Data from: A strong test of the Maximum Entropy Theory of Ecology

The maximum entropy theory of ecology (METE) is a unified theory of biodiversity that predicts a large number of macroecological patterns using information on only species richness, total abundance, and total metabolic rate of the community. We evaluated four major predictions of METE simultaneously at an unprecedented scale using data from 60 globally distributed forest communities including more than 300,000 individuals and nearly 2,000 species. METE successfully captured 96% and 89% of the variation in the rank distribution of species abundance and individual size but performed poorly when characterizing the size-density relationship and intraspecific distribution of individual size. Specifically, METE predicted a negative correlation between size and species abundance, which is weak in natural communities. By evaluating multiple predictions with large quantities of data, our study not only identifies a mismatch between abundance and body size in METE but also demonstrates the importance of conducting strong tests of ecological theories.

生态学最大熵理论（Maximum Entropy Theory of Ecology, METE）是一套统一的生物多样性理论，仅依托群落的物种丰富度、总个体多度以及总代谢速率信息，便可预测诸多宏观生态学格局。本研究以覆盖全球的60个森林群落的监测数据为基础，对该理论的四项核心预测开展了前所未有的大规模同步验证，所用数据集涵盖超过30万个个体与近2000个物种。结果显示，生态学最大熵理论成功拟合了物种多度等级分布与个体体型大小分布中96%和89%的变异，但在表征体型-密度关系以及种内个体体型分布时表现欠佳。具体而言，该理论预测体型大小与物种多度间存在负相关关系，但这一关联在自然群落中仅表现微弱。本研究通过海量数据对多项理论预测开展系统性验证，不仅揭示了生态学最大熵理论在物种多度与个体体型关联上的偏差，同时凸显了对生态学理论开展严格检验的重要性。