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Highlights: [•] We directly measure the isotopic composition of NEE in a forest by eddy covariance. [•] Precision is limited both by instrument noise and by horizontal heterogeneity. [•] Precision is sufficient to partition NEE into photosynthesis and respiration. [•] The ‘EC/flask’ indirect flux measurement method can be biased by 2‰. [•] Laser spectrometer accuracy is on par with isotope ratio mass spectrometry. [ABSTRACT FROM AUTHOR]

Abstract: We determined the effective line strengths of the trans conformer of nitrous acid (HONO) near 1275cm−1 (R-branch of ν 3 mode, NOH bend) and of the cis conformer at 1660cm−1 (R-branch of ν 2 mode, NO stretch), both at a spectral resolution of 0.001cm−1 by tunable infrared laser differential absorption spectroscopy (TILDAS) utilizing continuous-wave quantum cascade (cw-QC) lasers. Absorbance of one conformer was measured while simultaneously quantifying the mixing ratio of total HONO by catalytic conversion to nitric oxide (NO) followed by calibrated absorption spectroscopy. Line strengths obtained here are consistent with previously reported band strengths for the trans conformer but are lower by a factor of approximately 2.4 for the cis conformer. [Copyright &y& Elsevier]

Abstract: Spatially explicit and temporally continuous estimates of photosynthesis will be of great importance for increasing our understanding of and ultimately closing the terrestrial carbon cycle. Current capabilities to model photosynthesis, however, are limited by accurate enough representations of the complexity of the underlying biochemical processes and the numerous environmental constraints imposed upon plant primary production. A potentially powerful alternative to model photosynthesis through these indirect observations is the use of multi-angular satellite data to infer light-use efficiency (ε) directly from spectral reflectance properties in connection with canopy shadow fractions. Hall et al. (this issue) introduced a new approach for predicting gross ecosystem production that would allow the use of such observations in a data assimilation mode to obtain spatially explicit variations in ε from infrequent polar-orbiting satellite observations, while meteorological data are used to account for the more dynamic responses of ε to variations in environmental conditions caused by changes in weather and illumination. In this second part of the study we implement and validate the approach of Hall et al. (this issue) across an ecologically diverse array of eight flux-tower sites in North America using data acquired from the Compact High Resolution Imaging Spectroradiometer (CHRIS) and eddy-flux observations. Our results show significantly enhanced estimates of ε and therefore cumulative gross ecosystem production (GEP) over the course of one year at all examined sites. We also demonstrate that ε is greatly heterogeneous even across small study areas. Data assimilation and direct inference of GEP from space using a new, proposed sensor could therefore be a significant step towards closing the terrestrial carbon cycle. [Copyright &y& Elsevier]

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km2) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms. [Copyright &y& Elsevier]