Impeding access to tributary spawning habitat and releasing experimental fall-timed floods increase brown trout immigration into a dam’s tailwater
Bibliographic record
Abstract
River ecosystems have been altered by flow regulation and species introductions. Regulated flow regimes often include releases designed to benefit certain species or restore ecosystem processes, and invasive species suppression programs may include efforts to restrict access to spawning habitat. The impacts of these management interventions are often uncertain. Here, we assess hypotheses regarding introduced brown trout ( Salmo trutta) movement in a regulated river. We model mark–recapture data in a multistate framework to assess whether movement was affected by the operation of a tributary weir (restricting access to spawning habitat), experimental releases of fall-timed high flow experiments (Fall HFEs), or simply increased during the fall, spawning season. Our results suggest that the presence of the weir led to reduced tributary homing and the release of Fall HFEs stimulated upstream movement and straying. Both effects are of a similar magnitude, however the Fall HFE effect is more certain. Our results suggest the expansion of an invasive species was stimulated by management interventions, and demonstrate the potential for unanticipated outcomes of restoration in highly altered river ecosystems.
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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 | 0.001 |
| 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 | 0.001 | 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".