Native Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri Bendire 1882 growth and survival in a headwater stream primarily driven by warming stream temperatures, with non-native brown trout Salmo trutta Linnaeus 1758, posing an additional threat to survival
Bibliographic record
Abstract
Warming rivers and interactions with non-native species impact salmonid species globally. Understanding how hydroclimatic conditions synergistically and independently interact with non-native species is critical for effectively managing salmonids into the future. We used a 10-year mark-recapture dataset to assess how native Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri Bendire 1882 (hereafter YCT) and non-native brown trout Salmo trutta Linnaeus 1758 growth rates and apparent survival were affected by hydroclimatic conditions and (for YCT) the presence of brown trout in a tributary. Growth (YCT) and survival (both species across size classes) were negatively related to warming stream temperatures. Brown trout growth was positively related to increasing daily streamflow variability (a proxy for streamflow), but this variable was not included in the top YCT growth model. Density dependent effects appeared to be nonexistent (growth) or weakly positive (survival). When sympatric with brown trout, YCT displayed worse survival than allopatric YCT across environmental conditions. Broadly, we found native and non-native trout respond to different hydroclimatic conditions that shift with changing climatic conditions; and brown trout represent an additional threat to YCT survival.
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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".