Multiscale hydrogeomorphic influences on bull trout (<i>Salvelinus confluentus</i>) spawning habitat
Bibliographic record
Abstract
We investigated multiscale hydrogeomorphic influences on the distribution and abundance of bull trout (Salvelinus confluentus) spawning in snowmelt-dominated streams of the upper Flathead River basin, northwestern Montana. Within our study reaches, bull trout tended to spawn in the finest available gravel substrates. Analysis of the mobility of these substrates, based on one-dimensional hydraulic modeling and calculation of dimensionless shear stresses, indicated that bed materials in spawning reaches would be mobilized at moderate (i.e., 2-year recurrence interval) high-flow conditions, although the asynchronous timing of the fall–winter egg incubation period and typical late spring – early summer snowmelt high flows in our study area may limit susceptibility to redd scour under current hydrologic regimes. Redd occurrence also tended to be associated with concave-up bedforms (pool tailouts) with downwelling intragravel flows. Streambed temperatures tracked stream water diurnal temperature cycles to a depth of at least 25 cm, averaging 6.1–8.1 °C in different study reaches during the spawning period. Ground water provided thermal moderation of stream water for several high-density spawning reaches. Bull trout redds were more frequent in unconfined alluvial valley reaches (8.5 versus 5.0 redds·km−1 in confined valley reaches), which were strongly influenced by hyporheic and groundwater – stream water exchange. A considerable proportion of redds were patchily distributed in confined valley reaches, however, emphasizing the influence of local physical conditions in supporting bull trout spawning habitat. Moreover, narrowing or “bounding” of these alluvial valley segments did not appear to be important. Our results suggest that geomorphic, thermal, and hydrological factors influence bull trout spawning occurrence at multiple spatial scales.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".