Marshall Burke

Prioritizing climate change adaptation needs for food security in 2030

Investments aimed at improving agricultural adaptation to climate change inevitably favor some crops and regions over others. An analysis of climate risks for crops in 12 food-insecure regions was conducted to identify adaptation priorities, based on statistical crop models and climate projections for 2030 from 20 general circulation models. Results indicate South Asia and Southern Africa as two regions that, without sufficient adaptation measures, will likely suffer negative impacts on several crops that are important to large food-insecure human populations. We also find that uncertainties vary widely by crop, and therefore priorities will depend on the risk attitudes of investment institutions.

Quantifying the influence of climate on human conflict

Introduction Despite the existence of institutions designed to promote peace, interactions between individuals and groups sometimes lead to conflict. Understanding the causes of such conflict is a major project in the social sciences, and researchers in anthropology, economics, geography, history, political science, psychology, and sociology have long debated the extent to which climatic changes are responsible. Recent advances and interest have prompted an explosion of quantitative studies on this question. Climate and conflict across spatial scales. Evidence that temperature influences the risk of modern human conflict: (A) local violence in 1° grid cells, (B) civil war in countries, and (C) civil conflict risk in the tropics. The map depicts regions of analysis corresponding to nonparametric watercolor regressions in (A) to (C). The color intensity in (A) to (C) indicates the level of certainty in the regression line. Methods We carried out a comprehensive synthesis of the rapidly growing literature on climate and human conflict. We examined many types of human conflict, ranging from interpersonal violence and crime to intergroup violence and political instability and further to institutional breakdown and the collapse of civilizations. We focused on quantitative studies that can reliably infer causal associations between climate variables and conflict outcomes. The studies we examined are experiments or “natural experiments”; the latter exploit variations in climate over time that are plausibly independent of other variables that also affect conflict. In many cases, we obtained original data from studies that did not meet this criterion and used a common statistical method to reanalyze these data. In total, we evaluated 60 primary studies that have examined 45 different conflict data sets. We collected findings across time periods spanning 10,000 BCE to the present and across all major world regions. Results Deviations from normal precipitation and mild temperatures systematically increase the risk of conflict, often substantially. This relationship is apparent across spatial scales ranging from a single building to the globe and at temporal scales ranging from an anomalous hour to an anomalous millennium. Our meta-analysis of studies that examine populations in the post-1950 era suggests that the magnitude of climate’s influence on modern conflict is both substantial and highly statistically significant (P < 0.001). Each 1-SD change in climate toward warmer temperatures or more extreme rainfall increases the frequency of interpersonal violence by 4% and intergroup conflict by 14% (median estimates). Discussion We conclude that there is more agreement across studies regarding the influence of climate on human conflict than has been recognized previously. Given the large potential changes in precipitation and temperature regimes projected for the coming decades—with locations throughout the inhabited world expected to warm by 2 to 4 SDs by 2050—amplified rates of human conflict could represent a large and critical social impact of anthropogenic climate change in both low- and high-income countries. Climate and Conflict Knowledge silos can hinder attempts to explore questions of interest across many disciplines. Hsiang et al. (p. 1235367, published online 1 August) provide a meta-analysis of data from disciplines as disparate as archaeology and psychology to examine the relation between climate and conflict. Overall, warmer temperatures or extremes of rainfall can be causally associated with changes in interpersonal violence and in civil war. Across disciplinary boundaries, recently published evidence links climate change to increased violent conflict. A rapidly growing body of research examines whether human conflict can be affected by climatic changes. Drawing from archaeology, criminology, economics, geography, history, political science, and psychology, we assemble and analyze the 60 most rigorous quantitative studies and document, for the first time, a striking convergence of results. We find strong causal evidence linking climatic events to human conflict across a range of spatial and temporal scales and across all major regions of the world. The magnitude of climate’s influence is substantial: for each one standard deviation (1σ) change in climate toward warmer temperatures or more extreme rainfall, median estimates indicate that the frequency of interpersonal violence rises 4% and the frequency of intergroup conflict rises 14%. Because locations throughout the inhabited world are expected to warm 2σ to 4σ by 2050, amplified rates of human conflict could represent a large and critical impact of anthropogenic climate change.

The Ripple Effect: Biofuels, Food Security, and the Environment

An additional 2–2.5 billion people living on

Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation

1 to

Global non-linear effect of temperature on economic production

2 per day are also at risk, as rising commodity prices could pull them swiftly into a food-insecure state.The potential impact of a large global expansion of biofuels production capacity on net food producers and consumers in low-income countries presents challenges for food policy planners and raises the question of whether sustainable development targets at a more general level can be reached.

Assessing risks of climate variability and climate change for Indonesian rice agriculture

Estimates of climate change impacts are often characterized by large uncertainties that reflect ignorance of many physical, biological, and socio-economic processes, and which hamper efforts to anticipate and adapt to climate change. A key to reducing these uncertainties is improved understanding of the relative contributions of individual factors. We evaluated uncertainties for projections of climate change impacts on crop production for 94 crop–region combinations that account for the bulk of calories consumed by malnourished populations. Specifically, we focused on the relative contributions of four factors: climate model projections of future temperature and precipitation, and the sensitivities of crops to temperature and precipitation changes. Surprisingly, uncertainties related to temperature represented a greater contribution to climate change impact uncertainty than those related to precipitation for most crops and regions, and in particular the sensitivity of crop yields to temperature was a critical source of uncertainty. These findings occurred despite rainfalls important contribution to year-to-year variability in crop yields and large disagreements among global climate models over the direction of future regional rainfall changes, and reflect the large magnitude of future warming relative to historical variability. We conclude that progress in understanding crop responses to temperature and the magnitude of regional temperature changes are two of the most important needs for climate change impact assessments and adaptation efforts for agriculture.

Combining satellite imagery and machine learning to predict poverty

Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies, but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries. In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature, while poor countries respond only linearly. Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems and to anticipating the global impact of climate change. Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is non-linear in temperature for all countries, with productivity peaking at an annual average temperature of 13 °C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change, with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.

Solar-powered drip irrigation enhances food security in the Sudano–Sahel

El Niño events typically lead to delayed rainfall and decreased rice planting in Indonesias main rice-growing regions, thus prolonging the hungry season and increasing the risk of annual rice deficits. Here we use a risk assessment framework to examine the potential impact of El Niño events and natural variability on rice agriculture in 2050 under conditions of climate change, with a focus on two main rice-producing areas: Java and Bali. We select a 30-day delay in monsoon onset as a threshold beyond which significant impact on the countrys rice economy is likely to occur. To project the future probability of monsoon delay and changes in the annual cycle of rainfall, we use output from the Intergovernmental Panel on Climate Change AR4 suite of climate models, forced by increasing greenhouse gases, and scale it to the regional level by using empirical downscaling models. Our results reveal a marked increase in the probability of a 30-day delay in monsoon onset in 2050, as a result of changes in the mean climate, from 9–18% today (depending on the region) to 30–40% at the upper tail of the distribution. Predictions of the annual cycle of precipitation suggest an increase in precipitation later in the crop year (April–June) of ≈10% but a substantial decrease (up to 75% at the tail) in precipitation later in the dry season (July–September). These results indicate a need for adaptation strategies in Indonesian rice agriculture, including increased investments in water storage, drought-tolerant crops, crop diversification, and early warning systems.

Climate, conflict, and social stability: what does the evidence say?

Measuring consumption and wealth remotely Nighttime lighting is a rough proxy for economic wealth, and nighttime maps of the world show that many developing countries are sparsely illuminated. Jean et al. combined nighttime maps with high-resolution daytime satellite images (see the Perspective by Blumenstock). With a bit of machine-learning wizardry, the combined images can be converted into accurate estimates of household consumption and assets, both of which are hard to measure in poorer countries. Furthermore, the night- and day-time data are publicly available and nonproprietary. Science, this issue p. 790; see also p. 753 Satellites collect data that can be used to measure income and wealth. Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries—Nigeria, Tanzania, Uganda, Malawi, and Rwanda—we show how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes. Our method, which requires only publicly available data, could transform efforts to track and target poverty in developing countries. It also demonstrates how powerful machine learning techniques can be applied in a setting with limited training data, suggesting broad potential application across many scientific domains.

Adaptation to Climate Change: Evidence from US Agriculture

Meeting the food needs of Africa’s growing population over the next half-century will require technologies that significantly improve rural livelihoods at minimal environmental cost. These technologies will likely be distinct from those of the Green Revolution, which had relatively little impact in sub-Saharan Africa; consequently, few such interventions have been rigorously evaluated. This paper analyzes solar-powered drip irrigation as a strategy for enhancing food security in the rural Sudano–Sahel region of West Africa. Using a matched-pair comparison of villages in northern Benin (two treatment villages, two comparison villages), and household survey and field-level data through the first year of harvest in those villages, we find that solar-powered drip irrigation significantly augments both household income and nutritional intake, particularly during the dry season, and is cost effective compared to alternative technologies.