Regulation of L-alanine dehydrogenase in Rhizobium leguminosarum bv. viciae and its role in pea nodules

Alanine dehydrogenase (AldA) is the principal enzyme with which pea bacteroids synthesize alanine de novo. In free-living culture, AMA activity is induced by carboxylic acids (succinate, malate, and pyruvate), although the best inducer is alanine. Measurement of the intracellular concentration of alanine showed that AldA contributes to net alanine synthesis in laboratory cultures. Divergently transcribed from aldA is an AsnC type regulator, aldR. Mutation of aldR prevents induction of AldA activity. Plasmid-borne gusA fusions showed that aldR is required for transcription of both aldA and aldR; hence, AldR is autoregulatory. However, plasmid fusions containing the aldA-aldR intergenic region could apparently titrate out AldR, sometimes resulting in a complete loss of AldA enzyme activity. Therefore, integrated aldR::gusA and aldA::gusA fusions, as well as Northern blotting, were used to confirm the induction of aldA activity. Both aldA and aldR were expressed in the II/III interzone and zone III of pea nodules. Overexpression of aldA in bacteroids did not alter the ability of pea plants to fix nitrogen, as measured by acetylene reduction, but caused a large reduction in the size and dry weight of plants. This suggests that overexpression of aldA impairs the ability of bacteroids to donate fixed nitrogen that the plant can productively assimilate. We propose that the role of AldA may be to balance the alanine level for optimal functioning of bacteroid metabolism rather than to synthesize alanine as the sole product of N-2 reduction.

Metabolism of Rhizobium bacteroids

Nitrogen fixation within legume nodules results from a complex metabolic exchange between bacteria of the family Rhizobiaciae and the plant host. Carbon is supplied to the differentiated bacterial cells, termed bacteroids, in the form of dicarboxylic acids to fuel nitrogen fixation. In exchange, fixed nitrogen is transferred to the plant. Both the bacteroid and the plant-derived peribacteroid membrane tightly regulate the exchange of metabolites. In the bacteroid oxidation of dicarboxylic acids via the TCA cycle occurs in an oxygen-limited environment. This restricts the TCA cycle at key points, such as the 2-oxoglutarate dehydrogenase complex, and requires that inputs of carbon and reductant are balanced with outputs from the TCA cycle. This may be achieved by metabolism through accessory pathways that can remove intermediates, reductant, or ATP from the cycle. These include synthesis of the carbon polymers PHB and glycogen and bypass pathways such as the recently identified 2-oxoglutarate decarboxylase reaction in soybean bacteroids. Recent labeling data have shown that bacteroids synthesize and secrete amino acids, which has led to controversy over the role of amino acids in nodule metabolism. Here we review bacteroid carbon metabolism in detail, evaluate the labeling studies that relate to amino acid metabolism by bacteroids, and place the work in context with the genome sequences of Mesorhizobium loti and Sinorhizobium meliloti. We also consider a wider range of metabolic pathways that are probably of great importance to rhizobia in the rhizosphere, during nodule initiation, infection thread development, and bacteroid development.

A comparative evaluation of functions for partitioning nitrogen and amino acid intake between maintenance and growth in broilers

The results from three types of study with broilers, namely nitrogen (N) balance, bioassays and growth experiments, provided the data used herein. Sets of data on N balance and protein accretion (bioassay studies) were used to assess the ability of the monomolecular equation to describe the relationship between (i) N balance and amino acid (AA) intake and (ii) protein accretion and AA intake. The model estimated the levels of isoleucine, lysine, valine, threonine, methionine, total sulphur AAs and tryptophan resulting in zero balance to be 58, 59, 80, 96, 23, 85 and 32 mg/kg live weight (LW)/day, respectively. These estimates show good agreement with those obtained in previous studies. For the growth experiments, four models, specifically re-parameterized for analysing energy balance data, were evaluated for their ability to determine crude protein (CP) intake at maintenance and efficiency of utilization of CP intake for producing gain. They were: a straight line, two equations representing diminishing returns behaviour (monomolecular and rectangular hyperbola) and one equation describing smooth sigmoidal behaviour with a fixed point of inflexion (Gompertz). The estimates of CP requirement for maintenance and efficiency of utilization of CP intake for producing gain varied from 5.4 to 5.9 g/kg LW/day and 0.60 to 0.76, respectively, depending on the models.

Evaluation of milk urea nitrogen as a diagnostic of protein feeding

An evaluation of milk urea nitrogen (MUN) as a diagnostic of protein feeding in dairy cows was performed using mean treatment data (n = 306) from 50 production trials conducted in Finland (n = 48) and Sweden (n = 2). Data were used to assess the effects of diet composition and certain animal characteristics on MUN and to derive relationships between MUN and the efficiency of N utilization for milk production and urinary N excretion. Relationships were developed using regression analysis based on either models of fixed factors or using mixed models that account for between-experiment variations. Dietary crude protein (CP) content was the best single predictor of MUN and accounted for proportionately 0.778 of total variance [ MUN (mg/dL) = -14.2 + 0.17 x dietary CP content (g/kg dry matter)]. The proportion of variation explained by this relationship increased to 0.952 when a mixed model including the random effects of study was used, but both the intercept and slope remained unchanged. Use of rumen degradable CP concentration in excess of predicted requirements, or the ratio of dietary CP to metabolizable energy as single predictors, did not explain more of the variation in MUN (R-2 = 0.767 or 0.778, respectively) than dietary CP content. Inclusion of other dietary factors with dietary CP content in bivariate models resulted in only marginally better predictions of MUN (R-2 = 0.785 to 0.804). Closer relationships existed between MUN and dietary factors when nutrients (CP to metabolizable energy) were expressed as concentrations in the diet, rather than absolute intakes. Furthermore, both MUN and MUN secretion (g/d) provided more accurate predictions of urinary N excretion (R-2 = 0.787 and 0.835, respectively) than measurements of the efficiency of N utilization for milk production (R-2 = 0.769). It is concluded that dietary CP content is the most important nutritional factor influencing MUN, and that measurements of MUN can be utilized as a diagnostic of protein feeding in the dairy cow and used to predict urinary N excretion.

Impact of perturbations of nitrogen oxide emissions from global aviation

Short-range urban dispersion experiments using fixed and moving sources

Four perfluorocarbon tracer dispersion experiments were carried out in central London, United Kingdom in 2004. These experiments were supplementary to the dispersion of air pollution and penetration into the local environment (DAPPLE) campaign and consisted of ground level releases, roof level releases and mobile releases; the latter are believed to be the first such experiments to be undertaken. A detailed description of the experiments including release, sampling, analysis and wind observations is given. The characteristics of dispersion from the fixed and mobile sources are discussed and contrasted, in particular, the decay in concentration levels away from the source location and the additional variability that results from the non-uniformity of vehicle speed. Copyright © 2009 Royal Meteorological Society

Assessing nitrogen dynamics in European ecosystems, integrating measurement and modelling: conclusions

This contribution closes this special issue of Hydrology and Earth System Sciences concerning the assessment of nitrogen dynamics in catchments across Europe within a semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (INCA). New developments in the understanding of the factors and processes determining the concentrations and loads of nitrogen are outlined. The ability of the INCA model to simulate the hydrological and nitrogen dynamics of different European ecosystems is assessed and the results of the first scenario analyses investigating the impacts of deposition, climatic and land-use change on the nitrogen dynamics are summarised. Consideration is given as to how well the model has performed as a generic too] for describing the nitrogen dynamics of European ecosystems across Arctic, Maritime. Continental and Mediterranean climates, its role in new research initiatives and future research requirements.

Carbon (C-13) and nitrogen (N-15) translocation in a maize-Striga hermonthica association

The translocation of C and N in a maize-Striga hermonthica association was investigated at three rates of nitrogen application in a glasshouse experiment. The objectives were to measure the transfer of C and N from maize to S. hermonthica and to determine whether the amount of N in the growing medium affected the proportions of C and N transferred. Young plants of maize were labelled in a (CO2)-C-13 atmosphere and leaf tips were immersed in ((NH4)-N-15)(2)SO4 Solution. The Striga x N interaction was not significant for any of the responses measured. Total dry matter for infected maize was significantly smaller than for uninfected maize from 43 to 99 days after planting, but N application increased total dry matter at all sampling times. Infected maize plants partitioned 39-45 % of their total dry matter to the roots compared with 28-31 % for Uninfected maize. Dry matter of S. hermonthica was not affected by the rate of N applied. S. hermonthica derived 100 % of its carbon from maize before emergence, decreasing to 22-59 % thereafter; the corresponding values for nitrogen were up to 59 % pre-emergence and Lip to 100 % after emergence. The relative proportions of nitrogen depleted from the host (up to 10 %) were greater than those of carbon (maximum 1.2 %) at all times of sampling after emergence of the parasite. The results show that the parasite was more dependent on the host for nitrogen than for carbon.

Potassium budgets in grassland systems as affected by nitrogen and drainage

The main inputs, outputs and transfers of potassium (K) in soils and swards under typical south west England conditions were determined during 1999/00 and 2000/01 to establish soil and field gate K budgets under different fertilizer nitrogen (N) (0 and 280 kg ha(-1) yr(-1)) and drainage (undrained and drained) treatments. Plots receiving fertilizer N also received farmyard manure (FYM). Potassium soil budgets ranged, on average for the two years, from -5 (+N, drained) to +9 (no N and undrained) kg K ha(-1) yr(-1) and field gate budgets from +23 (+N, drained) to +89 (+N, undrained). The main inputs and outputs to the soil K budgets were fertilizer application (65%) and plant uptake (93%). Animals had a minor effect on K export but a major impact on K recycling. Nitrogen fertilizer application and drainage increased K uptake by the grass and, with it, the efficiency of K used. It also depleted easily available soil K, which could be associated with smaller K losses by leaching.

A geostatistical analysis of the spatial variation of soil mineral nitrogen and potentially available nitrogen within an arable field.

The technology for site-specific applications of nitrogen (N) fertilizer has exposed a gap in our knowledge about the spatial variation of soil mineral N, and that which will become available during the growing season within arable fields. Spring mineral N and potentially available N were measured in an arable field together with gravimetric water content, loss on ignition, crop yield, percentages of sand, silt, and clay, and elevation to describe their spatial variation geostatistically. The areas with a larger clay content had larger values of mineral N, potentially available N, loss on ignition and gravimetric water content, and the converse was true for the areas with more sandy soil. The results suggest that the spatial relations between mineral N and loss on ignition, gravimetric water content, soil texture, elevation and crop yield, and between potentially available N and loss on ignition and silt content could be used to indicate their spatial patterns. Variable-rate nitrogen fertilizer application would be feasible in this field because of the spatial structure and the magnitude of variation of mineral N and potentially available N.

Modelling stream and soil water nitrate dynamics during experimentally increased nitrogen deposition in a coniferous forest catchment at Gardsjon, Sweden

Increased atmospheric deposition of inorganic nitrogen (N) may lead to increased leaching of nitrate (NO3-) to surface waters. The mechanisms responsible for, and controls on, this leaching are matters of debate. An experimental N addition has been conducted at Gardsjon, Sweden to determine the magnitude and identify the mechanisms of N leaching from forested catchments within the EU funded project NITREX. The ability of INCA-N, a simple process-based model of catchment N dynamics, to simulate catchment-scale inorganic N dynamics in soil and stream water during the course of the experimental addition is evaluated. Simulations were performed for 1990-2002. Experimental N addition began in 1991. INCA-N was able to successfully reproduce stream and soil water dynamics before and during the experiment. While INCA-N did not correctly simulate the lag between the start of N addition and NO 2 3 breakthrough, the model was able to simulate the state change resulting from increased N deposition. Sensitivity analysis showed that model behaviour was controlled primarily by parameters related to hydrology and vegetation dynamics and secondarily by in-soil processes.

Modelling cereal root systems for water and nitrogen capture: Towards an economic optimum

A quantitative model of wheat root systems is developed that links the size and distribution of the root system to the capture of water and nitrogen (which are assumed to be evenly distributed with depth) during grain filling, and allows estimates of the economic consequences of this capture to be assessed. A particular feature of the model is its use of summarizing concepts, and reliance on only the minimum number of parameters (each with a clear biological meaning). The model is then used to provide an economic sensitivity analysis of possible target characteristics for manipulating root systems. These characteristics were: root distribution with depth, proportional dry matter partitioning to roots, resource capture coefficients, shoot dry weight at anthesis, specific root weight and water use efficiency. From the current estimates of parameters it is concluded that a larger investment by the crop in fine roots at depth in the soil, and less proliferation of roots in surface layers, would improve yields by accessing extra resources. The economic return on investment in roots for water capture was twice that of the same amount invested for nitrogen capture. (C) 2003 Annals of Botany Company.

Sensitivity analysis of a catchment-scale nitrogen model

There are now considerable expectations that semi-distributed models are useful tools for supporting catchment water quality management. However, insufficient attention has been given to evaluating the uncertainties inherent to this type of model, especially those associated with the spatial disaggregation of the catchment. The Integrated Nitrogen in Catchments model (INCA) is subjected to an extensive regionalised sensitivity analysis in application to the River Kennet, part of the groundwater-dominated upper Thames catchment, UK The main results are: (1) model output was generally insensitive to land-phase parameters, very sensitive to groundwater parameters, including initial conditions, and significantly sensitive to in-river parameters; (2) INCA was able to produce good fits simultaneously to the available flow, nitrate and ammonium in-river data sets; (3) representing parameters as heterogeneous over the catchment (206 calibrated parameters) rather than homogeneous (24 calibrated parameters) produced a significant improvement in fit to nitrate but no significant improvement to flow and caused a deterioration in ammonium performance; (4) the analysis indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters (as opposed to calibrating all parameters together) was not a sensible strategy in this case; (5) even the parameters to which the model output was most sensitive suffered from high uncertainty due to spatial inconsistencies in the estimated optimum values, parameter equifinality and the sampling error associated with the calibration method; (6) soil and groundwater nutrient and flow data are needed to reduce. uncertainty in initial conditions, residence times and nitrogen transformation parameters, and long-term historic data are needed so that key responses to changes in land-use management can be assimilated. The results indicate the general, difficulty of reconciling the questions which catchment nutrient models are expected to answer with typically limited data sets and limited knowledge about suitable model structures. The results demonstrate the importance of analysing semi-distributed model uncertainties prior to model application, and illustrate the value and limitations of using Monte Carlo-based methods for doing so. (c) 2005 Elsevier B.V. All rights reserved.

Spatial analysis of the error in a model of soil nitrogen

Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

Adaptation of the Integrated Nitrogen Model for Catchments (INCA) to seasonally snow-covered catchments

Testing of the Integrated Nitrogen model for Catchments (INCA) in a wide range of ecosystem types across Europe has shown that the model underestimates N transformation processes to a large extent in northern catchments of Finland and Norway in winter and spring. It is found, and generally assumed, that microbial activity in soils proceeds at low rates at northern latitudes during winter, even at sub-zero temperatures. The INCA model was modified to improve the simulation of N transformation rates in northern catchments, characterised by cold climates and extensive snow accumulation and insulation in winter, by introducing an empirical function to simulate soil temperatures below the seasonal snow pack, and a degree-day model to calculate the depth of the snow pack. The proposed snow-correction factor improved the simulation of soil temperatures at Finnish and Norwegian field sites in winter, although soil temperature was still underestimated during periods with a thin snow cover. Finally, a comparison between the modified INCA version (v. 1.7) and the former version (v. 1.6) was made at the Simojoki river basin in northern Finland and at Dalelva Brook in northern Norway. The new modules did not imply any significant changes in simulated NO3- concentration levels in the streams but improved the timing of simulated higher concentrations. The inclusion of a modified temperature response function and an empirical snow-correction factor improved the flexibility and applicability of the model for climate effect studies.