An Examination of Transformation Techniques to Investigate and Interpret Multivariate Geochemical Data Analysis: Tellus Case Study

This research aims to use the multivariate geochemical dataset, generated by the Tellus project, to investigate the appropriate use of transformation methods to maintain the integrity of geochemical data and inherent constrained behaviour in multivariate relationships. The widely used normal score transform is compared with the use of a stepwise conditional transform technique. The Tellus Project, managed by GSNI and funded by the Department of Enterprise Trade and Development and the EU’s Building Sustainable Prosperity Fund, involves the most comprehensive geological mapping project ever undertaken in Northern Ireland. Previous study has demonstrated spatial variability in the Tellus data but geostatistical analysis and interpretation of the datasets requires use of an appropriate methodology that reproduces the inherently complex multivariate relations. Previous investigation of the Tellus geochemical data has included use of Gaussian-based techniques. However, earth science variables are rarely Gaussian, hence transformation of data is integral to the approach. The multivariate geochemical dataset generated by the Tellus project provides an opportunity to investigate the appropriate use of transformation methods, as required for Gaussian-based geostatistical analysis. In particular, the stepwise conditional transform is investigated and developed for the geochemical datasets obtained as part of the Tellus project. The transform is applied to four variables in a bivariate nested fashion due to the limited availability of data. Simulation of these transformed variables is then carried out, along with a corresponding back transformation to original units. Results show that the stepwise transform is successful in reproducing both univariate statistics and the complex bivariate relations exhibited by the data. Greater fidelity to multivariate relationships will improve uncertainty models, which are required for consequent geological, environmental and economic inferences.

Alternate wetting and drying irrigation for rice in Bangladesh: Is it sustainable and has plant breeding something to offer?

The crop management practice of alternate wetting and drying (AWD) is being promoted by IRRI and the national research and extension program in Bangladesh and other parts of the world as a water-saving irrigation practice that reduces the environmental impact of dry season rice production through decreased water usage, and potentially increases yield. Evidence is growing that AWD will dramatically reduce the concentration of arsenic in harvested rice grains conferring a third major advantage over permanently flooded dry season rice production. AWD may also increase the concentration of essential dietary micronutrients in the grain. However, three crucial aspects of AWD irrigation require further investigation. First, why is yield generally altered in AWD? Second, is AWD sustainable economically (viability of farmers' livelihoods) and environmentally (aquifer water table heights) over long-term use? Third, are current cultivars optimized for this irrigation system? This paper describes a multidisciplinary research project that could be conceived which would answer these questions by combining advanced soil biogeochemistry with crop physiology, genomics, and systems biology. The description attempts to show how the breakthroughs in next generation sequencing could be exploited to better utilize local collections of germplasm and identify the molecular mechanisms underlying biological adaptation to the environment within the context of soil chemistry and plant physiology.

Evidence and Spatial Planning for Sustainable Development: A Model for Spatially Allocating Material Flows

The aspiration the spatial planning should act as the main coordinating function for the transition to a sustainable society is grounded on the assumption that it is capable of incorporating both a strong evidence base of environmental accounting for policy, coupled with opportunities for open, deliberative decision-making. While there are a number of increasingly sophisticated methods (such as material flow analysis and ecological footprinting) that can be used to longitudinally determine the impact of policy, there are fewer that can provide a robust spatial assessment of sustainability policy. In this paper, we introduce the Spatial Allocation of Material Flow Analysis (SAMFA) model, which uses the concept of socio-economic metabolism to extrapolate the impact of local consumption patterns that may occur as a result of the local spatial planning process at multiple spatial levels. The initial application the SAMFA model is based on County Kildare in the Republic of Ireland, through spatial temporal simulation and visualisation of construction material flows and associated energy use in the housing sector. Thus, while we focus on an Ireland case study, the model is applicable to spatial planning and sustainability research more generally. Through the development and evaluation of alternative scenarios, the model appears to be successful in its prediction of the cumulative resource and energy impacts arising from consumption and development patterns. This leads to some important insights in relation to the differential spatial distribution of disaggregated allocation of material balance and energy use, for example that rural areas have greater resource accumulation (and are therefore in a sense “less sustainable”) than urban areas, confirming that rural housing in Ireland is both more material and energy intensive. This therefore has the potential to identify hotspots of higher material and energy use, which can be addressed through targeted planning initiatives or focussed community engagement. Furthermore, due to the ability of the model to allow manipulation of different policy criteria (increased density, urban conservation etc), it can also act as an effective basis for multi-stakeholder engagement.

Environmental Education and Education for Sustainable Development

This article attempts a broad characterization of environmental education (EE) and education for sustainable development (ESD), and includes a short overview of the history of the field, key debates, the main approaches to ESD and EE, and a look toward the future. However, such a brief account should not be considered to be fully comprehensive, and can only be considered to provide a broad overview of the field from the authors’ perspectives

Life Cycle Assessment guidelines for the sustainable production and recycling of aggregates:The Sustainable Aggregates Resource Management project (SARMa)

The mining/quarrying industry is a sector of industry where there are very few Life Cycle Assessment (LCA) tools, and where the role of LCA has been poorly investigated. A key issue is the integration of three inter-dependent life cycles: Project, Asset and Product. Given the unique features of mining LCAs, this Note from the Field presents a common methodology implemented within the Sustainable Aggregates Resource Management (SARMa) Project (www.sarmaproject.eu) in order to boost adoption of LCA in the aggregate industry in South Eastern Europe. The proposed methodology emphasises the importance of resource efficiency and recycling in the context of a Sustainable Supply Mix of aggregates for the construction industry. Through its adoption, aggregate producers, recyclers, and governmental planners would gain confidence with LCA tools and conduct consistent and meaningful life cycle analyses of natural and recycled aggregates. © 2011 Elsevier Ltd. All rights reserved.