Natures Chorus: Determining Avian Richness across Microhabitats using AudioMoths
Bibliographic record
Abstract
Bird surveys are commonly actively performed using point count techniques; however, more recently, passive acoustics have become a complementary method to evaluate species richness and trends across microhabitats. Traditional methods like point counts may lead to biases in data records depending on the researcher's experience level. Autonomous recording devices (ARU), such as AudioMoths, are an affordable method for those studying avifauna to add to their toolbox. Confidence in rare species identification may increase by being able to leave AudioMoths out for a longer duration than feasible with traditional point counts and the ease with which artificial intelligence program workflows can attempt species confirmation. In the fall of 2024, we performed both passive (ARU) and active (point count) avifauna surveys across three microhabitats (e.g., wetland, forest, meadow) at Point au Roche State Park. Our active surveying method used binoculars and Merlin Bird ID to help identify species for three-10-minute intervals during each visit. Our passive surveying method used AudioMoths to record vocalizations deployed for seven days, recording during peak hours from 20:00-8:00. BirdNet-Analyzer was used to identify vocalizations from audio files. Species richness was greatest in the meadow (51) and wetland (47) and least in the forest (27). Merlin Bird ID recorded black-capped chickadee (Poecile atricapillus), Canada goose (Branta canadensis), northern cardinal (Cardinalis cardinalis), blue jay (Cyanocitta cristata), and downy woodpeckers (Picoides pubescens) across the sites. The American crow (Corvus brachyrhynchos) and barred owl (Strix varia) called abundantly at the wetland (43%) and the meadow (36%) sites, while the forest site was more limited. Avian community similarity was greatest between the wetland and meadow (64%) microhabitats. Other notable species observed are stripe-faced meadow katydid (Orchelimum concinnum), wood frog (Lithobates sylvaticus), and spring peeper (Pseudacris crucifer). We highlight the importance of conducting active and passive surveying across multiple habitats to more adequately capture rare species that might be difficult to capture with shorter survey durations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".