Seasonal and interannual variability in ¹³C composition of ecosystem carbon fluxes in the U.S. Southern Great Plains

Abstract

Abstract

Evaluation of 4 years of continuous <i>δ</i><sup>13</sup>C(CO<sub>2</sub>) data using a moving Keeling plot method

“…Unfortunately, the isotopic end members are often not known with high accuracy. The uncertainty of the isotopic end members often impedes or even prevents a unique straightforward determination of the source contribution in the catchment area (e.g., Torn et al, 2011, Lopez et al 2013 and calls for elaborated statistical models based on Bayesian statistics. This important fact is sometimes mentioned, but the consequences for quantitative evaluations are rarely emphasized, preserving the high expectations associated with isotope measurements.…”

“…For example, the CO 2 fluxes from land and ocean can be distinguished using the ratio of stable carbon isotopologue 13 CO 2 / 12 CO 2 in addition to CO 2 concentration measurements (Mook et al, 1983;Ciais et al, 1995;Alden et al, 2010). In other studies, measurements of 13 CO 2 have been used to distinguish between different fuel types Lopez et al 2013;Newman et al, 2016) or to evaluate ecosystem behavior (Torn et al, 2011), to mention but a few examples of the many published in the literature.…”

“…(Ballantyne et al, 2010;Bastos et al, 2016). Likewise, the mean source signature can be used to separate between different source CO 2 contributions if the isotopic end members of these sources are known at all times Torn et al, 2011;Lopez et al 2013;Moore and Jacobson, 2015;Newman et al, 2016).…”

20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models

“…The δ 13 C data representing atmospheric air are used to quantify the global ocean and land carbon sources and sinks (Keeling et al, 1989;Joos and Bruno, 1998;Trudinger et al, 2002;Bauska et al, 2015). Furthermore, δ 13 C observations allow identification of the imprint of fossil-fuel carbon in atmospheric air to quantify regional-tolocal-scale land carbon sources and sinks (Torn et al, 2011;Vardag et al, 2016), or to evaluate air-sea transfer velocity parameterizations (Krakauer et al, 2006). The δ 13 C data from the modern ocean are applied to infer the oceanic uptake of anthropogenic carbon (Heimann and Maier-Reimer, 1996;Gruber et al, 1999;Sonnerup and Quay, 2012;Becker et al, 2016), while paleoproxy δ 13 C data from ocean sediments and ice cores permit inference of land carbon changes between the last glacial maximum and the current warm period (Shackleton, 1977;Ciais et al, 2012;Peterson et al, 2014).…”

Role of Surface Energy Exchange for Simulating Wind Turbine Inflow: A Case Study in the Southern Great Plains, USA

“…The region has fine scale spatial heterogeneity due to small land holdings and changing crop rotations. Regional heterogeneity is enhanced by climatic gradients resulting in a wide range of precipitation across the larger SGP ARM domain from the northwest (380 mm) to the southeast (1270 mm) [30]. The crops are not irrigated and crop losses, delayed plantings, and early or late harvests can result from anomalous climate conditions.…”