Understanding the origin of universal macroecological patterns in microbial communities remains a central open question in ecology. A key observation is that species abundance fluctuations across diverse biomes are well described by a gamma distribution, yet the mechanism responsible for this regularity is debated. Prevailing explanations invoke exogenous stochastic forcing, while endogenous interaction-based approaches—grounded in generalized Lotka-Volterra (gLV) dynamics—have so far failed to reproduce this pattern: instead, they predict a power-law abundance distribution with exponent -1, arising from the chaotic turnover of species between rare and dominant states. Here we show that incorporating spatial structure resolves this discrepancy. In a gLV model with constant migration, local abundance dynamics remain inconsistent with a gamma distribution. However, when the community is embedded in a fragmented landscape as a meta-community—with species dispersing among patches—aggregating abundances across patches yields distributions that closely match the empirically observed gamma form. We further demonstrate that this result can be reproduced by aggregating independent realizations of the constant-migration gLV model, entailing statistical aggregation rather than a specific biological mechanism as the origin of this macroecological pattern. Our findings highlight the fundamental role of spatial structure in shaping microbial macroecology, and suggest that observed abundance distributions may largely reflect the spatial coarse-graining inherent in metagenomic sampling. We propose that experimentally isolating or spatially resolving microbial communities will be essential to uncover the true microscopic dynamics governing these ecosystems.
