Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/74621
Type: Conference item
Title: Simulating the phytoplankton dynamics in a mesotrophic reservoir
Author: Rigosi, A.
Escot, C.
Basanta, A.
Marce, R.
Rueda, F.
Citation: XIV Congreso de la Asociación Ibérica de Limnología, celebrado del 8 al 12 de septiembre de Huelva, 8-12 September 2008 / G. Soria, J. Miguel, P. Marin (eds.)
Publisher: Asociacion Iberica de Limnologia
Issue Date: 2008
ISBN: 9788492161881
Conference Name: Congreso de la Asociación Ibérica de Limnología (14th : 2008 : Huelva, Spain)
Statement of
Responsibility: 
A. Rigosi, C. Escot, A. Basanta, R. Marcé y F.J. Rueda
Abstract: It is now widely accepted that phytoplankton communities in lakes and reservoirs, their functional structure andtheir seasonal variability, are the results of changes experienced in light levels and the availability of nutrients fortheir growth (e.g. Margalef, 1997 or Reynolds, 1997). If we accept Margalef’s Mandala as a valid interpretation ofsuccession in freshwater ecosystems, one necessarily concludes that the understanding of the functional structureof phytoplankton communities and its evolution needs to be grounded on the knowledge of the physical processesof transport and mixing determining turbulence levels and nutrient distribution in the water column. Our goal is todevelop, calibrate and validate a simulation model which can be used to understand the role of physics indetermining phytoplankton growth and succession in a reservoir in Southern Spain (El Gergal, Seville). Our model ofEl Gergal-Seville has been constructed using a one-dimensional generic lake and reservoir ecological/hydraulicmodeling tool (DYRESM-CAEDYM), which simulates the physical, chemical and biological processes occurring inwater bodies. We will show that the model provides accurate predictions of mixing and transport processesoccurring in the water column and determining the seasonal evolution of stratification in the reservoir. We will alsodemonstrate that our model predicts the seasonal evolution of phytoplankton abundance and the functionalstructure of the phytoplankton communities. Our modeling exercises are done within a Bayesian framework whichallows us not only to provide predictions of growth and composition, but also establish the uncertainty of such predictions.
Rights: Copyright status unknown
Appears in Collections:Aurora harvest 4
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