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Change Issues (change + issues)

Distribution by Scientific Domains

Earth and Environmental Science	50%

Selected Abstracts

Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in Australia

GLOBAL CHANGE BIOLOGY, Issue 8 2001
Damian J. Barrett
Abstract Quantifying continental scale carbon emissions from the oxidation of above-ground plant biomass following land-use change (LUC) is made difficult by the lack of information on how much biomass was present prior to vegetation clearing and on the timing and location of historical LUC. The considerable spatial variability of vegetation and the uncertainty of this variability leads to difficulties in predicting biomass C density (tC ha,1) prior to LUC. The issue of quantifying uncertainties in the estimation of land based sources and sinks of CO2, and the feasibility of reducing these uncertainties by further sampling, is critical information required by governments world-wide for public policy development on climate change issues. A quantitative statistical approach is required to calculate confidence intervals (the level of certainty) of estimated cleared above-ground biomass. In this study, a set of high-quality observations of steady state above-ground biomass from relatively undisturbed ecological sites across the Australian continent was combined with vegetation, topographic, climatic and edaphic data sets within a Geographical Information System. A statistical model was developed from the data set of observations to predict potential biomass and the standard error of potential biomass for all 0.05° (approximately 5 × 5 km) land grid cells of the continent. In addition, the spatial autocorrelation of observations and residuals from the statistical model was examined. Finally, total C emissions due to historic LUC to cultivation and cropping were estimated by combining the statistical model with a data set of fractional cropland area per land grid cell, fAc (Ramankutty & Foley 1998). Total C emissions from loss of above-ground biomass due to cropping since European colonization of Australia was estimated to be 757 MtC. These estimates are an upper limit because the predicted steady state biomass may be less than the above-ground biomass immediately prior to LUC because of disturbance. The estimated standard error of total C emissions was calculated from the standard error of predicted biomass, the standard error of fAc and the spatial autocorrelation of biomass. However, quantitative estimates of the standard error of fAc were unavailable. Thus, two scenarios were developed to examine the effect of error in fAc on the error in total C emissions. In the first scenario, in which fAc was regarded as accurate (i.e. a coefficient of variation, CV, of fAc = 0.0), the 95% confidence interval of the continental C emissions was 379,1135 MtC. In the second scenario, a 50% error in estimated cropland area was assumed (a CV of fAc = 0.50) and the estimated confidence interval increased to between 350 and 1294 MtC. The CV of C emissions for these two scenarios was 25% and 29%. Thus, while accurate maps of land-use change contribute to decreasing uncertainty in C emissions from LUC, the major source of this uncertainty arises from the prediction accuracy of biomass C density. It is argued that, even with large sample numbers, the high cost of sampling biomass carbon may limit the uncertainty of above-ground biomass to about a CV of 25%. [source]

EU sustainable development indicators: An overview

NATURAL RESOURCES FORUM, Issue 4 2005
Laure Ledoux
Abstract The European Union's commitment to sustainable development at the 1992 Earth Summit resulted in an EU-wide sustainable development strategy, adopted in Gothenburg in 2001. This article presents an overview of the set of sustainable development indicators (SDIs) recently adopted by the European Commission to monitor, assess and revise the strategy. It provides a critical assessment of the current status of the indicator set, and reviews the main policy trends in the areas of the strategy through a brief analysis of headline indicators, placing energy and climate change issues in a broader perspective. Finally, the article compares the energy SDIs to the recent inter-agency energy indicators for sustainable development (EISD), underlining their similarities as well as their different priorities and objectives. The article concludes that further research is needed to improve the SDI set and further explore the linkages between themes. [source]

Remote visualisation of Labrador convection in large oceanic datasets

ATMOSPHERIC SCIENCE LETTERS, Issue 4 2005
L. J. West
Abstract The oceans relinquish O(1PW) of heat into the atmosphere at high latitudes, the lion's share of which originates in localised ,hotspots' of violent convective mixing, but despite their small horizontal scale,O(10,100km),these features may penetrate deeply into the thermocline and are vital in maintaining the Atlantic Meridional Overturning Circulation (MOC). Accurate modelling of the MOC, therefore, requires a large-scale numerical model with very fine resolution. The global high-resolution ocean model, Ocean Circulation Climate Advanced Model (OCCAM) has been developed and run at the Southampton Oceanography Centre (SOC) for many years. It was configured to resolve the energetic scales of oceanic motions, and its output is stored at the Manchester Supercomputer Centre. Although this community resource represents a treasure trove of potential new insights into the nature of the world ocean, it remains relatively unexploited for a number of reasons, not the least of which is its sheer size. A system being developed at SOC under the auspices of the Grid for Ocean Diagnostics, Interactive Visualisation and Analysis (GODIVA) project makes the remote visualisation of very large volumes of data on modest hardware (e.g. a laptop with no special graphics capability) a present reality. The GODIVA system is enabling the unresolved question of oceanic convection and its relationship to large-scale flows to be investigated; a question that lies at the heart of many current climate change issues. In this article, one aspect of the GODIVA is presented, and used to locate and visualise regions of convective mixing in the OCCAM Labrador Sea. Copyright © 2006 Royal Meteorological Society [source]

Using Soft Systems Methodology for Performance Improvement and Organisational Change in the English National Health Service

JOURNAL OF CONTINGENCIES AND CRISIS MANAGEMENT, Issue 4 2004
Brian Jacobs
The Soft Systems Methodology (SSM) advocated by Checkland and Scholes (1990) has considerable potential. It can provide policy makers, professionals, and managers in complex health organisations with a valuable addition to management approaches leading to practical improvements through innovative organisational change. With reference to the English National Health Service (NHS), this author argues that SSM can enable managers and others to address problem situations holistically, identify critical issues, and reach an accommodation of different viewpoints as a basis for improvement. The SSM approach can usefully compliment strategic frameworks, such as the Balanced Scorecard, in achieving clarity of thinking about performance and change issues'. [source]