Agronomy Journal 94:23-32 (2002)
© 2002 American Society of Agronomy
SYMPOSIUM PAPERS
Soil Quality
Science and Process
Michelle M. Wander*,a,
Gerald L. Walterb,
Todd M. Nissena,
German A. Bolleroc,
Susan S. Andrewsd and
Deborah A. Cavanaugh-Granta
a Dep. of Nat. Resources and Environ. Sci., Univ. of Illinois, Urbana, IL 61801
b Dep. of Human and Community Dev., Univ. of Illinois, Urbana, IL 61801
c Dep. of Crop Sci., Univ. of Illinois, Urbana, IL 61801
d USDA-ARS, Natl. Soil Tilth Lab., Ames, IA 50011
* Corresponding author (mwander{at}uiuc.edu)
Received for publication May 22, 2000.
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ABSTRACT
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The term soil quality (SQ) encompasses both a soil's productive and environmental capabilities. Strategies or frameworks that help farmers manage SQ are vital as sole emphasis on production can have negative environmental consequences and exclusive focus on environmental considerations could endanger supplies of food or fiber. Recent efforts in the USA have prioritized the development of SQ assessment strategies that would be used by individual farmers. The Illinois Soil Quality Initiative (ISQI) is an example of a participatory research strategy coupled with a SQ index-screening trial conducted on farm fields. A multivariate approach was used to identify promising indices and document tradeoffs in soil condition that were associated with tillage choices. Participatory aspects of the project confirmed that farmers appreciated the multivariate nature of soil and had great interest in SQ and stewardship. A dialogue component of the project had been structured to identify and then respond to cooperators' SQ information needs and to contribute to the development of indices that were related to soil function. Cooperator feedback suggested that a simple extension of this approach would be incapable of motivating or justifying the adoption of SQ building practices because factors constraining management choices were primarily structural (socioeconomic). Constructive follow-up efforts might strive to develop techniques to integrate SQ information into frameworks that reflect the outcomes to be achieved within social or economic contexts. Only by devising such strategies (which might combine models, indices, expert knowledge, and/or direct measurement) will we be able to manage the soil resource to achieve desired ends.
Abbreviations: CT, conventional tillage • ISQI, Illinois Soil Quality Initiative • ND, nondisturbed • NT, no-till • POM, particulate organic matter • SQ, soil quality
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INTRODUCTION
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SINCE ITS INCEPTION, the soil quality (SQ) concept has been strongly associated with efforts to address agricultural sustainability (Youngberg, 1992; Parr et al., 1992; Warkentin, 1995). General definitions for SQ, which are understandably broad, emphasize the capacity of soil to perform services including the production of plants and animals and the transport and regulation of matter (water and other compounds) present in or added to soils (Doran and Parkin, 1994; Karlen et al., 1998). In addition, descriptions of SQ reflect appreciation for soils' fitness for use (Larson and Pierce, 1994) and the capacity of soil to resist and recover from degradation (Blum, 1998; Greenland and Szabolcs, 1994). Inherent differences in soils arise from influences of various climates, parent materials, topographies, and biota, all acting over geologic time (Jenny, 1941). Inherent differences are well reflected by the soil series description of the U.S. system of soil taxonomy, which includes a relatively complete description of the makeup and characteristics of the horizons present in a given soil. A variety of classification systems have been developed to describe the soils' suitability for specific types of land use and natural ability to tolerate factors that degrade soils; these inherent characteristics of soils vary within and among continents (Fig. 1), regions, and landscapes (Eswaran et al., 1999; Oldeman et al., 1991). The traits that provide the basis for taxonomic classification schemes are relatively use-invariant and so are not as useful as are dynamic aspects of soils that change as a function of human management expressed over a comparatively short time frame (within a decade) (Lal, 1998). Dynamic fractions of organic matter (Gregorich et al., 1994) or biological and physical aspects of soils influenced by organic matter status that are responsive to management are often favored as indices of SQ (Wander and Bollero, 1999; Wander and Drinkwater, 2000). This is true even in environments where concentrations of soil organic matter are quite low (Bird et al., 2000).
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Midwest Row Crop Systems
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A balance between the productive and environmental performance of Midwest soils must be sought as pressure on these lands is likely to increase. Many argue that there is a need to maintain or even increase the production capacity of land to satisfy growing food and fiber demands and spare land for alternate uses (World Resources Inst., 1998; Waggoner, 1994). Increasing demand for high quality water will likely reduce agricultural access to irrigation waters (FAO, 1997; World Meteorol. Organ., 1997), making stewardship of soils used for rainfed production all the more important. Increases in monoculture production of cash grains, cultivation, and reliance on chemical fertilizers and pesticides have increased yields and reduced on-farm labor demands; however, these intensified production practices are often associated with losses in soil organic matter, increased erosion, and surface and ground water contamination (Matson et al., 1997; Tilman, 1999; Cassman, 1999).
Current emphasis on SQ reflects our need to simultaneously achieve production and environmental goals. Based on his observations of many long-term studies, Cassman (1999) outlined a theoretical relationship between SQ and crop yield potential (Fig. 2a). He argued that both crop yield potential (plateau height) and input use efficiency, which is depicted by the slope representing yield response to inputs, can be reduced as SQ is diminished. In the Morrow Plots, which is the oldest agricultural trial in the USA (see Aref and Wander, 1997), corn (Zea mays L.) yield response to inputs averaged over 30 yr (1967–1997) reflects SQ differences that have resulted from more than 130 yr of agronomic use (Fig. 2b). In this example, the inputs axis reflects all management inputs (manure, lime, P, inorganic nutrients, and seeding density) instead of a single input. Treatment yields serve as a sort of biological assay of SQ. Yield response suggests continuous cropping to corn has reduced both the input use efficiency and yield potential of those plots (Yd type curve), compared with plots where either soybean [Glycine max (L.) Merr.] or sweetclover (Melilotus alba Medikus)–red clover (Trifolium pratens L.)–alfalfa (Medicago sativa L.) hay have been grown in rotation with corn. Production of corn and soybean for 30 yr on plots where corn and oat (Avena sativa L.) had been rotated for 100 yr reduced input use efficiency but not yield potential (Yb type curve). The figure indirectly demonstrates how yield potential and environmental efficiency are interlinked. Maximum responses were achieved with fewer inputs in plots where longer crop rotations had been used (Ya type curve). Organic matter is the soil property that has been most notably influenced by crop rotation, with levels increasing with rotation length (Aref and Wander, 1997). The figure does not indicate that the 3-yr rotation used in the Morrow Plots is the best land use practice for this site. Trends indicate that SQ must be maintained to maximize yield potential and environmental benefits. Ideal cropping practices are productive in terms of grain, SQ, and environmental services.
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Fig. 2. Soil quality and yield response: Example 2a was adapted from Cassman (1999). This depicts the conceptual relationship between yield and input requirements as influenced by soil quality. A decrease in soil quality from an initial state (Ya) can reduce input use efficiency (Yb), yield potential (Yc), or both (Yd). Fig. 2b provides examples of performance outcomes for production potential and nutrient use efficiency in the Morrow Plots, which have been farmed since 1876. Means (1967–1997) are of yield when corn was grown in all plots. Different levels of inputs have been applied to plots maintained under three rotations. Inputs include: none (unamended), manure (approximately 9.9 t ha-1 applied every year to the continuous corn rotation while 13.44 Mg ha-1 are applied before corn in the corn soybean and corn, and corn, oat, hay rotations. Lime and P have also been applied to those plots. Plant density is 19800 plants ha-1 in the manured and unamended plots), manure+ (same amendment rates as those listed above, and plant density is 39600 plants ha-1), NPK (N is applied at 224 kg ha-1 as urea; plots testing <50 and 377 kg ha-1 P and K, respectively, have been amended with 55 and 104 kg ha-1 triple super phosphate and muriate of potash. Plant density is 59400 plants ha-1), MNPK (the manure treatment was applied until 1955, after which N, P, and K and planting density have been applied as listed above), and HNPK (plots that had received the manure treatment until 1967 that have since been amended with only 336 kg N ha-1 as urea; P and K were maintained at test values >125 and 628 kg ha-1 P and K, respectively. Plant density is 59400 plants per ha-1).
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Efforts have been expended to quantify soil properties directly rather than infer soil condition from performance variables that are likely to be influenced by other factors. This is because annual yield response to inputs and SQ can be masked by weather or production variables. For example, Bollero and Bullock (1994) attributed the increased input use efficiency (N fertilizer) and yield potential (Fig. 3) to enhanced SQ in corn plots where hairy vetch (Vicia villosa Roth) had been used as a winter cover crop. Although the yield increase observed after a single year was not large enough to economically justify planting hairy vetch, the cumulative yield benefit and increased efficiency accrued over several years would likely support a different conclusion. In that same study, reduced yield potential in plots where rye (Secale cereale L.) had been used as a cover crop were caused by low crop stand populations that were the result of bad weather that delayed cover crop killing. In that case, yield response was unrelated to SQ.
In an effort to directly assess SQ using the fewest attributes necessary, minimum data sets, or suites of measures, have been proposed that could describe the dynamic nature of soils (Larson and Pierce, 1994; Bouma, 1989; Dick et al., 1996; Muckel and Mausbach, 1996). To select useful soil attributes, one must first decide which of many possible soil ecosystem functions to monitor (Harris et al., 1996; Karlen et al., 1997). In addition, the practicality and informational value of indicators (Wander and Bollero, 1999), as well as their applicability with respect to various spatial and temporal scales (Halvorson et al., 1997; Seybold et al., 1997), should be considered in light of the stresses incurred by the soil management system to be assessed. Finally, management practices should be related to both site- and use-specific shifts in indicators (Walter et al., 1997).
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ILLINOIS SOIL QUALITY INITIATIVE CASE STUDY
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In Illinois, the pressures on row crop production systems are readily apparent. The state is graced by more than 8.1 million ha of prime farmland. In 1997, 7.57 million ha were in crops, which is the most of any state and 9% of the nation's total (USDA, 2000a). For the years 1997–1999, corn and soybean yields have exceed the national average by 4 and 13%, respectively, and exceeded the world average by 102 and 30%, respectively (USDA, 2000b). Despite the inherent productivity of the region, economic and environmental pressures plague farmers. The amount of prime farmland in crops has decreased by 181440 ha since 1982 (USDA, 2000a). In 1997, Illinois farm debt exceeded $8.8 billion (USDA Econ. Res. Serv., 1999). In addition, agriculture has been blamed for nitrates, P, and pesticides found in ground and surface waters (Natl. Resources Conserv. Serv., 1997).
The Illinois Soil Quality Initiative (ISQI) is a case study in the development of the SQ concept where both the multiple (productive and environmental) and simultaneous functions of soils and the multiple (economic, aesthetic, and stewardship) and simultaneous goals of project participants were recognized. Beginning in 1994, a group of University of Illinois researchers, farmers, USDA personnel, and representatives of many public and private organizations worked to determine whether the concept of SQ could be meaningfully applied in Illinois row crop systems. During the start-up phase of ISQI, it became clear that advisory board members held strong but often differing ideas about SQ (Walter et al., 1997). Board members agreed to adopt a working definition of SQ based on the SSSA definition: SQ is the capacity of soils within landscapes to sustain biological productivity, maintain environmental quality, and promote plant and animal health.
The board's purpose was to provide direction and help develop the objectives for the project. In January 1995, ISQI Phase I was funded by the University of Illinois Agricultural Experiment Station. The objectives of that proposal were to conduct (i) a dialog to increase idea exchange among concerned parties, (ii) a planning or pilot study to develop a strategy to monitor Illinois SQ, and (iii) a farmer participatory SQ index-screening trial. The outcomes sought by ISQI were to promote the protection of the state's soil resource by improving the understanding of the SQ issue and to identify SQ indices that farmers could use to make decisions about their own specific management practices.
On-Farm Research
In 1995 and 1996, ISQI studied SQ in 36 farm fields under conventional tillage (CT) or no-till (NT) management. At the request of cooperating farmers, relatively nondisturbed (ND) areas adjacent to each field were also sampled for use as benchmarks even though those areas were often not pristine. Most were narrow grass strips located along roadways, woodlots, or yards. A few were adjacent prairies or graveyards. Soils included in the study were Mollisols or Alfisols. During the on-farm study, 23 physical, chemical, and biological properties were characterized. The on-farm design of ISQI forced the project into a large physical scale that was multivariate in nature. That design and the resulting data set enabled us to rapidly and efficiently characterize the effects of management on soil properties in Illinois, as affected by region (inherent soil characteristics) and tillage practices (dynamic soil quality).
We used a multivariate approach to group and rank data and found that this approach allowed us to effectively interpret a complex data set (Wander and Bollero, 1999). Using this approach, we identified factors sensitive to management and the inherent characteristics of soils and gained knowledge of parameters and their interrelatedness or lack thereof. Clusters of measures were more powerful descriptors of the soil system than were individual measures. Biological and physical aspects of soils that are influenced by organic matter status were the properties most altered by agronomic practices. Particulate organic matter (POM) was identified as a particularly promising SQ measure because of its sensitivity to management and its tie to soil nutrient dynamics and structural integrity. Trends in POM were more sensitive to management than were total organic C contents, potentially mineralizable N, or microbial biomass (chloroform labile C) (Needelman et al., 1999).
By assessing numerous variables with the capacity to respond to recent management and by considering their characteristics at more than one depth, we were able to identify potential tradeoffs in soil condition that might result from management choices. For example, the total organic matter content of soils under CT and NT management did not differ significantly; however, the use of NT practices had improved the biological and physical condition of properties dependent on organic matter (e.g., residue cover, wet aggregate stability, potentially mineralizable N, and microbial biomass C) in the surface depth (0–15 cm) (Wander and Bollero, 1999). Despite those improvements, NT soils were on average more consolidated (had higher penetration resistance and bulk density) than CT soils. Under NT management, POM contents of surface soils (0–5 cm) were increased, and the subsurface (5–15 cm) POM contents were decreased relative to tilled soils. The vertical stratification of POM was more extreme in very fine-textured soils, suggesting that the application of NT practices to those soils might enhance soil condition in the surface at the expense of soil condition at depth (Needelman et al., 1999). By assessing a wide number of properties and multiple soil depths, we were able to document the subtlety and complexity of the responses of soils to management.
Soil Quality Dialogue Project
To learn about nontechnical factors that influence SQ in Illinois, we augmented findings from the on-farm research project with various other kinds of interactions with and among collaborators. These dialogue project activities began with meetings at which a board of farmers, farm managers, state and conservation agency personnel, soil scientists, agronomists, and social scientists established the project's goals and the means for monitoring its progress. Subsequent activities included surveys, semistructured interviews, and focus groups of collaborators and others interested in SQ. These activities were conducted to identify participants' SQ beliefs, the nature of their interest in SQ, and their perceived need for information about SQ and related topics. Cooperating farmers received a small monetary compensation for their participation in meetings and surveys and for providing access to their fields and management information. The project also produced periodic newsletters about ISQI goals, progress, and findings.
At annual board meetings, the technical staff and individual cooperating farmers reported on project progress and outcomes. Feedback from these meetings and from focus groups and interviews revealed that definitions and beliefs about SQ varied according to the context—production, conservation, or regulation—in which they might be used (Walter et al., 1997). Yet regardless of how they defined SQ, farmers and board members alike expressed great interest in obtaining more soils information. Many participants also expressed concern about the long-term maintenance of SQ (Walter et al., 1997).
Here we report, for the first time, findings that reflect on the manner in which producers might implement SQ information. During focus-group meetings with researchers, cooperators identified both the SQ parameters that currently guide their management decisions and those they might use if information was more readily available. Eighty percent indicated that they currently use soil test reports of pH and of available P and K in choosing management practices; half indicated that they use information about residue cover and cation exchange capacity. Most said that before participating in the focus groups, they had been interested in obtaining indicators of infiltration rates, bulk density, and Ca/Mg ratios. More than half expressed interest in learning more about soil microbial biomass, soil respiration rates, available K, and pH as a result of our meetings. The farmers in the focus groups also made it clear that even though they tend to hold a complex view of SQ, they nonetheless desire a set of measures (or some other strategy) that would simplify the soil system enough to help them identify and even quantify the SQ benefits associated with specific management practices.
These focus-group findings reinforce findings from semistructured interviews with 51 farmers and professional farm managers conducted in 1995. The majority of these survey respondents (including 16 ISQI cooperating farmers) indicated both that they perceive SQ as multidimensional and that they are seeking practical ways to make it part of their planning process. The survey further found (Fig. 4) that the relatively easily observed physical properties of soils figure prominently in producers' and managers' SQ assessments, just as they influence such management decisions as the timing of plowing and planting. Respondents also named crop appearance and health, leaf color, and stand quality as SQ indicators, and they indicated strong interest in obtaining information about soil biological activity. They called soil fertility a critical component of SQ and said that they rely on soil tests to tell them whether they are effectively maintaining soil nutrient status. However, they also ranked soil's ability to regulate water movement as an aspect of SQ that is nearly as important as its capacity to support crops.
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Fig. 4. Results of an Illinois Soil Quality Initiative (ISQI) survey of 45 farmers and land managers showing variations in terms used to describe soil quality (SQ).
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The dialogue project made clear to us that one of the biggest challenges producers face is putting new SQ information into a useful context. At the second annual meeting, we gave cooperators a listing of 23 soil properties measured using samples from their fields and asked them to evaluate three SQ assessment strategies, including: (i) the Wisconsin Soil Health Score Card (Garlynd et al., 1994), which allowed them to visually assess SQ; (ii) a worksheet that included an adaptation of scoring functions (Karlen and Stott, 1994) with which they could compute the condition of their soil with regard to water relations, nutrient supply, and rooting environment; and (iii) radar graphs (sensu Gomez et al., 1996) that provided an at-a-glance view of laboratory results grouped to reflect fertility, soil organic matter, and environmental performance. Cooperating farmers used each strategy to assess their fields in relation to adjacent nondisturbed areas and to treatment means from the project.
Following these individual assessments, the farmers were asked to reflect on the relative merits of each strategy. They expressed reservations about the highly subjective nature of the score cards (Table 1), but these impressions were likely influenced by the juxtaposition of the more subjective measures with the other, more quantitative measures. Many cooperators noted the cards' potential to yield SQ trend information if used over a number of years.
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Table 1. Farmer-based assessment: Adapted from the Wisconsin Soil Health Scorecard (Romig et al., 1996). Reprinted here are only the soil-related questions that refer mainly to the plow layer. Users are advised to complete this near or just before harvest. To score soils, users are asked to (i) read questions and focus on properties separately; (ii) choose answers that best describe properties with the left-hand scale corresponding to healthy (3–4), impaired (1.5–2.5), and unhealthy (0–1) condition; (iii) answer as completely as possible; and (iv) enter a NA if not applicable to their scenario.
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Participants also had the opportunity to compare their scores derived from the scoring-function worksheets with those of other participants and with project means (Table 2). Project means reflect a typical result where the enhanced soil water function of the NT soil can be weighed against the greater fertility status and rooting environment of the CT soils. The separate scores for soil water relations, nutrient supply, and rooting could be combined to generate an overall SQ score, but participants expressed no interest or inclination to do so. Instead, they indicated a preference for information capturing the tradeoffs or complexities of their soil.
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Table 2. Scoring functions calculated from Illinois Soil Quality Initiative (ISQI) data (1991–1992) treatment means collected from farm fields under conventional tillage (CT) or no-tillage (NT) management and from areas adjacent to those fields that were relatively nondisturbed (ND). Functions were adapted from Karlen and Stott (1994) to utilize alternate measures. These functions were developed for use during focus-group meetings held with cooperating farmers as examples of how soil quality (SQ) measures could be integrated for use.
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The producers' desire to manipulate SQ information themselves came across fully when they were exposed to the radar graphs we had prepared, which plotted data from their individual fields and nondisturbed areas to summarize the fields' fertility, organic matter, and environmental status. These graphs showed several related SQ measures simultaneously, such that more desirable values for each measure lay farther from the graph's origin. For comparison purposes, we plotted summaries of project means for NT, CT, and ND areas on acetate overlays (Fig. 5) that the participants could superimpose on the plotted data for their own fields. The participants were enthusiastic about this presentation mode's ability to make tradeoffs or compensating factors more obvious and their soil's inherent capabilities (abstracted from the characteristics of their nondisturbed areas) more apparent.
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Fig. 5. Radar graphs for indices of (a) soil environmental quality and (b) soil organic matter quality from the Illinois Soil Quality Initiative (ISQI) project. Each axis depicts an individual indicator. Measures farther from the center of the graph are assumed to represent better quality. Axes scales were selected to include the full range of measured values. The solid line represents the mean values of indices from no-tilled (NT) fields, the dashed line represents the values from conventionally tilled (CT) fields, and the dotted line represents the mean value from nondisturbed (ND) areas. Indices proposed for soil environmental quality include aggregate dry mean weight diameter (DMWD); aggregate wet mean weight diameter (MWWD); soil NO3 measured at 30-cm depth; percent residue measured at planting; soil organic C content in the top 15 cm; penetration resistance assessed with an impact penetrometer; macropores >1 cm2, which were not measurable in the ND soils due to the abundance of roots in those soils; and bulk density in the top 15 cm. Indices proposed for assessment of soil organic matter quality include organic matter content in the surface depth, particulate organic matter (POM, g C/kg soil) in the surface (0–5 cm) and subsurface depths (5–15 cm), MWWD, residue at planting, soil N supply potential (Min N) measured with anaerobic incubation, microbial biomass C (Bio C) chloroform fumigation extraction, and soil C/N ratios. The relevance of some of the variables included (e.g., MWWD) and the direction of their axes are hypothesized, not proved.
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For example, the graph depicting environmental quality (Fig. 5a) shows that soils under CT management had, on average, less residue cover at the surface and lower wet aggregate stability than soils under NT management but that those deficiencies might be offset by lower bulk densities and lower NO3–N concentrations measured in the subsurface of the tilled soils. Agricultural use of soil reduced organic matter status relative to nondisturbed soils in all cases (Fig. 5b). Typically, indicators of organic matter status were more degraded in CT than in NT systems.
We shared a summary of research findings and cooperator feedback about assessment strategies with the ISQI board at a final meeting. Board members were then asked to identify SQ-related issues they felt had not been adequately addressed or that should receive more emphasis in the future. The board endorsed plans to continue to refine a minimum data set for Illinois and to expand sampling to fields where more diverse cropping sequences were in use. Some called for development of a more complete or integrated view of farming systems and argued that SQ be considered one part of those systems. Board members also expressed frustration with the economic and social pressures faced by growers in the region, suggesting that those same factors influence SQ by limiting farmers' ability to significantly alter their management strategies in ways that might improve or maintain soil condition. The group concluded with a consensus that mere identification of SQ indicators, including those with the potential to detect SQ trends and link them to management practices, would not likely result in improved stewardship or enhanced farm sustainability.
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SOIL QUALITY, PROCESSES, AND SYSTEMS RESEARCH
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For SQ application, the challenge will be to make environmental and social pressures and the economic costs of management choices, which are apparent over large physical and temporal scales, obvious at the farm scale where key management decisions are made. Given the uncertain links between proposed SQ indices and desired outcomes such as improved yield and water quality, farmers and other land use decision makers currently have little basis for estimating the returns on investment in soil quality (Jaenicke and Lengnick, 1999). The first hurdle will be to overcome a market-based accounting system that fails to incorporate environmental services, and therefore fails to reckon the true costs of pollution or degradation (Daly, 1991). Efforts to accurately value those costs is difficult because the link between soil function and economic costs has rarely been studied. Stewardship ethics and personal factors do influence perceptions of environmental problems, but economic factors are generally more effective in promoting adoption of conservation technologies (Cary and Wilkinson, 1997). However, the balance sheet associated with adoption of practices that favor SQ may not need to outperform the status quo. According to Lohr et al. (1992), landowners presented with relatively equal revenues and feasible management alternatives will likely choose the more environmentally sound option.
To promote sustainable land use practices, work in the SQ arena will need to be integrated into frameworks that predict management effects on a full set of outcomes. In Illinois, a relevant set of management outcomes for row crop production systems might include yield, profit, crop quality, input use efficiency, water quality, C sequestration, and possibly aesthetic outcomes. Results from experimental assessments of SQ like the on-farm ISQI project can be used to explain what has happened to SQ as a result of past management but will not provide a complete basis for predicting what will happen to SQ or desired outcomes, especially if factors influencing the system change. Shifts in crop prices, available technologies, government programs, or environmental disasters such as drought or flooding can radically alter the priority of outcomes. Wagenet and Hutson (1997) suggest using agroecosystem simulation models judiciously in combination with direct measurement of indicators to help farmers capture the dynamism of soil processes and estimate the accumulated effects of management practices or changes in those practices.
Current efforts to identify effective agricultural land use strategies to sequester C provide a real-life example of such a process. Paustian et al. (2002) have developed a methodology that incorporates spatial databases, data from long-term studies, simulation models, and county-level surveys of land use practices to assess the potential for C sequestration in agricultural lands. Andrews et al. (1999) developed a model where SQ research contributes to a multiobjective decision model that would include both economic and environmental end points. Antle et al. (2000) combined a field-scale economic model with a biophysical process model to evaluate policy options that could be used to promote C sequestration in agricultural soils. These examples illustrate how technical information that relates management practices to SQ and broader ecosystem effects can be merged into frameworks to assess economic and environmental outcomes, and thereby facilitate decision making.
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SUMMARY AND CONCLUSIONS
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The ISQI project highlighted issues associated with the SQ concept that influence our ability to use scientific information to assess and ultimately influence land use practices to achieve multiple goals. We found that most farmers appreciate the multifunctionality of soils and believe that SQ research has the potential to be useful in decision making. Even though the desire exists to use SQ information rationally, the means do not. Efforts in the past decade provide an opportunity for researchers to identify means by which they can make a wider array of information useful to decision makers. No doubt the decisions to be made include policy and elements not influenced by the science behind SQ assessments. This fact should not prevent soil and crop scientists from making pertinent information available and meaningful to decision makers by explicitly linking mechanisms to outcomes. By combining interdisciplinary research methods with strategies (which might combine models, indices, expert knowledge, and/or direct measurement) to integrate technical information into useful frameworks, we will be able to fully utilize our scientific understanding of soils to manage the soil resource to achieve desired ends.
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ACKNOWLEDGMENTS
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Research related to ISQI was funded through a Special Research Initiative Hatch grant from the Agricultural Experiment Station of the University of Illinois, through the Illinois Department of Agriculture's Conservation 2000 Program, and a cooperative agreement with the Natural Resources Conservation Service's National Soil Quality Institute. We thank the farmers and board members participating in the ISQI project and Brian Needelman, Georgine Paris, Guangqin Shi, and Jason Tor for their efforts in the field and laboratory.
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ABSTRACT
INTRODUCTION
