For this assignment, I was tasked with calculating home ranges from the observed locations of seven coyotes using two methods. The first method entailed using the tool "Minimum Bounding Geometry" to get a general area of each coyote's home range. The second method involved using the tool "Kernel Density" to estimate the probability of encountering an animal in any given location in the home range. This density surface was also used to find the general (95%) and core (50%) home ranges of the coyotes. Finally, I used LANDFIRE data in combination with the coyotes' locations to determine the landcover types that the animals are differentially preferring, known as the preference ratio. The dataset used for this lab was provided by Dr. Eric Gese.

Home Ranges

Preference Ratios

In the figure above, you will find that landcover types with a preference ratio of one or higher are they coyotes' preferred environments. However, it should be noted that some of the higher preference ratio results may be skewed due to the small amount of observations on that landcover type.

Density Surfaces

In order to determine general and core coyote home ranges, a kernel density surface must be calculated. The "Kernel Density" tool in Arc Pro is uses the known locations of coyotes to calculate a density surface where each raster cell is the density of points around that cell, or the probability of encountering an animal in that cell. 

Core and Home Ranges

In order to determine core and general home ranges, I used the "Extract Values to Points" tool to connect the density surface with the coyotes' locations. Each coyote location was now assigned an attribute with its kernel density value. To calculate the core home range, I sorted the density values by descending and recorded the total number of records in the attribute table. I then multiplied the total number by .5 to find the entry containing break value which would determine which records were in the core range. I then ran the "Reclassify" tool on the kernel density raster using the break value I had previously collected to create a new raster illustrating the coyotes' core home range (50%). This process was then repeated for the general home range (95%). Finally, my home range rasters were converted to polygons using the "Raster to Polygon" tool.

Individual Animal Home Ranges

Unfortunately, Arc Pro tools do not allow density surfaces to be based on an attribute field (i.e. Animal). So instead of creating individual shapefiles for each animal to run the Kernel Density tool multiple times, I was able to use a Python script written by Chris Garrard and Tyler Hatch for Arc Pro in 2021. This generated the core and general home ranges for individual coyotes, as illustrated in the map figure above.