Hydrogeomorphic effects on bedload scour in bull char (Salvelinus confluentus) spawning habitat, western Washington, USA
Bibliographic record
Abstract
We investigated the vulnerability of fall-spawned bull char ( Salvelinus confluentus ) embryos to redd scour during winter rain and rain-on-snow flood discharges in western Washington, USA. It was hypothesized that the magnitude of bedload scour at bull char redds is reduced by the provision and selection of stable refugia habitat controlled by local-, reach-, or subcatchment-scale variables such as hydraulic habitat unit and channel type. Bedload scour and channel change were measured using 96 scour monitors and 34 elevational transects in three catchments over 2 to 4 years. Scour to cited egg burial depths of bull char did not commence until discharge typically exceeded the 2-year recurrence interval. At a local scale, scour varied significantly among side channel, protected main channel, and unprotected main channel redd sites. Unprotected gravel patches in simplified channel types with moderate gradients were most susceptible to deep scour, especially if coupled with the transient supply and storage of sand and gravel from mass wasting. Partially transport-limited reaches had reduced scour due to lower stream power and armored gravel beds. Complex spawning habitat (i.e., with abundant large woody debris and side channels) was important in providing refuge from deep scour and in buffering embryos against inhospitable hydrologic or sediment regimes.
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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".