Mexican mixed-species forest shows resilience to high-intensity fire
Bibliographic record
Abstract
In the aftermath of a high-intensity wildfire in La Michilía Biosphere Reserve, Mexico, an initial study suggested a shift from an oak–pine forest to a grass–savanna ecosystem. We conducted repeated measurements on 60 permanent plots 1, 5, 10, and 20 years after the original wildfire at paired burned and unburned study sites to capture spatial and temporal dynamics in forest composition and structure. We found that the burned site regained most pre-wildfire characteristics two decades after the wildfire. The ongoing regeneration in the burned site suggests that despite the remaining differences, the site is approaching a complete recovery, with forest characteristics analogous to the unburned site. Our findings indicate that the combination of seeders' wildfire resistance and resprouters’ post-wildfire sprouting strategies in mixed-species forests provides high resilience to high-intensity wildfire. Moreover, protecting La Michilía as a biosphere reserve and heightened public awareness of the natural environment likely played an indispensable role in facilitating the recovery of the post-wildfire ecosystem.
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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".