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首页> 外文期刊>Journal of great lakes research >Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales
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Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales

机译：底栖视频图像分析有助于在空间范围内监控Dreissena种群

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摘要

In contrast to marine systems where remote sensing methods in studies of benthic organisms have been widely used for decades, these methods have experienced limited use in studies of freshwater benthos due to the general lack of large epifauna. The situation has changed with the introduction of dreissenid bivalves capable of creating visible aggregations on lake bottoms into North American freshwaters in the 1980s and 1990s. The need for assessment of Dreissena densities prompted exploration of videography as a potentially cost-effective tool. We developed a novel sampling method that analyzes video recorded using a GoPro camera mounted to a benthic sled to estimate Dreissena coverage, density, and biomass over relatively large areas of the lake bed in the Laurentian Great Lakes compared to traditional sampling methods. Using this method, we compared quagga mussel coverage, density, and biomass estimates based on three replicate Ponar grabs vs. 500 m-long video transects across 43 stations sampled in Lake Michigan in 2015. Our results showed that analysis of images from video transects dramatically increased the bottom area surveyed compared to Ponar grabs and increased the precision of Dreissena density and biomass estimations at monitoring stations. By substantially increasing the ability to detect relatively small (20%) changes between years within a particular station, this method could be a useful and cost-effective addition for monitoring Dreissena populations in the Great Lakes and other freshwater systems where they occur. (C) 2018 The Author(s). Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.
机译：与在底栖生物研究中广泛使用遥感方法的海洋系统相比，数十年来，由于普遍缺乏大型动物，这些方法在淡水底栖动物研究中的应用受到限制。随着可在1980年代和1990年代在北美淡水中在湖底形成可见聚集的类脂杜鹃双壳类动物的出现，情况发生了变化。需要对Dreissena密度进行评估，促使人们将录像技术作为一种潜在的具有成本效益的工具进行探索。我们开发了一种新颖的采样方法，该方法可以分析使用安装在底栖雪橇上的GoPro摄像机录制的视频，以估计与传统采样方法相比，劳伦大湖中较大面积湖床上Dreissena的覆盖率，密度和生物量。使用此方法，我们比较了2015年在密歇根湖采样的43个台站上的三个重复Ponar抓取与500 m长视频样带的夸克贻贝覆盖率，密度和生物量估计。我们的结果表明，对视频样例图像的分析显着与Ponar抓斗相比，增加了调查的底部面积，并提高了监测站Dreissena密度和生物量估计的精度。通过显着提高在特定站点内几年间检测相对较小（<20％）变化的能力，此方法可能是一种有用且具有成本效益的方法，用于监视大湖和其他淡水系统中Dreissena种群的发生。 （C）2018作者。由Elsevier B.V.代表国际大湖研究协会出版。

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