Liana abundance and relationships to sapling and tree hosts in an East African primary forest
Bibliographic record
Abstract
Abstract Lianas are an important structural component of tropical rain forests. Recent concern regarding a putative global rise in liana abundance, and its implications for forest conservation, calls for data collection across biomes. We here provide a first assessment and baseline data for a geographical gap in liana surveys to date. We surveyed liana (diameter at breast height [DBH] > 1 cm), tree (DBH > 10 cm) and sapling (DBH ≤ 10 cm) abundance and basal area, as well as liana–host relationships, in a tropical East African primary forest. We recorded a total of 347 liana stems (DBH > 1 cm) in 0.31 ha, with an average basal area of 1.21 m 2 /ha. Lianas were found to be widespread, with 24% of saplings and 57% of trees colonised by at least one liana, independently of bark texture or host diameter. The dominant liana colonisation strategy was to associate with a single host, through stem twining. We found no evidence of liana density being influenced by host density. We synthesised published liana density data across continents and report that our estimate of liana density for Kibale's primary forest fits within the expected range of liana densities for primary tropical forests. This synthesis further highlights a neotropical sampling bias, which our findings make a step towards addressing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".