Statistical analyses to support guidelines for marine avian sampling: Final report. [Digital Supplements A-G attached]

Interest in development of offshore renewable energy facilities has led to a need for high-quality, statistically robust information on marine wildlife distributions. A practical approach is described to estimate the amount of sampling effort required to have sufficient statistical power to identify species specific “hotspots” and “coldspots” of marine bird abundance and occurrence in an offshore environment divided into discrete spatial units (e.g., lease blocks), where “hotspots” and “coldspots” are defined relative to a reference (e.g., regional) mean abundance and/or occurrence probability for each species of interest. For example, a location with average abundance or occurrence that is three times larger the mean (3x effect size) could be defined as a “hotspot,” and a location that is three times smaller than the mean (1/3x effect size) as a “coldspot.” The choice of the effect size used to define hot and coldspots will generally depend on a combination of ecological and regulatory considerations. A method is also developed for testing the statistical significance of possible hotspots and coldspots. Both methods are illustrated with historical seabird survey data from the USGS Avian Compendium Database.

USE OF TSIM IN DIGITAL SIMULATION.

In this paper we shall discuss the use of the TSIM simulation software for modelling large-scale industrial processes. The discussion draws on our recent experience of modelling a large plant in the food-processing industry. We shall focus on those features of software organization and software engineering which proved to be particularly necessary for the execution of this project, and illustrate the extent to which the use of TISM facilitated the implementation of these features. We shall also make some general remarks about the 'life-cycle' of models resulting from projects of this kind.