Assessing indirect biodiversity conservation benefits of fisheries closures in the Gulf of St. Lawrence, Canada
Bibliographic record
Abstract
Marine biodiversity loss is a pressing global issue, intensified by human activities and climate change. Complementary to marine protected areas (MPAs), Other Effective Area-Based Conservation Measures (OECMs) have emerged as a key tool to mitigate this loss by providing long-term biodiversity protection. However, while OECMs primarily target specific taxa, they can also offer indirect biodiversity conservation benefits (BCBs) to a wider range of taxa. In this study, we assess the indirect BCBs of eleven OECMs in the Gulf of St. Lawrence, focusing on their role in supporting the life-history processes of commercially important species such as Atlantic halibut, Greenland halibut, and redfish. We apply an integrated assessment that combines knowledge and data previously unconnected to provide information to support OECM management. Our analysis reveals that eight of the eleven OECMs overlap with potential spawning habitats for these species, suggesting important life-history benefits. However, projected climate-driven changes in bottom temperature, oxygen concentration, and pH levels pose a threat to these habitats, potentially undermining the long-term effectiveness of OECMs. These findings underscore the need for adaptive management strategies that incorporate climate-informed ecosystem indicators and broaden the conservation focus beyond economically important species. Such approaches are crucial to ensuring that OECMs continue to provide both direct and indirect BCBs in the face of accelerating climate change, thereby contributing to global marine biodiversity conservation efforts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".