Patch size but not short‐term isolation influences occurrence of westslope cutthroat trout above human‐made barriers
Bibliographic record
Abstract
Abstract Habitat fragmentation in aquatic systems has led to widespread isolation of stream fishes. Metapopulation theory predicts that persistence is directly related to local patch size and its characteristics, but because these relationships tend to be taxon‐specific, empirical data are important. We assembled 246 observations of occurrence of westslope cutthroat trout (WCT), a taxon of concern in the western U.S. and Canada, in stream networks isolated for up to 100 years (median 40 years) above human‐made barriers, mostly culverts, at road crossings within U.S. National Forests. We used logistic regression to analyse how WCT occurrence varied with patch size, isolation time and stream‐level covariates. Occurrence was positively related to stream length and habitat quality within the isolated stream network and negatively related to elevation and channel gradient. Unexpectedly, the probability of occurrence was not related to how long a habitat patch had been isolated. At the median elevation (1354 m) and channel gradient (14%), and where habitat quality was poor, WCT were likely to occur (probability >0.5) if an isolated stream network was at least 1.7 km. If habitat quality was high, about 0.2 km of habitat produced the same probability. Although there are important limitations, this analysis provides the first empirical estimate for how patch size and patch‐level characteristics influence persistence of WCT in isolated stream networks.
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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 | 0.002 |
| 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 | 0.001 | 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".