Results
Trait- environment interactions: As expected, the four
traits differed in their interaction with environmental variables to
predict species distributions across the landscape (Krishnadas et al.,
2018b), and trait-environment interactions differed between fragments
and contiguous forest (Table 1). Interestingly, models with elevation
alone explained similar extents of variation in trait-mediated
abundances as models with multiple environmental predictors (Table S1).
In contiguous forest, higher elevations had lower abundances of species
with higher SLA and greater maximum height, wood density and seed size,
with seed size showing the strongest interaction with elevation. Only
seed size-elevation interaction differed between fragments and
contiguous forest; fragments had larger-seeded species at higher
elevations (Figure 1).
In contiguous forest, lower water deficit (less negative CWD)
corresponded with increased abundance of shorter statured and
smaller-seeded species, and these relationships did not change for
fragments (Table 1). Although SLA did not interact with any
environmental gradient to shape abundances in contiguous forest, in
fragments, higher SLA species increased as water deficit decreased
(lower CWD) and declined with higher values of climate axis 1, i.e.,
wetter, cooler sites. Larger values of climate axis 1 also associated
with larger-seeded species in contiguous forest, with no change in
fragments. However, in fragments, larger-seeded species declined with
larger values of climate axis 2 (warmer sites) even though climate axis
2 did not influence trait-mediated abundances in contiguous forest.
Trends remained similar with PCA axes, which explained similar variation
in the data as individual traits (Table S1). Overall, trait-environment
interactions at most explained ~16% of the variation in
species abundances, with maximum height being the trait that best
explained change in species abundance across climate gradients (Table
1). Except for the model with maximum height, random effects explained
more variation than fixed effects (Table 1, see conditional vs. marginal
R2).
RLQ and fourth-corner analysis: Only contiguous forest
showed significant trait-environment linkages in driving compositional
change—the first RLQ axis explained 76.4% and second axis 21.1% of
the cross-variance in traits and environment (Figure 2a). In fragments,
88% of the cross-variance between traits and environment was explained
by the model (Figure 2b), but results were not statistically significant
after accounting for multiple comparisons. In contiguous forest,
fourth-corner analysis revealed that trait-mediated structuring of
communities across environmental gradients occurred along multiple
pathways (Figure 3a). Trait axis R1 showed significant positive
correlation with environmental axis Q1, which represented a trait
syndrome defined by a combination of wood density, SLA and seed size.
Correspondingly, sites defined by a combination of greater elevation,
higher C:N ratio, and less negative CWD had significantly higher SLA and
seed sizes (Figure 3b). Elevation showed a positive correlation with the
syndrome represented by trait axis 1 representing phenotypes of smaller
seeded, shorter, and thicker-leaved species (Figure 3c). Fourth corner
analysis for fragments revealed no significant correlations between
trait axes and broad-scale environmental axes, when corrected for
multiple comparisons. Moreover, no individual trait showed significant
correlation with any individual environmental variable in either
fragments or contiguous forest.
Trait covariance: All coefficients for the models of
trait covariance are provided in Table S3. In fragments, WD-SS
covariance showed a significant negative correlation with CWD, while
this relationship was not statistically significant in contiguous forest
(Figure 4a). SS-MH covariance decreased in wetter, warmer sites (higher
values of climate axes 1 and 2), and increased with greater C:N ratio in
contiguous forest (Figure 4b, 4c). In fragments, the relationship with
both climate axes reversed. SS-MH covariance increased with greater
variance in seed size in contiguous forest, with no significant change
in this relationship within fragments. In contiguous forest, SLA-WD
covariance decreased with declining climatic water deficit and
increasing soil CN ratio.
SLA-WD covariance had positive and negative correlations respectively
with multi-trait functional dispersion (FDis) and variance in SLA, both
correlations changed sign in fragments (Figure 5, a-c). SLA-MH
covariance did not correlate with any predictor. SLA-SS covariance
decreased with larger variance in SLA in contiguous forest, and this
remained similar in fragments (Figure 5d). WD-MH covariance in
contiguous forest was only correlated with biotic variables: decreasing
with greater FDis and increasing with greater variance of both traits
(Figure 5, g-i). Only the correlation with MH variance changed in
fragments, becoming strongly negative. Unlike for trait-mediated
abundances, elevation alone did not explain trait covariance as well as
multiple climate variables together (Table S4).