Trends in Ecology & Evolution
ReviewSpecial Issue: Ecological and evolutionary informaticsData-intensive science applied to broad-scale citizen science
Section snippets
The need for citizen-science data in ecology
The conservation of species begins with an understanding of the distribution, abundance, habitat preferences and movements of organisms across wide geographic areas and over long periods of time. Although inroads have been made into automating the collection of information on species occurrence 1, 2, 3, typically only human observers can reliably identify organisms to the species level [4]. Intensive surveys made by expert observers can accurately identify patterns of species occurrence within
Designing and implementing broad-scale citizen-science projects
Maximizing the information obtained from broad-scale citizen-science projects that gather species occurrence data depends on finding the proper balance between data quantity and quality. Quantity is important, because a sufficiently large volume of data with relatively lower per-datum information content can contain more information for broad-scale species distribution estimates than a smaller amount of higher quality data [20]. High data quality is essential and requires attention to the
Extracting ecological and evolutionary insights during analysis
Effective research requires clearly articulated questions. Typically, these questions are formulated prior to data collection, allowing the data collection processes to be tailored to help answer the questions identified 10, 24. Under such circumstances, the types of analysis used will typically be those conventionally used by ecologists (Hochachka, W.M. et al., unpublished data). By contrast, many broad-scale observational data sets, which include citizen-science data, are collected with only
Concluding remarks
In this review, we have illustrated some of the unique challenges inherent in broad-scale citizen-science data sets and how novel data-intensive techniques can overcome these challenges. Although our discussion has focused on one citizen-science project, eBird, the general approaches that we have taken to designing the data collection and analyses processes are more widely applicable. Our experience has shown that an uncomplicated protocol and appropriate rewards for volunteer participation is
Acknowledgements
We thank R. Bonney, T. Dietterich, B. Sullivan and three anonymous reviewers for improving the clarity of our article. This work was funded by the Leon Levy Foundation, Wolf Creek Foundation and the National Science Foundation (Grant Numbers OCI-0830944, CCF-0832782, ITR-0427914, DBI-1049363, DBI-0542868, DUE-0734857, IIS-0748626, IIS-0844546, IIS-0612031, IIS-1050422, IIS-0905385, IIS-0746500, AGS-0835821, CNS-0751152, CNS-0855167, TG-DEB110008).
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