Ecoinformatics Conference Service, International Conference on Ecological Informatics 6

Data quality from "student" citizen scientists collecting plant biodiversity data in urban and suburban settings

Robert D Stevenson, Robert Sheldon

Last modified: 2008-09-13


Science educators often use experiments for teaching in which the outcome is already known. New knowledge is gained by students but not for science. "Canned" labs limit the students' experience of doing real science, but on the other hand, most scientists are skeptical of the data that non scientists collect. For a non majors course, I am developing a plant field project in which college students collect data on the distribution of flowering plants in urban and suburban environments. The project has three components: a field notebook containing drawings, photographs and pressed plants, a site description, and a species list for their site. Students pick their own study site which is usually near their place of residence. Locations include town and state parks, abandoned lots, and areas along transportation corridors. Students are asked to use Newcomb's Guide to Wildflowers as well as internet sites including our Electronic Field Guide site ( and the USDA Plants site ( to aid identification. Students submit their lists electronically and identification is checked by comparison with the images, drawings or collected plants in their field notebooks and our knowledge of the species they thought they found. From 48 sets of student observations, there were 850 plant species observed from over 230 genera. Solidago, Polygonum, Aster, Trifolium, Symphyotrichum, Phytolacca, Daucus, Linaria, Taraxacum, and Ambrosia were the most common genera observed. For a mean list length of 18.2 (s.d = 6.3) species per student, 89% (s.d. = 0.14) was the likely percentage of correctly identified species. Some students became hooked on the identification process while many found it challenging. Feedback from students suggests easier identification tools with smaller numbers of species and more practice will improve identification accuracy. As the accuracy of the data improve, we will be able to test hypotheses about weed and invasive species distributions and urbanization.