Biodiversity change in the Irish uplands - the effects of grazing management

As a prominent form of land use across much of upland Europe, extensive livestock grazing may hold the key to the sustainable management of these landscapes. Recent agricultural policy reform, however, has resulted in a decline in upland sheep numbers, prompting concern for the biodiversity value of these areas. This study quantifies the effects of varying levels of grazing management on plant, ground beetle and breeding bird diversity and assemblage in the uplands and lowlands of hill sheep farms in County Kerry, Ireland. Farms represent a continuum of light to heavy grazing, measured using a series of field indicators across several habitats, such as the internationally important blanket bog, home to the ground beetle, Carabus clatratus. Linear mixed effects modelling and non-metric multidimensional scaling are employed to disentangle the most influential management and environmental factors. Grazing state may be determined by the presence of Molinia caerulea or Nardus stricta, and variables such as % traditional ewes, % vegetation litter and % scrub prove valuable indicators of diversity. Measures of ecosystem functioning, e.g. plant biomass (nutrient cycling) and % vegetation cover (erosion rates) are influenced by plant diversity, which is influenced by grazing management. Levels of the ecosystem service, soil organic carbon, vary with ground beetle abundance and diversity, potentially influencing carbon sequestration and thereby climate change. The majority of species from all three taxa are found in the lowlands, with the exception of birds such as meadow pipit and skylark. The scale of measurement should be determined by the size and mobility of the species in question. The challenge is to manage these high nature value landscapes using agri-environment schemes which enhance biodiversity by maintaining structural heterogeneity across a range of scales, altitudes and habitats whilst integrating the decisions of people living and working in these marginal areas.

Designing tools that enhance communication and understanding between multiple stakeholders: the case of mobile payment value networks

The pervasive use of mobile technologies has provided new opportunities for organisations to achieve competitive advantage by using a value network of partners to create value for multiple users. The delivery of a mobile payment (m-payment) system is an example of a value network as it requires the collaboration of multiple partners from diverse industries, each bringing their own expertise, motivations and expectations. Consequently, managing partnerships has been identified as a core competence required by organisations to form viable partnerships in an m-payment value network and an important factor in determining the sustainability of an m-payment business model. However, there is evidence that organisations lack this competence which has been witnessed in the m-payment domain where it has been attributed as an influencing factor in a number of failed m-payment initiatives since 2000. In response to this organisational deficiency, this research project leverages the use of design thinking and visualisation tools to enhance communication and understanding between managers who are responsible for managing partnerships within the m-payment domain. By adopting a design science research approach, which is a problem solving paradigm, the research builds and evaluates a visualisation tool in the form of a Partnership Management Canvas. In doing so, this study demonstrates that when organisations encourage their managers to adopt design thinking, as a way to balance their analytical thinking and intuitive thinking, communication and understanding between the partners increases. This can lead to a shared understanding and a shared commitment between the partners. In addition, the research identifies a number of key business model design issues that need to be considered by researchers and practitioners when designing an m-payment business model. As an applied research project, the study makes valuable contributions to the knowledge base and to the practice of management.

Quantifying the value of improved wind energy forecasts in a pool-based electricity market

This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.