Ultrasonic monitoring to assess the impacts of forest conversion on Solomon Island bats
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Paleotropical islands are experiencing extensive land-use change, yet little is known about how such changes are impacting wildlife in these biodiversity hotspots. To address this knowledge gap, we characterized bat responses to forest conversion in a biodiverse, human-threatened coastal rainforest habitat on Makira, Solomon Islands. We analysed ~200hrs of acoustic recordings from echolocating bats in the four dominant types of land-use on Makira: intact forest, secondary forest, food gardens and cacao plantations. Bat calls were identified to the species level using a supervised classification model (where labelled data are used to train the system). We examined relative activity levels and morphological traits across habitats. Relative activity levels were highest in intermediately disturbed habitats and lowest in the most heavily disturbed habitat, although these differences were not significant. There were significant differences in the mean forearm length of bat assemblages across habitats, with the highest mean forearm length found in the most open habitat (Cacao). Overall, our study constitutes the first detailed exploration of anthropogenic effects on mammalian diversity in the Solomon Islands and includes the first acoustic and morphological information for many bat species in Melanesia. We use our experience to discuss the challenges of acoustic monitoring in such a remote and poorly studied region.
Davies , T E , Ruzicka , F , Lavery , T , Walters , C L & Pettorelli , N 2016 , ' Ultrasonic monitoring to assess the impacts of forest conversion on Solomon Island bats ' Remote Sensing in Ecology and Conservation , vol. 2 , no. 2 , pp. 107-118 . https://doi.org/10.1002/rse2.19
Remote Sensing in Ecology and Conservation
© 2016 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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