Considering climate change in the development of marine protected areas

Marine ecosystems are facing a diverse range of threats, including climate change, prompting international efforts to safeguard marine biodiversity through the use of spatial management measures. Marine Protected Areas (MPAs) have been implemented as a conservation tool throughout the world, but their usefulness and effectiveness is strongly related to climate change. However, few MPA programmes have directly considered climate change in the design, management or monitoring of an MPA network. Under international obligations, EU, UK and national targets, Scotland has developed an MPA network that aims to protect marine biodiversity and contribute to the vision of a clean, healthy and productive marine environment. This is the first study to critically analyse the Scottish MPA process and highlight areas which may be improved upon in further iterations of the network in the context of climate change. Initially, a critical review of the Scottish MPA process considered how ecological principles for MPA network design were incorporated into the process, how stakeholder perceptions were considered and crucially what consideration was given to the influence of climate change on the eventual effectiveness of the network. The results indicated that to make a meaningful contribution to marine biodiversity protection for Europe the Scottish MPA network should: i) fully adopt best practice ecological principles ii) ensure effective protection and iii) explicitly consider climate change in the management, monitoring and future iterations of the network. However, this review also highlighted the difficulties of incorporating considerations of climate change into an already complex process. A series of international case studies from British Columbia, Canada; central California, USA; the Great Barrier Reef, Australia and the Hauraki Gulf, New Zealand, were then conducted to investigate perceptions of how climate change has been considered in the design, implementation, management and monitoring of MPAs. The key lessons from this study included: i) strictly protected marine reserves are considered essential for climate change resilience and will be necessary as scientific reference sites to understand climate change effects ii) adaptive management of MPA networks is important but hard to implement iii) strictly protected reserves managed as ecosystems are the best option for an uncertain future. This work provides new insights into the policy and practical challenges MPA managers face under climate change scenarios. Based on the Scottish and international studies, the need to facilitate clear communication between academics, policy makers and stakeholders was recognised in order to progress MPA policy delivery and to ensure decisions were jointly formed and acceptable. A Delphi technique was used to develop a series of recommendations for considering climate change in Scotland’s MPA process. The Delphi participant panel was selected for their knowledge of the Scottish MPA process and included stakeholders, policy makers and academics with expertise in MPA research. The results from the first round of the Delphi technique suggested that differing views of success would likely influence opinions regarding required management of MPAs, and in turn, the data requirements to support management action decisions. The second round of the Delphi technique explored this further and indicated that there was a fundamental dichotomy in panellists’ views of a successful MPA network depending upon whether they believed the MPAs should be strictly protected or allow for sustainable use. A third, focus group round of the Delphi Technique developed a feature-based management scenario matrix to aid in deciding upon management actions in light of changes occurring in the MPA network. This thesis highlights that if the Scottish MPA network is to fulfil objectives of conservation and restoration, the implications of climate change for the design, management and monitoring of the network must be considered. In particular, there needs to be a greater focus on: i) incorporating ecological principles that directly address climate change ii) effective protection that builds resilience of the marine and linked social environment iii) developing a focused, strong and adaptable monitoring framework iv) ensuring mechanisms for adaptive management.

Hierarchically grouped 2D local features applied to edge contour localisation

One of the most significant research topics in computer vision is object detection. Most of the reported object detection results localise the detected object within a bounding box, but do not explicitly label the edge contours of the object. Since object contours provide a fundamental diagnostic of object shape, some researchers have initiated work on linear contour feature representations for object detection and localisation. However, linear contour feature-based localisation is highly dependent on the performance of linear contour detection within natural images, and this can be perturbed significantly by a cluttered background. In addition, the conventional approach to achieving rotation-invariant features is to rotate the feature receptive field to align with the local dominant orientation before computing the feature representation. Grid resampling after rotation adds extra computational cost and increases the total time consumption for computing the feature descriptor. Though it is not an expensive process if using current computers, it is appreciated that if each step of the implementation is faster to compute especially when the number of local features is increasing and the application is implemented on resource limited ”smart devices”, such as mobile phones, in real-time. Motivated by the above issues, a 2D object localisation system is proposed in this thesis that matches features of edge contour points, which is an alternative method that takes advantage of the shape information for object localisation. This is inspired by edge contour points comprising the basic components of shape contours. In addition, edge point detection is usually simpler to achieve than linear edge contour detection. Therefore, the proposed localization system could avoid the need for linear contour detection and reduce the pathological disruption from the image background. Moreover, since natural images usually comprise many more edge contour points than interest points (i.e. corner points), we also propose new methods to generate rotation-invariant local feature descriptors without pre-rotating the feature receptive field to improve the computational efficiency of the whole system. In detail, the 2D object localisation system is achieved by matching edge contour points features in a constrained search area based on the initial pose-estimate produced by a prior object detection process. The local feature descriptor obtains rotation invariance by making use of rotational symmetry of the hexagonal structure. Therefore, a set of local feature descriptors is proposed based on the hierarchically hexagonal grouping structure. Ultimately, the 2D object localisation system achieves a very promising performance based on matching the proposed features of edge contour points with the mean correct labelling rate of the edge contour points 0.8654 and the mean false labelling rate 0.0314 applied on the data from Amsterdam Library of Object Images (ALOI). Furthermore, the proposed descriptors are evaluated by comparing to the state-of-the-art descriptors and achieve competitive performances in terms of pose estimate with around half-pixel pose error.

Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging

This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.