Forest composition and structure after 200 years of succession following the eruption of Mount Tambora (Indonesia)
Bibliographic record
Abstract
We examined the changes in tropical forest diversity, structure and trait composition during primary succession after volcanic disturbance. Whilst many studies have examined early stages of succession, fewer have looked at a precisely dated older location: 200 years old in this instance. To do this, we established a 0.5 ha plot on the lower slopes of Gunung (Mount) Tambora (Sumbawa, Indonesia) in which we enumerated and identified all trees ≥ 10 cm dbh, determined their key traits and calculated forest above-ground biomass. Saplings (1.5–3.0 cm dbh) were enumerated in one quarter of this area. We recorded 214 stems ≥ 10 cm dbh within 21 taxa contributing to an above-ground biomass of 135 Mg ha−1. Most trees had light wood and broad distributions suggestive of early successional traits, but leaves were generally small; most trees were insect pollinated and animal dispersed as expected at later stages of succession. Saplings were variable in their density and showed some floristic similarity with adult trees, but differences indicated the future trajectory of succession. Our floristic and structural data from the poorly studied drier forests of eastern Indonesia show that this 200-year-old forest is still undergoing succession at a slow rate.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".