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、总个体丰度与总代谢速率三类信息，即可预测诸多宏观生态学格局。本研究采用覆盖全球60个森林群落的监测数据（包含逾30万个个体与近2000个物种），以空前的研究规模同时验证了METE的四项核心预测。结果显示，METE能够分别解释物种多度秩次分布与个体体型分布96%和89%的变异，但在表征体型-密度关系以及个体体型的种内分布时表现欠佳。具体而言，METE预测体型与物种多度之间存在负相关关系，但该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验证，不仅揭示了METE在物种多度与体型匹配关系上存在的偏差，同时也彰显了对生态学理论开展严格检验的重要意义。