Using microphone arrays to examine effects of observers on birds during point count surveys
Bibliographic record
Abstract
ABSTRACT Point count surveys are widely used for monitoring songbird populations, but little is known of the effect of the observer on songbird behavior during point counts. We used a novel, wireless array of recorders to determine the location of singing birds with and without the presence of an observer. The array consisted of seven autonomous recording units synchronized to Global Positioning System (GPS) clocks, set around the perimeter of a 50-m-radius circle with one in the middle. Units were set to record automatically from half an hour before dawn until 10:00 each morning. We sampled 26 different locations in old fields at the Prince Edward Point National Wildlife Area in eastern Ontario between 1 June and 4 July 2007. Position estimates derived from a time-lag cross-correlation algorithm had a mean error of 1.7 m within 50 m and 5.6 m at 100 m from the center of the array. We found no difference in the positions of birds when an observer was present or absent. We also found no difference in the number of individuals or species detected or in the onset of singing. Our results suggest that, at least in the community we studied, observers conducting point counts do not cause significant changes in bird behavior. Los conteos por puntos se utilizan ampliamente para el monitoreo de poblaciones de aves, pero poco se sabe del efecto del observador sobre el comportamiento del ave durante el conteo por punto. Utilizamos una novedosa serie inalámbrica de grabadoras para determinar la ubicación de aves que estaban cantando, con y sin la presencia de un observador. La serie estuvo formado por siete unidades autónomas de grabación, situados en el perímetro de un círculo de 50 m de radio, con una unidad en el centro. Estas unidades estaban sincronizadas con relojes del Sistema de Posicionamiento Global (GPS). Las unidades estaban programadas para grabar automáticamente desde media hora antes del amanecer hasta las 10:00 de cada mañana. Tomamos muestras en 26 lugares distintos en campos viejos del Prince Edward Point National Wildlife Area en el este de Ontario entre el 1 de junio y el 4 de julio de 2007. Estimaciones de la posición de las aves, derivadas de un algoritmo de tiempo retardado con una correlación cruzada, tenían una media de error de 1,7 m dentro de 50 m, y de 5,6 m a 100 m del centro de la serie de unidades. No encontramos diferencias en las posiciones de las aves cuando un observador estuvo presente o ausente. Tampoco encontramos diferencias en el número de individuos o especies detectadas, o en la iniciación de cantos. Nuestros resultados sugieren que, al menos en la comunidad que estudiamos, los observadores que realizan conteos por puntos no producen cambios significativos en el comportamiento de las aves.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".