Comparison of the green crab (Carcinus maenas) population trends of different Nova Scotian sites and comparison of green crab management strategies from Atlantic Canada and the U.S.
Bibliographic record
Abstract
Despite the green crabs (Carcinus maenas) devastating ecological impacts, there have been few studies that have done a green crab population comparison between N.S sites. This study will aim to do a comparison analysis between various sites by analysing the number of crabs caught, the sex ratio changes, and the carapace width changes over time. This study will also compare the different management strategies (eradication, prevention, and control) practised in both Atlantic Canada and the U.S. Data of the green crabs from Kejimkujik Seaside and Malagash Wharf were collected by Parks Canada manager Gabrielle Beaulieu (Kejimkujik Seaside) and Dalhousie Professor Scott Jefferey (Malagash Wharf). Both sites used standard procedures for capturing and collecting the data from the crabs. A regression analysis was conducted to determine the significance of the time trends for each individual site, and a comparison of two regressions was used to compare and determine the significance between the time trends of two sites. In this study, three comparisons of the various time trends were made: Little Port Joli sub-sites (lagoon, basin, river), Little Port Joli and St Catherine's River, and Kejimkujik Seaside (Little Port Joli + St Catherine's River) and Malagash Wharf. The majority of the sites, with the exception of the basin (from Little Port Joli) and Malagash Wharf, showed a decrease in the number of crabs over time. The sample of green crabs caught at all sites showed a increased proportion of males captured compared to females over time. Lastly, all sites (with the exception of Malagash Wharf) experienced an increase in the average carapace size over time. Both Atlantic Canada and the U.S have similar management strategies in dealing with green crabs (prevention, eradication, and control), however both countries are currently trying to establish a fishery market for this species.
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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 | 0.001 | 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".