Journal of
agricuktural science
www.pnas.org/cgi/doi/10.1073/pnas.0912890107
PNAS |
November 16, 2010 | vol. 107
| no. 46 |
19671
POTENTIAL FOR
REDUCED METHANE AND CARBON DIOXIDE EMISSIONS FROM LIVESTOCK AND PASTURE
MANAGEMENT IN THE TROPICS
Philip K. Thorntona,b,1 and Mario Herrerob
aConsultative
Group on International Agricultural Research/Earth System Science Partnership
Challenge Program on Climate Change, Agriculture & Food Security,
University of Copenhagen, DK-1958 Frederiksberg, Denmark; and bInternational
Livestock Research Institute, Nairobi 00100, Kenya
Edited by Ruth S.
DeFries, Columbia University, New York, NY, and approved July 30, 2010
(received for review November 10, 2009)
Upload by I Made Adi Sudarma, Animal
Science Programs, Post Graduate Program of Nusa Cendana University, Kupang, November
28, 2012.
abstract
We estimate
the potential reductions
in methane and
carbon dioxide emissions from several livestock and pasture management options
in the mixed and rangeland-based production systems in the tropics.
The impacts of
adoption of improved
pastures, intensifying ruminant
diets, changes in
land-use practices, and changing breeds of large ruminants on the
production of methane and carbon dioxide
are calculated for
two levels of
adoption: complete adoption, to estimate the upper limit to reductions
in these greenhouse gases
(GHGs), and optimistic
but plausible adoption rates
taken from the literature, where these exist. Results are expressed both in GHG
per ton of livestock product and in Gt CO 2 -eq. We estimate that the maximum
mitigation potential of these options in the land-based livestock systems in
the tropics amounts to approximately 7% of the global agricultural mitigation potential
to 2030. Using historical adoption rates from the literature, the plausible
mitigation potential of these options could contribute approximately 4% of
global agricultural GHG mitigation. This could be worth on the order of $1.3
billion per year at a price of $20 per t CO 2 -eq. The household-level and
sociocultural impacts of some of these options warrant further study, however,
because livestock have multiple roles in tropical systems that often go far beyond
their productive utility.
bovines | intensi fi cation |
mitigation | systems
At the same time, climate change
will have significant negative impacts on livestock production systems (3, 4),
particularly in the drier rangeland systems of the tropics. However, livestock
are also a large contributor to the climate change problem (5). By some estimates
they contribute 18% of global anthropogenic greenhouse gas (GHG) emissions (1).
The main sources and types of greenhouse
gases from livestock
systems are carbon
dioxide (CO 2 ) from land
use and its changes (feed
production, deforestation), which
accounts for 32% of emissions from livestock; nitrous oxide (N 2 O) from manure
and slurry management, which accounts for 31%; and methane (CH 4 ) production
from ruminants, which accounts for 25% of emissions.
Livestock systems will need to
adapt in the future, requiring signi fi cant changes in production technology
and farming methods in places,
which could affect productivity
as well as development
goals (6). Agriculture and livestock in particular are likely to be required to
play a much greater role than they have hitherto in reducing GHG emissions.
Livestock keepers could mitigate some of these in various ways (7). Here we
carry out analysis that attempts to quantify the extent to which several
different options could mitigate GHGs from bovines in the mixed and rangeland-based
livestock systems in the tropics. We concentrate on grazing systems and on the
biophysical impacts and limits of some known mitigation options that people
believe could work. The focus is on the mitigation of CO 2 and CH 4 . The role
of N 2 O emissions from certain grazing systems is currently undergoing reevaluation
(8).
RESULTS
We estimated the impacts of adoption
of improved pastures, intensifying
ruminant diets, changes
in land-use practices,
and changing breeds of ruminants on the production of CH 4 and CO 2 for
two levels of adoption: complete adoption, to estimate the upper limit
to GHG reductions,
and optimistic but
plausible adoption rates taken
from the literature,
where these exist. Results for the six options summarized
in Table 1 are shown in Table 2, in terms of the amount of CH 4 produced per
ton of milk and meat, and the number of bovines needed to satisfy milk and meat
demand in 2030 for the region and systems shown (i.e., it is assumed that
demand for these livestock products is satisfied from within each system in
each region). Methane production was calculated
separately for milk and meat, with due regard to the estimated proportions of
dual-purpose animals in each system and
by splitting the
herd into milk-producing animals
(adult females) and meat-producing animals (males and replacement females)
(SI Text). Results also are shown for the amount of CO 2 equivalent (CO 2 -eq)
mitigated in relation to the three pathways considered, where these come into
play for the different options: a reduction in livestock numbers associated
with diet improvement, the carbon sequestered via restoration of degraded range
lands, and the extra carbon sequestered as a result of land-use change,
expressed as Mt CO 2 -eq. Results for all options except 3a are shown for two
levels of adoption: for 100% adoption rates in the systems and regions
considered for each option, to de fi ne the upper limit of mitigation
potential; and for an optimistic but plausible adoption rate taken from the
literature, where possible.
Table 1. Mitigation options evaluated
No.
|
Option
|
Region
|
System
|
Gas affected
|
Changes
evaluated
|
1
|
Adoption of
improved
pastures
|
CSA
|
LGH
|
CH 4 , CO 2
|
Cerrado
vegetation to Brachiaria spp. pasture: digestibility increase, impacts on
animal productivity
Carbon
sequestration (9)
Restoration of
degraded soils (10)
Area adopted:
best case from Central America, 1990–2003, 1.3% per year (30% to 2030);
average of fi ve countries, 0.6% per year (11)
|
2
|
Diet intensi fi
cation
(a) Stover
digestibility
improvement
|
SSA, SA
|
MRA, MRH,
MRT, MIA,
MIH, MIT
|
CH 4
|
Stover
digestibility increase by 10%, impacts on animal productivity
Adoption rate:
43%, maximum observed for genetically improved dual-purpose cowpea in West
Africa (12); generally much lower rates (<10%) are observed or expected
(13); 23% to 2030 used here (1% per year)
|
(b) Grain
supplements
|
SSA, SA
|
MRH, MRT,
MIH, MIT
|
CH 4
|
Grain
supplement: increase from 0.5 to 2.0 kg per head per day, impacts on animal
productivity
Adoption rate:
23% to 2030 assumed (1% per year). In the absence of data, similar adoption
rates to agroforestry-based supplements may be plausible
|
|
3
|
Land use
(a) Carbon
sequestration
in rangelands
|
CSA, SSA
|
LGA, LGH,
LGT
|
CO 2 (CH 4 )
|
Changed carbon
sequestration rates (10)
(Methane
production at intermediate stocking rates: not evaluated here)
Complete
adoption
|
(b) Increasing
agroforestry
practices
|
CSA, SSA,
SA, SEA
|
MRH, MRT
|
CH 4 , CO 2
|
Leucaena spp
supplement of leaves, animal performance:
Adoption rate:
1% per year, 23% to 2030 assumed, plausible for the best case (14)
Carbon
sequestration per ha: average lower limit for different tropical agroforestry
systems (15)
|
|
4
|
Changing breeds
of
large ruminants
|
CSA, SSA,
SA, SEA
|
LG (meat), MRH,
MRT, MIH,
MIT (dairy)
|
CH 4
|
Local to a
cross-bred animal: animal productivity, meat in the LG systems and milk in
the MRH/T and MIH/T systems
Adoption rate:
29% to 2030 assumed, based on Kenya’s adoption of crossbred dairy animals,
the best case in East and Southern Africa (16)
|
CSA, tropical
Central and South America; SA, South Asia; SEA, Southeast Asia; SSA,
Sub-Saharan Africa; LG, rangeland-based systems; MI, mixed crop-livestock irrigated
systems; MR, mixed crop-livestock rainfed systems; A, arid-semiarid systems
(including hyper-arid); H, humid-subhumid systems; T, tropical highland
systems.
Adoption
of Improved Pastures in Latin America. Differences in CH 4 production per ton
of milk between the natural cerrado vegetation and improved pastures can be large,
but these depend on the level of adoption of improved pasture varieties.
Although CH 4 production per animal (expressed as one tropical livestock unit, equivalent
to a body weight of 250 kg) consuming Brachiaria pastures compared with natural
grasslands is higher (38.7 compared with 31.2 kg CH 4 per year), milk
production and liveweight gain per animal per day are three times higher (see
Materials and Methods and SI Text ). This results in a significant reduction in
CH 4 production per unit of milk and meat produced and in total CH 4 produced.
The number of animals required to satisfy demand is reduced under the improved
pastures option, thus reducing pressure on natural resources. Adoption of
improved deep-rooted pastures such as Brachiaria spp. has the additional
advantage of sequestering 29.5 t per ha more carbon than natural rangeland vegetation
(9). The direct and indirect impacts of this strategy and a plausible adoption
rate (30%) represent mitigation of 29.8 Mt CO 2 -eq; diet improvement and reduction
of animal numbers account for 7% of the mitigation potential. This option could
result in the use of less land as well as fewer animals to satisfy demand. This
could translate into more CO 2 savings from deforestation avoided, although we
have not included that effect here.
Diet
Intensification Options. Diet improvements through increases in the quality
of the basal diet or through supplementation are common strategies to intensify
the diets of ruminants. In mixed systems in the developing world, stover from
crops is widely used as a feed resource and can represent up to 50% of the diet
of ruminants (17). Stover from different varieties of the same crop species has
a wide range of digestibilities, and these differences are exploited by crop
breeders to create dual-purpose crops with higher quality residues. The two
strategies tested here (options 2a and 2b) operate under similar principles as
with the improvements of the diet through adoption of Brachiaria pastures.
Better-quality diets reduce the CH 4 output per unit of product and therefore
can reach a target quantity of animal product at lower CH 4 emissions and usually
with fewer animals. Improving the digestibility of crop residues produces less
milk (3.6 compared with 4.9 kg milk per day) and more CH 4 (33.0 compared with
31.7 kg CH 4 per year; SI Text) than supplementing the same basal diet with
grain concentrates. However, both produce more milk, meat, and CH 4 than the
control diet and can offset CH 4 production by a significant reduction in the numbers
of animals to satisfy meat and milk demand. The total mitigation potential of
crop residue digestibility improvements is higher than grain supplementation
owing to its broader recommendation domain. This option is widely applicable
across most rain-fed and irrigated mixed systems where large concentrations of animals
exist and numbers are projected to increase. Therefore, significant reductions
in the numbers of animals to meet demand can occur, whereas feeding grain
concentrates is an option that is most appropriate to the humid and temperate
mixed systems.
Land
Use Options.
We tested two options commonly believed to have a high mitigation potential:
carbon sequestration through restoration of degraded rangelands in tropical
Central and South America (CSA) and sub-Saharan Africa (SSA), and the use of agroforestry
practices in mixed crop–livestock systems in humid and tropical highland areas of the developing world. Despite lower potential rates of
carbon sequestration in SSA rangelands than in CSA (190 compared with 691 kg C
per ha per year) (10), a higher proportion of degraded lands and a greater
rangeland extent lead to a higher (almost double) mitigation potential for SSA
rangelands than in CSA.
Agroforestry practices
have dual mitigation
benefits. Agroforestry species
usually have a high nutritive value and can help to intensify
diets of ruminants
while they can
also sequester carbon. In this
example, replacing some concentrates and part of the basal diet with leaves of
Leucaena leucocephala also intensifies
diets so that
animal numbers can
be reduced to
meet livestock product demand. Approximately 28% of the plausible mitigation
potential of 32.9 Mt CO 2 -eq for this option comes from the reduction in
livestock numbers possible, compared with 72% contributed from the carbon
sequestration effects.
Table 2. Mitigation potentials for the options shown
in Table 1
No.
|
Option
|
CH 4
production
(kg) per t of
|
No. of bovines
(×10 6 )
needed to
satisfy demand
in 2030 for
|
Mitigation of
CH 4 via
reduction
in bovine nos.
(Mt CO 2 -eq)
|
C sequestered
via restoration
of degraded
pastures*
(Mt CO 2 -eq)
|
C sequestered
via land-use
change
(Mt CO 2 -eq)
|
Total
mitigation
(Mt CO 2 -eq)
|
||
Milk
|
Meat
|
Milk
|
Meat
|
||||||
1
|
Adoption of
improved pastures in LGH systems in CSA
|
||||||||
Cerrado
|
78
|
1,552
|
45.5
|
45.5
|
—
|
—
|
—
|
—
|
|
100% adoption †
of Brachiaria pasture
|
31
|
713
|
14.7
|
16.8
|
7.4
|
23.5
|
13.5 ‡
|
44.5
|
|
30% adoption †
of Brachiaria pasture
|
64
|
1,300
|
36.2
|
36.9
|
2.2
|
23.5
|
4.1 ‡
|
29.8
|
|
2.a
|
Diet intensi fi
cation: stover digestibility improvement in MR, MI systems in SSA, SA
|
||||||||
Baseline diet §
|
58
|
1,958
|
490.1
|
490.1
|
—
|
—
|
—
|
—
|
|
100% adoption †
of stover with
50%
digestibility (from 40%)
|
25
|
548
|
177.0
|
114.3
|
61.6
|
—
|
—
|
61.6
|
|
23% adoption †
of stover with
50%
digestibility (from 40%)
|
50
|
1,634
|
418.1
|
403.6
|
14.2
|
—
|
—
|
14.2
|
|
2.b
|
Diet intensi fi
cation: grain supplementation in MRH, MRT, MIH, MIT systems in SSA, SA
|
||||||||
Baseline diet
§
|
58
|
1,958
|
148.0
|
148.0
|
—
|
—
|
—
|
—
|
|
100% adoption †
of increasing grain
supplementation
from 0.5 to 2 kg/head/d
|
18
|
395
|
39.3
|
22.5
|
22.1
|
—
|
—
|
22.1
|
|
23% adoption †
of increasing grain
supplementation
from 0.5 to 2 kg/head/d
|
49
|
1,598
|
123.0
|
119.1
|
5.1
|
—
|
—
|
5.1
|
|
3.a
|
Land use:
restoration of degraded pastures in the LG systems in CSA and SSA
|
||||||||
In CSA
|
—
|
—
|
—
|
—
|
—
|
53.6
|
—
|
53.6
|
|
In SSA
|
—
|
—
|
—
|
—
|
—
|
96.7
|
—
|
96.7
|
|
3.b
|
Land use:
increasing agroforestry practices in the MRH, MRT systems in CSA, SSA, SA,
SEA
|
||||||||
Baseline diet §
|
58
|
1,958
|
287.6
|
287.6
|
—
|
—
|
—
|
—
|
|
1 kg Leucaena
supplement replacing
0.5 kg stover
and 0.5 kg concentrate
(100% adoption
† )
|
25
|
523
|
103.9
|
59.2
|
40.3
|
—
|
102.7 ¶
|
143.0
|
|
1 kg Leucaena
supplement replacing
0.5 kg stover
and 0.5 kg concentrate
(23% adoption †
)
|
50
|
1,628
|
245.3
|
235.1
|
9.3
|
—
|
23.6 ¶
|
32.9
|
|
4.
|
Changing breeds
of large ruminants in the LG (meat) and MRH, MRT, MIH, MIT (milk) systems in
CSA, SSA, SA, SEA
|
||||||||
Local
breeds
|
31
|
713
|
363.3
|
172.8
|
—
|
—
|
—
|
—
|
|
100% adoption †
of crossbreeds
|
26
|
568
|
171.6
|
77.8
|
19.5
|
—
|
—
|
19.5
|
|
29% adoption †
of crossbreeds
|
30
|
671
|
307.7
|
145.2
|
5.6
|
—
|
—
|
5.6
|
|
*Rates of carbon
sequestration from ref. 10.
†“Adoption”
refers to the proportion of total milk and meat production in 2030 that comes
from implementing the option analyzed.
‡ Carbon
sequestration data from ref. 9.
§ Baseline diet:
grazing (1.3 kg DM), stover at 45% digestibility (2 kg DM), cut-and-carry (1 kg
DM), grain concentrates (0.5 kg DM).
¶ Carbon sequestration data from
ref. 15.
Changing
Breeds of Ruminants.
At current adoption rates of improved breeds with higher milk production
potential and higher body weights, only modest reductions in the amount of CH 4
produced per ton of milk can be obtained. This happens because of a body weight
effect in which larger animals (500 kg compared with 250 kg) on the same diets
will have higher intakes. As a result, differences in CH 4 production per
animal are 38.7 kg CH 4 per year compared with 68.5 kg CH 4 per year, but the
CH 4 output per unit of animal product does not change significantly. The
larger animals produce more milk and meat, and as a result fewer animals are required
to meet demand. This option potentially could be applied to many animals and
across large areas, but the maximum mitigation potential is estimated to be a
relatively modest 19 Mt CO 2 -eq.
Comparisons
Between the Different Options. Comparison of options at observed or
plausible adoption rates suggest that restoration of degraded rangelands in SSA
and CSA has the highest mitigation potential, owing to the magnitude of
degradation and rangeland extent,
although there may
well be issues
associated with its implementation. Next is the agroforestry
option, which sequesters carbon and intensifies diet quality to reduce animal
numbers. Improvements in the use of improved pastures and crop residue digestibility
have the next-highest mitigation potentials owing to their broad recommendation
domains and the marginal reductions in CH 4 production per unit of output that
can be obtained. Replacing breeds has the second-lowest mitigation potential of
the options considered here, mainly because larger animals have higher intakes
and produce significantly more CH 4 than smaller indigenous breeds,
and this negates
most of the
benefit of increases in milk and
meat production. Grain supplementation had the lowest mitigation potential,
apparently mostly because of the relatively limited recommendation domain for
this option.
Discussion
If we sum the various mitigation
potentials (and subtract the restoration of degraded pastures in CSA in option
1, because this is already counted in option 3a), the total mitigation
potential is 417 Mt CO 2 -eq. This amounts to approximately 12% of the global livestock-related CH 4 and
CO 2 emissions that are
associated mainly with extensive livestock systems (1). The total
mitigation potential using plausible adoption rates amounts to 214 Mt CO 2 - eq,
or 6% of the extensive livestock system-related CH 4 and CO 2 emissions. If
some of these options were implemented in the same system simultaneously, further
emission reductions might
be obtained (for example, changing breed of animal together with supplementing
the diet in several ways), but we have not estimated those effects here.
These estimates are highly
indicative, because there are several limitations to the analysis. Although we
attempted a breakdown by region and system, the true complexity of the changes
examined is not comprehensively addressed. For example, option 2b, if adopted widely
in a region, could have significant impacts on grain price, which could then
translate into shifts in demand for grain for human food and for livestock
feed. For most of the options considered, there may well be indirect impacts on
natural resources that are not considered here, as well as impacts on (and of)
livestock diseases, for example. Quantifying all of the potential impacts of systems’
and land-use change is not straightforward, however. The replacement of cerrado
vegetation with improved pastures, for example (option 1), could potentially
reduce rates of future deforestation, because less land would be required to
maintain fewer but more productive animals. The sowing of improved pasture in the
forest margins, in areas that have already been deforested, could thus help to
reduce future rates of deforestation.
All these mitigation options have
costs associated. For example, restoration of degraded lands in the warm-dry
and warm-moist climatic zones is estimated to cost $50 per ha per year and $15
per t CO 2 -eq per year, whereas livestock feeding options in the same zones
are estimated to cost $60 per t CO 2 -eq per year (18). There are many reasons
for the gap between what could potentially be achieved and realized GHG
mitigation, such as policy barriers, institutional, sociocultural, educational,
and economic constraints, and particularly for the future,
the price of CO 2 equivalents. Global agriculture could offset 5–14% (with a
potential maximum of 20%)
of total annual
CO 2 emissions for prices ranging from $20 to $100 per t CO 2
-eq (18). Even given the highly indicative nature of the numbers reported here,
the mitigation potential of these strategies for the land-based livestock
systems in the tropics amounts to approximately 7% of the (total) global agricultural
mitigation potential to 2030. Using plausible adoption rates, this decreases to
a contribution of approximately 4%. This could still be worth on the order of
$1.3 billion per year at a price of $20 per t CO 2 -eq (18), however. There are
currently approximately 43 million livestock keepers living in the tropical rangeland-based
systems on less than $1 per day (19). Although the mitigation options looked at
here may contribute only modestly to mitigation in relation to the global total
from agriculture, such carbon payments could represent a meaningful amount of potential
income for resource-poor livestock keepers in the tropics: an average of some
$30 per household per year would increase some household incomes by 15% or
more.
How can we increase the
contribution of tropical land-based livestock systems to global agricultural
mitigation? The analyses here highlight the contribution that reducing the
number of livestock could play in mitigating GHGs from land-based systems in
the tropics. Most of the strategies investigated in this study involve significant
reductions in animal numbers while increasing their productivity. However,
there are likely to be sociocultural tradeoffs involved. For many pastoralist
societies in Africa and Asia, wealth is measured at
least partially in
terms of livestock
numbers (1). Options that propose
reducing peoples’ assets may not only affect households culturally, but they
may also have unintended consequences on households’ ability to manage risk.
The value of livestock to livelihoods in marginal environments goes far beyond the
direct impacts of their productive capacity. There are other options, however,
that could still generate income for livestock keeping households and from that
perspective may well be worth seriously considering. This highlights the need
to carry out household-level analysis to estimate what income levels these
options might generate, in view of changes in production costs and production
levels. Another option would be to improve adoption rates of these strategies
and other mitigation options, via investments that reduce transaction costs and
provide services and incentives to farmers so that they can adopt selected
practices. These need to be accompanied by systems of payments for GHG ef fi
ciency at the farm gate (such as paying premiums for low emissions per kilogram
of animal product produced) and also by establishing constraints on carbon emissions
for the livestock sector.
Materials and Methods
Land Use and Livestock Systems Classification. We postulate
large differences in mitigation potential between different livestock
production systems, and so to disaggregate
the results of
the analysis here,
we used a
dynamic livestock production system classification scheme (20). The
scheme characterizes grassland-based systems, in which more than 10% of the dry
matter fed to animals is farm produced and in which annual average stocking rates
are less than 10 temperate livestock units per ha of agricultural land; rain-fed
mixed farming systems, in which more than 90% of the value of nonlivestock farm
production comes from rain-fed land use, including the following classes; and
irrigated mixed farming systems, in which more than 10% of the value of
nonlivestock farm production comes from irrigated land use. These are further
categorized on the basis of climate: arid–semiarid (with a length of growing
period (LGP) <180 d), humid–subhumid (LGP >180 d), and
tropical highlands/temperate regions.
The classification scheme (Table S1) was mapped using proxies
(21, 22) and has been updated using new datasets. The key proxies are cropland,
LGP, and human population density. Cropland was estimated from the Global Land
Cover (GLC) 2000 data layer (http://bioval.jrc.ec.europa.eu/products/glc2000/glc2000.php).
Despite the age of GLC 2000, the estimates of cropland that are based on it have
been shown to be no better or worse, in general, than estimates based on some
other data products for Africa (23) and globally (24). Rangelands were defined
according to certain land cover classes (22), modi fi ed according to
whether areas had
a human population
density greater than
20
persons per square kilometer, as
well as an LGP >60 d (which can occasionally allow cropping); in such cases,
the areas were included in the mixed system categories. In our mapping of
livestock systems, cropland areas from GLC 2000 may be overestimated in some
situations, although using some other land-cover data products may result in
underestimates (23, 24). Different estimates of cropland extent may affect the
results of the analysis presented here, but probably only to a limited extent,
given that livestock numbers were allocated to the different systems in such a
way as to match national livestock statistics. The weaknesses of current
land-cover datasets with respect to cropland identi fi cation are slowly being
recti fi ed through evaluation and harmonization of different datasets in
different situations (see ref. 25, for example). The irrigated areas are based
on the Food and Agriculture Organization (FAO) Aquastat map version 4.0.1 (26).
For human population, we use the 1-km Global Rural-Urban Mapping Project
(GRUMP) data (http://sedac.ciesin.columbia.edu/gpw/ancillary figures.jsp#1kmdens),
which also defines urban areas. For 2030, the GRUMP population data are
allocated pro rata according to
the United Nations
Population Division’s medium-variant population data for each year
by country (http://esa.un.org/unpp). Length of growing period data have been
developed from the WorldClim 1-km data for the year 2000 (27), together with a
new tropical highlands layer for the same year based on the same dataset, and
for the year 2030 (28).
Livestock
Numbers and Future Projections. For future projections of livestock numbers
in the grazing systems of the tropics, we used a set of “reference world”
simulations (29). These were derived using the International Model for Policy Analysis
of Agricultural Commodities and Trade (IMPACT) combined with a global water
simulation model based on global water databases (30). IMPACT is a partial
equilibrium agricultural sector model and simulates food production (for 32
crop, livestock, and fish commodities) according to economic, demographic, and
technological change. The model generates annual projections for irrigation,
livestock, and nonagricultural water withdrawals and depletion, as well as
irrigated and rain-fed crop area, yield, production, demand for
food, feed, and
other uses, prices,
and trade; and
livestock numbers, yield, production, demand, prices, and trade. The
model also estimates the number of malnourished preschool children in
developing countries as a proxy for poverty rates. A scenario has been
simulated to 2050 that quanti fi es global economic growth and shifts in the
demand and supply of agricultural
products, which imagines
a world developing
in the coming decades much as it does today (the
“reference world”) (29). Economic growth assumptions and
agricultural productivity estimates
are largely based
on those of the TechnoGarden scenario of the Millennium Ecosystem
Assessment (31). The reference world assumes a set of energy use and production
projections that lie
in the middle
of available energy
projections. The GHG emissions scenario associated with this
is the SRES B2 scenario (32), and climate projections to 2050 using the outputs
from the Hadley Centre Coupled Model version 3, HadCM3 (33), were used to drive
the various modeling tools (29). We use the same climate and human population
data to modify the livestock system classi fi cation in the analyses here. We
used reference world numbers of bovines for both 2000 and for 2030 (29). The
data for 2000 are based on averages for the years 1999–2001 from the FAOSTAT
database (http://faostat.fao.org/default.aspx), and these country-level data
were then allocated pro rata according to the Gridded Livestock of the World
dataset (34). For livestock in 2030, the livestock numbers that were generated
as output from the IMPACT model were converted to live-animal equivalents using
country-level ratios of live-to-slaughtered animals from FAOSTAT for the
average of the 3 y centered on 2000. These future livestock numbers were then
allocated to the modi fi ed system extents on a pro rata basis. In the
reference run, although there are signi fi cant improvement in animal yields,
growth in numbers will continue to be the main source of production growth in
developing countries, re fl ecting recent trends (29). Numbers of bovines by
region and system for 2000 and 2030 are shown in Table S2.
Estimating
Emissions from Livestock Systems. Diets of domestic ruminants in the
tropics are varied and depend to a great extent on the type of production system
in which animals are kept. To account for these systems’ and regional differences,
we divided the tropics up into four regions: SSA, South Asia (SA), Southeast
Asia (SEA), and tropical CSA. We omitted East Asia and West Asia–North Africa
from the analysis because the great majority of the land-based livestock
systems in these regions are subtropical rather than tropical. We estimated
livestock diets using expert knowledge and literature reviews for each production
system (17). Diets are made up of seven generic feeds: arid rangelands, humid
rangelands, cooler tropical rangelands, stover (crop residues), cut-and-carry
pastures, opportunistic feeds such as weeds and roadside grasses, and grains.
The availability of these feeds and the complexity of diets depend on the level
of intensification of the production system (35). Such dietary differences are
essential in estimating differences in CH 4 production between systems and
regions (17). We use a dynamic model for predicting feed intake and nutrient
supply in ruminants, RUMINANT (36) (SI Text), as the basis of our calculations
of CH 4 produced from enteric fermentation. The model estimates intake and
supply of nutrients to the animal from fermentation kinetics and passage of
carbohydrate and protein through the animal and subsequent excretion (37) and
estimates the animal’s nutrient requirements (38). The model can simulate
animals of different body weights because of the incorporation of allometric
rules for scaling passage rates (37), and it calculates stoichiometries (39).
RUMINANT has been validated with a wide range of tropical and temperate diets.
Because constraints on intake due to scarcity of feed resources are common in
many farming systems (17), we assume that feed scarcity amounts to 25% of total
feed intake for
dry-season diets. For
each system and
region, RUMINANT was run for dry and wet season diets and the results
multiplied by the number
of days in
each season to
obtain yearly CH 4 production estimates per animal. These
were then aggregated to the system level by multiplying by the number of
livestock present in each system. Methane from
ruminant manure management
systems was assumed
to be proportional to the CH 4 produced from
enteric fermentation, amounting to 3% of the CH 4 coming from enteric
fermentation (17, 40). RUMINANT was also used to estimate the impacts of
dietary changes on meat production, and we estimated offtake rates by region
from ref. 29) (SI Text).
Rationale for the Mitigation Options Assessed. We estimated
the mitigation potential of six region- and system-speci fi c options to 2030.
The rationale for their selection follows.
Option 1: Intensifying
rangeland productivity in the neotropics
via adoption of improved pastures. Taken as a whole, CSA
is the highest contributor to agricultural GHG emissions. At the same time, the
region has human population densities
that are sufficiently
low to permit
the expansion of
ruminant livestock production. However, it is critical that any
expansion of livestock production
does not happen
at the expense of
forest loss. Considerable expansion of the areas in
improved pasture we judge to be plausible, because improved pastures have been
widely adopted in tropical CSA in recent times: the historical
precedent exists. There
is less scope
for the widespread adoption of improved pastures in
the tropics of SSA and Asia, however. For the
former, there is
little historical precedent,
and substantial economic development of the rangelands is
unlikely. In the tropical regions of Asia, pressure on land resources means
that there is only limited scope for the expansion of land-based ruminant
production systems (41). To evaluate this option, we assumed conversion of
rangelands from native cerrado vegetation to an improved pasture such as
Brachiaria decumbens, one of several species of cultivated grass of African
origin that are already widely cultivated as a livestock feed in the tropics.
We applied modified animal productivity
parameters and calculated
CH 4 emissions using the
RUMINANT model. The results were scaled up to the whole of the
humid–subhumid grassland-based system (LGH) in CSA by applying historical rates
of improved pasture expansion to the total area (11). Expansion of improved
pastures in the rangelands of CSA could also affect carbon sequestration rates,
and we estimated this effect using data for Brachiaria humidicola (9). We
estimated the added carbon sequestration potential that arises from restoration
of degraded pastures in the region using existing data (10).
Option
2:
Diet intensi fi cation in mixed systems in SSA and Asia. The manipulation of
dietary components in ruminants is considered by many to be one of the most
direct and effective ways of mitigating CH 4 . Mixed crop–livestock systems in
the tropics usually have complex diets that are amenable to modification.
Productivity is inherently low in many of the mixed systems in SSA and Asia but
could be substantially increased through diet intensification, about which a
considerable body of
research exists. Widespread
application of different options
is plausible in many situations. To assess the effects of diet intensification
in the mixed systems in SSA and SA, we evaluated two options in relation to a
common baseline large ruminant diet, made up of daily intakes per head of 1.3
kg dry matter (DM) of grazing, 2 kg DM of cereal stover with a digestibility of
45%, 1 kg DM of cut-and-carry forage, and 0.5 kg DM of a grain concentrate.
Such a diet can support milk production of 1.3 kg per day and liveweight gain
of 0.07 kg per day. The source of cereal stover changes, depending on the
system and region, from maize in many parts of SSA to rice and sorghum in SA,
for example. First (option 2a), we posited an increase in stover digestibility
of 10 percentage points, which is well within the range of variation in
digestibility that has been observed in sorghum, for example (42). We evaluated
the impacts of this change in the diet and scaled up the results to all of the
MR (mixed rain-fed) and MI (mixed irrigated) systems in SSA and SA. Adoption
rates of up to 43% for genetically improved dual-purpose crops have been observed
in some parts of West Africa (12). Although lower adoption rates may be
expected in general, the potential domain for adopting this option is large and
extends throughout the mixed systems of SA (13). Second (option 2b), we modi fi
ed the basal diet by increasing the amount of grain fed as a supplement from
0.5 to 2 kg per animal per day. As for option 2a, we evaluated the impact of
the change in diet on milk and CH 4 production. Unlike option 2a, we judged
that this option would not be so applicable to the arid–semiarid mixed systems,
given the importance of grain production
for human consumption
in these systems.
Accordingly, the results were scaled up to the mixed humid–subhumid and tropical
highland systems in SSA and SA, for the livestock numbers projected to 2030. We
could find no direct adoption data in the literature and thus used a rate of 1%
per year (some 23% to 2030), the same rate as for option 2a and for the
agroforestry-based supplementation option (see below, option 3b).
Option 3: Land-related alternatives. Weevaluated
two options with a specific focus on land-use change: one that improved the
sequestration of carbon in degraded rangelands (via some reduction in animal
numbers to moderate stocking rates in theseareas),and one that evaluated broad adoption
of agroforestry options that can increase carbon sequestration and also provide
improvements to ruminant diets via supplementation with highly digestible
leaves.
Option 3a:
Carbon sequestration in rangelands.
Globally,
the rangelands occupy vast areas of land, and the potential for carbon
sequestration has been amply demonstrated (10). Important social bene fi ts
could accrue in addition to the environmental benefits, by providing an
additional source of income for the poor livestock producers that predominate
in the tropics. There is considerable activity in this area, but uncertainties
persist regarding the mechanisms that are needed to set up efficient and
equitable payment schemes. We applied existing carbon sequestration rates (10)
to the degraded proportion of the rangeland-based systems (LG) in SSA and SA
and calculated total amount of extra carbon sequestered.
Option 3b:
Increasing the uptake of agroforestry practices.
This option has
both direct and indirect impacts on the environment and livestock. Increasing
tree coverage can markedly increase the rate of carbon sequestration, depending
on the system and region (15), while at the same time it can improve the diets
of livestock because of the higher nutritive value and increased digestibility
of some agroforestry species. This option can tackle CH 4 and CO 2 emissions
simultaneously. To estimate the effects, we increased the area under
agroforestry according to historical rates of adoption and scaled this up to
the systems in which it is most like to be practiced: the mixed rain-fed humid/subhumid
and tropical highland (MRH, MRT) systems in the tropics. We estimated the
additional CO 2 captured in these systems. We ran RUMINANT with a modified diet
that included the leaves of L. leucocephala as a supplementary feed for cattle
in the dry season and quanti fi ed the CH 4 mitigated as a result. Adoption
rates on the order of 1% per year of agroforestry practices such as improved
fallows and boundary plantings have been observed in some situations (14), and
we applied this here (23% to 2030).
Option
4:
Shifts in breeds of ruminant livestock. Historically, the use of conventional
livestock breeding techniques has been largely responsible for the increases in
yield of livestock products observed over recent decades (43). Genetic improvement
coupled with diet intensification could lead to substantial efficiency gains in
livestock production and CH 4 output. This would result in fewer but more
productive animals being kept, which could have positive consequences for CH 4
production and land use. To quantify this option, we changed the potential
productivity of animals in the RUMINANT model to simulate a change in breed
from a local cow to a cross-bred animal and estimated the impacts on both meat
production in the rangeland (LG) systems and dairy production in the MR and MI
systems. We excluded the arid–semiarid systems from this scaling up, because we
assumed that adoption in these systems of such an option would be low. In the
humid–subhumid and tropical highland systems, we assumed an adoption rate of
29% to 2030, based on the historical adoption rate of crossbred dairy animals
in Kenya (16).
ACKNOWLEDGMENTS. We thank Rich
Conant, Federico Holmann, Matthieu Lesnoff,
Frank Place, Mark
Rosegrant, and Russ
Kruska for providing information and links to relevant
literature.
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