The potential impacts of climate change in the Midwest United States present unprecedented challenges to regional agriculture. In response to these challenges, a variety of climate-smart agricultural methodologies have been proposed to retain or improve crop yields, reduce agricultural greenhouse gas emissions, retain soil quality and increase climate resilience of agricultural systems. One component that is commonly neglected when assessing the environmental impacts of climate-smart agriculture is the biophysical impacts, where changes in ecosystem fluxes and storage of moisture and energy lead to perturbations in local climate and water availability. Using a combination of observational data and an agroecosystem model, a series of climate-smart agricultural scenarios were assessed to determine the biophysical impacts these techniques have in the Midwest United States. The first scenario extended the growing season for existing crops using future temperature and CO2 concentrations. The second scenario examined the biophysical impacts of no-till agriculture and the impacts of annually retaining crop debris. Finally, the third scenario evaluated the potential impacts that the adoption of perennial cultivars had on biophysical quantities. Each of these scenarios was found to have significant biophysical impacts. However, the timing and magnitude of the biophysical impacts differed between scenarios.

There are inherent challenges in scaling stomatal conductance (g s) from leaf to canopy particularly over seasonal time scales when species distribution and canopy structure evolve. We address this gap using carbonyl sulfide (OCS) and CO 2 fluxes from a predominantly C3 prairie and C4 maize field in the midwestern United States. The g s derived from OCS fluxes captured a transition in the stomatal limitation on gross primary productivity (GPP) through the growing season as well as seasonally persistent g s dynamics such as temperature optimum and a positive response of nighttime g s to vapor pressure deficit. Near the termination of the prairie growing season, we observed a decrease in the relative OCS to CO 2 flux that we hypothesize emerged from a rising contribution of C4 plants to productivity. The results show how plot‐scale OCS and CO 2 fluxes can be used as a trace gas diagnostic for transitions in the limiting factors for community GPP.

Perennial grasses are promising feedstocks for bioenergy production in the Midwestern USA. Few experiments have addressed how drought influences their carbon fluxes and storage. This study provides a direct comparison of ecosystem-scale measurements of carbon fluxes associated with miscanthus (Miscanthus × giganteus), switchgrass (Panicum virgatum), restored native prairie and maize (Zea mays)/soybean (Glycine max) ecosystems. The main objective of this study was to assess the influence of a naturally occurring drought during 2012 on key components of the carbon cycle and plant development relative to non-extreme years. The perennials reached full maturity 3-5 years after establishment. Miscanthus had the highest gross primary production (GPP) and lowest net ecosystem exchange (NEE) in 2012 followed by similar values for switchgrass and prairie, and the row crops had the lowest GPP and highest NEE. A post-drought effect was observed for miscanthus. Over the duration of the experiment, perennial ecosystems were carbon sinks, as indicated by negative net ecosystem carbon balance (NECB), while maize/soybean was a net carbon source. Our observations suggest that perennial ecosystems, and in particular miscanthus, can provide a high yield and a large potential for CO2 fixation even during drought, although drought may negatively influence carbon uptake in the following year, questioning the long-term consequence of its maintained productivity.