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Higher food prices arising from restrictions on exports from Russia or Ukraine have been exacerbated by energy price rises, leading to higher costs for agricultural inputs such as fertiliser. Using a scenario approach with a global land use and food system model (LandSyMM), we quantify the potential outcomes of increasing agricultural input costs and the curtailment of exports from Russia and Ukraine on human health and the environment. We show that, combined, agricultural inputs costs and food export restrictions could increase food costs by 60-100% from 2021 levels, potentially leading to undernourishment of 60-110 million people and annual additional deaths of 400 thousand to 1 million people if the associated dietary patterns are maintained. In additional to lower yields, reduced land use intensification arising from higher input costs would lead to agricultural land expansion of 130-349 Mha by 2030, with associated carbon and biodiversity loss. The impact of agricultural input costs on food prices is larger than that from curtailment of Russian and Ukrainian exports. Restoring food trade from Ukraine and Russia alone is therefore insufficient to avoid food insecurity problem from higher energy and fertiliser prices. While the Black Sea Grain Initiative has been a welcome development and has largely allowed Ukraine food exports to be re-established, the immediacy of these issues appears to have diverted attention away from the impacts of fertiliser prices. While fertiliser prices at the start of 2023 have come down from the peaks of mid-2022, they remain at historically high levels. Our results suggest the costs and lower crop yields achieved through reduced fertiliser use will drive high food price inflation in 2023 and beyond. More needs to be done to break the link between higher food prices and harm to human health and the environment. This study demonstrates how modelling can be used to explore the complexity and interlinked nature of the globalised food system and to quantifying the trade-offs and synergies for health and environmental outcomes of difference scenarios.

Land degradation continues to be an enormous challenge to human societies, reducing food security, emitting greenhouse gases and aerosols, driving the loss of biodiversity, polluting water, and undermining a wide range of ecosystem services beyond food supply and water and climate regulation. Climate change will exacerbate several degradation processes. Investment in diverse restoration efforts, including sustainable agricultural and forest land management, as well as land set aside for conservation wherever possible, will generate co-benefits for climate change mitigation and adaptation and morebroadly for human and societal well-being and the economy. This review highlights the magnitude of the degradation problem and some of the key challenges for ecological restoration. There are biophysical as well as societal limits to restoration. Better integrating policies to jointly address poverty, land degradation, and greenhouse gas emissions and removals is fundamental to reducing many existing barriers and contributing to climate-resilient sustainable development.

Global food prices are rising rapidly in response to a dramatic increase in global energy prices and the Ukraine-Russia war, causing severe impacts on the world’s poorest people. The FAO Food Price Index increased by 23% from May 2021 to May 2022 and the Cereals Price Index increased by 30%. Sanctions or blockades that restrict exports from Russia or Ukraine – two of the world’s most important food-exporting countries – are exacerbated by energy price rises which further increase food prices through higher costs for agricultural inputs, such as fertiliser. We consider the role of increasing agricultural input costs and the curtailment of exports from Russia and Ukraine to quantify the potential outcomes on human health and the environment. We show that the combination of agricultural inputs costs and food export restrictions could increase food costs by 60-100% in 2023 from 2021 levels, leading to the deaths of 400 thousand to 1 million additional people in 2023 and undernourishment of 60-110 million people. Furthermore, a reduction in land use intensification, arising from higher input costs, leads to agricultural land expansion, especially in the tropics, with potential consequences for deforestation and carbon and biodiversity loss. We find that the impact of agricultural input costs on food prices is larger than the effect of the curtailment of exports from Russia and Ukraine. Restoring food trade from Ukraine and Russia alone would be insufficient to substantially reduce the magnitude of the current food insecurity problem. We contend that the immediacy of the food export problems associated with the Ukraine-Russia war has diverted attention away from the principal causes of current global food insecurity, which may hinder the quest to find solutions.

Background The COVID-19 pandemic arrived at a time of faltering global poverty reduction and increasing levels of diet-related diseases, both of which have a strong link to poor outcomes for those with COVID-19. Governments responded to the pandemic by placing unprecedented restrictions on internal and external movements, which have resulted in an economic contraction. In response to the economic shock, G20 governments have committed to providing US$14 trillion stimuli to support economic recovery. We aimed to assess the impact of different COVID-19 recovery paths on human health, environmental sustainability, and food sustainability. Methods We used LandSyMM, a global gridded land use change model, to analyse the impact of recovery paths from COVID-19. The paths were illustrated by four scenarios that represent different pandemic severities (including a single or recurrent pandemic) and alternate modes of recovery, including a transition of food demand towards healthier diets that result in changes to the food system: (1) solidarity and celery, (2) nothing new, (3) fries and fragmentation, and (4) best laid plans. For each scenario, we modelled the economic shocks of the pandemic and the impact of policy measures to promote healthier diets in the years after the COVID-19 pandemic, including the supply of and demand for food, environmental outcomes, and human health outcomes. The four scenarios use established future population growth and economic development projections derived from the Shared Socioeconomic Pathways 2. We quantified the outcomes from more societally cooperative pandemic responses that result in reduced trade barriers and improved technological development against less cooperative responses. Findings Repeated pandemic shocks (the fries and fragmentation and best laid plans scenarios) reduce the ability of the lowest income countries to ensure food security. A post-pandemic recovery that includes dietary transition towards the consumption of less meat and more fruits and vegetables (the solidarity and celery scenario) could prevent 2583 premature deaths per million in 2060, whereas recovery paths that are focused on economic recovery (the fries and fragmentation scenario) could trigger an additional 778 deaths per million in 2060. The transition of dietary preferences towards healthier diets (the solidarity and celery scenario) also reduces nitrogen fertiliser use by 40 million tonnes and irrigation water by 400 km3 compared with no dietary change in 2060 (the nothing new scenario). Finally, the scenario with dietary transition increases the affordability of the average diet. Interpretation The economic impact of the COVID-19 pandemic is most visible in low-income countries, where a reduction in growth projections makes a greater difference to the affordability of a basic diet. A change in dietary preferences is most impactful in reducing mortality and the burden of disease when income levels are high. At lower income, a transition towards lower meat consumption reduces undernourishment and diet-related mortality. Funding The Global Food Security's Resilience of the UK Food System Programme project, with support from the Biotechnology and Biological Sciences Research Council, Economic and Social Research Council, Natural Environment Research Council, and the Scottish Government.

Land use/cover change is central to understanding the global sustainability challenges of climate change, biodiversity loss, and food security. Yet, while the magnitude of global land use has often been studied, little is known about land use transitions and their drivers, and how these vary across the world. A major obstacle has been the lack of consistent long-term data with sufficiently high resolution.Here we analyse the drivers of major global land use transitions based on a novel high-resolution land use reconstruction, HILDA+ (Historic Land Dynamics Assessment+). We (1) identify key land use transitions and their spatiotemporal patterns and (2) correlate national time series of annual land use transitions with a range of influencing variables that represent indirect drivers (demography, politics and economics) and direct drivers (production and environment) across the globe.We identify 12 major land use transitions and find that agricultural expansion accounted for the largest share of global land use change (~7.6 million km2), an area as large as Greece every year between 1960 and 2019. A major portion of this land is made up of pasture/rangeland expansion, mainly used for nomadic pastoralism. Areas of cropland expansion are mainly located in the Global South, particularly in South America (Argentina, Brazil), Africa (Ethiopia, Nigeria, Uganda), India and Thailand. Here we notice a shift of agricultural expansion from South America to Africa since the late 1980s. Globally, forest loss (~3.6 million km2), including deforestation for pasture/rangelands or cropland and forest degradation to shrub/grassland, outweighed forest expansion (~2.6 million km2) during 1960-2019. Whereas forestry, crop-pasture dynamics and cropland abandonment dominated in the Global North, deforestation, forest degradation and agricultural expansion are major transitions of the Global South.Our driver analysis reveals that economic factors are the largest indirect drivers of global land use transitions in terms of area (~6.7 million km2). Of these, Gross Domestic Production (GDP) is the strongest driver in the Global North, mainly for forest expansion, forestry and urban growth. In contrast, wage and cereal price lead the list in the South, mostly related to agricultural expansion. Indirect-direct driver combinations of economy with production (~4.7 million km2), politics with production (~3.2 million km2) and demography with production (~2.3 million km2) affected the largest areas. We find that environmental indicators have a greater influence on land use change in the South, related to deforestation or desertification, than in the North, linked to crop-pasture dynamics. Indirect drivers show higher correlations than direct drivers, which underlines the importance of social systems on the extent and speed of land use change.Giving new data-driven and quantitative insights into a largely untouched field, we reveal the importance of indirect drivers from economy, politics and demography for land use transitions across the globe. Learning from the recent past, understanding how socio-economic and environmental factors affect the way humans use the land surface is essential for estimating impacts of land use change and implementing measures of climate mitigation and sustainable land use policies. With our findings, we can make a contribution to this.

Yearly, per-area carbon sequestration rates are used to estimate mitigation potentials by comparing types and areas of land management in 1990 and 2000 and projected to 2010, for the European Union (EU)-15 and for four country-level case studies for which data are available: UK, Sweden, Belgium and Finland. Because cropland area is decreasing in these countries (except for Belgium), and in most European countries there are no incentives in place to encourage soil carbon sequestration, carbon sequestration between 1990 and 2000 was small or negative in the EU-15 and all case study countries. Belgium has a slightly higher estimate for carbon sequestration than the other countries examined. This is at odds with previous reports of decreasing soil organic carbon stocks in Flanders. For all countries except Belgium, carbon sequestration is predicted to be negligible or negative by 2010, based on extrapolated trends, and is small even in Belgium. The only trend in agriculture that may be enhancing carbon stocks on croplands at present is organic farming, and the magnitude of this effect is highly uncertain. Previous studies have focused on the potential for carbon sequestration and have shown quite significant potential. This study, which examines the sequestration likely to occur by 2010, suggests that the potential will not be realized. Without incentives for carbon sequestration in the future, cropland carbon sequestration under Article 3.4 of the Kyoto Protocol will not be an option in EU-15.

Climate change, growing populations and economic shocks are adding pressure on the global agricultural system’s ability to feed the world. In addition to curbing the emissions from fossil fuel use, land-based actions are seen as essential in the effort to mitigate climate change, but these tend to reduce areas available for food production, thereby further increasing this pressure. The actors of the food system have the capacity to respond and adapt to changes in climate, and thereby reduce the negative consequences, while potentially creating additional challenges, including further greenhouse gas emissions. The food system actors may respond autonomously based on economic drivers and other factors to adapt to climate change, whereas policy measures are usually needed for mitigation actions to be implemented. Much research and policy focus has been given to land-based climate change mitigation, but far less emphasis has to date been given to the understanding of adaptation, or the interaction between adaptation and mitigation in the land use and food system. Here, we present an approach to better understand and plan these interactions through modelling. Climate change adaptation and mitigation strategies and the impacts on the global food system and socio-economic development can be simulated over long-term predictions, thanks to the new combination of multiple models into the Land System Modular Model (LandSyMM). LandSyMM takes into account the impacts in changes in climate (i.e. temperature, precipitation, atmospheric greenhouse gas concentrations) and land management on crop yields with its implications for land allocation, food security and trade. This new coupled model integrates, over fine spatial scale, the interactions between commodities consumption, land use management, vegetation and climate into a worldwide dynamic economic system. This study offers an outline description of the LandSyMM as well as the perspectives of uses for climate adaptation assessment.

Projecting the distribution of population is critical in supporting analysis of the impacts and risks associated with climate change. In this paper, we apply a computational algorithm parameterised for the UK Shared Socioeconomic Pathway (UK-SSP) narratives to create 1-km gridded urban land use and population projections for the UK to the end of the twenty-first century. Using a unimodal neighbourhood function, we model heterogeneity in urban sprawl patterns. The urban land use maps are used as weights to create downscaled population projections. We undertake a model uncertainty analysis using 500 simulations with varying parameter settings per UK-SSP. Results illustrate how sprawl can emerge from scenario conditions even when population numbers decline, and irrespective of socio-economic wellbeing. To avoid negative environmental externalities associated with uncontrolled sprawl, such as in UK-SSP5 and UK-SSP3, planning policies will be vital. Uncertainties about future population development in the UK are higher in rural areas than in urban areas. This has an effect on the competition for land and influences confidence in projections of broader land system change.

Trichostatin A (TSA) has been shown to prevent fibrosis in vitro and in vivo. The present study aimed at investigating the role of reactive oxygen species (ROS) scavenging by TSA on transforming growth factor-β (TGF-β)-induced myofibroblast differentiation of corneal fibroblasts in vitro. Human immortalized corneal fibroblasts were treated with TGF-β in the presence of TSA, the NAD(P)H oxidase inhibitor diphenyleneiodonium (DPI), the antioxidant N-acetyl-cysteine (NAC), the NF-E2–related factor 2-antioxidant response element (Nrf2-ARE) activator sulforaphane, or small interfering RNA. Myofibroblast differentiation was assessed by α-smooth muscle actin (α-SMA) expression, F-actin bundle formation, and collagen gel contraction. ROS, H2O2, intracellular glutathione (GSH) level, cellular total antioxidant capacity, and the activation of Nrf2-ARE signaling were determined with various assays. Treatment with TSA and the Nrf2-ARE activator resulted in increased inhibition of the TGF-β–induced myofibroblast differentiation as compared with treatment with DPI or NAC. Furthermore, TSA also decreased cellular ROS and H2O2 accumulation induced by TGF-β, whereas it elevated intracellular GSH level and cellular total antioxidant capacity. In addition, TSA induced Nrf2 nuclear translocation and up-regulated the expression of Nrf2-ARE downstream antioxidant genes, whereas Nrf2 knockdown by RNA interference blocked the inhibition of TSA on myofibroblast differentiation. In conclusion, this study provides the first evidence implicating that TSA inhibits TGF-β–induced ROS accumulation and myofibroblast differentiation via enhanced Nrf2-ARE signaling.

Communication is a popular method to raise awareness and promote action against the impacts of climate change. However, there is little scientific evidence that climate change communication can inf...

Achieving the Paris Agreement’s aim of limiting average global temperature increases to 1.5 °C requires substantial changes in the land system. However, individual countries’ plans to accomplish these changes remain vague, almost certainly insufficient and unlikely to be implemented in full. These shortcomings are partially the result of avoidable ‘blind spots’ relating to time lags inherent in the implementation of land-based mitigation strategies. Key blind spots include inconsistencies between different land-system policies, spatial and temporal lags in land-system change, and detrimental consequences of some mitigation options. We suggest that improved recognition of these processes is necessary to identify achievable mitigation actions, avoiding excessively optimistic assumptions and consequent policy failures. The Paris Agreement requires substantial changes in the land system. However, national implementation plans are vague, largely insufficient and unlikely to be fully achieved. Realistic policies require proper consideration of land-system lags.

Global biodiversity is rapidly declining and goals to halt biodiversity loss, such as the Aichi Biodiversity Targets, have not been achieved. To avoid further biodiversity loss and aid recovery some have argued for the protection of 50% or 30% of the Earth’s terrestrial land surface. We use a state of the art global land use model, LandSyMM, to assess global and regional human health and food security outcomes when potential area based strategies for conserving biodiversity are modelled. We find diet and weight changes in strictly enforced 30% and 50% land protection scenarios, cause an additional 5.1 million deaths in 2060. At a regional level, South Asia and Sub-Saharan Africa experience high levels of underweight-related mortality, causing an additional 200,000 deaths in these regions alone. Developed regions in contrast are less affected by protection measures. Our results highlight that radical measures to protect areas of biodiversity value may jeopardise food security and human health in the most vulnerable regions of the world.

Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of bioenergy, often used in conjunction with carbon capture and storage. We review the literature on bioenergy use for climate change mitigation, including studies that use top‐down integrated assessment models or bottom‐up modelling, and studies that do not rely on modelling. We summarize the state of knowledge concerning potential co‐benefits and adverse side effects of bioenergy systems and discuss limitations of modelling studies used to analyse consequences of bioenergy expansion. The implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and how bioenergy alters energy systems and land use. Depending on previous land use, widespread deployment of monoculture plantations may contribute to mitigation but can cause negative impacts across a range of other sustainability criteria. Strategic integration of new biomass supply systems into existing agriculture and forest landscapes may result in less mitigation but can contribute positively to other sustainability objectives. There is considerable variation in evaluations of how sustainability challenges evolve as the scale of bioenergy deployment increases, due to limitations of existing models, and uncertainty over the future context with respect to the many variables that influence alternative uses of biomass and land. Integrative policies, coordinated institutions and improved governance mechanisms to enhance co‐benefits and minimize adverse side effects can reduce the risks of large‐scale deployment of bioenergy. Further, conservation and efficiency measures for energy, land and biomass can support greater flexibility in achieving climate change mitigation and adaptation.

Land use change is a major contributor to greenhouse gas emissions and biodiversity loss and, hence, a key topic for current sustainability debates and climate change mitigation. To understand its impacts, accurate data of global land use change and an assessment of its extent, dynamics, causes and interrelations are crucial. However, although numerous observational data is publicly available (e.g. from remote sensing), the processes and drivers of land use change are not yet fully understood. In particular, current global-scale land change assessments still lack either temporal consistency, spatial explicitness or thematic detail. Here, we analyse the patterns of global land use change and its underlying drivers based on our novel high-resolution (~1x1 km) dataset of global land use/cover (LULC) change from 1960-2019, HILDA+ (Historic Land Dynamics Assessment+). The data harmonises multiple Earth Observation products and FAO land use statistics. It covers all transitions between six major LULC categories (urban areas, cropland, pasture/rangeland, forest, unmanaged grass-/shrubland and no/sparse vegetation).On this basis, we show (1) a classification of global LULC transitions into major processes of land use change, (2) a quantification of their spatiotemporal patterns and (3) an identification of their major socioeconomic and environmental drivers across the globe. By using temporal cross-correlation, we study the influence of selected drivers on processes such as agricultural land abandonment, deforestation, forest degradation or urbanisation.With this, we are able to map the patterns and drivers of global land use change at unprecedented resolution and compare them for different world regions. Giving new data-driven and quantitative insights into a largely untouched field, we identify tele-coupled globalisation patterns and climate change as important influencing factors for land use dynamics. Learning from the recent past, understanding how socio-economic and environmental factors affect the way humans use the land surface is essential for estimating future impacts of land use change and implementing measures of climate mitigation and sustainable land use policies.

There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.

Global pet ownership, especially of cats and dogs, is rising with income growth, and so too are the environmental impacts associated with their food. The global extent of these impacts has not been quantified, and existing national assessments are potentially biased due to the way in which they account for the relative impacts of constituent animal by-products (ABPs). ABPs typically have lower value than other animal products (i.e. meat, milk and eggs), but are nevertheless associated with non-negligible environmental impacts. Here we present the first global environmental impact assessment of pet food. The approach is novel in applying an economic value allocation approach to the impact of ABPs and other animal products to represent better the environmental burden. We find annual global dry pet food production is associated with 56–151 Mt CO2 equivalent emissions (1.1%−2.9% of global agricultural emissions), 41–58 Mha agricultural land-use (0.8–1.2% of global agricultural land use) and 5–11 km3 freshwater use (0.2–0.4% of water extraction of agriculture). These impacts are equivalent to an environmental footprint of around twicethe UK land area, and would make greenhouse gas emission from pet food around the 60th highest emitting country, or equivalent to total emissions from countries such as Mozambique or the Philippines. These results indicate that rising pet food demand should be included in the broader global debate about food system sustainability.

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.

Highlights • Stakeholders can valuably facilitate the exploration of future shocks and impacts • Connectivity in food systems can increase volatility and vulnerability to shocks • Loss of food system diversity exposed as another potential source of weakness • Social media is increasingly important in shaping attitudes/ behaviours towards food • Increasing automation within food systems may create new sources of shock, Globalised food supply chains are increasingly susceptible to systemic risks, with natural, social and economic shocks in one region potentially leading to price spikes and supply changes experienced at the global scale. When projections extrapolate from recent histories and adopt a ‘business as usual’ approach they risk failing to take account of shocks or unpredictable events that can have dramatic consequences for the status quo as seen with the global Covid-19 pandemic. This study used an explorative stakeholder process and shock centred narratives to discuss the potential impact of a diversity of shocks, examining system characteristics and trends that may amplify their impact. Through the development of scenarios, stakeholders revealed concerns about the stability of the food system and the social, economic and environmental consequence of food related shocks. Increasing connectivity served as a mechanism to heighten volatility and vulnerability within all scenarios, with reliance on singular crops and technologies (i.e. low diversity) throughout systems highlighted as another potential source of vulnerability. The growing role of social media in shaping attitudes and behaviours towards food, and the increasing role of automation emerged as contemporary areas of concern, which have thus far been little explored within the literature.

People have increasingly been shaping the surface of our planet. Land use/cover change – the most visible human footprint on Earth – is one of the main contributors to greenhouse gas emissions and biodiversity loss and, hence, is a key topic for current sustainability debates and climate change mitigation. To understand these land surface dynamics and its impacts, accurate reconstructions of global land use/cover change are necessary. Although more and more observational data sets are publicly available (e.g. from remote sensing), current land change assessments are still incomplete and either lack temporal consistency, spatial explicitness or thematic detail. Here, we show a consistent reconstruction of global land use/cover change from 1960-2015, using an open data-driven approach that combines national land use statistics with earth observation data of multiple sources and scales. Our land change reconstruction model HILDA+ (Historic Land Dynamics Assessment) accounts for data-derived gross changes within six main land use/cover classes at 1 km spatial resolution: Urban areas, cropland, pastures and rangeland, forest, (semi-)natural grass- or shrubland, other land. As a result, we present yearly land use/cover maps at 1 km spatial resolution, magnitudes and hot spot areas of change. Globally, around 20 % of the land surface – almost three times the size of Brazil - has undergone change within the last 55 years. Further, gross change is about seven times as high as yearly net change extent for forest, cropland and pasture dynamics. We prove that land change studies accounting for net change only can lead to severe underestimations of change extent and frequency. With this purely data-driven approach, we address current research needs of the earth system modelling community by providing new layers of land use/cover change with unprecedented level of detail. Learning from the recent past, understanding how management and land cover dynamics interactively affect the climate is essential for implementing measures of mitigation and sustainable land use policies. In this context, a solid information base can support informed decision-making.

Importing millions of tonnes of crops and meat each year undercuts farming standards in the European Union and destroys tropical forests. Importing millions of tonnes of crops and meat each year undercuts farming standards in the European Union and destroys tropical forests.

There is a clear need for transformative change in the land management and food production sectors to address the global land challenges of climate change mitigation, climate change adaptation, combatting land degradation and desertification, and delivering food security (referred to hereafter as “land challenges”). We assess the potential for 40 practices to address these land challenges and find that: Nine options deliver medium to large benefits for all four land challenges. A further two options have no global estimates for adaptation, but have medium to large benefits for all other land challenges. Five options have large mitigation potential (>3 Gt CO2eq/year) without adverse impacts on the other land challenges. Five options have moderate mitigation potential, with no adverse impacts on the other land challenges. Sixteen practices have large adaptation potential (>25 million people benefit), without adverse side effects on other land challenges. Most practices can be applied without competing for available land. However, seven options could result in competition for land. A large number of practices do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at a large scale, though the impact is scale and context specific, highlighting the need for safeguards to ensure that expansion of land for mitigation does not impact natural systems and food security. A number of practices, such as increased food productivity, dietary change and reduced food loss and waste, can reduce demand for land conversion, thereby potentially freeing‐up land and creating opportunities for enhanced implementation of other practices, making them important components of portfolios of practices to address the combined land challenges., There is a clear need for transformative change in the land management and food production sectors to address the global land challenges of climate change mitigation, climate change adaptation, combatting land degradation and desertification, and delivering food security (referred to hereafter as “land challenges”). We assess the potential for 40 practices to address these land challenges and find that most practices deliver across all land challenges. Some practices could result in competition for land, but those that reduce demand for land conversion potentially free‐up land, creating opportunities for enhanced implementation of other practices, making them important for addressing combined land challenge.

Formal institutions impact on the dynamics of land use change through their objectives, actions and decision-making processes in response to socio-economic or environmental changes such as climate change. The effects and interplay of these actions are not fully understood, and hence, institutional processes are rarely integrated in modelling analyses of land use change. The complex effects of institutional interactions within land systems can be better understood through modelling approaches that address the heterogeneity of the institutional actors involved and how their decisions affect temporal and spatial dynamics. In this paper, we present an agent-based model of autonomous land managers interacting with institutional agents at two spatial scales. We explore different parameters of institutional intervention (subsidy rate, triggers for action, delay in monitoring, scale-based precedence) under socio-economic drivers and analyse key metrics such as the maximum over- and undersupply of ecosystem services, connectivity of land uses, and degree of change in land use patterns. Levels of subsidy and action triggers have the greatest impact on the magnitude of land use change and the maximum oversupply of ecosystem services. In terms of achieving institutional objectives, subsidy rate is the most important single parameter in the model. Furthermore, we find non-linearity with variations in parameters that have important implications for current land use change modelling and requirements for empirical studies of land use planning institutions. Finally, the effects of high-end climate change may require entirely novel institutional behaviours.

Changes and innovations in land management have been hypothesised to spread through knowledge diffusion between land managers. Such diffusion can occur directly between neighbours or, in recent yea...

A growing body of literature argues that subjective factors can more accurately explain individual adaptation to climate change than objective measurers of adaptive capacity. Recent studies have shown that personal belief in climate change and affect are much better in explaining climate awareness and action than income, education or gender. This study focuses on the process of individual adaptation to climate change. It assesses and compares the influence of cognitive, experiential and structural factors on individuals’ views and intentions regarding climate change adaptation. Data from this study comes from a survey with 836 forest owners in Sweden. Ordinal and binary logistic regression was used to test hypotheses about the different factors. Results show that cognitive factors—namely personal level of trust in climate science, belief in the salience of climate change and risk assessment—are the only statistically significant factors that can directly explain individuals’ intention to adapt to climate change and their sense of urgency. Findings also suggest that structural or socio-demographic factors do not have a statistically significant influence on adaptation decision-making among Swedish forest owners. The study also offers valuable insights for communication interventions to promote adaptation. Findings strongly suggest that communication interventions should focus more strongly on building trust and addressing stakeholders’ individual needs and experiences.

Adaptation is necessary to cope with or take advantage of the effects of climate change on socio-ecological systems. This is especially important in the forestry sector, which is sensitive to the ecological and economic impacts of climate change, and where the adaptive decisions of owners play out over long periods of time. Relatively little is known about how successful these decisions are likely to be in meeting demands for ecosystem services in an uncertain future. We explore adaptation to global change in the forestry sector using CRAFTY-Sweden; an agent-based model that represents large-scale land-use dynamics, based on the demand and supply of ecosystem services. Future impacts and adaptation within the Swedish forestry sector were simulated for scenarios of socio-economic change (Shared Socio-economic Pathways) and climatic change (Representative Concentration Pathways, for three climate models), between 2010 and 2100. Substantial differences were found in the competitiveness and coping ability of land owners implementing different management strategies through time. Generally, multi-objective management was found to provide the best basis for adaptation. Across large regions, however, a combination of management strategies was better at meeting ecosystem service demands. Results also show that adaptive capacity evolves through time in response to external (global) drivers and interactions between individual actors. This suggests that process-based models are more appropriate for the study of autonomous adaptation and future adaptive and coping capacities than models based on indicators, discrete time snapshots or exogenous proxies. Nevertheless, a combination of planned and autonomous adaptation by institutions and forest owners is likely to be more successful than either group acting alone.

The uncertain effects of climatic change and changing demands for ecosystem services on the distribution of forests and their levels of service provision require assessments of future land-use change, ecosystem service provision, and how ecosystem service demands may be met. We present CRAFTY-Sweden, an agent-based, land-use model that incorporates land owner behaviour and decision-making in modelling future ecosystem service provision in the Swedish forestry sector. Future changes were simulated under scenarios of socio-economic and climatic change between 2010 and 2100. The simulations indicate that the influence of climatic change (on land productivities) may be less important thanthat of socio-economic change or behavioural differences. Simulations further demonstrate that the variability in land owner and societal behaviour has a substantial role in determining the direction and impact of land-use change. The results indicate a sizeable increase in timber harvesting in coming decades, which together with a substantial decoupling between supply and demand for forest ecosystem services highlights the challenge of continuously meeting demands for ecosystem services over long periods of time. There is a clear need for modelapplications of this kind to better understand the variation in ecosystem service provision in the forestry sector, and other associated land-use changes.

A future of increasing atmospheric carbon dioxide concentrations, changing climate, growing human populations, and shifting socioeconomic conditions means that the global agricultural system will need to adapt in order to feed the world. These changes will affect not only agricultural land but terrestrial ecosystems in general. Here, we use the coupled land use and vegetation model LandSyMM (Land System Modular Model) to quantify future land use change (LUC) and resulting impacts on ecosystem service indicators relating to carbon sequestration, runoff, biodiversity, and nitrogen pollution. We additionally hold certain variables, such as climate or land use, constant to assess the relative contribution of different drivers to the projected impacts. Some ecosystem services depend critically on land use and management: for example, carbon storage, the gain in which is more than 2.5 times higher in a low-LUC scenario (Shared Socioeconomic Pathway 4 and Representative Concentration Pathway 6.0; SSP4-60) than a high-LUC one with the same carbon dioxide and climate trajectory (SSP3-60). Other trends are mostly dominated by the direct effects of climate change and carbon dioxide increase. For example, in those two scenarios, extreme high monthly runoff increases across 54 % and 53 % of land, respectively, with a mean increase of 23 % in both. Scenarios in which climate change mitigation is more difficult (SSPs 3 and 5) have the strongest impacts on ecosystem service indicators, such as a loss of 13 %–19 % of land in biodiversity hotspots and a 28 % increase in nitrogen pollution. Evaluating a suite of ecosystem service indicators across scenarios enables the identification of tradeoffs and co-benefits associated with different climate change mitigation and adaptation strategies and socioeconomic developments.