Effects of fire intensity on survival and recovery of soil microarthropods after a clearcut burning
Bibliographic record
Abstract
We studied responses of soil microarthropods to different burning intensities at a clearcut that was burnt in May 2002. Fire intensity was manipulated by adding or removing logging residues as fuel from the experimental plots. Samples were taken 1 week before and 1 week after burning as well as during autumn of the same year. Samples were taken in the 2 following years to estimate long-term recovery. No difference in humus combustion could be detected between burning intensities, but most microarthropod species showed lower abundances in the hard-burnt than in the light-burnt plots immediately after fire. Surface-living species also declined in light-burnt plots, whereas soil-living species were particularly affected in hard-burnt plots. This is probably explained by greater heat transfer into the hard-burnt soil. Total abundances of Oribatida and Protura remained low for several years in the burnt plots, whereas abundances of Collembola and Mesostigmata recovered within 1 year, which indicates that at least these groups had enough habitat space and food resources after fire. The study indicates that fire severity (depth of burn) is more decisive than fire intensity (heat release) for the long-term recovery of soil fauna, whereas fire intensity determines the acute survival of animals.
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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 | 0.000 | 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".