Deglacial records of terrigenous organic matter accumulation off the Yukon and Amur rivers based on lignin phenols and long-chain n-alkanes
Bibliographic record
Abstract
Abstract. Arctic warming and sea level change will lead to widespread permafrost thaw and subsequent mobilization. Sedimentary records of past warming events during the last glacial–interglacial transition can be used to study the conditions under which permafrost mobilization occurs. Long-chain n-alkyl lipids and lignin phenols are two types of biomarkers excellently suited for the reconstruction of terrestrial higher plant vegetation, as they are derived from epicuticular waxes and from the major rigidifying material of higher plants. For the Okhotsk and Bering Seas off the mouths of the Amur and Yukon rivers, respectively, published records reported the temporal variations of n-alkyl lipid accumulation recording mostly erosive processes. Surface runoff, vegetation type, and degree of organic matter degradation as reflected by lignin have not been investigated so far. Here, we present new lignin phenol records from marine sediment cores and compare them with previously published lipid biomarker data from these two subarctic marginal seas. We find that in the Yukon Basin, vegetation change and wetland expansion began already in the early deglaciation (ED, 14.6–19 ka BP). This timing is different from observed changes in the Okhotsk Sea reflecting input from the Amur Basin, where wetland expansion and vegetation change occurred later in the Preboreal (PB). In the two basins, angiosperms contribution and wetland extent all reached maxima during the PB, both decreasing and stabilizing after the PB. We also find that the permafrost of the Amur Basin began to become remobilized in the PB. Retreat of sea-ice coupled with increased sea-surface temperatures in the Bering Sea during the ED might have promoted early permafrost mobilization. In both records, accumulation rates of lignin phenols and lipids are similar, suggesting that under conditions of rapid sea-level rise and shelf flooding, both types of terrestrial biomarkers are delivered by the same transport pathway.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".