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Abstract: The stable carbon isotope ratio, , is a valuable tracer for studying the processes controlling the autotrophic (F Ra ) and heterotrophic (F Rh ) contributions to ecosystem respiration (F R ) and the influence of photosynthesis on F R . There is increasing interest in quantifying the temporal variability of the carbon isotope composition of ecosystem respiration (δ R ) because it contains information about the sources contributing to respiration and is an important parameter used for partitioning net ecosystem CO2 exchange using stable isotope methods. In this study, eddy covariance, flux gradient, automated chambers, and stable carbon isotope techniques were used to quantify and improve our understanding of the temporal variability in F R and δ R in a C3/C4 agricultural ecosystem. Six years (2004–2009) of isotope flux-gradient measurements indicated that δ R had a very consistent annual pattern during both C3 (soybean) and C4 (corn) growing seasons due to significant contributions from F Ra , which was strongly influenced by the isotope composition of the recent photosynthate. However, in the spring, δ R exhibited a C3 signal regardless of the crop grown in the previous season. One hypothesis for this anomaly is that at these low soil temperatures microbial activity relied predominantly on C3 substrates. Automated chamber measurements of soil respiration () and its isotope composition () were initiated in the early corn growing season of 2009 to help interpret the variability in δ R . These measurements showed good agreement with EC measurements of F R (within 0.5μmolm2 s−1) and isotope flux gradient measurements of δ R (within 2‰) at nighttime for near-bare soil conditions (LAI<0.1). At peak growth, nighttime δ R above the corn canopy was consistently 1–6‰ more enriched than . The relatively enriched signal above the canopy indicates that δ R was strongly influenced by aboveground plant respiration (F R,ag ), which accounted for about 40% of F R . The automated chamber data and analyses also revealed a strong diel pattern in . In the early growth period, showed a sharp morning enrichment of up to 4‰ followed by a gradual depletion throughout the afternoon and evening. Daytime enrichment in was most pronounced during dry conditions and was not observed when the upper soil was near saturation. We provide anecdotal evidence that the diel variability during early growth may have been influenced by turbulence (advection/non-diffusive transport), which reduced the kinetic fractionation effect. At peak growth, there is evidence that the sheltering effect of the corn plants diminished the influence of turbulence on the chamber measurement of . Further research is needed to evaluate and separate the contributions of biotic and abiotic (advection and non-steady state effects) influences on chamber observations. [Copyright &y& Elsevier]

Abstract: Separation of the photosynthetic (F P ) and respiratory (F R ) fluxes of net CO2 exchange (F N ) remains a necessary step toward understanding the biological and physical controls on carbon cycling between the soil, biomass, and atmosphere. Despite recent advancements in stable carbon isotope partitioning methodology, several potential limitations can cause uncertainty in the partitioned results. Here, we combined an automated chamber system with a tunable diode laser (TDL) to evaluate carbon isotope partitioning under controlled environmental conditions. Experiments were conducted in a climate controlled greenhouse utilizing both soybean (C3 pathway) and corn (C4 pathway) treatments. Under these conditions, net exchange of and was obtained with an improved signal to noise ratio. Further, the chamber system was used to estimate soil evaporation (E) and plant transpiration (T), allowing for an improved estimate of the total conductance to CO2 (g c ). This study found that the incorporation of short-term and diel variability in the isotope composition of respiration (δ R ) caused F P to nearly double in the corn system while only slightly increasing in the soybean system. Variability in both g c and the CO2 bundle sheath leakage factor for C4 plants (ϕ) also had a significant influence on F P . In addition, chamber measurements of F N and its isotope composition (δ N ) indicated that post-illumination processes caused a decrease in plant respiration for up to 3h following light termination. Finally, this study found systematic differences between the isotope and temperature-regression partitioning methods on the diel time scale. [Copyright &y& Elsevier]

• Phenological controls over aerodynamic resistance (R ah) were investigated. • R ah exhibits significant seasonal variability across a wide range of sites. • These shifts in R ah were caused by phenology in some ecosystems. • Accounting for variation in kB −1 is important for improving predictions of H. Surface roughness – a key control on land-atmosphere exchanges of heat and momentum – differs between dormant and growing seasons. However, how surface roughness shifts seasonally at fine time scales (e.g., days) in response to changing canopy conditions is not well understood. This study: (1) explores how aerodynamic resistance changes seasonally; (2) investigates what drives these seasonal shifts, including the role of vegetation phenology; and (3) quantifies the importance of including seasonal changes of aerodynamic resistance in "big leaf" models of sensible heat flux (H). We evaluated aerodynamic resistance and surface roughness lengths for momentum (z 0m) and heat (z 0h) using the kB −1 parameter (ln(z 0m / z 0h)). We used AmeriFlux data to obtain surface-roughness estimates, and PhenoCam greenness data for phenology. This analysis included 23 sites and ∼190 site years from deciduous broadleaf, evergreen needleleaf, woody savanna, cropland, grassland, and shrubland plant-functional types (PFTs). Results indicated clear seasonal patterns in aerodynamic resistance to sensible heat transfer (R ah). This seasonality tracked PhenoCam-derived start-of-season green-up transitions in PFTs displaying the most significant seasonal changes in canopy structure, with R ah decreasing near green-up transitions. Conversely, in woody savanna sites and evergreen needleleaf forests, patterns in R ah were not linked to green-up. Our findings highlight that decreases in kB −1 are an important control over R ah , explaining > 50% of seasonal variation in R ah across most sites. Decreases in kB −1 during green-up are likely caused by increasing z 0h in response to higher leaf area index. Accounting for seasonal variation in kB −1 is key for predicting H as well; assuming kB −1 to be constant resulted in significant biases that also exhibited strong seasonal patterns. Overall, we found that aerodynamic resistance can be sensitive to phenology in ecosystems having strong seasonality in leaf area, and this linkage is critical for understanding land-atmosphere interactions at seasonal time scales. [ABSTRACT FROM AUTHOR]

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO 2) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO 2 concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54 μ mol m − 2 s − 1 ) persists for all seasons leading to a 110% overestimate of the ecosystem CO 2 sink (cumulative error of 78 gC m−2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m−2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO 2 fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m−2) or to systematic over-correction (by 17-37 gC m−2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5 μ mol m − 3 K − 1 . This temperature sensitivity causes CO 2 calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO 2 measurement errors. [ABSTRACT FROM AUTHOR]