditions for bivalve growth performance. Consequently, 31 further investigations should be conducted to explore the relationship of X K to 32 environmental variables and/or to the sophistication of the functional response to food 33 availability with the final objective of creating a general model that can be applied to 34 different ecosystems without the need for calibration. 35 36

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