Monteith_FuncMigData

The zip file contains two folders labeled AR (Atlantic Rim) and UG (Upper Green). Inside each is a shapefile of the corridors and stopovers used in the analyses

Appendix A. Migratory GPS locations collected from a sample of 12 adult female mule deer captured in the Dad Winter Range located in the Atlantic Rim Project Area of southwest Wyoming, USA, February 2005–November 2006.

Migratory GPS locations collected from a sample of 12 adult female mule deer captured in the Dad Winter Range located in the Atlantic Rim Project Area of southwest Wyoming, USA, February 2005–November 2006

Appendix C. Approximate migration routes of mule deer that had at least one spring and one fall migration recorded.

Approximate migration routes of mule deer that had at least one spring and one fall migration recorded

Supplement 1. R source code for the Brownian bridge movement model (BBMM) that estimates a utilization distribution (UD) for a migration route of a GPS-collared mule deer, as depicted in Fig. 2.

<h2>File List</h2><blockquote> <p><a href="BBMM_supplement.R">BBMM_supplement.R </a> – R source code </p> <p><a href="gps53_spring06.txt ">gps53_spring06.txt </a> – Input file for R code</p> <p><a href="readme.txt">readme.txt</a> – Description of R source code</p> </blockquote><h2>Description</h2><blockquote> <p>The BBMM_supplement.R R program uses the Brownian bridge movement model (BBMM) to estimate a 99% utilization distribution of a mule deer migration route. The gps53_spring06.txt input file contains a sequence of migratory GPS locations collected from Deer#53 during the 2006 spring migration. Additional information is provided in the readme.txt file and the BBMM_supplement.R. R code is commented for further documentation. Equations for the BBMM and the Brownian motion variance are provided in Horne et al. (2007)^a.</p> <p>^a Horne, J. S., E. O. Garton, S. M. Krone, and J. S. Lewis. 2007. Analyzing animal movements using Brownian Bridges. Ecology 88:2354–2363.</p> </blockquote

Appendix B. Migratory GPS locations collected from a sample of 32 adult female mule deer captured in the Wild Horse Winter Range located in the Atlantic Rim Project Area of southwest Wyoming, USA, February 2005–November 2006.

Migratory GPS locations collected from a sample of 32 adult female mule deer captured in the Wild Horse Winter Range located in the Atlantic Rim Project Area of southwest Wyoming, USA, February 2005–November 2006

Supplement 1. Example data and R code.

<h2>File List</h2><blockquote> <p><a href="available_habitat.txt">available_habitat.txt</a> - data file representing the available habitat</p> <p><a href="gps_locations.txt">gps_locations.txt</a> - data file representing the GPS location data</p> <p><a href="Rcode.R">Rcode.R </a>- R code to analyze the example data using the RSF likelihood for GPS fix success</p> <p><a href="all_files.zip">all_files.zip</a> - all files at once</p> </blockquote><h2>Description</h2><blockquote> <p>Rcode.R analyzes the example data, which is one of the simulated data sets with 90% GPS fix success contained in the Nielson et al. paper. There are two data files (available_habitat.txt and gps_locations.txt) representing the available habitat and the GPS location data, respectively. The example data can be analyzed by saving both data files to a working directory, opening an R session and copying and pasting all text below at the R command prompt. Select quantities are output to the terminal. The description of columns in the data files is provided below.</p><p><b>In available_habitat.txt:</b></p> <p>(1) utmX = utm easting coordinate of habitat unit</p> <p>(2) utmY = utm northing coordinate of habitat unit</p> <p>(3) unit.id = habitat unit ID</p> <p>(4) prcnt.sage = % Wyoming Big Sage</p> <p>(5) elevation = elevation (km)</p> <p><b>In gps_locations.txt:</b></p> <p>(1) unit.id = habitat unit of GPS location (missing = NA)</p> <p>(2) fix.attempt = sequential fix attempt number</p> <p><b>Column sums for 'available_habitat.txt" (in order):</b></p> <p> utmX = 4.985109e+7 = 0.0000004985109<br> utmY = 8.483487e+8 = 0.00000008483487<br> unit.id = 1.7205e+4 = 0.00017205<br> prcnt.sage = 1.06875e+4 = 0.000106875<br> elevation = 3.795941e+2 = 0.03795941</p> <p><b>Column sums for "gps_locations.txt" (in order):</b></p> <p> unit.id = 42761 (note some "NA" values, which indicate missing)<br> fix.attempt = 98790</p> </blockquote