Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula

Bacterial community structure can be combined with observations of ecophysiological data to build predictive models of microbial ecosystem function. These models are useful for understanding how function might change in response to a changing environment. Here we use five spring–summer seasons of ba...

Full description

Bibliographic Details
Published in:The ISME Journal
Main Authors: Bowman, Jeff S, Amaral-Zettler, Linda A, J Rich, Jeremy, M Luria, Catherine, Ducklow, Hugh W
Format: Text
Language:English
Published: Nature Publishing Group 2017
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5437343/
http://www.ncbi.nlm.nih.gov/pubmed/28106879
https://doi.org/10.1038/ismej.2016.204
id ftpubmed:oai:pubmedcentral.nih.gov:5437343
record_format openpolar
spelling ftpubmed:oai:pubmedcentral.nih.gov:5437343 2023-05-15T13:46:05+02:00 Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula Bowman, Jeff S Amaral-Zettler, Linda A J Rich, Jeremy M Luria, Catherine Ducklow, Hugh W 2017-06 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5437343/ http://www.ncbi.nlm.nih.gov/pubmed/28106879 https://doi.org/10.1038/ismej.2016.204 en eng Nature Publishing Group http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5437343/ http://www.ncbi.nlm.nih.gov/pubmed/28106879 http://dx.doi.org/10.1038/ismej.2016.204 Copyright © 2017 International Society for Microbial Ecology Original Article Text 2017 ftpubmed https://doi.org/10.1038/ismej.2016.204 2018-06-03T00:08:38Z Bacterial community structure can be combined with observations of ecophysiological data to build predictive models of microbial ecosystem function. These models are useful for understanding how function might change in response to a changing environment. Here we use five spring–summer seasons of bacterial community structure and flow cytometry data from a productive coastal site along the western Antarctic Peninsula to construct models of bacterial production (BP), an ecosystem function that heterotrophic bacteria provide. Through a novel application of emergent self-organizing maps we identified eight recurrent modes in the structure of the bacterial community. A model that combined bacterial abundance, mode and the fraction of cells belonging to the high nucleic acid population (fHNA; R2=0.730, P<0.001) best described BP. Abrupt transitions between modes during the 2013–2014 spring–summer season corresponded to rapid shifts in fHNA. We conclude that parameterizing community structure data via segmentation can yield useful insights into microbial ecosystem function and ecosystem processes. Text Antarc* Antarctic Antarctic Peninsula PubMed Central (PMC) Antarctic Antarctic Peninsula The ISME Journal 11 6 1460 1471
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Original Article
spellingShingle Original Article
Bowman, Jeff S
Amaral-Zettler, Linda A
J Rich, Jeremy
M Luria, Catherine
Ducklow, Hugh W
Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula
topic_facet Original Article
description Bacterial community structure can be combined with observations of ecophysiological data to build predictive models of microbial ecosystem function. These models are useful for understanding how function might change in response to a changing environment. Here we use five spring–summer seasons of bacterial community structure and flow cytometry data from a productive coastal site along the western Antarctic Peninsula to construct models of bacterial production (BP), an ecosystem function that heterotrophic bacteria provide. Through a novel application of emergent self-organizing maps we identified eight recurrent modes in the structure of the bacterial community. A model that combined bacterial abundance, mode and the fraction of cells belonging to the high nucleic acid population (fHNA; R2=0.730, P<0.001) best described BP. Abrupt transitions between modes during the 2013–2014 spring–summer season corresponded to rapid shifts in fHNA. We conclude that parameterizing community structure data via segmentation can yield useful insights into microbial ecosystem function and ecosystem processes.
format Text
author Bowman, Jeff S
Amaral-Zettler, Linda A
J Rich, Jeremy
M Luria, Catherine
Ducklow, Hugh W
author_facet Bowman, Jeff S
Amaral-Zettler, Linda A
J Rich, Jeremy
M Luria, Catherine
Ducklow, Hugh W
author_sort Bowman, Jeff S
title Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula
title_short Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula
title_full Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula
title_fullStr Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula
title_full_unstemmed Bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western Antarctic Peninsula
title_sort bacterial community segmentation facilitates the prediction of ecosystem function along the coast of the western antarctic peninsula
publisher Nature Publishing Group
publishDate 2017
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5437343/
http://www.ncbi.nlm.nih.gov/pubmed/28106879
https://doi.org/10.1038/ismej.2016.204
geographic Antarctic
Antarctic Peninsula
geographic_facet Antarctic
Antarctic Peninsula
genre Antarc*
Antarctic
Antarctic Peninsula
genre_facet Antarc*
Antarctic
Antarctic Peninsula
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5437343/
http://www.ncbi.nlm.nih.gov/pubmed/28106879
http://dx.doi.org/10.1038/ismej.2016.204
op_rights Copyright © 2017 International Society for Microbial Ecology
op_doi https://doi.org/10.1038/ismej.2016.204
container_title The ISME Journal
container_volume 11
container_issue 6
container_start_page 1460
op_container_end_page 1471
_version_ 1766236557347389440