Erin A. Mordecai, Nicole A. Molinari, Karen A. Stahlheber, Kevin Gross, and Carla D’antonio. 2015. Controls over native perennial grass exclusion and persistence in California grasslands invaded by annuals. Ecology 96:2643–2652. http://dx.doi.org/10.1890/14-2023.1


Supplement

R script files containing parameter data, model fitting, and model analyses.
Ecological Archives E096-234-S1.

Copyright


Authors
File list (downloads)
Description


Author(s)

Authors: Erin A. Mordecai1,5 Nicole A. Molinari,2 Karen A. Stahlheber,2,4 Kevin Gross,3 and Carla D’Antonio2

1 Author to whom correspondence should be addressed. Department of Biology, University of North Carolina at Chapel Hill.
2 Ecology, Evolution, and Marine Biology, University of California Santa Barbara.
3 Biomathematics Program, North Carolina State University.
4 Present address: W. K. Kellogg Biological Station, Michigan State University and Department of Agronomy, University of Wisconsin-Madison.
5 Present address: Department of Biology, Stanford University, Stanford, CA 94305. emordeca@stanford.edu


File list

Rcode.zip (MD5: f7b43cfb2e69885f1d571fd09509875a)

Description

This ZIP file contains two R files, three BUG files, and four Rsave files. These files contain the code and data used to fit and analyze the models described in the main text.

mordecai_parameter_fitting.R

This is an R script that fits posterior distributions of parameters from data. This script uses the following BUG files: bayes_survival.bug, bayes_seed_production.bug, bayes_seedling_survival.bug. It also uses the raw data saved in the file: mordecai_data_sources.Rsave.

The script runs through Bayesian model fitting using MCMC for each of the parameters listed in Table A1, with specified priors and MCMC methods. It saves MCMC samples for further model analyses. It creates Figs. B1–B11.

mordecai_analyses.R

This is an R script containing all analyses of the parameterized population growth models. It uses the following data files: samps.Rsave, sensitivity.Rsave.

The script analyzes the parameterized population growth models by calculating growth rates when rare (GRWR) and performing sensitivity and uncertainty analyses. It creates Figs. 1–3 and B12–B18.