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。热带雨林生态系统的理想状态--也可以说是基本状态--是稳定、有弹性和可持续的状态，但没有方法可以在现实世界的生态系统中明确量化这些概念。然而，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证明（Dai等人，2012，Drake和格里芬，2010）。如果能够检测到这些实验室和微观研究中记录的指标的实地生态系统类似物，就有机会开发一个强大的预警系统，能够近实时地检测生态系统恢复力的丧失。生态声学-环境的声音-可能是最好的选择。声学融合了来自生态系统内所有物种的所有噪声，并且我们已经证明了其量化生态系统特性（包括栖息地质量和生物多样性）的能力（Sethi等人，2020年）。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等人，2012年）：在声学信号的波动的大小和持续时间的增加。论文将由两部分组成。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，以调查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弹性。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），这将通过添加多麦克风阵列来进一步扩展。3D声音分析和定位技术（例如波束形成-货车Veen，1988）将在时域/频域中使用，以确定录制的声景的各种元素的方向性和扩散性（Pulkki，2007）。这些信息随后将与其他声学数据相结合，便于测量时间变异性和量化生态系统复原力。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，并将其用于受控和可复制环境中的进一步声场分析。

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.