4.7 Article

Mapping ecoacoustic hot spots and moments of biodiversity to inform conservation and urban planning

Journal

ECOLOGICAL INDICATORS
Volume 126, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2021.107627

Keywords

Ecoacoustics; Acoustic complexity index; Spatial interpolation; Biodiversity; Conservation planning; Urbanisation

Funding

  1. Queensland University of Technology

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As urbanisation rates continue to rise, habitat destruction in peri-urban areas has led to significant environmental impacts, emphasizing the need for effective monitoring of biodiversity and ecosystem health using acoustic recording. By mapping biodiversity patterns in space and time with ecoacoustic monitoring, hot spots and hot moments of biodiversity activity can be identified, supporting informed conservation decision-making and ecological urban design in future urban planning frameworks.
As the rate of urbanisation continues to increase, widespread habitat clearing within peri-urban landscapes contributes to significant environmental impacts, including loss of biological diversity. Acoustic recording has recently been identified as an effective tool for monitoring biodiversity and ecosystem health. With increasing pressure from urbanisation, it is critical that spatial and temporal variability in biodiversity is mapped across future development sites to enable sound decision-making and to deliver ecological urban design outcomes. This study used ecoacoustic monitoring to map biodiversity patterns in space and time to identify hot spots and hot moments of biodiversity activity across a peri-urban landscape in south-east Queensland, Australia. In this study, a hot spot represents an increase in acoustic activity at a given spatial location, whereas hot moments represent an increase in acoustic activity at a given time point. An acoustic index (Acoustic Complexity Index, ACI) was used as a proxy for biodiversity and visualised through spatial interpolation. The acoustic data were statistically modelled using Boosted Regression Trees (BRT). This approach enabled predictors related to acoustic complexity to be identified, including vegetation and landform. Results of this study have shown that ecoacoustic data can be used to map hot spots and hot moments of biodiversity and support more informed conservation decision-making in future urban planning frameworks, to avoid or mitigate negative impacts on biodiversity.

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