Citizen science can complement professional invasive plant surveys and improve estimates of suitable habitat

Aim Citizen science is a cost-effective potential source of invasive species occurrence data. However, data quality issues due to unstructured sampling approaches may discourage the use these observations by and conservation professionals. This study explored utility low-structure iNaturalist citizen in plant monitoring. We first examined prevalence taxa biases associated with Using four as examples, we then compared professional agency used two datasets model suitable habitat for each species. Location Hawai'i, USA. Methods To estimate data, number recorded botanical checklists Hawai'i. Sampling bias was quantified along gradients site accessibility, protective status vegetation disturbance using index. Habitat suitability modelled Maxent, from iNaturalist, agencies stratified subsets Results were biased towards species, which frequently areas higher road/trail density disturbance. Professional example tended occur less accessible, native-dominated sites. models based on versus showed moderate overlap different distributions across classes. Stratifying had little effect how distributed this study. Main Conclusions Opportunistic have complement expand monitoring, found often affected inverse biases. Invasive represented high proportion observations, environments that not captured surveys. Combining thus led more comprehensive estimates habitat.