Do finer gap mosaics provide a wider niche for <i>Quercus gilva</i> in young Japanese cedar plantations than coarser mosaics? Simulation of spatial heterogeneity of light availability and photosynthetic potentialThis article is one of a selection of papers published in the Special Forum IUFRO 1.05 Uneven-Aged Silvicultural Research Group Conference on Natural Disturbance-Based Silviculture: Managing for Complexity.
Bibliographic record
Abstract
Both the size and the density of gaps affect seedling growth, but these two parameters have a reciprocal relationship at a given gap ratio. The objective of the present study was to clarify the appropriate gap mosaic coarseness required to facilitate the growth of Quercus gilva Blume seedlings in Cryptomeria japonica D. Don plantations. The spatial heterogeneity of the photosynthetic photon flux density on the forest floor was predicted using mimicked hemispherical diagrams under five levels of gap mosaic coarseness ranging from the finest gap mosaic with a gap size of 25 m 2 and a gap density of 100·ha –1 to the coarsest mosaic of 400 m 2 and 6.25·ha –1 . Photosynthetic potentials (PP) were calculated by combining the predicted photosynthetic photon flux density and photosynthetic relationships of Q. gilva and two nontree major competitors ( Mallotus japonicus (Thunb.) Muell. Arg. and Miscanthus sinensis Anderss.). The coarser gap mosaic formed a more heterogeneous and bimodal PP frequency and resulted in a wider site in which the three species had high growth potential without considering competition among species. However, an intermediate mosaic with a gap width to mean canopy height ratio of 0.7 formed the widest realized niche in which Q. gilva would show good growth with a relative PP > 70%, whereas the competitor species would be suppressed with a relative PP < 70%.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".