Carabids, which are frequently distributed in agricultural landscapes, are natural enemies of different pests including slugs. Semi-natural habitats are known to affect carabids and thus, their potential to support natural pest control. The impact of semi-natural habitats was investigated on carabids and slugs within different non-crop habitats (chapter 2). Most carabids and Deroceras reticulatum showed preferences for herbaceous semi-natural habitats, while Arion spp. occured mainly in woody habitats. An increase of predatory carabid abundance, which was linked to an inclining amount of semi-natural habitats in the landscape, and a decrease of Arion spp. densities, indicated a high potential for slug control in structural rich landscapes. Effects of semi-natural habitats were investigated on predatory carabids and slugs in 18 wheat fields (chapter 3). Predatory carabid species richness was positively affected by the increasing amount of semi-natural habitats in the landscape, whereas predatory carabid abundance was neither influenced by adjacent habitat type nor by the proportion of semi-natural habitats in the landscape. The target pest species showed divergent patterns, whereas Arion spp. densities were highest in structural poor landscapes near woody margins. D. reticulatum was not affected by habitat type or landscape, reflecting its adaptation to agriculture. Results indicate an increased control of Arion spp. by carabids in landscapes with a high amount of semi-natural habitats. Effects of semi-natural habitats and the influence of farming system was tested on carabid distribution within 18 pumpkin fields (chapter 4). Carabid species richness generally increased with decreasing distance to the field margins, whereas carabid abundance responded differently according to the adjacent habitat type. Farming system had no effect on carabids and landscape heterogeneity only affected carabids in organic pumpkin fields. Slug and slug egg predation of three common carabid species was tested in single and double species treatments in the laboratory (chapter 5). Results show additive and synergistic effects depending on the carabid species. In general, semi-natural habitats can enhance the potential of slug control by carabids. This counts especially for Arionid slugs. Semi-natural habitats can support carabid communities by providing shelter, oviposition and overwintering sites as wells as complementary food sources. Therefore, it is important to provide a certain amount of non-crop habitats in agricultural landscapes. 

Navigation is a natural way to explore and discover content in a digital environment. Hence, providers of online information systems such as Wikipedia---a free online encyclopedia---are interested in providing navigational support to their users. To this end, an essential task approached in this thesis is the analysis and modeling of navigational user behavior in information networks with the goal of paving the way for the improvement and maintenance of web-based systems. Using large-scale log data from Wikipedia, this thesis first studies information access by contrasting search and navigation as the two main information access paradigms on the Web. Second, this thesis validates and builds upon existing navigational hypotheses to introduce an adaptation of the well-known PageRank algorithm. This adaptation is an improvement of the standard PageRank random surfer navigation model that results in a more "reasonable surfer" by accounting for the visual position of links, the information network regions they lead to, and the textual similarity between the link source and target articles. Finally, using agent-based simulations, this thesis compares user models that have a different knowledge of the network topology in order to investigate the amount and type of network topological information needed for efficient navigation. An evaluation of agents' success on four different networks reveals that in order to navigate efficiently, users require only a small amount of high-quality knowledge of the network topology. Aside from the direct benefits to content ranking provided by the "reasonable surfer" version of PageRank, the empirical insights presented in this thesis may also have an impact on system design decisions and Wikipedia editor guidelines, i.e., for link placement and webpage layout.

Wikipedia is the biggest, free online encyclopaedia that can be expanded by any-one. For the users, who create content on a specific Wikipedia language edition, a social network exists. In this social network users are categorised into different roles. These are normal users, administrators and functional bots. Within the networks, a user can post reviews, suggestions or send simple messages to the "talk page" of another user. Each language in the Wikipedia domain has this type of social network. In this thesis characteristics of the three different roles are analysed in order to learn how they function in one language network of Wikipedia and apply them to another Wikipedia network to identify bots. Timestamps from created posts are analysed to reveal noticeable characteristics referring to continuous messages, message rates and irregular behaviour of a user are discovered. Through this process we show that there exist differences between the roles for the mentioned characteristics.

The Internet of Things (IoT) is a concept in which connected physical objects are integrated into the virtual world to become active partakers of businesses and everyday processes (Uckelmann, Harrison and Michahelles, 2011; Shrouf, Ordieres and Miragliotta, 2014). It is expected to have a major impact on businesses (Council, Nic and Intelligence, 2008), but small and medium enterprises’ business models are threatened if they do not adopt the new concept (Sommer, 2015). Thus, this thesis aims to showcase a sample implementation of connected devices in a small enterprise, demonstrating its added benefits for the business. Design Science Research (DSR) is used to develop a prototype based on a use case provided by a carpentry. The prototype comprises a hardware sensor and a web application which can be used by the wood shop to improve their processes. The thesis documents the iterative process of developing a prototype from the grounds up to useable hard- and software. This contribution provides an example of how IoT can be used and implemented at a small business.

Estuaries are characterized by a longitudinal salinity gradient. This gradient is one of the main environmental factors responsible for the distribution of organisms. Distinguishing salinity zones is of crucial importance, e.g., for the development of tools for the assessment of ecological quality. The methods most often applied for classifying water according to salinity are the Venice System and the method of Bulger et al. (1993), both of which determine zone boundaries using species occurrences relative to mean salinity. However, although these methods were developed for homoiohaline waters, they have also been routinely applied to poikilohaline systems. I tested the applicability of both methods using salinity and macroinvertebrate data for the poikilohaline Elbe Estuary (Germany). My results showed that the mid-estuary distribution of macro-invertebrates is determined by variation in salinity rather than by mean salinity. Consequently, neither of the two methods is applicable for defining salinity zones in the Elbe Estuary. Cluster analysis combined with a significance test, by contrast, was a better tool for identifying the boundaries of salinity zones in poikilohaline systems. In many estuaries, such as the Elbe Estuary, a maximum turbidity zone (MTZ) develops, where suspended matter accumulates owing to circulation processes. It is assumed that the MTZ is a stressful environment with an excess of organic matter, high deposition rates, large variations in salinity, and dredging activities. Under such harsh conditions, populations might remain below the carrying capacity, and it is assumed that competition is of little importance, as predicted by the stress gradient hypothesis. I tested whether competition for food is important in the MTZ of the Elbe Estuary using stable isotope analysis of the macroinvertebrate community. The isotopic niches of no two taxa within a feeding group overlapped, which indicated different resource use and the absence of competition. The main reasons for the lack of overlap of isotopic niches were differences in habitat, feeding behavior, and migration behavior. The Elbe Estuary is nowadays highly industrialized and has long been subjected to a plethora of human-caused alterations. However, it is largely unknown what changes occurred in benthic communities in the last century. Hence, I considered taxonomic and functional aspects of macrobenthic invertebrates of the Elbe Estuary given in data from 1889 (most natural state), 1985 and 1986 (highly polluted state), and 2006 (recent state) to assess benthic community shifts. Beta-diversity analysis showed that taxonomic differences between the sampling dates were mainly due to species turnover, whereas functional differences were predominantly a result of functional nestedness. Species number (S), functional richness (FRic), and functional redundancy reached minimum values in 1985 and 1986 and were highest and rather similar in 1889 and 2006. The decline in FRic from 1889 to 1985/1986 was non-random, consistent with habitat filtering. FRic, functional beta diversity, and S data suggested that the state of the estuary from 1889 was almost re-established in 2006. However, the community in 1889 significantly differed from that in 2006 owing to species replacement. My results indicate that FRic and FR in 1889 could have promoted ecosystem resilience and stability.

Ontologies are valuable tools for knowledge representation and important building blocks of the Semantic Web. They are not static and can change over time. Changing an ontology can be necessary for various reasons: the domain that is represented by an ontology can change or an ontology is reused and must be adapted to the new context. In addition, modeling errors could have been introduced into the ontology which must be found and removed. The non-triviality of the change process has led to the emerge of ontology change as an own field of research. The removal of knowledge from ontologies is an important aspect of this change process, because even the addition of new knowledge to an ontology potentially requires the removal of older, conflicting knowledge. Such a removal must be performed in a thought-out way. A naïve change of concepts within the ontology can easily remove other, unrelated knowledge or alter the semantics of concepts in an unintended way [2]. For these reasons, this thesis introduces a formal operator for the fine-grained retraction of knowledge from EL concepts which is partially based on the postulates for belief set contraction and belief base contraction [3, 4, 5] and the work of Suchanek et al. [6]. For this, a short introduction to ontologies and OWL 2 is given and the problem of ontology change is explained. It is then argued why a formal operator can support this process and why the Description Logic EL provides a good starting point for the development of such an operator. After this, a general introduction to Description Logic is given. This includes its history, an overview of its applications and common reasoning tasks in this logic. Following this, the logic EL is defined. In a next step, related work is examined and it is shown why the recovery postulate and the relevance postulate cannot be naïvely employed in the development of an operator that removes knowledge from EL concepts. Following this, the requirements to the operator are formulated and properties are given which are mainly based on the postulates for belief set and belief base contraction. Additional properties are developed which make up for the non-applicability of the recovery and relevance postulates. After this, a formal definition of the operator is given and it is shown that the operator is applicable to the task of a fine-grained removal of knowledge from EL concepts. In a next step, it is proven that the operator fulfills all the previously defined properties. It is then demonstrated how the operator can be combined with laconic justifications [7] to assist a human ontology editor by automatically removing unwanted consequences from an ontology. Building on this, a plugin for the ontology editor Protégé is introduced that is based on algorithms that were derived from the formal definition of the operator. The content of this work is then summarized and a final conclusion is drawn. The thesis closes with an outlook into possible future work.

This thesis addresses the automated identification and localization of a time-varying number of objects in a stream of sensor data. The problem is challenging due to its combinatorial nature: If the number of objects is unknown, the number of possible object trajectories grows exponentially with the number of observations. Random finite sets are a relatively new theory that has been developed to derive at principled and efficient approximations. It is based around set-valued random variables that contain an unknown number of elements which appear in arbitrary order and are themselves random. While extensively studied in theory, random finite sets have not yet become a leading paradigm in practical computer vision and robotics applications. This thesis explores random finite sets in visual tracking applications. The first method developed in this thesis combines set-valued recursive filtering with global optimization. The problem is approached in a min-cost flow network formulation, which has become a standard inference framework for multiple object tracking due to its efficiency and optimality. A main limitation of this formulation is a restriction to unary and pairwise cost terms. This circumstance makes integration of higher-order motion models challenging. The method developed in this thesis approaches this limitation by application of a Probability Hypothesis Density filter. The Probability Hypothesis Density filter was the first practically implemented state estimator based on random finite sets. It circumvents the combinatorial nature of data association itself by propagation of an object density measure that can be computed efficiently, without maintaining explicit trajectory hypotheses. In this work, the filter recursion is used to augment measurements with an additional hidden kinematic state to be used for construction of more informed flow network cost terms, e.g., based on linear motion models. The method is evaluated on public benchmarks where a considerate improvement is achieved compared to network flow formulations that are based on static features alone, such as distance between detections and appearance similarity. A second part of this thesis focuses on the related task of detecting and tracking a single robot operator in crowded environments. Different from the conventional multiple object tracking scenario, the tracked individual can leave the scene and later reappear after a longer period of absence. Therefore, a re-identification component is required that picks up the track on reentrance. Based on random finite sets, the Bernoulli filter is an optimal Bayes filter that provides a natural representation for this type of problem. In this work, it is shown how the Bernoulli filter can be combined with a Probability Hypothesis Density filter to track operator and non-operators simultaneously. The method is evaluated on a publicly available multiple object tracking dataset as well as on custom sequences that are specific to the targeted application. Experiments show reliable tracking in crowded scenes and robust re-identification after long term occlusion. Finally, a third part of this thesis focuses on appearance modeling as an essential aspect of any method that is applied to visual object tracking scenarios. Therefore, a feature representation that is robust to pose variations and changing lighting conditions is learned offline, before the actual tracking application. This thesis proposes a joint classification and metric learning objective where a deep convolutional neural network is trained to identify the individuals in the training set. At test time, the final classification layer can be stripped from the network and appearance similarity can be queried using cosine distance in representation space. This framework represents an alternative to direct metric learning objectives that have required sophisticated pair or triplet sampling strategies in the past. The method is evaluated on two large scale person re-identification datasets where competitive results are achieved overall. In particular, the proposed method better generalizes to the test set compared to a network trained with the well-established triplet loss.

The aquatic environment is exposed to multiple environmental pressures and mixtures of chemical substances, among them petroleum and petrochemicals, metals, and pesticides. Aquatic invertebrate communities are used as bioindicators to reflect long-term and integral effects. Information on the presence of species can be supplemented with information on their traits. SPEAR-type bioindicators integrate such trait information on the community level. This thesis aimed at enhancing specificity of SPEAR-type bioindicators towards particular groups of chemicals, namely to mixtures of oil sands-derived compounds, hydrocarbons, and metals. For developing a bioindicator for discontinuous contamination with oil-derived organic toxicants, a field study was conducted in the Canadian oil sands development region in Northern Alberta. The traits ‘physiological sensitivity towards organic chemicals’ and ‘generation time’ were integrated to develop the bioindicator SPEARoil, reflecting the community sensitivity towards oil sands derived contamination in relation to fluctuating hydrological conditions. According to the SPEARorganic approach, a physiological sensitivity ranking of taxa was developed for hydrocarbon contamination originating from crude oil or petroleum distillates. For this purpose, ecotoxicological information from acute laboratory tests was enriched with rapid and mesocosm test results. The developed Shydrocarbons sensitivity values can be used in SPEAR-type bioindicators. To specifically reflect metal contamination in streams via bioindicators, Australian field studies were re-evaluated with focus on the traits ‘physiological metal sensitivity’ and ‘feeding type’. Metal sensitivity values, however, explained community effects in the field only weakly. Instead, the trait ‘feeding type’ was strongly related to metal exposure. The fraction of predators in a community can, thus, serve as an indicator for metal contamination in the field. Furthermore, several metrics reflecting exposure to chemical cocktails in the environment were compared using existing pesticide datasets. Exposure metrics based on the 5% fraction of species sensitivity distributions were found to perform best, however, closely followed by Toxic Unit metrics based on the most sensitive species of a community or Daphnia magna.

With 47% land coverage in 2016, agricultural land was one of the largest terrestrial biomes in Germany. About 70% of the agricultural land was cropped area with associated pesticide applications. Agricultural land also represents an essential habitat for amphibians. Therefore, exposure of amphibians to agrochemicals, such as fertilizers and pesticides, seems likely. Pesticides can be highly toxic for amphibians, even a fraction of the original application rate may result in high amphibian mortality. To evaluate the potential risk of pesticide exposure for amphibians, the temporal coincidence of amphibian presence on agricultural land and pesticide applications (N = 331) was analyzed for the fire-bellied toad (Bombina bombina), moor frog (Rana arvalis), spadefoot toad (Pelobates fuscus) and crested newt (Triturus cristatus) during spring migration. In 2007 and 2008, up to 80% of the migrating amphibians temporally coincided with pesticide applications in the study area of Müncheberg, about 50 km east of Berlin. Pesticide interception by plants ranged between 50 to 90% in winter cereals and 80 to 90% in winter rape. The highest coincidence was observed for the spadefoot toad, where 86.6% of the reproducing population was affected by a single pesticide in winter rape during stem elongation with 80% pesticide interception by plants. Late migrating species, such as the fire-bellied toad and the spadefoot toad, overlapped more with pesticide applications than early migrating species, such as the moor frog, did. Under favorable circumstances, the majority of early migrants may not coincide with the pesticide applications of arable fields during spring migration. To evaluate the potential effect of pesticide applications on populations of the common frog (Rana temporaria), a landscape genetic study was conducted in the vinicultural area of Southern Palatinate. Due to small sample sizes at breeding sites within viniculture, several DNA sampling methods were tested. Furthermore, the novel repeated randomized selection of genotypes approach was developed to utilize genetic data from siblings for more reliable estimates of genetic parameters. Genetic analyses highlighted three of the breeding site populations located in viniculture as isolated from the meta-population. Genetic differentiation among breeding site populations in the viniculture (median pairwise FST=0.0215 at 2.34 km to 0.0987 at 2.39 km distance) was higher compared to genetic differentiation among breeding site populations in the Palatinate Forest (median pairwise FST=0.0041 at 5.39 km to 0.0159 at 9.40 km distance). The presented studies add valuable information about the risk of pesticide exposure for amphibians in the terrestrial life stage and possible effects of agricultural land on amphibian meta-populations. To conserve endemic amphibian species and their (genetic) diversity in the long run, the risk assessment of pesticides and applied agricultural management measures need to be adjusted to protect amphibians adequately. In addition, other conservation measures such as the creation of new suitable breeding site should be considered to improve connectivity between breeding site populations and ensure the persistence of amphibians in the agricultural land.

Systemic neonicotinoids are one of the most widely used insecticide classes worldwide. In addition to their use in agriculture, they are increasingly applied on forest trees as a protective measure against insect pests. However, senescent leaves containing neonicotinoids might, inter alia during autumn leaf fall, enter nearby streams. There, the hydrophilic neonicotinoids may be remobilized from leaves to water resulting in waterborne exposure of aquatic non-target organisms. Despite the insensitivity of the standard test species Daphnia magna (Crustacea, Cladocera) toward neonicotinoids, a potential risk for aquatic organisms is evident as many other aquatic invertebrates (in particular insects and amphipods) display adverse effects when exposed to neonicotinoids in the ng/L- to low µg/L-range. In addition to waterborne exposure, in particular leaf-shredding invertebrates (= shredders) might be adversely affected by the introduction of neonicotinoid-contaminated leaves into the aquatic environment since they heavily rely on leaf litter as food source. However, dietary neonicotinoid exposure of aquatic shredders has hardly received any attention from researchers and is not considered during aquatic environmental risk assessment. The primary aim of this thesis is, therefore, (1) to characterize foliar neonicotinoid residues and exposure pathways relevant for aquatic shredders, (2) to investigate ecotoxicological effects of waterborne and dietary exposure on two model shredders, namely Gammarus fossarum (Crustacea, Amphipoda) and Chaetopteryx villosa (Insecta, Trichoptera), and (3) to identify biotic and abiotic factors potentially modulating exposure under field conditions. During the course of this thesis, ecotoxicologically relevant foliar residues of the neonicotinoids imidacloprid, thiacloprid and acetamiprid were quantified in black alder trees treated at field relevant levels. A worst-case model – developed to simulate imidacloprid water concentrations resulting from an input of contaminated leaves into a stream – predicted only low aqueous imidacloprid concentrations (i.e., ng/L-range). However, the model identified dietary uptake as an additional exposure pathway relevant for shredders up to a few days after the leaves’ introduction into the stream. When test organisms were simultaneously exposed (= combined exposure) to neonicotinoids leaching from leaves into the water and via the consumption of contaminated leaves, adverse effects exceeded those observed under waterborne exposure alone. When exposure pathways were separated using a flow-through system, dietary exposure towards thiacloprid-contaminated leaves caused similar sublethal adverse effects in G. fossarum as observed under waterborne exposure. Moreover, the effect sizes observed under combined exposure were largely predictable using the reference model “independent action”, which assumes different molecular target sites to be affected. Dietary toxicity for shredders might, however, be reduced under field conditions since UV-induced photodegradation and leaching decreased imidacloprid residues in leaves and thereby the toxicity for G. fossarum. In contrast, both shredders were found unable to actively avoid dietary exposure. This thesis thus recommends considering dietary exposure towards systemic insecticides, such as neonicotinoids, already during their registration to safeguard aquatic shredders, associated ecosystem functions (e.g., leaf litter breakdown) and ultimately ecosystem integrity.