An Analysis of Campground Resources in the Lake States Larry A Leefers1 J. Michael Vasievich2 Abstract: Developed camping participation has increased in recent decades, and this trend is projected to continue. Campgrounds supply opportunities for this activity. As part of the Great Lakes Ecological Assessment, we gathered information on 1,854 campgrounds located in the Lake States (Michigan, Wisconsin, and Minnesota). Campgrounds were mapped and attributes compiled from a variety of published and online sources. The analysis compares campground attributes, including fees, facilities, and spatial characteristics. Findings show that public and private campgrounds differ substantially in their characteristics and spatial distribution. This information is useful for resource management, but limitations of the data must be understood. Introduction English et al. (1993) examined regional recreation supply and demand trends. One region, the North, covered 21 states in the midwestern and northeastern United States, including the Lake States (Michigan, Wisconsin, and Minnesota). Relative to year 2000, they projected that developed camping consumption in the North will increase by over 25% in the next 20 years. And the Lake States will provide many opportunities to satisfy future demands. This paper presents an overview of private and public campgrounds in the Lake States and assembled data provide a baseline for future comparative analyses. Data were compiled for 1,854 campgrounds in the Lake States as part of the Great Lakes Ecological Assessment (http://econ.usfs.msu.edu/gla/). The Great Lakes Ecological Assessment (GLA) is an interagency project, started in 1995, involving the USDA Forest Service and Natural Resource Conservation Service, USDI Biological Resource Division, the US Environmental Protection Agency, Michigan State University, Michigan Technological University, the University of Michigan, the University of Wisconsin at Madison, and the University of Minnesota at Duluth. The initial phase of the project focused on data collection, including data related to outdoor recreation (Vasievich & Webster, 1997). The second phase is focusing on policy-relevant analyses with an emphasis on sustainability. This analysis of campground data falls into the second phase. Data and metadata are available from the USDA Forest Service North Central Research Station3. The campground data are in MS-Access format. Over 50 sources were used to compile information resulting in uneven coverage for certain variables of interest (e.g., rates charged were not available for all campgrounds). However, the data provide the first region-wide compilation of campground information. Campground Data In 1998, public and private campground data were compiled for the Lake States. Campgrounds are defined as facilities with two or more sites available for rental on a daily basis to the public. Some private campgrounds, such as church and scout camps, are not included. Dispersed campsites in designated special use areas, such as federal wilderness areas, are not generally included. And, in some cases (e.g., Isle Royale) multiple, small dispersed sites were aggregated for reporting purposes. The following data are included in the campground database: campground name, general location (some directions, city, county, state, and zip code), geographic location (latitude and longitude in decimal degrees), administrators of the campground (e.g., Ottawa National Forest), and ownership class (e.g., private, county, etc.). If available, high and low daily site rental rates, number and types of campsites, campground size, and campground amenities are included, too. To develop latitude and longitude data, campgrounds were geo-referenced by locating the site on a computerized map (DeLorme and American Automobile Association, 1998). Few sites were geo-referenced prior to our data compilation. Multiple sources were used to assure accurate location, but campground locations have not 1 Associate Professor, Department of Forestry, Michigan State University, East Lansing, MI 48824-1222. Email: leefers@msu.edu 2 USDA Forest Service, Natural Resource Information System, 1407 S. Harrison Road, East Lansing, MI 48823. Email: mvasievich@fs.fed.us3 Data are available from Sharon Hobrla, USDA Forest Service, North Central Research Station, 1407 S. Harrison Road, East Lansing, MI 48823. Phone: 517-355-7740, ext. 20. Email: shobrla@fs.fed.us been independently verified (e.g., with global positioning systems). Figure 1 presents the spatial distribution of public and private campgrounds across the Lake States. Because these data are geo-referenced, they can be combined with a myriad of other types of spatial data (e.g., highways, hydrography, administrative units, etc.). Figure 1 illustrates several patterns across the region. First, campgrounds are available in almost all counties in the region, from urban areas to remote peninsulas. Second, private campgrounds tend to cluster in more populated areas (e.g., Minneapolis-St. Paul, MN) and near popular locations (e.g., Door County, WI which juts into Lake Michigan northeast of Green Bay). While not as evident in the figure, major highways are magnets for private campground development. Finally, most public campgrounds are concentrated in the more forested northern counties where public lands are more common. Figure 1. Distribution of 1,854 private and public campgrounds in the Lake States, circa 1998. Comparative Analysis of Private and Public Campground Data Public campgrounds provide unique camping opportunities, distinct from private campgrounds. Public land managers often have limited information about other campgrounds, and users generally have even less information. This section of the paper provides an overview of the campground resources or supply in the three states. Specifically, we summarize data on number of campgrounds by ownership class, number of campground sites by ownership class, average daily rates charged by campgrounds, and attributes of private and public campgrounds. Of the 1,854 campgrounds identified, the private sector accounts for 56% (Table 1). The largest number of campgrounds is in Michigan (747), followed by Wisconsin (562) and Minnesota (545). Half of Michigan’s campgrounds are in public ownership; approximately 40% of Wisconsin and Minnesota campgrounds are in public ownership. Michigan’s largest public lands holdings are in state forests and national forests, respectively—they are also the largest public providers of campgrounds. Michigan also has the most state recreation areas, which are concentrated mostly in the southern counties near urban areas. Wisconsin public land ownership is dominated more by counties, and county parks provide the largest number of campgrounds. Minnesota has a more balanced public lands ownership pattern, and this balance is reflected in the distribution of public campgrounds. The number of campgrounds provides one measure of opportunities, but the number of campground sites (number of individual sites within a campground) provides a better measure of capacity. Table 1 Campgrounds in the Lake States by ownership class (n = 1,854 campgrounds) Ownership Class Minnesota Wisconsin Michigan TOTAL Private 330 332 374 1,036 State Forest 43 36 140 219 National Forest 46 48 73 167 State Park 60 38 58 156 County Park 22 79 41 142 Municipal Park 32 24 35 91 State Recreation Area 2 1 19 22 Army Corp of Engineers 8 3 1 12 National Park 1 6 7 Regional Park 2 2 TOTAL 545 562 747 1,854 Approximately two-thirds of the campground sites are in private ownership (Table 2). This measure of capacity indicates that Michigan has significantly more sites than Wisconsin, which has considerably more than Minnesota. The pattern likely reflects the larger populations in the eastern part of the Lake States. Regionally, state parks are the second largest suppliers of campground sites followed by county parks, which are particularly important in Wisconsin. State recreation areas have the largest number of sites per campground (133); state parks average 118 sites, and private campgrounds average 97 sites. National forests (26 sites/campground) and state forests (27 sites/campground) have the lowest average capacity. On average, people wanting less interaction with others will likely camp at national forest or state forest campgrounds. Limited data on different types of sites (e.g., tent only, recreational vehicle, etc.) are available, but not here reported due to the small sample size. Table 2 Campground sites in the Lake States by ownership class (n = 1,813 campgrounds) Ownership Class Minnesota Wisconsin Michigan TOTAL Private 19,725 36,819 41,088 97,632 State Park 4,011 3,561 10,875 18,447 County Park 1,180 5,386 5,422 11,988 State Forest 933 1,997 3,073 6,003 Municipal Park 2,036 704 2,393 5,133 National Forest 1,297 1,191 1,865 4,353 State Recreation Area 108 217 2,602 2,927 Army Corp of Engineers 283 223 506 National Park 21 485 506 Regional Park 90 90 TOTAL 29,663 50,119 67,803 147,585 Campgrounds are also differentiated by the rate or fee they charge customers (Table 3). On average (calculated as the mean of the highest and lowest rate generally charged), private campgrounds charge considerably more than public campgrounds ($17.01 versus $13.00 or less). State forests ($6.49) and national forests ($7.03) are the lowest cost options for campers. There are patterns worth noting within ownerships as well. For example, the average daily rate for a national forest site in Michigan is $5.60, whereas the average rates in Wisconsin and Minnesota are over $8.00. Average state forest rates are higher in Wisconsin ($10.00) than in Michigan ($7.00) and Minnesota ($7.00). Table 3 Average daily rate (1998 dollars) and standard deviation in the Lake States by ownership class (n = 1,315 campgrounds) Average Standard Ownership Class Daily Rate Deviation Sample Size ($) ($) (n) Private 17.01 4.03 685 Regional Park 13.00 NA 1 Municipal Park 11.92 3.96 19 State Park 10.80 2.13 155 State Recreation Area 10.67 2.09 21 National Park 10.08 3.95 6 Army Corp of Engineers 9.67 1.37 6 County Park 9.42 2.76 49 National Forest 7.03 2.19 154 State Forest 6.49 1.11 219 To provide more information on the regional distribution of daily rates, we examined the 4 ownership classes (i.e., private, national forest, state forest, and state park) with the highest number of samples (Figure 2). National forests and state forests compete with state parks and private campgrounds at the low-cost end of the spectrum. State parks tend to concentrate in the low to medium price range, and private campgrounds dominate the medium to high price range. Public campgrounds tend to have one set price, or perhaps two prices, within a geographic area (e.g., a state) whereas private campgrounds have a much wider range in daily rates. Attributes of the campgrounds play a major role in determining rates. Attributes of areas were reported in various formats using similar, but not identical, language (e.g. fishing vs. pond fishing vs. river fishing and swimming vs. swimming pool). In many cases, only the most important attributes may have been highlighted—this is a shortcoming of using various published sources. We categorized attribute data into lake/swimming, fishing, boating/canoeing, playgrounds, hiking, other trail-related activities, picnic areas, sports fields, and other recreation areas/facilities (Table 4). Over 1,700 campgrounds had some information on campground attributes and many had multiple attributes listed (e.g., fishing and swimming). Water was the most noticeable attribute—via the mention of lakes, swimming, fishing, and boating/canoeing. About two- thirds mentioned a lake and/or swimming. In the private sector, swimming pools were often mentioned (n = 276); this was a rare attribute in the public sector. Playgrounds and recreation areas/facilities were often noted for private campgrounds. In total, these facility investments and the need for a profit lead to higher prices in the private sector. Public campgrounds tend to provide a higher proportion of hiking, other trail-related activities, and picnic areas. The property-tax-free status of public lands and profit needs of private campgrounds lead to a lower rate structure for public campgrounds. Figure 2. Distribution of daily campground rates for major providers. Thus, there are many types of data that are used to categorize campgrounds (e.g., location, ownership, number of sites, fees charged, types of attributes, etc.). A unique feature of our data is that it is spatially referenced. This allows managers, marketing specialists, researchers and others the opportunity to examine relationships that were previously difficult to explore—and mapping the results is useful in its own right. Table 4 Attributes of Public and Private Campgrounds in the Lake States (n = 1,714 campgrounds) Attribute Private Public Total Lake/Swimming 742 477 1219 Fishing 427 366 793 Boating/Canoeing 239 287 526 Playground 376 76 452 Hiking 69 167 236 Recreation Areas/Facilities 188 26 214 Picnic Area 38 67 105 Sports Field 67 18 85 Other Trail-Related 16 22 38 Spatial Analysis of Campground Data A geo-referenced campground database provides opportunities to analyze the location of campgrounds relative to each other, natural resources, population centers, and transportation corridors. Spatial analyses are useful for explaining factors that affect market dynamics, location decisions, and supply-demand issues. A variety of spatial attributes can be mapped and analyzed. For example, price differences across the region can be displayed (Figure 3)—this provides an example of simply displaying existing spatial attribute data. Effectiveness of such analyses, however, depends on the accuracy and completeness of spatial and attribute data. Figure 3. Average prices (1998 $/day) charged at campgrounds (n = 1,315 campgrounds where rate data were available). As an example of looking at campground density, we identified areas with high concentrations of campgrounds that may be considered key market areas or preferred destinations. ArcView was used to construct buffers with a 25-mile radius around each campground location. The buffer radius was set as a reasonable distance that campers might drive to find alternative facilities and also as a practical distance that could effectively discriminate high-density areas. Buffers were intersected with the full set of campground locations to count the total number of campgrounds located within each buffer. Buffer areas (1,854 in total) were found with 1 to 51 campgrounds in each buffer. Fifty percent of the buffers had at least 15 campgrounds; 25 percent of the buffers had at least 20 campgrounds; and 10 percent of the buffers had at least 30 campgrounds. We selected the top 10 percent of the buffers with 30 or more campgrounds and designated these as very high campground concentration areas. A second tier of high concentration areas was selected by using buffers with at least 20 campgrounds. Some concentration areas are larger than others because buffers meeting the same selection criteria overlap. This process identified six areas in the Lake States (Figure 4) with very high concentrations exceeding 30 campgrounds within any 25-mile radius buffer. Areas are clusters of circular buffers all meeting the same count criterion. Buffers appear oval in Figure 4 because it is an Albers map projection. In Wisconsin, the Wisconsin Dells - Baraboo Hills area showed the highest campground concentration in the region, exceeding 40 campgrounds in each buffer. The lake region near Vilas County, Wisconsin also showed very high campground densities. Two areas were found in the northern lower peninsula of Michigan—generally from Houghton Lake to Cheboygan and along the western portion of the northern lower peninsula including the Lake Michigan shoreline from Muskegon to Traverse City. In Minnesota, very high concentrations were located in the Brainerd and Bemidji areas. Several patterns emerged in the second tier of high concentration areas with at least 20 campgrounds within each buffer. The relaxed number of campgrounds in the selection criterion resulted in expansions of the six very high concentration areas and also identified several additional areas. Additional high concentration areas were found near major metropolitan areas—northeast of Minneapolis-St. Paul, west of Milwaukee, and in a crescent stretching through lower Michigan. High concentration areas also showed up in northwestern Wisconsin near Hayward, northeastern Wisconsin near the Nicolet National Forest, the eastern upper peninsula of Michigan, and Door County, Wisconsin. Although this method is imprecise, it demonstrates the potential for spatial analysis that can serve as a first- step for more in-depth analyses of campground markets. Other analyses might examine the proximity of campgrounds to water resources, public lands, travel corridors or major urban centers. Also, opportunities exist to compare areas or examine patterns within areas such as price competition or factors that influence the mix of public and private facilities. Figure 4. Location of areas of very high and high concentrations of campgrounds in the Lake States (Very high concentration areas had at least 30 campgrounds within a 25-mile radius buffer. High concentration areas had at least 20 campgrounds.). Discussion The Great Lakes Ecological Assessment provided the means to assemble spatial data on campgrounds in the Lake States. Data collection is, of course, only the first step. These data are available to all interested parties for further summary and analysis. But the quality of this spatial data must be considered as well as the quality of data with which it is combined. For example, we looked at hydrography data associated with a nearby state park in Michigan. We expected that our geo-referenced campground location would be close to the lake in the park, however there was no lake on the hydrographic layer. In some cases, we may have located the campground near its entrance leading to some bias, but we are unable to quantify this. Moreover, we used multiple data sources to create our database and in some cases, attribute data were missing. Nonetheless, this database provides the first comprehensive set of spatial campground information for the region. Several data summaries are presented in this paper, and some simple spatial analyses are illustrated. All are based on secondary data. In the future, researchers should consider developing campground data in the Lake States through primary data collection. A more complete census of campground attributes, pricing, capacity, and other factors could be developed. Capacity trend data could be created by identifying when the campgrounds were developed and expanded. Information on water access and seasons of operation would also be of interest. Until then the data we have compiled should be viewed as incomplete or partial, but it provides an important baseline. Natural resource data related to recreation is always of interest, and its policy relevance can be explored. For the data we have compiled, pricing policies may be of most interest to public and private campground managers. What factors influence public and private supply? Why does one campground charge a higher price than another? Who are nearby competitors? We have not answered these questions, but our compiled data provide an opportunity to begin to address these questions. References DeLorme and American Automobile Association. (1998). AAA Map ‘n’ Go (Version 4.0) [Computer software]. Yarmouth, ME: DeLorme. English, D.B.K., Betz, C.J., Young, J.M., Bergstrom, J.C., & Cordell, H.K. (1993). Regional demand and supply projections for outdoor recreation (Gen. Tech. Rep. RM-230). Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station. Vasievich, J.M., & Webster, H.H. (Tech. Coords.). (1997). Lake States regional forest resources assessment: Technical papers (Gen. Tech. Report NC-189). St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station. Acknowledgments The authors would like to thank Jennifer Ross and Kayce Bloom for their assistance in compiling and verifying campground information. Also, thanks to the North Central Research Station, USDA Forest Service and in particular Sharon Hobrla for supporting these data and maintaining the Great Lakes Ecological Assessment web site (http://econ.usfs.msu.edu/gla/) and Dr. David T. Cleland for his encouragement and unwavering support.