Determination of physical processes influencing Chl a distribution using remotely sensed images
In management of the Japanese scallop Mizuhopecten yessoensis culture, it is important to understand the phytoplankton bloom development in the coastal region of the Okhotsk Sea. Variations in food available to this benthic bivalve are a primary environmental factor affecting growth in nature. This...
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Published in: | Pakistan journal of biological sciences Vol. 14; no. 2; pp. 82 - 90 |
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Pakistan
15-01-2011
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Abstract | In management of the Japanese scallop Mizuhopecten yessoensis culture, it is important to understand the phytoplankton bloom development in the coastal region of the Okhotsk Sea. Variations in food available to this benthic bivalve are a primary environmental factor affecting growth in nature. This paper determined the seasonal variability of Chlorophyll a (Chl a) at the scallop farming region in the Okhotsk Sea from 1998 to 2004 using satellite imageries. Satellite images were processed using default NASA coefficients and community-standard algorithms as implemented by Sea DAS. Spatial and temporal variation of Chl a was determined by EOF analysis. The Chl a concentration showed high seasonal and interannual variability. Peak of Chl a concentration occurred in spring followed by autumn and summer. This was evident in the Empirical Orthogonal Function (EOF) analysis. The spatial pattern of the first mode of EOF analysis of Chl a revealed intensified Chl a at the shelf and offshore areas in spring and autumn (51.8% of variance). The second mode explained 14.2% of the variance indicating enhancement of spring (April-May) Chl a pattern in the frontal area along the coast. Meanwhile, the third mode captured 9.0% of the variability demonstrating high Chl a extending seaward from the shelf area during late autumn. These seasonal variability of Chl a resulted from the variability in occurrences of physical processes associated with retreat of sea ice in spring, advection of Soya Warm Current in summer and intrusion of East Sakhalin Current in autumn. |
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AbstractList | In management of the Japanese scallop Mizuhopecten yessoensis culture, it is important to understand the phytoplankton bloom development in the coastal region of the Okhotsk Sea. Variations in food available to this benthic bivalve are a primary environmental factor affecting growth in nature. This paper determined the seasonal variability of Chlorophyll a (Chl a) at the scallop farming region in the Okhotsk Sea from 1998 to 2004 using satellite imageries. Satellite images were processed using default NASA coefficients and community-standard algorithms as implemented by Sea DAS. Spatial and temporal variation of Chl a was determined by EOF analysis. The Chl a concentration showed high seasonal and interannual variability. Peak of Chl a concentration occurred in spring followed by autumn and summer. This was evident in the Empirical Orthogonal Function (EOF) analysis. The spatial pattern of the first mode of EOF analysis of Chl a revealed intensified Chl a at the shelf and offshore areas in spring and autumn (51.8% of variance). The second mode explained 14.2% of the variance indicating enhancement of spring (April-May) Chl a pattern in the frontal area along the coast. Meanwhile, the third mode captured 9.0% of the variability demonstrating high Chl a extending seaward from the shelf area during late autumn. These seasonal variability of Chl a resulted from the variability in occurrences of physical processes associated with retreat of sea ice in spring, advection of Soya Warm Current in summer and intrusion of East Sakhalin Current in autumn. |
Author | Mustapha, A M Lihan, T Saitoh, S |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/21916257$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Algorithms Animals Chlorophyll - metabolism Chlorophyll A Climate Environmental Monitoring Geography Japan Models, Statistical Oceans and Seas Pectinidae Seasons Telemetry Temperature Time Factors |
Title | Determination of physical processes influencing Chl a distribution using remotely sensed images |
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