Taxonomy and remote sensing of leaf mass per area (LMA) in humid tropical forests

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Abstract

Leaf mass per area (LMA) is a trait of central importance to plant physiology and ecosystem function, but LMA patterns in the upper canopies of humid tropical forests have proved elusive due to tall species and high diversity. We collected top-of-canopy leaf samples from 2873 individuals in 57 sites spread across the Neotropics, Australasia, and Caribbean and Pacific Islands to quantify environmental and taxonomic drivers of LMA variation, and to advance remote-sensing measures of LMA. We uncovered strong taxonomic organization of LMA, with species accounting for 70% of the global variance and up to 62% of the variation within a forest stand. Climate, growth habit, and site conditions are secondary contributors (1–23%) to the observed LMA patterns. Intraspecific variation in LMA averages 16%, which is a fraction of the variation observed between species. We then used spectroscopic remote sensing (400–2500 nm) to estimate LMA with an absolute uncertainty of 14–15 g/m2 (r2 = 0.85), or ∼10% of the global mean. With radiative transfer modeling, we demonstrated the scalability of spectroscopic remote sensing of LMA to the canopy level. Our study indicates that remotely sensed patterns of LMA will be driven by taxonomic variation against a backdrop of environmental controls expressed at site and regional levels.

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