Human-Induced Long-Term Shifts in Gull Diet from Marine to Terrestrial Sources in North America’s Coastal Pacific: More Evidence from More Isotopes (δ<sup>2</sup>H, δ<sup>34</sup>S)
Bibliographic record
Abstract
Measurements of naturally occurring stable isotopes in tissues of seabirds and their prey are a powerful tool for investigating long-term changes in marine foodwebs. Recent isotopic (δ(15)N, δ(13)C) evidence from feathers of Glaucous-winged Gulls (Larus glaucescens) has shown that over the last 150 years, this species shifted from a midtrophic marine diet to one including lower trophic marine prey and/or more terrestrial or freshwater foods. However, long-term isotopic patterns of δ(15)N and δ(13)C cannot distinguish between the relative importance of lower trophic-level marine foods and terrestrial sources. We examined 48 feather stable-hydrogen (δ(2)H) and -sulfur (δ(34)S) isotope values from this same 150-year feather set and found additional isotopic evidence supporting the hypothesis that gulls shifted to terrestrial and/or freshwater prey. Mean feather δ(2)H and δ(34)S values (± SD) declined from the earliest period (1860-1915; n = 12) from -2.5 ± 21.4 ‰ and 18.9 ± 2.7 ‰, respectively, to -35.5 ± 15.5 ‰ and 14.8 ± 2.4 ‰, respectively, for the period 1980-2009 (n = 12). We estimated a shift of ∼ 30% increase in dependence on terrestrial/freshwater sources. These results are consistent with the hypothesis that gulls increased terrestrial food inputs in response to declining forage fish availability.
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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 | 0.000 | 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".