Predicting the environmental responses of leaf photosynthesis is central to many models of changes in the future global carbon cycle and terrestrial biosphere. The steady-state biochemical model of C3 photosynthesis of Farquhar et al. (Planta 149, 78–90, 1980) provides a basis for these larger scale predictions; but a weakness in the application of the model as currently parameterized is the inability to accurately predict carbon assimilation at the range of temperatures over which significant photosynthesis occurs in the natural environment. The temperature functions used in this model have been based on in vitro measurements made over a limited temperature range and require several assumptions of in vivo conditions. Since photosynthetic rates are often Rubisco-limited (ribulose, 1-5 bisphosphate carboxylase/oxygenase) under natural steady-state conditions, inaccuracies in the functions predicting Rubisco kinetic properties at different temperatures may cause significant error. In this study, transgenic tobacco containing only 10% normal levels of Rubisco were used to measure Rubisco-limited photosynthesis over a large range of CO2 concentrations. From the responses of the rate of CO2 assimilation at a wide range of temperatures, and CO2 and O2 concentrations, the temperature functions of Rubisco kinetic properties were estimated in vivo. These differed substantially from previously published functions. These new functions were then used to predict photosynthesis in lemon and found to faithfully mimic the observed pattern of temperature response. There was also a close correspondence with published C3 photosynthesis temperature responses. The results represent an improved ability to model leaf photosynthesis over a wide range of temperatures (10–40 °C) necessary for predicting carbon uptake by terrestrial C3 systems.
The proliferation of digital cameras co‐located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra‐annual and interannual variability in canopy photosynthesis. We used 59 site‐years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needleleaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.
Abstract Perennial crops have been the focus of bioenergy research and development for their sustainability benefits associated with high soil carbon (C) and reduced nitrogen (N) requirements. However, perennial crops mature over several years and their sustainability benefits can be negated through land reversion. A photoperiod‐sensitive energy sorghum ( Sorghum bicolor ) may provide an annual crop alternative more ecologically sustainable than maize ( Zea mays ) that can more easily integrate into crop rotations than perennials, such as miscanthus ( Miscanthus × giganteus ). This study presents an ecosystem‐scale comparison of C, N, water and energy fluxes from energy sorghum, maize and miscanthus during a typical growing season in the Midwest United States. Gross primary productivity (GPP) was highest for maize during the peak growing season at 21.83 g C m −2 day −1 , followed by energy sorghum (17.04 g C m −2 day −1 ) and miscanthus (15.57 g C m −2 day −1 ). Maize also had the highest peak growing season evapotranspiration at 5.39 mm day −1 , with energy sorghum and miscanthus at 3.81 and 3.61 mm day −1 , respectively. Energy sorghum was the most efficient water user (WUE), while maize and miscanthus were comparatively similar (3.04, 1.75 and 1.89 g C mm −1 H 2 O, respectively). Maize albedo was lower than energy sorghum and miscanthus (0.19, 0.26 and 0.24, respectively), but energy sorghum had a Bowen ratio closer to maize than miscanthus (0.12, 0.13 and 0.21, respectively). Nitrous oxide (N 2 O) flux was higher from maize and energy sorghum (8.86 and 12.04 kg N ha −1 , respectively) compared with miscanthus (0.51 kg N ha −1 ), indicative of their different agronomic management. These results are an important first look at how energy sorghum compares to maize and miscanthus grown in the Midwest United States. This quantitative assessment is a critical component for calibrating biogeochemical and ecological models used to forecast bioenergy crop growth, productivity and sustainability.
Abstract The introduction of new crops to agroecosystems can change the chemical composition of the atmosphere by altering the amount and type of plant‐derived biogenic volatile organic compounds ( BVOC s). BVOC s are produced by plants to aid in defense, pollination, and communication. Once released into the atmosphere, they have the ability to influence its chemical and physical properties. In this study, we compared BVOC emissions from three potential bioenergy crops and estimated their theoretical impacts on bioenergy agroecosystems. The crops chosen were miscanthus ( M iscanthus × giganteus ), switchgrass ( P anicum virgatum ), and an assemblage of prairie species (mix of ~28 species). The concentration of BVOC s was different within and above plant canopies. All crops produced higher levels of emissions at the upper canopy level. Miscanthus produced lower amounts of volatiles compared with other grasses. The chemical composition of volatiles differed significantly among plant communities. BVOC s from miscanthus were depleted in terpenoids relative to the other vegetation types. The carbon flux via BVOC emissions, calculated using the flux‐gradient method, was significantly higher in the prairie assemblage compared with miscanthus and switchgrass. The BVOC carbon flux was approximately three orders of magnitude lower than the net fluxes of carbon measured over the same fields using eddy covariance systems. Extrapolation of our findings to the landscape scale leads us to suggest that the widespread adoption of bioenergy crops could potentially alter the composition of BVOC s in the atmosphere, thereby influencing its warming potential, the formation of atmospheric particulates, and interactions between plants and arthropods. Our data and projections indicate that, among at least these three potential options for bioenergy production, miscanthus is likely to have lower impacts on atmospheric chemistry and biotic interactions mediated by these volatiles when miscanthus is planted on the landscape scale.
Abstract Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ∼ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ∼ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p < 0.001) while non-physiological signals of SIF did not respond ( p > 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)