Second, we tested if measures of
individual EFs differed among years, seasons, species richness levels,
and plot identities (Fig. 1). Considering all EFs, year explained on
average 4.7% of the variation of EFs, and season explained on average
4.1%. Additionally, species
richness explained 8.6%, while plot identity explained 21.3% of the
variation of individual EFs. These differences explained about
one-fourth of the variation of the individual EFs. One-third of the
variation in individual EFs was unexplained: 34.1% for EFs, which were
measured in several seasons, and 48.3% for EFs measured in just one
season. All tested interaction terms explained only a small part of the
total variation of the EFs (Fig. 1).
Different variables explained the
variation of EFs in different classes of EFs. For example, for invasion
resistance and plant productivity, SR explained a large proportion of
the variation (on average, 23.1% and 21.0%; Fig. 1, green). For
consumer-related functions, year explained a large proportion (on
average 11.9%; Fig. 1, red). For plant nutrients, plot identity
explained, on average, 38% of the variation (Fig. 1, blue). This means,
that classes of EFs were differently affected by biological and
environmental conditions (classes of EF: F7,245=4.2,
p=<0.01; Driver F12,245=38.35,
p<0.01; classes of EF: Driver: F60,245=5.4,
p<0.01, where ”driver” represents the year, season, SR, plotID
and their interactions).