Wildland fire effects on understory plant communities in two fire-prone forests
Bibliographic record
Abstract
Our understanding of wildland fire effects on understory plant communities is limited because of a lack of repeated measurements before and after lightning-ignited fires. We examined vegetation responses to a surface fire in a ponderosa pine forest and a mixed-severity fire in a spruce–fir–aspen forest using before–after, control–impact (BACI) study designs. We hypothesized that the surface fire would stimulate plant species richness and minimally alter community composition, but that the mixed-severity fire would decrease richness and significantly alter composition. In ponderosa pine forests, total species richness and plant cover increased slightly because of annual and biennial forb and grass establishment in soils where duff layers were reduced by the surface fire. In spruce–fir–aspen forests, total species richness and plant cover were similar in burned and unburned forests after 2 years, although annual and biennial forbs and graminoids increased significantly in the burned area. Plant community composition was altered by both fires. Wildfires may indirectly influence the understory plant community through the mediating effects of overstory basal area and litter depth. Fire effects on plant species richness and cover were weaker than effects due to environmental factors. Managers should anticipate increases in both native and non-native ruderal species following landscape-scale fires.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".