Data from: A bioacoustic record of a conservancy in the Mount Kenya ecosystem

Environmental degradation is a major threat facing ecosystems around the world. In order to determine ecosystems in need of conservation interventions, we must monitor the biodiversity of these ecosystems effectively. Bioacoustic approaches offer a means to monitor ecosystems of interest in a sustainable manner. In this work we show how a bioacoustic record from the Dedan Kimathi University wildlife conservancy, a conservancy in the Mount Kenya ecosystem, was obtained in a cost effective manner. A subset of the dataset was annotated with the identities of bird species present since they serve as useful indicator species. These data reveal the spatial distribution of species within the conservancy and also point to the effects of major highways on bird populations. This dataset will provide data to train automatic species recognition systems for birds found within the Mount Kenya ecosystem. Such systems are necessary if bioacoustic approaches are to be employed at the large scales necessary to influence wildlife conservation measures.

生态系统退化是全球范围内各类生态系统面临的主要威胁。为识别亟需开展保护干预的生态系统，我们需对其生物多样性开展高效监测。生物声学（bioacoustic）监测方法可为可持续监测目标生态系统提供可行途径。本研究展示了如何以低成本方式获取肯尼亚山（Mount Kenya）生态系统内的德丹·基马蒂大学（Dedan Kimathi University）野生动物保护区的生物声学记录。鉴于鸟类是有效的指示物种（indicator species），本数据集的部分子集已完成对其中出现的鸟类物种身份的标注。这些数据不仅揭示了该保护区内物种的空间分布特征，同时也印证了大型公路对鸟类种群的影响。本数据集可为训练针对肯尼亚山生态系统内鸟类的自动物种识别系统提供数据支撑。若要在能够影响野生动物保护措施制定的必要大规模范围内应用生物声学监测方法，这类自动识别系统则不可或缺。