ArticleeLife2022
Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Fitness advantage of sequential metabolic strategies emerges from community interactions in strongly fluctuating environments.PLoS computational biology · 2026Article
- Mathematical Modelling and Intuition in Microbiology: A Perspective.Environmental microbiology · 2026Review
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- Standardized and batch effect-independent technologies enable global collaboration in microbiome research.The ISME journal · 2026Article
- How nutrient starvation impacts the gut microbiome.Nature microbiology · 2025Review
- Macroecological Laws Can Naturally Arise from Chaotic Internal Species Dynamics.bioRxiv : the preprint server for biology · 2025Article
- Article
- Macroecological patterns in experimental microbial communities.PLoS computational biology · 2025Article
- Dynamic coexistence driven by physiological transitions in microbial communities.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Microbial functional guilds respond cohesively to rapidly fluctuating environments.bioRxiv : the preprint server for biology · 2025Article
- SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome.Nature microbiology · 2025Article
- Article
- Timescale of environmental change modulates metabolic guild cohesion in microbial communities.The ISME journal · 2025Article
- Ecosystem stability relies on diversity difference between trophic levels.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The strength of interspecies interaction in a microbial community determines its susceptibility to invasion.PLoS biology · 2024Article
- SAMPL-seq reveals micron-scale spatial hubs in the human gut microbiome.bioRxiv : the preprint server for biology · 2024Article
- Predicting the first steps of evolution in randomly assembled communities.Nature communications · 2024Article
- Maternal transmission as a microbial symbiont sieve, and the absence of lactation in male mammals.Nature communications · 2024Article
- Predicting the First Steps of Evolution in Randomly Assembled Communities.bioRxiv : the preprint server for biology · 2024Article
- The MTIST platform: a microbiome time series inference standardized test.Research square · 2024Article
Corrections and comments
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Authors and funding
3 authors.
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Abstract
Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.