Published in

Springer Nature [academic journals on nature.com], The ISME Journal: Multidisciplinary Journal of Microbial Ecology, 3(6), p. 513-523, 2011

DOI: 10.1038/ismej.2011.127

Links

Tools

Export citation

Search in Google Scholar

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

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

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.