Abstract
The results in this report represent the application of the modelling framework developed under WP2 of the InTaS project funded by the Carbon Trust as part of the broader ORJIP initiative. The framework combines, for the first time, the statistical inference methods traditionally used in isolation for survey and telemetry data. It aims to accurately and precisely apportion the exposure of particular seabird colonies and age stages, to anthropogenic offshore disturbance. Razorbills (Alca torda) were identified as one of four priority species during the literature survey undertaken in WP1 of the same project. A large-scale proof of concept was agreed for the east coast of Scotland. Survey and adult-only telemetry data were collated for similar spatial and temporal extents. The locations and sizes of razorbill colonies were provided and used to guide the habitat modelling and apportionment algorithm. Model selection was carried out to explore combinations of nine environmental covariates that most parsimoniously explained the pooled telemetry and survey data sets. Using the best model (arrived at by model selection), a comparison of survey-only, telemetry-only and joint survey-telemetry analyses confirmed the conclusions of simulation experiments from WP2 suggesting that the convergence and precision of joint analyses are superior to any single-data analysis. The covariates retained in the selected model indicated a coastal distribution, close to colonies for both adults and juveniles. Apparent foraging areas had flat, gravelly seabeds and occured in waters with high potential energy anomaly measures. We present results on the spatial distribution of usage by different colonies and size ages and present an illustrative calculation of apportionment for an exemplar off-shore region, along with a software tool that can use the results of our modelling for any area of interest for potential offshore development.