Holocene Fire Regime Changes in the Southern Lake Baikal Region Influenced by Climate-Vegetation-Anthropogenic Activity Interactions
Bibliographic record
Abstract
Catastrophic fire years that have taken place during the last decade in Siberia, and more generally within the boreal forest, have been directly linked to global warming and had strong repercussions on boreal ecosystems and human populations. In this context the study of the past dynamics of these fires is essential for understanding their links with climate, vegetation and human activity changes on longer time scales than the last few decades. However, few studies on fire dynamics are available for Siberia, and none have been conducted for the entire Holocene period. This study presents the first fire history reconstruction of this area during the Holocene based on charcoals sequestered in sediments of two lakes located on the southern shore of Lake Baikal, in Siberia. The results show a similar trend in the two lakes, with high frequency and high peak magnitude during the Early Holocene and low magnitudes after 6500 cal. yr BP. This difference is interpreted as crown fires versus surface fires. According to pollen records (Dulikha, Vydrino, Ochkovoe) available near the studied lakes, a vegetation transition occurred at the same time. Picea obovata, which has a tree structure prone to crown fires, was dominant during the Early humid Holocene. After 6500 cal. yr BP, conditions were drier and Pinus sylvestris and Pinus sibirica became the dominant species; their tree structure favors surface fires. In addition to vegetation dynamics, the nearby pollen sequence from Dulikha has been used to provide quantitative estimates of past climate, indicating an Early to Middle Holocene climatic optimum between 8000 and 5000 cal. yr BP and an increase in temperatures at the end of the Holocene. These results have been compared to outputs from regional climate models for the Lake Baikal latitudes. Fire dynamics appear to have been more linked to the vegetation than climatic conditions. Over the past 1500 years, the greater presence of human populations has firstly resulted in an increase in the fire frequency, then in its maintenance and finally in its suppression, which may possibly have been due to very recent fire management, i.e., after ca 500 cal. BP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 0.001 |
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 teacher head, 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".