|Appears in Collections:||Aquaculture eTheses|
|Title:||GIS based models for optimisation of marine cage aquaculture in Tenerife, Canary Islands|
|Author(s):||Perez Martinez, Oscar|
|Publisher:||University of Stirling|
|Abstract:||This study focused on the optimisation of offshore marine fish-cage farming in Tenerife, Canary Islands. The main objective was to select the most suitable sites for offshore cage culture. This is a key factor in any aquaculture operation, affecting both success and sustainability. Moreover, it can solve conflicts between different coastal activities, making a rational use of the coastal space. Site selection was achieved by using Geographical Information Systems (GIS) based models and related technology, such as satellite images and Global Positioning System (GPS), to support the decision-making process. Three different cage systems were selected and proposed for different areas around Tenerife. Finally, a particulate waste distribution model (uneaten feed and faeces) was developed, also using GIS, for future prediction of the dispersive nature of selected sites. This can reduce the number of sites previously identified as most suitable, by predicting possible environmental impacts on the benthos if aquaculture was to be developed on a specific site. The framework for spatial multi-criteria decision analysis used in this study began with a recognition and definition of the decision problem. Subsequently, 31 production functions (factors and constraints) were identified, defined and subdivided into 8 sub-models. These sub-models were then integrated into a GIS database in the form of thematic layers and later scored for standardization. At this stage, the database was verified by field sampling to establish the quality of data used. The decision maker's preferences were incorporated into the decision model by assigning weights of relative importance to the evaluation under consideration. These, together with the thematic layers, were integrated by using Multi-criteria Evaluation (MCE) and simple overlays to provide an overall assessment of possible alternatives. Finally, sensitivity analysis was performed to determine the model robustness. The integration, manipulations and presentation of the results by means of GIS-based models in this sequential and logical flow of steps proved to be very effective for helping the decision-making process of site selection in study. On the whole, this study revealed the usefulness of GIS as an aquaculture planning and management tool. Cage systems that can withstand harsh environments were found to be suitable for use over a broader area of Tenerife's coastline. Thus, the more robust self-tensioned cage (SeaStation®) could be used over a greater area than the weaker gravity cages (Corelsa®). From the 228 km2 of available area for siting cages in the coastal regions with depth of 50 m, the suitable area (sum of scores 6, 7 and 8) for siting SeaStation® cages was 61 km2, while the suitable area for SeaStation® and Corelsa® cages was 49 and 37 km2 respectively. Most of the variation between these three cage systems was found among the intermediate suitability scores. It was concluded that the biggest differences in suitable area among cage systems are between Corelsa® and SeaStation® systems, followed by differences between Corelsa® and OceanSpar® cages, and OceanSpar® and SeaStation® respectively. This variability was mostly located on the N and NNW of the island, where waves, both long and short-term, are higher.|
|Type:||Thesis or Dissertation|
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