Impacts of feeding less food-competing feedstuffs to livestock on global food system sustainability

Abstract

Increasing efficiency in livestock production and reducing the share of animal products in human consumption are two strategies to curb the adverse environmental impacts of the livestock sector. Here, we explore the room for sustainable livestock production by modelling the impacts and constraints of a third strategy in which livestock feed components that compete with direct human food crop production are reduced. Thus, in the outmost scenario, animals are fed only from grassland and by-products from food production. We show that this strategy could provide sufficient food (equal amounts of human-digestible energy and a similar protein/calorie ratio as in the reference scenario for 2050) and reduce environmental impacts compared with the reference scenario (in the most extreme case of zero human-edible concentrate feed: greenhouse gas emissions -18%; arable land occupation -26%, N-surplus -46%; P-surplus -40%; non-renewable energy use -36%, pesticide use intensity -22%, freshwater use -21%, soil erosion potential -12%). These results occur despite the fact that environmental efficiency of livestock production is reduced compared with the reference scenario, which is the consequence of the grassland-based feed for ruminants and the less optimal feeding rations based on by-products for non-ruminants. This apparent contradiction results from considerable reductions of animal products in human diets (protein intake per capita from livestock products reduced by 71%). We show that such a strategy focusing on feed components which do not compete with direct human food consumption offers a viable complement to strategies focusing on increased efficiency in production or reduced shares of animal products in consumption.

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rsif.royalsocietypublishing.org
Research
Cite this article: Schader C et al. 2015
Impacts of feeding less food-competing feed-
stuffs to livestock on global food system
sustainability. J. R. Soc. Interface 12: 20150891.
http://dx.doi.org/10.1098/rsif.2015.0891
Received: 10 October 2015
Accepted: 18 November 2015
Subject Areas:
environmental science, biophysics,
bioinformatics
Keywords:
food security, livestock, sufficiency, consistency,
sustainable intensification, food system
Author for correspondence:
Christian Schader
e-mail: christian.schader@fibl.org
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rsif.2015.0891 or
via http://rsif.royalsocietypublishing.org.
Impacts of feeding less food-competing
feedstuffs to livestock on global food
system sustainability
Christian Schader1, Adrian Muller1,2, Nadia El-Hage Scialabba3, Judith Hecht1,
Anne Isensee1, Karl-Heinz Erb4, Pete Smith5, Harinder P. S. Makkar3,
Peter Klocke1,6, Florian Leiber1, Patrizia Schwegler2, Matthias Stolze1
and Urs Niggli1
1
Research Institute of Organic Agriculture (FiBL), Ackerstrasse 113, 5070 Frick, Switzerland
2
Institute of Environmental Decisions, ETH Zu¨rich, Universita
¨tstrasse 22, 8092 Zu¨rich, Switzerland
3
Food and Agriculture Organization of the United Nations (FAO), Viale Terme di Caracalla, 00150 Rome, Italy
4
Institute of Social Ecology Vienna (SEC), Alpen-Adria University Klagenfurt-Vienna-Graz, Schottenfeldgasse 29,
1070 Vienna, Austria
5
Scottish Food Security Alliance-Crops and Institute of Biological and Environmental Sciences, University of
Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UK
6
Bovicare GmbH, Hermannswerder Haus 14, 14473 Potsdam, Germany
CS, 0000-0002-4910-4375; AM, 0000-0001-7232-9399; NE-HS, 0000-0001-6421-1462;
K-HE, 0000-0002-8335-4159; PS, 0000-0002-3784-1124
Increasing efficiency in livestock production and reducing the share of animal
products in human consumption are two strategies to curb the adverse environ-
mental impacts of the livestock sector. Here, we explore the room for sustainable
livestock production by modelling the impacts and constraints of a third strat-
egy in which livestock feed components that compete with direct human food
crop production are reduced. Thus, in the outmost scenario, animals are fed
only from grassland and by-products from food production. We show that
this strategy could provide sufficient food (equal amounts of human-digestible
energy and a similar protein/calorie ratio as in the reference scenario for 2050)
and reduce environmental impacts compared with the reference scenario (in the
most extremecase of zero human-edible concentrate feed: greenhouse gas emis-
sions 218%; arable land occupation 226%, N-surplus 246%; P-surplus 240%;
non-renewable energy use 236%, pesticide use intensity 222%, freshwater use
221%, soil erosion potential 212%). These results occur despite the fact that
environmental efficiency of livestock production is reduced compared with
the reference scenario, which is the consequence of the grassland-based feed
for ruminants and the less optimal feeding rations based on by-products for
non-ruminants. This apparent contradiction results from considerable
reductions of animal products in human diets (protein intake per capita from
livestock products reduced by 71%). We show that such a strategy focusing
on feed components which do not compete with direct human food consump-
tion offers a viable complement to strategies focusing on increased efficiency in
production or reduced shares of animal products in consumption.
1. Background
Since the 1960s, breeding efforts to improve genetic potential, improvements in
herd management, increase in use of protein- and energy-rich concentrate feed
and a reduction in use of low-productivity grassland systems have increased
the productivity of livestock systems [1]. This led to an increase in feed conver-
sion efficiency, per-animal yields and labour productivity, and a decrease in
greenhouse gas (GHG) emissions per kg of animal product [2].
&2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.

However, the livestock sector as a whole has considerably
grown in absolute terms and contributes substantially to
global warming, water and air pollution and biodiversity
loss [1,3,4]. This overall growth of livestock production paral-
lels population growth and increasing per capita incomes that
are associated with increasing shares of animal products in
human diets [5].
About one-third of arable land is currently used for feed
production [1,6,7] and about a third of global cereal pro-
duction is fed to animals [8]. This leads to considerable
trade-offs with producing food for direct human consump-
tion as food provision via animals entails large conversion
losses [9–12]. The proportion of arable land used for live-
stock feed production is expected to increase further, thus
increasing the pressure on arable land areas [8].
Several strategies to increase sustainability in livestock
production have been suggested. They largely fall into
three categories.
(1) Productivity increases, aiming at meeting expected
demand while curbing environmental impacts (‘effi-
ciency strategies’ [13]): they include improved feeding
and feed use efficiency, improved digestibility, protein
and mineral contents, optimally matching the animals’
requirements, breeding and herd management [2]. They
contribute to the sustainable intensification of agriculture
[14,15] and provide many benefits for society. For
example, if applied globally, GHG emissions from the
livestock sector could be reduced by 30% when com-
pared with a reference without such intensification [16].
(2) Reduced demand for animal products (‘sufficiency strat-
egies’): they include changes in human diets and demand
patterns, but also measures such as the replacement of
ruminants’ products with monogastrics’ products
[9,17,18]. Changes in dietary patterns can have consider-
able mitigation potential, as demonstrated by several
modelling studies [19– 21]. A comprehensive overview
of the literature, distinguishing between supply and
demand-side measures, can be found in [21].
(3) Reduction of the use of food-competing feed components
in livestock rations, which also affects the availability of
livestock products (a ‘consistency strategy’ [22] or ‘trans-
formation of the food system’ [15]): this consistency
strategy shifts the focus from livestock’s role in the food
system as a source for high-quality protein, to another
role, which is to use resources that cannot otherwise be
used for food production. These resources are (a) grass-
lands, which cover two-third of global agricultural area
and can be used for food production by ruminants, whereas
a large proportion of these grasslands is not or less suitable
for arable crop production [23– 25] and (b) food waste and
by-products of food production– consumption chains, such
as brans, whey and oil-cakes [26,27]. The rationale is that
environmental pressures from livestock production could
be reduced by focusing on grassland-based ruminant
production and by reducing the amount of primary feed-
stuffs derived from cropland in both ruminant and
monogastric feeding rations [3,7,20,28]. This affects pro-
duction and consumption at the same time as it would
also lead to a reduction in animal product supply.
While the impacts of the efficiency and sufficiency strategies
have been modelled in detail in previous works
[9,16,18,29,30], the consistency strategy of reducing food-
competing feedstuffs (FCF) in livestock rations has not
previously been assessed to this extent.
In this paper, we explore the potential for sustainable
livestock productionby modelling the impacts of such a consist-
ency strategy on food provision as well as on natural processes.
We scrutinize the potential and challenges of reductions in FCF
and investigate the implications of such a consistency strategy
as one option for sustainable livestock production.
It has to be pointed out that the consistency strategy that
we analyse in this paper is a complement and not a substitute
of the sufficiency and efficiency strategies. It restricts the feed-
ing rations for livestock and thus limits the availability of
livestock products for human consumption. Corresponding
changes in consumption patterns are thus one important
implication of this strategy.
We use a mass-flow model of the food system to investigate
the effects of the consistency strategy of reducing FCF on crop
and livestock production patterns, human dietary patterns and
key environmental indicators. This study examines the impli-
cations of such a strategy from a physical and biological
perspective, aiming at maximal coverage regarding country-
wise production and availability of final and intermediate
commodities and related nutrient requirements and avail-
ability, as well as environmental impacts. It explicitly does
not aim at assessing price changes and market effects and
the decision behaviour of farmers and consumers. The purpose
of this study is, instead, to examine the system-level food and
environmental implications of pursuing this consistency strat-
egy and to identify whether it could be a complement to
efficiency and sufficiency strategies.
2. Methods
This analysis employs a bottom-up mass-flow model of the agri-
cultural and food sector, described in the following and the
electronic supplementary material. The model uses FAOSTAT
[6] as the central data source and covers 180 plant production
activities (e.g. cultivating 1 ha of wheat for a year) and 22 live-
stock production activities (e.g. keeping a dairy cow for a
year). The base year refers to mean values for the years 2005 –
2009. These are the most recent data available that are compatible
with the other datasets used, with 192 single countries and
territories as geographical reference units.
Country-specific herd structures for cattle, pigs and chickens
were estimated to improve calculations of feed requirements and
GHG emissions. Herd structures were calculated for each
country with an optimization model using a cross-entropy esti-
mator. These models predict the most likely average herd
structure in a country based on the relation between producing
and living animals according to FAOSTAT as well as a number
of normative data (see electronic supplementary material, §1.3.2).
For each activity, we defined inputs and outputs, i.e. all phys-
ical flows related to individual activities. Inputs for livestock
activities include four categories of livestock feeds: (i) fodder
crops grown on arable land, i.e. according to FAO, land being
cropped or fallow, (ii) concentrate feed derived from human-
edible food (e.g. grains, pulses) grown on arable land, (iii) grass-
land-based fodder, and (iv) fodder from agricultural/agri-
industrial by-products. While (i) and (ii) are in competition
with production of human-edible food, (iii) and (iv) are not.
The term grasslands is used synonymously with the term graz-
ing land. Further inputs for livestock activities are energy input
for buildings, in-stall processes and fences. Outputs of animal
production activities include human-edible and human-inedible
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products, manure excretion, nutrient losses and GHG emissions
owing to enteric fermentation and manure management (CH
4
,
N
2
O, NO
3
and NH
3
). Country-specific data for amounts of con-
centrate feed and by-products used are derived from FAOSTAT
food balance sheets (see electronic supplementary material,
§1.3.7). Inputs for plant production activities included arable or
grassland areas, mineral fertilizers, manure, crop residues, sym-
biotic nitrogen fixation, herbicides, fungicides, insecticides and
management practices. Outputs from plant production activities
include crop yield quantities, crop residues and nitrogen losses
during fertilizer application. Based on these data, we calculated
livestock feed and fertilizer supply/demand balances at national,
regional and global level.
The main model outputs are food availability (equation (2.1))
and environmental impacts (equation (2.2)).
FAi,m¼
Xjk ALi,j,kOUTi,j,k,l¼yields,s¼massNCHCi,j,k,mUFi,j,k,n¼food 8i,m,
ð2:1Þ
where iis the index of geographical units, jis the index of activi-
ties, kis the index of farming systems, lis the index of inputs and
outputs, mis the index of nutrients for human consumption, nis
the index of utilization types (food, feed, seed, waste, other) and
sis the index of units of inputs and outputs. FA is the food avail-
ability expressed in kcal or g protein, AL is the activity level (ha
per year for land-use activities, number of animals per year for
livestock activities), OUT is the output (kg per ha or kg per
animal), NCHC is the nutrient contents for human consumption
[%] and UF is the utilization factor [%].
In the electronic supplementary material, we describe how food
availability per person, activity levels, inputs and outputs, nutrient
contents and utilization factors are determined in our model.
2.1. Modelling environmental impacts
Environmental impacts are aggregated across all geographical
units, activities and farming systems (equation (2.2)). Activity
levels (AL
i,j,k
) are multiplied by inputs (IN
i,j,k,s,o
) and the impact
factors of the inputs (IF
i,j,k,l,s,o
).
EIi,o¼X
jk
ALi,j,kðINi,j,k,l,s,oþOUTi,j,k,l,s,oÞIFi,j,k,l,s,o8i,o,ð2:2Þ
where EI is an environmental impact, ois the index of environ-
mental impacts, IN ¼inputs [kg or ha] and IF ¼impact factors
[environmental impact per kg of input or output per emission].
An overview of the environmental indicators used in this study
and their units are given in table 1. In the main body of the
paper, we focus on land occupation, N-surplus, GHG emissions
and deforestation, whereas the other indicators (P-surplus,
renewable energy use, pesticide use, freshwater use, soil erosion)
are addressed only shortly. Further methodological details on the
main indicators and more detailed results on the other indicators
are provided in the electronic supplementary material, §1.3.10.
2.1.1. Land occupation
This indicator measures how much land is necessary for agricul-
tural production each year. Because arable land is much scarcer
and more valuable than permanent grasslands for food production,
we differentiate between land occupation of arable land and grass-
land. For equation (2.2), the inputs (IN) that are taken into account
are grassland and arable land. For all arable crops and grasslands,
the IF is defined as one. This indicator combines values for areas
harvested with values for cropping intensities that indicate how
often, on average, a hectare isharvested per year.On average, crop-
ping intensity is less than one; therefore, land occupation is larger
than the values for areas harvested [6,8].
2.1.2. N-surplus
NO
3
losses to soil, and NH
3
and N
2
O losses to the atmosphere
occur as a result of N use in agricultural systems. Consequently,
sensitive terrestrial and aquatic ecosystems are adversely affected.
N-surplus is defined as the difference between the N content
of outputs (e.g. yields) and inputs (e.g. fertilizer quantities) for
each country and activity. Changes in cropping areas, animal
numbers (manure), production quantities, mineral fertilizer use
and N-fixation thus potentially lead to changes in N-surplus.
Based on equation (2.2), the amount of N is calculated by multi-
plying the mass of an input (IN) or output (OUT) by its N
content. Relevant inputs for calculating the N-surplus are min-
eral N fertilizers, N-fixation, organic fertilizer, crop residues
and seeds. Relevant outputs are yields and crop residues. IF is
defined as the N-content of the inputs, whereas all outputs are
defined as negative values. As a basis for calculating GHG emis-
sions, N-losses during fertilizer application are separated
according to the type of fertilizer (mineral, manure, crop resi-
dues) and the substance emitted (NH
3
,NO
3
,N
2
O). Model
factors are specified according to IPCC 2006 Guidelines (Tier
1). Model calculations for the total N-balance in the base year
are in line with literature values reported for different sources
and the overall balance [1,31,32]. We did not include estimates
of atmospheric nitrogen deposition in the N-surplus calculations.
2.1.3. Greenhouse gas emissions
GHG emissions of the agricultural sector have been estimated by
several projects at regional [28] or global level [33–36].
Table 1. Overview of the indicators for analysing environmental impacts in the model.
environmental impact indicator unit
land occupation land occupation by arable and grassland ha
soil erosion potential crop-specific factor covering the erosion susceptibility of crops combined
with country-specific or regional average soil erosion rates
t soil lost per year
non-renewable energy demand cumulative energy demand, versions 1.05– 1.08 GJ per year
greenhouse gas emissions global warming potential (GWP) IPCC100a t CO
2
-eq per year
nitrogen surplus nitrogen surplus N-surplus per ha per year
phosphorus surplus P
2
O
5
surplus P
2
O
5
-surplus per ha per year
pesticide use classification of pesticide use per ha by intensity and by crop, legislation
by country and access to pesticides by farmers
semi-quantitative indicator
annual deforestation potential additional crop land required annually ha per year
water use use of water for irrigation m
3
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Estimations of global GHG emissions of the agricultural sector
are between 4.2 and 5.2 Gt CO
2
-eq [21] and this constitutes
approximately 10– 12% of total global emissions.
GHG emissions were modelled according to the Global
Warming Potential (GWP) ‘IPCC 2006 100a’ tier 1 methodology
[37]. For enteric fermentation modelling, we used the tier 2 meth-
odology in order to capture the impacts of different feeding
regimes on GHG emissions. Additionally, the GWP owing to
the production of inputs from non-agricultural sectors (mineral
fertilizers and pesticides) was included in calculations according
to LCA studies [38,39], the ecoinvent 2.0 database and [40]. To
calculate the GHG emissions from processes and buildings, the
cumulative energy demand (CED) values for different processes
were taken from ecoinvent 2.0 and transformed into GWP values
with process-specific conversion factors derived from ecoinvent
2.0. Emissions from deforestation and from organic soils under
agricultural use were taken directly from [41]. According to
equation (2.2), all relevant inputs (e.g. fertilizers) and processes
(e.g. enteric fermentation) were specified in physical quantities.
The respective CO
2
-eq values of CO
2
,CH
4
(25) and N
2
O (298)
were used as IF, as suggested in the IPCC 2006 guidelines.
Restricting the analysis to the common emission categories,
total GHG emissions calculated for the base year in our model
are similar to [16,41]. These references only differ substantially
in terms of enteric fermentation calculations; the results of our
model are similar to [41].
2.1.4. Annual deforestation potential
Because agricultural land is scarce and natural grasslands are
generally not well suited for cultivation (water or temperature
limited), increasing the amount of land needed for agricultural
production increases pressure on grasslands and forests [42].
Conversion of grassland to cropland may also indirectly lead to
increased deforestation, owing to displacement effects that
result in the conversion of forests to meadows and pastures
[43,44]. With limited data available, we have assumed that
additional cropland generally increases pressure on forests and
may lead to increased deforestation. Following Kissinger et al.
[45], we have attributed 80% of deforestation to agriculture. Fol-
lowing Alexandratos & Bruinsma [8], we have forecast constant
grassland areas.
The deforestation potential of agricultural land expansion
was estimated from the average annual growth in agricultural
area and the average annual deforestation rates in each country
from 2005 to 2009 (taken from FAOSTAT). Deforestation rates
in the scenarios were calculated by multiplying the change in
land areas in each scenario by the ratio of deforestation areas
over agricultural land area expansion, scaled by a factor of 0.8
to account for the 80% of deforestation attributed to agriculture.
In cases where no change in agricultural land area was
reported for the years 2005–2009, deforestation values were cal-
culated using the total agricultural area (instead of the change in
agricultural area) as a proxy for the pressure of agriculture on
forests. In these cases, deforestation rates were calculated by mul-
tiplying the total agricultural land area in each scenario by the
ratio of deforestation areas from [41] over total agricultural
land area in the base years, scaled by the factor 0.8. The indi-
cators for deforestation were applied only in the cases of
positive deforestation rates. Deforestation was set to zero in
countries where total forest area increased.
2.1.5. Other indicators
Here, we provide short descriptions only, further details can be
found in the electronic supplementary material, §1.3.9. P-surplus
is calculated analogously to the N-surplus. All P-flows are
expressed as P
2
O
5
. No differentiation between types of P-losses
is made. Therefore, the balance (inputs– outputs) calculated
expresses a ‘loss potential’, acknowledging that large quantities
of P are fixed in soils. The total P-balance in the base year as cal-
culated in our model is in line with literature values reported in
[31]. Non-renewable energy use is calculated according to the life
cycle impact assessment methodology, ‘CED’ [40]. Only the
non-renewable energy categories (fossil and nuclear energy)
are used, and renewable energy components are disregarded.
Inventory data for each activity were taken from the ecoinvent
2.0 database and [41– 44]. Water use was derived based on
AQUASTAT [46] data for irrigation use per tonne of irrigated
production and data on irrigated areas for various crops and
crop categories covered in [13]. As there is no consistent dataset
on pesticide use covering different countries, we developed an
impact assessment model for assessing pesticide use incorporat-
ing three factors: pesticide use intensity per crop and farming
system, pesticide legislation in a country, and access to pesticides
by farmers in a country (for details, see electronic supplementary
material, §1.3.9.4). Soil erosion potentials were derived based on an
assessment of soil erosion susceptibility per crop and soil erosion
rates per country (literature review and expert judgements,
details in electronic supplementary material,§1.3.9.5).
2.2. Scenarios
We calculated a reference scenario based on the most recent
FAO projections for agricultural production patterns and food
production and demand in 2050 [8], and a range of scenarios
with a gradual reduction of FCF ranging from the reference scen-
ario (referred to as 100% FCF) to 0% FCF. Each scenario
presented provides the same amount of per capita energy as the
reference scenario as the main measure of food availability.
Additional scenarios, for constant per capita protein supply and
for constant land use are given in the electronic supplementary
material, §2. By-products from food production (brans, oilseed
cake, whey, etc.) are assumed to be fed to animals in each scen-
ario (electronic supplementary material, §1.3.5). Livestock
numbers were derived from per-animal feed requirements and
the available feed supply in each scenario. Land no longer
required to supply animal feed was allocated to plant food pro-
duction, according to the mix of crops in the reference scenario
until the global levels of energy or protein for human consump-
tion match the requirements of the reference scenario. For
making the scenarios more comparable, grassland areas were
kept at the level of the reference scenario [8]. Yields per animal
were assumed to drop with reduced FCF. To account for the
uncertainties regarding this effect, we computed the uncertainty
range of 0–40% yield decrease with such feed pattern changes
(electronic supplementary material, §1.4.3). The values presented
in the paper refer to the mid-value of 20% yield reduction. Values
for the boundary cases (0% and 40%) are presented in the elec-
tronic supplementary material, §2. Fish and seafood also
decreased with a reduction of FCF, as such feed is used in aqua-
culture (assuming fed aquaculture to comprise about 20% of fish
and seafood in the current situation, about 45% in the reference
scenario [47,48], electronic supplementary material, §1.4.1.6).
For the scenario with 0% food-competing feedstuffs (0%FCF),
the induced reductions in animal protein supply were compen-
sated by adjusting the share of legumes in cropping patterns to
at least 20%, by allocating larger shares of the areas freed from
feed production to legumes (electronic supplementary material,
§2). This allows keeping the share of energy delivered through
protein at recommended levels of at least 10% also without
animal products. Average crop rotations were thus assumed to
include a legume crop once every 5 years. This is also feasible
agronomically, e.g. regarding breaking disease cycles in legumes.
The effect of climate change on yields was assessed by means of
sensitivity analysis based on the references and details given in
electronic supplementary material, §1.4.3, covering a range
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from zero yield increases under strong climate change impacts
to yield increases as reported in [8], signifying no climate
change impact.
3. Results
Figure 1 gives an overview of the results comparing the base
year (BAS), reference scenario (REF) and the scenario with
0%FCF. The other figures provide further details with
regard to the impacts of a partial switch towards less FCF
(figures 2 –4) and sensitivity analyses (figures 2–4 and
figure 5).
3.1. Changes in agricultural production patterns
In the reference scenario for 2050 [8], grassland area is
assumed to stay constant compared with the current situation
(base year), whereas arable land is projected to increase from
1.54 to 1.63 Mha, i.e. by 6% (figures 1 and 2), resulting in a 2%
increase in total agricultural land area. In the reference scen-
ario, animal numbers are projected to increase from 1.39 to
1.85 billion animals for cattle (33% increase), from 0.9 to 1.2
billion animals for pigs (27% increase) and from 17.6 to 33.9
billion animals for chickens (by 93%) if compared with the
base year (figures 1 and 3).
Compared with the base year, the scenario with 100%
reduction of FCF resulted in a 335 Mha decrease in arable
land area, which corresponds to a decrease of 22% in arable
and 7% in the total agricultural area. For cattle, in the scenario
with 0%FCF, the number would increase by 60 million,
i.e. 4% compared with the base year, and goat, sheep and buf-
falo numbers would increase by 320, 240 and 80 million,
respectively (i.e. 37%, 22% and 44%), as these animals are
mainly fed on grasslands and are thus less dependent on
feed sources that compete with direct food production. In
the 0%FCF scenario, the number of monogastrics is substan-
tially reduced by 12.37 billion (i.e. 70%) for chickens and 810
million (88%) for pigs (figures 1 and 3).
Depending on the extent to which climate change limits
the growth of crop yields (electronic supplementary material,
§1.4.3), cropland area would need to increase by up to
0.85 Mha, i.e. 55%, in the reference scenario compared with
the base year. In the 0%FCF scenario, these increases in crop-
land area are limited to 0.29 Mha (19%) for the worst-case
scenario, showing a considerable reduction in pressure on
land use from this scenario, particularly if projected crop
yield increases cannot be achieved (figure 2).
3.2. Changes in food consumption patterns
Food consumption patterns are represented via projected
provision in quantities, calories and proteins per capita and
day (table 2), differentiated by commodity group (see elec-
tronic supplementary material, §1.3.8). We report food
supply before subtraction of food waste at retail and consump-
tion level. For the production level, the quantities of food loss
reported in FAOSTAT have been used in order to be
consistent with Alexandratos & Bruinsma [8].
To allow for optimal comparison with the reference scen-
ario, per capita calorie supply from both plants and animals in
the scenarios was kept constant at the level of the reference
land use livestock
environment
diets
energy supply
kcal per cap per day
total: 2763
15%
85%
17%
83%
5%
95%
current situation:
base year
protein supply
g protein per cap per day
total: 77
34% 38%
66% 62%
11%
89%
total: 82 total: 78
2050:
reference scenario
2050:
food - not feed
current situation:
base year
2050:
reference scenario
2050:
food - not feed
total: 3028 total: 3028
billion hectares billion animalscurrent situation: base year
current situation: base year
cattle 1.39
1.85
1.45
17.56
33.85
5.19
0.86
1.39
1.18
chickens
goats
pigs 0.92
1.17
0.11
0.18
0.27
0.26
1.10
1.60
1.34
buffaloes
sheep
2050: reference scenario 2050: reference scenario
2050: food - not feed
2050: food - not feed
current situation: base year
arable land occupation
billion hectares
1.54
1.63
1.20
N-surplus
million tonnes N
87.9
121.8
65.2
P-surplus
million tonnes P
47.2
64.0
38.4
GHG emissions*
Gt CO2-eq
11.0
12.8
10.4
freshwater use
km3
1371
2178
1718
7.2
6.5
* GHG emissions include emissions from input provision, deforestation and organic soils.
deforestation
million ha
8.2
36.8
32.2
soil erosion from water
billion tonnes soil lost
33.7
22.6
26.7
17.2
non-renewable energy use
exajoules
14.1
15.4
12.0
pesticide use
dimensionless index
2050: reference scenario 2050: food - not feed
livestock products
plant products
livestock products
plant products
1.54
1.63
1.20
3.38
3.38
3.38
land occupation:
crop
grass
Figure 1. Impacts of feeding less food-competing feedstuffs to livestock (‘food - not feed’) on land use, livestock numbers, human diets and the environment in 2050.
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5

scenario (3028 kcal cap
21
d
21
). This slightly differs from the
3070 kcal cap
21
d
21
reported in [8] owing to some differences
in assumptions for cases where we had access to newer
information, or where underlying information from [8] has
not been available. This high number of calorie availability
includes food wastage of about 30–40% on global average,
which when deducted leads to a level in the range of human
maintenance requirements. In the scenario with 0%FCF and
at the same time keeping energy levels in human diet constant,
the share of energy delivered through protein would change
from 10.8% to 10.3% owing to the higher share of crops in
the human diet, and crops generally having lower protein
relative to energy contents (figures 1 and 4).
Owing to the decreasing animal numbers and livestock
yields, the share of livestock products in the total protein
supply would drop from 38% to 11% and the share of live-
stock products in the total energy supply would drop from
17% to 5% (with 20% livestock yield reduction; figures 1
and 4). This is also reflected in the per capita daily consump-
tion quantities of different commodity groups. Meat, eggs
and milk drop from 136, 26 and 274 g cap
21
day
21
to 26, 2
and 138 g cap
21
day
21
, respectively. Climate change (i.e.
lower yield increases) leads to further small changes in diet-
ary composition with less livestock products and more
grains, legumes and fish.
3.3. Environmental impacts
We focus on the presentation of the results on N-surplus,
GHG emissions and deforestation. Results on land
occupation have been covered already above. Results for
the other impacts (P-surplus, non-renewable energy use,
water use, pesticide use and soil erosion) are included in
figures 1 and 5 and discussed shortly; more details can be
found in the electronic supplementary material, §2.1. Details
for the calculations are provided in the Methods section and
in particular in the electronic supplementary material, §1.3.
In the reference scenario, all environmental impacts are
exacerbated compared with the base year, except for defores-
tation rates (figures 1 and 5). The N-surplus (i.e. total input
minus total extraction by crops per ha; global average, includ-
ing grasslands) increases by 34%, which means an increase
from 18.6 to 25.0 kg ha
21
yr
21
. This is driven by the increase
in output from the whole food system, which leads to corre-
spondingly increased input use, i.e. mineral fertilizer inputs
and N-fixation (as legume areas and production increase as
well), whereas the increases in agricultural area are much
lower. GHG emissions increase by 27%. This again reflects
the increase in production volume; increased emissions
from higher ruminant numbers and manure quantities as
well as increased fertilizer inputs to the fields are the main
drivers of these emission increases. With deforestation and
organic soils included, the increase in GHG emissions in com-
parison with the base year is 16%, which reflects the lower
changes in those two additional categories in comparison
with the agricultural production. Deforestation pressure
decreases by 13% compared with the base year. The decrease
in deforestation rates is due to the reduced expansion rates in
agricultural area between now and 2050 compared with the
expansion rate in the base years 2005–2009. The lower
expansion rates of agricultural land are due to assumptions
6
land occupation grassland
land occupation cropland
land occupation total
5
4
land occupation (billion ha)
3
2
1
0base
year
100 80 60
supply of food-competing feedstuffs
to livestock in 2050 (% of base
y
ear)
40 20 0
Figure 2. Land occupation by cropland, grassland and total agricultural land
in the base year, reference scenario, i.e. no reduction in food-competing feed-
stuffs (¼100%) and with reduced usage of such feedstuffs. Diamonds (filled
diamonds): levels in the base year. Solid lines: negative impact of climate
change (CC) on yields absent; dashed lines: CC impact present. Sensitivity
to livestock yield reductions owing to reduction of food-competing feedstuffs:
0% (dark-coloured lines), 20% (medium-coloured), 40% (light-coloured).
2.5
cattle
sheep
goats
buffaloes
pigs 60
50
40
30
20
10
0
chicken
2.0
no. mammalian animals (billion heads)
no. chicken (billion heads)
1.5
1.0
0.5
0base
year
100 80 60
supply of food-competing feedstuffs
to livestock in 2050 (% of base
y
ear)
40 20 0
Figure 3. Livestock numbers in the base year, reference scenario, i.e. no
reduction in food-competing feedstuffs (¼100%) and with reduced usage
of such feedstuffs. Diamonds (filled diamonds): levels in the base year.
Solid lines: negative impact of climate change (CC) on yields absent;
dashed lines: CC impact present.
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6

about yield increase and cropping intensity increase in the
reference scenario [8]. Those effects, and not the utilization
of additional land, are the main mechanisms through which
increased food demand would be met. For the other environ-
mental impacts, most notably, freshwater use increases by
about 60%, owing to an increase in irrigated areas and irriga-
tion intensity. Pesticide use and erosion potential increase by
about 10% each, driven by the increase in arable land areas,
and P-surplus and non-renewable energy demand increase
by 30% and 20%, driven by the general increase in production
volumes and corresponding input use.
For the 0%FCF scenario, the environmental impacts are
lower than in the reference scenario just described (figures 1
and 5). Compared with the current situation, the N-surplus
per ha would drop by 22%, as the whole production
volume and corresponding demand for inputs is decreased.
GHG emissions would increase by 1%, or would drop by
5% by including deforestation and organic soils. This is due
protein supply (g per day)
40
60
80
100 0.16
0.14
0.12
protein/energy ratio (4*g protein/kcal)
0.10
0.08
100base year 80 60
0% livestock yield reduction, no climate change
0% livestock yield reduction, climate change
20% livestock yield reduction, no climate change
20% livestock yield reduction, climate change
40% livestock yield reduction, no climate change
40% livestock yield reduction, climate change
40 20 0
supply of food-competing feedstuffs to livestock in 2050 (% of base year)
Figure 4. Daily protein supply per person [g protein per person per day] and protein/calorie ratio in the base year, the reference scenario for 2050 and with
reduction of food-competing feedstuffs (global averages). Filled triangles, protein supply; filled circles, protein/energy ratio. Black symbols: base year.
water use
non-renewable energy demand
greenhouse
gas emissions
P-surplus
N-surplus
base year 2005 –2009
reference scenario 2050
reference scenario 2050 considering climate change
0% food-competing feedstuffs 2050
0% food-competing feedstuffs 2050 considering climate change
soil erosion potential
annual deforestation
potential
arable land
occupation
60 80 100 120 140 160 180 [%]
pesticide
use
Figure 5. Change of environmental pressures resulting from a reduction in food-competing feedstuffs relative to the base year [%]. Solid lines: negative impact of
CC on yields absent; dashed lines: CC impact present. Black: base year; blue: reference scenario (same level of food-competing feedstuffs use assumed for 2050); red:
0% food-competing feedstuffs. Black whiskers: range from 0% to 40% animal yield reduction.
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7

Table 2. Daily intake of main food categories per person (fresh matter, primary crop equivalents, global average) in the base year, the reference scenario and in scenarios with reduced food-competing feedstuffs (no climate change
impacts on yields, 20% yield reduction in livestock due to reduction in food-competing feedstuffs use, cf. Methods).
food types (PPE)
a
unit
b
base year
(2005– 2009)
supply of food-competing feedstuffs to livestock in scenarios
for 2050 [% of base year] difference of 0% food-
competing feedstuffs
scenario to base
year (%)
difference of 0% to
100% food-competing
feedstuffs scenario (%)100% 80% 60% 40% 20% 0%
plant products g/(cap*day) 1442 1484 1495 1507 1512 1509 1499 4 1
grains g/(cap*day) 519 499 531 555 570 577 575 11 15
starchy roots g/(cap*day) 185 193 201 207 212 214 212 15 10
oil crops g/(cap*day) 74 104 96 90 84 79 73 21230
legumes g/(cap*day) 42 52 69 89 112 140 177 317 242
vegetables g/(cap*day) 343 295 278 263 248 231 213 238 228
fruits g/(cap*day) 210 260 243 228 215 201 187 211 228
sugars and sweeteners
c
g/(cap*day) 65 78 73 70 66 63 60 28223
others
d
g/(cap*day) 5 4 44433239 229
livestock products g/(cap*day) 425 484 400 336 283 239 201 253 258
milk g/(cap*day) 242 274 237 207 181 158 138 243 250
meat g/(cap*day) 110 136 101 75 54 38 26 277 281
non-ruminants meat g/(cap*day) 77 97 68 46 29 16 7 291 293
ruminants meat g/(cap*day) 34 39 33 29 25 22 19 243 250
fish g/(cap*day) 50 48 44 41 39 37 35 230 227
eggs g/(cap*day) 23 26 19 13 8 5 2 290 291
all products g/(cap*day) 1867 1968 1896 1843 1794 1747 1701 29214
total energy availability kcal/(cap*day) 2763 3028 3028 3028 3028 3028 3028 10 0
total protein availability g CP/(cap*day)
e
77 82 79 78 77 77 78 1 25
animal protein/total protein (%) ratio 34 38 31 24 19 15 11 267 270
energy from proteins/total
energy
ratio 0.111 0.108 0.104 0.103 0.102 0.102 0.103 2825
a
PPE, primary product equivalents.
b
Cap, person.
c
Raw sugar equivalents.
d
Mainly treenuts, stimulants and spices.
e
CP, crude protein.
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8

to a drastic reduction in animal numbers and manure quan-
tities, as well as in total N-fertilizer quantities needed. It is
important to point out that owing to the focus on grassland
feed, the number of ruminants is reduced much less than
the number of monogastrics (figures 1 and 3), and that the
effect of reduced emissions from enteric fermentation is
thus less prominent than it would be in a strategy that
would predominantly aim at reducing ruminants to reduce
emissions from enteric fermentation. We also note that we
did not include atmospheric N-deposition in the calculations.
Given that animal husbandry and mineral fertilizers account
for a large share of NH
3
emissions as the key source for
N-deposition [49], we thus rather underestimate how the
reduction of FCF affects the N-surplus, as these sources are
also correspondingly lower. Deforestation pressure is
reduced by 21% compared with the base year, which reflects
the reduced land demand already reported above. The other
environmental impacts besides water use are lower than in
the base year, driven by the reduced production volumes,
animal numbers and cropland areas. Freshwater use still
increases by 25% owing to the increase in the share of
irrigated areas (figures 1 and 5).
How environmental impacts change as a result of climate
change effects on yields is also displayed in figure 5. Gener-
ally, the environmental impacts in the 0%FCF scenario are
still smaller than in the reference scenario, but the relative
advantages decrease if climate change impacts are included
(electronic supplementary material,§1.4).
4. Discussion and conclusions
4.1. Creating synergies between enhanced food
availability and reduced environmental impact
A continuation of current food consumption and production
trends, as forecast in Alexandratos & Bruinsma [8], increases
per capita food availability until 2050. However, food avail-
ability in that scenario hinges on large yield increases over
the next 40 years, with environmental impacts projected to
increase substantially. If projections of climate change effects
and natural limitations on yields are considered, then agricul-
tural land areas would have to increase drastically to meet the
forecast demand for 2050 (figure 2).
Livestock production with lower shares of FCF would
generate synergies between increased food availability and
reduced environmental impacts. Our exploration of the
impacts of a consistency strategy with 0%FCF shows that
reduction in land use and emissions can be realized, albeit
with significant changes in people’s diets, as well as
changes of the role of livestock. It would avoid drastic
increases in the demand for agricultural land area, in
particular if more pessimistic yield forecasts under climate
change transpire.
The results of our study are not to be understood as fore-
casts but as explorations of possible long-term futures. It is
important to note that the results of this study are subject
to uncertainties, stemming from known data flaws or lacking
data, particularly for smaller countries and developing
countries. Therefore, extrapolation of some datasets is un-
avoidable, and uncertainties of future trends that are not
included in the model, for instance the share of renewable
energies in country-specific energy mixes, demand for
biofuels or potential new technologies such as cultured
meat, evolve. However, because we use the model at global
level and model only fundamental changes in food systems,
the general trends of our results are meaningful, as shown
in the uncertainty analysis (see electronic supplementary
material). Such an exploration of possible long-term futures
is required, as fundamental changes in the food system will
not be feasible within the timeframe of only one decade.
4.2. Implications of the strategy with reduced food-
competing feedstuffs for livestock production
Advocating reduced grass-based production of ruminants
and enhanced use of concentrates, which contain human-
edible feedstuffs, for both ruminants and monogastrics is
not the only strategy to achieve sustainable intensification.
Here, we show that a consistency strategy which reduces
FCF is a viable alternative. Such a strategy could combine
the advantages of breeding, veterinary health measures and
feed management, with a strategy that aims at reducing the
amount of cropland-derived feedstuffs, to thus alleviate
land-use competition [50].
Ruminants have been the focus of sustainability discus-
sions because of the large CH
4
emissions from enteric
fermentation [1,3]. Roughage-fed ruminants could, however,
play an important role for food security, as they allow the
use of resources that are otherwise not, or only barely,
usable for food production, as is the case with most global
grasslands [23]. Therefore, in the scenarios with 0%FCF, the
number of monogastrics is reduced much more than the
number of ruminants, and roughage-fed ruminants still pro-
vide an important source of protein. We show that a food
system with ruminant- and grassland-based animal products
can provide enough food while reducing environmental
impacts. Furthermore, grasslands can contain large carbon
stocks and can provide many ecosystem functions [24]: much
of which would be lost if grassland were converted to arable
land [51– 53]. An important challenge to the livestock feed
industry will be to further improve the use of agricultural resi-
dues, agro-industrial by-products and waste material to
produce high-quality feedstuffs [54,55], where reuse is a far
better option than landfilling, incineration, composting or
anaerobic digestion.
4.3. From modelling production systems to modelling
food systems
While most studies concentrate either on production issues
[16] or consumption patterns [15,30], this assessment empha-
sizes the importance of considering the nexus between
agricultural production patterns and systems with food con-
sumption. Thus, it links the discussion of sustainable food
production and sustainable food consumption and can be
used to assess integrative strategies that have an impact
on both resource efficiency of production and the availability
of certain foodstuffs. We show that despite roughage-
fed beef or milk having a higher carbon footprint than
products from intensive, concentrate-fed cattle systems, or
even pig and poultry, the scenario with 0%FCF results in a
more sustainable food system than the reference scenario
based on business-as-usual projections, as losses in resource
efficiency are more than offset by the beneficial effects of
reducing feed production on arable land. This perspective
rsif.royalsocietypublishing.org J. R. Soc. Interface 12: 20150891
9

of connecting efficiency and consumption strategies can
complement existing life cycle assessments and economic
modelling approaches [56].
The scenarios we have investigated would necessitate
dietary change; namely reduced consumption of animal pro-
ducts, with particular reductions in pig and poultry meat,
and eggs. This is viable from a physical and food availability
point of view and would also yield other benefits, primarily
related to human health [57]. High consumption of livestock
products has been linked to non-communicable and chronic
diseases, and obesity [29]. The societal acceptability of such
dietary change is not well understood, but is clearly key to
any successful implementation of such a strategy [19], and
likely remains challenging [58].
While other studies examining the impacts of changing
food consumption patterns concentrated on the reduction of
ruminant production or on livestock products in general,
this study provides insights into the relative benefits of
roughage-fed meat and milk over other livestock products
from the perspective of sustainable consumption. We have
shown that in such a scenario, the reduction in consumption
of monogastric livestock products would be much more dras-
tic than for ruminant meat. Thus, there are alternatives to the
frequently suggested replacement of ruminant with mono-
gastric meat, which is based on carbon footprints or
attributional life cycle assessments of single products that
do not consider the limited availability of arable land and
the utilization of grasslands.
Our scenarios are based on nutrient balances and assess-
ments of the physical and technical viability of different food
production scenarios and global food system scenarios that
have not previously been captured in global land-use
models. This provides important insights concerning the
physical viability and environmental effects of these food
system scenarios. However, to assure food security, access
to food, stability and utilization also need to be addressed
in addition to food availability [14].
Reducing the amount of human-edible crops that are fed
to livestock represents a reversal of the current trend of steep
increases in livestock production, and especially of monogas-
trics, so would require drastic changes in production and
consumption. Achieving such drastic changes is a huge chal-
lenge for society. Policy measures on both the supply and
demand sides would be required to assist such structural
change necessary to prevent potential future crises for food
availability, the environment and human health [15,50].
Long-term and global ex ante impact assessments, such as
that presented here, are essential to inform the scientific
debate and to provide a basis for informed decision-making.
Clearly, to decide on specific policy measures and
implementation options for these strategies, physical
models that assess the principal viability and impacts need
to be complemented with economic models to take
market effects on demand and supply into account [59].
Such economic assessment is, however, beyond the scope of
this study.
Ideally, elements of all proposed strategies may best be
combined to achieve sustainable food systems, complement-
ing increased efficiency with reduced meat consumption
and changed livestock feeding patterns towards less
human-edible crops and feed from arable land. Such a com-
bination would avoid the need to pursue one strategy to
very high levels of implementation, that are likely expensive
and unrealistic, but a combination of strategies, each
implemented at intermediate levels may be promising. The
contribution of this paper is to show that a consistency strat-
egy with 0% FCF can play a significant role in such a
combination of complementary strategies, on par with the
other previous suggestions.
Data accessibility. All data and modelling code are accessible as .gms and
.gdx files at ftp://paper.fibl.ch (username: Paper; password:
þpAp!er-2).
Authors’ contributions. C.S., A.M. designed the research, collected data,
programmed the model and wrote the paper, E-H.S., K-H.E.
designed the research, collected data and wrote the paper, J.H. col-
lected data and programmed the herd structure submodel and
contributed to writing the manuscript, A.I collected data and
designed the animal feed research part and contributed to writing
the manuscript, P.S. designed the research and wrote the paper,
H.M designed the research and wrote the paper, P.K. collected data
and designed the animal feed research part and contributed to writ-
ing the manuscript, F.L. collected data, designed the animal feed
research, designed the graphs and wrote the paper, P.S. collected
data and designed the environmental impact research part and com-
mented the paper, M.S., U.N. designed the research and wrote the
paper. All authors gave final approval to the manuscript.
Competing interests. We declare we have no competing interests.
Funding. Christian Schader, Adrian Muller, Nadia El-Hage Scialabba,
Judith Hecht, Anne Isensee, Harinder P.S. Makkar, Peter Klocke,
Florian Leiber, Matthias Stolze, Urs Niggli thank FAO for funding
this research. K.E. gratefully acknowledges funding from ERC-
2010-Stg-263522 LUISE. Additional data and method details are pro-
vided in the supplementary materials. The contribution of P.S. is
supported by funding from the Belmont Forum-FACCE-JPI Project
‘Delivering Food on Limited Land’ (DEVIL), with the UK
contribution supported by NERC (NE/M021327/1).
Acknowledgements. The authors are grateful for the inputs, data and
ideas in support of this study by the following experts: Caterina
Batello, Jan Breithaupt, Carlo Cafiero, Marianna Campeanu, Renato
Cumani, Rich Conant, Piero Conforti, Luming Ding, Marie-Aude
Even, Karen Frenken, Andreas Gattinger, Pierre Gerber, Helmut
Haberl, Frank Hayer, Robert Home, Jippe Hoogeveen, Stefan
Ho
¨rtenhuber, Mathilde Iweins, John Lantham, Holger Matthey,
Robert Mayo, Dominique van der Mensbrugghe, Eric Meili, Soren
Moller, Jamie Morrison, Alexander Mu
¨ller, Noemi Nemes, Monica
Petri, Tim Robinson, Nicolas Sagoff, Henning Steinfeld, Francesco
Tubiello and Helga Willer. We furthermore thank Thomas Fritschi
for designing figure 1. Finally, we want to thank the two referees
that provided very detailed comments that contributed much to
improve the manuscript.
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