Biological Sciences Division
Published November 30, 2022 | Version v1
Journal article Open

Modelling ecological communities when composition is manipulated experimentally

Creators

  • 1. University of Chicago

Description

  1. In an experimental setting, the composition of ecological communities can be manipulated directly. Starting from a pool of $n$ species, it is possible to co-culture species in different combinations, ranging from monocultures, to pairs, and all the way up to the full species pool. Leveraging datasets with this experimental design, we advance methods to infer species interactions using density measurements taken at a single time point across a variety of distinct community compositions.
  2. First, we introduce a fast and robust algorithm to estimate parameters for simple statistical models describing these data, which can be combined with likelihood maximization approaches. Second, we derive from consumer–resource dynamics a family of statistical models with few parameters, which can be applied to study systems where only a small fraction of the potential community compositions have been observed. Third, we show how a Weighted Least Squares framework can be used to account for the fact that species abundances often display a strong relationship between means and variances.
  3. To illustrate our approach, we analyse datasets spanning plant, bacteria and phytoplankton communities, as well as simulations, consistently recovering a good fit to the data and demonstrating the ability of our methods to predict equilibrium densities in out-of-sample communities.
  4. By combining more robust model structures and fitting procedures along with a more flexible error model, we greatly extend the applicability of recently proposed methods to model community composition from experimental data, opening the door for the analysis of larger pools of species using sparser and noisier datasets than was previously possible.

Notes

Due to the large number of authors, only the first 20 and the University of Chicago authors are included on the above author list. Please download the article for the complete list of authors.

Data availability

All data and model code necessary to recreate the analyses presented in this manuscript are available at https://github.com/StefanoAllesina/skwara_et_al_2022 and archived in Zenodo at https://doi.org/10.5281/ZENODO.7240345 (Skwara et al., 2022).

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Methods Ecol Evol - 2022 - Skwara - Modelling ecological communities when composition is manipulated experimentally.pdf

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Additional details

Identifiers

DOI
10.1111/2041-210X.14028
Other
oai:uchicago.tind.io:13933

Funding

National Science Foundation
DEB-#2022742
National Science Foundation
DGE-1746045

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Ecology and Evolution