Flowering and fruiting phenology of a Philippine submontane rain forest: climatic factors as proximate and ultimate causes
Bibliographic record
Abstract
1 Phenological patterns of flowering and fruiting are presented for 5800 trees of a Philippine submontane forest community during a 4-year period. Circular vector algebra allowed species to be grouped into annual (34 species), supra-annual (3), irregular (7), and continuous (13) reproducers. 2 Wind- and gravity-dispersed species had extended fruiting periods coinciding with the typhoon season (July to November), whereas fleshy fruited trees showed peaks matching those of solar irradiance. Most species flowered at the beginning and fruited at the end of the first peak (April), or they flowered during the first peak and fruited during the second peak (September), indicating that solar irradiance may be a strong selective factor in shaping community-wide phenology patterns. 3 An El Niño and a La Niña climate anomaly occurred during the study period. Principal component analysis showed that 95% of intraspecific variation of flowering and fruiting dates could be explained by delayed or advanced flowering and fruiting of a limited number of species. Mast-fruiting of dipterocarp species could not be correlated with El Niño and La Niña events. 4 Large climate-induced variation in phenology was demonstrated for the percentage of trees that reproduce, while the timing of phenology remained unaffected for most species, suggesting that climatic factors are not directly responsible for triggering and synchronization of phenological events.
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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 | 0.000 |
| 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".