High-frequency monitoring enables machine learning-based forecasting of acute child malnutrition for early warning.

The number of acutely food insecure people worldwide has doubled since 2017, increasing demand for early warning systems (EWS) that can predict food emergencies. Advances in computational methods, and the growing availability of near-real time remote sensing data, suggest that big data approaches might help meet this need. But such models have thus far exhibited low predictive skill with respect to subpopulation-level acute malnutrition indicators.

Microlevel structural poverty estimates for southern and eastern Africa.

For many countries in the Global South traditional poverty estimates are available only infrequently and at coarse spatial resolutions, if at all. This limits decision-makers' and analysts' ability to target humanitarian and development interventions and makes it difficult to study relationships between poverty and other natural and human phenomena at finer spatial scales. Advances in Earth observation and machine learning-based methods have proven capable of generating more granular estimates of relative asset wealth indices.

Climate change exacerbates the environmental impacts of agriculture.

Agriculture's global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture's environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change-reinforcing feedback loop.

From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II-Harnessing data.

Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented.

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I-Harnessing theory.

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g.

Journal submissions, review and editorial decision patterns during initial COVID-19 restrictions.

We use the full administrative records from four leading agricultural economics journals to study the impacts of the COVID-19 pandemic on manuscript submission, editorial desk rejection and reviewer acceptance rates, and time to editorial decision. We also test for gender differences in these impacts. Manuscript submissions increased sharply and equi-proportionately by gender.

Sustainability standards in global agrifood supply chains.

Agrifood supply chains contribute to many environmental and social problems. Sustainability standards-rules that supply chain actors may follow to demonstrate their commitment to social equity and/or environmental protection-aim to mitigate such problems. We provide a narrative review of the effects of many distinct sustainability standards on different supply chain actors spanning multiple crops.

Multivariate random forest prediction of poverty and malnutrition prevalence.

Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies' programming. However, state of the art models often rely on proprietary data and/or deep or transfer learning methods whose underlying mechanics may be challenging to interpret. We demonstrate how interpretable random forest models can produce estimates of a set of (potentially correlated) malnutrition and poverty prevalence measures using free, open access, regularly updated, georeferenced data.

On design-based empirical research and its interpretation and ethics in sustainability science.

Generating credible answers to key policy questions is crucial but difficult in most coupled human and natural systems because complex feedback mechanisms can confound identification of the causal mechanisms behind observed phenomena. By using explicit research designs intended to isolate the causal effects of specific interventions on community monitoring of common property resources, and on the well-being of those resources and their human neighbors, the papers in this Special Feature offer an important advance in empirical sustainability science research. Like earlier advances in my own field of development economics, however, they suffer some avoidable interpretive and ethical errors.

Post-farmgate food value chains make up most of consumer food expenditures globally.

Progress towards many United Nations Sustainable Development Goals depends on interventions in food value chains, yet data and methods have thus far limited the production of cross-nationally comparable estimates of food value chains' magnitudes. Here we develop a standardized method and data series to estimate the distribution of consumer food expenditures between value-added activities on farms and in the post-farmgate value chain. Using data from 61 countries over 2005-2015, representing 90% of the global economy, we show that farmers receive, on average, 27% of consumer expenditure on foods consumed at home and a far lower percentage of food consumed away from home.

The intertemporal evolution of agriculture and labor over a rapid structural transformation: Lessons from Vietnam.

We combine nationally representative household and labor force survey data from 1992 to 2016 to provide a detailed description of rural labor market evolution and how it relates to the structural transformation of rural Vietnam, especially within the agricultural sector. Our study adds to the emerging literature on structural transformation in low-income countries using micro-level data and helps to answer several policy-related questions. We find limited employment creation potential of agriculture, especially for youth.

Cohort Description of the Madagascar Health and Environmental Research-Antongil (MAHERY-Antongil) Study in Madagascar.

The Madagascar Health and Environmental Research-Antongil (MAHERY-Antongil) study cohort was set up in September 2015 to assess the nutritional value of seafood for the coastal Malagasy population living along Antongil Bay in northeastern Madagascar. Over 28 months of surveillance, we aimed to understand the relationships among different marine resource governance models, local people's fish catch, the consumption of seafood, and nutritional status. In the Antongil Bay, fisheries governance takes three general forms: traditional management, marine national parks, and co-management.

Emerging human infectious diseases and the links to global food production.

Infectious diseases are emerging globally at an unprecedented rate while global food demand is projected to increase sharply by 2100. Here, we synthesize the pathways by which projected agricultural expansion and intensification will influence human infectious diseases and how human infectious diseases might likewise affect food production and distribution. Feeding 11 billion people will require substantial increases in crop and animal production that will expand agricultural use of antibiotics, water, pesticides and fertilizer, and contact rates between humans and both wild and domestic animals, all with consequences for the emergence and spread of infectious agents.

Review: Food loss and waste in Sub-Saharan Africa.

The research, development practitioner, and donor community has begun to focus on food loss and waste - often referred to as post-harvest losses (PHL) - in Sub-Saharan Africa. This article reviews the current state of the literature on PHL mitigation. First, we identify explicitly the varied objectives underlying efforts to reduce PHL levels.

Agricultural factor markets in Sub-Saharan Africa: An updated view with formal tests for market failure.

This paper uses the recently collected Living Standard Measurement Study-Integrated Surveys on Agriculture Initiative data sets from five countries in Sub-Saharan Africa to provide a comprehensive overview of factor market participation by agrarian households and to formally test for failures in rural markets. Under complete and competitive markets, households can solve their consumption and production problems separately, so that household factor endowments do not predict input demand. This paper implements a simple, theoretically grounded test of this separation hypothesis, which can be interpreted as a reduced form test of market failure.

Ten striking facts about agricultural input use in Sub-Saharan Africa.

Conventional wisdom holds that Sub-Saharan African farmers use few modern inputs despite the fact that most poverty-reducing agricultural growth in the region is expected to come largely from expanded use of inputs that embody improved technologies, particularly improved seed, fertilizers and other agro-chemicals, machinery, and irrigation. Yet following several years of high food prices, concerted policy efforts to intensify fertilizer and hybrid seed use, and increased public and private investment in agriculture, how low is modern input use in Africa really? This article revisits Africa's agricultural input landscape, exploiting the unique, recently collected, nationally representative, agriculturally intensive, and cross-country comparable Living Standard Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) covering six countries in the region (Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda). Using data from over 22,000 households and 62,000 agricultural plots, we offer ten potentially surprising facts about modern input use in Africa today.