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dc.contributor.advisorRoss, Lindsay G.-
dc.contributor.advisorTelfer, Trevor C.-
dc.contributor.authorHunter, Donna-Claire-
dc.description.abstractScotland’s coastal environment has many areas which are potentially suitable for sustainable aquaculture development. However previous studies have shown that aquaculture may have a detrimental impact on sensitive environments. The main objective of this study is to develop a holistic management tool for sustainable coastal marine aquaculture in the Western Isles of Scotland through development of a multi-faceted holistic model that allows consideration of sensitive environments. As the Scottish Government promotes better collaboration and integration of all involved in coastal zone governance (Baxter et al, 2008) this study illustrates the benefits to be gained from harmonized management of information in a Geographical Information System. GIS models are strong support tools designed to aid decision-making. The main strengths are that GIS can generate easily understandable visual displays of results which are based on robust models capable of incorporating vast amounts of spatial data and which can be predictive and can simulate future coastal environment scenarios. Within this study it is demonstrated that GIS-based models can successfully manage and manipulate a wide range of datasets that are essential components in the determination and management of suitable aquaculture locations. The GIS decision support tools evaluated and integrated in this study were based on four main sub models. These were Cage Site Suitability, Particulate Dispersion, Sensitivity Biodiversity Indicators and Visual Landscape Capacity. Exploration of a combination of these sub-models into an overall decision support system was also completed. All sub models developed were flexible, instrumentally coherent and communicatively balanced for the management and planning of the coastal environment . A sub-model was designed to evaluate and optimize the location of marine cage systems. This required development of data layers and modelled sub-components relevant to the important environmental and engineering factors affecting cage designs which included wave climate, bathymetric and substrate profiles. Three cage types were explored; those designed for sheltered, semi-exposed and exposed areas. These environmental factor layers were combined through weighting and Multi criteria evaluation consideration for each cage type. The resulting three sub-models indicated that while the archipelago has quite restricted development potential for cages designed for sheltered environments (91km2), there is a limited development potential for cages designed for semi exposed environments (1543km2) and an optimal potential for aquaculture development with cages designed for exposed environments (3103km2). The greatest potential environmental impact from aquaculture comes from particulate dispersion. Currently, assessing footprints of effect from fish farms is carried out on an individual site basis mostly at ten metre resolution. The sub-model successfully developed in this work resulted in a partially validated multisite particulate sub model at one metre resolution which implemented maximum current velocity as the friction/force image. The sub-model was run on a range of coastal loch fjord systems and demonstrated the variation in particulate dispersion patterns in each fjord system. In all the fjord systems modelled, even where farm sites are close neighbours, there appears to be minimal interaction in the particulate dispersion. While the particulate sub-model is effective and rapid to deploy for multiple sites, it requires further development in order to incorporate the quantitative aspects of particulate dispersion. Aquaculture biodiversity sensitivity indicators were evaluated and five main sub-components were developed; Species sensitive to Aquaculture, Endangered species, Species important to the Western Isles, important spawning and nursery areas and Protected Areas. The sub-model was constructed by combining these layers through weighting and Multicriteria evaluation. The outcomes indicated that within the study area there are 1168km2 (4% of study area) which are highly sensitive to aquaculture activity, although 20595km2 (65% of study area) has a biodiversity that is much less sensitive to aquaculture. This sub-model, and some of its components, can operate as a “stand alone” tool or can be combined into a larger framework. Little modification and re-parameterisation would be required to enable models to be developed to cover the whole of the Scottish coastline, or other coastal locations. Aquaculture can visually affect landscapes, seascapes and can adversely affect visual capacity of different areas. GIS was successfully applied to investigate this contentious issue. This comprehensive and flexible sub-model successfully develops Seascape and Landscape sensitivity analysis of aquaculture structures and also incorporated a novel approach to visual assessment through use of proportional assessment. Combining the sensitivity layers, 6448km2 of the waters of the archipelago (20% of study area) were categorized as having high capacity to incorporate new aquaculture developments, whilst 3301km2 (10% of study area) have a moderate capacity for new aquaculture structures and 1324km2 (4% of study area) have a low capacity for new developments. An overall conceptual framework was designed to explore two methods for the combination of the major sub-models in order to identify the most appropriate areas for sustainable aquaculture with consideration of possible conflicts including conservation issues. Initial evaluations involved the extraction of information from the component GIS sub-models into a structured database. The extracted data provides a range of information that can be used for statistical analysis and decision support, but which leaves the evaluation of the optimal siting of aquaculture at any location in the Western Isles in the hands of the database interrogator. The second method involved combining the sub-models within GIS whole considering trade offs in relation to conservation. This GIS combination of models indicated that, taking many factors into consideration, the Western Isles has 748km2 (2.5% of study area) appropriate for aquaculture development when implementing the C315 and whilst considering the interactions with conservation areas. There were 498km2 (1.6% of study area) appropriate for development when implementing the intermediate C250 cage types but only 15km2 (0.04% of study area) were appropriate for development based on the LMS cage designs for sheltered environments. Both analytical approaches had strengths and weakness and clearly both need to be used in combination to maximise the benefit of the GIS model outcomes. This study has demonstrated the ability to apply scientific rigour to spatial modelling of aquaculture problems including site suitability, biodiversity, landscape capacity and multi-site particulate dispersion. The various sub-models and their components sub-models can be stand-alone decision-making tools or combined into a holistic model which incorporates a flexible method of trade-off management. The range of GIS-based coastal analytical tools developed form the core of a decision support system that can enable the objective management of the increasing demands on the coastal zone, while having the capacity to bring together stakeholders, multiple agencies and governing bodies that are responsible for management and use of these precious and sometimes threatened resources.en
dc.publisherUniversity of Stirlingen
dc.subject.lcshAquaculture industry Scotlanden
dc.titleA GIS-based decision support tool for optimisation of marine cage siting for aquaculture: A case study for the Western Isles, Scotland.en
dc.typeThesis or Dissertationen
dc.type.qualificationnameDoctor of Philosophyen
dc.rights.embargoreasonThesis chapters are currently being finalised for peer review submission and publication.en
dc.contributor.affiliationSchool of Natural Sciences-
Appears in Collections:Aquaculture eTheses

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