Statistical analyses
The effects of tree species diversity on Ψpd,
Ψmd, ΔΨ, Anet,
gs, xylem δ2H and
δ18O were determined through linear mixed-effects
models for each species using the package lmer . The effect of the
season (i.e., spring, summer, fall), year (i.e., 2021, 2022), and
species diversity (i.e.,
monospecific/monofunctional/multifunctional/four-species mixtures) were
used as fixed effects, and the individual plot was treated as a random
effect. Similar models were used to determine differences in soil water
δ2H and δ18O. Sampling dates,
species diversity, species, and soil depth were used as explanatory
factors in the fixed part of the model. Significant differences between
depths for each species’ diversity and sampling dates were found,
allowing us to use the Bayesian isotope mixing model to determine the
water source contribution of trees as described above (Fig. S3). The
output of this model was analyzed similarly with linear mixed-effects
models for each species. First, the effect of soil depth (i.e., shallow,
deep, bedrock), season, year, and species diversity (i.e., monospecific
and four-species mixture) were set as fixed effects, and the individual
plot as a random effect. Then, we ran similar models for each soil depth
and species where the season, year, and species diversity were used as
fixed effects and the plots as random effects. To reveal significant
differences between species richness for each measurement at each
sampling date and each species, post hoc analyses were performed with
Tukey’s HSD test, with FDR correction for multiple testing. Linear
regressions were used to test the relationships between
ΔΨ, Ψpd, gs, xylem
δ18O, P/PET, and PW. All analyses were
performed using the R v.4.2.2 statistical software (R Development Core
Team, Vienna, Austria, 2022). Before performing each model, the
homogeneity of variances and the normality of residuals were assessed,
and data were log-transformed if necessary.