Calculating recorder effort for data sources
Accurate estimations of recorder effort have been a significant quandary for many previous studies2,31–33. Here, we defined recorder effort as a ratio between the number of records of a species in a location, and the species’ estimated abundance in that location. High ratios indicate grid-cells where a species is detected frequently relative to its abundance, and thus recorder effort is high. Recorder effort could not be calculated for JTM itself since there are no independent estimates of its abundance across the study region. Therefore, we used a surrogate species: the Eurasian blackbird,Turdus merula , which has a consistent range and abundance between 2000 and 2018, is easily identifiable, is charismatic (thus of interest to social media users), and has been recorded across all data sources considered between 2000 and 2018 across the study region. Furthermore, the blackbird occupied both urban and rural environments, so using blackbirds to estimate recorder effort should minimise the difference in abundance recording between urban and rural areas. We therefore judged records for this species’ occurrence to reflect the interest in recording wildlife in a given time or location34. Estimations of blackbird abundance throughout Europe were acquired from the European Breeding Bird Atlas 235.
In order to calculate the recorder effort ratio for each data source, we collected blackbird occurrences using the search terms and processes in table S1. A ratio between the number of blackbird records for each data source and the estimated abundance was calculated for each UTM grid-cell (Figure S1 – 3) from the European Breeding Bird Atlas (~50 km2 resolution, although some cells varied in size). Recorder effort for GBIF was calculated for all years, whereas the recorder effort for other sources was produced for 2016, 2017, and 2018 (the years for which social media data sources were studied; figures S3 – S5). Other approaches to recorder effort have used the number of species recorded in an area31, however our approach has the advantage that it is not affected by species richness. Moreover, if social media users are indeed more likely to record eye catching or charismatic species, their recorder effort may not be reflected by the overall number of species recorded in a given time or location.
There is a potential confound within this measure of recorder effort given that traditional data are used to estimate blackbird relative abundance: blackbird abundance may underestimated in urban environments as per our own hypotheses. Using blackbird abundance as the denominator in recorder effort calculations could mean we over-estimate recorder effort in urban areas, relative to rural areas. However, this shouldn’t affect the relative difference in recorder effort between data sources within urban areas.