Regional switchgrass carbon sequestration estimates from high‐frequency eddy covariance and Mesonet observations

• Published in: Agrosystems, geosciences & environment Vol. 6; no. 1
• Main Authors: Dhakal, Kundan, Kakani, Vijaya Gopal, Wagle, Pradeep, Sharma, Sonisa
• Format: Journal Article
• Language: English
• Published: Hoboken John Wiley & Sons, Inc 2023; Wiley
• Subjects: Alternative energy sources; Biodiesel fuels; Biofuels; Biomass; Carbon dioxide; Carbon sequestration; Consumption; Covariance; Crops; Ecological monitoring; Ecosystems; Estimates; Ethanol; Geographic information systems; Geostatistics; Growth models; Heat; Heterogeneity; Humidity; Light effects; Meteorological data; Panicum virgatum; Prairies; Precipitation; Primary production; Productivity; Radiation; Raw materials; Regions; Remote sensing; Response functions; Temporal resolution; Thematic mapping; Vortices; United States > US; Oklahoma; Great Plains
• ISSN: 2639-6696; 2639-6696
• DOI: 10.1002/agg2.20328

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) sums of NEE across potential switchgrass establishment landscapes in Oklahoma, USA. We identified ensemble areas for potential switchgrass expansion regions and created thematic maps of switchgrass productivity using geostatistics and geographic information systems (GIS) routines. The purpose of this study was to explore if model parametrizations based on high temporal frequency meteorological forcing can be used for reliable estimates of NEE for evaluating the source–sink status of carbon. Rectangular hyperbolic light‐response curve and temperature response functions were fitted using EC measurements to estimate gross primary production (GPP) and ecosystem respiration (ER), respectively, on a seasonal scale. Model performance validated by comparing EC‐measured seasonal NEE for 3 yr showed good‐to‐strong agreement (.29 < R2 < .91; p < .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 (SD) 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 approach 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. Core Ideas NEE CO2 estimates in switchgrass ecosystem were generated and validated using eddy flux and meteorological data. NEE was estimated using radiation use efficiency, air and soil temperature, VPD, and quantum use efficiency. Switchgrass productivity estimates were characterized for the potential production areas in Oklahoma.