Empirical Approach to Estimate Net Ecosystem Exchange Using High
Frequency Mesonet Observations across Potential Switchgrass
Establishment Landscapes in Oklahoma
Abstract
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.