Airborne eDNA documents a diverse and ecologically complex tropical bat and other mammal community
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Environmental (e)DNA has rapidly become a powerful biomonitoring tool, particularly in aquatic ecosystems. This approach has not been as widely adopted in terrestrial communities where the methods of vertebrate eDNA collection have varied from the use of secondary collectors such as blood feeding parasites and spider webs, to washing surfaces of leaves and soil sampling. Recent studies have demonstrated the potential of direct collection of eDNA from air sampling, but none have tested how effective airborne eDNA sampling might be in a biodiverse environment. We used three prototype samplers to actively sample a mixed neotropical bat community in a partially controlled environment. We assess whether airborne eDNA can accurately characterize a high diversity community with skewed abundances and to determine if filter design impacts DNA collection and taxonomic recovery. Our study provides evidence for the accuracy of airborne eDNA as a detection tool and highlights its potential for monitoring high density, diverse assemblages such as bat roosts. Analysis of air samples recovered >91% of the species present and some limited relationship between species abundance and read count. Our data suggests this method can accurately depict a diverse mixed‐mammal community, particularly when the location is contained (e.g., a roost, den or burrow) but also highlights the potential for secondary transfer of eDNA material on clothing and equipment. Our results also demonstrate that simple, inexpensive, battery‐operated homemade air samplers can collect an abundance of eDNA from the air, opening the opportunity for sampling in remote environments.
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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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 it