Data-intensive science applied to broad-scale citizen science

Identifying ecological patterns across broad spatial and temporal extents requires novel approaches and methods for acquiring, integrating and modeling massive quantities of diverse data. For example, a growing number of research projects engage continent-wide networks of volunteers (‘citizen-scient...

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Bibliographic Details
Published in:Trends in ecology & evolution (Amsterdam) 2012-02, Vol.27 (2), p.130-137
Main Authors: Hochachka, Wesley M., Fink, Daniel, Hutchinson, Rebecca A., Sheldon, Daniel, Wong, Weng-Keen, Kelling, Steve
Format: Article
Language:English
Subjects:
Animal Migration
Animals
Biodiversity
Data Collection - methods
Ecology - methods
Ecology - trends
Hawks - physiology
Models, Theoretical
Population Density
Stochastic Processes
United States
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Summary:Identifying ecological patterns across broad spatial and temporal extents requires novel approaches and methods for acquiring, integrating and modeling massive quantities of diverse data. For example, a growing number of research projects engage continent-wide networks of volunteers (‘citizen-scientists’) to collect species occurrence data. Although these data are information rich, they present numerous challenges in project design, implementation and analysis, which include: developing data collection tools that maximize data quantity while maintaining high standards of data quality, and applying new analytical and visualization techniques that can accurately reveal patterns in these data. Here, we describe how advances in data-intensive science provide accurate estimates in species distributions at continental scales by identifying complex environmental associations.
ISSN:0169-5347
1872-8383
DOI:10.1016/j.tree.2011.11.006