Effects of non-native <i>Salmo trutta</i> and multiscale habitat factors on native fishes in the Driftless Area
Bibliographic record
Abstract
We collected fishes and habitat data at 138 streams to evaluate the effects of introduced brown trout ( Salmo trutta) and habitat conditions on occurrence, detection, abundance, and size structure of sculpin ( Cottus spp.), longnose dace ( Rhinichthys cataractae), and southern redbelly dace ( Chrosomus erythrogaster) in the Driftless Area, USA. Sculpin detection decreased with increasing stream velocity, whereas southern redbelly dace detection increased with stream depth. Sculpin occupancy declined with increasing stream temperature and velocity and increased with increasing forested land, boulder substrate, and brown trout length and abundance. Longnose and southern redbelly dace occupancy and abundance declined with increasing brown trout abundance and occupancy increased with stream temperature. Longnose dace occupancy also increased with increasing stream temperature and cobble substrate and declined with increasing elevation. Native fish size structure was unrelated to brown trout presence. Our results suggest that effects of brown trout are not ubiquitous across native fishes and depend on abiotic conditions and species-specific habitat requirements, highlighting the need to consider both biotic and abiotic conditions when balancing native species conservation with introduced sportfish management.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".