Brown Nathan, van den Bosch Frank, Parnell Stephen, Denman Sandra
Computational and Systems Biology, Rothamsted Research, Harpenden, UK
Computational and Systems Biology, Rothamsted Research, Harpenden, UK.
Proc Biol Sci. 2017 Jul 26;284(1859). doi: 10.1098/rspb.2017.0547.
The number of emerging tree diseases has increased rapidly in recent times, with severe environmental and economic consequences. Systematic regulatory surveys to detect and establish the distribution of pests are crucial for successful management efforts, but resource-intensive and costly. Volunteers who identify potential invasive species can form an important early warning network in tree health; however, what these data can tell us and how they can be best used to inform and direct official survey effort is not clear. Here, we use an extensive dataset on acute oak decline (AOD) as an opportunity to ask how verified data received from the public can be used. Information on the distribution of AOD was available as (i) systematic regulatory surveys conducted throughout England and Wales, and (ii) ad hoc sightings reported by landowners, land managers and members of the public (i.e. 'self-reported' cases). By using the available self-reported cases at the design stage, the systematic survey could focus on defining the boundaries of the affected area. This maximized the use of available resources and highlights the benefits to be gained by developing strategies to enhance volunteer efforts in future programmes.
近年来,新出现的树木疾病数量迅速增加,造成了严重的环境和经济后果。进行系统的监管调查以发现并确定害虫的分布情况,对于成功开展管理工作至关重要,但此类调查资源密集且成本高昂。识别潜在入侵物种的志愿者能够在树木健康方面形成一个重要的早期预警网络;然而,这些数据能告诉我们什么,以及如何才能最好地利用它们为官方调查工作提供信息并加以指导,目前尚不清楚。在此,我们利用一个关于急性橡树衰退(AOD)的广泛数据集,探讨如何利用从公众那里获得的经核实的数据。AOD分布的信息来源有两个:一是在英格兰和威尔士各地进行的系统监管调查,二是土地所有者、土地管理者和公众报告的临时发现情况(即“自我报告”案例)。通过在设计阶段使用现有的自我报告案例,系统调查能够集中精力确定受影响区域的边界。这最大限度地利用了可用资源,并凸显了通过制定战略来加强未来项目中的志愿者工作所带来的好处。