A.A. Tabeau

Climate change effects on agriculture: Economic responses to biophysical shocks

Significance Plausible estimates of climate change impacts on agriculture require integrated use of climate, crop, and economic models. We investigate the contribution of economic models to uncertainty in this impact chain. In the nine economic models included, the direction of management intensity, area, consumption, and international trade responses to harmonized crop yield shocks from climate change are similar. However, the magnitudes differ significantly. The differences depend on model structure, in particular the specification of endogenous yield effects, land use change, and propensity to trade. These results highlight where future research on modeling climate change impacts on agriculture should focus. 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. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Climate change impacts on agriculture in 2050 under a range of plausible socioeconomic and emissions scenarios

Previous studies have combined climate, crop and economic models to examine the impact of climate change on agricultural production and food security, but results have varied widely due to differences in models, scenarios and input data. Recent work has examined (and narrowed) these differences through systematic model intercomparison using a high-emissions pathway to highlight the differences. This paper extends that analysis to explore a range of plausible socioeconomic scenarios and emission pathways. Results from multiple climate and economic models are combined to examine the global and regional impacts of climate change on agricultural yields, area, production, consumption, prices and trade for coarse grains, rice, wheat, oilseeds and sugar crops to 2050. We find that climate impacts on global average yields, area, production and consumption are similar across shared socioeconomic pathways (SSP 1, 2 and 3, as we implement them based on population, income and productivity drivers), except when changes in trade policies are included. Impacts on trade and prices are higher for SSP 3 than SSP 2, and higher for SSP 2 than for SSP 1. Climate impacts for all variables are similar across low to moderate emissions pathways (RCP 4.5 and RCP 6.0), but increase for a higher emissions pathway (RCP 8.5). It is important to note that these global averages may hide regional variations. Projected reductions in agricultural yields due to climate change by 2050 are larger for some crops than those estimated for the past half century, but smaller than projected increases to 2050 due to rising demand and intrinsic productivity growth. Results illustrate the sensitivity of climate change impacts to differences in socioeconomic and emissions pathways. Yield impacts increase at high emissions levels and vary with changes in population, income and technology, but are reduced in all cases by endogenous changes in prices and other variables.

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

Abstract 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. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

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. Two contrasting scenarios are used to capture some of the uncertainty in the development of typical combinations of economic, demographic and policy variables. The scenario storylines include different measurable assumptions concerning scenario specific drivers (variables) and parameters. Many of these assumptions are estimations and thus include a certain level of uncertainty regarding their true values. This leads to uncertainty within the scenario outcomes. In this study we have explored how uncertainty in national-level assumptions within the contrasting scenario assumptions translates into uncertainty in the location of changes in agricultural land use in Europe. The results indicate that uncertainty in coarse-scale assumptions does not translate into a homogeneous spread of the uncertainty within Europe. Some regions are more certain than others in facing specific land change trajectories irrespective of the uncertainty in the macro-level assumptions. The spatial spread of certain and more uncertain locations of land change is dependent on location conditions as well as on the overall scenario conditions. Translating macro-level uncertainties to uncertainties in spatial patterns of land change makes it possible to better understand and visualize the land change consequences of uncertainties in model input variables.

Simulating and delineating future land change trajectories across Europe

Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets.

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. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Identifying pathways to visions of future land use in Europe

Plausible scenarios of future land use derived from model projections may differ substantially from what is actually desired by society, and identifying such mismatches is important for identifying policies to resolve them. This paper presents an approach to link explorative projections of future land use for the European Union to normative visions of desired land-use futures. We used the results of 24 scenario projections obtained from seven linked simulation models to explore uncertainty in future land-use developments. Land-use projections were linked to statements made by stakeholders for three normative visions of desired, future land use. The visions differed in the scale of multifunctionality of land use: at European (Best Land in Europe), regional (Regional Connected) or local (Local Multifunctional) level. To identify pathways to these visions, we analysed in which cases projected land-use changes matched with the land-use changes desired in the visions. We identified five pathways to the vision Regional Connected, two pathways to the vision Best Land in Europe, but no pathway to the vision Local Multifunctional. Our results suggest that policies have the ability to change the development of land use such that it is more in line with land-use futures desired by society. We believe our approach represents an interesting avenue for foresight studies on land use, as it combines the credibility from explorative scenarios with legitimacy and saliency of normative visions.

Potential impacts on agricultural commodity markets of an EU enlargement to Turkey

This report provides an in-depth model based quantitative assessment of the potential impacts of an EU enlargement to Turkey for agricultural commodity markets in Turkey and the EU. For the purpose of the study a detailed dataset and modelling structure for the main agricultural commodities in the EU candidate country Turkey has been developed and integrated into the overall AGMEMOD modelling framework.

A cross-scale impact assessment of European nature protection policies under contrasting future socio-economic pathways.

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.

The Effects of Bioenergy Production on Food Security

The purpose of this paper is to deliver a framework and initial application of a model-based assessment of the food security impacts of changes in bioenergy production and relevant policies on food security. In an economic framework, four pathways are established by which biofuel production potentially affects the dimensions of food security: (1) food availability in connection with the competition for arable land; (2) the contribution of biofuel use of feedstock to food price volatility; (3) biofuel markets as a source of income opportunities for farmers; (4) sector-wide contributions to macroeconomic performance and living standards. Computable general equilibrium (CGE) modeling is proposed as methodology for an encompassing empirical examination of these pathways, although the limitations of the tool and data warrant the use of complementary qualitative and quantitative analyses.