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| Titel |
Understanding controls of diel patterns of biological CO2 fixation in the North Atlantic Ocean |
| VerfasserIn |
Helmuth Thomas, Susanne E. Craig, Blair W. Greenan, William Burt, Gerhard J. Herndl, Simon Higginson, Lesley Salt, Elizabeth H. Shadwick, Jorge Urrego-Blanco |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250076102
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| Zusammenfassung |
| Much of the variability in the surface ocean's carbon cycle can be attributed to the availability of
sunlight, through processes such as surface heat flux and photosynthesis, which regulate carbon flux
over a wide range of time scales. The critical processes occurring on timescales of a day or less,
however, have undergone few investigations, and most of these have been limited time spans of several
days to months. Optical methods have helped to infer short-term biological variability, but
corresponding investigations of the oceanic CO2 system are lacking. We employ high-frequency CO2
and optical observations covering the full seasonal cycle on the Scotian Shelf, Northwestern Atlantic
Ocean, in order to unravel diel periodicity of the surface ocean carbon cycle and its effects on annual
budgets. Significant diel periodicity ion the surface CO2 system occurs only if the water column is
sufficiently stable as observed during seasonal warming. During that time biological CO2 drawdown, or
net community production (NCP), are delayed for several hours relative to the onset of
photosynthetically available radiation (PAR), due to diel cycles in Chlorophyll a concentration and to
grazing. In summer, NCP decreases by more than 90%, coinciding with the seasonal minimum of the
mixed layer depth and resulting in the disappearance of the diel CO2 periodicity in the surface waters.
Ongoing work focuses on the transfer of these patterns to the individual -ideally remotely detectable-
biological species, responsible for the CO2 fixation at the seasonal scale in order to predict vulnerability
of the system due to climate change. |
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