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.

The role of bivalve mariculture in the CO 2 cycle has been commonly evaluated as the balance between respiration, shell calcium carbonate sequestration and CO 2 release during biogenic calcification. However, this approach neglects the ecosystem implications of cultivating bivalves at high densities, e.g. the impact on phytoplankton dynamics and benthic−pelagic coupling, which can significantly contribute to the CO 2 cycle. Therefore, an ecosystem approach that accounts for the trophic interactions of bivalve aquaculture, including dissolved and particulate organic and inorganic carbon cycling, is needed to provide a rigorous assessment of the role of bivalve mariculture in the CO 2 cycle. On the other hand, the discussion about the inclusion of shells of cultured bivalves into the carbon trading system should be framed within the context of ecosystem goods and services. Humans culture bivalves with the aim of producing food, not sequestering CO 2 in their shells, therefore the main ecosystem good provided by bivalve aquaculture is meat production, and shells should be considered as by-products of this human activity. This reasoning provides justification for dividing up respired CO 2 between meat and shell when constructing a specific bivalve CO 2 budget for potential use of bivalve shells in the carbon trading system. Thus, an integrated ecosystem approach, as well as an understanding of the ecosystems goods and services of bivalve aquaculture, are 2 essential requisites for providing a reliable assessment of the role of bivalve shells in the CO 2 cycle.

The extension and intensity of the upwelling season in the NW Iberian Peninsula (42º-43ºN) have decreased by 30% and 45% over the last 40 years, respectively. Accordingly, the renewal time (τ) of the Rías Baixas, four large coastal inlets where 15% of the World extraction of blue mussels occurs, has increased by 240%. We indirectly demonstrate here that the growing τ has caused the increasing occurrence of harmful microalgae in these embayments, dramatically affecting mussel raft cultivation. The equation            ) c exp(1 365 D 1 τ explains 80% of the variability of the number of days per year that mussels cannot be extracted from the hanging ropes because of the occurrence of harmful microalgae (D). The coefficient c 1 = 37± 2 days indicates that an average τ over the upwelling season of > 25±1 or 50± 3 days reduce mussel extraction to only 50% or 25% of the year, respectively.

There is an ongoing discussion in the scientific literature about methodological aspects of clearance rate (CR) measurement with regard to bivalves, especially when the CR is measured by flow-through chamber method. In the present paper, an experimental chamber, a mesocosm system, and a validation protocol have been developed for determining the CR using the flow-through method. The procedure consisted of a preliminary analysis of the fluid dynamics in the interior of the chamber and a statistical analysis of the CR measurement in the mussel Mytilus galloprovincialis L at different water inflows. This allowed the performance of the chamber for each flow to be identified. The performance of the chamber for all the flows studied was also modeled simultaneously by means of Ivlev curve. The protocol, applied to an individual cylindrical experimental chamber (ICEC) (radius 71 mm, height 76 mm, volume 1200 mL), established that the ICEC complies with all the requirements for CR measurement using the flow-through chamber method, provided that the percentage of particles cleared is approximately 20% (minimum 13%, maximum 25%). In agreement with the allometric relationship between length and volume of Mytilus galloprovincialis, 3 types of ICEC were designed for CR measurement on individuals of 20 to 85 mm length. After validation of the ICEC, the performance of a mesocosm system used regularly by our group (box raft experimental chamber or BREC) was evaluated. Three comparative measurements were carried out for the ICEC and BREC, two in situ and one in the laboratory. No statistically significant differences were observed between the experimental systems for the CR determinations, which validates the BREC for CR measurement using the flow-through chamber method.

Qualifying and quantifying nutrient flows within open‐water Integrated Multi‐Trophic Aquaculture (IMTA) systems is necessary to determine transfer efficiencies and to assess overall system performance. There are numerous empirical performance metrics, such as spatially defined growth and nutrient sequestration, which may have application. When used in combination with modelling techniques, empirical approaches can be a powerful tool for system assessment or prediction. Simple empirical growth models, such as the thermal‐growth coefficient (TGC) and scope for growth (SFG), are applicable to aquatic animals and can include nutritional mass‐balance approaches to estimate nutrient loads. Comparable empirical growth models exist for seaweeds. Mechanistic‐based dynamic growth and reproduction models, such as Dynamic Energy Budget (DEB), are more complex, but have application beyond site‐specific empirical models and can, therefore, be included into larger ecosystem models for application to IMTA. Proximity, ecological transfer efficiencies, particle dynamics, species culture ratios and the timing of multi‐species production cycles can have profound implications for IMTA effectiveness and require careful consideration for system assessment. This review provides a pragmatic evaluation of performance measures and models to assess nutrient transfer and growth in open‐water IMTA systems.

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Connectivity in an aquatic setting is determined by a combination of hydrodynamic circulation and the biology of the organisms driving linkages. These complex processes can be simulated in coupled biological-physical models. The physical model refers to an underlying circulation model defined by spatially-explicit nodes, often incorporating a particle-tracking model. The particles can then be given biological parameters or behaviors (such as maturity and/or survivability rates, diel vertical migrations, avoidance, or seeking behaviors). The output of the bio-physical models can then be used to quantify connectivity among the nodes emitting and/or receiving the particles. Here we propose a method that makes use of kernel density estimation (KDE) on the output of a particle-tracking model, to quantify the infection or infestation pressure (IP) that each node causes on the surrounding area. Because IP is the product of both exposure time and the concentration of infectious agent particles, using KDE (which also combine elements of time and space), more accurately captures IP. This method is especially useful for those interested in infectious agent networks, a situation where IP is a superior measure of connectivity than the probability of particles from each node reaching other nodes. Here we illustrate the method by modeling the connectivity of salmon farms via sea lice larvae in the Broughton Archipelago, British Columbia, Canada. Analysis revealed evidence of two sub-networks of farms connected via a single farm, and evidence that the highest IP from a given emitting farm was often tens of kilometers or more away from that farm. We also classified farms as net emitters, receivers, or balanced, based on their structural role within the network. By better understanding how these salmon farms are connected to each other via their sea lice larvae, we can effectively focus management efforts to minimize the spread of sea lice between farms, advise on future site locations and coordinated treatment efforts, and minimize any impact of farms on juvenile wild salmon. The method has wide applicability for any system where capturing infectious agent networks can provide useful guidance for management or preventative planning decisions.

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