This repository contains the scripts used to develop a stochastic landscape spread model for sudden oak death (SOD)
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README.md
SOD-modeling.Rproj

README.md

SOD-modeling

This repository contains the scripts used to develop a stochastic landscape spread model of forest pathogen P. ramorum, causal agent of the emerging infectious disease sudden oak death (SOD). This project is adjusted from the published research article:

Ross K. Meentemeyer, Nik J. Cunniffe, Alex R. Cook, Joao A. N. Filipe, Richard D. Hunter, David M. Rizzo, and Christopher A. Gilligan 2011. Epidemiological modeling of invasion in heterogeneous landscapes: spread of sudden oak death in California (1990–2030). Ecosphere 2:art17. DOI: http://dx.doi.org/10.1890/ES10-00192.1

layers

This folder contains all the GIS layers necessary to test run our code. Subfolder weather contains weekly m (=moisture) and c (=mean temperature) raster files. These are called by the main R script during execution.

scripts

This folder contains the scripts used in this project. Files with a .r extension are written in R, while a .cpp extension indicates C++ files written using the R package [Rcpp] (http://www.rcpp.org/). The file SOD_aniso_clim_RGRASS.r is the main R script implementing the spread of P. ramorum with the option of accounting for wind direction (anisotropy) and weather suitability. The file SOD_aniso_clim.r is a stand-alone version of the same model to be run within R (NO GRASS GIS needed).

Usage

As of now, the main R script is meant to be run from within [GRASS GIS 7.0.0] (http://grass.osgeo.org/) using the [rgrass7] (http://cran.r-project.org/web/packages/rgrass7/index.html) package. If you want to use GRASS GIS 6 instead, use the [spgrass6] (http://www.cran.r-project.org/web/packages/spgrass6/index.html) package. However, the latter may require some manual adjustments to the code as functions changed names between versions.

NOTE: if you plan on running the code within R only, please checkout the main script and replace the appropriate I/O parameters to read/write raster files and set up initial parameters.

Before running the code make sure to follow these steps:

  1. Install R (our code was tested with version 3.0.2) from here

  2. Open R and install the required packages using the statement: install.packages(c("rgdal","raster","lubridate","CircStats","Rcpp","rgrass7", "optparse", "plotrix")

  3. Open GRASS GIS 7. Select a location from the main window (if none, create one), and a mapset (default is PERMANENT). Go to File >> Import raster data >> common format imports and make sure you import both any rasters to be called during program execution. For example, import the initial host index raster, and the initial sources of infection raster.

  4. Open GRASS GIS 7 and set up a location + mapset where to store/import your initial raster files. This step is necessary in order to (a) have a consistent projection across multiple files (all files within a GRASS location should be in the same coordinate system), and (b) make sure all the output raster files will be stores in the same GRASS location. Select a location from the main window (if none, create one), and a mapset (default is PERMANENT). Go to File >> Import raster data >> common format imports and make sure you import both any rasters to be called during program execution. For example, import the initial host index raster, and the initial sources of infection raster.

  5. Open the GRASS terminal prompt. Set up the GRASS region to match the imported initial raster file using:

  • g.region raster = reference_raster_name
  1. Run the code by invoking the R script from the GRASS terminal prompt using:
    • Rscript path_to_script --arguments_list

Each parameter in the argument list is specified using either the -shortflag or the --longflag option.

-u or --umca input bay laurel (UMCA) raster map

-ok or --oaks input SOD-oaks raster map

-lvt or --livetree input live tree (all) raster map

-src or --sources initial sources of infection raster map

-img or --image your background satellite raster image for plotting (use extention after file name, e.g. image.tif)

-s or --start starting year for the simulation

-e or --end last year for the simulation

-ss or --seasonal restrict pathogen spread to the rainy season only YES (default), NO

-w or --wind account for wind direction for the pathogen spread YES, NO (default)

-pd or --pwdir if you account for wind, what should the predominant wind direction be for the area? N (= North), NE (= Northeast), E (= East), etc.

-spr or --spore_rate spore production rate per week for each infected tree

-o or --output basename for output GRASS raster maps

-n or --nth_output output every nth map

-scn or --scenario future weather scenario

Contacts

Francesco Tonini: ftonini84@gmail.com

Devon Gaydos: dagaydos@ncsu.edu

Anna Petrasova akratoc@ncsu.edu

Vaclav Petras: vpetras@ncsu.edu

License

Apache 2.0