Effects of environmental change, fisheries and trophodynamics on the ecosystem of the western Scotian Shelf, Canada
Bibliographic record
Abstract
The dynamics of marine ecosystems, which are complex and non-linear, are difficult to predict.Like most marine ecosystems, NW Atlantic systems have been subjected to centuries of fisheries exploitation as well as environmental and internal trophodynamic drivers.By reducing the complexity of the western Scotian Shelf ecosystem to 57 functional living groups, we were able to reproduce many of its observed dynamics, such as major decadal trends in abundance and mortality for most groups, and explore the relative strength within the triad of drivers using a trophodynamic model.We explored potential biophysical drivers through the use of a primary production anomaly, generated by a model fitting routine.The estimated primary production series was negatively correlated with the spring sea surface temperature for the Scotian Shelf Large Marine Ecosystem, a stratification index and the Atlantic Multidecadal Oscillation (AMO) index.The aggregated biomass of the main resident fish species was also negatively correlated with the AMO index.All 3 drivers contribute to shaping the observed biological and ecological changes of the western Scotian Shelf.This has substantial implications for fisheries management: (1) climate change (global warming) may negatively affect productivity at the species and ecosystem level; (2) these effects may be magnified due to the combined effects of trophic interactions and exploitation; and (3) fisheries assessments must account for environmental and climate change, and for the broader ecosystem effects.Failing this, fisheries should be managed well below their single-species reference points.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".