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Evaluation of Acoustic Recording Devices to Survey Northern Bobwhite Populations
Wildlife Society Bulletin ( IF 0.9 ) Pub Date : 2020-02-06 , DOI: 10.1002/wsb.1061
Nathan G. Wilhite 1 , Paige E. Howell 1 , James A. Martin 2
Affiliation  

Reliable methods for monitoring wildlife populations are paramount to effective conservation and management. There are a variety of available techniques that vary in cost and feasibility. We field‐tested a commercially available acoustic recording device (ARD) in July and August of 2018 with the goal of standardizing the process of surveying northern bobwhite (Colinus virginianus) populations using acoustic data. We projected bobwhite covey calls from programmable speakers, and analyzed recordings manually and with automatic recognition software. We manually detected 48% of projected covey calls with the furthest detection at 241 m. We developed an automatic classifier using Kaleidoscope Pro (Wildlife Acoustics Inc.), which detected 31% of the manually detected covey calls. The automatic classifier was ineffective, so we used manual analysis to acquire measurements for call strength and background noise at each visible covey call spectrogram signature. Detection probability declined as distance from the ARD increased and background noise increased. However, in our study system, there was no effect of vegetation structure on detection probability. Our results provide a blueprint for evaluating ARDs for application to wildlife monitoring. We believe ARDs can be used to evaluate northern bobwhite occupancy at fine scales and may potentially be useful in estimating autumn densities for setting harvest regulations. We encourage the evaluation of other software recognition programs and the relationship between covey call detection and landscape structure. © 2020 The Wildlife Society.

中文翻译:

评估声记录设备以调查北部Bobwhite种群的评估

监测野生动植物种群的可靠方法对于有效的保护和管理至关重要。有多种可用的技术,其成本和可行性各不相同。我们于2018年7月和8月对市售的声波记录设备(ARD)进行了现场测试,目的是使北方垂头white(Colinus virginianus)使用声学数据进行填充。我们投影了来自可编程扬声器的bobwhite covey呼叫,并使用自动识别软件手动分析了录音。我们以241 m的最大距离手动检测了48%的预计柯维呼叫。我们使用Kaleidoscope Pro(Wildlife Acoustics Inc.)开发了自动分类器,该分类器检测到31%的手动检测到的柯维呼叫。自动分类器无效,因此我们使用手动分析来获取每个可见的柯维呼叫频谱图签名处的呼叫强度和背景噪声的测量值。随着与ARD的距离增加和背景噪声增加,检测概率下降。但是,在我们的研究系统中,植被结构对检测概率没有影响。我们的结果为评估可用于野生生物监测的ARD提供了一个蓝图。我们认为,ARDs可以用于以细微的比例评估北部的bobwhite的占有率,并且可能在估计秋季密度以制定收获法规方面可能有用。我们鼓励评估其他软件识别程序以及covey呼叫检测与景观结构之间的关系。©2020野生动物协会。
更新日期:2020-02-06
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