LETTER Assessing citizen science data quality: an invasive species case study Alycia W. Crall 1 , Gregory J. Newman 1 , Thomas J. Stohlgren 2 , Kirstin A. Holfelder 1 , Jim Graham 1 , & Donald M. Waller 3 1 Natural Resource Ecology Laboratory, Colorado State University, Campus Delivery 1499, Fort Collins, CO 80523, USA 2 Fort Collins Science Center, US Geological Survey, 2150 Centre Avenue Bldg C, Fort Collins, CO 80526, USA 3 Department of Botany, University of Wisconsin-Madison, 430 Lincoln Drive, Madison, WI 53706, USA Keywords Citizen science; data quality; invasive species; non-native species; vegetation monitoring; volunteer monitoring protocols. Correspondence Alycia W. Crall, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523–1499, USA. Tel: +(970) 491-2302; fax: +(970) 491-1965. E-mail: Alycia.Crall@colostate.edu Received 11 April 2011 Accepted 5 July 2011 Editor Edward Webb doi: 10.1111/j.1755-263X.2011.00196.x Abstract An increase in the number of citizen science programs has prompted an exam- ination of their ability to provide data of sufficient quality. We tested the abil- ity of volunteers relative to professionals in identifying invasive plant species, mapping their distributions, and estimating their abundance within plots. We generally found that volunteers perform almost as well as professionals in some areas, but that we should be cautious about data quality in both groups. We analyzed predictors of volunteer success (age, education, experience, sci- ence literacy, attitudes) in training-related skills, but these proved to be poor predictors of performance and could not be used as effective eligibility crite- ria. However, volunteer success with species identification increased with their self-identified comfort level. Based on our case study results, we offer lessons learned and their application to other programs and provide recommendations for future research in this area. Introduction Citizen science represents a partnership between volun- teers and scientists to address research questions. These partnerships have expanded in number and scope as a way to connect scientific research to public outreach and education while providing additional resources to professional surveys (Bonney et al. 2009; Lepczyk et al. 2009). Data collected by citizen scientists inform natu- ral resource management (Brown et al. 2001), environ- mental regulation (Penrose and Call 1995), and scientific research (Cooper et al. 2007). Therefore, data quality is paramount and could have far-reaching environmental, social, and/or political implications (Engel and Voshell 2002). Several studies have examined data quality in citizen science programs by determining predictors of partici- pant success (Danielsen et al. 2005). Accuracy rates within these programs tend to vary, and results are rarely made available to the larger citizen science community. Stan- dardizing monitoring protocols, designed by professionals and field-tested with citizen scientists working under re- alistic conditions, can improve data quality and analyses (Delaney et al. 2008). We tested the ability of volunteers to conduct an inva- sive plant species monitoring protocol following 1 day of training. We tested participants’ ability to identify species and implement the protocol compared with professionals to determine eligibility criteria by examining which fac- tors were most strongly associated with performance. To our knowledge, no other study has yet used social predic- tors to assess success in such programs. Methods Participant recruitment We recruited participants from existing volunteer net- works (typical of citizen science programs) and provided Conservation Letters 0 (2011) 1–10 Copyright and Photocopying: c  2011 Wiley Periodicals, Inc. 1