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Related Experiment Video

Updated: Feb 16, 2026

Visually Sexing Loggerhead Shrike Lanius Ludovicianus Using Plumage Coloration and Pattern
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Factors affecting availability for detection: An example using radio-collared Northern Bobwhite (Colinus

Christopher M Lituma1, David A Buehler1, Evan P Tanner1

  • 1Department of Forestry, Wildlife and Fisheries, University of Tennessee, Knoxville, Tennessee, United States of America.

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Bird call surveys can underestimate Northern Bobwhite populations. Increased conspecific calling significantly boosts individual detection probability, especially in longer surveys. Account for this to avoid biased population estimates.

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Area of Science:

  • Wildlife Ecology
  • Ornithology
  • Bioacoustics

Background:

  • Avian monitoring often relies on vocalizations, but individual detection is influenced by social cues.
  • The impact of conspecific calling on Northern Bobwhite (Colinus virginianus) detection probability is not well quantified.

Purpose of the Study:

  • To assess how behavioral and temporal factors influence Northern Bobwhite breeding season detection availability.
  • To evaluate detection probability across different survey durations (3, 5, and 10 minutes).

Main Methods:

  • Radio-collared male Northern Bobwhites were monitored during 10-minute surveys.
  • Vocalizations (singing rate, number of other calling males), time since sunrise, and day of season were recorded.
  • Logistic regression modeled individual availability for detection and singing behavior.

Main Results:

  • Individual detection availability increased significantly with the number of other calling Northern Bobwhites.
  • Detection availability was 30-100% higher in 10-minute surveys compared to 3- or 5-minute surveys.
  • Northern Bobwhites called more frequently and at higher rates when stimulated by other calling individuals.

Conclusions:

  • Survey duration and conspecific vocalizations are critical factors affecting Northern Bobwhite detection probability.
  • Failure to account for these factors can lead to underestimation of population sizes, particularly in low-density populations.
  • Adjusting monitoring protocols to incorporate these findings is essential for accurate avian population assessment.