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Data from: Microbial population dynamics decouple growth response from environmental nutrient concentration

Cite this dataset

Fink, Justus Wilhelm; Held, Noelle A.; Manhart, Michael (2023). Data from: Microbial population dynamics decouple growth response from environmental nutrient concentration [Dataset]. Dryad.


To explore the diversity of microbial growth responses, we have compiled 247 measurements of half-saturation concentrations K and maximum growth rates gmax from previously-published studies (see Methods). The data includes a wide range of resources, including sources of carbon, nitrogen, phosphorus, metals, and vitamins, with phosphate, glucose, and nitrate having the largest number of measurements due to their emphasis in marine and laboratory systems.  Organisms include prokaryotes and eukaryotes as well as autotrophs and heterotrophs.

This data has been analyzed in a companion research article. For data plots and a discussion of results, please refer to:

Fink, Justus Wilhelm, Noelle A. Held, and Michael Manhart. “Microbial Population Dynamics Decouple Growth Response from Environmental Nutrient Concentration.” Proceedings of the National Academy of Sciences 120, no. 2 (January 10, 2023).


We collected measurements of Monod model parameters (half-saturation concentration K and maximum growth rate gmax) through a targeted literature search that included prior surveys and reviews [1, 2], the phytoplankton trait database [3], as well as original research papers. In all but two cases, we traced data from surveys and reviews back to their original papers, which we report in Dataset S1 (sheet 1).

We included only experiments that directly measured population growth rates, rather than nutrient uptake rates or respiration. We excluded measurements where the actual limiting resource was unclear, such as measurements in rich medium with added glucose. Where possible, we checked the raw data of growth rate over resource concentrations to determine if the focal resource concentration was measured up to saturation and had sufficient sampling of concentrations around $K$.  For a subset of measurements of E.coli on glucose, we also checked for the concentration of a nitrogen source to determine the relative impact of colimitation (Dataset S1, sheet 2). To assess the effect of pre-acclimation, we focused on a subset of isolates with paired measurements under different regimes of acclimation (Dataset S1, sheet 3). If the original K value was reported as weight per volume, we converted these into units of micromolar (µM) using the calculated molecular weight of the compound's chemical formula. We preserved significant digits from the original studies.

  • [1] Kovárová-Kovar, Karin, and Thomas Egli. “Growth Kinetics of Suspended Microbial Cells: From Single-Substrate-Controlled Growth to Mixed-Substrate Kinetics.” Microbiology and Molecular Biology Reviews 62, no. 3 (1998): 646–66.
  • [2] Owens, J.D., and J.D. Legan. “Determination of the Monod Substrate Saturation Constant for Microbial Growth.” FEMS Microbiology Letters 46, no. 4 (1987): 419–32.
  • [3] Edwards, Kyle F., Christopher A. Klausmeier, and Elena Litchman. “Nutrient Utilization Traits of Phytoplankton.” Ecology 96, no. 8 (2015): 2311–2311.

Usage notes

The datafile can be opened with Microsoft Excel or the free open-source alternative Libre Office.  To open the dataset in Python, we recommend the package pandas. We give a short example how to load this dataset with pandas in the accompanying file ''. 


Swiss National Science Foundation, Award: PZ00P3_180147

Simons Foundation, Award: 542379

ETH Zurich, Award: SEED-26 21-2