4.4 Article

Where to search: the use of opportunistic data for the detection of an invasive forest pest

Journal

BIOLOGICAL INVASIONS
Volume 24, Issue 11, Pages 3523-3537

Publisher

SPRINGER
DOI: 10.1007/s10530-022-02857-9

Keywords

Oak lace bug; Ecological modelling; Citizen science; Invasive alien species; Early detection; Corythucha arcuata

Funding

  1. LIFE programme, Ministry of Environment and Spatial planning of the Republic of Slovenia [LIFE15 GIE/SI/000770]
  2. Slovenian Research Agency
  3. municipality of Ljubljana
  4. research core group Forest Biology, Ecology and Technology [P40107]
  5. COST action Alien CSI Increasing understanding of alien species through citizen science (COST Action) [CA17122]
  6. Natural Environment Research Council, UK-SCAPE programme delivering National Capability [NE/R016429/1]

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Early detection is crucial for the management of invasive alien species, and citizen science has become an important source of data for this purpose. In this study, the distribution of the oak lace bug in Slovenia was examined using records from a citizen science project. The findings indicate that the bug is more likely to be found in eastern regions, closer to highways and railways, and in areas with more oak trees and lower elevations, suggesting accidental human transport as the main mode of introduction and dispersal. This information can be used to guide future citizen science efforts for efficient early detection.
Early detection is important for the management of invasive alien species. In the last decade citizen science has become an important source of such data. Here, we used opportunistic records from the LIFE ARTEMIS citizen science project, in which people submitted records from places where they observed tree pests, to understand the distribution of a rapidly-spreading forest pest: the oak lace bug (Corythucha arcuata) in Slovenia. These citizen science records were not distributed randomly. We constructed a species distribution model for C. arcuata that accounted for the biased distribution of citizen science by using the records of other tree pests and diseases from the same project as pseudo-absences (so-called constrained pseudo-absences), and compared this to a model with pseudo-absences selected randomly from across Slovenia. We found that the constrained pseudo-absence model showed that C. arcuata was more likely to be found in east, in places with more oak trees and at lower elevations, and also closer to highways and railways, indicating introduction and dispersal by accidental human transport. The outputs from the model with random pseudo-absences were broadly similar, although estimates from this model tended to be higher and less precise, and some factors that were significant (proximity to minor roads and human settlements) were artefacts of recorder bias, showing the importance of taking the distribution of recording into account wherever possible. The finding that C. arcuata is more likely to be found near highways allows us to design advice for where future citizen science should be directed for efficient early detection.

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