Dispersal ecology of the lowland rain forest in the Vava'u island group, Kingdom of Tonga
Bibliographic record
Abstract
Abstract We explore the dispersal ecology of the tropical lowland rain forest on the Vava'u island group, Kingdom of Tonga, to understand dispersal adaptations across successional vegetation types and by species origin. We utilise quantitative data on the relative plant abundance (basal area for overstorey and cover for understorey) of forest species from 64 600‐m 2 vegetation plots on 13 islands. Frequencies of species by dispersal mechanisms permit comparisons according to community types, between understorey and overstorey taxa, and between endemic, indigenous, and exotic species (both Polynesian and European introductions). Birds and bats disperse 80% of the plant species in the lowland rain forests of Vava'u; water dispersal (40% of the species) is of secondary importance. Plants introduced by Polynesians comprise 5–10% of the rain forest overstorey; European introductions are common in the early successional forest, principally in the understorey. Over 30% of the indigenous trees in the late successional rain forest are potentially dispersed by rodents, but more likely these introduced (Polynesian and European) rats primarily act as seed predators. Plants in the lowland tropical rain forests of Vava'u are largely dispersed intra‐island by birds and bats. While plants dispersed by epizoochory and human cultivation are encroaching in the early successional stages of the rain forest, perhaps the greater effect on these tropical forests may be seed predation by rodents, especially in late successional rain forest. Since the majority of the indigenous rain forest species are dispersed by native fauna, it is imperative that the extant birds and fruit bats of the Kingdom of Tonga continue to be preserved to maintain the regeneration of the rain forests on these relatively isolated oceanic islands.
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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 | 0.003 | 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".