CCPortal
DOI10.1016/j.jglr.2018.05.003
Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales
Karatayev, Alexander Y.1; Mehler, Knut1; Burlakova, Lyubov E.1; Hinchey, Elizabeth K.2; Warren, Glenn J.2
发表日期2018-08-01
ISSN0380-1330
卷号44期号:4页码:629-638
英文摘要

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.


英文关键词Remote sensing;Dreissena rostriformis bugensis;Lake Michigan;Underwater video;Distribution;Benthos
语种英语
WOS记录号WOS:000440959300009
来源期刊JOURNAL OF GREAT LAKES RESEARCH
来源机构美国环保署
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/58365
作者单位1.SUNY Buffalo State, Great Lakes Ctr, Buffalo, NY 14222 USA;
2.US EPA, Great Lakes Natl Program Off, Chicago, IL USA
推荐引用方式
GB/T 7714
Karatayev, Alexander Y.,Mehler, Knut,Burlakova, Lyubov E.,et al. Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales[J]. 美国环保署,2018,44(4):629-638.
APA Karatayev, Alexander Y.,Mehler, Knut,Burlakova, Lyubov E.,Hinchey, Elizabeth K.,&Warren, Glenn J..(2018).Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales.JOURNAL OF GREAT LAKES RESEARCH,44(4),629-638.
MLA Karatayev, Alexander Y.,et al."Benthic video image analysis facilitates monitoring of Dreissena populations across spatial scales".JOURNAL OF GREAT LAKES RESEARCH 44.4(2018):629-638.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Karatayev, Alexander Y.]的文章
[Mehler, Knut]的文章
[Burlakova, Lyubov E.]的文章
百度学术
百度学术中相似的文章
[Karatayev, Alexander Y.]的文章
[Mehler, Knut]的文章
[Burlakova, Lyubov E.]的文章
必应学术
必应学术中相似的文章
[Karatayev, Alexander Y.]的文章
[Mehler, Knut]的文章
[Burlakova, Lyubov E.]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。