867 resultados para Species Distribution Models


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Persistent organic pollutants (POPs) is a group of chemicals that are toxic, undergo long-range transport and accumulate in biota. Due to their persistency the distribution and recirculation in the environment often continues for a long period of time. Thereby they appear virtually everywhere within the biosphere, and poses a toxic stress to living organisms. In this thesis, attempts are made to contribute to the understanding of factors that influence the distribution of POPs with focus on processes in the marine environment. The bioavailability and the spatial distribution are central topics for the environmental risk management of POPs. In order to study these topics, various field studies were undertaken. To determine the bioavailable fraction of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated naphthalenes (PCNs), and polychlorinated biphenyls (PCBs) the aqueous dissolved phase were sampled and analysed. In the same samples, we also measured how much of these POPs were associated with suspended particles. Different models, which predicted the phase distribution of these POPs, were then evaluated. It was found that important water characteristics, which influenced the solid-water phase distribution of POPs, were particulate organic matter (POM), particulate soot (PSC), and dissolved organic matter (DOM). The bioavailable dissolved POP-phase in the water was lower when these sorbing phases were present. Furthermore, sediments were sampled and the spatial distribution of the POPs was examined. The results showed that the concentration of PCDD/Fs, and PCNs were better described using PSC- than using POM-content of the sediment. In parallel with these field studies, we synthesized knowledge of the processes affecting the distribution of POPs in a multimedia mass balance model. This model predicted concentrations of PCDD/Fs throughout our study area, the Grenlandsfjords in Norway, within factors of ten. This makes the model capable to validate the effect of suitable remedial actions in order to decrease the exposure of these POPs to biota in the Grenlandsfjords which was the aim of the project. Also, to evaluate the influence of eutrophication on the marine occurrence PCB data from the US Musselwatch and Benthic Surveillance Programs are examined in this thesis. The dry weight based concentrations of PCB in bivalves were found to correlate positively to the organic matter content of nearby sediments, and organic matter based concentrations of PCB in sediments were negatively correlated to the organic matter content of the sediment.

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The motivation for the work presented in this thesis is to retrieve profile information for the atmospheric trace constituents nitrogen dioxide (NO2) and ozone (O3) in the lower troposphere from remote sensing measurements. The remote sensing technique used, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), is a recent technique that represents a significant advance on the well-established DOAS, especially for what it concerns the study of tropospheric trace consituents. NO2 is an important trace gas in the lower troposphere due to the fact that it is involved in the production of tropospheric ozone; ozone and nitrogen dioxide are key factors in determining the quality of air with consequences, for example, on human health and the growth of vegetation. To understand the NO2 and ozone chemistry in more detail not only the concentrations at ground but also the acquisition of the vertical distribution is necessary. In fact, the budget of nitrogen oxides and ozone in the atmosphere is determined both by local emissions and non-local chemical and dynamical processes (i.e. diffusion and transport at various scales) that greatly impact on their vertical and temporal distribution: thus a tool to resolve the vertical profile information is really important. Useful measurement techniques for atmospheric trace species should fulfill at least two main requirements. First, they must be sufficiently sensitive to detect the species under consideration at their ambient concentration levels. Second, they must be specific, which means that the results of the measurement of a particular species must be neither positively nor negatively influenced by any other trace species simultaneously present in the probed volume of air. Air monitoring by spectroscopic techniques has proven to be a very useful tool to fulfill these desirable requirements as well as a number of other important properties. During the last decades, many such instruments have been developed which are based on the absorption properties of the constituents in various regions of the electromagnetic spectrum, ranging from the far infrared to the ultraviolet. Among them, Differential Optical Absorption Spectroscopy (DOAS) has played an important role. DOAS is an established remote sensing technique for atmospheric trace gases probing, which identifies and quantifies the trace gases in the atmosphere taking advantage of their molecular absorption structures in the near UV and visible wavelengths of the electromagnetic spectrum (from 0.25 μm to 0.75 μm). Passive DOAS, in particular, can detect the presence of a trace gas in terms of its integrated concentration over the atmospheric path from the sun to the receiver (the so called slant column density). The receiver can be located at ground, as well as on board an aircraft or a satellite platform. Passive DOAS has, therefore, a flexible measurement configuration that allows multiple applications. The ability to properly interpret passive DOAS measurements of atmospheric constituents depends crucially on how well the optical path of light collected by the system is understood. This is because the final product of DOAS is the concentration of a particular species integrated along the path that radiation covers in the atmosphere. This path is not known a priori and can only be evaluated by Radiative Transfer Models (RTMs). These models are used to calculate the so called vertical column density of a given trace gas, which is obtained by dividing the measured slant column density to the so called air mass factor, which is used to quantify the enhancement of the light path length within the absorber layers. In the case of the standard DOAS set-up, in which radiation is collected along the vertical direction (zenith-sky DOAS), calculations of the air mass factor have been made using “simple” single scattering radiative transfer models. This configuration has its highest sensitivity in the stratosphere, in particular during twilight. This is the result of the large enhancement in stratospheric light path at dawn and dusk combined with a relatively short tropospheric path. In order to increase the sensitivity of the instrument towards tropospheric signals, measurements with the telescope pointing the horizon (offaxis DOAS) have to be performed. In this circumstances, the light path in the lower layers can become very long and necessitate the use of radiative transfer models including multiple scattering, the full treatment of atmospheric sphericity and refraction. In this thesis, a recent development in the well-established DOAS technique is described, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS). The MAX-DOAS consists in the simultaneous use of several off-axis directions near the horizon: using this configuration, not only the sensitivity to tropospheric trace gases is greatly improved, but vertical profile information can also be retrieved by combining the simultaneous off-axis measurements with sophisticated RTM calculations and inversion techniques. In particular there is a need for a RTM which is capable of dealing with all the processes intervening along the light path, supporting all DOAS geometries used, and treating multiple scattering events with varying phase functions involved. To achieve these multiple goals a statistical approach based on the Monte Carlo technique should be used. A Monte Carlo RTM generates an ensemble of random photon paths between the light source and the detector, and uses these paths to reconstruct a remote sensing measurement. Within the present study, the Monte Carlo radiative transfer model PROMSAR (PROcessing of Multi-Scattered Atmospheric Radiation) has been developed and used to correctly interpret the slant column densities obtained from MAX-DOAS measurements. In order to derive the vertical concentration profile of a trace gas from its slant column measurement, the AMF is only one part in the quantitative retrieval process. One indispensable requirement is a robust approach to invert the measurements and obtain the unknown concentrations, the air mass factors being known. For this purpose, in the present thesis, we have used the Chahine relaxation method. Ground-based Multiple AXis DOAS, combined with appropriate radiative transfer models and inversion techniques, is a promising tool for atmospheric studies in the lower troposphere and boundary layer, including the retrieval of profile information with a good degree of vertical resolution. This thesis has presented an application of this powerful comprehensive tool for the study of a preserved natural Mediterranean area (the Castel Porziano Estate, located 20 km South-West of Rome) where pollution is transported from remote sources. Application of this tool in densely populated or industrial areas is beginning to look particularly fruitful and represents an important subject for future studies.

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Investigation on impulsive signals, originated from Partial Discharge (PD) phenomena, represents an effective tool for preventing electric failures in High Voltage (HV) and Medium Voltage (MV) systems. The determination of both sensors and instruments bandwidths is the key to achieve meaningful measurements, that is to say, obtaining the maximum Signal-To-Noise Ratio (SNR). The optimum bandwidth depends on the characteristics of the system under test, which can be often represented as a transmission line characterized by signal attenuation and dispersion phenomena. It is therefore necessary to develop both models and techniques which can characterize accurately the PD propagation mechanisms in each system and work out the frequency characteristics of the PD pulses at detection point, in order to design proper sensors able to carry out PD measurement on-line with maximum SNR. Analytical models will be devised in order to predict PD propagation in MV apparatuses. Furthermore, simulation tools will be used where complex geometries make analytical models to be unfeasible. In particular, PD propagation in MV cables, transformers and switchgears will be investigated, taking into account both irradiated and conducted signals associated to PD events, in order to design proper sensors.

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La materia ordinaria copre soli pochi punti percentuali della massa-energia totale dell'Universo, che è invece largamente dominata da componenti “oscure”. Il modello standard usato per descriverle è il modello LambdaCDM. Nonostante esso sembri consistente con la maggior parte dei dati attualmente disponibili, presenta alcuni problemi fondamentali che ad oggi restano irrisolti, lasciando spazio per lo studio di modelli cosmologici alternativi. Questa Tesi mira a studiare un modello proposto recentemente, chiamato “Multi-coupled Dark Energy” (McDE), che presenta interazioni modificate rispetto al modello LambdaCDM. In particolare, la Materia Oscura è composta da due diversi tipi di particelle con accoppiamento opposto rispetto ad un campo scalare responsabile dell'Energia Oscura. L'evoluzione del background e delle perturbazioni lineari risultano essere indistinguibili da quelle del modello LambdaCDM. In questa Tesi viene presentata per la prima volta una serie di simulazioni numeriche “zoomed”. Esse presentano diverse regioni con risoluzione differente, centrate su un singolo ammasso di interesse, che permettono di studiare in dettaglio una singola struttura senza aumentare eccessivamente il tempo di calcolo necessario. Un codice chiamato ZInCo, da me appositamente sviluppato per questa Tesi, viene anch'esso presentato per la prima volta. Il codice produce condizioni iniziali adatte a simulazioni cosmologiche, con differenti regioni di risoluzione, indipendenti dal modello cosmologico scelto e che preservano tutte le caratteristiche dello spettro di potenza imposto su di esse. Il codice ZInCo è stato usato per produrre condizioni iniziali per una serie di simulazioni numeriche del modello McDE, le quali per la prima volta mostrano, grazie all'alta risoluzione raggiunta, che l'effetto di segregazione degli ammassi avviene significativamente prima di quanto stimato in precedenza. Inoltre, i profili radiale di densità ottenuti mostrano un appiattimento centrale nelle fasi iniziali della segregazione. Quest'ultimo effetto potrebbe aiutare a risolvere il problema “cusp-core” del modello LambdaCDM e porre limiti ai valori dell'accoppiamento possibili.

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Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data.

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In Switzerland, a national database with 1028 Campylobacter isolates from poultry, pigs, cats, dogs, cattle, humans, zoo animals and water has been created. The database contains the genetic fingerprint and background information of each Campylobacter isolate. Dominant species could be identified in the different sources with a majority of Campylobacter jejuni in poultry (73%), humans (79%), cattle (95%), zoo animals (40%) and water (100%), of Campylobacter coli in pigs (72%), and of Campylobacter upsaliensis/helveticus in cats and dogs (55%). The comparison of three genotyping methods, amplified fragment length polymorphism (AFLP), pulsed field gel electrophoresis and restriction fragment length polymorphism, revealed that AFLP allows discrimination between the different Campylobacter species and is the most appropriate method to distinguish specific strains within the same species. Genotyping analysis demonstrated that the Campylobacter population is heterogeneous among the different sources and that no dominant clone is spread in the country. Genotyping and the resulting database are useful tools to trace back future Campylobacter infections.

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Equine Actinobacillus species were analysed phylogenetically by 16S rRNA gene (rrs) sequencing focusing on the species Actinobacillus equuli, which has recently been subdivided into the non-haemolytic A. equuli subsp. equuli and the haemolytic A. equuli subsp. haemolyticus. In parallel we determined the profile for RTX toxin genes of the sample of strains by PCR testing for the presence of the A. equuli haemolysin gene aqx, and the toxin genes apxI, apxII, apxIII and apxIV, which are known in porcine pathogens such as Actinobacillus pleuropneumoniae and Actinobacillus suis. The rrs-based phylogenetic analysis revealed two distinct subclusters containing both A. equuli subsp. equuli and A. equuli subsp. haemolyticus distributed through both subclusters with no correlation to taxonomic classification. Within one of the rrs-based subclusters containing the A. equuli subsp. equuli type strain, clustered as well the porcine Actinobacillus suis strains. This latter is known to be also phenotypically closely related to A. equuli. The toxin gene analysis revealed that all A. equuli subsp. haemolyticus strains from both rrs subclusters specifically contained the aqx gene while the A. suis strains harboured the genes apxI and apxII. The aqx gene was found to be specific for A. equuli subsp. haemolyticus, since A. equuli subsp. equuli contained no aqx nor any of the other RTX genes tested. The specificity of aqx for the haemolytic equine A. equuli and ApxI and ApxII for the porcine A. suis indicates a role of these RTX toxins in host species predilection of the two closely related species of bacterial pathogens and allows PCR based diagnostic differentiation of the two.

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In order to understand and protect ecosystems, local gene pools need to be evaluated with respect to their uniqueness. Cryptic species present a challenge in this context because their presence, if unrecognized, may lead to serious misjudgement of the distribution of evolutionarily distinct genetic entities. In this study, we describe the current geographical distribution of cryptic species of the ecologically important stream amphipod Gammarus fossarum (types A, B and C). We use a novel pyrosequencing assay for molecular species identification and survey 62 populations in Switzerland, plus several populations in Germany and eastern France. In addition, we compile data from previous publications (mainly Germany). A clear transition is observed from type A in the east (Danube and Po drainages) to types B and, more rarely, C in the west (Meuse, Rhone, and four smaller French river systems). Within the Rhine drainage, the cryptic species meet in a contact zone which spans the entire G. fossarum distribution range from north to south. This large-scale geographical sorting indicates that types A and B persisted in separate refugia during Pleistocene glaciations. Within the contact zone, the species rarely co-occur at the same site, suggesting that ecological processes may preclude long-term coexistence. The clear phylogeographical signal observed in this study implies that, in many parts of Europe, only one of the cryptic species is present.

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Many parasites infect multiple host species. In coevolving host–parasite interactions, theory predicts that parasites should be adapted to locally common hosts, which could lead to regional shifts in host preferences. We studied the interaction between freshwater Gammarus (Crustacea, Amphipoda) and their acanthocephalan parasites using a large-scale field survey and experiments, combined with molecular identification of cryptic host and parasite species. Gammarus pulex is a common host for multiple species of Acanthocephala in Europe but, in Switzerland, is less common than two cryptic members of the Gammarus fossarum species complex (type A and type B). We found that natural populations of these cryptic species were frequently infected by Pomphorhynchus tereticollis and Polymorphus minutus. Four additional parasite species occurred only locally. Parasites were more common in G. fossarum type B than in type A. Infection experiments using several host and parasite sources confirmed consistently lower infection rates in G. pulex than in G. fossarum type A, suggesting a general difference in susceptibility between the two species. In conclusion, we could show that cryptic host species differ in their interactions with parasites, but that these differences were much less dramatic than differences between G. fossarum (type A) and G. pulex. Our data suggest that the acanthocephalans in Switzerland have adapted to the two most common Gammarus species in this region where host species frequencies differ from near-by regions in Europe.

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Female mate choice has often been proposed to play an important role in cases of rapid speciation, in particular in the explosively evolved haplochromine cichlid species flocks of the Great Lakes of East Africa. Little, if anything, is known in cichlid radiations about the heritability of female mating preferences. Entirely sympatric distribution, large ecological overlap and conspicuous differences in male nuptial coloration, and female preferences for these, make the sister species Pundamilia pundamilia and P. nyererei from Lake Victoria an ideally suited species pair to test assumptions on the genetics of mating preferences made in models of sympatric speciation. Female mate choice is necessary and sufficient to maintain reproductive isolation between these species, and it is perhaps not unlikely therefore, that female mate choice has been important during speciation. A prerequisite for this, which had remained untested in African cichlid fish, is that variation in female mating preferences is heritable. We investigated mating preferences of females of these sister species and their hybrids to test this assumption of most sympatric speciation models, and to further test the assumption of some models of sympatric speciation by sexual selection that female preference is a single-gene trait. We find that the differences in female mating preferences between the sister species are heritable, possibly with quite high heritabilities, and that few but probably more than one genetic loci contribute to this behavioural speciation trait with no apparent dominance. We discuss these results in the light of speciation models and the debate about the explosive radiation of cichlid fishes in Lake Victoria.

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In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.