Marshall Burke is assistant professor in the Department of Earth System Science, and Center Fellow at the Center on Food Security and the Environment at Stanford University. His research focuses on social and economic impacts of environmental change, and on the economics of rural development in Africa. His work has appeared in both economics and scientific journals, including recent publications in Nature, Science, the Proceedings of the National Academy of Sciences, and the Review of Economics and Statistics. He holds a PhD in Agricultural and Resource Economics from UC Berkeley, and a BA in International Relations from Stanford.
Prospective students should see my personal webpage, linked at right.
Assistant Professor, Earth System Science
Center Fellow, Freeman Spogli Institute for International Studies
Center Fellow (By courtesy), Stanford Woods Institute for the Environment
- CLIMATE AND SOCIETY
EARTH 2 (Win)
- World Food Economy
EARTHSYS 106, EARTHSYS 206, ECON 106, ESS 106, ESS 206 (Spr)
- Independent Studies (3)
- Prior Year Courses
Satellite-based assessment of yield variation and its determinants in smallholder African systems.
Proceedings of the National Academy of Sciences of the United States of America
2017; 114 (9): 2189-2194
The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest ([Formula: see text] up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods.
View details for DOI 10.1073/pnas.1616919114
View details for PubMedID 28202728
View details for PubMedCentralID PMC5338538
Sources of variation in under-5 mortality across sub-Saharan Africa: a spatial analysis.
The Lancet. Global health
Detailed spatial understanding of levels and trends in under-5 mortality is needed to improve the targeting of interventions to the areas of highest need, and to understand the sources of variation in mortality. To improve this understanding, we analysed local-level information on child mortality across sub-Saharan Africa between 1980-2010.We used data from 82 Demographic and Health Surveys in 28 sub-Saharan African countries, including the location and timing of 3·24 million childbirths and 393 685 deaths, to develop high-resolution spatial maps of under-5 mortality in the 1980s, 1990s, and 2000s. These estimates were at a resolution of 0·1 degree latitude by 0·1 degree longitude (roughly 10 km × 10 km). We then analysed this spatial information to distinguish within-country versus between-country sources of variation in mortality, to examine the extent to which declines in mortality have been accompanied by convergence in the distribution of mortality, and to study localised drivers of mortality differences, including temperature, malaria burden, and conflict.In our sample of sub-Saharan African countries from the 1980s to the 2000s, within-country differences in under-5 mortality accounted for 74-78% of overall variation in under-5 mortality across space and over time. Mortality differed significantly across only 8-15% of country borders, supporting the role of local, rather than national, factors in driving mortality patterns. We found that by the end of the study period, 23% of the eligible children in the study countries continue to live in mortality hotspots-areas where, if current trends continue, the Sustainable Developent Goals mortality targets will not be met. In multivariate analysis, within-country mortality levels at each pixel were significantly related to local temperature, malaria burden, and recent history of conflict.Our findings suggest that sub-national determinants explain a greater portion of under-5 mortality than do country-level characteristics. Sub-national measures of child mortality could provide a more accurate, and potentially more actionable, portrayal of where and why children are still dying than can national statistics.The Stanford Woods Institute for the Environment.
View details for DOI 10.1016/S2214-109X(16)30212-1
View details for PubMedID 27793587
Combining satellite imagery and machine learning to predict poverty.
2016; 353 (6301): 790-794
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.
View details for DOI 10.1126/science.aaf7894
View details for PubMedID 27540167
- Adaptation to Climate Change: Evidence from US Agriculture AMERICAN ECONOMIC JOURNAL-ECONOMIC POLICY 2016; 8 (3): 106-140
Global non-linear effect of temperature on economic production
2015; 527 (7577): 235-?
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.
View details for DOI 10.1038/nature15725
View details for Web of Science ID 000364396700045
View details for PubMedID 26503051
- INCORPORATING CLIMATE UNCERTAINTY INTO ESTIMATES OF CLIMATE CHANGE IMPACTS REVIEW OF ECONOMICS AND STATISTICS 2015; 97 (2): 461-471
- Climate and Conflict ANNUAL REVIEW OF ECONOMICS, VOL 7 2015; 7: 577-?
- Reconciling climate-conflict meta-analyses: reply to Buhaug et al. CLIMATIC CHANGE 2014; 127 (3-4): 399-405
- Climate, conflict, and social stability: what does the evidence say? CLIMATIC CHANGE 2014; 123 (1): 39-55
Quantifying the influence of climate on human conflict.
2013; 341 (6151): 1235367-?
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.
View details for DOI 10.1126/science.1235367
View details for PubMedID 24031020
- On the use of statistical models to predict crop yield responses to climate change AGRICULTURAL AND FOREST METEOROLOGY 2010; 150 (11): 1443-1452
- The poverty implications of climate-induced crop yield changes by 2030 GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS 2010; 20 (4): 577-585
Solar-powered drip irrigation enhances food security in the Sudano-Sahel
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2010; 107 (5): 1848-1853
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.
View details for DOI 10.1073/pnas.0909678107
View details for Web of Science ID 000274296300011
View details for PubMedID 20080616
- Impacts of El Nino-Southern Oscillation events on China's rice production JOURNAL OF GEOGRAPHICAL SCIENCES 2010; 20 (1): 3-16
Warming increases the risk of civil war in Africa
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2009; 106 (49): 20670-20674
Armed conflict within nations has had disastrous humanitarian consequences throughout much of the world. Here we undertake the first comprehensive examination of the potential impact of global climate change on armed conflict in sub-Saharan Africa. We find strong historical linkages between civil war and temperature in Africa, with warmer years leading to significant increases in the likelihood of war. When combined with climate model projections of future temperature trends, this historical response to temperature suggests a roughly 54% increase in armed conflict incidence by 2030, or an additional 393,000 battle deaths if future wars are as deadly as recent wars. Our results suggest an urgent need to reform African governments' and foreign aid donors' policies to deal with rising temperatures.
View details for DOI 10.1073/pnas.0907998106
View details for Web of Science ID 000272553000024
View details for PubMedID 19934048
- Shifts in African crop climates by 2050, and the implications for crop improvement and genetic resources conservation GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS 2009; 19 (3): 317-325
- A Global Model Tracking Water, Nitrogen, and Land Inputs and Virtual Transfers from Industrialized Meat Production and Trade ENVIRONMENTAL MODELING & ASSESSMENT 2009; 14 (2): 179-193
- Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation ENVIRONMENTAL RESEARCH LETTERS 2008; 3 (3)
Prioritizing climate change adaptation needs for food security in 2030
2008; 319 (5863): 607-610
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.
View details for DOI 10.1126/science.1152339
View details for Web of Science ID 000252772000037
View details for PubMedID 18239122
International trade in meat: The tip of the pork chop
2007; 36 (8): 622-629
This paper provides an original account of global land, water, and nitrogen use in support of industrialized livestock production and trade, with emphasis on two of the fastest-growing sectors, pork and poultry. Our analysis focuses on trade in feed and animal products, using a new model that calculates the amount of "virtual" nitrogen, water, and land used in production but not embedded in the product. We show how key meat-importing countries, such as Japan, benefit from "virtual" trade in land, water, and nitrogen, and how key meat-exporting countries, such as Brazil, provide these resources without accounting for their true environmental cost. Results show that Japan's pig and chicken meat imports embody the virtual equivalent of 50% of Japan's total arable land, and half of Japan's virtual nitrogen total is lost in the US. Trade links with China are responsible for 15% of the virtual nitrogen left behind in Brazil due to feed and meat exports, and 20% of Brazil's area is used to grow soybean exports. The complexity of trade in meat, feed, water, and nitrogen is illustrated by the dual roles of the US and The Netherlands as both importers and exporters of meat. Mitigation of environmental damage from industrialized livestock production and trade depends on a combination of direct-pricing strategies, regulatory approaches, and use of best management practices. Our analysis indicates that increased water- and nitrogen-use efficiency and land conservation resulting from these measures could significantly reduce resource costs.
View details for Web of Science ID 000251979900002
View details for PubMedID 18240675
The ripple effect: Biofuels, food security, and the environment
2007; 49 (9): 30-43
View details for Web of Science ID 000250943700005
Assessing risks of climate variability and climate change for Indonesian rice agriculture
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2007; 104 (19): 7752-7757
El Niño events typically lead to delayed rainfall and decreased rice planting in Indonesia's 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 country's 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 approximately 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.
View details for DOI 10.1073/pnas.0701825104
View details for Web of Science ID 000246461500007
View details for PubMedID 17483453