The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities.
The large taxonomic variability of microbial community composition is a consequence of the combination of environmental variability, mediated through ecological interactions, and stochasticity. Most of the analysis aiming to infer the biological factors determining this difference in community struc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-04-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1010043 |
| _version_ | 1818245083637481472 |
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| author | Silvia Zaoli Jacopo Grilli |
| author_facet | Silvia Zaoli Jacopo Grilli |
| author_sort | Silvia Zaoli |
| collection | DOAJ |
| description | The large taxonomic variability of microbial community composition is a consequence of the combination of environmental variability, mediated through ecological interactions, and stochasticity. Most of the analysis aiming to infer the biological factors determining this difference in community structure start by quantifying how much communities are similar in their composition, trough beta-diversity metrics. The central role that these metrics play in microbial ecology does not parallel with a quantitative understanding of their relationships and statistical properties. In particular, we lack a framework that reproduces the empirical statistical properties of beta-diversity metrics. Here we take a macroecological approach and introduce a model to reproduce the statistical properties of community similarity. The model is based on the statistical properties of individual communities and on a single tunable parameter, the correlation of species' carrying capacities across communities, which sets the difference of two communities. The model reproduces quantitatively the empirical values of several commonly-used beta-diversity metrics, as well as the relationships between them. In particular, this modeling framework naturally reproduces the negative correlation between overlap and dissimilarity, which has been observed in both empirical and experimental communities and previously related to the existence of universal features of community dynamics. In this framework, such correlation naturally emerges due to the effect of random sampling. |
| first_indexed | 2024-12-12T14:27:17Z |
| format | Article |
| id | doaj.art-01ee18efd8ce40bda8fc04d7571a844a |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-12T14:27:17Z |
| publishDate | 2022-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-01ee18efd8ce40bda8fc04d7571a844a2022-12-22T00:21:38ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582022-04-01184e101004310.1371/journal.pcbi.1010043The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities.Silvia ZaoliJacopo GrilliThe large taxonomic variability of microbial community composition is a consequence of the combination of environmental variability, mediated through ecological interactions, and stochasticity. Most of the analysis aiming to infer the biological factors determining this difference in community structure start by quantifying how much communities are similar in their composition, trough beta-diversity metrics. The central role that these metrics play in microbial ecology does not parallel with a quantitative understanding of their relationships and statistical properties. In particular, we lack a framework that reproduces the empirical statistical properties of beta-diversity metrics. Here we take a macroecological approach and introduce a model to reproduce the statistical properties of community similarity. The model is based on the statistical properties of individual communities and on a single tunable parameter, the correlation of species' carrying capacities across communities, which sets the difference of two communities. The model reproduces quantitatively the empirical values of several commonly-used beta-diversity metrics, as well as the relationships between them. In particular, this modeling framework naturally reproduces the negative correlation between overlap and dissimilarity, which has been observed in both empirical and experimental communities and previously related to the existence of universal features of community dynamics. In this framework, such correlation naturally emerges due to the effect of random sampling.https://doi.org/10.1371/journal.pcbi.1010043 |
| spellingShingle | Silvia Zaoli Jacopo Grilli The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities. PLoS Computational Biology |
| title | The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities. |
| title_full | The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities. |
| title_fullStr | The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities. |
| title_full_unstemmed | The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities. |
| title_short | The stochastic logistic model with correlated carrying capacities reproduces beta-diversity metrics of microbial communities. |
| title_sort | stochastic logistic model with correlated carrying capacities reproduces beta diversity metrics of microbial communities |
| url | https://doi.org/10.1371/journal.pcbi.1010043 |
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