Integrating metabolic scaling variation into the maximum entropy theory of ecology explains Taylor's law for individual metabolic rate in tropical forests

2021 
Abstract Individual trait variation has important ecological implications for species populations and communities. In particular, individual variation of metabolic rate links directly with the energy use estimation and scaling patterns in community ecology. Here, we examine the mean-variance relationship of individual metabolic rate by testing Taylor's law (a power-function relationship between mean and variance) for individual rescaled metabolic rate across tree communities in tropical forests. We use a constraint-based model called maximum entropy theory of ecology (METE) to estimate and predict the parameters of Taylor's law. Our results show that, when assuming a universal metabolic scaling between metabolic rate and aboveground biomass, the METE generates the form of Taylor's law but fails to predict its slope. When setting the metabolic scaling exponent as a community-level parameter in the METE model, the estimated and predicted slopes of Taylor's law agree with each other. Our parameterized METE model reveals the positive effect of number of individuals on the metabolic scaling exponent. These results suggest that fluctuation scaling of individual metabolic rate can be explained solely by the macroecological constraints of communities, without relying on the physiological or genetic characters of individual organisms.
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