Conference Agenda

Natural resources—land, water, soils, and natural vegetation—are essential for sustaining crop production and enabling climate change adaptation. Yet their role as a dimension of food systems’ adaptive capacity remains underexplored. Using the global land-use model MAgPIE, we assess current and future resource availability across global crop-producing regions under three socioeconomic and climate scenarios. Currently, about 23% of cropland faces low resource availability due to land and water overexploitation, with hotspots in North Africa and Afghanistan. Projections show widespread resource declines across all scenarios, especially in South America, India, and Sub-Saharan Africa, driven by cropland expansion and intensification. These findings highlight the need to integrate sustainability and resilience into agricultural development.

Land conversion from noncropland to cropland has major implications for food production, carbon sequestration, biodiversity, and water quality. Once land is converted, restoring its original environmental functions can be costly and time-consuming. Using over 8 million field-level observations, this study examines the impact of climate change on noncropland-to-cropland transitions in North and South Dakota, United States. We estimate how changes in growing-season temperature and precipitation normals—measured as 30-year rolling averages—influence the likelihood of such transitions, focusing on corn and soybeans, the region’s two major crops. Because previous studies have relied primarily on data from already cultivated land, little is known about how climate change affects the probability of noncropland being converted to cropland. This study addresses this gap by providing spatially explicit, field-level estimates of climate-induced transition probabilities. We estimate climate–land conversion relationships separately for two distinct regions: one with fertile, flood-prone conditions and the other with infertile, semi-arid conditions. Results show that precipitation discourages conversion in the former but encourages it in the latter. Temperature has a strongly positive effect in the fertile region but little effect in the semi-arid region. Our projections indicate that an additional 18.2 million acres—over 35% of the remaining noncropland—could be converted to cropland by 2081 under the moderate-emissions scenario RCP4.5, relative to 2018, with most of this expansion occurring in fertile areas. These findings highlight the potential for substantial cropland expansion in regions historically less suited to crop production. Regional heterogeneity underscores the need for region-specific adaptation and conservation strategies to balance the economic gains from cropland expansion with the loss of ecosystem services in a changing climate.

Mechanization is a key ingredient for raising agricultural productivity. Currently, however, globally comparable information on agricultural mechanization rates is hard to come by. Here, we globally model agricultural mechanization at an unprecedented ~ 5km resolution and examine its empirical association with crop yield gaps but also soil compaction and forest loss. We find that many high-income countries are close to fully mechanized by now, whereas, especially in Sub-Saharan Africa and Southern Asia, mechanization rates are still low. We then estimate that for each ten-percentage point increase in the mechanization rate, the average crop yield gap shrinks by 3 to 4 percentage points and soil compaction increases by 1.5 to 2 percentage points. There is no clear effect of agricultural mechanization on tree cover loss.

California's ambitious renewable energy targets will require that considerable land be allocated to solar-powered electricity generation infrastructure, which has a significantly lower energy footprint than traditional fossil-fueled power plants. The role that the Central Valley (CV) will play in this transition is significant, as land conversion in this region comes with the opportunity cost of lost revenue from agriculture. The decision of whether and how to protect land currently being used for farming will thus be crucial to the state's future agricultural productivity and environmental sustainability. This paper examines how land allocation to solar development and cropland differs under two decision-making perspectives, one that only optimizes private benefits (the Land Manager) and another that considers social welfare (the Central Planner). We use a two-stage, spatially-explicit optimization model to simulate solar power capacity targets ranging from 0 to 50 GW, considering agricultural profits, solar revenues, and environmental benefits. This allows us to quantify economic tradeoffs across these various benefits and the gap between the solution that is preferred by private landholders and the socially optimal. Our findings suggest that the misalignment between privately and socially optimal solar siting may require additional incentives, such as public financing of transmission infrastructure or lease rate offsets through subsidies, to achieve capacity targets over 25 GW. In addition, socially optimal PV siting has the potential to reduce overdraft in the southern CV by 80%.