The effect of resource dynamics on species packing in diverse ecosystems

Cui, Wenping; Marsland, Robert; Mehta, Pankaj

doi:10.1101/833533

Cited by 12 publications

(19 citation statements)

References 32 publications

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“…We have also employed the package to reproduce large-scale patterns in microbial biodiversity from the Human Microbiome Project, Earth Microbiome Project, and similar surveys [34]. Finally, the random matrix approach implemented in this package is amenable to analytic calculation in the limit of large numbers of species and resources, using cavity methods from the physics of disordered systems [35,36]. It is our belief that the Community Simulator will facilitate the further development of these mathematical techniques through efficient testing of new conjectures.…”

Section: Discussionmentioning

confidence: 99%

The Community Simulator: A Python package for microbial ecology

et al. 2020

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Natural microbial communities contain hundreds to thousands of interacting species. For this reason, computational simulations are playing an increasingly important role in microbial ecology. In this manuscript, we present a new open-source, freely available Python package called Community Simulator for simulating microbial population dynamics in a reproducible, transparent and scalable way. The Community Simulator includes five major elements: tools for preparing the initial states and environmental conditions for a set of samples, automatic generation of dynamical equations based on a dictionary of modeling assumptions, random parameter sampling with tunable levels of metabolic and taxonomic structure, parallel integration of the dynamical equations, and support for metacommunity dynamics with migration between samples. To significantly speed up simulations using Community Simulator, our Python package implements a new Expectation-Maximization (EM) algorithm for finding equilibrium states of community dynamics that exploits a recently discovered duality between ecological dynamics and convex optimization. We present data showing that this EM algorithm improves performance by between one and two orders compared to direct numerical integration of the corresponding ordinary differential equations. We conclude by listing several recent applications of the Community Simulator to problems in microbial ecology, and discussing possible extensions of the package for directly analyzing microbiome compositional data.

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Section: Discussionmentioning

confidence: 99%

The Community Simulator: A Python package for microbial ecology

et al. 2020

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“…To this end, it is useful to focus first on what we can learn from simple mathematical models before discussing similarities and differences with empirical data. Specifically, we will focus on results that can be derived from recent consumer-resource models of crossfeeding [54,85], which are useful tools to develop null expectations about the behavior of microbial communities dominated by interspecies metabolite flux.…”

Section: Assembly Dynamics Of Trophic Systemsmentioning

confidence: 99%

Trophic Interactions and the Drivers of Microbial Community Assembly

et al. 2020

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Despite numerous surveys of gene and species content in heterotrophic microbial communities, such as those found in animal guts, oceans, or soils, it is still unclear whether there are generalizable biological or ecological processes that control their dynamics and function. Here, we review experimental and theoretical advances to argue that networks of trophic interactions, in which the metabolic excretions of one species are the primary resource for another, constitute the central drivers of microbial community assembly. Trophic interactions emerge from the deconstruction of complex forms of organic matter into a wealth of smaller metabolic intermediates, some of which are released to the environment and serve as a nutritional buffet for the community. The structure of the emergent trophic network and the rate at which primary resources are supplied control many features of microbial community assembly, including the relative contributions of competition and cooperation and the emergence of alternative community states. Viewing microbial community assembly through the lens of trophic interactions also has important implications for the spatial dynamics of communities as well as the functional redundancy of taxonomic groups. Given the ubiquity of trophic interactions across environments, they impart a common logic that can enable the development of a more quantitative and predictive microbial community ecology. ll

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“…This is still largely unresolved because, traditionally, different facets of resource availability have been tackled separately, with theory focusing on the effects of the number of resources on species coexistence, e.g. (4)(5)(6)(7), and experiments concentrating on the impact of resource identity on community composition and function (8)(9)(10)). Yet, understanding how the identity and number of available resources shape microbial diversity is key to anticipating the response of ecosystem to alterations in the environment, including global climate change and evolving human diets (11).…”

Section: Main Textmentioning

confidence: 99%

Resource-diversity relationships in bacterial communities reflect the network structure of microbial metabolism

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Lee

Goyal

et al. 2020

Preprint

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Microbial community diversity is pivotal for the functioning of our planet, but its drivers are still unclear, in particular the role of resource number and identity. To fill this gap, we studied the assembly of hundreds of soil-derived microbial communities on a wide range of well-defined resource environments, from single carbon sources to combinations of up to 16. We found a remarkable diversity in single resources but a linear one-by-one increase in the number of species with the number of additional resources. We show, both experimentally and theoretically, that both these observations could originate from generalist and specialist taxa interacting in a modular fashion within the community. Since generalists and specialists are ubiquitous in natural microbiomes, our results might apply to a variety of different ecological settings, providing a framework to predict how community diversity responds to changes in resource availability.

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The effect of resource dynamics on species packing in diverse ecosystems

Cited by 12 publications

References 32 publications

The Community Simulator: A Python package for microbial ecology

The Community Simulator: A Python package for microbial ecology

Trophic Interactions and the Drivers of Microbial Community Assembly

Resource-diversity relationships in bacterial communities reflect the network structure of microbial metabolism

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