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Study of the nutrient and plankton dynamics in Lake Tanganyika using a reduced-gravity model
Institution:1. Université catholique de Louvain, Institut d’astronomie et de géophysique Georges Lemaître, Chemin du Cyclotron 2, B-1348 Louvain-La-Neuve, Belgium;2. Facultés Universitaires Notre-Dame de la Paix, Laboratoire d’Ecologie des Eaux Douces, Rue de Bruxelles 61, B-5000 Namur, Belgium;3. Université catholique de Louvain, Institut d’astronomie et de géophysique Georges Lemaître and Centre for systems engineering and applied mechanics, 4 Avenue Georges Lemaître, B-1348 Louvain-La-Neuve, Belgium;4. Australian Institute of Marine Science, PMB No. 3, Townsville MC, Qld. 4810, Australia;1. Departamento de Matemática Aplicada, E.T.S.I. Industriales, Universidad Nacional de Educación a Distancia (UNED), c/ Juan del Rosal 12, 28040 Madrid, Spain;2. Centre for Mathematical Biology, Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, UK;1. Griffith School of Environment, Griffith University, 170 Kessels Rd., Nathan, QLD 4111, Australia;2. Mathematical Institute, University of Oxford, Andrew Wiles Building, ROQ, Woodstock Road, Oxford OX2 6GG, UK
Abstract:An eco-hydrodynamic (ECOH) model is proposed for Lake Tanganyika to study the plankton productivity. The hydrodynamic sub-model solves the non-linear, reduced-gravity equations in which wind is the dominant forcing. The ecological sub-model for the epilimnion comprises nutrients, primary production, phytoplankton biomass and zooplankton biomass. In the absence of significant terrestrial input of nutrients, the nutrient loss is compensated for by seasonal, wind-driven, turbulent entrainment of nutrient-rich hypolimnion water into the epilimnion, which gives rise to high plankton productivity twice in the year, during the transition between two seasons. Model simulations predict well the seasonal contrasts of the measured physical and ecological parameters. Numerical tests indicate that the half saturation constant for grazing by zooplankton and the fish predation rate on zooplankton affect the zooplankton biomass measurably more than that of phytoplankton biomass. This work has implications for the application of this model to predict the climatological biological productivity of Lake Tanganyika.
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