Spawning habitat suitability for coastal cutthroat trout: Microhabitat and mesohabitat
Bibliographic record
Abstract
Abstract The conservation of aquatic species with complex life histories requires the protection of habitat for each life stage. Coastal cutthroat trout (Oncorhynchus clarkii clarkii) exhibit both mobile and sessile stages and are of conservation concern in north‐western North America. Models that predict how habitat changes with flow can inform water management for the species but rely on habitat descriptors that change with flow and are not suited to sessile life stages. Spawning and incubation habitat availability and use for coastal cutthroat trout were assessed in mesohabitats and microhabitats. Primary channel units were tallied, dimensions were measured, redds were counted, and redd locations within channel units were measured. Primary channel units were subdivided based on relative residual depth (RRD, bed elevation in relation to maximum pool depth) and hydraulic control (HC, the lowest point on the highest ridge across the riffle that controls the water surface elevation in the upstream pool). Habitat suitability was calculated for depth (D), velocity (V), Froude number (Fr), substrate (S), RRD, and channel units. Redds in riffles and pools were close to hydraulic controls; suitability decreased upstream in pools and downstream in riffles. Maximum suitability values were: 21–24 cm for D, 0.05–0.10 for RRD, 61–64 cm s−1 for V, >0.80 for Fr, and 1.3 to <3.8 cm for S. Channel units, RRDs, and microhabitat better identified spawning habitat than microhabitat alone. The results suggest that RRD and stage of zero flow are good indicators of habitat suitability for spawning through fry emergence and could be adapted for use with other species. This work generates criteria for delineating flow‐independent channel units that can be used to set more protective instream flows, prioritize the acquisition of instream water or conservation easements to protect critical habitat, and inform restoration projects to optimize habitat availability.
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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) | 0.002 | 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".