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| Titel |
Bio-optical provinces in the eastern Atlantic Ocean and their biogeographical relevance |
| VerfasserIn |
B. B. Taylor, E. Torrecilla, A. Bernhardt, M. H. Taylor, I. Peeken, R. Röttgers, J. Piera, A. Bracher |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 8, no. 12 ; Nr. 8, no. 12 (2011-12-12), S.3609-3629 |
| Datensatznummer |
250006244
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| Publikation (Nr.) |
 copernicus.org/bg-8-3609-2011.pdf |
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| Zusammenfassung |
| The relationship between phytoplankton assemblages and the associated
optical properties of the water body is important for the further
development of algorithms for large-scale remote sensing of phytoplankton
biomass and the identification of phytoplankton functional types (PFTs),
which are often representative for different biogeochemical export
scenarios. Optical in-situ measurements aid in the identification of
phytoplankton groups with differing pigment compositions and are widely used
to validate remote sensing data. In this study we present results from an
interdisciplinary cruise aboard the RV Polarstern along a north-to-south
transect in the eastern Atlantic Ocean in November 2008. Phytoplankton
community composition was identified using a broad set of in-situ
measurements. Water samples from the surface and the depth of maximum
chlorophyll concentration were analyzed by high performance liquid
chromatography (HPLC), flow cytometry, spectrophotometry and microscopy.
Simultaneously, the above- and underwater light field was measured by a set
of high spectral resolution (hyperspectral) radiometers. An unsupervised
cluster algorithm applied to the measured parameters allowed us to define
bio-optical provinces, which we compared to ecological provinces proposed
elsewhere in the literature. As could be expected, picophytoplankton was
responsible for most of the variability of PFTs in the eastern Atlantic
Ocean. Our bio-optical clusters agreed well with established provinces and
thus can be used to classify areas of similar biogeography. This method has
the potential to become an automated approach where satellite data could be
used to identify shifting boundaries of established ecological provinces or
to track exceptions from the rule to improve our understanding of the
biogeochemical cycles in the ocean. |
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