Lianas Abundance is Positively Related with the Avian Acoustic Community in Tropical Dry Forests
Bibliographic record
Abstract
Dry forests are important sources of biodiversity where lianas are highly abundant given their ability to grow during times of drought and as a result of secondary growth processes. Lianas provide food and shelter for fauna such as birds, but there are no studies assessing the influence of liana abundance on birds in dry forests. Here we evaluate the influence of liana abundance on the avian acoustic community in the dry forests of Costa Rica at Santa Rosa National Park. We selected forest sites with different levels of liana abundance and set up automated sound recorders for data collection, analysis and estimation of the avian acoustic community. When the number of lianas increases, the avian acoustic community becomes more complex. Lianas could provide important direct and indirect resources for birds such as structure for shelter, protection, nesting and roosting, and food. The positive relationship that lianas have with birds is particularly important in dry forests where lianas are becoming highly abundant due to the level of forest disturbance and climate change, especially for some bird species that are restricted to this ecosystem. By validating the number of bird species detected in the recordings with the acoustic complexity index, we found that a higher acoustic complexity means higher species richness.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".