OMEGA – OYSTER MAPPING, ECOMODELLING, AND GROWTH ASSESSMENT
Introduction
Shellfish growing areas have for centuries formed a natural part of the seascape and culture of the Island of Ireland, in part due to the large natural sea loughs which provide an ideal growing environment for bivalves such as mussels, oysters, and scallops.
Bivalve shellfish aquaculture is by nature extensive, and farmers typically have some challenges with respect to stock control, environmental variables, pathogens, and other parts of the business process.
Management of shellfish growing areas is a complex problem: at the core of management is the knowledge of the types, locations, and areas of shellfish culture. The application of models to evaluate carrying capacity and environmental effects relies on sound datasets with respect to stocked areas, stocking density, and other input variables.
Fig 1 shows extensive cultivation of rock oyster (Magallana gigas) on trestles in Lough Foyle. Because the culture is organically extractive, rock oysters compete with the native oyster (Ostrea edulis) fishery.
Blue mussels (Mytilus edulis) were also traditionally grown in the Foyle but at present this is not a key economic resource or a major ecosystem driver.
Over the last fifty years, the industry has changed significantly, in part due to internationalisation, both in terms of Dutch and French entry into the island of Ireland and in terms of the export and branding of Irish product, which is now well recognised in demanding and distant markets such as China.
The expansion of rock oyster cultivation in the Foyle, driven
Fig . Pacific oyster cultivation in Lough Foyle a transboundary system on the island of Ireland. in part by the resistance to oyster Herpes virus at lower water temperatures, has led to stakeholder disputes over the carrying capacity of the lough for different bivalves. The Oyster Management, Ecomodelling, and Growth Assessment (OMEGA) project was developed to: (i) determine the role of Pacific oysters in partitioning the food resource; and (ii) contribute to a fuller understanding of sustainable carrying capacity and top-down eutrophication control in Lough Foyle.
Methods
This paper identifies some of the key methodologies used to address these objectives. The first of these, and the main focus of this paper, was the combined use of remote sensing, in particular drone and satellite images, with machine-learning techniques to train algorithms to accurately identify and count oyster bags, which are typically smaller than 1 m2. Such algorithms must be able to distinguish between stocked and unstocked trestle areas.
The resulting registry was stored in the AquaScape platform (https://longline.co.uk/aquascape/), a web-based geospatial framework that has been used to map about 3.5 million aquaculture structures throughout the world, corresponding to thirty million tonnes of annual production.
In parallel, the well-known EcoWin ecological model, which has been applied to a number of sea loughs on the island of Ireland (e.g. Ferreira et al., 2008; Nunes et al., 2011; Ferreira et al., 2023) was used to simulate bivalve growth and environmental effects, with an emphasis on depletion of algae and organic detritus, to examine various scenarios of future industry development.
The accurate assessment of the actual area occupied by Pacific oyster and the geographic distribution of the structures used for cultivation was a substantial improvement to the existing carrying capacity modelling of Lough Foyle, providing a robust tool for stakeholder engagement, scenario review, and policy definition.
Results and Discussion
Fig 2 shows an example of the results obtained for image analysis of Pacific oyster culture. Not all the estuarine area can be mapped by drones due to security restrictions—satellite imagery is not as accurate for bag counts. This is a caveat for other shellfish growing areas.
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Fig . Application of machine-learning algorithms showing (left) the accurate distinction between empty trestles and those with oyster bags; and (right) the calculated skill for accurate identification of stocked and unstocked oyster bags.
Drone images allowed the mapping of individual bags and the identification of trestles without bags, whereas satellite imagery can only map groups of trestles. In the present work, drone imagery was available for two-thirds of the area (12.31 km2) and resulted in an estimation of a trestle area of 198,693 m2, with a corresponding bag count of 272,897.
The total trestle area determined by remote sensing and machine learning was 272,437 m2, that contained an estimated 323,935 bags; on average, 53% of the trestle area contained no bags—empty bags were removed by the growers. The ongoing application of the EcoWin model will provide detailed outcomes for carrying capacity, but simple calculations were made using the data acquired to date and the AquaShell bivalve growth model (e.g. Woźniacka et al., 2026)
Fig 3 shows the application of AquaShell to simulate one Pacific oyster, using environmental drivers extracted from the EcoWin model.
The outputs were used to scale up the production and environmental effects,
Fig . Simulated Pacific oyster growth and environmental effects using the AquaShell model. considering a stocking density of 80 oysters per bag and a culture period of 850 days. This would result in an annualised production of about 780 tonnes live weight and a corresponding drawdown of 830 kg of chlorophyll.
These numbers do not account for food depletion; EcoWin results will provide a clearer picture of the role of Pacific oysters in partitioning the food resource and of their contribution to top-down control of eutrophication.
Acknowledgements
The authors wish to acknowledge funding from the Loughs Agency.
Key references
FAO (Food and Agriculture Organization of the United Nations), 2024. The state of world fisheries and aquaculture (SOFIA). FAO, Rome, 264 pp.
Ferreira, J.G., Hawkins, A.J.S., Monteiro, P., Moore, H., Service, M., Pascoe, P.L., Ramos, L., Sequeira, A., 2008. Integrated Assessment of Ecosystem-Scale Carrying Capacity in Shellfish Growing Areas. Aquaculture, 275, 138-151.
Ferreira, J.G., Bernard-Jannin, L., Cubillo, A., Lencart-Silva, J., Diedericks, G.P.J., Moore, H., Service, M., Nunes, J.P. 2023. From soil to sea: an ecological modelling framework for sustainable aquaculture. Aquaculture 557, 1-14.
Nunes, J.P., J. G. Ferreira, S. B. Bricker, B. O'Loan, T. Dabrowski, B. Dallaghan, A. J. S. Hawkins, B. O'Connor, T. O'Carroll, 2011. Towards an ecosystem approach to aquaculture: assessment of sustainable shellfish cultivation at different scales of space, time and complexity. Aquaculture, 315, 369-383.
Woźniacka, K., Moore, H., Pinn, E., Bricker, S.B., Cubillo, A.M., Ferreira, J.G., Service, M., 2026. Bivalves at Work: Quantifying Nutrient Removal Services in UK Coastal Waters. Estuaries and Coasts 49, 84. https://doi.org/10.1007/s12237-026-01689-3.