Long term impact of no-till on soil properties and crop productivity on the Canadian prairies

Soil & Tillage Research 117 (2011) 110–123

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Long term impact of no-till on soil properties and crop productivity on the Canadian prairies Guy P. Lafond a,*, Fran Walley b, W.E. May a, C.B. Holzapfel c a

Agriculture and Agri-Food Canada, RR#1 Gov Rd, Box 760, Indian Head, SK, Canada, S0G2K0 Dept of Soil Science, University of Saskatchewan, 51 Campus Dr, Saskatoon, SK, Canada, S7N5A8 c Indian Head Agricultural Research Foundation, RR#1 Gov Rd, Box 156, Indian Head, SK, Canada, S0G2K0 b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 24 February 2011 Received in revised form 7 September 2011 Accepted 18 September 2011 Available online 15 October 2011

Meeting the needs of an increasing population requires protection of our arable land base and improvements in productivity. The study compared soil quality characteristics and crop yield to nitrogen (N) fertilizer in two adjacent fields; one field managed with no-till for 31 years while the other for 9 years. In 2003, the two fields along with native prairie were sampled for soil quality parameters across two landscape positions. A small plot study involving five rates of urea N (0, 30, 60 90 and 120 kg N ha1) and two phosphorus fertilizer placement methods (seed-placed vs side-banded) was conducted on the two adjacent fields for the period 2002–2009. The rates of N were superimposed on the same plots each year whereas wheat and canola were normally grown in alternate years. An N balance was conducted after 8 years to account for inputs and outputs of N. Soil bulk density values were 0.98 g cm3 for native prairie and 1.46 for LTNT and STNT in the 0–15 cm soil layer. The native prairie had 48.2 t ha1of SOC vs 44.4 and 36.7 for LTNT and STNT, respectively, in the 0–15 cm soil layer and no detectable differences for the 15–30 cm soil layer in 2003. Potentially mineralizable N using the Hot KCl digestion in the 0–15 cm soil layer was 60 kg ha1 of ammonium nitrogen for native prairie and 30 and 22 kg ha1 for LTNT and STNT, respectively. For amino sugar-N, native prairie had 558 kg ha1 vs 462 and 370 kg ha1 for the LTNT and STNT, respectively. This indicates a positive relationship between SOC levels measured and potentially mineralizable N reflecting differences in land management. Phosphorus fertilizer placed in the side-band with N yielded 3.5% more than seed-placed phosphorus in spring wheat and no difference in canola. Grain yields were 14% and 16% more for LTNT than STNT in spring wheat and canola, respectively. Maximum grain N removal averaged in wheat was 87 kg ha1 for LTNT and 74 kg ha1 for STNT and 71 and 65.4 kg ha1 in canola, respectively. A positive N balance was obtained provided that 60 kg ha1 of N was applied every year and no accumulation of nitrate-N was noted even with rates that exceeded N removal in the grain. This supports the view that no-till combined with continuous cropping and proper fertility represents a path to sustaining the global soil resource. ß 2011 Elsevier B.V. All rights reserved.

Keywords: Triticum aestivum L. Spring wheat Canola Brassica napus L. Nitrogen balance Nitrate-nitrogen Grain protein Soil organic carbon

1. Introduction Approximately 93–99% of the food consumed by humans comes from the land (Pimentel and Pimentel, 2000; Smil, 2000). On a global basis, the estimated land area available for annual crop production is 1.351 b hectares (ha) which amounts to 0.20 ha per person based on a population of 6.79 billion people (World Fact Book, 2010). However, 45% of global arable soils are affected by degradation (Lal, 2007). As well, 0.3–0.8% of the world’s arable land

Abbreviations: LNTN, long-term no till; STNT, short-term no till; N, nitrogen; SOC, soil organic carbon; SON, soil organic nitrogen; ISNT, Illinois soil nitrogen test, amino sugar nitrogen test. * Corresponding author. Tel.: +1 306 695 5220; fax: +1 306 695 3445. E-mail address: [email protected] (G.P. Lafond). 0167-1987/$ – see front matter ß 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.still.2011.09.006

is rendered unsuitable yearly for agricultural production owing to excessive soil degradation, with wind and water erosion accounting for 84% of the degradation (den Biggelaar et al., 2004a,b). At a recent World Congress on Conservation Agriculture (CA), the Food and Agriculture Organization endorsed CA as the key step to meeting the long-term global demand for food, feed and fibre for the projected 9 billion people by 2050 (Mackenzie, 2009). On the Canadian Prairies, early estimates suggest that from the start of cultivation to the 1940s, soils lost 15–40% of their organic N content (Mitchell et al., 1944; Anon., 1984). Several later studies reported similar impacts of cultivation on soil organic matter on the Prairies (Monreal and Janzen, 1993; Anderson, 1995; McArthur et al., 2001; Pennock, 2003; Schnitzer et al., 2006; Leinweber et al., 2009), typically attributing losses to enhanced decomposition or increased erosivity. In a synthesis of several studies, Janzen et al. (1998a,b) concluded that although estimates of organic matter

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losses vary, particularly in relation to climatic zone, approximately 25% of the soil organic carbon (SOC) from Canadian prairie surface soils has been lost since conversion to arable agriculture. The decline in SOC levels typically is highest soon after initial cultivation, with rapid loss occurring within the first 20 years (Bowman et al., 1990). This loss of SOC is also associated with an overall loss in soil fertility and productivity. Research from the past decade or so has shown that diversified continuous cropping systems combined with proper fertilization, in the absence of wind or water erosion, can sustain and even increase overall soil fertility and productivity (Campbell et al., 1997; Campbell and Zentner, 1997). The ability of standing stubble and surface residues to enhance water conservation and reduce wind erosion has been well documented (Smika and Unger, 1986) and no-till also has proven effective in protecting soils against water erosion (Mostaghimi et al., 1992). The positive benefits of no-till production systems on crop production (Lafond et al., 1996, 2006), economic performance (Gray et al., 1996; Zentner et al., 2002; Holm et al., 2006) and energy use efficiency (Zentner et al., 2004) are well recognized. No-till increases macro-aggregation (>0.25 mm) and mean weight diameter of soil aggregates, even in coarse textured soils, indicating the potential for no-till soils to sequester carbon (C) (Franzluebbers and Arshad, 1996). The potential of no-till to sequester C has since been verified by others (McConkey et al., 2003). Arshad et al. (1999) also showed that with no-till, water retention and infiltration can be increased due to a redistribution of pore size classes into more small pores and fewer large pores having the potential to improve crop water use and crop production. Because of their positive impact on soil C, notill production systems are seen as a necessary component to sustaining and enhancing the global soil resource (den Biggelaar et al., 2004a,b; Montgomery, 2007; Lal, 2007). The soil chemical constituents of greatest interest are SOC and soil organic nitrogen (SON). In the semi-arid and sub-humid prairies, increases in SOC and SON are closely related to the amount of crop residue returned to the soil, cropping frequency, the N content of the residues and the requirements for positive nutrient balances, especially for N and phosphorus (P) (Campbell and Zentner, 1997; Campbell et al., 1997, 2007). The combination of no-till, tall stubble and proper fertility can increase the potential of no-till to further increase SOC and SON as a result of higher grain yields due to increased snow retention, reduced surface evaporation and improved water use efficiency, especially in the semi-arid areas (Cutforth and McConkey, 1997; Cutforth et al., 2002, 2006). Other studies in the semi-arid areas have strongly suggested that continuous cropping combined with no-till would increase SOC and SON over time (Janzen et al., 1997). In the sub-humid areas of the prairies, the maintenance of SOC and SON to ensure optimum crop growth is dependent on continuous cropping and adequate fertility from either the addition of manures or inorganic fertilizers or the inclusion of forage crops in rotations (Campbell et al., 1997; Juma et al., 1997). Soil organic matter (SOM) also plays a key role in soil quality. The size of the microbial community is directly proportional to SOM content and soil microbes are the principal mediators of nutrient cycling (Hamel et al., 2006). Although soil microbial biomass represents only a small proportion of overall SOM, it is more dynamic than total SOM and a better indicator of how tillage and cropping systems impact soil health and productive capacity (Lupwayi et al., 1998, 1999; Campbell et al., 2001). Soil organic carbon and SON, microbial biomass carbon (MBC), light fraction carbon (LFC), light fraction organic nitrogen (LFN) and wet aggregate stability were enhanced with increased cropping frequency, fertilization and also with the inclusion of annual green manure crops and forage-legume hay crops but LFC, LFN, MBC and potentially mineralizable N were more sensitive to

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changes in cropping practices than simple measures of total SOC and SON (Campbell et al., 2001). When no-till is included as an additional factor, Lupwayi et al. (2004) noted that microbial biomass was increased further along with the functional diversity and activity of microbes. In turn, these increases have a positive effect on the decomposition processes of crop residues and therefore nutrient cycling. Soon and Clayton (2003) observed that N mineralization was higher with no-till. Given the many reported benefits of no-till on soil health, soil fertility, crop production, economic and energy performance in the short to medium term and the protection afforded against tillage, wind and water erosion, what can be expected from 20 to 30 years of no-till continuous cropping practices? Can the SOM content be brought back to, or even exceed, its original native level? Can notill continuous cropping systems provide the productivity required to meet the future challenges of a burgeoning world population, the increasing demands for food, feed and fibre and a decrease in arable land per capita? The objectives of this study were (1) to compare two adjacent fields with different no-till and cropping histories for their SOC content and their ability to mineralize SON based on indirect measurements of potentially mineralizable N and (2) to relate these measures to the responses of canola (Brassica napus L.) and spring wheat (Triticum aestivum L.) to different rates of N fertilizer with respect to grain yield, grain protein, soil residual N and N balance over an 8-year period. The soil quality of these two contrasting fields also was compared to that of an adjacent native prairie soil to estimate the progress made with no-till after more than 23 years of no-till. Results from two separate components of the study are presented. The first part reports on the extensive soil testing done in 2003 to characterize the two fields and the native prairie across different landscape positions for soil quality differences in relation to SOC levels, potentially mineralizable N and soil bulk density. The second part reports on a paired, large plot N response trial conducted during eight field seasons from 2002 to 2009. 2. Materials and methods 2.1. Site description The research site consisting of two adjacent fields with contrasting land management histories, long-term no-till (LTNT) and short-term no-till (STNT), is located approximately 19 km south-east of Indian Head, Saskatchewan, Canada (50.428 North 103.588 West). A small area of native prairie was present next to the LTNT field. The soil type for both fields and the native prairie is an Oxbow loam (Orthic Black Chernozem or Typic Haplocryoll) situated in the thin Black soil zone with a climate that is considered sub-humid continental. The mean annual temperature and total precipitation are 2.5 8C and 427 mm, respectively. The mean annual evapo-transpiration is 607 mm, giving an average annual moisture deficit of 180 mm (based on panevaporative values) (Campbell et al., 1990) and the average frostfree period is 110 days. The soil texture is 58% sand, 26% silt and 16% clay. The soil organic carbon content in the 0–15 cm soil layer was 3.50% for the native prairie site, 2.25% for the LTNT field and 1.72% for the STNT no-till site from soil samples taken in the spring of 2003. 2.2. Weather information A summary of weather information is provided in Table 1. During the 8-year period, growing season precipitation ranged from 34 to 150% of normal while growing season temperature ranged from 76 to 102% of normal (i.e., based on a 100-year average). Although overall temperatures were cooler than normal,

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Table 1 The average monthly air temperature and total monthly precipitation for the period 2002–2009 at the study site. Year

Precipitation (mm)

Growing season (% long-term)

May

June

July

August

Growing season

18 24 105 58 39 83 7 20

15 18 85 99 80 47 81 57

49 23 75 59 4 51 96 42

48 11 71 98 12 65 39 105

130 76 336 314 135 246 223 224

43

87

49

45

224

May

June

July

August

Growing season

2002 2003 2004 2005 2006 2007 2008 2009

7 11.4 6.7 8.7 11.1 11.2 8.6 8.1

15.7 15.5 12.6 14.8 16 15.1 13.9 14.0

18.6 18.5 16.2 16.9 17.9 20.1 16.8 14.4

15.6 19.5 13.1 15.5 17.3 15.7 12.5 15.3

14.2 16.2 12.2 14.0 15.6 15.5 12.9 12.9

Long-term Mean

11.4

16.1

18.4

17.5

15.9

2002 2003 2004 2005 2006 2007 2008 2009 Long-term mean Year

Temperature (8C)

58 34 150 140 60 110 99 100

Growing season (% long-term)

growing season precipitation was wide ranging providing for a robust evaluation of the long-term benefits of no-till. 2.3. Study description-Part 1. Quantifying the difference in certain soil quality parameters from two adjacent fields with contrasting management histories against a native prairie site The two adjacent commercial fields with contrasting management histories were sampled for certain soil quality characteristics (described below) and the samples were segregated according to the landscape position they were collected from. The LTNT field has been managed using a continuous cropping no-till system since 1978 while the adjacent STNT field (STNT) has been managed using a continuous cropping no-till system since 2001. Prior to this, the management on the STNT field consisted of a fallow-crop system

89 102 76 88 98 98 81 81

involving extensive tillage due to the frequent use of fallow in the cropping system. The depth of tillage was in the range of 7–10 cm. The native prairie area was located near the LTNT field. The exact scaled representation of the fields and the locations of native prairie was delineated using a geographical information system and is provided in Fig. 1. A detailed listing of the actual crop rotations for each field is given in Table 2. On May 22, 2003, the LTNT, STNT fields and native prairie area were sampled. The LTNT and STNT fields were sampled at 20 different locations of which half were located on convex landform positions that shed water and the other half were from concave positions that receive the water shed from corresponding convex areas. The end result was 10 pairs for each of the LTNT and STNT fields. The same sampling approach was used for the native prairie area at 10 sites resulting in 5 pairs of data. The diameter of the core used was 6.53 cm, giving an area of 33.49 cm2. The exact sampling points within each field and for the native prairie area are included in Fig. 1. At each sampling point, two samples were taken with a soil probe with area of 33.49 cm2. The depth increments were 0– 15 cm and 15–30 cm. The volume of the core for each depth increment was 505.44 cm3. The samples were put in plastic bags to prevent moisture loss and then placed in coolers and transported to the laboratory. The samples were stored at 5 8C until further processing. The following analyses were conducted on the soil samples collected and separate analysis was done for each depth. 2.3.1. Bulk density Bulk density was determined according to Blake and Hartge (1986). Gravimetric soil moisture was determined by oven drying approximately 20 g of field moist soils for 48 h at 105 8C, and subsequently converted to a volumetric basis using the bulk density of the sample (Topp, 1993).

Fig. 1. Exact scaled representation of the LTNT and STNT fields and the exact location of the sampling points reported in Part 1 of the study.

2.3.2. Soil nitrate and ammonium content Spring nitrate-N (NO3-N) and ammonium (NH4-N) were determined for field-moist soil using 2.0 M KCl extract according to Keeney and Nelson (1982), and colorimetric analysis using a Technicon Autoanalyzer II (Labtronics Inc., Tarrytown, NY).

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Table 2 Cropping histories of long-term and short term no-till fields used in the study. No-till combined with continuous cropping was initiated in 2001 on the short-term no-till field site. Long-term no-till

Short-term no-till

Year

Crop rotation

Year

Short-term no-till field

1978–1983 1984–1990

No-till annual cropping Brome grass seed production for 5 years and 2 years of hay Chemical fallow Spring wheat Canola Spring wheat Canola Spring wheat Canola Spring wheat Lentil Spring wheat Canola Spring wheat Canola Spring wheat Canola Spring wheat Canola Spring wheat Spring wheat

1984–1998

Conventional tillage wheat/fallow system

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Summerfallow Barley – conventional tillage Canola – start of no-till Spring wheat Field pea Spring wheat Canola Spring wheat Canola Spring wheat Spring wheat

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

2.3.3. N extraction by Hot KCl Hot KCl extractable N was determined according to Jalil et al. (1996). Briefly, 3 g of air-dried soil was ground to pass a 2 mm sieve and added to 20 mL of 2 M KCl. The solution was heated in a block digester for 4 h at 100 8C. Once cooled to room temperature, the solution was decanted, filtered through Whatman #2 paper, and analyzed for NO3-N and NH4-N using a Technicon Autoanalyzer II (Labtronics Inc., Tarrytown, NY). 2.3.4. Amino-sugar nitrogen The Illinois soil N test (ISNT) method of Khan et al. (2001) was used to estimate amino sugar N according to the specifications of Technical Note 02-01 [University of Illinois at Urbana Champaign (UIUC), 2003]. Briefly, a 1.0 g soil sample (air-dried and ground) was placed in a 500 mL widemouth glass preserving jar along with 10 mL of 2.0 M NaOH. A glass petri dish containing 5 mL of H3BO3 (4%, w/v) was suspended within the jar from the lid. Jars and lids were sealed and heated for 5 h at 50 8C. Temperature was monitored by suspending a thermometer in a jar containing 100 mL of deionized water placed in the center of the hotplate. After the heating period, jars were removed from the hot plate, the H3BO3 was diluted with 5 mL of deionized water, and titrated with 0.001 M H2SO4 to determine the ISNT-N values. 2.3.5. Organic carbon Total and organic soil C were determined by dry combustion at 1100 8C and 840 8C, respectively, using a LECO Analyzer CR-12 Carbon Determinator (LECO Corp., St. Joseph, MO); only organic C is combusted at 840 8C (Wang and Anderson, 1998). 2.3.6. Statistical analysis The analysis of the data was conducted under the assumption that differences between the land management effects were due to long-term management differences rather than inherent differences in soil properties and climatic conditions. Data from each depth were separately subjected to a CRD analysis of variance with the PROC GLIMMIX procedure of SAS (SAS Institute Inc., 2005). The effect of land use and landscape position was considered to be fixed for all analyses. Spatial variation among

sampling points within each land use treatment was modeled with a spatial exponential covariance structure; the degree of spatial correlation between any two points decreases gradually as the distance between two points in space increases. Furthermore, estimating a spatial covariance estimate in addition to a residual covariance estimate almost always improved model fit and never resulted in an inferior model fit relative to a CRD analysis without a spatial covariance estimate (results not shown). This type of analysis was described and explained in Littell et al. (2006) and Payne (2006). Contrasts were used to make a priori comparisons among treatment means. Statistical significance was declared at p < 0.10. We selected a lower confidence level for this portion of the study because of the high inherent variability expected in landscapescale based studies which increases the probability of Type II errors, as suggested by Pennock et al. (1994) and Walley et al. (1996). Standard errors of differences and corresponding denominator df, and LSD (0.10) were provided as measurements of precision and tools to further explore mean differences. 2.4. Study description-Part 2. Quantifying the impact of management histories of the LTNT and STNT fields on the response to fertilizer N, grain N removal and residual nitrate-N A plot study was superimposed on near level areas on each of the LTNT and STNT fields to avoid potential problems with excess water (refer to Fig. 1 for the location of the trial). The year 2009 represents 31 years of no-till continuous cropping on the LTNT field and 9 years of no-till continuous cropping on the STNT field. The study involved five rates of granular-urea N (0, 30, 60, 90 and 120 kg N ha1) with an analysis of 46-0-0 and one rate of monoammonium phosphate (11-52-0) that was either seed-placed or side-banded. The rates of P used ranged from 10 to 15 kg P ha1, depending on the year and crop and are provided in Table 3. When P was side-banded, it was placed with the N. The fertilizer sideband was located 2.5 cm to the side and 7.5 cm below the seed using a commercial hoe opener with individual press wheels on each opener for precise seed placement. The row spacing used during both the canola and spring wheat phases was 30.48 cm. The plots were 3.96 m  10.7 m (43.372 m2). During the years when

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Table 3 Other pertinent agronomic information related to Part 2 of the study. Agronomic variables

Cultivar Seeding date Seeding rate (kg ha1) Harvest date P fertilizer (kg ha1) Agronomic variables

Cultivar Seeding date Seeding rate (kg ha1) Swathing date Harvest date P fertilizer (kg ha1) z

Spring wheat 2002

2004

2006

2008

CDC Teal May 28 134 September 16 10

AC Abbey May 5 134 September 7 15

Prodigy May 9 134 August 23 15

Prodigy May 1 134 August 28 11

Canola 2003

2005

2007

2009

InVigor 2663 May 14 8.8 August 7 August 19 10

InVigor 5020 May 3 10 –z September 9 15

InVigor 5020 May 8 6 – August 28 15

InVigor 5440 May 5 6 – September 16 11

For the years 2005, 2007 and 2009, the canola was harvested standing and not swathed.

canola was seeded on the plots, potassium sulfate (K2SO4) with an analysis of 0-0-52-17 was broadcast on the surface the previous fall at a rate of 88 kg ha1 to provide 15 kg S ha1. During the 8 years of the study (2002–2009), the rates of N and placement of P used were repeated on the same plots. The plots were seeded to spring wheat in 2002, 2004, 2006 and 2008 and to canola in 2003, 2005, 2007 and 2009 giving a wheat–canola rotation. Refer to Table 3 for other pertinent agronomic information. A summary of the variable measured for each crop and the measurement methods used is provided below. 2.4.1. Plant density Plant density was measured approximately 3 weeks after planting. For each plot, the number of plants present in two separate one-meter length of row was determined. The average plant density for each plot was reported as plants m2. 2.4.2. Spike density (spring wheat phase only) Spike density was measured approximately 2 weeks after anthesis. For each plot, the number of spikes present in two separate one-meter length of row was determined. The average spike density for each plot was reported as spikes m2. 2.4.3. Flag leaf nitrogen and phosphorus concentration (spring wheat phase only) Flag leaves were collected randomly the full length of the plots near the center of each plot after full heading. Enough leaves were collected so that 25 g of dry leaf material was obtained. Immediately after collection, the leaves were dried at 40 8C and then ground using a Wiley Mill. A sub-sample of the ground flag leaf tissue was analyzed for N using the Kjeldahl digestion method after grinding the entire 25 g subsample in a Wiley-Thomas mill (Thomas Scientific, Swedes-6010, NJ) to <1 mm. Phosphorus in flag leaves was determined using another sub-sample of ground tissue by digesting the latter material in H2SO4–H2O2 and using the indophenol blue method to determine P concentration (Varley, 1966). The results for both N and P concentrations are expressed as g kg1. 2.4.4. Grain yield Grain yields were determined by mechanically harvesting the entire plot and weighing the grain. Grain yields were corrected to 14% grain moisture for spring wheat and 10% moisture for canola. Results are reported as kg ha1. After recording the grain weights for each plot, a sub-sample of 500 g was retained for grain N analysis.

2.4.5. Grain nitrogen Nitrogen in grain was determined by the Kjeldahl digestion method after grinding a 50 g subsample in a Wiley-Thomas mill (Thomas Scientific, Swedes-6010, NJ) to <1 mm (American Association of Cereal Chemists, 1976). The percent N was multiplied by grain yield to estimate the amount of N removed in the grain in kg ha1. 2.4.6. Protein content The grain protein concentration is expressed as g kg1. Grain N, determined using the Kjeldahl method, was converted to protein concentration using a conversion factor of 5.7 for spring wheat and 6.3 for canola (Tkachuk, 1969). 2.4.7. Residual soil NO3-N Following harvest, soil samples were collected using a 0–15 cm and 15–60 cm depth increment. The soil samples were air-dried immediately, ground and sieved to <2 mm aggregates and stored until analyzed for NaHCO3 extractable NO3-N (Hamm et al., 1970). The ppm concentrations of NO3-N were converted to kg ha1 using a factor of 1.8 for the 0–15 cm depth and 6 for the 15–60 cm depth. 2.4.8. Statistical analysis A mixed model analysis of the data was conducted with the PROC MIXED procedure of SAS (Littell et al., 2006). The effect of year, year by field history and year by field history by P fertilizer placement by N fertilizer rate interactions, and replicate within field history were considered random. The effects of field history, P fertilizer placement, and N fertilizer rate were considered fixed. The two field history study areas were not replicated within year. Consequently, the effect of replicate was nested within field history, and the tests for the effect of year, history, and year by history were included in the analysis but not reported (e.g., Linquist et al., 2008). The wheat–canola cropping sequence was conducted on the same plots from 2002 to 2009. The covariance for measurements made across years in the same plot were modeled with the repeated statement of PROC MIXED. Corrected Akaike’s Information Criterion (AICC) was used to ascertain that a heterogeneous variance compound symmetry covariance structure relative to other covariance structures was found to best account for covariance within experimental units. Contrasts compared treatment means across years and compared treatment responses for years when wheat was grown vs years when canola was grown. Selected treatment combinations also were compared on a by-year basis to further explore treatment interactions among years. Contrasts involving the random effect of year were

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conducted as described in more detail by Littell et al. (2006). Means and standard error (SE) also were estimated on a by-year basis when corresponding contrasts were statistically significant using methods described by Littell et al. (2006). Statistical significance was declared at p < 0.05. Standard errors of differences and corresponding denominator degrees of freedom were provided as measurements of precision for means. The effect of N fertilizer rate was further explored for grain yield and grain N accumulation by regressing responses against N fertilizer rate (N) using the following beta growth function model (Yin et al., 2003; Eq. (13B)):

Response ¼ wb þ

ðwmax  wbÞ  ðð3  NeÞ  ð2  NÞÞ  ðN2 Þ Ne3

where response represents either grain yield or grain N yield, wmax represents maximum response, wb represents the response intercept with the Y axis, N represents the rate of nitrogen used and Ne represents the N fertilizer rate at which the maximum grain yield occurred. Non-linear regression model coefficients were estimated with the PROC NLMIXED procedure of SAS (SAS Institute Inc., 2004). Contrasts were used to statistically compare coefficients among the treatment combinations. 3. Results and discussion 3.1. Part 1: Quantifying the differences for soil quality parameters from two adjacent fields with contrasting management histories against an adjacent native prairie site When examining the land management and landscape position, a land management effect and a land management by landscape position interaction were noted for soil bulk density (SBD) at the 0– 15 cm soil depth (Table 4). Land management and landscape position had similar values at the 15–30 cm soil depth. The SBD at the 0–15 cm depth was least for the native prairie site with no differences between the LTNT and STNT site (Table 5). Although the overall SBD was not different between the concave and convex areas, there was an interaction. In this case, the interaction was such that the SBD differences were greater between native vs LTNT and STNT in the convex position than the concave positions and the SBD trended lower for the concave areas in LTNT and STNT but higher for the native situation (Table 6). Boehm and Anderson (1997) also reported similar SBDs between concave and convex landform elements but higher SBDs on crop-fallow vs continuously

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cropped fields. The different results obtained in this study are probably due to the timing of when the measurements were taken. The measurements were taken in May of 2003 and the STNT field already had 2 complete years of no-till with continuous cropping. The lower SBDs for the native soil is likely due to more aggregation and higher litter content at the soil surface. The higher SBDs on the convex areas of LTNT and STNT would have also been strongly influenced by a combination of tillage and water erosion moving soil into the concave areas, thus explaining the lower SBDs for concave areas. The influence of tillage erosion in hummocky landscapes has been well documented (Lobb et al., 1995; Li et al., 2007). With soil residual NH4-N, no main effects or interactions were noted for either soil depth; however, main effects but no interactions were observed for soil residual NO3-N (Table 4). In the 0–15 cm soil depth, total inorganic N levels were greater for LTNT than both the STNT and native prairie site (Table 5). In addition, the amounts were greater for the concave than the convex areas which can likely be explained by more top soil moving from the convex to the concave areas prior to no-till resulting in higher soil organic matter in the concave positions. When combined with a greater likelihood for water accumulation, the higher organic matter resulted in a greater potential for N mineralization in the concave areas (Table 5). At the 15–30 cm soil depth, differences were noted for land management but not landscape position (Table 4). Nitrate-N levels were greater for LTNT followed by STNT followed by native prairie (Table 5). From an environmental perspective, the residual nitrate-N levels recorded would be considered very low and of little concern. When total SOC was measured, differences were noted for land management and landscape position at the 0–15 cm soil depth (Table 4). The values were the same between native prairie and LTNT at the 0–15 cm soil depth and between LTNT and STNT at the 15–30 cm soil depth (Table 5). In the 0–15 soil depth, LTNT and native prairie had higher levels of SOC than STNT (Table 5). The higher level of SOC in native than tilled soils is well known (Verity and Anderson, 1990; Landi et al., 2004). With landscape position, an effect was observed at both depths (Table 4) and the SOC content was always highest for the concave areas (Table 5). Of interest is the interaction at the 15–30 cm soil depth (Table 7). In this case, SOC was highest in the convex than the concave area for the native prairie site but the opposite was observed for LTNT and STNT. This could be due to the more intense erosion processes (combinations of wind, water and/or tillage erosion) in LTNT and STNT than under native prairie. It could also be due to contribution

Table 4 Analysis of variance results for selected variables collected in Part 1 of the study. A separate analysis was done for the 0–15 cm and 15–30 cm soil depth. Effect

Land management (L) Native vs LTNT and STNTz LTNT vs STNT Landscape position (Po) L  Po Effect

Land management (L) Native vs LTNT + STNTz LTNT vs STNT Landscape position (Po) L  Po z

Soil depth (0–15 cm) Soil bulk density

Soil residual NH4-N

Soil residual NO3-N

Total N (NO3 + NH4)

Hot KCl NH4-N

Hot KCl NO3-N

Amino sugar-N

Soil organic carbon

<0.001 0.001 0.71 0.483 0.025

0.642 0.992 0.357 0.930 0.481

0.001 0.028 <0.001 0.032 0.385

0.108 0.518 0.041 0.281 0.410

0.013 0.019 0.032 0.001 0.030

<0.001 0.001 0.001 0.727 0.347

0.017 0.041 0.025 0.0001 0.118

0.092 0.267 0.052 0.001 0.120

Soil depth (15–30 cm) Soil bulk density

Soil residual NH4-N

Soil residual NO3-N

Total N (NO3 + NH4)

Hot KCl NH4-N

Hot KCl NO3-N

Amino sugar-N

Soil organic carbon

0.804 0.970 0.512 0.483 0.252

0.221 0.132 0.319 0.252 0.206

0.046 0.065 0.073 0.743 0.751

0.062 0.186 0.050 0.481 0.440

0.017 0.009 0.366 0.002 0.032

0.131 0.230 0.102 0.503 0.710

0.099 0.047 0.361 0.024 0.023

0.586 0.330 0.769 0.060 0.067

Contrasts – Native refers to the native prairie site and LTNT to the long-term no-till site and STNT to the short-term no-till site.

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Table 5 Means of selected variables for the main effects land management (native vs long-term no-till vs short-term no-till) and landscape position (convex-area shedding water vs concave-area receiving the water from the corresponding convex area). Each sampling depth is reported separately. Land management

Soil depth (0–15 cm) Soil bulk density (g cm3)

Soil residual NH4-N (kg ha1)

Soil residual NO3-N (kg ha1)

Total N (NO3 + NH4) (kg ha1)

Hot KCl NH4-N (kg ha1)

Hot KCl NO3-N (kg ha1)

Amino sugar-N (kg ha1)

Soil organic carbon (t ha1)

Native LTNT STNT SEDz df LSD (0.10)

0.98 1.46 1.47 0.07 13 0.13

2 3 1 3.7 13 6.5

4 9 5 1.1 18 2.0

6 12 6 3.9 9 7.3

60 38 22 10.1 12 17.9

12 20 14 3.9 9 7.3

558 462 370 56 14 99

48.2 44.4 36.7 5.8 14 10.3

Land management

Soil depth (15–30 cm)

Native LTNT STNT SEDz df LSD (0.10) Landscape position

Soil bulk density (g cm3)

Soil residual NH4-N (kg ha1)

Soil residual NO3-N (kg ha1)

Total N (NO3 + NH4) (kg ha1)

Hot KCl NH4-N (kg ha1)

Hot KCl NO3-N (kg ha1)

Amino sugar-N (kg ha1)

Soil organic carbon (t ha1)

1.35 1.34 1.38 0.10 15 0.2

1 <0 <0 0.4 11 0.8

1 4 3 1.2 10 2.1

2 5 3 1.3 11 2.3

33 15 12 5 13 10

4 8 5 1.3 11 2.3

394 248 210 65 11 116

27.5 19.6 18.3 7.2 9 13.1

Soil depth (0–15 cm) Soil bulk density (g cm3)

Soil residual NH4-N (kg ha1)

Soil residual NO3-N (kg ha1)

Total N (NO3 + NH4) (kg ha1)

Hot KCl NH4-N (kg ha1)

Hot KCl NO3-N (kg ha1)

Amino sugar-N (kg ha1)

Soil organic carbon (t ha1)

Convex Concave SEDz df LSD (0.10)

1.32 1.29 0.04 16 0.07

2 2 2.2 14 3.9

4 7 1.3 20 2.2

6 9 2.8 10 5.1

28 51 5.3 16 9.2

14 16 6 40 10.8

379 545 31 17 54

35.6 50.6 3.7 16 6.5

Landscape Position

Soil depth (15–30 cm)

Convex Concave SEDz df LSD (0.10) z

Soil bulk density (g cm3)

Soil residual NH4-N (kg ha1)

Soil residual NO3-N (kg ha1)

Total N (NO3 + NH4) (kg ha1)

Hot KCl NH4-N (kg ha1)

Hot KCl NO3-N (kg ha1)

Amino sugar-N (kg ha1)

Soil organic carbon (t ha1)

1.33 1.38 0.07 17 0.13

<1 <1 0.2 21 0.3

2 3 0.7 12 1.2

3 3 0.6 15 1.1

12 28 4 14 7.1

5 6 1.0 9 1.8

235 333 38 13 68

17.3 26.3 4.3 11 7.7

SED represents standard error of difference with corresponding denominator degrees of freedom (df) immediately below.

differences in cumulative root distribution and between native prairie and annual crops grown under no-till. The effect of landscape position on SOC has been well documented on the Canadian Prairies (Verity and Anderson, 1990; Boehm and Anderson, 1997; Landi et al., 2004). Estimates of N mineralization using the Hot-KCl extraction method showed effects for land management and landscape Table 6 Interaction between land management and landscape position for soil bulk density and NH4-N release from the Hot KCl extraction for the 0–15 cm soil depth. Land management

Native LTNT STNT SEDz df LSD (0.10)

Soil bulk density (g cm3)

Hot KCl NH4-N (kg ha1)

Convex

Concave

Convex

Concave

0.89 1.52 1.54

1.08 1.39 1.40

61 18 7

59 58 37

0.08 29 0.14

11.3 26 19.3

z SED represents standard error of difference with corresponding denominator degrees of freedom (df) immediately below.

position and interactions at both soil depths for the release of NH4N (Table 4). Regardless of soil depth, NH4-N release was greater for the native site followed by the LTNT site and then the STNT site, except at the 15–30 cm depth where there was no difference between LTNT and STNT (Table 5). This is consistent with the observation of higher SON and SOC levels in the native prairie followed by LTNT and STNT. For both depths, there was two times as much NH4-N released from the concave landscape positions than from the convex positions. This is expected given the higher SOC content in the concave areas. The interaction for the 0–15 cm soil layer is due to the larger amounts for the native site than the LTNT and STNT sites in the convex areas and similar values between the native site and LTNT in the concave area with both being higher than the STNT site (Table 6). At the 15–30 cm depth, release of NH4-N was highest for native prairie and no difference was observed between LTNT and STNT; the concave areas released more ammonium-N than the convex areas (Table 5). For the interaction at the 15–30 cm depth, release of NH3-N was very large for the native site relative to the LTNT and STNT sites in the convex position but there were no differences among the three land management treatments in the concave positions, likely a reflection of tillage erosion over time (Table 7).

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Table 7 Interaction between land management and landscape position for NH4-N release from the Hot KCl extraction, amino sugar-N released and soil organic carbon for the 15– 30 cm soil depth. Land management

Native LTNT STNT SEDz df LSD (0.10) z

Hot KCl NH4-N (kg ha1)

Amino Sugar-N (kg ha1)

Soil organic carbon (t ha1)

Convex

Concave

Convex

Concave

Convex

Concave

35 <1 <1

31 29 23

445 136 124

234 361 295

32 10 10

23 30 27

7.0 32 12.0

76 28 131

8.5 27 14.7

SED represents standard error of difference with corresponding denominator degrees of freedom (df) immediately below.

Estimates of inorganic-N in Hot KCl extractions revealed land management differences only at the 0–15 cm depth (Table 4). The values were highest and different for LTNT than the native soil and similar with the STNT site (Table 5). When N mineralization potential was estimated using the ISNT method, a land management and a land position effect was observed for both soil depths and an interaction occurred at the 15–30 cm soil depth (Table 4). At both soil depths, the ISNT-N release was highest for the native prairie followed by the LTNT site and then the STNT site (Table 5). However, it should be noted that at the 15–30 cm soil depth, there was no difference between the LTNT and STNT sites. More ISNT-N was released from the concave positions in the landscape compared to the convex areas at both soil depths (Table 5). The interaction was such that for the convex areas, the values were highest for the native site and similar between the LTNT and STNT sites while, in the concave area, the highest ISNT release was observed with LTNT and the lowest for native prairie with the STNT site being intermediate (Table 7). Of the two methods for estimating N mineralization potential, the Hot-KCl extraction and the ISNT-N determination, both provided similar results in terms of measured inorganic-N release from the various land management sites and landscape positions. The results followed the observed differences for SOC levels closely with the higher recorded SOC values resulting in higher amounts of N released. Similar observations have been reported for different soil types and geographical locations as a function of different tillage and cropping systems (Salinas-Garcia et al., 2002; Soon and Clayton, 2003; Liebig et al., 2004). The detailed sampling of the three land management sites and two landscape positions confirms that the conversion of native prairie to annual cropping has resulted in important changes in soil properties. An increase in soil bulk density in the 0–15 cm soil layer was observed for LTNT and STNT with the largest increases observed in the convex areas of the field. Reductions in potentially mineralizable-N associated with the conversion to annual cropping systems were observed to the measured depth of 30 cm. The convex areas showed the smallest N release reflecting the loss of SOC over time from a combination of tillage and wind/water erosion. It is important to note that not all the soil would be removed from the field during wind and/or water erosion events. However the conversion to no-till has resulted in some important improvements after 25 years as indicated by the results for mineralizable-N and the increases in SOC. The difference in SOC content between LTNT and native prairie was less than between LTNT and STNT which indicates that the LTNT soils are still improving and slowly approaching the SOC levels of native prairie. The next part of the paper quantifies how the observed soil improvements in terms of SOC and potentially mineralizable N affect crop productivity and response to N fertilizer.

3.2. Part 2. Quantifying the effects of LTNT and STNT on spring wheat and canola response to nitrogen fertilizer and phosphorus fertilizer placement The only treatment effects on plant density were from placement of P and N fertilizer (Table 8). When averaged over both crops, plant densities decreased by approximately 6% when P was seed-placed as opposed to side-banded, 225 vs 239 plants m2 (SED = 6). The negative effect of seed-placed mono-ammonium phosphate is well known due to the toxic effects of ammonium (Grant et al., 2001). However the number of plants established was still above the recommended densities of 200 plants m2 and 60 plants m2 for spring wheat and canola, respectively (data not shown). With side-banded N fertilizer, linear reductions in plant populations were observed as N rate increased. The values, averaged over crops and P placement treatments, decreased by about 10% (244–220 plants m2) going from 0 to 120 kg N ha1. Over the 8 years of the study, the observed reduction never resulted in plant populations that were below the thresholds recommended to maximize grain yield for either crop (data not shown). The effects of high rates of side-banded N on reductions in plant densities has been reported elsewhere (Johnston et al., 1997, 2001); hence it is important to ensure that side-band openers provide consistent separation between seed and fertilizer taking into consideration soil conditions and wear on the opener (Johnston et al., 2001). The main effect of P placement was not significant for grain yield but a crop by P placement interaction was observed (Table 8). Spring wheat grain yields were increased by 3.5% when P was sidebanded as opposed to seed-placed but there was no observed difference for canola (Table 9). However, there is general agreement that, in situations where soil residual P is very low, it is better to seed place the P fertilizer than away from the seed as in a side-banded situation (Grant et al., 2001). Phosphorus response studies adjacent to the studies under discussion showed that the soils would not be considered P deficient based on their low responses to added fertilizer P (Lafond et al., 2008). However, this study showed a spring wheat grain yield benefit to sidebanding P as opposed to seed-placement, even under a low soil responsive situation for P. Similar grain yield benefits from dual bands of N and P have been previously reported in barley (Karamanos et al., 2008). Mooleki et al. (2010) reported no yield differences in wheat between side-banded and seed-placed P while Lemke et al. (2009) reported higher seed yields in canola when the P was seed-placed as opposed to side-banded. May et al. (2008) reported no effects of P placement in durum wheat. As expected, grain yields increased with increasing N rates (Table 8); however there were few interactions between crop, land management history, P placement and N rate. This signifies that responses were very similar between the two crops and the two

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Table 8 Combined analysis of variance over years, land management history, crop, phosphorus placement and rate of nitrogen for eight variables. p-valuey

Effect

P placement (P) Land management (L)  P N fertilizer rate (N) LN L  N (linear) PN LPN Crop (C)  P CLP CN CLN CLPN Effect

YLPN

Plant density (# m2)

Grain yield (kg ha1)

Grain N (kg ha1)

Grain protein (g kg1)

N balancez (kg ha1)

Soil residual NO3-N (0–60 cm) (kg ha1)

Flag leaf N (g kg1)

Flag leaf P (g kg1)

<0.001 ns <0.001 ns ns ns ns ns ns ns ns ns

ns ns <0.001 ns ns ns ns 0.014 ns ns ns ns

ns ns <0.001 ns ns ns ns ns ns ns ns ns

ns ns <0.001 ns ns ns ns ns ns ns ns ns

ns ns <0.001 ns ns ns ns ns ns ns ns ns

ns ns <0.001 ns ns ns ns ns ns ns ns ns

ns ns <0.001 ns 0.026 ns ns – – – – –

0.011 ns <0.001 ns ns ns ns – – – – –

Variance estimatex Plant density (# m2)

Grain yield (kg ha1)

Grain N (kg ha1)

Grain protein (g kg1)

N balancez (kg ha1)

Soil residual NO3-N (0–60 cm) (kg ha1)

Flag leaf N (g kg1)

Flag leaf P (g kg1)

7**

28**

35**

1

11*

14

21**

5**

x

The percentage of the variance associated with the Y  H  P  N random effect variance estimates divided by the sum of the total variance associated with the effect of year (sum of all variance estimates including year). The statistical significance of the variance estimate is indicated as follows: ‘*’ = 0.05  p value  0.01; and ‘**’ = p value < 0.01 and not significant by ns. y The statistical significance of the variance estimates are indicated by the actual p-values from the statistical analysis when the p-value is less than 0.05 and by ns when the p-value is greater than 0.05. z N balance represents N fertilizer inputs minus grain N exported (grain N accumulation).

land management histories (Fig. 2a). Using estimates from the fitted beta growth function model, a crop by land management history interaction was observed for maximum yield response and optimum N rate (Table 10). The difference in maximum grain yield was numerically larger between LTNT and STNT for spring wheat than for canola (406 vs 280 kg ha1, respectively), which is probably a reflection that spring wheat and canola were grown in alternate years. The N rate required to achieve maximum grain yield was the same between LTNT and STNT for spring wheat but higher for STNT than LTNT for canola (Table 10). This likely reflects the greater N requirements of canola relative to wheat. An identical pattern of response was observed for N removed in the grain except that, with grain N, there was no crop by P placement interaction or crop by land management history interaction (Table 10 and Fig. 2b). With grain protein, an effect due to N rate was noted but no interactions were observed (Fig. 2c). Grain protein levels were higher for LTNT than STNT when the N rates were 90 kg N ha1 or less, presumably indicating that LTNT supplied more N via mineralization of SON during the growing season and that N was more limiting in STNT. The maximum grain protein level obtained was the same between LTNT and STNT in spring wheat and the optimum N rate to achieve the maximum grain protein level was also the same (Table 10). Leaf P and N concentration were measured in the flag leaf during the spring wheat phase. Side-banded P increased leaf phosphorus content more than seed-placed P (2.74 vs 2.68 g kg1; Table 8). Furthermore, as the rate of N increased, the P content of flag leaves also increased (data not shown). With leaf N content, an N rate effect and a land management history by N rate interaction Table 9 The interaction of crop and P placement on grain yield (kg ha1). Crop

Seed-placed

Side-banded

SEz

Wheat Canola

2434 1299

2521 1306

103 101

z

SE represents standard error of mean.

were observed (Table 8). Overall, increases in N rate resulted in increased leaf N concentration (Table 11). The interaction was due to the more rapid increases in leaf N concentration at the lower N rates under LTNT than STNT. Positive relationships between flag leaf N concentrations and grain protein have been reported in other studies (Echeverria and Studdert, 1998; Tindall et al., 1995; Miller et al., 1999; Sexton et al., 2006) and with grain yield (Hargrove et al., 1983). The results from this study strongly support the positive association of flag leaf N concentration (Table 11) with grain protein (Fig. 2c) and with grain yields (Fig. 2a). Hargrove et al. (1983) proposed that maximum grain yields in winter wheat were achieved with flag leaf N concentrations of 35–40 g kg1. Donahue and Braun (1984) suggested that flag leaf concentrations in winter wheat ranging from 40.0 to 50.0 g kg1 would represent N sufficiency. More recently, Ziadi et al. (2010) proposed a value of 38.2 g kg1 as the critical N level of the most expanded wheat leaf. In this study, maximum grain yields were obtained with flag leaf N concentrations ranging from 41.0 to 42.8 g kg1 under LTNT and from 38.1 to 40.6 g kg1 under STNT. The lower leaf N levels recorded for STNT coincides with the lower potentially mineralizable N values also observed with STNT (Table 5). However, given that the flag leaf N levels were in the sufficiency range for STNT based on the critical leaf N values reported Ziadi et al. (2010) but that the grain yields were still lower than LTNT would imply that LTNT is providing additional benefits that go beyond simply supplying more N. Additional supply of P from the LTNT soils have been previously reported (Lafond et al., 2008) and this was reflected in the higher P content of the flag leaves as N rate was increased. An N balance was calculated based on inputs and outputs of N for the two land management histories and five rates of applied fertilizer N (Table 12). The only effects noted for N balance was due to N rates (Table 8). From 0 to 30 kg N ha1, N removal from the soil was greater than the N applied as fertilizer for both LTNT and STNT and the removal was greater for LTNT than for STNT. From 60 to 120 kg N ha1, N removal was always less than N applied such that a positive N balance of 15–327 kg N ha1 was noted with LTNT and

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speculate the extra N added but not removed in the grain is still present in the crop residues and soil microbial biomass. 4. General discussion

Fig. 2. The response of (a) grain yield, (b) grain N and (c) grain protein concentration to nitrogen rates for spring wheat and canola grown under long-term no-till (LTNT) and short-term no-till (STNT). Each line on the graphs represents the average response over eight growing seasons for the period 2002–2009.

131–410 kg N ha1 for STNT. Soil residual NO3-N, determined for the 0–60 cm soil layer after grain harvest, was only affected by N rates (Table 8). Very low and similar average values with rates of fertilizer N ranging from 0 to 90 kg ha1 were observed for both LTNT and STNT. At the high annual N rate of 120 kg ha1, the average soil residual NO3-N levels were higher than at the lower N rates and again similar between LTNT and STNT. Overall the residual soil NO3-N levels were low. When the residual soil NO3-N levels were determined after the 8th year, the levels were the same between LTNT and STNT. The repeated use of 120 kg N ha1 did not result in a build-up of soil residual NO3-N and the values were the same between LTNT and STNT. Given that the studies were managed with no-till and that all fertilizers were applied at the time of planting, these low reported accumulations of soil NO3-N are not unexpected. Other research studying repeated applications of animal manures and inorganic fertilizers for a similar agroecological zone, using rates greater than removal from grain, also reported low and slow accumulations of soil residual NO3-N over time in the crop rooting profile (Stumborg et al., 2007). We

The study attempts to quantify the long-term benefits of no-till on soil quality and consequent grain yield and grain protein concentration. To our knowledge, no previous studies have evaluated how the average performance of a field with 9 years of no-till and continuous cropping compares to that of an adjacent field with 31 years of no-till and continuous cropping. In this case the two adjacent fields had a similar soil type and experienced similar climatic conditions. Given the numerous benefits of no-till on soil quality and fertility, how does 31 years of no-till continuous cropping practices impact crop production relative to a shorter time frame of 9 years? The detailed field characterizations established that LTNT had more SOC and higher levels of potentially mineralizable-N than STNT after 2 and 24 years, respectively (Table 5). Moreover, the maximum spring wheat grain yield recorded for LTNT was 14% higher than on STNT (Table 10). Importantly, higher maximum grain yields in spring wheat under LTNT were obtained with similar rates of N as those for STNT. Maximum grain protein concentration was similar between LTNT and STNT despite LTNT having higher grain yields with similar N rates. These results imply that LTNT soils provide more N to support crop growth during the growing season than STNT soils. This assertion is supported by the differences in potentially mineralizable-N. We postulate that STNT may be in a ‘‘soil building’’ phase, thus limiting soil N supply to the growing crop relative to LTNT. The observation that higher rates of N cycling are occurring with LTNT are further supported by higher recorded N concentrations in the flag leaf in LTNT than in STNT, regardless of N rate used (Table 11). The higher flag leaf N concentrations in LTNT at all N rates provides further evidence that LTNT soils are cycling more SON during the growing season than STNT soils. Similar results were also reported by Soon and Clayton (2003). With canola, the highest maximum grain yield recorded was 16% higher on LTNT than STNT and more N fertilizer was required under STNT than LTNT (116 vs 106 kg N ha1) to achieve the maximum seed yield. Again, the evidence points to more soil N cycling under LTNT than STNT. Grain protein in canola always tended to be higher with LTNT than STNT at the intermediate N rates (Fig. 2c). Also of interest is the lack of convergence of grain yield responses to N between LTNT and STNT. Even after 9 years of no-till continuous cropping in STNT and with N rates in excess of grain N removal, the yield differences between LTNT and STNT were still apparent (Fig. 2a–c vs Fig. 3a–c). This would imply that the LTNT soils are possibly still improving (i.e., still in a soil building phase), even after 31 years. It has been suggested that soil organic matter is most useful biologically when it decays, leading to the dilemma of whether we can continue to sequester soil organic matter and simultaneously profit from its decay (Janzen, 2006). The ability of no-till continuous cropping systems to sequester carbon has been well documented (Franzluebbers and Arshad, 1996; McConkey et al., 2003). Increases in the quantity and diversity of the microbial community (Lupwayi et al., 2004) and increases in N mineralization (Soon and Clayton, 2003) are also observed with no-till. Increases in potentially mineralizable N with LTNT were demonstrated in this study (Table 5). Janzen (2006) asked the challenging question of whether we should hoard SOC or use it. Using SOC implies changes in soil and crop management (i.e., resorting to tillage) to accelerate SOC decay via microbial activity (Lupwayi et al., 2004) or else adding less nutrients than what is removed in the

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Table 10 Analysis of variance of the parameters derived from fitting a nitrogen rate response curves to the beta growth function model for grain yield, grain N accumulation and grain protein content. Coefficientz/treatmenty

Estimate (SE) Grain yield (kg ha1)

Grain N (kg ha1)

Grain protein (g kg1)

Maximum response Wheat – LTNT Wheat – STNT Canola – LTNT Canola – STNT

3283 2877 1996 1716

87.4 73.7 70.7 65.4

157 (6) 158 (5) –w –

Coefficientz/treatmenty

Estimate (kg N ha1)

Optimum N rate Wheat – LTNT Wheat – STNT Canola – LTNT Canola – STNT Coefficientz/treatmenty

(23) (23) (23) (28)

(0.7) (0.6) (0.7) (1.5)

Grain yield (kg ha1)

Grain N (kg ha1)

Grain protein (g kg1)

108 106 106 116

119 116 118 135

170 (25) 166 (18) – –

(2) (2) (2) (3)

(2) (2) (2) (4)

p-valuex

Maximum response Crop (C)  Land Management (L) Wheat Canola Optimum N rate CL Wheat Canola

Grain yield (kg ha1)

Grain N (kg ha1)

Grain protein (g kg1)

0.037 <0.001 <0.001

0.003 <0.001 0.014

ns –

0.050 ns 0.041

0.012 ns 0.010

ns –

w

Results for canola were not included for grain protein because the response to N rate was not appropriate for the beta growth function model. The statistical significance of the variance estimates are indicated by the actual p-values from the statistical analysis when the p-value is less than 0.05 and by ns when the p-value is greater than 0.05. y Abbreviations for levels of history are as follows: LTNT – long-term no-till and STNT – short-term no-till. z Coefficients from non-linear regression were the maximum predicted response and N fertilizer rate to achieve the maximum predicted response (optimum N rate). x

grain. However, loss of SOC with time will also negatively impact crop production because of the beneficial effects of soil organic matter on the chemical, physical and biological properties of soils. Given that tillage has to be done either before seeding or after Table 11 The effects of nitrogen fertilizer rates on flag leaf N concentration (g kg1) for the two land management histories. Nitrogen rate (kg ha1)

LTNT

STNT

0 30 60 90 120

33.0 35.2 38.3 41.0 42.8

29.0 29.9 34.7 38.1 40.6 SE = 0.6z

z

SE = standard error of mean.

harvest, tilling the soil for SOC decay may not necessarily result in nutrients being released at the most opportune time for crop uptake. Furthermore, tillage increases the potential for rapid loss of nutrients that could result from erosion or leaching. Janzen (2006) suggests that one solution to this dilemma is to increase the inflow of carbon into the soil. The results from this study showed higher productivity with LTNT than STNT in the form of higher grain yields. Given that the amount of carbon removed in the grain is less than half of the total carbon produced (i.e., harvest index is usually less than 0.5), LTNT is still adding carbon to the soil while simultaneously mineralizing SON. This is evident in that we observed higher grain N uptake in LTNT than STNT at all N rates used. Carbon inputs in no-till could be further increased with simple changes to stubble management involving tall stubble which has been shown to increase water use efficiency and grain yields in a number of crops (Cutforth and McConkey, 1997;

Table 12 The effects nitrogen rates and land management histories on nitrogen balance (inputs and outputs of nitrogen). N rate (kg ha1)

0 30 60 90 120 SED (DDF) y

Total N applied (8 years)

Total N removed with grain after 8 years (kg ha1)

Nitrogen balance (kg ha1) (applied N – N removed in grain) after 8 years

Average yearly residual soil NO3-N (0–60 cm) (kg ha1) over an 8-year period

Residual soil NO3N (0–60 cm) in the 8th year (kg ha1)

LTNT

STNT

LTNT

STNT

LTNT

STNT

LTNT

STNT

LTNT

STNT

50 240 480 720 960

270 342 465 577 632

181 244 349 491 550

220 102 15 143 327

131 3.6 131 229 410

15 16 18 19 34

11 12 15 19 34

12 13 15 14 28

8 10 12 14 29

z

50 240 480 720 960 y

–

20 (36)

20 (36)

3 (37)

4.4

SED represent standard error of difference and DDF represents denominator degrees of freedom. For residual soil N in the 8th year, only the standard error of the means is presented. z This represents the total amount of nitrogen added on the 0 nitrogen treatment after 8 years of the study. The nitrogen came from the yearly application of monoammonium phosphate.

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management are a necessary component to sustaining and enhancing the global soil resource (Montgomery, 2007; Lal, 2007). The higher cycling rates of N from the stored SON also provide important evidence that, under favourable climatic conditions, LTNT will make more N available for crop growth and support higher grain yields and grain protein levels. Higher grain yields will be achieved without necessarily having to add additional crop inputs like fertilizer. This will add the necessary resiliency to cropping systems while at the same time lowering the production risks for producers. No-till production systems will increase soil productivity over time and help feed a growing human population.

Acknowledgements This research was made possible with funding from Agriculture and Agri-Food Canada (AAFC), Vale Farms Ltd of Indian Head, the Indian Head Agricultural Research Foundation and Government of Canada’s Taking Charge Initiative on the development of Best Management Practices to mitigate greenhouse gas emissions at the farm gate and the Natural Sciences and Engineering Research Council of Canada. The technical support of Roger Geremia, Orla Willoughby, Randy Shiplack, and Steve Kopp from AAFC and Shelagh Steckler (nee Torrie) is greatly appreciated.

References

Fig. 3. The response of (a) grain yield, (b) grain N and (c) grain protein concentration to nitrogen rates for spring wheat and canola grown under long-term no-till (LTNT) and short-term no-till (STNT). Each line on the graphs quantifies the response observed in 2009 which is the 8th year of the study and represents the 9th year of no-till and continuous cropping for STNT and 31 years for LTNT.

Cutforth et al., 2002, 2006). Given the results from this study, we would argue that using the carbon is not an option and hoarding C confers benefits beyond the potential nutrient release. We have no effective means to use the SOC effectively and the potential negative risks appear to be higher than the possible rewards; thus, at the present time, the benefits of hoarding SOC outweigh the benefits of using it. We would also argue that after 31 years of notill, the soils are still improving and that it may be possible to attain or even exceed SOC and SON levels observed prior to the start of cultivation. Research using a Brazilian Oxisol soil has shown that no-till can increase SOC levels in the soil beyond the native prairie levels (Sa´ et al., 2001). In other words, more productivity is still possible with no-till. 5. Conclusions Because of the positive impact on soil carbon, the results of this study support the currently held view that no-till production systems combined with continuous cropping and proper fertility

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