Effects of climate change and industrialization on Lake Bolshoe Toko, eastern Siberia
Bibliographic record
Abstract
Abstract Industrialization in the Northern Hemisphere has led to warming and pollution of natural ecosystems. We used paleolimnological methods to explore whether recent climate change and/or pollution had affected a very remote lake ecosystem, i.e. one without nearby direct human influence. We compared sediment samples that date from before and after the onset of industrialization in the mid-nineteenth century, from four short cores taken at water depths between 12.1 and 68.3 m in Lake Bolshoe Toko, eastern Siberia. We analyzed diatom assemblage changes, including diversity estimates, in all four cores and geochemical changes (mercury, nitrogen, organic carbon) from one core taken at an intermediate water depth. Chronologies for two cores were established using 210Pb and 137Cs. Sedimentation rates were 0.018 and 0.033 cm year−1 at the shallow- and deep-water sites, respectively. We discovered an increase in light planktonic diatoms (Cyclotella) and a decrease in heavily silicified euplanktonic Aulacoseira through time at deep-water sites, related to more recent warmer air temperatures and shorter periods of lake-ice cover, which led to pronounced thermal stratification. Diatom beta diversity in shallow-water communities changed significantly because of the development of new habitats associated with macrophyte growth. Mercury concentrations increased by a factor of 1.6 since the mid-nineteenth century as a result of atmospheric fallout. Recent increases in the chrysophyte Mallomonas in all cores suggested an acidification trend. We conclude that even remote boreal lakes are susceptible to the effects of climate change and human-induced pollution.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".