Seasonal assemblages and short-lived blooms in coastal north-west Atlantic Ocean bacterioplankton

Heba El-Swais, Katherine A. Dunn, Joseph P. Bielawski, William K.W. Li, David A. Walsh

Résultat de recherche: Articleexamen par les pairs

41 Citations (Scopus)

Résumé

Temperate oceans are inhabited by diverse and temporally dynamic bacterioplankton communities. However, the role of the environment, resources and phytoplankton dynamics in shaping marine bacterioplankton communities at different time scales remains poorly constrained. Here, we combined time series observations (time scales of weeks to years) with molecular analysis of formalin-fixed samples from a coastal inlet of the north-west Atlantic Ocean to show that a combination of temperature, nitrate, small phytoplankton and Synechococcus abundances are best predictors for annual bacterioplankton community variability, explaining 38% of the variation. Using Bayesian mixed modelling, we identified assemblages of co-occurring bacteria associated with different seasonal periods, including the spring bloom (e.g. Polaribacter, Ulvibacter, Alteromonadales and ARCTIC96B-16) and the autumn bloom (e.g. OM42, OM25, OM38 and Arctic96A-1 clades of Alphaproteobacteria, and SAR86, OM60 and SAR92 clades of Gammaproteobacteria). Community variability over spring bloom development was best explained by silicate (32%) – an indication of rapid succession of bacterial taxa in response to diatom biomass – while nanophytoplankton as well as picophytoplankton abundance explained community variability (16–27%) over the transition into and out of the autumn bloom. Moreover, the seasonal structure was punctuated with short-lived blooms of rare bacteria including the KSA-1 clade of Sphingobacteria related to aromatic hydrocarbon-degrading bacteria.

Langue d'origineEnglish
Pages (de-à)3642-3661
Nombre de pages20
JournalEnvironmental Microbiology
Volume17
Numéro de publication10
DOI
Statut de publicationPublished - oct. 1 2015

Note bibliographique

Funding Information:
We would like to acknowledge Kevin Pauley and Jeff Anning for logistical support in collecting samples from Bedford Basin. We thank Joseph R. Mingrone for helpful discussions about the computational challenges posed by our analysis,and for his direct assistance with the computational resources. This work was supported by National Sciences and Engineering Researh Council of Canada (DG402214-2011 and DG298294-2009), Canada Research Chairs Program (950-221184) and Canadian Institutes of Health Research (CMF-108026) research grants and the Bedford Basin Monitoring Program of Fisheries and Oceans Canada, the Atlantic Computational Excellence Network (ACEnet) and the Tula Foundation. The authors have no conflict of interest.

Funding Information:
We would like to acknowledge Kevin Pauley and Jeff Anning for logistical support in collecting samples from Bedford Basin. We thank Joseph R. Mingrone for helpful discussions about the computational challenges posed by our analysis,and for his direct assistance with the computational resources. This work was supported by National Sciences and Engineering Researh Council of Canada (DG402214‐2011 and DG298294‐2009), Canada Research Chairs Program (950‐221184) and Canadian Institutes of Health Research (CMF‐108026) research grants and the Bedford Basin Monitoring Program of Fisheries and Oceans Canada, the Atlantic Computational Excellence Network (ACEnet) and the Tula Foundation. The authors have no conflict of interest.

Publisher Copyright:
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd

ASJC Scopus Subject Areas

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics

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