367 research outputs found

    Local Staple Food Price Indices in the Age of Biofuels

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    In many poor, food insecure regions, agriculture is a primary source of income and farmers are reliant both on their own production and on purchasing food in the market to feed their families. Large local food price increases over a short time period can be indicative of a deteriorating food security situation and may be the consequence of weather-related food production declines, Dr can simply be the result of price transmission from the international commodity market. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets far from the places where the chronically food insecure live. A much better understanding of how local staple food prices in isolated regions such as West Africa that grow most of the food they eat to better understand the impact of global commodity market transformations on sensitive communities at the margin. This information will also enable improved strategies for these farmers who are extraordinarily sensitive to climate change impacts on agricultural growing conditions

    Understanding Climate Policy Data Needs. NASA Carbon Monitoring System Briefing: Characterizing Flux Uncertainty, Washington D.C., 11 January 2012

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    Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them.

    Bringing Together Users and Developers of Forest Biomass Maps

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    Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales

    A Model of West African Millet Prices in Rural Markets

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    In this article we specify a model of millet prices in the three West African countries of Burkina Faso, Mali, and Niger. Using data obtained from USAID’s Famine Early Warning Systems Network (FEWS NET) we present a unique regional cereal price forecasting model that takes advantage of the panel nature of our data, and accounts for the flow of millet across markets. Another novel aspect of our analysis is our use of the Normalized Difference Vegetation Index (NDVI) to detect and control for variation in conditions for productivity. The average absolute out-of-sample prediction error for 4-month-ahead millet prices is about 20 %.Millet, cereal, West Africa, price forecasting, remote sensing, NDVI, regional panel data

    Remote Sensing for Food Security Monitoring in Afghanistan

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    Two decades of war have severely weakened Afghanistan s economy and infrastructure. Along with larger impacts on civil stability, education and health care, the current conflict in Afghanistan has resulted in widespread hunger and destitution. The 2005 National Risk and Vulnerability Assessment conducted by the United Nations found that 6.6 million Afghans do not meet their minimum food requirements and approximately 400,000 people each year are seriously affected by natural disasters, such as droughts, floods and extreme weather conditions. Given the poor security situation in the country, systems that will enable remote observations of variations of climate and their impacts on food production are critical for providing an appropriate and timely response. This chapter describes the remote sensing systems and food security analyses that the US Agency for International Development s Famine Early Warning Systems Network (FEWS NET) conducts in Afghanistan to monitor and provide information to international donors to ensure that adequate assistance is provided during this time of development and recovery

    Food Security, Decision Making and the Use of Remote Sensing in Famine Early Warning Systems

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    Famine early warning systems use remote sensing in combination with socio-economic and household food economy analysis to provide timely and rigorous information on emerging food security crises. The Famine Early Warning Systems Network (FEWS NET) is the US Agency for International Development's decision support system in 20 African countries, as well as in Guatemala, Haiti and Afghanistan. FEWS NET provides early and actionable policy guidance for the US Government and its humanitarian aid partners. As we move into an era of climate change where weather hazards will become more frequent and severe, understanding how to provide quantitative and actionable scientific information for policy makers using biophysical data is critical for an appropriate and effective response

    Earth Science Data and Models for Improved Targeting of Humanitarian Aid

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    Humanitarian assistance to developing countries has long focused on countries that have political, economic and strategic interest to the United States. Recent changes in global security concerns have heightened the perception that humanitarian action is becoming increasingly politicized. This is seen to be largely driven by the 'global war on terror' along with a push by donors and the United Nations for closer integration between humanitarian action and diplomatic, military and other spheres of engagement in conflict and crisis-affected states (HPG 2010). As we enter an era of rising commodity prices and increasing uncertainty in global food production due to a changing climate, scientific data and analysis will be increasingly important to improve the targeting of humanitarian assistance. Earth science data enables appropriate humanitarian response to complex food emergencies that arise in regions outside the areas of current strategic and security focus. As the climate changes, new places will become vulnerable to food insecurity and will need emergency assistance. Earth science data and multidisciplinary models will enable an information-based comparison of need that goes beyond strategic and political considerations to identify new hotspots of food insecurity as they emerge. These analyses will improve aid targeting and timeliness while reducing strategic risk by highlighting new regions at risk of crisis in a rapidly changing world. Improved targeting with respect to timing and location could reduce cost while increasing the likelihood that those who need aid get it

    Linking Research to Practice: FEWS NET and Its Use of Satellite Remote Sensing Data

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    The purpose of the Famine Early Warning Systems Network (FEWS NET) is to collaborate with international, regional and national partners to provide timely and rigorous early warning and vulnerability information on emerging and evolving food security issue

    Declining global per capita agricultural production and warming oceans threaten food security

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    Despite accelerating globalization, most people still eat food that is grown locally. Developing countries with weak purchasing power tend to import as little food as possible from global markets, suffering consumption deficits during times of high prices or production declines. Local agricultural production, therefore, is critical to both food security and economic development among the rural poor. The level of local agricultural production, in turn, will be determined by the amount and quality of arable land, the amount and quality of agricultural inputs (fertilizer, seeds, pesticides, etc.), as well as farm-related technology, practices and policies. This paper discusses several emerging threats to global and regional food security, including declining yield gains that are failing to keep up with population increases, and warming in the tropical Indian Ocean and its impact on rainfall. If yields continue to grow more slowly than per capita harvested area, parts of Africa, Asia and Central and Southern America will experience substantial declines in per capita cereal production. Global per capita cereal production will potentially decline by 14% between 2008 and 2030. Climate change is likely to further affect food production, particularly in regions that have very low yields due to lack of technology. Drought, caused by anthropogenic warming in the Indian and Pacific Oceans, may also reduce 21st century food availability in some countries by disrupting moisture transports and bringing down dry air over crop growing areas. The impacts of these circulation changes over Asia remain uncertain. For Africa, however, Indian Ocean warming appears to have already reduced rainfall during the main growing season along the eastern edge of tropical Africa, from southern Somalia to northern parts of the Republic of South Africa. Through a combination of quantitative modeling of food balances and an examination of climate change, this study presents an analysis of emerging threats to global food security

    A multi-country assessment of factors related to smallholder food security in varying rainfall conditions

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    Given that smallholder farmers are frequently food insecure and rely significantly on rain-fed agriculture, it is critical to examine climate variability and food insecurity. We utilize data from smallholder farmer surveys from 12 countries with 30 years of rainfall data to examine how rainfall variability and household resources are correlated with food security. We find that on average, households that experienced a drier than average year are 3.81 months food insecure, while households within a normal range of rainfall were 3.67 months food insecure, and wetter than average households were 2.86 months food insecure. Reduced odds of food insecurity is associated with agricultural inputs, ownership of livestock, water use efficiency, financial services, and participation in a group. However, in drier than average households, financial services as compared to agricultural inputs and agroecological practices have a greater prevalence of reduced instances of food insecurity, while agricultural inputs are more common for reduced food insecurity in wetter than average households. Only the use of fertilizer consistently results in reduced odds of food insecurity across all households regardless of rainfall, demonstrating that one-size fits all approaches to food security interventions are likely ineffective, and place-specific interventions considering climatic factors are critically important
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