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Objective 1: Comparing the Two Survey Methods. Methods: Isolated all 6 minute recorded standard surveys (172 in total) Use “recognizers” to automatically detect and identify target species calls on recordings NO!! Ran into problems: missed detections and too many false positives.
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Objective 1: Comparing the Two Survey Methods Methods: • Isolated all 6 minute recorded standard surveys (172 in total) • Use “recognizers” to automatically detect and identify target species calls on recordings • NO!! Ran into problems: missed detections and too many false positives
Manual Scan Method • Resorted to the “Manual Scan” Method • Quickly visually and aurally scan through recording to detect target species • Robust design occupancy model in Program MARK
Probability of Detection -Each species -Each survey repetition -Each survey method
Why? • Most calls not detected on ARU recording, but that were detected during Standard Survey, were too faint or not “strong” enough to be recorded by ARU • Reduced detection by ARUs was likely due to human observers being able to detect birds at greater distances
However • Because ARUs are in the field for longer periods than human observers, there are more cumulative opportunities for detection
Objective 2: Factors affecting detection • Looking at temporal and environmental variables that may affect calling and/or detection of these species • Generalized linear mixed models in R • Presence/absence from 3035 three minute recordings, from 43 ARU stations • Hourly weather data
Variables of Interest • Random effect = Survey Site • Fixed effects = • Year • Julian day • Precipitation (yes or no) • Temperature • Wind speed • Atmospheric pressure • Moonlight • Hours after sunset
Yellow Rail • Precipitation No precip. = 0.63(95%CI = 0.55 and 0.71) Precip. = 0.47(95%CI = 0.36 and 0.59)
Nelson’s Sparrow • Precipitation • No precip. = 0.22(95%CI = 0.16 and 0.30) • Precip. = 0.08(95%CI = 0.03 and 0.16
Management Implications • Incorporate these factors into existing survey protocols to improve survey efforts • Standard surveys • Use of ARUs • Improvement of systematic surveys
Acknowledgements Funding: • HAPET – US Fish and Wildlife Service • Agassiz National Wildlife Refuge • South Dakota State University