The cumulative impacts of climate change on Fraser River sockeye salmon (<i>Oncorhynchus nerka</i>) and implications for management
Bibliographic record
Abstract
Anadromous Pacific salmon ( Oncorhynchus spp.) are vulnerable to climate change in both freshwater and marine habitats. I use a qualitative model to assess the cumulative effects of climate change across life stages and generations of Fraser River sockeye salmon ( Oncorhynchus nerka ) and other salmon species. The effects of climate change most relevant to Fraser River sockeye include warming of freshwater and marine habitats, altered hydrology in spawning rivers, reduced productivity in nursery habitats, and changed distribution and phenology of predator and prey species. The weight of evidence indicates that these changes will negatively affect growth and survival of Fraser River sockeye at all life stages. Effects on one life stage will also carry forward to heighten adverse effects at subsequent life stages and across generations so that the cumulative impact is greater than the impact on individual stages. Salmon can adapt to climate change but probably not enough to sustain productivity. In the south, focus of policy and management on conserving and enhancing resilience is needed to retain some salmon production. At the same time, Arctic habitats are becoming accessible to salmon. Management in the Arctic should protect potentially productive habitats from development and facilitate their colonization by Pacific salmon.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".