Quantifying historical, contemporary, and anthropogenic influences on the genetic structure and diversity of lake sturgeon (Acipenser fulvescens) populations in northern Ontario
Bibliographic record
Abstract
Lake sturgeon (Acipenser fulvescens) are a species of conservation concern across their range, with impoundments and exploitation acting as significant impediments to their recovery. Northern Ontario contains some of the few remaining intact systems with healthy lake sturgeon populations because of low exploitation and undammed, unregulated watersheds. Although preliminary research suggests that northern Ontario lake sturgeon are genetically distinct from depleted sturgeon populations in the Great Lakes basin, this region represents a large gap in our understanding of genetic diversity of lake sturgeon. Recent identification of hydroelectric development potential in four major rivers in northern Ontario may pose future threats to these populations. The two goals of this study were to address the lack of genetic information from a significant portion of the species range, and to compare levels of local and regional diversity between relatively intact systems and more intensively studied (and fragmented) areas to the south. Comparison of 23 putative populations from three major drainages identified three divergent genetic groups which corresponded with historical drainages more than contemporary watersheds. The three groups reflected colonization from Mississippian and Missourian glacial refugia, as well as a novel third group in western Ontario characterized by low genetic variability. Diversity within populations similarly reflected historical influences more than anthropogenic stressors, including impoundments and population abundances resulting from harvest. Genetic similarities among geographically separated populations within major drainages underscore their historical connections, reflecting lake sturgeon dispersal abilities and the importance of habitat connectivity.
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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 | 0.001 |
| 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) | 0.000 | 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 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".