Spatial correlation patterns in coastal environmental variables and survival rates of salmon in the north‐east Pacific Ocean
Bibliographic record
Abstract
We examined spatial correlations for three coastal variables [upwelling index, sea surface temperature (SST), and sea surface salinity (SSS)] that might affect juvenile salmon ( Oncorhynchus spp.) during their early marine life. Observed correlation patterns in environmental variables were compared with those in survival rates of pink ( O. gorbuscha ), chum ( O. keta ), and sockeye ( O. nerka ) salmon stocks to help identify appropriate variables to include in models of salmon productivity. Both the upwelling index and coastal SST were characterized by strong positive correlations at short distances, which declined slowly with distance in the winter months, but much more rapidly in the summer. The SSS had much weaker and more variable correlations at all distances throughout the year. The distance at which stations were no longer correlated (spatial decorrelation scale) was largest for the upwelling index (> 1000 km), intermediate for SST (400–800 km in summer), and shortest for SSS (< 400 km). Survival rate indices of salmon showed moderate positive correlations among adjacent stocks that decreased to zero at larger distances. Spatial decorrelation scales ranged from approximately 500 km for sockeye salmon to approximately 1000 km for chum salmon. We conclude that variability in the coastal marine environment during summer, as well as variability in salmon survival rates, are dominated by regional scale variability of several hundred to 1000 km. The correlation scale for SST in the summer most closely matched the observed correlation scales for survival rates of salmon, suggesting that regional‐scale variations in coastal SST can help explain the observed regional‐scale covariation in survival rates among salmon stocks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".