PSG 2012 Hawaii abstracts - Pacific Seabird Group
PSG 2012 Hawaii abstracts - Pacific Seabird Group
PSG 2012 Hawaii abstracts - Pacific Seabird Group
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abundance at colonies. Sensors recorded ambient noise at Forster’s Tern (Sterna forsteri) breeding<br />
colonies in San Francisco Bay for two breeding seasons. We used an automated method (spectrogram<br />
cross-correlation) to detect and count tern vocalizations from recordings. We calculated mean calling<br />
rates at different time scales and compared these to active nest counts at colonies. Our results show that<br />
acoustic activity was a strong index of colony size within years (2009 r 2 =.84, n=5; 2010 r 2 =.59, n=7) and<br />
a powerful index of change in colony size between years (r 2 =.92, n=5). We also estimated the predictive<br />
power of an acoustic activity index to detect population changes. Quantifying the relationship between<br />
acoustic activity and relative abundance is a fundamental step in designing effective acoustic monitoring<br />
programs for seabirds and other vocalizing wildlife. These tools present low-cost, scalable and<br />
comparable tools for measuring population trends and responses to conservation actions.<br />
MONITORING MARBLED MURRELETS WITH ACOUSTIC SENSORS – COMPARING<br />
AUTOMATED DETECTIONS WITH HUMAN AUDIO-VISUAL MONITORING<br />
Abraham L. Borker* 1 , Matthew W. McKown 1 , Portia Halbert 2 , Cody Sullivan 1 , Bernie R. Tershy 1 , and<br />
Donald A. Croll 1 , 1 CCAL - Department of Ecology and Evolutionary Biology, University of California<br />
Santa Cruz, 100 Shaffer Road, Santa Cruz, CA 95060 USA, aborker@ucsc.edu; 2 California State Parks,<br />
303 Big Trees Park Road, Felton, CA 95060 USA<br />
Acoustic sensors provide a potentially low-cost alternative for monitoring Marbled Murrelets in remote<br />
areas over long survey periods. To assess the efficacy of this approach we compared monitoring<br />
methodologies at 7 sites in the Santa Cruz Mountains (CA) in 2010 – audio-visual surveys by trained<br />
observers and acoustic monitoring with automated acoustic sensors. We compared audio/visual<br />
detections of murrelets by trained observers with acoustic detections of murrelets, identified from sensor<br />
recordings using automated spectrogram cross-correlation. Mean automated acoustic detections were<br />
highly correlated with mean rates of human a/v detections across sites (r 2 =.97 n=7, p=
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