Examining the natural and disturbed behaviours of Alewife (Alosa pseudoharengus) using hydroacoustic surveys in Lake Ontario
Bibliographic record
Abstract
In Lake Ontario, Alewife are the primary prey for salmonids, which provide a popular and socio-economically important recreational fishery. There is concern with regards to whether the Alewife population has the ability to support the predatory demand in Lake Ontario after a crash in the Alewife and predator populations occurred in Lake Michigan. To avoid such a crash, it is imperative that agencies working on Lake Ontario have accurate methods of assessing fish populations. Mobile hydroacoustic surveys of the lake began in 1991 as a method to assess the Alewife population, however, there is growing concern about the accuracy of these estimates. Fish in hydroacoustic surveys can appear to be smaller when oriented off-axis, as is common with fish displaying boat avoidance behaviour. The mobile assessment estimates are made using size thresholds to classify targets in the survey and Alewife which are diving may be appearing too small to be correctly classified. Using information from mobile, as well as stationary up-looking surveys, this study assesses how Alewife react to the survey vessel, and how the reactions may be impacting their observed target strength. The results indicate that Alewife are observed at smaller sizes in the mobile survey than would be expected. The mobile survey observed fish at deeper depths and the behaviour of the fish was indicative of boat avoidance. Fish from the mobile survey swam faster and more linearly than fish from the stationary survey. Consecutive targets in tracks from the mobile survey also increased in depth with a more negative track tilt. There were no strong predictors of changes in target strength tested with linear models which could be used as correction factors in the current dataset. In future studies, analysis of variables such as the true orientation of the fish may provide appropriate correction factors for this type of data. The current survey approach provides a valuable index of “relative” Alewife abundance from year to year, however, additional research will be required to provide more accurate estimates of the absolute abundance of Alewife 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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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".