Extreme climate events increase risk of global food insecurity and adaptation needs (original) (raw)
References
Handmer, J. et al. in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, (eds Field, C. B. et al.) 231–290 (Cambridge Univ. Press, 2012).
Tao, F. & Zhang, Z. Climate change, high-temperature stress, rice productivity, and water use in eastern China: a new superensemble-based probabilistic projection. J. Appl. Meteorol. Climatol.52, 531–551 (2013). ArticleADS Google Scholar
Challinor, A. J., Simelton, E. S., Fraser, E. D. G., Hemming, D. & Collins, M. Increased crop failure due to climate change: assessing adaptation options using models and socio-economic data for wheat in China. Environ. Res. Lett.5, 034012 (2010). ArticleADS Google Scholar
Urban, D., Roberts, M. J., Schlenker, W. & Lobell, D. B. Projected temperature changes indicate significant increase in interannual variability of US maize yields. Clim. Change112, 525–533 (2012). ArticleADS Google Scholar
Müller, C. & Robertson, R. D. Projecting future crop productivity for global economic modeling. Agric. Econ.45, 37–50 (2014). Article Google Scholar
Nelson, G. C. et al. Climate change effects on agriculture: economic responses to biophysical shocks. Proc. Natl Acad. Sci. USA111, 3274–3279 (2014). ArticleADSCASPubMed Google Scholar
Rosenzweig, C. & Parry, M. L. Potential impact of climate change on world food supply. Nature367, 133–138 (1994). ArticleADS Google Scholar
Fischer, G., Shah, M., N. Tubiello, F. & van Velhuizen, H. Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080. Philos. Trans. R. Soc. B Biol. Sci.360, 2067–2083 (2005). Article Google Scholar
Nelson, G. C. et al. Food Security, Farming, and Climate Change to 2050, Scenarios, Results, Policy Options (IFPRI, 2010). Google Scholar
Hasegawa, T. et al. Climate Change impact and adaptation assessment on food consumption utilizing a new scenario framework. Environ. Sci. Technol.48, 438–445 (2014). ArticleADSCASPubMed Google Scholar
Lobell, D. B. et al. Prioritizing climate change adaptation needs for food security in 2030. Science319, 607–610 (2008). ArticleCASPubMed Google Scholar
Fuss, S. et al. Global food security & adaptation under crop yield volatility. Technol. Forecast. Soc. Change98, 223–233 (2015). Article Google Scholar
Diffenbaugh, N. S., Hertel, T. W., Scherer, M. & Verma, M. Response of corn markets to climate volatility under alternative energy futures. Nat. Clim. Chang.2, 514–518 (2012). ArticleADSPubMedPubMed Central Google Scholar
Ahmed, A. S., Diffenbaugh, S. N. & Hertel, W. T. Climate volatility deepens poverty vulnerability in developing countries. Environ. Res. Lett.4, 034004 (2009). ArticleADS Google Scholar
Ahmed, S. A. et al. Climate volatility and poverty vulnerability in Tanzania. Glob. Environ. Change21, 46–55 (2011). Article Google Scholar
Suweis, S., Carr, J. A., Maritan, A., Rinaldo, A. & D’Odorico, P. Resilience and reactivity of global food security. Proc. Natl Acad. Sci. USA112, 6902–6907 (2015). ArticleADSCASPubMedPubMed Central Google Scholar
Puma, M. J., Bose, S., Chon, S. Y. & Cook, B. I. Assessing the evolving fragility of the global food system. Environ. Res. Lett.10, 024007 (2015). ArticleADS Google Scholar
Chatzopoulos, T., Perez Dominguez, I., Zampieri, M. & Toreti, A. Climate extremes and agricultural commodity markets: a global economic analysis of regionally simulated events. Weather Clim. Extrem.27, 100193 (2019). Article Google Scholar
Katz, R. W. & Brown, B. G. Extreme events in a changing climate: variability is more important than averages. Clim. Change21, 289–302 (1992). ArticleADS Google Scholar
Salinger, M. J. Climate variability and change: past, present and future–an overview. Clim. Change70, 9–29 (2005). ArticleADSCAS Google Scholar
Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.), 741–866 (Cambridge University Press, 2013).
The State of Food Insecurity in the World 2012: Economic Growth Is Necessary but Not Sufficient to Accelerate Reduction of Hunger and Malnutrition (Food and Agriculture Organization, 2012).
Hasegawa, T. et al. Consequence of climate mitigation on the risk of hunger. Environ. Sci. Technol.49, 7245–7253 (2015). ArticleADSCASPubMed Google Scholar
Sakurai, G., Iizumi, T., Nishimori, M. & Yokozawa, M. How much has the increase in atmospheric CO2 directly affected past soybean production? Sci. Rep.4, 4978 (2014). ArticleADSCASPubMedPubMed Central Google Scholar
Fujimori, S., Masui, T. and Matsuoka, Y. AIM/CGE [Basic] Manual (Center for Social and Environmental Systems Research, NIES, 2012).
Sillmann, J. et al. Understanding, modeling and predicting weather and climate extremes: challenges and opportunities. Weather Clim. Extrem.18, 65–74 (2017). Article Google Scholar
Attribution of Extreme Weather Events in the Context of Climate Change (National Academies Press, 2016).
Stephenson, D. B. in Climate Extremes and Society (eds Diaz H. F. & Murnane R. J.) 11–23 (Cambridge University Press, 2008).
Hasegawa, T., Fujimori, S., Takahashi, K. & Masui, T. Scenarios for the risk of hunger in the twenty-first century using shared socioeconomic pathways. Environ. Res. Lett.10, 014010 (2015). ArticleADS Google Scholar
Fujimori, S. et al. A multi-model assessment of food security implications of climate change mitigation. Nat. Sustain.2, 386–396 (2019). Article Google Scholar
van Meijl, H., Tabeau, A., Stehfest, E., Doelman, J. & Lucas, P. How food secure are the green, rocky and middle roads: food security effects in different world development paths. Environ. Res. Commun.2, 031002 (2020). Article Google Scholar
van Vuuren, D. P. et al. The representative concentration pathways: an overview. Clim. Change109, 5–31 (2011). ArticleADS Google Scholar
Hasegawa, T. et al. Risk of increased food insecurity under stringent global climate change mitigation policy. Nat. Clim. Chang.8, 699–703 (2018). ArticleADS Google Scholar
Lassa, J. A., Teng, P., Caballero-Anthony, M. & Shrestha, M. Revisiting emergency food reserve policy and practice under disaster and extreme climate events. Int. J. Disaster Risk Sci.10, 1–13 (2019). Article Google Scholar
International Assessment of Agricultural Knowledge: Science and Technology for Development Global Report (IAASTD, 2009).
Stathers, T., Lamboll, R. & Mvumi, B. M. Postharvest agriculture in changing climates: its importance to African smallholder farmers. Food Sec.5, 361–392 (2013). Article Google Scholar
Chriest, A. & Niles, M. The role of community social capital for food security following an extreme weather event. J. Rural Stud.64, 80–90 (2018). Article Google Scholar
World Agricultural Supply and Demand Estimates Report (US Department of Agriculture, 2016).
O’Neill, B. C. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim. Change122, 387–400 (2014). ArticleADS Google Scholar
Riahi, K. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Global Environ. Change42, 153–168 (2017). Article Google Scholar
Fujimori, S. et al. SSP3: AIM implementation of Shared Socioeconomic Pathways. Global Environ. Change42, 268–283 (2017). Article Google Scholar
Masutomi, Y., Takahashi, K., Harasawa, H. & Matsuoka, Y. Impact assessment of climate change on rice production in Asia in comprehensive consideration of process/parameter uncertainty in general circulation models. Agric. Ecosyst. Environ.131, 281–291 (2009). Article Google Scholar
Denman, K. L. et al. Couplings Between Changes in the Climate System and Biogeochemistry (Cambridge University Press, 2007). Google Scholar
Lal, P. N. et al. in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, [Field, C.B. et al. (eds.)]. 339–392 (Cambridge University Press, 2012).
Hertel, T. W. Food security under climate change. Nat. Clim. Chang.6, 10–13 (2016). ArticleADS Google Scholar
O’Neill, B. C. et al. Achievements and needs for the climate change scenario framework. Nat. Clim. Chang.10, 1074–1084 (2020). ArticleADS Google Scholar
Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc.93, 485–498 (2011). ArticleADS Google Scholar
Hempel, S.F., Frieler, K., Warszawski, L., Schewe, J. & Piontek, F. Bias Corrected GCM Input Data for ISIMIP Fast Track (GFZ Data Services, 2013).
Iizumi, T., Takikawa, H., Hirabayashi, Y., Hanasaki, N. & Nishimori, M. Contributions of different bias-correction methods and reference meteorological forcing data sets to uncertainty in projected temperature and precipitation extremes. J. Geophys. Res. Atmos.122, 7800–7819 (2017). ArticleADS Google Scholar
Iizumi, T. et al. Prediction of seasonal climate-induced variations in global food production. Nat. Clim. Chang.3, 904–908 (2013). ArticleADS Google Scholar
Parry, M., Rosenzweig, C., Iglesias, A., Fischer, G. & Livermore, M. Climate change and world food security: a new assessment. Global Environ. Change9, S51–S67 (1999). Article Google Scholar
Mastrandrea, M. D. et al. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties (IPCC, 2010).
Zhou, D., Yu, X. & Herzfeld, T. Dynamic Food Demand in Urban China. GlobalFood Discussion Paper (Georg-August-Universität Göttingen, 2014).
Bhargava, A. Estimating short and long run income elasticities of foods and nutrients for rural south India. J. R. Stat. Soc. Ser. A Stat. Soc.154, 157–174 (1991). Article Google Scholar
Farquhar, G. D., von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta149, 78–90 (1980). ArticleCASPubMed Google Scholar
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Williams, J. R. & King, K. W. Soil and Water Assessment Tool Theoretical Documentation (Grassland Soil and Water Research Laboratory, Agricultural Research Service, United States Department of Agriculture, 2009).
Iizumi, T. et al. Historical changes in global yields: major cereal and legume crops from 1982 to 2006. Glob. Ecol. Biogeogr.23, 346–357 (2014). Article Google Scholar
Vrugt J. A. A. H., et al. Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling. Int. J. Nonlinear Sci. Numer. Simul. 10 (2009).
Baldocchi, D. An analytical solution for coupled leaf photosynthesis and stomatal conductance models. Tree Physiol.14, 1069–1079 (1994). ArticlePubMed Google Scholar
Fujimori, S., Hasegawa, T., Masui, T. & Takahashi, K. Land use representation in a global CGE model for long-term simulation: CET vs. logit functions. Food Sec.6, 685–699 (2014). Article Google Scholar
von Lampe, M. et al. Why do global long-term scenarios for agriculture differ? An overview of the AgMIP global economic model intercomparison. Agric. Econ.45, 3–20 (2014). Article Google Scholar
Hanasaki, N. et al. A global water scarcity assessment under Shared Socio-economic Pathways—part 1: water use. Hydrol. Earth Syst. Sci.17, 2375–2391 (2013). ArticleADS Google Scholar
FAO Methodology for the Measurement of Food Deprivation: Updating the Minimum Dietary Energy Requirements (Food and Agriculture Organization, 2008).