Shade tolerance and the functional trait: demography relationship in temperate and boreal forests
Bibliographic record
Abstract
Summary Despite being instrumental in forest ecology, the definition and nature of shade tolerance are complex and not beyond controversy. Moreover, the role it plays in the trait–demography relationship remains unclear. Here, we hypothesize that shade tolerance can be achieved by alternative combinations of traits depending on the species' functional group (evergreen vs. deciduous species) and that its ability to explain the array of traits involved in demography will also vary between these two groups. We used dimension reduction to identify the main trait spectra for 48 tree species, including 23 evergreens and 25 deciduous – dispersed across 21 genera and 13 families. We assessed the relationship between functional traits, shade tolerance, and demographic performance at high and low light using structural equation modelling. The dimensions found corresponded to the trait spectra previously observed in the literature and were significantly related to measures of demography. However, our results support the existence of a divergence between evergreen and deciduous species in the way shade tolerance relates to the demography of species along light gradients. We show that shade tolerance can be attained through different combination of traits depending on the functional and geographical context, and thus, its utilization as a predictor of forest dynamics and species coexistence requires previous knowledge on the role it plays in the demographic performance of the species under study. A lay summary is available for this article.
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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 | 0.000 | 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".