Trait coordination is largely independent of climate
A major aim of the Glopnet collaboration was to obtain enough
coverage of climate variation to dissect out effects of climate on
relationships between leaf economic traits. There were indeed
statistically significant effects of climate. Nevertheless, a major
finding from this project is that the influence of climate was, in
general, quite modest. How can this be, given that traits such as
LMA and LL vary systematically with MAR, MATand other climate
indices? The answer seems to have two elements.
First, much of the total leaf economic variation occurs among coexisting
species. The proportion of total variation in LLwithin sites
was 57%, the remaining 43% occurring between sites (variance
components analysis). For Rmass, the proportion of within-site
variation was 67%, for Amass 48%, for Nmass 38%, for LMA 36%,for Pmass 20%. Similar or higher proportions of within-site variation
were seen for area-based traits (40–57% of total variation).
Second, leaf traits tend to vary in concert, with the leaf economics
spectrum operating similarly in different biomes. Considered across
all species, when single or multiple climate variables were included
in regressions of LMA on Nmass, of Amass on Nmass, or of LL on
Amass, they added a maximum of 0.05 to the r 2. Similar results were
found for most other bivariate trait relationships, as well as for
regression models predicting one leaf trait from two or more other
leaf traits as well as climate variables (,15% explanatory power
added).
This is not to say that climate does not exert important influences
on trait relationships. With such large sample sizes, these effects
were still highly statistically significant. Rather, it is an extension of
the fact that so much of the total variation in leaf traits is captured
by the primary axis of the leaf economics spectrum. Adding climate
variables to regressions involving area-based traits also added little
explanatory power, for the most part. Exceptions were cases where
the bivariate trait relationship was particularly weak to start with
(for example, between Aarea and LMA, Rarea and LMA, or LL and
Aarea, climate variables added 0.15 to 0.28 to the model r 2).