Within‐stand spatial structure and relation of boreal canopy and understorey vegetation
Bibliographic record
Abstract
Abstract Question: How do spatial patterns and associations of canopy and understorey vegetation vary with spatial scale along a gradient of canopy composition in boreal mixed‐wood forests, from younger Aspen stands dominated by Populus tremuloides and P. balsamifera to older Mixed and Conifer stands dominated by Picea glauca? Do canopy evergreen conifers and broad‐leaved deciduous trees differ in their spatial relationships with understorey vegetation? Location: EMEND experimental site, Alberta, Canada. Methods: Canopy and understorey vegetation were sampled in 28 transects of 100 contiguous 0.5 m × 0.5 m quadrats in three forest stand types. Vegetation spatial patterns and relationships were analysed using wavelets. Results: Boreal mixed‐wood canopy and understorey vegetation are patchily distributed at a range of small spatial scales. The scale of canopy and understorey spatial patterns generally increased with increasing conifer presence in the canopy. Associations between canopy and understorey were highly variable among stand types, transects and spatial scales. Understorey vascular plant cover was generally positively associated with canopy deciduous tree cover and negatively associated with canopy conifer tree cover at spatial scales from 5–15 m. Understorey non‐vascular plant cover and community composition were more variable in their relationships with canopy cover, showing both positive and negative associations at a range of spatial scales. Conclusions: The spatial structure and relation of boreal mixed‐wood canopy and understorey vegetation varied with spatial scale. Differences in understorey spatial structure among stand types were consistent with a nucleation model of patch dynamics during succession in boreal mixed‐wood forests.
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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 | 0.001 | 0.001 |
| 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".