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Deep vision: an in-trawl stereo camera makes a step forward in monitoring the pelagic community.

Underwood MJ, Rosen S, Engås A, Eriksen E - PLoS ONE (2014)

Bottom Line: 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.This study suggests modifications to the Deep Vision and the trawl to increase our understanding of the population dynamics.

View Article: PubMed Central - PubMed

Affiliation: Institute of Marine Research, Bergen, Norway; Department of Biology, University of Bergen, Bergen, Norway.

ABSTRACT
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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Related in: MedlinePlus

Example of tracking fish through sequential images.(A) Four polar cod (Boreogadus saida) enter the Deep Vision chamber and (B) move towards to the codend in the next image, taken 200 ms later. The white arrows show the movement by each individual.
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pone-0112304-g002: Example of tracking fish through sequential images.(A) Four polar cod (Boreogadus saida) enter the Deep Vision chamber and (B) move towards to the codend in the next image, taken 200 ms later. The white arrows show the movement by each individual.

Mentions: A total of 21 030 images from haul 04 and 19 714 images from haul 06 were analysed in two ways. First, all finfish and lion's mane jellyfish (Cyanea capillata) were counted, in accordance with the BESS catch sampling protocol. Most individuals were imaged several times as they passed through the 41–102 cm field of view (generally taking 3 images or 600 ms to pass). In order to prevent double-counting, individuals were tracked across images (Fig. 2) and counted in the image when they first entered the field of view. Individuals that exited the field of view from the direction of the trawl entrance were subtracted from counts and added again when they re-entered the field of view. Individuals that could not be identified were recorded as ‘unidentified’. Second, all other zooplankton were quantified by sampling the first image of each 30-second interval and counting the number of individuals present (a total of 140 images from haul 04 and 124 images from haul 06). This method was used because it was impossible to track small zooplankton between images when densities were high (hundreds of individuals in a single image). Since there was a 30-second interval between images, it is unlikely that any individuals were double-counted. To estimate the total count of zooplankton in each haul, each sub-sample representing the number of passages in 600 ms was multiplied by 50 to estimate total number of individuals passing in each 30-second interval.


Deep vision: an in-trawl stereo camera makes a step forward in monitoring the pelagic community.

Underwood MJ, Rosen S, Engås A, Eriksen E - PLoS ONE (2014)

Example of tracking fish through sequential images.(A) Four polar cod (Boreogadus saida) enter the Deep Vision chamber and (B) move towards to the codend in the next image, taken 200 ms later. The white arrows show the movement by each individual.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230979&req=5

pone-0112304-g002: Example of tracking fish through sequential images.(A) Four polar cod (Boreogadus saida) enter the Deep Vision chamber and (B) move towards to the codend in the next image, taken 200 ms later. The white arrows show the movement by each individual.
Mentions: A total of 21 030 images from haul 04 and 19 714 images from haul 06 were analysed in two ways. First, all finfish and lion's mane jellyfish (Cyanea capillata) were counted, in accordance with the BESS catch sampling protocol. Most individuals were imaged several times as they passed through the 41–102 cm field of view (generally taking 3 images or 600 ms to pass). In order to prevent double-counting, individuals were tracked across images (Fig. 2) and counted in the image when they first entered the field of view. Individuals that exited the field of view from the direction of the trawl entrance were subtracted from counts and added again when they re-entered the field of view. Individuals that could not be identified were recorded as ‘unidentified’. Second, all other zooplankton were quantified by sampling the first image of each 30-second interval and counting the number of individuals present (a total of 140 images from haul 04 and 124 images from haul 06). This method was used because it was impossible to track small zooplankton between images when densities were high (hundreds of individuals in a single image). Since there was a 30-second interval between images, it is unlikely that any individuals were double-counted. To estimate the total count of zooplankton in each haul, each sub-sample representing the number of passages in 600 ms was multiplied by 50 to estimate total number of individuals passing in each 30-second interval.

Bottom Line: 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.This study suggests modifications to the Deep Vision and the trawl to increase our understanding of the population dynamics.

View Article: PubMed Central - PubMed

Affiliation: Institute of Marine Research, Bergen, Norway; Department of Biology, University of Bergen, Bergen, Norway.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus