Allometric scaling and allocation patterns: Implications for predicting productivity across plant communities

Abstract

As the application of allometry continues to expand, the variability in the allometry exponent has generated a great deal of debate in forest ecology. Some studies have reported counterintuitive values of the exponent, but the sources of such values have remained both unexplored and unexplained. Therefore, the objectives of our analyses were to: (1) uncover the global patterns of allometric variation in stem height with stem diameter, crown radius with stem diameter or stem height, crown depth with stem diameter, crown volume with stem diameter, crown depth with crown diameter, aboveground biomass with stem diameter or height, and belowground biomass with aboveground biomass; (2) assess variations in allometry parameters with taxonomic levels, climate zones, biomes and historical disturbance regimes; and (3) identify the sources of counterintuitive values of the allometry exponents. Here, we provide novel insights into the tight allometric co-variations between stem and crown dimensions and tree biomass. We also show a striking similarity in scaling across climate zones, biomes and disturbance regimes consistent with the allometry constraint hypothesis. We show that the central tendency of the exponent is toward 2/3 for the scaling of stem height with diameter, crown dimensions with stem diameter and height, 5/2–8/3 for the scaling of aboveground biomass with stem diameter, and 1 for the scaling of belowground biomass with aboveground biomass. This is indicative of an integrated growth regulation acting in tandem on growth in stem diameter, height, crown dimensions and biomass allocation. We also demonstrate that counterintuitive values of the exponent arise as artifacts of small sample sizes (N < 60), measurement errors, sampling biases and inappropriate regression techniques. We strongly recommend the use of larger sample sizes (N > 60) and representative samples of the target population when testing hypothesis about allometric variation. We also caution against conflation of statistical artifacts with violations of theoretical predictions.