984 resultados para nitrogen dynamics


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Inland waters are of global biogeochemical importance receiving carbon inputs of ~ 4.8 Pg C y-1. Of this 12 % is buried, 18 % transported to the oceans, and 70 % supports aquatic secondary production. However, the mechanisms that determine the fate of organic matter (OM) in these systems are poorly defined. One important aspect is the formation of organo-mineral complexes in aquatic systems and their potential as a route for OM transport and burial vs. their use potential as organic carbon (C) and nitrogen (N) sources. Organo-mineral particles form by sorption of dissolved OM to freshly eroded mineral surfaces and may contribute to ecosystem-scale particulate OM fluxes. We tested the availability of mineral-sorbed OM as a C & N source for streamwater microbial assemblages and streambed biofilms. Organo-mineral particles were constructed in vitro by sorption of 13C:15N-labelled amino acids to hydrated kaolin particles, and microbial degradation of these particles compared with equivalent doses of 13C:15N-labelled free amino acids. Experiments were conducted in 120 ml mesocosms over 7 days using biofilms and streamwater sampled from the Oberer Seebach stream (Austria), tracing assimilation and mineralization of 13C and 15N labels from mineral-sorbed and dissolved amino acids.Here we present data on the effects of organo-mineral sorption upon amino acid mineralization and its C:N stoichiometry. Organo-mineral sorption had a significant effect upon microbial activity, restricting C and N mineralization by both the biofilm and streamwater treatments. Distinct differences in community response were observed, with both dissolved and mineral-stabilized amino acids playing an enhanced role in the metabolism of the streamwater microbial community. Mineral-sorption of amino acids differentially affected C & N mineralization and reduced the C:N ratio of the dissolved amino acid pool. The present study demonstrates that organo-mineral complexes restrict microbial degradation of OM and may, consequently, alter the carbon and nitrogen cycling dynamics within aquatic ecosystems.

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Os estuários são ecossistemas complexos, onde os processos físicos, químicos e biológicos estão intimamente ligados. A dinâmica bacteriana num estuário reflete a interação e a elevada variação temporal e espacial desses processos. Este trabalho teve como objetivo elucidar as interações entre os processos físicos, fotoquímicos e microbiológicos no sistema estuarino da Ria de Aveiro (Portugal). Para tal, foi realizada uma abordagem inicial no campo, durante a qual as comunidades bacterianas na coluna de água foram caracterizadas em termos de abundância e atividade ao longo de 2 anos. O estudo foi realizado em dois locais distintos, escolhidos por tipificarem as características marinhas e salobras do estuário. Estes locais possuem diferentes hidrodinâmicas, influências fluviais e, quantidade e composição de matéria orgânica. Numa perspectiva mecanicista, foram realizadas simulações laboratoriais no sentido de elucidar a resposta das bactérias à matéria orgânica foto-transformada. As comunidades bacterianas no estuário adaptam-se a diferentes regimes de água doce, desenvolvendo padrões de abundância e atividade distintos nas zonas marinha e salobra. Os elevados caudais dos rios induzem estratificação vertical na zona marinha, promovendo o fluxo de fitoplâncton do mar para o estuário, do bacterioplâncton do estuário para o mar, e estimulam a importação de bactérias aderentes a partículas na zona salobra. O transporte advectivo e os processos de ressuspensão contribuem para aumentar 3 vezes o número de bactérias aderentes a partículas durante os períodos de intensas descargas fluviais. Adicionalmente, a atividade bacteriana no estuário é controlada pela concentração de azoto inerente à variações de água doce. O fornecimento de azoto em associação com a fonte dos substratos bacterianos induzem alterações significativas na produtividade. O padrão de variação vertical de comunidades bacterianas foi distinto nas duas zonas do estuário. Na zona marinha, as bactérias na microcamada superficial (SML) apresentaram taxas de hidrólise mais elevadas, mas menores taxas de incorporação de monómeros e produção de biomassa que na água subjacente (UW), enquanto na zona salobra, as taxas de hidrólise e incorporação foram similares nos dois compartimentos, mas a produtividade foi significativamente mais elevada na SML. Apesar da abundância bacteriana ter sido semelhante na SML e UW, a fração de células aderentes a partículas foi significativamente maior na SML (2-3 vezes), em ambas as zonas do estuário. A integração dos resultados microbiológicos com as variáveis ambientais e hidrológicos mostraram que fortes correntes na zona marinha promovem a mistura vertical, inibindo o estabelecimento de uma comunidade bacteriana na SML distinta da UW. Em contraste, na zona de água salobra, a menor velocidades das correntes fornece as condições adequadas ao aumento da atividade bacteriana na SML. Características específicas do local, tais como a hidrodinâmica e as fontes e composição da matéria orgânica, conduzem também a diferentes graus de enriquecimento superficial de matéria orgânica e inorgânica, influenciando a sua transformação. Em geral, o ambiente da SML estuarina favorece a hidrólise de polímeros, mas inibe a utilização de monómeros, comparativamente com água subjacente. No entanto, as diferenças entre as duas comunidades tendem a atenuar-se com o aumento da atividade heterotrófica na zona salobra. A matéria orgânica dissolvida cromófora (CDOM) das duas zonas do estuário possui diferentes características espectrais, com maior aromaticidade e peso molecular médio (HMW) na zona de água salobra, em comparação com a zona marinha. Nesta zona, a abundância bacteriana correlacionou-se com a350 e a254, sugerindo uma contribuição indireta das bactéria para HMW CDOM. A irradiação do DOM resultou numa diminuição dos valores de a254 e a350, e, em um aumento do declive S275-295 e dos rácios E2:E3 (a250/a365) e SR. No entanto, a extensão de transformações foto-induzidas e as respostas microbianas são dependentes das características iniciais CDOM, inferidas a partir das suas propriedades ópticas. A dinâmica estuarina influencia claramente as atividades heterotróficas e a distribuição dos microorganismos na coluna de água. A entrada de água doce influencia a dinâmica e os principais reguladores das comunidades bacterianas no estuário. Os processos fotoquímicos e microbianos produzem alterações nas propriedades ópticas da CDOM e a combinação desses processos determina o resultado global e o destino da CDOM nos sistemas estuarinos com influência na produtividade nas áreas costeiras adjacente.

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Please consult the paper edition of this thesis to read. It is available on the 5th Floor of the Library at Call Number: Z 9999.5 B63 P54 2007

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In the present thesis entitled” Implications of Hydrobiology and Nutrient dynamics on Trophic structure and Interactions in Cochin backwaters”, an attempt has been made to assess the influence of general hydrography, nutrients and other environmental factors on the abundance, distribution and trophic interactions in Cochin backwater system. The study was based on five seasonal sampling campaigns carried out at 15 stations spread along the Cochin backwater system. The thesis is presented in the following 5 chapters. Salient features of each chapter are summarized below: Chapter 1- General Introduction: Provides information on the topic of study, environmental factors, back ground information, the significance, review of literature, aim and scope of the present study and its objectives.Chapter 2- Materials and Methods: This chapter deals with the description of the study area and the methodology adopted for sample collection and analysis. Chapter 3- General Hydrograhy and Sediment Characteristics: Describes the environmental setting of the study area explaining seasonal variation in physicochemical parameters of water column and sediment characteristics. Data on hydrographical parameters, nitrogen fractionation, phosphorus fractionation and biochemical composition of the sediment samples were assessed to evaluate the trophic status. Chapter 4- Nutrient Dynamics on Trophic Structure and Interactions: Describes primary, secondary and tertiary production in Cochin backwater system. Primary production related to cell abundance, diversity of phytoplankton that varies seasonally, concentration of various pigments and primary productivitySecondary production refers to the seasonal abundance of zooplankton especially copepod abundance and tertiary production deals with seasonal fish landings, gut content analysis and proximate composition of dominant fish species. The spatiotemporal variation, interrelationships and trophic interactions were evaluated by statistical methods. Chapter 5- Summary: The results and findings of the study are summarized in the fifth chapter of the thesis.

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Distribution and chemistry of major inorganic forms of nutrients along with physico-chemical parameters were investigated. Surface sediments and overlying waters of the Ashtamudi and Vembanad Lakes were taken for the study, which is situated in the southwest coast of India. High concentrations of dissolved nitrogen and phosphorus compounds carried by the river leads to oxygen depletion in the water column. A concurrent increase in the bottom waters along with decrease in dissolved oxygen was noticed. This support to nitrification process operating in the sediment-water interface of the Ashtamudi and Vembanad Lake. Estuarine sediments are clayey sand to silty sand both in Ashtamudi and Vembanad in January and May. Present study indicates that the sediment texture is the major controlling factor in the distribution of these nutrient forms. For water samples nitrite, inorganic phosphate was high in Vembanad in January and May compared to Ashtamudi. For sediments, enhanced level of inorganic phosphate and nitrite was found in Vembanad during January and May. It had been observed that the level of N and P is more in sediments. A comparative assessment of the Ashtamudi and Vembanad Lake reveals that the Vembanad wetland is more deteriorated compared to the Ashtamudi wetland system

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Kerala is one of the smallest states in India which is situated in the south west coast of the country. Sediment samples from four prominent areas of Kerala Coast were collected and analyzed for nutrients. Variation of nutrients was highlighted according to the distributional characteristics of the designated sites. Nutrient trend in Cape, Trivandrum, Kollam was in the order as Ammonia > Nitrite >Nitrate, where as Cochin showed the trend as Ammonia > Nitrate > Nitrite. Greater concentration of ammonia in the entire sediments showed the ammonification of nitrogen compounds

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The spatial and temporal dynamics in the stream water NO3-N concentrations in a major European river-system, the Garonne (62,700 km(2)), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byrans Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed tinder the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3-N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distrubuted catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3-N patterns at large spatial (> 300 km(2)) and temporal (>= monthly) scales using available national datasets.

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There have been only a few studies of potassium (K) losses from grassland systems, and little is known about their dynamics, especially in relation to nitrogen (N) management. A study was performed during the autumn and winter of 1999 and 2000 to understand the effects of N and drainage on the dynamics of K leaching on a hillslope grassland soil in southwestern England. Two N application rates were studied (0 and 280 kg N ha(-1) yr(-1)), both with and without the drainage. Treatments receiving N also received farmyard manure (FM). Higher total K losses and K concentrations in the leachates were found in the N + FM treatments (150 and 185% higher than in 0 N treatments), which were related to K additions in the FM. Drainage reduced K losses by 35% because of an increase in dry matter production and a reduction in overland and preferential flow. The pattern of change in K concentration in the leachates was associated with preferential flow at the beginning of the drainage season and with matrix flow later in winter, and was best described by a double exponential curve. Rainfall intensity and the autumn application of FM were the main determinants of K losses by leaching. The study provided new insights into the relationships between soil hydrology, rainfall, and K leaching and its implications for grassland systems.

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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.

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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.

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The spatial and temporal dynamics in the stream water NO3-N concentrations in a major European river-system, the Garonne (62,700 km(2)), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byrans Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed tinder the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3-N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distrubuted catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3-N patterns at large spatial (> 300 km(2)) and temporal (>= monthly) scales using available national datasets.

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The Integrated Catchment Model of Nitrogen (INCA-N) was applied to the Lambourn and Pang river-systems to integrate current process-knowledge and available-data to test two hypotheses and thereby determine the key factors and processes controlling the movement of nitrate at the catchment-scale in lowland, permeable river-systems: (i) that the in-stream nitrate concentrations were controlled by two end-members only: groundwater and soil-water, and (ii) that the groundwater was the key store of nitrate in these river-systems. Neither hypothesis was proved true or false. Due to equifinality in the model structure and parameters at least two alternative models provided viable explanations for the observed in-stream nitrate concentrations. One model demonstrated that the seasonal-pattern in the stream-water nitrate concentrations was controlled mainly by the mixing of ground- and soil-water inputs. An alternative model demonstrated that in-stream processes were important. It is hoped further measurements of nitrate concentrations made in the catchment soil- and ground-water and in-stream may constrain the model and help determine the correct structure, though other recent studies suggest that these data may serve only to highlight the heterogeneity of the system. Thus when making model-based assessments and forecasts it is recommend that all possible models are used, and the range of forecasts compared. In this study both models suggest that cereal production contributed approximately 50% the simulated in-stream nitrate toad in the two catchments, and the point-source contribution to the in-stream load was minimal. (c) 2006 Elsevier B.V. All rights reserved.

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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.

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Steady state and dynamic models have been developed and applied to the River Kennet system. Annual nitrogen exports from the land surface to the river have been estimated based on land use from the 1930s and the 1990s. Long term modelled trends indicate that there has been a large increase in nitrogen transport into the river system driven by increased fertiliser application associated with increased cereal production, increased population and increased livestock levels. The dynamic model INCA Integrated Nitrogen in Catchments. has been applied to simulate the day-to-day transport of N from the terrestrial ecosystem to the riverine environment. This process-based model generates spatial and temporal data and reproduces the observed instream concentrations. Applying the model to current land use and 1930s land use indicates that there has been a major shift in the short term dynamics since the 1930s, with increased river and groundwater concentrations caused by both non-point source pollution from agriculture and point source discharges. �

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Agro-hydrological models have widely been used for optimizing resources use and minimizing environmental consequences in agriculture. SMCRN is a recently developed sophisticated model which simulates crop response to nitrogen fertilizer for a wide range of crops, and the associated leaching of nitrate from arable soils. In this paper, we describe the improvements of this model by replacing the existing approximate hydrological cascade algorithm with a new simple and explicit algorithm for the basic soil water flow equation, which not only enhanced the model performance in hydrological simulation, but also was essential to extend the model application to the situations where the capillary flow is important. As a result, the updated SMCRN model could be used for more accurate study of water dynamics in the soil-crop system. The success of the model update was demonstrated by the simulated results that the updated model consistently out-performed the original model in drainage simulations and in predicting time course soil water content in different layers in the soil-wheat system. Tests of the updated SMCRN model against data from 4 field crop experiments showed that crop nitrogen offtakes and soil mineral nitrogen in the top 90 cm were in a good agreement with the measured values, indicating that the model could make more reliable predictions of nitrogen fate in the crop-soil system, and thus provides a useful platform to assess the impacts of nitrogen fertilizer on crop yield and nitrogen leaching from different production systems. (C) 2010 Elsevier B.V. All rights reserved.