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acousticindicespredictbirdcommunityrecovery

https://github.com/kami2012/acousticindicespredictbirdcommunityrecovery

Science Score: 49.0%

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Basic Info
  • Host: GitHub
  • Owner: kami2012
  • Language: R
  • Default Branch: incidences-as-input
  • Size: 155 MB
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Created over 1 year ago · Last pushed 7 months ago
Metadata Files
Readme Citation

README.md

Predicting Bird Community Recovery with Acoustic Indices

This repository contains the data and scripts for the manuscript:
"Acoustic indices predict taxonomic, functional, and phylogenetic recovery of bird communities in tropical forest restoration."

Manuscript Summary

Quantifying ecosystem restoration success is a priority of the UN Decade on Ecosystem Restoration.
In this study, we tested whether acoustic indices can effectively predict bird community recovery in abandoned agricultural areas within a biodiversity hotspot in Ecuador.

Using extensive sound recordings from lowland tropical forests, we:

  • Identified 334 bird species through expert annotation and AI-based recognition.
  • Calculated standard acoustic indices from the recordings.
  • Analyzed community composition using Hill numbers and accounting for incomplete sampling.
  • Evaluated predictions of taxonomic, functional, and phylogenetic diversity based on acoustic indices.

Key Findings

  • Acoustic indices predicted validated species data with R values between 0.59 and 0.76.
  • Taxonomic recovery was best predicted for common and dominant species.
  • Functional and phylogenetic recovery was best predicted for both rare and common species.
  • A small set of validated acoustic indices can serve as an efficient tool to monitor large-scale tropical restoration, including recovery of functionally rare bird species.

DOI

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  • Login: kami2012
  • Kind: user

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