Animals Wildlife The Art of Listening to Birds With David Sibley By Melissa Breyer Melissa Breyer Editorial Director Hunter College F.I.T., State University of New York Cornell University Melissa Breyer is Treehugger’s editorial director. She is a sustainability expert and author whose work has been published by the New York Times and National Geographic, among others. Learn about our editorial process Updated May 29, 2020 CC BY 2.0. Wikimedia Commons Share Twitter Pinterest Email Animals Wildlife Pets Animal Rights Endangered Species In which the walking ornithology encyclopedia known as David Sibley showed me how to identify birds by their songs in New York City's Central Park. It might seem the unlikeliest of places, but there I found myself – in the middle of a city with soaring mountains of concrete and steel, 6000 miles of streets, 8.5 million humans – looking for little birds with one of the foremost experts on the topic, David Sibley. A small group of us gathered with Sibley at Central Park early in the morning to take the bird-song identifying app, Song Sleuth, out for a spin. The app (which we wrote about in February) turns the already mysterious wonder box known as an iPhone into something even more magical. Basically, at the touch a few buttons, it will tell you what birds are hiding in the trees around you. As Sibley told us, "It's really Star Trek technology." The nifty avian detective was created by Wildlife Acoustics in collaboration with Sibley. Wildlife Acoustics has been working for years on developing algorithms for wildlife study using software based on similar concepts to speech recognition software; or in this case, tweet recognition. Sherwood Snyder, the product manager at Wildlife Acoustics – as well as a self-described "obsessive birder" and actual developer of Song Sleuth – listened to some 250,000 recordings of bird song in the creation of the app. He came along with us as well. Given the company's background in the field and the work put into Song Sleuth, it's little wonder that it actually works. And work, it does. I know that because we were walking around Central Park with David Sibley! He would say, "Oh, warbling vireo in the distance," and like a pocket fortune telling machine, Song Sleuth would present the information for a warbling vireo. Sibley's ear would perk again, "cedar waxwing!" and the Star Trekish tricorder offered a cedar waxwing for confirmation. © Melissa Breyer/Song Sleuth The son of a Yale ornithologist, and birding since a child – not to mention the author of a collection of definitive guides to North American birds, of which more than 1.75 million copies have been sold all together – Sibley clearly does not need an iPhone to tell him what birds are in the vicinity. Walking through the woods of the park, resounding with what seemed like the songs of about a million birds, I asked if he knew every bird we were hearing – he smiled and said yes. He pointed out robins sounding somewhat strident, before spotting an American kestrel from the corner of his eye. (As a member of the falcon family, the robins were alerting the small feathered hunter that they knew he was there and he could kindly keep away from their kids.) Sibley explained that a grey catbird hopping around on the ground – and identified by its song long before being seen – was young as evidenced by its color and awkward teen gestures. He explained the difference between mockingbird songs and other mimickers. But even for a man who knows everything about birds, he loves the app and uses it all the time, mentioning that he also really enjoys the app's spectrogram. This is an integral part of the app which helps analyse the songs. What might sound like pretty similar chirps to the human ear has a whole visual range when shown on these graphs displaying the spectrum of frequencies in a bird’s vocalization. The song of each bird has signature shapes and patterns; Snyder likened it to calligraphy. © Melissa Breyer/Song Sleuth And it's more than just a birdsong Shazam, the app includes Sibley's iconic illustrations and detailed descriptions, as well as range maps and charts developed exclusively for Song Sleuth that show the likelihood of a bird's presence in the user's area at any given time of year. Sibley says that he hopes the app will prove useful for everyone from serious birders to the simply bird curious. He told us that people are always asking him about the backyard birds that they hear; for people who don't have access to a birder, they can use the app to learn about their avian visitors. One thing I particularly like – aside from the impossible magic of it all – is that a user can build a birdsong library from their recordings. What a cool souvenir, to be able to save the sound of a bird singing. I also like that the app can remember the location, date, and time of each recording, which it can then display on a Google-enabled map – click on a recording on the map to hear it again and to see the species, date, and more information about the bird. I know that my map will be a little cluster around NYC of urban birds and migrating guests ... and soon I'll be able to call each one of them by name. Song Sleuth is currently available for iPhone; the $9.99 well worth what you get in return. An Android version is expected this fall. And once you have David Sibley in pocket, so to speak, follow these Song Sleuth tips in the fine art of birding by ear. 1. Start small. Begin by learning the songs of the birds that come to your feeders. As you learn songs, expand your area to a local park, and then further. 2. The best times of day for birding is the morning and evening, but birds can be heard any time of day. 3. The best times of year for birding is in the migration seasons of spring and fall, but birds can be heard year round. 4. Birds are everywhere. As you vary your environment from woodlands to wetlands to urban spaces you will expand the species you will encounter. 5. Reference Song Sleuth’s integrated Sibley’s Guide to Birds to learn likely birds in your area at any given time and the likely environment they will be found in.