Does environmental contamination influence egg coloration? A long‐term study in herring gulls
Bibliographic record
Abstract
Summary Although considerable progress has been made in reducing concentrations of persistent organic compounds in the environment, these contaminants are still found in many taxa. Here, we investigate the relationship between environmental contamination and avian egg coloration to examine whether egg coloration could be used as a bioindicator of contaminant load. The H erring G ull M onitoring P rogramme has documented changes in contaminant levels found in herring gull L arus argentatus Pontoppidan eggs across the Great Lakes for nearly 40 years. We measured the coloration of these eggs using reflectance spectrophotometry and evaluated the influence of a suite of contaminants on egg colour using general linear mixed models. Herring gull egg coloration was related to the levels of environmental contaminants found within the eggs. Our findings reveal a negative association between blue‐green chroma and a principal component explaining contaminant load. We also found that ultraviolet chroma varied positively with contaminant load, whereas brown chroma was not significantly related to contaminant load. In addition, a cross‐validated discriminant function analysis was able to correctly classify 84% of eggs to either high or low contaminant load. This is an important first step in assessing the utility of using egg coloration as a proxy for contaminant load in a colonially breeding waterbird. Synthesis and applications . Our study utilized a large, multi‐year data set to provide the first evidence that a suite of environmental contaminants appear to influence avian eggshell coloration. We also found that objective spectrophotometric measurements provide a reliable tool for assessment of egg contaminant load, and we provide a discriminant function for contaminant classification directly in the field. Our findings should be broadly relevant, because the pigments responsible for avian egg coloration are shared across all birds. The application of eggshell colour as a bio‐monitoring tool has important conservation and management applications; measuring egg coloration may provide a rapid, inexpensive and nondestructive means of estimating contaminant levels in the environment. This may provide an essential tool for monitoring areas or species of concern, as well as evaluating potential human health risks, by identifying populations supported by an environment that requires more attention and potentially environmental remediation.
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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 | 0.000 |
| 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) | 0.002 | 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".