Competition for water for the food system

Although the global agricultural system will need to provide more food for a growing and wealthier population in decades to come, increasing demands for water and potential impacts of climate change pose threats to food systems. We review the primary threats to agricultural water availability, and model the potential effects of increases in municipal and industrial (M&I) water demands, environmental flow requirements (EFRs) and changing water supplies given climate change. Our models show that, together, these factors cause an 18 per cent reduction in the availability of worldwide water for agriculture by 2050. Meeting EFRs, which can necessitate more than 50 per cent of the mean annual run-off in a basin depending on its hydrograph, presents the single biggest threat to agricultural water availability. Next are increases in M&I demands, which are projected to increase upwards of 200 per cent by 2050 in developing countries with rapidly increasing populations and incomes. Climate change will affect the spatial and temporal distribution of run-off, and thus affect availability from the supply side. The combined effect of these factors can be dramatic in particular hotspots, which include northern Africa, India, China, parts of Europe, the western US and eastern Australia, among others

Income distribution trends and future food demand

This paper surveys the theoretical literature on the relationship between income distribution and food demand, and identifies main gaps of current food modelling techniques that affect the accuracy of food demand projections. At the heart of the relationship between income distribution and food demand is Engel's law. Engel's law establishes that as income increases, households' demand for food increases less than proportionally. A consequence of this law is that the particular shape of the distribution of income across individuals and countries affects the rate of growth of food demand. Our review of the literature suggests that existing models of food demand fail to incorporate the required Engel flexibility when (i) aggregating different food budget shares among households; and (ii) changing budget shares as income grows. We perform simple simulations to predict growth in food demand under alternative income distribution scenarios taking into account nonlinearity of food demand. Results suggest that (i) distributional effects are to be expected from changes in between-countries inequality, rather than within-country inequality; and (ii) simulations of an optimistic and a pessimistic scenario of income inequality suggest that world food demand in 2050 would be 2.7 per cent higher and 5.4 per cent lower than distributional-neutral growth, respectively

Globalization's effects on world agricultural trade, 1960–2050

Recent globalization has been characterized by a decline in the costs of cross-border trade in farm and other products. It has been driven primarily by the information and communication technology revolution and—in the case of farm products—by reductions in governmental distortions to agricultural production, consumption and trade. Both have boosted economic growth and reduced poverty globally, especially in Asia. The first but maybe not the second of these drivers will continue in coming decades. World food prices will depend also on whether (and if so by how much) farm productivity growth continues to outpace demand growth and to what extent diets in emerging economies move towards livestock and horticultural products at the expense of staples. Demand in turn will be driven not only by population and income growth, but also by crude oil prices if they remain at current historically high levels, since that will affect biofuel demand. Climate change mitigation policies and adaptation, water market developments and market access standards particularly for transgenic foods will add to future production, price and trade uncertainties

Global food security and food riots – an agent-based modelling approach

Due to negative consequences of climate change for agriculture and food production shocks affecting different areas of the world, the past two decades saw the conditions of global food security increasingly worsen. This has resulted in negative consequences for the world economy, partly causing international food price spikes and social upheavals. In this paper we present statistical findings along with a preliminary version of an original agent-based model called the Dawe Global Security Model that simulates the global food market and the political fragility of countries. The model simulates the effects of food insecurity on international food prices and how these, coupled with national political fragility and international food trade can, in turn, increase the probability of food riots in countries. The agents in the model are the 213 countries of the world whose characteristics reflect empirical data and the international trade of food is also simulated based on real trade partnerships and data. The model has been informed, calibrated and validated using real data and the results of these procedures are presented in the paper. To further test the model we also present the model’s forecasts for the near future in terms of food prices and incidence of food riots. The Dawe Global Security Model can be used to test scenarios on the evolution of shocks to global food production and analyse consequences for food riots. Further developments of the model can include national responses to food crises to investigate how countries can influence the spread of global food crises

CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate.

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.Online Version of Record before inclusion in an issue

How Close Do We Live to Water? A Global Analysis of Population Distance to Freshwater Bodies

Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water

Factors that transformed maize productivity in Ethiopia

Published online: 26 July 2015Maize became increasingly important in the food security of Ethiopia following the major drought and famine that occurred in 1984. More than 9 million smallholder house- holds, more than for any other crop in the country, grow maize in Ethiopia at present. Ethiopia has doubled its maize produc- tivity and production in less than two decades. The yield, currently estimated at >3 metric tons/ha, is the second highest in Sub-Saharan Africa, after South Africa; yield gains for Ethiopia grew at an annual rate of 68 kg/ha between 1990 and 2013, only second to South Africa and greater than Mexico, China, or India. The maize area covered by improved varieties in Ethiopia grew from 14 % in 2004 to 40 % in 2013, and the application rate of mineral fertilizers from 16 to 34 kg/ ha during the same period. Ethiopia ’ s extension worker to farmer ratio is 1:476, compared to 1:1000 for Kenya, 1:1603 for Malawi and 1:2500 for Tanzania. Increased use of im- proved maize varieties and mineral fertilizers, coupled with increased extension services and the absence of devastating droughts are the key factors promoting the accelerated growth in maize productivity in Ethiopia. Ethiopia took a homegrown solutions approach to the research and development of its maize and other commodities. The lesson from Ethiopia ’ s experience with maize is that sustained investment in agricul- tural research and development and policy support by the national government are crucial for continued growth of agricultur

A Validated Genome Wide Association Study to Breed Cattle Adapted to an Environment Altered by Climate Change

Continued production of food in areas predicted to be most affected by climate change, such as dairy farming regions of Australia, will be a major challenge in coming decades. Along with rising temperatures and water shortages, scarcity of inputs such as high energy feeds is predicted. With the motivation of selecting cattle adapted to these changing environments, we conducted a genome wide association study to detect DNA markers (single nucleotide polymorphisms) associated with the sensitivity of milk production to environmental conditions. To do this we combined historical milk production and weather records with dense marker genotypes on dairy sires with many daughters milking across a wide range of production environments in Australia. Markers associated with sensitivity of milk production to feeding level and sensitivity of milk production to temperature humidity index on chromosome nine and twenty nine respectively were validated in two independent populations, one a different breed of cattle. As the extent of linkage disequilibrium across cattle breeds is limited, the underlying causative mutations have been mapped to a small genomic interval containing two promising candidate genes. The validated marker panels we have reported here will aid selection for high milk production under anticipated climate change scenarios, for example selection of sires whose daughters will be most productive at low levels of feeding

Assessing inter-sectoral climate change risks: the role of ISIMIP

The aims of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) are to provide a framework for the intercomparison of global and regional-scale risk models within and across multiple sectors and to enable coordinated multi-sectoral assessments of different risks and their aggregated effects. The overarching goal is to use the knowledge gained to support adaptation and mitigation decisions that require regional or global perspectives within the context of facilitating transformations to enable sustainable development, despite inevitable climate shifts and disruptions. ISIMIP uses community-agreed sets of scenarios with standardized climate variables and socio-economic projections as inputs for projecting future risks and associated uncertainties, within and across sectors. The results are consistent multi-model assessments of sectoral risks and opportunities that enable studies that integrate across sectors, providing support for implementation of the Paris Agreement under the United Nations Framework Convention on Climate Change