Late Quaternary Vegetation Dynamics in the Southern Amazon Basin Inferred from Carbon Isotopes in Soil Organic Matter
Bibliographic record
Abstract
Abstract Carbon isotopes of soil organic matter (SOM) were used to evaluate and establish the chronology of the vegetation dynamics of an ecosystem presently composed of savannas surrounded by forests. The study was carried out on a 200-km transect along highway BR 319, on the border of Amazonas and Rondônia states, in southern Amazon, Brazil. Large ranges in δ13C values were observed in SOM collected from profiles in the savanna (−27 to −14‰) and forest regions (−26 to −19‰), reflecting changing distribution of13C-depleted C3forest and13C-enriched C4savanna vegetation in response to climate change. These results indicate that from about 17,000 to 900014C yr B.P., the study area was covered by forest vegetation. Between approximately 9000 and 300014C yr B.P., savanna vegetation expanded at the expense of the forest. Although the expansion of savanna did not occur with the same intensity along the study transect, this process was very clearly registered by13C-enrichment in the SOM. Since 300014C yr B.P., the carbon isotope data suggest that forested regions have expanded. This study adds to the mounting evidence that extensive forested areas existed in the Amazon during the last glaciation and that savanna vegetation expanded in response to warm and dry conditions during the early to middle Holocene.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".