Productive land is a scarce resource with a decreasing supply (Gomiero, 2016) but ever growing demands (Gomiero, 2016;Lambin & Meyfroidt, 2011). Increasing population and wealth cause greater demand for crops, meat, and other agricultural products and therefore for the water and energy resources needed to produce these products. At the same time, non-commercial land is an integral part of most environmental objectives. Land conservation is necessary to maintain biodiversity and healthy stable ecosystems (Thompson et al., 2009), and forests and soils are valuable carbon sinks that aid in mitigating severe climate change (Asner et al., 2004;Lal, 2004). These services improve the long-term quality of life on Earth and help achieve the relatively near-term goals of international environmental agreements such as the Convention on Biodiversity and the Paris Accords. The competing multi-sector demands for land (Carrasco et al., 2017;Dooley et al., 2018;Grass et al., 2020;Meyfroidt, 2018) emphasize the importance of modeling land scarcity in the context of the complex coupled human-Earth system. To more fully understand the multisector dynamics that drive land scarcity and its impacts, multiple metrics should be evaluated so that synergies and tradeoffs between competing sectors are made known (Kroll et al., 2019;van Vuuren et al., 2015). Further, these dynamics should be analyzed in the context of the abundant uncertainty present in the system. Dynamics may shift depending on the circumstances and it is important to understand the drivers of these dynamical shifts so that planners can make decisions that are robust to future changes. Other land use studies assess multiple impact metrics without explicitly accounting for future uncertainty (Kroll et al., 2019;van Vuuren et al., 2015) or assess economic (Waldron et al., 2020) or environmental (Borrelli et al., 2020;Mouratiadou et al., 2016) impacts under uncertainty, but few studies implement all of these elements (Gao & Bryan, 2017). Considering only one metric may lead to myopic decisions and high regret, whereas failing to account for uncertainty can lead to decisions that leave the population vulnerable to high losses (Reckhow, 1994).