Statistical developments for understanding anthropogenic impacts on marine ecosystems

Abstract

Over the past decades technological developments have both changed and increased human influence on the marine environment. We now have greater potential than ever before to introduce disturbance and deplete marine resources. Two of the issues currently under public scrutiny are the exploitation of fish stocks worldwide and levels of anthropogenic noise in the marine environment. The aim of this thesis is to investigate and develop novel analyses and simulations to provide additional insight into some of the challenges facing the marine ecosystem today. These methodologies will improve the management of these risks to marine ecosystems. This thesis first addresses the issue of competition between humans and grey seals (Halichoerus grypus) for marine resources, providing compelling evidence that a substantial proportion of the sandeels consumed by grey seals in the North Sea are in fact H. lanceolatus, which is not commercially exploited, rather than the commercially important A. marinus. In addition, we present quantitative results regarding sources of bias when estimating the total biomass of sandeels consumed by grey seals. Secondly, we investigate spatially adaptive 2-dimensional smoothing to improve the prediction of both the presence and density of marine species, information that is often key in the management of marine ecosystems. Particularly, we demonstrate the benefits of such methods in the prediction of sandeel occurrence. Lastly this thesis provides a quantitative assessment of the protocols for real-time monitoring of marine mammal presence, which require that acoustic operations cease when an animal is detected within a certain distance (i.e. the "monitoring zone") of the sound source. We assess monitoring zones of different sizes with regards to their effectiveness in reducing the risks of temporary and permanent damage to the animals' hearing, and demonstrate that a monitoring zone of 2 km is generally recommendable.