Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

The environmental impacts of technical change

The thesis is concerned with relationships between profit, technology and environmental change. Existing work has concentrated on only a few questions, treated at either micro or macro levels of analysis. And there has been something of an impasse since the neoclassical and neomarxist approaches are either in direct conflict (macro level), or hardly interact (micro level). The aim of the thesis was to bypass this impasse by starting to develop a meso level of analysis that focusses on issues largely ignored in the traditional approaches - on questions about distribution. The first questions looked at were descriptive - what were the patterns of distribution over time of the variability in types and rates of environmental change, and in particular, was there any evidence of periodization? Two case studies were used to examine these issues. The first looked at environmental change in the iron and steel industry since 1700, and the second studied pollution in five industries in the basic processing sector. It was established that environmental change has been markedly periodized, with an apparently fairly regular `cycle length' of about fifty years. The second questions considered were explanatory - whether and how this periodization could be accounted for by reference to variations in aspects of profitability and technical change. In the iron and steel industry, it was found that diffusion rates and the rate of nature of innovation were periodized on the same pattern as was environmental change. And the same sort of variation was also present in the realm of profits, as evidenced by cyclical changes in output growth. Simple theoretical accounts could be given for all the empirically demonstrable links, and it was suggested that the most useful models at this meso level of analysis are provided by structural change models of economic development.

Informational institutions in the agrifood sector:meta-information and meta-governance of environmental sustainability

In the agrifood sector, the explosive increase in information about environmental sustainability, often in uncoordinated information systems, has created a new form of ignorance ('meta-ignorance') that diminishes the effectiveness of information on decision-makers. Flows of information are governed by informal and formal social arrangements that we can collectively call Informational Institutions. In this paper, we have reviewed the recent literature on such institutions. From the perspectives of information theory and new institutional economics, current informational institutions are increasing the information entropy of communications concerning environmental sustainability and stakeholders' transaction costs of using relevant information. In our view this reduces the effectiveness of informational governance. Future research on informational governance should explicitly address these aspects.