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Enhanced crude oil degradation observed in sea ice following bioaugmentation with arctic bacteria

2024· article· en· W4405942084 on OpenAlexafffundabout
Diana Saltymakova, Durell S. Desmond, Alastair F. Smith, María A. Bautista, Eric S. Collins, Katarzyna Polcwiartek, Nolan Snyder, Teresinha Wolfe, Casey R. J. Hubert, Dustin Isleifson, Gary A. Stern

Bibliographic record

VenueMarine Environmental Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of CalgaryUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationUniversity of ManitobaGenome Canada
KeywordsBioaugmentationBacteriaEnvironmental scienceArcticDegradation (telecommunications)Crude oilChemistryEnvironmental chemistryBiologyEcologyBioremediationGeologyPetroleum engineering

Abstract

fetched live from OpenAlex

Petroleum-derived contamination is a growing hazard for the Arctic Ocean and northern marine transportation corridors. In northern settings where the accessibility to oil spills can be limited, natural attenuation is the most promising remediation process. The goal of the presented research is to evaluate the impact of biodegradation on crude oil inside sea ice. To this end, a bioremediation experiment was conducted at the Sea-ice Environmental Research Facility, University of Manitoba. The experiment utilized two mesocosm tanks (Augmented and Native) filled with nutrient-enriched artificial seawater (i.e., biostimulation). The water in the Augmented tank also contained oil-acclimated bacteria enriched from Arctic surface seawater from Cambridge Bay, Canada (i.e., bioaugmentation). The Native tank was not inoculated, but both tanks contained a bacterial community originating with the artificial seawater preparation. Crude oil was added under the naturally formed ice cover within each tank, creating areas that contained different oil concentrations. The Augmented tank contained 22 distinct bacterial genera compared to the Native tank, presumably due to the inoculation. The abundance of distinct bacterial genera was maximal in the water column and in low-contaminated ice core samples (<0.21 g oil/L). In these ice cores, bioaugmentation affected the concentration of low-molecular-weight aliphatic compounds (<C 18 ) and naphthalenes (<C 5 ). We also observed a 1% loss per day of n-nonadecane, n-docosane, methylphenanthrene, and tetramethylnaphthalene in the Augmented tank, which we attribute to bioaugmentation by the Arctic bacterial enrichment. In contrast, losses of these same compounds plateaued after day 15 in the Native tank. • Oil-in-sea ice mesocosm experiments were conducted in parallel in winter conditions. • Over 90% of C11 hydrocarbons were lost from both tanks over 52 days. • One tank augmented with Arctic bacteria led to a 24% greater loss of oil components. • The augmented tank contained known oil-degraders like Alcanivorax and Idiomarina . • Hydrocarbon losses were significantly correlated with Gammaproteobacteria proportion.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations5
Published2024
Admission routes3
Has abstractyes

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