Statistical analysis
Differences between site averages of macro- and micronutrient
concentrations in the foliage and soil samples from 8 sampled sites were
tested by means of one-way ANOVA - checking data and residuals
distribution normality and homogeneity of variance - followed by Tukey
(HSD) post-hoc tests, using the Statistica 7.0 software (Statsoft
Inc., Tulsa Ok). After standardization of Na and Cl data, the causal
role of NaCl accumulation in foliage regarding the univariate changes in
leaf nutrients and structural parameters was tested by means of linear
mixed effects model (LMEM), using the lme4 package (Bates et al. 2015)
of R software, version 3.4.2 (R Core Team 2017). The individual tree
formed the statistical unit whilst the site effect was treated as a
random factor. Given their correlation, separate models for Na and Cl
factors were calculated. For each model, the marginal
R2 was calculated using the r2glmm package (Jaeger,
2017) of R. The correlations between structural changes, salt
concentration in foliage and leaf injury were investigated by means of
Pearson’s correlations, also using the aforementioned Statistica
software, after variable normalization. Finally, the multivariate
responses of palisade parenchyma cells to salt contamination in foliage
was tested by means of redundancy analysis (RDA), using the vegan
package (Oksanen, et al., 2017) of R and main structural size and shape
variables. The dependent matrix included structural data from the
aforementioned five sites subsample used for quantitative TEM, the
explanatory variables consisted of foliage concentration of salt
contaminants (Na, Cl), whilst leaf injury and the study site centroids
were passively projected in the hyperspace determined by the RDA axes.