Mulching and Tillage Effects on GHG Emissions and Properties of an Alfisol In

Mulching and tillage effects on GHG emissions and properties of an Alfisol in

Central Ohio

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

By Merrie Ann Varughese Environmental Science Graduate Program

The Ohio State University 2011

Master's Examination Committee: Dr. Rattan Lal, Advisor Dr. Craig B. Davis, committee member Dr. Martin J. Shipitalo, committee member

Abstract

No-tillage (NT) management in conjunction with crop residue retention on soil has been promoted as a practice capable of enhancing the soil quality as well as offsetting greenhouse gas (GHG) emissions because of its ability to sequester carbon in soils.

Therefore, the objective of this study was to evaluate the long term effects of application wheat (Triticum aestivum) residue mulch under NT and conventional tillage (CT) on

GHG emissions, soil physical and chemical properties in an ongoing experiment in

Central Ohio. Treatments included three rates of mulch at 0 Mg ha-1 yr-1 (M0), 8 Mg ha-1 yr-1 (M8) and 16 Mg ha-1 yr-1 (M16) without crop cultivation. All treatments were replicated thrice and laid out according to a completely randomized design. The data presented showed that application of straw mulch under NT can reduce GHG emissions

-2 compared to CT. The average diurnal CO2 fluxes were lower under NT (8.58g CO2-C m

-1 -2 -1 d ) compared to CT (9.69g CO2-C m d ). The effects of plowing on N2O flux, although

-2 -1 not significant, indicated a trend of higher N2O fluxes under NT (0.27 mg m d ) than

CT (0.21 mg m-2 d-1). Similarly, there was no definite trend among tillage treatments with regards to CH4 flux. However, NT was more of a sink for CH4 while CT treatments were sources. CO2 and N2O fluxes were significantly affected by mulch treatments, but mulching did not significantly affect CH4 flux. Furthermore, the application of mulch

ii directly influences chemical and physical properties of the soil. The current study shows that the application of mulch conserves soil moisture, reduces bulk density, moderates soil temperature, reduces soil salinity and enhances soil aggregation. Results suggest that mulching in conjunction with NT has positive effects on temperate agricultural soils, yet further research needs to be conducted to provide additional insight on the over-all impact and interactions between management regimes and GHG emissions, especially in relation to soil properties and climate factors.

iii

Dedication This document is dedicated to my beloved, George Oommen, and my family.

Acknowledgements

First and foremost, I would like to express my most sincere gratitude to my advisor

Prof. Rattan Lal for giving me the opportunity to join his team. I thank him for his patience, continuous encouragement, guidance and funding to make my Masters experience productive and stimulating. I would also like to thank other members of my committee, Prof. Craig Davis and Dr. Martin Shipitalo for their insightful comments and guidance.

I express my whole hearted thanks to the Carbon Management and Sequestration Centre group for their constructive criticism and excellent advice during the preparation of this I owe my gratitude to Dr. Meherban Kahlon, Senior Soil Scientist, Department of Soils,

PAU, Ludhiana, India. for helping me with soil sampling and lab experiments. I am especially grateful to Basant Rimal for his constant support with lab experiments and gas sample analysis. I would also like to thank Matthew Yin of OSU‘s Statistical Consulting

Service (SCS) for helping with the statistical analysis of my data.

Most importantly, I would like to thank my family and my friends for all their love and support. I wish to express my deepest gratitude to my beloved, George Oommen, for always offering me a helping hand during my sampling process and for being a constant source of encouragement through-out my research and thesis work.

Vita

2001-2005 ...... Vidyodaya School (Higher Secondary Education)

2005-2009 ...... B.E. Biotechnology, Vellore Institute of Technology University

Fields of Study

Major Field: Environmental Science

Table of Contents

Abstract…………………………………………………………………………………………...... ii Dedication………………………………………………………………………………………………...iv Acknowledgements………………………………………………………………………………………v Vita….……………………………………………………………………………………………………...vi List of Tables………………………………………………………………………………………….....ix List of Figures…………………………………………………………………………………………….x Chapter 1: Introduction ...... 1 1.1 GHG concentrations in the atmosphere: ...... 3 1.2 Factors affecting GHG emissions from agricultural soils: ...... 6 1.2.1 Soil physical properties: ...... 6 1.2.2 Soil chemical properties:...... 7 1.2.3 Tillage systems...... 8

1.2.3.1 CO2 emissions ...... 10

1.2.3.2 CH4 emissions ...... 10

1.2.3.3 N2O emissions ...... 11 1.2.4 Crop residue management...... 12 1.2.4.1 Mulch amendments ...... 13 References: ...... 16 Chapter 2: Mulching and tillage effects on Greenhouse Gas (GHG) emissions ...... 25 2.1 Abstract ...... 25 2.2 Introduction: ...... 26 2.3 Materials and methods: ...... 30 2.3.1 Field site and experimental design:...... 30

2.3.2 Monitoring CO2, CH4 and N2O fluxes ...... 31 2.3.3 Analysis of gas samples ...... 32 2.3.4 Data analysis ...... 33 vii

2.4 Results and discussion ...... 34

2.4.1 Diurnal CO2 fluxes ...... 34

2.4.2 Diurnal N2O fluxes ...... 41

2.4.3 Diurnal CH4 fluxes ...... 45 2.5 Conclusion ...... 49 References ...... 51 Chapter 3: Mulching and tillage effects on soil physical and chemical properties ..... 57 3.1 Abstract ...... 57 3.2 Introduction ...... 58 3.3 Materials and method: ...... 62 3.3.1 Field site and experimental design:...... 62 3.3.2 Determination of soil physical properties: ...... 63 3.3.3 Determination of chemical properties ...... 64 3.3.4 Statistical analysis ...... 65 3.4 Results and discussion:...... 65 3.4.1 Soil physical parameters ...... 65 3.4.1.1 Soil bulk density under different mulch and tillage treatments ...... 65 3.4.1.2 Soil moisture under different mulch and tillage treatments ...... 68 3.4.1.3 Soil temperature under different mulch and tillage treatments ...... 70 3.4.2 Soil chemical parameters ...... 73 3.4.2.1 Soil pH under different mulch and tillage treatments ...... 73 3.4.2.2 Soil EC under different mulch and tillage treatments ...... 73 3.4.2.3 Soil macro and micro-aggregate C and N concentration under different mulch and tillage treatments ...... 75 3.5 Conclusion ...... 78 References ...... 81 Chapter 4: General Conclusion ...... 88 Complete References...... 91

Appendix: Statistical Data…………………………………………………………………………...107

viii

List of Tables

Table 1. Ohio GHG Emission and Trends by Economic Sector: 1990-2003………………...5

Table 2. Diurnal GHG from different tillage methods at different mulch rates...... 34 Table 3. Mean bulk density, moisture, temperature under tillage treatments at different mulch rate...... 67

Table 4. Mean pH and EC as affected by different mulch rates…………………………………….74 Table 5. Macro-aggregate associated C and N concentrations and C:N ratios of tillage treatments at different mulch rate………………………….………………………………………...76 Table 6. Micro aggregate associated C and N concentrations and C:N ratios of tillage treatments at different mulch rate……………………………………………………………………77

List of Figures

Figure 1. Gas chamber fitted with the lid prior to gas sampling………………………………31

Figure 2. Diurnal CO2 flux from different mulch treatment and different tillage plots….35

Figure 3. (a) Diurnal CO2 flux from different mulch treatment under NT

(b) Diurnal CO2 flux from different mulch treatment under CT…………………37

Figure 4. (a)Average diurnal CO2, N2O and CH4 respectively flux from different mulch treatment and different tillage plots…………………………………………………………………38

Figure 5. (a) CO2 flux varying with air temperature (b) CO2 flux varying with volumetric moisture content…………………………….39 Figure 5.(c) A 3-D representation of CO2 flux varying with moisture and air temperature……….………………………………………………………………………………………40

Figure 6. Diurnal N2O flux from different mulch treatment and different tillage plots....42

Figure 7. (a), (b) diurnal N2O flux from different mulch treatment under NT and CT.…44

Figure 8. Diurnal CH4 flux from different mulch treatment and different tillage plots….47

Figure 9. (a), (b) Diurnal CH4 flux from different mulch treatment under NT and CT….48 Figure 10. (a), (b) Average bulk density of 0-10 cm and 10-20 cm respectively for different mulch rates and tillage treatments…………………………………………………..…..66 Figure 11. (a), (b) Diurnal VMC (volumetric moisture content) from different mulch treatment and tillage treatments……………………………………………………………………69

Figure 11(c) Average VMC from different mulch and tillage treatments…………………70

Figure 12. (a), (c) Soil temperature at 0-5 and 5- 10 cm depths respectively, for different mulch treatments under NT. (b), (d) Soil temperature at 0-5 and 5- 10 cm depths respectively, for different mulch treatments under CT………………………….………………………………………………..71

Figure 13. (a), (b) Average soil temperature at 0-5 and 5-10cm respectively, for different mulch and tillage treatments………………………………………….………………………………72

Chapter 1: Introduction Since the advent of the industrial era, anthropogenic activities have been releasing a wide variety of Greenhouse Gases (GHGs) into the atmosphere in quantities large enough to affect the global composition of the atmosphere (Ruddiman, 2003). This composition is affected both by the release of radiative forcing GHGs and other chemically active but non-radiative gases. About one third of the solar energy that is radiated by the Sun at short wave length is partially reflected back to space by clouds, aerosols and reflective surfaces on earth such as snow, ice, and deserts (Kiehl and

Trenberth, 1997). The balance of this solar energy warms the earth and the warmed surface in turn radiates energy back to space, but at a much longer wavelength. Much of this thermal radiation emitted from land and ocean is absorbed by the atmosphere by clouds and gaseous constituents and is reradiated back to the Earth (Le Treut et al., 2007).

These gaseous constituents are known as GHGs, part of the energy re-radiated by these

GHGs is absorbed by the Earth’s surface, raising the Earth’s temperature. This natural process is known as the greenhouse effect.

GHGs are defined by their radiative forcing, which changes the Earth’s atmospheric energy balance; typically, expressed as watts per square meter (W m-2) (IPCC, 1996). A positive value indicates an increase in the level of energy remaining on the Earth, while a

1 negative value indicates an increase in the level of energy returning to space. Global warming potential (GWP) is a function of radiative forcing, mean lifetime and emissions.

Several naturally produced GHGs trap heat, including water vapor, carbon dioxide (CO2), ozone (O3), methane (CH4) and nitrous oxide (N2O). These natural GHGs can also be produced by human activity. Other GHGs (e.g., hydrofluorocarbon, perfluorocarbons and sulfur hexafluorides) are solely the result of human activity (IPCC, 1996). Several

GHGs (i.e., CO2, CH4, and N2O) are long-lived in the atmosphere and are the major contributors to positive increases in radiative forcing (IPCC, 1996). The GWP of each of these gases can be expressed in CO2 equivalents. The GWPs, by mass, of N2O and of

CH4 are 296 and 23 times greater, respectively, than a unit of CO2.

Agriculture plays a substantial role in the balance of the three most significant

GHGs. Agriculture releases significant amounts of CO2, CH4, and N2O to the atmosphere

(Cole et al., 1997; Paustian et al., 2004). CO2 is released largely from microbial decay or burning of plant litter and soil organic matter (Smith, 2004; Janzen, 2005). However, CH4 is produced when organic materials decompose in oxygen-deprived conditions, notably from fermentative digestion by ruminant livestock, stored manures, and rice grown under flooded conditions (Mosier et al., 1998). In comparison, N2O is generated by the microbial transformation of nitrogen (N) in soils and manures, and is often enhanced where available nitrogen exceeds plant requirements, especially under wet conditions

(Oenema et al., 2005; Smith and Conen, 2004). Agricultural GHG fluxes are complex and heterogeneous, and historically, agricultural soils have been a major source of large amounts of C and N to the atmosphere (IPCC, 2007). However, the identification and 2 implementation of judicious land use management and C sequestration strategies can make soils an important sink for both C and N (Lal et al., 1995).

1.1 GHG concentrations in the atmosphere:

The global atmospheric concentrations of the major GHGs which include CO2,

CH4 and N2O have been increasing since the beginning of the industrial era (Munoz,

2010). Concentrations of CO2, CH4, and N2O have increased from a pre-industrial value of about 280 to 385.2 ppm, 714 to 1797 ppb and 270 to 321.8 ppb in 2008 respectively

(WMO, 2009). Anthropogenically induced accumulation of these GHGs has been continuing to rise at a rapid rate due to burning of fossil fuels, deforestation, inefficient land use management and land use change. Total C emissions from terrestrial ecosystems, fossil fuel combustion and other energy sources are estimated to be 8.9 Pg C yr-1, of which 10–12% (1.69 ± 0.8 Pg C yr-1) of total anthropogenic GHG emission is caused by tropical deforestation and land use change and degradation (Koonin, 2008).

This includes 0.76 Pg C in the form of N2O emissions and 0.90 Pg C in the form of CH4 emissions (Smith, 2007).

The total US GHG emissions in 2009 were 6,639.7 Tg CO2 Eq (US EPA, 2011).

Gaseous emissions from U.S. increased by 7.4 % between 1990 and 2009. However, changes in the economic situation have caused emissions to decrease by 6.0 % (422.2 Tg

CO2 Eq.) between 2008 and 2009. The primary cause for this decrease was due to (i) a decline in the economic output resulting in a decrease in energy consumption across all sectors, and (ii) a spike in the coal prices and depreciation in natural gas prices, leading to

3 a decrease in the carbon intensity of fuels used to generate electricity due to fuel switching.

A recent inventory of the United States GHG emission separated major emitters into categories: (1) energy (90.4%), (2) agriculture (6.3%), (3) industrial (4.3%), (4) waste (2.3%) and (5) solvent and product use (<1%) (US EPA, 2009). The primary GHG emitted from anthropogenic activities in the US is CO2, representing approximately

83.0% of total GHG emissions. Fossil fuel combustion is the largest source of CO2 and of overall GHG emissions. CH4 emissions, which have increased by 1.7% since 1990, result primarily from natural gas systems, enteric fermentation associated with domestic livestock, rice cultivation and decomposition of wastes in landfills. The major sources of

N2O emissions are agricultural soil management and mobile combustion. Conversely, land use, land-use change, and forestry activities in 2009 resulted in a net C sequestration of 1,015.1 Tg CO2 Eq. This led to an offset in the US GHG emissions by 15.3% of total emissions in 2009.

Ohio is the largest GHG emitting state in the Midwest, and the fourth largest in the nation in terms of absolute emissions. In 2003, Ohio GHG emissions totaled 299 Tg

CO2 Eq, representing 19% of Midwest emissions and 4% of U.S. emissions (Larsen et al.,

2007). Approximately 92% of Ohio’s electricity is generated from coal. As a result, 42% of total emissions are produced by the electric generation sector—5% more than the

Midwest average.

Table 1.Ohio GHG Emission and Trends by Economic Sector: 1990-2003

1990 2003 1990% 2003% 1990-2003 Emission Trends Sector Emission Emission Emission Emission Ohio Midwest (MtCO2e) (MtCO2e) % % U.S % Change Change Change Energy Sectors 251 92 267 89 6 14 14 Electric Generation 109 43 126 47 16 25 24

Transportation 58 23 71 27 22 20 19

Industrial 52 21 37 14 -29 -11 -3

Residential 21 8 22 8 5 8 12

Commercial 11 4 11 4 7 9 7 Fugitive Emissions 2 1 1 0 -48 -40 -35

Agriculture 9 3 8 3 -10 -8 0 Industrial Processes 4 2 18 6 -14 -5 8

Waste 9 3 6 2 -31 -21 -9

Total 272 100 299 100 5 11 13 *Source: WRI, CAIT-US(2007)

Approximately 78% of Ohio’s GHG emissions are produced by the major energy

sectors: electric generation (42%), transportation (24%), and industrial energy use (12%).

Apart from the major sources, other listed sources were industrial process (6%), waste

(2%) and agriculture (3%) (Table 1).

Between 1990 and 2003, GHG emissions from energy use in Ohio’s industrial

sector declined by nearly 15 Tg CO2 Eq, or 29 %, the largest decrease in this sector of

any Midwest state. This trend was primarily due to a reduction in coal consumption, as

the total amount of coal used by Ohio’s industrial sector as an energy fuel source

5 declined by nearly 70 % between 1990 and 2003 (EIA, 2007). The economic recession during these years appears may be a driving factor in limiting the growth of both energy consumption and GHG emissions.

1.2 Factors affecting GHG emissions from agricultural soils:

1.2.1 Soil physical properties:

Several physical factors that control GHG emissions from soil include soil temperature, soil moisture, and pore size distribution (Jarecki and Lal, 2006; Ussiri and Lal, 2009).

Alternating wetting-drying cycles and increasing soil moisture up to about 60% water filled pore spaces (WFPS), but below saturation, exacerbates nitrification and contributes to N2O emissions and CO2 emissions (Granli and Bockman, 1994; Ruser et al., 2006).

Soil with a good structure is a sink for CH4 and waterlogged soil is a source. Fluxes of

CH4 from dry land cropping are small compared with those from animal or paddy rice production. Jarecki and Lal (2006) analyzed the impacts of soil temperature and soil moisture on GHG emissions. The study showed that CO2 fluxes were positively correlated with soil and air temperatures, and negatively correlated with soil moisture content. Precipitation was highly correlated with fluxes of N2O but had no effect on CH4 fluxes.

Bulk density (ρb) is yet another soil physical property that can affect GHG emissions.

Naturally high ρb associated with fragipans and compaction by tillage implements and agricultural equipment (e.g. grain carts, combines, tractors etc.) can reduce aeration under moist soil conditions. Mosquera et al. (2007) reported that compaction can reduce the ability of soils to consume or oxidize atmospheric CH4 by as much as 30 to 90%. Even

6 slight soil compaction can increase N2O emissions by as much as 20%, while severe compaction may double N2O emissions. Yamulki (2002) examined short-term compaction effects over a period of 3 weeks, and observed that compaction increased the emissions of N2O and CH4, 3.5 and 4.4 times, respectively, compared with emissions from uncompacted plots.

1.2.2 Soil chemical properties:

Chemical properties such as soil pH, the quantity and quality of soil organic matter (SOM) or soil organic carbon (SOC) also influences gaseous emissions. Soil pH affects the proportions of different gases that are released from the soil. However, there is no clear relationship between GHG emissions and soil pH that has thus far been established due to difficulties in understanding how various biogeochemical processes occur simultaneously. A few studies have been done on N2O emissions. Soil pH is a

‘master variable’ of N transformations (Morkved et al., 2007), and has been demonstrated to have a strong influence on ammonia oxidizer (Backman et al., 2003; Nicol et al.,

2008) and denitrifier populations (Enwall et al., 2005) and on net N2O emissions (Simek and Hopkins, 1999). When denitrification is the main source of N loss, N2O emissions tend to decrease with increasing pH in acid soils (pH below 5-6), but where nitrification is the main source, emissions of N2O tend to increase with increasing pH at least in the range 6-8 (Granli and Bockman, 1994).

The SOC is yet another crucial factor that affects GHG emissions and C sequestration. One of the major objectives of the adoption of sustainable management of soil resources is to increase the SOC pool, an important indicator of soil quality and agronomic sustainability because of its impact on other physical, chemical and biological

7 properties of soil (Sharma et al, 2008). It contributes to productivity and environmental quality through its role in supplying nutrients, nutrient recycling, enhancing soil/plant water reserves, increasing soil buffering capacity, and stabilizing soil structure (Hobbs et al., 2008). Hence it is relevant to adopt soil and crop management systems that accentuate humiﬁcation and increase the stable or non-labile fraction of SOC (Gulde, 2007).

The quantity and quality of SOC depends on various factors like tillage practices, crop residue managements, climate, landscape position and vegetation. Arable land almost always has lower SOC concentration than that under forest or grass (Franzluebbers, 2005), probably due to stimulation of SOM decomposition which occurs during cultivation by frequent tillage and disrupting the SOM protected in aggregates and redistributing it in the soil profile where environmental conditions are more favorable for decomposition.

Several studies have shown that no-till (NT) results in greater SOC sequestration because of improved aggregation which protects it from mineralization compared to conventional tillage (CT). Puget and Lal (2005) compared an 8 year old tillage experiment and observed an increase in the SOC concentration under NT compared to CT plots. They concluded that switching from CT to NT sequestered 0.33 Mg C ha-1yr-1. West and Post

(2002) examined global data on CT and NT plots and concluded that changing from CT to NT can sequester an average of 0.57 Mg C ha-1yr-1.

1.2.3 Tillage systems

Tillage practices not only significantly impacts SOC but can also mitigate GHG emissions. The NT system began in the 1940s as an alternative to CT with the

8 development of hormonal herbicides that allowed farmers to control weeds without resorting to plows or hoes (Faulkner, 1943; Blevins and Fyre, 1993). CT refers to a mold board plow tillage system (inversion of the soil) followed by a secondary tillage operation such as disking and /or harrowing (Blevins and Fyre, 1993). Initially, NT was just recommended to control the soil erosion. By developing a litter layer, NT successfully reduces erosion and this has been the principal factor for increased SOM in

NT compared to CT systems (Needelman et al., 1999; Valentin et al., 2008). While tillage increases the aeration of the topsoil and mixes the crop residues with the soil which is considered as a practice that enhances C losses from agricultural soils, NT helps in slowing down the decomposition of crop residues and enhances the stability and aggregation of the topsoil, which potentially would help in conserving C in the surface layer of the soil (Lal, 1997).

Soil disturbance caused by tillage can increase emissions by aerating the soil and mechanically breaking down soil aggregates, causing the release of protected organic C fractions (Ball, 1999; Sainju et al., 2010; Jacinthe and Lal, 2005). In comparison to CT, some studies indicate higher emissions from NT (Ball, 1999; Rochette et al., 2008), and others have reported lower emissions for NT (Chatskikh and Olesen, 2007; Gregorich et al., 2008). ZhiDan et al. (2009) analysed the impacts of NT and CT on the distribution and stability of SOC. Results showed that in 0-5 cm depth, long-term NT soil contained more SOC relative to long-term CT and short-term NT soils, and it was also more labile in the former than in the latter.

1.2.3.1 CO2 emissions

Tillage strongly affects the flux of CO2 from the soil. When soils are tilled, it accelerates SOC oxidation to CO2 by improving soil aeration, increasing contact between soil and crop residues, and exposing aggregate-protected SOM to microbial attack (Beare et al., 1994). In general, CO2 fluxes are less under NT than CT (Reicosky and Archer,

2007). Curtin et al. (2000) measured the CO2 fluxes from a 13 year old tillage treatment plot in Canada. They concluded that the mean annual CO2 fluxes were 20 to 25% less from NT than CT. Lower CO2 fluxes under NT than under CT were attributed to slower decomposition of crop residues placed on the surface of NT soil, compared to residue incorporation under CT. Alluvione et al. (2009) studied the CO2 flux from NT and CT plots during the growing season and observed a 14 % reduction in the cumulative CO2 emissions under NT than CT. Recent studies also show that there is an increase in CO2 emissions from the soil right after tillage operations (Al-Kaisi and Yin, 2005; Omonode et al., 2007; Reicosky and Archer, 2007).

1.2.3.2 CH4 emissions

Mixed responses of soil CH4 fluxes from aerobic soils have been reported across various soil types and regions. There are reports of negative effect on CH4 oxidation on soil of arable cropland soils compared to forest soils (Mosier et al., 1991; Ojima et al.,

1993; Hütsch, 2001), which could be due to the soil structure disturbance associated with agricultural tillage that can reduce the capacity of soils to oxidize CH4, primarily from disruption of methanotrophs and methanogens (Dobbie and Smith, 1996; Powlson et al.,

1997). Other studies have reported an increase in CH4 consumption in NT soils (Hütsch,

1998; Kessavalou et al., 1998; Venterea et al., 2005; Ussiri et al., 2009; Six et al., 2004), while the reverse effect was observed by Omonode et al. (2007) and Venterea et al.

(2005) in conjunction with the application of anhydrous ammonia as fertilizer. Yet other studies have analyzed the differences between the total flux of CH4 from CT and NT and reported that the differences in CH4 fluxes were relatively small or insignificant

(Sanhueza, 1994; Yamulki, 2002; Jacinthe and Lal, 2005; Mosier et al., 2006).

1.2.3.3 N2O emissions

Denitrification is a major source of N2O in agricultural soils, which is more prevalent in soils under NT than CT as a result of higher ρb and moisture content (Doran,

1980; Arah et al., 1991; Palma et al., 1997). As N2O ~ 300 times more potent than CO2, the benefits adopting NT on atmospheric CO2 sequestration could be offset by increased

N2O emissions (Li et al., 2005; Six et al., 2004).

The impact of tillage on N2O emissions is also variable. While some studies indicate higher emissions from NT (Ball et al., 1999; Rochette, 2008), others have yielded lower emissions from NT (Passianoto et al., 2003; Chatskikh and Olesen, 2007;

Gregorich et al., 2008) in comparison to CT soils while other studies have observed no difference between CT and NT treatments (Choudhary et al., 2002; Yamulki and Jarvis,

2002).

Duration since conversion to NT, climatic factor, and soil aeration may also affect

N2O emission. Six et al. (2004) concluded that N2O emissions increased under NT but that this impact decreased over time. The study also reported that net effect not only

11 depends on durationsince conversion to NT but also on the prevailing climatic conditions.

Six and his colleagues observed a clearer reduction in N2O emission under NT in humid than dry areas. Rochette (2008) evaluated soil N2O levels under NT systems located in humid region and concluded that the impact of NT systems on N2O emissions was

−1 −1 negligible in well-aerated soils while N2O emissions increased by 2 kg N ha yr from the soils where aeration was reduced.

1.2.4 Crop residue management

Just as world soils are an important active pool of organic C and N and play a major role in the global C and N cycles, crop residues are also a major renewable resource (Lal, 2004). Crop residue strongly impacts both C and N cycles, and there is a great potential to enhance the sequestration of C and N in soils with the implementation of appropriate tillage methods and crop residue management (Lal and Kimble, 1997;

Follet, 2001). Global annual production of crop residues is about 3.4 Pg (Lal and Bruce,

1999). If 15% of C contained in the residues can be converted to passive SOC fraction, it may lead to C sequestration at the rate of 0.15–0.175 Pg yr-1 by the adoption of conservation tillage and crop residue management, and another 0.18–0.24 Pg yr-1 by the adoption of improved cropping system (Lal and Bruce, 1999). Appropriate residue management in conjunction with the application of nutrients also enhances the humification of biomass. Jacinthe et al. (2002) observed that application of wheat residues with N fertilization increased humification of biomass and enhanced the SOC sequestration rate. Numerous other positive impacts of crop residue retention include

12 improving soil nutrient cycling, infiltration rate, microbial biomass C, microbial activity, and species diversity of soil biota.

1.2.4.1 Mulch amendments

During 1950s and 1960’s, mulching was primarily used to reduce soil erosion and moisture loss from the profile. Several researchers studied the beneficial roles of mulch to conserve soil moisture and reduce soil temperature (Bristow, 1988; Kar, 2003; Kar and

Singh, 2004). Mulch is a poorly conducting material that reduces the flux of incoming solar energy into the soil, and as a result the maximum soil temperature is less in mulched plots (Kar and Kumar, 2007). Mulches are also effective in protecting soil surface from rainfall induced erosion by reducing the rain drop impact and snow melt run off (Rees et al. 2002). Jordan et al. (2010) reported a significant reduction of soil loss, negligible run off generation and enhanced infiltration under high mulching rates. Soil moisture conservation is yet another major advantage of mulch farming system. In Ohio, Mulumba and Lal (2008) studied the effect of soil moisture content under mulch and observed a significant increase in the moisture content as a consequence of greater soil porosity and lower evaporation.

Mulch can provide additional benefits beyond temperature, moisture, and erosion control; moderate GHG fluxes. Application of mulch to cultivated soil increases SOC concentration (Saroa and Lal 2003; Blanco-Canqui and Lal 2007). It also has beneficial effects on SOC sequestration and strongly influences the temporal pattern of CO2 emissions from soil (Jacinthe et al., 2002). Evenly incorporated straw mulch can increase

CH4 emission significantly by a factor of 3.9–10.5, while decreasing N2O emission by 1– 13

78% when compared to no mulch plots (Ma et al., 2009). Mutegi et al. (2010) assessed the impact of residue retention and reported significantly high N2O emissions in CT than

RT (Ridge tillage).

The literature is replete with data on effects of mulching under tillage and cropping systems on a range of physical properties. Several studies have shown positive effects of conservation tillage with straw mulching on different soil properties (Mulumba and Lal, 2008; Blanco-Canqui and Lal, 2007; Duiker and Lal, 1999; Allmaras et al.,

2004; Obalum and Obi, 2010). However, there are limited studies that have simultaneously evaluated the long term effects of NT vs CT on soil properties and GHG emissions under straw mulch of wheat (Triticum aestivum L.) covered fields without any vegetation cover. Thus, the overall objective of this study was to evaluate and compare the long term effects of mulching under NT and CT soils and determine the effects of different mulch rates on GHG emissions and soil properties.

Specific objective of the present study are to: (i) quantify the long term effects of mulching and on gaseous emissions (ii) determine the effects of NT vs CT under different mulch rates on soil physical properties and chemical properties and (iii) assess tillage and mulching impacts on soil quality and the factors affecting it.

These objectives were assessed by testing the following hypothesis: (i) addition of mulch reduces CH4 and N2O emissions more under NT than CT (ii) application of mulch

14 improves soil physical and chemical properties, and (iii) mulch and tillage significantly affects several soil parameters which in turn affects the overall soil quality.

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Alluvione, F., Halvorson, A. D., Del Grosso, S. J., 2009. Nitrogen, Tillage, and Crop Rotation Eff ects on Carbon Dioxide and Methane Fluxes from Irrigated Cropping Systems. J. Environ. Qual. 38, 2023–2033.

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Chapter 2: Mulching and tillage effects on Greenhouse Gas (GHG) emissions

2.1 Abstract

Increasing C stocks in soil requires increasing C inputs and/or reducing soil heterotrophic respiration. Adopting practices that contribute to reduce soil respiration and enhance SOC include reduced tillage practices (especially no-till) and retention of crop residues on soil.

Thus, a field experiment was conducted on an Alfisol in central Ohio to assess the interactive effect of wheat (Triticum aestivum) residue mulch and tillage on Greenhouse

Gas (GHG) emissions. Treatments consisted of three mulch rates: 0 (M0), 8 (M8) and 16

Mg ha-1 yr-1 (M16) and two tillage treatments: No-till (NT) and conventional till (CT). All treatments were replicated thrice and laid out according to a completely randomized design. Fluxes of CO2, N2O, and CH4 were measured using static, closed chambers, on a biweekly basis, from Sept 2010 through July 2011. The data presented showed that application of straw mulch under NT can reduce GHG emissions compared to CT. The

-2 -1 average diurnal CO2 fluxes were lower under NT (8.58g CO2-C m d ) compared to CT

-2 -1 (9.69g CO2-C m d ). The effects of plowing on N2O flux, although not significant,

-2 -1 -2 indicated a trend of higher N2O fluxes under NT (0.27 mg m d ) than CT (0.21 mg m

-1 d ). Similarly there was no definite trend among tillage treatments with regards to CH4 flux. However, NT was more of a sink for CH4 while CT was more of a source. CO2 and

N2O fluxes were significantly affected by mulch treatments, but mulching did not

25 significantly affect CH4 flux. The study showed no consistent correlation between soil moisture content and N2O and CH4 fluxes. However, the diurnal CO2 flux was negatively correlated (r = -0.34 at P<0.0001) with soil moisture content. Additionally, both N2O and

CO2 were not significantly correlated with soil temperatures .On the contrary, CH4 flux was negatively correlated (r =-0.35 at P=0.01) with soil temperature, as is also indicated by increased emissions during winter and reduced emissions during summer.

2.2 Introduction:

As the global atmospheric concentrations of the major Green-house gases (GHG), which include carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) , have been rising in the atmosphere since the beginning of the industrial era (Muñoz, 2010), there is an ever-increasing interest in restraining this growth in order to reduce the potential impacts on the global climate. Concentration of CO2, CH4 and N2O have increased from a pre- industrial value of 280 to 385.2 ppm, 714 to 1797 ppb and 270 to 321.8 ppb in 2008 respectively (WMO, 2009). Anthropogenically induced accumulation of these GHGs has continued to rise at a rapid rate due to burning of fossil fuels, cement production, deforestation, inefficient land use management and conversion (IPCC, 2007). The total C emissions from terrestrial ecosystems, fossil fuel combustion and other energy sources are estimated to be 8.9 Gt yr-1, of which 10–12% (1.69 ± 0.8 Gt C yr-1) is contributed from tropical deforestation and land use change and degradation (Koonin, 2008; IPCC,

2007). This includes 0.76 GtC in the form of N2O emissions and 0.90 GtC in the form of

CH4 emissions (Smith, 2007). World soils have been a major source of increasing C

(CO2, CH4) and N (N2O, NOx) compounds in the atmosphere. However, the identification

26 and implementation of judicious land use management and C sequestration strategies can make soils an important sink for atmospheric CO2 and CH4 (Lal et al., 1995).

Conservation tillage systems such as no-till (NT) vis-à-vis conventional tillage (CT) is promoted as an agricultural practice that can be used to increase soil organic carbon

(SOC) pool concomitant with mitigating GHG emissions (West and Maryland, 2002).

Tillage system may affect soil properties and hence influence GHG emissions (Ussiri et al., 2009). Soil disturbance caused by tillage can increase emissions by aerating the soil and disrupting soil aggregates, causing the release of protected organic C fractions (Ball,

1999; Sainju et al., 2006; Jacinthe and Lal, 2005). In general, CO2 emissions are less under NT than CT (Reicosky and Archer, 2007). Curtin et al. (2000) measured the CO2 fluxes from a 13 year old tillage experiment in Canada, and concluded that the mean annual CO2 fluxes were 20 to 25% less from NT than CT. Lower CO2 fluxes under NT than CT are attributed to slower decomposition of crop residues placed on the surface of

NT soil, compared to residue incorporation under CT. Alluvione et al. (2009) studied the

CO2 flux from NT and CT plots during the growing season and observed a 14 % reduction in the cumulative CO2 emissions under NT than CT. It is widely reported that there is an increase in CO2 emissions from the soil immediately following tillage operations (Al-Kaisi and Yin, 2005; Omonode et al., 2007; Reicosky and Archer,

2007).In comparison, CH4 fluxes from aerobic soils vary across different soil types and eco-regions. The flux of CH4 can be positive from soil under arable land compared to that under forest soils (Mosier et al., 1991; Ojima et al., 1993; Hütsch, 2001).These differences may be due to decline in soil structure caused by disturbance associated with agricultural tillage that can reduce the capacity of soils to oxidize CH4, and from 27 disruption of methanotrophs and methanogens (Dobbie and Smith, 1996; Powlson et al.,

1997). In contrast to CT, soils managed by NT can oxidize CH4 and cause a negative flux (Hutsch, 1998; Kessavalou et al., 1998; Venterea et al., 2005; Ussiri et al., 2009; Six et al., 2004), yet in some NT soils the CH4 flux can be positive (Omonode et al., 2007;

Venterea et al., 2005), especially if measurements are made in conjunction with the application of anhydrous ammonia as fertilizer. This effect may have been related to competitive inhibition of methanotrophic enzyme systems due to substrate similarity between CH4 and NH4 (or NH3). Furthermore, in other studies, the differences in CH4 flux among CT and NT systems are small or insignificant (Sanhueza, 1994; Yamulki,

2002; Jacinthe and Lal, 2005; Mosier et al., 2006). The impact of tillage on N2O emissions is also variable. While some studies indicate higher emissions from NT (Ball et al., 1999; Rochette et al., 2008), others have reported lower emissions (Passianoto et al.,

2003; Chatskikh and Olesen, 2007; Gregorich et al., 2008), and still other studies observed no difference between CT and NT treatments (Choudhary et al., 2002; Yamulki and Jarvis, 2002). Indeed, the interactions of controlling factors for nitrification and denitrification are complex because N2O flux depends on numerous factors including the type of fertilizer, method of application, soil moisture regime, soil temperature and the amount of available O2 (Snyder, 2009).

In conjunction with conservation tillage, crop residue management also has a crucial impact on the C and N cycles, and there is a great potential to enhance the sequestration of C and N in soils. Mulching with crop residues and other biomass has beneficial effects on SOC sequestration, and also strongly influences the temporal pattern

28 of CO2 emissions from soil (Jacinthe et al., 2002). A uniform application of straw increases CH4 emission significantly by a factor of 3.9–10.5, while decreasing N2O emission by 1–78% in comparison with unmulched control. Thus, residue retention plays an important role on N2O emission (Ma et al., 2009). All other factors remaining the same, N2O emissions are significantly higher from soils managed by CT than NT (Mutegi et al., 2010; Chatsisk 2008; Liu et al. 2005)

The literature is replete with data regarding the effects of mulching under different tillage and cropping systems on a range of soil physical properties. In general, mulching with crop residues has positive effects on a wide range of soil properties

(Mulumba and Lal, 2008; Blanco-Canqui and Lal, 2007; Duiker and Lal, 1999;

Allamaras et al 2004; Obalum and Obi, 2010). However, data from long term experiments on the effects of NT vs CT on GHG emissions under straw mulch without the confounding effects of crops are scarce. Therefore, the objective of this study was to

(i) quantify CO2, CH4 and N2O emissions from long term plots under different mulch rates, and (ii) assess the effects of mulch-induced differences in soil temperature and soil moisture regimes on GHG emissions. The hypothesis with respect to the objective-

(i) CH4 and N2O flux would decrease in NT relative to CT, and (ii) the mulch induced effects of soil temperature and moisture would differ from one GHG to the other with respect to their emission process.

2.3 Materials and methods:

2.3.1 Field site and experimental design:

The experimental site was at the Waterman farm of The Ohio State University,

Columbus, Ohio, USA (longitude 83° 01´W 40°00´N). The experiment was initiated in

1989 to study the effects of tillage and mulching with wheat (T. aestivum L.) residue on soil quality, SOC sequestration and dynamics, and GHG emissions. The site has an average annual temperature at 11°C and annual precipitation is 932 mm (USDA, 2004).

The soil at the study site is a Crosby silt loam (Stagnic Luvisol in the FAO classification

(FAO, 1988) and a fine, mixed, active mesic Aeric Epiqualf in the USDA classification

(USDA, 2004).

Mulch treatments consisted of three mulch rates: 0 (M0), 8 (M8) and 16 (M16) Mg ha-1 yr-1 (high) of dry straw. There were two tillage treatments: conventional tillage (CT) and no-till (NT). Each year, the soil under CT was tilled in the spring using a moldboard plow to a depth of 20 cm followed by the application of wheat straw on the CT and NT plots. The residue compacted rapidly after a rain storm and hence, there was no mechanical operation performed to keep the mulch on the plots (Duiker and Lal,

1999).No crops were planted to avoid confounding effects of plant roots. Herbicides

(usually Glyphosates) were applied to eliminate weeds, as and when needed. All the treatments were replicated thrice having a plot size of 2 m x 2 m. A total of 18 plots, based on a factorial combination, were laid out according to a completely randomized block design.

2.3.2 Monitoring CO2, CH4 and N2O fluxes

The CO2, CH4 and NO2 fluxes were measured using the static chamber method (Jacinthe and Dick, 1997; Rolston 1986) on a bimonthly basis from September

2010- July 2011. A polyvinyl gas chamber (PVC) was inserted in each of the 18 plots.

The chamber consisted of two parts: a base and a lid (Figure. 1). The base was approximately 15 cm in diameter and 30cm in length which was coupled to a trough. The lid consisted of a cap fitted with a sampling pot and a rubber septum. Prior to gas sampling, the troughs were filled with water creating a water gasket in order to reduce the gas escape from the chamber.

Figure 1. (a) Gas chamber and (b) Gas chamber fitted with the lid prior to gas sampling (a) (b)

\The chambers were then closed with a lid and approximately 20 ml gas samples were withdrawn and transferred into a crimp sealed and pre-evacuated vials (<0.05 kPa) fitted with rubber septa. The gas sampling was performed over a period of 60min at 0, 30 and

60min with a 20ml syringe. During each gas sampling, soil samples from 0-5cm were

31 collected to determine the soil moisture content. In addition, soil temperature for each plot was recorded at 5 cm and 10 cm depths by using a digital thermocouple probe.

Once the chambers were installed, they remained in place during the entire monitoring period in NT plots but chambers were removed in CT plots during plowing and were re- installed immediately after field operations.

2.3.3 Analysis of gas samples

The analysis of soil air samples for CO2 and CH4 were conducted using a

Schimadzu GC 14 A gas chromatograph fitted with a 3cm long by 0.3cm internal diameter Hayesep D column (Alltech, Deerfield, IL). The gas chromatograph was equipped with a thermal conductivity detector (TCD-CO2 analysis) and a flame ionization detector (FID for CH4 analysis). Helium was used as career gas at a flow rate

-1 -1 -1 of 22 ml min , hydrocarbon-free air (300 ml min ) and H2 (25ml min ) were used as flame gases for CH4 analysis. Detector and the oven temperatures were 150 and 50ºC, respectively.

Soil air samples were analyzed for N2O with Schimadzu GC-14A gas chromatography equipped with a 63Ni electron capture detector (ECD). It was fitted with a pre-column (100cm long and 0.3cm internal diameter) and an analytical column (300 cm long and 0.3 cm internal diameter). These columns were packed with 80/100 mesh

Porapak Q and linked through a time-programmed eight port valve. (Jarecki and Lal,

2006; Jacinthe and Lal, 2003). This configuration was based on elution time differences between O2 and N2O and was programmed to vent out O2 as it elutes out the pre-column

32 which, inturn, reduces the amount of O2 reaching the ECD. The career gas used was an argon-methane (95:5) mixture at a flow rate of 30 ml min-1. The detector and the oven temperature were 350 and 70ºC, respectively. Standard CO2, CH4 and N2O (Altech,

-2 Deerfield, IL) samples were used for GC calibration. Diurnal fluxes of gases (CO2-C m

-2 -2 -1 or mg N2O-N m or mg CH4-C m d ) were computed using Eq (1):

where, ΔCO2-C or ΔN2O-N or ΔCH4-C is the linear change in gaseous concentration

-3 -1 3 inside the chamber (eg. CO2-C m min ); V is the chamber volume (m ), A is the surface area circumscribed by the chamber (m2) and k is the time conversion factor (1440 min day-1). The chamber gas concentrations were converted from molar mixing ratio unit of parts per million (ppm) determined by GC analysis to mass per volume by assuming ideal gas relation.

2.3.4 Data analysis

The treatment effects were examined for each individual sampling date for the gaseous flux data, moisture and temperature parameters using the SAS general linear model (GLM) procedure (SAS institute, Inc 2003). The means were compared by using Fischer’s least significant difference (LSD) test at P=0.05. Pearson correlation coefficients were calculated using SAS to determine the correlation between fluxes and soil parameters.

2.4 Results and discussion

2.4.1 Diurnal CO2 fluxes

-2 -1 The average diurnal CO2 fluxes ranged from 0.81 to 2.41 g CO2-C m d (Table

-2 -1 -2 - 1). The maximum flux from NT was 8.58g CO2-C m d and CT was 9.69g CO2-C m d

1 (Figure 2). The CO2 flux data of this study for all the management regimes were comparable to the study conducted by Duiker and Lal (2000) at the same site and with other studies in Ohio (Jacinthe et al., 2002; Jarecki and Lal, 2006; Elder and Lal, 2008;

Ussiri et al., 2009). The data based on these studies indicated a magnitude of CO2 fluxes

-2 -1 -2 -1 ranging from 0.02 g CO2-C m d to 41.94 g CO2-C m d . Jacinthe and Lal (2002) ,

Jarecki and Lal (2006) and Ussiri et al. (2009) observed CO2 fluxes in Central Ohio

-2 -1 -2 -1 ranging from 0.50 to 4.41g CO2-C m d for mulched plots, 0.26 to 6.77 g CO2-C m d

-2 -1 for compost plots and 0.15 to 6.74 g CO2-C m d for crop residue plots. The present results regarding the effects of the NT and CT on CO2 flux are consistent with the findings from a study in the Cerrado region of Brazilian Amazon (Carvalho, 2009) having similar temperate climate as Ohio. In contrast, there are other studies that showed high average diurnal flux measurements from similar tillage treatments (Chatskikh and

Olesen, 2008; Bauer et al., 2006).

Table 2. Average diurnal GHG from different tillage methods at different mulch rates Gaseous Emissions Mulch Rate CO -C CH -C N O-N Tillage 2 4 2 (Mg ha-1 yr-1) (Mg m-2 d-1) (mg m-2 d-1) (mg m-2 d-1) NT†ﬃ 0 1.34A a (-1.25) A a 0.06A a 8 1.46A ab 1.19A a 0.31A ab 16 2.22A b 0.16A a 0.44A b CT 0 0.81B a (-0.21)A a 0.23A a 8 1.67A ab 0.45A a 0.25A a 16 2.41A b 2.41A a 0.17A a 34

P value Tillage (T) 0.83 0.35 0.41 Mulch (M) 0.001 0.25 0.01 T × M 0.38 0.45 0.07 †Means within columns followed by the same upper case are not significantly different between tillage treatments at P<0.05 ﬃMeans in the same column followed by the same upper case letter are not significantly different between mulch rates at P < 0.05

Anova table F ratio

Parameter CO2-C CH4-C N2O-N Tillage (T) 0.05 (n.s) 0.87(n.s) 0.67(n.s) Mulch (M) 7.01** 1.41(n.s) 4.81* T × M 0.97 (n.s) 0.79(n.s) 2.69(n.s) * P<0.05 ** P< 0.01 n.s- not significant at P<0.05

7.0

(a) 6.0

5.0

)

- d

2 2 4.0

- M0/NT

3.0

C (g C M0/CT -

2 2.0 CO 1.0

0.0

Jul

Oct

Sep Feb

Dec

Aug

Mar

- -

May

1 -

4 1

23 12 Sampling Date

Figure 2. (a), (b) and (c) represents the diurnal CO2 flux from different mulch treatment and different tillage plots. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1 respectively. ** Bars represent LSD Value at P < 0.05 between NT and CT.

Figure Continued .

Figure Continued

16.0 (b) 14.0

12.0

) 1

- 10.0

d 2 2

- 8.0 M8/NT

6.0 M8/CT

C (g C -

2 4.0 CO 2.0

0.0

Jul

Oct

Sep Feb

Dec

Aug

Mar

- -

May

1 -

4 1

23 12

Sampling Date

20.0 ) )

1 15.0

2 2

- m 10.0 M16/NT

C (g C M16/CT -

2 5.0 CO

0.0

Jul

Oct

Sep Feb

Dec

Aug

Mar

- -

May

1 -

4 1

23 12

Sampling Date

Significant treatment effects on soil CO2 flux were observed throughout the monitoring period among tillage and mulch treatments. Tillage treatment (NT and CT), had a significant effect (P<0.05) on the diurnal average fluxes, and the fluxes were comparatively higher in CT than in NT [Table 1; Figure 4(a)]. Lower CO2 emissions from NT compared to CT were consistent with results from other studies (Al-Kaisi and

Yin, 2005; Reicosky and Archer, 2007; Alluvione, 2009). Similarly, significant

-1 -1 differences (P<0.05) were observed in CO2 flux between 0 and 16 Mg ha yr mulch

rate (Figure 3), with average fluxes being generally higher in the mulched than in the

unmulched plot. Higher CO2 fluxes were attributed to the increased surface roughness

and voids that are created by soil disturbance that accelerate decomposition of SOM by

CT (Ussiri et al., 2009; Elder and Lal, 2008).

16.0

(a) 14.0

) 12.0

d 2 2

- 10.0 m

8.0 C (g C

- M0/NT 2 6.0

CO 4.0 2.0

0.0

Jul

Oct

Sep Feb

Dec

Aug

Mar

- -

May

1 -

4 1

23 12 Sampling Date

(b) 25.0

) 20.0

d 2 2

- 15.0

M0/CT

C (g C 10.0 - 2 M8/CT CO 5.0 M16/CT

0.0

Jul

Oct

Sep Feb

Dec

Aug

Mar

- -

May

1 -

4 1

23 12 Sampling Date

Figure 3. (a) represents the diurnal CO2 flux from different mulch treatment under NT. (b) represents the diurnal CO2 flux from different mulch treatment under CT. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1 respectively. ** Bars represent LSD Value at P < 0.05 between M0, M8 and M16. 37

3.5

) 1

- 3

d 2 2 - 2.5 2

NT C (gm C

- 1.5 2

1 CT CO 0.5 0 0 8 16 Mulch Rate (Mg ha-1 yr-1)

0.5

) 1

- 0.4

- m

0.3 N(mg

- 0.2 NT

O 2

N PT 0.1

0 0 8 16 Mulch Rate (Mg ha-1yr-1)

6.0

5.0

) 1

- 4.0

- 3.0

2.0 NT

C (mg C 1.0 -

4 4 CT

0.0 CH -1.0 -2.0 0 8 16 Mulch Rate (Mg ha-1 yr-1)

Figure 4. (a), (b) and (c) represents the Average diurnal CO2, N2O and CH4 respectively flux from different mulch treatment and different tillage plots. *Bars represent LSD value at P < 0.05 between NT and CT 38

12 (a)

10 y = 0.2043e0.0923x

R² = 0.63

)

1 8

2 - 6

CO2

C (g (g C m

- 2 Expon. (CO2) CO 4

0 -10 0 10 20 30 40 Air Temperature (°C)

12 (b)

y = 2.4772e-0.029x

) R² = 0.12

1 8

2 - 6

CO2

C (g (g C m

- 2 Expon. (CO2) CO 4

0 0 20 40 60 80 100 Volumteric Moisture Content (m3 m-3)

Figure 5. (a) CO2 flux varying with air temperature (b) CO2 flux varying with volumetric moisture content

z=-0.31+0.07x+0.01y+0.001xy R2=0.42

Figure 5(c) A 3-D representation of CO2 flux varying with moisture and air temperature.

r Additionally, the measu ed CO2 flux had high seasonal variability. The flux patterns were divided into four different periods - autumn (September 15-December 5), winter

(December 6 to March 20), spring (March 20-June 21), and summer (June 22- September

21) (Ussiri et al., 2009). The CO2 flux was in the order of spring > summer > autumn > winter. The maximum observed CO2 fluxes were measured during the end of May and

July 2011(high soil temperatures), and the lowest flux was recorded in December, 2010, corresponding with the lowest soil temperatures. The low CO2 fluxes during winter are attributed to low temperatures owing to minimal soil microbial activity, and hence reduced soil respiration (Ussiri et al.,2009; Al Kaisi and Yin, 2005). However, there was no statistically significant correlation between CO2 flux and soil temperature. It could be due to the lack of adequate temperature sample point (5 sample points only). Similar results were reported by Koizumi et al. (1999) and Jarecki et al. (2006). Nonetheless, there existed a negative correlation (r = -0.34207 at P<0.0001) between soil moisture content and CO2 emission.

2.4.2 Diurnal N2O fluxes

All tillage treatments recorded an average positive flux of N2O. The mean diurnal

-2 -1 fluxes ranged from 0.06 to 0.44 mg N2O-N m d (Figure 4). Although there were no significant differences between tillage treatments, the mean N2O fluxes were comparatively higher under NT than those from CT except at M0 [Table 1; Figure 3(b)].

These data are in accord with those reported by Gregorich et al. (2008) and Baggs et al.

(2003), Rochett et al. (2008). The underlying mechanism related to higher N2O fluxes could be due to the litter accumulation at the surface thereby increasing N substrate in the

41 top layer under NT (MacKenzie, 1998; Baggs et. al, 2003). Yet, other studies have shown that N2O fluxes can be higher from CT when compared to NT plots (Chatskikh and

Olesen, 2008; Liu et al. 2005; Elder and Lal, 2008; Ussiri et al., 2009; Jarecki and Lal,

2006; Mutegi et al., 2010).

2.0

1.5

)

d 2

- 1.0

0.5

N(mg m N(mg M0/NT

- 0.0 O

2 M0/CT N -0.5

-1.0

Jul

Jan

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

1 -

4 1

2 30 Sampling Date

3.0

2.5

) 1

- 2.0

d 2

- 1.5

1.0

N(mg M8/NT

- 0.5 O 2 M8/CT

N 0.0 -0.5

-1.0

Jul

Jan

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

- 1

4 1

2 30 Sampling Date

Figure 6: (a), (b) and (c) represents the diurnal N2O flux from different mulch treatment and different tillage plots. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1 respectively ** Bars represent LSD value at P < 0.05 between NT and CT

Figure Continued 42

Figure Continued

12.0

10.0

)

1 -

d 8.0

2 - 6.0 4.0

N(mg m N(mg M16/NT

- O

2 2.0 M16/CT N 0.0

-2.0

Jul Jul

Jan

Jun

- -

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

4 1

2 30 Sampling Date

Mulch application rate had a significant effect on N2O flux with average fluxes generally higher from mulched compared with unmulched plots (Figure 5). These results corroborated with those reported by Huang et al. (2004) and Jarecki and Lal (2006). The default IPCC conversion factor assumes that 1% of N in treatment with unburnt crop residue are converted to N2O (IPCC, 2006), which implies that agricultural systems that retain crop residues in the field will always observe an increase in N2O fluxes (Mutegi et al., 2010).

4.5 4.0

3.5

) 1

- 3.0

d 2 - 2.5 2.0 M0/NT

1.5 N(mg m N(mg

- 1.0 M8/NT O 2 0.5 N M16/NT 0.0 -0.5

-1.0

Jul

Jan

- -

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

4 1

2 30 Sampling Date

2.5

2.0

) 1

- 1.5

2 - 1.0 M0/CT

0.5 N(mg m N(mg

- M8/CT O 2 0.0 N M16/CT

-0.5

-1.0

Jul

Jan

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

1 -

4 1

3 2 Sampling Date 30

Figure 7. (a) represent the diurnal N2O flux from different mulch treatment under NT. (b) represent the diurnal N2O flux from different mulch treatment under CT. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1 respectively. ** Bars represent LSD value at P < 0.05 between M0, M8 and M16.

There were no clear seasonal variations observed in the mean diurnal fluxes for

N2O .The maximum flux was observed during the month of July, 2011 and the lowest during the snowy months of January, 2011. There was an observed increase in the N2O flux from winter to spring, and this peak is attributed to the rapid rise in air and soil

44 temperatures. Episodic flux of N2O may occur when well-aerated soils become moistened or saturated from precipitation or irrigation, or when frozen soils thaw (Snyder, 2009)

These trends are consistent with the results reported by others for similar soils and climate (Ussiri et al., 2009; Jacinthe and Lal, 2009). On the other hand, there were reduced N2O fluxes during winter due to low temperatures owing to reduced microbial activity. However, the current study did not show any statistical significant differences in

N2O fluxes because of management induced effects on soil temperature or soil moisture regime.

2.4.3 Diurnal CH4 fluxes

-2 -1 The mean diurnal CH4 flux ranged from -1.21 to 2.41 mg CH4-C m d (Figure 6). The

CH4 fluxes were highly variable, and exhibited large fluctuations between emissions and uptake throughout the monitoring period. Hence, there was no observed significant difference in flux between sampling dates and management regimes (Table 1). The negative flux or CH4 uptake was observed more often in NT (8 out of 17 sampling events) than CT plots (5 out of 17 events). The results of CH4 flux are in accord with those reported by other studies from temperate regions (Jacinthe and Lal, 2004; Venterea et al., 2005; Jarecki and Lal, 2006; Ussiri et al., 2009). The uptake (or oxidation) of CH4 in NT may be attributed to the protected environment created for the CH4 oxidizers by

NT, improved macro porosity, and higher gaseous diffusion. Plowing disrupts the

45 ecological niche for methanotrophic bacteria, influence the gaseous diffusivity, and affect the rate of supply of atmospheric CH4 (Hutsch, 1998).

Significant negative correlations (r =-0.35160 at P=0.01) were observed between soil temperatures and CH4 flux. The highest CH4 fluxes were recorded during the spring thaw

(May 2011) in all treatments. In contrast, the maximum CH4 uptake was measured during the summer (July 2011). The results from this study differ from some previous studies.

The general trend that has been reported from other studies indicates that winter emissions comprise a large portion of the annual CH4 flux (Kern et al., 2011; Elder and

Lal, 2008; Jacinthe and Lal, 2003).

Conversely, Hyvönen et al. (2009) reported results in which the mean CH4 flux was higher in the closed chamber method (without snow) than in the snow gradient measurements. Hence, the reduced flux in the winter may be attributed to: (i) accumulation of snow over the uppermost soil layer limiting the gas transport from the soil to the atmosphere (Hyvönen, 2009), and (ii) reduction in microbial activity owing to low temperatures.

10.0

6.0

) 1

- 2.0

2 - -2.0 -6.0

-10.0 M0/NT C (mg m (mg C - -14.0 4 4 M0/CT

-18.0 CH -22.0

-26.0

Jul Jul

Jan

Jun

- -

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

4 1

3 2 Sampling Date 30

22.0

17.0

)

- d

12.0

2 - 7.0

2.0 M8/NT

C (mg m (mg C -

4 4 -3.0 M8/CT

CH -8.0

-13.0

Jul Jul

Jan

Jun

- -

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

1 -

4 1

2 30 Sampling Date

25.0

20.0

) 1

- 15.0

2 10.0

- m

5.0 0.0

-5.0 M16/NT

C (mg C -

-10.0 4 M16/CT

-CH 15.0 -20.0

-25.0

Jul

Jan

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

1 -

4 1

3 2 Sampling Date 30 Figure 8: (a), (b) and (c) represents the diurnal CH4 flux from different mulch treatment and different tillage plots. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1 respectively. **Bars represent LSD at P < 0.05 Value between NT and CT 47

30.0

20.0

)

- d

10.0

0.0 M0/NT C (mg C - M8/NT 4 4 -10.0

CH M16/NT -20.0

-30.0

Jul

Jan

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

1 -

4 1

2 30 Sampling Date

30.0

20.0

)

- d

10.0

2 -

0.0 M0/CT C (mg m (mg C

- M8/CT 4 4 -10.0

CH M16/CT -20.0

-30.0

Jul

Jan

Jun

Oct

Apr

Sep Feb

Dec

Aug

Nov

Mar

- -

May

1 -

4 1

2 30 Sampling Date Figure 9. (a) represents the diurnal CH4 flux from different mulch treatment under NT. (b) represents the diurnal CH4 flux from different mulch treatment under CT. *M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1 respectively. ** Bars represent LSD at P < 0.05 between M0, M8 and M16.

However, the results obtained on the uptake of CH4 during summer in the present study are consistent with those presented in earlier reports. The high CH4 flux may be attributed to the increased soil moisture during the end of winter (thawing period) or during winter 48 which indicates the occurrence of anaerobiosis and increase in methanogenesis (Ussuri et al., 2009). However, there was no observed statistical difference between soil moisture and CH4 fluxes.

2.5 Conclusion

The significant interaction between the management regimes and the magnitude of the different GHG flux measurements, have important implications with respect to identification of strategies for mitigating and adopting to climate change through adoption of recommended management practices. The data presented indicate that application of straw mulch under NT can reduce GHG emissions compared to CT. The average diurnal CO2 fluxes were lower under NT compared to CT treatment, which may be due to improved aeration caused by plowing, especially prior to the formation of surface seals. The effects of plowing on N2O flux, although not significant, indicated a trend of higher N2O fluxes under NT than CT, which may be attributed to the increased substrate accumulation in NT treatments. There was no definite trend among tillage treatments with regards to CH4 flux However, NT treatments were more a sink of CH4 than CT. Furthermore, CO2 and N2O fluxes were significantly affected by mulch treatments, but mulching did not significantly affect CH4 flux. The average diurnal CO2 flux from plots with a mulch rate of 16 Mg ha-1 yr-1 was approximately twice as much as that from the unmulched plots. There were no consistent correlation between soil moisture content and N2O and CH4 fluxes. However, the diurnal CO2 flux was negatively correlated with soil moisture content. Additionally, both N2O and CO2 were not significantly correlated with soil temperatures .On the contrary, CH4 flux was negatively

49 correlated with soil temperature, as is also indicated by increased emissions during winter and reduced emissions during summer. Additional research is needed to better understand the over-all impact and interactions between management regimes and GHG emissions, especially in relation to soil properties and climate factors. Studying the stable isotopic

- concentrations of CO2 can be useful to identify the CO2 sources and assessing the NO3 levels within soil solution can be a useful indicator of N2O emissions.

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Ma, J., Ma, E., Xu, H., Yagi, K., 2009. Wheat straw management affects CH4 and N2O emissions from rice fields. Soil Biol. Biochem. 41, 1022-1028.

MacKenzie, A. F., Fan, M. X., Cadrin, F., 1998. Nitrous oxide emissions in three years as affected by tillage, corn-soyabean-alfaalfa rotation and nitrogen fertilization. J. Environ. Qual. 27, 698-703.

Mosier, A., Schimel, D., Valentine, D., Bronson, K., Parton, W., 1991. Methane and nitrous oxide fluxes in native, fertilized and cultivatedgrasslands. Nature (London). 350, 330–332.

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Omonode, R.A., Vyn, T. J., Smith, D. R., Hegymegi, P., Gal, A., 2007. Soil carbondioxide and methane fl uxes from long-term tillage systems in continuouscorn and corn-soybean rotations. Soil Till. Res. 95, 182–195.

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Chapter 3: Mulching and tillage effects on soil physical and chemical properties

3.1 Abstract

No till (NT) practice in conjunction with crop residue mulch, can improve soil quality and enhance the sequestration of C and N in soils. However, the magnitudes of these impacts are soil and site- specific. Therefore, the objective of this study was to evaluate the long term effects of application wheat (Triticum aestivum) residue mulch under NT and conventional tillage (CT) on soil physical and chemical properties in an ongoing long-term experiment in Central Ohio. Treatments included three rates of mulch at 0 Mg ha-1 yr-1 (M0), 8 Mg ha-1 yr-1 (M8) and 16 Mg ha-1 yr-1 (M16) without crop cultivation.

All treatments were replicated thrice and laid out according to a completely randomized design. The selected key parameters evaluated were bulk density (ρb), soil moisture content, soil temperature, pH, electrical conductivity(EC) and C and N concentrations associated with macro and micro-aggregates. Soil decreased with increase in mulch

-3 rate in NT and CT treatments, and mean was lower in NT (1.25 – 1.45Mg m ) than

CT (1.39 - 1.49 Mg m-3). Mulching significantly reduced the diurnal amplitude of soil temperature by increasing the minima and decreasing the maxima. The maximum soil temperatures in the surface layer were 4 – 6°C lower in the mulched than in the unmulched plots. Over the year, soil moisture content (SMC) was significantly higher in mulched than unmulched plots. The average pH in soil under NT (5.7 - 6.1) was lower

57 than that under CT (5.8 - 6.3). Mulch treatments also significantly affected soil pH, being lower in mulched than unmulched soil. There were no definite trends in concentration of

C and N associated with macro and micro aggregates because of large variations between treatments. The general trend indicated that mean concentrations of C and N in macroaggregate were somewhat higher in NT than CT, and also higher under mulched than unmulched plots. These trends support the hypothesis that the reduced soil disturbance in

NT with residue retention enhances soil quality, improves aggregation, and conserves soil moisture.

3.2 Introduction

Just as world soils are an important pool of organic C and N and play a major role in the global cycles of these elements, crop residues and their management also have a crucial impact on the C and N cycles (Lal, 2004). There is a great potential to enhance the sequestration of C and N in soils with the implementation of appropriate tillage methods and crop residues management systems (Lal and Kimble, 1997; Follet, 2001).

The annual production of crop residues is about 3.4 billion Mg (Gt) in the world (Lal and

Bruce, 1999). If 15% of C contained in the residue can be converted to passive SOC fraction, it may lead to C sequestration at the rate of 0.15–0.175 Pg yr-1 by the adoption of conservation tillage and crop residue management, and another 0.18–0.24 Pg yr-1 by the adoption of improved cropping system (Lal and Bruce, 1999).

The proposed C sequestration strategies involve increased input of crop residues while minimizing C loses by erosion and decomposition. These strategies can be accomplished by mulching, in which crop residues are applied on to the soil surface to 58 reduce soil erosion and conserve soil moisture loss from the profile (Follett, 2001;

Jacinthe and Lal, 2002). In general, mulching conserves soil moisture and moderates soil temperature (Kar, 2003; Kar and Singh, 2004). Being a poorly conducting material, mulch reduces the incoming solar energy into the soil, and as a result the maximum or summer time soil temperature is less in mulched than in unmulched plots (Kar and

Kumar, 2007; Sharatt, 2002). Mulches are also effective in protecting soil surface by reducing rain drop impact and snow melt run off (Rees et al., 2002). Mulching helps in significantly reducing soil loss, reducing run off, and enhances water infiltration rate

(Jordan et al., 2010; Sharatt, 2000; Johnston et al., 2002; Shaver et al., 2002). Soil moisture conservation is a major advantage of mulch farming system. Application of mulch leads to a significant increase in the moisture content as a consequence of greater soil porosity and lower evaporation (Ji and Ugner, 2001; Mulumba and Lal, 2008).

Surface mulching has variable effects on soil bulk density. Some researchers observed a decrease in bulk density under mulch (Khurshid, 2006; Ojeniyi, 2008; Glab and Kulig,

2008; Blanco-Canqui et al., 2007) while few reported an increase in the bulk density

(Bottenberg. et al, 1999). Yet others observed no significant effect of mulching on bulk density (Obalum, 2010; Mulumba, 2008; Duiker, 1999).

During decomposition of crop residues, organic acids are formed resulting in the short term increase of soil acidity (Ismail, 1994). Hence, assessments of soil pH and electrical conductivity (EC) may provide better insights on the interaction of tillage and mulch systems on soil properties. In most cases, there may be no significant effects of

59 tillage systems and mulching on soil pH (Obalum, 2011; Agbede and Ojeniyi, 2009;

Chaterji and Lal, 2008).

Mulching generates additional benefits beyond temperature, moisture, and erosion control, which involve moderating fluxes of principal greenhouse gases (GHGs).

Application of mulch to cultivated soil in particular increases soil organic carbon (SOC) and N concentrations (Sainju, 2006; Sarao and Lal 2003; Blanco-Canqui and Lal 2007).

Mulching also has beneficial effects on SOC sequestration, through strong influences on temporal patterns of CO2 emissions from soil (Jacinthe et al., 2002). One of the major objectives of the adoption of techniques of sustainable management of soil resources is to increase the SOC pool, an important indicator of soil quality and agronomic sustainability because of its impact on other physical, chemical and biological properties of soil

(Sharma et al., 2008). It contributes to productivity and environmental quality through its role in supplying nutrients, elemental recycling, enhancing soil/plant water reserves, increasing soil buffering capacity, and stabilizing soil structure (Hobbs et al., 2008).

Hence it is relevant to adopt soil and crop management systems that accentuate humiﬁcation and increase the stable or non-labile fraction of SOC (Gulde, 2007).

The quantity and quality of SOC depends on wide range of factors including tillage practices, crop residue management, climate, landscape position and vegetation. Arable land almost always has lower SOC concentration than land under forest or pastures

(Franzluebbers, 2005). This trend could be due to stimulation of decomposition of soil organic matter (SOM) which occurs during cultivation involving frequent tillage and disrupting the SOM protected in aggregates and redistributing it in the soil profile where 60 environmental conditions increase its decomposition. Several studies have shown that no- till (NT) accompanied with mulching results in greater SOC sequestration because of improved aggregation that protects it from mineralization compared to conventional tillage (CT). West and Post (2002) examined the global data on CT and NT plots and concluded that changing from CT to NT can sequester an average of 0.57 Mg C ha-1yr-1.

Puget and Lal (2005) compared 56 paired tillage experiments and observed an increase in the SOC concentration under NT compared to CT plots. They concluded that switching from CT to NT sequestered 0.33 Mg C ha-1yr-1. Increased SOC levels with NT compared to CT management have often been observed concomitant with enhanced soil aggregation in temperate soils (Six et al., 2000; Zotarelli et al., 2005). Increases in total

SOC under NT relative to CT management are attributed not only to a greater amount of

C-rich macro-aggregates (>250um), but also to a reduced rate of macro-aggregate turnover under NT (Six et al., 2000). The slower turnover of macro-aggregates may enhance the formation of highly stable micro-aggregates in which C is stabilized and sequestered in the long term.

Therefore, the objective of this study was to evaluate the effects of different tillage and mulching systems on selected soil physical and chemical properties. The hypothesis with respect to long term straw management and NT are: (i) bulk density decreases in NT, and with increase in mulch rate, (ii) soil temperature is stabilized in summer with mulch compared to unmulched plots, (iii) residue application increases soil moisture content, and (iv) mulching increases the macro and micro- aggregate C content, stabilizes pH and electrical conductivity (EC).

3.3 Materials and method:

3.3.1 Field site and experimental design:

The experimental site was at the Waterman farm of The Ohio State University,

Columbus, Ohio, USA (longitude 83° 01´W 40°00´N). Measurements were made on a long-term experiment initiated in 1989 to study the effects of tillage and mulching with wheat (T. Aestivum L.) residue on soil physical quality, SOC sequestration and dynamics, and GHG emissions The site has an average annual temperature at 11°C and annual precipitation is 932 mm (USDA, 2004). The soil at the study site is a Crosby silt loam

(Stagnic Luvisol in the FAO classification (FAO, 1988) and a fine, mixed, active mesic

Aeric Epiqualf in the USDA classification (USDA, 2004).

Mulch treatments consisted of three mulch rates: 0 Mg ha-1 yr-1 (M0), 8 Mg ha-1 yr-1

(M8) and 16 Mg ha-1 yr-1 (M16) of dry straw. There were two tillage treatments: conventional tillage (CT) and no-till (NT). Each year, the soil under CT was tilled in the spring using a moldboard plow to a depth of 20cm followed by the application of wheat straw on the plots. The residue compacted rapidly after a rain storm and hence, there was no mechanical operation performed to keep the mulch on the plots (Duiker and Lal,

1999).No crops were planted to avoid confounding effects of plant roots. Herbicides

(usually Glyphosate) were applied to eliminate weeds, as and when needed. All treatments were replicated thrice having a plot size of 2 x 2 m. A total of 18 plots, based on a factorial combination, were laid out according to a completely randomized block design.

3.3.2 Determination of soil physical properties:

Soil samples were collected from all plots for 0-10 cm and 10-20 cm depths in

July 2009 for determination of soil properties. Undisturbed samples were collected from each plot using a core of 5.5 cm diameter and 6 cm long cores from 0-10 cm and 10-

20cm depths for bulk density (ρb) measurements. Dry ρb was computed for each depth by knowing the gravimetric moisture content (Blake and Hartge, 1986) and it was corrected for gravel (>2mm). The dry weight of the soil was obtained by oven drying it at 105°C for 48 hours until the constant weight was obtained. Dry ρb was computed using the following Eq (1):

…………………………………………………………………………………………………………...... (1) where, ρb is the dry bulk density, Ms is the mass of oven dried soil at 105°C and Vt is the total volume of the soil (volume of the core).

Soil temperatures at 5cm and 10cm depths were measured using a digital thermocouple probe, spike stem thermometer inserted into the soil. Soil moisture content was determined gravimetrically on bulk samples obtained from each plot on two week intervals at approximately 5cm depth and dried at 105°C.

Gravimetric water content was calculated by using Eq (2):

……………………………………………………………………. (2) where, θg is gravimetric water content, Mw is mass of the wet soil sample, and Md is the mass of the soil sample dried at 105°C.

3.3.3 Determination of chemical properties

Bulk soil samples were air dried and sieved through a (5 – 8 mm) sieve. 50 g of the 5 – 8 mm sieved aggregates were placed on a nested stack of sieves (4.75, 2, 1, 0.5, and 0.25 mm). These aggregates were pre-wetted for 30 minutes, and wet-sieved for 30 minutes at

30 cycles min-1 with oscillation of 1.25 cm. Aggregates were separated using a wet sieving apparatus (Yoder, 1936) as described by Nimmo and Perkins (2002). Aggregates retained on each sieve were then washed off from the sieve with deionized water and collected in separate beakers 0 - 0.25 mm-micro aggregates and 0.25 – 4.75 mm- macro aggregates and oven dried at 60°C for 72 hrs. Soil samples were ball milled to produce a fine and homogeneous mixture, and analyzed for macro and micro-aggregate C and N concentrations by the dry combustion method at 900°C (Nelson and Sommers, 1996) using an elemental analyzer (Elementar Vario MAX; GmbH, Hanau, Germany). Because the pH was below 7, the soil was assumed to have no inorganic C in 0-20 cm depth.

Hence, the C values obtained were assumed to be equal to SOC.

Soil pH and EC values of 0–5 cm soil depth were measured electrometrically using a

Thermo Scientific Orion 4 star (Thermo Fisher Scientific Inc., Beverly, MA) of 1:2.5 soil/water extract (Thomas, 1996; Rhoades, 1996).

3.3.4 Statistical analysis

The effects of tillage practice and mulch rate for physical (bulk density, soil temperature, soil moisture) and chemical parameters (pH, EC, micro and macroaggregate C and N) were determined using the SAS general linear model (GLM) procedure (SAS institute, Inc 2003). The means were compared by using Fischer’s least significant difference (LSD) test at P=0.05. Pearson correlation coefficients were calculated using SAS to determine the correlation between soil parameters.

3.4 Results and discussion:

3.4.1 Soil physical parameters

3.4.1.1 Soil bulk density under different mulch and tillage treatments

-3 The mean soil for each mulch rate was greater in CT (1.39 - 1.49 Mg m ) than NT

-3 (1.25 – 1.45 Mg m ) soil samples. Soil was not significantly different between NT and CT for M0 and M8 irrespective of the depth. In contrast, significant differences were observed between NT and CT at the M16 rate. Lower soil in NT compared to CT is consistent with results of Sur, 2001; Ussuri et al., 2009, Blanco et al., 2009; Nyamadzawo et al., 2009; and Ishaq et al, 2002. Terbugg and During (1999) reported that soil decreased in the surface layer (0-3cm) under long-term NT treatments and that explained it as a direct consequence to the mulch layer on top of NT soils that provide soil organic 65 matter (SOM) and food for soil fauna which, in turn, increased earthworm activity

(bioturbation) indicative of protected soil structure. Contrary to these findings, several authors have reported a higher mean value for of NT soils compared to CT soils

(Khurshid, 2006; Singh and Mahli, 2006). Yet, some others reported mixed results with regards to soil and tillage (Blanco-Canqui et al., 2009; Chatterji, 2009).

Bulk Density (0-10 cm) 1.70

1.60

)

3 1.50 - 1.40 NT

(Mg m (Mg 1.30

푏

휌 1.20 CT 1.10 1.00 0 8 16 -1 -1 Mulch Rate (Mg ha yr )

Bulk density (10-20 cm) 1.70

1.60

)

3 1.50 - 1.40

(Mg m (Mg 1.30 NT

푏

휌 1.20 CT 1.10 1.00 0 8 16 Mulch Rate (Mg ha-1 yr-1)

Figure 10. (a), (b) represents the average bulk density of 0-10 cm and 10-20 cm respectively for different mulch rates and tillage treatments. *Bars represent LSD Value between NT and CT at P < 0.05

Figure Continued

Bulk density (Average) 1.70

1.60

) 1.50

3 - 1.40

(Mg m (Mg 1.30 NT

푏 휌 1.20 CT 1.10 1.00 0 8 16 Mulch Rate (Mg ha-1 yr-1)

Soil decreased with increasing mulching rates. Mean was lower in mulched (1.25 -

-3 -3 1.44 Mg m ) than unmulched (1.45 – 1.49 Mg m ) soil. Soil was significantly different between 0 and 16 Mg ha-1 yr-1 mulch rate in NT. In contrast, no differences were observed in M0, M8 or 16 under CT. Decreasing soil with increasing mulch rates were in accord with studies conducted by Khurshid, 2006; Ojeniyi, 2008; Glab and Kulig,

2008; Jordan et al., 2009 and Blanco, 2007. The decrease in soil under mulch could be attributed to increase in SOM and total porosity (Oliviera and Merwin, 2001; Pervaiz et al., 2009). However, the interactive effect of mulch and tillage was non-significant.

Table 3. Mean bulk density, moisture and temperature under tillage treatments at different mulch rates. Mulch Rate Bulk density Moisture Temperature (°C) Tillage -1 -1 -3 (Mg ha yr ) (Mg m ) (v/v %) (0-5 cm) (5-10 cm) NT†ﬃ 0 1.45 A a 33.24 A a 25.09 A a 22.93 A a 21.01 A 19.79 A 8 1.35 A ab 40.05 A b b ab 20.45 A 16 1.25 A b 44.41 A c 19.15 A b b CT 0 1.50 B a 32.09 A a 24.69 A 22.35 A a 8 1.44 A a 37.86 A b 21.36 A 19.93 A a 16 1.40 A a 42.45 A c 21.03 A 19.17 A a

P value Tillage (T) 0.09 0.95 0.86 0.89 Mulch (M) 0.12 0.05 0.002 0.02 T × M 0.72 0.78 0.92 0.96 †Means in the same column followed by the same upper case letter are not significantly different between tillage treatments P < 0.05 ﬃMeans in the same column followed by the same lower case letter are not significantly different between mulch rates at P < 0.05 Anova table F ratio Parameter Temperature Bulk density Moisture (0-5 cm) (5-10 cm) Tillage (T) 3.38 (n.s) 0.004 (n.s) 0.03 (n.s) 0.02 (n.s) Mulch (M) 2.52 (n.s) 2.98* 6.87 ** 4.13* T × M 0.35 (n.s) 0.25 (n.s) 0.09 (n.s) 0.04 (n.s) * P<0.05 ** P< 0.01 n.s- not significant at P<0.05

3.4.1.2 Soil moisture under different mulch and tillage treatments

Although tillage treatments did not have significant effect on soil moisture content, NT retained slightly higher moisture (0.23-0.36 % v/v) content than CT (0.21-0.31 % v/v).

These results are similar to those reported by Pervaiz (2009), Vita (2007) and Gruber

(2011). In contrast, mulch rates significantly affected soil moisture content in NT and CT, the maximum was recorded for M16 (0.31 - 0.36% v/v) followed by M8 (0.26 - 0.30 % v/v), and the minimum in M0 (0.21 - 0.23% v/v). These results are in accord with those reported by Govearts (2009); Bunna 2011; Fuentes 2009; Liu 2011; Agarwal and

Sharma, 2002. Pervaiz (2009) and Khurshid et al. (2006) concluded that mulching improves the ecological environment of the soil and significantly increases soil water content. Mulching is also effective in reducing water evaporation rate by forming a barrier between the soil surface and the atmosphere and thus reducing the vapor pressure gradient at the soil–atmosphere interface (Gupta and Acharya, 1993).

100 90 80

)

m 60

3 3 5cm)

- 50 M0/NT (0

40 M8/NT VMC VMC (m 30 M16/NT 20 10 0 10-Aug 29-Sep 18-Nov 7-Jan 26-Feb 17-Apr 6-Jun 26-Jul 14-Sep Sampling Date

120

100

)

m 3 3

5cm) 60 M0/CT -

(0 M8/CT VMC (m VMC 40 M16/CT

0 10-Aug 29-Sep 18-Nov 7-Jan 26-Feb 17-Apr 6-Jun 26-Jul 14-Sep Sampling Date

Figure 11. (a) and (b) represents the diurnal VMC (volumetric moisture content) from different mulch treatment and tillage treatments. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1, respectively. ** Bars represent LSD Value between M0, M8 and M16

) ) %

- m 3 3 30 NT

20 CT VMC (m VMC

0 0 8 16 Mulch Rate (Mg ha-1 yr-1)

Figure 11(c) represents the average VMC from different mulch and tillage treatments. *Bars represent LSD at P < 0.05 between NT and CT

3.4.1.3 Soil temperature under different mulch and tillage treatments

Mulch treatments had significant effect on soil temperature but no significant difference was observed among tillage treatments. Treatments with M0 and M 8, M0 and M16 had significantly different temperatures; however M8 and M16 had similar temperatures in

NT at 0-5 cm depths. In contrast, there was only significant difference between M0 and

M16 in soil temperature for 5-10 cm depths for both NT and CT. Reduced temperature in mulched compared to unmulched plots was also reported by Liu et al. (2011) and Kar and

Kumar (2007). The maximum soil temperatures in the surface layer were 4–6°C lower in the mulched than in the unmulched plots. The higher albedo of the mulch and its lower thermal conductivity than bare soil reduces the transmission of solar radiation to the soil layer (Kar and Kumar, 2007; Sharatt, 2002) and reduces the magnitude of the temperature increase during warmer conditions (Horton et al., 1996). Although there was

70 no significant difference between depths in NT and CT, average temperature for 0-5cm

(20.47 - 24.69°C) was comparatively higher than that for 5-10 cm depth (19.15 -

22.93°C) in both CT and NT treatments.

Temperature (0-5 cm) 40

C) ° 30

25 M0/NT M8/NT 20

Temperature( M16/NT 15

10 7-Apr 27-Apr 17-May 6-Jun 26-Jun 16-Jul 5-Aug Sampling Date

Temperature (0-5 cm) 40

35 C) ° 30 25 M0/CT 20 M8/CT

Temperature( M16/CT 15 10 7-Apr 27-Apr 17-May 6-Jun 26-Jun 16-Jul 5-Aug Sampling Date

Figure 12. (a) and (c) represent soil temperature at 0-5 and 5- 10 cm depths respectively, for different mulch treatments under NT. (b) and (d) represent the soil temperature at 0-5 and 5- 10 cm depths respectively, for different mulch treatments under CT. * M0, M8 and M16 represent the mulch rate at 0, 8 and 16 Mg ha-1 yr-1, respectively. ** Bars represent LSD at P < 0.05 between M0, M8 and M16.

Figure Continued

Temperature (5-10 cm) 35

30 C) ° 25 20 M0/NT 15 10 M8/NT

Temperature( 5 M16/NT 0 7-Apr 27-Apr 17-May 6-Jun 26-Jun 16-Jul 5-Aug Sampling Date

Temperature (5-10)

C) ° 30

20 M0/CT

10 M8/CT

Temperature( M16/CT 0 7-Apr 27-Apr 17-May 6-Jun 26-Jun 16-Jul 5-Aug Sampling Date

35 30

30 25

5 5 cm)

10cm) - 25 -

C) C) (0

C) C) (5 °

20 ° 15 15 NT NT 10 10 CT CT

5 5

Temperature Temperature ( Temperature ( Temperature 0 0 0 8 16 0 8 16 Mulch Rate (Mg ha-1 yr-1) Mulch Rate (Mg ha-1 yr-1)

Figure 13. (a) and (b) represent the average soil temperature at 0-5 and 5-10cm respectively, for different mulch and tillage treatments. *Bars represent LSD at P < 0.05 between NT and CT 72

3.4.2 Soil chemical parameters

3.4.2.1 Soil pH under different mulch and tillage treatments

Soil pH values differed significantly among tillage treatments. The average pH of NT

(5.7 - 6.1) was lower than that of CT (5.8 - 6.3). Similar results have been reported by

Limousin and Tessier, 2007; Lopez, 2009; Rahman, 2008; and Govearts, 2007. The observation that the surface soil becomes more acidic under NT than under CT could be attributed to higher SOM content and increased biological activity in NT than in CT

( Moebius-Clune et al., 2007). Generally lower soil pH under NT practice may be attributed to the formation of organic acids from mineralization of crop residues in the surface layer of NT (Ismail et al., 1994), and to surface application of chemical fertilizers.

As with tillage, mulch treatments also significantly affected soil pH. The average pH of mulched plots was lower than those of unmulched plots. Furthermore, M0 and M16 treatments had significant differences in pH while M0 and M8, M8 and M 16 treatments did not have significant differences in pH for NT. In contrast, M0 and M8, M0 and M16 treatments had significantly different pH. However, M8 and M16 had similar pH in CT.

These results are in accord with the observations made by Huang et al. (2008).

3.4.2.2 Soil EC under different mulch and tillage treatments

Tillage treatments did not have a significant effect on EC. However, there was a trend for average EC values to be somewhat lower in NT than in CT for all mulch rates. This trend of NT having lower EC values than CT has been reported by many others (Brye et al.,

2006; Patiño-Zúñiga, 2009; Chatterji, 2009). Soil EC or the amount of salt present in NT

73 practice is reduced relative to CT: (i) enhanced soil structure and water infiltration (Dalal,

1989) ,(ii) increased moisture content due to decreased evaporation because of the mulch cover, and (iii) leaching of salts out of top soil layer which decreases the EC (Patiño-

Zúñiga, 2009). Although mulch treatments also did not have any significant effect on EC, there was a general trend of a somewhat higher EC in unmulched compared to mulched plots. The results of the present study are in accord with those reported by others

(Govearts, 2007; Fuentes, 2009). These trends may be attributed to a level of soil compaction (higher soil ), that hinders the water movement throughout the profile that causes a deficit of moisture, which, in turn, results in the increase of salts in the soil

(Fuentes, 2009).

Table 4. Mean pH and EC as affected by different mulch rates. Mulch Rate EC Tillage pH (Mg ha-1 yr-1) (ds m-1 )

NT†ﬃ 0 6.02A ab 0.29A ab 8 5.74A a 0.28A b 16 6.15A b 0.31A a CT† 0 6.39B a 0.32A a 8 6.05B b 0.38A a 16 5.88A b 0.33A a P value Tillage (T) 0.04 0.06 Mulch (M) 0.01 0.64 T × M 0.004 0.29 †Means in the same column followed by the same upper case letter are not significantly different between tillage treatments P < 0.05 ﬃMeans in the same column followed by the same lower case letter are not significantly different between mulch rates at P < 0.05 Anova table F ratio Parameter pH EC Tillage (T) 3.77* 5.13 (n.s) Mulch (M) 5.98* 0.46 (n.s) T × M 7.77** 1.35 (n.s) * P<0.05 ** P< 0.01 n.s - not significant at P<0.05

3.4.2.3 Soil macro and micro-aggregate C and N concentration under different mulch and tillage treatments

Although tillage did not significantly affect the concentrations of aggregate -associated C and N, the macro and micro- aggregate associated C and N concentrations were higher in

NT than CT treatment. Mean macro aggregate associated C and N concentrations were

13.37 g kg-1 and 1.29 g kg-1 in NT in comparison with those of 11.83 g kg-1 and 1.207 g kg-1, respectively, in CT. Average concentrations of micro aggregate -associated C and N were 10.03 g kg-1 and 1.02 g kg-1 in NT compared with 8.91 g kg-1 and 1.03 g kg-1 , respectively in CT. These results are in accord with those reported by others (Green,

2005; Bossyutt, 2002; Six et al., 2000; Six et al, 2002, Zortelli, 2007). Use of NT practices improves aggregation over a long period of time, whereas that of CT disrupts the aggregation process every season (Green, 2005). In general, CT disrupts soil structure by mechanical disturbance and by continually exposing SOC encapsulated within aggregates to wet-dry and freeze-thaw cycles in the surface layer (Rovira and Greacen,

1957; Beare et al., 1994) thereby increasing the disruption of aggregates. In contrast, NT generally improves aggregation and aggregate stability as it reduces soil disturbance and soil mixing (Six, 2000). Yet another reason for increased aggregation under NT maybe due to the increase in fauna and microbial biomass, particularly the increase in fungal growth (Frey et al., 1999) which in turn results in the formation of more binding agents

(e.g., extra-cellular polysaccharides) and the development of hyphal networks enmeshing the aggregates and enhancing aggregate stability (Six et al., 2002).

Statistical significance of mulch and tillage treatments on macro and micro aggregate associated C and N concentrations were uncertain as concentrations varied widely between treatments. However, there was a significant effect on macro aggregate associated C was observed between the mulch treatments in NT. In contrast, there was no significant effect in CT, but macro aggregate associated C was higher in mulched than unmulched plots in both tillage treatments. Micro aggregate associated C differed significantly among mulching treatments in CT, but no significant differences were observed in NT. Conversely, mulch treatment did not have any significant effect on micro or macro associated N in NT or CT. These results are in accord with those reported by Mikah (2004), Wright (2005), and Olchin (2006). Increased C and N concentrations may be attributed to the increase in SOM due to the surface application of crop residues

(Mikah, 2004). Additionally, crop residues may also improve aggregate stability by reducing the exposure of SOM to direct wet -dry and freeze- thaw cycles being a barrier between the soil surface and the atmosphere.

Table 5. Macro-aggregate associated C and N concentrations and C:N ratios of tillage treatments at different mulch rate. Tillage Mulch Rate C N C: N method (Mg ha-1 yr-1) (g kg-1) (g kg-1) Ratio NT†ﬃ 0 11.83A a 1.25A a 9.72A a 8 12.87A ab 1.25A a 9.31A a 16 15.44A b 1.39A a 10.07A a CT 0 10.14A a 1.21A a 8.21A a 8 12.47A a 1.12A a 11.42A a 16 12.89B a 1.30A a 11.03A a P value Tillage (T) 0.07 0.26 0.50 Mulch (M) 0.02 0.26 0.21 T × M 0.54 0.88 0.17 †Means in the same column followed by the same upper case letter are not significantly different between tillage treatments at P < 0.05 ﬃMeans in the same column followed by the same lower case letter are not significantly different between mulch rates at P < 0.05

Anova table F ratio Parameter C N C:N Tillage (T) 3.90 (n.s) 1.41 (n.s) 0.48 (n.s) Mulch (M) 5.53* 1.49(n.s) 1.78 (n.s) T × M 0.64n (n.s) 0.12 (n.s) 2.03 (n.s) * P<0.05 ** P< 0.01 n.s - not significant at P<0.05

Table 6. Micro aggregate associated C and N concentrations and C:N ratios of tillage treatments at different mulch rate. Tillage Mulch Rate C N C: N method (Mg ha-1 yr-1) (g kg-1) (g kg-1) NT† 0 8.18A a 1.06A a 7.73A a 8 9.77A a 0.92A a 11.28A a 16 12.16A a 1.09A a 11.11A a CT 0 7.33A a 1.08A a 6.78A a 8 9.21A ab 1.06A a 8.80A ab 16 10.21A b 0.96A a 10.70B b P value Tillage (T) 0.23 0.86 0.27 Mulch (M) 0.03 0.58 0.05 T × M 0.80 0.26 0.73 †Means in the same column followed by the same upper case letter are not significantly different between tillage treatments at P < 0.05 ﬃMeans in the same column followed by the same lower case letter are not significantly different between mulch rates at P < 0.05

Anova table F ratio Parameter C N C:N Tillage (T) 1.60 (n.s) 0.03 (n.s) 1.35 (n.s) Mulch (M) 4.96* 0.56 (n.s) 3.99* T × M 0.23 (n.s) 1.53 (n.s) 0.32 (n.s) * P<0.05 ** P< 0.01 n.s - not significant at P<0.05

Furthermore, macro -aggregates are generally less stable than micro- aggregates (Olchin,

2007; Bosyutt, 2002). The binding agents in macro-aggregates are less stable than those in micro-aggregates (eg. stronger organic bonds) (Beare et al., 1994). Temporary (e.g.,

77 roots and fungal hyphae) and transient (e.g., polysaccharides) agents bind macro- aggregates and are relatively more labile or decomposable (Elliot, 1986), and consequently more susceptible to the tillage – induced disruptive forces (Tisdall and

Oades, 1982).

Soil C:N ratio was not significantly impacted by tillage treatments. However, the average macro - aggregate associated C:N ratios were lower in NT than CT. Similar results were reported by Zebelisk (2007). Soil C:N ratio is a good predictor of aggregate stability

(Bird et al., 2002). The low C:N ratios in NT treatments may indicate that SOM has undergone humification (Lopez, 2009). Conversely, the average micro aggregate associated C:N ratio was greater in NT than CT, and there existed no specific trend with relation to mulch rate for either NT or CT. Mulch treatment had a significant effect on soil micro-aggregate C:N ratio in CT. The C:N ratio differed significantly among mulch rates of M0 and M16 treatments. The micro and macroaggregate C:N ratios were higher in mulched compared to unmulched plots in both NT and CT treatments. The higher C:N ratio could be attributed to the less humification of SOM and to more enrichment of C (Lopez, 2009) in mulched compared to unmulched plots.

3.5 Conclusion

Results of this study provided insights into the effects of long-term application of mulch on soil quality, relative to the effects of tillage, in a temperate region. The long term study demonstrated that mulching with wheat straw contributed to a general improvement

78 of soil physical and chemical characteristics. The results of this study were in accord with the above stated hypothesis.

 Increasing rate of mulch application contributed to a decrease in in NT and

-3 CT. Mean was lower in mulched (1.25 - 1.44 Mg m ) than unmulched (1.45 –

1.49 Mg m-3) soil. Additionally, the soil bulk density was lower in NT than CT.

-3 The mean soil was approximately 1.25 – 1.45Mg m in NT and 1.39 - 1.49 Mg

m-3 in CT.

 Mulching significantly buffered soil temperature from increasing during warmer

conditions. The maximum soil temperatures in the surface layer were 4–6°C

lower in the mulched than in the unmulched plots.

 Mulch rates significantly increased the moisture content both in NT and CT

treatments. The maximum moisture content was recorded for M16 (0.31 - 0.36%

v/v), followed by M8 (0.26 - 0.30 % v/v), and the minimum in M0 (0.21 - 0.23%

v/v).

 Macro and micro-aggregate associated C was slightly higher in mulched than

unmulched plots in both tillage treatments. The mean macro aggregated C was

approximately 12.47 - 15.44 g kg-1 in mulched and 10.14 - 11.83 g kg-1 in

unmulched soil. Furthermore, the mean micro-aggregate associated C was 9.21-

12.51 g kg-1 in mulched and 7.32 - 8.17 g kg-1 in unmulched soil.

 Soil pH values differed significantly among tillage treatments. The average pH of

NT (5.7 - 6.1) was lower than that of CT (5.8 - 6.3). Mulch treatments also

significantly affected soil pH. The average pH of mulched plots was lower than

those of unmulched plots.

 Tillage and mulch treatments did not have any significant effect on EC. However,

the average EC values were lower in NT than in CT for all mulch rates and there

was a general trend of a higher EC in unmulched compared to mulched plots.

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Chapter 4: General Conclusion

Owing to the burgeoning global demand for food, fiber, and fuel, the atmospheric GHG emissions rates have been escalating. Cropland soils can be both sources and sinks for

GHG, however their sink or source strength depend critically on soil management.

Hence, the appropriate strategies to manage GHG emissions must involve conservation agriculture and crop management practices that enhance soil C storage and maintain soil quality while continuing to achieve gains in yield. Understanding the environmental benefits of conservation practices and implementation of these practices on the land will hasten sustainable development and improvement of environmental quality in this sector while increasing production of food and fiber and offsetting industrial greenhouse emissions.

The current study has demonstrated the use of conservation practice such as NT and crop residue retention to minimize C loses and enhance the overall all soil quality. The data presented in this thesis suggest that mulching directly influences soil properties of the soil. Subsequent application of mulch to agricultural soils (i) increase the soil moisture content as it reduces the evaporation rate from the soil surface forming a barrier between the soil and the atmosphere, (ii) moderates or stabilizes the magnitude of the temperature from increasing during summer owing to its low thermal conductivity and high albedo,

(iii) reduces the bulk density of the soil due to enhanced porosity by soil fauna 88

(iv) enhance soil aggregation which alleviates compaction and increases porosity by bioturbation, (v) lowers the salinity of the soil especially in NT practice due to enhanced soil structure, water infiltration and leaching out of salts from the top layer.

(vi) lowers soil pH under NT due to the formation of organic acids from mineralization of crop residues in the surface layer of NT.

Furthermore, mulching in conjunction to NT moderates the principal GHG fluxes from soil than CT. The average diurnal CO2 fluxes were lower under NT compared to CT treatment, which may be due to increased surface roughness and soil aeration created by soil disturbance caused by plowing that accelerate decomposition of SOM, especially prior to the formation of surface seals. The effects of plowing on N2O flux, although not significant, indicated a trend of higher N2O fluxes under NT than CT, which may be attributed to the increased substrate accumulation in NT treatments. Similarly there was no definite trend among tillage treatments with regards to CH4 flux However, NT treatments were mostly a sink for CH4 while CT treatments were mostly sources.

Additionally, CO2 and N2O fluxes were significantly affected by mulch treatments, but mulching did not significantly affect CH4 flux. Reduced GHG flux was observed during winter and it may be attributed to: (i) accumulation of snow over the uppermost soil layer limiting the gas transport from the soil to the atmosphere (ii) due to shutting down of microbial activity owing to low temperatures. The present study showed no consistent correlation between soil moisture content and N2O and CH4 fluxes. However, the diurnal

CO2 flux was negatively correlated (r = -0.34207 at P<0.0001) with soil moisture content.

Additionally, both N2O and CO2 were not significantly correlated with soil temperatures 89

.On the contrary, CH4 flux was negatively correlated (r =-0.35160 at P=0.01) with soil temperature, as is also indicated by increased emissions during winter and reduced emissions during summer.

Researchable priorities

Additional research is needed to better understand the over-all impact and interactions between management regimes and GHG emissions, especially in relation to soil properties and climate factors. Studying the stable isotopic concentrations of CO2 and

- CH4 can be useful to identify the CO2 and CH4 sources; assessing the NO3 levels within soil solution can be a useful indicator of N2O emissions. Measurements show that there are major uncertainties especially with regard to N2O flux from the soil. This can be overcome by additional intensive measurement accompanied with the development of process oriented models, capable of simulating N2O flux under varying climatic conditions.

Furthermore, chemical and biological studies on mulch and soil will provide insight on the interaction and mechanism of microbial growth and activity. Further studies on the macro and micro aggregate associated C can be helpful to understand whether C in these aggregates is recalcitrant or labile. Additionally, in order to better understand the full account of C accumulation rates and the potential of these management regimes, it will be necessary to include not only GHG emissions and soil properties but also C sequestration rate of each of the treatment plots.

Complete References

Agbede, T.M., Ojeniyi, S.O., 2009. Tillage and poultry manure effects on soil fertility and sorghum yield in southwestern Nigeria. Soil Till. Res. 104: 74–81.

Aggarwal, P., Sharma, N.K., 2002. Water uptake and yield of rainfed wheat in relation to tillage and mulch. Indian J. Soil Conserv. 30 (2), 155–160.

Al-Kaisi, M.M.,Yin, X. H., 2005. Tillage and crop residue eff ects on soil carbon and carbon dioxide emission in corn-soybean rotations. J. Environ. Qual.34, 437–445.