Citation
Do USDA farm program participants contribute to soil erosion?

Material Information

Title:
Do USDA farm program participants contribute to soil erosion?
Series Title:
Agricultural economic report
Creator:
Reichelderfer, K. H
United States -- Dept. of Agriculture. -- Economic Research Service
Place of Publication:
[Washington DC]
Publisher:
U.S. Dept. of Agriculture, Economic Research Service
Publication Date:
Language:
English
Physical Description:
iv, 74 p. : ill. ; 28 cm.

Subjects

Subjects / Keywords:
Soil erosion -- United States ( lcsh )
Soil conservation -- United States ( lcsh )
Genre:
bibliography ( marcgt )
federal government publication ( marcgt )
non-fiction ( marcgt )

Notes

Bibliography:
Bibliography: p. 42.
General Note:
Cover title.
General Note:
Distributed to depository libraries in microfiche.
General Note:
"April 1985"--P. i.
Funding:
Electronic resources created as part of a prototype UF Institutional Repository and Faculty Papers project by the University of Florida.
Statement of Responsibility:
Katherine H. Reichelderfer.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
The University of Florida George A. Smathers Libraries respect the intellectual property rights of others and do not claim any copyright interest in this item. This item may be protected by copyright but is made available here under a claim of fair use (17 U.S.C. §107) for non-profit research and educational purposes. Users of this work have responsibility for determining copyright status prior to reusing, publishing or reproducing this item for purposes other than what is allowed by fair use or other copyright exemptions. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. The Smathers Libraries would like to learn more about this item and invite individuals or organizations to contact Digital Services (UFDC@uflib.ufl.edu) with any additional information they can provide.
Resource Identifier:
001307278 ( ALEPH )
12604208 ( OCLC )
AGF8089 ( NOTIS )

Full Text
i4




d6pie 'O.f Thia
d*Itt' '04
can be purchased, from the- S# intendentof."Doculgeiltd, U S.;: ; ve piin' per, rument ting,
Office, Washiugton, DC 204G2. Ask for Do USDA Farm Program--Part# Contribute ,: to Soil Erosion? (AER-532). Write to the above 11 address for price and order ins tr'u-c.t ions. !For faster servIce, eall -the GP6iordei desk.at (202) 783-3238 an charge your purchase to your VISA, MasterCa,rd, or. GPQ Deposit Actount A 25-percent. bulk discount is available on orde .rs of 100. orz- more. copies shipped to, siogle address-. ,Please add, 25--, per eentrr extra f or pastage,4or shipments to f 'eign1:addres4es.
111cr6ft-che copies ($4i.50 each) can b6purchAsed from.the Identificatio National, Technical Iftformation Service,.5285 Port Royal Road, Spriugfi el-A VA ,22161. Ask for Do ZSDA, -Farm ProgrAswPqrtiS,2ants Contribute to Soil Erosion? JAER-532). Enclose check-or money orddr,,.p-ayab1e;to NTIS.'.F'or faster-service,. icall NTISat (.703) 487-4780 and charge you I purchase to your VISA,,HasterCard,
Amerlcan'Expregs, or:.: NTIS. Deposit Ace-94*t
:'The Nconom1c Research-, Service has uq4;copiekfor, free mailing.




DO USDA FARM PROGRAM PARTICIPANTS CONTRIBUTE TO SOIL EROSION? By Katherine H. Reichelderfer, Economic Research Service, U.S. Department of Agriculture. Agricultural Economic Report No. 532.
ABSTRACT
Only about one-third of U.S. cropland with excessive soil erosion rates is operated by farmers who might be influenced to reduce erosion if changes were made in the U.S. Department of Agriculture's commodity and soil conservation programs. The present commodity programs may conflict with conservation programs by encouraging the cultivation of erosive crops. Efforts to increase the consistency of USDA commodity and conservation programs would contribute little to overcoming the Nation's total erosion problems. Such efforts, however, should balance conservation objectives with objectives for farm income,
commodity prices, production, and export.
Keywords: Commodity programs, conservation, program consistency, soil erosion.
ACKNOWLEDGMENTS
Jerry Lee and Keith Schmude of SCS and Gordon Nebeker and Jack Webb of ASCS made significant contributions to the development, planning, design, and implementation of means of assembling data for the study. Special acknowledgment goes to the ASCS and SCS county personnel who willingly, and efficiently assembled data from their county offices. Also, special thanks go to the agricultural economists who coordinated and recorded the massive set of
assembled data: Lee Christensen, Richard Clark, Neil Cook, Merlin Erickson, Andrew Hudson, James Kasal, Doug Lewis, Arnold Paulsen, Robert Pfeiffer, Jesse Russell, Gordon Sloggett, Marlow Vesterby, and Jerry Williams. Keith Schmude, Stephanie Taylor, and Jack Webb were particularly helpful in designing and pretesting the data assembly process. Joyce Su gave excellent attention to editing, summarizing, and running computerized statistical tests on the data set. Venita Dimmick and Wanda Nelson typed various drafts of this report, as well as all material dealing with the USDA Program Consistency Study. Dennie Burns, Lee Christensen, Richard Clark, Neil Cook, Thomas Hertel, James Kasal, Tom McDonald, Arnold Paulsen, Jesse Russell, and Peter Tidd provided helpful comments and suggestions on former drafts. Lindsay Mann edited the manuscript.
Washington, DC 20250 April 1985




PREFACE
This report contributes that part of the U.S. Department of Agriculture's Program Consistency Study dealing with a definition of problems. This study is one of a series of tasks being undertaken by USDA agencies in support of Departmental implementation of the 1977 Resource Conservation Act (RCA).
One goal of the National Conservation Program, which is required by the RCA, is to obtain consistency of Departmental commodity and conservation programs and objectives. There have been several Departmental attempts in this and previous administrations to examine ways that commodity programs could be designed to simultaneously achieve soil and water conservation objectives and meet farm price and income support objectives.
An integrated program approach requires information on the erosion problem on farms participating in commodity programs and the potential response of these farm operators to integrated program alternatives. The "problem-definition phase" of the USDA Program Consistency Study was initiated to fill this information gap.
The USDA Program Consistency Study is an interagency effort. Participating agencies include the Economic Research Service (ERS), the Soil Conservation Service (SCS), the Agricultural Stabilization and Conservation Service (ASCS), and other USDA agencies.
The Consistency Study is split into three phases. The first phase, and the subject of this report, is an effort to define more adequately the nature and extent of program consistency problems. In the second phase, farm programs have been examined for their impacts on soil erosion. In the third phase, three alternative policies have been examined to assess their expected effects on soil and water resources, agricultural production, farm income maintenance, and other important Departmental goals. The analytical work for all three phases is complete, and published reports on results are forthcoming.
OTHER REPORTS ON FARM LEGISLATION
Other USDA reports providing background for 1985 farm bill discussions deal with the major program commodities, the farm industries that produce them, and the farm programs under which they are produced. These commodity papers are available from EMS Information, Room 0054-S, USDA, Washington, DC 20250, (202) 447-7255. They include Honey (AIB-465), Wool and Mohair (AIB-466), Wheat (AIB-467), Tobacco (AIB-468), Peanuts (AIB-469), Rice (AIB-470), Corn (AIB-471), Soybeans (AIB-472), Oats (AIB-473), Dairy (AIB-474), Sorghum (AIB-475), Cotton (AIB-476), Barley (AIB-477), and Sugar (AIB-478).
Background reports are also available on Federal Credit Programs for Agriculture (AIB-483), the History of Agricultural Price Support and Adjustment Programs, 1933-84 (AIB-485), The Current Financial Condition of Farmers and Farm Lenders (AIB-490), A Summary Report on the Financial Condition of Family-size Commercial Farms (AIB-492), Foreign Exchange Constraints to Trade and Development (FAER-209), Financial Constraints to Trade and Growth: The World Debt Crisis and Its Aftermath (FAER-211), Possible Economic Consequences of Reverting to Permanent Legislation or Eliminating Price and Income Supports (AER-526), and the Impacts of Policy on U.S. Agricultural Trade (ERS Staff Report No. AGES840802).
ii




CONTENTS
Page
HIGHLIGHTS* ..... . . . . .. .. .. .. iv
INTRODUCTION. . . . . . . . . . .1
CONCEPTUAL BASES FOR PROGRAM INCONSISTENCY ...... . ........ 2
U.S. FARM PROGRAM PARTICIPATION AND EROSION PROBLEMS. . . . . . 5
Soil Erosion in the United States . . . . . * . 6
Do Farm Program Participation and Soil Erosion Overlap?. .. .*. . 8
DATA ASSEMBLY PROCEDURES .. .. .. . .. . . . . . . 8
PROGRAM PARTICIPATION AND SOIL EROSION IN CRITICAL RESOURCE AREAS . .. 14
Program Participation. e . e .15
Soil Erosion Rates ........................ 25
Relationships Between Program Participation and Soil
Erosion in Critical Resource Areas......g............ 28
Who Contributes to the Soil Erosion Problem? ............. 32
FARMER CHARACTERISTICS BY PROGRAM PARTICIPATION AND SOIL EROSION CLASS 34
Ownership .. .. 35
Tenure! 35
Off-farm Work . . . .. ......... 36
Operator Age .. . . . . .................. 36
Operating Loan Source ......... ..... ......... 36
Land Capability Class and Subclass .. ............ 36
SUMMARY AND IMPLICATIONS . . . . . . . . . ...... 37
REFERENCES ................................. 42
APPENDIX A: USDA PROGRAM CONSISTENCY STUDY SAMPLE COUNTIES . . . . 43
APPENDIX B: INSTRUCTIONS FOR COMPLETING AD-862 FORMS FOR USDA PROGRAM CONSISTENCY STUDY . ........ ... .... ...... 45
APPENDIX C: DISTRIBUTION OF FARM AND OPERATOR CHARACTERISTICS AMONG PROGRAM PARTICIPATION CATEGORIES AND SOIL EROSION CLASSES . . . 52
iii




HIGHLIGHTS
The present commodity programs of USDA may conflict with conservation programs by encouraging the cultivation of erosive crops. This study indicates that only about one-third of U.S. cropland with excessive soil erosion rates is operated by participants in the U.S. Department of Agriculture!* (USDA) commodity and soil conservation programs. Nevertheless, efforts to increase the consistency among USDA commodity and conservation programs should attempt to balance conservation objectives with objectives concerning farm income, commodity prices, production, and exports.
These findings and judgments are based on a satudy of 1982 data for 2,882 farms to determine the extent to Which USDA's commodity and couservation programs may be at odds with USIA's goals to control soil erosion.
The author concludes that modifying USDA commodity and conservation programs to achieve greater consistency could affect one-third to one-half of the Nation's cropland acres eroding at unacceptable rates. However, any changes in commodity and conservation programs would also need to protect the program participants who do maintain soil erosion,at tolerable levels.
Commodity and related farm program supportt.prices and reduce risks of producing crops that are relatively more erosive than nousupported production activities. However, because program crops such as cotton$ soyesas, corn, and .other food and feed grains are vital to farm income and export, changes in farm programs must jointly address these issues along with soil conservation goals.
iv




Do USDA Farm Program
Participants Contribute to Soil Erosion?
Katherine H. Reicheiderfer*
INTRODUCTION
National policy seeks, through a variety of Federal conservation programs, to reduce excessive erosion on U.S. agricultural land to levels that maintain the long-term productivity of our soil resources and improve water quality.
Another goal of Federal policy is to stabilize commodity prices and assure adequate farm income. These goals are achieved primarily through commodity, loan, and crop insurance programs that support market prices, reduce production risk, or provide direct income payments to participants.
Beneficiaries of these federally subsidized credit, crop insurance, and commodity programs include farmers who operate excessively eroding cropland as well as noneroding cropland. The direct and indirect financial benefits of producing commodity program crops are available to farmers regardless of the erosion on their land. Some commodity program participants who have erosion problems apply conservation measures to reduce erosion. Commodity program participants who till erodible soils without employing adequate conservation measures contribute to the erosion problem.
Current commodity program provisions discourage long-term conservation uses of land by denying base acreage status to land not recently used to produce program crops. Thus, some farmers who utilize long-term soil conservation measures may be penalized by being declared ineligible for commodity program benefits.
The Secretary of Agriculture has called for investigations of measures to ensure that programs aimed at commodity supply management and farm income support are as consistent as possible with efforts to conserve soil and water resources. Until now a lack of information has precluded addressing the question of how consistent these programs are with soil conservation goals.
Knowledge of the extent to which commodity program participants currently contribute to national soil erosion and how participants differ from nonparticipants in
* The author is Chief, Western Hemisphere Branch, International Economics Division, Economic Research Service (ERS). When this study was prepared, she was Deputy Chief, Inputs and Productivity Branch, Natural Resource Economics Division, ERS. She served as leader of the group assigned to prepare that part of the USDA Program Consistency Study dealing with the definition of problems.
1




this respect is a prerequisite to planning for better program integration. The study summarized in this report was initiated to develop such information.
Specific questions addressed by this study include:
" Are there logical conceptual bases for hypothesizing that commodity and
related farm program activities are inconsistent with soil conservation
goals?
" What group or groups of agricultural producers are the largest contributors to soil erosion problems?
" To what extent, and in what way, is commodity program participation
related to erosion problems?
" Do contributions of USDA program participants to soil erosion problems
differ from those of nonparticipants?
" How much cropland on which there is an erosion problem is operated by
individuals participating in USDA programs?
" What are. the characteristics of farms and their operators that could
be affected by policies designed to integrate commodity, farm income,
and soil conservation objectives?
The answers to these questions should help provide the knowledge base required to design and analyze policy options for resolving serious land use or erosion problems on lands of farm program participants without placing a burden on individuals not contributing to resource conservation problems.
The hypothesis was set forth that certain aspects of current commodity, credit, and crop insurance programs may encourage production patterns that are inconsistent with soil conservation goals. Data assembled to test the accuracy of this hypothesis indicate that USDA program participants in certain production areas make significant contributions to soil erosion problems. Up to half of cropland with high erosion rates in those areas may, in fact, be operated by individuals who might be influenced to reduce erosion on their farms through changes in USDA commodity and conservation programs. 1/
CONCEPTUAL BASES FIOR PROGRAM INCONSISTENCY
There are logical bases for hypothesizing an inconsistency between commodity and natural resource related goals, concludes.Osteen's exploration of the relationships between current farm policies and soil conservation (7). 2/ The principal
1/ Some currently proposed congressional legislation (for example, H.R. 3 37 and S. 663) would modify provisions of current commodity and related farm programs to make them more consistent with soil conservation goals. The bills Propose a variety of methods to achieve this, such as basing eligibility for farm program benefits on adherence to soil-conserving production activities and allowing base acreage status for land in long-term conservation uses. This report does not address specific program options. Rather, a data and information base was developed that may be used for subsequent analyses of specific alternative program changes.
2/ Underlined numbers in parentheses refer to sources cited in References at eri of report,
2




factor contributing to these inconsistencies is the positive effect of commodity, credit, and crop insurance programs on the relative economic attractiveness of crops covered by these programs.
As explained by Osteen, there are three factors that determine erosion from a given site:
o The physical and climatic characteristics of the site.
0 Planting and crop management decisions determining what and how crops
are cultivated on the site.
0 Investments in long-term soil conservation practices applied on the site.
Farm policies and programs do not affect inherent physical and climatic factors. Policies and programs that affect the relative price or relative production risk of alternative crops do, however, strongly influence planting and crop management decisions. Policies and programs that increase farm income and credit availability may affect the extent to which long-term conservation investments are made.
Price supports, target prices, nonrecourse loans, acreage reduction programs, subsidized crop insurance, disaster payments, Farmers Home Administration (FmHA)
emergency loans, and current commodity export policies all have one thing in common: each increases the economic attractiveness of the commodities to which it applies in relation to commodities not covered by the program or affected by the policy. Price supports, acreage reduction programs, and export policies increase the market prices of program commodities or reduce the price risk associated with them. These program crops offer high and stable relative price advantages to all farmers--not just to program participants. Target price programs create additional incentives for program crop production and participation. Nonrecourse loans, the farmer-owned reserve, and other price support programs help stablilize or guarantee the price received by complying farmers for commodities covered. Finally, subsidized crop insurance, disaster assistance, and FmHA emergency loans help protect participating farmers producing crops covered under specific programs from suffering financial disaster during bad crop years or because of poor cropping conditions. These safeguards are available only for production of certain commodities. Thus, farmers may find production of these commodities more attractive than production of commodities which are not covered by such programs.
If an individual farmer has the right to decide what, where, and how much of
various commodities to produce, he or she will naturally take program benefits (direct and indirect) into consideration when making planting and crop management decisions. Those decisions may subsequently affect soil erosion rates. It is useful, therefore, to compare the likelihood of soil erosion resulting from various production activities with those activities' eligibility for program benefits. Given the same physical factors and the same level of..management, production of commodity program crops'produces more erosion (table 1). None of the "least erosive" activities shown in table 1 is eligible to receive deficiency, diversion, or disaster payments, or obtain nonrecourse loans. 3/ Few are
eligible for coverage through federally subsidized crop insurance.
3/ The dairy program, which supports and stabilizes milk prices, does provide additional benefits to some producers whose land is in grassland, hayland, and pasture.
3




Farmers may be particularly encouraged to plant program crops during periods of economic recession and recovery. Currently U.S. farmers have a high rate of indebtedness, and loans have been made at high interest rates., Substantial cash flow is required to pay off debts and other expenses. Production of program crops helps assure cash flow is forthcoming.
Commodity programs create situations that are relatively profitable and that may increase the likelihood that erosive crops will be planted on erodible land. However, the income-enhancing effects of the programs may also encourage conservation investments. Farmers are likely to invest in terraces and other costly structures only when they perceive a long-term net benefit from the investment and have a sufficiently high income to cover its cost. Commodity programs, by offering relatively profitable and stable production possibilities, help producers meet the criterion of adequate farm income for investment purposes.
FmHA ownership, operating, and soil and water loans increase the availability of credit to farmers. As credit availability increases, the ability to invest in long-term improvements, including conservation practices, also increases. Translating credit availability into conservation investments, however, depends upon the farm operator's perception that current soil erosion is reducing or
Table 1--Agricultural land uses, erosion potential, and eligibility for major
direct farm program benefits
Eligibility to receive-Relative Land use! Deficiency, ::Federal
erosiveness production : diversion, : Nonrecourse : all-risk
activity 1/ and disaster : loans crop
payments insurance 2/
Most erosive Cotton Eligible Eligible Eligible
Most erosive Soybeans Ineligible Eligible Eligible
Moderately erosive Corn Eligible Eligible Eligible
Moderately erosive Grain sorghum Eligible Eligible Eligible
Less erosive Wheat Eligible Eligible Eligible
Less erosive Barley Eligible Eligible Eligible
Less erosive Oats Eligible Eligible Eligible
Less erosive Rice Eligible Eligible Eligible
Least erosive Grassland Ineligible Ineligible Ineligible
Least erosive Hayland Ineligible Ineligible Ineligible 3/
Least erosive Range and pasture Ineligible Ineligible Ineligible
Least erosive Forest and tree crop Ineligible Ineligible Ineligible 3/
I/ Land use/production activities are grouped according to relative erosiveness.Specialty and miscellaneous crop production is not included since the relative erosiveness of crops in those categories can range from high (such as tobacco) to low (such as vineyards).
2/ Federal Crop Insurance Corporation (FCIC) all-risk crop insurance is availab le in locations where disaster payments are not made in conjunction with commodity programs.
3/ FCIC all-risk crop insurance is available for some forage and seed enterprises and tree fruit producers in only a few U.S. counties.
4




will negatively affect the productivity of land. There is considerable controversy concerning farmers' perceptions of the long-term benefits from soil conservation investments.
Although there are reasonable bases for linking soil erosion with farm program participation, such relationships remain questionable. This report presents information which we assembled to address these questions.
U.S. FARM PROGRAM PARTICIPATION AND EROSION PROBLEMS
Studies characterizing participants in commodity programs throughout the sixties and those participating in 1978 commodity programs consistently reveal the following (3):
" Program participants typically have larger farms than do nonparticipants;
a larger proportion of operators of large farms participate in commodity
programs,
" Program participants typically have a larger portion of land in crops'and
obtain a larger share of sales from crops than do nonparticipants.
" Farms of program participants tend to be cropped more intensively
and to include a high proportion of specialized cash crop operations.
These observations were reconfirmed in 1982. In addition, 1982 participation
by region was found to be (8):
" Highest in the Plains States, where most producers usually participate.
" High in the North Central and Southern States, which account for
most participating producers outside the Plains States.
" Low in the Northwest, Southwest, and Northeast, where fewer than'4
percent of producers participated in 1982 commodity programs.
Much of the reason for the variation in participation rates among regions is the difference in crops produced. Most U.S. wheat is produced in the Plains States, corn in the North Central States, and cotton and rice in the South. The proportion of program crops produced in the Northwest, Southwest, and Northeast is less than that for the other three regions. The participation rates for specific commodity programs vary according to benefits offered in a given year, In 1082, program participation rates were greatest, in order, for
wheat, corn, cotton, and sorghum-.
More information is available on commodity program participation than on the distribution of participation in federally subsidized credit and crop
insurance programs.
FmHA is the lender of last resort for many farm operators, It provides lowinterest credit to farmers who are unable to obtain financing from commercial sources. FmHA subsidies per cropland acre are highest for States that have a large proportion of small farms (5). By its very nature, FmHA is likely to be the primary source of credit for lower income farmers. However, no current data on the characteristics of FmHA borrowers are available to test this hypothesis.
5




The Federal Crop Insurance Act of 1980 authorized the substitution of disaster payments with the availability of federally subsidized all-risk crop insurance. Any producer of an insurable crop in counties where the Federal Crop Insurance Corporation (FCIC) coverage is available can obtain Federal crop insurance. FCIC will insure some 41 crop programs for the 1985 crop year. Principal crops insured through FCIC are corn, grain sorghum, oats, barley, and peanuts. No data are available to describe the characteristics of individuals purchasing Federal
crop insurance.
Soil Erosion in the United States
Soil erosion is considered tolerable when annual rates are at or below the level
needed to maintain long-term soil productivity--popularly expressed as the "soil loss tolerance," or "T value." In the United States, 67 percent of all soils have a tolerance level, "T" value, of 5 tons per acre per year (TAY), which is the highest permissible rate, but T is lower on many soils, going as low as 1 TAY on some sensitive soils. In 1982, about 56 percent of all U.S. cropland was eroding at levels equal to or less than T. About 44 percent of all cropland is eroding at levels greater than T (4). Over 140 million acres of that land have sheet and rill erosion (resulting from rainfall) plus wind erosion resulting in erosion of
more than 5 tons per acre per year (9).
Soil erosion rates vary significantly among and within regions as a result of differences in physical and climatic characteristics, crop mix, crop management practices, and extent of conservation investments. Bills and Heimlich report a
soil erosion taxonomic system that groups sheet and rill erosion factors into fixed and manageable components (1)'. They derive four erosion classes:
1. Nonerosive land is land for which physical characteristics are such that
regardless of the crop or practices applied, it will not erode at rates
greater than 5 tons per acre per year (TAY).
2. Moderately erosive land managed below tolerance is land that has the
potential for erosion rates greater than 5 TAY but is managed (through
crop choice and practices) in a manner that keeps erosion below the 5
TAY maximum tolerance level.
3. Moderately erosive land managed above tolerance is land on which erosion
rates could be restricted to 5 TAY, but management practices cause
erosion rates greater than 5 TAY.
4. Highly erosive land is so inherently erosive that almost no management
except permanent sod cover can keep the erosion rate at 5 TAY or below.
This classification scheme is useful in defining two distinctly different types of erosion problems:
0
The problem of moderately erodible land on which erosion can be reduced
to tolerable levels, but which is managed in ways that cause erosion
above tolerance.
0
The problem of land cultivated despite the fact that it is inherently
highly erodible and not subject to management below tolerance unless placed in a noncultivated use, such as permanent sod or forest cover.
6




Poor management of moderately erodible soils results from economic barriers to
investment in soil conservation, lack of knowledge of ways to reduce erosion on these manageable soils, lack of perception of a problem, or some combination of these factors. On some land, erosion above 5 tons per acre per year is not considered by farmers to be a problem because it will not result in productivity losses within any foreseeable time frame, or it would cost more to reduce the erosion than could be captured in returns.
Conversion of inherently erodible soils that are under grass to cropland occurs in response to a variety of economic incentives, including high grain prices relative to livestock prices, the increased land value and favorable tax structure that allow-capital gains to be made from plowing up grasslands, and availability of commodity program benefits on cultivated land used for program crop production. However, agricultural programs do not seem to be the driving force behind observed plowing and conversion of western grasslands to cropland (2, 11, 12).
Bills and Heimlich also examined the regional, crop-specific, and owner-operator characteristics of land that in 1977 fell into each of their soil erosion classes for sheet and rill erosion. Major findings include the following (1):
0 Land highly susceptible to sheet and rill erosion is relatively more
prevalent in the Northeast, Appalachian, and Corn Belt regions;
relatively large amounts of cropland moderately susceptible to sheet and
rill erosion is managed above tolerance in the Appalachian, Corn Belt,
Delta, and Southeast regions.
0
More than two-thirds of cropland most susceptible to sheet and rill
erosion was committed to the production of row crops during the 1977 crop
year; more than three-fourths of all cropland moderately susceptible to
sheet and rill erosion eroding at more than 5 TAY was planted to corn,
soybeans, and other row crops; while approximately half of cropland
moderately susceptible to sheet and rill erosion was committed to wheat,
hay, or other close-grown crops and grasses.
Small differences were found among soil erosion and size of landholding:
relatively large numbers of owners with cropland highly susceptible to
sheet and rill erosion have small farm landholdings; relatively large
numbers of owners situated on cropland not susceptible to sheet and rill
erosion have large landholdings.
0 There are no obvious characteristics defining groups of owner-operators
of nonerodible, moderately erodible, or highly erodible cropland.
Owner-operators seem to be distributed fairly evenly among sheet and rill
soil erosion classes by age, net farm income, principal occupation, type
of ownership, and educational level. 4/
Rates of wind erosion on cropland are highest in the Southern Plains. However, no information is available on the characteristics of farms or farm operators on whose land wind erosion is a major soil erosion problem.
4/ The Bills and Heimlich study considered only owner-operators of cropland
and- addressed only-the problem of sheet and' / rill erosion. No data were available to examine characteristics of tenants among soil erosion classes. Owneroperators constitute about half of all farm operators (1).
7




Do Farm Program Participation and Soil Erosion Overlap?
A comparison of the characteristics of farm program participation and Boil erosion suggests the possibility of some overlap. Specifically, participation in farm programs is fairly high among row crop producers, and row crop production is closely related to erosion problems.
On the other hand, some evidence suggests that operators of eroding cropland and participants in commodity programs are more distinctly grouped. While program participation is skewed toward operators of larger farms, high levels of soil erosion are more prevalent among small farms. Further, the most erodible soil may not exist in regions of the country that typically have high rates of commodity program participation. Ogg, Miller, and Clayton compare the proportion of agricultural counties' cropland acreage eroding over 25 TAY with the proportion of those counties' cropland enrolled in 1977 commodity programs (6). They find no positive correlation between these proportions, and maps illustrating their findings suggest a negative correlation.
Aggregate data on program participation and soil erosion, while enlightening, do not adequately define the dimensions of the problems of consistency in farm programs. There is a need to look specifically at regions and crop production activities that make soil naturally prone to all forms of erosion before we can judge whether farm programs affect observed erosion where erosion is most likely to occur. For example, while program participation rates are relatively low in most counties that experience excessive erosion, it is necessary to know for purposes of policy analysis whether the excessive erosion in these areas is the result of practices on program participants' land. A more disaggregated data set is needed to answer the questions posed at the beginning of this report. This report, therefore, brings together primary data directly relating farm program participation to soil erosion in regions of the country that have critical erosion problems.
DATA ASSEMBLY PROCEDURES
Characterizing producers by joint soil erosion and farm program participation
requires observations linking physical, demographic, and farm program participation information on an appropriate sample of farming operations. Data collected for this study linked preliminary physical data on erosion from the 1982 Soil Conservation Service's (SCS) National Resources Inventory (NRI) with information supplied by the Agricultural Stabilization and Conservation Service on the farm and the operator of the land on which sampled NRI cropland points fall.
National Resources Inventories of soil and water conservation needs, conducted every 5 years by SGS, provide detailed data on land capability, land use, sheet and rill erosion, wind erosion, soil quality, and conservation needs for various land uses. The 1982 NRI contains information on 328,014 specific points of land across the United States. SCS field personnel conducted onsite inspections of each point and recorded resource data, including the information needed to estimate annual soil erosion from the point.
The data base for this study was derived by first selecting a sample of NRI cropland points in regions of the country that have critical soil erosion problems.
8




Major land resource areas (MLRA's) were chosen as the units of regional delineation. An MLRA is a geographically associated land resource unit within which physical and climatic conditions are relatively homogeneous (9). Eleven MLRA's were selected from among those having high concentrations of critical soil erosion problems. The criterion used for identifying such an MLRA was that USDA had targeted a high proportion of counties in the MLRA to receive increased conservation technical assistance because of cropland or rangeland erosion or water conservation and salinity control problems or both. The areas targeted for water conservation and salinity control were considered representative of critical wind erosion areas. Critical erosion control target areas were selected as representative of sheet and rill erosion problem areas. The five individual and three paired sets of MLRA's designated as study areas are illustrated in figure 1 and are further described by figures 3 to 10. The study areas, or 11 MLRA's comprising them, contain 41 percent of all U.S. counties identified by SCS as critical "cropland erosion control" counties. They also include 31 percent of those identified as critical "water conservation and salinity control" counties, that is, areas in which wind erosion is expected to occur at critical rates.
Sample counties within study areas were chosen on the basis of whether a county was included in SCS's set of sample counties for its Conservation Technical Assistance (CTA) Program Evaluation. Those counties were previously selected to provide a nationally valid sample of agricultural counties for SCS and ASCS program evaluation purposes. The advantage of using a subsample of those counties for the USDA Program Consistency Study is that it allowed for coordination and supplementation of data sets collected for other related studies. The consistency study data, however, are not subject to evaluation within the framework of the CTA evaluation sample frame. The two separate samples were designed to intersect one another, but the characteristics of the two samples are distinct. Some 66 counties were CTA counties within the eight study areas. Two additional counties were randomly selected from study areas that had too few CTA counties to provide a sample of reasonable size. The 68 counties selected from among the eight study areas for the consistency study sampling are listed in appendix A and illustrated in figure 2. The set of sample counties represents over 6 percent of Conservation Technical Assistance Target Areas.
A random sample of NRI cropland points was drawn, according to standardized procedures, for each of the 68 sample counties. SCS personnel in the sample counties indicated the location of each randomly selected NRI cropland point on county mapping materials. The land capability class and subclass and the sum of wind and water erosion rates estimated for each selected point were also recorded alongside the point's location on the mapping material.
SCS mapping materials were then lent to ASCS county offices where ASCS county personnel identified the farm operation on which each mapped NRI cropland point was located. ASCS county office records, supplemented by personal knowledge of ASCS county personnel, were used to assemble the following information on the operation associated with each selected sample NRI point:
0
Farm identifier;
0
Farm type;
0
Farm size;
0
Cropland acreage;
9




Figure 1
Location of Study Areas Covered by USDA Program Consistency Study Data Assembly
Loess Uplands and Till Plains and LoessDrift Hills
Palouse and Nez
Perce Prairies EKIowa and Missouri
Deep Loess Hills
Conis enStudrampl Countiesher
Plains and Upper Piedmont
,Arkansas Valley
Rolling PlainsI
Southen~l !Southern SotenMississippi -. Southern High Valley 'Coastal Plains
,,.Plains Silty Uplnd
Figure 2
Consistency Study Sample Counties
10




0
Commodity and conservation program participation for 1978, 1982, and
1983;
0
Type of farm ownership;
0
Farm tenure arrangement;
0
Primary source of operating loans to farm operator;
0
off-farm work status of farm operator;
Age class of operator; and
0
Base acreage and effective yield of program crops produced.
Data on farm size, farm type, cropland acreage, cropping information, and ASCS program participation were available on filed farm record cards. Participation in SCS programs was determined through consultation with SCS personnel or examination of SCS file records. Type of ownership, classification of tenure arrangements, loan sources, off-farm work status, and age class of operator were determined on the basis of personal knowledge of ASOS county personnel. Because ASCS personnel are generally very familiar with their local farming communities and since they had the option of stating whether or not they are aware of a particular characteristic of a given farm operator, the data based on personal knowledge appear to be very reliable.
Conservation program participation 'for a given year was defined as the receipt of payments in that year for a farm operator's participation in any ASCS-administered conservation program 5/ or any SCS-administered program 6/, and the submission of a conservation plan to SCS in that year or action taken that year in accordance with a previously filed plan. Thus, the study considers only the financial and technical assistance aspects of USDA's overall conservation goals. Appendix B provides definitions of other variables.
Data were assembled between October 1983 and January 1984. A total of 2,882 observations linking soil erosion, farm type, and operator characteristics were collected. The distributions of sample data among study areas, farm types, and land capability classes are shown in tables 2-4.
The data set assembled to relate soil erosion and farm program participation in critical resource areas of the country represents a merger of systematically selected subsets of 1982 data from the Natural Resources Inventory and ASCS farm records that randomly overlap with data independently collected for other SCS conservation program evaluation purposes. The nature of the data assembly process and the multiple objectives for which the data originally were collected impose several limitations on the value of the data.
5/ ASCS-administered conservation programs include the Agricultural Conservation Program, Emergency Conservation Program, Rural Clean Water Program, Water Bank, and Forestry Incentives Program.
6/ Formalized SCS conservation programs include Great Plains, Rural Abandoned Mines Program, Resource Conservation and Development, PL-566 (Small Watersheds), and the Conservation Technical Assistance Program.
11




First, the study sample is purposefully biased to reflect the erosion rates and program participation situations in specific areas of the country. The sample was derived strictly from areas of the country where observed sheet and rill or wind erosion rates are highest. Not all cropland within these areas erodes at high rates; much of it erodes at far lower than tolerable levels. However, the study areas are characterized by greater than average soil erosion rates and the sample data reflect this. As a result, the data from the geographically biased sample universe do not present a description that can be applied to other regions of the country or to the Nation as a whole. (See "Study Areas Are Not Representative of the United States," page 15.)
The study data are not derived from a probability-based sampling technique. Although observations were randomly selected, statistically determined confidence limits cannot be placed on derived numerical averages.
These limitations restrict the use of our study area sample data to the provision of descriptive information on the study areas only. In the sections immediately following, the sample data on erosion, program participation, and farm characteristics are compared to derive generally observed relationships
among relevant factors in the study areas.
Table 2--Distribution of sample data among study areas
Study area : Observations : Proportion of
: total sample
Number Percent
Columbia Plateau and Palouse and
Nez Perce Prairies (MLRA's 8
and 9) 1/ 320 11.1
Central High Plains and Upper
Arkansas Valley Rolling Plains
(MLRA's 67 and 69) 261 9.1
Southern High Plains (MLRA 77) 300 10.4
Loess Uplands and Till Plains and
Nebraska and Kansas Loess-Drift
Hills (MLRA's 102B and 106) 291 10.1
Iowa and Missouri Deep
Loess Hills (MLRA 107) 304 10.6
Southern Coastal Plains (MLRA 133A) 730 25.3
Southern Mississippi Valley Silty
Uplands (MLRA 134) 491 17.0
Southern Piedmont (MLRA 136) 185 6.4
Total 2,882 100.0
1/ Major land resource area (MLRA) numbers are those designated by the U.S.
Soil Conservation Service (10).
12




Results apply only to the critical resource study areas from which the data were drawn. Subsequently, we used these study area-specific descriptions to derive broad implications for U.S. conservation and commodity program interrelationships.
Table 3--Distribution of sample data among farm types
Farm type : Observations : Proportion of
: : total sample
Number Percent
Cash grain farms 1,321 45.8
Cotton farms 219 7.6
Tobacco farms 37 1.3
Other field crop farms 111 3.9
Vegetable and melon farms 17 .6
Fruit, berry, and nut farms 18 .6
Livestock farms and ranches 142 4.9
Miscellaneous farms 1/ 14 .5
Combination livestock and grain farms 986 34.2
Tree farms 17 .6
Total 2,882 100.0
1/ Includes fur-bearing animals, bees, grass, and seed, among other types of farming.
Table 4--Distribution of sample data by USDA land capability class
Land capability class 1/ : Percent of total sample
I 5.8
II 42.9
III 32.9
IV 14.0
V 1.0
VI 2.7
VII .8
VIII 0
Total 100;.0
Land in subclass e 61.3
Land in classes IVe, VI, and VII 14.8
Note: Total does noteadd to: 100.0 due to rounding.
1/ The SCS land capability classification system groups soils at several
levels. The capability class, ds -~gnated by Roman adherals, indicates progressively greater limitations and narrower choices for land uses. The-capability subclasses, designated by letters, are subgroups of soils that have particular limitations due to climate or soil characteristics. Risk of erosion is designated by subclass e.
13




Table 5--Program participation rates for sample points by year
Program participation 1978 1982 1983
Number Percent Number Percent Number Percent
Land of operators
participating in neither commodity
nor conservation
programs 1,236 43.4 1,188 41.2 777 27.0
Land of operators
participating only
in commodity programs 861 30.2 799 27.7 1,093 37.9
Land of operators
participating only
in conservation
programs 294 10.3 405 14.1 254 8.8
Land of operators
participating in
both commodity and
conservation programs 459 16.1 490 17.0 758 26.3
Total 2,850 100.0 2,882 100.0 2,882 100.0
PROGRAM PARTICIPATION AND SOIL EROSION IN CRITICAL RESOURCE AREAS
All data are aggregated to study area levels. Each study area represents an area of the country-that experiences unique and relatively critical soil
resource problems.
Using 1982 data, four different program participation classes as specified for the sample as follows:
0
Land operated by individuals participating in neither commodity nor
financial and technical assistance conservation programs.
0
Land operated by individuals participating only in commodity programs.
0
Land operated by individuals participating only in financial or technical
assistance conservation programs.
0
Land operated by individuals jointly participating in both commodity
and financial or technical assistance conservation programs.
14




STUDY AREAS ARE NOT REPRESENTATIVE OF THE UNITED STATES
The areas of the country that were sampled for purposes of the USDA Program Consistency Study are among those that have the most severe
soil erosion problems. Consequently, the erosion and land use
characteristics of the study areas differ from national averages for
erosion and land use.
0 The 1982 average annual soil erosion-rate estimated for
cropland samples in the study area (11.4 tons per acre
per year) is 56 percent greater than the average rate of cropland erosion nationwide (7.3 tons per acre per
year) (4).
0
While 50.5 percent of U.S. cropland is designated by SCS
as being subject to erosion hazard (categorized in SCS
land capability subclass e), a greater proportion of cropland in the study area sample (61.3 percent) is
classified as erosion prone.
0
The average size of farms sampled in the study areas is
1,187 acres, which is 2.7 times larger than the national
average of 433 acres.
Program participation characteristics also differ between the study
areas and the Nation. For instance, 45 percent of the study area
was enrolled in 1982 commodity programs as compared with the national
average of 23 percent of total cropland reported by ASCS as having
been enrolled in 1982 commodity programs. Because of these differences, results specific to the study areas cannot be applied to the Nation as a
whole.
Figures 3-10 describe the study areas sampled and summarize area-specific findings regarding commodity program participation, farm-type distribution, land capability classes, and soil erosion. The study areas differ in many respects. Wheat is the principal crop in the Columbia Plateau and Palouse area. Operators in the north-central study areas are primarily livestock and grain producers, and the southeastern study areas farmers are more diversified. In the study area sample, average estimated erosion rates range from a high of 30.7 tons per acre per year in the Southern High Plains to a low of 6.3 tons per acre per year in the Southern Coastal Plains. Program participation patterns vary greatly among the study areas. In the Southern Piedmont, roughly half of the sample points fall on land of individuals who do not participate in either commodity or conservation programs. By contrast, nearly all land sampled in the Southern High Plains is operated by commodity program participants. Program participation patterns for the entire sample are reviewed below.
Program Participation
Commodity program participation data assembled from the eight study areas reflect the popularity of the programs in 1978, 1982, and 1983 (table 5). While 1978 showed moderate commodity program participation rates, 1982 showed relatively low participation, and 1983 showed high program participation. Operators of land
15




Figure 3
Columbia Plateau and Palouse and Nez Perce Prairies
" Area located in Northwestern Wheat and Range Program Participation Pattern
Region. ______________________" More than 80 percent of study area land is In farms Program 1978 1982 1983
and ranches. participation
" About half of agricultural land Is cropland. Percent
" Principal production activity is dryland wheat. Neither program 57.8 41.9 29.1
* Average farm size is 3,035 acres. Average estimated soil erosion rate Is 7.25 tons per Commodity
acre per year. only 30.3 42.8 50.3
Conservation
Farm Types only 4.4 3.4 3.1
Percent Both program
types, jointly 7.5 11.9 17.5
Cash grain 78.4
Land Capability Class Distribution
Class Percent
Combination 1 1.0D
livestock 18.4
and grain 11 14.7[j
111 42.8
Livestock 2.2 IV 36.3
V ol
Miscellaneous 1.9VI 1.
16




Figure 4
Central High Plains and Upper Arkansas Valley Rolling Plains
" Area is located in Western Great Plains region. Program Participation Pattern
" Most of study area is in farms and ranches. About 65 percent of agricultural land is in range of Paoriation 98 18
native grasses grazed by cattle and sheep. participation_________________" About 20 percent of agricultural land Is dry-farmed to Percent
wheat and other grains. Neither
* Average farm size is 2,343 acres. porm3. 873.
" Average estimated soil erosion rate is 7.25 tons per Commodity
acre per year. only 51.3 39.1 54.8
Conservation
Farm Types only 2.3 4.2 2.7
Percent Both program
types, jointly 12.6 8.0 2.9
Cash grain 55.6
Land Capability Class Distribution
Class Percent
Combination 1 m.
livestock 36.4I 8.[ j
and grain 11295
111I 29.5 1
Livestock 5.7 LiIV 26.81
V 01
VI 4.6
Miscellaneous 2.3UVIi ]
17




Figure 5
Southern High Plains
* Area Is In Central Great Plains region. Program Participation Pattern
* Almost all of study area is In farms and ranches. More than 40 percent of land area Is range of Program 17 9218
native grasses and shrubs grazed by beef cattle. participation 17 9218
" About one-third of land area Is dry-farmed, nearly Neither Percent
one-third is irrigated, program 1.0 1.0 0.7
* Principal crops are winter Wheat, grain sorghum, and Commodity
cotton. only 55.3 48.0 48.3
" Average farm size Is 1,j322 acres: osrvto
" Average -estimated erosion rate Is 30.71 tons per only 0 1.3 0
acre per year. Bt rga
types, jointly 43.7 49.7 51.0
Farm Types
Percent Land Capability Class Distribution
Cash grain 14.0 Class Percent
1 01
Combination 11 38.21
livestock 44.7 111 50.51
and grain L .JIV 9.6 E~
IV 01
Cotton farms 41.3 IVI 1.30
I I Vii 0.31
18




Figure 6
Loess Uplands and Till Plains and Nebraska and Kansas Loess-Drift"Hills
" Area is in the Central Feed Grains and Livestock Program Participation Pattern
region._______________________ __" Most of study area Is in farms, and 60-70 percent Program 1978 1982 1983
is cropland. participation
" Corn, soybeans, and other feed grains are the Percent
principal crops grown; much of crops grown is fed Neither
to beef cattle and hogs on farms where It Is grown. program 30.6 53.3 2&.4
" Average farm size Is 322 acres.Comdt Average estimated erosion rate is 8.1 tons per acre only 47.8 25.8 45.0
per year.
Conservation
Farm Types only 8.6 14.8 4.8
Percent Both program
types, jointly 13.1 6.2 24.7
Cash grain 21.6
Land Capability Class Distribution
Class Percent
Combination 1 17.31
livestock 77.3 11 36.01
and grain -[il3.
IV 12.81~
DV 01
Miscellaneous 1.1 Vi 1.00
UVii 01
19




Figure 7
Iowa and Missouri Deep LoessHllls
" Area is in the Central Feed Grains and Livestock Program Participation PatteM
region.
* Most of the area is in farms, and about 60 percent, Program
is cropland, about 20 percent of the area is in participation 1978 1982 1983
permanent pasture.
" Corn, soybeans, and hay are the principal crops. Neither Percent
" Beef cattle and hog production are important, program 41.8 45.1 17.8
enterprises on many farms in the area.
* Average farm size is 414 acres. Commodity
only 27.0 24.7 44.7
" Average estimated erosion rate Is 18 tons per acre
per year. Conservation
only 18.1 19.7 8.2
Farn Types Both program
Percent types, jointly 13.2 10.5 29.3
Cash grain 28 Land Capability Class Distribution
Class Percent
1 8.6
Combination II 41.4
livestock 72
and grain
III 42.8
IV- 5.9 L7
V 01
VI 1.3fl
VII 01
20




Figure 8
Southern Coastal Plain
" Area Is In the South Atlantic and Gulf Slope Program Participation Pattern
region.______________________ __* The area is about 69 percent woodland, 17 percent Program
cropland, 11 percent pastureland, and about 3 participation
percent urban and other land uses.Pecn
" Cash crops include soybeans, c orn, peanuts and NeitherPecn
cotton. program 55.5 44.1 30.3
" Average farm size is 925 acres. Commodity
" Average estimated erosion rate for cropland is 6.26 only 18.0 24.1 33.0
tons per acre per year. Cnevto
only 12.1 17.5 11.0
Farm Types Both program
Percent types, jointly 14.5 14.3 25.7
Cash grain 53.1
Combination r--~Land Capability Class Distribution
livestock 18.2 [
and grain Class Percent
Livestock 4.4 D1 7.2 =
Cotton 2.70 11 57.51 _--111 18.5
Other 14.9 IV 10.6
field crops L..........JV 1.2 0
VI 6.4
Miscellaneous 6.6DF VII 3.2E
21




Figure 9
Southern Mississippi Valley Silty Uplands
d
" Area Is in the South Atlantic and Gulf Slope Program Participation Pattern
region.
" Most of the area Is in farms; about 46 percent of Program 1978 1982 1983
land area is In forests; 35 percent Is cropland; and participation
16 percent Is In pasture or hay.
" Urban development Is Infringing on farmland In some Neither Percent
locations; In other locations, pasture and forests program 51.7 41.5 31.8
are being converted to cropland.
" Cash-cropping of cotton, corn, soybeans, and wheat Commodity
are major enterprises; feed grains and forage are only 19.6 15.7 23.2
grown on dairy farms.
" Average farm size Is 984 acres. Conservation
only 15.5. 20.4 15.3
" Average estimated erosion rate Is 9.88 tons per acre
per year. Both program
types, jointly 13.2 22.4 29.7
Farm Types
Percent Land Capability Class Distribution
Cash grain 68.6 Class Percent
Combination 1 4.3
livestock 4.1 11 49.1
and grain
111 32.6 1
Livestock 9.6 IV 8.0
Cotton 15.3 V 3.70
V1 2.10
Miscellaneous 2.4 VII 0.21
22




Figure 10
Southern Piedmont
" Area is in the South Atlantic and Gulf Slope region. Program Participation Pattern Area is characterized by small farms and
considerable residential development; sizeable Program 1978 1982 1983
acreage is wooded. participation
" Most of the open land is pasture, but some Percent
soybeans, small grain, corn, cotton, wheat, and Neither
tobacco are grown. program 55.6 57.3 47.6
" Average farm size is 329 acres. Average estimated erosion rate Is 9.29 tons per Commodity
acre per year. only 10.5 7.0 11.9
Conservation
Farm Types only 19.6 26.0 23.2
Percent Both program
types, jointly 14.4 9.7 17.3
Cash grain 32.4
Land Capability Class Distribution Class Percent
Combination
livestock 27.6 0
and grain 11 55.7
111 31.3 1
Livestock 23.8 IV 9.7
V 0.5
Miscellaneous 16.2 VI 2.70
Vil 0
23




sampled in the critical resource study areas had a higher rate of commodity program participation than the Nation as a whole. In 1978, 35 percent of U.S. farmers were enrolled in commodity programs, but 46 percent of farm operators in our sample participated in 1978 commodity programs. National commodity program participation was 19 percent in 1982, compared with our sample's participation rate of 45 percent.
Conservation program participation by farm operators in the eight study areas seems to have increased between 1978 and 1983. Conservation program participation rates for the sample population were 26.4, 31.1, and 35.1 percent for 1978, 1982, and 1983, respectively. In all three sample years, most conservation program participants (62, 55, and 75 percent for 1978, 1982, and 1983, respectively) also participated in commodity programs.
Bayes Theorum. is used to examine the expected overlap of commodity and conservation program participation. 7/ Given that a farm participated in commodity programs, the probability that it also participated in a conservation program is 35, 38, and 41 percent for 1978, 1982, and 1983, respectively. By contrast, the probability that a farm was involved in conservation programs given that it was not involved in commodity programs is 19, 25, and 25 percent for 1978, 1982, and
1983, res 'pectively. This suggests that commodity program participants are more inclined to participate in conservation programs than are other farm operators. Similarly, conservation program participants are more likely to participate in commodity programs than are those who do not participate in conservation programs. These findings suggest that the two program types are complementary.
Commodity and conservation program-participation rates vary greatly by farm type. Within the study areas, cotton has the highest commodity program participation rate; nearly 100 percent of sampled cotton farms participated in commodity programs. The second highest commodity program participation rate from the sample is for farms classified as "other field crop farms." Almost all of these farms are located in the Southern Coastal Plains and produce a mixture of peanuts, soybeans, corn, and wheat. The commodity program participation rate for "other field crop farms" is over 50 percent for all three sample years. Also in relatively high commodity program participation categories are cash grain farms and combination livestock and grain farms. Commodity program participation is relatively low among sampled farms classified as "specialty and miscellaneous farms." These farms are not represented in commodity programs because of the crops produced on such farms, only tobacco has a commodity program. Almost none of the sampled farms classified as "livestock farms or ranches" participated in commodity programs. This is to be expected since there are no programs for cattle or hog operations, the primary livestock production activities in the sample study areas. Conservation program participation is highest for "other field crop farms," ranging between 26 and 35 percent for other sampled farm types in all three sample years. Table 6 shows 1982 program participation by farm type and serves as an illustration of variation among farm types.
7/ Bayes Therum tells us that:
Pr (RIC) Pr(RflC)
Pr (C)
Where: Pr (RIC) is the probability that a farm participates in conservation programs (R), given that it participates in commodity programs (C); Pr (RflC) is the proportion of farms participating jointly in commodity and conservation programs; and Pr(C) is the proportion of farms participating in commodity programs.
24




The sample data reflect national variation in program participation by farm size (table 7). Nonparticipants' average farm size is significantly smaller than that for farms participating in either program type. Average cropland acreage is significantly larger for commodity program participants than for nonparticipants.
Finally, commodity and conservation program participation rates vary among the study areas sampled. This variation, illustrated by comparison of information in area-specific figures 3 to 10, is primarily a function of the distribution of farm types and farm sizes among the study areas, but may partially be explained by differences in regional preferences for participation. For example, the consistently high commodity program participation rates observed for the Southern High Plains are due in large part to the fact that over 40 percent of sample observations from that study area are cotton farms. However, the finding that over 98 percent of grain farmers in the Southern High Plains participate in commodity programs (versus less than 50 percent for the total sample) indicates a regional preference for participation. The Southern Piedmont, which has the lowest program participation rates, also has the smallest average farm size.
Soil Erosion Rates
Soil erosion rates obtained for sample points are those estimated by SCS on a subset of sites sampled for that agency's 1982 National Resources Inventory. Sheet and ril erosion were estimated by SCS by use of the Universal Soil Loss Equation (USLE). Wind erosion is estimated by the wind erosion equation (WEE). Our erosion data relating to each sample point was restricted to the sum of sheet and rill plus wind erosion. We did not obtain values of the specific USLE or WEE components.
We assume, for analytical purposes, that the point sampled for erosion is representative of the total cropland acreage surrounding the point and farmed by the
Table 6--Study sample program participation rate, by farm type, 1982
Land of operators participating in -Farm type :Neither :Commodity :Conservation : Both :Total
program : program only :program only :programs:
Percent
Cash grain farms 45.8 26.6 13.4 14.2 100
Cotton farms 1.0 64.4 2.3 32.4 100
Other field crops 1/ 27.9 17.1 12.6 42.3 100
Livestock farms and
ranches 65.5 1.4 31.0 2.1 100
Combination livestock and grain
farms 40.6 27.0 15.3 17.1 100
Specialty and miscell~aneous 2/ 55.3 18.4 13.6 12.6 100
Note: Totals may not add due to rounding.
1/ Includes sugar, potatoes, and peanuts, among other field crops.
2/ Tobacco; vegetable and melon; fruit, berry, and nut; tree farms; and other miscel lane ous farms.
25




operator on whose cropland the point falls. While this assumption will not hold true for individual landholdings, the number of samples obtined for a given MLRA or farm type is sufficiently large for the assumption to be reasonable when aggregated to the level of an MLRA or farm type.
The average 1982 estimate of sheet and rill plus wind erosion obtained from study area sample points is 11.4 tons per acre per year (TAY). This estimate is higher than the national average erosion rate for cropland (7.3 TAY) obtained from analysis of the full 1982 NRI data set (4). The difference is explained by the origin of this study's sample points--they are derived from areas of the country that have the highest erosion rates.
Soil erosion estimates vary significantly among farm types (table 8). Average erosion rates are highest for points sampled from cotton farms. Sample points from cash grain and combination livestock and grain farms have the next highest rates of erosion in the eight study areas. These farms produce most of the corn, soybean, wheat, and small grains represented in the sample. Points from "other field crop farms" exhibit a moderate rate of erosion. Sample average estimated erosion rates in the critical erosion study areas are near the 5-TAY level only on livestock farms and ranches and specialty and miscellaneous farms.
Average estimated erosion rates vary among study areas (table 9). This variance is due both to differences in the physical and climatic characteristics of the
Table 7-Average farm size and cropland acreage for sample farms, by program
participation category, 1982
Program participation Average farm Average cropland
category size 1/ per farm 1/
Acres
Land of operators participating
in neither commodity nor conservation programs 835.2 B 450.4 B
Land of operators participating
only in commodity programs 1,400.6 A 932.6 A
Land of operators participating
only in conservation programs 1,425.0 A 502.7 B
Land of operators participating
in both program types 1,495.3 A 875.6 A
Total sample 1,187.1 663.8
1/ Numbers followed by the same letter in a given column exhibit no statistically significant differences from one another at a 95-percent confidence level. (For example, under the "Average cropland per farm" column, the 932.6- and 875.6-acre averages are not statistically different from one another; neither are the 450.4- and 502.7-acre averages significantly different from one another. However, the two averages followed by the letter "A" are significantly greater than the two averages followed by the letter "B.")
26




Table 8--Estimated soil erosion rates for sample points, by farm type from which
points were sampled, 1982
Farm type Average soil erosion rate
Tons per acre per year 1/
Cotton farms 33.6 A
Combination livestock and grain farms 11.3 B
Cash grain farms 9.4 B,C
Other field crop farms 2/ 6.0 C,D
Livestock farms and ranches 5.0 D
Specialty and miscellaneous 3/ 4.9 D
1/ Numbers followed by the same letter exhibit no statistically significant differences at a 95-percent confidence level. (For example, the average rate for cotton farms is significantly greater than average rates from any other farm type. The average rate from combination livestock and grain farms is not significantly different from the average obtained for cash grain farms, but it is significantly greater than the average rate for other field crop farms.)
2/ Includes sugar, potatoes, and peanuts.
3/ Tobacco; vegetable and melon; fruit, berry, and nut; tree farms; and other miscellaneous farms.
Table 9--Estimated soil erosion rates for sample points, by study area, 1982
Study area Average soil erosion rate
Tons per acre per year 1/
Southern High Plains 30.7 A
Iowa and Missouri Deep Loess Hills 18.0 B
Southern Mississippi Valley Silty Uplands 9.9 C
Southern Piedmont 9.3 C,D
Central High Plains and Upper Arkansas Valley
Rolling Plains 8.7 C,D
Loess Uplands and Till Plains and Nebraska
and Kansas Loess-Drift Hills 8.1 C,D
Columbia Plateau and Palouse and Nez Perce
Prairies 7.5 C,D
Southern Coastal Plains 6.3 D
1/ Numbers followed by the same letter exhibit no statistically significant differences from one another at a 95-percent confidence level. (For example, the average rates for the Southern Mississippi Valley Silty Uplands and the Southern Coastal Plains are significantly different from one another. However, neither of these is significantly different from the rates shown for study areas listed between them in the soil erosion rate column.)
27




study areas and differences in crop production patterns. Table 10 shows erosion rates by farm type and study area. Several things are suggested by this tabular
information:
" Production of livestock or specialty and miscellaneous crops results in
relatively low rates of soil erosion regardless of the region in which
production takes place.
" Where production is concentrated in cash grain and combination livestock
and grain operations (Columbia Plateau and Palouse; Central High Plains; and study areas in the north-central region), erosion rates do not vary
significantly among the farm types that were sampled.
" Differences in average estimated erosion rates from samples on cash
grain and combination livestock and grain farms reflect regional
differences in erosion.
" Erosion rates for samples from cotton farms are significantly higher
than those from other farm types in every study area where cotton is
grown. Cotton.farm samples exhibit highest erosion rates in the
Southern High Plains, where wind erosion presents a greater threat
than in any other area where cotton is produced.
" Average soil erosion rates obtained from specialty and miscellaneous farm
samples are lower than those for any other farm types in the Southern
Coastal Plains and Southern Mississippi Valley Silty Uplands. But that
observation is not true in the Southern Piedmont where many of the
specialty farms grow tobacco.
Relationships Between Program Participation and Soil Erosion in Critical Resource Areas
Average estimated soil erosion rates from land of sample operators participating in commodity programs are significantly higher than rates observed for land of those who participate only in conservation programs or for that of those who participate in neither program. However, erosion levels by farm type do not differ significantly among categories of program participation (table 11). Erosion rates for a given farm type are similar for 1982 regardless of whether the operator participated in a commodity program in 1982. Theone exception is for the farms raising "other field crops," where erosion rates for the land of those who participated solely in conservation programs are significantly higher than erosion rates for farmland of those in other groups. This may be because field crop farmers with severe erosion problems seek or are more receptive to assistance in conserving soil.
only in the Southern Coastal Plains and Southern Mississippi Valley Silty Uplands are there significant differences in erosion rates among categories of program participation (table 12). These two study areas have the greatest diversity in farm types. When erosion rates for these study areas are further broken down by farm type, again there is no difference in erosion rates among categories of program participation.
Large differences in inherent erodibility of cropland and in crop production practices exist among study areas, and commodity program participation also varies by farm type and study area. These data imply that location and type of crop production have a greater effect on soil erosion than any other variable
28




Table 10--Estimated soil erosion rate, by study area and farm type, 1982
Average soil erosion rate from sample points on-Study area : : : Specialty : Other:Livestock:Combination
:Cash grain:Cotton: and : field: farms : livestock
farms : farms:miscellaneous: crop : and : and grain farms : farms: ranches : farms
Tons per acre per year 1/
Columbia Plateau and
Palouse and Nez
Perce Prairies 2/ 7.1 C 3/ 2.3 A 3/ 2.0 A 8.6 C
Central High Plains
and Upper Arkansas
Valley Rolling
Plains 2/ 7.9 C 3/ 1.7 A 3/ 2.7 A 10.1 B,C
Southern High
Plains 4/ 25.4 A 50.6 A 3/ 3/ 3/ 14.0 A,B
Loess Uplands and
Till Plains and
Nebraska and Kansas
Loess-Drift Hills 2/ 8.3 C 3/ 3/ 3/ 3/ 8.1 C
Iowa and Missouri
Deep Loess
Hills 2/ 16.3 B 3/ 3/ 3/ 3/ 18.7 A
Southern Coastal
Plains 4/ 6.5 C 9.2 B 4.6 A 6.1 6.0 A 5.8 A
Southern Mississippi
Valley Silty
Uplands 4/ 10.1 C 12,2 B 4.4 A 3/ 5.8 A 10.9 B,C
Southern
Piedmont 5/ 15.3 B 3/ 6.9 A 3/ 4.7 A 7.6 C
1/ Mean erosion values followed by the same letter in a farm type column are not significantly different from one another at the 95-percent confidence level.
2/ Mean erosion values for farm types within study area exhibit no statistically significant differences from one another at the 95-percent confidence level.
3/ One or no observations of specified farm type in specified study area.
T/ Erosion from points sampled on cotton farms is significantly higher than that sampled from other farm types in the Southern High Plains, Southern Coastal Plains, and Southern Mississippi Valley study areas.
5/ Erosion from points sampled on cash grain farms is significantly higher than that sampled from other farm types in the Southern Piedmont.
29




Table 11--Estimated soil erosion rates for study sample points, by program participation category and
farm type, 1982
* Average soil erosion rate on land sampled from-- :Average,
Program participation Specialty : Other :Livestock :Combination:all farm
* Cash and : field farms : livestock : types
: grain : Cotton :miscellaneous: crop and : and grain :
: farms : farms farms 1/ farms ranches farms
Tons per acre per year 2/
Operators participating
in neither commodity 9.5 A 3/ 4.9 A 5.6 B 5.2 A 10.7 A 9.2 B
nor conservation programs
Operators participating only
in commodity programs 9.3 A 36.5 A 4.3 A 4.2 B 3/ 11.9 A 14.7 A
Operators participating only
in conservation programs 8.9 A 3/ 4.1 A 11.2 A 4.9 A 11.8 A 9.4 B
Operators participating
in both program ty1Pes 9.6 A 30.7 A 6.8 A 5.6 B 3/ 11.4 A 12.8 A
1/ Includes tobacco; vegetable and melon; fruit, berry, and nut; and tree farms as well as other miscellaneous farm types.
2/ Mean erosion values followed by the same letter in a farm-type column exhibit no statistically significant differences from one another at the 95-percent confidence level.
3/ Less than 3 percent of farm types sampled fell in specified program participation category.




Table 12--Estimated soil erosion rates for study sample, by program participation category and
study area, 1982
Average soil erosion rate from major land resource area :Average,
Program participation :8 & 9: 67 & 69 77 : 102B : 107 133A : 134 136 :all study
: & 106 :: : :areas
Tons per acre per year 1/
Land of operators
participating in
neither commodity
nor conservation 6.9 A 8.1 A 2/ 9.3 A 17.9 A 6.5 A,B 10.0 A,B 9.1 A 9.2 A
programs
Land of operators
participating only
in commodity 8.4 A 9.0 A 38.8 A 7.7 A 18.7 A 5.8 A,B 12.2 A 11.1 A 14.7 B
programs
Land of operators
participating only
in conservation 5.4 A 5.5 A 2/ 5.4 A 19.4 A 7.6 A 9.5 A,B 7.7 A 9.4 A
programs
Land of operators
participating in
both program types 4.9 A 13.0 A 24.1 A 5.8 A 14.2 A 4.7 B 8.3 B 13.4 A 12.8 B
1/ Mean erosion values followed by the same letter within a single MLRA column exhibit no statistically significant differences from one another at the 95-percent confidence level. (See table 2 for identification of MLRA's.)
2/ Less than 2 percent of study area sample falls in specified program participation category.




considered in this study. The crop type and location factors completely override any contribution of participation in either or both commodity and conservation technical or financial assistance programs in explaining erosion from cropland in critical erosion areas.
Who Contributes to the Soil Erosion Problem?
To the extent that USDA program participants contribute to the cause or to the solution of soil erosion problems, there may be ways to encourage them to further reduce erosion while continuing to enjoy program benefits. For example, commodity program participants might have their benefits reduced if they did not manage croplands so as to conserve soil. However, farmers who are not in USDA programs are not vulnerable to the exertion of financial leverage as a way to influence
soil conservation.
Farm operators can be classified into eight groups with respect to their vulnerability to and target potential for policies to integrate commodity and conservation programs. Operators in each of the four previously defined program participation categories are further categorized on the basis of whether erosion rates for their land meet or exceed the tolerance level or 5 tons per acre per
year (table 13).
Tables 13-15 show that in the critical resource study areas:
oMore than half of the sampled cropland erodes at rates greater than 5
tons per acre per year. (only about 34 percent of total U.S. cropland
erodes at rates above that level.)
Table 13--Participation in USDA commodity and conservation programs in critical
resource study areas, by soil erosion levels, 1982 1/
:Land eroding at rates : Land eroding at rates :Total Program participation : less than 5 tons per :of 5 or more tons per : all :acre per year :acre per year :cropland
Percent of total sample
Land of operators participating in neither commodity
nor conservation programs 19.0 22.1 41.1
Land of operators participating in commodity
programs only 11.6 16.2 27.8
Land of operators participating in conservation
programs only 7.1 7.0 14.1
Land of operators participating in both commodity
and conservation programs 8.0 9.0 17.0
Total 45.7 54.3 100.0
I/ See app. table 10 for distribution among more finely detailed soil erosion classes.
32




-- Almost 62 percent of 1982 cropland eroding at rates above 5 TAY was
operated by individuals participating in USDA commodity and/or financial
or technical assistance conservation programs in that same year.
-- The other 38 percent of operators of land eroding above 5 TAY
participated in neither commodity nor financial or technical assistance
conservation programs.
In the critical resour ce areas studied, land eroding above and below 5 TAY is distributed fairly evenly between the commodity and conservation program participation categories. Concurrent participation of commodity program participants in conservation programs is only slightly higher (41 percent) on land eroding at or below 5 TAY than on land eroding above 5 TAY (37 percent). Table 13 also shows that in the study areas:
0About 40 to 45 percent of the cropland sampled is operated-by commodity
program participants (some of whom also are conservation program
participants).
-- Of the land operated by commodity program participants, 58 percent
erodes above 5 TAY!.
Table 14--Participation in USDA commodity and conservation programs for
cropland eroding at or above 5 tons per acre per year in critical
resource study areas, 1982
:Cropland eroding at rates of Program participation :5 or more tons per acre per year
_____: in critical resource study areas
Percent
Land of operators participating
neither in commodity nor conservation
programs 38
Land of operators participating in
commodity programs only 28
Land of operators participating in
conservation programs only 16
Land of operators participating in
both commodity and conservation
programs 18
Total 100
33




-- 42 percent of commodity program participants maintain rates of
erosion at or below 5 TAY, even though the majority of these
operators do not also participate in financial or technical assistance
conservation programs.
0 About one-third of the cropland sampled is operated by financial or
technical assistance conservation program participants (some of whom also
are commodity program participants).
-- Of the land operated by financial or technical assistance conservation
program participants, about half erodes at a rate of more than 5 TAY and
half erodes at or below that maximum T level.
Availability of 1982 National Resources Inventory data will permit further classification of USDA program participation by the extent of erosion. It will then be possible to provide estimates of the degree to which land operated by program participants and eroding at excessive rates is either moderately erodible and managed so that erosion is above tolerance or is inherently erodible land placed into cultivation.
FARMER CHARACTERISTICS BY PROGRAM PARTICIPATION AND SOIL EROSION CLASS
Factors other than farm type and region may influence the behavior of farmers with respect to farm programs and soil conservation. This section of the report reviews analyses of the distribution of farm ownership, tenure, off-farm work, loan source, and land capability classes among program participation and soil erosion classes.
Table 15--Participation in USDA commodity and conservation programs for
cropland eroding below 5 tons per acre per year in critical
resource study areas, 1982
Cropland eroding at less than Program participation 5 tons per acre per year in
critical resource study areas
Percent
Land of operators participating neither
in commodity nor conservation programs 41
Land of operators participating in
commodity programs only 25
Land of operators participating in
conservation programs only 16
Land of operators participating in
both commodity and conservation
programs 17
Total 100
Note: Total does not add due to rounding.
34




Program participation classes are the same as those defined previously. Sample results were grouped for analytical purposes according to land falling into classes 8/:
Low rate of erosion = Less than 5 TAY
Medium-low rate of erosion =5-13 TAY
Medium-high rate of erosion =14-24 TAY
High rate of erosion 25 TAY and above
We conducted chi-square statistical tests to determine whether the distribution of selected farm and operator characteristics among operators of land in different soil erosion classes (or program participation classes) are the same as for the whole sample. Differences in the distributions provide clues as to what factors may be related to soil erosion and program participation. Identification of important characteristics also provides information that can be used to describe various groups that could be affected by changes in commodity or conservation programs.
ownership
Individuals or families own 92 percent of the sample farms. Cropland owned by either individuals or families is fairly evenly distributed among program participation and soil erosion classes. Nonfamily partnerships or corporations own 3 percent of the sample farms. These few farms fall with disproportionately high frequency in the lowest and highest erosion classes. Operators of the nonfamily and corporate farms have significantly lower participation in conservation planning and cost-sharing programs, but appear with relatively high frequency in the "commodity program only" participation class. (See app. tables
2 and 3 for details.)
Tenure
Half of the sample farms are operated by the owners. Statistical tests indicate that owner-operators and tenants with long-term leases are similarly distributed among program participation and soil erosion classes. The distribution of these groups contrasts with that of tenants with short-term leases in several ways. First, owner-operators and tenants with long-term leases appear with relatively greater frequency in the low rate of erosion class and with relatively less frequency in the high rate of erosion class than do tenants with annual leases. Owner-operators and tenants with long-term leases are more likely to be participants in conservation .programs only, or to be general program nonparticipants than are tenants with annual leases. These findings lend some support to the theory.that operators with long-term interests in the land tend to better protect and conserve soil resources. (See app. tables 4 and 5 for details.)
8/ Bills and Heimlich find that virtually all of the land estimated to erode
at 25 or more TAY in 1977 fell into their "highly erosive" category, as did 63 percent of the land eroding at 14-2 4 TAY; most of the land eroding at 5-13 TAY fell into their "moderately erosive--managed above tolerance" category; land eroding at less than 5 TAY fell strictly in the "nonerosive" and "moderately erosive--managed below tolerance" categories (1).
35




Off-farm Work
The distributions among off-farm work categories do not significantly differ among soil erosion classes, implying off-farm work is not a determinant of erosion probability. However, differences among program participation categories are highly significant. As time off the farm increases, participation in commodity programs (solely or in conjunction with conservation programs) decreases. (See app. table 6 for details.)
Operator Age
Age seems to be a significant determinant of operator behavior in the sample areas. -With respect to soil erosion, a relatively greater proportion of operators of seriously eroding cropland are 21-40 years old. And a relatively greater-proportion of operators of cropland eroding under 5 TAY are over 50 years old. A possible explanation for this finding is that young operators are less financially able to purchase or rent good farmland. They may, consequently, be operating a greater proportion of marginal, erodible land. Older operators who obtained land at a time-when land prices were lower may be farming better land. With respect to program participation, age differences are highly significant. Operators 31 to 60 years of age are heavier participants in conservation programs (both solely and in conjunction with commodity programs) than the younger and older operators. Participation in commodity programs only is relatively higher in the 21-30 and 61-70 age classes. Operators over 70 years of age are far more likely to be program nonparticipants. (See app. tables 7 and
8 for details.)
operating Loan Source
The principal source of operating loans is unknown for 40 percent of the sample population. Of the remaining sample, operators whose primary source of operating loans is FmHA or the Production Credit Association (PCA) fall with relatively greater frequency in the group whose land has a high rate of erosion than do those who borrow primarily from commercial banks and insurance companies. This finding suggests that FmHA and PCA may be providing credit for operators whose land is more highly erodible, who plant high percentages of their land to erosive crops, or who are less able to invest in conservation measures. (See app. table 9 for details.) Differences in principal loan sources among program participation classes suggest only that FmHA- and PCA-financed operators are more likely than others to be in commodity programs. There is no evidence to suggest that commercial banks are more likely to lend to operators who participate in commodity programs. Operators borrowing primarily from commercial banks and insurance companies are evenly distributed among program participation categories.
Land Capability Class and Subclass
Our study data lend some support to the theory that commodity program benefits encourage cultivation of marginal, erodible cropland. At least that appears to be the case in the sample areas. Erodible cropland, with the greatest erosion hazard, defined either as all cropland in land capability subclass e, or all cropland in land capability classes 4e, 6e, and 7, is represented at a greater than proportionate level in the "commodity program only" participation class. This holds true for 1982 and 1983, but it is more pronounced in 1982. (See app. tables 11 through 14 for details.)
36




The effect on soil erosion of relatively higher program crop production on erodible lands is not clear. Table 16 shows average estimated erosion rates by program participation category and land capability class. In land capability classes II, III, and IV, average erosion rates are significantly higher for sole commodity program participants. This, again, is a function of the fact that program crops tend to be more erosive than other commodities. It implies that the distribution of program crop production among land classes may have an important effect on soil erosion.
SUMMARY AND IMPLICATIONS
USDA influences farmer decisions to produce or not produce particular commodities through credit, crop insurance, commodity, and other agricultural programs Federal programs outside USDA, such as tax provisions, further influence farmers' choices regarding type and intensity of operation. Along with general economic conditions, each of these factors affects what is produced, how agricultural land is used, and, consequently, the amount of soil erosion on agricultural land.
The availability of commodity program benefits, in particular, may make the production of certain crops more attractive to farmers. Farmers who are in debt or face a cost-price squeeze are especially likely to be attracted to the advantages of producing program crops. Because program crops are relatively more erodible than other production activities, increased soil erosion may unintentionally result from farmers' response to farm program incentives.
Any commodity or conservation technical or financial assistance program change designed to make the goals of price support and farm income more consistent with soil conservation objectives would primarily affect the farm operators who participate in the programs. The size and characteristics of potentially affected groups have important implications for the success of program integration efforts.
In the critical resource areas of the United States, more than half of the cropland eroding above 5 TAY is cultivated by participants in either USDA conservation financial or technical assistance or commodity programs or both. Thus, program changes could have a positive effect on a major portion of the erosion problem in these areas.
Various groups of operators in critical resource areas could be affected by program changes. Changes in commodity program provisions or policies applying to highly erodible cropland would have a greater relative effect on nonfamily and corporate farms than on family-owned farms in generally erodible areas of the country. Similarly, changes in approaches to commodity program implementation and erosion problems would have a relatively greater effect on short-term tenants than on owner-operators or long-term tenants in the critical erosion s 'tudy areas. Changes in conservation programs will affect mainly middle-aged owner-operators and long-term tenants, the most predominant participants in conservation programs in these areas. The age distribution of U.S. farmers is highly skewed to older individuals. The few young individuals currently operating farms would be relatively more affected by changes in commodity programs or policies aimed at soil conservation in critical erosion areas than would middle-aged or older farmers.
Both the proportion of land eroding above tolerance and the percentage of cropland operated by commodity program participants are greater in the critical resource study areas than in the rest of the country. Because the critical
37




Table 16--Estimated erosion rates for consistency study sample, by land capability class and program
participation category, 1982
Program participation Average erosion rate for land capability class 1/
I II III IV V VI VII
Tons per acre per year 2/
Land of operators participating in
neither commodity nor conservation
programs 4.1 A 6.4 B,C 12.2 B 11.9 B 2.8-A 21.4 A 14.0 A
Land of operators participating in
commodity programs only 4.4 A 8.6 A 17.9 A 23.2 A 1.0 A 24.0 A 15.1 A
Land of operators participating in
conservation programs only 3.4 A 5.9 C 11.8 B 20.9 A,B 5.4 A 20.9 A 29.0 A
Land of operators participating in
both commodity and conservation
programs 3.8 A 7.7 A,B 14.8 A,B 18.1 A 2.1 A 28.4 A --- = No observations.
I/ The SCS land capability classification system groups soils at several levels. The capability
class, designated by Roman numerals, indicates progressively greater limitations and narrower choices for land uses. Capability class I has the least limitations, and VII represents the class of soils with greatest limitations.
2/ Average values followed by the same letter within the column exhibit no statistically significant differences from one another at the 95-percent confidence level.




r source areas are targeted for extra conservation cost-share funding and technical assistance, these areas also are likely to contain a greater proportion of conservation program participants than many other areas of the country.
Table 17 shows the approximate number of acres known to have been in commodity programs in 1982 and those eroding above 5 TAY in the study area and in the Nation. Assumptions regarding the distribution of cropland eroding above 5 tons per acre per year among program participation categories (table 17) are made on the basis of national statistics and the relationships observed from the study areas.
The assumptions shown in table 17 are derived from 1982 information on commodity program participation. To compensate for the fact that commodity program participation rates vary significantly from year to year, we assume a 20-percent standard deviation is associated with the average rates shown in table 17. This series of assumptions leads us to conclude the following:
" Roughly 40 to 65 million acres of U.S. cropland eroding above 5 tons per
acre per year are operated by participants in USDA commodity or conservation financial and technical assistance programs or both.
" Between 75 and 110 million acres of cropland eroding at rates greater
than 5 tons per acre per year are operated by individuals who participate in neither commodity nor conservation financial and technical
assistance programs.
" Roughly 65 to 105 million acres of U.S. cropland eroding at rates
below 5 tons per acre per year are operated by USDA program participants.
" Between 150 and 230 million acres of U.S. cropland eroding at rates
below 5 tons per acre per year are operated by individuals participating
in neither USDA commodity nor conservation financial and technical
assistance programs.
These figures are very rough estimates. They are based on deductive logic rather than on the basis of a probability sample. While the absolute values should not be too literally interpreted, the relative magnitude of values in each group is useful in examining the extent to which soil erosion problems might be addressed through program modifications. 9/
Between one-fourth and one-half of the total erosion apparently could be addressed through modifications in USDA commodity or conservation financial and technical assistance programs or both. Barriers to designing conservation-oriented program changes include the need to assure that the programs will be relatively low cost and that they will not impair farm income, commodity price, production, or export objectives.
In a given year, from 45 to 80 percent of the cropland enrolled in prevailing USDA conservation and commodity programs may be maintained so that soil erosion rates are under 5 tons per acre per year. This outcome, like the proportion of program participants whose land erodes above tolerance, varies from year to year
9/ Values reported here differ from preliminary estimates published earlier in the Journal of Soil and Water Conservation due to the later availability of better data on regional and national ASCS commodity program participation rates.
39




Table 17--Assumed quantities of cropland acreage by-program participation,
soil erosion levels, and proportions of cropland in and outside
of study areas
* Study : All other : United States
Cropland groups areas : areas
* (A) : (B) (C)
Million acres
Total cropland 55 366 421
Cropland eroding above
5 tons per acre per year 1/ 30 2/ 114 3/ 144
Cropland in 1982 commodity
programs 1/ 25 2/ 72 4/ 97
Cropland in 1982 commodity
programs and eroding above
5 tons per acre per year 1/ 14 5/ 22 6/ 36
Approximate acres in
Conservation Technical
Assistance Targeted Areas 50 84 134
Cropland in 1982 conservation
programs 1/ 17 7/ 73 6/ 90
Cropland in 1982 conservation
programs and eroding above
5 tons per acre per year 1/ 9 8/ 23 6/ 32
Cropland in either or both
program type 1/ 32 9/ 105 6/ 137
Cropland in either or both
program type and eroding 1/ 18 5/ 8/ 33 6/ 51
above 5 tons per acre
per year
I/ Based on percentage observations from study.
~/Value in column A subtracted from value in column C.
~/Source: (9)
~/source: Airicultural Stabilization and Conservation Service
5/ Assumes land of commodity program participants is distributed among land eroding above and below 5 tons per acre per year in same proportions as land is generally distributed. (This holds true for the study areas.)
6/ Value in column A plus value'in column B.
f/ Assumes conservation program participation is twice as high on targeted acreage as on nontargeted acreage.
8/ Assumes land of conservation program participants is distributed among
land eroding above and below 5 tons per acre per year in same proportion as land is generally distributed. (This holds true for the study areas.)
9/ Assumes the same Bayes probability of commodity program participation given conservation program participation in nonstudy areas as was determined for study
areas.
40




according to program availability, provisions, and participation rates. The intermittent nature of some commodity programs and consequential variance in program participation rates pose additional problems regarding the potential effectiveness of conservation-oriented program changes.
Finally, operators of from one-half to three-fourths of cropland eroding above the 5-ton-per-acre maximum tolerance level do not participate in USDA commodity or conservation financial or technical assistance programs. These farmers would not be directly influenced by program changes designed to reduce erosion. They might, however, be influenced by State or local programs.
Because there are differences among the characteristics of farmers participating
in various programs and operating different types of land, program changes could have differential effects on large and small, young and old, or family and nonfamily farmers. Program alternatives for reducing inconsistencies between farm programs and conservation goals need to be specifically formulated, their costs estimated, and their effects on soil erosion, agricultural production, and farm income estimated before the feasibility or desirability of any one option can be judged.
41




REFERENCES
1. Bills, Nelson L., and Ralph Heimlich. Assessing Erosion on U.S. Cropland:
Land Management and Physical Features. AER-513. U.S. Dept. Agr., Econ. Res.
Serv., July 1984.
2. Huszar, Paul C., Kenneth Nobe, and John E. Young. "Policy Assessment and
Implications of the Grasslands Plowout Problem in Eastern Colorado,"
Proceedings of Howard E. Conklin Conference on Rural Land Use and Public
Policy, Ithaca, NY: Cornell Univ., 1984.
3. Johnson, James D., and Sara D. Short. Commodity Programs: Who Has Received
the Benefits? Paper presented at 1983 annual meeting, American Agricultural
Economics Association, West Lafayette, IN, Aug. 1983.
4. Lee, Linda K. "Land Use and Soil Loss: A 1982 Update," Journal of Soil and
Water Conservation, Vol. 39, No. 4 (July-Aug., 1984), 226-28.
5. Ogg, Clayton. Cross-Compliance Proposals and Fragile Croplands. Paper presented at 1983 annual meeting, American Agricultural Economics Association, West Lafayette, IN, Aug. 1983.
6. Arnold B. Miller, and Kenneth C. Clayton. Agricultural Program
Integration to Achieve Soil Conservation. Unpublished working
paper. U.S. Dept. Agr., Econ. Res. Serv., 1984.
7. Osteen, Craig. The Impacts of Farm Policies on Soil Erosion: A Problem
Definition Paper. ERS Staff Report AGES841109. U.S. Dept. Agr., Econ. Res.
Serv., Jan. 1985.
8. U.S. Senate, Committee on the Budget, 98th Congress, 2d Session. The
Distribution of Benefits from the 1982 Federal Crop Programs. Committee
print 98-238, Nov. 1984.
9. U.S. Department of Agriculture, Soil Conservation Service. Basic Statistics:
1977 National Resources Inventory. SB-686. Dec. 1982.
10. Soil Conservation Service. Land Resource Regions and Major Land
Resource Areas of the United States. AH-296. Dec. 1981.
11. Watts, Myles J., Lloyd D. Bender, and James B. Johnson. Economic Incentives
for Converting Rangeland to Cropland. Bulletin 1302. Montana State Univ.,
Coop. Ext. Serv., Nov. 1983.
12. Young, John Edward. "Economics of Grassland Plowing and Its Regulation."
M.S. thesis. Colorado State Univ., 1984.
42




Appendix A: Appendix table 1--USDA program consistency study sample counties
County categories,
Major land resource areas and counties : other than CTA 1/
Columbia Plateau:
Adams, WA -5
Gilliam, OR 5
Umatilla, OR 5, 6
Palouse and Nez Perce Prairies:
Spokane, WA 4, 5
Whitman, WA 5
Central High Plains and
Upper Arkansas Valley Rolling Plains:
Kit Carson, CO 2/
Otero, CO 1, 6
Prowers, CO 6
Weld, CO 2/
Platte, WY 6
Southern High Plains:
Carson, TX 6
Dallam, TX 6
Hale, TX 6
Hockley, TX 6
Terry, TX
Loess Uplands and Till Plains and Nebraska and Kansas Loess-Drift Hills: Lyon, IA 2/
Leavenworth, KS 4, 5
Lancaster, NE 2/ 5
Pierce, NE 5
Bon Homme, SD
Iowa and Missouri Deep Loess Hills:
Carroll, IA 5
Ida, IA 2/ 5
Mills, IA 5
Page, IA 5
Holt, MO 5
Southern Coastal Plains:
Clarke, AL Dale, AL 5, 9
Elmore, AL
Franklin, AL
Mobile, AL 5
Pike, AL 5
See footnotes at end of table. --Continued
43




Appendix A: Appendix table 1--USDA program consistency study sample
counties--Continued
: County categories
Major land resource areas and counties : other than CTA 1/
Southern Coastal Plains continued:
Bulloch, GA 5
Emanuel, GA 1, 5
Irwin, GA
Mitchell, GA
Screven, GA 5
Stewart, GA 3
Toombs, GA 5
Alcorn, MS 5
Itawamba, MS 5
Lamar, MS
Pontotoc, MS 5
Simpson, MS
Stone, MS
Tippah, MS 3, 5
Edgecombe, NC 4
Decatur, TN 3, 5
Southern Mississippi Valley Silty Uplands:
Arkansas, AR 1, 4
Calloway, KY 5
Fulton, KY 5, 9
E. Baton Rouge, LA 4
E. Feliciana, LA
Copiah, MS 4
Jefferson Davis, MS 4
Warren, MS
Crockett, TN 5
Shelby, TN 5
Weakley, TN 5
Southern Piedmont:
Gwinnett, GA
Henry, GA Monroe, GA
Cleveland, NC 4
Vance, NC 1, 5
Greenville, SC 1, 3, 4
McCormick, SC
Cumberland, VA 1
Halifax, VA 1, 3, 5
Louisa, VA
- County not categorized beyond its having been a CTA county.
1/ All but five counties (those indicated below) are CTA counties. Codes indicate the following: 1 Original Study Evaluation County; 3 = Variable Cost-Share Level Counties; 4 = Nationally Funded Special Projects; 5 = Critical Erosion Target Areas; 6 Critical Water Storage Targeted Areas; 9 = Rural Clean Water Program.
2/ Not a CTA county. These counties were included in the sample to assure that sufficient data points were collected for critical MLRA's
44




APPRNDIX B:
INSTRUCTIONS FOR COMPLETING AD-862 FORMS FOR USDA PROGRAM CONSISTENCY STUDY (The following instructions for completing the data assembly form are included to give the reader a better idea of what information was collected and how it was collected.)
Form AD-862 shall be completed as prescribed below for identified sample farms. Leave all other portions of form AD-862 blank. The circled numbers below identify or locate specific sections on the attached blank copy of AD-862. Following the blank copy, you will find a copy of a completed form (from a Carson County, Texas pretest).
SECTION A GENERAL INFORMATION
Complete the data items indicated below as follows:
1 A-i (Date) Enter the date form is prepared. Use 2 digits each to enter
the month, day, and calendar year. For example, September 1, 1983, is
entered as 090183.
2 A-2 (Reporting Location) Enter the FIPS code in blocks 2a and 2b.
Enter a check digit in right-hand block of 2b. Enter the SCS 3-digit
field office code in block 2c. (County personnel will provide these
codes. The reporting location code will be the same for all observations
in a given county.)
3 A-3 (Farm identifier) Enter the ASCS Community Code in block 3a.
Enter the farm number in block 3b, using right-justification of the digits. (NOTE: If the county only has one community, enter an "A"
in the farthest right-hand cell of block 3a.)
4 A-4 (Data Code) Enter code "6" for identification as ERS Consistency
Study Data.
5 A-5 Enter one of the following codes to indicate primary (largest
single) lender of producer, for operating loans. (ASCS personnel will
provide this information on the basis of personal knowledge.)
CODE
1 FmHA
3 PCA
4 Insurance companies
5 Commercial banks
6 Other, or no lender
7 Unknown
45




6 A-7 (Program Code) Enter one of the following codes in: 7a for 1978;
7b for 1982; and 7c for 1983.
1 Neither commodity nor conservation program* participation
2 Farm participated in commodity program only
3 Farm participated in conservation program* only
4 Farm participated in both commodity, and conservation* programs
*NOTE: Conservation programs include:
a. ASCS-administrated programs:
Agricultural Conservation Program (ACP)
Emergency Conservation Program (ECP)
Rural Clean Water Program (RCWP)
Water Bank
Forestry Incentives Program (FIP)
ASCS conservation program participation for a given year is defined by
the operator's having received payment in that year for one of the
above.
b. SCS-administrated programs:
Great Plains
Rural Abandoned Mines Prqgram (RAMP)
Resource Conservation and Development (RC&D)
PL-566 (Small Watersheds)
Operator filing of a conservation plan with SCS
Determine from a follow-up visit with SCS District Conservationist
in county whether specific individual operators who did not participate
in ASCS conservation programs in given years did participate in SCS conservation programs during those years. Revise codes previously
filled in as "I" or "2" in Block A-7, as appropriate after follow-up.
7 A-9 Enter SCS code, recorded on mapping material, in 9b. For one-digit
codes, record as two-digit number, with a "0" preceding digit (For example,
record SCS code 4 as 04).
8 A-10 (Farm Type) Enter the appropriate code for farm type. If a variety
of commodities are grown, choose the code that represents the predominant
commodity. (NOTE; ASCS personnel will classify the farms from their knowledge of the operations. Farm record cards do not provide enough
information to independently determine farm type.)
Code Type
1 Cash grain farms (includes grain sorghum, corn, soybeans, rice,
wheat, oats, barley, among others; crops can be in rotation with
hay or pasture or can be on a continuous basis).
46




2 Cotton farms.
3 Tobacco farms.
4 Other field crop farms (includes sugar, potatoes, peanuts, among
others)
5 Vegetable and melon farms.
6 Fruit, berry, and nut farms.
7 Livestock farms and ranches (includes sheep, cattle, dairy, swine,
and poultry.)
8 Miscellaneous farms (includes fur-bearing animals, bees, grass,
seed, among others)
9 Combination livestock aild grain farms.
10 Tree farms.
9 A-11 (Farm Size) Enter in whole numbers the total acres in this farm
operating unit. (The operating unit may include State or Federal land.) Total acres are shown on the farm record card as the first whole number
to the right of the operator's name.
THE PURPOSE OF ITEMS A-12 and A-14 TO A-16 IS TO IDENTIFY SOME OF THE
MAJOR CHARACTERISTICS OF THE OWNERS AND DECISIONMAKERS OF THE SELECTED
FARM UNITS. THESE ITEMS ARE TO BE ANSWERED USING PERSONAL KNOWLEDGE
AND JUDGMENT OF ASCS PERSONNEL. IF UNABLE TO ANSWER THESE ITEMS USING
EXISTING KNOWLEDGE AND JUDGMENT, ENTER THE CODE FOR UNKNOWN.
NOTE: ITEM A-12, BELOW, REFERS TO THE OWNER OF THE FARM UNIT, WHO MAY OR
MAY NOT BE THE DECISIONMAKER.
10 A-12 (Type of Ownership) Enter the appropriate code.
Code Tp
1 Individual or family (including husband-wife, family partnership,
or family corporation).
2 Nonfamily partnership or corporation.
3 Government other than Federal (State, county, municipal).
4 Federal Government.
5 Indian tribal trust lands.
47




6 Combination of Federal-State-private, Federal-private, or Stateprivate.
7 Any other combination.
8 Other (estates, trusts, institutions, foundations, among others).
9 Unknown.
ITEMS A-14 to A-16 REFER TO THE DECISIONMAKER (OPERATOR) FOR THIS FARM.
S A-14 (Type of Decisionmaker) Enter the appropriate code.
Code Type
1 Ag-owner operator the decisionmaker owns and operates all
the land in the unit for agricultural purposes.
2 Ag-tenant operator the decisionmaker rents or leases all the
land in the unit from others on an annual basis for agricultural purposes.
3 Ag-tenant operator the decisionmaker rents or leases all the
land in the unit from others for more than 1 year for agricultural purposes.
4 Ag-landlord the decisionmaker owns all the land in the unit
but rents or leases it to others for agricultural purposes.
5 Nonag operator the decisionmaker owns and operates all of
the land in the unit for NONFARM PURPOSES such as an airport,
golf course, industrial site, or for other use.
6 Nonag operator the decisionmaker rents or leases all of the
land in the unit from others on an' annual basis for NONFARM
PURPOSES such as an airport, golf course, industrial site, or
for other use.
7 Nonag operator the decisionmaker rents or leases all of the
land in the unit from others for more than 1 year for NONFARM PURPOSES such as an airport, golf course, industrial site, or
for other use.
8 Nonag operator the decisionmaker owns all of the land in
the unit but rents or leases it to others for NONFARM PURPOSES such as an airport, golf course, industrial site, or for other
use.
9 Part ag-owner operator the decisionmaker owns part of the
land in the unit and rents and leases on an annual basis part
of the land from others for agricultural purposes.
48




10 Part ag-owner operator the decisionmaker owns part of the land
in the unit and rents or leases for more than 1 year part of
the land from others for agricultural purposes.
11 Other
12 Unknown
12 A-15 (Off-Farm Work) Enter the appropriate code.
Code Item
1 Decisionmaker is a full-time operator with no off-farm work.
2 Decisionmaker is a farm operator with 1-99 days per year off-farm
employment.
3 Decisionmaker is a farm operator with 100 or more days per year
off-farm employment.
4 Decisionmaker is not a farm operator.
5 Unknown
13 A-16 (Age) Enter one of the following codes to most nearly approximate the
operator's age.
Code Range of age
1 Less than 21
2 21-30
3 31-40
4 41-50
5 51-60
6 61-70
7 Over 70
8 Unknown
49




14 A-18 (Control Number) Enter 83 in block 18a. Enter unique "4000" series
numbers for each AD-862 submitted from a given county. For example:
834001, for the first form filled out in a county; 834002, for the second
form filled out in the same county, etc.
SECTION B CTU CHARACTERISTICS Complete the data items indicated below as follows: 15 B-4 (Soil Record No.) This area of the form will be used to record total
cropland acres for the farm unit. Enter in whole numbers the total cropland acres in the decision maker's operating unit. This may be found on the farm
record card as the second whole number to the right of the operator's name. 16 B-5 (Land Capability Class and Subclass) Enter land capability class and
subclass as recorded on SCS mapping materials.
17 B-8 This area of the form will be used to ascertain yield and allotment
data for up to 4 crops. Use blocks 8a, b, c, and d to list predominent
crops for this purpose.
Enter the appropriate crop code and most recently determined effective
yield from the following list in the first block under the "B" subheading.
Code Crop Units
A Oats bu/acre
B Barley bu/acre
C Corn bu/acre
G Grain sorghum bu/acre
R Rice cwt/acre
S Soybeans bu/acre (estimated)
T Cotton cwt/acre
W Wheat bu/acre
P Peanut cwt/acre (estimated)
X Tobacco cwt/acre
50




Enter the crop yield in the units identified above in the remaining blocks
under the "B" subheading. For example: Enter a 47 bushel/acre wheat yield as
B B
1W1014171. Enter a 3,450 pound/acre rice yield as ]R1013141.
NOTE: In some counties on some farms, yields will be given both for irrigated
and nonirrigated production of the same crop. Decide which of the two yields
to record in these instances on the basis of the land capability class and
subclass recorded for the cropland point from the farm. For example, if the
capability class and subclass is 2S, record effective yield for irrigated
production; if the capability class and subclass is 3E, record effective
yield for nonirrigated production.
Enter in whole numbers under the subheading "A" the base acreage for the crop
identified in subheading "B." For allotments exceeding 9,999, enter 9,999.
Enter 10 acres as IOI0011 Commodity program nonparticipants for 1982-83
will not have an established base.
SECTION C APPLICATION OF RESOURCE MANAGEMENT SYSTEMS
18 lb (Units) Enter the last five digits of the control number from AD-862's
previously submitted by ASCS for this farm unit. If more than one AD-862,
enter the last five digits of each control number up to 5 on line 2, 3, (and
so forth). No more than five previously submitted control numbers may be
listed. If CUA evaluation was submitted, be sure to include in lb.
SECTION D EROSION CONTROL
19 la(B) (Erosion) In the first three cells in Section D, enter in whole numbers
the sum of sheet and rill and wind erosion as recorded on SCS mapping materials. Right-justify the erosion figure in space la(B).
51




APPENDIX C: DISTRIBUTION OF FARM AND OPERATOR
CHARACTERISTICS AMONG PROGRAM PARTICIPATION CATEGORIES
AND SOIL EROSION MASSES
We conducted chi-square tests for differences in distributions using the two-way tables in this appendix. The tables contain figures showing the absolute and percentage distributions of the study sample operators among various characteristic groupings, as well as the percentage distributions of each grouping within the other.
Chi-square statistics are presented in table footnotes. The null hypotheses tested through the chi-square procedure are that operators in specified soil erosion or program participation classes have the same characteristics as all sample operators.
The general formula used to calculate the chi-square statistics is:
n
X2 E (f-F)2
i-1 F
where: f = the observed frequency in an erosion
class or program participation category;
F the frequency in the whole population
of operators; and
n the number of classes of the characteristic.
52




Appendix table 2--Farm ownership by program-participation category, 1982 1/
* Program participation category
Type of farm ownership :Unit :Neither : Corn- :Conser- : Joint : Totals
* : program : modity :vation :commodity and: :only : only :conservation :
Individual or family:
Total observations Number 1,099.0 722.0 373.0 467.0 2,661.0
in program category
Proportion of total Percent 38.4 25.2 13.0 16.3 92.9
sample
Proportion of do. 41.3 27.1 14.0 17.6 NA
ownership category
Proportion of do. 93.6 90.5 92.3 95.9 NA
program category
Nonfamily partnership,
or corporation: Total observations Number 34.0 30.0 5.0 7.0 76.0
in program category
Proportion of total Percent 1.2 1.1 .2 .2 2.7
sample
Proportion of do. 44.7 39.5 6.6 9.2 NA
ownership category
Proportion of do. 2.9 3.8 1.2 1.4 NA
program category
Government, comibination private and
Government, and Indian tribes: Total observations Number 18.0 17.0 13.0 5.0 53.0
in program category
Proportion of total Percent .6 .6 .5 .2 1.9
sample
Proportion of do. 34.0 32.1 24.5 9.4 NA
ownership category
Proportion of do. 1.5 2.1 3.2 1.0 NA
program category
See footnotes at end of table. --Continued
53




Appendix table 2--Farm ownership by program participation category,
1982 l/--Continued
: : Program participation category
Type of farm ownership Unit : Neither : Com- : Conser- : Joint : Totals
: program : modity : nation :commodity and : : only : only :conservation :
Other:
Total observations Number 23.0 29.0 13.0 8.0 73.0
in program category
Proportion of total Percent .8 1.0 .5 .3 2.6
sample
Proportion of do. 31.5 39.7 17.8 11.0 NA
ownership category
Proportion of do. 2.0 3.6 3.2 1.6 NA
program category
Total:
Observations in this Number 1,174.0 798.0 404.0 487.0 2,863.0
program category
Proportion of Percent 41.0 27.9 14.1 17.0 100.0
total sample
NA = Not applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom = 9; chi-square = 25.159; probability of null hypothesis f 0.0028.
54




Appendix table 3--Farm ownership among soil erosion classes, 1982 1/ : :Soil erosion class
:Less than: 5-13 : : 25 or
Type of farm ownership : Unit : 5 tons/ :tons/acre/:14-24 tons/more tons: Totals :acre/year: year : acre/year :acre/year:
Individual or family:
Total observations Number 1,204.0 832.0 315.0 310.0 2,661.0
in erosion class
Proportion of total Percent 42.1 29.1 11.0 10.8 93.0
sample
Proportion of do. 45.3 31.3 11.8 11.7 NA
ownership category
Proportion of do. 92.2 94.0 91.8 94.2 NA
erosion class
Nonfamily partnership or corporation: Total observations Number 44.0 12.0 6.0 14.0 76.0
in erosion class
Proportion of total Percent 1.5 .4 .2 .5 2.6
sample
Proportion of do. 57.9 15.8 7.9 18.4 NA
ownership category
Proportion of do. 3.4 1.4 1.8 4.3 NA
erosion class
Government, combination private and Government, and Indian tribes: Total observations Number 24.0 20.0 8.0 1.0 53.0
in erosion class
Proportion of total Percent .8 .7 .3 .1 1.9
sample
Proportion of do. 45.3 37.7 15.1 1.9 NA
ownership category
Proportion of do. 1.8 2.3 2.3 .3 NA
erosion class
See footnotes at end of tables. --Continued
55




Appendix table 3--Farm ownership among soil erosion classes, 1982 l./--Continued : : Soil erosion class :
: :Less than: 5-13 : : 25 or :
Type of farm ownership : Unit : 5 tons/ :tons/acre/:14-24 tons/:more tons: Totals : :acre/year: year : acre/year :acre/year:
Other:
Total observations Number 34.0 21.0 14.0 4.0 73.0
in erosion class
Proportion of total Percent 1.2 .7 .5 .1 2.5
sample
Proportion of do. 46.6 28.8 19.2 5.5 NA
ownership category
Proportion of do. 2.6 2.4 4.1 1.2 NA
erosion class
Total:
Observations in Number 1,306.0 885.0 343.0 329.0 2,863.0
this erosion class
Proportion of Percent 45.6 30.9 12.0 11.5 100.0
total sample
NA Not applicable.
1/ The statistics for this two-way table are as follows: degrees of
freedom = 9; chi-square 23.72; probability of null hypothesis = 0.0048.
56




Appendix table 4--Farm tenure among program participation categories, 1982 1/
: Program participation category
Type of decisionmaker : Unit : Neither : Com- : Conser- Joint Totals
: program : modity : nation :commodity and:
* : only : only :conservation
Owner operator:
Total observations Number 605.0 368.0 215.0 229.0 1,417.0
in program category
Proportion of total Percent 21.3 12.9 7.5 8.1 49.8
sample
Proportion of do. 42.7 26.0 15.2 16.2 NA
decisionmaker
category
Proportion of do. 52.2 46.2 53.2 47.1 NA
program category
Tenant with annual lease:
Total observations Number 279.0 222.0 91.0 125.0 717.0
in program category
Proportion of total Percent 9.8 7.8 3.2 4.4 25.2
sample
Proportion of do. 38.9 31.0 12.7 17.4 NA
decisionmaker
category
Proportion of do. 24.1 27.9 22.5 25.7 NA
program category
Tenant with longterm lease: Total observations Number 170.0 101.0 59.0 55.0 385.0
in program category
Proportion of total Percent 6.0 3.5 2.1 1.9 13.5
sample
Proportion of do. 44.2 26.2 15.3 14.3 NA
decisionmaker
category
Proportion of do. 14.7 12.7 14.6 11.3 NA
program category
Landlord:
Total observations Number 30.0 8.0 20.0 13.0 71.0
in program category
Proportion of total Percent 1.1 .3 .7 .5 2.5
sample
Proportion of do. 42.3 11.3 28.2 18.3 NA
decisionmaker
category
Proportion of do. 2.6 1.0 5.0 2.7 NA
program category
See footnotes at end of table. --Continued
57




Appeldix table 4--Fe*m t~er aewa psw spig iptincatseatries,
1982 1/--Continued
: : Program parttipation category :
Type of dcip i=wker : Unit : Neither : Can- I Conser- : Joint : Totals
pro :pram medtty v ation :commodity and:
: : only : only touarvationl:
Part owner operator with annual lease: Total observations Number 13.0 16.0 7-.0 10.0 46.0
in program category
Proportion of total Percent .5 .6 .3 .4 1M6
sample
Propo rtion of do. 28.3 34.8 152 21.7 NA
deoisionmaker
category
Proportion of do. 1.1 2.0 1.7 2.1 NA
program category
Part owner operator
with long-term lease: Total observations Number 54.0 71.0 60 51.0 182.0
in program category
Proportion of-tot4 Percent 1.9 2.5 .2 1.8 6.4
sample
Proportion of do. 29.7 39.0 3.3 28.0 NA
decisionmaker
category
Proportion of do. 4.7 8.9 1.5 10.5 NA
program category
Other:
Total observations Number 8.0 11.0 6.0 3.0 28.0
in program category
proportion of total Percent .3 .4 .2 .1 1.0
sample
Proportion of do. 28.6 39.3 21.4 10.7 NA
decisionmaaker
category
Proportion of do. .7 1.4 1.5 .6 NA
program category
Total:
Observations in Number 1,159.0 797.0 404.0 486.0 2,846.0
this program category
Proportion of Percent 40.7 28.0 14.2 17.1 100.0
total sample
NA t applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom18; chi-sqware 78.172; probability of null hypothesis -0.0001.
58




Appendix table 5-Farm tenure by soil erosion class, 1982
: Soil erosion class
Less :
Type of operator : Unit than 5-13 25.or Totals
: 5 tonal : tons/acre/: 14-24 tonsl: more tons: acre/ynar: year, ". acre/year :acre/year:
Owner operator:
Total observations Number 691.0, 414.0 16.6.0 146., 1,417.0
in erosion class
Proportion of total Percent 24.3 14.6 5.8 5.1 49.8
sample
Proportion of do. 48.8 29.2 11.7 10.3 NA
operator category
Proportion of do. 53.05 46.9 48.4 44.5 NA
erosion class
Tenant with annual lease:
Total observations Number 274.0 256.0 71.0 1-16.0 717.0
in erosion class
Proportion of total Percent 9.6 9.0 2.5 4.1 25.2
sample
Proportion of do. 38.2 35.7 9.9 16.2 NA
operator category
Proportion of do. 21.2 29.0 20.7 35.4 NA
erosion class
Tenant with longterm lease: Total observations Number 200.0 98.0 53.0 34.0 385.0
in erosion class
Proportion of total Percent 7.0 3.4 1.9 1.2 13.5
sample
Proportion of do. 52.0 25.5 13.8 8.8 NA
operator category
Proportion of do. 15.5 11.1 15.5 10.4 nNA
erosion class
Landlord:
Total observations Number 32.0 24.0 8.0 7.0 -71.0
in erosion class
Proportion of total Percent 1.1 .8 .3 .3 2.5
sample
Proportion of do. 45.1 33.8 11.3 9.9 NA
operator category
Proportion of do. 2.5 27- 2.3 2.1. NA
erosion class
See footnotes at end of table. --Continued
59




Appendix table 5-Farm tenure by soil erosion class, 1982--Continued
Soil erosion class
Less : :
Type of operator : Unit : than : 5-13 : 25 or :Totals
: 5 tons/ : tons/acre/: 14-24 tons/: more tons: : acre/year: year : acre/year : acre/year:
Part owner operator with annual lease: Total observations Number 25.0 14.0 2.0 5.0 46.0
in erosion class
Proportion of total Percent .9 .5 .1 .2 1.7
sample
'-Proportion of do. 54.4 30,4 4.4 10.9 NA
operator category
Proportion of do. 1.9 1.6 .6 1.5 NA
erosion class
Part owner operator
with long-term lease: Total observations Number 59.0 66.0 39.0 18.0 182.0
in erosion class
Proportion of total Percent 2.1 2.3 1.4 .6 6.4
sample
Proportion of do. 32.4 36.3 21.4 9.9 NA
operator category
Proportion of do. 4.6 7.5 11.4 5.5 NA
erosion class
Other:
Total observations Number 11.0 11.0 4.0 2.0 28.0
in erosion class
Proportion of total Percent .4 .4 .1 .1 1.0
sample
Proportion of do. 39.3 39.3 14.3 7.1 NA
operator category
Proportion of do. .9 1.3 1.2 .6 NA
erosion class
Total:
Observations in Number 1,292.0 883.0 343.0 328.0 2,846.0
this erosion class
Proportion of Percent 45.4 31.0 12.1 11.6 100.1
total sample
NA Not applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom18; chi-square 74.261; probability of null hypothesis- 0.0001.
60




Appendix table 6--Off-farm work by program participation category, 1982 1/
Program participation category
Work status of operator Unit :Neither: :Com- : Conser- Joint Totals
:program: modity : vation :commodity and: only : only :conservation
Full-time farm operator:
Total observations Number 788.0 618.0 291.0 406.0 2,103.0
in program category
proportion of total Percent 30.0 23.5 11.1 15.4 80.0
sample
Proportion of do. 37.5 29.4 13.8 19.3 NA
work status category
Proportion of do. 75.5 85.6 76.0 84.6 NA
program category
off-farm work 1-99 days per year:
Total observations Number 45.0 37.0 18.0 19.0 119.0
in program category
Proportion of total Percent 1.7 1.4 .7 .7 4.5
sample
Proportion of work do. 37.8 31.1 15.1 16.0 NA
status category
Proportion of do. 4.3 5.1 4.7 4.0 NA
program category
off-farm work 100 or more days
per year:
Total observations Number 175.0 54.0 60.0 46.0 335.0
in program category
Proportion of total Percent 6.7 2.1 2.3 1.8 12.9
sample
Proportion of work do. 52.2 16.1 17.9 13.7 NA
status category
Proportion of do. 16.8 7.5 15.7 9.6 NA
program category
See footnotes at end of table. --Continued
61




Appendix table 6--0ff-farm work by program-participation category, 1982 1/--Continued
Program participation category
Work status of operator Unit :Neither: Com- : Conser- Joint Totals
:program: modity : vation :commodity and: only : only :conservation
Full-time of f-farm worker:
Total observations Number 36.0 13.0 14.0 9.0 72.0
in program category
Proportion of total Percent 1.4 .5 .5 .3 2.7
sample
Proportion of work do. 50.0 18.1 19.4 12.5 NA
status category
Proportion of do. 3.5 1.8 3.7 1.9 NA
program category
Total:
Observations in this Number 1,044.0 722.0 383,.0 480.0 2/ 2,629.0
program category
Proportion of Percent 39.8 27.5 14.6 18.2 100.1
total sample
NA Not appliable.
I/ The statistics for this two-way table are as follows: degrees of freedom = 9; chi-square 50.561; probability of null hypothesis.- 0.0001.
2/ Off-farm work status is unknown for 9 percent of the sample.
62




Appendix table 7--Operator age by program participation category, 1982 1/
Program participation category
Age of operator Unit :Neither : Com- : Conser- : Joint :Totals
:program : modity : vation : commodity and : : only : only : conservation :
Less than 21 years:
Total observations Number 1.0 2.0 3.0 0 6.0
in program category
Proportion of total Percent <.1 .1 .1 0 .2
sample
Proportion of do. 16.7 33.3 50.0 0 NA
age category
Proportion of do. .1 .3 .8 0 NA
program category
21-30 years:
Total observations Number 61.0 45.0 16.0 23.0 145.0
in program category
Proportion of total Percent 2.3 1.7 .6 .9 5.5
sample
Proportion of do. 42.0 31.0 11.0 15.9 NA
age category
Proportion of do. 5.8 6.1 4.1 4.8 NA
.program category
31-40 years:
Total observations Number 176.0 120.10 70.0 90.0 456.0
in program category
Proportion of total Percent 6.6 4.5 2.6 3.4 17.1
sample
Proportion of do. 38.6 26.3 15.4 19.7 NA
age category
Proportion of do. 16.8 16.3 17.9 18.8 NA
program category
41-50 years:
Total observations Number 285.0 180.0 112.0 137.0 714.0
in program category
Proportion of total Percent 10.8 6.8 4.2 5.2 27.0
sample
Proportion of do. 39.9 25.2 15.7 19.2 NA
age category
Proportion of do. 27.3 24.4 28.6 28.7 NA
program category
See footnotes at end of table. --Continued
63




Appendix table 7--Operator age by program. participation category, 1982 1/--Continued
Program parcipation. cIategory
Age of operator : t t :Neither. : Co-. : Cnser- : Joint. :Totals
S :program : modity : nation : commodity and : : only : only : conservation :
51-60 years:
Total observations Number 294.0 231.0 121.0 155.0 801.0
in program category
Proportion of Percent 11.1 8.7 4.6 5.8 30.2
total sample
Proportion of do. 36.7 28 8 15.1 19.4 NA
age category
Proportion of do. 28.1 31.3 30.9 32.4 NA
program category
61-70 years:
Total observations Number 172.0 137.0 58.0 59.0 426.0
in program category
PropOrtivn of-total Percent 6.5 5.2 2.2 2.2 16.1
sample
Proportion of do. 40.4 32.2 13.6 13.9 NA
age category
Proportion of do. 16.5 18.6 14.8 12.3 NA
program category
Over 70 years:
Total observations Number 56.0 22.0 12.0 14.0 104.0
in program, category
Proportion of total Percent 2.1 .8 .5 .5 3.9
sample
Proportion of do. 53.9 21.2 11.5 13.5 NA
age category
Proportion of do. 5.4 3.0 3.1 2.9 NA
program category
Total:
Observations in Number 1,045.0 737.0 392.0 478.0 2,652.0
this categOry
Proportion of sample Percent 39.4 27.8 14.8 18.0 100.0
NA Not applicable. 1/ The statistics for this two-way table are as follows: degrees of freedom = 18; chi-square = 32.769; probability of null hypothesis 0.0178.
64




Appendix table 8--Operator age by soil erosion class, 1982 1/
: :Soil erosion class
Age of operator : Unit :Less than: 5-13 :14-24 tons/: 25 or : Totals
* : 5 tons/ :tons/acre/: acre/year :more tons!:
: :acre/year: year : :acre/year
Less than 21 years:
Total observations Number 5.0 1.0 0 0 6.0
in erosion class
Proportion of total Percent .2 < .1 0 0 <.3
sample
Proportion of do. 83.3 16.7 0 0 NA
age category
Proportion of do. .4 .1 0 0 NA
erosion class
21-30 years:
Total observations Number 52.0 50.0 15.0 28.0 145.0
in erosion class
Proportion of total Percent 2.0 1.9 .6 1.1 5.6
sample
Proportion of do. 35.9 34.5 10.3 19.3 NA
age category
Proportion of do. 4.3 6.1 4.7 9.3 NA
erosion class
31-40 years:
Total observations Number 193.0 139.0 56.0 68.0 456.0
in erosion class
Proportion of total Percent 7.3 5.2 2.1 2.6 17.2
sample
Proportion of do. 42.3 30.5 12.3 14.9 NA
age category
Proportion of do. 16.0 16.9 17.5 22.5 NA
erosion class
41-50 years:
Total observations Number 329.0 229.0 86.0 70.0 714.0
in erosion class
Proportion of total Percent 12.4 8.6 3.2 2.6 26.8
sample
Proportion of do. 46.1 32.1 12.0 9.8 NA
age category
Proportion of do. 27.3 27.8 26.9 23.2 NA
erosion class
See footnotes at end of table. --Continued
65




Appendix table 8--Operator age by soil erosion class, 1982.1/--Continued
: : Soil erosion class :
Age of operator : Unit :Less than: 5-13 :14-24 tons/: 25 or : Totals : :5 tons/ :tons/asre/: acre/year :more tons/: : :are/year: year :acre/year :
51-60 years:
Total observations Number 378.0 233.0 100.0 90.0 801.0
in erosion class
Proportion of total Percent 14.2 8.8 3.8 3.4 30.2
sample
Proportion of do. 47.2 29.1 12.5 11.2 NA
age category
Proportion of do. 31.3 28.3 31.3 29.8 NA
erosion class
61-70 years:
Total observations Number 193.0 141.0 53.0 39.0 426.0
in erosion class
Proportion of total Percent 7.3 5.3 2.0 1.5 16.1
sample
Proportion of do. 45.3 33.1 12.4 9.2 NA
age category
proportion of do. 16.0 17.1 16.6 12.9 NA
erosion class
Over 70 years:
Total observations Number 56.0 31.0 10.0 .7.0 104.0
in erosion class
Proportion of total Percent 2.1 1.2 .4 .3 4.0
sample
Proportion of do. 53.9, 29.8 9.6 6.7 NA
age category
Proportion of do. 4.6 3.8 3.1 2.3 NA
erosion class
Total:
Observations in Number 1,206.0 824.0 320.0 302.0 2/ 2,632.0
this erosion class
Proportion of Percent 45.5 31.1 12.1 11.4 100.1
total sample
NA = Not applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom 18; chi-square = 31.735; probability of null hypothesis 0.0236. 2/ Operator age is unknown for 8 percent of sample.
66




/
Appendix table 9--Primary source of operating loan, by soil erosion class, 1982 1/
: : Soil erosion class
Primary source of : Unit :Less than: 5-13 : : 25 or : Totals
operating loans : : 5 tons/ :tons/acre/:14-24 tons/:more tons/:
:acre/year: year : acre/year :acre/year :
Farmers Home Administration:
Total observations Number 128.0 101.0 35.0 53.0 317.0
in erosion class
Proportion of total Percent 7.5 5.9 2.1 3.1 18.6
sample
Proportion of loan do. 40.4 31.9 11.0 16.7 NA
source category
proportion of do. 16.7 19.5 17.6 23.1 NA
erosion class
Production Credit Association: Total observations Number 87.0 90.0 24.0 39.0 240.0
in erosion class
Proportion of total Percent 5.1 5.3 1.4 2.3 14.1
sample
Proportion of do. 36.2 37.5 10.0 16.3 NA
loan source category
Proportion of do. 11.4 17.4 12.1 17.0 NA
erosion class
Commercial banks and insurance companies: Total observations Number 429.0 243.0 102.0 95.0 869.0
in erosion class
Proportion of total Percent 25.1 14.2 6.0 5.6 50.9
sample
Proportion of do. 49.4 28.0 11.7 10.9 NA
loan source category
Proportion of do. 56.1 47.0 51.3 41.5 NA
erosion class
See footnotes at end of table. --Continued
67




Apperuixf table 9- P yster re of operatiag 1ean,, b Ll evasion class, 1982 1/ --Continued
: Soil erosion class :
Primary source of :Unit :Less than: 5-13 : : 25 or : Totals
operating loans : : 5 tons/ :tons/acrel:14-24 tons/:more tons/:
: :acre/year: year : acre/year :acre/year :
Other 2/
Total' observattooe Nuatr 121.0 83.0 36e0 41.0 281.0
in erosion class
Proportion of total Peraent 7.1 4.9 2.1 2.4 16.5
sample
Proportion of loan do. 43.1 29.5 128 14.6 NA
source category
Proportion of do. 15.8 16.1 18.1 17.9 NA
erosion class
Total:
Observation in this Number 765.0 517.0 197.0 228.0 3/1,707.0
erosion class
Proportion of Percent 44.8 30.3 11.5 13.4 100.0
total sample
NA Not applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom = 18; chi-square = 45.92; probability of ull hypothesis 0. 0003.
2/ "Other" includes operators not borrowing operating funds.
3/ Total sample size is 2,882 observations. Prima;y operating loan source is unknown for 40 percent of sample.
68




Appendix table 10--Program participation by soil erosion class, 1982 1/
: :Soil erosion class
Program : :
participation : Unit : Less than: 5-13 : : 25 or :Totals
category : 5 tons/ :tons/acre/:14-24 tons/:more tons!:
: : acre/year: year : acre/year :acre/year
Neither commodity nor conservation programs:
Total observations Number 548.0 393.0 142.0 105.0 1,188.0
in erosion class
Proportion of total Percent 19.0 13.6 4.9 3.6 41.1
sample
Proportion of do. 46.1 33.1 11.9 8.8 NA
program participation category
Proportion of do. 41.6 44.2 41.4 31.6 NA
erosion class
Commodity programs only:
Total observations Number 334.0 239.0 97.0 129.0 799.0
in erosion class
Proportion of total Percent 11.6 8.3 3.4 4.5 27.8
sample
Proportion of do. 41.8 29.9 12.1 16.1 NA
program participation category
Proportion of do. 25.4 26.8 28.3 38.9 NA
erosion class
Conservation programs only:
Total observations Number 204.0 126.0 43.0 32.0 405.0
in erosion class
Proportion of total Percent 7.1 4.4 1.5 1.1 14.1
sample
Proportion of do. 50.4 31.1 10.6 7.9 NA
program participation category
Proportion of do. 15.5 14.2 12.5 13.5 NA
erosion class
See footnotes at end of table. --Continued
69




Appendix table 10--Program participation by soil erosion class, 1982 1/--Continued
Soil erosion class
Program
participation : Unit : Less than: 5-13 : : 25 or :Totals
category : : 5 tons/ :tons/acre/:14-24 tons/:more tons/:
: acre/year: year : acre/year :acre/year
Both program types: Total observations Number 231.0 132.0 61.0 66.0 490.0
in erosion class
Proportion of total Percent 8.0 4.6 2.1 2.3 17.0
sample
Proportion of do. 47.1 26.9 12.5 13.5 NA
program participation category
Proportion of do. 17.5 14.8 17.8 19.9 NA
erosion class
Total:
Observations in this Number 1,317.0 890.0 343.0 332.0 2,882.0
erosion class
Proportion of Percent 45.7 30.9 11.9 11.5 100.0
total sample
NA Not applicable.
I/ The statistics for this two-way table are as follows: degrees of freedom = 9; chi-square = 38.637; probability of null hypothesis = 0.0001.
70




Appendix table 11--Program participation categories, by land capability subclass e, 1982 1/
Program participation category
Land capability class : Unit : : : Joint :Totals
:Neither: Commodity: Conservation: commodity and: :program: only : only :conservation
All land in subclass e: Total observations Number 704.0 546.0 237.0 279.0 1,766.0
in program category
Proportion of total Percent 24.4 19.0 8.2 9.7 61.3
sample
proportion of land do. 39.9 30.9 13.4 15.8 NA
capability class
Proportion of do. 59.3 68.3 58.5 56.9 NA
program category
All land not in
subclass e:
Total observations Number 484.0 253.0 168.0 211.0 1,116.0
in program category
Proportion of total Percent 16.8 8.8 5.8 7.3 38.7
sample
Proportion of land do. 43.4 22.7 15.1 18.9 NA
capability class
Proportion of do. 40.7 31.7 41.5 43.1 NA
program category
Total:
Observations in this Number 1,188.0 799.0 405.0 490.0 2,882.0
program category
Proportion of total Percent 41.2 27.8 14.0 17.0 100.0
sample
NA = Not applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom
3; chi-square = 24; probability of null hypothesis = 0.0001. Subclass e indicates erosive cropland.
71




Appendix table 12--Program participation categories, by land capability subclass e, 1983 1/
Program participation
Joint
Land capability class : Unit : : : Conser- : commodity : Totals
: Neither :. Commodity: vation : and : program : only : only :conservation:
All land in subclass e: Total observations Number 462.0 712.0 156.0 436.0 1,766.0
in program category
Proportion of total Percent 16.0 24.7 5.4 15.1 61.2
sample
Proportion of do. 26.2 40.3 8.8 24.7 NA
land capability class
Proportion of do. 59.5 65.1 61.4 57.5 NA
program category
All land not in subclass e:
Total observations Number 315.0 381.0 98.0 322.0 1,116.0
in program -category
Proportion of total Percent 10.9 13.2 3.4 11.2 38.7
sample
Proportion of do. 28.2 34.1 8.8 28.9 NA
land capability class
Proportion of do. 40.5 38.9 38.6 42.5 NA
program category
Total:
Observations in this Number 777.0 1,093.0 254.0 758.0 2,882.0
program category
Proportion of total Percent 26.9 37.9 8.8 26.3 100.0.
sample
NA Not applicable. 1/ The statistics for this two-way table are as follows:, degrees of freedom f 3; chi-square 12.474; probability of null hypothesis 0.0059. Subclass e indicates erosive cropland.




Appendix table 13--Program participation. categories by land capability classes, 1982 1/
S: Program participation
: :: Joint
Land capability class : Unit : : Conser-: commodity : Totals
: Neither : Commodity: vation : and : program : only : only :conservation:
All land in classes IV-e, VI-e, and VII: Total observations
in program category Number 166.0 i51.0 51.0 59.0 427.0
Proportion of total
sample Percent 5.8 5.2 1.8 2.1 14.8
Proportion of land
capability class do. 38.9 35.4 11.9 13.8 NA
Proportion of
program category do. 14.0 18.9 12.6 12.0 NA
All land in classes I, II, III, V, and IV (not subclass e) or VI (not subclass e):
Total observations Number 1,022.0 648.0 354.0 431.0 2,455.0
in program category
Proportion of total Percent 35.5 22.5 12.3 15.0 85.2
sample
Proportion of land do. 41.6 26.4 14.4 17.6 NA
capability class
Proportion of do. 86.0 81.1 87.4 88.0 NA
program category
Total:
Observations in this Number 1,188.0 799.0 405.0 490.0 2,882.0
program category
Proportion of total Percent 41.2 27.7 14.1 17.0 100.0
sample
NA = Not applicable.
I/ The statistics for this two-way table are as follows: degrees of freedom = 3; chi-square = 15.797; probability of null hypothesis 0.0012. The lower a Roman numeral, the fewer are the physical limitations on the land's use. Subclass e indicates erosive cropland.
73




Appendix table 14--Program participation categories by land capability class, 1983 1/
: :Program participation
Joint tTotals Land capability class Unit : : Conser- : commodity
: : Neither : Commodity: nation : and
: : program : only : only :conservation:
All land in subclass IV-e, VI-e, and VII: Total observations
in program category Number 111.0 198.0 31.0 87.0 427.0
Proportion of total
sample Percent 3.9 6.9 1.1 3.0 14.8
Proportion of land
capability class do. 26.0 46.4 7.3 20.4 NA
Proportion of
program category do. 14.3 18.1 12.2 11.5 NA
All land in classes I, II, III, V, and IV
(not subclass e) and VI (not subclass e): Total observations Number 666.0 895.0 223.0 671.0 2,455.0
in program category
Proportion of total Percent 23.1 31.1 7.7 23.3 85.2
sample
Proportion of land do. 27.1 36.5 9.1 27.3 NA
capability class
Proportion of do. 85.7 81.9 87.8 88.5 NA
program category
Total:
Observations in this Number 777.0 1,093.0 254.0 758.0 2,882.0
program category
Proportion of total Percent 27.0 37.9 8.8 26.3 100.0
sample
NA Not applicable.
1/ The statistics for this two-way table are as follows: degrees of freedom = 3; chi-square = 17.666; probability of null hypothesis = 0.0005. The lower a Roman numeral, the fewer are the physical limitations on the land's use. Subclass e
indicates erosive cropland.
74
*U.S. GOVERNMENT PRINTING OFFICE: 1985-460-941 20068-ERS




I Charting
the Course of Agriculture
A valuable research tool, popular teaching device, and
convenient format for presenting a complete overview
of the agricultural sector, the two-color 1984 Handbook Sof Agricultural Charts is a USDA "bestseller"
Its 272 charts clearly illustrate data and trends for
1 1 agricultural subjects ranging from farm income to
consumer costs, and from commodities to energy
production and use. Trade data, cost of production
figures, and other pertinent information are depicted
as well.
I An enlargements version of this chartbook, with each 47
of the 272 charts in black and white on an 8"x /0" V
page of its own, will also be offered by GPO
this year.
Both handbooks are available from GPO. Order your
1 copies now.
PLEASE SEND ME A COPY OF: Credit card order only: 0]VISA 0 Mastercard
1 1984 Handbook of Agricultural Charts. AH-637. 92 pp. Order SN: 001-019-00368-5 from GPO. $3.75 Total charges $-----------------------------Enlargements: 1984 Handbook of Agricultural Charts. 276 pp. Order Credit card no.
SN: 001-019-00371-5 from GPO. $7.50 Expiration date: month/year --------------------Enclosed is $--------NAME ---------------------------------------------- Check
" Money order
ADDRESS ------------------------------ - - - - - - --- Charge to my Deposit Account No.-----------------CITY, STATE, ZIP --------------------------------- - - ---For Office Use Only
Quantity Charges Quantity Charges Write check payable to Superintendent of Documents. Add 25% for foreign address. --- Enclosed ----- MMOB------------ To be mailed --- OPNR...........
MAIL ORDER FORM TO: Superintendent of Documents ---Subscriptions --- ----------- UPNS
Government Printing Office Postage ------------------DISCOUNT
Washington, DC 20402 Foreign handling ---- --------REFUND




F-conomic indicators
-- il ,,,ar Sec tO
an octthe Keep tabs on farm income and expenses with the Economic Indicators of the Farm
El odV,.79
1 s~s ,Sector series.
This series of five separate reports, offered now on a subscription basis, explores
- the economic status of U.S. farms to give you a comprehensive update on where
U.S. agriculture is headed.
Here are the titles you will be receiving:
Income and Balance Sheet Statistics State Income and Balance Sheet Statistics Farm Sector Review
Production and Efficiency Statistics Costs of Production
Subscriptions may be purchased from: Superintendent of Documents U.S. Government Printing Office Washington, D.C. 20402
Send $15 ($18.75 for foreign subscribers) in check or money order to Superintendent of Documents. Request the Economic Indicators of the Farm Sector (ECI FS) series.
AGRICULTURAL
OUTLOOK
racking the Business of Agriculture...
Agricultural Outlook pools Outlook is USDA's official outlet
-' -st analyses of the agri- for farm income and food price Annual subscription: $31.00 US., $38.50 foreign. A
- iomy in one compre- forecasts. While emphasizing short-:.jthly package. Besides its term outlook information, the 25-percent discount is offered on orders of 100 copies or ;siar outlook coverage-including magazine also publishes special re- more to one address. Order from the Superintendent of : 1-- i supply and demand, ports containing long-term analyses Documents, Government Printing Office, Washington, D.C.
-,'z i3lture and trade, food of topics ranging from international
-. _-'ng, farm inputs, agricul- trade policies to U.S. land use and 20402. Make check payable to Superintendent of
- transportation and availability. Agricultural Outlook Documents. Allow 6 to 8 weeks for delivery.
_ and related developments in averages 48 pages and includes 6 pages
--- ----: conomy-Agricultural of updated charts and 20 pages of statistical tables.




United States
Department of Agriculture
Washington, D.C.
20250 Postage and Fees Paid
U.S. Department of Agriculture mmu OFFICIAL BUSINESS AGR-101
Penalty for Private Use, $300 THIRD CLASS BULK RATE
New fro ERS..........
Stay ahead with the latest F USDA' kMnonI I
market information-Introduction
~ .~.:g ERS Periodicals Subscribe now to ew fRo .
SERS Annual Reportsw fr ERS
Reports t"
.Re ors Reports from GPO
Reports .s Reports from NTIS
Reports (formerly ERS Abstracts) brings you, several times a year, descriptive listings of new publications from ERS.
To get on our free mailing list, send your name and address to: Reports, EMS Information, USDA, Room 1470-South, Washington, D.C. 20250.