Effect of nutrient enrichments on the bacterial assemblage of Antarctic soils contaminated by diesel or crude oil
Why this work is in the frame
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Bibliographic record
Abstract
There is an urgent need to develop new technologies to address the problem of soil remediation in high-latitude regions. A field study was initiated in January 1997 in two contaminated soils in Terre Adélie (Antarctica) with the objective of determining the long-term effectiveness of two bioremediation agents on total and hydrocarbon-degrading microbial assemblages under severe Antarctic conditions. This study was conducted in two steps, from January to July 1997 and from February to November 1999 in the Géologie Archipelago (Terre Adélie, 66°40′S, 140°01′E). Changes in bacterial communities were monitored in situ after crude oil or diesel addition in a series of 600 cm 2 soil sectors (20×30 cm). Four contaminated sectors were used for each experiment: diesel oil (10 ml), diesel oil (10 ml) + fertilizer (1 ml), Arabian light crude oil (10 ml), and crude oil (10 ml) + fertilizer (1 ml). Two different bioremediation agents were used: a slow release fertilizer Inipol EAP-22 (Elf Atochem) in 1997 and a fish compost in 1999. Plots were sampled on a regular basis during a three-year period. All samples were analysed for total, saprophytic psychrophilic, and hydrocarbon-utilising bacteria. A one order of magnitude increase of saprophytic and hydrocarbon-utilising micro-organisms occurred during the first month of the experiment in most of the contaminated enclosures, but no clear differences appeared between fertilized and unfertilized plots. Diesel-oil contamination induced a significant increase of all bacterial parameters in all contaminated soils. Crude-oil contamination had no clear effects on microbial assemblages. It was clear that the microbial response could be rapid and efficient in spite of the severe weather conditions. However, microbial growth was not clearly improved in the presence of bioremediation agents.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it