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Sound-mapping a coniferous forest—Perspectives for biodiversity monitoring and noise mitigation

Turner, Anthony, Fischer, Michael D., Tzanopoulos, Joseph (2018) Sound-mapping a coniferous forest—Perspectives for biodiversity monitoring and noise mitigation. PLoS ONE, 13 (1). ISSN 1932-6203. (doi:10.1371/journal.pone.0189843)

Abstract

Acoustic diversity indices have been proposed as low-cost biodiversity monitoring tools. The acoustic diversity of a soundscape can be indicative of the richness of an acoustic community and the structural/vegetation characteristics of a habitat. There is a need to apply these methods to landscapes that are ecologically and/or economically important. We investigate the relationship between the acoustic properties of a coniferous forest with stand-age and structure. We sampled a 73 point grid in part of the UK’s largest man-made lowland coniferous plantation forest, covering a 320ha mosaic of different aged stands. Forest stands ranged from 0–85 years old providing an age-gradient. Short soundscape recordings were collected from each grid point on multiple mornings (between 6am-11am) to capture the dawn chorus. We repeated the study during July/August in 2014 and again in 2015. Five acoustic indices were calculated for a total of 889 two minute samples. Moderate relationships between acoustic diversity with forest stand-age and vegetation characteristics (canopy height; canopy cover) were observed. Ordinations suggest that as structural complexity and forest age increases, the higher frequency bands (4-10KHz) become more represented in the soundscape. A strong linear relationship was observed between distance to the nearest road and the ratio of anthropogenic noise to biological sounds within the soundscape. Similar acoustic patterns were observed in both years, though acoustic diversity was generally lower in 2014, which was likely due to differences in wind conditions between years. Our results suggest that developing these relatively low-cost acoustic monitoring methods to inform adaptive management of production landscapes, may lead to improved biodiversity monitoring. The methods may also prove useful for modelling road noise, landscape planning and noise mitigation.

Item Type: Article
DOI/Identification number: 10.1371/journal.pone.0189843
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QH Natural history > QH541 Ecology
Q Science > QH Natural history > QH75 Conservation (Biology)
Divisions: Faculties > Social Sciences > School of Anthropology and Conservation
Depositing User: Joseph Tzanopoulos
Date Deposited: 29 Jan 2018 21:34 UTC
Last Modified: 29 May 2019 20:12 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/65814 (The current URI for this page, for reference purposes)
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