Fires control spatial variability of subalpine vegetation dynamics during the Holocene in the Maurienne valley (French Alps)
Bibliographic record
Abstract
Due to stresses resulting from their high altitudes, subalpine forests are sensitive to disturbances, including fire. This study analyzes the long-term relationships between fire and subalpine vegetation in the western Alps. High-resolution analyses of charcoal, pollen, macroremains, and other palynomorphs were performed on sedimentary cores from 2 small peaty ponds located above 2000 m asl. in the Maurienne valley, France. Results reveal similar long-term vegetation dynamics, with differences concerning the structure and composition of local and surrounding plant communities. The vegetation pattern appears partially related to local fire occurrence, which was most frequent between 8900 and 6500 cal. BP at one lake and between 4100 and 1800 cal. BP at the second. Fires notably triggered the development and occurrence of populations of Acer and Alnus incana-type during a 2000-y period and the asynchronous alteration of Pinus cembra forests at both sites. Results show that the low-competitive species, i.e., Larix decidua or Pinus uncinata, were never stimulated by increasing fire frequency. This highlights the past importance of local-scale processes such as fire, which favoured pioneer broad-leaved species but did not threaten the resilience of the subalpine forests dominated by the cembra pine.
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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 | 0.001 | 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".