Abundance and spatial distribution of <i>Mysis diluviana</i> in Lake Ontario in 2008 estimated with 120 kHz hydroacoustic surveys and net tows
Bibliographic record
Abstract
Mysids are an important component of Great Lakes foodwebs, both as a prey for fish and as a predator on zooplankton. We monitored mysid abundance in Lake Ontario using lake-wide hydroacoustics data and vertical net hauls collected 1–5 August 2008 during the Ontario Ministry of Natural Resources and New York State Department of Conservation forage fish survey. Acoustic volume backscattering strength was highly correlated with both density and biomass of mysids although the correlation with biomass was stronger. The slopes of these relationships were not significantly different from theory (0.10) indicating a linear relationship between abundance and backscattering strength. Size structure significantly affected the relationship between backscattering strength and density but not between backscattering strength and biomass. Average target strength for areas with small mysids was −91.9 dB per mysid, and in areas with both small and large mysids it was −88.2 dB per animal. Acoustic estimates for Lake Ontario calculated with these regressions provided a lake-wide estimate weighted by lake area within depth intervals, of 228 mysids m−2 (CV 17.6%) and 0.93 g dw m−2 (CV 12.9%). Density and biomass in 14 net hauls averaged 316 mysids m−2 (range 0 to 1113) and 1.35 g dw m−2 (range 0 to 3.89). Mysid biomass was 33% of the biomass of other crustacean zooplankton in the summer of 2008. As in 2005, areas of low mysid abundance were detected in the middle of the transects and along the north shore. Lakewide mysid abundance in the summer of 2008 was higher than in a similar acoustic survey in the summer of 2005 and in whole-lake autumn 2000–2007 net surveys, suggesting that mysids are persisting in Lake Ontario and abundant relative to other Great Lakes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 teacher head, 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".