Modelling Growth-Competition Relationships in Trembling Aspen and White Spruce Mixed Boreal Forests of Western Canada
Bibliographic record
Abstract
We examined the effect of competition on stem growth of Picea glauca and Populus tremuloides in boreal mixedwood stands during the stem exclusion stage. We combined traditional approaches of collecting competition data with dendrochronology to provide retrospective measurements of stem diameter growth. Several competition indices including stand basal area (BA), the sum of stem diameter at breast height (SDBH), and density (N) for the broadleaf and coniferous species, as well as similar indices considering only trees with diameters greater than each subject (BAGR, SDBHGR, and NGR), were evaluated. We used a nonlinear mixed model to characterize the basal area increment over the past 5, 10, 15, 20, 25, 30, and 35 years as a function of growth of nearby dominant trees, the size of the subject trees, deciduous and coniferous competition indices, and ecoregions. SDBHGR and BAGR were better predictors for spruce, and SDBHGR and NGR were better for aspen, respectively, than other indices. Results showed strongest correlations with long-term stem growth, as the best models integrated growth for 10-25 years for aspen and ≥ 25 for spruce. Our model demonstrated a remarkable capability (adjusted R(2)>0.67) to represent this complex variation in growth as a function of site, size and competition.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".