Figure Legends
Figure 1. Relationships between 11 ‘Chardonnay’ leaf traits and
soil bulk density. Trend lines correspond to statistically significant
relationships (where p ≤0.05 for the slope parameter) between
traits and bulk density, based on linear mixed effects models predicting
traits as a function of soil bulk density (as a fixed factor) while
accounting for plant identity (as a random factor; see Table S2 for full
model diagnostics and fits). Also presented are marginalr 2 values (“Marg.r 2”) for each relationship, which represents
the proportion of variation in a given trait explained by fixed factors
alone (i.e., bulk density and model intercept), and conditionr 2 values (“Cond.r 2”), which represent the proportion of trait
variation explained by fixed and random factors. Sample sizes for all
models were 45 leaves, measured across 15 individual vines.
Log-transformed trait values were used in models according to results
presented in Table 1, and trait acronyms are presented in Table 1.
Figure 2. Principal Component Analysis (PCA) for seven
‘Chardonnay’ wine grape leaf traits measured in 2020 across a soil
compaction gradient. Data point colours correspond to vine sampling
rows, which are situated along a gradient of bulk density values, and
dotted black lines represent 95% confidence ellipses for leaves across
different rows. Planting row explained 39.6% of the multivariate trait
variation evaluated here (p ≤ 0.001, and see Table S4 for full
Permutational Multivariate Analysis of Variance results). Trait acronyms
are presented in Table 1.
Figure 3. Relationships across four Leaf Economics Spectrum
traits in ‘Chardonnay’ wine grapes. Colours correspond to sampling rows
reflecting a soil compaction gradient, black solid trend lines
correspond to the standardized major axis (SMA) regression model of a
given bivariate trait relationship in ‘Chardonnay’, and dashed black
trend lines represent convex hull models that encapsulate the
two-dimensional trait space occupied by ‘Chardonnay’ leaves. Also shown
are the data and SMA models for the same LES trait relationships
observed among wild plants in the GLOPNET dataset (grey dashed trend
lines and points). Details on all SMA models shown here are presented in
full in Table 2. Trait acronyms are presented in Table 1.