The role of passive surveillance and citizen science in plant health

Abstract

The early detection of plant pests and diseases is vital to the success of any eradication or control programme, but the resources for surveillance are often limited. Plant health authorities can however make use of observations from individuals and stakeholder groups who are monitoring for signs of ill health. Volunteered data is most often discussed in relation to citizen science groups, however these groups are only part of a wider network of professional agents, land-users and owners who can all contribute to significantly increase surveillance efforts through "passive surveillance". These ad-hoc reports represent chance observations by individuals who may not necessarily be looking for signs of pests and diseases when they are discovered. Passive surveillance contributes vital observations in support of national and international surveillance programs, detecting potentially unknown issues in the wider landscape, beyond points of entry and the plant trade. This review sets out to describe various forms of passive surveillance, identify analytical methods that can be applied to these "messy" unstructured data, and indicate how new programs can be established and maintained. Case studies discuss two tree health projects from Great Britain (TreeAlert and Observatree) to illustrate the challenges and successes of existing passive surveillance programmes. When analysing passive surveillance reports it is important to understand the observers' probability to detect and report each plant health issue, which will vary depending on how distinctive the symptoms are and the experience of the observer. It is also vital to assess how representative the reports are and whether they occur more frequently in certain locations. Methods are increasingly available to predict species distributions from large datasets, but more work is needed to understand how these apply to rare events such as new introductions. One solution for general surveillance is to develop and maintain a network of tree health volunteers, but this requires a large investment in training, feedback and engagement to maintain motivation. There are already many working examples of passive surveillance programmes and the suite of options to interpret the resulting datasets is growing rapidly.

Keywords: Citizen science; Early warning; Surveillance; Tree health; Unstructured data.

Fig. 1

The ‘passive to active surveillance spectrum’ in plant health and suggested overall probability to detect, report, degree of structure in data collection, and potential search effort for different sources of surveillance. Figure developed from Hester and Cacho (2017)

Fig. 2

Comparison of reports collected through two passive surveillance programmes, each at two time points. Data are shown for sightings of Agrilus biguttatus (a native beetle) collected through the National Biodiversity Network (NBN) and for Acute Oak Decline (AOD, an emerging decline disease where A. biguttatus has been implicated) collected by Forest Research (Brown et al. ; Doonan et al. 2020). For both datasets, the current distribution of observations is shown alongside maps containing only earliest historical records. a Shows NBN reports before 1987 (when Shirt published a red data book for insects (Shirt 1987)) and b shows all NBN reports to 2017; c shows Forest Research records before 2009 (when Denman and Webber first described AOD (Denman and Webber 2009)) and d shows Forest Research reports up to 2017. Data are discussed further by Baker et al. (2018)