Stochastic logistic models reproduce experimental time series of microbial communities

We analyze properties of experimental microbial time series, from plankton and the human microbiome, and investigate whether stochastic generalized Lotka-Volterra models could reproduce those properties. We show that this is the case when the noise term is large and a linear function of the species abundance, while the strength of the self-interactions varies over multiple orders of magnitude. We stress the fact that all the observed stochastic properties can be obtained from a logistic model, that is, without interactions, even the niche character of the experimental time series. Linear noise is associated with growth rate stochasticity, which is related to changes in the environment. This suggests that fluctuations in the sparsely sampled experimental time series may be caused by extrinsic sources.Read more…

We analyze properties of experimental microbial time series, from plankton and the human microbiome, and investigate whether stochastic generalized Lotka-Volterra models could reproduce those properties. We show that this is the case when the noise term is large and a linear function of the species abundance, while the strength of the self-interactions varies over multiple orders of magnitude. We stress the fact that all the observed stochastic properties can be obtained from a logistic model, that is, without interactions, even the niche character of the experimental time series. Linear noise is associated with growth rate stochasticity, which is related to changes in the environment. This suggests that fluctuations in the sparsely sampled experimental time series may be caused by extrinsic sources.Read more…


Type Path Last modified Size Actions
Data 1 week, 4 days ago 168.7MiB
Experimental.ipynb 1 week, 4 days ago 280.9KiB
Figures eLife.ipynb 1 week, 4 days ago 322.3KiB
Fisher Mehta neutral model annotated.ipynb 1 week, 4 days ago 108.5KiB
Influence interactions SOI and sgLV.ipynb 1 week, 4 days ago 2.1MiB
Noise color fit comparison (linear vs spline).ipynb 1 week, 4 days ago 50.0KiB
README 1 week, 4 days ago 1.1KiB
Study noise no interaction.ipynb 1 week, 4 days ago 1.5MiB
Study noise with interaction.ipynb 1 week, 4 days ago 1.3MiB
Understand noise color.ipynb 1 week, 4 days ago 60.6KiB
Understanding Fisher Mehta Figure 2B.ipynb 1 week, 4 days ago 2.0MiB
Width distribution dx.ipynb 1 week, 4 days ago 184.7KiB
article.ipynb Main 1 week, 1 day ago 311.0KiB
article.xml 1 week, 4 days ago 135.8KiB
article.xml.media 1 week, 4 days ago 300.6KiB
brownian.py 1 week, 4 days ago 2.6KiB
elife_settings.py 1 week, 4 days ago 1.1KiB
generate_timeseries.py 1 week, 4 days ago 15.2KiB
index.html 1 week, 1 day ago 435.6KiB
index.html.media 1 week, 1 day ago 586.8KiB
make_colormap.py 1 week, 4 days ago 1.8KiB
neutral_covariance_test.py 1 week, 4 days ago 5.1KiB
neutrality_analysis.py 1 week, 4 days ago 4.0KiB
noise_analysis.py 1 week, 4 days ago 26.9KiB
noise_color_analysis.py 1 week, 4 days ago 2.7KiB
noise_parameters.py 1 week, 4 days ago 409.0B
noise_properties_plotting.py 1 week, 4 days ago 22.8KiB
results 1 week, 4 days ago 669.2MiB
smooth_spline.py 1 week, 4 days ago 4.6KiB
timeseries_plotting.py 1 week, 4 days ago 1.0KiB