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The curse of the past
(2021)
One challenge for modern agricultural management schemes is the reduction of harmful effects on the envi-ronment, e.g. in terms of the emission of nutrients. Sampling the effluent of tile drains is a very efficient way to sample seepage water from larger areas directly underneath the main rooting zone. Time series of solute con-centration in tile drains can be linked to agricultural management data and thus indicate the efficacy of individual management measures. To that end, the weekly runoff and solute concentration were determined in long-term measurement campaigns at 25 outlets of artificial tile drains at 19 various arable fields in the German federal state of Mecklenburg-Vorpommern. The study sites were distributed within a 23,000 km(2) region and were deemed representative of intense arable land use. In addition, comprehensive meteorological and man-agement data were provided. To disentangle the different effects, monitoring data were subjected to a principal component analysis. Loadings on the prevailing principal components and spatial and temporal patterns of the component scores were considered indicative of different processes. Principal component scores were then related to meteorological and management data via random forest modelling. Hydrological conditions and weather were identified as primary driving forces for the nutrient discharge behaviour of the drain plots, as well as the nitrogen balance. In contrast, direct effects of recent agricultural management could hardly be identified. Instead, we found clear evidence of the long-term and indirect effects of agriculture on nearly all solutes. We conclude that tile drain effluent quality primarily reflected the soil-internal mobilisation or de-mobilisation of nutrients and related solutes rather than allowing inferences to be drawn about recent individual agricultural management measures. On the other hand, principal component analysis revealed a variety of indirect and long-term effects of fertilisation on solutes other than nitrogen or phosphorus that are still widely overlooked in nutrient turnover studies.
The major aim of this thesis was to study the effect of nitrate on primary metabolism and in development of the model plant Arabidopsis thaliana. The present work has two separate topics. First, to investigate the GDH family, a small gene family at the interface between nitrogen and carbon metabolisms. Second, to investigate the mechanisms whereby nitrogen is regulating the transition to flowering time in Arabidopsis thaliana. To gain more insights into the regulation of primary metabolism by the functional characterization of the glutamate dehydrogenase (GDH) family, an enzyme putatively involved in the metabolism of amino acids and thus suggested to play different and essential roles in carbon and nitrogen metabolism in plants, knock out mutants and transgenic plants carrying RNA interference construct were generated and characterized. The effect of silencing GDH on carbon and nitrogen metabolisms was investigated, especially the level of carbohydrates and the amino acid pool were further analysed. It has been shown that GDH expression is regulated by light and/or sugar status therefore, phenotypic and metabolic analysis were developed in plants grown at different points of the diurnal rhythm and in response to an extended night period. In addition, we are interested in the effect of nutrient availability in the transition from vegetative growth to flowering and especially in nitrate as a metabolite that triggers widespread and coordinated changes in metabolism and development. Nutrient availability has a dramatic effect on flowering time, with a marked delay of flowering when nitrate is supplied (Stitt, 1999). The use of different mutants and transgenic plants impaired in flowering signalling pathways was crucial to evaluate the impact of different nitrate concentrations on flowering time and to better understand the interaction of nitrate-dependent signals with other main flowering signalling pathways. Plants were grown on glutamine as a constitutive source of nitrogen, and the nitrate supply varied. Low nitrate led to earlier flowering. The response to nitrate is accentuated in short days and in the CONSTANS deficient co2 mutant, whereas long days or overexpression of CONSTANS overrides the nitrate response. These results indicate that nitrates acts downstream of the known flowering signalling pathways for photoperiod, autonomy, vernalization and gibberellic acid. Global analyses of gene expression of two independent flowering systems, a light impaired mutant (co2tt4) and a constitutive over-expresser of the potent repressor of flowering (35S::FLC), were to be investigated under two different concentrations of nitrate in order to identify candidate genes that may be involved in the regulation of flowering time by nitrate.
Chemical transformations and hydraulic processes in soil and groundwater often lead to an apparent retention of nitrate in lowland catchments. Models are needed to evaluate the interaction of these processes in space and time. The objectives of this study are i) to develop a specific modelling approach by combining selected modelling tools simulating N-transport and turnover in soils and groundwater of lowland catchments, ii) to study interactions between catchment properties and nitrogen transport. Special attention was paid to potential N-loads to surface waters. The modelling approach combines various submodels for water flow and solute transport in soil and groundwater: The soil-water- and nitrogen-model mRISK-N, the groundwater flow model MODFLOW and the solute transport model RT3D. In order to investigate interactions of N-transport and catchment characteristics, the distribution and availability of reaction partners have to be taken into account. Therefore, a special reaction-module is developed, which simulates various chemical processes in groundwater, such as the degradation of organic matter by oxygen, nitrate, sulphate or pyrite oxidation by oxygen and nitrate. The model approach is applied to different simulation, focussing on specific submodels. All simulation studies are based on field data from the Schaugraben catchment, a pleistocene catchment of approximately 25 km², close to Osterburg(Altmark) in the North of Saxony-Anhalt. The following modelling studies have been carried out: i) evaluation of the soil-water- and nitrogen-model based on lysimeter data, ii) modelling of a field scale tracer experiment on nitrate transport and turnover in the groundwater as a first application of the reaction module, iii) evaluation of interactions between hydraulic and chemical aquifer properties in a two-dimensional groundwater transect, iv) modelling of distributed groundwater recharge and soil nitrogen leaching in the study area, to be used as input data for subsequent groundwater simulations, v) study of groundwater nitrate distribution and nitrate breakthrough to the surface water system in the Schaugraben catchment area and a subcatchment, using three-dimensional modelling of reactive groundwater transport. The various model applications prove the model to be capable of simulating interactions between transport, turnover and hydraulic and chemical catchment properties. The distribution of nitrate in the sediment and the resulting loads to surface waters are strongly affected by the amount of reactive substances and by the residence time within the aquifer. In the Schaugraben catchment simulations, it is found that a period of 70 years is needed to raise the average seepage concentrations of nitrate to a level corresponding to the given input situation, if no reactions are considered. Under reactive transport conditions, nitrate concentrations are reduced effectively. Simulation results show that groundwater exfiltration does not contribute considerably to the nitrate pollution of surface waters, as most nitrate entering soils and groundwater is lost by denitrification. Additional sources, such as direct inputs or tile drains have to be taken into account to explain surface water loads. The prognostic value of the models for the study site is limited by uncertainties of input data and estimation of model parameters. Nevertheless, the modelling approach is a useful aid for the identification of source and sink areas of nitrate pollution as well as the investigation of system response to management measures or landuse changes with scenario simulations. The modelling approach assists in the interpretation of observed data, as it allows to integrate local observations into a spatial and temporal framework.
Solute concentration variability is of fundamental importance for the chemical and ecological state of streams. It is often closely related to discharge variability and can be characterized in terms of a solute export regime. Previous studies, especially in lowland catchments, report that nitrate is often exported with an accretion pattern of increasing concentrations with increasing discharge. Several modeling approaches exist to predict the export regime of solutes from the spatial relationship of discharge generating zones with solute availability in the catchment. For a small agriculturally managed lowland catchment in central Germany, we show that this relationship is controlled by the depth to groundwater table and its temporal dynamics. Principal component analysis of groundwater level time series from wells distributed throughout the catchment allowed derivation of a representative groundwater level time series that explained most of the discharge variability. Groundwater sampling revealed consistently decreasing nitrate concentrations with an increasing thickness of the unsaturated zone. The relationships of depth to groundwater table to discharge and to nitrate concentration were parameterized and integrated to successfully model catchment discharge and nitrate export on the basis of groundwater level variations alone. This study shows that intensive and uniform agricultural land use likely results in a clear and consistent concentration-depth relationship of nitrate, which can be utilized in simple approaches to predict stream nitrate export dynamics at the catchment scale. (C) 2016 Elsevier Ltd. All rights reserved.