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被动监测与公民科学在植物健康中的作用。

The role of passive surveillance and citizen science in plant health.

作者信息

Brown Nathan, Pérez-Sierra Ana, Crow Peter, Parnell Stephen

机构信息

Woodland Heritage, P.O. Box 1331, Cheltenham, GL50 9AP UK.

Tree Health Diagnostics and Advisory Service, Forest Research, Alice Holt Lodge, Farnham, Surrey, GU10 4LH UK.

出版信息

CABI Agric Biosci. 2020;1(1):17. doi: 10.1186/s43170-020-00016-5. Epub 2020 Oct 30.

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.

摘要

早期发现植物病虫害对于任何根除或控制计划的成功至关重要,但监测资源往往有限。然而,植物卫生当局可以利用个人和利益相关者群体的观察结果,这些人正在监测植物健康状况的迹象。志愿数据通常是在公民科学团体的背景下讨论的,然而这些团体只是更广泛的专业机构、土地使用者和所有者网络的一部分,他们都可以通过“被动监测”为大幅增加监测工作做出贡献。这些临时报告是个人的偶然观察结果,他们发现病虫害迹象时不一定是在刻意寻找。被动监测为国家和国际监测计划提供了至关重要的观察结果,在更广泛的区域内发现潜在的未知问题,而不仅仅局限于入境点和植物贸易。本综述旨在描述各种形式的被动监测,确定可应用于这些“杂乱”非结构化数据的分析方法,并说明如何建立和维持新的监测计划。案例研究讨论了来自英国的两个树木健康项目(TreeAlert和Observatree),以说明现有被动监测计划面临的挑战和取得的成功。在分析被动监测报告时,重要的是要了解观察者发现并报告每个植物健康问题的概率,这将因症状的明显程度和观察者的经验而有所不同。评估报告的代表性以及它们是否在某些地点更频繁出现也至关重要。越来越多的方法可用于从大型数据集中预测物种分布,但需要更多工作来了解这些方法如何应用于新引入等罕见事件。一般监测的一个解决方案是建立并维持一个树木健康志愿者网络,但这需要在培训、反馈和参与方面进行大量投资以保持积极性。被动监测计划已经有很多实际例子,并且用于解释所得数据集的选项套件正在迅速增加。

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