Search

Sea lice are one of the most economically costly and ecologically concerning problems facing the salmon farming industry. Here, we validated a coupled biological and physical model that simulated sea lice larvae dispersal from salmon farms in the Broughton Archipelago (BA), British Columbia, Canada. We employed a concept from ecological agent-based modeling known as ‘pattern matching’, which identifies similar emergent properties in both the simulated and observed data to confirm that the simulation contained sufficient complexity to recreate the emergent properties of the system. One emergent property from the biophysical simulations was the existence of sub-networks of farms. These were also identified in the observed sea lice count data in this study using a space-time scan statistic (SaTScan) to identify significant spatio-temporal clusters of farms. Despite finding support for our simulation in the observed data, which consisted of over a decade’s worth of monthly sea lice abundance counts from salmon farms in the BA, the validation was not entirely straightforward. The complexities associated with validating this biophysical dispersal simulation highlight the need to further develop validation techniques for agent-based models in general, and biophysical simulations in particular, which often result in patchiness in their dispersal fields. The methods utilised in this validation could be adopted as a template for other epidemiological dispersal models, particularly those related to aquaculture, which typically have robust disease monitoring data collection plans in place.

Aquaculture, or the farmed production of fish and shellfish, has grown rapidly, from supplying just 7% of fish for human consumption in 1974 to more than half in 2016. This rapid expansion has led to the growth of Precision Aquaculture concept that aims to exploit data-driven management of fish production, thereby improving the farmer's ability to monitor, control, and document biological processes in farms. Fundamental to this paradigm is monitoring of environmental and animal processes within a cage, and processing those data toward farm insight using models and analytics. This paper presents an analysis of environmental and fish behaviour datasets collected at three salmon farms in Norway, Scotland, and Canada. Information on fish behaviour were collected using hydroacoustic sensors that sampled the vertical distribution of fish in a cage at high spatial and temporal resolution, while a network of environmental sensors characterised local site conditions. We present an analysis of the hydroacoustic datasets using AutoML (or automatic machine learning) tools that enables developers with limited data science expertise to train high-quality models specific to the data at hand. We demonstrate how AutoML pipelines can be readily applied to aquaculture datasets to interrogate the data and quantify the primary features that explains data variance. Results demonstrate that variables such as temperature, wind conditions, and hour-of-day were important drivers of fish motion at all sites. Further, there were distinct differences in factors that influenced in-cage variations driven by local variables such as water depth and ambient environmental conditions (particularly dissolved oxygen). The framework offers a transferable approach to interrogate fish behaviour within farm systems, and quantify differences between sites.

This paper focuses on the availability of economic indicators and metrics to assess effects of marine aquaculture production in the North Atlantic area (the EU, Norway, Canada and USA), including also social and environmental effects. We consider how aquaculture planning and management is organised in the different countries and the usefulness of economic information to address different aquaculture‐related policies. We find that the most relevant economic data for aquaculture management should be at the local and regional levels rather than nationally. The availability of such economic data is mapped for national, regional and local level. The focus is on data that are publicly available from authorities or research institutions. The availability of data is generally fairly good for national and regional data on the direct economic effects of aquaculture. Data on how aquaculture‐related products or input markets are affected are however poorly available, as are economic data on external effects from aquaculture. Countries with a larger aquaculture sector tend to have better availability of aquaculture‐related economic data than those with a smaller sector. An index is developed and calculated to show more specifically where the countries have relatively good or poor data availability compared to their needs. While it will not always be cost‐effective or meaningful to collect economic data on the effects of aquaculture, our study indicates that several countries could benefit from expanding such data collection. It can make trade‐off decisions more consistent and easier to perform, and aquaculture policies and measures can be better tailored to specific contexts This article is based upon work from COST Action OceansPast Platform (OPP – IS1403), supported by COST (Euro-pean Cooperation in Science and Technology). We gratefully acknowledge support also from the institutions of the authors, and discussions in the ICES Working Group onSocial and Economic Dimensions of Aquaculture. In particular, we thank Max Troell, Cecile Brugere and Max Ebeling for input. Lucia Fanning was supported by the Ocean Frontier Institute Large Research Project on Social Licenseand Planning in Coastal Communities SI

Until very recently, governments of many countries, as well as their supporting organizations, have primarily addressed the biological, technical and economic aspects of aquaculture. In contrast, social and cultural aspects of aquaculture production have taken a backseat. Drawing on the observation that aquaculture development in Western Societies has largely failed to address these social effects across different scales and contexts, this paper offers a new way of capturing and visualising the diverse social dimensions of aquaculture. It does so by testing the ability to operationalise a set of social dimensions based on categories and indicators put forward by the United Nations, using several case studies across the North Atlantic. Local/regional stakeholder knowledge realms are combined with scientific expert knowledge to assess aquaculture operations against these indicators. The approach indicates that one needs to have a minimum farm size in order to have an impact of a visible scale for the different social dimension categories. While finfish aquaculture seems to be more social impactful than rope mussel farming, the latter can hold important cultural values and contribute to place-based understanding, connecting people with place and identity, thus playing a vital role in maintaining the working waterfront identity. It could be shown that aquaculture boosts a potential significant pull-factor to incentivise people to remain in the area, keeping coastal communities viable. By visualising the social effects of aquaculture, a door may be opened for new narratives on the sustainability of aquaculture that render social license and social acceptability more positive.

Warming waters are changing marine pathogen dispersal patterns and infectivity worldwide. Coupled biological–physical modelling has been used in many systems to determine the connectivity of metapopulations via infectious disease particles. Here we model the connectivity of sea lice larvae (Lepeophtheirus salmonis) among salmon farms in the Broughton Archipelago, British Columbia, Canada, using a coupled biological–physical model. The physical model simulated pathogen dispersal, while the biological component influenced the survival and developmental rates of the sea lice. Model results predicted high temporal variability in connectivity strength among farms, an emergent effect from the interacting parts of the simulation (dispersion versus survival and development). Drivers of temporal variability were disentangled using generalized additive modeling, which revealed the variability was most strongly impacted by the spring freshet, which can act as a natural aid for sea lice control in the Broughton Archipelago. Our results suggest that farm management strategies can benefit by accounting for short-term spikes in regional pathogen connectivity among farms. Additionally, future scenarios of a warming climate with reduced snowpack can make sea lice control more challenging.

Precision aquaculture is founded on a set of disparate, interconnected sensors deployed within the marine environment to monitor, analyze, interpret, and provide decision support for farm operations. Recent technological innovations facilitate aquaculture becoming part of the Internet of Things (IoT) -- modern farms are characterized by hundreds of interconnected sensors that store and serve data, interact with other sensors and devices, and connect with a fog and cloud ecosystem. We describe the implementation of the precision aquaculture concept to a number of farms in eastern Canada. The work combines partners from industry, technology, and academia to provide data-driven insight and decision that promotes ecologically sustainable intensification of aquaculture. The article presents a first case study on how IoT can instrument, inform, and impact the aquaculture industry. Challenges related to connectivity, interoperability, and standardization are discussed, and we elucidate how our experiences can inform future activities.

Marine aquaculture is the most promising industry for ensuring future provision of seafood. Yet, the worldwide growth and expansion of this industry have been slower than expected, calling for the identification of environmentally suitable sites while accounting for all factors that could constrain or benefit its establishment. Here, we determine the main obstacles and risks hindering the growth and expansion of marine aquaculture, as well as the needs and recommendations to overcome such constraints. Our analysis is based on results obtained from a consultation process held in 16 study sites located around the world with the participation of 614 stakeholders representing the research community, aquaculture industry, government, conservation groups, and education and fishermen associations. A high level of commonality exists in the main issues hindering aquaculture growth and expansion in coastal, off-the-coast and offshore aquaculture with most being attributed to interactions with other maritime activities, including conflicts with other users and administrative procedures, including licensing. Critical needs for improved management and expansion of the aquaculture industry are related to planning andmanagement of developments and technological advances, with economic and market needs featuring to a lesser extent. Key procedures recommended to assist further aquaculture growth are th standardisation and simplification of regulatory frameworks, improvement of governance, and the adoption of participatory processes to facilitate meaningful and productive stakeholder engagement. We strongly recommend stakeholder participation to enhance insights on the full environmental and human dimensions of marine management and for implementation of ecosystem-based marine spatial planning.

An aquaculture investor (AQI) index was developed in order to provide a broad view of the relative attractiveness of 29 different European countries to aquaculture investors. AQI is based on five complementary categories: Market, Production, Regulatory, Environment, and Social, with each category containing four indicators. The attraction of investment into aquaculture depends on the viability of developing aquaculture for each country, and these five categories account for the connectivity in the aquaculture industry. The index benchmarks and tracks countries' progress by producing a quantitative and scalable tool for stakeholders to assess and monitor aquaculture attractiveness, and is designed to rank aquaculture competitiveness for each country. Index scores calculated for Europe range from moderate to good, on a heuristic five-class scale. Countries in Northern Europe with well-established aquaculture sectors score better than countries in Southern Europe. Countries with developing aquaculture sectors tend to score moderately. While high scores within single categories can be achieved, the index rewards countries with high scores across the five categories, to provide a more useful tool for stakeholders. No countries within Europe rank below the middle of the moderate range. The index identifies several countries with high scores that do not have significant aquaculture industries (e.g. Sweden and Finland), and further research is warranted to identify why aquaculture has not been developed. It is expected that as AQI is expanded to lower income countries spanning other geographic regions, countries with lower quality indicator scores will have lower overall scores. The index provides a broad-scale approach across a wide range of categories, and should be interpreted in that context, since it is designed to provide high-level guidance of the general attractiveness for aquaculture in each country. Appropriate due diligence for specific circumstances is warranted by all stakeholders requiring further knowledge to assist decision-making. To ensure a wide dissemination and maximum visual appeal to both investors and the public, the AQI index was deployed as a smartphone application (AquaInvestor), freely available on the Google Play Store, together with a companion website, and to our knowledge provides the first country-wide comparative assessment of aquaculture potential, available to investors and the general public in eight European languages and Chinese.

Maximizing the mitigation potential of open-water finfish-shellfish integrated multi-trophic aquaculture (IMTA) farms is complex in terms of co-locating the trophic components. Both the dispersal of finfish aquaculture wastes and biological processes are highly influenced by water circulation. Consequently, the evaluation of shellfish-finfish synergy requires a combined study of biological and physical processes, which can be achieved by the implementation and coupling of mathematical models. A highly configurable mathematical model was developed that can be applied at the apparent spatial scale of IMTA sites. The model tracks different components of the seston, including feed wastes, fish faeces, shellfish faeces, natural detritus and phytoplankton. Based on the characterization of these fluxes, a hypothetical IMTA site was used to explore different spatial arrangements for evaluating finfish-shellfish farm mitigation efficiency. The site was modelled following a factorial design, which tested 2 levels of background seston concentrations, 3 farm designs, 2 hydrodynamic conditions and 2 levels of aquaculture intensity. The model predicts that mitigation efficiency is highly dependent on the background environmental conditions, obtaining maximum mitigation under oligotrophic conditions that stimulate shellfish filtration activity. The dominance of vertical fluxes of particulate matter triggered by the high settling velocity of finfish aquaculture wastes suggests that suspended shellfish aquaculture cannot significantly reduce organic loading of the seabed. Consequently, this suggests that waste mitigation at IMTA sites should be best achieved by placing organic extractive species (e.g. deposit feeders) on the seabed directly beneath finfish cages rather than in suspension in the water column.

Food provisioning is a prominent feature of marine bivalve production, applicable worldwide since ancient times. Easy accessibility of this food source and high nutritional value make bivalves a possible driver in human evolution. In this section bivalve meat production is addressed, as well as other provisioning services including pearls and bio-active compounds. In both bivalve aquaculture and fisheries, harvest and production for meat provisioning must be balanced against carrying capacity and its implications for other services including water quality maintenance and habitat structure. Provisioning of meat through aquaculture can be improved via hatchery and breeding advances, a necessity in the changing ocean climate.

In this paper we focus on the role of ecosystem models in improving our understanding of the complex relationships between bivalve farming and the dynamics of lower trophic levels. To this aim, we review spatially explicit models of phytoplankton impacted by bivalve grazing and discuss the results of three case studies concerning an estuary (Baie des Veys, France), a bay, (Tracadie Bay, Prince Edward Island, Canada) and an open coastal area (Adriatic Sea, Emilia-Romagna coastal area, Italy). These models are intended to provide insight for aquaculture management, but their results also shed light on the spatial distribution of phytoplankton and environmental forcings of primary production. Even though new remote sensing technologies and remotely operated in situ sensors are likely to provide relevant data for assessing some the impacts of bivalve farming at an ecosystem scale, the results here summarized indicate that ecosystem modelling will remain the main tool for assessing ecological carrying capacity and providing management scenarios in the context of global drivers, such as climate change.

Correction to: A. C. Smaal et al. (eds.), Goods and Services of Marine Bivalves, https://doi.org/10.1007/978-3-319-96776-9. This book was inadvertently published with an incorrect copyright year '2018' within the book references. This has now been amended throughout the book to the correct copyright year '2019'.

Bivalve aquaculture is commonly carried out in shallow water systems, which are susceptible to resuspension of benthic particulate matter by natural processes such as tidal currents, winds and wave action, as well as human activity. The resuspended material can alter the availability of food particles for cultured bivalves. The effect of resuspended material on bivalve bioenergetics and growth is a function of the quality and concentration of resuspended particles and background diet in the water column. Given the potential for positive or negative impacts on bivalve growth and consequently on farm productivity, farmers must position the cultured biomass at the appropriate depth to benefit from or mitigate the impact of this resuspended material. A combination of field measurements, a 1-D vertical resuspension model and a bioenergetic model for mussels based on Dynamic Energy Budget (DEB) theory has been carried out for a mussel farm in Skive Fjord, a shallow Danish fjord, with the aim of identifying the optimal depth for culture. Observations at the farm location revealed that horizontal advection is more important than vertical resuspension during periods with predominant Eastern winds. In addition, high background seston in the water column reduces the impact of resuspension on the available food for mussels. The simulation of different scenarios in terms of food availability suggested minimal effects of resuspension on mussel growth. Based on this finding and the fact that phytoplankton concentration, the main food source for mussels, is usually higher in the upper part of the water column, suspended culture in the top ~ 3 m of the water column seems to be the optimal practice to produce mussels in Skive Fjord.

Although models of carrying capacity have been around for some time, their use in aquaculture management has been limited. This is partially due to the cost involved in generating and testing the models. However, the use of more generic and flexible models could facilitate the implementation of modelling in management. We have built a generic core for coupling biogeo- chemical and hydrodynamic models using Simile (www.simulistics.com), a visual simulation en - vironment software that is well-suited to accommodate fully spatial models. Specifically, Simile integrates PEST (model-independent parameter estimation, Watermark Numerical Computing, www. pesthomepage.org), an optimization tool that uses the Gauss-Marquardt-Levenberg algo- rithm and can be used to estimate the value of a parameter, or set of parameters, in order to mini- mize the discrepancies between the model results and a dataset chosen by the user. The other crit- ical aspect of modelling exercises is the large amount of data necessary to set up, tune and ground truth the ecosystem model. However, ecoinformatics and improvements in remote sensing procedures have facilitated acquisition of these datasets, even in data-poor environments. In this paper we describe the required datasets and stages of model development necessary to build a biogeochemical model that can be used as a decision-making tool for bivalve aquaculture man- agement in data-poor environments.

Downward fluxes of organically rich biodeposits under suspended mussel lines can cause benthic impacts such as changes in benthic community structure or microbial mat production. Quantifying sediment erosion in these coastal ecosystems is important for understanding how fluxes of organic matter and mussel biodeposits contribute to benthic–pelagic coupling. Critical shear velocity (u*crit), erosion rates and particle size distributions of resuspended sediment were measured at four stations distributed along a transect perpendicular to a mussel farm in Lagune de la Grande Entree, Iles-de-la-Madeleine (Quebec, Canada). Stations were selected underneath the outer-most mussel line (0 m) and at distances of 15, 30 m and at a reference station (500 m) further along the transect. Shear velocity was measured using a calibrated portable Particle Erosion Simulator, also referred to as the BEAST (Benthic Environmental Assessment Sediment Tool). Undisturbed sediment cores obtained by divers were exposed to shear stress to compare differences between stations. Erosion sequences indicated no significant differences in u*crit between stations, but there were significant differences in erosion rates beneath mussel lines compared to other stations. Erosion rates were the highest in cores from beneath mussel lines, but paradoxically had the lowest u*crit. Mean erosion rates at u*crit varied between 25 and 47 g m− 2 min− 1 and critical erosion thresholds varied between 1.58 and 1.73 cm s− 1, which compare with intensive mussel culture sites elsewhere in eastern Canada. Significant differences existed in biotic and abiotic properties of sediments which could explain variation in maximum erosion rates within and between stations. Particle sizes measured by videography of resuspended sediment at different shear velocities ranged from 0.2 to 3.0 mm. Quantifying sediment erosion from intact marine sediments helps to improve our mechanistic understanding of these processes, and the BEAST further contributes to predictive capability in benthic–pelagic coupling modeling.

Growth of Mytilus edulis was simulated using individual based models following both Scope For Growth (SFG) and Dynamic Energy Budget (DEB) approaches. These models were parameterized using independent studies and calibrated for each dataset by adjusting the half-saturation coefficient of the food ingestion function term, XK, a common parameter in both approaches related to feeding behavior. Auto-calibration was carried out using an optimization tool, which provides an objective way of tuning the model. Both approaches yielded similar performance, suggesting that although the basis for constructing the models is different, both can successfully reproduce M. edulis growth. The good performance of both models in different environments achieved by adjusting a single parameter, XK, highlights the potential of these models for (1) producing prospective analysis of mussel growth and (2) investigating mussel feeding response in different ecosystems. Finally, we emphasize that the convergence of two different modeling approaches via calibration of XK, indicates the importance of the feeding behavior and local trophic conditions for bivalve growth performance. Consequently, further investigations should be conducted to explore the relationship of XK to environmental variables and/or to the sophistication of the functional response to food availability with the final objective of creating a general model that can be applied to different ecosystems without the need for calibration., This research was funded by the CANO project (CArrying capacity in NOrwegian aquaculture). RF salary was supported by an Angeles Alvariño (Xunta de Galicia) contract and a Xunta de Galicia fellowship co-funded by the European Social Fund (Operative Program Galicia 2007-2013).

8 páginas, 2 tablas, 6 figuras, Shellfish carryingcapacity is determined by the interaction of cultured species with the ecosystem, principally constrained by environmental characteristics, especially food availability. A recent experiment carried out in Lysefjord (SW Norway) has shown that induced upwelling of nutrient-rich deeper water stimulated phytoplankton growth, potentially increasing the carryingcapacity for mussel cultivation. With the aim of assisting in development of sustainable musselculture in Lysefjord, an object-oriented model of aquaculture–environment interactions and musselcarryingcapacity was constructed. A multiple box ecosystem model was developed within the visual simulation environment of Simile software allowing explicit coupling between boxes, which represent regions of the fjord. Once the box model was developed and calibrated, subsequent application of PEST (Parameter ESTimation) allowed optimization of different parameters of the model in order to manage mussel production according to carryingcapacity criteria. The Simile model and the simultaneous application of PEST allowed several scenarios taking into account different stocking densities, upwelling alternatives, and the creation of new cultivation areas, This research was funded by the CANO project (CArrying capacity in NOrwegian aquaculture) and a Fundación Juana de Vega fellowship to R.F.

12 páginas, 2 tablas, 5 figuras.-- The final publication is available at www.springerlink.com, Shellfish carrying capacity is determined by the interaction of cultured species with the ecosystem principally constrained by environmental characteristics, and particularly food availability. A multiple box ecosystem model was constructed to examine the carrying capacity for mussel aquaculture in Tracadie Bay, Prince of Edward Island, Canada. The model was run in two different years, 1998 and 1999, in which time series in the far field and three points inside the bay were available. This dataset constitutes an ideal situation for groundtruthing, allowing a spatial validation of the ecosystem model and checking its robustness when the boundary conditions are changed. The groundtruthing process suggested that the differential equations and parameters used on the model could provide a good prediction of the ecological dynamics within the bay. Results indicated that the mussel biomass exerts a top-down control of phytoplankton populations. Given that phytoplankton constitute the first step in marine food webs and that mussels exert a control of primary producers, carrying capacity has been studied in terms of chlorophyll depletion. The analysis of the chlorophyll depletion highlighted the importance of inter-annual variability in carrying capacity of the bay. In this way, results of the model suggest that the conditions observed during 1999 are more sensitive to aquaculture activity than observed during 1998. This result is very important from an ecosystem-level point of view because it reveals the importance of applying a precautionary policy in the management of aquaculture activity, This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) and a Fundación Juana de Vega fellowship to R.F

Sungo Bay (China) has a mean depth of 10 m, a total area of 140 km(2) and is occupied by several types of aquaculture, whilst opening to the ocean. The production of scallops (Chlamys farreri) cultured on long lines is estimated to exceed 50 000 tonnes (total weight) per year. Selection of sites for scallop growth and determination of suitable rearing densities have become important issues. In this study, we focused on the local scale (e.g. 1000 m) where rearing density, food concentration and hydrodynamics interact. We have developed a depletion model coupling a detailed model of C. farreri feeding and growth and a one-dimensional horizontal transport equation. The model was applied to assess the effect of some environmental parameters (e.g. food availability, temperature, hydrodynamism) and spatial variability on growth, and to assess the effect of density according to a wide range of hydrodynamical and environmental conditions. In the simulations, food concentrations always enabled a substantial weight increase with a final weight above 1.5 g dry weight. Compared to a reference situation without depletion, a density of 50 ind m(-3) decreased growth between 0% and 100%, depending on current velocity when maximum current velocity was below 20 cm s(-1). The mean ratio between food available inside and outside the cultivated area (depletion factor) varied with the percentage of variation in scallop growth that was due to density. Our model suggests that scallop growth was correlated with maximum current velocity for a given density and current velocity below 20 cm s(-1). The model was integrated within a Geographical Information System (GIS) to assist in making decisions related to appropriate scallop densities suitable for aquaculture at different locations throughout the bay. Concepts (depletion), methods (coupling hydrodynamics and growth models), and the underlying framework (GIS) are all generic, and can be applied to different sites and ecosystems where local interactions must be taken into account., La baie de Sungo (Chine) est une baie largement ouverte sur l'océan, qui occupe une surface de 140 km2 pour une profondeur moyenne de 10 m et dont une grande partie est consacrée à l'aquaculture. La production annuelle de pétoncles (Chlamys farreri) dépasse ainsi les 50 000 tonnes (poids total). La sélection de sites et la définition de densité d'élevage favorables à la croissance sont devenues un enjeu important. Nous avons développé un modèle mathématique prenant en compte les interactions entre densité d'élevage, concentration de nourriture et hydrodynamisme à un niveau local, défini par une distance typique de 1000 m, afin de prédire la diminution de nourriture liée à la consommation par les pétoncles (appelée par la suite « déplétion ») et son effet sur la croissance. Ce modèle s'appuie d'une part sur des équations détaillant la nutrition et la croissance du pétoncle et d'autre part sur un modèle de transport horizontal unidimensionnel. Il permet d'évaluer l'effet des conditions environnementales (nourriture, température, hydrodynamisme) et de leur variabilité spatiale sur la croissance et de tester l'influence de la densité d'élevage pour ces différentes conditions. Nous avons comparé une situation sans déplétion (où la croissance est maximale) à une situation avec une densité d'élevage de 50 ind par m3. Le modèle indique des diminutions de croissance entre 0 et 100 % en fonction de la vitesse du courant tant que la vitesse maximale reste en dessous de 20 cm s¿1. Cette variation de croissance annuelle peut être mise en relation avec le rapport entre la concentration moyenne de nourriture à l'intérieur et à l'extérieur du domaine cultivé, qui est un indice de déplétion reflétant principalement l'effet de la vitesse du courant. Le modèle a été intégré à un Système d'Informations Géographiques (SIG) ce qui permet de simuler et cartographier rapidement et automatiquement la croissance annuelle et de fournir ainsi des recommandations sur la densité d'élevage appropriée. Le concept de déplétion, le couplage d'un modèle de croissance et d'un modèle hydrodynamique et l'utilisation d'un SIG sont transposables à d'autres systèmes comparables dans lesquels les interactions locales doivent être considérées.