The effects of diluted bitumen, the shoreline washing agent Corexit EC9580A, and bio-stimulation on the lower food web of a boreal lake
Bibliographic record
Abstract
Small scale oil spills and secondary clean up methods were implemented in shoreline enclosures within the littoral zone of a boreal lake to examine impacts on lower trophic organism (periphyton, phytoplankton and zooplankton) communities. Treatment enclosures received 1.5 L (1300 g) of weathered diluted bitumen on June 21st, 2019, followed four days later by primary recovery (i.e. freshwater flushing and absorbent recovery of floating oil) and then either the shoreline washing agent (SWA) Corexit EC9580A or enhanced monitored natural recovery (eMNR) with a slow-release nutrient fertilizer. Indicators of water quality and biota were tracked for 95 days, until September 24th, 2019. Maximum polycyclic aromatic compound (PAC) concentrations in both SWA and eMNR treatments reached 7.3 – 9.4 mg m −3 . Phytoplankton appeared resilient to direct toxic effects of oil and these treatments and no significant effects on photosystem II (F v /F m ) or community structure were detected. Phytoplankton biomass increased in both the SWA (c. +130 %) and eMNR (c. +60 %) treatments during the first 33 days after oil additions, relative to the reference treatment, which did not receive oil, SWA, or eMNR. DNA metabarcoding and microscopy revealed that the phytoplankton community structure was dominated by chrysophytes and dinoflagellates with a greater similarity between eMNR and reference treatments relative to the SWA treatment. While no difference in periphyton biomass was detected between the eMNR and reference treatments, within the SWA treatment periphyton biomass was c. −77 % lower than within the reference for the first 48 days of the experiment. No statistically significant differences in zooplankton biomass were detected between the reference and either the eMNR or SWA treatments, but values within the SWA treatment dropped to < 4 % of values within the reference treatment on day 11 of the experiment, before rebounding by Day 33 of the experiment, suggesting reduced grazing pressure on phytoplankton. While our results revealed no acute toxic effects to the phytoplankton, the experimental oil spills and the use of shoreline cleaners within freshwaters resulted in complex changes in food web structure including increases in phytoplankton biomass and declines in both periphyton and zooplankton biomass.
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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 | 0.000 | 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) | 0.001 | 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".