Microbial Community Composition, Functions, and Activities in the Gulf of Mexico 1 Year after the Deepwater Horizon Accident
Bibliographic record
Abstract
Several studies have assessed the effects of the released oil on microbes, either during or immediately after the Deepwater Horizon accident. However, little is known about the potential longer-term persistent effects on microbial communities and their functions. In this study, one water column station near the wellhead (3.78 km southwest of the wellhead), one water column reference station outside the affected area (37.77 km southeast of the wellhead), and deep-sea sediments near the wellhead (3.66 km southeast of the wellhead) were sampled 1 year after the capping of the well. In order to analyze microbial community composition, function, and activity, we used metagenomics, metatranscriptomics, and mineralization assays. Mineralization of hexadecane was significantly higher at the wellhead station at a depth of ∼1,200 m than at the reference station. Community composition based on taxonomical or functional data showed that the samples taken at a depth of ∼1,200 m were significantly more dissimilar between the stations than at other depths (surface, 100 m, 750 m, and >1,500 m). Both Bacteria and Archaea showed reduced activity at depths of ∼1,200 m when the wellhead station was compared to the reference station, and their activity was significantly higher in surficial sediments than in 10-cm sediments. Surficial sediments also harbored significantly different active genera than did 5- and 10-cm sediments. For the remaining microbial parameters assessed, no significant differences could be observed between the wellhead and reference stations and between surface and 5- to 10-cm-deep sediments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".