Rapid assessment of the suitability of multi-species citizen science datasets for occupancy trend analysis

Species records from volunteers are a vast and valuable source of information on biodiversity for a wide range of taxonomic groups. Although these citizen science data are opportunistic and unstructured, occupancy analysis can be used to quantify trends in distribution. However, occupancy analysis of unstructured data can be resource-intensive and requires substantial expertise. It is valuable to have simple 9rules of thumb9 to efficiently assess the suitability of a dataset for occupancy analysis prior to analysis. Our analysis was possible due to the production of trends, from our Bayesian occupancy analysis, for 10 967 species from 34 multi-species recording schemes in Great Britain. These schemes had an average of 500 visits to sites per year, and an average of 20% of visited sites received a revisit in a year. Occupancy trend outputs varied in their precision and we used expert elicitation on a subset of outputs to determine a precision threshold above which trends were suitable for further consideration. We then used classification trees with seven metrics to define simple rules explaining when the data would result in outputs that met the precision threshold. We found that the suitability of a species9 data was best described by (i) the number of records of the focal species in the 10% best-recorded years, and (ii) the proportion of recording visits for that taxonomic group with non-detections of the focal species. Surprisingly few data were required to be predicted to meet the precision threshold. Specifically, for 98% confidence that our Bayesian occupancy models would produce outputs meeting the precision threshold, there needed to be at least 29 records of the focal species in the 10% best-recorded years (equivalent to an average of 12.5 records per year in our dataset), although only at least 10 records (equivalent to 4.5 records per year) were required for species recorded in less than 1 in 25 visits. We applied these rules to regional species data for Great Britain. Data from 32% of the species:region combinations met the precision threshold with 80% confidence, and 14% with 98% confidence. There was great variation between taxonomic groups (e.g. butterflies, moths and dragonflies were well recorded) and region (e.g. south-east England was best recorded). These simple criteria provide no indication of the accuracy or representativeness of the trend outputs: this is vital, but needs to be assessed individually. However our criteria do provide a rapid, quantitative assessment of the predicted suitability of existing data for occupancy analysis and could be used to inform the design and implementation of multi-species citizen science recording projects elsewhere in the world.