Scholarlink

<p>The decline of the endemic Patagonian bumblebee (<i>Bombus dahlbomii</i>) as a result of invasive species and habitat loss, among other stressors, has raised significant conservation concerns for the species and the ecosystem it inhabits. In order to monitor this endangered species, traditional methods are limited by labor-intensive visual surveys or lethal sampling methods. We applied passive acoustic monitoring (PAM) as a non-invasive alternative to conventional monitoring techniques to collect a comprehensive dataset of the soundscape of Puerto Blest, Argentina, focusing on bumblebee bioacoustics and environmental variables. Our dataset, collected using custom stereo acoustic recorders, includes audio, temperature, humidity, and gas concentration data from twelve locations over six days, covering different weather conditions. Annotations marking native and invasive bee segments provide insights into the ecology of <i>B. dahlbomii</i> and its interactions with invasive species, <i>Bombus terrestris</i>. This dataset facilitates the development of machine learning models for monitoring <i>Bombus</i> populations, crucial for conservation efforts. Additionally, our robust data annotation techniques enhance the dataset’s reliability for future modeling work.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

High-Res Acoustic and Environmental Data to Monitor Bombus dahlbomii Amid Invasive Species, Habitat Loss

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月1日

查看全文
  • Patrick Chwalek,
  • Marie Kuronaga,
  • Isamar Zhu,
  • Sophia Montague,
  • Victoria Campopiano Robinson,
  • Josefina Lohrmann,
  • Cristian Alfonso Villagra Gil,
  • David Susič,
  • Anton Gradišek,
  • Johannes Schul,
  • Joseph A. Paradiso,
  • Marina Arbetman

摘要

The decline of the endemic Patagonian bumblebee (Bombus dahlbomii) as a result of invasive species and habitat loss, among other stressors, has raised significant conservation concerns for the species and the ecosystem it inhabits. In order to monitor this endangered species, traditional methods are limited by labor-intensive visual surveys or lethal sampling methods. We applied passive acoustic monitoring (PAM) as a non-invasive alternative to conventional monitoring techniques to collect a comprehensive dataset of the soundscape of Puerto Blest, Argentina, focusing on bumblebee bioacoustics and environmental variables. Our dataset, collected using custom stereo acoustic recorders, includes audio, temperature, humidity, and gas concentration data from twelve locations over six days, covering different weather conditions. Annotations marking native and invasive bee segments provide insights into the ecology of B. dahlbomii and its interactions with invasive species, Bombus terrestris. This dataset facilitates the development of machine learning models for monitoring Bombus populations, crucial for conservation efforts. Additionally, our robust data annotation techniques enhance the dataset’s reliability for future modeling work.