The effect of natural dissolved organic carbon on the acute toxicity of copper to larval freshwater mussels (glochidia)
Bibliographic record
Abstract
The present study examined the effect of dissolved organic carbon (DOC), both added and inherent, on Cu toxicity in glochidia, the larvae of freshwater mussels. Using incremental additions of natural DOC concentrate and reconstituted water, a series of acute copper toxicity tests were conducted. An increase in DOC from 0.7 to 4.4 mg C/L resulted in a fourfold increase (36-150 µg Cu/L) in the 24-h median effective concentration (EC50) and a significant linear relationship (r² = 0.98, p = 0.0008) between the DOC concentration and the Cu EC50 of Lampsilis siliquoidea glochidia. The ameliorating effect of added DOC on Cu toxicity was confirmed using a second mussel species, the endangered (in Canada) Lampsilis fasciola. The effect of inherent (i.e., not added) DOC on Cu toxicity was also assessed in eight natural waters (DOC 5-15 mg C/L). These experiments revealed a significant relationship between the EC50 and the concentration of inherent DOC (r² = 0.79, p = 0.0031) with EC50s ranging from 27 to 111 µg Cu/L. These laboratory tests have demonstrated that DOC provides glochidia with significant protection from acute Cu toxicity. The potential risk that Cu poses to mussel populations was assessed by comparing Cu and DOC concentrations from significant mussel habitats in Ontario to the EC50s. Although overall mean Cu concentration in the mussel's habitat was well below the acutely toxic level given the concentration of DOC, episodic Cu releases in low DOC waters may be a concern for the recovery of endangered freshwater mussels. The results are examined in the context of current Cu water quality regulations including the U.S. Environmental Protection Agency's (U.S. EPA) biotic ligand model.
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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".