Influence of rainfall and beaver dams on upstream movement of spawning Atlantic salmon in a restored brook in Nova scotia, Canada
Bibliographic record
Abstract
Abstract In a restored, third‐order stream in northern Nova Scotia, Canada, we used redd counts over 12 years to examine the influence of beaver dams and the timing and intensity of autumn rains on spawning activity of Atlantic salmon. Most beaver dams in most years had no detectable effect on the distribution of spawning redds, but in 2004 the density of redds downstream from a three‐dam complex was significantly greater than that above, suggesting the dams were a barrier to many fish. A second complex of dams blocked salmon passage completely in 2003 and 2004 until they were notched to provide access upstream. The length of stream used by salmon for spawning was linearly correlated with total precipitation in the basin in October plus November (R2 = 0.60), to a ceiling of 325 mm, above which the fish had access to the entire brook, if beaver dams were notched. Number of redds in the whole brook was strongly correlated (R2 = 0.94) with the coefficient of variation (CV) of daily rainfall in October, but only for 7 of 11 years. This relationship disappeared when the impassable beaver dam complex failed in 2005, allowing salmon free access to 4 km of the upper brook. Variation in rainfall, and hence discharge, in this flashy brook evidently influences migration and spawning of Atlantic salmon in conjunction with channel blocking by beaver dams. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".