Quantifying survival and behaviour of hatchery-reared juvenile bloater stocked across bathymetric depths in Lake Ontario
Bibliographic record
Abstract
Over 20 million native and non-native fishes are stocked into the Great Lakes annually as part of restoration initiatives and to support commercial and recreational fisheries. Bloater (Coregonus hoyi), a deep-water planktivore that was extirpated from Lake Ontario in the 1980s, has been consistently stocked in the lake since 2012 by Canadian and American natural resource agencies with the goal of producing a self-sustaining population. Previous research has highlighted challenges with stocking such as poor survival, attributed to high predation, potential maladaptive behaviour and barotrauma resulting from introducing a hatchery-reared species into a foreign environment. To address these survival challenges, bloater in this study were tagged with acoustic predation tags and stocked over three bathymetric depths in Lake Ontario (5, 50, and 100 m) to assess survival, behaviour, and to quantify sources of mortality at each depth. Coupling high resolution receivers (HR2) with predation tags permits fine-scale auto-estimation of predation-related mortality, in turn improving detailed survival estimates of stocked fish, specifically juveniles. Time-to-event modeling indicated a low survival rate (12%) in the first three-weeks post-stocking for individuals within the study area. Initial data suggested that predation played a dominant role in shallower depths, while mortality at deeper depths could be linked to barotrauma, although, no statistical differences were found in survival between the three depths. Relative position estimates demonstrated rapid dispersion of bloater post-release, with movement rates suggesting a tendency to migrate towards deeper waters. Continued investigation into the movement and predation of bloater post-release will be used to determine the survival of the stocked population. This enhanced understanding of the movement and mortality of stocked fish will play a crucial role in refining stocking strategies and assessing the overall restoration potential for bloater in Lake Ontario.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".