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Automated Acoustic Biodiversity Assessment in Cities

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Automated Acoustic Biodiversity Assessment in Cities i Automated acoustic biodiversity assessment in cities Alison J. Fairbrass A thesis submitted in partial fulfilment of the requirements for the degree of: Engineering Doctorate in Urban Sustainability & Resilience University College London 2017 Primary supervisor: Dr. Helena Titheridge Secondary supervisor: Prof. Kate Jones Industry supervisor: Dr. Carol Williams ii iii Declaration I, Alison J. Fairbrass, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Alison J. Fairbrass 27th September 2017 iv Abstract In the last 40 years more than half of the world’s wildlife populations have disappeared while anthropogenic disturbance continues to push many species to extinction. Cities, which now support over half of the world’s human population, also support biodiversity. Yet the green infrastructure (GI) components of cities are not currently supporting high biodiversity, partly due to the resource-intensity of biodiversity assessment in urban environments. Ecoacoustics, which uses biotic sound as a proxy for biodiversity, could provide an improved way of assessing urban biodiversity, although the use of ecoacoustics in cities dominated by anthropogenic noise remains untested. Here, I demonstrate how ecoacoustics can be used to assess biodiversity in complex and highly disturbed urban environments. I set the scene by using a global terrestrial urban studies database to show that GI does not currently mitigate against biodiversity losses in cities. Then, using an annotated urban ecoacoustics dataset, CitySounds2017, generated from audio data I collected within and surrounding Greater London, UK, I show that several commonly used Acoustic Indices are unsuitable for use in cities without the prior removal of non-biotic sounds from audio data. Next, using CitySounds2017 I develop CityNet, a pair of machine learning algorithms for quantifying biotic and anthropogenic sound in urban audio data. Finally, I show that a strong correlation exists between acoustic and environmental measures in urban GI habitats in London. I anticipate the methods developed here to be a starting point for improved assessment of biodiversity that informs management to maximise the wildlife supported by cities. For example, CityNet could be integrated into urban sensing networks to facilitate large-scale biodiversity assessment. As anthropogenic disturbance increases globally, the need for methods of biodiversity assessment that are reliable in disturbed environments will only increase, and I see these methods as having the potential to support biodiversity assessment globally. v Impact Statement Ecoacoustics provides new methods for assessing biodiversity at scales not possible with traditional biodiversity assessment methods. However, the use of ecoacoustics to assess biodiversity in complex and acoustically disturbed cities is not well understood. This thesis showcases a new tool and knowledge for applying ecoacoustics for biodiversity assessment in the urban environment. The tool and knowledge developed in this thesis are of interest to a range of disciplines of academic research including biodiversity science, urban studies, acoustic engineering and computer science. The research has been presented to a wide audience from broad ecological conferences to specialised international ecoacoustic conferences. The work in this thesis has also been published in a leading international peer reviewed journal. Once published, the CityNet tool will be made available on open-source platforms so that it can be used by other scientists in other study systems. There is interest in this research from a range of industries responsible for the design and management of the built environment, including the construction industry, environmental consultancy, architecture and urban design, as well as public bodies including local and regional authorities, DEFRA, the Environment Agency, public health bodies, and the environmental NGO sector. The research has been presented to a wide practitioner audience through presentations at national industry conferences. Project stakeholders representing these industries, sectors and organisations have been consulted throughout the project and the research will be disseminated through this network. Immediate impact is likely to be limited to London and the UK, but when the CityNet tool is made freely available it is hoped that the impact will become international as the tool is tested in international study systems. vi Acknowledgements Firstly, and most importantly, to my dear Charlie. For having confidence in me always. To my parents, Valerie and Dennis, who have supported me in so many ways to pursue a career that I love, and to my family and friends with whom I definitely could not have done this without. To my supervisors Kate Jones, Helena Titheridge and Carol Williams who have been such great mentors. Your different skills and characters have complimented each other wonderfully as supervisors. Thank you for your overwhelming intelligence, patience and care throughout. I am very grateful to have had you to guide me through this journey. I would also like to thank Kelly Gunnell and Lisa Hundt for your supervision and roles in developing the research project. I am very grateful for the support of the Doctoral Training Centre of Urban Sustainability and Resilience (USAR), it has been a very enlightening experience working in such an interdisciplinary research centre. I am also very grateful to have been a part of the Centre for Biodiversity and Environment Research (CBER) which has been a very stimulating place to be a student. Jane Doogan and Chris Langridge have been immensely supportive throughout. To my fellow students in USAR and CBER, especially Patrick Cottam, Henry Ferguson-Gow, Roee Maor, Laura Nunes, and the Kate Jones lab group past and present. Life would have been a lot duller without you. I feel very fortunate to have been supported by the Bat Conservation Trust. It has been a pleasure to be part of this wonderful organisation that works so hard for the conservation of bats and has so much fun doing it! Thank you to Michael Firman and Peter Rennert for being so great to work with. It has been a lovely experience learning the ways of the computer scientist. I would like to thank Brian Cuthbertson immensely for supporting the data collection of the research. I am very grateful for your support throughout the project. I am also vii very grateful to Andy Lester, David Kirby and Craig Llewellyn for producing such excellent data. I would like to thank Martin Ballard and Peter Johnson for financially supporting the project. It has been very confidence-boosting to have your support. Also I would like to thank the wide range of industry experts who have intellectually supported the project. I would like to thank a number of interns who were a wonderful assistance in the data collection and audio analysis of the project including Charles Hearst, Verity Miles, Patrick Bell and Imogen Mansfield. Finding places to conduct biodiversity surveys in London with suspicious black boxes of audio recorders was a big challenge. I am very grateful to everyone that helped me access study sites including Brian Cuthbertson, Lee Evans, Austin Brown, Simon Bateman, Tony Chadwick, Jean Frame, Stuart Connop, Emma Allen, Brian Roberts, Nick Ketchell, Rosie Sotillo, Lizzie Goodwin, Sarah-Jane Durman, David Perkins, Susan Reid, Anna Konarska, Michael Smythe, Leyla Laksari, Tim Lund, Kate Allardyce, Sylvia Myers, Amanda Durham and Anna Rogers. viii Attribution I received valuable advice on my research direction from my supervisors Dr Helena Titheridge, Prof Kate Jones, and Dr Carol Williams, and earlier industry supervisors Kelly Gunnell and Lisa Hundt. Dr Tim Newbold assisted me with the statistical analysis and Dr Thomas Matthews assisted with the database development of Chapter 2. The work presented in Chapter 3 was conducted in collaboration with Peter Rennert and is now published in Ecological Indicators (Fairbrass et al. 2017, Appendix B). The text presented in Chapter 3 is almost completely reproduced from Fairbrass et al. (2017). I collected, annotated and analysed the data. Peter Rennert wrote the code that underlies the AudioTagger software which created the acoustic data for Chapters 3, 4 and 5. I led the writing of the manuscript with contributions from the co-authors. With Dr Michael Firman I co-developed the CityNet algorithms for Chapter 4 which were used to create the acoustic activity data for Chapter 5. In Chapter 4 Dr Michael Firman wrote the code that underlies the CityNet algorithms and conducted the precision-recall analysis. I conducted all other data generation, analysis and modelling. ix Table of Contents Declaration ............................................................................................................. iii Abstract ................................................................................................................... iv Impact Statement ...................................................................................................... v Acknowledgements ................................................................................................. vi Attribution ............................................................................................................ viii Table of Contents ...................................................................................................
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