Vertical stratification of bat communities in primary forests of Central Amazon, Brazil
Bibliographic record
Abstract
The vertical stratification of bat communities in primary forests of the Central Amazon (80 km north of Manaus, Brazil) was investigated using capture nets in the canopy (17 to 30 m high) and in the understorey (from 0-2.5 m). Seventeen sites were sampled during one year (3398.5 mistnet-hours) and 936 individuals captured, belonging to 6 families, 29 genera and 51 species. Utilizing Non-Metric Multidimensional Scaling (NMMDS), a well-marked vertical stratification between the communities was verified, the canopy being the more utilized region. Fifteen species were exclusively captured in the canopy, 10 were predominantly captured in the canopy, and 12 species were exclus ively captured in ground nets. Species recorded and the communities they form were analysed using a matrix of guilds. The matrix obtained had 24 cells. A guild composed by background cluttered/gleaning frugivores was the richest in species (19), followed by background cluttered/gleaning insectivores (12 species). The results illustrate that when studying tropical forests it is highly desirable to involve both the lower and the upper part of the forests; otherwise the fauna would be merely subsampled, thus under-estimating the status and abundance of some species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".