Divergence in digestive and metabolic strategies matches habitat differentiation in juvenile salmonids
Bibliographic record
Abstract
Abstract Divergent energy acquisition and processing strategies associated with using different microhabitats may allow phenotypes to specialize and coexist at small spatial scales. To understand how ecological specialization affects differentiation in energy acquisition and processing strategies, we examined relationships among digestive physiology, growth, and energetics by performing captive experiments on juveniles of wild coho salmon ( Oncorhynchus kisutch ) and steelhead trout ( O. mykiss ) that exploit adjacent habitats along natural low‐to‐high energy flux gradients (i.e., pools versus riffles) in coastal streams. We predicted that: (i) the specialization of steelhead trout to high‐velocity, high‐energy habitats would result in elevated food intake and growth at the cost of lower growth efficiency relative to coho salmon; (ii) the two species would differentiate along a rate‐maximizing (steelhead trout) versus efficiency‐maximizing (coho salmon) axis of digestive strategies matching their ecological lifestyle; and (iii) the higher postprandial metabolic demand (i.e., specific dynamic action, SDA) associated with elevated food intake would occupy a greater fraction of the steelhead trout aerobic budget. Relative to coho salmon, steelhead trout presented a pattern of faster growth and higher food intake but lower growth efficiency, supporting the existence of a major growth versus growth efficiency trade‐off between species. After accounting for differences in ration size between species, steelhead trout also presented higher SDA than coho salmon, but similar intestinal transit time and lower assimilation efficiency. Both species presented similar aerobic budgets since the elevated SDA of steelhead trout was largely compensated by their higher aerobic scope relative to coho salmon. Our results illustrate the key contribution of digestive physiology to the adaptive differentiation of juvenile growth, energetics, and overall performance of taxa with divergent habitat specializations along a natural productivity gradient.
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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".