Response of trout populations in five Colorado streams two decades after habitat manipulation
Bibliographic record
Abstract
Evaluating the effectiveness of instream structures for increasing trout populations is complicated by a paucity of long-term studies. We report on a study spanning 23 years to assess the effect of installing log weirs on stream habitat and trout abundance. Structures were installed in a randomly selected half of a 500 m study reach in six small Colorado, USA, mountain streams in 1988, and habitat and trout abundance and biomass were measured annually from 1987 to 1994. When five of the streams were resampled in 2009, none of the 53 logs had moved, and all but one were functioning properly. Pool volume remained more than three times higher in treatment sections than in adjacent controls, and mean depth was also greater. Adult trout abundance increased rapidly after structures were installed and remained 53% higher in treatment sections than in controls 21 years later. Effects on juvenile trout abundance were not detected, probably because fry recruitment is strongly influenced by effects of snowmelt runoff, which vary annually among basins. This evaluation shows that instream structures placed in small, stable channels can function for more than two decades when properly installed and can cause long-lasting increases in trout abundance when habitat is limiting.
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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 | 0.001 | 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".