Stand- and plot-level changes in a boreal forest understory community following wildfire
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Boreal forest understory plant communities are known to be resilient to fire – the species composition of stands after a fire is quite similar to the pre-fire composition. However, we know little about recovery of individual plants within particular locations in forest stands (i.e. plot-level changes) since we usually do not have pre-fire data for plots.Aims: We wanted to determine whether species recruited into the same or different locations in a Pinus banksiana stand that experienced a severe wildfire.Methods: We used pre-existing permanent plots to evaluate the cover of understory after an unplanned wildfire.Results: Across the entire stand nine of 47 species showed a significant change in cover. The largest change in a plant functional group was in the mosses, with all species present before fire being eliminated. There was no change in species diversity or total cover. At the plot level, species composition showed a much greater change. An average of 47% of the species present in a plot before the fire were absent in the same plot after the fire, and the total species turnover in plots was 88% of the species present before the fire. The plots showed a similar shift in species composition.Conclusions: These results confirm that boreal forest communities show a high degree of resilience to fire, but within a forest stand species will be found in different locations following fire, potentially exposing them to a different set of biotic and abiotic conditions in these new locations.
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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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it