The importance of interaction strength for food web dynamics and ecosystem functioning

Global biodiversity is eroding at an alarming rate, through a combination of anthropogenic disturbance and environmental change. Ecological communities are bewildering in their complexity. Experimental ecologists strive to understand the mechanisms that drive the stability and structure of these complex communities in a bid to inform nature conservation and management. Two fields of research have had high profile success at developing theories related to these stabilising structures and testing them through controlled experimentation. Biodiversity-ecosystem functioning (BEF) research has explored the likely consequences of biodiversity loss on the functioning of natural systems and the provision of important ecosystem services. Empirical tests of BEF theory often consist of simplified laboratory and field experiments, carried out on subsets of ecological communities. Such experiments often overlook key information relating to patterns of interactions, important relationships, and fundamental ecosystem properties. The study of multi-species predator-prey interactions has also contributed much to our understanding of how complex systems are structured, particularly through the importance of indirect effects and predator suppression of prey populations. A growing number of studies describe these complex interactions in detailed food webs, which encompass all the interactions in a community. This has led to recent calls for an integration of BEF research with the comprehensive study of food web properties and patterns, to help elucidate the mechanisms that allow complex communities to persist in nature. This thesis adopts such an approach, through experimentation at Lough Hyne marine reserve, in southwest Ireland. Complex communities were allowed to develop naturally in exclusion cages, with only the diversity of top trophic levels controlled. Species removals were carried out and the resulting changes to predator-prey interactions, ecosystem functioning, food web properties, and stability were studied in detail. The findings of these experiments contribute greatly to our understanding of the stability and structure of complex natural communities.

Miniaturised multi-MEMS sensor development

Complex systems, from environmental behaviour to electronics reliability, can now be monitored with Wireless Sensor Networks (WSN), where multiple environmental sensors are deployed in remote locations. This ensures aggregation and reading of data, at lower cost and lower power consumption. Because miniaturisation of the sensing system is hampered by the fact that discrete sensors and electronics consume board area, the development of MEMS sensors offers a promising solution. At Tyndall, the fabrication flow of multiple sensors has been made compatible with CMOS circuitry to further reduce size and cost. An ideal platform on which to host these MEMS environmental sensors is the Tyndall modular wireless mote. This paper describes the development and test of the latest sensors incorporating temperature, humidity, corrosion, and gas. It demonstrates their deployment on the Tyndall platform, allowing real-time readings, data aggregation and cross-correlation capabilities. It also presents the design of the next generation sensing platform using the novel 10mm wireless cube developed by Tyndall.

Hazard and early warning analysis based on domain specific modeling technologies

An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future.