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Titel |
Effect of temperature and light intensity on diatoms growth rate: impact on biogeochemical cycles |
VerfasserIn |
Sophie Chollet, Erik Buitenhuis, Corinne Le Quéré |
Konferenz |
EGU General Assembly 2011
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 13 (2011) |
Datensatznummer |
250057274
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Zusammenfassung |
Understanding the effects of climate change on marine ecosystems is one of the biggest
current issues for ecologists. Modelling plankton abundance and its diversity, coupled with
physical processes and environmental conditions is an important tool to predict the
effect of climate change on the planktonic communities and on biogeochemical
cycles.
Our model includes several plankton functional types (PFTs), including diatoms which
play a major role and dominate the export of carbon. Phytoplankton distribution and
abundance are closely linked with environmental conditions such as temperature, irradiance
and nutrients concentration. To improve the model, we tested first the dependence of diatoms
growth rate to the temperature. Literature suggests that the increase of phytoplankton growth
rate with the temperature is either linear or exponential. A database of diatoms maximum
growth rates as a function of temperature (500 data, representing 63 species) was
compiled from the published literature. Linear, exponential and optimal functions were
fitted to the data. Statistical analyses show the exponential relation best fits to the
data.
Then we improved the relation of diatoms growth rate with the light intensity.
Our photosynthesis model is based on three parameters: the initial slope of the
Photosynthesis versus Irradiance (PI) curve, the maximum rate of photosynthesis and the
Chlorophyll: Carbon ratio. In an attempt to best represent the diatoms photosynthesis,
laboratory experiments were carried out on different species (2 polar species, 2 from
temperate waters and 2 from warm waters). Sub-cultures of each of them were grown at
different light intensities. Oxygen production was measured with an Oxygraph
(Hansatech) to build PI curves. Parameters extracted from those experiments were
implemented into the model. Comparison of the model outcomes using different growth
parameters shows the importance of experimentally validating the model parameters. |
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