An Invisible Threat to Natural Heritage: Examples of Large Protected Areas with Hg-Enriched Freshwater Environments
Bibliographic record
Abstract
Freshwater environments of large protected areas such as national parks and biosphere reserves concentrate a significant amount of natural heritage. An active release of mercury (Hg) to the global environment may challenge the state of this heritage. The present work synthesizes tentatively the information on Hg-enrichment in freshwater environments of large protected areas. A major bibliographical database was used to find the related literature (articles in international journals), which then was filtered to leave only the most relevant sources. Their content was analyzed to extract the necessary information. This bibliographical survey permitted us to find a few dozen examples of protected areas with freshwater environments enriched in mercury and methylmercury. These areas are present in the different parts of the world, and most commonly the Americas. The researchers paid more attention to mercury in biota than in water and sediments. The reported factors of Hg-enrichment differ, with the prevalence of those anthropogenic. The role of volcanism and long-distance dispersal of mercury by air and water is also significant. Interpreting the examples faces various uncertainties, but it is generally clear that Hg-enrichment can be regarded as a potential threat to natural heritage of protected areas on the global scale. It is proposed that Hg-hotspots (e.g., in Nova Scotia in Canada and Patagonia in Argentina) are rare phenomena constituting a new category of heritage. This interpretation extends the vision of the overall natural heritage of national parks and biosphere reserves. Several recommendations to natural heritage management in large protected areas with Hg-enriched freshwater environments are specified.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".