Free atmospheric CO2 enrichment increased above ground biomass but did not affect symbiotic N2-fixation and soil carbon dynamics in a mixed deciduous stand in Wales

Through increases in net primary production (NPP), elevated CO2 is hypothesizes to increase the amount of plant litter entering the soil. The fate of this extra carbon on the forest floor or in mineral soil is currently not clear. Moreover, increased rates of NPP can be maintained only if forests can escape nitrogen limitation. In a Free atmospheric CO2 Enrichment (FACE) experiment near Bangor, Wales, 4 ambient CO2 and 4 FACE plots were planted with patches of Betula pendula, Alnus glutinosa and Fagus sylvatica on a former arable field. Four years after establishment, only a shallow L forest floor litter layer had formed due to intensive bioturbation. Total soil C and N contents increased irrespective of treatment and species as a result of afforestation. We could not detect an additional C sink in the soil, nor were soil C stabilization processes affected by FACE. We observed a decrease of leaf N content in Betula and Alnus under FACE, while the soil C/N ratio decreased regardless of CO2 treatment. The ratio of N taken up from the soil and by N2-fixation in Alnus was not affected by FACE. We infer that increased nitrogen use efficiency is the mechanism by which increased NPP is sustained under elevated CO2 at this site.

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soybean, maize and rice. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soybean at the global and country levels, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index, gross primary production and canopy height better than in the standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an Earth system and crop yield model perspective is encouraging. However, more effort is needed to develop the parametrisation of the model for specific applications. Key future model developments identified include the introduction of processes such as irrigation and nitrogen limitation which will enable better representation of the spatial variability in yield.

Glomus intraradices and Gigaspora margarita arbuscular mycorrhizal associations differentially affect nitrogen and potassium nutrition of Plantago lanceolata in a low fertility dune soil

Two controlled microcosm experiments aimed at a critical re-assessment of the contributions of divergent arbuscular mycorrhizal (AM) fungi to plant mineral nutrition were established that specifically targeted Plantago lanceolata–Glomus intraradices (B.B/E) and –Gigaspora margarita (BEG 34) symbioses developed in a native, nutrient limited, coastal dune soil. Plant tissue nitrogen (N), phosphorus (P) and potassium (K) status as well as plant growth parameters and levels of mycorrhizal colonization were assessed at harvest. In addition to the general well-established mycorrhizal facilitation of P uptake, the study was able to demonstrate a G. intraradices-specific contribution to improved plant nitrogen and potassium nutrition. In the two respective experiments, G. intraradices-inoculated plants had 27.8% and 40.8% more total N and 55.8% and 23.3% more total K when compared to Gi. margarita inoculated counterparts. Dissimilar overall contribution of the two isolates to plant nutrition was identified in AM-genus specific differences in plant tissue N:P:K ratios. G. intraradices inoculated and non-mycorrhizal plants generally exhibited N:P:K ratios indicative of P limitation whereas for Gi.margarita mycorrhizal plants, corresponding ratios strongly implied either N or K limitation. The study provides further evidence highlighting AM functional biodiversity in respect to plant nutrient limitation experienced by mycorrhizal P. lanceolata in an ecologically relevant soil system.

Impact of perturbations of nitrogen oxide emissions from global aviation

Liberation or limitation? Understanding Iyengar Yoga as a practice of the self

This article explores the Foucauldian notions of practices of the self and care of the self, read via Deleuze, in the context of Iyengar yoga (one of the most popular forms of yoga currently). Using ethnographic and interview research data the article outlines the Iyengar yoga techniques which enable a focus upon the self to be developed, and the resources offered by the practice for the creation of ways of knowing, experiencing and forming the self. In particular, the article asks whether Iyengar yoga offers possibilities for freedom and liberation, or whether it is just another practice of control and management. Assessing Iyengar yoga via a ‘critical function’, a function of ‘struggle’ and a ‘curative and therapeutic function’, the article analyses whether the practice might constitute a mode of care of the self, and what it might offer in the context of the contemporary need to live better, as well as longer.

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.

Integrated Nitrogen CAtchment model (INCA) applied to a tropical catchment in the Atlantic Forest, Sao Paulo, Brazil

Stream-water flows and in-stream nitrate and ammonium concentrations in a small (36.7 ha) Atlantic Forest catchment were simulated using the Integrated Nitrogen in CAtchments (INCA) model version 1.9.4. The catchment, at Cunha, is in the Serra do Mar State Park, SE Brazil and is nearly pristine because the nearest major conurbations, Sao Paulo and Rio, are some 450 km distant. However, intensive farming may increase nitrogen (N) deposition and there are growing pressures for urbanisation. The mean-monthly discharges and NO3-N concentration dynamics were simulated adequately for the calibration and validation periods with (simulated) loss rates of 6.55 kg.ha(-1) yr(-1) for NO3-N and 3.85 kg.ha(-1) yr(-1) for NH4-N. To investigate the effects of elevated levels of N deposition in the future, various scenarios for atmospheric deposition were simulated; the highest value corresponded to that in a highly polluted area of Atlantic Forest in Sao Paulo City. It was found that doubling the atmospheric deposition generated a 25% increase in the N leaching rate, while at levels approaching the highly polluted Sao Paulo deposition rate, five times higher than the current rate, leaching increased by 240%, which would create highly eutrophic conditions, detrimental to downstream water quality. The results indicate that the INCA model can be useful for estimating N concentration and fluxes for different atmospheric deposition rates and hydrological conditions.