This work was funded by The Nature Conservancy and private donors, Resources Legacy Fund Foundation, Gordon and Betty Moore Foundation, Environmental Defense Fund, California Sea Grant Program, the NMFS National Cooperative Research Program, and a NOAA Saltonstall-Kennedy Grant #13-SWR-008. Marine Applied Research and Exploration (Dirk Rosen, Rick Botman, Andy Lauerman, and David Jefferies) developed, constructed and maintained the video Lander tool. We thank Jim Seager and SeaGIS&#8482; software for technical support. Captain and commercial fisherman Tim Maricich and crew onboard the F/V Donna Kathleen provided support in deploying the Lander from 2012-2015. Thank you to all who participated in video data collection or analysis (Anne Tagini, Donna Kline, Lt. Amber Payne, Bryon Downey, Marisa Ponte, Rebecca Miller, Matt Merrifield, Walter Heady, Steve Rienecke, EJ Dick, and John Field).

NOTE: Screenshots of software steps are included as Supplementary Files. Please note that the software steps described below are specific to the chosen software (see the Table of Materials). The overall approach can be extended to any stereo software platform.
1. Prepare Stereo-camera Footage for Analysis
NOTE: Calibration using a calibration cube is recommended. A calibration cube is a three-dimensional aluminum-frame with precisely ...

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The authors have nothing to disclose

The traditional MaxN metric is predicated on the idea of counting a guaranteed minimum number of individuals present during a survey. If a certain number of fish are simultaneously visible in a single video frame, there cannot be any fewer present, but because fish are mobile and heterogeneously distributed, the likelihood of seeing all individuals simultaneously during a single video frame is low. It is therefore likely that traditional MaxN underestimates true fish abundance16,<sup cl...

Along the U.S. Pacific Coast, many of the species important to commercial and recreational groundfish fisheries (e.g., the rockfish complex (Sebastes spp.) and Lingcod (Ophiodon elongatus)) are strongly associated with high-relief, hard-bottom habitats1,2,3,4,5. Stereo-video drop cameras are an attractive non-extractive tool to use in rocky habitats due to the relative ease and simplicity of operation. A variety of stereo-video camera systems have been developed and deployed in southern-hemisphere, shallow-water ecosystems6,7,8,9,10, and recently, video drop-cameras have gained traction as a management tool for deep water rocky-reef environments along the Pacific Coast11,12,13. We sought to modify these existing stereo-camera designs by using a stereo-video camera system (hereafter referred to as &#34;Lander&#34;) to more efficiently characterize fish populations in high-relief seafloors along the central Pacific Coast (see Table of Materials). The Lander used was different than existing video systems because cameras were mounted to a central rotating bar, which allowed for a full 360&#176; of coverage of the seafloor at the drop location14. The Lander completed one full rotation per minute, which allowed us to rapidly characterize the abundance and community composition of an area and achieve the same level of statistical power with fewer Lander deployments. (See Starr (2016)14 for greater detail on the specifics of the Lander configuration). Preliminary tests in the study system suggested that eight rotations of the cameras in our surveys were sufficient to characterize species abundance and richness. This determination was made by an observation of diminishing returns in species abundance and fish density over longer drops. We recommend that a pilot study including longer soak times be conducted in any new system to determine the optimal soak time for a given ecosystem/study species.
By using paired stereo cameras, both total survey area and absolute fish density can be calculated for each video survey; however, the use of rotating cameras necessitated the modification of traditional fish count metrics. Stationary video systems most often use &#34;MaxN&#34; as a conservative count of fishes on a deployment6,10. Traditional MaxN describes the maximum number of fish of a given species observed together in a single video frame, in order to avoid double counting a fish that has left and returned to frame. MaxN has therefore been an estimate of the minimum number of fish known to be present and may underestimate true fish abundance6,10. The MaxN metric was redefined to represent the greatest number of fish seen in each full rotation of the cameras.
The second modification to previous stereo video methods was to account for the fact that species of various sizes, color, and shapes have different maximum distances of reliable identification. For example, large species such as O. elongatus have a distinct elongated shape and can reliably be identified at much greater distances compared with small and cryptic species such as the Squarespot Rockfish (Sebastes hopkinsi). These different maximum ranges of detectability change the effective area sampled by the Lander for each species. Because the stereo cameras allow us to place every fish in three-dimensional space with a high degree of accuracy, one can determine the distance from the cameras that each fish was measured (i.e., the &#34;Z distance&#34;, named for the &#34;z-axis&#34; which is perpendicular to the straight line drawn between the cameras). For each species, the distance within which 95% of all individuals were observed (hereafter &#34;95% Z distance&#34;) was considered to be the radius of the survey area, and was used to calculate the total area surveyed. In addition to species-specific characteristics, identifiability will be impacted by environmental conditions such as water turbidity. Because these factors can vary in time and space, it is important to use the 95% Z statistic only in aggregate. While it will be highly accurate for large samples, any one individual survey may vary in area surveyed.
The protocol detailed below provides guidance on how to create and use these metrics. Though the focus was to characterize deep-water rocky habitat along the Pacific Coast, the methodology described for modified MaxN count is readily applicable to any rotating drop-camera system. The number of camera rotations needed to characterize fish populations will depend on local ecosystem dynamics, but the conceptualization of the modified MaxN will remain the same. Similarly, whereas we used 3D photogrammetric software to analyze stereo video, the techniques described herein are easily applied across software platforms, as long as the precise location of fish in three-dimensional space is possible. Additionally, the approach of applying a 95% Z distance value could be considered in future studies with stereo-cameras to account for species-specific ranges of detectability and to more accurately calculate fish abundance.

<table border="0" cellpadding="0" cellspacing="0" style="width:877px;" width="876">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="84">
			<td height="84" style="height:84px;width:201px;">calibration cube</td>
			<td style="width:193px;">SeaGIS</td>
			<td style="width:279px;">http://www.seagis.com.au/hardware.html</td>
			<td style="width:204px;">1000x1000x500 mm is the preferred dimensions. Other methods of calibration are available.&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:201px;">CAL calibration software</td>
			<td style="width:193px;">SeaGIS</td>
			<td style="width:279px;">http://www.seagis.com.au/bundle.html</td>
			<td style="width:204px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:201px;">EventMeasure stereo measurement software</td>
			<td style="width:193px;">SeaGIS</td>
			<td style="width:279px;">http://www.seagis.com.au/event.html</td>
			<td style="width:204px;"></td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:201px;">Statistical software</td>
			<td style="width:193px;">R Core Team 2017 (v. 3.4.0)</td>
			<td style="width:279px;"></td>
			<td style="width:204px;">Bootstrapping code can be found: https://github.com/rfields2017/JoVE-Bootstrap-Function</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:201px;">Spreadsheet Software</td>
			<td style="width:193px;">Microsoft Excel</td>
			<td style="width:279px;"></td>
			<td style="width:204px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:201px;">2&#160; waterproof cameras</td>
			<td style="width:193px;">Deep Sea Power and Light</td>
			<td style="width:279px;"></td>
			<td style="width:204px;">HD quality preferred</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:201px;">2 depth rated, waterproof lights</td>
			<td style="width:193px;">Deep Sea Power and Light : 3000 lumen LED with 5000k color temperature</td>
			<td style="width:279px;"></td>
			<td style="width:204px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:201px;">DVR recorder</td>
			<td style="width:193px;">Stack LTD DVR</td>
			<td style="width:279px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:201px;">standard PC</td>
			<td style="width:193px;"></td>
			<td style="width:279px;"></td>
			<td>Windows 10 preferred OS</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:201px;">rotating Lander platform</td>
			<td style="width:193px;">Marine Applied Research and Engineering (MARE)</td>
			<td style="width:279px;"></td>
			<td></td>
		</tr>
	</tbody>
</table>

development of new methods for quantifying fish density using underwater stereo-video tools

The use of video camera systems in ecological studies of fish continues to gain traction as a viable, non-extractive method of measuring fish lengths and estimating fish abundance. We developed and implemented a rotating stereo-video camera tool that covers a full 360 degrees of sampling, which maximizes sampling effort compared to stationary camera tools. A variety of studies have detailed the ability of static, stereo-camera systems to obtain highly accurate and precise measurements of fish; the focus here was on the development of methodological approaches to quantify fish density using rotating camera systems. The first approach was to develop a modification of the metric MaxN, which typically is a conservative count of the minimum number of fish observed on a given camera survey. We redefine MaxN to be the maximum number of fish observed in any given rotation of the camera system. When precautions are taken to avoid double counting, this method for MaxN may more accurately reflect true abundance than that obtained from a fixed camera. Secondly, because stereo-video allows fish to be mapped in three-dimensional space, precise estimates of the distance-from-camera can be obtained for each fish. By using the 95% percentile of the observed distance from camera to establish species-specific areas surveyed, we account for differences in detectability among species while avoiding diluting density estimates by using the maximum distance a species was observed. Accounting for this range of detectability is critical to accurately estimate fish abundances. This methodology will facilitate the integration of rotating stereo-video tools in both applied science and management contexts.

Between 2013 and 2014, we conducted 816 surveys with the rotating stereo-video Lander (Figure 1) along the central California coast and collected MaxN and 95% Z distance (Figure 4) data on more than 20 species. There were clear patterns in the effective detectable range of species observed, likely due to the interaction of species&#39; size, shape, and coloration (Figure 5). For instance, the Flag Ro...

Watch this Scientific Journal Video about Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools at JoVE.com

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

We describe a new method for counting fishes, and estimating relative abundance (MaxN) and fish density using rotating stereo-video camera systems. We also demonstrate how to use distance from camera (Z distance) to estimate species-specific detectability.

The use of video camera systems in ecological studies of fish continues to gain traction as a viable, non-extractive method of measuring fish lengths and ...

The overall goal of this video analysis technique is to more accurately estimate density, mean length and species composition of fish in deep rocky habitats. This method can help answer key questions in the field of fisheries management such as what is the abundance and size distribution of species inhabiting deep-water rocky reefs. The main advantage of this technique is that it provides more accurate density estimates without extracting fish from the environment.In advance of this procedure, collect field data as outlined in the text protocol. In stereophotogrammetry, knowing the exact relative position of the cameras is important for accurate measurements. Proper calibration is an important step in this process.After the field study is complete, create a new project folder containing both the video and calibration files. In the stereo measurement software, navigate to Measurement, New measurement file. Set the picture directory by navigating to Picture.Set picture directory and then choose the folder containing all of the project files. Navigate to Stereo, Cameras, Left, then Load camera file to select and load the appropriate left camera file. Repeat this process choosing Right instead to load the right camera file.Next, navigate to Picture, Define movie sequence. Select the left camera video file to define the movie sequence for the left video. Click Picture, Load picture to load the left video file into the measurement software.After this, click Stereo, Picture, Define movie sequence to define the movie sequence for the right video. Load the video file by selecting Stereo, Picture then load video. Navigate to Measurement, Attributes, Edit load species file to load the species list.Click Measurement, Information fields, Edit field values to open the information field values table. Enter the survey ID information and save the file to create an event measure observations project. If using a UTC timestamp, frame step forward in the left video until the timestamp starts a new second or until a light flash or hand clap occurs.Frame step the right video forward until the timestamp light flash or hand clap matches the left video exactly. Then, click the Lock button to ensure the videos play together and maintain synchronization. As soon as the lander starts its first rotation, right-click and select Period definitions, Add new start period to define a new sample period.Enter zero one as the first period name and click OK.While the lander rotates, mark each fish that comes into frame with a 2D point by right-clicking, select Add point and choose the correct species name. Label to the lowest possible taxonomic level and then click OK.Continue marking each new fish until the rotation completes. It's critical to identify and count each fish to get accurate estimates of MaxN.Repeat this process for an additional lander rotation ensuring that a new period is defined at the start of each. After all rotations have been enumerated, navigate to Measurement, Measurement summaries, Point measurements and save the 2D points as a TXT file. Open this file as a spreadsheet.Navigate to Insert, Pivot Table to create a pivot table. Selecting Genus and Species for the row label and Period for the column label. Select the camera rotation that has the greatest number of individuals for a given species to choose the MaxN for that species.For fish identified only to genus, select a genus level MaxN based on the rotation that had the greatest number of individuals identified to species in that particular genus. Next, use the saved 2D points to navigate to the exact same fish for the 3D measurement. Zoom in at least four times to better identify the tip of the fish snout and the edges of the caudal fins.Manually click on the tip of the snout and then the edge of the tail in the left camera. Repeat the selection in the same order in the right video. Then, right-click, select Add length and select the correct species identification.If 3D length measurement is not possible, left-click in the same position on the fish in both videos to mark a 3D point. Fill out the information fields leaving the comment Exclude from length measurement. After completing 3D measurements for all fish, navigate to Measurement, Measurement summaries and 3D point and length measurements.Save the data as a TXT file to export it for further analysis. Then, determine if adequate samples were obtained as outlined in the text protocol. In this study, underwater stereo video tools are utilized to quantify fish density.There are clear patterns in the detectable range of the species observed which is likely due to the interaction of each species'size, shape and coloration. The 95%Z distance calculations are then performed for two species in particular. For Sebastes wilsoni and Ophiodon elongatus, the 95%Z distance is seen to be 2.65 meters for Sebastes wilsoni and 3.96 meters for Ophiodon elongatus which translates into effective survey areas of 18.6 meters squared and 46 meters squared respectively.A simple bootstrap analysis confirms that sufficient sample sizes are obtained as the estimate of 95%Z distance for both samples stabilizes when over 50 surveys are sampled. MaxN counts per survey are then converted into densities. For both species, the densities are seen to be significantly greater over high and medium-relief habitats as compared to low-relief habitats.Density estimates for the pseudo-stationary lander are standardized using reduced areas of coverage. Mean densities obtained by the rotating camera are 18%greater than those obtained with stationary cameras. Additionally, the coefficient of variation is seen to be a 1.8 times greater when using stationary cameras.Once mastered, this technique can be used to count and measure fish in only a few minutes if properly performed. When performing this procedure, it's important to remember that 95%Z values are tool and survey specific. And specific values should not be used universally.Following this procedure, a variety of multivariate or ordination statistics can be performed to answer additional questions about species composition across different habitat types. The implications of this technique extend toward improved understanding of the ecology of deep-water rocky reef species as current survey mechanisms provide only a poor understanding of fish length and abundances. Thought this technique can provide insight into deep-water marine habitats, it can also be useful in other systems such as coral reefs and kelp forests.Generally, individuals new to this method will struggle because it requires an understanding of the geometry of stereo camera systems. Visual demonstration of this technique is helpful because the calculation of MaxN is derived from a variety of data and thus requires many steps in the software.

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Research

JoVE Journal

Environment

9.1K Görüntüleme.  Moss Landing Marine Laboratories. The overall goal of this video analysis technique is to more accurately estimate density, mean length and species composition of fish in deep rocky habitats. This method can help answer key questions in the field of fisheries management such as what is the abundance and size distribution of species inhabiting deep-water rocky reefs. The main advantage of this technique is that it provides more accurate density estimates without extracting fish from the environment.In advance of this pr...