Dataset Information

Diel size distributions reveal seasonal growth dynamics of a coastal phytoplankter.

ABSTRACT: Phytoplankton account for roughly half of global primary production; it is vital that we understand the processes that control their abundance. A key process is cell division. We have, however, been unable to estimate division rate in natural populations at the appropriate timescale (hours to days) for extended periods of time (months to years). For phytoplankton, the diel change in cell size distribution is related to division rate, which offers an avenue to obtain estimates from in situ observations. We show that a matrix population model, fit to hourly cell size distributions, accurately estimates division rates of both cultured and natural populations of Synechococcus. Application of the model to Synechococcus at the Martha's Vineyard Coastal Observatory provides an unprecedented view that reveals a distinct seasonality in division rates. This information allows us to separate the effects of growth and loss quantitatively over an entire seasonal cycle. We find that division and loss processes are tightly coupled throughout the year. The large seasonal changes in cell abundance are the result of periods of time (weeks to months) when there are small systematic differences that favor either net growth or loss. We also find that temperature plays a critical role in limiting division rate during the annual spring bloom. This approach opens a path to quantify the role of Synechococcus in ecological and biogeochemical processes in natural systems.

SUBMITTER: Hunter-Cevera KR

PROVIDER: S-EPMC4103375 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Diel size distributions reveal seasonal growth dynamics of a coastal phytoplankter.

Hunter-Cevera Kristen R KR Neubert Michael G MG Solow Andrew R AR Olson Robert J RJ Shalapyonok Alexi A Sosik Heidi M HM

Proceedings of the National Academy of Sciences of the United States of America 20140623 27

Phytoplankton account for roughly half of global primary production; it is vital that we understand the processes that control their abundance. A key process is cell division. We have, however, been unable to estimate division rate in natural populations at the appropriate timescale (hours to days) for extended periods of time (months to years). For phytoplankton, the diel change in cell size distribution is related to division rate, which offers an avenue to obtain estimates from in situ observ ...[more]

PMID: 24958866

Similar Datasets

Project description:How microbial communities change over time in response to the environment is poorly understood. Previously a six-year time series of 16S rRNA V6 data from the Western English Channel demonstrated robust seasonal structure within the bacterial community, with diversity negatively correlated with day-length. Here we determine whether metagenomes and metatranscriptomes follow similar patterns. We generated 16S rRNA datasets, metagenomes (1.2 GB) and metatranscriptomes (157 MB) for eight additional time points sampled in 2008, representing three seasons (Winter, Spring, Summer) and including day and night samples. This is the first microbial 'multi-omic' study to combine 16S rRNA amplicon sequencing with metagenomic and metatranscriptomic profiling. Five main conclusions can be drawn from analysis of these data: 1) Archaea follow the same seasonal patterns as Bacteria, but show lower relative diversity; 2) Higher 16S rRNA diversity also reflects a higher diversity of transcripts; 3) Diversity is highest in winter and at night; 4) Community-level changes in 16S-based diversity and metagenomic profiles are better explained by seasonal patterns (with samples closest in time being most similar), while metatranscriptomic profiles are better explained by diel patterns and shifts in particular categories (i.e., functional groups) of genes; 5) Changes in key genes occur among seasons and between day and night (i.e., photosynthesis); but these samples contain large numbers of orphan genes without known homologues and it is these unknown gene sets that appear to contribute most towards defining the differences observed between times. Despite the huge diversity of these microbial communities, there are clear signs of predictable patterns and detectable stability over time. Renewed and intensified efforts are required to reveal fundamental deterministic patterns in the most complex microbial communities. Further, the presence of a substantial proportion of orphan sequences underscores the need to determine the gene products of sequences with currently unknown function.

Dataset Information

Diel size distributions reveal seasonal growth dynamics of a coastal phytoplankter.

Publications

Diel size distributions reveal seasonal growth dynamics of a coastal phytoplankter.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure