Changing ecosystems promote generalism and enhanced heterogeneity in diet composition in the endangered St. Lawrence Estuary beluga
Bibliographic record
Abstract
Changes in trophodynamics may affect trophic niche both at the individual and population levels. Using stable isotope ratios, we showed how contrasting oceanographic and trophic conditions in 1997-2003 and 2015-2020 have altered the diet and degree of individual specialization of St. Lawrence Estuary beluga (Delphinapterus leucas). The trophic niche of all sex and age classes changed over time, with beluga consuming more small pelagic prey during the first than the second period. Adult male diets differed from that of adult females and juveniles during the first period due to the other prey that were consumed. In 2015-2020, diet contributions by small pelagic prey decreased in all segments of the population and led to marginally significant differences in diet between adult males and females. These dietary changes were concomitant to a diversification of diet at the individual level and to an increase in diet heterogeneity among conspecifics and years within the 2015-2020 period. Whether these patterns emerged from an environment-driven reduction in prey biomass or from an increase in intra- and/or interspecific competition is unknown. Our findings illustrate the importance of considering individuals and not just the population when studying the foraging ecology of endangered species.
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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 | 0.001 |
| 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".