The assessment and development of methods in (spatial) sound ecology

As vital ecosystems across the globe enter unchartered pressure from climate change industrial land use, understanding the processes driving ecosystem viability has never been more critical. Nuanced ecosystem understanding comes from well-collected field data and a wealth of associated interpretations. In recent years the most popular methods of ecosystem monitoring have revolutionised from often damaging and labour-intensive manual data collection to automated methods of data collection and analysis. Sound ecology describes the school of research that uses information transmitted through sound to infer properties about an area's species, biodiversity, and health. In this thesis, we explore and develop state-of-the-art automated monitoring with sound, specifically relating to data storage practice and spatial acoustic recording and data analysis. In the first chapter, we explore the necessity and methods of ecosystem monitoring, focusing on acoustic monitoring, later exploring how and why sound is recorded and the current state-of-the-art in acoustic monitoring. Chapter one concludes with us setting out the aims and overall content of the following chapters. We begin the second chapter by exploring methods used to mitigate data storage expense, a widespread issue as automated methods quickly amass vast amounts of data which can be expensive and impractical to manage. Importantly I explain how these data management practices are often used without known consequence, something I then address. Specifically, I present evidence that the most used data reduction methods (namely compression and temporal subsetting) have a surprisingly small impact on the information content of recorded sound compared to the method of analysis. This work also adds to the increasing evidence that deep learning-based methods of environmental sound quantification are more powerful and robust to experimental variation than more traditional acoustic indices. In the latter chapters, I focus on using multichannel acoustic recording for sound-source localisation. Knowing where a sound originated has a range of ecological uses, including counting individuals, locating threats, and monitoring habitat use. While an exciting application of acoustic technology, spatial acoustics has had minimal uptake owing to the expense, impracticality and inaccessibility of equipment. In my third chapter, I introduce MAARU (Multichannel Acoustic Autonomous Recording Unit), a low-cost, easy-to-use and accessible solution to this problem. I explain the software and hardware necessary for spatial recording and show how MAARU can be used to localise the direction of a sound to within ±10˚ accurately. In the fourth chapter, I explore how MAARU devices deployed in the field can be used for enhanced ecosystem monitoring by spatially clustering individuals by calling directions for more accurate abundance approximations and crude species-specific habitat usage monitoring. Most literature on spatial acoustics cites the need for many accurately synced recording devices over an area. This chapter provides the first evidence of advances made with just one recorder. Finally, I conclude this thesis by restating my aims and discussing my success in achieving them. Specifically, in the thesis’ conclusion, I reiterate the contributions made to the field as a direct result of this work and outline some possible development avenues.Open Acces

Proceedings of the 10th International Conference on Ecological Informatics: translating ecological data into knowledge and decisions in a rapidly changing world: ICEI 2018

The Conference Proceedings are an impressive display of the current scope of Ecological Informatics. Whilst Data Management, Analysis, Synthesis and Forecasting have been lasting popular themes over the past nine biannual ICEI conferences, ICEI 2018 addresses distinctively novel developments in Data Acquisition enabled by cutting edge in situ and remote sensing technology. The here presented ICEI 2018 abstracts captures well current trends and challenges of Ecological Informatics towards: • regional, continental and global sharing of ecological data, • thorough integration of complementing monitoring technologies including DNA-barcoding, • sophisticated pattern recognition by deep learning, • advanced exploration of valuable information in ‘big data’ by means of machine learning and process modelling, • decision-informing solutions for biodiversity conservation and sustainable ecosystem management in light of global changes

Proceedings of the 10th International Conference on Ecological Informatics: translating ecological data into knowledge and decisions in a rapidly changing world: ICEI 2018

The Conference Proceedings are an impressive display of the current scope of Ecological Informatics. Whilst Data Management, Analysis, Synthesis and Forecasting have been lasting popular themes over the past nine biannual ICEI conferences, ICEI 2018 addresses distinctively novel developments in Data Acquisition enabled by cutting edge in situ and remote sensing technology. The here presented ICEI 2018 abstracts captures well current trends and challenges of Ecological Informatics towards: • regional, continental and global sharing of ecological data, • thorough integration of complementing monitoring technologies including DNA-barcoding, • sophisticated pattern recognition by deep learning, • advanced exploration of valuable information in ‘big data’ by means of machine learning and process modelling, • decision-informing solutions for biodiversity conservation and sustainable ecosystem management in light of global changes

Good practice guidelines for long-term ecoacoustic monitoring in the UK: with a particular focus on terrestrial biodiversity at the human-audible frequency range

Passive acoustic monitoring has great potential as a cost-effective method for long-term biodiversity monitoring. However, to maximise its efficacy, standardisation of survey protocols is necessary to ensure data are comparable and permit reliable inferences. The aim of these guidelines is to outline a basic long-term acoustic monitoring protocol that can be adapted to suit a range of projects according to specific objectives and size

Good practice guidelines for long-term ecoacoustic monitoring in the UK

The popularity of ecoacoustics as an innovative environmental discipline has enjoyed immensegrowth within the last five years, to a point where it is now becoming difficult to keep up withall the new research papers published. What soon becomes apparent, however, is a lack ofconsensus on which recording and analysis protocols to follow; partly a result of the differingrequirements of each research project, but also an historical artefact of the tropical originsof much of this research. As more acoustic long-term monitoring schemes start to becomeestablished throughout the UK and neighbouring countries there arises a need to adopt a morecommon set of protocols, more akin to our temperate conditions, to allow for valid future analysisand comparison. To that end a group of ecoacoustic researchers and practitioners met in June2022 to discuss the formulation of such a set. This work was then taken forward by the authors togenerate the guidelines contained herein.Digital technologies now allow us the ability to record our acoustic environments widely, withrelative ease; and to subject the resulting recordings to an ever-expanding range of analyticalmethods. This opens up the potential to create new approaches to gauging biodiversity andassessing the changing fortunes of species and their habitats. To maximise these benefits itis vitally important that we secure now, and into the future, data which will illustrate baselineassessments and highlight change. These guidelines therefore provide welcome instruction andconformity, particularly for those new to ecoacoustics. Please use them, as appropriate, to helpguide your own contributions to the growing awareness, and use, of sound as an environmentalmetric within the UK and Europe