Note: as of 05-2023 this codebase is being redeveloped for the Conservation of Wild Grapes project. This redevelopment includes some significant updates to the code base, namely, the transistion from SP to SF and raster to terra. Conceptual the metrics and the modeling process are not being significantly altered. Please consider utilizing the Wild Grapes project repository if you are interested in engaing with this code base.
maintainer: dan - carverd@colostate.edu
Code base for a reproducible maxnet modeling methodology written in R.
If you are interest in using this material for your own analysis, three folders are significant
- datePrep : Functions that are called by run_linear.R for individual species model runs.
- dataPrep/dataBaseTransform folder: a series of scripts that covert data from various sources into a common schema. The input datasets for these scripts are not provded in this repo. The final dataset used in the analysis for the paper is available on the Harvard Dataverse.
- alternative : a script called by run_linear.R for species with not enough valid occurrence data to run the Maxnet modeling process.
- maxnet : scripts called by run_linear.R that conduct a variable section, model fitting, model project, and a series of model evaluations.
The gap analysis methodology can be applied to existing species distribution models. We recommend utilizing the GapAnalysis R package if you are applying these assessment methodology for your own work.
- Combinded: a script called by run_linear.R for generate final conservation metric
- exsitu: scripts called by run_linear.R forgenerating the three exsitu conservation metrics
- insitu: scripts called by run_linear.R for generating the three insitu conservation metrics
- redlist: a script called by run_linear.R for evaluting the EOO and AOO red list conservation metrics. Utilizes the function provided by redlisr package
Primary script for declaring all input variables and output locations