The diet of black-backed jackal (Canis Mesomelas) on two contrasting land-use types in the Eastern Cape Province, South Africa and the validation of a new analytical method of mammalian hair identification

Diet assessments are critical for understanding the foraging behaviour, habitat use and trophic separation of mammalian predators and are vital for gaining insight into how predators influence prey populations. The aim of this research was to qualitatively describe the diet of black-backed jackals (Canis mesomelas, Schreber 1775) using scat analysis on two contrasting land-use types in the Eastern Cape Province, South Africa. Scats were collected on a monthly basis from November 2009 to October 2010 from two game reserves (Great Fish River Reserve and Shamwari Private Game Reserve) and two neighbouring livestock farms. The relative frequency of occurrence of mammal hair (33 – 47 %) and vegetation (32 – 45%)dominated jackal diet throughout the year across the four study sites. Other important prey items included invertebrates (8 – 21 %) and fruit and seeds (3 – 11 %). Birds and reptiles constituted ≤ 2 % of the diet and were only recorded on the game reserves. Significant seasonal dietary shifts were observed on the game reserves but not on the farms. Fruit and seeds were significantly more frequent in the diet during autumn at Great Fish River Reserve and invertebrates were significantly less common in the diet during winter on both reserves. In addition, vegetation was significantly more common in the diet during winter at Shamwari Private Game Reserve. The significant temporal variation of certain prey items is testament to black-backed jackals being opportunistic generalists, foraging on those food items which are most abundant, accessible and energetically beneficial. Land-use type also influenced the diet of black-backed jackals with significantly more invertebrates and, fruit and seeds being recorded on the game reserves than on the farms. By contrast, significantly more mammal hair and vegetation were present in the diet on the farms compared with the game reserves. The mammalian component of the diet was dominated by ruminants and rodents on the game reserves and by ruminants and livestock on the farms. The presence of livestock in the diet of black-backed jackals on the farms highlights their potential impact on the livestock industry in the region and may assist farmers in determining which predators are responsible for stock loss. Previous approaches for identifying mammalian hairs from predator scats have utilised dichotomous keys and reference collections but these are often time-consuming and require a trained individual to carry out the identification. Thus, I also tested the efficacy of an automated pattern recognition programme (HairSnap) for identifying mammalian hairs from black-backed jackal scats. The overall accuracy of the programme was 38 % with black-backed jackal, Greater kudu (Tragelaphus strepsiceros) and striped polecat (Ictonyx striatus) hairs being accurately identified more often (70 – 80 %) than any other species tested. It is likely that both the size and species composition of the sample resulted in the poor accuracy of the programme. However, with the implementation of several improvement measures (e.g. adjustment of the algorithm) the programme may offer a superior, bias-free method of mammalian hair identification. The dietary information gathered here furthers our knowledge of the biology of the blackbacked jackals, especially in the locally important thicket biome. Moreover, understanding their foraging habits allows for more effective management of the species on both game reserves and farmlands. I recommend that future research should focus on quantitatively assessing the diet of black-backed jackals in the Eastern Cape Province and elsewhere. This will compliment the dietary description provided in this study and may offer a biologically more meaningful indication of the relative importance of the prey items

Exploring Engineering Applications of Visual Analytics in Virtual Reality

Recent advancements and technological breakthroughs in the development of so-called immersive interfaces, such as augmented (AR), mixed (MR), and virtual reality (VR), coupled with the growing mass-market adoption of such devices has started to attract attention from academia and industry alike. Out of these technologies, VR offers the most mature option in terms of both hardware and software, as well as the best available range of different off-the-shelf offerings. VR is a term interchangeably used to denote both head-mounted displays (HMDs) and fully immersive, bespoke 3D environments which these devices transport their users to. With modern devices, developers can leverage a range of different interaction modalities, including visual, audio, and even haptic feedback, in the creation of these virtual worlds. With such a rich interaction space it is thus natural to think of VR as a well-suited environment for interactive visualisation and analytical reasoning of complex multidimensional data. Research in \textit{visual analytics} (VA) combines these two themes, spanning the last one and a half decades, and has revealed a number of research findings. This includes a range of new advanced and effective visualisation and analysis tools for even more complex, more noisy and larger data sets. Furthermore, the extension of this research and the use of immersive interfaces to facilitate visual analytics has spun-off a new field of research: \textit{immersive analytics} (IA). Immersive analytics leverages the potential bestowed by immersive interfaces to aid the user in swift and effective data analysis. Some of the most promising application domains of such immersive interfaces in the industry are various branches of engineering, including aerospace design and in civil engineering. The range of potential applications is vast and growing as new stakeholders are adopting these immersive tools. However, the use of these technologies brings its own challenges. One such difficulty is the design of appropriate interaction techniques. There is no optimal choice, instead such a choice varies depending on available hardware, the user’s prior experience, their task at hand, and the nature of the dataset. To this end, my PhD work has focused on designing and analysing various interactive, VR-based immersive systems for engineering visual analytics. One of the key elements of such an immersive system is the selection of an adequate interaction method. In a series of both qualitative and quantitative studies, I have explored the potential of various interaction techniques that can be used to support the user in swift and effective data analysis. Here, I have investigated the feasibility of using techniques such as hand-held controllers, gaze-tracking and hand-tracking input methods used solo or in combination in various challenging use cases and scenarios. For instance, I developed and verified the usability and effectiveness of the AeroVR system for aerospace design in VR. This research has allowed me to trim the very large design space of such systems that have been not sufficiently explored thus far. Moreover, building on top of this work, I have designed, developed, and tested a system for digital twin assessment in aerospace that coupled gaze-tracking and hand-tracking, achieved via an additional sensor attached to the front of the VR headset, with no need for the user to hold a controller. The analysis of the results obtained from a qualitative study with domain experts allowed me to distill and propose design implications when developing similar systems. Furthermore, I worked towards designing an effective VR-based visualisation of complex, multidimensional abstract datasets. Here, I developed and evaluated the immersive version of the well-known Parallel Coordinates Plots (IPCP) visualisation technique. The results of the series of qualitative user studies allowed me to obtain a list of design suggestions for IPCP, as well as provide tentative evidence that the IPCP can be an effective tool for multidimensional data analysis. Lastly, I also worked on the design, development, and verification of the system allowing its users to capture information in the context of conducting engineering surveys in VR. Furthermore, conducting a meaningful evaluation of immersive analytics interfaces remains an open problem. It is difficult and often not feasible to use traditional A/B comparisons in controlled experiments as the aim of immersive analytics is to provide its users with new insights into their data rather than focusing on more quantifying factors. To this end, I developed a generative process for synthesising clustered datasets for VR analytics experiments that can be used in the process of interface evaluation. I further validated this approach by designing and carrying out two user studies. The statistical analysis of the gathered data revealed that this generative process for synthesising clustered datasets did indeed result in datasets that can be used in experiments without the datasets themselves being the dominant contributor of the variability between conditions.Engineering and Physical Sciences Research Council (EPSRC-1788814); Trinity Hall and Cambridge Commonwealth, European & International Trust; Cambridge Philosophical Societ

The relationship between research data management and virtual research environments

The aim of the study was to compile a conceptual model of a Virtual Research Environment (VRE) that indicates the relationship between Research Data Management (RDM) and VREs. The outcome of this study was that VREs are ideal platforms for the management of research data. In the first part of the study, a literature review was conducted by focusing on four themes: VREs and other concepts related to VREs; VRE components and tools; RDM; and the relationship between VREs and RDM. The first theme included a discussion of definitions of concepts, approaches to VREs, their development, aims, characteristics, similarities and differences of concepts, an overview of the e-Research approaches followed in this study, as well as an overview of concepts used in this study. The second theme consisted of an overview of developments of VREs in four countries (United Kingdom, USA, The Netherlands, and Germany), an indication of the differences and similarities of these programmes, and a discussion on the concept of research lifecycles, as well as VRE components. These components were then matched with possible tools, as well as to research lifecycle stages, which led to the development of a first conceptual VRE framework. The third theme included an overview of the definitions of the concepts ‘data’ and ‘research data’, as well as RDM and related concepts, an investigation of international developments with regards to RDM, an overview of the differences and similarities of approaches followed internationally, and a discussion of RDM developments in South Africa. This was followed by a discussion of the concept ‘research data lifecycles’, their various stages, corresponding processes and the roles various stakeholders can play in each stage. The fourth theme consisted of a discussion of the relationship between research lifecycles and research data lifecycles, a discussion on the role of RDM as a component within a VRE, the management of research data by means of a VRE, as well as the presentation of a possible conceptual model for the management of research data by means of a VRE. This literature review was conducted as a background and basis for this study. In the second part of the study, the research methodology was outlined. The chosen methodology entailed a non-empirical part consisting of a literature study, and an empirical part consisting of two case studies from a South African University. The two case studies were specifically chosen because each used different methods in conducting research. The one case study used natural science oriented data and laboratory/experimental methods, and the other, human orientated data and survey instruments. The proposed conceptual model derived from the literature study was assessed through these case studies and feedback received was used to modify and/or enhance the conceptual model. The contribution of this study lies primarily in the presentation of a conceptual VRE model with distinct component layers and generic components, which can be used as technological and collaborative frameworks for the successful management of research data.Thesis (DPhil)--University of Pretoria, 2018.National Research FoundationInformation ScienceDPhilUnrestricte