Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
279
AN ECONOMIC IMPACT ANALYSIS
OF A PROPOSED DAKOTA PRAIRIE
NATIONAL HERITAGE AREA
Xiaobing Zhao
The W. A. Franke College of Business
Northern Arizona University
Flagstaff, AZ 86011
Russell Stubbles
Department of Horticulture, Forestry, Landscape and Parks
South Dakota State University
Brookings, SD 57007
ABSTRACT
Although the United States National Park Service (USNPS 2008) has designated 37 National Heritage Areas, they are located mainly in the eastern U.S.
Thus, the Dakota Prairie National Heritage Area (DPNHA) proposed for Brookings, Kingsbury, and Lake County in South Dakota has important significance
for preserving Midwest culture and history. Although the cultural benefits of the
DPNHA are evident, its economic benefits have not been examined and remain
unclear. This study intends to fill this gap by investigating the economic impacts
of the DPNHA. Money Generation Model version 1 (MGM1) developed by the
USNPS (1990) was utilized to estimate sales benefits, tax benefits, and job benefits. Our results showed that the DPNHA could increase significantly the sales,
taxes, and jobs in the three counties. Therefore, the DPNHA is also economically
beneficial for the region.
Keywords
Money generation model, economic benefits, national heritage area
INTRODUCTION
According to the U.S. National Park Service (2008), a national heritage area
(NHA) is a place where “natural, cultural, historic and recreational resources
combine to form a cohesive, nationally-distinctive landscape arising from patterns of human activity shaped by geography”. Conservation and other activities
in a NHA are managed by federal, state, and local governments and the private
sector.
Although the United States National Park Service (USNPS 2008) has designated 37 National Heritage Areas, they are located mainly in the eastern U.S.
Thus, the Dakota Prairie National Heritage Area (DPNHA) proposed for Brook-
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Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
ings, Kingsbury, and Lake County in South Dakota has important significance
for preserving Midwest culture and history. The theme for the DPNHA is the
historical account of European settlement of the tall grass prairie. In addition to
all existing historical and cultural attractions in this area, future features include
the development of four new South Dakota historical prairie village parks, located between Brookings and DeSmet, along the corridor of Highway 14. The
village parks will represent the time periods of the European settlement of 1880,
1890, 1900, and 1910. They could include restored farm buildings, antique
farming equipment, artifacts, Wild West reenactments, pow-wows and theatrical
performances depicting historical accounts, etc.
Although the cultural benefits of the DPNHA are evident, its economic
benefits have not been examined and remain unclear. This study intends to fill
this gap by investigating the economic impacts of the DPNHA. Previous studies
show that recreation and tourism activities arising from designated NHAs have
significant impacts on regional economies. For instance, a number of economic
impact studies have been done for Michigan’s Automobile National Heritage
Area (Vander Stoep et al. 2004), Cane River National Heritage Area in Louisiana (Stynes and Sun 2004a), and Essex National Heritage Area in Massachusetts
(Stynes and Sun 2004b).
METHODS
Economic impacts were measured as the changes in sales, tax, and jobs in
the region resulting from spending by non-resident visitors, the federal government, and other parties. The economic estimates were produced using MGM1
as originally developed by Ken Hornback for USNPS (USNPS 1990). MGM1
generates quick and inexpensive estimates of the economic benefits of recreation
visitor spending on local economies (Stynes 1997).
Note that previous research also uses money generation model version 2
(MGM2) developed by Stynes and Propst (2008). It is an update of MGM1.
Based on survey data, MGM2 provides more details on visitor spending categories. However, it is more costly and time-consuming (Stynes 1997).
The MGM1 we use in our study provides the following (USNPS 1990):
1) visitor spending effects: the economic benefits to the local area resulting
from expenditures by visitors who live outside the local area (i.e., non-local or
non-resident tourists);
2) Federal Government spending effects: the economic benefits to the local
area resulting from park-related Federal Government expenditure (for example,
National Park Service expenditures for park supplies, services, construction
projects, etc.); and
3) other spending effects: the economic benefits to the local area resulting
from park-related expenditures by other non-local parties (for example, State expenditures for park access road; or capital expenditures to build a new marina).
Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
281
To apply the MGM1, three types of economic benefits are considered (USNPS 1990):
1) sales benefits: consist of income to local area businesses or individuals
for goods and services that these businesses or individuals provide as a result of
expenditures by non-local visitors, Federal Government expenditures, and parkrelated expenditures by other non-local parties;
2) tax benefits: consist of local area sales tax and income tax revenues that result from expenditures by non-local visitors, Federal Government expenditures,
and park-related expenditures by other non-local parties; and
3) job benefits: consist of jobs that are created in the local area as a result of
expenditures by non-local visitors, Federal Government expenditures, and parkrelated expenditures by other non-local parties.
RESULTS
Our estimation results depend on our assumptions of the parameters in
the model. We first present the base case in which we use the parameters that
are commonly used in the literature (USNPS 1990). We then use Cases 1 to 5
to discuss the results when we allow the parameters to change within plausible
ranges.
Base Case
Visitor Spending Effects
To estimate the potential increase in sales induced by the DPNHA designation, we first use a deterministic trend model to project the visitor spending
without the designation based on the historical data from Madden (2006), then
we use the multiple 15% to estimate the induced sales. The use of the 15% multiple is based on evidence from existing National Heritage Areas (NHAs) such as
Yuma Crossing NHA in Arizona and the Quinebaug & Shetucket Rivers NHA
in Connecticut which suggest that the NHA designation can generally increase
visitor revenues by about 15% per year (Dakota Prairie Heritage Area 2008).
Specifically, we first estimate the following deterministic trend model with annual data from 1998 to 2005,
Spendingt = a + b × t + et
where Spendingt is the visitor spending in year t, a is the slope, b is the slope coefficient, et is the random disturbance term, and t = 1998, 1999, …, 2005. The
historical data of visitor spending for the relevant three counties as well as the
estimated trend line over 1998 to 2005 are shown in Figure 1. R2 is nearly 0.70,
which suggests that our model is reliable enough for forecasting purposes.
Based on the trend model, we project the visitor spending without the designation for years from 2010 to 2019. That is,
the projected visitor
spending in
^
^
year τ without the designation is equal to a^ + b x τ, where a^ and b are the Ordinary
Least Squares (OLS) estimates of a and b, and τ=2010, 2011,…, 2019. Then we
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Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
Visitor Spending
25,000,000
20,000,000
15,000,000
10,000,000
5,000,000
0
1998
1999
2000
2001
2002
2003
2004
2005
2
Year
R = 0.6906
Figure 1. Visitor Spending, 1998-2005.
multiply it by 0.15 to compute the direct increase in sales induced by the designation. In other
words, the direct increase in sales induced by the designation is
^
equal to a^ + b x τ. Next we use a multiplier of two to compute the total increase
in sales. Two is the average value for the multiplier used by many researchers
(USNPS
1990). Therefore, the total increase in sales is equal to 2(1 + 0.15)
^
(a^ + b x τ) After that, we compute the increases in sales tax, income tax, and the
total tax by using the sales tax rate of 4% (Madden 2006) and the income tax
rate of 0%. Finally, we estimate the increase in jobs by assuming that every one
million dollars can create 30 jobs, which is commonly used in literature (USNPS
1990).
Table 1. Visitor Spending Benefits, 2010-2019.
Year
Visitor
Spending
without the
Designation
Direct
Increase
in Sales
Total
Increase
in Sales
Increase
in Sales
Tax
Increase
in Income
Tax
Total
Increase
in Tax
Increase
in Jobs
2010
20,104,538
3,015,681
6,031,361
241,254
0
241,254
181
2011
20,898,315
3,134,747
6,269,494
250,780
0
250,780
188
2012
21,692,092
3,253,814
6,507,627
260,305
0
260,305
195
2013
22,485,869
3,372,880
6,745,761
269,830
0
269,830
202
2014
23,279,646
3,491,947
6,983,894
279,356
0
279,356
210
2015
24,073,423
3,611,013
7,222,027
288,881
0
288,881
217
2016
24,867,199
3,730,080
7,460,160
298,406
0
298,406
224
2017
25,660,976
3,849,146
7,698,293
307,932
0
307,932
231
2018
26,454,753
3,968,213
7,936,426
317,457
0
317,457
238
2019
27,248,530
4,087,280
8,174,559
326,982
0
326,982
245
The results are shown in Table 1. The DPNHA is projected to increase the
sales in the three counties by $6,031,361 in 2010 and $8,174,559 in 2019. It is
Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
283
also projected to increase the tax by $241,254 in 2010 and $326,982 in 2019.
It would also create 181 new jobs in 2010 and 245 in 2019.
Federal Government Spending Effects
We assume the federal government would invest $1 million per year from
2010 to 2019. Using the same parameters as in the last step, we project the increases in sales, tax, and jobs induced by the spending. The results are reported
in Table 2. The DPNHA is projected to increase the sales in the three counties
by $2 millions every year from 2010 to 2019. It is also projected to increase the
tax by $80,000 per year from 2010 to 2019, and create 60 new jobs.
Table 2. Federal Government Spending Effects, 2010 – 2019.
Year
Direct
Total
Increase
Total
Increase in Increase in Increase in in Income Increase in Increase in
Sales
Sales
Sales Tax
Tax
Jobs
Tax
2010
1,000,000
2,000,000
80,000
0
80,000
60
2011
1,000,000
2,000,000
80,000
0
80,000
60
2012
1,000,000
2,000,000
80,000
0
80,000
60
2013
1,000,000
2,000,000
80,000
0
80,000
60
2014
1,000,000
2,000,000
80,000
0
80,000
60
2015
1,000,000
2,000,000
80,000
0
80,000
60
2016
1,000,000
2,000,000
80,000
0
80,000
60
2017
1,000,000
2,000,000
80,000
0
80,000
60
2018
1,000,000
2,000,000
80,000
0
80,000
60
2019
1,000,000
2,000,000
80,000
0
80,000
60
Other Spending Effects
We assume that the state government and other parties will not increase their
spending for the DPNHA from 2010 to 2019. Using the same parameters, we
can estimate the direct increase in sales, total increase in sales, increase in sales
tax, increase in income tax, total increase in tax, and increase in jobs in each year
from 2010 to 2019. They are all equal to zero.
Combined Effects
Combined visitor spending effects, federal government spending effects, and
other spending effects are shown in Table 3. The DPNHA is projected to increase
the sales in the three counties by $8.7 million in 2010 and about $11 million in
2019. It is also projected to increase the tax by $349,830 in 2010 and $435,558
in 2019. It would also create 262 new jobs in 2010 and 327 in 2019.
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Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
Table 3. Combined Effects of Visitor and Federal Government Spending, 2010 – 2019.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
8,745,761
349,830
0
349,830
262
2011
8,983,894
359,356
0
359,356
270
2012
9,222,027
368,881
0
368,881
277
2013
9,460,160
378,406
0
378,406
284
2014
9,698,293
387,932
0
387,932
291
2015
9,936,426
397,457
0
397,457
298
2016
10,174,559
406,982
0
406,982
305
2017
10,412,692
416,508
0
416,508
312
2018
10,650,825
426,033
0
426,033
320
2019
10,888,958
435,558
0
435,558
327
Case 1
In the base case, we assume that visitor spending will increase by 15% per
year. Although it is observed in some NHAs, there is no guarantee that this
would also be precise for the proposed DPNHA. We therefore considered two
alternative values: 10% and 20%. The results are presented in Tables 4 and 5.
Table 4. Combined Effects of Visitor and Federal Government Spending: Visitor Spending Growth
= 10%.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
6,497,174
259,887
0
259,887
195
2011
6,655,929
266,237
0
266,237
200
2012
6,814,685
272,587
0
272,587
204
2013
6,973,440
278,938
0
278,938
209
2014
7,132,195
285,288
0
285,288
214
2015
7,290,951
291,638
0
291,638
219
2016
7,449,706
297,988
0
297,988
223
2017
7,608,461
304,338
0
304,338
228
2018
7,767,217
310,689
0
310,689
233
2019
7,925,972
317,039
0
317,039
238
Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
285
Table 5. Combined Effects of Visitor and Federal Government Spending: Visitor Spending Growth
= 20%.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
10,994,347
439,774
0
439,774
330
2011
11,311,858
452,474
0
452,474
339
2012
11,629,369
465,175
0
465,175
349
2013
11,946,880
477,875
0
477,875
358
2014
12,264,391
490,576
0
490,576
368
2015
12,581,901
503,276
0
503,276
377
2016
12,899,412
515,976
0
515,976
387
2017
13,216,923
528,677
0
528,677
397
2018
13,534,434
541,377
0
541,377
406
2019
13,851,945
554,078
0
554,078
416
With 10% annual visitor spending growth, the DPNHA is projected to increase sales in the three counties by about $6.5 million in 2010 and $7.9 million
in 2019. It is projected to increase the tax by $259,887 in 2010 and $317,039
in 2019. It would create 195 new jobs in 2010 and 238 in 2019. With 20% annual visitor spending growth, the DPNHA is projected to increase sales in the
three counties by about $11.0 million in 2010 and $13.9 million in 2019. It
is projected to increase the tax by $439,774 in 2010 and $554,078 in 2019. It
would create 330 new jobs in 2010 and 416 in 2019.
Case 2
In the base case, we assume that the spending multiplier is two. Although
it is commonly used by researchers, there is also no guarantee that this would
be appropriate for the proposed DPNHA. We therefore consider two alternative
values for this multiplier: 1.2 and 2.8.
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Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
Table 6. Combined Effects of Visitor and Federal Government Spending: Spending Multiplier =
1.2.
Year
Total
ncrease in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
5,247,456
209,898
0
209,898
157
2011
5,390,336
215,613
0
215,613
162
2012
5,533,216
221,329
0
221,329
166
2013
5,676,096
227,044
0
227,044
170
2014
5,818,976
232,759
0
232,759
175
2015
5,961,856
238,474
0
238,474
179
2016
6,104,735
244,189
0
244,189
183
2017
6,247,615
249,905
0
249,905
187
2018
6,390,495
255,620
0
255,620
192
2019
6,533,375
261,335
0
261,335
196
Table 7. Combined Effects of Visitor and Federal Government Spending: Spending Multiplier =
2.8.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
12,244,065
489,763
0
489,763
367
2011
12,577,451
503,098
0
503,098
377
2012
12,910,837
516,433
0
516,433
387
2013
13,244,224
529,769
0
529,769
397
2014
13,577,610
543,104
0
543,104
407
2015
13,910,996
556,440
0
556,440
417
2016
14,244,383
569,775
0
569,775
427
2017
14,577,769
583,111
0
583,111
437
2018
14,911,155
596,446
0
596,446
447
2019
15,244,542
609,782
0
609,782
457
The results are presented in Tables 6 and 7. When the spending multiplier
is 1.2, the DPNHA is projected to increase the sales in the three counties by
about $5.2 million in 2010 and $6.5 million in 2019. It is projected to increase
the tax by $209,898 in 2010 and $261,335 in 2019. It would create 157 new
jobs in 2010 and 196 in 2019. When the spending multiplier increases to 2.8,
the DPNHA is projected to increase sales in the three counties by about $12.2
million in 2010 and $13.6 million in 2019. It is projected to increase the tax by
Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
287
$489,763 in 2010 and $609,782 in 2019. It would create 367 new jobs in 2010
and 457 in 2019.
Case 3
In the base case, we assume that one million dollars can create 30 jobs. In
Case 3, we consider two alternative values for this parameter: 20 and 40. The
results are presented in Tables 8 and 9.
Table 8. Combined Effects of Visitor and Federal Government Spending: One Million Dollars
Create 20 Jobs.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
8,745,761
349,830
0
349,830
175
2011
8,983,894
359,356
0
359,356
180
2012
9,222,027
368,881
0
368,881
184
2013
9,460,160
378,406
0
378,406
189
2014
9,698,293
387,932
0
387,932
194
2015
9,936,426
397,457
0
397,457
199
2016
10,174,559
406,982
0
406,982
203
2017
10,412,692
416,508
0
416,508
208
2018
10,650,825
426,033
0
426,033
213
2019
10,888,958
435,558
0
435,558
218
Table 9. Combined Effects of Visitor and Federal Government Spending: One Million Dollars
Create 40 Jobs.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
8,745,761
349,830
0
349,830
350
2011
8,983,894
359,356
0
359,356
359
2012
9,222,027
368,881
0
368,881
369
2013
9,460,160
378,406
0
378,406
378
2014
9,698,293
387,932
0
387,932
388
2015
9,936,426
397,457
0
397,457
397
2016
10,174,559
406,982
0
406,982
407
2017
10,412,692
416,508
0
416,508
417
2018
10,650,825
426,033
0
426,033
426
2019
10,888,958
435,558
0
435,558
436
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Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
If one million dollars create 20 jobs, the DPNHA would create only 175
new jobs in 2010 and 218 in 2019; if one million dollars create 40 jobs, the
DPNHA would create 350 new jobs in 2010 and 436 in 2019. Increases in sales
and increases in tax in 2010-2019 shown in Table 8 and 9 are the same as the
results in the base case.
In Cases 1 to 3, only one parameter is allowed to deviate from its base-case
value. To gain more insights, we next examine the economic impacts of the
DPNHA when all the parameters can deviate from their base-case values. To
save space, we report only the results with the most conservative parameters (the
worst case) and the least conservative parameters (the best case).
Case 4: the Worst Case
In the worst case, as shown in Table 10, the DPNHA still could increase sales
in the three counties by about $4.0 million in 2010 and $4.8 million in 2019.
It is projected to increase the tax by $155, 932 in 2010 and $190, 223 in 2019.
It would create 78 new jobs in 2010 and 95 in 2019.
Table 10. Combined Effects of Visitor and Federal Government Spending: Visitor Spending Growth
= 10%, Spending Multiplier = 1.2, and One Million Dollars Create 20 Jobs.
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
3,898,304
155,932
0
155,932
78
2011
3,993,557
159,742
0
159,742
80
2012
4,088,811
163,552
0
163,552
82
2013
4,184,064
167,363
0
167,363
84
2014
4,279,317
171,173
0
171,173
86
2015
4,374,570
174,983
0
174,983
87
2016
4,469,824
178,793
0
178,793
89
2017
4,565,077
182,603
0
182,603
91
2018
4,660,330
186,413
0
186,413
93
2019
4,755,583
190,223
0
190,223
95
Case 5: the Best Case
In the best case, as shown in Table 11, the DPNHA would increase sales in
the three counties by about $15.9 million in 2010 and $19.4 million in 2019.
It is projected to increase the tax by $615,683 in 2010 and $775,709in 2019. It
would create 616 new jobs in 2010 and 776 in 2019!
Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
289
Table 11. Combined Effects of Visitor and Federal Government Spending: Visitor Spending Growth
= 20%, Spending Multiplier = 2.8, and One Million Dollars Create 40 Jobs
Year
Total
Increase in
Sales
Increase in
Sales Tax
Increase in
Income Tax
Total
Increase in
Tax
Increase in
Jobs
2010
15,392,086
615,683
0
615,683
616
2011
15,836,601
633,464
0
633,464
633
2012
16,281,117
651,245
0
651,245
651
2013
16,725,632
669,025
0
669,025
669
2014
17,170,147
686,806
0
686,806
687
2015
17,614,662
704,586
0
704,586
705
2016
18,059,177
722,367
0
722,367
722
2017
18,503,692
740,148
0
740,148
740
2018
18,948,207
757,928
0
757,928
758
2019
19,392,722
775,709
0
775,709
776
DISCUSSION
As a simple money generation model, the MGM1 developed by the USNPS
(1990) captures the essential elements of an economic impact analysis. With
sound judgment in choosing the parameters, the model can yield reasonable ballpark estimates of economic impacts at minimum cost. This approach, however,
provides little details on spending categories or which sectors of the economy
benefit from either direct or indirect and induced effects. The aggregate nature
of the approach also makes it difficult to adjust recommended spending rates or
multipliers to different applications (Stynes 1997). Nevertheless, it is emphasized
that the MGM1 is intended to provide a fast and virtually zero cost estimate of
the economic consequences of a park on the economy of the surrounding local
area.
Based on MGM1, visitor spending effects, Federal Government spending
effects, and other spending effects were estimated. Within each type of effects,
three categories of economic benefits were considered: sales benefits, tax benefits,
and job benefits. The results from the base case showed that the DPNHA was
projected to increase the sales in the three counties by $8.7 million in 2010 and
about $11 million in 2019. It was also projected to increase the tax by $349,830
in 2010 and $435,558 in 2019. It would create 262 new jobs in 2010 and 327
in 2019. Although a number of assumptions were made about taxable income
ratio, indirect and induced sales multiplier, and multiplier for jobs created per
million dollars of total sales in order to simplify the economic benefit calculations in the base case, the robustness study in Cases 1 to 5 suggested that the
DPNHA was economically beneficial for the region within the plausible ranges
of the parameters.
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Proceedings of the South Dakota Academy of Science, Vol. 87 (2008)
We note that the money generation model is driven by visitor and park
expenditure data; it does not consider economic benefits such as enhanced real
estate values, improved recreational and cultural opportunities for local residents,
improved community services, etc., that derive from the park. We intend to incorporate such analysis in future research.
LITERATURE CITED
Dakota Prairie Heritage Area. 2008. Frequently Asked Questions. http://dakotaprairienha.com/index_files/Page665.htm retrieved on July 15, 2008.
Madden, M. K. 2006. Economic and Fiscal Impacts Associated with the Vacation Travel Industry in South Dakota: November 2004 through October
2005. The South Dakota Office of Tourism. 23 pp.
Stynes, D. 1997. Economic impacts of tourism. Urbana, IL: University of Illinois, Cooperative Extension Service bulletin. 19 pp.
Stynes, D., and D. Propst. 2008. Money Generation Model—Version 2. http://
web4.canr.msu.edu/mgm2/ retrieved on July 15, 2008.
Stynes, D., and Y. Sun. 2004a. Cane River National Heritage Area: Visitor Characteristics and Economic Impacts. Department of Community, Agriculture,
Recreation and Resource Studies, Michigan State University, East Lansing,
MI. http://web4.canr.msu.edu/mgm2/ retrieved on August 1, 2004.
Stynes, D., and Y. Sun. 2004b. Essex National Heritage Area; Visitor Characteristics and Economic Impacts. Department of Community, Agriculture,
Recreation and Resource Studies, Michigan State University, East Lansing,
MI. http://web4.canr.msu.edu/mgm2/ retrieved on August 1, 2004.
USNPS (United States National Park Service). 1990. The Money Generation
Model. Denver: Office of Social Science, Socio-Economic Studies Division.
25pp.
USNPS (United States National Park Service). 2008. What is a National Heritage Area? http://www.nps.gov/history/heritageareas/FAQ/INDEX.HTM
retrieved on June 5, 2008.
Vander Stoep, G. A., D. J. Stynes and Y. Sun. 2004. Visitor Awareness and
Economic Impacts of Motor Cities Hub Sites: Providing a Baseline for
Michigan’s Automobile National Heritage Area. Department of Community, Agriculture, Recreation and Resource Studies, Michigan State University,
East Lansing, MI. http://web4.canr.msu.edu/mgm2/ retrieved on August 1,
2004.