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dc.contributor.supervisorHowell, Kerry
dc.contributor.authorGraves, Kyran Patrick
dc.contributor.otherSchool of Biological and Marine Sciencesen_US

As the development of new technologies continues, so do industrial activities. As a result, such industries can extract natural resources and use the marine environment at deeper and deeper depths, for example, fisheries, oil and gas, submarine cabling, and – the latest emergence – deep-sea mining. Despite these developments, the majority of the deep ocean, including national waters and the High Seas, remains unmapped. The absence of data across large swathes of the deep sea means that conducting adequate environmental impact assessments when new activities are proposed is difficult, and what data is available is often sparse. Predictive habitat models are tools that can be used in a deep-sea context to help address the lack of observational data, by creating full coverage maps of the predicted distribution of a species or habitat.

This thesis reviews predictive habitat models and how these models are currently used in deep-sea settings. Additionally, this thesis aims to utilise habitat suitability models – a type of predictive habitat model – to predict the distribution of seven Vulnerable Marine Ecosystems (VMEs) across the UK and Irish national waters, and evaluate their performance. The model outputs are used to demonstrate how they can be used to inform spatial management, such as assessing the effectiveness of existing marine protection measures and identifying areas where VMEs are at high risk from deep-sea bottom fisheries. The evaluation of model performance suggest that habitat suitability models used are effective at predicting the presence of VMEs and that; generally, combining modelling methods (ensembling) improves the model's ability to successfully predict occurrences. The assessment of model outputs concerning existing conservation measures suggests that the 800 m ban on bottom-fishing is a highly successful conservation measure for the seven VME modelled, whilst also identifying that the network of marine protected areas is considerably less effective. The study also identifies two example areas of the Irish continental slope where suitable habitat for several VMEs is high but coincides with historically intense bottom-fishing activities that have since ceased, and therefore recommends these areas for habitat-recovery monitoring. Lastly, this thesis discusses the potential uses of spatial transfers in addressing the regional disparities in available distribution data, as well as the challenges around the acceptability of PHMs in formal advice to marine conservation managers and policymakers.

dc.description.sponsorshipMarine Institute (Galway)en_US
dc.publisherUniversity of Plymouth
dc.rightsCC0 1.0 Universal*
dc.subjectDeep-sea Ecologyen_US
dc.subjectMarine Spatial Planningen_US
dc.subjectHabitat Suitability Modellingen_US
dc.subjectBiotope Mappingen_US
dc.titleThe Application of Habitat Suitability Modelling to Mapping VME Distribution in the Deep Sea to Inform Spatial Managementen_US
dc.rights.embargoperiod12 monthsen_US

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