Statistical power analysis of seabird monitoring methods in strong tidal streams

Due to imprecisions in the assessments of the environmental impacts of marine renewable energy devices on the surrounding environments, regulatory authorities often adopt a conservative approach by requiring extensive and stringent monitoring of potentially impacted species. Field surveys of seabirds, before and after device installation, are required to establish baseline conditions and monitor changes to these baselines, should a project be consented/licensed. However, assessments of the impact of devices through comparisons of pre-and post-construction species abundances may be unreliable due to the dynamic nature of environmental factors affecting the seasonal and spatial distribution of seabirds, resulting in survey programs with low statistical power to detect all but substantial changes. We hypothesise that including simultaneously collected data on predators, prey, and finescale characteristics of the water column in traditional survey designs could improve the ability to detect marine renewable devices' effects. Using power analysis methods, we show that incorporating hydrodynamic and prey covariates into the models not only increases the power to detect small changes in the number of seabirds due to the presence of devices but also reduced the number the surveys required to achieve similar power. Therefore, we recommend that power analyses covering multiple scenarios are included in the design phase of monitoring programmes to implement statistically robust and costeffective plans.