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Understanding and modelling bivalve growth dynamics under variable environmental conditions are crucial for the development of management and sustainability aquaculture plans. This work proposes a new dynamic bivalve growth model that combines net production Dynamic Energy Budget (DEB) theory and the species-specific growth dynamics of the Ecophysiological Model for Mussels (EMMY). In our approach, the assimilated energy is first used for metabolic requirements, and the surplus partitioned between shell formation, somatic growth, reserves and reproduction. We also incorporate site-specific estimates for feeding and spawning. We compare the performance of our model with a standard DEB model for the simulation of mussel growth in a low seston environment (Ría de Ares-Betanzos, NW Spain). Our model provides realistic estimations of shell and soft tissue growth, while the standard DEB model overestimates soft tissue growth. Indeed the Relative Mean Square Error (RMSE), which measures the discrepancy between field and simulated shell-soft tissue relationships, of our model is below 10% of that obtained with the standard DEB. Our model also captures the different effects of environmental variability on shell and flesh growth. • Dynamic growth model that accounts for the cost of shell formation. • Shell and soft tissue growth are modeled separately. • Accurate simulations of mussel growth in the natural field are obtained. [ABSTRACT FROM AUTHOR]

Interest on the potential CO 2 sequestration of marine bivalve aquaculture has increased during the last decade. However, there is still some controversy about which biological processes are involved and how to estimate their contribution to the carbon footprint of bivalve aquaculture. This work considers the dissolved inorganic carbon, CO 2 and alkalinity fluxes linked to flesh and shell growth, calcification, respiration, faeces egestion, and ammonia excretion, accounting also for the RDOC production associated to these processes. We have developed an algorithm for a dynamic estimation of these fluxes based on a net production DEB growth model for mussels. The resulting model has been implemented in Python to create a toolbox with a graphical user interface. This toolbox allows the selection of different culture strategies, in terms of seeding date, seed size and culture length, and consequently analyzes the carbon footprint and impact on the carbonate chemistry of seawater of aquaculture management. • Mussel physiology is commonly ignored in carbon footprint estimates of mussel aquaculture. • MusselCF provides dynamic estimation of mussel culture carbon footprint and its impact on the seawater carbonate chemistry. • Hydrography, carbonate chemistry, seeding time and mussel seed and harvest size dictate the physiological carbon footprint. [ABSTRACT FROM AUTHOR]