Multiple resource limitation and ontogeny combined: a growth rate comparison of three co-occurring conifers
Bibliographic record
Abstract
The combined effects of light, soil fertility, and ontogenetic changes on plant growth rates are poorly understood, yet these three factors play fundamental roles in structuring plant communities. We sought to determine how lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia), interior spruce (Picea glauca × engelmanii (Moench) Voss), and subalpine fir (Abies lasiocarpa (Hook.) Nutt.) sapling growth responds to the combination of light, soil fertility, and ontogeny and how these three dominant conifer species in sub-boreal forests of British Columbia differ in their responses. Using maximum likelihood methods, we found that 0.20–4 m tall sapling growth rates changed during ontogeny and were limited by both light and soil resources. The strongest differences among species’ growth rates were due to tree size, with smaller differences due to soil fertility, and there were no differences among species in the shape of their growth responses to light. Rank order in growth rates for small saplings (pine > spruce > fir) inversely corresponded to classic shade-tolerance ratings, thus supporting the carbon balance theory. Interior spruce height growth rates increased relative to lodgepole pine with increasing soil fertility, clearly matching the landscape-scale increase in canopy dominance of interior spruce over lodgepole pine with increasing soil fertility.
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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 | 0.000 |
| 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".