Effects of fire severity and initial tree composition on understorey vegetation dynamics in a boreal landscape inferred from chronosequence and paleoecological data
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Question and Location: How does soil burn severity and early post‐fire tree composition affect long‐term understorey vegetation dynamics in the coniferous forests of eastern Canada? Method: Vegetation dynamics were assessed using paleoecological methods and a chronosequence analysis of extant stands. The relation between environmental factors and succession was evaluated using ordination techniques on the chronosequence data. Understorey succession was studied by regression analysis on the chronosequence data and through within‐site Markovian transition probabilities between successive 1‐cm layers of plant macroremains from soil organic matter profiles. Results: Initial tree composition ( Picea mariana and Pinus banksiana ) had little effect on understorey composition. Soil burn severity (measured as the thickness of the residual forest floor humus) significantly affected temporal changes in understorey species. Following fires of high severity, stands underwent a gradual paludification with a net increase in Sphagnum and ericaceous shrubs (Ledum groenlandicum) , and a decrease in feathermosses. Paludification was accelerated after low severity fires, which led to the dominance of Sphagnum less than 200 years after fire, and of L. groenlandicum shortly after fire. In situ paleo‐ecological work confirmed results obtained with the chronosequence analysis. Conclusions: One vegetation gradient related to time after disturbance is insufficient to account for the full complexity of long‐term changes in understorey composition following fire. Current forestry practices that protect the forest floor humus may induce a premature paludification.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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