Spring rainstorm in Iowa. photo: Nathan Mueller Climate is a key determinant of crop production, and coping with climate change and variability in agricultural systems is a central challenge of our time (2017). However, land use and land cover change associated with agriculture can influence local climate by altering the surface energy budget. Understanding the impacts of climate change on agriculture will require better understanding of land-atmosphere interactions in agricultural landscapes. Recent work using observational data has demonstrated how intensification of cropland productivity, and associated increases in evapotranspiration, have suppressed extreme temperatures over croplands in the United States (2016) and in other major summer cropping systems around the world (2017). Land use practices are also related to farmer perceptions of climate change, an association that may influence the adoption of adaptation measures (2016). Several recent collaborations have also examined the contribution of agriculture to greenhouse gas emissions, and we have put forward the first global, crop-specific, and spatially-explicit maps of cropland N2O emissions (2016) and greenhouse gas emissions intensity (2017).
Intensive management practices adopted throughout the Green Revolution led to large increases in crop production on existing lands, but often with substantial environmental tradeoffs. My work has estimated potential spatial changes to irrigation and NPK fertilizer associated with increases in production (2012). As part of this study, a global crop-specific dataset of fertilizer application was developed, available for research purposes on earthstat.org. In a related study, we showed that there are large production and environmental gains possible from more optimal spatial allocation of nitrogen resources (2014). Using historical nitrogen budget data, we demonstrated that this opportunity space has increased since the 1960s as the allocation of nitrogen between regions has become less efficient (2017).
Earlier research examined global patterns of crop attainable yields and yield gaps to understand the capacity for agricultural development across the globe (2012). A new, ongoing project updates the yield gap modeling framework and is characterizing the spatio-temporal trends in attainable yields and yield gaps using newly-developed historical datasets of agricultural census and survey data. We are also examining the extent to which historical agricultural development impacted food security and health outcomes by merging spatially-precise estimates of modern crop variety diffusion with Demographic and Health Survey data across the developing world.
Stagnation of crop yield growth is a major concern given ongoing increases in food demand. With Deepak Ray and others, we analyzed the most complete dataset of time-series crop census data ever compiled (13,500 census units, 2.5 million observations). Roughly 1/3 of the world's croplands are experiencing stagnant yield trends (2012) and current yield trends are not keeping pace with the expected doubling of food demand (2013). Ongoing research is focused on in-season crop monitoring using remote sensing data.