Landscape-level stream fragmentation caused by hanging culverts along roads in Alberta’s boreal forest
Bibliographic record
Abstract
Hanging culverts (i.e., outfall elevated above the stream surface) can fragment fish communities in streams by creating upstream movement barriers. We conducted a retrospective study of culvert stream crossings along industrial roads in Alberta’s boreal forest to describe factors relating to the occurrence of hanging culverts and to quantify watershed fragmentation. One-half (50%; 187/374) of culverts surveyed in four watersheds during 2002 and 2003 were hanging. Logistic regression showed that the occurrence of a hanging culvert was positively and significantly related to culvert age and reach slope. We quantified fragmentation in the watersheds as the length-based percentage of stream reaches above hanging culverts. In three watersheds, stream fragmentation was approximately 5%, whereas one watershed showed 20% fragmentation. Extrapolating our results to Alberta’s entire boreal forest, we estimated that several thousand hanging culverts were fragmenting tens of thousands of kilometres of streams in 2003. These numbers are likely increasing as a result of continued road development and ageing culverts. We conclude that the traditional management approach of road builders and regulatory agencies has failed to prevent the development of hanging culverts and fragmentation of small boreal streams in Alberta. We provide recommendations for future study and management of this growing problem.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".