The physiology of fish in acidic waters rich in dissolved organic carbon, with specific reference to the Amazon basin: Ionoregulation, acid–base regulation, ammonia excretion, and metal toxicity
Bibliographic record
Abstract
Abstract Although blackwaters, named for their rich content of dissolved organic carbon (DOC), are often very poor in ions and very acidic, they support great fish biodiversity. Indeed, about 8% of all freshwater fish species live in the blackwaters of the Rio Negro watershed in the Amazon basin. We review how native fish survive these harsh conditions that would kill most freshwater fish, with a particular focus on the role of DOC, a water quality parameter that has been relatively understudied. DOC, which is functionally defined by its ability to pass through a 0.45‐µm filter, comprises a diverse range of compounds formed by the breakdown of organic matter and is quantified by its carbon component that is approximately 50% by mass. Adaptations of fish to acidic blackwaters include minimal acid–base disturbances associated with a unique, largely unknown, high‐affinity Na + uptake system that is resistant to inhibition by low pH in members of the Characiformes, and very tight regulation of Na + efflux at low pH in the Cichliformes. Allochthonous (terrigenous) DOC, which predominates in blackwaters, consists of larger, more highly colored, reactive molecules than autochthonous DOC. The dissociation of protons from allochthonous components such as humic and fulvic acids is largely responsible for the acidity of these blackwaters, yet at the same time, these components may help protect organisms against the damaging effects of low water pH. DOC lowers the transepithelial potential (TEP), mitigates the inhibition of Na + uptake and ammonia excretion, and protects against the elevation of diffusive Na + loss in fish exposed to acidic waters. It also reduces the gill binding and toxicity of metals. At least in part, these actions reflect direct biological effects of DOC on the gills that are beneficial to ionoregulation. After chronic exposure to DOC, some of these protective effects persist even in the absence of DOC. Two characteristics of allochthonous DOC, the specific absorbance coefficient at 340 nm (determined optically) and the PBI (determined by titration), are indicative of both the biological effectiveness of DOC and the ability to protect against metal toxicity. Future research needs are highlighted, including a greater mechanistic understanding of the actions of DOCs on gill ionoregulatory function, morphology, TEP, and metal toxicity. These should be investigated in a wider range of native fish Orders that inhabit one of the world's greatest biodiversity hotspots for freshwater fishes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".