Testing the ability of Kaleidoscope Pro software to detect and cluster sounds embedded within anthropogenic noise.
Dr. Darren S Proppe, Calvin College, Grand Rapids, MI
I am pleased to announce that Chad Apol, an undergraduate biology student at Calvin College, has been hired to conduct full-time research this summer on the impacts of noise on detectability in acoustic recordings. Chad has spent the semester learning the techniques of bioacoustical analysis and is currently becoming proficient in Kaleidoscope. He has just begun a course in field natural history that will prepare him to identify the birds he will be seeing and hearing this summer. We have familiarized ourselves with the SM4 recordings units, and we have purchased a noise-making sleep machine that will be used to introduce noise to our recordings on a very limited spatial scale. We are in the process of finalizing field sites for our experiments. We will use at least 10 abandoned oil pads located in Northern Michigan. They provide both a forested and open ecosystem for our work. We intend to test varying levels of white, pink, and Brownian noise; comparing Kaleidoscope's ability to detect and appropriately cluster bird vocalizations in comparison to quiet controls. Recording will begin at the end of May and continue throughout the summer. No data yet, but we are itching to get started. More soon!
Recorders are in the field! We are up to 16 complete trials, each containing one microphone exposed to noise playback, and a control microphone that is unexposed. Noise playback comes in the form of white, pink, and brownian played at 40, 50, 60, and 70 dBA. We have trained Kaleidoscope to detect five species commonly found in our recordings: blue jay (Cyanocitta cristata), ovenbird (Seiurus aurocapilla), red-eyed vireo (Vireo olivaceus), Eastern wood-pewee (Contopus virens), and black-throated green warbler (Setophaga virens). The first results are coming in, but it's too early to describe any patterns. We've also decided to add a human detection component. Chad will be visually detecting vocalizations in a subset of our recordings to compare human detection rates in varying noise levels to the capabilities of Kaleidoscope. Stay tuned...
Kaleidoscope analysis is well underway, with nearly half of the data from our sites having been compiled. We are already seeing significant trends for a number of parameters. One of the expected, yet interesting, preliminary results is that Kaleidoscope software has been more successful in correctly detecting vocalizations from a control SM4 unit compared to a SM4 unit subjected to noise input (see Figure). We will be completing data analysis soon and are looking forward to reporting additional trends related to noise level and noise type.