eBird: Engaging Birders in Science and Conservation

eBird: Engaging Birders in Science and Conservation

Chris Wood, Brian Sullivan, Marshall Iliff, Daniel Fink, Steve Kelling

Identifying a species is a complex task that relies upon a combination of factors. Observers must be able to process impressions of shape, size, and behavior under variable conditions. As this process takes place, the observer must reconcile these impressions against a list of species most likely to occur at that specific location and date, and constantly recalibrate until the two agree, and the species is correctly identified. Only humans can make this difficult computation of classifying organisms to the species level. And for birds, tens of thousands of people do this every day for fun.

For more than two hundred years the public has contributed significantly to our understanding of bird identification, distribution, and abundance [1]. Building on this tradition, eBird (http://ebird.org/) is a citizen science project that takes advantage of numerous information technologies to engage a global network of birders to report their bird observations to a centralized database [2]. Anyone, anywhere, and at anytime can submit observations of birds via the Internet or through a variety of handheld devices. These amassed observations provide scientists, researchers, and amateur naturalists with data about bird distribution and abundance across varying spatio-temporal extents. All data are free and readily accessible through the Avian Knowledge Network [3],[4]. eBird data have been used in a wide variety of applications, from highlighting the importance of public lands in conservation [5] to studies on evolution [6], and to explore biogeography [7].

eBird is part of the growing field of human computation, which focuses on harnessing human intelligence to solve computational problems that are beyond the scope of existing artificial intelligence algorithms [8]. Many of these services use the web, and include game-based approaches such as the ESP Game, which has collected millions of image labels [9]; FoldIt, which attempts to predict the structure of a protein by taking advantage of humans’ puzzle solving abilities [10]; Galaxy Zoo, which has engaged more than 200,000 participants to classify more than 100 million galaxies collected during the Sloan Digital Sky Survey [11]; and reCAPTCHA, which provides security measures on the web while transcribing old print material one word at a time [12]. In this paper, we describe our experiences in developing the eBird network of volunteers, whose observations provide an open data resource containing the most current and comprehensive information on bird distribution, migratory pathways, population trends, and landscape use.

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