Data from: Allometric convergence in savanna trees and implications for plant scaling models in variable ecosystems

Theoretical models of allometric scaling provide frameworks for
understanding and predicting how and why the morphology and function of
organisms vary with scale. It remains unclear, however, if the predictions
of ‘universal’ scaling models for vascular plants hold across diverse
species in variable environments. Phenomena such as competition and
disturbance may drive allometric scaling relationships away from
theoretical predictions based on an optimized tree. Here, we use a
hierarchical Bayesian approach to calculate tree-specific,
species-specific, and ‘global’ (i.e. interspecific) scaling exponents for
several allometric relationships using tree- and branch-level data
harvested from three savanna sites across a rainfall gradient in Mali,
West Africa. We use these exponents to provide a rigorous test of three
plant scaling models (Metabolic Scaling Theory (MST), Geometric
Similarity, and Stress Similarity) in savanna systems. For the allometric
relationships we evaluated (diameter vs. length, aboveground mass, stem
mass, and leaf mass) the empirically calculated exponents broadly
overlapped among species from diverse environments, except for the scaling
exponents for length, which increased with tree cover and density. When we
compare empirical scaling exponents to the theoretical predictions from
the three models we find MST predictions are most consistent with our
observed allometries. In those situations where observations are
inconsistent with MST we find that departure from theory corresponds with
expected tradeoffs related to disturbance and competitive interactions. We
hypothesize savanna trees have greater length-scaling exponents than
predicted by MST due to an evolutionary tradeoff between fire escape and
optimization of mechanical stability and internal resource transport.
Future research on the drivers of systematic allometric variation could
reconcile the differences between observed scaling relationships in
variable ecosystems and those predicted by ideal models such as MST.