United States

Department of

Agriculture

Forest Service

Forest

Products

Laboratory

Research

Paper

FPL–RP–542

National Forests

of Wisconsin

Demographics and

Recreation Participation

Joanne T. Alig

Paul R.Voss
Abstract

The primary benefit of this research was to lay a foundation

for examining and predicting future participation in recreation

on a specific national forest. We explain some of the obstacles involved in site-specific projections and note that this is

an area in need of additional research. This study used data

from the 1990 U.S. Census to examine changes in the human population surrounding the Chequamegon and Nicolet

National Forests in Wisconsin. A methodology was then

developed to project future participation in recreation on

those national forests based solely on demographics. This

research highlights the difficulties inherent in making pointin-time estimates or forecasts of recreation participation for a

specific location, such as a national forest. This research also

demonstrates how demographic variables can be used to

describe general trends in recreation participation and plan for

future recreation resource needs. Expected changes in the size,

age, and race and ethnicity of the U.S. population are compared with expected population changes in the areas surrounding the Nicolet and Chequamegon National Forests.

Although other studies have shown that population age will

likely have the most pronounced effect on future recreation

participation at the national level, a decomposition analysis

for the Nicolet National Forest shows that population size

will likely have the greatest effect at the local level.

Keywords: Demographics, recreation, national forests

September 1995

Alig, Joanne T.; Voss, Paul R. 1995. National forests of Wisconsin: demographics and recreation participation. Res. Pap. FPL–RP–542. Madison,

WI: U.S. Department of Agriculture, Forest Service, Forest Products

Laboratory. 14 p.

A limited number of free copies of this publication are available to the

public from the Forest Products Laboratory, One Gifford Pinchot Drive,

Madison, WI 53705–2398. Laboratory publications are sent to more than

1,000 libraries in the United States and elsewhere.

The Forest Products Laboratory is maintained in cooperation with the

University of Wisconsin.

The United States Department of Agriculture (USDA) prohibits

discrimination in its programs on the basis of race, color, national origin,

sex, religion, age, disability, political beliefs, and marital or familial status.

Persons with disabilities who require alternative means of communication

of program information (braille, large print, audiotape, etc.) should contact

the USDA Office of Communications at (202) 720–2791. To file a

complaint, write the Secretary of Agriculture, U.S. Department of

Agriculture, Washington, DC 20250, or call (202) 720–7327 (voice), or

(202) 720–1127 (TTD). USDA is an equal employment opportunity

employer.

Acknowledgments

This study was supported through a cooperative agreement

between the USDA Forest Service, Forest Products Laboratory, and the University of Wisconsin–Madison Applied

Population Laboratory. This research was conducted while

Dr. Voss was Director of the Applied Population Laboratory

at the University of Wisconsin–Madison. Additional support

came from the University of Wisconsin–Madison, College of

Agricultural and Life Sciences, and the Center for Demography and Ecology through a grant from the Center for Population Research of the National Institute of Child Health and

Human Development. We thank Jenny Vanderlin of the

Applied Population Laboratory for data extraction from

Summary Tape File 3A, 1990 Census of Population;

Bob Bodine of the Nicolet National Forest for providing us

with data; and Mary Reuter of the Forest Products Laboratory

for help in creating and organizing the tables and figures in

this report. Finally, we thank the reviewers of this report for

the many helpful comments and suggestions.

Contents

Page

Introduction................................................................1

Methodology ..............................................................1

Current Use Estimate................................................2

Population and Distance ............................................2

Participation Rate.....................................................3

Results...................................................................3

Demographic Characteristics..........................................4

Population Size and Growth.......................................5

Population Age........................................................6

Race and Hispanic Distribution...................................7

Implications for Recreation Participation..........................8

Age Distribution and Population Size ..........................8

Ethnic Diversity.......................................................9

Key Findings............................................................10

Future Research.........................................................10

References................................................................11

Appendix—Demographic Information............................12
National Forests of Wisconsin

Demographics and

Recreation Participation

Joanne T. Alig, Economist

Forest Products Laboratory, Madison, Wisconsin

Dr. Paul R. Voss, Professor and Department Chairman

University of Wisconsin–Madison, Wisconsin

Introduction

Forest resources contribute to our well being in a variety of

ways, including providing for human leisure and recreation.

Opportunities exist in the U.S. national forests to hike,

backpack, camp, picnic, view wildlife, and canoe, just to

name a few. To provide the optimal recreation opportunities,

national forest planners need to have an understanding of who

their customers are and how changes in the population can

affect future participation in recreation.

At the national level, population in the United States is

expected to increase from 262 to 338 × 106 by 2025 (Day

1993). Further, the U.S. population is expected to become

older and more diverse. Demographic changes such as these

can have a significant effect on the demand for recreation.

National population projections have been used to project

recreation participation at the national level (Clawson 1985,

Dwyer 1994, Kelly 1987, Loomis and Ditton 1988, Murdock

and others 1991). State-level work along these lines also

exists (Dwyer, in press; Murdock and others 1990, 1992).

Typically, such studies have multiplied the anticipated

population in an area, often segmented by age, sex, race,

and ethnicity, by similarly segmented participation rates to

obtain a demographic forecast of future participation in an

activity. The majority of work in this general area has used

national or state-wide participation rates obtained from

representative sample surveys of participation and national

population projections to derive nationwide forecasts of

participation. Such use is straightforward and presents no

conceptual difficulties as long as the participation rates by

demographic groups are correct for the given level of analysis

and the demographic projections are reliable. However,

problems emerge when applying this methodology to

subnational recreational areas such as individual national

forests.

This research tested a potential method to estimate future

recreation participation on individual national forests. This

method involved using age-specific demographic variables

coupled with age-specific participation rates to determine

future participation in selected recreational activities. The

results and explanation of difficulties involved in conducting

these analyses are documented. Expected demographic

changes over the next two decades are examined, and a decomposition analysis is used to provide information on the

general trends in future recreation participation.

Methodology

This study tested a new methodology for projecting future

participation in recreation on the national forests in

Wisconsin based solely on demographics. This methodology

involved using a finite distance from the forests such that the

population contained within a circle defined by a radius equal

to that finite distance might reasonably estimate actual current use when multiplied by appropriate participation rates.

If the population so defined does yield a reasonable estimate

of actual current use when multiplied by appropriate participation rates, then changes in the demographic characteristics

of the population can be used to determine changes in future

recreation participation. The methodology involved the

following four steps:

1. Obtain estimates of actual current use.

2. Determine appropriate population base.

3. Obtain appropriate recreation participation rates for the

national forests in Wisconsin.

4. Multiply population by participation rates and compare

with actual use estimates.
2

Current Use Estimate

Recreation activities on the national forests in Wisconsin

include camping, swimming, picnicking, boating, fishing,

hiking, biking, cross-country skiing, snowmobiling, canoeing, and horseback riding (Masberg and Hronek [n.d.]). It is

difficult to determine the number of recreation visitor days or

visitors for each of these activities because numerous points

of entry are available into the forest. Many of these activities

are considered dispersed, and no survey card or other means of

tracking participation in the various activities is currently

available. The exception is developed camping. To camp at a

developed campsite in a national forest, you must pay a fee,

thus the camping experience is recorded. Because use data for

camping are the most reliable, we used camping as the recreational activity of analysis throughout this report.

Estimates of current use of Federal lands by activity typically

contain estimates of recreation visitor days (RVDs), but not

the number of recreation visits or visitors. For purposes of

this study, we wanted the number of recreation visitors rather

than the RVDs. One RVD is equal to 12 h. This could mean

one person recreating for 12 h or three persons recreating for

4 h each. To obtain an estimate of the number of visitors for

camping on each forest, we converted the number of RVDs,

as recorded by each national forest, to hours and divided that

number by the average length of stay in hours as shown in

the following calculation:

Chequamegon Nicolet

Total RVDs for camping 207,300 239,600

× 12 (hours in 1 RVD) 12 12

Equals total recreation

 visitor hours

2,487,600 2,875,200

Divided by average length

 (hours) of stay (1 person)

8 72

Equals annual visitors 30,711 39,933

Total RVDs for camping in the Nicolet and Chequamegon

were obtained from national forest data (Robert Bodine 1993–

1994, personal correspondence). For the Chequamegon, the

average length of stay was determined from a survey of visitors to the Chequamegon National Forest in 1990 (Cordell

and others 1991). For the Nicolet, the average length of stay

was determined from a customer report card for the Lakewood

District, Bagley Rapids campground (Robert Bodine 1993–

1994, personal correspondence). Although the average length

of stay for the entire Nicolet National Forest may not coincide with the average length of stay on the Bagley Rapids

campground, these were the only data available for our use.

Therefore, we determined that the annual number of visitors

is the number of total visitor hours divided by the average

length of stay. For the Chequamegon, the estimated number

of visitors was 30,711 and for the Nicolet, 39,933 (Table 1).

Population and Distance

After determining that our estimates of current participation

in camping in both the Nicolet and Chequamegon National

Forests were reasonable, the next step was to determine the

appropriate population by age that would best represent current participation. The approach in this step of the research

began by acknowledging that participation in an activity at a

specific site generally decreases for persons who live farther

away from that site, and areas with large populations contribute more to participation than do areas with small populations regardless of distance. This can be represented as

PR P /D D D

b b 1 2 ≈

where

PRD = participation rate at distance D from the site

PD = population residing at distance D from the site

D = distance from the site

b1 and b2 = empirically determined parameters that

 describe the slope of the exponential decay

The decrease is steep for those recreational activities that

require people to generally travel only short distances to take

part in (e.g., picnic) and shallow for activities where people

are willing to travel longer distances for (e.g., camp). But, in

general, the observation holds that participation is high for

those who live near a recreational site and low for those who

live far from the site. This presented a problem. We knew of

no survey (with a sufficiently large sample and detailed content) that would permit the determination of participation

rates that are jointly specific to site, distance from site, and

recreational activity, as well as by age (and perhaps by other

useful demographics such as gender and race).

So the question was, Can you take a general participation

rate for an activity and find some distance from a specific

recreational site that permits the demographic estimation of

use? Stated differently, Is there some average distance from a

Table 1—Current use estimate for camping and

population within a 125-mile radius of each forest

National forest Annual visitorsa

Populationb (×106)

Nicolet 39,933 1.68

Chequamegon 30,711 2.38

a

Information based on national forest data.

b

Source: Census of Population 1990.
3

site such that an average participation rate applied to the

population within that average distance yields a reasonable

estimate of use? Implicit in this question is acknowledgment

that not everyone who lives inside the distance radius participates in recreation at the site and, similarly, that some people

who live long distances beyond the radius do participate.1

 The

success of the methodology depends on the validity of using

averages.

Fortunately, a recent survey provided information giving a

frequency distribution of participation in various activities by

distance traveled to the Chequamegon National Forest

(Cordell and others 1991). This information provided a means

of directly deriving an average distance of travel by participants. The average distance traveled by campers to the

Chequamegon National Forest was approximately 140 miles

(1 mile = 1.6 km). Because we did not have an estimate specific to the Nicolet National Forest, 140 miles was also used

for the Nicolet.

Participation Rate

A participation rate is the number of people in a given population that participate in an activity, expressed as a percentage

of the total population. Participation rates are often given for

various age groups. Because specific forests (e.g., Nicolet and

Chequamegon located in the Wisconsin northwoods) are

sought for recreational pursuits by a national and international population, it was deemed appropriate to use national

participation rates for camping in a national forest. However,

national level participation rates for camping specific to national forests do not exist. Rather, age-specific participation

rates for an activity such as camping at the national level are

all-inclusive, representing the percentage of the national

population that camp at a national forest, national park, state

park, county park, or private campground.

Participation rates do exist for Wisconsin residents who have

camped in a national forest. The problem with using these

participation rates is that they reflect participation in any

national forest, not just those in Wisconsin. Furthermore,

the rates are specific only to Wisconsin residents, and we

know that people who camp in the Chequamegon and Nicolet

also come from areas outside Wisconsin.

To derive a national estimate of camping rates specific to

national forests, we assumed that the ratio of Wisconsin

 

1 For example, we know that many visitors to the Nicolet

National Forest come from Chicago, Illinois, and metropolitan areas in southeastern Wisconsin, even though these areas

are outside the 125-mile radius chosen for this study. In this

instance, the large populations in these areas overcome the

“distance effect.” That is, large populations participating at

low rates still yield a relatively large number of visitors.

residents who camp in a national forest to Wisconsin residents who camp in all locations is proportionate to the ratio

of the national population who camp in a national forest to

the national population who camp in all locations.

Data on camping in a national forest and camping in all locations by Wisconsin residents were obtained from the Wisconsin Statewide Comprehensive Outdoor Recreation Plan

(Wisconsin Department of Natural Resources 1991, personal

communication). Data on camping by U.S. residents in all

locations were obtained from Dwyer (1994). Although this

still did not provide us with an age-specific participation rate

specific to a particular national forest, it did provide us with

an age-specific national participation rate for camping specific to national forests (Table 2).

The validation test, then, became one of comparing the outcome of multiplying the estimated vector of national participation rates, by age, with camping in a national forest by the

age vector of the population residing within 140 miles of

each of the two national forests. Because the target use figures and the national participation rates were referenced to the

early 1990s, it seemed suitable to use population data, by

age, from the Census of Population (1990), which includes

Minnesota, Wisconsin, and Michigan. Profiles of the population from the counties of these states falling within the

specified radius were created.

Results

For both the Nicolet and Chequamegon National Forests,

this methodology yielded estimates of actual use that were

too high. Our initial experimentation had used a radius of

140 miles; therefore, we reduced this to a 125-mile radius to

see if this might validate the methodology, but again the

estimates were too high. Using a radius of 125 miles, our

estimate was that 43,775 people used the Nicolet National

Forest for camping annually. This estimate is 9.5 percent

Table 2—Estimated participation rate

for camping in a national foresta

Age group (years) Population (%)

15 to 24 4.42

25 to 34 4.95

35 to 44 4.43

45 to 54 3.49

55 to 64 1.88

65+ 0.36

a

Data obtained by multiplying national

 participation rates for camping by an

 adjusted ratio (DNR 1991, personal

 communication; Dwyer 1994).
4

greater than the estimate of the actual number of participants

of 39,993 based on national forest data. For the Chequamegon National Forest, we estimated that 63,547 people would

use the forest for camping, but actual use was estimated to be

only 30,711, a difference of 106.9 percent. Several factors

may have contributed to our results.

First, we suspect that state borders constitute barriers to use

for some campers. According to a survey, more people are

aware or have visited the Chequamegon and Nicolet from

Milwaukee than from Minneapolis and St. Paul (Dwyer and

others 1992). Milwaukee is both smaller and farther away

from the forests than are Minneapolis and St. Paul, providing

evidence that the border between the two states, presumably

coupled with other recreation opportunities in Minnesota,

reduces visitor awareness and use by Minnesota residents of

the Nicolet and Chequamegon National Forests.

Second, our analysis found that, although the number of visitors to the Chequamegon National Forest for camping was

less than the number of visitors to the Nicolet National Forest according to national forest data, the number of people

living within the 125-mile radius of the Chequamegon is

greater than that for the Nicolet (Table 1). The greater population surrounding the Chequamegon is due to the inclusion

of a large metropolitan county in Minnesota that lies within

the 125-mile radius. The greater participation in camping in

the Nicolet National Forest may be due to the location of the

Nicolet in Northeastern Wisconsin where an abundance of

lakes and water resources are available. Because the Nicolet

and Chequamegon can act as substitutes for each other, future

studies might analyze the population in the market areas of

the two forests together. Further, other substitute sites

should be considered, such as state parks, state forests, and

private campgrounds that have more developed facilities than

do typical national forest campgrounds.

A third reason for our results is that populations are distributed in nonuniform patterns. If the populations distributed in

the three states were uniformly distributed, a method based on

averages would work. This suggests that a distance circle

defined by the average camper does not work in estimating

the actual participation in camping in a specific national

forest, at least under the conditions of widely disparate

population densities.

Fourth, our results were based on use data provided by the

national forests. Although better for camping than for most

other activities, these use data are somewhat unreliable.

National forest personnel have improved their use of surveys

in the past few years, and efforts should continue to further

improve data collection. To obtain good estimates of future

participation, reliable estimates of current participation are

needed. Such information is currently unavailable.

Finally, our results were based up national age-specific participation rates of camping in a national forest derived from

age-specific ratios for Wisconsin of camping in a national

forest to camping in general. Because Wisconsin residents

have greater participation rates for camping in all locations

than nationally, we suspect that Wisconsin residents also

have greater participation rates for camping in national forests. If the presence of two popular national forests in the

state tend to increase the latter rates, then our estimates of

national participation in camping in a national forest may

be high because they are based on Wisconsin data.

Our analysis found that using an average distance traveled and

based only on demographics, it is difficult to obtain accurate

point-in-time estimates or forecasts of participation in recreation. However, our analysis does reveal that the population

contained within the radius that represents the average distance traveled to the forest for recreation actually matches

well with the demographic characteristics revealed in user

surveys conducted in the Chequamegon (Cordell and others

1991). For example, our estimates of participation by age

indicate that 56 percent of those participating in camping

would be between the ages of 25 and 44 and 19 percent would

be between the ages of 45 and 64. These findings are similar

to those from the Chequamegon Customer Survey (Cordell

and others 1991) that indicated that 60 percent of campers in

the Chequamegon are between the ages of 25 and 44 and

21 percent are between the ages of 45 and 64.

This finding results from the fact that our point-in-time estimates of participation were highly dependent on having

chosen a market area of the appropriate population size. A

comparison of the characteristics of the population in terms

of age, race, education, and income with actual user surveys

is less dependent on population size. The population within a

125-mile radius of each of the Wisconsin national forests

then seems appropriate for further analysis, because we know

most users have characteristics similar to these populations.

The next section of this report explains the demographic

characteristics of the populations within the 125-mile radius

of both the Chequamegon and Nicolet National Forests.

Demographic Characteristics

The demographic variables of population size, growth rate,

age, and race/ethnicity were examined at the national and forest level and the results are given in Tables 2−6. (Additional

demographic illustrations for the Chequamegon and Nicolet

National Forests are given in the Appendix.) National level

population projections were obtained from the U.S. Bureau

of the Census (Day 1993). At the forest level, population

data by age were obtained from the Census of Population

(1990) for Minnesota, Wisconsin, and Michigan. Profiles of

the population from only those counties falling within the

specified radius were obtained.
5

The population projections are based on Census of Population (1990) results and employ a standard cohort-component

projection methodology (Irwin 1977). This methodology

uses age-specific rates of mortality, fertility, and net migration to separately account for the three components of population change. In particular, for net migration, an assumption

is first made regarding the future net migration in the state.

This volume of net migration is then allocated to counties

based on prior and anticipated trends. Finally, the number of

projected net migrants for counties is allocated to age groups

based on the particular county-specific age pattern of net

migration observed in the past decade. For the three states

involved, population projections were obtained from the

demographic units in the three state governmental executive

agencies (McMurray and Gillaspy 1993, Wisconsin Department of Administration 1993, Michigan Office of the Budget

1993, personal communication).

Population Size and Growth

National population projections (Day 1993) indicate that

although the U.S. population is expected to increase, it will

grow more slowly than in the past (Tables 3, 4). During the

1990s, the population is expected to grow at an annual rate

of 1.03 percent, from 249 × 106 in 1990 to 276 × 106 in

2000. The annual growth rate is expected to decrease to 0.84

percent by 2010, with a population of 300 × 106, and to 0.82

percent per year by 2020 with a population of 326 × 106.

At the forest level, more than 2.4 × 106 people from counties

in Minnesota, Wisconsin, and northern Michigan lived

within a 125-mile radius of the Chequamegon National Forest in 1990, and more than 1.68 × 106 people from counties

in Wisconsin and northern Michigan lived within a

125-mile radius of the Nicolet National Forest. Counties

included in this analysis are shown in Figure 1.

As shown in Table 3, the population within the 125-mile

radius of the Chequamegon National Forest is expected to

increase 13.6 percent, from 2.4 × 106 in 1990 to 2.7 × 106 in

2020, and the population within the 125-mile radius of the

Nicolet National Forest is expected to increase 8.4 percent,

from 1.68 × 106 in 1990 to 1.82 × 106 in 2020. Faster

growth in the Chequamegon National Forest region is due to

Table 3—Projected population size for the

United States and within a 125-mile radius

of each national foresta

Population (×106)

Year United States Chequamegon Nicolet

1990 249 2.38 1.68

2000 276 2.54 1.78

2010 300 2.64 1.81

2020 326 2.70 1.82

a

Day 1993; Census of Population 1990.

Table 4—Projected population growth rates for

the United States and within a 125-mile radius

of each national foresta

Population growth rate (%)

Year

United

States Chequamegon Nicolet

1990–2000 1.0 0.66 0.57

2000–2010 0.84 0.38 0.2

2010–2020 0.82 0.27 0.05

a

Day 1993; Census of Population 1990.

Table 5—Projected median age for the United

States and within a 125-mile radius of each national foresta

Median age

Year United States Chequamegon Nicolet

1990 32.8 32.9 33.6

2000 35.7 36.3 37.2

2010 37.4 38.8 40.1

2020 38 40.6 41.8

a

Day 1993; Census of Population 1990.

Table 6—Race and Hispanic origin of the United States

and within a 125-mile radius of each national foresta

Total population (%)

United

States Chequamegon Nicolet

White non-Hispanic 83.9 95.3 97.1

African American 12.3 1.3 0.3

Asian/Pacific Islander 3 1.7 0.8

Native American 0.8 1.4 1.5

Other NA 0.4 0.2

Hispanic 9 1 0.6

a

Day 1993; Census of Population 1990.
6

Figure 1—Map showing counties in Minnesota, Wisconsin, and northern Michigan

within a 125-mile radius of the Chequamegon and the Nicolet National Forests.

the increased rates of growth in the suburban and exurban

counties to the east of Minneapolis and St. Paul. Similar to

the nation’s population, the growth rate for the market population of both forests is expected to decrease, as shown in

Table 4. From 1990 to 2000, the population surrounding the

Chequamegon National Forest is expected to grow at a rate of

0.66 percent per year, and the population surrounding the

Nicolet National Forest is expected to grow at a rate of

0.57 percent per year. By 2010, the growth rate for the

Chequamegon National Forest is expected to slow to

0.27 percent per year, and for the Nicolet, the growth rate

is expected to slow to 0.05 percent per year.

Population Age

Baby Boomers and Baby Busters

Understanding the U.S. population and sublevel populations

requires an understanding of the “Baby Boom” and the “Baby

Bust” generations. The Baby Boom took place between 1946

and 1964, two decades when more births took place than at

any other time in U.S. history. Not only were women

having more children, but more women were having children

(Bouvier 1980). In the peak year of the Baby Boom, 1957,

more than 4.3 × 106 births took place. The Baby Bust took

place in the decade following 1964, when the number of

recorded births again decreased. By the mid-1970s, births had

decreased to just over 3 × 106, slightly greater than the

number recorded in the early 1940s.

The implication for the future age distribution of the U.S.

population is significant. The Baby Boomers will be in the

age range 26–44 in 1990, 36–54 in 2000, 46–64 in 2010,

and 56–74 in 2020. The population will age with the Baby

Boomers, affecting the median age of the population and the

age distribution.

Median Age

In the presence of relatively low fertility rates, the median

age is driven primarily by the aging of the population. Because the Baby Boom generation is currently passing through

the age marked by the median, the increase in the median is

especially fast (Table 5). The estimated median age of the

U.S. population in 1990 was 32.8 years. Census Bureau

projections suggest that the median age will increase to 35.7

by 2000 and to 38.0 by 2020 (Day 1993).

Green Bay

Madison

Lake

Superior

Lake

Michigan

Minneapolis

St. Paul

125-mile radius around the

Chequamegon National Forest

125-mile radius around the

Nicolet National Forest
7

The median age of the population living within the 125-mile

radius of the Chequamegon in 1990 was 32.9, almost exactly

the median age for the nation as a whole. Projections indicate

that the median age should increase to 36.3 by 2000, and to

40.6 by 2020 (Table 4). The median age of the population

within the 125-mile radius of the Nicolet National Forest

was 33.6 in 1990, slightly greater than the median age for

the nation as a whole. Projections indicate that the median

age should increase to 37.2 by 2000, and to 41.8 by 2020

(Table 5).

Age Distribution

For the U.S. population, the age group with the largest

expected increase in number between now and the year 2000

is expected to be persons 45–54 years old. This group numbered 25.2 × 106 people in 1991 and is expected to number

36.2 × 106 by 2000, an increase of 44 percent. As the Baby

Boomers move into retirement, around 2010, the average

annual rate of growth for persons 65 and older will increase

from 1.3 percent between 1991 and 2010 to 2.8 percent between 2010 and 2030.

Such changes affect the age distribution of the population.

As illustrated in Figure 2, the percentage of the total population in the age groups under 45 was 68.9 percent in 1990.

This number is projected to decrease to 58.8 percent by 2020.

At the forest level, between 1990 and 2020, the number of

people in all age groups under 45 is projected to decrease. For

the population surrounding the Chequamegon National

Forest, the age group 0–14 is projected to decrease more than

10 percent, from 543 × 103 in 1990 to 486 × 103 in 2020.

The age group 15–24 is projected to decrease by 4 percent

during the projection period, the number of 25–34 year olds

will decrease nearly 14 percent, and the number of people age

35–44 is expected to decrease by about 3 percent.

For the population surrounding the Nicolet National Forest,

similar decreases are projected. The age group 0–14 is projected to decrease 14 percent, from 376 × 103 in 1990 to

324 × 103 in 2020. The age group 15–24 is projected to

decrease nearly 8 percent; the number of 25–34 year olds will

decrease more than 19 percent; and the number of 35–44 year

olds is expected to decrease more than 8 percent.

The number of people in every age group over 45 increases

throughout the projection period for the population surrounding both forests. For the Chequamegon National Forest from

1990 to 2000, the 45–54 age class is projected to increase by

36 percent, from 235 × 103 in 1990 to 319 × 103 in 2020.

During the same period, the number of people age 55–64

nearly doubles (increases by 95 percent). The number of

people over age 65 also increases substantially—more than

60 percent; as life expectancy improves, the number of

people in the age group 75 and over also increases—more

than 44 percent. As shown in Figure 3, the portion of the

population surrounding the Chequamegon National Forest in

the age groups over 45 increases, and the portion of the total

population in the younger age groups decreases.

For the Nicolet National Forest from 1990 to 2000, the

number of people age 45–54 increases 28 percent, from

163 × 103 in 1990 to 209 × 103 in 2020. During the same

period, the number of people age 55–64 increases by 83 percent. The number of people over age 65 also increases substantially—more than 47 percent; as life expectancy improves, the number of people in the age group 75 and over

also increases—more than 32 percent from 1990 to 2020. As

illustrated in Figure 4, the portion of the population in the

age groups over 45 increases, and the portion of the total

population in the younger age groups decreases.

Race and Hispanic Distribution

The U.S. population is expected to become more ethnically

diverse in coming years, as illustrated in Figure 5. In 1980,

85.9 percent of the population was white non-Hispanic. By

1990 2000 2010 2020

0

20

40

60

80

100

%0-14

%15-24

%25-44

%45-64

%65+

Percent

Figure 2—Age distribution of the U.S. population.

Source: Day 1993.

1990 2000 2010 2020

0

20

40

60

80

100

%0-14

%15-24

%25-44

%45-64

%65+

Percent

Figure 3—Age distribution within a 125-mile

radius of the Chequamegon National Forest.

Source: Census of Population 1990.
8

1990, that percentage had decreased to 83.9 percent and is

expected to decrease further to 78.2 percent by 2020. The

African American population is expected to increase from

12.3 percent of the total population in 1990 to 13.9 percent

in 2020. Asian/Pacific Islanders are expected to have the

greatest growth rate, possibly exceeding 4 percent annually in

the 1990s. As a percentage of the total population, the

Asian/Pacific Islander group is expected to increase from

3 percent in 1990 to 7 percent in 2020. The percentage of the

total population that is Native American is also expected to

increase from 0.8 percent in 1990 to 0.9 percent in 2020.

Finally, those of Hispanic origin will represent 15.7 percent

by 2020, up from 9.0 percent in 1990. Thus, racial and

ethnic groups other than white non-Hispanic are increasing in

numbers, and this trend is expected to continue.2

 

2

 Persons of Hispanic origin are a separate category used by

the Census Bureau. Each person included in the census answers a question on race (e.g., white non-Hispanic, African

American, Asian/Pacific Islanders, Native American) and a

separate question on Hispanic origin.

The populations surrounding the Chequamegon and Nicolet

National Forests are not as diverse as the U.S. population.

Both populations consist primarily of white non-Hispanic

residents. As shown in Table 6, only 4.7 percent of the

population within the 125-mile radius of the Chequamegon

National Forest are African American, Asian/Pacific Islander,

Native American, or other race; only 2.87 percent of the

population within the 125-mile radius of the Nicolet

National Forest are minorities. Those who indicated that they

were of Hispanic origin were approximately 1.0 percent of

the population surrounding the Chequamegon National Forest, and less than 1.0 percent for the Nicolet National Forest.

Population projections by race were not available at the

county level for Michigan, Minnesota, or Wisconsin. Therefore, apart from indicating that the populations at the forest

level are not as diverse as the national population and are not

likely to be, little can be said about the future ethnic diversity of the forests.

Implications for

Recreation Participation

At the national level, outdoor recreation customers for many

activities are likely to increase in numbers at a slower rate

than in the past, will be increasingly older, and from racial/

ethnic minority groups (Dwyer 1994). If participation rates

for recreation on the Chequamegon and Nicolet National Forests remain constant over time, projected demographic

changes are likely to result in changes in recreation participation patterns. Based upon the demographic changes projected

for the populations within the 125-mile radius of the two

forests, recreation customers for the Chequamegon and Nicolet will also increase in numbers at a slower rate than in the

past and will be increasingly older. Although the populations

surrounding the forests are likely to become more diverse, the

race/ethnicity mix of the population will probably change

more slowly than the projected changes at the national level.

The following discusses possible changes in recreation participation that can be partially attributed to age distribution,

population size, and ethnic diversity.

Age Distribution and Population Size

Murdock and others (1991) and Dwyer (1993) found a general

trend that increasing age will have a depressing effect on

overall participation in recreation, because most recreation

activities are associated with high participation rates in

younger age groups. Thus, in the United States, the number

of participants in activities such as camping that are popular

with younger participants will decline in the future (Murdock

and others 1991). Murdock and others developed a cohortcomponent projection model using national population projections by age and race/ethnicity, coupled with national participation rates for specific recreation activities. The activities

1990 2000 2010 2020

0

20

40

60

80

100

%0-14

%15-24

%25-44

%45-64

%65+

Percent

Figure 4—Age distribution within a 125-mile

radius of the Nicolet National Forest.

Source: Census of Population 1990.

White nonHispanic

African

American

Asian/

Pacific

Islander

Native

American

Hispanic 

0

20

40

60

80

100 1990

2020

Figure 5—Race/Hispanic origin of total

U.S. population. Source: Day 1993.
9

studied were backpacking, bird watching, camping, day hiking, hunting, picnicking, and walking. Assuming constant

participation rates, Murdock and others conducted a decomposition analysis as developed by Das Gupta (1978) and found

that age will have the most significant effect on change in

future recreation participation in the activities studied, at the

national level. Furthermore, Murdock and others also examined the effect of changes in the number of participants in

recreation activities that could be attributed to population

growth (called the rate effect). They found, as expected, that

population growth enhances the level of participation in

recreation for all activities studied.

For our research, a decomposition analysis was conducted to

determine the effect that the individual components of age and

size will have on future participation in camping on the

Nicolet National Forest, holding current participation rates

constant. Based on techniques developed by Das Gupta

(1978), the decomposition analysis was used to determine

how much of the expected change in future participation in

an activity is directly attributable to age, holding size

constant, and how much is attributable to size, holding age

constant.

We used the following formula to conduct the analysis:

 (e. − E.) = ∑ Ti

 [(ni/n. × N.) − (Ni/N. × N.)]

 + ∑ Ti [(Ni/N. × n.) − (Ni/N. × N.)] + I (1)

where

e. = number of campers expected in 2020

E. = number of campers estimated in 1990

Ti = participation rate for age group i

Ni = 1990 population for age group i

N. = ∑ Ni

ni = 2020 population for age group i

n. = ∑ ni

I = the interaction term

The difference between the estimated number of participants

in camping on the Nicolet National Forest in 1990 and

those projected for 20203, represented by the left-hand side of

Equation (1), is

 (e. − E.) = 43802.56 − 43774.79 = 27.77 (2)

Thus, given our estimates of current and future use, the estimated change in the number of people participating in camping on the Nicolet National Forest will be 27.77, a difference

of 0.06 percent. However, is this realistic? Given the average

distance traveled for camping is 125 miles, the age distribution, and expected change in size of the population, we

 

3

 We conducted the decomposition analysis only for the Nicolet National Forest because the results of our previous

analysis were more accurate for the Nicolet.

believe that the difference of 0.06 percent is realistic. The

following calculates the age effect, the portion of

Equation (1) that tells us how much we can expect participation to change based on changing age distribution, holding

size and participation rates constant:

∑ Ti [ (ni/n. × N.) − (Ni/N. × N.)] = −5649.87 (3)

The result of Equation (3) indicates that because the population within the 125-mile radius of the Nicolet National Forest is expected to have more people in older age groups in the

year 2020, given no change in the size of the population,

there would be a decrease of 13 percent in the number of

people participating in camping. However, this decrease is

expected to be offset by the increase in population size.

The following calculates the size effect, the portion of

Equation (1) that tells us how much we can expect participation to change based on increasing population size, holding

age distribution of the population constant:

∑ Ti [ (Ni/N. × n.) − (Ni/N. × N.)] = 6519.03 (4)

The result of Equation (4) indicates that because the population within the 125-mile radius of the Nicolet National

Forest is expected to increase, the number of people participating in camping would increase by 15 percent.

The interaction term, I, from Equations (1) to (4) is

27.77 − (−5649.87) − (6519.03) = −841.39. The interaction

term is the effect of simultaneously changing population

size and age composition.

This decomposition analysis reveals the effect that the individual components of age and size will have on future participation in recreation, holding constant current participation

rates. Our analysis of the area within a 125-mile radius of the

Nicolet National Forest indicates that population size will

have a more pronounced effect on future participation in

camping than will age. We believe this is because the population within these 125 miles of the Nicolet is already heavily distributed toward the older age groups, thus aging will

not have as large an effect on participation in recreation by

this population as it does for the national population.

Ethnic Diversity

Murdock and others (1991) also examined the effect of

changes in the number of participants in recreation activities

that could be attributed to changes in race. At the national

level, population projections indicate that the proportion of

the population that is white non-Hispanic will decrease from

83.9 percent of the total population to 78.2 percent of the

total population. In general, increasing minority populations

will result in slowing the rate of participation for the activities studied (Murdock and others 1991).
10

Dwyer (1994) examined several recreation activities in

addition to the activities examined by Murdock and others

(1991). Dwyer (1994) found that for some activities, Hispanic and other population groups had comparable or even

greater participation rates than white non-Hispanic, depending

on the activity. Thus, for some activities increasing minority

populations could result in an increase in the rate of participation. Such activities include freshwater fishing.

An examination of the populations within a 125-mile radius

of the Chequamegon and Nicolet National Forests shows that

the proportion of the minority population is less than

4 percent in each case. Although these population groups are

likely to become more diverse, they are unlikely to experience the magnitude of change in diversity that is projected at

the national level. Thus, ethnic diversity will likely play a

less significant role in the change in recreation participation

on these national forests than it will at the national level.

To the extent that the minority population increases in the

areas surrounding these national forests, the number of participants in a given recreation activity may increase or

decrease, depending on the activity.

Key Findings

This study furthers research in projecting participation in

recreation for a specific site, such as a national forest.

Because planners and recreation managers often have limited

budgets and time, we attempted to develop a relatively simple

method of estimating future participation in recreation based

only on demographics. Similar methods have been used at

national and state levels, but problems occur when

attempting to make such projections at the level at which

resource use actually occurs.

Our first obstacle was obtaining reliable recreation use estimates. Data were most reliable for camping, thus our study

was limited to estimating participation in camping. A second

obstacle was that the national forests do not have reliable

information on where visitors are from and how many come

from a particular location. Thus, based upon previous studies, we used a 125-mile radius as a conservative estimate of

the average distance traveled to the national forest for camping. The third obstacle was that participation rates for camping in a national forest do not exist. We derived such participation rates based on data of Wisconsin residents.

We multiplied the population within a 125-mile radius of

each national forest in Wisconsin by the derived participation

rates to obtain estimates of camping in each national forest

in Wisconsin. Results gave us estimates of use that were

high compared with national forest data on actual use. We

cited several reasons for our results and suggested ways to

improve projections in future studies. Nevertheless, characteristics of the local population are important to understand.

Planners and managers are usually aware of national

population shifts, but are unaware of what changes to expect

in the local population structure. Thus, we provided information about the current population and expected demographic

changes for the population within a 125-mile radius of the

Chequamegon and Nicolet National Forests. We then compared these to expected national population changes.

The U.S. population is expected to increase at a slower rate

than in the past, become increasingly older, and more ethnically diverse. Populations in the market areas of the

Chequamegon and Nicolet National Forests are also expected

to grow but at a slower rate than in the past. Further, these

populations are projected to age faster than the nation as a

whole. In 1990, these areas were primarily white nonHispanic. Population projections by race and ethnicity are

not available for these areas, but it is unlikely that these areas will experience the same increase in minority populations

that is projected for the U.S. population.

The final section of this report discusses a decomposition

analysis for expected changes in participation in camping in

the Nicolet National Forest. The analysis showed that,

although age will have the most pronounced effect on future

participation in recreation at the national level, population

size will have the greatest effect at the local level (within the

125-mile radius of the Nicolet). Thus, future participation in

camping will increase overall, but is not expected to change

significantly (less than 1 percent).

The primary benefit of this research was to lay a foundation

for examining and predicting future participation in recreation

on a specific national forest. We have explained some of the

obstacles involved in site-specific projections and note that

this is an area that is in need of additional research.

Future Research

This study investigated a simple methodology to estimate

recreational use of specific national forests based only on

demographics. The task now is to begin refining this methodology to overcome problems inherent in the use of simple

averages, circle distances, and the consideration of forests as

single points when their areas actually stretch for 100 miles

or more.

Some suggestions for future research were received from

reviewers of our study. One suggestion was to use procedures

similar to those used in market area analysis, such as concentric zones in which the probability of participation in an

activity is inversely related to the distance from the site to

the service area. Another suggestion was to develop a distance minimization model, including alternative or substitute

sites. Similarly, a travel cost-based model could be developed

that is useful for predicting site use, but does not reveal how
11

use will change with changing demographics, other than a

possible shift in population across origins. Those shifts can

only be examined using county-level population projections.

Future research should also consider that many retirees have

second homes in northern Wisconsin but are considered nonresidents. Because U.S. Census data do not account for these

nonresidents, some other means of accounting for them

should be considered. Finally, the Nicolet National Forest

has developed the use of “Customer Report Cards” in the past

few years. Data from these report cards were not available at

the time we developed our procedures. and data available at

the time of our study were not considered statistically valid.

Since then, the Nicolet has improved data collection and

tabulation, and this information should be considered in

subsequent research.

References

Bouvier, L.F. 1980. America’s baby boom generation:

the fateful bulge. Population Reference Bureau, Inc. 35(1).

Census of Population. 1990. Summary tape file (STF)

3A for Minnesota, Michigan, and Wisconsin.

Clawson, M. 1985. Outdoor recreation: twenty-five years

of history, twenty-five years of projection. Leisure Sciences.

7(1): 73–99.

Cordell, H.K.; Reed, P.; Clemmons, R.; Coker,

J. [and others]. 1991. Customer. . . understanding today’s

recreating public. Customer Final Report. Athens, GA: U.S.

Department of Agriculture, Forest Service, Southeastern

Forest Experiment Station.

Day, J.C. 1993. Population projections of the United

States by age, sex, race, and Hispanic origin: 1993–2050.

U.S. Bureau of the Census, Current Population Reports,

P25–1104. Washington, DC: U.S. Government Printing

Office.

Das Gupta, P. 1978. A general method of decomposing a

difference between two rates into several components.

Demography. 15(2): 99–112.

Dwyer, J.F., Jr. 1994. Customer diversity and the future

demand for outdoor recreation. Gen. Tech. Rep. RM–252. Ft.

Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station.

Dwyer, J.F., Jr. [In press]. Forecasting outdoor recreation

participation: a cohort-component projection model for Illinois residents. In: 1994 Northeastern recreation research

symposium; 1994 April 10–12; Radnor, PA. Radnor, PA:

U.S. Department of Agriculture, Forest Service, Northeastern

Forest Experiment Station.

Dwyer, J.F., Jr.; Gobster, P.H.; Schroeder, H.W.

1992. Urbanites’ awareness and use of six Lake States

national forests: a spatial analysis. In: 1992 Northeastern

recreation research symposium. Gen. Tech. Rep. NE–176.

Radnor, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station.

Irwin, Richard. 1977. Guide for local area population

projections. U.S. Bureau of the Census. Technical Paper 39.

Washington, DC: U.S. Department of Commerce. July.

Kelly, J.R. 1987. Recreation trends toward the year 2000.

Champaign, IL: Management Learning Laboratories, Ltd.

Loomis, D.K.; Ditton, R.B. 1988. Technique for projecting the future growth and distribution of marine recreational fishing demand. North American Journal of Fisheries

Management. 8: 259–263.

Masberg, B.; Hronek, B. [n.d.]. Communicating with

national forest visitors in Northern Wisconsin: a report on

enhancing the experience of visitors on the Chequamegon and

Nicolet National Forests.

McMurray, M.; Gillaspy, R.T. 1993. Minnesota’s

changing counties: the next 30 years. Minnesota Planning.

October.

Murdock, S.H.; Backman, K.; Colberg, E.;

Hoque, M.N.; Hamm, R. 1990. Modeling demographic

change and characteristics in the analysis of future demand for

leisure services. Leisure Sciences. 12: 79–102.

Murdock, S.H.; Backman, K.; Hoque, M.N.;

Ellis, D. 1991. The implications of change in population

size and composition on future participation in outdoor recreational activities. Journal of Leisure Research. 23:

238–259.

Murdock, S.H.; Backman, K.; Ditton, R.B.;

Hoque, M.N.; Ellis, D. 1992. Implications of future

demographic change for participation in fishing in Texas.

North American Journal of Fisheries Management. 12:

548–558.

Wisconsin Department of Administration. 1993.

Population projections for all Wisconsin counties: in accordance with Wisconsin Statute 16.96. Demographic Services

Center. June.
12

Appendix—Demographic

Information

This Appendix contains demographic illustrations for the

Chequamegon and Nicolet National Forests. Within a

125-mile radius of each forest, current and predicted data

are given for the following:

Based on 1990 Census: [STF 3A Machine Readable Database]

75+

69-74

65-69

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

15-19

10-14

5-9

0-4

Age

120 100 80 60 40 20 0

Thousands

0 20 40 60 80 100 120

Population that resides within 125 miles of the Chequamegon National Forest

Total population, Chequamegon National Forest, 1990

Male

Female

75+

69-74

65-69

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

15-19

10-14

5-9

0-4

Age

Thousands

Total population, Nicolet National Forest, 1990

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Nicolet National Forest

80 60 40 20 0 20 40 60 80

Female

Male

• Total population by age

• Rural and urban population

• Educational attainment of those 18 years and older

• Occupation of those 16 years and older

• Employment status of those 16 years and older

• Household income

75+

69-74

65-69

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

15-19

10-14

5-9

0-4

Age

Thousands

Total population, Chequamegon National Forest, 2020

Source: State demographic units in MI, WI.

Population that resides within 125 miles of the Chequamegon National Forest

140 20 40 60 80 100 120 140 120 100 80 60 40 20 0

Female

Male

75+

69-74

65-69

60-64

55-59

50-54

45-49

40-44

35-39

30-34

25-29

20-24

15-19

10-14

5-9

0-4

Age

Thousands

Total population, Nicolet National Forest, 2020

Source: State demographic units in MI, WI.

Population that resides within 125 miles of the Nicolet National Forest

100 20 40 60 80 100 80 60 40 20 0

Female

Male
13

Population that resides within 125 miles of the Chequamegon National Forest

Based on 1990 Census: [STF 3A Machine Readable Database]

Rural and urban population,

Chequamegon National Forest, 1990

Rural

40.8%

Urban

59.2%

<9th

grade

8.3%

Associate's

7.4%

Grad. or 

prof.

4.8%

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Chequamegon National Forest

Universe: Persons 18 years and over

Educational attainment,

Chequamegon National Forest, 1990

High school 

graduate

36.7%

Some

college

19.9%

9-12th

grade

11.4%

Bachelor's

11.5%

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Chequamegon National Forest

Armed 

Forces

0.1%

Unemployed

3.9%

Universe: Persons 16 years and over

Employment status,

Chequamegon National Forest, 1990

Not in

labor force

33.1%

Employed

62.8%

Population that resides within 125 miles of the Nicolet National Forest

Based on 1990 Census: [STF 3A Machine Readable Database]

Rural and urban population,

Nicolet National Forest, 1990

Rural

48.9%

Urban

51.1%

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Nicolet National Forest

Armed 

Forces

0.3%

Employed

60.8%

Unemployed

3.7%

Not in

labor force

35.2%

Universe: Persons 16 years and over

Employment status,

Nicolet National Forest, 1990

<9th

grade

10.1%

9-12th

grade

12.3% High school 

graduate

40.8%

Some

college

17.1%

Associate's

6.9%

Bachelor's

9.2%

Grad. or 

prof.

3.6%

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Nicolet National Forest

Universe: Persons 18 years and over

Educational attainment,

Nicolet National Forest, 1990
14

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Chequamegon National Forest

Universe: employed persons 16 years and over

Occupation, Chequamegon National Forest, 1990

Administrative

support

15.7% 

Operators,

fabricators

16.6%

Professional 

specialty

13.3%

Service

14.4%

Managerial

10.3%

Sales

10.5%

Precision

production,

11.0% 

Technicians

3.7%

Farming/

forestry/

fish

4.4%

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Chequamegon National Forest

0-9,999

10,000-14,999

15,000-19,999

20,000-24,999

25,000-29,999

30,000-34,999

35,000-39,999

40,000-44,999

45,000-49,999

50,000-54,999

55,000-59,999

60,000-74,999

75,000-99,000

100,000+

0 40 80 120 160 200

Thousands

Household income,

Chequamegon National Forest, 1990

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Nicolet National Forest

Universe: employed persons 16 years and over

Occupation, Nicolet National Forest, 1990

Professional 

specialty

11.2%

Service

14.6%

Managerial

9.1%

Precision

production,

12.2% 

Technicians

3.0%

Operators,

fabricators

20.6%

Administrative

support

14.0% 

Sales

10.1%

Farming/

forestry/

fish

5.3%

Service

14.6%

Based on 1990 Census: [STF 3A Machine Readable Database]

Population that resides within 125 miles of the Nicolet National Forest

0-9,999

10,000-14,999

15,000-19,999

20,000-24,999

25,000-29,999

30,000-34,999

35,000-39,999

40,000-44,999

45,000-49,999

50,000-54,999

55,000-59,999

60,000-74,999

75,000-99,000

100,000+

0 40 80 120 160 200

Thousands

Household income,

Nicolet National Forest, 1990