Data from: Prediction of forest aboveground net primary production from high-resolution vertical leaf-area profiles

Temperature and precipitation explain about half the variation in
aboveground net primary production (ANPP) among tropical forest sites, but
determinants of remaining variation are poorly understood. Here we test
the hypothesis that the amount of leaf area, and its vertical arrangement,
predicts ANPP when other variables are held constant. Using measurements
from airborne lidar in a lowland Neotropical rain forest, we quantify
vertical leaf-area profiles and develop models of ANPP driven by leaf area
and other measurements of forest structure. Vertical leaf-area profiles
predict 38% of the variation among plots. This number is 4.5 times greater
than models using total leaf area (disregarding vertical arrangement) and
2.1 times greater than models using canopy height alone. Further, ANPP
predictions from vertical leaf-area profiles were less biased than
alternate metrics. Variation in ANPP not attributable to temperature or
precipitation can be predicted by the vertical distribution of leaf area
in this system.