Gull Eggs as Indicators of Mercury Bioavailability: Application of Amino Acid-Compound Specific Nitrogen Isotope Analysis
Bibliographic record
Abstract
Spatial trends in levels of biomagnifying environmental contaminants in tissues of top predators can provide insights into potential contaminant sources and dynamics, as well as inform efforts to control contaminant releases into the environment.Here, I use gull eggs to elucidate spatial trends in environmental availability of mercury in western Canada.I begin by validating the use of eggs as a matrix for monitoring mercury bioavailability through an experimental laboratory study.Next, I investigate mercury spatial trends in wild gull eggs collected at twelve sites located across 14 degrees of latitude.Assessing levels of biomagnifying contaminants can be confounded by dietary variability, therefore I apply amino acid-compound specific stable nitrogen isotope analysis (AA-CSIA) to generate trophic-position adjusted mercury levels that are more suitable for spatial comparisons.Spatial differences in egg mercury levels were evident with highest values observed at sites in receiving waters of the Athabasca River.My research demonstrates the utility of the AA-CSIA approach in enhancing our ability to interpret contaminant monitoring data collected through biomonitoring programs.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".