Elsevier

Biological Conservation

Volume 169, January 2014, Pages 31-40
Biological Conservation

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

https://doi.org/10.1016/j.biocon.2013.11.003Get rights and content

Highlights

  • eBird is a rapidly evolving citizen-science project that meets the needs of a broad user community.

  • We are developing a novel approach to citizen science based on interdisciplinary collaboration.

  • We have successfully increased data quantity, while maintaining rigorous data quality.

  • eBird is a major source of avian biodiversity data, now being used across many disciplines.

  • Feedback and communication from all aspects of the eBird enterprise improve the project’s success.

Abstract

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.

Introduction

Citizen science is gaining momentum (Irwin, 1995, Dickinson et al., 2010), but citizen-science projects vary in their ability to deliver useful data for research and conservation. Tulloch et al. (2013) reviewed the efficacy of various citizen-science approaches, and recommended a series of actions that could improve the impact and utility of citizen-science data. These included incorporating more rigorous sampling techniques into unstructured data collection processes, improving data quality, broadening the data-user community, and improving communication between those using the data and those collecting it. We suggest that achieving these objectives is best accomplished by expanding the range of activities routinely encompassed with the running of citizen-science projects to extend beyond data collection to include community engagement, data curation, data synthesis and analysis, pattern visualization, and delivery of results to a broad community of possible stakeholders. In this paper we will illustrate this point using eBird (ebird.org; Sullivan et al., 2009) as our example. eBird has evolved from a stand-alone citizen-science project focused on collecting data, into a cooperative partnership involving several distinct user groups spanning multiple scientific domains and dozens of partner organizations, each with its own unique interests in the project’s success.

eBird collects information about the distribution and abundance of birds, taking advantage of the enormous popularity of watching birds to create a global network of volunteers who submit bird observations via the Internet to a central data repository. Through a combination of broad-based community engagement and global partnerships, the volume of data coming into eBird has increased exponentially (30–40% annually) for a decade (Fig. 1). By mid-year 2013, over 140 million observations had been submitted by 150,000 separate observers, who spent 10.5 million hours in the field collecting data. While global in scope, the majority of eBird data still come from North America.

Not only has input of data grown, but output of information has grown as well, fostered by collaboration among researchers from diverse scientific domains including ornithology, landscape ecology, macroecology, biogeography, computer science, statistics, computational sustainability, human computation, informal science education, conservation science, and public policy. Engagement in eBird across these domains creates continuous investment and feedback from a diverse community that helps shape eBird to meet the needs of a wide array of both academic and non-academic audiences. This communication is aided by eBird’s integrated project structure involving participants who collect data, researchers analyzing the data, agencies adopting policies based on the data, and land managers taking direct conservation action (Fig. 2). Ultimately, these collaborations have enabled us to increase both the quantity and the quality of useful data available for analysis. Further, this broad spectrum of intellectual contributions and applications has fundamentally changed our view of the project, which we now see as a collective enterprise.

Section snippets

Increasing data quantity while improving data quality

Hochachka et al. (2012) showed that maximizing the analytical value of citizen-science data requires striking the right balance between data quantity and data quality. Large quantities of data are needed because the per-datum information content of citizen-science data is often low, because most projects use relatively simple protocols. However, we also need to identify minimal standards of quality, and ideally raise these standards through time. Thus, we have focused on both growing the

Access to eBird data

Successful citizen science does not end at data collection; data management and delivery are also critical. eBird data are maintained in a highly managed centralized data infrastructure that serves as a benchmark among citizen-science programs (Kelling, 2011). A core principle of eBird is providing free and open access to data for a broad spectrum of data consumers. This diversity of users and uses of eBird data requires that we develop and curate multiple eBird data products to meet the

Diverse uses of eBird data

By combining the strengths and motivation of volunteer observers with computer technologies, the eBird project is generating biodiversity data for an increasing variety of uses. In the past decade, more than 90 peer-reviewed publications either used eBird data or studied aspects of the eBird project. Over the past year, more than 1100 individuals from 40 countries have requested eBird data, making more than 3400 downloads representing ca. 2.6 terabytes of data. Data users were classified into

The future

We anticipate a series of key future developments that will help all facets of the eBird enterprise continue to evolve.

Conclusion

Citizen science has the potential to transform our understanding of many ecological processes. For studies of avian ecology, data from citizen-science projects offer the ability to test hypotheses at spatial and temporal scales never before possible. Due to their popularity, birds lend themselves to this approach perhaps better than any other organism. However, in order to be successful, careful attention must be paid to all aspects of the project, from data collection to data delivery and use.

Acknowledgments

We thank the thousands of eBird participants around the world who serve as the engine for the eBird enterprise, and the hundreds of regional editors who volunteer their time to review incoming data. We thank our international partners. We thank Tim Lenz, Kevin Webb, and Tim Levatich for their technical work on the project. Multiple facets of this work have been supported by the following National Science Foundation awards: NSF-ISE:0087760, NSF-ITR:46456, BIO-BDI:49605, CISE-SEI+II:50913,

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