Recent sedimentary legacy of sockeye salmon (Oncorhynchus nerka) and climate change in an ultraoligotrophic, glacially turbid British Columbia nursery lake
Bibliographic record
Abstract
Paleolimnological studies of sockeye salmon ( Oncorhynchus nerka ) nursery lakes have shown that lake trophic status is often regulated by climate and harvest via marine-derived nutrients (MDN) from adult spawners. However, these controls are not well understood for sockeye nursery lakes in coastal British Columbia, many of which are ultraoligotrophic and glacially turbid. We examined climate, sockeye population dynamics, and sedimentary indicators of lake algal production from 1958 to 2005 using a radioisotope-dated sediment core from Kitlope Lake, British Columbia. Despite high sedimentation rates (~4.7 mm·year–1), significant influence of terrestrial and aquatic organic matter from the main tributary, and the lowest mean (± standard deviation) δ15N (–0.28‰ ± 0.79‰; a proxy for MDN flux) yet reported from a sockeye nursery lake, sedimentary δ15N, C–N ratio, and fossil pigments were coherent with order-of-magnitude changes in sockeye escapements. Moreover, air temperatures were positively correlated with δ15N, indicating a climate influence counteracting declines of MDN import related to declining spawner returns. Despite elevated production potential, Kitlope Lake remains nutrient-limited with a declining sockeye population, and the productivity of this system would benefit from increased sockeye returns.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".