Shade tolerance, canopy gaps and mechanisms of coexistence of forest trees
Bibliographic record
Abstract
The belief that canopy gaps are important for the maintenance of tree species diversity appears to be widespread, but there have been no formal theoretical models to assess under what conditions gap phase processes allow coexistence. Much of the empirical research on niche differentiation in response to gaps has focused on evidence for an interspecific tradeoff between low light survival and high light growth. The objectives of this study are first to distinguish the possible mechanisms allowing coexistence based on this tradeoff, and second, to explore their limitations. We present a theory of forest dynamics driven by small‐scale disturbances as a special case of the theory of coexistence in variable environments. We demonstrate that temporal and spatial heterogeneity in light conditions that results from canopy gaps can allow stable coexistence as a result of three previously documented general mechanisms: ‘relative non‐linearity’, ‘the successional niche’ and the ‘storage effect’. We find that temporal fluctuations in light availability alone allow the stable coexistence of only two species. Spatial variation in disturbance synchronicity and intensity allows three species to coexist in a narrow parameter space. The rate of extinction is, however, extremely slow and there is transient coexistence of a larger number of species for a long period of time. We conclude that while the low light survival/high light growth tradeoff may be ubiquitous in forest tree species, it is unlikely to function as an important mechanism for the stable coexistence of several tree species.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".