Variable effects of marine‐derived nutrients on algal production in salmon nursery lakes of Alaska during the past 300 years
Bibliographic record
Abstract
We measured historical changes in sedimentary δ15N and fossil pigments in four lakes with anadromous semelparous salmon and two reference lakes to quantify the degree to which the flux of marine‐derived nutrients (MDNs as N isotopes) regulate algal production (as pigments). During the past 300 yr, production of the predominant algae (diatoms) was positively correlated (r = 0.42–0.93, p < 0.02) with sedimentary δ15N in nursery lakes of sockeye salmon (Oncorhynchus nerka) but was inversely correlated with sedimentary δ15N (r = 20.71 to 20.73, p < 0.0001) in reference lakes that lacked migratory fishes. Overall, the pigment‐δ15N correlation during the 20th century was strongly correlated with both mean densities of spawning sockeye salmon during 1956–2000 (r = 0.97, p < 0.002) and the fraction of total ecosystem N derived from salmon during 1900‐2000 (r = 0.98, p < 0.001). Together these patterns suggest that the sign of the δ15N‐pigment correlation can be used to distinguish among lakes or periods of time in which algal production is regulated mainly by MDN influx (positive correlation) or other factors (negative correlation). Tests of this hypothesis revealed that the degree to which MDNs regulated algal production in nursery lakes varied greatly since 1700, with significant periods of weak control even in lakes with abundant salmon. Further, when considered at the landscape scale, the importance of MDNs to individual lakes varied substantially through time and in space, with little evidence of synchrony among sites or catchments.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".