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Published online 8 January 2009
Published in Agron J 101:175-183 (2009)
DOI: 10.2134/agronj2008.0184
© 2009 American Society of Agronomy
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Rotational and Cover Crop Determinants of Soil Structural Stability and Carbon in a Potato System

Edgar A. Po, Sieglinde S. Snapp* and Alexandra Kravchenko

Dep. of Crop and Soil Sciences, Michigan State Univ., Kellogg Biological Station, East Lansing, MI 48824-1325

* Corresponding author (snapp{at}msu.edu).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Understanding processes that ameliorate structural degradation in sandy soils is particularly important in intensively managed potato (Solanum tuberosum L.) systems. Seven 2-yr potato rotation systems were evaluated over 3 yr in an irrigated field trial comparing winter management systems bare (B) and cover crops: rye (Secale cereale L.; R), rye-hairy vetch (Vicia villosa Roth; RV) mixture and red clover (Trifolium pratense L.; C). Crops rotated with potatoes (P) were snap bean (Phaseolus vulgaris (L.); SB), wheat (Triticum aestivum L.; W) and sweet corn (Zea mays L.; SC). The systems consisted of: S1 PBSBB; S2 PRSBR; S3 PRSCB; S4 PWWR; S5 PWWCC; S6 PRVSBRV; and S7 PRVSCRV, both entry points evaluated each year. Carbon inputs above- and belowground were measured and systems grouped as low (S1 and S4), medium (S2 and S6), and high (S5, S3 and S7): 1.2, 2.0, and 2.8 Mg C ha–1, respectively. Response variables included water stable aggregate (WSA) size fractions, macroaggregates (≥0.25 mm) and microaggregates (<0.25 mm), mean weight diameter (MWD), soil C, nitrogen mineralization potential (NMP), and potato tuber yield. Systems with SC contributed twofold higher biomass than rotations with W or SB, and the presence of RC contributed higher amounts of carbon (1.2 Mg ha–1) compared to R (0.7 Mg ha–1). Only the entry year influenced macroaggregates in 2001; both entry year and cropping system influenced aggregate size classes in 2004. Over 3 yr the macro-WSAs declined by 13%, except for high carbon input systems. Residue C input was a moderate predictor of total soil C (31% of variability explained), whereas macro- and micro-WSAs were predictors of soil C, accounting for 58 and 72% of observed variability, respectively. Low levels of aggregation were observed in this sandy soil and the modest amounts of C inputs from winter cover crops posed a challenge to detecting treatment effects, which was in part overcome by georeferencing, to improve precision of sampling over time.

Abbreviations: B, winter management systems bare • C, clover • CEC, cation exchange capacity • MWD, mean weight diameter • NMP, nitrogen mineralization potential • P, potatoes • PEI, Prince Edward Island • R, rye • RV, rye-hairy vetch • SB, snap bean • SC, sweet corn • SOC, soil organic carbon • W, wheat • WSA, water stable aggregate

Received for publication May 28, 2008.
   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
SOIL STRUCTURE is an important crop production factor affecting numerous processes critical to crop growth and ecological function (Martin, 1953; Pachepsky and Rawls, 2003). Soil structure is also a dynamic property that is subject to several formative and destructive forces including wetting and drying (Mikha et al., 2005; Park et al., 2007), freezing and thawing, as well as frequent tillage and harvest operations (Grandy et al., 2002). The type of crop grown can have a considerable impact on soil structure as well (Rasse et al., 2000; Villamil et al., 2006). Intensive cropping systems management is common in the Great Lakes Region, where high value crops with low residue return are grown on sandy soils with little structure. To understand the impact of these practices on the soil environment in a potato-based cropping system under Michigan conditions, there is a need to evaluate alternative management practices for their ability to mitigate the negative impacts of cropping on soils in the Great Lakes Region.

Economic considerations and alternative land use could explain the increasing preference for short crop rotation cycles among potato farmers. From 1950 to 1997, U.S. farmland declined by 20% (Theobald, 2001). Adoption of alternative crop management strategies becomes contingent on observed improvements in soils over the shortest time period possible. A single application of manure (24.5 Mg ha–1) in a Maine potato rotation trial resulted in significant formation of medium and large stable aggregates, whereas green manure crops of oat and hairy vetch performed over 5 yr had no discernable effects on soil aggregation (Grandy et al., 2002). After 5 yr, a barley–forage rotation had higher aggregation (as measured by mean weight diameter) when compared with a barley monoculture in both plots managed with conventional mineral fertilization or with liquid dairy manure (Bissonnette et al., 2001).

Soil aggregates are formed by bridging actions among clay micelles, quartz surfaces, organic colloids (Emerson, 1959), cations, and anions (Hillel, 2004). However, in sandy soils, cores and bonds of soil aggregates are largely composed of soil organic carbon (SOC). As soil particles physically and chemically bond with SOC, the resulting aggregates provide protection to the SOC and improve soil structure in the process. Over time, aggregates can be composed of SOC coming from different time periods, with recently added organic matter located on the outer perimeter of aggregates (Kavdir and Smucker, 2005). Hence, the effectiveness of different rotation cropping systems in improving soil structure can be evaluated by examining the proportion of stable macroaggregates.

The presence of legumes in a crop rotation scheme provides N-enriched residues, which may support microbial activity that enhances polysaccharide production and aggregation indirectly. Mazurak et al. (1954) found a high degree of aggregate stability in potato rotations that involved alfalfa (Medicago sativa L.). Under laboratory conditions, alfalfa and clover inputs led to increased MWD of aggregates in a silty-clay loam soil after only 9 d (Martens, 2000). An equilibrium in the formation of new aggregate binding material may have occurred as no further increases in aggregation were observed. The use of a green manure resulted in improved water stable aggregate stability (P < 0.10) for a potato rotation system in Maine (Porter et al., 1999). In a cotton (Gossypium hirsutum L.) production system, the use of clover improved aggregate stability by 100%, compared to a nonlegume cotton system (Hubbs et al., 1998).

Winter cover crops are used by some producers of high value, irrigated crops such as potato. However, farmers generally prefer cold-tolerant and productive cereal cover crops in the Upper Midwest, and rarely experiment with legume cover crops (Snapp et al., 2005). A number of researchers have found that soil structure and fertility are enhanced by the presence of legumes and legume–cereal mixtures in row crop systems (Griffin and Hesterman, 1991; Honeycutt et al., 1996). In addition to a cover crop, the residues of the main crop rotated with a potato crop are expected to influence soil aggregation and C over time. Research has not fully resolved the question of relative benefits of quantity vs. quality of residues in terms of their effect on aggregate formation and long-term soil productivity.

The objectives of this study were (i) to quantify above- and belowground C inputs from seven potato systems with contrasting main crops (snap bean, corn, and wheat) and three winter cover crop management systems (fallow, rye, rye-hairy vetch, and red clover); and (ii) to determine the impact of the potato rotation systems and cropping system phase on the formation of water stable aggregates, soil C dynamics, and soil productivity.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Field Experiment
A trial was established on 2 Apr. 2001 at the Montcalm Research Farm (MRF; 85°10'32'' longitude and 43°21'12'' latitude; Montcalm County near Entrican, MI). The soil type was a McBride sandy loam (coarse-loamy, mixed Eutric Glossoboralfs; and coarse-loamy, mixed, semiactive, frigid Alfic Fragiorthods) (Nyiraneza and Snapp, 2007). The trial was located at a potato research farm where the long-term rotation (bean-potato-corn) is representative of Michigan potato systems. Table 1 shows soil properties of the study site from samples collected and analyzed as described below. Seven 2-yr rotation systems were evaluated (Table 2 ). In S4, after potato was harvested in September/October, the plot was seeded with wheat. Wheat grew through the winter and grain was harvested before planting a rye cover-crop in September/October of the following year (Table 3 ). Therefore, for S4, wheat provided cover but was a main crop and thus biomass accounting reflected its harvested main crop status. The S5 system followed a similar sequence until April when the standing crop of wheat was seeded with clover. Wheat was harvested in September/October, while clover continued as a cover crop until incorporated before potato was planted.


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  		Table 1. Soil properties (mean ± standard error) of a McBride sandy loam monitored at a short rotation potato cropping system research at the Montcalm Research Farm, Entrican, MI in 2001 and 2004.

 

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  		Table 2. Rotation system and winter cover crop treatments implemented at a short rotation potato cropping system research at the Montcalm Research Farm near Entrican, MI.

 

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  		Table 3. Dates of field operations recorded from a short rotation potato cropping system research at the Montcalm Research Farm near Entrican, MI.

 
The treatments were laid out in a randomized complete block design with four replicates, where plots were 5.5 by 16.7 m. To account for variability in seasonal conditions, two entry years were included for each system (thus the total number of systems present each year was 14).

Cultural practices and field operations for the main crops and cover crops of this study followed Michigan State University recommendations, and are summarized here (Table 3). Cover crops were seeded at the following rates: rye 101 kg ha–1, red clover 22 kg ha–1 and hairy vetch 17 kg ha–1. Snowden potato tuber pieces (cut to 56 g) were planted in May of each year at a spacing of 30.5 cm within rows, and 86 cm between rows in six-row plots. Potassium as K2O was applied before planting at the rate of 201.6 kg ha–1. Fertilizer N was applied at planting with the seed pieces using a two-row planter with a starter fertilizer (P2O5) that contained 37.6 kg P ha–1. The remaining N fertilizer was applied through multiple splits at hilling and tuberization for a total of 224 kg N ha–1 in S1, and adjusted downward in the other systems based on the appropriate cover crop N credit (11 kg N ha–1 for rye in S2-S4, 30 kg N ha–1 for red clover in S5, and 18 kg N ha–1 for rye + hairy vetch in S6 and S7, respectively) The N credit was calculated based on earlier potato-cover crop research findings (Nyiraneza and Snapp, 2007). Tillage was performed by chisel plow (20–25 cm depth), followed by a field cultivator (10 cm depth) (Table 3).

Monthly precipitation data recorded from the study area in 2001 to 2004 are shown in Fig. 1 . The precipitation values of 991, 827, 478, and 735 mm for 2001, 2002, 2003, and 2004, respectively, indicated that 2003 was a dry growing season which could potentially influence observed soil structure differences between initial measurements taken in 2001, and those taken in 2004. Supplemental irrigation was applied of 170, 167, 227, and 201 mm for 2001–2004. The application of supplemental irrigation follows standard potato production practice in the Great Lakes region, which presumably diluted impact of seasonal precipitation.


Figure 1
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  		Fig. 1. Total monthly precipitation at Montcalm Research Farm near Entrican, MI for 2001–2004, and the 8-yr average. Annual precipitation was 991, 827, 478, and 735 mm for 2001, 2002, 2003, and 2004, respectively.

 
Carbon and Nitrogen Input
The annual amount of C that was incorporated in each of the systems over the cropping cycle was calculated as the total oven-dry weight of aboveground biomass, less any economic product that was removed. Aboveground biomass was collected using two subsamples per plot from 0.25 m2 quadrats, and oven dried at 65°C for 48 h. Cover crop biomass was measured just before incorporation in May (Table 3). Cash crop biomass was measured before harvest in July for wheat; in August for bean and corn, and in September for potato.

To account for the belowground C contribution, root biomass was measured for cover crops in 2003 and 2004 by collecting a composite of five 2-cm diam. soil cores per quadrat from the 0 to 25 cm depth randomly located across the plot (two quadrats per replicate x four replicates). Soil samples were wet sieved using a 4 mm mesh, roots were collected off the sieve with tweezers and oven dried at 65°C for 48 to 72 h until there was no change in weight. This was expected to be an underestimation of C inputs as root exudates and turnover of roots were not measured due to methodological challenges. For SB, C, and W, the shoot-to-root ratios used were set to 5:1, 5:1, and 4:1, respectively (Bolinder et al., 1999). For potato, the ratio was 6.7:1, computed from Opena and Porter (1999) and Porter et al. (1999). The average shoot-to-root ratio for cover crops was 1.25:1, similar to the literature values for vegetatively growing cover crops, such as a rye cover crop on a sandy soil in southern Michigan (Snapp et al., 2007). To determine C inputs from total biomass, a multiplier of 0.45 was used based on average %C in residues from this potato rotation trial (Nyiraneza and Snapp, 2007). In 2002, subsamples of shoot tissues from cover crops and cash crops were ground to pass a 1 mm mesh sieve and used to determine tissue N concentration using the total Kjeldahl N digestion procedure (Bremner and Mulvaney, 1982).

Water Stable Aggregates
Water stable aggregate samples were collected using a geopositioning system to identify two point locations per plot, and five samples within 0.5 m diam. area of each point were collected with a trowel (0–10 cm depth) to preserve aggregates in the composite sample. Two sets of five subsamples per plot were composited on the first (21 Nov. 2001) and the fourth year (11 Nov. 2004) of the trial. To improve ability to detect treatment effects on soil properties, sampling was conducted at the same geographic coordinates in both sampling instances. Improvement in soil structure is complicated by spatial variability in properties related to microtopography and parent material heterogeneity, thus it was decided to conduct georeferenced sampling to improve precision in detecting treatment effects over 3 yr. Samples were air dried, sieved through a nest of sieves to acquire a representative sample of soil aggregates sized between 2 and 4 mm. Overall, approximately 80% of the soil material by weight ended up in the <2 mm size range.

The WSA was determined using a modification of the Rasse et al. (2000) method by placing a single layer of 4- to 2-mm aggregates (~25 g) on the top sieve of a nest of 2, 1, 0.25, and 0.106-mm sieves in a water bath container attached to a reciprocating machine with a vertical amplitude of 5 cm, running at 35 rpm. Water was applied to the water bath until it was in contact with the 2-mm sieve, facilitating hydration of individual aggregates by capillary action for 10 min, and then reciprocated for 10 min. Sand-free water stable aggregates were determined following the methodology of Grandy et al. (2002). For the rest of the text, referral to water stable aggregate size fractions of 2, 1, 0.25, 0.106, and 0.053 mm refers to aggregate size ranges of 4 to 2 mm, 2 to 1 mm, 1 to 0.25 mm, 0.25 to 0.106 mm, and 0.106 to 0.053 mm, respectively. Data was also presented as stable macroaggregates (≥0.25 mm) and microaggregates (<0.25 mm). Mean weight diameter was computed as the summation of the average aggregate size remaining on each sieve, multiplied by the percent of total sample represented by the respective aggregate class as outlined by Kemper and Rosenau (1986).

Chemical Soil Properties
A representative soil sample from 0 to 20 cm depth was collected and sieved (<2 mm), then ground to powdery consistency using a Shatterbox rotary grinder (Spex Industry, Edison, NJ) for 2 min. Subsamples of 60 to 70 µg were weighed into tin capsules and sent to the Stable Isotope Laboratory at the University of California at Davis, for total carbon and N analysis by Europa Hydra 20/20 isotope ratio mass spectrometer (Europa Scientific, Crewe, UK). Another representative subsample was analyzed by A&L Great Lakes laboratories (Fort Wayne, IN) for the determination of available phosphorous (Bray P1), exchangeable K, Mg, Ca, cation exchange capacity (CEC; NH4OAc saturation, KCl displacement), soil pH (1:1 soil/water suspension), buffer pH (SMP solution), and texture components of sand, silt, and clay (hydrometer). All methodologies for the analysis were based on the North Central Regional Research Publication no. 221 (revised; Brown, 1998). Determination of pH, CEC, and percent base saturation followed Page et al. (1982), and soil texture was determined using the hydrometer method (Gee and Bauder, 1986).

Statistical Analyses
Data analyses were conducted using SAS ver. 9.1 (SAS Institute, 2006) MIXED procedure. Two-factor ANOVA were conducted with cropping systems S1 through S7 as factor A, and the two entry years as factor B. The first (2001) and fourth (2004) year data were analyzed separately. The differences between 2001 and 2004 were calculated for each plot and also analyzed. Comparisons among the systems and between the entry years were conducted using Fisher-protected least significant differences. Preplanned contrasts of three groups were tested: low C input (LCI consisting of S1 and S4), medium C input (MCI consisting of S2 and S6), and high C input (HCI consisting of S3, S5, and S7), compared via linear contrasts. Note that systems were categorized into different C input group based on initial hypotheses, as this was a preplanned contrast (the only system that had less than predicted root C input was S5, which our results indicated was a medium not high C input treatment). To control type 1 error, Bonferroni adjustment was used in comparing the different group means.

The contribution of water stable aggregates and biomass C input to soil C prediction was evaluated through the sum of squares reduction test (Schabenberger et al., 1999; Perez and Kogan, 2003). The test involved comparisons between the residual sums of squares of single factor reduced model consisting of either WSA (i.e., macro or micro) or C input, and the sum of squares of the full model involving all of the aforementioned factors. The observed F value from the comparison was compared to the F distribution table and the significance reported (Schabenberger et al., 1999).


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Entry Year Effects
Incorporation of entry-year as a factor in the experimental design was effective in quantifying the detrimental effects of potato production practices on soil quality. This was shown in 2001, early on in the experiment: soil samples taken after the alternative cash crop of corn, W, or SB harvest had 58, 46, and 17%, respectively, higher proportion of WSA in the larger size classes of 2 mm, 1 mm, and the overall MWD, compared to aggregates after the potato main crop (Table 4 , entry year P < 0.0001). A similar decline in aggregate size after potato harvest was documented by Carter and Sanderson (2001).


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  		Table 4. Mean water stable aggregate (WSA) size fractions, macroaggregates (Macro-Agg), total soil carbon (TSC), mean weight diameter (MWD) and its associated standard errors across different size classes recorded from a short rotation potato cropping system research at the Montcalm Research Farm near Entrican, MI, in 2001.

 
Additional evidence of soil structure degradation with potato production was found in 2004 (Table 5 ). Soil monitored after alternative main crops were associated with a high (11%) proportion of 1 mm size class aggregates compared to after the potato crop (8%) (Table 5; P < 0.001). Other size fractions showing significant effects of entry year in 2004 were the 0.25 mm and 0.053 mm WSA's, with 10% reduction and 8% increase, respectively, for the alternative cash crops compared to the potato entry year. The alternative crops were not able to maintain the level of aggregation and stability in 2004 compared to what was observed in 2001 (Tables 4 and 5). This is consistent with the decline in soil quality observed in other potato rotations trials (Angers et al., 1999), in the absence of substantial inputs from soil organic matter amendments (Grandy et al., 2002). The results point to the importance of finding a suitable system that can improve soil structure in the nonpotato phase of the 2-yr rotations commonly practiced in Michigan potato farms.


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  		Table 5. Mean water stable aggregate (WSA) size fractions, macroaggregates (Macro-Agg), total soil carbon (TSC), mean weight diameter (MWD), carbon input and their corresponding standard errors across different size classes recorded from a short rotation potato cropping system research at the Montcalm Research Farm near Entrican, MI in 2004.

 
System Organic Inputs and Soil Response
The limited amount of biomass remaining in the field in potato cropping systems (Mazurak et al., 1954; Rees et al., 2002) necessitates the identification of management systems that enhance residue input and maintain or slow down total soil carbon degradation. In this present study, the average amount of carbon returned to the soil by the seven potato cropping systems was 2.08 Mg ha–1 per year (range of 0.93 Mg ha–1 [S1] to 3.32 Mg ha–1 per year [S7]-Fig. 2A ). The amount of carbon contributed by S1 in this study was 44% less than that observed in a previous long-term study of potato systems (Angers et al., 1999). Considering that S1 had a bare fallow, a low biomass legume as the alternative cash crop (SB), and the site had low soil carbon (Table 1), all these factors could have contributed to the limited growth observed, and the modest carbon input levels.


Figure 2
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  		Fig. 2. (A) Annual carbon inputs from seven potato rotations (see Table 2 for system descriptions) and (B) averaged across systems for preplanned contrasts, S1 and S4 for the low input category; S2 and S6 for the medium category; and S3, S5, and S7 for the high carbon input category. Carbon inputs included above- and belowground organic material averaged over 2 yr (i.e., 2003 and 2004) and two entry years. Bottom, middle, and upper letters designate statistical significance for main crop, cover crop, and total carbon input across but not within systems. Columns with similar letters are not significantly different at 5%.

 
The carbon input from the cropping systems had the following pattern of decreasing magnitude: S7 (P-RV, SC-RV) > S3 (P-R, SC-B) > S5 (P-W/, W/C-C) > S2 (P-R, SB-R) > S6 (P-RV, SB-RV), and S4 (P-W, W-R) > S1 (P-B, SB-B). Planned contrast between low (S1 and S4), medium (S2 and S6), and high (S5, S3, and S7) carbon input categories indicated the presence of highly significant differences, with low input having an average annual C of 1.164 Mg ha–1, while medium and large inputs had 68 and 137% higher carbon returned to the soil, respectively (Fig. 2B). It is important to point out that although the amount of carbon contributed by S5 was not statistically different from S2 and S6, the inclusion of wheat was hypothesized to result to a bigger carbon input (being cold tolerant and allowed to maximize biomass accumulation) compared to SB complemented with either R or RV. The presence of a bi-annual C with a tap root system was initially hypothesized as producing more root inputs. However, the variability of root system growth is known to be high and the methodology may have not been refined enough to fully test this hypothesis.

Crop growth potential and residue generation have an impact on the amount of carbon returned to the soil. All systems with corn had higher carbon contributions (S3 and S7), followed by systems with W and R (S5, S2, S6, and S4; Fig. 2). These results were expected, considering that corn has an efficient C4 photosynthetic pathway, while wheat together with rye are C3 plants. Previous research has indicated that corn can produce 70% more biomass than wheat (Wilhelm et al., 2004).

The impact of a cropping system on soil carbon is dependent on other factors than the quantity of carbon added, including residue quality, the tillage intensity of cropping systems, the rate of carbon assimilation and the soil environment. The proportion of labile to recalcitrant forms of soil carbon is important, as annual contributions of residues have minimal impact on systems dominated by high proportions of inert carbon (Paul, 2007). In low carbon soils, the addition of carbonaceous residues may be able to increase total soil carbon in a relatively short time frame (Shrestha et al., 2002). Addition of 3.5 times the amount of carbon in S7 relative to S1 did not, however, significantly increase soil carbon in this study (Table 5). Three years between initial and subsequent measurements may have been insufficient to document changes in the total soil C pool, even though measures were taken to reduce variability by using geo-positioning methods to improve sampling precision.

As this was a cropping systems experiment, both the quantity and quality of residues varied with treatment. Crop residues were mature with a low N concentration, between 0.7 and 1.6% in 2002. However, cover crop residues were incorporated at vegetative stages and had high N concentration, particularly the legume–cereal mixtures. The rye cover crop in S2, S3, and S4 was incorporated at a vegetative stage and had a mean value of 2.2 N% (SD 0.3), whereas the legume–cereal mixed tissues in S5, S6, and S7 had a mean value of 2.7 N% (SD 0.4). The nitrogenous residues of S5, S6, and S7 could have a priming effect, and they had been associated with accelerated residue decomposition resulting in limited soil C assimilation in previous studies (Cope et al., 1958; Rasse et al., 2000). The presence of leguminous material ensures a relatively faster biomass breakdown compared to biomass of wider carbon-to-N ratios. Inclusion of C in the S5 P-W system was associated with 30% higher N mineralization potential (0.26 mg N g–1 d–11), compared to the S4 P-W system (0.20 mg N g–1 d–1; P = 0.05). No significant effects on N mineralization potential were found for other treatments, which averaged 0.25 mg N g–1 d–1.

System Effects and Aggregation
Four years after the trial was initiated in 2000, the cropping systems significantly affected the WSA size fractions of 1 mm, >0.25 mm, >0.106 mm, >0.053 mm, and macroaggregates (≥0.25 mm) (Table 5). The MWD demonstrated improvements of 19.5% in 2004 compared to 2001 levels, averaged across all treatments (Table 1). There was a small change in MWD for the low carbon input systems, based on the planned comparison of S1 and S4 (low carbon inputs) with all other systems (Fig. 3 ). S1 had a bare winter fallow and demonstrated a trend consistent with no increase in MWD size after 3 yr, although this was not significantly different from the other systems. It is interesting that S4 had low tillage intensity, yet it was still associated with a limited change in aggregate MWD, which may be accounted for by the low C inputs associated with this system. In another study using twice as much annual carbon input, less disruptive tillage in combination with crop rotation did have a significant increase in MWD (Bissonnette et al., 2001).


Figure 3
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  		Fig. 3. Response over time of mean weight diameter (MWD, mm) as shown by percentage change observed in 2004 compared to 2001 at the Montcalm Research Farm, Entrican, MI. (A) Influence of seven potato rotations (see Table 2 for system descriptions); (B) Influence of the systems when grouped by carbon input based on low (LC, 1.2 Mg ha–1), medium (MC, 2.0 Mg ha–1), and high (HC, 2.8 Mg ha–1) carbon input. Values averaged over rotation entry point. Bars with the same letter designation are not statistically different at 5%.

 
The WSA increases above the 2001 levels averaged 13%, 4%, and 31% for aggregate fractions 1, 0.106, and 0.053 mm, respectively (Table 1). In a Maine potato field trial, green manure involving hairy vetch increased the proportion of 1 to 2 mm, and 2 to 6.5 mm aggregate size fractions, with no increase observed for small macroaggregates (0.250–1 mm) (Grandy et al., 2002). The relatively high increase in the 0.053 mm size fraction in this present study suggests an inherent weakness of aggregates formed by the various systems. This is consistent with the sandy soil texture at our study site in contrast with the greater presence of clay to stablize aggregates in the loamy soil at the Maine site. Continuous tillage of the soil may have interfered with aggregate formation. Angers et al. (1999) reported that increases in WSA were observed only after the 6th yr and not on the 10th yr of a decade-long study. This discrepancy was attributed to different initial moisture contents of the processed samples. Samples in the present Michigan study were air dried before wet sieving as opposed to field moist samples used by Angers et al. (1999), therefore initial soil moisture content appeared to have little influence on the proportion of microaggregates observed among the seven treatments.

The amount of macroaggregates (diameter ≥ 0.25 mm) decreased for all treatments after 4 yr, except for S5 (Fig. 4 ). We observed a 6% decline from an average of 55% in 2001 to 49% in 2004; this was minimal compared to the 20% decline in macroaggregates measured over 4 yr in a potato rotation trial conducted on Prince Edward Island (PEI), Canada (Angers et al., 1999). In the PEI study, continuous potato production showed the greatest decline in macroaggregates. This was similar to declines we observed in the S1 system, which also had the lowest amount of residues.


Figure 4
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  		Fig. 4. Response over time of macroaggregates as shown by percentage change observed in 2004 compared to 2001 at the Montcalm Research Farm, Entrican, MI. (A) Influence of seven potato rotations (see Table 2 for system descriptions); (B) Influence of the systems when grouped by C input based on low (LC, 1.2 Mg ha–1), medium (MC, 2.0 Mg ha–1), and high (HC, 2.8 Mg ha–1) C input. Values averaged over rotation entry point. Bars with the same letter designation are not statistically different at 5%.

 
A comparison of systems grouped by preplanned contrasts demonstrated significant differences in macroaggregates over the 3 yr of the study. The limited capacity of sandy soils to form large aggregates under frequent tillage may have contributed to observed declines in macroaggregates. Under treatment S5, where P are rotated with W/C, the minimal tillage disruption associated with system–compared to the other rotations–appears to have led to no decline in macroaggregates compared to the 2001 levels (Fig. 4). In contrast, the other systems experienced as much as 15% declines.

Soil Aggregation and Carbon Dynamics
Relating the amount of total soil carbon to the amount of macro-, microaggregation, and residue contributed carbon input showed an inconsistent pattern. Although S4 had high macroaggregation, the amount of carbon input was not significantly different from S1 (Fig. 5 ). The high amount of aggregation in S5 could be attributed to the reduced amount of tillage received as W was grown across seasons, and C being frost seeded in the spring (Table 2). It is important to point out that the seven systems reported in this study do not only refer to the amount of carbon generated, but the whole "system" involved in the production of carbon, which necessarily included differences in intensity of tillage. Both the carbon input and the aggregation contributed significantly to total soil carbon level, as determined by the sum of square reduction test (Table 6 ). The residue carbon input was a moderate predictor of total soil carbon (31% of variability explained), whereas macro- and micro-WSAs were significant predictors of total soil carbon, accounting for 58 and 72% of observed variability, respectively. Inclusion of macroaggregation components and the amount of C input in the full model was able to account for 83% of the observed variability in total soil carbon.


Figure 5
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  		Fig. 5. Relationship of total soil carbon (C, %), carbon input, and water stable macroaggregates (2–0.25 mm diam.) for a potato short rotation system study at the Montcalm Research Farm, Entrican, MI. Letters refer to comparisons in water stable aggregates. Systems with similar letters are not statistically different at 5%. 1 = potato-bare/snapbean-bare, 2 = potato-rye/snapbean-rye, 3 = potato-rye/corn-bare, 4 = potato-wheat/wheat-rye, 5 = potato-wheat/(wheat/clover)-clover, 6 = potato-(rye/vetch)/snapbean-(rye/vetch), 7 = potato-(rye/vetch)/corn-(rye/vetch).

 

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  		Table 6. Sums of squares reduction test results from comparing total soil carbon full model consisting of macroaggregates, microaggregates, and carbon input with reduced model consisting of each of the three aforementioned independent factors from a potato short rotation cropping system study at the Montcalm Research Farm near Entrican, MI.

 
System Yield Potential and Soil Properties
Yield is a complex crop attribute that is affected by a wide range of factors, including climate, insects, disease, and soil moisture content among others, acting singly or in combination. Soil quality is a characteristic that integrates across several properties and can be an important predictor of crop yield (Snapp and Morrone, 2008). The evaluation of the relative tuber yield over time for each system compared to a reference system provides a "bioassay" of soil quality, one that is particularly relevant to agronomic concerns regarding which system can achieve the highest potato yield potential. System S1 US No. 1 tuber yields (Mg ha–1) were 29.3, 22.7, 31.4, and 25.6 for 2001, 2002, 2003, and 2004, respectively. This system was expected to have the lowest yield potential, as crop residues were minimal and a bare winter fallow provided no soil conservation cover (Snapp et al., 2005). As shown in Fig. 6 , yields of S5 and S6 were higher than S1 by an average of 23% from 2001–2003, but were lower than S1 in 2004 by 33% (P = 0.01).


Figure 6
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  		Fig. 6. Potato U.S. No. 1 tuber yield expressed relative to yield of system 1, over 4 yr of a field trial study comparing seven short potato rotations at Montcalm Research Farm, Entrican, MI. Systems S1 through S7 are described in Table 2.

 
Tuber yields of the other systems studied, S2-S4 and S7, did not significantly vary from S1. There was no observed clear relationship between P yield potential and soil carbon status, aggregate size classes or aggregate dynamics, although all of the short potato rotations studied were found to decline in yield potential with time. Environmental conditions vary from year to year, thus plant growth response to soil properties is also expected to vary, as previously demonstrated for P systems in an eastern Canada study by Carter and Sanderson (2001). A spring that is very wet, such as observed in 2004 in the present study, may have provided an environment where limited benefit was derived from increased soil water holding capacity or other soil quality features. This could explain the lack of plant yield response in S5 and S6 systems in that year.


   CONCLUSIONS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
The largest input of carbon was associated with the P rotation systems that involved corn, showing threefold higher carbon return than the S1 P-SB system. No significant change was observed in terms of total soil carbon. It was possible, however, to detect small, but significant, increases in macroaggregation and soil structure within a 2-yr potato rotation with W, an indication that it is feasible to improve soil quality even within the "real world context" of an economically viable potato rotation. Overall, the use of georeferenced sampling points minimized the challenge of high spatial variability in a sandy soil, and provided improved precision for detecting differences in soil characteristics over time.


   ACKNOWLEDGMENTS
 
The authors would like to acknowledge the financial support provided by Project GREEEN of the state of Michigan, the valuable advice of Dr. Alvin Smucker and the technical assistance of Katherine O'Neil. Author Po would also like to thank the Fulbright-Philippine Agriculture Scholarship Program for making it possible to pursue graduate studies at Michigan State University.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher.


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





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