POPULATION DYNAMICS AND MOVEMENT OF \nCHANNEL CATFISH \nIN THE RED RIVER OF THE NORTH
Bibliographic record
Abstract
Channel Catfish are widely distributed across North America and highly valued as a sport fish and for food. While most Channel Catfish fisheries are managed under liberal harvest regulations, the Red River of the North (Red River) in Manitoba, Canada is managed with restrictive harvest regulations to promote a trophy fishery. Two barriers (dams) are present on the main stem of the Red River and may fragment the population to some degree. My objectives were to: 1) analyze population dynamics of the trophy Channel Catfish population on the lower Red River, 2) compare population characteristics of Channel Catfish in selected reaches throughout the Red River in Manitoba, and 3) determine movement characteristics of Channel Catfish and the permeability of a dam on the lower Red River. We compared our results to the most recent studies on Channel Catfish in the Red River, and also to range-wide age, growth, and mortality statistics. Channel Catfish in the lower Red River commonly reached ages > 20, grew slowly, and had a low mortality rate. Trophy Channel Catfish were most abundant below the dam on the lower river. The size structure within the most upstream reaches we studied were predominantly comprised of small- and intermediate-sized Channel Catfish. We determined the dam is passable by large Channel Catfish (>600 mm), but may be an impediment to small Channel Catfish. My mark-recapture data indicated Channel Catfish can move long distances, where upstream movements > 500 kilometers were common for large Channel Catfish. This research provides insight into the age, growth, and mortality of a trophy fishery for Channel Catfish. We believe restrictive harvest regulations are adequately maintaining the desired age structure and size structure of Channel Catfish in the lower Red River and by consequence, sustaining one of the premier fisheries in North America.\nAdvisor: Mark A. Pegg
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".