Short- and long-term warming effects of methane may affect the cost-effectiveness of mitigation policies and benefits of low-meat diets.

Methane's short atmospheric life has important implications for the design of global climate change mitigation policies in agriculture. Three different agricultural economic models are used to explore how short- and long-term warming effects of methane can affect the cost-effectiveness of mitigation policies and dietary transitions. Results show that the choice of a particular metric for methane's warming potential is key to determine optimal mitigation options, with metrics based on shorter-term impacts leading to greater overall emission reduction.

Land-based climate change mitigation measures can affect agricultural markets and food security.

Earlier studies have noted potential adverse impacts of land-related emissions mitigation strategies on food security, particularly due to food price increases-but without distinguishing these strategies' individual effects under different conditions. Using six global agroeconomic models, we show the extent to which three factors-non-CO emissions reduction, bioenergy production and afforestation-may change food security and agricultural market conditions under 2 °C climate-stabilization scenarios. Results show that afforestation (often simulated in the models by imposing carbon prices on land carbon stocks) could have a large impact on food security relative to non-CO emissions policies (generally implemented as emissions taxes).

Snakes and ladders: World development pathways' synergies and trade-offs through the lens of the Sustainable Development Goals.

This paper takes three global visions of world development to 2050 and quantifies their implications for sustainable progress employing the metrics of the Sustainable Development Goals (SDGs). The SDG outcomes are structured through the interconnectivities of the three 'wedding cake' layers of 'economy', 'society' and 'biosphere', as posited by the Stockholm Resilience Centre. The key policy contribution is to quantify the resulting SDG synergies and trade-offs, whilst also decomposing and calculating the part-worth of the market drivers which contribute to these outcomes.

Afforestation for climate change mitigation: Potentials, risks and trade-offs.

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.

Key determinants of global land-use projections.

Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions.

Assessing uncertainties in land cover projections.

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas.

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions.

Climate change effects on agriculture: economic responses to biophysical shocks.

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data.

Assessing spatial uncertainties of land allocation using a scenario approach and sensitivity analysis: a study for land use in Europe.

Land change model outcomes are vulnerable to multiple types of uncertainty, including uncertainty in input data, structural uncertainties in the model and uncertainties in model parameters. In coupled model systems the uncertainties propagate between the models. This paper assesses uncertainty of changes in future spatial allocation of agricultural land in Europe as they arise from a general equilibrium model coupled to a spatial land use allocation model.