H. van Meijl

Indirect land use change: review of existing models and strategies for mitigation

This study reviews the current status, uncertainties and shortcomings of existing models of land use change (LUC) and associated GHG emissions as a result of biofuel production. The study also identifies options for improving the models and conducting further analysis. Moreover, because the extent of indirect LUC related to biofuels largely depends on other land uses, particularly agriculture, this study explores strategies for mitigating overall LUC and its effects. Despite recent improvements and refinements of the models, this review finds large uncertainties, primarily related to the underlying data and assumptions of the market-equilibrium models. Thus, there is still considerable scope for further scientific improvements of the modeling efforts. In addition, analyzing how overall LUC and its effects can be minimized is an important topic for further research and can deliver more concrete input for developing proper policy strategies. Future studies should investigate the impact of sustainability criteria and the effects of strategies for mitigating LUC, such as increasing agricultural efficiency, optimizing bioenergy production chains, using currently unused residues and byproducts, and producing feedstocks on degraded and marginal land.

Model collaboration for the improved assessment of biomass supply, demand, and impacts

Existing assessments of biomass supply and demand and their impacts face various types of limitations and uncertainties, partly due to the type of tools and methods applied (e.g., partial representation of sectors, lack of geographical details, and aggregated representation of technologies involved). Improved collaboration between existing modeling approaches may provide new, more comprehensive insights, especially into issues that involve multiple economic sectors, different temporal and spatial scales, or various impact categories. Model collaboration consists of aligning and harmonizing input data and scenarios, model comparison and/or model linkage. Improved collaboration between existing modeling approaches can help assess (i) the causes of differences and similarities in model output, which is important for interpreting the results for policy‐making and (ii) the linkages, feedbacks, and trade‐offs between different systems and impacts (e.g., economic and natural), which is key to a more comprehensive understanding of the impacts of biomass supply and demand. But, full consistency or integration in assumptions, structure, solution algorithms, dynamics and feedbacks can be difficult to achieve. And, if it is done, it frequently implies a trade‐off in terms of resolution (spatial, temporal, and structural) and/or computation. Three key research areas are selected to illustrate how model collaboration can provide additional ways for tackling some of the shortcomings and uncertainties in the assessment of biomass supply and demand and their impacts. These research areas are livestock production, agricultural residues, and greenhouse gas emissions from land‐use change. Describing how model collaboration might look like in these examples, we show how improved model collaboration can strengthen our ability to project biomass supply, demand, and impacts. This in turn can aid in improving the information for policy‐makers and in taking better‐informed decisions.

Cross sector land use modelling framework

The purpose of the model component in SENSOR is to quantify the effects of a comprehensive set of policies on land use. The need to include interaction between sectors as well as a high level of detail for each sector calls for a combination of sector specific and sector wide models. This chapter describes the modelling system, with emphasis on the linking of the models to a coherent system. Five sectors of significant importance for land use are modelled individually: Forestry, agriculture, urban land use, transport infrastructure and tourism. All models are connected as sub-modules to an economy-wide partial econometric model. In addition, a land cover model is used to disaggregate land use down to 1 km grid resolution.

Towards pathways bending the curve terrestrial biodiversity trends within the 21st century

Unless actions are taken to reduce multiple anthropogenic pressures, biodiversity is expected to continue declining at an alarming rate. Models and scenarios can be used to help design the pathways to sustain a thriving nature and its ability to contribute to people. This approach has so far been hampered by the complexity associated with combining projections of pressures on, and subsequent responses from, biodiversity. Most previous assessments have projected continuous biodiversity declines and very few have identified pathways for reversing the loss of biodiversity without jeopardizing other objectives such as development or climate mitigation. The Bending The Curve initiative set out to advance quantitative modelling techniques towards ambitious scenarios for biodiversity. In this proof-of-concept analysis, we developed a modelling approach that demonstrates how global land use and biodiversity models can shed light on wedges able to bend the curve of biodiversity trends as affected by land-use change, the biggest current threat to biodiversity. In order to address the uncertainties associated with such pathways we used a multi-model framework and relied on the Shared Socioeconomic Pathway/Representative Concentration Pathway scenario framework. This report describes the details of this modelling approach.