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Using semantic data from general-purpose programming languages does not provide the unified experience one would want for such an application. Static error checking is lacking, especially with regards to static typing of the data. Based on the previous work of λ-DL, which integrates semantic queries and concepts as types into a typed λ-calculus, this work takes its ideas a step further to meld them into a real-world programming language. This thesis explores how λ-DL's features can be extended and integrated into an existing language, researches an appropriate extension mechanism and produces Semantics4J, a JastAdd-based Java language semantic data extension for type-safe OWL programming, together with examples of its usage.
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.
Part-of-Speech tagging is the process of assigning words with similar grammatical properties to a part of speech (PoS). In the English language, PoS-tagging algorithms generally reach very high accuracy. This thesis undertakes the task to test against these accuracies in PoS-tagging as a qualitative measure in classification capabilities for a recently developed neural network model, called graph convolutional network (GCN). The novelty proposed in this thesis is to translate a corpus into a graph as a direct input for the GCN. The experiments in this thesis serve as a proof of concept with room for improvements.
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.
Pelagic oxyclines, the transition zone between oxygen rich surface waters and oxygen depleted deep waters, are a common characteristic of eutrophic lakes during summer stratification. They can have tremendous effects on the biodiversity and the ecosystem functioning of lakes and, to add insult to injury, are expected to become more frequent and more pronounced as climate warming progresses. On these grounds, this thesis endeavors to advance the understanding of formation, persistence, and consequences of pelagic oxyclines: We test, whether the formation of metalimnetic oxygen minima is intrinsically tied to a locally enhanced oxygen consuming process, investigate the relative importance of vertical physical oxygen transport and biochemical oxygen consumption for the persistence of pelagic oxyclines, and finally assess their potential consequences for whole lake cycling. To pursue these objectives, the present thesis nearly exclusively resorts to in situ measurements. Field campaigns were conducted at three lakes in Germany featuring different types of oxyclines and resolved either a short (hours to days) or a long (weeks to months) time scale. Measurements comprised temperature, current velocity, and concentrations of oxygen and reduced substances in high temporal and vertical resolution. Additionally, vertical transport was estimated by applying the eddy correlation technique within the pelagic region for the first time. The thesis revealed, that the formation of metalimnetic oxygen minima does not necessarily depend on locally enhanced oxygen depletion, but can solely result from gradients and curvatures of oxygen concentration and depletion and their relative position to each other. Physical oxygen transport was found to be relevant for oxycline persistence when it considerably postponed anoxia on a long time scale. However, its influence on oxygen dynamics was minor on short time scales, although mixing and transport were highly variable. Biochemical consumption always dominated the fate of oxygen in pelagic oxyclines. It was primarily determined by the oxidative breakdown of organic matter originating from the epilimnion, whereas in meromictic lakes, the oxidation of reduced substances dominated. Beyond that, the results of the thesis emphasize that pelagic oxyclines can be a hotspot of mineralization and, hence, short-circuit carbon and nutrient cycling in the upper part of the water column. Overall, the present thesis highlights the importance of considering physical transport as well as biochemical cycling in future studies.
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.