Evidence map›Paper›PMID 25988950›Full record

ReviewGlobal change biology2016

Bridging the gap between omics and earth system science to better understand how environmental change impacts marine microbes.

Thomas Mock, Stuart J Daines, Richard Geider, Sinead Collins, Metodi Metodiev, Andrew J Millar, Vincent Moulton, Timothy M Lenton

Abstract readReview
In one paragraph

Review in Global change biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Linking regional shifts in microbial genome adaptation with surface ocean biogeochemistry.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Depth perception: the need to report ocean biogeochemical rates as functions of temperature, not depth.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Thomas MockSchool of Environmental Sciences, University of East Anglia, Norwich Research Park, NR4 7TJ, Norwich, UK.
Stuart J DainesCollege of Life and Environmental Sciences, University of Exeter, EX4 4QE, Exeter, UK.
Richard GeiderSchool of Biological Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK.
Sinead CollinsAshworth Laboratories, Edinburgh University, EH9 3JF, Edinburgh, UK.
Metodi MetodievSchool of Biological Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK.
Andrew J MillarSynthSys and School of Biological Sciences, Edinburgh University, EH9 3BF, Edinburgh, UK.
Vincent MoultonSchool of Computing Sciences, University of East Anglia, Norwich Research Park, NR4 7TJ, Norwich, UK.
Timothy M LentonCollege of Life and Environmental Sciences, University of Exeter, EX4 4QE, Exeter, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/J009423/1Biotechnology and Biological Sciences Research Council J009423
6 · The paper itself

Abstract

The advent of genomic-, transcriptomic- and proteomic-based approaches has revolutionized our ability to describe marine microbial communities, including biogeography, metabolic potential and diversity, mechanisms of adaptation, and phylogeny and evolutionary history. New interdisciplinary approaches are needed to move from this descriptive level to improved quantitative, process-level understanding of the roles of marine microbes in biogeochemical cycles and of the impact of environmental change on the marine microbial ecosystem. Linking studies at levels from the genome to the organism, to ecological strategies and organism and ecosystem response, requires new modelling approaches. Key to this will be a fundamental shift in modelling scale that represents micro-organisms from the level of their macromolecular components. This will enable contact with omics data sets and allow acclimation and adaptive response at the phenotype level (i.e. traits) to be simulated as a combination of fitness maximization and evolutionary constraints. This way forward will build on ecological approaches that identify key organism traits and systems biology approaches that integrate traditional physiological measurements with new insights from omics. It will rely on developing an improved understanding of ecophysiology to understand quantitatively environmental controls on microbial growth strategies. It will also incorporate results from experimental evolution studies in the representation of adaptation. The resulting ecosystem-level models can then evaluate our level of understanding of controls on ecosystem structure and function, highlight major gaps in understanding and help prioritize areas for future research programs. Ultimately, this grand synthesis should improve predictive capability of the ecosystem response to multiple environmental drivers.

Indexed as

EcosystemGenomeMicrobiological PhenomenaAdaptation, PhysiologicalAquatic OrganismsBiological EvolutionModels, BiologicalTranscriptomeevolutiongenomicsmicrobesmodellingocean

Identifiers

PMID25988950
PMCPMC4949645

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.