Contrasting patterns of variance partitioning across scales in six leaf functional traits

Background/Question/Methods

Comparing the relative amount of variance found at different ecological scales is informative of the relative importance of drivers of trait variation acting at those scales.  In a recent study by Messier et al. (2010) two central traits of the leaf economic spectrum, Leaf Mass per Area and Leaf Dry Matter Content, have shown two surprising patterns: (1) intraspecific and interspecific trait variation were of similar magnitude and (2) plot level variation was insignificant despite large species turnover among plots. In this study we explore whether these patterns are exclusive to these two leaf traits or if they are also observed in other leaf traits of the leaf economic spectrum, and more broadly in leaf traits belonging to other functional dimensions. We analyzed and compared the trait variance pattern across scales of four additional traits from the same dataset that are strongly (Leaf Nitrogen Content), moderately (Nitrogen to Carbon ratio) and uncorrelated (Leaf Area and Leaf Carbon Content) with the leaf economic spectrum. 

Results/Conclusions

The patterns of variation of the four new traits are different from those expressed by Leaf Mass per Area and Leaf Dry Matter Content. Traits whose values are moderately to strongly correlated vary in the relative importance of different scales of variation, reflecting different primary drivers of variation among those traits. Further analyses suggest that two main elements distinguish the patterns of variance partitioning across scales for these six traits. First, traits differ mainly in their degree of intraspecific variability relative to interspecific variability. Second, the traits show different levels of site-level variability. In conclusion, the realtive amount of intra- vs inter-specific variability strongly varies among traits and although traits aRE correlated, the main drivers affecting their variation may be different.