Spatial Ecology of Smallmouth Bass (Micropterus dolomieu) in the St. Lawrence River
Bibliographic record
Abstract
Smallmouth Bass (Micropterus dolomieu) are an important sportfish in the connected waters of Lake Ontario and the St. Lawrence River and provide large socio-economic benefits. For several reasons, including increasing pressure from competitive angling events, as well as uncertainty about the state of the Smallmouth Bass population arising from provincial and state assessment programs, there is an urgent need for more information about the spatial ecology of this species in these waters. The St. Lawrence River provides a unique opportunity to examine the spatial ecology of this species in habitats without a thermocline. This study used acoustic telemetry with pressure (dBar ≈ depth in m) and temperature sensors to examine the spatial ecology of Smallmouth Bass in the Forty Acre Shoal, which is a section of the St. Lawrence River that contains deep water areas (>20 meters) as well as an abundance of connected shallow (<20 meters) habitat. Smallmouth Bass occupied similar depths as found in previous studies, indicating that factors other than temperature might play an important role in summer depth selection. Home range estimates (95% and 50% Minimum Convex Polygons) were more than double the size of estimates from a nearby study in Lake Ontario. The home ranges of individuals in this study indicate that Smallmouth Bass caught during competitive fishing events are likely displaced well beyond their established home ranges where return rates and long-term effects are currently unknown. Preferred depths and activity rates varied seasonally, with winter characterized by deeper depths and reduced horizontal activity relative to summer. Large movements during winter were also found, providing further evidence that reduced movement and activity during winter may be facultative instead of obligate. This thesis improves our understanding of the spatial ecology of Smallmouth Bass within the St. Lawrence River and provides important considerations for assessing, managing, and conserving the Smallmouth Bass populations in large waterbodies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".