Assessing citizen science data quality: an invasive species case study

TLDR

An increase in citizen science programs has prompted an examination of their ability to provide data of sufficient quality. The study aimed to evaluate whether volunteers could match professionals in identifying invasive plant species, mapping their distributions, and estimating abundance within plots. The authors compared volunteer and professional performance by having both groups identify species, map distributions, and estimate abundance in plots. Volunteers performed almost as well as professionals in some tasks, but data quality should be approached cautiously for both groups; predictors such as age, education, experience, science literacy, and attitudes were poor, though self‑identified comfort level correlated with better species identification.

Abstract

An increase in the number of citizen science programs has prompted an examination of their ability to provide data of sufficient quality. We tested the ability 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, science literacy, attitudes) in training-related skills, but these proved to be poor predictors of performance and could not be used as effective eligibility criteria. 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.