Editing IPCC:AR6/WGII/Chapter-5 (section)

=== 5.4.1 Observed Impacts ===

<div id="h2-8-siblings" class="h2-siblings"></div>

<div id="5.4.1.1" class="h3-container"></div>

<span id="observed-impacts-on-major-crops"></span>
==== 5.4.1.1 Observed impacts on major crops ====

<div id="h3-1-siblings" class="h3-siblings"></div>

AR5 [[IPCC:Wg2:Chapter:Chapter-7|Chapter 7]] ( [[#Porter--2014|Porter et al., 2014]] ) stated with confidence that warmer temperatures have benefited agriculture in the high latitudes, and more evidence has been published to support this statement. Typical examples include pole-ward expansion of growing areas and reduction of cold stress in East Asia and North America (Table SM5.1).

Recent warming trends have generally shortened the life cycle of major crops ( ''high confidence'' ) ( [[#Zhang--2014|Zhang et al., 2014]] ; [[#Shen--2015|Shen and Liu, 2015]] ; [[#Ahmed--2018|Ahmed et al., 2018]] ; [[#Liu--2018c|Liu et al., 2018c]] ; [[#Tan--2021|Tan et al., 2021]] ). Some studies, however, observed prolonged crop growth duration despite the warming trends ( [[#Mueller--2015|Mueller et al., 2015]] ; [[#Tao--2016|Tao et al., 2016]] ; [[#Butler--2018|Butler et al., 2018]] ; [[#Zhu--2018b|Zhu et al., 2018b]] ) because of shifts in planting dates and/or adoption of longer-duration cultivars in mid-to-high latitudes. Conversely, in mid-to-low latitudes in Asia, a review study found that farmers favoured early maturing cultivars to reduce risks of damages due to drought, flood and/or heat ( [[#Shaffril--2018|Shaffril et al., 2018]] ), suggesting that region-specific adaptations are already occurring in different parts of the world ( ''high confidence'' ).

Global yields of major crops per unit land area have increased 2.5- to 3-fold since 1960. Plant breeding, fertilisation, irrigation and integrated pest management have been the major drivers, but many studies have found significant impacts from recent climate trends on crop yield ( ''high confidence'' ) (Figure 5.3; see [[#5.2.1|Section 5.2.1]] for the change attributable to anthropogenic climate change).

Climate impacts for the past 20–50 years differ by crops and regions. Positive effects have been identified for rice and wheat in Eastern Asia, and for wheat in Northern Europe. The effects are mostly negative in Sub-Saharan Africa, South America and Caribbean, Southern Asia, and Western and Southern Europe. Climate factors that affected long-term yield trends also differ between regions. For example, in Western Africa, 1°C warming above preindustrial climate has increased heat and rainfall extremes, and reduced yields by 10–20% for millet and 5–15% for sorghum (Sultan et al., 2019). In Australia, declined rainfall and increased temperatures reduced yield potential of wheat by 27%, accounting for the low yield growth between 1990 and 2015 ( [[#Hochman--2017|Hochman et al., 2017]] ). In Southern Europe, climate warming has negatively impacted yields of almost all major crops, leading to recent yield stagnation ( [[#Moore--2015|Moore and Lobell, 2015]] ; [[#Agnolucci--2020|Agnolucci and De Lipsis, 2020]] ; [[#Brás--2021|Brás et al., 2021]] ).

[[#Ortiz-Bobea--2021|Ortiz-Bobea et al. (2021)]] analysed agricultural total factor productivity (TFP), defined as the ratio of all agricultural outputs to all agricultural inputs, and found that, while TFP has increased between 1961 and 2015, the climate change trends reduced global TFP growth by a cumulative 21% over a 55-year period relative to TFP growth under counterfactual non-climate change conditions. Greater effects (30–33%) were observed in Africa, Latin America and the Caribbean (Figure 5.3).

<div id="_idContainer010" class="Figure"></div>

[[File:dbf41cc585e3e4c6655b7bef7aa97b71 IPCC_AR6_WGII_Figure_5_003.png]]

'''Figure 5.3 |''' '''Synthesis of literature on observed impacts of climate change on productivity by crop type and region.''' The figure draws on &gt;150 articles categorized by: agriculture total factor productivity including literature estimating all agricultural outputs in a region; major crop species including literature assessing yield changes in the four major crops; crop categories including productivity changes (yield, quality and other perceived changes) in a range of crops with different growth habits. The assessment uses literature published since AR5, although the timespan often extends prior to 2014. The direction of the effect and the confidence are based on the reported impacts and attribution, and on the number of articles. See SM5.1 and SM5.2 for details.

Climate variability is a major source of variation in crop production ( [[#Ray--2015|Ray et al., 2015]] ; [[#Iizumi--2016|Iizumi and Ramankutty, 2016]] ; [[#Frieler--2017|Frieler et al., 2017]] ; [[#Cottrell--2019|Cottrell et al., 2019]] )(Table SM5.1). Weather signals in yield variability are generally stronger in productive regions than in the less productive regions ( [[#Frieler--2017|Frieler et al., 2017]] ), where other yield constraints exist such as pests, diseases and poor soil fertility ( [[#Mills--2018|Mills et al., 2018]] ; 5.2.2). Nevertheless, yield variability in less productive regions has severe impacts on local food availability and livelihood ( ''high confidence'' ) ( [[#FAO--2021|FAO, 2021]] ).

Climate-related hazards that cause crop losses are increasing ( ''medium evidence'' , ''high agreement'' ) ( [[#Cottrell--2019|Cottrell et al., 2019]] ; [[#Mbow--2019|Mbow et al., 2019]] ; [[#Brás--2021|Brás et al., 2021]] ; [[#FAO--2021|FAO, 2021]] ; [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). Drought-related yield losses have occurred in about 75% of the global harvested area ( [[#Kim--2019b|Kim et al., 2019b]] ) and increased in recent years ( [[#Lesk--2016|Lesk et al., 2016]] ). Heatwaves have reduced yields of wheat ( [[#Zampieri--2017|Zampieri et al., 2017]] ) and rice ( [[#Liu--2019b|Liu et al., 2019b]] ) ''.'' The combined effects of heat and drought decreased global average yields of maize, soybeans and wheat by 11.6%, 12.4% and 9.2%, respectively ( [[#Matiu--2017|Matiu et al., 2017]] ). In Europe, crop losses due to drought and heat have tripled over the last five decades ( [[#Brás--2021|Brás et al., 2021]] ), pointing to the importance of assessing multiple stresses. Globally, floods also increased in the past 50 years, causing direct damages to crops and indirectly reduced yields by delaying planting, which cost 4.5 billion USD in the 2010 flood in Pakistan and 572 million USD in the 2015 flood in Myanmar ( [[#FAO--2021|FAO, 2021]] ).

<div id="5.4.1.2" class="h3-container"></div>

<span id="observed-impacts-on-other-crops-vegetables-fruit-nut-and-fibre"></span>
==== 5.4.1.2 Observed impacts on other crops (vegetables, fruit, nut and fibre) ====

<div id="h3-2-siblings" class="h3-siblings"></div>

The impact of climate change on these diverse crop types is under-researched and uncertain ( [[#Manners--2018|Manners and van Etten, 2018]] ; [[#Alae-Carew--2020|Alae-Carew et al., 2020]] ); there are reports of positive impacts in some cases, but overall the observed impacts are negative across all crop categories (Figure 5.3).

Above-ground annual crops consumed as vegetables, fruits or salad are essential for food security and nutrition (5.12). In temperate regions, climate change can result in higher yields ( [[#Potopová--2017|Potopová et al., 2017]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ), while in subtropical/tropical regions, negative impacts from heat and drought take precedence ( [[#Scheelbeek--2018|Scheelbeek et al., 2018]] ). Different species have different sensitivities to heat and drought ( [[#Prasad--2017|Prasad et al., 2017]] ; [[#Scheelbeek--2018|Scheelbeek et al., 2018]] ) and to combinations of stresses ( [[#Zandalinas--2018|Zandalinas et al., 2018]] ). Above-ground vegetables are especially vulnerable to heat and drought stress during pollination and fruit set, resulting in negitive impacts on yield ( [[#Daryanto--2017|Daryanto et al., 2017]] ; [[#Sita--2017|Sita et al., 2017]] ; [[#Brás--2021|Brás et al., 2021]] ) and harvest quality ( [[#Mattos--2014|Mattos et al., 2014]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ). Growers have already seen negative impacts from the expansion of pest and disease agents due to warming ( [[#5.4.1.3|Section 5.4.1.3]] ; Figure 5.3).

Below-ground vegetables include starchy roots and tubers that form a regular diet in many parts of the tropics and subtropics. Warming and climate variability has altered the rate of tuber development, with yield impacts varying by location, including yield increases in some cases ( [[#Shimoda--2018|Shimoda et al., 2018]] ; [[#Ray--2019|Ray et al., 2019]] ). These crops are considered stress tolerant but are more sensitive to drought than cereals ( [[#Daryanto--2017|Daryanto et al., 2017]] ). Impacts on water supply are critical as root crops are water-demanding for long periods, and highly sensitive to drought and heat events during tuber initiation ( [[#Dua--2013|Dua et al., 2013]] ; [[#Potopová--2017|Potopová et al., 2017]] ; [[#Brás--2021|Brás et al., 2021]] ).

Among perennial tree crops, only grapevine, olive, almond, apple, coffee and cocoa have received significant research attention. Concerns about climate impacts on harvest quality are widespread (Figure 5.3) ( [[#Barnuud--2014|Barnuud et al., 2014]] ; [[#Bonada--2015|Bonada et al., 2015]] ). In higher-latitude regions, the primary concern is the effect of temperature variability on harvest stability, pests and diseases and phenology (including fulfilment of winter chill requirements and risks due to early emergence in spring), ( [[#El%20Yaacoubi--2014|El Yaacoubi et al., 2014]] ; [[#Ramírez--2015|Ramírez and Kallarackal, 2015]] ; [[#Santos--2017|Santos et al., 2017]] ; [[#Gitea--2019|Gitea et al., 2019]] ). In lower-latitude regions, information is limited, but studies are focused on increased tree mortality and yield loss due to drought, heat and impacts from variability in the timing of the wet and dry seasons ( [[#Glenn--2013|Glenn et al., 2013]] ; [[#Ramírez--2015|Ramírez and Kallarackal, 2015]] ); see Box 5.7). In fruit trees, warming and climate variability have already affected fruit quality, such as acidity and texture in apples, or skin colour in grape berries ( [[#Sugiura--2013|Sugiura et al., 2013]] ; [[#Sugiura--2018|Sugiura et al., 2018]] ). The reliability and stability of harvests has been impacted by climate variability, changes in the distribution of pests and pathogens ( [[#Seidel--2014|Seidel, 2014]] ; [[#Bois--2017|Bois et al., 2017]] ), and the mismatch of important phenological events (such as bud emergence and flowering) ( [[#Guo--2015|Guo and Shen, 2015]] ; [[#Legave--2015|Legave et al., 2015]] ; [[#Ito--2018|Ito et al., 2018]] ; [[#Vitasse--2018|Vitasse et al., 2018]] ). Perennial crops are particularly vulnerable to these impacts as they are exposed throughout the year, with little potential for growers to adjust planting date or location. Negative impacts via disruption to phenology and pest dynamics are best studied in grapevine (see Box 5.2).

Among the fibre crops, cotton is particularly well studied. As cotton is heat tolerant and yield increases with extra plant growth, positive effects of increasing temperature are expected, but observed impacts have been mixed due to negative impacts on phenology and plant water status ( [[#Traore--2013|Traore et al., 2013]] ; [[#Chen--2015a|Chen et al., 2015a]] ; [[#Cho--2017|Cho and McCarl, 2017]] ). Negative impacts of climate change due to proliferation of the pest cotton bollworm are widely reported ( [[#Ouyang--2014|Ouyang et al., 2014]] ; [[#Huang--2020|Huang and Hao, 2020]] ).

The impacts of climate change on water availability (rainfall and irrigation supply) are an emerging issue. Increased occurrence of drought combined with limited access to irrigation water is already a key constraint; for example, Californian almonds are predicted to increase their potential geographical range under climate warming ( [[#Parker--2018|Parker, 2018]] ), yet a trend of increasing drought has already resulted in trees being removed due to lack of access to irrigation water ( [[#Keppen--2015|Keppen and Dutcher, 2015]] ; [[#Kerr--2018|Kerr et al., 2018]] ; [[#Reisman--2019|Reisman, 2019]] ).

<div id="5.4.1.3" class="h3-container"></div>

<span id="observed-impacts-on-pests-diseases-and-weeds"></span>
==== 5.4.1.3 Observed impacts on pests, diseases and weeds ====

<div id="h3-3-siblings" class="h3-siblings"></div>

AR5 and SRCCL (IPCC, 2019) indicated that more frequent outbreaks and area expansion of pests and diseases are serious concerns under climate change but are under-researched because of the difficulties in assessing multi-species interactions ( [[#Porter--2014|Porter et al., 2014]] ; [[#Mbow--2019|Mbow et al., 2019]] ). High-quality historical and current observational data to detect changes in pests and diseases attributable to recent trends in climate are still limited.

Bebber (2013) found significant poleward expansions of many important groups of crop pests and pathogens since 1960, with an average shift of 2.7 km yr −1 . Different pest species populations respond differently to ongoing climate change, with some shifting, contracting or expanding their current distribution range and others persisting or disappearing in their current range ( ''high confidence'' ). These asymmetric distribution changes can create novel species combinations or decouple existing ones ( [[#Pecl--2017|Pecl et al., 2017]] ; [[#Hobbs--2018|Hobbs et al., 2018]] ), but their consequences on future crop production and food security are hard to predict. Multi-species climate change experiments are rare ( [[#Bonebrake--2018|Bonebrake et al., 2018]] ), but one study shows that under future climates different pest assemblages of interacting species may alter levels of damage to crops compared with that by only one species ( [[#Crespo-Perez--2015|Crespo-Perez et al., 2015]] ). Some studies highlight the importance of location-specific species interactions for more realistic projections of pest distribution, performance and damage to crops, which in turn would allow more effective prevention and pest control strategies ( [[#Wilson--2015|Wilson et al., 2015]] ; [[#Carrasco--2018|Carrasco et al., 2018]] ).

Weeds are recognised as a primary constraint on crop production ( [[#Oerke--2006|Oerke, 2006]] ), rangelands ( [[#DiTomaso--2017|DiTomaso et al., 2017]] ) and forests ( [[#Webster--2006|Webster et al., 2006]] ). Climate change could favour the growth and development of weeds over crops with negative consequences for desired plants in managed systems ( ''medium evidence'' , ''high agreement'' ) ( [[#Peters--2014|Peters et al., 2014]] ; [[#Ziska--2016|Ziska and McConnell, 2016]] ). First, changes in temperature and precipitation alter the range, composition and competitiveness of native and invasive weeds ( [[#Bradley--2010|Bradley et al., 2010]] ). Second, rising concentrations of CO 2 enhance growth of C 3 species (~85% of plant species, including many weeds) ( [[#Ogren--1982|Ogren and Chollet, 1982]] ; [[#Ziska--2003|Ziska, 2003]] ), and increase plant water use efficiency with potentially strong effects on invasive plant species establishment ( [[#Smith--2000|Smith et al., 2000]] ; [[#Belote--2004|Belote et al., 2004]] ; [[#Blumenthal--2013|Blumenthal et al., 2013]] ).

Some invasive species within unmanaged areas will expand further, proliferate and be more competitive under climate change as they may benefit from increased resource ability (e.g., additional CO 2 , enhanced precipitation) ( [[#Bradley--2010|Bradley et al., 2010]] ; [[#Kathiresan--2016|Kathiresan and Gualbert, 2016]] ; [[#Merow--2017|Merow et al., 2017]] ; [[#Ramesh--2017|Ramesh et al., 2017]] ; [[#Waryszak--2018|Waryszak et al., 2018]] ), which will make chemical weed control more problematic ( ''medium evidence'' , ''high agreement'' ) ( [[#Waryszak--2018|Waryszak et al., 2018]] ; [[#Ziska--2020|Ziska, 2020]] ). The range of other invasive weeds may become static, or even decline ( [[#Bradley--2016|Bradley et al., 2016]] ; [[#Buckley--2017|Buckley and Csergo, 2017]] ). A recent meta-analysis also supports that invasive plants respond more favourably to elevated CO 2 concentrations and elevated temperatures than native plants ( [[#Korres--2016|Korres et al., 2016]] ; [[#Liu--2017|Liu et al., 2017]] ). Movement of invasive species into low-fertility areas, however, could provide resource opportunities, especially if agriculture in those areas is limited ( [[#Randriambanona--2019|Randriambanona et al., 2019]] ).

Rising CO 2 concentrations and climate change could reduce herbicide efficacy ( ''medium evidence'' , ''high agreement'' ). These reductions may be associated with physical environmental changes (precipitation, wind speed) that influence herbicide coverage ( [[#Ziska--2016|Ziska, 2016]] ) as well as direct effects of CO 2 on plant biochemistry and herbicide resistance ( [[#Refatti--2019|Refatti et al., 2019]] ). Increasing CO 2 levels and altered temperature and precipitation are therefore projected to affect all aspects of weed biology ( [[#Peters--2014|Peters et al., 2014]] ; [[#Ziska--2016|Ziska and McConnell, 2016]] ), including establishment ( [[#Bradley--2016|Bradley et al., 2016]] ), competition ( [[#Fernando--2019|Fernando et al., 2019]] ), distribution, ( [[#Castellanos-Frías--2016|Castellanos-Frías et al., 2016]] ) and management ( [[#Waryszak--2018|Waryszak et al., 2018]] ).

A warmer climate increases the need for pesticides ( [[#Shakhramanyan--2013|Shakhramanyan et al., 2013]] ; [[#Ziska--2014|Ziska, 2014]] ; [[#Delcour--2015|Delcour et al., 2015]] ; [[#Zhang--2018|Zhang et al., 2018]] ). Increases in temperature and CO 2 concentration may reduce pesticide efficiency by altering its metabolism, or accelerating detoxification ( [[#Matzrafi--2016|Matzrafi et al., 2016]] ; [[#Matzrafi--2019|Matzrafi, 2019]] ). Intense rainfall also reduces persistence ( [[#Delcour--2015|Delcour et al., 2015]] ). Invasive pests and pathogens impose an additional cost for the society ( [[#Bradshaw--2016|Bradshaw et al., 2016]] ). Rapid and large-scale dispersal of pests is already a major threat to food security, as exemplified by the recent outbreak of desert locusts (see Box 5.8), indicating the importance of international cooperation. Taken together, the need for control of pests, disease and weeds will increase under climate change ( ''medium evidence'' , ''high agreement'' ). The use of toxic agricultural chemicals also has human health and environmental risks ( [[#Whitmee--2015|Whitmee et al., 2015]] ; [[#IPBES--2019|IPBES, 2019]] ). Surveillance for monitoring pest distribution and damages, climate-relevant pest risk analysis, and climate-smart strategies for controlling pests with minimal impacts on human and environmental health are important tools in the face of climate change ( [[#IPPC%20Secretariat--2021|IPPC Secretariat, 2021]] ).

<div id="5.4.1.4" class="h3-container"></div>

<span id="observed-impacts-of-ozone-on-crops"></span>
==== 5.4.1.4 Observed impacts of ozone on crops ====

<div id="h3-4-siblings" class="h3-siblings"></div>

Tropospheric (i.e., the lowest 6–10 km of the atmosphere) ozone exacerbates negative impacts of climate change ( ''high confidence'' ) ( [[#Mattos--2014|Mattos et al., 2014]] ; [[#Chuwah--2015|Chuwah et al., 2015]] ; [[#McGrath--2015|McGrath et al., 2015]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Mills--2018|Mills et al., 2018]] ; [[#Scheelbeek--2018|Scheelbeek et al., 2018]] ). Ozone is an air pollutant and short-lived GHG that affects air quality and global climate. It is a strong oxidant that reduces physiological functions, yield and quality of crops and animals. Surface ozone concentration has increased substantially since the late 19 th century ( [[#Cooper--2014|Cooper et al., 2014]] ; Forster et al., 2021; [[#Gulev--2021|Gulev et al., 2021]] ; [[#Szopa--2021|Szopa et al., 2021]] ) and in some locations and times reaches levels that harm plants, animals and human ( ''high confidence'' ) ( [[#Fleming--2018|Fleming et al., 2018]] ).

[[#Mills--2018|Mills (2018)]] estimated global distributions of current yield losses of major crops due to ozone, pest and diseases, heat, and aridity (Figure 5.4). Ozone-induced yield losses in 2010–2012 averaged 12.4%, 7.1%, 4.4% and 6.1% for soybean, wheat, rice and maize, respectively. Spatial variation in yield losses is similar among different stresses; areas with a large loss due to ozone are also at high risk of yield losses due to pest and diseases and heat. Many vegetable crops are also susceptible to ozone, which will adversely impact quality and quantity ( [[#Mattos--2014|Mattos et al., 2014]] ; [[#Bisbis--2018|Bisbis et al., 2018]] ; [[#Scheelbeek--2018|Scheelbeek et al., 2018]] ).

<div id="_idContainer013" class="Figure"></div>

[[File:9cb2c3164051a26bb5ff3bf260e4b9b7 IPCC_AR6_WGII_Figure_5_004.png]]

'''Figure 5.4 |''' '''The global effects of five biotic and abiotic stresses on soybean and wheat.''' All data are presented for the 1 × 1° (latitude and longitude) grid squares where the mean production of soybean or wheat was &gt;500 tonnes (0.0005 Tg). The effect of each stress on yield is presented as a Yield Constraint Score (YCS) on a scale of 1–5, where 5 is the highest level of stress from ozone, pests and diseases, heat stress and aridity ( [[#Mills--2018|Mills et al., 2018]] ). Data are available at [[#Sharps--2020|Sharps et al. (2020)]] . See Annex I: Global to Regional Atlas for all four crops.

The estimated yield loss does not account for interactions with other climatic factors. Temperatures enhance not only ozone production but also ozone uptake by plants, exacerbating yield and quality damage. Burney (2014) estimated current yield losses due to the combined effects of ozone and heat in India at 36% for wheat and 20% for rice. [[#Schauberger--2019a|Schauberger et al. (2019a)]] found global yield losses, ranging from 2% to 10% for soybean and 0% to 39% for wheat with a model that accounts for temperature, water and CO 2 concentration on ozone uptake.

<div id="box-5.1:-evidence-for-simultaneous-crop-failures-due-to-climate-change" class="h2-container box-container"></div>

'''Box 5.1: Evidence for Simultaneous Crop Failures Due to Climate Change'''
<div id="h2-60-siblings" class="h2-siblings"></div>

Simultaneous yield losses across major producing regions can be a threat to food security but had not been quantified by the time of AR5. Large-scale sea surface temperature (SST) oscillations greatly influence global yield of major crops ( ''high confidence'' ) ( [[#Anderson--2019b|Anderson et al., 2019b]] ; [[#Najafi--2019|Najafi et al., 2019]] ; [[#Ubilava--2019|Ubilava and Abdolrahimi, 2019]] ; [[#Heino--2020|Heino et al., 2020]] ; [[#Iizumi--2021b|Iizumi et al., 2021b]] ) and food prices ( [[#Ubilava--2018|Ubilava, 2018]] ). Some studies showed that crop yields in different regions covaried with SST oscillations, suggesting occurrences of tele-connected yield failures (crop losses caused by related factors in distant regions; Table Box 5.1.1) ( ''medium confidence'' ). Evidence of synchronised crop failures increasing with ongoing climate change is still limited.

'''Table Box 5.1.1 |''' A summary of peer-review papers detecting synchronised yield losses.

{| class="wikitable"
|-
! Regions/ commodities

! Period studied

! Observed impacts

! Climate driver

! Evidence for multiple breadbasket failures

! Evidence for increasing risks due to multiple breadbasket failures

! Reference

|-
| Global breadbaskets for maize, rice, sorghum and soybean

| 1961–2013

| Not only yields of each crop covaried in many countries, but also those of different crops, maize in particular, covaried with other crops.

| SST anomalies, atmospheric and oceanic in- dices, air temperature anomalies and Palmer Drought Severity Index

| High

| NA

| Najafi et al. (2019)

|-
| Global breadbaskets for wheat, soybean and maize

| 1980–2010

| Climate modes (El Niño-Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), tropical Atlantic variability (TAV) and the North Atlantic Oscillation (NAO)) account for 18%, 7% and 6% of global maize, wheat and soybean production variability, respectively. ENSO events sometimes offset yield reductions in some places by increases in other places (e.g., soybean yields in the USA and southeast South America).

Since 1961, ENSO in 1983 was the only climate mode that showed global synchronous crop failures.

| Climate modes

| Medium (1983)

| NA

| [[#Anderson--2019b|Anderson et al. (2019b)]]

|-
| Global breadbaskets for wheat, soybean and maize

|
| Climate modes induce yield variability in major breadbaskets, e.g., ENSO affects about half of maize and wheat areas. IOD and ENSO influence wheat in Australia. ENSO affects soybean in northern South America.

| Climate modes

| Medium

| NA

| [[#Heino--2020|Heino et al. (2020)]]

|-
| 67 maize producing countries

| 1961–2017

| SST anomalies from the 1980–2010 base period in the Niño3.4 region, a rectangular area bounded by 120°W–170°W and 5°S–5° is used as a driver. Maize yields are tele-connected among the southeastern tier of Sub-Saharan Africa, as well as Central America, South Asia and Australia. A 1° increase in SST reduced maize yield by up to 20% in these countries.

| Climate modes (SST), precipitation

| Medium

| NA

| [[#Ubilava--2019|Ubilava and Abdolrahimi (2019)]]

|-
| Global breadbasket (the USA, Argentina, Europe, Russia/Ukraine, China, India, Australia, Indonesia and Brazil)

| 1967–2012

| Likelihood of simultaneous climate risks increased from 1967–1990 to 1991–2012 in the global breadbasket (lower 25 th yield deviation percentile events at province level) for wheat, soybean and maize, but not rice.

Likelihood of simultaneous climate risks increased from 1967–1990 to 1991–2012 in China (lower 25 th yield deviation percentile events at province level).

| Unspecified

| Medium

| Medium

| [[#Gaupp--2020|Gaupp et al. (2020)]]

|-
| Global

| 1961–2008

| Synchronous yield losses among major breadbaskets within each commodity, such as maize and soybean, decreased between 1961 and 2008. In contrast, synchronous yield variation between crops has increased. Under a scenario of synchronisation of all four crops, the global maximum production losses for rice, wheat, soybean and maize are estimated to reach between −17% and −34%.

| Unspecified

| Medium

| Medium

| [[#Mehrabi--2019|Mehrabi and Ramankutty (2019)]]

|}

<div id="5.4.2" class="h2-container"></div>

<span id="assessing-vulnerabilities-within-production-systems"></span>