Mercury in the Soil-Plant-Deer-Predator Food Chain of a Temperate Forest in Slovenia
Bibliographic record
Abstract
Total mercury and methylmercury concentrations from long-term monitoring of the terrestrial soil-vegetation-herbivore-carnivore food chain with regard to accumulation and transformation processes were studied in areas of Slovenia contaminated with mercury to differing degrees, as well as uncontaminated areas. Assessment of the inhaled and ingested contribution of mercury from the environment in roe deer ( Capreolus capreolus L.), the selected wild mammal species living in these areas, showed that while the ratio between these two routes of uptake is relatively constant, food intake of mercury in roe deer is much more important than inhaled mercury, which represents only up to 0.2% of ingested Hg. Although the plant species comprising roe deer foodstuffs were not active accumulators of mercury from soil or air, vegetation mediates significant transfer of Me-Hg to herbivores, and this becomes subject to further accumulation in the higher trophic levels of this food chain. Besides roe deer other bioindicators such as chamois ( Rupicapra rupicapra L.) were selected to confirm the uptake of mercury from plants. Though the conclusions drawn from the carnivorous predators lynx ( Felis lynx L.) and wolves ( Canis lupus L.) are limited due to the limited number of subjects (8 and 2, respectively), the results and their comparison to other environmental data showed the transfer of Hg from soil (and air) to vegetation, herbivores and carnivores further up the food chain. The results of the measurements as well as concentration factors ( CF ) and bio-accumulation factors ( BAF ) show appreciable accumulation of Me-Hg and less marked accumulation of T-Hg at higher trophic levels of this terrestrial food chain. Interestingly, higher accumulation of Me-Hg was observed in those environments polluted with high concentrations of inorganic mercury compared to less contaminated and control areas.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".