Ecotoxicological Assessment of an In-Lake Remediation Method
Bibliographic record
Abstract
Abstract Eutrophication and contaminated sediments are preoccupying issues in aquatic ecosystems and water resources protection. Saint-Augustin Lake (Quebec, Canada) is affected by both problems (eutrophication and contaminated sediment) and the presence of de-icing salts. According to sustainable management principles, Galvez and collaborators are developing an in-lake remediation method to restore eutrophicated lakes which consists of (a) the precipitation of the phosphorus present in the water column by the addition of alum in association with (b) the deposit of an active capping layer (calcite+sand) to isolate P, Al, and the contaminated sediments. The objective of this study is to assess the ecotoxicological impact of this restoration method for the Saint-Augustin Lake. Two ecotoxicological approaches will be used to assess this impact: (a) single-species bioassays using algal (Pseudokirchneriella subcapitata; growth), duckweed (Lemna minor; growth), daphnid (Daphnia magna; survival and reproduction), amphipod (Hyalella azteca; survival and reproduction), and invertebrate (Chironomus riparius; survival, growth, and emergence); and (b) a 2-L microcosm assay using the same organisms for purpose of comparisons. Alum toxicity, calcite impact, and organisms’ recolonization ability will be studied separately: first in artificial conditions, by using formulated sediments and artificial water and by considering de-icing salts impact, and secondly by using the sediments and overlying water of the Saint-Augustin lake. Preliminary results are available and presented here. No effect was measured for salt (NaCl) toxicity on algae, daphnids, chironomids, and amphipods. Alum inhibited algal growth strongly, had no impact on D. magna mobility and survival, but a clear dose-effect response was observed for daphnid reproduction. The global remediation method had almost the same effect as alum on P. subcapitata but stimulated daphnid reproduction at 10 mg/L alum, while it was reduced with 20 mg/L, and completely inhibited with 30 mg/L.
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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".