Potential loss and rehabilitation of stream longitudinal connectivity: fish populations in urban streams with culverts
Bibliographic record
Abstract
Riverine connectivity is important to the persistence of fish communities, but culverts may impede fish movements to varying degrees and in both directions. Baffles can be installed in culverts to mitigate upstream connectivity loss; however, evaluation of their effectiveness is limited. To examine the potential impacts of culverts and their potential rehabilitation with baffles, we sampled fish populations in 26 streams that contained either (i) nonbaffled culverts or (ii) baffled culverts or (iii) lacked culverts (reference streams) in Metro Vancouver, British Columbia, Canada. Using mixed effects models, we compared fish responses across these three stream types to infer effects at the whole-stream scale (i.e., over both upstream and downstream positions equally), the within-stream scale (i.e., upstream versus downstream of culverts), and the interaction of scales. Densities (n·m−2) of coastrange sculpin (Cottus aleuticus) and prickly sculpin (Cottus asper) were significantly lower in nonbaffled and baffled stream types than in reference stream types, while densities of cutthroat trout (Oncorhynchus clarkii) and rainbow trout (Oncorhynchus mykiss) were significantly lower in reference stream types, indicating whole-stream differences. Using multivariate statistics, we similarly found that fish community compositions were significantly different across stream types. For our various fish responses, we found no interaction between stream type and upstream or downstream position. Further, we found reaches directly downstream of baffled culverts had greater fish biomass and that overall species richness increased with age of baffles. These data suggest that culverts may drive changes in fish populations at whole-stream scales, and restoration of these effects with baffles may take decades.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".