Literature DB >> 27837363

Remote sensing of bacterial response to degrading phytoplankton in the Arabian Sea.

P Priyaja1, R Dwivedi2, S Sini3, M Hatha3, N Saravanane1, M Sudhakar1.   

Abstract

A remote sensing technique has been developed to detect physiological condition of phytoplankton using in situ and moderate imaging spectroradiometer (MODIS)-Aqua data. The recurring massive mixed algal bloom of diatom and Noctiluca scintillans in the Northern Arabian Sea during winter-spring was used as test bed to study formation, growth and degradation of phytoplankton. The ratio of chlorophyll (chl) to particulate organic carbon (POC) was considered as an indicator of phytoplankton physiological condition and used for the approach development. Algal blooms represent the areas of new production, and therefore, knowledge of their degradation is important to the study microbial loop and export carbon flux. Relation of chl/POC ratio with bacterial abundance revealed Gaussian distribution. Bacteria were strongly correlated with POC, and hence, the latter which is available from satellite data could be used as a proxy for remote assessment of bacteria. Thresholds for active and degrading phytoplankton were determined using the ratio computed from the satellite data. The criteria were implemented on MODIS data to generate an image representing distribution of degrading algal bloom. Bacteria abundance data from two validation cruises during dinoflagellate and cyanobacteria bloom confirmed well match up of phytoplankton degradation information from the satellite. Comparison of environmental parameters during decay phase of dinoflagellate (N. scintillans bloom (winter) and Trichodesmium bloom (summer) revealed that degradation after active Trichodesmium bloom was more severe as compared to the N. scintillans. The present study also highlights the prediction capability of phytoplankton degradation using a time series of satellite retrieved chlorophyll/POC images.

Entities:  

Keywords:  Algal bloom; Arabian Sea; Degradation; Remote sensing

Mesh:

Substances:

Year:  2016        PMID: 27837363     DOI: 10.1007/s10661-016-5666-8

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  3 in total

1.  Revisiting the Chesapeake Bay phytoplankton index of biotic integrity.

Authors:  Jacqueline M Johnson; Claire Buchanan
Journal:  Environ Monit Assess       Date:  2013-10-11       Impact factor: 2.513

2.  Species identification of mixed algal bloom in the Northern Arabian Sea using remote sensing techniques.

Authors:  R Dwivedi; M Rafeeq; B R Smitha; K B Padmakumar; Lathika Cicily Thomas; V N Sanjeevan; Prince Prakash; Mini Raman
Journal:  Environ Monit Assess       Date:  2015-02-01       Impact factor: 2.513

3.  Massive outbreaks of Noctiluca scintillans blooms in the Arabian Sea due to spread of hypoxia.

Authors:  Helga do Rosário Gomes; Joaquim I Goes; S G P Matondkar; Edward J Buskey; Subhajit Basu; Sushma Parab; Prasad Thoppil
Journal:  Nat Commun       Date:  2014-09-09       Impact factor: 14.919

  3 in total

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