Eurasian otter (Lutra lutra) as sentinel species for the long-term biomonitoring of the Guadiamar River after the Aznalcóllar mine spill
Bibliographic record
Abstract
Accidents at mines involving stored tailings have produced catastrophic environmental damage. In April 1998 the dam of the Aznalcóllar mine tailings pond in the surroundings of the Doñana National Park (southwestern Spain) broke, discharging into the Guadiamar River more than 6 million m3 of toxic mud and acidic water with high concentrations of heavy metals and arsenic. We used the Eurasian otter (Lutra lutra) as sentinel species to assess the potential impact of the toxic spill on the river ecosystems and their recovery with time by studying the spatial and temporal variation (1999-2003, 2006) of selected trace element (Cu, Zn, Cd, Pb and As) concentrations in feces. Throughout the sampling period, the highest heavy metal and As levels were found in the most spill-affected reaches of the Guadiamar River (i.e., the Middle and, to a lesser extent, the Lower reaches), pointing out the mining accident as the main origin of the contamination. Overall, levels of trace elements decreased with the time elapsed since the toxic spill, except for Cd (F1,352 = 0.29, P = 0.59). However, rebounds for some elements (Pb, As, and Cu) were also observed, especially in the Middle and Lower reaches of the river, which might be attributed to the residual contamination in abiotic compartments and/or new inputs from industrial and agricultural activities in the nearby areas. Concentrations were relatively high when compared to those reported for both our reference area (Guadalete River) and other metal-polluted zones. We found that the estimated amounts of Pb and As ingested during the first years after the spill in the Guadiamar Middle reach would be high enough to cause reproductive issues. This could affect the local population recovery, although evidence on distribution range and numbers suggests otherwise, with thriving populations at regional scale. Our results support the role of otters as sentinel species for biomonitoring contaminants and thus to evaluate fluvial ecosystem health.
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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 | 0.000 |
| 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".