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沿海林地声音景观动态的波形分析:伯纳特-蒂西诺河公园
Roberto Benocci1, Giorgia Guagliumi1, Andrea Potenza1
1Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
通过新的能源指标可以改进被动声学监测 (PAM). 这种方法增强了用于生态研究和在杂环境中评估息地质量的声音景观分析.
科学领域:
- 生态生态学 生态生态学
- 生物声学是一种生物声学.
- 环境科学 环境科学
背景情况:
- 被动声学监测 (PAM) 对于生态研究至关重要.
- 由于噪音和方法,现有的生态声学指数往往产生不一致的生物多样性相关性.
研究的目的:
- 引入一种新的,物理上可解释的方法,使用能量衍生度量来补充现有的PAM方法.
- 在复杂的,杂的环境中评估音景特征和息地质量.
主要方法:
- 使用1秒相当的连续声音压力水平 (Leq1s),峰值间隔统计,最大重叠离散波形变换 (MODWT) 和时间碎片分析分析音频录音的分析.
- 多分辨率分析,以跨频率跟踪声能和时间结构.
- 来自高速公路附近的三个地点的数据与专家注释的数据比较.
主要成果:
- 确定了特定位置的声学差异,最遥远的位置显示出更高的高频能量和更长的时间持久性,表明更丰富的生物声活动.
- 靠近高速公路的地点呈现出更平坦的光谱形状和更快的自相对应衰变.
- 观察到调节模式和频率/位置依赖的声学记忆.
结论:
- 整合Leq1s,峰值指标和波形分解,为声音景观的特征提供了一个强大的框架.
- 这种方法显示出有效的长期生态声学监测和息地质量评估的巨大潜力,特别是在具有挑战性的环境中.
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