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

Assessing the potential biomass yield is a key step in aquaculture site selection. This is challenging, especially for shellfish, as the growth rate depends on both trophic status and water temperature. Individual ecophysiological models can be used for mapping potential shellfish growth in coastal...

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Bibliographic Details
Published in:Sustainability
Main Authors: Bertolini Camilla, Brigolin Daniele, Porporato Erika M.D., Hattab Jasmine, Pastres Roberto, Tiscar Pietro Giorgio
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
AZA
Online Access:https://zenodo.org/record/4610728
https://doi.org/10.3390/su13063309
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Summary:Assessing the potential biomass yield is a key step in aquaculture site selection. This is challenging, especially for shellfish, as the growth rate depends on both trophic status and water temperature. Individual ecophysiological models can be used for mapping potential shellfish growth in coastal areas, using as input spatial time series of remotely sensed SST and chlorophylla. This approach was taken here to estimate the potential for developing oyster (Crassostrea gigas) farming in the western Adriatic Sea. Industry relevant indicators (i.e., shell length, total individual weight) and days required to reach marketable size were mapped using a dynamic energy budget model, finetuned on the basis of site-specific morphometric data collected monthly for a year. Spatially scaled-up results showed that the faster and more uniform growth in the northern Adriatic coastal area, compared with the southern one, where chlorophyll-a levels are lower and summer temperatures exceed the critical temperature limit for longer periods. These results could be used in planning the identification of allocated zones for aquaculture, (AZA), taking into account also the potential for farming or co-farming C. gigas. In perspective, the methodology could be used for getting insights on changes to the potential productivity indicators due to climatic changes.