A strong test of the Maximum Entropy Theory of Ecology
Xiao Xiao, Daniel J. McGlinn, and Ethan P. White

TL;DR
This study rigorously tests the Maximum Entropy Theory of Ecology across 60 global forest communities, confirming some predictions while revealing significant mismatches, especially regarding size-abundance relationships.
Contribution
It provides an extensive empirical evaluation of METE's predictions at an unprecedented scale, highlighting its strengths and limitations in modeling biodiversity patterns.
Findings
METE accurately predicts species abundance and size distributions.
METE poorly predicts size-density relationships and intraspecific size variation.
The study emphasizes the importance of large-scale tests for ecological theories.
Abstract
The Maximum Entropy Theory of Ecology (METE) is a unified theory of biodiversity that predicts a large number of macroecological patterns using only information on the 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 over 300,000 individuals and nearly 2000 species. METE successfully captured 96% and 89% of the variation in the species abundance distribution and the individual size distribution, 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…
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