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• W2820761262 abstract "Microbiomes impact nearly all systems on Earth, and despite vast differences among systems, we contend that it is possible and highly beneficial to develop a unified conceptual framework for understanding microbiome dynamics that is applicable across systems. The ability to robustly predict and control environmental and human microbiomes would provide impactful opportunities to sustain and improve the health of ecosystems and humans alike. Doing so requires understanding the processes governing microbiome temporal dynamics, which currently presents an enormous challenge. We contend, however, that new opportunities can emerge by placing studies of both environmental and human microbiome temporal dynamics in the context of a unified conceptual framework. Our conceptual framework poses that factors influencing the temporal dynamics of microbiomes can be grouped into three broad categories: biotic and abiotic history, internal dynamics, and external forcing factors. Both environmental and human microbiome science study these factors, but not in a coordinated or consistent way. Here we discuss opportunities for greater crosstalk across these domains, such as leveraging specific ecological concepts from environmental microbiome science to guide optimization of strategies to manipulate human microbiomes towards improved health. To achieve unified understanding, it is necessary to have a common body of theory developed from explicit iteration between models and molecular-based characterization of microbiome dynamics across systems. Only through such model-experiment iteration will we eventually achieve prediction and control across microbiomes that impact ecosystem sustainability and human health." @default.
• W2820761262 created "2018-07-19" @default.
• W2820761262 creator A5004588687 @default.
• W2820761262 creator A5007509063 @default.
• W2820761262 creator A5073834446 @default.
• W2820761262 date "2018-08-01" @default.
• W2820761262 modified "2023-10-01" @default.
• W2820761262 title "A unified conceptual framework for prediction and control of microbiomes" @default.
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• W2820761262 doi "https://doi.org/10.1016/j.mib.2018.06.002" @default.
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• W2820761262 hasPublicationYear "2018" @default.
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