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Afforestation is considered a cost‐effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade‐offs with food security are often not considered. Here we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework. In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9 GtCO2/year at 200 US$/tCO2 in 2050 leading to large‐scale application in an SSP2 scenario aiming for 2°C (410 GtCO2 cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock‐in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub‐Saharan Africa. Afforestation also requires large amounts of land (up to 1,100 Mha) leading to large reductions in agricultural land. The increased competition for land could lead to higher food prices and an increased population at risk of hunger. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade‐offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade‐offs in order to achieve mitigation sustainably. [ABSTRACT FROM AUTHOR]

Climate change mitigation is crucial to limit detrimental impacts of climate change on food production. However, cost-optimal mitigation pathways consistent with the Paris agreement project large-scale land-based mitigation for bio-energy and afforestation to achieve stringent climate targets. Land demand from land-based mitigation leads to competition with food production, raising concerns that climate policy (SDG13 – climate action) conflicts with food security objectives (SDG2 – zero hunger). In this study we use the computable general equilibrium model MAGNET and the IMAGE integrated assessment model to quantify the food security effects of large-scale land-based mitigation. Subsequently, we implement two measures to prevent reduced food security: increased agricultural intensification and reduced meat consumption. We show that large-scale land-based mitigation (∼600 Mha in 2050) leads to increased food prices (11%), reduced food availability (230 kcal/cap/day) and substantially more people at risk of hunger (230 million) compared to the baseline scenario in 2050, most notably in developing regions. Land-based mitigation also leads to yield increases (9%) and intensified ruminant production (11%). Additional crop yield improvement (9%) and intensification in ruminant production (3%) could prevent the negative effect of mitigation on food security. Introducing a reduction in meat consumption in high- and middle-income regions reduces required crop yield improvement (7%) and ruminant intensification (2%). Our study highlights the importance of transparency about food security effects in climate change mitigation scenarios. In addition, it provides an example of explicitly including measures to limit negative trade-offs in mitigation scenarios. In this way, we show how the Paris agreement can be made consistent with food security objectives and how multiple Sustainable Development Goals can be achieved. • Large-scale land-based mitigation (~600 Mha) in pathways in line with the Paris agreement could conflict with food security. • Mitigation in 2050 might change food prices (+11%), food availability (-230 kcal/cap/day) and risk of hunger (+230 million). • Additional improvements in crop yields and livestock production could prevent negative effects on food security. • Lower meat consumption makes it easier to prevent negative effects of mitigation on food security. • Research should not only investigate cost-optimal solutions but multiple sustainable development goals (SDG2 and SDG13). [ABSTRACT FROM AUTHOR]

Protection of natural or semi-natural ecosystems is an important part of societal strategies for maintaining biodiversity, ecosystem services, and achieving overall sustainable development. The assessment of multiple emerging land use trade-offs is complicated by the fact that land use changes occur and have consequences at local, regional, and even global scale. Outcomes also depend on the underlying socio-economic trends. We apply a coupled, multi-scale modelling system to assess an increase in nature protection areas as a key policy option in the European Union (EU). The main goal of the analysis is to understand the interactions between policy-induced land use changes across different scales and sectors under two contrasting future socio-economic pathways. We demonstrate how complementary insights into land system change can be gained by coupling land use models for agriculture, forestry, and urban areas for Europe, in connection with other world regions. The simulated policy case of nature protection shows how the allocation of a certain share of total available land to newly protected areas, with specific management restrictions imposed, may have a range of impacts on different land-based sectors until the year 2040. Agricultural land in Europe is slightly reduced, which is partly compensated for by higher management intensity. As a consequence of higher costs, total calorie supply per capita is reduced within the EU. While wood harvest is projected to decrease, carbon sequestration rates increase in European forests. At the same time, imports of industrial roundwood from other world regions are expected to increase. Some of the aggregate effects of nature protection have very different implications at the local to regional scale in different parts of Europe. Due to nature protection measures, agricultural production is shifted from more productive land in Europe to on average less productive land in other parts of the world. This increases, at the global level, the allocation of land resources for agriculture, leading to a decrease in tropical forest areas, reduced carbon stocks, and higher greenhouse gas emissions outside of Europe. The integrated modelling framework provides a method to assess the land use effects of a single policy option while accounting for the trade-offs between locations, and between regional, European, and global scales. [ABSTRACT FROM AUTHOR]

Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. To advance our understanding of the sources of the differences, 10 global economic models that produce long-term scenarios were asked to compare a reference scenario with alternate socioeconomic, climate change, and bioenergy scenarios using a common set of key drivers. Several key conclusions emerge from this exercise: First, for a comparison of scenario results to be meaningful, a careful analysis of the interpretation of the relevant model variables is essential. For instance, the use of 'real world commodity prices' differs widely across models, and comparing the prices without accounting for their different meanings can lead to misleading results. Second, results suggest that, once some key assumptions are harmonized, the variability in general trends across models declines but remains important. For example, given the common assumptions of the reference scenario, models show average annual rates of changes of real global producer prices for agricultural products on average ranging between −0.4% and +0.7% between the 2005 base year and 2050. This compares to an average decline of real agricultural prices of 4% p.a. between the 1960s and the 2000s. Several other common trends are shown, for example, relating to key global growth areas for agricultural production and consumption. Third, differences in basic model parameters such as income and price elasticities, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. Fourth, the analysis shows that agro-economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross-fertilize analyses at different scales. [ABSTRACT FROM AUTHOR]

Understanding the capacity of agricultural systems to feed the world population under climate change requires projecting future food demand. This article reviews demand modeling approaches from 10 global economic models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP). We compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion. In the reference scenario (SSP2), food demand increases by 59-98% between 2005 and 2050, slightly higher than the most recent FAO projection of 54% from 2005/2007. The range of results is large, in particular for animal calories (between 61% and 144%), caused by differences in demand systems specifications, and in income and price elasticities. The results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios. When considering a world with higher population and lower economic growth (SSP3), consumption per capita drops on average by 9% for crops and 18% for livestock. The maximum effect of climate change on calorie availability is −6% at the global level, and the effect of biofuel production on calorie availability is even smaller. [ABSTRACT FROM AUTHOR]

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty. [ABSTRACT FROM AUTHOR]

Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land-use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive comparison of global agro-economic models that have harmonized drivers of population, GDP, and biophysical yields. The comparison allows us to ask two research questions: (1) How much cropland will be used under different socioeconomic and climate change scenarios? (2) How can differences in model results be explained? The comparison includes four partial and six general equilibrium models that differ in how they model land supply and amount of potentially available land. We analyze results of two different socioeconomic scenarios and three climate scenarios (one with constant climate). Most models (7 out of 10) project an increase of cropland of 10-25% by 2050 compared to 2005 (under constant climate), but one model projects a decrease. Pasture land expands in some models, which increase the treat on natural vegetation further. Across all models most of the cropland expansion takes place in South America and sub-Saharan Africa. In general, the strongest differences in model results are related to differences in the costs of land expansion, the endogenous productivity responses, and the assumptions about potential cropland. [ABSTRACT FROM AUTHOR]

This article compares the theoretical and functional specification of production in partial equilibrium (PE) and computable general equilibrium (CGE) models of the global agricultural and food system included in the AgMIP model comparison study. The two model families differ in their scope-partial versus economy-wide-and in how they represent technology and the behavior of supply and demand in markets. The CGE models are 'deep' structural models in that they explicitly solve the maximization problem of consumers and producers, assuming utility maximization and profit maximization with production/cost functions that include all factor inputs. The PE models divide into two groups on the supply side: (1) 'shallow' structural models, which essentially specify area/yield supply functions with no explicit maximization behavior, and (2) 'deep' structural models that provide a detailed activity-analysis specification of technology and explicit optimizing behavior by producers. While the models vary in their specifications of technology, both within and between the PE and CGE families, we consider two stylized theoretical models to compare the behavior of crop yields and supply functions in CGE models with their behavior in shallow structural PE models. We find that the theoretical responsiveness of supply to changes in prices can be similar, depending on parameter choices that define the behavior of implicit supply functions over the domain of applicability defined by the common scenarios used in the AgMIP comparisons. In practice, however, the applied models are more complex and differ in their empirical sensitivity to variations in specification-comparability of results given parameter choices is an empirical question. To illustrate the issues, sensitivity analysis is done with one global CGE model, MAGNET, to indicate how the results vary with different specification of technical change, and how they compare with the results from PE models. [ABSTRACT FROM AUTHOR]

Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Intercomparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, for example, from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an ambitious mitigation scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in a high-emission scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise. [ABSTRACT FROM AUTHOR]

This article analyses the impact of the EU Biofuels Directive (BFD) on the EU agri-food supply chain using a computable general equilibrium model of the world economy, LEITAP. LEITAP is an extended version of the Global Trade Analysis Project (GTAP) model including improved land market modeling, substitution possibilities between capital and energy, different energy sources including biofuels, feed byproducts of biofuel production and the substitution between different feed components and feed byproducts. The simulation results show that the implementation of the EU BFD has a pronounced impact on the markets of cereals, oilseeds and sugar and shows only with a limited impact on production and consumption of other agri-food commodities not directly affected by biofuel production. As a direct effect of the BFD the harvested area and production of biofuel crops (grains, oilseeds) is expected to increase by 17% and 25%, respectively, and sugar production by 12%. EU imports of these commodities are expected to more than double. The increasing demand for biofuel crops and sugar will raise domestic prices of these commodities by 25% and 19%, respectively, but overall agri-food price inflation will be limited to 3% in the EU and to less than 1% at world market level. [ABSTRACT FROM AUTHOR]

Global economic models have been increasingly used to project food and agricultural developments for long term-time horizons, but food security aspects have often been limited to food availability projections. In this paper, we propose a broader framework to explore the future of food and nutrition security with a focus on food availability, food access, and a reasonable proxy for food utilisation. This framework is applied to a new set of stakeholder-designed scenarios of alternative future worlds that were developed for the FOODSECURE project and are structured around the two dimensions of inequality and sustainability. The framework is tested with two global models, MAGNET-IMAGE and GLOBIOM, and illustrated through an assessment of the possible trade-offs between food and nutrition security and sustainability in each of the worlds. Our results indicate that more equal worlds improve food security over a wider range of food security indicators and neglecting the sustainability dimension might revert food security gains over time. This paper concludes that there is a need for model-based scenario analysis to assess the complex and multi-dimensional characteristics of global food security. • Inequality and sustainability are two key dimensions of the FOODSECURE scenarios. • Model-based scenario analysis to assess the complex and multi-dimensional characteristics of food security is needed. • More equal worlds improve food security over a wider range of food security indicators. • Neglecting the sustainability dimension might revert food security gains over time. • Inequality dimension is under researched in long term food security scenarios. [ABSTRACT FROM AUTHOR]

Improved skills and rural-urban location of labor are generally implicit or ignored in food security projections. We analyze alternative labor supply assumptions for four contrasting scenarios. Changing skill levels and urbanization reverses a decrease in food prices and improves instead of worsens within country income inequality. It however slows the decrease in number of people with less than 2500 calories a day available, and increases the environmental impact of agriculture. With urbanization, observed net income benefits of higher food prices for the poor may no longer hold in the future. Explicitly addressing demographic change is thus key in projections guiding policymakers to address the unequal impacts of food security, combat climate change and promote sustainable food production. • Labor market and urbanization dynamics are key and neglected food security drivers. • Food prices reverse to an increase when accounting for plausible labor skill changes. • Accessibility of staple food for the poor improves due to positive income effects. • Less unskilled labor increases land use, affecting GHGs emission and biodiversity. • Tackling food security needs researchers and policymakers to look beyond agriculture. [ABSTRACT FROM AUTHOR]