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Global Leaf Trait Relationships: Mass, Area, And The Leaf Economics Spectrum

J. L. D. Osnas, J. Lichstein, P. B. Reich, S. W. Pacala
Published 2013 · Biology, Medicine

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Getting It Wright? In 2004, a paper by Wright et al. comparing six leaf traits of over 2000 plant species showed that between-species variation among the traits was confined primarily to a single multidimensional axis, but only if traits were normalized by leaf mass. This “leaf economic spectrum” has been influential in guiding understanding of the roles of plants in global carbon cycling. Osnas et al. (p. 741, published online 28 March) now show that the principal finding of Wright et al. is primarily a mathematical consequence of the way that the data were normalized. Analysis of the same data suggests that traits are primarily proportional to leaf area, not leaf mass. Using a method to analyze relationships among traits without normalization-induced correlations revealed a multidimensional correlation between leaf traits. These relationships imply weaker effects of leaf nitrogen on rates of photosynthesis and respiration, with important implications for current models of global change. Leaf traits are distributed in proportion to area; relationships between leaf traits are independent of leaf mass and area. The leaf economics spectrum (LES) describes multivariate correlations that constrain leaf traits of plant species primarily to a single axis of variation if data are normalized by leaf mass. We show that these traits are approximately distributed proportional to leaf area instead of mass, as expected for a light- and carbon dioxide–collecting organ. Much of the structure in the mass-normalized LES results from normalizing area-proportional traits by mass. Mass normalization induces strong correlations among area-proportional traits because of large variation among species in leaf mass per area (LMA). The high LMA variance likely reflects its functional relationship with leaf life span. A LES that is independent of mass- or area-normalization and LMA reveals physiological relationships that are inconsistent with those in global vegetation models designed to address climate change.
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