A transboundary dilemma: dichotomous designations of Atlantic halibut status in the Northwest Atlantic
Bibliographic record
Abstract
Abstract We investigated conflicting perspectives over a transboundary species (Atlantic Halibut-Hippoglossus hippoglossus L.) assumed to be one population spanning the border separating the USA and Canada. In Canada, the fishery is certified as sustainable by the international Marine Stewardship Council (2013). In the USA, that same population is listed as a “Species of Concern” under the US Endangered Species Act (1973). There are fishery-independent trawl surveys conducted by both USA and Canada on juvenile halibut abundance across the border. The data are sorted and both nations use their own jurisdictional boundaries to define the geographical area of their separate stock assessments. Here, we undertake a spatially unified, in-depth comparison of juvenile halibut distribution and abundance, and quantify the amount of suitable habitat for halibut across both sides of the border from 1965 to 2014. Juvenile halibut abundance was, on average, five times greater in Canada than in USA waters. The median per cent of occupied sets in Canada was about four times greater than in the US (2.5%). These differences could not be explained by the availability of “suitable” habitat. The lack of halibut in US waters, in contrast to Canada, suggests a finer-scale stock structure exists and that halibut have not re-established in the USA due to historical serial overfishing. A gradient from high occupancy of halibut in Canada to lower occupancy in the USA is evident, suggestive of connectivity between the two areas and supported by a lag correlation analysis of temporal abundance trends. The USA may now be a sink to Canada's source of halibut. While both countries have been correct in their individual assessments, a bilateral assessment of halibut would benefit both nations, and could include analyses of how fishing patterns in Canada will influence the magnitude and speed of halibut re-colonization in the USA.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".