GIS 335
Mapping Black Bear Habitat in Marquette County, Michigan
Introduction:
The American Black Bear (Ursus americanus) is a common North American big game animal and is a favorite for many hunters as well as nature enthusiasts. The purpose of this project was to establish areas suitable for black bear habitat to create management areas for the Michigan Department of Natural Resources (DNR). This was done by using multiple geoprocessing tools for vector analysis to analyze which areas were favorable for black bears.
For this project I took on the roll of an employee for the Michigan DNR that was in charge of mapping suitable black bear habitats in Marquette County, Michigan.
To complete the project our objectives were:
Objective 1. Generate a map of bear locations within the pre-determined study area using a GPS MS Excel file of known black bear locations.
Objective 2. Use the GPS locations of black bears to decide which forest types they prefer to inhabit.
Objective 3. Decide whether black bears are found in proximity to streams.
Objective 4. Determine preferable black bear habitat using their preferred forest type and proximity to streams as criteria.
Objective 5. Locate black bear habitat that falls within land already managed by the DNR.
Objective 6. Remove proposed habitat areas that are near urban or developed lands.
Objective 7. Create a data flow model of the how the results were obtained.
Objective 8. Generate some python script based off of the work flow.
Methods:
All data was downloaded from the State of Michigan Open GIS Data Michigan Data. Land-cover data was from USGS NLCD Land-Cover.
To complete objective one, the known bear locations with (x,y) coordinates had to be added to ArcMap as an event theme. This was done so the bear locations could be displayed. In objective two, black bear habitat was determined by using a spatial join to join land-cover with the bear locations. The bear/land-cover join was then summarized to determine which three forest types black bears preferred. It was then determined in objective three that bears were commonly located near streams (results). This result was determined by generating a 500 meter buffer around all streams. After the buffer was created the streams buffer was intersected with the bear/land-cover join, and we were able to see how the amount of bears associated with streams.
Since it was determined that bears preferred mixed forest, forested wetlands, evergreen forests, and were often associated within 500 meters or streams, objective four was completed by using a query of the three preferred forest types. Then preferred forest types were intersected with the streams buffer to generate suitable black bear habitat areas.
To resolve objective five, DNR lands was dissolved into one, then intersected with suitable black bear habitat to determine management areas.
Management areas located within five miles of urban or developed areas were then removed using the erase tool to complete objective six.
A data flow model was then generated to display how the map was generated (Figure 1), and python script was created from some of the operations that were performed (Figure 2).
Results:
Figure 1. Shows the data flow model used to create the bear habitat map, and identify management areas.
Figure 2. Python script showing some of the operations used in lab 3 including buffer, intersect, and erase.
Figure 3. Black bear habitat map showing bear locations, preferred black bear habitat, management areas, streams, DNR lands, urban areas, and the study area.
Results from objective three: Out of the 68 total black bear locations, 49 of them were located within 500 meter of a stream (72%).
Sources:
http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm
DNR management unites
http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html
Streams
http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html
USGS NLCD
http://gis.michigan.opendata.arcgis.com/
State of Michigan Open GIS Data
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