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Non-PR, IFPRI1; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; Statistics from Space, Natural Resources and Resilience (NRR); Transformation Strategies

Non-PR, IFPRI1; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; Statistics from Space, Natural Resources and Resilience (NRR); Transformation Strategies, Objective: Produce and disseminate accurate crop production statistics data leveraging satellite remote sensing data for timely food policy decisions in Mozambique.

PR, IFPRI3; ISI; 4 Transforming Agricultural and Rural Economies, Natural Resources and Resilience (NRR); Transformation Strategies

Non-PR, IFPRI1; DCA, Natural Resources and Resilience (NRR); Transformation Strategies, Farm Radio International (FRI) and the CGIAR Research Initiative on Digital Innovation have col laborated on the development of an end-to-end, automatic speech recognition pipeline for the tran scription, translation, and analysis of Swahili and Luganda. This task is particularly challenging due to the number of languages used by FRI's clients and the limited training data available for speech recognition in African languages. The tool is named 'Longa', or 'Let's chat' in Swahili. Longa will be used to answer the surplus of phone calls currently being received from smallholder farmers asking questions about radio programs which FRI does not presently have the capacity to address. When fully implemented, Longa should allow FRI to design their broadcasts more intricately in line with the needs of farmers and better deliver insights to those most in need, such as female and youth farmers. Key results from the collaboration include a series of design principles iteratively and col laboratively developed to reflect the common values and goals of FRI and the CGIAR, a proof of concept for Longa, building on open-source models and open access corpora, to be shared with the developer community upon completion of the final tool, a 10% improvement upon the state-of-the art automatic speech recognition in Luganda radio-speech performance and accuracy, some im provement in performance with audio enhancement processes using real-world data, and proof that fine-tuning is an effective approach to expanding Longa to new languages. The next steps of the collaboration will focus on the analysis and interpretation of an aggregation of farmer phone calls and integration with the existing FRI workflow and software.

Non-PR, IFPRI1, CPA; Natural Resources and Resilience (NRR); Transformation Strategies, Generative large language models (LLMs), while widely accessible and capable of simulating policy recommendations, pose challenges in the assessment of their accuracy. Users, including policy ana lysts and decision-makers, bear the responsibility of evaluating the outcomes from these models. A significant limitation of LLMs is their potential to overlook critical, context-specific factors. For example, in formulating food policies, it is vital to consider regional climate and environmental variables that influence water and resource availability. Nonetheless, due to their reliance on word sequencing probabilities from training datasets, LLMs might propose similar policies for distinct regions. Despite these limitations, LLMs offer considerable advantages for rapid policy analysis, particularly when resources are constrained. They serve as quick, accessible, and cost-effective tools for policy research and development, requiring minimal training and infrastructure. In our study, we assessed the efficacy of LLMs in generating policy briefs by inputting an IFPRI discussion paper into three different LLM-based approaches: a standard chatbot without extra data, a Retrieval Aug mented Generation model integrating semantic search with LLM, and a custom-developed Brief Generator designed to create policy summaries from AI-analyzed paper structures. Our findings revealed that none of the LLM-generated briefs fully captured the original paper's intent, underscor ing the need for further research. Future investigations should focus on gathering more empirical data with diverse text types and volumes to better understand these outcomes.

Non-PR, IFPRI1, Natural Resources and Resilience (NRR); Transformation Strategies, ICTforAg is an annual convening where agricultural stakeholders and technology experts come together to share knowledge, find solutions, and form partnerships to address challenges in agri-food systems across low- and middle-income countries. The main goal of ICTforAg is to grow communities and catalyze meaningful conversations, insights, and collaborations, increase participation of participants from the developing world, promote knowledge sharing and learning, and inspire practitioners to develop inclusive and sustainable ICT solutions. ICTforAg has a strong history since 2015 and owes its success to the contributions made by various organizations to build this community. In 2023, CGIAR and DevGlobal, in partnership with USAID Feed the Future and DAI Digital Frontiers, jointly implemented ICTforAg 2023 as a global online conference on November 7-9 with 145 speakers across 40 sessions. Out of the 2,608 individuals who registered for the event, a total of 1,778 attendees (constituting 68% of registrants) participated over the three days. In addition to the main sessions, the conference also featured the Expo, virtual exhibition space that allowed various organizations from academia, research, and the private sector to showcase their innovations interactively, the Inspire Challenge, a new Pay-for-Results program intended to increase women’s participation in digital agri-food advisory services and programs, the ICTforAg+ Satellite Events, a series of locally-led satellite events in four countries (Indonesia, Mexico, Nepal, and India), and the ICTforAg Learning Network, an online platform designed to support the collaboration amongst the global ICTforAg community of practice.

Non-PR, IFPRI5; 5 Strengthening Institutions and Governance, Natural Resources and Resilience (NRR); Transformation Strategies, Agricultural extension services play a crucial role in supporting 570 million small-scale farmers worldwide, contributing to food security and rural development through the dissemination of technical advice and best practices. These vital services, however, often face significant challenges, including weak institutional capacity, inadequate reach and limited access to up-to-date scientific knowledge. Language is also a significant barrier. Advisories provided only in the world’s predominant languages cannot easily be understood in many communities speaking regional or local languages and dialects. Many information and communications technologies have been piloted to address these systemic challenges, such as videos, texting/short message services and interactive voice response services. And, what about artificial intelligence (AI) chatbots?

Non-PR, IFPRI5; 5 Strengthening Institutions and Governance, Natural Resources and Resilience (NRR); Transformation Strategies, Artificial intelligence (AI) tools are rapidly transforming the way people work, providing opportunities for improving efficiency, accelerating innovations and supporting human decision-making. The area of food policy research and policymaking is no exception. In a previous blog, we argued that policymakers should not rely exclusively on AI-powered chatbots (e.g., Bard, ChatGPT, and Claude), given that the outputs of current versions of AI simply draw upon a vast number of existing passages in publications written by humans, assembled without logic and, consequently, prone to errors. In addition, many chatbots do not identify the sources used for assembling specific policy information, thus potentially undermining trust and credibility. Still, the potential of having a virtual assistant at your fingertips is so appealing that we wanted to test it ourselves.

PR, IFPRI3; ISI; Cross-cutting gender theme; 1 Fostering Climate-Resilient and Sustainable Food Supply, Innovation Policy and Scaling (IPS); Natural Resources and Resilience (NRR); Transformation Strategies, CGIAR Gender Platform, Climate change poses a greater threat for more exposed and vulnerable countries, communities and social groups. People whose livelihood depends on the agriculture and food sector, especially in low-and middle-income countries (LMICs), face significant risk. In contexts with gendered roles in agri-food systems or where structural constraints to gender equality underlie unequal access to resources and services and constrain women's agency, local climate hazards and stressors, such as droughts, floods, or shortened crop-growing seasons, tend to negatively affect women more than men and women's adaptive capacities tend to be more restrained than men's . Transformation towards just and sustainable agri-food systems in the face of climate change will not only depend on reducing but also on averting aggravated gender inequality in agri-food systems. In this paper, we developed and applied an accessible and versatile methodology to identify and map localities where climate change poses high risk especially for women in agri-food systems because of gendered exposure and vulnerability. We label these localities climate-agriculture-gender inequality hotspots. Applying our methodology to LMICs reveals that the countries at highest risk are majorly situated in Africa and Asia. Applying our methodology for agricultural activity-specific hotspot subnational areas to four focus countries, Mali, Zambia, Pakistan and Bangladesh, for instance, identifies a cluster of districts in Dhaka and Mymensingh divisions in Bangladesh as a hotspot for rice. The relevance and urgency of identifying localities where climate change hits agri-food systems hardest and is likely to negatively affect population groups or sectors that are particularly vulnerable is increasingly acknowledged in the literature and, in the spirit of leaving no one behind, in climate and development policy arenas. Hotspot maps can guide the allocation of scarce resources to most at-risk populations. The climate-agriculture

Non-PR, IFPRI5; DCA; 4 Transforming Agricultural and Rural Economies, Natural Resources and Resilience (NRR); Transformation Strategies, Digitalization is transforming existing agricultural business processes and services and enabling new means to deploy innovative services and products at scale. At the core of these services and innovations is open data. In India, Central and State Governments, academic, research institutions, and the private sector have done critical work in conceptualizing different approaches and aspects of an AgriStack to digitally transform agriculture. Recognizing the need to integrate these efforts and incorporate use cases, CGIAR Research Initiative on Digital Innovation, in partnership with The Agri Collaboratory (TAC), organized a consultation workshop in Delhi in November 2022. Participated by 70 stakeholders representing 54 organizations, the workshop enabled in-depth discussion on the design principles of thematic use cases and facilitated a broader debate on the specific building blocks needed. This document summarizes key principles discussed throughout the workshop.

Non-PR, IFPRI5; DCA; 5 Strengthening Institutions and Governance, Innovation Policy and Scaling (IPS); Transformation Strategies, The role of intellectual property has become increasingly important in protecting creations of the mind and making day-to-day business decisions. Hence, if innovations are left unprotected, they can be exploited by competitors with capacity to commercialize them. This policy brief points out that lowand middle-income countries face intellectual property-related challenges compared to high-income countries due to inadequate intellectual property awareness, the high cost of processing patent applications, weak enforcement of intellectual property rights, and weak research and development capacity. Group of Seven (G7) countries are thus better positioned, as high-income countries, to lead globally on intellectual property enforcement, and leverage the flexibilities within the traderelated aspects of intellectual property to support and encourage future technologies in low- and middle-income countries. We propose that G7 countries support the creation of equity- and rights-based awareness on intellectual property rights, the improvement of mechanisms and systems for enforcement, and investment in research and development via building local support to reduce costs.

PR, IFPRI4; 4 Transforming Agricultural and Rural Economies; CRP2, Foresight and Policy Modeling (FPM); Development Strategies and Governance (DSG); Natural Resources and Resilience (NRR); Transformation Strategies; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM), The number of people living in rural areas of low and middle-income countries is projected to increase in the coming decades. It is in the rural areas of these countries where a large majority of the world’s extreme poor reside. The livelihoods of two to three billion rural people depend on small farms. These small farms are responsible for the production and supply of a large portion of the calories feeding low- and middle-income countries. Small farms are also preservers of crops and associated biodiversity and with the right incentives can contribute to land stewardship. Small farms are diverse, and, hence, so are their associated challenges. We categorize small farms as commercial farms, small farms in transition and subsistence-oriented farms and highlight evidence-based innovations for the sustainable transformation of each type of small farm. Broadly, small farms face high transaction costs, lack collective action, and experience coordination failure in production and marketing. Lack of market access is also a major challenge. Investments in infrastructure, including those that support access to digital technologies, can improve farmers’ access to markets and incentives as well as foster growth in the midstream segments of the value chain that provide inputs, storage, processing, and logistics to small farms. Rural Non-Farm Employment (RNFE) is increasingly the main source of income for most small farmers and provides them with a risk diversification strategy and cash, both to purchase food and for farm investments to raise productivity, expand commercial activities, and produce higher-value products. Public investments and policies that facilitate growth of the agrifood system must pay more attention to creating enabling environments for the development of RNFE and strengthening the synergy between agriculture and RNFE in rural areas.

PR, 1 Fostering Climate-Resilient and Sustainable Food Supply; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; IFPRI4; ASTI, Innovation Policy and Scaling (IPS); Transformation Strategies, This chapter looks at food system innovations and digital technologies as important drivers of productivity growth and improved food and nutrition security. The analysis emphasizes a mix of research feasibility and technology-enabling policy factors necessary to realize pro-poor benefits. Given their transformative potential and the urgency of developing the enabling R&D and policy trajectories required for impact, we highlight genome editing bio-innovations, specifically CRISPR-Cas9, to address sustainable agricultural growth; and digital technologies, including remote sensing, connected sensors, artificial intelligence, digital advisory services, digital financial services, and e-commerce, to help guide the operations and decision-making of farmers, traders, and policymakers in agricultural value chains. The analysis points to the need to close critical gaps in R&D investments, capabilities, and enabling policies and regulations to accelerate the scaling and adoption of innovations. At the global level, the engagement of low- and middle-income countries (LMICs) with global players should be facilitated to strengthen intellectual property (IP) access and the management of innovations; and North–South, South–South, and triangular cooperation should be promoted to strengthen LMICs’ regulatory capabilities. At the national level, countries need to invest in science-based participatory approaches to identify and adapt technologies to local conditions; close regulatory gaps through evidence-based frameworks that enable the rapid development, deployment, and safe use of innovations; close institutional and human capacity gaps by addressing limitations in institutional capacities and coordination, while training a new generation of scientists with the skills needed to develop and deliver innovations; develop an understanding of political economy factors for a nuanced knowledge of actors’ agendas to better inform communications and address technology hesitancy; close digit

Non-PR, IFPRI1; 4 Transforming Agricultural and Rural Economies; Cross-cutting gender theme, EPTD, This paper analyzes transaction data from agricultural surveys carried out in five countries in low-and-middle-income countries to test for a difference in the prices received by men and by women marketing the same crop in the same village. In a unique finding, we identify a gap between the price received by women and the price received by men on three separate continents. Echoing similar results from other countries in subSaharan Africa, using mobile phone ownership and use data, we provide evidence to suggest that women farmers likely suffer from unequal access to information. The presence of asymmetric information is therefore indicated to be a limiting factor in women’s ability to receive a fair unit price.

PR, IFPRI4; 4 Transforming Agricultural and Rural Economies, EPTD; MTID, Climate change and associated extreme weather events directly impact the functioning and sustainability of food systems. The increasingly erratic onset of seasonal rainfall and prolonged heat stress during growing seasons are already causing crop losses. As of late 2021, for example, Madagascar’s three successive seasonal droughts had put 1.35 million people at risk of the world’s first climate-change-induced famine. In the United States, the number of days between billion-dollar weather-related disasters has fallen from more than 80 in the 1980s to just 18 in recent years. Without adequate preparation, these weather hazards disrupt food supply chains by interrupting production and cause problems farther along these chains by raising costs and prices of processing, storage, transport, retail, and consumption and reducing business revenues.

PR, IFPRI3; 5 Strengthening Institutions and Governance, EPTD, Future societal systems will be characterized by heterogeneous human behaviors and data-driven collective action. Complexity will arise as a consequence of the 5th Industrial Revolution and 2nd Data Revolution possible, thanks to a new generation of digital systems and the Metaverse. These technologies will enable new computational methods to tackle inequality while preserving individual rights and self-development. In this context, we do not only need data innovation and computational science, but also new forms of digital policy and governance. The emerging fragility or robustness of the system will depend on how complexity and governance are developed. Through data, humanity has been able to study a number of multi-scale systems from biological to migratory. Multi-scale governance is the new paradigm that feeds the Data Revolution in a world that would be highly digitalized. In the social dimension, we will encounter meta-populations sharing economy and human values. In the temporal dimension, we still need to make all real-time response, evaluation, and mitigation systems a standard integrated system into policy and governance to build up a resilient digital society. Top-down governance is not sufficient to manage all the complexities and exploit all the data available. Coordinating top-down agencies with bottom-up digital platforms will be the design principle. Digital platforms have to be built on top of data innovation and implement Artificial Intelligence (AI)-driven systems to connect, compute, collaborate, and curate data to implement data-driven policy for sustainable development based on Collective Intelligence.

Non-PR, IFPRI5; 2 Promoting Healthy Diets and Nutrition for all; G Cross-cutting gender theme, EPTD, CGIAR Gender Platform, Climate change is influencing the transformation of agriculture and food systems across the globe in unprecedented ways. A large number of smallholder farmers in low- and middle-income countries (LMICs) who depend on these systems for their food and nutrition security, and incomes are experiencing increasing vulnerability. Women are at a particular disadvantage, given their lower adaptive capacity due to unequal access to productive resources and services, driven by deeply entrenched social and gender norms and other structural barriers. However, addressing these gender gaps can enable women to use their knowledge and skill to contribute to climate-resilient agriculture. This paper proposes a methodology to map climate–agriculture–gender inequality hotspots at national and subnational levels where climate hazards, women’s exposure to climate hazards affecting food systems, and gender inequalities converge to impact women’s vulnerability to climate change. These hotspots are geographical areas where extreme climate hazards intersect with large concentrations of women participating in food systems and in the agricultural labor force, and with high levels of gender inequalities—and as such, result in high risk and exposure, low adaptive capacities, and higher vulnerability of women to adverse effects of climate change. The hotspots are identified using a set of indicators based on available secondary data comparable across the countries, conforming to the framework developed for this assessment, and using the Principal Component Analysis methodology. The paper also presents the results of the analysis emerging from the application of this methodology. This includes a global ranking of 87 LMICs in Latin America, Asia and Africa by a climate–agriculture–gender inequality hotspot index using representative national-level data. Identification of subnational climate–agriculture–gender inequality hotspot areas using representative subnational level data in four selected coun

Non-PR, IFPRI5; CGIAR Platform for Big Data in Agriculture; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD, CGIAR Platform for Big Data in Agriculture (Big Data), The number of people experiencing food insecurity has increased for the third consecutive year, a worrying reversal of progress since the 1990s (FAO, 2020). Addressing food insecurity and achieving the United Nations' second sustainable development goal to eradicate hunger by 2030 will require more timely and accurate information on agricultural yield, food availability, and land use, with data that are relevant for the most vulnerable populations. Special attention should focus on smallholder farming, which continues to dominate the agricultural landscape of sub-Saharan Africa, Asia, Latin America, and the Middle East. While the definitions of a "smallholder farm" differ, as of 2018, 475 million out of 580 million farms worldwide were smaller than two hectares in size and that more than 500 million were family-operated (Lowder et al., 2018). These farms are often intercropped, used primarily for home consumption, and operated by a single household or family.

Non-PR, IFPRI5; CGIAR Platform for Big Data in Agriculture; 1 Fostering Climate-Resilient and Sustainable Food Supply; 5 Strengthening Institutions and Governance, EPTD; DSGD, CGIAR Platform for Big Data in Agriculture (Big Data), CGIAR’s digital extension services bridge the gap between the development and the adoption of new climate change adaptation strategies. These services include new ways to disperse information on rainfed systems of agriculture, nutrition, pest control, new crop varieties, crop management practices, and more.

Non-PR, IFPRI5; UNFSS; CRP2, DSGD; EPTD; PIM, 16 pages, CGIAR Research Program on Policies, Institutions, and Markets (PIM), By 2050, the United Nations projects that 68 percent of the world population will live in cities (UN DESA 2019). However, with continuous population growth, the number of people living in rural areas of many lowand low-middle-income countries (LMICs) will continue to rise. Two-thirds of the extreme poor live in rural areas (World Bank 2016) and the livelihoods of two to three billion rural people, often the most food insecure and vulnerable, still depend primarily on small farms (Laborde, Parent, and Smaller 2020; Woodhill, Hasnain, and Griffith 2020). There are various estimates of the number of small farms in the world, but they all suggest these farms are numerous. Lowder et al. (2016) used agricultural census data from 167 countries to estimate that, of the total 570 million farms in the world, 475 million farms have less than 2 hectares (ha), dominating agriculture in most LMICs, where farm sizes continue to fall. Africa south of the Sahara has the highest rural population growth rate globally, and thus the number of small farms is expected to increase more than in other regions. Africa’s share of total world rural poverty is also expected to rise from 39.6 percent in 2015 to 58.1 percent in 2050 (Thurlow, Dorosh, and Davies 2019). Transforming Africa’s agriculture sector is thus a priority embodied in the Malabo Declaration on Accelerated Agricultural Growth and Transformation for Shared Prosperity and Improved Livelihoods (AU 2014). But to meet the Malabo goals and to achieve multiple SDGs in all LMICs by 2030, creating an enabling environment where small farms are included in and benefit from rapid growth and transformation of agrifood systems is urgent (Barrett et al. 2020).

Non-PR, IFPRI5; UNFSS; CRP2; 1 Fostering Climate-Resilient and Sustainable Food Supply; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance, EPTD; PIM, 19 pages, CGIAR Research Program on Policies, Institutions, and Markets (PIM), This brief looks at food system innovations and digital technologies as important drivers of productivity growth and improved food and nutrition security. The analysis emphasizes a mix of research feasibility and technology-enabling policy factors necessary to realize pro-poor benefits. Given their transformative potential and the urgency of developing the enabling R&D and policy trajectories required for impact, we highlight genome editing bio-innovations, specifically CRISPR-Cas9, to address sustainable agricultural growth; and digital technologies, including remote sensing, connected sensors, artificial intelligence, digital advisory services, digital financial services, and e-commerce, to help guide the operations and decision-making of farmers, traders, and policymakers in agricultural value chains. The analysis points to the need to close critical gaps in R&D investments, capabilities, and enabling policies as well as regulations to accelerate the scaling and adoption of innovations. At the global level, the engagement of low- and middle income countries with global players should be facilitated so as to strengthen intellectual property (IP) access and management of innovations; and North– South, South–South, and triangular cooperation should be promoted to strengthen LMICs’ regulatory capabilities. At the national level, countries need to invest in science-based participatory approaches to identify and adapt technologies to local conditions; close regulatory gaps through evidence-based frameworks that enable the rapid development, employment, and safe use of innovations; close institutional and human capacity gaps by addressing limitations in institutional capacities and coordination, while training a new generation of scientists with the skills needed to develop and deliver innovations; develop an understanding of political economy factors for a nuanced knowledge of actors’ agendas to better inform communications and address technology hesitancy; close digit

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CRP7; CGIAR Platform for Big Data in Agriculture; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), In anticipation of the development of a safe and effective COVID-19 vaccine—the distribution of which will be a complex and sensitive issue—governments will need to assess the number and location of the most vulnerable people within their populations. Problematically, however, tracking data for most low- and middle-income countries are only available at the national level. The most widely used dataset by the Johns Hopkins University Center for Systems Science and Engineering (Dong, Du, and Gardner 2020), for example, does not include subnational data for Feed the Future’s 12 target countries in Africa south of the Sahara (SSA) and South Asia: Bangladesh, Ethiopia, Ghana, Guatemala, Honduras, Kenya, Nepal, Niger, Nigeria, Mali, Senegal, and Uganda. For this reason, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to correlate Demographic and Health Survey data from the United States Agency for International Development (USAID) with geospatial data in order to develop a subnational dataset of key COVID-19 risk indicators based on which potential risk hotspots were identified. This policy note summarizes the study’s analysis in the 12 Feed the Future countries and across subnational administrative units within each country.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI1; GCAN; CGIAR Platform for Big Data in Agriculture; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Feed the Future Initiative, EPTD; PHND, CGIAR Platform for Big Data in Agriculture (Big Data); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), As COVID-19 vaccines are becoming available, governments will need to assess the number and location of the most vulnerable people within their populations. However, problematically, tracking data for most low- and middle-income countries are only available at the national level. To support the COVID-19 relief effort, the Gender, Climate Change, and Nutrition Integration Initiative (GCAN) was commissioned to develop a subnational dataset of key COVID-19 risk indicators and potential risk hotspots.

Non-PR, IFPRI5; CRP7; CGIAR Platform for Big Data in Agriculture; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD, CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS); CGIAR Platform for Big Data in Agriculture (Big Data), This report summarizes a rapid assessment of climate-related challenges to food-, land- and water- systems across the six CGIAR regions. Based on the evidence, priority geographies and systems are proposed which provide a starting point for the Regional Initiatives design process. It then assesses the readiness of the Two Degree Initiative (2DI) regional challenges for their fit to the challenges, and potential to form the basis for developing the first batch of Regional Integrated Initiatives.

Non-PR, IFPRI1; CGIAR Platform for Big Data in Agriculture; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD, CGIAR Platform for Big Data in Agriculture (Big Data), The global research consortium CGIAR is restructuring itself to build a more integrated global organization (“One CGIAR”) that fully leverages its strengths and refocuses its research strategy through 2030 in service of a renewed mission: End hunger—through science to transform food, land, and water systems in a climate crisis. The CGIAR Platform for Big Data in Agriculture led strategic research in support of this effort, looking into digital trends that have the potential to transform global agriculture in the coming years, the roles public-interest organizations should play in the digital agriculture landscape, and the capabilities CGIAR must have if it is to use data and digital technology to their full potential in the service of its mission.

Non-PR, IFPRI5, EPTD, Access to the resources, services and opportunities that are concentrated in urban areas is an important indicator for development. Urban areas and the transport networks that connect them together and to their surrounding rural areas are essential infrastructure. This infrastructure provides the means for people and products to travel from A to B. It enables social and economic interactions and the delivery of basic services such as education and healthcare. People with good access generally have greater opportunity for social and economic development, reduced costs and greater levels of interaction, whereas those with poor access generally face higher costs, fewer opportunities and poorer health and education outcomes.

PR, IFPRI3; ISI; CRP2; IFPRIOA; 1 Fostering Climate-Resilient and Sustainable Food Supply; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; 4 Transforming Agricultural and Rural Economies, MTID; EPTD; PIM, CGIAR Research Programs on Policies, Institutions, and Markets (PIM), Since Amartya Sen's famous work on Poverty and Famines, economists have understood that the impacts of food market shocks on the poor depend much more on their impacts on households’ incomes and access to food than on overall food availability, and that availability-based policies frequently exacerbate adverse impacts on household welfare. Perhaps because household-level impacts are not directly observable many policy makers have continued to rely on availability-oriented policies such as export bans. In the Zambia case considered in this article, export bans imposed in response to an El Niño event appear to have greatly exacerbated the small increase in poverty resulting from the weather shock. The combination of household-level data and crop models used in this article allows us to assess the impacts of weather and price shocks at the household level, and to evaluate the suitability of availability-based policies for dealing with weather shocks. These analytical techniques can also help identify the households and regions adversely affected, and design policies to improve poor consumers’ access to food.

PR, IFPRI3; ISI; DCA; 1 Fostering Climate-Resilient and Sustainable Food Supply; Africa Rising; IFPRIOA, EPTD, CONTEXT The accessibility and availability of forages is a common concern in crop-livestock systems in West Africa; however, options to increase forage production may entail trade-offs within the farm system that can be challenging to quantify explicitly. OBJECTIVE This study examined how maize (Zea mays L.) leaf stripping affected maize and sheep productivity and associated labour requirements, and farm system trade-offs and synergies in four communities in the Northern Region of Ghana. METHODS Maize leaf stripping involved removing almost senesced leaves from maize plants below the cob level at silking. We combined data from three sources: on-farm maize trials with 28 farmers from two seasons (2017 and 2018), on-farm sheep feeding trials where the pasture-based diets of weaner sheep were supplemented with stripped maize leaves fed in pens (conducted in 2019), and farm survey data from 117 households (conducted in 2014), seven of which were in the on-farm maize trials and owned sheep. We examined the trial data using linear mixed-effects models. RESULTS AND CONCLUSIONS Maize leaf stripping had no significant effect on maize grain yield but had a significant positive effect on maize forage protein yield from leaf and stover. Offering maize leaves to weaner sheep had a significant positive effect on average daily liveweight gain, estimated marginal mean was 29.3 g with maize leaves and −10.9 g without maize leaves. For the maize-sheep systems of the seven households, non-inferential statistics suggested that on average maize leaf stripping reduced total maize grain production by 12% (range −46 to 38) and increased maize forage protein production from leaf and stover by 90% (range −16 to 298). Stripping the maize leaves from one hectare of land took an extra 34 h (range 27 to 42) of labour, which was counterbalanced by reduced labour time for grazing as sheep were fed the maize leaves in pens. For the 117 farmers, heterogeneity in maize areas planted and livestock num

PR, IFPRI5; Program of Accompanying Research for Agricultural Innovation; Feed the Future Innovation Laboratory for Small-Scale Irrigation; 1 Fostering Climate-Resilient and Sustainable Food Supply; DCA; Capacity Strengthening; AGRODEP; Feed the Future Innovation Laboratory for Small-Scale Irrigation, EPTD, Small-scale irrigation has been identified as a potential adaptation strategy for climate change and boosting food security and livelihoods in dry regions. This study presents the analysis of the potential adoption of small-scale irrigation in two West African countries (Mali and Niger) by using a spatially explicit analytical framework. It underscores the need for strategically investing in the management of ground and surface water resources for the development of small-scale irrigation systems in the two countries. The study implemented an agent-based modeling technique to simulate small-scale irrigation decisions at the district and national level. The results revealed that, while small-scale irrigation can increase crop productivity in both countries, its adoption may be constrained by water scarcity and tensions in water allocation. Strategic water resource development plans should be established to ensure efficient and sustainable irrigation schemes, especially for areas with high potential profitability.

Non-PR, IFPRI5; 1 Fostering Climate-Resilient and Sustainable Food Supply, DGO; EPTD

Non-PR, IFPRI1; HarvestChoice; CRP2; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM), HarvestChoice began in 2006, when detailed and readily accessible data on agriculture, human welfare, and the environment were scarce for Africa South of the Sahara (SSA). Statistics to support agricultural policy and investment decisions in the region were often too coarse—available only at national scale. Since then, technology advances (e.g., remote sensing, geographic information systems, and modeling tools) have enabled rapid data generation.

PR, IFPRI3; DCA; CRP7; ISI; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD, CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS); CGIAR Platform for Big Data in Agriculture (Big Data), Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains ‘to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?’. Here, we address this question by critically reviewing how model‐based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better‐targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts.

Non-PR, IFPRI1; CRP2; 1 Fostering Climate-Resilient and Sustainable Food Supply; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; Capacity Strengthening, MTID; EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM), Since Amartya Sen’s famous work on Poverty and Famines, economists have understood that policy responses to food market shocks should be guided by changes in households’ incomes and access to food, rather than by overall food availability. Perhaps because the household-level impacts are not directly observable, many policy makers have continued to rely on availability-oriented policies such as export bans. In the Zambia case considered in this paper, export bans imposed in response to an El Niño event exacerbated the poverty problems resulting from the output shock. The combination of household-level data and crop models used in this paper allows us to assess the impacts of weather and price shocks at the household level, and hence to evaluate the suitability of availability-based policies for dealing with weather shocks. These analytical techniques are also useful in identifying the households and regions adversely affected by food output shocks, and hence in designing policies to improve poor consumers’ access to food.

PR, IFPRI3; CRP2; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD; PIM, CGIAR Research Programs on Policies, Institutions, and Markets (PIM); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Existing approaches and methodologies that investigate effects of land degradation on food security vary greatly. Although a relatively rich body of literature that investigates localized experiences, geophysical, and socioeconomic drivers of land degradation, and the costs and benefits of avoiding land degradation already exists, less rigorously explored are the global effects of restoring degraded landscapes for the health of the land, the climate, and world food security. The current scale of land degradation is such that the problem can be meaningfully addressed only if local successes are upscaled and a large number of landowners and land managers implement restoration activities. Significant global efforts to address degradation exist, but studies that evaluate the global benefits of these efforts generally do not account for global market forces and the complex web of relationships that determine the effects of wide-scale restoration on production and food security. This paper provides important insights into how a full integration of crop production in restoration efforts could impact food production levels, food availability, forest carbon stocks, and Greenhouse gas emissions.

PR, IFPRI3; ISI; CRP2; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; Global Futures and Strategic Foresight, EPTD; PIM, CGIAR Research Programs on Policies, Institutions, and Markets (PIM); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Most business-as-usual scenarios for farming under changing climate regimes project that the agriculture sector will be significantly impacted from increased temperatures and shifting precipitation patterns. Perhaps ironically, agricultural production contributes substantially to the problem with yearly greenhouse gas (GHG) emissions of about 11% of total anthropogenic GHG emissions, not including land use change. It is partly because of this tension that Climate Smart Agriculture (CSA) has attracted interest given its promise to increase agricultural productivity under a changing climate while reducing emissions. Considerable resources have been mobilized to promote CSA globally even though the potential effects of its widespread adoption have not yet been studied. Here we show that a subset of agronomic practices that are often included under the rubric of CSA can contribute to increasing agricultural production under unfavorable climate regimes while contributing to the reduction of GHG. However, for CSA to make a significant impact important investments and coordination are required and its principles must be implemented widely across the entire sector.

PR, IFPRI3; CRP5; Capacity Strengthening; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD, CGIAR Research Program on Water, Land and Ecosystems (WLE)

PR, IFPRI2; CRP7; CRP2; 1 Fostering Climate-Resilient and Sustainable Food Supply, EPTD; DSGD; PIM, CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS); CGIAR Research Program on Policies, Institutions, and Markets (PIM), Ethiopia has made consistent progress in improving development indicators, but vulnerability to extreme weather events is a continuing concern, especially for people reliant on agriculture for their livelihoods. The 2015/16 El Niño event caused both a severe drought and flooding, which highlighted the remarkable improvements in the country’s resilience and the remaining challenges in ensuring that everyone “bounces back” relatively quickly from adverse climatic shocks. Given the links between climate change, cyclical droughts, and poverty, and the high cost of emergency humanitarian assistance, the Government of Ethiopia and development partners decided to review the country’s resilience programming and identify opportunities and challenges to building greater resilience into the agricultural system. This work included three components: a review of the literature and government programs on resilience in Ethiopia; key informant interviews in several regions of the country; and quantitative crop modeling and economywide analyses to inform resilience programming.

PR, IFPRI3; ISI; 1 Fostering Climate-Resilient and Sustainable Food Supply; HarvestChoice, EPTD, One major challenge in applying crop simulation models at the regional or global scale is the lack of available global gridded soil profile data. We developed a 10-km resolution global soil profile dataset, at 2 m depth, compatible with DSSAT using SoilGrids1km. Several soil physical and chemical properties required by DSSAT were directly extracted from SoilGrids1km. Pedo-transfer functions were used to derive soil hydraulic properties. Other soil parameters not available from SoilGrids1km were estimated from HarvestChoice HC27 generic soil profiles. The newly developed soil profile dataset was evaluated in different regions of the globe using independent soil databases from other sources. In general, we found that the derived soil properties matched well with data from other soil data sources. An ex-ante assessment for maize intensification in Tanzania is provided to show the potential regional to global uses of the new gridded soil profile dataset.

PR, IFPRI3; ISI; 1 Fostering Climate-Resilient and Sustainable Food Supply; HarvestChoice, EPTD, CGIAR Platform for Big Data in Agriculture (Big Data), Good access to resources and opportunities is essential for sustainable development. Improving access, especially in rural areas, requires useful measures of current access to the locations where these resources and opportunities are found. Recent work has developed a global map of travel times to cities with more than 50,000 people in the year 2015. However, the provision of resources and opportunities will differ across the broad spectrum of settlements that range from small towns to megacities, and access to this spectrum of settlement sizes should also be measured. Here we present a suite of nine global travel-time accessibility indicators for the year 2015, at approximately one-kilometre spatial resolution, for a range of settlement size classes. We validated the travel-time estimates against journey times from a Google driving directions application across 1,511 2° × 2° tiles representing 47,812 journeys. We observed very good agreement, though our estimates were more frequently shorter than those from the Google application with a median difference of −13.7 minutes and a median percentage difference of −16.9%.