Site Suitability for Finfish Marine Aquaculture in the Central Mediterranean Sea

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

An R package for simulating growth and organic wastage in aquaculture farms in response to environmental conditions and husbandry practices

A new R software package, RAC, is presented. RAC allows to simulate the rearing cycle of 4 species, finfish and shellfish, highly important in terms of production in the Mediterranean Sea. The package works both at the scale of the individual and of the farmed population. Mathematical models included in RAC were all validated in previous works, and account for growth and metabolism, based on input data characterizing the forcing functions-water temperature, and food quality/quantity. The package provides a demo dataset of forcings for each species, as well as a typical set of husbandry parameters for Mediterranean conditions. The present work illustrates RAC main features, and its current capabilities/limitations. Three test cases are presented as a proof of concept of RAC applicability, and to demonstrate its potential for integrating different open products nowadays provided by remote sensing and operational oceanography

Making space for shellfish farming along the Adriatic coast

This work focuses on the selection of new areas for shellfish farming along the coast of the Northern Adriatic Sea (Italy). Shellfish site suitability was assessed by means of a methodology based on Spatial Multi-Criteria Evaluation (SMCE), which provided the framework to combine mathematical models and operational oceanography products. Intermediate level criteria considered in the analysis included optimal growth conditions, environmental interactions, and socio-economic evaluation (e.g. organic carbon deposition; distance to harbour). Results showed that the whole coastal area comprised within 0 and 3 nm is highly suitable for farming of mussel, while the area comprised between 3 and 12 nm is divided between a highly suitable northern part, and a less suitable southern one. Seven different scenarios of development of shellfish aquaculture industry were explored. The introduction of a new species, and the assessment of the exposure to storm events are specific aspects taken into account in development scenarios. Results show that the degree of suitability for shellfish aquaculture in this area would not change dramatically with the introduction of oyster farming. Furthermore, results highlight that: (i) the growth potential in this area is high; (ii) the space with suitability index >0.5 increases when prioritizing the optimal growth condition criteria, and (iii) the socio-economic is the most restrictive Intermediate Level Criteria. Results were discussed by deriving general lessons concerning the use of SMCE in aquaculture space allocation, from the specific application in the Northern Adriatic Sea. Challenges and opportunities related to the proposed methodological framework, with particular reference to the use of resources provided by remote sensing and operational oceanography by means of mathematical models, were also discussed. Results can support a science-based identification of allocated zones for aquaculture in order to avoid conflicts, and promote sustainable aquaculture in the Mediterranean Sea, where the space for these activities is becoming increasingly limited

Forcing variables required as input data for each model species at both individual and population level.

<p>Forcing variables required as input data for each model species at both individual and population level.</p

Case study sites and species.

<p><i>M</i>. <i>galloprovincialis</i> and <i>R</i>. <i>philippinarum</i>, and finfish, <i>S</i>. <i>aurata</i> and <i>D</i>. <i>labrax</i>. The shapefile of Italian boundaries was downloaded from DIVA-GIS dataset (freely available at <a href="http://www.diva-gis.org/Data" target="_blank">http://www.diva-gis.org/Data</a>) and the layout was made in QGIS version 2.18.5.</p

Current individual model outputs of shellfish, <i>M</i>. <i>galloprovincialis</i> and <i>R</i>. <i>philippinarum</i>, and finfish, <i>S</i>. <i>aurata</i> and <i>D</i>. <i>labrax</i>.

<p>On the left panels the individual growth in terms of length (cm and mm) for the shellfish (a and b) and of weight (g) for the finfish (d and e). On the right panel the organic waste produced by <i>M</i>. <i>galloprovincialis</i> (c) in terms of faeces and pseudofaeces (g d^-1) and the quantity of uneaten feed (g d^-1), in terms of protein, lipids and carbohydrates, produced by <i>S</i>. <i>aurata</i> (f).</p

General workflow of RAC package.

<p>Arrows show the information flow. The grey boxes indicate the functions called directly by the user.</p

Future population model outputs of <i>S</i>. <i>aurata</i> simulated at Bisceglie (Southern Adriatic Sea) under RCP 4.5 and 8.5 temperature scenarios.

<p>a) mean growth and ± standard deviation (g); b) the uneaten feed in terms of protein, lipids and carbohydrates (Kg d^-1); c) faeces produced in terms of protein, lipids and carbohydrates (Kg d^-1).</p

Output data obtained from the models of each species at both individual and population level.

<p>Output data obtained from the models of each species at both individual and population level.</p

RAC spatial application: Output of <i>M</i>. <i>galloprovincialis</i>.

<p>In these maps are represented the number of days necessary to reach the commercial size of 5 cm (a) and 7 cm (b). The shapefile of Italian boundaries was downloaded from DIVA-GIS dataset (freely available at <a href="http://www.diva-gis.org/Data" target="_blank">http://www.diva-gis.org/Data</a>) and the layout was made in QGIS version 2.18.5.</p