Biotelemetry Provides New Insights About the Migration of Adult Walleye in Lake Ontario
Bibliographic record
Abstract
Walleye (Sander vitreus) populations throughout the Laurentian Great Lakes complete annual migrations between spawning and foraging habitats. Until recently, information regarding these migrations was collected using traditional assessment methods and fisheries-dependent data, which can be biased based on the distribution of effort. Advances in tracking technology and electronic tagging techniques now provide the tools to collect information from free-swimming individuals, including those from highly mobile species. This thesis examined the timing, extent, and patterns of migration for adult walleye that spawn in the Bay of Quinte and migrate through eastern Lake Ontario. The within-individual repeatability of these annual migrations was determined to be high at the temporal, spatial, and combined spatiotemporal levels. Tagging fish with a combination of acoustic transmitters and pop-off data storage tags (pDSTs) provided insights into the benefits and limitations of each method and identified a novel diving behaviour for this species. Combining the data from both methods provided an overview of the seasonal temperatures, depths, and activity levels experienced by these fish across an entire annual migration. There were sex-based differences in the timing, extent, area use, and vertical activity rates during the annual migration, as well as the number of dives per day during the summer. Within-individual repeatability of migrations was not influenced by sex or size, however it was different between spawning locations. For most studies, acoustic transmitters can provide estimates of thermal and depth preferences, but they are highly influenced by receiver coverage, often omit extreme values, and cannot produce accurate measures of vertical activity. This thesis improves our understanding of migratory behaviour in freshwater fish, and the degree to which they are able to repeat these behaviours. It outlines the benefits and limitations of new methods that can be used to collect high-resolution data throughout the year. Future studies should examine the drivers behind these movements, and the mechanisms that these fish use to navigate across large inland waterbodies.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".