The interactive effects of stream temperature, stream size, and non-native species on Yellowstone cutthroat trout
Bibliographic record
Abstract
Climate change and non-native species are considered two of the biggest threats to native salmonids in North America. We evaluated how non-native salmonids and stream temperature and discharge were associated with Yellowstone cutthroat trout (Oncorhynchus clarkii bouvieri) distribution, abundance, and body size to gain a more complete understanding of the existing threats to native populations. Allopatric Yellowstone cutthroat trout were distributed across a wide range of average August temperatures (3.2 to 17.7 °C), but occurrence significantly declined at colder temperatures (<10 °C) with increasing numbers of non-natives. At warmer temperatures, occurrence remained high, despite sympatry with non-natives. Yellowstone cutthroat trout relative abundance was significantly reduced with increasing abundance of non-natives, with the greatest impacts at colder temperatures. Body sizes of large Yellowstone cutthroat trout (90th percentile) significantly increased with warming temperatures and larger stream size, highlighting the importance of access to these more productive stream segments. Considering multiple population-level attributes demonstrates the complexities of how native salmonids (such as Yellowstone cutthroat trout) are likely to be affected by shifting climates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".