A physical-biological coupled ecosystem model for integrated aquaculture of bivalve and seaweed in sanggou bay

L.I.N. Fan, D.U. Meirong, L.I.U. Hui, F.A.N.G. Jianguang, Asplin Lars and J.I.A.N.G. Zengjie

Ecological Modelling, 2020, vol. 431, issue C

Abstract: To understand the biological process in an aquaculture dominant coastal system and to provide a tool for further aquaculture management, an ecosystem model has been implemented to study the aquaculture-environmental interaction and the carrying capacity for Sanggou Bay. The model coupled the pelagic system, kelp growth dynamics, oyster energetics, and population dynamics with hourly hydrodynamic and water quality data. The study area was divided into four boxes according to similarities in the hydrological environment and aquaculture layout. Scenario simulations were conducted with different combinations of oyster and kelp seeding densities to examine the environmental impacts and production under different aquaculture layouts. Results showed that the model could capture the main characteristics of observed environmental variables and culture organism growth. Increased seeding density of both oysters and kelp generally leads to increased production with diminished individual growth. Kelp aquaculture plays a leading role in the nutrient cycle in the bay, acting as a large reception tank during the rapid growth period. The model results indicate that there is still potential to increase production for both oyster and kelp in Sanggou bay. The current aquaculture practice seems to have the right balance of carrying capacity, management efforts, and other costs under the existing production procedures. The ecosystem model is a promising tool for further study with sustained observation effort and better boundary conditions.

Keywords: Sanggou bay; Bivalve-seaweed integrated aquaculture; Ecosystem model; Individual growth model; Carrying capacity estimation (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:431:y:2020:i:c:s0304380020302520

DOI: 10.1016/j.ecolmodel.2020.109181

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