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The idea that human impacts on natural systems might trigger large‐scale, social–ecological 'crises' or 'breakdowns' is attracting increasing scientific, societal and political attention, but the risks of such crises remain hard to assess or ameliorate. Social–ecological systems have complex dynamics, with bifurcations, nonlinearities and tipping points all emerging from the interaction of multiple human and natural processes. Computational modelling is a key tool in understanding these processes and their effects on system resilience. However, models that operate over large geographical extents often rely on assumptions such as economic equilibrium and optimisation in social–economic systems, and mean‐field or trend‐based behaviour in ecological systems, which limit the simulation of crisis dynamics. Alternative forms of modelling focus on simulating local‐scale processes that underpin the dynamics of social–ecological systems. Recent improvements in data resources and computational tools mean that such modelling is now technically feasible across large geographical extents. We consider the contributions that the different types of model can make to simulating social–ecological crises. While no models are able to predict exact outcomes in complex social–ecological systems, we suggest that one new approach with substantial promise is hybrid modelling that uses existing model architectures to isolate and understand key processes, revealing risks and associated uncertainties of crises emerging. We outline convergent and efficient functional descriptions of social and ecological systems that can be used to develop such models, data resources that can support them, and possible 'high‐level' processes that they can ...

Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European integrated land use models that utilise the same climatic and socio-economic scenarios but which adopt fundamentally different modelling paradigms. One of these is a constrained optimising economic-equilibrium model, and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatially aggregate and disaggregate land use changes and ecosystem service supply levels in food, forest and associated environmental systems. We find that the models produce very different results in some scenarios, with simulated food production varying by up to half of total demand and the extent of intensive agriculture varying by up to 25 % of the EU land area. The agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of land abandonment in large parts of Europe. We relate the principal differences observed to underlying model assumptions and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios in which economic and other scenario conditions prevent the changes in prices and responses required to approach economic equilibrium. In these circumstances, agent-based modelling allows explicit consideration of behavioural processes, but in doing so it provides a highly flexible account of land system development that is harder to link to underlying assumptions. We suggest that structured comparisons of parallel and transparent but paradigmatically distinct models are an important method for better understanding the potential scope and uncertainties of future land use change, particularly given the substantive differences that currently exist in the outcomes of such models.

Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European integrated land use models that utilise the same climatic and socio-economic scenarios but which adopt fundamentally different modelling paradigms. One of these is a constrained optimising economic-equilibrium model, and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatially aggregate and disaggregate land use changes and ecosystem service supply levels in food, forest and associated environmental systems. We find that the models produce very different results in some scenarios, with simulated food production varying by up to half of total demand and the extent of intensive agriculture varying by up to 25 % of the EU land area. The agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of land abandonment in large parts of Europe. We relate the principal differences observed to underlying model assumptions and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios in which economic and other scenario conditions prevent the changes in prices and responses required to approach economic equilibrium. In these circumstances, agent-based modelling allows ...

Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European integrated land use models that utilise the same climatic and socio-economic scenarios but which adopt fundamentally different modelling paradigms. One of these is a constrained optimising economic-equilibrium model, and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatially aggregate and disaggregate land use changes and ecosystem service supply levels in food, forest and associated environmental systems. We find that the models produce very different results in some scenarios, with simulated food production varying by up to half of total demand and the extent of intensive agriculture varying by up to 25 % of the EU land area. The agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of land abandonment in large parts of Europe. We relate the principal differences observed to underlying model assumptions and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios in which economic and other scenario conditions prevent the changes in prices and responses required to approach economic equilibrium. In these circumstances, agent-based modelling allows explicit consideration of behavioural processes, but in doing so it provides a highly flexible account of land system development that is harder to link to underlying assumptions. We suggest that structured comparisons of parallel and transparent but paradigmatically distinct models are an important method for better understanding the potential scope and uncertainties of future land use change, particularly given the substantive differences that currently exist in the outcomes of such models.

Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European land use models that are based on the same integrated modelling framework and utilise the same climatic and socio-economic scenarios, but which adopt fundamentally different model paradigms. One of these is a constrained optimising economic-equilibrium model and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatial and aggregate land use change and ecosystem service supply. We find that the agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of active management in large, contiguous parts of Europe. We relate the principal differences observed to underlying model assumptions, and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios where economic and other scenario conditions prevent the normal functioning of price signals and responses. In these circumstances, agent-based modelling allows explicit consideration of behavioural processes, but in doing so provides a highly flexible account of land system development that is harder to link to underlying assumptions. We suggest that structured comparisons of parallel, transparent but paradigmatically distinct models are an important method for better understanding the potential scope and uncertainties of future land use change.

Human land use has placed enormous pressure on natural resources and ecosystems worldwide and may even prompt socio-ecological collapses under some circumstances. Efforts to avoid such collapses are hampered by a lack of knowledge about when they may occur and how they may be prevented. Computational models that illuminate potential future developments in the land system are invaluable tools in this context. While such models are widely used to project biophysical changes, they are currently less able to explore the social dynamics that will be key aspects of future global change. As a result, strategies for navigating a hazardous future may suffer from "blind spots" at which individual, social and political behaviours divert the land system away from predicted pathways. We apply CRAFTY-EU, an agent-based model of the European land system, in order to investigate the effects of human behavioural aspects of land management at the continental scale. We explore a range of potential futures using climatic and socio-economic scenarios and present a coherent set of cross-sectoral projections without imposed equilibria or optimisation. These projections include various behavioural responses to scenarios including non-economic motivations, aversion to change and heterogeneity in decision-making. We find that social factors and behavioural responses have dramatic impacts on simulated dynamics and can contribute to a breakdown of the land system's essential functions in which shortfalls in food production of up to 56 % emerge. These impacts are largely distinct from, and at least as large as, those of projected climatic change. We conclude that the socio-economic aspects of future scenarios require far more detailed and varied treatment. In particular, deviation from simple economic rationality at individual and aggregate scales may profoundly alter the nature of land system development and the achievability of policy ...

Impacts of socio-economic, political and climatic change on agricultural land systems are inherently uncertain. The role of regional and local-level actors is critical in developing effective policy responses that accommodate such uncertainty in a flexible and informed way across governance levels. This study identified potential regional challenges in arable land use systems, which may arise from climate and socio-economic change for two counties in western Hungary: Veszprém and Tolna. An empirically-grounded, agent-based model was developed from an extensive farmer household survey about local land use practices. The model was used to project future patterns of arable land use under four localised, stakeholder-driven scenarios of plausible future socio-economic and climate change. The results show strong differences in farmers' behaviour and current agricultural land use patterns between the two regions, highlighting the need to implement focused policy at the regional level. For instance, policy that encourages local food security may need to support improvements in the capacity of farmers to adapt to physical constraints in Veszprém and farmer access to social capital and environmental awareness in Tolna. It is further suggested that the two regions will experience different challenges to adaptation under possible future conditions (up to 2100). For example, Veszprém was projected to have increased fallow land under a scenario with high inequality, ineffective institutions and higher-end climate change, implying risks of land abandonment. By contrast, Tolna was projected to have a considerable decline in major cereals under a scenario assuming a de-globalising future with moderate climate change, inferring challenges to local food self-sufficiency. The study provides insight into how socio-economic and physical factors influence the selection of crop rotation plans by farmers in western Hungary and how farmer behaviour may affect future risks to agricultural land systems under environmental change.

Impacts of socio-economic, political and climatic change on agricultural land systems are inherently uncertain. The role of regional and local level actors is critical in developing effective policy responses that accommodate such uncertainty in a flexible and informed way across governance levels. This study identified potential regional challenges in arable land use systems, which may arise from climate and socio-economic change for two counties in western Hungary: Veszprém and Tolna. An empirically-grounded, agent-based model was developed from an extensive farmer household survey about local land use practices. The model was used to project future patterns of arable land use under four localised, stakeholder-driven scenarios of plausible future socio-economic and climate change. The results show strong differences in farmers' behaviour and current agricultural land use patterns between the two regions, highlighting the need to implement focused policy at the regional level. For instance, policy that encourages local food security may need to support improvements in the capacity of farmers to adapt to physical constraints in Veszprém and farmer access to social capital and environmental awareness in Tolna. It is further suggested that the two regions will experience different challenges to adaptation under possible future conditions (up to 2100). For example, Veszprém was projected to have increased fallow land under a scenario with high inequality, ineffective institutions and higher-end climate change, implying risks of land abandonment. By contrast, Tolna was projected to have a considerable decline in major cereals under a scenario assuming a de-globalising future with moderate climate change, inferring challenges to local food self-sufficiency. The study provides insight into how socio-economic and physical factors influence the selection of crop rotation plans by farmers in western Hungary and how farmer behaviour may affect future risks to agricultural land systems under environmental ...

We quantify the impact of land use change, determined by our growing need for food and biofuel production, on isoprene emissions and subsequent atmospheric oxidant chemistry in 2015 and 2030, relative to 1990, ignoring compound climate change effects over that period. We estimate isoprene emissions from an ensemble n=1000 of land use change realizations from 1990--2050, broadly guided by the IPCC AR4/SRES scenarios A1 and B1. We also superimpose land use change required to address projected biofuel usage using two scenarios: (1) assuming that world governments make no changes to biofuel policy after 2009, and (2) assuming that world governments develop biofuel policy with the aim of keeping equivalent atmospheric CO2 at 450 ppm. We present the median and interquartile range (IQR) statistics of the ensemble and show that land use change between -1.50 x 10 12 m2 to +6.06 x 10 12 m2 was found to drive changes in the global isoprene burden of -3.5 to +2.8 Tg yr-1 in 2015 and -7.7 to +6.4 Tg yr-1 in 2030. We use land use change realizations corresponding to the median and IQR of these emission estimates to drive the GEOS-Chem global 3-D chemistry transport model to investigate the perturbation to global and regional surface concentrations of isoprene, nitrogen oxides (NO+NO2), and the atmospheric concentration and deposition of ozone (O3). We show that across sub-continental regions the monthly surface O3 increases by 0.1--0.8 ppb, relative to a zero land-use change calculation, driven by increases (decreases) in surface isoprene in high (low) NOx environments. At the local scale (4 x 5) we find that surface O3 increases by 5-12 ppb over temperate North America, China and Boreal Eurasia, driven by large increases in isoprene emissions from short-rotation coppice crop cultivation for biofuel production.