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Record W3104594765 · doi:10.1093/femsec/fiaa230

Temporal changes in water temperature and salinity drive the formation of a reversible plastic-specific microbial community

2020· article· en· W3104594765 on OpenAlexfundno aff
Lee J. Pinnell, Jeffrey W. Turner

Bibliographic record

VenueFEMS Microbiology Ecology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
FundersDivision of Computer and Network SystemsNatural Sciences and Engineering Research Council of Canada
KeywordsSalinityBiologyMesocosmTemperature salinity diagramsMicrobial population biologyAbundance (ecology)Relative species abundanceEcologyCommunity structureSubstrate (aquarium)Extreme environmentEcosystemBacteria

Abstract

fetched live from OpenAlex

Plastic is a ubiquitous pollutant in the marine environment. Here, we investigated how temporal changes in environmental factors affect the microbial communities formed on plastic (polyethylene terephthalate; PET) versus a ceramic substrate. In situ mesocosms (N = 90 replicates) were deployed at the sediment-water interface of a coastal lagoon and sampled every 4 weeks for 424 days. Sequencing data (16S rRNA) was parsed based on variation in temperature with the exposure starting in fall 2016 and remaining in situ through the next four seasons (winter, spring, summer and fall 2017). PET biofilms were distinct during the summer when salinity and temperature were highest. In particular, a significant shift in the relative abundance of Ignavibacteriales and Cytophagales was observed during the summer, but PET and ceramic communities were again indistinguishable the following fall. Water temperature, salinity and pH were significant drivers of PET biofilm diversity as well as the relative abundance of plastic-discriminant taxa. This study illustrates the temporal and successional dynamics of PET biofilms and clearly demonstrates that increased water temperature, salinity, pH and exposure length play a role in the formation of a plastic-specific microbial community, but this specificity can be lost with a change in environmental conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.191
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations64
Published2020
Admission routes1
Has abstractyes

Explore more

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