Allometric Scaling Across Environmental Gradients
Abstract:
Ht ∝ DBH2/3
nDBH ∝ DBH-2
where Ht is height, DBH is Diameter at Breast Height, and nDBH is the number of trees in a given DBH size class.
We obtained DBH and height data from the U.S. Forest Inventory Analysis (FIA) dataset, and fit an exponent to each relationship for every FIA plot across the US. We extracted environmental data from the FIA plots (forest maximum height, species type, age, topography) and the North American Regional Reassessment dataset (precipitation, temperature, PAR) and performed random forest regression to estimate observed exponents as a function of environment. We found that forest height, age, and forest type were the most important drivers of allometry, explaining about 40% of observed variability. We found that for both relationships, as forest height and age increase, exponents constrain to the theoretical predictions presented by WBE. This suggests that WBE predictions are valid and may be useful constraints in biomass mapping and ecosystem flux models. However, they deviate from predictions in younger, shorter stands where forests have not had time to develop a complex size structure. Additionally, there is a significant difference in both relationships between conifer and deciduous-dominated stands, suggesting that species type must be considered in the further development and application of this work.
