Analysis of the enhanced snow crab survey for monitoring conservation priorities in St. Anns Bank Marine Protected Area
Bibliographic record
Abstract
St. Anns Bank, situated offshore of Cape Breton, Nova Scotia/Unama’ki, was designated as a Marine Protected Area (MPA) under the Oceans Act in 2017 to conserve and protect benthic, demersal, and pelagic habitats, in addition to the high biodiversity and productivity in the area. Since 2015, the annual Snow Crab Survey (SCS) has been supplemented with enhanced stations inside and adjacent to the MPA, which, in addition to Snow Crab, provide length and weight data on fish and invertebrate bycatch, as well as diet data collected from fish stomachs. Here we investigated trends in biomass, species richness, and animal size data inside and outside the MPA between 2015-2023, as well as community composition and predator diets. Species richness from the SCS continues to increase as additional stations are sampled. Power analyses of the trawl data to investigate catch per unit effort in several key species revealed that additional stations would be required to adequately monitor changes in animal abundance and richness in the MPA at high power (>80%). Overall, the SCS provides vital information for monitoring the MPA’s conservation objectives related to biodiversity and productivity, but additional years and stations or new supplementary data streams will be needed to confidently identify trends over time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".