The Success of the Horse-Chestnut Leaf-Miner, Cameraria ohridella, in the UK Revealed with Hypothesis-Led Citizen Science

Abstract

Citizen science is an increasingly popular way of undertaking research and simultaneously engaging people with science. However, most emphasis of citizen science in environmental science is on long-term monitoring. Here, we demonstrate the opportunities provided by short-term hypothesis-led citizen science. In 2010, we ran the ‘Conker Tree Science’ project, in which over 3500 people in Great Britain provided data at a national scale of an insect (horse-chestnut leaf-mining moth, Cameraria ohridella) undergoing rapid range-expansion. We addressed two hypotheses, and found that (1) the levels of damage caused to leaves of the horse-chestnut tree, Aesculus hippocastanum, and (2) the level of attack by parasitoids of C. ohridella larvae were both greatest where C. ohridella had been present the longest. Specifically there was a rapid rise in leaf damage during the first three years that C. ohridella was present and only a slight rise thereafter, while estimated rates of parasitism (an index of true rates of parasitism) increased from 1.6 to 5.9% when the time C. ohridella had been present in a location increased from 3 to 6 years. We suggest that this increase is due to recruitment of native generalist parasitoids, rather than the adaptation or host-tracking of more specialized parasitoids, as appears to have occurred elsewhere in Europe. Most data collected by participants were accurate, but the counts of parasitoids from participants showed lower concordance with the counts from experts. We statistically modeled this bias and propagated this through our analyses. Bias-corrected estimates of parasitism were lower than those from the raw data, but the trends were similar in magnitude and significance. With appropriate checks for data quality, and statistically correcting for biases where necessary, hypothesis-led citizen science is a potentially powerful tool for carrying out scientific research across large spatial scales while simultaneously engaging many people with science.

Detecting host–parasitoid interactions in an invasive Lepidopteran using nested tagging DNA metabarcoding

“…The development of parasitism often exhibits a lag period of some years after the arrival of a new host (e.g. Stone et al., for natural communities; Pocock & Evans, for another example of an invasive Lepidopteran species in the United Kingdom), and much of the parasitoid community associated with OPM in its native range may simply not be present in the United Kingdom, or even if present as a taxonomic species, the local race may be an ecologically adapted cryptic species with different host preferences (e.g. Smith et al., ).…”

Identifying future research directions for biodiversity, ecosystem services and sustainability: perspectives from early-career researchers

“…ESM-Apps) allows researchers to reach wide audiences in what may be geographically or politically sensitive areas. In the United Kingdom, the smart phone application Leafwatch used citizen science to document cases of the leaf-mining moth across the country (Pocock and Evans 2014). Recently, the mini Stream Assessment Scoring System (miniSASS) used a reduced checklist of aquatic invertebrates that can be easily identified with a smartphone application to allow South Africans to assess their local river catchment quality and upload results to an interactive Google Earth map and database, providing invaluable tools to governmental advisors to ensure the provision of clean and safe drinking water (Water Research Commission 2015).…”

Using citizen science butterfly counts to predict species population trends

“…). Distinction can be made, however, between citizen science projects in which standardized protocols are used to conduct systematic, repeatable sampling in long‐term studies (e.g., the Breeding Bird Survey [Gregory & Baillie ]) or for hypothesis‐driven enquiry (e.g., Conker Tree Science [Pocock & Evans ]) and schemes reliant on opportunistic sampling undertaken with relatively unstructured protocols (e.g., eBird [Sullivan et al. ]).…”