Integrated environmental assessment of freshwater sediments: a chemical and ecotoxicological approach at the Alqueva reservoir
Bibliographic record
Abstract
In order to study the pollution of an aquatic ecosystem, it is necessary to analyze not only the levels of chemical pollutants in water, but also those accumulated in the sediment matrix, as well as to assess its ecotoxicological status. The Alqueva reservoir, the largest artificial lake in Europe, was chosen as case study as it constitutes the most important water supply source in southern Portugal. It is located in the Guadiana River Basin, in a semi-arid region with high levels of water scarcity and where agriculture is one of the main activities. The evaluation of sediments comprised: (1) physical and chemical analysis (grain size, pH, organic matter, nitrogen, phosphorus); (2) potentially toxic trace elements (Cu, As, Pb, Cr, Cd, Zn and Ni); and (3) ecotoxicological evaluation with Vibrio fischeri, Thamnocephalus platyurus, Daphnia magna, and Heterocypris incongruens. Total trace element concentrations indicated that As, Cd, and Pb surpassed the Canadian levels for the protection of aquatic life, in most of Alqueva's sites. The results of the toxicity assessment showed that some locations induced acute and chronic toxicity in the species used. Further, the H. incongruens was the most sensitive species as far as the contamination found in the sediment is concerned, followed by the bacteria V. fischeri. This integrative approach, together with the water column quality assessment, allowed a comprehensive evaluation of the environmental quality of this strongly modified water body and will allow the implementation of remediation strategies to obtain a good ecological potential as proposed in the Water Framework Directive.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".