Does trait plasticity of three boreal nutrient-conserving species relate to their competitive ability?
Bibliographic record
Abstract
The present study investigates potential differences in trait plasticity as an additional contributing mechanism explaining ericaceous shrub dominance during different periods after logging. Two ericaceous species (Kalmia angustifolia, Rhododendron groenlandicum), and black spruce plants (Picea mariana), were submitted to combinations of 3 light levels and 2 levels of nitrogen addition during a simulated growing season of 9 weeks under greenhouse conditions. Plant traits related to light (photosynthesis, leaf mass per unit of area, leaf and aboveground biomass allocation, foliar N concentration) and nutrient acquisition (root mass ratio, specific absorption ratio, absorption of 15N) were measured in response to the manipulation of these resources. The leaf mass per unit of area (LMA) of both ericaceous species was significantly reduced by shading; LMA of Rhododendron and Kalmia was, respectively, 54% and 31% higher in the highest light treatment. The LMA of black spruce was unchanged in response to light level. There were few differences among species in trait response to N addition. Black spruce was characterized by higher nutrient absorption rate and specific absorption rate at higher N levels compared to the 2 ericads. With the exception of LMA, plasticity to light was higher for Kalmia; in contrast, plasticity to N addition was higher for Rhododendron and black spruce. Finally, LMA appears to be a key trait explaining the competitive advantage of ericaceous species (especially Rhododendron) and potential encroachment on forested sites after disturbance.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".