Poissons sans frontiers: Comparing contiguous surveys for major ecological and commercial species in the Northwest Atlantic, with a focus on trends, synchronies and coherences
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Fish know no national borders, yet for a plethora of reasons, we delineate fish into distinct population or stock units that often reflect human institutional borders more so than biological factors. Across a wide variety of taxa, population dynamics can be synchronous over a range of spatial scales. Common patterns are generally attributed to a meta-population structure supported through dispersal, or a common response to large scale environmental forcing. In the NW Atlantic, common species occur in the broader Gulf of Maine Area (GOMA), yet the area is managed in the south by the US and in the north by Canada. Many species occurring in the GOMA are subject to common forcing resulting in coherent patterns of recruitment and growth among distinct populations. To evaluate these issues, we compared six survey biomass time series of 19 representative species from US and Canadian waters. We further explored the biomass trends of aggregate groups such as the top 13 groundfish or total fish biomass. Many of these individual species and aggregates species groupings showed synchronous trends. For instance, Canadian and US populations of haddock, thorny skate and white hake have comparable trends within species. Conversely, some species show differing survey time series trends and asynchronous event timing, suggesting forcing processes may influence these species differently. Collectively our results demonstrate the value of comparing time-series for common species from contiguous ecosystems, with the potential to elucidate the relative importance of major factors affecting such 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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.002 |
| 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".