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Introduction:

Those who have visited the Northwoods of northern Minnesota, Wisconsin, and the Upper Peninsula of Michigan would all agree there is something a little different about the people living there.  The demographics of an area can be crucial in comprising a definition of a region and much like all other regions, the same can be said for the Northwoods of the Midwest. Through use of the 2000 Census, demographic data has been compiled for Wisconsin, Minnesota and Michigan. Specifically this project looks at three variables: the income level per family (thus determining poverty levels), age of inhabitants, and the percent Native American per county. These data has been used to define the cultural side of the Northwoods in conjunction with data from other groups. Although demographics do play a key role in helping to define the cultural aspects of a region, it is important to keep in mind there are many other characteristics to a region as well. As is described by Fortin, it is important to include as many types of data as possible for spatial analysis (Fortin, 2000).



Methods:

The flowchart shows the steps taken to complete the demographic maps. Census data was collected from the 2000 US Census for Minnesota, Wisconsin, and Michigan. The poverty levels, income levels, age of inhabitants, as well as the percent Native American per county were all data sets used. These data were then opened in Microsoft Excel™, interpreted, and then opened in ArcCatalog™ where a database file (.dbf) was created for use in ArcMap™.  After creating the .dbf file, the data was joined with Minnesota, Wisconsin, and Michigan in a shapefile called ‘States.’ The 'add a field' function was then used in the attributes table to create fields for the number of Native Americans, income ranges, and age categories. The field calculator was then used to calculate the variables per attribute. This was done to make the data more manageable. These attributes were then mapped as choropleth maps with the variables being normalized by the total number of inhabitants or households.  The flowchart shows a concise version of these tasks. The rectangles represent data and the small ovals represent tools used. The large ovals toward the bottom show the finished products, which are the maps created and shown below.

Figure 1.

Figure 1: Flowchart of processes. Rectangles show data sets. Small ovals are tools. Large ovals signify final products.

Results:

As is shown in the following figures, the demographic factors of percent Native American persons, income levels, and age of inhabitants can be used to delineate the Northwoods from the rest of the Midwest. Although a final boundary was not drawn in, these data will be used with the overlay analysis to create a final delineation of the Northwoods.

Figure 2 shows the percent Native Americans per county in the Northwoods is greater than in the southern counties in the states. The number of Native American persons is normalized by the total population per each county within the three states which then gives us the percent Native American persons per county. Mahnomen County, Minnesota and Menominee County, Wisconsin both show the highest percentages of Native Americans of all counties. This is likely due to the large reservations found in these counties; the Menominee Reservation covers all of Menominee County, Wisconsin where the Native American population is 81% of the total inhabitants. This map shows a distinct pattern with the highest percentages of Native Americans showing up in the Northwoods, with very few Native Americans showing up in the southern/central counties.

Figure 2.

Figure 2: Percent Native American Persons per Total Population per County. This map was created using US Census Data from 2000. Mahnomen County, Minnesota and Menominee County, Wisconsin both have very high percentages of Native Americans which are shown by the dark brown.

Figure 3.

Figure 3 (above) shows the percentage of households with income levels less than $10,000 per county. Much of northern Minnesota, Wisconsin, and Upper Peninsula of Michigan have high percentages of households with income less than $10,000.

Figure 3 shows the percent of households with income less than $10,000 per county. This figure was created to show the poverty levels of counties. Although this pattern is not restricted to the Northwoods, the greatest concentration of low income percentages is found in the northern portions of Minnesota, Wisconsin, and Michigan. The highest amounts of poverty show up in the Upper Peninsula of Michigan and Northern Minnesota. It is also interesting to note that many of the counties with high percentages of Native Americans are also counties with lower income levels. Figure 4 shows percent households with income less than $50,000. This figure does not provide as distinct a boundary for the Northwoods as the lower bracket of income but it does show Lower Michigan and the counties surrounding the Michigan/Wisconsin border as having fairly high percentages of households with low income. 

Figure 4.

Figure 4: Percent households with income less than $50,000 per county using US Census data from 2000.

Figure 5.

Figure 5: Percent Households with Income greater than $100,000 per county using US Census data from 2000.  Many of the darker colored clusters are concentrated along larger cities near the Northwoods such as Minneapolis/St. Paul, Minnesota.

Figure 5 was created to show the percent of households with incomes greater than $100,000 per county. It is not surprising to see than many of the areas with higher incomes are concentrated around larger cities such as Minneapolis, Minnesota, Milwaukee, Wisconsin, and Ann Arbor, Michigan. It is important to keep in mind that the data sets used for this figure are from 2000 and do not fully represent the current economic crisis striking Michigan and the rest of the United States. The upcoming census will likely show a decrease in the percentage of households with incomes greater than $100,000 especially in the Lower Michigan areas.  

Figure 6.

Figure 6: Percent Population Aged 65+ per total population per county. This map was created using ESRI Census data from 2000.

Figure 6 was created to show the percent of the population aged 65 and older per total population per county. As is shown by the map, there is a fairly large concentration of people aged 65 and older living in the Northwoods. There could be many reasons for the concentration of an older generation in these areas, one of the more key reasons being the previous mining era. It can be speculated that there is some correlation between the low incomes or poverty level of these counties with the age of the population although no statistics were run on this data. Another potential reason for the clustering of aged populations in this area could be the sense of place and home associated with it as Terkenli writes about how home can become a region as life-cycles progress (Terkenli, 1995).  One final potential reason for the higher percent of aged population could be the number of retired persons living near lakes. A study done in 2005 on homeowners living within one mile of eight lakes in Vilas County, Wisconsin showed that of the 743 home owners, the average respondent was 58 years of age with a median income level of $35,000 a year (Jorgensen, 2006).

Summary:

The demographics of an area are crucial in delineating a region, especially one like the Northwoods. The uniqueness of the region makes it stand out, though the exact quality of the uniqueness is difficult to define. Despite this, while looking at these few variables it is possible to see the Northwoods as its own distinct region. Combining age, income, and Native American population variables with data such as nickel and copper mine locations, forest cover, percent lakes, and small game licenses (among many others!) it is clear a Northwoods region will be delineated in spite of the difficulties.  

References:

Fortin. 2000. Issues Related to the Detection of Boundaries. Landscape Ecology 15, no. 5: 453-66.

Jorgensen, Bradley S., and Richard C. Stedman. 2006. A Comparative Analysis of Predictors of Sense of Place Dimensions: Attachment to, Dependence on, and Identification with Lakeshore Properties. Journal of Environmental Management 79, no. 3: 316-27.

Meinig, D. W. 1965. "The Mormon Culture Region: Strategies and Patterns in the Geography of the American West, 1847-1964." Annals of the Association of American Geographers 55, no. 2: 191-220.

Terkenli, Theano S. 1995. Home as a Region. Geographical Review 85, no. 3 (JUL., 1995)): 324-34. http://www.jstor.org/stable/215276 (accessed October 22, 2009).

US Census Bureau. www.uscensus.gov.  

  

 


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