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Asseng, S. et al. Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time. We thank the Agricultural Model Intercomparison and Improvement Project and its leaders C. Rosenzweig from NASA Goddard Institute for Space Studies and Columbia University (USA), J. Jones from University of Florida (USA), J. Hatfield from United States Department of Agriculture (USA) and J. Antle from Oregon State University (USA) for support. We also thank M. Lopez from CIMMYT (Turkey), M. Usman Bashir from University of Agriculture, Faisalabad (Pakistan), S. Soufizadeh from Shahid Beheshti University (Iran), and J. Lorgeou and J-C. Deswarte from ARVALIS—Institut du Végétal (France) for assistance with selecting key locations and quantifying regional crop cultivars, anthesis and maturity dates and R. Raymundo for assistance with GIS. S.A. and D.C. received financial support from the International Food Policy Research Institute (IFPRI). C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Science Foundation (project EW 119/5-1). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM—Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and P.D.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O’L. was funded through the Australian Grains Research and Development Corporation and the Department of Environment and Primary Industries Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. E.W. and Z.Z. were funded by CSIRO and the Chinese Academy of Sciences (CAS) through the research project ‘Advancing crop yield while reducing the use of water and nitrogen’ and by the CSIRO-MoE PhD Research Program. Peer reviewed

AbstractThis Analysis presents a recently developed food system indicator framework and holistic monitoring architecture to track food system transformation towards global development, health and sustainability goals. Five themes are considered: (1) diets, nutrition and health; (2) environment, natural resources and production; (3) livelihoods, poverty and equity; (4) governance; and (5) resilience. Each theme is divided into three to five indicator domains, and indicators were selected to reflect each domain through a consultative process. In total, 50 indicators were selected, with at least one indicator available for every domain. Harmonized data of these 50 indicators provide a baseline assessment of the world’s food systems. We show that every country can claim positive outcomes in some parts of food systems, but none are among the highest ranked across all domains. Furthermore, some indicators are independent of national income, and each highlights a specific aspiration for healthy, sustainable and just food systems. The Food Systems Countdown Initiative will track food systems annually to 2030, amending the framework as new indicators or better data emerge.

Diversification of production to strengthen resilience is a key tenet of climate-smart agriculture (CSA), which can help to address the complex vulnerabilities of agriculture-dependent rural communities. In this study, we investigated the relationship between the promotion of different CSA practices across four climate-smart villages (CSVs) in Myanmar. To determine the impact of the CSA practices on livelihoods and health, survey data were collected from agricultural households (n = 527) over three years. Within the time period studied, the results indicate that some the CSA practices and technologies adopted were significantly associated with changes in household dietary diversity scores (HDDS), but, in the short-term, these were not associated with improvements in the households’ food insecurity scores (HFIAS). Based on the survey responses, we examined how pathways of CSA practice adoption tailored to different contexts of Myanmar’s four agroecologies could contribute to the observed changes, including possible resulting trade-offs. We highlight that understanding the impacts of CSA adoption on household food security in CSVs will require longer-term monitoring, as most CSA options are medium- to long-cycle interventions. Our further analysis of knowledge, attitudes and practices (KAPs) amongst the households indicated a poor understanding of the household knowledge, attitudes and practices in relation to nutrition, food choices, food preparation, sanitation and hygiene. Our KAP findings indicate that current nutrition education interventions in the Myanmar CSVs are inadequate and will need further improvement for health and nutrition outcomes from the portfolio of CSA interventions.

West and East Africa experience high vari- ability of rainfall that is expected to increase with climate change. This results in fluctuations in water availability for food production and other socioeconomic activities. Water harvesting and storage can mitigate the adverse effects of rainfall variability. But past studies have shown that when investments in water storage are not guided by environ- mental health considerations, the increased availability of open water surface may increase the transmission of water- related diseases. This is demonstrated for schistosomiasis associated with small reservoirs in Burkina Faso, and for malaria in Ethiopia around large dams, small dams, and water harvesting ponds. The concern is that the rush to develop water harvesting and storage for climate change adaptation may increase the risk for already vulnerable people, in some cases more than canceling out the benefits of greater water availability. Taking health issues into account in a participatory approach to planning, design, and management of rainwater harvesting and water storage, as well as considering the full range of water storage options would enable better opportunities for enhancing resilience against climate change in vulnerable populations in sub-Saharan Africa.

Tropical reforestation (TR) has been highlighted as an important intervention for climate change mitigation because of its carbon storage potential. TR can also play other frequently overlooked, but significant, roles in helping society and ecosystems adapt to climate variability and change. For example, reforestation can ameliorate climate‐associated impacts of altered hydrological cycles in watersheds, protect coastal areas from increased storms, and provide habitat to reduce the probability of species' extinctions under a changing climate. Consequently, reforestation should be managed with both adaptation and mitigation objectives in mind, so as to maximize synergies among these diverse roles, and to avoid trade‐offs in which the achievement of one goal is detrimental to another. Management of increased forest cover must also incorporate measures for reducing the direct and indirect impacts of changing climate on reforestation itself. Here we advocate a focus on “climate‐smart reforestation,” defined as reforesting for climate change mitigation and adaptation, while ensuring that the direct and indirect impacts of climate change on reforestation are anticipated and minimized.

Over the past 70 years, the world has witnessed extraordinary growth in crop productivity, enabled by a suite of technological advances, including higher yielding crop varieties, improved farm management, synthetic agrochemicals, and agricultural mechanization. While this “Green Revolution” intensified crop production, and is credited with reducing famine and malnutrition, its benefits were accompanied by several undesirable collateral effects (Pingali, 2012). These include a narrowing of agricultural biodiversity, stemming from increased monoculture and greater reliance on a smaller number of crops and crop varieties for the majority of our calories. This reduction in diversity has created vulnerabilities to pest and disease epidemics, climate variation, and ultimately to human health (Harlan, 1972). The value of crop diversity has long been recognized (Vavilov, 1992). A global system of genebanks (e.g., www.genebanks.org/genebanks/) was established in the 1970s to conserve the abundant genetic variation found in traditional “landrace” varieties of crops and in crop wild relatives (Harlan, 1972). While preserving crop variation is a critical first step, the time has come to make use of this variation to breed more resilient crops. The DivSeek International Network (https://divseekintl.org/) is a scientific, not-for-profit organization that aims to accelerate such efforts.