Jacob Smith

Trout Population Survey by Underwater Videography

ABSTRACT:

As native trout and steelhead populations are declining there is a gap in

the knowledge of how many of these fish are truly left. In Southern California

these fish are as endangered as anywhere else in the world, with only a couple

known watersheds holding genetically wild trout, including the San Gabriel River

system, Santa Ana River, and the San Luis Rey River system (Jacobson et al 2014).

In the San Luis Rey drainage is Pauma Creek, a small extremely healthy trout

stream that has historically had trout of native steelhead lineage.

In order to study these fish this study develops a protocol for using

underwater videography as a method for quantifying population size. This was

done in order to replace the existing methods that are either inaccurate or

detrimental to the fish being studied. Using multiple cameras suspended in

holding pools within Pauma Creek recordings were taken and analyzed to

quantify these imperiled fish. These cameras were used in a way to maximize

the amount of the stream being recorded while still maintaining a lightweight

system that can easily be taken into remote areas of the backcountry. As a

result this study has produced footage that when analyzed has contained more

accurate population data than the other methods used to calibrate it.

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INTRODUCTION:

Rainbow trout of the species Oncorhynchus mykiss are naturally occurring

along the Pacific basin, ranging from Alaska through Mexico in cold headwaters,

creeks, small to large rivers, cool lakes, estuaries, and oceans (Staley & Mueller,

2000). Because of their ability to thrive in hatchery environments they have

been introduced all over the United States and even in areas overseas. These

trout are key predators in the habitats that they live in, eating many different

invertebrates and occasionally other fish. The best habitat for them is moving

water that is cool and clean with many different hiding places for them as well as

gravel beds for them to spawn on (Staley & Mueller, 2000).

California is home to 20 endemic salmonids and the vast majority of them

are in decline with studies projecting that 65% of them will be extinct within 100

years (Moyle et al, 2008). These trout have long stood as both economically

valuable due to the recreational fisheries based on them, as well as their

ecological importance to the waters that they live in. Native trout can be used as

a meter stick for the health of a watershed, as healthy populations are typically

found in areas with intact ecological systems (Staley & Mueller, 2000). As factors

such as reduced flows, diversions, sedimentation, pollution, increased

temperatures, migration barriers and invasive species hurt our water supply the

trout populations steadily decline. In Southern California trout habitat is being

lost at an alarming rate as the water they need to survive is being diverted for

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human needs and agriculture especially in times of drought. This impacted the

anadromous life history form of rainbow trout called steelhead. The decline in

Southern California Steelhead populations led to the federal listing under the

Endangered Species Act (ESA) of the Southern California Coast steelhead in 1997

from the Santa Maria River at the north end to Malibu Creek at the south end

(NOAA, 2012). Following steelhead sightings and genetic documentation in

watersheds south of Malibu Creek, the geographic boundary was extended

southward to the U.S.-Mexico border in 2002. The listing status of this expanded

region was reaffirmed in 2006 (NOAA, 2012).

Baseline trout population counts are essential parts of restoration efforts

to quantify success of restoration programs. Areas of Southern California that

hold trout are generally in remote areas in pools that are too deep for other

forms of population surveys, and equipment needs to be light for multi-day

backpacking trips to the site.

Trout in these small streams are difficult to get accurate population data

on while not being too stressful on the fish. The protocol under development

here is designed to overcome issues with each of the well-known methods for

quantifying trout populations including electrofishing, netting, and snorkel

survey in deep headwater pools. Electrofishing is a method that involves

introducing an electrical charge to an area with the intention to stun the fish in

which case they will float to the surface to be counted and inspected. For

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netting as a population survey, the selected area is netted all the way around and

slowly drawn together as to catch the fish in the confines of the net to be

counted and inspected. Snorkel surveys are taken by one or more person

getting in the water with snorkel gear where they will slowly move through the

area counting individuals as they go.

An issue with these existing methods is that when trout in remote

locations in southern California are surveyed the drawbacks of current methods

are exacerbated both statistically and biologically. This is due to the small

streams in which that they live and the lack of access to them. The fact that the

streams are so small presents an interesting challenge in snorkel surveying as the

fish are extremely skittish in these areas and can avoid being seen by hiding

under banks and behind rocks. The issue with electrofishing this area, besides

the stress it puts on the fish, is the weight of the equipment carried into the

backcountry as it can require additional people to accompany the field crew. It

has been noted that snorkel surveys, though less accurate than electrofishing,

sample a larger proportion of the water which can improve their population

estimates, but to produce data that is more accurate multiple methods can be

used to calibrate the data (Hankin and Reeves, 1988).

A study was done in 2011 using underwater videography and three pass

electrofishing to determine population counts of Eastern Cape redfin,

Pseudobarbus afer, and the Cape kurper, Sandelia capensis, in South Africa

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(Ellender et al, 2011). This study recorded underwater video data of these

imperiled fish and analyzed it using maxN statistics, “where relative abundance is

defined as the maximum number of individuals for each species present in the

field of view at the same time” (Ellender et al, 2011). These numbers were

referenced against the three pass electrofishing statistics using various statistical

models to determine if underwater videography was a reasonable alternative to

electrofishing (Ellender et al, 2011). For the Eastern Cape redfin the correlations

between underwater videography and electrofishing were highly significant

while the correlation for Cape kurper was not (Ellender et al, 2011). There are

various behavioral reasons given why the correlation was not as good for the

Caper kurper but for the Eastern Cape redfin the underwater video data

consistently detected a higher abundance of fish than three pass electrofishing.

This led to the conclusion that underwater videography was a viable alternative

to population studies for some species of fish.

Ellender pointed out that a primary prerequisite for studying imperiled

fish was to use the least destructive method possible that still provides accurate

and precise results. Stress, injuries, and mortalities among captured fish during

electrofishing are unavoidable, in Ellender’s study there were instantaneous

mortalities of two individuals of Eastern Cape redfin. This accounted for less

than one percent of the fish sampled by electrofishing. However it was noted

that this number may not be an accurate indication of actual mortality rates

(Ellender et al, 2011). A study of rainbow trout that examined effects of

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electrofishing took post capture X-rays showed that over half the fish sampled

had some sort of spinal cord injury and hemorrhages (Snyder, 2003). The

findings of these studies mentioned helped to mold my experiment.

California Trout, or CalTrout, is a nonprofit organization whose mission is

to protect and restore wild trout and other salmonids as well as their native

waters in California. I worked in conjunction with the Southern California region

of the organization and directly with the South Coast Steelhead Coalition

Coordinator, Sandra Jacobson. Southern California is one of the most imperiled

trout fisheries due to groundwater withdrawal and surface water diversions,

urbanization, the presence of invasive species, fish passage barriers, and overall

decreased water quality (Moyle et al, 2008). The Coalition has developed a

Strategic and Implementation Plan aligned with the federal NMFS Southern

California Steelhead Recovery Plan, which is geared towards implementing

projects that restore the endangered steelhead. It further utilizes its diverse

stakeholder base to educate the community through public outreach events.

The goal of my project with CalTrout was to develop a protocol for

deploying appropriate camera equipment to collect population data during fish

and habitat surveys in less than an hour in remote areas, in an approach that

overcomes technical drawbacks of snorkel survey, netting and electrofishing in

terms of accuracy, reproducibility and species identification. The whole project

is centered on the West Fork San Luis Rey River, which has one of the two known

remaining native rainbow trout populations in Southern California.

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The majority of the testing was to be done on Pauma Creek, a stream

that is part of the San Luis Rey River system though they are now separated by

fish barriers in the watershed. The area tested in Pauma Creek is from Palomar

Mountain down into Pauma Indian Reservation. This creek historically had wild

trout of native coastal steelhead descent (Jacobson et al, 2014). However,

population genetic surveys performed in recent years showed introgression of

hatchery lineage in the upper Pauma Creek population since 1997 (Jacobson et al

2014). It is currently not known whether the lower sections of Pauma still retain

native trout. Much of the water from the San Luis Rey watershed is diverted

away to the City of Escondido at a point upstream of where Pauma Creek enters

the River. Years of water quality testing and fisheries surveys have

demonstrated that this stream is one of the healthiest in San Diego County and is

a prime candidate for augmenting the trout population that currently resides

there, and restoring a steelhead population in Pauma Creek.

This study seeks to develop a protocol using a multicamera system for

conducting population surveys using underwater videography. This is done in

order to improve upon the accuracy and portability of the methods of snorkel

surveys and electrofishing currently used in order to protect native trout

populations and maintain healthy stream systems and eventually make these

fish open to recreational fishing again in a more sustainable fashion.

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MATERIALS AND METHODS:

Materials:

Once the grant for our project was funded I began researching cameras

by using field of view (FOV), low light capabilities and resolution as the main

factors in the evaluation. These specifications were compared among several

action style cameras that are available on the market. It was also necessary for

the cameras to have high adaptability to the different camera rigs that were

being developed. More research was done on the battery life of the cameras

and the memory that would be needed for long field tests. All of this was done

in conjunction with Sandra Jacobson from Caltrout who was integral in the

logistics of the entire project.

The monetary support for this project came from a grant funded by the

California Wildland Grassroots Fund to the Lead Applicant Trout Unlimited – San

Diego Chapter 920. The concept for this project arose in collaboration with the

Steelhead Coalition coordinator Sandra Jacobson; a Trout Unlimited-San Diego

member Howard Pippen; a regional CDFW fisheries biologist Russell Barabe, and

environmental staff member Jeremy Zagarella with the Pauma Band of Mission

Indians. The small grant for equipment provided enough money for the cameras

and accessories while also being paired with matching funds from Golden State

Flycasters to outfit the underwater robotic device.

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The Gopro Hero4 Silver camera was selected and three of them were

purchased. The cameras were purchased by Sandra Jacobson along with three

32 GB micro SD cards and three 64 GB micro SD cards. The micro SD cards

selected were with class 10 speed ratings. To build the multiple camera

configuration three Gopro handlebar clamp mounts were purchased to attach

the cameras. For the body of the camera configuration threaded half inch PVC

sprinkler risers were purchased in assorted lengths from 12-24 inches. To attach

the risers together half inch couplings were purchased one per riser. For the top

and bottom pieces a half inch PVC ‘T’ was bought along with an end cap

respectively. As a float for the top a can float was purchased from a local marine

store. Finally there was cordage purchased to anchor the camera configuration

for the trials. After the unit was assembled the weight of the multiple camera

unit as it would be tested was 22 ounces. A test plan was also written up that

outlined that variables to be tested, resources required, risks assessment, as well

a schedule in the form of a standard Microsoft Project Gantt chart to create a

timeline and resource allocation for the project.

Once the data was collected the cameras memory was uploaded onto a

computer to analyze the video. For best results the videos should be analyzed

on a screen with 1080p capabilities. The video is watched by a minimum of two

people who do not share their findings with each other until after viewing in

order to not bias results. Once these numbers were recorded they could be

compared to the snorkel surveys performed.

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The initial series of tests focused on components of the underwater

videography rig. To test portability, weight of the multiple camera rig was

measured. The original tests were based on the battery and memory available

for us on the cameras chosen. The camera tests were repeated in different

capture settings. All cameras were 1080p at different fps settings (frames per

second); 60, 30, and 24 fps.

To test memory and battery life simultaneously, fully charged cameras

were turned on to record until the battery was fully depleted. The videos were

then uploaded to see the file size and length of the video. The battery-depleted

cameras were put on the charger in a standard 120 volt wall outlet and timed

until the red charging indicator light turned off.

For interpreting the video a media player had to be identified that could

play three videos side by side. Online research was done extensively to find a

player that could control the three videos at once and also be able to control

them individually.

The next series of tests was performed collaboratively with Sandra

Jacobson, CalTrout; Russell Barabe of the California Department of Fish and

Wildlife; Dylan Nickerson of CDFW; Howard Pippen of the Golden State

Flycasters and Trout Unlimited; and Jeremy Zagarella of the Pauma Band of

Mission Indians. With the camera configuration in a beta prototype rig we went

to Lake Miramar to test FOV and camera setting issues.

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The first field test on May 29, 2015 at Lake Miramar compared the wide

and medium camera angle settings, described on the cameras specifications as

170o and 127o respectively. The camera was set to 1080p and 60fps in the

medium viewing angle and suspended in the lake to 27 inches. Video was taken

as we moved an object that was intended to be a makeshift secchi disk (a tool

used to measure water turbidity as a unit of distance); a Gopro surf-mount plate

that was grey on one side and white on the opposite which we named the “surfie

disk.” The surfie disk away from the camera out to a distance of 20 feet. This

test was repeated in the wide viewing angle and the video was analyzed the next

day.

To determine the blind spots in the camera configuration and to

maximize the cameras’ view of the trout underwater in the streams, further field

of view testing was performed. For the lateral blind spots we ran a test at the

lake in which a pole suspended from a string held at distances of 12, 18, and 24

inches from the lens. An additional test was run to test the horizontal blind

spots in which an object was held in between two cameras, 60o from each

camera, at the center pole and moved away from the cameras until it could be

viewed by both cameras. The video was analyzed in real time using the cameras

wifi enabled mobile application. The range of this wifi was also tested in the lake

by suspending the camera until it lost connection with the mobile application on

an IPad Mini (Figure 1).

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Figure 1. Jacob Smith syncing the Gopro camera’s wifi to an IPad mini on a dock at Lake Miramar.

To determine vertical GoPro camera rig blind spots and test the

OpenROV robot underwater capabilities, tests were again performed during the

second field test on June 25, 2015 at Lake Miramar. The camera was set to the

wide viewing angle at 1080p and 60fps and suspended to depths of 26 inches, 52

inches, and 87 inches. At each depth the “surfie disk” was brought in one foot

increments, rotating from the white to grey side each foot, until it was at the

pole which the camera was suspended on. This video was analyzed and the

information used to find the actual vertical viewing angle of the camera which

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showed the blind spots. The turbidity of the water on this test was also tested

using a secchi disk that was lowered until no longer visible.

Figure 2. The camera rig is made up of 3 Gopro Hero4 cameras arranged around a PVC pipe at 120o increments. This design is to optimize the video coverage of the stream while maintaining the lightest and most packable unit possible.

To develop the anchor system, an array of different materials that could

possibly be used to keep the cameras stationary in the streams was purchased

and tested. Bailing wire, tent stakes, fishing weights and assorted lengths of

cordage were tested. The first anchor configuration tested was using two

lengths of quarter inch cordage to attach to the top of the float to natural

features on the shore. If there was no suitable place to tie these lines to the

shore then tent stakes could be driven into the ground for tie off. The next

configuration used bailing wire to tie the cordage to river rocks that could then

be used as anchors.

The openROV 2.6 robot, assembled and built by Howard Pippen built

from the openRov 2.6 kit, was tested to run initial tests and gain piloting

experience (Figure 3). The field group tested various hardware variables and

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learned the openROV’s capabilities in the lake. When in the lake the openROV

was piloted near fish to see their response and interaction with it.

Figure 3. The openROV robot seen above enabled video footage up to 100 yards away and video documented areas not be reachable on foot.

The third field test on July 13, 2015 was performed in upper Pauma Creek

near Palomar State Park (Figure 6) Members of the field crew included Russell

Barabe of CDFW, myself and Sandra Jacobson of CalTrout. The objective of this

test was to gather initial information about how to set up the cameras in the

pool, observe trout’s reaction to the camera, and gather sufficient video for trout

population counts. We hiked through the Palomar Conference Center about one

mile to the creek which due to drought conditions had reduced flow and pool

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size. We successfully found a pool of sufficient depth (about 26 inches deep) and

visible trout that warranted testing the underwater videography rig.

Figure 4. A trout rises in a pool before being tested in upper Pauma Creek.

The camera rig was tied to shore using two lengths of rope tied from the

top of rig then onto tree limbs on the banks of the creek. The cameras were

deployed into the center of the pool with subjective discretion involving viewing

obstructions, the depth of the water, and observations of fish locations in the

pool (Figure 5).

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Figure 5. Using a rope tied to the top of the camera rig, the rig is anchored at two points on shore to maintain a stationary position.

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The cameras were placed into the water while recording and were

allowed to record between 15 and 25 minutes while participants were sitting out

of site taking water chemistry measurements. These pools were then allowed to

sit for 5-10 minutes to let the trout readjust.

The fourth field test was performed on July 16 in Pauma Creek in the

middle section of Pauma canyon that has larger pools and more remote terrain.

Members of the field crew included Russell Barabe (CDFW), Dylan Nickerson of

CDFW, and myself. This area had to be reached by an extremely strenuous trail

that used a system of ropes to make a steep descent down to the creek from the

road that was roughly 1000 feet above and under one mile away (Figure 6).

The pools tested were all within a one mile stretch of each other on a

section of Pauma Creek with extremely limited access. The pools ranged from

three by five yards to five by seven yards. A max depth of each pool was also

estimated from 0.3 yards up to two yards in the largest pool tested. Along with

varying sizes and depths the pools also ranged from full sun to partial to near

complete shade from the vegetation canopy. All of the tests were run between

9:45AM and 2:30PM. Two snorkel surveys were performed by different

individuals to use as comparison to the video data.

The fifth field test was performed on July 17 in Pauma Creek in the lower

section on Pauma Indian Reservation, with permission from Pauma Band of

Mission Indians and participation of Jeremy Zagarella, a member of the

17 | S m i t h

environmental staff at Pauma. Members of the field crew included Russell

Barabe of CDFW, Jeremy Zagarella of Pauma environmental staff, Howard Pippen

of Golden State Flycasters, and myself. The objective of this test was to test the

openROV in a deep pool in lower Pauma Creek The openROV was deployed for

roughly an hour in this deep pool and flown in various patterns to test

capabilities. The pool had an estimated size of 12 yards by 10 yards with a depth

of over three yards.

Figure 6. Pauma Creek canyon showing sites of field tests, Palomar Mountain is shown on the right and Pauma Indian Reservation on the left (the creek flows right to left).

Results:

The depletion time for the Gopro batteries while recording was found to

be on average 1 hour and 50 minutes. The total charge time was 1 hour 45

minutes with the original Gopro batteries plugged into the wall outlet. The

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charge time using the portable power source was 2 hours 5 minutes. The

underwater wifi capabilities of the Gopro cameras only allowed connection to a

submersion in 1 inch of water.

In the turbidity test for both the medium and the wide FOV settings the

grey side of the “surfie disk” was lost at 18 feet in the lateral direction at a depth

of 27 inches in Lake Miramar. The white side of the disk was never lost in the test

out to 20 feet (Table 1). The test relating depth and lateral viewing ability

showed that at a depth of 10.5 feet there was no impact on the presence of a

fish-like object.

Results:Test 1 Measurement: Visibility at either white side (Y or N) or gray side (Y or N) of submerged disk

Distance from camera 4 ft 5 ft 6 ft 7 ft 8 ft 9 ft 10 ft 11 ft 12 ft 13 ft 14 ft 15 ft 16 ft 17 ft 18 ft 19 ft 20 ft27" depth, med angle Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/N Y/N Y/N27" depth, wide angle n/d n/d n/d n/d Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/Y Y/N Y/N Y/N

Table 1. The results show from testing the camera settings as they relate to the ability to see the presence of an object at a known depth and distance in Lake Miramar.

The original lateral blind spot test at Lake Miramar was found to be only

partially successful resulting in an estimate of 120o-140o lateral viewing field in

the wide angle and roughly 90o in the medium angle. The second test showed

the lateral blind spots between the cameras went out to 7 inches in the wide

angle and 15 inches in the medium angle. After these tests it was concluded the

wide angle was best for our purposes and the remaining results were all done in

the wide viewing angle.

In the vertical blind spot test the first depth of 26 inches precluded view

of the surface object at three feet, at the depth of 52 inches it was lost at six

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feet, and at 87 inches it was lost at 12 feet (Table 2). By taking these numbers

and solving the triangle the vertical angle field of vision was determined to be

roughly 60o from the vertical axis, with the results consistent across all depths.

The metric of turbidity was also taken on this day using a secchi disk and taken to

be 383 inches.

Distance to Camera2' 3' 4' 5' 6' 7' 8' 9' 10' 11' 12' 13' 14'

Camera 67 cm N N Y Y Y Y Y Y Y Y Y Y YDepth: 131 cm N N N N N Y Y Y Y Y Y Y Y

220 cm N N N N N N N N N N N Y Y

Table 2. The results from testing the blind spots of Gopro cameras in the vertical dimension with the camera in the wide FOV setting.

When the openROV was piloted in front of the largemouth bass

(Micropterus salmoides) present in Lake Miramar they did not have visible

negative response and if anything they were inquisitive. The openROV

performed well in the water, with performance pertaining to maneuverability

and camera ability, and its capabilities grew as piloting experience was gained.

In every test that was done in Pauma Creek the number of fish counted

by the video analyzed was more than the number of fish counted by snorkel

survey. The video data was very clear due to the low turbidity of the creek and

the high resolution of the cameras. The best way thus far to analyze the video

was to count the maximum amount of fish visible at one moment in the cameras

and use that as the metric for population of the pool.

The raw video data was viewed and times recorded with the highest

densities of fish present. These highest trout density time stamps were noted

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and 5-20 second clips of the videos surrounding the timestamp were then

excised from the full video. This was performed using the Gopro studio

software. This footage was then sent out to the team working on the project

for analysis. Every person recorded the maximum number of fish present at one

time in each clip independently. These numbers are to be reported back to me

so the average can be taken and a population estimate for the pool can be made.

This data is still being processed and the findings will soon give us an idea

of these trout population sizes. My estimate of the initial numbers indicates a

higher population than what was estimated by us while observing the pool

before camera deployment.

DISCUSSION:

A multicamera system can effectively be used to gather video information

about trout streams and their populations, though the process of developing

specific methods for data collection and analysis is still ongoing. If these

methods continue to be refined, they will replace less precise methods of

population study and give valuable insight into the population dynamics of these

endangered native fish. This data will ultimately allow for better protection of

the species.

The multitude of FOV tests and blind spot checks gave us a good idea of

the video coverage we have of the pools with the three cameras. The results of

this test show us that we will cover the majority of the pools out to a distance of

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20 feet in relatively high resolution. This was important because it allows us to

see the individuals in the stream and avoid double counting the fish by being

able to identify markings and size. The lateral blind spots showed the area lost

was negligible as we don’t expect the trout to approach the cameras in that

close of a range due to their skittish nature. However in the vertical blind spot

test there was a considerable amount of water that is missed by the cameras.

This test proved to be very important in developing the protocol for counting the

trout as it is common behavior for the trout to be near the surface hunting for

food. Because of this there was a decision to be made whether it was more

important for our video to cover more of the surface or of the substrate in the

streams. For our purposes in the warm Southern California summer we decided

to focus the study in the bottom half of the pool where the water may be slightly

cooler.

The simple design of the multiple camera configuration allowed the

system to have optimal portability when travelling into the remote backcountry

trout streams. This was such an integral part of the project as most of the areas

that are remaining in Southern California that have wild trout are in rarely

travelled areas that can be especially difficult to get to. It has been near

impossible to get heavy electrofishing equipment into these areas so accurate

population counts have not been attainable. Trout are very easily spooked so

having something that is so small and portable added to our stealth when

deploying the camera rig.

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One of the biggest concerns was how the trout would respond to our

testing equipment in their natural environment. The field tests at Lake Miramar

showed that many largemouth bass were very inquisitive of our cameras and

ROV but quickly adapted to it and swam nearby the camera rig and OpenROV

robot. This is consistent with speculation that bass are a much more curious fish

and studies that indicate different hunting techniques and life cycles than trout.

Pauma Creek where we did our initial testing embodied all of these

factors. The access point used on July 16 to Pauma creek was a trail that covered

almost 1000 vertical feet down to the stream and larger pools to get a more

accurate assessment of population counts. Once we reached the stream it was

flowing at less than 0.5 cubic feet per second. Also every time the water was

disturbed in the majority of these pools the trout would scatter into hiding

places, even doing this before the water was disturbed just by our presence.

However, in deeper sections trout were visible near the camera within one to

two minutes suggesting that they adapt to the camera presence quickly.

The problem of trout skittishness addressed in the tests by allowing the

pools to have a ‘reset period’ before accurate data could be collected after we

had disturbed the pool. When pools containing trout were approached, they

behaved normally until they detected stranger presence, and then swam into

hiding places out of sight. This ‘reset period’ was a five minute rest before we

started the timer on our survey. This decision was made after watching the

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preliminary footage of trout streams and seeing the behavior of the fish return

to a more stable and normal behavior in a time of roughly five minutes. This

information allows us to analyze the video more effectively as well by allowing us

to skip through a few minutes of raw data to the point at which the fish have

settled back into more normal behavior. We learned that these fish were also

very variable from one location to the next, theories about why this may be

include the amount of sun that the pool has on it, the depth of the water,

previous human contact, and water flow.

Another reason why this rest period is important in the running of these

tests is because of the silty substrate of this stream. When setting up the

cameras there were times where we would have to step into the water, and it

would kick up a lot sediment into the water column that brought down the

clarity of the water drastically. Because these tests hinged so heavily on visibility

this extra time allowed the water to settle back down and lower the turbidity we

had caused. Another factor that was discovered in this test was how light

conditions affected the camera’s ability to record clear video. It was discovered

that when light was coming towards the camera from overhead the visibility was

cut by more than half. This led to further subjectivity as to where to anchor the

cameras as putting them in a shady or indirect sunlight area was very important

to collecting clear data.

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One of the hardest parts of this experiment was finding a way to analyze

the data and quantify it as a number. A method used for quantifying snorkel

surveys and electrofishing is to calculate fish densities (fish/m2) and basin-wide

average density per species (Constable and Suring, 2007). This appears as a good

start to metrics for this study as it is still a work in progress to come up with an

effective method for quantification. Also maxN will be evaluated as this data is

analyzed, by taking stills from the video at increments in order to get an average

maximum of fish in the pool.

Analysis of the raw video data takes a longer than the originally expected

amount of time to analyze. This is due to the process of originally watching the

videos of an average length of 15 minutes then excising the clips of highest

densities followed by an analysis of the video done by a minimum of two people.

This process, though tedious, allows us to get concrete data from an otherwise

meaningless video. Also with extracted clips data can be presented in a much

quicker and more effective process. These clips can easily be circulated amongst

peers to get many peoples input if there is any controversy amongst the original

reviewer’s data. It is a task that most anyone can do and is a good way to get

involvement in a project about fish that need protecting from people who would

otherwise have no idea an issue ever even existed.

The openROV, when tested in Pauma Creek showed the piece of

equipment’s short comings in that environment, as it would be better suited for

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a bigger body of water, but also allowed us to capture a few very clear images of

trout in larger pools. Due to the skittish nature of these trout, their response

was very skeptical due to the buzzing of the propellers on the openROV. Beyond

the noise of it, it was difficult to use the camera for population counts because of

the lack of precision in its movements that are expected to be overcome with

the purchase of new components. It seems that there are other potential

applications for the openROV in larger river or estuarine systems that can’t be

accurately surveyed by cameras in a single location. They can also be fitted with

water chemistry sensors to transmit real-time data on water microenvironments

supplemented with visual documentation of aquatic organisms present to

position the system for behavioral analysis of aquatic organisms in unstudied

places.

Pauma Creek is currently impacted by drought conditions. This showed

the cameras’ optimal conditions to be used. With the stream being so low, a

majority of the trout were concentrated in the small pools throughout. When

these pools were snorkeled, the amount of sediment that was kicked up by the

diver allowed the fish to hide from sight and get lower count numbers than even

those informally taken when we walked up onto the pool and took note of the

fish visible from the surface.

There are plans to continue this study in Pauma Creek by going back to

the area where we did our testing and electrofishing a small sample of pools as

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further control studies. This will be done on pools that were marked with

flagging tape when doing our testing. This will help to calibrate the results that

we got from our video versus the snorkel surveys. Care will be taken to minimize

impact to fish, but is needed to test the accuracy of our protocol.

Underwater videography is the only form of surveying that can be done

without someone present in or around the water which seemed to be an

important part of getting accurate data. With cameras suspended in the water

without anything else to disturb them there is opportunity for more than just

population counts. Much is unknown about trout behavior especially these wild

fish that are disappearing and with these tests we have the rare opportunity to

watch them in their native environments. If this information can be attained, it

could lead to a better understanding of how to protect these fish and their

habitat.

There is hope that this survey study could be used to study the Southern

California Steelhead (Oncorhynchus mykiss) which are an ocean going rainbow

trout that come into fresh water to spawn. These fish have undergone a massive

decline due to fish barriers and declining habitats (Moyle et al, 2008). They are

only found in a couple of streams at this point and are very near extinction

(Jacobson et al, 2014). These fish are native to the San Luis Rey River so their

presence in our study was always thought to have future potential to try to

restore these fish if we can gain more knowledge about them and their habitat.

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Figure 7. The Southern California steelhead pictured here is one of the most endangered fish in the country with a population that has declined an estimated over 90 %( Moyle et al, 2008).

CONCLUSION:

In this study I experimented with a new form of population study to be

used on trout in slow moving pools that are located in remote backcountry

areas. This study used GoPro cameras as opposed to electrofishing and snorkel

surveys and is much less harmful to the fish and more accurate in these habitats.

While in the drought conditions that were tested in Pauma Creek, this new

method shows promise as a way to efficiently and accurately collect data while

keeping the stream habitat as pristine as possible. The results have preliminarily

proved this method to be effective and have opened up an avenue to many

future tests. There are plans to take this new protocol into a multitude of

Southern California streams with the hopes of gaining knowledge that will allow

us to better understand and protect native trout and steelhead for the

generations to come.

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REFERENCES:

Constable, Jr, R.J. and E. Suring. Smith River Steelhead and Coho Monitoring Verification Study, 2007. Monitoring Program Report Number OPSW-ODFW-2009-11, Oregon Department of Fish and Wildlife, Salem

Ellender, B.R., Becker A., Weyl, O.L.F. and E.R. Swartz (2012) Underwater video analysis as a non-destructive alternative to electrofishing for sampling imperilled headwater stream fishes. Aquatic Conserv: Mar. Freshw. Ecosyst. 22: pp. 58-65.

Hankin, D. G. and G. H. Reeves. (1988). Estimating total fish abundance and total habitat area in small streams based on visual estimation methods. Canadian Journal of Fisheries and Aquatic Sciences 45:834-844.

Jacobson, S., Marshall, J., Dalrymple, D., Kawasaki, F., Pearse, D., Abadia-Cordoso, A., and J.C. Garza (2014) Genetic Analysis of Trout (Oncorhynchus mykiss) in Southern California Coastal Rivers and Streams. Final Report for California Department of Fish and Wildlife, Project No. 0950015.

Moyle, P., Israel, J., Purdy, S. (2008) SOS: California’s Native Fish Crisis. California Trout. http://caltrout.org/pdf/SoS-Californias-Native-Fish-Crisis.pdf

Snyder, D. E. (2003). Electrofishing and its harmful effects on fish (No. USGS/BRD/ITR-2003-0002). GEOLOGICAL SURVEY RESTON VA BIOLOGICALRESOURCES DIV.

Staley, K., Mueller, M. (2000) Rainbow Trout (Oncorhynchus mykiss). United States Department of Agriculture. Web http://www.fws.gov/northeast/wssnfh/pdfs/RAINBOW1.pdf

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