Biomass dynamics of central Siberian Scots pine forests following surface fires of varying severity
Bibliographic record
Abstract
In 2000–2002 nine 4-ha prescribed fires of various severities were conducted on experimental plots in mature Scots pine forest in the central Siberian taiga, Russia. Total above-ground living biomass decreased after low- and moderate-severity fires by 10 and 15%, whereas high-severity fire reduced living above-ground biomass by 83%. We monitored changes in fuel structure and biomass for 6–8 years following these fires. By 6–8 years after burning the ground fuel loading had recovered to 101, 96 and 82% of pre-fire levels after fires of low-, moderate- and high-severity. Down woody fuel loading increased by 0.18 ± 0.04 kg m–2 year–1. We developed regressions relating time since fire to changes in above-ground biomass components for fires of different severity for feather moss–lichen Scots pine forest of Siberia. Our results demonstrate the importance of both burn severity and composition of pre-fire surface vegetation in determining rates and patterns of post-fire vegetation recovery on dry Scots pine sites in central Siberia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
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".