Search

Cities will play a key role in the grand challenge of nourishing a growing global population, because, due to their population density, they set the demand. To ensure that food systems are sustainable, as well as nourishing, one solution often suggested is to shorten their supply chains toward a regional rather than a global basis. While such regional systems may have a range of costs and benefits, we investigate the mitigation potential of regionalized urban food systems by examining the greenhouse gas emissions associated with food transport. Using data on food consumption for 7108 urban administrative units (UAUs), we simulate total transport emissions for both regionalized and globalized supply chains. In regionalized systems, the UAUs' demands are fulfilled by peripheral food production, whereas to simulate global supply chains, food demand is met from an international pool (where the origin can be any location globally). We estimate that regionalized systems could reduce current emissions from food transport. However, because longer supply chains benefit from maximizing comparative advantage, this emission reduction would require closing yield gaps, reducing food waste, shifting toward diversified farming, and consuming seasonal produce. Regionalization of food systems will be an essential component to limit global warming to well below 2 °C in the future.

Northeast Farming Region of China (NFR) produces about one-third of the national maize output. Shortage of crop irrigation water is one of the main threat to the stable level of maize production in the NFR. Previous studies on the sensitivity of maize production to drought are typically based on field experiments and treat the maize growing season as a whole, with rare attention to the varying impacts of drought across different maize growth stages. Given the importance of NFR on China’s food security, it is crucial to optimize the irrigation schedule to mitigate the adverse effects of drought. In this study, we employ Agro-ecological Zone (AEZ) model to investigate how climate change affects irrigation water requirement (IWR) of maize during different growth stages and under different climate change scenarios. Results indicate that the NFR would experience a substantial increase in the probability of extremely shortage of crop irrigation water under future climate change. The ensemble simulation under future climate projections indicates more frequent demands for irrigation with substantially increased amount in the mid-season stage (G3) when maize is more sensitive to water deficit compared with other stages. These findings indicate that earlier planning of irrigation infrastructure and development of more efficient irrigation scheme and technologies is of great importance to secure maize production in the region.

This paper presents one of the first quantitative scenario assessments for future water supply and demand in Asia to 2050. The assessment, developed by the Water Futures and Solutions (WFaS) initiative, uses the latest set of global climate change and socioeconomic scenarios and state-of-the-art global hydrological models. In Asia, water demand for irrigation, industry and households is projected to increase substantially in the coming decades (30-40% by 2050 compared to 2010). These changes are expected to exacerbate water stress, especially in the current hotspots such as north India and Pakistan, and north China. By 2050, 20% of the land area in the Asia-Pacific region, with a population of 1.6-2 billion, is projected to experience severe water stress. We find that socioeconomic changes are the main drivers of worsening water scarcity in Asia, with climate change impacts further increasing the challenge into the 21st century. Moreover, a detailed basin-level analysis of the hydro-economic conditions of 40 Asian basins shows that although the coping capacity of all basins is expected to improve due to GDP growth, some basins continuously face severe water challenges. These basins will potentially be home to up to 1.6 billion people by mid-21st century.

Chinese Medicinal Yam (CMY) has been prescribed as medicinal food for thousand years in China by Traditional Chinese Medicine (TCM) practitioners. Its medical benefits include nourishing the stomach and spleen to improve digestion, replenishing lung and kidney, etc., according to the TCM literature. As living standard rises and public health awareness improves in recent years, the potential medicinal benefits of CMY have attracted increasing attention in China. It has been found that the observed climate change in last several decades, together with the change in economic structure, has driven significant shift in the pattern of the traditional CMY planting areas. To identify suitable planting area for CMY in the near future is critical for ensuring the quality and supply quantity of CMY, guiding the layout of CMY industry, and safeguarding the sustainable development of CMY resources for public health. In this study, we first collect 30-year records of CMY varieties and their corresponding phenology and agro-meteorological observations. We then consolidate these data and use them to enrich and update the eco-physiological parameters of CMY in the agro-ecological zone (AEZ) model. The updated CMY varieties and AEZ model are validated using the historical planting area and production under observed climate conditions. After the successful validation, we use the updated AEZ model to simulate the potential yield of CMY and identify the suitable planting regions under future climate projections in China. This study shows that regions with high ecological similarity to the genuine and core producing areas of CMY mainly distribute in eastern Henan, southeastern Hebei, and western Shandong. The climate suitability of these areas will be improved due to global warming in the next 50 years, and therefore, they will continue to be the most suitable CMY planting regions.

The Northeast Farming Region (NFR) is a major maize cropping region in China, which accounts for about 30% of national maize production. Although the regional maize production has an increasing trend in the last decades, it has greater inter-annual fluctuation. The fluctuation is caused by the increased variations of the local temperature and precipitation given the dominance of rainfed maize in the region. To secure high and stable level of maize production in the NFR under the warmer and drier future climate conditions, we employed a cross-scale model-coupling approach to identify the suitable maize cultivars and planting adaptation measures. Our simulation results show that, with proper adaptations of maize cultivars and adjustments of planting/harvest dates, both maize planting area and yield per unit of land will increase in most regions of NFR. This finding indicates that proactive adaptation can help local farmers to reap the benefits of increasing heat resource brought in by global warming, thus avoiding maize production losses as reported in other studies. This research can potentially contribute to the development of agricultural climate services to support climate-smart decisions for agricultural adaptations at the plot, farm and regional scales, in terms of planning the planting structure of multiple crops, breeding suitable maize varieties, and optimizing planting and field management schedules.

Water scarcity, a critical environmental issue worldwide, has primarily been driven by a significant increase in water extractions during the last century. In the coming decades, climate and societal changes are projected to further exacerbate water scarcity in many regions worldwide. Today, a major issue for the ongoing policy debate is to identify interventions able to address water scarcity challenges in the presence of large uncertainties. Here, we take a probabilistic approach to assess global water scarcity projections following feasible combinations of shared socioeconomic pathways and representative concentration pathways for the first half of the twenty-first century. We identify—alongside trends in median water scarcity—changes in the uncertainty range of anticipated water scarcity conditions. Our results show that median water scarcity and the associated range of uncertainty are generally increasing worldwide, including many major river basins. On the basis of these results, we develop a general decision-making framework to enhance policymaking by identifying four representative clusters of specific water policy challenges and needs. Designing interventions to address water scarcity under climate change is challenging given the large uncertainties in projected water availability. In this study, changes in the uncertainty range of anticipated water scarcity conditions are identified, and a general decision-making framework to support policy decisions is developed.

In preparation for the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the international community is developing new advanced Earth System Models (ESMs) to assess the combined effects of human activities (e. g. land use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being provided by four Integrated Assessment Model (IAM) teams to be used as input to the ESMs for future carbon-climate projections (Moss et al. 2010). The diversity of approaches and requirements among IAMs and ESMs for tracking land-use change, along with the dependence of model projections on land-use history, presents a challenge for effectively passing data between these communities and for smoothly transitioning from the historical estimates to future projections. Here, a harmonized set of land-use scenarios are presented that smoothly connects historical reconstructions of land use with future projections, in the format required by ESMs. The land-use harmonization strategy estimates fractional land-use patterns and underlying land-use transitions annually for the time period 1500-2100 at 0.5° × 0.5° resolution. Inputs include new gridded historical maps of crop and pasture data from HYDE 3.1 for 1500-2005, updated estimates of historical national wood harvest and of shifting cultivation, and future information on crop, pasture, and wood harvest from the IAM implementations of the RCPs for the period 2005-2100. The computational method integrates these multiple data sources, while minimizing differences at the transition between the historical reconstruction ending conditions and IAM initial conditions, and working to preserve the future changes depicted by the IAMs at the grid cell level. This study for the first time harmonizes land-use history data together with future scenario information from multiple IAMs into a single consistent, spatially gridded, set of land-use change scenarios for studies of human impacts on the past, present, and future Earth system. © 2011 The Author(s).

What are the implications for agriculture of mitigating greenhouse gas emissions? By when and by how much are impacts reduced? Where does it matter most? We investigated these questions within the new A2 emission scenario, recently developed at the International Institute of Applied Systems Analysis with revised population and gross domestic product projections. Coupling an agro-ecological model to a global food trade model, two distinct sets of climate simulations were analyzed: 1) A non-mitigated scenario, with atmospheric CO2 concentrations over 800 ppm by 2100; and 2) A mitigation scenario, with CO2 concentrations stabilized at 550 ppm by 2100. Impacts of climate change on crop yield were evaluated for the period 1990–2080, then used as input for economic analyses. Key trends were computed over the 21st century for food demand, production and trade, focusing on potential monetary (aggregate value added) and human (risk of hunger) impacts. The results from this study suggested that mitigation could positively impact agriculture. With mitigation, global costs of climate change, though relatively small in absolute amounts, were reduced by 75–100%; and the number of additional people at risk of malnutrition was reduced by 80–95%. Significant geographic and temporal differences were found. Regional effects often diverged from global net results, with some regions worse off under mitigation compared to the unmitigated case.

Recent conclusions that new free-air carbon dioxide enrichment (FACE) data show a much lower crop yield response to elevated CO2 than thought previously – casting serious doubts on estimates of world food supply in the 21st century – are found to be incorrect, being based in part on technical inconsistencies and lacking statistical significance. First, we show that the magnitude of crop response to elevated CO2 is rather similar across FACE and non-FACE data-sets, as already indicated by several previous comprehensive experimental and modeling analyses, with some differences related to which “ambient” CO2 concentration is used for comparisons. Second, we find that results from most crop model simulations are consistent with the values from FACE experiments. Third, we argue that lower crop responses to elevated CO2 of the magnitudes in question would not significantly alter projections of world food supply. We conclude by highlighting the importance of a better understanding of crop response to elevated CO2 under a variety of experimental and modeling settings, and suggest steps necessary to avoid confusion in future meta-analyses and comparisons of experimental and model data.

This paper analyses the global consequences to crop yields, production, and risk of hunger of linked socio-economic and climate scenarios. Potential impacts of climate change are estimated for climate change scenarios developed from the HadCM3 global climate model under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) A1FI, A2, B1, and B2. Projected changes in yield are calculated using transfer functions derived from crop model simulations with observed climate data and projected climate change scenarios. The basic linked system (BLS) is used to evaluate consequent changes in global cereal production, cereal prices and the number of people at risk from hunger. The crop yield results elucidate the complex regional patterns of projected climate variables, CO 2 effects, and agricultural systems that contribute to aggregations of global crop production. The A1FI scenario, as expected with its large increase in global temperatures, exhibits the greatest decreases both regionally and globally in yields, especially by the 2080s. The contrast between the yield change in developed and developing countries is largest under the A2a–c scenarios. Under the B1 and B2 scenarios, developed and developing countries exhibit less contrast in crop yield changes, with the B2 future crop yield changes being slightly more favourable than those of the B1 scenario. When crop yield results are introduced to the BLS world food trade system model, the combined model and scenario experiments demonstrate that the world, for the most part, appears to be able to continue to feed itself under the SRES scenarios during the rest of this century. However, this outcome is achieved through production in the developed countries (which mostly benefit from climate change) compensating for declines projected, for the most part, for developing nations. While global production appears stable, regional differences in crop production are likely to grow stronger through time, leading to a significant polarisation of effects, with substantial increases in prices and risk of hunger amongst the poorer nations, especially under scenarios of greater inequality (A1FI and A2). The use of the SRES scenarios highlights several non-linearities in the world food supply system, both in the biophysical sense, where the levels of atmospheric CO 2 tested reach new levels, and the socio-economic sense, where changes in population dynamics and economic and political structures complicate the translation of biophysical climate change impacts into social indices, such as the number of people at risk of hunger.

The recent warming trends have led to rising concerns on how the changing climate has been altering and will continue to alter agroclimatic conditions in China. In this study, high resolution climate scenarios from regional climate models (RCMs) are used as input to the agro-ecological zones (AEZ) model for China and to compute a comprehensive set of agroclimatic indicators. Uncertainties in the projected impacts of climate change on agroclimatic conditions are also discussed with respect to (1) RCM outputs for different emission scenarios, and (2) differences in projections obtained from two different RCMs under the same emission scenario. The results indicate a significant extension of the crop growing period in tandem with the rising temperatures during the crop growing season, which may lead to increase in multi-cropping opportunities at high latitudes and thus advance the total potential output per unit of cropland. On the other hand, the results show that the Southwest China will experience a significant reduction in the value of humidity index, implying severe challenges for future agricultural development in the region. Spatially explicit patterns of changes in future agroclimatic conditions, as revealed in this study, can be beneficial for policy-makers, farming communities and other stakeholders to assess risk factors, design adaptation and mitigation measures, and improve management practices at the local to regional scales.

Building on previous work quantitative estimates of climate change impacts on global food production have been made for the UK Hadley Centre's HadCM2 greenhouse gas only ensemble experiment and the more recent HadCM3 experiment (Hulme et al., 1999). The consequences for world food prices and the number of people at risk of hunger as defined by the Food and Agriculture Organisation (FAO, 1988) have also been assessed. Climate change is expected to increase yields at high and mid-latitudes, and lead to decreases at lower latitudes. This pattern becomes more pronounced as time progresses. The food system may be expected to accommodate such regional variations at the global level, with production, prices and the risk of hunger being relatively unaffected by the additional stress of climate change. By the 2080s the additional number of people at risk of hunger due to climate change is about 80 million people (±10 million depending on which of the four HadCM2 ensemble members is selected). However, some regions (particularly the arid and sub-humid tropics) will be adversely affected. A particular example is Africa, which is expected to experience marked reductions in yield, decreases in production, and increases in the risk of hunger as a result of climate change. The continent can expect to have between 55 and 65 million extra people at risk of hunger by the 2080s under the HadCM2 climate scenario. Under the HadCM3 climate scenario the effect is even more severe, producing an estimated additional 70+ million people at risk of hunger in Africa.

Projections of climate impacts on crop yields simulated for different General Circulation Model (GCM) scenarios are used, in a recursively dynamic general equilibrium framework, to account for potential economy-wide impacts of climate change in Egypt. Comparing these impact projections to those obtained under a reference, business-as-usual, scenario assuming some moderate changes in the political, economic or technological spheres, indicates that global warming has potentially negative effects. The analysis is based on a global assessment of potential climate change-induced variations in world commodity production and trade. The Egyptian agricultural sector, and the non-agricultural sector to a lesser extent, are projected to be increasingly less self-sufficient. Specific potential adverse impacts are identified. The simulation results show that high-cost adaptation measures involving major changes in the agricultural system and practices may mitigate these adverse impacts. Stimulating economic development of the rural areas and creating appropriate conditions for effective diffusion and development of technologies — particularly for the agricultural sector — would seem a desirable strategy. Perhaps, more importantly, the simulation results show that the assumption of exogenously determined technological progress may be inappropriate, in which case the potential adverse impacts of a future warming of the global climate are likely to be fewer than is indicated in this study — if prevailing constraints on productivity growth in the major food and feed grains are ‘released’ by endogenous advances in technology.

This paper summarizes the findings of a major interdisciplinary research effort by scientists in 25 countries. The study examined the potential biophysical responses of major food crops to changing atmospheric composition and climate, and projected potential socioeconomic consequences. In a first step crop models were used to estimate how changing climatic conditions might alter yields of major crops at a number of sites representing both major production areas and vulnerable regions at low, mid and high latitudes. Then a dynamic recursive national-level model of the world food system was used to assess socio-economic impacts for the period 1990 up to year 2060.

A comprehensive assessment of the impacts of climate change on agro-ecosystems over this century is developed, up to 2080 and at a global level, albeit with significant regional detail. To this end an integrated ecological–economic modelling framework is employed, encompassing climate scenarios, agro-ecological zoning information, socio-economic drivers, as well as world food trade dynamics. Specifically, global simulations are performed using the FAO/IIASA agro-ecological zone model, in conjunction with IIASAs global food system model, using climate variables from five different general circulation models, under four different socio-economic scenarios from the intergovernmental panel on climate change. First, impacts of different scenarios of climate change on bio-physical soil and crop growth determinants of yield are evaluated on a 5′×5′ latitude/longitude global grid; second, the extent of potential agricultural land and related potential crop production is computed. The detailed bio-physical results are then fed into an economic analysis, to assess how climate impacts may interact with alternative development pathways, and key trends expected over this century for food demand and production, and trade, as well as key composite indices such as risk of hunger and malnutrition, are computed. This modelling approach connects the relevant bio-physical and socio-economic variables within a unified and coherent framework to produce a global assessment of food production and security under climate change. The results from the study suggest that critical impact asymmetries due to both climate and socio-economic structures may deepen current production and consumption gaps between developed and developing world; it is suggested that adaptation of agricultural techniques will be central to limit potential damages under climate change.

Agreements to mitigate climate change have been hampered by several things, not least their cost. But the cost might well be more acceptable if we had a clear picture of what damages would be avoided by different levels of emissions reductions, in other words, a clear idea of the pay off. The problem is that we do not. The Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) published this year (IPCC (2001a) and IPCC (2001b)) lists a wide range of potential impacts but has difficulty in discriminating between those that are critical in their nature and magnitude from those that are less important. Yet, the identification of critical impacts (e.g. ones that should be avoided at any reasonable cost) is obviously a key to addressing targets for mitigating climate change. Indeed, a central objective of the UN Framework Objective on Climate Change (UNFCCC) is to avoid “dangerous levels” of climate change that could threaten food security, ecosystems and sustainable development (areas of risk that are specifically mentioned in UNFCCC Article 2). For several years, we have been researching impacts in key areas of risk: hunger, water shortage, exposure to malaria transmission, and coastal flooding, as part of a global fast-track assessment (Parry and Livermore, 1999). 1 The results of our work have been reported widely and form a significant part of the IPCC's assessment of likely impacts (IPCC (2001a) and IPCC (2001b)). But they are scattered through different parts of the IPCC report and other literature and, before now, we have not brought them together. For this review, we have graphed our estimates of effects as a single measure: the additional millions of people who could be placed at risk as a result of different amounts of global warming ( Fig. 1). Full-size image (36K) - Opens new window Full-size image (36K) Fig. 1. Additional millions at risk due to climate change in 2050s and 2080s for hunger, coastal flooding, water shortage and malaria. The width of the curve indicates one standard deviation of variance around the mean, based on results from four HadCM2 experiments (Parry and Livermore, 1999; IPCC, 2000). Solid lines indicate model-based estimates. Dotted lines are inferred ( IPCC (2001a) and IPCC, 2001b. Climate change 2001: The Scientific Basis. Technical Summary of the Working Group I Report, Geneva, 2001.IPCC (2001b)) and intended as schematic. Stab. 450 (etc.)=stabilisation@450 ppmv (etc.). View Within Article The figure shows the increase in millions at risk due to higher temperatures for two time periods—2050s and 2080s. The analysis takes into account likely non-climate developments such as growth in population, and income and developments of technology, and these become important assumptions behind future trends in, for example, increases in crop yield and the building of coastal defences. These developments themselves have very great effects on the numbers at risk and represent a (non-climate change) reference case. The graph thus shows the additional millions at risk due specifically to estimated future changes in climate. But now for the caveats: the reference case is only for one future world (what the IPCC used to call a best estimate or “business-as-usual” future, now referred to as IS92a). More recently, the IPCC has explored a set of six different developmental pathways that the world may follow (IPCC, 2000), and the millions at risk in these alternative futures will certainly differ. Our work on these is in hand but will probably take a year to complete. We need also to emphasise that the graph is a global estimate which hides important regional variations and, so far, it is based on one model of future climate patterns (the UK's Hadley Centre second generation global climate model) ( Johns et al., 1997). While these are the only global impact estimates currently available, we need urgently to complete similar ones for different climate models and for a variety of development pathways. Five important points emerge from this figure. First, the curves of additional millions at risk generally become steeper over time. Less obviously, this results as much from a larger and more vulnerable exposed population in 2080 than in 2050, as from increases in temperature or inferred changes in precipitation and sea-level rise. For example, the remarkable steepness of the water shortage curve in 2080 is the outcome of very large city populations in China and India becoming newly at risk. In the case of hunger, however, the rising curve in 2080 stems from widespread heat stress of crops, while up to about 2050 lesser amounts of warming lead to yield gains in temperate regions that balance losses elsewhere and lead to only small net increases in hunger (Parry and Livermore, 1999). These complex interactions between exposure and climate change tell a clear story: there will be more millions at risk as time progresses. Secondly, the figure indicates how much we need to reduce emissions in order to draw-down significantly the numbers at risk. We have estimated effects assuming that atmospheric concentrations of CO2 are stabilised at 750 parts per million (ppmv) by 2250 and at 550 ppmv by 2150 (Arnell, in press). These are approximately equivalent, respectively, to 10 times and 20 times the reduction in emissions assumed in the Kyoto Protocol. The 750 ppmv target delays the damage but does not avoid it. By 2080, it would halve the number at risk from hunger and flooding, reduce the population at risk of malaria by perhaps a third and water shortage by about a quarter. But to bring risk levels down from hundreds to tens of millions would require a stabilisation target of about 550 ppmv. We have also indicated on the graph, but only in a schematic form, the approximate locations of 450, 650 and 1000 ppmv stabilisation pathways and their effect on millions at risk (IPCC (2001a) and IPCC (2001b)). Although impact analyses have not yet been conducted for these stabilisation levels, it appears that the 450 ppmv pathway would achieve very great reductions in millions at risk, although very high costs of mitigation would be incurred. It is precisely this kind of pay-off that needs to be analysed properly. A third conclusion is that information is now available that can help inform the selection of climate change targets. Thus far these targets, such as Kyoto, have been chosen in broadly a top–down manner, without clear knowledge of the impacts that would be avoided, and that has been partly their weakness. Now we may argue, for example, that in order to keep damages below an agreed tolerable level (for example, a given number of additional people at risk) global temperature increases would need to be kept below a given amount; and emissions targets could then be developed to achieve that objective. Fourthly, it is clear that mitigation alone will not solve the problem of climate change. Adaptation will be necessary to avoid, or at least reduce, much of the possible damage, and since we need many of the benefits of adaptation today, regardless of climate change in the future (e.g. increased drought protection of agriculture, improved flood defences, more efficient use of water, better malaria control), many of the adaptive strategies for climate change can be “win–win”. We need to find a blend of mitigation and adaptation to meet the challenge of climate change. Mitigation can buy time for adaptation (for example, delaying impacts until improved technology and management can handle them), and adaptation can raise thresholds of tolerance that need to be avoided by mitigation (for example, by increasing drought tolerance of crops). Considered separately, they appear inadequate to meet such a challenge, but combined they would make a powerful response.

The purpose of this paper is to exemplify a means by which an integrated assessment can be made of global and regional effects on land use of climate change. This is achieved by use of data on the effects of climate change on world food prices as inputs to a regional land use allocation model. Data on world prices are drawn from a recent global study of climate change and crop yields. In a case study of England and Wales a land allocation model is used to infer changes of land use that are the product of the integrated effect of climate-induced global price changes and climate-related changes of yield in England and Wales. This combination of changed prices and yield potential is used to calculate the land use providing the highest returns for each of 155,235 1 km2 cells of land in England and Wales for a future assumed for the year 2060 (without climate change) and then for that same environment with climate change. The difference between these two is then treated as an estimated effect resulting from climate change.