Acoustic survey index revision and standardization for the Atlantic Herring (Clupea harengus) 2009-2021 fall series in NAFO divisions 4RSw
Bibliographic record
Abstract
Hydroacoustic surveys provide the main input for the assessment of Atlantic herring (Clupea harengus) in Northwest Atlantic Fisheries Organization (NAFO) division 4R since 1991. While the time-series from 1991 to 2002 has been deemed acceptable based on available diagnostic tools, the series that began in 2009 encountered several methodological challenges which led to the rejection of its associated population model in 2020. Furthermore, the preliminary results of a recent tagging experiment suggest that herring in divisions 4R and 4Sw should be assessed together. Here, focusing on the surveys conducted in the combined divisions 4RSw in the fall from 2009 to 2021, we standardized three main aspects of the methods which are believed to have affected the comparability of estimates over time and among strata. Specifically, we (1) processed and analyzed the raw acoustic data files in a more consistent manner; (2) employed a target strength equation considered more representative for the present survey; and (3) revised the stratum surface areas, a key input for the estimation of the mean biomass by spawning component, stratum and survey. The largest deviations from original (unrevised) values occurred as a result of changing the target strength equation; this revision resulted in the density being reduced by a constant 65% across all strata and surveys. The effects of re analyzing acoustic data and strata surface areas were highly stratum- and survey-specific, but had an overall negligible impact on the interannual variability in abundance. Although the present revisions have allowed for many improvements in our understanding of the methods, there remains a perception that the “optimal” spatio-temporal window for conducting the survey – that corresponding to a peak in herring abundance – has been missed over many of the years considered herein. Therefore, the next steps for this work will focus on identifying a better timing for future surveys, as well as on predicting missing observations and optimizing the use of biological samples within each stratum.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".