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Ecological modelling approaches for predicting emergent properties in microbial communities
Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems they are part of. Emergent properties - patterns or functions that cannot be deduced linearly from the properties of the constituent parts - underlie important ecological...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613029/ https://www.ncbi.nlm.nih.gov/pubmed/35577982 http://dx.doi.org/10.1038/s41559-022-01746-7 |
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author | van den Berg, Naomi Iris Machado, Daniel Santos, Sophia Rocha, Isabel Chacon, Jeremy Harcombe, William Mitri, Sara Patil, Kiran R. |
author_facet | van den Berg, Naomi Iris Machado, Daniel Santos, Sophia Rocha, Isabel Chacon, Jeremy Harcombe, William Mitri, Sara Patil, Kiran R. |
author_sort | van den Berg, Naomi Iris |
collection | PubMed |
description | Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems they are part of. Emergent properties - patterns or functions that cannot be deduced linearly from the properties of the constituent parts - underlie important ecological characteristics such as resilience, niche expansion, and spatial self-organisation. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages, and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based, and genome-scale metabolic models. Future efforts in this research area would benefit from capitalising on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems. |
format | Online Article Text |
id | pubmed-7613029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76130292022-11-16 Ecological modelling approaches for predicting emergent properties in microbial communities van den Berg, Naomi Iris Machado, Daniel Santos, Sophia Rocha, Isabel Chacon, Jeremy Harcombe, William Mitri, Sara Patil, Kiran R. Nat Ecol Evol Article Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems they are part of. Emergent properties - patterns or functions that cannot be deduced linearly from the properties of the constituent parts - underlie important ecological characteristics such as resilience, niche expansion, and spatial self-organisation. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages, and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based, and genome-scale metabolic models. Future efforts in this research area would benefit from capitalising on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems. 2022-07 2022-05-16 /pmc/articles/PMC7613029/ /pubmed/35577982 http://dx.doi.org/10.1038/s41559-022-01746-7 Text en https://www.springernature.com/gp/open-research/policies/accepted-manuscript-termsUsers may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms |
spellingShingle | Article van den Berg, Naomi Iris Machado, Daniel Santos, Sophia Rocha, Isabel Chacon, Jeremy Harcombe, William Mitri, Sara Patil, Kiran R. Ecological modelling approaches for predicting emergent properties in microbial communities |
title | Ecological modelling approaches for predicting emergent properties in microbial communities |
title_full | Ecological modelling approaches for predicting emergent properties in microbial communities |
title_fullStr | Ecological modelling approaches for predicting emergent properties in microbial communities |
title_full_unstemmed | Ecological modelling approaches for predicting emergent properties in microbial communities |
title_short | Ecological modelling approaches for predicting emergent properties in microbial communities |
title_sort | ecological modelling approaches for predicting emergent properties in microbial communities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613029/ https://www.ncbi.nlm.nih.gov/pubmed/35577982 http://dx.doi.org/10.1038/s41559-022-01746-7 |
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