The Effects of Natural Suspended Solids on Copper Toxicity to the Cardinal Tetra in Amazonian River Waters
Bibliographic record
Abstract
Abstract The aim of the present study was to characterize the effects of particles on metal aquatic toxicity in a tropical system. To this end, we investigated the effects of natural suspended solids on copper (Cu) geochemistry and acute toxicity to the cardinal tetra (Paracheirodon axelrodi), in 2 Amazonian rivers with different total suspended solids (TSS) levels: the Rio Negro (low TSS ~ 8 mg L–1) and the Rio Solimões (high TSS ~ 70 mg L–1). The effect of particles on Cu aqueous geochemistry was assessed by measuring total, dissolved, and free ionic Cu concentrations in filtered (<0.45 μm) and unfiltered waters. Furthermore, acute Cu toxicity to fish was assessed in both filtered and unfiltered waters, by measuring physiological net fluxes of Na+, Cl–, K+, and total ammonia (in both river waters) and 96-h fish mortality (in Rio Solimões only). The particles in the Rio Negro were not abundant enough to play a significant role in our study. On the other hand, the Rio Solimões particles bound approximately 70% of total aqueous Cu in our tests. In agreement with bioavailability-based models, this decrease in dissolved (and free ionic) Cu concentration decreased Cu lethality in the 96-h toxicity tests. In the physiological measurements, the best evidence of particle protection was the total alleviation of Cu-induced Cl– losses. These flux tests also suggested that the particles themselves may negatively affect Na+ balance in the fish. Overall, the present study supports the use of bioavailability concepts to account for the role of natural suspended solids on metal biological effects in the Amazon River basin. Environ Toxicol Chem 2019;38:2708–2718. © 2019 SETAC Abstract Effects of suspended solids on copper acute toxicity to the cardinal tetra.
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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".