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Organisms often employ ecophysiological strategies to exploit environmental conditions and ensure bio-energetic success. However, the many complexities involved in the differential expression and flexibility of these strategies are rarely fully understood. Therefore, for the first time, using a three-part cross-disciplinary laboratory experimental analysis, we investigated the diversity and plasticity of photoresponsive traits employed by one family of environmentally contrasting, ecologically important phytoflagellates. The results demonstrated an extensive inter-species phenotypic diversity of behavioural, physiological, and compositional photoresponse across the Chlamydomonadaceae, and a multifaceted intra-species phenotypic plasticity, involving a broad range of beneficial photoacclimation strategies, often attributable to environmental predisposition and phylogenetic differentiation. Deceptively diverse and sophisticated strong (population and individual cell) behavioural photoresponses were observed, with divergence from a general preference for low light (and flexibility) dictated by intra-familial differences in typical habitat (salinity and trophy) and phylogeny. Notably, contrasting lower, narrow, and flexible compared with higher, broad, and stable preferences were observed in freshwater vs. brackish and marine species. Complex diversity and plasticity in physiological and compositional photoresponses were also discovered. Metabolic characteristics (such as growth rates, respiratory costs and photosynthetic capacity, efficiency, compensation and saturation points) varied elaborately with species, typical habitat (often varying more in eutrophic species, such as Chlamydomonas reinhardtii), and culture irradiance (adjusting to optimise energy acquisition and suggesting some propensity for low light). Considerable variations in intracellular pigment and biochemical composition were also recorded. Photosynthetic and accessory pigments (such as chlorophyll a, xanthophyll-cycle components, chlorophyll a:b and chlorophyll a:carotenoid ratios, fatty acid content and saturation ratios) varied with phylogeny and typical habitat (to attune photosystem ratios in different trophic conditions and to optimise shade adaptation, photoprotection, and thylakoid architecture, particularly in freshwater environments), and changed with irradiance (as reaction and harvesting centres adjusted to modulate absorption and quantum yield). The complex, concomitant nature of the results also advocated an integrative approach in future investigations. Overall, these nuanced, diverse, and flexible photoresponsive traits will greatly contribute to the functional ecology of these organisms, addressing environmental heterogeneity and potentially shaping individual fitness, spatial and temporal distribution, prevalence, and ecosystem dynamics.
Organisms often employ ecophysiological strategies to exploit environmental conditions and ensure bio-energetic success. However, the many complexities involved in the differential expression and flexibility of these strategies are rarely fully understood. Therefore, for the first time, using a three-part cross-disciplinary laboratory experimental analysis, we investigated the diversity and plasticity of photoresponsive traits employed by one family of environmentally contrasting, ecologically important phytoflagellates. The results demonstrated an extensive inter-species phenotypic diversity of behavioural, physiological, and compositional photoresponse across the Chlamydomonadaceae, and a multifaceted intra-species phenotypic plasticity, involving a broad range of beneficial photoacclimation strategies, often attributable to environmental predisposition and phylogenetic differentiation. Deceptively diverse and sophisticated strong (population and individual cell) behavioural photoresponses were observed, with divergence from a general preference for low light (and flexibility) dictated by intra-familial differences in typical habitat (salinity and trophy) and phylogeny. Notably, contrasting lower, narrow, and flexible compared with higher, broad, and stable preferences were observed in freshwater vs. brackish and marine species. Complex diversity and plasticity in physiological and compositional photoresponses were also discovered. Metabolic characteristics (such as growth rates, respiratory costs and photosynthetic capacity, efficiency, compensation and saturation points) varied elaborately with species, typical habitat (often varying more in eutrophic species, such as Chlamydomonas reinhardtii), and culture irradiance (adjusting to optimise energy acquisition and suggesting some propensity for low light). Considerable variations in intracellular pigment and biochemical composition were also recorded. Photosynthetic and accessory pigments (such as chlorophyll a, xanthophyll-cycle components, chlorophyll a:b and chlorophyll a:carotenoid ratios, fatty acid content and saturation ratios) varied with phylogeny and typical habitat (to attune photosystem ratios in different trophic conditions and to optimise shade adaptation, photoprotection, and thylakoid architecture, particularly in freshwater environments), and changed with irradiance (as reaction and harvesting centres adjusted to modulate absorption and quantum yield). The complex, concomitant nature of the results also advocated an integrative approach in future investigations. Overall, these nuanced, diverse, and flexible photoresponsive traits will greatly contribute to the functional ecology of these organisms, addressing environmental heterogeneity and potentially shaping individual fitness, spatial and temporal distribution, prevalence, and ecosystem dynamics.
Personal Big Data
(2017)
Many users of cloud-based services are concerned about questions of data privacy. At the same time, they want to benefit from smart data-driven services, which require insight into a person’s individual behaviour. The modus operandi of user modelling is that data is sent to a remote server where the model is constructed and merged with other users’ data. This thesis proposes selective cloud computing, an alternative approach, in which the user model is constructed on the client-side and only an abstracted generalised version of the model is shared with the remote services.
In order to demonstrate the applicability of this approach, the thesis builds an exemplary client-side user modelling technique. As this thesis is carried out in the area of Geoinformatics and spatio-temporal data is particularly sensitive, the application domain for this experiment is the analysis and prediction of a user’s spatio-temporal behaviour.
The user modelling technique is grounded in an innovative conceptual model, which builds upon spatial network theory combined with time-geography. The spatio-temporal constraints of time-geography are applied to the network structure in order to create individual spatio-temporal action spaces. This concept is translated into a novel algorithmic user modelling approach which is solely driven by the user’s own spatio-temporal trajectory data that is generated by the user’s smartphone.
While modern smartphones offer a rich variety of sensory data, this thesis only makes use of spatio-temporal trajectory data, enriched by activity classification, as the input and foundation for the algorithmic model. The algorithmic model consists of three basal components: locations (vertices), trips (edges), and clusters (neighbourhoods).
After preprocessing the incoming trajectory data in order to identify locations, user feedback is used to train an artificial neural network to learn temporal patterns for certain location types (e.g. work, home, bus stop, etc.). This Artificial Neural Network (ANN) is used to automatically detect future location types by their spatio-temporal patterns. The same is done in order to predict the duration of stay at a certain location. Experiments revealed that neural nets were the most successful statistical and machine learning tool to detect those patterns. The location type identification algorithm reached an accuracy of 87.69%, the duration prediction on binned data was less successful and deviated by an average of 0.69 bins. A challenge for the location type classification, as well as for the subsequent components, was the imbalance of trips and connections as well as the low accuracy of the trajectory data. The imbalance is grounded in the fact that most users exhibit strong habitual patterns (e.g. home > work), while other patterns are rather rare by comparison. The accuracy problem derives from the energy-saving location sampling mode, which creates less accurate results.
Those locations are then used to build a network that represents the user’s spatio-temporal behaviour. An initial untrained ANN to predict movement on the network only reached 46% average accuracy. Only lowering the number of included edges, focusing on more common trips, increased the performance. In order to further improve the algorithm, the spatial trajectories were introduced into the predictions. To overcome the accuracy problem, trips between locations were clustered into so-called spatial corridors, which were intersected with the user’s current trajectory. The resulting intersected trips were ranked through a k-nearest-neighbour algorithm. This increased the performance to 56%. In a final step, a combination of a network and spatial clustering algorithm was built in order to create clusters, therein reducing the variety of possible trips. By only predicting the destination cluster instead of the exact location, it is possible to increase the performance to 75% including all classes.
A final set of components shows in two exemplary ways how to deduce additional inferences from the underlying spatio-temporal data. The first example presents a novel concept for predicting the ‘potential memorisation index’ for a certain location. The index is based on a cognitive model which derives the index from the user’s activity data in that area. The second example embeds each location in its urban fabric and thereby enriches its cluster’s metadata by further describing the temporal-semantic activity in an area (e.g. going to restaurants at noon).
The success of the client-side classification and prediction approach, despite the challenges of inaccurate and imbalanced data, supports the claimed benefits of the client-side modelling concept. Since modern data-driven services at some point do need to receive user data, the thesis’ computational model concludes with a concept for applying generalisation to semantic, temporal, and spatial data before sharing it with the remote service in order to comply with the overall goal to improve data privacy. In this context, the potentials of ensemble training (in regards to ANNs) are discussed in order to highlight the potential of only sharing the trained ANN instead of the raw input data.
While the results of our evaluation support the assets of the proposed framework, there are two important downsides of our approach compared to server-side modelling. First, both of these server-side advantages are rooted in the server’s access to multiple users’ data. This allows a remote service to predict spatio-in the user-specific data, which represents the second downside. While minor classes will likely be minor classes in a bigger dataset as well, for each class, there will still be more variety than in the user-specific dataset. The author emphasises that the approach presented in this work holds the potential to change the privacy paradigm in modern data-driven services. Finding combinations of client- and server-side modelling could prove a promising new path for data-driven innovation.
Beyond the technological perspective, throughout the thesis the author also offers a critical view on the data- and technology-driven development of this work. By introducing the client-side modelling with user-specific artificial neural networks, users generate their own algorithm. Those user-specific algorithms are influenced less by generalised biases or developers’ prejudices. Therefore, the user develops a more diverse and individual perspective through his or her user model. This concept picks up the idea of critical cartography, which questions the status quo of how space is perceived and represented.
Im Sinne des Refinements von Tierversuchen sollen alle Bedingungen während der Zucht, der Haltung und des Transports von zu Versuchszwecken gehaltenen Tieren und alle Methoden während des Versuchs so verbessert werden, dass die verwendeten Tiere ein minimales Maß an potentiellem Distress, Schmerzen oder Leiden erfahren. Zudem soll ihr Wohlbefinden durch die Möglichkeit des Auslebens speziesspezifischer Verhaltensweisen und die Anwendung tierschonender Verfahren maximal gefördert werden. Zur Etablierung von Grundsätzen des Refinements sind grundlegende Kenntnisse über die physiologischen Bedürfnisse und Verhaltensansprüche der jeweiligen Spezies unabdingbar. Die Experimentatoren sollten das Normalverhalten der Tiere kennen, um potentielle Verhaltensabweichungen, wie Stereotypien, zu verstehen und interpretieren zu können. Standardisierte Haltungsbedingungen von zu Versuchszwecken gehaltenen Mäusen weichen in diversen Aspekten von der natürlichen Umgebung ab und erfordern eine gewisse Adaptation. Ist ein Tier über einen längeren Zeitraum unfähig, sich an die gegebenen Umstände anzupassen, können abnormale Verhaltensweisen, wie Stereotypien auftreten. Stereotypien werden definiert als Abweichungen vom Normalverhalten, die repetitiv und ohne Abweichungen im Ablauf ausgeführt werden, scheinbar keiner Funktion dienen und der konkreten Umweltsituation nicht immer entsprechen.
Bisher war unklar, in welchem Ausmaß stereotypes Verhalten den metabolischen Phänotyp eines Individuums beeinflusst. Ziel dieser Arbeit war es daher, das stereotype Verhalten der FVB/NJ-Maus erstmals detailliert zu charakterisieren, systematisch zusammenzutragen, welche metabolischen Konsequenzen dieses Verhalten bedingt und wie sich diese auf das Wohlbefinden der Tiere und die Verwendung stereotyper Tiere in Studien mit tierexperimentellem Schwerpunkt auswirken.
Der Versuch begann mit der Charakterisierung der mütterlichen Fürsorge in der Parentalgeneration. Insgesamt wurden 35 Jungtiere der F1-Generation vom Absatz an, über einen Zeitraum von 11 Wochen einzeln gehalten, kontinuierlich beobachtet, bis zum Versuchsende wöchentlich Kotproben gesammelt und das Körpergewicht bestimmt. Zusätzlich erfolgten begleitende Untersuchungen wie Verhaltenstests und die Erfassung der physischen Aktivität und metabolischer Parameter. Anschließend wurden u.a. die zerebralen Serotonin- und Dopamingehalte, fäkale Glucocorticoidlevels, hepatisches Glykogen und muskuläre Glykogen- und Triglyceridlevels bestimmt.
Nahezu unabhängig von der mütterlichen Herkunft entwickelte sich bei mehr als der Hälfte der 35 Jungtiere in der F1-Generation stereotypes Verhalten. Diese Daten deuten darauf hin, dass es keine Anzeichen für das Erlernen oder eine direkte genetische Transmission stereotypen Verhaltens bei der FVB/NJ-Maus gibt. Über den gesamten Beobachtungszeitraum zeichneten sich die stereotypen FVB/NJ-Mäuse durch ein eingeschränktes Verhaltensrepertoire aus. Zu Gunsten der erhöhten Aktivität und des Ausübens stereotypen Verhaltens lebten sie insgesamt weniger andere Verhaltensweisen (Klettern, Graben, Nagen) aus. Darüber hinaus waren Stereotypien sowohl im 24-Stunden Open Field Test als auch in der Messeinrichtung der indirekten Tierkalorimetrie mit einer erhöhten Aktivität und Motilität assoziiert, während die circadiane Rhythmik nicht divergierte. Diese erhöhte körperliche Betätigung spiegelte sich in den niedrigeren Körpergewichtsentwicklungen der stereotypen Tiere wieder. Außerdem unterschieden sich die Körperfett- und Körpermuskelanteile.
Zusammenfassend lässt sich sagen, dass das Ausüben stereotypen Verhaltens zu Differenzen im metabolischen Phänotyp nicht-stereotyper und stereotyper FVB/NJ-Mäuse führt. Im Sinne der „Guten Wissenschaftlichen Praxis“ sollte das zentrale Ziel jedes Wissenschaftlers sein, aussagekräftige und reproduzierbare Daten hervorzubringen. Jedoch können keine validen Resultate von Tieren erzeugt werden, die in Aspekten variieren, die für den vorgesehenen Zweck der Studie nicht berücksichtigt wurden. Deshalb sollten nicht-stereotype und stereotype Individuen nicht innerhalb einer Versuchsgruppe randomisiert werden. Stereotype Tiere demzufolge von geplanten Studien auszuschließen, würde allerdings dem Gebot des zweiten R’s – der Reduction – widersprechen. Um Refinement zu garantieren, sollte der Fokus auf der maximal erreichbaren Prävention stereotypen Verhaltens liegen. Diverse Studien haben bereits gezeigt, dass die Anreicherung der Haltungsumwelt (environmental enrichment) zu einer Senkung der Prävalenz von Stereotypien bei Mäusen führt, dennoch kommen sie weiterhin vor. Daher sollte environmental enrichment zukünftig weniger ein „Kann“, sondern ein „Muss“ sein – oder vielmehr: der Goldstandard. Zudem würde eine profunde phänotypische Charakterisierung dazu beitragen, Mausstämme zu erkennen, die zu Stereotypien neigen und den für den spezifischen Zweck am besten geeigneten Mausstamm zu identifizieren, bevor ein Experiment geplant wird.
In this BEEBOOK paper we present a set of established methods for quantifying honey bee behaviour. We start with general methods for preparing bees for behavioural assays. Then we introduce assays for quantifying sensory responsiveness to gustatory, visual and olfactory stimuli. Presentation of more complex behaviours like appetitive and aversive learning under controlled laboratory conditions and learning paradigms under free-flying conditions will allow the reader to investigate a large range of cognitive skills in honey bees. Honey bees are very sensitive to changing temperatures. We therefore present experiments which aim at analysing honey bee locomotion in temperature gradients. The complex flight behaviour of honey bees can be investigated under controlled conditions in the laboratory or with sophisticated technologies like harmonic radar or RFID in the field. These methods will be explained in detail in different sections. Honey bees are model organisms in behavioural biology for their complex yet plastic division of labour. To observe the daily behaviour of individual bees in a colony, classical observation hives are very useful. The setting up and use of typical observation hives will be the focus of another section. The honey bee dance language has important characteristics of a real language and has been the focus of numerous studies. We here discuss the background of the honey bee dance language and describe how it can be studied. Finally, the mating of a honey bee queen with drones is essential to survival of the entire colony. We here give detailed and structured information how the mating behaviour of drones and queens can be observed and experimentally manipulated.
The ultimate goal of this chapter is to provide the reader with a comprehensive set of experimental protocols for detailed studies on all aspects of honey bee behaviour including investigation of pesticide and insecticide effects.
1. We generally assume that animals should maximize information acquisition about their environment to make prudent decisions. But this is a naive assumption, as gaining information typically involves costs. <br /> 2. This is especially so in the social context, where interests between interacting partners usually diverge. The arms race involved in mutual assessment is characterized by the attempt to obtain revealing information from a partner while providing only as much information by oneself as is conducive to one's own intentions. <br /> 3. If obtaining information occasions costs in terms of time, energy and risk, animals should be selected to base their decisions on a cost-benefit ratio that takes account of the trade-off between the risk of making wrong choices and the costs involved in information acquisition, processing and use. <br /> 4. In addition, there may be physiological and/or environmental constraints limiting the ability to obtaining, processing and utilizing reliable information. <br /> 5. Here, we discuss recent empirical evidence for the proposition that social decisions are to an important extent based on the costs that result from acquiring, processing, evaluating and storing information. Using examples from different taxa and ecological contexts, we aim at drawing attention to the often neglected costs of information recipience, with emphasis on the potential role of sensory ecology and cognition in social decisions.