Continental-scale nutrient and contaminant delivery by Pacific salmon
Bibliographic record
Abstract
The movement of large amounts of nutrients by migrating animals has ecological benefits for recipient food webs1,2 that may be offset by co-transported contaminants3,4. Salmon spawning migrations are archetypal of this process, carrying marine-derived materials to inland ecosystems where they stimulate local productivity but also enhance contaminant exposure5–7. Pacific salmon abundance and biomass are higher now than in the last century, reflecting substantial shifts in community structure8 that probably altered nutrient versus contaminant delivery. Here we combined nutrient and contaminant concentrations with 40 years of annual Pacific salmon returns to quantify how changes in community structure influenced marine to freshwater inputs to western North America. Salmon transported tonnes of nutrients and kilograms of contaminants to freshwaters annually. Higher salmon returns (1976–2015) increased salmon-derived nutrient and contaminant inputs by 30% and 20%, respectively. These increases were dominated by pink salmon, which are short-lived, feed lower in marine food webs than other salmon species, and had the highest nutrient-to-contaminant ratios. As a result, the delivery of nutrients increased at a greater rate than the delivery of contaminants, and salmon inputs became more ecologically beneficial over time. Even still, contaminant loadings may represent exposure concerns for some salmon predators. The Pacific salmon example demonstrates how long-term environmental changes interact with nutrient and contaminant movement across large spatial scales and provides a model for exploring similar patterns with other migratory species9. Pacific salmon transport of nutrients and contaminants to freshwaters increased by 30% and 20%, respectively, between 1976 and 2015, an increase dominated by pink salmon, which had the highest nutrient-to-contaminant ratios.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".