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FAO ANIMAL PRODUCTION AND HEALTH
working paper
MAPPING
SUPPLY AND DEMAND FOR
ANIMAL-SOURCE FOODS
TO 2030
ISSN 2221-8793
2
Cover photographs:
Left image: FAO/Giuseppe Bizzarri
Centre image: FAO/Noel Celis
Right image: FAO/Giulio Napolitano
2
FAO ANIMAL PRODUCTION AND HEALTH
working paper
MAPPING
SUPPLY AND DEMAND FOR
ANIMAL-SOURCE FOODS
TO 2030
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS
Rome, 2011
Recommended Citation
FAO. 2011. Mapping supply and demand for animal-source foods to 2030, by T.P. Robinson & F. Pozzi.
Animal Production and Health Working Paper. No. 2. Rome.
Keywords
Livestock commodities; growth; consumption; demand; production; mapping; geographic information systems;
projections; population; livelihoods; animal-source foods; consumption; production; projections; mapping; global;
supply and use accounts.
Authors’ details
Timothy Robinson works for FAO’s Livestock Information, Sector Analysis and Policy Branch (AGAL), where he
is responsible for the development of livestock information systems. This includes the mapping and analysis of
livestock distributions and production systems, and exploring the social, environmental, animal and public
health outcomes of the livestock sector.
Francesca Pozzi conducted this work as a consultant to the PPLPI. Her research interests focus on population
and poverty mapping and the spatial analysis of environmental and socio-economic correlates.
The designations employed and the presentation of material in this
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nature that are not mentioned.
The views expressed in this information product are those of the author(s) and
do not necessarily reflect the views of FAO.
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© FAO 2011
Table of contents
List of tables and figures
iv
Acknowledgments
v
Preface
vi
Abbreviations
vii
Executive summary
viii
Introduction1
Thirty years into the livestock revolution
World population projections
World income projections
The livestock sector
3
3
4
5
Methods7
Human population distribution
7
Livestock distribution
8
Projected production and consumption of livestock commodities
10
Mapping changing consumption of livestock commodities
12
Mapping changing production of livestock commodities
13
Mapping production surpluses/deficits
15
Standardising consumption of animal-source foods
15
Results16
Discussion and conclusions
27
References32
Annex A
Countries and country groupings
36
Annex B
Global maps of growth in demand for livestock commodities
from 2000 to 2030
42
Annex C
Consumption and production of livestock commodities
in 2000 and 2030
48
Annex D
Consumption of livestock commodities by city
125
iii
List of tables and figures
TABLES
1. Generic list of variables used in livestock distribution modelling. 9
2 Livestock commodities included in the FAO projections. 11
3 Livestock commodities included in the FAO projections and livestock
species available from the GLW databases.
14
4 Growth in demand for livestock products from 2000 to 2030.
20
5 Growth in per-capita demand for livestock products from 2000 to 2030.
21
FIGURES
1 Production, consumption and production surplus of beef in 2000;
consumption in 2030 and growth in demand from 2000 to 2030 in Africa.
17
2 Growth in demand for poultry meat from 2000 to 2030 in Asia.
18
3 Growth in demand for poultry meat from 2000 to 2030 in Central America. 18
4 Growth in demand for pork and milk from 2000 to 2030 in Latin America.
19
5 Demand growth for poultry meat in China and India from 2000 to 2030.
22
6 Demand growth for milk in Kenya from 2000 to 2030, disaggregated by
rural and urban areas.
23
7 Global, projected consumption of protein from animal-source foods in 2030.
24
8 Proportional consumption of protein from animal-source foods, broken down
by the six major livestock commodity groupings, in 2000 and 2030.
25
iv
Acknowledgments
The authors would like to acknowledge the support and collaboration offered by
Jelle Bruinsma, who has kindly provided the data on livestock projections and made
valuable contributions to the analysis. The authors would also like to thank Giulia
Conchedda, who has assisted with the data preparation for the tables and maps, and
Gregory Yetman, who provided the updated version of Global Rural-Urban Mapping Project (GRUMP) data, and the urban extent data used in this analysis.
Valuable suggestions for analysis and comments on the paper were received from
Joachim Otte and Henning Steinfeld.
Francesca Pozzi, Claudia Ciarlantini and Carmen Hopmans are acknowledged
for the design, layout and formatting of the working paper.
v
Preface
Around 2.6 billion people in the developing world are estimated to have to make a
living on less than $2 a day and of these, about 1.4 billion are ‘extremely’ poor; surviving on less than $1.25 a day. Nearly three quarters of the extremely poor – that is
around 1 billion people – live in rural areas and, despite growing urbanization, more
than half of the ‘dollar-poor’ will reside in rural areas until about 2035. Most rural
households depend on agriculture as part of their livelihood and livestock commonly form an integral part of their production system. On the other hand, to a large
extent driven by increasing per capita incomes, the livestock sector has become one
of the fastest developing agricultural sub-sectors, exerting substantial pressure on
natural resources as well as on traditional production (and marketing) practices.
In the face of these opposing forces, guiding livestock sector development on a
pathway that balances the interests of low and high income households and regions
as well as the interest of current and future generations poses a tremendous challenge to policymakers and development practioners. Furthermore, technologies are
rapidly changing while at the same time countries are engaging in institutional ‘experiments’ through planned and un-planned restructuring of their livestock and related industries, making it difficult for anyone to keep abreast with current realities.
This ‘Working Paper’ Series pulls together into a single series different strands
of work on the wide range of topics covered by the Animal Production and Health
Division with the aim of providing ‘fresh’ information on developments in various
regions of the globe, some of which is hoped may contribute to foster sustainable
and equitable livestock sector development.
In 2006 the FAO Global Perspective Studies Unit revised their estimates of
prospective developments in food demand and consumption to 2030/2050 (FAO,
2006b). In this paper we take the estimates of supply and demand for animal-source
foods and disaggregate them spatially for the years 2000 and 2030. By so doing we
are able to present detailed maps and tables of change in supply and demand that are
of direct use to researchers and decision makers in the livestock sector.
vi
Abbreviations
AGAL
CAST
CIAT
CIESIN
ESRI
FAO
FCR
GAUL
GDP
GHG
GIS
GLIMS
GLW
GPW
GRUMP
HPAI
IMF
LDPS-2
LGP
NRC
ORNL
SUA
UN
FAO Livestock Information, Sector Analysis and Policy Branch
Council For Agricultural Science And Technology
Centro Internacional de Agricultura Tropical
Center for International Earth Science Information Network
Environmental Systems Research Institute (Redlands, California)
Food and Agriculture Organisation
Feed conversion ratios
Global Administrative Unit Layers
Gross Domestic Product
Greenhouse Gas
Geographic Information System
Global Livestock Impact Mapping System
Gridded Livestock of the World
Gridded Population of the World
Global Rural and Urban Mapping Project
Highly Pathogenic Avian Influenza
International Monetary Fund
Livestock Development Planning System Version 2
Length of Growing Period
National Research Council
Oak Ridge National Laboratory
Supply Utilisation Accounts
United Nations
vii
Executive summary
Livestock is one of the fastest-growing sectors in agriculture, potentially presenting
opportunities for economic growth and poverty reduction in rural areas, though
unless carefully managed the main social effects may be negative – if the livestockdependent poor are squeezed out of markets and are presented with few viable livelihood alternatives. There may be other negative outcomes to sector growth. A matter for recent concern has been the contribution that livestock make to greenhouse
gas (GHG) emissions, for example, and there are public health implications of livestock production: the rapid spread of infectious diseases, typified by the recent and
ongoing H5N1 avian influenza panzootic and the pandemic (H1N1) influenza A
crisis, demonstrates the magnitude of problems arising from the emergence of novel
diseases at the animal-human-ecosystems interface. Dealing with these important
social, environmental and public health issues will require solutions that embrace
the way in which the livestock sector grows to meet the increasing demand.
Given these important externalities to rapid livestock sector growth, it is important to understand where growth in demand for livestock commodities is likely to
occur, and how and where production of livestock commodities will be increased
in order to meet it.
Estimates of supply and demand for animal-source foods, provided by the Global Perspective Studies Unit at FAO, have been disaggregated spatially for the years
2000 and 2030. Demand for animal-source foods was mapped by estimating percapita consumption and applying this to mapped population distributions in 2000.
Population maps were produced for 2030 based on projected population growth
and urbanisation rates and future estimates of per-capita demand applied to these.
Similarly, livestock production maps were produced by spatially disaggregating the
estimated production based on maps of the relevant livestock species. This has resulted in detailed maps and tables of change in supply and demand from 2000 to
2030 that are freely available to be downloaded from the Gridded Livestock of the
World website (www.fao.org/ag/againfo/resources/en/glw/home.html).
The disaggregation of demand growth in this way allows distinctions to be made
a) between growth arising from population growth, as compared to that arising
from changing consumption patterns, and b) between urban and rural growth, with
urban growth being explicitly linked to the major urban centres.
The results show that by far the most dramatic change is the projected increase
in demand for poultry meat in South Asia; a 725 percent increase overall. This is
driven by growth in demand in India where a staggering 850 percent increase is
projected over the 30 year period (from 1.05 to 9.92 million tonnes, annually). They
also show that the vast majority of growth in most areas is caused by increasing
per capita consumption rates rather than by increasing population levels. In India, for example if consumption rates of poultry meat remained constant to 2030
only 5 percent of the projected growth would occur; whilst, even if the population
size remained static 69 percent of the demand growth would still occur, driven by
changing food consumption patterns. The results also highlight the importance of
urbanisation in growth patterns; taking again the example of poultry meat in India,
the relative increase in demand from the urban areas from 2000 to 2030 is 1 277
percent, almost twice that in the rural areas (677 percent).
viii
The implications of these patterns of growth in demand for animal-source foods
lie in structural changes to the livestock sector: there will need to be a rapid intensification of production in some areas accompanied by value chain development
linking production zones with consumption centres. The maps of demand growth
presented here can help identify where intensification of production is likely to occur in the coming decades.
Whilst the methodology can be improved in numerous ways, most importantly
in linking production explicitly to production systems, the resulting maps and databases can be of direct use to researchers and decision makers in the livestock sector;
through analysis of the social, environmental and animal and public health impacts
of rapid growth and intensification in livestock production.
ix
Introduction
The recently published flagship publication of the Food and Agriculture Organisation (FAO): ‘Livestock in the balance’ (FAO, 2010a) points to continuing growth
of the livestock sector, stating that: ‘Decisive action is required if increasing demand
is to be met in ways that are environmentally sustainable and contribute to poverty
alleviation and improved human health’.
Driven by population growth and increasing incomes, the demand for animalsource foods in developing countries is growing rapidly, while urbanisation leads
to demand becoming highly concentrated. Up to a point of saturation, a more affluent population uses a proportional, or even increasing proportion of its growing
income on animal-source foods. Economists describe this in terms of income elasticity. In China, for example, income elasticity for meat is about 1 percent and that
for milk is about 1.2 percent. This means that for every percentage point increase
in income, expenditure on meat and milk will increase by 1 and 1.2 percent, respectively (World Bank, 2005).
Livestock is one of the fastest-growing sectors in agriculture, presenting potential opportunities for economic growth and poverty reduction in rural areas. Current estimates (Robinson et al., in press) are that 766 million poor people (< US$ 2
per day) keep livestock. Livestock sector growth could directly benefit these, and
others who are less immediately linked to the livestock sector. The social and economic benefits of this increase in demand include the sector’s potential contribution
to economic growth, especially in economies where agriculture contributes significantly to Gross Domestic Product (GDP), possibly creating market opportunities
for the livestock-dependent poor, and improvements in food security and nutrition.
But positive social outcomes of sector growth may not be ubiquitous. There is
also a risk that smallholders dependent on livestock for their livelihoods may be
squeezed out of the sector as production intensifies and becomes geographically
concentrated. Beyond possible social problems are environmental and public health
issues that are likely to be associated with rapid, poorly regulated sector growth.
There has been considerable debate of late about the contribution that livestock
make to greenhouse gas (GHG) emissions. Published estimates range from 18 percent of annual worldwide GHG emissions (FAO, 2006a) to 51 percent (Goodland
and Anhang, 2009). These estimates include the effect of deforestation and other
negative land use changes that can arise as a result of increasing livestock production. Other negative environmental effects include land degradation (e.g. from
overgrazing), loss of biodiversity and pollution from effluents (FAO, 2006a).
Regularly making the news headlines are some of the public health consequences
of rapidly increasing livestock production. The spread of infectious zoonotic and
non-zoonotic diseases, typified by the recent and ongoing H5N1 avian influenza
panzootic and the pandemic (H1N1) influenza A crisis, demonstrates the magnitude of such problems. Dealing with the staggering human and animal disease burden that persists in the developing world and the continual emergence of novel
diseases at the animal-human-ecosystems interface require solutions that embrace
the way in which the livestock sector grows to meet increasing demand.
Understanding where growth in demand for specific livestock commodities is
likely to occur, and where production will rise to meet this increasing demand, are
1
Mapping supply and demand for animal-source foods to 2030
therefore important for a number of reasons.
In 2003 the Global Perspective Studies Unit of the Food and Agriculture Organisation (FAO) published the report ‘World Agriculture: Towards 2015/2030’ (Bruinsma, 2003). The study presented prospective developments in food demand and
consumption and possible implications for nutrition and under-nourishment. Since
the publication of that study, estimates of population growth have been revised
considerably and the world energy markets have become increasingly tight. High
energy prices affect the food and agriculture sectors in many ways, with, for example, direct increases in the costs of inputs and of transporting agricultural products,
and the more complex interactions that result from an increased use of agricultural
land to produce biofuels. For these and other reasons FAO has revised and extended the 2015/2030 estimates to 2030/2050 (FAO, 2006b).
These new estimates present the possibility of mapping changing demand for
livestock products, and possibly the associated changes in production that will be
required to meet that demand growth.
In this paper we first provide an overview of demographic and economic changes
in the world that are influencing the livestock sector. The following section describes the methodological approaches to mapping human and livestock populations, provides a summary of how the FAO projections are made (focussing on
livestock commodities), and describes how these can be combined to map projected
demand for and supply of livestock commodities. The results section presents some
examples of the outputs of the analysis and the concluding section mentions some
ways in which the methodology might further be developed in the future, and discusses some implications and potential uses of the results.
Detailed maps and tables of projected change in supply and demand for animalsource food, disaggregated in a number of ways, are provided in the Annexes.
2
Thirty years into the livestock revolution
Since the late 1970s, increasing population, growth in per-capita GDP and urbanization have combined to boost demand for animal-source foods in developing
countries – a phenomenon that has been termed the ‘livestock revolution’ (Delgado
et al., 1999). With livestock contributing to the livelihoods of some 42 percent of
the world’s poor (Thornton et al., 2002), this growth in demand has been widely
attributed considerable potential for poverty reduction.
Delgado et al. (1999) described the transformation in demand for animal-source
foods that occurred in the 1980s and early 1990s. They reported that during this period, the total amount of meat consumed in developing countries grew at three times
the rate of that in the developed countries, and they predicted this growth to continue
at a rate of 2.8 percent for meat and at 3.3 percent for milk in the developing countries
up to 2020. During the past 10 years, much of the forecast increase in demand has occurred, but in a rather patchy manner. China and Brazil in particular have witnessed
massive increases in demand for and production of livestock products, but sub-Saharan Africa has for the most part been virtually stagnant, with the possible exceptions
of milk in Kenya and poultry in South Africa. It would appear that economic growth
must accompany population growth if the ‘revolution’ is to occur.
world population projections
The population of the world was estimated at 6.8 billion in 2009, with 5.6 billion
(or 82 per cent of the world’s total) living in the less developed regions (UN, 2009).
Current estimates are that the population will grow to 9.1 billion in 2050, with most
of the growth occurring in developing countries (UN, 2009).
According to the United Nations (UN) long-term projections, the world population will reach its peak in 2075, at 9.2 billion, then decline slightly and increase
again to reach a second peak of 9 billion by 2300 (UN, 2004). To project future population the UN Population Division makes assumptions regarding future trends in
fertility, mortality and international migration. This pattern of rise, decline, and rise
again results from these assumptions on vital rates: that, country by country, fertility will fall below replacement level and eventually return to replacement; and that,
country by country, life expectancy will eventually follow a path of uninterrupted
but slowing increase.
However, with alternative, plausible assumptions about fertility, long-range
trends could be quite different, so a number of projection variants is produced, to
deal with uncertainties of making projections into the future. For example, with
long-range total fertility of 0.3 children above replacement, projected world population in 2300 is four times as large as the main projection; with total fertility of 0.2
children below replacement, world population in 2300 is one-quarter of the main
projection (UN, 2004).
The projected population trends also depend on sustained progress in HIV/
AIDS prevention and treatment. Although a growing number of the countries that
are most affected by the epidemic is reaching and maintaining lower prevalence
levels, in countries where the prevalence has been high the impact of the epidemic is
still evident and, in these countries, the growth rate is expected to continue declining.
3
Mapping supply and demand for animal-source foods to 2030
Based on these assumptions, the UN estimates that the populations of 30 countries, most of which are categorised as least developed, will at least double between
2010 and 2050, according to the medium variant. In contrast, the population of the
more developed regions is expected to change minimally, passing from 1.23 billion
to 1.28 billion, and would actually decline to 1.15 billion were it not for the projected net migration from developing to developed countries (UN, 2004).
An important issue in population growth is the distribution and the growth of
urban areas. According the 2007 World Urbanization Prospect, the population living in urban areas is projected to rise from 3.3 billion in 2007 to 6.4 billion 2050.
Globally, the level of urbanization is thus expected to rise from 50 percent in 2008
to 70 percent in 2050 (UN, 2008).
There is considerable diversity in the levels of urbanization in different regions.
While 74 percent of the inhabitants of more developed regions lived in urban areas
in 2007, just 44 percent of those in the less developed regions did so. Urbanization
is expected to continue rising in both the more developed and the less developed regions so that, by 2050, urban dwellers will account for 86 percent of the population
in the more developed regions and for 67 percent in the less developed regions (UN,
2008). Among the less developed regions, Latin America and the Caribbean have
exceptionally high levels of urbanization (78 percent), while Africa and Asia retain
larger shares of rural inhabitants. Over the coming decades, however, the level of
urbanization is expected to increase in all major areas of the developing world, with
Africa and Asia urbanising more rapidly than the rest.
Furthermore, the urban population is distributed unevenly among urban settlements of different size. Despite their visibility and dynamism, mega-cities (defined
as a metropolis with a population greater than 10 millions) account for a small proportion of the world’s urban population: about 9 percent in 2007. This proportion
is expected to rise to almost 10 percent in 2025. Mega-cities account today for only
4 percent of the global population. In contrast, over half of the urban population
lives and will continue to live in small urban centres, with fewer than half a million
inhabitants (UN, 2008).
world income projections
Forecasting national incomes, in terms of GDP, presents even more challenges than
projecting population, given the uncertainties and instabilities of markets and financial systems. The International Monetary Fund (IMF) regularly produces shortterm future estimates of GDP and economic growth. Global growth, for example,
is projected to reach 3.1 percent in 2010, following a contraction in activity of 1.1
percent in 2009. By 2014, global growth is forecast to have reached 4.5 percent
(IMF, 2009).
The World Bank also regularly produces future estimates of national GDP and
per-capita GDP over a 5-year period, along with poverty forecasts. For example,
per-capita GDP in developing countries over the period from 2010 to 2015 is expected to expand at a relatively rapid annual pace of 4.6 percent, much faster than
the 2.1 percent pace of the 1990s (World Bank, 2009). Producing robust forecasts of
GDP and economic growth more than about 5 years into the future is challenging,
however, due to the vagaries of markets and financial systems.
Notwithstanding these difficulties the World Bank has produced some medium-
4
Thirty years into the livestock revolution
to long-term projections of GDP. At assumed growth rates in per-capita GDP of 2
percent in high income countries (which is the average over the past 20 years) and
3.3 percent in low- and middle-income countries (an optimistic figure, representing the growth experienced in the 1960s and 1970s), world income in 2050 would
be more than US$ 135 trillion, up from US$ 35 trillion today (World Bank, 2006b).
At these rates, the total GDP in 2050 of today’s developing countries will be twice
that of industrial countries today. Whilst expected GDP growth in the developing
regions may sound promising in terms of meeting basic human needs for food and
shelter, poverty could still increase significantly in a number of developing economies; notably in sub-Saharan Africa, where per-capita GDP contracted in 2009 for
the first time in a decade (IMF, 2009).
the livestock sector
Overall growth in agricultural production is slowing down, and is expected to continue to do so as a consequence of the slowdown in population growth, in spite of
the fact that levels of food consumption are likely to increase. Notwithstanding a
slowing in the growth rate of the population, agricultural production will need to
increase by 70 percent (nearly 100 percent in developing countries) by 2050 to cope
with a 40 percent increase in world population and to raise average food consumption to 3 1301 kcal per person per day. Bruinsma (2009) provides some estimates
of the additional crop and livestock production that would be needed to meet this
increase in demand for food; an additional billion tonnes of cereals, for example,
and 200 million tonnes of meat would need to be produced annually by 2050, as
compared with production in 2005/07.
For the livestock sector, this raises important questions: Where will that meat be
consumed? Where and how will it be produced? What will be the economic, social,
environmental and public health outcomes of that increased production?
Whilst overall production must increase to meet the increasing demand it is projected that there will be a deceleration in growth of meat production and consumption, though the milk sector is expected to continue to grow, mainly because of
growth in demand in developing countries (FAO, 2006b). Meat consumption in
China grew massively from an annual average of 9 kg per person to more than 50
kg per person in the space of 30 years. Consumption in the rest of the developing
world, which now averages a modest 16 kg per person, still has considerable potential for growth, considering that per-capita consumption could easily double by
2050.
In developing countries, where most of the global growth in population occurs,
meat consumption has grown at over 5 percent per annum during recent decades,
and milk consumption at nearly 4 percent per annum – but these impressive growth
figures have been driven largely by China and to some extent Brazil. FAO (2006b)
reported the average meat consumption in industrial countries to be around 90 kg
per person per year (in 2000); 26 developing countries had an average consumption
rate under 10 kg, and a further 30 had average consumption rates of between 10 and
20 kg. Of these 56 countries, 23 consumed less meat per capita on average than they
had 10 years before.
1
2 200 kcal per person per day is considered to be the minimum required food energy intake (SPHERE, 2004).
5
Mapping supply and demand for animal-source foods to 2030
If the consumption figures for China are removed from the equation, the growth
rate for world meat consumption of 2.9 percent per annum seen in the 1990s is
halved. The livestock revolution described by Delgado et al. (1999) is not a ubiquitous phenomenon, largely because of the much slower development and income
growth in many countries. On top of that, growth in meat consumption is and will
continue to be moderated by cultural factors in some very large developing economies – for example the consumption of beef in India and pork in Muslim countries.
By far the largest proportion of livestock sector growth in recent years is attributable to the poultry sector, which has consistently grown at more than 5 percent
per annum since the 1960s. Its share in world meat production doubled from 15
percent thirty years ago to 30 percent in 2000. Growth and an increased share in
overall meat consumption have also been seen in pork, but ruminant meat consumption has actually been on the decline. Further details of the more recent trends
in consumption and production of animal-source foods can be found in numerous
publications: FAO (2008), Bruinsma (2009) and Rae and Nayga (2010), to name a
few.
The Global Perspective Studies Unit at FAO has an on-going programme to
estimate current demand for and production of agricultural commodities, and to
project these into the future (Bruinsma, 2003; FAO, 2006b). In the next section we
summarise how this is done and describe a methodology to map these estimates and
projections.
6
Methods
The approach taken here to map consumption of livestock commodities essentially
involves taking the FAO estimates of consumption and mapping these, based on the
distribution of people. The analysis is constrained by the level of disaggregation of
the available data; which provides average consumption rates of livestock products
for each country. In reality we know that consumption rates for livestock commodities tend to be higher in the more affluent urban areas and amongst the wealthier
sectors of society in general. Production of livestock commodities can be mapped
in a similar way – disaggregating estimated production based on the distributions
of the relevant livestock species.
Below, we describe the data and methods used to map changing demand and supply of livestock commodities.
human population distribution
There are various estimates of current and future populations. The most widely
used come from the UN World Population Prospects (e.g. UN, 2009) and World Urbanisation Prospects (e.g. UN, 2008). These data include total population numbers
and the proportion of the population living in urban areas now and in the future.
Whilst the UN figures provide national totals there have been various projects to
disaggregate population data globally, the most important of which are the Landscan project (ORNL, 2008), the Gridded Population of the World (GPW) (CIESIN and CIAT, 2005) and the Global Rural and Urban Mapping Project (GRUMP)
(CIESIN et al., 2004).
Landscan provides the most up-to date, gridded (i.e. presented in geographic
information system (GIS) format as a raster layer), worldwide population database
and its population values are the result of a model that apportions census counts
(at sub-national level) to each cell of a 30 arc-second grid (about 1 km at the equator) according to likelihood coefficients. These coefficients are based on proximity
to roads, slope, land cover, night-time lights, and other information. The database
is updated annually by incorporating new spatial data and remotely sensed imagery, and the distribution algorithms are revised accordingly. Comparing different
versions of the dataset, cell by cell over time, therefore, may result in misleading
conclusions, and thus the data should not be used to infer change, for example as a
result of migration (ORNL, 2008).
GPW and GRUMP gridded data are derived from a simple proportional allocation gridding algorithm of national and sub-national level population data from as
close as possible to the time of the estimate. GPW data are available at a resolution
of 2.5 arc-minutes (about 5 km at the equator) for the years 1990, 1995 and 2000.
GRUMP has been developed to allow analysis of urban and rural population
figures based on a consistent global dataset. It does not provide future population
estimates, but it distinguishes urban and rural population taken from around the
year 2000, and also provides a map of urban extents, which was derived largely from
the night-time lights (Elvidge et al., 1997). GRUMP is available at the finer spatial
resolution of 30 arc-seconds (about 1 km at the equator). Details on the methodology and data sources are provided in Balk et al. (2004).
7
Mapping supply and demand for animal-source foods to 2030
Whilst future projections of national totals and rates of urbanisation of human
populations are readily available, there have been few attempts to map future human population distributions. One project implemented by the Center for International Earth Science Information Network (CIESIN) and FAO provides projected
populations to 2015 but no further (CIESIN et al., 2005)
livestock distribution
FAO has an ongoing programme to collate and disseminate sub-national livestock
statistics for the globe: the Global Livestock Impact Mapping System (GLIMS)
(Franceschini et al., 2009). Sub-national livestock statistics are collected from a variety of sources and geo-registered to digital administrative area boundaries, standardised to the Global Administrative Unit Layers (GAUL)2 system where possible. One of the products derived from GLIMS is the Gridded Livestock of the
World (GLW)3 (Robinson et al. 2007; FAO 2007a), which provides modelled distribution data in ESRI grid format for cattle, buffalo, sheep, goats, pigs, chickens
and other poultry. The map values are animal densities per square kilometre, at a
resolution currently of 3 arc-minutes (approximately 5 km at the equator) with
work in progress to upgrade this to a 1 km product (30 arc-seconds). These maps
are updated regularly using the method summarised below (and described in detail
in FAO, 2007a).
Firstly the best available sub-national data on livestock populations, at a range of
spatial resolutions depending on availability, are collected and standardised. These
are converted to densities, at the same time adjusting to account for the area of land
deemed suitable for livestock production, for example where satellite-derived vegetation indices indicate there to be insufficient grazing (for ruminant species); where
other features of land-cover, such as elevation and slope would preclude livestock
development; and where prevailing land-use would not permit livestock to occur,
such as in urban and protected areas.
The resulting suitability-adjusted livestock densities are then used to establish
robust statistical relationships between livestock densities and an extensive suite
of predictor variables, summarised in Table 1. Details and references to the data
sources are provided in Robinson et al. (2007) and FAO (2007a).
Since the predictors of animal densities are unlikely to be consistent from region
to region, or across different agro-ecological zones, models are developed separately for different regions and for different ecological zones defined empirically
by clustering (unsupervised classification) of remotely sensed climatic variables. A
series of stepwise multiple regression analyses is performed between the livestock
densities and the predictor variables and the best-fitting equations are then applied
back to the images of predictor variables to generate a map of modelled density for
each species. To avoid spurious predictions, the modelled total numbers for each
administrative unit are adjusted to equal those reported for a given administrative
unit. Further products are then generated, adjusting the modelled data so that national totals match FAO’s official national statistics for the years 2000 and 2005,
providing time-standardised datasets.
2
3
8
The Global Administrative Unit Layer (GAUL):
http://www.fao.org/geonetwork/srv/en/metadata.show?id=12691&currTab=simple
The Gridded Livestock of the World (GLW): www.fao.org/ag/againfo/resources/en/glw/home.html
Methods
Table 1. Generic list of variables used in livestock distribution modelling.
Generic type
Variables
Locational
Longitude, latitude
Anthropogenic
Distance to roads
Distance to city lights
Demographic
Human population
Topographic
Elevation
Land cover
Normalised difference vegetation index (NDVI)
Temperature
Land surface temperature
Air temperature
Middle-infrared
Water and moisture
Vapour pressure deficit
Distance to rivers
Cold cloud duration
Potential evapotranspiration
General climatic
Modelled length of growing period
Other
Tsetse distribution (for Africa)
Source: adapted from Robinson et al. (2007).
Following from livestock distribution maps, attempts have been made in some
parts of the world to map production of various livestock commodities. Livestock production and off-take rates vary across different agro-ecological zones and
livestock production systems, and in a broadly predictable way. Thus models for
livestock growth and off-take can be applied to the livestock distribution maps –
parameterised differentially for different zones or systems. For example, beef and
milk production and use of draught power in sub-Saharan Africa have been estimated by deriving annual output per head of cattle within each of seven major agroecological zones (FAO, 2002a and FAO, 2002b). These zones were defined and
mapped by combining a number of spatial variables (temperature, elevation, Length
of Growing Period (LGP) and crop type) in a decision tree. Livestock production
was modelled for each zone using the herd growth model within the Livestock
Development Planning System Version 2 (LDPS-2) (FAO, 1997). The herd models
were parameterised separately for each zone, based on available published data (for
some parameters, data were sparse). More recently meat and milk off-take maps
were re-evaluated for Africa using the updated GLW cattle distributions (Robinson
et al., 2007) and the Thornton et al. (2002) livestock production systems to stratify
production modelling (FAO, 2007a).
A number of attempts has been made to map future livestock populations. Herrero et al. (2008), for example estimated the distribution of African ruminant livestock in 2030 based on FAOSTAT trends applied to the GLW livestock distributions. A more sophisticated approach takes the outputs from global agricultural
sector models and makes the conversion from tonnes of livestock products back to
spatial distributions of livestock, again based on GLW (Rosegrant et al., 2009). Both
of these approaches involve pro-rata adjustments to current estimates, based on
GLW. A logical next level of sophistication would be to apply differential growth
rates for different livestock production systems. Such an approach has been taken
for cattle in West Africa (Shaw et al., 2006) and, more recently, in East Africa (FAO,
in press; Wint et al. 2011) with the specific purpose of mapping the benefits of dis-
9
Mapping supply and demand for animal-source foods to 2030
ease control – trypanosomosis in this instance – over a 20 year period. In these examples cattle herd models have been differentially parameterised for each of a series
of cattle production systems and the populations grown accordingly. An estimate
of maximum stocking rate, based on climate and human population is further employed to decide when cattle need to migrate away from an area of growth. Such approaches, whilst almost certainly the way forward with the larger, slower growing
species of livestock, are not really applicable to the monogastric species with their
much higher turnover rates.
projected production and consumption of livestock
commodities
The methodology used for producing the FAO projections, summarised below, is
described in detail in Alexandratos (1995), who stresses the importance of noting
that the resulting projections are not ‘trend extrapolations’, but rather are based
on expectations of the future. The overall approach is to estimate the food balance
sheets for a base year, driven primarily by estimates of current production levels,
and then to project demand for each commodity using Engel demand functions and
exogenous assumptions of population and GDP growth. Provisional production
targets are derived for each commodity and country based on rules about future
levels of self-sufficiency and trade. Specialists in each country and discipline are
engaged and the production targets are revised during several rounds of iterations
and adjustments based what are considered to be feasible and realistic levels of land
use, production intensity, yields and trade.
For the livestock sector a formal ‘flex-price model’ is used (FAO, 1993) to provide starting levels for the iterations and to keep track of the implications, for all
variables, of the changes in any one variable introduced in successive rounds. Again,
the results of the model projections are scrutinised at each iteration by specialists,
particularly with respect to realistic levels of production growth and trade.
The livestock commodities included in the FAO projections are listed in Table 2
and the countries and country groupings for which FAO projections are available
are given in Annex A.
Base year data preparation
First a base year is selected, and represented using a 3 year average centred on that
year. For each commodity and country production, demand and net trade balances
are estimated. For the demand-supply analysis the Supply Utilisation Accounts
(SUAs) framework is adopted, which is structured as follows:
Food (direct) + Industrial non-food uses + Feed + Seed + Waste (+ Discrepancy)
= Demand (total domestic use)
= Production + (Imports - Exports) + (Opening stocks - Closing stocks)
For the base year the SUAs are driven by production estimates. Net trade, feed,
seed, waste and industrial use are estimated for each commodity and the food avail-
10
Methods
Table 2. Livestock commodities included in the FAO projections
Commodity groupings
Beef, veal and buffalo meat
Mutton, lamb and goat meat
Pig meat
Poultry meat
Milk and dairy products (whole milk equivalent)
Eggs
Source: Alexandratos (1995)
able for direct human consumption is the residual. For the most recent estimates
that are currently available (FAO, 2006b) the base year SUA was constructed using FAOSTAT data from 1999, 2000 and 2001 on crop and livestock commodities
where possible, but adjusted by the authors where other sources of data provided
more reliable estimates.
A major component of data preparation is the task of unravelling the SUA element production for the base year into its constituent components. The rather complex procedure is described in detail in Alexandratos (1995) but, put simply, crop
production requires the areas, cropping intensities and yields to be estimated, and
livestock production requires the total stock, off-take rates and carcass weights (or
yields per animal in the case of milk and eggs) to be estimated.
Production (crops) = Area planted × Cropping intensity × Yield
Production (meat) = Number of animals × Off-take rate × Carcass weight
Production (milk and eggs) = Number of animals × Yield
Projections of human population and GDP
The most recent estimates of human population and GDP now and in the future are
described above but the currently available FAO projections are based on earlier
versions of these. Whilst the newer figures are being incorporated into the FAO
projections these were not available when this paper was written.
Population figures used in the FAO projections were taken from the medium
variant UN World Population Prospects 2002 revision (UN, 2003). Those estimates
projected the world population to grow from the 2000 level of 6.07 billion to 8.13
billion in 2030 and 8.92 billion in 2050. These do vary from the most recent medium
variant revisions, which are less conservative: 8.31 billion in 2030 and 9.15 billion
in 2050 (UN, 2009).
Estimates of economic performance were based largely on the World Bank’s
Global Economic Prospects, 2006 (World Bank, 2006a), which provide economic
growth (per-capita GDP) projections for the period from 2001 to 2015. These projections and extensions to 2030 ‘... provided the basis for defining the GDP projections used as exogenous assumptions in the present study. Projections for the period
2030-50 were formulated by the authors of this study, largely on the assumption of
continuation of the growth of the period to 2030, but with some important exceptions.’. These exceptions are listed in FAO (2006b).
11
Mapping supply and demand for animal-source foods to 2030
Projecting supply and demand for livestock commodities
Whilst it may seem more logical to separate the discussion on projecting demand
from that on projecting supply, the two sides of the equation are intimately linked
so are discussed together. The FAO projections involve three broad steps: a) drawing up SUAs, by commodity and country, for the years to be projected, in this case
2030 and 20504; b) unravelling the projected production into its component elements; and c) drawing up land use balances.
The SUA projections for livestock commodities (as well as those for cereals and
oil-crops) are derived using a flex-price model (FAO, 1993). This provides year-byyear world price equilibrium solutions for the commodities covered, it has demand
(for food, feed, other uses) and supply (area, yields, animal numbers, etc.) equations
for each country, and each country’s solution is influenced by those for every other
country through imports and exports, which are equated at the world level by price
changes. (For some other commodities, such as sugar, rubber, cotton and jute, single
commodity models are used to generate the initial projections.) For all commodities
parallel projections are prepared for each SUA element, as described in Alexandratos (1995). In the livestock sector, for meat commodities the food element is by
far the most important as very little of overall production is assigned to the other
elements of the demand side (industrial non-food uses, feed and waste – seed is not
relevant in this case). For milk products, however, there are significant amounts of
total demand assigned to the elements of feed and waste and, with eggs, some of the
demand is assigned to waste and a proportion to the seed element.
The food element (more correctly termed ‘food available for direct human consumption’) is projected in per-capita terms using the base year data, a set of estimated food demand functions (Engel curves) for up to 52 separate commodities in
each country, and assumptions about the growth of per-capita GDP. The results are
reviewed by commodity and nutrition specialists and adjusted taking into account
any relevant knowledge and information; in particular the historical evolution of
per-capita demand and the nutritional patterns in each country. The total projected
food demand is then obtained by multiplying the projected per-capita levels with
projected population.
mapping changing consumption of livestock commodities
The first stage in mapping consumption of livestock commodities involves mapping
the human population now and in the future. For the base year (2000) the GRUMP
population map was used but was adjusted so that national totals matched those
used by the FAO projections, which themselves were based on those reported in
UN (2003). For the 2030 and 2050 projections the adjusted GRUMP 2000 maps
were used, and the base year population figures were multiplied by ‘growth’ factors, so that the total number of people in each country matched the FAO projected
figures. Urban and rural population totals for 2000, 2030 and 2050 were also estimated, based on the proportions of the population living in urban areas from the
UN World Urbanisation Prospects (UN, 2008). Then, for each country, the urban
and rural population distributions from GRUMP were adjusted to match the UN/
4
12
Data were prepared for 2050 in the same way as for 2030, but we do not include any of the 2050 projections in
this paper.
Methods
FAO urban and rural totals in 2000, and ‘grown’ separately to map future urban
and rural populations. No attempt at this stage has been made to adjust the urban
extents (provided by GRUMP) or to disperse population growth from high density
rural areas within countries (international migration and movements from rural to
urban areas are already accounted for in the UN projections).
For each time period the food consumption for each commodity was distributed equally among the population of each country resulting in a map of absolute
consumption, measured in metric tonnes per pixel. Since the population map is
based not on an equal area projection but on a geographic Plate Carée projection
the actual land area represented by a pixel decreases north and south of the equator
(whereas the size of the pixel remains the same on the map). To make consumption
values equivalent across the globe, therefore, these were re-expressed as consumption per square kilometre.
Absolute changes in consumption can then be estimated for each commodity by
subtracting the map of consumption estimates for the base year, 2000, from those
for 2030 or 2050. Since the changes are applied evenly to the population there is little point in mapping the proportional changes in demand growth for livestock commodities as the population distribution cancels out, resulting in two values within
each country – an urban value and a rural value – which is merely the proportional
increase in food from 2000 to 2030 from the FAO projections, weighted across rural
and urban areas. Whilst maps of relative change in demand would be of little value,
these important results can be summarised in tabular form.
mapping changing production of livestock commodities
A similar approach can be taken to mapping production but the process is even
more complex and there are greater constraints imposed by the available data. Most
importantly is that all livestock are not equal – an increase in demand for milk
in Kenya, for example, will not be met by increased production in the arid and
semi-arid pastoral areas, but by increased production in the temperate and highland
areas that are closer to the main population centres. Accounting for this differential growth is no trivial matter and will require a good understanding of livestock
production systems, how these systems are likely to evolve, and how that evolution will be influenced by trade in livestock commodities, resource availability and
many other factors.
The ways in which increased demand for livestock products will be met will a)
vary for different commodities, b) depend very much on accessibility to growth
centres, c) depend on the cost and availability of inputs – the most important of
which is usually feed and d) depend on competition from potential imports - for
example coastal population centres may more readily be served by importation of
cheap frozen meat, or dried milk and egg products, than by increasing production
in the vicinity. The ways in which increasing demands are met will vary considerably from centre to centre so simply to increase local production pro rata, based on
existing livestock distributions, could in some places give rise to quite misleading
results.
Table 3 shows the commodities that are included in the FAO projections against
the livestock species maps that are available globally from the GLW dataset. For
beef production cattle and buffalo have to be combined into a large ruminant layer.
13
Mapping supply and demand for animal-source foods to 2030
Table 3. Livestock commodities included in the FAO projections and livestock
species available from the Gridded Livestock of the World (GLW) databases.
Commodity groupings
Relevant livestock species
Beef, veal and buffalo meat
Cattle, buffalo
Mutton, lamb and goat meat
Sheep, goat
Pig meat
Pigs
Poultry meat
Poultry
Milk and dairy products
(whole milk equivalent)
Cattle, buffalo, sheep, goats
(camels not available)
Eggs
Poultry
No distinction is made between cattle and buffalo by the FAO projections in terms
of animal numbers, off-take rates or carcass weights. The same applies to small
ruminants. With milk and dairy products, large ruminants and small ruminants are
dealt with separately in the FAO projections. Milk from camels is also included in
the FAO projections but the GLW datasets do not currently include this species.
With poultry and ruminants a further problem is faced in that there are two primary outputs; meat and eggs, and meat and milk, respectively. In reality it tends to
be different animals in different production systems that are specialised to produce
one or the other, though these distinctions are much less evident in small-holder
systems. Our available livestock datasets, however, make no such distinction so the
production of these commodities has to be distributed evenly across all animals.
In order to map production of different livestock commodities now and in the
future the production estimates provided in the FAO projections have been spatially disaggregated using the GLW estimates, merging the species that contribute
to the same commodity (see Table 3). As with the estimates of consumption these
were then re-assigned from estimates per pixel to estimates per square kilometre (by
dividing absolute production in each pixel by its area).
The absolute change in production from 2000 to 2030, or form 2000 to 2050
can again be estimated by simple subtraction, but given the assumptions made in
mapping production without accounting for the evolution of livestock production
systems, maps of changing production should be treated with extreme caution.
As with consumption, the changes are applied evenly to the livestock distribution so there is no point in mapping the proportional increase as the population
of livestock cancels out, resulting in a single figure for each country. In the case of
production, there is no urban/rural distinction so we have only one value for each
country.
A further possibility here would be to produce maps of livestock numbers in
the future using the FAO projections. Stock numbers are also provided in the FAO
projections but would need to be split out for species groups: cattle and buffalo,
sheep and goats, poultry. Currently it is unlikely that the GLW data are sufficiently
detailed to assist much with this, though work is underway to incorporate more
detail that would enable such analysis. Potential applications for projected livestock
distributions are many and include environmental impact assessment and disease
risk mapping. To be of real value, however, such projections would need to be explicitly linked to livestock production systems.
14
Methods
mapping production surpluses/deficits
With a few exceptions, demand and supply of livestock products tend to grow hand
in hand and imports of livestock products comprise a significant share of total consumption in very few countries. In most cases, therefore, one is unlikely to find
much difference in demand and supply trends of livestock products at a national
level. Within countries, however, the areas of high production, particularly for the
more land-based ruminant species, can be very different from the highly populated
consumption areas.
Having spatially disaggregated consumption and production, maps of production surpluses (or deficits) can be produced by simple subtraction. Thus, areas
where production exceeds consumption can be identified, and vice versa. Such maps
have in the past been created and used to infer movements of livestock or products
thereof. Two examples of such, summarised in FAO (2007a), are estimated movements of sheep meat in the Near East (FAO, 2004a) and areas of inferred cattle
movements in sub-Saharan Africa, assumed to pose a high risk of Foot and Mouth
Disease (FMD) transmission (FAO, 2005).
standardising consumption of animal-source foods
Comparing consumption of milk and beef, for example, in terms of weight in kilogrammes, makes no sense; milk is made up almost entirely of water, as compared to
beef. To make comparisons among commodities, therefore, they must first be standardised. The SUA approach is primarily designed to look at food insecurity in the
world and, as such, contains valuable information that can be used to standardise
commodities: the amounts of a) protein, b) fat and c) energy that they provide, per
unit of weight. The conversion factors provided obviously vary for each commodity, but, for a given commodity, also differ from country to country and from year
to year, based on assumptions about the production environments in which they
are produced.
We have applied these conversion factors to the consumption estimates and used
them to make regional comparisons of the relative sources of animal-derived protein, and to make composite maps of consumption of animal-source food, in terms
of protein.
15
Results
Maps of production, consumption and production surplus of bovine meat in 2000
are shown in Figure 1 for Africa, along with the growth in demand from 2000 to
2030. The full collection of maps is freely available to be downloaded from the GLW
website1 in graphic, Google Earth or ESRI format GIS file formats for each of six
regional tiles: Africa, Asia, Australasia, Europe, North America and South America.
The most interesting and useful of these maps are really the ones for demand growth.
Some regional examples of these are given for poultry meat in Asia (Figure 2) and
Central America (Figure 3), and for pig meat (Figure 4a) and milk (Figure 4b) in
Latin America. Global maps of growth in demand for each of the six livestock
commodities included in the supply and use analysis are shown in Annex B.
The maps speak for themselves. Figure 1b and Figure 1c clearly highlight the
high population areas as those of high beef consumption (Figure 1b) with a negative
production surplus (Figure 1c). Of particular note are the coastal areas of North
Africa; the Nile delta in Egypt; the East African highlands and the shores of Lake
Victoria; the irrigation schemes of Sudan; southern Nigeria; western Senegal; the
south-east coastal areas and northern areas of South Africa; and the eastern parts
of Madagascar. The pattern of high density urban settlements is evident across the
continent. The production surplus map (Figure 1c) clearly shows these areas of net
beef consumption in red, contrasting with the areas of excess production, which
include the pastoralist areas of East, West and southern Africa.
These maps obviously reflect strongly the distribution of people, but it is in the
absolute values, particularly for consumption growth (Figure 1e and Figure 1f),
that their real value lies. The same applies to the global maps of demand growth
that are shown in Annex B, though important regional differences are also evident.
Projected demand growth for poultry meat is widespread in all regions and very
high rates of increase are forecast to occur in Asia (Figure 2) and in Central America
(Figure 3). Demand growth in areas with large rural populations, such as in India, is
rather ubiquitous, whereas in more developed areas such as North America growth
is much more focussed on the urban centres. Demand growth for milk and dairy
products is also widespread. The pattern of growth seen in Latin America (Figure
4b) shows growth in Brazil to be focussed on the urban centres, in contrast to more
broadcast growth in the Andean region, reflecting the more rural population in
these countries. The global map of demand growth for pork clearly reflects food
preferences determined by cultural and religious factors.
Because of the massive range of values in the maps – very high in densely populated cities and very low in remote rural areas – many of the differences, particularly
at the high end of the scale, are difficult to visualise. Tabular data show these differences more clearly. Table 4 provides regional estimates of absolute and proportional
growth in demand for the different livestock commodities from 2000 to 2030.
5
16
www.fao.org/ag/AGAInfo/resources/en/glw/home.html
Results
Figure 1. a) Production, b) consumption and c) production surplus of beef in
2000; d) consumption in 2030 and e) growth in demand from 2000 to 2030 in Africa, with f) a more detailed view of East Africa.
a)
b)
Production (kg/sqkm)
0
0 - 50
Consumption (kg/sqkm)
50 - 100
100 - 250
250 - 500
500 - 1 000
> 1 000
No Data
0
0 - 50
c)
50 - 100
100 - 250
250 - 500
500 - 1 000
> 1 000
No Data
250 - 500
500 - 1 000
> 1 000
No Data
d)
Production Surplus (kg/sqkm)
High : 1 000
Consumption (kg/sqkm)
No Data
0
0 - 50
Low : -1 000
50 - 100
100 - 250
e)
f)
Consumption (kg/sqkm)
Consumption (kg/sqkm)
<0
0 - 50
100 - 250
500 - 1 000
0
50 - 100
250 - 500
> 1 000
No Data
<0
0
0 - 50
50 - 100
100 - 250
250 - 500
500 - 1 000
> 1 000
No Data
17
Mapping supply and demand for animal-source foods to 2030
Figure 2. Growth in demand for poultry meat from 2000 to 2030 in Asia.
Consumption (kg/sqkm)
<0
0 - 50
100 - 250
500 - 1 000
0
50 - 100
250 - 500
> 1 000
No Data
Figure 3.Growth in demand for poultry meat from 2000 to 2030 in Central
America.
Consumption (kg/sqkm)
18
<0
0 - 50
100 - 250
500 - 1 000
0
50 - 100
250 - 500
> 1 000
No Data
Results
Figure 4.Growth in demand for a) pork and b) milk from 2000 to 2030 in Latin
America.
a)
b)
Consumption (kg/sqkm)
Consumption (kg/sqkm)
<0
0 - 50
100 - 250
500 - 1 000
0
50 - 100
250 - 500
> 1 000
No Data
<0
0
0 - 100
100 - 250
250 - 500
500 - 1 000
1 000 - 5 000
5 000 - 50 000
> 50 000
No Data
The results presented in Table 4 reflect trends both in population and in consumption patterns. The most striking factor is that growth in poultry consumption
outstrips growth in all other animal-source foods in all regions of the world. By far
the most dramatic change is the projected increase in demand for poultry meat in
South Asia; a 725 percent increase overall. This is driven by growth in demand in
India where a staggering 850 percent increase is projected over the 30 year period.
The growth in poultry meat consumption in Asia is accompanied by a four-fold
(about 300 percent) increase in egg consumption (280 percent in India alone). In
terms of sheer volumes the growth of consumption in milk products is impressive,
but very high absolute values for milk and dairy cannot be compared directly with
the other livestock commodities since they refer to whole milk equivalent – which
contains a large proportion of water in comparison to meat and eggs. In South
Asia consumption of milk and dairy products will more than double (125 percent)
to some 213 million metric tonnes in 2030. Seventy percent of that – 146 million
metric tonnes – will be consumed in India. Because of its large and rapidly-growing
population, East Asia is also projected to have large increases in consumption, particularly of pork, poultry meat and milk. Most of this is accounted for by China.
The largest absolute and relative increases in mutton consumption are projected to
occur in sub-Saharan Africa. Beef consumption is projected to increase most in East
Asia and the Pacific, again driven by consumption in China.
Table 5 shows per-capita consumption of the same commodities for the same
regions. Similar trends are evident, with the highest increases occurring in Asia,
especially for pork, poultry and eggs.
19
Mapping supply and demand for animal-source foods to 2030
Table 4. Growth in demand for livestock products from 2000 to 2030 (‘Abs.’ is the
absolute increase in annual consumption from 2000 to 2030 in thousands of metric
tonnes; ‘Prop.’ is the increase expressed as a percentage of consumption in 2000).
REGION
Beef
Mutton
Abs.
Prop.
Pork
Prop.
Abs.
Prop.
Abs.
8 798
130%
23 765
132%
1 669
58%
28 075
China
6 888
132%
15 936
143%
1 537
56%
Eastern
Europe and
Central Asia
290
11%
4 364
15%
204
Latin
America and
Caribbean
7 302
58%
39 818
72%
Middle East
and North
Africa
1 929
112%
17 913
South Asia
3 367
84%
India
1 338
Sub-Saharan
Africa
Poultry
Prop.
Eggs
Abs.
Prop.
Abs.
63%
22 522
143%
10 188
45%
22 050
54%
14 609
121%
6 810
34%
40%
112
5%
2 310
108%
684
28%
239
54%
4 405
100%
14 434
126%
3 246
78%
111%
1 287
103%
9
52%
6 296
243%
1 799
148%
118 942
126%
1 722
115%
950
160%
11 491
725%
5 947
294%
51%
79 330
119%
588
85%
921
160%
8 865
844%
4 251
280%
3 768
113%
20 939
107%
1 883
137%
1 106
155%
3 235
170%
1 727
155%
All Regions
25 454
81%
225 741
97%
7 004
88%
34 656
66%
60 287
170%
23 590
70%
Low Income
Countries
3 523
124%
22 440
136%
1 776
177%
3 481
167%
4 789
301%
1 972
208%
Lower
Middle
Income
14 642
114%
158 467
124%
4 602
82%
26 861
61%
38 353
203%
17 470
68%
Upper
Middle
Income
7 289
47%
44 834
50%
625
46%
4 314
68%
17 145
115%
4 148
60%
High Income
Countries
2 441
15%
31 312
31%
275
33%
2 935
22%
12 414
65%
1 911
24%
East Asia and
Pacific
Abs.
Milk
Prop.
Note: The regions are defined according to the World Bank 2010 classification (World Bank, 2010). A full list of the
countries included in the WB regions is provided in Annex A, along with their income ratings.
Tables 4 and 5 also highlight differences in consumption growth across low,
middle, and high income countries. It is abundantly clear that growth in total and
per-capita consumption of animal-source foods is much less in the high income
countries compared to the low and middle income countries. This is partly because
of a saturation effect – people already eat as much animal-source foods as they need
and would like to – but also due to a trend towards reduced consumption of animalsource foods, particularly of beef, in many of these countries.
The effect that urbanisation will have on changing demand for animal-source
foods is not illustrated in Table 4, nor does it come out clearly in the maps produced
at the scales of those in Figures 1-4, or those in Annex B. Country-level estimates
of demand, production, import and export of the different livestock commodities
in 2000 and 2030 and their absolute and proportional changes are reported in Annex C. These tables include two important disaggregations: a) a breakdown of the
growth attributable to changing consumption patterns, in comparison with that
due to changing population numbers and b) the proportion of change projected to
occur in urban areas, versus that projected to occur in rural areas.
20
Results
Table 5. Growth in per-capita demand for livestock products from 2000 to 2030
(‘Abs.’ is the absolute increase in annual per-capita consumption from 2000 to
2030 in kg/person; ‘Prop.’ is the increase expressed as a percentage of consumption in 2000).
REGION
Beef
Abs.
Milk
Prop.
Abs.
Mutton
Prop.
Abs.
Pork
Prop.
Abs.
Poultry
Prop.
Abs.
Prop.
Eggs
Abs.
Prop.
East Asia and
Pacific
3.8
61%
7.6
55%
0.2
39%
6.3
61%
7.7
91%
2.8
48%
China
4.3
103%
10.1
113%
0.8
37%
11.5
35%
9.1
94%
2.8
17%
Eastern
Europe and
Central Asia
10.7
25%
26.2
20%
0.5
15%
2.0
28%
11.4
116%
3.8
36%
Latin America
and Caribbean
17.2
16%
24.7
27%
0.1
8%
2.5
34%
13.7
73%
2.6
45%
Middle East
and North
Africa
5.5
42%
20.9
31%
1.6
31%
0.0
12%
11.2
97%
2.6
49%
South Asia
4.2
24%
20.7
32%
1.0
45%
0.2
78%
4.1
271%
1.9
134%
0.2
8%
37.6
57%
0.2
33%
0.5
86%
6.0
577%
2.6
173%
Sub-Saharan
Africa
5.3
25%
6.1
17%
0.7
30%
0.6
47%
2.6
73%
0.9
66%
All Regions
7.8
26%
17.7
26%
0.7
28%
1.9
44%
8.5
94%
2.4
48%
Low Income
Countries
4.5
26%
4.3
16%
0.6
32%
1.3
70%
2.2
95%
0.9
73%
Lower Middle
Income
7.2
32%
20.3
38%
0.7
32%
1.5
37%
9.0
109%
2.4
54%
Upper Middle
Income
15.2
17%
21.8
22%
0.5
19%
2.3
37%
13.1
66%
2.8
43%
High Income
Countries
21.0
-1%
6.1
3%
-0.7
-10%
2.0
11%
9.3
36%
0.9
9%
India
Note: The regions are defined according to the World Bank 2010 classification (World Bank, 2010). A full list of the
countries included in the WB regions is provided in Annex A, along with their income ratings.
It is interesting to distinguish the proportion of overall growth attributable to
changing consumption patterns, in comparison with that due to changing population numbers. Growth due mainly to increasing numbers of people is unlikely
to require particular shifts in the structure of a given sector, if the proportion of
the population who produce remains constant (though when population growth
involves significant urbanisation this proportion is likely to decrease). When, however, growth is due to changing consumption patterns, it will require structural
changes in the sector, through a combination of: a) an increase in the number of
producers, relative to consumers; b) intensification of production; and c) importation of that commodity. By and large, the second change is the most likely to occur
in order to meet this ‘disproportionate’ increase in demand.
This is illustrated in Figure 5, which shows how overall growth in demand for
poultry meat in China and India is divided among population growth and changing consumption patterns (Table C.10). The percentages shown in Figure 5 indicate
the proportion of the overall growth that is attributable to a) population growth
21
Mapping supply and demand for animal-source foods to 2030
Figure 5. Demand growth for poultry meat in a) China and b) India, 2000 to 2030,
disaggregated into that accounted for by population growth, versus that accounted
for by changing consumption patterns.
a) China
Population (billions)
1.4
11%
1.4
(11%)
1.2
1.0
0.8
78%
0.6
1.0
0.6
0.2
0.2
2
4
6
8
10 12 14 16 18
Per capita consumption (kg/peron/year)
20
(27%)
0.8
0.4
0
5%
1.2
0.4
0
b) India
1.6
Population (billions)
1.6
0
68%
0
2
4
6
8
10 12 14 16 18
Per capita consumption (kg/peron/year)
20
Demand in 2000
Growth to 2030
Demand growth attributable to population growth
Demand growth attributable to changing consumption patterns
Demand growth as a function of both
(red) and b) increased consumption rates for poultry meat (blue). Looking at the
diagram, though, it is quite clear that, if population numbers were to stay the same,
consumption in China would slightly less than double, whereas that in India would
increase seven-fold. The implications for the poultry sector in India are immense.
The FAO projections do not anticipate this increase in demand to be met through
imports, which remain at zero (Table C.9), but through an increase in production.
This will require a massive, rapid intensification of the poultry sector.
Some dramatic details also become evident when growth is disaggregated in
terms of urban versus rural areas. Looking again at poultry meat consumption in
India, for example, which is projected to increase by about 8.8 million metric tonnes
per year in 2030, compared to in 2000; an 844 percent increase (Table C.9). Whilst
the greater share of this increase – 5.1 million tonnes – is to occur in the rural areas
(compared to 3.7 million tonnes in urban areas), the relative increase in the urban
areas – 1 277 percent – will be almost twice that in the rural areas – 677 percent. This
contributes to the driving force behind the rapid intensification in the poultry sector that is ongoing in India (USDA, 2004).
Similar patterns are seen in other commodities. For example, pork consumption in China overall is projected to increase by 22 million metric tonnes between
2000 and 2030, a 55 percent increase (Table C.7). Urban consumption, however, is
projected to increase by 20 million metric tonnes over this period, a 160 percent
increase, whilst rural consumption is projected to increase only by 1 million metric
tonnes (5 percent increase); reflecting very high rates of urbanisation.
For each of the cities considered in the GRUMP urban extents database, estimates of consumption in 2000 and 2030 and growth in demand from 2000 to 2030
have been extracted from the digital maps. The contribution made by each city to
overall growth in demand for each country has also been estimated (expressed as
22
Results
the percentage of overall national growth in demand accounted for by each city).
For a selection of cities in each region (generally the most populous), data on consumption in 2000 and 2030, growth in demand from 2000 to 2030, and the contribution that makes to overall, national growth, are presented in Annex D.
Results show that the highest increases in consumption will occur, not surprisingly, in cities with the largest rates of increase in population. However, their contribution to the national growth can be fairly low, if they only account for a small
proportion of the population as a whole. This is particularly striking if we look at
consumption of poultry meat and eggs in India, for example, where the populations in the main cities are expected to double, more or less (from 2000 to 2030) and
consumption of poultry meat is expected to increase thirteen-fold. Consumption
growth in the three largest cities together, however, accounts for less than 10 percent of the total growth. This is in stark contrast to other countries, where growth
in demand can be accounted for in large part by a single city. Sixty-four percent of
overall growth in demand for beef in South Africa will, for example, be accounted
for by Johannesburg (Table D.1). Figure 6 shows how growth in consumption of
milk will be accounted for in Kenya: 32 percent of overall growth accounted for by
Nairobi alone, completely dwarfing the four next largest cities.
If consumption estimates of commodities are standardised by expressing them
in some common unit, it is possible: a) to combine them and b) to compare them,
in meaningful ways. An example of each is shown. Figure 7a shows the global,
projected consumption of protein from animal-source foods in 2030, per square
kilometre, derived by combining the totals from the six commodity groups. This
obviously reflects strongly the distribution of people in the world, highlighting,
for example, the widespread, high-density populations of South and East Asia. If
however, the effect of population is removed by expressing this as consumption of
protein derived from animal-source foods, per person (Figure 7b), a very different picture emerges. Figure 7b shows the very high levels of protein derived from
animal-source foods per person in the United States of America, Argentina and
Australia, intermediate levels in much of North Africa, the Middle-East and Asia,
Figure 6. Demand growth for milk in Kenya, 2000 to 2030, disaggregated by rural
and urban areas, with urban growth shown separately for the five largest cities.
23
Mapping supply and demand for animal-source foods to 2030
Figure 7. Global, projected consumption of protein from animal-source foods in
2030: (a) per square kilometre and (b) per person.
a)
Consumption (kg/sqkm)
0
0 - 10
10 - 50
50 - 100
100 - 500
500 - 5 000
> 5 000
No Data
No individual country data available for Europe
b)
Values (kg/person)
0 - 0,5
0,5 - 2,5
2,5 - 5
5 - 7,5
7,5 - 10
10 - 15
15 - 20
> 20
No Data
No individual country data available for Europe
and very low values over most of sub-Saharan Africa and much of South and SouthEast Asia.
Expressing consumption in common units also allows commodities to be compared. Figure 8 shows the proportional intake of protein derived from animalsource foods for the major developing regions of the world in 2000 and in 2030,
from each of the six major livestock commodity groups. Regional differences are
very clear. East Asia and the Pacific is distinguished, not only by the large contribution of pork meat to overall protein derived from animal-source foods (almost half),
but also by the large contribution made by eggs; both considerably larger than in
any other region. Latin America and the Caribbean have a similar pattern of intake
compared to the high income countries, though there is a smaller contribution from
beef in the high income countries; the difference being made up by pork, largely.
The Middle East and North Africa and sub-Saharan Africa are characterised by
relatively large contributions from mutton, but poultry is quite important in the
Middle East and North Africa, and beef more so in sub-Saharan Africa. The con-
24
Results
tribution made by pork is negligible in the Middle East and North Africa and very
small in South Asia, reflecting its absence in Muslim areas. Beef makes the greatest
contribution to dietary protein from animal-source foods in Latin America and the
Caribbean and in sub-Saharan Africa. The most striking feature of all, though, is the
massive contribution made by the dairy sector in South Asia, where almost 70 percent of dietary protein from animal-source foods comes from milk, and products
thereof. This is in stark contrast to East Asia and the Pacific.
Projected changes in these patterns to 2030 are relatively small. The contribution
made by poultry is predicted to increase in all regions of the world; by almost ten
percentage points in Eastern Europe and Central Asia, the Middle East and North
Africa and South Asia. The contributions made by beef and milk are projected to
decline everywhere, with the exception of East Asia and the Pacific, where it is expected to increase by two percentage points.
Figure 8. Proportional consumption of protein from animal-source foods, broken
down by the six major livestock commodity groupings, in 2000 and 2030, for the
major developing regions of the world, and for high income countries.
East Asia and Pacific
2000
2030
Eastern Europe and Central Asia
2000
2030
Latin America and Caribbean
2000
2030
25
Mapping supply and demand for animal-source foods to 2030
Middle East and North Africa
2000
2030
South Asia
2000
2030
Sub-Saharan Africa
2000
2030
High income countries
2000
26
2030
Discussion and conclusions
The maps and tabular data described here have many potential applications, but
before elaborating on these it is worthwhile to comment on some of the limitations
and assumptions in their generation and to mention some ways in which they could
be improved upon.
On mapping demand for animal-source foods, growing human populations
based only on existing population distributions is probably somewhat simplistic
and, furthermore, when growing urban populations no allowance has been made
for urban extents to increase. The latter could be investigated empirically by plotting urban extent against urban population for a series of settlements, by region,
to see if there is a relationship that could be used to expand the urban extents accordingly. But, even if there were a strong relationship – implementing selective
growth of urban extents within the GIS would by no means be simple. A further
limitation is the assumption that consumption patterns for all people in a country
are the same. Whilst sub-national data on consumption rates of different commodities could be found for some countries, the coverage and degree of standardisation
would be poor. In theory, models could be developed that allowed such patterns
to be extended to areas where no such data exist, using proxies such as wealth, or
proximity to urban areas. Determining the extent to which such generalisations
could be made would require a considerable research effort. A reasonable first step,
though, would be to estimate differences between urban and rural consumption
rates for each commodity.
The limitations and assumptions in mapping production are even greater. Assuming production levels to be the same for all livestock producing a particular
commodity in a country is clearly wrong, but dealing with it appropriately was
beyond the scope of this paper. We know well that production varies among production systems and agro-ecological zones and, indeed, we regularly use these differences to stratify herd models. This should be accounted for in an intelligent way
when mapping livestock production. With the more land-tied, ruminant livestock
(cattle, buffalo, sheep and goats) the environmentally-derived production system
stratifications (e.g. Thornton et al., 2002) are most relevant. With monogastric species (pigs and poultry) the more important distinction will be in the degree of intensification and industrialization; growing demand in urban centres will be met primarily by intensive, industrial production (Robinson et al., in press). Growing the
livestock populations based only on existing distributions is even more risky than
is the case with human population distributions. Herd models that incorporate feed
resource requirements should be used to increase cattle and small ruminant populations – with appropriate dispersal functions coming in to play at high stocking rates.
For pigs and poultry, rules should probably be devised for placing the increased
production in relation to, and in proportion to the increases in demand, and where
access to concentrate feed is good.
Whilst production surplus maps have many potential uses, in addition to the
problems relating to each of the components (consumption and production), described above, there are further issues that arise when these two sides of the SUAs
are brought together. Consumption refers only to food consumption for a commodity, whereas production refers to all production that goes towards food, indus-
27
Mapping supply and demand for animal-source foods to 2030
trial non-food use, feed, seed and waste. These differences are relatively small for
meat products but significant for milk and eggs. Nor are the effects of the trade balances visible from the maps – in cases where this results in significant importation
of a commodity, a proportion of the consumption will be met by imported product,
rather than by movements from high production areas within that country. In the
reverse situation, where a country is a net exporter – some of the production will be
exported rather than moved to areas of high consumption. Whilst the FAO projections do list imports and exports there is no indication of where commodities come
from and go to. Since in most cases net trade in livestock commodities is relatively
small, no attempt was made here to adjust for trade and the maps should give reasonable indications of movements within countries. A further issue is that the use of
human population distributions as a predictor variable to disaggregate the reported
livestock statistics (FAO, 2007a), may lead to some circularity when combining
maps of consumption and production. The effect of this could not be anticipated,
but human population distributions could be excluded from the list of predictor
variables used in mapping livestock distribution and abundance, for this purpose.
Many of the above issues could be dealt with, given time and research inputs,
but other important issues relate to the SUAs and the projections themselves. It is
important to remember that the primary objective of the SUAs is to evaluate how
many people in the world are under-nourished. Each year FAO produces its flagship publication: the State of Food Insecurity in the World (most recently, FAO,
2010b). Whilst the topical emphasis varies from year to year, the central theme
is about how many people in the world are under-nourished. This number is reevaluated each year using a food balance sheet approach. For a broad group of
crop and livestock commodities, national estimates of the food available for human consumption are made using the SUAs, along with the caloric content of each
food commodity. These data are used to calculate total availability of calories in the
country. Since different age and sex groups have different minimum caloric requirements, data on population structure are used to estimate the total caloric requirements for the entire population. Household survey data, typically used to measure
living standards, are used to estimate the country-specific distribution of calories.
Then, from the total calories available, total calories needed for a given population,
and the distribution of calories, the number of people who fall below the minimum
energy requirement is estimated. This represents the number of undernourished
people.
With this objective it is quite reasonable to combine bovines; sheep and goats;
poultry species; and milk and eggs from different species: eggs from ducks and
chickens have relatively similar caloric, protein and fat values per unit of weight, for
example. From a production perspective, however, this is far from ideal: ducks and
chickens, for example, are produced in quite different production systems, achieving different production efficiencies, often serving quite different purposes and occurring in different areas.
That, for each commodity, the production coefficients - off-take rates, carcass
weights and, for milk and eggs, yields – that are applied to the stocks, are averaged across the country presents a significant limitation to the approach. Considerably greater accuracy could be achieved if the stocks in each country were divided
among the prevalent production systems, and appropriate production coefficients
28
Discussion and conclusions
applied to each. Moreover, when projecting production this would allow a) for the
evolution of production systems to be accounted for explicitly, for example a migration from extensive to more intensive systems, and b) for the evaluation of different scenarios of livestock sector growth and evolution. In a collaborative effort
between the Economic and Social Development Department (ESS), which is responsible for the SUAs and projections, and the Livestock Production and Health
Division (AGA), ways in which this could be done and the benefits of so doing, are
being evaluated, initially for the pig sector, globally.
The disaggregation of demand growth, presented here, shows that the majority
of the growth will stem from the burgeoning urban areas of the developing world,
rather than rural populations, and closely linked to that, will be driven by changing
consumption patterns to a far greater extent than by population growth. Demand
growth associated with increasing consumption rates and urbanisation will require
structural changes to the livestock sector in order that demand is met by increased
supply: intensification of production and longer supply chains.
The growth in demand for animal source food offers opportunities for economic
growth, poverty reduction and increased food security in rural areas. Livestock
producers who can gain access to growing markets may benefit from increased sales
and higher prices. Many of these producers number among the livestock-dependent
poor, but the extent to which poor, or even small-scale livestock producers can link
to the growing markets will vary greatly from place to place, and for different commodities. Even where production is in the hands of larger-scale commercial livestock owners though, there will be employment opportunities generated along the
value chain; both up-stream and down-stream of the producer. Growing markets
for animal-source foods will stimulate demand for purchased inputs such as young
or breeding stock, genetic material, feeds and animal health services, for example.
Poorer urban consumers should also benefit from more affordable meat, milk and
eggs; enjoying the nutritional benefits associated with increased dietary intake of
animal-source foods.
But the outcomes of livestock sector growth are by no means all positive; detrimental social, animal health, public health and environmental impacts of rapid sector growth are well-documented in ‘Livestock in the balance’ (FAO, 2010a).
Small-scale, mixed production systems face increasing competition from larger-scale intensive systems. There are social implications for small-holders whose
opportunities to supply new markets are constrained, and who can be squeezed
out of markets to which they have traditionally been linked. Combining spatial
data on demand growth, as described here, with information on livestock production systems and the distributions of poor livestock keepers, (e.g. Thornton et al.,
2002; Robinson et al., in press) offers the possibility of identifying vulnerable rural
populations of livestock keepers. This in turn will help with targetting, impact assessment and the design of policy and institutional measures that that can assist
the more commercially-oriented small-holders in accessing growing markets, for
example through their ability to meet increasingly stringent health and food-safety
standards; to obtain access to capital and credit; and to improve their access to input services. For those small-holders that are unable to compete, policies need to
be designed that facilitate their transition from the livestock sector towards other
livelihood options.
29
Mapping supply and demand for animal-source foods to 2030
Significant animal and public health risks have also been associated with the concentration of intensive production systems in close proximity to densely-populated
urban areas, and particularly in areas where this may occur among large populations of livestock raised by small-holders, under extensive production systems,
with low levels of biosecurity. The fears are firstly of rapid multiplication of pathogens moving from extensive to intensive systems (and vice-versa), which could lead
to the emergence or re-emergence of diseases, for example through virulence jumps
within high-density, genetically similar, susceptible populations, and secondly the
passage of zoonotic pathogens to the human population from these high-density
production systems. When thousands of animals are confined in close proximity
the probability of pathogen transfer within and between populations is greatly elevated, and in consequence, so is the rate of pathogen evolution. Furthermore, the
waste from these livestock can contain large quantities of pathogens, posing further
risks of transmission to hosts, often wildlife, outside the production system. It has
been shown that highly pathogenic avian influenza (HPAI) viruses can be produced
from low pathogenic strains following consecutive passages through chickens of
similar genetic makeup; the very conditions found in intensive production units
(Ito et al., 2001). Rapid increases in the number of large-scale production units
would thus favour the emergence of highly pathogenic strains from a pool of low
pathogenic viruses maintained in wild or domestic birds. Panzootic HPAI H5N1
emerged in China in 1996 (Li et al., 2004) following several years of intensification
of chicken and duck production. Whilst the specific roles of intensive production
systems in the emergence of novel strains of pathogen are not well understood,
and there are few if any examples where it has been shown conclusively that the
occurrence of intensive systems in the midst of an abundance of extensive production causes elevated risk, CAST (2005) concluded that a consequence of intensive
livestock production systems was that they created ideal conditions for rapid selection and amplification of highly pathogenic strains of disease agents. FAO (2007b)
provides a comprehensive review of how pathogens can get in and out of such, apparently biosecure systems.
With the extensive use of antimicrobial drugs in intensive production systems,
genes for antimicrobial resistance can also be selected for and amplified, posing a
risk that such genes migrate into human-infective pathogens (Bonfoh et al., 2010).
Maps of demand growth are important inputs to predicting where the production
of livestock is likely to increase, and where intensive production units may be expected to emerge in close proximity to more extensive production systems.
Maps of production surplus can be produced by combining maps of livestock
production with those of animal-source food consumption (Figure 1c, for example). These can be used to infer trade-related movement of livestock or livestock
commodities from areas of production surplus to areas where demand exceeds supply. Areas in Africa, for example, where such movements of cattle would be expected, have been associated with risk of FMD transmission (FAO, 2005). Maps
of demand growth for animal-source foods, combined with production maps, can
therefore make important contributions to mapping the risk of disease emergence,
persistence and spread.
30
Discussion and conclusions
Tilman et al. (2001) warn of some of the potentially massive, irreversible environmental impacts of agricultural expansion over the coming decades; highlighting
the need to anticipate and monitor growth. Whilst intensive systems produce relatively less GHG per unit of output than do extensive systems, they often exceed
the nutrient adsorptive capacity of the land on which they occur. It has been estimated that more than 130 000 square kilometres of arable land in China and 30 000
square kilometres in Thailand, have an annual livestock nutrient waste production
of phosphate of at least 20 kilograms per hectare per year in excess of the adsorptive capacity of the surrounding ecosystem (World Bank, 2005). Currently, animal
waste receives little or no treatment and makes a significant contribution to surface
water pollution and terrestrial nitrogen deposition (NRC, 2000). If used to locate
the distribution of intensive production units, demand growth maps can contribute
to pin-pointing areas of likely environmental pollution. More generally, maps of
production growth could be used to identify areas of elevated, livestock related environmental impacts, be they through GHG emissions, land degradation or waste
production, so that policies and interventions can be appropriately targetted.
By far the most costly input to intensification of livestock production is feed,
which, in highly intensive poultry operations, for example, can account for 60 to
80 percent of the total cost of inputs (FAO, 2004b). As livestock production intensifies, it becomes de-coupled from the land resource; dependent increasingly on
traded feed concentrates than on locally available feed resources. In 2004, for example, 34 percent of the global cereal harvest, a total of 690 million tonnes, were
fed to livestock (Steinfeld et al., 2006). A rapid growth of intensive production of
livestock will call for commensurate increases in the production of feed, which will
exert considerable pressures on land and water resources in some areas of the world.
There are many factors which influence the demand for animal-source foods
now and in the future. Some will come from the supply side; competition for land,
carbon constraints and legislation relating to the environment and animal welfare,
for example. Others will come from the demand side, such as increasing wealth
and urbanisation, human health concerns and socio-cultural trends. How exactly
these will interact to determine demand for and production of specific livestock
commodities in the coming decades is uncertain (Thornton, 2010). What is certain
is that the land use changes required to meet the projected demands in livestock
may contribute substantially to undermining the capacity of global ecosystems to
sustain food production, maintain fresh water and forest resources, regulate climate
and air quality and ameliorate infectious diseases (Foley et al., 2005). It is important
therefore, carefully to monitor the situation as it unfolds, and to take timely and
appropriate action to ensure that the benefits of livestock sector growth are maximised and that the many possible negative effects are controlled.
31
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35
Annex A. Countries and country groupings
Table A 1. List of countries included in the FAO projections, grouped by World
Bank region and showing the most recent income groupings (World Bank, 2010).
COUNTRY
INCOME LEVEL
(World Bank, 2010) Country data
availability
FAO PROJECTIONS
Country aggregate
Latin America and Caribbean
Argentina
Upper middle
I
Belize
Lower middle
G
Bolivia
Lower middle
I
Brazil
Upper middle
I
Chile
Upper middle
I
Colombia
Upper middle
I
Costa Rica
Upper middle
I
Cuba
Upper middle
I
Dominica
Upper middle
G
Dominican Republic
Upper middle
I
Ecuador
Lower middle
I
El Salvador
Lower middle
I
Grenada
Upper middle
G
Guatemala
Lower middle
I
Guyana
Lower middle
I
Low
I
Honduras
Lower middle
I
Jamaica
Upper middle
I
Mexico
Upper middle
I
Nicaragua
Lower middle
I
Panama
Upper middle
I
Paraguay
Lower middle
I
Peru
Upper middle
I
Saint Kitts and Nevis
Upper middle
G
Latin America and Caribbean
Saint Lucia
Upper middle
G
Latin America and Caribbean
Saint Vincent and the Grenadines
Upper middle
G
Latin America and Caribbean
Suriname
Upper middle
I
Uruguay
Upper middle
I
Venezuela
Upper middle
I
Lower middle
I
Low
I
Haiti
Latin America and Caribbean
Latin America and Caribbean
Latin America and Caribbean
Sub-Saharan Africa
Angola
Benin
‘Country data availability’ indicates whether data, for the projections described in this paper, are available for
individual countries (I), for country aggregates (G), or not available (N). The term ‘Not listed’ refers to countries
that are not considered in the FAO projections. For countries that are aggregated, the last column indicates those
groups, according FAO group classification which therefore might not correspond to the WB regions. Source:
Bruinsma (personal communication, 2010).
36
Annex A
COUNTRY
Botswana
INCOME LEVEL
(World Bank, 2010) Country data
availability
Upper middle
I
Burkina Faso
Low
I
Burundi
Low
I
Cameroon
Lower middle
I
Cape Verde
Lower middle
G
Central African Republic
Low
I
Chad
Low
I
Comoros
Low
G
Congo
Lower middle
I
Cote d’Ivoire
Lower middle
I
Dem. Rep. of the Congo
Low
I
Eritrea
Low
I
Low
I
Gabon
Ethiopia
Upper middle
I
Gambia
Low
I
Ghana
Low
I
Guinea
Low
I
Guinea-Bissau
Low
G
Kenya
Low
I
Lesotho
Lower middle
I
Liberia
Low
I
Madagascar
Low
I
Malawi
Low
I
Mali
Low
I
Mauritania
Low
I
Mauritius
Upper middle
I
Mayotte
Upper middle
Not listed
Low
I
Upper middle
N
Low
I
Mozambique
Namibia
Niger
Nigeria
Lower middle
I
Rwanda
Low
I
Lower middle
G
Low
I
Upper middle
G
Sao Tome and Principe
Senegal
Seychelles
Sierra Leone
Low
I
Somalia
Low
I
South Africa
Upper middle
I
Sudan
Lower middle
I
Swaziland
Lower middle
I
Low
I
Togo
FAO PROJECTIONS
Country aggregate
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
Sub-Saharan Africa
37
Mapping supply and demand for animal-source foods to 2030
COUNTRY
INCOME LEVEL
(World Bank, 2010) Country data
availability
Uganda
Low
I
United Republic of Tanzania
Low
I
Zambia
Low
I
Zimbabwe
Low
I
Algeria
Upper middle
I
Djibouti
Lower middle
G
Egypt
Lower middle
I
Iran (Islamic Republic of)
Lower middle
I
Iraq
Lower middle
I
Jordan
Lower middle
I
Lebanon
Upper middle
I
Libyan Arab Jamahiriya
Upper middle
I
Morocco
Lower middle
I
Syrian Arab Republic
Lower middle
I
Tunisia
Lower middle
I
West Bank
Lower middle
Not listed
Low
I
Upper middle
Not listed
Low
I
Lower middle
I
FAO PROJECTIONS
Country aggregate
Middle East and North Africa
Yemen
Sub-Saharan Africa
East Asia and Pacific
American Samoa
Cambodia
China
Low
I
Fiji
Dem People’s Rep of Korea
Upper middle
G
Indonesia
Lower middle
I
Kiribati
Lower middle
G
Low
I
Malaysia
Lao People’s Dem. Rep.
Upper middle
I
Marshall Islands
Lower middle
Not listed
Micronesia (Federated States of)
Lower middle
Not listed
Mongolia
Lower middle
N
Myanmar
Low
I
Papua New Guinea
Lower middle
G
Philippines
Lower middle
I
Samoa
Lower middle
N
Solomon Islands
Lower middle
G
Thailand
Lower middle
I
Tonga
Lower middle
N
Vanuatu
Lower middle
G
Low
I
Viet Nam
38
East Asia
East Asia
East Asia
East Asia
East Asia
Annex A
COUNTRY
INCOME LEVEL
(World Bank, 2010) Country data
availability
FAO PROJECTIONS
Country aggregate
South Asia
Afghanistan
Low
I
Bangladesh
Low
I
Bhutan
Lower middle
Not listed
India
Lower middle
I
Maldives
Lower middle
N
Low
I
Pakistan
Lower middle
I
Sri Lanka
Lower middle
I
Albania
Lower middle
G
Eastern Europe
Armenia
Lower middle
G
Central Asian Republics
Azerbaijan
Lower middle
G
Central Asian Republics
Belarus
Upper middle
G
Eastern Europe
Bosnia and Herzegovina
Upper middle
G
Eastern Europe
Bulgaria
Upper middle
G
Eastern Europe
Georgia
Lower middle
G
Central Asian Republics
Kazakhstan
Upper middle
G
Central Asian Republics
Kyrgyzstan
Low
G
Central Asian Republics
Latvia
Upper middle
G
EUN9
Lithuania
Upper middle
G
EUN9
Moldova, Republic of
Lower middle
G
Eastern Europe
Poland
Upper middle
G
EUN9
Romania
Upper middle
G
Eastern Europe
Russian Federation
Upper middle
I
Serbia and Montenegro
Upper middle
G
Eastern Europe
Low
G
Central Asian Republics
Upper middle
G
Eastern Europe
Nepal
Eastern Europe and Central Asia
Tajikistan
The former Yug. Rep. of
Macedonia
Turkey
Upper middle
I
Turkmenistan
Lower middle
G
Central Asian Republics
Ukraine
Lower middle
G
Eastern Europe
Low
G
Central Asian Republics
Andorra
High
Not listed
Antigua and Barbuda
High
G
Aruba
High
Not listed
Australia
High
I
Austria
High
G
EU15
Bahamas
High
G
Latin America and Caribbean
Barbados
High
G
Latin America and Caribbean
Uzbekistan
High Income Countries
Latin America and Caribbean
39
Mapping supply and demand for animal-source foods to 2030
COUNTRY
INCOME LEVEL
(World Bank, 2010) Country data
availability
FAO PROJECTIONS
Country aggregate
Belgium
High
G
EU15
Bermuda
High
G
Latin America and Caribbean
Brunei Darussalam
High
G
East Asia
Canada
High
I
Croatia
High
G
Eastern Europe
Cyprus
High
G
Near East/North Africa
Czech Republic
High
G
EUN9
Denmark
High
G
EU15
Equatorial Guinea
High
Not listed
Estonia
High
G
EUN9
Finland
High
G
EU15
France
High
G
EU15
French Polynesia
High
G
East Asia
Germany
High
G
EU15
Greece
High
G
EU15
Greenland
High
Not listed
Guam
High
Not listed
Hong Kong
High
Not listed
Hungary
High
G
Iceland
High
I
Ireland
High
G
Israel
High
I
Italy
High
G
Japan
High
I
Kuwait
High
G
Liechtenstein
High
Not listed
Luxembourg
High
G
EU15
Malta
High
G
EUN9
Monaco
High
Not listed
Netherlands
High
G
EU15
EUN9
EU15
EU15
Near East/North Africa
Netherlands Antilles
High
G
Latin America and Caribbean
New Caledonia
High
G
East Asia
New Zealand
High
I
Norway
High
I
Oman
High
Not listed
Portugal
High
G
Qatar
High
Not listed
Republic of Korea
High
I
Saudi Arabia
High
I
Singapore
High
N
Slovakia
High
G
40
EU15
EUN9
Annex A
COUNTRY
INCOME LEVEL
(World Bank, 2010) Country data
availability
FAO PROJECTIONS
Country aggregate
Slovenia
High
G
EUN9
Spain
High
G
EU15
Sweden
High
G
EU15
Switzerland
High
I
Trinidad and Tobago
High
I
United Kingdom
High
G
EU15
United Arab Emirates
High
G
Near East/North Africa
United States of America
High
I
United States Virgin Islands
High
Not listed
Note: EU15 refers to the European Union, while EU9 refers to the new EU member countries (Bruinsma, personal
communication, 2010).
41
42
50 - 100
0
250 - 500
100 - 250
No individual country data available for Europe
0 - 50
<0
Consumption (kg/sqkm)
> 1 000
500 - 1 000
Figure B1. Growth in demand for beef from 2000 to 2030
No Data
Annex B. Global maps of growth in demand for
livestock commodities from 2000 to 2030
0 - 100
100 - 250
250 - 500
500 - 1 000
No individual country data available for Europe
<0
0
Consumption (kg/sqkm)
1 000 - 5 000
5 000 - 50 000
Figure B2. Growth in demand for milk from 2000 to 2030
> 50 000
No Data
Annex B
43
44
0 - 50
50 - 100
100 - 250
250 - 500
No individual country data available for Europe
<0
0
Consumption (kg/sqkm)
500 - 1 000
> 1 000
Figure B3. Growth in demand for mutton from 2000 to 2030
No Data
Mapping supply and demand for animal-source foods to 2030
50 - 100
0
250 - 500
100 - 250
No individual country data available for Europe
0 - 50
<0
Consumption (kg/sqkm)
> 1 000
500 - 1 000
Figure B4. Growth in demand for pork from 2000 to 2030
No Data
Annex B
45
46
50 - 100
0
250 - 500
100 - 250
No individual country data available for Europe
0 - 50
<0
Consumption (kg/sqkm)
> 1 000
500 - 1 000
Figure B5. Growth in demand for poultry meat from 2000 to 2030
No Data
Mapping supply and demand for animal-source foods to 2030
50 - 100
0
250 - 500
100 - 250
No individual country data available for Europe
0 - 50
<0
Consumption (kg/sqkm)
> 1 000
500 - 1 000
Figure B6. Growth in demand for eggs from 2000 to 2030
No Data
Annex B
47
Annex C. Consumption and production
of livestock commodities in 2000 and 2030
In this section we report country-level totals of consumption, production, import
and export of the different livestock commodities (beef, milk, mutton, pork, poultry meat and eggs), in 2000 and 2030, and their absolute and proportional change.
The consumption totals have been disaggregated by urban and rural areas based on
the baseline 2000 GRUMP population distribution, and UN urban and rural proportions in 2000, and those projected in 2030. Absolute values have been summed
at the regional level, while the proportional changes are expressed as a percentage
of the total values in 2000.
48
7.6
234.3
29.1
46.8
88.0
148.5
158.8
141.3
172.1
8.1
79.5
34.9
208.5
72.4
44.6
Malaysia
Myanmar
Philippines
Thailand
Viet Nam
120.8
228.1
174.5
55.4
1 250.0
47.9
10 034.0
1 991.6
104.1
4 710.9
276.4
Latin America/Caribbean
Argentina
Bolivia
Brazil
Chile
2 659.7
1 747.0
Russian Federation
Turkey
626.7
1 975.1
Eastern Europe and
Central Asia
Lao People’s Dem. Rep.
Indonesia
747.5
2 585.8
13.1
Dem. People’s Rep. of Korea
China
2 647.8
3 493.1
Rural
Consumption
52.9
3 293.7
Urban
12.7
Cambodia
East Asia and Pacific
COUNTRY
324.3
5 960.9
159.5
2 166.1
12 693.7
348.9
2 373.7
2 722.6
185.9
231.2
357.0
122.9
126.3
37.2
406.4
20.7
5 233.6
65.6
6 786.8
Total
223.8
6 536.7
158.7
2 631.6
13 713.8
349.3
1 877.9
2 227.2
185.8
193.4
216.8
137.8
13.2
42.0
325.1
20.5
5 298.2
67.1
6 499.9
Production
BEEF 2000
101.1
53.2
1.3
16.8
658.9
0.1
505.6
505.7
0.1
43.5
140.4
0.0
115.7
0.0
81.4
0.2
9.0
0.0
390.3
Import
0.6
629.0
0.7
310.6
1 456.8
0.5
5.9
6.4
0.0
5.8
0.2
14.8
2.5
4.8
0.1
0.0
73.6
1.6
103.4
Export
501.7
7 967.5
251.2
2 506.8
17 284.9
482.5
1 829.8
2 312.4
133.1
172.5
683.4
115.9
269.6
55.4
681.2
30.0
8 031.6
61.0
10 233.9
Urban
46.7
1 048.9
73.3
118.2
2 710.8
135.4
564.5
699.8
190.2
204.6
212.6
124.7
57.9
51.3
309.0
10.0
4 090.3
100.6
5 351.0
Rural
Consumption
548.4
9 016.4
324.5
2 625.0
19 995.7
617.9
2 394.3
3 012.2
323.3
377.1
896.0
240.6
327.5
106.7
990.2
40.0
12 121.9
161.6
15 584.9
Total
398.4
10 716.4
324.5
3 711.3
23 031.2
617.9
1 898.2
2 516.1
323.3
250.0
646.0
250.6
18.0
118.7
790.2
35.0
12 221.9
161.6
14 815.3
Production
BEEF 2030
Table C 1. Consumption and production of beef in 2000 and 2030 (all measures are in thousands of metric tonnes).
150.0
0.0
0.0
0.0
707.2
0.0
500.0
500.0
0.0
127.1
250.0
0.0
309.5
0.0
200.0
5.0
0.0
0.0
891.6
Import
0.0
1 700.0
0.0
845.7
3 413.2
0.0
0.0
0.0
0.0
0.0
0.0
10.0
0.0
12.0
0.0
0.0
100.0
0.0
122.0
Export
Annex C
49
50
36.8
1.3
23.1
29.5
9.9
444.5
11.6
19.1
91.0
24.1
0.5
14.6
30.6
0.6
14.3
24.7
10.8
1 329.7
14.4
37.2
110.2
80.9
3.1
165.4
350.6
908.9
99.3
Guatemala
Haiti
Honduras
Jamaica
Mexico
Nicaragua
Panama
Paraguay
Suriname
Uruguay
Venezuela
Middle East/North Africa
Algeria
Peru
Guyana
42.1
814.0
52.6
18.5
Ecuador
71.0
25.8
42.8
Dominican Republic
25.7
33.7
40.5
Cuba
105.3
27.1
40.5
El Salvador
197.0
523.9
Rural
Costa Rica
Urban
Consumption
Colombia
COUNTRY
141.4
1 722.9
403.2
180.0
3.6
105.0
201.2
56.3
26.0
1 774.2
20.7
54.2
37.4
1.9
67.4
44.2
176.3
68.6
74.2
67.6
720.9
Total
126.0
1 259.4
418.7
417.0
2.0
135.6
247.5
63.8
61.7
1 482.7
14.0
52.9
37.3
1.9
62.0
28.8
175.9
68.4
74.1
82.2
736.5
Production
BEEF 2000
15.5
478.0
5.5
0.2
0.5
3.3
1.5
1.0
2.6
433.0
7.0
2.9
0.2
0.0
7.7
15.4
0.4
0.2
0.1
2.3
2.7
Import
0.0
2.7
0.2
251.2
0.0
0.0
47.8
7.0
38.6
145.0
0.2
1.6
0.0
0.0
2.4
0.0
0.0
0.0
0.0
16.9
5.0
Export
279.9
2 314.7
655.1
201.9
5.2
197.0
262.7
78.1
57.8
2 779.6
19.0
71.8
49.5
1.0
114.8
67.0
276.1
88.5
73.1
69.8
989.7
Urban
60.4
1 337.6
47.7
11.8
0.5
44.6
109.2
16.5
29.7
559.2
11.4
45.5
22.6
1.4
74.2
29.7
87.9
22.1
55.1
24.2
230.4
Rural
Consumption
340.3
3 652.3
702.8
213.7
5.7
241.6
371.9
94.6
87.5
3 338.8
30.4
117.3
72.1
2.4
189.0
96.7
364.0
110.6
128.2
94.0
1 220.1
Total
305.3
2 830.7
725.0
913.7
3.9
258.5
421.9
101.8
170.0
2 836.9
19.6
117.3
72.1
2.4
189.0
76.7
364.0
110.6
128.2
114.0
1 255.0
Production
BEEF 2030
35.0
823.0
14.4
0.0
1.8
10.0
0.0
0.0
0.0
500.0
11.0
0.0
0.0
0.0
0.0
20.0
0.0
0.0
0.0
0.0
0.0
Import
0.0
0.0
0.0
700.0
0.0
0.0
50.0
5.0
82.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
20.0
10.0
Export
Mapping supply and demand for animal-source foods to 2030
14.8
5.6
4.7
5.5
65.7
21.9
22.8
33.1
20.2
30.4
17.9
75.1
23.6
39.4
14.9
Jordan
Lebanon
Libyan Arab Jamahiriya
Morocco
Syrian Arab Republic
Tunisia
Yemen
45.9
11.4
2.7
55.6
7.1
4.1
Angola
Benin
Botswana
2 147.0
27.9
5.6
Sri Lanka
1 195.1
592.2
Sub-Saharan Africa
146.9
22.8
293.9
1 895.2
733.1
India
Pakistan
133.4
41.8
Bangladesh
Nepal
94.9
32.9
Afghanistan
2 890.5
1 130.1
South Asia
40.6
111.3
204.4
Iran (Islamic Republic of)
Iraq
478.9
Rural
350.7
Urban
Consumption
Egypt
COUNTRY
6.8
18.5
101.5
3 342.1
33.5
886.1
169.7
2 628.3
175.2
127.8
4 020.6
55.5
62.2
45.5
140.8
23.4
35.1
25.8
47.9
315.7
829.6
Total
27.2
16.8
85.0
3 298.9
33.5
887.5
170.0
2 861.4
175.2
127.8
4 255.4
43.6
59.6
45.2
138.2
6.0
10.0
0.7
47.9
287.3
494.9
Production
BEEF 2000
2.7
1.7
16.5
173.0
0.1
0.0
0.6
0.2
0.0
0.0
0.9
12.0
2.6
0.3
2.8
4.7
49.8
26.8
0.1
28.4
335.0
Import
23.3
0.0
0.0
124.8
0.1
1.4
0.9
233.3
0.0
0.0
235.7
0.1
0.0
0.0
0.6
0.0
0.1
1.6
0.0
0.0
0.3
Export
9.6
21.3
220.2
3 584.5
9.6
1 134.6
99.3
1 609.0
142.9
164.6
3 160.0
85.7
80.0
73.7
163.5
41.7
72.3
39.4
206.4
516.7
755.4
Urban
2.9
18.6
74.3
3 525.6
33.7
1 152.0
226.6
2 357.4
209.6
248.3
4 227.6
101.7
26.5
41.3
84.7
8.5
7.5
8.7
81.7
144.4
772.2
Rural
Consumption
12.5
39.9
294.5
7 110.1
43.3
2 286.6
325.9
3 966.4
352.5
412.9
7 387.6
187.4
106.5
115.0
248.2
50.2
79.8
48.1
288.1
661.1
1 527.6
Total
51.9
36.9
279.3
6 854.1
43.3
2 286.6
325.9
4 266.4
352.5
412.9
7 687.6
127.4
102.5
105.0
233.2
10.1
12.0
1.0
113.1
621.1
1 200.0
Production
BEEF 2030
0.0
3.0
15.2
396.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
60.0
4.0
10.0
15.0
40.1
69.2
47.1
175.0
40.0
327.6
Import
39.4
0.0
0.0
139.4
0.0
0.0
0.0
300.0
0.0
0.0
300.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
51
52
43.1
8.2
43.6
34.9
55.4
1.8
30.8
14.3
13.5
247.3
0.5
1.5
14.5
20.5
227.7
7.0
0.9
105.4
13.2
65.4
5.6
49.4
24.6
20.7
2.3
22.9
6.7
3.0
48.6
3.8
1.9
12.9
12.0
59.2
1.8
1.1
44.2
2.3
27.0
4.8
Cameroon
Central African Republic
Chad
Congo
Dem. Rep. of the Congo
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Kenya
Lesotho
Liberia
Mauritania
Mali
Malawi
Madagascar
Cote d’Ivoire
Burkina Faso
0.8
Rural
10.8
Urban
Consumption
Burundi
COUNTRY
10.4
92.4
15.5
149.6
2.0
8.8
286.9
32.5
27.4
3.4
4.3
295.9
16.5
21.0
53.7
4.1
76.1
59.5
93.0
9.0
53.9
Total
16.4
114.4
15.5
149.6
0.8
7.5
287.0
33.1
21.6
3.3
0.7
295.9
16.2
13.5
25.6
1.6
86.8
57.0
93.1
9.0
69.2
Production
BEEF 2000
0.0
0.0
0.0
0.0
1.2
1.3
0.1
0.7
5.8
0.0
3.5
0.0
0.2
7.5
28.2
2.5
0.0
3.4
0.1
0.0
0.2
Import
6.0
22.0
0.0
0.0
0.0
0.1
0.2
1.4
0.1
0.0
0.0
0.1
0.0
0.0
0.0
0.0
10.7
0.9
0.1
0.0
15.5
Export
20.1
108.9
8.3
130.3
4.0
4.1
170.2
46.6
50.2
5.8
8.6
184.9
16.9
53.4
71.4
9.4
84.8
56.2
133.6
5.9
64.0
Urban
15.5
119.5
17.5
170.9
1.5
5.6
344.1
41.4
24.9
1.9
0.6
462.3
31.7
53.6
44.9
4.2
110.1
53.8
51.4
24.1
117.4
Rural
Consumption
35.6
228.4
25.8
301.2
5.5
9.7
514.3
88.0
75.1
7.7
9.2
647.2
48.6
107.0
116.3
13.6
194.9
110.0
185.0
30.0
181.4
Total
40.6
248.4
25.8
301.2
2.6
7.7
514.3
88.0
40.0
7.2
2.2
647.2
48.3
47.0
75.0
4.6
204.9
107.5
185.0
30.0
211.4
Production
BEEF 2030
0.0
0.0
0.0
0.0
2.9
2.0
0.0
0.0
35.1
0.5
7.0
0.0
0.3
60.0
41.3
9.0
0.0
2.5
0.0
0.0
0.0
Import
5.0
20.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10.0
0.0
0.0
0.0
30.0
Export
Mapping supply and demand for animal-source foods to 2030
191.7
15.0
29.5
4.1
39.1
244.8
180.2
13.5
3.1
86.4
173.7
27.7
149.2
3.2
21.4
2.5
21.0
319.7
112.7
4.5
2.3
11.7
49.7
15.2
29.8
Nigeria
Rwanda
Senegal
South Africa
Sudan
Swaziland
Togo
Uganda
United Republic of Tanzania
Zambia
Zimbabwe
151.4
0.1
11.0
882.1
3.6
113.5
Canada
Iceland
Israel
97.7
680.8
2 881.3
Australia
High income countries
Somalia
Sierra Leone
13 577.9
34.3
58.5
26.9
6.7
Niger
Mozambique
Mauritius
12.5
Rural
3.4
Urban
Consumption
5.4
COUNTRY
124.5
3.7
1 033.5
778.5
16 459.2
88.3
42.9
223.4
98.1
5.4
18.0
292.9
564.5
60.1
6.6
50.9
18.2
340.9
41.0
39.4
8.8
Total
37.1
3.7
1 616.6
2 259.4
17 305.7
101.8
42.7
223.4
98.0
5.2
14.6
298.5
558.2
70.2
4.7
48.8
18.1
285.1
44.9
37.4
0.5
Production
BEEF 2000
87.7
0.0
366.2
5.9
3 749.3
0.2
0.2
0.1
0.0
0.3
5.1
0.3
20.2
0.0
1.9
2.2
0.1
55.8
0.1
2.0
8.9
Import
0.0
0.0
947.0
1 486.9
4 345.3
13.8
0.0
0.1
0.0
0.0
1.6
5.9
8.3
10.1
0.0
0.0
0.0
0.0
4.0
0.0
0.6
Export
179.0
3.1
1 079.9
821.9
16 588.4
55.0
35.8
174.9
57.6
8.4
7.3
361.1
449.1
98.2
8.3
57.7
13.4
688.3
28.5
43.2
8.5
Urban
14.0
0.9
140.4
71.8
2 312.2
53.6
43.4
280.3
228.0
5.4
12.1
225.9
183.5
94.2
8.1
48.9
29.7
386.5
92.8
36.7
4.3
Rural
Consumption
193.0
4.0
1 220.3
893.7
18 900.6
108.6
79.2
455.2
285.6
13.8
19.4
587.0
632.6
192.4
16.4
106.6
43.1
1 074.8
121.3
79.9
12.8
Total
65.0
4.0
1 711.5
2 192.1
19 385.6
123.6
79.2
455.2
285.6
13.6
14.4
592.0
593.4
202.4
13.5
101.6
43.1
924.8
126.3
77.9
0.5
Production
BEEF 2030
128.0
0.0
0.0
0.0
1 954.9
0.0
0.0
0.0
0.0
0.2
5.0
0.0
40.1
0.0
2.9
5.0
0.0
150.0
0.0
2.0
12.3
Import
0.0
0.0
491.1
1 300.0
2 391.1
15.0
0.0
0.0
0.0
0.0
0.0
5.0
0.0
10.0
0.0
0.0
0.0
0.0
5.0
0.0
0.0
Export
Annex C
53
54
413.2
15.4
16.7
107.4
11.1
34.1
4.8
2 018.5
75.6
434.5
50.6
116.3
1.1
10 323.6
Norway
Saudi Arabia
Switzerland
United States of America
Trinidad and Tobago
Republic of Korea
Japan
99.9
Rural
796.2
Urban
Consumption
New Zealand
COUNTRY
12 342.1
5.9
150.4
61.7
541.9
92.3
115.3
1 209.4
Total
11 770.8
0.9
136.7
20.0
291.2
90.2
575.9
503.2
Production
BEEF 2000
2 036.8
6.0
15.7
44.9
260.5
5.6
11.0
909.0
Import
1 403.6
1.0
2.0
3.3
9.8
3.5
485.7
2.5
Export
11 935.0
2.5
94.2
168.5
778.2
81.8
110.1
1 334.1
Urban
1 399.3
5.8
22.3
23.4
122.5
17.4
13.3
481.2
Rural
Consumption
13 334.3
8.3
116.5
191.9
900.7
99.2
123.4
1 815.3
Total
13 038.7
1.4
106.5
31.9
650.7
99.2
723.4
761.2
Production
BEEF 2030
300.0
6.9
10.0
160.0
250.0
0.0
0.0
1 100.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
600.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
47.3
190.1
81.0
474.9
100.2
88.5
337.3
82.8
254.4
Malaysia
Myanmar
Philippines
Thailand
Viet Nam
Eastern Europe and
Central Asia
Russian Federation
Turkey
509.1
Indonesia
Lao People’s Dem. Rep.
16.9
5 383.8
48.3
6 940.2
Urban
14.6
-62.2
-47.7
48.9
45.7
64.1
36.7
11.1
22.2
74.7
2.4
1 504.5
47.7
1 857.9
Rural
Total
269.0
20.6
289.6
137.4
145.9
539.0
117.7
201.2
69.5
583.8
19.3
6 888.3
96.0
8 798.1
Absolute change
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
111.6
4.7
17.1
198.4
138.4
227.8
231.8
239.1
583.6
295.9
129.6
203.3
380.4
210.7
Urban
12.1
-9.9
-6.4
34.6
28.8
43.2
41.8
23.7
76.4
31.9
31.0
58.2
90.1
53.2
Rural
Percent change
Consumption
77.1
0.9
10.6
73.9
63.1
151.0
95.8
159.3
186.8
143.7
93.2
131.6
146.3
129.6
Total
40.9
2 612.0
34.4
50.3
44.4
54.1
43.6
33.8
59.7
77.5
78.6
25.6
44.9
-2 047.8
52.3
37.7
33.3
30.2
33.3
40.6
21.7
13.0
10.5
54.1
268.6
20.3
288.9
137.5
56.6
429.2
112.8
4.8
76.7
465.1
14.5
6 923.7
94.5
8 315.4
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
76.9
1.1
13.0
74.0
29.3
198.0
81.9
36.4
182.6
143.1
70.7
130.7
140.8
127.9
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
-0.1
-5.6
-5.7
-0.1
83.6
109.6
0.0
193.8
0.0
118.6
4.8
-9.0
0.0
501.3
Absolute
change
-100.0
-1.1
-1.1
-100.0
192.2
78.1
167.5
145.7
2 400.0
-100.0
128.4
Percent
change
Import
-0.5
-5.9
-6.4
0.0
-5.8
-0.2
-4.8
-2.5
7.2
-0.1
0.0
26.4
-1.6
18.6
-100.0
-100.0
-100.0
-100.0
-100.0
-32.4
-100.0
150.0
-100.0
35.9
-100.0
18.0
Absolute Percent
change change
Export
Table C 2. Change in consumption and production of beef between 2000 and 2030 (absolute change is in thousands of metric tonnes, proportional change
in percentage).
Annex C
55
56
225.3
465.7
29.3
32.7
45.6
170.8
Chile
Colombia
Costa Rica
Cuba
Dominican Republic
Ecuador
1 449.9
Mexico
Honduras
8.2
47.1
Haiti
Jamaica
0.3
35.3
Guyana
84.3
3 256.6
Brazil
Guatemala
147.2
Bolivia
41.3
-56.3
515.2
Argentina
El Salvador
51.1
Latin America/Caribbean 7 250.9
114.7
1.5
16.0
-0.6
0.2
37.3
11.2
16.9
-3.6
21.3
-2.9
33.5
-1.2
-201.1
17.8
Rural
Total
1 564.6
9.7
63.1
34.7
0.5
121.6
52.5
187.7
42.0
54.0
26.4
499.2
224.1
3 055.5
165.0
458.9
7 302.0
Absolute change
Urban
COUNTRY
109.0
76.3
190.9
247.2
54.3
275.8
160.4
162.2
106.5
80.8
72.4
88.9
81.5
69.1
141.4
25.9
72.3
Urban
25.8
14.9
54.2
-2.4
12.3
101.3
60.8
23.9
-14.0
63.1
-10.8
17.0
-2.5
-16.1
32.2
-32.3
1.9
Rural
Percent change
Consumption
88.2
46.9
116.4
92.8
26.3
180.4
118.8
106.5
61.2
72.8
39.1
69.2
69.1
51.3
103.4
21.2
57.5
Total
44.6
25.8
26.1
42.2
144.2
29.1
45.7
45.0
31.5
97.1
-17.9
24.8
38.7
33.2
26.5
-35.8
39.7
66.2
56.7
41.6
-32.0
46.5
35.2
37.2
57.4
1.7
126.8
64.2
48.4
57.1
57.6
146.9
1 354.2
5.6
64.4
34.8
0.5
127.0
47.9
188.1
42.2
54.1
31.8
518.5
174.6
4 179.7
165.8
1 079.7
9 317.4
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
91.3
40.0
121.7
93.3
26.3
204.8
166.3
106.9
61.7
73.0
38.7
70.4
78.0
63.9
104.5
41.0
67.9
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
67.0
4.0
-2.9
-0.2
0.0
-7.7
4.6
-0.4
-0.2
-0.1
-2.3
-2.7
48.9
-53.2
-1.3
-16.8
48.3
Absolute
change
15.5
57.1
-100.0
-100.0
-100.0
29.9
-100.0
-100.0
-100.0
-100.0
-100.0
48.4
-100.0
-100.0
-100.0
7.3
Percent
change
Import
-145.0
-0.2
-1.6
0.0
0.0
-2.4
0.0
0.0
0.0
0.0
3.1
5.0
-0.6
1 071.0
-0.7
535.1
1 956.4
-100.0
-100.0
-100.0
-100.0
18.3
100.0
-100.0
170.3
-100.0
172.3
134.3
Absolute Percent
change change
Export
Mapping supply and demand for animal-source foods to 2030
41.9
23.7
88.4
50.2
Libyan Arab Jamahiriya
Morocco
Syrian Arab Republic
173.3
Iraq
Lebanon
312.4
Iran (Islamic Republic of)
19.2
404.6
Egypt
Jordan
180.7
523.7
Middle East/North Africa 1 405.7
Algeria
-5.0
19.3
19.0
3.1
2.8
3.1
66.9
33.0
293.4
18.2
-2.7
36.4
304.6
0.0
20.5
Venezuela
116.1
Peru
18.1
Uruguay
152.6
Paraguay
-2.6
18.0
2.1
40.9
Rural
Suriname
43.5
Panama
Urban
299.6
33.7
2.1
136.6
170.7
38.3
61.5
Total
69.5
107.4
26.8
44.7
22.3
240.2
345.4
698.0
198.9
1 929.4
Absolute change
Nicaragua
COUNTRY
213.1
117.8
132.4
137.7
95.2
523.1
152.9
115.4
182.0
154.7
86.9
22.0
66.8
143.5
138.5
109.8
302.3
Urban
88.0
28.9
55.9
60.2
54.9
453.0
29.7
61.3
43.3
64.3
-9.4
-18.8
5.2
85.2
19.9
-13.6
155.2
Rural
Percent change
Consumption
152.7
76.3
114.5
127.4
86.4
501.5
109.4
84.1
140.7
112.0
74.3
18.7
58.3
130.1
84.8
68.0
236.5
Total
29.9
27.2
33.5
53.8
10.0
41.5
43.3
17.1
46.2
19.4
1.3
64.5
46.6
2.7
14.4
38.6
48.2
60.3
48.1
27.4
82.9
19.0
38.5
72.4
32.6
70.5
98.5
25.8
33.2
95.2
77.9
32.1
59.8
95.0
4.1
2.0
0.3
65.2
333.8
705.1
179.3
1 571.3
306.3
496.7
1.9
122.9
174.4
38.0
108.3
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
132.3
68.7
68.3
20.0
42.9
136.1
116.2
142.5
142.3
124.8
73.2
119.1
95.0
90.6
70.5
59.6
175.5
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
9.7
12.2
35.4
19.4
20.3
174.9
11.6
-7.4
19.5
345.0
8.9
-0.2
1.3
6.7
-1.5
-1.0
-2.6
Absolute
change
3 233.3
435.7
753.2
39.0
75.7
174 900.0
40.8
-2.2
125.8
72.2
161.8
-100.0
260.0
203.0
-100.0
-100.0
-100.0
Percent
change
Import
0.0
-0.6
0.0
-0.1
-1.6
0.0
0.0
-0.3
0.0
-2.7
-0.2
448.8
0.0
0.0
2.2
-2.0
43.9
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
178.7
4.6
-28.6
113.7
Absolute Percent
change change
Export
Annex C
57
58
101.2
875.9
76.5
840.7
4.0
Bangladesh
India
Nepal
Pakistan
Sri Lanka
5.1
84.2
31.6
Burundi
Cameroon
Central African Republic
5.5
53.2
Burkina Faso
14.2
Benin
Botswana
164.7
Angola
2 389.4
131.6
Afghanistan
Sub-Saharan Africa
2 029.9
70.8
Yemen
South Asia
40.5
Urban
18.9
7.8
15.9
74.3
0.2
7.2
28.3
1 378.6
5.8
559.8
79.7
462.2
76.1
153.5
1 337.1
61.1
3.8
Rural
131.9
44.3
Total
50.5
92.0
21.0
127.5
5.7
21.4
193.0
3 768.0
9.8
1 400.5
156.2
1 338.1
177.3
285.1
3 367.0
Absolute change
Tunisia
COUNTRY
128.5
170.3
648.5
493.1
131.7
199.5
296.4
199.9
71.4
286.0
335.3
119.5
242.3
399.5
179.6
475.8
102.9
Urban
54.1
18.0
193.3
172.3
9.0
63.1
61.7
64.2
20.7
94.5
54.3
24.4
57.0
161.8
46.3
150.4
16.5
Rural
Percent change
Consumption
84.9
98.9
233.3
236.5
83.8
115.7
190.1
112.7
29.3
158.1
92.0
50.9
101.2
223.1
83.7
237.7
71.2
Total
29.9
38.6
22.9
18.4
122.7
9.5
13.6
37.3
22.5
11.8
16.4
25.7
17.3
8.6
44.9
56.0
44.5
50.3
56.8
-11.2
81.5
68.7
56.5
57.2
79.5
77.2
59.0
59.6
76.0
41.8
50.5
91.9
21.0
142.2
24.7
20.1
194.3
3 555.2
9.8
1 399.1
155.9
1 405.0
177.3
285.1
3 432.2
83.8
42.9
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
88.6
98.7
233.3
205.5
90.8
119.6
228.6
107.8
29.3
157.6
91.7
49.1
101.2
223.1
80.7
192.2
72.0
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
-0.9
-0.1
0.0
-0.2
-2.7
1.3
-1.3
223.3
-0.1
0.0
-0.6
-0.2
0.0
0.0
-0.9
48.0
1.4
Absolute
change
-26.5
-100.0
-100.0
-100.0
76.5
-7.9
129.1
-100.0
-100.0
-100.0
-100.0
400.0
53.8
Percent
change
Import
-0.9
-0.1
0.0
14.5
16.1
0.0
0.0
14.6
-0.1
-1.4
-0.9
66.7
0.0
0.0
64.3
-0.1
0.0
-100.0
-100.0
93.5
69.1
11.7
-100.0
-100.0
-100.0
28.6
27.3
-100.0
Absolute Percent
change change
Export
Mapping supply and demand for animal-source foods to 2030
6.0
81.9
15.3
Mali
Mauritania
86.1
Madagascar
Malawi
2.9
Liberia
Kenya
2.3
34.6
111.0
Guinea
Lesotho
37.3
136.3
Ethiopia
Ghana
13.9
Eritrea
3.8
46.7
Dem. Rep. of the Congo
Gambia
48.5
Cote d’Ivoire
4.8
7.1
Gabon
64.1
Congo
Urban
9.9
54.1
4.3
65.5
0.6
-1.4
116.4
20.9
10.4
0.5
0.1
215.0
18.2
39.3
14.1
2.4
54.7
Rural
Absolute change
Chad
COUNTRY
25.2
136.0
10.3
151.6
3.5
0.9
227.4
55.5
47.7
4.3
4.9
351.3
32.1
86.0
62.6
9.5
118.8
Total
319.5
304.0
254.5
194.9
262.7
126.8
187.7
287.3
288.4
198.1
127.7
280.7
459.3
696.0
211.5
304.7
309.2
Urban
176.2
82.6
32.9
62.1
68.2
-20.0
51.1
102.2
72.1
31.1
13.7
86.9
135.3
275.2
45.9
135.4
98.8
Rural
Percent change
Consumption
242.3
147.2
66.5
101.3
175.0
10.2
79.3
170.8
174.1
126.5
114.0
118.7
194.5
409.5
116.6
231.7
156.1
Total
26.9
-0.3
-7.0
27.2
10.4
258.0
41.7
27.7
37.1
21.4
27.7
10.8
19.4
32.2
40.6
22.1
8.7
44.2
100.8
112.2
60.3
75.7
-125.0
43.8
49.1
38.3
61.8
54.9
79.1
58.5
29.3
40.3
51.5
80.3
24.2
134.0
10.3
151.6
1.8
0.2
227.3
54.9
18.4
3.9
1.5
351.3
32.1
33.5
49.4
3.0
118.1
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
147.6
117.1
66.5
101.3
225.0
2.7
79.2
165.9
85.2
118.2
214.3
118.7
198.1
248.1
193.0
187.5
136.1
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
0.0
0.0
0.0
0.0
1.7
0.7
-0.1
-0.7
29.3
0.5
3.5
0.0
0.1
52.5
13.1
6.5
0.0
Absolute
change
141.7
53.8
-100.0
-100.0
505.2
100.0
50.0
700.0
46.5
260.0
Percent
change
Import
-1.0
-2.0
0.0
0.0
0.0
-0.1
-0.2
-1.4
-0.1
0.0
0.0
-0.1
0.0
0.0
0.0
0.0
-0.7
-16.7
-9.1
-100.0
-100.0
-100.0
-100.0
-100.0
-6.5
Absolute Percent
change change
Export
Annex C
59
60
High income countries
3 010.5
25.3
125.2
United Republic of Tanzania
Zimbabwe
45.9
Uganda
20.6
6.2
Togo
Zambia
2.9
248.4
Swaziland
129.5
Sudan
36.3
Senegal
South Africa
10.2
Rwanda
77.1
539.1
Nigeria
Somalia
21.8
Niger
5.8
30.8
Mozambique
Sierra Leone
3.2
Urban
-569.1
-5.0
15.7
106.6
141.6
2.2
-1.5
45.7
-61.4
55.2
4.0
19.4
14.7
194.8
58.5
9.7
0.8
Rural
20.3
36.3
231.8
187.5
8.4
1.4
294.1
68.1
132.3
9.8
55.7
24.9
733.9
80.3
40.5
4.0
Total
2 441.4
Absolute change
Mauritius
COUNTRY
22.2
84.8
135.4
252.1
391.9
270.8
64.6
220.4
40.5
366.9
231.4
169.7
320.2
361.3
325.9
247.2
58.8
Urban
-19.8
-8.5
56.7
61.3
163.9
71.4
-10.9
25.4
-25.1
141.2
97.7
65.8
97.7
101.7
170.5
36.1
24.6
Rural
Percent change
Consumption
14.8
23.0
84.6
103.8
191.1
155.6
7.8
100.4
12.1
220.1
148.5
109.4
136.8
215.3
195.9
102.8
45.5
Total
94.4
31.0
23.8
3.7
27.9
131.2
24.6
139.8
6.6
22.9
14.8
25.5
34.9
2.5
35.1
43.4
4.6
54.6
61.1
90.1
50.2
-28.4
60.4
-34.0
81.6
57.5
73.3
55.2
37.2
93.1
47.7
47.3
2 079.9
21.8
36.5
231.8
187.6
8.4
-0.2
293.5
35.2
132.2
8.8
52.8
25.0
639.7
81.4
40.5
0.0
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
12.0
21.4
85.5
103.8
191.4
161.5
-1.4
98.3
6.3
188.3
187.2
108.2
138.1
224.4
181.3
108.3
0.0
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
-1 794.4
-0.2
-0.2
-0.1
0.0
-0.1
-0.1
-0.3
19.9
0.0
1.0
2.8
-0.1
94.2
-0.1
0.0
3.4
Absolute
change
-47.9
-100.0
-100.0
-100.0
-33.3
-2.0
-100.0
98.5
52.6
127.3
-100.0
168.8
-100.0
0.0
38.2
Percent
change
Import
-1 954.2
1.2
0.0
-0.1
0.0
0.0
-1.6
-0.9
-8.3
-0.1
0.0
0.0
0.0
0.0
1.0
0.0
-0.6
-45.0
8.7
-100.0
-100.0
-15.3
-100.0
-1.0
25.0
-100.0
Absolute Percent
change change
Export
Mapping supply and demand for animal-source foods to 2030
-0.5
65.5
537.9
Iceland
Israel
Japan
-22.1
Switzerland
United States of America
1 611.4
1.4
117.9
Saudi Arabia
Trinidad and Tobago
343.6
6.2
Republic of Korea
Norway
10.2
197.8
New Zealand
141.1
Canada
Urban
-619.2
1.0
-11.8
12.3
15.2
0.7
-2.1
68.0
3.0
0.8
-11.0
-25.9
Rural
Absolute change
Australia
COUNTRY
992.2
2.4
-33.9
130.2
358.8
6.9
8.1
605.9
68.5
0.3
186.8
115.2
Total
15.6
128.6
-19.0
232.8
79.1
8.2
10.2
67.6
57.7
-13.2
22.4
20.7
Urban
-30.7
20.3
-34.7
111.3
14.1
4.1
-13.7
16.5
27.2
546.7
-7.2
-26.5
Rural
Percent change
Consumption
8.0
40.7
-22.5
211.0
66.2
7.5
7.0
50.1
55.0
8.1
18.1
14.8
Total
-209.8
90.1
73.3
28.2
83.9
-29.0
-130.4
114.9
8.0
-93.9
-9.8
-52.4
372.7
7.2
32.0
45.0
10.4
131.9
253.6
-9.4
88.1
209.9
111.7
165.2
1 267.9
0.5
-30.2
11.9
359.5
9.0
147.5
258.0
27.9
0.3
94.9
-67.3
Proportion Proportion
of change of change
due to Absolute
due to
change in change in change
consump. population
%
rates %
10.8
55.6
-22.1
59.5
123.5
10.0
25.6
51.3
75.2
8.1
5.9
-3.0
Percent
change
Production
BEEF, CHANGE BETWEEN 2000 AND 2030
-1 736.8
0.9
-5.7
115.1
-10.5
-5.6
-11.0
191.0
40.3
0.0
-366.2
-5.9
Absolute
change
-85.3
15.0
-36.3
256.3
-4.0
-100.0
-100.0
21.0
46.0
-100.0
-100.0
Percent
change
Import
-1 403.6
-1.0
-2.0
-3.3
-9.8
-3.5
114.3
-2.5
0.0
0.0
-455.9
-186.9
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
23.5
-100.0
-48.1
-12.6
Absolute Percent
change change
Export
Annex C
61
62
73.6
Viet Nam
194.0
15 420.6
1 462.8
Bolivia
Brazil
Chile
7 585.2
Latin America/Caribbean
Argentina
5 236.0
43 096.7
Turkey
16 116.7
430.2
Thailand
Russian Federation
885.6
Philippines
21 352.7
197.9
Myanmar
Eastern Europe and
Central Asia
725.2
Malaysia
4.9
688.4
Indonesia
Lao People’s Dem. Rep.
53.8
5 656.6
8.7
8 724.8
Urban
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
253.2
4 087.3
98.4
664.2
12 514.4
2 757.6
5 803.8
8 561.4
232.0
942.9
629.1
496.8
426.0
17.4
936.7
31.1
5 503.4
35.8
9 251.3
Rural
Consumption
1 716.0
19 507.9
292.4
8 249.4
55 611.1
7 993.6
21 920.5
29 914.1
305.6
1 373.1
1 514.7
694.7
1 151.2
22.3
1 625.1
84.9
11 160.0
44.5
17 976.1
Total
2 086.9
20 535.7
251.1
10 212.1
58 054.3
9 790.5
32 517.3
42 307.8
81.4
516.3
10.3
619.3
37.1
5.9
768.6
89.3
12 325.9
20.4
14 474.5
Production
MILK 2000
168.2
1 429.1
82.3
90.6
7 054.6
78.4
1 371.8
1 450.2
226.8
963.4
1 605.9
120.1
1 334.9
16.8
1 187.4
0.0
599.9
25.3
6 080.5
Import
139.8
37.1
20.8
1 431.3
2 601.1
19.0
1 120.5
1 139.5
0.0
138.1
59.1
0.0
135.0
0.0
243.3
0.0
202.9
0.0
778.4
Export
2 973.1
29 436.7
540.1
11 335.2
81 393.4
10 411.8
16 011.0
26 422.8
332.0
1 658.1
2 431.4
641.6
1 795.2
33.2
2 200.9
111.6
17 953.3
44.5
27 201.9
Urban
276.6
3 875.0
150.2
535.8
14 035.2
2 916.6
4 938.7
7 855.3
473.3
1 962.3
754.9
688.8
383.8
30.2
991.8
38.2
9 142.7
73.2
14 539.1
Rural
Consumption
3 249.7
33 311.7
690.3
11 871.0
95 428.6
13 328.4
20 949.7
34 278.1
805.3
3 620.4
3 186.3
1 330.4
2 179.0
63.4
3 192.7
149.8
27 096.0
117.7
41 741.0
Total
3 940.1
36 174.3
682.7
15 290.2
102 050.1
15 905.2
31 649.0
47 554.2
262.1
2 474.9
20.7
1 188.0
90.8
21.0
2 441.3
155.1
29 613.4
40.0
36 307.3
Production
MILK 2030
Table C 3. Consumption and production of milk in 2000 and 2030 (all measures are in thousands of metric tonnes).
55.1
803.3
51.7
0.0
7 695.0
174.4
250.1
424.5
550.0
1 200.0
3 170.0
201.7
2 279.7
53.9
1 009.6
0.2
893.2
80.6
9 438.9
Import
0.0
0.0
0.0
2 501.9
3 505.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
211.8
Guatemala
203.7
Paraguay
23.5
604.5
1 756.6
9 591.2
2 294.7
Suriname
Uruguay
Venezuela
Middle East/North Africa
Algeria
1 016.3
132.7
Panama
Peru
103.2
Mexico
Nicaragua
57.8
8 267.8
Jamaica
316.7
315.2
El Salvador
Honduras
719.8
Ecuador
49.8
313.1
Dominican Republic
Haiti
559.9
Cuba
22.2
398.5
Costa Rica
Guyana
3 360.9
Urban
Colombia
COUNTRY
971.7
6 598.9
262.7
53.2
3.7
300.7
167.7
67.7
83.2
2 764.1
53.3
378.7
80.8
46.2
254.5
225.8
484.9
188.1
466.5
266.6
1 263.0
Rural
Consumption
3 266.4
16 190.1
2 019.3
657.7
27.2
1 317.0
371.4
200.4
186.4
11 031.9
111.1
695.4
130.6
68.4
466.3
541.0
1 204.7
501.2
1 026.4
665.1
4 623.9
Total
1 478.2
16 271.7
1 388.8
1 465.4
13.2
1 084.8
368.6
170.8
234.4
9 354.4
28.4
575.8
63.0
30.0
262.7
379.8
2 064.5
406.3
617.5
758.5
5 701.6
Production
MILK 2000
1 862.2
3 785.2
641.4
5.5
9.5
273.7
22.6
59.1
54.2
2 774.0
94.9
125.8
70.3
38.4
205.3
186.4
10.7
115.7
439.7
32.5
124.7
Import
0.0
137.3
5.2
524.7
0.0
8.1
1.4
17.5
107.3
123.4
9.9
5.9
0.0
0.0
2.3
5.5
5.6
0.0
0.0
42.4
112.9
Export
4 965.6
23 570.8
3 277.3
822.5
31.9
2 033.4
647.2
309.8
378.9
15 802.4
104.0
872.3
157.9
40.3
600.3
721.9
1 775.6
662.4
776.8
938.4
7 154.7
Urban
1 068.9
10 532.6
236.9
48.3
3.2
457.0
268.1
64.9
193.9
3 166.3
62.5
552.8
71.7
60.4
386.8
319.8
564.6
165.3
583.8
324.1
1 667.5
Rural
Consumption
6 034.5
34 103.4
3 514.2
870.8
35.1
2 490.4
915.3
374.7
572.8
18 968.7
166.5
1 425.1
229.6
100.7
987.1
1 041.7
2 340.2
827.7
1 360.6
1 262.5
8 822.2
Total
3 671.1
33 022.7
2 263.7
2 315.6
19.1
2 296.1
915.6
325.7
580.3
16 541.6
43.9
1 345.4
107.9
80.7
587.1
871.9
4 059.1
603.6
1 079.8
1 320.5
10 605.2
Production
MILK 2030
2 500.0
7 785.9
1 300.0
0.0
17.5
270.7
30.9
50.0
0.0
3 580.2
125.0
80.0
126.5
20.0
400.0
204.8
0.0
251.8
321.7
0.0
5.8
Import
0.0
0.0
0.0
990.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
4.4
0.0
0.0
8.7
0.0
Export
Annex C
63
64
595.9
143.3
Tunisia
Yemen
111.9
24.9
134.9
Angola
Benin
Botswana
6 850.1
126.5
Sri Lanka
Sub-Saharan Africa
7 514.1
126.3
Nepal
Pakistan
18 564.6
India
458.9
749.7
Syrian Arab Republic
Bangladesh
532.2
Morocco
388.3
284.1
Libyan Arab Jamahiriya
Afghanistan
358.8
Lebanon
27 178.8
264.8
Jordan
South Asia
434.0
2 489.1
Iraq
1 444.7
Iran (Islamic Republic of)
Urban
Egypt
COUNTRY
87.2
39.7
92.4
12 678.7
625.9
15 134.3
808.1
47 882.7
1 464.9
1 116.5
67 032.3
389.4
343.8
695.8
464.5
86.0
55.4
73.5
192.8
1 355.2
1 970.7
Rural
Consumption
222.1
64.6
204.3
19 528.8
752.4
22 648.4
934.4
66 447.3
1 923.8
1 504.8
94 211.1
532.7
939.7
1 445.5
996.7
370.1
414.2
338.3
626.8
3 844.3
3 415.4
Total
104.1
29.0
193.7
19 116.9
295.8
28 364.6
1 172.0
81 626.6
2 115.7
1 661.8
115 236.5
228.0
918.3
1 635.6
1 215.7
207.6
208.2
195.3
534.6
5 807.4
3 842.8
Production
MILK 2000
154.4
37.2
22.3
2 261.3
478.0
91.0
14.8
68.0
333.9
3.6
989.3
319.3
71.1
92.6
137.5
193.8
357.2
171.5
141.2
61.6
377.2
Import
0.5
0.2
0.0
321.8
1.2
0.8
0.0
289.3
0.2
0.0
291.5
2.9
10.6
9.6
45.1
0.0
2.1
18.6
0.0
20.8
27.6
Export
175.0
85.0
449.0
20 279.1
252.2
27 478.5
650.7
59 327.0
1 959.1
1 593.9
91 261.4
787.7
1 237.7
1 935.2
1 242.5
588.1
573.9
610.8
2 520.0
5 684.2
3 425.1
Urban
52.9
73.4
151.4
20 189.0
874.7
27 846.4
1 475.9
86 450.4
2 839.7
2 405.0
121 892.1
932.2
410.4
1 083.5
640.8
119.0
59.6
134.4
994.6
1 587.8
3 501.4
Rural
Consumption
227.9
158.4
600.4
40 468.1
1 126.9
55 324.9
2 126.6
145 777.4
4 798.8
3 998.9
213 153.5
1 719.9
1 648.1
3 018.7
1 883.3
707.1
633.5
745.2
3 514.6
7 272.0
6 926.5
Total
159.8
87.0
576.7
39 507.1
498.9
65 297.1
2 622.9
178 407.8
5 361.1
4 400.8
256 588.6
557.3
1 617.3
3 392.5
2 223.9
477.4
449.5
550.3
1 966.5
10 441.7
7 675.2
Production
MILK 2030
119.6
75.0
49.5
3 649.3
659.3
616.6
22.0
233.0
661.9
23.8
2 216.6
1 200.0
100.6
187.1
215.7
247.1
400.0
215.7
1 735.7
283.3
700.7
Import
0.0
0.0
0.0
140.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
12.9
14.2
206.7
34.5
19.0
55.2
39.3
531.4
Dem. Rep. of the Congo
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Kenya
162.5
160.6
Mauritania
6.4
155.0
Mali
Malawi
Madagascar
4.1
49.1
Cote d’Ivoire
Liberia
20.8
Congo
5.8
56.4
Chad
Lesotho
25.4
121.2
2.9
51.3
Urban
Central African Republic
Cameroon
Burundi
Burkina Faso
COUNTRY
187.7
392.6
35.7
369.3
3.4
22.0
2 042.5
66.6
61.1
14.3
4.7
1 052.4
63.6
27.1
65.7
15.6
150.4
35.9
106.7
29.9
204.2
Rural
Consumption
348.3
555.1
42.1
524.3
7.5
27.8
2 573.9
105.9
116.3
33.3
39.2
1 259.1
77.8
40.0
114.8
36.4
206.8
61.3
227.9
32.8
255.5
Total
320.6
500.2
34.7
533.3
0.7
23.5
2 705.9
79.0
34.2
7.6
1.6
1 304.7
67.9
5.2
24.7
1.0
219.8
62.8
184.0
29.3
221.0
Production
MILK 2000
45.1
65.4
9.2
18.3
6.8
6.0
25.9
31.0
84.9
26.2
37.8
7.8
13.3
35.0
137.0
35.5
4.7
1.7
56.4
5.0
50.1
Import
0.1
0.0
0.1
0.2
0.0
0.0
2.8
0.2
1.0
0.1
0.0
0.0
0.0
0.0
53.2
0.1
0.0
0.0
3.3
0.0
0.7
Export
418.5
717.3
23.6
519.6
17.4
14.4
1 322.5
122.8
185.5
49.2
75.4
888.7
67.8
80.7
142.8
83.9
239.3
70.0
267.4
27.0
266.4
Urban
321.6
785.0
49.8
681.1
6.5
19.3
2 668.1
108.5
92.0
16.3
5.1
2 217.4
127.4
79.8
89.8
37.0
310.1
66.9
102.5
109.5
487.2
Rural
Consumption
740.1
1 502.3
73.4
1 200.7
23.9
33.7
3 990.6
231.3
277.5
65.5
80.5
3 106.1
195.2
160.5
232.6
120.9
549.4
136.9
369.9
136.5
753.6
Total
694.7
1 380.8
48.6
1 197.7
2.0
29.1
4 146.2
188.9
131.6
26.3
6.2
3 177.5
176.5
61.4
74.5
3.0
581.1
138.6
332.1
111.0
777.6
Production
MILK 2030
70.7
150.0
27.2
46.2
22.0
6.0
24.2
50.0
150.0
40.0
74.7
59.8
25.1
100.0
160.0
117.9
5.5
3.1
50.0
30.0
9.9
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
65
66
18.8
116.1
Rwanda
Senegal
4 348.9
5 411.9
56.4
Australia
Canada
Iceland
83 285.1
80.5
High income countries
Zimbabwe
179.3
United Republic of
Tanzania
24.8
58.7
Uganda
Zambia
8.7
Togo
18.7
1 822.6
Sudan
Swaziland
1 364.3
South Africa
554.6
423.9
Nigeria
Somalia
52.7
Niger
10.8
30.9
Sierra Leone
78.7
Mozambique
Urban
Mauritius
COUNTRY
11.5
928.7
623.7
17 986.0
157.9
45.1
626.4
429.5
11.8
56.6
2 911.4
1 043.8
1 029.4
17.5
159.8
88.3
544.2
269.4
66.4
50.1
Rural
Consumption
67.9
6 340.6
4 972.6
101 271.1
238.4
69.9
805.7
488.2
20.5
75.3
4 734.0
2 408.1
1 584.0
28.3
275.9
107.1
968.1
322.1
97.3
128.8
Total
105.8
8 120.0
10 850.7
124 661.4
306.7
63.3
804.4
510.4
9.0
36.3
4 893.0
2 557.0
2 194.5
21.2
142.3
100.6
408.6
307.6
68.7
4.8
Production
MILK 2000
1.0
566.9
451.7
10 283.6
10.2
12.0
24.4
2.4
14.3
54.6
45.0
149.1
6.6
8.1
147.8
11.5
661.5
37.8
32.4
126.6
Import
0.7
791.4
6 130.3
19 962.1
50.0
1.9
1.1
0.5
5.4
11.3
0.0
175.7
0.0
0.0
7.3
0.0
2.2
2.3
0.0
1.6
Export
59.8
7 047.8
5 423.9
116 530.5
168.3
51.7
700.6
297.7
27.3
32.2
6 064.4
2 096.0
2 317.4
33.4
293.4
96.5
1 352.7
207.4
108.1
123.0
Urban
17.6
914.0
472.4
16 052.6
163.7
62.5
1 120.3
1 173.2
17.3
52.9
3 788.0
855.9
2 222.1
32.2
248.2
212.9
755.6
672.4
91.5
61.5
Rural
Consumption
77.4
7 961.8
5 896.3
132 583.1
332.0
114.2
1 820.9
1 470.9
44.6
85.1
9 852.4
2 951.9
4 539.5
65.6
541.6
309.4
2 108.3
879.8
199.6
184.5
Total
121.7
9 060.4
19 200.0
167 488.9
408.1
103.0
1 840.4
1 502.3
18.5
59.5
10 208.6
3 210.2
5 425.3
47.8
335.6
308.1
922.2
827.5
176.2
4.9
Production
MILK 2030
0.0
0.0
0.0
5 151.2
0.0
15.0
30.0
21.6
23.0
35.1
68.8
0.0
30.3
20.0
220.0
11.5
1 405.4
91.2
30.0
181.0
Import
0.3
417.9
12 730.6
27 647.6
40.6
0.0
0.0
0.0
0.0
0.0
0.0
100.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
1 654.2
Switzerland
United States of America
60 864.0
23.8
1 595.1
Saudi Arabia
Trinidad and Tobago
1 023.6
949.2
Norway
Republic of Korea
657.0
5 543.0
Japan
New Zealand
1 157.9
Urban
Israel
COUNTRY
11 908.4
102.7
485.8
344.8
252.7
239.9
101.2
2 875.4
111.3
Rural
Consumption
72 772.4
126.5
2 140.0
1 939.9
1 276.3
1 189.1
758.2
8 418.4
1 269.2
Total
74 965.2
10.4
3 919.9
923.9
2 282.7
1 741.2
12 092.8
8 419.2
1 229.6
Production
MILK 2000
4 807.9
137.2
344.6
1 278.2
308.9
31.2
56.1
2 167.6
132.3
Import
2 241.1
10.9
676.3
211.6
9.2
199.0
9 669.9
13.1
8.6
Export
83 953.0
48.2
1 614.9
4 355.3
2 379.1
1 033.4
696.0
8 004.8
1 914.4
Urban
9 843.9
109.3
381.7
601.6
373.2
219.4
83.9
2 886.8
148.7
Rural
Consumption
93 796.9
157.5
1 996.6
4 956.9
2 752.3
1 252.8
779.9
10 891.6
2 063.1
Total
95 625.2
14.3
4 079.7
3 563.5
4 669.5
2 046.7
16 200.0
10 811.9
2 096.0
Production
MILK 2030
0.0
144.0
0.0
1 500.0
672.2
0.0
0.0
2 710.1
124.9
Import
0.0
0.0
421.1
0.0
0.0
171.9
13 905.8
0.0
0.0
Export
Annex C
67
68
5 175.8
Turkey
258.4
Viet Nam
-105.7
1 227.9
Thailand
Russian Federation
1 545.8
Philippines
5 070.1
443.7
Myanmar
Eastern Europe and
Central Asia
1 070.1
28.3
1 512.5
57.9
12 296.7
35.9
18 477.1
Urban
159.0
-865.1
-706.1
241.3
1 019.4
125.8
192.0
-42.3
12.8
55.1
7.0
3 639.3
37.3
5 287.8
Rural
Total
5 334.8
-970.8
4 364.0
499.7
2 247.3
1 671.6
635.7
1 027.8
41.1
1 567.6
64.9
15 936.0
73.2
23 764.9
Absolute change
Malaysia
Lao People’s Dem. Rep.
Indonesia
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
98.9
-0.7
23.7
350.9
285.4
174.6
224.3
147.6
573.5
219.7
107.6
217.4
413.4
211.8
Urban
5.8
-14.9
-8.2
104.0
108.1
20.0
38.6
-9.9
73.9
5.9
22.6
66.1
104.2
57.2
Rural
Percent change
Consumption
66.7
-4.4
14.6
163.5
163.7
110.4
91.5
89.3
184.3
96.5
76.4
142.8
164.5
132.2
Total
35.7
-366.4
55.0
69.0
36.2
53.0
26.5
33.5
51.6
75.0
79.3
29.0
51.9
401.3
23.7
14.5
45.6
31.6
59.4
41.1
32.3
15.9
9.7
48.1
6 114.7
-868.3
5 246.4
180.7
1 958.6
10.4
568.7
53.7
15.1
1 672.7
65.8
17 287.5
19.6
21 832.8
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
62.5
-2.7
12.4
222.0
379.4
101.0
91.8
144.7
255.9
217.6
73.7
140.3
96.1
150.8
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
96.0
-1 121.7
-1 025.7
323.2
236.6
1 564.1
81.6
944.8
37.1
-177.8
0.2
293.3
55.3
3 358.4
Absolute
change
122.4
-81.8
-70.7
142.5
24.6
97.4
67.9
70.8
220.8
-15.0
48.9
218.6
55.2
Percent
change
Import
-19.0
-1 120.5
-1 139.5
0.0
-138.1
-59.1
0.0
-135.0
0.0
-243.3
0.0
-202.9
0.0
-778.4
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Table C 4. Change in consumption and production of milk between 2000 and 2030 (absolute change is in thousands of metric tonnes, proportional
change in percentage).
Mapping supply and demand for animal-source foods to 2030
3 793.9
539.9
216.9
349.3
Colombia
Costa Rica
Cuba
Dominican Republic
46.2
7 534.6
555.6
Honduras
Mexico
108.1
Haiti
Jamaica
18.1
388.6
Guatemala
Guyana
406.6
El Salvador
1 055.8
1 510.3
Chile
Ecuador
346.1
14 016.1
Brazil
3 750.0
38 296.7
Urban
402.2
9.2
174.1
-9.1
14.2
132.2
94.1
79.7
-22.8
117.3
57.5
404.4
23.4
-212.3
51.8
-128.4
1 520.8
Rural
Total
7 936.8
55.4
729.7
99.0
32.3
520.8
500.7
1 135.5
326.5
334.2
597.4
4 198.3
1 533.7
13 803.8
397.9
3 621.6
39 817.5
Absolute change
Bolivia
Argentina
Latin America/
Caribbean
COUNTRY
91.1
80.0
175.4
217.0
81.2
183.5
129.0
146.7
111.6
38.7
135.5
112.9
103.2
90.9
178.4
49.4
88.9
Urban
14.6
17.2
46.0
-11.3
30.8
51.9
41.7
16.4
-12.1
25.2
21.6
32.0
9.2
-5.2
52.6
-19.3
12.2
Rural
Percent change
Consumption
71.9
49.9
104.9
75.8
47.2
111.7
92.6
94.3
65.1
32.6
89.8
90.8
89.4
70.8
136.1
43.9
71.6
Total
38.0
28.9
22.4
35.4
128.7
13.6
38.7
41.6
34.1
95.1
30.0
35.3
46.9
45.4
35.2
22.2
48.7
62.2
62.9
50.9
-17.9
75.1
45.1
42.0
54.0
3.8
55.1
49.0
37.4
41.4
43.8
70.9
7 187.2
15.5
769.6
44.9
50.7
324.4
492.1
1 994.6
197.3
462.3
562.0
4 903.6
1 853.2
15 638.6
431.6
5 078.1
43 995.8
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
76.8
54.6
133.7
71.3
169.0
123.5
129.6
96.6
48.6
74.9
74.1
86.0
88.8
76.2
171.9
49.7
75.8
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
806.2
30.1
-45.8
56.2
-18.4
194.7
18.4
-10.7
136.1
-118.0
-32.5
-118.9
-113.1
-625.8
-30.6
-90.6
640.4
Absolute
change
29.1
31.7
-36.4
79.9
-47.9
94.8
9.9
-100.0
117.6
-26.8
-100.0
-95.3
-67.2
-43.8
-37.2
-100.0
9.1
Percent
change
Import
-123.4
-9.9
-5.9
0.0
0.0
-2.3
-5.5
-1.2
0.0
0.0
-33.7
-112.9
-139.8
-37.1
-20.8
1 070.6
903.9
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-21.4
-79.5
-100.0
-100.0
-100.0
-100.0
74.8
34.8
Percent
change
Export
Annex C
69
70
443.5
Paraguay
346.1
215.1
303.9
710.3
Libyan Arab Jamahiriya
Morocco
2 086.1
Iraq
Lebanon
3 195.2
Iran (Islamic Republic
of)
Jordan
1 980.4
13 979.6
Middle East/North
Africa
Egypt
1 520.7
Venezuela
2 670.9
218.0
Uruguay
Algeria
8.4
Suriname
1 017.2
177.1
Panama
Peru
275.8
Urban
176.3
33.1
4.2
60.8
801.7
232.5
1 530.7
97.2
3 933.7
-25.8
-4.9
-0.5
156.2
100.4
-2.8
110.6
Rural
1 494.9
213.1
7.9
1 173.4
543.9
174.3
386.4
Total
886.6
337.0
219.3
406.9
2 887.8
3 427.7
3 511.1
2 768.1
17 913.3
Absolute change
Nicaragua
COUNTRY
133.4
107.0
59.9
130.7
480.7
128.4
137.1
116.4
145.8
86.6
36.1
36.0
100.1
217.7
133.5
267.3
Urban
38.0
38.5
7.6
82.7
415.8
17.2
77.7
10.0
59.6
-9.8
-9.1
-14.7
51.9
59.9
-4.2
132.9
Rural
Percent change
Consumption
89.0
91.1
52.9
120.3
460.7
89.2
102.8
84.7
110.6
74.0
32.4
29.0
89.1
146.4
87.0
207.3
Total
33.1
25.5
25.2
23.6
40.7
37.1
25.3
31.5
19.2
36.4
41.8
35.9
24.8
25.5
36.0
51.7
60.5
66.0
59.5
20.7
47.2
59.3
54.1
70.8
56.9
51.8
48.5
55.2
61.0
36.7
1 008.2
269.8
241.3
355.0
1 431.9
4 634.3
3 832.4
2 192.9
16 751.0
874.9
850.2
5.9
1 211.3
547.0
154.9
345.9
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
82.9
130.0
115.9
181.8
267.8
79.8
99.7
148.3
102.9
63.0
58.0
44.7
111.7
148.4
90.7
147.6
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
78.2
53.3
42.8
44.2
1 594.5
221.7
323.5
637.8
4 000.7
658.6
-5.5
8.0
-3.0
8.3
-9.1
-54.2
Absolute
change
56.9
27.5
12.0
25.8
1 129.2
359.9
85.8
34.2
105.7
102.7
-100.0
84.2
-1.1
36.7
-15.4
-100.0
Percent
change
Import
-45.1
0.0
-2.1
-18.6
0.0
-20.8
-27.6
0.0
-137.3
-5.2
465.3
0.0
-8.1
-1.4
-17.5
-107.3
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
88.7
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
524.4
Nepal
146.1
Burkina Faso
Cameroon
40.1
215.2
Botswana
24.1
60.1
Benin
Burundi
337.1
13 428.9
Angola
Sub-Saharan Africa
125.6
40 762.4
India
Sri Lanka
1 500.2
Bangladesh
19 964.4
1 205.6
Afghanistan
Pakistan
64 082.6
644.4
Yemen
South Asia
641.8
1 185.5
Urban
1 187.2
708.4
1 573.2
Total
-4.1
79.6
282.9
-34.3
33.7
59.0
7 510.4
248.9
12 712.1
667.8
38 567.7
1 374.8
1 288.5
142.0
103.7
498.1
5.8
93.8
396.1
20 939.3
374.5
32 676.5
1 192.2
79 330.1
2 875.0
2 494.1
54 859.8 118 942.4
542.8
66.6
387.7
Rural
Absolute change
Tunisia
Syrian Arab Republic
COUNTRY
120.5
836.2
419.8
29.7
241.3
301.2
196.0
99.3
265.7
415.2
219.6
326.9
310.5
235.8
449.8
107.7
158.1
Urban
-3.9
265.9
138.5
-39.3
84.9
63.8
59.2
39.8
84.0
82.6
80.5
93.9
115.4
81.8
139.4
19.4
55.7
Rural
Percent change
Consumption
62.3
316.2
195.0
2.6
145.2
193.9
107.2
49.8
144.3
127.6
119.4
149.4
165.7
126.3
222.9
75.4
108.8
Total
20.4
28.9
13.3
507.5
18.1
14.2
57.3
19.6
24.6
48.1
37.6
8.5
6.8
46.6
18.7
70.6
37.1
68.9
-359.8
64.9
67.3
33.2
62.7
57.4
32.9
40.0
80.2
81.0
39.5
67.6
148.1
81.7
556.6
55.7
58.0
383.0
20 390.2
203.1
36 932.5
1 450.9
96 781.2
3 245.4
2 739.0
141 352.1
329.3
699.0
1 756.9
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
80.5
278.8
251.9
53.5
200.0
197.7
106.7
68.7
130.2
123.8
118.6
153.4
164.8
122.7
144.4
76.1
107.4
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
-6.4
25.0
-40.2
-34.8
37.8
27.2
1 388.0
181.3
525.6
7.2
165.0
328.0
20.2
1 227.3
880.7
29.5
94.5
Absolute
change
-11.3
500.0
-80.2
-22.5
101.6
122.0
38.0
37.9
577.6
48.6
242.6
98.2
561.1
124.1
275.8
41.5
102.1
Percent
change
Import
-3.3
0.0
-0.7
-0.5
-0.2
0.0
-181.0
-1.2
-0.8
0.0
-289.3
-0.2
0.0
-291.5
-2.9
-10.6
-9.6
Absolute
change
-100.0
-100.0
-100.0
-100.0
-128.6
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Annex C
71
72
Madagascar
17.3
364.6
Liberia
Malawi
8.6
13.3
Lesotho
791.1
40.9
Gabon
Kenya
682.0
Ethiopia
83.5
53.6
Eritrea
Guinea
67.8
Dem. Rep. of the
Congo
30.2
93.8
Cote d’Ivoire
130.3
63.1
Congo
Ghana
182.9
Chad
Gambia
44.6
Urban
14.0
311.8
3.1
-2.7
625.6
41.9
30.9
2.0
0.4
1 165.0
63.8
52.7
24.0
21.4
159.7
31.0
Rural
Absolute change
Central African
Republic
COUNTRY
31.3
676.4
16.4
5.9
1 416.7
125.4
161.2
32.2
41.3
1 847.0
117.4
120.5
117.8
84.5
342.6
75.6
Total
270.5
235.3
322.3
147.8
148.9
212.4
236.2
159.1
118.5
329.9
377.0
525.2
191.2
302.8
324.3
175.9
Urban
39.3
84.4
92.0
-12.1
30.6
63.0
50.6
13.8
9.0
110.7
100.3
194.6
36.5
137.7
106.2
86.2
Rural
Percent change
Consumption
74.3
129.0
218.7
21.2
55.0
118.4
138.6
96.7
105.4
146.7
150.9
301.3
102.6
232.1
165.7
123.3
Total
-0.2
7.2
16.9
183.7
27.4
15.9
31.2
10.7
25.0
18.5
11.5
27.4
36.9
22.2
10.8
41.7
100.3
84.9
60.6
-60.3
63.1
70.8
48.0
80.9
59.4
64.0
75.4
39.8
45.8
51.4
75.7
38.5
13.9
664.4
1.3
5.6
1 440.3
109.9
97.4
18.7
4.6
1 872.8
108.6
56.2
49.8
2.0
361.3
75.8
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
40.1
124.6
185.7
23.8
53.2
139.1
284.8
246.1
287.5
143.5
159.9
1 080.8
201.6
200.0
164.4
120.7
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
18.0
27.9
15.2
0.0
-1.7
19.0
65.1
13.8
36.9
52.0
11.8
65.0
23.0
82.4
0.8
1.4
Absolute
change
195.7
152.5
223.5
0.0
-6.6
61.3
76.7
52.7
97.6
666.7
88.7
185.7
16.8
232.1
17.0
82.4
Percent
change
Import
-0.1
-0.2
0.0
0.0
-2.8
-0.2
-1.0
-0.1
0.0
0.0
0.0
0.0
-53.2
-0.1
0.0
0.0
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
44.3
77.2
154.7
928.8
77.7
177.3
Mauritius
Mozambique
Niger
Nigeria
Rwanda
Senegal
United Republic of
Tanzania
26.9
521.3
Uganda
Zambia
18.6
239.0
Togo
13.5
4 241.8
731.7
1 762.8
Swaziland
Sudan
South Africa
Somalia
22.6
257.9
Sierra Leone
554.8
Mauritania
Urban
17.4
493.9
743.7
5.5
-3.7
876.6
-187.9
1 192.7
14.7
88.4
124.6
211.4
403.0
25.1
11.4
133.9
392.4
Rural
Absolute change
Mali
COUNTRY
44.3
1 015.2
982.7
24.1
9.8
5 118.4
543.8
2 955.5
37.3
265.7
202.3
1 140.2
557.7
102.3
55.7
391.8
947.2
Total
108.4
290.8
407.1
214.5
72.6
232.7
53.6
317.9
210.3
152.8
412.1
219.1
293.6
250.3
56.2
160.6
341.4
Urban
38.6
78.8
173.2
46.3
-6.6
30.1
-18.0
115.9
83.7
55.3
141.2
38.8
149.6
37.7
22.9
71.4
99.9
Rural
Percent change
Consumption
63.4
126.0
201.3
117.6
13.0
108.1
22.6
186.6
131.8
96.3
188.9
117.8
173.1
105.1
43.2
112.5
170.6
Total
18.5
30.4
5.3
18.8
119.6
27.3
123.2
1.3
19.0
9.3
34.2
17.7
-1.9
35.8
41.4
2.3
5.3
72.9
50.3
85.5
66.5
-16.9
56.1
-18.2
96.3
64.8
83.2
40.0
68.0
105.3
46.6
49.7
95.3
86.9
39.7
1 036.0
991.9
9.5
23.2
5 315.6
653.2
3 230.8
26.6
193.3
207.5
513.6
519.9
107.5
0.1
374.1
880.6
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
62.7
128.8
194.3
105.6
63.9
108.6
25.5
147.2
125.5
135.8
206.3
125.7
169.0
156.5
2.1
116.7
176.0
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
3.0
5.6
19.2
8.7
-19.5
23.8
-149.1
23.7
11.9
72.2
0.0
743.9
53.4
-2.4
54.4
25.6
84.6
Absolute
change
25.0
23.0
800.0
60.8
-35.7
52.9
-100.0
359.1
146.9
48.8
0.0
112.5
141.3
-7.4
43.0
56.8
129.4
Percent
change
Import
-1.9
-1.1
-0.5
-5.4
-11.3
0.0
-75.5
0.0
0.0
-7.3
0.0
-2.2
-2.3
0.0
-1.6
-0.1
0.0
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-43.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Annex C
73
74
2 461.7
Japan
-39.4
24.3
Switzerland
Trinidad and Tobago
23 088.9
2 760.2
Saudi Arabia
United States of
America
1 355.5
Republic of Korea
84.2
756.5
Israel
39.0
3.4
Iceland
Norway
1 635.9
Canada
New Zealand
1 075.0
Australia
-2 064.4
6.7
-104.0
256.8
120.5
-20.5
-17.3
11.5
37.4
6.1
-14.7
-151.3
-1 933.4
High income countries 33 245.4
Rural
5.8
Urban
93.6
Total
21 024.5
31.0
-143.4
3 017.0
1 476.0
63.7
21.7
2 473.2
793.9
9.5
1 621.2
923.7
31 312.0
Absolute change
87.8
Zimbabwe
COUNTRY
37.9
102.2
-2.4
173.0
132.4
8.9
5.9
44.4
65.3
6.1
30.2
24.7
39.9
109.2
Urban
-17.3
6.5
-21.4
74.5
47.7
-8.6
-17.1
0.4
33.6
52.8
-1.6
-24.3
-10.7
3.6
Rural
Percent change
Consumption
28.9
24.5
-6.7
155.5
115.6
5.4
2.9
29.4
62.6
14.0
25.6
18.6
30.9
39.3
Total
-2.9
85.5
-8.2
19.9
88.0
-76.5
-443.5
121.9
15.2
-18.5
17.5
-25.4
96.3
103.7
12.0
107.6
61.1
5.9
184.1
622.5
-16.1
77.5
121.7
79.0
131.6
2.7
20 660.0
3.9
159.8
2 639.6
2 386.8
305.5
4 107.2
2 392.7
866.4
15.9
940.4
8 349.3
42 827.5
101.4
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
27.6
37.5
4.1
285.7
104.6
17.5
34.0
28.4
70.5
15.0
11.6
76.9
34.4
33.1
Percent
change
Production
MILK, CHANGE BETWEEN 2000 AND 2030
-4 807.9
6.8
-344.6
221.8
363.3
-31.2
-56.1
542.5
-7.4
-1.0
-566.9
-451.7
-5 132.4
-10.2
Absolute
change
-100.0
5.0
-100.0
17.4
117.6
-100.0
-100.0
25.0
-5.6
-100.0
-100.0
-100.0
-49.9
-100.0
Percent
change
Import
-2 241.1
-10.9
-255.2
-211.6
-9.2
-27.1
4 235.9
-13.1
-8.6
-0.4
-373.5
6 600.3
7 685.5
-9.4
Absolute
change
-100.0
-100.0
-37.7
-100.0
-100.0
-13.6
43.8
-100.0
-100.0
-57.1
-47.2
107.7
38.5
-18.8
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
91.0
10.6
Brazil
Chile
9.2
13.7
Colombia
53.2
Bolivia
344.1
Latin America/Caribbean
Argentina
237.9
1.1
Viet Nam
Turkey
0.2
Thailand
103.8
19.5
Philippines
Russian Federation
2.4
Myanmar
341.8
9.3
Malaysia
Eastern Europe and
Central Asia
0.1
33.2
Indonesia
Lao People’s Dem. Rep.
6.8
1 384.2
China
Dem. People’s Rep. of
Korea
1 456.8
Urban
East Asia and Pacific
COUNTRY
3.5
1.9
24.5
7.7
4.7
98.1
125.5
38.1
163.5
3.7
0.9
14.5
6.6
5.5
0.4
45.4
4.0
1 356.8
1 437.8
Rural
Consumption
12.7
12.5
115.5
21.4
57.9
442.2
363.4
141.9
505.3
4.8
1.1
34.0
9.0
14.8
0.5
78.6
10.8
2 741.0
2 894.6
Total
13.0
17.1
108.2
21.4
57.0
406.7
367.1
138.9
506.0
4.8
0.9
33.5
9.0
0.2
0.5
78.0
10.8
2 732.1
2 869.8
Production
MUTTON 2000
0.0
0.1
7.3
0.0
1.8
65.2
0.1
3.1
3.2
0.0
0.2
0.5
0.0
14.8
0.0
0.7
0.0
16.9
33.1
Import
0.3
4.7
0.0
0.0
1.0
21.6
3.8
0.2
4.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
8.0
8.2
Export
15.3
17.3
164.9
31.2
85.9
577.6
415.0
135.4
550.4
4.0
0.4
52.1
8.9
18.6
1.0
95.7
16.8
2 825.2
3 022.5
Urban
3.7
1.7
22.5
9.6
4.1
103.5
116.7
42.5
159.2
6.8
1.0
16.2
9.5
4.0
0.9
43.2
5.7
1 453.1
1 540.6
Rural
Consumption
19.0
19.0
187.4
40.8
90.0
681.1
531.7
177.9
709.6
10.8
1.4
68.3
18.4
22.6
1.9
138.9
22.5
4 278.3
4 563.1
Total
19.0
24.0
168.2
40.8
90.0
630.0
541.7
157.9
699.6
10.8
1.0
68.3
18.4
0.5
1.9
138.9
22.5
4 268.3
4 530.6
Production
MUTTON 2030
Table C 5. Consumption and production of mutton in 2000 and 2030 (all measures are in thousands of metric tonnes).
0.0
0.0
19.2
0.0
0.0
89.8
0.0
20.0
20.0
0.0
0.4
0.0
0.0
22.1
0.0
0.0
0.0
10.0
32.5
Import
0.0
5.0
0.0
0.0
0.0
33.3
10.0
0.0
10.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
75
76
0.3
2.6
0.1
3.4
85.0
Guyana
Haiti
Honduras
Jamaica
Mexico
748.4
126.2
44.5
275.8
Egypt
Iran (Islamic Republic of)
8.0
Venezuela
Algeria
35.4
Uruguay
Middle East/North Africa
0.1
Suriname
22.6
0.7
Guatemala
Peru
0.0
El Salvador
1.8
4.6
Ecuador
Paraguay
0.7
Dominican Republic
0.0
1.0
Nicaragua
0.0
Cuba
Urban
Costa Rica
COUNTRY
150.4
61.2
53.6
503.7
1.3
3.2
0.0
6.9
1.5
0.1
29.4
3.1
0.2
4.2
0.5
1.0
0.1
3.2
0.4
0.8
0.0
Rural
Consumption
426.2
105.7
179.8
1 252.1
9.3
38.6
0.1
29.5
3.3
0.1
114.4
6.5
0.3
6.8
0.8
1.7
0.1
7.8
1.1
1.8
0.0
Total
437.2
100.1
176.4
1 238.2
9.1
54.2
0.1
37.7
3.3
0.0
63.7
1.7
0.3
6.8
0.8
1.7
0.1
7.7
1.0
1.8
0.0
Production
MUTTON 2000
0.8
5.4
3.4
47.4
0.2
0.0
0.0
0.2
0.0
0.0
50.7
4.8
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
Import
11.8
0.1
0.0
33.5
0.0
15.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
568.4
97.1
277.7
1 795.3
13.8
39.1
0.1
39.2
3.6
0.1
129.9
6.1
0.3
11.4
0.3
2.2
0.1
7.8
0.8
8.4
0.0
Urban
158.8
100.0
60.1
743.6
1.0
2.4
0.0
9.1
1.5
0.0
27.4
3.7
0.2
5.2
0.4
1.4
0.1
2.6
0.3
6.3
0.1
Rural
Consumption
727.2
197.1
337.8
2 538.9
14.8
41.5
0.1
48.3
5.1
0.1
157.3
9.8
0.5
16.6
0.7
3.6
0.2
10.4
1.1
14.7
0.1
Total
727.2
187.1
337.8
2 339.5
14.8
66.5
0.1
53.2
5.1
0.1
94.9
2.2
0.5
16.6
0.7
3.6
0.2
10.4
1.1
18.0
0.0
Production
MUTTON 2030
0.0
10.0
0.0
226.8
0.0
0.0
0.0
0.5
0.0
0.0
62.4
7.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
Import
0.0
0.0
0.0
15.0
0.0
25.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.3
0.0
Export
Mapping supply and demand for animal-source foods to 2030
40.2
12.8
428.8
33.8
Tunisia
Yemen
South Asia
Afghanistan
0.4
5.8
2.5
5.0
7.3
0.3
Angola
Benin
Botswana
Burkina Faso
Burundi
514.8
Sri Lanka
Sub-Saharan Africa
167.6
Pakistan
5.3
93.9
Syrian Arab Republic
Nepal
78.5
Morocco
31.2
31.2
Libyan Arab Jamahiriya
190.4
8.2
Lebanon
India
17.5
Jordan
Bangladesh
19.6
Urban
Iraq
COUNTRY
3.7
29.2
3.2
4.0
4.9
856.9
2.1
337.6
34.6
496.9
100.4
97.4
1 068.9
34.7
23.2
87.5
68.6
9.4
1.3
4.9
8.9
Rural
Consumption
4.0
36.5
8.2
6.5
10.7
1 371.7
2.5
505.2
39.9
687.3
131.6
131.2
1 497.7
47.5
63.4
181.4
147.1
40.6
9.5
22.4
28.5
Total
4.0
38.6
7.6
6.5
10.7
1 374.8
1.8
507.3
39.8
696.3
131.5
131.2
1 507.9
47.4
64.1
188.0
146.8
35.5
5.4
8.8
28.5
Production
MUTTON 2000
0.0
0.0
0.6
0.0
0.0
81.1
0.6
0.0
0.3
0.2
0.2
0.0
1.3
3.6
0.0
5.3
0.2
1.1
7.7
19.9
0.0
Import
0.0
2.2
0.0
0.0
0.0
84.3
0.0
2.1
0.2
9.3
0.1
0.0
11.7
3.5
0.0
11.9
-0.1
0.0
0.0
6.3
0.0
Export
1.9
39.4
7.2
7.1
27.8
1 737.6
1.3
498.0
27.2
513.3
130.3
209.2
1 379.3
73.2
78.8
231.5
176.9
72.9
12.8
42.5
163.5
Urban
7.7
72.2
2.2
6.2
9.4
1 516.9
4.4
506.9
62.4
761.6
189.8
315.7
1 840.8
87.1
26.2
129.9
91.4
14.8
1.3
9.4
64.6
Rural
Consumption
9.6
111.6
9.4
13.3
37.2
3 254.5
5.7
1 004.9
89.6
1 274.9
320.1
524.9
3 220.1
160.3
105.0
361.4
268.3
87.7
14.1
51.9
228.1
Total
9.6
116.6
8.9
13.3
37.2
3 278.8
3.2
994.9
89.6
1 024.9
320.1
524.9
2 957.6
150.3
105.1
388.0
267.3
82.7
6.0
8.0
80.0
Production
MUTTON 2030
0.0
0.0
0.5
0.0
0.0
91.2
2.5
10.0
0.0
250.0
0.0
0.0
262.5
10.0
0.0
0.0
1.0
5.0
8.8
43.9
148.1
Import
0.0
5.0
0.0
0.0
0.0
115.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
15.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
77
78
4.4
8.3
0.6
4.3
7.0
2.1
10.1
1.1
0.5
8.9
2.9
11.5
1.1
0.7
2.9
0.9
17.7
13.6
3.4
0.9
Chad
Congo
Cote d’Ivoire
Dem. Rep. of the Congo
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
16.5
Urban
Central African Republic
Cameroon
COUNTRY
1.8
2.1
15.9
42.9
5.2
6.9
0.6
4.1
44.3
5.0
10.1
0.3
0.1
51.8
9.4
14.9
5.7
0.5
22.2
6.2
14.5
Rural
Consumption
2.7
5.5
29.5
60.6
6.1
9.8
1.3
5.2
55.8
7.9
19.0
0.8
1.2
61.9
11.5
21.9
10.0
1.1
30.5
10.6
31.0
Total
2.7
0.2
34.3
66.5
6.1
9.8
1.3
4.3
55.6
8.1
17.8
0.8
1.0
63.1
11.6
21.8
8.1
1.0
32.6
10.5
31.0
Production
MUTTON 2000
0.0
5.3
0.0
0.0
0.0
0.0
0.0
0.9
0.2
0.2
1.1
0.0
0.2
0.0
0.1
0.1
1.9
0.1
0.0
0.1
0.0
Import
0.0
0.0
4.8
5.8
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
1.2
0.1
0.0
0.0
0.0
2.1
0.0
0.0
Export
4.3
6.7
44.9
91.5
6.3
8.7
2.4
1.6
29.9
12.7
32.7
1.2
2.0
41.5
11.0
36.2
11.3
1.6
34.0
14.0
43.9
Urban
3.7
3.4
34.6
100.4
13.5
11.4
1.0
2.2
60.6
11.2
16.3
0.4
0.2
104.5
20.8
36.8
7.3
0.7
44.0
13.4
17.0
Rural
Consumption
8.0
10.1
79.5
191.9
19.8
20.1
3.4
3.8
90.5
23.9
49.0
1.6
2.2
146.0
31.8
73.0
18.6
2.3
78.0
27.4
60.9
Total
8.0
0.3
84.5
200.0
19.8
20.1
3.4
2.8
90.5
23.9
47.9
1.6
2.0
146.0
32.0
73.0
16.6
2.2
80.1
27.4
60.9
Production
MUTTON 2030
0.0
9.8
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.0
1.1
0.0
0.2
0.0
0.0
0.0
2.0
0.1
0.0
0.0
0.0
Import
0.0
0.0
5.0
8.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
2.1
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
22.3
6.5
6.5
17.6
Iceland
Israel
Japan
4.5
Zimbabwe
Canada
1.7
Zambia
293.1
8.8
United Republic of
Tanzania
Australia
3.6
Uganda
708.5
2.9
Togo
High income countries
0.8
98.1
Swaziland
Sudan
25.7
107.1
South Africa
13.4
Senegal
Somalia
0.6
Rwanda
0.6
100.5
Nigeria
Sierra Leone
6.4
Urban
Niger
COUNTRY
10.1
0.6
1.3
4.0
42.2
134.6
9.0
3.2
30.6
26.4
4.0
2.5
156.7
82.0
47.7
1.1
18.5
2.8
130.0
32.7
Rural
Consumption
27.7
7.1
7.8
26.3
335.3
843.1
13.5
4.9
39.4
30.0
6.9
3.3
254.8
189.1
73.4
1.7
31.9
3.4
230.5
39.1
Total
0.3
5.2
9.0
12.8
802.9
1 572.5
13.5
4.9
39.3
30.0
6.9
2.8
284.2
134.2
107.7
1.2
27.0
3.4
221.3
42.8
Production
MUTTON 2000
28.0
1.9
0.0
16.1
0.4
215.2
0.0
0.0
0.1
0.0
0.0
0.5
0.0
55.1
0.0
0.4
5.0
0.0
9.2
0.0
Import
0.0
0.0
1.2
1.8
415.9
797.0
0.0
0.0
0.1
0.0
0.0
0.0
29.5
0.2
34.2
0.0
0.0
0.0
0.0
3.7
Export
16.9
10.8
6.0
29.1
331.0
993.6
9.7
6.8
29.3
15.7
10.4
1.3
466.5
129.4
126.3
1.7
41.3
1.7
352.8
22.9
Urban
7.3
0.7
1.7
4.0
28.9
124.9
9.5
8.4
47.3
62.6
6.6
2.1
291.4
53.1
121.3
1.6
34.9
3.9
198.9
74.2
Rural
Consumption
24.2
11.5
7.7
33.1
359.9
1 118.5
19.2
15.2
76.6
78.3
17.0
3.4
757.9
182.5
247.6
3.3
76.2
5.6
551.7
97.1
Total
0.3
8.0
8.7
13.5
1 216.8
2 294.5
19.2
15.2
76.6
78.3
17.0
3.0
810.0
121.8
287.6
2.9
71.2
5.6
541.7
100.1
Production
MUTTON 2030
24.4
3.5
0.0
19.6
0.0
402.7
0.0
0.0
0.0
0.0
0.0
0.4
0.0
60.7
0.0
0.4
5.0
0.0
10.0
0.0
Import
0.0
0.0
1.0
0.0
850.0
1 551.0
0.0
0.0
0.0
0.0
0.0
0.0
52.1
0.0
40.0
0.0
0.0
0.0
0.0
3.0
Export
Annex C
79
80
United States of America
131.1
0.4
10.3
Switzerland
Trinidad and Tobago
114.4
Saudi Arabia
4.5
19.5
Republic of Korea
82.4
Norway
Urban
New Zealand
COUNTRY
27.8
1.7
3.1
24.8
1.3
4.9
12.7
Rural
Consumption
158.9
2.1
13.4
139.2
5.8
24.4
95.1
Total
118.2
0.5
6.3
51.3
2.8
23.5
539.7
Production
MUTTON 2000
61.2
1.7
7.1
89.9
4.0
0.9
4.0
Import
15.8
0.0
0.0
2.0
1.0
0.1
359.2
Export
165.8
0.7
9.5
310.4
8.7
21.1
83.5
Urban
19.4
1.7
2.3
43.0
1.4
4.5
10.1
Rural
Consumption
185.2
2.4
11.8
353.4
10.1
25.6
93.6
Total
115.2
0.0
7.0
78.4
7.1
25.6
813.9
Production
MUTTON 2030
70.0
2.4
4.8
275.0
3.0
0.0
0.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
700.0
Export
Mapping supply and demand for animal-source foods to 2030
3.1
0.2
2.9
Thailand
233.5
Latin America/
Caribbean
31.6
177.1
Russian Federation
Turkey
208.7
Eastern Europe and
Central Asia
Viet Nam
0.1
32.6
5.4
-8.8
4.4
-4.4
1.7
3.0
Philippines
-1.5
9.3
6.4
Malaysia
Myanmar
0.5
0.9
Lao People’s Dem. Rep.
-2.2
62.5
1.8
96.3
102.8
Rural
Indonesia
9.9
1 441.0
China
Dem. People’s Rep. of
Korea
1 565.7
Urban
Total
238.9
168.3
36.0
204.3
6.0
0.3
34.3
9.4
7.8
1.4
60.3
11.7
1 537.3
1 668.5
Absolute change
East Asia and Pacific
COUNTRY
67.9
74.4
30.4
61.1
256.0
82.5
167.5
263.9
100.2
831.5
188.5
145.8
104.1
107.5
Urban
5.5
-7.0
11.6
-2.7
84.7
15.6
11.5
45.2
-26.9
136.2
-4.9
44.2
7.1
7.1
Rural
Percent change
Consumption
54.0
46.3
25.4
40.4
125.0
27.3
100.9
104.4
52.7
280.0
76.7
108.3
56.1
57.6
Total
18.7
206.8
49.8
10.3
33.4
56.0
-0.4
41.5
45.2
79.1
66.2
74.8
-70.0
30.9
87.2
49.9
27.7
100.6
27.1
40.7
11.2
24.7
223.3
174.6
19.0
193.6
6.0
0.1
34.8
9.4
0.3
1.4
60.9
11.7
1 536.2
1 660.8
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
54.9
47.6
13.7
38.3
125.0
11.1
103.9
104.4
150.0
280.0
78.1
108.3
56.2
57.9
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
24.6
-0.1
16.9
16.8
0.0
0.2
-0.5
0.0
7.3
0.0
-0.7
0.0
-6.9
-0.6
Absolute
change
37.7
-100.0
545.2
525.0
100.0
-100.0
49.3
-100.0
-40.8
-1.8
Percent
change
Import
11.7
6.2
-0.2
6.0
0.0
0.0
0.0
0.0
-0.1
0.0
-0.1
0.0
-8.0
-8.2
Absolute
change
54.2
163.2
-100.0
150.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Table C 6. Change in consumption and production of mutton between 2000 and 2030 (absolute change is in thousands of metric tonnes, proportional change in percentage).
Annex C
81
82
-2.0
-0.1
73.9
Brazil
-0.1
-0.6
0.0
7.4
0.1
Costa Rica
Cuba
Dominican Republic
2.7
44.9
0.0
1.8
Jamaica
Mexico
Nicaragua
Paraguay
1.0
8.8
0.1
Haiti
0.0
Guyana
Honduras
-0.1
1.4
Guatemala
0.0
0.0
-2.0
0.6
0.1
0.5
0.0
3.2
0.1
Ecuador
El Salvador
5.5
0.1
0.2
6.6
6.1
Chile
Colombia
1.9
17.5
Bolivia
-0.6
Rural
32.7
Urban
Absolute change
Argentina
COUNTRY
1.8
0.0
42.9
3.3
0.2
9.8
-0.1
1.9
0.1
2.6
0.0
12.9
0.1
6.3
6.5
71.9
19.4
32.1
Total
98.3
110.4
52.9
81.1
123.1
343.1
7.7
199.0
237.1
68.7
19.9
754.1
0.0
66.6
62.4
81.2
127.5
61.4
Urban
2.1
-43.1
-6.9
18.1
30.3
23.5
-22.1
46.7
21.8
-17.5
-32.0
672.2
100.0
5.2
-7.6
-8.0
24.8
-12.7
Rural
Percent change
Consumption
54.5
0.0
37.5
50.8
66.7
144.1
-12.5
111.8
100.0
33.3
0.0
716.7
100.0
49.6
52.0
62.3
90.7
55.4
Total
-26.6
4.9
29.7
0.6
52.9
35.5
13.6
41.1
-13.4
98.6
66.9
7.2
26.8
41.0
21.4
33.5
148.1
93.4
61.1
99.0
26.8
67.5
75.0
41.8
118.7
0.2
0.0
89.6
64.3
47.0
65.8
56.1
1.8
0.1
31.2
0.5
0.2
9.8
-0.1
1.9
0.1
2.7
0.1
16.2
0.0
6.0
6.9
60.0
19.4
33.0
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
54.5
49.0
29.4
66.7
144.1
-12.5
111.8
100.0
35.1
10.0
900.0
46.2
40.4
55.5
90.7
57.9
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
0.0
0.0
11.7
2.8
0.0
0.0
0.0
0.0
0.0
0.0
-0.1
0.0
0.1
0.0
-0.1
11.9
0.0
-1.8
Absolute
change
23.1
58.3
-100.0
-100.0
163.0
-100.0
Percent
change
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.3
0.0
-0.3
0.3
0.0
0.0
-1.0
Absolute
change
-100.0
6.4
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
3.7
5.8
Uruguay
Venezuela
60.5
Yemen
950.5
38.6
Tunisia
South Asia
137.5
Syrian Arab Republic
41.7
98.4
4.5
Lebanon
Libyan Arab Jamahiriya
25.0
Jordan
Morocco
292.6
143.9
Iran (Islamic Republic of)
52.7
Egypt
Iraq
151.5
Algeria
1 047.0
0.0
Middle East/
North Africa
16.5
Peru
Urban
771.9
52.3
3.0
42.5
22.8
5.4
0.1
4.5
55.7
8.4
38.7
6.5
239.8
-0.3
-0.8
0.0
2.3
Rural
5.5
2.9
0.0
18.8
Total
1 722.4
112.8
41.6
180.0
121.2
47.1
4.6
29.5
199.6
301.0
91.4
158.0
1 286.8
Absolute change
Suriname
COUNTRY
221.7
474.1
96.1
146.4
125.4
133.9
55.1
142.9
733.4
106.1
118.5
120.0
139.9
72.0
10.5
5.5
73.0
Urban
72.2
150.6
12.7
48.6
33.2
56.9
5.6
91.6
627.3
5.6
63.2
12.1
47.6
-21.5
-25.3
-29.3
33.1
Rural
115.0
237.5
65.6
99.2
82.4
116.0
48.4
131.7
700.4
70.6
86.5
87.9
102.8
59.1
7.5
0.0
63.7
Total
8.5
42.1
14.9
30.2
33.9
20.6
26.6
44.3
28.4
18.4
32.8
7.5
-122.7
22.4
76.0
45.4
74.2
55.8
47.5
72.1
54.4
13.6
59.6
70.5
52.2
88.6
245.3
67.8
1 449.7
102.9
41.0
200.0
120.5
47.2
0.6
-0.8
51.5
290.0
87.0
161.4
1 101.3
5.7
12.3
0.0
15.5
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
96.1
217.1
64.0
106.4
82.1
133.0
11.1
-9.1
180.7
66.3
86.9
91.5
88.9
62.6
22.7
0.0
41.1
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
261.2
6.4
0.0
-5.3
0.8
3.9
1.1
24.0
148.1
-0.8
4.6
-3.4
179.4
-0.2
0.0
0.0
0.3
Absolute
change
20 092.3
177.8
-100.0
400.0
354.5
14.3
120.6
-100.0
85.2
-100.0
378.5
-100.0
150.0
Percent
change
Import
-11.7
-3.5
0.0
3.1
0.1
0.0
0.0
-6.3
0.0
-11.8
-0.1
0.0
-18.5
0.0
9.4
0.0
0.0
Absolute
change
-100.0
-100.0
26.1
-100.0
-100.0
-100.0
-100.0
-55.2
60.3
Percent
change
Export
Annex C
83
84
2.2
7.0
Cote d’Ivoire
29.2
1.0
Congo
Dem. Rep. of the Congo
25.7
9.6
Chad
2.5
27.4
Cameroon
Central African Republic
21.9
1.6
0.2
21.8
7.2
4.1
1.5
Burundi
43.0
32.1
Burkina Faso
-1.0
4.6
2.2
Benin
Botswana
659.9
4.5
1 222.9
2.3
22.0
Angola
Sub-Saharan Africa
0.9
Sri Lanka
169.3
27.8
21.9
330.4
Nepal
Pakistan
264.7
89.4
218.3
Rural
322.9
99.1
Bangladesh
India
175.4
Urban
3.2
499.7
49.7
587.6
188.5
393.7
Total
51.1
8.6
1.2
47.5
16.8
29.9
5.6
75.1
1.2
6.8
26.5
1 882.8
Absolute change
Afghanistan
COUNTRY
418.3
164.8
160.9
309.4
219.7
166.2
443.0
438.6
44.8
183.4
375.9
237.6
210.1
197.2
409.1
169.6
317.3
518.4
Urban
146.7
27.5
42.4
98.3
115.4
17.3
111.1
147.4
-32.0
55.5
93.6
77.0
112.1
50.1
80.6
53.3
89.1
224.2
Rural
Percent change
Consumption
233.3
86.0
109.1
155.7
158.5
96.5
140.0
205.8
14.6
104.6
247.7
137.3
128.0
98.9
124.6
85.5
143.2
300.1
Total
22.1
30.9
-4.3
8.6
47.5
37.8
7.5
14.8
181.2
5.1
20.5
74.7
4.5
23.8
38.8
36.5
23.9
51.4
54.6
109.4
80.5
30.0
45.6
83.8
65.3
-64.2
90.1
52.7
12.9
91.4
58.8
46.0
41.7
44.3
51.2
8.5
1.2
47.5
16.9
29.9
5.6
78.0
1.3
6.8
26.5
1 904.0
1.4
487.6
49.8
328.6
188.6
393.7
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
234.9
104.9
120.0
145.7
161.0
96.5
140.0
202.1
17.1
104.6
247.7
138.5
77.8
96.1
125.1
47.2
143.4
300.1
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
-100.0
Percent
change
-0.1
0.1
0.0
0.0
-0.1
0.0
0.0
0.0
-0.1
0.0
0.0
10.1
1.9
10.0
-0.3
-100.0
5.3
0.0
-100.0
-16.7
12.5
316.7
-100.0
249.8 124 900.0
-0.2
0.0
Absolute
change
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.8
0.0
0.0
0.0
31.2
0.0
-2.1
-0.2
-9.3
-0.1
0.0
Absolute
change
0.0
127.3
37.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
0.0
6.2
1.0
0.8
23.8
9.8
18.5
0.5
1.7
5.8
5.4
Gabon
Gambia
Ghana
Guinea
Kenya
Lesotho
Liberia
Madagascar
Malawi
11.4
16.5
252.3
1.1
Niger
Nigeria
Rwanda
1.2
3.4
3.5
Mauritius
Mozambique
1.1
68.9
41.5
1.8
18.6
31.4
Mauritania
57.5
73.8
Mali
8.3
4.5
0.4
-1.9
16.2
6.2
0.0
52.7
8.9
31.4
Rural
Eritrea
Urban
Absolute change
Ethiopia
COUNTRY
2.2
321.2
58.0
5.3
4.6
50.0
131.3
13.7
10.3
2.1
-1.4
34.7
16.0
30.0
0.8
1.0
84.1
20.3
Total
190.6
251.1
258.5
408.2
100.3
230.7
416.8
593.1
201.7
243.3
52.1
160.6
333.8
266.8
166.5
94.9
309.9
426.2
Urban
38.0
53.0
126.8
98.8
57.5
117.2
134.1
159.8
64.9
63.0
-47.1
36.7
125.5
61.5
12.9
2.1
101.8
120.8
Rural
64.7
139.3
148.3
196.3
83.6
169.5
216.7
224.6
105.1
161.5
-26.9
62.2
202.5
157.9
100.0
83.3
135.9
176.5
Total
-9.5
23.6
-8.1
50.3
61.1
17.7
12.7
38.3
-2.0
7.7
60.2
32.8
31.9
34.7
12.2
15.3
15.9
16.6
116.7
57.5
122.9
25.0
25.7
63.2
68.5
33.2
104.2
82.1
47.5
55.9
41.4
42.2
78.2
75.1
69.1
64.5
2.2
320.4
57.3
5.3
0.1
50.2
133.5
13.7
10.3
2.1
-1.5
34.9
15.8
30.1
0.8
1.0
82.9
20.4
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
64.7
144.8
133.9
196.3
50.0
146.4
200.8
224.6
105.1
161.5
-34.9
62.8
195.1
169.1
100.0
100.0
131.4
175.9
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
0.0
0.8
0.0
0.0
4.5
0.0
0.0
0.0
0.0
0.0
0.1
-0.2
-0.2
0.0
0.0
0.0
0.0
-0.1
Absolute
change
8.7
84.9
11.1
-100.0
-100.0
0.0
0.0
-100.0
Percent
change
Import
0.0
0.0
-0.7
0.0
0.0
0.2
2.3
0.0
0.0
0.0
0.0
0.0
-0.4
0.0
0.0
0.0
-1.2
0.1
Absolute
change
-18.9
4.2
39.7
-100.0
-100.0
100.0
Percent
change
Export
Annex C
85
86
22.2
0.5
5.2
0.4
0.1
6.8
-0.5
4.3
-0.7
Canada
Iceland
Israel
Japan
-2.8
0.0
-13.3
37.9
Australia
-9.7
285.1
High income countries
Zimbabwe
5.2
5.1
Zambia
16.6
20.6
United Republic of
Tanzania
36.1
2.6
12.2
7.5
Togo
-0.4
134.7
-28.8
73.6
0.6
16.4
Rural
Uganda
0.5
Swaziland
368.4
South Africa
Sudan
100.6
1.0
Sierra Leone
Somalia
27.9
Urban
Absolute change
Senegal
COUNTRY
-3.5
4.4
-0.1
6.8
24.6
275.4
5.7
10.3
37.2
48.3
10.1
0.1
503.1
-6.6
174.2
1.6
44.3
Total
-3.8
65.6
-8.1
30.5
12.9
40.2
114.8
292.8
235.0
342.3
256.3
57.2
375.7
20.7
391.9
161.2
208.0
Urban
-28.0
21.8
32.2
-0.3
-31.6
-7.2
5.7
164.9
54.2
136.6
66.1
-14.8
85.9
-35.2
154.2
53.6
88.8
Rural
Percent change
Consumption
-12.6
62.0
-1.3
25.9
7.3
32.7
42.2
210.2
94.4
161.0
146.4
3.0
197.4
-3.5
237.3
94.1
138.9
Total
65.7
14.7
1 220.0
18.2
-187.4
96.5
53.3
20.1
-2.5
26.2
176.7
43.1
-18.4
8.7
5.0
23.5
37.4
78.2
-1 327.7
78.1
333.2
2.5
22.0
67.1
106.9
53.4
-72.8
30.7
117.7
75.7
90.7
57.7
0.0
2.8
-0.3
0.7
413.9
722.0
5.7
10.3
37.3
48.3
10.1
0.2
525.8
-12.4
179.9
1.7
44.2
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
0.0
53.8
-3.3
5.5
51.6
45.9
42.2
210.2
94.9
161.0
146.4
7.1
185.0
-9.2
167.0
141.7
163.7
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
-3.6
1.6
0.0
3.5
-0.4
187.5
0.0
0.0
-0.1
0.0
0.0
-0.1
0.0
5.6
0.0
0.0
0.0
Absolute
change
-12.9
84.2
21.7
-100.0
87.1
-100.0
-20.0
10.2
0.0
0.0
Percent
change
Import
0.0
0.0
-0.2
-1.8
434.1
754.0
0.0
0.0
-0.1
0.0
0.0
0.0
22.6
-0.2
5.8
0.0
0.0
Absolute
change
-16.7
-100.0
104.4
94.6
-100.0
76.6
-100.0
17.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
-8.4
0.0
34.7
0.3
United States of America
Trinidad and Tobago
-0.8
-0.8
18.1
0.1
Switzerland
4.2
Republic of Korea
-0.5
-2.7
196.1
1.7
Rural
Saudi Arabia
1.2
Norway
Urban
Absolute change
New Zealand
COUNTRY
26.3
0.3
-1.6
214.2
4.3
1.2
-1.5
Total
26.4
85.7
-7.6
171.4
92.1
8.5
1.4
Urban
-30.1
-2.2
-26.4
73.0
11.0
-9.3
-20.8
Rural
16.6
14.3
-11.9
153.9
74.1
4.9
-1.6
Total
-62.4
77.1
42.7
19.6
84.9
-91.5
1 043.6
181.0
20.6
60.4
61.7
9.3
200.5
-1 129.6
-3.0
-0.5
0.7
27.1
4.3
2.1
274.2
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
-2.5
-100.0
11.1
52.8
153.6
8.9
50.8
Percent
change
Production
MUTTON, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
8.8
0.7
-2.3
185.1
-1.0
-0.9
-4.0
Absolute
change
14.4
41.2
-32.4
205.9
-25.0
-100.0
-100.0
Percent
change
Import
-15.8
0.0
0.0
-2.0
-1.0
-0.1
340.8
Absolute
change
-100.0
-100.0
-100.0
-100.0
94.9
Percent
change
Export
Annex C
87
88
317.0
Viet Nam
0.0
261.9
49.0
1 287.4
211.7
Bolivia
Brazil
Chile
3 337.3
Argentina
Latin America/Caribbean
Turkey
1 501.8
147.0
Thailand
Russian Federation
609.5
Philippines
1 501.8
32.2
Myanmar
Eastern Europe and
Central Asia
106.3
Malaysia
7.3
201.6
Indonesia
Lao People’s Dem. Rep.
90.0
20 623.4
20.4
22 154.7
Urban
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
36.6
342.1
26.9
23.0
1 078.5
0.1
540.9
541.0
999.4
322.4
433.2
81.4
62.7
26.0
275.0
50.9
20 075.2
84.7
22 410.9
Rural
Consumption
248.3
1 629.5
75.9
284.9
4 415.8
0.1
2 042.7
2 042.8
1 316.4
469.4
1 042.7
113.6
169.0
33.3
476.6
140.9
40 698.6
105.1
44 565.6
Total
269.6
1 845.9
75.6
208.4
4 327.8
0.2
1 517.4
1 517.6
1 381.5
471.6
1 014.8
113.5
166.1
33.3
493.2
139.6
40 896.1
105.1
44 814.8
Production
PORK 2000
3.1
1.1
0.3
77.3
418.6
0.1
403.6
403.7
-0.3
0.1
28.4
0.2
8.1
0.0
1.9
1.3
148.5
0.0
188.2
Import
24.4
218.0
0.0
0.8
310.7
0.2
10.2
10.4
64.9
10.0
0.5
0.0
5.0
0.0
19.1
0.0
340.3
0.0
439.8
Export
371.5
3 434.3
123.0
368.4
7 465.1
0.1
1 645.9
1 646.0
1 415.4
448.8
1 866.9
147.5
292.0
48.2
1 153.9
186.7
41 575.2
133.4
47 268.1
Urban
34.7
452.1
36.3
17.2
1 356.1
0.0
508.9
508.9
2 017.9
531.7
579.7
159.0
62.4
44.6
520.7
63.0
21 173.4
219.9
25 372.2
Rural
Consumption
406.2
3 886.4
159.3
385.6
8 821.2
0.1
2 154.8
2 154.9
3 433.3
980.5
2 446.6
306.5
354.4
92.8
1 674.6
249.7
62 748.6
353.3
72 640.3
Total
446.2
4 736.4
159.3
305.6
8 634.9
0.3
1 958.5
1 958.8
3 533.3
990.5
2 426.6
306.5
354.5
92.8
1 694.6
247.7
62 758.0
353.3
72 757.8
Production
PORK 2030
Table C 7. Consumption and production of pork in 2000 and 2030 (all measures are in thousands of metric tonnes).
0.0
0.0
0.0
80.0
1 103.4
0.0
200.0
200.0
0.0
0.0
20.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
22.0
Import
40.0
850.0
0.0
0.0
890.0
0.2
0.0
0.2
100.0
10.0
0.0
0.0
0.0
0.0
20.0
0.0
0.0
0.0
130.0
Export
Mapping supply and demand for animal-source foods to 2030
69.2
Ecuador
Algeria
0.2
12.4
100.3
Venezuela
Middle East/North Africa
33.9
Uruguay
59.1
Peru
1.4
76.9
Paraguay
Suriname
20.8
Panama
Mexico
3.5
4.2
909.2
Jamaica
Nicaragua
7.7
12.9
Haiti
Honduras
0.3
Guyana
7.2
39.3
Dominican Republic
14.9
79.9
Cuba
Guatemala
18.5
Costa Rica
El Salvador
68.1
Urban
Colombia
COUNTRY
0.0
4.1
15.1
3.0
0.2
17.5
63.7
10.7
2.9
304.2
3.9
9.2
20.9
0.5
18.0
5.1
46.8
23.7
66.5
12.4
25.6
Rural
Consumption
0.2
16.5
115.4
36.9
1.6
76.6
140.6
31.5
6.4
1 213.4
8.1
16.9
33.8
0.8
32.9
12.3
116.0
63.0
146.4
30.9
93.7
Total
0.1
6.3
116.1
26.5
1.1
94.2
139.9
22.2
5.9
1 017.4
6.6
9.5
28.7
0.5
24.5
8.1
115.4
60.6
133.0
31.8
86.3
Production
PORK 2000
0.0
10.8
1.0
10.4
0.4
0.5
0.8
10.2
1.4
258.7
1.6
7.5
5.1
0.3
10.3
4.8
0.7
2.4
11.8
1.5
7.4
Import
0.0
0.3
0.1
0.0
0.0
0.1
0.1
0.2
0.9
62.6
0.1
0.1
0.0
0.0
1.9
0.7
0.1
0.0
-1.5
2.1
0.0
Export
0.2
20.0
164.9
44.0
2.5
170.0
159.5
62.6
17.7
1 718.4
7.4
19.6
61.0
0.8
57.3
18.2
171.0
126.5
116.5
52.4
197.5
Urban
0.0
5.0
12.0
2.5
0.2
38.2
66.4
13.2
9.1
345.3
4.4
12.5
27.8
1.3
37.2
8.2
54.4
31.6
87.6
18.1
45.9
Rural
Consumption
0.2
25.0
176.9
46.5
2.7
208.2
225.9
75.8
26.8
2 063.7
11.8
32.1
88.8
2.1
94.5
26.4
225.4
158.1
204.1
70.5
243.4
Total
0.2
9.7
177.2
36.5
2.0
210.0
225.9
67.3
26.8
1 163.7
11.8
24.1
83.7
0.5
84.5
19.4
225.4
158.1
180.0
70.5
220.0
Production
PORK 2030
0.0
16.4
2.2
10.0
0.7
21.3
0.0
10.0
0.0
900.0
0.0
8.0
5.1
1.6
10.0
7.0
0.0
0.0
24.1
0.0
23.4
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
89
90
21.7
1.6
1.5
1.7
0.3
8.6
5.0
0.1
4.2
5.5
8.5
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Central African Republic
Chad
Congo
Cote d’Ivoire
Dem. Rep. of the Congo
0.3
279.5
Sri Lanka
Sub-Saharan Africa
2.0
Nepal
0.0
Tunisia
159.1
0.3
Morocco
India
10.7
Lebanon
161.3
0.0
South Asia
1.1
Jordan
Urban
Egypt
COUNTRY
18.5
7.6
3.1
0.4
7.2
7.6
3.7
7.1
1.0
2.5
17.9
434.0
1.4
12.6
418.3
432.4
0.0
0.4
1.7
0.1
2.0
Rural
Consumption
27.0
13.1
7.3
0.5
12.2
16.2
4.0
8.8
2.5
4.1
39.6
713.5
1.7
14.6
577.4
593.7
0.0
0.7
12.4
0.1
3.1
Total
26.1
12.4
2.1
0.4
12.2
14.8
4.0
8.7
0.2
4.0
28.6
667.4
1.8
15.1
576.9
593.8
0.1
0.6
2.4
0.0
3.1
Production
PORK 2000
0.9
0.7
5.3
0.0
0.0
1.4
0.0
0.1
2.3
0.1
11.0
51.2
0.0
0.0
0.6
0.6
0.0
0.1
10.6
0.1
0.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
6.2
0.1
0.5
0.4
1.0
0.0
0.0
0.1
0.2
0.0
Export
62.8
18.4
21.0
0.8
17.6
18.7
3.0
13.0
2.2
4.5
85.5
937.6
1.0
12.3
605.3
618.7
0.0
0.6
17.0
0.1
2.2
Urban
64.5
11.8
9.2
1.0
16.9
7.4
12.2
24.1
0.6
4.0
28.9
881.4
3.7
28.4
893.1
925.1
0.0
0.4
1.8
0.0
2.7
Rural
Consumption
127.3
30.2
30.2
1.8
34.5
26.1
15.2
37.1
2.8
8.5
114.4
1 819.0
4.7
40.7
1 498.4
1 543.8
0.0
1.0
18.8
0.1
4.9
Total
122.3
29.2
16.5
1.8
34.5
24.6
15.2
37.1
0.4
8.5
103.4
1 746.4
4.7
40.7
1 498.4
1 543.8
0.0
1.0
3.6
0.0
4.9
Production
PORK 2030
5.0
1.0
13.7
0.0
0.0
1.5
0.0
0.0
2.4
0.0
11.0
74.6
0.0
0.0
0.0
0.0
0.0
0.0
16.3
0.1
0.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
0.6
2.9
0.9
0.0
71.0
Rwanda
Senegal
Sierra Leone
Somalia
South Africa
0.6
69.8
Nigeria
Swaziland
0.2
Niger
19.5
Madagascar
4.1
2.8
Liberia
Mozambique
0.6
Lesotho
1.7
2.3
Kenya
0.7
0.6
Guinea
Mauritius
6.2
Ghana
Mali
0.2
Gambia
3.1
8.4
Gabon
Malawi
0.2
Urban
Ethiopia
COUNTRY
1.7
54.4
0.1
1.5
4.0
2.6
90.8
1.2
9.1
1.1
1.7
17.6
46.7
2.3
2.1
9.1
1.1
7.0
0.1
1.2
1.3
Rural
Consumption
2.3
125.4
0.1
2.4
6.9
3.2
160.6
1.4
13.2
2.8
2.4
20.7
66.2
5.1
2.7
11.4
1.7
13.2
0.3
9.6
1.5
Total
1.1
116.3
0.1
2.3
6.7
3.2
158.6
1.4
12.8
0.8
2.3
20.6
66.0
4.3
2.7
12.2
1.6
10.6
0.3
3.1
1.5
Production
PORK 2000
1.9
11.3
0.0
0.0
0.2
0.0
2.0
0.0
0.3
2.0
0.1
0.1
0.1
0.8
0.0
0.1
0.1
2.6
0.0
6.5
0.0
Import
1.7
2.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.0
0.0
0.0
0.0
0.0
Export
1.2
115.9
0.1
2.7
11.8
2.5
265.2
0.6
15.9
2.9
3.0
22.3
72.3
9.0
2.1
12.1
3.2
21.6
0.5
19.1
0.7
Urban
2.1
47.7
0.2
2.6
10.2
5.6
148.2
2.4
13.4
1.4
3.3
47.1
95.0
3.3
3.0
24.9
2.8
11.0
0.2
1.3
2.4
Rural
Consumption
3.3
163.6
0.3
5.3
22.0
8.1
413.4
3.0
29.3
4.3
6.3
69.4
167.3
12.3
5.1
37.0
6.0
32.6
0.7
20.4
3.1
Total
1.6
153.6
0.0
5.3
22.0
8.1
408.4
3.0
29.0
1.3
6.3
69.4
167.3
11.3
5.1
37.0
6.0
26.6
0.5
7.9
3.1
Production
PORK 2030
1.7
10.0
0.3
0.0
0.0
0.0
5.0
0.0
0.3
3.0
0.0
0.0
0.0
1.0
0.0
0.0
0.0
6.0
0.2
12.5
0.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
91
92
2.9
3.8
6.2
United Republic of
Tanzania
Zambia
Zimbabwe
United States of America
7 115.2
0.9
190.2
Switzerland
Trinidad and Tobago
0.2
Saudi Arabia
815.5
Republic of Korea
1 479.6
Japan
82.5
9.3
Israel
60.1
4.1
Iceland
Norway
799.0
Canada
New Zealand
312.4
Australia
10 868.9
9.2
High income countries
1.9
Uganda
Urban
Togo
COUNTRY
1 394.2
4.0
55.8
0.2
201.6
20.9
9.3
768.2
0.9
0.8
137.4
44.9
2 638.3
12.3
7.0
10.4
68.7
2.7
Rural
Consumption
8 509.4
4.9
246.0
0.4
1 017.1
103.4
69.4
2 247.8
10.2
4.9
936.4
357.3
13 507.2
18.5
10.8
13.3
77.9
4.6
Total
8 285.4
1.8
228.6
0.0
946.7
107.0
47.5
1 257.6
10.4
4.9
2 029.6
366.1
13 285.6
19.7
10.6
12.8
77.8
4.5
Production
PORK 2000
827.6
3.6
17.7
1.3
162.7
2.4
22.7
1 035.5
0.0
0.0
93.4
35.7
2 202.6
0.2
0.2
0.5
0.2
0.2
Import
576.9
0.6
0.3
1.0
64.4
6.0
0.4
0.9
0.1
0.0
1 036.3
44.5
1 731.4
1.3
0.0
0.0
0.0
0.1
Export
9 213.2
2.0
172.2
0.4
1 427.6
106.5
78.7
1 777.9
16.6
6.1
982.0
460.4
14 243.5
19.4
9.6
17.3
52.7
6.5
Urban
1 083.8
4.4
40.8
0.4
223.8
22.7
9.5
642.4
1.3
1.8
127.4
40.1
2 198.5
18.9
11.7
28.2
209.7
4.1
Rural
Consumption
10 297.0
6.4
213.0
0.8
1 651.4
129.2
88.2
2 420.3
17.9
7.9
1 109.4
500.5
16 442.0
38.3
21.3
45.5
262.4
10.6
Total
10 552.4
2.4
197.1
0.0
1 451.4
133.0
63.2
1 188.1
17.9
7.9
2 300.0
500.5
16 413.9
40.3
21.3
45.5
262.4
10.6
Production
PORK 2030
0.0
4.0
15.8
0.8
200.0
0.0
25.0
1 280.0
0.0
0.0
0.0
0.0
1 525.6
0.0
0.0
0.0
0.0
0.0
Import
250.0
0.0
0.0
0.0
0.0
5.0
0.0
0.0
0.0
0.0
1 031.4
0.0
1 286.4
2.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
Turkey
0.1
144.2
144.2
Russian Federation
209.3
301.8
1 098.4
Thailand
Viet Nam
Eastern Europe and
Central Asia
146.5
1 257.4
Philippines
-0.1
-32.1
-32.1
1 018.5
77.6
115.3
-0.2
18.6
Myanmar
40.9
185.6
Lao People’s Dem. Rep.
245.8
12.0
1 098.1
135.2
2 961.3
Rural
Malaysia
952.2
96.8
20 951.9
113.0
25 113.4
Urban
Total
0.0
112.1
112.1
2 116.9
511.1
1 403.9
192.9
185.4
59.5
1 198.0
108.8
22 050.0
248.2
28 074.7
Absolute change
Indonesia
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
78.1
9.6
9.6
346.4
205.3
206.3
357.8
174.6
563.6
472.2
107.6
101.6
554.1
113.4
Urban
-78.1
-5.9
-5.9
101.9
64.9
33.8
95.3
-0.4
71.3
89.4
23.6
5.5
159.6
13.2
Rural
Percent change
Consumption
0.0
5.5
5.5
160.8
108.9
134.6
169.8
109.7
178.7
251.4
77.2
54.2
236.2
63.0
Total
515.4
54.8
63.1
41.7
64.3
33.8
32.7
66.8
75.1
65.4
37.1
-323.8
24.1
21.9
37.4
17.1
48.3
42.4
12.4
15.8
25.5
33.5
0.1
441.1
441.2
2 151.8
518.9
1 411.8
193.0
188.4
59.5
1 201.4
108.1
21 861.9
248.2
27 943.0
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
50.0
29.1
29.1
155.8
110.0
139.1
170.0
113.4
178.7
243.6
77.4
53.5
236.2
62.4
Percent
change
Production
PORK, CHANGE BETWEEN 2000 AND 2030
-0.1
-203.6
-203.7
0.3
-0.1
-8.4
-0.2
-8.1
0.0
-1.9
0.7
-148.5
0.0
-166.2
Absolute
change
-100.0
-50.4
-50.5
-100.0
-100.0
-29.6
-100.0
-100.0
-100.0
53.8
-100.0
-88.3
Percent
change
Import
0.0
-10.2
-10.2
35.1
0.0
-0.5
0.0
-5.0
0.0
0.9
0.0
-340.3
0.0
-309.8
Absolute
change
0.0
-100.0
-98.1
54.1
0.0
-100.0
-100.0
4.7
-100.0
-70.4
Percent
change
Export
Table C 8. Change in consumption and production of pork between 2000 and 2030 (absolute change is in thousands of metric tonnes, proportional
change in percentage).
Annex C
93
94
48.2
11.9
3.2
809.2
Honduras
Jamaica
Mexico
0.6
Guyana
Haiti
11.1
42.5
El Salvador
Guatemala
101.7
Ecuador
87.1
Dominican Republic
129.5
Colombia
33.9
159.8
Chile
36.7
2 146.9
Brazil
Costa Rica
74.0
Cuba
106.5
Argentina
4 127.8
Urban
41.1
0.5
3.3
6.8
0.7
19.1
3.0
7.7
8.0
21.0
5.7
20.2
-1.9
110.0
9.4
-5.8
277.6
Rural
Total
850.3
3.7
15.2
55.0
1.3
61.6
14.1
109.4
95.1
57.7
39.6
149.7
157.9
2 256.9
83.4
100.7
4 405.4
Absolute change
Bolivia
Latin America/
Caribbean
COUNTRY
89.0
75.4
155.5
373.6
217.8
285.2
154.7
147.0
221.5
45.9
183.2
190.1
75.5
166.8
150.9
40.6
123.7
Urban
13.5
13.6
35.4
32.7
134.8
106.3
58.8
16.4
33.6
31.6
46.1
79.0
-5.2
32.2
35.0
-25.1
25.7
Rural
Percent change
Consumption
70.1
45.7
89.9
162.7
162.5
187.2
114.6
94.3
151.0
39.4
128.2
159.8
63.6
138.5
109.9
35.3
99.8
Total
9.1
37.0
24.5
16.1
55.1
114.9
30.0
44.8
41.6
56.8
95.7
41.0
50.0
35.6
61.0
28.6
88.1
50.0
67.9
73.3
23.7
-5.2
44.8
36.5
42.0
23.3
3.1
38.6
27.8
52.6
21.1
54.3
146.3
5.2
14.6
55.0
0.0
60.0
11.3
110.0
97.5
47.0
38.7
133.7
176.6
2 890.5
83.7
97.2
4 307.1
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
14.4
78.8
153.7
191.6
0.0
244.9
139.5
95.3
160.9
35.3
121.7
154.9
65.5
156.6
110.7
46.6
99.5
Percent
change
Production
PORK, CHANGE BETWEEN 2000 AND 2030
641.3
-1.6
0.5
0.0
1.3
-0.3
2.2
-0.7
-2.4
12.3
-1.5
16.0
-3.1
-1.1
-0.3
2.7
684.8
Absolute
change
247.9
-100.0
6.7
0.0
433.3
-2.9
45.8
-100.0
-100.0
104.2
-100.0
216.2
-100.0
-100.0
-100.0
3.5
163.6
Percent
change
Import
-62.6
-0.1
-0.1
0.0
0.0
-1.9
-0.7
-0.1
0.0
1.5
-2.1
0.0
15.6
632.0
0.0
-0.8
579.3
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
63.9
289.9
-100.0
186.4
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
457.3
446.2
10.4
South Asia
India
Nepal
0.0
Tunisia
0.1
6.3
0.0
Jordan
0.2
1.0
Egypt
Lebanon
0.0
Algeria
Morocco
0.0
7.5
Middle East/
North Africa
-0.5
15.7
474.8
492.8
0.0
0.1
0.8
0.0
1.0
-3.1
10.1
64.6
Uruguay
0.0
1.1
20.7
2.6
2.5
6.2
Rural
Venezuela
Suriname
110.9
82.7
Paraguay
Peru
14.2
41.8
Nicaragua
Urban
Absolute change
Panama
COUNTRY
26.1
921.0
950.1
0.0
0.3
6.4
0.0
1.8
0.0
8.5
61.5
9.6
1.1
131.6
85.3
44.3
20.4
Total
526.8
280.5
283.5
0.0
80.4
58.5
79.8
88.1
-22.6
60.5
64.4
29.6
78.0
187.7
107.5
200.7
400.9
Urban
124.6
113.5
114.0
0.0
12.9
7.2
-52.1
40.4
-382.6
24.0
-20.5
-15.2
11.0
118.2
4.1
23.5
217.2
Rural
178.8
159.5
160.0
0.0
42.9
51.6
0.0
58.1
0.0
51.5
53.3
26.0
68.8
171.8
60.7
140.6
318.8
Total
34.1
54.1
-5.0
23.9
-3.1
1.1
24.6
67.9
52.2
-18.3
40.7
43.3
41.0
24.6
107.4
67.7
104.9
98.3
70.8
21.9
25.2
133.1
37.7
23.8
25.6
921.5
950.0
-0.1
0.4
1.2
0.0
1.8
0.1
3.4
61.1
10.0
0.9
115.8
86.0
45.1
20.9
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
169.5
159.7
160.0
-100.0
66.7
50.0
58.1
100.0
54.0
52.6
37.7
81.8
122.9
61.5
203.2
354.2
Percent
change
Production
PORK, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
0.0
-0.6
-0.6
0.0
-0.1
5.7
0.0
0.0
0.0
5.6
1.2
-0.4
0.3
20.8
-0.8
-0.2
-1.4
Absolute
change
-100.0
-100.0
-100.0
53.8
0.0
51.9
120.0
-3.8
75.0
4 160.0
-100.0
-2.0
-100.0
Percent
change
Import
-0.5
-0.4
-1.0
0.0
0.0
-0.1
-0.2
0.0
0.0
-0.3
-0.1
0.0
0.0
-0.1
-0.1
-0.2
-0.9
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Annex C
95
96
11.3
2.7
10.1
12.6
0.6
16.8
12.9
54.3
0.5
10.7
0.3
15.4
Burkina Faso
Burundi
Cameroon
Central African Republic
Chad
Congo
Cote d’Ivoire
Dem. Rep. of the Congo
Ethiopia
Gabon
Gambia
Ghana
1.4
3.0
0.6
Benin
Botswana
4.0
0.1
0.1
1.1
46.0
4.2
6.1
0.7
9.7
-0.2
8.5
17.0
-0.3
10.9
63.9
Angola
447.4
2.3
Rural
658.1
0.7
Urban
3.0
Total
19.4
0.4
10.8
1.6
100.3
17.1
22.9
1.3
22.3
9.9
11.2
28.3
0.3
4.4
74.8
1 105.5
Absolute change
Sub-Saharan Africa
Sri Lanka
COUNTRY
246.8
210.2
126.3
238.4
635.9
232.2
403.4
486.4
250.0
117.3
761.1
646.9
41.2
191.2
294.7
235.4
261.8
Urban
57.8
38.9
12.1
84.5
249.2
55.9
194.4
177.8
135.5
-2.4
234.1
241.2
-33.5
55.8
61.0
103.1
159.5
Rural
Percent change
Consumption
147.0
133.3
112.5
106.7
371.5
130.5
313.7
260.0
182.8
61.1
280.0
321.6
12.0
107.3
188.9
154.9
176.5
Total
32.8
23.2
27.3
6.2
30.8
43.6
28.3
23.0
50.2
19.5
26.7
24.8
196.8
6.3
13.4
77.8
45.3
58.7
55.7
88.1
32.3
36.0
38.0
48.2
26.0
72.0
41.9
41.8
-78.3
87.8
69.1
9.4
16.0
0.2
4.8
1.6
96.2
16.8
14.4
1.4
22.3
9.8
11.2
28.4
0.2
4.5
74.8
1 079.0
2.9
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
150.9
66.7
154.8
106.7
368.6
135.5
685.7
350.0
182.8
66.2
280.0
326.4
100.0
112.5
261.5
161.7
161.1
Percent
change
Production
PORK, CHANGE BETWEEN 2000 AND 2030
3.4
0.2
6.0
0.0
4.1
0.3
8.4
0.0
0.0
0.1
0.0
-0.1
0.1
-0.1
0.0
23.4
0.0
Absolute
change
130.8
20.0
92.3
455.6
42.9
158.5
7.1
-100.0
4.3
-100.0
0.0
45.7
Percent
change
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-4.2
-0.1
Absolute
change
-67.7
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
0.1
1.8
0.1
Sierra Leone
44.9
0.7
4.5
South Africa
Swaziland
Togo
Somalia
1.1
8.9
Senegal
1.5
0.3
-6.7
6.2
2.9
2.0
Rwanda
1.2
57.4
0.4
195.4
Nigeria
Niger
0.3
4.4
1.2
Mauritius
1.6
29.6
48.4
1.0
0.8
15.8
1.7
Rural
11.7
2.3
Mozambique
19.1
Malawi
Mali
6.2
Liberia
52.7
1.6
Lesotho
Madagascar
2.6
9.8
Guinea
Urban
Absolute change
Kenya
COUNTRY
6.0
1.0
38.2
0.2
2.9
15.1
4.9
252.8
1.6
16.1
1.5
3.9
48.7
101.1
7.2
2.4
25.6
4.3
Total
234.7
119.1
63.2
307.8
194.1
310.0
356.4
279.8
181.6
283.7
67.3
326.0
611.5
269.7
220.7
289.6
419.8
426.0
Urban
55.1
18.6
-12.3
162.5
76.2
153.4
110.5
63.2
101.2
48.3
32.0
95.8
168.2
103.7
44.8
37.5
174.4
158.0
Rural
130.4
43.5
30.5
200.0
120.8
218.8
153.1
157.4
114.3
122.0
53.6
162.5
235.3
152.7
141.2
88.9
224.6
252.9
Total
22.5
107.4
118.3
3.6
15.8
35.2
28.9
27.3
-21.1
40.1
49.3
3.5
39.1
13.5
2.6
131.2
62.7
36.3
59.9
-5.1
-13.5
89.8
70.6
36.6
49.3
50.9
159.5
40.2
40.1
91.3
31.7
71.7
93.9
-14.4
15.5
33.2
6.1
0.5
37.3
-0.1
3.0
15.3
4.9
249.8
1.6
16.2
0.5
4.0
48.8
101.3
7.0
2.4
24.8
4.4
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
135.6
45.5
32.1
-100.0
130.4
228.4
153.1
157.5
114.3
126.6
62.5
173.9
236.9
153.5
162.8
88.9
203.3
275.0
Percent
change
Production
PORK, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
-0.2
-0.2
-1.3
0.3
0.0
-0.2
0.0
3.0
0.0
0.0
1.0
-0.1
-0.1
-0.1
0.2
0.0
-0.1
-0.1
Absolute
change
-100.0
-10.5
-11.5
30.0
-100.0
150.0
0.0
50.0
-100.0
-100.0
-100.0
25.0
-100.0
-100.0
Percent
change
Import
-0.1
-1.7
-2.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.9
0.0
Absolute
change
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Annex C
97
98
5.8
Zambia
2.0
7.3
298.4
18.6
24.0
Israel
Japan
New Zealand
Norway
-310.3
0.5
2 097.9
1.0
United States of America
Trinidad and Tobago
-15.1
-17.9
Switzerland
0.2
0.2
22.1
1.8
0.2
-125.9
0.4
1.0
-9.9
-4.8
-439.8
6.7
4.7
17.8
141.0
Rural
Saudi Arabia
612.2
182.9
Canada
Iceland
Republic of Korea
148.0
3 374.6
Australia
High income countries
13.1
14.4
United Republic of
Tanzania
Zimbabwe
43.5
Urban
19.8
10.5
32.2
184.5
Total
1 787.6
1.5
-33.0
0.4
634.3
25.8
18.8
172.5
7.7
3.0
173.0
143.2
2 934.8
Absolute change
Uganda
COUNTRY
29.5
112.0
-9.4
108.4
75.1
29.1
30.9
20.2
78.8
50.0
22.9
47.4
31.0
210.8
151.8
487.3
471.5
Urban
-22.3
11.7
-27.0
93.0
11.0
8.6
2.6
-16.4
42.5
116.1
-7.2
-10.7
-16.7
54.3
67.6
172.4
205.3
Rural
Percent change
Consumption
21.0
30.6
-13.4
100.0
62.4
25.0
27.1
7.7
75.5
61.2
18.5
40.1
21.7
107.0
97.2
242.1
236.8
Total
-32.8%
87.8
49.9
2.6
83.3
55.0
29.1
169.6
24.1
61.7
-7.8
31.3
98.0
35.9
45.2
10.0
142.6%
9.6
53.7
95.0
11.0
39.5
65.8
-61.6
64.2
27.8
109.3
61.0
1.0
47.6
26.2
72.7
2 267.0
0.6
-31.5
0.0
504.7
26.0
15.7
-69.5
7.5
3.0
270.4
134.4
3 128.3
20.6
10.7
32.7
184.6
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
27.4
33.3
-13.8
53.3
24.3
33.1
-5.5
72.1
61.2
13.3
36.7
23.5
104.6
100.9
255.5
237.3
Percent
change
Production
PORK, CHANGE BETWEEN 2000 AND 2030
-827.6
0.4
-1.9
-0.5
37.3
-2.4
2.3
244.5
0.0
0.0
-93.4
-35.7
-677.0
-0.2
-0.2
-0.5
-0.2
Absolute
change
-100.0
11.1
-10.7
-38.5
22.9
-100.0
10.1
23.6
-100.0
-100.0
-30.7
-100.0
-100.0
-100.0
-100.0
Percent
change
Import
-326.9
-0.6
-0.3
-1.0
-64.4
-1.0
-0.4
-0.9
-0.1
0.0
-4.9
-44.5
-445.0
0.7
0.0
0.0
0.0
Absolute
change
-56.7
-100.0
-100.0
-100.0
-100.0
-16.7
-100.0
-100.0
-100.0
-0.5
-100.0
-25.7
53.8
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
84.7
Viet Nam
933.4
90.6
3 969.4
301.8
Bolivia
Brazil
Chile
8 843.0
413.3
Argentina
Latin America/Caribbean
Turkey
1 115.2
270.9
Thailand
Russian Federation
340.8
Philippines
1 528.5
56.5
Myanmar
Eastern Europe and
Central Asia
520.6
Malaysia
2.7
321.7
Indonesia
Lao People’s Dem. Rep.
17.4
6 108.3
4.9
7 728.5
Urban
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
52.4
1 052.5
48.5
82.0
2 621.8
217.9
401.5
619.4
267.7
593.7
242.6
142.0
306.0
9.6
437.8
9.6
5 950.5
20.4
7 979.9
Rural
Consumption
354.2
5 021.9
139.1
1 015.4
11 464.8
631.2
1 516.7
2 147.9
352.4
864.6
583.4
198.5
826.6
12.3
759.5
27.0
12 058.8
25.3
15 708.4
Total
381.9
6 056.0
138.9
992.2
12 237.8
631.8
796.4
1 428.2
351.4
1 262.8
559.7
198.3
835.6
12.2
751.0
27.0
11 775.1
25.1
15 798.2
Production
POULTRY MEAT 2000
0.7
4.3
0.7
53.7
654.9
6.2
774.5
780.7
1.1
1.6
23.9
0.2
61.8
0.1
11.4
0.0
788.0
0.1
888.2
Import
34.0
1 038.4
0.5
30.4
1 141.8
6.8
3.2
10.0
0.0
377.6
0.2
0.0
50.4
0.0
2.9
0.0
499.7
0.0
930.8
Export
613.0
7 847.8
327.8
1 671.2
21 905.7
1 611.3
1 832.2
3 443.5
495.9
908.2
1 537.0
369.0
1 449.4
31.2
2 487.6
59.9
17 660.1
32.3
25 030.6
Urban
57.2
1 035.3
97.0
78.8
3 992.7
452.0
562.1
1 014.1
707.2
1 075.1
477.3
396.4
310.1
28.6
1 123.5
20.0
9 008.0
53.4
13 199.6
Rural
Consumption
670.2
8 883.1
424.8
1 750.0
25 898.4
2 063.3
2 394.3
4 457.6
1 203.1
1 983.3
2 014.3
765.4
1 759.5
59.8
3 611.1
79.9
26 668.1
85.7
38 230.2
Total
740.0
11 883.1
424.8
1 740.0
27 974.5
2 100.0
1 594.3
3 694.3
1 203.1
2 631.4
1 973.5
765.4
1 789.8
59.8
3 461.1
79.9
26 171.5
85.7
38 221.2
Production
POULTRY MEAT 2030
Table C 9. Consumption and production of poultry meat in 2000 and 2030 (all measures are in thousands of metric tonnes).
0.0
0.0
0.0
10.0
1 138.4
0.0
800.0
800.0
0.0
0.0
40.8
0.0
0.0
0.0
150.0
0.0
500.0
0.0
690.8
Import
75.5
3 000.0
0.0
0.0
3 081.9
36.7
0.0
36.7
0.0
600.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
600.0
Export
Annex C
99
100
246.7
11.0
48.2
550.5
Peru
Suriname
Uruguay
Venezuela
Algeria
160.5
1 513.6
28.5
Middle East/North Africa
48.5
1 658.8
Mexico
Paraguay
57.9
Jamaica
Panama
37.6
Honduras
26.6
11.5
Haiti
Nicaragua
6.3
69.9
Guatemala
Guyana
26.8
126.5
Dominican Republic
95.6
59.0
Cuba
El Salvador
43.0
Ecuador
394.9
Costa Rica
Urban
Colombia
COUNTRY
68.1
1 079.9
82.5
4.1
1.8
73.2
23.3
24.8
21.5
555.7
53.4
45.0
18.6
13.0
84.1
19.2
64.4
76.1
49.3
28.8
147.6
Rural
Consumption
228.6
2 593.5
633.0
52.3
12.8
319.9
51.8
73.3
48.1
2 214.5
111.3
82.6
30.1
19.3
154.0
46.0
160.0
202.6
108.3
71.8
542.5
Total
226.5
2 534.3
632.5
54.7
4.3
594.3
47.6
75.9
44.0
1 855.9
78.6
72.9
8.1
12.1
131.3
47.7
161.2
198.8
59.8
73.6
515.5
Production
POULTRY MEAT 2000
2.1
97.2
2.2
0.9
7.9
11.5
4.3
4.2
4.8
368.1
33.0
9.7
22.1
7.2
25.8
3.3
3.2
3.8
48.4
1.4
33.7
Import
0.0
11.3
1.6
0.5
0.0
1.8
0.0
0.4
0.7
9.6
0.2
0.1
0.0
0.0
3.0
5.0
4.4
0.0
0.0
3.5
7.7
Export
555.5
5 971.5
1 552.4
91.5
17.8
1 001.2
133.7
156.7
129.9
5 004.2
126.7
164.0
53.4
12.6
370.4
103.7
394.5
354.9
129.5
139.6
1 509.3
Urban
119.8
2 917.6
112.2
5.1
1.8
225.4
55.3
32.9
66.5
1 007.4
76.1
103.9
24.3
18.7
238.7
45.9
125.5
88.6
97.3
48.3
350.4
Rural
Consumption
675.3
8 889.1
1 664.6
96.6
19.6
1 226.6
189.0
189.6
196.4
6 011.6
202.8
267.9
77.7
31.3
609.1
149.6
520.0
443.5
226.8
187.9
1 859.7
Total
650.0
8 413.3
1 664.6
96.6
8.6
1 362.9
183.0
186.6
191.4
5 211.6
177.8
257.9
37.7
26.7
559.1
150.0
520.0
443.5
155.0
193.9
1 759.7
Production
POULTRY MEAT 2030
25.3
493.9
0.0
0.0
11.0
0.0
6.0
5.0
5.0
800.0
25.0
10.0
40.0
4.6
50.0
0.0
0.0
0.0
71.8
0.0
100.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.0
0.0
6.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
22.6
Benin
5.5
24.3
Angola
Botswana
855.6
Sub-Saharan Africa
1.8
Nepal
11.6
292.6
India
Sri Lanka
27.0
Bangladesh
107.9
3.4
Afghanistan
Pakistan
444.2
South Asia
Morocco
30.2
75.9
137.2
Libyan Arab Jamahiriya
Yemen
66.0
Lebanon
66.1
91.9
Jordan
Tunisia
33.8
Iraq
58.8
536.5
Iran (Islamic Republic of)
Syrian Arab Republic
256.7
Urban
Egypt
COUNTRY
3.6
36.1
20.1
1 051.4
57.4
218.7
11.2
758.0
86.5
9.7
1 141.6
82.1
38.3
54.5
120.0
23.0
10.2
25.6
15.0
292.7
350.4
Rural
Consumption
9.1
58.7
44.4
1 907.0
69.0
326.6
13.0
1 050.6
113.5
13.1
1 585.8
112.3
104.4
113.3
257.2
98.9
76.2
117.5
48.8
829.2
607.1
Total
3.4
11.6
7.5
1 656.7
66.9
326.8
12.5
1 052.0
110.6
13.1
1 581.9
67.9
103.3
112.8
243.9
96.9
99.0
114.3
46.5
823.6
599.6
Production
POULTRY MEAT 2000
5.6
50.3
36.9
283.6
2.2
0.9
0.6
0.0
3.0
0.0
6.7
44.4
2.4
0.6
13.3
2.0
4.6
3.5
2.2
13.6
8.5
Import
0.0
3.2
0.0
34.5
0.1
1.2
0.0
1.4
0.0
0.0
2.7
0.0
1.4
0.1
0.0
0.0
0.4
0.3
0.0
8.0
1.1
Export
13.8
64.8
128.1
2 899.7
53.3
956.4
25.0
4 029.7
313.8
56.6
5 434.9
277.8
212.6
395.2
469.9
216.2
153.0
249.3
467.1
1 896.4
1 078.6
Urban
4.1
56.1
43.4
2 242.4
185.1
971.4
56.5
5 886.3
457.3
85.6
7 642.1
329.2
70.6
221.7
242.8
43.8
15.9
54.9
184.5
530.7
1 103.6
Rural
Consumption
17.9
120.9
171.5
5 142.1
238.4
1 927.8
81.5
9 916.0
771.1
142.2
13 077.0
607.0
283.2
616.9
712.7
260.0
168.9
304.2
651.6
2 427.1
2 182.2
Total
12.9
35.9
36.5
4 586.8
230.4
1 927.8
71.5
9 916.0
771.1
132.2
13 049.0
350.0
283.2
606.9
692.7
271.6
165.4
304.2
500.0
2 417.1
2 172.2
Production
POULTRY MEAT 2030
5.0
85.0
135.0
562.3
8.0
0.0
10.0
0.0
0.0
10.0
28.0
257.0
0.0
10.0
20.0
5.0
5.0
0.0
151.6
10.0
10.0
Import
0.0
0.0
0.0
7.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
101
102
8.4
3.0
Mali
Mauritania
17.9
Madagascar
2.3
5.3
Liberia
Malawi
1.2
Lesotho
16.5
Ghana
1.8
1.3
Gambia
11.3
15.4
Gabon
Kenya
6.8
Ethiopia
Guinea
0.3
Eritrea
28.5
Cote d’Ivoire
7.3
8.7
Congo
Dem. Rep. of the Congo
1.3
Chad
19.0
Cameroon
1.2
0.5
Central African Republic
5.3
Burundi
Urban
Burkina Faso
COUNTRY
3.5
20.2
13.1
42.8
4.3
4.6
43.5
3.0
18.4
0.9
2.1
34.8
1.6
15.9
38.2
6.5
3.4
1.8
16.9
5.5
21.1
Rural
Consumption
6.5
28.6
15.4
60.7
9.6
5.8
54.8
4.8
34.9
2.2
17.5
41.6
1.9
23.2
66.7
15.2
4.7
3.0
35.9
6.0
26.4
Total
4.1
28.6
14.8
60.5
6.9
1.8
56.9
4.1
18.7
0.9
3.6
41.5
1.7
11.4
63.3
4.4
4.7
3.0
25.6
5.9
27.8
Production
POULTRY MEAT 2000
2.3
0.1
0.5
0.2
2.7
4.0
0.1
0.7
16.2
1.3
13.9
0.2
0.2
11.9
3.5
10.8
0.0
0.0
10.3
0.1
0.2
Import
0.0
0.1
-0.2
0.0
0.0
0.0
2.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
1.5
Export
9.3
50.5
11.4
94.0
29.9
3.7
54.4
8.6
87.3
5.3
38.3
54.6
2.7
106.5
104.3
30.5
6.2
3.4
62.6
4.9
34.0
Urban
7.1
55.6
24.3
123.5
11.1
4.9
110.2
7.7
43.3
1.7
2.6
136.5
5.2
107.5
65.5
13.3
8.0
3.2
24.4
19.7
62.5
Rural
Consumption
16.4
106.1
35.7
217.5
41.0
8.6
164.6
16.3
130.6
7.0
40.9
191.1
7.9
214.0
169.8
43.8
14.2
6.6
87.0
24.6
96.5
Total
13.4
106.1
34.7
217.5
41.0
4.6
166.6
13.3
95.6
3.0
10.7
191.1
7.6
114.0
165.8
23.8
14.2
6.6
77.0
24.6
96.5
Production
POULTRY MEAT 2030
3.0
0.0
1.0
0.0
0.0
4.0
0.0
3.0
35.0
4.0
30.2
0.0
0.3
100.0
4.0
20.0
0.0
0.0
10.0
0.0
0.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
5.1
9.5
12.4
9.5
Uganda
United Republic of
Tanzania
Zambia
Zimbabwe
539.3
936.2
3.0
Australia
Canada
Iceland
15 516.4
6.7
High income countries
1.3
Togo
11.5
Sudan
Swaziland
443.2
South Africa
1.2
27.8
Senegal
Somalia
0.3
Rwanda
4.0
77.4
Nigeria
Sierra Leone
4.3
12.2
Mozambique
Niger
13.4
Urban
Mauritius
COUNTRY
0.4
160.8
77.4
3 438.1
18.8
22.6
33.2
38.3
9.1
3.9
18.5
339.5
2.2
6.5
38.3
1.3
100.1
22.3
26.4
8.6
Rural
Consumption
3.4
1 097.0
616.7
18 954.5
28.3
35.0
42.7
43.4
15.8
5.2
30.0
782.7
3.4
10.5
66.1
1.6
177.5
26.6
38.6
22.0
Total
3.2
1 049.2
638.9
20 607.7
33.7
34.5
45.5
42.7
9.8
2.5
29.8
706.4
3.4
9.6
63.9
1.6
178.4
26.5
34.2
21.5
Production
POULTRY MEAT 2000
0.2
183.0
0.5
1 560.2
0.4
0.2
0.6
0.8
6.3
8.3
0.2
87.2
0.0
0.9
2.3
0.0
-0.9
0.1
4.4
0.8
Import
0.0
131.3
23.0
3 114.3
5.8
-0.4
3.4
0.1
0.2
5.6
0.0
12.5
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.3
Export
5.6
1 309.6
865.8
27 547.4
36.2
51.7
65.5
34.1
32.2
3.5
77.4
868.0
21.1
12.5
123.7
1.7
437.6
21.4
69.2
35.0
Urban
0.7
169.6
75.6
3 821.2
35.3
62.5
105.2
135.6
20.4
5.7
48.9
354.9
20.2
12.1
104.8
3.7
245.8
69.6
58.6
17.5
Rural
Consumption
6.3
1 479.2
941.4
31 368.6
71.5
114.2
170.7
169.7
52.6
9.2
126.3
1 222.9
41.3
24.6
228.5
5.4
683.4
91.0
127.8
52.5
Total
6.3
1 379.2
971.4
33 258.6
76.5
114.2
170.7
168.7
42.6
3.2
126.3
1 162.9
36.3
23.6
226.5
5.4
650.0
91.0
123.4
52.5
Production
POULTRY MEAT 2030
0.0
100.0
0.0
2 259.0
0.0
0.0
0.0
1.0
10.0
6.0
0.0
60.0
5.0
1.0
2.0
0.0
33.4
0.0
4.4
0.0
Import
0.0
0.0
30.0
4 035.0
5.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
103
104
402.6
582.4
71.7
Republic of Korea
Saudi Arabia
Switzerland
United States of America
11 319.7
6.5
25.9
Norway
Trinidad and Tobago
92.9
New Zealand
260.0
1 276.3
Japan
Urban
Israel
COUNTRY
2 216.1
27.8
21.1
126.0
99.6
6.3
14.3
663.1
25.1
Rural
Consumption
13 535.8
34.3
92.8
708.4
502.2
32.2
107.2
1 939.4
285.1
Total
16 418.5
31.2
36.0
380.2
426.5
31.9
107.8
1 194.8
289.5
Production
POULTRY MEAT 2000
102.8
3.4
57.3
344.0
77.6
0.4
0.5
783.1
7.4
Import
2 925.3
0.3
0.4
15.7
1.9
0.1
1.3
3.7
11.3
Export
19 793.1
15.2
96.9
1 635.7
1 037.7
66.2
135.2
2 045.6
540.9
Urban
2 319.6
34.5
22.9
226.2
163.3
12.4
16.3
737.8
42.2
Rural
Consumption
22 112.7
49.7
119.8
1 861.9
1 201.0
78.6
151.5
2 783.4
583.1
Total
26 176.7
45.7
64.8
1 261.9
1 101.0
78.6
151.5
1 433.4
588.1
Production
POULTRY MEAT 2030
0.0
4.0
55.0
600.0
100.0
0.0
0.0
1 400.0
0.0
Import
4 000.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.0
Export
Mapping supply and demand for animal-source foods to 2030
1 198.1
716.9
Russian Federation
Turkey
1 915.0
481.3
637.4
411.2
Thailand
Viet Nam
Eastern Europe and
Central Asia
234.8
1 196.1
Philippines
234.0
160.7
394.7
439.5
254.4
312.5
Myanmar
4.1
928.8
19.0
685.7
2 165.9
28.5
10.3
3 057.5
11 551.8
42.6
33.0
5 219.7
Rural
27.4
17 302.1
Urban
Total
1 432.1
877.6
2 309.7
850.7
1 118.7
1 430.9
566.9
932.9
47.5
2 851.6
52.9
14 609.3
60.4
22 521.8
Absolute change
Malaysia
Lao People’s Dem. Rep.
Indonesia
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
289.9
64.3
125.3
485.4
235.3
351.0
553.5
178.4
1 049.3
673.2
244.8
189.1
556.8
223.9
Urban
107.4
40.0
63.7
164.2
81.1
96.8
179.1
1.3
198.5
156.6
107.6
51.4
161.9
65.4
Rural
Percent change
Consumption
226.9
57.9
107.5
241.4
129.4
245.3
285.6
112.9
386.2
375.5
195.9
121.2
238.7
143.4
Total
62.9
159.0
60.6
65.9
52.9
69.7
34.6
45.7
69.9
83.6
77.8
37.3
15.3
-30.7
16.0
18.4
20.5
10.1
47.0
19.6
8.3
6.2
11.4
33.2
1 468.2
797.9
2 266.1
851.7
1 368.6
1 413.8
567.1
954.2
47.6
2 710.1
52.9
14 396.4
60.6
22 423.0
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
232.4
100.2
158.7
242.4
108.4
252.6
286.0
114.2
390.2
360.9
195.9
122.3
241.4
141.9
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
-6.2
25.5
19.3
-1.1
-1.6
16.9
-0.2
-61.8
-0.1
138.6
0.0
-288.0
-0.1
-197.4
Absolute
change
-100.0
3.3
2.5
-100.0
-100.0
70.7
-100.0
-100.0
-100.0
1 215.8
-36.5
-100.0
-22.2
Percent
change
Import
29.9
-3.2
26.7
0.0
222.4
-0.2
0.0
-50.4
0.0
-2.9
0.0
-499.7
0.0
-330.8
Absolute
change
439.7
-100.0
267.0
58.9
-100.0
-100.0
-100.0
-100.0
-35.5
Percent
change
Export
Table C 10. Change in consumption and production of poultry meat between 2000 and 2030 (absolute change is in thousands of metric tonnes,
proportional change in percentage).
Annex C
105
106
126.4
68.8
3 345.5
Honduras
Mexico
42.0
6.3
Jamaica
Haiti
Guyana
76.9
300.5
El Salvador
Guatemala
70.4
Cuba
298.9
96.6
Ecuador
1 114.4
Colombia
Costa Rica
228.4
202.8
311.2
Chile
Dominican Republic
4.8
3 878.4
Brazil
-3.2
451.6
22.7
58.9
5.6
5.7
154.6
26.7
61.1
12.5
48.1
19.5
-17.2
48.5
737.8
237.2
1 371.0
Rural
Argentina
13 062.6
Urban
Total
3 797.1
91.5
185.3
47.6
12.0
455.1
103.6
360.0
240.9
118.5
116.1
1 317.2
316.0
3 861.2
285.7
734.6
14 433.6
Absolute change
Bolivia
Latin America/
Caribbean
COUNTRY
201.7
118.9
336.0
366.3
99.2
429.7
287.2
312.7
180.5
119.3
224.6
282.2
103.1
97.7
261.8
79.0
147.7
Urban
81.3
42.5
131.0
30.3
44.2
183.9
138.8
94.9
16.5
97.5
67.7
137.3
9.2
-1.6
100.0
-3.9
52.3
Rural
Percent change
Consumption
171.5
82.2
224.3
158.1
62.2
295.5
225.2
225.0
118.9
109.4
161.7
242.8
89.2
76.9
205.4
72.3
125.9
Total
43.5
58.9
47.5
42.5
54.6
124.0
39.0
57.4
59.0
52.1
97.7
46.4
56.6
46.9
47.9
44.5
43.0
20.4
37.7
29.4
24.4
-13.6
28.4
18.6
17.6
29.6
1.1
30.6
18.3
37.5
38.1
29.0
3 355.7
99.2
185.0
29.6
14.6
427.8
102.3
358.8
244.7
95.2
120.3
1 244.2
358.1
5 827.1
285.9
747.8
15 736.7
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
180.8
126.2
253.8
365.4
120.7
325.8
214.5
222.6
123.1
159.2
163.5
241.4
93.8
96.2
205.8
75.4
128.6
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
431.9
-8.0
0.3
17.9
-2.6
24.2
-3.3
-3.2
-3.8
23.4
-1.4
66.3
-0.7
-4.3
-0.7
-43.7
483.5
Absolute
change
117.3
-24.2
3.1
81.0
-36.1
93.8
-100.0
-100.0
-100.0
48.3
-100.0
196.7
-100.0
-100.0
-100.0
-81.4
73.8
Percent
change
Import
-9.6
-0.2
-0.1
0.0
0.0
-3.0
-4.6
-4.4
0.0
0.0
2.5
-7.7
41.5
1 961.6
-0.5
-30.4
1 940.1
Absolute
change
-100.0
-100.0
-100.0
-100.0
-92.0
-100.0
71.4
-100.0
122.1
188.9
-100.0
-100.0
169.9
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
122.8
332.7
336.4
Morocco
Syrian Arab Republic
167.2
20.8
5.7
140.3
Libyan Arab Jamahiriya
87.0
Lebanon
29.3
169.4
433.4
157.4
Iraq
238.0
753.2
51.7
1 837.7
29.8
1.0
0.0
152.2
32.0
8.1
45.0
Rural
1 359.9
Jordan
Iran (Islamic Republic of)
821.9
Egypt
4 457.9
Middle East/
North Africa
395.0
1 001.8
Venezuela
Algeria
6.8
43.3
754.5
Peru
Suriname
105.2
Paraguay
Uruguay
103.3
108.2
Nicaragua
Urban
44.3
6.8
906.7
137.2
116.3
148.3
Total
503.6
455.5
161.1
92.7
186.7
602.8
1 597.9
1 575.1
446.7
6 295.6
1 031.6
Absolute change
Panama
COUNTRY
572.7
242.4
184.7
131.8
171.1
1 283.2
253.5
320.2
246.2
294.5
182.0
89.8
61.4
305.8
369.7
223.1
388.0
Urban
306.4
102.4
90.7
56.0
114.8
1 127.5
81.3
215.0
75.9
170.2
36.1
25.2
1.1
207.9
137.0
32.8
209.6
Rural
444.5
177.1
162.9
121.7
158.9
1 235.2
192.7
259.4
195.4
242.7
163.0
84.7
53.1
283.4
264.9
158.7
308.3
Total
48.1
50.7
42.7
52.8
32.0
47.3
55.0
47.5
52.5
44.5
66.1
62.3
59.2
38.4
43.5
42.8
16.6
26.0
33.8
28.7
45.1
7.7
21.9
23.5
23.5
32.1
21.8
28.3
15.3
30.5
33.4
24.7
494.1
448.8
174.7
66.4
189.9
453.5
1 593.5
1 572.6
423.5
5 879.0
1 032.1
41.9
4.3
768.6
135.4
110.7
147.4
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
438.0
184.0
180.3
67.1
166.1
975.3
193.5
262.3
187.0
232.0
163.2
76.6
100.0
129.3
284.5
145.8
335.0
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
9.4
6.7
3.0
0.4
-3.5
149.4
-3.6
1.5
23.2
396.7
-2.2
-0.9
3.1
-11.5
1.7
0.8
0.2
Absolute
change
1 566.7
50.4
150.0
8.7
-100.0
6 790.9
-26.5
17.6
1 104.8
408.1
-100.0
-100.0
39.2
-100.0
39.5
19.0
4.2
Percent
change
Import
-0.1
0.0
0.0
-0.4
-0.3
0.0
-8.0
-1.1
0.0
-11.3
-1.6
-0.5
0.0
-1.8
0.0
-0.4
-0.7
Absolute
change
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Annex C
107
108
75.9
0.6
4.3
43.6
2.1
4.9
Burundi
Cameroon
Central African Republic
Chad
4.6
1.5
7.5
14.3
41.3
8.2
28.8
Burkina Faso
Botswana
20.0
42.2
Benin
23.3
103.8
1 191.0
Angola
2 044.1
41.7
Sub-Saharan Africa
752.7
848.5
Pakistan
Sri Lanka
127.7
45.2
23.3
Nepal
5 128.3
370.8
3 737.1
53.2
286.8
Afghanistan
Bangladesh
6 500.6
247.1
32.4
Rural
India
4 990.6
247.6
Yemen
South Asia
146.4
Urban
494.7
178.8
Total
9.5
3.6
51.1
18.6
70.1
8.8
62.2
127.1
3 235.1
169.4
1 601.2
68.5
8 865.4
657.6
129.1
11 491.2
Absolute change
Tunisia
COUNTRY
387.0
173.6
229.0
826.0
544.8
148.1
186.8
426.7
238.9
359.8
786.4
1 329.0
1 277.1
1 063.9
1 575.3
1 123.5
821.0
221.4
Urban
133.4
82.8
44.5
260.5
195.7
16.5
55.4
116.2
113.3
222.4
344.2
402.1
676.6
428.5
780.6
569.4
300.8
84.6
Rural
Percent change
Consumption
202.1
120.0
142.3
310.0
265.5
96.7
106.0
286.3
169.6
245.5
490.3
526.9
843.8
579.4
985.5
724.6
440.5
171.3
Total
16.8
41.0
48.0
28.6
21.1
121.1
5.7
23.6
80.0
42.8
49.7
68.4
56.2
37.1
21.0
63.7
62.0
39.6
30.9
37.8
50.6
-9.7
88.9
45.6
6.7
18.4
13.9
4.7
10.3
13.5
41.0
17.4
9.5
3.6
51.4
18.7
68.7
9.5
24.3
29.0
2 930.1
163.5
1 601.0
59.0
8 864.0
660.5
119.1
11 467.1
282.1
179.9
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
202.1
120.0
200.8
316.9
247.1
279.4
209.5
386.7
176.9
244.4
489.9
472.0
842.6
597.2
909.2
724.9
415.5
174.2
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
0.0
0.0
-0.3
-0.1
-0.2
-0.6
34.7
98.1
278.7
5.8
-0.9
9.4
0.0
-3.0
10.0
21.3
212.6
-2.4
Absolute
change
-2.9
-100.0
-100.0
-10.7
69.0
265.9
98.3
263.6
-100.0
1 566.7
-100.0
317.9
478.8
-100.0
Percent
change
Import
0.0
0.0
0.0
0.0
-1.5
0.0
-3.2
0.0
-27.5
-0.1
-1.2
0.0
-1.4
0.0
0.0
-2.7
0.0
-1.4
Absolute
change
-100.0
-100.0
-79.7
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
56.9
9.1
Malawi
Mozambique
76.0
Madagascar
21.6
24.6
Liberia
Mauritius
2.5
6.3
43.2
Kenya
Lesotho
Mauritania
6.9
Guinea
42.1
66.6
70.7
Ghana
Mali
4.6
4.0
Gambia
32.3
8.9
3.6
35.4
11.2
80.8
6.8
0.3
25.0
0.8
0.5
101.7
47.8
3.6
22.9
2.4
Eritrea
91.6
Ethiopia
99.2
Dem. Rep. of the Congo
27.3
6.8
Rural
Gabon
21.8
75.8
Congo
Urban
Absolute change
Cote d’Ivoire
COUNTRY
89.2
30.5
9.9
77.5
20.3
156.8
31.4
2.8
109.8
11.5
95.7
4.8
23.4
149.5
6.0
190.8
103.1
28.6
Total
465.7
160.4
210.1
504.6
392.0
423.9
467.4
199.4
383.0
385.9
427.5
320.4
148.6
704.8
689.0
1 358.7
266.2
250.2
Urban
122.3
104.5
103.1
174.6
85.5
188.9
156.7
7.3
153.1
153.6
136.0
81.5
24.9
292.1
232.6
576.2
71.4
105.2
Rural
231.1
138.6
152.3
271.0
131.8
258.3
327.1
48.3
200.4
239.6
274.2
218.2
133.7
359.4
315.8
822.4
154.6
188.2
Total
52.9
69.5
14.3
18.2
24.9
27.5
25.6
145.0
61.4
35.3
45.4
36.0
32.7
38.1
29.9
38.8
47.4
16.7
21.2
15.5
70.4
54.7
56.6
42.4
40.5
-26.5
17.3
35.0
24.3
35.8
46.8
26.1
36.0
14.6
30.4
63.4
89.2
31.0
9.3
77.5
19.9
157.0
34.1
2.8
109.7
9.2
76.9
2.1
7.1
149.6
5.9
102.6
102.5
19.4
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
260.8
144.2
226.8
271.0
134.5
259.5
494.2
155.6
192.8
224.4
411.2
233.3
197.2
360.5
347.1
900.0
161.9
440.9
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
0.0
-0.8
0.7
-0.1
0.5
-0.2
-2.7
0.0
-0.1
2.3
18.8
2.7
16.3
-0.2
0.1
88.1
0.5
9.2
Absolute
change
0.0
-100.0
30.4
-100.0
100.0
-100.0
-100.0
0.0
-100.0
328.6
116.0
207.7
117.3
-100.0
50.0
740.3
14.3
85.2
Percent
change
Import
0.0
-0.3
0.0
-0.1
0.2
0.0
0.0
0.0
-0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-0.1
0.0
Absolute
change
-100.0
-100.0
-100.0
-9.1
-100.0
Percent
change
Export
Annex C
109
110
8.5
56.0
39.3
26.7
United Republic of
Tanzania
Zambia
Zimbabwe
326.4
373.4
Australia
Canada
12 031.0
29.0
Uganda
High income countries
25.5
2.2
Togo
30.4
65.9
Sudan
Swaziland
8.8
-1.7
383.1
16.5
39.9
72.0
97.3
11.3
1.8
15.4
18.0
5.6
424.8
South Africa
19.9
66.5
95.9
Senegal
Sierra Leone
Somalia
2.4
1.4
Rwanda
145.6
360.3
Nigeria
47.4
Rural
17.0
Urban
43.2
79.2
128.0
126.3
36.8
4.0
96.3
440.2
37.9
14.1
162.4
3.8
505.9
64.4
Total
382.2
324.7
12 414.1
Absolute change
Niger
COUNTRY
39.9
60.5
77.5
280.5
316.4
592.4
564.0
381.9
169.1
573.4
95.8
1 672.9
213.1
345.2
528.0
465.6
392.4
Urban
5.5
-2.3
11.1
87.9
176.8
216.6
254.3
123.7
46.4
164.1
4.5
814.8
86.0
173.5
178.1
145.5
212.8
Rural
Percent change
Consumption
34.8
52.7
65.5
152.7
226.3
299.8
291.0
232.9
76.9
321.0
56.2
1 114.7
134.3
245.7
237.5
285.0
242.1
Total
35.0
43.0
98.3
54.4
48.3
15.0
37.3
105.2
50.5
111.9
30.0
19.7
37.4
38.9
39.9
8.8
58.0
46.4
0.7
20.4
21.1
59.2
33.5
-2.9
18.9
-7.3
16.1
63.6
32.6
31.8
28.1
75.3
330.0
332.5
12 650.9
42.8
79.7
125.2
126.0
32.8
0.7
96.5
456.5
32.9
14.0
162.6
3.8
471.6
64.5
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
31.5
52.0
61.4
127.0
231.0
275.2
295.1
334.7
28.0
323.8
64.6
967.6
145.8
254.5
237.5
264.3
243.4
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
-83.0
-0.5
698.8
-0.4
-0.2
-0.6
0.2
3.7
-2.3
-0.2
-27.2
5.0
0.1
-0.3
0.0
34.3
-0.1
Absolute
change
-45.4
-100.0
44.8
-100.0
-100.0
-100.0
25.0
58.7
-27.7
-100.0
-31.2
11.1
-13.0
-3 811.1
-100.0
Percent
change
Import
-131.3
7.0
920.7
-0.8
0.4
-3.4
-0.1
-0.2
-5.6
0.0
-12.5
0.0
0.0
-0.1
0.0
0.0
0.0
Absolute
change
-100.0
30.4
29.6
-13.8
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
6.1
8.7
Trinidad and Tobago
8 473.4
25.2
Switzerland
United States of America
1 053.3
Saudi Arabia
635.1
40.3
Republic of Korea
Norway
2.0
42.3
New Zealand
103.5
6.7
1.8
100.2
63.7
74.7
769.3
Japan
17.0
0.3
Rural
281.0
2.6
Urban
698.8
46.4
44.3
844.0
298.0
2.9
Total
8 576.9
15.4
27.0
1 153.5
Absolute change
Israel
Iceland
COUNTRY
74.9
135.3
35.2
180.9
157.7
155.4
45.6
60.3
108.1
86.4
Urban
4.7
23.9
8.5
79.5
64.0
97.5
13.7
11.3
67.8
77.4
Rural
63.4
44.9
29.1
162.8
139.1
144.1
41.3
43.5
104.5
85.3
Total
40.6
90.8
134.5
21.4
89.0
84.8
48.3
116.4
36.1
68.4
47.3
6.6
-24.8
58.4
4.9
6.8
43.1
-10.9
46.4
20.0
9 758.2
14.5
28.8
881.7
674.5
46.7
43.7
238.6
298.6
3.1
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
59.4
46.5
80.0
231.9
158.1
146.4
40.5
20.0
103.1
96.9
Percent
change
Production
POULTRY MEAT, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
-102.8
0.6
-2.3
256.0
22.4
-0.4
-0.5
616.9
-7.4
-0.2
Absolute
change
-100.0
17.6
-4.0
74.4
28.9
-100.0
-100.0
78.8
-100.0
-100.0
Percent
change
Import
1 074.7
-0.3
-0.4
-15.7
-1.9
-0.1
-1.3
-3.7
-6.3
0.0
Absolute
change
36.7
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-55.8
Percent
change
Export
Annex C
111
112
41.2
Viet Nam
361.6
19.8
956.8
70.2
Brazil
Chile
250.2
3 133.0
Bolivia
Argentina
Latin America/Caribbean
Turkey
1 375.3
189.6
Thailand
Russian Federation
274.6
Philippines
1 736.9
21.1
Myanmar
Eastern Europe and
Central Asia
176.9
Malaysia
1.9
259.3
Indonesia
Lao People’s Dem. Rep.
64.3
10 281.7
2.6
11 313.3
Urban
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
12.2
253.6
10.5
21.8
1 010.5
190.5
495.2
685.7
129.9
415.6
195.0
53.1
104.0
6.5
352.9
36.8
10 004.8
10.8
11 309.3
Rural
Consumption
82.4
1 210.4
30.3
272.0
4 143.5
552.1
1 870.5
2 422.6
171.1
605.2
469.6
74.2
280.9
8.4
612.2
101.1
20 286.5
13.4
22 622.6
Total
109.9
1 561.5
38.9
315.9
5 028.7
636.2
1 911.6
2 547.8
186.0
795.1
514.9
87.8
407.2
9.9
739.5
108.3
22 382.5
14.9
25 246.1
Production
EGGS 2000
0.1
0.5
0.0
4.0
44.9
1.9
25.6
27.5
1.7
1.8
2.5
0.4
1.7
0.0
2.5
0.1
0.3
0.0
11.0
Import
1.5
7.0
0.5
0.5
29.6
14.9
8.2
23.1
1.9
6.6
0.2
0.0
59.4
0.0
2.6
0.0
60.1
0.0
130.8
Export
130.1
1 766.2
53.6
381.9
6 171.1
789.8
1 601.1
2 391.0
178.7
483.6
868.4
103.5
463.9
14.5
1 407.9
142.9
17 953.0
17.8
21 634.2
Urban
12.1
232.5
15.6
17.9
1 217.9
221.3
493.9
715.1
254.8
572.3
269.6
111.1
99.1
13.3
634.4
49.4
9 143.0
29.3
11 176.3
Rural
Consumption
142.2
1 998.7
69.2
399.8
7 389.0
1 011.1
2 095.0
3 106.1
433.5
1 055.9
1 138.0
214.6
563.0
27.8
2 042.3
192.3
27 096.0
47.1
32 810.5
Total
184.2
2 571.1
86.5
470.0
8 864.8
1 160.8
2 160.1
3 320.9
470.5
1 382.9
1 253.8
255.2
713.2
32.7
2 465.6
206.3
29 418.0
52.5
36 250.7
Production
EGGS 2030
Table C 11. Consumption and production of eggs in 2000 and 2030 (all measures are in thousands of metric tonnes).
0.0
0.0
0.0
0.0
24.0
0.0
20.0
20.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Import
0.0
5.0
0.0
0.0
12.0
20.0
0.0
20.0
0.0
5.0
0.0
0.0
30.0
0.0
0.0
0.0
100.0
0.0
135.0
Export
Mapping supply and demand for animal-source foods to 2030
33.8
Guatemala
28.7
125.5
727.2
61.5
Uruguay
Venezuela
Middle East/North Africa
Algeria
92.8
Peru
2.2
30.8
Paraguay
Suriname
4.9
Panama
11.1
Mexico
Nicaragua
2.8
1 139.4
Jamaica
19.5
24.5
El Salvador
Honduras
24.5
Ecuador
1.4
28.6
Dominican Republic
Haiti
32.3
Cuba
0.3
22.1
Costa Rica
Guyana
210.7
Urban
Colombia
COUNTRY
26.0
491.6
18.8
2.5
0.3
27.4
25.5
2.5
9.0
384.7
2.5
23.3
2.4
0.7
40.7
17.5
16.5
17.2
27.0
14.8
79.2
Rural
Consumption
87.5
1 218.8
144.3
31.2
2.5
120.2
56.3
7.4
20.1
1 524.1
5.3
42.8
3.8
1.0
74.5
42.0
41.0
45.8
59.3
36.9
289.9
Total
104.0
1 483.8
175.0
37.2
2.8
162.1
61.7
12.6
20.8
1 771.6
7.0
41.8
4.6
1.4
81.3
52.8
61.5
59.8
67.6
42.4
338.5
Production
EGGS 2000
3.2
26.7
6.9
0.4
0.1
1.1
0.2
0.3
2.0
11.0
3.0
7.5
0.0
0.5
1.5
1.3
0.8
0.7
0.0
1.0
2.0
Import
0.0
29.8
0.0
0.2
0.0
0.8
0.0
0.9
0.0
0.8
0.0
0.0
0.0
0.0
0.6
8.3
5.3
0.0
0.0
0.7
2.5
Export
216.4
2 112.2
276.0
44.9
4.5
227.6
88.6
22.4
37.2
2 110.7
6.1
67.7
9.1
0.9
114.9
73.2
59.7
86.8
58.2
57.2
493.5
Urban
46.6
905.7
19.9
2.6
0.5
51.2
36.8
4.7
19.1
427.5
3.7
42.9
4.2
1.2
74.1
32.4
19.0
21.7
43.8
19.7
114.9
Rural
Consumption
263.0
3 017.9
295.9
47.5
5.0
278.8
125.4
27.1
56.3
2 538.2
9.8
110.6
13.3
2.1
189.0
105.6
78.7
108.5
102.0
76.9
608.4
Total
318.3
3 604.7
376.0
57.0
5.4
354.4
137.8
42.3
62.1
2 859.1
19.7
122.2
16.3
4.3
208.7
123.2
106.1
143.8
116.2
89.1
709.3
Production
EGGS 2030
5.0
44.0
0.0
0.0
0.3
1.2
0.0
0.0
2.0
10.0
3.0
7.0
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Import
0.0
3.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
7.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
113
114
32.2
423.7
3.1
95.1
7.6
Bangladesh
India
Nepal
Pakistan
Sri Lanka
5.4
2.1
2.2
Angola
Benin
Botswana
466.2
3.9
Afghanistan
Sub-Saharan Africa
565.4
South Asia
9.0
107.6
Morocco
42.7
39.9
Libyan Arab Jamahiriya
Yemen
16.3
Lebanon
Tunisia
27.8
Jordan
54.9
11.1
Iraq
Syrian Arab Republic
61.4
295.1
Iran (Islamic Republic of)
Urban
Egypt
COUNTRY
1.4
3.3
4.5
650.7
37.3
191.5
19.6
1 092.7
102.7
11.2
1 455.2
24.3
24.6
51.0
93.9
12.1
2.5
7.7
4.9
160.7
83.8
Rural
Consumption
3.6
5.4
9.9
1 116.9
44.9
286.6
22.7
1 516.4
134.9
15.1
2 020.6
33.3
67.3
105.9
201.5
52.0
18.8
35.5
16.0
455.8
145.2
Total
3.0
7.2
4.3
1 328.7
52.4
338.8
24.4
1 807.1
158.7
18.3
2 399.7
31.4
78.3
122.1
238.3
58.4
36.3
49.4
12.5
576.6
176.5
Production
EGGS 2000
1.2
0.0
7.5
22.5
0.0
0.1
0.3
0.0
4.6
0.0
5.0
9.6
1.1
0.0
0.9
3.2
0.0
0.1
7.7
0.3
0.6
Import
0.0
0.0
0.0
7.2
0.4
0.5
0.0
23.4
0.0
0.0
24.3
1.2
0.1
1.2
0.0
0.0
0.8
1.8
0.0
24.6
0.1
Export
5.8
8.4
25.7
1 630.0
24.3
647.5
20.5
2 347.3
262.0
31.3
3 332.8
70.3
91.2
147.4
293.5
92.6
30.2
71.2
74.1
812.1
213.3
Urban
1.7
7.3
8.6
1 214.1
84.1
656.2
46.3
3 420.3
380.1
47.2
4 634.3
83.1
30.3
82.6
151.5
18.7
3.1
15.7
29.2
226.8
218.0
Rural
Consumption
7.5
15.7
34.3
2 844.1
108.4
1 303.7
66.8
5 767.6
642.1
78.5
7 967.1
153.4
121.5
230.0
445.0
111.3
33.3
86.9
103.3
1 038.9
431.3
Total
8.9
20.2
20.5
3 337.3
125.5
1 487.3
72.9
6 558.4
753.2
91.8
9 089.1
173.1
135.9
262.2
527.3
129.6
42.6
119.6
122.7
1 247.3
526.1
Production
EGGS 2030
0.0
0.0
20.0
35.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
15.0
0.0
0.0
1.0
3.0
0.0
0.0
20.0
0.0
0.0
Import
0.0
0.0
0.0
5.0
0.0
0.0
0.0
20.0
0.0
0.0
20.0
0.0
0.0
0.0
0.0
0.0
0.0
3.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
1.4
0.8
7.6
3.4
9.5
0.3
2.6
4.3
2.6
2.0
2.0
Gabon
Gambia
Ghana
Guinea
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Cote d’Ivoire
4.5
1.0
11.5
Congo
Ethiopia
1.0
Chad
0.3
0.5
Central African Republic
Eritrea
5.6
Cameroon
1.7
0.2
Burundi
Dem. Rep. of the Congo
2.3
Urban
Burkina Faso
COUNTRY
2.4
4.9
14.6
10.2
2.1
1.0
36.4
5.8
8.5
0.6
0.2
23.1
1.2
3.5
15.4
0.8
2.6
0.7
4.9
2.2
9.1
Rural
Consumption
4.4
6.9
17.2
14.5
4.7
1.3
45.9
9.2
16.1
1.4
1.6
27.6
1.5
5.2
26.9
1.8
3.6
1.2
10.5
2.4
11.4
Total
4.9
11.9
19.4
19.0
4.3
1.5
59.6
12.3
21.3
0.7
2.0
31.7
1.8
7.0
32.1
1.2
4.4
1.4
13.6
3.1
17.5
Production
EGGS 2000
0.6
0.0
1.0
0.1
1.6
0.1
0.0
0.0
0.1
1.0
0.0
0.0
0.0
0.4
0.2
1.2
0.0
0.0
0.0
0.0
0.0
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
6.2
12.7
12.8
17.4
10.0
1.1
32.1
15.8
43.6
2.8
3.8
32.8
2.2
21.3
50.0
3.7
3.9
1.4
15.7
2.2
14.8
Urban
4.8
13.9
26.9
22.8
3.7
1.5
64.8
14.0
21.7
0.9
0.3
81.7
4.2
21.5
31.4
1.6
5.0
1.3
6.1
8.7
27.1
Rural
Consumption
11.0
26.6
39.7
40.2
13.7
2.6
96.9
29.8
65.3
3.7
4.1
114.5
6.4
42.8
81.4
5.3
8.9
2.7
21.8
10.9
41.9
Total
13.4
40.5
44.5
52.6
15.3
3.2
118.4
37.4
87.2
2.5
5.2
131.6
7.3
57.8
97.7
4.4
10.7
3.2
27.1
13.5
58.6
Production
EGGS 2030
0.0
0.2
1.0
0.0
2.0
0.0
0.4
0.1
0.0
2.0
0.0
0.0
0.0
0.2
0.0
2.5
0.0
0.0
0.0
0.0
0.3
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Annex C
115
116
0.3
10.8
Rwanda
Senegal
1.8
12.8
14.6
Uganda
United Republic of
Tanzania
Zambia
119.3
298.0
1.5
Canada
Iceland
6 122.8
Australia
High income countries
5.7
2.0
Togo
Zimbabwe
0.6
14.6
148.9
Swaziland
Sudan
South Africa
0.7
169.0
Nigeria
Somalia
1.1
Niger
2.7
3.5
Sierra Leone
2.3
Mozambique
Urban
Mauritius
COUNTRY
0.3
51.1
17.1
1 731.6
11.1
26.5
44.8
13.1
2.7
2.0
23.4
113.9
1.2
4.5
14.8
1.6
217.1
5.6
7.6
1.4
Rural
Consumption
1.8
349.1
136.4
7 854.4
16.8
41.1
57.6
14.9
4.7
2.6
38.0
262.8
1.9
7.2
25.6
1.9
386.1
6.7
11.1
3.7
Total
2.2
372.3
165.5
8 947.9
21.4
46.4
62.4
19.9
6.3
0.9
44.8
328.3
2.5
7.7
33.0
2.2
438.3
10.2
14.0
5.2
Production
EGGS 2000
0.1
37.6
1.2
137.6
0.0
0.1
1.1
0.0
0.1
2.4
0.1
0.0
0.0
1.8
0.2
0.0
0.4
0.1
1.2
0.0
Import
0.3
15.4
1.2
127.2
1.9
0.8
0.1
0.0
0.0
0.3
0.0
4.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
1.5
345.8
156.3
8 261.4
16.6
52.3
32.9
10.3
9.4
2.0
63.5
269.5
6.5
9.2
50.4
2.1
733.9
3.6
17.3
4.3
Urban
0.5
44.8
13.6
1 503.7
16.1
63.4
52.5
40.9
6.0
3.2
39.7
110.0
6.2
8.9
42.7
4.6
410.0
11.6
14.6
2.2
Rural
Consumption
2.0
390.6
169.9
9 765.1
32.7
115.7
85.4
51.2
15.4
5.2
103.2
379.5
12.7
18.1
93.1
6.7
1 143.9
15.2
31.9
6.5
Total
2.3
423.3
206.1
11 185.5
39.6
130.0
92.8
64.1
19.8
5.0
117.8
454.2
15.7
20.6
116.4
7.6
1 299.9
21.3
41.6
9.2
Production
EGGS 2030
0.0
20.0
0.0
108.0
0.0
0.0
1.0
0.2
0.1
2.1
0.0
0.0
0.0
2.1
0.0
0.0
0.0
0.1
1.0
0.0
Import
0.0
0.0
0.0
106.1
2.0
0.0
0.0
0.0
0.0
0.0
0.0
3.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Export
Mapping supply and demand for animal-source foods to 2030
364.2
83.0
55.7
Republic of Korea
Saudi Arabia
Switzerland
United States of America
3 452.5
0.7
35.7
Norway
Trinidad and Tobago
31.8
1 620.8
Japan
New Zealand
59.7
Urban
Israel
COUNTRY
675.3
3.2
16.4
17.9
89.8
9.0
4.9
840.8
5.7
Rural
Consumption
4 127.8
3.9
72.1
100.9
454.0
44.7
36.7
2 461.6
65.4
Total
4 997.6
3.3
36.7
135.1
509.2
49.4
45.4
2 543.1
88.1
Production
EGGS 2000
7.5
2.7
39.0
5.8
2.7
0.8
0.4
39.5
0.3
Import
97.6
0.0
0.0
5.3
0.1
2.3
0.8
0.2
4.0
Export
4 529.3
1.7
53.9
224.8
778.7
40.5
35.6
2 010.1
83.3
Urban
530.8
4.0
12.7
31.0
122.0
8.6
4.3
724.9
6.4
Rural
Consumption
5 060.1
5.7
66.6
255.8
900.7
49.1
39.9
2 735.0
89.7
Total
6 113.0
2.4
29.6
343.0
1 012.6
53.8
48.8
2 829.4
121.2
Production
EGGS 2030
0.0
5.0
40.0
0.0
3.0
0.0
0.0
40.0
0.0
Import
100.0
0.0
0.0
0.0
0.0
1.1
0.0
0.0
5.0
Export
Annex C
117
118
593.8
294.0
137.5
654.1
225.9
428.2
Philippines
Viet Nam
Eastern Europe and
Central Asia
Russian Federation
Turkey
82.4
Myanmar
Thailand
286.9
12.7
1 148.6
78.6
7 671.3
15.2
10 320.9
Urban
30.8
-1.4
29.4
124.9
156.7
74.6
58.0
-4.8
6.7
281.5
12.6
-861.8
18.5
-133.0
Rural
Total
459.0
224.5
683.5
262.4
450.7
668.4
140.4
282.1
19.4
1 430.1
91.2
6 809.5
33.7
10 187.9
Absolute change
Malaysia
Lao People’s Dem. Rep.
Indonesia
Dem. People’s Rep. of
Korea
China
Cambodia
East Asia and Pacific
COUNTRY
118.4
16.4
37.7
333.6
155.1
216.3
389.7
162.1
679.6
442.9
122.3
74.6
580.3
91.2
Urban
16.2
-0.3
4.3
96.2
37.7
38.2
109.4
-4.6
103.2
79.8
34.1
-8.6
171.6
-1.2
Rural
Percent change
Consumption
83.1
12.0
28.2
153.4
74.5
142.3
189.2
100.4
231.0
233.6
90.2
33.6
251.5
45.0
Total
86.5
31.3
35.4
76.1
31.2
55.8
105.0
21.4
74.9
127.7
65.0
15.7
71.2
30.0
-17.4
35.6
18.1
45.9
24.5
36.6
64.3
25.8
11.4
12.5
524.6
248.5
773.1
284.5
587.8
738.9
167.4
306.0
22.8
1 726.1
98.0
7 035.5
37.6
11 004.6
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
82.5
13.0
30.3
153.0
73.9
143.5
190.7
75.1
230.3
233.4
90.5
31.4
252.3
43.6
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
-1.9
-5.6
-7.5
-1.7
-1.8
-2.5
-0.4
-1.7
0.0
-2.5
-0.1
-0.3
0.0
-11.0
Absolute
change
-100.0
-21.9
-27.3
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
Percent
change
Import
5.1
-8.2
-3.1
-1.9
-1.6
-0.2
0.0
-29.4
0.0
-2.6
0.0
39.9
0.0
4.2
Absolute
change
34.2
-100.0
-13.4
-100.0
-24.2
-100.0
-49.5
-100.0
66.4
3.2
Percent
change
Export
Table C 12. Change in consumption and production of eggs between 2000 and 2030 (absolute change is in thousands of metric tonnes, proportional
change in percentage).
Mapping supply and demand for animal-source foods to 2030
7.7
Haiti
Mexico
971.3
3.4
0.5
Jamaica
81.1
Guatemala
Guyana
48.2
48.7
El Salvador
Honduras
35.2
Ecuador
42.8
1.1
19.6
1.8
0.6
33.4
14.9
2.5
4.5
16.8
25.9
58.2
Cuba
Dominican Republic
4.9
35.1
Costa Rica
35.8
-0.1
282.7
59.9
Chile
-21.1
5.1
-3.9
207.4
Rural
Colombia
33.8
809.4
Bolivia
Brazil
131.7
3 038.1
Urban
Total
1 014.1
4.5
67.8
9.5
1.1
114.5
63.6
37.7
62.7
42.7
40.0
318.5
59.8
788.3
38.9
127.8
3 245.5
Absolute change
Argentina
Latin America/
Caribbean
COUNTRY
85.2
122.0
247.3
531.0
153.8
239.8
199.0
143.8
203.5
80.0
158.5
134.2
85.2
84.6
170.9
52.7
97.0
Urban
11.1
44.6
84.1
76.7
87.7
82.1
85.0
15.0
26.1
62.4
33.5
45.2
-0.5
-8.3
48.4
-18.0
20.5
Rural
66.5
84.9
158.4
250.0
110.0
153.7
151.4
92.0
136.9
72.0
108.4
109.9
72.6
65.1
128.4
47.0
78.3
Total
20.1
31.1
57.0
126.0
92.4
34.8
61.5
25.0
57.6
61.3
34.3
38.8
22.0
21.5
33.5
10.4
30.1
23.5
67.5
31.9
-6.0
76.8
33.2
26.4
26.9
1.1
43.1
38.1
25.1
22.7
46.4
26.8
1 087.5
12.7
80.4
11.7
2.9
127.4
70.4
44.6
84.0
48.6
46.7
370.8
74.3
1 009.6
47.6
154.1
3 836.1
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
61.4
181.4
192.3
254.3
207.1
156.7
133.3
72.5
140.5
71.9
110.1
109.5
67.6
64.7
122.4
48.8
76.3
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
-1.0
0.0
-0.5
0.0
0.0
-1.5
-1.3
-0.8
-0.7
0.0
-1.0
-2.0
-0.1
-0.5
0.0
-4.0
-20.9
Absolute
change
-9.1
0.0
-6.7
0.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-100.0
-46.5
Percent
change
Import
-0.8
0.0
0.0
0.0
0.0
-0.6
-1.3
-5.3
0.0
0.0
-0.7
-2.5
-1.5
-2.0
-0.5
-0.5
-17.6
Absolute
change
-100.0
-100.0
-15.7
-100.0
-100.0
-100.0
-100.0
-28.6
-100.0
-100.0
-59.5
Percent
change
Export
Annex C
119
120
23.7
134.9
150.4
Venezuela
43.4
13.9
52.6
Jordan
Lebanon
Libyan Arab Jamahiriya
92.5
63.0
Syrian Arab Republic
516.9
Iran (Islamic Republic of)
Iraq
185.9
151.9
Egypt
Morocco
154.9
Algeria
1 385.0
16.2
Uruguay
Middle East/
North Africa
2.4
Suriname
Peru
11.4
57.7
Paraguay
31.6
57.6
6.7
0.6
8.0
24.3
66.2
134.2
20.6
414.1
1.2
0.1
0.1
2.2
17.5
Panama
10.1
Rural
26.1
Urban
151.6
16.3
2.5
158.6
69.1
19.7
36.2
Total
124.1
243.5
59.3
14.5
51.4
87.3
583.1
286.1
175.5
1 799.1
Absolute change
Nicaragua
COUNTRY
168.5
172.9
131.9
85.2
156.4
568.6
175.2
247.2
252.1
190.5
119.8
56.4
110.8
145.4
187.4
357.0
234.8
Urban
61.9
61.3
55.1
24.6
103.0
493.8
41.2
160.2
79.0
84.2
6.2
4.7
32.2
86.4
44.5
88.0
112.3
Rural
Percent change
Consumption
117.2
120.8
114.0
77.1
144.8
545.6
127.9
197.0
200.6
147.6
105.1
52.2
100.0
131.9
122.7
266.2
180.1
Total
21.8
43.3
33.9
16.2
30.6
295.4
47.7
69.6
89.3
28.5
23.9
65.9
45.9
21.2
81.8
57.1
63.8
38.9
49.0
18.1
51.5
121.8
33.3
50.1
38.6
43.2
15.5
13.4
32.1
73.7
31.1
73.5
140.1
289.0
71.2
6.3
70.2
110.2
670.7
349.6
214.3
2 120.9
201.0
19.8
2.6
192.3
76.1
29.7
41.3
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
114.7
121.3
121.9
17.4
142.1
881.6
116.3
198.1
206.1
142.9
114.9
53.2
92.9
118.6
123.3
235.7
198.6
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
0.0
0.1
-0.2
0.0
-0.1
12.3
-0.3
-0.6
1.8
17.3
-6.9
-0.4
0.2
0.1
-0.2
-0.3
0.0
Absolute
change
11.1
-6.3
-100.0
159.7
-100.0
-100.0
56.3
64.8
-100.0
-100.0
200.0
9.1
-100.0
-100.0
0.0
Percent
change
Import
-1.2
0.0
0.0
-0.8
1.2
0.0
-24.6
-0.1
0.0
-26.8
0.0
-0.2
0.0
-0.8
0.0
-0.9
0.0
Absolute
change
-100.0
-100.0
66.7
-100.0
-100.0
-89.9
-100.0
-100.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
16.7
Sri Lanka
12.5
1.9
10.1
0.9
2.9
Cameroon
Central African Republic
Chad
3.6
Botswana
Burkina Faso
6.3
Benin
Burundi
20.2
Angola
1 163.8
552.4
Pakistan
Sub-Saharan Africa
17.4
Nepal
229.8
Bangladesh
1 923.6
27.4
Afghanistan
India
2 767.4
South Asia
48.6
61.3
Tunisia
Urban
2.4
0.6
1.2
6.6
18.0
0.3
4.0
4.2
563.4
46.8
464.7
26.7
2 327.6
277.4
36.0
3 179.1
58.8
5.6
Rural
120.1
54.2
Total
5.3
1.5
11.3
8.5
30.5
3.9
10.3
24.4
1 727.2
63.5
1 017.1
44.1
4 251.2
507.2
63.4
5 946.5
Absolute change
Yemen
COUNTRY
294.7
178.1
181.8
921.5
547.8
162.6
304.7
373.0
249.6
221.2
581.0
567.1
454.0
714.8
703.0
489.4
684.4
113.8
Urban
91.8
87.5
23.4
299.4
197.2
23.5
119.2
93.1
86.6
125.3
242.6
136.0
213.0
270.0
321.4
218.5
241.5
22.9
Rural
147.2
125.0
107.6
354.2
267.5
108.3
190.7
246.5
154.6
141.4
354.9
194.3
280.3
376.0
419.9
294.3
360.7
80.5
Total
7.9
45.0
34.1
84.4
37.0
155.9
37.3
115.7
91.8
117.5
65.0
145.2
168.3
101.6
68.1
33.6
102.6
40.7
34.0
90.8
87.5
-11.3
70.7
300.6
14.2
76.5
68.1
33.0
50.8
109.7
191.5
25.6
6.3
1.8
13.5
10.4
41.1
5.9
13.0
16.2
2 008.6
73.1
1 148.5
48.5
4 751.3
594.5
73.5
6 689.4
141.7
57.6
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
143.2
128.6
99.3
335.5
234.9
196.7
180.6
376.7
151.2
139.5
339.0
198.8
262.9
374.6
401.6
278.8
451.3
73.6
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
0.0
0.0
0.0
0.0
0.3
-1.2
0.0
12.5
12.8
0.0
-0.1
-0.3
0.0
-4.6
0.0
-5.0
5.4
-1.1
Absolute
change
-100.0
166.7
56.9
-100.0
-100.0
-100.0
-100.0
56.3
-100.0
Percent
change
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-2.2
-0.4
-0.5
0.0
-3.4
0.0
0.0
-4.3
-1.2
-0.1
Absolute
change
-30.6
-100.0
-100.0
-14.5
-17.7
-100.0
-100.0
Percent
change
Export
Annex C
121
122
4.2
2.1
Mauritania
Mauritius
13.8
10.7
Mali
Mozambique
13.1
10.2
7.4
Liberia
Madagascar
0.8
Lesotho
Malawi
12.4
22.6
36.0
Ghana
Guinea
2.0
Gambia
Kenya
2.4
Gabon
7.0
0.7
2.4
9.0
12.3
12.6
1.6
0.5
28.4
8.2
13.2
0.3
0.1
58.7
2.9
2.0
28.2
Eritrea
Ethiopia
17.9
19.7
Dem. Rep. of the Congo
16.0
0.8
Rural
38.5
2.7
Urban
Absolute change
Cote d’Ivoire
Congo
COUNTRY
20.8
2.8
6.6
19.7
22.5
25.7
9.0
1.3
51.0
20.6
49.2
2.3
2.5
86.9
4.9
37.6
54.5
3.5
Total
390.8
91.6
206.6
528.6
390.5
305.9
286.4
291.3
238.6
363.2
471.5
248.8
172.7
623.0
711.2
1 178.2
334.9
258.7
Urban
93.0
50.7
101.6
184.9
84.4
123.3
75.5
46.0
78.0
141.7
155.9
51.2
36.1
254.3
240.6
507.8
103.9
108.3
Rural
Percent change
Consumption
187.4
75.7
150.0
285.5
130.8
177.2
191.5
100.0
111.1
223.9
305.6
164.3
156.3
314.9
326.7
723.1
202.6
194.4
Total
73.6
31.7
18.6
32.0
28.6
24.7
27.7
112.1
43.7
57.0
108.4
96.6
46.1
99.2
83.0
203.8
88.8
51.4
38.9
15.3
96.2
86.0
66.1
83.6
144.9
-11.1
26.7
62.7
50.3
156.4
50.1
81.8
94.8
89.1
39.4
179.0
27.6
4.0
8.5
28.6
25.1
33.6
11.0
1.7
58.8
25.1
65.9
1.8
3.2
99.9
5.5
50.8
65.6
3.2
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
197.1
76.9
173.5
240.3
129.4
176.8
255.8
113.3
98.7
204.1
309.4
257.1
160.0
315.1
305.6
725.7
204.4
266.7
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
-0.2
0.0
-0.6
0.2
0.0
-0.1
0.4
-0.1
0.4
0.1
-0.1
1.0
0.0
0.0
0.0
-0.2
-0.2
1.3
Absolute
change
-16.7
-100.0
0.0
-100.0
25.0
-100.0
-100.0
100.0
-50.0
-100.0
108.3
Percent
change
Import
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Absolute
change
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
4.4
10.9
Zimbabwe
Australia
Canada
47.8
37.0
2 138.6
37.8
Zambia
High income countries
20.0
3.3
7.4
8.6
Togo
Uganda
United Republic of
Tanzania
1.3
1.3
Swaziland
-6.3
-3.5
-227.9
5.0
36.8
7.8
27.7
16.3
-3.9
5.0
48.9
6.5
5.8
Sierra Leone
Somalia
27.8
Sudan
39.7
Senegal
3.0
120.6
1.8
Rwanda
192.9
6.0
Rural
South Africa
564.9
2.5
Urban
15.9
74.6
27.8
36.3
10.7
2.6
65.2
116.7
10.8
10.9
67.5
4.8
757.8
8.5
Total
41.5
33.5
1 910.7
Absolute change
Nigeria
Niger
COUNTRY
16.0
31.0
34.9
192.3
259.1
156.4
480.6
373.6
204.5
334.2
81.0
874.6
236.6
368.3
525.9
334.1
226.9
Urban
-12.3
-20.4
-13.2
44.9
138.9
17.3
211.5
120.5
65.4
69.8
-3.4
403.5
99.2
187.7
194.2
88.9
107.3
Rural
11.9
24.6
24.3
94.6
181.5
48.3
243.6
227.7
100.0
171.6
44.4
568.4
151.4
263.7
252.6
196.3
126.9
Total
-6.5
0.1
72.7
81.9
-8.5
19.7
62.6
301.9
58.5
40.5
105.6
33.3
79.0
87.2
56.8
-12.9
18.9
20.1
0.8
40.9
58.5
128.9
58.3
-6.4
51.5
-3.3
136.5
79.8
62.2
65.2
70.6
119.7
51.0
40.6
2 237.6
18.2
83.6
30.4
44.2
13.5
4.1
73.0
125.9
13.2
12.9
83.4
5.4
861.6
11.1
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
13.7
24.5
25.0
85.0
180.2
48.7
222.1
214.3
455.6
162.9
38.3
528.0
167.5
252.7
245.5
196.6
108.8
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
Percent change
Consumption
-17.6
-1.2
-29.6
0.0
-0.1
-0.1
0.2
0.0
-0.3
-0.1
0.0
0.0
0.3
-0.2
0.0
-0.4
0.0
Absolute
change
-46.8
-100.0
-21.5
-100.0
-9.1
0.0
-12.5
-100.0
16.7
-100.0
-100.0
0.0
Percent
change
Import
-15.4
-1.2
-21.1
0.1
-0.8
-0.1
0.0
0.0
-0.3
0.0
-1.1
0.0
0.0
0.0
0.0
0.0
0.0
Absolute
change
-100.0
-100.0
-16.6
5.3
-100.0
-100.0
-100.0
-26.8
Percent
change
Export
Annex C
123
124
0.8
1 076.8
1.0
United States of America
Trinidad and Tobago
-3.6
-1.9
Switzerland
-144.5
13.1
141.8
Saudi Arabia
32.2
414.5
-0.4
-0.6
-115.9
0.7
0.2
Rural
Republic of Korea
3.8
4.8
389.3
Japan
New Zealand
23.6
Israel
Norway
0.0
Urban
Absolute change
Iceland
COUNTRY
932.3
1.8
-5.5
154.9
446.7
4.4
3.2
273.4
24.3
0.2
Total
31.2
137.3
-3.4
170.9
113.8
13.5
12.0
24.0
39.6
3.2
Urban
-21.4
25.0
-22.2
73.1
35.8
-4.7
-12.4
-13.8
12.0
50.1
Rural
Percent change
Consumption
22.6
46.2
-7.6
153.5
98.4
9.8
8.7
11.1
37.2
11.1
Total
-4.7
49.6
-0.9
22.4
76.4
0.0
-6.2
16.1
-5.7
-4.1
24.7
3.5
-14.2
71.0
6.1
8.9
14.4
-4.6
36.0
13.9
1 115.4
-0.9
-7.1
207.9
503.4
4.4
3.4
286.3
33.1
0.1
Proportion Proportion
of change of change
Absolute
due to
due to
change in change in change
consump. population
%
rates %
22.3
-27.3
-19.3
153.9
98.9
8.9
7.5
11.3
37.6
4.5
Percent
change
Production
EGGS, CHANGE BETWEEN 2000 AND 2030
-7.5
2.3
1.0
-5.8
0.3
-0.8
-0.4
0.5
-0.3
-0.1
Absolute
change
-100.0
85.2
2.6
-100.0
11.1
-100.0
-100.0
1.3
-100.0
-100.0
Percent
change
Import
2.4
0.0
0.0
-5.3
-0.1
-1.2
-0.8
-0.2
1.0
-0.3
Absolute
change
2.5
-100.0
-100.0
-52.2
-100.0
-100.0
25.0
-100.0
Percent
change
Export
Mapping supply and demand for animal-source foods to 2030
Annex D. Consumption of
livestock commodities by city
The following tables report city-level data on population, consumption of the different livestock commodities and the growth between 2000 and 2030 for the most
populous or significant cities in each region. The ‘percentage of national growth
attributable to city’ represents the contribution of each city to national growth in
demand. Consumption values are in thousands of metric tonnes, while growth is
expressed as percentage.
125
126
Shanghai
Bejing
Tianjin
Pyongyang
Jakarta
Surabaya
Kuala Lampur
Yangon City
Metro Manila
Bangkok
Thanh Pho Ho Chi Minh
China
China
Dem. People’s Rep. of
Korea
Indonesia
Indonesia
Malaysia
Myanmar
Philippines
Thailand
Viet Nam
Moscow
Sankt Peterburg
Istanbul
Ankara
Russian Federation
Russian Federation
Turkey
Turkey
Eastern Europe and Central Asia
Shenzhen
China
CITY
China
East Asia and Pacific
COUNTRY
BEEF
MILK
3.3
11.6
5.1
12.7
5.1
8.8
12.2
4.2
3.6
5.1
19.9
2.4
6.8
10.0
13.7
26.3
5.3
18.7
4.4
10.9
12.2
16.1
24.0
9.2
7.3
11.0
42.8
3.2
13.0
19.2
26.4
50.4
62
62
-14
-14
139
82
97
123
103
115
115
35
92
92
92
92
18.6
51.5
73.1
265.0
15.8
41.5
145.4
14.2
26.9
11.8
47.0
5.1
24.6
40.8
67.7
125.1
39.7
109.4
76.7
278.5
47.4
99.4
478.2
47.9
92.0
47.2
187.7
11.9
96.3
159.7
263.4
485.1
113
113
5
5
200
140
229
238
242
299
299
135
291
291
289
288
8
22
18
66
23
40
62
29
32
6
24
35
1
2
3
5
427.5
1 181.1
675.0
2 447.5
26.1
246.8
617.5
80.2
245.2
47.3
188.1
21.0
52.6
87.2
144.6
267.2
855.7
2 359.7
671.3
2 436.7
118.1
956.4
1 701.3
265.0
612.4
152.6
606.4
44.5
215.2
356.9
588.7
1 084.2
100
100
-1
0
353
287
176
230
150
222
222
112
309
309
307
306
8
22
0
1
18
32
65
29
36
7
27
36
1
2
3
5
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Table D 1. Consumption and consumption growth between 2000 and 2030 of beef and milk for selected cities.
Sao Paulo
Rio de Janeiro
Belo Horizonte
Santiago
Bogota
Santo Domingo
Mexico City
Monterrey
Guadalajara
Lima
Caracas
Brazil
Brazil
Brazil
Chile
Colombia
Dominican Republic
Mexico
Mexico
Mexico
Peru
Venezuela
Alger
Al Qahirah
Al Iskandariyah
Asyut
Tehran
Algeria
Egypt
Egypt
Egypt
Iran (Islamic Republic of)
North Africa/Middle East
Buenos Aires
CITY
Argentina
Latin America/Caribbean
COUNTRY
BEEF
MILK
9.6
3.3
3.8
11.4
3.6
6.3
6.9
5.5
5.5
26.9
2.2
6.3
5.5
4.2
11.2
19.4
12.6
16.6
6.3
7.1
21.5
6.7
10.3
10.7
8.3
8.3
40.4
3.8
10.3
7.8
6.1
16.3
28.2
17.3
72
88
88
88
86
64
55
50
50
50
73
62
43
45
45
45
38
65.1
109.5
31.5
118.5
22.2
134.0
38.5
73.3
75.1
363.1
22.9
64.3
104.9
189.0
489.9
881.7
796.3
165.4
236.3
67.9
255.6
68.2
251.4
96.0
153.8
157.6
761.5
47.2
122.2
190.5
320.9
831.5
1 497.1
1 013.6
154
116
116
116
207
88
149
110
110
110
107
90
82
70
70
70
27
29
18
5
20
23
39
42
5
5
25
58
12
38
4
11
20
47
792.9
451.2
129.7
488.1
514.0
671.5
484.1
456.2
467.2
2 258.2
167.1
412.4
555.3
618.7
1 603.7
2 886.0
3 033.2
1 818.9
1 071.4
307.9
1 159.0
1 210.4
1 257.8
991.2
874.1
895.2
4 326.9
353.7
883.8
1 128.7
1 185.7
3 072.2
5 531.0
4 583.8
129
137
137
137
135
87
105
92
92
92
112
114
103
92
92
92
51
30
18
5
19
25
39
43
5
5
26
57
11
37
4
11
19
43
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Annex D
127
128
Baghdad
Amman
Beirut
Tripoli
Casablanca
Damascus
Tunis
Sanaa
Iraq
Jordan
Lebanon
Libyan Arab Jamahiriya
Morocco
Syrian Arab Republic
Tunisia
Yemen
Kabul
Dhaka
Chittagong
Mumbai
Delhi Municipality
Kolkata
Karachi
Lahore
Colombo
Afghanistan
Bangladesh
Bangladesh
India
India
India
Pakistan
Pakistan
Sri Lanka
South Asia
CITY
COUNTRY
BEEF
MILK
2.0
5.5
9.9
12.8
14.3
17.4
2.3
6.5
2.0
1.3
1.9
2.1
3.4
1.9
1.3
2.4
5.5
3.2
15.7
28.4
26.2
29.2
35.6
6.4
18.1
7.9
6.5
2.9
4.6
6.2
3.2
1.9
4.3
11.2
59
186
186
104
104
104
178
178
297
384
54
115
80
68
41
80
103
3.4
38.3
73.0
42.1
44.8
45.1
5.5
15.2
9.3
5.2
16.7
5.0
30.7
6.6
18.5
15.1
15.4
5.9
148.3
281.5
93.2
99.0
99.6
19.0
51.6
51.0
30.1
33.9
15.7
66.8
15.3
44.0
29.5
96.4
75
287
285
121
121
121
247
240
449
484
103
214
118
133
138
95
525
26
8
15
4
4
4
8
21
15
19
39
15
34
33
57
65
34
75.4
979.2
1 867.4
1 067.5
1 134.5
1 141.6
60.1
166.8
109.4
49.6
252.7
158.9
217.5
104.2
218.0
198.4
202.0
153.8
3 591.1
6 818.4
3 437.5
3 653.2
3 672.1
260.0
707.1
493.8
276.6
525.1
411.3
507.9
216.1
349.1
457.7
1 177.0
104
267
265
222
222
222
333
324
351
457
108
159
134
107
60
131
483
21
8
15
3
3
3
7
19
15
19
38
16
33
33
60
64
34
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Mapping supply and demand for animal-source foods to 2030
Abidjan
Kinshasa
Addis Ababa
Accra
Nairobi
Lagos
Kano
Ibadan
Dakar
Johannesburg
Durban
Al Khartum
Dar es Salaam
Cote d’Ivoire
Dem. Rep. of the Congo
Ethiopia
Ghana
Kenya
Nigeria
Nigeria
Nigeria
Senegal
South Africa
South Africa
Sudan
United Republic of
Tanzania
Toronto
Melbourne
Australia
Canada
Sydney
Australia
High Income Countries
Luanda
CITY
Angola
Sub-Saharan Africa
COUNTRY
BEEF
MILK
5.6
3.6
4.8
2.1
7.1
3.0
14.5
2.5
2.8
3.4
8.5
2.3
2.4
2.9
2.7
2.0
3.7
7.2
4.7
6.4
6.0
19.1
3.6
17.4
5.8
7.6
9.0
22.8
5.2
5.9
10.1
9.7
4.3
12.4
27
31
31
183
170
20
20
136
169
169
169
126
145
256
262
112
237
182.9
144.3
139.3
16.3
42.4
44.6
106.8
12.3
9.7
9.2
32.2
31.7
4.2
16.3
3.2
13.3
31.0
227.9
174.5
168.4
57.5
142.9
62.7
150.2
33.6
45.7
43.2
151.4
95.3
16.9
65.3
26.8
41.5
131.5
25
21
21
253
237
41
41
174
371
371
371
200
306
301
743
213
324
24
26
25
18
34
27
64
38
5
5
16
28
27
14
27
45
52
1 121.9
921.5
889.8
58.8
685.9
190.5
456.0
66.5
27.6
26.1
91.4
284.9
17.8
69.3
6.1
28.4
62.5
1 487.6
1 151.4
1 111.0
230.3
2 400.8
292.7
700.7
170.7
89.8
84.9
297.5
739.6
62.6
313.9
40.2
83.0
268.1
33
25
25
292
250
54
54
157
226
226
226
160
251
353
561
192
329
23
25
24
17
34
19
45
39
5
5
18
32
28
13
28
46
52
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Annex D
129
130
CITY
Montreal
Jerusalem
Tokyo
Sapporo
Seoul
Pusan
Jiddah
ArRiyadh
New York
Los Angeles
Chicago
COUNTRY
Canada
Israel
Japan
Japan
Republic of Korea
Republic of Korea
Saudi Arabia
Saudi Arabia
United States of America
United States of America
United States of America
BEEF
MILK
9.9
17.8
23.2
3.6
3.9
5.1
19.8
3.4
78.6
5.0
3.6
14.1
25.4
33.2
7.5
8.1
5.9
22.9
3.6
83.8
7.6
4.6
43
43
43
111
111
16
16
7
7
51
27
444.0
766.1
1 089.3
13.3
14.4
54.5
226.3
23.4
607.0
107.7
132.9
527.5
909.3
1 288.6
44.7
48.3
95.9
406.7
39.3
1 018.3
169.8
158.6
19
19
18
236
236
76
80
68
68
58
19
8
14
20
24
26
12
50
3
68
91
14
2 618.4
4 517.8
6 423.5
419.0
452.3
128.3
533.0
162.8
4 225.4
1 097.8
815.2
3 710.5
6 395.9
9 064.5
1 156.3
1 248.1
293.3
1 243.6
235.7
6 109.8
1 815.9
1 035.1
42
42
41
176
176
129
133
45
45
65
27
5
9
13
24
26
11
48
3
76
90
14
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Mapping supply and demand for animal-source foods to 2030
Shanghai
Bejing
Tianjin
Pyongyang
Jakarta
Surabaya
Kuala Lampur
Yangon City
Metro Manila
Bangkok
Thanh Pho Ho Chi Minh
China
China
China
Dem. People’s Rep. of
Korea
Indonesia
Indonesia
Malaysia
Myanmar
Philippines
Thailand
Viet Nam
Istanbul
Turkey
Ankara
Sankt Peterburg
Russian Federation
Turkey
Moscow
Russian Federation
EasternEurope and Central Asia
Shenzhen
CITY
China
East Asia and Pacific
COUNTRY
MUTTON
PORK
3.3
11.6
5.1
12.7
5.1
8.8
12.2
4.2
3.6
5.1
19.9
2.4
6.8
10.0
13.7
26.3
5.3
18.7
4.4
10.9
12.2
16.1
24.0
9.2
7.3
11.0
42.8
3.2
13.0
19.2
26.4
50.4
62
62
-14
-14
139
82
97
123
103
115
115
35
92
92
92
92
19.4
53.7
4.3
15.8
0.4
0.1
13.6
1.0
3.1
2.3
9.1
2.6
12.9
21.3
35.4
65.4
34.1
94.1
5.7
20.6
1.4
0.2
36.5
3.7
6.3
6.6
26.4
6.7
33.9
56.2
92.6
170.6
76
75
31
31
258
82
168
271
102
191
191
153
163
163
162
161
9
24
4
13
17
30
67
28
41
7
29
34
1
2
4
7
62.9
228.1
112.2
84.3
425.0
13.1
36.0
13.9
55.1
34.7
191.6
317.9
527.1
974.1
69.0
250.5
503.7
258.8
1 306.3
60.9
99.6
80.0
317.9
74.0
498.3
826.6
1 363.3
2 510.9
10
10
349
207
207
366
177
477
477
113
160
160
159
158
5
20
18
34
63
25
34
6
22
36
1
2
4
7
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Table D 2. Consumption and consumption growth between 2000 and 2030 of mutton and pork for selected cities.
Annex D
131
132
Sao Paulo
Rio de Janeiro
Belo Horizonte
Santiago
Bogota
Santo Domingo
Mexico City
Monterrey
Guadalajara
Lima
Caracas
Brazil
Brazil
Chile
Colombia
Dominican Republic
Mexico
Mexico
Mexico
Peru
Venezuela
Alger
Al Qahirah
Al Iskandariyah
Asyut
Tehran
Algeria
Egypt
Egypt
Egypt
Iran (Islamic Republic of)
North Africa/Middle East
Buenos Aires
Brazil
CITY
Argentina
Latin America/Caribbean
COUNTRY
MUTTON
PORK
9.6
3.3
3.8
11.4
3.6
6.3
6.9
5.5
5.5
26.9
2.2
6.3
5.5
4.2
11.2
19.4
12.6
16.6
6.3
7.1
21.5
6.7
10.3
10.7
8.3
8.3
40.4
3.8
10.3
7.8
6.1
16.3
28.2
17.3
72
88
88
88
86
64
55
50
50
50
73
62
43
45
45
45
38
87.8
13.9
4.0
15.0
28.3
3.1
10.8
4.7
4.8
23.3
0.4
1.1
4.0
3.7
9.5
17.0
21.3
181.9
30.4
8.7
32.9
67.7
5.3
19.1
7.2
7.4
35.7
0.4
1.9
6.6
6.6
17.2
31.0
34.7
107
119
119
119
139
73
77
53
53
53
20
68
62
82
82
82
63
31
18
5
20
25
41
44
6
6
29
0
12
39
4
11
19
42
0.4
0.1
0.4
0.0
38.3
28.1
50.2
51.4
248.3
21.0
8.3
80.3
51.7
133.9
240.9
104.7
0.7
0.2
0.7
0.0
63.3
82.8
95.1
97.3
470.5
67.5
24.4
141.0
138.3
358.4
645.3
148.8
88
88
88
-16
65
194
90
90
90
222
192
76
168
168
168
42
18
5
19
0
41
42
5
5
26
49
11
38
4
10
18
44
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Mapping supply and demand for animal-source foods to 2030
Baghdad
Amman
Beirut
Tripoli
Casablanca
Damascus
Tunis
Sanaa
Iraq
Jordan
Lebanon
Libyan Arab Jamahiriya
Morocco
Syrian Arab Republic
Tunisia
Yemen
Kabul
Dhaka
Chittagong
Mumbai
Delhi Municipality
Kolkata
Karachi
Lahore
Colombo
Afghanistan
Bangladesh
Bangladesh
India
India
India
Pakistan
Pakistan
Sri Lanka
South Asia
CITY
COUNTRY
MUTTON
PORK
2.0
5.5
9.9
12.8
14.3
17.4
2.3
6.5
2.0
1.3
1.9
2.1
3.4
1.9
1.3
2.4
5.5
3.2
15.7
28.4
26.2
29.2
35.6
6.4
18.1
7.9
6.5
2.9
4.6
6.2
3.2
1.9
4.3
11.2
59
186
186
104
104
104
178
178
297
384
54
115
80
68
41
80
103
0.2
21.8
41.6
10.9
11.6
11.7
4.1
11.4
9.5
4.4
17.0
19.9
32.1
11.4
5.0
13.1
9.1
0.8
65.1
123.5
29.7
31.6
31.8
17.3
47.1
64.8
25.7
33.4
49.2
72.3
26.8
7.8
31.8
76.4
217
198
197
172
172
171
323
314
580
482
96
147
126
134
55
143
736
16
9
16
3
3
3
7
19
14
19
39
16
33
33
60
64
34
0.2
9.1
9.7
9.8
0.1
6.5
0.0
0.6
35.1
37.3
37.5
0.2
10.3
0.1
270
283
283
283
80
59
80
15
3
3
3
34
60
0
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Annex D
133
134
Abidjan
Kinshasa
Addis Ababa
Accra
Nairobi
Lagos
Kano
Ibadan
Dakar
Johannesburg
Durban
Al Khartum
Dar es Salaam
Dem. Rep. of the Congo
Ethiopia
Ghana
Kenya
Nigeria
Nigeria
Nigeria
Senegal
South Africa
South Africa
Sudan
United Republic of
Tanzania
Sydney
Melbourne
Toronto
Australia
Australia
Canada
High Income Countries
Luanda
Cote d’Ivoire
CITY
Angola
Sub-Saharan Africa
COUNTRY
MUTTON
PORK
5.6
3.6
4.8
2.1
7.1
3.0
14.5
2.5
2.8
3.4
8.5
2.3
2.4
2.9
2.7
2.0
3.7
7.2
4.7
6.4
6.0
19.1
3.6
17.4
5.8
7.6
9.0
22.8
5.2
5.9
10.1
9.7
4.3
12.4
27
31
31
183
170
20
20
136
169
169
169
126
145
256
262
112
237
4.6
62.1
60.0
2.9
36.9
15.0
35.8
7.7
6.5
6.2
21.7
6.2
2.9
3.4
3.3
2.5
3.3
6.1
70.3
67.8
9.6
184.7
18.1
43.2
24.0
23.4
22.2
77.6
16.7
11.1
14.7
18.2
6.6
16.6
33
13
13
236
400
21
21
213
258
258
258
172
283
332
447
166
408
22
33
32
18
29
-47
-113
37
5
5
17
30
27
13
29
48
50
165.7
66.2
63.9
1.0
9.9
23.7
1.7
4.5
4.3
15.1
1.3
2.0
0.1
4.1
3.2
12.1
207.3
97.7
94.3
5.7
16.2
38.7
6.9
17.6
16.7
58.3
6.8
7.3
0.3
31.6
10.7
51.1
25
48
48
488
63
63
316
288
288
288
443
262
256
677
233
322
24
22
21
15
16
39
35
5
5
17
22
27
12
27
44
52
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Mapping supply and demand for animal-source foods to 2030
CITY
Montreal
Jerusalem
Tokyo
Sapporo
Seoul
Pusan
Jiddah
ArRiyadh
New York
Los Angeles
Chicago
COUNTRY
Canada
Israel
Japan
Japan
Republic of Korea
Republic of Korea
Saudi Arabia
Saudi Arabia
United States of America
United States of America
United States of America
MUTTON
PORK
9.9
17.8
23.2
3.6
3.9
5.1
19.8
3.4
78.6
5.0
3.6
14.1
25.4
33.2
7.5
8.1
5.9
22.9
3.6
83.8
7.6
4.6
43
43
43
111
111
16
16
7
7
51
27
5.6
9.7
13.8
30.0
32.4
0.6
2.4
0.5
13.4
6.1
3.4
7.3
12.6
17.9
82.4
89.0
1.1
4.5
0.5
12.9
10.1
4.3
30
30
29
174
174
89
93
-4
-4
65
27
6
11
15
24
26
12
51
1
14
91
13
306.1
528.1
750.9
0.0
0.1
102.2
424.6
43.5
1 127.9
8.8
120.4
407.2
701.9
994.7
0.1
0.1
176.0
746.3
52.3
1 357.0
15.7
144.2
33
33
32
111
111
72
76
20
20
79
20
6
10
14
13
14
12
51
5
133
90
14
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Annex D
135
136
5.1
3.6
Bejing
Tianjin
Pyongyang
Jakarta
Surabaya
China
China
Dem. People's Rep. of
Korea
Indonesia
Indonesia
26.3
8.8
5.1
Metro Manila
Bangkok
Thanh Pho Ho Chi Minh
Philippines
Thailand
Viet Nam
Moscow
Sankt Peterburg
Istanbul
Ankara
Russian Federation
Russian Federation
Turkey
Turkey
3.3
11.6
5.1
12.7
12.2
4.2
Kuala Lampur
Yangon City
Malaysia
Myanmar
19.9
2.4
6.8
10.0
13.7
Shenzhen
Shanghai
Eastern Europe and Central Asia
POULTRY MEAT
EGGS
5.3
18.7
4.4
10.9
12.2
16.1
24.0
9.2
7.3
11.0
42.8
3.2
13.0
19.2
26.4
50.4
62
62
-14
-14
139
82
97
123
103
115
115
35
92
92
92
92
33.7
93.2
46.7
169.2
30.0
155.4
237.6
22.9
176.1
22.1
87.9
6.6
56.8
94.1
156.1
288.5
132.4
365.2
76.7
278.5
176.5
523.8
1,075.4
152.4
494.4
172.5
685.4
23.6
211.7
351.1
579.1
1,066.6
293
292
64
65
488
237
353
566
181
680
680
256
273
273
271
270
7
19
3
12
17
33
59
23
34
5
21
32
1
2
3
5
29.5
81.6
57.6
208.8
14.6
108.8
191.4
8.6
59.8
17.8
70.9
25.0
95.5
158.5
262.8
485.6
64.9
179.0
67.1
243.7
63.6
278.9
607.6
42.8
158.2
97.6
387.9
57.1
215.2
356.9
588.7
1,084.2
120
119
17
17
336
156
217
399
164
448
447
129
125
125
124
123
8
21
4
16
19
38
62
24
35
6
22
35
2
3
5
9
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
China
CITY
China
East Asia and Pacific
COUNTRY
POPULATION
Table D 3. Consumption and consumption growth between 2000 and 2030 of poultry meat and eggs for selected cities.
Mapping supply and demand for animal-source foods to 2030
5.5
6.3
Belo Horizonte
Santiago
Brazil
Chile
19.4
6.9
Monterrey
Guadalajara
Lima
Caracas
Mexico
Mexico
Peru
Venezuela
Al Qahirah
Al Iskandariyah
Asyut
Tehran
Egypt
Egypt
Egypt
Iran (Islamic Republic of)
Alger
Algeria
North Africa/Middle East
5.5
Mexico City
Mexico
9.6
3.3
3.8
11.4
3.6
6.3
5.5
26.9
2.2
Bogota
Santo Domingo
Colombia
Dominican Republic
4.2
11.2
Sao Paulo
Rio de Janeiro
Brazil
12.6
Brazil
Buenos Aires
CITY
Argentina
Latin America/Caribbean
COUNTRY
POULTRY MEAT
EGGS
16.6
6.3
7.1
21.5
6.7
10.3
10.7
8.3
8.3
40.4
3.8
10.3
7.8
6.1
16.3
28.2
17.3
72
88
88
88
86
64
55
50
50
50
73
62
43
45
45
45
38
170.9
80.2
23.0
86.7
35.9
210.5
117.5
91.6
93.8
453.2
67.5
48.4
114.6
159.3
412.8
742.9
373.2
606.8
337.4
97.0
365.0
135.4
595.8
488.1
277.0
283.7
1,371.3
189.5
186.3
232.7
316.1
819.0
1,474.6
675.7
255
321
321
321
277
183
315
203
203
203
181
285
103
98
98
98
81
27
16
5
18
22
37
41
5
5
24
51
10
37
4
11
19
41
94.0
19.2
5.5
20.8
13.8
48.0
44.2
63.0
64.5
312.0
15.3
25.9
26.7
38.4
99.5
179.1
100.0
259.9
66.7
19.2
72.2
52.8
105.9
111.0
117.0
119.8
579.0
46.4
60.9
49.4
71.1
184.3
331.9
154.4
176
248
248
248
283
121
151
86
86
86
204
136
85
85
85
85
54
28
17
5
18
22
38
42
5
5
26
50
11
38
4
11
19
43
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Annex D
137
138
Sanaa
Yemen
Lahore
Colombo
Pakistan
Sri Lanka
12.8
Kolkata
Karachi
India
Delhi Municipality
India
Pakistan
14.3
Mumbai
India
6.5
2.0
5.5
9.9
17.4
2.3
Dhaka
Chittagong
Bangladesh
2.0
1.3
1.9
2.1
3.4
1.9
Bangladesh
Kabul
Afghanistan
South Asia
Damascus
Tunis
Syrian Arab Republic
Casablanca
Morocco
Tunisia
Tripoli
Libyan Arab Jamahiriya
1.3
2.4
Amman
Beirut
Baghdad
Iraq
Jordan
5.5
CITY
COUNTRY
Lebanon
POULTRY MEAT
EGGS
3.2
15.7
28.4
26.2
29.2
35.6
6.4
18.1
7.9
6.5
2.9
4.6
6.2
3.2
1.9
4.3
11.2
59
186
186
104
104
104
178
178
297
384
54
115
80
68
41
80
103
6.9
14.1
26.8
16.8
17.9
18.0
3.5
9.8
1.0
10.4
28.1
12.5
56.1
27.8
40.1
68.9
15.7
32.5
125.0
237.3
233.5
248.1
249.4
41.7
113.3
17.5
97.5
90.2
84.0
192.1
79.4
93.1
186.8
218.2
371
789
785
1288
1288
1286
1080
1055
1742
834
222
575
243
185
132
171
1288
15
7
13
2
3
3
6
16
13
18
35
14
30
32
57
63
34
4.5
12.4
23.6
24.4
25.9
26.1
4.2
11.7
1.1
3.1
18.1
11.6
44.0
14.6
9.9
20.8
5.2
14.8
84.6
160.7
136.0
144.5
145.3
34.8
94.6
9.7
24.7
38.7
31.3
120.0
34.0
18.4
53.4
34.6
229
583
580
458
458
458
726
709
783
695
114
169
173
132
85
156
571
16
7
13
3
3
3
6
16
14
18
38
16
31
33
58
63
34
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Mapping supply and demand for animal-source foods to 2030
Al Khartum
Dar es Salaam
Sudan
United Republic of
Tanzania
Melbourne
Toronto
Australia
Canada
Sydney
Australia
High Income Countries
Johannesburg
Durban
Dakar
Senegal
South Africa
Ibadan
Nigeria
South Africa
Kano
Nigeria
2.3
Nairobi
Lagos
Kenya
Accra
Ghana
Nigeria
2.4
Addis Ababa
Ethiopia
2.0
5.6
3.6
4.8
2.1
7.1
3.0
14.5
2.5
2.8
3.4
8.5
2.9
2.7
Abidjan
Kinshasa
Cote d'Ivoire
3.7
Luanda
CITY
Dem. Rep. of the Congo
Angola
Sub-Saharan Africa
COUNTRY
POULTRY MEAT
EGGS
7.2
4.7
6.4
6.0
19.1
3.6
17.4
5.8
7.6
9.0
22.8
5.2
5.9
10.1
9.7
4.3
12.4
27
31
31
183
170
20
20
136
169
169
169
126
145
256
262
112
237
194.1
114.3
110.3
3.1
4.3
61.9
148.1
15.9
5.0
4.8
16.7
6.0
5.3
2.3
3.5
16.5
13.6
276.4
183.8
177.3
21.5
30.7
121.2
290.2
72.0
29.1
27.5
96.3
30.5
29.5
19.3
53.6
60.6
76.5
42
61
61
594
608
96
96
352
477
477
477
404
451
748
1442
267
463
22
21
21
14
27
13
32
35
5
4
16
22
25
11
26
43
49
61.8
25.3
24.4
4.2
5.5
20.8
49.8
6.2
11.0
10.4
36.4
5.1
2.5
1.5
0.8
6.7
3.0
73.0
33.2
32.0
10.8
25.1
37.6
90.1
29.3
48.7
46.1
161.4
18.0
14.7
11.6
10.7
29.0
15.3
18
31
31
157
357
81
81
375
343
343
343
254
497
662
1256
336
405
27
24
23
24
30
14
35
34
5
5
16
25
25
12
26
41
50
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Annex D
139
140
Pusan
Jiddah
ArRiyadh
New York
Los Angeles
Chicago
Republic of Korea
Saudi Arabia
United States of America
United States of America
United States of America
Seoul
Republic of Korea
Saudi Arabia
Sapporo
Japan
9.9
17.8
23.2
3.6
3.9
5.1
19.8
3.4
78.6
5.0
Jerusalem
Tokyo
Montreal
Canada
Israel
3.6
CITY
COUNTRY
Japan
POULTRY MEAT
EGGS
14.1
25.4
33.2
7.5
8.1
5.9
22.9
3.6
83.8
7.6
4.6
43
43
43
111
111
16
16
7
7
51
27
487.0
840.3
1,194.7
153.0
165.1
50.5
209.6
37.5
972.9
246.6
141.0
874.6
1,507.6
2,136.6
434.3
468.7
127.9
542.4
60.2
1,561.4
513.2
192.3
80
79
79
184
184
153
159
61
60
108
36
5
8
11
24
26
11
48
3
70
89
13
148.5
256.3
364.4
21.8
23.5
45.6
189.7
47.6
1,235.5
56.6
44.9
200.2
345.0
489.0
59.7
64.4
96.0
407.1
59.2
1,534.2
79.0
50.8
35
35
34
174
174
110
115
24
24
40
13
6
10
13
24
26
11
49
4
109
92
14
Percentage
Percentage
Cons
Cons
of national
of national
Pop growth
Growth
Growth
Pop 2000 Pop 2030
growth atgrowth at- Cons 2000 Cons 2030
2000-2030 Cons 2000 Cons 2030
2000-2030
2000-2030
(millions) (millions)
tributable
tributable
%
%
%
to city
to city
POPULATION
Mapping supply and demand for animal-source foods to 2030
141
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