Large scale intraspecific trait variation
In addition to mapping phylogenetic and environmental trait signals,
another essential reason for a combined approach is that it allows for
predictions of intraspecific variation (Figure 5). Models based on CWMs,
by definition, do not account for intraspecific variation. Although
environment-only models implicitly include intraspecific variation, it
is not decoupled from trait variation due to shifts in species
composition (Hulshof & Swenson, 2010). This interspecific variation
must be separated from intraspecific variation to quantify the latter.
Our combined modeling approach makes this separation possible for
hundreds of species-trait combinations. Quantifying intraspecific
variation in a comprehensive manner (i.e., for all species and across a
large geographic region) is a necessary step towards testing hypotheses
about the role of individual trait variation in species coexistence and
interspecific competition (Hart et al., 2016). We explore the potential
for our approach to enable research understanding the role of
intraspecific variation in community dynamics by (i) comparing our
estimates of intraspecific variation to field data for three widespread
species, (ii) describing how the predicted intraspecific variation
varies among eastern US species, and (iii) describing how trait
variation may affect trends in one of the trait-tradeoffs described by
the LES.
The combined model produced realistic ranges of intraspecific variation
when compared with available independent data for widely distributed
species. Specifically, the intraspecific variation of N% predicted from
the combined model showed ranges similar to those observed from the
field by independent datasets for three widespread and abundantly
sampled species in the NEON, FIA and TRY datasets (Abies balsamea,
Acer rubrum , and Fagus grandifolia ). For these species (Figure
5b-d), predictions from the combined model showed N% covering a large
range of values (1.12 N% on average), comparable to the average
difference between evergreen needleleaf and deciduous broadleaf species
in the eastern US (1.13 N% based on NEON field data). Such a wide range
of intra-species variation further supports the idea that adaptation to
the environment accounts for a large proportion of community-level
variation and may be driving community-level shifts across environmental
gradients (Albert et al. 2010, Violle et al. 2012, Siefert et al. 2015,
Fajardo & Siefert, 2018). The contribution of the environment to
intra-species variation may also explain altitudinal (e.g. Acer
rubrum) and latitudinal (e.g. Abies balsamea ) gradients observed
for these three species.
Predicted patterns of intraspecific variation varied widely across
species. For N%, the ratio of predicted intraspecific to total observed
interspecific variation ranged from less than 10% for species with
limited geographic ranges (e.g., Populus heterophylla ,Sabal palmetto , and Gleditsia aquatica ) to over 60% for
broadleaf species with broad geographic ranges (e.g., Cercis
canadensis, Betula lenta , and Carpinus caroliniana ).
Intraspecific responses of N% to temperature also showed a variety of
patterns among species (Figure 5a, Figure S.15), including 1)
bell-shaped patterns (n=85) like those observed in compilations of field
data (Reich & Oleksyn, 2004, Laughlin et al., 2012); 2) negative
relationships (n = 7); and 3) cases with no significant relationship
(n=108). We observed these different patterns despite the model not
including species-by-environment interactions. This is possible due to
differences in how the environmental drivers are jointly related in
different subregions of the posterior predictive distribution that
represent different geographic regions and different environments by
trait combinations. Therefore, while the underlying relationship between
traits and temperature in the model contains a single dominant mode with
an uptick at very high temperatures, analyzing patterns of trait
distributions from predictions across large geographic areas shows that
focusing only on the subregions of the posterior that are relevant to
the species of interest can yield different species level relationships.
Variation in environmental drivers may also impact trends in trait
trade-offs, including those described in the LES. Since these
relationships affect nutrient and carbon use efficiency in plants
(Reich, 2014), understanding how they change geographically under
different environmental conditions is fundamental for improving how
carbon dynamics are simulated by earth system models (Weng et al.,
2017). Our results suggest that within the Eastern US, the relationship
between N% and LMA is weaker than the global inter-species average, but
stronger than local within-species relationships (Figure 6). This
relationship, first observed from field data from the western US
(Anderegg et al., 2018), generalizes to the Eastern US and holds when
extrapolating trait values continuously across species ranges. The
scale-dependent change in the strength of the relationship may be driven
by different nitrogen to mass allocation strategies between maximizing
short term productivity (higher foliar photosynthetic mass) or long-term
defense (higher foliar structural mass) (Osnas et al., 2018). According
to this conceptual model, we expect stronger negative N%-LMA
relationship for datasets with high variation in LMA, due to variation
in leaf structural components. This is the case of the global LES,
calculated on species sampled from all biomes and many ecosystems (slope
of the logarithmic N%-LMA linear relationship ~-0.7,
Wright et al., 2004). At local scales, where macro-environmental drivers
have a much smaller effect on LMA variation, adaptations to local
conditions may drive higher variation in photosynthetic mass leading to
weaker N% to LMA relationships (slope of the logarithmic N%-LMA linear
relationship ~-0.2; Osnas et al. 2018). At the
intermediate scale of the Eastern US, both strategies may contribute
significantly to the relationship, resulting in N%-LMA trends falling
halfway in between the two extremes (slope of the logarithmic N%-LMA
linear relationship ~-0.43). This slope was consistent
across broadleaves, needleleaves, deciduous and evergreen species,
providing support that this trait-tradeoff can be represented the same
across plant functional types used in earth system models.