Brown, N 
ORCID: https://orcid.org/0000-0003-3590-0538, Pérez-Sierra, A, Crow, P and Parnell, SR ORCID: https://orcid.org/0000-0002-2625-4557
2020,
'The role of passive surveillance and citizen science in plant health'
, CABI Agriculture and Bioscience, 1 (1)
, p. 17.
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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.
| Item Type: | Article |
|---|---|
| Additional Information: | ** From Springer Nature via Jisc Publications Router ** Licence for this article: https://creativecommons.org/licenses/by/4.0/ **Journal IDs: eissn 2662-4044 **Article IDs: publisher-id: s43170-020-00016-5; manuscript: 16 **History: collection 12-2020; published_online 30-10-2020; online 30-10-2020; accepted 06-10-2020; registration 06-10-2020; submitted 21-08-2020 |
| Schools: | Schools > School of Environment and Life Sciences |
| Journal or Publication Title: | CABI Agriculture and Bioscience |
| Publisher: | BioMed Central |
| ISSN: | 2662-4044 |
| Related URLs: | |
| Funders: | Woodland Heritage (GB), Forest Research (UK), Natural Environment Research Council (NERC), Biotechnology and Biological Sciences Research Council (BBSRC) |
| SWORD Depositor: | Publications Router |
| Depositing User: | Publications Router |
| Date Deposited: | 03 Nov 2020 14:33 |
| Last Modified: | 16 Feb 2022 05:53 |
| URI: | https://usir.salford.ac.uk/id/eprint/58673 |
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