Physiological health of wintering glaucous-winged gulls in coastal British Columbia
Bibliographic record
Abstract
Abstract Gulls (Laridae) use natural and urban environments and are useful ‘biomonitors’ of coastal ecosystem health. Here, we assessed physiological health of glaucous-winged gulls (Larus glaucescens, GWGU) wintering in the Salish Sea, British Columbia, Canada, a biodiverse region undergoing rapid anthropogenic change. We measured six physiological health biomarkers (blood glucose, triglycerides, haemoglobin, haematocrit, reactive oxygen metabolites and total antioxidants). Gulls sampled on the west coast of Vancouver Island had higher blood δ13C and δ15N values likely reflecting more marine diets compared with birds sampled in the Lower Mainland of Vancouver and in associated urban habitats such as landfills but terrestrial isotopic inputs are confounding. We found few differences in any of the six physiological markers in relation to region and habitat, or in overall indices of ‘health’ and ‘nutritional state’ using principal components analysis, even though these were characterized by varying levels of urban development and anthropogenic activity. Furthermore, individual variation in physiological traits was independent of individual variation in blood δ13C and δ15N values. This likely reflects the fact that we sampled ‘physiologically homeostatic’ individuals at all locations and habitats. Our study establishes reference values for six putative ‘health’ biomarkers, highlighting important covariates that need to be considered (e.g. sex, location) and provides a foundation for long-term physiological monitoring in relation to future anthropogenic impacts in this region.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".