Knowledge gap and conditional receptivity: why tree and forest professionals underutilize citizen science for quarantine pest detection in France
CASTAGNEYROL, B.; Bah, S.; Bedessem, B.; de Groot, M.; Ennabih, A.
Show abstract
Exotic pests and pathogens pose a major threat to forest ecosystems. Early detection of newly introduced organisms is critical for implementing effective eradication measures before they become established. Citizen science platforms have emerged as promising sources of biodiversity data for detecting invasive pests and pathogens, yet their integration into formal biosecurity surveillance remains limited. Using France as a case study, we surveyed 101 professionals involved in forest and urban tree management and pest surveillance to assess their knowledge of regulated tree pests and pathogens and their attitudes towards online citizen science platforms for biosecurity applications. We focused on ten focal species representing different regulatory statuses under EU legislation. We assessed the knowledge professionals have of these species and their regulatory status, and explored sources of variation in their opinions regarding the use of citizen science platforms as a tool for post-border biosecurity. Experts involved in mandatory surveillance of regulated organisms (SORE experts) demonstrated consistent knowledge of quarantine pests, whereas other professionals knowledge varied by species, with greater familiarity for non-quarantine, widely distributed pests. Half of respondents used citizen science platforms, predominantly to consult species distribution rather than to contribute observations. Professionals receptivity to citizen science increased significantly when species were perceived as easy to identify, but they expressed more confidence in citizen science for monitoring established pests than for the early detection of quarantine species. The survey reveals that while citizen science platforms are known and valued as information sources, they remain underutilized as mechanisms for sharing field observations, even among surveillance professionals.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sources 91%
- Conservation networks do not match the ecological requirements of amphibians 90%
- A pipeline for assessing the quality of iNaturalist data and images and the importance of metadata and image quality control when using crowd-sourced databases. 90%
Similar papers in this journal
Similar papers in this journal
- Mothbox: inexpensive, lightweight, automated light trap for scalable insect biodiversity monitoring 91%
- Real-time alerts from AI-enabled camera traps using the Iridium satellite network: a case-study in Gabon, Central Africa 90%
- Thinking like a naturalist: enhancing computer vision of citizen science images by harnessing contextual data 90%
Similar papers in this journal
- Understanding pollination in urban food production: the importance of data validation and participant feedback for citizen science project design 92%
- Building a botanical foundation for perennial agriculture: Global inventory of wild, perennial herbaceous Fabaceae species 91%
- Brazil Seed Transfer Zones: Supporting Seed Sourcing for Climate-Resilient Ecosystem Restoration 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.