Why do we monitor? Using seabird eggs to track trends in Arctic environmental contamination
Bibliographic record
Abstract
Contaminant levels and trends have been monitored in the eggs of seabirds from the Canadian Arctic since 1975. Nearly 50 years of monitoring have provided key information regarding the temporal and spatial variation of various contaminant classes in different seabird species. However, previous work has primarily assessed individual or related contaminant classes in isolation. There is therefore a need to collectively consider all of the contaminants monitored in seabird eggs to determine where monitoring has been successful, to find areas for improvement, and to identify opportunities for future research. In this review, we evaluated monitoring data for the major legacy and emerging contaminants of concern in five seabird species from three High Arctic and three Low Arctic colonies in Canada. We review the history of Canada’s Arctic seabird egg monitoring program and discuss how monitoring efforts have changed over time; we summarize temporal, spatial, and interspecies variations in Arctic seabird egg contamination and identify important knowledge gaps; and, we discuss future directions for ecotoxicology research using seabird eggs in Arctic Canada. Ultimately, this paper provides a high-level overview of the egg contaminant monitoring program and underscores the importance of long-term and continued seabird contaminant monitoring in Arctic Canada.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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; both teacher heads agree on what is shown here.
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".