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.

Integrated visual perception architecture for robotic clothes perception and manipulation

This thesis proposes a generic visual perception architecture for robotic clothes perception and manipulation. This proposed architecture is fully integrated with a stereo vision system and a dual-arm robot and is able to perform a number of autonomous laundering tasks. Clothes perception and manipulation is a novel research topic in robotics and has experienced rapid development in recent years. Compared to the task of perceiving and manipulating rigid objects, clothes perception and manipulation poses a greater challenge. This can be attributed to two reasons: firstly, deformable clothing requires precise (high-acuity) visual perception and dexterous manipulation; secondly, as clothing approximates a non-rigid 2-manifold in 3-space, that can adopt a quasi-infinite configuration space, the potential variability in the appearance of clothing items makes them difficult to understand, identify uniquely, and interact with by machine. From an applications perspective, and as part of EU CloPeMa project, the integrated visual perception architecture refines a pre-existing clothing manipulation pipeline by completing pre-wash clothes (category) sorting (using single-shot or interactive perception for garment categorisation and manipulation) and post-wash dual-arm flattening. To the best of the author’s knowledge, as investigated in this thesis, the autonomous clothing perception and manipulation solutions presented here were first proposed and reported by the author. All of the reported robot demonstrations in this work follow a perception-manipulation method- ology where visual and tactile feedback (in the form of surface wrinkledness captured by the high accuracy depth sensor i.e. CloPeMa stereo head or the predictive confidence modelled by Gaussian Processing) serve as the halting criteria in the flattening and sorting tasks, respectively. From scientific perspective, the proposed visual perception architecture addresses the above challenges by parsing and grouping 3D clothing configurations hierarchically from low-level curvatures, through mid-level surface shape representations (providing topological descriptions and 3D texture representations), to high-level semantic structures and statistical descriptions. A range of visual features such as Shape Index, Surface Topologies Analysis and Local Binary Patterns have been adapted within this work to parse clothing surfaces and textures and several novel features have been devised, including B-Spline Patches with Locality-Constrained Linear coding, and Topology Spatial Distance to describe and quantify generic landmarks (wrinkles and folds). The essence of this proposed architecture comprises 3D generic surface parsing and interpretation, which is critical to underpinning a number of laundering tasks and has the potential to be extended to other rigid and non-rigid object perception and manipulation tasks. The experimental results presented in this thesis demonstrate that: firstly, the proposed grasp- ing approach achieves on-average 84.7% accuracy; secondly, the proposed flattening approach is able to flatten towels, t-shirts and pants (shorts) within 9 iterations on-average; thirdly, the proposed clothes recognition pipeline can recognise clothes categories from highly wrinkled configurations and advances the state-of-the-art by 36% in terms of classification accuracy, achieving an 83.2% true-positive classification rate when discriminating between five categories of clothes; finally the Gaussian Process based interactive perception approach exhibits a substantial improvement over single-shot perception. Accordingly, this thesis has advanced the state-of-the-art of robot clothes perception and manipulation.