Population structure and growth acclimation of mountain maple along a successional gradient in the southern boreal forest
Bibliographic record
Abstract
:A range of stands was sampled in the southern boreal forest of eastern Canada to determine the impact of forest development stages and light availability on the dynamics of an abundant understory shrub: mountain maple (Acer spicatum). Mountain maple was studied at both the population and individual stem levels. At the population level, a total of 190 1-m2 quadrats were sampled in five forest types representing a successional gradient (young aspen, mature aspen, mixedwood, shade-tolerant conifer, and old spruce budworm-affected conifer forests). At the individual stem level, a total of 100 stems of different sizes were harvested in a sub-sample of the quadrats. Mountain maple stem biomass, density, and population structure were found to be affected by forest composition, the coniferous forest being the least favourable. At the individual stem level, light availability and stem size were found to have an important impact on stem morphology and growth, suggesting a high level of plasticity in relation to canopy opening. From these results, four developmental phases of mountain maple population dynamics were identified: 1) following a drastic disturbance, a first phase of rapid growth, and potentially intense competition with aspen suckers, when present, takes place; 2) following the development of a closed aspen canopy, the overall density, biomass, and presence of mountain maple in the understory increase; 3) following recruitment of conifer trees into the overstory canopy, mountain maple enters a suppression phase associated with a decrease in light; and 4) following the occurrence of small scale disturbances, mountain maple quickly responds to rapidly dominate the openings, which further ensures its maintenance in the understory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".