Postfire root distribution of Scots pine in relation to fire behaviour
Bibliographic record
Abstract
Fire can potentially have a large direct impact on tree roots and, thus, contribute to reduced vitality. Tree canopy status after fire should have an impact on the postfire production of fine roots, further affecting root function. We analyzed the standing crop of live and dead roots in Pinus sylvestris L. with varying degrees of crown scorch, 1 year after fire in northern Sweden. On the burned sites, total Pinus live fine-root biomass was 74% of that at the control sites, and it was only 19% of the control for roots <2 mm, indicating an 80% reduction due to fire. Root mortality was highest for high-scorch trees, but this was probably due to greater depth of burn in the organic soil for these trees and not to higher fire intensity per se. Fine-root production was also assessed by an ingrowth experiment. This showed relatively similar fine-root production in both control trees and fire-damaged trees, indicating a high allocation to root growth for the damaged trees, to make up for lost root function. Root dynamics after fire are related to a number of factors, and direct effects are determined by the depth of burn in the organic soil layer. Indirect, long-lasting effects could be due mainly to girdling of coarse roots close to tree stems and canopy loss.
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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 | 0.000 | 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 | 0.000 |
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".