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Complexity–stability trade-off in empirical microbial ecosystems


May’s stability theory, which holds that large ecosystems can be stable up to a critical level of complexity, a product of the number of resident species and the intensity of their interactions, has been a central paradigm in theoretical ecology. So far, however, empirically demonstrating this theory in real ecological systems has been a long-standing challenge with inconsistent results. Especially, it is unknown whether this theory is pertinent in the rich and complex communities of natural microbiomes, mainly due to the challenge of reliably reconstructing such large ecological interaction networks. Here we introduce a computational framework for estimating an ecosystem’s complexity without relying on a priori knowledge of its underlying interaction network. By applying this method to human-associated microbial communities from different body sites and sponge-associated microbial communities from different geographical locations, we found that in both cases the communities display a pronounced trade-off between the number of species and their effective connectance. These results suggest that natural microbiomes are shaped by stability constraints, which limit their complexity.

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Fig. 1: Observing complexity–stability patterns in natural microbial communities without network reconstruction.
Fig. 2: Dissimilarity–overlap analysis of cross-sectional data uncovers the predetermined connectance of the underlying GLV dynamics.
Fig. 3: DOCs across real-world microbial communities from diverse ecological environments.
Fig. 4: Complexity–stability patterns observed in real microbial ecosystems.

Data availability

All the data analysed in this research are publicly and freely available online.

Human Microbiome Project22:

Sponge Microbiome Project41:

Code availability

All MATLAB codes used in this research are available at:


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We thank D. Vaknin Ben Porath for reviewing the manuscript. A.B. thanks the German-Israeli Foundation for Scientific Research and Development (grant number I-1523-500.15/2021), the Israel Science Foundation (grant number 1258/21) and the Azrieli Foundation for supporting this research.

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Authors and Affiliations



A.B. conceived and supervised the project. Y.Y. and G.A. developed the methodology, performed numerical simulations and analysed the real data. Y.Y., G.A., J.F. and A.B. analysed the results. Y.Y., G.A. and A.B. wrote the manuscript. Y.Y., G.A., J.F. and A.B. edited the manuscript.

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Correspondence to Amir Bashan.

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The authors declare no competing interests.

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Nature Ecology & Evolution thanks Akshit Goyal and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary discussion, analytical derivations and Figs. 1–27.

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Yonatan, Y., Amit, G., Friedman, J. et al. Complexity–stability trade-off in empirical microbial ecosystems. Nat Ecol Evol 6, 693–700 (2022).

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