Combined usage of stable isotopes and GPS-based telemetry to understand the feeding ecology of an omnivorous bird, the Ring-billed Gull (<i>Larus</i> <i>delawarensis</i>)
Bibliographic record
Abstract
The aim of the present study was to investigate the feeding ecology of an omnivorous bird, the Ring-billed Gull (Larus delawarensis Ord, 1815), breeding in a highly urbanized and heterogeneous landscape (Montréal area, Quebec, Canada). We used gastrointestinal (G.I.) tract content analysis, GPS-based tracking information, and stable isotope profiles of carbon (δ13C) and nitrogen (δ15N) in selected tissues and major food items. Based on GPS tracking data (1–3 days), Ring-billed Gulls were categorized according to their use of three main foraging habitats: agricultural, St. Lawrence River, and anthropogenic (comprising urban areas, landfills, and wastewater treatment plant basins). Ring-billed Gulls that foraged predominantly in anthropogenic habitats exhibited significantly lower δ15N in blood cells and higher total C to N ratios (C:N) in liver. These lower δ15N and higher C:N ratios were characteristic of profiles determined in food items consumed by Ring-billed Gulls at these urbanized sites (e.g., processed foods). The strong positive correlations between δ13C and δ15N in Ring-billed Gull tissues (plasma, blood cells, and liver) that differed in isotopic turnover times, as well as the strong positive correlations in both δ13C and δ15N between tissue pairs, indicated that Ring-billed Gulls exhibited conserved dietary habits throughout the nesting period. This study demonstrates that combining conventional dietary examination, tissue stable isotope analysis, and fine-scale GPS tracking information may improve our understanding of the large intrapopulation variations in foraging behaviour (and isotopic profiles) commonly observed in omnivorous birds.
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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 | 0.001 |
| 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) | 0.000 | 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".