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

==== 5.2.2.1 Impacts on crop production ====

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'''Observed impacts''' . Since AR5, there have been further studies that document impacts of climate change on crop production and related variables (Supplementary Material Table SM5.3). There have also been a few studies that demonstrate a strengthening relationship between observed climate variables and crop yields that indicate future expected warming will have severe impacts on crop production (Mavromatis 2015 <sup>[[#fn:r182|182]]</sup> ; Innes et al. 2015 <sup>[[#fn:r183|183]]</sup> ). At the global scale, Iizumi et al. (2018) <sup>[[#fn:r184|184]]</sup> used a counterfactual analysis and found that climate change between 1981 and 2010 has decreased global mean yields of maize, wheat, and soybeans by 4.1, 1.8 and 4.5%, respectively, relative to preindustrial climate, even when CO <sub>2</sub> fertilisation and agronomic adjustments are considered. Uncertainties (90% probability interval) in the yield impacts are –8.5 to +0.5% for maize, –7.5 to +4.3% for wheat, and –8.4 to –0.5% for soybeans. For rice, no significant impacts were detected. This study suggests that climate change has modulated recent yields on the global scale and led to production losses, and that adaptations to date have not been sufficient to offset the negative impacts of climate change, particularly at lower latitudes.

Dryland settlements are perceived as vulnerable to climate change with regard to food security, particularly in developing countries; such areas are known to have low capacities to cope effectively with decreasing crop yields (Shah et al. 2008 <sup>[[#fn:r185|185]]</sup> ; Nellemann et al. 2009 <sup>[[#fn:r186|186]]</sup> ). This is of concern because drylands constitute over 40% of the earth’s land area, and are home to 2.5 billion people (FAO et al. 2011 <sup>[[#fn:r187|187]]</sup> ).

''Australia''

In Australia, declines in rainfall and rising daily maximum temperatures based on simulations of 50 sites caused water-limited yield potential to decline by 27% from 1990 to 2015, even though elevated atmospheric CO <sub>2</sub> concentrations had a positive effect (Hochman et al. 2017 <sup>[[#fn:r188|188]]</sup> ). In New South Wales, high-temperature episodes during the reproduction stage of crop growth were found to have negative effects on wheat yields, with combinations of low rainfall and high temperatures being the most detrimental (Innes et al. 2015 <sup>[[#fn:r189|189]]</sup> ).

''Asia''

There are numerous studies demonstrating that climate change is affecting agriculture and food security in Asia. Several studies with remote sensing and statistical data have examined rice areas in north-eastern China, the northernmost region of rice cultivation, and found expansion over various time periods beginning in the 1980s, with most of the increase occurring after 2000 (Liu et al. 2014 <sup>[[#fn:r190|190]]</sup> ; Wang et al. 2014 <sup>[[#fn:r191|191]]</sup> ; Zhang et al. 2017 <sup>[[#fn:r192|192]]</sup> ). Rice yield increases have also been found over a similar period (Wang et al. 2014 <sup>[[#fn:r193|193]]</sup> ). Multiple factors, such as structural adjustment, scientific and technological progress, and government policies, along with regional warming (1.43°C in the past century) (Fenghua et al. 2006 <sup>[[#fn:r194|194]]</sup> ) have been put forward as contributing to the observed expanded rice areas and yield in the region. Shi et al. (2013) <sup>[[#fn:r195|195]]</sup> indicate that there is a partial match between climate change patterns and shifts in extent and location of the rice-cropping area (2000–2010).

There have also been documented changes in winter wheat phenology in Northwest China (He 2015 <sup>[[#fn:r196|196]]</sup> ). Consistent with this finding, dates of sowing and emergence of spring and winter wheat were delayed, dates of anthesis and maturity was advanced, and length of reproductive growth period was prolonged from 1981–2011 in a study looking at these crops across China (Liu et al. 2018b <sup>[[#fn:r197|197]]</sup> ). Another study looking in Northwest China demonstrated that there have been changes in the phenology and productivity of spring cotton (Huang and Ji 2015 <sup>[[#fn:r198|198]]</sup> ). A counterfactual study looking at wheat growth and yield in different climate zones of China from 1981–2009 found that impacts were positive in northern China and negative in southern China (Tao et al. 2014 <sup>[[#fn:r199|199]]</sup> ). Temperature increased across the zones while precipitation changes were not consistent (Tao et al. 2014 <sup>[[#fn:r200|200]]</sup> ).

Similar crop yield studies focusing on India have found that warming has reduced wheat yields by 5.2% from 1981 to 2009, despite adaptation (Gupta et al. 2017 <sup>[[#fn:r201|201]]</sup> ), and that maximum daytime temperatures have risen along with some night-time temperatures (Jha and Tripathi 2017 <sup>[[#fn:r202|202]]</sup> ).

Agriculture in Pakistan has also been affected by climate change. From 1980 to 2014, spring maize growing periods have shifted an average of 4.6 days per decade earlier, while sowing of autumn maize has been delayed 3.0 days per decade (Abbas et al. 2017 <sup>[[#fn:r203|203]]</sup> ). A similar study with sunflower showed that increases in mean temperature from 1980 to 2016 were highly correlated with shifts in sowing, emergence, anthesis, and maturity for fall and spring crops (Tariq et al. 2018 <sup>[[#fn:r204|204]]</sup> ).

Mountain people in the Hindu-Kush Himalayan region encompassing parts of Pakistan, India, Nepal, and China, are particularly vulnerable to food insecurity related to climate change because of poor infrastructure, limited access to global markets, physical isolation, low productivity, and hazard exposure, including Glacial Lake Outburst Floods (GLOFs) (Rasul et al. 2019 <sup>[[#fn:r205|205]]</sup> ; Rasul 2010 <sup>[[#fn:r206|206]]</sup> ; Tiwari and Joshi 2012 <sup>[[#fn:r207|207]]</sup> ; Huddleston et al. 2003 <sup>[[#fn:r208|208]]</sup> ; Ward et al. 2013 <sup>[[#fn:r209|209]]</sup> ; FAO 2008 <sup>[[#fn:r210|210]]</sup> ; Nautiyal et al. 2007 <sup>[[#fn:r211|211]]</sup> ; Din et al. 2014 <sup>[[#fn:r212|212]]</sup> ). Surveys have been conducted to determine how climate-related changes have affected food security (Hussain et al. 2016 <sup>[[#fn:r213|213]]</sup> ; Shrestha and Nepal 2016 <sup>[[#fn:r214|214]]</sup> ) with results showing that the region is experiencing an increase in extremes, with farmers facing more frequent floods as well as prolonged droughts with ensuing negative impacts on agricultural yields and increases in food insecurity (Hussain et al. 2016 <sup>[[#fn:r215|215]]</sup> ; Manzoor et al. 2013 <sup>[[#fn:r216|216]]</sup> ).

''South America''

In another mountainous region, the Andes, inhabitants are also beginning to experience changes in the timing, severity, and patterns of the annual weather cycle. Data collected through participatory workshops, semi-structured interviews with agronomists, and qualitative fieldwork from 2012 to 2014 suggest that in Colomi, Bolivia, climate change is affecting crop yields and causing farmers to alter the timing of planting, their soil management strategies, and the use and spatial distribution of crop varieties (Saxena et al. 2016 <sup>[[#fn:r217|217]]</sup> ). In Argentina, there has also been an increase in yield variability of maize and soybeans (Iizumi and Ramankutty 2016 <sup>[[#fn:r218|218]]</sup> ). These changes have had important implications for the agriculture, human health, and biodiversity of the region (Saxena et al. 2016 <sup>[[#fn:r219|219]]</sup> ).

''Africa''

In recent years, yields of staple crops such as maize, wheat, sorghum, and fruit crops, such as mangoes, have decreased across Africa, widening food insecurity gaps (Ketiem et al. 2017 <sup>[[#fn:r220|220]]</sup> ). In Nigeria, there have been reports of climate change having impacts on the livelihoods of arable crop farmers (Abiona et al. 2016 <sup>[[#fn:r221|221]]</sup> ; Ifeanyi-obi et al. 2016 <sup>[[#fn:r222|222]]</sup> ; Onyeneke 2018 <sup>[[#fn:r223|223]]</sup> ). The Sahel region of Cameroon has experienced an increasing level of malnutrition. This is partly due to the impact of climate change since harsh climatic conditions leading to extreme drought have a negative influence on agriculture (Chabejong 2016 <sup>[[#fn:r224|224]]</sup> ).

Utilising farmer interviews in Abia State, Nigeria, researchers found that virtually all responders agreed that the climate was changing in their area (Ifeanyi-obi et al. 2016 <sup>[[#fn:r225|225]]</sup> ). With regard to management responses, a survey of farmers from Anambra State, Nigeria, showed that farmers are adapting to climate change by utilising such techniques as mixed cropping systems, crop rotation, and fertiliser application (Onyeneke et al. 2018 <sup>[[#fn:r226|226]]</sup> ). In Ebonyi State, Nigeria, Eze (2017) <sup>[[#fn:r227|227]]</sup> interviewed 160 women cassava farmers and found the major climate change risks in production to be severity of high temperature stress, variability in relative humidity, and flood frequency.

''Europe''

The impacts of climate change are varied across the continent. Moore and Lobell (2015) <sup>[[#fn:r228|228]]</sup> showed via counterfactual analysis that climate trends are affecting European crop yields, with long-term temperature and precipitation trends since 1989 reducing continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and having slightly increased maize and sugar beet yields. Though these aggregate affects appear small, the impacts are not evenly distributed. In cooler regions such as the United Kingdom and Ireland, the effect of increased warming has been ameliorated by an increase in rainfall. Warmer regions, such as Southern Europe, have suffered more from the warming; in Italy this effect has been amplified by a drying trend, leading to yield declines of 5% or greater.

Another study examining the impacts of recent climate trends on cereals in Greece showed that crops are clearly responding to changes in climate – and demonstrated (via statistical analysis) that significant impacts on wheat and barley production are expected at the end of the 21st century (Mavromatis 2015 <sup>[[#fn:r229|229]]</sup> ). In the Czech Republic, a study documented positive long-term impacts of recent warming on yields of fruiting vegetables (cucumbers and tomatoes) from 4.9 to 12% per 1°C increase in local temperature, but decreases in yield stability of traditionally grown root vegetables in the warmest areas of the country (Potopová et al. 2017 <sup>[[#fn:r230|230]]</sup> ). A study in Hungary also indicated the increasingly negative impacts of temperature on crops and indicated that a warming climate is at least partially responsible for the stagnation in crop yields since the mid-1980s in Eastern Europe (Pinke and Lövei 2017 <sup>[[#fn:r231|231]]</sup> ).

In summary, climate change is already affecting food security ( ''high confidence'' ). Recent studies in both large-scale and smallholder farming systems document declines in crop productivity related to rising temperatures and changes in precipitation. Evidence for climate change impacts (e.g., declines and stagnation in yields, changes in sowing and harvest dates, increased infestation of pests and diseases, and declining viability of some crop varieties) is emerging from detection and attribution studies and ILK in Australia, Europe, Asia, Africa, North America, and South America ( ''medium evidence, robust agreement'' ).

''Projected impacts''

Climate change effects have been studied on a global scale following a variety of methodologies that have recently been compared (Lobell and Asseng 2017 <sup>[[#fn:r232|232]]</sup> ; Zhao et al. 2017a <sup>[[#fn:r233|233]]</sup> and Liu et al. 2016 <sup>[[#fn:r234|234]]</sup> ). Approaches to study global and local changes include global gridded crop model simulations (e.g., Deryng et al. 2014 <sup>[[#fn:r235|235]]</sup> ), point-based crop model simulations (e.g., Asseng et al. 2015 <sup>[[#fn:r236|236]]</sup> ), analysis of point-based observations in the field (e.g., Zhao et al. 2016 <sup>[[#fn:r237|237]]</sup> ), and temperature-yield regression models (e.g., Auffhammer and Schlenker 2014 <sup>[[#fn:r238|238]]</sup> ). For an evaluation of model skills see example used in AgMIP (Müller et al. 2017b <sup>[[#fn:r239|239]]</sup> ).

Results from Zhao et al. (2017a <sup>[[#fn:r240|240]]</sup> ) across different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. A limitation of Zhao et al. (2017a) is that it is based on the assumption that yield responses to temperature increase are linear, while yield response differs depending on growing season temperature levels. Iizumi et al. (2017) <sup>[[#fn:r241|241]]</sup> showed that the projected global mean yields of maize and soybean at the end of this century do decrease monotonically with warming, whereas those of rice and wheat increase with warming but level off at about 3°C (2091–2100 relative to 1850–1900).

Empirical statistical models have been applied widely to different cropping systems, at multiple scales. Analyses using statistical models for maize and wheat tested with global climate model scenarios found that the RCP4.5 scenario reduced the size of average yield impacts, risk of major slowdowns, and exposure to critical heat extremes compared to RCP8.5 in the latter decades of the 21st century (Tebaldi and Lobell 2018 <sup>[[#fn:r242|242]]</sup> ). Impacts on crops grown in the tropics are projected to be more negative than in mid – to high-latitudes as stated in AR5 and confirmed by recent studies (e.g., Levis et al. 2018 <sup>[[#fn:r243|243]]</sup> ). These projected negative effects in the tropics are especially pronounced under conditions of explicit nitrogen stress (Rosenzweig et al. 2014 <sup>[[#fn:r244|244]]</sup> ) (Figure 5.4).

Reyer et al. (2017b) examined biophysical impacts in five world regions under different warming scenarios: 1°C, 1.5°C, 2°C, and 4°C warming. For the Middle East and northern African region a significant correlation between crop yield decrease and temperature increase was found, regardless of whether the effects of CO <sub>2</sub> fertilisation or adaptation measures are taken into account (Waha et al. 2017 <sup>[[#fn:r245|245]]</sup> ). For Latin America and the Caribbean the relationship between temperature and crop yield changes was only significant when the effect of CO <sub>2</sub> fertilisation is considered (Reyer et al. 2017a <sup>[[#fn:r246|246]]</sup> ).

A review of recent scientific literature found that projected yield loss for West Africa depends on the degree of wetter or drier conditions and elevated CO <sub>2</sub> concentrations (Sultan and Gaetani 2016 <sup>[[#fn:r247|247]]</sup> ). Faye et al. (2018b) in a crop modelling study with RCPs 4.5 and 8.5 found that climate change could have limited effects on peanut yield in Senegal due to the effect of elevated CO <sub>2</sub> concentrations.

'''Crop productivity changes for 1.5°C and 2.0°C''' . The IPCC Special Report on global warming of 1.5°C found that climate-related risks to food security are projected to increase with global warming of 1.5°C and increase further with 2°C (IPCC 2018b <sup>[[#fn:r248|248]]</sup> ). These findings are based among others on Schleussner et al. (2018); Rosenzweig et al. (2018a) <sup>[[#fn:r249|249]]</sup> ; Betts et al. (2018) <sup>[[#fn:r250|250]]</sup> , Parkes et al. (2018) <sup>[[#fn:r251|251]]</sup> and Faye et al. (2018a) <sup>[[#fn:r252|252]]</sup> . The importance of assumptions about CO <sub>2</sub> fertilisation was found to be significant by Ren et al. (2018) and Tebaldi and Lobell (2018).

AgMIP coordinated global and regional assessment (CGRA) results confirm that at the global scale, positive and negative changes are mixed in simulated wheat and maize yields, with declines in some breadbasket regions, at both 1.5°C and 2.0°C (Rosenzweig et al. 2018a <sup>[[#fn:r253|253]]</sup> ). In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan resulted in an increase in vulnerable households and poverty rate (Rosenzweig et al. 2018a).

'''Crop suitability''' . Another method of assessing the effects of climate change on crop yields that combined observations of current maximum-attainable yield with climate analogues also found strong reductions in attainable yields across a large fraction of current cropland by 2050 (Pugh et al. 2016 <sup>[[#fn:r254|254]]</sup> ). However, the study found the projected total land area in 2050, including regions not currently used for crops, climatically suitable for a high attainable yield similar to today. This indicates that large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth and keep pace with current trajectories of demand.

'''Fruits and vegetables''' . Understanding the full range of climate impacts on fruits and vegetables is important for projecting future food security, especially related to dietary diversity and healthy diets.

However, studies for vegetables are very limited (Bisbis et al. 2018 <sup>[[#fn:r255|255]]</sup> ). Of the 174 studies considered in a recent review, only 14 described results of field or greenhouse experiments studying impacts of increased temperatures on yields of different root and leafy vegetables, tomatoes and legumes (Scheelbeek et al. 2018 <sup>[[#fn:r256|256]]</sup> ). Bisbis et al. (2018) found similar effects for vegetables as have been found for grain crops. That is, the effect of increased CO <sub>2</sub> on vegetables is mostly beneficial for production, but may alter internal product quality, or result in photosynthetic down-regulation. Heat stress reduces fruit set of fruiting vegetables, and speeds up development of annual vegetables, shortening their time for photoassimilation. Yield losses and impaired product quality result, thereby increasing food loss and waste. On the other hand, a longer growing season due to warmer temperatures enables a greater number of plantings and can contribute to greater annual yields. However, some vegetables, such as cauliflower and asparagus, need a period of cold accumulation to produce a harvest and warmer winters may not provide those requirements.

For vegetables growing in higher baseline temperatures (&gt;20°C), mean yield declines caused by 4°C warming were 31.5%; for vegetables growing in cooler environments (≤20°C), yield declines caused by 4°C were much less, on the order of about 5% (Scheelbeek et al. 2018 <sup>[[#fn:r257|257]]</sup> ). Rippke et al. (2016) <sup>[[#fn:r258|258]]</sup> found that 30–60% of the common bean growing area and 20–40% of the banana growing areas in Africa will lose viability in 2078–2098 with a global temperature increase of 2.6°C and 4°C respectively. Tripathi et al. (2016) <sup>[[#fn:r259|259]]</sup> found fruits and vegetable production to be highly vulnerable to climate change at their reproductive stages and also due to potential for greater disease pressure.

In summary, studies assessed find that climate change will increasingly be detrimental to crop productivity as levels of warming progress ( ''high confidence'' ). Impacts will vary depending on CO <sub>2</sub> concentrations, fertility levels, and region. Productivity of major commodity crops as well as crops such as millet and sorghum yields will be affected. Studies on fruits and vegetables find similar effects to those projected for grain crops in regard to temperature and CO <sub>2</sub> effects. Total land area climatically suitable for high attainable yield, including regions not currently used for crops, will be similar in 2050 to today.

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'''Figure 5.4'''

<span id="agmip-median-yield-changes-for-rcp8.5-20702099-in-comparison-to-19802010-baseline-with-co2-effects-and-explicit-nitrogen-stress-over-five-gcms-힆-four-global-gridded-crop-models-ggcms-for-rainfed-maize-wheat-rice-and-soy-20-ensemble-members-from-epic-gepic-pdssat-and-pegasus-except-for-rice-which-has-15.-grey-areas-indicate"></span>
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'''AgMIP median yield changes (%) for RCP8.5 (2070–2099 in comparison to 1980–2010 baseline) with CO2 effects and explicit nitrogen stress over five GCMs 힆 four Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate […]'''
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[[File:63de8b189ca1afd3873414bb46e938b6 Figure-5.4.jpg]]

AgMIP median yield changes (%) for RCP8.5 (2070–2099 in comparison to 1980–2010 baseline) with CO <sub>2</sub> effects and explicit nitrogen stress over five GCMs 힆 four Global Gridded Crop Models (GGCMs) for rainfed maize, wheat, rice, and soy (20 ensemble members from EPIC, GEPIC, pDSSAT, and PEGASUS; except for rice which has 15). Grey areas indicate historical areas with little to no yield capacity. All models use a 0.5°C grid, but there are differences in grid cells simulated to represent agricultural land. While some models simulated all land areas, others simulated only potential suitable cropland area according to evolving climatic conditions. Others utilised historical harvested areas in 2000 according to various data sources (Rosenzweig et al. 2014) <sup>[[#fn:r1422|1422]]</sup> .

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