Climate Change and Land
An IPCC Special Report on climate change, desertification, land
degradation, sustainable land management, food security, and
greenhouse gas fluxes in terrestrial ecosystems

Summary for Policymakers

WG I

WG II

WG III

IPCC Special Report on Climate Change, Desertification, Land
Degradation, Sustainable Land Management, Food Security, and
Greenhouse gas fluxes in Terrestrial Ecosystems
Summary for Policymakers
Approved Draft
Subject to copy edit and layout
Date of draft: 07 August 2019
Drafting Authors:
Almut Arneth (Germany), Humberto Barbosa (Brazil), Tim Benton (United Kingdom), Katherine
Calvin (The United States of America), Eduardo Calvo (Peru), Sarah Connors (United Kingdom),
Annette Cowie (Australia), Edouard Davin (France/Switzerland), Fatima Denton (The Gambia),
Renée van Diemen (The Netherlands/United Kingdom), Fatima Driouech (Morocco), Aziz Elbehri
(Morocco), Jason Evans (Australia), Marion Ferrat (France), Jordan Harold (United Kingdom),
Eamon Haughey (Ireland), Mario Herrero (Australia/Costa Rica), Joanna House (United Kingdom),
Mark Howden (Australia), Margot Hurlbert (Canada), Gensuo Jia (China), Tom Gabriel Johansen
(Norway), Jagdish Krishnaswamy (India), Werner Kurz (Canada), Christopher Lennard (South
Africa), Soojeong Myeong (Republic of Korea); Nagmeldin Mahmoud (Sudan), Valérie MassonDelmotte (France), Cheikh Mbow (Senegal), Pamela McElwee (The United States of America),
Alisher Mirzabaev (Germany/Uzbekistan), Angela Morelli (Norway/Italy), Wilfran Moufouma-Okia
(France), Dalila Nedjraoui (Algeria), Suvadip Neogi (India), Johnson Nkem (Cameroon), Nathalie De
Noblet-Ducoudré (France), Lennart Olsson (Sweden), Minal Pathak (India), Jan Petzold (Germany),
Ramón Pichs-Madruga (Cuba), Elvira Poloczanska (United Kingdom/Australia), Alexander Popp
(Germany), Hans-Otto Pörtner (Germany), Joana Portugal Pereira (United Kingdom), Prajal Pradhan
(Nepal/Germany), Andy Reisinger (New Zealand), Debra C. Roberts (South Africa), Cynthia
Rosenzweig (The United States of America), Mark Rounsevell (United Kingdom/Germany), Elena
Shevliakova (The United States of America), Priyadarshi Shukla (India), Jim Skea (United Kingdom),
Raphael Slade (United Kingdom), Pete Smith (United Kingdom), Youba Sokona (Mali), Denis Jean
Sonwa (Cameroon), Jean-Francois Soussana (France), Francesco Tubiello (The United States of
America/Italy), Louis Verchot (The United States of America/Colombia), Koko Warner (The United
States of America/Germany), Nora Weyer (Germany), Jianguo Wu (China), Noureddine Yassaa
(Algeria), Panmao Zhai (China), Zinta Zommers (Latvia).

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Introduction
This Special Report on Climate Change and Land 1 responds to the Panel decision in 2016 to
prepare three Special Reports 2 during the Sixth Assessment cycle, taking account of proposals
from governments and observer organizations 3. This report addresses greenhouse gas (GHG)
fluxes in land-based ecosystems , land use and sustainable land management 4 in relation to climate
change adaptation and mitigation, desertification 5, land degradation 6 and food security 7. This
report follows the publication of other recent reports, including the IPCC Special Report on Global
Warming of 1.5°C (SR15), the thematic assessment of the Intergovernmental Science Policy
Platform on Biodiversity and Ecosystem Services (IPBES) on Land Degradation and Restoration,
the IPBES Global Assessment Report on Biodiversity and Ecosystem Services, and the Global
Land Outlook of the UN Convention to Combat Desertification (UNCCD). This report provides
an updated assessment of the current state of knowledge 8 while striving for coherence and
complementarity with other recent reports.
This Summary for Policymakers (SPM) is structured in four parts: A) People, land and climate in
a warming world; B) Adaptation and mitigation response options; C) Enabling response options;
and D) Action in the near-term.
Confidence in key findings is indicated using the IPCC calibrated language 9; the underlying
scientific basis of each key finding is indicated by references to the main report.
The terrestrial portion of the biosphere that comprises the natural resources (soil, near-surface air, vegetation and
other biota, and water), the ecological processes, topography, and human settlements and infrastructure that operate
within that system.
2
The three Special reports are: “Global Warming of 1.5°C. An IPCC special report on the impacts of global warming
of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of
strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate
poverty.”; “Climate Change and Land: an IPCC Special Report on Climate Change, Desertification, Land
Degradation, Sustainable Land Management, Food Security, and Greenhouse gas fluxes in Terrestrial Ecosystems”;
“The Ocean and Cryosphere in a Changing Climate”
3
related proposals were: climate change and desertification; desertification with regional aspects; land degradation –
an assessment of the interlinkages and integrated strategies for mitigation and adaptation; agriculture, foresty and other
landuse; food and agriculture; and food security and climate change.
4
Sustainable Land Management is defined in this report as “the stewardship and use of land resources, including soils,
water, animals and plants, to meet changing human needs, while simultaneously ensuring the long-term productive
potential of these resources and the maintenance of their environmental functions”.
5
Desertification is defined in this report as ‘land degradation in arid, semi-arid, and dry sub-humid areas resulting
from many factors, including climatic variations and human activities’.
6
Land degradation is defined in this report as ‘a negative trend in land condition, caused by direct or indirect human
induced processes, including anthropogenic climate change, expressed as long-term reduction and as loss of at least
one of the following: biological productivity, ecological integrity, or value to humans’.
7
Food security is defined in this report as ‘a situation that exists when all people, at all times, have physical, social,
and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an
active and healthy life’.
8
The assessment covers literature accepted for publication by 7th April 2019.
9
Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed
using five qualifiers: very low, low, medium, high and very high, and typeset in italics, for example, medium
1

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A. People, land and climate in a warming world
A 1.
Land provides the principal basis for human livelihoods and well-being
including the supply of food, freshwater and multiple other ecosystem services, as well as
biodiversity. Human use directly affects more than 70% (likely 69-76%) of the global, icefree land surface (high confidence). Land also plays an important role in the climate system.
{1.1, 1.2, 2.3, 2.4, Figure SPM.1}
A1.1.
People currently use one quarter to one third of land’s potential net primary
10
production for food, feed, fibre, timber and energy. Land provides the basis for many other
ecosystem functions and services 11, including cultural and regulating services, that are essential
for humanity (high confidence). In one economic approach, the world's terrestrial ecosystem
services have been valued on an annual basis to be approximately equivalent to the annual global
Gross Domestic Product 12 (medium confidence). {1.1, 1.2, 3.2, 4.1, 5.1, 5.5, Figure SPM.1}
A1.2.
Land is both a source and a sink of greenhouse gases (GHGs) and plays a key role
in the exchange of energy, water and aerosols between the land surface and atmosphere. Land
ecosystems and biodiversity are vulnerable to ongoing climate change and weather and climate
extremes, to different extents. Sustainable land management can contribute to reducing the
negative impacts of multiple stressors, including climate change, on ecosystems and societies (high
confidence). {1.1, 1.2, 3.2, 4.1, 5.1, 5.5, Figure SPM.1}
A1.3.
Data available since 1961 13 show that global population growth and changes in per
capita consumption of food, feed, fibre, timber and energy have caused unprecedented rates of
land and freshwater use (very high confidence) with agriculture currently accounting for ca. 70%
of global fresh-water use (medium confidence). Expansion of areas under agriculture and forestry,
including commercial production, and enhanced agriculture and forestry productivity have
supported consumption and food availability for a growing population (high confidence). With
confidence. The following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually
certain 99–100% probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%,
very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%, more likely than
not >50–100%, more unlikely than likely 0–<50%, extremely unlikely 0–5%) may also be used when appropriate.
Assessed likelihood is typeset in italics, for example, very likely. This is consistent with IPCC AR5.
10
Land’s potential net primary production (NPP) is defined in this report as the amount of carbon accumulated through
photosynthesis minus the amount lost by plant respiration over a specified time period that would prevail in the
absence of land use.
11
In its conceptual framework, IPBES uses “nature’s contribution to people” in which it includes ecosystem goods
and services.
12
i.e. estimated at $75 trillion for 2011, based on US dollars for 2007.
13
This statement is based on the most comprehensive data from national statistics available within FAOSTAT, which
starts in 1961. This does not imply that the changes started in 1961. Land use changes have been taking place from
well before the pre-industrial period to the present.
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large regional variation, these changes have contributed to increasing net GHG emissions (very
high confidence), loss of natural ecosystems (e.g. forests, savannahs, natural grasslands and
wetlands) and declining biodiversity (high confidence). {1.1, 1.3, 5.1, 5.5, Figure SPM.1}
A1.4.
Data available since 1961 shows the per capita supply of vegetable oils and meat
has more than doubled and the supply of food calories per capita has increased by about one third
(high confidence). Currently, 25-30% of total food produced is lost or wasted (medium confidence).
These factors are associated with additional GHG emissions (high confidence). Changes in
consumption patterns have contributed to about 2 billion adults now being overweight or obese
(high confidence). An estimated 821 million people are still undernourished (high confidence).
{1.1, 1.3, 5.1, 5.5, Figure SPM.1}
A1.5.
About a quarter of the Earth’s ice-free land area is subject to human-induced
degradation (medium confidence). Soil erosion from agricultural fields is estimated to be currently
10 to 20 times (no tillage) to more than 100 times (conventional tillage) higher than the soil
formation rate (medium confidence). Climate change exacerbates land degradation, particularly in
low-lying coastal areas, river deltas, drylands and in permafrost areas (high confidence). Over the
period 1961-2013, the annual area of drylands in drought has increased, on average by slightly
more than 1% per year, with large inter-annual variability. In 2015, about 500 (380-620) million
people lived within areas which experienced desertification between the 1980s and 2000s. The
highest numbers of people affected are in South and East Asia, the circum Sahara region including
North Africa, and the Middle East including the Arabian peninsula (low confidence). Other dryland
regions have also experienced desertification. People living in already degraded or desertified
areas are increasingly negatively affected by climate change (high confidence). {1.1, 1.2, 3.1, 3.2,
4.1, 4.2, 4.3, Figure SPM.1}

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Land use and observed climate change
A. Observed temperature change relative to 1850-1900
Since the pre-industrial period (1850-1900) the observed mean land surface air
temperature has risen considerably more than the global mean surface (land and ocean)
temperature (GMST).
CHANGE in TEMPERATURE rel. to 1850-1900 (°C)
2

CHANGE in emissions rel. to 1961
1 Net CO2 emissions from FOLU (Gt CO2/yr)
2 CH4 emissions from Agriculture (Gt CO2eq/yr)
3 N2O emissions from Agriculture (Gt CO2eq/yr)

Change in
surface air
temperature
over land (°C)

1.5

Gt CO2eq/yr

Change in global
(land-ocean)
mean surface
temperature
(GMST) (°C)

1
0.5

B. GHG emissions
An estimated 23% of total anthropogenic
greenhouse gas emissions (2007-2016)
derive from Agriculture, Forestry and
Other Land Use (AFOLU).

6
1

0

4

2

2

3

0

-0.5
1850

1880

1900

1920

1940

1960

1980

2000

1961

2018

1980

2000

2016

Global ice-free land surface 100% (130 Mkm2)
1% (1 - 1%)

Infrastructure 1%

37% (30 - 47%)

12% (12 - 14%)

22% (16 - 23%)

Plantation forests 2%

Intensive pasture 2%

Irrigated cropland 2%

C. Global land use
in circa 2015
The barchart depicts
shares of different uses
of the global, ice-free
land area. Bars are
Non-irrigated cropland 10%
ordered along a gradient
of decreasing land-use
intensity from left to right.
Used savannahs and

28% (24 - 31%)

0

Unforested ecosystems with
minimal human use 7%

10

Forests (intact or primary)
with minimal human use 9%

shrublands 16%

Forests managed for timber
and other uses 20%

D. Agricultural production
Land use change and rapid land use
intensification have supported the
increasing production of food, feed and
fibre. Since 1961, the total production of
food (cereal crops) has increased by 240%
(until 2017) because of land area
expansion and increasing yields. Fibre
production (cotton) increased by 162%
(until 2013).

Other land (barren, rock) 12%
30

Extensive pasture 19%

CHANGE in % rel. to 1961
1 Inorganic N fertiliser use
2 Cereal yields
3 Irrigation water volume
4 Total number of ruminant livestock
%
800

CHANGE in % rel. to 1961 and 1975

CHANGE in % rel. to 1961 and 1970

1 Population
2 Prevalence of overweight + obese
3 Total calories per capita

1 Population in areas experiencing desertification
2 Dryland areas in drought annually
3 Inland wetland extent

4 Prevalence of underweight

700
300
250
2

200
150

%

%

250

250

200

200

150
3

100

4

50

-50

-50
2000

2017

2

50
0

1980

1

100

0

1961

F. Desertification and
land degradation
Land-use change, land-use intensification
and climate change have contributed to
desertification and land degradation.

E. Food demand
Increases in production are linked to
consumption changes.
1

20

1961

3

1

150
100
50

2

0
4
1980

2000

2017

3

-50
1961

1980

2000

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2017

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Figure SPM.1: Land use and observed climate change
A representation of the land use and observed climate change covered in this assessment report. Panels A-F show the
status and trends in selected land use and climate variables that represent many of the core topics covered in this report.
The annual time series in B and D-F are based on the most comprehensive, available data from national statistics, in
most cases from FAOSTAT which starts in 1961. Y-axes in panels D-F are expressed relative to the starting year of
the time series (rebased to zero). Data sources and notes: A: The warming curves are averages of four datasets {2.1;
Figure 2.2; Table 2.1} B: N2O and CH4 from agriculture are from FAOSTAT; Net CO2 emissions from FOLU using
the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in
units of CO2-eq are based on AR5 100 year Global Warming Potential values without climate-carbon feedbacks
(N2O=265; CH4=28). {see Table SPM.1, 1.1, 2.3} C: Depicts shares of different uses of the global, ice-free land area
for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar
represents a broad land cover category; the numbers on top are the total % of the ice-free area covered, with uncertainty
ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area
of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area.
{1.2, Table 1.1, Figure 1.3} D: Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser
use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion
of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} E: Overweight population is defined
as having a body mass index (BMI) > 25 kg m-2; underweight is defined as BMI < 18.5 kg m-2. {5.1, 5.2} F: Dryland
areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980-2015) to identify areas
where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based
on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent
(including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland
area over time. {3.1, 4.2, 4.6}

A 2.
Since the pre-industrial period, the land surface air temperature has risen
nearly twice as much as the global average temperature (high confidence). Climate change,
including increases in frequency and intensity of extremes, has adversely impacted food
security and terrestrial ecosystems as well as contributed to desertification and land
degradation in many regions (high confidence). {2.2, 3.2, 4.2, 4.3, 4.4, 5.1, 5.2, Executive
Summary Chapter 7, 7.2}

A2.1.
Since the pre-industrial period (1850-1900) the observed mean land surface air
temperature has risen considerably more than the global mean surface (land and ocean)
temperature (GMST) (high confidence). From 1850-1900 to 2006-2015 mean land surface air
temperature has increased by 1.53°C (very likely range from 1.38°C to 1.68°C) while GMST
increased by 0.87°C (likely range from 0.75°C to 0.99°C). {2.2.1, Figure SPM.1}
A2.2.
Warming has resulted in an increased frequency, intensity and duration of heatrelated events, including heat waves 14 in most land regions (high confidence). Frequency and
intensity of droughts has increased in some regions (including the Mediterranean, west Asia, many
parts of South America, much of Africa, and north-eastern Asia) (medium confidence) and there
A heatwave is defined in this report as ‘a period of abnormally hot weather. Heatwaves and warm spells have various
and in some cases overlapping definitions’.

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has been an increase in the intensity of heavy precipitation events at a global scale (medium
confidence). {2.2.5, 4.2.3, 5.2}
A2.3.
Satellite observations 15 have shown vegetation greening 16 over the last three
decades in parts of Asia, Europe, South America, central North America, and southeast Australia.
Causes of greening include combinations of an extended growing season, nitrogen deposition, CO2
fertilisation 17, and land management (high confidence). Vegetation browning 18 has been observed
in some regions including northern Eurasia, parts of North America, Central Asia and the Congo
Basin, largely as a result of water stress (medium confidence). Globally, vegetation greening has
occurred over a larger area than vegetation browning (high confidence). {2.2.3, Box 2.3, 2.2.4,
3.2.1, 3.2.2, 4.3.1, 4.3.2, 4.6.2, 5.2.2}
A2.4.
The frequency and intensity of dust storms have increased over the last few decades
due to land use and land cover changes and climate-related factors in many dryland areas resulting
in increasing negative impacts on human health, in regions such as the Arabian Peninsula and
broader Middle East, Central Asia (high confidence) 19. {2.4.1, 3.4.2}
A2.5.
In some dryland areas, increased land surface air temperature and
evapotranspiration and decreased precipitation amount, in interaction with climate variability and
human activities, have contributed to desertification. These areas include Sub-Saharan Africa,
parts of East and Central Asia, and Australia. (medium confidence) {2.2, 3.2.2, 4.4.1}
A2.6.
Global warming has led to shifts of climate zones in many world regions, including
expansion of arid climate zones and contraction of polar climate zones (high confidence). As a
consequence, many plant and animal species have experienced changes in their ranges,
abundances, and shifts in their seasonal activities (high confidence). {2.2, 3.2.2, 4.4.1}
A2.7.
Climate change can exacerbate land degradation processes (high confidence)
including through increases in rainfall intensity, flooding, drought frequency and severity, heat
stress, dry spells, wind, sea-level rise and wave action, permafrost thaw with outcomes being
The interpretation of satellite observations can be affected by insufficient ground validation and sensor calibration.
In addition their spatial resolution can make it difficult to resolve small-scale changes.
16
Vegetation greening is defined in this report as an increase in photosynthetically active plant biomass which is
inferred from satellite observations.
17
CO2 fertilization is defined in this report as the enhancement of plant growth as a result of increased atmospheric
carbon dioxide (CO2) concentration. The magnitude of CO2 fertilization depends on nutrients and water availability.
18
Vegetation browning is defined in this report as a decrease in photosynthetically active plant biomass which is
inferred from satellite observations.
19
Evidence relative to such trends in dust storms and health impacts in other regions is limited in the literature assessed
in this report.
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modulated by land management. Ongoing coastal erosion is intensifying and impinging on more
regions with sea level rise adding to land use pressure in some regions (medium confidence).
{4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1, 7.2.1, 7.2.2}
A2.8.
Climate change has already affected food security due to warming, changing
precipitation patterns, and greater frequency of some extreme events (high confidence). In many
lower-latitude regions, yields of some crops (e.g., maize and wheat) have declined, while in many
higher-latitude regions, yields of some crops (e.g., maize, wheat and sugar beets) have increased
over recent decades (high confidence). Climate change has resulted in lower animal growth rates
and productivity in pastoral systems in Africa (high confidence). There is robust evidence that
agricultural pests and diseases have already responded to climate change resulting in both increases
and decreases of infestations (high confidence). Based on indigenous and local knowledge, climate
change is affecting food security in drylands, particularly those in Africa, and high mountain
regions of Asia and South America 20. {5.2.1, 5.2.2, 7.2.2}
Agriculture, Forestry and Other Land Use (AFOLU) activities accounted for
A 3.
around 13% of CO2, 44% of methane (CH4), and 82% of nitrous oxide (N2O) emissions from
human activities globally during 2007-2016, representing 23% (12.0 +/- 3.0 GtCO2e yr-1) of
total net anthropogenic emissions of GHGs 21 (medium confidence). The natural response of
land to human-induced environmental change caused a net sink of around 11.2 GtCO2 yr-1
during 2007-2016 (equivalent to 29% of total CO2 emissions) (medium confidence); the
persistence of the sink is uncertain due to climate change (high confidence). If emissions
associated with pre- and post-production activities in the global food system 22 are included,
the emissions are estimated to be 21-37% of total net anthropogenic GHG emissions (medium
confidence). {2.3, Table 2.2, 5.4}.
A3.1.
Land is simultaneously a source and a sink of CO2 due to both anthropogenic and
natural drivers, making it hard to separate anthropogenic from natural fluxes (very high
confidence). Global models estimate net CO2 emissions of 5.2 ± 2.6 GtCO2 yr-1 (likely range) from
land use and land-use change during 2007-16. These net emissions are mostly due to deforestation,
partly offset by afforestation/reforestation, and emissions and removals by other land use activities

The assessment covered literature whose methodologies included interviews and surveys with indigenous peoples
and local communities.
21
This assessment only includes CO2, CH4 and N2O.
22
Global food system in this report is defined as ‘all the elements (environment, people, inputs, processes,
infrastructures, institutions, etc.) and activities that relate to the production, processing, distribution, preparation and
consumption of food, and the output of these activities, including socioeconomic and environmental outcomes at the
global level’. These emissions data are not directly comparable to the national inventories prepared according to the
2006 IPCC Guidelines for National Greenhouse Gas.
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(very high confidence) (Table SPM.1) 23. There is no clear trend in annual emissions since 1990
(medium confidence) (Figure SPM.1). {1.1, 2.3, Table 2.2, Table 2.3}
The natural response of land to human-induced environmental changes such as
A3.2.
increasing atmospheric CO2 concentration, nitrogen deposition, and climate change, resulted in
global net removals of 11.2 +/– 2.6 Gt CO2 yr–1 (likely range) during 2007-2016 (Table SPM.1).
The sum of the net removals due to this response and the AFOLU net emissions gives a total net
land-atmosphere flux that removed 6.0+/-2.6 GtCO2 yr-1 during 2007-2016 (likely range). Future
net increases in CO2 emissions from vegetation and soils due to climate change are projected to
counteract increased removals due to CO2 fertilisation and longer growing seasons (high
confidence). The balance between these processes is a key source of uncertainty for determining
the future of the land carbon sink. Projected thawing of permafrost is expected to increase the loss
of soil carbon (high confidence). During the 21st century, vegetation growth in those areas may
compensate in part for this loss (low confidence). {Box 2.3, 2.3.1, 2.5.3, 2.7; Table 2.3}
Global models and national GHG inventories use different methods to estimate
A3.3.
anthropogenic CO2 emissions and removals for the land sector. Both produce estimates that are in
close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ
for managed forest. Global models consider as managed forest those lands that were subject to
harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed
forest more broadly. On this larger area, inventories can also consider the natural response of land
to human-induced environmental changes as anthropogenic, while the global model approach
{Table SPM.1} treats this response as part of the non-anthropogenic sink. For illustration, from
2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1±1.0 GtCO2yr1
, while the mean of two global bookkeeping models is 5.1±2.6 GtCO2yr-1 (likely range).
Consideration of differences in methods can enhance understanding of land sector net emission
estimates and their applications.

The net anthropogenic flux of CO2 from “bookkeeping” or “carbon accounting” models is composed of two
opposing gross fluxes: gross emissions (about 20 GtCO2 yr-1) are from deforestation, cultivation of soils, and
oxidation of wood products; gross removals (about 14 GtCO2 yr-1) are largely from forest growth following wood
harvest and agricultural abandonment (medium confidence).
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Table SPM1. Net anthropogenic emissions due to Agriculture, Forestry, and other Land Use (AFOLU) and non-AFOLU (Panel 1) and global
food systems (average for 2007-2016)1 (Panel 2). Positive value represents emissions; negative value represents removals.
Direct Anthropogenic
Net anthropogenic emissions due to
Agriculture, Forestry, and Other Land
Use (AFOLU)
Panel 1: Contribution of AFOLU
FOLU
A
CO22
CH43,8
N2O3,8

Agriculture
B

Total
C=B+A

AFOLU as a
% of total net
anthropogenic
emissions, by
gas

Natural response
of land to humaninduced
environmental
change7

Net land –
atmosphere
flux from all
lands

D

E=C+D

F = (C/E)*100

G

A+G

39.1 ± 3.2

~13%

-11.2 ± 2.6

-6.0 ± 2.0

Gt CO2 y-1

5.2 ± 2.6

--11

5.2 ± 2.6

Mt CH4 y-1

19 ± 6

142 ± 43

162 ± 48.6

33.9 ± 1.8
201 ± 100

Gt CO2e y-1

0.5 ± 0.2

4.0 ± 1.2

4.5 ± 1.4

5.6 ± 2.8

10.1 ± 3.1

Mt N2O y-1

0.3 ± 0.1

8 ±2

8.3 ± 2.5

2.0 ± 1.0

10.4 ± 2.7

0.09 ± 0.03
5.8 ± 2.6

2.2 ± 0.7
6.2 ± 1.4

2.3 ± 0.7
12.0 ± 3.0

0.5 ± 0.3

2.8 ± 0.7

~82%

40.0 ± 3.4

52.0 ± 4.5

~23%

Non-AFOLU5 other
sectors pre- to postproduction

Total global food
system emissions

Gt CO2e y-1
Total (GHG) Gt CO2e y-1

Panel 2: Contribution of global food system
Land-use
change
CO24 Landuse change
CH43,8,9
Agriculture
N2O3,8,9
Agriculture
CO2 other
sectors
Total
(CO2e)10

Non-AFOLU
anthropogenic GHG
emissions6

Total net
anthropogenic
emissions
(AFOLU + nonAFOLU) by gas

Gt CO2 y-1

Agriculture

~44%

4.9 ± 2.5

Gt CO2e y-1

4.0 ± 1.2

Gt CO2e y-1

2.2 ± 0.7

Gt CO2 y-1
Gt CO2e y-1

363 ± 111

2.4 – 4.8
4.9 ± 2.5

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6.2 ± 1.4

2.4 – 4.8

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Data sources and notes:
1
Estimates are only given until 2016 as this is the latest date when data are available for all gases.
2
Net anthropogenic flux of CO2 due to land cover change such as deforestation and afforestation, and land
management including wood harvest and regrowth, as well as peatland burning, based on two bookkeeping models as
used in the Global Carbon Budget and for AR5. Agricultural soil carbon stock change under the same land use is not
considered in these models. {2.3.1.2.1, Table 2.2, Box 2.2}
3
Estimates show the mean and assessed uncertainty of two databases, FAOSTAT and USEPA 2012 {2.3; Table 2.2}
4
Based on FAOSTAT. Categories included in this value are “net forest conversion” (net deforestation), drainage of
organic soils (cropland and grassland), biomass burning (humid tropical forests, other forests, organic soils). It
excludes “forest land” (forest management plus net forest expansion), which is primarily a sink due to afforestation.
Note: total FOLU emissions from FAOSTAT are 2.8 (±1.4) Gt CO2 yr-1 for the period 2007-2016. {Table 2.2, Table
5.4}
5
CO2 emissions induced by activities not included in the AFOLU sector, mainly from energy (e.g. grain drying),
transport (e.g. international trade), and industry (e.g. synthesis of inorganic fertilizers) part of food systems, including
agricultural production activities (e.g. heating in greenhouses), pre-production (e.g. manufacturing of farm inputs)
and post-production (e.g. agri-food processing) activities. This estimate is land based and hence excludes emissions
from fisheries. It includes emissions from fibre and other non-food agricultural products since these are not separated
from food use in data bases. The CO2 emissions related to food system in other sectors than AFOLU are 6-13% of
total anthropogenic CO2 emissions. These emissions are typically low in smallholder subsistence farming. When
added to AFOLU emissions, the estimated share of food systems in global anthropogenic emissions is 21-37%. {5.4.5,
Table 5.4}
6
Total non-AFOLU emissions were calculated as the sum of total CO2e emissions values for energy, industrial
sources, waste and other emissions with data from the Global Carbon Project for CO2, including international aviation
and shipping and from the PRIMAP database for CH4 and N2O averaged over 2007-2014 only as that was the period
for which data were available {2.3; Table 2.2}.
7
The natural response of land to human-induced environmental changes is the response of vegetation and soils to
environmental changes such as increasing atmospheric CO2 concentration, nitrogen deposition, and climate change.
The estimate shown represents the average from Dynamic Global Vegetation Models {2.3.1.2.4, Box 2.2, Table 2.3}
8
All values expressed in units of CO2e are based on AR5 100 year Global Warming Potential (GWP) values without
climate-carbon feedbacks (N2O = 265; CH4 = 28). Note that the GWP has been used across fossil fuel and biogenic
sources of methane. If a higher GWP for fossil fuel CH4 (30 per AR5), then total anthropogenic CH4 emissions
expressed in CO2e would be 2% greater.
9
This estimate is land based and hence excludes emissions from fisheries and emissions from aquaculture (except
emissions from feed produced on land and used in aquaculture), and also includes non-food use (e.g. fibre and
bioenergy) since these are not separated from food use in databases. It excludes non-CO2 emissions associated with
land use change (FOLU category) since these are from fires in forests and peatlands.
10
Emissions associated with food loss and waste are included implicitly, since emissions from food system are related
to food produced, including food consumed for nutrition and to food loss and waste. The latter is estimated at 8-10%
of total anthropogenic emissions in CO2e. {5.5.2.5}
11
No global data are available for agricultural CO2 emissions

A3.4.
Global AFOLU emissions of methane in the period 2007-2016 were 162 ± 49 Mt
CH4 yr-1 (4.5 ± 1.4 GtCO2eq yr-1) (medium confidence). The globally averaged atmospheric
concentration of methane shows a steady increase between the mid-1980s and early 1990s, slower
growth thereafter until 1999, a period of no growth between 1999-2006, followed by a resumption
of growth in 2007 (high confidence). Biogenic sources make up a larger proportion of emissions
than they did before 2000 (high confidence). Ruminants and the expansion of rice cultivation are
important contributors to the rising concentration (high confidence). {Table 2.2, 2.3.2, 5.4.2, 5.4.3,
Figure SPM.1}.

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A3.5.
Anthropogenic AFOLU N2O emissions are rising, and were 8.3 ± 2.5 MtN2O yr-1
(2.3 ± 0.7 GtCO2eq yr-1) during the period 2007-2016. Anthropogenic N2O emissions (Figure
SPM.1, Table SPM.1) from soils are primarily due to nitrogen application including inefficiencies
(over-application or poorly synchronised with crop demand timings) (high confidence). Cropland
soils emitted around 3 Mt N2O yr-1 (around 795 MtCO2-eq yr-1) during the period 2007-2016
(medium confidence). There has been a major growth in emissions from managed pastures due to
increased manure deposition (medium confidence). Livestock on managed pastures and rangelands
accounted for more than one half of total anthropogenic N2O emissions from agriculture in 2014
(medium confidence). {Table 2.1, 2.3.3, 5.4.2, 5.4.3}
A3.6.
Total net GHG emissions from agriculture, forestry, and other land use (AFOLU)
emissions represent 12.0 +/- 3.0 GtCO2eq yr-1 during 2007-2016. This represents 23% of total net
anthropogenic emissions 24 (Table SPM.1). Other approaches, such as global food system, include
agricultural emissions and land use change (i.e., deforestation and peatland degradation), as well
as outside farm gate emissions from energy, transport and industry sectors for food production.
Emissions within farm gate and from agricultural land expansion contributing to the global food
system represent 16-27% of total anthropogenic emissions (medium confidence). Emissions
outside the farm gate represent 5-10% of total anthropogenic emissions (medium confidence).
Given the diversity of food systems, there are large regional differences in the contributions from
different components of the food system (very high confidence). Emissions from agricultural
production are projected to increase (high confidence), driven by population and income growth
and changes in consumption patterns (medium confidence). {5.5, Table 5.4}
A 4.
Changes in land conditions 25, either from land-use or climate change, affect
global and regional climate (high confidence). At the regional scale, changing land conditions
can reduce or accentuate warming and affect the intensity, frequency and duration of
extreme events. The magnitude and direction of these changes vary with location and season
(high confidence). {Executive Summary Chapter 2, 2.3, 2.4, 2.5, 3.3}
A4.1.
Since the pre-industrial period, changes in land cover due to human activities have
led to both a net release of CO2 contributing to global warming (high confidence), and an increase
in global land albedo 26 causing surface cooling (medium confidence). Over the historical period,
the resulting net effect on globally averaged surface temperature is estimated to be small (medium
confidence). {2.4, 2.6.1, 2.6.2}

This assessment only includes CO2, CH4 and N2O.
Land conditions encompass changes in land cover (e.g. deforestation, afforestation, urbanisation), in land use (e.g.
irrigation), and in land state (e.g. degree of wetness, degree of greening, amount of snow, amount of permafrost)
26
Land with high albedo reflects more incoming solar radiation than land with low albedo.
24
25

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A4.2.
The likelihood, intensity and duration of many extreme events can be significantly
modified by changes in land conditions, including heat related events such as heat waves (high
confidence) and heavy precipitation events (medium confidence). Changes in land conditions can
affect temperature and rainfall in regions as far as hundreds of kilometres away (high confidence).
{2.5.1, 2.5.2, 2.5.4, 3.3; Cross-Chapter Box 4 in Chapter 2}
A4.3. Climate change is projected to alter land conditions with feedbacks on regional climate. In
those boreal regions where the treeline migrates northward and/or the growing season lengthens,
winter warming will be enhanced due to decreased snow cover and albedo while warming will be
reduced during the growing season because of increased evapotranspiration (high confidence). In
those tropical areas where increased rainfall is projected, increased vegetation growth will reduce
regional warming (medium confidence). Drier soil conditions resulting from climate change can
increase the severity of heat waves, while wetter soil conditions have the opposite effect (high
confidence). {2.5.2, 2.5.3}
Desertification amplifies global warming through the release of CO2 linked with
A4.4.
the decrease in vegetation cover (high confidence). This decrease in vegetation cover tends to
increase local albedo, leading to surface cooling (high confidence). {3.3}
A4.5.
Changes in forest cover for example from afforestation, reforestation and
deforestation, directly affect regional surface temperature through exchanges of water and
energy 27 (high confidence). Where forest cover increases in tropical regions cooling results from
enhanced evapotranspiration (high confidence). Increased evapotranspiration can result in cooler
days during the growing season (high confidence) and can reduce the amplitude of heat related
events (medium confidence). In regions with seasonal snow cover, such as boreal and some
temperate, increased tree and shrub cover also has a wintertime warming influence due to reduced
surface albedo 28 (high confidence). {2.3, 2.4.3, 2.5.1, 2.5.2, 2.5.4}
A4.6.
Both global warming and urbanisation can enhance warming in cities and their
surroundings (heat island effect), especially during heat related events, including heat waves (high
confidence). Night-time temperatures are more affected by this effect than daytime temperatures
(high confidence). Increased urbanisation can also intensify extreme rainfall events over the city
or downwind of urban areas (medium confidence). {2.5.1, 2.5.2, 2.5.3, 4.9.1, Cross-Chapter Box
4 in Chapter 2}

The literature indicates that forest cover changes can also affect climate through changes in emissions of reactive
gases and aerosols {2.4, 2.5}.
28
Emerging literature shows that boreal forest-related aerosols may counteract at least partly the warming effect of
surface albedo {2.4.3}.
27

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A. Risks to humans and ecosystems from changes in land-based processes as a result
of climate change

GMST change
relative to levels in pre-industrial time (°C)

Increases in global mean surface temperature (GMST), relative to pre-industrial levels, affect processes involved in desertification (water
scarcity), land degradation (soil erosion, vegetation loss, wildfire, permafrost thaw) and food security (crop yield and food supply
instabilities). Changes in these processes drive risks to food systems, livelihoods, infrastructure, the value of land, and human and
ecosystem health. Changes in one process (e.g. wildfire or water scarcity) may result in compound risks. Risks are location-specific and
differ by region.
5°

L

4°
3°

M

2°

M

M

M
M

L
M

M
M

1.5°

1°

M

H
Dryland
water scarcity

Soil
erosion

H

H

Vegetation
loss

Wildfire
damage

M

M

H

M
H

H

H
Permafrost
degradation

Tropical crop
yield decline

2006-2015

Food
supply instabilities

Systems at risk:
Food
Livelihoods
Value of land
Human health
Ecosystem health
Infrastructure

GMST change
relative to levels in pre-industrial time (°C)

Indicative example of transitions

5°

Over 100M
people
additionally
exposed

Over 50%
increase in
area burned in
Mediterranean
region

4°
3°

Indicative example of transitions

5°

Sustained food
supply
disruptions
globally

4°
Infrequent
price spikes
affect
individual
countries

3°

M

2°

2°
M

Increase in fire
weather season

1°

M
M
H

1°

H

Periodic food
shocks across
regions

Wildfire damage

Food supply instabilities

B. Different socioeconomic pathways affect levels of climate related risks
Desertification

GMST change
relative to levels in pre-industrial time (°C)

(water scarcity in drylands)

Land degradation

(habitat degr., wildfire, floods)

Food insecurity
(availability, access)

3°

M
M

L

2°

M

M
M

1.5°

M

M

1°

H

SSP1

H

SSP3

H

SSP1

H

SSP3

M

SSP1

M

SSP3

2006-2015

Socio-economic choices can reduce or
exacerbate climate related risks as well as
influence the rate of temperature increase.
The SSP1 pathway illustrates a world with
low population growth, high income and
reduced inequalities, food produced in low
GHG emission systems, effective land use
regulation and high adaptive capacity. The
SSP3 pathway has the opposite trends.
Risks are lower in SSP1 compared with
SSP3 given the same level of GMST
increase.

Legend: Level of impact/risk
Very high

High
Risks
Moderate
Impacts

Undetectable

Purple: Very high probability of severe impacts/ risks
and the presence of significant irreversibility or the
persistence of climate-related hazards, combined with
limited ability to adapt due to the nature of the hazard
or impacts/risks.
Red: Significant and widespread impacts/risks.
Yellow: Impacts/risks are detectable and attributable
to climate change with at least medium confidence.
White: Impacts/risks are undetectable.

Legend: Confidence
level for
transition
H High
M Medium
L Low
H

Example

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Figure SPM. 2 Risks to land-related human systems and ecosystems from global climate
change, socio-economic development and mitigation choices in terrestrial ecosystems.
As in previous IPCC reports the literature was used to make expert judgements to assess the levels of global warming
at which levels of risk are undetectable, moderate, high or very high, as described further in Chapter 7 and other parts
of the underlying report. The figure indicates assessed risks at approximate warming levels which may be influenced
by a variety of factors, including adaptation responses. The assessment considers adaptive capacity consistent with
the SSP pathways as described below. Panel A: Risks to selected elements of the land system as a function of global
mean surface temperature {2.1; Box 2.1; 3.5; 3.7.1.1; 4.4.1.1; 4.4.1.2; 4.4.1.3; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 7.2;7.3, Table
SM7.1}. Links to broader systems are illustrative and not intended to be comprehensive. Risk levels are estimated
assuming medium exposure and vulnerability driven by moderate trends in socioeconomic conditions broadly
consistent with an SSP2 pathway. {Table SM7.4}. Panel B: Risks associated with desertification, land degradation
and food security due to climate change and patterns of socio-economic development. Increasing risks associated with
desertification include population exposed and vulnerable to water scarcity in drylands. Risks related to land
degradation include increased habitat degradation, population exposed to wildfire and floods and costs of floods. Risks
to food security include availability and access to food, including population at risk of hunger, food price increases
and increases in disability adjusted life years attributable due to childhood underweight. Risks are assessed for two
contrasted socio-economic pathways (SSP1 and SSP3 {SPM Box 1}) excluding the effects of targeted mitigation
policies {3.5; 4.2.1.2; 5.2.2; 5.2.3; 5.2.4; 5.2.5; 6.1.4; 7.2, Table SM7.5}. Risks are not indicated beyond 3°C because
SSP1 does not exceed this level of temperature change. All panels: As part of the assessment, literature was compiled
and data extracted into a summary table. A formal expert elicitation protocol (based on modified-Delphi technique
and the Sheffield Elicitation Framework), was followed to identify risk transition thresholds. This included a multiround elicitation process with two rounds of independent anonymous threshold judgement, and a final consensus
discussion. Further information on methods and underlying literature can be found in Chapter 7 Supplementary
Material.

******************************************************************************
BOX SPM.1: Shared Socioeconomic Pathways (SSPs)
In this report the implications of future socio-economic development on climate change mitigation,
adaptation and land-use are explored using shared socio-economic pathways (SSPs). The SSPs
span a range of challenges to climate change mitigation and adaptation.
 SSP1 includes a peak and decline in population (~7 billion in 2100), high income and
reduced inequalities, effective land-use regulation, less resource intensive consumption,
including food produced in low-GHG emission systems and lower food waste, free trade
and environmentally-friendly technologies and lifestyles. Relative to other pathways, SSP1
has low challenges to mitigation and low challenges to adaptation (i.e., high adaptive
capacity).
 SSP2 includes medium population growth (~9 billion in 2100), medium income;
technological progress, production and consumption patterns are a continuation of past
trends, and only gradual reduction in inequality occurs. Relative to other pathways, SSP2
has medium challenges to mitigation and medium challenges to adaptation (i.e., medium
adaptive capacity).

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 SSP3 includes high population (~13 billion in 2100), low income and continued
inequalities, material-intensive consumption and production, barriers to trade, and slow
rates of technological change. Relative to other pathways, SSP3 has high challenges to
mitigation and high challenges to adaptation (i.e., low adaptive capacity).
 SSP4 includes medium population growth (~9 billion in 2100), medium income, but
significant inequality within and across regions. Relative to other pathways, SSP4 has low
challenges to mitigation, but high challenges to adaptation (i.e., low adaptive capacity).
 SSP5 includes a peak and decline in population (~7 billion in 2100), high income, reduced
inequalities, and free trade. This pathway includes resource-intensive production,
consumption and lifestyles. Relative to other pathways, SSP5 has high challenges to
mitigation, but low challenges to adaptation (i.e., high adaptive capacity).
The SSPs can be combined with Representative Concentration Pathways (RCPs) which imply
different levels of mitigation, with implications for adaptation. Therefore, SSPs can be consistent
with different levels of global mean surface temperature rise as projected by different SSP-RCP
combinations. However, some SSP-RCP combinations are not possible; for instance RCP2.6 and
lower levels of future global mean surface temperature rise (e.g., 1.5ºC) are not possible in SSP3
in modelled pathways. {1.2.2, Cross-Chapter Box 1 in Chapter 1, 6.1.4, Cross-Chapter Box 9 in
Chapter 6}
******************************************************************************
Climate change creates additional stresses on land, exacerbating existing risks
A 5.
to livelihoods, biodiversity, human and ecosystem health, infrastructure, and food systems
(high confidence). Increasing impacts on land are projected under all future GHG emission
scenarios (high confidence). Some regions will face higher risks, while some regions will face
risks previously not anticipated (high confidence). Cascading risks with impacts on multiple
systems and sectors also vary across regions (high confidence). {2.2, 3.5, 4.2, 4.4, 4.7, 5.1, 5.2,
5.8, 6.1, 7.2, 7.3, Cross-Chapter Box 9 in Chapter 6, Figure SPM.2}
With increasing warming, the frequency, intensity and duration of heat related
A5.1.
events including heat waves are projected to continue to increase through the 21st century (high
confidence). The frequency and intensity of droughts are projected to increase particularly in the
Mediterranean region and southern Africa (medium confidence). The frequency and intensity of
extreme rainfall events are projected to increase in many regions (high confidence). {2.2.5, 3.5.1,
4.2.3, 5.2}

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A5.2.
With increasing warming, climate zones are projected to further shift poleward in
the middle and high latitudes (high confidence). In high-latitude regions, warming is projected to
increase disturbance in boreal forests, including drought, wildfire, and pest outbreaks (high
confidence). In tropical regions, under medium and high GHG emissions scenarios, warming is
projected to result in the emergence of unprecedented 29 climatic conditions by the mid to late 21st
century (medium confidence). {2.2.4, 2.2.5, 2.5.3, 4.3.2}
Current levels of global warming are associated with moderate risks from increased
A5.3.
dryland water scarcity, soil erosion, vegetation loss, wildfire damage, permafrost thawing, coastal
degradation and tropical crop yield decline (high confidence). Risks, including cascading risks, are
projected to become increasingly severe with increasing temperatures. At around 1.5°C of global
warming the risks from dryland water scarcity, wildfire damage, permafrost degradation and food
supply instabilities are projected to be high (medium confidence). At around 2°C of global warming
the risk from permafrost degradation and food supply instabilities are projected to be very high
(medium confidence). Additionally, at around 3°C of global warming risk from vegetation loss,
wildfire damage, and dryland water scarcity are also projected to be very high (medium
confidence). Risks from droughts, water stress, heat related events such as heatwaves and habitat
degradation simultaneously increase between 1.5°C and 3°C warming (low confidence). {Figure
SPM.2, 7.2.2, Cross-Chapter Box 9 in Chapter 6, Chapter 7 supplementary material}
The stability of food supply 30 is projected to decrease as the magnitude and
A5.4.
frequency of extreme weather events that disrupt food chains increases (high confidence).
Increased atmospheric CO2 levels can also lower the nutritional quality of crops (high confidence).
In SSP2, global crop and economic models project a median increase of 7.6% (range of 1 to 23%)
in cereal prices in 2050 due to climate change (RCP6.0), leading to higher food prices and
increased risk of food insecurity and hunger (medium confidence). The most vulnerable people
will be more severely affected (high confidence). {5.2.3, 5.2.4, 5.2.5, 5.8.1, 7.2.2.2, 7.3.1}
A5.5.
In drylands, climate change and desertification are projected to cause reductions in
crop and livestock productivity (high confidence), modify the plant species mix and reduce
biodiversity (medium confidence). Under SSP2, the dryland population vulnerable to water stress,
drought intensity and habitat degradation is projected to reach 178 million people by 2050 at 1.5°C
warming, increasing to 220 million people at 2°C warming, and 277 million people at 3°C warming
(low confidence). {3.5.1, 3.5.2, 3.7.3}

29
Unprecedented climatic conditions are defined in this report as not having occurred anywhere during the 20th
century. They are characterized by high temperature with strong seasonality and shifts in precipitation. In the literature
assessed, the effect of climatic variables other than temperature and precipitation were not considered.
30
The supply of food is defined in this report as encompassing availability and access (including price). Food supply
instability refers to variability that influences food security through reducing access.

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Asia and Africa 31 are projected to have the highest number of people vulnerable to
A5.6.
increased desertification. North America, South America, Mediterranean, southern Africa and
central Asia may be increasingly affected by wildfire. The tropics and subtropics are projected to
be most vulnerable to crop yield decline. Land degradation resulting from the combination of sea
level rise and more intense cyclones is projected to jeopardise lives and livelihoods in cyclone
prone areas (very high confidence). Within populations, women, the very young, elderly and poor
are most at risk (high confidence). {3.5.1, 3.5.2, 4.4, Table 4.1, 5.2.2, 7.2.2, Cross-Chapter Box 3
in Chapter 2}
A5.7.
Changes in climate can amplify environmentally induced migration both within
countries and across borders (medium confidence), reflecting multiple drivers of mobility and
available adaptation measures (high confidence). Extreme weather and climate or slow-onset
events may lead to increased displacement, disrupted food chains, threatened livelihoods (high
confidence), and contribute to exacerbated stresses for conflict (medium confidence). {3.4.2, 4.7.3,
5.2.3, 5.2.4, 5.2.5, 5.8.2, 7.2.2, 7.3.1}
A5.8
Unsustainable land management has led to negative economic impacts (high
confidence). Climate change is projected to exacerbate these negative economic impacts (high
confidence). {4.3.1, 4.4.1, 4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8, 5.2, 5.8.1, 7.3.4, 7.6.1, CrossChapter Box 10 in Chapter 7}
A6.
The level of risk posed by climate change depends both on the level of warming
and on how population, consumption, production, technological development, and land
management patterns evolve (high confidence). Pathways with higher demand for food, feed,
and water, more resource-intensive consumption and production, and more limited
technological improvements in agriculture yields result in higher risks from water scarcity
in drylands, land degradation, and food insecurity (high confidence). {5.1.4, 5.2.3, 6.1.4, 7.2,
Cross-Chapter Box 9 in Chapter 6, Figure SPM.2b}
A6.1.
Projected increases in population and income, combined with changes in
consumption patterns, result in increased demand for food, feed, and water in 2050 in all SSPs
(high confidence). These changes, combined with land management practices, have implications
for land-use change, food insecurity, water scarcity, terrestrial GHG emissions, carbon
sequestration potential, and biodiversity (high confidence). Development pathways in which
incomes increase and the demand for land conversion is reduced, either through reduced
West Africa has a high number of people vulnerable to increased desertification and yield decline. North Africa is
vulnerable to water scarcity.
31

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agricultural demand or improved productivity, can lead to reductions in food insecurity (high
confidence). All assessed future socio-economic pathways result in increases in water demand and
water scarcity (high confidence). SSPs with greater cropland expansion result in larger declines in
biodiversity (high confidence). {6.1.4}
Risks related to water scarcity in drylands are lower in pathways with low
A6.2.
population growth, less increase in water demand, and high adaptive capacity, as in Shared Socioeconomic Pathway 1 (SSP1) (See BOX SPM.1). In these scenarios the risk from water scarcity in
drylands is moderate even at global warming of 3°C (low confidence). By contrast, risks related to
water scarcity in drylands are greater for pathways with high population growth, high vulnerability,
higher water demand, and low adaptive capacity, such as SSP3. In SSP3 the transition from
moderate to high risk occurs between 1.2°C and 1.5°C (medium confidence). {7.2, Figure SPM.2b,
BOX SPM.1}
Risks related to climate change driven land degradation are higher in pathways with
A6.3.
a higher population, increased land-use change, low adaptive capacity and other barriers to
adaptation (e.g., SSP3). These scenarios result in more people exposed to ecosystem degradation,
fire, and coastal flooding (medium confidence). For land degradation, the projected transition from
moderate to high risk occurs for global warming between 1.8°C and 2.8°C in SSP1 (low
confidence) and between 1.4°C and 2°C in SSP3 (medium confidence). The projected transition
from high to very high risk occurs between 2.2°C and 2.8°C for SSP3 (medium confidence). {4.4,
7.2, Figure SPM.2b}
Risks related to food security are greater in pathways with lower income, increased
A6.4.
food demand, increased food prices resulting from competition for land, more limited trade, and
other challenges to adaptation (e.g., SSP3) (high confidence). For food security, the transition from
moderate to high risk occurs for global warming between 2.5°C and 3.5°C in SSP1 (medium
confidence) and between 1.3°C and 1.7°C in SSP3 (medium confidence). The transition from high
to very high risk occurs between 2°C and 2.7°C for SSP3 (medium confidence). {7.2, Figure
SPM.2b}
A6.5 Urban expansion is projected to lead to conversion of cropland leading to losses in food
production (high confidence). This can result in additional risks to the food system. Strategies for
reducing these impacts can include urban and peri-urban food production and management of
urban expansion, as well as urban green infrastructure that can reduce climate risks in cities 32 (high
confidence). {4.9.1, 5.5, 5.6, 6.3, 6.4, 7.5.6} (Figure SPM3)
The land systems considered in this report do not include urban ecosystem dynamics in detail. Urban areas, urban
expansion, and other urban processes and their relation to land-related processes are extensive, dynamic, and complex.
32

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B. Adaptation and mitigation response options
B 1.
Many land-related responses that contribute to climate change adaptation and
mitigation can also combat desertification and land degradation and enhance food security.
The potential for land-related responses and the relative emphasis on adaptation and
mitigation is context specific, including the adaptive capacities of communities and regions.
While land-related response options can make important contributions to adaptation and
mitigation, there are some barriers to adaptation and limits to their contribution to global
mitigation. (very high confidence) {2.6, 4.8, 5.6, 6.1, 6.3, 6.4, Figure SPM.3}

B1.1.
Some land-related actions are already being taken that contribute to climate change
adaptation, mitigation and sustainable development. The response options were assessed across
adaptation, mitigation, combating desertification and land degradation, food security and
sustainable development, and a select set of options deliver across all of these challenges. These
options include, but are not limited to, sustainable food production, improved and sustainable
forest management, soil organic carbon management, ecosystem conservation and land
restoration, reduced deforestation and degradation, and reduced food loss and waste (high
confidence). These response options require integration of biophysical, socioeconomic and other
enabling factors. {6.3, 6.4.5; Cross-Chapter Box 10 in Chapter 7}
B1.2.
While some response options have immediate impact, others take decades to deliver
measurable results. Examples of response options with immediate impacts include the
conservation of high-carbon ecosystems such as peatlands, wetlands, rangelands, mangroves and
forests. Examples that provide multiple ecosystem services and functions, but take more time to
deliver, include afforestation and reforestation as well as the restoration of high-carbon
ecosystems, agroforestry, and the reclamation of degraded soils (high confidence). {6.4.5; CrossChapter Box 10 in Chapter 7}
B1.3.
The successful implementation of response options depends on consideration of
local environmental and socio-economic conditions. Some options such as soil carbon
management are potentially applicable across a broad range of land use types, whereas the efficacy
of land management practices relating to organic soils, peatlands and wetlands, and those linked
to freshwater resources, depends on specific agro-ecological conditions (high confidence). Given
Several issues addressed in this report such as population, growth, incomes, food production and consumption, food
security, and diets have close relationships with these urban processes. Urban areas are also the setting of many
processes related to land-use change dynamics, including loss of ecosystem functions and services, that can lead to
increased disaster risk. Some specific urban issues are assessed in this report.
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the site-specific nature of climate change impacts on food system components and wide variations
in agroecosystems, adaptation and mitigation options and their barriers are linked to environmental
and cultural context at regional and local levels (high confidence). Achieving land degradation
neutrality depends on the integration of multiple responses across local, regional and national
scales, multiple sectors including agriculture, pasture, forest and water (high confidence). {4.8,
6.2, 6.3, 6.4.4}
Land based options that deliver carbon sequestration in soil or vegetation, such as
B1.4.
afforestation, reforestation, agroforestry, soil carbon management on mineral soils, or carbon
storage in harvested wood products do not continue to sequester carbon indefinitely (high
confidence). Peatlands, however, can continue to sequester carbon for centuries (high confidence).
When vegetation matures or when vegetation and soil carbon reservoirs reach saturation, the
annual removal of CO2 from the atmosphere declines towards zero, while carbon stocks can be
maintained (high confidence). However, accumulated carbon in vegetation and soils is at risk from
future loss (or sink reversal) triggered by disturbances such as flood, drought, fire, or pest
outbreaks, or future poor management (high confidence). {6.4.1}
B 2.
Most of the response options assessed contribute positively to sustainable
development and other societal goals (high confidence). Many response options can be
applied without competing for land and have the potential to provide multiple co-benefits
(high confidence). A further set of response options has the potential to reduce demand for
land, thereby enhancing the potential for other response options to deliver across each of
climate change adaptation and mitigation, combating desertification and land degradation,
and enhancing food security (high confidence). {4.8, 6.2, 6.3.6, 6.4.3; Figure SPM.3}
A number of land management options, such as improved management of cropland
B2.1.
and grazing lands, improved and sustainable forest management, and increased soil organic carbon
content, do not require land use change and do not create demand for more land conversion (high
confidence). Further, a number of response options such as increased food productivity, dietary
choices and food losses and waste reduction, can reduce demand for land conversion, thereby
potentially freeing land and creating opportunities for enhanced implementation of other response
options (high confidence). Response options that reduce competition for land are possible and are
applicable at different scales, from farm to regional (high confidence). {4.8, 6.3.6, 6.4; Figure
SPM.3}
B2.2.
A wide range of adaptation and mitigation responses, e.g. preserving and restoring
natural ecosystems such as peatland, coastal lands and forests, biodiversity conservation, reducing
competition for land, fire management, soil management, and most risk management options (e.g.
use of local seeds, disaster risk management, risk sharing instruments) have the potential to make
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positive contributions to sustainable development, enhancement of ecosystem functions and
services and other societal goals (medium confidence). Ecosystem-based adaptation can, in some
contexts, promote nature conservation while alleviating poverty and even provide co-benefits by
removing greenhouse gases and protecting livelihoods (e.g. mangroves) (medium confidence).
{6.4.3, 7.4.6.2}
Most of the land management-based response options that do not increase
B2.3.
competition for land, and almost all options based on value chain management (e.g. dietary
choices, reduced post-harvest losses, reduced food waste) and risk management, can contribute to
eradicating poverty and eliminating hunger while promoting good health and wellbeing, clean
water and sanitation, climate action, and life on land (medium confidence). {6.4.3}
Although most response options can be applied without competing for
B 3.
available land, some can increase demand for land conversion (high confidence). At the
deployment scale of several GtCO2yr-1, this increased demand for land conversion could lead
to adverse side effects for adaptation, desertification, land degradation and food security
(high confidence). If applied on a limited share of total land and integrated into sustainably
managed landscapes, there will be fewer adverse side-effects and some positive co-benefits
can be realised (high confidence). {4.5, 6.2, 6.4; Cross-Chapter Box 7 in Chapter 6; Figure
SPM.3}
B3.1.
If applied at scales necessary to remove CO2 from the atmosphere at the level of
several GtCO2yr-1, afforestation, reforestation and the use of land to provide feedstock for
bioenergy with or without carbon capture and storage, or for biochar, could greatly increase
demand for land conversion (high confidence). Integration into sustainably managed landscapes at
appropriate scale can ameliorate adverse impacts (medium confidence). Reduced grassland
conversion to croplands, restoration and reduced conversion of peatlands, and restoration and
reduced conversion of coastal wetlands affect smaller land areas globally, and the impacts on land
use change of these options are smaller or more variable (high confidence). {Cross-Chapter Box 7
in Chapter 6; 6.4; Figure SPM.3}
B3.2.
While land can make a valuable contribution to climate change mitigation, there
are limits to the deployment of land-based mitigation measures such as bioenergy crops or
afforestation. Widespread use at the scale of several millions of km2 globally could increase risks
for desertification, land degradation, food security and sustainable development (medium
confidence). Applied on a limited share of total land, land-based mitigation measures that displace
other land uses have fewer adverse side-effects and can have positive co-benefits for adaptation,
desertification, land degradation or food security. (high confidence) {4.2, 4.5, 6.4; Cross-Chapter
Box 7 in Chapter 6, Figure SPM3}
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The production and use of biomass for bioenergy can have co-benefits, adverse side
B3.3
effects, and risks for land degradation, food insecurity, GHG emissions and other environmental
and sustainable development goals (high confidence). These impacts are context specific and
depend on the scale of deployment, initial land use, land type, bioenergy feedstock, initial carbon
stocks, climatic region and management regime, and other land-demanding response options can
have a similar range of consequences (high confidence). The use of residues and organic waste as
bioenergy feedstock can mitigate land use change pressures associated with bioenergy
deployment, but residues are limited and the removal of residues that would otherwise be left on
the soil could lead to soil degradation (high confidence). {2.6.1.5; Cross-Chapter Box 7 in Chapter
6; Figure SPM3}
For projected socioeconomic pathways with low population, effective land-use
B3.4.
regulation, food produced in low-GHG emission systems and lower food loss and waste (SSP1),
the transition from low to moderate risk to food security, land degradation and water scarcity in
dry lands occur between 1 and 4 million km2 of bioenergy or BECCS (medium confidence). By
contrast, in pathways with high population, low income and slow rates of technological change
(SSP3), the transition from low to moderate risk occurs between 0.1 and 1 million km2 (medium
confidence). {6.4; Cross-Chapter Box 7 in Chapter 6; Table SM7.6; Box SPM1}
Many activities for combating desertification can contribute to climate change
B 4.
adaptation with mitigation co-benefits, as well as to halting biodiversity loss with sustainable
development co-benefits to society (high confidence). Avoiding, reducing and reversing
desertification would enhance soil fertility, increase carbon storage in soils and biomass,
while benefitting agricultural productivity and food security (high confidence). Preventing
desertification is preferable to attempting to restore degraded land due to the potential for
residual risks and maladaptive outcomes (high confidence). {3.6.1, 3.6.2, 3.6.3, 3.6.4, 3.7.1,
3.7.2}
B4.1.
Solutions that help adapt to and mitigate climate change while contributing to
combating desertification are site and regionally specific and include inter alia: water harvesting
and micro-irrigation, restoring degraded lands using drought-resilient ecologically appropriate
plants; agroforestry and other agroecological and ecosystem-based adaptation practices (high
confidence). {3.3, 3.6.1, 3.7.2, 3.7.5, 5.2, 5.6}
Reducing dust and sand storms and sand dune movement can lessen the negative
B4.2.
effects of wind erosion and improve air quality and health (high confidence). Depending on water
availability and soil conditions, afforestation, tree planting and ecosystem restoration programs,

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which aim for the creation of windbreaks in the form of “green walls”, and “green dams” using
native and other climate resilient tree species with low water needs, can reduce sand storms, avert
wind erosion, and contribute to carbon sinks, while improving micro-climates, soil nutrients and
water retention (high confidence). {3.3, 3.6.1, 3.7.2, 3.7.5}
Measures to combat desertification can promote soil carbon sequestration (high
B4.3.
confidence). Natural vegetation restoration and tree planting on degraded land enriches, in the long
term, carbon in the topsoil and subsoil (medium confidence). Modelled rates of carbon
sequestration following the adoption of conservation agriculture practices in drylands depend on
local conditions (medium confidence). If soil carbon is lost, it may take a prolonged period of time
for carbon stocks to recover. {3.1.4, 3.3, 3.6.1, 3.6.3, 3.7.1, 3.7.2}
B4.4 Eradicating poverty and ensuring food security can benefit from applying measures
promoting land degradation neutrality (including avoiding, reducing and reversing land
degradation) in rangelands, croplands and forests, which contribute to combating desertification,
while mitigating and adapting to climate change within the framework of sustainable development.
Such measures include avoiding deforestation and locally suitable practices including management
of rangeland and forest fires (high confidence). {3.4.2, 3.6.1, 3.6.2, 3.6.3, 4.8.5}.
B4.5 Currently there is a lack of knowledge of adaptation limits and potential maladaptation to
combined effects of climate change and desertification. In the absence of new or enhanced
adaptation options, the potential for residual risks and maladaptive outcomes is high (high
confidence). Even when solutions are available, social, economic and institutional constraints
could pose barriers to their implementation (medium confidence). Some adaptation options can
become maladaptive due to their environmental impacts, such as irrigation causing soil salinisation
or over extraction leading to ground-water depletion (medium confidence). Extreme forms of
desertification can lead to the complete loss of land productivity, limiting adaptation options or
reaching the limits to adaptation (high confidence). {Executive Summary Chapter 3, 3.6.4, 3.7.5,
7.4.9}
Developing, enabling and promoting access to cleaner energy sources and
B4.6.
technologies can contribute to adaptation and mitigating climate change and combating
desertification and forest degradation through decreasing the use of traditional biomass for energy
while increasing the diversity of energy supply (medium confidence). This can have socioeconomic
and health benefits, especially for women and children. (high confidence). The efficiency of wind
and solar energy infrastructures is recognized; the efficiency can be affected in some regions by
dust and sand storms (high confidence). {3.5.3, 3.5.4, 4.4.4, 7.5.2, Cross-Chapter Box 12 in
Chapter 7}

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Sustainable land management 33, including sustainable forest management 34,
B 5.
can prevent and reduce land degradation, maintain land productivity, and sometimes
reverse the adverse impacts of climate change on land degradation (very high confidence). It
can also contribute to mitigation and adaptation (high confidence). Reducing and reversing
land degradation, at scales from individual farms to entire watersheds, can provide cost
effective, immediate, and long-term benefits to communities and support several Sustainable
Development Goals (SDGs) with co-benefits for adaptation (very high confidence) and
mitigation (high confidence). Even with implementation of sustainable land management,
limits to adaptation can be exceeded in some situations (medium confidence). {1.3.2, 4.1.5,
4.8, Table 4.2}

B5.1.
Land degradation in agriculture systems can be addressed through sustainable land
management, with an ecological and socioeconomic focus, with co-benefits for climate change
adaptation. Management options that reduce vulnerability to soil erosion and nutrient loss include
growing green manure crops and cover crops, crop residue retention, reduced/zero tillage, and
maintenance of ground cover through improved grazing management (very high confidence).
{4.8}
B5.2.
The following options also have mitigation co-benefits. Farming systems such as
agroforestry, perennial pasture phases and use of perennial grains, can substantially reduce erosion
and nutrient leaching while building soil carbon (high confidence). The global sequestration
potential of cover crops would be about 0.44 +/- 0.11 GtCO2 yr-1 if applied to 25% of global
cropland (high confidence). The application of certain biochars can sequester carbon (high
confidence), and improve soil conditions in some soil types/climates (medium confidence).
{4.8.1.1, 4.8.1.3, 4.9.2, 4.9.5, 5.5.1, 5.5.4; Cross-Chapter Box 6 in Chapter 5}
B5.3.
Reducing deforestation and forest degradation lowers GHG emissions (high
confidence), with an estimated technical mitigation potential of 0.4–5.8 GtCO2 yr-1. By providing
long-term livelihoods for communities, sustainable forest management can reduce the extent of
Sustainable land management is defined in this report as the stewardship and use of land resources, including soils,
water, animals and plants, to meet changing human needs, while simultaneously ensuring the long-term productive
potential of these resources and the maintenance of their environmental functions. Examples of options include inter
alia agroecology (including agroforestry), conservation agriculture and forestry practices, crop and forest species
diversity, appropriate crop and forest rotations, organic farming, integrated pest management, the conservation of
pollinators, rain water harvesting, range and pasture management, and precision agriculture systems.
34
Sustainable forest management is defined in this report as the stewardship and use of forests and forest lands in a
way, and at a rate, that maintains their biodiversity, productivity, regeneration capacity, vitality, and their potential to
fulfill now and in the future, relevant ecological, economic and social functions at local, national and global levels
and that does not cause damage to other ecosystems.
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forest conversion to non-forest uses (e.g., cropland or settlements) (high confidence). Sustainable
forest management aimed at providing timber, fibre, biomass, non-timber resources and other
ecosystem functions and services, can lower GHG emissions and can contribute to adaptation.
(high confidence). {2.6.1.2, 4.1.5, 4.3.2, 4.5.3, 4.8.1.3, 4.8.3, 4.8.4}
Sustainable forest management can maintain or enhance forest carbon stocks, and
B5.4.
can maintain forest carbon sinks, including by transferring carbon to wood products, thus
addressing the issue of sink saturation (high confidence). Where wood carbon is transferred to
harvested wood products, these can store carbon over the long-term and can substitute for
emissions-intensive materials reducing emissions in other sectors (high confidence). Where
biomass is used for energy, e.g., as a mitigation strategy, the carbon is released back into the
atmosphere more quickly (high confidence). {2.6.1, 2.7, 4.1.5, 4.8.4, 6.4.1, Figure SPM.3, CrossChapter Box 7 in Chapter 6}
Climate change can lead to land degradation, even with the implementation of
B5.5.
measures intended to avoid, reduce or reverse land degradation (high confidence). Such limits to
adaptation are dynamic, site specific and are determined through the interaction of biophysical
changes with social and institutional conditions (very high confidence). In some situations,
exceeding the limits of adaptation can trigger escalating losses or result inundesirable
transformational changes (medium confidence), such as forced migration (low confidence),
conflicts (low confidence) or poverty (medium confidence). Examples of climate change induced
land degradation that may exceed limits to adaptation include coastal erosion exacerbated by sea
level rise where land disappears (high confidence), thawing of permafrost affecting infrastructure
and livelihoods (medium confidence), and extreme soil erosion causing loss of productive capacity
(medium confidence). {4.7, 4.8.5, 4.8.6, 4.9.6, 4.9.7, 4.9.8}
B 6.
Response options throughout the food system, from production to
consumption, including food loss and waste, can be deployed and scaled up to advance
adaptation and mitigation (high confidence). The total technical mitigation potential from
crop and livestock activities, and agroforestry is estimated as 2.3-9.6 GtCO2e.yr-1 by 2050
(medium confidence). The total technical mitigation potential of dietary changes is estimated
as 0.7-8 GtCO2e.yr-1 by 2050 (medium confidence). {5.3, 5.5, 5.6}
B6.1.
Practices that contribute to climate change adaptation and mitigation in cropland
include increasing soil organic matter, erosion control, improved fertiliser management, improved
crop management, for example, paddy rice management, and use ofvarieties and genetic
improvements for heat and drought tolerance. For livestock, options include better grazing land
management, improved manure management, higher-quality feed, and use of breeds and genetic
improvement. Different farming and pastoral systems can achieve reductions in the emissions
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intensity of livestock products. Depending on the farming and pastoral systems and level of
development, reductions in the emissions intensity of livestock products may lead to absolute
reductions in GHG emissions (medium confidence). Many livestock related options can enhance
the adaptive capacity of rural communities, in particular, of smallholders and pastoralists.
Significant synergies exist between adaptation and mitigation, for example through sustainable
land management approaches (high confidence). {4.8, 5.3.3, 5.5.1, 5.6}
Diversification in the food system (e.g., implementation of integrated production
B6.2.
systems, broad-based genetic resources, and diets) can reduce risks from climate change (medium
confidence). Balanced diets, featuring plant-based foods, such as those based on coarse grains,
legumes, fruits and vegetables, nuts and seeds, and animal-sourced food produced in resilient,
sustainable and low-GHG emission systems, present major opportunities for adaptation and
mitigation while generating significant co-benefits in terms of human health (high confidence). By
2050, dietary changes could free several Mkm2 (medium confidence) of land and provide a
technical mitigation potential of 0.7 to 8.0 GtCO2e yr-1, relative to business as usual projections
(high confidence). Transitions towards low-GHG emission diets may be influenced by local
production practices, technical and financial barriers and associated livelihoods and cultural habits
(high confidence). {5.3, 5.5.2, 5.5, 5.6}
B6.3.
Reduction of food loss and waste can lower GHG emissions and contribute to
adaptation through reduction in the land area needed for food production (medium confidence).
During 2010-2016, global food loss and waste contributed 8-10% of total anthropogenic GHG
emissions (medium confidence). Currently, 25-30% of total food produced is lost or wasted
(medium confidence). Technical options such as improved harvesting techniques, on-farm storage,
infrastructure, transport, packaging, retail and education can reduce food loss and waste across the
supply chain. Causes of food loss and waste differ substantially between developed and developing
countries, as well as between regions (medium confidence). {5.5.2} By 2050, reduced food loss
and waste can free several Mkm2 of land (low confidence). {6.3.6}
B 7.
Future land use depends, in part, on the desired climate outcome and the
portfolio of response options deployed (high confidence). All assessed modelled pathways
that limit warming to 1.5ºC or well below 2°C require land-based mitigation and land-use
change, with most including different combinations of reforestation, afforestation, reduced
deforestation, and bioenergy (high confidence). A small number of modelled pathways
achieve 1.5ºC with reduced land conversion (high confidence) and, thus, reduced
consequences for desertification, land degradation, and food security (medium confidence).
{2.6, 6.4, 7.4, 7.6; Cross-Chapter Box 9 in Chapter 6; Figure SPM.4}

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B7.1.
Modelled pathways limiting global warming to 1.5ºC 35 include more land-based
mitigation than higher warming level pathways (high confidence), but the impacts of climate
change on land systems in these pathways are less severe (medium confidence). {2.6, 6.4, 7.4,
Cross-Chapter Box 9 in Chapter 6, Figure SPM.2, Figure SPM.4}
Modelled pathways limiting global warming to 1.5°C and 2ºC project a 2 million
B7.2.
2
km reduction to a 12 million km2 increase in forest area in 2050 relative to 2010 (medium
confidence). 3ºC pathways project lower forest areas, ranging from a 4 million km2 reduction to a
6 million km2 increase (medium confidence). {2.5, 6.3, 7.3, 7.5; Cross-Chapter Box 9 in Chapter
6; Figure SPM.3, Figure SPM.4}
B7.3.
The land area needed for bioenergy in modelled pathways varies significantly
depending on the socioeconomic pathway, the warming level, and the feedstock and production
system used (high confidence). Modelled pathways limiting global warming to 1.5°C use up to 7
million km2 for bioenergy in 2050; bioenergy land area is smaller in 2°C (0.4 to 5 million km2)
and 3°C pathways (0.1 to 3 million km2) (medium confidence). Pathways with large levels of land
conversion may imply adverse side-effects impacting water scarcity, biodiversity, land
degradation, desertification, and food security, if not adequately and carefully managed, whereas
best practice implementation at appropriate scales can have co-benefits, such as management of
dryland salinity, enhanced biocontrol and biodiversity and enhancing soil carbon sequestration
(high confidence). {2.6, 6.1, 6.4, 7.2; Cross-Chapter Box 7 in Chapter 6, Figure SPM.3}
B7.4.
Most mitigation pathways include substantial deployment of bioenergy
technologies. A small number of modelled pathways limit warming to 1.5ºC with reduced
dependence on bioenergy and BECCS (land area below <1 million km2 in 2050) and other carbon
dioxide removal (CDR) options (high confidence). These pathways have even more reliance on
rapid and far-reaching transitions in energy, land, urban systems and infrastructure, and on
behavioural and lifestyle changes compared to other 1.5°C pathways. {2.6.2, 5.5.1, 6.4, CrossChapter Box 7 in Chapter 6
B7.5.
These modelled pathways do not consider the effects of climate change on land or
CO2 fertilisation. In addition, these pathways include only a subset of the response options assessed
in this report (high confidence); the inclusion of additional response options in models could
reduce the projected need for bioenergy or CDR that increases the demand for land. {6.4.4, CrossChapter Box 9 in Chapter 6}

In this report references to pathways limiting global warming to a particular level are based on a 66% probability
of staying below that temperature level in 2100 using the MAGICC model.
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Potential global contribution of response options to mitigation, adaptation,
combating desertification and land degradation, and enhancing food security
Panel A shows response options that can be implemented without or with limited competition for land, including some that have the
potential to reduce the demand for land. Co-benefits and adverse side effects are shown quantitatively based on the high end of the
range of potentials assessed. Magnitudes of contributions are categorised using thresholds for positive or negative impacts. Letters
within the cells indicate confidence in the magnitude of the impact relative to the thresholds used (see legend). Confidence in the
direction of change is generally higher.

Soils

Forests

Agriculture

Response options based on land management

Desertification

Land Degradation

Increased food productivity

Mitigation
L

Adaptation
M

L

M

H

Agro-forestry

M

M

M

M

L

Improved cropland management

M

L

L

L

L

Improved livestock management

M

L

L

L

L

Agricultural diversification

L

L

L

M

L

Improved grazing land management

M

L

L

L

L

Integrated water management

L

L

L

L

L

Reduced grassland conversion to cropland

L

L

L

L

Forest management

M

L

L

L

L

Reduced deforestation and forest degradation

H

L

L

L

L

Increased soil organic carbon content

H

L

M

M

L

Reduced soil erosion

L

L

M

M

L

L

L

L

L

L

L

M

M

M

L

Reduced soil salinization

Other ecosystems

Reduced soil compaction

L

Fire management

M

Food Security

Cost

Reduced landslides and natural hazards

L

L

L

L

L

Reduced pollution including acidification

M

M

L

L

L

Restoration & reduced conversion of coastal wetlands

M

L

M

M

L

Restoration & reduced conversion of peatlands

M

M

L

L

L

H

L

H

H

L

M

M

L

L

na

Supply

Demand

Response options based on value chain management
Reduced post-harvest losses

H

Dietary change

H

Reduced food waste (consumer or retailer)

H

M

Sustainable sourcing

L

Improved food processing and retailing

L

L

L

Improved energy use in food systems

L

L

L

Response options based on risk management
Risk

Livelihood diversification

L

Management of urban sprawl

L

Risk sharing instruments

L

L

L

L

L

M

L

L

L

Options shown are those for which data are available to assess global potential for three or more land challenges.
The magnitudes are assessed independently for each option and are not additive.

Positive

Key for criteria used to define magnitude of impact of each integrated response option

Large
Moderate
Small

Negative

Negligible
Small
Moderate
Large

Confidence level

Food Security
Million people

Indicates confidence in the
estimate of magnitude category.

Mitigation
Gt CO2-eq yr¯1

Adaptation
Million people

Desertification
Million km2

Land Degradation
Million km2

More than 3

Positive for
more than 25

Positive for
more than 3

Positive for
more than 3

Positive for
more than 100

0.3 to 3

1 to 25

0.5 to 3

0.5 to 3

1 to 100

Less than 0.3

Less than 1

Less than 0.5

Less than 0.5

Less than 1

No effect

No effect

No effect

No effect

No effect

Cost range

Less than -0.3

Less than 1

Less than 0.5

Less than 0.5

Less than 1

See technical caption for cost
ranges in US$ tCO2e-1 or US$ ha-1.

-0.3 to -3

1 to 25

0.5 to 3

0.5 to 3

1 to 100

More than -3

Negative for
more than 25

Negative for
more than 3

Negative for
more than 3

Negative for
more than 100

Variable: Can be positive or negative

no data

na

not applicable

H High confidence
M Medium confidence
L Low confidence

High cost
Medium cost
Low cost
no data

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Potential global contribution of response options to mitigation, adaptation,
combating desertification and land degradation, and enhancing food security
Panel B shows response options that rely on additional land-use change and could have implications across three or more land
challenges under different implementation contexts. For each option, the first row (high level implementation) shows a quantitative
assessment (as in Panel A) of implications for global implementation at scales delivering CO2 removals of more than 3 GtCO2 yr-1 using
the magnitude thresholds shown in Panel A. The red hatched cells indicate an increasing pressure but unquantified impact. For each
option, the second row (best practice implementation) shows qualitative estimates of impact if implemented using best practices in
appropriately managed landscape systems that allow for efficient and sustainable resource use and supported by appropriate
governance mechanisms. In these qualitative assessments, green indicates a positive impact, grey indicates a neutral interaction.
Bioenergy and BECCS
Mitigation

Desertification

Adaptation

H

Land degradation

Food security

L

Cost

L

High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts, assuming carbon dioxide removal by BECCS at
a scale of 11.3 GtCO2 yr-1 in 2050, and noting that bioenergy without CCS can also achieve emissions reductions of up to several GtCO2 yr-1 when it is a low carbon energy
source {2.7.1.5; 6.4.1.1.5}. Studies linking bioenergy to food security estimate an increase in the population at risk of hunger to up to 150 million people at this level of
implementation {6.4.5.1.5}. The red hatched cells for desertification and land degradation indicate that while up to 15 million km2 of additional land is required in 2100
in 2°C scenarios which will increase pressure for desertification and land degradation, the actual area affected by this additional pressure is not easily quantified
{6.4.3.1.5; 6.4.4.1.5}.
Mitigation

Desertification

Adaptation

Land degradation

Food security

Best practice: The sign and magnitude of the effects of bioenergy and BECCS depends on the scale of deployment, the type of bioenergy feedstock, which other
response options are included, and where bioenergy is grown (including prior land use and indirect land use change emissions). For example, limiting bioenergy
production to marginal lands or abandoned cropland would have negligible effects on biodiversity, food security, and potentially co-benefits for land degradation;
however, the benefits for mitigation could also be smaller. {Table 6.58}

Reforestation and forest restoration
Mitigation

Desertification

Adaptation

M

M

Land degradation

M

Food security

M

Cost

M

High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts assuming implementation of reforestation and
forest restoration (partly overlapping with afforestation) at a scale of 10.1 GtCO2 yr-1 removal {6.4.1.1.2}. Large-scale afforestation could cause increases in food prices of
80% by 2050, and more general mitigation measures in the AFOLU sector can translate into a rise in undernourishment of 80–300 million people; the impact of
reforestation is lower {6.4.5.1.2}.
Desertification
Land degradation
Food security
Mitigation
Adaptation
Best practice: There are co-benefits of reforestation and forest restoration in previously forested areas, assuming small scale deployment using native species and
involving local stakeholders to provide a safety net for food security. Examples of sustainable implementation include, but are not limited to, reducing illegal logging
and halting illegal forest loss in protected areas, reforesting and restoring forests in degraded and desertified lands {Box6.1C; Table 6.6}.

Afforestation
Mitigation

Desertification

Adaptation

M

M

Land degradation

M

Food security

L

Cost

M

High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts assuming implementation of afforestation
(partly overlapping with reforestation and forest restoration) at a scale of 8.9 GtCO2 yr-1 removal {6.4.1.1.2}. Large-scale afforestation could cause increases in food prices
of 80% by 2050, and more general mitigation measures in the AFOLU sector can translate into a rise in undernourishment of 80–300 million people {6.4.5.1.2}.
Mitigation

Desertification

Adaptation

Land degradation

Food security

Best practice: Afforestation is used to prevent desertification and to tackle land degradation. Forested land also offers benefits in terms of food supply, especially when
forest is established on degraded land, mangroves, and other land that cannot be used for agriculture. For example, food from forests represents a safety-net during
times of food and income insecurity {6.4.5.1.2}.

Biochar addition to soil
Mitigation

Desertification

Adaptation

M

X

Land degradation

X

Food security

L

Cost

L

High level: Impacts on adaptation, desertification, land degradation and food security are maximum potential impacts assuming implementation of afforestation at a
scale of 6.6 GtCO2 yr-1 removal {6.4.1.1.3}. Dedicated energy crops required for feedstock production could occupy 0.4–2.6 Mkm2 of land, equivalent to around 20% of
the global cropland area, which could potentially have a large effect on food security for up to 100 million people {6.4.5.1.3}.
Mitigation

Adaptation

Desertification

Land degradation

Food security

Best practice: When applied to land, biochar could provide moderate benefits for food security by improving yields by 25% in the tropics, but with more limited
impacts in temperate regions, or through improved water holding capacity and nutrient use efficiency. Abandoned cropland could be used to supply biomass for
biochar, thus avoiding competition with food production; 5-9 Mkm2 of land is estimated to be available for biomass production without compromising food security
and biodiversity, considering marginal and degraded land and land released by pasture intensification {6.4.5.1.3}.

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Figure SPM.3 Potential global contribution of response options to mitigation, adaptation,
combating desertification and land degradation, and enhancing food security.
This Figure is based on an aggregation of information from studies with a wide variety of assumptions about how
response options are implemented and the contexts in which they occur. Response options implemented differently at
local to global scales could lead to different outcomes. Magnitude of potential: For panel A, magnitudes are for the
technical potential of response options globally. For each land challenge, magnitudes are set relative to a marker level
as follows. For mitigation, potentials are set relative to the approximate potentials for the response options with the
largest individual impacts (~3 GtCO2-eq yr-1). The threshold for the “large” magnitude category is set at this level.
For adaptation, magnitudes are set relative to the 100 million lives estimated to be affected by climate change and a
carbon-based economy between 2010 and 2030. The threshold for the “large” magnitude category represents 25% of
this total. For desertification and land degradation, magnitudes are set relative to the lower end of current estimates of
degraded land, 10-60 million km2. The threshold for the “large” magnitude category represents 30% of the lower
estimate. For food security, magnitudes are set relative to the approximately 800 million people who are currently
undernourished. The threshold for the “large” magnitude category represents 12.5% of this total. For panel B, for the
first row (high level implementation) for each response option, the magnitude and thresholds are as defined for panel
A. In the second row (best practice implementation) for each response option, the qualitative assessments that are
green denote potential positive impacts, and those shown in grey indicate neutral interactions. Increased food
production is assumed to be achieved through sustainable intensification rather than through injudicious application
of additional external inputs such as agrochemicals. Levels of confidence: Confidence in the magnitude category
(high, medium or low) into which each option falls for mitigation, adaptation, combating desertification and land
degradation, and enhancing food security. High confidence means that there is a high level of agreement and evidence
in the literature to support the categorisation as high, medium or low magnitude. Low confidence denotes that the
categorisation of magnitude is based on few studies. Medium confidence reflects medium evidence and agreement in
the magnitude of response. Cost ranges: Cost estimates are based on aggregation of often regional studies and vary
in the components of costs that are included. In panel B, cost estimates are not provided for best practice
implementation. One coin indicates low cost (<USD10 tCO2-eq-1 or <USD20 ha-1), two coins indicate medium cost
(USD10-USD100 tCO2-eq-1 or USD20-USD200 ha-1), and three coins indicate high cost (>USD100 tCO2-eq-1 or
USD200 ha-1). Thresholds in USD ha-1 are chosen to be comparable, but precise conversions will depend on the
response option. Supporting evidence: Supporting evidence for the magnitude of the quantitative potential for land
management-based response options can be found as follows: for mitigation tables 6.13 to 6.20, with further evidence
in Section 2.7.1; for adaptation tables 6.21 to 6.28; for combating desertification tables 6.29 to 6.36, with further
evidence in Chapter 3; for combating degradation tables 6.37 to 6.44, with further evidence in Chapter 4; for enhancing
food security tables 6.45 to 6.52, with further evidence in Chapter 5. Other synergies and trade-offs not shown here
are discussed in Chapter 6. Additional supporting evidence for the qualitative assessments in the second row for each
option in panel B can be found in the tables 6.6, 6.55, 6.56 and 6.58, section 6.3.5.1.3, and Box 6.1c.

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C. Enabling response options
C 1.
Appropriate design of policies, institutions and governance systems at all
scales can contribute to land-related adaptation and mitigation while facilitating the pursuit
of climate-adaptive development pathways (high confidence). Mutually supportive climate
and land policies have the potential to save resources, amplify social resilience, support
ecological restoration, and foster engagement and collaboration between multiple
stakeholders (high confidence). {Figure SPM.1, Figure SPM.2, Figure SPM.3; 3.6.2, 3.6.3,
4.8, 4.9.4, 5.7, 6.3, 6.4, 7.2.2, 7.3, 7.4, 7.4.7, 7.4.8, 7.5, 7.5.5, 7.5.6, 7.6.6; Cross-Chapter Box 10
in Chapter 7}
C1.1.
Land-use zoning, spatial planning, integrated landscape planning, regulations,
incentives (such as payment for ecosystem services), and voluntary or persuasive instruments
(such as environmental farm planning, standards and certification for sustainable production, use
of scientific, local and indigenous knowledge and collective action), can achieve positive
adaptation and mitigation outcomes (medium confidence). They can also contribute revenue and
provide incentive to rehabilitate degraded lands and adapt to and mitigate climate change in certain
contexts (medium confidence). Policies promoting the target of land degradation neutrality can
also support food security, human wellbeing and climate change adaptation and mitigation (high
confidence). {Figure SPM.2; 3.4.2, 4.1.6, 4.7, 4.8.5, 5.1.2, 5.7.3, 7.3, 7.4.6, 7.4.7, 7.5}
C1.2.
Insecure land tenure affects the ability of people, communities and organisations to
make changes to land that can advance adaptation and mitigation (medium confidence). Limited
recognition of customary access to land and ownership of land can result in increased vulnerability
and decreased adaptive capacity (medium confidence). Land policies (including recognition of
customary tenure, community mapping, redistribution, decentralisation, co-management,
regulation of rental markets) can provide both security and flexibility response to climate change
(medium confidence). {3.6.1, 3.6.2, 5.3, 7.2.4, 7.6.4, Cross-Chapter Box 6 in Chapter 5}
C1.3.
Achieving land degradation neutrality will involve a balance of measures that avoid
and reduce land degradation, through adoption of sustainable land management, and measures to
reverse degradation through rehabilitation and restoration of degraded land. Many interventions to
achieve land degradation neutrality commonly also deliver climate change adaptation and
mitigation benefits. The pursuit of land degradation neutrality provides impetus to address land
degradation and climate change simultaneously (high confidence). {4.5.3, 4.8.5, 4.8.7, 7.4.5}

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C1.4.
Due to the complexity of challenges and the diversity of actors involved in
addressing land challenges, a mix of policies, rather than single policy approaches, can deliver
improved results in addressing the complex challenges of sustainable land management and
climate change (high confidence). Policy mixes can strongly reduce the vulnerability and exposure
of human and natural systems to climate change (high confidence). Elements of such policy mixes
may include weather and health insurance, social protection and adaptive safety nets, contingent
finance and reserve funds, universal access to early warning systems combined with effective
contingency plans (high confidence). {1.2, 4.8, 4.9.2, 5.3.2, 5.6, 5.6.6, 5.7.2, 7.3.2, 7.4, 7.4.2, 7.4.6,
7.4.7, 7.4.8, 7.5.5, 7.5.6, 7.6.4, Figure SPM.4}
Policies that operate across the food system, including those that reduce food
C2.
loss and waste and influence dietary choices, enable more sustainable land-use management,
enhanced food security and low emissions trajectories (high confidence). Such policies can
contribute to climate change adaptation and mitigation, reduce land degradation,
desertification and poverty as well as improve public health (high confidence). The adoption
of sustainable land management and poverty eradication can be enabled by improving access
to markets, securing land tenure, factoring environmental costs into food, making payments
for ecosystem services, and enhancing local and community collective action (high
confidence). {1.1.2, 1.2.1, 3.6.3, 4.7.1, 4.7.2, 4.8, 5.5, 6.4, 7.4.6, 7.6.5}
Policies that enable and incentivise sustainable land management for climate
C2.1.
change adaptation and mitigation include improved access to markets for inputs, outputs and
financial services, empowering women and indigenous peoples, enhancing local and community
collective action, reforming subsidies and promoting an enabling trade system (high confidence).
Land restoration and rehabilitation efforts can be more effective when policies support local
management of natural resources, while strengthening cooperation between actors and institutions,
including at the international level. {3.6.3, 4.1.6, 4.5.4, 4.8.2, 4.8.4, 5.7, 7.2}
Reflecting the environmental costs of land-degrading agricultural practices can
C2.2.
incentivise more sustainable land management (high confidence). Barriers to the reflection of
environmental costs arise from technical difficulties in estimating these costs and those embodied
in foods. {3.6.3, 5.5.1, 5.5.2, 5.6.6, 5.7, 7.4.4, Cross-Chapter Box 10 in Chapter 7}
Adaptation and enhanced resilience to extreme events impacting food systems can
C2.3.
be facilitated by comprehensive risk management, including risk sharing and transfer mechanisms
(high confidence). Agricultural diversification, expansion of market access, and preparation for
increasing supply chain disruption can support the scaling up of adaptation in food systems (high
confidence). {5.3.2, 5.3.3, 5.3.5}

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C2.4.
Public health policies to improve nutrition, such as increasing the diversity of food
sources in public procurement, health insurance, financial incentives, and awareness-raising
campaigns, can potentially influence food demand, reduce healthcare costs, contribute to lower
GHG emissions and enhance adaptive capacity (high confidence). Influencing demand for food,
through promoting diets based on public health guidelines, can enable more sustainable land
management and contribute to achieving multiple SDGs (high confidence). {3.4.2, 4.7.2, 5.1, 5.7,
6.3, 6.4}
Acknowledging co-benefits and trade-offs when designing land and food
C 3.
policies can overcome barriers to implementation (medium confidence). Strengthened
multilevel, hybrid and cross-sectoral governance, as well as policies developed and adopted
in an iterative, coherent, adaptive and flexible manner can maximise co-benefits and
minimise trade-offs, given that land management decisions are made from farm level to
national scales, and both climate and land policies often range across multiple sectors,
departments and agencies (high confidence). {Figure SPM.3; 4.8.5, 4.9, 5.6, 6.4, 7.3, 7.4.6,
7.4.8, 7.4.9, 7.5.6, 7.6.2}
Addressing desertification, land degradation, and food security in an integrated,
C3.1.
coordinated and coherent manner can assist climate resilient development and provides numerous
potential co-benefits (high confidence). {3.7.5, 4.8, 5.6, 5.7, 6.4, 7.2.2, 7.3.1, 7.3.4, 7.4.7, 7.4.8,
7.5.6, 7.5.5}
Technological, biophysical, socio-economic, financial and cultural barriers can
C3.2.
limit the adoption of many land-based response options, as can uncertainty about benefits (high
confidence). Many sustainable land management practices are not widely adopted due to insecure
land tenure, lack of access to resources and agricultural advisory services, insufficient and unequal
private and public incentives, and lack of knowledge and practical experience (high confidence).
Public discourse, carefully designed policy interventions, incorporating social learning and market
changes can together help reduce barriers to implementation (medium confidence). {3.6.1, 3.6.2,
5.3.5, 5.5.2, 5.6, 6.2, 6.4, 7.4, 7.5, 7.6}
The land and food sectors face particular challenges of institutional fragmentation
C3.3.
and often suffer from a lack of engagement between stakeholders at different scales and narrowly
focused policy objectives (medium confidence). Coordination with other sectors, such as public
health, transportation, environment, water, energy and infrastructure, can increase co-benefits,
such as risk reduction and improved health (medium confidence). {5.6.3, 5.7, 6.2, 6.4.4, 7.1, 7.3,
7.4.8, 7.6.2, 7.6.3}

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C3.4.
Some response options and policies may result in trade-offs, including social
impacts, ecosystem functions and services damage, water depletion, or high costs, that cannot be
well-managed, even with institutional best practices (medium confidence). Addressing such tradeoffs helps avoid maladaptation (medium confidence). Anticipation and evaluation of potential
trade-offs and knowledge gaps supports evidence-based policymaking to weigh the costs and
benefits of specific responses for different stakeholders (medium confidence). Successful
management of trade-offs often includes maximising stakeholder input with structured feedback
processes, particularly in community-based models, use of innovative fora like facilitated
dialogues or spatially explicit mapping, and iterative adaptive management that allows for
continuous readjustments in policy as new evidence comes to light (medium confidence). {5.3.5,
6.4.2, 6.4.4, 6.4.5, 7.5.6; Cross-Chapter Box 13 in Chapter 7}
C 4.
The effectiveness of decision-making and governance is enhanced by the
involvement of local stakeholders (particularly those most vulnerable to climate change
including indigenous peoples and local communities, women, and the poor and marginalised)
in the selection, evaluation, implementation and monitoring of policy instruments for landbased climate change adaptation and mitigation (high confidence). Integration across sectors
and scales increases the chance of maximising co-benefits and minimising trade-offs (medium
confidence). {1.4, 3.1, 3.6, 3.7, 4.8, 4.9, 5.1.3, Box 5.1, 7.4, 7.6}
Successful implementation of sustainable land management practices requires
C4.1.
accounting for local environmental and socio-economic conditions (very high confidence).
Sustainable land management in the context of climate change is typically advanced by involving
all relevant stakeholders in identifying land-use pressures and impacts (such as biodiversity
decline, soil loss, over-extraction of groundwater, habitat loss, land-use change in agriculture, food
production and forestry) as well as preventing, reducing and restoring degraded land (medium
confidence). {1.4.1, 4.1.6, 4.8.7, 5.2.5, 7.2.4, 7.6.2, 7.6.4}
Inclusiveness in the measurement, reporting and verification of the performance of
C4.2.
policy instruments can support sustainable land management (medium confidence). Involving
stakeholders in the selection of indicators, collection of climate data, land modelling and land-use
planning, mediates and facilitates integrated landscape planning and choice of policy (medium
confidence). {3.7.5, 5.7.4, 7.4.1, 7.4.4, 7.5.3, 7.5.4, 7.5.5, 7.6.4, 7.6.6}
C4.3.
Agricultural practices that include indigenous and local knowledge can contribute
to overcoming the combined challenges of climate change, food security, biodiversity
conservation, and combating desertification and land degradation (high confidence). Coordinated
action across a range of actors including businesses, producers, consumers, land managers and
policymakers in partnership with indigenous peoples and local communities enable conditions for

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the adoption of response options (high confidence) {3.1.3, 3.6.1, 3.6.2, 4.8.2, 5.5.1, 5.6.4, 5.7.1,
5.7.4, 6.2, 7.3, 7.4.6, 7.6.4}
Empowering women can bring synergies and co-benefits to household food
C4.4.
security and sustainable land management (high confidence). Due to women’s disproportionate
vulnerability to climate change impacts, their inclusion in land management and tenure is
constrained. Policies that can address land rights and barriers to women’s participation in
sustainable land management include financial transfers to women under the auspices of antipoverty programmes, spending on health, education, training and capacity building for women,
subsidised credit and program dissemination through existing women’s community-based
organisations (medium confidence). {1.4.1, 4.8.2, 5.1.3, Box 5.1, Cross-Chapter Box 11 in Chapter
7}.

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A. Pathways linking socioeconomic development, mitigation responses and land
Socioeconomic development and land management influence the evolution of the land system including the relative amount of land
allocated to CROPLAND, PASTURE, BIOENERGY CROPLAND, FOREST, and NATURAL LAND. The lines show the median across Integrated
Assessment Models (IAMs) for three alternative shared socioeconomic pathways (SSP1, SSP2 and SSP5 at RCP1.9); shaded areas show
the range across models. Note that pathways illustrate the effects of climate change mitigation but not those of climate change impacts
or adaptation.
A. Sustainability-focused (SSP1)
Sustainability in land management,
agricultural intensification, production
and consumption patterns result in
reduced need for agricultural land,
despite increases in per capita food
consumption. This land can instead be
used for reforestation, afforestation, and
bioenergy.

B. Middle of the road (SSP2 )
Societal as well as technological
development follows historical patterns.
Increased demand for land mitigation
options such as bioenergy, reduced
deforestation or afforestation decreases
availability of agricultural land for food,
feed and fibre.

C. Resource intensive (SSP5)
Resource-intensive production and
consumption patterns, results in high
baseline emissions. Mitigation focuses on
technological solutions including
substantial bioenergy and BECCS .
Intensification and competing land uses
contribute to declines in agricultural land.

SSP1 Sustainability-focused
Change in Land from 2010 (Mkm2)
10

SSP2 Middle of the road
Change in Land from 2010 (Mkm2)
10

SSP5 Resource intensive
Change in Land from 2010 (Mkm2)
10

F

7.5
5

BC

2.5
0

7.5

BC

5

5

F

2.5

2.5

0

0

7.5

NL

-2.5

-2.5

-5

-5

C
P

-7.5
-10

2010

2025

2050

2075

2100

BC
F

NL
C

CROPLAND

-2.5

C

-5

-7.5
-10

NL

P

2010

2025

PASTURE

2050

2075

BIOENERGY CROPLAND

2100
FOREST

-7.5
-10

P

2010

2025

2050

2075

NATURAL LAND

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B. Land use and land cover change in the SSPs
Change in Bioenergy
Cropland from 2010
Mkm2

Change in Cropland
from 2010
Mkm2

0.5 ( -4.9 , 1 )

2.1 ( 0.9 , 5 )

-1.2 ( -4.6 , -0.3 )

3.4 ( -0.1 , 9.4 )

-4.1 ( -5.6 , -2.5 )

0 ( -7.3 , 7.1 )

4.3 ( 1.5 , 7.2 )

-5.2 ( -7.6 , -1.8 )

7.5 ( 0.4 , 15.8 )

-6.5 ( -12.2 , -4.8 )

-0.9 ( -2.2 , 1.5 )

1.3 ( 0.4 , 1.9 )

-1 ( -4.7 , 1 )

2.6 ( -0.1 , 8.4 )

-3 ( -4 , -2.4 )

0.2 ( -3.5 , 1.1 )

5.1 ( 1.6 , 6.3 )

-3.2 ( -7.7 , -1.8 )

6.6 ( -0.1 , 10.5 )

-5.5 ( -9.9 , -4.2 )

0.5 ( -1 , 1.7 )

0.8 ( 0.5 , 1.3 )

0.1 ( -3.2 , 1.5 )

0.6 ( -0.7 , 4.2 )

-2.4 ( -3.3 , -0.9 )

1.8 ( -1.7 , 6 )

1.9 ( 1.4 , 3.7 )

-2.3 ( -6.4 , -1.6 )

3.9 ( 0.2 , 8.8 )

-4.6 ( -7.3 , -2.7 )

0.3 ( -1.1 , 1.8 )

0.5 ( 0.2 , 1.4 )

0.2 ( -1.6 , 1.9 )

-0.1 ( -0.8 , 1.1 )

-1.5 ( -2.9 , -0.2 )

3.3 ( -0.3 , 5.9 )

1.8 ( 1.4 , 2.4 )

-1.5 ( -5.7 , -0.9 )

0.9 ( 0.3 , 3 )

-2.1 ( -7 , 0 )

-2.2 ( -7 , 0.6 )

4.5 ( 2.1 , 7 )

-1.2 ( -2 , 0.3 )

3.4 ( -0.9 , 7 )

-4.8 ( -6.2 , -0.4 )

-2.3 ( -9.6 , 2.7 )

6.6 ( 3.6 , 11 )

-2.9 ( -4 , 0.1 )

6.4 ( -0.8 , 9.5 )

-7.6 ( -11.7 , -1.3 )

-3.2 ( -4.2 , 0.1 )

2.2 ( 1.7 , 4.7 )

0.6 ( -1.9 , 1.9 )

1.6 ( -0.9 , 4.2 )

-1.4 ( -3.7 , 0.4 )

-5.2 ( -7.2 , 0.5 )

6.9 ( 2.3 , 10.8 )

-1.4 ( -4 , 0.8 )

5.6 ( -0.9 , 5.9 )

-7.2 ( -8 , 0.5 )

5/5

-2.2 ( -2.2 , 0.7 )

1.5 ( 0.1 , 2.1 )

1.2 ( -0.9 , 2.7 )

-0.9 ( -2.5 , 2.9 )

-0.1 ( -2.5 , 1.6 )

-3.4 ( -4.7 , 1.5 )

4.1 ( 0.4 , 6.3 )

0.7 ( -2.6 , 3.1 )

-0.5 ( -3.1 , 5.9 )

-2.8 ( -5.3 , 1.9 )

5/5

-1.5 ( -2.6 , -0.2 )

0.7 ( 0 , 1.5 )

1.3 ( 1 , 2.7 )

-1.3 ( -2.5 , -0.4 )

-0.1 ( -1.2 , 1.6 )

2100

-2.1 ( -5.9 , 0.3 )

1.2 ( 0.1 , 2.4 )

1.9 ( 0.8 , 2.8 )

-1.3 ( -2.7 , -0.2 )

-0.2 ( -1.9 , 2.1 )

RCP1.9 in 2050

Infeasible in all assessed models

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-3.4 ( -4.4 , -2 )

1.3 ( 1.3 , 2 )

2.3 ( 1.2 , 3 )

-2.4 ( -4 , -1 )

2.1 ( -0.1 , 3.8 )

-6.2 ( -6.8 , -5.4 )

4.6 ( 1.5 , 7.1 )

3.4 ( 1.9 , 4.5 )

-3.1 ( -5.5 , -0.3 )

2 ( -2.5 , 4.4 )

-3 ( -4.6 , -1.7 )

1 ( 0.2 , 1.5 )

2.5 ( 1.5 , 3 )

-2.5 ( -4 , -1.5 )

2.4 ( 0.6 , 3.8 )

-5 ( -7.1 , -4.2 )

1.1 ( 0.9 , 2.5 )

5.1 ( 3.8 , 6.1 )

-5.3 ( -6 , -2.6 )

3.4 ( 0.9 , 6.4 )

-

-

-

-

-

-

-

-

-4.5 ( -6 , -2.1 )

3.3 ( 1.5 , 4.5 )

0.5 ( -0.1 , 0.9 )

0.7 ( -0.3 , 2.2 )

-0.6 ( -0.7 , 0.1 )

-5.8 ( -10.2 , -4.7 )

2.5 ( 2.3 , 15.2 )

-0.8 ( -0.8 , 1.8 )

1.4 ( -1.7 , 4.1 )

-1.2 ( -2.5 , -0.2 )

-2.7 ( -4.4 , -0.4 )

1.7 ( 1 , 1.9 )

1.1 ( -0.1 , 1.7 )

-1.8 ( -2.3 , 2.1 )

0.8 ( -0.5 , 1.5 )

-2.8 ( -7.8 , -2 )

2.7 ( 2.3 , 4.7 )

1.1 ( 0.2 , 1.2 )

-0.7 ( -2.6 , 1 )

1.4 ( -1 , 1.8 )

-2.8 ( -2.9 , -0.2 )

1.1 ( 0.7 , 2 )

1.1 ( 0.7 , 1.8 )

-1.8 ( -2.3 , -1 )

1.5 ( -0.5 , 2.1 )

-2.4 ( -5 , -1 )

1.7 ( 1.4 , 2.6 )

1.2 ( 1.2 , 1.9 )

-2.4 ( -2.5 , -2 )

1.3 ( -1 , 4.4 )

-1.5 ( -3.9 , 0.9 )

6.7 ( 6.2 , 7.2 )

-1.9 ( -3.5 , -0.4 )

3.1 ( -0.1 , 6.3 )

-6.4 ( -7.7 , -5.1 )

-0.5 ( -4.2 , 3.2 )

7.6 ( 7.2 , 8 )

-3.4 ( -6.2 , -0.5 )

4.7 ( 0.1 , 9.4 )

-8.5 ( -10.7 , -6.2 )

-3.4 ( -6.9 , 0.3 )

4.8 ( 3.8 , 5.1 )

-2.1 ( -4 , 1 )

3.9 ( -0.1 , 6.7 )

-4.4 ( -5 , 0.2 )

-4.3 ( -8.4 , 0.5 )

9.1 ( 7.7 , 9.2 )

-3.3 ( -6.5 , -0.5 )

3.9 ( -0.1 , 9.3 )

-6.3 ( -9.1 , -1.4 )

-2.5 ( -3.7 , 0.2 )

1.7 ( 0.6 , 2.9 )

0.6 ( -3.3 , 1.9 )

-0.1 ( -1.7 , 6 )

-1.2 ( -2.6 , 2.3 )

-4.1 ( -4.6 , 0.7 )

4.8 ( 2 , 8 )

-1 ( -5.5 , 1 )

-0.2 ( -1.4 , 9.1 )

-3 ( -5.2 , 2.1 )

-0.6 ( -3.8 , 0.4 )

0.8 ( 0 , 2.1 )

1.5 ( -0.7 , 3.3 )

-1.9 ( -3.4 , 0.5 )

-0.1 ( -1.5 , 2.9 )

-0.2 ( -2.4 , 1.8 )

1 ( 0.2 , 2.3 )

1 ( -2 , 2.5 )

-2.1 ( -3.4 , 1.1 )

-0.4 ( -2.4 , 2.8 )

Quantitative indicators
for the SSPs
RCP1.9 in 2050

Count of
models
included*

Change in Natural
Land from 2010
Mkm2

5/5

2100
RCP2.6 in 2050
SSP1

5/5

2100
RCP4.5 in 2050

5/5

2100
Baseline in 2050

5/5

2100
RCP1.9 in 2050

4/5

2100
RCP2.6 in 2050
SSP2

5/5

2100
RCP4.5 in 2050
2100
Baseline in 2050

2100
RCP2.6 in 2050
SSP3

Infeasible in all assessed models

2100
RCP4.5 in 2050

3/3

2100
Baseline in 2050

4/4

2100
RCP1.9 in 2050

Infeasible in all assessed models**

2100
RCP2.6 in 2050
SSP4

3/3

2100
RCP4.5 in 2050

3/3

2100
Baseline in 2050

3/3

2100
RCP1.9 in 2050

2/4

2100
RCP2.6 in 2050
SSP5

4/4

2100
RCP4.5 in 2050

4/4

2100
Baseline in 2050
2100

4/4

Change in Forest
from 2010
Mkm2

Change in Pasture
from 2010
Mkm2

* Count of models included / Count of models attempted. One model did not provide land data and is excluded from all entries.
** One model could reach RCP1.9 with SSP4, but did not provide land data

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Figure SPM.4 Pathways linking socioeconomic development, mitigation responses and land
Future scenarios provide a framework for understanding the implications of mitigation and socioeconomics on land.
The Shared Socioeconomic Pathways (SSPs) span a range of different socioeconomic assumptions (Box SPM.1).
They are combined with Representative Concentration Pathways (RCPs) 36which imply different levels of mitigation.
The changes in cropland, pasture, bioenergy cropland, forest, and natural land from 2010 are shown. For this figure:
Cropland includes all land in food, feed, and fodder crops, as well as other arable land (cultivated area). This category
includes 1st generation non-forest bioenergy crops (e.g. corn for ethanol, sugar cane for ethanol, soybeans for
biodiesel), but excludes 2nd generation bioenergy crops. Pasture includes categories of pasture land, not only high
quality rangeland, and is based on FAO definition of "permanent meadows and pastures". Bioenergy cropland includes
land dedicated to 2nd generation energy crops (e.g., switchgrass, miscanthus, fast-growing wood species). Forest
includes managed and unmanaged forest. Natural land includes other grassland, savannah, and shrubland. Panel A:
This panel shows integrated assessment model (IAM) 37 results for SSP1, SSP2 and SSP5 at RCP1.9 38. For each
pathway, the shaded areas show the range across all IAMs; the line indicates the median across models. For RCP1.9,
SSP1, SSP2 and SSP5 include results from five, four and two IAMs respectively. Panel B: Land use and land cover
change are indicated for various SSP-RCP combinations, showing multi-model median and range (min, max). {Box
SPM.1, 1.3.2, Cross-Chapter Box 1 in Chapter 1, 2.7.2, Cross-Chapter Box 9 in Chapter 6, 6.1, 6.4.4, 7.4.2, 7.4.4,
7.4.5, 7.4.6, 7.4.7, 7.4.8, 7.5.3, 7.5.6; Cross-Chapter Box 9 in Chapter 6}

D. Action in the near-term
D 1.
Actions can be taken in the near-term, based on existing knowledge, to address
desertification, land degradation and food security while supporting longer-term responses
that enable adaptation and mitigation to climate change. These include actions to build
individual and institutional capacity, accelerate knowledge transfer, enhance technology
transfer and deployment, enable financial mechanisms, implement early warning systems,
undertake risk management and address gaps in implementation and upscaling (high
confidence). {3.6.1, 3.6.2, 3.7.2, 4.8, 5.3.3, 5.5, 5.6.4, 5.7, 6.2, 6.4, 7.3, 7.4.9, 7.6; Cross-Chapter
Box 10 in Chapter 7}

D1.1.
Near-term capacity-building, technology transfer and deployment, and enabling
financial mechanisms can strengthen adaptation and mitigation in the land sector. Knowledge and
technology transfer can help enhance the sustainable use of natural resources for food security
under a changing climate (medium confidence). Raising awareness, capacity building and
education about sustainable land management practices, agricultural extension and advisory
Representative Concentration Pathways (RCPs) are scenarios that include timeseries of emissions and
concentrations of the full suite of greenhouse gases (GHGs) and aerosols and chemically active gases, as well as land
use/land cover”.
37
Integrated Assessment Models (IAMs) integrate knowledge from two or more domains into a single framework. In
this figure, IAMs are used to assess linkages between economic, social and technological development and the
evolution of the climate system.
38
The RCP1.9 pathways assessed in this report have a 66% chance of limiting warming to 1.5C in 2100, but some
of these pathways overshoot 1.5C of warming during the 21st century by >0.1C.
36

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services, and expansion of access to agricultural services to producers and land users can
effectively address land degradation (medium confidence). {3.1, 5.7.4, 7.2, 7.3.4, 7.5.4}
Measuring and monitoring land use change including land degradation and
D1.2.
desertification is supported by the expanded use of new information and communication
technologies (cellphone based applications, cloud-based services, ground sensors, drone imagery),
use of climate services, and remotely sensed land and climate information on land resources
(medium confidence). Early warning systems for extreme weather and climate events are critical
for protecting lives and property and enhancing disaster risk reduction and management (high
confidence). Seasonal forecasts and early warning systems are critical for food security (famine)
and biodiversity monitoring including pests and diseases and adaptive climate risk management
(high confidence). There are high returns on investments in human and institutional capacities.
These investments include access to observation and early warning systems, and other services
derived from in-situ hydro-meteorological and remote sensing-based monitoring systems and data,
field observation, inventory and survey, and expanded use of digital technologies (high
confidence). {1.2, 3.6.2, 4.2.2, 4.2.4, 5.3.1, 5.3.6, 6.4, 7.3.4, 7.4.3, 7.5.4, 7.5.5, 7.6.4; CrossChapter Box 5 in Chapter 3}
Framing land management in terms of risk management, specific to land, can play
D1.3.
an important role in adaptation through landscape approaches, biological control of outbreaks of
pests and diseases, and improving risk sharing and transfer mechanisms (high confidence).
Providing information on climate-related risk can improve the capacity of land managers and
enable timely decision making (high confidence). {5.3.2, 5.3.5, 5.6.2, 5.6.3; Cross-Chapter Box 6
in Chapter 5; 5.6.5, 5.7.1, 5.7.2, 7.2.4}
D1.4.
Sustainable land management can be improved by increasing the availability and
accessibility of data and information relating to the effectiveness, co-benefits and risks of emerging
response options and increasing the efficiency of land use (high confidence). Some response
options (e.g., improved soil carbon management) have been implemented only at small-scale
demonstration facilities and knowledge, financial, and institutional gaps and challenges exist with
upscaling and the widespread deployment of these options (medium confidence). {4.8, 5.5.1, 5.5.2,
5.6.1, 5.6.5, 5.7.5, 6.2, 6.4,}
D 2.
Near-term action to address climate change adaptation and mitigation,
desertification, land degradation and food security can bring social, ecological, economic and
development co-benefits (high confidence). Co-benefits can contribute to poverty eradication
and more resilient livelihoods for those who are vulnerable (high confidence). {3.4.2, 5.7, 7.5}
Near-term actions to promote sustainable land management will help reduce land
D2.1.
and food-related vulnerabilities, and can create more resilient livelihoods, reduce land degradation
and desertification, and loss of biodiversity (high confidence). There are synergies between
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sustainable land management, poverty eradication efforts, access to market, non-market
mechanisms and the elimination of low-productivity practices. Maximising these synergies can
lead to adaptation, mitigation, and development co-benefits through preserving ecosystem
functions and services (medium confidence). {3.4.2, 3.6.3, Table 4.2, 4.7, 4.9, 4.10, 5.6, 5.7, 7.3,
7.4, 7.5, 7.6; Cross-Chapter Box 12 in Chapter 7}
Investments in land restoration can result in global benefits and in drylands can
D2.2.
have benefit-cost ratios of between three and six in terms of the estimated economic value of
restored ecosystem services (medium confidence). Many sustainable land management
technologies and practices are profitable within three to 10 years (medium confidence). While they
can require upfront investment, actions to ensure sustainable land management can improve crop
yields and the economic value of pasture. Land restoration and rehabilitation measures improve
livelihood systems and provide both short-term positive economic returns and longer-term benefits
in terms of climate change adaptation and mitigation, biodiversity and enhanced ecosystem
functions and services (high confidence). {3.6.1, 3.6.3, 4.8.1, 7.2.4, 7.2.3, 7.3.1, 7.4.6, CrossChapter Box 10 in Chapter 7}
Upfront investments in sustainable land management practices and technologies
D2.3.
can range from about USD 20 ha-1 to USD 5000 ha-1, with a median estimated to be around USD
500 ha-1. Government support and improved access to credit can help overcome barriers to
adoption, especially those faced by poor smallholder farmers (high confidence). Near-term change
to balanced diets (see B6.2) can reduce the pressure on land and provide significant health cobenefits through improving nutrition (medium confidence). {3.6.3, 4.8, 5.3, 5.5, 5.6, 5.7, 6.4, 7.4.7,
7.5.5; Cross-Chapter Box 9 in Chapter 6}

D 3.
Rapid reductions in anthropogenic GHG emissions across all sectors following
ambitious mitigation pathways reduce negative impacts of climate change on land
ecosystems and food systems (medium confidence). Delaying climate mitigation and
adaptation responses across sectors would lead to increasingly negative impacts on land and
reduce the prospect of sustainable development (medium confidence). {Box SPM.1, Figure
SPM.2, 2.5, 2.7, 5.2, 6.2, 6.4, 7.2, 7.3.1, 7.4.7, 7.4.8, 7.5.6; Cross-Chapter Box 9 in Chapter 6,
Cross-Chapter Box 10 in Chapter 7}
Delayed action across sectors leads to an increasing need for widespread
D3.1.
deployment of land-based adaptation and mitigation options and can result in a decreasing
potential for the array of these options in most regions of the world and limit their current and
future effectiveness (high confidence). Acting now may avert or reduce risks and losses, and
generate benefits to society (medium confidence). Prompt action on climate mitigation and
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adaptation aligned with sustainable land management and sustainable development depending on
the region could reduce the risk to millions of people from climate extremes, desertification, land
degradation and food and livelihood insecurity (high confidence). {1.3.5, 3.4.2, 3.5.2, 4.1.6, 4.7.1,
4.7.2, 5.2.3, 5.3.1, 6.3, 6.5, 7.3.1}
In future scenarios, deferral of GHG emissions reductions implies trade-offs
D3.2.
leading to significantly higher costs and risks associated with rising temperatures (medium
confidence). The potential for some response options, such as increasing soil organic carbon,
decreases as climate change intensifies, as soils have reduced capacity to act as sinks for carbon
sequestration at higher temperatures (high confidence). Delays in avoiding or reducing land
degradation and promoting positive ecosystem restoration risk long-term impacts including rapid
declines in productivity of agriculture and rangelands, permafrost degradation and difficulties in
peatland rewetting (medium confidence). {1.3.1, 3.6.2, 4.8, 4.9, 4.9.1, 5.5.2, 6.3, 6.4, 7.2, 7.3;
Cross-Chapter Box 10 in Chapter 7}
Deferral of GHG emissions reductions from all sectors implies trade-offs including
D3.3.
irreversible loss in land ecosystem functions and services required for food, health, habitable
settlements and production, leading to increasingly significant economic impacts on many
countries in many regions of the world (high confidence). Delaying action as is assumed in high
emissions scenarios could result in some irreversible impacts on some ecosystems, which in the
longer-term has the potential to lead to substantial additional GHG emissions from ecosystems
that would accelerate global warming (medium confidence). {1.3.1, 2.5.3, 2.7, 3.6.2, 4.9, 4.10.1,
5.4.2.4, 6.3, 6.4, 7.2, 7.3; Cross-Chapter Box 9 in Chapter 6, Cross-Chapter Box 10 in Chapter 7}

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