Spatio-temporal planning within the framework of ecosystem approach to aquaculture

In recent years, marine aquaculture has emerged as a possible solution to offset stagnation of capture fisheries production, and to meet growing global seafood demands. The rapid growth in marine aquaculture development however has raised several concerns over potential ecological and social impacts in coastal and marine waters. In response to these growing concerns, various experts and stakeholders have proposed a holistic Ecosystem-Based Management (EBM) framework to establish an appropriate balance between production, ecological and social components of the ecosystem. The Food and Agriculture Organisation (FAO) Ecosystem Approach to Aquaculture (EAA) is an example of a holistic EBM framework that is specifically designed for aquaculture and aims to address the combined and long-term ecological and social impacts of aquaculture development.

Implementing an EAA framework requires a clear understanding of the functions and interactions of both aquaculture operations and the surrounding ecosystem. These relationships and interactions depend on both spatial and temporal scales of the ecosystem, are constantly evolving, and should be included in spatial decision-making procedures. One way of integrating across scales for management of ecosystems is through the process of Marine Spatial Planning (MSP). However, in recent years much of the development in MSP has been dedicated to policy making and developing guidelines without giving enough attention to the models that are required for its implementation. This thesis considered how EAA/MSP modelling could be improved, using aquaculture development in Tasmania, Australia as a case study.

An appropriate definition of MSP suitable for implementing of an EBM approach (e.g., EAA) needs to include temporal processes within the spatial decision-making procedure. This inclusion is highlighted as an essential requirement for balancing different carrying capacities (e.g., physical, production, ecological, social) as the spatial structure of the ecosystem evolves. In reviewing the MSP platform and current spatial modelling tools through an aquaculture lens (EAA) two key improvements were identified: 1) MSP as an integrative governance platform needs to develop advanced modelling or management techniques for the inclusion of temporal processes into spatial decision-making procedures (causal relationships between time and space) in order to realistically balance different carrying capacities in the ecosystem; 2) MSP/EAA modelling tools need to develop models at a strategic scale (e.g., regional, national) that go beyond the fixed narrow spatial scale that is often used for site selection.

Chapter 2 first provides a brief review of some of the limitations confronted by coastal marine aquaculture for further development followed by some of the proposed technological solutions that can partially mitigate such limitations and therefore suggest a more holistic approach. The last section review the FAO’s EAA framework and its four carrying capacities: physical, production, ecological and social. It identifies some of the challenges and current knowledge gaps in advancing the required tools for implementation of an EAA in the marine environment. Furthermore, it identifies some of the key components and interactions among different carrying capacities that can help to keep them in balance.

Chapter 3 provides an investigation on how spatial planning can better facilitate interactions between space and time for more proactive spatial decision-making. First Agent Based Modelling (ABM) and System Dynamics (SD) were assessed as two of the most important modelling paradigms for simulating complex systems, along with GIS as the prime modelling paradigm for spatial planning and decision-making. Second, it was demonstrated that any of these modelling paradigms individually could not successfully integrate spatio-temporal processes within MSP. However, the findings indicated that when AMB and SD were employed in combination with GIS (either through embedding or coupling techniques) they were better able to provide the three essential elements for implementing an EBM approach: 1) spatial structure and relationships among the spatial components, 2) temporal processes among the spatial components, and 3) changes or alterations in the spatial structure and function over time.

Chapter 4 examines physical limitations on marine aquaculture using southeast Tasmania as a case study. A physical carrying capacity model was designed to evaluate and optimise the location of marine cage systems at a strategic scale (e.g., regional), taking into account the physiological tolerances of the cultured species and specifications of available cage designs. A series of related models were developed to examine how the physical limits of marine areas might influence resource management within a Geographical Information System (GIS) platform. The first part of the model examined worst-case physical conditions based on maximum significant wave height, maximum ocean swells, and current velocity applied to five cage designs specifications intended for exposed marine environment. The second part of the model assessed Atlantic salmon physiological responses to water temperature, current velocity, and salinity. The results show that there is scope to expand production of post-smolt and adult Atlantic salmon in the region using cages purposefully designed for exposed conditions, whereas there is limited potential for expansion using cages designed for low to moderately exposed environments. These models will enable marine spatial decision-making to better identify potential zones for aquaculture development based on the types of farming proposed, which can then be targeted for more site-specific analyses.

Chapter 5 examines key social limitations on marine aquaculture using southeast Tasmania as a case study. A seascape visual characterisation model was developed to inform questions around social carrying capacity at a strategic scale in terms of visual impacts. A three stage model was developed within a GIS platform to provide several complementary visual baselines. The first stage of the model was based on the viewing geometry of an observer and sought to characterise and describe the seascape through five submodels: 1) area of the visibility, 2) length of the visible coastline, 3) distance to the view, 4) horizontal extent of the view and 5) vertical extent of the view. The second stage of the model used an Analytical Hierarchical Process (AHP) methodology to allocate two different preference weightings to each of the five submodels for viewpoints on both the land and the sea. These preference weights in combination with the actual values obtained from the submodels in the first stage, were then used to generate an individual visual quality score for each viewpoint across the entire study area. These visual quality scores in the last stage of the model were utilised in a series of interpolation and extrapolation processes to create baseline map layers that visually characterise the seascape and reflects the visual quality and visual significance of both the landward and seaward extents of the study area. These outputs can be used by stakeholders to inform and facilitate discussions regarding the quality of the seascape from different perspectives.

This thesis demonstrate how that it is possible to improve spatial modelling of aquaculture by providing a working example of a model that can determine physical carrying in relation to environmental conditions, and social carrying capacity in relation to visual amenity of the seascape. It identifies some clear recommendations on how to improve spatial planning and management of aquaculture by linking modelling paradigms from complex system and spatial planning disciplines as a part of an integrated resource management for marine spatial planning. Whilst there are a number of elements in the broader theoretical management model that need to be developed further, the roadmap outlined in this thesis provides clear and practical operational guidance for the future of MSP/EAA.