Introduction Limited knowledge of these species: – Yellow Rail – Nelsons Sparrow – Le Contes Sparrow

Conservation Loss and degradation of wetlands due to human activity All three = Species of Greatest Conservation Need in MN Yellow Rail = species of high concern – North American Waterbird Conservation Plan – Northern Prairie and Parkland Waterbird Conservation Plan

Systematic surveys are needed – USFWS & USGS: Standardized North American Marsh Bird Monitoring Protocols (Conway 2009) However… – Tendencies to call at night = often times missed by surveys Also… – Secretive habits – Cryptic coloration – Difficult to access habitat Dr. Jim Petranka

Autonomous Recording Units (ARUs) Good candidates for surveying with ARUs that can be analyzed in a laboratory Benefits: – Minimize observer biases – Permanent records of surveys – 24 hr/day data collection – Limited numbers of expert field observers Disadvantages: – No visual detections – Estimating distances and numbers of birds? – Time spent going through recordings

Song Scope Bioacoustics Recognition Software Ideally, you build recognizers to scan recordings

Main Objectives Compare the detection probabilities of these three species using ARUs versus the standard marsh bird monitoring protocol. Use ARU recordings to determine temporal (daily and seasonal) changes in species calling and environmental factors affecting detection, in order to improve survey efforts

Field Methods 16 survey routes, 10 stations 22 ARUs (per season; 1-4 ARUs/route) – SM1 Song Meter, Wildlife Acoustics – 10 min every 15 min, from 20:00 until 08:00

Field Methods Standard Marsh Bird Protocol – Call-broadcast surveys-- Yellow Rail call only – Start 1 hour after sunset – May-June = survey season – 4 times/season

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

How many 6 minute ARU recordings to be at least 95% sure of detection? 6 Minute Surveys Species12345 YERA72.6%92.3%97.8%.. LCSP53.2%80.7%93.1%97.8%. NESP51.1%75.9%88.0%94.0%97.0%

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)

Le Contes Sparrow

Nelsons 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: