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Macroecological laws describe variation and diversity in microbial communities

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  • Jacopo Grilli

    (The Abdus Salam International Centre for Theoretical Physics (ICTP)
    Santa Fe Institute)

Abstract

How the coexistence of many species is maintained is a fundamental and unresolved question in ecology. Coexistence is a puzzle because we lack a mechanistic understanding of the variation in species presence and abundance. Whether variation in ecological communities is driven by deterministic or random processes is one of the most controversial issues in ecology. Here, I study the variation of species presence and abundance in microbial communities from a macroecological standpoint. I identify three macroecological laws that quantitatively characterize the fluctuation of species abundance across communities and over time. Using these three laws, one can predict species’ presence and absence, diversity, and commonly studied macroecological patterns. I show that a mathematical model based on environmental stochasticity, the stochastic logistic model, quantitatively predicts the three macroecological laws, as well as non-stationary properties of community dynamics.

Suggested Citation

  • Jacopo Grilli, 2020. "Macroecological laws describe variation and diversity in microbial communities," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18529-y
    DOI: 10.1038/s41467-020-18529-y
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    Cited by:

    1. Ting-Ting Gao & Baruch Barzel & Gang Yan, 2024. "Learning interpretable dynamics of stochastic complex systems from experimental data," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Kai Ma & Yueyue Li & Wen Song & Jiayin Zhou & Xia Liu & Mengqi Wang & Xiaofan Gong & Linlin Wang & Qichao Tu, 2024. "Disentangling drivers of mudflat intertidal DOM chemodiversity using ecological models," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Joe J. Lim & Christian Diener & James Wilson & Jacob J. Valenzuela & Nitin S. Baliga & Sean M. Gibbons, 2023. "Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Dekaj, Ermanda & Gjini, Erida, 2024. "Pneumococcus and the stress-gradient hypothesis: A trade-off links R0 and susceptibility to co-colonization across countries," Theoretical Population Biology, Elsevier, vol. 156(C), pages 77-92.
    5. Guy Amit & Amir Bashan, 2023. "Top-down identification of keystone taxa in the microbiome," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Enrico Ser-Giacomi & Ricardo Martinez-Garcia & Stephanie Dutkiewicz & Michael J. Follows, 2023. "A Lagrangian model for drifting ecosystems reveals heterogeneity-driven enhancement of marine plankton blooms," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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