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The eBird enterprise: An integrated approach to development and application of citizen science Public Deposited

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  • Citizen-science projects engage volunteers to gather or process data to address scientific questions. But citizen-science projects vary in their ability to contribute usefully for science, conservation, or public policy. eBird has evolved from a basic citizen-science project into a collective enterprise, taking a novel approach to citizen science by developing cooperative partnerships among experts in a wide range of fields: population and distributions, conservation biologists, quantitative ecologists, statisticians, computer scientists, GIS and informatics specialists, application developers, and data administrators. The goal is to increase data quantity through participant recruitment and engagement, but also to quantify and control for data quality issues such as observer variability, imperfect detection of species, and both spatial and temporal bias in data collection. Advances at the interface among ecology, statistics, and computer science allow us to create new species distribution models that provide accurate estimates across broad spatial and temporal scales with extremely detailed resolution. eBird data are openly available and used by a broad spectrum of students, teachers, scientists, NGOs, government agencies, land managers, and policy makers. Feedback from this broad data use community helps identify development priorities. As a result, eBird has become a major source of biodiversity data, increasing our knowledge of the dynamics of species distributions, and having a direct impact on the conservation of birds and their habitats.
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  • Sullivan, B. L., Aycrigg, J. L., Barry, J. H., Bonney, R. E., Bruns, N., Cooper, C. B., ... & Kelling, S. (2014). The eBird enterprise: An integrated approach to development and application of citizen science. Biological Conservation, 169, 31-40. doi:10.1016/j.biocon.2013.11.003
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  • Multiple facets of this work have been supported by the following National Science Foundation awards: NSF-ISE:0087760, NSFITR:46456, BIO-BDI:49605, CISE-SEI+II:50913, NSF-EHR:53811, BIO-RAPID:62570, NSF-CDI TYPE II:64083, NSF IIS:1017793, NSF IIS-1125098, DEB:110008, DEB:100009, and CISE-SOCS:66281. We thank the Wolf Creek Charitable Foundation and the Leon Levy Foundation for continued support.
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