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On the issue of limiting nutrient and predictions of cyanobacteria in aquatic systems
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. (Miljöanalys)
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. (Miljöanalys)
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. (Miljöanalys)
2007 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 379, no 1, p. 89-108Article in journal (Refereed) Published
Abstract [en]

This study aims at bridging the gap between freshwater and marine eutrophication studies by presenting (1) a cross-system analysis of the relationship between chlorophyll and the total nitrogen (TN) to total phosphorus (TP) ratio (2) a general model to predict concentrations of cyanobacteria from data on TP, the TN/TP ratio, salinity and temperature, and (3) a general trophic level classification for aquatic systems based on chlorophyll classes (for oligo-, meso-, eu- and hypertrophic systems). The data compiled in this study concerns more than 500 lakes and coastal areas covering a very wide domain in terms of nutrient concentrations and salinity. There was no simple relationship between the TN/TP ratio and empirical chlorophyll concentrations or concentrations of cyanobacteria. Variations in TP rather than TN generally seem to be more important to predict variations among systems in chlorophyll-a and cyanobacteria. Different “bioavailable” forms of the nutrients (DIN, DIP, phosphate, nitrate, etc.) have been shown to have very high coefficients of variation (CV), which means that many samples are needed to obtain reliable empirical data which are necessary in models aiming for high predictive power and practical usefulness.

Place, publisher, year, edition, pages
2007. Vol. 379, no 1, p. 89-108
Keyword [en]
Chlorophyll, Cyanobacteria, Phosphorus, Nitrogen, Salinity, Temperature, Lakes, Marine systems, Empirical data, Models
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:uu:diva-10970DOI: 10.1016/j.scitotenv.2007.03.009ISI: 000247521700007PubMedID: 17448525OAI: oai:DiVA.org:uu-10970DiVA, id: diva2:38738
Available from: 2011-09-29 Created: 2007-05-08 Last updated: 2017-12-11Bibliographically approved

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