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This is to certify that the
thesis entitled

Dairy Forage Cropping Best Management Practices: A Comparison
of Yield, Forage Quality, Soil Carbon Sequestration, and

Greenhouse Gas Emissions

presented by
James Donald DeYoung

has been accepted towards fulﬁllment
of the requirements for the

Master of degree in Department of Crop and Soil
Science Science

&W%@

Major Professor’s Signature

7 //s’/a%

Date

 

MSU is an Afﬁrmative Action/Equal Opportunity Institution

 

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PLACE IN RETURN BOX to remove this checkout from your record.

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2/05 p:/ClRC/DaleDue.indd-p.1

DAIRY FORAGE CROPPING BEST MANAGEMENT PRACTICES: A
COMPARISON OF YIELD, FORAGE QUALITY, SOIL CARBON
SEQUESTRATION, AND GREENHOUSE GAS EMISSIONS.

By

James Donald De Young

A THESIS

Submitted to
Michigan State University
In partial fulﬁllment of the requirements
For the degree of

MASTER OF SCIENCE
Department of Crop and Soil Science

2006

ABSTRACT
DAIRY FORAGE CROPPING BEST MANAGEMENT PRACTICES: A
COMPARISON OF YIELD, FORAGE QUALITY, SOIL CARBON
SEQUESTRATION, AND GREENHOUSE GAS EMISSIONS.
By

James Donald De Young

Increases in greenhouse gas (GHG) emissions have been found to contribute toward
global warming. Better management practices in agriculture have been proposed as a
partial solution to this problem. This study evaluated forage cropping systems and
additions of manure or compost for their ability to sequester carbon (C) and reduce GHG
emissions from the soil. Cropping systems and C additions were compared at a southern
Michigan (K88) and northern Michigan (UP) location. Compost was applied at [(88 and
manure slurry was applied at UP at rates to supply 3000 kg C ha". Results indicated
forage quality differences (P<0.0001) between forage species within each location.

There were also Signiﬁcant (P<0.0001) yield differences between crops. The addition of
compost at the K88 location had a signiﬁcant (P<0.0459) impact on yield. The addition
of manure at the UP location resulted in signiﬁcant interactions on yield between crop x
year (P<0.0001) and crop x manure (P<0.0442). GHG ﬂuxes at the K88 location were
not signiﬁcantly different due to crop or compost additions, however N20 ﬂuxes were
signiﬁcantly greater (P<0.040) with manure additions at the UP location. Total soil C
measured at KBS was greater with compost additions than without (0.943 kg C cm'2 and
0.798 kg C cm"2 respectively). POM differences at KBS were also signiﬁcant (P<0.0037)
(0.211 kg POM C om'2 with compost additions and 0.202 kg POM C om‘2 without
compost). The UP location TSC and POM did not respond in a measurable way to

manure additions or cropping treatments.

Dedicated to Lisa Ann, and Asher James

iii

ACKNOWLEDGMENTS
I wish to thank the many people who have helped me along the way through this

project. To my committee, Drs. Richard H. Leep, Doo-Hong Min, Kurt D. Thelen, and
Tim M. Harrigan; thank you for this great opportunity to study, learn, grow, and travel. I
have appreciated your candor, wisdom, and guidance through this process. To my fellow
lab mates, Tim Dietz, Tim Boring, Debbie Warnock, Nasser Al-Gumaiz, and Dan
Hudson; thank you for the endless help with sample collection, ideas, data processing,
and statistical analysis. To the KBS post does and grads who helped me out with this
project, Claire McSwiney, Sven Bohm, Drew Corbin, Terry Locke, Stuart Grandy; thank
you for all the ideas, problem solving, borrowed equipment, brains picked, and expertise.
To the staff at KBS including Nina, Sally, Alice, Jim, Greg, and various others who
helped with ofﬁce and ﬁeld work through my stay at KBS; thank you for all that you do
with very little thanks, you deﬁnitely made KBS home for me. To Todd Martin, Dave
DeYoung, Brian Demming, Chris Kapp, Simon, thank you for all the soil cores, sieves,
hand separations, numbers entered and overall good attitude. To my family; thanks
Mom, Dad, Tim, Pam, and David for your encouragement, love, and understanding
through all of this. And ﬁnally, to my beautiful wife Lisa and amazing son Asher; thank
you for understanding the late nights, long trips to Chatham, frustrations, joys, and
everything in between. I love you and am truly blessed by your companionship. This

thesis is dedicated to you, since it took up so much of our time together.

iv

TABLE OF CONTENTS

LIST OF TABLES
INTRODUCTION
TILLAGE

vi

 

CROPS

 

MAN URE AND SOIL ORGANIC MATTER

 

MEASURING SOIL ORGANIC MATTER

 

GREENHOUSE GASSES AND AGRICULTURE

 

OBJECTIVES
HYPOTHESIS
MA TERIALS AND METHODS
SITE DESCRIPTION AND EXPERIMENTAL DESIGN

 

SOIL ANALYSIS

 

FORAGE YIELD AND NUTRATIV E EVALUATION

 

GAS ANALYSIS

 

STATISTICAL ANALYSIS
RES UL TS AND DISCUSSION
UP FORAGE YIELDS

 

KBS F ORAGE YIELD

 

FORAGE NUTRITIVE ANALYSIS

 

GREENHOUSE GAS F LUXES
GREENHOUSE GAS FLUXES AS CO; EQUIVALENTS
TOTAL SOIL C AND POM

 

 

CONCLUSIONS
TABLES
APPENDICES

ll
12

I 7
17
I 8
18
20
22
23
24
24
24
26
28
30
34
35
4 I
44
62

LIST OF TABLES

Table l Cropping and organic matter input treatments at UP ......................................... 44
Table 2. Cropping and organic matter input treatments at KBS ...................................... 45
Table 3. Dry matter forage yield at the UP location ANOVA ......................................... 46
Table 4. UP forage dry matter yield treatment means. .................................................... 46
Table 5. KBS forage yields ANOVA. ............................................................................. 47
Table 6. KBS forage yield treatment means by year and cropping treatment. ................ 47
Table 7. KBS forage yield treatment means by compost treatment. ............................... 47
Table 8. Forage quality at the UP location ANOVA ....................................................... 48
Table 9. Forage quality treatment means at the UP location. .......................................... 48
Table 10. Forage quality at the KBS location ANOVA .................................................. 49
Table 11. Forage quality treatment means at KBS location. ........................................... 49
Table 12. UP greenhouse gas ﬂux ANOVA .................................................................... 50
Table 13. UP greenhouse gas flux treatment means. ....................................................... 50
Table 14. UP greenhouse gas ﬂuxes by organic matter treatment. .................................. 50
Table 15. KBS greenhouse gas ﬂux ANOVA. ................................................................ 5]
Table 16. KBS greenhouse gas ﬂux treatment means. .................................................... 51
Table 17. KBS greenhouse gas ﬂuxes by organic matter treatment. ............................... 51
Table 18. Total Soil Carbon (TSC) ANOVA. ................................................................. 52
Table 19. TSC cropping treatment means 2004 ............................................................... 52
Table 20. TSC organic matter treatment means 2004 ...................................................... 52
Table 21. TSC differences 2004-2002 ............................................................................. 53
Table 22. TSC difference 2004-2002 cropping treatment means .................................... 53
Table 23. TSC difference 2004-2002 organic matter treatment means ........................... 53
Table 24. POM Soil Carbon (POM C) ANOVA ............................................................. 54
Table 25. POM C cropping treatment means 2004 .......................................................... 54
Table 26. POM C organic matter treatment means 2004 ................................................. 54
Table 27. Agronomic ﬁeld activities for KBS 2004. ....................................................... 62
Table 28. Agronomic ﬁeld activities for KBS 2003. ....................................................... 63
Table 29. Agronomic ﬁeld activities for KBS 2002. ....................................................... 63
Table 30. Agronomic ﬁeld activities for UP, 2004 .......................................................... 64
Table 31. Agronomic ﬁeld activities for UP, 2003 .......................................................... 64
Table 32. Agronomic ﬁeld activities for UP, 2002 .......................................................... 65
Table 33. Organic matter treatment characteristics. ........................................................ 65
Table 34. Soil bulk density at start and end of study ....................................................... 65
Table 35. Soil total N at start and end of study ................................................................ 65

vi

INTRODUCTION

Best management practices (BMPs) have been used to describe best-case
scenarios for management decisions based on desired outcomes which reduce negative
environmental impacts. BMPs have been used for reducing runoff during construction,
reducing soil erosion and improving pest control for cropping systems. BMPs in
cropping systems dictate the best times of year to harvest, fertility regimes, tillage
practices and can include improved rotations of perennial forages, cover crops, reduced
tillage, and manure additions which increase soil organic matter. Soil residues have been
shown to minimize water and wind erosion, increase soil fertility, and improve ground
and surface water quality (Halvorson et al., 2002a). The goal of most cropping BMPs is
to reduce erosion and improve crop yields. BMPs have not been evaluated for dairy
forage production. This study evaluated how forage cropping systems using best
management practices, of reduced tillage, manure or compost addition, and crop rotations
affect crop yields, forage quality, soil greenhouse gas production, and soil carbon (C)
sequestration.

Increases in three major GHGs, including carbon dioxide (C02), methane (CH4)
and nitrous oxide (N 20) have been proposed as the main cause of the radiative forcing of
the atmosphere leading to global climate change (Prather et al., 1995; Shine and Forster,
I999). Increases in atmospheric CO; since the 1700’s have been documented through
Antarctic ice core data (Siegenthaler and Sarrniento, 1993). Atmospheric data collected
since the 1950’s in Hawaii also support this trend (Etheridge et al., 1996; Keeling and
Whorf, 2000; Siegenthaler and Sarrniento, 1993). These documented increases in global

COz levels are largely attributed to increased burning of fossil fuels and the conversion of

land toward more intensive agricultural uses (IPCC, 1990; IPCC, 1992; Marland and
Boden, 1991). Increases in CH4 and N20 gases also follow the growth of human
population and activity(Liebig et al., 2005). CO2 levels increased from 280 ppb to 360
ppb, CH4 levels rose from 750 ppb to levels close to I600 ppb in 2000 and N20 increased
from around 270 ppb to almost 300 ppb (IPCC, 2001). There has been a marked
increase in each of the above greenhouse gasses, which can be tied directly to human
activity. CO2 release from soil results from the oxidation of soil organic matter due to
increased tillage and fossil fuel use. N20 results from increased fertilizer usage but is
also from fossil fuel consumption. CH4 comes from garbage landﬁlls, stored animal
wastes, rice production, and domesticated animals (mainly sheep and cattle)(Cole et al.,
1997; Hutsch, 1998; Seneviratne and van Holm, 1998).

Plants use energy from the sun in combination with water and C02 to produce
both structural and energy storing carbohydrates through the process of photosynthesis.
By removing CO2 from the atmosphere and converting it to organic matter, plants can
play an important role in C sequestration. Cropping rotations can inﬂuence the
production of greenhouse gases through their nitrogen (N) requirements. For example,
corn is fertilized with N while a legume grown for forage ﬁxes its own N. Soil
conditions can also be affected by cropping practices including, but not limited to tillage
and harvest practices (Prior et al., 2000). Irrigation of crops has been shown to
temporarily increased soil CH4 production (Liebi g et al., 2005). Best management
practices (BMPs) have been developed for different crops which dictate planting,
fertilizing, and harvest practices. These BMPs can have an impact on the role that

agriculture plays in GHG emissions and potentially, global warming.

Tillage is involved in increasing atmospheric CO2 (Dyer and Desjardins, 2003;
Halvorson et al., 2002b; Lal, 1997; West and Post, 2002). Tillage has long been used to
prepare the soil for planting. Tillage prepares the seedbed for the crop to be planted by
providing good seed to soil contact, weed control, and by helping to aerate the soil.
However, with the advent of mechanized farm equipment, it is possible to till much more
soil in a shorter amount of time than ever before In the process of tilling the soil for
planting, nutrients are mineralized through the microbial breakdown of organic matter in
the soil (Wander and Bidart, 2000). Microbes consume the organic matter in the soil and
use it for energy. Through the different levels of animals, bacteria, and fungi in the soil,
organic matter is broken into smaller and smaller pieces, with each trophic level releasing
some waste products (Paustian et al., 2000). This helps recycle nutrients into forms that
can be taken up and used by plants, but it also releases some of the CO2 that has been
immobilized in the form of structural carbohydrates in plant organic matter. If the
conditions for the breakdown cause the material to accumulate faster than animals,
bacteria, and fungi living in the soil can break it down, organic matter levels will
increase. This scenario has occurred in the past and is the source of our reserves of fossil
fuels and deep organic soils of the prairies. This stored (or sequestered) C remains in
place until conditions arise when it can be released back to the atmosphere. This happens
when fossil fuels are burned for energy. It also happens when the organic matter in soil is
exposed to air, moisture, and other conditions that favor microbial degradation. Many of
these conditions are present after the soil is tilled in preparation for planting crops.

In the United States, it is estimated that 30-70% of the original C in soils (in the

form of organic matter) has been lost to the atmosphere due to tillage (Haas et al., 195 7).

Jackson et al. (2003) found that the breakdown of soil organic matter from tillage events
resulted in high rates of soil N mineralization for several days following tillage as well as
a large ﬂux of CO2 from the soil.

Tillage is primarily used to prepare the seedbed for crop seeds to be planted into,
thus ensuring good seed to soil contact and subsequent germination. Nutrients are
released from tillage through the breakdown of soil organic matter. These nutrients play
a critical role in the early development of seedlings. These nutrients include, but are not
limited to organic forms of N, phosphorus, and potassium. However, this practice of
tillage results in a breakdown of soil organic matter with a subsequent loss of soil C. The
recovery of this lost organic matter from tillage can take many years (Burke et al., 1995)
because the C contents of many agricultural soils are linearly related to C inputs from
organic matter (Paul et al., 1999; Paustian et al., 1995; Rasmussen and Collins, 1991).
Tillage reduces the total C input to the soil by increasing the level of oxygen in the soil
and encouraging the microbial degradation of those inputs. Labile C is a form of C that is
generally very quick to be degraded by soil microbes. Often, labile C and organic matter
that was not readily available to microbes due to its placement in the soil (i.e. within soil
aggregates and other anaerobic portions of the soil) is made available by disrupting soil
aggregates and/or moving organic matter around in the soil proﬁle to more aerobic
portions of the soil (Min et al., 2003; Six et al., 2000; Wander and Yang, 2000; Wander
and Bidart, 2000).

Tillage also affects the recovery of soil organic matter by reducing the mean
residence time (MRT) of soil organic matter twice as much as no-till (NT) (Balesdent et

al., 1990; Six et al., 1998). Speciﬁcally at the Kellogg Biological Station, Hickory

Corners, Michigan (where a portion of this study took place), the MRT for soil C was 30-
66 days for the active pool and 9-13 years for the slow pool (Paul et al., 1999). This
means that by tilling a previously untilled ground, it is possible to reduce the MRT for
soil C to as little as 15-33 days.

Robertson et al. (2000) stated that conventional cropping systems have the highest
overall global warming potential (GWP), but by adopting no-till and including perennial
forage crops, they suggested it was possible to offset that potential. Globally, this
potential for C sequestration by agriculture has been estimated to be on the order of 75-
200 million MT C y'l (Bruce et al., 1999; Eve et al., 20023; Lal R. et al., 1998). With 166
million hectares of cropland in the contiguous United States (USDA_NRCS, 2000), and
global cropland containing close to twice as much C as is present in the atmosphere
(Prentice, 2001), it is easy to understand why agriculture has been touted as an important
means to mitigate the effects of GHG through C sequestration (Lal, 2003b; Paustian et
al., 1996; Sperow et al., 2003).

In many agricultural cropping systems, A few changes can bring about signiﬁcant
results. In the case of agriculture and soil C, turning losses into gains can be as simple as
reducing tillage (Lal and Kimble, 1997; Post and Mann, 1990) and including manure or
perennial crops in the cropping rotation (Lal et al., 1978). Robertson et al. (2000) found
that this reduction in GWP from conversion to reduced tillage came from reduced fuel
uses, lower soil greenhouse gas ﬂuxes, and improved cropping efﬁciency. Paustch et al.
(1999) argues that if all crop producers in the United States switched to conservation

tillage, an additional 14 million metric tons of C could be sequestered in the soil. In the

Great Lakes region, conversion from conventional tillage to no-till has been suggested to
have the potential to accumulate 0.36 MT C ha'I y" (Eve et al., 2002b).

Other cropping practices which encourage C sequestration include increasing
yields, using perennial crops, and using legumes to ﬁx elemental N and reduce fossil fuel
consumption associated with N-fertilizer production as well as N applications (F ortuna et
al., 2003; Jastrow et al., 2005; Lal, 2002; Lal, 2003a). The potential to offset the GWP of
certain crops by making small changes to management practices is substantial and can be
done in a cost effective manner. Antle et al. (2001) estimated that in Montana,
conversion from crop-fallow to continuous cropping of wheat could sequester 12 million
tons of C. In the Midwest, Eve et al. (2002b) estimated that by adding hay, a winter
cover crop, or manure applications to an annual cropping rotation, an additional 0.75 C
ha'l y'I could be accumulated. Additionally, agriculture has the mitigation potential to
reduce fossil C consumption through the production of biofuels which are renewable
resources and provide an alternative to the ﬁnite resources of fossil fuels (Paustian et al.,
1998).

TILLAGE

The adoption of no-till has had a positive effect on soil C sequestration (Campbell
et al., 2001; Liebig et al., 2005; West and Post, 2002). No-till encourages soil
aggregation and the development of improved soil structure. No-tillage (NT) is a practice
which involves tilling only a small strip of soil, usually just wide and deep enough for the
seed to be placed into the soil ensuring good seed to soil contact. Weeds are controlled
with synthetic herbicides and crop rotations instead of intensive conventional tillage.

This practice reduces the disruption of soil structures such as aggregates, root channels,

and earthworm tunnels which all help to increase soil aeration, reduce soil compaction,
and increase water inﬁltration. The practice of no-till leaves more crop residues on the
soil surface where they are not broken down as quickly which leads to reduced C losses
from crop residue, especially root material placed underground. Traditional soil tillage
methods require massive amounts of energy to turn acres of soil over; however NT
requires much less fuel to prepare ﬁelds for planting since ﬁelds do not need to be tilled
before each crop. This results in lower fossil fuel derived CO2 emissions produced by the
NT planting operation.

Rochette et al. (1999) found that using no-till resulted in less corn residue C lost
compared to moldboard plowing. Increased crop residues result in less wind and water
erosion losses of soil (Hussain et al., 1998; Hussain et al., 1999; Ortega et al., 2002). It is
estimated that no-till in the Great Lakes region has the potential to sequester up to 0.36
MT C ha '1 yr'l (Eve et al., 2002b). However, it has been suggested that by just stopping
tillage by taking by taking land out of crop production as in CRP (Conservation Reserve
Program) conversion will yield little in the way of C sequestration (Robles and Burke,
1998)

Concerns about no-till contributing to soil compaction have led to some of the
questions regarding the effects of compaction in the lower soil horizons and reduction in
yields (Bakhsh et al., 2000; Hussain et al., 1998; Logsdon and Cambardella, 2000). On
the other hand, one study showed increased yields and improved soil surface properties in
no-till cotton ﬁelds which also had been deep tilled to break up the plow pan
(Franzluebbers et al., 1999a). Water can have the same effect as compaction on soil

aeration by ﬁlling soil pores leading to anaerobic soil conditions. Tillage also affects the

availability of soil water through short term increased evaporation and by disrupting soil
structure such as worm burrows and old root channels which may help with water
diffusion deeper into the soil proﬁle. Tillage disrupts those structures and replaces them
with a less stable soil structure which is more susceptible to degradation and more
anaerobic conditions.

The increased soil C in no-till cropping systems has been shown to be mainly the
result of accumulations of root material that are not degraded by microbial activity
(Bolinder et al., 1999; Cambardella and Elliott, 1993). This root material has been shown
to play a key role in the development of C-rich soil macroaggregates and
microaggregates, both of which are important factors in building good soil structure.
Intensive tillage operations disrupt soil structure by breaking up macroaggregates and
increasing the number of C poor microaggregates and can lead to a reduction in soil
porosity, soil water holding capacity, and air diffusion through the soil.

CROPS

One way of reducing effects of intensive tillage is to adopt perennial cropping
systems. Forage crops such as alfalfa (Medicago sativa), various clovers (Trifolium
spp.), timothy (Phleum pratense L. ), orchardgrass (Dactylis glomerata L.) and many
others are different in that they are grown as perennial crops with most of their above
ground biomass harvested while their crowns and roots stay in the soil. Perennial crops
encourage the building of soil organic matter through a reduction of tillage (once every 3-
6 years or longer in the case of pastures, versus annual tillage events). For this reason,

forage crops have been found to have a strong GWP mitigation potential (Robertson et

al., 2000). One of these perennial forage crops used extensively in the United States is
Alfalfa (Medicago sativa L.).

Alfalfa is a perennial legume native to the Middle East, but grown extensively
throughout the world as a forage crop. It is highly productive, ﬁxes its own N, and
provides high quality fodder for many classes of livestock animals. Alfalfa is used
extensively in the United States as dry hay, silage, and grazing stocks for beef and dairy
production. Paul et al. (1999) applauded the use of alfalfa due to its high productivity
and the added beneﬁt of underground C storage in long taproots. This potential for
storing carbohydrates underground was also noted by Paul and Clark (1996) who found
that the symbiotic relationship between alfalfa and its associated Rhizobium increase the
transport of carbohydrates derived from photosynthesis to the underground portions of
the plant.

Complex cropping rotations which include perennial forage crops such as alfalfa
and orchardgrass have the added beneﬁt of increased cropping intensity which in turn
yields higher levels of surface soil organic C (Ortega et al., 2002). As noted by several
researchers, residue quality as affected by legumes plays a key role in retention of soil C.
Drinkwater et al. (1998) found legume-based systems have reduced C and N losses, while
Gregorich et al. (2001) noted that soils under legume-based rotations were “more
preservative of residue C” inputs (roots) than soils under monoculture. However, these
beneﬁts do not have to be limited to arable land. Robles and Burke (1997) found that by
including legumes in CRP land they were able to increase the labile C and N fractions in
the soils. Increases in soil N result in more Particulate Organic Matter (POM), more

organic C, and more organic N (Liebig et al., 2002).

Forage cropping systems are not all based on legumes. Many producers feed corn
grain and silage and use pastures for grazing. These crops can also play a signiﬁcant role
in soil C sequestration. Buyanovsky and Wagner (1986) estimated that com grain
residues have the potential for 9.2 ton ha'l annual input, with approximately 50% of the
input from root material. In contrast, corn silage cropping systems have the majority of
the above ground biomass removed which results in much lower amounts of crop residue
inputs for building soil organic matter levels.

Pasture systems, which are often perennial and include legumes, are also good
ways to increase C sequestration. Pastures with tall fescue and common bermudagrass
have been shown to increase C sequestration more than conservation tillage
(Franzluebbers et al., 2000). Additionally, soils in which endophyte infected tall-fescue
is grown had higher concentrations of soil organic C and N than soils with non-infected
fescue (Franzluebbers et al., 1999b). This addition of organic C and N was most likely
due to the increased underground fungal biomass.

While it is generally understood that by increasing crop yields one can expect
more soil C production through increased biomass production both above and below
ground, Puget and Drinkwater (2001) found that the origin of plant litter also plays a role
in the fate of these inputs. They found that when legumes are used as green manures, up
to 87% of the shoot material decomposed while close to 50% of root derived material
was still present in the soil at the end of the growing season. Honneycutt et al. (1993)
also found that the quality (ratio of CzN) of inputs affected C mineralization more than
the loading rate, and Gale et al. (2000a; Gale et al., 2000b) showed that root derived C

was more important in stabilizing macroaggregates than shoot derived C. A crop with

10

larger amounts of ﬁne roots stabilizes macroaggregates better than one with non-ﬁbrous
roots. This was also demonstrated by Davenport et a1. (1988) who found that soil
aggregates under bromegrass were more persistent than under corn due to the large
additions of ﬁne roots, shallow depth, and larger inputs of biomass C below ground.
MAN URE AND SOIL ORGANIC MATTER

Manure has been tied to agriculture for as long as humans have grown crops and
owned livestock and it is still used today on livestock farms as an important source of
organic nutrients such as N, phosphorus, and potassium (Eghball, 2000; Paul and
Beaucharnp, 1993; Paul and Beaucharnp, 1995; Sommerfeldt et al., 1988; Whalen and
Chang, 2001 ). Manure is beneﬁcial to cropping systems in that it supplies large amounts
of partially decomposed C which translates into increased soil organic matter, improved
soil water holding capacity, and higher soil fertility (Ginting et al., 2003; Min et al.,
2003). Manure also inﬂuences soil microbial activity by providing an easily digestible
food source for microbes. For example, Rochette et al. (2000a) describes how soil
amended with pig manure resulted in a rapid increase of microbial biomass coinciding
with peaks in concentrations of extractable C and CO2 ﬂuxes. In addition, Rochette and
Gregorich (1998) found that soils with manure applied had large amounts of soluble C
with a slower turnover rate than soluble C in unamended soil. However, it should also be
noted that as much as half of C and N applied in manure can be lost to the atmosphere as
CO2 and NH4 (Kulling et al., 2003; Rochette and Gregorich, 1998). This amount can
increase when manure is not incorporated as in the case of no—till or winter applications

of manure on frozen ground.

11

MEASURING SOIL ORGANIC MATTER

Tillage, crops, and manure inputs affect soil organic matter decomposition or
accumulation at different rates and to differing degrees. However, measuring soil
organic matter changes in soils and the subsequent effects of different treatments is
difﬁcult due to high levels of background C in the soil and lack of soil C homogeneity
(Schuman et al., 2000). In order to measure small changes in large volumes of soil C, it
is usually the case that long periods of time are needed to accurately assess changes. In
one example of this problem, Conen et al. (2003) calculated that it would take 26 and 43
years to accurately measure signiﬁcant soil organic C changes at two sites in Mongolia
based on the local soil C variability and background levels. The difﬁculty in measuring
changes in soil C arises from the minimum detectable difference (MDD), which is
deﬁned as the smallest difference that can be detected (at a = 0.05) between two means
with 95% conﬁdence. MDD is inﬂuenced by sample variation and by the number of
replications.

Because of difﬁculties of measuring changes in soil C, researchers have studied
different methods for accuracy in detecting changes in soil C. One method developed for
detecting changes in soil C is accomplished by dividing the total soil C into several pools,
which are deﬁned by their lifespan. Generally these divisions lead to three pools of soil
C, a slow pool (10-40 years MRT), a resistant pool (500-1000 years MRT), and a fast
pool (20-60 days MRT) (Fortuna et al., 2003; Paul et al., 2001). Because the time span
for turnover in the slow and resistant pools is much longer than most research projects
can allow, there has been emphasis on analyzing the fast pool C to detect changes in C in

soils.

12

One proposed component of the fast pool C is a portion called particulate organic
matter (POM). POM is a major component of soil organic matter lost very quickly
following soil cultivation. POM plays a key role in soil quality in its relationship to
structural stability, aggregate formation, water holding capacity, and soil N (Cambardella
and Elliott, 1992; Denef et al., 2001; Schwenke et al., 2002; Wander and Bollero, 1999;
Wander and Yang, 2000).

Cambardella and Elliott (1992) noted that POM is often the fraction of soil C that
changes most rapidly following tillage events. Using electron microscopy they saw that
POM was comprised mostly of ﬁne root materials. POM is involved in the formation of
structural material for aggregate formation as many soil organisms feed on the easily
digestible forms of C and their wastes help to cement the organic matter together
(Jongmans et al., 2001). This process continues until small aggregates are formed around
the small pieces of organic material resulting in the organic matter being precluded from
further degradation within the aggregate. We focused on POM in this short term study
based on the fact that it changes rapidly after tillage and with supplemental organic
matter applications such as manure or compost.

GREENHOUSE GASSES AND AGRICULTURE

Greenhouse gases such as carbon dioxide, methane, and nitrous oxide result from
agricultural practices. CO2 is the GHG produced in the greatest volume by agricultural
practices which include tillage and manure handling activities. Land use changes have
since resulted in CO2 levels increasing as much as 136+/-55 Pg C (Lal, 2003a) however,
other GHGs including CH4 and N20 are also produced from agricultural practices such as

fertilization, irrigation, and manure handling (Ginting et al., 2003; Hao et al., 2001b;

l3

Hutsch, 2001). Equal amounts of CH4 and N20 are more harmful than CO2 as they have
the potential to inﬂuence global warming through the absorption of more IR light which
would otherwise be reﬂected back into space. CH4 absorbs 30 times more thermal
energy while N20 absorbs 150 times more than CO2. It should be noted however that
CO2 is produced by agriculture at quantities which far outweigh the stronger effects of
CH4 and N20. The production of these gases has increased steadily over the past 50
years due to greater consumption of fossil fuels and increased intensive agriculture
production. However, agriculture may still provide an answer to these increases in
GHGs. For example in Canada it has been proposed that a conversion of 10.5 million
hectares of cropped land to grassland has the potential to meet GHG reduction goals
(Mummey et al., 1998).

Plants ﬁx CO2 from the atmosphere through photosynthesis and convert the CO2
into structural carbohydrates, proteins, amino acids, and sugars. These products of
photosynthesis can be harvested in crops or they become food for soil fauna when plants
die. Plant residues which are decomposed by the soil fauna result in soil evolved CO2 as
a direct product of respiration by the soil fauna as they consume these plant residues for
energy. Examples of this organic matter include crop residues and tree leaves, stems
branches, and roots. Perennial plants such as grasses and legumes store up energy and
can transfer up to 50% of the photosynthates to their roots (Paul and Clark, 1996). The
decomposition of ﬁne roots in perennial systems plays a very important role in C cycling
in these systems.

Soil respiration of organic matter by soil fauna generally requires water and O2 to

take place. Diffusion of 02 through soil pores is inﬂuenced by soil structure and

14

saturation with water. A heavily compacted soil will slow O2 diffusion, where the O2 is
quickly depleted leading to anoxic soil conditions. N20 can be produced under these
anoxic conditions. Tillage quickly increases available 02 by creating many passageways
for air to enter the soil and by mixing the soil which often provides fresh organic matter
for decomposition. This inﬂux of O2 and mixing of the soil quickly leads to increases of
soil respiration of organic matter (Reicosky et al., 1997). Applications of manure also
increase soil CO2 production by providing an easily degradable source of C for soil
fauna. Even under cold soil temperatures C02 production has been shown to continue for
up to 29-d aﬂer manure applications under simulated snow (Chantigny et al., 2002).
Nitrous Oxide (N20) is another greenhouse gas of interest arising from
agriculture. N20 generally arises from the reduction of synthetic fertilizers and from the
reduction of organic forms of N found in soil organic matter under O2-limited conditions.
Denitriﬁcation is the term given to the transformation of different forms of organic N into
forms that can leave the biological system through leaching, volitization and/or diffusion.
Denitriﬁcation of soil N as N20 contributes little to global warming by itself. However it
plays a key role in the production and destruction of ozone. In the lower atmosphere
increased ozone can lead to smog, while in the upper atmosphere, through the process of
photolysis, N20 is transformed into NO which in turn reacts with both 03 and CH4.
Fertilizer bands, crop root residues, and small scale topographic features affect
soil N dynamics since they contribute to determining local N and 02 supplies. N
availability in the soil directly affect the various forms of gaseous nitrogen oxide (N 0,.)
exchange, while 02 availability affects the total amount of N gasses produced by the soil.

One example of denitriﬁcation is shown by Rochette et al. (2000b) who saw a large ﬂux

15

of N20 for 30d after applying pig manure to soil. They postulated the ﬂux of N20 was
probably related to the N03 in the manure which became available for denitriﬁcation.
These results agree with Paul et al. (1993) who saw that additions of cattle manure raise
denitriﬁcation rates and soil N20 production in the laboratory. Fan et al. (1997) found
that denitriﬁcation rates due to gaseous N20 emissions were linear with N-fertilizer
application rates. However, Hao et al. (2001a) found that by incorporating straw (a high
C source), it was possible to reduce soil N20 emissions after applying manure. Six and
Feller et al. (2002b) saw that no-till had higher CH4 uptake and greater N20 production
but still lea to reduced global warming potential due to reduced fuel use. Marland et al.
(2003) argue that conversion to no-till can have positive effects on building soil C over
approximately 40 years, however, reduction of the global warming potential by that
agricultural practice will mostly depend on N fertilizer use.

Methane (CH4) is the other GHG of importance to agriculture. Methane is usually
produced through the anaerobic respiration of organic matter by methanogenic bacteria
(archeobacteria) under conditions like those found in rice paddies, or even after cropland
irrigation through the creation of small, temporary anaerobic microsites and thus
contribute to methane production.

Methane is unique among these three agiculturally derived GHG’s, in that the
oxidation of methane by another group of bacteria called methanotrophs has the potential
to offset a portion of the global warming potential of the other GHG’s produced by
agriculture. In early successional settings, that potential has been estimated to be as
much as 211 g of carbon dioxide equivalents m"2 yr’l (Robertson et al., 2000). This

potential is reduced through N fertilization oxidation in arable soils (Mosier et al., 1991).

16

Methane oxidation requires NO3' and N02' but is inhibited by NH4+ and very dry
conditions (Hutsch, 1998). The reason for inhibition of methane oxidation by NH4+ is not
very well understood, but is thought to arise from competition for the non-selective
enzyme mono-oxygenase which is used by the methanotrophs to oxidize CH4. Methane
oxidation rates are greater in direct drilled (no-till) treatments than oxidation rates under
other forms of tillage (Six et al., 2002b). Wang et a1. (1999) observed Canadian prairies
and woodlands to discover that much like no-till, these unbroken soils are an important
sink for CH4.

It soon becomes obvious why there has been so much interest in these three
greenhouse gasses and their ties to agriculture. It is almost impossible to remove one
from the other. Now that the increases of each of these greenhouse gases have been seen
and their origins have been better understood, efforts are being made to reduce their

production due to agriculture.
OBJECTIVES

This study evaluated the effect of four forage cropping systems (no-till alfalfa,
corn, corn/alfalfa, and alfalfa/orchardgrass) with and without compost or manure on soil
C sequestration, greenhouse gas emissions, forage quality and yield at two locations of
different climate that contained large differences in background soil C.

HYPOTHESIS

1. Additions of compost and manure to the soil will increase soil C concentration

within three years.

2. Emissions of greenhouse gases, C02, CH4, and N20 will be different between

forage cropping systems.

17

3. The two locations in this study with different soil type (medium OM content
vs. high OM content) will sequester C at different rates, and result in differing
rates of greenhouse gas emissions.

4. Forage nutritive value of crude protein, NDF and ADF will not be affected by
manure or compost treatments.

5. Forage dry matter yield will be higher with soil treated with both manure and

compost.

MATERIALS AND METHODS

SITE DESCRIPTION AND EXPERIMENTAL DESIGN

This study was conducted at the Michigan State University W. K. Kellogg
Biological Station (KBS, Hickory Comers, Ml; 42.42 °N, 85.37 °W) and the Michigan
Agricultural Upper Peninsula Experiment Station (UP, Chatham, MI; 46.34 °N, 86.92
°W). The soils at the KBS site are Kalamazoo sandy loam (ﬁne-loamy, mixed, mesic
Typic Hapludalfs) and Oshtemo sandy loam (coarse-loamy, mixed, mesic Typic
Hapludalfs). At the UP site the soil is a Ternary sandy loam (mixed, ﬁigid Alﬁc
Haplorthodes). The experiment was a randomized complete block design with 4
replications with 8 treatments (four cropping systems with two organic matter treatments
each). Plot size was 10.6 x 9.1 m at KBS and 12.2 x 12.2 m at the UP site based upon the
available machinery at each location for planting, manure spreading, and harvesting.
Both sites had grown corn in the year prior to the initiation of the experiment.

Fertility management was speciﬁc to each plot based upon soil samples taken

from each plot in the spring of each year. Fertilizer recommendations for P, K, lime, and

18

N were made according to “Tri-State” (Vitosh, 1995) guidelines using a 58 Mg ha'l (1 1
Mg ha'l DM) yield goal for corn silage, and 11 Mg ha'l (DM) yield goal for the
establishment year of the alfalfa and alfalfa/orchardgrass mix and 16 Mg ha'1 (DM) yield
goal for every year thereafter. Fertilizer applications to the compost and manure
amended plots were corrected for nutrients available in the applied compost and manure
treatments to ensure similar fertility levels. Soil pH at the KBS site was 6, while at the
UP site, soil pH was 7.4. Soil bulk density and soil total N values are shown in the
appendix (Table 35).

Four forage cropping systems with two organic matter treatments per system (for
a total of 8 treatments) were selected based on their importance to Michigan dairy
production: continuous silage corn with winter rye cover (corn), continuous alfalfa
(alfalfa), corn with winter rye cover followed by continuous alfalfa rotation (com/alfalfa),
and continuous binary mixture of alfalfa and orchardgrass (13.5 kg ha'l alfalfa seed
mixed with 4.9 kg ha'| orchardgrass) (alfalfa/orchardgrass) (Tables I and 2).

The seedbed at KBS was prepared for planting with a primary tillage operation
using a chisel plow in the fall prior to spring planting followed by two passes of a ﬁeld
cultivator in the spring (once north-south, and once east-west). At KBS corn was planted
using a JD 7300 (Deere & Company). The legumes were planted with a conventional
tillage John Deere grain drill set up for planting small seeded legumes or grasses using
band seeding with press wheels, (Deere & Company) and each legume plot was
coultipacked to ensure good seed-soil contact (treatments alfalfa and

alfalfa/orchardgrass). At the UP location, the soil was disked in the spring prior to

19

planting and the legume plots (treatments alfalfa and alfalfa/orchardgrass) were
coultipacked before the ﬁeld was seeded.

Compost (at KBS) and manure slurry (at UP) treatments were applied in the
spring before corn planting (A table comparing the two organic matter source treatments
is given in the appendix, Table 33). A dairy manure and sawdust bedding compost
(18.8% C, 3.6% N, C:N = 5.22) from the Michigan State University Dairy Cattle
Teaching and Research Center in East Lansing was applied at KBS at a rate of 35,860 kg
compost ha" using a Millcreek model 50 (Millcreek Manufacturing Co., Leola,
Pennsylvania) small plot manure spreader. This provided approximately 3000 kg of C
ha'l yr". At UP, manure slurry (3.83% C, 0.287% N, C:N = 13.34) from the dairy at the
Upper Peninsula Experiment Station was spread using a Houle 3150 (J. Houle & Fils
Inc., Drummondville, Quebec, Canada #527) liquid manure tanker/spreader at a rate of
84,200 L manure ha'l to provide approximately 3000 kg of C ha'I yr". Each lot of
compost and manure was tested for nutrients and C content prior to application (N, P, and
K as well as C:N Ratio and % C). Summary tables of all ﬁeld activities are shown in the
appendix (Tables 27 through 32).

SOIL ANALYSIS

Three soil cores were collected from each replication using a 5-cm diameter corer
(Geoprobe® Macro-Core®, (Geoprobe Systems)) prior to compost and manure
applications each year (4/23/2002, 4/20/03, and 4/27/04 at KBS and on 5/ 14/2002,
5/5/03, and 4/3/04 at UP). The cores from each plot were divided into 0-5 cm and 5-25
cm portions, composited by depth, and analyzed for bulk density, available N, total N,

total C, and POM. Air-dried sub samples from each of the composited soil cores from

20

each replication were also analyzed for soil pH, phosphorus, and potassium by the
Michigan State University Soil and Plant Nutrient Laboratory.

The procedures for soil analysis were as follows. Available soil N was
determined using KCl extraction by shaking 20 g soil in a l-M KCl solution for 45 min.
The solution was allowed to settle for approximately 10 min and the resultant supernatant
ﬁltered using Whatrnan brand, size 1 ﬁlter paper (Whatman plc). The ﬁltered liquid was
frozen in plastic sample vials until it could be analyzed by the Michigan State University
Soil and Plant Nutrient Laboratory for available soil N. For total soil N and C
determination (TSN and TSC), a sub-sample of soil was passed through a sieve (2-mm
mesh size), powder-ground using a ball mill grinder. Approximately lS-mg (+/- 3-m g)
sub-samples were analyzed for total soil N and C using a Costech Instruments ECS 4010
combustion furnace (Costech Analytical Technologies, Valencia, CA). The protocol
developed by the Michigan State University, Kellogg Biological Station, Long Term
Ecological Research project (Protocol: KBS024-prot01 (1): Soil C and N) was used to
analyze total C and N. For POM determination, a modiﬁed version of the POM by
subtraction method was used (Cambardella and Elliott, 1992; Carter, 1993). Thirty mL
of 0.50% (5 g L") sodium hexametaphosphate was added to a 10 g sub-sample of sieved
soil (2 mm) and shaken for 15 hr in a reciprocal shaker to disperse soil particles. The
solution was poured through a 53 um sieve. The material remaining on the sieve was
thoroughly washed with distilled water and the mineral solution containing silt and clay
was collected as it passed through the sieve. The mineral solution was dried overnight at
70 C° and weighed. The dried material was powder-ground and a lS-mg sub-sample was

analyzed for C and N of the mineral fraction using a combustion fumace as previously

21

described for total C and N. Subtracting this value from the total soil C and N results in
POM C and N.

FORAGE YIELD AND NUTRATIVE EVALUATION

Alfalfa and orchardgrass were harvested with a Carter research plot ﬂail harvester (Carter
Manufacturing Co. Inc., Brookston, IN) designed to harvest a 1.2-m wide swath down the
center of the plot. Com silage was harvested using a research two-row corn silage
chopper (custom built 2-row chopper built using a John Deere 34 corn silage chopper and
a Kincaid plot combine, Kincaid Company, Haven, Kansas). In the seeding year, two
cuttings of the alfalfa and alfalfa/orchardgrass treatments were harvested when alfalfa
reached 10% bloom. Each successive year, ﬁrst cutting for alfalfa, com/alfalfa, and
alfalfa/orchardgrass treatments were harvested when the alfalfa reached 10% bloom, and
every 30-35 days thereaﬁer for a total of four cuttings at KBS, and three cuttings at UP
each year. The orchardgrass in the alfalfa/orchardgrass treatments at UP matured earlier
in 2004 and the alfalfa/orchardgrass plots were subsequently harvested 10 days earlier
than the alfalfa or com/alfalfa treatments for the remainder of the season. Total forage
wet-weight from each harvested strip was recorded for each plot and a sub-sample from
each plot was used for dry matter determination and was retained for forage nutritive
analysis.

Forage nutritive analysis was done by the Michigan State University Forage
Research Laboratory. A sub-sample of approximately 20-g was retained for nutritive
analysis, ground to pass a l-mm screen using A Norris 8” lab mill (Ipswich UK), and was
scanned with a 6500 near-infrared spectrophotometer for forage quality determination

(FOSS NIRSystems Inc., Silver Spring, Maryland). Reﬂected wavelengths (between 800

and 2500 nm) were recorded. A subset of these scanned samples was selected using the
“Select” program from WinISI software (Infrasoﬂ International LLC., Port Matilda,
Pennsylvania) to create equations for the prediction of crude protein (CP), neutral
detergent ﬁber (N DF), and acid detergent ﬁber (ADF). Total N was determined for the
subset by the Hach modiﬁed Kjeldahl procedure (Watkins, 1987), and CP was estimated
by multiplying total N by 6.25. The Goering and Van Soest (1970) method was used for
NDF and ADF determination with the addition of 1 ml of alpha-amylase to the neutral
detergent solution to break down starch. Dry matter (DM) content was determined by
drying 0.5-g of sample in ceramic crucibles at 100°C for 12 hrs. The samples were then
ignited in a mufﬂe furnace at 500 °C for 6 hrs to determine ash content.

GAS ANALYSIS

CO2, CH4, and N20 ﬂuxes were estimated monthly using in-situ closed-cover ﬂux
chambers. Bases of the chambers (25.4-cm circular PVC drainage pipe, lO-cm high) were
installed in all plots (removed only for farming activities and in the winter). A PVC end-
cap was placed over the exposed portion of the chamber and latex sheeting
(approximately 94 x 7.5-cm) was wrapped around the edge of the cap to provide a gas-
tight seal between the cap and the base. Soil temperature and a soil sample (analyzed for
moisture content) were taken each time gas ﬂuxes were sampled.

Gas ﬂux sampling was done at four 45-min sampling intervals by drawing 40-mL
of gas from each chamber. Sealed lO-mL Labco Exetainer glass vials were ﬂushed with
30-mL of the collected gas. The vial was over-pressurized with lO-mL of gas from the
chamber. In the laboratory, CO2 was analyzed using an infrared gas analyzer (SB 100,

Analytical Development Co. Ltd., Hoddeson, England). CH4 and N20 were analyzed by

23

gas chromatography using a Hewlet Packard 5890 Series 11 Gas Chromatograph; Poropak
0 column (1.8-m, 80/ 100 mesh) at 80 °C. N20 was detected by electron capture at 350
°C (ECD), CH4 by ﬂame ionization at 300 °C (FID).
STATISTICAL ANALYSIS

Analysis of variance (ANOVA) was performed on yield, forage quality,
greenhouse gas ﬂux, soil POM, and soil TOC data using Proc Mixed (SAS Institute,
2000). The crop and organic matter treatments were considered ﬁxed effects, while
replication was considered a random effect. Greenhouse gas ﬂux data was log
transformed when necessary to meet ANOVA assumptions of normal distribution.

Unless otherwise stated, differences were considered signiﬁcant at an alpha level of 0.05.

RESULTS AND DISCUSSION
UP FORAGE YIELDS

At the UP location, statistical analysis revealed the strongest effect on forage dry
matter (DM) yields (Table 3) was from the crop x year interaction (P<0.0001). There
was also a signiﬁcant effect of crop x manure interaction (P<0.05). Due to the signiﬁcant
interaction effects for crop x year as well as for crop x manure; it is not possible to
compare individual cropping treatment or manure treatment effects on DM.

There were no signiﬁcant differences between the cropping treatments with and
without manure with the exception of the Com treatment. Although not statistically
signiﬁcant, in 2002, the treatments which received manure additions had higher yields
than the cropping treatments which did not receive manure (Table 4). The perennial
cropping systems were only harvested once in the seeding year and this resulted in these

treatments yielding approximately one third less than the corn and com/alfalfa treatments.

24

In the second year of the study (2003) at UP, the perennial crops (alfalfa, and
alfalfa/orchardgrass) were harvested three times and resulted in higher dry matter yields
than the corn treatment. The alfalfa treatment with manure resulted in the highest
recorded DM yield (16.62 Mg ha"). The alfalfa treatment without manure resulted in a
DM yield of 13.38 Mg ha". The alfalfa/orchardgrass treatments were not signiﬁcantly
different (10.84 Mg DM ha" with manure and 11.27 Mg DM ha" without manure). The
corn without manure treatment (8.37 Mg ha") tended to yield more than corn with
manure (6.91 Mg ha"). The alfalfa in the com/alfalfa treatment was not harvested this
year because the alfalfa was not well established at harvest time.

In 2004, the third year of the study, the alfalfa with manure resulted in the highest
yield with l 1.37 Mg ha'1 per hectare. The corn with manure (6.54 Mg ha") and non-
manured corn (6.64 Mg ha!) treatments were not signiﬁcantly different from each other
or the non-manured alfalfa (8.12 Mg ha") and both corn treatments (7.61 Mg ha’' with
manure and 7.01 Mg ha'l without manure). While not statistically signiﬁcant, the
com/alfalfa treatment DM yields were slightly higher with manure added, while both
corn/alfalfa with and without manure tended to out yield both of the alfalfa/orchard grass
treatments. This may have been due to increased competition from two species compared
to the monoculture cropping systems in the corn/alfalfa treatment.

For each of the cropping treatments there were no signiﬁcant differences in three-
year accumulated yields from the manure treatments; however, manured treatments did

yield slightly more than the non-manured treatments.

25

KBS FORAGE YIELD

At the KBS location, statistical analysis (Table 5) revealed the strongest effect on
forage yield was from year (P<0.0001). However, there was also a signiﬁcant
(P<0.0001) crop x year interaction; therefore it is not possible to compare differences
between cropping treatment yields. Cropping treatment means by year at KBS are
presented in Table 6. There was a signiﬁcant increase in DM yield with the addition of
compost at the KBS location (P<0.0459). On average, treatments amended with compost
yielded of 7.78 Mg ha'l compared with 7.09 Mg ha'l for the non-amended plots.
However the corn with compost treatment in 2004 averaged 3.36 Mg ha-l more than the
corn without compost added, while the alfalfa and alfal fa/orchard grass treatments with
compost only averaged 0.63 and 0.62 Mg ha-l more than their respective non-composted
treatments.

At KBS, corn yields in 2002 (Table 6 and 7) were much lower than those at the
UP due to poor stand establishment at the KBS site which was caused by seed predation
by birds and ground squirrels (Spermophilus tridecemlineatus, Mitchill). However, both
the corn and com/alfalfa (corn/alfalfa treatment was planted to corn in 2002) treatments
tended to yield more than other cropping treatments. The corn treatment yielded 7.37 Mg
ha'I and the com/alfalfa treatment yielded 8.24 Mg ha". The alfalfa and
alfalfa/orchardgrass treatments were only harvested once during this the seeding year.
The alfalfa treatment yielded 2.31 Mg ha". The alfalfa/orchardgrass treatment yielded
1.78 Mg ha'1 in the ﬁrst year.

In the second year (2003) the alfalfa and alfalfa/orchardgrass treatments were

each harvested 4 times at KBS. There were no signiﬁcant differences between crop

26

treatment yields. The corn treatment yielded 4.89 Mg ha", the alfalfa treatment yielded
10.26 Mg ha", the com/alfalfa treatment (planted to alfalfa) yielded 2.68 Mg ha", and the
alfalfa/orchardgrass treatment yielded 10.67 Mg ha". For the second year, ground
squirrels were a problem for the corn treatments. It was decided that planting another
crop as similar to corn as possible (C-4 grass, harvested as forage, similar growth cycle,
and nutrient requirements) would be the best remedy for this situation. Sorghum was
planted that year since ground squirrels, contributed to a loss of approximately 50% of
the corn stand for the second year. These research plots had a history of problems with
ground squirrels in no-till situations which were not explained to us when we started the
experiment. While damage to larger stands of corn may have been negligible, in this
small plot setting, seed predation by ground squirrels was a serious issue. Sorghum was
planted into the corn treatment on June 17, 2003 after it became evident that there would
not be enough corn to harvest due to excessive stand loss.

In the third year of the study (2004), ground squirrels were more effectively
controlled at KBS by trapping, poisoning, and by planting earlier resulting in the corn
yields being closer to expected yields (12.48 Mg ha'l), the alfalfa treatment yielded 12.78
Mg ha", and the corn/alfalfa yielded a more typical 12.78 Mg ha". The
alfalfa/orchardgrass treatment yielded 11.57 Mg ha".

After three years, the average yield for the corn treatment was 8.24 Mg ha'l and
the alfalfa treatment yielded an average of 8.45 Mg ha". The three year average for the
corn/alfalfa treatment was 6.98 Mg ha'l, and the alfalfa/orchardgrass treatment yielded an
average of 8.01 Mg ha]. The difference seen between the corn/alfalfa treatment and the

other treatments was due to this treatment having to catch up one year later than the other

27

perennial crops. While yields for this treatment tended to be lower than the other
treatment planted to alfalfa, it yielded similarly to the alfalfa treatment in the prior year.
FORAGE NUTRITIVE ANALYSIS

Statistical analysis of forage nutritive analysis at both locations showed no
signiﬁcant differences between manure or compost treatments. This was probably due to
the additions of synthetic fertilizers to compensate the plots not receiving manure or
compost at both locations. There were however signiﬁcant Crop x Manure x Year
interactions at the UP location (Table 8), and signiﬁcant Crop x Year interactions at the
KBS location (Table 10). Treatment means for both locations are given in Tables 9 and
11. Signiﬁcant differences between crops and years were expected since the differences
in forage quality between different species of plant are what make some more desirable
as fodder than others (Hoﬁnann and Isselstein, 2005). The differences between years has
also been shown by since growing conditions (rainfall and daily temperature) (Kim et
al., 2005) as well as the timing of harvests signiﬁcantly impact forage quality (Crasta et
al., 1997). These impacts far outweigh the slight improvements or declines in forage
quality with and without additional organic matter amendments in the forms of manure
and compost. Additionally since the legumes ﬁx their own nitrogen from the atmosphere
and consume available nitrogen in the soil when it is present, the additions of N in the
compost and manure do not be play a role in differences between the organic matter
treatments.

The corn treatments which did not receive compost or manure were fertilized with
inorganic fertilizer at a comparable rate as the treatments amended with compost and

manure. At the UP location, manure was applied one month before the corn planting in

28

2004, 2 weeks before corn planting in 2003, and 1 week before corn planting in 2002.
The inorganic N fertilizer was applied approximately one month after the corn was
planted as anhydrous ammonia (28%).

At the KBS location, compost was applied the day before corn planting in 2004, 5
days before corn planted in 2003, and one month before corn planting in 2002.
Anhydrous ammonia was applied to the corn treatments in 2004, approximately 6 weeks
after corn was planted, and approximately one month after corn was planted in 2002. In
2003, the sorghum received ammonium sulfate (34%) after each harvest.

The different timing of N fertilization through the manure and compost compared
with inorganic fertilizers was not signiﬁcant for any of the forage quality factors studied
here. There did appear to be a slight trend for CP to be higher at the UP location without
manure. This may have been due to the timing of N applications. Manure derived N was
surface applied almost 2 moths before the crop would need it for growth. It is likely that
the majority of the nitrogen applied in the manure was lost to volitization of NH4 before
the crop was even planted. The anhydrous ammonia applied 4 weeks after planting
would be much more readily available for plant uptake and growth.

At KBS the compost was applied much closer to the time when the plants would
have used the N, however since the compost was also surface applied and not
incorporated, it is likely that the majority of the available N in the form of NH4 was lost
due to volitization before the crop required the additional N. The lack of differences
between organic matter treatments for the corn cropping system shows that this lost N did

not play a role in affecting forage quality for this crop.

29

Differences in forage quality between the alfalfa/orchard grass cropping treatments
and the pure alfalfa cropping treatments were signiﬁcant at both the UP location and the
KBS location. This was due to the higher ﬁber content of the grass and because the grass
matured more quickly than the alfalfa (Wiersma et al., 1999). At the UP location, ADF
was not different in 2002, but it was signiﬁcantly greater in 2004 (30.8% and 27.3% for
the manured and non manured 2002 Alfalfa treatments compared with 31.8% and 32%
for the manured and non manured 2002 Alfalfa/Orchardgrass treatments). In 2004, NDF
content was 33.3% and 32.1% for the manured and non manured Alfalfa treatments
respectively while the Alfalfa/Orchardgrass treatment NDF averaged 38.2% and 35.9%
for the manured and non manured treatments respectively. NDF content was similar to
the differences found in ADF levels with higher NDF content in the Alfalfa/Orchardgrass
treatment than the Alfalfa monoculture treatment. This is because alfalfa matures more
slowly than orchardgrass resulting in increased NDF and ADF at harvest time in the
Alfalfa/Orchardgrass treatments. Alfalfa/Orchardgrass CP measured in 2002 and 2004
was signiﬁcantly lower than the Alfalfa cropping treatment CP. This is due to alfalfa
maturing more slowly than the alfalfa/orchardgrass mixture (Sheaffer et al., 1990; Sleugh
et al., 2000). At the KBS location, these trends were the same for the Alfalfa and
Alfalfa/Orchardgrass cropping treatments. These differences are shown in Tables 9 and
11.

GREENHOUSE GAS FLUXES

Soil greenhouse gas ﬂuxes were sampled and analyzed each year of the study;

however, due to equipment problems and different 1St year protocols, only the 2004 data

is presented here. In 2002 gas ﬂuxes were measured only twice and were not reliable

30

measures of greenhouse gas ﬂuxes for that growing season. As a result that data is not
reported here. In 2003 gas ﬂuxes were measured 4 times at KBS and 6 times at UP
however problems with analytical equipment made these data unreliable. In 2004, with
the exception of one set of samples taken at KBS (5/20/2004), and two sets of samples
taken at UP (5/4/2004 and 10/18/04), the majority of the problems with the equipment
and sampling protocol were corrected. Data reported here include only gas samples
collected in 2004.

The measured gas ﬂuxes at both locations were extremely variable through time.
This high level of variability is attributed to differences in weather, soil moisture, ground
cover, as well as the crop and manure or compost treatments at each location and through
time. At the UP location in 2004, statistical analysis (Table 12 and 13) of seasonal
greenhouse gas ﬂuxes showed signiﬁcant effects from manure on N20 ﬂuxes (P<0.0405).
This was probably because the manure provided a much more readily available source of
N than the 28% N applied to the corn treatments two months earlier. Differences in N20
ﬂuxes from crop effects were not signiﬁcant (P<0.09). The greater variability in soil
moisture, differences in spatial distribution of available N early in the season, differences
in ﬁeld microtopography, and other factors likely had greater inﬂuences on N20 ﬂuxes
than the effect of plant species (Ambus and Christensen, 1995; Anderson et al., 1983;
Ball et al., 1997). The alfalfa/orchardgrass cropping treatment with manure had the
largest cumulative ﬂux of N20 (266 g N20 ha" growing" season) of all the cropping
treatments (Table 13), however this cropping treatment also had a large amount of

variability between samples.

31

CO2 ﬂuxes at the UP location were not signiﬁcantly different between manure
and non-manured treatments, however, all manured treatments with the exception of the
alfalfa/orchardgrass treatment, resulted in higher ﬂuxes of CO2 than their non-manured
counterparts did. The manure may have provided a readily available source of N and C
to the soil bacteria that consumed it which would have produced more CO2 as a result
(Dao and Cavigelli, 2003; Liebig et al., 1995; Min et al., 2003). The effects of cropping
treatments were not signiﬁcant (P< 0.0583). The Alfalfa/Orchardgrass plots with manure
resulted in the greatest C02 ﬂux (88.29 kg ha" season") similar to previous research
(Paul et al., 1999), while the non-manured Corn treatments resulted in the lowest
recorded ﬂuxes (35.37 kg ha" season").

At the UP location, CH4 ﬂuxes were not signiﬁcantly different due to manure or
cropping treatment. The ﬂuxes at the UP location were all negative indicating that CH4
uptake was occurring. CH4 uptake was greater at UP than at KBS. This was most likely
because the environmental conditions in the UP were more conducive to CH4 uptake.
Cooler temperatures tend to result in moist soil conditions through the summer which
provided optimal conditions for methanophilic bacteria in the soil at the UP location.
Higher soil organic matter levels and sand content also helped keep soil moist and well
aerated for good CH4 uptake. Uptake was lowest in the Corn treatment without manure (-
2.12 g ha" season"). The Corn without manure received supplemental N (in row). This
additional N may have contributed to the reduced CH4 uptake since CH4 oxidation has
been shown to be competitive with de-nitriﬁcation (Hutsch, 1998; Hutsch, 2001). CH4

uptake under manure treated plots tended to be greater than plots without manure. The

32

greatest CH4 uptake took place under the Alfalfa/ Orchard grass with manure treatment (-
4.57 g ha" season").

At the KBS location, measured greenhouse gas ﬂuxes were only statistically
different for N20 and then only by crop treatments (P<0.0327) (Table 16). The measured
greenhouse gas ﬂuxes tended to be greater than at UP (Table 13). At KBS, with the
exception of the Corn treatment, compost amended plots showed a tendency towards
lower N20 ﬂuxes, opposite of the trends at UP for the manured plots. This may have
been due to the fact that the N in the applied compost was generally tied up in organic
forms not immediately available for plant uptake (Hartz et al., 2000; Paul and
Beauchamp, 1993; Paul and Beauchamp, 1994) and that the high levels of ligniﬁed
carbon applied in the compost may have tied up any free nitrogen in the soil. This is in
contrast to the N applied in the manure which would have been much more readily
available in the ammonium and organic N forms. The Alfalfa treatment had the highest
measured N20 ﬂux (2.91 g ha" season"). The Alfalfa/Orchardgrass had the lowest
measured N20 ﬂux (1.58 g ha" season").

CO2 ﬂuxes at KBS were not signiﬁcant for crop or for compost treatments. There
was a tendency for plots amended with compost to have lower CO2 ﬂuxes through the
season than the plots not receiving compost (109.05 and 115.97 kg ha" season"
respectively). This may also be tied to the large amounts of ligniﬁed carbon applied in
the compost which may have had the effect of tying up free nitrogen which would have
been required for the breakdown of the respiration of CO2 by microorganisms. The
Alfalfa plots had the highest measured C02 ﬂuxes (132.20 kg ha" season") and the Corn

plots had the lowest measured CO2 ﬂuxes (83.64 kg ha" season"). The higher ﬂuxes

33

under alfalfa may have been due to additional organisms within the soil matrix, namely
the nitrogen ﬁxing bacterial residing in the roots of the alfalfa plants. The higher CO2
ﬂuxes may also have been due to ﬁne root decomposition each time the alfalfa and
orchardgrass plots were harvested. However, the Alfalfa/Orchardgrass treatment only
had a measured ﬂux of 105.33 kg ha-l season-l which was greater than the corn (83.64
kg ha-l season-l), but still less than the Com/Alfalfa treatment (114.01 kg ha-l season-
l). One would assume that the Alfalfa/Orchardgrass treatment would have the most ﬁne
roots of any of the cropping treatments.

CH4 ﬂuxes at KBS were all negative, as in the UP, and while differences were not
statistically different, there appeared to be a trend for lower CH4 uptake following
compost additions (-2.28 and -2.47 g ha" season" for the composted and non composted
plots respectively). The greatest CH4 uptake was in the Corn/Alfalfa treatment (-2.83 g
ha" season"). The Alfalfa treatment resulted in the lowest uptake of CH4 (-2.07 g ha"
season") potentially due to the increased availability of NH4 and the non-selective
enzyme mono-oxygenase which is used by the methanotrophs to oxidize CH4 (Mosier
and Sehimel, 1991). Overall, CH4 uptake at KBS was 2-3 times lower than at UP. This
was likely due to drier soil conditions which occurred at the KBS site, which led to
poorer conditions for the methanophilic bacteria.

GREENHOUSE GAS FLUXES AS C02 EQUIVALENTS

The differences between cropping systems with and without organic matter
additions at both locations were evident after converting the accumulated greenhouse gas
ﬂuxes into 100-year C02 equivalents (comparison based on the 100-year global warming

potential, GWP, of each gas; N20 = 310 times the relative thermal absorption of CO2 and

34

CH4 = 21 times the relative thermal absorption of CO2 (Robertson et al., 2000). This
system allows a common scale for comparison purposes. The differences between
locations were signiﬁcant, however between treatments, differences were not statistically
signiﬁcant. There appear to be some trends however. In this experiment, the UP location
had much lower ﬂuxes of N20 and much greater uptake of CH4 than KBS location (Table
16 and 17). This resulted in a higher GWP for the KBS compared with the UP location.
Greenhouse gas production at the UP was higher under manured treatments for all
cropping systems except the Corn/Alfalfa treatment. The Corn and Alfalfa treatments
without manure resulted in the lowest overall greenhouse gas ﬂuxes.

In 2004, the seasonal greenhouse gas ﬂuxes from the cropping systems at the
KBS location (like at the UP location), were driven primarily by the N20 ﬂuxes.
Treatments with high N20 ﬂuxes included the Corn with compost, and un-amended
Com/Alfalfa treatments. The cropping system which appeared to result in the lowest
greenhouse gas ﬂuxes was the Alfalfa/Orchardgrass with compost.
TOTAL SOIL C AND POM

Total soil C (TSC) in the 0-5 and 5-25 cm soil horizons at the UP location and the
5-25 cm soil horizon at the KBS location measured in 2004 were not signiﬁcantly
different due to crop or manure treatments (Table 18). The lack of detectable differences
was probably most likely due to the small amounts of C added by the treatments in
comparison to the large amounts of background C. Cropping treatment means are
presented in Table 19 and manure treatment means in Table 20. TSC concentration in the
0-5 cm horizon at KBS in 2004 were nearly half that at the UP location. TSC in the 0-5

cm soil horizon at the KBS location was signiﬁcantly different for the compost

35

treatments (P > 0.0214). Plots receiving compost had an average TSC of 0.943 kg m’2
while plots without compost averaged 0.798 kg m’z. The addition of the compost which
was comprised of sawdust and dairy manure provided a high 1i gnin source which was not
easily broken down, in comparison to the dairy manure slurry applied at the UP location
which was easily broken down by soil micro-organisms.

There are methods which can measure soil C accurately, however, small changes
in soil C levels are difﬁcult to detect due to factors of seasonal variability, spatial
variability, and the difﬁculties inherent in detecting changes with large background levels
of C (Bamwell et al., 1992; Conen et al., 2003; Paul et al., 2001; Paustian et al., 1995).
The mean soil C sampled at the KBS location had a standard error of 0.01 7 % C at the 0-
5 cm depth and, 0.02 % C at the 5-25 cm depth while the UP location the mean soil C
standard error was 0.048 % C for the 0-5 cm depth, and 0.046 % C for the 5-25 cm depth
in the ﬁrst year of the study (2002).

The minimum detectable difference in soil C can be estimated in a one-tailed, one
sample t-test as a product of the standard error and the sum of the critical t values for type
I and 11 error probabilities (Zar, 1999). To achieve a statistical power of 0.90, that sum is
2.978. Therefore the minimum detectable difference is 0.05, 0.06, 0.14, and 0.13 %
change in C for KBS 0-5 cm, 5-25 cm, Chatham 0-5 cm, and 5-25 cm respectively,
assuming variability did not increase. However, as a result of the different treatments and
temporal variation, variability did in fact increase. This increase was greatest at KBS,
where the CV increased from 9.6 to 15 and from 14 to 16 in the 0—5 and 5-25 cm horizons
respectively. These results follow previous research by Bird et al., Conant and Paustain,

and Conant et al. (Bird et al., 2002; Conant and Paustian, 2002; Conant et al., 2003).

36

The increase in the variability of these data resulted from the combination of
changes in bulk density (which can be very susceptible to changes in soil moisture), small
scale spatial variability, and the effects of cropping treatments and organic matter inputs.
Since the amount of C in the soil expressed as mass per volume requires the soil bulk
density for the calculation, the variability of the bulk density and its changes were added
into the calculations for total soil C. The increase in variability of the bulk density is
translated into variability of the measured total soil C. Bulk density was not uniformly
variable over the 3-year study. The background bulk density CV was 8 and 9 in the 0-5
cm horizons at KBS and Chatham respectively. Bulk density in 2004 declined to 5 g cm'
3 and increased to 10 g cm’3 at KBS and Chatham respectively.

We hypothesized that adding large amounts of C in the forms of manure and
compost it would be possible to signiﬁcantly affect soil organic matter differences in a
short time period. Initial POM levels were not measured in 2002 due to the high cost of
analysis and time constraints. It was also felt that since calculating POM requires the use
of soil bulk density (which is very susceptible to changes in soil moisture and time of
year), the best course of action would be to work with one year’s soil. The resulting
comparison of POM levels between organic matter treatments for the same cropping
system treatment would then be sufﬁcient for detecting changes in soil POM without
confusing the data with temporal, moisture, and various other factors which could have
affected soil POM more than the treatments applied in this experiment.

C was added at a rate of 350 g C rn’2 y'2 at both locations to the plots receiving
organic matter inputs (manure at Chatham, compost at KBS). This represented

approximately 48% of the background C in the top 5 cm at KBS and 25% of the

37

background C present in the top 5 cm at Chatham. Since the organic matter was not
incorporated into the soil at either location, increases in the amount of soil organic matter
in the 5-25 cm horizon would only be expected to result through the action of cropping
system root biomass inputs. These differences are much harder to detect as the process
of C sequestration due to plant roots is much-slower than amending with compost or
manure and thus detecting those changes was not possible in the time allotted for this
experiment.

Both the compost and the manure were surface applied rather than incorporated at
both locations to achieve no-till planting. At the KBS location, that surface application of
compost may have resulted in increased surface soil C. By applying the compost on the
surface, it was more exposed to sunlight and environmental conditions which kept it drier
than the manure applied at the UP location, which was applied as slurry. The compost
also was composed of a more ligniﬁed form of C, namely sawdust which made it less
susceptible to degradation by soil microbes (Honeycutt et al., 1993). These two sources
of organic matter were very different, and resulted in different fates for the two types of
organic matter. For example, compost was still visible on the soil surface 7 months after
application, while the manure was broken down by microorganisms within three weeks
of application. The manure provided readily available sources of organic N, phosphorus,
and easily degraded forms of C that were utilized more quickly by the crops and soil
microbes. The compost, on the other hand, had much lower available N and greater
amounts of ligniﬁed material which takes much longer to break down in the soil (Baldock
et al., 1997; Chantigny et al., 2002). The composted treatments also had half the

available N of the non-composted plots as measured by KCl extraction. The large

38

amount of C (compost had 5 times more carbon on a percent basis than the manure) in
the applied compost resulted in N immobilization in the soil as measured in 2003. At the
KBS location a pre-sidedress nitrogen test (PSNT) was taken (July 18, 2003) after the
corn stand failed due to seed predation. Treatments which received compost had reduced
available N (2.8 ppm) compared to plots not receiving compost (5.6 ppm).

Because of difﬁculties associated with measuring changes in total soil C, our
research focused on the POM fraction (which is thought to be responsive to changes in
tillage regimes and possibly cropping systems within a shorter time period)(Cambardella
and Elliott, 1992). There were no signiﬁcant differences between any of the cropping or
manure treatments at the UP location (Table 20). The lack of signiﬁcant differences
between treatments at the UP location was likely due to high background levels of soil C
inherent in the soils which averaged 0.72 kg POM C m'2 in the 0-5 cm soil horizon, and
1.91 kg POM C m'2 in the 5-25 cm soil horizon (Table 20). Although total soil C
concentration did not change signiﬁcantly between treatments at the UP location over the
3-year study, POM C means with manure treatments were 10% lower than non-manured
plot treatments for both depths (0.52 and 0.56 kg POM C m'2 for the manured and non-
manured 0-5 cm soil horizons respectively). There also appeared to be a trend in that
plots with the highest measured POM C were the Corn treatments at both depths (0.69
and 2.08 kg POM C rn’2 for the 0-5 cm and 5-25 cm soil horizons respectively) while the
Alfalfa/Orchardgrass cropping treatments had the lowest measured POM C (0.51 and
1.69 kg POM C m'2 for the 0-5 cm and 5-25 cm soil horizons respectively).

POM C levels at KBS were approximately half those at the UP; (0.27 kg POM C

rn’2 for the 0-5 cm soil horizon and 0.72 kg POM C rn'2 for the 5-25 cm soil horizon).

39

Signiﬁcant differences were detected in POM C between compost treatments in the 0-5
cm soil horizon (Table 26). The plots receiving compost had 0.94 kg POM C m'2 while
the plots not receiving compost had 0.80 kg POM C m'z. This slight increase may have
been due to additional inputs of large amounts of ligniﬁed C present as decomposed
sawdust in the compost. Any changes occurring in the 5-25 cm soil horizon was from
changes in plant root material inputs, since the organic matter applied at both locations
was not incorporated.

The effect of cropping system was not signiﬁcant. However, in contrast to the UP
location where the Alfalfa/Orchardgrass cropping treatment had the lowest measured
POM C, at the KBS location, the Alfalfa/Orchardgrass had the highest measured amount
of POM C for both soil depths (0.30 and 1.23 kg POM c m'2 for the 0-5 cm and 5-25 cm
soil horizons respectively). The Alfalfa treatment resulted in the lowest measured POM
C in the 0-5 cm soil horizon (0.19 kg mi!) and the Com/Alfalfa cropping treatment
resulted in the lowest POM C in the 5-25 cm soil horizon (0.59 kg m'z).

The increase in measured POM C under the Alfalfa/Orchardgrass cropping
treatment may have been due to the addition of ﬁne roots from the Orchardgrass after
each harvest (Fu et al., 2002; Robertson et al., 1995; Urquiaga et al., 1998). It may have
been that due to the higher amount of clay in the soil at the KBS location there was a
greater capacity to sequester carbon while at the UP location, the capacity for additional
carbon inputs in the form of ﬁne root material had already been ﬁlled.

While soil C levels can be rapidly depleted by tillage, increases due to changes in
management practices happen slowly and over long periods of time resulting in

signiﬁcant time spans for soil C stocks to reach new equilibriums(Robertson et al., 2000).

40

It is likely that the short time frame allotted for this experiment was not adequate to allow
the soil C stocks or the soil structure to stabilize and therefore it was not possible to
detect the changes in soil C for most of the treatments. If additional time had been

available for this study, additional changes in soil C may have been detected.

CONCLUSIONS

There were signiﬁcant forage quality differences between species, but these
differences were not tied to organic matter treatments. These differences were due to
differences in protein and ﬁber content of the different plants used in this study, namely
alfalfa, corn, and orchardgrass. Each of these crops has differing amounts of protein and
ﬁber which make them suitable as forage crops.

The higher Corn yields at the UP location were due to pests found at the KBS
site primarily from ground squirrels feeding on newly emerged corn seedlings. Higher
Alfalfa/Orchardgrass yields at KBS were greater mainly due to the shorter growing
season and subsequently fewer harvests taken at Chatham. Chatham’s corn growing
season is limited by late frosts until from late May, while at KBS; corn could be planted
in early May without fear of frost damaging the stand. Frost can appear in September at
the UP location while at KBS it is usually delayed by 2-3 weeks.

The slightly lower yields of the Alfalfa/Orchardgrass treatment at KBS compared
with the Alfalfa treatment indicate that while the system may not yield as high as the
Alfalfa treatment, it still may an option for a more diverse cropping system that can be
incorporated into forage cropping rotations to increase soil carbon. It was hypothesized
that the Alfalfa/Orchardgrass cropping system would help build soil C due to the

diversity of roots in the soil (ﬁbrous roots from Orchardgrass, and the deep taproots of

41

alfalfa) as well as the orchardgrass scavenging excess N ﬁ'om the alfalfa plants. That was
not the case at the UP location where there was a high level of background soil C. It was
the case at the KBS location and may have been due to increased clay content in the soil.

When comparing the differences between greenhouse gas ﬂuxes, the UP location
resulted in lower N20, and CO2 ﬂuxes while having greater CH4 uptake, compared to the
KBS location which had high N20 and CO2 ﬂuxes and very little CH4 uptake. This
resulted in a lower overall GWP for the UP location compared to the KBS location. This
was most likely due to differences in climate and higher amounts of soil organic matter
which lead to moist soil conditions and were more conducive to CH4 uptake at the UP
location. The warmer climate at the KBS location was more favorable for increasing
N20 production and reducing CH4 uptake. There were no differences seen in the two
organic matter treatments at the two locations, however if gas ﬂuxes had been measured
immediately following application of the manure and compost at both locations,
differences may have been apparent between the treatments.

The UP location had a higher background level of soil C present at the beginning
of the experiment compared to the KBS location. This indicates that the climate has been
more conducive to soil C building over a long period of time than the KBS location.
However, signiﬁcant changes in soil C due to additions of organic matter or different
cropping treatments were not evident at the UP location in the time allotted for this
experiment. It was interesting to note however that at the UP there appeared to be a trend
for the plots amended with manure to have lower amounts of POM C than the plots

which did not receive manure.

42

There were no signiﬁcant differences in POM C due to cropping treatment after 3
years; however there was a trend which resulted in the Alfalfa/Orchard grass cropping
treatment exhibiting the highest POM C for both 0-5 and 5-25 cm soil horizons. This
shows the potential for increasing POM signiﬁcant by cropping systems overtime. The
signiﬁcant difference in soil C in the 0-5 cm soil horizon at the KBS location may have
been the start of a change in soil C levels or it may have just been due to a buildup of
ligniﬁed C from the sawdust in the compost. If it was the beginning of a change in soil C
levels, it may be that the higher clay content of the soil helped contribute to this increase
by improving POM stability (Six et al., 2002a).

The cooler summers, cold winters, and short growing season may provide
challenges for growing crops at the UP location. However, compared to the KBS
location, it appears that this more northerly climate may reduce the GWP of similar
farming operations taking place further south. This reduction may not enough to offset
the higher GWP at the more southerly location however it helps provide additional
information for reducing the GWP of certain farming activities. The signiﬁcant effects of
additional carbon inputs from compost at the KBS location point to potential sources for

offsetting the negatives associated with the higher GWP of this site.

43

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APPENDICES

Table 27. Agronomic ﬁeld activities for KBS 2004.

 

Date Field Activity Treatment

4/14/04 Oats planted, Kura Clover killed (Trt. 9 & 10)

4/20/04 Gas sample # 1 (All)

4/27/04 Soil sample (All)

4/29/04 Compost applied (Trt. 1 & 9)

4/30/04 Corn planted (Trt. l & 2)

5/10/04 Rye harvested (Trt. l & 2)

5/18/04 Oats harvested (Trt. 9 & 10)

5/20/04 Sorghum planted (Trt. 9 & 10)

5/20/04 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 5, 6, 7 & 8)
5/24/04 Compost applied (Trt. 3, 5, & 7)

6/ 16/04 150 lbs/A N applied (28%) (Trt. 2)

6/21/04 Gas sample # 2 (All)

7/06/04 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 5, 6, 7 & 8)
7/29/04 Gas sample # 3 All)

8/02/04 Fertilize sorghum plots 75 lbs/A N applied (34%) (Trt. 9 & 10)

8/09/04 Gas sample # 4 (All)

8/13/04 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 5, 6, 7 & 8)
8/19/04 Sorghum harvested (Trt. 9 & 10)

8/19/04 Sorghum fertilized 75 lbs/A N applied (34%) (Trt. 9 & 10)

9/09/04 Corn harvested (Trt. l & 2)

9/ 16/04 Sorghum harvested (Trt. 9 & 10)

9/23/04 Gas sample # 5 (All)

9/30/04 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 5, 6, 7 & 8)

55

Table 28. Agronomic field activities for KBS 2003.

 

 

 

 

Date Field Activity Treatment
5/01/03 Gas sample # 1 (All)
5/14/03 Alfalfa, Alfalfa/Orchardgrass and Kura harvested (Trt. 3, 4, 7, 8, 9 & 10)
5/19/03 Rye harvested (Trt. l & 2)
5/22/03 Compost applied (Trt. 1, 3, 5, 7 & 9)
5/23/03 Alfalfa planted ' (Trt. 5 & 6)
5/27/03 Corn planted (Trt. l & 2)
6/03/03 Gas sample # 2 (All)
7/02/03 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 7 & 8)
7/l 7/03 Corn killed (1.5 oz Roundup/A) Sorghum planted (Trt. l & 2)
7/21/03 Poast and Baythroid applied to new alfalfa (Trt. 5 & 6)
7/31/03 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 7 & 8)
8/05/03 Gas sample # 3 (All)
8/28/03 Sorghum harvested (Trt. 1 & 2)
8/28/03 901bs/A N applied (34%) (Trt. l & 2)
9/1 “03 Sorghum harvested (Trt. l & 2)
9/12/03 90 lbs/A N applied (34%) (Trt. l & 2)
10/17/03 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 5, 6, 7 & 8)
10/23/03 Gas sample # 4 (All)
Table 29. Agronomic field activities for KBS 2002.
Date Field Activity Treatment
4/17/02 Field cultivator run over ﬁeld (North to South) (All)
4/23/02 Soil sampling (Rep. A & B)
4/24/02 Soil sampling (Rep. C & D)
4/30/02 Compost applied (9000 lbs/A) (Trt. 1, 3, 5, 7 .& 9)
5/03/02 0-0-60 (450 lbs/A) 0-46-0 (156 lbs/A) applied (Trt. l, 3, 5, 7 & 9)
5/03/02 0-0-60 (500 lbs/A) 0—46-0 (182 lbs/A) applied (Trt. 2, 4, 6, 8 & 10)
5/05/02 Coulter-mulcher run over Alfalfa and (Trt. 3, 4, 7 & 8)
Alfalfa/Orchardgrass plots
5/05/02 Alfalfa and Alfalfa/Orchardgrass planted (Trt. 3, 4, 7 & 8)
5/05/02 Corn planted (Trt. 1 & 2)
5/08/02 Corn planted (Trt. 5 & 6)
7/09/02 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 7 & 8)
7/14/02 Gas Sample # 1 (Rep. A, B & D)
8/05/02 Gas Sample # 2 (Rep. A, B & D)
8/14/02 Alfalfa and Alfalfa/Orchardgrass harvested (Trt. 3, 4, 7 & 8)
9/13/02 Corn harvested (Trt. l, 2, 5 & 6)
9/26/02 Winter-rye planted (Trt 1, 2, 5 & 6)
9/26/02 Gas sample # 3 (Rep. A, B & D)

56

Table 30. Agronomic ﬁeld activities for UP, 2004.

 

 

 

 

Date Field Activity Treatment

4/03/04 Soil sample (All)

4/04/04 Gas sample # l (was not analyzed) (All)

4/04/04 Manure applied (Trt. 1. 3. 5. 7 & 9)
5/ 17/04 Corn planted (Trt. 1 & 2)
6/07/04 Gas sample # 2 (All)

6/15/04 Alfalfa/Orchardgrass harvested (Trt. 7 & 8)
6/20/04 150 lbs/A N applied to com (28%) (Trt. 2)

6/28/04 Alfalfa harvested (Trt. 3, 4, 5 & 6)
6/30/04 Gas sample # 3 (All)

7/08/04 50 lbs/A N applied to oats (28%) (Trt. 10)

7/20/04 Oats harvested (Trt. 9 & 10)
7/27/04 Gas sample # 4 (All)

7/28/04 Alfalfa/Orchardgrass harvested (Trt. 7 & 8)
8/05/04 Alfalfa harvested (Trt. 3, 4, 5 & 6)
8/28/04 Gas sample # 5 (All)

9/28/04 Alfalfa harvested (Trt. 3 & 4)

10/1 l/04 Corn harvested (Trt. l & 2)
10/18/04 Gas sample # 6 (All)

Table 31. Agronomic ﬁeld activities for UP, 2003.

Date Field Activity Treatment

5/05/03 Soil sample # 1 (All)

5/06/03 Gas sample (All)

5/06/03 Manure applied (Trt. l, 3, 5, 7 & 9)
5/21/03 Corn planted (Trt. 1 & 2)
6/03/03 Alfalfa planted (Trt. 4 & 5)
6/23/03 Alfalfa, Alfalfa/Orchardgrass and Kura harvested (Trt. 3, 4, 7, 8, 9 & 10)
6/26/03 150 lbs/A N applied to com (28%) (Trt. 2)

7/08/03 Gas sample # 2 (All)

7/28/03 Gas sample # 3 (All)

8/06/03 Alfalfa, Alfalfa/Orchardgrass and Kura harvested (Trt. 3, 4, 7, 8, 9 & 10)
8/15/03 Gas sample # 4 (All)

9/05/03 Gas sample # 5 (All)

9/25/03 Corn harvest (Trt. 1 & 2)
lO/04/03 Gas sample # 6 (All)

57

Table 32. Agronomic ﬁeld activities for UP, 2002.

 

Date Field Activity Treatment

5/14/02 Soil sample (Rep. A)

5/15/02 Soil sample (Rep. B & C)
5/16/02 Soil sample (Rep. D)

5/20/02 Manure applied (10,000 gal/A) (Trt. l, 3, S, 7 & 9)
6/04/02 Plant Corn, Alfalfa, Alfalfa/Orchardgrass and Kura (All)

7/19/02 Alfalfa, Alfalfa/Orchardgrass and Kura harvested (Trt. 3, 4, 7, 8, 9 & 10)
7/20/02 Gas sample (Rep. A, C & D)
8/23/02 Gas sample (Rep A, C & D)
9/23/02 Corn harvest (Trt. 1, 2, 5 & 6)
9/24/02 Winter-rye planted (Trt. 1, 2, 5 & 6)

Table 33. Organic matter treatment characteristics.

 

 

 

 

 

 

 

Compost (KBS) Manure (UP)
Application Rate 35,858 kg ha" 84,200 L ha"
DM 47% 8%
C:N 5.22 13.34
Total C 18.8% 13.3%
Total N 3.6% 3.8%
N Applied (Available) 45 kg ha'I 180 kg ha'l
P Applied 42 kg ha" 180 kg ha"
K Applied 498 kg ha" 115 kg ha"
C Applied 3168 kg ha" 3476 kg ha"
Table 34. Soil bulk density at start and end of study
2002 g cm'2 2004 g cm‘2
KBS 0-5 cm 1.248 1.331
5—25 cm 1.355 1.499
UP 0.5 cm 1.195 1.240
5-25 cm 1.101 1.246

 

 

 

 

Table 35. Soil total N at start and end of study

 

 

 

 

 

 

 

2002 g N or2 2004 g N or2
0-5 cm 70.14 91.86
KBS 5-25 cm 279.57 333.39
up 0-5 cm 119.49 128.22
5.25 cm 351.69 411.61

 

 

58

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ﬂuxes in danish forest-, grassland-, and agroecosystems. Journal of Environmental
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Anderson, R.V., W.D. Gould, L.E. Woods, C. Cambardella, R.E. Ingham, and DC.
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Antle, J .M., S.M. Capalbo, S. Mooney, E.T. Elliott, and RH. Paustian. 2001. Economic
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Bakhsh, A., R.S. Kanwar, D.L. Karlen, C.A. Cambardella, T.S. Colvin, T.B. Moorman,
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Baldock, J .A., J .M. Oades, P.N. Nelson, T.M. Skene, A. Golchin, and P. Clarke. 1997.
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Balesdent, J ., A. Mariotti, and D. Boisgontier. 1990. Effect of Tillage on Soil Organic-

Carbon Mineralization Estimated from C-l3 Abundance in Maize Fields. Journal of Soil
Science 41:587-596.

Ball, B.C., G.W. Horgan, H. Clayton, and J .P. Parker. 1997. Atmospheric pollutants and
trace gases: Spatial variability of nitrous oxide ﬂuxes and controlling soil and
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Bamwell, T.O., R.B. Jackson, E.T. Elliott, l.C. Burke, C.V. Cole, K. Paustian, E.A. Paul,
A.S. Donigian, A.S. Patwardhan, A. Rowell, and K. Weinrich. 1992. An Approach to

Assessment of Management Impacts on Agricultural Soil Carbon. Water Air and Soil
Pollution 64:423-435.

Bird, 8.8., J .E. Herrick, M.M. Wander, and SF. Wright. 2002. Spatial heterogeneity of
aggregate stability and soil carbon in semi-arid rangeland. Environmental Pollution
1 16:445-455.

Bolinder, M.A., D.A. Angers, M. Giroux, and MR. Laverdiere. 1999. Estimating C
inputs retained as soil organic matter from corn (Zea Mays L.). Plant and Soil 215:85-91.

59

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