Refine
Year of publication
Document Type
- Article (6)
- Doctoral Thesis (5)
- Postprint (3)
- Monograph/Edited Volume (1)
Keywords
- nutrients (15) (remove)
In der randomisierten, multizentrischen DASH-Studie (Dietary Approaches to Stop Hy-pertension), die unter kontrollierten Bedingungen stattfand, führte eine fettreduzierte Mischkost, reich an Obst, Gemüse und Milchprodukten, bei Borderline-Hypertonikern zu einer signifikanten Blutdrucksenkung. Während der Studienphase wurden Körpermasse, Natrium-Aufnahme sowie Alkoholzufuhr aufgrund der bekannten Einflussnahme auf den Blutdruck konstant gehalten. In der eigenen Pilot-Studie sollte untersucht werden, ob das Ergebnis der DASH-Studie (i) mit deutschen Hypertonikern und (ii) unter habituellen Ernährungs- und Lebensbedingungen mit regelmäßig durchgeführter Ernährungsberatung und ad libitum Verzehr anstelle des streng kontrollierten Studienansatzes bestätigt werden kann. Eine Konstanz der Körpermasse, der Natrium-Urinausscheidung (unter diesem Studienansatz valider als die Aufnahme) und des Alkoholkonsums wurde vorausgesetzt. Die Studienpopulation setzte sich aus 53 übergewichtigen Probanden mit einer nicht medikamentös therapierten Borderline-Hypertonie und ohne Stoffwechselerkrankungen zusammen. Die Studienteilnehmer wurden randomisiert entweder der Idealgruppe mit einer fettarmen Kost reich an Milchprodukten, Obst und Gemüse (ähnlich der DASH-Idealgruppe) oder der Kontrollgruppe mit habitueller Ernährungsweise zugeteilt. Über einen Zeitraum von fünf Wochen wurde den Probanden etwa 50% ihres täglichen Lebensmittelbedarfes entsprechend ihrer Gruppenzugehörigkeit kostenfrei zur Verfügung gestellt. Gelegenheitsblutdruckmessungen und 24h-Blutdruckmessungen, Ernährungs- und Aktivitätsprotokolle, Blut- und Urinproben sowie anthropometrische Messungen wurden vor, während und fünf Wochen nach der Interventionsphase durchgeführt. Die Ergebnisse zeigen, dass in der Idealgruppe keine signifikante Blutdrucksenkung beobachtet werden konnte. Dies lässt sich durch die Tatsache erklären, dass die Lebens-mittel- und Nährstoffaufnahme der deutschen Kontrollgruppe eher der amerikanischen Idealgruppe entsprach. In der Pilot-Studie waren die Unterschiede in der Nährstoffzufuhr zwischen den beiden Gruppen viel geringer als in der DASH-Studie; für eine blutdrucksenkende Ernährungsumstellung bestand somit nur ein geringer Spielraum. Eine weitere Erklärung besteht in der unterschiedlichen Zusammensetzung der Studienpopulation. Bei DASH wurden vorwiegend farbige Probanden (40% höhere Hypertonieprävalenz) untersucht. Die Studienergebnisse lassen also den Schluss zu, dass Ernährungs- und Lebensstilgewohnheiten sowie der genetische Hintergrund der entsprechenden Bevölkerungsgruppe bei der Formulierung von nährstoff- oder lebensmittelbezogenen Empfehlungen zur Senkung des Bluthochdruckes Berücksichtigung finden müssen.
A water quality model for shallow river-lake systems and its application in river basin management
(2007)
This work documents the development and application of a new model for simulating mass transport and turnover in rivers and shallow lakes. The simulation tool called 'TRAM' is intended to complement mesoscale eco-hydrological catchment models in studies on river basin management. TRAM aims at describing the water quality of individual water bodies, using problem- and scale-adequate approaches for representing their hydrological and ecological characteristics. The need for such flexible water quality analysis and prediction tools is expected to further increase during the implementation of the European Water Framework Directive (WFD) as well as in the context of climate change research. The developed simulation tool consists of a transport and a reaction module with the latter being highly flexible with respect to the description of turnover processes in the aquatic environment. Therefore, simulation approaches of different complexity can easily be tested and model formulations can be chosen in consideration of the problem at hand, knowledge of process functioning, and data availability. Consequently, TRAM is suitable for both heavily simplified engineering applications as well as scientific ecosystem studies involving a large number of state variables, interactions, and boundary conditions. TRAM can easily be linked to catchment models off-line and it requires the use of external hydrodynamic simulation software. Parametrization of the model and visualization of simulation results are facilitated by the use of geographical information systems as well as specific pre- and post-processors. TRAM has been developed within the research project 'Management Options for the Havel River Basin' funded by the German Ministry of Education and Research. The project focused on the analysis of different options for reducing the nutrient load of surface waters. It was intended to support the implementation of the WFD in the lowland catchment of the Havel River located in North-East Germany. Within the above-mentioned study TRAM was applied with two goals in mind. In a first step, the model was used for identifying the magnitude as well as spatial and temporal patterns of nitrogen retention and sediment phosphorus release in a 100~km stretch of the highly eutrophic Lower Havel River. From the system analysis, strongly simplified conceptual approaches for modeling N-retention and P-remobilization in the studied river-lake system were obtained. In a second step, the impact of reduced external nutrient loading on the nitrogen and phosphorus concentrations of the Havel River was simulated (scenario analysis) taking into account internal retention/release. The boundary conditions for the scenario analysis such as runoff and nutrient emissions from river basins were computed by project partners using the catchment models SWIM and ArcEGMO-Urban. Based on the output of TRAM, the considered options of emission control could finally be evaluated using a site-specific assessment scale which is compatible with the requirements of the WFD. Uncertainties in the model predictions were also examined. According to simulation results, the target of the WFD -- with respect to total phosphorus concentrations in the Lower Havel River -- could be achieved in the medium-term, if the full potential for reducing point and non-point emissions was tapped. Furthermore, model results suggest that internal phosphorus loading will ease off noticeably until 2015 due to a declining pool of sedimentary mobile phosphate. Mass balance calculations revealed that the lakes of the Lower Havel River are an important nitrogen sink. This natural retention effect contributes significantly to the efforts aimed at reducing the river's nitrogen load. If a sustainable improvement of the river system's water quality is to be achieved, enhanced measures to further reduce the immissions of both phosphorus and nitrogen are required.
Ziel dieser Arbeit war es, die Stickstoff- und Phosphorprozesse im nordostdeutschen Tiefland detailliert zu untersuchen und Handlungsoptionen hinsichtlich der Landnutzung zur nachhaltigen Steuerung der Stickstoff- und Phosphoreinträge in die Fließgewässer aufzuzeigen. Als Grundvoraussetzung für die Modellierung des Nährstoffhaushaltes mussten zunächst die hydrologischen Prozesse und die Abflüsse für die Einzugsgebiete validiert werden. Dafür wurde in dieser Arbeit das ökohydrologische Modell SWIM verwendet. Die Abflussmodellierung umfasste den Zeitraum 1991 - 2000. Die Ergebnisse dazu zeigen, dass SWIM in der Lage war, die hydrologischen Prozesse in den Untersuchungsgebieten adäquat wiederzugeben. Auf der Grundlage der Modellierung des Wasserhaushaltes wurden mit SWIM die Stoffumsatzprozesse für den Zeitraum 1996 - 2000 simuliert. Um dabei besonders das Prozessgeschehen im Tiefland zu berücksichtigen, war die Erweiterung von SWIM um einen Ammonium-Pool mit dessen Umsatzprozessen erforderlich. Außerdem wurde der Prozess der Nährstoffversickerung so ergänzt, dass neben Nitrat auch Ammonium und Phosphat durch das gesamte Bodenprofil verlagert und über die Abflusskomponenten zum Gebietsauslass transportiert werden können. Mit diesen Modellerweiterungen konnten die Stickstoff und Phosphorprozesse in den Untersuchungsgebieten gut abgebildet werden. Mit dem so validierten Modell wurden weitere Anwendungen ermöglicht. Nährstoffsimulationen für den Zeitraum 1981 bis 2000 dienten der Untersuchung des abnehmenden Trends in den Nährstoffkonzentrationen der Nuthe. Die Untersuchungsergebnisse lassen deutlich erkennen, dass sich die Konzentrationen nach 1990 hauptsächlich auf Grund der Reduzierung der Einträge aus punktförmigen Quellen und Rieselfeldern verringert haben. Weitere Modellrechnungen zur Herkunft der Nährstoffe haben ergeben, dass Nitrat überwiegend aus diffusen Quellen, Ammonium und Phosphat dagegen aus punktförmigen Quellen stammen. Als besonders sensitiv auf die Modellergebnisse haben sich die Parameter zu Landnutzung und -management und die Durchwurzelungstiefe der Pflanzen herausgestellt. Abschließend wurden verschiedene Landnutzungsszenarien angewendet. Die Ergebnisse zu den Szenariorechnungen zeigen, dass fast alle vorgegebenen Landnutzungsszenarien zu einer Verringerung der Stickstoff- bzw. Phosphoremissionen führten. Die Anwendung von Szenarien, die alle relevanten Zielvorgaben und Empfehlungen zum Ressourcenschutz berücksichtigen, zeigen die größten Veränderungen.
Ziel dieser Arbeit war es, die Stickstoff- und Phosphorprozesse im nordostdeutschen Tiefland detailliert zu untersuchen und Handlungsoptionen hinsichtlich der Landnutzung zur nachhaltigen Steuerung der Stickstoff- und Phosphoreinträge in die Fließgewässer aufzuzeigen. Als Grundvoraussetzung für die Modellierung des Nährstoffhaushaltes mussten zunächst die hydrologischen Prozesse und die Abflüsse für die Einzugsgebiete validiert werden. Dafür wurde in dieser Arbeit das ökohydrologische Modell SWIM verwendet. Die Abflussmodellierung umfasste den Zeitraum 1991 - 2000. Die Ergebnisse dazu zeigen, dass SWIM in der Lage war, die hydrologischen Prozesse in den Untersuchungsgebieten adäquat wiederzugeben. Auf der Grundlage der Modellierung des Wasserhaushaltes wurden mit SWIM die Stoffumsatzprozesse für den Zeitraum 1996 - 2000 simuliert. Um dabei besonders das Prozessgeschehen im Tiefland zu berücksichtigen, war die Erweiterung von SWIM um einen Ammonium-Pool mit dessen Umsatzprozessen erforderlich. Außerdem wurde der Prozess der Nährstoffversickerung so ergänzt, dass neben Nitrat auch Ammonium und Phosphat durch das gesamte Bodenprofil verlagert und über die Abflusskomponenten zum Gebietsauslass transportiert werden können. Mit diesen Modellerweiterungen konnten die Stickstoff und Phosphorprozesse in den Untersuchungsgebieten gut abgebildet werden. Mit dem so validierten Modell wurden weitere Anwendungen ermöglicht. Nährstoffsimulationen für den Zeitraum 1981 bis 2000 dienten der Untersuchung des abnehmenden Trends in den Nährstoffkonzentrationen der Nuthe. Die Untersuchungsergebnisse lassen deutlich erkennen, dass sich die Konzentrationen nach 1990 hauptsächlich auf Grund der Reduzierung der Einträge aus punktförmigen Quellen und Rieselfeldern verringert haben. Weitere Modellrechnungen zur Herkunft der Nährstoffe haben ergeben, dass Nitrat überwiegend aus diffusen Quellen, Ammonium und Phosphat dagegen aus punktförmigen Quellen stammen. Als besonders sensitiv auf die Modellergebnisse haben sich die Parameter zu Landnutzung und -management und die Durchwurzelungstiefe der Pflanzen herausgestellt. Abschließend wurden verschiedene Landnutzungsszenarien angewendet. Die Ergebnisse zu den Szenariorechnungen zeigen, dass fast alle vorgegebenen Landnutzungsszenarien zu einer Verringerung der Stickstoff- bzw. Phosphoremissionen führten. Die Anwendung von Szenarien, die alle relevanten Zielvorgaben und Empfehlungen zum Ressourcenschutz berücksichtigen, zeigen die größten Veränderungen.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Red, orange or green snow is the macroscopic phenomenon comprising different eukaryotic algae. Little is known about the ecology and nutrient regimes in these algal communities. Therefore, eight snow algal communities from five intensively tinted snow fields in western Spitsbergen were analysed for nutrient concentrations and fatty acid (FA) composition. To evaluate the importance of a shift from green to red forms on the FA-variability of the field samples, four snow algal strains were grown under nitrogen replete and moderate light (+N+ML) or N-limited and high light (-N+HL) conditions. All eight field algal communities were dominated by red and orange cysts. Dissolved nutrient concentration of the snow revealed a broad range of NH4+ (<0.005-1.2 mg NI-1) and only low PO43- (< 18 mu g P I-1) levels. The external nutrient concentration did not reflect cellular nutrient ratios as C:N and C:P ratios of the communities were highest at locations containing relatively high concentrations of NH4- and PO43-. Molar N:P ratios ranged from 11 to 21 and did not suggest clear limitation of a single nutrient. On a per carbon basis, we found a 6-fold difference in total FA content between the eight snow algal communities, ranging from 50 to 300 mg FA g C-1. In multivariate analyses total FA content opposed the cellular N:C quota and a large part of the FA variability among field locations originated from the abundant FAs C181n-9, C18 2n-6, and C183n-3. Both field samples and snow algal strains grown under -N+HL conditions had high concentrations of C181n-9. FAs possibly accumulated due to the cessation of growth. Differences in color and nutritional composition between patches of snow algal communities within one snow field were not directly related to nutrient conditions. We propose that the highly patchy distribution of snow algae within and between snow fields may also result from differences in topographical and geological parameters such as slope, melting water rivulets, and rock formation.
Periphyton is a major contributor to aquatic primary production and often competes with phytoplankton and submerged macrophytes for resources. In nutrient-limited environments, mobilization of sediment nutrients by groundwater can significantly affect periphyton (including epiphyton) development in shallow littoral zones and may affect other lake primary producers. We hypothesized that epiphyton growth in the littoral zone of temperate oligomesotrophic hard-water lakes could be stimulated by nutrient (especially P) supply via lacustrine groundwater discharge (LGD). We compared the dry mass, chlorophyll a (chl a), and nutrient content of epiphyton grown on artificial substrates at different sites in a groundwater-fed lake and in experimental chambers with and without LGD. During the spring-summer periods, epiphyton accumulated more biomass, especially algae, in littoral LGD sites and in experimental chambers with LGD compared to controls without LGD. Epiphyton chl a accumulation reached up to 46 mg chl a/m(2) after 4 wk when exposed to LGD, compared to a maximum of 23 mg chl a/m(2) at control (C) sites. In the field survey, differences in epiphyton biomass between LGD and C sites were most pronounced at the end of summer, when epilimnetic P concentrations were lowest and epiphyton C:P ratios indicated P limitation. Groundwater-borne P may have facilitated epiphyton growth on macrophytes and periphyton growth on littoral sediments. Epiphyton stored up to 35 mg P/m(2) in 4 wk (which corresponds to 13% of the total P content of the littoral waters), preventing its use by phytoplankton, and possibly contributing to the stabilization of a clear-water state. However, promotion of epiphyton growth by LGD may have contributed to an observed decline in macrophyte abundance caused by epiphyton shading and a decreased resilience of small charophytes to drag forces in shallow littoral areas of the studied lake in recent decades.
Understanding how variance in environmental factors affects physiological performance, population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-limitation theory into a single unified conceptual framework that has general applicability. We show how the framework can be applied (1) to generate mathematically tractable predictions of the physiological effects of multiple fluctuating co-limiting factors, (2) to understand how each co-limiting factor contributes to these effects, and (3) to detect mechanisms such as acclimation or physiological stress when they are at play. We show that the statistical covariance of co-limiting factors, which has not been considered before, can be a strong driver of physiological performance in various ecological contexts. Our framework can provide powerful insights on how the global change-induced shifts in multiple environmental factors affect the physiological performance of organisms.
In a changing world facing several direct or indirect anthropogenic challenges the freshwater resources are endangered in quantity and quality. An excessive supply of nutrients, for example, can cause disproportional phytoplankton development and oxygen deficits in large rivers, leading to failure of the aims requested by the Water Framework Directive (WFD). Such problems can be observed in many European river catchments including the Elbe basin, and effective measures for improving water quality status are highly appreciated.
In water resources management and protection, modelling tools can help to understand the dominant nutrient processes and to identify the main sources of nutrient pollution in a watershed. They can be effective instruments for impact assessments investigating the effects of changing climate or socio-economic conditions on the status of surface water bodies, and for testing the usefulness of possible protection measures. Due to the high number of interrelated processes, ecohydrological model approaches containing water quality components are more complex than the pure hydrological ones, and their setup and calibration require more efforts. Such models, including the Soil and Water Integrated Model (SWIM), still need some further development and improvement.
Therefore, this cumulative dissertation focuses on two main objectives: 1) the approach-related objectives aiming in the SWIM model improvement and further development regarding nutrient (nitrogen and phosphorus) process description, and 2) the application-related objectives in meso- to large-scale Elbe river basins to support adaptive river basin management in view of possible future changes. The dissertation is based on five scientific papers published in international journals and dealing with these research questions.
Several adaptations were implemented in the model code to improve the representation of nutrient processes including a simple wetland approach, an extended by ammonium nitrogen cycle in the soils, as well as a detailed in-stream module, simulating algal growth, nutrient transformation processes and oxygen conditions in the river reaches, mainly driven by water temperature and light. Although this new approaches created a highly complex ecohydrological model with a large number of additional calibration parameters and rising uncertainty, the calibration and validation of the SWIM model enhanced by the new approaches in selected subcatchment and the entire Elbe river basin delivered satisfactory to good model results in terms of criteria of fit. Thus, the calibrated and validated model provided a sound base for the assessment of possible future changes and impacts in climate, land use and management in the Elbe river (sub)basin(s).
The new enhanced modelling approach improved the applicability of the SWIM model for the WFD related research questions, where the ability to consider biological water quality components (such as phytoplankton) is important. It additionally enhanced its ability to simulate the behaviour of nutrients coming mainly from point sources (e.g. phosphate phosphorus). Scenario results can be used by decision makers and stakeholders to find and understand future challenges and possible adaptation measures in the Elbe river basin.
Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a-nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic-eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a-nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic-eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
Brown adipose tissue (BAT) is responsible for non-shivering thermogenesis, thereby allowing mammals to maintain a constant body temperature in a cold environment. Thermogenic capacity of this tissue is due to a high mitochondrial density and expression of uncoupling protein 1 (UCP1), a unique brown adipocyte marker which dissipates the mitochondrial proton gradient to produce heat instead of ATP. BAT is actively involved in whole-body metabolic homeostasis and during aging there is a loss of classical brown adipose tissue with concomitantly reduced browning capacity of white adipose tissue. Therefore, an age-dependent decrease of BAT-related energy expenditure capacity may exacerbate the development of metabolic diseases, including obesity and type 2 diabetes mellitus. Given that direct effects of age-related changes of BAT-metabolic flux have yet to be unraveled, the aim of the current thesis is to investigate potential metabolic mechanisms involved in BAT-dysfunction during aging and to identify suitable metabolic candidates as functional biomarkers of BAT-aging. To this aim, integration of transcriptomic, metabolomic and proteomic data analyses of BAT from young and aged mice was performed, and a group of candidates with age-related changes was revealed. Metabolomic analysis showed age-dependent alterations of metabolic intermediates involved in energy, nucleotide and vitamin metabolism, with major alterations regarding the purine nucleotide pool. These data suggest a potential role of nucleotide intermediates in age-related BAT defects. In addition, the screening of transcriptomic and proteomic data sets from BAT of young and aged mice allowed identification of a 60-kDa lysophospholipase, also known as L-asparaginase (Aspg), whose expression declines during BAT-aging. Involvement of Aspg in brown adipocyte thermogenic function was subsequently analyzed at the molecular level using in vitro approaches and animal models. The findings revealed sensitivity of Aspg expression to β3-adrenergic activation via different metabolic cues, including cold exposure and treatment with β3-adrenergic agonist CL. To further examine ASPG function in BAT, an over-expression model of Aspg in a brown adipocyte cell line was established and showed that these cells were metabolically more active compared to controls, revealing increased expression of the main brown-adipocyte specific marker UCP1, as well as higher lipolysis rates. An in vitro loss-of-function model of Aspg was also functionally analyzed, revealing reduced brown adipogenic characteristics and an impaired lipolysis, thus confirming physiological relevance of Aspg in brown adipocyte function. Characterization of a transgenic mouse model with whole-body inactivation of the Aspg gene (Aspg-KO) allowed investigation of the role of ASPG under in vivo conditions, indicating a mild obesogenic phenotype, hypertrophic white adipocytes, impairment of the early thermogenic response upon cold-stimulation and dysfunctional insulin sensitivity. Taken together, these data show that ASPG may represent a new functional biomarker of BAT-aging that regulates thermogenesis and therefore a potential target for the treatment of age-related metabolic disease.