The interactive effect of competition and climate on growth of boreal tree species in western Canada and Alaska
Bibliographic record
Abstract
Understanding interactions between competition and climate in relation to their effects on individual tree growth is crucial to the development of climate-sensitive growth models required for modelling boreal forest succession in a changing climate. We used data from permanent growth and yield sample plots in western Canada and Alaska to investigate the impact of competition within a regional gradient of climatic conditions for lodgepole pine (Pinus contorta Douglas ex Loudon), jack pine (Pinus banksiana Lamb.), trembling aspen (Populus tremuloides Michx.), balsam poplar (Populus balsamifera L.), white spruce (Picea glauca (Moench) Voss), and black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.). We characterized the effects of competition (basal area of spruce–fir, deciduous, and pine trees larger than the focal tree) and climate (mean annual temperature and precipitation) and their interactions on basal area growth of individual trees using linear mixed-effects models. Our results indicated that intraspecific competition had stronger effects on growth than interspecific competition and climate. Moreover, significant interactions between intraspecific competition and climate suggest that an increase in intraspecific competition will lead to a reduction in tree growth for warmer regions (lodgepole pine, trembling aspen, balsam poplar, and white spruce) and wetter regions (jack pine). The manner in which interspecific competition altered tree growth responses to climate was variable, depending on tree species and competition type. These results indicate that the relationships between growth and climate may differ according to the degree of competition and the structure of the stand.
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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 | 0.001 | 0.001 |
| 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".