Diet composition and habitat use of piscivorous fishes (Arctic grayling, burbot, Dolly Varden, inconnu, and northern pike) in Chena, Unalakleet, and upper Yukon watersheds, 2013-2015
Bibliographic record
Abstract
Predation on anadromous salmon can have important consequences for both predators and prey. Salmon provide large seasonal pulses of energy and nutrients via carcasses, eggs, and juveniles to many freshwater consumers, and conversely predation can represent a significant source of mortality for juvenile salmon. Recent declines of Chinook salmon (Oncorhynchus tshawytscha) populations in Alaska have raised concern that predation might inhibit their recovery. Using this dataset, we quantified patterns of predation by freshwater fishes on juvenile salmon across seasons, habitats, predator sizes, and streamflow levels in the Arctic-Yukon-Kuskokwim region of Alaska. We analyzed piscivore stomach contents and identified prey using DNA sequence ‘barcoding’. In coastal rivers, juvenile pink (O. gorbuscha) and chum (O. keta) salmon contributed heavily to Arctic grayling (Thymallus arcticus) and Dolly Varden char (Salvelinus malma) diets, coho salmon (O. kisutch) prey were rare, and Chinook salmon were not detected. In interior rivers, Arctic grayling, burbot (Lota lota), and northern pike (Esox lucius) consumed small numbers of Chinook salmon. Predation on Chinook salmon was documented disproportionately in sloughs during a summer of exceptionally high streamflow. Dietary and distributional patterns suggested northern pike and burbot may exclude salmon from sloughs in low-gradient river reaches that would otherwise provide suitable rearing habitat. The data also provided tentative support for the hypothesis that high streamflow induces juvenile Chinook salmon to move from mainstem habitats into sloughs, where they face an increased risk of mortality. Incorporating predation risk into climate adaptation, fisheries management, and habitat restoration decisions may help to facilitate Chinook salmon recovery.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".