Abstract
The integrated multi-trophic aquaculture (i.e., IMTA) is a practice combining organisms with different trophic levels with the final purpose of transforming the continuous waste of food by targeting species into nutrient input for other non-target species. This practice very often involves filter feeders, such as bivalves, by the use of which bioenergetics budgets are strongly influenced by the quality and quantity of different foods. However, to date, scant information is available, to really understand the rebounds of food availability on the growth performances of these harvested biomasses in the natural environment. By choosing the mussel Mytilus galloprovincialis as a model, this study aims to (1) characterize the functional response of the species to define all parameters related to food intake strategies and (2) to investigate how responses change as a function of varying food sources. Laboratory procedures have been designed to evaluate the clearance rates (CR) and assimilation efficiencies (AE) of M. galloprovincialis with varying food concentrations, while different diets (i.e., seagrass, phytoplankton, and pellets) have been provided to investigate how differently they reach saturation. Results show that in the presence of phytoplankton and seagrass as food sources, the feeding strategies of M. galloprovincialis follow a II-type Holling's curve, while it shows a I-type Holling's curve when pellet food is provided. Investigating the behavioural components of functional responses may improve our ability to predict where to place shellfish cultures, as it may be useful in the context of IMTA management and in addressing siting studies. Statement of relevanceOur paper focuses on a question central to understanding and predicting the likely impacts of one among the most important human economic activity like the aquaculture in coastal habitats. The main question deals with the possibility to combine experimental procedures with the new mechanistic functional trait based bioenergetic models in order to effectively predict life history traits of cultivated species.
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