Climate change modulates structural and functional lake ecosystem responses to introduced anadromous salmon
Bibliographic record
Abstract
We integrated limnological, paleolimnological, and fisheries analyses in Tuya Lake, British Columbia, Canada, to explore the effects and interactions of climate warming and sockeye salmon introductions on northern lake ecology. We tracked millennially unprecedented, climate-correlated changes in inferred lake production, stratification, and trophic structure since the mid-1800s, most likely resulting from declining ice cover and enhanced stratification. Post-1970s algal (diatom) species turnover, coeval across several remote northern Cordilleran lakes, marked an apparent increase in warming and the induction of inferred nitrogen deficiencies in Tuya Lake. Lower post-stocking phosphorus (P) and nitrogen (N) concentrations and a strong P-modeled salmon biomass correlation (r2 = 0.87) indicated salmon production reduced epilimnetic nutrient availability. Post-stocking chlorophyll reductions, late-summer algal dominance by heterocystous cyanobacteria and low-N-tolerant diatoms, and a strong chlorophyll-modeled salmon biomass correlation (r2 = 0.87) indicated that salmon influenced lake productivity, most likely by enhancing climate-induced N-deficiencies. Predicted smolt-biomass nutrient exports were minimal, with post-introduction nutrient reductions likely related to planktivory and enhanced sedimentation losses. Our study highlights how climate warming changes northern lake ecosystem structure and functioning, influencing responses to subsequent stresses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".