Citizen science and invasive alien species: An analysis of citizen science initiatives using information and communications technology (ICT) to collect invasive alien species observations

Owing to the huge number of species observations that can be collected by non-professional scientists, “citizen science” has great potential to contribute to scientific knowledge on invasive alien species (IAS). Citizen science has existed for centuries, but the recent adoption of information and communications technology (ICT) in this field (e.g. web- or mobile application-based interfaces for citizen training and data generation) has led to a massive surge in popularity, mainly due to reduced geographic barriers to citizen participation. Several challenges exist, however, to effectively utilize citizen-generated data for monitoring IAS (or other species of interest) at the global scale. Here, we conducted a systematic analysis of citizen science initiatives collecting IAS data using ICT, hoping to better understand their scientific contributions and challenges, their similarities/differences, and their interconnections. Through a search of the Scopus database, we identified 26 initiatives whose data had been used in scientific publications related to IAS, and based our analyses on these initiatives. The most common scientific uses of these citizen science data were to visualize the spatial distribution of IAS, better understand their behaviour/phenology, and elucidate citizen science data quality issues. To alleviate data quality concerns, most initiatives (19/26) had mechanisms for verifying citizen observations, such as user-submitted photographs. While many initiatives collected similar data parameters for each species observation, only 54% of the initiatives had a practice of data sharing. This lack of data sharing causes fragmentation of the citizen-generated IAS data, and is likely inhibiting the wider usage of the data for scientific studies on IAS involving large geographic scales (e.g. regional or global) and/or broad taxonomic scopes. To reduce this fragmentation and better consolidate the collected citizen science data, finally we provide some general data sharing guidelines for citizen science initiatives as well as individual volunteers.