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.

个体性状变异对物种种群和群落具有重要的生态意义。特别是，代谢率的个体差异与社区生态学中的能量使用估计和缩放模式直接相关。在这里，我们通过测试泰勒定律（均值和方差之间的幂函数关系）对热带森林中树木群落的个体重新调整代谢率来检查个体代谢率的均值-方差关系。我们使用称为最大生态熵理论 (METE) 的基于约束的模型来估计和预测泰勒定律的参数。我们的结果表明，当假设代谢率和地上生物量之间存在通用代谢标度时，METE 生成泰勒定律的形式，但无法预测其斜率。在 METE 模型中将代谢标度指数设置为社区级参数时，泰勒定律的估计斜率和预测斜率彼此一致。我们的参数化 METE 模型揭示了个体数量对代谢缩放指数的积极影响。这些结果表明，个体代谢率的波动标度可以完全由群落的宏观生态约束来解释，而不依赖于个体生物的生理或遗传特征。