Observations regarding Lake Sturgeon spawning below a hydroelectric generating station on a large river based on egg deposition studies
Bibliographic record
Abstract
Abstract Spawning behaviour of the Lake Sturgeon ( Acipenser fulvescens ) in large rivers is poorly understood, complicating the approach to fish‐friendly hydroelectric design and mitigation. In 2006, dam safety concerns prompted the need to modernize the spillway infrastructure of the 100‐year old Pointe du Bois Generating Station on the Winnipeg River, Manitoba. The associated regulatory process provided an opportunity to study Lake Sturgeon spawning in a location characterized by water depths >5 m, high velocities, and hydraulic instability. Over six spawning periods (2007–2012), a wide range of flow conditions occurred, and spawning was documented using egg mats in both the powerhouse tailrace and downstream of the spillway rapids. Herein, we consider “…. the preferential utilization by sturgeon of certain ranges of the physical variables studied, but within habitats considered favourable for the reproduction of the species ” conclusion forwarded by La Haye et al. as our working hypothesis. Overall, 27,362 of 30,085 (90.1%) Lake Sturgeon eggs were captured during the primary spawning intervals, defined based on 6‐day annual periods encompassing the date of peak deposition. Of the 2,200 mats retrieved, 74.4% captured 0 eggs, 12.0% captured 1–5 eggs, 5.2% captured 6–25 eggs, 6.1% captured 26–99 eggs, and just 2.2% captured ≥100 eggs (high‐yield). Data were examined in relation to status‐quo habitat variables (depth, velocity, and substrate), as well as two additional variables hypothesized to have predictive power: distance from physical and/or energetic barriers and hydraulic complexity. Distance‐based analyses revealed upstream to downstream redistribution of eggs via flow. Spawning (as inferred based on high‐yield mats) was spatially discrete during each spawning period as opposed to well‐distributed among habitats broadly considered to be suitable for the species. We suggest that the current‐edges located proximal to physical and/or energetic barriers (i.e., at the upstream extent of usable habitat) drive Lake Sturgeon spawning site selection in large rivers, and advise caution prior to making fine‐scale inferences when only small quantities of Lake Sturgeon eggs are captured.
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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 | 0.000 | 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 | 0.002 | 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) | 0.000 | 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".