Assessing ecosystem resilience through the use of ecoacoustics

热带雨林是全球重要的生态系统，对全球生物多样性、全球碳预算和全球生计产生重大影响。对于热带雨林生态系统来说，理想的——也可以说是必不可少的——状态是稳定、有弹性和可持续的，但是在现实世界的生态系统中，没有方法可以明确地量化这些概念。然而，也有一些概念，如临界减速（Clements和Ozgul， 2018），已经在实验室系统中得到了证明（Dai等人，2012，Drake和Griffen， 2010）。如果能够检测到这些实验室微观研究中记录的指标的野外生态系统类似物，就有机会开发一个强大的早期预警系统，能够近乎实时地检测生态系统恢复能力的丧失。生态声学——环境的声音——可能是最好的选择。声学融合了生态系统中所有物种的所有噪音，我们已经证明了它能够量化生态系统属性，包括栖息地质量和生物多样性（Sethi等人，2020）。在本项目中，您将扩展这项工作，以检查与临界减速相关的时间信号的声学数据（Dai et al., 2012）：声学信号波动的大小和持续时间的增加。论文将由两个部分组成。首先，您将收集和分析在马来西亚沙巴的原始森林到油棕种植园栖息地梯度中收集的长期连续声学记录的时间变化。其次，您将开发和实施新的现场实验，引入声学干扰，以研究跨越栖息地梯度到标准化干扰的声学变化，以期通过实验量化生态系统的恢复能力。对于这两个研究组件，声学监测将使用我们实验室开发的设备进行（Sethi, 2018），该设备将通过添加多麦克风阵列进一步扩展。3D声音分析和定位技术（例如波束成形—Van Veen， 1988）将在时间/频域中使用，以确定录制的音景的各种元素的指向性和扩散（Pulkki, 2007）。然后，这些信息将与其他声学数据结合起来，促进时间变异性的测量和生态系统恢复力的量化。此外，3D音频记录将允许通过扬声器阵列在实验室中重新创建原始环境的声场，并在受控和可复制的环境中使用这些声场进行进一步的声场分析。

Tropical rainforests are globally important ecosystems that exert strong influence on global biodiversity, global carbon budgets and global livelihoods. The desirable - and arguably essential - state for a tropical rainforest ecosystem is one that is stable, resilient and sustainable, but there are no methods available to unambiguously quantify these concepts in real-world ecosystems. There are, however, concepts such as critical slowing down (Clements and Ozgul, 2018) that have been demonstrated in laboratory systems (Dai et al., 2012, Drake and Griffen, 2010). Should it be feasible to detect field ecosystem analogues of the metrics recorded in these laboratory, microcosm studies, there is opportunity to develop a robust, early warning system capable of detecting the loss of ecosystem resilience in near real-time.EcoAcoustics - the sound of the environment - is probably the best available option to do this. Acoustics amalgamates all of the noise from all of the species within an ecosystem, and we have demonstrated its ability to quantify ecosystem properties including habitat quality and biodiversity (Sethi et al., 2020). In this project, you will extend this work to examine acoustic data for the temporal signals associated with critical slowing down (Dai et al., 2012): an increase in the size and duration of fluctuations in the acoustic signal. The thesis will have two components. First, you will collect and analyse temporal variability in long-term, continuous acoustic records collected across a primary forest to oil palm plantation habitat gradient in Sabah, Malaysia. Second, you will develop and implement novel field experiments that introduce acoustic disturbances to investigate acoustic variation across a habitat gradient to a standardised disturbance, with a view to experimentally quantifying ecosystem resilience. For both research components, acoustic monitoring will be carried out using devices developed in our lab (Sethi, 2018), which will be further extended by adding multi-microphone arrays. 3D sound analysis and localisation techniques (e.g. beamforming - Van Veen, 1988) will be employed in the time/frequency domain in order to determine the directivity and diffuseness of the various elements of the recorded soundscape (Pulkki, 2007). This information will then be integrated with the other acoustic data and facilitate the measurement of the temporal variability and the quantification of ecosystem resilience. Furthermore, the 3D audio recording will allow to re-create the acoustic field of the original environment in the lab through loudspeaker arrays, and to use these for further soundfield analyses in a controlled and replicable environment.