Population biology and diet of the southern kingcroaker Menticirrhus americanus (Linnaeus, 1758) (Perciformes: Sciaenidae) in Caraguatatuba Bay, southeastern Brazil

This study evaluated the spatio-temporal distribution, population biology and diet of Menticirrhus americanus in Caraguatatuba Bay. Samples were taken monthly between August 2003 and October 2004, by trawling in two previously selected areas. The northern area is more exposed to wave activity and is influenced by a river, functioning as a small estuary. In contrast, the southern area is relatively sheltered from wave energy and influenced to a lesser degree by smaller rivers. The fishes' length was measured, and the sex and gonadal stage macroscopically identified. The abundance of this species was compared between areas and among months. The diet was identified and quantified. M. americanus occurred in equal proportions in the two study areas, being most abundant in April 2004, followed by December 2003 and January 2004. The population was dominated by small immature individuals. The few individuals in maturation or mature that were captured showed no seasonal pattern of distribution. This species had a varied diet, feeding on worms (nemerteans, sipunculans and echiurans), mollusks (bivalves and cephalopods), polychaetes, crustaceans and fish. The presence of intact nematodes in the intestine suggests that these are parasites. The results demonstrated that M. americanus has a homogeneous spatial and temporal distribution in Caraguatatuba Bay, being uniformly distributed between the south and north areas as well as across the months. This species can be considered a carnivorous predator, showing a preference for consuming benthic sandy-beach species such as glycerids and other polychaetes, crustaceans, and bivalve siphons.

Urediospores of rust fungi are ice nucleation active at > -10°C and harbor ice nucleation active bacteria

Various features of the biology of the rust fungi and of the epidemiology of the plant diseases they cause illustrate the important role of rainfall in their life history. Based on this insight we have characterized the ice nucleation activity (INA) of the aerially disseminated spores (urediospores) of this group of fungi. Urediospores of this obligate plant parasite were collected from natural infections of 7 species of weeds in France, from coffee in Brazil and from field and greenhouse-grown wheat in France, the USA, Turkey and Syria. Immersion freezing was used to determine freezing onset temperatures and the abundance of ice nuclei in suspensions of washed spores. Microbiological analyses of spores from France, the USA and Brazil, and subsequent tests of the ice nucleation activity of the bacteria associated with spores were deployed to quantify the contribution of bacteria to the ice nucleation activity of the spores. All samples of spores were ice nucleation active, having freezing onset temperatures as high as −4 °C. Spores in most of the samples carried cells of ice nucleation-active strains of the bacterium Pseudomonas syringae (at rates of less than 1 bacterial cell per 100 urediospores), but bacterial INA accounted for only a small fraction of the INA observed in spore suspensions. Changes in the INA of spore suspensions after treatment with lysozyme suggest that the INA of urediospores involves a polysaccharide. Based on data from the literature, we have estimated the concentrations of urediospores in air at cloud height and in rainfall. These quantities are very similar to those reported for other biological ice nucleators in these same substrates. However, at cloud level convective activity leads to widely varying concentrations of particles of surface origin, so that mean concentrations can underestimate their possible effects on clouds. We propose that spatial and temporal concentrations of biological ice nucleators active at temperatures > −10 °C and the specific conditions under which they can influence cloud glaciation need to be further evaluated so as to understand how evolutionary processes could have positively selected for INA.

Human Abuses of Coral Reefs- Adaptive Responses and Regime Transitions

During the last few decades, coral reefs have become a disappearing feature of tropical marine environments, and those reefs that do remain are severely threatened. It is understood that humans have greately altered the environment under which these ecosystems previously have thrived and evoloved. Overharvesting of fish stocks, global warming and pollution are some of the most prominent threats, acting on coral reefs at several spatial and temporal scales. Presently, it is common that coral reefs have been degraded into alternative ecosystem regimes, such as macroalgae-dominated or sea urchin-barren. Although these ecosystems could potentially return to coral dominance in a long-term perspective, when considdering current conditions, it seems likely that they will persist in their degraded states. Thus, recovery of coral reefs cannot be taken for granted on a human timescale. Multiple stressors and disturbances, which are increasingly characteristic of coral reef environments today, are believed to act synergistically and produce ecological surprises. However, current knowledge of effects of compounded disturbances and stress is limited. Based on five papers, this thesis investigates the sublethal response of multiple stressors on coral physiology, as well as the effects of compounded stress and disturbance on coral reef structure and function. Adaptive responses to stress and disturbance in relation to prior experience are highlighted. The thesis further explores how inherent characteristics (traits) of corals and macroalgae may influence regime expression when faced with altered disturbance regimes, in particular overfishing, eutrophication, elevated temperature, and enhanced substrate availability. Finally, possibilities of affecting the resilience of macroalgae-dominaed reefs and shifting the community composition towards a coral-dominated regime are explored.

Database of diazotrophs in global ocean: abundances, biomass and nitrogen fixation rates

[EN] Marine N2 fixing microorganisms, termed diazotrophs, are a key functional group in marine pelagic ecosystems. The biological fixation of dinitrogen (N2) to bioavailable nitrogen provides an important new source of nitrogen for pelagic marine ecosystems 5 and influences primary productivity and organic matter export to the deep ocean. As one of a series of efforts to collect biomass and rates specific to different phytoplankton functional groups, we have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling about 12 000 direct field measurements of cyanobacterial diazotroph abundances (based on microscopic cell counts or qPCR 10 assays targeting the nifH genes) and N2 fixation rates. Biomass conversion factors are estimated based on cell sizes to convert  abundance data to diazotrophic biomass. The database is limited spatially, lacking large regions of the ocean especially in the Indian Ocean. The data are approximately log-normal distributed, and large variances exist in most sub-databases with non-zero values differing 5 to 8 orders of magnitude. 15 Lower mean N2 fixation rate was found in the North Atlantic Ocean than the Pacific Ocean. Reporting the geometric mean and the range of one geometric standard error below and above the geometric mean, the pelagic N2 fixation rate in the global ocean is estimated to be 62 (53–73) TgNyr−1 and the pelagic diazotrophic biomass in the global ocean is estimated to be 4.7 (2.3–9.6) TgC from cell counts and to 89 (40–20 200) TgC from nifH-based abundances. Uncertainties related to biomass conversion factors can change the estimate of geometric mean pelagic diazotrophic biomass in the global ocean by about ±70 %. This evolving database can be used to study spatial and temporal distributions and variations of marine N2 fixation, to validate geochemical estimates and to parameterize and validate biogeochemical models. The database is 25 stored in PANGAEA (http://doi.pangaea.de/10.1594/PANGAEA.774851).

Temporal constraints in large optical flow estimation

[EN] The aim of this work is to propose a model for computing the optical flow in a sequence of images. We introduce a new temporal regularizer that is suitable for large displacements. We propose to decouple the spatial and temporal regularizations to avoid an incongruous formulation. For the spatial regularization we use the Nagel-Enkelmann operator and a newly designed temporal regularization. Our model is based on an energy functional that yields a partial differential equation (PDE). This PDE is embedded into a multipyramidal strategy to recover large displacements. A gradient descent technique is applied at each scale to reach the minimum.

The use of image analysis systems for the assesment of zooplankton physiological rates and carbon fluxes

Trabajo realizado por: Garijo, J. C., Hernández León, S.

Length scales of dynamic heterogeneities of low and high molecular weight glass formers from multidimensional NMR

Das Ziel der vorliegenden Arbeit ist die Untersuchung der räumlichen und zeitlichen Aspekte der heterogenen Dynamik in Modellglasbildnern. Dabei wird vor allem die langsame alpha-Relaxationsdynamik oberhalb des Glasüberganges Tg untersucht. Die nukleare Magnetresonanz zeigt ihre einmalige Vielseitigkeit bei der Untersuchung molekularer Dynamik, wenn die angewandten Techniken und Experimente durch Simulationen unterstützt werden. Die räumliche Aspekt dynamischer Heterogenitäten wird untersucht durch ein reduziertes vierdimensionales Spindiffusionsexperiment (4D3CP), ein Experiment, das Reorientierungsraten örtlich korreliert. Eine Simulation dieses Experimentes an einem System harter Kugeln liefert wertvolle Informationen über die Auswertemethode des 4D3CP Experiments. Glycerol und o-terphenyl werden durch das 4D3CP Experiment untersucht. Die erhaltenen Resultate werden mit bereits publizierten Daten des polymeren Glasbildners PVAc verglichen. Während PVAc und o-terphenyl eine Längenskale von 3.7 nm bzw. 2.9 nm aufweisen, ist die Längenskale von Glycerol signifikant kleiner bei 1.1 nm. Ein neues Experiment, welches sensitiv auf Translationsbewegung reagiert, wird vorgestellt. Durch Verwendung eines pi-Impulszuges kann eine separate Evolution unter dem Hamiltonian der dipolaren Kopplung und der chemischen Verschiebungsanisotropie erreicht werden.

Multi-level models and infrastructures for simulating biological system development

The hierarchical organisation of biological systems plays a crucial role in the pattern formation of gene expression resulting from the morphogenetic processes, where autonomous internal dynamics of cells, as well as cell-to-cell interactions through membranes, are responsible for the emergent peculiar structures of the individual phenotype. Being able to reproduce the systems dynamics at different levels of such a hierarchy might be very useful for studying such a complex phenomenon of self-organisation. The idea is to model the phenomenon in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartment events determines the emergent behaviour resulting in the formation of spatial patterns. According to these premises the thesis proposes a review of the different approaches already developed in modelling developmental biology problems, as well as the main models and infrastructures available in literature for modelling biological systems, analysing their capabilities in tackling multi-compartment / multi-level models. The thesis then introduces a practical framework, MS-BioNET, for modelling and simulating these scenarios exploiting the potential of multi-level dynamics. This is based on (i) a computational model featuring networks of compartments and an enhanced model of chemical reaction addressing molecule transfer, (ii) a logic-oriented language to flexibly specify complex simulation scenarios, and (iii) a simulation engine based on the many-species/many-channels optimised version of Gillespie’s direct method. The thesis finally proposes the adoption of the agent-based model as an approach capable of capture multi-level dynamics. To overcome the problem of parameter tuning in the model, the simulators are supplied with a module for parameter optimisation. The task is defined as an optimisation problem over the parameter space in which the objective function to be minimised is the distance between the output of the simulator and a target one. The problem is tackled with a metaheuristic algorithm. As an example of application of the MS-BioNET framework and of the agent-based model, a model of the first stages of Drosophila Melanogaster development is realised. The model goal is to generate the early spatial pattern of gap gene expression. The correctness of the models is shown comparing the simulation results with real data of gene expression with spatial and temporal resolution, acquired in free on-line sources.

Hepatobiliary diseases in small animals: a comparison of ultrasonography and multidetector-row computed tomography

Ultrasonography (US) is an essential imaging tool for identifying abnormalities of the liver parenchyma, biliary tract and vascular system. US has replaced radiography as the initial imaging procedure in screening for liver disease in small animals. There are few reports of the use of conventional and helical computed tomography (CT) to assess canine or feline parenchymal and neoplastic liver disease and biliary disorders. In human medicine the development of multidetector- row helical computed tomography (MDCT), with its superior spatial and temporal resolution, has resulted in improved detection and characterization of diffuse and focal liver lesions. The increased availability of MDCT in veterinary practice provides incentive to develop MDCT protocols for liver imaging in small animals. The purpose of this study is to assess the rule of MDCT in the characterization of hepatobiliary diseases in small animals; and to compare this method with conventional US. Candidates for this prospective study were 175 consecutive patients (dogs and cats) referred for evaluation of hepatobiliary disease. The patients underwent liver US and MDCT. Percutaneous needle biopsy was performed on all liver lesions or alterations encountered. As for gallbladder, histopatological evaluation was obtained from cholecystectomy specimens. Ultrasonographic findings in this study agreed well with those of previous reports. A protocol for dual-phase liver MDCT in small animals has been described. MDCT findings in parenchymal disorders of the liver, hepatic neoplasia and biliary disorders are here first described in dogs and cats and compared with the corresponding features in human medicine. The ability of MDCT in detection and characterization of hepatobiliary diseases in small animals is overall superior to conventional US. Ultrasonography and MDCT scanning, however, play complementary rules in the evaluation of these diseases. Many conditions have distinctive imaging features that may permit diagnosis. In most instances biopsy is required for definitive diagnosis.

Simulations of physics and chemistry of polar stratospheric clouds with a general circulation model

A polar stratospheric cloud submodel has been developed and incorporated in a general circulation model including atmospheric chemistry (ECHAM5/MESSy). The formation and sedimentation of polar stratospheric cloud (PSC) particles can thus be simulated as well as heterogeneous chemical reactions that take place on the PSC particles. For solid PSC particle sedimentation, the need for a tailor-made algorithm has been elucidated. A sedimentation scheme based on first order approximations of vertical mixing ratio profiles has been developed. It produces relatively little numerical diffusion and can deal well with divergent or convergent sedimentation velocity fields. For the determination of solid PSC particle sizes, an efficient algorithm has been adapted. It assumes a monodisperse radii distribution and thermodynamic equilibrium between the gas phase and the solid particle phase. This scheme, though relatively simple, is shown to produce particle number densities and radii within the observed range. The combined effects of the representations of sedimentation and solid PSC particles on vertical H2O and HNO3 redistribution are investigated in a series of tests. The formation of solid PSC particles, especially of those consisting of nitric acid trihydrate, has been discussed extensively in recent years. Three particle formation schemes in accordance with the most widely used approaches have been identified and implemented. For the evaluation of PSC occurrence a new data set with unprecedented spatial and temporal coverage was available. A quantitative method for the comparison of simulation results and observations is developed and applied. It reveals that the relative PSC sighting frequency can be reproduced well with the PSC submodel whereas the detailed modelling of PSC events is beyond the scope of coarse global scale models. In addition to the development and evaluation of new PSC submodel components, parts of existing simulation programs have been improved, e.g. a method for the assimilation of meteorological analysis data in the general circulation model, the liquid PSC particle composition scheme, and the calculation of heterogeneous reaction rate coefficients. The interplay of these model components is demonstrated in a simulation of stratospheric chemistry with the coupled general circulation model. Tests against recent satellite data show that the model successfully reproduces the Antarctic ozone hole.

Micro-simulation models at neighbourhood scale: the interplay of agents, buildings, activities and transport.

Urban systems consist of several interlinked sub-systems - social, economic, institutional and environmental – each representing a complex system of its own and affecting all the others at various structural and functional levels. An urban system is represented by a number of “human” agents, such as individuals and households, and “non-human” agents, such as buildings, establishments, transports, vehicles and infrastructures. These two categories of agents interact among them and simultaneously produce impact on the system they interact with. Try to understand the type of interactions, their spatial and temporal localisation to allow a very detailed simulation trough models, turn out to be a great effort and is the topic this research deals with. An analysis of urban system complexity is here presented and a state of the art review about the field of urban models is provided. Finally, six international models - MATSim, MobiSim, ANTONIN, TRANSIMS, UrbanSim, ILUTE - are illustrated and then compared.

Anatomic study of the feline bronchial and vascular structures with a 64 detector-row computed tomography

Multidetector row computed tomography over the last decade is commonly used in veterinary medicine. This new technology has an increased spatial and temporal resolution, could evaluate wider scanning range in shorter scanning time, providing an advanced imaging modality. Computed tomography angiographic studies are commonly used in veterinary medicine in order to evaluate vascular structures of the abdomen and the thorax. Pulmonary pathology in feline patients is a very common condition and usually is further evaluating with computed tomography. Up to date few references of the normal computed tomographic aspects of the feline thorax are reported. In this study a computed tomographic pulmonary angiography (CTPA) protocol is reported in normal cats and is compared with the up to date anatomical references. A CTPA protocol using a 64 MDCT in our study achieved high resolution images of the pulmonary arteries, pulmonary veins and bronchial lumen till the level of minor segmental branches. Feline pulmonary bronchial parenchyma demonstrates an architecture of mixed type with a monopedial model observed in the most anatomical parts and the dichotomic aspect is seen at the accessory lobe. The arterial and venous architecture is similar to the bronchial. Statistical analysis demonstrates the linear correlation of tracheal diameter to the felines weight. Vascular variations were noticed. The pulmonary venous system enters into the left atrium through three ostia (left cranial ostia: consisted of the anastomosis of the cranial and caudal portion of the left cranial pulmonary vein; right ostia: consisted of the anastomosis of the right cranial and middle pulmonary vein; and the caudal ostia: consisted of the anastomosis of the right and left caudal pulmonary vein). In conclusion CTPA is applicable in feline patients and provides an excellent imaging of the pulmonary arterial, venous and bronchial system till the level of minor segmental branches.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.

The genetic history of Italians: new-insights from uniparentally-inherited markers

Genetic differences among human groups can be ascribed both to the broad-scale extents of pre-historical and historical migrations and to the fine-scale impacts of socio-cultural and geographic heterogeneity. In this thesis, the genetic information provided by uniparental markers were exploited to address different aspects of the Italian population history, by combining macro- and micro-geographic investigations at different spatial and temporal scales. To firstly assess the overall Italian variability, Y-chromosome and mtDNA markers were deeply typed in ~900 individuals from continental Italy, Sicily and Sardinia. Sex-biased patterns and contrasting demographic histories were observed for males and females. Differential European and Mediterranean contributions were invoked to explain the paternal genetic sub-structure observed in peninsular Italy, compared to the homogeneous maternal genetic landscape. If Neolithic showed to be one principal determinant of the detected paternal structure, local insights into specific Italian regional contexts highlighted the importance of Post-Neolithic contributions. Among them, migrations from the Balkans (particularly Greece) during late Metal Ages, played a relevant role in the cultural and genetic transitions occurred in Sicily and Southern Italy. On a finer geographic and temporal perspective, the more recent layers of Italian genetic history and some aspects of the gene-culture interaction were assessed by exploring the genetic variability within two “marginal populations”: Arbereshe of Southern Italy and Partecipanza in Northern Italy. The Arbereshe are Albanian-speaking communities settled in Sicily and Calabria since the end of Middle Ages. Despite sharing common genetic and cultural backgrounds, these groups revealed diverging micro-evolutionary histories, implying different founding events and different patterns of cultural isolation and local admixture. Partecipanza is an idiosyncratic institution of Medieval origin aimed at sharing and devolving collective lands. This case-study exemplified that socio-economic stratification within the same population may induce sex-biased genetic structuring and the maintenance of otherwise hidden historical genetic traces.

A Bayesian changepoint analysis on spatio-temporal point processes

Changepoint analysis is a well established area of statistical research, but in the context of spatio-temporal point processes it is as yet relatively unexplored. Some substantial differences with regard to standard changepoint analysis have to be taken into account: firstly, at every time point the datum is an irregular pattern of points; secondly, in real situations issues of spatial dependence between points and temporal dependence within time segments raise. Our motivating example consists of data concerning the monitoring and recovery of radioactive particles from Sandside beach, North of Scotland; there have been two major changes in the equipment used to detect the particles, representing known potential changepoints in the number of retrieved particles. In addition, offshore particle retrieval campaigns are believed may reduce the particle intensity onshore with an unknown temporal lag; in this latter case, the problem concerns multiple unknown changepoints. We therefore propose a Bayesian approach for detecting multiple changepoints in the intensity function of a spatio-temporal point process, allowing for spatial and temporal dependence within segments. We use Log-Gaussian Cox Processes, a very flexible class of models suitable for environmental applications that can be implemented using integrated nested Laplace approximation (INLA), a computationally efficient alternative to Monte Carlo Markov Chain methods for approximating the posterior distribution of the parameters. Once the posterior curve is obtained, we propose a few methods for detecting significant change points. We present a simulation study, which consists in generating spatio-temporal point pattern series under several scenarios; the performance of the methods is assessed in terms of type I and II errors, detected changepoint locations and accuracy of the segment intensity estimates. We finally apply the above methods to the motivating dataset and find good and sensible results about the presence and quality of changes in the process.