Abstract
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.
Highlights
The threat to natural environments and commercial crops from emerging plant pests and pathogens is growing, due to both increased global trade and a changing environment [1,2,3,4]
In order to limit the negative impact of pests and disease outbreaks, it is important to quickly understand their distribution and impact, so that control can be implemented in an expedient manner [17,18]
We investigated the potential to integrate a citizen science dataset collected by Forest Research, which contained landowner reports of acute oak decline (AOD)-affected sites
Summary
The threat to natural environments and commercial crops from emerging plant pests and pathogens is growing, due to both increased global trade and a changing environment [1,2,3,4]. The survey aimed to estimate a national-scale distribution from a limited sample which was constrained by a fixed budget for survey time To achieve this aim, we investigated the potential to integrate a citizen science dataset collected by Forest Research, which contained landowner reports of AOD-affected sites. Selection of hectads was independent of the existing AOD data, hectads that were already known to contain AOD-affected woodlands were not resurveyed, but retained as a subsample of already positive locations This reduced the amount of time required on site, effectively giving a larger survey without increasing its cost. The additional ‘landowner’ reports selected either as a random sample of locations with infected trees or as a biased sample where detection was more likely in high-prevalence locations Both strategies were assessed as two intensities: including either 29 additional infected locations or 145 (1% or 5% of all infected squares, respectively; full methods can be found in electronic supplementary material D)
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