Site Suitability for Finfish Marine Aquaculture in the Central Mediterranean Sea

Abstract

Farm site selection plays a critical role in determining the productivity, environmental impact, and interactions of aquaculture activities with ecosystem services. Satellite Remote Sensing (SRS) provide spatially extensive datasets at high temporal and spatial resolution, which can be useful for aquaculture site selection. In this paper we mapped a finfish aquaculture Suitability Index (SI) applying the Spatial Multi-criteria Evaluation (SMCE) methodology. The robustness of the outcome of the SMCE was investigated using Uncertainty Analysis (UA), and in parallel we evaluate a set of alternative scenarios, aimed at minimizing the subjectivity associated with the decision process. The index is based on the outputs of eco-physiological models, which were forced using time series of sea surface temperature data, and on data concerning Significant Wave Height (SWH), distance to harbor, current sea uses, and cumulative impacts. The methodology was applied to map the suitability for farming of European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata) within the Italian Economic Exclusive Zone (EEZ), under three scenarios: Blue Growth, Economic and Environment. Tyrrhenian and Ionian coastal areas were found to be more suitable, compared to the Northern Adriatic and southern Sicilian ones. In the latter, and in the western Sardinia, the index is also affected by higher uncertainty. The application presented suggests that SRS data could play a significant role in designing the Allocated Zones for Aquaculture, assisting policy makers and regulators in including aquaculture within maritime spatial planning.

Towards Environmental Sustainability in Marine Finfish Aquaculture

“…Environmental impacts of a single farm may not be significant when considered individually but may be relevant if other farms, fishing grounds, or activities are located in the same area. Environmentally sound selections of the site, away from habitats of ecological interest, together with adequate management, are the best tools to prevent or minimize the negative environmental effects of farming (Porporato et al, 2020). Therefore, aquaculture operators must act as environmental managers to ensure a pollution-free environment in which to culture healthy organisms.…”

Application of Exploratory Modeling in Support of Transdisciplinary Inquiry: Regulation of Fishing Bycatch of Loggerhead Sea Turtles in Gulf of Ulloa, Mexico

“…Marine space was conceptualized in the MSP-NPMR as a complex socio-environmental system that coupled a set of biophysical attributes with the values, needs, and interests of multiple stakeholders (Pedroza-Páez et al, 2020). the MSP-NPMR entailed the implementation of suitability assessment through Spatial Multi-criteria Evaluation (SMCE), a widely used approach for tackling geographic decision-making problems (Malczewski and Rinner, 2015;Porporato et al, 2020). Operationally, SMCE involved carrying out a series of expert consultation workshops in which representatives of each sector were convened to develop geospatial models.…”

Testing a Model of Pacific Oysters’ (Crassostrea gigas) Growth in the Adriatic Sea: Implications for Aquaculture Spatial Planning

“…Individual-based growth models can be used as tools to estimate a set of indicators, such as time to harvest and average size at harvest, in relation to site-specific time series of forcing functions: for shellfish the most important ones are water temperature and chlorophyll-a, which is taken as a proxy of energy available to filter feeders. The above forcings can be estimated over large coastal areas from remotely sensed data; therefore, potential productivity indicators can be mapped and used in aquaculture site selection [15,20,21]. Dynamic energy budget (DEB) theory [22] has provided a framework for developing robust individual ecophysiological models [23], based on a limited set of assumptions and applicable to a wide range of species, including farmed ones (e.g., [24]).…”

“…Dynamic energy budget (DEB) theory [22] has provided a framework for developing robust individual ecophysiological models [23], based on a limited set of assumptions and applicable to a wide range of species, including farmed ones (e.g., [24]). The large amount of satellite data currently available allows one to run ecophysiological models in a spatially explicit manner [15,21].…”