Goods and services of integrated multi-trophic aquaculture (IMTA)

In Integrated Multi-Trophic Aquaculture (IMTA) systems different cultures are linked with the goal to maximize ‘input’ nutrient retention into harvestable products. ‘Fed species’ (e.g. fish, crab and shrimp) only retain a fraction of the nutrients provided through feeding, while an amount similar to the non-retained nutrients by the fed species can be harvest in the form of ‘extractive species’ (e.g. filter feeders, detritus feeders and autotrophs).

Nowadays a clear picture is lacking on the ‘connectivity’ of the different compartments in open sea IMTA systems. Although a higher productivity of molluscs and seaweeds have been observed in the vicinity of sea cages, there are also indications that in open sea IMTA systems only a minor fraction (<5%) of the input nutrients ends up in other cultures. However, there is no satisfying explanation linking the low uptake of input nutrients in open systems with the high productivity increases by extractive species due to the presence of fed species.

From an ‘ecosystem based management’ point of view the ‘connectivity’ between the IMTA compartments should be evaluated at ecosystem level. With this concept, the main objective is not to recapture the same nutrients that were introduced into the system, but to balance inputs and outputs in the IMTA system. However when most of the nutrients captured by extractive species are nutrients naturally present in the ecosystem, while the majority of the ‘fed input nutrients’ remain in the system, the question can be asked: is this concept also sustainable?

The aim of his PhD project is to qualify and quantify in IMTA the nutrient fluxes (N, P and C) between the fed and extractive components. Nutrient flows between system components will be analysed using replicate mini- and mesocosms and biomarkers like fatty acids (FA) and stable isotopes (SI). Insights gained from these experiments will be used to integrate measured nutrient retention rates into a model and to predict fluxes within this model.