Community assembly outcome prediction and prioritization - Learning Outcomes Via Experiments (LOVE)

Benjamin Blonder ([email protected]) Michael H. Lim ([email protected])

All included datasets are obtained from public repositories and re-shared here. We do not claim ownership over any of these files. More information on data provenance is available in the Supporting Information of the accompanying manuscript.

Sequentially run the R scripts below in order to replicate all results from the main study.

• 1-predict.R
• 2-plot.R
• 3-plot_abundances.R
• 4-cross_validate.R
• 5-plot-cross-validate.R

To change run parameters (e.g. CORES), see src/config.R. The default parameters for the first script will generate approximately 6GB of outputs which are used to run the second script.