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.
Type
Thesis, PhD Doctor of Philosophy
Rights
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
http://creativecommons.org/licenses/by-nc-sa/3.0/
Embargo Date: Print and electronic copy of Chapter 4 restricted until 5th June 2017
Embargo Reason: Thesis restricted in accordance with University regulations
Collections
Except where otherwise noted within the work, this item's licence for re-use is described as Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Related items
Showing items related by title, author, creator and subject.
-
Computational modelling of cancer development and growth : modelling at multiple scales and multiscale modelling
Szymanska, Zuzanna; Cytowski, Maciej; Mitchell, Elaine; Macnamara, Cicely K.; Chaplain, Mark A. J. (2018-05) - Journal articleIn this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of ... -
Distinguishing between models of mammalian gene expression : telegraph-like models versus mechanistic models
Braichenko, Svitlana; Holehouse, James; Grima, Ramon (2021-10-01) - Journal articleTwo-state models (telegraph-like models) have a successful history of predicting distributions of cellular and nascent mRNA numbers that can well fit experimental data. These models exclude key rate limiting steps, and ... -
Correct model-to-model transformation for formal verification
Meedeniya, Dulani Apeksha (University of St Andrews, 2013-06-26) - ThesisModern software systems have increasingly higher expectations on their reliability, in particular if the systems are critical and real-time. The development of these complex software systems requires strong modelling and ...