Data extraction and effect size calculation
When two different landscape categories were compared; natural or rural
versus urban sites, we selected the most extreme category comparison
(natural versus urban; Fenoglio et al. 2020). We obtained mean
values, sample sizes, and standard deviation from texts or tables
(mean value -type data), for each of the two contrasting
ecosystems: control (natural, forest, rural, or suburban sites) versus
urban (urban sites). A meta-analysis may produce
spurious
results and further exacerbate publication bias when excluding studies
with missing information. Therefore, we converted or
imputed
data from relevant studies that report incomplete information on means,
correlations, variances and sample sizes (Koricheva et al. 2013).
When the effect of urbanisation was measured using a continuous variable
(i.e., impervious surfaces, distance to the city centre or green area),
we extracted Pearson’s correlation coefficients (r) or the coefficients
of determination (R2; r -type data). When none
of these values was reported, we
used
statistical values of parametric tests (e.g., ANOVAs, Chi-square,
t-tests; statistic values -type data). If these parameter values
were only presented in graphs, we estimated the values from the figures
using WebPlotDigitizer
(Burdaet al. 2017). If the standard deviation was not shown in graphs;
but instead using a boxplot of minimum, maximum, first quartile or third
quartile, we estimated it according to Wan et al. (2014).
Moreover, when all the above information was not available in the main
text, we calculated means and standard deviation or correlation
coefficients from supporting material and/or original datasets.
If a publication reported the results of several taxonomic groups or
cities separately, each was considered to be a separate observation
(Aguilaret al. 2006). When abundance, species richness, traits, or plant
reproductive success were reported at multiple time points (months or
years), we selected the time point with the higher sample size; if
multiple time points had equal sample sizes, we chose the most recent
period of sampling, or if possible, we chose the sampling period of
maximum pollinator activity (Fenoglio et al. 2020). For
pollination services, in addition to the fruit and seed set,
the
number, rate and duration of visits were also extracted and used as
proxies of plant reproductive success (Kleijn et al. 2015).