@article{599,
  keywords = {Butterfly, Citizen Science, Opportunistic, biological recording, Occupancy analysis, Motivations, volunteer},
  author = {Pocock Michael J.O. and Logie Mark and Isaac Nick J.B. and Fox Richard and August Tom},
  title = {The recording behaviour of field-based citizen scientists and its impact on biodiversity trend analysis},
  abstract = {Summary Opportunistic species sightings submitted by citizen science volunteers are a valuable source of species data for trends analysis, as used in biodiversity indicators. However, projects collecting these data give people flexibility where and when to make records, and the recording behaviour of participants varies between individuals. Here we tested the effect of recorder behaviour on outputs of the analysis of temporal biodiversity trends. Using a large (c. 3 million records), 20 year unstructured citizen science dataset of butterfly records in Great Britain, we manipulated recorder behaviour by constructing biased 50% subsamples of the dataset by preferentially including different types of recorders (based on high and low values of four metrics independently describing the temporal, spatial and taxonomic attributes of recorder behaviour). We found that, in general, the three outputs (namely: occupancy trend, precision of the trend, and the estimate of occupancy) showed relatively little deviation from random expectation across most of the different types of recorder behaviour. Occupancy trends showed least deviation, while estimates of occupancy itself showed greatest deviation from the random expectation. Regarding the recorder behaviours, the outputs were most sensitive to variation in ‘recorder potential’, which describes the difference between ‘thorough’ and ‘incidental’ recorders. Importantly, by demonstrating the robustness of occupancy trends to differences in recorder behaviour, this study provides support for the appropriate use of occupancy trend modelling for unstructured citizen science. However, we did not consider change in recorder behaviour over time, so further research is required to assess the impact of this on trend modelling. This study highlights the value of developing solutions to further increase the robustness of biodiversity trend analysis. These solutions should include both analytical developments and enhancements in project design to engage participants.},
  year = {2023},
  journal = {Ecological Indicators},
  volume = {151},
  pages = {110276+},
  month = {2023/07/01/},
  isbn = {1470-160X},
  url = {https://www.sciencedirect.com/science/article/pii/S1470160X23004181},
  doi = {https://doi.org/10.1016/j.ecolind.2023.110276},
}