How different is different? Defining management and conservation units for a problematic exploited species
Bibliographic record
Abstract
Discontinuous genetic structure is widely used to delineate local, regional, and phylogenetic groups within species for conservation and management purposes. We used microsatellite markers to assess the genetic distinctiveness of putative stocks and populations of lake whitefish ( Coregonus clupeaformis ) in Ontario waters. Analysis of spawning aggregations in eastern Lake Ontario showed fish from Chaumont Bay, New York, to be weakly differentiated from spawning whitefish in and near the Bay of Quinte, Ontario. No significant differences were found between lake- and bay-spawning aggregations within the Bay of Quinte. These same genetic tools were used to test the distinctiveness and evolutionary significance of Lake Simcoe lake whitefish as a designatable unit (DU) under guidelines established by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC). Although there was marked differentiation among populations from across Ontario, the Lake Simcoe population was closely allied with lake whitefish populations from Lake Ontario and Lake Huron, suggesting that a distinct status is not warranted on genetic grounds. This work demonstrates how assessing hierarchical diversity under COSEWIC’s framework can provide key information of the status of exploited populations for fishery management.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".