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Abstract: A land surface model (a modified version of the Simple Biosphere Model, Version 2; SiB2) was parameterized and tested against two years of eddy covariance flux measurements made over un-grazed tallgrass prairie and a winter wheat field in Oklahoma, USA. The land surface model computed 30-min estimates of sensible and latent heat flux and carbon dioxide flux that agree well with the patterns observed in the field, simulating in particular the contrasting seasonal timing of fluxes in the wheat, where leaf area and physiological activity peak in the spring, and prairie, where leaf area and physiological activity peak in summer. However, systematic errors in flux estimates were also identified for particular times of day and season. These systematic errors are sometimes related to difficulty in correct definition of vegetation structure (LAI) and physiological activity. This was observed particularly in the wheat site towards the end of the growing season when senescence, which reduces both the amount and the physiological activity of leaves, is difficult to parameterize. Simulation errors are also attributed to problems in the mathematical description of water stress, soil respiration, and the leaf-to-canopy scaling methodology. SiB2 tends to predict too much photosynthetic activity at low solar angles, while developing soil moisture stress before it is seen in the field. Systematic errors in energy balance terms (heat and water fluxes) occur for bare soil and dormant vegetation, related to simulation of soil heat flux. Daytime errors in sensible and latent heat fluxes average 20Wm−2, and can be more than 100Wm−2 at certain times. In regional and global climate models, the effect of land surface sub-model errors on atmospheric dynamics will depend in part on the magnitude of the systematic error, but also on the spatial extent and temporal duration over which the systematic error persists. [Copyright &y& Elsevier]

Abstract: We analyzed net CO2 exchange data from 13 flux tower sites with 27 site-years of measurements over maize and wheat fields across midcontinent North America. A numerically robust “light-soil temperature-VPD”-based method was used to partition the data into photosynthetic assimilation and ecosystem respiration components. Year-round ecosystem-scale ecophysiological parameters of apparent quantum yield, photosynthetic capacity, convexity of the light response, respiration rate parameters, ecological light-use efficiency, and the curvature of the VPD-response of photosynthesis for maize and wheat crops were numerically identified and interpolated/extrapolated. This allowed us to gap-fill CO2 exchange components and calculate annual totals and budgets. VPD-limitation of photosynthesis was systematically observed in grain crops of the region (occurring from 20 to 120 days during the growing season, depending on site and year), determined by the VPD regime and the numerical value of the curvature parameter of the photosynthesis-VPD-response, σ VPD. In 78% of the 27 site-years of observations, annual gross photosynthesis in these crops significantly exceeded ecosystem respiration, resulting in a net ecosystem production of up to 2100g CO2 m−2 year−1. The measurement-based photosynthesis, respiration, and net ecosystem production data, as well as the estimates of the ecophysiological parameters, provide an empirical basis for parameterization and validation of mechanistic models of grain crop production in this economically and ecologically important region of North America. [Copyright &y& Elsevier]

Abstract: The global savanna biome is characterized by enormous diversity in the physiognomy and spatial structure of the vegetation. The foliage clumping index can be calculated from bidirectional reflectance distribution function (BRDF) data. It measures the response of the darkspot reflectance to increased shadow associated with clumped vegetation and is related to leaf area index. Clumping index theoretically declines with increasing woody cover until the tree canopy begins to become uniform. In this study, clumping index is calculated for Moderate Resolution Imaging Spectroradiometer BRDF data for the Australian tropical savanna, the tropical savannas of South America, and the tropical savannas of east, west and southern Africa and compared with site-based measurements of tree canopy cover, and with area-based classifications of land cover. There were differences in sensitivity of clumping index between red and near-infrared reflectance channels, and between savanna systems with markedly different woody vegetation physiognomy. Clumping index was broadly related to foliage cover from historical site data in Australia and in West Africa and Kenya, but not in Southern Africa nor with detailed site-based demographic data in the cerrado of Brazil. However, clumping index decreased with proportion of woody cover in land cover datasets for east Africa, Australia and the Colombian Llanos. There was overlap in the range of clumping index values for forest, cerrado and campo land covers in Brazil. Clumping index was generally negatively correlated with percentage tree cover from the MODIS Vegetation Continuous Fields product, but regional differences in the relationship were evident. There were large differences in the frequency distributions of clumping index from savanna, woody savanna and grassland land cover classes between global ecoregions. The clumping index shows differing sensitivity to savanna woody cover for red and NIR reflectance, and requires regional calibration for application as a universal indicator. [Copyright &y& Elsevier]