ArticleProceedings of the National Academy of Sciences of the United States of America2024
Sparse species interactions reproduce abundance correlation patterns in microbial communities.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Omnidirectional Interaction Networks Modulating Phenotypic Plasticity in the Gut Microbiota Towards Ulcerative Colitis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- A Dynamic Mechanism for Prevalence of Triangles in Competitive Networks.Bulletin of mathematical biology · 2026Article
- Towards Key Principles of Host-Associated Microbiome Assembly.Ecology letters · 2026Article
- Assessing the Ecological Roles of Resistomes within Microbial Communities in Antibiotic-contaminated Ecosystems.Microbial ecology · 2026Review
- The eco-evolutionary assembly of complex communities with multiple interaction types.Nature communications · 2026Article
- Emergent coexistence and the limits of reductionism in ecological communities.PLoS computational biology · 2026Article
- Linking complex microbial interactions and dysbiosis through a disordered Lotka-Volterra model.eLife · 2026Article
- Bayesian inference captures metabolite-bacteria interactions in a microbial community.ISME communications · 2026Article
- Macroecological Laws Can Naturally Arise from Chaotic Internal Species Dynamics.bioRxiv : the preprint server for biology · 2025Article
- Scarce data, noisy inferences and overfitting: the hidden flaws in ecological dynamics modelling.Journal of the Royal Society, Interface · 2025Article
- Macroecological patterns in experimental microbial communities.PLoS computational biology · 2025Article
- Exploring interspecific interaction variability in microbiota: A review.Engineering microbiology · 2024Review
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5 authors.
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Abstract
During the last decades, macroecology has identified broad-scale patterns of abundances and diversity of microbial communities and put forward some potential explanations for them. However, these advances are not paralleled by a full understanding of the dynamical processes behind them. In particular, abundance fluctuations of different species are found to be correlated, both across time and across communities in metagenomic samples. Reproducing such correlations through appropriate population models remains an open challenge. The present paper tackles this problem and points to sparse species interactions as a necessary mechanism to account for them. Specifically, we discuss several possibilities to include interactions in population models and recognize Lotka-Volterra constants as a successful ansatz. For this, we design a Bayesian inference algorithm to extract sets of interaction constants able to reproduce empirical probability distributions of pairwise correlations for diverse biomes. Importantly, the inferred models still reproduce well-known single-species macroecological patterns concerning abundance fluctuations across both species and communities. Endorsed by the agreement with the empirically observed phenomenology, our analyses provide insights into the properties of the networks of microbial interactions, revealing that sparsity is a crucial feature.
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