DeepVision in-trawl imaging: Sampling the water column in four dimensions

Rosen, Shale; Holst, Jens Christian

doi:10.1016/j.fishres.2013.08.002

Cited by 40 publications

(24 citation statements)

References 92 publications

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“…The biological information in our study was collected with a mesopelagic midwater trawl with a headline height of 12-15 m and a door spread of around 140-160 m, which remains open through the WC as it descends to the depth where the targeted acoustic marks for mark identification were observed on the echograms. Traditional trawling does not provide a fine spatial scale resolution causing the loss of crucial information to classify discrete acoustic layers into species (Kracker, 1999;Rosen and Christian, 2013). This issue is accentuated when the sampling aims to collect biological information from one of the DSLs commonly observed in open ocean ecosystems, which are distributed vertically at different depth ranges.…”

Section: Mark Classificationmentioning

confidence: 99%

“…This issue is accentuated when the sampling aims to collect biological information from one of the DSLs commonly observed in open ocean ecosystems, which are distributed vertically at different depth ranges. To overcome this limitation, we need to move away from traditional single cod end trawl nets to use trawls with opening-closing mouths or cod ends, or in-trawl stereo cameras, or combine different types or trawls, or use acoustic and optic sampling (AOS) devices mounted on trawls and combine their information (Pearcy, 1983;Rosen and Christian, 2013;Kwong et al, 2018). Sampling of micronekton is still a topic that requires further research and development, as all sampling methods have their particular biases (often referred to as catchability).…”

Section: Mark Classificationmentioning

confidence: 99%

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Acoustic Assessment of the Micronekton Community on the Chatham Rise, New Zealand, Using a Semi-Automated Approach

2019

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Micronekton are a key component of the pelagic food web of the Chatham Rise east of New Zealand. The Chatham Rise is an important fishing area for hoki (Macruronus novaezelandiae), New Zealand's largest finfish fishery, and a predator on mesopelagic fish. Four fisheries oceanographic voyages provided multi-frequency acoustic data (18, 38, 70, 120, and 200 kHz) and midwater trawls, which were used to define a classification tree to separate micronektonic organisms. We carried out validation and sensitivity analyses that showed that we were able to classify pearlside (Maurolicus australis) and euphausiids. Other mesopelagic targets (mainly myctophids) were classified together based on their acoustic frequency response. Using scripting in the open-source software ESP3, we applied our classification tree to an independent time series of acoustic data from trawl surveys on the Chatham Rise between 2009 and 2018, that was not used for model development or validation. Our methodology allowed us to study temporal and spatial patterns of M. australis, euphausiids, and total backscatter in the water column. Total backscatter associated with micronekton has varied over the last 10 years, with no clear trend. The abundance of euphausiids showed a significant decreasing trend over the last 10 years. Abundance of M. australis also decreased since 2012, though this was not significant. This work contributes to ongoing efforts to monitor and detect changes in the pelagic ecosystems.

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Section: Mark Classificationmentioning

confidence: 99%

Section: Mark Classificationmentioning

confidence: 99%

Acoustic Assessment of the Micronekton Community on the Chatham Rise, New Zealand, Using a Semi-Automated Approach

2019

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“…Five images per second were collected, starting before the trawl was set out and ending when it came back onboard the vessel, saving a continuous time-referenced record of all objects that passed through the trawl during the shooting, trawling, and heaving phases. The system and its measurement accuracy are described in detail by Rosen et al [10] and Rosen and Holst [12] . In this study, the system was operated in autonomous mode without cable connection to the vessel.…”

Section: Methodsmentioning

confidence: 99%

“…The Deep Vision system has been used for several surveys to identify, quantify and measure the length of large fish such as adult Northeast Arctic cod ( Gadus morhua ), haddock ( Melanogrammus aeglefinus ) and Atlantic mackerel ( Scomber scombrus ) along the trawl track. Time-references for each image can be matched up with data such as geographic position and acoustic backscatter information collected by the vessel's echo sounder [12] . The stereo images can be processed to calculate the size of passing objects with high accuracy (less than 5% error; [10] ) as well as the spatial distribution along the trawl path.…”

Section: Introductionmentioning

confidence: 99%

Deep Vision: An In-Trawl Stereo Camera Makes a Step Forward in Monitoring the Pelagic Community

et al. 2014

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Ecosystem surveys are carried out annually in the Barents Sea by Russia and Norway to monitor the spatial distribution of ecosystem components and to study population dynamics. One component of the survey is mapping the upper pelagic zone using a trawl towed at several depths. However, the current technique with a single codend does not provide fine-scale spatial data needed to directly study species overlaps. An in-trawl camera system, Deep Vision, was mounted in front of the codend in order to acquire continuous images of all organisms passing. It was possible to identify and quantify of most young-of-the-year fish (e.g. Gadus morhua, Boreogadus saida and Reinhardtius hippoglossoides) and zooplankton, including Ctenophora, which are usually damaged in the codend. The system showed potential for measuring the length of small organisms and also recorded the vertical and horizontal positions where individuals were imaged. Young-of-the-year fish were difficult to identify when passing the camera at maximum range and to quantify during high densities. In addition, a large number of fish with damaged opercula were observed passing the Deep Vision camera during heaving; suggesting individuals had become entangled in meshes farther forward in the trawl. This indicates that unknown numbers of fish are probably lost in forward sections of the trawl and that the heaving procedure may influence the number of fish entering the codend, with implications for abundance indices and understanding population dynamics. This study suggests modifications to the Deep Vision and the trawl to increase our understanding of the population dynamics.

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“…). When affixed to the entrance of nets, camera systems also offer the potential to gather in‐trawl information on target and non‐target species during surveys, allowing for a more detailed description of the catch, species distribution in the water column, and method efficiency (Rosen and Holst ). The impact of trawl methods on non‐target fishery stocks is another consideration, with implications for management.…”

Section: Ecosystem‐ and Population‐level Monitoringmentioning

confidence: 99%

Camera technology for monitoring marine biodiversity and human impact

Bicknell

Godley

Sheehan

et al. 2016

Frontiers in Ecol & Environ

134

106

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Human activities have fundamentally altered the marine environment, creating a need for effective management in one of Earth's most challenging habitats. Remote camera imagery has emerged as an essential tool for monitoring at all scales, from individuals to populations and communities up to entire marine ecosystems. Here we review the use of remote cameras to monitor the marine environment in relation to human activity, and consider emerging and potential future applications. Rapid technological advances in equipment and analytical tools influence where, why, and how remote camera imagery can be applied. We encourage the inclusion of cameras within multi‐method and multi‐sensor approaches to improve our understanding of ecosystems and help manage human activities and minimize impacts.

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DeepVision in-trawl imaging: Sampling the water column in four dimensions

Cited by 40 publications

References 92 publications

Acoustic Assessment of the Micronekton Community on the Chatham Rise, New Zealand, Using a Semi-Automated Approach

Acoustic Assessment of the Micronekton Community on the Chatham Rise, New Zealand, Using a Semi-Automated Approach

Deep Vision: An In-Trawl Stereo Camera Makes a Step Forward in Monitoring the Pelagic Community

Camera technology for monitoring marine biodiversity and human impact

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