This repository contains files that contribute to our supplementary materials of the Manuscript: 'Model-based evaluation of management options in ornamental plant nurseries' by Marius Ruett, Cory Whitney, and Eike Luedeling (2020) (https://doi.org/10.1016/j.jclepro.2020.122653).
Within this repository we provide all necessary files to comprehend procedure of code calculations. We illustrate our code for data visualization that enables reproductivity of our figures. Code chunks can be used or optimized for own illustrations based on
decisionSupport
outcomes.
Decision Analysis in ornamental plant nurseries enables assessment of management options concerning fungal disease regulation. Implementation of management options in ornamental plant nurseries need to be accompanied by maintaining economic viability, determination of systems' uncertainties and factors that influence possible outcome distributions. Results of this approach facilitate decision support for heather producers that seek to implement novel management practices but are exposed to the risky nature of heather production. In addition, recommendations can be made to identify risks before making new decisions.
Our input table Input_file.csv
contains all expert estimates that are used in our Calluna_Simulation
function.
Our legend file Legend_file.csv
contains all variable descriptions that we use in our code.
The_Model.R
contains our full code to run the model and to create all figures.
Supplementary_Ruett_2020.Rproj
is where we stored our R project.
The_R_Markdown.Rmd
contains our RMarkdown file as basis of our Supplementary materials.
Our RMarkdown file The_R_Markdown.Rmd
generates the html file The_R_Markdown.html
that represents our Supplementary materials.
We apply journal-of-cleaner-production.csl
as a citation style for our Manuscript and Supplementary materials. All citations are stored in the biblibrary.bib file
.
EVPI csv-files are stored there for further data visualization.
Probability distributions are generated by Monte Carlo outcome and stored in csv files.