Trophic pathways supporting juvenile Chinook and coho salmon in the glacial Susitna River, Alaska: patterns of freshwater, marine, and terrestrial food resource use across a seasonally dynamic habitat mosaic
Bibliographic record
Abstract
Contributions of terrestrial-, freshwater-, and marine-derived prey resources to stream fishes vary over time and space, altering the energy pathways that regulate production. In this study, we determined large-scale use of these resources by juvenile Chinook and coho salmon (Oncorhynchus tshawytscha and Oncorhynchus kisutch, respectively) in the glacial Susitna River, Alaska. We resolved spatial and temporal trophic patterns among multiple macrohabitat types along a 97 km segment of the river corridor via stable isotope and stomach content analyses. Juvenile salmon were supported primarily by freshwater-derived resources and secondarily by marine and terrestrial sources. The relative contribution of marine-derived prey to rearing salmon was greatest in the fall within off-channel macrohabitats, whereas the contributions of terrestrial invertebrate prey were generally greatest during midsummer, across all macrohabitats. No longitudinal (upstream–downstream) diet pattern was discernable. These results highlight large-scale spatial and seasonal patterns of energy flow and the dynamic interplay of pulsed marine and terrestrial prey subsidies to juvenile Chinook and coho salmon in a large, complex, and relatively pristine glacial river.
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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) | 0.000 | 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".