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An ecosystem model for optimising production in integrated multitrophic aquaculture systems

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  • Ren, Jeffrey S.
  • Stenton-Dozey, Jeanie
  • Plew, David R.
  • Fang, Jianguang
  • Gall, Mark

Abstract

Integrated multitrophic aquaculture (IMTA) aims to be an ecologically balanced aquaculture practice that co-cultures species from multiple trophic levels to optimise the recycling of farm waste as a food resource. It provides an opportunity for product diversification and an increase in economic return if managed at the optimal stocking densities for each co-cultured species. A generic IMTA ecosystem model, incorporating dynamic energy budgets for a number of co-culture species from different trophic levels was developed to design IMTA farms for optimisation of multispecies productivity. It is based on the trophic similarity in the ecophysiological behaviour of cultured organisms to describe the uptake and use of energy. This approach can accommodate different species within a trophic group and is transferable to IMTA operations based on finfish–shellfish-detritivore-primary producer systems. Model simulations were firstly performed considering the monoculture of mussels and finfish, each “farm” interacting with the natural variability of the local environment. The next step was running the IMTA model with the co-culture groups added in: one run was with finfish as the key species in co-culture with seaweed and sea cucumbers and the other with mussels as the key culture species in association with seaweed and sea cucumbers. Scenario simulations show that conversion from monoculture to IMTA would considerably reduce waste products and increase farm productivity. Although the development of IMTA practices will depend on acceptable levels of waste products, feasibility and profitability of culture operations, the IMTA model provides a research tool for designing IMTA practices and to understand species interactions and predict productivity of IMTA farms. The refinement of the model and its power to predict multispecies productivity depends on emerging data from trial and commercial sea-based IMTA operations.

Suggested Citation

  • Ren, Jeffrey S. & Stenton-Dozey, Jeanie & Plew, David R. & Fang, Jianguang & Gall, Mark, 2012. "An ecosystem model for optimising production in integrated multitrophic aquaculture systems," Ecological Modelling, Elsevier, vol. 246(C), pages 34-46.
  • Handle: RePEc:eee:ecomod:v:246:y:2012:i:c:p:34-46
    DOI: 10.1016/j.ecolmodel.2012.07.020
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    1. Grant, Jon & Curran, Kristian J. & Guyondet, Thomas L. & Tita, Guglielmo & Bacher, Cédric & Koutitonsky, Vladimir & Dowd, Michael, 2007. "A box model of carrying capacity for suspended mussel aquaculture in Lagune de la Grande-Entrée, Iles-de-la-Madeleine, Québec," Ecological Modelling, Elsevier, vol. 200(1), pages 193-206.
    2. Ren, Jeffrey S. & Ross, Alex H. & Hadfield, Mark G. & Hayden, Barbara J., 2010. "An ecosystem model for estimating potential shellfish culture production in sheltered coastal waters," Ecological Modelling, Elsevier, vol. 221(3), pages 527-539.
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    3. Sun, Ke & Zhang, Jihong & Lin, Fan & Ren, Jeffrey S. & Zhao, Yunxia & Wu, Wenguang & Liu, Yi, 2020. "Evaluating the influences of integrated culture on pelagic ecosystem by a numerical approach: A case study of Sungo Bay, China," Ecological Modelling, Elsevier, vol. 415(C).
    4. Guillaumot, Charlène & Saucède, Thomas & Morley, Simon A. & Augustine, Starrlight & Danis, Bruno & Kooijman, Sebastiaan, 2020. "Can DEB models infer metabolic differences between intertidal and subtidal morphotypes of the Antarctic limpet Nacella concinna (Strebel, 1908)?," Ecological Modelling, Elsevier, vol. 430(C).
    5. Junbo Zhang & Daisuke Kitazawa & Chenxing Yang, 2016. "A numerical modeling approach to support decision-making on design of integrated multitrophic aquaculture for efficiently mitigating aquatic waste," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(8), pages 1247-1261, December.
    6. Dong Tian & Min Zhang & Xuejian Wei & Jing Wang & Weisong Mu & Jianying Feng, 2018. "GIS-Based Energy Consumption and Spatial Variation of Protected Grape Cultivation in China," Sustainability, MDPI, vol. 10(9), pages 1-21, September.
    7. Zhao, Yunxia & Zhang, Jihong & Lin, Fan & Ren, Jeffrey S. & Sun, Ke & Liu, Yi & Wu, Wenguang & Wang, Wei, 2019. "An ecosystem model for estimating shellfish production carrying capacity in bottom culture systems," Ecological Modelling, Elsevier, vol. 393(C), pages 1-11.
    8. Ren, Jeffrey S. & Jin, Xianshi & Yang, Tao & Kooijman, Sebastiaan A.L.M. & Shan, Xiujuan, 2020. "A dynamic energy budget model for small yellow croaker Larimichthys polyactis: Parameterisation and application in its main geographic distribution waters," Ecological Modelling, Elsevier, vol. 427(C).
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    10. Yang, Tao & Ren, Jeffrey S. & Kooijman, Sebastiaan A.L.M. & Shan, Xiujuan & Gorfine, Harry, 2020. "A dynamic energy budget model of Fenneropenaeus chinensis with applications for aquaculture and stock enhancement," Ecological Modelling, Elsevier, vol. 431(C).
    11. Venolia, Celeste T. & Lavaud, Romain & Green-Gavrielidis, Lindsay A. & Thornber, Carol & Humphries, Austin T., 2020. "Modeling the Growth of Sugar Kelp (Saccharina latissima) in Aquaculture Systems using Dynamic Energy Budget Theory," Ecological Modelling, Elsevier, vol. 430(C).
    12. Lavaud, Romain & Filgueira, Ramón & Nadeau, André & Steeves, Laura & Guyondet, Thomas, 2020. "A Dynamic Energy Budget model for the macroalga Ulva lactuca," Ecological Modelling, Elsevier, vol. 418(C).

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