Inter-annual variability in diet of non-breeding pelagic seabirds Puffinus spp. at migratory staging areas: evidence from stable isotopes and fatty acids
Bibliographic record
Abstract
During nesting periods, seabirds are known to exhibit considerable inter-annual variability in diets, yet little is known about the diets of pelagic seabirds during non-breeding periods.Over 5 yr (2005 to 2009), we studied dietary partitioning between sympatric greater and sooty shearwaters, Puffinus gravis and P. griseus, during migratory staging periods in the Northwest Atlantic.Stable-isotope (SI; n = 253) and fatty-acid (FA; n = 127) signatures from blood samples were used to assess inter-annual patterns in diet and quantify prey choices.In addition to significant effects of year, capture site, and body condition, SI signatures revealed subtle, but consistent, dietary partitioning between species.In all years, greater shearwaters fed at slightly higher trophic levels (overall mean δ 15 N = 13.6 ‰) and lower δ 13 C (-19.1 ‰) than sooty shearwaters (δ 15 N = 13.3 ‰, δ 13 C = -18.9‰).SI mixing models revealed that sooty shearwaters relied more heavily on euphausiids Meganyctiphanes norvegica, while greater shearwaters consumed more herring Clupea harengus, squid Illex illecebrosus, and, in some years, mackerel Scomber scombrus.In 2005/2006, bird diets consisted primarily of herring and krill, but demonstrated a shift towards krill and squid during 2007-2009.FA from bird plasma showed little inter-specific partitioning but a strong signal of annual variation for both species.We used a subset of prey FA and a modified multivariate approach to model bird diets and obtained dietary preferences broadly in agreement with SI results.The present study revealed inter-annual variability and dietary partitioning in sympatric species of pelagic seabirds, and highlights potential shifts in prey availability to predators in the Bay of Fundy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".