From proxy to practice: GIS-based evaluation of production carrying capacity in pre-selected allocated zones for aquaculture

In this study, we apply a GIS-based proxy model to estimate the production carrying capacity within the official Spanish allocated zones for aquaculture (AZAs) designated for marine finfish in the Mediterranean region. The model used integrates georeferenced data on various factors such as distance between facilities, distance to priority habitats, depth, current velocity, and employment provided. The study area was divided into 1 × 1 km cells, each assigned a weighting value (V) based on the ranges identified in the proxy model. Prior to the capacity analysis, cells deemed unsuitable for aquaculture were removed in accordance with AZA zoning criteria, so estimates refer exclusively to already compliant sites. Additionally, three self-limiting factors (unit cost of production, tonnes of feed per hectare and cage arrangement) were analyzed separately as scenarios due to their dependence on existing and projected aquaculture facility data. The carrying capacity was classified according to the upper and lower values of the production granted to the Spanish facilities currently operating in the Mediterranean region as follows: low (LCC; < 10.6 t ha −1 year −1 ), medium (MCC; 10.6–187.5 t ha −1 year −1 ) and high carrying capacity (HCC; >187.5 t ha −1 year −1 ). Under the neutral scenario, 81.8 % of the AZA surface fell within the MCC class and Andalusia was the only region obtaining HCC (13.15 %). The Valencian Community and Catalonia showed larger shares of LCC (23.28 % and 16.17 %, respectively) while MCC dominated in all regions. The percentage of high-capacity areas increased when self-limiting factors were set to their maximum values, with ‘tonnes of feed per hectare’ having the most significant impact. These self-limiting factors are linked to best practices, such as reducing feed volume or improving spatial organization within concession areas. Our findings demonstrate how a proxy-based carrying capacity layer can support spatial planning and adaptative management of Mediterranean finfish aquaculture. • The GIS-integrated proxy model classifies production carrying capacity for offshore farming cages of gilthead seabream, European seabass and meagre, and shows that farmers can increase the capacity through the use of best practices such as feed optimisation and cage-layout adjustments. • The modular and exportable nature of the model increases its effectiveness in adapting to other regions as it allows for the incorporation of other elements into its factors, such as other sensitive habitats. • This model is a useful tool that could be used for management purposes by public administrations and aquaculture companies, either to grant new concessions or to identify concessions on sites with considerable carrying capacity, provided that basic GIS training and data-sharing protocols are in place.