Differing marine animal biomass shifts under 21st century climate change between Canada’s three oceans
Bibliographic record
Abstract
Under climate change, species composition and abundances in high-latitude waters are expected to substantially reconfigure with consequences for trophic relationships and ecosystem services. Outcomes are challenging to project at national scales, despite their importance for management decisions. Using an ensemble of six global marine ecosystem models we analyzed marine ecosystem responses to climate change from 1971 to 2099 in Canada’s Exclusive Economic Zone (EEZ) under four standardized emissions scenarios. By 2099, under business-as-usual emissions (RCP8.5) projected marine animal biomass declined by an average of −7.7% (±29.5%) within the Canadian EEZ, dominated by declines in the Pacific (−24% ± 24.5%) and Atlantic (−25.5% ± 9.5%) areas; these were partially compensated by increases in the Canadian Arctic (+26.2% ± 38.4%). Lower emissions scenarios projected successively smaller biomass changes, highlighting the benefits of stronger mitigation targets. Individual model projections were most consistent in the Atlantic and Pacific, but highly variable in the Arctic due to model uncertainties in polar regions. Different trajectories of future marine biomass changes will require regional-specific responses in conservation and management strategies, such as adaptive planning of marine protected areas and species-specific management plans, to enhance resilience and rebuilding of Canada’s marine ecosystems and commercial fish stocks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".