Monitoring net ecosystem carbon dioxide (CO2) exchange (NEE) using eddy covariance (EC) flux towers is quite common, but the measurements are valid at the scale of tower footprints. Alternative ways to quantify and extrapolate EC-measured NEE across potential production areas have not been explored in detail. To address this need, we used NEE measurements from a switchgrass (Panicum virgatum L.) ecosystem and detailed meteorological measurements from the Oklahoma Mesonet and developed empirical relationships for quantifying seasonal (April to October) NEE across potential switchgrass establishment landscapes in Oklahoma, USA. We identified ensemble area for potential switchgrass expansion regions and created thematic maps of switchgrass productivity using geostatistics and GIS routines. The purpose of this study was not to calibrate the model for estimating NEE in the future but to explore if model parametrizations based on high temporal frequency meteorological forcing can be used to construct reliable estimates of NEE for evaluating the source-sink status of organic carbon. Based on EC measurements, empirical models, a) rectangular hyperbolic light-response curve and b) temperature response functions, were fitted to estimate gross primary production (GPP) and ecosystem respiration (ER) on a seasonal scale. Model performance validated by comparing EC-measured seasonal NEE for three years showed good-to-strong agreement (0.29 < R2 <0.91; p < 0.05). Additionally, total seasonal NEE estimates were validated with measured biomass data in three additional locations. The estimated seasonal average net ecosystem production (NEP =-NEE) was 3.97 ± 1.92 (S.D.) Mg C ha-1. However, results based on a simple linear model suggested significant differences in NEP between contrasting climatic years. Overall, the results from this study indicate that this new scaling-up exercise involving high temporal resolution meteorological data may be a helpful tool for assessing spatiotemporal heterogeneity of switchgrass production and the potential of switchgrass fields to sequester carbon in the Southern Great Plains of the United States.

Understanding the consequences of different management practices on vegetation phenology, forage production and quality, plant and microbial species composition, greenhouse gas emissions, and water budgets in tallgrass prairie systems is vital to identify best management practices. As part of the Southern Plains Long-Term Agroecosystem Research (SP-LTAR) grassland study, a long-term integrated Grassland-LivestOck Burning Experiment (iGLOBE) has been established with a cluster of six eddy covariance (EC) systems on differently managed (i.e., different burning and grazing regimes) native tallgrass prairie systems located in different landscape positions. The purpose of this paper is to describe this long-term experiment, report preliminary results on the responses of differently managed tallgrass prairies under variable climates using satellite remote sensing and EC data, and present future research directions. In general, vegetation greened-up and peaked early, and produced greater forage yields in burned years. However, drought impacts were greater in burned sites due to reductions in soil water availability by burning. The impact of grazing on vegetation phenology was confounded by several factors (e.g., cattle size, stocking rate, precipitation). Moreover, prairie systems located in different landscapes responded differently, especially in dry years due to differences in water availability. The strong correspondence between vegetation phenology and eddy fluxes was evidenced by strong linear relationships of greenness index (i.e., enhanced vegetation index) with evapotranspiration and gross primary production. Results indicate that impacts of climate and management practices on vegetation phenology may profoundly impact carbon and water budgets of tallgrass prairie. Interacting effects of multiple management practices and inter-annual climatic variability on the responses of tallgrass prairie highlight the necessity of establishing an innovative and comprehensive long-term experiment to address inconsistent responses of tallgrass prairie to different intensities, frequencies, timing, and duration of management practices, and to identify best management practices.