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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bgd-10-815-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bgd-10-815-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 15 Jan 2013

Research article | 15 Jan 2013

Review status
This discussion paper is a preprint. It has been under review for the journal Biogeosciences (BG). The revised manuscript was not accepted.

Incorporating genomic information and predicting gene expression patterns in a simplified biogeochemical model

P. Wang1, A. B. Burd1, M. A. Moran1, R. R. Hood2, V. J. Coles2, and P. L. Yager1 P. Wang et al.
  • 1Department of Marine Science, University of Georgia, Athens, GA, 30602, USA
  • 2Center for Environmental Science, University of Maryland, Cambridge, MD, 21613, USA

Abstract. We present results from a new marine plankton model that combines selective biogeochemical processes with genetic information. The model allows for phytoplankton to adapt to a changing environment by invoking different utilization pathways for acquisition of nutrients (nitrogen and phosphorus) in response to concentration changes. The simulations use simplified environmental conditions represented by a continuously stirred tank reactor, which is populated by 96 different types of phytoplankton that differ in their physiological characteristics and nutrient uptake/metabolism genes. The results show that the simulated phytoplankton community structure is conceptually consistent with observed regional and global phytoplankton biogeography, the genome content from the dominant types of phytoplankton reflects the imposed environmental constraints, and the transcription of the gene clusters is qualitatively simulated according to the environmental changes. The model shows the feasibility of including genomic knowledge into a biogeochemical model and is suited to understanding and predicting changes in marine microbial community structure and function, and to simulating the biological response to rapid environmental changes.

P. Wang et al.
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
P. Wang et al.
P. Wang et al.
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