Seasonal Synechococcus and Thaumarchaeal population dynamics examined with high resolution with remote in situ instrumentation

Robidart, Julie C. ORCID: https://orcid.org/0000-0001-9805-3570; Preston, Christina M.; Paerl, Ryan W.; Turk, Kendra A.; Mosier, Annika C.; Francis, Christopher A.; Scholin, Christopher A.; Zehr, Jonathan P.. 2012 Seasonal Synechococcus and Thaumarchaeal population dynamics examined with high resolution with remote in situ instrumentation. The ISME Journal, 6 (3). 513-523. https://doi.org/10.1038/ismej.2011.127

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Official URL: http://dx.doi.org/10.1038/ismej.2011.127

Abstract/Summary

Monterey Bay, CA is an Eastern boundary upwelling system that is nitrogen limited much of the year. In order to resolve population dynamics of microorganisms important for nutrient cycling in this region, we deployed the Environmental Sample Processor with quantitative PCR assays targeting both ribosomal RNA genes and functional genes for subclades of cyanobacteria (Synechococcus) and ammonia-oxidizing Archaea (Thaumarchaeota) populations. Results showed a strong correlation between Thaumarchaea abundances and nitrate during the spring upwelling but not the fall sampling period. In relatively stratified fall waters, the Thaumarchaeota community reached higher numbers than in the spring, and an unexpected positive correlation with chlorophyll concentration was observed. Further, we detected drops in Synechococcus abundance that occurred on short (that is, daily) time scales. Upwelling intensity and blooms of eukaryotic phytoplankton strongly influenced Synechococcus distributions in the spring and fall, revealing what appear to be the environmental limitations of Synechococcus populations in this region. Each of these findings has implications for Monterey Bay biogeochemistry. High-resolution sampling provides a better-resolved framework within which to observe changes in the plankton community. We conclude that controls on these ecosystems change on smaller scales than are routinely assessed, and that more predictable trends will be uncovered if they are evaluated within seasonal (monthly), rather than on annual or interannual scales.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1038/ismej.2011.127
ISSN:	1751-7362
Date made live:	02 Feb 2015 17:09 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/509563

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1038/ismej.2011.127

ISSN:

1751-7362

Date made live:

02 Feb 2015 17:09 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/509563