Growth, mortality, and morphological response of European beech and downy oak along a light gradient in sub-Mediterranean forest
Bibliographic record
Abstract
We examined light as a niche partitioning factor between the late-successional European beech (Fagus sylvatica L.) and the mid-successional downy oak (Quercus pubescens Willd.), two dominant species in the sub-Mediterranean area of southern France. For these species we estimated sapling growth models (in radius and in height) as a function of light availability. Beech had a higher growth in low light and a higher asymptotic growth rate than oak. We estimated species-specific growthmortality functions. Beech showed a higher tolerance to slow growth than oak. By linking lightgrowth functions and growthmortality functions, we found that beech had a lower mortality at low light than oak. Beech saplings had a higher probability of survival than oak at low and at high light levels. Beech exhibited the highest plasticity of morphological traits (i.e., biomass allocation, leaf morphology, and architectural traits) as a function of light. Since beech has higher growth and survival than oak at variable light regimes, we conclude that niche partitioning for light cannot explain the coexistence of these two species. We propose that disturbance and water stress should be explicitly taken into account to understand niche partitioning and succession in the sub-Mediterranean area.
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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) | 0.000 | 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 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".