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.