Spatial and temporal variability of pCO2 and CO2 efflux in seven Amazonian Rivers

Current estimates of CO₂ outgassing from Amazonian rivers and streams have considerable uncertainty since they are based on limited-time surveys of pCO₂ measurements along the Amazon mainstem and mouths of major tributaries, using conservative estimates of gas exchange velocities. In order to refine basin-scale CO₂ efflux estimates from Amazonian rivers, we present a long time (5-year) dataset of direct measurements of CO₂ fluxes, gas transfer velocities and pCO₂ measurements in seven representative rivers of the lowland Amazon basin fluvial network, six non-tidal (Negro, Solimões, Teles Pires, Cristalino, Araguaia and Javaés) and one tidal river (Caxiuanã), with sizes ranging from 4th to 9th order. Surveys were conducted from January 2006 to December 2010, in a total of 389 campaigns covering all stages of their hydrographs. CO₂ fluxes and gas transfer velocities (k) were measured using floating chambers and pCO₂ was measured simultaneously by headspace extraction followed by gas chromatography analysis. Results show high CO₂ flux rate variability among rivers and hydrograph stages, ranging from ?0.8 to 15.3 μmol CO₂ m^?2 s^?1, with unexpected negative fluxes in clear-water rivers during low waters. Non-tidal rivers showed marked seasonal CO₂ flux patterns, with significantly higher exchange during high waters. Seasonality was modulated by pCO₂, which was positive and strongly correlated with discharge. In these rivers k was well correlated with wind speed, which allowed the use of wind data to model k. We estimate a release of 360 ± 60 Tg C year^?1 from Amazonian rivers and streams within a 1.47 million km² quadrant in the central lowland Amazon. Extrapolating these values to the basin upstream of Óbidos, results in an outgassing of 0.8 Pg C to the atmosphere each year. Our results are a step forward in achieving more accurate gas emission values for Amazonian rivers and their role in the annual carbon budget of the Amazon basin.     

A new estimation of global soil greenhouse gas fluxes using a simple data-oriented model

Soil greenhouse gas fluxes (particularly CO₂, CH₄, and N₂O) play important roles in climate change. However, despite the importance of these soil greenhouse gases, the number of reports on global soil greenhouse gas fluxes is limited. Here, new estimates are presented for global soil CO₂ emission (total soil respiration), CH₄ uptake, and N₂O emission fluxes, using a simple data-oriented model. The estimated global fluxes for CO₂ emission, CH₄ uptake, and N₂O emission were 78 Pg C yr⁻¹ (Monte Carlo 95% confidence interval, 64–95 Pg C yr⁻¹), 18 Tg C yr⁻¹ (11–23 Tg C yr⁻¹), and 4.4 Tg N yr⁻¹ (1.4–11.1 Tg N yr⁻¹), respectively. Tropical regions were the largest contributor of all of the gases, particularly the CO₂ and N₂O fluxes. The soil CO₂ and N₂O fluxes had more pronounced seasonal patterns than the soil CH₄ flux. The collected estimates, including both the previous and the present estimates, demonstrate that the means of the best estimates from each study were 79 Pg C yr⁻¹ (291 Pg CO₂ yr⁻¹; coefficient of variation, CV = 13%, N = 6) for CO₂, 21 Tg C yr⁻¹ (29 Tg CH₄ yr⁻¹; CV = 24%, N = 24) for CH₄, and 7.8 Tg N yr⁻¹ (12.2 Tg N₂O yr⁻¹; CV = 38%, N = 11) for N₂O. For N₂O, the mean of the estimates that was calculated by excluding the earliest two estimates was 6.6 Tg N yr⁻¹ (10.4 Tg N₂O yr⁻¹; CV = 22%, N = 9). The reported estimates vary and have large degrees of uncertainty but their overall magnitudes are in general agreement. To further minimize the uncertainty of soil greenhouse gas flux estimates, it is necessary to build global databases and identify key processes in describing global soil greenhouse gas fluxes.     

The metabolic origins of non-photorespiratory CO2 release during photosynthesis: a metabolic flux analysis

Respiration in the light (R_L) releases CO₂ in photosynthesizing leaves and is a phenomenon that occurs independently from photorespiration. Since R_L lowers net carbon fixation, understanding R_L could help improve plant carbon-use efficiency and models of crop photosynthesis. Although R_L was identified more than 75 years ago, its biochemical mechanisms remain unclear. To identify reactions contributing to R_L, we mapped metabolic fluxes in photosynthesizing source leaves of the oilseed crop and model plant camelina (Camelina sativa). We performed a flux analysis using isotopic labeling patterns of central metabolites during ¹³CO₂ labeling time course, gas exchange, and carbohydrate production rate experiments. To quantify the contributions of multiple potential CO₂ sources with statistical and biological confidence, we increased the number of metabolites measured and reduced biological and technical heterogeneity by using single mature source leaves and quickly quenching metabolism by directly injecting liquid N₂; we then compared the goodness-of-fit between these data and data from models with alternative metabolic network structures and constraints. Our analysis predicted that R_L releases 5.2 μmol CO₂ g⁻¹ FW h⁻¹ of CO₂, which is relatively consistent with a value of 9.3 μmol CO₂ g⁻¹ FW h⁻¹ measured by CO₂ gas exchange. The results indicated that ≤10% of R_L results from TCA cycle reactions, which are widely considered to dominate R_L. Further analysis of the results indicated that oxidation of glucose-6-phosphate to pentose phosphate via 6-phosphogluconate (the G6P/OPP shunt) can account for >93% of CO₂ released by R_L.     

Quantitative analysis of photosynthetic carbon metabolism in protoplasts and intact leaves of barley. Determination of carbon fluxes and pool sizes of metabolites in different cellular compartments

Rates of carbon fluxes and pool sizes of photosynthetic metabolites in different cellular compartments of barley protoplasts were calculated from the time curves of their labeling in the medium of ¹⁴CO₂. Using membrane filtration procedure, kinetics of ¹⁴C incorporation into the products of steady-state photosynthesis was determined separately in chloroplasts, mitochondria and cytosol of barley protoplasts illuminated for different periods in the air containing ¹⁴CO₂. To extract the quantitative information, analytical labeling functions P(t) describing the dependence of ¹⁴C content in the primary, intermediate and end products of a linear reaction chain upon the duration of tracer feeding have been derived. The parameters of these functions represent pool sizes of metabolites and rates of carbon fluxes. The values of these parameters were determined by fitting the experimental labeling curves to the functions P(t) by means of non-linear regression procedure. To elucidate the possible effects of fractionation on the photosynthetic carbon metabolism, the parameters of protoplasts were compared with corresponding values in intact leaves of barley.     

A new model of net ecosystem carbon exchange for the deciduous-dominated forest by integrating MODIS and flux data

The eddy covariance technique provides continuous measurements of plot-level net ecosystem carbon exchange (NEE) across a wide range of vegetation types. However, these NEE estimates only represent fluxes at the tower footprint scale. To quantify the NEE over regions or continents, flux tower measurements need to be up-scaled to large areas. In the present study, we propose a new NEE model solely based on Moderate Resolution Imaging Spectroradiometer data, including enhanced vegetation index (EVI), land surface water index (LWSI), land surface temperature (LST), and Terra nighttime LST′. Site-specific data from the deciduous-dominated Harvard Forest flux site were used. Analysis covered six years (2001-2006) of CO₂ flux data. The data of the first four years were used for model building and the rest as validation set. Compared with the model based solely on EVI, we also introduced LST and LSWI into the new model. The results showed that this method could further improve the precision (R² and RMSE reached 0.857 and 1.273, respectively) and generally capture the expected seasonal patterns of NEE.     

Kinetic isotope effects significantly influence intracellular metabolite 13C labeling patterns and flux determination

Rigorous mathematical modeling of carbon-labeling experiments allows estimation of fluxes through the pathways of central carbon metabolism, yielding powerful information for basic scientific studies as well as for a wide range of applications. However, the mathematical models that have been developed for flux determination from ¹³C labeling data have commonly neglected the influence of kinetic isotope effects on the distribution of ¹³C label in intracellular metabolites, as these effects have often been assumed to be inconsequential. We have used measurements of the ¹³C isotope effects on the pyruvate dehydrogenase enzyme from the literature to model isotopic fractionation at the pyruvate node and quantify the modeling errors expected to result from the assumption that isotope effects are negligible. We show that under some conditions kinetic isotope effects have a significant impact on the ¹³C labeling patterns of intracellular metabolites, and the errors associated with neglecting isotope effects in ¹³C-metabolic flux analysis models can be comparable in size to measurement errors associated with GC–MS. Thus, kinetic isotope effects must be considered in any rigorous assessment of errors in ¹³C labeling data, goodness-of-fit between model and data, confidence intervals of estimated metabolic fluxes, and statistical significance of differences between estimated metabolic flux distributions.     

Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver

Computational models based on the metabolism of stable isotope tracers can yield valuable insight into the metabolic basis of disease. The complexity of these models is limited by the number of tracers and the ability to characterize tracer labeling in downstream metabolites. NMR spectroscopy is ideal for multiple tracer experiments since it precisely detects the position of tracer nuclei in molecules, but it lacks sensitivity for detecting low-concentration metabolites. GC-MS detects stable isotope mass enrichment in low-concentration metabolites, but lacks nuclei and positional specificity. We performed liver perfusions and in vivo infusions of ²H and ¹³C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from ²H and ¹³C NMR positional isotopomer enrichments served to validate GC-MS-based flux estimates obtained from the same experimental samples. NMR-derived fluxes were largely recapitulated by modeling the mass isotopomer distributions of six glucose fragment ions measured by GC-MS. Modest differences related to limited fragmentation coverage of glucose C1–C3 were identified, but fluxes such as gluconeogenesis, glycogenolysis, cataplerosis and TCA cycle flux were tightly correlated between the methods. Most importantly, modeling of GC-MS data could assign fluxes in primary mouse hepatocytes, an experiment that is impractical by ²H or ¹³C NMR.     

Spatial variation in landscape‐level CO2 and CH4 fluxes from arctic coastal tundra: influence from vegetation,wetness, and the thaw lake cycle

Regional quantification of arctic CO₂ and CH₄ fluxes remains difficult due to high landscape heterogeneity coupled with a sparse measurement network. Most of the arctic coastal tundra near Barrow, Alaska is part of the thaw lake cycle, which includes current thaw lakes and a 5500‐year chronosequence of vegetated thaw lake basins. However, spatial variability in carbon fluxes from these features remains grossly understudied. Here, we present an analysis of whole‐ecosystem CO₂ and CH₄ fluxes from 20 thaw lake cycle features during the 2011 growing season. We found that the thaw lake cycle was largely responsible for spatial variation in CO₂ flux, mostly due to its control on gross primary productivity (GPP). Current lakes were significant CO₂ sources that varied little. Vegetated basins showed declining GPP and CO₂ sink with age (R² = 67% and 57%, respectively). CH₄ fluxes measured from a subset of 12 vegetated basins showed no relationship with age or CO₂ flux components. Instead, higher CH₄ fluxes were related to greater landscape wetness (R² = 57%) and thaw depth (additional R² = 28%). Spatial variation in CO₂ and CH₄ fluxes had good satellite remote sensing indicators, and we estimated the region to be a small CO₂ sink of ?4.9 ± 2.4 (SE) g C m^?2 between 11 June and 25 August, which was countered by a CH₄ source of 2.1 ± 0.2 (SE) g C m^?2. Results from our scaling exercise showed that developing or validating regional estimates based on single tower sites can result in significant bias, on average by a factor 4 for CO₂ flux and 30% for CH₄ flux. Although our results are specific to the Arctic Coastal Plain of Alaska, the degree of landscape‐scale variability, large‐scale controls on carbon exchange, and implications for regional estimation seen here likely have wide relevance to other arctic landscapes.     

Partitioning net ecosystem carbon exchange with isotopic fluxes of CO2

Because biological and physical processes alter the stable isotopic composition of atmospheric CO₂, variations in isotopic content can be used to investigate those processes. Isotopic flux measurements of ¹³CO₂ above terrestrial ecosystems can potentially be used to separate net ecosystem CO₂ exchange (NEE) into its component fluxes, net photosynthetic assimilation (F_A) and ecosystem respiration (F_R). In this paper theory is developed to partition measured NEE into F_A and F_R, using measurements of fluxes of CO₂ and ¹³CO₂, and isotopic composition of respired CO₂ and forest air. The theory is then applied to fluxes measured (or estimated, for ¹³CO₂) in a temperate deciduous forest in eastern Tennessee (Walker Branch Watershed). It appears that there is indeed enough additional information in ¹³CO₂ fluxes to partition NEE into its photosynthetic and respiratory components. Diurnal patterns in F_A and F_R were obtained, which are consistent in magnitude and shape with patterns obtained from NEE measurements and an exponential regression between night‐time NEE and temperature (a standard technique which provides alternate estimates of F_R and F_A). The light response curve for photosynthesis (F_A vs. PAR) was weakly nonlinear, indicating potential for saturation at high light intensities. Assimilation‐weighted discrimination against ¹³CO₂ for this forest during July 1999 was 16.8–17.1‰, depending on canopy conductance. The greatest uncertainties in this approach lie in the evaluation of canopy conductance and its effect on whole‐canopy photosynthetic discrimination, and thus the indirect methods used to estimate isotopic fluxes. Direct eddy covariance measurements of ¹³CO₂ flux are needed to assess the validity of the assumptions used and provide defensible isotope‐based estimates of the component fluxes of net ecosystem exchange.     

Linking Annual N2O Emission in Organic Soils to Mineral Nitrogen Input as Estimated by Heterotrophic Respiration and Soil C/N Ratio

Organic soils are an important source of N₂O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N₂O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO₂ flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO₂ and N₂O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N₂O fluxes, whereas CO₂ flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N₂O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N₂O flux. Our proposed approach, which uses the product of soil-derived CO₂ flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N₂O fluxes from organic soils, although some further enhancements may be warranted.     

Gross primary productivity and transpiration flux of the Australian vegetation from 1788 to 1988 AD: effects of CO2 and land use change

We present a novel approach to estimating the transpiration flux and gross primary productivity (GPP) from Normalized Difference Vegetation Index, leaf functional types, and readily available climate data. We use this approach to explore the impact of variations in the concentration of carbon dioxide in the atmosphere ([CO₂]) and consequent predicted changes in vegetation cover, on the transpiration flux and GPP. There was a near 1 : 1 relationship between GPP estimated with this transpiration flux approach and that estimated using a radiation‐use efficiency (RUE) approach. Model estimates are presented for the Australian continent under three vegetation–[CO₂] scenarios: the present vegetation and hypothetical ‘natural’ vegetation cover with atmospheric CO₂ concentration ([CO₂]) of 350 μmol mol^?1 (pveg₃₅₀ and nveg₃₅₀), and for the ‘natural’ vegetation with [CO₂] 280 μmol mol^?1 (nveg₂₈₀). Estimated continental GPP is 6.5, 6.3 and 4.3 Gt C yr^?1 for pveg₃₅₀, nveg₃₅₀ and nveg₂₈₀, respectively_. The corresponding transpiration fluxes are 232, 224 and 190 mm H₂O yr^?1. The contribution of the raingreen and evergreen components of the canopy to these fluxes are also estimated.     

Estimating Relative Changes of Metabolic Fluxes

Fluxes are the central trait of metabolism and Kinetic Flux Profiling (KFP) is an effective method of measuring them. To generalize its applicability, we present an extension of the method that estimates the relative changes of fluxes using only relative quantitation of ¹³C-labeled metabolites. Such features are directly tailored to the more common experiment that performs only relative quantitation and compares fluxes between two conditions. We call our extension rKFP. Moreover, we examine the effects of common missing data and common modeling assumptions on (r)KFP, and provide practical suggestions. We also investigate the selection of measuring times for (r)KFP and provide a simple recipe. We then apply rKFP to ¹³C-labeled glucose time series data collected from cells under normal and glucose-deprived conditions, estimating the relative flux changes of glycolysis and its branching pathways. We identify an adaptive response in which de novo serine biosynthesis is compromised to maintain the glycolytic flux backbone. Together, these results greatly expand the capabilities of KFP and are suitable for broad biological applications.     

The role of light in soybean seed filling metabolism

Soybean (Glycine max) yields high levels of both protein and oil, making it one of the most versatile and important crops in the world. Light has been implicated in the physiology of developing green seeds including soybeans but its roles are not quantitatively understood. We have determined the light levels reaching growing soybean embryos under field conditions and report detailed redox and energy balance analyses for them. Direct flux measurements and labeling patterns for multiple labeling experiments including [U‐¹³C₆]‐glucose, [U‐¹³C₅]‐glutamine, the combination of [U‐¹⁴C₁₂]‐sucrose + [U‐¹⁴C₆]‐glucose + [U‐¹⁴C₅]‐glutamine + [U‐¹⁴C₄]‐asparagine, or ¹⁴CO₂ labeling were performed at different light levels to give further insight into green embryo metabolism during seed filling and to develop and validate a flux map. Labeling patterns (protein amino acids, triacylglycerol fatty acids, starch, cell wall, protein glycan monomers, organic acids), uptake fluxes (glutamine, asparagine, sucrose, glucose), fluxes to biomass (protein amino acids, oil), and respiratory fluxes (CO₂, O₂) were established by a combination of gas chromatography‐mass spectrometry, ¹³C‐ and ¹H‐NMR, scintillation counting, HPLC, gas chromatography‐flame ionization detection, C:N and amino acid analyses, and infrared gas analysis, yielding over 750 measurements of metabolism. Our results show: (i) that developing soybeans receive low but significant light levels that influence growth and metabolism; (ii) a role for light in generating ATP but not net reductant during seed filling; (iii) that flux through Rubisco contributes to carbon conversion efficiency through generation of 3‐phosphoglycerate; and (iv) a larger contribution of amino acid carbon to fatty acid synthesis than in other oilseeds analyzed to date.     

13C Metabolic Flux Analysis Identifies an Unusual Route for Pyruvate Dissimilation in Mycobacteria which Requires Isocitrate Lyase and Carbon Dioxide Fixation

Mycobacterium tuberculosis requires the enzyme isocitrate lyase (ICL) for growth and virulence in vivo. The demonstration that M. tuberculosis also requires ICL for survival during nutrient starvation and has a role during steady state growth in a glycerol limited chemostat indicates a function for this enzyme which extends beyond fat metabolism. As isocitrate lyase is a potential drug target elucidating the role of this enzyme is of importance; however, the role of isocitrate lyase has never been investigated at the level of in vivo fluxes. Here we show that deletion of one of the two icl genes impairs the replication of Mycobacterium bovis BCG at slow growth rate in a carbon limited chemostat. In order to further understand the role of isocitrate lyase in the central metabolism of mycobacteria the effect of growth rate on the in vivo fluxes was studied for the first time using ¹³C-metabolic flux analysis (MFA). Tracer experiments were performed with steady state chemostat cultures of BCG or M. tuberculosis supplied with ¹³C labeled glycerol or sodium bicarbonate. Through measurements of the ¹³C isotopomer labeling patterns in protein-derived amino acids and enzymatic activity assays we have identified the activity of a novel pathway for pyruvate dissimilation. We named this the GAS pathway because it utilizes the Glyoxylate shunt and Anapleurotic reactions for oxidation of pyruvate, and Succinyl CoA synthetase for the generation of succinyl CoA combined with a very low flux through the succinate – oxaloacetate segment of the tricarboxylic acid cycle. We confirm that M. tuberculosis can fix carbon from CO₂ into biomass. As the human host is abundant in CO₂ this finding requires further investigation in vivo as CO₂ fixation may provide a point of vulnerability that could be targeted with novel drugs. This study also provides a platform for further studies into the metabolism of M. tuberculosis using ¹³C-MFA.     

13CO2 labeling kinetics in maize reveal impaired efficiency of C4 photosynthesis under low irradiance

C₄ photosynthesis allows faster photosynthetic rates and higher water and nitrogen use efficiency than C₃ photosynthesis, but at the cost of lower quantum yield due to the energy requirement of its biochemical carbon concentration mechanism. It has also been suspected that its operation may be impaired in low irradiance. To investigate fluxes under moderate and low irradiance, maize (Zea mays) was grown at 550 µmol photons m⁻² s^−l and ¹³CO₂ pulse-labeling was performed at growth irradiance or several hours after transfer to 160 µmol photons m⁻² s⁻¹. Analysis by liquid chromatography/tandem mass spectrometry or gas chromatography/mass spectrometry provided information about pool size and labeling kinetics for 32 metabolites and allowed estimation of flux at many steps in C₄ photosynthesis. The results highlighted several sources of inefficiency in low light. These included excess flux at phosphoenolpyruvate carboxylase, restriction of decarboxylation by NADP-malic enzyme, and a shift to increased CO₂ incorporation into aspartate, less effective use of metabolite pools to drive intercellular shuttles, and higher relative and absolute rates of photorespiration. The latter provides evidence for a lower bundle sheath CO₂ concentration in low irradiance, implying that operation of the CO₂ concentration mechanism is impaired in this condition. The analyses also revealed rapid exchange of carbon between the Calvin–Benson cycle and the CO₂-concentration shuttle, which allows rapid adjustment of the balance between CO₂ concentration and assimilation, and accumulation of large amounts of photorespiratory intermediates in low light that provides a major carbon reservoir to build up C₄ metabolite pools when irradiance increases.

Analysis of metabolite pools, sizes, and fluxes reveals that multiple interlocking factors decrease the efficiency of photosynthesis in low irradiance in maize.     

Process-level controls on CO<Subscript>2</Subscript> fluxes from a seasonally snow-covered subalpine meadow soil,Niwot Ridge,Colorado

Fluxes of CO₂ during the snow-covered season contribute to annual carbon budgets, but our understanding of the mechanisms controlling the seasonal pattern and magnitude of carbon emissions in seasonally snow-covered areas is still developing. In a subalpine meadow on Niwot Ridge, Colorado, soil CO₂ fluxes were quantified with the gradient method through the snowpack in winter 2006 and 2007 and with chamber measurements during summer 2007. The CO₂ fluxes of 0.71 μmol m⁻² s⁻¹ in 2006 and 0.86 μmol m⁻² s⁻¹ in 2007 are among the highest reported for snow-covered ecosystems in the literature. These fluxes resulted in 156 and 189 g C m⁻² emitted over the winter, ~30% of the annual soil CO₂ efflux at this site. In general, the CO₂ flux increased during the winter as soil moisture increased. A conceptual model was developed with distinct snow cover zones to describe this as well as the three other reported temporal patterns in CO₂ flux from seasonally snow-covered soils. As snow depth and duration increase, the factor controlling the CO₂ flux shifts from freeze–thaw cycles (zone I) to soil temperature (zone II) to soil moisture (zone III) to carbon availability (zone IV). The temporal pattern in CO₂ flux in each zone changes from periodic pulses of CO₂ during thaw events (zone I), to CO₂ fluxes reaching a minimum when soil temperatures are lowest in mid-winter (zone II), to CO₂ fluxes increasing gradually as soil moisture increases (zone III), to CO₂ fluxes decreasing as available carbon is consumed. This model predicts that interannual variability in snow cover or directional shifts in climate may result in dramatically different seasonal patterns of CO₂ flux from seasonally snow-covered soils.     

Seasonal patterns in soil surface CO<Subscript>2</Subscript> flux under snow cover in 50 and 300 year old subalpine forests

Soil CO₂ flux can contribute as much as 60–80% of total ecosystem respiration in forests. Although considerable research has focused on quantifying this flux during the growing season, comparatively little effort has focused on non-growing season fluxes. We measured soil CO₂ efflux through snow in 50 and ~300 year old subalpine forest stands near Fraser CO. Our objectives were to quantify seasonal patterns in wintertime soil CO₂ flux; determine if differences in soil CO₂ flux between the two forest ages during the growing season persist during winter; and to quantify the sample size necessary to discern treatment differences. Soil CO₂ flux during the 2002–2003 and 2003–2004 snow season averaged 0.31 and 0.35 μmols m⁻² s⁻¹ for the young and old forests respectively; similar to the relative difference observed during summer. There was a significant seasonal pattern of soil CO₂ flux during the winter with fluxes averaging 0.22 μmols m⁻² s⁻¹ in December and January and increasing to an average of 0.61 μmols m⁻² s⁻¹ in May. Within-plot variability for measurements used in calculating flux was low. The coefficients of variation (CV) for CO₂ concentration, snowpack density, and snow depth were 17, 8 and 14%, respectively, yielding a CV for flux measurements within-plot of 29%. A within plot CV of 29% requires 8 sub-samples per plot to estimate the mean flux with a standard error of ±10% of the mean. Variability in CO₂ flux estimates among plots (size = 400 m²) was similar to that within plot and was also low (CV = ~28%). With a CV of 28% among plots, ten plots per treatment would have a 50% probability of detecting a 25% difference in treatment means for α = 0.05.     

Metabolic flux analysis of Cyanothece sp. ATCC 51142 under mixotrophic conditions

Cyanobacteria are a group of photosynthetic prokaryotes capable of utilizing solar energy to fix atmospheric carbon dioxide to biomass. Despite several “proof of principle” studies, low product yield is an impediment in commercialization of cyanobacteria-derived biofuels. Estimation of intracellular reaction rates by ¹³C metabolic flux analysis (¹³C-MFA) would be a step toward enhancing biofuel yield via metabolic engineering. We report ¹³C-MFA for Cyanothece sp. ATCC 51142, a unicellular nitrogen-fixing cyanobacterium, known for enhanced hydrogen yield under mixotrophic conditions. Rates of reactions in the central carbon metabolism under nitrogen-fixing and -non-fixing conditions were estimated by monitoring the competitive incorporation of ¹²C and ¹³C from unlabeled CO₂ and uniformly labeled glycerol, respectively, into terminal metabolites such as amino acids. The observed labeling patterns suggest mixotrophic growth under both the conditions, with a larger fraction of unlabeled carbon in nitrate-sufficient cultures asserting a greater contribution of carbon fixation by photosynthesis and an anaplerotic pathway. Indeed, flux analysis complements the higher growth observed under nitrate-sufficient conditions. On the other hand, the flux through the oxidative pentose phosphate pathway and tricarboxylic acid cycle was greater in nitrate-deficient conditions, possibly to supply the precursors and reducing equivalents needed for nitrogen fixation. In addition, an enhanced flux through fructose-6-phosphate phosphoketolase possibly suggests the organism’s preferred mode under nitrogen-fixing conditions. The ¹³C-MFA results complement the reported predictions by flux balance analysis and provide quantitative insight into the organism’s distinct metabolic features under nitrogen-fixing and -non-fixing conditions.     

Carbon Flux Analysis by 13C Nuclear Magnetic Resonance To Determine the Effect of CO2 on Anaerobic Succinate Production by Corynebacterium glutamicum

Wild-type Corynebacterium glutamicum produces a mixture of lactic, succinic, and acetic acids from glucose under oxygen deprivation. We investigated the effect of CO₂ on the production of organic acids in a two-stage process: cells were grown aerobically in glucose, and subsequently, organic acid production by nongrowing cells was studied under anaerobic conditions. The presence of CO₂ caused up to a 3-fold increase in the succinate yield (1 mol per mol of glucose) and about 2-fold increase in acetate, both at the expense of l-lactate production; moreover, dihydroxyacetone formation was abolished. The redistribution of carbon fluxes in response to CO₂ was estimated by using ¹³C-labeled glucose and ¹³C nuclear magnetic resonance (NMR) analysis of the labeling patterns in end products. The flux analysis showed that 97% of succinate was produced via the reductive part of the tricarboxylic acid cycle, with the low activity of the oxidative branch being sufficient to provide the reducing equivalents needed for the redox balance. The flux via the pentose phosphate pathway was low (∼5%) regardless of the presence or absence of CO₂. Moreover, there was significant channeling of carbon to storage compounds (glycogen and trehalose) and concomitant catabolism of these reserves. The intracellular and extracellular pools of lactate and succinate were measured by in vivo NMR, and the stoichiometry (H⁺:organic acid) of the respective exporters was calculated. This study shows that it is feasible to take advantage of natural cellular regulation mechanisms to obtain high yields of succinate with C. glutamicum without genetic manipulation.     

Contribution of the polychaete,Neanthes japonica (Izuka), to the oxygen uptake and carbon dioxide production of an intertidal mud-flat of the Nanakita River estuary,Japan

The benthic oxygen consumption and carbon dioxide production of undisturbed and sieved sediment cores with various values for the biomass of polychaetes collected from the intertidal mud-flat of Nanakita River estuary of Japan were measured simultaneously. The benthic oxygen consumption and carbon dioxide production increased in proportion to the biomass of a dominant polychaete species Neanthes japonica (Izuka). This increase was not explained by the respiration of the animals alone. The residual increase in benthic O₂ and CO₂ fluxes may be due to mineralization processes in the burrow wall and enhanced diffusion caused by the pumping activity of the worms. From the average biomass of polychaetes at the study site, total benthic O₂ and CO₂ fluxes were estimated to be 5.2 mmol·m⁻²·h⁻¹ and 7.3 mmol·m⁻²·h⁻¹, respectively, at 20 ° C. The worms were responsible for 79% of the total O₂ flux and 73% of the total CO₂ flux but the respiration of the worms accounted for only 53% of the total O₂ flux and 36% of the total CO₂ flux. The residual enhanced fluxes were 26% and 37% for the total O₂ and CO₂ fluxes, respectively.