The critical role of extreme heat for maize production in the United States
TL;DR: In this article, a process-based agricultural production system simulator (APSIM) is used to simulate the effects of extreme degree days (EDD) on maize yields in the United States.
Abstract: Statistical studies of rainfed maize yields in the United States(1) and elsewhere(2) have indicated two clear features: a strong negative yield response to accumulation of temperatures above 30 degrees C (or extreme degree days (EDD)), and a relatively weak response to seasonal rainfall. Here we show that the process-based Agricultural Production Systems Simulator (APSIM) is able to reproduce both of these relationships in the Midwestern United States and provide insight into underlying mechanisms. The predominant effects of EDD in APSIM are associated with increased vapour pressure deficit, which contributes to water stress in two ways: by increasing demand for soil water to sustain a given rate of carbon assimilation, and by reducing future supply of soil water by raising transpiration rates. APSIM computes daily water stress as the ratio of water supply to demand, and during the critical month of July this ratio is three times more responsive to 2 degrees C warming than to a 20% precipitation reduction. The results suggest a relatively minor role for direct heat stress on reproductive organs at present temperatures in this region. Effects of elevated CO2 on transpiration efficiency should reduce yield sensitivity to EDD in the coming decades, but at most by 25%.
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TL;DR: It is shown that droughts and extreme heat significantly reduced national cereal production by 9–10%, whereas the analysis could not identify an effect from floods and extreme cold in the national data, which may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
Abstract: In recent years, several extreme weather disasters have partially or completely damaged regional crop production. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964-2007. We show that droughts and extreme heat significantly reduced national cereal production by 9-10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8-11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
1,934 citations
TL;DR: This study uses detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide.
Abstract: Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32-39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability.
1,168 citations
TL;DR: This paper updates the earlier work by Keating et?al.
Abstract: Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond.Keating et?al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands.This paper updates the earlier work by Keating et?al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a "next generation" framework with improved features and capabilities that allow its use in many diverse topics. APSIM is an agricultural modelling framework used extensively worldwide.It can simulate a wide range of agricultural systems.It begins its third decade evolving into an agro-ecosystem framework.
1,151 citations
01 Jan 2014
TL;DR: The questions for this chapter are how far climate and its change affect current food production systems and food security and the extent to which they will do so in the future.
Abstract: Many definitions of food security exist, and these have been the subject of much debate. As early as 1992, Maxwell and Smith (1992) reviewed more than 180 items discussing concepts and definitions, and more definitions have been formulated since (DEFRA, 2006). Whereas many earlier definitions centered on food production, more recent definitions highlight access to food, in keeping with the 1996 World Food Summit definition (FAO, 1996) that food security is met when “all people, at all times, have physical and economic access to sufficient, safe, and nutritious food to meet their dietary needs and food preferences for an active and healthy life.” Worldwide attention on food access was given impetus by the food “price spike” in 2007–2008, triggered by a complex set of long- and short-term factors (FAO, 2009b; von Braun and Torero, 2009). FAO concluded, “provisional estimates show that, in 2007, 75 million more people were added to the total number of undernourished relative to 2003–05” (FAO, 2008); this is arguably a low-end estimate (Headey and Fan, 2010). More than enough food is currently produced per capita to feed the global population, yet about 870 million people remained hungry in the period from 2010 to 2012 (FAO et al., 2012). The questions for this chapter are how far climate and its change affect current food production systems and food security and the extent to which they will do so in the future (Figure 7-1).
960 citations
Cites background or methods from "The critical role of extreme heat f..."
...Process-based models, which extrapolate based on measured interactions and mechanisms, can be used to develop a causal understanding of the empirically determined relationships in statistical models (cf. Schlenker and Roberts, 2009; Lobell et al., 2013a)....
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...…as the shortening of the time to maturity of a crop with increasing mean temperature (Iqbal et al., 2009), decline in grain set when high temperatures occur during flowering (Moriondo et al., 2011), and increased water stress at high temperatures throughout the growing cycle (Lobell et al., 2013a)....
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...Many additional projections of this type have been made since AR4, expanding the number of trade models used, the diversity of yield projections considered, and the disaggregation of prices by commodity (Hertel et al., 2010; Calzadilla et al., 2013; Lobell et al., 2013b; Nelson et al., 2013)....
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...…and agricultural technology, global arable area is projected to increase from 2007 to 2050, with projected increases over this period of +9% (Bruinsma, 2009), +8% (Fischer et al., 2009), +10 to 20% (Smith et al., 2010), and +18 to 23% (Lobell et al., 2013b) (medium evidence, medium agreement)....
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TL;DR: The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields but not to decreasing drought sensitivity of yields at the field scale, which is a key question for climate change adaptation.
Abstract: A key question for climate change adaptation is whether existing cropping systems can become less sensitive to climate variations. We use a field-level data set on maize and soybean yields in the central United States for 1995 through 2012 to examine changes in drought sensitivity. Although yields have increased in absolute value under all levels of stress for both crops, the sensitivity of maize yields to drought stress associated with high vapor pressure deficits has increased. The greater sensitivity has occurred despite cultivar improvements and increased carbon dioxide and reflects the agronomic trend toward higher sowing densities. The results suggest that agronomic changes tend to translate improved drought tolerance of plants to higher average yields but not to decreasing drought sensitivity of yields at the field scale.
805 citations
References
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Book•
01 Jul 2001
TL;DR: In this paper, the authors set the stage for impact, adaptation, and vulnerability assessment of climate change in the context of sustainable development and equity, and developed and applied scenarios in Climate Change Impact, Adaptation, and Vulnerability Assessment.
Abstract: Summary for policymakers Technical summary Part I. Setting the Stage for Impact, Adaptation, and Vulnerability Assessment: 1. Overview 2. Methods and tools 3. Development and application of scenarios in Climate Change Impact, Adaptation, and Vulnerability Assessment Part II. Sectors and Systems: Impacts, Adaptation, and Vulnerability: 4. Hydrology and water resources 5. Natural and managed ecosystems 6. Coastal zones and marine ecosystems 7. Energy, industry, and settlements 8. Financial services 9. Human health Part III. Regional Analyses: Impacts, Adaptation, and Vulnerability: 10. Africa 11. Asia 12. Australasia 13. Europe 14. Latin America 15. North America 16. Polar regions (Arctic and Antarctic) 17. Small island states Part IV. Global Issues and Synthesis: 18. Adaptation to climate change in the context of sustainable development and equity 19. Synthesis and integration of impacts, adaptation, and vulnerability Index.
12,541 citations
Book•
01 Jan 2007
TL;DR: In this paper, the authors present a cross-chapter case study on climate change and sustainability in natural and managed systems and assess key vulnerabilities and the risk from climate change, and assess adaptation practices, options, constraints and capacity.
Abstract: Foreword Preface Introduction Summary for policymakers Technical summary 1. Assessment of observed changes and responses in natural and managed systems 2. New assessment methodologies and the characterisation of future conditions 3. Fresh water resources and their management 4. Ecosystems, their properties, goods and services 5. Food, fibre and forest products 6. Coastal systems and low-lying areas 7. Industry, settlement and society 8. Human health 9. Africa 10. Asia 11. Australia and New Zealand 12. Europe 13. Latin America 14. North America 15. Polar regions (Arctic and Antarctic) 16. Small islands 17. Assessment of adaptation practices, options, constraints and capacity 18. Inter-relationships between adaptation and mitigation 19. Assessing key vulnerabilities and the risk from climate change 20. Perspectives on climate change and sustainability - 811 Cross-chapter case studies Appendix I. Glossary Appendix II. Contributors to the IPCC WGII Fourth Assessment Report Appendix III. Reviewers of the IPCC WGII Fourth Assessment Report Appendix IV. Acronyms and abbreviations Appendix V. Index and database of regional content Index CD-ROM.
8,465 citations
01 Jan 2007
TL;DR: The Intergovernmental Panel on Climate Change (IPCC) was set up jointly by the World Meteorological Organization and the United Nations Environment Programme to provide an authoritative international statement of scientific understanding of climate change as discussed by the authors.
Abstract: The Intergovernmental Panel on Climate Change (IPCC) was set up jointly by the World Meteorological Organization and the United Nations Environment Programme to provide an authoritative international statement of scientific understanding of climate change. The IPCC’s periodic assessments of the causes, impacts and possible response strategies to climate change are the most comprehensive and up-to-date reports available on the subject, and form the standard reference for all concerned with climate change in academia, government and industry worldwide. Through three working groups, many hundreds of international experts assess climate change in this Fourth Assessment Report.
3,633 citations
TL;DR: It was found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability.
Abstract: Efforts to anticipate how climate change will affect future food availability can benefit from understanding the impacts of changes to date. We found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability. Models that link yields of the four largest commodity crops to weather indicate that global maize and wheat production declined by 3.8 and 5.5%, respectively, relative to a counterfactual without climate trends. For soybeans and rice, winners and losers largely balanced out. Climate trends were large enough in some countries to offset a significant portion of the increases in average yields that arose from technology, carbon dioxide fertilization, and other factors.
3,231 citations
TL;DR: Yields increase with temperature but that temperatures above these thresholds are very harmful, suggesting limited historical adaptation of seed varieties or management practices to warmer temperatures because the cross-section includes farmers' adaptations to warmer climates and the time-series does not.
Abstract: The United States produces 41% of the world's corn and 38% of the world's soybeans. These crops comprise two of the four largest sources of caloric energy produced and are thus critical for world food supply. We pair a panel of county-level yields for these two crops, plus cotton (a warmer-weather crop), with a new fine-scale weather dataset that incorporates the whole distribution of temperatures within each day and across all days in the growing season. We find that yields increase with temperature up to 29° C for corn, 30° C for soybeans, and 32° C for cotton but that temperatures above these thresholds are very harmful. The slope of the decline above the optimum is significantly steeper than the incline below it. The same nonlinear and asymmetric relationship is found when we isolate either time-series or cross-sectional variations in temperatures and yields. This suggests limited historical adaptation of seed varieties or management practices to warmer temperatures because the cross-section includes farmers' adaptations to warmer climates and the time-series does not. Holding current growing regions fixed, area-weighted average yields are predicted to decrease by 30–46% before the end of the century under the slowest (B1) warming scenario and decrease by 63–82% under the most rapid warming scenario (A1FI) under the Hadley III model.
2,536 citations