From landscape to soundscape: what drives spatial variation in natural soundscape characteristics?

自然声景是地方独特性的基本属性，也是与自然接触并从自然中获得健康和福祉的关键途径。更复杂的声景可以改善人们对自然的体验，增加人们对自然环境的重视。在温带系统中，鸟类在定义声景特征方面起着主导作用，其声学特性取决于发声物种的多样性和丰度。反过来，鸟类群落的组成基本上是由地理位置、栖息地可用性和景观配置等因素支撑的。自然音景正受到越来越大的威胁。土地利用变化、城市化和农业集约化正在推动鸟类群落组成的变化，可能对人类健康和福祉产生广泛而深刻的有害影响。尽管人们越来越认识到保护自然声景观的重要性，但景观和声景观之间的机制联系，以及自然声景观时空变化的主要驱动因素，在很大程度上仍然未知。解决这一知识差距对于保护和恢复自然声景以及保护它们所支持的健康和福祉至关重要。PI Butler最近开发了一种分析管道，将鸟类组合数据与单个物种的记录相结合，以在大的时间和空间尺度上重建音景（Morrison et al . 2021）。在这个项目中，学生将把这种方法应用到BTO的繁殖鸟类调查（BBS）数据（1994-2022）中，重建和绘制全英国自然声景观的声学特性。年度计数数据将与Xeno-Canto （www.xeno-canto.org）的声音文件相结合，为每个BBS广场构建栖息地和年份特定的声音景观，首次详细研究人类体验这些声音景观的尺度上的声音景观变化。综合声学指数将用于量化人造声景观的特性，并确定自然声景观特征与景观组成/配置之间的关系，量化生境可用性和多样性、农业强度、人类基础设施（交通、建筑等）、海拔、经度和纬度等因素的影响，并建立预测框架。该方法还将应用于英国2007-11年鸟类地图集夏季和冬季调查期间收集的数据，以构建英国每10平方公里的季节性声景，并量化不同季节声景特征的年内变化和空间一致性。声生态学是一个快速发展的科学研究领域，具有很大的潜力，可以进一步了解声音环境的基本生态知识，并加深我们对人类与野生动物之间的经验及其所带来的好处的理解。学生将领导这个项目，并将有机会根据他们特别感兴趣的领域量身定制项目的各个方面。他们将在高级数据处理和分析方面发展强大的技能，并将通过在国内和国际会议上展示结果获得经验。

Natural soundscapes are a fundamental property of the distinctiveness of place and a key pathway for engaging with, and deriving health and well-being benefits from, nature. More complex soundscapes can improve people's experience of nature and increase the value placed on natural environments. In temperate systems, birds play a dominant role in defining soundscape characteristics, with their acoustic properties determined by the diversity and abundance of vocalising species. In turn, avian community composition is fundamentally underpinned by factors such as location, habitat availability, and landscape configuration. Natural soundscapes are under growing threat. Land-use change, urbanisation and agricultural intensification are driving changes in avian community composition, with potentially widespread and profound detrimental implications for human health and well-being. Whilst the importance of conserving natural soundscapes is increasingly recognised, the mechanistic links between landscape and soundscape, and therefore the principal drivers of spatial and temporal variation in natural soundscapes, remain largely unknown. Addressing this knowledge gap is critical to preserving and restoring natural soundscapes and protecting the health and well-being benefits they support.PI Butler has recently developed an analytical pipeline that combines avian assemblage data with recordings of individual species to reconstruct soundscapes over large temporal and spatial scales (Morrison et al 2021). In this project, the student will apply this approach to BTO's Breeding Bird Survey (BBS) data (1994-2022) to reconstruct and map the acoustic properties of natural soundscapes across the UK. Annual count data will be combined with sound files from Xeno-Canto (www.xeno-canto.org) to construct habitat- and year-specific soundscapes for each BBS square, providing the first detailed study of soundscape variation at the scale humans experience these soundscapes. An ensemble of acoustic indices will be used to quantify the properties of constructed soundscapes and to determine the relationship between natural soundscape characteristics and landscape composition/configuration, quantifying the influence of e.g. habitat availability and diversity, agricultural intensity, human infrastructure (transport, buildings etc), elevation, longitude, and latitude and building a predictive framework. This approach will also be applied to data collected during summer and winter surveys for the UK 2007-11 Bird Atlas to construct seasonal soundscapes for every 10-km square across the UK and quantify intra-annual variation and spatial consistency in soundscape characteristics across seasons. Acoustic ecology is a rapidly developing field of scientific study with great potential to further fundamental ecological knowledge about the sonic environment, as well as deepen our understanding of human-wildlife experiences and the benefits they convey. The student will lead this project and will have the opportunity to tailor aspects of the project towards areas they are specifically interested in. They will develop strong skills in advanced data handling and analysis and will gain experience by presenting results at national and international conferences.