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The effects of intensive aquaculture on nutrient residence time and transport in a coastal embayment

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Abstract

Aquaculture in many countries around the world has become the biggest source of seafood for human consumption. While it alleviates the pressure on wild capture fisheries, the long-term impacts of large-scale, intensive aquaculture on natural coastal systems need to be better understood. In particular, aquaculture may alter habitat and exceed the carrying capacity of coastal marine ecosystems. In this paper, we develop a high-resolution numerical model for Sanggou Bay, one of the largest kelp and shellfish aquaculture sites in Northern China, to investigate the effects of aquaculture on nutrient transport and residence time in the bay. Drag from aquaculture is parameterized for surface infrastructure, kelp canopies, and bivalve cages. A model for dissolved inorganic nitrogen (DIN) includes transport, vertical turbulent mixing, sediment and bivalve sources, and a sink due to kelp uptake. Test cases show that, due to drag from the dense aquaculture and thus a reduction of horizontal transport, kelp production is limited because DIN from the Yellow Sea is consumed before reaching the interior of the kelp farms. Aquaculture drag also causes an increase in the nutrient residence time from an average of 5 to 10 days in the middle of Sanggou Bay, and from 25 to 40 days in the shallow inner bay. Low exchange rates and a lack of DIN uptake by kelp make these regions more susceptible to phytoplankton blooms due to high nutrient retention. The risk is further increased when DIN concentrations rise due to river inflows.

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References

  1. Bleck R (2002) An oceanic general circulation model framed in hybrid isopycnic-cartesian coordinates. Ocean Model 4:55–88

    Article  Google Scholar 

  2. Blumberg AF, Mellor GL (1987) A description of a three-dimensional coastal ocean circulation model. In: Heaps N (ed) Three-dimensional coastal ocean models. American geophysical union, Washington, DC, pp 1–16

    Google Scholar 

  3. Blumberg AF, Galperin B, O’Connor DJ (1992) Modeling vertical structure of open-channel flows. J Hydraul Eng 118:1119–1134

    Article  Google Scholar 

  4. Bolin B, Rodhe H (1973) A note on the concepts of age distribution and transit time in natural reservoirs. Tellus 25(1):58

    Article  Google Scholar 

  5. Boller ML, Carrington E (2006) In situ measurements of hydrodynamic forces imposed on chondrus crispus stackhouse. J Exp Mar Biol Ecol 337:159–170

    Article  Google Scholar 

  6. Boyd AJ, Heasman KG (1998) Shellfish mariculture in the benguela system: water flow patterns within a mussel farm in Saldanha Bay, South Africa. J Shellfish Res 17:25–32

    Google Scholar 

  7. Cao L, Naylor R, Henriksson P, Leadbitter D, Metian M, Troell M, Zhang W (2015) China’s aquaculture and the world’s wild fisheries. Science 347:133–135

    Article  Google Scholar 

  8. Chen C, Liu H, Beardsley RC (2003) An unstructured grid, finite-volume, three-dimensional, primitive equations ocean model:application to coastal ocean model: application to coastal ocean and estuaries. J Atmos Ocean Technol 20:159186

    Article  Google Scholar 

  9. Deleersnijder E, Campin JM, Delhez EJM (2001) The concept of age in marine modelling i. Theory and preliminary model results. J Mar Syst 28(3–4):229–267

    Article  Google Scholar 

  10. Delhez EJM, Campin JM, Hirst AC, Deleersnijder E (1999) Toward a general theory of the age in ocean modelling. Ocean Model 1(1):17–27

    Article  Google Scholar 

  11. Duarte P, Meneses R, Hawkins AJS, Zhu M, Fang J, Grant J (2003) Mathematical modelling to assess the carrying capacity for multi-species culture within coastal waters. Ecol Model 168:109–143

    Article  Google Scholar 

  12. Egbert GD, Bennett AF, Foreman MGG (1994) Topex/poseidon tides estimated using a global inverse model. J Phys Oceanogr 15(C12):24821–24852

    Google Scholar 

  13. Fan X (2008) Preliminary studies on the features of tidal-dynamic structure in a typically high density mariculture coastal bay-observation and simulations. PhD thesis, Ocean University of China, Qingdao, China, 132 pp

  14. Fang J, Zhang J, Xiao T, Huang D, Liu S (2016) Integrated multi-trophic aquaculture (IMTA) in Sanggou Bay, China. Aquac Environ Interact 8:201–205

    Article  Google Scholar 

  15. FAO (1989) Culture of Kelp ( Laminaria Japonica) in China. Food and Agriculture Organization of the United Nations, RAS/86/034, Training Manual

  16. FAO (2014) The state of world fisheries and aquaculture. Food and Agriculture Organization of the United Nations, Rome

    Google Scholar 

  17. FAO (2015) FAO global aquaculture production database updated to 2013 summary information. Food and Agriculture Organization of the United Nations, Rome

    Google Scholar 

  18. Fenocchi A, Sibilla S (2016) Hydrodynamic modelling and characterisation of a shallow fluvial lake: a study on the superior lake of mantua. J Limnol 75(3):455

    Google Scholar 

  19. Fringer OB, Gerritsen M, Street RL (2006) An unstructured-grid, finite-volume, nonhydrostatic, parallel coastal ocean simulator. Ocean Model 14:139–173

    Article  Google Scholar 

  20. Fu M, Pu X, Wang Z, Liu X (2013) Integrated assessment of mariculture ecosystem health in sanggou bay. Acta Ecol Sinica 33(1):238–248

    Article  Google Scholar 

  21. Gaylord B, Denny MW, Koehl MAR (2008) Flow forces on seaweeds: field evidence for roles of wave impingement and organism inertia. Biol Bull 215:295–308

    Article  Google Scholar 

  22. Geider RJ, Roche JL (2002) Redfield revisited: variability of C:N: P in marine microalgae and its biochemical basis. Eur J Phycol 31:1–17

    Article  Google Scholar 

  23. Gibbs MM, James MR, Pickmere SE, Woods PH, Shakespear BS, Hickman RW, Illingworth J (1991) Hydrodynamics and water column properties at six stations associated with mussel farming in Pelorus Sound 1984–85. N Z J Mar Freshwater Res 25:239–254

    Article  Google Scholar 

  24. Grant J, Bacher C (2001) A numerical model of flow modification induced by suspended aquaculture in a Chinese Bay. Can J Fish Aquat Sci 58:1003–1011

    Article  Google Scholar 

  25. Hoffmann MR (2004) Application of a simple space-time averaged porous media model to flow in densely vegetated channels. J Porous Media 7:183–191

    Article  Google Scholar 

  26. Jackson GA, Winant CD (1983) Effect of a kelp forest on coastal currents. Cont Shelf Res 2(1):75–80

    Article  Google Scholar 

  27. Johnson AS (2001) Drag, drafting, and mechanical interactions in canopies of the red alga chondrus crispus. Biol Bull 201:126–135

    Article  Google Scholar 

  28. Kim SJ, Stoesser T (2011) Closure modeling and direct simulation of vegetation drag in flow through emergent vegetation. Water Resour Res 47(10):W10,511

    Article  Google Scholar 

  29. Kishi MJ, Uchiyama M, Iwata Y (1994) Numerical simulation model for quantitative management of aquaculture. Ecol Model 79:21–40

    Article  Google Scholar 

  30. Li R, Liu S, Zhang J, Jiang Z, Fang J (2016) Sources and export of nutrients associated with integrated multi-trophic aquaculture in Sanggou Bay, China. Aquac Environ Interact 8:285–309

    Article  Google Scholar 

  31. Liu H, Qi Z, Zhang J, Mao Y, Fang J (2013) Ecosystem service and value evaluation of different aquaculture mode in Sungo Bay. China Ocean University Press, Qingdao

    Google Scholar 

  32. Liu Z (2016) On the eutrophication level of mariculture zone in Sanggou Bay based on fuzzy synthesis evaluation. Ocean Dev Manag 3:43–47

    Google Scholar 

  33. Liu Z, Wei H (2007) Estimate of the TKE dissipation and shear stress in the bottom boundary layer in the Yellow Sea. Progress Nat Sci 17(3):362–369

    Google Scholar 

  34. Lueck R (2009) Turbulence in the benthic boundary layer. In: Thorpe SA (ed) Encyclopedia of ocean sciences: elements of physical oceanography. Academic Press, Cambridge, pp 311–316

    Google Scholar 

  35. MAPRC (2001) Environmental-friendly food technical specifications of laminaria japonica Aresch-Agricultural industry standard of People’s Republic of China. NY/T 5057-2001

  36. Mellor GL, Oey LY, Ezer T (1998) Sigma coordinate pressure gradient errors and the seamount problem. J Atmos Ocean Technol 35(1):1122–1131

    Article  Google Scholar 

  37. Monson N, Cloern J, Lucas L, Monismith S (2002) A comment on the use of flushing time, residence time, and age as transport time scales. Limnol Oceanogr 47(5):1545–1553

    Article  Google Scholar 

  38. Nepf HM (1999) Drag, turbulence, and diffusion in flow through emergent vegetation. Water Resour Res 35(2):479–489

    Article  Google Scholar 

  39. Nepf HM (2012) Flow and transport in regions with aquatic vegetation. Ann Rev Fluid Mech 44(1):123–142

    Article  Google Scholar 

  40. Oldham CE, Sturman JJ (2001) The effect of emergent vegetation on convective flushing in shallow wetlands: scaling and experiments. Limnol Oceanogr 46:1486–1493

    Article  Google Scholar 

  41. Rayson M, Gross ES, Monismith SG, Fringer OB (2015) Modelling the tidal and sub-tidal hydrodynamics in a shallow, micro-tidal estuary. Ocean Model 89:29–44. https://doi.org/10.1016/j.ocemod.2015.02.002

    Article  Google Scholar 

  42. Rosman JH, Monismith SG, Denney MW, Koseff JR (2010) Currents and turbulence within a kelp forest (macrocystis pyrifera): insights from a dynamically scaled laboratory model. Limnol Oceanogr 55(3):1145–1158

    Article  Google Scholar 

  43. Rosmond TE (1992) The design and testing of the navy operational global atmospheric prediction system. Weather Forcast 7:262–272

    Article  Google Scholar 

  44. Shi J (2009) Numerical study on the influences of physical processes on the aquaculture carrying capacity in a semi-enclosed bay. PhD thesis, Ocean University of China, Qingdao, China, 126 pp

  45. Sun Y, Song Y, Cui Y, Fang J (1996) Distribution and behavior of dissolved inorganic nitrogen in the aquaculture zone in Sanggou Bay China. Mar Fish Res 17(2):52–59

    Google Scholar 

  46. Teague WJ, Pistek P, Jacobs GA, Perkins HT (2000) Evaluation of the tides from topex/poseidon in the bohai and yellow seas. J Atmos Ocean Technol 17:679–687

    Article  Google Scholar 

  47. Wang B, Zhao G, Fringer OB (2011) Reconstruction of vector fields for semi-Lagrangian advection on unstructured, staggered grids. Ocean Model 40(1):52–71

    Article  Google Scholar 

  48. Wood TM (2008) Modeling hydrodynamics and heat transport in upper Klamath Lake, Oregon, and implications for water quality. Technical Report, United States Geological Survey

  49. Wu Y, Chaffey J, Law B, Greenberg DA, Drozdowski A, Page F, Haigh S (2014) A three-dimensional hydrodynamic model for aquaculture: a case study in the Bay of Fundy. Aquac Environ Interact 5:235248

    Article  Google Scholar 

  50. Yu R, Liu D (2016) Harmful algal blooms in the coastal waters of China: current situation, long-term changes and prevention strategies. J Chin Acad Sci 31(10):11167–11174

    Google Scholar 

  51. Zhang J, Jiang Z, Wang W, Zou J, Xue S, Fang J, Lian Y, Zhang X, Liu X, Zhou Y (2010) Seasonal distribution and variation of nutrients and nutrients limitation in Sanggou Bay. Prog Fish Sci 31(4):16–25

    Google Scholar 

  52. Zhang J, Wang W, Han T, Liu D, Fang J, Jiang Z, Liu X, Zhang X, Lian Y (2012) The distributions of dissolved nutrients in spring of Sungo Bay and potential reason of outbreak of red tide. J Fish China 36(1):132–139

    Article  Google Scholar 

  53. Zhang J, Wang W, Ren JS, Lin F (2016a) A model for the growth of mariculture kelp saccharina japonica in Sanggou Bay, China. Aquac Environ Interact 8:273–283

    Article  Google Scholar 

  54. Zhang Z (2010) Numerical simulations of nonlinear internal waves in the South China Sea. Ph.D. thesis, Stanford University, Stanford, California

  55. Zhang Z, Lv J, Ye S, Zhu M (2007) Values of marine ecosystem services in Sanggou Bay. Chin J Appl Ecol 18(11):2540–2547

    Google Scholar 

  56. Zhang Z, Huang H, Liu Y, Yan L, Bi H (2016b) Effects of suspended culture of the seaweed laminaria japonica aresch on the flow structure and sedimentation process. J Ocean Univ China 15:643–654

    Article  Google Scholar 

  57. Zink P (2012) Application of a porous media approach for vegetation flow resistance. In: Mun̄oz RM (ed) River flow, proceedings of the international conference on fluvial hydraulics, San Jose, Costa Rica, 5–7 September, 2012, CRC Press, Boca Raton. pp 301–308

  58. Zinke P (2010) Flow resistance parameters for natural emergent vegetation derived from a porous media model. In: Dittrich A, Koll K, Aberle J, Geisenhainer P (eds) River flow, proceedings of the international conference on fluvial hydraulics, Braunschweig, Germany, September 08–10, 2010, pp 461–468

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Acknowledgements

We thank S. Dong, X. Chen and Q. Gao from Ocean University of China for assistance in the field visit and data collection. This research is funded by the Stanford Woods Institute for the Environment at Stanford University.

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Correspondence to Bing Wang.

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Wang, B., Cao, L., Micheli, F. et al. The effects of intensive aquaculture on nutrient residence time and transport in a coastal embayment. Environ Fluid Mech 18, 1321–1349 (2018). https://doi.org/10.1007/s10652-018-9595-7

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  • DOI: https://doi.org/10.1007/s10652-018-9595-7

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