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A comparison of automated and traditional monitoring techniques for marbled murrelets using passive acoustic sensors

机译:使用无源声学传感器对大理石紫罗兰色自动和传统监视技术的比较

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Autonomous sensors and automated analysis have great potential to reduce cost and increase efficacy of wildlife monitoring. By increasing sampling effort, autonomous sensors are powerful at detecting rare and elusive species such as the marbled murrelet (Brachyramphus marmoratus). New approaches must be tested for comparability to existing methodologies, so we compared the results of inland audio–visual and of automated acoustic monitoring for marbled murrelets, conducted during the 2010 breeding season, at 7 sites in the Santa Cruz Mountains, California, USA. We found automated acoustic surveys and analysis had fewer detections per morning compared with audio-visual surveyors, but the rate of automated acoustic detections per morning was positively and strongly correlated with the rate of audio–visual detections per mornings (r=0.96, P<0.01). Furthermore, acoustic monitoring sampled 10 times more mornings per site (inline image=48) than were monitored by human surveyors (inline image=4.4) at a comparable cost. We used resampling to estimate the power to detect murrelet presence with acoustic sensors at >80% within 8 continuous days of recordings, even at low-activity sites. Our results suggest that autonomous sensor and automated analysis approaches could greatly increase the scale and efficacy of murrelet monitoring, allowing for more cost-effective surveying of large and remote areas of potential habitat, as well as, improved ability to measure changes in inland activity. Further study of passive acoustic recordings would be valuable to examine for acoustic signs of breeding phenology, and site occupancy, if acoustic surveys are to replace the utility of audio–visual surveys.
机译:自主传感器和自动分析在降低成本和提高野生动植物监测效率方面具有巨大潜力。通过增加采样工作量,自主传感器可以强大地检测稀有和难以捉摸的物种,例如大理石murrelet(Brachyramphus marmoratus)。必须测试新方法与现有方法的可比性,因此我们比较了2010年繁殖季节在美国加利福尼亚州圣克鲁斯山的7个地点进行的内陆视听和自动声学监测大理石marble的结果。我们发现,相比于视听调查员,自动声学调查和分析每天早上的侦听次数要少,但是每天早晨的自动声学检测率与每天早上的视听检测率均呈正相关且强烈相关(r = 0.96,P < 0.01)。此外,在每个站点进行的声波监测采样(内嵌图像= 48)比人类测量师(内嵌图像= 4.4)监测的早晨多10倍,而成本却相当。我们使用重采样来估计在连续录制的8天内,即使在低活跃度的位置,使用声传感器检测> 80%的紫红色的可能性。我们的研究结果表明,自主传感器和自动分析方法可以大大增加Murrelet监测的规模和效力,从而可以对潜在栖息地的大片和偏远地区进行更具成本效益的调查,并提高了测量内陆活动变化的能力。如果用声学勘测代替视听勘测的实用性,对无源声学记录的进一步研究将对检查繁殖物候学和场所占用的声学信号很有帮助。

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