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Published online 19 April 2006
Published in Soil Sci Soc Am J 70:1005-1012 (2006)
DOI: 10.2136/sssaj2005.0158
© 2006 Soil Science Society of America
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Symposium: Meaningful Pools in Determining Soil C and N Dynamics

Importance of Soil Organic Matter Fractions in Soil-Landscape and Regional Assessments of Pesticide Sorption and Leaching in Soil

Annemieke Farenhorst*

Dep. of Soil Science, Univ. of Manitoba, Winnipeg, MB R3T 2N2 Canada

* Corresponding author (farenhor{at}ms.umanitoba.ca)


   ABSTRACT
TOP
 ABSTRACT
PESTICIDE USAGES AND RISKS
 SOIL-SORPTION PARTITION...
 STRUCTURAL AND CHEMICAL...
 RECOMMENDATIONS FOR FUTURE...
 REFERENCES
 
Agricultural policy frameworks aim to develop scientifically sound measures that can be used to assess the environmental performance and risks associated with agricultural systems. As part of this assessment, pesticide leaching models are applied at large scales to assess the risk of pesticide groundwater contamination across soil series, agricultural fields, watersheds, or regions. Measurements of pesticide sorption by soil are among the most sensitive input parameters in pesticide leaching models. Soil organic matter (SOM) is the single most important soil constituent influencing pesticide sorption in soils. The interaction of pesticides with SOM is often studied in the laboratory using batch-equilibrium experiments in combination with techniques that quantify chemical and structural characteristics of SOM. This paper reviews these laboratory studies and discusses their importance to the development of agricultural policy frameworks. This review paper was written as part of a symposium on "Meaningful pools in determining soil C and N dynamics" which was held by the SSSA and the Canadian Soil Science Society during the 2004 ASA-CSSA-SSSA International Annual Meetings in Seattle, WA.

Abbreviations: CPMAS 13C-NMR, cross polarization and magic-angle spinning 13C-nuclear magnetic resonance • FA, fulvic acid • HA, humic acid • HOC, hydrophobic organic compound • IROWC-Pest, indicator of risk of water contamination by pesticides • LEACHM, leaching estimation and chemistry model • NAHARP, National Agri-Environmental Health Analysis and Reporting Program • PRZM, pesticide root zone model • SOM, soil organic matter


   PESTICIDE USAGES AND RISKS
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 ABSTRACT
 PESTICIDE USAGES AND RISKS
SOIL-SORPTION PARTITION...
 STRUCTURAL AND CHEMICAL...
 RECOMMENDATIONS FOR FUTURE...
 REFERENCES
 
Pesticides are the active ingredients in pest control products. They are designed to mitigate or prevent the injurious, noxious, or troublesome effects of pests on human life. There are >1200 active ingredients used worldwide in about 8000 pest control products (Copping, 2004; Tomlin, 2005). Most of these active ingredients are synthetic chemicals as opposed to those derived from natural sources. Pest control products often contain other ingredients that increase the effectiveness of active ingredients through improved handling, storage, application, or efficacy. Because of the proprietary nature of the formulations, specific information on these ingredients is difficult to obtain.

Pesticides are important tools in agriculture that help to minimize economic losses caused by weeds, insects, and pathogens. Although their use has helped to increase crop yields and value, they may also contribute to environmental degradation. The extent of pesticide contamination in North America has been recently reviewed for groundwater (Barbash and Resek, 1997), surface water (Larson et al., 1997), the atmosphere (Majewski and Capel, 1995), and stream sediments and aquatic biota (Nowell et al., 1999). Mitigating the risks of environmental contamination is advisable, particularly for controversial but widely-used herbicides such as 2,4-D [(2,4-dichlorophenoxy)acetic acid] and atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine). Increased incidences of cancer in humans has been associated with frequent exposure to these herbicides (Donna et al., 1989; Hoar et al., 1990; Hayes et al., 1995; Mills, 1998; McDuffie et al., 2001; De Roos et al., 2003), although there was no clear evidence of such association in other studies (Burns et al., 2001; Rusiecki et al., 2004). Van Leeuwen et al. (1999) indicated that atrazine contamination levels were associated with decreased colon cancer, presumably because there was increased vegetable production and consumption in areas with greater atrazine use.

Studies as early as the 1950s have demonstrated that SOM is the driving force for the sorption of pesticides by soil, and that this sorption influences pesticide persistence and transport as well as pesticide bioavailability to soil fauna and flora (Wade, 1954; Upchurch, 1958; Upchurch and Pierce, 1958; Upchurch and Mason, 1962; Sheets et al., 1962). Although modern synthetic chemicals tend to be more polar and more soluble in water than their predecessors, SOM remains the single most important soil constituent influencing pesticide sorption in soils (Wauchope et al., 2002) even though other soil properties such as the nature and amount of clay could also impact pesticide sorption. A good understanding of the interaction between currently used pesticides and SOM is therefore important for assessing the risk of pesticide transport from agricultural fields into the broader environment.

Studies on the interaction between pesticides and SOM have moved from crude assessments made over half a century ago to molecular level measurements in more recent years. Although the need for molecular level measurements is widely discussed by the scientific community, funding for such studies is becoming increasingly dependent on actual evidence of how this scientific knowledge will benefit society. It is challenging to provide this evidence particularly because molecular level measurements are highly-specialized, labor-intensive, and costly. In addition, assessments of the risk of pesticide transport from agricultural fields to the broader environment are typically performed at large scales such as across soil series, agricultural fields, watersheds, or regions. There has been only a limited discussion in the literature on how very detailed measurements on pesticide–SOM interactions could be helpful in analyzing risk at large scales.

The objective of this paper is to review the current knowledge of pesticide sorption by SOM in relation to the usefulness of this knowledge to the analysis of risk of pesticide leaching to groundwater at the large scale.


   SOIL-SORPTION PARTITION COEFFICIENTS IN PESTICIDE LEACHING MODELS
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 PESTICIDE USAGES AND RISKS
 SOIL-SORPTION PARTITION...
STRUCTURAL AND CHEMICAL...
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The risk of pesticide off-site movement can be assessed using mathematical models such as PRZM (pesticide root zone model) (Carsel et al., 2003), LEACHM (leaching estimation and chemistry model) (Hutson, 2003), and MACRO (Jarvis, 2001). The PRZM and MACRO have been used to assess the risk of pesticide leaching to ground water as part of policy analyses on pesticide registrations in the European Union (Dubus et al., 2003). The PRZM, LEACHM, and MACRO are also being used in the development of the indicator of risk of water contamination by pesticides (IROWC-Pest) under the National Agri-Environmental Health Analysis and Reporting Program (NAHARP), Agriculture and Agri-Food Canada (Cessna et al., 2004). The NAHARP is bridging the gap between science and policy by developing scientifically sound indicators that can be used to assess the environmental performance and risks associated with agricultural systems. The IROWC-Pest will provide relative estimates of the risk of water contamination by pesticides by comparing risk among all agricultural soils across Canada and comparing changes in risk across time. The purpose of the IROWC-pest is to improve the rate and the extent to which farmers adopt beneficial management practices, thus ensuring adequate pest control while minimizing pesticide environmental contamination.

Sorption-partition coefficients (measures of pesticide sorption by soil) are among the most sensitive input parameters in pesticide leaching models (Boesten and van der Linden, 1991). Failure to accurately describe soil-partition coefficients in soils could create large uncertainties in the prediction of pesticide loss at large scales (Dubus et al., 2003). There are excellent review articles available on the theory and application of sorption partition coefficients (Clapp et al., 2001; Wauchope et al., 2002).

Sorption-partition coefficients are determined by batch-equilibrium experiments where a small amount of whole soil or one of its components is shaken with a solution of pesticides until equilibrium conditions are reached. When a range of concentrations of pesticide solutions are being used, the Freundlich sorption coefficient, Kf (e.g., in g1–1/n Kg–1 L1/n), is calculated:

Formula
where Cs = the amount of pesticide in soil at equilibrium [e.g., in g Kg–1], Ce = the amount of pesticide in solution at equilibrium [e.g., in g L–1], and 1/n = the dimensionless Freundlich constant describing nonlinearity. Although Kf, when reported with 1/n, provides a more comprehensive measure of the extent of sorption of pesticides by soil, this coefficient is often replaced in pesticide leaching models by the soil sorption coefficient, Kd (e.g., in L Kg–1). One reason for this is that Kd is more easily determined because only one concentration of a pesticide solution is being used: Kd = Cs/Ce. Currently, there are no standard protocols on the range of concentrations of pesticide solutions recommended for use in batch-equilibrium procedures. Ideally, this concentration range should encompass the point (coordinate) at which Kd or Kf is evaluated; in the standard Freundlich Equation, K is always evaluated at Ce = 1 (Log Ce = 0), regardless of which unit system being used. For most pesticides, Kd values tend to decrease when the concentration of the initial pesticide solution increases (Fig. 1 ) because pesticides increasingly compete for the limited number of available sorption sites in SOM. Although Kf is less sensitive to changes in the range of concentrations of initial pesticide solutions (Table 1), the nonlinearity of the isotherm increases (1/n decreases) with greater concentrations of initial pesticide solutions due to the progressive saturation of the available sorption sites in SOM. There are other challenges in utilizing Freundlich isotherms in pesticide leaching models, particularly if these models are being applied across soils or regions. Theoretically, Kf values cannot be directly compared if 1/n differs between soils (Bowman, 1981). It is also difficult to compare published Kf values among samples since researchers typically use different sets of units for Ce and Cs. Improved ways to compare Freundlich isotherms among samples have been proposed (Bowman, 1982; Chen et al., 1999), but this information has not been integrated in current pesticide leaching models.


Figure 1
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  		Fig. 1. The effect of the concentration of the initial herbicide solution on the extent of 2,4-D sorption in a Long Plain sandy loam soil as determined by a batch-equilibrium experiment that utilized a 1:2 soil–solution ratio. The soil was obtained (0–10cm) from an agricultural field in Manitoba, Canada. Soil organic carbon content is 0.6%, soil pH is 7.7, and soil clay content is 13%. Data points are mean values (triplicates). Data from Reimer (2004).

 

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  		Table 1. The effect of the concentration of the initial herbicide solutions on the Freundlich sorption coefficient (Kf) and the dimensionless Freundlich constant (1/n) in a Long Plain sandy loam soil as determined by a batch-equilibrium experiment that utilized a 1:2 soil–solution ratio. Soil organic carbon content is 0.6%, soil pH is 7.7, and soil clay content is 13%.{dagger} Data from Reimer (2004).

 
It has been proposed that SOM is a dual-mode sorbent with both flexible (expanded) and rigid (condensed) domains (Xing and Pignatello, 1997). The sorption of hydrophobic organic compounds (HOCs) by SOM occurs through partitioning into both the flexible and rigid domains, as well as though adsorption-like interactions (micropore-filling retention) that occur at the surface (intramatrix) of the rigid domain (Xing, 2001a; Ran et al., 2002). As such, the flexible domain generates a linear sorption isotherm (1/n = 1), whereas the rigid domain with competitive adsorption generates a nonlinear sorption isotherm (1/n != 1) (Gunasekara and Xing, 2003). The nonlinearity of Freundlich isotherms has been attributed to the sorption of HOCs by both aromatic and aliphatic moieties in SOM (Chefetz et al., 2000; Xing, 2001a, 2001b; Mao et al., 2000; Salloum et al., 2002) because both moieties exist in rigid and flexible domains (Gunasekara and Xing, 2003). Since 1/n is one of the most sensitive input parameters in many pesticide leaching models (Dubus et al., 2003), the integration of the dual-sorbent model with current pesticide leaching models could ultimately lead to more accurate predictions of pesticide fate in soils.

When Kf or Kd values are not available, users of pesticide leaching models utilize the soil organic carbon sorption coefficient, Koc, which reflects the sorption of a pesticide per unit soil organic carbon and is a universal approach to normalize pesticide sorption across a range of soil types (Wauchope et al., 2002). The value of Koc for a given pesticide is readily obtained from a pesticide database (e.g., Wauchope et al., 1992). This value is then multiplied by the fraction of organic matter in soil (foc) to obtain Kd. Since foc can be derived from values of soil organic carbon contents in soil databases, this approach is practical for calculating Kd values for a wide range of soils. Unfortunately, the reliability of this approach is unsatisfactory because the extent of pesticide sorption per unit organic carbon varies among soils (Wauchope et al., 2002) and even across slope positions within agricultural fields (Stephens, 2003; Gaultier et al., 2006). Consequently, improved knowledge of how the extent of pesticide sorption per unit organic carbon varies among soils should improve the applicability and accuracy of pesticide leaching models at large scales. Several researchers have suggested that sorption-partition coefficients such as Koc can be calculated using the structural parameters of SOM (Gauthler et al., 1987; Chen et al., 1996).


   STRUCTURAL AND CHEMICAL CHARACTERISTICS OF SOM AND PESTICIDE SORPTION
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Soil organic matter has a wide range of physical, chemical, and biological characteristics. It has been demonstrated that humified matter is more chemically reactive with pesticides than nonhumified matter (Kozak et al., 1983; Gaillardon et al., 1983; Payá-Pérez et al., 1992; Senesi et al., 1997; Fig. 2 ). Humified matter is composed of humic substances such as humic acids (HAs), fulvic acids (FAs), and humin. Most soils are relatively rich in HAs (Martin and Haider, 1971; Stevenson, 1972), and these HAs are more chemically reactive with pesticides than FAs or humin (Hayes, 1970; Khan, 1972; Stevenson, 1972; Senesi, 1992; Senesi et al., 2001). Much of our knowledge of pesticides–humic substances interactions has been derived by isolating and separating HAs, FAs, and humin from soil by chemical means followed by measurements of pesticide sorption onto these fractions (Damanakis et al., 1970; Martin-Neto et al., 1994; Piccolo et al., 1996; Clapp et al., 1997; Senesi et al., 2001). Although fractionations by chemical means are more relevant than extractions that are based on physical means (2005, unpublished data), it has long been debated whether such studies are representative of what is occurring in agricultural fields (McGlamery and Slife, 1966; Weed and Weber, 1974; Ding et al., 2002a; Tan, 2003). For example, the extraction and separation of humin in soil results in the exposure of available binding sites, which would not be available for pesticides under natural conditions because these sites are occupied in whole soils by HAs and FAs (Salloum et al., 2001; Gunasekara and Xing, 2003). Determining pesticide sorption on whole soils, and then isolate SOM fractions in these soils for correlation analyses with pesticide sorption, is thus a better approach to achieve an understanding of the importance of humic substances to pesticide sorption.


Figure 2
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  		Fig. 2. The effect of soil organic matter characteristics on the sorption of 2,4-D. Data reflects mean values and standard deviation (triplicates). Data from Halabicki-Picton (2003).

 
Cross polarization and magic-angle spinning 13C-nuclear magnetic resonance (CPMAS 13C-NMR) spectroscopy is an important technique for characterizing the structural and chemical characteristics of humic substances and their interactions with organic chemicals (Gauthler et al., 1987; Chen et al., 1996; Piccolo et al., 1998; Ahmad et al., 2001; Xing, 2001a; Salloum et al., 2001, 2002; Ran et al., 2002; Ding et al., 2002b; Simpson, 2005, this issue). Much attention has been directed to separating aromatic and aliphatic moieties in SOM in relation to their reactivity to low polar pesticides and other HOCs. There is evidence that HOCs have a strong affinity for aromatic moieties of SOM, including HOCs such as carbaryl (1-naphthyl methylcarbamate) (Ahmad et al., 2001), metolachlor [2-chloro-N-(2-ethyl-6-methyphenyl)-N-(2-methoxy-1-methylethyl)-acetamide] (Ding et al., 2002b), naphthalene (Xing, 2001a), {alpha}-naphthol (1-Hydroxynaphthalene) (Chen et al., 1996), phenanthrene, (Huang and Weber, 1997; Xing, 2001a), phosalone (S-6-chloro-2,3-dihydro-2-oxobenzoxazol-3-ylmethyl O,O-diethyl phosphoro-dithioate) (Ahmad et al., 2001), and pyrene (Gauthler et al., 1987). Using samples from 27 soils under different vegetation in several ecological zones in Australia and Pakistan, Ahmad et al. (2001) demonstrated that the Koc of carbaryl and phosalone is strongly, positively correlated with the aryl and O-aryl structural components (fraction of aromatic C) of SOM. If the degree of aromaticity of SOM is indeed a reliable parameter for the prediction of Koc (Gauthler et al., 1987; Ahmad et al., 2001), large scale assessments of pesticide sorption by soil will benefit from classifying soils based on their degree of SOM aromaticity. Such classification may be feasible because the degree of aromaticity of SOM is influenced by factors such as geological diagenesis, pedogenesis, and humification (Grathwohl, 1990; Chen and Pawluk, 1995; Xing, 2001b; Cuypers et al., 2002), as well as by land management practices such as tillage management and the application of sewage sludge (Stearman et al., 1989; Senesi et al., 1996; Ding et al., 2002a). There is also general agreement that SOM becomes more aromatic and less aliphatic with increasing soil depth (Xing and Chen, 1999; Chen and Pawluk, 1995; Ding et al., 2002a).

It is difficult to assess whether or not knowledge of the size of aromatic pools in SOM and their interaction with pesticides will provide more definite answers on how the strength of pesticide sorption varies among and within agricultural soils. Specifically, recent studies that emphasize the strong affinity of HOCs for aliphatic moieties of SOM cannot be ignored (Li et al., 2003). Hydrophobic organic compounds such as naphthalene, phenanthrene, and pyrene are strongly sorbed by aliphatic moieties (Chefetz et al., 2000; Mao et al., 2000; Salloum et al., 2002; Gunasekara and Xing, 2003). In addition, Piccolo et al. (1998) demonstrated that the sorption of the relatively polar herbicide atrazine was better correlated with aliphatic HA than aromatic HA.

Most of the above studies examined pesticide sorption by comparing soils among regions that have different geological and climatic characteristics. However, it has been demonstrated that spatial variability of pesticide sorption occurs even within small geographical units such as soil-landscapes (Novak et al., 1997; Oliveira et al., 1999; Farenhorst et al., 2001, 2003; Liu et al., 2002; Stephens et al., 2002; Coquet, 2002). A greater understanding of the spatial variability of pesticide sorption within geographical units will strengthen the accuracy of estimates of soil-sorption partition coefficients for geographical units such that pesticide leaching models could be applied to large scales with greater confidence (Dubus et al., 2003). Digital terrain modeling can help to provide quantitative information on the variability of soil properties within soil-landscapes and regions (Pennock et al., 1987; McKenzie and Ryan, 1999; MacMillan and Pettapiece, 2000; Florinsky et al., 2002), and is used to classify soil-landscapes into homogeneous units with similar water distribution characteristics and soil development. Digital terrain modeling has shown its usefulness in improving the prediction of the spatial variability of soil-partition coefficients within agricultural fields (Farenhorst et al., 2003).

The spatial distribution of herbicide sorption within agricultural fields has been examined for alachlor [2-Chloro-2'-6'-diethyl-N-(methoxymethyl)-acetanilide] (Liu et al., 2002), atrazine (Novak et al., 1997; Liu et al., 2002), imazethapyr {2-[4,5-dihydro-4-methyl-4-(1-methylethyl)-5-oxo-1H-imadazol-2-yl]-5-ethyl-3-pyridinecarboxylic acid} (Oliveira et al., 1999), 2,4-D (Farenhorst et al., 2001, 2003; Stephens et al., 2002), and other herbicides (Wood et al., 1987; Mallawatantri and Mulla, 1992). These studies have demonstrated that soil-partition coefficients vary within agricultural fields due to differences in soil properties across slope positions (Novak et al., 1997; Farenhorst et al., 2001). This may be because soil properties vary due to the influence of topography on hydrologic and pedogenic processes (Gerrard, 1981). Cultivation of agricultural fields also increases the spatial variability of soil properties in soil-landscapes because of the redistribution of topsoil from upper slope to lower slope positions by tillage (Gregorich and Anderson, 1985; Lindstrom et al., 1990, 1992; Govers et al., 1994, 1999; Lobb and Kachanoski, 1999a, 1999b). In addition to tillage erosion, wind and water erosion may amplify spatial differences in soil characteristics within agricultural fields (Sutherland and de Jong, 1990; Schumacher et al., 1999; Lobb et al., 2004).

Differences in the amount of SOM across slope positions is an important factor in explaining the variation of herbicide sorption within fields (Novak et al., 1997; Farenhorst et al., 2003). Soils from lower slope positions contain more SOM and therefore demonstrate greater Kd and Kf values compared with soil from upper slope positions. For ionizable herbicides such as atrazine and imazethapyr, soil pH also had an effect on the distribution of soil-sorption partition coefficients across agricultural fields (Novak et al., 1997; Oliveira et al., 1999). This is not surprising since it is well known that the extent of pesticide sorption by soil can vary among soils due to the influence of soil pH on the charge density of SOM as well as on the degree of ionization of pesticides (Hayes, 1970; Weed and Weber, 1974). This effect is noticeable when the pKa (weakly acidic pesticides) or pKb (weakly basic pesticides) are within about 2 units of the soil pH. Otherwise, soil pH can be expected to have little influence on pesticide sorption by soil. For example, in western Canada, weakly acidic herbicides such as 2,4-D (pKa = 2.64; Ahrens, 1994) are commonly applied to agricultural fields characterized by calcareous soils. As such, no significant correlation was found between the pH of these soils and their sorption to 2,4-D (Farenhorst et al., 2001, 2003; Gaultier et al., 2006) because the range in soil pH in these fields ranges from neutral to slightly alkaline which is well above the pKa of 2,4-D. However, within these calcareous soil-landscapes, Koc varies between upper and lower slope positions (Stephens, 2003; Gaultier et al., 2006) and even within slope positions over short distances (Fig. 3 ). On the basis of preliminary results in our laboratory, it appears that differential SOM characteristics within soil-landscapes have a profound effect on the extent of 2,4-D sorption by soil (Farenhorst et al., 2005). Specifically, 2,4-D sorption by soil was well correlated with alkaline-extracted fractions of HAs and FAs, but poorly correlated with pyrophosphate-extracted fractions of HAs and FAs (Farenhorst et al., 2005). We encourage researchers to examine the effect of topography on SOM characteristics as this would improve quantitative information on the spatial variability of soil properties within soil-landscapes and could ultimately lead to better predictions of pesticide leaching losses at large scales.


Figure 3
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  		Fig. 3. Soil pH and Koc values for 2,4-D in an Ap-horizon along a 360-m transect running west to east in an agricultural field near Miami, Manitoba. Details on this study can be found in Gaultier et al. (2006). Data points are mean values (duplicates). The sample numbers 1, 2, 12, 20, 34, and 62 were further analyzed (triplicates) for soil organic matter characteristics (Farenhorst et al., 2005). The soil organic carbon content of these samples is given in parentheses after their numbers.

 

   RECOMMENDATIONS FOR FUTURE STUDIES ON PESTICIDE–SOM INTERACTIONS
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 PESTICIDE USAGES AND RISKS
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 STRUCTURAL AND CHEMICAL...
 RECOMMENDATIONS FOR FUTURE...
REFERENCES
 
It has already been demonstrated that the degree of aromaticity of SOM can be used to better predict the Koc of carbaryl and phosalone across soil types in Australia and Pakistan (Ahmad et al., 2001) but it is unclear whether such an approach can be applied to a wider range of pesticides and soils. Assuming that structural characteristics of SOM can be used to adequately predict sorption coefficients, there is a need for additional molecular level measurements to be conducted on a much wider range of pesticides applied to a much wider range of agricultural soils before information on structural characteristics of SOM can be integrated into pesticide leaching models. The integration of molecular level measurements into policy analysis on the performance and risks associated with pesticide use in agricultural systems will be enhanced if the structural characteristics of SOM can be predicted using soil type and land management.

Many CPMAS 13C-NMR studies have been performed using organic soils. Agricultural soils typically have much lower soil organic carbon contents. Although this can provide challenges from an analytical point of view, the mineral soils deserve much greater attention because they are the ones most frequently exposed to a wide range of pest control products. Studies using mineral soils would also need to direct attention to the distribution of SOM characteristics within agricultural fields.

Interactions of pesticides with specific pools of SOM are often analyzed without considering the size, characteristics, and interactions of these pools in the soil itself. It has been well documented that because of modifications caused by extraction methods in separating SOM fractions from soil, pesticide sorption by specific SOM fractions are not representative of what occurs in agricultural fields. It is therefore important that if the studies are to relate the characteristics of SOM in whole soils to pesticide fate, they should focus on determining the sorption of pesticides in whole soils rather than selected fractions.

The type of pesticides being selected in a given study is based on several factors, including the availability of suitable analytical techniques, the extent to which the selected pesticide is being used in the region or country in which the researcher operates, as well as the availability of research funds to obtain the selected pesticide in radiolabeled form. A greater collaboration among research groups is warranted so that a wider range of pesticide sorption behavior can be examined for a suite of selected, representative soil samples. This will provide a more comprehensive and definitive understanding of how structural differences in SOM can be used to explain variations in the extent of pesticide sorption within and across agricultural fields.


   ACKNOWLEDGMENTS
 
I thank Drs. Cindy Cambardella, Ed Gregorich, and Dan Olk for giving me the opportunity to participate in the symposium. I thank the anonymous reviewers for their useful comments on an earlier draft of this manuscript. I would also like to thank my research associates, Drs. Ross McQueen and Ibrahim Saiyed, for their technical assistance in preparing this manuscript. In addition, I thank my graduate students, Marguerite Reimer, Jeanette Foidart, and Paula Halibicki for giving me permission to display some of their data in this manuscript. These data were collected with financial support from the Natural Science and Engineering Research Council (NSERC) of Canada.

Received for publication May 20, 2005.


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