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- Department Psychologie (6)
- Institut für Jüdische Studien und Religionswissenschaft (6)
Due to the unique environmental conditions and different feedback mechanisms, the Arctic region is especially sensitive to climate changes. The influence of clouds on the radiation budget is substantial, but difficult to quantify and parameterize in models. In the framework of the PhD, elastic backscatter and depolarization lidar observations of Arctic clouds were performed during the international Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) from Svalbard in March and April 2007. Clouds were probed above the inaccessible Arctic Ocean with a combination of airborne instruments: The Airborne Mobile Aerosol Lidar (AMALi) of the Alfred Wegener Institute for Polar and Marine Research provided information on the vertical and horizontal extent of clouds along the flight track, optical properties (backscatter coefficient), and cloud thermodynamic phase. From the data obtained by the spectral albedometer (University of Mainz), the cloud phase and cloud optical thickness was deduced. Furthermore, in situ observations with the Polar Nephelometer, Cloud Particle Imager and Forward Scattering Spectrometer Probe (Laboratoire de Météorologie Physique, France) provided information on the microphysical properties, cloud particle size and shape, concentration, extinction, liquid and ice water content. In the thesis, a data set of four flights is analyzed and interpreted. The lidar observations served to detect atmospheric structures of interest, which were then probed by in situ technique. With this method, an optically subvisible ice cloud was characterized by the ensemble of instruments (10 April 2007). Radiative transfer simulations based on the lidar, radiation and in situ measurements allowed the calculation of the cloud forcing, amounting to -0.4 W m-2. This slight surface cooling is negligible on a local scale. However, thin Arctic clouds have been reported more frequently in winter time, when the clouds' effect on longwave radiation (a surface warming of 2.8 W m-2) is not balanced by the reduced shortwave radiation (surface cooling). Boundary layer mixed-phase clouds were analyzed for two days (8 and 9 April 2007). The typical structure consisting of a predominantly liquid water layer on cloud top and ice crystals below were confirmed by all instruments. The lidar observations were compared to European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological analyses. A change of air masses along the flight track was evidenced in the airborne data by a small completely glaciated cloud part within the mixed-phase cloud system. This indicates that the updraft necessary for the formation of new cloud droplets at cloud top is disturbed by the mixing processes. The measurements served to quantify the shortcomings of the ECMWF model to describe mixed-phase clouds. As the partitioning of cloud condensate into liquid and ice water is done by a diagnostic equation based on temperature, the cloud structures consisting of a liquid cloud top layer and ice below could not be reproduced correctly. A small amount of liquid water was calculated for the lowest (and warmest) part of the cloud only. Further, the liquid water content was underestimated by an order of magnitude compared to in situ observations. The airborne lidar observations of 9 April 2007 were compared to space borne lidar data on board of the satellite Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The systems agreed about the increase of cloud top height along the same flight track. However, during the time delay of 1 h between the lidar measurements, advection and cloud processing took place, and a detailed comparison of small-scale cloud structures was not possible. A double layer cloud at an altitude of 4 km was observed with lidar at the West coast in the direct vicinity of Svalbard (14 April 2007). The cloud system consisted of two geometrically thin liquid cloud layers (each 150 m thick) with ice below each layer. While the upper one was possibly formed by orographic lifting under the influence of westerly winds, or by the vertical wind shear shown by ECMWF analyses, the lower one might be the result of evaporating precipitation out of the upper layer. The existence of ice precipitation between the two layers supports the hypothesis that humidity released from evaporating precipitation was cooled and consequently condensed as it experienced the radiative cooling from the upper layer. In summary, a unique data set characterizing tropospheric Arctic clouds was collected with lidar, in situ and radiation instruments. The joint evaluation with meteorological analyses allowed a detailed insight in cloud properties, cloud evolution processes and radiative effects.
A macro-tidal freshwater ecosystem recovering from hypereutrophication : the Schelde lease study
(2009)
We report a 40 year record of eutrophication and hypoxia on an estuarine ecosystem and its recovery from hypereutrophication. After decades of high inorganic nutrient concentrations and recurring anoxia and hypoxia, we observe a paradoxical increase in chlorophyll-a concentrations with decreasing nutrient inputs. We hypothesise that algal growth was inhibited due to hypereutrophication, either by elevated ammonium concentrations, severe hypoxia or the production of harmful substances in such a reduced environment. We study the dynamics of a simple but realistic mathematical model, incorporating the assumption of algal growth inhibition. It shows a high algal biomass, net oxygen production equilibrium with low ammonia inputs, and a low algal biomass, net oxygen consumption equilibrium with high ammonia inputs. At intermediate ammonia inputs it displays two alternative stable states. Although not intentional, the numerical output of this model corresponds to observations, giving extra support for assumption of algal growth inhibition. Due to potential algal growth inhibition, the recovery of hypereutrophied systems towards a classical eutrophied state, will need reduction of waste loads below certain thresholds and will be accompanied by large fluctuations in oxygen concentrations. We conclude that also flow-through systems, heavily influenced by external forcings which partly mask internal system dynamics, can display multiple stable states.
Rain fall-runoff response in temperate humid headwater catchments is mainly controlled by hydrolo gical processes at the hillslope scale. Applied tracer experiments with fluore scent dye and salt tracers are well known tools in groundwater studies at the large scale and vadose zone studies at the plot scale, where they provide a means to characterise subsurface flow. We extend this approach to the hillslope scale to investigate saturated and unsaturated flow path s concertedly at a forested hill slope in the Austrian Alps. Dye staining experiments at the plot scale revealed that crack s and soil pipe s function as preferential flow path s in the fine-textured soils of the study area, and these preferenti al flow structures were active in fast subsurface transport of tracers at the hillslope scale. Breakthrough curves obtained under steady flow conditions could be fitted well to a one-dimensional convection-dispersion model. Under natural rain fall a positive correlation of tracer concentrations to the transient flows was observed. The results of this study demon strate qualitative and quantitative effects of preferential flow feature s on subsurface stormflow in a temperate humid headwater catchment. It turn s out that , at the hill slope scale, the interaction s of structures and processes are intrinsically complex, which implies that attempts to model such a hillslope satisfactorily require detailed investigation s of effective structures and parameters at the scale of interest.
Many cellular processes require decision making mechanisms, which must act reliably even in the unavoidable presence of substantial amounts of noise. However, the multistable genetic switches that underlie most decision-making processes are dominated by fluctuations that can induce random jumps between alternative cellular states. Here we show, via theoretical modeling of a population of noise-driven bistable genetic switches, that reliable timing of decision-making processes can be accomplished for large enough population sizes, as long as cells are globally coupled by chemical means. In the light of these results, we conjecture that cell proliferation, in the presence of cell-cell communication, could provide a mechanism for reliable decision making in the presence of noise, by triggering cellular transitions only when the whole cell population reaches a certain size. In other words , the summation performed by the cell population would average out the noise and reduce its detrimental impact.
This thesis investigates the Casimir effect between plates made of normal and superconducting metals over a broad range of temperatures, as well as the Casimir-Polder interaction of an atom to such a surface. Numerical and asymptotical calculations have been the main tools in order to do so. The optical properties of the surfaces are described by dielectric functions or optical conductivities, which are reviewed for common models and have been analyzed with special weight on distributional properties and causality. The calculation of the Casimir energy between two normally conducting plates (cavity) is reviewed and previous work on the contribution to the Casimir energy due to the surface plasmons, present in all metallic cavities, has been generalized to finite temperatures for the first time. In the field of superconductivity, a new analytical continuation of the BCS conductivity to to purely imaginary frequencies has been obtained both inside and outside the extremely dirty limit of vanishing mean free path. The Casimir free energy calculated from this description was shown to coincide well with the values obtained from the two fluid model of superconductivity in certain regimes of the material parameters. The Casimir entropy in a superconducting cavity fulfills the third law of thermodynamics and features a characteristic discontinuity at the phase transition temperature. These effects were equally encountered in the Casimir-Polder interaction of an atom with a superconducting wall. The magnetic dipole coupling of an atom to a metal was shown to be highly sensible to dissipation and especially to the surface currents. This leads to a strong quenching of the magnetic Casimir-Polder energy at finite temperature. Violations of the third law of thermodynamics are encountered in special models, similar to phenomena in the Casimir-effect between two plates, that are debated controversely. None of these effects occurs in the analog electric dipole interaction. The results of this work suggest to reestablish the well-known plasma model as the low temperature limit of a superconductor as in London theory rather than use it for the description of normal metals. Superconductors offer the opportunity to control the dissipation of surface currents to a great extent. This could be used to access experimentally the low frequency optical response of metals, which is strongly connected to the thermal Casimir-effect. Here, differently from corresponding microwave experiments, energy and momentum are independent quantities. A measurement of the total Casimir-Polder interaction of atoms with superconductors seems to be in reach in today’s microchip-based atom-traps and the contribution due to magnetic coupling might be accessed by spectroscopic techniques
Submarine landslides can generate local tsunamis posing a hazard to human lives and coastal facilities. Two major related problems are: (i) quantitative estimation of tsunami hazard and (ii) early detection of the most dangerous landslides. This thesis focuses on both those issues by providing numerical modeling of landslide-induced tsunamis and by suggesting and justifying a new method for fast detection of tsunamigenic landslides by means of tiltmeters. Due to the proximity to the Sunda subduction zone, Indonesian coasts are prone to earthquake, but also landslide tsunamis. The aim of the GITEWS-project (German-Indonesian Tsunami Early Warning System) is to provide fast and reliable tsunami warnings, but also to deepen the knowledge about tsunami hazards. New bathymetric data at the Sunda Arc provide the opportunity to evaluate the hazard potential of landslide tsunamis for the adjacent Indonesian islands. I present nine large mass movements in proximity to Sumatra, Java, Sumbawa and Sumba, whereof the largest event displaced 20 km³ of sediments. Using numerical modeling, I compute the generated tsunami of each event, its propagation and runup at the coast. Moreover, I investigate the age of the largest slope failures by relating them to the Great 1977 Sumba earthquake. Continental slopes off northwest Europe are well known for their history of huge underwater landslides. The current geological situation west of Spitsbergen is comparable to the continental margin off Norway after the last glaciation, when the large tsunamigenic Storegga slide took place. The influence of Arctic warming on the stability of the Svalbard glacial margin is discussed. Based on new geophysical data, I present four possible landslide scenarios and compute the generated tsunamis. Waves of 6 m height would be capable of reaching northwest Europe threatening coastal areas. I present a novel technique to detect large submarine landslides using an array of tiltmeters, as a possible tool in future tsunami early warning systems. The dislocation of a large amount of sediment during a landslide produces a permanent elastic response of the earth. I analyze this response with a mathematical model and calculate the theoretical tilt signal. Applications to the hypothetical Spitsbergen event and the historical Storegga slide show tilt signals exceeding 1000 nrad. The amplitude of landslide tsunamis is controlled by the product of slide volume and maximal velocity (slide tsunamigenic potential). I introduce an inversion routine that provides slide location and tsunamigenic potential, based on tiltmeter measurements. The accuracy of the inversion and of the estimated tsunami height near the coast depends on the noise level of tiltmeter measurements, the distance of tiltmeters from the slide, and the slide tsunamigenic potential. Finally, I estimate the applicability scope of this method by employing it to known landslide events worldwide.
In this thesis, the properties of nonlinear disordered one dimensional lattices is investigated. Part I gives an introduction to the phenomenon of Anderson Localization, the Discrete Nonlinear Schroedinger Equation and its properties as well as the generalization of this model by introducing the nonlinear index α. In Part II, the spreading behavior of initially localized states in large, disordered chains due to nonlinearity is studied. Therefore, different methods to measure localization are discussed and the structural entropy as a measure for the peak structure of probability distributions is introduced. Finally, the spreading exponent for several nonlinear indices is determined numerically and compared with analytical approximations. Part III deals with the thermalization in short disordered chains. First, the term thermalization and its application to the system in use is explained. Then, results of numerical simulations on this topic are presented where the focus lies especially on the energy dependence of the thermalization properties. A connection with so-called breathers is drawn.
Pectic polysaccharides, a class of plant cell wall polymers, form one of the most complex networks known in nature. Despite their complex structure and their importance in plant biology, little is known about the molecular mechanism of their biosynthesis, modification, and turnover, particularly their structure-function relationship. One way to gain insight into pectin metabolism is the identification of mutants with an altered pectin structure. Those were obtained by a recently developed pectinase-based genetic screen. Arabidopsis thaliana seedlings grown in liquid medium containing pectinase solutions exhibited particular phenotypes: they were dwarfed and slightly chlorotic. However, when genetically different A. thaliana seed populations (random T-DNA insertional populations as well as EMS-mutagenized populations and natural variations) were subjected to this treatment, individuals were identified that exhibit a different visible phenotype compared to wild type or other ecotypes and may thus contain a different pectin structure (pec-mutants). After confirming that the altered phenotype occurs only when the pectinase is present, the EMS mutants were subjected to a detailed cell wall analysis with particular emphasis on pectins. This suite of mutants identified in this study is a valuable resource for further analysis on how the pectin network is regulated, synthesized and modified. Flanking sequences of some of the T-DNA lines have pointed toward several interesting genes, one of which is PEC100. This gene encodes a putative sugar transporter gene, which, based on our data, is implicated in rhamnogalacturonan-I synthesis. The subcellular localization of PEC100 was studied by GFP fusion and this protein was found to be localized to the Golgi apparatus, the organelle where pectin biosynthesis occurs. Arabidopsis ecotype C24 was identified as a susceptible one when grown with pectinases in liquid culture and had a different oligogalacturonide mass profile when compared to ecotype Col-0. Pectic oligosaccharides have been postulated to be signal molecules involved in plant pathogen defense mechanisms. Indeed, C24 showed elevated accumulation of reactive oxygen species upon pectinase elicitation and had altered response to the pathogen Alternaria brassicicola in comparison to Col-0. Using a recombinant inbred line population three major QTLs were identified to be responsible for the susceptibility of C24 to pectinases. In a reverse genetic approach members of the qua2 (putative pectin methyltransferase) family were tested for potential target genes that affect pectin methyl-esterification. The list of these genes was determined by in silico study of the pattern of expression and co-expression of all 34 members of this family resulting in 6 candidate genes. For only for one of the 6 analyzed genes a difference in the oligogalacturonide mass profile was observed in the corresponding knock-out lines, confirming the hypothesis that the methyl-esterification pattern of pectin is fine tuned by members of this gene family. This study of pectic polysaccharides through forward and reverse genetic screens gave new insight into how pectin structure is regulated and modified, and how these modifications could influence pectin mediated signalling and pathogenicity.
Trying to do two things at once decreases performance of one or both tasks in many cases compared to the situation when one performs each task by itself. The present thesis deals with the question why and in which cases these dual-task costs emerge and moreover, whether there are cases in which people are able to process two cognitive tasks at the same time without costs. In four experiments the influence of stimulus-response (S-R) compatibility, S-R modality pairings, interindividual differences, and practice on parallel processing ability of two tasks are examined. Results show that parallel processing is possible. Nevertheless, dual-task costs emerge when: the personal processing strategy is serial, the two tasks have not been practiced together, S-R compatibility of both tasks is low (e.g. when a left target has to be responded with a right key press and in the other task an auditorily presented “A” has to be responded by saying “B”), and modality pairings of both tasks are Non Standard (i.e., visual-spatial stimuli are responded vocally whereas auditory-verbal stimuli are responded manually). Results are explained with respect to executive-based (S-R compatibility) and content-based crosstalk (S-R modality pairings) between tasks. Finally, an alternative information processing account with respect to the central stage of response selection (i.e., the translation of the stimulus to the response) is presented.
Myrmecochory, i.e. dispersal of seeds by ants towards and around their nests, plays an important role in temperate forests. Yet hardly any study has examined plant population spread over several years and the underlying joint contribution of a hierarchy of dispersal modes and plant demography. We used a seed-sowing approach with three replicates to examine colonization patterns of Melampyrum pratense, an annual myrmecochorous herb, in a mixed Scots pine forest in northeastern Germany. Using a spatially explicit individualbased (SEIB) model population patterns over 4 years were explained by short-distance transport of seeds by small ant species with high nest densities, resulting in random spread. However, plant distributions in the field after another 4 years were clearly deviating from model predictions. Mean annual spread rate increased from 0.9 m to 5.1 m per year, with a clear inhomogeneous component. Obviously, after a lag-phase of several years, non-random seed dispersal by large red wood ants (Formica rufa) was determining the species’ spread, thus resulting in stratified dispersal due to interactions with different-sized ant species. Hypotheses on stratified dispersal, on dispersal lag, and on non-random dispersal were verified using an extended SEIB model, by comparison of model outputs with field patterns (individual numbers, population areas, and maximum distances). Dispersal towards red wood ant nests together with seed loss during transport and redistribution around nests were essential features of the model extension. The observed lag-phase in the initiation of non-random, medium-distance transport was probably due to a change of ant behaviour towards a new food source of increasing importance, being a meaningful example for a lag-phase in local plant species invasion. The results demonstrate that field studies should check model predictions wherever possible. Future research will show whether or not the M. pratense–ant system is representative for migration patterns of similar animal dispersal systems after having crossed range edges by long-distance dispersal events.
Background: The EXO (EXORDIUM) gene was identified as a potential mediator of brassinosteroid (BR)-promoted growth. It is part of a gene family with eight members in Arabidopsis. EXO gene expression is under control of BR, and EXO overexpression promotes shoot and root growth. In this study, the consequences of loss of EXO function are described. Results: The exo loss of function mutant showed diminished leaf and root growth and reduced biomass production. Light and scanning electron microscopy analyses revealed that impaired leaf growth is due to reduced cell expansion. Epidermis, palisade, and spongy parenchyma cells were smaller in comparison to the wild-type. The exo mutant showed reduced brassinolide-induced cotyledon and hypocotyl growth. In contrast, exo roots were significantly more sensitive to the inhibitory effect of synthetic brassinolide. Apart from reduced growth, exo did not show severe morphological abnormalities. Gene expression analyses of leaf material identified genes that showed robust EXO-dependent expression. Growth-related genes such as WAK1, EXP5, and KCS1, and genes involved in primary and secondary metabolism showed weaker expression in exo than in wild-type plants. However, the vast majority of BR-regulated genes were normally expressed in exo. HA- and GFP-tagged EXO proteins were targeted to the apoplast. Conclusion: The EXO gene is essential for cell expansion in leaves. Gene expression patterns and growth assays suggest that EXO mediates BR-induced leaf growth. However, EXO does not control BR-levels or BR-sensitivity in the shoot. EXO presumably is involved in a signalling process which coordinates BR-responses with environmental or developmental signals. The hypersensitivity of exo roots to BR suggests that EXO plays a diverse role in the control of BR responses in the root.
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physicsbased model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.
Background: Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results: We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion: While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structurebased P-site prediction method has been made available at http://phos3d.mpimp-golm.mpg.de.
Background: Mitochondrial genomes are a valuable source of data for analysing phylogenetic relationships. Besides sequence information, mitochondrial gene order may add phylogenetically useful information, too. Sipuncula are unsegmented marine worms, traditionally placed in their own phylum. Recent molecular and morphological findings suggest a close affinity to the segmented Annelida. Results: The first complete mitochondrial genome of a member of Sipuncula, Sipunculus nudus, is presented. All 37 genes characteristic for metazoan mtDNA were detected and are encoded on the same strand. The mitochondrial gene order (protein-coding and ribosomal RNA genes) resembles that of annelids, but shows several derivations so far found only in Sipuncula. Sequence based phylogenetic analysis of mitochondrial protein-coding genes results in significant bootstrap support for Annelida sensu lato, combining Annelida together with Sipuncula, Echiura, Pogonophora and Myzostomida. Conclusion: The mitochondrial sequence data support a close relationship of Annelida and Sipuncula. Also the most parsimonious explanation of changes in gene order favours a derivation from the annelid gene order. These results complement findings from recent phylogenetic analyses of nuclear encoded genes as well as a report of a segmental neural patterning in Sipuncula.
For three small, mountainous catchments in Germany two medium-range forecast systems are compared that predict precipitation for up to 5 days in advance. One system is composed of the global German weather service (DWD) model, GME, which is dynamically downscaled using the COSMO-EU regional model. The other system is an empirical (expanded) downscaling of the ECMWF model IFS. Forecasts are verified against multi-year daily observations, by applying standard skill scores to events of specified intensity. All event classes are skillfully predicted by the empirical system for up to five days lead time. For the available prediction range of one to two days it is superior to the dynamical system.
ChlamyCyc : an integrative systems biology database and web-portal for Chlamydomonas reinhardtii
(2009)
Background: The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern highthroughput technologies there is an imperative need to integrate large-scale data sets from highthroughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. Results: In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. Conclusion: ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.
Background: The loss of photosynthesis has occurred often in eukaryotic evolution, even more than its acquisition, which occurred at least nine times independently and which generated the evolution of the supergroups Archaeplastida, Rhizaria, Chromalveolata and Excavata. This secondary loss of autotrophic capability is essential to explain the evolution of eukaryotes and the high diversity of protists, which has been severely underestimated until recently. However, the ecological and evolutionary scenarios behind this evolutionary ‘‘step back’’ are still largely unknown. Methodology/Principal Findings: Using a dynamic model of heterotrophic and mixotrophic flagellates and two types of prey, large bacteria and ultramicrobacteria, we examine the influence of DOC concentration, mixotroph’s photosynthetic growth rate, and external limitations of photosynthesis on the coexistence of both types of flagellates. Our key premises are: large bacteria grow faster than small ones at high DOC concentrations, and vice versa; and heterotrophic flagellates are more efficient than the mixotrophs grazing small bacteria (both empirically supported). We show that differential efficiency in bacteria grazing, which strongly depends on cell size, is a key factor to explain the loss of photosynthesis in mixotrophs (which combine photosynthesis and bacterivory) leading to purely heterotrophic lineages. Further, we show in what conditions an heterotroph mutant can coexist, or even out-compete, its mixotrophic ancestor, suggesting that bacterivory and cell size reduction may have been major triggers for the diversification of eukaryotes. Conclusions/Significance: Our results suggest that, provided the mixotroph’s photosynthetic advantage is not too large, the (small) heterotroph will also dominate in nutrient-poor environments and will readily invade a community of mixotrophs and bacteria, due to its higher efficiency exploiting the ultramicrobacteria. As carbon-limited conditions were presumably widespread throughout Earth history, such a scenario may explain the numerous transitions from phototrophy to mixotrophy and further to heterotrophy within virtually all major algal lineages. We challenge prevailing concepts that affiliated the evolution of phagotrophy with eutrophic or strongly light-limited environments only.
We propose two strategies to characterize organisms with respect to their metabolic capabilities. The first, investigative, strategy describes metabolic networks in terms of their capability to utilize different carbon sources, resulting in the concept of carbon utilization spectra. In the second, predictive, approach minimal nutrient combinations are predicted from the structure of the metabolic networks, resulting in a characteristic nutrient profile. Both strategies allow for a quantification of functional properties of metabolic networks, allowing to identify groups of organisms with similar functions. We investigate whether the functional description reflects the typical environments of the corresponding organisms by dividing all species into disjoint groups based on whether they are aerotolerant and/or photosynthetic. Despite differences in the underlying concepts, both measures display some common features. Closely related organisms often display a similar functional behavior and in both cases the functional measures appear to correlate with the considered classes of environments. Carbon utilization spectra and nutrient profiles are complementary approaches toward a functional classification of organism-wide metabolic networks. Both approaches contain different information and thus yield different clusterings, which are both different from the classical taxonomy of organisms. Our results indicate that a sophisticated combination of our approaches will allow for a quantitative description reflecting the lifestyles of organisms.
The ability of an organism to survive depends on its capability to adapt to external conditions. In addition to metabolic versatility and efficient replication, reliable signal transduction is essential. As signaling systems are under permanent evolutionary pressure one may assume that their structure reflects certain functional properties. However, despite promising theoretical studies in recent years, the selective forces which shape signaling network topologies in general remain unclear. Here, we propose prevention of autoactivation as one possible evolutionary design principle. A generic framework for continuous kinetic models is used to derive topological implications of demanding a dynamically stable ground state in signaling systems. To this end graph theoretical methods are applied. The index of the underlying digraph is shown to be a key topological property which determines the so-called kinetic ground state (or off-state) robustness. The kinetic robustness depends solely on the composition of the subdigraph with the strongly connected components, which comprise all positive feedbacks in the network. The component with the highest index in the feedback family is shown to dominate the kinetic robustness of the whole network, whereas relative size and girth of these motifs are emphasized as important determinants of the component index. Moreover, depending on topological features, the maintenance of robustness differs when networks are faced with structural perturbations. This structural off-state robustness, defined as the average kinetic robustness of a network’s neighborhood, turns out to be useful since some structural features are neutral towards kinetic robustness, but show up to be supporting against structural perturbations. Among these are a low connectivity, a high divergence and a low path sum. All results are tested against real signaling networks obtained from databases. The analysis suggests that ground state robustness may serve as a rationale for some structural peculiarities found in intracellular signaling networks.
With the increasing availability of observational data from different sources at a global level, joint analysis of these data is becoming especially attractive. For such an analysis – oftentimes with little prior knowledge about local and global interactions between the different observational variables at hand – an exploratory, data-driven analysis of the data may be of particular relevance. In the present work we used generalized additive models (GAM) in an exemplary study of spatio-temporal patterns in the tropospheric NO2-distribution derived from GOME satellite observations (1996 to 2001) at global scale. We focused on identifying correlations between NO2 and local wind fields, a quantity which is of particular interest in the analysis of spatio-temporal interactions. Formulating general functional, parametric relationships between the observed NO2 distribution and local wind fields, however, is difficult – if not impossible. So, rather than following a modelbased analysis testing the data for predefined hypotheses (assuming, for example, sinusoidal seasonal trends), we used a GAM with non-parametric model terms to learn this functional relationship between NO2 and wind directly from the data. The NO2 observations showed to be affected by winddominated processes over large areas. We estimated the extent of areas affected by specific NO2 emission sources, and were able to highlight likely atmospheric transport “pathways”. General temporal trends which were also part of our model – weekly, seasonal and linear changes – showed to be in good agreement with previous studies and alternative ways of analysing the time series. Overall, using a non-parametric model provided favorable means for a rapid inspection of this large spatio-temporal NO2 data set, with less bias than parametric approaches, and allowing to visualize dynamical processes of the NO2 distribution at a global scale.