A Field-Tested Protocol for the Measurement and Mapping of Bat Guano Deposition Rate in Caves
Bibliographic record
Abstract
Measurement of bat guano deposition rate in caves can be an important research tool for estimation of colony size, for monitoring the record of long-term bat population trends, and for allied studies of guano invertebrate ecology, environmental contaminants, and paleoecology. However, previously published methodologies have lacked consistency. In the context of our recent studies of insectivorous bat guano deposition rates in Deer Cave, Sarawak, Borneo, we review some past studies and offer suggestions for best practises, along with proposed experimental design considerations for future studies (e.g., design of guano catchers, optimum deployment of catchers in relation to specific site characteristics, data reporting standards, and examples of mapping techniques). Consistent techniques will facilitate inter-site comparisons, and determination of intra-site changes over time. As a case study, and the first publication of detailed mapping of spatial variability in guano deposition rates, we present spatially explicit guano deposition rates for Deer Cave, ranging up to 88 g (dry weight)/m2/day in the main cave, and up to 540 g (dry weight)/m2/day in the northern extension.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.018 |
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".