Roost availability and population size of <i>Thyroptera tricolor</i>, a leaf-roosting bat, in north-eastern Costa Rica
Bibliographic record
Abstract
Estimates of roosting habitat availability and population size using unbiased sampling regimes are completely lacking for any bat species. The use of conspicuous and accessible roosts in the developing, rolled leaves of Heliconia and Calathea plants by Thyroptera tricolor (Spix's disc-winged bat) provided an ideal opportunity to address this need. To assess roost availability and population size, the number of occupied and unoccupied leaves and bats in known areas in an area of lowland rain forest in north-eastern Costa Rica were quantified in 1998–99. A high density of leaves was available on any given day (mean: 43 leaves ha−1), but the density of roost leaves was low (mean: 2.5 leaves ha−1), corresponding with a low occupancy rate of 5.7 or 12% based on different methods of estimation. Developing leaves were available for 8–16 h in the preferred size range of leaves used by T. tricolor, and a maximum of 28–60 h, depending on the plant species. Using closed-population mark–recapture models, the 5.69-ha study area supported 261 individuals over a 4-mo period in 1998, corresponding to a density of 43 bats ha−1. These results have important implications for the results of studies on bat community structure and rarity, and for the behaviour and ecology of T. tricolor.
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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 | 0.000 | 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) | 0.001 | 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".