Robust negative impacts of climate change on African agriculture
Open accessAbstract
There is widespread interest in the impacts of climate change on agriculture in Sub-Saharan Africa (SSA), and on the most effective investments to assist adaptation to these changes, yet the scientific basis for estimating production risks and prioritizing investments has been quite limited.Here we show that by combining historical crop production and weather data into a panel analysis, a robust model of yield response to climate change emerges for several key African crops.By mid-century, the mean estimates of aggregate production changes in SSA under our preferred model specification are -22, -17, -17, -18, and -8% for maize, sorghum, millet, groundnut, and cassava, respectively.In all cases except cassava, there is a 95% probability that damages exceed 7%, and a 5% probability that they exceed 27%.Moreover, countries with the highest average yields have the largest projected yield losses, suggesting that well-fertilized modern seed varieties are more susceptible to heat related losses.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The use of the multi-model ensemble in probabilistic climate projections
Tebaldi, C., & Knutti, R. (2007) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2007.2076 · Cited by 1,862 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
What Do We Learn from the Weather? The New Climate-Economy Literature
Dell, M., Jones, B. F., & Olken, B. A. (2014) · Journal of Economic Literature · doi:10.1257/jel.52.3.740 · Cited by 2,300 · see citing works
Quantifying the influence of climate on human conflict
Hsiang, S. M., Burke, M., & Miguel, E. (2013) · Science · doi:10.1126/science.1235367 · Cited by 1,827 · see citing works
Social and economic impacts of climate
Carleton, T. A., & Hsiang, S. M. (2016) · Science · doi:10.1126/science.aad9837 · Cited by 1,348 · see citing works
Nonlinear heat effects on African maize as evidenced by historical yield trials
Lobell, D. B., Bänziger, M., Magorokosho, C., & Vivek, B. (2011) · Nature Climate Change · doi:10.1038/nclimate1043 · Cited by 1,206 · see citing works
Self-citationThe critical role of extreme heat for maize production in the United States
Lobell, D. B., Hammer, G. L., McLean, G., Messina, C., Roberts, M. J., & Schlenker, W. (2013) · Nature Climate Change · doi:10.1038/nclimate1832 · Cited by 1,026 · see citing works
Self-citationClimate change impacts in Sub-Saharan Africa: from physical changes to their social repercussions
Serdeczny, O., Adams, S., Baarsch, F., Coumou, D., Robinson, A., Hare, W., Schaeffer, M., Perrette, M., & Reinhardt, J. (2017) · Regional Environmental Change · doi:10.1007/s10113-015-0910-2 · Cited by 1,037 · see citing works
Adaptation to climate change: Evidence from US agriculture
Burke, M., & Emerick, K. (2016) · American Economic Journal: Economic Policy · doi:10.1257/pol.20130025 · Cited by 922 · see citing works
Using weather data and climate model output in economic analyses of climate change
Auffhammer, M., Hsiang, S. M., Schlenker, W., & Sobel, A. (2013) · Review of Environmental Economics and Policy · doi:10.1093/reep/ret016 · Cited by 662 · see citing works
Self-citationBurke, M., Hsiang, S. M., & Miguel, E. (2015) · Annual Review of Economics · doi:10.1146/annurev-economics-080614-115430 · Cited by 655 · see citing works
Effect of warming temperatures on US wheat yields
Tack, J., Barkley, A., & Nalley, L. L. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1415181112 · Cited by 472 · see citing works
Crop-damaging temperatures increase suicide rates in India
Carleton, T. A. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1701354114 · Cited by 446 · see citing works
A meta-analysis of country-level studies on environmental change and migration
Hoffmann, R., Dimitrova, A., Muttarak, R., Crespo Cuaresma, J., & Peisker, J. (2020) · Nature Climate Change · doi:10.1038/s41558-020-0898-6 · Cited by 362 · see citing works
Extreme Weather and Civil War: Does Drought Fuel Conflict in Somalia through Livestock Price Shocks?
Maystadt, J.-F., & Ecker, O. (2014) · American Journal of Agricultural Economics · doi:10.1093/ajae/aau010 · Cited by 346 · see citing works
Abid, M., Schneider, U. A., & Scheffran, J. (2016) · Journal of Rural Studies · doi:10.1016/j.jrurstud.2016.08.005 · Cited by 296 · see citing works
Martin-Shields, C. P., & Stojetz, W. (2019) · World Development · doi:10.1016/j.worlddev.2018.07.011 · Cited by 302 · see citing works
The global technical potential of bio-energy in 2050 considering sustainability constraints
Haberl, H., Beringer, T., Bhattacharya, S. C., Erb, K.-H., & Hoogwijk, M. (2010) · Current Opinion in Environmental Sustainability · doi:10.1016/j.cosust.2010.10.007 · Cited by 285 · see citing works
Decreases in global beer supply due to extreme drought and heat
Xie, W., Xiong, W., Pan, J., Ali, T., Cui, Q., Guan, D., Meng, J., Mueller, N. D., Lin, E., & Davis, S. J. (2018) · Nature Plants · doi:10.1038/s41477-018-0263-1 · Cited by 226 · see citing works
The influence of climate variability on internal migration flows in South Africa
Mastrorillo, M., Licker, R., Bohra-Mishra, P., Fagiolo, G., D. Estes, L., & Oppenheimer, M. (2016) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.04.014 · Cited by 219 · see citing works
Drought and Civil War in Sub‐Saharan Africa
Couttenier, M., & Soubeyran, R. (2014) · The Economic Journal · doi:10.1111/ecoj.12042 · Cited by 212 · see citing works
Negative impacts of climate change on cereal yields: statistical evidence from France
Gammans, M., Mérel, P., & Ortiz-Bobea, A. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/aa6b0c · Cited by 185 · see citing works
Estimating global agricultural effects of geoengineering using volcanic eruptions
Proctor, J., Hsiang, S., Burney, J., Burke, M., & Schlenker, W. (2018) · Nature · doi:10.1038/s41586-018-0417-3 · Cited by 159 · see citing works
Self-citationReconciling top-down and bottom-up modelling on future bioenergy deployment
Creutzig, F., Popp, A., Plevin, R., Luderer, G., Minx, J., & Edenhofer, O. (2012) · Nature Climate Change · doi:10.1038/nclimate1416 · Cited by 147 · see citing works
Climate variability and migration in the Philippines
Bohra-Mishra, P., Oppenheimer, M., Cai, R., Feng, S., & Licker, R. (2017) · Population and Environment · doi:10.1007/s11111-016-0263-x · Cited by 137 · see citing works
Jones, B. T., Mattiacci, E., & Braumoeller, B. F. (2017) · Journal of Peace Research · doi:10.1177/0022343316684662 · Cited by 132 · see citing works
Waha, K., Müller, C., & Rolinski, S. (2013) · Global and Planetary Change · doi:10.1016/j.gloplacha.2013.02.009 · Cited by 106 · see citing works
Climate change, agricultural production and civil conflict: evidence from the Philippines
Crost, B., Duquennois, C., Felter, J. H., & Rees, D. I. (2018) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2018.01.005 · Cited by 91 · see citing works
The supply and demand of net primary production in the Sahel
Abdi, A. M., Seaquist, J., Tenenbaum, D. E., Eklundh, L., & Ardö, J. (2014) · Environmental Research Letters · doi:10.1088/1748-9326/9/9/094003 · Cited by 86 · see citing works
Climate variability and educational attainment: Evidence from rural Ethiopia
Randell, H., & Gray, C. (2016) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.09.006 · Cited by 81 · see citing works
Agroecological transitions: a mathematical perspective on a transdisciplinary problem
Ong, T. W. Y., & Liao, W. (2020) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2020.00091 · Cited by 46 · see citing works
Is environmentally induced income variability a driver of human migration?
Marchiori, L., Maystadt, J.-F., & Schumacher, I. (2017) · Migration and Development · doi:10.1080/21632324.2015.1020106 · Cited by 24 · see citing works
da Silva Dias, J. C. (2015) · Molecular Approaches to Genetic Diversity · doi:10.5772/60080 · Cited by 13 · see citing works
The evolution of the evidence base for observed impacts of climate change
Hansen, G. (2015) · Current Opinion in Environmental Sustainability · doi:10.1016/j.cosust.2015.05.005 · Cited by 12 · see citing works
- Authors
- Schlenker, W., & Lobell, D. B.
- Affiliations
- Columbia University (US)
- Stanford University (US)
- Venue
- Environmental Research Letters
- Publisher
- IOP Publishing
- Published
- 2010-01
- Volume
- 5
- Issue
- 1
- Pages
- 014010
- ISSN
- 1748-9326 (ISSN-L)
- OpenAlex
- W2079350221
- Cited by
- 1,492
- References
- 1
- Citations by year
- 2026: 80 · 2025: 88 · 2024: 94 · 2023: 80 · 2022: 101 · 2021: 132 · 2020: 180 · 2019: 111 · 2018: 110 · 2017: 103 · 2016: 83 · 2015: 69 · 2014: 97 · 2013: 59 · 2012: 63
- FWCI
- 54.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Environmental Research Letters (publishedVersion, cc-by)
- Funders
- U.S. Department of Energy
- Rockefeller Foundation
- Office of Science
- Topics
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Climate change impacts on agriculture
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Agricultural risk and resilience
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Keywords
- climate change impacts on agriculture, crop yield loss, sub-Saharan Africa, maize, sorghum, millet, groundnut, cassava, heat stress, agricultural adaptation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review