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dc.contributor.authorMylius SD
dc.date.accessioned2012-12-12T18:18:28Z
dc.date.available2012-12-12T18:18:28Z
dc.date.issued1992-01-31
dc.identifier714201002
dc.identifier.urihttp://hdl.handle.net/10029/259207
dc.description.abstractAbstract niet beschikbaar
dc.description.abstractA simulation model was used to analyse quantitatively the carbon and silicate metabolism of the phytoplankton population in the lower reaches of the river Rhine. Field measurements were carried out five times in 1988, by sampling a body of water during its transport downriver through the Netherlands. Parameters of the model were chosen by interpolation of these data. The potential photosynthetic productivity was estimated from laboratory measurements of the carbon fixation in the samples at saturating light conditions. The actual productivity was calculated by incorporating the varying solar illumination, the extinction coefficient of the water and the river depth in a 'plugflow' model. It was also assumed that the productivity of the diatom-dominated phytoplankton and the silicate uptake as relative to carbon fixation were limited by low silicate concentrations. On the basis of the productivity, the silicate uptake of the diatoms and silicate regeneration in the river bottom simulations of the dissolved silicate concentration were made and found to match with the observed silicate dynamics, thus corroborating the calculated productivity. For a further verification of the model, and as a first step in the construction of a foodchain model for the river Rhine, the phytoplankton concentration was simulated. Loss factors such as respiration, sedimentation and grazing were specified analogous to published models for phytoplankton dynamics. After calibration, using the assumed grazer densities as tuning parameters, these simulations matched well with the observations in spring. In summer situations however, an overestimation of the productivity and/or an underestimation of the loss factors seemed to occur.
dc.description.sponsorshipDGM/DWB-W
dc.format.extent70 p
dc.language.isonl
dc.relation.ispartofRIVM Rapport 714201002
dc.relation.urlhttp://www.rivm.nl/bibliotheek/rapporten/714201002.html
dc.subject14nl
dc.subject92-1nl
dc.subjectrijnnl
dc.subjectmodelnl
dc.subjectfytoplanktonnl
dc.subjectproduktienl
dc.subjectsilikaatnl
dc.subjectriver rhine; modelnl
dc.subjectphytoplanktonnl
dc.subjectproductionnl
dc.subjectsilicatenl
dc.titleEen model voor de produktie van fytoplankton in de Nederlandse Rijntakken: interactie met de silicium cyclusnl
dc.title.alternativeA model for the production of phytoplankton in the Dutch reaches of the river Rhine: interactions with silicate cycleen
dc.typeReport
dc.date.updated2012-12-12T18:18:29Z
html.description.abstractAbstract niet beschikbaar
html.description.abstractA simulation model was used to analyse quantitatively the carbon and silicate metabolism of the phytoplankton population in the lower reaches of the river Rhine. Field measurements were carried out five times in 1988, by sampling a body of water during its transport downriver through the Netherlands. Parameters of the model were chosen by interpolation of these data. The potential photosynthetic productivity was estimated from laboratory measurements of the carbon fixation in the samples at saturating light conditions. The actual productivity was calculated by incorporating the varying solar illumination, the extinction coefficient of the water and the river depth in a 'plugflow' model. It was also assumed that the productivity of the diatom-dominated phytoplankton and the silicate uptake as relative to carbon fixation were limited by low silicate concentrations. On the basis of the productivity, the silicate uptake of the diatoms and silicate regeneration in the river bottom simulations of the dissolved silicate concentration were made and found to match with the observed silicate dynamics, thus corroborating the calculated productivity. For a further verification of the model, and as a first step in the construction of a foodchain model for the river Rhine, the phytoplankton concentration was simulated. Loss factors such as respiration, sedimentation and grazing were specified analogous to published models for phytoplankton dynamics. After calibration, using the assumed grazer densities as tuning parameters, these simulations matched well with the observations in spring. In summer situations however, an overestimation of the productivity and/or an underestimation of the loss factors seemed to occur.


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