Niche dynamics of sympatric non‐breeding shearwaters under varying prey availability
Bibliographic record
Abstract
Variation in prey availability can cause changes in species interactions among marine predators. Foraging theory predicts that niche breadth will expand when resources become limited, possibly leading to higher niche overlap among sympatric species; however, a species’ niche can become constrained by interactions with other similar species, resulting in an inability to shift niche breadth or position. In coastal Newfoundland, Capelin Mallotus villosus is the main forage fish species and its availability (i.e. biomass) during the summer has varied considerably following a population collapse in the 1990s. During the summer, non‐breeding Great and Sooty Shearwaters Ardenna gravis and A. grisea migrate and aggregate at annually persistent Capelin spawning sites. We used stable isotope ratios (δ13C, δ15N) of blood components (plasma, red blood cells) to investigate variation in isotopic niche breadth (95% prediction ellipse areas) and overlap of the two shearwater species during 2014, 2015 and 2016. Capelin availability varied among years, illustrated by lower peak biomass in 2015 (0.126 g/m²) and 2016 (0.027 g/m²) relative to 2014 (0.254 g/m²). The isotopic niche breadth (plasma) of both shearwater species expanded similarly from 2014 (0.65–0.66‰²) to 2015 (2.22–2.57‰²) and 2016 (1.15–1.42‰²), suggesting the incorporation of alternative prey types into their diet during years of lower prey availability. Isotopic niche overlap between Great and Sooty Shearwaters remained high across years (44–63%), however, providing little evidence for dietary niche partitioning during years of lower prey availability. Findings suggest that both shearwater species are flexible foragers and can modify their diet during the non‐breeding season to accommodate fluctuations in prey 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".