Resolving Stock Structure of Sauger (Sander canadensis) in Manitoba, Canada using Biometric, Isotopic, and Genetic Approaches
Bibliographic record
Abstract
Many sauger (Sander canadensis) populations in Manitoba have declined in numbers and biomass. Fisheries managers have proposed a province-wide sauger management plan to protect and restore sauger populations, but they are uncertain how sauger populations should be defined and to what extent they may interact. In this thesis, I used a multifaceted approach to resolve population structure and identify migratory corridors of sauger in Manitoba. First, I mined biometric data from several long-term monitoring datasets to calculate life history indices for sauger stocks across 29 waterbodies. Sauger growth generally decreased and the age at 50% maturity increased among lakes of increasing latitude. This trend was also observed within Lake Winnipeg, yet the length at 50% maturity remained constant. Sauger grew exceptionally fast in Lake Manitoba and Lake Winnipegosis and matured at an early age. Next, I performed a stable isotope analysis (13C and 15N) of sauger tissue to investigate contemporary sauger migration throughout the Lake Winnipeg watershed. Sauger from Lake Winnipeg, Lake Manitoba, and Lac du Bonnet occupied distinct isotopic niches, and I identified several possible migrants from Lake Manitoba and the Winnipeg River in Lake Winnipeg. Finally, I used microsatellites to assess the genetic health and structure of sauger stocks across Manitoba. Genetic diversity within sample populations was moderate to high, and incidence of inbreeding and hybridization with walleye (Sander vitreus) was low. I identified four broad genetic sauger stocks: Lake Winnipeg; Lake Manitoba and Lake Winnipegosis; the Red and Assiniboine Rivers; and the Churchill and Saskatchewan Rivers. Gene flow between Lake Winnipeg and Lake Manitoba stocks is minimal. These findings will assist managers in defining stock management units and optimizing management efforts for sauger populations in Manitoba.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".