Abstract

BackgroundEnvironmental 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.New informationWe provide acoustic recordings from the Dedan Kimathi University wildlife conservancy, a conservancy in the Mount Kenya ecosystem, obtained using a low cost acoustic recorder. A total of 2701 minute long recordings are provided including both daytime and nighttime recordings. We present an annotation of a subset of the daytime recordings indicating the bird species present in the recordings. The dataset contains recordings of at least 36 bird species. In addition, the presence of a few nocturnal species within the conservancy is also confirmed.

Highlights

  • With increasing demands on natural resources, there is a growing need to ensure that the exploitation of these resources is environmentally sustainable

  • From the results obtained in this work, we see that acoustic indices of biodiversity computed from audio recordings collected in ecosystems of interest are correlated to the number of bird species recorded during point counts

  • This paper has demonstrated the use of acoustic recordings obtained using low cost electronic components in biodiversity monitoring and bird species identification

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Summary

Introduction

With increasing demands on natural resources, there is a growing need to ensure that the exploitation of these resources is environmentally sustainable. Traditional methods of biodiversity assessment involve survey of plant and animal species in habitats of interest by trained experts [1]. These methods are costly and time consuming and cannot be applied on the scale necessary to monitor all ecosystems of interest. Techniques such as rapid biodiversity assessment (RBA) aim to reduce the amount of effort required to survey an area by focusing on a few indicator species that serve to gauge the health of a particular ecosystem [2]. RBA still requires trained experts who can identify members of the indicator species and is difficult to scale

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