Effect of Organic Complexation on Copper Accumulation and Toxicity to the Estuarine Red Macroalga <i>Ceramium tenuicorne</i>: A Test of the Free Ion Activity Model
Bibliographic record
Abstract
Current water quality criteria (WQC) regulations on copper toxicity to biota are still based on total dissolved (<0.4 μm membrane filter) copper concentrations with a hardness modification for freshwaters. There are however ongoing efforts to incorporate metal speciation in WQC and toxicity regulations (such as the biotic ligand model-BLM) for copper and other metals. Here, we show that copper accumulation and growth inhibition of the Baltic macroalga Ceramium tenuicorne exposed to copper in artificial seawater at typical coastal and estuarine DOC concentrations (similar to 2-4 mg/L-C as fulvic acid) are better correlated to weakly complexed and total dissolved copper concentrations rather than the free copper concentration [Cu2+]. Our results using a combination of competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-ACSV) measurements and model calculations (using visual MINTEQ incorporating the Stockholm Humic Model) show that copper accumulation in C. tenuicorne only correlates linearly well to [Cu2+] at relatively high [Cu2+] and in the absence of fulvic acid. Thus the FIAM fails to describe copper accumulation in C. tenuicorne at copper and DOC concentrations typical of most marine waters. These results seem to indicate that at ambient total dissolved copper concentration in coastal and estuarine waters, C. tenuicorne might be able to access a sizable fraction of organically complexed copper when free copper concentration to the cell membrane is diffusion limited.
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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 | 0.001 |
| 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 | 0.001 | 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".