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• Opportunistic citizen science is valuable for biodiversity trend analysis. • Participants in citizen science vary in their recording behaviour. • Estimated trends in occupancy were robust to differences in recorder behaviour. • Species occupancy itself was more sensitive to some aspects of recorder behaviour. 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. [ABSTRACT FROM AUTHOR]

Invasive alien species, including pests and diseases of plants and animals, are a major cause of biodiversity change and may impact upon human well-being and the economy. If new, potentially invasive, taxa arrive then it is most cost-effective to respond as early in their establishment as possible. Information to support this can be gained from volunteers, i.e. via citizen science. However, it is vital to develop ways of quantifying volunteer recorder effort to assess its contribution to the detection of rare events, such as the arrival of invasive alien species. We considered the potential to detect adult oak processionary moths ( Thaumetopoea processionea ) by amateur naturalists recording moths at light traps. We calculated detection rates from the Netherlands, where T. processionea is widely established and poses a risk to tree health and human health, and applied these to the spatial pattern of moth recording effort in the UK. The probability of recording T. processionea in the Netherlands varied across provinces from 0.05–2.4% per species of macro-moth recorded on a list of species (so equalling 1–52% for a list of 30 species). Applying these rates to the pattern of moth recording in the UK: T. processionea could be detected (detection > 0%), if it were present, in 69% and 4.7% of 10 km and 1 km squares, respectively. However, in most squares detection probability is low (< 1% of 1 km squares have annual detection probability of > 10%). Our study provides a means to objectively assess the use of citizen science as a monitoring tool in the detection of rare events, e.g. the arrival of invasive alien species, occurrence of rare species and natural colonisation. [ABSTRACT FROM AUTHOR]