Lab 7

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Lab 7 Information

The intent of this lab was to take GPS points from seven collared coyotes near Dugway Proving Grounds and create 95% and 50% home ranges for each individual, then to calculate the amount of used and available coyote habitat, separated by habitat type.

To do this, I started by importing a shapefile with all of the coyote GPS points into ArcGIS Pro and verifying it showed up near the Dugway Proving Grounds (it did!). To visualize each coyote, I set the symbology to display unique values as different colors, using the Animal column in the coyote data as the values. From there I calculated Minimum Convex Polygons (MCP) for each individual, using the "Minimum Bounding Geometry" tool, with "convex hull" as the geometry type. The area for each coyote's MCP was listed in the attribute table of the shapefile. After calculating the MCPs, I ran the "Kernel Density" tool to calculate habitat use concentration for the entire coyote population. The resulting raster showed where coyotes were most likely to hang out, with high values indicating high area use, and low values indicating low area use.

With this new raster and the coyote GPS points, I used the "Extract Values to Points" tool to create a new shapefile that lists all the coyote GPS points and the corresponding kernel density raster values at each of their locations. Then, to begin calculating the general home range for the population, I selected the GPS points in the shapefile attribute table with the 95% of highest kernel density values, and determined the minimum raster value within the selected points. Using this value, I ran the "Reclassify" tool on the Kernel Density Raster, designating anything below that value as "NODATA" and anything at or above that value as 95. To calculate the core use area, I repeated this with the highest 50% of the kernel density values, designating anything below the highest 50% of values as "NODATA" and anything above as 50. This process created two new rasters, one showing where we would expect to see a coyote if we watched the population 95% of the time (general home range), and the second where we would expect to see a coyote if we only watched the population 50% of the time (core use area). Finally, I ran the "Raster to Polygon" tool to convert the new rasters to polygons.

Next, I opened ArcMap to run the Coyote Toolbox included in this week's lab. The toolbox allows us to calculate home and core ranges for individuals, not just the entire population, without having to split the coyote GPS data into individuals. The "Coyote Script" tool asks for the coyote GPS shapefile I added to ArcGIS Pro at the beginning of the lab and outputs individual 95% and 50% range rasters and shapefiles automatically. After it finished running, I switched back to ArcGIS Pro and imported the new shapefiles, along with the LANDFIRE habitat type raster.

To calculate used and available habitat within the coyote home ranges, I started by clipping the LANDFIRE raster to the population 95% home range, using the "Clip" tool. This created a new raster of only the habitat types within the 95% coyote population home range. Then I calculated the percent of each habitat type within the raster by summing the "COUNT" field in the raster attribute table to get the total number of raster cells, and then using the "Field Calculate" option to divide the number of raster cells of each habitat type by the total number of raster cells. This gives us the percentage of available habitat types within the 95% home range. For the used habitat, I selected only the GPS points that were within the 95% home range by using the "Select by Location" tool, and then I ran the "Extract Values to Points" tool to create a shapefile containing the habitat types at each of those GPS points. I copied that shapefile attribute table from ArcGIS Pro using the copy button, and inserted it into Excel as a Pivot table.

I set the Pivot table to count how many GPS points were recorded from each habitat type (using the RASTERVALU field). To calculate percentage of each habitat type the GPS points were recorded in, I took the number of points for each habitat type from the Pivot table and divided them by the total number of points.

I summarized the available and used raster cell counts and proportions in the table below:

I also calculated expected habitat type use and habitat preference ratios to see if the coyote population was using certain habitats at a higher rate than others. I calculated the expected habitat use by multiplying the number of used cells by the total proportion of available habitat for each habitat type. This gave the number of habitat cells we'd expect to see being used in each habitat type if coyotes were using habitats at random (no habitat preference). Then, to calculate the preference ratio, I divided the number of used cells by the expected number of used cells. Values above 1 indicated that coyotes in this population used those habitat types more than expected, while values below 1 indicated that coyotes used those habitat types less often than expected.

Finally, I created a map showcasing the individual coyote core and general home ranges, and exported it as a .png and a .pdf file.

Lab 7 Answers

1. What is the name of the library that lets Python "talk" to ArcMap?

   1. • Arcpy

2. Which line(s) in the code turn the script's parameters into Python text strings?

   1. • arcpy.GetParameterAsText()

3. Which line(s) in the code output data into the output folder?

   1. • The raster.save(), core_raster.save(), home_range_raster.save() lines tell ArcMap to save the created rasters in the output folder.

      • The arcpy.RasterToPolygon_conversion() lines convert the newly created rasters into polygons and save them in the output folder.

4. What is the resolution of the Landfire data?

   1. • 30m x 30m

5. What numeric attribute field contains the essential data about this vegetation data, the one you will be using for all your calculations?

   1. • The COUNT column

6. How many coyotes in this example would you expect to be mucking about in the water?

   1. • If territories don't overlap, 30% of coyotes, or ~2 individuals would be hanging around in the wetlands. However, if we assume coyotes aren't territorial, then we could have all coyotes mucking about in the water, 30% of the time.

7. What Existing Vegetation Type (CLASSNAME) do the coyotes prefer (highest ratio)?

   1. • Developed-Medium Intensity landcover (2.6 preference ratio)...although it's worth noting the number of cells of this landcover type used was 5, and the expected was 2. Not a whole lot compared to the total number of raster cells used.

8. Did the coyotes prefer Low Intensity Developed landcover?

   1. • Although not the highest preference of the categories, they did seem to prefer it more than expected (1.3 preference ratio).

Additional Downloads

High resolution (PDF) download available here