Modern Pollen and Conifer Stomates from North-central Siberian Lake Sediments: Their Use in Interpreting Late Quaternary Fossil Pollen Assemblages
Bibliographic record
Abstract
To determine the modern relationship between pollen and stomate deposition and vegetation, surface sediments from 26 lakes along the Lena River in northeastern Siberia were analyzed for pollen and conifer stomate content. The lakes sampled, crossed a vegetation gradient from tundra, forest-tundra, to closed boreal forest. The pollen spectra of tundra lakes are dominated by Betula and Alnus. Cyperaceae and Poaceae are also abundant. Forest-tundra lakes are dominated by Betula and Alnus, but contain lower percentages of Artemisia than tundra lakes. Forest pollen spectra are also dominated by Betula and Alnus pollen, however, forest lakes contain greater percentages of Larix pollen. Principal components analysis indicates that forest and tundra sites were distinct from one another, but considerable overlap exists between forest-tundra and forest and tundra pollen assemblages. Larix stomates were abundant in all samples from regions where trees are currently present except for one lake. Small numbers of Larix stomates were found in tundra lakes, likely due to the redeposition of older material from eroding peat banks. It is likely that this process also contributed some older pollen to modern lake sediments as well. Principal components analysis was used to compare fossil samples from a lake-sediment core to the modern spectra. Early Holocene vegetation assemblages, dominated by herb and Betula shrub tundra and subsequent Larix forests, do not have modern pollen analogs in the lower Lena River region. Modern pollen analogs developed after 6 ka BP, when forest vegetation developed around the site. This was gradually replaced by modern tundra after 3.5 ka BP.
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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 | 0.003 | 0.002 |
| 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".