: Logarithmic growth-rates are fundamental observables for describing ecological systems and the characterization of their distributions with analytical techniques can greatly improve their comprehension. Here a neutral model based on a stochastic differential equation with demographic noise, which presents a closed form for these distributions, is used to describe the population dynamics of microbiota. Results show that this model can successfully reproduce the log-growth rate distribution of the considered abundance time-series. More significantly, it predicts its temporal dependence, by reproducing its kurtosis evolution when the time lag τ is increased. Furthermore, its typical shape for large τ is assessed, verifying that the distribution variance does not diverge with τ. The simulated processes generated by the calibrated stochastic equation and the analysis of each time-series, taken one by one, provided additional support for our approach. Alternatively, we tried to describe our dataset by using a logistic neutral model with an environmental stochastic term. Analytical and numerical results show that this model is not suited for describing the leptokurtic log-growth rates distribution found in our data. These results support an effective neutral model with demographic stochasticity for describing the considered microbiota.

Growth-rate distributions of gut microbiota time series

Azaele S.
2025

Abstract

: Logarithmic growth-rates are fundamental observables for describing ecological systems and the characterization of their distributions with analytical techniques can greatly improve their comprehension. Here a neutral model based on a stochastic differential equation with demographic noise, which presents a closed form for these distributions, is used to describe the population dynamics of microbiota. Results show that this model can successfully reproduce the log-growth rate distribution of the considered abundance time-series. More significantly, it predicts its temporal dependence, by reproducing its kurtosis evolution when the time lag τ is increased. Furthermore, its typical shape for large τ is assessed, verifying that the distribution variance does not diverge with τ. The simulated processes generated by the calibrated stochastic equation and the analysis of each time-series, taken one by one, provided additional support for our approach. Alternatively, we tried to describe our dataset by using a logistic neutral model with an environmental stochastic term. Analytical and numerical results show that this model is not suited for describing the leptokurtic log-growth rates distribution found in our data. These results support an effective neutral model with demographic stochasticity for describing the considered microbiota.
2025
   Emergent Dynamical Patterns of Disordered Systems with Applications to Natural Communities
   ministero
   PNRR M4C2 Investimento 1.1 Progetti di Ricerca di Rilevante Interesse Nazionale (PRIN)
   2022WPHMXK
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3562697
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