Data from: Tropical tree height and crown allometries for the Barro Colorado Nature Monument, Panama: a comparison of alternative hierarchical models incorporating interspecific variation in relation to life history traits

Tree allometric relationships are widely employed for estimating forest
biomass and production and are basic building blocks of dynamic vegetation
models. In tropical forests, allometric relationships are often modeled by
fitting scale-invariant power functions to pooled data from multiple
species, an approach that fails to capture changes in scaling during
ontogeny and physical limits to maximum tree size and that ignores
interspecific differences in allometry. Here, we analyzed allometric
relationships of tree height (9884 individuals) and crown area (2425) with
trunk diameter for 162 species from the Barro Colorado Nature Monument,
Panama. We fit nonlinear, hierarchical models informed by species traits –
wood density, mean sapling growth, or sapling mortality – and assessed the
performance of three alternative functional forms: the scale-invariant
power function and the saturating Weibull and generalized Michaelis–Menten
(gMM) functions. The relationship of tree height with trunk diameter was
best fit by a saturating gMM model in which variation in allometric
parameters was related to interspecific differences in sapling growth
rates, a measure of regeneration light demand. Light-demanding species
attained taller heights at comparatively smaller diameters as juveniles
and had shorter asymptotic heights at larger diameters as adults. The
relationship of crown area with trunk diameter was best fit by a power
function model incorporating a weak positive relationship between crown
area and species-specific wood density. The use of saturating functional
forms and the incorporation of functional traits in tree allometric models
is a promising approach for improving estimates of forest biomass and
productivity. Our results provide an improved basis for parameterizing
tropical plant functional types in vegetation models.