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Programmable Automated System for Songbird Ecobehavioral Research (PASSER): Using flexible computer-integrated feeders to conduct high resolution studies of environment-behavior dynamics in songbirds.

Conner S PhilsonAndrew RaySarah FoltzJason Davis
Published in: Ecology and evolution (2018)
Field studies seeking to identify interactions between the environment and behaviors of wild songbirds are often restricted by time, labor, and accessibility of the site; hampering the collection of long-term, high-resolution data. Here, we describe the development, utilization, and initial results of a long-term field study of wild songbird feeding patterns using data collected through an inexpensive microcomputer-controlled automated feeder. Our studies indicate the "smart feeder" is capable of reliable and accurate data collection on feeding and behavioral metrics over long durations with relation to a wide range of environmental conditions. This enables detailed analysis of songbird's environment-behavior interactions. Our results have identified trends in environment-behavior interactions, microhabitat variations, species-specific feeding profiles, and differences in the frequency and involvement of displacement events. Computerized feeders enabled us to address environment-behavior interactions, resulting in more detailed data than traditional observational methods. This reinforces conclusions from previous work regarding the potential for automated data collection to be adapted for a wide variety of research studies across the field of ethology.
Keyphrases
  • high resolution
  • electronic health record
  • big data
  • deep learning
  • machine learning
  • high throughput
  • case control
  • mass spectrometry
  • data analysis
  • artificial intelligence