Impact of perturbations of nitrogen oxide emissions from global aviation

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.

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.

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.

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.

Exploring the spatial variation of take-all (Gaeumannomyces graminis var. tritici) for site-specific management

The fungus Gaeumannomyces graminis var. tritici (Ggt), commonly known as the take-all fungus, causes damage to roots of wheat and barley that limits crop growth and causes loss of yield. There was little knowledge on the within-field spatial variation of take-all and relations with features in the growing crop, selected soil properties and spectral information from remotely sensed imagery. Geostatistical analyses showed that take-all, chlorosis and leaf area index had similar patchy distributions. Many of the spectral bands from a hyperspectral image also had similar spatial patterns to take-all and chlorosis. Relations between take-all and mineral nitrogen, elevation and pH were generally weaker.

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.

Promoting microbial immobilization of soil nitrogen during restoration of abandoned agricultural fields by organic additions

Application of organic materials to soils to enhance N immobilization into microbial biomass, thereby reducing inorganic N concentrations, was studied as a management option to accelerate the reestablishment of the native vegetation on abandoned arable fields on sandy soils the Kiskunsag National Park, Hungary. Sucrose and sawdust were used at three different topographic sites over 4 years. N availability and extractable inorganic N concentrations were significantly reduced in all sites. Soil microbial biomass C and microbial biomass N increased significantly following C additions, but the microbial C to microbial N ratio remained unaffected. It is concluded that the combined application of the rapidly utilized C source (sucrose) promoted N immobilization, whereas the addition of the slowly utilized C source (sawdust) maintained the elevated microbial biomass C and microbial biomass N in the field.

Presubmergence and green manure affect the transformations of nitrogen-15-labeled urea under lowland soil conditions

The effect of presubmergence and green manuring on various processes involved in [N-15]-urea transformations were studied in a growth chamber after [N-15]-urea application to floodwater. Presubmergence for 14 days increased urea hydrolysis rates and floodwater pH, resulting in higher NH3 volatilization as compared to without presubmergence. Presubmergence also increased nitrification and subsequent denitrification but lower N assimilation by floodwater algae caused higher gaseous losses. Addition of green manure maintained higher NH4+-N concentration in floodwater mainly because of lower nitrification rates but resulted in highest NH3 volatilization losses. Although green manure did not affect the KCl extractable NH4+-N from applied fertilizer, it maintained higher NH4+-N content due to its decomposition and increased mineralization of organic N. After 32 days about 36.9% (T-1), 23.9% (T-2), and 36.4% (T-3) of the applied urea N was incorporated in the pool of soil organic N in treatments. It was evident that the presubmergence has effected the recovery of applied urea N.