Assessing Walleye Movement among Reaches of a Large, Fragmented River
Bibliographic record
Abstract
Abstract Movement of Walleyes Sander vitreus among reaches in a large, fragmented river was assessed by employing a combination of tagging, telemetry, and genetic analyses. Our objective was to determine whether the existing dams in the Ottawa River, Canada, were impeding Walleye movement among river reaches. Movement was predicted to be greater among contiguous, unimpounded reaches in comparison with impounded reaches. In total, 1,586 Walleyes were tagged in five river reaches, and 35 Walleyes were tracked by radiotelemetry in three river reaches. Genetic analyses (linkage disequilibrium, genetic divergence and diversity, effective population size, genetic structuring, bottlenecks, and migration rates) were conducted on 221 Walleyes from seven river reaches by genotyping at six microsatellite loci. Based on both tag returns (return rate = 12.1%) and telemetry data, there was limited movement among river reaches whether impounded or unimpounded, and movement was predominately upstream. Genetic analyses identified population structuring, with three genetic groupings occurring within the river. There was also evidence of genetic isolation in an upper reach of the river, indicating potential residual effects of a bottleneck or genetic drift. Our results suggest that existing dams may not act as significant barriers to Walleye movement in the Ottawa River, but limited movements appear to maintain genetic diversity and minimize genetic drift. Consequently, maintaining the genetic attributes of Walleye stocks in segmented rivers may require some level of fish passage. Received July 9, 2012; accepted January 16, 2015
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".