Using the Dynamic Energy Budget theory to evaluate the bioremediation potential of the polychaete Hediste diversicolor in an integrated multi-trophic aquaculture system
•The DEB model for Hediste diversicolor accurately predicts metabolic processes•Bioremediation potential of fish farm waste by H. diversicolor was estimated for different scenarios•A 100 m−2 ragwom farm could bioremediate 2-9% fish faeces produced by a 20T seabass farm per year•DEB modelling appears...
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Veröffentlicht in: | Ecological modelling 2020-12, Vol.437, p.109296, Article 109296 |
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Sprache: | eng |
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Zusammenfassung: | •The DEB model for Hediste diversicolor accurately predicts metabolic processes•Bioremediation potential of fish farm waste by H. diversicolor was estimated for different scenarios•A 100 m−2 ragwom farm could bioremediate 2-9% fish faeces produced by a 20T seabass farm per year•DEB modelling appears to be a promising tool for further IMTA development
Integrated Multi-Trophic Aquaculture (IMTA) systems have been designed to optimize nutrient and energy use, to decrease waste, and to diversify fish-farm production. Recently, the development of detritivorous aquaculture has been encouraged, as detrivores can consume organic particulate matter, reducing benthic eutrophication and the environmental footprint of aquaculture. To this end, the polychaete Hediste diversicolor is a promising species due to its broad feeding behaviour and its resistance in a wide range of environments. In this study, an existing Dynamic Energy Budget (DEB) model of H. diversicolor was used to predict the ragworm's metabolic processes in various environmental conditions and to estimate its bioremediation capacity in an aquaculture context. First, the scaled functional response (f) was calibrated in a 98-day growth experiment with two types of food (Fish faeces and Fish feed). Then, we further validated the model using data on the ammonia excretion and oxygen consumption of individuals fed with fish faeces at four different temperatures using the previously calibrated f. Overall, we found that the DEB model was able to correctly predict the experimental data (0.51 |
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ISSN: | 0304-3800 1872-7026 |
DOI: | 10.1016/j.ecolmodel.2020.109296 |