Release episodes at the periphery of gaps: a modeling assessment of gap impact extent
Bibliographic record
Abstract
Gaps are recognized as important features of temperate forest dynamics and have been extensively studied in the last decades. Their definition has progressively evolved from the simplistic physical projection of the canopy opening to a more resource-based and functional approach (extended and species extended gaps). However, to truly define gap extent, the peripheral impact of gaps on the trees has to be considered. This study was undertaken to characterize the impact extent of gaps on their periphery using the SORTIE forest succession model. The sapling growth responses to gaps of different sizes (5002000 m2) was used as an indicator of the impact extent. Ten replicates of a simulation (for each gap size) were performed (305 years, 25-ha lattice). Gaps were introduced after 300 years. Growth ratios (pregap/postgap growth) for each sapling were computed and compared with a release threshold to determine sapling release episodes. These release episodes were analyzed to assess the extent of gap impact. Results indicate that gap effect extends significantly into the adjacent forest. Release episode orientations are concentrated in the northern hemisphere of gaps, and release episodes mostly appear in the first 20 m from gaps. Based on different degrees of release occurrence, new gap areas were defined and compared with areas from existing gap definitions. The differences are substantial and reveal that gap spatial extent observed through release patterns surpasses gap areas defined by traditional definitions.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".