Automated acoustic detection of Geoffroy's spider monkey highlights tipping points of human disturbance

Jenna Lawson, George Rizos, Dui Jasinghe, Andrew Whitworth, Björn Schuller, Cristina Banks-Leite

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

As more land is altered by human activity and more species become at risk of extinction, it is essential that we understand the requirements for conserving threatened species across human-modified landscapes. Owing to their rarity and often sparse distributions, threatened species can be difficult to study and efficient methods to sample them across wide temporal and spatial scales have been lacking. Passive acoustic monitoring (PAM) is increasingly recognized as an efficient method for collecting data on vocal species; however, the development of automated species detectors required to analyse large amounts of acoustic data is not keeping pace. Here, we collected 35 805 h of acoustic data across 341 sites in a region over 1000 km 2 to show that PAM, together with a newly developed automated detector, is able to successfully detect the endangered Geoffroy's spider monkey (Ateles geoffroyi), allowing us to show that Geoffroy's spider monkey was absent below a threshold of 80% forest cover and within 1 km of primary paved roads and occurred equally in old growth and secondary forests. We discuss how this methodology circumvents many of the existing issues in traditional sampling methods and can be highly successful in the study of vocally rare or threatened species. Our results provide tools and knowledge for setting targets and developing conservation strategies for the protection of Geoffroy's spider monkey.

Original languageEnglish
Article number20222473
JournalProceedings of the Royal Society B: Biological Sciences
Volume290
Issue number1995
DOIs
StatePublished - 29 Mar 2023
Externally publishedYes

Keywords

  • automated species detector
  • bioacoustics
  • passive acoustic monitoring
  • primate
  • threatened species
  • tipping points

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