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Climate change poses complex impacts on the global wheat supply and demand chain. The impacts of climate change on average wheat yields are reasonably well studied, but its effects on yield variability and the associated economic consequences are poorly understood. Here, we show that future global wheat prices will exhibit steeper spikes at 2°C global warming (6.2% increase in the 95th percentile of global consumer price anomalies) despite a 1.7% increase in production given that CO2 fertilization benefits crops. Such economic stresses could be abated by trade liberalization with lower prices. However, on the supply side, trade liberalization has contrasting effects: the profitability of farmers in advanced economies can be maintained or even raised, but this will inevitably cause economic losses and inequalities for farmers in less-developed, wheat-importing countries. Agricultural trade liberalization accompanied by protection policies in developing countries would be beneficial for global food security in the threat of climate change.

Humans’ essential ability to combat heat stress through sweat-based evaporative cooling is modulated by ambient air temperature and humidity, making humid heat a critical factor for human health. In this study, we relate the occurrence of extreme humid heat in two focus regions to two related modes of intraseasonal climate variability: the Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). In the Persian Gulf and South Asia during the May–June and July–August seasons, wet-bulb temperatures of 28°C are found to be almost twice as likely during certain oscillation phases than in others. Variations in moisture are found, to varying degrees, to be an important ingredient in anomalously high wet-bulb temperatures in all three areas studied, influenced by distinct local circulation anomalies. In the Persian Gulf, weakening of climatological winds associated with the intraseasonal oscillation’s propagating center of convection allows for anomalous onshore advection of humid air. Anomalously high wet-bulb temperatures in the northwestern region of South Asia are closely aligned with positive specific humidity anomalies associated with the convectively active phase of the oscillation. On the southeastern coast of India, high wet-bulb temperatures are associated with convectively inactive phases of the intraseasonal oscillation, suggesting that they may be driven by increased surface insolation and reduced evaporative cooling during monsoon breaks. Our results aid in building a foundation for subseasonal predictions of extreme humid heat in regions where it is highly impactful. Significance Statement Understanding when and why extreme humid heat occurs is essential for informing public health efforts protecting against heat stress. This analysis works to improve our understanding of humid heat variability in two at-risk regions, the Persian Gulf and South Asia. By exploring how subseasonal oscillations affect daily extreme events, this analysis helps bridge the prediction gap between weather and climate. We find that extreme humid heat is more than twice as likely during specific phases of these oscillations than in others. Extremes depend to different extents upon combinations of above-average temperature and humidity. This new knowledge of the regional drivers of humid heat variability is important to better prepare for the increasingly widespread health and socioeconomic impacts of heat stress.

International audience; That climate variability and change can potentially force multiple simultaneous breadbasket crop yield shocks has been established. But research quantifying the mechanisms behind such simultaneous shocks has been constrained by short records of crop yields. Here we compile a dataset of subnational crop yields in 25 countries dating back to 1900 to study the frequency and trends in multiple breadbasket yield shocks and how large-scale climate anomalies on interannual timescales have affected multiple breadbasket yield shocks over the last century. We find that major simultaneous breadbasket yield shocks have occurred in at least three, four, or five of nine breadbaskets 10.3%, 2.3% and 1.1% of the time for maize and 18.4%, 4.6% and 2.3% of the time for wheat. Furthermore, we find that multiple breadbasket yield shocks decreased in frequency even as those breadbaskets experience increasingly frequent climate-related shocks. For both maize and wheat breadbaskets, there were fewer simultaneous yield shocks during the 1975–2017 time period as compared to 1931–1975. Finally, we find that interannual modes of climate variability - such as the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the North Atlantic Oscillation (NAO) - have all affected the relative probability of simultaneous yield shocks in pairs of breadbaskets by up to 20–40% in both maize and wheat breadbaskets. While past literature has focused on the effects of ENSO, we find that at the global scale the NAO affects the overall number of wheat yield shocks most strongly despite only affecting northern hemisphere breadbaskets.

openaire: EC/HE/819202/EU//SOS.aquaterra Funding Information: The study was funded by Maa- ja vesitekniikan tuki ry, Academy of Finland funded project WATVUL (Grant No. 317320), Academy of Finland funded project TREFORM (grant no. 339834), and European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 819202). M.J.P. acknowledges support from the Army Research Office/Army Research Laboratory under the Multidisciplinary University Research Initiative (Grant # W911NF1810267) and the Defense Advanced Research Project Agency (DARPA) under the World Modelers program (Grant # W911NF1910013). The views and conclusions contained in this manuscript are those of the authors and should not be interpreted as representing the official policies either expressed or implied of the Army Research Office or the US Government. D.K.R. acknowledges support from the Institute on the Environment, University of Minnesota. We thank Ilkka Mellin from Aalto University for his comments and advice regarding the methodology of this study. Finally, we acknowledge the Aalto high-performance computing cluster Triton for making this study possible. Funding Information: The study was funded by Maa- ja vesitekniikan tuki ry, Academy of Finland funded project WATVUL (Grant No. 317320), Academy of Finland funded project TREFORM (grant no. 339834), and European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 819202). M.J.P. acknowledges support from the Army Research Office/Army Research Laboratory under the Multidisciplinary University Research Initiative (Grant # W911NF1810267) and the Defense Advanced Research Project Agency (DARPA) under the World Modelers program (Grant # W911NF1910013). The views and conclusions contained in this manuscript are those of the authors and should not be interpreted as representing the official policies either expressed or implied of the Army Research Office or the US Government. D.K.R. acknowledges support from the Institute on the Environment, University of Minnesota. We thank Ilkka Mellin from Aalto University for his comments and advice regarding the methodology of this study. Finally, we acknowledge the Aalto high-performance computing cluster Triton for making this study possible. Publisher Copyright: © 2023, The Author(s). Although extreme weather events recur periodically everywhere, the impacts of their simultaneous occurrence on crop yields are globally unknown. In this study, we estimate the impacts of combined hot and dry extremes as well as cold and wet extremes on maize, rice, soybean, and wheat yields using gridded weather data and reported crop yield data at the global scale for 1980–2009. Our results show that co-occurring extremely hot and dry events have globally consistent negative effects on the yields of all inspected crop types. Extremely cold and wet conditions were observed to reduce crop yields globally too, although to a lesser extent and the impacts being more uncertain and inconsistent. Critically, we found that over the study period, the probability of co-occurring extreme hot and dry events during the growing season increased across all inspected crop types; wheat showing the largest, up to a six-fold, increase. Hence, our study highlights the potentially detrimental impacts that increasing climate variability can have on global food production.

Lactation insufficiency is variously defined and includes the inability to produce milk, not producing enough milk to exclusively meet infant growth requirements, and pathological interruption of lactation (e.g., mastitis). Of women with intent-to-breastfeed, lactation insufficiency has been estimated to affect 38%–44% of newly postpartum women, likely contributing to the nearly 60% of infants that are not breastfed according to the World Health Organization’s guidelines. To date, research and clinical practice aimed at improving feeding outcomes have focused on hospital lactation support and education, with laudable results. However, researchers’ reports of recent rodent studies concerning fundamental lactation biology have suggested that the underlying pathologies of lactation insufficiency may be more nuanced than is currently appreciated. In this article, we identify mucosal biology of the breast and lactation-specific liver biology as two under-researched aspects of lactation physiology. Specifically, we argue that further scientific inquiry into reproductive state-dependent regulation of immunity in the human breast will reveal insights into novel immune based requirements for healthy lactation. Additionally, our synthesis of the literature supports the hypothesis that the liver is an essential player in lactation—highlighting the potential that pathologies of the liver may also be associated with lactation insufficiency. More research into these biologic underpinnings of lactation is anticipated to provide new avenues to understand and treat lactation insufficiency.

The climate of South America (SA) has long held an intimate connection with El Nino, historically describing anomalously warm sea-surface temperatures off the coastline of Peru. Indeed, throughout SA, precipitation and temperature exhibit a substantial, yet regionally diverse, relationship with the El Nino–Southern Oscillation (ENSO). For example, El Nino is typically accompanied by drought in the Amazon and north-eastern SA, but flooding in the tropical west coast and south-eastern SA, with marked socio-economic effects. In this Review, we synthesize the understanding of ENSO teleconnections to SA. Recent efforts have sought improved understanding of ocean–atmosphere processes that govern the impact, inter-event and decadal variability, and responses to anthropogenic warming. ENSO’s impacts have been found to vary markedly, affected not only by ENSO diversity, but also by modes of variability within and outside of the Pacific. However, while the understanding of ENSO–SA relationships has improved, with implications for prediction and projection, uncertainty remains in regards to the robustness of the impacts, inter-basin climate interactions and interplay with greenhouse warming. A coordinated international effort is, therefore, needed to close the observational, theoretical and modelling gaps currently limiting progress, with specific efforts in extending palaeoclimate proxies further back in time, reducing systematic model errors and improving simulations of ENSO diversity and teleconnections. The El Nino–Southern Oscillation exerts a strong influence on the global climate, including South America, where understanding of the phenomenon first emerged. This Review outlines the impacts of the El Nino–Southern Oscillation on South America, focusing on the mechanisms and diversity of resulting teleconnections.

Simultaneous yield shocks in multiple breadbaskets pose a potential threat to global food security, yet the historical risks and causes of such shocks are poorly understood. Here, we compile a dataset of subnational maize and wheat yield anomalies in 25 countries dating back to 1900 to better characterize the past, present, and future risk of multiple breadbasket shocks. We find that years in which at least half of all maize or wheat breadbaskets fall 10% (5%) below expected yields has occurred in ~2-3% (~14-16%) of years over the last century. Importantly, multiple breadbasket shocks have been decreasing in frequency from 1930 to 2017. The El Niño Southern Oscillation (ENSO) most strongly affects the probability of multiple maize breadbasket shocks, while the North Atlantic Oscillation (NAO) most strongly affects the probability of multiple wheat breadbasket shocks, each influencing the probability by up to 40%. The effect of climate change on climate stress in maize and wheat breadbaskets is mixed; extreme heat will increase uniformly, agricultural soil moisture stress will remain constant or increase, but hydrological stress (as measured by runoff) will remain constant or decrease in breadbasket regions.

In the original version of the article contained errors in the fig 3 and 4 and captions of Figures 3 and 4 with respect to the panels in the top row.

While many Madden–Julian Oscillation (MJO) teleconnections are well documented, the significance of these teleconnections to agriculture is not well understood. Here we analyze how the MJO affects the climate during crop flowering seasons, when crops are particularly vulnerable to abiotic stress. Because the MJO is located in the tropics of the summer hemisphere and maize is a tropical, summer-grown crop, the MJO teleconnections to maize flowering seasons are stronger and more coherent than those to wheat, which tends to be grown in midlatitudes and flowers during the spring. The MJO significantly affects not only daily average precipitation and soil moisture, but also the probability of extreme precipitation, soil moisture and maximum temperatures during crop flowering seasons. The average influence on the probability of extreme daily precipitation, soil moisture, and maximum temperature events is roughly equal. On average the MJO modifies the probability of a 5th or 95th, 10th or 90th, and 25th or 75th percentile event by $$\sim $$∼ 2.5%, $$\sim $$∼ 4% and $$\sim $$∼ 7%, respectively. This means that an exceptionally dry (10th percentile) soil moisture value, for example, would become $$\sim $$∼ 40% more common (happening 14% of the time) during certain MJO phases. That the MJO can simultaneously dry soils and raise maximum air temperatures may be particularly damaging to crops because without available soil water during times of heat stress, plants are unable to transpire to cool leaf-level temperatures as a means of avoiding long-term damage. As a result, even though teleconnections from the MJO last only a few days to a week, they likely affect crop growth.

ImportanceBreast cancer diagnosed within 5 to 10 years after childbirth, called postpartum breast cancer (PPBC), is associated with increased risk for metastasis and death. Whether a postpartum diagnosis is an independent risk factor or a surrogate marker of cancer features associated with poor outcomes remains understudied.ObjectiveTo determine whether diagnostic temporal proximity to childbirth is associated with features of breast cancer associated with poor outcomes, including tumor stage, estrogen receptor (ER) status, and risk for distant metastasis and breast cancer–specific mortality, using a population database from the state of Utah.Design, Setting, and ParticipantsThis population-based cohort study using the Utah Population Database (UPDB) included individuals with stage I to III breast cancer diagnosed at age 45 years or younger between 1996 and 2017, followed-up until February 2020. Participant data were analyzed from November 2019 to August 2022.ExposureThe primary exposures were no prior childbirth or time between most recent childbirth and breast cancer diagnosis. Patients were grouped by diagnoses within less than 5 years, 5 to less than 10 years, or 10 years or more since recent childbirth.Main Outcomes and MeasuresThe 2 primary outcomes were distant metastasis–free survival and breast cancer–specific death. Cox proportional hazard models were used to investigate associations between exposures and outcomes adjusting for diagnosis year, patient age, tumor stage, and estrogen receptor (ER) status.ResultsOf 2970 individuals with breast cancer diagnosed at age 45 years or younger (mean [SD] age, 39.3 [5.0] years; 12 Black individuals [0.4%], 2679 White individuals [90.2%]), breast cancer diagnosis within 5 years of recent childbirth was independently associated with approximately 1.5-fold elevated risk for metastasis (hazard ratio [HR], 1.5; 95% CI, 1.2-2.0) and breast cancer–specific death (HR, 1.5; 95% CI, 1.1-2.1) compared with nulliparous individuals. For cancers classically considered to have tumor features associated with good outcomes (ie, stage I or II and ER-positive), a postpartum diagnosis was a dominant feature associated with increased risk for metastasis and death (eg, for individuals with ER-positive disease diagnosed within P = .01; age-adjusted death HR, 1.5; 95% CI, 1.0-2.1; P = .04) compared with nulliparous individuals. Furthermore, liver metastases were specifically increased in the group with diagnosis within 5 years postpartum and with positive ER expression (38 of 83 patients [45.8%]) compared with the nulliparous (28 of 77 patients [36.4%]), although the difference was not statistically significant. Overall, these data implicate parity-associated breast and liver biology in the observed poor outcomes of PPBC.Conclusions and RelevanceIn this cohort study of individuals with breast cancer diagnosed at age 45 years or younger, a postpartum breast cancer diagnosis was a risk factor associated with poor outcomes. Irrespective of ER status, clinical consideration of time between most recent childbirth and breast cancer diagnosis could increase accuracy of prognosis in patients with young-onset breast cancer.

Spatially compound extremes pose substantial threats to globally interconnected social-economic systems. We use an Earth system model large ensemble to examine the future risk of compound droughts during the boreal summer over ten global regions with highly seasonal climate. Relative to the late-20th century, the probability, mean extent and severity of compound droughts increase by ~60%, ~10% and ~20% respectively by the late-21st century, with a disproportionate increase in risk across North America and the Amazon. These changes result in a ~9-fold increase in exposure over agricultural areas and ~5 to 20-fold increase in population exposure depending on the shared socioeconomic pathway. ENSO is the predominant large-scale driver of compound droughts with 68% of historical events occurring during El Niño or La Niña conditions. ENSO teleconnections remain stationary in the future though an ~22% increase in ENSO extremes combined with projected warming, drive the elevated risk of compound droughts.

Spatially compounding droughts over multiple regions pose amplifying pressures on the global food system, the reinsurance industry, and the global economy. Using observations and climate model simulations, we analyze the influence of various natural Ocean variability modes on the likelihood, extent, and severity of compound droughts across ten regions that have similar precipitation seasonality and cover important breadbaskets and vulnerable populations. Although a majority of compound droughts are associated with El Niños, a positive Indian Ocean Dipole, and cold phases of the Atlantic Niño and Tropical North Atlantic (TNA) can substantially modulate their characteristics. Cold TNA conditions have the largest amplifying effect on El Niño-related compound droughts. While the probability of compound droughts is ~3 times higher during El Niño conditions relative to neutral conditions, it is ~7 times higher when cold TNA and El Niño conditions co-occur. The probability of widespread and severe compound droughts is also amplified by a factor of ~3 and ~2.5 during these co-occurring modes relative to El Niño conditions alone. Our analysis demonstrates that co-occurrences of these modes result in widespread precipitation deficits across the tropics by inducing anomalous subsidence, and reducing lower-level moisture convergence over the study regions. Our results emphasize the need for considering interactions within the larger climate system in characterizing compound drought risks rather than focusing on teleconnections from individual modes. Understanding the physical drivers and characteristics of compound droughts has important implications for predicting their occurrence and characterizing their impacts on interconnected societal systems.

Conflict, drought and locusts are leading concerns for African food security but the relative importance and spatiotemporal scale of crises resulting from each hazard is poorly characterized. Here we use continuous, subnational data to demonstrate that the rise of food insecurity across sub-Saharan Africa that began in 2014 is attributable to an increase in violent conflict, particularly in South Sudan and Nigeria. Although drought remains a leading trigger of food crises, the prevalence of drought-related crises did not increase from 2009 to 2018. When exposed to drought, pastoralists experienced more widespread, severe and long-lasting food crises than people living in agricultural zones. Food insecurity remained elevated in pastoral regions for 2 years following a drought, while agricultural regions returned to pre-drought food-security levels in ~12 months. The few confirmed famines during the 2009–2018 period coincided with both conflict and drought, while locusts had little effect on food security during this period. Subnational data indicate that the increasing frequency of food-security crises since 2014 is more attributable to conflict in South Sudan and Nigeria than to drought or locust swarms, with pastoralists remaining more vulnerable to drought than those in agricultural zones.

El Niño–Southern Oscillation (ENSO) teleconnections have been recognized as possible negative influences on crop yields in the United States during the summer growing season, especially in a developing La Niña summer. This study examines the physical processes of the ENSO summer teleconnections and remote impacts on the United States during a multiyear La Niña life cycle. Since 1950, a developing La Niña summer is either when an El Niño is transitioning to a La Niña or when a La Niña is persisting. Due to the distinct prior ENSO conditions, the oceanic and atmospheric characteristics in the tropics are dissimilar in these two different La Niña summers, leading to different teleconnection patterns. During the transitioning summer, the decaying El Niño and the developing La Niña induce suppressed deep convection over both the subtropical western Pacific (WP) and the tropical central Pacific (CP). Both of these two suppressed convection regions induce Rossby wave propagation extending toward North America, resulting in a statistically significant anomalous anticyclone over northeastern North America and, therefore, a robust warming signal over the Midwest. In contrast, during the persisting summer, only one suppressed convection region is present over the tropical CP induced by the La Niña SST forcing, resulting in a weak and insignificant extratropical teleconnection. Experiments from a stationary wave model confirm that the suppressed convection over the subtropical WP during the transitioning summer not only contributes substantially to the robust warming over the Midwest but also causes the teleconnections to be different from those in the persisting summer.

Conflict, drought, and locusts have been leading concerns for African food security in recent years, but the relative importance and spatiotemporal scales of crises resulting from each hazard is poorly characterized. Here we use continuous, subnational data from Sub-Saharan Africa to characterize how food crises differ according to livelihood strategy in response to each hazard. We find that when exposed to drought, pastoralists experienced more widespread, severe, and long-lasting food crises compared to those in agricultural zones. From 2009-2013 drought was the primary trigger of food security crises in all non-riverine zones; after 2013 conflict-related food security crises become prevalent. The few confirmed famines coincided with both conflict and drought. Locusts had little effect on food security during this time. These results provide multidimensional empirical evidence of how hazards affect food security in different livelihood zones, which provides an opportunity to improve scenario development in food security early warning forecasts.

It is well known that climate extremes and variability have strong implications for crop productivity. Previous research has estimated that annual weather conditions explain a third of global crop yield variability, with explanatory power above 50% in several important crop producing regions. Further, compared to average conditions, extreme events contribute a major fraction of weather induced crop yield variations. Here we aim to analyse how extreme weather events are related to the likelihood of very low crop yields at the global scale. We investigate not only the impacts of heat and drought on crop yields but also excess soil moisture and abnormally cool temperatures, as these extremes can be detrimental to crops as well. In this study, we combine reanalysis weather data with national and sub-national crop production statistics and assess relationships using statistical copulas methods, which are especially suitable for analysing extremes. Further, because irrigation can decrease crop yield variability, we assess how the observed signals differ in irrigated and rainfed cropping systems. We also analyse whether the strength of the observed statistical relationships could be explained by socio-economic factors, such as GDP, social stability, and poverty rates. Our preliminary results indicate that extreme heat and cold as well as soil moisture abundance and excess have a noticeable effect on crop yields in many areas around the globe, including several global bread baskets such as the United States and Australia. This study will increase understanding of extreme weather-related implications on global food production, which is relevant also in the context of climate change, as the frequency of extreme weather events is likely to increase in many regions worldwide.

The El Nino Southern Oscillation (ENSO) is a major source of interannual climate variability. ENSO life cycles and the associated teleconnections evolve over multiple years at a global scale. This analysis is the first attempt to characterize the structure of the risk posed by trans-Pacific ENSO teleconnections to crop production in the greater Pacific Basin region. In this analysis we identify the large-scale atmospheric dynamics of ENSO teleconnections that affect heat and moisture stress during the growing seasons of maize, wheat and soy. We propose a coherent framework for understanding how trans-Pacific ENSO teleconnections pose a correlated risk to crop yields in major agricultural belts of the Americas, Australia and China over the course of an ENSO life cycle by using observations and a multi-model ensemble of climate anomalies during crop flowering seasons. Trans-Pacific ENSO teleconnections are often (but not always) offsetting between major producing regions in the Americas and those in northern China or Australia. El Ninos tend to create good maize and soybean growing conditions in the US and southeast South America, but poor growing conditions in northern China, southern Mexico and the Cerrado in Brazil. The opposite is true during La Nina. Wheat growing conditions in southeast South America generally have the opposite sign of those in Australia. Furthermore, multi-year La Ninas can force multi-year growing season anomalies in Argentina and Australia. Most ENSO teleconnections relevant for crop flowering seasons are the result of a single trans-Pacific circulation anomaly that develops in boreal summer and persists through the following spring. During the late summer and early fall of a developing ENSO event, the tropical Pacific forces an atmospheric anomaly in the northern midlatitudes that spans the Pacific from northern China to North America and in the southern midlatitudes from Australia to southeast South America. This anomaly directly links the soybean and maize growing seasons of the US, Mexico and China and the wheat growing seasons of Argentina, southern Brazil and Australia. The ENSO event peaks in boreal winter, when the atmospheric circulation anomalies intensify and affect maize and soybeans in southeast South America. As the event decays, the ENSO-induced circulation anomalies persist through the wheat flowering seasons in China and the US.

This paper assesses the potential role of investments in irrigation in Sub-Saharan Africa in improving food security and self-sufficiency in the region. Focusing on the region’s drylands, the study identifies a potential for expanded irrigated area of 6–14 million hectares (ha), depending on technology costs and other factors. Linkage of these results with a global agricultural trade model shows that accelerated irrigation investment can effectively reduce growing food import dependency from 54% under a business-as-usual scenario to a much smaller 17–40%; and can also reduce the population at risk of hunger and child under-nutrition.

Universities and research centres around the world have made significant progress towards establishing collaborative, interdisciplinary initiatives in sustainability science. However, more needs to be done to support the career development of junior sustainability scholars whose work is often team based and outreach oriented.

In this analysis we show how globally coherent teleconnections from life-cycles of the El Nino Southern Oscillation (ENSO) lead to correlated crop production anomalies in North and South America. We estimate the magnitude of ENSO-induced Pan-American production anomalies and discuss how increasing crop harvesting frequency may affect Pan-American production variability. We find that ENSO accounts for ∼72%, 30% and 57% of Pan-American maize, soybean and wheat production variability, respectively. ENSO-induced production anomalies are greatest for maize, with median anomalies of ∼5% of Pan-American production. ENSO-induced yield anomalies for maize and soybeans tend to be of the same sign in North America and southeast South America but of an opposite sign in northeast Brazil. Teleconnections for wheat are more complicated because ENSO affects wheat yields via lagged soil moisture teleconnections in the US and an increased probability of disease in South America, but anomalies tend to be of the same sign in North America and southeast South America. After broadly characterizing ENSO-induced production anomalies, we demonstrate that they are not static in time. Increasing crop harvesting frequency has affected the correlated risks posed by ENSO. We use a soil water balance to show that in Brazil changing to a safrinha cropping cycle increases both the mean water stress and the ENSO-induced soil water content anomalies during flowering in both the maize and soybean seasons, which is a result of increasing evaporative demand during times of lower precipitation and moving the flowering seasons into months with strong ENSO teleconnections. Increasing crop harvesting frequency in Brazil has therefore increased ENSO-induced production variability of soybeans and maize.

Understanding what causes weather-related stresses that lead to crop failures is a critical step towards stabilizing global food production. While there are many sources of weather-related stresses...

The characteristic evolution of El Nino Southern Oscillation (ENSO) on timescales of months to years means that risks to agriculture have structure between seasons and years. The potential for consecutive ENSO-induced yield anomalies is of particular interest in major food producing areas, where modest changes in yield have significant effects on global markets. In this study, we analyse how multi-year El Nino and La Nina life cycles relate to climate sensitive portions of major crop-growing seasons in North and South America. We analyse the dynamics underlying these life cycles to illustrate which aspects of the system are most important for agriculture. In North America, the same-season teleconnections affecting soybean and maize have been well studied, but we demonstrate the importance of lagged soil moisture teleconnections for wheat in the southern Great Plains. In South America, peak ENSO sea surface temperature (SST) teleconnections are concurrent with, and therefore critical for, wheat and maize growing seasons while soil moisture memory in Argentina plays an important role during the soybean growing season. Finally, we show that ENSO teleconnection life cycles are consistent with historical yield anomalies. Both El Nino and La Nina life cycles tend to force consecutive seasons of either above or below expected yields. While the magnitude of the yield anomalies forced by ENSO is often modest, they occur in major crop-producing regions.

Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010–2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically-based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa.

Motivated by the United Nations target of achieving zero net land degradation by 2030 and the Rio + 20 United Nations' “future we want” resolution, which aims to achieve a green economy, this study was conducted with an objective of identifying strategies for achieving sustainable use of lands at a global and a regional level. Using econometric approaches, we observed that achievement of zero net degradation is possible, even in developing regions, if land users are provided with good market access and secure land rights and if institutions are strengthened to regulate land use. Such achievement is possible, even in densely populated and severely impoverished areas. The probability of achieving zero net land degradation is greater in drylands – especially among communities with pastoral and other livestock-based livelihoods.

© The Editor(s) (if applicable) and The Author(s) 2016. Identification of factors catalyzing sustainable land management (SLM) could provide insights for national policies and international efforts to address land degradation. Building on previous studies, and using novel datasets, this chapter identifies major drivers of land degradation at global and regional levels. The findings of this study confirm the earlier insights in the literature on the context-specific nature of the drivers of land degradation. This context-dependence explains the previous contradictions in the literature on the effects of various socio-economic and institutional factors on land degradation. It also calls for the localized diagnostic of the drivers of land degradation. The drivers of land degradation are predominantly local, so actions to address them should be based on the understanding of the local interplay of various factors and how they affect land degradation. ispartof: Economics of Land Degradation and Improvement - A Global Assessment for Sustainable Development pages:167-196 ispartof: pages:167-196 status: published

Understanding the impacts of land degradation is, at least in part, limited by our ability to accurately characterize those impacts in space and time. While in recent decades remote sensing has offered unprecedented coverage of the land surface, the evaluation of remote sensing products is often limited or lacking altogether. In this chapter we use a survey-based approach to evaluate how well already existing remotely sensed datasets depict areas of land degradation. Ground-based surveys are compared to existing maps of land degradation and independent remote sensing datasets. This provides a metric of evaluation by using the commonly understood confusion-matrix. A representative set of case study countries was chosen after all countries were grouped using a k-means clustering approach (see Chap. 2). Survey sites within each country were sampled according to the intersection of agro-ecological zones, land cover, and the dataset to be evaluated. This two-tiered approach to sampling ensured a diversity of ground-truth surveys and therefore a robustness of results. Although ground-based surveys are resource and time-intensive, they provide information on both the evolution of the land cover and the drivers of land-cover change. Land degradation is a very complex process where diverse data are often needed for interpretation.

Land degradation—defined by the Millennium Ecosystem Assessment report as the long-term loss of ecosystems services—is a global problem, negatively affecting the livelihoods and food security of billions of people. Intensifying efforts, mobilizing more investments and strengthening the policy commitment for addressing land degradation at the global level needs to be supported by a careful evaluation of the costs and benefits of action versus costs of inaction against land degradation. Consistent with the definition of land degradation, we adopt the Total Economic Value (TEV) approach to determine the costs of land degradation and use remote sensing data and global statistical databases in our analysis. The results show that the annual costs of land degradation due to land use and land cover change (LUCC) are about US$231 billion per year or about 0.41 % of the global GDP of US$56.49 trillion in 2007. Contrary to past global land degradation assessment studies, land degradation is severe in both tropical and temperate countries. However, the losses from LUCC are especially high in Sub-Saharan Africa, which accounts for 26 % of the total global costs of land degradation due to LUCC. However, the local tangible losses (mainly provisioning services) account only for 46 % of the total cost of land degradation and the rest of the cost is due to the losses of ecosystem services (ES) accruable largely to beneficiaries other than the local land users. These external ES losses include carbon sequestration, biodiversity, genetic information and cultural services. This implies that the global community bears the largest cost of land degradation, which suggests that efforts to address land degradation should be done bearing in mind that the global community, as a whole, incurs larger losses than the local communities experiencing land degradation. The cost of soil fertility mining due to using land degrading management practices on maize, rice and wheat is estimated to be about US$15 billion per year or 0.07 % of the global GDP. Though these results are based on a crop simulation approach that underestimates the impact of land degradation and covers only three crops, they reveal the high cost of land degradation for the production of the major food crops of the world. Our simulations also show that returns to investment in action against land degradation are twice larger than the cost of inaction in the first six years alone. Moreover, when one takes a 30-year planning horizon, the returns are five dollars per each dollar invested in action against land degradation. The opportunity cost accounts for the largest share of the cost of action against land degradation. This explains why land users, often basing their decisions in very short-time horizons, could degrade their lands even when they are aware of bigger longer-term losses that are incurred in the process.

This study was conducted with the objective of determining the returns to sustainable land management (SLM) at the national level in Bhutan. The study first uses satellite data on land change (Landsat) to examine land use change in 1990–2010 and its impact on sediment loading in hydroelectric power plants. The study then uses the Soil and Water Assessment Tool (SWAT) model to analyze the impact of land use change and land management on sediment loading. The results from the land use change and SWAT analyses are used to assess the economic benefits of SLM. We estimate the benefits and costs of SLM practices and compare them with the land-degrading practices that are most prevalent in Bhutan—that is, business as usual. An analysis of the drivers of adoption of SLM practices is also done to draw conclusions about strategies that Bhutan could use to enhance adoption of SLM practices. The land cover change results show that the vast majority of forested areas remained as such between 1994 and 2010. SWAT results show that with long-term SLM practices such as contouring, increased forested cover and density, terracing, and other SLM practices, soil erosion from forested area could be reduced by 50 %. Analysis of returns to SLM practices showed that citrus orchards are the most profitable enterprises in 13 of the 20 districts (dzongkhag), but they require farmers to wait for at least six years before the first harvest. Improved pasture management is the second most profitable enterprise—underscoring the potential role it can play to meet the growing demand for livestock products as household incomes increase. Returns to community forest management are low but profitable at a 10 % discount rate. Considering the drivers of SLM adoption, our research shows an inverse relationship between returns to land management and their corresponding adoption rates. The factors that increase adoption of SLM were land security, access to extension services, and roads. In summary, Bhutan’s policies and its cultural and historical background have set the country on the path to becoming a global green growth success story. Results of this study vindicate the country’s efforts to invest in sustainable land and forest management and highlight the additional policies and strategies that will enhance achievement of Bhutan’s SLM objectives.

Climate change has great impact on cropping system. Understanding how the rice production system has historically responded to external forces, both natural and anthropogenic, will provide critical insights into how the system is likely to respond in the future. The observed historic rice movement provides insights into the capability of the rice production system to adapt to climate changes. Using province-level rice production data and historic climate records, here we show that the centroid of Chinese rice production shifted northeastward over 370 km (2.98°N in latitude and 1.88°E in longitude) from 1949 to 2010. Using a linear regression model, we examined the driving factors, in particular climate, behind such rice production movement. While the major driving forces of the rice relocation are such social economic factors as urbanization, irrigation investment, and agricultural or land use policy changes, climate plays a significant role as well. We found that temperature has been a significant and coherent influence on moving the rice center in China and precipitation has had a significant but less spatially coherent influence.

This study summarizes the concept of the food-energy-water security nexus (FEW nexus). The aim is to create awareness about the importance of the nexus and to enable stakeholders to consider interconnections between the sectors in their work. The FEW nexus is discussed in the context of Africa south of the Sahara (SSA)—using Malawi and Mozambique as case studies. Even though analyzing food, energy, and water security issues simultaneously is critical given the interconnections, summarizing interventions with the FEW nexus approach in Malawi and Mozambique, we found that there are only a limited number of interventions in place. Additionally, this study reviews macro- and microeconomic models that are able to analyze the FEW nexus. On the macrolevel, especially general equilibrium models are discussed, because they show trade-offs and synergies of nexus interventions at all economic levels. These models can help guide policymakers’ understanding of nexus effects ex ante and convince them to think beyond their respective political departments. On the microlevel, the impact of nexus interventions can be assessed with qualitative and quantitative approaches. There are specific challenges for nexus interventions when it comes to aggregation and planning of the targeting. A secondary data analysis of nexus interventions shows that existing data is not sufficient to conduct research specifically related to the FEW nexus. The results of this study will help research programs to reflect the key questions required to enhance adoption of FEW technologies and inform policymakers as they formulate policies that will exploit the strong synergies of food security, energy, and water investments.

This study was conducted with the objective of determining the returns to sustainable land management (SLM) at the national level in Bhutan. The study first uses satellite data on land change (Landsat) to examine land use change in 1990–2010 and its impact on sediment loading in hydroelectric power plants. The study then uses the Soil and Water Assessment Tool (SWAT) model to analyze the impact of land use change and land management on sediment loading. The results from the land use change and SWAT analyses are used to assess the economic benefits of SLM. We estimate the benefits and costs of SLM practices and compare them with the land-degrading practices that are most prevalent in Bhutan — that is, business as usual. An analysis of the drivers of adoption of SLM practices is also done to draw conclusions about strategies that Bhutan could use to enhance adoption of SLM practices.

Agricultural practices have dramatically altered the Earth’s land cover, but the spatial extent and intensity of these practices is often difficult to catalogue. Cropland accounts for nearly 15 million square kilometers of Earth’s land cover — amounting to 12 percent of the planet’s ice-free land surface — yet information on the distribution and performance of specific crops is often available only through national or subnational statistics. Although remote-sensing products offer spatially disaggregated information, those currently available on a global scale are ill suited for many applications due to the limited separation of crop types within the area classified as cropland. Recently, however, the field has seen multiple independent efforts to incorporate the detailed information available from statistical surveys with supplemental spatial information to produce a spatially explicit global dataset specific to individual crops for the year 2000. Although these datasets provide analysts and decision makers with improved information on global cropping systems, the final global cropping maps differ from one another substantially. This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products: the dataset of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000), the spatial production allocation model (SPAM), the global agroecological zone (GAEZ) dataset, and the M3 dataset developed by Monfreda, Ramankutty, and Foley. The analysis explores not only the final cropping systems maps but also the interdependencies of each product, methodological differences, and modeling assumptions, which will provide users with information vital for discerning between datasets in selecting a product appropriate for each intended application.