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The Web contains some extremely valuable information; however, often poor quality, inaccurate, irrelevant or fraudulent information can also be found. With the increasing amount of data available, it is becoming more and more difficult to distinguish truth from speculation on the Web. One of the most, if not the most, important criterion used to evaluate data credibility is the information source, i.e., the data origin. Trust in the information source is a valuable currency users have to evaluate such data. Data popularity, recency (or the time of validity), reliability, or vagueness ascribed to the data may also help users to judge the validity and appropriateness of information sources. We call this knowledge derived from the data the provenance of the data. Provenance is an important aspect of the Web. It is essential in identifying the suitability, veracity, and reliability of information, and in deciding whether information is to be trusted, reused, or even integrated with other information sources. Therefore, models and frameworks for representing, managing, and using provenance in the realm of Semantic Web technologies and applications are critically required. This thesis highlights the benefits of the use of provenance in different Web applications and scenarios. In particular, it presents management frameworks for querying and reasoning in the Semantic Web with provenance, and presents a collection of Semantic Web tools that explore provenance information when ranking and updating caches of Web data. To begin, this thesis discusses a highly exible and generic approach to the treatment of provenance when querying RDF datasets. The approach re-uses existing RDF modeling possibilities in order to represent provenance. It extends SPARQL query processing in such a way that given a SPARQL query for data, one may request provenance without modifying it. The use of provenance within SPARQL queries helps users to understand how RDF facts arederived, i.e., it describes the data and the operations used to produce the derived facts. Turning to more expressive Semantic Web data models, an optimized algorithm for reasoning and debugging OWL ontologies with provenance is presented. Typical reasoning tasks over an expressive Description Logic (e.g., using tableau methods to perform consistency checking, instance checking, satisfiability checking, and so on) are in the worst case doubly exponential, and in practice are often likewise very expensive. With the algorithm described in this thesis, however, one can efficiently reason in OWL ontologies with provenance, i.e., provenance is efficiently combined and propagated within the reasoning process. Users can use the derived provenance information to judge the reliability of inferences and to find errors in the ontology. Next, this thesis tackles the problem of providing to Web users the right content at the right time. The challenge is to efficiently rank a stream of messages based on user preferences. Provenance is used to represent preferences, i.e., the user defines his preferences over the messages' popularity, recency, etc. This information is then aggregated to obtain a joint ranking. The aggregation problem is related to the problem of preference aggregation in Social Choice Theory. The traditional problem formulation of preference aggregation assumes a I fixed set of preference orders and a fixed set of domain elements (e.g. messages). This work, however, investigates how an aggregated preference order has to be updated when the domain is dynamic, i.e., the aggregation approach ranks messages 'on the y' as the message passes through the system. Consequently, this thesis presents computational approaches for online preference aggregation that handle the dynamic setting more efficiently than standard ones. Lastly, this thesis addresses the scenario of caching data from the Linked Open Data (LOD) cloud. Data on the LOD cloud changes frequently and applications relying on that data - by pre-fetching data from the Web and storing local copies of it in a cache - need to continually update their caches. In order to make best use of the resources (e.g., network bandwidth for fetching data, and computation time) available, it is vital to choose a good strategy to know when to fetch data from which data source. A strategy to cope with data changes is to check for provenance. Provenance information delivered by LOD sources can denote when the resource on the Web has been changed last. Linked Data applications can benefit from this piece of information since simply checking on it may help users decide which sources need to be updated. For this purpose, this work describes an investigation of the availability and reliability of provenance information in the Linked Data sources. Another strategy for capturing data changes is to exploit provenance in a time-dependent function. Such a function should measure the frequency of the changes of LOD sources. This work describes, therefore, an approach to the analysis of data dynamics, i.e., the analysis of the change behavior of Linked Data sources over time, followed by the investigation of different scheduling update strategies to keep local LOD caches up-to-date. This thesis aims to prove the importance and benefits of the use of provenance in different Web applications and scenarios. The exibility of the approaches presented, combined with their high scalability, make this thesis a possible building block for the Semantic Web proof layer cake - the layer of provenance knowledge.
Grassland management has been increasingly intensified throughout centuries since mankind started to control and modify the landscape. Species communities were always shaped alongside management changes leading to huge alterations in species richness and diversity up to the point where land use intensity exceeded the threshold. Since then biodiversity became increasingly lost. Today, global biodiversity and especially grassland biodiversity is pushed beyond its boundaries. Policymakers and conservationists seek for management options which fulfill the requirements of agronomic interests as well as biodiversity conservation alongside with the maintenance of ecosystem processes. However, there is and will always be a trade-off.
Earlier in history, natural circumstances in a landscape mainly determined regionally adapted land use. These regional adaptions shaped islands for many specialist species, and thus diverse species communities, favoring the establishment of a high β-diversity. With the raising food demand, these regional and traditional management regimes became widely unprofitable, and the invention of mineral fertilizers ultimately led to a wide homogenization of grassland management and, as follows, the loss of biotic heterogeneity. In the course of the green revolution, this immediate coherence and the dependency between grassland biodiversity and traditional land use practices becomes increasingly noticed. Indeed, some traditional forms of management such as meadow irrigation have been preserved in a few regions and thus give us the opportunity to directly investigate their long-term relevance for the species communities and ecosystem processes. Traditional meadow irrigation was a common management practice to improve productivity in lowland, but also alpine hay meadows throughout Europe until the 20th century. Nowadays, meadow irrigation is only practiced as a relic in a few remnant areas. In parts of the Queichwiesen meadows flood irrigation goes back to the Middle Ages, which makes them a predestined as a model region to study the long- and short-term effects of lowland meadow irrigation on the biodiversity and ecosystem processes.
Our study pointed out the conservation value of traditional meadow irrigation for the preservation of local species communities as well as the plant diversity at the landscape scale. The structurally more complex irrigated meadows lead to the assumption of a higher arthropod diversity (Orthodoptera, Carabidae, Araneae), which could not be detected. However, irrigated meadows are a significant habitat for moisture dependent arthropod species. In the light of the agronomic potential, flood irrigation could be a way to at least reduce fertilizer costs to a certain degree and possibly prevent overfertilization pulses which are necessarily hazardous to non-target ecosystems. Still, the reestablishment of flood irrigation in formerly irrigated meadows, or even the establishment of new irrigation systems needs ecological and economic evaluation dependent on regional circumstances and specific species communities, at which this study could serve as a reference point.
In scientific data visualization huge amounts of data are generated, which implies the task of analyzing these in an efficient way. This includes the reliable detection of important parts and a low expenditure of time and effort. This is especially important for the big-sized seismic volume datasets, that are required for the exploration of oil and gas deposits. Since the generated data is complex and a manual analysis is very time-intensive, a semi-automatic approach could on one hand reduce the time required for the analysis and on the other hand offer more flexibility, than a fully automatic approach.
This master's thesis introduces an algorithm, which is capable of locating regions of interest in seismic volume data automatically by detecting anomalies in local histograms. Furthermore the results are visualized and a variety of tools for the exploration and interpretation of the detected regions are developed. The approach is evaluated by experiments with synthetic data and in interviews with domain experts on the basis of real-world data. Conclusively further improvements to integrate the algorithm into the seismic interpretation workflow are suggested.
Introduction:
In March 2012 a secessionist-Islamist insurgency gained momentum in Mali and quickly took control of two-thirds of the state territory. Within weeks radical Islamists, drug smugglers and rebels suddenly ruled over a territory bigger than Germany. News of the abuse of the population and the introduction of harsh Sharia law spread soon, and word got out that the Malian Army had simply abandoned the land. The general echo of the IC was surprise, a reaction that was, as this research will show, as unfunded as it was unconstructive*. When Malian state structures collapsed, the world watched in shock, even though the developments couldhave been anticipated –and prevented. Ultimately, the situation had to be resolved by international forces (most notably French troops), who are still in Mali at the time of writing (Arieff 2013a: 5; Lohmann 2012: 3; Walther and Christopoulos 2015: 514f.; Shaw 2013: 204; Qantara, Interview, 2012;L’Express, Mali, 2015; Deutscher Bundestag, MINUSMA und EUTM Mali, 2016; UN, MUNISMA, 2016; Boeke and Schuurmann 2015: 801; Chivvis 2016: 93f.).
This research will show that the developments in Mali in 2012 have been developing for a long time and could have been avoided. In doing so, it will also show why state security can never be analyzed or consolidated in an isolated manner. Instead, it is necessary to take into account regional dynamics and developments in order to find a comprehensive approach to security in individual states. Once state failure occurs, not only does the state itself fail, but the surrounding region equally failed to prevent the failure.
Weak states are a growing concern in many world regions, particularly in Africa. As international intervention often proves unsustainable for various reasons*, the author believes that states which cannot stabilize themselves need a regional agent to support them. This regional agent should be a Regional Security Complex (RSC) asdefined by Barry Buzan and Ole Waever (Buzan and Waever 2003). As the following analysis will show, Mali is a case in point. The hope is that this study will help avoid similar failures in the future by making a strong case for the establishment of RSC’s.
…
With the emergence of current generation head-mounted displays (HMDs), virtual reality (VR) is regaining much interest in the field of medical imaging and diagnosis. Room-scale exploration of CT or MRI data in virtual reality feels like an intuitive application. However in VR retaining a high frame rate is more critical than for conventional user interaction seated in front of a screen. There is strong scientific evidence suggesting that low frame rates and high latency have a strong influence on the appearance of cybersickness. This thesis explores two practical approaches to overcome the high computational cost of volume rendering for virtual reality. One lies within the exploitation of coherency properties of the especially costly stereoscopic rendering setup. The main contribution is the development and evaluation of a novel acceleration technique for stereoscopic GPU ray casting. Additionally, an asynchronous rendering approach is pursued to minimize the amount of latency in the system. A selection of image warping techniques has been implemented and evaluated methodically, assessing the applicability for VR volume rendering.
For a comprehensive understanding of evolutionary processes and for providing reliable prognoses about the future consequences of environmental change, it is essential to reveal the genetic basis underlying adaptive responses. The importance of this goal increases in light of ongoing climate change, which confronts organisms worldwide with new selection pressures and requires rapid evolutionary change to avoid local extinction. Thereby, freshwater ectotherms like daphnids are particularly threatened. Unraveling the genetic basis of local adaptation is complicated by the interplay of forces affecting patterns of genetic divergence among populations. Due to their key position in freshwater communities, cyclic parthenogenetic mode of reproduction and resting propagules (which form biological archives), daphnids are particularly suited for this purpose.
The aim of this thesis was to assess the impact of local thermal selection on the Daphnia longispina complex and to reveal the underlying genetic loci. Therefore, I compared genetic differentiation among populations containing Daphnia galeata, Daphnia longispina and their interspecific hybrids across time, space, and species boundaries. I revealed strongly contrasting patterns of genetic differentiation between selectively neutral and functional candidate gene markers, between the two species, and among samples from different lakes, suggesting (together with a correlation with habitat temperatures) local thermal selection acting on candidate gene TRY5F and indicating adaptive introgression. To reveal the candidate genes’ impact on fitness, I performed association analyses among data on genotypes and phenotypic traits of D. galeata clones from seven populations. The tests revealed a general temperature effect as well as inter-population differences in phenotypic traits and imply a possible contribution of the candidate genes to life-history traits. Finally, utilizing a combined population transcriptomic and reverse ecology approach, I introduced a methodology with a wide range of applications in evolutionary biology and revealed that local thermal selection was probably a minor force in shaping sequence and gene expression divergence among four D. galeata populations, but contributed to sequence divergence among two populations. I identified many transcripts possibly under selection or contributing strongly to population divergence, a large amount thereof putatively under local thermal selection, and showed that genetic and gene expression variation is not depleted specifically in temperature-related candidate genes.
In conclusion, I detected signs of local adaptation in the D. longispina complex across space, time, and species barriers. Populations and species remained genetically divergent, although increased gene flow possibly contributed, together with genotypes recruited from the resting egg bank, to the maintenance of standing genetic variation. Further work is required to accurately determine the influence of introgression and the effects of candidate genes on individual fitness. While I found no evidence suggesting a response to intense local thermal selection, the high resilience and adaptive potential regarding environmental change I observed suggest positive future prospects for the populations of the D. longispina complex. However, overall, due to the continuing environmental degradation, daphnids and other aquatic invertebrates remain vulnerable and threatened.
Natural pest control and pollination are important ecosystem services for agriculture. They can be supported by organic farming and by seminatural habitats at the local and landscape scale.
The potential of seminatural habitats to support predatory flies (chapters 2 and 3) and bees(chapter 7) at the local and landscape scale was investigated in seminatural habitats. Predatory flies were more abundant in woody habitats and positively related to landscape complexity. The diversity and the abundance of honey and wild bees were positively related to the supply of flowers offered in the seminatural habitats.
The influence of organic farming, adjacent seminatural habitats and landscape complexity on pest control (chapter 4) and pollination (chapter 6) was investigated in 18 pumpkin fields. Organic farming lacked strong effects both on the pest control and on the pollination of pumpkin.
Pest control is best supported at the local scale by the flower abundance in the adjacent habitat. The flower supply positively affected the density of natural enemies and tended to reduce aphid densities in pumpkin fields.
Pumpkin provides a striking example for a dominant role of wild pollinators for pollination success, because bumble bees are the key pollinators of pumpkin in Germany, despite a higher visitation frequency of honey bees. Pollination is best supported by landscape complexity. Bumble bee visits and as a result pollen delivery in pumpkin were negatively related to the dominance of agricultural land in the surrounding landscape.
The influence of aphid density (chapter 8) and pollination (chapter 5) on pumpkin yield was evaluated. Pumpkin yields were not affected by aphid densities observed in the pumpkin fields and not limited by pollination at the current levels of bee visitation.
In conclusion, especially seminatural habitats, that provide diverse, continuous floral resources, are important for natural enemies and pollinators. A sufficient proportion of different seminatural habitat types in agricultural landscapes should be maintained and restored. Thereby natural enemies such as predatory flies, wild pollinators such as bumble bees, and the pest control and pollination provided by them can be supported.
Statistical eco(-toxico)logy
(2017)
Freshwaters are of immense importance for human well-being.
Nevertheless, they are currently facing unprecedented levels of threat from habitat loss and degradation, overexploitation, invasive species and
pollution.
To prevent risks to aquatic ecosystems, chemical substances, like agricultural pesticides, have to pass environmental risk assessment (ERA) before entering the market.
Concurrently, large-scale environmental monitoring is used for surveillance of biological and chemical conditions in freshwaters.
This thesis examines statistical methods currently used in ERA.
Moreover, it presents a national-scale compilation of chemical monitoring data, an analysis of drivers and dynamics of chemical pollution in streams and, provides a large-scale risk assessment by combination with results from ERA.
Additionally, software tools have been developed to integrate different datasets used in ERA.
The thesis starts with a brief introduction to ERA and environmental monitoring and gives an overview of the objectives of the thesis.
Chapter 2 addresses experimental setups and their statistical analyses using simulations.
The results show that current designs exhibit unacceptably low statistical power, that statistical methods chosen to fit the type of data provide higher power and that statistical practices in ERA need to be revised.
In chapter 3 we compiled all available pesticide monitoring data from Germany.
Hereby, we focused on small streams, similar to those considered in ERA and used threshold concentrations derived during ERA for a large-scale assessment of threats to freshwaters from pesticides.
This compilation resulted in the most comprehensive dataset on pesticide exposure currently available for Germany.
Using state-of-the-art statistical techniques, that explicitly take the limits of quantification into account, we demonstrate that 25% of small streams are at threat from pesticides.
In particular neonicotinoid pesticides are responsible for these threats.
These are associated with agricultural intensity and can be detected even at low levels of agricultural use.
Moreover, our results indicated that current monitoring underestimates pesticide risks, because of a sampling decoupled from precipitation events.
Additionally, we provide a first large-scale study of annual pesticide exposure dynamics.
Chapters 4 and 5 describe software solutions to simplify and accelerate the integration of data from ERA, environmental monitoring and ecotoxicology that is indispensable for the development of landscape-level risk assessment.
Overall, this thesis contributes to the emerging discipline of statistical ecotoxicology and shows that pesticides pose a large-scale threat to small streams.
Environmental monitoring can provide a post-authorisation feedback to ERA.
However, to protect freshwater ecosystems ERA and environmental monitoring need to be further refined and we provide software solutions to utilise existing data for this purpose.
With global and distributed project teams being increasingly common Collaborative Project Management is becoming the prevalent paradigm for the work in most organisations. Software has for many years been one of the most used tools for supporting Project Management and with the focus on Collaborative Project Management and accompanied by the emergence of Enterprise Collaboration Systems (ECS), Collaborative Project Management Software (CPMS) is gaining increased attention. This thesis examines the capabilities of CPMS for the long-term management of information which not only includes the management of files within these systems, but the management of all types of digital business documents, particularly social business documents. Previous research shows that social content in collaboration software is often poorly managed which poses challenges to meeting performance and conformance objectives in a business. Based on literature research, requirements for the long-term management of information in CPMS are defined and 7 CPMS tools are analysed regarding the content they contain and the functionalities for the long-term management of this content they offer. The study shows that CPMS by and large are not able to meet the long-term information management needs of an organisation on their own and that only the tools geared towards enterprise customers have sufficient capabilities to support the implementation of an Enterprise Information Management strategy.
The presence of anthropogenic chemicals in the natural environment may impact both habitats and human use of natural resources. In particular the contamination of aquatic resources by organic compounds used as pharmaceuticals or household chemicals has become evident. The newly identified environmental pollutants, also known as micropollutants, often have i) unknown ecotoxicological impacts, ii) unknown partitioning mechanisms, e.g. sorption to sediments, and iii) limited regulation to control their emission. Furthermore, like any compound, micropollutants can be transformed while in the environmental matrix to unknown transformation products (TPs), which add to the number of unknown chemicals to consider and thus increase the complexity of risk management. Transformation is at the same time a natural mechanism for the removal of anthropogenic compounds, either by complete degradation (mineralisation) or to innocuous TPs. However, how transformation occurs in real-world conditions is still largely unknown. During the transport of micropollutants from household wastewater to surface water, a large amount of transformation can occur during wastewater treatment—specifically during biological nitrifying–denitrifying treatment processes. The thesis considers the systematic optimisation of laboratory investigative techniques, application of sensitive mass-spectrometry-based analysis techniques and the monitoring of full-scale wastewater treatment plants (WWTPs) to elucidate transformation processes of five known micropollutants.
The first of the five compounds investigated was the antibiotic trimethoprim. Incubation experiments were conducted at different analyte spike concentrations and different sludge to wastewater ratios. Using high-resolution mass spectrometry, a total of six TPs were identified from trimethoprim. The types of TPs formed was clearly influenced by the spike concentration. To the best of our knowledge, such impacts have not been previously described in the literature. Beginning from the lower spike concentration, a relatively stable final TP was formed (2,4-diaminopyrimidine-5-carboxylic acid, DAPC), which could account for almost all of the transformed trimethoprim quantity. The results were compared to the process in a reference reactor. Both by the detection of TPs (e.g., DAPC) and by modelling the removal kinetics, it could be concluded that only experimental results at the low spike concentrations mirrored the real reactor. The limits of using elevated spike concentrations in incubation experiments could thus be shown.
Three phenolic micropollutants, the antiseptic ortho-phenylphenol (OPP), the plastics additive bisphenol A (BPA) and the psychoactive drug dextrorphan were investigated with regard to the formation of potentially toxic, nitrophenolic TPs. Nitrite is an intermediate in the nitrification– denitrification process occurring in activated sludge and was found to cause nitration of these phenols. To elucidate the processes, incubation experiments were conducted in purified water in the presence of nitrite with OPP as the test substance. The reactive species HNO2, N2O3 and the radicals ·NO and ·NO2 were likely involved as indicated by scavenger experiments. In conditions found at WWTPs the wastewater is usually at neutral pH, and nitrite, being an intermediate, usually has a low concentration. By conducting incubation experiments inoculated with sludge from a conventional WWTP, it was found that the three phenolic micropollutants, OPP, BPA and dextrorphan were quickly transformed to biological TPs. Nitrophenolic TPs were only formed after artificial increase of the nitrite concentration or lowering of the pH. However, nitrophenolic-TPs can be formed as sample preparation artefacts through acidification or freezing for preservation, creating optimal conditions for the reaction to take place.
The final micropollutant to be studied was the pain-reliever diclofenac, a micropollutant on the EU-watch list due to ecotoxicological effects on rainbow trout. The transformation was compared in two different treatment systems, one employing a reactor with suspended carriers as a biofilm growth surface, while the other system employed conventional activated sludge. In the biofilm-based system, the pathway was found to produce many TPs each at relatively low concentration, many of which were intermediate TPs that were further degraded to unknown tertiary TPs. In the conventional activated sludge system some of the same reactions took place but all at much slower rates. The main difference between the two systems was due to different reaction rates rather than different transformation pathways. The municipal WWTPs were monitored to verify these results. In the biofilm system, a 10-day monitoring campaign confirmed an 88% removal of diclofenac and the formation of the same TPs as those observed in the laboratory experiments. The proposed environmental quality standard of 0.05 μg/L might thus be met without the need for additional treatment processes such as activated carbon filtration or ozonation.