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Research Paper Future of Food: Journal on Food, Agriculture and Society
4 (3) Winter 2016
Potential mitigation of midwest grass-nished beef
production emissions with soil carbon sequestration in the
United States of America
Jason E. RowntREE*1, REbEcca Ryals2, MaRcia s. DElongE3, w. RichaRD tEaguE, MaRilia b. chiavEgato, PEtER byck6,7,
tong wang8 & sutiE Xu1
1 Department of Animal Science, Michigan State University
2 Department of Natural Resources and Environmental Management, University of Hawaii
3 Union of Concerned Scientists, Washington, DC
4 Department of Ecosystem Science and Management, Texas A & M University
5 Departmental de Zootecnia, Universida de de São Paulo
6 School of Sustainability, Arizona State University
7 Walter Cronkite School of Journalism and Mass Communications, Arizona State University
8 Department of Economics, South Dakota State University
* Corresponding author: rowntre1@msu.edu | Tel.: +1-517-974-9539
Data of the article
First received : 30 March 2016 | Last revision received : 28 November 2016
Accepted : 05 December 2016 | Published online : 23 December 2016
URN: nbn:de:hebis:34-2016111451469
Key words
Grass-nishing beef, GHG
emissions, Soil organic
carbon sequestration
Abstract
Beef production can be environmentally detrimental due in large part to associated enteric
methane (CH4) production, which contributes to climate change. However, beef production in
well-managed grazing systems can aid in soil carbon sequestration (SCS), which is often ignored
when assessing beef production impacts on climate change. To estimate the carbon footprint
and climate change mitigation potential of upper Midwest grass-finished beef production sys-
tems, we conducted a partial life cycle assessment (LCA) comparing two grazing management
strategies: 1) a non-irrigated, lightly-stocked (1.0 AU/ha), high-density (100,000 kg LW/ha) system
(MOB) and 2) an irrigated, heavily-stocked (2.5 AU/ha), low-density (30,000 kg LW/ha) system
(IRG). In each system, April-born steers were weaned in November, winter-backgrounded for 6
months and grazed until their endpoint the following November, with average slaughter age of
19 months and a 295 kg hot carcass weight. As the basis for the LCA, we used two years of data
from Lake City Research Center, Lake City, MI. We included greenhouse gas (GHG) emissions as-
sociated with enteric CH4, soil N2O and CH4 fluxes, alfalfa and mineral supplementation, and farm
energy use. We also generated results from the LCA using the enteric emissions equations of the
Intergovernmental Panel on Climate Change (IPCC). We evaluated a range of potential rates of
soil carbon (C) loss or gain of up to 3 Mg C ha-1 yr-1. Enteric CH4 had the largest impact on total
emissions, but this varied by grazing system. Enteric CH4 composed 62 and 66% of emissions for
IRG and MOB, respectively, on a land basis. Both MOB and IRG were net GHG sources when SCS
was not considered. Our partial LCA indicated that when SCS potential was included, each graz-
ing strategy could be an overall sink. Sensitivity analyses indicated that soil in the MOB and IRG
systems would need to sequester 1 and 2 Mg C ha-1 yr-1 for a net zero GHG footprint, respectively.
IPCC model estimates for enteric CH4 were similar to field estimates for the MOB system, but
were higher for the IRG system, suggesting that 0.62 Mg C ha-1 yr-1 greater SCS would be needed
to offset the animal emissions in this case.
Citation (APA):
Rowntree, J. E., Ryals, R., DeLonge, M.S., Teague, W.R., Chiavegato, M.B., Byck, P., Wang,T., Xu, S. (2016). Potential mitigation of midwest grass-nished
beef production emissions with soil carbon sequestration in the United States of America.
Future of Food: Journal on Food, Agriculture and Socie-
ty
, 4(3), 31 -38.
31
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32 UniKassel & VDW, Germany- December 2016
Future of Food: Journal on Food, Agriculture
and Society, 4 (3)
Introduction
There is a growing concern about beef production’s
impact on the environment, including contributions to
climate change. However, beef production systems are
variable, ranging broadly from intensive confined feed-
lots to diverse grazing systems. As a result, these sys-
tems contribute differently to climate change through
mechanisms such as animal impacts, off-farm inputs,
and land management. Identifying opportunities to re-
duce climate impacts requires a systematic approach
that considers the larger agroecosystem. This need for
a systems approach has become increasingly urgent,
particularly in light of the fact that one outcome of the
United Nations Conference on Climate Change (COP21)
was a call for greater adoption of regenerative agricul-
tural practices. Specifically, this call includes the “4/1000
Initiative: Soils for Food Security and Climate” and the
Life Beef Carbon Initiative, which recommends greater
adoption of grazing systems that sequester C and re-
duce net GHG emissions from beef production.
Life cycle assessments (LCAs) are important tools that
have been applied to evaluate the costs and benefits of
beef production systems with respect to the environ-
ment and climate change. While LCAs can be insightful,
the outputs are highly sensitive to the methodologies
and boundaries used to develop the analysis. Many ex-
isting beef LCAs have concluded that grazing systems
have a bigger climate footprint than more intensive,
confined systems due to reduced meat yield per unit
land and increased enteric methane (CH4) associated
with greater ruminal fiber digestion (Eshel, Shepon, Ma-
kov, & Milo, 2014; Ripple et al., 2014; Capper, 2012). How-
ever, these assessments have generally not accounted
for the important influence that land management and
soil dynamics can have on the outcome.
Soil is an important pool of C that is sensitive to land
management and can cumulatively have a significant
impact on climate change. Recently, Teague et al. (2016)
indicated agriculturally induced global soil erosion esti-
mates at 1.86 Gt C yr-1, resulting in an annual 0.5 ppm
atmospheric CO2 increase. Because soils can be either a
source or sink of C depending on management practic-
es, soil C is a potentially important component of beef
LCAs (Teague et al., 2016). Soil C has often been unac-
counted for in LCAs (Stackhouse-Lawson, Rotz, Oltjen, &
Mitloehner, 2012; Capper & Bauman, 2013), but has been
found to have a large impact on net GHG footprints
when explicitly included (Liebig, Gross, Kronberg, & Phil-
lips, 2010; Wang, Teague, Park, & Bevers, 2015) or at least
considered (Pelletier, Pirog, & Rasmussen, 2010; Lupo,
Clay, Benning, & Stone, 2013). The availability of experi-
mental data on soil C and GHG effects of grazing systems
has been an obstacle in filling this critical gap in LCAs.
The purpose of this study is to develop a data-driven
partial LCA of upper Midwest grass-finishing beef pro-
duction systems. Our LCA explicitly considers soil C and
GHG dynamics and uses data from localized field exper-
iments. We employ a simple sensitivity analysis to eval-
uate the potential for soil carbon sequestration (SCS) to
offset emissions within grass-finished beef production
systems.
Materials and Methods
LCA components and boundaries
An LCA was constructed to determine net GHG impacts
of two different grazing management practices for beef
production in the upper Midwest, USA. Components of
Figure 1 : Grass-Finishing beef production phase
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Future of Food: Journal on Food, Agriculture
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the LCA include direct and indirect GHG emissions asso-
ciated with the grassland ecosystem, enteric emissions
from cattle, feed production and transportation, and on-
farm energy use. The model boundary was restricted to
the grass-finishing portion of the beef production cycle,
beginning at the time of weaning and ending at slaugh-
ter (Figure 1).
The model quantified the impacts of grazing manage-
ment practices on the net greenhouse gas emissions
(GHGnet) as:
GHGnet = GHGecosystem + GHGfeed + GHGenergy - GHGseq
where GHGecosystem represents biological greenhouse
gas emissions generated on the pasture. This parameter
includes enteric CH emissions from steers (> 1 year old)
and the difference in soil nitrous oxide (N2O) and CH4
emissions relative to an ungrazed control pasture. Emis-
sions associated with the mining, production, and trans-
portation of supplemental feed and minerals are repre-
sented as GHGfeed. Emissions generated from the use of
fossil fuels for on-farm technologies (i.e., irrigation) are
represented as GHGenergy. The change in soil carbon
is shown as GHGseq, where a positive value represents
sequestration (i.e., a sink). All model components are
expressed as GHG fluxes in CO2-equivalents using 100-
year global warming potentials (Intergovernmental Pan-
el on Climate Change, 2006). Positive values represent
a source of GHGs to the atmosphere, whereas negative
values represent a GHG sink. Metrics for comparison of
GHG impacts due to grazing practices were expressed
on a per steer and per area basis.
Study system
Data used for the LCA was derived from two years of on-
farm experiments conducted at the Lake City Research
Center in Lake City, Michigan. The experiments were
composed of grass-finishing beef production systems
that compared two different grazing management strat-
egies. The approaches were: 1) MOB: a non-irrigated,
high-density grazing system stocked at 1.0 animal units
(AU) ha-1 (100,000 kg live weight (LW) ha-1 d-1) and 2) IRG:
an irrigated, low-density grazing system stocked at 2.5
AU ha-1 (30,000 kg LW ha-1 d-1). An AU is considered
one 454 kg cow with or without calf. We define stocking
rate as the number of AUs assigned to the land base for
a given year, while stock density refers to the kg LW/ha
of animal weight assigned to a land base for 1 day. While
our LCA was driven by data specific to the Upper Mid-
west, the management characteristics of the IRG system
are similar to many grazing dairies and beef systems in
New Zealand, parts of Europe, Australia and the United
States. The IRG system is characterized by aggressive
plant defoliation with short (21-45 day) recoveries to
promote a highly vegetative sward. In contrast, MOB is
a grazing system characterized by high stock densities
with a lower stocking rate. The MOB system allows for
longer (> 60 day) plant recovery periods. As a result,
forage is typically more mature when compared to IRG
and has a higher fiber content when compared to other
rotational systems (Chiavegato, Powers, Carmichael, &
Rowntree, 2015b). In each grazing strategy, steers were
born in April, weaned in November, backgrounded on
high quality hay for 6 months, and grazed on pasture
until slaughter the following November, with an average
age at slaughter of 19 months and a 295 kg hot carcass
weight (HCW). Our life cycle model focuses on the peri-
od from weaning to slaughter (Figure 1).
Ecosystem greenhouse gas emissions
Ecosystem GHG emissions included enteric CH and
soil NO and CH fluxes measured at the experimental
site from 2012-13 (Chiavegato, Rowntree, Carmichael, &
Powers, 2015a, Chiavegato et al., 2015b). Emissions were
measured in spring (April/May; Period 1) and late sum-
mer (August/Sept; Period 2) for 2 years. These time pe-
riods were considered to be representative of seasonal
fluxes and were scaled by the numbers of days in each
season. For the base case scenario, soil emissions during
winter months are assumed to be negligible.
Enteric emissions were derived from on-site data from
cow-calf pairs with a mean weight of 555 kg (SE= 20 kg)
using a standard SF tracer gas technique (Johnson, Huy-
ler, Westberg, Lamb, & Zimmerman, 1994). Sampling was
conducted twice daily over 7 days in Periods 1 and 2 in
2012 and 2013. During each sampling period, cattle were
also dosed with chromic oxide to determine dry matter
intake (DMI). There was no management effect on DMI
as cows consumed 2.6 and 2.8% of their body weight
daily during the collection periods for MOB and IRG, re-
spectively. There were no differences between years or
treatments for enteric CH, with emissions ranging from
195 to 249 g CH4 d-1. We used a metabolic body weight
conversion of 0.85 to convert emissions from a mature
cow (555 kg) to a growing steer (454 kg). For both sys-
tems, we estimated winter CH emissions to be 120 g L-1
d-1 on high quality hay, based Stewart et al. (2014). We
also compared our data to enteric CH calculations using
the Tier 1 Methodology of the Intergovernmental Panel
on Climate Change (IPCC):
DayEmit = [GEI XYm ] / [55.65 MJ/kg CH]
where:
DayEmit = emission factor (kg CH head-1 day-1)
GEI = gross energy intake (MJ head-1 day-1)
Ym = CH4 conversion rate, which is the fraction of gross
Eq. 1
Eq. 2
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energy in
feed converted to CH (%)
To complete the IPCC equation, site-specific mean GEI
forage values (Chiavegato et al., 2015a) and the recom-
mended Ym of 6.5% (Mangino, Peterson, & Jacobs, 2003)
were used.
Soil GHG emissions data used for the base case scenario
is detailed in Chiavegato et al. (2015b). Briefly, soil N2O
and CH₄ emissions were measured via the static flux
chamber method and analyzed by gas chromatography.
A 14 day post-graze collection period in both periods in
2012 and 2013 was used.
Greenhouse gas emissions from protein and mineral sup-
plements
The grazed pastures and supplemented feed were pri-
marily alfalfa (Medicago sativa L.). For the supplemental
feed GHG assessment, we used the Farm Energy Analysis
Tool (FEAT ) (Camargo et al., 2013). Assumptions involved
in FEAT indicate a three-year lifespan for the alfalfa, with
an energy use of 9000 MJ input ha-1 y-1 and energy pro-
duction efficiency of 25 MJ output per MJ input (Camar-
go, Ryan, & Richard, 2013). No differences in supplement
consumption were used between the different grazing
systems. The on-farm supplemental feed consumption
per animal for the production cycle was 2044 kg. Half
of the alfalfa was produced on site, while the other half
was brought on farm from an average distance of 24 km.
In each case, a yield of 7490 kg ha-1 y-1 was used based
on USDA harvest estimates (USDA, 2015). All associated
transportation GHG emissions were estimated using die-
sel heavy-duty truck data from the EPA (2008).
Mineral supplement calculations were based on a dai-
ly intake of 77 g head-1 across each grazing treatment
(Buskirk, 2002). Mineral associated emissions were esti-
mated based on Lupo, Clay, Benning, and Stone (2013).
This involves the mining and processing components of
NaCl, CaCO and CaHPO production, along with trans-
port and delivery to the farm.
On-farm energy use
Any associated energy used for alfalfa production and
subsequent feeding is accounted for in the feed compo-
nent. Supplemental irrigation was used in IRG (K-Line Ir-
rigation, St. Joseph, MI) with a goal of providing 2.54 cm
water ha-1 wk-1. The estimated annual usage of irrigation
electricity was 7452 kW yr-1. EPA (2014) emission factors
were used to determine emissions associated with elec-
tricity use.
Soil carbon sequestration
To account for soil C change in each system, we consid-
ered a C-response gradient ranging from -3 Mg C ha-1 yr-1
to 3 Mg C ha-1 yr-1. Grazing lands have the potential to act
as C sinks, but reported rates of SCS due to grazing sys-
tem management vary considerably based on climate,
biome, time of observation, and site-specific conditions.
A review of 81 ranch sites reported SCS rates ranging
from 0.11 to 3.04 Mg C ha-1 yr-1 (Conant, Paustian, & Elli-
ott, 2001). More recent attention to emerging intensive
rotational grazing practices has indicated even greater
potential SCS rates. Teague et al. (2011) reported annual
sequestration rates of 3 Mg C ha-1 yr-1 in a 10 year chron-
osequence study in Texas comparing stocking rate and
grazing management influence on beef production and
ecosystems services. Machmuller et al. (2015) observed
SCS of 8.0 Mg C ha-1 yr-1 in a 7 year chronosequence of
irrigated management-intensive grazing in the south-
eastern USA. Thus, the relatively wide range of SCS rates
used for this LCA provides an opportunity to incorporate
soil C dynamics and uncertainties.
Results and Discussion
LCA results of MOB and IRG systems on a kg CO2-eq ha-1
production cycle and animal basis derived from Eq.1 are
indicated in Figure 2. The MOB system had lower emis-
sions on a land basis when compared to the IRG system
(3.3 vs. 7.1 Mg CO-eq ha-1) due to lower stocking rates.
The IRG farm energy use was 1064 kg CO-eq ha-1 due to
the electricity used for irrigation, compared to no energy
use for the MOB system. For both systems, enteric CH
was the largest contributor to overall emissions, ranging
from 62 to 66% for the IRG and MOB systems, respective-
ly. This finding is lower than results found by Pelletier,
Pirog, & Rasmussen (2010), who estimated enteric CH
emissions to make up 79% of total GHG emissions from
a grass-finishing system.
Enteric emissions ranged from 142 to 268 g CH d-1 (Chi-
avegato et al., 2015a). These results are similar to those
reported by DeRamus, Clement, Giampola, and Dicki-
son (2003), who indicated yearling heifers, first calf heif-
ers and mature cows ranged from emitting 120 to 255
g CH d-1. Similarly, Pavao-Zuckerman, Waller, Ingle, and
Fribourg (1999) reported a range of 150 to 240 g CH d-1.
However, these data fall slightly lower than estimates by
McCaughey, Wittenberg, and Corrigan et al. (1999) and
Pinares-Patiño, Baumont, and Martin (2003), who found
ranges in emissions from 173 to 273 g CH d-1. The lower
stocking rate in MOB also resulted in lower enteric CH4
emissions compared to IRG (2165 vs. 4430 kg CO-eq ha-
1) on a land area basis. However, on a per steer basis, IRG
enteric emissions were 393 kg CO-eq steer-1 less than
MOB. The grazing effect on enteric CH emissions may
be explained by the observed increase in forage crude
protein and reduction in fiber content for IRG compared
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Future of Food: Journal on Food, Agriculture
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to MOB (Chiavetago et al., 2015a).
The beef production systems used to calculate this LCA
represent improved grazing management as compared
to continuous set stocking strategies, which have been
shown to reduce plant diversity and productivity due to
overgrazing of preferred plants and patches (Murphy,
1998; Gerrish, 2004; Teague, Provenza, Kreuter, Steffens,
& Barnes, 2013). The lower enteric CH emissions in the
observations reported here might be due to the relative-
ly high plant diversity we observed in the well-managed
systems. Both systems included multiple daily to weekly
moves to new pasture, allowing for greater forage resid-
ual biomass and longer recovery periods, feeding back
to the ecosystem by increasing the plant diversity and
forage quality (Chiavegato et al., 2015a). Conceptually,
this agrees with Bannink et al. (2010), who indicated that
forage quality is a primary driver in relative daily enteric
emissions.
Enteric CH emissions were also assessed using Tier 1
IPCC daily enteric emission predictive equations (Eq.1)
(IPCC, 2006), as it is a commonly used methodology
when site- or regionally-specific data are lacking. There
was very little difference between the MOB GHG foot-
print calculated using our field observations compared
to the IPCC approach (3.3 vs 3.5 Mg CO-eq yr-1, respec-
tively) (Figures 2 & 3). However, when evaluating the
IRG system, the IPCC approach generated a greater en-
teric CH4 value and concurrently a larger footprint on a
land and steer basis by 34%. In a review of measured and
simulated enteric emission rates, Stackhouse et al. (2012)
indicated the IPCC overestimated emissions by 16.4% on
average, with a differential range of -0.01 to 55%.
___________Net GHG (Mg C ha-1 yr-1)__________
On-farm IPCC
Soil C Emission MOB IRG MOB IRG
(Mg C ha-1 yr-1)
-3 -2.11 -1.07 -2.05 -0.45
0 0.89 1.93 0.95 2.55
3 3.89 4.93 3.95 5.55
Figure 2 : Life cycle assessment of on-farm data estimated with metabolic body weight
Table 1: Impact of soil C emission gradient on net GHG in two man-
agement systems
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Future of Food: Journal on Food, Agriculture
and Society, 4 (3)
Table 1 denotes overall C footprint balance (in CO2-eq)
based on a plausible gradient of soil C flux, representing
soil C loss or gain ranging from ±3 Mg C ha-1 yr-1. Assum-
ing a sequestration rate of 3 Mg C ha-1 yr-1, all systems
and methods indicate an overall GHG sink ranging from
2.11 to 1.07 (MOB) and 2.0 and 0.45 Mg C ha-1 yr-1 (IRG),
representing on-farm and IPCC calculations, respective-
ly. A soil C flux gradient allows for a greater understand-
ing of soil C influence on the overall environmental foot-
print. As Stackhouse et al. (2012) indicated, LCA’s often
consider soil C to be in dynamic equilibrium. However,
empirical data suggest otherwise (e.g. Machmuller et al.,
2015; Teague et al., 2011). Recent studies such as Ripple
et al. (2014) and Eshel et al. (2014) have reported the
emissions from ruminants in food production without
accounting for the beneficial ecosystem services that
well-managed grazing systems can provide. In our study,
we used 3 Mg C ha-1 yr-1 as a potential C sequestration
figure, which is relatively high (Conant et al., 2001) but
viable based on existing studies (Teague et al., 2011; Del-
gado et al., 2011; Machmuller et al., 2015; Teague et al.,
2016). Importantly, the results presented here suggest
that with appropriately managed grazing, a grass-fin-
ished beef model can not only contribute to food pro-
visioning but also be ecologically regenerative as well.
Conclusions
The recent call for improved management of grazing
systems as part of an international climate change miti-
gation strategy is critical, particularly in light of many ex-
isting beef LCAs that have concluded that beef cattle pro-
duced in grazing systems are a particularly large sources
of GHG emissions. To identify the best opportunities to
reduce GHG emissions from beef production, a systems
approach that considers the potential to increase soil C
and reduce ecosystem-level GHG emissions is essential.
Using a combination of on-farm collected data, litera-
ture values, and IPCC Tier 1 methodology, we generat-
ed an LCA that indicates highly-managed grass-finished
beef systems in the Upper Midwestern United States can
mitigate GHG emissions through SCS while contribut-
ing to food provisioning at stocking rates as high as 2.5
AU ha-1. From this data, we conclude that well-managed
grazing and grass-finishing systems in environmentally
appropriate settings can positively contribute to reduc-
ing the carbon footprint of beef cattle, while lowering
overall atmospheric CO concentrations.
Acknowledgements
The authors express their thanks to the Michigan Animal
Agriculture Alliance and Thornburg Foundation for par-
tial support of this project. Moreover, the authors would
like to thank the anonymous reviewers.
Conict of Interests
The authors hereby declare that there are no conflicts of
interest.
Figure 3 : Life cycle assessment of IPCC data to estimate enteric methane emissions
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Future of Food: Journal on Food, Agriculture
and Society, 4 (3)
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