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Biogeosciences An interactive open-access journal of the European Geosciences Union
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
14 Jul 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).
Delineation of marine ecosystem zones in the northern Arabian Sea using an objective method
Saleem Shalin1, Annette Samuelsen2, Anton Korosov2, Nandini Menon1, Björn C. Backeberg2,3,4, and Lasse H. Pettersson2 1Nansen Environmental Research Centre (India), Kochi, India
2Nansen Environmental and Remote Sensing Center, Bergen, Norway
3Coastal Systems Research Group, Natural Resources and the Environment, Council for Scientific and Industrial Research, Stellenbosch, South Africa
4Nansen-Tutu Centre for Marine Environmental Research, Department of Oceanography, University of Cape Town, South Africa
Abstract. The spatial and temporal variability of marine autotrophic abundance, expressed as chlorophyll concentration, is monitored from space and used to delineate the surface signature of marine ecosystem zones with distinct optical characteristics. An objective zoning method is presented and applied to satellite-derived Chlorophyll a (Chl-a) data from the northern Arabian Sea (50°–75° E and 15°–30° N) during the winter months (November–March). Principal Component Analysis (PCA) and Cluster Analysis (CA) were used to statistically delineate the Chl-a into zones with similar surface distribution patterns and temporal variability. The PCA identifies principal components of variability and the CA splits these into zones based on similar characteristics. Based on the temporal variability of Chl-a pattern within the study area, the statistical clustering revealed six distinct ecological zones. The obtained zones are related to the Longhurst provinces to evaluate how these compared to established ecological provinces. The Chl-a variability within each zone was then compared with the variability of oceanic and atmospheric properties viz. mixed-layer depth (MLD), wind speed, sea-surface temperature (SST), Photosynthetically Active Radiation (PAR), nitrate and Dust Optical Thickness (DOT) as an indication of atmospheric input of iron to the ocean. The analysis showed that in all zones, peak values of Chl-a coincided with low SST and deep MLD. Rate of decrease in SST and deepening of MLD are observed to trigger the intensity of the algae bloom events in the first four zones. Lagged cross-correlation analysis shows that peak Chl-a follows peak MLD and SST minima. The MLD time-lag is shorter than the SST lag by eight days, indicating that the cool surface conditions might have enhanced mixing, leading to increased primary production in the study area.

An analysis of monthly climatological nitrate values showed increased concentrations associated with the deepening of the mixed-layer. The input of iron seems to be important in both the open ocean and coastal areas of the northern and north-western part of the Northern Arabian Sea, where the seasonal variability of the Chl-a pattern closely follows the variability of iron deposition.

Citation: Shalin, S., Samuelsen, A., Korosov, A., Menon, N., Backeberg, B. C., and Pettersson, L. H.: Delineation of marine ecosystem zones in the northern Arabian Sea using an objective method, Biogeosciences Discuss.,, in review, 2017.
Saleem Shalin et al.
Saleem Shalin et al.
Saleem Shalin et al.


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Short summary
This work objectively classified the northern Arabian Sea into six ecological zones based on surface Chl-a distribution patterns during winter. Distinct Chl-a characteristics within each delineated zone shows that this classification method is a good way of separating regions with different phytoplankton dynamics during winter. The study provides improved understanding of how environmental factors control the spatio-temporal variability of the marine Chl-a concentration in the area during winter
This work objectively classified the northern Arabian Sea into six ecological zones based on...