Contaminant levels and their effects on the American continent chelonian: A systematic review
Bibliographic record
Abstract
Abstract Excessive metal pollution from anthropogenic activities like mining and industrial waste discharge has increasingly impacted freshwater ecosystems. Freshwater chelonians (Testudines) are bioindicators of environmental pollution because of their longevity, ecological diversity, and trophic positioning. This systematic review assessed toxic metal bioaccumulation in freshwater turtles across the American continent, focusing on mercury (Hg), a global public health and ecological concern. A comprehensive search on PubMed, Scopus and Web of Science identified 620 papers, of which 32 met the inclusion criteria. The United States and Brazil (93.6%) contributed the most data, with Chelydra serpentina and Podocnemis expansa frequently studied, followed by Canada (4.26%) and Colombia (2.13%). Hg was the predominant contaminant (75% of studies), with the highest concentrations observed in hatchlings and keratinized tissues, such as carapace and claws. Bioaccumulation patterns varied by region, species and life stage, emphasizing physiological and reproductive impacts. This review highlights the need for noninvasive sampling methods and long‐term monitoring to guide conservation strategies and assess ecosystem and turtle health. It also highlights the significant lack of data in South America and the lack of studies on juveniles and eggs. Freshwater chelonians remain essential for understanding contamination dynamics and mitigating environmental degradation in aquatic habitats.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".