Assessing the general patterns of forest structure: quantifying tree and forest allometric scaling relationships in theUnitedStates

Abstract

AbstractAimUnderstanding the drivers of forest structure, function and change is a fundamental problem in both theoretical ecology and applied forestry for carbon mapping and monitoring. An important component of forest ecology research often utilizes allometric equations to scale up local measurements to predict large‐scale forest and ecosystem‐level properties. However, both applied and theoretical allometries in forest ecology (such as metabolic scaling theory,MST) assume that many scaling relationships are insensitive to broad‐scale climate gradients or species life histories. We aim to test these assumptions by mapping continental‐scale forest allometry across environmental gradients in theUnitedStates.LocationUnitedStates.MethodsWe fit exponents to two allometric relationships inc. 100,000ForestInventoryAnalysis (FIA) field plots: (1) the relationship between the height of an individual tree and its diameter, and (2) plot‐level tree size distributions. We compare fitted exponents to environmental and life‐history variables, such as climate, topography and forest structure, in an attempt to explain allometric variability and deviations from theoretically predicted allometries.ResultsWe find that the structural allometry of forests varies strongly as a function of location in theUnitedStates. Allometric exponents appear to asymptote at approximately whereMSTtheory predicts with increasing forest height, while deviations fromMSTare partially explained as a function of environmentally driven recruitment limitations and successional status.Main conclusionsWhile we find support for invariant tree and stand allometric scaling relationships in forests that are in steady state with regard to demography and resources, we also find considerable spatial variability in forest allometric relationships when steady‐state conditions are violated. These findings suggest that extensions of metabolic scaling theory should incorporate variation in demographic dynamics in younger successional forests, and factors influencing recruitment limitation.