How are the SSP storylines being implemented in the Integrated Assessment Models—with a focus on land-use changes

The Shared Socioeconomic Pathways (SSPs) articulate five different future socioeconomic development pathways (O’Neill et al., nd). These SSPs were designed to explore uncertainty in challenges to mitigation and challenges to adaptation. However, the resulting stories lead to large differences in population, income, diet, biomass, trade, and terrestrial climate mitigation potential, making these scenarios ideal for exploring uncertainty in the evolution of the terrestrial system. Land use, land use change, and forestry (LULUCF) both influence and are influenced by climate change. LULUCF contributes approximately 25% of global greenhouse emissions today, mostly from deforestation CO2, CH4 from livestock and rice, and N2O from fertilized soils (Tubiello et al., 2015). Conversely, climate-induced changes in ecosystem productivity alter LULUCF, resulting in changes in agricultural land and ecosystem carbon storage. The terrestrial system also has the potential to contribute to climate change mitigation, e.g., through biomass production or afforestation (Wise et al., 2009; Reilly et al., 2012; Popp et al., 2013). The future evolution of the terrestrial system is highly uncertain, depending on, among other sources of uncertainty, numerous factors that shape the five SSP storylines. This paper will provide a deep dive into a single sector in the SSPs, focusing on the quantification of land use and land use change by six different Integrated Assessment Models. We will briefly describe the elements of the SSP storylines that are pertinent to the terrestrial system. Then, we will show land-related results from the SSP quantifications, including land use and land cover, food consumption, bioenergy production, emissions, and agricultural commodity prices. We will conclude with a brief discussion of how these results can be used by other communities, e.g., the Earth System Modeling and Impacts, Adaptation, and Vulnerability communities.