Herring gulls and great black-backed gulls as indicators of contaminants in bald eagles in Lake Ontario, Canada
Bibliographic record
Abstract
In 2000, a pair of bald eagles (Haliaeetus leucocephalus) nested successfully along the shorelines of Lake Ontario in North America for the first time since 1957. However, it is a continuing question whether bald eagles will be able to reproduce successfully as they return to nest on Lake Ontario. Great black-backed gulls (Larus marinus) and herring gulls (L. argentatus) were selected as surrogate species to predict contaminant levels in eggs of bald eagles nesting on Lake Ontario. Because of the suspected overlap in the diets of great black-backed gulls and bald eagles (i.e., fish, gull chicks, and waterfowl), the two species probably occupy a similar trophic level in the Lake Ontario food web and, thus, may have similar contaminant levels. Fresh great black-backed gull and herring gull eggs were collected from three study sites in eastern Lake Ontario in 1993 and 1994 and analyzed for contaminants. Average contaminant levels of dichlorodiphenyldichloroethane (p,p'-DDE), total polychlorinated biphenyls (PCBs), and dieldrin in great black-backed gull eggs were 12.85, 26.27, and 0.27 microg/g, respectively. The mean ratio of contaminant levels in great black-backed gull eggs to contaminant levels in herring gull eggs for these three contaminants was 2.09 (range of means, 1.73-2.38). Predicted levels of contaminants in bald eagle eggs in Lake Ontario would be expected to be similar to the mean levels reported for great black-backed gull eggs. As a comparison, contaminant levels in bald eagle eggs collected from other Great Lakes nesting sites were compared to mean levels reported for herring gull eggs collected from nearby sites in 1986 to 1995. The mean ratio of contaminant levels in bald eagle eggs to contaminant levels in herring gull eggs from these sites for DDE, total PCBs, and dieldrin was 2.40 (range of means, 1.73-3.28). These ratios are very similar to those reported using great black-backed gull eggs, illustrating the apparent similarity in trophic status shared by the two top predator species at these Great Lakes sites. Predicted levels of contaminants in bald eagle eggs at Lake Ontario are similar to levels reported for bald eagles breeding at other Great Lakes sites, suggesting that bald eagles may be able to breed on the shores of Lake Ontario. However, it is unclear at this time what level of breeding success should be expected, given that productivity at other similarly contaminated Great Lakes sites may be below that required to sustain a successful breeding population. The absence of an inland bald eagle population from which bald eagles may begin to colonize the shorelines of Lake Ontario may be delaying initiation of nesting site selection; other factors such as habitat and prey availability would likely not limit reproductive success.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".