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N abaee-Tabriz , Saeed
AN ECONOMIC ANALYSIS OF SOIL CONSERVATION LIMITATIONS ON THE INTENSITY OF CROPLAND USE IN OHIO
The Ohio State University Ph.D. 1985
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UniversityMicrofilms
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AN ECONOMIC ANALYSIS OF SOIL CONSERVATION LIMITATIONS ON THE INTENSITY OF CROPLAND USE IN OHIO
•*
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate
School of the Ohio State University
By
Saeed Nabaee-Tabriz, B.A., M.A.
it it * * A
The Ohio State University
1985
Reading Committee:
Norman Rask Approved by
D. Lynn Forster
Douglas Southgate
Fred HitzhusenAdvisor
Department of Agricultural Economics and Rural Sociology
ACKNOWLEDGMENTS
I wish to extend my special thanks to the many people who
assisted me in my doctoral program at the Ohio State University.
To Dr. Norman Rask for his excellent guidance, patience, and
encouragement in the development of this dissertation.
To the rest of my committee members, Drs. D. Lvnn Forster,
Fred Hitzhusen, and Douglas Southgate for their constructive
comments and assistance in writing this dissertaion.
To Dr. Don Eckert whose expertise provided the writer with a
great help on the agronomy aspects of the study.
To Mr. Mike McCullough for his technical assistance in
computer programming, and for his friendship and moral support.
To Mrs. Beth Burger and Mrs. Judy Petticord for their sincere
moral support and their professional advice in typing this disser
tation .
To my special friends and fellow graduate students, Adelaida
Alicbusan, Guaracy Vieira, Gill Miranda, Ming Ming Wu , and
Dowlat Budhram for giving me the moral support when I needed.
Finally, special thanks to my brother, Hamid who provided
me with the opportunity of graduate studies, and gave me his love and
invaluable support throughout my entire college education.
LIST OF CONTENTS
PageDEDICATION ........ ii
ACKNOWLEDGEMENTS ........... „........ m
LIST OF TABLES ............................................ vi
LIST OF FIGURES .......................... viii
Chapter
I. INTRODUCTION .......................................... 1
1.1 The Problem ............................. 11.2 Sources of Soil Erosion in Ohio 61.3 Needed Research in Ohio ......... 81.4 The Study Objectives ................ 10
II. THE PROBLEM OF EXTERNALITIES AND ALTERNATIVEMETHODS OF ABATING SOIL EROSION ...... 12
2.1 Introduction ....... ............. 122.2 The Problem of Externalities ............ 132.3 The Benefits and Costs of Soil Conervation 152.4 Alternative Methods of Abating Soil Erosion 16
III. REGIONAL DIFFERENCES IN SOIL CHARACTERISTICSINFLUENCING A0R1CULTUTAL LAND-USE IN OHIO .......... 30
3.1 Introduction ............................. 303.2 Ohio’s Soil Regions ..................... 303.3 Classification of Ohio Soils ............ 343.4 Regionalization of the S t a t e .......... 36
IV. METHODOLOGY .......................................... 43
4.1 Objective Function ....................... 444.2 Activity Matrix ........ 464.3 Restrictions 474.4 Soil Groups in the Model ................. 504.5 Universal Soil Loss Equation ............ 604.6 Alternative Tillage Systems in the Model. 61
iv
Page
V. RESULTS ............................................... 65
5.1 Major Model Scenarios ........................ 6 65.2 Cropland Utilization ........................ 6 65.3 Soil Erosion Impacts ........................ 825.4 Economic Impacts 855.5 Sensitivity Analysis ....... 93
VI. SUMMARY AND CONCLUSIONS .............................. 102
6.1 Summary ...................................... 1026.2 Conclusions .................................. 1046.3 Policy Implications and Needs for
Further Research ............................ 106
BIBLIOGRAPHY .............. 10?
v
LIST OF TABLES
Table Page
2.1.1. Funding for Soil and Water Conservationin the U.S. 195Q-1980 27
. Parameters of Price Determinant Equations...................114
4.4.1. Classification of Ohio Soils by Slope, Erodibility,T—value, Response to Reduced Tillage, and Productivity .. 51
4.4.2. Ohio Agricultural Cropland by Region and Slope ........... 54
4.4.3. Ohio Agricultural Cropland by Region and Erosion Class .. 56
4.4.4. Ohio Agricultural Cropland by Region, Productivity Category, and Crop Yield Levels ....................... 58
4.6.1. Description of Alternative Tillage Systems .......... 62
5.1.1. Major Model Scenarios .................................... 6 6
5.2.1. Changes in Ohio Crop Yield Levels by SoilManagement Group and Tillage System ..................... 67
5.2.2. Changes in Per Acre Production Costs of Ohio's Major Crops Under Conservation Tillage Systems ....................... 69
5.2.3. Ohio's Simulated Cropland Use Patterns by Region and Tillage Method, with and Without T-Restrictions onSoil Loss ........... 70
5.3.1. Simulated Annual Erosion Rates by Tillage System andSoil Loss Limits ................................... 83
5U4.1. Simulated Percent Changes in Ohio Agricultural Production Resulting from Tillage System Substitution and Soil Loss Restriction .................................... 8 6
5.4.2. Simulated Percent Changes in Ohio Agricultural Prices Resulting from Tillage System Substitution andSoil Loss Restriction by Region ......................... 87
5.4.3. Simulated Changes in Ohio's Average Crop YieldsUnder Alternative Tillage Systems ................ 8 8
vi
Table Page
5.4.4. Simulated Changes in Ohio Farmers? Net Returnsresulting from Changes in Tillage Systems and Soil Loss Restriction by Region ..................... 90
5.5.1. Simulated Percent Changes in Ohio Agricultural Land-Use?Production, and Prices at Three Levels of ExportDemand for Corn, Soybeans, and Wheat ................ 95
5.5.2. Simulated Percent Changes in Ohio Agricultural Land-Use Production and Prices at Three Levels of Expansionin Export Demand for Corn, Soybeans, and Wheat,Soil Loss Restricted to T—values....................... 96
5.5.3. Simulated Changes in Annual Erosion Rates at ThreeLevels of Expansion in Export Demand ................. 9 7
5.5.4. Simulated Changes in Annual Erosion Rates at TwoLevels of Expansion in Industrial Demand for CornUnder Conventional Tillage Methods ..... 100
vii
LIST OF FIGURES
Figure Page
1.1. Distribution of Estimated Tonnage Soil LostFrom U.S. Cropland by Seet and Rill Erosion in 1977 ... 4
1.2. Areas Where Loss of Soil From Wind and Erosionwas Estimated to Exceed 5 Tons Per Acre in 1977 ...... 4
1.3. Millions of Acres of Cropland on Which ErosionExceeded Tolerance Levels by State and Farm Production Regions ................. 5
2.1. The Divergence Between Social and Private OptimumLevels of Output ................................... 18
2.3. Comparison of Resource Costs of AbatementUnder Taxation and a Uniform Standard ................ 21
3.1. Ohio's Soil Regions ...................... 3 3
3.3. Ohio Agricultural Regions, ODOE State Model .......... 3 3
4.1. Illustration of Economic Surplus ...................... 46
CHAPTER I
INTRODUCTION
1.1 The Problem
Soil erosion is a natural process that occurs even without
human intervention. Excessive soil erosion, however, is usually a
by-product of interaction of human activities with land. A major
cause of excessive erosion is intensive agricultural use of land,
particularly for production of row crops which exposes unprotected
soil to wind and water.
In the United States, especially during the recent decades,
several factors have contributed to more intensive use of cropland.
A continuing growth in domestic population and per capita income have
favored grain-fed cattle, poultry, and other commodities based on row
crop farming. Furthermore, since 1972, the acreage of corn, sorghum,
soybeans, and wheat has increased substantially to meet increased
worldwide demand for these crops. Despite the present decline in
rapid growth rate of crop exports, further intensification of U.S.
agriculture may continue as world demands for food increase and new
(unconventional) demands upon agriculture are developed. Expanding
production of alcohol and sugar substitutes from grain are the major
examples of new demands made upon agriculture.
These developments, on the one hand, have contributed positively
to the U.S. balance of payments. On the other hand, they set off an
2
inflationary price explosion of farm commodites, farm inputs, and
agricultural land. Paying high prices for land in the 1970s, a large
number of farmers had been placed in a situation where they had to
"farm the hell out of the land" to maintain an immediate cash flow
and to be able to service debts (Heady, 1980). Specifically, land
purchased on credit at $4,000 per acre, tractors at $50,000-$75,000,
and cash rent at $150 per acre in the Corn-Belt, with parallel con
ditions elsewhere have given rise to high fixed costs in interest
rates and rents which have emphasized heavy immediate cropping at
the expense of future productivity (Heady, 1980).
The commodity-resource pricing complex which has encouraged
intensive cropland-use patterns, has also intervened with the
developing structure of U.S. agriculture. That is, under a rise in
the real price oJ farm labor against machine capital, the machinary
industry has generated Large tractors and complementary field
equipment that can pull 60-80 feet wide planters and tilling equip
ment. This has enabled many larger farms to specialized in row-crop
monoculture, resulting in an increased tempo of soil erosion (Heady,
1980).
The above-mentioned economic developments have given rise to
a continuously increasing concern over excessive loss of topsoil
from U.S. cropland. I'he ability of soil to tolerate erosion is called
the soil-loss-tolerance level, or T-value. The relation of T-values
to actual, rates of erosion and soil formation is highly important in
establishing what constitutes excessive erosion from the long-term,
societal point of view. T-value has been defined as the maximum rate
of soil erosion which will permit a high level of crop productivity
to .be sustained economically for the indifinite future (USDA, 1978a).
Accordingly, annual erosion rates exceeding T-values are considered
excessive. Typical T—values for many major agricultural soils in the
U.S. are between 3 to 5 tons per acre per year.
Avereage soil erosion rates are not strongly alarming for the
U.S. as whole, however, serious problems exist in many regions and
localized areas where rates of erosion exceed the rates of soil form
ation. According to the 1977 National Resource Inventories (NRI),
erosion is the most important conservation problem on 51% of the
nation's cropland (USDA, 1978b). In other words, about 97 million
acres, or about 23% of the 413 million acres of cropland in the U.S.,
suffer erosion which exceeds T-value. Such soils are deteriorating
and their long-term productivity is in danger. In the aggregate,
nearly 2 billion tons of topsoil are removed from U.S. cropland each
year. Figures 1.1 and 1.2 show the broad geographic distribution of
cropland erosion and the distribution of areas where wind and water
erosion exceeded 5 tons per acre per year in 1977.
Soil erosion is especially serious in the 12 north central
states. The long-term seriousness of this situation is emphasized
by the fact that these states produce 46% of the nation's food grains,
77% of the feed grains, 64% of the oilseeds, 42% of all crops, and
45% of all livestock sales (USDA, 1981a). The heart of this region
is the Corn-Belt, including Ohio, which is one of the richest agri-
4
Figure 1.1
Distribution of estimated tonnage o f soii lost from U.S. cropland by sheet and rill erosion in 1977. One dot equals 250,000 torts of soil. The tota l soil loss in 1977 was estimated at 2 billion tons. The m ost serious sheet and nil erosion occurred in the Corn Baft and Mississippi Defte states and in western Tennessee <U.S. Department o f Agriculture, 1980).
30.000 acni
Areas where loss o f soil from w ind and water erosion was estimated to exceed 5 tons per acre in 1977 One dot equals 30.000 acres. The loss exceeded 5 tons o f sort per acre on 241 million acres <U. S. Departm ent of A gricu ltu re , 19801.
5
cultural regions in the world. NRI data show that erosion losses of
5 tons or more per acre per year are common in this region, and
losses of 1 0 tons or more per acre per year occur on approximately
20 percent of row-cropped land (USDA, 1978b). Figure 1.3 shows the
situation of excessive soil erosion for the nation's different regions
in 1977.
From the standpoint of natural resource economics, there are
two major problems associated with excessive soil erosion.
1) If soil is allowed to erode too far, crop yields could be
Figure 1.3
303.11o
2.0 jrtpTN ortheast
0.5P a c i f i c
5 2 Northern \ 12 3 881 Plains \ ------- no 11“ t“ „ i Corn Belt 2.9
R 1 U 6-kuafMountain/ 0.1 I -^ A p p a la c h ia n
T q 2.7
S ou theast
2.8 \ 3.2 sDelta
StatesSouthernPlains
A la ska ■ Oata not a va ilab le H a w a ii 0 1C aribbean 0.2
M illio n s o f acres o f c ro p lan d on w h ic h the ra te o f shee t end n il e ro s ion e xceeded th e so il loss to le ran ce level by s ta te and farm p ro d u c tio n re g ion s in 1977 IU S D e p a rtm e n t o f A g r ic u ltu re , 1980).
depressed to the extent that commodity production costs and supply
prices rise sharply over the long-run, as natural formation capabi
lity of soil is depleted. In other words, intensive use of soil in
the present could inversely affect economic welfare of the future
generations through lower supply and higher prices of food and fiber.
2) The sediment resulting from erosion of agricultural land
which is the largest nonpoint pollutant by volume, imposes substan
tial external costs on society . The sediment may lower water
qaulity, or require removal in order to restore adequate drainage,
flood control or navigation. In the U.S., from the aforementioned
2 billion tons of soil which are pemoved annualy from cropland, only
about one-half billion tons reach the ocean, the rest are deposited
in uplands, flood plains, channel systems, and reservoirs (USDA,
1974).
1.2 Sources of Soil Erosion in Ohio
A. Water Erosion. Soil erosion by water is the dominant
hazard on almost 50 percent of Ohio cropland. Sixty-four percent of
the soil loss from the State's agricultural land is from cropland,
21 percent from forest, and 15 percent from pasture land (Ohio State
University, 1979). Estimated annual soil loss on Ohio's cropland
1/ Nonpoint pollutants are those environmental pollutants which do not originate from discrete locations. These include sediment, pesticides, minerals, natural organic waste materials, radio activity, and microbes (Abraham, 1982).
ranges from less than 1 ton per acre on nearly level cropland in
the northwest and up to 13 tons per acre on 12-18 percent slope
cropland in the southeast. T-values for Ohio soils range from 1 to
5 tons per acre per year. Excessive soil loss beyond T—values
results in soil structure damage and increased crusting problems,
reduced crop yields due to plant nutrient loss, and loss of available
water to plants by reduction of the water holding capacity of soil
(USDA, 1978b).
Types of water erosion include soil detachment, sheet erosion,
and rill erosion. Soil detachment is the breakdown of soil aggregate
and the scattering of small soil particles by falling raindrops. It
is the first step in water erosion and the formation of soil crusts.
The formation of a crust results in reduced ability of the soil to
absorb water, and consequently, more run off and erosion. Sheet
erosion is the removal of a uniform layer of soil material from the
surface by flowing water. Sheet erosion is not easily recognized,
but often removes 3-5 tons of soil per acre per year. Rill erosion
is the removal of soil particles by water flowing in small channels
or between rows. This erosion may result in movement of 7-10 tons
of soil per acre per year (Ohio State University, 1979).
B. Wind Erosion. Wind erosion can be another source of
sediment pollution, resulting in fine particles of soil material
being removed from the soil surface and carried by the wind. This
results in severe crop damage, soil loss, air pollution, and off-site
soil deposits. Wind erosion damage has been increasing on the
wind-erodible soils in northwestern Ohio. These are primarily
sandy soils of the flat lakebed region, but also include areas of
organic soils and fine-textured clay soils with finely aggregated
surfaces throughout the State. Studies on sandy-textured soils in
northwestern Ohio have shown soil losses caused by wind erosion as
high as 130 tons per acre per year during a severe windstorm (Ohio
State University, 1979).
Research has considerably increased the understanding of soil
erosion and the factors affecting it. Farmers now have a wide
variety of research-based soil and water conservation practices
from which to choose. Crop management and erosion control practices
are the main examples of these options. Specifically, soil conserving
crop management practices include crop rotations, conservation
tillage methods which increase vegetative cover for reducing run-off
and erosion, and incorporating of crop residues in the fall for
soil protection, plant nutrient utilization and greater fertilizer
efficiency ( USDA, 1978b). Erosion control practices include
contour tillage, stripcropping, terraces, and diversions with
stabilized waterways ( Ohio State University, 1979).
1.3 Needed Research in Ohio
For long-term societal continuity, there must be a balance
between human activity and a natural resource such as soil which
will permit permanent use of the resource '. From the echological
perspective, soil will be needed for food and fiber production into
9
the indefinite future. Hence, private and public actions are needed
to bring rates of soil loss by erosion into equilibrium with rates
of soil formation.
However, a policy or set of goals to eliminate excessive soil
erosion from U.S. cropland may pose important economic impacts upon
farmers and consumers. These impacts would be even more significant
from regional perspective when vast differences in soil characteris
tics and cropland-use patterns across the nation are taken into
account.
In Ohio, predominant substitution of soil conserving tillage
systems for conventional tillage practices, and imposition of T-value
limits on soil loss would each have a significant impact on the
State's agricultural economy. These impacts would emerge primarily
from the State's regional diversity of soil and topographic con
ditions which historically have resulted in a variety of cropland
use patterns and other agricultural activities. Specifically,
nearly 60 percent of the agricultural land in Ohio has slopes of
greater than two percent which can seriously erode if not properly
managed. The most erosive of this is in the southeast, where, the
average slope is about 12 percent. The remaining of the State's
agricultural land has little or no slope (less than 2 percent). A
large percentage of this is in northwestern Ohio. Since these
soils have little slope, minor concern has been given to soil loss.
However, erosion can occut on these soils because of their high
content of fine, collodial material that is easily dispersed and
10
carried by surface water runoff, the high percentage of intensive
cropping, and bare surfaces over winter and spring (Ohio State Univ
ersity, 1980).
Two major studies, Becker 1977, and Abraham 1982, have modelled
the economic impacts of conservation tillage methods and T—based
restrictions on soil loss in Ohio. Both of these studies are
region-specific. Becker's work focuses on the Honey Creek watershed
in north central Ohio, and Abraham's study covers northwestern Ohio.
These studies used a price-exogeneous (linear programming) model as
their quantitative tool of analysis. Linear programmign models as
will be described in Chapter IV, are built based on the simplistic
assumption of fixed output prices that does not allow the model to
determine the price flexibilities which take place in response to
some changes in policy.
The present study builds on this earlier work in several ways.
The diverse regional soil and type of farming characteristics of
Ohio agriculture, including regional economic inter-relationships
are incorporated into a price-endogenous programming model of the
State's agricultural economy. This is used to analyze the potential
land-use and economic impacts of alternative soil conservation
strategies for Ohio. The specific objectives are the following.
1.4 The Study Objectives
The general objective of this study is to determine the poten
tial economic trade-offs between alternative soil conservation
11
strategies and Ohio agricultural production, farmers' net returns,
and consumers' surplus. Three different tillage systems, and T-values
will be evaluated through a multi-region, soil-specific, and price-
endogeneous programming model of Ohio's agricultural economy.
The operational objectives are to determine the following:
1 ) the soil-specific cropland use patterns under the alternative
tillage methods, with and without limiting annual erosion to T-values;
2) the changes in the State's average and regional erosion rates
resulting from soil conserving tillage practices and T-value rest
riction of soil loss;
3) the impacts on agricultural production, farm prices, crop
exports, farmers' net returns, and consumers' surplus from tillage
system substitutions and T-value. restriction of soil loss;
4) sensitivity of the model to some potential expansions in
export demands for grain and soybeans, and domestic industrial
demand for corn, under alternative tillge systems, with and without
T—value limitations on soil loss.
The three different tillage systems which will be incorporated
into the model are conventional tillage (moldboard plow), conser
vation tillage (chisel plow), and no-tillage, These tillage systems
are described in detail in Chapter IV.
CHAPTER II
THE PROBLEM OF EXTERNALITIES AND ALTERNATIVE METHODS OF ABATINGSOIL EROSION
2.1 Introduction. "The economic arena is one of conflict. Given
that resources are scarce, that production possibilities are limited
by technology, and that individuals are both selfish and insatiable,
how could it be anything else?" (Randall, 1981).
The conventional or the so-called neo-classical economic theory
views the markets as incredibly effective devices for conflict
resolution. According to this theory, markets could establish prices
that provide incentives for production, generate personal income,
distribute commodities among consumers, and provide a flow of
information about relative scarcity. In this way, markets would
allocate resources and distribute commodities effectively without
the need for institutional intervention. To the conventional
economic wisdom, allocation of resources is efficient when a profit
maximizing firm operating under perfectly competitive system,
produces the level of output at which price equals marginal cost.
This level of output is then assumed to be socially optimum imply
ing no divergence between social and private costs (Langham, 1972).
However, in many real world situations the market mechanism
fails to secure a socially efficient allocation of resources.
"Market Failure" in the context of the natural resource economics
refers to any divergence between the market price of a resource
(reflecting private costs) and those prices that would have to exist12
11
(reflecting social costs) if a socially optimal state ol resource
utilization is to be secured. For example, some functions of
environmental resources such as their waste receiving facilities are
generally not marketed at all. But their ’shadow’ price (the price
that would exist if these functions were marketed in an optimal way)
is clearly positive because using the environment in this way would
preclude its use from other purposes. Specifically, if we permit
watercourses to be used as dumps for municipal and industrial wastes,
or to be saturated with cropland sediments, we preclude that resource
from alternative uses such as fishing, navigation, recreation, etc.
However, if prices were charged for using waste receiving facilities
of the environment we would expect a different pattern of uses compared
to a situation in which prices are not charged. The failure of the
market mechanism to recognize the 'shadow' prices associated with the
use of the similar functions of many natural resources results in the
divergence between social and private costs.
This chapter attempts to explore a major source of the
market failure , the so-called externalities, which are pertinent to
utilization of many natural resources including cropland. It will
further discuss the benefits and costs of soil conservation, and
finally will identify alternative economic methods of dealing with
soil erosion problem.
2.2. The Problem of Externalities. Effects upon economic agents
not associated with their own economic activities are called
14externalities (Davis and Kamien, 1977). Alternative terms for
externalities are "spillovers", "external effects", and "social
"effects" (Mishan, 1976; Dasgupta and Pearce, 1974; and Pearce
1976).
While the contemporary economic literature distinguishes
many kinds of externalities, for the purpose of this study, it is
necessary to focus on so-called "technological, or non-pecuniary
external diseconomies". This type of externality refers to those
costs that one economic agent might impose on another, or perhaps
on all members of society — . Technological external diseconomies
arise when there is a lack of institutions which i\/ould insure that
individuals pay for all costs of their actions. External costs
prevent the market mechanism from functioning efficiently and result
in the divergence between social and private costs (Davis and Kamien,
1977).
An important case of external diseconomies, which is related to
the subject matter of the present research, is the sediment problem
caused by soil run—off from agricultural land. Looking from the
standpoint of natural resource economics, soil erosion imposes two
types of external costs on society:
i) depleting the long-run productive capacity of the cropland;
ii) contributing significantly to the non-point source pollution
_1/ Pecuniary externalities refer only to changes in prices as a result of individual decisions. Since they pose no problem for market economy, their discussion in this study is unnecessary.
15
of the waterways.
The first of the above external costs can be interpreted as
inter-generational or user costs reflecting the present value of
future sacrifices associated with the loss of a particular unit of
topsoil. The second of the above, represents the so-called
off-site damage costs, major examples of which include lost reservoir
capacity, increased flood damages, increased navigational channel
dredging, and water treatment costs. These external costs are
imposed upon present as well as future generations. In fact, crop
land sediments comprise almost half of the total amount of sediments
entering the U.S. waterways (Bogges, ejt £l. , 1980). Monetarily,
these damages have been estimated to be nearly a billion dollars
per year (Cooley, 1976).
Existence of the aforementioned external effects calls for some
collective measures to eliminate or internalize these social costs.
Accordingly, the succeeding sections of this chapter discuss the
benefits and costs of soil conservation, and alternative ways of
abating soil erosion.
2.3 The Benefits and Costs of Soil Conservation.
A. Benefits The benefits of a soil conservation policy may
be divided into two categories. 1) a reduction in off—site damages
due to sedimentation of streams, rivers, and lakes; also, there may
be reductions in levels of some plant nutrients in these surface
waters, particularly, phosphorus which tends to be chemically bound
16
to soil particles. 2) Preserving the productive capacity of soils
for a longer time than if no conservation measures were practiced.
From the productivity standpoint, if conservation is successful,
then a benefit will accrue to society through larger supplies of
agricultural products at sometime in the future.
B. Costs. The costs of a soil conservation program may also
be placed into two categories. 1) The costs that are incured by
society in forms of program payments and/or administrative costs
in encouraging or forcing land-owners and farm operators to
practice soil conservation methods that they would not ordinarily
use if acting on their own individual self-interest. 2) The costs
to society that would emerge from adoption of conservation tillage
methods and/or land-use restrictions. These conservation measures
may reduce current farm output and increase food prices for the
present generations. They may also result in some off-site damage
costs as a result of more intensive application of fertilizers in
substitution for the land to be set aside, and additional herbicide
and pesticide loads used under conservation tillage systems.
2.4 Alternative Methods of Abating Soil Erosion.
A. Theoretical Approach The economic literature of external
ities identifies three major approaches for correcting environmental
externalities including soil erosion. These approches are the
following:
(1) tax-subsidy solution,
17
(.2) soultion hy regulation or standards, and
(3) market or bargaining solution.
Tax-Subsidy Solution. as discussed earlier in this chapter, the
economic approach to environmental problems requires us to think of
soil erosion as an external cost, and to identify the socially optimal
level of these costs. Invariably, this level will not be zero, since
some positive amount of soil loss is justified. Figure 2.1 shows the
situation of a perfectly competitive farm firm for which the demand
curve ( PP ) is perfectly elastic. MPS represents marginal private
costs which differ from marginal social costs (MSC) by an amount equal
to marginal external costs (MEC), i.e., the marginal cost of soil
erosion. The private optimal level of output for this firm is at X ,P
but at this level of output external costs of Ocd (the two shaded
areas) are imposed. The social optimum output is at Xg , where, the
product price ,p , equals MSC. Moving from the private to social
optimum saves external costs ol abed but leaves Oab external costs.
One method of achieving the socially optimal level of output,
Xg, at the optimal level of soil loss, Oab, is to tax the farmer
according to the undesirable external costs he imposes on society.
Mathematically, it can be proven that the optimal tax is equal to MEC.
That is, social profit is maximized by setting a tax equal to marginal
erosion cost at the optimal output. The firm will now bear the
external costs in form of a tax which it will obviously treat as a
private cost. In this way, the external cost is said to be 'inter-
18
MSC MPC+MEC
c o s t , revenue
price MPC
MR
Output
= AR
Figure 2.1
The Divergence Between Social and Private Optimum Levels of Output
nalized' .
Alternatively, the correction of externality may be approached
by subsidizing the firm at the rate of S = MEC for every unit of output
produced below X^ upto Xg . The decision by the firm to produce a unit
of output beyond Xg implies that the foregoing of the subsidy on that
output. Accordingly, the firm will choose to produce at X^ in order to
benefit from the total amont of subsidy, abc.
Both the taxation and subsidy schemes result in exactly the
same net social gains. However, in terms of income distribution, the
firm is better off under a subsidy scheme and the rest of society is
worse off. While, under a taxation program the opposite is true. A
major difficulty with the tax solution is that it requires knowledge of
the magnitude of the marginal damage costs which may not be readily
19
available. While, the problem with subsidy program is that it
requires knowledge of the socially desirable level of output (X in
Fig. 2.1) which may not be readily available either.
Solution by Regulation or Standards. In practice, many environmental
policies are implemented via standards. For each polluting firm a
government agency will determine the maximum permissible level of the
externality. Soil erosion standards can be determined either in terms
of the soil loss tolerance levels (T-values), or based on the desired
quality and assimilative capacity of receiving environment (e.g., a
given river should not receive more than a certain amount of sediment,
annually). In order to assure that farmers will comply with a given
erosion standard, some penalties can be identified and enforced.
Penalties may take various forms: lump-sum fines or fines for each
cropping season the standard is violated, and fines per unit of soil
loss beyond those permitted under the standard, etc.
In the real world, conceptual and empirical difficulties make
it unlikely that a regulatory agency could succeed in setting a
standard exactly equal to the efficient level of abatement (i.e., the
level at which marginal social benefits of abatement equals its
marginal social cost). The setting of the penalty is not conceptually
difficult: it simply needs to be so high, and so well enforced that,
all polluters will prefer to comply with the standard. Howevere,
government agencies have exprienced substantial political pressures
militating against such effective penalities (Pearce, 1976).
20
Taxes versus Regulations Most of the economic literature on environ
ment, such as Randall,1981; Davis and Kamien, 1977; Pearce, 1976;
and Layard and Walters, 1978 tend to argue that taxes are the least-
cost method of securing a given level of pollution abatement. A
brief elaboration of this argument using an example from Randall is
presented below.
Let's consider a three firm industry which emits a particular
kind of pollution. The respective marginal abatement cost curves of
these firms (MAC)^, (MAC)2, and (MAC)^ are shown in Figure 2,2.
Now, if a fixed rate emmission tax is imposed on this industry, each
firm will act to abate its pollution discharge upto the point where
its marginal abatemeent cost (MAC) equals the tax rate. Accordingly,
the respective abatement levels of these firms are shown by Q^,Q2 ,and
Q^, in Figure 2.2. Under this scheme, the total resource copt
of abatement is equal to (OAQ^+OBC^+OCQ^). Now, if instead of tax,
a uniform standard is enforced such that each firm is required to
provide pollution abatement of Q2> the total resource cost of abate
ment will be equal to (ODQ2+OBQ2+OEQ2). In order to let the total
amount of abatement under two schemes be the same, Figure 2.2 is
drawn such that (Q^-K^+Q^) = 3Q2 and ~ Abstraction
of the total resource cost of abatement under taxtation from the one
under standard yields: (DQ2Q^A - CQ^Q2E). DQ2Q^A is greater than
CQ^Q^E, since (Q2~Q0) = ((>2-Q^) . Thus, the total resource cost of
abatement under taxation is less than the one inder regulation for
21
Lhe same level of abatement.
(MAC)s t a n d a r d .
/
(MAC)
(MAC)
Z e r o p o l l u t i o n
Figure 2.2
Comparison of Resource Costs of Abatement Under Taxation and a Uniform Standard
It is important to note that the strength of the above
conclusion, heavily relies upon the assumption of setting a uniform
standard . However, the inefficiency of a regulatory scheme mav be
avoided through application of differential standards. That is,
varying levels of abatement requirements can be established with
regard to the differences in polluting firm’s economic and technolog
ical constraints in providing the abatement. In the above example,
the emissions tax is more efficient than the standard because it
encourages the most efficient supplier of abatement, the firm with
(MAC)^, to provide the most share of abating, and the least efficient
22abator, the firm with (MAC)^, to do the least abating. While, under
the uniform standard, regardless of its highest MAC, firm 1 is
required to provide the same amount of abatement as the other two.
This is the major reason for inefficiency.
In general, emissions taxes may have the advantage of
providing continuing incentives for innovations and investments in
pollution abatements which would reduce both the remaining emissions
and the pollution-associated costs with the polluter.
As far as the soil erosion abatement is concerned, the
availability of soil loss tolerance levels (T-values) makes the use
of both taxation and differential standards two alternative policy
options. The present study will incorporate T-based differential
standards to analyze the economic impacts of soil erosion abatement
in Ohio . The specific procedure for using this policy option will
be discussed in Chapter IV.
Market or Bargaining Solution. Coase, I960, has theoretically
proven that "given non-attenuated property rights, trade among the
involved parties will eliminate (Pareto-relevant) externalities,2/resulting in an efficient solution" — . The economic logic behind
the Coase Theorem is that it will be in the interests of the acting
and affected parties to enter a bargaining process to correct the
externality since there are potential benefits to be gained from such
2 / Pareto-relevant externalities refer to those technological external dis-economies that can be modified to make the affected party better-off without making the acting party worse-off.
23
bargaining. But in reality, the bargaining solution faces many
problems. First, it depends on sufficiently well-defined property
right. Second, it presumes that external costs in question involve
readily identifiable parties. Consequently, a bargaining solution
does not seem to be applicable to more complex or non-point cases
of externalities such as soil erosion. Erosion entails a large and
probably unidentifiable number of sufferers, and it is uncertain in
magnitude, liable to occur at considerable geographical distance
from the source of emraision, and is liable to occur at a point in
time quite far from the time of eramision. For these reasons, it
is less likely that farmers and sufferers ever could come together
to bargain.
B. Soil Conservation Strategies in Practice
The aforementioned corrective approaches to externalities are
principally general within a theoretical framework. Looking from
the real world perspective, this section focuses on the major U.S.
soil conservation efforts in the past and present, and some future
policy alternatives of achieving control of excessive soil erosion.
The Past and Present Soil Conservation Efforst. In the U.S.,
the first public program to aid in soil conservation were enacted in
1930s. These programs provided financial and technical assistance
to encourage land owners and farm operators to control excessive
runoff and erosion.
Initially, soil conservation practices were presented to farmers
as ways to maintain soil productivity and promote viable farm
operations. However, unlike many other farm policy issues that call
for rapid and dramatic governmental action during crisis, conserv
ation efforts remained in the background for many years. Low farm
income and commodity supply problems .especially in 1960s, diverted
the policy makers' attention from conservation goals (Clawson, 1976)..
Recent legislative efforts, namely, the Soil and Water
Resources Conservation Acts of 1972, and 1977, demonstrated that many
politicians and farm leaders feel that the goal of soil conservation
deserves a renewed federal commitment. These Acts have directed the
U.S. Department of Agriculture to undertake a thorough examination
of existing soil resources (USDA, 1980).
Currently, public programs are carried out at local, state,
and federal levels. Thirty-four programs administered by the USDA
have a conservation mission or componenet (CAST,1982).The programs are
carried out to inform the public about soil and water conservation,
identify and locate conservation problems, develop proposed solutions,
and establish institutional agreements for action. The programs
provide cost-sharing, loans, on-site technical assistance in
planning, research, and education. A brief description of these
programs follows.
Cost-Sharing (Subsidy). The cost-sharing strategy which
has been studied more than any other over the past four decades has
been Agricultural Conservation Program (ACP). Since 1936, ACP has
expanded over $8 billion to assist farmers and landowners In adopting
soil conserving practices. This program, during the period of excess
agricultural capacity (1950s and 1960s) was criticized for assisting
25
short-term output enhancing practices such as drainage, irrigation,
and liming rather than soil conservation (Conter, 1964).
Low Interest Loans. The low interest loans for conservation
practices would seem to be well suited to deal with two types of
problems,, First would be private discount rates that are higher
than those society would select for long-term investment decisions.
Second would be farm operators or landowners who have time prefere
nce that are shorter than those of society. The problem is to
identify those cases and to estimate the reduction in interest
rate necessary to bring the private soil conservation investment
up to the level desired by society. Currently, federal loans for
conservation practices account for only 3 percent of the investment
in selected conservation practices (USDA, 1981).
Technical Assistance, Research, and Education. Technical
assistance and educational programs help reduce information or
knowledge gaps and complement other strategies. Examples might be
information concerning a new or no-till farming system from a land
grant university, or SCS's help in designing terraces. Educational
and technical assistance can be an important part of any soil
conservation strategy involving new practices or special design and
layout problems (CAST, 1982). Yet, just the lack of information
about programs may be a restraint to soil conservation. For
example, a survey by Leitch and Danielson,1979, found that the
primary reason for farmers not participating in waterland programs
was the lack of information concerning the available program.
26
The total federal funding of the aforementioned programs was
nearly 1.5 billion dollars in 1980. Table 2.1 shows the distribut
ion of the federal expenditure on these programs for the period of
1950-1980.
The combined effects of public programs and private soil
conservation efforts over the past 45 years has been substantial.
Although, U.S. waterways currently receive an estimated 3.5 billion
tons of soil per year, soil conservation programs have been credited
with preventing the loss of an additional one billion tons (Abraham,
1982).
Some Policy Options for the Future. The Council for Agricultural
Science and Technology (CAST), in its 1982 report has suggested
two general objectives of achieving control of excessive
as a base for considering policy alternatives for the future.
i) Protect U.S. soils from excessive runoff so as to retain
indefinitely the capability to produce crops for food, feed, fiber,
and energy to meet national needs, with consideration of apDropriate
exports.
ii) Protect water resources from unwarranted damages by
sediment and other pollutants from excessive soil erosion.
To attain these goals the Council has outlined a number of policy
alternatives for the future. The foregoing section focuses on these
policy alternatives.
Regulations. Each landowner or farm operator could be
T a b le 2 .1 .1
F u n d in g f o r S o i l and W ater C o n s e r v a t io n i n t h e U .S .
1950-1980
y e a r jC o s t :
S h a r in g :T e c h n ic a l : A s s i s t a n c e :
R eso u rc em anagem ent : L oans
R e se a r c h: •
••
E d u c a t io n T o t a l >"1572
d o l l a r s
1 9 5 0 -5 4 1 ,2 4 6 291 98
m i l l i o n
16
d o l l a r s
5 NA 1 ,6 5 5 3 ,0 3 1
1 9 5 5 -5 9 1 ,3 6 3 352 144 67 21 NA 1 ,9 4 7 3 ,1 8 7
1 9 6 0 -6 4 1 ,5 8 4 454 322 80 47 NA 2 ,4 8 7 3 ,8 7 4
1 9 6 5 -6 9 1 ,6 8 1 643 381 141 112 NA 2 ,9 5 8 4 ,0 3 5
1 9 7 0 -7 4 1 ,7 2 5 953 747 192 171 54 3 ,8 4 2 3 ,8 0 8
1 9 7 5 -7 9 2 ,3 7 7 1 ,4 3 3 1 ,7 2 2 313 309 44 6 ,1 9 8 3 ,8 9 3
1980 487 327 458 62 91 11 1 ,4 3 6 717
S o u r ce : I n i t i a l r e p o r t on t h e Land and w a te r C o n s e r v a t io n P ro g ra m s, USDA, D ec . 1 9 7 7 . U p d ated by
D a l la s L e a , N a tu r a l R e so u rc e E con om ics D i v . , E SS, USDA, F eb . 1 9 8 1 .
28
required to develop and implement a soil conservation plan. A number
of years would be required to develop and implement such plans and to
install the needed conservation practices. In many cases, substantial
progress could be made toward compliance by simple changes in tillage
practices which could significantly reduce erosion with little or no
added costs.
However, implementation of such a policy would challenge
some existing beliefs about social equity. Some research findings
suggest that a regulatory policy would have the greatest negative
impacts upon small farm operations located on poor quality land with
operators lacking managerial capacity or capital to adopt many of the
recommended practices. To counter this potential inequality,
a desirable feature of any regulation would be flexibility to include
consideration of managerial and other characteristics of a specific
farm operation including the soil characteristics such as T-values.
Investment Tax Credits. For some farmers, tax implications
exert a powerful influence upon their decisions. If investment in
conservation practices and equipment were given liberal tax breaks,
these activities might increase significantly.
Conservation Incentive Payments. A farmer would be offered
a payment based upon estimated soil loss reductions due to changing
of farming practices. It would encourage control of erosion whenever
the payment offered exceeded the sum of the control costs and the
crop income reductions. Problems of this alternative would be likely
29
in determining the appropriate payment rates and in documenting whether
or not the standards of soil conservation applicable to a particular
field or farm had been met.
Taxation of Soil Loss. Under this scheme, farmers would pay
taxes on the estimates of soil losses exceeding soil loss tolerance
limits and thus would be expected to adop conservation practices to
avoid the tax. Previous studies (Seitz, et_ al., 1978; and Taylor
et al., 1978) suggest that such a tax system would achieve erosion
control efficiently. However, it would likely meet with considerable
resistance from agricultural community,, This system would tend to
penalize farm operations on highly erodible lend. Farms on such land
are usually smaller, and owners or operators often have lower manag
erial capabilities and less economic flexibility than those on high
quality land with less erodibility.
Cross-Compliance. This would be a policy requiring control
of erosion to a certain degree or in some specified way, for a farm
operator to be eligible for other governmnet agricultural programs.
For example, a farmer might be required to demonstrate effective soil
conservation practices to be eligible for crop price support payments
or loans. Another from of cross-compliance would provide crop price
support payment bonuses to farmers with adequate soil conservation
programs.
CHAPTER III
Regional Differences in Soil Characteristics Influencing Agricultural Land-Use in Ohio
3.1. INTRODUCTION. As specified in Chapter I, a major objective
of the present study is to determine the potential impacts of soil
conservation strategies on the pattern of agricultural land-use in
Ohio. Since the State has a wide variety of soils (i.e., more than
500 soil types), achievement of this objective requires knowledge of
the basic characteristics of these soils and their regional locations
Accordingly, this chapter explores the following:
i) regional classification of Ohio soils on the basis of
their origin and parent materials,
ii) classification of Ohio soils based on the so-called
'capability class'; and
iii) regionalization of the State for model formulation.
3.2. Ohio's Soil Regions. The soils of Ohio have been classifie
by soil specialists into eight major soil regions (Figure 3.1) This
classification has been performed on the basis of soil properties as
they relate to the parent material and the length of time they have
been exposed at the surface of the earth. Most soils in the western
half of the State have been derived from limestone and have a fairly
high soil pH throughout the profile — ^, while those in the eastern
j_/ Soil reaction, pH, is a measure of the intensity of acidity oralkalinity. Most of Ohio soils have pH values ranging from 4.0 to 8.5. The higher the pH, the lower intensity of acidity.
31
Figure 3.1
Oh io1s Soil Reg ions Source: Ohio State University, 1981
half of Ohio have been derived, for the most part, from sandstone and
shales and tend to have a lower pH (Sitterley, 1935).
Approximately, 3/4 of the State has been involved in several
glacial inva'ions which have affected both its soils and topography.
Topographically, the glaciers tended to have a leveling effect.
They have left most of the land surface in western Ohio level to near
level. In the eastern half of the State, only northern and a part of
the east central areas were glaciated. The remainder of eastern Ohio
along with all or parts of five counties in southwest were unaffected
by glacial action. The topography in unglaciated Ohio can be
characterized as generally rolling or hilly, with parts rough and
broken (Sitterley, 1976). The following briefly describes the
general classification of Ohio soils as shown in Figure 3.. 1.
Soil Region I . This region consists of soils in high lime
glacial lake sediments which include the great lake plain area of
northwestern Ohio. The larger part of this region is occupied by flat
areas of dark-colored, natutally poorly-drained clay soils such as
Brookston, Paulding clay, and Toledo silty clay. With adequate drain
age these heavy soils are very suitable for corn, sugar beets,
and similar crops. In this region the associated heavy light-colored
soils such as Nappanee and Fulton silty clay loam are of only fair
agricultural value.
Soil Region II. Soils of this region are fine-textured and
have been developed from "calcareous glacial drift" . They include
some of the most fertile lands in Ohio. The light colored soils have
been leached of lime to a depth of 24 to 36 inches and are commonly
slightly acid in reaction in the surface soil. These soils with
adequate artificial drainage include some of the best corn land in th
State.
Soil Region III. Soils in Medium-Textured High Lime
Glacial Drifts: these soils have the same general features
of those in Soil Region II, except that the size of soil particles in
this region are larger.
Soil Region IV. Old Glacial Limestone Soils: this soil
region includes glacial limestone soils derived from "very old cal
3 J
careous glacial drift" which has been leached of lime to a depth of 8
to 10 feet. Because of this extreme leaching these soils are all very
acid in reaction and relatively low in natural productivity. Those
with fair to good natural drainage are of fair agricultural value,
whereas the very pooly-drained gray soils would be ranked as low in
value.
Soil Region V . Lacustrine Sandstone and Shale Soils: the
narrow belt of lake plain soils in northeastern Ohio includes much the
same range in texture as in northwestern Ohio. Being derived primarily
from sandstone and shale material these soils are naturally acid in
reaction. The area of dark colored heavy soils is somewhat limited.
In this region, the sandy soils are well adapted to truck crops and
fruits.
Soil Region VI. These soils have been derived from galcial
drift made up largely of non-calcareous sandstone and shale. Where
sandstone predominates the subsoils are open and porous, making it
possible to drain the wet area by tilling fairly easily. The soils
with fair to good natural drainage are some of the best grain soils
in the State.
Soil Region VII. Residual sandstone and shale soils: this is
the largest residual soil region in Ohio. Glaciation has had little
influence on the soils in this area. As a result, topography ranges
from nearly level to extremely steep. The residual soils derived
from sandstone and shale are acid in reaction and of fair fertility.
34
Soil Region VIII. This area in Adams and adjointing counties
includes residual soils from limstone or from limestone and shale.
A considerable proportion of the area has a very steep topogarphy.
These sloping lands vthich are well supplied with lime are excellent
for pasture and legumes like alfalfa.
3.3. Classification of Ohio Soils Based on Capability Class.The nature of the above classification is very general in the
sense that it groups the Ohio soils principally on the basis of origin
and parent materials. There is a second method which has been use
to classify soils of the State for their agricultural potential by
capability class . These range from Class I soils which have few
limitations for producing crops through Class VIII soils which are
not capable of producing crops or timber and are suitable only for
wildlife, water supply, recreation, etc.
The following is a brief discription of the eight land
capability classes adapted from the USDA Conservation Needs Inventory
Committee (CNIC) report for 1971.
Class I. Soils with few limitations that restrict their use.
These soils are on slopes of 0 to 2 percent. They are medium textured,
deep, well drained with good water holding capacity. They are suited
for continuous use for row crops, small grains, hay crops, and pasture
as well as vegtables and other specialty crops.
Class II. These soils have moderate limitations tli.iL affect
the choice of plant grown or that require the use of moderate
3 5
conservation practices. These soils based on their dominant hazard
have been divided into three subclasses: He, IIw, and IIs. The
respective dominant hazard or problem in their use are erosion,excess
water, and root limitations.
Class III. Soils with severe limitations which influence
the choices for plants and require special conservation practices.
Similar to Class II, the subclasses of this category are IHe, IIIw,&
Ills, which represent respective limitations of erosion, prolonged
wetness, and shallow depth to bedrock.
Class IV. Soils with very severe limitations that restrict
the choice of plants, require very careful management or both.
The subclasses of these soils are IVe, IVw, and IVs. The respective
limitations of these are severe erosion, drainage, and shallow depth
to bedrock.
Class V. These soils are neary level so they have no erosion
problems but have limitations that are impractical to remove. They
frequently overflow or are stoney or shallow.
Class VI. Soils in this class are generally unsuited for
cultivation. They usually need liming, fertilizing, water diversions,
drainage ditches, etc.
Class VII. Soils with very severe limitations but with good
management 5 they can be safely used for grazing and woodland, the
physical conditions of these soils are such that it is impractical
to apply improvements such as lime, fertilizer, water control, etc.
36
Class VIII. Soils and land forms in this class have
limitations that preclude their use for commercial plant production
and restrict their use to recreation, wildlife, water supply, or
similar purposes.
3.4. Regionalization of the State for Model FormulationFrom the economic standpoint, the aforementioned differences
in soil characteristics within the State have varying degrees of
comparative advantage in terms of crop yield levels and production
costs of each region to specialize in different agricultural
production activities. In turn, the differences in comparative
advantage among regions have resulted in a tremendous diversity in
agricultural land-use in Ohio. The general structure of this diversity
can be described by the greatest concentration of land under corn
and soybeans in the west/northwest, of dairy activities in the north
east, and of woodland and pastureland in southeastern Ohio.
A major problem in attempting to model the economic trade-offs
between soil conservation policies and agricultural production levels
in Ohio emerges from the above mentioned diversity in cropland use
within the State. In other words, analyzing the State as one homo
geneous unit would not permit a realistic representation of its
differences in soil series and agricultural production activities.
Thus, in order to build a reliable model for achieving the objectives
of this study it is necessary to divide the State into subareas
which are relatively homogeneous with respect to physical character
istics and current agricultural production patterns.
37
Based on the regional differences in soil characteristics and
land capability classes described above, Sitterley's subareas, and
major transportation nodes Ohio was divided into seven agricultural
regions (Fig. 3.3). The following describes main features of these
regions which have been incorporated into the model used in the
present study.
Region 1 This region comprises 14 counties in northwestern
Ohio. Most of this region was covered by water (Lake Maumee) some
thousand years ago during the glacial period. Topographically, with
minor exceptions the are is quite level and when artificially
drained is highly productive. In terms of percent of land suitable
for cropping this region ranks the second among the seven regions.
In 1982, 28 percent of the harvested crops was corn, 47 percent was
soybeans, and the remaining 25 percent was comprised of small grains
and vegtables (Ohio Agricultural Statistics, 1983).
Region 2. This region is formed of 18 counties in western
Ohio. Approximately 97 percent of the total land in this region was
classified by CNIC as capable of being used for crop production with
proper erosion control practices. The most visible features which
distinguish this region from region 1 are the larger concentration of
corn and livestock production and the higher percentage of total land
being in farms. In 1982, 41 percent of the harvested crops acreage
was corn, 39 percent was soybeans, and the remaining 20 percent was
39
comprised of small grains, hay crops, and fruits. In terms of the
total land in farms as well as in terms of percent of land considered
suitable for cropping, this region ranks first among the 7 regions.
Region 3 contains 17 counties in northeastern Ohio. For
the most part, this region was settled by the Pennsylvania Dutch who
brought with them a livestock and wheat farming* It mostly was
covered by glaciers of the Wisconsin Ice Age, resulting in formation
of glacial soils derived from sandstone and shale. In 1982, one acre
out of every four was occupied by urban uses and slightly
more than 44 percent of the total land was in farms.In the same year,
cash receipts from livestock was approximately 75 percent of total
cash receipts from farming.
Region 4 consists of 13 counties in the central section of
eastern Ohio. These counties are part of Appalachian Highlands
and are either predominantly or totally unglaciated. The soils are
largely derived from sandstone and shale are deficient in lime.
Except for a limited amount of river land, the topography ranges from
hilly to rough. This makes the land highly erosive if used for crop
production. The CNI has classified only 63.5 percent of the land
in this region as suitable for crop production, compared to the 84.0
average for the State. The small and irrigular shaped areas suitable
for cropping are generally inconvenient and costly to use lor ctop
production. In 1982, crops where harvested on 12 percent of total
land area or 23 percent of the land in farms. Hay was the region's
most imporatnt single crop in terms of acreage, followed by corn.
4 0Region 5. This region is comprised of 11 counties in
southeastern Ohio. Similar to Region 4, this area is part of the
Appalachian Highlands. Topographically, the area is hilly to rough
and in places broken. This makes the land very prone to erosion if it
is used for crop production. Only slightly more than half of the
total land was identified by CNI as suitable for crop production
provided that intensive erosion control practices are employed. In
1982, crops were harvested on 7 percent of the total land area. Hay
followed by small grains were the region's major crops.
Region 6. It forms a seven-county transitional group
in cenrtal Ohio. This region is the dividing line between the
geological limestone outcropping to the west and sandstone and shale
to the east. These counties were glaciated during the Illinian and
Wisconsin Ice Ages, as were the counties to the east and north.
However, because of the direction of the ice flow and some
differences in the nature of the parent material out of which the
soils were derived, many different soil types as well as signi
ficant differences in topography exist. Consequently, none of
these counties fit well into the adjacent regions. CNI has
classified 74.7 percent of the land in this region as suitable
for cultivation with proper erosion control practices. In 1982,
70 percent of total land in the region was in farms. Corn was the
most important single crop in terms of harvested acreage followed
by soybeans and hay crops.
41
Region 7. This region includes eight counties in southwestern
Ohio. Most of this area was covered by Illinoian Glacier. However,
the southeastern parts of Brown and Adams counties were not affected
by glaciation. In this region, the topography ranges from level to
steep and broken with both drainage and erosion being major hazards.
Approximately, 26 percent of the land in this region was classified
by CNI as not suitable for crop production. In 1982, about 55 percent
of the total land was in farms, and almost 30 percent of the total
land was in forests. Nearly 20 percent of the total farmland was
used for pasture,and crops were harvested in 33 percent of the total
land in farms.
Analyzing Ohio's agricultural economy based on the above
regions allows us to determine the potential land—use and economic
impacts resulting from implementing alternative soil conservation
strategies, and expansions in export/and or industrial demand for the
State's major crops more accurately. For example, as it will be shown
in Chapter V, . 1—value restriction of soil loss would pose
different land-use and economic impacts on each of the seven regions
described above. Alternatively, the main impact of a major rise in
idustrial demand for corn on regions 1 and 2, where most of the land
'.nut is suitable lor row crops has already been utilized for that
purpose, would consist of corn production expanding at the expense of
oLiier crops. Whereas, such a change in demand for corn, would reverse
a long, declining trend in row crop production in the State's most
42
erosive regions, i.e., eastern and southeastern Ohio, by possible
conversion of woodland and pastureland into cropland. Therefore,
from the policy making standpoint, regionalization of the State as
described above, seems to be an essential part of a programming model
which is designed to represent an accurate picture of Ohio's
agricultural economy.
CHAPTER IV
METHODOLOGY
4.1 Introduction. To achieve the proposed objectives, this study
uses a mathematical programming model as its quantitative tool of
analysis. Mathematical programming (MP) models are optimization
techniques with wide application in economics and business. The MP
technique used most often in agricultural policy and planning are
linear programming (LP) and quadratic programming (QP). For example,
several previous studies on the economic impacts of restricting soil
loss at the watershed level (Alt, 1976; Kasai, 1976; Forster, 1978;
Forster and Becker, 1979; Abraham, 1982; and Narayanan, 1974), at
the state level (Nagadevara, 1975), at the regional level (Osteen,
1978) and at the national level (Wade, 1977) have used linear
programming as their quantitative method of analysis. Examples of
the economic studies which have applied quadratic programming are
Ott, 1981, and Meister, 1978.
The Lp and QP techniques can be considered as two alternative
ways of delieating a problem where limited resources are to be
allocated among the competing activities in an optimal manner.
However, as far as the economic theory is concerned there is a major
conceptual difference between the two models. In an LP model, demand
for all outputs is assumed to be perfectly elastic. However, the
QP technique relaxes this simplistic assumption by allowing any
output demand function of a linear form to be incorporated
43
4 4
into the model. Therefore, when commodity demand functions or the
price elasticities of demand are available, formulation of a QP
model would be more appropriate than an LP model in the sense that
the former allows output prices to be endogeneously determined by
the model.
To utilize the conceptual strength of a price-endogeneous model,
the specific quantitative method employed in the present study is a
QP model. It adapts the main structure and assumptions of a seven-
region, price-endogenous model of Ohio's agricultural economy
developed by Raslt et_ al., 1983. However, the present model
substantially expands the activity matrix and restrictions set of the
ODOE model by adding over 200 soil groups and incorporating nearly
250 soil loss constraints. The following describes main
features of the model, and discusses the procedures used for
classification of Ohio soils and developing soil loss restrictions.
The Model
4.1. Objective Function. The objective function comprises maximiz
ation of economic surplus or net social welfare pertaining to Ohio's
nine principle agricultural commodities,beef, pork, poultry meat,
eggs, milk, and exports of corn, soybeans, wheat, and soybean meal.
Conceptually, economic surplus gained by society from production and
consumption of a commodity, x, at an equilibrium level of output and
the corresponding market price, is the area under (ordinary) demand
4 5
curve for x less the cost of producing that level of output,
ally, economic surplus is shown by the shaded area in Figure 4.1.1.
Assuming linear demand functions, mathematical form of the
objective function is the following.
Z = a'x + h x ' B x ~ £ ’n (1)
Where,
Z = monetary value of economic surplus,
a = 9~X1 vector of intercepts in the inverted demand functions:
p = a + B x , (2)
x = 9x1 vector of commodity production levels,
B E 9x9 matrix of farm-level own- and cross price effects,
c 5 vector of employment levels of non-restricted inputs,including transportation services
Parameters of the demand functions (equation 2) have been
derived from the national demand coefficients estimated by Heien,
1982, and Ray and Richardson, 1978. The procedure has been performed
using the concept of proportional demand. That is, it has been
assumed that Ohio production of the nine commodities comprise a
constant proportion of national production levels of those goods.
Generally speaking, this is a plausibel assumption since the market
forces that cause changes in production in Ohio are also prevailing
in other regions of the nation. The set of derived parameters
for the nine commodities are shown in Table la in Anpendix A.
4 6Figure 4.1.1
Illustration of Economic Surplus
Price
Supply
Demand
Q*0 Quantity
(AP*E = Consumers' Surplus [BP*E = Producers' Surplus
ABE = Economic Surplus OBEQ* = Cost of Production
4.2 Activity Matrix. The model's activity matrix defines the
relationship between inputs (i.e., capital,labor,energy,and land) and
agricultural outputs. In building this matrix it was assumed that
(Ohio) agriculture is a constant cost industry upto the point where a
given type of land-resource is available. This assumption means that
for a given type of land, input-output ratio and marginal cost at any
level of output remains the same. Since the model's land-resonrce
constraints reflect the differences in productivity levels, the
assumption of constant returns to scale has not caused a significant
distortion in the study results.
4-7Cropping a nd Livestock Systems. Cropping activities are
comprised of the State's major cropping options, namely, corn,
corn silage, soybeans, wheat, oats, alfalfa, grass hay, pasture-on-
cropland, and wheat/soybeans double cropping. Five different yield
levels have been specified for each of these cropping options. They
pertain to the five land productivity classes which were identified
on the basis of data complied by Van Doren and Triplett, 1980, and
U.S. Soil Conservation Service, 1978. (See Section 4.4 for details.)
As a result, five different activities have been specied for eacb
crop on each soil group.
The model's livestock system includes the following activities:
dairy (or milk), beef, cow-calf, sheep, swine, layers (or eggs),
broilers (or chicken), and turkey. The relationship between the
model's livestock and cropping systems has been defined based on the
animal feed rations. Feed rations represent combinations of protein
and energy required to achieve a certain production level of a given
type of livestock. Corn and soybean meal are the two basic sources of
energy and protein, respectively. Wheat, oats, and pasture are the
other feeding activities in the model. A detailed description of
the activities pertaining to processing of corn, soybeans, and wheat;
transportation of inputs and outputs; and byproducts of ethanol
as livestock feed is found in Rask et_ al., 1983.
4.3 Restrictions. The model features the following types of
restrictions., 1) In order to represent the State's agricultural
production activities more acurately, a certain acreage of each
48
region's cropland has been allocated to production of Ohio's minor
crops such as rye and barley. The right-hand-sides of these
constraints have been specified with reference to acreages of those
crops during the recent years-
2) Three types of grain delivery restraints have been specified
to satisfy: a) the 40 million bushel c o m demand from the Dayton
c o m sweetner plant, b) the 24 million bushel corn shipment to the
ethanol plant in Southpoint, Ohio, and c) certain domestic food
demand (i,e., milled wheat, corn , and oats) and out-of-state feed
demand (i.e., corn, soybean meal, and oats).
3) Land resource constraints which specify the State's total
stock of cropland and the total cropland acreage within each of the
seven regions,,
4) Land characteristic constraints which specify total acreage
of a each soil group within each region. The original version of
the model (Rask et al., 1983) contained only five constraints of
this type for each region. They were identified solely based on the
five land productivity classes that were mentioned before. However,
the present model includes 30-47 land characteristic constraints for
each region and a total of 248 for the State as a whole. The number
of these restrictions are equal to the number of regional soil
groups which will be discussed in Section 4.4 in this chapter.
Land characteristic constraints, in addition to the five productivity
levels, reflect the soil differences in terms of slope, erosion
class, response to conservation tillage, and T-value. Two sets of
49
data were employed to identify the right-hand-sides of the land
resource and land characteristic constraints: i) estimates from
the Bureaue of Census,1980; and ii) the SCS Conservation Needs
Inventory, 1967. The latter is a county-reliable, soil-specific
data.
5) Based on maximum sustainable soil loss limits (T-values)
an upperlimt has been placed on total amount of annual erosion corres
ponding to each soil group in each region. T-values, as defined by
agronomists, represent maximum permissible topsoil loss per acre per
year that will allow a high level of crop productivity to be sustained
economically and indefinitely(USDA, 1978).
Mathematically, the soil loss constraint for a given soil group in a
region in the model has been formulated as follows:
_l'x - T * ACR -AO
Where, 1_ represents vector of the soil loss coefficients which
are the topsoil losses per acre per year pertaining to each of the
model's cropping activities. Soil loss coefficients have been
estimated using the Universal Soil loss Equation (USLE) which will
be described in Section 4.5 in this chapter.
x represents vector of acreages of the cropping activities
optimal amounts of which are determined by the model.
T represents the soil group's maximum permissible erosion
per acre per year.
ACR represents the soil group's total cropland acreage in
50
the region.
4.4 Soil Groups in the Model As discussed in the preceeding
chapter, there are more than 500 soil types in Ohio. These soils
have been distinguished from each other according to differences
in parent material, natural drainage, surface texture, and natural
productivity. For the modelling purpose, in the present research,
many of the different soil types withir each region were grouped
together based on their similarities in slope, erosion class,
productivity level, response to conservation tillage, and T-value.
The soil grouping procedure has resulted in 77 different soil
categories in the State. However, since many of these soil groups
are prevalently found across the seven regions. the total number of
soil categories represented by the model is 248. The respective
number of the soil groups corresponding to each of the seven regions
is 30, 36, 47, 33 ,35 ,33., and 34. Table 4.4.1. illustrates
the identified soil groups including the names of the major soil
types within each soil group.
Specifically, the soil grouping process has included four
slopes, three erosion classes,five productivity levels, four indices
of suitability of conservation tillage, and four different T-values,
these factors are described blow.
The four different slopes which represent almost 100% of the
State's cropland area are 0 < 2% , 2^B<^6%, 6 12%, and
12V< D < 18% . Table 4.4.2 shows the distribution of of each region's
Table 4.4.1 5 1
Classification of Ohio Soils by Slope, Erodibility, T-value, Response to Reduced Tillage, and Productivity
Soil Soil Principle _____________ Area by RegionNo. Code Soils 1 2 3 4 5 6 7 St at<
1 11151 Da rroch 0 5(000
1Ac res)
0 0 0 5 112 11451 Hoytville 862 59 10 0 0 0 0 9313 11351 Brookston 0 594 0 0 55 71 109 8294 11141 Ross 0 0 0 0 5 0 0 55 1 1341 Pewamo 269 389 17 39 0 90 0 8046 12451 Wetzel 6 0 0 0 0 0 0 67 11152 Chagrin, Crane 0 31 13 0 0 16 39 998 11452 Latty, Toledo 315 59 10 0 0 0 29 4139 11352 Bono, Marengo 0 90 38 39 26 91 0 28410 11142 Haney, Sketh 14 0 0 21 16 0 0 5111 11132 Unidentified 0 4 0 0 0 0 0 412 12452 Montgomery 0 25 0 0 0 0 25 5013 12352 Algiers, Sloan 14 74 15 20 36 37 39 23514 12142 Lorain, Lippincott 0 56 15 0 0 19 31 12115 12232 Crosby 0 251 25 0 11 53 36 37616 13342 Avonburg 0 0 0 0 0 0 92 9217 132 32 Blount, Del.Ray 191 242 15 8 12 0 0 46818 21142 Wooster, Alleghney 17 0 75 19 0 0 0 1 1 119 22152 Celina, Miamian 0 4 70 42 0 0 136 100 74820 22142 Canefield, Tuscola 0 0 186 43 30 53 87 39921 22232 Crosby 0 125 33 0 0 0 104 26222 23232 Blount 159 434 23 11 3 23 24 67723 32142 Cardington 0 2 7 0 0 0 0 924 11153 Ottokoe, Sloan 0 0 19 0 10 0 0 2925 11453 Miner 78 0 21 0 0 0 4 10 326 11353 Me tea, Bogart 165 0 12 0 0 0 0 17727 11143 Ottokee, Haskins 24 0 33 12 0 0 o 0928 11133 Rimer, Willette 25 0 0 0 0 0 o
\J j
2529 12353 Milton, Fitchville 0 0 41 15 14 38 o 10830 12143 Sloan, Haskins 37 0 0 0 4 33 12 8631 13233 Nappanee, Fulton 125 32 174 6 6 107 0 45 132 13333 Fulton, Nappanee 87 0 0 0 0 0 0 8733 21143 Alexandria, Haney 31 0 13 18 0 0 18 8034 21133 Clymer, Galen 0 0 31 0 6 0 0 3735 22143 Zanesville 0 0 0 0 19 69 4 9 736 22 133 Fitchville 0 0 0 32 0 0 57 4
3 7 2 7537 23233 Nappanne, Blount 14 0 108 45 40 57 1138 31 133 Wooster, I.oudonville 0 0 102 32 6 22 15 1 7739 32143 Alexandria, Celina 0 91 14 22 14 50 22 2 1 3 6 340 32133. Keene, Ockley 0 0 0 44 0 0 19
(continued)
Table 4.1.1 (continued from page 51)
5 2
No Soil Principle _____________Area by ReRlon11U 1 Code Soils 1 2 3 4 5 6 7 State
(000 Acres)
42 4 1 133 Wooster 0 0 13 12 0 14 10 494 3 1 1 154 Oakville, Plainfield 0 0 3 0 0 2 0 544 1 1 154 U n i de n t. 0 0 7 0 0 0 0 745 1 1 244 fed row 14 0 0 0 0 0 0 1446 l 1 134 Spinks 0 0 4 0 0 8 0 1247 12 354 Orrville 0 3 87 6 20 0 0 1 1648 12144 Fox, Condit 0 34 0 0 14 0 0 4849 1 33 34 Remsen, Candice 0 0 29 7 0 0 0 3650 21154 Unident. 38 0 0 0 0 0 0 3851 21 144 Seward, Tedrow 16 0 12 0 0 0 0 2852 22134 Fox, Milton 0 39 0 0 4 7 12 6253 2 32 34 Unident. 147 209 73 0 0 0 0 42954 31134 Unident. 2 0 20 68 8 1 0 9955 32144 Unident. 0 22 0 0 0 0 0 2256 32134 Kendallville 0 26 25 79 0 0 7 1 3 757 33124 florley 0 30 0 11 8 10 14 7 358 33324 Un ident. 0 4 0 32 0 0 0 3659 41134 Muskingum 0 0 28 1 11 39 10 0 18860 42144 Unident. 0 0 6 0 0 0 0 661 42134 Unident. 0 10 0 4 0 0 3 1 762 43134 Morley 0 0 7 0 12 0 0 1963 11 355 Unident. 8 0 0 0 0 0 0 864 12255 Unident. 0 34 0 0 0 7 2 4 365 12145 Mentor 0 0 8 0 0 0 0 866 1 3335 Rose 1ms 12 3 0 0 3 0 0 1867 21155 Oakville 11 0 6 0 0 0 0 1 768 22135 Ritchy, Fox 2 14 0 0 0 0 7 2 369 23135 Unident. 0 0 0 0 4 32 0 3670 31135 Oakville 3 0 4 7 26 10 0 5071 32135 Cardington 0 10 0 0 26 27 17 8072 33125 Horne 0 0 8 4 14 6 0 3273 33325 St. Clair 10 9 0 0 0 0 0 1974 41 135 Uniden t. 0 0 4 31 32 5 2 7475 42145 Unident. 0 16 0 0 4 16 1 7 5 376 42 135 Uni dent. 0 0 0 35 7 0 1 1 5 377 4 3 1 35 Morley 7 10 6 22 7 4 1 4 70
(continued)
53
Classification of Ohio Soils by Slope, Erodibi11ty, T-value, Response to Reduced Tillage, and Productivity
Guide for 1 nter;>retlng Soil Codes
Co 1 umn D e s l g n a t ion Explanat ion
1 (Slope) 1 ..... Slope of 0- 2%2 ...... 3- 6%3 ..... 7-11%4 ..... ' 12-18%
2 (Erosion 1....... Slight erosionClass) 2....... Mode r a t e e r osion
3 ..... Severe erosion
3 (Soil Magmnt. 1........ Very well drained, resulting hig h e r yieldsGroup) wit h conservation tillage.
2 ..... Well to m o derately well drained, no changein yield with conservation tillage.
3.. ..... Frequently flooded, unsuitable forc o nservation tillage.
4 ..... Poorly drained, resulting lower yieldswith conservation tillage.
4( 1-value) 5 Tolerable topsoil loss of i tons per acre per year4 4 t ons3 3 tons2 2 tons1 1 ton
5 (Productivity) 1 Havi n g corn-equivalent yield ol 130 bu per arce2 ..... 115 bu3 100 bu4 ! 85 bu5 70 bu
Table 4.4.2
Ohio A g r icultural Crop l a n d by Region and H o p e
Ohio Agricultural Model 1981
(000)Acres
1 (C C C : Acres
(000'Acres
(0 0 0 )Acresi Acres 1 Acres i: Acres
216673 36 ' 38 6 , 4 2 8
1, 338 671 181 130 398 413 39 3 , 5 8 9
189 335 139242 23! 102 195 18 1 , 2 3 7 •
36 255 118 19 Of 600
1,661 100'15100 3,642 IOC 30 5 I 1,011100 623 100 10CTOTAL: 987 100
a: P e rcent of crop l a n d in the region b: P e r c e n t of the state's total cropland
Canplied based on the 1967 en-SCS Data.Cropland acres have been adjusted to approximate the present situation.
tn
as well as the State's cropland among the four slopes.
The three erosion classes iu ve been identified based on the
erodibility factor (K-value) in the USLE. From direct soil loss
measurements on selected soils, soil scientists have determined the
relative erodibility for most soil types in tons per acre per year,
per unit of erosion potential (5). The soil erodibility or K-values
for Ohio soils range from 0.15 for sandy soils (e.g., Spinks) to 0.49
for some highly erosive medium-textured soils such as Nappanee. After
consultation with agronomists, the present study divided the different
K-values of Ohio soils into three categories (Eckert and Zobeck,1983).
These categories are K-values of .15-.32, .37, and .40-.49, respect
ively. According to this classification, the category containing
K-values of .15-.32 represents a situation of slight erosion, while
the two latter categories indicate situations of moderate and severe
erosion, respectively. Table 4.4.3 illustrates cropland acreages of
the three erosion classes for each of the seven regions.
The productivity categories used in the soil grouping
process represent five different yield levels for each crop in the
model. They have been adapted from the original version of the ODOE
model (57) , in which the following procedure was used to arrive at
these crop yield levels. First, utilizing two comprehensive data
sets (USDA, 1967; and Ohio State University, 1981) a total of 22
different productivity levels for each region were identified.
Then, those productivity categories which had similar corn yields or
very small cropland acreage were combined together. (Corn yield was
Table A.4.3
Ohio Agricultural Cropland by Region and Erosion Class
Ohio Agricultural Model-1984\ - - \r£gio R E G I 0 N S S T A T E
1 2 I— 3 ...... '4 -----5 ■■ - 6 7\__\ (000) | (000) | 1 (000) 1 (000) (000) (000) (000) (COO)\ Acres a 1 b Acres a b ! Acres a • b Acres a b Acres a b Acres a b Acres a b Acres b
1 1,996 70 17 1,278 35 11
1
545'
33 : 4 447 45 4 253 41 2 258 25 2 242 23 2 5,019 42
:: 62 2 0.5 1,370 38 i: 576 35 ' 5 391 40 3 221 35 2 544 54 4 612 58 5 3,776 ■5 -»
::i 814 28 7
j
994 27 8 540 32 ; 4 149 15 1 149 24 1 209 2] 2 204 19 2 3,059 26
Octal: 2,872i
100 24! i I 1
3,642 ,100 30: |
1,6611
100j 13 987 100 8 623 100 5 1,011 10C 8 1,058 100 9 11,854 10
a: Percent of cropland in the region b: Percent of cropland in the state
Canplied based on the 1967 QJI-SCS Data.
Cropland acres have been adjusted to approxinete the present sitiation.
LnO'
57
used as the primary basis of combining productivity categories
because it is highly important in Ohio's agriculture.) As a result,
five different yields for each crop were specified. These yield
levels and their pertinent regional cropland acreages are shown in
Table 4.4.4,.
The four indices of suitability of conservation tillage incorp
orated in the model, have been determined based on the "No-tillage
Soil Classification Identification" prepared by Van Doren and
Triplett (1980). Van Doren and Triplett(V&T) divided Ohio soils into
five categories with respect to their response to no-tillage. Their
categories 1,2, and 4 include those soils which are suitable for
no-tillage, but may need adequate drainage or sufficient residue
cover. The expected yields pertaining to these categories are
greater than normal (i.e., with conventional tillage), normal, and
less than norma, respectively. On the other hand, soil categories
3 and 5 are unsuitable for no-tillage in the sense that adoption of
no-till on these soils results in reduced stands and/or depressed
yields. Accordingly, the four indices of conservation tillage
suitability used in the present model represents the following
situations„
1) V&T *s soil category one: based on consultation with agro
nomist (Eckert, 1983) it is assumed that adoption of chisel plowing
and no-tillage on these soils results in 5 and 10 percent higher
yields than those under conventional tillage, respectively;
2) V&T's soil category two: for these soils no changes in yield
Table 4.4.4
O h i o A g r i c u l t u r a l Cropland by Region, Produc t i v i t y Category, andCrop Yield Levels
Ohio Agricultural Model - 1981
ProductivityCategory
Crop Yield Levels/Acre bushels tons
Region Region 1 2
Region Region 3 4
Region Pecion Region 5 6 7 S"ATE
S0YBNS.
( 000) ? ( 000 ) ; %
Of 'Oft o e s rcl*i Acres rcl
(000)
tores
-t“
of*-rcl
(000)
Acres
(000)
Acres
i -lofrcl
(000) % I (000)of • of
Acres , trj Acrestrcl1 rci.
(000)
ACHES
, ; 1 1-i
!
140 ,14! 122 12i1
394 . 39 : 680 64
of
130 41 50 75 5.0
115 36 45 70 4.5
100 31 40 65 4.0
85 26 35 60 3.5
70 21 30 55 3.0
1,205 42 1,085 ( 30
753 26 1,932 ' 53
637 j 22 : 128 , 3
229
48
390 j 11
107 3
31
547
691
348
44
2 ' 41
33
42
173 18
299 30
362 37
112 jll
63
145
166
116
133
27 I 342 : 34 ' 143 13
40
95
28 | 3
85
2,687
4,624
2,406
1,513
624
1 23 II 39 ii 20 I; 13
5
TOTAL j2,872 100 3,642) 100 1,661 100 987 100 623 100)1,011 j100 1,058 100 11,854 100
* Percent of Cropland in Region.** Percent of Total Cropland in the State.
Canplied 3ased on the Information frcm "A Model of Ohio's Aaricultural E c r w r w " ,CD30 Model ( 57 ).
5 9
levels is assumed;
3) V&T's categories three and five: these soils are assumed ro
be cultivated by conventional tillage methods only; and
4) V&T's category four: it is assumed that with chisel plowing
or no-tillage these soils result in 5 percent lower yields than those
under conventional tillage„
The four T-values used in the model represent annual
soil losses of 5,4,3, and 2 tons per acre. They have been developed
by soil scientists based on research data, experience, and knowledge
of soil properties such as soil depth, root depth, permeability, and
prior erosion. In Ohio (and most part of the U.S.) T-values range
from 1 to 5 tons per acre per year. However, the Ohio soils with
T-value of 1 ton comprise even less than one percent of the State's
total cropland. To avoid an unnecessary expansion in the model
size, those soil types having T-value of 1 were combined with soils
which have T-value of 2 or 3 but have similar slope, erosion class,
productivity level, and conservation tillage suitability index.
In summary, the specified soil groups within a region differ
from one another at least with respect to one factor. For example,
soil groups 6 and 7 have the same slope, erosion class, index of
conservation tillage suitability, and T-value, but they have
different productivity levels. Example of an extreme case is com
parison of soil groups 6 and 41 which differ from one another with
respect to all the described factors included in the soil grouping
process (Table 4.4.1).
60
4.5._____ The Universal Soil Loss Equation (USLE) The USLE is an
erosion model designed to predict the longtime average soil losses in
runoff from specific field areas in specific cropping and management
systems. With appropriate selection of it s factor values, the USLE
can compute the average annual soil loss per acre for a multicrop
system, or for a particular crop year in a rotation (USDA, 1978).
Mathematically, the IJST.F, is written as follows:
A = R * K * LS * C * P.
Where, A is the computed soil loss in tons per acre per year;
R, the rainfall and runoff factor, is the number of rainfall erosion index units, plus a factor for runoff from snowmelt or applied water, where such runoff is significant; the R factors for Ohio range from 175 at Cincinnati to about 110 in Toledo;
K, the soil erodibility factor, is the soil loss rate per erosion index unit for a specified soil as measured on a unit plot, which is defined as a 72.6-ft length of a uniform 9-percent slope continuosly in a clean-tilled fallow.
LS, the topographic factor, is the expected ratio of soil loss per unit area from a field slope to that from a 72.6-ft length of uniform 9-percent slope under otherwise identical conditions; Mathematically: „LS (X/72.6)IP a (65.41 Sin d +4.56 Sind- + .065); where, ^ *= slope length in feet, -Q - angle of slope,and m =.5 if slope ^>5 percent,=.4 on slopes of 3.5 to4.5 percent, etc;
C, the cover and management factor, is the ratio of soil loss from an area with specified cover and management to thatfrom an identical area in tilled continuous fallow.
61P, the support practice factor, is the ratio of soil loss
with a support practice like contouring, strip cropping, or terracing to that with straight-row farming up and down slope.
4.6 Tillage Systems in the Model
To analyze the statewide economic and land-use impacts of
soil conserving tillage systems, in addition to conventional tillage
(i.e., moldboard plowing) the model features two other tillage
methods. These are chisel plowing or reduced tillage, and no-tillage.
Table 4.6.1 indicates the typical operations and equipment which are
applied under each tillage system.
In general, there are three major differences between conven
tional and soil conserving tillage systems.
1) Conservation tillage systems reduce excessive cropland
erosion by 30 to 75 percent. This is related, primarily, to the
fact that reduced tillage and no-tillage provide a good amount of
residue cover on bare cropland during fall and spring, hence,
decreasing soil's erosion susceptibility. These factors have been
incorporated into the model in calculation of C-factor for the USLE.
2) Conservation tillage systems require less machinary, and
therefore, less repairs and fuel. However, they require more
chemicals for weed control such as herbicides. Changes in per acre
production costs of Ohio's major crops under chisel plowing and
no-till which have been estimated by the present study, are shown
in Table 5.2.2 in Chpater V.
3) Conservation tillage systems may result in an increase or
Table 4.6.1
Description of the Alternative Tillage Systems
Ohio Agricultural Model - 1984
kTillage System Operations and Equipment Used
Moldboard chisel Disking Field Planter Fertilizer Herbecide Plow Plow Cultivator Spreader Sprayer
Conventional yes no yes no yes yes yes
Reduced no yes no yes yes yes yes
No-Till no no no no yes yes yes
* Source: Eckert (1983), Duvick (1983), and Lines (1983).
ho
63
a decrease in crop yields. This related to soil's natural drainage
capacity. In general, adoption of chisel plowing and no-tillage on
well-drained soils results in higher per acre yields, while the
opposite occurs on poorly drained soils. The classification of Ohio
soils with respect to their yield responses to chisel plowing and
no-till were described in Section 4.4 in this chapter.
Methodological Issues. In general, there are two types of method
ological problems associated with solving a non-linear mathematical
programming model. The first issue is that, maximization of the
non-linear objective function might not lead to an optimal solution.
However, Kuhn and Tucker (1959) have shown that the optimal solution
to a mathematical programming model can be found if the objective
function and the restrictions both form a convex set. For the model
used in the present study these two conditions are satidfied. Since,
all production activities are linear combinations of inputs, and soil
loss constraints are linear functions of cropping activities, there
fore, the model's restrictions set is convex. The objective function
also forms a convex set since the matrix of price-effects described
in Section 4.1, i.e., matrix B in equations (1) and (2), is negative
definite. Thus an optimal solution to the present model can be found.
The second issue relates to somewhat inefficiency of the
algorithms available for solving non-linear programs. Fortunately,
this has not been a problem for the present model. It has been
successfully run with the MINOS programming package. MINOS uses
reduced gradient algorithm to find the optimal solution (Murtagh and
CHAPTER V
RESULTS
This chapter is comprised of five sections. The first section
describes the major model scenarios of the analysis. The second
section discusses the cropland use patterns under the alternative
tillage methods and the land use impacts from limiting annual
erosion to soil loss tolerance levels, or T-values. The changes in
erosion rates resulting from soil conserving tillage practices and
soil loss restrictions are presented in the third section. The
fourth part discusses the impacts on agricultural production, farm
prices, crop exports, farmers* net returns,and consumers' surplus
from tillage system substitutions and T-value restrictions on soil
loss. The results of sensitivity analysis pertaining to some
potential expansions in grain exports and industrial demand for
corn are presented in the fifth section.
5.1. Major Model Scenarios. To achieve the study objectives, model
simulations reflecting three different tillage systems, with and
without restrictions on soil loss were analyzed. The six principal
model scenarios are listed in Table 5.1.1.
The Base Run (Scenario I) simulates Ohio's agricultural
economy under current demand levels, assuming that conventional
tillage (fall molboard plow) is practiced on all soil groups. Scen
arios II and III replace this assumption by using reduced tillage
6 5
Table 5.1.1
Major Model Scenarios
66
Model Scenario Tillage System Soil Loss Restriction
I (Base Run) Conventional None
II Chisel Plow None
III No-Tillage None
IV Conventional at T-value
V Chisel Plow at T-value
VI No-Tillage at T-value
(fall chisel plow) and no-tillage on all economically suitable soils,
respectively. Scenarios IV,V, and VI add the soil loss restrictions
to the model under each of the three tillage systems. On soils where
farm net income is significantly reduced with chisel plowing or
no-tillage, conventional tillage is used.
5.2 Cropland Utilization Under Alternative Tillage Methods, withand without Restrictions on soil loss
Aside from their long-run soil conservation and environmental
benefits, the economic impacts of soil conserving tillage systems on
farmers' cropland use decisions consist of two major factors:
1) variation in crop yields;
2) changes in per acre costs of certain inputs.
Crop yield differences by tillage systems are related to soil drainage
67
capacity. As described in the previous chapter, adoption of chisel
plowing and no-tillage on well-drained soils will result in higher
yields per acre, while the opposite occurs on poorly drained soils.
The use of the above soil conserving tillage methods on farmland
with severe drainage problems is considered to be economically
unsuitable because of resulting in depressed yields. In terms of
their suitability and yield response to soil conserving tillage
practices, Ohio soils can be placed into four major soil management
groups. These soil management groups which have been incorporated
in the present study were described in Chapter IV. Table 5.2.1
shows the changes in crop yield levels pertaining to the four
soil management groups under alternative tillage systems.
Tab 1e 5.2.1
Changes in Ohio Crop Yield Levels by Soil Management Group and TillageTillage System
Management Group Conventional Conservation No-Tillage
1 100 105 110
2 100 100 100
3 100 NA NA
4 100 95 95
Source: Eckert (1983).
68
Substitution of tillage system also affects production costs,
depending on cropping patterns and the type and quantity of inputs
required. However, the changes in cost levels for specific components
of the tillage systems such as machinary or chemicals is often greater
than the difference in overall costs. For example, compared to con
ventional tillage, production of corn under a no-tillage system
demonstrates substantial savings in costs of machinary, repairs, fuel,
and labor, while, it increases substantially the application levels and
costs of chemicals. Specific changes in per acre production costs of
Ohio's major crops, resulting from substitution of conservation tillage
systems are presented in Table 5.2.2.
In Ohio, because of regional differences in soil types and
agricultural activities, statewide adoption of soil conserving tillage
methods, especially, on the basis of changes in crop yields, would
have a major impact on the State's cropland use patterns. Simulated
cropland use patterns in Ohio under the three tillage systems, with
and without T-value restriction of soil loss (Scenarios I-VI) are
presented in Table 5.2.3.
In the absence of soil loss restraints, under each tillage
method (Scenarios I-III), the State's currently available cropland
(appriximately, 11,250,000 acres) is completely utilized. However,
substitution of soil conserving tillage systems for conventional
tillage on all adaptable farmland would result in a transfer of up to
200,000 acres from corn, small grains, and forages to soybeans. This.
Table 5.2.2
Changes in Per Acre Production
1'nder Conservation 1
i Costs
ii iiayo
o : Oh i o '
Systems
s Maji r Crops
corncorn
andsilage soybeans wheat oats a 11 n 1 f a grass
hay
Ti l l a g e : A B A B A B A B A B A B
Inputs ( S per acre)
Chemicals +3.6 + 12.0 +2.0 +12.7 - +6.0 - +6.0 NA + 8 . 5 NA + 8 . 5
Repairs -2.4 - 5.3 -2.2 - 5.8 -2.6 -5.0 -2.9 -5.3 NA - 3.6 NA - 3.3
Fuel -0.7 - 2.7 -0.8 - 2.8 -0.8 -1.6 -0.8 -1.6 NA - 1 . 3 NA - 1 . 6
Labor -1.4 - 4.3 -0.5 - 4.5 -1.4 -3.6 -1.4 -4.0 NA -14.0 NA -10.8
Net Difference -0.9 - 0.3 -1.5 - 0.4 -4.8 -4.2 -5.1 -4.9 NA -10.4 NA - 7.2
A :chisel plow vs. conventional tillage Source: Complied based on '‘Ohio Farm Machinary EconomicB :no-tillage vs. conventional tillage Cost Estimates for 1983" ( 63 ), and "Ohio cropX a : data not available Enterprise Budgets for 1984" ( 64 ).
CTnvo
70
Table 5.2,3
Ohio's Simulated Cropland Use Patterns, by Region and Tillage Methods
-tch and ’-'lthout T-Value cestrlctions on Soil Loss
ALL ROW CROPS SMALL CRAINS rORAOE & PASTURE TOTAL rRrP’ANU
TILLAGE SYSTEMS
(UOO Acres)
a. Nj Restrictions on Soil Loss
196 16-1,066 716
267,886 2,786 2 , 790 |L6)730
120350585502 502
Lnglaclaced166>632-9
157133 119 158212
957 9 b ' 9577656777 Southwest 98
1,7597,995 8,078 8,05'State
b. Soil Loss Restricted to T-Values
11 1,186 840 694 1,137 1,441 1,452 2,323 2,281 2,145 |310 357 409 78 73 157 2,711 2,711 2,711
JCornbelt871 827 962 1,473 1,927 1,813 2,344 2,754 2,776 434 457 512 575 302 226 3,353 3,513 3,513
3 Dairy 713 590 538 120 109 114 833 695 632 295 53“ 508 341 239 315 1,469 1,475 1,475
245 370 461 0 0 0 245 370 461 140 106 35 234 395 384 619 871 880'
57Unglaciated
251 253 249 4 c C 234 253 249 94 129 142 8, 174 166 A Z 2 356 357
6 Transition 530 B92 673 121 6 189 651 698 862 307 92 133 195 163 158 1,153 1,153 1,153
7 Suuthwest 217 545 632 245 130 159 462 675 791 310 214 84 113 67 81 885 956 95t
State 4,012 4,317 4,209 3,100 3,607 3,727 7,112 7,924 7,936 1.89C 1,892 1,823 1,620 1,413 1,407 10,622 11,235 11,245
A: Conventional Tillage B: Conservation Tillage C: No-Tillage
71
reallocation would occur as a result of higher net returns per acre
associate with growing soybeans under conservation tillage practices,
on specific soil groups . (See the succeeding section on regional
impacts.)
Under conventional tillage practices, implementation of the
soil conservation policy (Scenario IV vs. I) would force Ohio farmers
to remove nearly six percent ( approximately, 650,000 acres) of the
State's currently utilized cropland from production. This adjustment
would consist of a 900,000 acre (11 percent) reduction in row crops,
a nearly 200,000 acre (14 percent) increase in forages and pasture,
and a 50,000 acre (3 percent) expansion in small grains.
Adoption of chisel plowing or no-tillage on all suitable soils,
however, would largely eliminate the need for these changes, since the
two soil conserving tillage methods would potentially drop the average
annual erosion rate on Ohio farmland to a level very close or even
below the State's average T-value.(See Section 5.3 for details.) With
chisel plow and no-till, respective impacts of soil loss constraints
on the State's total row crop acreage would only be a 2 and 1 percent
reduction (vs. the 11 percent with conventional tillage). As a result,
the expansion in forages and pasture acreage would only be 4 percent
(compared to the 14 percent under conventional tillage).
Regional cropland use changes resulting from substitution of
soil conserving tillage system for conventional tillage and T-value
restriction of soil loss would be more substantial than the overall
72
impacts discussed above. A general background describing the main
causes as well as a detailed discussion of these regional changes are
presented below.
Historically, regional differences in Ohio cropland use
patLerns have emerged as a result of the diversity of the State's
soils, especially, with respect to natural productivity, drainage,
and topographyo The limestone-based and highly fertile soils of
northwestern and western Ohio have resulted in a heavy concentration
of row crop agriculture in these regions. Alternatively, a large
acreage of sand-stone based and less productive soils in northeastern
and eastern Ohio have been used for production of small grains,
forages, and pasture,,
First of all, in response to soil conserving tillage practices,
these existing land use patterns would be affected differently, due to
the observed variations in respective crop yields and production
costs. For example, a major substitution of soybeans for corn would
occur on the fine-textured, poorly drained soils of northwestern
Ohio because of relatively lower per acre costs of growing soybeans
on these soils. (For details, see the succeeding section on cropland
use changes in Region 1.) In contrast, on the medium-textured, well-
drained soils of northeastern Ohio, a significant expansion in row
crop agriculture would take place as a result of increased profit
ability of growing these crops using conservation tillage systems.
Secondly, imposition of soil loss restraints regardless of
tillage systems would change the historical cropland use patterns
73
in Ohio on the basis of regional differences in topography, erosion
susceptibility, and soil loss tolerance levels (T-values). In
general, the direction of regional cropland use changes resulting
from soil loss restraints would be a fairly significant expansion
of row crop agriculture on less erosive soils of northwestern and
northeastern Ohio in conjunction with restriction of corn and
soybeans production on more erosive soils, especially, in western,
southwestern, and eastern regions.
A. Land Use Changes in Northwestern Ohio (Region 1)
As described in Chapter III, most of northwest Ohio's cropland
is level and is comprised of highly fertile and poorly-drained clay
soils such as Hoytville, Pewamo, Paulding, and Toledo. As a result,
excessive surface water rather than erosion has been the dominant
agricultural hazard in this region. Historically, row crop agri
culture has occupied more tahn 80 percent of the region's cropland
under conventional tillage systems.
In this region, the main impacts of replacing moldboard plow
ing with conservation tillage systems would be the following.
1) A major susbstitution of soybeans for corn would take
place on almost 10 percent (250,000 acres) of the region's cropland.
The substitution would primarily occur on soil group 8 which is
comprised of the poorly drained soils, i.e„, Latty and Toledo. On
these soils, adoption of conservation tillage practices results in
five percent yields, and hence five percent less gross returns.
(See Table 5.2.1.) Production of soybeans on these soils, however,
74
would result in a smaller reduction in net returns than corn by2/almost $4.00 per acre — .
2) Nearly 8 percent (80,000 acres) would be transferred from
corn to wheat on the well-drained, moderately productive soils
such as Haskins and Rimer.
The major conclusions from imposing T-value soil loss
restrictions on northwestern Ohio cropland are the following.
1) There would be no impact on the region's total acreage of
utilized cropland resources. This is the State's only region in
which the average annual erosion per acre, under conventional tillage
practices, is less than the average T-value. (See section 5.3 for
details.) As a result, limiting soil loss to T-values would not
restrain utilization of northwest Ohio's cropland resources.
2) The region's row crop acreage would be expanded by nearly
6 percent in response to reduction of row crop acreage in the
State's more erosive regions (i,e., 2, 4, 6, and 7). With moldboard
or chisel plowing about 120,000 acres of well-drained soils of
average productivity (e.g., Bennington and Fulton) would be shifted
from wheat to com. In return, almost an equal amount of land of
less fertile soils such as (Seward and Tedrow) would be transferred
from oats and pasture to wheat production. The primary reason for
a major reduction in oats and pasture acreages in northwest Ohio
would be a substantial expansion in producing these crops in regions
2,6,and 7 because of imposing soil loss restraints.
7 5
B . Land-Use Changes in Western and Southwestern Ohio(Regions 2 and 7)
More than 90 percent of western Ohio cropland has slopes of
less than six percent and nearly two-third of the soils in this region
are well- to fairly well-drained. Region 2 has the State's largest
portion of cropland (31 percent), the largest of row crop acreage
(36 percent), and the most fertile soils such as Brookston, Pewamo,
Crosby, Celina, and Blount. In contrast southwestern Ohio
comprises one of the State's smallest cropland regions. (It ranks the
fifth among the seven regions in terms of cropland acreage) , In
addition to the major soils of western Ohio, this region includes
more erosive and less fertile soils such as Hagerstown, Russel,
and Rossmoyne.
In these regions, the most noticeable cropland use changes
stemming from conservation tillage practices would be: a moderate
substitution of small grains and pasture for row crops on the poorly-
drained soils such as Raub, Wetzel, and Montgomery.
In region 2, nearly three percent (100,000 acres) of total row crop
acreage would be transferred to wheat and pasture. Similarly, in region
7, about 8 percent (60,000 acres) of corn would be shifted to wheat
production. Substitution of wheat and pasture for row crops in
regions 2 and 7 would take place, primarily, because of two
reasons: (i) a major substitution of row crops for wheat on
the well-drained soils of regions 3,4, and 6; and (ii) a relatively
7 6larger reductions in per acre costs of wheat and pasture using
conservation tillage (Table 5.2.2).
Under conventional tillage systems, T-value limitations of
soil loss would cause the following changes in these regions'cropland
utilization.
(1) A relatively small portion of total cropland would be
removed from production.
In western Ohio, the area to be set aside from production would amount
to approximately five percent (160,000 acres) of total cropland. In
southwestern Ohio, this adjustment would be close to seven percent
(70,000 acres) of total cropland.
(2) A major reduction in row crop acreage and a 1arge
expansion in forages, pasture, and small grain acreages would occur
on more sloped soil groups, i.e., 19 and 21.
In region 2, soybeas acreage would be reduced by nearly 31 percent
(670,000 acres). Almost 20 percent (125,000 acres) of this area may
be shifted to corn, nearly 60 percent (400,000 acres) would be trans
ferred to forages and pasture, and the remaining 20 percent would be
left unutilized. In summary, imposition of soil loss restraints
would cause a 20 percent (550,000 acre) reduction in western Ohio's
total row crop acreage and more than a 250 percent increase in the
region's acreages of hay and pasture-on-cropland.
In Southwestern Ohio, the decline in row crop acreage would be
considerably sharper than in region 2, because of a proportionally
heavier concentration of these crops on more erosive soils such as
7 7
Xenia, Miamian, and Cincinnati. Specifically, region seven's
total row crop acreage would decrease by 45 percent or nearly
400,000 acres. While small grain agriculture is this region would
expand by almost 700 percent.
Under conservation tillage systems, T-value erosion control
limitations would place no restraint on utilization of total cropland
resources in western and southwestern Ohio. Nevertheless, some minor
changes in land-use composition of these regions similar to those under
conventional tillage systems would still prevail (Table 5.2.3).
C. Changes in Land-Use Patterns in Northeastern Ohio(Region 3)
Similar to northwestern Ohio, more than 80 percent of the
cropland in northeastern Ohio is level to moderately-sloped. However,
most of the region's soils are sandstone, well-drained, and less
productive . In terms of the total cropland acreage, after regions 2
and 1, region 3 ranks the third among the seven regions. Dairy
and livestock production comprise northeast -Ohio's main agricultural
activities. Historically, row crop agriculture has occupied only one-
third of this region's cropland. Forages, pasture, and small grains
have been grown on nearly two-third of the cropland.
A significant substitution of row crops (mainly soybeans)
for pasture and wheat would be the main land-use impact of con
servation tillage systems in northeastern Ohio. Specifical.lv, row-
crop acreage would be expanded by approximately 20 percent (100,000
7 8
acres). This expansion primarily would occur because of an increase
in corn and soybeans prices resulting from the aforementioned
decline in production of these crops in regions 1,2, and 7.
T-value restriction of soil loss not only would leave north
eastern Ohio's total cropland acreage unaffected, it would even cause a
major expansion of row crop agriculture in this region. That is as
erosion control limitations would restrain supply of row crops in the
State's erosive regions, higher corn and soybeans prices would lead to
an increase of more than 55 percent (300,000 acres) in production of
these crops in region 3. Specifically, nearly 45 percent (200,000
acres) of the highly fertile and less erosive land (including soil
series Bono, Marengo, Wooster, and Canfield) would be transferred from
wheat to corn production. Similarly, soybeans acreage would expand by
removing nearly 30 percent ( 90,000 acres) from pasture on the less
fertile soils Condit and Frenchtown.
Even under conservation tillage systems, relatively strong
impacts of soil loss constraints on regions 2, 4, and 7 would still
cause some substitution of row crops for pasture in northeastern Ohio.
With chisel plowing, the total expansion in this region's row crop
agriculture would be almost 10 percent (65,000 acres) and with no-till
it would be less than a 2 percent (10,000 acres).
D. Land Use Changes in Unglaciated Ohio (regions 4 & 5)
These regions (eastern and southeastern Ohio)are part of
Appalachian Highlands and are either predominantly or totally unglaci
7 9
ated. As a result, the topography in 40-60% of cropland ranges from
hilly to rough. They include the State's most erosive and less fertile
sandstone soils such as Musk ingum,Clymer,Zanesville, and Coolville.
Among the seven regions, eastern and southeastern Ohio comprise the
State's smallest portions of cropland as well as the smallest shares
of row-crop agriculture.
Similar to the northeast, adoption of conservation tillage
methods would encourage a major substitution of corn for forages and
pasture in eastern Ohio. The corn-to-pasture substitution would be
up to a 30 percent (150,000 acre) expansion in region 4's row crop
acreage.
Since eastern and southeastern Ohio have the largest proportions
fo rolling and hilly cropland, impacts of T-value limits on these
regions' cropland utilization would be the strongest among the
seven regions. Under conventional tillage, imposition of soil loss
constraints would cause the following land-use changes to take place.
(1) In eastern Ohio, approximately 30 percent (270000 acres)
of total cropland would be removed from production. As a result, the
region's row crop (corn) acreage would decline by nearly 50 percent.
Almost half of this area (formed of soil groups 20 and 37-40) would be
transferred to oats and the other half would be set aside. The rest of
cropland to removed from production would mostly consist of soil group
59 which includes the poorly fertile soils such as Muskingum with
slopes of 12-18 percent.
8 0
(2) In Southeast Ohio, about 22 percent (125,000 acres) of
total cropland would be removed from productions of small grains,
forages, and pasture. This adjustment would take place on the
region's marginal and highly erosive soil groups 35-41,59,62, and
70-77. Row crop acreage would not be restrained in this region.
Corn acreage would be expanded by nearly 5 percent (10,000 acres) on
the highly fertile and level soil Lindside (soil group 3). The minor
increase in this region's row crop acreage would occur as a result of
the sharp decline in row-crop agriculture on more erosive soils of
regions 2, 4, and 7.
Under conservation tillage systems, the impacts of soil loss
constraints on these regions' total cropland acreage would be
negligible. However, in region 4, a substantial decline in row-crop
agriculture and a large expansion in small grains production would
still take place (Table 5.2.3).
E. Cropland Use Changes in Central Ohio (Region 6)
This region is the so-called transitional area between the
highly fertile, limestone soils of western- and the predominantly
less productive, sandstone and shale soils of eastern Ohio. The
topography on more than 85 percent of central Ohio cropland is level
to moderately sloped and nearly 2/3 of the region's soils are well-
to fairly well drained. Historically, row crops have been grown on
almost 70%, small grains on about 20%, and forages and pasture on
81
nearly 10% of this region's cropland.
Statewide substitution of conservation tillage methods for
conventional tillage would result in a considerable substitution of
corn for soybeans and small grains in central Ohio.
With chisel plowing, the land displacement would consist of a 30 per
cent (200,000 acre) expansion in corn acreage, a complete ( 115,000
acre) removal of land from soybeans, and nearly 40 percent (80,000 acre)
reduction in small grains. With no-tillage, however, the land-use
changes would be somewhat moderate. That is^a 20 percent increase in
corn, 50 percent decrease in soybeans and a 44 percent reduction in
small grains. In both cases, the corn-for-soybeans substitution would
take place, primarily, because of the mjor soybeans-for-corn substitu
tion on the poorly-drained soils of region 1. Similarly, substitution
of corn for small grains in central Ohio would occur in conjunction
with the described wheat-for-corn substitution in region 7.
Statewide restriction of soil loss to T-values would not
restrain utilization of available cropland resources in central Ohio.
However, under conventional tillage, the region's total row crop
acreage would be reduced by nearly 17 percent (130,000 acres),
corn production would become more intensified on the region’s level
soil groups (5-15), while, it would be diminished or discontinued on
more erosive soil groups 19,20, and 31-37. Approximately, 3/4 of the
land to be removed from corn would be shifted to wheat and the balance
would be used for forages and pasture on the region's most erosive and
less productive soils groups 70-77. With chisel plowing, cropland use
8 2impacts of soil loss restrictions in central Ohio would be very
moderate. It would be a minor substitution of small grains for corn.
On the other hand, under no-tillage sytem, enforcement of T-value
limits on soil loss would cause a major soybeans-for-corn substitution
in region 6. That is, as soil loss constraints raise soybeans prices
by depressing its production in western Ohio, they would stimulate a
transfer of nearly 15 percent (135,000 acres) from corn to soybeans
on the moderatley erosive soils in central Ohio (Table 5.2.3).
5.3 Soil Erosion Impacts of Alternative Tillage Systems on Ohio Cropland with and without Limiting Annual Soil Loss to T-values
Based on the cropland use patterns described in the preceding
section, average annual erosion rates (soil losses per acre per year)
for the State as a whole, as well as the seven regions were computed.
Soil loss computations for each soil group, under each model
scenario , were performed through the Universal Soil Loss Equation
(USLE). A detailed discussion of the USLE and the procedure of
estimating its factors for Ohio soils was presented in Chapter IV.
Ohio's simulated annual erosion rates under each of the six model
scenarios are presented in Table 5.3.1. These results are described
below.
1) Under conventional tillage systems the erosion impacts
associated with the aforementioned cropland use patterns would be
the following.
With no restrictions imposed on soil loss, the average
83
annual erosion rate on Ohio cropland (per acre topsoil loss of
5.3 tons ) would exceed the State's average T-value (tolerable soil
loss of 3.7 tons per acre per year) by 44 percent. However,
Tab le 5.3.1
SIMULATED ANNUAL EROSION RATES BY TILLAGE SYSTEM AND SOIL LOSS LIMITS
Model Scenario : I 11 III IV V vi T-ValueAvg.i illage Sys tern : A B C A B C
Regions (tons of soil loss per acre per year)No Restriction1 on Soil loss limited
soil loss to T-values
^.CornbeIt 2.8 1.4 1.0 2.5 1.3 1.0 4.22) 5.6 3. 3 2.5 3.3 2.5 1.6 3.83 Dairy 3.8 3. 3 2.4 3.0 1.5 1.0 3.34)(Unglaciated 9.3 7.6 3.6 3.6 2.5 2.0 3.65) 3.5 3.0 1.7 3.6 1.8 1.0 3. 76 Transition 7.0 2.7 1.7 3.2 1.9 1.4 3.27 southwest 8.8 4.6 3. 1 3.9 2.6 1.7 3.8
State 5.3 3.2 2.2 3.2 2.0 1.3 3. 7
A: Conventional Tillage practiced on all croplandB : Conse rva t i 011 Tillage practiced on all suitable t■ roplandC: No 'Ullage practiced on all suiatble cropland
the excessive <cropland erosion in eastern, southwestern, and central
Ohio (regions 4,7, and 6) would be more drastic than the State as a
whole. In these regions, annual erosion rates would exceed the
respective T-values by 160%, 130%, and 120%. In terms of individual
soil groups, excessive erosion would be even more severe. In all of
8 4
the seven regions, a number of major soils would erode at annual rates
considerably higher than the regional average rates.
For example, in northwestern Ohio, under the described
cropping patterns, the average per acre soil loss would be 33 percent
less than the region's average T-value, while a major soil,
i.e„, Blount, would erode at a rate 225% higher than its corresponding
T-value. Similarly, in western Ohio, annual erosion on three
principle soils, i.e., Miamian, Celina, and Blount (comprising nearly
26% of the region's cropland), would be 250-350 percent greater than
the pertinent T-values. An example of a more rigorous case would be
in region 4, where, annual soil loss rate on soil group 56 (forming
almost 10% of the regions cropland) would exceed its corresponding
T-value by more than 600 percent.
2) Switching to conservation tillage (chisel plowing) on all
adaptable soils, would drop the average annual erosion rate on Ohio
cropland to a level 14 percent below the State's average T-value.
Nevertheless, the excessive erosion in eastern and southwestern Ohio
still would remain approximately 120 percent above the pertinent
T-values (Table 5.3.1). Also, in all regions,except in the northwest,
excessive soil loss on highly erosive soil groups such as groups 22
and 75 in regions 2 and 7, and group 38 in regions 3,4,6, and 7
still would prevail.
3) Adoption of no-tillage on all suitable soils would
reduce the annual erosion on Ohio cropland to a level nearly
8 5
40 percent below the State's average T-value. In this case,
on average, none of the seven regions would suffer from excessive
erosion (Table 5.3.1). However, excessive soil loss on a total of
ten soil groups having slopes of higher than 6 percent still would
persist.
5.4. Economic Impacts Associated with Tillage Systems Substitutionand T-value Restriction of Soil Loss.
As described in Section 5.2, statewide substitution of
conservation tillage practices for conventional tillage, and T-value
restriction of soil loss would each result in a number of major
changes in regional cropland use patterns in Ohio. This section
discusses the potential economic impacts associated with these land-
use changes in terms of the State's agricultural production, farm
prices, crop exports, net returns to farmers, and consumers' surplus.
A. Economic Impacts Associated with Change to Conservation Tillage Systems
At the State level, soil conserving tillage practices would
have a moderate impact on Ohio's agricultural economy. However,
regional economic changes stemming from these tillage systems would
be more noticeable (Tables 5.4.1 and 5.4.2).
Under chisel plowing, total production levels of corn, soy
beans, wheat and oats would increase at respective rates of 0.6, 1.4,
0.6, and 1.0 percent. With no-tillage, however, corn and soybeans
production would increase at a higher rate, i.e., 1.6 and 2.5 percent
Ta bl e 5 .4 . 1
Siauiacea Percent Changes in d u o Agricultural Production Resulting froo Tillage Svsteo Substitution and Soil Loss Restriction bv Region
A«* _ic ns 6 State
c. IL.jiC 5 • stec.s A 8 3 c A 8 *- A c A c A C A 3 A B
Row Cr. Ps-icrn - 56 - 2' •1 0 - * - • I S ♦ i: * 1- - ■: •33 •28 - .2 • - *12 *lu * 32 *28 -16 - 5 - - V, * . ♦ 1.6 - 3.cm Si! a<e - 13 - -i -* i - - ■; * • 20 - ib * b * 0 - 93 0 -i 0 -85 0 -85 - ;; - - 60 0 -2 -64*> ovbe m s * 15 - 1 -• * 1 - 1 - - 2 5 * •:?9 •266 ~ " o 0 -23 - 89 --7 *20 0 - 10 *1 iv *1.9 *2.5 -10
Ssa.l Crain■heat •J * 0 * J *13 * - i2 0 - j 0 - :c -2 i -a: - 3 3 -58 *200 *-00 +1 30 - .6 + .6 * 2Cat s “ L- " * * * - * - 2 ■ > 0 0 *360 3 0 ■ 4 *200 *20 *10 - 20 - 10 ’ *1 *1
' 2Alfa! : j * 50 * 52 „C - * A , 33 •1 •yC - 13 ♦ i n -2 3 -27 * 9 r -17 0 0 *25 - A0 20 . A-- -6 -o ♦30Crass nav - - 3r- — :' • 'j - N •2*2 - 1? - 3 - .A -1* ■> - 30 * 6 • 6 0 * 8 *1" *67 - 10 - 20 - . 0 ♦8 * '5Past re n LL -2ee> *:jc -9 3 31 •515 - 15 - 2b - 30 -32 - n: * 3 * 9 -60 • 5 * q *19 0 * n; 0 *> *10
Hi ik - 18 - 18 - * ♦13 * 13 - 13 * .6 - 3 - -- -. 5 * i - .8 • 1 -1? -19 - .6 * 1 - 9 - 17 - 17 - : ♦ .6 +1 - 1
LivestocASee t 0 * 4 - ; 0 * ♦ 22 0 0 - 13 0 * 3 * u 0 * 3 -15 0 • 4 -i: 0 + i. * 33 * .4 *4 * 6?or« 0 0 - fc 0 LI - 3 0 0 - 5 0 0 - 5 0 0 *16 0 0 -11 0 0 - 6 ♦ .4 ♦ .- * 5Ugs 0 0 -:o ♦ 5 - 16 - 5 0 0 - 20 0 0 - i: 0 0 -14 0 -28 0 - ei *7.3 -13CH;ck •n 0 0 o 0 0 - - o • 25 0 0 - 6 0 0 -33 0 - 2 - 2 0 0 _• *1 ♦4 - 3T -ruev 3 0 n 3 0 i 0 0 0 *10 0 0 0 0 0 0 0 0 0 - cl 0 3
A C.u,t*; r.ov vs. conventional tillage, no restriction on soil loss, j. -rill ui vs. conventional til..ice. no restriction or. -.c-il loss.
S.ii i.o* restricted co T-va»cej> unaer conventional ttllaae.
00ON
Table 5.4.2
Simulated Percent Changes in Ohio Agricultural Prices Resulting from Tillage System Substitution and Soil Loss Restriction by Region
Regions 1 + - * 5 6 7 State
Scenarios A B C A B C A B C A B C A B C A B C A B C A B C
Row CropsCorn _2 -6 + 19 _2 - 6 + 18 - 2 - 6 *19 _ i - 6 + 19 -2 - 6 +16 _ -i -6 + 19 -6 + 19 -2 - 6 -19Corn silage -I -b *-L j - 2 - 6 + 19 _ ^ - 6 + 19 -2 - 6 -19 _ T - 6 + 16 -2 - b + 19 _ T -6 -19 -2 - 6 + 19Soybeans -3 -8 *25 -3 - 8 +26 - 3 - 8 +22 -3 - 8 +26 -3 - S +26 -3 -8 +26 - 3 -3 + 2 5 -3 - B +2 5
Small CrainWheat -3 -5 + 16 -4 - 8 - 8 - 6 -10 + 2 -5 - 9 - 4 —4 - 8 - 8 -3 -8 - 3 -4 -8 - 8 -4 - 9 _ -)Oats -1 -6 +16 -3 -10 -10 -27 -31 -14 -5 -11 -10 -6 -11 - 8 -5 -9 - - -3 -8 -12 -8 -12 - 7
Milk -1 -3 + 12 -2 - - - 2 _ 2 - 4 + 3 -2 — 4 + 1 - 3 + 2 -1 -3 + 3 -1 -3 0 - 3 + 3
LivestockBeef -1 -6 0 -1 - 6 -10 - 2 - 7 + 6 +3 - 2 + 3 -1 - 7 _ 2 _2 -7 - 1 -.2 -6 - 9 -1 - 6 - 3Pork -1 +12 -1 - <4 +11 - 2 - 5 +11 -1 - 4 + 12 -1 - 4 +11 -2 -4 +12 1 -4 + 11 -1 - 3 + 11
_ 2 -5 + 12 _2 - 5 + 9 - 2 - 5 + 8 -2 - 5 + 9 —4. - 5 + 9 -2 -5 + 9 -2 -5 + 9 -2 - 5 + 9Broilers and -2 -4 +-13 -2 - 4 +13 - 2 - 4 + 13 -2 - 4 +13 -2 - 4 +13 -2 —4 +13 _2 -4 +13 -2 - 4 + 13turkeys
A: Conservation tillage vs. conventional tillage no soil loss restriction. B: No-cillage vs. conventional tillage no soil loss restriction.C: Soil loss restricted to T-values with conventional tillage.
00
8 8
respectively. Expansion in quantities of corn and small grains would
occur, primarily, due to an increase in the State's average yields ol
these crops in response to conservation tillage practices(Table 5.4.3)
However, the increase in the State's soybeans supply would result from
a substitution of this crop for corn and small grains under chisel
plowing and no-tillage. (The economic rationale and details of this
substitution were described in Section 5.2.)
Table 5.4.3
Simulated Changes in Ohio's Average Crop YieldsUnder Alternative Tillage Systems
CropsTillage System
Conventional Chisel Plow No-tillage
( Yield per Acre )
Corn ......... ( bu ) 109.5 110.9 114.7
Corn Silage ... (tons) 15.5 16.3 17.2
Soybeans ( bu ) 39.0 38.3 38.1
Wheat ......... ( bu ) 44.7 45.7 46.3
Oats ......... ( bu ) 65.1 66.6 69.0
Alfalfa ..... (tons) 5.2 5.1 4.6
Grass Hay .... (tons) 3.3 3.5 3.5
Cropland Pasture (tons) 2.2 2.2 2.3
89In response to expansion in crop production levels under
chisel plowing, the State's average prices of corn, soybeans, and
wheat would fall by nearly 2, 3, and 4 percent, respectively.
Average prices of these commodities would fall even more noticeably
with no-tillage, i.e., by 6, 8, and 9 percent respectively. As a
result, quantities of corn, soyebeans, and wheat exported would
increase, (3,4, and 4 percent, respectively). Also, the rise in
supply and the fall in prices of major feed crops (i.e., corn,
soybeans, and oats) would induce a small increase in production and
a minor decrease in the State's average prices of milk, beef,
pork, poultry meat, and eggs (Table 5.4.2).
Substitution of chisel plowing and no-tillage for con
ventional tillage would also increase the State's economic surplus
from the farm sector (i.e., farmers' net returns + consumer's
surplus) by 1.5 and 5.5 percent, respectively. Specifically,
because of the higher production levels and lower prices, under
the two tillage systems consumers' surplus would rise by nearly
4 and 13 percent. However, for the same reasons, farmers' net
returns would decline , approximately, by 6 and 14 percent, res
pectively (Table 5.4.4).
In terms of the changes in crop production and farmers'
net returns, regional impacts of conservation tillage systems would
be much stronger than the State as a whole (Tables 5.4.1, 5.4.2,
and 5.4.4). As described in Section 5.2, production of row crops
would be substantially expanded in northeastern and eastern Ohio,
where, cropland is predominantly well-drained. In contrast, in
90Table 5.4.4
Simulated Changes in Ohio Farmers' Net Returns Resulting from Changes in Tillage Systems.and Soil Loss Restriction
By Region
Model Scenario A B C
Regions ( Percent Change in Net Returns)
Corn-belt -15 -28 +202 - 6 -16 + 3
3 Dairy + 5 +11 +13
Appalachian +12 +17 -235 + 1 + 3 -17
6 Transition - 7 -13 +10
7 Southwest - 4 - 6 -16
State - 6 -14 + 5
A : Tillage system change from conventional to chisel plow, with no restrictions imposed on soil loss
B : Tillage system change from conventional to no-tillage , with no restrictions imposed on soil loss
C : Annual per acre soil loss restricted to T-values under conventional tillage systems
91
western and southwestern Ohio, a large increase in production of
small grains and/or forages in substitution for row crops would
take place. As a result, total net returns to farmers would
noticeably rise in regions 3 and 4, while, they would significantly
decline in rest of the State (Table 5.4.4). The strongest negative
impact on farmers' net returns would occur in northwest Ohio.
In that region, (primarily, because of the yield-depressing-effects
of conservation tillage on poorly-drained soils), farmers' total3/net returns would decline 15-28 percent — .
B. Economic Impacts from T-value Restriction ofSoil Loss
Under conventional tillage systems, T-value limitation of
annual erosion from Ohio cropland would cause a considerable
cut-back in the State's row crop acreage and a major expansion in
acreages of forages and pasture-on-cropland. Major economic impactsVstemming from these land-use adjustments would be the following — .
(1) The State's corn and soybeans production would decline
by 5 and 10 percent, respectively. As a result, prices of these
crops would rise at respective rates of 20 and 25 percent.
3_/ As discussed in Section 5.2, this study has assumed that adoption of conservation tillage methods on poorly-drained soils decreases average crop yields by 5 percent.
4/ Remember from Chapter IV that,based on the proportionaldemand, model assumes similar changes in other major production areas in the nation.
92
(2) Production of forages and pasture would expand upto
75 percent. As a result, shadow prices of hay and pasture-on-
cropland (i.e., oppotunity cost of allocating cropland to these
crops) would decrease by 18 percent.
(3) The changes in production and prices of feed grains,
forages, and pasture-on-cropland would induce:
a) a 6 percent increase in production, and a 3 percent
reduction in price of beef; and
b) respective reductions of 5, 13, and 3 percent in
production of pork, eggs, and poultry meat; and the respective
increases of 11, 9, and 13 percent in prices of these commodities.
(4) As a result of higher corn and soybeans prices, Ohio's
exports of these crops would decline by 10 and 16 percent, respectively.
(5) The cut-back in production and the rise in prices of
major crops and livestock commodities would decrease the farm-sector's
consumers’ surplus by almost 5 percent. However, because of a
relatively large increase in farm prices, total net returns to
farmers would rise nearly 5 percent. Nevertheless, total economic
surplus from the State's farm sector would decline by approximately
2.5 percent. That is, the total loss occuring to consumers from
T-value restriction of soil loss would be greater than the total
gains accruing to Ohio farmers.
(6) Regionally, T—value limitation of soil loss would lead
to a 20 percent rise in farmers' total net returns in regions 1, 3,
and 6, where, cropland is relatively less prone to erosion. In
93
contrast, implementation of this policy would substantially squeeze
farmers' net income in regions 4, 5, and 7 , where, cropland is
highly erosive ( Table 5.4.4). Northwestern Ohio, the State's
least erosive region, would benefit the most among three regions
which would gain from a T-value based erosion control policy. On
the other hand, eastern Ohio farmers would lose the most from
such a policy, as their net returns would decline as much as 25
percent . In western Ohio (region 2), despite a considerable
reduction in soybeans acreage, soil loss restriction would have
the least impact on farmers' net returns. In this region, a major
corn-for-soybeans substitution and the higher row crop prices
resulting from soil loss restraints would increase farmers' total
net returns by nearly 3 percent.
5.5._____ Sensitivity Analysis
In order to investigate sensitivity of the model to some
potential expansions in export and industrial demand for grain and
soybeans, a total of 17 runs were made. They reflect a 5, 10, 15,
and 20 percent increase in export demand for corn, soybeans, and
wheat, and a 60 and 100 percent increase in (domestic) industrial 5/
demand for corn . These scenarios were analyzed under both
conventional and conservation tillage systems, with and without
The 60 and 100 percent increase in industrial demand for corn — refer to 60 and 100 million gallons of alcohol production,
respectively. These levels of alcohol production add a 24 million and a 40 million bushel increase in industrial corn demand to the 40 million bushels of corn which are currently used by the corn sweetner plant at Dayton.
imposing T-value limits on soil loss. In general, the results
indicate that, under conventional tillage practices, soil erosion
and economic impacts from the potential expansions in demand for
grain and soybeans would be fairly strong. Especially, with
T-value restriction of soil loss, the aforementioned levels of
expansion in export demand would cause a sharp increase in crop and
livestock prices. Under conservation tillage systems, soil erosion
impacts from the above changes in demand would be insignificant,
however,the economic impacts would be similar to those under
conventional tillage systems. The following focuses on the results
of conventional tillage scenarios.
A. Impacts from the Potential Expansions in Export Demand
Simulated changes in Ohio's agricultural land-use, production,
prices, and annual erosion rates at different levels of export
demand are presented in Tables 5.5.1, 5.5.2, and 5.5.3.
Changes in Land-Use and Erosion Rates. With no limits
imposed on soil loss, a 5-20 percent increase in export demand
would cause a minor to moderate expansion in corn, soybeans, and
wheat acreages in substitution for forages and pasture. The
increase in row crops acreage would occur mainly in northeastern,
eastern, and central Ohio, while, wheat acreage would expand in
western and southwestern Ohio. As a result, the State's average
erosion rate would rise by 10 percent. Regionally, the most drastic
increase in soil loss would take place in eastern Ohio, where,
Table 5.5.1 95
Simulated Percent Changes in Ohio's Agricultural Land-Usa, Production, and Prices at Three Levels of Expansion in Export Demand
for Corn, Soybeans, and Wheat
(No Restrictions on Soil Loss)
Percent Change
Demand Intercepts +10 +15 +20
Land-UseCorn + 2 + 4 + 5Soybeans + 3 + 4 + 5Small Grains + 2 + 2 + 2Forages & Pasture - 8 -25 -32
Crop ProductionCorn Produced + 3 + 4 + 6
Feed (ohio) - 5 - 8 -10Feed ( US ) — — —Export +11 +12 +16Alcohol — — —Corn Sweetner — — —
Soybeans Produced + 2 + 3 + 4Processed — — —
Export + 4 + 6 + 8
Livestock ProductsMilk - 3 - 4 - 6Beef -15 -22 -28Pork - 0.3 - 0 .6 - 1Eggs - 6 - 9 -13Poultry meat - 1 - 2 - 3
Commodity PricesCorn +14 +21 +29Soybeans +19 +29 +39Wheat +18 +27 +35Milk + 3 +12 +18Beef +22 +31 +40pork +10 +15 +20Eggs +12 +18 +23Poultry Meat +11 +17 +23
Table 5.5.2 96
Simulated Percent Changes in Ohio's Agricultural Land-Use, Production, and Prices at Three Levels of Expansion In Export Demand
for Corn, Soybeans, and Wheat
(Soil Loss Restricted to T-Values )
Demand Intercepts +10
Percent Change
+15 +20
Land-UseCorn Soybeans Small Grains Forages & Pasture
Crop ProductionCorn Produced
Feed (Ohio) Feed ( US ) Export Alcohol Corn Sweetner
Soybeans Produced Processed Export
Livestock ProductsMilkBeefPorkEggsPoultry Meat
Commodity PricesCornSoybeansWheatMilkBeefPorkEggsPoultry Meat
- 9 -13 + 6 +18
- 3- 9
- 3
- 9
-15
- 2.5+ 2.5- 9 -24- 4
+37 +51 + 1 + 7 + 5 +24 +22 +28
- 8.5 -14 + 7 +23
- 3 -12
- 2
- 9.5
-16
- 3+ 0.6 -11 -29- 5
+47 +64 + 7 +10 + 9 +31 +28 +35
- 8 -15 + 8 +22
- 3 -15
+ 2
-10
-16
- 4.5- 2 -35 -35 - 6
+57+90+13+17+15+38+34+42
97
Table 5.5.3
Simulated Changes in Annual Erosion Rates At Three Levels of Expansion in Export Demand for
Corn, Soybeans, and Wheat Under Conventional Tillage Methods - Ohio
Percent Change in)emand Intercepts +10 +15 +20
legions percent Change in Top-■Soil Loss
1 — —
Corn-Belt2 + 0.5 + 0.7 + 0.9
3 Dairy + 3.0 + 7.0 +21.0
A +30.0 +43.0 +49.0Appalachian
5 + 3.0 + 6.0 + 9.0
6 Central + 1.0 + 1.3 + 2.0
7 Southwest + 5.0 + 8.0 +11.0
State + 6.0 + 8.0 +10.0
98
annual erosion rates would rise 30 to 50 percent (Table 5.5.3).
Changes in Crop and Livestock Prices. The general price
impacts from the above changes in crop exports would be fairly
strong. Especially, within the range of a 10-20 percent increase
in demand, prices of corn, soybeans, and wheat rise 30, 35, and 40
percent, respectively. This would induce a significant upsurge
in prices of beef, pork, poultry meat, and eggs. However, the
sharpest impact would be on beef price which would rise 40 percent
(Table 5.5.1). The stronger impact on price of beef, (in addition to
higher corn and soybeans prices), would be caused by a major
cut-back in production of foragesand pasture-on-cropland.
These price impacts would become even more substantial when the
State's erosion rates are restricted to T-values. In that case,
the expansions in export demand combined with more than a 10 percent
reduction in the State's row crop acreage would push respective
prices of corn and soybeans up to 60 and 90 percent above their
current levels. However, since soil loss restraints would cause
nearly a 20 percent expansion in acreages of forages and pasture,
the rise in beef price would be relatively moderate (Table 5.5.2).
B. Impacts from Expansions in Industrial Demandfor Corn
99Impacts on Land-Use and Soil Erosion. With no restrictions
on soil loss, production of 60 and 100 million gallons of ethanol,
(demanding an additional 24-40 million bushel of corn) would induce
a 5-8 percent expansion the State's corn acreage — ^. Close to a 90
percent of the new corn acreage would be shifted from soybeans and
the rest would be removed from other crops. Regionally, the major
increase in corn production would occur in northeastern, central,
and southeastern Ohio.
The new demand for corn would not lead to an increase in the State's
average erosion rate. In fact, due to the substitution of corn for
soybeans, Ohio's overall annual soil loss per acre would fall
nearly 2 percent. Especially, in central Ohio, a larger corn-for-
soybeans substitution would result in upto 16 percent reduction in
average annual soil loss. However, in eastern and southeastern
Ohio (location of alcohol plants) because of a net expansion in row-
crop agriculture, average annual erosion would rise about 20 percent
(Table 5.5.4).
Impacts on Commodity Prices. The 24-40 million bushels of
additional demand for corn would not pose an important impact on the
State's average prices of major crops or livestock commodities.
Specifically, corn price would rise upto two percent or $0.06
6/ Remember that, 60 million gallons is the State's current alcohol — production level. The 24 million bushel demand for corn pertaining
to this level of alcohol production was included in all other runs of the model which were discussed earlier. However, in this section, to show the specific impacts from the alcohol industry's demand for corn, the results are compared with a situation of zero- alcohol production, for which additional runs have been made.
100
Tahlp 5.5.4
Simulated Changes in Annual Erosion Rates at Two Levels of Expansion in Industrial Demand for Corn
Under Conventional Tillage Methods - Ohio
Industrail Demand of
P.egions 24 mil. bu. 40 mil. bu.
( percent change in annual soil loss )
12
Corn-belt : —
3 Dairy — —
45
Appalachian + 4 +12
+ 7 +20
6 Transition -10 -16
7 Southwest — —
State
per bushel at the State levels and in regions distant from
the alcohol plant site. However, in the vicinity of the plant
location (southeastern Ohio), corn price would increase 5 percent
or $0.15 per bushel.
CHAPTER VI
Summary and Conclusions
6.1. Summary.
The ability of soil to tolerate impact of erosion is called
the soil loss tolerance level, or T-value. T-value has been defined
as the maximum rate of soil erosion that will permit a high level of
crop productivity to be maintained economically and indefinitely.
Annual erosion rates exceeding T-values are considered excessive.
A major cause of excessive soil erosion is intensive use
of agricultural land. Production of row crops such as corn and
soybeans accelerates excessive soil loss from cropland, as it exposes
unprotected soil to wind and water.
From the economic and societal standpoints, excessive
erosion causes two major problems. 1) It depletes the future
productivity of cropland. 2) sedimentation caused by cropland
erosion imposes substantial costs upon society.
In order to maintain the long-term productivity of soils
and to prevent the substantial external costs of cropland erosion,
private and public actions are needed to reduce excessive
soil loss.However, implementation of a soi] conservation policy may have important economic impacts on farmers and consumers.
In Ohio, given the State's regional diversity of soil and
topographic conditions, statewide use of soil conserving tillage
systems, and T—value restriction of soil loss would each have
significant regional economic impacts.1 0 2
103
To analyze these potential impacts, the objectives of the
present study have been to determine the following:
a) the State's cropland use patterns, agricultural production,
farm prices, and annual erosion rates under conventional and
conservation tillage systems;
b) the potential land-use and economic impacts from T-value
restriction of annual soil loss; and
c) Sensitivity of the State's agricultural economy and soil
erosion rates to some potential levels of expansion in export and
industrial demand for grain and soybeans.
These objectives were achieved by using a seven-region,
price-endogenous mathematical programming model of Ohio' agricultural
economy. Under assumption of proportional demand, competitive
equilibrium production and prices for Ohio's major agricultural
commodities (i.e., corn, soybeans, wheat, milk, beef, pork, poultry
meat, and eggs) were determined by maximizing total economic surplus
of the farm sector and consumers. The objective function was
maximized subject to four major types of restrictions: 1) land
resource constraints, 2) minimum output of Ohio's minor farm prodcuts
3) grain delivery constraints, and 4) soil loss restrictions.
To capture the diversity in soil characteristics, and to
estimate the State's soil erosion rates, the more than 500 soil series
of Ohio were divided into 77 soil groups. Similarities in slope,
erodibility, response to conservation tillage, T-value, and natural
productivity were used as criteria for the soil grouping process.
104
Average annual erosion rates for each soil group under different
cropping activities and tillage systems were estimated through
the Universal Soil Loss Equation.
The analysis included six major scenarios and a set of
sensitivity runs. They reflect three different tillage systems,
namely, conventional (moldboard plowing), reduced (chisel plowing)
and no-tillage. In general adoption of each tillage system (depending
on soil type) would result in different crop yields and/or different
production costs. These scenarios were analyzed with and without
imposing T-value restrictions on soil loss.
6.2. Conclusions. The principal conclusions are the following.
1) Substitution of conservation tillage systems for
conventional tillage would not cause any major change in Ohio's
total cropland allocation. However, regionally, conservation
tillage practices, especially, no-tillage, would have a major impact
on cropland-use patterns. For example, a major soybeans-for-corn
substitution on poorly-drained soils in the northwest, a major
expansion in row-crop production on well-drained soils in the north
east, and a moderate substitution of small grains for row crops in
western Ohio would take place.
2) Under conventional tillage systems, the State's overall
erosion rate would exceed its average T-value by nearly 44 percent.
However, in central, southwestern, and eastern Ohio excessive soil
loss would range from 120-160 percent. Predominant adoption of
1 0 5
conservation tillage systems on all suitable soils would decrease
overall annual erosion rates to a level nearly 15 percent below the
State's average T—value. Nevertheless, in eastern and southwestern
Ohio excessive soil loss still would persist,
3) Substitution of soil conserving tillage methods for
conventional tillage would result in a slight increase in Ohio's
average crop yields. This would lead to a small rise in production
and a moderate fall in the State's average prices of major crops
and livestock commodities. As a result, consumers' surplus would
increase by nearly 10 percent, while, farmers' net returns would
fall by almost the same amount. However, there would be a net
improvement in the farm sector's total economic surplus. That is,
the potential gain in consumers' surplus would be greater than the
potential decline in net returns to farmers.
4) Under conventional tillage systems, imposition of
T-value limits on soil loss would force Ohio farmers to remove
nearly 6 percent of the State's currently utilized cropland from
production. This would result in more than a 10 percent reduction in
row crop acreage and about 15 percent expansion in acreages of forage
and cropland pasture. As a result, average prices of corn and
soybeans would rise by nearly 20 percent, and a moderate increase in
prices of livestock commodities (except beef) would follow. The
cut-back in production and the rise in prices of major crops and
livestock products would decrease consumers' surplus by close to a
5 percent. At the same time, total net returns to farmers would
106
increase by 5 percent. Nevertheless, total economic surplus attribuat—
able to the State’s farm sector would decline by 2.5 percent.
Regionally, farmers and/or cropland owners in less erosive regions
(i.e., northwestern, northeastern, and central Ohio) would benefit
fror.i a T-value based erosion control policy, while, the opposite
would take place in Ohio's more erosive regions (i.e.,eastern,
southeastern, and southwestern Ohio).
5) T-value restriction of soil loss under conservation
tillage systems would not pose any restraints on utilization of
the State's available cropland acreage. However, some moderate
reduction in acreages of row crops in the State's most erosive
regions (i.e., eastern and southwestern Ohio) would prevail.
6) a 5-20 percent expansion in export demand for grains
and soybeans would cause a small expansion in acreage of corn,
soybeans, and wheat. As a result, Ohio's average erosion rate would
increase by 10 percent. The price impacts resulting from expansions
in export demand would be fairly strong. In this case, when annual
soil loss is restricted to T-values, corn and soybeans prices would
rise 60 and 90 percent above their current levels. In contrast,
channelling 24-40 million bushels of corn to Ohio's alcohol industry
would pose little overall impact on the State's agricultural economy.
6.3. Policy Implications and Needs for Further Research.
Viewed from the perspective of long-term soil conservation
policy, the major findings of this study suggest the following.
1 0 7
1) Abatement of excessive soil loss on Ohio cropland
can be well achieved by statewide substitution of conservation tillage
methods for conventional tillage practices. Furthermore, dealing with
the soil erosion problem through this approach would improve the
State's net economic welfare, although, specific groups of farmers
would incure moderate reduction in net returns.
2) If the predominant use of conventional tillage systems
is continued, then, imposition of soil-specific T-value limits to
eliminate excessive soil loss, would make consumers economically
worse-off, penalize farmers operating in the State's highly erosive
regions, and reward those farmers who operate on less erosive cropland.
3) In analyzing the economic and soil erosion impacts of
alternative cropland—use patterns in Ohio, the present study has deter
mined only those direct costs and benefits which would occur to the
present generation of farmers and consumers. However, the off-site
as well as the inter-generational economic impacts associated with
these land-use patterns remain undetermined. These general issues
require further research at the state level. They are:
a) the off-site damage costs of excessive cropland erosion
in Ohio;
b) the off-site benefits and costs associated with use of
alternative soil conservation strategies in Ohio; and
c) the potential inter-generational impacts resulting from
the present excessive loss of topsoil and implementation of alternative
erosion control strategies.
108
Results of the present study provide some structural
information towards formulation of the suggested research. The
soil-specific quantities of annual erosion and the shadow prices
associated with these soil losses which have been determined by the
present model can be used as a base for estimation of the off-site
economic impacts and the loss of future productivity.
Bibliography
109
Abraham, G., "Estimating Sediment Off-Site Damage Costs in Northwestern Ohio," Unpublished Ph.D. Dissertation,The Ohio State University, Columbus, Ohio 1982.
Alt, K.F., "An Economic Analysis of Field Crop Production:Insecticide Use and Soil Erosion in a Sub—Basin of the Iowa River," Unpublished Ph.D. Dissertation, Iowa State University, Ames, Iowa, 1976.
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APPENDIX A
Table la
Commodity
Parameters of Price-Determinant Equations
Unit of Measurement Intercept* Slope*
Corn Soybeans Wheat w ' , Milk Meal Pork Fowl Eggs
Corn
Soybeans
Wheat
Soybean Meal
Milk
BeefPork
Fowl
Eggs
thousand bushels 9,600
20,135
13,170
41,316
52,517(live wt) 201,225
C " JC " )
195,489
185,677
1 ,782
-0.0278
-0.1781
-0.3313
-2.5800
-0.9994-16.2071 - 0.3134 - 0.5362 -0.0048
- 8.5819 -14.1735 - 8,7253 -0.0835
- 4.9832 - 2.948h -50.4437 -0.0481
- 0.0976 - 0.0580 - 0.0993 -0.0017
* elements of vector in equations 1 and 2.
** elements of matrix B in equations 1 and 2.