Kiowa, Rita Blanca, Black Kettle, and 

McClellan Creek National Grasslands 

Plan Revision 

Economic Resource Report 

Prepared by: 

Joshua Wilson 

Economist 

USDA Forest Service, TEAMS Enterprise Unit 

For: 

Cibola National Forest and National Grasslands 

October 19, 2010
The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and 

activities on the basis of race, color, national origin, age, disability, and where applicable, sex, 

marital status, familial status, parental status, religion, sexual orientation, genetic information, 

political beliefs, reprisal, or because all or part of an individual's income is derived from any public 

assistance program. (Not all prohibited bases apply to all programs.) Persons with disabilities 

who require alternative means for communication of program information (Braille, large print, 

audiotape, etc.) should contact USDA's TARGET Center at (202) 720-2600 (voice and TDD). To 

file a complaint of discrimination, write to USDA, Director, Office of Civil Rights, 1400 

Independence Avenue, S.W., Washington, D.C. 20250-9410, or call (800) 795-3272 (voice) or 

(202) 720-6382 (TDD). USDA is an equal opportunity provider and employer. 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

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Table of Contents 

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

Affected Environment ..................................................................................................................... 1

Population and Demographics .................................................................................................... 2

Employment and Income ............................................................................................................ 5

Environmental Justice ..................................................................................................................... 7

Environmental Consequences ......................................................................................................... 9

Methodology ............................................................................................................................... 9

Incomplete and Insufficient Information .................................................................................... 9

Alternative A: No Action .......................................................................................................... 10

Direct and Indirect Effects ..................................................................................................... 10

Cumulative Effects ................................................................................................................ 13

Alternative B: Preferred Alternative ......................................................................................... 13

Direct and Indirect Effects ..................................................................................................... 13

Cumulative Effects ................................................................................................................ 17

Alternative C: Recommendation for Canadian River IRA Wilderness Designation ................ 17

Direct and Indirect Effects ..................................................................................................... 17

Cumulative Effects ................................................................................................................ 18

Monitoring and Mitigation ............................................................................................................ 19

Conclusion ..................................................................................................................................... 19

References ..................................................................................................................................... 21

Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

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Introduction 

The Kiowa, Rita Blanca, Black Kettle, and McClellan Creek National Grasslands (Grasslands) 

are part of the Cibola National Forest system. Although managed as a separate entity, the 

Grasslands must undergo a planning effort similar to that of the National Forest. Currently the 

2000 National Forest System Land and Resource Management Planning Rule (2000 rule) guides 

the revision effort for the Grasslands. The Forest Service may follow the provisions of the 1982 

National Forest System Land and Resource Management Planning Rule (1982 rule) through the 

2000 rule transition language (36 CFR 219.35(b)). The Agency’s expectation, based upon its 

experience with the 2000 rule, is that national forests and grasslands will use the 1982 rule 

provisions, as permitted by the transition provisions of the 2000 rule, to revise and amend 

existing plans until a new planning rule is issued. This report provides the economic analysis in 

partial fulfillment of the Environmental Impact Statement (EIS) component of the 1982 rule. 

This report includes two main sections: Affected Environment and Environmental Consequences. 

The Affected Environment section consists of a descriptive analysis of the economic environment 

under the existing conditions; i.e. it illustrates the current state of the economy through 

demographic and economic indicators. The Environmental Consequences section, on the other 

hand, estimates the impacts to the study area that would occur as a result of implementing 

alternatives to the existing plan. 

Affected Environment 

The Grasslands are located in northeastern New Mexico and the panhandles of Texas and 

Oklahoma. This region of the country is predominantly rural and has an economic base 

consisting largely of agricultural industries. Management of public lands in this area can have a 

long lasting impact on the economic conditions of nearby communities. The study area for this 

analysis is Harding, Mora and Union Counties in New Mexico, Roger Mills and Cimarron 

Counties in Oklahoma, and Dallam, Gray and Hemphill Counties in Texas. Colfax County, NM 

contains approximately 4 sections of rangeland on the Kiowa Grassland, however, this county 

was omitted from the study area because its population would skew demographics. The 

Grasslands land-base lies mostly in these counties along with the communities potentially 

impacted by their management. Table 1 reports the percent of each county under Grasslands 

management by district. Dallam County, TX has the largest percent of land-base under 

Grasslands management at 8 percent. Mora County, NM has the smallest percent of land-base at 

less than 0.5 percent. 

Table 1: Percent of County Under Grassland Management 

Forest Service Ranger 

District County, State 

 Percent of County within 

Grasslands 

Kiowa & Rita Blanca Harding County, NM 5%

Kiowa & Rita Blanca Union County, NM 2%

Kiowa & Rita Blanca Mora County, NM < 0.5%

Black Kettle Roger Mills County, OK 4%

Kiowa & Rita Blanca Cimarron County, OK 1%

Kiowa & Rita Blanca Dallam County, TX 8%

Black Kettle Gray County, TX < 0.2%

Black Kettle Hemphill County, TX < 0.1%
Economics Specialist Report 

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Source: UNM-BBER 2005, Accessed via USDA Forest Service 2008 

Defining the relationship between management of the Grasslands and the economic and social 

environments is twofold. First, individuals with different demographic and social backgrounds 

are likely to be affected differently. Second, social and economic well being may affect their taste 

and preference, for recreational opportunities. An important component of this analysis is to 

inform decision makers and the public of the social and economic conditions evident in the study 

area. Those conditions may affect the frequency and type of activities residents participate in, 

which in turn affect individual livelihoods. Recreational, subsistence and cultural activities 

taking place on the Grasslands play an important role in defining the social and economic 

dynamic of the study area. Visitors generate important economic stimulus for many businesses, 

which impact employment and income levels. 

The affected environment section is split into two parts: population and demographics, and 

employment and income. For more detailed information about the demographic variables 

describing the study area, readers are referred to the Socio-Economic Sustainability Report, 

(USDA Forest Service, 2008), which was prepared to provide comprehensive social and 

economic background information for the Grasslands planning area. This document can be found 

online at http://www.fs.fed.us/r3/cibola/plan-revision/national_grasslands/plandocs/ser_final.pdf 

Population and Demographics 

This section highlights population and demographic trends in the study area. Current population 

levels influence the use of natural resources; and forecasts of future population levels can indicate 

whether there may be the potential for increased pressures on Grassland resources. Age 

distributions provide insight into the proportion of individuals in the working age cohorts versus 

retirees and minors who typically have different use patterns and use services in different ways. 

Similarly, the racial composition of the population may affect cultural and heritage uses. 

Employment and income statistics describe the economic conditions of the study area, as well as 

aid in the identification of important sectors of the economy. Additionally household income 

could affect participation levels in outdoor recreation; the greater the income of local residents, 

the greater is their ability to participate in various recreational activities. 

Population is an important consideration in managing Forest and Grassland resources. In 

particular, population structure (size, composition, density, etc.) and population dynamics (how 

the structure changes over time) are “essential to describing the effects and consequences of 

forest management and planning on a social environment” (Seesholtz, et al., 2004). Population 

increases may lead to conflicts over land use, travel management, recreation activities and values. 

These are conflicts that Forest Service managers may have to contend with and attempt to balance 

when making management decisions. 

Table 2 shows the past, present and projected population trends for each county in the study area 

and the aggregated states. From 1980-2010, the population of Grassland counties declined 10 

percent while the combined state populations increased by 62 percent. This decline in the local 

population is due in part to limited economic opportunities and low income levels. This is a 

common trend among rural areas across the country, and can greatly increase the importance of 

the economic contribution of the Grasslands. The declining trend in population is expected to 

continue for all counties except Dallam and Mora. Growth in those counties is expected to be 

concentrated in urban areas outside the vicinity of the Grasslands (UNM-BBER 2005, accessed 

via USDA Forest Service 2008), available online at http://www.fs.fed.us/r3/cibola/planrevision/national_grasslands/backdocs/20050930_Socio-econ-Assessment_Report.pdf . 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

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Table 2: Population Trends for Grassland Counties and Aggregated States 

 1980 1990 2000 2010 2020 2030 

Harding 

County, NM 1,090 987 810 780 726 676 

Mora County, 

NM 4,205 4,264 5,205 6,205 7,137 7,826 

Union 

County, NM 4,725 4,124 4,174 4,365 4,507 4,619 

Cimarron 

County, OK 3,648 3,301 3,148 3,200 3,400 3,500 

Roger Mills 

County, OK 4,799 4,147 3,436 3,400 3,400 3,400 

Dallam 

County, TX 6,531 5,461 6,222 6,930 7,537 7,949 

Gray County, 

TX 26,386 23,967 22,744 22,434 22,365 21,859 

Hemphill 

County, TX 5,304 3,720 3,351 3,563 3,659 3,548 

Study Area 

Total 56,688 49,971 49,090 50,877 52,731 53,377 

NM, OK & 

TX 18,557,375 21,647,164 26,121,520 30,150,629 34,352,708 38,648,53

Source: US Census Bureau, Decennial Census 1980, 1990, and 2000. UNM-BBER 2005. Accessed via USDA Forest 

Service 2008. 

As indicated in Table 3 and Figure 1, the most dominant age group in the study area is 35 to 55 

years old. This is an older working-age group who are dependent on their employment status to 

support themselves and their families. The majority of counties have a median age of 39 years or 

above; Harding County has the oldest at 49 years. Dallam County has the youngest population 

with a median age of 31 years; this is due in part to its more urbanized nature relative to the rest 

of the study area. Gray County has the highest population among all the counties and is not far 

from the city of Amarillo, TX. According to the age distribution of study area residents reported 

in Figure 1, there is a low point in the 20 to 24 year old age group. This is common in rural areas 

that lack higher education and employment opportunities for young professionals. It is likely that 

people are leaving the area upon graduating from high school in search of better education and 

job opportunities. Without economic growth, it is likely that these individuals will begin 

livelihoods elsewhere due to the lack of opportunities locally. This will continue to drive the 

median age of the study area upward, and could lead to further isolation economically. 

Table 3: Median Age in Years by County 

Harding County, NM 49 

Mora County, NM 40 

Union County, NM 40 

Cimarron County, OK 39 

Roger Mills County, OK 42 

Dallam County, TX 31 

Gray County, TX 39 

Hemphill County, TX 39 

Source: US Census Bureau, Decennial Census 2000 
Economics Specialist Report 

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Figure 1: Age Distribution in the Study Area 

Source: US Census Bureau, Decennial Census 2000 

Table 4 reports the ethnic composition of the study area. According to census definitions, 

Hispanic or Latino may be of any race. As defined by the U.S. Census Bureau, race and Hispanic 

origin are two different concepts; thus, people of Hispanic origin may identify with any race 

(http://www.census.gov/population /www/socdemo/compraceho.html). Therefore, the 

percentages in Table 4 do not sum to 100 percent. The majority of the population in the study 

area is Caucasian; there is also a substantial proportion of the population that is of Hispanic 

Origin. Mora County is the most diverse with 58.9 percent of residents being Caucasian and 37 

percent identify themselves as some other race; 81.6 percent of residents are of Hispanic origin 

which is nearly double that of the county with next highest percentage (Harding County is 44.9 

percent Hispanic). Roger Mills County has the highest percentage of Caucasians at 91.8 percent 

and American Indians and Alaska Natives at 5.5 percent. Both the Hispanic and American Indian 

cultures have a strong presence in the study area. Residents of these descents have strong ties to 

the land and its natural resources, and experience important values from use of the Grasslands. 

Table 4: Ethnic Distribution of Total Population by County 

Caucasian

African 

American

Am. 

Ind. & 

Alaska 

Native 

Asian/ 

Pacific 

Islander 

Other 

Race 

2 or 

More 

Races 

Hispanic 

Origin 

(of any 

race) 

Harding 

County, NM 84.3% 0.4% 1.4% 0.0% 10.6% 3.3% 44.9% 

Mora County, 

NM 58.9% 0.1% 1.1% 0.1% 37.0% 2.8% 81.6% 

Union 

County, NM 80.4% 0.0% 1.0% 0.4% 16.0% 2.2% 35.1% 

Cimarron 

County, OK 85.8% 0.6% 1.0% 0.2% 9.9% 2.5% 15.4% 

Roger Mills 

County, OK 91.8% 0.3% 5.5% 0.1% 0.5% 1.9% 2.6% 

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

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Dallam 

County, TX 82.6% 1.6% 0.9% 0.2% 12.4% 2.2% 28.4% 

Gray County, 

TX 82.2% 5.8% 0.9% 0.4% 8.2% 2.4% 13.0% 

Hemphill 

County, TX 87.6% 1.6% 0.7% 0.3% 8.5% 1.3% 15.6% 

NM 66.8% 1.9% 9.5% 1.2% 17.0% 3.6% 42.1% 

OK 76.2% 7.6% 7.9% 1.5% 2.4% 4.5% 5.2% 

TX 71.0% 11.5% 0.6% 2.8% 11.7% 2.5% 32.0% 

United States 75.1% 12.3% 0.9% 3.7% 5.5% 2.4% 12.5% 

Source: US Census Bureau, Decennial Census 2000 

Employment and Income 

Employment and income statistics are important indicators of economic health. To assess the 

relative size of sectors in the local economy, data reported by the Minnesota IMPLAN Group 

(MIG) is utilized. IMPLAN stands for Impact Analysis for Planning. MIG reports annual 

economic data for all counties in the United States. The IMPLAN data utilized throughout this 

report is for the year 2008. MIG utilizes national, state and local data sources to report county 

level employment, and includes full-time, part-time, seasonal and self employment. Because 

IMPLAN employment data is reported simply as jobs, not full time equivalents (FTEs), one 

person with multiple jobs will show up more than once in the data. This prohibits the comparison 

to local population data provided by the US Census Bureau. 

IMPLAN employment data is reported by economic sectors, which are a set of local businesses 

by industry, grouped together according to similarities in the goods and services offered. 

Assessing employment and income by sector aids in the identification of industries important for 

economic sustainability. Table 5 lists the total jobs in the study area by sector. Agriculture 

supports the largest percentage of jobs in study area. Many of the activities on the Grasslands 

support jobs in that sector, making it a valuable source of economic stimulus. The second largest 

sector is the government, which include jobs on the Grasslands. Government jobs tend to be 

higher paying than jobs in other sectors of rural economies and are an important source of 

household income. 

Table 5: Number of Jobs and Percent of Total Jobs by Sector in the Study Area 

Agriculture 6,500 21.6% 

Mining 2,011 6.7% 

Utilities 143 0.5% 

Construction 1,784 5.9% 

Manufacturing 1,566 5.2% 

Wholesale Trade 1,115 3.7% 

Transportation & Warehousing 3,205 10.6% 

Retail Trade 1,120 3.7% 

Information 320 1.1% 

Finance & Insurance 830 2.8% 

Real Estate & Rental & Leasing 544 1.8% 

Prof, Scientific, & Tech Services 510 1.7% 

Mgmt of Companies 19 0.1% 

Admin, Waste Mgmt & Rem Serv 755 2.5% 

Educational Services 122 0.4% 
Economics Specialist Report 

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Health Care & Social Assistance 1,439 4.8% 

Arts, Entertainment, and Recreation 362 1.2% 

Accommodation & Food Services 1,411 4.7% 

Other Services 2,114 7.0% 

Government 4,261 14.1% 

Total 30,131 100.0% 

Source: IMPLAN 2008 

Another indicator of economic health is the level of unemployment. All counties in the study 

area, except for Mora County, have generally maintained an unemployment rate lower than their 

respective state average in recent years. Table 6 reports the annual unemployment rate for the 

counties and states from 2000 thru 2009. Mora County has the highest unemployment rate in the 

study area, much greater than that of its respective state. As jobs are created in a region, labor 

comes from two primary sources: local unemployment and in-migration of households. With the 

higher unemployment rates in Mora County, it is likely that any new demands for labor would be 

supplied from the local labor market; assuming that qualified individuals reside in the area. Thus, 

any additional jobs created by activities on the Grasslands would likely not affect household 

migration patterns, and may serve to reduce unemployment rates. One exception to this has been 

jobs in the mining sector. These jobs tend to be shorter term and filled by a transient workforce 

that does not take up residency in the area. This will be addressed in greater detail in the effects 

analysis below. 

Table 6: Unemployment Rates by Counties and States 

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 

Harding 

County, NM 4.3% 4.3% 3.9% 5.4% 5.0% 4.1% 4.2% 2.7% 2.8% 4.5% 

Mora County, 

NM 10.6% 9.8% 10.3% 10.9% 11.2% 11.3% 8.7% 7.4% 8.7% 12.3% 

Union County, 

NM 3.7% 3.5% 3.6% 3.8 3.6% 3.4% 2.8% 2.4% 2.7% 5.0% 

Cimarron 

County, OK 2.2% 2.8% 3.8% 3.8 3.1% 3.5% 3.4% 3.8% 3% 3.9% 

Roger Mills 

County, OK 2.5% 2.4% 3.3% 2.8 2.8% 2.8% 2.7% 2.7% 2.3% 4.6% 

Dallam County, 

TX 3.4% 3.1% 3.7% 4.1 3.8% 3.3% 3.4% 2.8% 3.1% 4.3% 

Gray County, 

TX 

5.1 4.4 6.1 6.1 5.2 4.2 3.9 3.4 3.6 8.2

Hemphill 

County, TX 

2.9 2.7 3.2 2.9 3.2 2.9 2.7 2.1 1.9 3.5

NM 5.0% 4.9% 5.5% 5.9 5.8% 5.2% 4.1% 3.5% 4.5% 7.2% 

OK 3.1% 3.7% 4.8% 5.6 5.0% 4.5% 4.1% 4.0% 3.7% 6.4% 

TX 4.4% 5.0% 6.4% 6.7 6.0% 5.4% 4.9% 4.4% 4.9% 7.6% 

Source: www.bls.gov

Income available to local residents directly impacts their ability to purchase goods and services. 

A total of 1.4 billion dollars of personal income was received by residents of the study area in 

2006. Income was generated from the following sources and proportions: payments for labor (62 

percent); transfer payments (21 percent); and dividends, interest and rent (17 percent). 

Dividends, interest and rent are forms of investment earnings, which along with transfer 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

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payments are considered non-labor forms of income. Transfer payments consist of a variety of 

non-labor income payments, including: retirement and disability, medical assistance, social 

security, unemployment benefits, welfare and veterans’ benefits. Earnings from dividends, 

interest and rent are sources of investment income generated through financial investments or 

other property income. Labor income is further broken down by wage and salary income, and 

farm and non-farm proprietor’s income. Proprietor’s income is earnings from self employment, 

and is reported separately from wages and salary. The majority of income for local residents is 

generated by wage and salary income (44 percent). However, a considerable amount of income in 

the study area is earned through non-labor sources. 

Table 7: Study Area Income, 2006 

Total Personal Income $1,400,214,000 

 Labor 62 

 Non-Labor 38 

 Dividends, Interest and Rent 17 

 Transfer Payments 21 

Source: EPS 2008 

Environmental Justice 

As stated in Executive Order 12898, it is required that all federal actions consider the potential of 

disproportionate effects on minority and low-income populations in the local region. The 

principals of Environmental Justice require agencies to address the equity and fairness 

implications associated with Federal land management actions. The Council on Environmental 

Quality (CEQ) (1997) provides the following definitions in order to provide guidance with the 

compliance of Environmental Justice requirements: 

• “Minority population: Minority populations should be identified where either: (a) the 

minority population of the affected area exceeds 50 percent or (b) the minority population 

percentage of the affected area is meaningfully greater than the minority population 

percentage in the general population or other appropriate unit of geographic analysis...” 

• “Low-income population: Low-income populations in an affected area should be 

identified with the annual statistical poverty thresholds from the Bureau of the Census' 

Current Population Reports, Series P-60 on Income and Poverty. In identifying lowincome populations, agencies may consider as a community either a group of individuals 

living in geographic proximity to one another, or a set of individuals (such as migrant 

workers or Native Americans), where either type of group experiences common 

conditions of environmental exposure or effect.” 

The general population that county data is compared to is that of the nation. Table 4 reports the 

ethnic distributions of the counties in the study area, their respective states, and the United States. 

All counties except for Roger Mills have a higher proportion of Hispanic residents than the 

United States; and Roger Mills County has the highest proportion of American Indian residents. 

Mora County has the lowest proportion of Caucasian residents at 58.9 percent. Due to the high 

proportion of Hispanic and American Indian residents in the study area, it has been determined 

that these ethnic groups meet the Environmental Justice requirements of a minority population 

meaningfully greater than the general population. Therefore decision makers on the Grasslands 
Economics Specialist Report 

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should pay careful attention to the potential impacts of management actions on those ethnic 

groups. 

Table 8 reports the number of individuals below the poverty level and poverty rates in 2000 and 

2008. Poverty rates in six of the eight counties decreased from 2000 to 2008; however poverty 

rates remain high in the study area. As of 2008, Mora County has the highest poverty rate at 23.0 

percent and Hemphill County had the lowest at 8.7 percent. Hemphill and Roger Mills are the 

only counties with 2008 poverty rates less than the national average. Such rates suggest that a 

substantial proportion of the existing population should be considered as a low income group. 

Therefore, decisions regarding future management actions on the Grasslands should carefully 

assess the effects on low income populations. 

Table 8: Poverty Status by County, 2000 and 2008 

2008 2000 

Number Percent Number Percent 

Harding 

County, NM 104 15.2 115 14.7 

Mora County, 

NM 1,154 23.0 1,250 24.2 

Union 

County, NM 602 16.0 677 17.0 

Cimarron 

County, OK 409 16.3 453 15.0 

Roger Mills 

County, OK 386 11.5 480 14.5 

Dallam 

County, TX 840 13.6 989 16.0 

Gray County, 

TX 3,018 14.7% 3,138 9.8% 

Hemphill 

County, TX 290 8.7% 313 15.3% 

NM 329,857 17.0% 309,103 17.3% 

OK 554,237 15.7% 467,081 13.8% 

TX 3,755,944 15.8% 3,041,115 14.6% 

United States 39,108,422 13.2% 31,581,086 11.3% 

Source: US Census Bureau, Small Area Income and Poverty Estimates 

In cases where the management decisions are expected to create jobs and income in the local 

economy, it is unlikely that there would be a disproportionate adverse effect on minority and low 

income populations. Individuals in those populations may benefit from any increase in jobs and 

income in the area. Alternatively, future management decisions that may negatively impact local 

employment and income conditions should carefully assess the distribution of effects across 

population demographics, paying careful attention to Hispanic, American Indian and low income 

populations. 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

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Environmental Consequences 

Methodology 

Principles of economic impact analysis are relied upon to estimate the effects of the Grasslands 

revised plan on the economic environment of the study area. “Economic impact analyses seek to 

determine short-term effects that Forest Service programs have on economic conditions in 

defined impact areas in which the planning area occurs” (FSM 1900). Economic impact analyses 

investigate the effects of the alternative development scenarios on employment and income. The 

relative size of the local communities plays an important role in the assessment of job and income 

impacts to the economy. Broader, more diverse, economies should be more resilient to changes 

in jobs and income than smaller, more rural, communities. For example, a loss of ten jobs in a 

large metropolitan area should have very little impact on the overall health of the economy. 

However, the same loss in jobs in a small rural community may severely affect local economic 

conditions. Thus, when assessing the magnitude of impacts to employment and income across 

alternatives, it is important to keep in mind the relative importance of those economic factors to 

the specified study area. 

Models of the local economy were built using IMPLAN Professional 3.0 software and 2008 data. 

For the purposes of this report, the local economy is defined the same as the study area. Changes 

in activity on the Grasslands may have several different consequences for the condition of the 

economic environment. Ultimately, a change in the activities would change the local economic 

stimulus. A change in economic stimulus to a region (e.g. increased recreational visits) would 

likely change the total level of jobs and income. Economic impact analyses are reserved for 

situations where a change is being made to the existing condition as is the case of the action 

alternatives. In the case of the No Action Alternative there would be no change to the existing 

Forest/Grasslands plan. Existing data for activities taking place under the current plan is used to 

estimate what the current economic contribution is to the local economy. Such a contribution 

analysis allows for the conditions under the No Action Alternative to be analyzed in detail and 

provides a better basis for comparison when analyzing the effects from the action alternatives. 

To conduct both the economic impact and contribution analyses, IMPLAN models are imported 

into the Forest Economic Analysis Spreadsheet Tool (FEAST), which is a Microsoft Excel-based 

workbook designed to describe the impacts to employment and income by resource program and 

major industry (fsweb.ftcol.wo.fs.fed.us/imi/economic_center/FEAST%20Economic%20 

Analysis%20Tool). IMPLAN and FEAST software account for the production cycles and interindustry purchasing habits of local firms, and can thus parcel out the levels of employment and 

income supported by activities on the Grasslands. This allows for an assessment of the overall 

importance of these lands to the local economy in terms of jobs and income supported. 

Incomplete and Insufficient Information 

For some resource areas it is difficult to predict how activity levels would change under the action 

alternatives and there is no data available to estimate the resulting effects. One such case is 

recreation. Insufficient information exists to accurately estimate changes in recreation use that 

would occur under implementation of the action alternatives analyzed in this report. Although 

certain trends in visitor use may be predicted from the guidelines set forth under each alternative, 

there is no methods and/or data available to estimate actual changes in visitation. Similar 

circumstances occur with grazing. Although allowable grazing can be addressed in the plan, 

uncontrollable factors may influence the actual grazing that may take place during future years. 
Economics Specialist Report 

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Existing data used for the analysis of the no action alternative may not represent healthy grazing 

activity under other ecosystem conditions. For example, rain plays an important role in permitted 

grazing from year to year. In drought years there is less grass that may be consumed by livestock, 

and consequently stocking levels may be decreased. Such uncertainty is difficult to control for at 

the planning stage. The effects analysis for action alternatives is limited by the lack of data for 

these types of circumstances. Therefore sensitivity analysis and qualitative analysis of potential 

economic effects are relied upon when analyzing action alternatives. Sensitivity analysis 

involves reporting the effects for a range of potential outcomes. High and low end values are 

reported, and the true effects are assumed to fall within that range. 

Alternative A: No Action 

Alternative A represents the 1985 Cibola National Forest Plan, as amended. It is the No Action 

alternative, meaning there would be no change from the current management direction offered by 

the current plan. 

Direct and Indirect Effects 

The Grasslands contribute to the livelihoods of local residents and stakeholders in a variety of 

ways. They contribute to jobs and income through employment opportunities with the USDA 

Forest Service, as well as employment and income associated with industry outputs dependent on 

National Forest System (NFS) lands. For example, a portion of output in the tourism and 

recreation, and agricultural industries is generated from the activities affected by Grasslands 

management. Oil and gas leases generate economic activity in the mining sector, which in turn 

supports jobs and income among local residents. These lands also support subsistence activities 

through hunting and fishing, firewood harvesting, and the gathering of other forest products. 

Such dependency on the Grasslands for economic sustainability and growth is largely a function 

of the local economic dynamic and total industrial outputs. Economic dependency in the study 

area is likely to vary across cities and towns, however, the data available does not allow for the 

estimate of contributions to such micro-economies. The Grasslands’ contributions to the local 

region are estimated as a whole, and certain economic dependency issues are addressed 

qualitatively. 

The study area for this analysis is predominantly rural and sparsely populated. Local businesses 

and firms depend heavily upon agricultural and natural resource based activities as a source of 

revenue. Therefore, management of the Grasslands plays an important role in the sustainability of 

the local economy. Table 1 reports the total jobs and labor income contributed to the local 

economy by resource area. For-recreation-only activity supported by non-local visitors is 

accounted for. Expenditures by non-locals represents new money to the economy, and are 

considered an export of goods and services. Recreation by local residents, on the other hand, 

does not introduce new money to the economy, and are therefore not considered to have an 

economic impact. In the case where locals would leave the study area for recreation if the 

Grasslands didn’t exist, then management of these lands would be influence the level of 

expenditures that remain local and would therefore impact the local economy. However, given 

the rural nature of the study area, it is assumed that locals would continue to recreate within the 

study area. 

Table 9 reports the annual economic contribution for each resource program. Contributions are 

estimated as the number of jobs and labor income supported from activities taking place on the 

Grasslands. The resource area with the largest economic contribution is minerals, supporting 52 

jobs and $5.204 million of labor income in the study area. Oil and gas are the most abundant 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

11

minerals commodities extracted from Grasslands; however all of that activity occurs on the Black 

Kettle. Ecosystems restoration and other Forest Service expenditures also have an important 

contribution to the local economy, supporting 23 and 21 jobs respectively. Agriculture is a way of 

life for many local residents, therefore grazing is an important resource. Currently, grazing 

permits on the Grasslands support an additional 32 jobs in the study area. Those 32 jobs are very 

important to local agricultural families who would like continued management for the grazing 

resource. 

Table 9: Economic Contribution by Resource Program 

Resource # of Jobs Labor Income ($1,000’s) 

Recreation: non-local only 4 $85 

Wildlife and Fish: non-local only 4 $83 

Grazing 32 $542 

Timber 0 $0 

Minerals 52 $5,204 

Ecosystem Restoration 23 $693 

Payments to States/Counties 17 $610 

Forest Service Expenditures 21 $0 

Total Grasslands Management 154 $7,217 

Source: IMPLAN 2008 and FEAST 2010 

Note: Contributions for each resource area do not constitute total employment or income within industry sectors that 

correspond to these resource areas (agriculture, mining, etc.). In fact, economic contributions for each resource area in 

Table 9 represent employment and income across multiple industry sectors. 

In aggregate, current Grasslands management supports 154 jobs and $7.217 million of labor 

income. In the third and sixth columns of Table 10 below (labeled Grasslands Contribution) jobs 

and income associated with Grassland management are distributed across industry sectors within 

the study area. The jobs and income for each industry is attributable to economic activity as a 

result of Grassland management and thus, is not a representation of total employment within the 

impact area for that industry. Total industry jobs and income within the study area are displayed 

in the second and fifth columns of Table 10 (labeled Study Area Total). Table 10 reports the total 

number of jobs, jobs supported by the Grasslands, and percent of total for each sector. The total 

jobs and labor income contributed only accounts for 0.51 percent and 0.60 percent of study area 

totals, respectively. However, that is valuable economic stimulus for those impacted. Agriculture 

is affected the most with 55 jobs, followed by mining with 29 jobs and government with 26 jobs. 

As measured proportionally, mining has the largest contribution by Grasslands management at 

1.44 percent of total employment and 2.06 percent of total labor income. 

Table 10: Economic Contribution by Sector 

Employment (# of Jobs) Labor Income ($1,000’s) 

 Study 

Area Total 

Grasslands 

Contribution 

% of 

Total 

Study 

Area Total 

Grasslands 

Contribution 

% of 

Total 

Agriculture 6,500 55 0.85% 85,976 $1,202 1.40% 

Mining 2,011 29 1.44% 211,251 $4,352 2.06% 

Utilities 143 0 0.01% 13,996 $50 0.36% 

Construction 1,784 4 0.22% 90,555 $272 0.30% 

Manufacturing 1,566 0 0.00% 134,206 $3 0.00% 

Wholesale Trade 1,115 2 0.19% 71,824 $148 0.21% 

Transportation & 

Warehousing 3,205 1 0.03% 80,945 $60 0.07% 

Retail Trade 1,120 8 0.72% 78,297 $201 0.26% 
Economics Specialist Report 

12

Information 320 1 0.32% 14,590 $26 0.18% 

Finance & Insurance 830 2 0.26% 43,885 $128 0.29% 

Real Estate & Rental & 

Leasing 544 1 0.20% 20,900 $53 0.25% 

Prof, Scientific, & Tech 

Services 510 2 0.40% 27,159 $112 0.41% 

Mgmt of Companies 19 0 0.00% 1,741 $10 0.58% 

Admin, Waste Mgmt & 

Rem Services 755 1 0.14% 23,292 $35 0.15% 

Educational Services 122 0 0.00% 1,862 $6 0.32% 

Health Care & Social 

Assistance 1,439 4 0.28% 48,295 $129 0.27% 

Arts, Entertainment, and 

Rec 362 1 0.28% 6,389 $20 0.31% 

Accommodation & Food 

Services 1,411 9 0.64% 21,425 $144 0.67% 

Other Services 2,114 4 0.19% 42,906 $66 0.15% 

Government 4,261 26 0.61% 182,048 $201 0.11% 

Total 

30,131 154 0.51%

1,201,54

3 $7,217 0.60%

Source: IMPLAN 2008 and FEAST 2010The information reported in Table 9 and the third and 

sixth columns of Table 10 represents the economic contribution under the current management 

plan. If the no action were to occur, it is assumed that these levels of jobs and income would 

continue to be supported. There would be no impact to the local economy, and therefore no direct 

or indirect effects can be measured. 

Calculating present net value (PNV) is also required as part of the planning process. However, 

the data required for a detailed financial efficiency analysis is unavailable. In order for the 

Grasslands to meet adaptive management objectives, the new plan will not prescribe specific 

management activities. This allows the flexibility to manage resources under ever-changing 

environmental conditions. A more detailed financial efficiency and economic impact analysis 

should be conducted during the NEPA stage for proposals of future management activities. 

The current resource programs managed by the grasslands generate revenue from sale of 

products, permits for various activities and leases for minerals. The programs generating revenue 

are recreation, range, minerals and non-recreation special uses. Grasslands personnel provided 

current data on revenue streams (Table 11). Under the no action it is assumed there would be no 

impact to these revenue streams, and they would continue throughout the next planning cycle. 

Since these plans are expected to be updated every 10 to 15 years, a 15 year planning cycle is 

used for the financial efficiency analysis. 

Table 11: Annual Revenues and Costs by Program 

Program Annual Revenue Annual Cost 

Recreation $18,000 $242,250 

Range $1,363,000 $233,524 

Minerals $40,404,000 $445,252 

Non-recreation Special Uses $58,000 $7,393 

The recreation, range, minerals and non-recreation special uses programs are funded under the 

general budget and externally funded activities such as volunteer and service agreements, and in-
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

13

kind sharing. There is much uncertainty about future budgets and no reliable data on future 

program costs. A three-year average for each resource program’s budget was used as an estimate 

of annual costs (Table 11). There are also a variety of ecosystems services projects are part of the 

management strategy for Grasslands resources. There is limited data regarding the costs for these 

types of projects, which include prescribed burning, thinning and weeds treatments. The financial 

efficiency analysis is limited to only the revenues received from management activities and the 

costs of annually funded ecosystems services projects. The costs included in this analysis are just 

a portion of the total operating budget. This greatly limits the informational capacity of this 

analysis; however, it provides some basis of comparison for future revenue streams back to the 

Grasslands. PNV is defined as the discounted sum of benefits minus the discounted sum of costs; 

however since not all costs are actually accounted for, this analysis should primarily be used to 

evaluate benefits. A Federally prescribed discount rate of 4% is used in this analysis (FSM 1900). 

Inflation is also a variable that can affect the NPV’s associated with each alternative. However, 

due to the uncertainty of future inflation, OMB Circular A-94 recommends the avoidance of 

making assumptions about the inflation rate whenever possible. Thus, for the purposes of this 

project, inflation will be left at zero. 

The PNV if Grasslands management were to continue under the No Action is $434,787,152. In 

this analysis costs are limited to only those for specific program areas and ecosystem services 

projects occurring on the Grasslands. Therefore this value provides a better relative measure of 

the discounted net revenue the Grasslands are expected to generate during the next planning cycle 

in 2010 dollars. As mentioned above, these programs are funded with a combination of the

general budget and external funding. Currently there is no information available regarding the 

level and distribution of these funds in future years. 

Cumulative Effects 

Given that there are no measurable direct and indirect effects that would occur under the No 

Action alternative, there would also be no measurable cumulative effects. 

Alternative B: Preferred Alternative 

Alternative B would emphasize management of vegetation and habitat to maintain or move closer 

to reference within the historical range of variability (HRV). This would be achieved through 

more intensive invasive species management, including removal of trees from historically 

grassland vegetation communities and a more adaptive management approach to grazing. The 

recreation program would emphasize maintain and rehabilitating existing infrastructure. Existing 

recreational opportunities would continue, but new development would be limited.

Direct and Indirect Effects 

The primary resources areas on the Grasslands are minerals, grazing and recreation. Ecosystems 

restoration and general expenditures by the agency are also important contributors to the local 

economy. It is difficult to forecast how implementation of this alternative would impact each 

resource area on any given year. Recreation use is largely dependent on population growth and 

tastes and preferences of visitors. Grazing is influenced by weather conditions during the season 

and minerals extraction is dependent on energy demand and global prices. Ecosystems 

restoration and agency expenditures are largely a function of budget and external funding. All of 

these factors introduce substantial uncertainty to models estimating the effects of this alternative. 

The baseline conditions reported in the contribution analysis for the no action alternative are 

assumed to accurately represent the jobs and income supported by each resource area unless a 
Economics Specialist Report 

14

change to the existing conditions would occur as a direct result of implementation of Alternative 

B. In cases where estimates of those changes can be made, they are introduced to the model and 

effects are reported. In cases where such estimates can’t be made, this analysis relies upon 

sensitivity analysis and a qualitative assessment to describe the effects on this alternative. 

Sensitivity analysis involves estimating the impacts of a range of activity levels for a resource, 

and reporting that range as possible effects. A qualitative assessment of the likelihood of activity 

levels falling with that range is then used as a descriptive tool to address the possibility of those 

effects being realized in the local economy. 

Alternative B would recommend guidelines for energy development, but does not introduce any 

management changes that would result in an increase or decrease in minerals production. Oil and 

gas extraction will continue to be a common activity on the Grasslands. Any change in extraction 

levels is assumed to be a result of market demands and not the plan itself. Therefore it is assumed 

that the minerals jobs and labor income reported in Table 9 would continue to be supported. 

During the next planning cycle it expected that demand for the development of wind energy on 

the Grasslands is likely to increase. Private ground in the area is quickly being developed and 

once it reaches a point of diminishing marginal returns it is likely that the industry will focus its 

efforts on public lands. However, proposed development for any mineral or energy source must 

still undergo a review process. That process would not change under this alternative. Effects 

analysis should be completed once such site specific proposals are presented to the agency. 

According to the current plan grazing is currently at the maximum permitted use; this would not 

change under this alternative. Grazing levels would not go beyond current use; however, it could 

decrease due to weather conditions or other unforeseen climatic circumstances. For example, 

during drought years when forage is limited, authorized stocking levels may be decreased to 

protect ecosystem diversity on the Grasslands. The jobs and income reported for grazing in Table 

9 above would continue as long as grazing continues at current levels. If permitted use decreases 

during any given year, the resulting effects would be a negative impact to local economy, e.g. loss 

of jobs and income. Table 12 reports current condition as well as the impact that would occur if 

grazing were to decrease by 25 percent and 50 percent. In the case of permitted use decreasing 

by 25 percent, the net impact would be a loss of 8 jobs and $136,000 of labor income in the study 

area. Such decreases are only hypothetical at this point because the plan under this alternative 

would not restrict the grazing resource any more than the current plan. However, uncertain 

factors, such as weather, could lead to decreased grazing for resource protection purposes. 

Table 12: Economic Impact if Grazing Decreased by 25 Percent and 50 Percent 

Current 

Condition 

25% 

Decrease 

Net Change 

from Current 

50% 

Decrease 

Net Change 

from Current 

Total Jobs 32 24 8 16 16

Labor Income 

($1,000's) $542 $407 $136 $271 $271

Total Output 

($1,000's) $6,087 $4,565 $1,522 $3,044 $3,044

Source: IMPLAN 2008 and FEAST 2010 

Recreation levels, on the other hand, are expected to increase during the next planning cycle. The 

net increase is unknown at this time, but is expected to largely be a function of population growth 

and tastes and preferences of Grasslands visitors. In a projections of demand report conducted by 

Wilson and Eichman (2009) it is predicted that the demand for outdoor recreation should rise at a 

rate of growth similar to that of the population. As reported in Table 2, the population of the 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

15

study area is forecasted to grow by 7 percent by 2020 and 12 percent by 2030. Table 13 reports 

the impact if recreation were to increase by those amounts in the current economic environment. 

Overall the effects would be negligible at the rates reported in Table 13. The true growth rate for 

recreation use is likely to vary somewhat, but the resulting impacts are not likely to dramatically 

affect the economic environment. 

Table 13: Economic Impact if Recreation Use Increased by 25 Percent and 50 Percent (Including 

Wildlife Recreation) 

Current 

Condition 

7% 

Increase 

Net Change 

from Current 

12% 

Increase 

Net Change 

from Current 

Total Jobs 8 9 1 10 2 

Labor Income 

($1,000's) 168 180 12 188 20 

Total Output 

($1,000's) 591 632 41 662 71 

Source: IMPLAN 2008 and FEAST 2010 

Ecosystems restoration is likely to be affected the most under this alternative because of its 

emphasis on vegetation management. Additional restoration work would be conducted compared 

to the No Action Alternative, resulting in a positive economic impact. There is some uncertainty 

as to the actual level of restoration work that would occur; therefore both low and high scenarios 

are reported. Additional restoration activities would include weed spraying, prescribed burning 

and invasive tree removal. Tree removal could be conducted using two different techniques, 

thinning or mastication. The preferred technique has not been identified so effects are reported 

for both. A more detailed analysis of effects should be conducted when site specific management 

activities are proposed. At the planning stage it is only possible to report a range of impacts 

because actual prescriptions have not yet been made. Table 14 reports the high, low and net 

change of effects to local economy when thinning is used as the mechanism for tree removal. In 

the low scenario, an additional 2 jobs and $66,000 of labor income would be supported in the 

local economy; the impact under the high scenario would be 4 jobs and $131,000 in labor income. 

If mastication were to be used as the method for tree removal, the low and high effects on the 

local economy would be 1 job and $31,000 in labor income, and 3 jobs and $62,000 in labor 

income, respectively (Table 15). In either case there would be positive economic impact in the 

form of jobs and income. Tables 14 and 15 also report the change in output associated with 

possible scenarios, which is the value of goods and services produced in the local economy. 

Table 14: Range of Economic Impact of Ecosystems Restoration with Thinning 

Current 

Condition Low 

Net Change 

from Current High 

Net Change 

from Current 

Total Jobs 23 25 2 27 4 

Labor Income 

($1,000's) 693 759 66 824 131 

Total Output 

($1,000's) 834 913 79 991 157 

Source: IMPLAN 2008 and FEAST 2010 

Table 15: Range of Economic Impact of Ecosystems Restoration with Mastication 

Current 

Condition Low 

Net Change 

from Current High 

Net Change 

from Current 

Total Jobs 23 24 1 26 3 
Economics Specialist Report 

16

Labor Income 

($1,000's) 693 724 31 755 62 

Total Output 

($1,000's) 834 867 33 900 66 

Source: IMPLAN 2008 and FEAST 2010 

Under this alternative, shelter belts could be removed if future analysis concludes that they are 

not needed for erosion control and it would improve native habitat. A detailed description of the 

effects associated with that type of project should be reported in that analysis. Removal of these 

shelter belts would involve eradicating trees through thinning or mastication. The annual rate at 

which such treatments would occur would not be dramatically different than those analyzed under 

Alternative B. Therefore the actual effects are estimated to fall within the ranges reported in 

Tables 14 and 15 above. It is likely that under this alternative the effects would fall more closely 

to the high end than the low end. Either scenario would represent a very minimal impact to the 

overall economy; however, the impact could be very important for those affected. In both 

scenarios the activity would result in a net increase in jobs, therefore it is likely that some local 

families will benefit from the increase in employment. 

It is also likely that agency expenditures will change from year to year during the next planning 

cycle, but that is a function of appropriated budget and is not directly influenced by the plan. Due 

to this uncertainty the effects resulting from this alternative may not be estimated. The jobs and 

income supported under the current budget are reported in the contribution analysis for the No 

Action. It is assumed that those jobs will continue to be supported during the next planning cycle 

barring any unforeseen circumstances with the budget. 

Overall, there are not any significant economic effects anticipated for this alternative. The 

possible effects reported in Tables 12 through 15 represent a very small proportion of economic 

activity in the study area. If Alternative B were to be implemented there would be no noticeable 

effects to the overall economy. Individual projects could impact certain user groups and 

stakeholders; however those effects cannot be estimated at this time. Adaptive management is a 

common theme among modern forest planning efforts; therefore some variability must be left in 

the plan so that managers can adapt to changing ecological conditions. Before any future projects 

are implemented under the plan a more detailed analysis of effects would be required. That 

analysis should highlight the effects to specific stakeholders. Planning is an evolving process, 

and the effects reported in this section represent a range that line officers may use when make 

decisions about which plan to implement. 

The PNV for this alternative was calculated using the same methods as described under the No 

Action. There is no data for the future revenues generated by resource program. However, this 

alternative does not prescribe any activities that would cause a change to those revenue streams. 

Any change in program revenues would occur as a result of supply and demand conditions, and 

tastes and preferences of stakeholders in the study area. This would occur regardless of the 

chosen alternative. Therefore the same revenue streams used for the No Action alternative are 

assumed to carry though under the action alternatives. Alternative B places a greater emphasis on 

vegetation management, which will increase restoration costs. This is reflected in a slightly lower 

PNV than the No Action Alternative. The PNV for this alternative is $433,740,633. Although 

this PNV is lower than that of the No Action, it does not account for non-financial benefits 

associated with the improved vegetative conditions. 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

17

Cumulative Effects 

Cumulative effects include the total change in economic conditions that would result from the 

specifications under this alternative in conjunction with the direct and indirect effects of other 

present and reasonably foreseeable activities being conducted in the study area. For example, any 

environmental change as a result of the proposed action would be in addition to other resource 

management activities occurring simultaneously in the region on both public and private lands. 

Based on a survey of local land use plans, there is not a list of projects that would contribute to 

the cumulative effects of this alternative. On the margin, other projects affecting natural 

resources are likely to have similar effects to those that would occur under this plan. Individually, 

such projects may not have much bearing on the local economy; however, cumulatively, they may 

substantially impact economic conditions. Mining is a good example; a project to develop one oil 

and gas well may not have much bearing on communities in the study area, however, all mining 

projects together are likely to have important economic implications. Currently there are no 

specific projects proposed under this alternative. This alternative sets the stage for future 

management decisions, but does not affect current activities occurring on the ground. Once 

actual activities are proposed, cumulative effects should be estimated for the resources affected. 

The direct and indirect effects specific to other projects that may occur in the study area are 

unknown. Individually, these projects would likely have a minimal impact on economic 

conditions; however, cumulatively they may substantially affect employment and income levels 

in the study area. The degree to which the economic environment would be impacted, as well as 

the distribution of effects, cannot be determined from the information available. 

Lands under other ownership may also undergo changes to resource conditions that would 

influence cumulative effects. Other public lands and property under private ownership offer 

additional opportunities for resource use. There may be other projects occurring on such lands 

that could impact social and economic conditions. The majority of projects would likely be small 

scale, and would not dramatically alter resource conditions individually. Direct and indirect 

effects from such projects would likely be minimal. As future land use decisions are made under 

this alternative, or any other alternative for that matter, managers should be mindful of 

cumulative effects and make a conscious effort to estimate those effects related to specific 

projects. 

Alternative C: Recommendation for Canadian River IRA 

Wilderness Designation 

Alternative C is similar to Alternative B except that a recommendation would be made to 

designate the Kiowa National Grassland Canadian River Inventoried Roadless Area (IRA) as a 

part of the Canadian River Potential Wilderness area. Plan components for a wilderness 

designation would be developed similar to those of the Mills Canyon Management Area in 

Alternative B, but wilderness regulations as outlined in FSM 2300, Chapter 2320 would be 

triggered. 

Direct and Indirect Effects 

The effects resulting from this alternative would be very similar to those reported for Alterative 

B. The only resource areas expected to have some change in activity levels compared to 

Alternative B are ecosystems restoration and recreation. For remaining resources, the direct and 

indirect effects are the same as those reported above. There is currently no data available that 

would allow for differentiating the effects between the two action alternatives, therefore the 
Economics Specialist Report 

18

effects in this case are described with a qualitative analysis with reference to the impacts reported 

above. 

Vegetation management activities would increase compared to the no action, but would not be as 

intensive as those under Alternative B. Shelter belts would not be completely removed as could 

happen under Alternative B. Tables 13 and 14 report a range of possible effects for ecosystems 

restoration relying on thinning and mastication respectively. Under this alternative it is likely that 

effects will be closer to the low end scenario. In this case of thinning be used as the primary 

method for tree removal the low end impact would be an increase of 2 jobs and $66,000 in labor 

income. If mastication were to replace thinning, the low end impact would be 1 job and $31,000 

in labor income. Either case would not result in a noticeable change in economic activity. 

The economic effects resulting from changes in visitation are more difficult to assess. Designated 

wilderness could alter recreational patterns, which in turn could alter economic activity. In any 

case it is unlikely that annual visitation rates will decrease. While overall annual visitation rates 

will likely remain the same, the distribution of activity types taking place on the Grasslands may 

change. This is likely to create more social impacts than economic. There is a substitution effect 

for recreation, as opportunities for one user group increase, they typically decrease for another. In 

the case of designating part of the grasslands as wilderness there is likely to be an increase in nonmotorized recreation. Since the area is an Inventoried Roadless Area (IRA) there is not much 

motorized recreation occurring there currently. However, if it was designated as wilderness, it 

would eliminate the opportunity to develop motorized recreation facilities. Motorized recreation 

is not expected to decrease under this alternative; however, non-motorized recreation is likely to 

increase at a rate greater than under the current plan or Alternative B. This may lead to slower 

growth in motorized use. The expected growth in recreation is still expected to be similar to that 

reported in Wilson and Eichman (2009); therefore the effects reported in Table 13 would still 

pertain. 

This alternative is not expected to result in a change in revenues back to the Grasslands. 

Therefore the same program revenues used for Alternatives 1 and 2 are also used for this 

alternative. Likewise, the expected costs of implementing this alternative are assumed to be the 

same as Alternative B. Therefore the PNV for Alternative C is the same and Alternative B, 

$433,740,633. This financial efficiency analysis is very limited due to the lack of data 

availability and site specific prescriptions in the alternatives. In the case of programmatic NEPA 

documents similar to this one, PNV does not provide a reliable indicator to base management 

decisions upon. The PNVs reported in this document are a measure of discounted revenues with 

very limited information on costs. 

Similar to Alternative B, there is little variation between this alternative and the No Action 

Alternative. Therefore no significant economic impacts are anticipated if Alternative C were to 

be implemented. The effects reported above represent a very small proportion of economic 

activity in the study area. Individual projects could impact certain user groups and stakeholders; 

however those effects cannot be estimated at this time. 

Cumulative Effects 

Cumulative effects would be similar to those reported under Alternative B paired with any 

changes in the levels and distribution of direct and indirect effects on the economic environment 

that would result from this alternative. 
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

19

Monitoring and Mitigation 

There are no specific monitoring and mitigation procedures in place for the economic 

environment. Most of the suggested monitoring methods listed in this section are already being 

conducted per Forest Service policy. For recreation, estimates of annual visitation by activity 

should be measured during future rounds of National Visitor Use Monitoring (NVUM) surveying. 

In order to monitor effects on the economic environment, visitation estimates from future NVUM 

rounds may be used in conjunction with the IMPLAN and the Recreation Economic Contribution 

Analysis tool (RECA) to estimate the contribution. For range and minerals resources use should 

be tracked overtime. That use data should be compared to the baseline data used to estimate the 

economic contribution of the No Action Alternative and trends highlighted. If trends indicate that 

a more detailed economic analysis is warranted then a new economic contribution may be 

calculated using the new data. Similar methods may be used for determining trends in ecosystems 

restoration work and Grasslands budget. Activity and financial information for both should be 

collected yearly and more detailed economic analysis may be completed in the future if trends 

indicate a substantial change in management. Maintaining working relationships with user 

groups and following public involvement procedures should provide an appropriate means of

understanding changes in the economic environment in the future. Collaboration with 

stakeholders is a key element of monitoring progress over the life of the plan. 

Conclusion 

The economic activity stimulated by Grasslands management is a very small proportion of total 

activity in the study area. Under current management, the total Grasslands economic contribution 

accounts for only 0.49 percent of total employment and 0.59 percent of total labor income. Any 

impacts resulting from implementation of Alternative A or Alternative B would not generate a 

noticeable effect on economic conditions overall. However, those individuals directly affected 

may experience changes to their livelihoods. Any impacts resulting from recreation or 

ecosystems restoration is likely to be in form of increased jobs and income. This is considered an 

economic benefit for local residents. Grazing is an important resource for many stakeholders. 

Agriculture remains a primary sector of the local economy and grazing is a traditional use of 

Grasslands resources. Changes in permitted grazing use, positive or negative, are likely to have 

an impact on the livelihoods of local ranchers, even though the overall economic effect may be 

negligible. This should be considered when making management decisions during the next 

planning cycle. 

Table 16 reports the results of the financial efficiency analysis. There is very limited data on the 

costs to implement projects during the next planning cycle, and current revenues by for each 

resource program are assumed to continue during future years. This greatly limits the 

informational capacity of the financial efficiency analysis. The values reported in Table 16 

should only be used to compare the expected differences between alternatives, and not be 

considered the actual value of implementation. 

Table 16: Results from the Financial Efficiency Analysis 

 Alternative A Alternative B Alternative C 

Present Net Value $434,787,152 $433,740,633 $433,740,633 

Present Value-Benefits $447,333,351 $447,333,351 $447,333,351 

Present Value-Costs -$12,546,199 -$13,592,718 -$13,592,718 
Economics Specialist Report 

20

There are not any substantial differences in the effects between action alternatives analyzed in 

this document. The alternatives do not prescribe any on-the-ground actions, but rather place a 

greater emphasis on vegetation and recreation management. When future project level decisions 

are made a more detailed effects analysis should be completed for those specific actions. This 

will shed more light on the economic effects of Grasslands management. For the purposes of this 

report, the action alternatives would not have a substantial effect on the local economy.
Kiowa, Rita Blanca, Black Kettle and McClellan Creek National Grasslands Plan Revision 

21

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