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Background: Heart failure (HF) due to myocarditis might not respond in the same way to standard therapy as HF due to other aetiologies. The aim of this study was to investigate the value of endomyocardial biopsies (EMB) for clinical decision-making and its relation to the outcome of paediatric patients with myocarditis. Methods: Clinical and EMB data of children with myocarditis collected for the MYKKE-registry between 2013 and 2020 from 23 centres were analysed. EMB studies included histology, immunohistology, and molecular pathology. The occurrence of major adverse cardiac events (MACE) including mechanical circulatory support (MCS), heart transplantation, and/or death was defined as a combined endpoint. Results: Myocarditis was diagnosed in 209/260 patients: 64% healing/chronic lymphocytic myocarditis, 23% acute lymphocytic myocarditis (AM), 14% healed myocarditis, no giant cell myocarditis. The median age was 12.8 (1.4-15.9) years. Time from symptom-onset to EMB was 11.0 (4.0-29.0) days. Children with AM and high amounts of mononuclear cell infiltrates were significantly younger with signs of HF compared to those with healing/chronic or healed myocarditis. Myocardial viral DNA/RNA detection had no significant effect on outcome. The worst event-free survival was seen in patients with healing/chronic myocarditis (24%), followed by acute (31%) and healed myocarditis (58%, p=0.294). A weaning rate of 64% from MCS was found in AM. Conclusions: EMB provides important information on the type and stage of myocardial inflammation and supports further decision-making. Children with fulminant clinical presentation, high amounts of mononuclear cell infiltrates or healing/chronic inflammation and young age have the highest risk for MACE.

Sustainable Intensification of agriculture is a means to meet increasing future food demand in regions with rapidly growing populations and economies. In many of these regions, productivity is currently low. Increasing productivity while limiting additional use of resources such as water and land is therefore key to providing demanded and nutritious food in these countries. To model sustainable intensification, we build an optimization model. In its main economic specification, the objective of the model is to maximize farmer profit while at the same time respecting ecological boundaries. Therefore, constraints of the model are given by land availability and agronomic and climatic constraints to crop growth from the Global Agroecological Zones (GAEZ) method, as well as water availability derived from the Global Hydro-Economic Model (ECHO). The framework can be applied for either a single crop or multiple crops. The results of our analysis provide guidance on where and under which circumstances production of a crop can most efficiently be intensified. This can include the spatial distribution of irrigation or the allocation of several crops to optimally meet estimated demand. Demand is derived from projections of human population, economic growth and income elasticities. We use scenario analysis to examine how optimal sustainable intensification strategies change under different trade regimes for agricultural products and under different levels of climate resilience. Application of the model focuses on the East African extended Lake Victoria Basin (eLVB). In eLVB agroecological conditions are favorable for a wide range of crops, sufficient water is available in several sub-basins and population and food demand are projected to rapidly expand.

The rapid growth of China's demand for grains is expected to continue in the coming decades, largely as a result of the increasing feed demand to produce protein-rich food. This leads to a great concern on future supply potentials of Chinese agriculture under climate change and the extent of China's dependence on world food markets. While the existing literature in both agronomy and climate economics indicates a dominance of the adverse impacts of climate change on rice, wheat, and maize yields, there is a lack of study to assess changes in multi-cropping opportunities induced by climate change. Multi-cropping benefits crop production by harvesting more than once per year from a given plot. To address this important gap, we established a procedure within the agro-ecological zones (AEZ) modeling framework to assess future spatial shifts of multi-cropping conditions. The assessment was based on an ensemble of five general circulation models under four representative concentration pathway scenarios in the phase five of coupled model inter-comparison project and accounted for the water scarcity constraints. The results show significant northward extensions of single-, double-, and triple-cropping zones in the future which would provide good opportunities for crop-rotation-based adaptation. The increasing multi-cropping opportunities would be able to boost the annual grain production potential by an average scale of 89(±49) Mt at the current irrigation efficiency and 143(±46) Mt at the modernized irrigation efficiency with improvement between the baseline (1981–2010) and the mid-21st century (2041–2070).

Summary The development of and access to freshwater resources in East Africa is fundamental to the region's sustainable development goals. Following vision documents for regional development and working with local stakeholders, we developed water scenarios up to 2050 that inform the hydro-economic modeling analysis of the extended Lake Victoria Basin, the headwaters of the Nile River. Water scenarios that take an integrated approach to assessing the combined effects of climate change, land use, and increasing human water use suggest that the flow regime of the Nile may remain relatively stable. However, if this stability is to be achieved, while at the same time sufficient water is preserved for healthy freshwater ecosystems, a large fraction of water infrastructure must rely on advanced, often costly technologies and management. Interconnected analyses of both upstream and downstream water resources over time, guided by co-developed scenarios, are indispensable for planning sustainable water-development pathways.

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.

The study presents an application of Agro‐Ecological Zones (AEZ) methodology for assessing the land suitability and production potential of selected crops in Bundelkhand region, India on a watershed basis. The assessment of the suitability index and respective output density of Kharif crops was done under rainfed conditions with a high level of input. The rabi crops showed no suitable category of suitability index under rainfed conditions, but various suitability was seen under irrigation conditions. The spatial agro-climatic assessment, provided by the GAEZ model, in terms of suitability index and output density will strengthen the decisions for cropping patterns under future climatic scenarios in the Ur River watershed., {"references":["FAO (1976). A framework for land evaluation. FAO Soils Bulletin 32. FAO, Rome, Italy.","FAO (1984). Tillage systems for soil and water conservation. FAO Soil Bulletin 54. FAO, Rome, Italy.","FAO (2007). Global Administrative Unit Layers (GAUL), available at: http://www.fao.org/geonetwork/srv/en /metadata.show?id=12691&currTab=s imple","FAO (2009). The State of Food Insecurity in the World 2009. Food and Agriculture Organization of the United Nations, Rome, Italy.","FAO/IIASA/ISRIC/ISS-CAS/JRC (2009). Harmonized World Soil Database (version 1.1). FAO and IIASA. Rome, Italy and Laxenburg, Austria.","Fischer, G. (2009). World food and agriculture to 2030/50. Tech. Pap. from Expert Meet. How to Feed World, 24-6.","Fischer, G., Shah, M., N. Tubiello, F., & Van Velhuizen, H. (2005). Socioeconomic and climate change impacts on agriculture: an integrated assessment, 1990–2080. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1463), 2067- 2083.","Fischer, G., & Sun, L. (2001). Model based analysis of future land-use development in China. Agriculture, Ecosystems & Environment, 85(1-3), 163-176.","Gohari, A., Eslamian, S., Abedi- Koupaei, J., Bavani, A. M., Wang, D., & Madani, K. (2013). Climate change impacts on crop production in Iran's Zayandeh-Rud River Basin. Science of the Total Environment, 442, 405-419.","Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M. M., Allen, S. K., Boschung, J., & Midgley, P. M. (2014). Climate Change 2013: The physical science basis. contribution of working group I to the fifth assessment report of IPCC the intergovernmental panel on climate change."]}

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.

The development of and access to freshwater resources is fundamental if East Africa aims to achieve its goal of increased economic growth. Following vision documents for regional development and working together with local stakeholders, we developed water scenarios up to 2050 that inform the hydro-economic modelling analysis for the extended Lake Victoria Basin, the headwaters of the Nile River. Results indicate a 4-5 fold increase in water demand, especially for expanding irrigation and domestic water needs. Together with climate and land use change, the discharge and flow regime of the Nile will remain relatively stable. However, if this is to be achieved, while sufficient water is preserved for environmental needs, a large fraction of future water infrastructure must rely on advanced, often costly, technological, and management options. The interconnected analysis, between up-stream and down-stream water resources and sectoral water demand, guided by co-developed scenarios, supports planning of sustainable water pathways.

Key messages • This book applies a unique, structured, systems methodology for characterizing and grouping large populations of farm households with broadly similar livelihood, production and consumption patterns, and for whom similar development strategies would be appropriate. • As a result African households across the continent are grouped into 15 major farming systems and 58 subsystems. • The farming systems analysis integrates an extensive range of spatial data, administrative statistics, assessment reports and expert knowledge, in order to update the African component of the 2001 FAO/World Bank farming systems analysis. • Pattern recognition is key to teasing out the diversity inherent in African agriculture and in understanding common livelihood patterns (derived from crops, trees, livestock, fish and off-farm income), constraints and opportunities which define each farming system. • The principle of central tendency is used to identify the core length of growing period and travel time to the nearest market town, which are two key indicators of access to agricultural resources and access to agricultural services, respectively, that shape livelihood patterns in each farming system. • The method allows farming system drivers, trends and strategic interventions to be identified for policymakers, investors and research planners, using a synthesis of UN statistics, assessment reports and expert knowledge. Summary This chapter describes the farming systems analysis methodology used to characterize African farming systems in this book, in particular the methods for identifying a common livelihood pattern (derived from crops, trees, livestock, fish and off-farm income) and the constraints and development opportunities for each farming system. The analysis integrated a wide range of data and information from spatial databases, administrative statistics, assessment reports and expert knowledge of the particular farming system characteristics, drivers and trends, constraints and development opportunities. The skill of pattern recognition is essential for identifying common mixes of system livelihoods. The farming system is shaped by access to agricultural resources (a basic indicator is length of growing period) and access to agricultural services (a basic indicator is travel time to the nearest market town), and these factors underpinned the mapping and characterization. The management and development of farming systems depend on the strategies of farm households for escape from poverty or improvement of farm incomes. The multidisciplinary analysis teams who identified the farming system constraints and opportunities, and the household strategies, subsequently wrote the relevant farming system chapters.

Replacing traditional fossil fuel with bioethanol has been adopted in many countries to reduce carbon emissions and achieve climate mitigation targets. However, the soaring global demand for food and bioethanol in the future may impose heavy environmental pressure on major sugar crops producing regions of Latin America and the Caribbean (LAC) through significant changes in land and water uses. Irrigation expansion in the rainfed dominant cropping areas would partially slow down the land use expansion by boosting yields, but require large-scale investments. This study assesses the future land and water demand triggered by sugar crops expansion from the food-energy-water/land nexus perspective through coupling the Global Agro-Ecological Zones model (GAEZ) with Multi-Regional Input-Output (MRIO) analysis. We further analyse the tradeoffs between water and land use under future scenarios of climate change and socio-economic development regarding to the expected goals of biofuel policies and irrigation expansion strategies in LAC countries due to sufficient local water resources. The results show that the projected water and land demand of sugar crops in LAC would increase by 198% and 205% from 2014 to 2040. Increasing the low- or non- irrigated area up to 50% would mitigate the yield loss and reduce the land demand by 10%, with limited impact on the local water resources in most LAC countries. Major bioethanol producers with limited water demand compared with available water resources, such as Brazil and Argentina, could further promote irrigation to avoid significant landuse change and benefit other countries’ land ecosystems via inter-regional bioethanol trade. While in potential higher water stress countries, including Dominican Republic, El Salvador, Guatemala and Mexico, under bioenergy orientated policy in 2040, reducing biofuel policy targets or importing bioethanol from resource rich countries would be a better option. These results could provide guidelines to balance sugar crops production and sustainable water and land use strategies across LAC.

Insufficient precipitation and continuous over-exploitation of groundwater for agricultural irrigation led to rapid drop of groundwater table in a large part of the North China Plain (NCP), the bread basket of China. It has become widely acknowledged that current practice of winter wheat-summer maize sequential cropping system (WM-S) in the NCP will have to come to an end as soon as possible. Great research efforts have been made at the local level via both field experiments and model simulations to construct groundwater neutral cropping systems but virtually all such constructs show a substantial penalty on total output per unit of land per year. In this research, we propose a strategy to meet the double challenge of maintaining regional grain production level and recovering local groundwater table: 1) Widely adopt winter fallow and early-sowing summer maize monocropping (E-M) in water scarce part of the region to enable groundwater recovery; 2) replace WM-S by wheat-maize relay intercropping system (WM-R) in the water richer part of the NCP to increase grain production so as to compensate yield losses in the water scarce part of the region. Our simulations using DSSAT 4.6 at the site level show that both yield and water productivity of E-M are 33.7% and 41.8% higher than those of existing summer maize, with less than 20% of increase in water requirement. In comparison with spring maize, E-M requires 62.4% less irrigation water, with a yield penalty of only 4.52%. At the regional scale, the simulations targeting at maximizing groundwater saving in water scarce area subject to maintaining the current level of regional total output indicate that about 20.45% of the wheat planting area can be put on fallow in winter, most of which is located in the driest regions of the NCP. This can result in a large amount of groundwater saving at 5.62 × 109 m3 and a substitution of wheat by maize at 24.3% of the total wheat output. These findings provide new rooms for the relevant policy makers and stakeholders to address the urgent groundwater recovering issues in the northern NCP without compromising the level of food grain production of 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.

Understanding teleconnections of regional consumption patterns and global land use supports policy making towards achieving sustainable land use. We present an innovative globally consistent hybrid land-flow accounting method to track biomass flows and embodied land along global supply chains. It uses the large FAOSTAT database, which is, for non-food commodities, complemented with a multi-regional input-output model. We employ the hybrid model globally between 1995 and 2010 and present results for 21 regional markets. Results highlight the growing integration in international markets. In 2010, 31% of cropland cultivation was for export markets compared to 16% in 1995. The higher land demand of livestock-based diets, which account for one third of global cropland use, and differences in land use intensities cause large regional variations in extents and composition of land footprints. The utilization of cropland changed towards a growing importance of the non-food sector accounting for 12% in 2010. Comparing land quality weighted cropland footprints across regions further reveals large differences in the appropriation of available global cropland productivity. Because of large uncertainties and quality differences in the actual use of grassland for feeding ruminants, we propose land quality weighted grassland footprints to discuss the additional land use for ruminant livestock products.

A rapidly growing share of global agricultural areas is devoted to the production of biomass for non-food purposes. The expanding non-food bioeconomy can have far-reaching social and ecological implications; yet, the non-food sector has attained little attention in land footprint studies. This paper provides the first assessment of the global cropland footprint of non-food products of the European Union (EU), a globally important region regarding its expanding bio-based economy. We apply a novel hybrid land flow accounting model, combining the biophysical trade model LANDFLOW with the multi-regional input–output model EXIOBASE. The developed hybrid approach improves the level of product and country detail, while comprehensively covering all global supply chains from agricultural production to final consumption, including highly processed products, such as many non-food products. The results highlight the EU's role as a major processing and the biggest consuming region of cropland-based non-food products, while at the same time relying heavily on imports. Two thirds of the cropland required to satisfy the EU's non-food biomass consumption are located in other world regions, particularly in China, the US and Indonesia, giving rise to potential impacts on distant ecosystems. With almost 39% in 2010, oilseeds used to produce for example biofuels, detergents and polymers represented the dominant share of the EU's non-food cropland demand. Traditional non-food biomass uses, such as fibre crops for textiles and animal hides and skins for leather products, also contributed notably (22%). Our findings suggest that if the EU Bioeconomy Strategy is to support global sustainable development, a detailed monitoring of land use displacement and spillover effects is decisive for targeted and effective EU policy making.

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.

Despite globalization and the scale of international food trade, access to sufficient food remains a major challenge in Africa. The most effective way to mitigate food insecurity is to increase crop production. To answer the question that whether African countries have the capacity to mitigate food shortages by best cultivating practices observed on current cropland, in this study, we use the local net primary productivity scaling (LNS) method to evaluate the currently attainable potential yield-gap (CAYgap). The CAYgap is initially used to suggest steps towards best regional agricultural practices and provide an indicator of regional divergence of cropland productivity in each homogeneous agro-climatic zone. Results indicate that under current climatic conditions, improving each countries’ productivity to the zonal optimal level, around ~ 90% of all African countries have the capacity to mitigate their current energy shortages independently. Thus, to achieve ending hunger, possible efforts are needed which include (1) clarifying what and how socio-economic and institutional factors cause yield divergence across agro-climatic zones and establishing relevant practical policies; (2) strengthening the resilience of food access to make national food availability favors households and individuals; and (3) establishing systematically monitoring platforms on dynamics of crop yields from pixel to regional and from growth phrase to decadal scales. Furthermore, our study demonstrates the feasibility of applying satellite-derived indicators for the maximum yield achieved method to quantify and map the current cropland yield divergence by LNS method, and this method could be applied on different spatial level from regional to global scale with reasonable homogeneous zone scheme.

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.

A rapidly growing share of global agricultural areas is devoted to the production of biomass for non-food purposes. The derived products include, for example, biofuels, textiles, detergents or cosmetics. Given the far-reaching global implications of an expanding non-food bioeconomy, an assessment of the bioeconomy’s resource use from a footprint perspective is urgently needed. We determine the global cropland footprint of non-food products with a hybrid land flow accounting model combining data from the Food and Agriculture Organization and the multi-regional input-output model EXIOBASE. The globally interlinked model covers all cropland areas used for the production of crop- and animal-based non-food commodities for the years from 1995 to 2010. We analyse global patterns of raw material producers, processers and consumers of bio-based non-food products, with a particular focus on the European Union. Results illustrate that the EU is a major processer and the number one consumer region of non-food cropland, despite being only the fifth largest producing region. Two thirds of the cropland required to satisfy EU non-food consumption are located in other world regions, giving rise to a significant dependency on imported products and to potential impacts on distant ecosystems. With almost 29% in 2010, oilseed production, used to produce, for example, biofuels, detergents and polymers, represents the dominant share in the EU’s non-food cropland footprint. There is also a significant contribution of more traditional non-food biomass uses such as fibre crops (for textiles) and animal hides and skins (for leather products). Our study emphasises the importance of comprehensively assessing the implications of the non-food bioeconomy expansion as envisaged in various policy strategies, such as the Bioeconomy Strategy of the European Commission.

This study presents a new database of land use categories in Brazil at a spatial resolution of 30 arc-second (about 1 km2). The spatial representation of current major land uses formally combines agricultural statistics from Brazil's latest census of the year 2006 at micro-region level and the Food and Agriculture Organization 2010 forest statistics with spatial land cover data sets. Spatial allocation (“downscaling”) algorithms were applied to obtain a spatial distribution of seven major land use categories. Remaining shares in each grid-cell were termed residual land, and were categorized according to legal protection status, biodiversity value, and whether they belong to the territory of the Amazon biome. We found a total of 84 Mha residual land of which 37 Mha occurred outside the territory of the Amazon biome and was neither legally protected nor categorized as highly biodiverse land. The 37 Mha “available residual land” equates to 4.4% of Brazil's geographical area and to 50% of its current cultivated land area. We assessed land quality using the Agro-ecological Zones modelling framework provides land suitability and productivity estimates of the available residual land. Nearly one-third of land emerged of prime quality and is therefore promising for biofuel feedstock production. Analysis of potential food-fuel competition suggests that until 2030 productivity improvements on current pastures could accommodate land demand for Brazil's increasing cattle herd and expanding croplands. If these productivity increases could be achieved on current agricultural land, residual land could provide areas for the sustainable expansion of biofuel feedstock production.

In an increasingly globalized world with more and more distributed international supply chains, sustainability studies and policies need to consider socioeconomic and environmental interactions between distant places. Studies of the global biomass metabolism investigate physical flows between and within nature and human systems, thus providing a useful basis for understanding the interrelatedness of changes in one place with impacts elsewhere. Various methodological approaches exist for studying the human-nature metabolism and estimating the land embodied in international trade flows, a core element of assessing telecouplings in the global land system. The results of recent studies vary widely, lacking robustness and thus hampering their application in policy making. This article provides a structured overview and comparative evaluation of existing accounting methods and models for calculating land footprints. We identify differences in available accounting methods and indicate their shortcomings, which are mainly attributable to the product and supply chain coverage and detail, and biases introduced by the use of monetary flows as a proxy for actual physical flows. We suggest options for further development of global land footprint accounting methods, particularly highlighting the advantages of hybrid accounting approaches as a framework for robust and transparent assessments of the global displacement of land use.

Climate, Energy, Water and Land-use Systems (CLEWS) are closely integrated. Yet, most related decision and policy making occurs in disparate institutional entities, informed by relatively disconnected assessments of the individual resource systems. This paper presents the added value of an integrated analytical assessment approach. In doing so, it explicitly values various interdependencies and interactions between CLEWS primarily from an energy sector perspective. The island state of Mauritius was identified as a useful case study given its diverse climate, its increasing water stresses, and its policy focus on reshaping agricultural land-use and reducing fossil fuel imports. Several scenarios to 2030 were defined and analysed to demonstrate the tensions around the CLEWS nexus. Results from an assessment of the energy system with no modelled interlinkages to land-use, energy and water systems are first presented. Then, these are compared to those from an integrated CLEWS assessment. This serves to highlight important dynamics that would have been overlooked without such a systems approach. As an example, the added value of this approach is clearly demonstrated when rainfall reductions are taken into account, and where future land-use changes might occur.

Can the predicted rise in global food demand by 2050 be met sustainably? A modelling study suggests that a combination of interventions will be needed to tackle the associated environmental challenges. Meeting future food demand sustainably will require a range of interventions.

Ecological-economic model simulations of the world food system have been used to study the impacts of historic and future liquid transport biofuel expansion on agricultural markets and the environment. Almost half of global cropland increase between 2000 and 2008 (about 8 Mha or 0.5% of global cropland) can be attributed to biofuel expansion alone. The central "New Policies Scenario" of the World Energy Outlook 2011 projects an increase of conventional crop-based biofuel use from 60 Mtoe (2.5 EJ) in 2010 to annually 160 Mtoe (6.7 EJ) in 2035. Until 2020, the projected biofuel consumption provides no or little cumulative net greenhouse gas (GHG) savings as the time period is hardly sufficient to compensate for carbon losses due to over 10 Mha of additional land use conversion. By 2035, cumulative net GHG savings improve up to 2.8 Pg CO2 equivalent in a scenario with assumed higher agricultural productivity growth in developing countries. This scenario increases the developing region's competitive positions and avoids additional people at risk of hunger due to higher commodity prices caused by biofuel use. Available underutilized grassland and woodland may provide land resources suitable for nonfood energy crop production required for the second-generation biofuel conversion pathways, while causing only limited impacts on food security and biodiversity. We estimate between 246 and 475 Mha of global grassland and woodland to be agronomically suitable for industrial-scale lignocellulosic energy crop production, with achievable rain-fed yields of at least 10 tons of dry matter per hectare, with good accessibility and relatively low ruminant livestock density.

The response of the agro-ecological system to the environment includes the response of individual crop's physiological process and the adaption of the crop community to the environment and its change. Observation and simulation at the single scale level cannot fully explain the above process. It is necessary to develop cross-scale agro-ecological models and study the interaction of agro-ecological processes across different scales. Two typical agro-ecological models (DSSAT and AEZ) are employed in this study and a framework for effective cross-scale data-model and model-model fusion is proposed and illustrated based on the application of DSSAT and AEZ models. The site-specific crop model is up-scaled by using this data-model fusion method, observed data from 36 different agricultural observation stations nationwide and historical weather stations observations (1962-1990) are employed and average crop productivity are estimated. Comparison of the estimation results shows the major consistency across the two models and also indicates specific directions for further improvement. This would help the future efforts in cross-scale crop model fusion.

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).

Growing population, rapid urbanization, rising incomes, and changing consumption preferences stimulate intensification of livestock production and excessive fertilization of crops in China. We present an innovative approach that sheds light on options to prevent negative environmental consequences of food production. Trends indicate that agricultural production expansion will take place in “profitable” locations around densely populated areas, where there are generally insufficient natural resources to recycle production wastes. This will likely lead to increased environmental impacts and risks to human health, with the largest impacts in close proximity to population hotspots. We identify trends in Chinese agricultural production and devise and compare feasible mitigation scenarios. We present a spatial allocation procedure that facilitates management of agricultural production expansion, accounting for environmental and health constraints. This procedure, based on behavioral principles, uses a spatial risk preference structure induced by local conditions, including environment, production, and demand, with important research and policy implications.

The idea of market-based carbon emission trading and carbon taxes is gaining in popularity as a global climate change policy instrument. However, these mechanisms might not necessarily have a positive outcome unless their value reflects socioeconomic and environmental impacts and regulations. Moreover, the fact that they have various inherent exogenous and endogenous uncertainties raises serious concerns about their ability to reduce emissions in a cost-effective way. This paper aims to introduce a simple stochastic model that allows the robustness of economic mechanisms for emission reduction under multiple natural and human-related uncertainties to be analyzed. Unlike standard equilibrium state analysis, the model shows that the explicit introduction of uncertainties regarding emissions, abatement costs, and equilibrium states makes it almost impossible for existing market-based trading and carbon taxes to be environmentally safe and cost-effective. Here we propose a computerized multi-agent trading model. This can be viewed as a prototype to simulate an emission trading market that is regulated in a decentralized way. We argue that a market of this type is better equipped to deal with long-term emission reductions, their direct regulation, irreversibility, and “lock-in” equilibria.

Agriculture is a major source of water, air and soil pollution. Pollution rates are often linked to intensification of agricultural activities, i.e., large-scale livestock production and excessive fertilization of crops. In this paper, we develop a concept of a spatially and temporally explicit model for sustainable agriculture production planning, which operates at a detailed spatial scale and integrates demand and agricultural production activities at national and sub-national levels. It distinguishes environmental loads and sources of agricultural pollution originating from two main agricultural activities: livestock raising and crop production. The indicators used to reflect the impacts of agricultural production comprise of fluxes to air (emissions of ammonia and nitrous oxide) and water (nitrate leaching). Possible domains of the indicator variables are subdivided into sub-domains of different impact severity classes. Risk functions indicate the degree of risk associated with agricultural production, similar to fuzzy logic approaches. Alternative production scenarios are compared in terms of human exposure to risk, i.e., the number of people in different risk classes. In this way the model allows for assessment and testing of strategies for mitigating agricultural pollution. Application of the integrated model is illustrated by a case study of agricultural production development in China. China is of global importance due to its huge size and is of scientific interest due to its heterogeneity. Experience gained from the case study can be used for similar research in other regions.

Traditional discounting dramatically affects the outcome of catastrophic risk management and spatio-temporal vulnerability modeling. The misperception of discount rates produces inadequate evaluations of risk management strategies, which may provoke catastrophes and significantly contribute to the increasing vulnerability of our society. This paper analyses the implication of potential catastrophic events on the choice of discounting. In particular, it shows the necessity of using proposed equivalent undiscounted stopping time criterion and Monte Carlo based stochastic optimization procedures.

In this paper we show that explicit treatment of risks and uncertainties in agricultural production planning may considerably alter strategies for achieving robust outcomes with regard to sustainable agricultural developments. We discuss production planning models under uncertainties and risks that may assist in planning location-specific production expansion within environmental and health risk indicators and constraints. The proposed approaches are illustrated with the example of spatially explicit livestock production allocation in China to 2030.

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.