 | Project example -Mule Deer Summer Habitat Availability/Preference On the Paunsaugunt Plateau In Southern Utah |
Typical low altitude mule deer habitat on the Paunsaugunt Plateau in Southern Utah |
Typical high altitude mule deer habitat on the Paunsaugunt Plateau in Southern Utah |
Flow chart of data analysis |
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Figure 6. Example of initial Calhome file with both, the MCP and Adaptive Kernel methods being used to calculate homerange |
Figure 7. ''Usable'' file with only the adaptive kernel method present. |
Figure 8. Example of 1 of 18 home range areas overlayed onto GAP vegetation data. (deer 148.465) |
Figure 9. One of eighteen homeranges (deer 148.465) dropped onto GAP vegetation data (close up view) and corresponding attribute table. |
Figure 9. One of eighteen homeranges (deer 148.465) dropped onto GAP vegetation data (close up view) and corresponding attribute table. |
Figure 10. Four homerange configurations super-imposed onto GAP vegetation data layer |
Figure 11. Example of clipped homerange used for vegetation analysis. |
Figure 12. Example of table summary of vegetation/habitats present, and quantity in each homerange; 18 total. |
Figure 13. Chart of vegetation utilization for mule deer of the Paunsaugunt Plateau. X axis = Vegetation class, Y axis = Frequency. |
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ndividual home ranges were superimposed onto a vegetation map of Utah (GAP). Then a query was preformed in order to determine how many hectares of each habitat type were in each home range. The actual point locations, that were used to calculate the home range, were then superimposed onto the GAP data to determine how many points fall in each habitat type. If an animal is found in a habitat more than expected, it was assumed it was selecting that habitat. For example, if sage occurs 20% in the home range and the animal was located in sage 30% of the time, we say that the animal was in the sage habitat more than expected, thus selecting it. A habitat availability/preference index for each individual animal was developed.
Summer home ranges of 18 mule deer, that were located on the Paunsaugunt Plateau, were identified. These home ranges were calculated by inputting UTM locations into the software "CalHome". Calhome calculated the configuration of each home range using between 40-50 individual locations. Both the home range configuration and point data (individual locations) were copied to our workspace.
The GAP vegitation data was aquired from CD-Rom and the study area was over layed onto it using IMAGINE. Using an AOI, the study area, and corresponding vegitation, was clipped and loaded to our file. The initial files using Calhome, had two methods of homerange calculations. One was the minimum convex polygon (MCP) method (straight lines) and the other was the adaptive kernel method (oval) (Fig. 6). Using ARC/INFO and Arcedit, we removed the MCP information, leaving the adaptive kernel polygon, which was to be used for final analysis (Fig. 7).
Our next step was to overlay the actual location/point files on to the homerange and query so as to discover the percentage of points that are found in each habitat type thus producing a habitat availability/preference index for each individual animal. For statistical reasons, similar vegetation types, in the GAP vegetation database, were combined thus we reduced 36 original classes to 11 classes. We changed point files to grid files and home range image files to grid files using ARC/Info. Then we overlaid each of the grid onto the other (ie. deer 1050 points onto deer 1050 homerange image ect. We then used the ''SAMPLE'' command in Arc to determine in which habitat the points were located (Fig. 13). The major class of vegitation from bottom left to bottom right are as follows: mtn. fir, juniper, aspen, ponderosa pine, sagebrush, mtn. shrub, wetlands, spruce, barrens, grassland, and other.
Our initial hypotheses were as follows:
Ho: Paunsaugunt mule deer are utilizing vegetational habitat in proportion to it''s availability.
Ha: Paunsaugunt mule deer are not utilizing vegetational habitat in proportion to it''s availability.
X observed = 473
X critical = 18.3
Based on the Chi-Square critical value, we reject the null hypothesis (Ho:) and accept the alternative (Ha:).
Our overall observations show that Paunsaugunt mule deer are not utilizing vegetational habitat in proportion to it''s availability. Based on figure 13 and the results table, we can infer that they are selecting some types of vegetation more than expected and avoiding others. Vegetation types that are being selected more than expected include Mtn. Fir, Aspen, Ponderosa Pine, Sagebrush, Wetlands, Grasslands and Other. Vegetation types that appear to be selected less than expected consist of Juniper, Mtn. Shrub, Spruce and Barrens. Some vegetation types are obviously avoided more than other types (juniper) while others are decidedly being selected for (ponderosa pine, sagebrush). It is, however, not as clear for other classes, in which observed and expected values are similar. In such cases further statistical evaluation is needed to determine the presence or absence of statistical significance. However based on this project, which is an initial attempt to quantify habitat availability/preference, we conclude that areas on the Paunsaugunt Plateau, that are characterized by heavy stands of juniper, be modified so as to stimulate increased growth of sagebrush and associated vegetation. In the past, this has been accomplished by techniques such as chaining or prescribed burning. In addition, areas that have a large percentage of ponderosa pine should be preserved as mule deer appear to be utilizing this vegetation type at least 50% more than it is available.
Mule Deer Summer Habitat Availability/Preference On the Paunsaugunt Plateau In Southern Utah
