A conceptual model for response to Arctic oil spills

The potential for oil spills in Arctic regions has increased significantly because of the development of petroleum resources. Response to an oil spill in the Arctic is likely to be much slower than that in the temperate region because of the remoteness of the area and its severe climate. In the face of these unique problems, accurate prediction of the extent and subsequent movement of an oil spill is vital to any cleanup effort. Presented is the framework of a program to study the movement of oil spills in the Arctic. Existing models of oil spreading and polar ice dynamics are reviewed and areas where new model development is required are defined. A system design is developed that may be used for developing a plan to act in the event of a major spill.     

Maritime oil spills— Environmental lessons and experiences with special reference to low-risk coastlines

Oil spill contingency plans are available for most coastlines but the amount of useful environmental data is variable. The information should be held on a GIS base. High risk areas should be identified and the pre-existing store of environmental knowledge should be commensurately extensive and should be available in considerable spatial detail. Contingency plans still depend on basic lists of coastal types as defined by static, sediment based shoreline characteristics. There is a lack of dynamic, process information. TheBraer oil spill of 1993 provides a case study of the application of sound coastal geomorphological and ecological data to impact assessment. Monitoring of the ecological effects of this massive oil spill reinforces other research which indicates that most coastlines can recover naturally from oil spills, and that oil spill clean up techniques may not necessarily benefit rapid shoreline recovery. Although pre-existing environmental informations is important, the key decisions must be taken quickly and are frequently judgmental and, therefore, place a premium on gathering appropriate scientific expertise to the site of the spill as soon as possible and with sufficient powers to affect both the oil spill response, to initiate early surveys of damage and to facilitate the initial monitoring programme.     

Diversity in Current Ecological Thinking: Implications for Environmental Management

Current ecological thinking emphasizes that systems are complex, dynamic, and unpredictable across space and time. What is the diversity in interpretation of these ideas among today’s ecologists, and what does this mean for environmental management? This study used a Policy Delphi survey of ecologists to explore their perspectives on a number of current topics in ecology. The results showed general concurrence with nonequilibrium views. There was agreement that disturbance is a widespread, normal feature of ecosystems with historically contingent responses. The importance of recognizing multiple levels of organization and the role of functional diversity in environmental change were also widely acknowledged. Views differed regarding the predictability of successional development, whether “patchiness” is a useful concept, and the benefits of shifting the focus from species to ecosystem processes. Because of their centrality to environmental management, these different views warrant special attention from both managers and ecologists. Such divergence is particularly problematic given widespread concerns regarding the poor linkages between science (here, ecology) and environmental policy and management, which have been attributed to scientific uncertainty and a lack of consensus among scientists, both jeopardizing the transfer of science into management. Several suggestions to help managers deal with these differences are provided, especially the need to interpret broader theory in the context of place-based assessments. The uncertainty created by these differences requires a proactive approach to environmental management, including clearly identifying environmental objectives, careful experimental design, and effective monitoring.