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Published online 27 February 2006
Published in Soil Sci Soc Am J 70:651-659 (2006)
DOI: 10.2136/sssaj2005.0036
© 2006 Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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Soil & Water Management & Conservation

Influence of Tillage Practices on Soil Structural Controls over Carbon Mineralization

Gayoung Yoo* and Michelle M. Wander

Dep. of Natural Resources and Environmental Sciences, Univ. of Illinois, N215 Turner Hall, 1102 S. Goodwin Ave., Urbana, IL 61801

* Corresponding author (gayoung.yoo{at}gmail.com)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
The influence of tillage practices on soil organic carbon (SOC) dynamics is manifested indirectly through the modification of soil structure. This study was conducted at two sites in Illinois where long-term use of conventional (CT) and no tillage (NT) practices has increased SOC at Monmouth, a silt loam, but not at DeKalb, a silty clay loam soil with higher SOC contents. We evaluated whether soil structural quality could be related to observed SOC mineralization and explain the inconsistent influence of tillage on SOC stocks. Soil physical parameters and soil CO2 evolution rates were measured in 2000, 2001, and 2002. At DeKalb, there was no difference in the mean (µmol m–1 s–1) or specific (µgCO2 s–1/µg SOC) SOC mineralization rates of NT and CT soils. In Monmouth, mean and specific SOC mineralization rates were greater from soils under CT than NT management. This indicates use of NT practices had increased physical protection of SOC at that site. The Q10 equation, which is based on soil temperature and moisture, better explained CO2 efflux in DeKalb than in Monmouth. The poorer fit of the equation in Monmouth reflects its reliance on gravimetric moisture content, which inadequately describes the status of soil water influencing heterotrophic activity. The least limiting water range (LLWR), which integrates the affects of clay content, bulk density, and soil moisture on biological activity and predicted observed soil CO2 efflux patterns (R = 0.600, p = 0.0025) better than any other physical parameter, indicated use of NT practices at Monmouth increased soil compaction or strength enough to reduce C mineralization. In DeKalb, where soils have an inherently high capacity to protect SOC from decay, tillage has had no influence on SOC dynamics. The variable affect of tillage practices on C sequestration were explained by soil physical properties.

Abbreviations: CT, conventional fall tillage • LLWR, least limiting water range • NT, no tillage • SOC, soil organic carbon


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
SOIL ORGANIC C STORAGE is widely reported to be increased by the adoption of NT practices (Kern and Johnson, 1993; Lal et al., 1994; Moldenhauer et al., 1995; Campbell et al., 1995; Campbell et al., 1996). However, use of NT practices sometimes fails to increase SOC sequestration in a whole soil profile relative to CT counterparts (Dick et al., 1991; Paustian et al., 1995; Angers et al., 1997; Needleman et al., 1999). In many fine-textured soils, use of NT practices has increased SOC contents in the surface at the expense of SOC stored within the rooting zone (Wander et al., 1998; Kay and VandenBygaart, 2002). When C inputs from crop residues do not account for differences in the SOC content of soils under NT and CT management and soil erosion by wind and water is not a significant factor (Hussain, 1997; Alvarez et al., 1998; Yang and Wander, 1999), attempts to understand when and why tillage practices vary in their effect on SOC conservation often focus on C mineralization (Alvarez et al., 1995; Dick et al., 1991; Angers et al., 1997; Karunatilake et al., 2000). Soil CO2 efflux patterns during the growing season may predict SOC storage patterns in soils under NT and CT practices. In many cases, soils under CT practice have greater CO2 evolution rates than soils under NT practice because tillage modifies the decomposition environment through aerating the soil, breaking up soil aggregates, and incorporating residues into the soil profile (Beare et al., 1994; Fortin et al., 1996; Lee et al., 1996; Prior et al., 1997; Six et al., 2002). However, reports of tillage-based losses in SOC may over emphasize the huge CO2 emission that occurs immediately after plowing (Reicosky and Lindstrom, 1993; Reicosky, 1997; Ellert and Janzen, 1999). The post-tillage CO2 flush may not be a significant contributor to the yearly SOC balance because it is a short-term process that is primarily due to passive degassing after the soil resistance to gas transfer is decreased by plowing (Reicosky and Lindstrom, 1993; Reicosky, 1997). Many observations suggest that CT soils do not have significantly greater soil CO2 evolution rates than NT soils during the growing seasons (Hendrix et al., 1988; Franzluebbers et al., 1995; Alvarez et al., 1995). In some cases, soil CO2 evolution has even been found to be greater from NT than CT soils because the accumulation of SOC in the surface of NT soils enhances infiltration and water holding capacity (Blevins, 1984; Linn and Doran, 1984; Hendrix et al., 1988; Follett and Schimel, 1989; Franzluebbers et al., 1995).

This study investigated two sites where the use of CT and NT practices for over a decade has had different influences on SOC storage. A comparison based on equivalent mass indicated that in one site, the use of NT practices failed to increase SOC storage in the soil profile while in the other site, soils under NT management had higher SOC contents than soils that were conventionally managed (Wander et al., 1998). Even though there is year-to-year variation in the influence of tillage on crop yields, no consistent effect of tillage on crop yields has been reported (Northern Illinois Agronomy Research Center, 1992, 1993, 1994, 1995, 1996, 1997; Northwestern Illinois Agricultural Research Center, 1992, 1993, 1994, 1995, 1996, 1997). Both sites are quite level and surface erosion is not an important issue. Accordingly, differences in soil CO2 flux observed during the growing season were expected to concur with observed differences in the SOC contents of CT and NT soils at these two sites.

In many studies, soil CO2 evolution rates are well explained by changes in soil temperature and moisture using a Q10 equation (Schlentner and Van Cleve, 1985; Buyanovsky et al., 1986; Prior et al., 1997; Davidson et al., 2000; Fang and Moncrieff, 2001). Even though soil temperature is one of the most important factors influencing soil respiration, tillage based differences in soil CO2 evolution are not fully explained by changes in soil temperature because differences in temperature of soils under different tillage practices are generally small and not significant compared with much larger seasonal temperature fluctuations (Franzluebbers et al., 1995). On the other hand, differences in soil moisture content under different tillage systems are more often reported to be large enough to influence soil CO2 evolution rates (Franzluebbers et al., 1995; da Silva et al., 2001). This is probably related to the fact that soil structure, which is changed by tillage practices, partially determines soil moisture content (Skopp et al., 1990; Jensen et al., 1996). Ilstedt et al. (2000) suggested that soil moisture available to support microbial activity should be determined in the context of structure. Even though bulk density and penetration resistance are commonly used measures of soil structure (Torbert and Wood, 1992; Liebig et al., 1995; De Neve and Hofman, 2000), they do not describe its interactions with moisture (Soane et al., 1981; Chen et al., 1998).

A multi-factor parameter might better represent the complex relationships that exist between soil structure and moisture. The LLWR, which integrates several soil physical parameters, has been proposed as an index of soil structural quality (da Silva et al., 1994; Carter et al., 1999; Tormena et al., 1999; Benjamin et al., 2003). The LLWR is the size of the range of volumetric soil water contents (cm3 cm–3) within a soil where biological processes are not limited by soil water or O2 availability (da Silva and Kay, 1997a, 1997b). Although the concepts of LLWR have been applied to processes in plants (da Silva and Kay, 1996; Sadras and Milroy, 1996), they have rarely been applied to microbial processes such as C mineralization (Drury et al., 2003). To our knowledge, this is the first attempt to relate LLWR to soil CO2 evolution. Based on the concept of LLWR developed for plant growth, biological activity is reduced as LLWR declines; We hypothesized that this concept should apply to SOC mineralization.

The experimental objectives of this work were to: (i) investigate soil CO2 evolution patterns at sites where tillage practices have had varied influences on SOC storage; (ii) determine the important site-based factors controlling different patterns in soil CO2 evolution; and (iii) evaluate LLWR as a predictive index of soil structural quality and soil CO2 evolution.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Experimental Sites
The experimental trials are located at two University of Illinois Agronomy Research Centers in DeKalb and Monmouth, IL. Soils at these locations are a Drummer silty clay loam (poorly drained, fine-silty, mixed, mesic Typic Haplaquoll) and a Muscatine silt loam (somewhat poorly drained, fine-silty, mixed, mesic Aquic Hapludoll), respectively. This study was conducted in the corn (Zea mays L.) phase of a corn–soybean [Glycine max (L.) Merr.] rotation. The main treatments, established in 1985, were conventional fall tillage (CT), which consisted of moldboard plowing after corn and chisel plowing after soybean, and no tillage (NT) practices. A randomized complete block design with three replicates was used for allocation of treatments to plots. There were three blocks per location and each block had two different tillage treatments.

Soil Parameters
Two collars made of PVC (10 cm i.d., 4.5 cm height) were installed approximately 2.54 cm (1 in) deep into, and extending approximately 2.54 cm (1 in) above, the soil surface in interrows of each plot right after corn was planted, kept there until just before fall tillage, and reinstalled for post-tillage measurements. These rings were used to seal the soil chamber of a Li-Cor 6400 (Li-Cor, Lincoln, NE) to measure soil CO2 evolution rates. Soil CO2 evolution rates were measured biweekly during the growing season (from May to September) in 2000, once a month from May to November in 2001, and every 2 mo from January to September in 2002. On the dates that soil CO2 evolution was measured, soil temperature and soil moisture content were determined at 0 to 5, 5 to 15, and 15 to 30 cm. To measure soil temperature in 0- to 5-, 5- to 15-, and 15- to 30-cm depths, copper-constantan thermocouples were placed in holes at 2.5-, 10-, and 22.5-cm positions in a PVC tube (1.5 cm i.d., 25 cm length) and fixed with paraffin (Meshkat et al., 1998). A tube containing three thermocouples was installed from spring after planting to fall before tillage in the interrow position of each subplot and the thermocouples were read with a digital thermometer (model HH501 DK, Omega Inc., Standford, CT). To determine gravimetric soil water content, two subsamples were taken from each subplot from the interrow position with a soil corer (1.8 cm i. d. and 25 cm in length). Samples were divided into three depths (0–5, 5–15, 15–30 cm) in the field. The subsamples were combined in a plastic bag, and transported on ice to the lab. In the lab, approximately 10 g of soil were taken from each plastic bag and dried in the oven at 105°C for 24 h to determine gravimetric soil water contents. Penetration resistance was measured on the same dates as soil CO2 efflux from May to July in 2000 and 2001. Measurements were limited to the early growing season because the soil became quite hard. Penetration resistance was recorded at 5-, 15-, and 30-cm depths twice in each subplot in the interrow position using a dynamic cone penetrometer (Herrick and Jones, 2002). It had a 30° hardened steel cone with a 20.3-mm diam. base mounted on a 72.4 cm-long, 15.9-mm diam. shaft. Bulk density was determined by the core method (Krzic et al., 2000) twice a year in 2000 and 2001, immediately after planting and after harvest. A splittable core sampler (4.7 cm i.d., 30 cm in length; Forest Supply, Jackson, MS) driven by a Giddings hydraulic soil probe (Giddings Machine Co., Fort Collins, CO) mounted on a truck was used to collect soil samples. Two cores were taken from each subplot. Each core was divided into three depths (0–5, 5–15, 15–30 cm), and samples from each core were combined by depth in a plastic bag in the field. Soil clay content was measured by the hydrometer method using soil samples collected in the spring of 2000 (Sheldrick and Wang, 1993). Twenty grams of soil were dispersed in 150 mL of sodium hexametaphosphate (50 g L–1) for 1 h with shaking on a reciprocal shaker. The suspension was diluted to 1 L in a cylinder with distilled water and mixed thoroughly. Hydrometer readings were taken at 40 s and 6 h after completion of stirring. Mean soil CO2 evolution rates from a unit surface area (a; µmol m–2 s–1) were transformed into the amount of CO2 evolved from the soil surface (b = a x 44 x 0.07850; µg CO2 s–1) covered by the surface area of soil chamber ({pi} x 0.052 = 0.07850 m2). To calculate specific SOC mineralization rates, the amount of CO2 evolved was divided by the total mass of C (µg CO2 s–1/µg SOC). Total mass of C contained in a volume of soil 5 cm in diameter and 30 cm deep (g C kg–1 soil x kg soil m–3) was calculated by multiplying the weighted average of total SOC concentrations in the 0- to 30-cm depth by the corresponding bulk density. Weighted averages of total SOC concentrations in the 0- to 30-cm depth were calculated from SOC values reported in Wander et al. (1998).

Least Limiting Water Range (LLWR)
To construct the LLWR for soils under NT and CT managements at any site, knowledge of field capacity, wilting point, air-filled porosity, and soil strength are needed for the range of bulk densities likely to occur in the field. The bulk density data collected twice a year in 2000, 2001, and 2002 was used to calculate LLWR for each site by tillage combination. The percentage of clay contents used to calculate LLWR were 40.0 and 26.5% for DeKalb and Monmonth, respectively. The percentage of SOC contents were adapted from Wander et al. (1998) and they were 3.53 and 3.77% in the NT and CT soils of DeKalb, respectively and 2.14 and 1.83% in the NT and CT soils of Monmouth, respectively. Pedotransfer functions developed by da Silva and Kay (1997a) were used to model the water release and soil resistance curves needed to calculate LLWR. The pedotransfer functions used to predict the soil water release curve (Eq. [1]) and soil resistance (Eq. [2]) curves follow:

Formula 1[1]

Formula 2[2]
where {theta} is volumetric water content (cm3 cm–3), CLAY is clay content (%) as a weighted average (0–30 cm), SOC is soil organic carbon content (%) in the 0- to 30 -cm depth, Db is bulk density (g cm–3), {psi} is matric suction (MPa), and SR is soil resistance (MPa).

The soil water contents at field capacity ({theta}fc) ({psi} = 0.01 MPa) and at wilting point ({theta}wp) ({psi} = 1.5 MPa) were calculated from Eq. [1]. The soil resistance curve Eq. [2] was used to compute the water content when SR = 2 MPa, which is the point where soil resistance ({theta}sr) becomes limiting. The water content at an air filled porosity of 10% ({theta}afp) was calculated as (total porosity –0.1). Total porosity was calculated using the following equation:

Formula 3[3]
where PD is particle density assumed to be 2.65 g cm–3 (Ilstedt et al., 2000).

We computed the minimum range of volumetric water content (LLWR) where soil biological activities are not limited by soil water availability or soil compaction.

Statistical Analysis
Analysis of variance was performed using the MIXED procedure of SAS (SAS Institute, 2001) on seasonal mean soil CO2 evolution rates, specific SOC mineralization rates, and weighted averages of soil temperature, soil moisture content, bulk density, and penetration resistance representing the 0- to 30-cm depth. We did not consider the depths separately for soil temperature, moisture content, bulk density, and penetration resistance because these parameters were related to soil CO2 efflux measured at the soil surface rather than CO2 production within each soil depth. Tillage, site, and dates were the fixed effects. Year, block (site), year x block (site), and year x tillage were the random effects. Analysis of variance was performed using the MIXED procedure on weighted averages of clay content representing the 0- to 30-cm depth, {theta}fc, {theta}wp, {theta}afp, {theta}sr, and calculated LLWR. Tillage and site were fixed effects and block within site was a random effect. Least square means of mean and specific soil CO2 evolution rates, weighted averages of bulk density, penetration resistance, and clay content in the 0- to 30-cm depth, {theta}fc, {theta}wp, {theta}afp, {theta}sr, and LLWR were used to compare site and tillage effects on these parameters. Pearson's correlation coefficients among specific SOC mineralization rate, soil temperature, soil moisture content, penetration resistance, and bulk density were calculated using the CORR procedure of SAS (SAS Institute, 2001). Specific SOC mineralization rates were used to standardize the effect of SOC content on SOC mineralization. The basic Q10 equation Eq. [4] suggested by Kang et al. (2003) was fitted using the nonlinear procedure of SAS (SAS Institute, 2001) with weighted averages of soil temperature and moisture content collected in 2000 and 2001 from each site.

Formula 4[4]
where SWC is weighted average of gravimetric soil water contents (%) in the 0 to 30 cm; Ts is the weighted average of soil temperature (°C) in the 0 to 30 cm; and b, r, and Q10 are coefficients. The Q10 equation developed from two sites was validated with soil temperature, soil moisture content, and soil CO2 evolution rates measured in 2002. Simple linear regression (SAS Institute, 2001) was used to compare the explanatory power of the model at each site; values of soil CO2 evolution predicted from the Q10 equation were compared with measured data.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Tillage Influence on Mean and Specific Soil Carbon Dioxide Evolution Rates
Overall mean soil CO2 evolution rates did not differ between soils under NT and CT management in DeKalb, but did differ in Monmouth, where mean soil CO2 evolution rates were significantly higher in CT than NT soils (Fig. 1a and Fig. 2 ). Data collected the day after cultivation in June 2001 from CT soils in Monmouth (marked with an asterisk in Fig. 2e), were not included in the analysis because rates were extremely high (20.99 µmol m–2 s–1) and may have included losses derived from degassing. Had those data been included, estimates of the effect of tillage on SOC mineralization in Monmouth would have been even greater. The mean CO2 evolution rates observed were consistent with SOC storage trends previously reported for these sites (Wander et al., 1998); where total SOC storage based on equivalent mass did not differ between NT and CT soils in DeKalb, but in Monmouth, NT soils had significantly larger SOC storage than did CT soils. Seasonal changes in mineralization rates at DeKalb showed that rates generally increased in early summer, declined mid to late season and then tended to rise again in the fall (Fig. 2a and 2b). A less temporally intensive but more extensive sampling in 2002 showed that tillage practices did not alter CO2 efflux rates at DeKalb during the fall and winter months (Fig. 2c). Seasonal CO2 efflux trends in Monmouth were generally similar to those observed in DeKalb, except that efflux from CT soils tended to be higher than from NT soils (Fig. 2d, 2e, and 2f). To avoid measurement of CO2 degassing induced by plowing, fall samples were collected 7 d after fall tillage in 2001. Tillage-induced CO2 degassing was reported to last for 24 h to 3 to 5 d (Reicosky and Lindstrom, 1993). In Monmouth, the soil CO2 efflux rate after tillage was higher than that from the NT soils, whereas in DeKalb, CO2 efflux rates recorded after tillage were similar to flux rates from NT soils (Fig. 2b and 2e). This indicates the variable effect of fall tillage on CO2 emission, which can be related to differences in soil microclimatic conditions that exist following plowing events at each site (Rochette et al., 1991; Rochette and Angers, 1999).


Figure 1
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  		Fig. 1. (a) Seasonal mean CO2 evolution rates and (b) specific mineralization rates of SOC from NT and CT soils in DeKalb and Monmouth, IL. If the letters above data from each location are not the same, then means were significantly different at P < 0.05.

 

Figure 2
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  		Fig. 2. Seasonal soil CO2 evolution rates from (a) DeKalb in 2000, (b) DeKalb in 2001, (c) DeKalb, 2002, (d) Monmouth in 2000, (e) Monmouth in 2001, and (f) Monmouth in 2002. The asterisk in Fig. 2e indicates the position for the outlier that was not used for analysis.

 
Specific SOC mineralization rates were lower in DeKalb than in Monmouth (Fig. 1b). Soil CO2 efflux rates were also similar while SOC contents were greater in DeKalb. This is attributed to the greater protective capacity of the DeKalb soil. Organic matter quality cannot account for these differences in specific mineralization as the proportion of SOC that is chemically labile is similar at the two sites (Wander et al., 1998). The relatively high content and surface activity of clay at DeKalb, which is associated with SOC stabilization (Hassink and Whitmore, 1997; Carter et al., 1999), account for site based differences. Specific mineralization rates were not altered by tillage practices in DeKalb. Franzluebbers et al. (1995) also found no tillage-based differences in specific SOC mineralization rates from a silty clay loam soil subject to a sorghum–wheat/soybean rotation. Alternatively, we found use of NT practices at Monmouth, a silt loam soil, reduced specific mineralization rates. Tillage-based differences in SOC mineralization were amplified at Monmouth when CO2 evolution rates, which are slightly greater in CT soils, were divided by SOC contents, which are slightly reduced. As before, differences in organic matter quality cannot explain these results. The amount of particulate organic matter is actually greater in the surface depth of Monmouth's NT soils than in its CT soils (Wander et al., 1998). Use of NT practices has increased physical protection of SOC at Monmouth but not at DeKalb.

Physical Properties and Soil Carbon Dioxide Evolution
Depth-weighted averages of soil temperature (0–30 cm) did not differ by site or by tillage practice (Tables 1 and 2). However, depth-weighted average of soil moisture contents (0–30 cm) were higher in DeKalb than in Monmouth and did not differ between the NT and CT soils (Tables 1 and 2). Soil bulk density in the 0- to 30-cm depth was greater in Monmouth than in DeKalb (Tables 1 and 2). The lower bulk density in DeKalb is consistent with the higher SOC and clay contents at this site, which Soane et al. (1981) and Chen et al. (1998) also observed. Bulk density was increased in NT soils at both sites, indicating a possible consolidation of soil under NT practice (Franzluebbers et al., 1995; Krzic et al., 2000). Seasonal mean penetration resistance in DeKalb was higher than in Monmouth and was higher in NT than in CT soils (Tables 1 and 2). Higher penetration resistance in soils under NT has also been reported by Taboada et al. (1998) and Ferreras et al. (2000). The high penetration resistance observed in DeKalb demonstrates the extreme texture- and moisture-dependence of this parameter (Gupta and Allmaras, 1987; Lampurlanes et al., 2001; Vyn and Raimbault, 1993; Dexter, 1997; Karunatilake et al., 2000). Use of penetration resistance may not be a suitable means to compare soil structural changes across sites.


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  		Table 1. Variance analysis of mean soil CO2 evolution rates (Mean CO2 min.), specific mineralization rates of total SOC (Specific C min rates), and weighted averages of soil temperature (Temp.), moisture (Moi.), bulk density, penetration resistance (PR).

 

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  		Table 2. The influence of site and tillage practices on physical parameters. Values are weighted averages representing the 0- to 30-cm depth.

 
Soil temperature was positively correlated, and soil water content was negatively correlated with specific C mineralization rates and soil moisture was negatively correlated with penetration resistance and bulk density (Table 3). The importance of the interaction between soil water and structure was reflected in the results from the Q10 equation developed using the data from both sites in 2000 and 2001. The Q10 equation (Eq. [4]) explained 63% of total variation in soil CO2 evolution patterns (Table 4), which was a relatively low degree of fit compared with those of Alvarez and Alvarez (2001) (r2 = 0.72) and Kang et al. (2003) (r2 = 0.84–0.96). This low degree of fit indicates that there are factors other than soil temperature and soil moisture influencing C mineralization. When the CO2 evolution rates predicted by the Q10 equation were regressed against CO2 efflux rates measured in 2002, the Q10 equation had a much higher explanatory power in DeKalb than in Monmouth (Table 4). Gravimetric water contents, which were used in the Q10 equation, may not be the best measure of water status important to heterotrophic activity especially when the water status of soils with different pore structures are compared. Related work suggests that microbial activity is better associated with the status of water holding pores (<30 µm) than the total pore volume (Yoo et al., 2006). Inadequacy of gravimetric water content as measure of soil water status may be more apparent in Monmouth because silty soils are more susceptible to compaction, and thus the loss of water holding pores important to heterotrophic activity, than are heavier textured soils (Horn et al., 1995). Apparently, the increase in water holding pores caused by compaction (Hillel, 1998) has increased intermediate-size pores outside the ideal for heterotrophic activity.


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  		Table 3. Pearson's correlation coefficients among specific C mineralization rates and weighted averages of soil temperature, moisture content, penetration resistance, and bulk density.

 

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  		Table 4. Coefficients and R2 value of the Q10 equation using 2000 and 2001 data and validation for DeKalb and Monmouth by comparison with 2002 results.

 
Least Limiting Water Range and Soil Carbon Dioxide Evolution Patterns
The calculated mean LLWR are reported in Table 5. Values for DeKalb NT and CT soils were 0.032 and 0.054 cm3 H2O cm–3 soil, respectively, while those for Monmouth NT and CT were 0.083 and 0.141 cm3 cm–3, respectively. These values were within the range (0.000–0.310 cm3 cm–3) that da Silva and Kay (1997a) calculated LLWRs for 64 different soils in Ontario, Canada. The findings of others (Tormena et al., 1999; Carter et al., 1999) that the LLWR of CT soils are higher than that of NT soils are consistent with our results from Monmouth. The relatively low LLWR observed in DeKalb indicates that soil structure limits water availability for biological activity in both the NT and CT soils. This is supported by findings of da Silva and Kay (1997a) and is consistent with the notion that physical protection of SOC is more important at this location. Tillage practices can only affect protection manifest at a larger physical scale than that exerted by soil particles. Use of NT practices resulted in lower LLWR at Monmouth. This indicates that soil structure imposes a greater limitation on SOC mineralization in the NT than in the CT soils. The size of the LLWR was positively correlated with specific SOC mineralization rates considered across sites (Pearson's correlation coefficient = 0.60, p = 0.0025), and LLWR predicted observed tillage-based differences in soil CO2 efflux patterns better than any individual physical parameter. The {theta}fc for DeKalb was higher than total porosity calculated from bulk density; this is likely the result of swelling in this soil which contains an abundance of high activity clay. This was not the case in Monmouth, where soil clay content and swelling potential is lower. The characteristics of the upper and lower limits of LLWR differed for the DeKalb and Monmouth soils. In both sites, the upper limits of the index were defined by the {theta}afp regardless of tillage practice (Table 5), while in DeKalb, the lower limits were defined by {theta}wp, and in Monmouth, by {theta}sr. This result is consistent with those based on the Q10 equation and further suggests that reduction in water holding pores within the LLWR induced by soil compaction limits SOC mineralization rates in Monmouth.


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  		Table 5. Least square means of least limiting water ranges (LLWR) and values of limits for LLWR.

 

   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
The influence of tillage on soil CO2 evolution rate and its relationship with soil physical factors was investigated at sites where use of CT and NT practices has had variable influence on SOC contents. None of the individual soil physical parameters measured varied among sites in a manner that could explain the different effects tillage practices had on SOC stocks, mean within season soil CO2 evolution rates, or specific SOC mineralization rates. Correlations among soil physical parameters showed that there are significant interactions between soil moisture, bulk density, and penetration resistance. Results from specific SOC mineralization rates and the Q10 equation suggest that differences in soil structural controls over SOC dynamics are important in these sites. In DeKalb, physical protection imparted by high clay content limits SOC mineralization regardless of tillage practices; whereas, in Monmouth, SOC is less protected but SOC mineralization is relatively reduced in the NT soil where soil is more compacted. The LLWR effectively described how soil moisture and structure interact to influence SOC dynamics. Least limiting water range was better correlated with specific SOC mineralization rates than bulk density or penetration resistance. Penetration resistance is a particularly ineffective way to predict compaction because of its high dependence on soil texture and moisture content. By considering physical factors that influence the availability of soil moisture, we were able to explain variable tillage affects on SOC mineralization. Use of an integrative measure, such as the LLWR, may help us predict whether or not the adoption of NT practice will increase SOC sequestration.

Received for publication January 29, 2005.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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The SCI Journals Agronomy Journal Crop Science
Journal of Natural Resources
and Life Sciences Education		 Vadose Zone Journal
Journal of Plant Registrations Journal of
Environmental Quality		 The Plant Genome