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Monitoring of forest pests and diseases is resource-intensive, requiring individual woodlands and trees to be visited and assessed for symptoms. Climate change and increased global connectivity are amplifying the scale of the monitoring challenge, with the number of new plant biosecurity threats increasing each year. Citizen science can increase the scale of pest and disease surveys. However, it is argued that citizen science data can be biased and inaccurate. This study examines potential biases in citizen science data by focusing on the case study of acute oak decline (AOD), a disease syndrome impacting native oaks within the UK associated with the beetle Agrilus biguttatus. Analysis was performed using two contrasting citizen science data set sources: the National Biodiversity Network (NBN) Atlas, which is a repository for citizen science data sets, and Tree Alert, a targeted citizen science project that encouraged landowners and the public to report the occurrence of AOD. For both data sets, detection was more likely in locations with higher Coleoptera reports, suggesting that there are hubs of recorder activity. For the NBN data set, A. biguttatus was more likely to be found in areas where historic parks and gardens were present. For the Tree Alert data set, A. biguttatus was less likely to be found on open access land, indicating that the programme was successful in engaging private landowners. These results indicate that understanding sources of bias within reporting schemes is an important step in data analysis and that the inclusion of structured survey designs would enable the extent of biases to be documented.