Seabird-driven shifts in Arctic pond ecosystems
Bibliographic record
Abstract
Migratory animals such as seabirds, salmon and whales can transport large quantities of nutrients across ecosystem boundaries, greatly enriching recipient food webs. As many of these animals biomagnify contaminants, they can also focus pollutants at toxic levels. Seabirds arguably represent the most significant biovectors of nutrients and contaminants from the ocean to the land, given their sheer numbers and global distribution. However, long-term census data on seabirds are rare. Using palaeolimnological proxies, we show that a colony of Arctic seabirds has experienced climate-induced population increases in recent decades. We then document increasing concentrations of contaminants, including polychlorinated biphenyls and cadmium, in pond sediments that are linked to biotransport by seabirds. Our findings suggest that climate-related shifts in global seabird populations will have the unexpected consequence of restructuring coastal ecosystems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".