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自动回声定位分类器在美国东北部蝙蝠物种的准确性各不相同

Donald I Solick^1,2, Bradley H Hopp¹, John Chenger³

¹Electric Power Research Institute, Palo Alto, California, United States of America.

|June 3, 2024

概括

像SonoBat和Kaleidoscope Pro这样的自动蝙蝠呼叫识别软件在排除物种方面表现出很高的准确性,但在确认它们的存在方面存在困难,特别是在Myotis蝙蝠. 专家验证对于保护决策至关重要.

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.
保护生物学保护生物学

背景情况:

声学调查对于监测受威胁和危蝙蝠种群至关重要.
自动蝙蝠呼叫分类软件 (BCID,KPro,SonoBat) 在美国东北部越来越多地使用.
缺乏对这些软件程序准确性的独立评估.

研究的目的:

独立评估BCID,KPro和SonoBat在分类蝙蝠回声定位呼叫到物种中的准确性.
使用诸如正预测值 (PPV),负预测值 (NPV),灵敏度 (SN) 和特异性 (SP) 等指标来评估性能.

主要方法:

利用来自美国东北部9种蝙蝠物种的1500个全频谱参考呼叫.
使用已建立的统计措施测试了BCID,KPro和SonoBat的准确性.
对比了三个自动分类程序的性能.

主要成果:

BCID的准确性较低,可能是因为它依赖于零交叉数据.
索诺巴特和KPro呈现出高的NPV和SP,有效地减少了假阳性.
索诺巴特和KPro的PPV和SN都较低,表明假阴性结果的趋势,特别是在Myotis物种.
索诺巴特和KPro在区分Myotis和非Myotis物种方面表现更好.

结论:

虽然SonoBat和KPro擅长排除物种,但它们在确认物种存在方面的准确性是有限的,特别是在Myotis蝙蝠.
在典型的现场条件下,自动分类的准确性可能较低.
对自动分类蝙蝠呼叫的专家审查对于在保护和监管环境中可靠的物种识别至关重要.

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相关概念视频

Echo

Echo

The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...