United States
Environmental Protection
Agency
Office of Research
and Development
Washington, DC 20460
EPA/600/R-98/038
June 1998
«EPA
Sustainability and
Resource Assessment
A Case Study of Soil Resources
in the United States
-------
ISBN 0-9665761-0-1
-------
EPA/600/R-98/038
June 1998
Sustainability and
Resource Assessment
A Case Study of Soil Resources
in the United States
by
Dana L. Hoag and Jennie S. Hughes Popp
Professor and Research Associate, Respectively
Department of Agricultural and Resource Economics
Colorado State University
Fort Collins, CO 80523
and
D. Eric Hyatt
National Center for Environmental Assessment
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
-------
Keywords:
agricultural conservation; agriculture-economic aspects-mathematical models; agricultural
productivity; assessment, ecological risk; conservation of natural resources, conservation of
natural resources-United States; crop yields; ecology-simulation methods; environmental policy;
environmental quality; environmental risk assessment; prediction of soil erosion; soils-United
States; soil erosion; soils-Iowa; soils-Minnesota; soils-Missouri; soil protection; sustainable
agriculture; sustainable development
Preferred citation:
Hoag, D. L.; Popp, J. S. H.; Hyatt, D. E. (1998) Sustainability and resource assessment:
a case study of soil resources in the United States. Research Triangle Park, NC: U.S.
Environmental Protection Agency, Office of Research and Development; report no.
EPA/600/R-98/038.
DISCLAIMER
This document has been reviewed in accordance with U.S. Environmental Protection
Agency policy and approved for publication. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
11
-------
ABSTRACT
Assessment of environmental condition is critical to wise management and policy
decisions. However, for some concerns such as sustainability, it is difficult to assess
environmental condition because it involves disparate social objectives and an understanding of
complex ecological systems. Here, a general framework is proposed to examine sustainability of
environmental resources in objective, measurable ways. By using soil quality as an example,
sustainability research is taken beyond theory and into application.
Sustainability depends on the quality of resource endowment. Endowment of a natural
resource can be modeled as an index of quality to assess the degree of sustainable management.
This index, consisting of the most important identifying characteristics of the resource, is placed
into a dynamic model of production to determine how resource use affects three different
versions of sustainability. The economic, social, and environmental impacts are identified for
each sustainability requirement, and the long-term path of resource quality is evaluated.
Soil quality was chosen as a natural resource because its importance is immediately
obvious and because there is a wealth of data compared to other resources. Three general soil
types—stable, neutral, and susceptible—were selected. The index of soil quality was used in a
corn production setting to address three questions: (1) What are the impacts of different
definitions of sustainability on the economy and the environment? (2) Do U.S. soil conservation
policies address sustainability objectives? (3) How do substitution, reversibility, and uncertainty
affect optimal soil use?
Results show that impacts, as well as the ability to meet sustainability goals, are highly
dependent on soil type and on how sustainability is defined. In some cases, soil can be managed
the same under any definition, but, in other cases, different sustainability concepts are at odds.
In general, the deeper and better the soil, the more obvious and consistent was the approach to
sustainability. Lower quality soil types require more complex approaches.
The results of this study can be used to help determine which soils need to be protected,
identify tradeoffs between conservation and nitrate leaching as erosion occurs, show how risk
and uncertainty affect soil conservation decisions, and provide other information helpful to
policy makers dealing with soil management. Additionally, the methods used here can be useful
to evaluate other, more complex natural resources such as forest health.
in
-------
-------
CONTENTS
Page
LIST OF TABLES vii
LIST OF FIGURES viii
ACKNOWLEDGMENTS ix
1. INTRODUCTION 1-1
1.1 Purpose 1-1
1.2 Objectives 1-2
2. WHAT IS SUSTAINABILITY? 2-1
2.1 Definition 2-1
2.1.1 Constant Consumption 2-1
2.1.2 Constant Stock of Natural Resources 2-2
2.1.3 Intergenerational Equity 2-2
2.2 Three Common Themes 2-3
2.2.1 Substitutability 2-3
2.2.2 Reversibility and Uncertainty 2-6
2.3 Assessing Sustainability 2-9
3. A CASE STUDY OF SOIL CONSERVATION IN THE UNITED STATES 3-1
3.1 Background 3-1
3.2 Conceptual Framework 3-3
3.2.1 Introduction to Soil Quality 3-3
3.2.2 Soil Quality Assessment 3-3
3.2.3 An Index of Soil Quality 3-4
3.2.4 Soil Quality in a Production Setting 3-5
3.2.5 Soil Quality Degradation—Natural Influences 3-7
3.2.6 Soil Quality Degradation—Human Influences 3-8
3.2.7 Managing Soil Quality for Sustainability 3-8
3.3 A Dynamic Model of Sustainability in Production 3-11
4. ANALYSIS AND RESULTS 4-1
4.1 Data Collection 4-1
4.1.1 EPIC Simulation Model 4-1
4.2 Development of a Soil Quality Index 4-2
4.2.1 Soil Quality and Yield 4-3
4.3 Econometric Evaluation of Relationships 4-4
4.4 Testing the Definitions of Sustainability in an Optimization Framework 4-5
4.4.1 Baseline Scenario 4-6
4.4.2 Profit Maximization Scenario 4-7
4.4.3 Sustainability as Constant Consumption 4-8
4.4.4 Sustainability as Constant Resource Stock 4-9
4.4.5 Sustainability as Intergenerational Equity—Reduced Leaching 4-10
4.4.6 Sustainability as Intergenerational Equity—Income Potential 4-11
-------
CONTENTS (cont'd)
Page
4.5 Scenario Wrap-Up 4-12
4.5.1 Observations About Reversibility and Uncertainty 4-13
Appendix 4A—Tables for Chapter 4 4A-1
5. CONCLUSIONS 5-1
5.1 Selected Findings 5-1
5.2 Further Research Opportunities 5-2
6. REFERENCES 6-1
VI
-------
LIST OF TABLES
Number Page
4A-1 Soil and Management for Simulation Model Scenarios 4A-2
4A-2 Simulated Soil Quality Over 100 Years for Three Tillage Levels 4A-3
4A-3 Simulated Yields by State and Soil Type for a 100-Year Simulation 4A-3
4A-4 Regression Coefficient Estimates in the Production Function 4A-4
4A-5 Regression Coefficients in the Soil Quality Function 4A-5
4A-6 Regression Coefficients in the Soil Nitrogen Function for All Soils 4A-6
4A-7 Regression Coefficients in the Leaching Function for All Soils 4A-7
4A-8 Summary of the Conditions, Results, and Impacts of Three Definitions of
Sustainability on Three Stable Soils 4A-8
4A-9 Summary of the Conditions, Results, and Impacts of Three Definitions of
Sustainability on Three Neutral Soils 4A-9
4 A-10 Summary of the Conditions, Results, and Impacts of Three Definitions of
Sustainability on Three Susceptible Soils 4A-10
4A-11 Compatibility of Sustainability Definitions on Different Soils 4A-11
vn
-------
LIST OF FIGURES
Number Page
2-1 Partial substitution/complementary relationships 2-5
2-2 Degrees of technical interdependence 2-6
2-3 Illustrating irreversibility 2-8
3-1 Impacts of soil quality on production 3-6
3-2 Three types of soil and their paths of soil quality deterioration 3-9
3-3 The effect of erosion on soil quality 3-10
3-4 Possible trade-off between soil quality and other inputs 3-10
4-1 Paths of soil quality with and without soil conservation possibilities 4-13
4-2 The impact of soil conservation on soil quality reversibility on susceptible
soils 4-14
Vlll
-------
ACKNOWLEDGMENTS
The authors are grateful to Verel Bensen and David Buland from the U.S. Department of
Agriculture (USDA), Blacklands Research Center, USDA Natural Research Conservation
Service, for partial funding and staff support and to Ray Sinclaire and the numerous scientists
that helped us through the maze of decisions about data and methods used throughout this study.
We also wish to thank Debra Meyer, Research Associate (Intern), U.S. Environmental Protection
Agency, and David Belton of OAO Corporation for their extensive assistance during the editing
process.
IX
-------
-------
1. INTRODUCTION
Society's ability to produce goods depends on the availability and quality of inputs. Inputs
may be natural, and either renewable or nonrenewable. They may also be unnatural, or
reproducible human made inputs, such as labor, technology, and physical capital. For a long time
these delineations were unimportant. The rise of the popular sustainability movement has,
however, given impetus to questions of where inputs come from and which resources are
affected. Disregard for sustainability may reduce long-term economic productivity and
encourage environmental and ecological losses. Sustainability of the production process requires
that inputs from natural resources be given equal consideration to outputs or consumption
because resources provide more services to society than simply producing goods.
Assessing natural resource sustainability is not easy. Ecosystems are complex compared to
the broad terms used to express societal goals, such as "clean water" and "sustainable"
environment. Consequently, policy makers need complex information about ecosystems
expressed in simple terms. Ecosystem assessment is the process of interpreting and evaluating
scientific data and information for the purpose of answering policy-relevant questions about
ecological resources. Addressing policy concerns involves more than integration and aggregation
of facts. Ecosystem assessment must help assign significance or value to the information
collected through appraisal and judgment. It is desirable to keep value judgments to a minimum
and to make such judgments as objective and transparent as possible. However, the intrusion of
values is unavoidable when condensing information about a complex system into a simple
measure.
1.1 PURPOSE
Sustainability suffers a similar predicament to many worthy causes. A majority want to
achieve it, but few can agree upon the means. Inputs are closely tied to each other and therefore
society's use of its natural resource endowment may have profound impacts on its future.
Sustainability advocates offer three general convictions. One group asserts that the flows from
1-1
-------
natural capital should be transformed into human capital to maintain sustainability. Another
contends that perpetuating a constant stock of natural capital is the only way to achieve
sustainability. A third group specifies no formula for sustainability, asserting only that the end
result should provide equity across generations.
The dilemma is not trivial. Society has a fixed endowment of natural resources and the
consequences of miscalculating appropriate resource management could be severe.
If management is too conservative, production in some sectors of the economy may needlessly
degenerate, and social welfare (standard of living) for future generations could decrease.
If management overly exploits natural resources, basic environmental functions may go
unfulfilled, leaving irreversible damages for future generations.
1.2 OBJECTIVES
The objective of this study is to evaluate the sustainability of a production process that uses
both renewable and nonrenewable inputs. Sustainability will be examined by testing for the
existence of substitutability, reversibility and uncertainty criteria for three different definitions of
sustainability. This study is applied to soil quality for producing crops. And, although it is
applied to agriculture, it offers some general procedures that may be applied to other areas of
production (such as forests), where the loss of nonrenewable resources is of great concern.
To explore sustainability in an agricultural production setting, sustainability literature and
economic theory are coupled with an empirical model of production. The objective may be met
by addressing the following three questions: (1) What are the impacts of different definitions of
sustainability on the economy and the environment? (2) Do U.S. soil conservation policies
address sustainability objectives? (3) How do substitution, reversibility, and uncertainty affect
optimal soil management?
1-2
-------
2. WHAT IS SUSTAINABILITY?
2.1 DEFINITION
Sustainability has been defined by many people in an almost equal number of ways
(Pezzey, 1992; Gold, 1994). In effect, it is much easier to agree to be sustainable than it is to
define or achieve it (Helmers and Hoag, 1993; Schuh and Archibald, 1993). Definitions range
from a precise sustain-me approach that focuses on one concern only, such as the health of rural
economies (DowElanco, 1994) or environmental conservation (U.S. Department of Agriculture,
1980), to an all-inclusive definition that addresses many considerations. However, a review of
the economic and development literature shows that most definitions are centered around
economic, environmental and social welfare objectives (Cernea, 1993; Munasinghe, 1993; Rees,
1993).
It is difficult to get people to agree about what is sustainable when objectives are valued so
differently. Although there are many interpretations, the three well known definitions we have
adopted for this study are (1) sustainability as constant consumption, (2) sustainability as a
constant stock of natural resources, and (3) sustainability as intergenerational equity.
2.1.1 Constant Consumption
Hartwick (1977, 1978) and Solow (1974a, 1974b) defined sustainability as the ability of
society to maintain a constant stock of consumption (or productivity). This definition, referred to
as weak sustainability, addresses economic concerns. Under weak sustainability, natural capital
(natural resources) and manmade capital (physical capital) may substitute for each other in the
production process. Researchers (Dixit et al., 1980; Hartwick, 1977, 1978; Page, 1977; Solow,
1974a, 1991) have proven theoretically that total production and per capita consumption may be
maintained as long as profits from the use of natural resources are invested into physical capital.
Weak sustainability does not require any particular endowment of capital or final goods to be
passed on to future generations. Instead, it requires only that a general capacity to reproduce be
maintained.
2-1
-------
2.1.2 Constant Stock of Natural Resources
A second and seemingly contradictory definition focuses on the means of sustainability by
placing great importance on the form in which productive capacity is transferred across
generations. Pearce and Atkinson (1993, 1995), among others (Beckerman, 1992; Boulding,
1973; Daly, 1995; Jansson et al., 1994), contend that natural and manmade capital complement
each other in the production process. In this relationship, known as strong sustainability, natural
capital that is not easily reproducible is the limiting factor of production and, therefore, must be
preserved for production to be sustainable.
Those who support strong sustainability defend their position by invoking three arguments.
First, uncertainty of the consequences of natural resource depletion should lead decision makers
to adopt a conservative position with regard to resource use. As Pearce and Warford (1996) note,
this is comparable to the notion of safe minimum standards for plant and animal species
advocated by Bishop (1978) and discussed by Lesser and Zerbe (1993). Second, natural resource
depletion is permanent and any permanent change should be approached very slowly and
carefully. Third, not only do natural resources provide inputs for production, they also perform
multiple functions in the environment. Resources should be preserved to ensure fulfillment of
these other functions.
2.1.3 Intergenerational Equity
A third and more general definition, created by the World Commission on the Environment
and Development, contends that sustainability is a process "... of change in which the
exploitation of resources, the direction of investment, the orientation of technological
development and institutional change are made consistent with future as well as present needs"
(World Commission on Environment and Development, 1987, p. 13). In other words,
sustainability requires that the needs of the present are met without compromising the ability of
future generations to meet their needs.
This definition differs from the previous two in that it imposes neither substitutability nor
complementary relationships on natural and human inputs but requires some undefined measure
of intergenerational equity to be fulfilled. This allows researchers the opportunity to test
different criteria for their contribution to sustainability.
2-2
-------
Support for both consumption and preservation of resources is reflected in governmental
policies and legislation. Over the course of six decades, the U.S. Department of Agriculture has
promoted both soil conservation (set asides) and maximum production (plant fence row to fence
row) policies. Similarly, logging has been restricted in some areas of the country and expanded
in other areas. These examples suggest that society benefits from both the consumption and the
preservation of its natural resources. But how much should be preserved? How much may be
consumed? Comparing the impacts of different resource management levels can help determine
where the optimal level of resource protection lies and what a genuine notion of sustainability
may be.
2.2 THREE COMMON THEMES
When resources are placed in a production setting, three criteria can be used to evaluate the
impacts of each definition of sustainability on resource management: substitutability,
reversibility, and uncertainty. The values placed on these criteria by society and by individuals
can determine the allocation of resources.
2.2.1 Substitutability
Substitutability refers to the change in the use of one input as the price or the availability of
another input changes. Ease of substitution is extremely relevant when one or more inputs to
production are becoming scarce, since sustainability will depend on how easily and effectively
other resources can substitute for the scarce input.
Substitution among inputs can be broken into three general cases: perfect substitution,
imperfect substitution, and complements. Inputs axe perfect substitutes when there is one input
that can completely replace another. For example, if the current supply of coal was depleted,
other fuels or hydroelectric power could be used in its place to maintain energy production.
Inputs are imperfect substitutes when one input can partially replace a scarce input; however,
some minimum amount of the scarce input is needed to maintain production. A high percentage
of the human workforce may be replaced with machines, but one human will always be needed to
make sure the machinery is operating properly. Inputs are complements when they can only be
2-3
-------
used in some fixed proportion to produce a given level of output. Water is produced when two
parts of hydrogen mix with one part of oxygen. Water will not form when any other ratio of
hydrogen to oxygen is combined.
Theory addresses the substitutability of inputs on two general levels: factor
interdependence and technical interdependence. Factor interdependence measures how the
change in the price of one input will affect the demand for another input as output is held
constant. Technical interdependence measures how the change of the price in one input will
affect the demand for another as both prices and output are allowed to change. The differences,
though subtle, are important. Under factor substitution, in order to maintain output at a given
level, as the use of one input goes up the use of its substitute goes down. Because output is free
to change under technical substitution, both inputs are free to move either up or down. Under
factor complementarity, for output to remain constant, the level of both inputs applied must
remain the same. Yet under technical complementarity, inputs are free to change, provided they
both move in the same direction. Factor and technical interdependence examples are illustrated
below.
Substitution/complementarity relationships are mapped on a single quadrant graph
(Figure 2-1) with the scarce/unique input on one axis and a potential substitute on the other axis.
An isoquant measures the various combinations of the two inputs which produce some constant
level of output. The optimal input mix is found where the isoquant is tangent to a line
representing the current price ratio (PRJ of the two inputs. In all three panels in Figure 2-1, the
optimal input mix rests at point M.
The ease of substitution is defined by the curvature of the isoquant. The flatter the
isoquant, the greater the substitution possibilities. Once the isoquant forms a 90° angle, it is no
longer possible to substitute away one input for another and maintain the given level of output.
Suppose the ratio of prices changes from PRl to PR2a. In order to find the new optimal input mix
that produces the same level of output, a parallel shift is made from the new price ratio line to
another (from PR2a to PR2b) so that the parallel line is tangent to the isoquant. The new point of
tangency (N) represents the new optimal input mix. In Panel 1, the flat isoquant line suggests
that even if all coal is depleted, energy production will be maintained with hydroelectric power.
In Panel 2, the slight curve in the isoquant suggests that machinery is an imperfect substitute
2-4
-------
05
O
o
Panel 1
Perfect Substitutes
VI
Energy
Hydroelectric Power
Isoquant
o
.a
c
03
E
Panel 2
Imperfect Substitutes
Factory
J'"!.,. output
Machines
PR,
Figure 2-1. Partial substitution/complementary relationships.
c
0)
D)
O
PR.
Panel 3
Perfect Complements
Water
2a
Oxygen
PR.
•2b
for human labor—some degree of human labor will be necessary to maintain production. The
kink in the isoquant in Panel 3 illustrates that there is no other mix of hydrogen and oxygen that
can produce the given amount of water as effectively.
Any two inputs that are perfect factor substitutes will be perfect technical substitutes. Any
two inputs that are perfect factor complements will be perfect technical complements. However,
as illustrated in Figure 2-2, imperfect factor complements can become either technical substitutes
or technical complements.
Assume that an automobile factory has the option to use both human labor and machinery
to produce cars. In the first panel of Figure 2-2, as the ratio of human wages to machinery prices
changes from P^ to PR2b, more automobiles can be produced by increasing the use of machinery
and decreasing the use of human labor (from Y0 to Yj). These inputs, which are factor
substitutes, are also technical substitutes. However, in other types of production (perhaps
another factory that uses both human and mechanical inputs), changes in output levels can only
be made by some fixed ratio of change in the level of inputs used. In this case, two inputs that
were factor substitutes are technical compliments.
2-5
-------
Panel 1
Technical Substitutes
Panel 2
Technical Compliments
o
_Q
CD
C
CD
1
I
O
.0
CD
E
Machines
Machines
Isoquant
PR,
PR,
PR.
2b
Figure 2-2. Degrees of technical interdependence.
2.2.2 Reversibility and Uncertainty
Reversibility and uncertainty are best explained together. Reversibility pertains to the
ability of production to revert back to a former input mix once it has chosen others. Uncertainty
refers to any unforeseen circumstances (both positive and negative) that may either follow as a
consequence of, or impact production. Uncertainty arises with respect to all prices, input supply,
output supply, profits, and environmental impacts.
As production depletes a natural resource it becomes more dependent on other inputs.
If use of these replacement inputs later leads to unforeseen consequences, the producer may not
be able to readjust because it is costly, difficult and time consuming, or even impossible. The
ability to reverse input mixes becomes extremely important for two reasons, especially when
circumstances resulting from uncertainty are negative. First, in many cases these impacts do not
limit themselves to the particular production process but may affect other sectors of the economy
or the environment. Second, these impacts may be irreversible. The three scenarios that follow
illustrate degrees of reversibility and possible consequences.
2-6
-------
Scenario 1 A manufacturer may use plantation trees or synthetics to produce
office paper. If the stock of mature plantation trees is depleted,
Reversibility: Easy production can be maintained with synthetic substitutes. If the
Consequences- Minimal price of synthetics increases greatly in the future, the manufacturer
can harvest the newest crop of mature trees, and manage the
plantation so that it provides a continuous supply of wood for the
future. It may take time, however, and be difficult to acquire an
equilibrium of trees, creating serious income or cook flow
problems.
Scenario 2 A land manager controls a parcel that is 50% dry land and 50%
wetlands. The wetlands are drained in order to have 100% dry
Reversibility: Difficult land for agricultural production. Later the land manager finds that
Consequences: Moderate the wetlands helped control water flow (important for production)
to Serious and provided habitat for rare birds. Part or all of the natural
wetlands may be restored, but it may take time, effort and expense.
Water flow and species habitat may be hampered until the wetland
is restored.
Scenario 3 A tea maker uses exotic and domestic tea leaves to produce a
flavorful tea. The exotic leaf is necessary to production because it
Reversibility: Impossible alone can produce the special taste. Other manufactures use this
Consequences: Severe leaf in other production processes and native insects depend on the
leaf as a vital food source. As the exotic leaf is consumed,
production remains relatively unaffected. When the plant
becomes more scarce, however, production drops until it reaches
zero as the leaf is completely depleted. Multiple production
processes have been slowed or halted, and two natural resources
(the exotic leaf and the insect species) have been lost forever.
The process of irreversibility is illustrated in Figure 2-3. Again, the isoquant represents all
the various combinations of two inputs which can be used to generate the same specified level of
2-7
-------
Panel 1
Exotic Plant Is Plentiful
Panel 2
Exotic Plant Is Threatened
Panel 3
Exotic Plant Is Depleted
P-
0_
o
"o
\
P-
0.
o
\
P-
Q_
O
"5 Q_
scH
\
Domestic Plant
Figure 2-3. Illustrating irreversibility.
Domestic Plant
Domestic Plant
output. Let this particular level correspond to the demand for the product in the market.
Returning to the tea leaves example, when the exotic plant is plentiful (P), the tea manufacturer
has the option to (a) move away from domestic leaves and use more exotic, or (b) move away
from the exotic and use more domestic, in response to availability and price of the two types of
leaves. However, as supplies of the exotic plant become scarce (S), the manufacturer will be
forced to move the input mix further down the curve in the (b) direction. Graphically, the
isoquant has been truncated, as shown in Panel II. Although in theory the isoquant still looks the
same, the loss of the exotic plant has reduced the manufacturer's real set of possible input
combinations to exclude the upper portion of the isoquant. At some point, as the supply of the
exotic plant falls below its critical level (Sc), the plant can no longer reproduce itself. Output
levels will drop with the loss of the plant, since there simply is not enough input to produce the
desired output. Ultimately, the plant is extinct and production no longer possible.
When input mixes dependent on substitutes for natural resources lead to unforeseen
negative consequences, it is likely that the magnitude of the negative impact will be much larger
for society than it will be for the individual producer. Profits for a tea maker may decline, if the
quality of tea is reduced by the loss of the exotic plant. However, two natural resources—a plant
and an insect species—have been completely destroyed. Reversing societal decisions can be
2-8
-------
slow or impossible (it might take a lawsuit to restrict the harvesting of the exotic plants— during
this time the plants could become extinct). Therefore, it is also likely that the risk that society
attaches to depleting a natural resource will be higher than that for an individual. Individuals will
be more likely to deplete a natural resource than society, and thus, when left to individuals, it is
likely that the resulting level of natural resource conservation will be suboptimal from society's
point of view.
Appropriate Input Substitution for Scarce Resources
Rule 1: A scarce input may be partially (completely) depleted when an imperfect (perfect) substitute
exists that imposes little or no negative externality (i.e., negative economic, environmental
or social impacts).
Consequence: Output may be maintained or increased, as shown in the cases of energy and
automobile production.
Rule 2: Resource conservation may be needed if an input's contribution is unique to a production,
ecological or valuation process and not easily substitutable.
Consequence: If the resource is regenerative, production can be maintained at a level that
requires the use of a resource that is less than or equal to its regenerative
rate. If the resource is finite, then production levels must decrease in order
to preserve the resource.
2.3 ASSESSING SUSTAINABILITY
There are many ways to consider whether the actions of society are sustainable. Here, the
following question is asked: How should society manage a unique resource stock to provide both
economic and environmental services? To begin to answer this question, the following points
should be considered.
• Society is endowed with a stock of a natural resource.
• This resource provides economic and environmental services.
• If the economic services of the resource are stressed, will it crash or can an equilibrium be
found where some environmental services are maintained?
• What is the relationship between the stock of the resource and the economic and environmental
services it provides?
2-9
-------
What is a sustainable path for the economic and environmental services?
Case 1: The resource quality crashes and both the economic and environmental values are lost.
Case 2: All environmental values are preserved and no economic value gained.
Case 3: A sustainable combination of both economic and environmental services is found
based on the value of each.
2-10
-------
3. A CASE STUDY OF SOIL CONSERVATION IN
THE UNITED STATES
3.1 BACKGROUND
Although many studies have discussed an assessment of the environment based on
sustainability criteria, few have been able to model real natural resources. Consequently, these
studies usually are unable to provide empirical conclusions that support theories about
substitution, reversibility and uncertainty. This study conducts a detailed empirical analysis of
one of the most impacted ecosystems in the country, soil on American farms. Soil management
is a reasonable place to start when examining environmental assessment. One reason is that soil
is the most studied environmental stock in the world. Examined first for its part in promoting
crop production (Hilgard, 1892; Karlen et al., 1997; Olsen, 1943; Walker and Young, 1986), data
and analyses now also exist to explain the role of soil in food quality and safety and ecosystem
management (Johnson et al., 1992; Kennedy and Papendick, 1995; National Research Council,
1993; Parr et al., 1992; Warkentin, 1995). Results from these studies illustrate other reasons why
environmental assessment may begin with the soil.
• Soil has an important impact on the environment. For example, according to the National
Research Council, erosion from agriculture is responsible for over half of all surface water
pollution (National Research Council, 1993). Soil is now recognized for its positive impact on
many functions of the ecosystem, such as nutrient recycling, rainfall partitioning and buffering.
However, when it leaves the farm, soil is also responsible for negative impacts that affect water
quality, air quality and wildlife habitat.
• For over a half century, the U.S. Government and farmers have spent billions of dollars for soil
conservation on croplands in an effort to reduce soil erosion and reduce impacts on wildlife
and water (U.S. Department of Agriculture, 1994).
• Because soil quality is related food production, it can significantly impact human life.
There are two further reasons which make soil an appropriate area of focus. First, recent
research in soil science has produced a list of measurable soil characteristics that can be used to
describe the quality (stock) of a particular soil (Bowman et al., 1989; Doran et al., 1996; Kiniry
3-1
-------
et al., 1983; Larson and Pierce, 1994; Pierce et al., 1983). This creates some general consensus
about the assessment endpoint of soil quality. Second, data for soil are more abundant in the
U.S. than data for any other natural resource. There are extensive national homogenous
databases (Soils-5, National Resource Inventories) with soil variables for polygons as small as a
few acres. In addition, a team at the USDA Blacklands Research Center in Temple, Texas,
supports the most extensive soil management database available to date. Together, these data
can be used in simulation models to examine the impacts of the multiple objectives of
sustainability on resource assessment. Policies or management that maintains soils, and those
that maintain other objectives such as economic returns, can be compared. Using biophysical
models of soil productivity, potential impacts can be observed before they actually happen.
The existing soils, sociology, development, ecology and economic literature was surveyed
for two purposes. The first was to determine what, if any, related work has been undertaken.
This included a review of the many notions of sustainability and the criteria used to judge
sustainability. The second purpose was to gather theories that would help formulate theoretical
underpinnings for resource management.
A review of the literature showed that many studies have acknowledged the need for an
extensive study of sustainability, but none have yet undertaken an analysis of multiple concepts
and criteria of sustainability via an expansive resource data set. Perhaps this is because no single
discipline possesses all the theoretical and empirical tools needed to attempt a project of this
proportion. By combining sustainability and evaluation criteria from the social and ecologic
literature with soil quality, degradation, and regeneration relationships adopted from the
agronomy and soil science fields, the following proposal was made: for soil, sustainable resource
management will be determined by the availability of soil and substitute inputs subject to the
ease of substitution and the risks associated with irreversibility and uncertainty.
This postulation is tested by developing an index of soil quality and applying it in a
dynamic model of production.
3-2
-------
3.2 CONCEPTUAL FRAMEWORK
3.2.1 Introduction to Soil Quality
Soil is a dynamic, heterogeneous, living system of micro-organisms, organic matter, water,
gases and mineral particles. Each system, comprised of surface and subsurface layers, or
horizons, is formed from long term interactions of parent materials,1 weathering and biological
processes. The resulting combination is called a soil series, of which there are over 17,000
classified in the United States to date (Natural Resources Conservation Service, 1995).
The particular combination of a soil's many chemical, biological and physical properties
determines its ability to function. The definition of soil quality proposed by the Soil Science
Society of America encompasses the multiple functions of the soil. "[Soil quality] is the capacity
of a specific kind of soil to function within natural or managed ecosystem boundaries, to sustain
plant and animal productivity, maintain or enhance water and air quality and support human
health and habitation" (Karlen et al., 1997, p. 6).
Soils acquired their particular characteristics through years of formation, and may still be
modified by natural processes (primarily erosion, yet also temperature and water content) and
human activities (mixing or erosion) today. Changes in these soil properties can alter the soil's
ability to function and, therefore, could have implications for sustainability.
3.2.2 Soil Quality Assessment
Assessing soil quality is often compared to assessing human health (Larson and Pierce,
1991; Doran and Parkin, 1994; Acton and Gregorich, 1995). During a medical exam, key
indicators such as temperature, heart rate, blood pressure, height and weight are measured that
together make a general account of health. If these measurements are within accepted levels, the
individual is assumed to be functioning normally. If these measurements are outside of an
acceptable range, further tests can be conducted to determine the cause for the irregularity and
perhaps prescribe a healing treatment. Similarly, if there exists a set of basic measurable soil
indicators, there would be a means of assessing soil health. If the indicators are within an
'Parent material is defined as the "unconsolidated and more or less chemically weathered mineral material
from which soils may be synthesized," (Buckman and Brady, 1960). These materials develop from igneous,
sedimentary and metamorphic rocks.
3-3
-------
acceptable range, the soil can be presumed to possess the capacity to carry out its functions.
If these indicators are outside of the acceptable range, a careful look at other chemical, physical,
and biological soil properties may help identify the cause of the abnormality.
The assessment endpoint (quality) may vary substantially for different purposes. Using the
health analogy, someone well enough to walk may not be well enough to run a marathon.
Consequently, any measure of soil quality must consider the intended use. For soil, producing
native grasses may be easier to sustain than monocultural cropping. Therefore, using a series of
indices to describe soil quality, each with its own purpose, is recommended. Here, the focus is
on two such indices, the quality of soil for producing crops, and nitrate leaching. No specific
index is developed for nitrate leaching, but rather the impact of quality for yield on leaching is
investigated to determine consistency between the two objectives.
3.2.3 An Index of Soil Quality
Recently, many researchers have recommended so called "complete" sets of soil quality
indicators.2 However, a model developed by Pierce et al. (1983) seems to be the best starting
point here. The Pierce model is simple to understand, and not only does it specify both a set of
soil quality indicators and a standard to measure them against, but it can also be used to predict
the changes in soil quality (and possibly production) brought on by resource degradation. In this
model, soil productivity (PI) was calculated as
PI = (SAWC * SBDt * SPHt * WR\ (3-1)
z=l
where SAWC is the sufficiency of available water capacity, SBD is the sufficiency of bulk
density, SPH is the sufficiency of pH, WF is a weighting factor associated with each /'th horizon,
and r is the number of 10-centimeter horizons in the rooting depth.
In the Pierce et al. (1983) study, soil quality was calculated for three different soils types:
(1) stable soil (soil quality does not change much with erosion), (2) neutral soil, and
(3) susceptible soil (soil quality may change greatly with erosion). The researchers forecasted
potential impacts of erosion on soil quality and production for each soil type. The analysis
2See National Research Council (1993), Doran et al. (1994) and Karlen et al. (1997) for more details.
3-4
-------
revealed four important insights about the relationship between erosion and soil productivity and
the relationship between soil productivity and production.
(1) Erosion can change the levels of available water capacity, bulk density and pH in the soil and
thus change the productivity of a soil.
(2) Susceptible soils will experience greater changes in soil quality than stable soils under
conditions of erosion.
(3) A positive (negative) change in soil productivity will likely have a positive (negative) effect
on agricultural production.
(4) The directional change in soil productivity depends on the relative quality of subsoils as
compared to the quality of the surface soils.3
3.2.4 Soil Quality in a Production Setting
In agricultural production, yield is a function of weather conditions, added inputs and soil
quality. Added inputs include variables of production that the farmer can control, such as tillage
level and use of fertilizers and chemicals. In addition to these inputs, there is an endowment of
soil quality. Soil quality is a unique input in the production process because (1) unlike added
inputs, the farmer has no control over the initial endowment, and (2) as illustrated in Figure 3-1,
soil quality can contribute to the effectiveness of the added inputs and thereby have implications
for production levels and the mix of inputs a farmer will use in production.
Assuming that a farmer chooses an optimal mix of two added inputs, fertilizer and water,
a maximum yield can be attained (Yfw) as in Figure 3-1. Including soil quality (sq) in the
production of the crop can have a positive impact on the plant growth. The amount of impact
depends on how much soil quality affects how water and fertilizer contribute to plant growth.
If soil quality acts independently of both water and fertilizer, productivity of those inputs does
not change. If their productivity levels do not change, the farmer will continue to use those
inputs in the same way, regardless of what happens to soil quality. For example, if soil quality
3From this insight, it is evident that soil is a very unusual resource. Erosion can remove some of the soil
base and negatively impact soil quality. But in some cases, by partially depleting the soil resource base, soil quality
may improve and therefore better perform its multiple functions in its ecosystem. See Popp (1997) for further
discussion of this particular case.
3-5
-------
Panel 1
Soil quality acts
independently of other
inputs.
Panel 2
The productivity of
fertilizer is increased
by soil quality.
Y
f,w,sq
f,w,sq
f,w
f,w,sq
Output is increased by
the amount of soil
quality.
f,w,sq
The higher the initial
productivity level of
the added input, the
greater the potential
of improved yields.
Figure 3-1. Impacts of soil quality on production.
Panel 3
The productivity of
fertilizer and water are
both increased by soil
quality.
f,w,sq
f,w
f,w,sq
All added inputs are
more productive than
before.
adds 50 units of productivity to the production process, output will be 50 units more for every
level of fertilizer and water used.
Sometimes soil quality and other inputs, such as water and fertilizer, are dependent on each
other (complements or imperfect substitutes). For example, a reduction in soil quality due to
erosion might make fertilizer less productive. If fertilizer is less productive than before, a farmer
might have to reduce fertilizer and, consequently, the output, as soil quality is diminished.
An example of how productivity increases for fertilizer as soil quality is improved (or diminishes
as soil quality is reduced) is shown in the second panel of Figure 3-1. Productivity gains are
3-6
-------
greater at higher levels of fertilizer input due to the multiplicative impacts of soil quality and
fertilizer working together.
Soil quality could affect all added inputs in the production process. As shown in the third
panel of Figure 3-1, output will increase the most for this example, because both water and
fertilizer are more productive. The substitutability of soil quality for other inputs, therefore,
greatly impacts the importance of protecting a given endowment of soil. Given that soil quality
improves output, farmers would rather have some endowment of soil quality than none at all.
And, to the extent soil quality improves the productivity of other inputs, farmers would rather
have higher levels of soil quality than lower levels.
3.2.5 Soil Quality Degradation—Natural Influences
All natural resources change over time through the normal operations of the natural
environment.4 Eutrophication (the aging process of a lake) provides a good example. When a
lake is newly formed, there is little plant life. But as time goes on, plant life multiplies and the
water slowly disappears until the lake no longer exists. Tourists may walk around the lake on
paved trails to observe plant life in its natural habitat. Just looking at the lake has no impact on
the eutrophication process. Eutrophication depends only on the resource quality, which in this
case is the characteristics of the lake and the living organisms within it.
Similarly, all soils are subject to a natural rate of change caused by erosion. Erosion
removes soil from the surface and eventually exposes the subsurface layers. Soil quality
degradation will depend, in part, on how much change erosion can cause (i.e., where potential
change is determined by the quality of the topsoil compared to the quality of the lower
horizons5). This will depend on the quality of the surface horizon when compared to the lower
horizon, on the ability of natural processes to offset erosion, and on the influence of human
activities that accelerate slow erosion rates.
"Only cases of deterioration are examined here. Although all soils have a natural rate of regeneration, that
rate is slow enough for soil to be considered a nonrenewable resource for the time frame of this research.
'Similarly, the erosion rate also will be determined, in part, by the slope of the land. The process remains
the same; only the rate will differ.
3-7
-------
There are many paths of change soils may take. This study examines three general cases as
depicted in Figure 3-2. Soils whose subsurface layers have a similar quality to the top soil are
called stable soils. As these soils are worn away by erosion, their quality remains relatively
unchanged (Panel 1). Some soils have lower layers that are similar but reduced in quality. These
are called neutral soils because as they are impacted by erosion; the soil degrades for a time but
then stabilizes, as shown in Panel 2. Other soils, susceptible soils, are very vulnerable to erosion
because beneath a thin good quality top layer is a very poor quality soil. With erosion, the
quality of the soil declines continuously until it (asymptotically or actually) reaches zero, as
shown in Panel 3. Examples of these soil cases are discussed further in Pierce et al. (1983).
3.2.6 Soil Quality Degradation—Human Influences
Humans can influence soil quality degradation by altering the rate of erosion. Some inputs
in a production process may increase or decrease erosion rates. As shown in each of the panels
of Figure 3-3, the natural path of soil quality is altered up or down. Conventional tillage
equipment (such as a moldboard plow) may loosen soils, making it easier for them to be carried
away by wind and water. This soil using input can have initial positive impacts on production,
but will increase the rate of production decline later. Inputs that do not have any impact on soil
degradation are considered to be soil neutral inputs. A producer may choose to establish
conservation practices, such as placing vegetative cover on fallow land, contour plowing, or
terracing. These practices may or may not impact current production levels, but will slow the
rate of soil degradation.
3.2.7 Managing Soil Quality for Sustainability
As soil quality changes, farmers will attempt to adjust the input mix to maintain economic
viability (and meet environmental standards if society requires them). In other words, these firms
manage for sustainability. Managers begin by asking, Is the production process sustainable as
soil quality declines? The answer depends on the relationship between soil quality and output, as
well as the relationship between soil quality and other inputs. The impacts of depreciating
natural capital can be complex. Human resources have a technical relationship among
themselves and with the natural capital (soil quality). The relationship between any input and
3-8
-------
Panel 1
Stable Soil
Surface
Root Zone
v
Bottom Depth
Panel 2
Neutral Soil
Surface
1
Panel 3
Susceptible Soil
Root Zone
Bottom Depth
High
Stable Soil
05
3
o
'o
CO
Time
Scale of Quality
CO
O
Poor
Neutral Soil
Time
Susceptible Soil
^
"(5
O
"o
Time
Figure 3-2. Three types of soil and their paths of soil quality deterioration.
soil quality will be independent, substitutable, or complementary. Moreover, this relationship
may change as soil quality deteriorates. It is expected that as long as substitutes exist, as soil
quality decreases, the use of other inputs will follow one of the paths in Figure 3-4 in an attempt
to maintain output levels.
A producer may choose to irreversibly depreciate soil quality in favor of a substitute, as
shown in Panel 1. When the input mix changes this dramatically, yields may be maintained for
a time. However, unforeseen economic and environmental consequences may ensue. For
3-9
-------
Panel 1
Panel 2
Panel 3
>
+^
"CD
O
'o
C/}
Time
£
CD
O
'o
0)
Time
CD
a
Time
Natural rate of
depletion
Accelerated depletion
from conventional
tillage
Figure 3-3. The effect of erosion on soil quality.
Panel 1
Panel 2
CO
-I—'
3
Q.
c
CO
"5
Q.
C
Slowed degradation
because of
conservation
practices
Panel 3
CO
-I—'
3
Q.
C
Time
Time
Time
Soil Quality
Other Inputs
Figure 3-4. Possible trade-off between soil quality and other inputs.
example, the increased use of a compensating input in one sector may cause excess demand in
the overall economy, increasing the price of the input, and reducing its affordability in all sectors.
Whereas moderate use of a particular input may cause little or no environmental damage, vast
3-10
-------
increases in the use of an input in a short period of time may overwhelm the assimilative capacity
of the environment and cause long term damage. In either circumstance, a producer may want
(or be forced) to change the optimal input mix to include more soil quality and less of one or
more other inputs. If soil quality has followed a path of degradation, as in Panels 2 or 3,
increasing soil quality may still be possible. However, if soil quality has followed a path of
irreversible decline, as in Panel 1, the possibility of altering the input mix to include more soil
quality has been eliminated and production may no longer be sustainable.
3.3 A DYNAMIC MODEL OF SUSTAINABILITY IN PRODUCTION
The empirical dimension of this investigation builds upon the works of Clark and Furtan
(1983), McConnell (1983), Pierce et al. (1983), Saliba (1985), Segarra and Taylor (1987) and
Hoag (1997). Although none of these projects sought to study sustainability directly, their
theoretical and empirical innovations have identified many of the key determinants of production
and the impacts of changes in soil quality. Along with data for real inputs and the characteristics
of soil quality, the models in the above studies provide the basis for a dynamic model of
production and soil quality that illustrates the economic, social, and environmental aspects of
various definitions of sustainability.
Production of any crop 7 is a function of soil quality (SQ), soil using inputs, and soil
neutral inputs. In agricultural production, tillage (L) is a soil using input, whereas soil nitrogen
(SN), nitrogen fertilizer applied (TV), and sprayed pesticides (P) are soil neutral inputs.
Accounting for precipitation (W) as well, production can be expressed as some function/
Yt = f(SQt,Lt,SNt,Nt,Pt,Wt). (3-2)
Soil quality is some function g of the characteristics that impact its ability to perform in its
environment. Pierce et al. (1983) stated that these characteristics were available water capacity
(AWC), bulk density (BD), and pH (PH). Recent studies (Doran et al., 1996; Karlen et al., 1997)
have stated that soil organic matter (SOM) is also an important indicator of soil quality. Together
these four components can be used to create an index of soil quality:
3-11
-------
SQt = g(AWCt,BDt,PHt,SOM,). (3-3)
The change in soil quality each year is determined by annual soil loss. Soil loss in any
period depends upon both the natural level of soil loss (a function of the previous period's soil
quality) and the decisions (M) a producer makes each period, which can increase (tillage) or
decrease (soil conservation) the rate of soil loss. Therefore, the change in soil quality in each
year can be expressed as some fraction h of soil quality and management decisions:
SQt= h(SQt_,,Mt}. (3-4)
Soil nitrogen, in any period, is some function k of the soil nitrogen level, nitrogen applied,
the level of tillage, what was taken up by the crop (proxied by yield) and what leached out
(LCH), all from the previous period:
SNt = *(£#,_, , Nt_lt Wt_, , Lt_, , Yt_, , LCHt_, ). (3-5)
Leaching, in any period, is some function m of soil nitrogen, nitrogen applied, tillage,
precipitation, and crop uptake in the same period:
LCHt = m(SNt,Nt,Wt,Yt). (3-6)
Together, Equations 3-2 through 3-6 provide the basis for a producer's dynamic problem
that can be used to address economic, environmental, and social aspects of production. Simply
stated, the producer's problem is to maximize the discounted profits of production subject to the
availability of soil quality and the level of the environmental byproducts of production:
max 11= Z(l + rr[
1=0 (3-7)
u^L - u2N - u3P - u4SC],
3-12
-------
subject to SQ, = h(SQt_,,Mt\ (3-8)
SNt = KSN^N^L^LCH^, (3-9)
LCHt = m(SNt,Nt,Lt,Wt,Yt) (3-10)
where Py is the price of the output, the w,are prices for the various management practices, and r is
the discount rate.
A producer's management decisions influence the level of crop production in any given
year and have economic, environmental, and social consequences. Social considerations are
captured by tracing the paths of the economic and environmental impacts, thus allowing the use
of this model to examine the various concepts of sustainability and soil quality identified above
in a more meaningful way. By imposing the different definitions of sustainability on the model,
the conditions described below are expected.
• For each soil type, there is an optimal path of input use that will result in the optimal amount of
soil quality depletion, output, profit, and environmental waste.
• When output levels are not allowed to fall on a stable soil, soil depletion may be averted by
changing the input mix. As a result, soil quality and profits may remain stable and
environmental impacts minimal.
• When output levels are not allowed to fall on a susceptible soil, adjustment of the input mix
may not be enough to compensate for the depleted soil quality. As a result, output may not be
maintained, profits may fall, and environmental impacts may become worse through the
increased use of substitutes for soil quality (i.e., more fertilizers that can run off into water
bodies).
• Because stable soils are not easily impacted by erosion, maintaining soil quality on a stable soil
may require only slight adjustments to the optimal input mix. Profits, output, input levels, and
environmental impacts may remain stable.
3-13
-------
• Maintaining soil quality on susceptible soils will likely require large investments in soil
conservation capital. Output may be maintained, but profits will decrease unless the revenue
from the maintained output exceeds the cost of soil conservation.
These conditions, among others, can be investigated over multiple soils and regions of the
country. Empirical results of this investigation are presented in Chapter 4.
3-14
-------
4. ANALYSIS AND RESULTS
This analysis is divided into four parts. First, soil series and crop management data are
placed into a model to simulate crop growth and other economic and environmental aspects of
production. Using some of the soil characteristics produced by the simulation runs, a new index
of soil quality is generated. Next, through regression analysis, simplified mathematical
representations of a producer's dynamic problem from the simulation output are estimated.
Finally, these functions are placed into an optimization framework where the three definitions of
sustainability are examined.
4.1 DATA COLLECTION
Nonirrigated corn production on three soils each in Minnesota, Iowa, and Missouri were
chosen as the setting to test the impacts of the various definitions of sustainability. The state,
crop, and soil selections were based on previous studies using productivity indices (Kiniry et al.,
1983; Pierce et al., 1983), and on advice from experts from the Natural Resources Conservation
Service (Ceolla, 1997; Tammons, 1997). Three levels of tillage, fertilizer, and pesticide use for
corn producers in those states were taken from a national survey of producers (U.S. Department
of Agriculture, 1990-1995), the USDA's newest and most extensive data set on soil quality
characteristics, and on information from USDA about soil management patterns. This data has
been integrated into a simulation model framework (EPIC) by members of the Natural Resource
Conservation Service in Temple, Texas, thereby providing a setting that simulates in multiyear
periods the economic, environmental, and social impacts of production on soils and for realistic
management practices.
4.1.1 EPIC Simulation Model
The Environmental Policy Integrated Climate (formerly Erosion Productivity Impact
Calculator), or EPIC, model has been used extensively to evaluate crop productivity, degradation
of soil resources, impacts on water quality, responses to different input levels and management
4-1
-------
practices, responses to spatial variations in climate and soils, and risks of crop failure (Mitchell
et al., 1995). It has also, in part, been designed to track and answer the following questions, all
of which are related to the issues of sustainability (Dyke and Heady, 1985).
• To what extent can capital and labor substitute for soil resources altered by erosion?
• What is the additional cost incurred when these substitutions are made?
• When do these substitutions become physically or economically impossible?
Crop production was simulated for 100 years based on the soil and management
specifications listed in Table A4-1 (all tables cited in this chapter are located in Appendix 4A).
Corn production was simulated for nine tillage/fertilizer management scenarios:
(1) conventional/low,
(2) conventional/medium,
(3) conventional/high,
(4) conservation/low,
(5) conservation/medium,
(6) conservation/high,
(7) no till/low,
(8) no till/medium, and
(9) no till/high.
Starting values for all other variables were set to the EPIC defaults. A total of 81 scenarios, nine
tillage/fertilizer scenarios on nine soils, were run for 100-year increments. As a result,
8,100 observations were generated for more than 200 soil, production, weather, economic, and
environmental indicator variables. Simulated yields were calibrated against actual reported yields
in the three regions to help ensure that the model results were representative of the study area.
4.2 DEVELOPMENT OF A SOIL QUALITY INDEX
Because many studies advocate the importance of soil organic matter for soil quality (Acton
and Gregorich, 1995; Bowman et al., 1989; Doran et al., 1996; Karlen et al., 1997; Olsen et al.,
1994), the index developed by Pierce et al. (1983) was adapted to include organic matter
information. A sufficiency for soil organic matter was created based on the works of Bowman
and Petersen (1996) and Fieri (1995). Calculations for the other index components were
4-2
-------
consistent with the methods used by Pierce et al. (1983). Soil quality (SQ), in any given year, is
the summation of the product of a weighting factor (WF) and sufficiencies of available water
capacity (SAWC\ bulk density (SBD\ pH (SPH), and organic matter content (SOMC) for each
/'th horizon in the rooting depth:6
SQ = Z(SAWC, * SBD, * SPH, * SOMC, * WF,). (4-1)
Values for the individual sufficiency equations and weighting factors range from zero to
one. When multiplied together, these sufficiencies form an index of soil quality that also ranges
from zero to one. The closer the value is to one, the better the soil quality.
Table 4A-2 shows the ranges of soil quality for each soil under three levels of tillage.
Fertilizer levels are ignored because fertilizer is a soil neutral input and has no influence on
inherent soil quality. Even under conventional tillage, stable soils reach a steady state quality at
0.72. Neutral soils are impacted by erosion and tillage more than stable soils, but eventually their
soil quality levels stabilize at about 0.66. The quality of susceptible soils decreased at an
increasing rate, even under no till practices, suggesting that susceptible soils may become
completely depleted over time.
4.2.1 Soil Quality and Yield
As reported in Table 4A-3, yield fluctuations over the 100 years were considerable. For
example, yields as high as 166.7 bushels and as low as 100.4 bushels were recorded on the Iowa
stable soil. Moreover, yields on neutral and susceptible soils sometimes were greater than on
stable soils. For example, Minnesota's neutral soil produced a high yield of 197.4, whereas the
high yield on the stable soil was only 164.7. These fluctuations occur in EPIC-type growth
models because of extreme weather events within the simulation period or other modeling
factors. On average, over the 100 years, soil quality/yield relationships were as expected for all
soil types. That is, the stable soils produced higher yields than neutral soils, and produced much
higher yields than the susceptible soils.
6Details about the index formulation can be found in Popp (1997).
4-3
-------
These results from the simulation model are consistent with the proposition that soil quality
is an important input into agricultural production. The better the soil quality, the greater the yield
per unit of input. Also, soils that are more susceptible to erosion (whether natural erosion or
erosion induced by human activities) have greater losses in soil quality.
4.3 ECONOMETRIC EVALUATION OF RELATIONSHIPS
Soil quality was placed in a dynamic setting to examine how changes can influence the use
of other inputs. This can be a convoluted process; EPIC expresses crop production as a
complicated relationship among hundreds of variables. Dynamic sustainability questions are,
however, more manageable when the components of the optimization model are expressed as a
function of a few key variables. Using fewer variables also provides more degrees of freedom
and reduces the possibility of multicollinearity. A brief discussion of the pertinent data
manipulation techniques follows.
The EPIC simulation model generates data both across characteristics and over time. Panel
data has been used frequently to address questions in classical areas of economics, such as
market structure return, investment, and market demand. Rarely has it been employed to
examine agricultural and resource issues in economics. Using the fixed effect regression
technique on the panel data, the following four equations over nine soils were estimated:
Yt = f(SQt,Lt,SNt,Nt,Pt,Wt) adj R2 = .729 (4-2)
SQt = KSQ^L^) adj R2 = .986 (4-3)
SNt = k(SNt^Wt_,Nt^Lt_,Jt^LCHt_,} adj R2 = .999 (4-4)
LCHt = n(SNt,Nt,Wt,SQt,Pt,Lt) adj R2 = .737, (4-5)
recalling that 7 is corn yield or output, SQ is soil quality, 57V is soil nitrogen, TV is added fertilizer,
P is pesticide, Wis precipitation, L is tillage (the soil conservation component of M, tillage and
soil conservation, was added later in the optimization section of the project), LCHis leaching,
and t and M represent current and previous period values, respectively. Using methods suggested
4-4
-------
by Hsiao (1986), Maddala (1993), and Vickner (1997), all equations were tested and corrected
for misspecification, homoskedasticity, and serial correlation associated with panel data analysis.
Although the set of relevant variables has been reduced from over 200 to only 14, the adjusted
R2 values reveal that these variables have captured between 73% and 100% of the variation in
the dependent variable for each equation.
For the fixed effects model, some of the estimated parameters are unique to a particular
group. Therefore, even within the regression equation for corn production, there are actually nine
estimated equations. The sets of parameters for the four estimated equations for each soil are
given in Tables 4A-4 through 4A-7.
The production function (Equation 4-2) was fitted to the transcendental functional form.
This form is extremely relevant to the issues of sustainability because it allows the substitution
and complementarity relationships among inputs and soil quality to change over the range of
input use (time). For example, fertilizer and soil quality may be substitutes at high levels of soil
quality. Once soil quality is reduced below a certain level, however, the relationship may
become complementary, meaning that further increases in fertilizer use cannot offset the declines
in production due to loss of soil quality. This and other scenarios are examined in the dynamic
model.
The soil quality function (Equation 4-3) has both quadratic and linear elements. The soil
nitrogen function (Equation 4-4) was estimated as a linear function. The leaching function
(Equation 4-5) was estimated as a logarithmic function, meaning that as the value of the variables
increases, their impact on leaching is still increasing, but at a decreasing rate.
4.4 TESTING THE DEFINITIONS OF SUSTAINABILITY IN AN
OPTIMIZATION FRAMEWORK
The optimization portion of the analysis was conducted using the GAMS (General
Algebraic Modeling System)/MINOS approach (Brooke et al., 1992). This model solves the
producer's dynamic problem over discrete time. Along with the equations estimated through
regression analysis, corn fertilizer, tillage, pesticide, and soil conservation prices and discount
rates taken from the USDA (U.S. Department of Agriculture, 1996, 1997) were incorporated into
the GAMS framework to create a total of nine optimization problems, one for each soil in each
4-5
-------
region. From these baselines, new scenarios were created to meet the conditions for the
following objectives:
• Profit maximization—Profit may be maximized based on the selection of fertilizer, tillage,
pesticide, and soil conservation practices in the production process.
• Sustainability as constant consumption—Yield in any year must be at least 90% of the yield
recorded in the first year of the baseline scenario.
• Sustainability as a constant stock of a resource—Conservation practices must be implemented
every year in the 100-year period.
• Sustainability as intergenerational equity—Leaching over the 100-year period must be at least
10% less than leaching over the 100-year period in the baseline scenario.
• Sustainability as intergenerational equity—Measured by income potential or profitability over
the 100-year period.
Baseline scenarios for all nine soils are in Appendix 4A.
Sustainability scenarios were constructed based upon Sustainability definitions found in the
literature. Based on the soil quality indices created from the soils data generated by EPIC, the
initial level of soil quality was set between 0.78 and 0.80, depending on the soil. Discounted
profit, and the paths for soil quality degradation and fertilizer, tillage, pesticide,7 and soil
conservation were noted in all relevant runs. Highlights from three Sustainability scenarios are
summarized in Tables 4A-8 to 4A-10.
4.4.1 Baseline Scenario
In the baseline scenario, producers maximized discounted profits over the 100-year period
by choosing an optimal input mix of soil quality, tillage, pesticide, and fertilizer. Soil
conservation options were not offered. As no conservation measures were available, the path of
soil quality depreciation generated by both natural and human influences over 100 years could be
observed.
In this scenario, soil quality on stable soils depreciated from 0.80 in the early years of
production but reached a steady state at around 0.72, even with the use of conventional tillage
7Pesticide usage was fairly constant under all scenarios and provided few insights. Thus, it has been left
out of the tables and most of the discussion.
4-6
-------
practices. The optimal mix of soil quality and added inputs generated high annual yields, no less
than 134 bushels per acre, and discounted profits of at least $7,100 per acre. In Iowa and
Missouri, fertilizer leaching increased as soil quality was degraded. On the Minnesota stable
soil, leaching decreased initially and then increased.
Steady states for soil quality and input use were also attained on the neutral soil, but later in
the planning period. Soil quality leveled out at roughly 0.66 on all three neutral soils.
Discounted profits were at least $6,500 and minimum yield in any year was at least 122 bushels.
Conventional tillage was used throughout the planning period on all soils. Although still
relatively low, fertilizer leaching was greater than for stable soils. In all three cases, leaching
increased as soil quality decreased over time.
None of the susceptible soils reached a steady state. The Iowa susceptible soil had
degraded to 0.198 by the end of the planning period and the Minnesota soil quality fell to 0.254.
For all soils, fertilizer inputs initially increased as soil quality fell, but then decreased as the
relationship between soil quality and fertilizer became complementary. No till replaced
conventional tillage as depletion of soil quality intensified. As these input levels fell, production
levels also fell about half (on average from 120 bushels to 60 bushels) on all susceptible soils.
Although leaching rates on two susceptible soils were up to nearly 11 Ibs/year, leaching levels for
the Missouri susceptible soil diminished from 1.6 to 0.59 Ibs/year as soil quality was degraded.
4.4.2 Profit Maximization Scenario
A soil conservation option was added to the baseline scenario to determine profitability of
soil conservation. The option available was dependent on soil type. A mathematical
representation of the impact of the respective conservation practice was included in the soil
quality equation in GAMS. Details are found in Popp (1997).
Implementing easy and inexpensive conservation measures on all stable soils for the entire
100 years slightly improved soil quality from 0.80 to 0.811 on average. Annual yields increased
and discounted profits were slightly greater than in the baseline. The input mix stayed relatively
constant throughout the entire planning period. In Iowa and Missouri, soil quality and the added
inputs produced a high steady output and high profits with low levels of leaching. In Minnesota,
however, an overall increase in soil quality led to high output and profit levels but increased, then
decreased leaching.
4-7
-------
Conservation measures were somewhat effective in maintaining soil quality on all neutral
soils, but because of regional price differences for input, output, and conservation practices, the
most profitable level of conservation varied. Consequently, the point in time and the level that
soil quality reached a steady state varied among the neutral soils. Given the high cost of
conservation practices for neutral soils (such as terracing) compared to other inputs, soil quality
was degraded and substituted with slightly more fertilizer for most years in the planning period.
As fertilizer costs grew, both conservation tillage and terraces were introduced into the
production process. Conservation tillage practices were introduced on all soils late in the
production period. Conservation practices were introduced and maintained on the land for
5 years in Minnesota, 10 years in Iowa and 19 years in Missouri. When compared to the baseline
scenario, minimum yields were raised about 3 bushels on each neutral soil, profits increased
slightly and leaching was reduced about 10%.
None of the susceptible soils reached a steady state of soil quality even when conservation
measures were available. Conservation practices for susceptible soils were the most costly of the
soil conservation investments. On the Iowa and Missouri soils, conservation practices were not
effective enough in maintaining soil quality and yield to justify their expense at any time in the
production period. Consequently, for these two soils, the paths of input use and soil quality
degradation that provide the best solution to this scenario are the same as those for the baseline
scenario. Conservation practices were employed for 5 years on the Minnesota soil. As a result,
profits increased about 1% over the baseline scenario and soil quality had fallen to 0.260 at the
end of the 100 years, as opposed to 0.254 in the baseline scenario.
4.4.3 Sustainability as Constant Consumption
The first definition of Sustainability examined was the ability of society to maintain a
constant stock of consumption. The condition required to fulfill this definition of Sustainability
was that annual yields for the entire 100-year period could not fall below 90% of the yield
attained in the first year of the baseline scenario.8 Results are summarized in Tables 4A-8
through 4A-10.
8Bellon (1995) and Marten (1988) have stated that Sustainability implies no more than a 10% change in
production capacity.
4-8
-------
For the stable and neutral soils, the best solution to the constant consumption scenario was
also the solution to the profit maximization scenario. The same did not hold for susceptible soils.
As previously noted, annual yields fell about 50% on the susceptible soils in the baseline
scenarios. On the Minnesota susceptible soil (where annual yield was required to be at least
110.42 bushels), the depreciation of soil quality was greatly slowed by implementing soil
conservation for 70 years, and reducing tillage intensity to no till. Fertilizer levels were also
adjusted. As a result, the minimum yield attained on the Minnesota susceptible soil was
110.47 bushels. Although fertilizer leaching increased from 1.73 to 2.86 Ibs over the 100-year
period, it was drastically lower than under the two previous scenarios on this soil.
For the Iowa and Missouri susceptible soils, there was no optimal path of input mix that
could maintain annual yields at 90% throughout the entire planning horizon. Presumably, this is
because conservation practices were ineffective in keeping soil quality at levels needed to
produce at least 108 bushels of corn on each soil every year.
4.4.4 Sustainability as Constant Resource Stock
The second definition of sustainability states that the stock of soil quality must be preserved
in order for production to be sustainable. One option a producer might consider is to temporarily
or permanently retire land from production. However, in this study, sustainability is examined
under a production setting. Therefore, conservation measures, whether it be contouring, residue
management, or terracing (depending on soil type), were fully implemented every year of the
planning period. Given the differing levels of effectiveness for different conservation practices,
each soil was examined first for its ability to maintain soil quality with the help of conservation
and then for its impacts on other inputs, leaching, and profit.
As soil conservation practices were already implemented on the stable soils in the profit
maximization and constant consumption scenarios, the soil management plan that met the
requirements of the previous two scenarios also fulfilled the constant stock requirement.
Although the constant stock and constant consumption definitions are often cited as having
competing objectives, these objectives are compatible on stable soils.
When all conservation measures were applied to neutral soils, soil quality again increased
from an average of 0.79 to 0.81. Annual yields increased and fertilizer leaching decreased.
4-9
-------
However, increases in total output over the planning period did not offset the added cost brought
on by 100 years of conservation practices. As a result, profit levels fell.
Conservation practices were unable to bring susceptible soils into a steady state with
continuous cropping over the 100-year period. However, erosion decreased such that soil quality
on average was only reduced to 0.63, compared to an average of 0.25 in previous scenarios.
Fertilizer levels again initially increased and eventually declined (sharply in Missouri). Annual
yields fell from an average of 120 bushels to 105 bushels. This is greatly improved over the
profit maximization scenario where annual yields fell from 120 bushels to about 60 bushels.
However, the high cost of conservation needed to improve soil quality and output greatly reduced
the profit level when compared to the constant consumption scenario.
4.4.5 Sustainability as Intergenerational Equity—Reduced Leaching
The third definition of Sustainability requires that the needs of the present are met without
compromising the ability of future generations to meet their own needs. As mentioned in
Chapter Three, there is no consensus regarding the appropriate measurement of intergenerational
equity. Two requirements based on quality of life measures, leaching reduction and income
potential, are explored here.
The first possibility considers human health issues. Groundwater contamination can result
when fertilizer leaches through the soil. Society may implement a policy to reduce overall nitrate
leaching. One way to achieve this is to set a tax on the price of fertilizer. This type of command
and control policy that targets the source of the contamination is effective in reducing pollution
(Baumol and Gates, 1990). Otherwise, if policy makers believe producers have free information
concerning the interactions of fertilizer and leaching on their particular soil, producers may be
left to choose the most appropriate means to reduce pollution from their activities.
Although command and control policies may reduce leaching, it is difficult to find the tax
rate associated with the desired level of pollution. In this optimization run, a 10% tax was levied
on the per pound cost of fertilizer. Interestingly, this tax rate was ineffective in reducing leaching
at least 10% on all soils. Furthermore, output and profits were lower than under other
Sustainability requirements.
The second method undertaken required that leaching in any one year be no greater than
90% of the leaching in the baseline scenario. Under this method, where the producers were free
4-10
-------
to choose their own means to meet the goal, the results were much improved. By reducing the
amount of fertilizer applied in production and maintaining soil quality with soil conservation
practices, all stable soils attained a reduction of at least 10% of overall leaching. For these soils,
the solution that fulfills the requirements of the other two definitions of sustainability is also
befitting to this intergenerational equity scenario. Even in Minnesota, where leaching initially
worsened with improvements in soil quality, overall reductions in leaching were sufficient to
fulfill the sustainability condition.
In all scenarios, the optimal input mixes changed most dramatically on the neutral soils.
Fertilizer levels decreased as conservation measures were added to maintain soil quality.
Leaching reductions were attained but overall production and profit levels fell compared to those
that resulted in the constant consumption scenario. When all conservation measures are
implemented over the entire planning period, as in the constant stock scenario, leaching is
reduced more than 10%.
Management decisions on two of the susceptible soils (Iowa and Minnesota) were
somewhat similar to those practiced on neutral soils. Soil conservation measures and reduced
tillage were implemented early to maintain soil quality. When conservation practices ceased to
be profitable (after about 10 years), fertilizer increased to offset soil quality losses and then
decreased as it became complimentary to soil quality. Overall, leaching was reduced a little more
than 10% on these soils. As with the neutral soils, the level of nitrogen leached over the
100 years was much less under the constant stock scenario. When leaching is reduced by the
10% minimum, profits are about 25% higher than under the constant stock scenario.
Given the direct relationship between leaching and soil quality on the Missouri susceptible
soil, as well as the high cost of conservation, the best way to meet the leaching requirement was
to let soil quality degrade. The input mix fluctuated greatly throughout the 100-year period and
overall production fell compared to the constant stock scenario. However, on this soil, both
profit and total leaching over the entire period were lower.
4.4.6 Sustainability as Intergenerational Equity—Income Potential
Income potential, proxied by greatest net discounted profits over the planning period, may
also be used as a measure of intergenerational equity. The best solution to this intergenerational
equity condition was already solved in the profit maximization scenario. This scenario, where
4-11
-------
there was no minimum yield, no maximum leaching, no input tax, and no soil conservation
requirements, is intuitively the most profitable of all scenarios no matter what soils are examined.
Sustainability of any other kind usually results in some kind of economic, environmental, or
social cost.
4.5 SCENARIO WRAP-UP
Table 4A-10 provides a summary of the compatibility of the definitions on the nine soils.
In terms of the compatibility of different Sustainability requirements, no conflicts arise on stable
soils. The optimal resource management policy that satisfies the conditions for all three
definitions generates many benefits such as stable high profits, output, and soil quality. It also
allows for a stable input mix and limits negative externalities such as leaching. On neutral and
susceptible soils, however, economic, social, and environmental consequences vary both by
Sustainability definition and by soil type. Furthermore, as soil degradation worsened, so did most
of the consequences. On neutral soils, the goals of the constant consumption and
intergenerational equity (income potential) definitions may be met with the same optimal path of
soil quality degradation and input mix. The goals of the constant resource stock, reduced
leaching and intergenerational equity definitions are also met, but each with its own optimal
input mix, output, leaching, and profit.
Attaining Sustainability on susceptible soils was difficult no matter what the definition.
Susceptible soils tended to erode easily, leach, and lose their productive capabilities and
profitability. Attempting to control any one of these factors (such as maintaining soil quality) led
to negative impacts elsewhere (in this case, in profits and fluctuations in input demand).
No optimal mix of added inputs and soil quality was found that could even attain the conditions
for the constant consumption definition of Sustainability on two soils. The conditions of other
definitions could be met with one exception (i.e., the two means to attain intergenerational equity
on the Missouri susceptible soil were compatible).
4-12
-------
4.5.1 Observations About Reversibility and Uncertainty
In the above scenario, soil quality on the stable and neutral soils reached a steady state over
the 100-year planning period. Of concern, however, is the recognition that conservation
measures (such as no till practices, residue management, and terracing) could be implemented to
stabilize the level of soil quality above its natural steady state of reversibility and uncertainty.
The same possibilities do not hold for the susceptible soil. As shown in Figure 4-1, this
soil erodes easily and cannot attain a steady state when continuously cropped for 100 years.
However, as long as the endowment of soil quality is high, soil conservation measures, if
undertaken immediately, may greatly slow degradation (i.e., elongate the shape of the
degradation curve) and help minimize unforeseen circumstances. These conservation practices
cannot slow this process forever. As shown in Figure 4-2, there is some level of soil quality
below which even conservation practices cannot slow degradation. It is at this point that
irreversibility becomes a reality. Therefore, in order to maintain quality of these soils, other
types of conservation practices, such as set asides in grass cover, may be needed. However, this
removes, at least temporarily, this land from the production process.
.80
>,.72
-^
"(5
3
O
"o
03
Panel 1
Stable Soil
£• .76
"(5 .66
^
O
'o
0)
Panel 2
Neutral Soil
.80
v
^Xs*^^_ ~ .69
^^***«-^ CD
13
0
"5.25
-------
High Initial
Endowment of Soil
Quality
Lower Initial
Endowment of Soil
Quality
CD
3
O
'o
CO
Time
t
t+x
Soil Conservation Measures
Slow Erosion Considerably
£
CD
O
"o
CO
Time
Conservation Measures
Virtually Ineffective in
Slowing Erosion
Without Soil Conservation With Soil Conservation
Figure 4-2. The impact of soil conservation on soil quality reversibility on susceptible
soils.
4-14
-------
APPENDIX 4A
TABLES FOR CHAPTER 4
4A-1
-------
TABLE 4A-1. SOIL AND MANAGEMENT FOR SIMULATION MODEL SCENARIOS
Region
Iowa
Missouri
Minnesota
Soil Type
Stable Neutral Susceptible
Tama Dinsdale Nordness
Haymond Mexico Hartville
Port Kenyon Rockton
Byron
Tillage Machinery3
Conventional
Tillage Pesticide
Tandem Disk; Atrazine
Field and row Lasso
cultivators Furadan
Tandem Disk; Atrazine
Field and row Lasso
cultivators Furadan
Moldboard Banvel
plow; Field Dual
and row
cultivators
Conservation
Tillage Pesticide
Field and Atrazine
row Lasso
cultivators Furadan
Field and Atrazine
row Lasso
cultivators Furadan
Chisel plow; Banvel
Field and Dual
row
cultivators
No Till
Tillage Pesticide0
None Atrazine
Lasso
Furadan
None Atrazine
Lasso
Furadan
None Banvel
Dual 2,4-D
Roundup
Fertilizer11 (pounds per acre)
Low Medium High
50 100 150
50 100 150
50 100 150
aDoes not include machinery common to all practices such as pesticide and fertilizer applicators or combines.
bActual pounds of nitrogen applied at low, medium, and high levels.
'Atrazine levels in Missouri and Minnesota increased under no-till practices compared to levels used under conventional and conservation practices.
-------
TABLE 4A-2. SIMULATED SOIL QUALITY OVER 100 YEARS FOR
THREE TILLAGE LEVELS
Region
Iowa
Missouri
Minnesota
Soil Type
Stable
Neutral
Susceptible
Stable
Neutral
Susceptible
Stable
Neutral
Susceptible
Soil Quality Index
Conventional
High Low
0.80 0.73
0.80 0.66
0.79 0.20
0.80 0.72
0.80 0.66
0.78 0.19
0.80 0.71
0.80 0.64
0.79 0.07
Conservation
High Low
0.80 0.77
0.80 0.68
0.79 0.33
0.80 0.79
0.80 0.67
0.78 0.36
0.80 0.78
0.80 0.68
0.79 0.18
No-Till
High Low
0.82 0.80
0.80 0.70
0.79 0.47
0.80 0.80
0.80 0.70
0.78 0.42
0.80 0.79
0.80 0.69
0.79 0.31
TABLE 4A-3. SIMULATED YIELDS BY STATE AND SOIL TYPE FOR A
100-YEAR SIMULATION
Region
Iowa
Missouri
Minnesota
Soil Type
Stable
Neutral
Susceptible
Stable
Neutral
Susceptible
Stable
Neutral
Susceptible
Yield (bushels per acre)
Low
100.4
92.6
63.9
105.6
94.3
46.9
103.0
94.1
26.5
High
166.7
167.2
168.5
177.0
177.0
159.0
164.7
197.4
157.3
Mean
128.9
108.2
76.8
130.0
116.9
57.3
131.0
101.8
48.0
4A-3
-------
TABLE 4A-4. REGRESSION COEFFICIENT ESTIMATES IN THE PRODUCTION FUNCTION
Soil" Type/
Location
Stable/IA
Neutral/IA
Susceptible/IA
StableVMO
Neutral/MO
Susceptible/MO
Stable/MN
Neutral/MN
Susceptible/MN
Variable Coefficients b'c>
A
-6.47
***
-5.35
***
-8.64
***
-1.11
***
2.37
***
1.91
***
-1.02
***
0.81
***
0.22
***
La
0.558
***
0.558
***
0.558
***
0.558
***
0.558
***
0.558
***
0.558
***
0.558
***
0.558
***
A
-1.69
***
-1.69
***
-1.69
***
-1.69
***
-1.69
***
-1.69
***
-1.69
***
-1.69
***
-1.69
***
^
1.115
***
1.115
***
1.115
***
1.115
***
1.115
***
1.115
***
1.115
***
1.115
***
1.115
***
Wb
-0.036
***
-0.036
***
-0.036
***
-0.036
***
-0.036
***
-0.036
***
-0.036
***
-0.036
***
-0.036
***
^
2.85
***
2.51
***
3.48
***
1.48
***
0.311
***
0.448
***
1.23
***
0.727
***
0.883
***
^
-0.03
***
-0.026
***
-0.039
***
-0.013
***
-0.0023
***
-0.005
***
-0.01
***
-0.0056
***
-0.0077
***
sva
0.146
***
0.146
***
0.146
***
0.146
***
0.146
***
0.146
***
0.146
***
0.146
***
0.146
***
SNb
-0.001
***
-0.001
***
-0.001
***
-0.001
***
-0.001
***
-0.001
***
-0.001
***
-0.001
***
-0.001
***
Pa
0.56
**
0.56
**
0.56
**
0.56
**
0.56
**
0.56
**
0.56
**
0.56
**
0.56
**
^
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
^ea
0.65
***
0.65
***
0.65
***
0.65
***
0.65
***
0.65
***
0.65
***
0.65
***
0.65
***
^e*
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
-0.316
**
'M, MO, and MW represent Iowa, Missouri, and Minnesota, respectively. A is the intercept term, L is tillage, W is precipitation, N is applied fertilizer, ,W is soil nitrogen, P is pesticide, and SQ is soil
quality.
"The production function is the transcendental form: y = ^xf'e*1*1:*:!2 e*2*2 and, therefore, there are two coefficients (a and b, respectively) assigned to each variable.
'These are the final values (after deviation from baseline values are accounted for in dummy variables) in the fixed effects model.
***Significantatthe 1% level.
"Significant at the 5% level.
*Significant at the 10% level.
-------
TABLE 4A-5. REGRESSION COEFFICIENTS IN THE SOIL QUALITY FUNCTION
Soil3 Type/Location
Stable/IA
Neutral/IA
Susceptible/IA
Stable/MO
Neutral/MO
Susceptible/MO
Stable/MN
Neutral/MN
Susceptible/MN
SQn
0.999
***
1.0265
***
0.9998
***
0.999
***
1.0265
***
1
***
0.999
***
1.0265
***
0.999
***
Variable
0
***
-0.039
***
0
***
0
***
-0.04
***
0
***
0
***
-0.04
***
0
***
Coefficient0
0
***
0
***
-0.0113
***
0
***
0
***
-0.0112
***
0
***
0
***
-0.0112
***
A-i
-0.0001
**
-0.0002
**
-0.0021
**
-0.0001
**
-0.0002
**
-0.0003
**
-0.0001
**
-0.0002
**
-0.0003
***
aIA, MO, and MN represent Iowa, Missouri, and Minnesota, respectively. SQ represents soil quality and
L represents the estimated part ofM, tillage.
bFor stable and susceptible soils, the soil quality function takes on a linear form 7 = A +Bx . The soil quality index
o
for the neutral soils is of the quadratic form y = A + bxx + b2x .
These are the final values (after deviation from baseline values are accounted for in dummy variables) in the fixed
effects model.
***Significant at the 1% level.
** Significant at the 5% level.
*Significant at the 10% level.
4A-5
-------
TABLE 4A-6. REGRESSION COEFFICIENTS IN THE SOIL NITROGEN FUNCTION
FOR ALL SOILS
Soil" Type/Location
Stable/IA
Neutral/IA
Susceptible/IA
Stable/MO
Neutral/MO
Susceptible/MO
Stable/MN
Neutral/MN
Susceptible/MN
Variable Coefficient1''0
A S3VM tfM Wt_, LCHt_, ZM 7M
1.32
***
1.32
***
1.3
***
0.283
***
-0.326
***
-0.492
***
0.393
***
0.308
***
-1.065
***
0.986
***
0.978
***
0.965
***
0.986
***
0.976
***
0.981
***
0.99
***
0.989
***
0.97
***
0.057
**
0.057
**
0.057
**
0.057
**
0.057
**
0.057
**
0.057
**
0.057
0.057
***
-0.026
-0.026
**
-0.026
-0.026
**
-0.026
-0.026
-0.026
**
-0.026
-0.026
**
-0.062
***
-0.062
***
-0.062
***
-0.062
***
-0.062
***
-0.062
***
-0.062
***
-0.062
***
-0.062
***
-0.784
**
-0.784
-0.784
**
-0.784
-0.784
**
-0.784
-0.784
-0.784
**
-0.784
***
-0.03
***
-0.029
***
-0.028
***
-0.026
***
-0.022
***
-0.02
***
-0.03
***
-0.033
***
-0.016
***
aIA, MO, and MN represent Iowa, Missouri, and Minnesota, respectively. A represents the intercept term, SN is soil
nitrogen, W is precipitation, LCH is leaching, and L is tillage.
bThe soil nitrogen function takes on a linear form y = A + btx 1..
These are the final values (after deviation from baseline values are accounted for in dummy variables).
***Significant at the 1% level.
** Significant at the 5% level.
*Significant at the 10% level.
4A-6
-------
TABLE 4A-7. REGRESSION COEFFICIENTS IN THE LEACHING FUNCTION
FOR ALL SOILS
Soil" Type/Location
Stable/IA
Neutral/IA
Susceptible/IA
Stable/MO
Neutral/MO
Susceptible/MO
Stable/MN
Neutral/MN
Susceptible/MN
A
-7.31
***
-10.02
***
-5.9
NS
-5.008
***
-5.68
***
-5.45
***
-7.56
***
-7.82
***
-5.6
***
L
0.01
*
0.01
*
0.01
*
0.01
*
0.01
*
0.01
*
0.01
*
0.01
*
0.01
*
Variable
W
0.87
***
2.38
***
0.22
***
0.807
***
0.724
***
0.692
***
1.22
***
1.33
***
0.69
***
Coefficient c
N
0.29
***
0.29
***
0.29
***
0.29
***
0.29
***
0.29
***
0.29
***
0.29
***
0.29
***
SN
0.613
***
0.618
***
0.5477
***
0.4227
***
0.623
***
0.619
***
0.5623
***
0.618
***
0.516
***
P
0.02
NSd
0.02
NS
0.02
NS
0.02
NS
0.02
NS
0.02
NS
0.02
NS
0.02
NS
0.02
NS
SQ
-1.429
**
-1.68
**
-2.004
**
0.016
**
-1.426
**
.7
**
0.0108
**
-1.495
**
-1.845
**
aIA, MO, and MN represent Iowa, Missouri, and Minnesota, respectively. A is the intercept term, L is tillage, W is
precipitation, TV is nitrogen applied, SN is soil nitrogen, P is pesticide, and SQ is soil quality.
bThe leaching function takes on a logarithmic form.
These are the final values (after deviation from baseline values are accounted for in dummy variables).
dNS indicates that the variable is not significant at the 10% level.
***Significant at the 1% level.
** Significant at the 5% level.
*Significant at the 10% level.
4A-7
-------
TABLE 4A-8. SUMMARY OF THE CONDITIONS, RESULTS, AND IMPACTS OF THREE DEFINITIONS OF
SUSTAINABILITY ON THREE STABLE SOILS
Soil
IA
MO
MN
SUSTAINABILITY SCENARIOS
Constant Consumption
Annual Condition3 Impacts'"
and Result Over Time
Condition Profit = $7,266.34
Minimum yield = 126.82 Yield rose from 140.92 to
142.85
SQ rose from 0.80 to 0.808
Result Conservation all years
Minimum yield = 140.92 Input mix steady
Maximum yield = 142.82 Leach fell from 0.68 to 0.61
Condition Profit = $7,268.27
Minimum yield = 125.05 Yield rose from 138.96 to
141.22
SQ rose from 0.80 to 0.809
Result Conservation all years
Minimum yield = 138.96 Input mix steady
Maximum yield = 141.22 Leach fell from 1.94 to 1.16
Condition Profit = $7,252.73
Minimum yield = 129.05 Yield rose from 143.38 to
145.78
SQ rose from 0.80 to 0.811
Result 100 years conservation
Minimum yield = 143.38 Input mix steady
Maximum yield = 145.78 Leach fell from 1.93 to 1.64
Constant Stock
Annual Condition Impacts
and Result Over Time
Condition Profit = $7,266.34
Full conservation every year Yield rose from 140.92 to
142.85
SQ rose from 0.80 to 0.808
Result Conservation all years
SQ rose from 0.80 to 0.808 Input mix steady
Leach fell from 0.68 to 0.61
Condition Profit = $7,268.27
Full conservation Yield rose from 138.96 to
every year 141.22
SQ rose from 0.80 to 0.809
Result Conservation all years
SQ rose from 0.80 to 0.809 Input mix steady
Leach fell from 1.94 to 1.16
Condition Profit = $7,252.73
Full conservation every year Yield rose from 143.38 to
145.78
SQ rose from 0.80 to 0.811
Result Conservation all years
SQrose from 0.80 to 0.811 Input mix steady
Leach fell from 1.93 to 1.64
Equity as Reduced Leaching
Final Condition Impacts
and Result Over Time
Condition Profit = $7,266.34
Maximum leach = 0.783 Ibs Yield rose from 140.92 to
142.85
SQ rose from 0.80 to 0.808
Result Conservation all years
Leaching fell from 0.68 to 0.61 Input mix steady
Leach fell from 0.68 to 0.61
Condition Profit = $7,268.27
Maximum leach = 1.97 Ibs Yield rose from 138.96 to
141.22
SQ rose from 0.80 to 0.809
Result Conservation all years
Leaching fell from 1.94 to 1.16 Input mix steady
Leach fell from 1.94 to 1.1 6
Condition Profit = $7,252.73
Maximum Leach = 2.007 Ibs Yield rose from 143.38 to
145.78
SQrose from 0.80 to 0.811
Result Conservation all years
Leaching fell from 1.93 to 1.64 Input mix steady
Leach fell from 1.93 to 1.64
General
Observations
The conditions
of all three
definitions
were met using
the same input
management
plan.
The conditions
of all three
definitions
were met using
the same input
management
plan.
The conditions
of all three
definitions
were met using
the same input
management
plan.
oo
"Condition states the requirement for the relevant definition of sustainability; result states whether the condition has been met and provides the relevant statistics.
""Impacts presented over time are: net discounted profit; yield trend with first and final year statistics; soil quality trend over time and first and last year statistics; number of years conservation was
implemented, whether input use was steady, had small changes over the 100 years or was volatile; leaching trend and first and last year statistics.
-------
TABLE 4A-9. SUMMARY OF THE CONDITIONS, RESULTS, AND IMPACTS OF THREE DEFINITIONS OF
SUSTAINABILITY ON THREE NEUTRAL SOILS
Soil
IA
MO
MN
SUSTAINABILITY SCENARIOS
Constant Consumption
Annual Condition3 Impacts'1
and Result Over Time
Condition Profit = $6,573 .95
Minimum yield = 120.14 Yield fell from 133.49 to
128.41
SQ fell from 0.79 to 0.687
Result 10 years conservation
Yield fell but minimum met Small input mix changes
Minimum yield = 128.41 Leach rose from 3.62 to 4.39
Maximum yield = 133.49
Condition Profit = $6,718.82
Minimum yield = 1 19.97 Yield down from 133.30 to
126.47
SQ down from 0.79 to 0.716
Result 19 years conservation
Yield fell but minimum met Small input mix changes
Minimum yield = 126.47 Leach rose from 2.75 to 2.96
Maximum yield = 133.30
Condition Profit = $6,75 1 .25,
Minimum yield = 121.97 Yield fell from 135.51 to
127.06
SQ fell from 0.79 to 0.672
Result 5 years conservation
Yield fell but minimum met Small input mix changes
Minimum yield = 127.06 Leach rose from 1 .83 to 2.79
Maximum yield = 135.51
Constant Stock
Annual Condition Impacts
and Result Over Time
Condition Profit = $6,300.79
Full conservation every year Yield rose from 134.18 to
139.79
SQ rose from 0.80 to 0.808
Result 100 years conservation
SQ rose from 0.79 to 0.805 Small input mix changes
Leach fell from 3.62 to 2.38
Condition Profit = $6,339.64
Full conservation every year Yield rose from 133.34 to
140.57
SQ rose from 0.790 to 0.808
Result 100 years conservation
SQ rose from 0.790 to Small input mix changes
°'808 Leach fell from 2.77 to 2.04
Condition Profit = $5,850.53
Full conservation every year Yield rose from 135.54 to
140.19
SQ rose from 0.79 to 0.808
Result 100 years conservation
SQ rose from 0.79 to 0.808 Small input mix changes
Leach fell from 1.83 to 1.60
Equity as Reduced Leaching
Final Condition Impacts
and Result Over Time
Condition Profit = $6,555.19
Maximum leach = 4.0 Ibs. Yield fell from 133.30 to
125.00
SQ fell from 0.79 to 0.699
Result 13 years conservation
Condition met but leach Input mix volatile
rose from 3 .62 to 3 .99 T , ,- ~,r^.
Leach rose from 3.62 to
3.99
Condition Profit = $6,608.62
Maximum leach = Yield fell from 133.30 to
2.943 Ibs. 125.47
SQ fell from 0.79 to 0.72
Result 24 years conservation
Condition met but leach Input mix volatile
rose from 2.77 to 2.94
Condition Profit = $6,048.32
Maximum leach = Yield fell from 135.51 to
2.54 Ibs. 126.32
SQ fell from 0.79 to 0.685
Result 1 1 years conservation
Condition met but leach Input mix volatile
rose from 1.83 to 2.51 T , ,, . 00 .
Leach rose trom 1.83 to
2.51
General
Observations
The conditions of
the definitions were
met with different
management plans.
The conditions of
the definitions were
met with different
management plans.
The conditions of
the definitions were
met with different
management plans.
•Condition states the requirement for the relevant definition of sustainability; result states whether the condition has been met and provides the relevant statistics.
""Impacts presented over time are: net discounted profit; yield trend with first and final year statistics; soil quality trend over time and first and last year statistics; number of years conservation was implemented,
whether input use was steady, had small changes over the 100 years or was volatile; leaching trend and first and last year statistics.
-------
TABLE 4A-10. SUMMARY OF THE CONDITIONS, RESULTS, AND IMPACTS OF THREE DEFINITIONS OF
SUSTAINABILITY ON THREE SUSCEPTIBLE SOILS
Soil
IA
MO
MN
SUSTAINABILITY SCENARIOS
Constant Consumption
Annual Condition3 Impacts'1
and Result Over Time
Condition No mix of inputs could
Minimum yield = 108.14 maintain annual outPut
at 108. 14
Result
Condition not met
Condition No mix of inputs could
maintain annual output
Minimum yield = 109.15 a^ JQ^ jj
Result
Condition not met
Condition Profit = $4,309.72
Minimum yield = 1 10.42 Yield fell from 122.71 to
11 0.47 over time
SQ fell from 0.79 to 0.601
70 years conservation
Result Small input mix changes
Yield fell but minimum met Leach rose from 1 .73 to
9 o/r
Minimum yield = 1 10.47
Maximum yield = 122.71
Constant Stock
Annual Condition Impacts
and Result Over Time
Condition Profit = $3,790.37
Full conservation Yield fell from 120.15 to
every year 100.14
SQ fell from 0.789 to 0.633
Result 100 years conservation
SQ fell from .789 Small input mix changes
t0 '633 Leach rose from 1 .37 to 2.97
Condition Profit = $4,169.17
Full conservation Yield fell from 121.30 to
every year 103.07
SQ fell from 0.79 to 0.58
Result 100 yrs conservation
SQ fell from 0 .790 Input mix volatile
to 0.58
Leach fell from 1.66 to 1.09
Condition Profit = $3,435.17
Full conservation Yield fell from 122.69 to
every year 109.10
SQ fell from 0.79 to 0.672
100 yrs conservation
Result Small input mix changes
SQ fell from 0.79 Leach fell from 1 .73 to 2.02
to 0.672
Intergenerational Equity
Final Condition Impacts
and Result Over Time
Condition Profit = $4,907.27
Maximum leach = 8.757 Ibs. Yield fell from 120.14 to
66.32
SQ fell from 0.79 to 0.260
Result 10 years conservation
Condition met but leach rose Inputs volatile
from 1.37 to 8.68 T , , -,„ „ ™
Leach rose 1.37-8.68
Condition Profit = $4,952.40
Maximum leach= 1 .491bs Yield fell from 1 16.79 to
60.03
SQ fell from 0.79 to 0.7 15
Result 0 years conservation
Leaching fell from 1 .49 to 0.58 Input mix volatile
Leach fell from 1.49 to 0.58
Condition Profit = $4,695 .47,
Maximum leach = 10.66 Ibs. Yield fell from 122.67 to
60.55
SQ fell from 0.79 to 0.258
1 1 years conservation
Result Input mix volatile
Condition met but leach rose Leach rose from 1 .73 to
from 1.73 to 10.36 10.36
General
Observations
Best minimum yield
attainable is met
with constant stock
conditions (83%
instead of 90%).
Best minimum yield
attainable is met
with constant stock
conditions (85%
instead of 90%).
Best minimum yield
attainable is met
with constant stock
conditions (85%
instead of 90%).
Condition states the requirement for the relevant definition of sustainability; result states whether the condition has been met and provides the relevant statistics.
Impacts presented over time are: net discounted profit; yield trend with first and final year statistics; soil quality trend over time and first and last year statistics; number of years conservation was
implemented, whether input use was steady, had small changes over the 100 years or was volatile; leaching trend and first and last year statistics.
-------
TABLE 4A-11. COMPATIBILITY OF SUSTAINABILITY DEFINITIONS
ON DIFFERENT SOILS
Soilb Type/Location
Stable/IA
Stable/MO
Stable/MN
Neutral/IA
Neutral/MO
Neutral/MN
Susceptible/IA
Susceptible/Mo
Sustainability Definitions Attained
with the Same Soil Management Plana
Constant
Consumption
X
X
X
X
X
X
N/AC
N/AC
Constant
Soil Stock
X
X
X
-
-
-
-
-
Intergenerati onal
Leaching
X
X
X
-
-
-
-
-
Equity
Income
X
X
X
X
X
X
-
-
aAn x is used to indicate all definitions that are compatible on the particular soil.
bIA, MO, and MN represent Iowa, Missouri, and Minnesota, respectively.
°On the Iowa and Missouri susceptible soils, the conditions for the constant consumption definition of
sustainability could not be achieved.
4 A-11
-------
-------
5. CONCLUSIONS
Assessment of environmental condition is critical to wise management and policy
decisions. However, it is difficult when there is so much dimensionality in objectives and
complexity in defining, measuring, monitoring, and predicting environmental outcomes.
This research proposes a general method to examine the sustainability of resource
management. For a unique production input, the endowment of a natural resource may be
modeled as an index of quality. This index, consisting of the most important identifying
characteristics of the resource, may be placed into a production setting where the benefits of
economic use and preservation may be compared.
The methods used for soil conservation here provide one approach to assessing
sustainability. Basic findings are summarized below. For simplicity, soil had one objective:
crop production. This allowed an effective model, although other objectives such as leaching
and soil quality were accounted for. Extrapolating this process to another environmental good,
such as forest health, would require expanding to multiple outputs and would be more difficult to
model. Therefore, the concepts that can be easily demonstrated by this relatively simple (but still
very difficult) example can serve as a guide for how more complex systems might function and
for future models with an expanded scope.
5.1 SELECTED FINDINGS
• As shown in the above scenarios, different definitions of sustainability have different impacts
on soils. Management practices that fulfill the requirements (constant output, constant resource
stock, and intergenerational equity) of one definition will not necessarily fulfill the
requirements of another. Besides yielding different results across definitions, results varied by
soil. On a stable soil, the optimal profit making strategy is the same as the constant
consumption and constant resource stock; public intervention is not necessary and societal and
private conflicts over sustainability are avoided. However, the pursuit of profits on a
susceptible soil does not yield a constant output, nor does the constant output assure a constant
5-1
-------
resource stock, and leaching also requires a different management scheme from any of the
others.
Soil conservation measures were implemented over the entire 100-year period in order to meet
the conditions for the different definitions of sustainability on all stable soils. Therefore, one
may conclude that a soil conservation policy would meet sustainability objectives on stable
soils. However, policies are not needed since conservation is already the most profitable
management scheme. Neutral and susceptible soils prove more of a challenge, since the most
profitable management does not always satisfy the other versions of sustainability.
All conservation measures were implemented on neutral and susceptible soils only when
sustainability was defined as constant resource stock. When the condition for sustainability is
constant consumption or intergenerational equity, conservation measures were used
sporadically throughout the 100-year period, and in some cases, not at all. Therefore, in
general, one may conclude that soil conservation measures do not meet sustainability objectives
on neutral and susceptible soils.
Reversibility is not a problem on stable soils, since it is already in the economic interest of the
farmer to preserve soil quality. Neutral soils may be preserved longer, thus averting the
problem of reversibility, but may also fall into the same trap as susceptible soils, depending on
conservation costs and on whether it is closer to a stable or susceptible soil.
Reversibility is not possible on some soils once a critical level has been surpassed. In this case,
susceptible soils with an initial soil quality level below .8 (as is the case for many soils that
have already been in production for years) will continue to be mined for their quality until their
productivity is greatly reduced. However, when the initial endowment is above .8, conservation
measures can greatly reduce the rate of degradation. The smaller the endowment of soil
quality, the less effective and less profitable conservation measures are in preserving it.
5.2 FURTHER RESEARCH OPPORTUNITIES
This research is the first step in uncovering the relationship between the path of change for
a natural resource and various definitions of sustainability. This concept is expected to hold
across a wide range of soils and crops within the United States. However, further research is
needed to support this claim. Management data for 17 additional crops on hundreds of soils
5-2
-------
across 63 regions, soon to be released by the National Resources Conservation Services, can be
utilized in a sensitivity analysis to examine the extent to which these relationships hold over
other crops and other soils.
In addition, these results may be contingent on various assumptions of the research. The
following assumptions could be examined in the future.
• The Discount Rate—Sensitivity analysis could be used to determine the rate which is needed
for all objectives of sustainability to be met on one or all soils.
• Relevant Time Frame—Further study is needed to best determine the appropriate time frame
for managing each resource in a sustainable manner.
• Clear Definitions—There is much discussion among those who support a particular definition
as to its exact meaning. Research could help determine the degree of flexibility within each
definition so that the same management plan remains acceptable.
• Technological Advancements—Inclusion of technological advancements could be modeled to
improve the results of this study.
• Conservation Cost Share—Sensitivity analysis could help determine what percentage of
conservation costs should be carried by society and by the producer in order to sustain a soil
resources.
• Improvements to Soil Quality Index—This is the first soil quality index used for productivity
purposes to include a sufficiency for soil organic matter. Further research could help identify
what other purposes this index may be applied to.
5-3
-------
-------
6. REFERENCES
Acton, D. F.; Gregorich, L. J. (1995) Understanding soil health. In: Acton, D. F.; Gregorich, L. J. eds. The health of
our soils: toward sustainable agriculture in Canada. Ottawa, Ontario, Canada: Center for Land and Biological
Resources Research, Agriculture and Agri-Food Canada; pp. 1-5; publication 1906/E.
Baumol, W. J.; Gates, W. E. (1990) The theory of environmental policy. New York, NY: Cambridge University
Press.
Beckerman, W. (1992) Economic growth and the environment. Whose growth? Whose environment? World Dev.
20: 481-496.
Bellon, M. R. (1995) Farmers' knowledge and sustainable agroecosystem management: an operational definition and
an example from Chiapas, Mexico. Hum. Org. 54: 263-272.
Bishop, R. (1978) Endangered species and uncertainty: the economics of a safe minimum standard. Am. J. Agric.
Econ. 60: 10-13.
Boulding, K. (1973) The economics of the coming of spaceship earth. In: Daly, H., ed. Toward a steady state
economy. San Francisco, CA: W. H. Freeman Press.
Bowman, R.; Petersen, M. (1996) Soil organic matter levels in the central Great Plains. Department of Agriculture,
Agricultural Research Service and Natural Resource Conservation Service; conservation tillage fact sheet
no. 1-96.
Bowman, R. A.; Reeder, J. D.; Schuman, G. E. (1989) Evaluation of selected soil physical, chemical and biological
parameters as indicators of soil productivity. In: Stewart, J. W. B., ed. Soil quality in semiarid agriculture:
proceedings of an international conference as part of the first global agricultural technology exposition; June;
Saskatoon, Saskatchewan, Canada.
Brooke, A.; Kendrick, D.; Meeraus, A. (1992) GAMS: a user's guide. Redwood City, CA: Scientific Press.
Buckman, H. O.; Brady, N. C. (1960) The nature and properties of soils: a college text of edaphology. 6th ed.
New York, NY: The Macmillan Company.
Ceolla, D. (1997) Personal communication. USDA Natural Resource Conservation Service.
Cernea, M. (1993) The sociologist's approach to sustainable development. Finance Dev. 30: 11-13.
Clark, J. S.; Furtan, W. H. (1983) An economic model of soil conservation-depletion. J. Environ. Econ. Manage.
10: 356-370.
Daly, H. (1995) On Wilfred Beckerman's critique of sustainable development. Environ. Values 4: 49-55.
Dixit, A.; Hammond, P.; Hoel, M. (1980) On Hartwick's rule for regular maximin paths of capital accumulation and
resource depletion. Rev. Econ. Stud. 47: 551-556.
Doran, J. W. Parkin, T. (1994) Defining and assessing soil quality. In: Doran, J. W.; Coleman, D. F.; Bezdicek,
D. F.; Stewart, B. A., eds. Defining soil quality for a sustainable environment. Madison, WI: American
Society of Agronomy, Inc.; Soil Science Society of America, Inc. special publication no. 35.
6-1
-------
Doran, J. W.; Coleman, D. C.; Bezdicek, D. F.; Stewart, B. A. (1994) Defining soil quality for a sustainable
environment: proceedings of a symposium sponsored by the Soil Science Society of America, American
Society of Agronomy, and the North Central Region Committee on Soil Organic Matter; November 1992;
Minneapolis, MN. Madison, WI: Soil Science Society of America, Inc.; American Society of Agronomy,
Inc.; SSSA special publication no. 35.
Doran, J. W.; Sarrantonio, M.; Liebig, M. A. (1996) Soil health and sustainability. In: Sparks, D. L., ed. Advances
in agronomy. San Diego, CA: Academic Press, Inc.; pp. 1-54.
DowElanco. (1994) What makes agriculture sustainable? The bottom line on agrichemical issues. Indianapolis, IN:
Sustainable Agriculture Issue.
Dyke, P. T.; Heady, E. (1985) Assessment of soil erosion and crop productivity with economic models. In: Follett,
R. F.; Stewart, B. A., eds. Soil erosion and crop productivity. Madison, WI: American Society of Agronomy,
Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc.; 106-119.
Gold, M. (1994) Sustainable agriculture: definitions and terms. Beltsville, MD: U.S. Department of Agriculture;
special reference brief no. 94-05.
Hartwick, J. M. (1977) Intergenerational equity and the investing of rents from exhaustible resources. Am. Econ.
Rev. 67: 972-974.
Hartwick, J. (1978) Substitution among exhaustible resources and intergenerational equity. Rev. Econ. Stud.
XLV-2: 347-354.
Helmers, G.; Hoag, D. (1993) Sustainable agriculture. In: Hallberg, M. C.; Spitze, R. F.; Ray, D. E., eds. Food,
agriculture, and rural policy into the twenty-first century. Boulder, CO: Westview Press.
Hilgard, E. W. (1892) Agriculture weather bureau bulletin. Volume 3. Washington, DC: U.S. Department of
Agriculture; pp. 1-59.
Hoag, D. (1997) The intertemporal impact of soil erosion on non-uniform soil profiles: a new direction in analyzing
erosion impacts. Agric. Systems: forthcoming.
Hsiao, C. (1986) Analysis of panel data. New York, NY: Cambridge University Press. (Econometric Society
monographs no. 11).
Jansson, A. M.; Hammer, M.; Folke, C.; Costanza, R., eds. (1994) Investing in natural capital: the ecological
economics approach to sustainability. Washington, DC: Island Press.
Johnson, M. G.; Lammers, D. A.; Anderson, C. P.; Rygiewcz, P. T.; Stern, J. S. (1992) Sustaining soil quality by
protecting the soil resource. In: Proceedings of the soil quality standards symposium; October 1990; San
Antonio, TX. Washington, DC: U.S. Department of Agriculture; watershed and air management report no.
WO-WSA-2.
Karlen, D. L.; Mausbach, M. J.; Doran, J. W.; Kine, R. G.; Harris, R. F.; Schuman, G. E. (1997) Soil quality:
a concept, definition and framework for evaluation (a guest editorial). Soil Sci. Soc. Am. J. 61: 4-10.
Kennedy, A. C.; Papendick, R. I. (1995) Microbial characteristics of soil quality. J. Soil Water Conserv.
50: 243-248.
Kiniry, L. N.; Scrivner, C. L.; Keener, M. E. (1983) A soil productivity index based upon predicted water depletion
and root growth. Columbia, MO: University of Missouri-Columbia, College of Agriculture; agricultural
experiment station research bulletin no. 1051.
6-2
-------
Larson, W. E.; Pierce, F. J. (1991) Conservation and enhancement of soil quality. In: Evaluation for sustainable
management in the developing world: summaries of papers [from an] international workshop; September;
Chiang Ral, Thailand. Bangkok, Thailand: Board for Soil Resources and Management; IBSRAM Proc.
12(2).
Larson, W. E.; Pierce, F. J. (1994) The dynamics of soil quality as a measure of sustainable management.
In: Doran, J. W.; Coleman, D. C.; Bezdicek, D. F.; Stewart, B. A., eds. Defining soil quality for a
sustainable environment. Madison, WI: American Society of Agronomy, Inc.; Soil Science Society of
America special publication no. 35.
Lesser, J.; Zerbe, R. O., Jr. (1993) What can economic analysis contribute to the sustainability debate? Contemp.
Econ. Policy 13: 88-100.
Maddala, G. S. (1993) The econometrics of panel data. Volumes 1-2. Brookfield, VT: Ashgate.
Marten, G. (1988) Productivity, stability, sustainability, equitability and autonomy as properties for agroecosystem
assessment. Agric. Syst. 26: 291-316.
McConnell, K. (1983) An economic model of soil conservation. Am. J. Agric. Econ. 65: 83-89.
Mitchell, G.; Griggs, R. H.; Benson, V.; Williams, J. (1995) The EPIC model: environmental policy integrated
climate (version 5300). Temple TX: Texas Agricultural Experiment Station, U.S. Department of Agriculture
Agricultural Research Service and Natural Resource Conservation Service.
Munasinghe, M. (1993) The economist's approach to sustainable development. Finance Dev. 30: 16-19.
National Research Council. (1993) Soil and water quality: an agenda for agriculture. Washington, DC: National
Academy Press.
Natural Resources Conservation Service. (1995) Soil quality. Washington, DC: U.S. Department of Agriculture;
RCA/issue brief 5.
Olson, L. (1943) Columella and the beginning of soil science. Agric. Hist. 17: 65-72.
Olson, K. R.; Lai, R.; Norton, L. D. (1994) Evaluation of methods to study soil erosion-productivity relationships.
J. Soil Water Conserv. 49: 586-590.
Page, J. (1977) Conservation and economic efficiency: an approach to materials policy. Baltimore, MD: Johns
Hopkins University Press.
Parr, J. F.; Papendick, R. L; Hornick, S. B.; Meyer, R. E. (1992) Soil quality: attributes and relationship to
alternative agriculture. Am. J. Altern. Agric. 7: 5-11.
Pearce, D.; Atkinson, G. (1993) Capital theory and the measurement of sustainable development. Ecol. Econ.
8: 103-108.
Pearce, D.; Atkinson, G. (1995) Measuring sustainable development. In: Bromley, D., ed. The handbook of
environmental economics. Cambridge, MA: Blackwell Publishers; pp. 166-181.
Pearce, D. W.; Warford, J. J. (1996) World without end economics: environment and sustainable development.
2nd ed. Oxford, United Kingdom: Oxford University Press for the World Bank.
Pezzey, J. (1992) Sustainability: an interdisciplinary guide. Environ. Values 1: 321-362.
6-3
-------
Pierce, F. I; Larson, W. E.; Dowdy, R. H.; Graham, W. A. P. (1983) Productivity of soils: assessing long-term
changes due to erosion. J. Soil Water Conserv. 38: 39-44.
Fieri, C. (1995) Long term experiments on soil management in semi-arid Francophone Africa. In: Lai, R.; Stewart,
B. A., eds. Soil management experimental basis for sustainability and environmental quality. Boca Raton,
FL: Lewis Publishers; pp. 228-266.
Popp, J. H. (1997) In search of sustainability. Economic, social and environmental consequences of natural resource
management: a case study of soil conservation in the United States [dissertation]. Fort Collins, CO: Colorado
State University.
Rees, C. (1993) An ecologist's approach to sustainable development. Finance Dev. 30: 14-15.
Saliba, B. C. (1985) Soil productivity and farmers' erosion control incentives—a dynamic modeling approach. West.
J. Agric. Econ. 10: 354-364.
Schuh, G. E.; Archibald, S. (1993) A methodological framework for the integration of environmental and
sustainable development issues into agricultural planning and policy analysis in developing countries.
Presented at: Food and Agricultural Organization of the United Nations seminar; Rome, Italy.
Segarra, E.; Taylor, D. B. (1987) Farm level dynamic analysis of soil conservation: an application to the piedmont
area of Virginia. South. J. Agric. Econ. 19: 61-73.
Solow, R. (1974a) Intergenerational equity and exhaustible resources. Rev. Econ. Stud.: 29-45.
Solow, R. (1974b) The economics of resources or the resources of economics. Am. Econ. Rev. 64(2): 1-13.
Solow, R. (1991) Growth theory. In: Greenaway, D.; Bleamey, M; Stewart, I., eds. Companion to economic
thought. New York, NY: Rutledge Press; pp. 393-415.
Tammons, R. (1997) Personal communication. Columbus, MO: U.S. Department of Agriculture, Natural Resource
Conservation Service.
U.S. Department of Agriculture. (1980) Report and recommendations on organic farming. Beltsville, MD: U.S.
Department of Agriculture, Biological Waste Management and Organic Resources Laboratory.
U.S. Department of Agriculture. (1990-1995) Cropping practices survey. Unpublished data. Washington, DC:
Economic Research Service.
U.S. Department of Agriculture. (1994) Agricultural statistics 1994. Washington, DC: U.S. Government Printing
Office.
U.S. Department of Agriculture. (1996) Agricultural prices 1995 summary. Washington, DC: National Agricultural
Statistics Service. Available online at:
http ://usda. mannlib .Cornell. edu/reports/nassr/price/zap-bb/agricultural_prices_annual_summary_07.16.96.
U.S. Department of Agriculture. (1997) Agricultural prices 1996 summary. Washington, DC: National Agricultural
Statistics Service. Available online at:
http://usda.mannlib.cornell.edu/reports/nassr/price/zap-bb/agricultural_prices_annual_summary_07.23.97.
Vickner, S. (1997) Personal communication. Colorado State University.
Walker, D. J.; Young, D. L. (1986) The effect of technical progress on erosion damage and economic incentives for
soil conservation. Land Econ. 62: 83-93.
6-4
-------
Warkentin, B. P. (1995) The changing concept of soil quality. J. Soil Water Conserv. 50: 226-228.
World Commission on Environment and Development. (1987) Our common future. Oxford, United Kingdom:
Oxford University Press.
6-5
------- |