Biotransport of metallic trace elements from marine to terrestrial ecosystems by seabirds
Bibliographic record
Abstract
Abstract Physical systems, such as currents and winds, have traditionally been considered responsible for transporting contaminants. Although evidence is mounting that animals play a role in this process through their movements, we still know little about how such contaminant biotransport occurs and the extent of effects at deposition sites. In the present study, we address this question by studying how rhinoceros auklets (Cerorhinca monocerata), a seabird that occurs in immense colonies (∼300 000 pairs at our study site, Teuri Island), affect contaminant levels at their colony and at nearby sites. More specifically, we hypothesize that contaminants are transported and deposited by seabirds at their colony and that these contaminants are passed on locally to the terrestrial ecosystem. To test this hypothesis, we analyzed the concentration of 9 heavy metal and metalloids, as well as δ13C and δ15N stable isotopes, in bird tissues, plants, and soil, both within and outside of the colony. The results show that rhinoceros auklets transport marine-derived mercury (Hg), possibly from their wintering location, and deposit Hg via their feces at their breeding site, thereby contaminating plants and soils within the breeding colony. The present study confirms not only that animals can transport contaminants from marine to terrestrial ecosystems, potentially over unexpectedly long distances, but also that bird tissues contribute locally to plant contamination. Environ Toxicol Chem 2019;38:106–114. © 2018 SETAC
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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 | 0.000 | 0.000 |
| 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".