Supplement 1. R script files and data from both the field introduction and the mesocosm experiment to execute the models described in the manuscript and in Appendix E.
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Gamma_Negbin_Fecund.R (MD5: 7cd8437e8cd555f777499ef6e3bc279e) -- # R code for fecundity predictions
NegBinFecund.R (MD5: fd282a2e324e20d7529bf51d2d2e14ef) -- # R code for seed model
Gamma_Biomass.R (MD5: 5926e4126625a807b86ebf3b48aa1b93) -- # R code for biomass model
generalBAYESIANcode.R (MD5: bce9894d372872da18a3ee5305f571f5) -- # R code for functions used in above code
garden.csv (MD5: 19d443db46af62e515e38ad07d8ee499) -- # Field introduction data
light_exp_seed.csv (MD5: ac8be1d03af3befc0e1f32e8c5311af8) -- # Mesocosm data
These files are provided to assist in reproduction of our modeling results using the statistical package R. The first supplement (Gamma_Negbin_Fecund) contains R code that jointly samples from the two data sets (garden.csv and light_exp_seed.csv) in order to create predictions of plant fecundity in the field. The hierarchical biomass model (Gamma_Biomass.R) and the seed production model (NegBinFecund.R) are also included separately.