Trade-offs in seedling survival, growth, and physiology among hardwood species of contrasting successional status along a light-availability gradient
Bibliographic record
Abstract
To better understand the regeneration ecology of northern red oak (Quercus rubra L.) in mesic forests, we compared its seedling growth and physiology with those of two other hardwoods, differing in successional status, along a gradient in light availability ranging from forest understories (2.6% of full light) to small clearings (69% of full light). Oak's relative growth rate (RGR) closely resembled that of shade-tolerant sugar maple (Acer saccharum Marsh.), and the positive response of both to increasing light was modest, especially beyond a relative light availability of 15%. Intolerant trembling aspen (Populus tremuloides Michx.) outgrew the others when relative light availability exceeded 5%, and its RGR increased more or less linearly with increasing light. However, there was a rank reversal of RGR in deep shade, where maple and oak had a higher RGR than aspen. This reversal was mirrored by seedling demography, as aspen survival was comparatively high in small clearings but negligible in deep shade. Aspen's low RGR and poor survival in low light were associated with a high rate of shoot dark respiration and minimal allocation to starch reserves. Aspen's high RGR in openings was attributed primarily to a high photosynthetic capacity per unit leaf mass. Thus, differential growth and survival among species could be explained in part by trade-offs in attributes that promoted rapid growth in high light at the expense of a favorable carbon balance in low light, or vice versa. Oak's suite of traits facilitated a positive carbon balance in perhaps all but the darkest understories. We suggest that the lack of persistence of oak seedlings in many understory environments may center around factors (e.g., vulnerability to biotic stresses) not directly related to carbon gain.
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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 | 0.000 | 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) | 0.001 | 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".