Soil Stresses, Quality and Care Proceedings from NJF seminar 310 Ås, April 10-12 2000

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Susanne Elmholt, Bo Stenberg, Arne Grønlund & Visa Nuutinen

Department of Crop Physiology and Soil Science P. O. Box 50

DK-8830 Tjele

Soil Stresses, Quality and Care

Proceedings from NJF seminar 310 Ås, April 10-12 2000

DIAS report Plant Production no. 38 • December 2000

Publisher: Danish Institute of Agricultural Sciences Tel. +45 89 99 19 00 Research Centre Foulum Fax +45 89 99 19 19 P.O. Box 50

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NJF-seminar Soil Stresses, Quality and Care

Different people understand differently the word soil. The soil can be looked upon as a body of nature and a part of the landscape. To many people soil is the substrate for plant growth and a prerequisite for food production and wealth. A third and perhaps growingly important view is soil as the physical ground for housings, roads and industry.

Soil is important to the whole society, not only for the agricultural sector. Soil has important ecological functions as it interacts with the dead bedrock, the atmosphere, the water, and the living organisms. Important functions are:

Biomass producer and transformer Geomembrane, filter and buffer Habitat for living organisms Raw material and building ground Cultural heritage

Even if these important roles of soil are probably widely known, the world's soil resources are degraded at an alarming rate. This is well documented by for instance the World Resources Institute (http://www.nhq.nrcs.usda.gov/WSR/).

We need to care for our prime agricultural soils, soils which provide the green in urban areas, as well as soil resources in natural landscapes.

Soil and agricultural scientists have detailed knowledge of specific functions and processes in soil. Seminar topics in NJF’s Section 1 (Soils and fertilisers) in the recent years show that soil biology and ecology have been added to the previous production-related research such as tillage and fertilisation. We are now prepared to study the whole soil and we have to show that our knowledge concerns the society and not only the farmers and gardeners. We believe that the concept of soil quality will help us to improve our communication about soils and soil use. Politicians, authorities, and farmers need a soil quality classification that makes the choices between different soil uses and managements based on soil science. Such classifications have been used in agriculture for many years. However, it is necessary to develop them and relate the classification systems and parameters used to present-day problems and technology. It is also important to use in communication modern language, as less and less people have hands-on experience with soils in an agricultural context.

This seminar intended to elucidate and discuss the present knowledge and research that can help us assess the quality of soils and to identify key properties which may be used as indicators of soil health. The seminar showed that we possess the knowledge, and that we have a good base for the further work with the soil quality concept and its practical use.

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On behalf of the Nordic Association of Agricultural Scientists I will thank the organising committee for a well planned and conducted seminar.

Svein Skøien, Chairman, NJF Section Soil and Fertilisers

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The land quality concept as a means to improve communications about soils

J. Bouma

Member Scientific Council for Government Policy, the Hague and Professor of Soils, Lab.

Soil Science and Geology, Wageningen University, the NETHERLANDS E-mail: Johan.Bouma@BodLan.BenG.WAU.NL

Summary

Soil expertise is not communicated effectively enough to the public at large, nor to planners and politicians. Use of the land quality (LQ) concept and emphasis on soil behavior as a function of management are expected to be helpful in improving communications. Existing definitions of “soil quality” and “sustainable land management” are analyzed to derive a procedure for defining LQ indicators of sustainable land management. Land- rather than soil qualities are considered to reflect the impact of the climate and the landscape on soil behavior.

Land quality is different for different types of land use and attention is arbitrarily confined here to agriculture. Simulation modeling of crop growth and solute fluxes is used to define land quality (LQ) as the ratio between yield and potential (or water-limited) yield (x 100), which defines a “yield gap LQ”. For soils with nutrient mining, a nutrient-depletion LQ is defined. The actual agro-ecological condition and its potential, both expressed by LQ ‘s for a given piece of land, is considered here as independent input into broader land-use discussions which tend to be dominated by socio-economic and political considerations. Agro-ecological considerations should not be held hostage to actual socio-economic and political

considerations, which may change in the near future while LQ’s have a much more permanent character. The proposed yield-gap LQ reflects yields and risks of production as simulations are made for many years, and soil and water quality associated with the production process is taken into account. Yields and pollution risks are expressed for Dutch conditions in terms of the probability that groundwater is polluted with nitrates. The proposed procedure requires the selection of acceptable production and pollution risks, before a LQ value can be obtained.

Existing definitions implicitly emphasize the field and farm level. However, LQ is also important at the regional and higher level, which, so far, has received little attention. Then, again, an agro-ecological approach is suggested when defining LQ’s as input into the planning process, emphasizing not only an independent assessment of the potential for agricultural production, but of nature conservation as well.

Keywords:agro-ecosystems, nitrate pollution, risk assessment, potential crop yields

Introduction

The condition of soils is generally not a prime concern when environmental problems are discussed in society. Global climate change due to greenhouse gasses, the “ozon hole”, solid and liquid waste disposal and, increasingly, water quality and worldwide water shortages have been more successful in catching theimagination of the public at large. These, of course, are

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worthy objectives of concern and study, but serious concerns about the environmental degradation of soils resulting from intensive forms of land use exceeding the ecological carrying capacity have widely been reported but don’t appear to lead to alarm or action (e. g.

Oldeman, 1994). Approximately 15% of the total land surface of the world is degraded as a result of adverse human action. Worldwide, about 38% of the agricultural land is affected by significant human-induced soil degradation, of which 56% is caused by water erosion, 28%

by wind erosion and 7% by nutrient decline. Substantial areas of prime agricultural land are, without much opposition, permanently taken out of production when used for city expansion and construction of shopping malls or roads. How can this relative indifference be explained?

Without making attempts to speculate about the psychology of public awareness, we may state that the soil science profession has been less than successful in communicating its expertise effectively to the public, to regulators and to politicians. In this paper I will attempt to briefly analyze this problem. Of course, the challenge is to improve our efforts to show that soils are important. One way to do so is to develop indicators that can quickly express the value or quality of soils. Such indicators are crucial in the modern world where attention spans are very short and where attention is increasingly attuned to attractive “ soundbites”.

Soil or land quality could be an ideal indicator as will be further explored in this paper. Our colleagues in economics and sociology have used attractive indicators for years (the Gross National Product may serve as an arbitrary example here). Such indicators have so far not been defined for soils (Pieri et al., 1995).

When discussing soil quality indicators in the context of achieving an effective external communication, we must link soils and their properties with functioning and use. This not only relates to agriculture, but also to nature areas and recreational facilities. Use patterns and management practices are only acceptable when they are sustainable in the long run. We will therefore discuss the soil quality aspect in the context of sustainable land use and

management.

Sustainable land management has been discussed widely within soil science and agronomy and guidelines have been proposed by FAO (1993). These guidelines list four criteria for sustainable land management relating to agriculture: (1) production should be maintained; (2) risks should not increase; (3) quality of soil and water should be maintained, and (4) systems should be economically feasible and socially acceptable. Soil quality is part of this definition and this term has, in turn, been defined in another context as: “the fitness of a specific kind of soil to function within its capacity and within natural and managed ecosystem boundaries, to sustain plant and animal productivity, maintain air and water quality and support human health and habitation” (Karlen et al, 1997). Even though it is tempting to discuss these

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management; (3) soil quality and soil quality indicators, and (4) use of the quality concept to improve communication. The focus will be on the field level, the usual area of activity of farmers. However, the quality concept is also important at other spatial scales, which have to be considered when dealing with policy issues in regions or countries. In this broader context, soil quality has not yet been analyzed and this issue will therefore also be explored in this paper.

Creating awareness about soils

Even though many people have a strong affinity with “ the land” they live on, it is a rather abstract affinity. Soils occur in darkness below the surface of the earth and, in contrast to weather and water, are not directly visible and cannot be experienced by the senses unless exposed in a hole or in an excavation. The vertical succession of layers, which is

characteristic for soils, can be shown in monoliths and can be displayed on walls of offices, schools and other buildings. In the USA, every State of the Union has a “ State Soil”, just like a “State Bird”, “State Animal” etc. The vertical succession of layers in any soil is often quite beautiful, certainly when a wide array of colors is exposed as in podzols and gley soils.

Successful exhibitions of soil monoliths have been held in art galleries! But soils represent more than just pretty pictures! To really understand the significance of soils, a functional approach is needed which demonstrates functioning within a landscape context as governed by interacting physical, chemical and biological processes. More specifically, functioning relates to supplying water and nutrients to agricultural crops and various types of natural vegetation, purification of percolating wastewater and carrying loads. All these functions taken together determine the value of soils for society.

How can the functioning of soils be characterized? Yields of crops are often known, as are types of natural vegetation that occur on different soil types. Chemical, physical and hydrological properties are often known to a certain extent but often in a rather qualitative, descriptive and static manner. How can we catch the effects of interacting physical, chemical and biological processes, which determine the dynamic character of soils and their

functioning in ecosystems?

Many monitoring techniques are available now to measure varying soil properties over time.

Use of transducers, recorders and proximal and remote sensing techniques allows us to “ take the pulse of mother earth” (e. g. Bouma, 1999). Such techniques are, however, costly and widespread application is therefore unlikely. The advance of computer simulation of soil processes has, however, proved to be quite helpful in documenting effects of soil processes and the impact of man. (e. g. Alcamo, 1999). Some examples will be cited later in this paper.

Use of computer simulation techniques to demonstrate the dynamic behavior of soils as a function of management by man is much more attractive for the modern soil user than classic soil interpretations, as presented in soil surveys, which list relative suitabilities of soils for a series of land uses. The sophisticated modern user wants a range of options to choose from

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when coping with land-use problems. He is used to making his own choices and does not like to be presented with single “ best” solutions to problems, developed by others without his active participation. He wants researchers to define a “ window of opportunity” for any given soil, while he (or she) makes the appropriate choices.

We expect that general soil awareness can increase when soil qualities are defined in the context of characteristic “ windows of opportunity” for any given soil, and when these soil qualities are communicated effectively to various users of soil information.

Sustainable land management

In their definition of sustainable land management, FAO (1993) clearly focused on

agricultural production. This can be a choice, but we should realize that land management has broader implications than agricultural production alone. This is expressed in the definition of soil quality where natural ecosystems are mentioned as well as human health and habitation.

Be that as it may, it should be recognized that FAO (1993) defines sustainable land

management and not sustainability as such. Emphasis is therefore on specific action by man and not on vague conceptual definitions, which is attractive. The elements of the definition are logical but they should, for better understanding, be grouped into two categories. The first three define plausible agro-ecological aspects: productivity, risks during production and quality of soil and water. The fourth category is different: economic feasibility (which also strongly effects social acceptability) is largely beyond the control of the land manager. Even though a management scheme may be sustainable from an agro-ecological point of view, it can be economically unsustainable because of poor prices for agricultural produce. This should certainly be considered but it is unwise to not explore various agro-ecological management options, even when at this point in time these options are not economically or socially feasible. Times may change: doubling of the world population, exhaustion of fossil fuels requiring growth of energy crops and needs for raw plant material to be grown in future by farmers as source materials for industry, are likely to change what may at this point in time be a negative economic outlook for agricultural production. Agro-ecological research, focused on developing future sustainable land management practices, should not be held ransom to current economic conditions.

How, then, to characterize agricultural production, production risks and the quality of soil and water? Monitoring of agricultural production systems can provide relevant information but procedures are tedious and costly and monitoring over periods of many years is needed to cover unusual weather conditions. The latter are needed to adequately express risks of

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analysis of sustainable management systems. Examples will be provided in a later section of this paper.

Soil quality

Many studies have been made about soil quality (e. g. Doran and Jones, 1996) but there is as yet not a well defined, universal methodology to characterize soil quality and to define a set of clear indicators. Doran and Jones (1996) present four physical, four chemical and three biological indicators which, according to the authors, together represent a minimal data set to characterize soil quality. But no examples are provided. Gomes et al. (1996) define six

indicators and threshold values for measuring sustainability of agricultural production systems at the farm level. Implicitly, higher degrees of sustainability correspond with higher soil qualities. Other examples of soil quality studies as reported by Doran and Jones (1996) list series of soil characteristics as indicators of soil quality but none really address the broad spirit or scope of the Karlen et al. (1997) definition.

A number of general considerations can be made when defining soil quality:

Any “fitness of a specific kind of soil to function” depends strongly on climatic conditions, which vary among climatic zones while the weather also varies at any given location during the year. Aside from this, soils are parts of landscapes and their functioning is strongly affected by their position in these landscapes. To consider “soil” without the climatic and landscape context, when defining quality, is not realistic. We should therefore speak about “ land quality” rather than “ soil quality” (Pieri et al, 1995), as the term “ land” expresses the broader context in which the soil functions.

“Fitness to function” will always be considered in practice in relation to other soils.

Production levels in years with favorable weather may not be too different among different soils but high quality soils tend to produce well under adverse conditions when other soils don’t deliver. Of course, production figures alone are not enough: cost and quality of produce must be considered as well. When similar yields are reached at lower costs or with a higher quality, the quality of the soil may be considered to be higher as well. But here the

management factor is introduced.

A potentially high-quality soil can still have low yields, resulting from poor management, while low-quality soils may have high yields due to excellent management. When defining land quality for a given type of soil, attention should be focussed on effects of a wide range of management types as applied for a given growing season. Studying a single growing season on a given farm will not provide useful information to derive representative land quality indicators. In fact, a high land quality implies that high yields may be obtained even under adverse conditions and under mediocre management. High quality land has a high resilience, which is best described as the ability to bounce back after the effects of poor management or poor weather conditions have been suffered. Low quality land does not have such resilience.

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The above point described short-term effects of management during a growing season. For instance, compaction of structure when driving over wet land which qualifies as poor management. When the farmer would have waited a few days, compaction might not have occurred. But there is also a long-term effect of management. When poor management leads to, for instance, erosion or strong subsoil compaction, changes in the soil are permanent. Lost soil will not return and subsoil compaction is difficult to remove. Long-term management may also be favorable, for instance when increasing the organic matter content of the soil by organic manuring. Droogers and Bouma (1997) used the term genoform to describe the genetic soil type and phenoform to describe long-term effects of management in the same soil type.

“Fitness to function” is closely tied to land utilization type. The function is quite different in natural ecosystems or in agricultural production systems. When functioning is directed

towards:” human health and habitation” one could also think about housing developments and recreation facilities. Here, attention will, arbitrarily, be confined to agricultural production systems, which is in line with the earlier discussion on sustainable management systems.

The definition of soil quality mentions:” a specific kind of soil”, which is not further explained. We believe that it would be wise to use soil surveys and soil taxonomy systems here to define specific soil types (genoforms, as mentioned above) that are well defined, also in terms of their positions in landscapes as shown on soil maps. In the USA, the soil series would be a proper “carrier” of information. In the context of the land quality concept, however, emphasis would be on land behavior in terms of crop production, its risks and environmental side effects. The implicit hypothesis would be that each soil series, occurring in a given agro-ecological zone with a characteristic climate, has a characteristic range of production rates, risks and side effects. We may call this a characteristic “ window of opportunity”. Well expressed phenoforms of a given genoform may have significantly different windows! Also, different genoforms have not always different ranges of properties:

two soils may be genetically different but may function identically. In all cases such ranges should define land quality. Again, high quality land performs well even under adverse conditions in terms of weather and management. Low quality land performs poorly even under good conditions of weather and management. The big challenge now is to quantify such broad descriptions.

The land quality concept should also indicate whether or not quality can be improved by management, either short- or long term. Is there an absolute theoretical upper level of production? If so, how can it be reached? Can it be reached without adversily affecting environmental quality? How does that level compare with the level of other soils in other

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type of soil, located within a given climatic zone. This may be either a genoform or well defined phenoforms of a given genoform. Of course, such simulations should be validated by field measurements. Models effectively integrate soil and weather as they calculate daily production values. Indeed, data are thus generated to characterize “ land” qualities. By calculating potential productions, an absolute upper yield level is obtained for any given site (at least for a given plant variety). Potential productions are based on climatic data only as well as plant parameters specific for a given species. Water and nutrient supply are supposed to be optimal while pests and diseases do not occur. Water-limited yields can also be

calculated, taking into account the water that can be supplied under natural conditions to the crop at the given site by the soil, again assuming that pests and diseases do not occur. Such yields are lower because water supply is not always optimal. Of course, pests and diseases may occur but they occur independently of the site conditions that are used to calculate water- limited yields. One major advantage of simulation models is that calculations can be made for many years, providing expressions for the effect of the varying weather conditions that could never be obtained by monitoring. This, however, is only true when models have been

independently validated using field measurements! Some examples will now be presented to illustrate the proposed procedure.

Land quality indicators

Exploratory studies for seven major tropical geno- and phenoforms

Bouma et al. (1998) studied seven major tropical soils to illustrate use of the land quality concept for exploratory purposes (Table 1). Potential and water-limited productions were calculated in terms of “ grain equivalents”, and soil data needed for the model included estimated infiltration rates, depth of rooting and available water. The reader is referred to the source publication for details (Bouma et al., 1998; Penning de Vries et al., 1995a, 1995b).

Land quality (LQ) was defined as:

LQ = (yield / potential yield) x 100.

Yield was expressed here as a calculated water-limited yield, but real yields could be used as well. Three hypothetical phenoforms were defined in this exploratory study for each of the seven genoforms in Table 1. Effects of erosion were expressed by removing the upper 40cm to 50 cm of soil, depending on soil properties. Compaction was expressed by restricting rooting to 40 cm, a depth at which a plowpan may occur. Liming expresses a potentially favorable effect of management. Acid subsoils that restrict rooting can be opened up by deep liming. Potential productions, as presented in Table 1, vary between 8 and 23 tons/ha,

illustrating climatic effects in terms of radiation and temperature. LQ values were relatively high, indicating relatively high rainfall rates leading to production values that are relatively close to potential values. The Zambia soil, however, occurring in a dryer climate had a LQ of only 50. Real yields can also be used in the equation, rather than water-limited yields. Then, an impression is obtained of the yield gap for the given site and for the actual land quality of

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the management system being used. Erosion clearly leads to reductions of LQ values, particularly in the Orthic Acrisol in China where erosion results in the occurrence of an acid subsoil near the soil surface which restricts rooting. The effects of compaction are stronger than those of erosion under the assumed conditions here, while liming has a strong effect due to deeper rooting. Values reported are relative LQ values in relation to the value for the site based on water-limited yields. An absolute LQ value can also be defined when calculated yields are compared with the highest potential production that is possible in the world (estimated to be 41.1 tons/ha). Then, LQ values are relatively low in the range of 20-39.

The exploratory analysis presented here allows a rough estimate of the relative effects of some management measures, using a simple simulation model and estimates of changes in soil parameters that are associated with certain effects of management. Also, average climatic data were used here. Running the model for a number of years with real-time weather data would have given a better impression about yield stability and risks. Still, the exploratory LQ analysis presented here can, in our opinion, be useful when discussing possible effects of different types of management and in comparing different soils.

Table 1.Potential yields, in terms of grain-equivalents, for seven major soil types of the tropics and derived relative and absolute land quality (LQ) values, based on water-limited and potential yields.

Absolute LQ values are derived from the maximum potential yield in the world of 41. 1 ton/ha/yr.

Values are derived for the seven genoforms and for three hypothetical phenoforms, expressing the effects of erosion, compaction and liming. (after Bouma et al., 1998).

Soil Type

Name Prot. Prod.

Tons Dry Matter/

Ha*Yr

Rel.

Land Quality Water Limited

Erosion Comp action

Liming

Absolute Land Quality Water Limited

1 Ferric Acrisol China 13 96 85 75 100 32

2 Orthic Ferralsol Indonesia 18 90 75 70 100 39

3 Cambic

Arenosol

Colombia 12 96 80 72 100 31

4 Ferric Luvisol Nigeria 14 90 75 55 90 32

5 Ferralic Nigeria 14 85 70 50 85 30

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Yield gap and soil nutrient balances in Africa

In a World-Bank funded study, Bindraban et al. (2000) studied land quality indicators for African soils also using potential, water-limited, nutrient-limited and actual yields. In contrast to the exploratory study of Bouma et al. (1998), they used specific data for field sites. The difference between actual and potential yield expresses the yield gap, which is considered to represent the LQ indicator. This is not unlike the approach followed by Bouma et al. (1998) except that the latter authors expressed LQ as a number between zero and one hundred and that they also defined an absolute LQ. The difference between potential and water-limited yield provides an indication what might be achieved by improved water management while the difference between water-limited and nutrient-limited yield indicates the potential impact of improved fertilization. Bindraban et al. (2000) also added a second LQ, which defines the soil nutrient balance. This is highly relevant for Africa where soil mining is rampant. The soil nutrient balance is the net difference between gross inputs and outputs of nutrients to the system and is expressed in relation to the soil nutrient stock. Of course, effects of depletion are much worse in soils with a low stock of nutrients as compared with soils having a high stock. Combining five classes for nutrient stock with five classes of N-P depletion results in six classes for the nutrient depletion LQ.

The attractive aspect of this study is its emphasis on the integrated characterization of the entire land system using quantitative and specifically defined techniques, such as simulation modeling and nutrient budgeting.

Balancing production and environmental requirements in a prime agricultural soil in the Netherlands

Application of simulation techniques for a series of growing seasons, expressing climate variability, was realized in a more detailed Dutch case study in a prime agricultural soil (Droogers and Bouma, 1997; Bouma and Droogers, 1998). Three phenoforms were identified in the field and were studied. Here, only conventional arable land is shown (CONV) and land affected by biodynamic farming for a period of 60 years (BIO). The latter soil had a

significantly higher organic matter content (appr. 4% versus 2%) as a result of biological management. A more detailed simulation model was used in this study, allowing calculations of crop growth and associated water and nitrogen regimes. Calculations were made for a 15- year period using real-time weather data and a large set of nitrogen fertilization rates. Results could therefore be expressed as probability curves (Figure 1) listing the probability that a certain yield would be exceeded on the vertical scale and the yield itself on the horizontal scale. Three yield curves are shown in the figure and they express the probability (never, 3%

and 10% of the years) that nitrate leaching will exceed the environmental threshold value for nitrate content of groundwater. Thus, risks are expressed in quantitative terms by combining the uncertainty of yields due to variable weather in different years with the associated leaching of nitrates. One more curve is shown: the dark solid, and almost vertical, line represents potential yield.

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P (X <X )

0.0 0.2 0.4 0.6 0.8 1.0

0 2500 5000 7500 10000

Yield (kg ha

^-1

)

0.0 0.2 0.4 0.6 0.8 1.0

0 2500 5000 7500 10000

Yield (kg ha

^-1

)

Bio Conv

Exceeding N-leaching

never 3% 10%

Potential production

Figure 1. Probabilities that yields of wheat are exceeded as a function of three probabilities that the threshold value for nitrate leaching to the groundwater is exceeded as well. Data are based on simulations for a 30-year period for a prime agricultural soil in the Netherlands (after Droogers and Bouma, 1997).

The graphs in Figure 1 force the user to make choices about risks to take when balancing yield versus nitrate leaching. This is a relevant key problem in Dutch agriculture where production interests have to be balanced against environmental restraints. Again, land quality can be expressed by: (actual / potential yield) x 100.

Assuming, arbitrarily, a yield level that has a probability of 20% of being exceeded and a 10%

probability that nitrate leaching will exceed the threshold, a LQ value of 89 is obtained for BIO and 84 for CONV. If however, the leaching probability is reduced to 3%, LQ values become 73 and 60. If leaching is never allowed, LQ values become 61 and 33, demonstrating the higher “quality” of the BIO soil. Different LQ values are obtained when different

exceedance values for yield probability are used. They can all be derived from Figure 1 as needed. Figures such as Figure 1 are suitable to allow the user to make choices. To the dismay of some, they do not provide clear-cut answers and judgements. Science provides the tools to users to allow them to exercise their responsibility. Science does not take away their

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of nitrate pollution of groundwater, which is the most important problem in Dutch soils.

Elsewhere other problems may figure. This comes close to what Karlen et al. (1997) must have had in mind. LQ’s are also indicators for sustainable land management, as defined above. They define production levels over the years and risks involved as well as the quality of water. Management practices, defined in this context, relate only to nitrogen fertilization and management includes, of course, much more than that. Any LQ value indicates a yield gap, being the difference between observed yields and the potential one. A logical question is how to bridge the yield gap. To answer that question all factors, which affect real yields, have to be identified.

Land quality at larger scales

Land qualities, discussed so far, were derived for individual pieces of land corresponding with a certain soil series and are implicitly focused on the farmer or local land user. Attention was confined to agricultural production and, in the Dutch case study, on important aspects of environmental quality. The definition of soil quality (Karlen et al., 1997) is focused on a

“specific kind of soil” and has, therefore, a built-in spatial scale dimension. But the LQ concept not only relates to plots or fields where single kinds of soil occur, but also to larger areas such as communities, regions, countries and even larger entities where many different soils occur. In that context, LQ’s are also important but questions are now asked by

politicians, planners and real estate brokers, rather than farmers. How should the quality of land in a large area be judged? A soil map can be used to distinguish all soil series or soil associations that occur in the area and individual land qualities of the different soil series can be considered for different land use categories. An average land quality, weighted by relative areas occupied by the different soil series, could then theoretically be calculated.

Functioning of land within natural or managed ecosystem boundaries, sustaining plant and soil productivity, maintenance of soil and water quality and support of human health and habitation” are many but not necessarily all elements of importance when dealing with land in larger areas. Infrastructure is important, but, particularly, socio-economic conditions that determine the population pressure on the land. As with the discussion on fields and farms, we advocate an approach in which the quality of land in a region is first judged in terms of its own inherent properties. Next, these properties will be only one (and as it turns out in real life, a rather minor) factor in determining the most desirable land use in a region which is highly influenced by socio-economic and political considerations and which will always be the result of tradeoffs between many conflicting land use options. The relevant question here is, then, how the quality of the land can play a role when weighing such alternative options.

Clearly, restricting the attention to agriculture in this context as the only land-use type is unsatisfactory. Aside from agricultural issues, regional land-use plans are likely to deal with establishing nature areas, transport corridors and locations for housing and industrial

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activities, LQ’s for land in a given area when considering such activities is bound to be relatively unimportant. Draining of potential building sites or adding thick layers of sand to increase the support capacity of land that has a low natural carrying capacity, is financially no problem. For nature areas and, less so, for agriculture, which are much less capital intensive, the picture is different. Local conditions of the land are very important in determining water, nutrient and temperature regimes that govern occurrence of natural vegetations but that also increasingly have an impact on types of agriculture that are ecologically balanced. The approach to take, therefore, would be to define LQ’s for agriculture and nature for land occurring in the area to be considered and to introduce this in time into the broader land-use planning process. LQ’s for agriculture have been discussed above. LQ’s for nature require a separate discussion, which is beyond the scope of this text.

Modern land-use planning increasingly uses simulation modeling in the context of systems analysis to derive optimal land-use patterns in a region. This approach was recently

demonstrated in Costa Rica (Bouman et al., 1999). Thus, interests of agriculture and nature would, as is often the case, not be a rest-factor left behind after land-use decisions have already been taken based on demands from housing, industry and infrastructure. Rather, these interests of agriculture and nature would be submitted at an early time allowing a significant effect on the decision making process by pointing out where prime land is located for

agriculture and nature. Use of LQ indicators can be quite helpful here! Of course, the political process may still ignore this, but nobody would be able to claim afterwards that they did not know.

Using the quality concept to improve communications about soils

Expression of the productive capacity of land in relation to environmental requirements in terms of a single indicator, which is related to potential production, can be helpful in our opinion to communicate more effectively with stakeholders about use of land in future as compared with current conditions where emphasis is more on the properties of land rather than on its behavior. The indicator, as proposed, provides a quality measure for a given soil type, but by recognizing occurrence of genoforms and phenoforms, it acknowledges

important effects of management. Thus, characteristic “ windows of opportunity” are obtained for any soil type occurring in a given agro-ecological zone. Use of actual yields provides an impression of yield gaps, while the absolute quality measure ranks the soil on a global scale.

We certainly cannot preserve all land for agricultural production. However, the quality

measure discussed here may help to more effectively show which land is particularly valuable and deserves more attention.

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Conclusions

The problem of worldwide land degradation and indiscriminate use of prime agricultural land for development is insufficiently recognized by society at large. One reason is the rather ineffective manner in which soil scientists present their expertise. We suggest that creative use of the land-quality concept, leading to specific indicators, may raise public awareness of the importance of the land.

Existing definitions of soil quality and sustainable land management have several elements in common. An approach is proposed here to define a land quality indicator for sustainable land management focused on agricultural land use which integrates elements of yield, risk and environmental quality using quantitative, reproducible techniques such as simulation

modeling or nutrient budgeting. Well intentioned normative and descriptive approaches will not be enough.

Socio- economic and political conditions are very important when defining land quality and sustainable land management. We advocate, however, a separate assessment of the agro- ecological potential of the land which should, in an early phase of discussions with all

stakeholders, be introduced as independent input into broader land use discussions. The future of the land cannot be held hostage to economic conditions of the day.

Land qualities, discussed in literature, have so far implicitly been focused on field and farm level and on agricultural land use, the latter increasingly within an ecologically sound context.

Land qualities are also important at larger scales, such as the regional and national level and this requires additional research because a single focus on agriculture is not realistic in this case as many other forms of land use present their demands as well.

References

Alcamo, J. 1999. The science in diplomacy and the diplomacy in science. Environment Science and Policy 2, 363-368.

Bindraban, P. S., Verhagen, A., Uithol, P.W.J. & Henstra, P., 2000. A land quality indicator for sustainable land management: the yield gap. The case of sub-saharan Africa. World Bank Institute report 106. AB-DLO Wageningen, The Netherlands.

Bouma, J., 1999. New tools and approaches for land evaluation. The Land 3. 1, 3-10.

Bouma, J. & Droogers, P., 1998. A procedure to derive land quality indicators for sustainable agricultural production. Geoderma 85, 103-110.

Bouma, J., Batjes, N.H. & Groot, J.J.R., 1998. Exploring land quality effects on world food supply. Geoderma 86, 43-59.

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Bouman, B.A.M., Jansen, H.G.P., Schipper, R.A., Nieuwenhuyse, A., Hengstdijk, H. &

Bouma, J., 1999. A framework for integrated biophysical and economic land use analysis at different scales. Agric. Ecosystems and Environment 75, 55-73.

Droogers, P. & Bouma, J., 1997. Soil survey input in exploratory modeling of sustainable land management practices. Soil Sci. Soc. Amer. J. 61, 1704-1710.

Doran, J. W. & Jones, A.J. (eds), 1996. Methods for assessing soil quality. SSSA Special Publication 49. Soil Sci. Soc. America, Madison, USA. 410 pp.

Food and Agricultural Organization (FAO), 1993. FESLM: An international framework for evaluating sustainable land management. World Resources Report 73. FAO, Rome, Italy.

125 pp.

Gomes, A.A., Swete kelly, D.E., Syers, J.K. & Coughlan, K.J., 1996. In: Methods for

Assessing Soil Quality. Doran, J.W. & Jones, A.J. (Eds). SSSA Special Publication no. 49, 401-409.

Karlen, D.L., Mausbach, M.J., Doran, J.W., Cline, R.G., Harris, R.F. & Schuman, G.E., 1997.

Soil Quality: A Concept, Definition and Framework for Evaluation. Soil Sci. Soc. Amer. J.

61, 4-10.

Oldeman, L. R. 1994 The global extent of soil degradation. In: Soil resilience and sustainable land use. Greenland, D.J. & Szabolcs, I. (Eds). CAB International. Wallingford, 99-118.

Penning de Vries, F. W. T., van Keulen, H. & Rabbinge, R., 1995a. Natural resources and the limits of food production. In: Bouma, J. et. al. (Eds). Ecoregional approaches for

sustainable land use and food production. Kluwer Acedemic Press. Dordrecht, The Netherlands. pp 65-89.

Penning de Vries, F. W. T., van Keulen, H. & Luyten, J.C., 1995b. The role of soil science in estimating global food security in 2040. In: Wagenet, R.J., Bouma, J. & Hutson, J.L. (Eds).

The role of soil science in interdisciplinary research. Soil Sci. Soc. Amer. Spec. Publ. 45:

17-37, Madison, USA.

Pieri, C., Dumanski, J., Hamblin, A. & Young, A., 1995. Land Quality Indicators. World Bank Discussion Papers 315. World Bank, Washington, D. C. USA. 51 pp.

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The soil quality concept: A tool for evaluating sustainability

Douglas L. Karlen and Susan S. Andrews

USDA-Agricultural Research Service, National Soil Tilth Laboratory, 2150 Pammel Drive, Ames, Iowa 50011-4420, US

E-mail: karlen@nstl.gov

Summary

Evolution of the soil quality concept in North America and its adoption around the world are briefly reviewed. Simply defined as “how the soil is functioning” within a field, across farms, or within entire watersheds, the soil quality concept is discussed in relation to physical,

chemical, and biological indicators that provide the actual measures needed to examine soil management effects such as the stresses that cultivation imposes. Various methods being used to monitor and assess soil quality, including user-friendly scorecards and development of indices, are discussed. Steps associated with the development of soil quality indices are outlined. They include (1) identification of appropriate indicators for various soil functions and/or land uses, (2) selection of an appropriate minimum data set, and (3) development of scoring functions that can be used to facilitate integration of the soil physical, chemical, and biological measurements in an efficient and meaningful manner. We emphasize that soil quality is not an end in itself, but rather that it should be used as a concept for evaluating the combined physical, chemical, and biological effects of various soil management practices.

The development and use of soil quality indices as tools for assessing the sustainability of all land management decisions is strongly recommended.

Keywords: soil health, conservation tillage, sustainable agriculture, soil management, land use planning, decision aids

Evolution of Soil Quality and Soil Health

Warkentin and Fletcher (1977) were among the first to suggest developing the concept of soil quality, specifically addressing its relationship to intensive agriculture. They stressed that it was not possible to obtain a quality parameter by defining pure soil as can be done for pure water and that there was no concept relating amounts of soil components to quality. With regard to land capability classes, they argued that those designations provided a quality concept based upon limitations rather than a concept based upon positive potential, and that the latter was needed for intensive agriculture. Warkentin and Fletcher (1977) suggested four criteria as the basis for a future concept of soil quality. They stressed recognizing the (i) increased range of uses for soil resources, (ii) various concerned public groups, (iii) changing priorities and demands of society, and (iv) human or institutional context. Although written for a conference nearly 25 years ago, they pointed out that soil resources were being called upon for (a) recycling and waste assimilation, (b) food and fiber production, and (c) aesthetics and leisure use. These multiple demands brought with them increased public awareness,

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resources. The theme for this conference, “Soil Stresses, Quality, and Care” suggests we are continuing to struggle with these same issues.

This broader concept of soil quality was not introduced in the North American literature until the mid-1980s. The primary emphasis before that time, with regard to soil resource

management, was simply the effects of erosion on productivity (Pierce et al., 1984).

However, in the mid- to late 1980s, several reports and books brought attention to the degradation of agricultural soils and its implications for sustainable agriculture and

environmental health. In Canada, a report by the Senate Standing Committee on Agricultures launched the subject of soil degradation into the sphere of political interest (Gregorich, 1996).

Although this and other similar reports succeeded in sounding the alarm, they were typically short on scientific evidence to support their sometimes dramatic claims. However, there was a strong incentive to focus federal soil science research on soil quality, and in 1990 the Soil Quality Evaluation Program (SQEP) was established in Canada under the broader National Soil Conservation Program.

During the same period, Larson and Pierce (1991) functionally defined soil quality, and suggested ways to evaluate it and how it changes due to soil management practices. They defined soil quality as the capacity to function within the ecosystem boundaries and to interact positively with the environment external to that ecosystem. They were also among the first to propose a quantitative formula for assessing soil quality. Very quickly, soil quality was interpreted as a more sensitive and dynamic way to document a soil’s condition, response to management changes, and resilience to stresses imposed by natural forces or human uses.

This new paradigm provided the impetus for the Rodale Institute Research Center to sponsor a workshop on “Assessment and Monitoring of Soil Quality” in Emmaus, PA (Haberern, 1992). The consensus among Workshop participants was that soil quality should not be limited to soil productivity, but should encompass environmental quality, human and animal health, and food safety and quality.

Interest among policymakers, natural resource conservationists, scientists, and farmers increased rapidly after the U.S. National Academy of Sciences published the book entitled Soil and Water Quality: An Agenda for Agriculture (National Research Council, 1993) and stated that there was a definite need for more holistic soil quality research. This interest resulted in several symposia (Doran et al., 1994; Doran and Jones, 1996) producing several definitions, functions, and uses for which soil quality should be assessed (Doran and Parkin, 1994). In response, Dr. L.P. Wilding, 1994 president of the Soil Science Society of America (SSSA), appointed a 14-person committee (S-581) with representatives from all divisions.

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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). The committee reported they had struggled with several different words such as replacing

“capacity” with “fitness”. However, because of the interdisciplinary nature of the concept, choice of words became much more difficult than anyone imagined. A similar reaction occurred when the committee suggested using soil quality and soil health interchangeably as suggested in the Canadian report entitled “The Health of Our Soils” (Acton and Gregorich, 1995).

Throughout the remainder of the 1990s, soil quality research and technology transfer

activities throughout the U.S. moved rapidly in several different directions. Soil quality test kits (Liebig et al., 1996; Sarrantonio et al., 1996), practical, farmer-based scorecards (Romig et al., 1996) and soil resource management programs (Walter et al., 1997) were developed.

Soil quality indicator evaluations (Karlen et al., 1999a; Liebig and Doran, 1999) and spatial extrapolation techniques (Smith et al., 1993) were studied. Doran et al. (1996) examined the broader linkages between soil quality (or soil health) and sustainability. Finally, various soil quality indexing approaches (Andrews, 1998; Andrews et al., 1999; Hussain et al., 1999;

Jaenicke and Lengnick, 1999; Karlen et al., 1998; Wander and Bollero, 1999) were pursued.

The indexing projects were carried out at several different scales and therefore with various degrees of accuracy (Fig. 1).

Related Indexing Projects

Spatial Scale

Predi cted Accur acy

SQ scorecard SQ test kit SQ Index

Farming Systems

Natural Resource Inventory

Figure 1. Scale and accuracy tradeoffs associated with soil quality indexing projects.

Another milestone with regard to the recent evolution of the soil quality concept was the 1994 reorganization of the USDA-Soil Conservation Service, renamed the Natural Resources Conservation Service (NRCS). This resulted in the creation of the Soil Quality Institute (SQI)

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acquisition and dissemination of soil quality information and technology to help people conserve and sustain our natural resources and the environment”. By emphasizing outreach and communication, the SQI has been successful in achieving their goal

(http://www.statlab.iastate.edu/survey/SQI/sqihome.shtml).

Evolution of the soil quality concept in the U.S. has not been without controversy (Sojka and Upchurch, 1999). A legitimate concern is that to date, assessments have generally focused on crop production and ecological functions despite the intention to address multiple soil

functions. We suggest that this occurred primarily because the technical disciplines of the people who were among the first to begin examining the concept were primarily soil biology, soil fertility and plant nutrition, and ecology. However, the need to develop a consensus on the proper means to assess soil quality from an environmental perspective was clearly identified by Sims et al. (1997). They stressed the need for soil scientists to take a proactive role in framing, from all perspectives, the debate on soil quality and environmental issues.

This includes developing new approaches for quantifying environmental risks posed by soils in agricultural and nonagricultural settings. From a global perspective, contaminant levels and their effects have been more central to the soil quality debate in Canada and Europe (Singer and Ewing, 2000). However, a recent review suggests that many German-language publications are continuing to struggle with how to differentiate the soil quality concept from the numerous definitions and attributes associated with soil fertility phenomena (Patzel et al., 2000).

Singer and Ewing (2000) stated that increasingly, contemporary discussion of soil quality includes the environmental cost of production and the potential for reclamation of degraded soils. They continue, stating that “reasons for assessing soil quality in an agricultural or managed system may be somewhat different than reasons for assessing soil quality in a natural ecosystem. In an agricultural context, soil quality may be managed to maximize production without adverse environmental effect, while in a natural ecosystem, soil quality may be observed as a baseline value or set of values against which future changes in the system may be compared.” The major challenge, however, is that determining soil quality requires one or more value judgments and since we still have a lot to learn about soil resources, these issues can not be easily addressed.

Sojka and Upchurch (1999) articulated the impact of those value judgments extremely well when they concluded that “our children and grandchildren of 2030 will not care whether we crafted our definitions or diagnostics well. They will care if they are well fed, whether there are still woods to walk in and streams to splash in - in short, whether or not we helped solve

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Soil Quality Indices as Tools for Assessing Sustainability

A fundamental principle associated with all of the soil quality index projects that we have been associated with is that any assessment process must recognize both inherent and dynamic components. The inherent characteristics are those determined by the basic soil forming factors: parent material, climate, time, topography, and vegetation (Jenny, 1941).

They determine why two soils (A and B) will always be different (Fig. 2).

Soil Q u ality

Time

Soil B Soil A

S o il Qu a lit y

Time

Degrading Aggrading

Sustaining

T_o baseline

Figure 2. Inherent soil quality for soil A and B, and trends identified by indexing.

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The dynamic fluctuation associated with soil quality assessment results from a combination of current or past land use and anthropogenic management decisions. A second caveat is that soil quality indexing should only be used as a tool to identify positive, negative, or neutral trends associated with specific sets of management practices imposed on a specific soil resource. There are no “magic” or perfect scores or ratings. The sole purpose for developing a soil quality index is to help visualize the integrated effects that land use decisions are having on the physical, chemical, and biological soil properties or processes.

Figure 3. Hierarchy of agricultural indices showing soil quality as one of the critical foundations for sustainable land management.

SOIL QUALITY INDEX

Soil Quality

Index

Air Quality

Index

Water Quality

Index ENVIRONMENTAL QUALITY INDEX AGRICULTURAL SUSTAINABILITY INDEX Environmental

Quality Index

Economic Sustainability

Index

Social Viability

Index

Biological Factors Chemical

Factors Physical

Factors

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Current Projects Focused on Measuring Soil Quality

Understanding conceptual linkages between soil quality, environmental quality and

agricultural sustainability is a first step toward recognizing that soil is a finite, dynamic and living resource that acts as a fragile interface between agriculture and the environment (Doran et al., 1996). Undoubtedly, this understanding was among the factors leading to this

conference on “Soil Stresses, Quality, and Care”. However, as our discussions will certainly document, soil quality cannot be measured directly. It must be inferred by measuring changes in various soil attributes or attributes of the ecosystem (Seybold et al., 1997). These

"indicators" of soil quality should (i) encompass ecosystem processes and relate to process oriented modeling, (ii) integrate soil physical, chemical, and biological properties and

processes, (iii) be accessible to many users and applicable to field conditions, (iv) be sensitive to variations in management and climate, and where possible, (v) be components of existing soil data bases (Doran and Parkin, 1994). They should also be easily measured and

reproducible (Gregorich et al., 1994) and sensitive enough to detect changes in the soil resource as a result of human use or degradation (Arshad and Coen, 1992).

It would be impossible to use all ecosystem or soil attributes as indicators of soil quality.

Thus, a minimum data set (MDS) consisting of selected chemical, physical, and biological soil properties has been suggested for assessment (Larson and Pierce, 1994). One indicator included in almost every published MDS is some measure of soil organic matter (SOM) (e.g., Doran and Parkin, 1994; Gregorich et al., 1994; Larson and Pierce, 1994). Several different SOM fractions, including microbial biomass, water-soluble organic matter, particulate organic matter, and humus or stabilized organic matter, have been included in the various MDS.

SOM is one of the more useful indicators of soil quality, because it interacts with numerous soil components. It greatly affects soil physical properties like infiltration, aeration, water retention, aggregate formation, bulk density, and soil temperature. SOM has also been shown to influence biological and chemical properties such as soil pH, buffer capacity, cation

exchange, nutrient mineralization, agricultural chemical sorption, the spectral environment for plant seedlings, and the diversity and activity of soil organisms (Doran and Jones, 1996) Descriptive or qualitative indicators have also been used to assess soil quality. Among these are soil crusting or surface sealing, rills, gullies, ripple marks, sand dunes, salt crusts, and standing or ponded water (Arshad and Coen, 1992). Others found that farmers often describe their soil using terms such as loose, soft, crumbly, loamy, earthy smelling, darkly colored, massive, lumpy, or dense (Romig et al., 1995). They also tend to rely on what their senses tell them about soil quality and how it affects tillage and yield more than any specific plant response or soil measurement.

In our soil quality studies (Fig. 1), the primary effort has focused on measuring numerous soil physical, chemical and biological properties and using various approaches to select the most appropriate ones for the assessment being made. For Major Land Resource Area (MLRA)

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evaluations, factor analysis was used to construct “soil quality factors” consisting of several different indicators (Brejda et al., 2000) using data from the U.S. Natural Resource Inventory.

Discriminant analysis was then used to identify the factors and indicators most sensitive to land use. The NRCS-SQI Farming Systems Project is developing a spreadsheet tool that predicts soil quality changes based on management practices at the field to farm scale. For our plot- and field-scale studies (Andrews et al., 1999), soil quality indexing has generally

involved three primary steps: (1) choosing indicators for a minimum data set (MDS) either by

“expert opinion” or using principal component analysis (PCA); (2) transforming indicator scores; and (3) combining the indicator scores into the index (Fig. 4). We have selected this approach so that when management goals focus on sustainability rather than just crop yields, the soil quality index (SQI) can be used as one component nested within a hierarchy of agricultural indices (Fig. 3).

SQI =

MINIMUM DATA SET (MDS)

PCA-chosen or Expert Opinion-selected variables

ƒƒƒƒ (transformed MDS)

BIOLOGICAL CHEMICAL

SCORING FUNCTIONS

1 0

1 0 1

0

PHYSICAL

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We are currently using this soil quality indexing protocol to compare organic and conventional management practices for vegetable and crop production in the Central Valley of California, to compare long-term ridge-tillage and conventional tillage practices for corn production on deep loess soils, and to quantify transitional effects of converting the deep loess conventional tillage watersheds to either no-tillage or contour strip cropping systems. Data are also being collected to quantify soil quality impacts of grazing cattle in a collaborative study between U.S. and New Zealand scientists. Preliminary results from the California study indicate that (i) an “expert opinion” choice of indicators can be skewed by disciplinary biases and using statistical methods may eliminate that source of error; (ii) use of PCA to triage large data sets can effectively represent variation in the total data set and it appears to select a MDS as well or better than the expert opinion; and (iii) organic and low input plots consistently received higher SQI scores compared with the conventional treatments (Karlen et al., 1999b).

Similar evaluations are planned for the other projects.

Finally, a soil quality indexing protocol (Andrews, 1999) is being developed to help interpret data collected using the Soil Quality Test Kit (Liebig et al., 1996; Sarrantonio et al. 1996).

The primary challenge associated with this multi-agency effort is to create a soil quality scoresheet that is transferable across soil and climatic regions as well as among management practices and priorities. Major tasks for this work-in-progress include: (1) delineate inherent soil quality regions across the U.S., (2) identify indicator ranges for each region, soil, or crop, (3) assign weighting factors to account for management priorities, and (4) calibrate and validate the scoresheet by testing in each region. Data is continuing to be compiled, but thus far, the scoresheet methodology appears to be adequately representing overall soil quality in an easily interpretable format for the tested regions.

Summary and Conclusions

Factors associated with the evolution of the soil quality concept were examined and use of the concept as a tool for assessing sustainability was reviewed. The fact that soil quality cannot be measured directly has been addressed by identifying and selecting appropriate indicators and sets of indicators for use in developing soil quality indices. Initial results suggest the process can be successful at several different scales and with appropriate accuracy for each of those scales. Additional efforts to develop soil quality indices, especially for non-crop

production functions are desperately needed. Hopefully, with the increased environmental quality emphasis of many European studies, an identifiable outcome of this conference on

“Soil Stresses, Quality, and Care” will be indexing protocols that truly facilitate solving the soil resource problems that our children and grandchildren will face if we fail to take appropriate action as we begin the 21^st Century.

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References

Acton, D. F. and L.J. Gregorich. 1995. The Health of Our Soils – Toward Sustainable Agriculture in Canada. Centre for Land and Biological resources Research, Research Branch, Agriculture and Agri-Food Canada, Ottawa, ON.

Andrews, S.S. 1998. Sustainable agriculture alternatives: ecological and managerial implications of poultry litter management alternatives applied to agronomic soils. PhD.

Dissertation. University of Georgia, Athens, GA., USA.

Andrews, S.S. 1999. Regional scoresheets for interpreting the soil quality test kit. p. 219.

Annual Meeting Abstracts. ASA-CSSA-SSSA, Inc., Madison, WI.

Andrews, S.S., L. Lohr, and M.L. Cabrera. 1999. A bioeconomic decision model comparing composted and fresh litter for winter squash. Agricultural Systems. 61(3):165-178.

Arshad, M.A., and G.M. Coen. 1992. Characterization of soil quality: Physical and chemical criteria. Am. J. Altern. Agric. 7:25-31.

Brejda, J.J., T.B. Moorman, D.L. Karlen, and T.H. Dao. 2000. Identification of regional soil quality factors and indicators: I. Central and Southern High Plains. Soil Sci. Soc. Am. J.

64:2115-2124.

Doran, J.W., D.C. Coleman, D.F. Bezdicek, and B.A. Stewart. 1994. Defining Soil Quality for a Sustainable Environment. SSSA Spec. Publ. No. 35, Soil Sci. Soc. Am., Inc. and Am. Soc. Agron., Inc., Madison, WI.

Doran, J.W., and T.B. Parkin. 1994. Defining and assessing soil quality. p. 3-21. In: J.W.

Doran et al., (ed.) Defining Soil Quality for a Sustainable Environment. SSSA Spec. Publ.

No. 35, Soil Sci. Soc. Am., Inc. and Am. Soc. Agron., Inc., Madison, WI.

Doran, J.W., and A.J. Jones. 1996. Methods for Assessing Soil Quality. SSSA Spec. Publ.

No. 49, Soil Sci. Soc. Am., Inc., Madison, WI.

Doran, J.W., M. Sarrantonio, and M.A. Liebig. 1996. Soil health and sustainability. p. 1-54.

In: D.L. Sparks (ed.) Adv. Agron., Vol. 56., Academic Press Inc., San Diego, CA.

Gregorich, E.G., M.R. Carter, D.A. Angers, C.M. Monreal, and B.H. Ellert. 1994. Towards a minimum data set to assess soil organic matter quality in agricultural soils. Can. J. Soil Sci. 74:367-385.

Gregorich, E.G. 1996. Soil Quality: A Canadian perspective. Proc. Soil Qual. Indic. Worksh.

Feb 8-9, 1996. Ministry of Agric. and Fisheries, and Lincoln soil Quality Res. Cntr.

Lincoln Univ., Christchurch, NZ.

Haberern, J. 1992. Coming full circle – The new emphasis on soil quality. Am. J. Altern.

Agric. 7:3-4.

Hussain, I., K.R. Olson, M.M. Wander, and D.L. Karlen. 1999. Adaptation of soil quality indices and application to three tillage systems in southern Illinois. Soil Till. Res. 50:237-

Soil Stresses, Quality and Care Proceedings from NJF seminar 310 Ås, April 10-12 2000

Soil Stresses, Quality and Care

NJF-seminar Soil Stresses, Quality and Care

Contents

The land quality concept as a means to improve communications about soils

Summary

Introduction

Creating awareness about soils

Sustainable land management

Soil quality

Land quality indicators

P (X <X )

Yield (kg ha

)

Yield (kg ha

)

Bio Conv

Land quality at larger scales

Using the quality concept to improve communications about soils

Conclusions

References

The soil quality concept: A tool for evaluating sustainability

Summary

Evolution of Soil Quality and Soil Health

Related Indexing Projects

Spatial Scale

Predi cted Accur acy

SQ scorecard SQ test kit SQ Index

Farming Systems

Natural Resource Inventory

Soil Quality Indices as Tools for Assessing Sustainability

Soil Q u ality

Time

S o il Qu a lit y

Time

SOIL QUALITY INDEX

Current Projects Focused on Measuring Soil Quality

SQI =

MINIMUM DATA SET (MDS)

ƒƒƒƒ (transformed MDS)

SCORING FUNCTIONS

Summary and Conclusions

References