Carbon stocks in tropical forests decrease with liana density
Bibliographic record
Abstract
Tropical forests are experiencing structural changes that may reduce carbon storage potential. The recent increase in liana abundance and biomass is one such potential change. Lianas account for approximately 25 per cent of woody stems and may have a strong impact on tree dynamics because severe liana infestation reduces tree growth and increases tree mortality. Based on forest inventory data from 0.1 ha plots, we evaluated the association between above-ground carbon stocks and liana abundance in 145 tropical forests worldwide. Liana abundance was negatively associated with carbon stocks of large trees (greater than 10 cm diameter), while it was not related to small trees (10 cm diameter or less). Results suggest that liana abundance may have pervasive effects on carbon stocks in tropical forests, as large trees store about 90 per cent of total forest carbon. We stress the need to include liana abundance in carbon stocks estimates, as this can enhance the accuracy of predictions of global changes in tropical forests.
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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".