Gap Model Simulation of Metrosideros-Cibotium Stand Structure and Displacement Dieback
Bibliographic record
Abstract
An individual-based, multiple-growthform gap model of forest stand development and succession (ZELIG.MGF) of the JABOWA and FORET lineage was modified to simulate long-term changes in ‘ōhi'a-hāpu'u montane rain forests on the island of Hawai‘i. Based on the autecology, architecture, and life history of the two dominant species, we were able to re-create some of the stand dynamics and population structures observed in these forests. The phenomenon of displacement dieback, which occurs only on rich sites with persistent cloud cover, is portrayed as a natural successional consequence of ‘ōhi’a lehua (Metrosideros polymorpha Gaud.) senescence and shade intolerance, which contrasts with the shorter stature, clonal reproduction, and shade tolerance of hāpu'u pulu tree fern (Cibotium glaucum (Sm.) Hook. & Arn.). ZELIG.MGF predicts that ‘ōhi’a will achieve a maximum basal area of 27 m2/ha in stands 80–90 years old, after which basal area is projected to decline to levels of 8–11 m2/ha that persist after 220 years. Alternating phases of ‘ōhi'a and hāpu'u may dominate individual gaps, but overall old-growth ‘ōhi’a populations do not recover to earlier levels. ‘Ōhi’a overstory mortality is consistent with senescence or a growing imbalance of respiratory to photosynthetic tissue in large trees. Understory mortality as modeled is largely due to shading by adults and by hāpu’u tree ferns, although mechanical damage from dead hāpu’u fronds, which was not modeled, may also be important. ‘Ōhi’a stand rejuvenation can occur when the density of hāpu’u is reduced by harvesting or wind storms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".