Maxent2ConsNet Manual

Transcription

1 Maxent2ConsNet Manual Ver 1.00 August 2008 Michael Ciarleglio Biodiversity and Biocultural Conservation Laboratory, Section of Integrative Biology, 1 University Station, C0390, University of Texas at Austin, Austin, TX Disclaimer Although the Maxent2ConsNet software package has been tested and run successfully on computer systems at the University of Texas at Austin, the software, data, and related materials contained therein are provided AS IS, without warranty of any kind, either expressed or implied, including, but not limited to, the implied warranties of merchantability and fitness for a particular task. University Affiliation Biodiversity and Biocultural Conservation Laboratory (BBCL) Section of Integrative Biology University of Texas at Austin 1 University Station, C 0930 Austin, TX 78712

2 1 Getting Started Software Description Maxent2ConsNet is a software application that reads Maxent output files and prepares a ConsNet input file. It is intended to be used with the Maxent Logistic output format, since this type of output is the most compatible with ConsNet. Maxent2ConsNet provides error checking to find and prevent common mistakes in data preparation. Minimum System Requirements Maxent2ConsNet requires 1GB of RAM and a 1.0 GHz processor. The installation files require less than 1MB of hard drive space. However, Maxent2ConsNet may create temporary hard drive files approximately equal in size to the contents of the Maxent output directory (which may require several GB for large datasets). Maxent2ConsNet has only been tested with the Windows operating system. Install Java Maxent2ConsNet requires a Java Runtime Environment (JRE) compatible with Java 6.0. Many free JREs are available. This software was tested with the JRE from Sun Microsystems, which can be downloaded for free at this website: If you already have an older version of the JRE from Sun Microsystems, please check to make sure that this version is JRE 6 update 1 (6u1) or later. Otherwise, Maxent2ConsNet will not run. Installing Maxent2ConsNet Once Java is installed, installing Maxent2ConsNet is quick and simple. Locate the file maxcon_v10.zip. Unzip the packaged files into a directory on your hard drive (any location that has the available space). Maxent2ConsNet can be completely uninstalled by removing this directory. Running Maxent2ConsNet If the proper Java Runtime Environment is installed, Windows users can run Maxent2ConsNet by double clicking the run_maxcon.bat file in the installation directory. This file contains a command line that will execute the program: start java -Xms512m -Xmx512m -jar maxcon.jar When the program starts, you will see the copyright and usage information. Once you have clicked OK, you should see the startup screen shown in Figure Getting Started pg 1

3 2 Using Maxent2ConsNet After the program starts up, users must provide three pieces of information in order to convert Maxent output data to a ConsNet input file. After providing this information, click the write output file button to start the conversion process. 1. raster cell ID file (see description below) 2. directory containing the Maxent surrogate data 3. the location to save the newly created ConsNet input file Figure 2.1 Startup screen 2.1 Preparing the cell ID file The cell ID file is an ASCII raster that must be created by users in GIS. The values contained in this raster should be a unique GIS ID assigned to each cell. ConsNet will use this cell ID to identify cells for both input and output files. This greatly simplifies the process of moving data between GIS and ConsNet and eliminates potential errors caused by bad input files. This file is easy to create if you have access to the GIS model which was used to create the Maxent input files for the environmental variables. If you were able to create a raster for each environmental variable (such as elevation or precipitation), then you can use the same method to create a raster file which contains the cell ID. The cell IDs must be unique integers (no repeats allowed). They do not have to appear in numerical order. The NODATA value may be any real number. 2 - Using Maxent2ConsNet pg 2

4 Figure 2.2 Example cell ID raster file ncols 720 nrows 300 xllcorner yllcorner cellsize 0.5 NODATA_value Locate Maxent output data The second step is to select the directory that contains the Maxent output data for each species or surrogate. Choose the select button to assign the correct directory. Remember, in this case, you will select a folder, not a single file. The Maxent output format must be logistic. ConsNet checks to make sure that the values in the Maxent output files are between 0 and 1. During the conversion process, Maxent2ConsNet will round these values to the nearest hundredth. The Maxent2ConsNet software will automatically populate a list of.asc files from the directory you selected. The user can select or deselect which individual surrogates should be considered in the final dataset by clicking in the checkboxes in the include column. The Maxent2ConsNet software also provides the user with an option to filter the surrogate data. This is useful when there is more than one set of data in a directory. For instance, you could select only those files whose name contains the text When all selections and filters are in place, click ok to continue. Figure 2.3 Locate Maxent output data 2 - Using Maxent2ConsNet pg 3

5 2.3 Select a location to save the output file The final step is to select the location to save the ConsNet output file. Users will be prompted to choose a location for this file. 2.4 Writing the output file When all three steps have been successfully completed, click write output file to begin writing the output file. Once Maxent2ConsNet has successfully finished writing the ConsNet output file, a message is displayed in the status box displays a message that reads, <filename> has been successfully written. finished, close this window to exit the program. If the conversion process was not successful, an error will be reported on this screen. Figure 2.4 Maxent2ConsNet progress screen Maxent2ConsNet performs consistency checks on the data to make sure all of the rasters are valid. If an error is detected, the conversion process will fail. Here are some of the common errors that can occur. item checked each surrogate raster must have the same dimensions as the cellid raster the masked and active cells in each surrogate raster must be in the same location as the cellid raster the cellids must be unique, no repeats the cellids must be integer values the surrogate names must be unique the values contained in the surrogate rasters (the Maxent output) must be between 0 and 1 error description dimension does not match raster mismatch cellids must be unique non-integer value cannot have duplicate surrogate names invalid data 2 - Using Maxent2ConsNet pg 4