Season‐specific survival rates and densities of coastal cutthroat trout across stream sizes in southwestern British Columbia
Bibliographic record
Abstract
Abstract Variation in seasonal survival rates, densities and growth rates of coastal cutthroat trout ( Oncorhynchus clarkii clarkii ) were assessed across a size gradient of small, forested streams in the Pacific Northwest. We used a robust, mark‐recapture study, stratified seasonally to estimate monthly survival rates of trout in coastal British Columbia (not including young‐of‐the‐year). Survival estimates showed that the summer season had the lowest monthly survival rates (0.907) across all streams in our study (0.927 remainder of year). Within the size range of the seven small streams studied, low‐flow habitat availability (defined by residual pool depth in summer) was the best predictor of mean monthly survival rates, supporting the hypothesis that trout survival increases with the quantity of aquatic habitat, particularly depths of residual pools. In addition, there was an asymptotic relation between water depth and survival rates, where beyond ~20 cm of residual pool depth, greater depth did not confer greater rates of trout survival. Growth rates in all but the largest stream were also lowest during summer. While densities tended to be higher in streams with greater residual depth, this was not significant. Body mass in a given season was a good predictor of survival to the next sampling period. The distribution and success of resident cutthroat trout populations in small streams appear to be constrained by summer low‐flow periods and specific geomorphologies that support deeper pools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".