Life-history Characteristics of Recreational Lake Trout (Salvelinus namaycush) Fisheries in Manitoba
Bibliographic record
Abstract
Contemporary data concerning lake trout (Salvelinus namaycush) populations have been lacking in the province of Manitoba for several decades. I compared life history characteristics (age, condition, growth, maturity, and survival) of lake trout from seven lakes in order to assess their present state. Furthermore, lake trout have been observed to have different ecotypes that exhibit different life-history traits and behaviours, therefore lake trout otolith morphology was compared to potentially identify suspected sympatric ecotypes in Clearwater Lake, Manitoba. Summer profundal index netting (SPIN) gillnets were set at varying depths during summer months in 2021 and 2022 to complete this project. Otolith morphology was compared using elliptic Fourier analyses. Length-at-age was back-calculated for lake trout individuals, and growth data was fitted by von Bertalanffy growth curves. Growth curves differed significantly across lakes based on several parameters (L8, K, t0, and w). Northern lakes had the propensity to hold trophy-sized lake trout, while southern lakes did not. Significant otolith morphological differences between suspected lake trout ecotypes within Clearwater Lake. However, it is not possible to ascertain that otolith morphological differences are a result of different ecotypes or differing growth rates. There was a notable scarcity of lake trout in most southern lakes, while northern lake trout populations appear to be healthy. Historical high fishing pressure might be a culprit associated with the poor status of several southern lake trout populations. Fisheries Manitoba should consider using the SPIN program to further evaluate lake trout fisheries in Manitoba.
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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 | 0.001 | 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".