Accessibility navigation


Sequential variations of phytoplankton growth and mortality in an NPZ model: a remote-sensing-based assessment

Roy, S. ORCID: https://orcid.org/0000-0003-2543-924X, Broomhead, D. S., Platt, T., Sathyendranath, S. and Ciavatta, S. (2012) Sequential variations of phytoplankton growth and mortality in an NPZ model: a remote-sensing-based assessment. Journal of Marine Systems, 92. pp. 16-29. ISSN 0924-7963

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Official URL: http://dx.doi.org/10.1016/j.jmarsys.2011.10.001

Abstract/Summary

Radiometric data in the visible domain acquired by satellite remote sensing have proven to be powerful for monitoring the states of the ocean, both physical and biological. With the help of these data it is possible to understand certain variations in biological responses of marine phytoplankton on ecological time scales. Here, we implement a sequential data-assimilation technique to estimate from a conventional nutrient–phytoplankton–zooplankton (NPZ) model the time variations of observed and unobserved variables. In addition, we estimate the time evolution of two biological parameters, namely, the specific growth rate and specific mortality of phytoplankton. Our study demonstrates that: (i) the series of time-varying estimates of specific growth rate obtained by sequential data assimilation improves the fitting of the NPZ model to the satellite-derived time series: the model trajectories are closer to the observations than those obtained by implementing static values of the parameter; (ii) the estimates of unobserved variables, i.e., nutrient and zooplankton, obtained from an NPZ model by implementation of a pre-defined parameter evolution can be different from those obtained on applying the sequences of parameters estimated by assimilation; and (iii) the maximum estimated specific growth rate of phytoplankton in the study area is more sensitive to the sea-surface temperature than would be predicted by temperature-dependent functions reported previously. The overall results of the study are potentially useful for enhancing our understanding of the biological response of phytoplankton in a changing environment.

Item Type:Article
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
Science > School of Archaeology, Geography and Environmental Science > Earth Systems Science
Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
ID Code:33653
Uncontrolled Keywords:Sequential data assimilation; State-parameter estimation; Dual Ensemble Kalman filter; NPZ model; Remote sensing of ocean color; Specific growth of phytoplankton; Phytoplankton mortality; Temperature-dependent phytoplankton growth
Publisher:Elsevier

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation