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High resolution time series reveals cohesive but short-lived communities in coastal plankton.


ABSTRACT: Because microbial plankton in the ocean comprise diverse bacteria, algae, and protists that are subject to environmental forcing on multiple spatial and temporal scales, a fundamental open question is to what extent these organisms form ecologically cohesive communities. Here we show that although all taxa undergo large, near daily fluctuations in abundance, microbial plankton are organized into clearly defined communities whose turnover is rapid and sharp. We analyze a time series of 93 consecutive days of coastal plankton using a technique that allows inference of communities as modular units of interacting taxa by determining positive and negative correlations at different temporal frequencies. This approach shows both coordinated population expansions that demarcate community boundaries and high frequency of positive and negative associations among populations within communities. Our analysis thus highlights that the environmental variability of the coastal ocean is mirrored in sharp transitions of defined but ephemeral communities of organisms.

SUBMITTER: Martin-Platero AM 

PROVIDER: S-EPMC5773528 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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High resolution time series reveals cohesive but short-lived communities in coastal plankton.

Martin-Platero Antonio M AM   Cleary Brian B   Kauffman Kathryn K   Preheim Sarah P SP   McGillicuddy Dennis J DJ   Alm Eric J EJ   Polz Martin F MF  

Nature communications 20180118 1


Because microbial plankton in the ocean comprise diverse bacteria, algae, and protists that are subject to environmental forcing on multiple spatial and temporal scales, a fundamental open question is to what extent these organisms form ecologically cohesive communities. Here we show that although all taxa undergo large, near daily fluctuations in abundance, microbial plankton are organized into clearly defined communities whose turnover is rapid and sharp. We analyze a time series of 93 consecu  ...[more]

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