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Functional trait-based layers - an aquaculture siting tool for the Mediterranean Sea
Giacoletti, A.; Lucido, G.D.; Mangano, M.C.; Sarà, G. (2021). Functional trait-based layers - an aquaculture siting tool for the Mediterranean Sea. Aquaculture 532: 736081. https://dx.doi.org/10.1016/j.aquaculture.2020.736081
In: Aquaculture. Elsevier: Amsterdam; London; New York; Oxford; Tokyo. ISSN 0044-8486; e-ISSN 1873-5622, more
Peer reviewed article  

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Keywords
    Aquaculture
    Dicentrarchus labrax (Linnaeus, 1758) [WoRMS]
    ANE, France, Mediterranean Sea
    Marine/Coastal
Author keywords
    Aquaculture; Environmental sustainability; Impact; Mediterranean Sea; DEB model; Dicentrarchus labrax

Authors  Top 
  • Giacoletti, A.
  • Lucido, G.D.
  • Mangano, M.C.
  • Sarà, G.

Abstract
    Aquaculture, the current fastest-growing food sector, is one of the major opportunities that could be reaped to cope with the increased demand for proteins from the sea and simultaneously generate economic growth while ensuring sustainable use of natural resources. The number of tools and approaches suggested to promote the selection of suitable areas - focusing mostly on the management of potential conflicting uses at sea - is rapidly increasing. However, to date, there is a lack of information regarding spatial planning according to a trait-based approach encompassing the functional and biological data of farmed species; a gap that may lead to selecting unsuitable areas for farming. To fill this gap, our study builds on a functional trait-based mechanistic approach based on the Dynamic Energy Budget (DEB) theory allowing to generated species and site-specific predictions of aquaculture performances and the related environmental impact. We applied this approach to a commercial species farmed in the Mediterranean Sea, namely, the European seabass (Dicentrarchus labrax). We used three seeding sizes (1.5, 2, 2.5 g) to run model simulations and answer a crucial question for farm management, i.e. the selection of the best seeding size. A sensitivity analysis coupled with our simulations allowed to spatially represent the performance growth and environmental impact per seeding size across Mediterranean countries. The accuracy of the model's outcome was strengthened by using high-resolution satellite data over a wide area of investigation (c.a. 302,000 km2). The novel informative obtained layers combine both the modelling of aquaculture performance and related environmental impact to fill a lacking perspective within both AZAs (Allocated Zones for Aquaculture) and AZEs (Allowable Zones of Effect) concepts. Our approach allowed discriminating the best zones for European sea bass aquaculture at country level for each of the tested seeding sizes. High-resolution predictions of aquaculture performances and impact were provided for each of the nineteen Mediterranean coastal countries, zooming at Exclusive Economic Zone scale (EEZ). We highlighted pole-ward negative patterns with the best values in the Southern basin; Libya, Tunisia and Egypt in particular. Our spatial contextualization - through high resolution mapped outcomes - represents an effective and salient tool for stakeholders and policy makers, based on the translation of complex computational modelling results into easy-to-read maps. The highlighted patterns may provide scientific evidence for proactive capacity-building programmes at country level in the future.

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