Effects of the abundance of spawning sockeye salmon (<i>Oncorhynchus nerka</i>) on nutrients and algal biomass in forested streams
Bibliographic record
Abstract
We used natural variation in sockeye salmon (Oncorhynchus nerka) spawner biomass among sites and years in three undisturbed, forested watersheds in interior British Columbia to test the hypotheses that salmon were a major source of particulate organic matter inputs to the streams and that carcass biomass determined stream-water nutrient concentrations and epilithic algal production. Sockeye carcasses were retained at the spawning sites, primarily (7580%) by large woody debris (LWD) or pools formed by LWD. The abundance and distribution of sockeye salmon determined stream-water nutrient concentrations and epilithic chlorophyll a concentrations during late summer and early fall when most primary production occurred in the oligotrophic streams. Periphyton accrual rates were elevated at sites with high salmon biomass. Peak chlorophyll a concentration increased with increasing carcass biomass per unit discharge above a threshold value to reach maxima 10-fold greater than ambient levels. Epilithic algae were dominated by a few common, large diatom taxa. Salmon carcasses were the dominant source of particulate organic carbon in low gradient stream reaches. Nutrient budget modeling indicated that most of the salmon-origin nutrients were exported from the spawning streams or removed to the terrestrial ecosystem; diffuse impacts may extend over a much larger area than simply the sites used for spawning.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".