Bull trout ( <scp> <i>Salvelinus confluentus</i> </scp> ) exhibit binge‐feeding and digestive flexibility during seasonal resource pulses associated with salmon migrations
Bibliographic record
Abstract
Resource pulses are infrequent, ephemeral events of resource hyperabundance that can represent important feeding opportunities for consumers. To capitalize on pulsed resources, consumers can exhibit behavioural and physiological traits including binge-feeding and phenotypic plasticity of digestive physiology, although expression of these traits has not been observed simultaneously. Further, past studies of binge-feeding have largely focused on times and locations where resources were highly concentrated, ignoring potential temporal and spatial variation in consumer responses. We investigated these traits in bull trout Salvelinus confluentus that experience seasonal resource pulses associated with the spring migration of sockeye salmon Oncorhynchus nerka smolts and their fall spawning migrations in a large lake-river system. We also examined spatial variation in S. confluentus diet and feeding behaviour within seasons to explore associations with proximity to aggregated salmon. To do this, we collected S. confluentus stomach contents and analysed consumption rates across seasons and capture locations. We also investigated if the size of digestive organs changed with season. In the spring and fall, S. confluentus consumed O. nerka smolts and eggs, respectively, at high rates, with consumption often exceeding theoretical daily maximums by up to 21.50-fold in the spring and 7.69-fold in the fall. The degree of binge-feeding was correlated with proximity to the lake outlet where smolts and spawning salmon congregate, increasing by 1.21-fold in the spring and 2.78-fold in the late fall for each ~13-km shift in capture location towards the outlet. Salvelinus confluentus also exhibited larger digestive organs during the spring and fall, while the same organs were atrophied during the summer. Our results indicate that a single consumer population can exhibit both behavioural and physiological responses to resource pulses, and that exploitation can vary along a spatial gradient of presumed resource availability. These responses emphasize the importance of resource pulses to consumers and the potential for intra-population differences in consumer responses to transient feeding opportunities.
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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".