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ABSTRACT

HUGHES, JACOB BRIAN. Combining Count Data from Split-beam and Multiple DIDSON

Sonar Techniques to Estimate Spawning Run Abundance of Anadromous Fishes in the

Roanoke River, NC. (Under the direction of Dr. Joseph E. Hightower.)

Riverine hydroacoustic techniques are a proven and effective method for evaluating

abundance of upstream migrating anadromous fishes. I used a combination of side-looking

split-beam and side- and down-looking DIDSON sonar count data in a Bayesian framework

to assess spawning run size of striped bass Morone saxatilis, American shad Alosa

sapidissima, hickory shad A. mediocris, alewife A. pseudoharengus, blueback herring A.

aestivalis, and semi-anadromous white perch M. americana, in the Roanoke River, NC

during 2010 and 2011. The Roanoke River, renowned for its recovered striped bass fishery,

historically supported regionally important fisheries for many of these anadromous species.

Today, American shad estimates are but a fraction of historical abundance and a harvest

moratorium is in effect for alewife and blueback herring due to low abundance. My goal for

this study is to produce reliable run-size estimates that can be used for management and

restoration efforts. To gather count data in mid-channel and near-bottom zones of the river, a

430 kHz split-beam transducer was aimed cross-channel. Long range capability is a major

advantage of split-beam sonar (relative to the DIDSON sonar), but river bottom unevenness

can result in ‗blind-spots‘. Also, in the near-range (< 10 m from transducer), narrow beam

width may reduce the ability to detect fish. I used a down-looking DIDSON sonar technique

to address blind-spots in split-beam coverage along bottom and monitor cross-channel and

vertical distribution of upstream migrants. Fixed-location, side-looking DIDSON sonar

monitored nearshore regions that exhibited higher densities of upstream migrants. Using a

Bayesian framework, I modeled sonar counts relative to their spatial distribution, simplified

into 4 cross-channel strata. Apportioning hydroacoustic counts by species was done using

species proportions from on-site boat electrofishing and gill nets and incorporating survey

gill net catch data from North Carolina Division of Marine Fisheries (NCDMF) in western

Albemarle Sound as a prior distribution. Using NCDMF data as a prior distribution reduces

uncertainty in estimates due to low and variable sample sizes from on-site species

composition sampling. My modeled estimates of total upstream migrants in 2010 and 2011

were 2.4 million and 4.2 million fish, respectively, considerably greater than prior

hydroacoustic estimates from 2004-2009. Run-size estimates for alewife and hickory shad

were similar to previous estimates, but American shad, blueback herring, striped bass, and

white perch were greater. Adding side-looking DIDSON on each bank improved precision

of estimates in nearshore regions with high numbers of upstream migrants. Incorporating

NCDMF survey data into the model stabilized estimates between years, unlike prior

hydroacoustic estimates for the Roanoke that were based on apportioned sonar counts from

on-site sampling only. Sonar applications targeting anadromous fish migrations are generally

restricted to rivers with relatively few species and ideal bank slope geometry, neither of

which is the case for the Roanoke River. This monitoring protocol and model should be

widely applicable to other river systems that are not well suited for traditional sonar

monitoring.

Combining Count Data from Split-beam and Multiple DIDSON

Sonar Techniques to Estimate Spawning Run Abundance of

Anadromous Fishes in the Roanoke River, NC

by

Jacob Brian Hughes

A thesis submitted to the Graduate Faculty of

North Carolina State University

in partial fulfillment of the

requirements for the degree of

Master of Science

Fisheries, Wildlife, and Conservation Biology

Raleigh, North Carolina

2012

APPROVED BY:

_______________________________ ______________________________

Dr. Brian J. Reich Dr. Jeffrey A. Buckel

________________________________

Dr. Joseph E. Hightower

Committee Chair

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BIOGRAPHY

Born and raised under the midnight sun in Fairbanks, Alaska, I developed a passion

for everything outdoors at an early age. As the oldest of three siblings, all brothers, there was

no shortage of outdoor play as we spent much of our youth at our parent‘s Salcha River cabin

chasing squirrels with BB guns and seeing who could catch the most arctic grayling. Fishing

has always been part of my life, but it was our cabin neighbor and Alaska Department of Fish

and Game sport-fish biologist, Jerry Hallberg, who first shed light on having a career as a

fisheries biologist. Needless to say, after hearing ―work‖ stories of hook and line sampling on

remote rivers and lakes, I was hooked.

After graduating from high school, I ventured to the ―Lower 48‖ and earned a B.S. in

Biology in 2007 from Eastern Oregon University and married my college sweetie shortly

thereafter. During and after college I worked seasonal fisheries technician jobs in Alaska,

Oregon, and Idaho before receiving a call from Dr. Joseph Hightower at NC State University,

offering me a graduate opportunity on the Roanoke River, NC. As with all my fisheries

experiences, North Carolina has been an incredible and unforgettable experience.

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ACKNOWLEDGMENTS

Funding for this project was provided by Dominion Power Company and North

Carolina Wildlife Resources Commission (NCWRC). Travel funding was awarded by North

Carolina Chapter of American Fisheries Society and the Joseph E. and Robin C. Hightower

endowment.

Completion of this project would not have been possible without the dedication and

hard work of fisheries technicians Joshua Ashline and Jacob Johnson. I sincerely thank them

for their efforts and optimistic outlook through long, hot, wet, toothy, and spiny field

seasons. Also, I thank Kyle Rachels, Joe Hughes, Gary Truman, and Taylor Jackson for

letting me trick them into helping with field work; your efforts are much appreciated. Also, I

would like to thank Michael Waine for crash courses in DIDSON and split-beam operations

and general wisdom on surviving the Roanoke River.

Many professionals from different agencies and organizations were essential in

completing my research. I cannot express enough thanks to Anna-Marie Mueller and Don

Degan of Aquacoustics for providing ideas and data processing help. I am very grateful for

fantastic assistance from the entire Echoview and Biosonics support staffs. I also thank Todd

Stuth and Hickey Brothers Fishing Inc. for building fantastic gill nets and Charlton Godwin

of North Carolina Division of Marine Fisheries (NCDMF) for providing monthly catch data

from NCDMF netting surveys.

My appreciation and thanks go out to the Gilliam family and Wayland Sermons Jr.

for use of their cabin on the Roanoke during 2010. Also, I thank Mary Outlaw and family for

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introducing me to true southern style cooking and sweet potato pie. I would like send a

special thanks to Maryanne Crowe for housing in 2011 and all her extended family and

friends for their hospitality, cookouts, and entertainment; I truly enjoyed their friendship.

Many staff and students at NC State University have helped on various parts of the

project and life in general. I thank Patrick Cooney, Joshua and Meredith Raabe, Jared

Flowers, Julie Harris, Ladd Bayliss, Michael Fisk, Nicholas Cole, Marybeth Brey, Dana

Sackett, and Lindsay Campbell. I am extremely grateful for the patience and immense

administrative support from Wendy Moore, who keeps me in line, on track, and under

budget! I thank Steve Williams for bailing me out numerous times with his computer fixing

abilities.

Input in study design and statistical analysis from my committee members Jeff

Buckel and Brian Reich have been invaluable to my research. I am grateful for their wisdom

and feedback, improving my thesis and professional development. I am forever indebted to

my advisor Dr. Joseph Hightower, for hiring me as a graduate student; I am extremely

fortunate to have been one of his students. Truly one of the greats, thank you Joe, for

everything.

Completing this degree has not been easy and certainly not possible without the love

and support of my family. As a proud parent to a beautiful 3 year old daughter, I‘d like to

apologize to my parents for whatever I put them through as a toddler! My deepest love and

gratitude goes out to my parents for encouraging and supporting me to follow my dreams, to

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my in-laws for their continued support and love, and especially to my wife and daughter for

their love, support, and willingness to put up with fish stuff all the time!

vi

TABLE OF CONTENTS

LIST OF TABLES ................................................................................................................ vii

LIST OF FIGURES ............................................................................................................... ix

INTRODUCTION................................................................................................................... 1

METHODS .............................................................................................................................. 6

STUDY SITE ............................................................................................................................ 6

HYDROACOUSTIC MONITORING ............................................................................................. 7 ACOUSTIC DATA PROCESSING ............................................................................................. 12 SPECIES COMPOSITION ......................................................................................................... 15 RUN SIZE ESTIMATES ........................................................................................................... 18

RESULTS .............................................................................................................................. 23

STUDY SITE .......................................................................................................................... 23

HYDROACOUSTIC MONITORING ........................................................................................... 23 ACOUSTIC DATA PROCESSING ............................................................................................. 26 SPECIES COMPOSITION ......................................................................................................... 27

RUN SIZE ESTIMATES ........................................................................................................... 29

DISCUSSION ........................................................................................................................ 31

HYDROACOUSTIC MONITORING ........................................................................................... 31 SPECIES COMPOSITION ......................................................................................................... 35

RUN SIZE ESTIMATES ........................................................................................................... 37

CONCLUSIONS ................................................................................................................... 43

REFERENCES ...................................................................................................................... 45

APPENDICES ....................................................................................................................... 96

vii

LIST OF TABLES

Table 1. Total number, mean length and standard error, and median distance off bottom for

all observed upstream migrants in DL DIDSON samples in 2010 and 2011 by location.

Locations are cross-channel station numbers (see Figure 5) .................................................. 53

Table 2. Total catch by species and gear in 2010 and 2011 in the Roanoke River, NC.

Highlighted species indicate target anadromous fish species classified as upstream migrants.

Anadromous fish determined to be post-spawn were classified as ‗spent‘ and assumed to be

out-migrating (downstream migrants), and are excluded from this catch table and further

analysis. ................................................................................................................................... 54

Table 3. Electrofishing dates of first and last capture by species, CPUE (fish/h), and

corresponding water temperatures for first, last, and maximum captures during 2010

sampling. ................................................................................................................................. 55



sampling. ................................................................................................................................. 55

Table 5. Bottom-set gill net dates of first, last, and maximum catches, CPUE (fish/net-hour),

and corresponding water temperatures for first, last, and maximum captures during 2010

sampling. ................................................................................................................................. 55

Table 6. Drift-gill net CPUE (fish∙drift-1

-set-1

) summary statistics and associated water

temperature in the Roanoke River, NC from February 24 to May 20, 2011 .......................... 56

Table 7. Mean length (mm) of anadromous species by gear during 2010 on the Roanoke

River, NC. ............................................................................................................................... 57

Table 8. Mean length (mm) of anadromous species by gear in during 2011 on the Roanoke

River, NC. ............................................................................................................................... 57

Table 9. Minimum, maximum, and mean daily CPUE (fish/h) for electrofishing in 2010 and

2011 on the Roanoke River, NC. ............................................................................................ 57

Table 10. Minimum, maximum, and mean daily bottom-set gill nets CPUE (fish/net hour)

and drift nets (fish/drift-set) 2010 and 2011 on the Roanoke River, NC. Drift set is defined

as one-200 m drift of each mesh size; two drift sets of four mesh sizes were conducted daily

and total catch was divided by 2 to calculate fish·drift-1

-set-1

. ............................................... 58

Table 11. Bottom-set gill net catch by species and mesh size captured in the Roanoke River,

NC from February 24 to May 20, 2010. Anadromous fish species include only those

classified as upstream migrants. Species titled ‗Other‘ refer to all non-target species

viii

captured. ALE=alewife, HSH=hickory shad, STB=striped bass, WPR=white perch,

OTH=other non-target species. ............................................................................................... 58

Table 12. Drift-gill net catch by species and mesh size from March 2 to May 20, 2011 in the

Roanoke River, NC. All drift gill nets were fished with equal effort. Anadromous fish

species include only those classified as upstream migrants. Species titled ‗Other‘ refer to all

non-target species captured. ALE=alewife, ASH=American shad, BBH=blueback herring,

HSH=hickory shad, STB=striped bass, WPR=white perch. ................................................... 59

Table 13. Modeled run size estimates and 95% credible intervals for 2010 and 2011. ......... 59

Table 14. Modeled parameter estimates and 95% credible intervals of intercept, gear

multipliers (SonarGear), and strata (XStrata) for 2010 and 2011. ―DL‖ = down-looking,

―SL‖ = side-looking. ............................................................................................................... 60

Table 15. Mean daily sonar count by stratum and overall mean count (standard error),

standardized to count∙m-2

∙d-1

, and ratio comparisons between sonar gears co-occurring in

strata. Abbreviations: DL= down-looking DIDSON, SL= side-looking DIDSON, and SB=

split-beam. ............................................................................................................................... 61

ix

LIST OF FIGURES

Figure 1. Location of sonar and fish sampling sites in 2010 and 2011 on the Roanoke River,

NC. Starting points for electrofishing transects are denoted by EF 1, EF 2, EF 3, and EF 4.

High current velocities and net fouling issues prompted the relocation of bottom-set gill nets

site #1 upstream to the inside bend of site #2 on March 17, 2010. ......................................... 62

Figure 2. Cross sectional view of the river profile, at hydroacoustic monitoring site (rkm

64)on the Roanoke River, NC. At full-bank river stage (shown), river width is 80 m. A

reference stake, used for standardizing fish detections from shore, was placed 80 m from the

west bank. . ............................................................................................................................. 63

Figure 3. Plot illustrating approximate split-beam deployment from February 24-May 20

2010. Split-beam was aimed cross channel, along river bottom for a 45-m range. Analyses

were restricted to 30 m to minimize effects of surface or bottom interference. Position of

split-beam unit moved inshore and out from shore as river level fluctuated. A fish diversion

fence (illustrated by black hatching from 65-80 m) was used to prevent fish from swimming

behind sonar. River level is illustrated at full-bank. .............................................................. 64

Figure 4. Plot illustrating approximate split-beam deployment from March 1-May 20 2011.

Split-beam was aimed cross channel using a 55-m range. Analyses were restricted to 30 m to

minimize effects of surface interference. Location of split-beam unit (red dot) was 19.05 m

from reference stake (~61 m from west bank) for the entire season. A fish diversion fence

was used to prevent fish from swimming behind sonar (illustrated by black hatching from 60-

80 m). River level is illustrated at full-bank. ......................................................................... 65

Figure 5. Illustration of DL DIDSON samples during 2010 and 2011 on the Roanoke River,

NC. Seven cross-channel samples were taken each weekday, 10 m apart, for 10 minutes

each. Sample locations are numbered 1-7, beginning closest to the west bank. Note, down-

looking DIDSON site is approximately 30 m downstream of split-beam site and river width

is 10 m wider than split-beam site. River level is illustrated at full-bank. ............................ 66

Figure 6. Plot showing approximate location and beam location of SL DIDSON deployed on

the east bank of the Roanoke River, NC during 2011. DIDSON was tripod mounted, 17.5 m

from the reference stake, and observed a range of 10 m beyond fish diversion fence with

bottom visible throughout window extent. River level illustrated at full-bank. .................... 67

Figure 7. Plot illustrating approximate location of west bank SL DIDSON monitoring. A 10

m window length was achieved, looking down the west bank slope with bottom visible from

2 m to window extent. Plot represents river at full-bank. Note, west bank SL DIDSON was

deployed at the same location as the DL DIDSON samples, approximately 30 m downstream

of split-beam and east bank DIDSON monitoring. No fish diversion fence was used on west

bank. River level illustrated at full-bank................................................................................ 67

x

Figure 8. Location of bottom-set gill nets in the Roanoke River, NC during 2010. High

current velocities and net fouling issues prompted the move of bottom-set gill nets site #1

upstream to the inside bend of site #2 on March 17, 2010. Red dot indicates location of sonar

site (inset map). ....................................................................................................................... 68

Figure 9. Illustration of cross-channel river profile (at full-bank water level) sectioned into 4

strata used to model count data from 2010 and 2011. ............................................................ 69

Figure 10. Approximate placement of all sonar gear types in 2011 with respect to river strata

(red numbers 1-4) for analysis of count data. Legend abbreviations are SL DIDSON = SL

DIDSON and DL DIDSON = down-looking DIDSON. For display purposes, DL DIDSON

beams are not drawn, but location of sample is represented by orange ovals and sample

location denoted by black numbers 1-7. Fish diversion fence illustrated by black hatching

from 60-80 m. ......................................................................................................................... 70

Figure 11. Gage height (m) measured at USGS gage station near Williamston, NC and river

discharge at Roanoke Rapids Dam, measured in cubic meters per second (m3/s), from

February 24 to May 20, 2010. ................................................................................................. 71


discharge at Roanoke Rapids Dam, measured in cubic meters per second (m3/s), from March

1 to May 20, 2011. .................................................................................................................. 71

Figure 13. Surface water temperature (ºC) measured during sampling days in 2010 and 2011

on the Roanoke River.............................................................................................................. 72

Figure 14. Daily split-beam counts, standardized to count·m-2

·day-1

by split-beam sonar

from February 24 to May 20, 2010 on the Roanoke River, NC. ............................................ 73

Figure 15. Daily split-beam counts, standardized to count·m-2

·day-1

by split-beam sonar

from March 1 to May 20, 2011 on the Roanoke River, NC. Estimated count for day 48

(April 17; no sonar coverage) is included and indicated by the open circle and dashed line. 73

Figure 16. Percent frequency of upstream fish tracks by hour detected by split-beam sonar in

2010 (solid black) and 2011 (dashed gray). ............................................................................ 74

Figure 17. Daily counts standardized to count/h to account for unequal sample time (i.e.,

missed sample location) of upstream migrants from DL DIDSON samples from February 23,

2010 to May 20, 2010. A total of 492 upstream migrants were observed. ............................ 74

Figure 18. Percent frequency of upstream migrants by location observed by DL DIDSON

samples from February 23, 2010 to May 20, 2010. Upstream migrants observed during days

with missed sampled locations were removed (N=38). Locations began 10 m from west bank

and progressed cross-channel at 10 m intervals. ..................................................................... 75

xi

Figure 19. Distance off bottom distribution of upstream migrants observed with DL

DIDSON samples from February 23 to May 20, 2010. .......................................................... 75

Figure 20. Length frequency comparison of 2010 electrofishing and gill net captured fish

versus DL DIDSON images of upstream migrants, manually measured using SMC software.

................................................................................................................................................. 76

Figure 21. Daily counts, standardized to count/h to account for unequal sample time (i.e.,

missed sample location), of upstream migrants from DL DIDSON samples from March 1,

2011 to May 20, 2011. A total of 1,583 upstream migrants were observed. ......................... 76

Figure 22. Cross-channel distribution of observed upstream migrants from DL DIDSON

samples in 2011. Upstream migrants observed during days with missed sampled locations

were removed (N=4). Locations began 10 m from west bank and progressed cross-channel at

10 m intervals. ......................................................................................................................... 77

Figure 23. Distance off bottom distribution of upstream migrants observed with down-

looking DIDSON samples from March 1 to May 20, 2011. ................................................... 77

Figure 24. Length frequency comparison for 2011 of electrofishing and gill net captured fish

versus DIDSON images of upstream migrants. Down-looking DIDSON images were

manually measured using SMC software. Length estimates from SL DIDSON images were

obtained through automated Echoview processing................................................................. 78

Figure 25. Corrected upstream migrant counts, from east bank (top) and west bank (bottom)

SL DIDSON, standardized to number of fish·hour-1

·m-2

to account for differences in

monitoring efforts across days in 2011. .................................................................................. 79

Figure 26. Snapshot image of east bank SL DIDSON monitoring on the Roanoke River, NC

during 2011. DIDSON data were recorded in high frequency (1.8MHz) at 7 frames·sec-1

, a

window start of 2.5 m, and a window length of 10 m. Bottom substrate is visible throughout

the entire field of view (left frame), eliminating concern of ‗blind spots‘ in sampled range.

Background subtraction (within SMC software) is enabled on the right frame. .................... 80

Figure 27. Frequency (%) of daily counts by hour (accounting for unequal sample effort

(days) across hours) from uncorrected east bank SL DIDSON monitoring during 2011.

Uncorrected counts were used to plot hourly passage because corrected counts were adjusted

on a daily scale, not hourly. .................................................................................................... 81

Figure 28. Snapshot image of SL DIDSON monitoring the west bank on the Roanoke River,

NC during 2011. DIDSON data were recorded in high frequency (1.8MHz) at 8 frames/sec,

a window start of 0.42 m, and a window length of 10 m. Substrate along the bank and

bottom is visible from 2 m to end of window length in left pane. Background subtraction

(within SMC software) is enabled in the right panel to better illustrate fish in the frame. ..... 82

xii

Figure 29. Correction factor analysis based on automated counts (Echoview‘s fish tracking

algorithm) versus manual counts: Panel A, 2010 split-beam; Panel B, 2011 split-beam; Panel

C, east bank SL DIDSON period 1; Panel D east bank SL DIDSON period 2; Panel E, east

bank SL DIDSON period 2 re-fit; Panel F, west bank SL DIDSON. Counts for which the

regression intercept was not statistically different than zero and slope not statistically

different than 1.0 were not corrected (panels A, B, F). There was no detectable relationship

between automated and manual counts from east bank SL DIDSON during Period 1 (March

1-11; Panel C); therefore average manual count (accounting for time and area sampled) were

applied to all days during Period 1. Automatic counts from east bank SL DIDSON (EB

DIDSON) during Period 2 (March 12-May 20; Panel E) were corrected using the estimated

slope from the refit regression. Red-dotted line represents one-to-one line and black line

represents fitted regression. .................................................................................................... 83

Figure 30. Proportion of species captured by electrofishing and bottom-set gill nets from

February 23-May 20, 2010 (top panel) and electrofishing and drift gill nets from February

28-May 20, 2011 (bottom panel) on the Roanoke River, NC. Species abbreviations are:

ALE=alewife, ASH=American shad, BBH=blueback herring, HSH=hickory shad,

STB=striped bass, WPR=white perch, OTH=other. ............................................................... 84

Figure 31. Electrofishing CPUE (fish/h) for targeted anadromous species and non-target

species from February 24 to May 20, 2011 in the Roanoke River, NC. ................................. 85

Figure 32. Electrofishing CPUE (fish/h) of targeted anadromous fish species from February

24 to May 20, 2010. Species abbreviations are: ALE=alewife, ASH=American shad,

BBH=blueback herring, HSH=hickory shad, STB=striped bass, WPR=white perch. ........... 85

Figure 33. Boat electrofishing CPUE (fish/h) for targeted anadromous species and non-target

species from March 1 to May 20, 2011 in the Roanoke River, NC. ....................................... 86

Figure 34. Electrofishing CPUE (fish/h) of targeted anadromous fish species from March 1

to May 20, 2011. Species abbreviations are: ALE=alewife, ASH=American shad,

BBH=blueback herring, HSH=hickory shad, STB=striped bass, WPR=white perch. ........... 86

Figure 35. Bottom-set gill net CPUE (fish/net-hour) of target and non-target species during

2010 on the Roanoke River, NC. Net site #1 was fished through March 16, 2010. From

March 17-May 19 all nets were set at net site # 2. ................................................................. 87

Figure 36. Bottom-set gill net CPUE (fish/net hour) for individual target species during 2010

on the Roanoke River, NC. Species abbreviations are: ALE=alewife, HSH=hickory shad,

STB=striped bass, WPR=white perch. ................................................................................... 87

Figure 37. Drift gill net CPUE (fish/drift-set) of target anadromous species and non-target

species from March 2-May 20, 2011 in the Roanoke River, NC. Drift-set is equivalent to

each mesh size drifted once on a given day. ........................................................................... 88

xiii

Figure 38. Individual species‘ drift gill net CPUE (fish/drift-set) of target anadromous

species and OTH (non-target species) from March 2-May 20, 2011 in the Roanoke River,

NC. Drift-set is equivalent to each mesh size drifted once on a given day. .......................... 88

Figure 39. Daily median (solid line) modeled run size estimates (in thousands) with 95%

credible intervals (dotted lines) for targeted anadromous fish in 2010. ................................. 89


credible intervals (dotted lines) for targeted anadromous fish in 2011. ................................. 89

Figure 41. Hydroacoustic species specific run-size estimates for all eight years of

hydroacoustic monitoring on the Roanoke River (2004-2011). Error bars represent 95%

confidence intervals (a), 90% credible intervals (b), and 95% credible intervals (c). Alewife,

blueback herring, and white perch run-size were not estimated in 2004-2005. No confidence

intervals were available for 2004 estimates. ........................................................................... 90

Figure 42. Hydroacoustic total upstream migrant run-size estimates for all eight years of




intervals were available for 2004 estimates (Mitchell 2006). ................................................. 91

Figure 43. Ratio of standardized counts (black line; fish·hour-1

·m-2

) between split-beam and

east bank (stratum 1) SL DIDSON during 2011. Blue line indicates water level (m),

measured at USGS gage 02081054 at Williamston, NC. ....................................................... 92


credible intervals for targeted anadromous fish in 2010. Note y-axis not uniform between

species. .................................................................................................................................... 93

Figure 45. Daily median (solid line) modeled run size estimates in thousands with 95%

credible intervals for targeted anadromous fish in 2011. Note y-axis not uniform. .............. 94

Figure 46. Proportion of non-target species from our in-river catch (NCSU, red) and the

modeled estimate (green) with 95% credible intervals during 2010. ..................................... 95


modeled estimate (green) with 95% credible intervals during 2011. ..................................... 95

1

INTRODUCTION

Anadromous fishes are ecologically, economically, and culturally important species,

spending a majority of their lives in the ocean and migrating to freshwater to spawn. Perhaps

the best known anadromous species are the Pacific salmon, some of which migrate over

2,500 kilometers (km) up freshwater to spawn (Milligan et al. 1986). Because of their vast

migrations, anadromous fishes provide valuable links to terrestrial environments and serve as

transporters of marine-derived nutrients to freshwater watersheds (Willson and Halupka

1995; Garman and Macko 1998; Willson et al. 1998; Gende et al. 2002; Naiman et al. 2009;

Quinn et al. 2009). Many anadromous species along the US East Coast once supported large

commercial fisheries, but several anthropogenic influences such as overfishing, water quality

degradation, and loss of spawning habitat, have caused major declines in abundance

(Limburg et al. 2003; Limburg and Waldon 2009). As an example, landings of alewife Alosa

pseudoharengus and blueback herring A. aestivalis (collectively termed ―river herring‖),

have declined from an average 25,000 metric tons from 1950-1969 to 1,000 metric tons in

2000 (Schmidt et al. 2003). In response to declining fisheries, major restoration and

monitoring programs have been established. Improving population assessments of

anadromous species is extremely important to guide fishery management and assess

restoration objectives.

The Roanoke River is a major river in the Mid-Atlantic region of the U.S east coast,

supporting populations of several anadromous fish species: striped bass Morone saxatilis,

American shad A. sapidissima, hickory shad Alosa mediocris, alewife, blueback herring, and

2

semi-anadromous white perch M. americana, all of which sustained fisheries at some time.

Striped bass abundance, once greatly diminished, was declared recovered in 1997 and was

estimated to be at record abundances in 2008 (Tekade-Heumacher 2010). Supporting a

commercial fishery in Albemarle Sound and a world renowned recreational fishery, striped

bass of the Roanoke River are an important resource for the region and a restoration success

story. American shad supported large fisheries beginning in the late 1800s (Walburg and

Nichols 1967; Hightower et al. 1996), but populations in Albemarle Sound which includes

the Roanoke River have declined substantially since the early 1900s (Hightower et al. 1996;

ASMFC 2007),and are currently a fraction of their historical abundance despite major

restoration efforts. River herring once supported large commercial and recreational landings,

but declining populations since the 1970s (Hightower et al. 1996) prompted the North

Carolina Division of Marine Fisheries (NCDMF) to implement a moratorium on recreational

and commercial harvest in 2007. Excessive fishing, loss of spawning habitat due to

hydroelectric dams, and deteriorating water quality have been attributed to declines of

anadromous fish in the Roanoke River (Walburg and Nichols 1967; Winslow 1990).

Spawning migrations of anadromous fishes offer an excellent opportunity to assess

their status due to accessibility in freshwater rivers. Upstream spawning migrations of

anadromous fish in the Roanoke River begin in late winter and continue through spring with

most spawning completed by mid-June. The progression of anadromous species generally

begins with hickory shad during late winter and early spring, typically spawning in shallow

water habitats near Roanoke Rapids (river kilometer (rkm) 217) and Weldon (rkm 209) at

3

water temperatures of 12-16o C (Burdick and Hightower 2006; Harris and Hightower 2007;

Harris 2010). Alewife are next in the progression of anadromous fishes, entering the

Roanoke in early March and primarily spawning in lentic waters such as sloughs or slow

flowing tributaries and flooded bottom lands, at water temperatures ranging from 11 to 22oC

(Street et al. 1975; Walsh 2005). Blueback herring enter freshwater rivers later than alewives

and exhibit similar spawning requirements, but often utilize lotic as well as lentic waters

(Walsh 2005). White perch are prevalent in the lower Roanoke River for much of the spring,

with abundance peaking during April (Magowan 2008; Waine 2010). Spawning locations of

river herring and white perch are not well defined in the Roanoke and it is believed that they

spawn in preferred habitats as they are encountered during their upstream migration, with

abundance decreasing as distance upstream increases (Hewitt 2003; Mitchell 2006). Striped

bass begin their spawning migration during late March and April, spawning near Weldon,

from late April to early June when water temperatures reach approximately 17-20oC

(Rulifison 1991; Carmichael et al. 1998). American shad spawn primarily in the Roanoke

Rapids area from May through June when water temperatures are between 15 and 25oC

(Sparks 1998; Hightower and Sparks 2003; Harris and Hightower 2010). Prior to dam

construction near Roanoke Rapids, American shad spawned as far upstream as rkm 557, near

Salem, VA (McDonald 1878).

Monitoring the migration of anadromous fishes is difficult in most southeastern

rivers, including the Roanoke River, due to channel morphology, turbid water, and bottom

obstruction and snags, making it difficult to deploy gill nets or other live capture gear.

4

Hydroacoustics, or underwater sonar, is a non-intrusive alternative that uses transmitted

sound in water to monitor aquatic physical and biological objects, such as fish (Brandt 1996;

Simmonds and MacLennan 2005). Objects with a density different than water reflect the

emitted sound pressure which is then received by the transducer and processed by the

echosounder and computer system. Ideally, sonars are deployed in areas that have laminar

flow, encouraging active fish migration past the site (i.e., no milling; Enzenhofer and

Cronkite 2000). Hydroacoustics offers an opportunity for directly enumerating population

size, unlike catch per unit effort (CPUE) indices (e.g., gill netting, trawling, creel census)

which are effective for monitoring long-term trends and large changes in abundance (Pine et

al. 2003).

Common types of sonar systems for monitoring fish populations include split-beam

and more recently, multi-beam. Split-beam sonar data can be difficult to interpret, but can

position targets in three-dimensional space, obtain directional movement, as well as other

acoustic and behavioral information such as target strength (TS) and swimming speed

(Ransom et al. 1998; Simmonds and MacLennan 2005), all very important components for

monitoring migratory fish. A series of temporally and spatially correlated returning echoes

from a fish are grouped or ―traced‖ to construct a ―fish-track‖ representing a single fish in the

beam (Ehrenburg and Torkelson 1996). Multi-beam sonars on the other hand, such as Dual

Frequency Identification Sonar (DIDSON; Sound Metrics Corporation, ―SMC,‖ Lake Forest,

WA.), capture high resolution, near-video quality images, even in turbid or dark water

(Belcher et al. 2001). Images are captured in either high frequency (1.8MHz) or low

5

frequency (1.1 MHz), the former having a shorter range ( <15 m), but better image quality.

Aside from near-video quality images, advantages of the DIDSON sonar are a large beam

width compared to traditional sonar systems, ease of interpretation of data (Boswell et al.

2008), ability to simultaneously image and discern substrate and fishes (Boswell et al. 2008),

and the ability to directly measure fish in the beam during post-processing (Holmes et al.

2006; Burwen et al. 2010). Regardless of sonar type, fixed-location hydroacoustics is an

effective and proven method for assessing in-river migratory fish in which sonar beams are

aimed cross-channel and along river bottom to enumerate migrating fish (Daum and Osborne

1998; Enzenhofer et al. 1998; Ransom et al. 1998; Romakkaniemi et al. 2000; Burwen et al.

2003; PACE 2003; Belcher 2004; Simmonds and MacLennan 2005; Xie 2005; Holmes et al.

2006; Kerkvliet et al. 2008).

A main challenge of hydroacoustic assessments is the difficulty or inability to

distinguish species directly (Romakkaniemi et al. 2000; Mueller 2010). Differences in

acoustic size (target strength), body morphology, length, run timing, or position in the water

column, can sometimes be used to separate acoustic data by species (Burwen and Bosch

1995; Miller et al. 2003; Burwen et al. 2003 ). However, many southeastern rivers contain

numerous migratory species that overlap in length and run timing, making it difficult to

utilize hydroacoustic technology to derive species-specific abundance estimates. The

standard approach is to use additional sampling (e.g., electrofishing, gillnetting) to obtain

species composition estimates that can be applied to hydroacoustic data and verify targets

(Simmonds and MacLennan 2005; Baldwin and McLennan 2008; Parker-Stetter et al. 2009).

6

This study is the final leg in eight years of hydroacoustic monitoring on the Roanoke

River. The previous three studies (2004-2005: Mitchell 2006; 2006-2007: Magowan 2008;

2008-2009: Waine 2010) showed the potential for hydroacoustic monitoring, but further

improvements in spatial coverage and species allocation of sonar counts are needed. My

objectives were to build on the prior studies but use multiple DIDSON deployments in order

to obtain reliable estimates of spawning run-size for the suite of anadromous fishes in the

Roanoke River. These acoustic derived estimates serve as important alternative and

supplemental assessments to widely used fishery-dependent surveys and stock-assessments.

Results from this study will aid in harvest management of striped bass and will serve as an

independent check on traditional stock assessment results. The results will also be helpful in

assessing American shad restoration efforts as part of Federal Energy Regulatory

Commission (FERC) relicensing agreement with Dominion Power for operation of the

Roanoke Rapids and Gaston hydroelectric dams. Also, modeled estimates of river herring,

hickory shad, and white perch serve as the only current abundance estimates for the Roanoke

River. Beyond the Roanoke, methods used in this study should be applicable to other

southeastern rivers in need of anadromous fish monitoring programs.

METHODS

Study Site

Originating in the mountains of western Virginia, the Roanoke River flows southeast

to its confluence with Albemarle Sound, NC, draining approximately 24,812 km2 of land.

Roanoke Rapids Dam (rkm 221) is a hydroelectric facility and the lowermost dam on the

7

Roanoke River. Located just upstream of primary spawning grounds for American shad

(Roanoke Rapids 217 rkm) and striped bass (Weldon 209 rkm), Roanoke Rapids Dam blocks

upstream migration. My hydroacoustic study site was near Williamston, NC at rkm 64

(Figure 1). The sonar site experiences laminar flow (minimizing milling behavior of fishes)

and is located below known spawning areas for anadromous species, ensuring active fish

migration past the sonar site. Furthermore, the site is upstream of the entrance to alternate

channels such as Conine Creek, forcing migrants to swim past the sonar site. Generally

speaking, the river bottom profile exhibits preferred characteristics for fixed-location

hydroacoustics (Enzenhofer and Cronkite 2000); however, ―blind spots‖ were a concern at

the split-beam sonar location due to river bottom unevenness. The split-beam sonar was

located on the east bank, which has a much gentler slope than the west bank (Figure 2). The

river at this location has a maximum channel depth of about 11 m and a total width of 80 m

at flood stage (full-bank). Sonar unit position measurements and fish tracks were referenced

to a stake placed on the east bank at the high-water mark (80 m from the west bank). U.S.

Geological Survey (USGS) river gage 02081054 at Williamston, NC was used to determine

water level.

Hydroacoustic Monitoring

Split-beam and DIDSON sonar systems were used to monitor upstream migrating

fishes. Deployment of the split-beam sonar system was similar between years. A down-

looking (DL) DIDSON deployment was used in both years and a side-looking (SL) DIDSON

8

deployment was added in 2011. Hydroacoustic data were collected from February 24 to May

20, 2010 and March 1 to May 20, 2011.

Split-beam. —A split-beam echosounder delivers an electrical transmission pulse to

the 4-quadrant transducer, which then transforms the electrical energy into sound pressure

emitting the signal from the transducer face as a whole. Objects with a density different than

water will reflect the sound pressure (returning echoes) to the transducer face. Differences

among quadrants in the time of receiving signals allows for 3-dimensional positioning and

tracking of targets within the beam (Simmonds and MacLennan 2005). An advantage of the

split-beam is that it can monitor a relatively long range, as long as the beam fits between the

water surface and river bottom.

The split-beam system used in this study was a 430 kHz Biosonics split-beam

echosounder (Biosonics, Inc., Seattle, WA) with a 7º circular transducer. The transducer was

mounted on a fixed H-frame and deployed on the east bank aimed cross-channel,

perpendicular to flow. Data collection occurred 24 h/d for the length of the season, except

during equipment maintenance and sonar malfunction. Sound transmission was pulsed at 10

pings/s, using a pulse width of 0.2 ms. A -70 dB sensitivity threshold was used for returning

echoes. Visual Acquisition software (version 6.0, Biosonics Inc.) recorded data, logging a

.RTPX data file every 20 minutes. Data were transferred at least once a week onto an

external hard drive. A battery bank and Honda EU2000i generator provided power to sonar

and laptop computer.

9

In 2010, the sonar beam was aimed close to, but off river bottom, with a 45 m range

(Figure 3). Excessive bottom reverberation restricted analysis to 30 m. The transducer was

placed in approximately 1.5 m of water, 0.2 m off bottom, and was moved up or down the

bank as river levels fluctuated to ensure the transducer remained submerged (range 12-16.75

m from reference stake). In 2011, the split-beam was deployed 19.05 m from the reference

stake for the entire season. Lower river stage during the beginning of 2011 field season

enabled split-beam placement farther from shore than in 2010. Due to placing the split-beam

unit farther from shore in 2011, the sonar beam was aimed farther off bottom than 2010 to

achieve a range of 55 m (figure 4) to attempt to monitor a large portion of the river cross-

section. However, water surface reverberation restricted analysis to 30 m.

Daily metrics at the sonar site included water temperature, transducer distance to

reference stake and water line, water depth at transducer, transducer depth, and in-unit

readings of transducer pitch, roll, and compass heading. To prevent fish from swimming

behind and around the sonar unit, a weir-fence, constructed of 5-cm square construction

fencing, was installed 1 m downstream and extended 1.5 m beyond the split-beam in 2010

and 1 m in 2011. The position of the fence changed in 2010 whenever the split-beam unit

was repositioned.

DIDSON — A standard DIDSON imaging sonar was used in down-looking and SL

deployments. The sonar was operated in the high frequency (1.8 MHz) mode, which

provides the best quality images but limits range to 15 m. The field of view (FOV) for a

standard DIDSON is 29º horizontal (H) x 14º vertical (V), but a 28º spreader lens was used

10

during this study to increase FOV to 29º H x 28º V, essentially doubling the vertical

dimension. DIDSON images are constructed using an acoustic lens system and 96 0.3º wide

beams that simultaneously transmit and receive eight sets of 12 beams (Belcher et al. 2001,

Burwen et al. 2007). DIDSON data are collected and displayed in 2-dimensions, with

resolution in the X and Y dimensions (horizontal and range), but not in the Z-dimension

(vertical). A horizontal deployment allows determination of range on the Y-axis (distance

from DIDSON) and direction of travel as fish move across adjacent beams along the X-axis.

Down-Looking DIDSON— Cross-channel and off-bottom distributions of upstream

migrants were assessed using a DIDSON sonar (1.8 MHz) in a DL aspect. The DIDSON

unit was deployed 60 cm below water surface to a pole attached to the boat‘s stern. Daily

samples (M-F) were taken at 7 cross-channel locations, spaced 10 m apart beginning 10 m

from the West bank (Figure 5). Each location marked by an anchored buoy was sampled 5

d/week for 10 min/buoy, beginning at the westernmost buoy (location 1) and proceeding in

order to the east bank. Start times for 2010 DL DIDSON monitoring were randomly selected

and restricted to daylight hours (0600-1800 hours). In 2011, start times occurred near mid-

day (1000-1400 hours), revolving around SL DIDSON monitoring protocol (see below).

Direction of travel (upstream or downstream) of fish was attainable because the X-axis was

parallel to river flow, meaning a fish would pass through adjacent beams as they traveled up

or downstream. Power to the DIDSON and laptop was provided by a 12V battery through a

350-watt DC to AC power inverter.

11

Side-Looking DIDSON— Monitoring nearshore regions was conducted in 2011 using

the DIDSON (1.8 MHz) in a SL aspect. Both banks were monitored for a subset of days or

hours. The east bank exhibited a gentler slope than the west bank and allowed for a

stationary tripod DIDSON mount (Figure 6). The West bank slope was too steep for tripod

use and therefore required a boat mount using the same pole mount used for DL DIDSON

sampling (Appendix Figure 1). The DIDSON was angled along the river bottom slope so

that bottom edges of beams grazed the river bank for the entire window length (Figure 7).

East bank monitoring occurred March 2-March 20, 2011. Data were recorded every

Friday afternoon to Monday morning and a minimum of one additional night from Tuesday-

Thursday. The DIDSON was mounted horizontally on a tripod stand, 50 cm off river

bottom, and 17.5 m from the reference stake, between the split-beam and fence-weir. The

fence-weir extended 2.6 m beyond the DIDSON unit, leading to a window start of 2.5 m and

window length of 10 m, collected at 7 frames/s. Data were logged in 20-min files onto a

portable external hard drive. A Honda EU2000i generator connected to a 6-gallon auxiliary

fuel tank provided power to the DIDSON and laptop for weekend sample periods. Attaching

an auxiliary fuel tank allowed sample periods to extend up to 72 h.

West bank monitoring occurred March 8-May 20, 2011. A minimum of 4 h/d were

monitored during week days, generally starting before 0900 hours (morning hours) or after

1300 hours (afternoon hours). Afternoon hours were monitored following DL samples

during Mondays and Thursdays, and four Tuesdays (March 8, 15, April 5, May 10).

Morning hours were monitored Wednesdays and Fridays and remaining Tuesdays (i.e., those

12

not monitored during afternoon). Data were collected at 8 frames/s with a window start of

0.42 m and a window length of 10 m and logged in 20 min files onto a portable external hard

drive. The boat was anchored at the bank, tied to two poles along the starboard gunwale,

providing stability against river currents and boat wakes. The DIDSON was angled

approximately -45º below horizontal, but varied between days (-38º to -51º), to ensure that

the bank was visible throughout the range of view. The unit was deployed at a depth range

of 36-42 cm, and 1.7 m from shore. A Honda EU2000i generator provided power to the

DIDSON unit and laptop computer.

Acoustic Data Processing

Split-beam acoustic data files were imported and post-processed in Echoview

software (version 5.1 Myriax Software Pty Ltd., Australia). Built-in fish tracking algorithms

were used, with the same settings for identifying fish tracks as previous years (Magowan

2008; Waine 2010). Due to a large volume of data (>80 days), file processing and fish

tracking was automated using Echoview‘s scripting module. The script identified each fish

track and associated acoustic variables including date and time, target strength, horizontal

direction, tortuosity, duration in beam, and angle of deviation from beam axes (Waine 2010).

Due to transducer orientation, fish exhibiting a horizontal direction of movement between

225º and 315º

were classified as upstream migrants (Magowan 2008). Upstream and

downstream fish tracks were separated based on horizontal trajectory, and further analysis

was restricted to upstream fish only.

13

Down-looking DIDSON data were processed manually using DIDSON software

version 5.23 (Sound Metrics Corporation ―SMC,‖ Lake Forest Park, WA). Images were

played back (up to 10x recording speed) until a fish moving upstream was detected. High

quality images (Appendix Figure 2) allowed a variety of measurements to be made with the

manual measuring tool within SMC software. Measurements included: range to river

bottom, fish depth, and total fish. Data were written as unformatted text files and exported

into Microsoft Excel and JMP (SAS Institute Inc., version 8) for data management and

analysis.

Side-looking DIDSON data were processed using Echoview software. Both east

bank and west bank DIDSON files were processed automatically, using an Echoview

template similar to Boswell et al. (2008) (Appendix Figure 3). An automated script module,

similar to split-beam processing, was used to process and export fish tracks and associated

variables from SL data due to large volumes of data. Because multi-beam sonars, such as the

DIDSON, can be used to estimate lengths of individual fish, a 20-cm length threshold was

used to export data for fish ≥ 20cm as a .csv text file. All exported .csv files were

concatenated into a single file and uploaded into JMP for analysis. Due to transducer

orientation, fish determined to be upstream migrants had a horizontal direction of travel of

0º-180º on the east bank and 180º-360º on the west bank. Fish were separated by direction of

travel and analysis was restricted to upstream migrants.

To determine misclassification rates of automated fish tracking algorithms used for

split-beam and SL DIDSON count data, I manually reviewed a subset of files. For split-

14

beam data, one AM (0000-1159 hours) and one PM file (1200-2359 hours) per week were

chosen randomly for manual inspection. I inspected counts for accuracy, using the single

target detection variable inside Echoview. For example, a series of single target echoes that

clearly appeared to represent a single fish but had been classified as two fish would be

corrected. Also, if a series of single targets that appeared to be a fish track but did not meet

the required criteria for the fish tracking algorithm would be corrected to be a fish track.

Corrected counts were compared to automated counts using linear regression. An intercept

not significantly different from zero (within 2×Standard Error (SE) of zero) and a slope not

different from 1(within 2×SE of one) indicated that automated fish counts did not need to be

‗corrected‘ for over- or under-counting bias by the fish tracking algorithm. An intercept not

significantly different from zero, but a slope significantly different from 1, would indicate a

bias in automated counts. To correct for this bias, the equation was re-fit without an intercept

and the resulting slope was used as a correction factor applied to each day‘s automated count.

For 2011 east bank SL DIDSON counts, I manually processed the first 5 minutes of a

20-minute file to reduce processing time. Large schools of milling fish, presumably

longnose gar Lepisosteus osseus due to length and body shape, during the first part of the

season when water levels were lowest (March 1-11) were visible in DIDSON files and

resulted in excessively high fish counts (Appendix Figure 4). For this reason, east bank files

were separated into a longnose gar period (weeks 1-2) and post-longnose gar period (weeks

3-12). Because the SL DIDSON was not deployed continuously, three time periods

consistently observed during east bank DIDSON monitoring were selected for manual count

15

comparison; 0700, 1900, and 0000 hours. For weeks 1 and 2 (longnose gar period) the 1st,

2nd

, and 3rd

occurrences of the selected hours (0700, 1900, and 0000 hours) were selected to

be manually processed. During the post-longnose gar period (weeks 3-12), the 1st and 2

nd

occurrence of the selected hours (0700, 1900, and 0000 hours) were manually processed.

Fewer subsets per week were selected during the post-longnose gar period because more

weeks were available to analyze subsamples. As above, a linear regression of manual versus

automated counts was used to evaluate bias due to automated fish tracking. For the period

in which there was not a significant relationship between manual and automated counts (see

Results), a simple average of manual counts was used.

West bank SL DIDSON assessment of automatic counts was accomplished by

analyzing the first 5 minutes from two samples per week. Date of sample was chosen at

random, but restricted to include one AM file and one PM file per week.

Species Composition

Boat electrofishing and gill nets were used to obtain fish species composition data at

sites upriver of the sonar site, ensuring that sampling would not affect sonar counts.

Recorded fish data included: species, sex and spawning condition of anadromous fishes

(green, ripe, spent), total length, sample gear, location, date, water temperature (oC), and

water conductivity (µs). To determine reproductive stage of anadromous fishes, slight

pressure was applied along the abdomen (Acolas et al. 2006). Reproductively ‗spent‘, or

post-spawn, anadromous fishes were classified as outmigrating and were not included in any

analyses or summary statistics.

16

Electrofishing— Boat electrofishing was conducted 5d/week from February 24 to

May 20, 2010 and March 1 to May 20, 2011. A 7.5 Generator Powered Pulsator (GPP)

Smith-Root electrofishing system was operated with 1000 volts of pulsed DC current at 60

pulses/s to maintain 4 to 5 amperes. Four shoreline areas were sampled throughout each

season (E1, E2, E3, and E4; Figure 1). Bank morphology classified each bank into cut bank

(E1 and E3) or flat bank (E2 and E4) (Magowan 2008). Two transects, representing opposite

bank morphology, were sampled each day for 900 s each. Sampled transects alternated by

day (e.g., day 1 transects E2 and E3; day 2 transects E1 and E4) as did start times (morning

or afternoon). CPUE was calculated as fish/h with immature or reproductively spent target

species excluded from analysis.

Gill netting— Bottom-set gill nets were deployed in 2010 to sample near-bottom

regions that indicated higher proportion of upstream migrating fish (Waine 2010). High

flows in 2010 created fouling issues and excessive net damage and therefore bottom-set gill

nets were discontinued in 2011. Drift gill nets were used in 2011 to reduce fouling and

damage concerns. Lower flows in 2011 enabled drift nets to effectively sample mid-channel

near-bottom regions of the river. Gill netting was concentrated either in morning or

afternoon, in the period opposite of electrofishing for a given day.

Bottom-set gill nets, deployed from March 1 to March 17, 2010, were set 2.5 rkm

above the hydroacoustic monitoring site, parallel to river current and soaked for 0.5 h

(Figures 1, 8). Due to flood-stage flows, nets fouled quickly with leafy and woody debris,

which prompted the net site to be moved upstream to a river bend that provided mild refuge

17

from high current velocities. From March 19 to May 20 nets were set for 1 h, 3.25 rkm

above the sonar site (Figure 8). Beginning with the furthest-upstream set, nets were set in

random order, parallel to slightly-angled to river current. Five nets, each 2.5 m tall x 46 m

long of individual mesh sizes (7 cm, 9 cm, 10 cm, 11.5 cm, and 14 cm stretched) were set 3

d·week-1

. All mesh sizes were fished unless a net was damaged and needed repair. No less

than 3 nets were fished on days with damaged nets to repair.

Drift gill netting was conducted 2.5 rkm above the hydroacoustic monitoring site 5

d/week from March 1 to May 20, 2011 (Figure 1). The drift net site was a straight stretch of

river with approximately 400 m of unobstructed bottom consisting of 2 m high rolling sand

hills. Maximum depth was 8.5 m during high flow and minimum depth was 4.5 m during

low flow. Four nets 7.3 m tall x 23 m long of individual mesh sizes were used (7 cm, 9, cm ,

10 cm, and 14 cm). Two-200 m drifts of each mesh size were deployed daily with same

mesh sizes drifted subsequently to each other and overall drift order chosen randomly on

each day (e.g., 7 mm, 7 mm, 10 cm, 10 cm, 14 cm, 14 cm, 9 cm, 9 cm). Daily CPUE was

calculated as fish/set where ‗set‘ equals the combined catch from all drifts divided by 2 to

account for two drifts of each mesh. Combining the catch across mesh sizes is intended to

reduce bias due to mesh size selectivity (Hubert 1996).

Additional species composition data used in modeling run size estimates were

acquired by North Carolina Division of Marine Fisheries (Charlton Godwin, NCDMF).

Annual fishery-independent gill net surveys targeting striped bass are conducted in western

Albemarle Sound by NCDMF (Takade-Heumacher 2010). Only monthly sample data were

18

available. Catches from mesh sizes 6.35 cm-14 cm were used to best match the gill net mesh

sizes used in my sampling. Because of the lack of current in Albemarle Sound, NCDMF

netting was much more effective with larger sample sizes and less variability than my in-

river species composition sampling.

Run Size Estimates

River Strata-To model upstream counts, the river cross-section was stratified into 4

zones based on cross-channel and water column distributions of fish: 2 nearshore strata

(strata 1 and 2), mid-channel ≤1 m from bottom (stratum 3), and mid-channel >1 m off

bottom (stratum 4) (Figure 9). Each stratum had at least one sonar deployment, with strata 1

and 4 having 2 gears in 2010 and stratum 1 containing 3 sonar deployments in 2011 (Figure

10). In both years, DL DIDSON has the most important role because it is the only gear used

in all four strata. Stratum 1 began at the end of the fence weir and extended to 30 m from the

reference stake (50 m from west bank). Due to transducer movement and fence-weir

relocation as water levels fluctuated in 2010, stratum 1 area (m2) varied in relation to its near-

shore boundary (end of fence weir). Stratum 2 began at the west bank shoreline and

extended 15 m towards mid-channel (65 m from reference stake). Strata 3 and 4 were

classified as mid-channel, encompassing the remaining range between strata 1 and 2 (30 m-

65 m from reference stake). Area (m2) and beam area of coverage within each stratum (m

2)

were calculated for each day. To assess the relative effectiveness of SL DIDSON versus

split-beam on a daily basis, I calculated the daily ratio of split-beam to SL DIDSON counts

in stratum 1. Also, a simple linear regression was performed to assess split-beam counts

19

relative to upstream migrant‘s mean distance off bottom observed from the easternmost DL

DIDSON sample (location #7).

Free, open source Bayesian statistical software (OpenBUGS, v. 3.2.1) was used to

model run-size (Appendix Figures 5-6). A Poisson generalized linear regression model was

used to model counts of upstream migrants, estimating a daily passage rate (λ) (Kery 2010).

The log-scale linear equation for λ, the expected number of upstream migrants per m2 per

hour, was a linear function of day and stratum. Time in hours and cross-sectional beam area

were offsets (Kery 2010) to account for variation in sampling time (e.g., 10-minute DL

DIDSON versus 24 hours for split-beam) and beam geometry. Gear was included as a

multiplier for each stratum to account for differences in gear effectiveness of detecting fish

tracks (Waine 2010), with DL DIDSON assigned a value of 1.0 in all strata, both years, and

SL DIDSON and split-beam estimated within the model for 2011. Because SL DIDSON was

not deployed in 2010, the split-beam multiplier value estimated for stratum 1 in 2011 was

used for 2010 in an informative prior beta distribution for stratum 1 split-beam, and

remaining split-beam gear multipliers were estimated similar to 2011. Using the 2011 split-

beam gear efficiency in 2010 is assumed to be warranted based on a consistent approach to

split-beam and DL DIDSON monitoring in the two years. Day (alpha, αd) was modeled as a

random effect. This resulted in a hierarchical model in which individual day effects were

drawn from a joint distribution (shared mean and variance), rather than estimating each day

separately and treating it as completely unrelated to surrounding days (Kery 2010).

20

Modeling day as random effect can also account for extra variation in counts, above what

would be expected in a Poisson distribution (McCarthy 2007).

The linear predictor for log-scale counts was:

log(λi) = log(Ti) + log(Ai) + log(γgs) + I + αd + βs

where Ti is the time sampled in hours for the ith

sample, Ai is the cross-sectional

beam area in m2 for the i

th sample, γgs is the gear multiplier for gear g in stratum s, I is the

intercept, αd is a day effect, and βs is the stratum effect. The estimated run size for day d was

the sum over strata of expected counts, expanded for the stratum area and 24 hours:

∑

where is the straum area for day d and stratum s. The random effect for day (α)

was drawn from a normal distribution with mean 0 and precision (1/variance) , where was

estimated using an uninformative gamma distribution (r 0.001, nu 0.001). The gamma prior

was chosen because that parameter can only take on positive values. An uninformative

normal distribution with mean 0 and precision 1E-6 was used for the stratum effect β. To

make fixed effects identifiable, the last level for β was set to 0 (Kery 2010). An

uninformative beta distribution was used for gear multipliers in 2011 (SL DIDSON and split-

beam) and 2010 for split-beam in stratum 4 (no split-beam data for strata 2-3). The mean and

variance (σ2) from 2011 were used to calculate the beta parameters (α,β) (McCarthy 2007) of

the informative distribution used to estimate the stratum 1 split-beam multiplier in 2010.

Beta distributions were chosen because their distributions are defined by the interval (0,1).

On April 17, 2011 (day 48 of season), no hydroacoustic data were obtained due to severe

21

weather. Within the model, each day must have counts for at least one gear, so I used the

average split-beam counts per m2 from the previous 3 days (45-47) and the following 3 days

(49-51) as a proxy for the missing split-beam counts on day 48. A less complex version of

the 2011 model was also constructed, using only DL DIDSON data to assess the effect of SL

DIDSON (full model) on precision and magnitude of estimates.

Species- or group-specific estimates of run size were estimated using a multinomial

distribution using seven categories: alewife, American shad, blueback herring, hickory shad,

striped bass, white perch, and other. Species proportions were estimated using weekly

samples from electrofishing and gill-netting. For each week, one parameter was used to

estimate the proportion of ―other‖ species (versus anadromous), and six parameters were

used to estimate the anadromous species proportions. An uninformative beta distribution

was used for the proportion of other species. Prior distributions for anadromous species

proportions were obtained using a Dirichlet distribution and total catches from the NCDMF

fishery-independent gill-net survey in western Albemarle Sound. Only monthly sample data

were available from the NCDMF survey and there is a lag between when species are present

in the western sound and in the lower Roanoke River, so each weekly prior was based on

NCDMF catches shifted forward in time to best match my weekly species composition. For

example, in 2010, NCDMF samples from February were used for weeks 1-3, March samples

for weeks 4-7, April samples for weeks 8-11, and May samples for weeks 12-13. Because of

low sample sizes from species composition sampling at the sonar site, NCDMF catches were

reduced by a factor of eight. This divisor was chosen arbitrarily, but it reduced NCDMF

22

sample sizes to a magnitude similar to my in-river samples, while allowing higher catches

from in-river sampling to have major influence on model estimates. Thus the NCDMF data

supplemented and stabilized run-size estimates but did not dominate the model when in-river

sampling provided moderate to large sample sizes (Appendix Figures 7-8). NCDMF data had

to be slightly modified for OpenBUGS to run properly; hickory shad in May 2010 and

alewife in May 2011 had to be changed from a catch of zero to 1. While this change allows

the model to run properly, it is not a significant influence in results due to high NCDMF

catches during those months (< 1% of total catch).

The FERC license for the Roanoke Rapid dam states that additional restoration efforts

(such as fish passage) are to be considered once two annual run size estimates exceed 20,000.

I used a ―step‖ function in the OpenBUGS analysis to determine the probability that 2010

and 2011 American shad run-size estimate were greater than 20,000 individuals. I ran the

model with two independent MCMC chains, each with 50,000 iterations. I thinned the

results to every 10th

sample to reduce autocorrelation and used a burn-in of 1,000 steps to

ensure model convergence.

I compared the ratio of my striped bass to American shad run-size estimates to the

average ratio of striped bass to American shad catch from NCDMF data from the last 21

years (1991-2011), restricting catch data to similar mesh sizes and sample season (February-

May). Also, to compare my run-size estimates to previous hydroacoustic estimates on the

Roanoke (2004-2009), I calculated 95% confidence intervals for estimates from 2004-2007

(mean run-size estimate ± SE×1.96; Zar 2010).

23

RESULTS

Study Site

Water level in 2010 was characterized by two distinct flow periods: above and below

flood stage (Figure 11). Water level was above 3.04 m (flood stage) at the Williamston

USGS water gage from February 24-April 20 and below flood stage from April 21 to the end

of the field season. River discharge, measured at Roanoke Rapids Dam, ranged from 149

m3/s

to

589 m

3/s.

In 2011, water levels were lower and fluctuated more often than 2010

(Figure 12). River discharge in 2011 ranged from 63 m3/s

to 394 m

3/s. Surface water

temperature at the sonar site ranged from 5.3ºC to 22.3ºC in 2010 and 10.6 to 21.8 in 2011

(Figure 13). The more gradual warming in 2010 was due to the higher flows.


Split-beam— Split-beam sonar recorded 1931.35 hours of data in 2010 (95% of

possible hours) and 1826.33 hours of data in 2011 (94% of possible hours); outages were due

to sonar or computer malfunction and power supply problems. A total of 154,977 upstream

moving fish were tracked in 2010 (Figure 14) and 87,098 in 2011 (Figure 15). A total of 609

fish tracks were removed from March 29-April 2, 2010 because plotted fish tracks in the

river cross-section suggested misclassification due to excessive bottom interference. From

March 1-11, 2011 low water levels caused excessive surface reverberation in the upper

portions of the sonar beam causing fish detections in the near surface zone to be indiscernible

from noise. All fish tracks in the noise-affected region were excluded from analysis and

beam area estimates were corrected.

24

Upstream passage rates were similar among hours in 2010 except for a distinct peak

between 0800-1200 hours (Figure 16). In contrast, day-time hours (0700-1700 hours)

exhibited the lowest passage rates in 2011 with highest rates of passage during early morning

(0500-0600 hours) and late evening (1800-2100 hours) (Figure 17).

Down-looking DIDSON— A total of 492 upstream migrants were observed in 62.17

hours of DL DIDSON effort. Counts were very low from late February through mid-March

but relatively constant afterward (Figure 17). Sample location #4 was not sampled from

April 12-15 due to large debris displacing the anchor buoy. No locations were sampled on

April 26 due to severe weather and from May 10-13 due to shared use of the DIDSON on an

NCWRC study. Sample locations 1 and 7 had the highest number of fish detections,

comprising 67% of total detections (days with unequal sample effort across locations were

removed) (Table 1; Figure 18). Observed fish were bottom oriented, with a median distance

off bottom of 0.17 m and 80% of fish being within 1 m of river bottom (Table 1; Figure 19).

Overall mean fish length was 33.28 cm (SE 0.42 cm) and exhibited a similar distribution as

hand-measured fish from electrofishing samples (Table 1; Figure 20).

In 2011, 1,583 upstream moving fish were observed in 62 hours of DL DIDSON

coverage (Table 1). Observed numbers of upstream migrants were relatively similar

throughout the field season except for a mid-April peak (Figure 21). Down-looking

DIDSON samples in 2011 were not taken on March 3 due to boat problems and from May 4-

6 due to NCWRC use of the DIDSON. Sample locations 3-7 were only sampled for 5

minutes each on April 26 due to severe weather. Accounting for days with unequal sample

25

effort across locations, sample locations 1 and 7 comprised 49% of total observed fish (Table

1; Figure 22). Fish were bottom oriented with a median distance off bottom of 0.30 m and

86% of observed fish within 1 m of river bottom (Table 1; Figure 23). Overall mean fish

length was 33.44 cm (SE 0.26 cm) which was very similar to 2010. Length estimates from

DL DIDSON images were similar to those from electrofishing but had a much higher

frequency of 20-30 cm fish than did drift gill netting samples (Figure 24).

Side-looking DIDSON—Side-looking DIDSON recorded 991.2 hours of data on the

east bank (51% of season). A total of 311,781 raw upstream fish counts was adjusted down

(correction factor) to 206,642 to account for over-counting, based on regression analysis of

manual counts versus Echoview‘s automated counts (see Correction Factors below). For

comparison of daily counts across days, corrected counts were standardized to fish·hour-1

·m-2

of beam cross-sectional area to account for unequal monitoring effort (hours and area

sampled) (Figure 25). Blind-spots along bottom were not a concern along the east bank, with

bottom image present throughout the FOV (Figure 26). Higher numbers of raw fish

detections (uncorrected counts, 311,781 fish tracks) in the early morning (0600-1000 hours)

and evening (1500-1900 hours) hours indicate strong diurnal upstream passage (Figure 27).

Mean fish length as estimated by Echoview was 37.42 cm (SE 0.02).

West bank SL DIDSON monitoring observed 54,524 raw upstream migrants in 205

hours sample time (11% of season). Raw counts for west bank SL DIDSON did not need to

be adjusted for target misclassification (see Correction Factors below). To account for

variation in sample effort (hours) across days, corrected counts were plotted as fish·hour-1

·

26

m-2

(Figure 25). Blind-spots along bottom were not a concern along the west bank, with the

steep bank and bottom substrate visible throughout the FOV (Figure 28). Mean fish length as

estimated by Echoview was 38.19 cm (SE 0.06).

Acoustic Data Processing

Correction factors— I manually inspected 26 and 24 split-beam automated files for

2010 and 2011, respectively, to determine if a correction factor needed to be applied to raw

counts produced by Echoview to account for under- or over-counting biases. The linear

regression fitted between manually-inspected and Echoview generated counts in 2010 and

2011 indicated intercepts were not statistically different from zero and slopes were not

statistically different from 1.0 (Figure 29; Appendix Table 1). Thus, Echoview generated

counts were used without a correction factor.

A total of 48 5-minute subsamples from east bank SL DIDSON data were analyzed to

determine a correction factor; 18 files from Period 1(longnose gar period, March 1-11, 2011)

and 30 files from Period 2 (remainder of season, March 12-May 20, 2011). Linear regression

between manual counts and Echoview counts during Period 1 indicated an intercept

significantly different from zero and a slope not statistically different from zero, indicating

that automated counts were not appropriate for analysis (Figure 29; Appendix Table 1). To

account for this, the average manual count·hour-1

·m-2

from the 18 5-minute files was applied

to each day during Period 1, expanding upwards to account for area and time sampled. The

linear fit for Period 2 did not show an intercept significantly different from zero, but did have

a slope significantly different from 1.0 (Figure 29; Appendix Table1), so the linear regression

27

was re-fit, forcing the intercept at zero, to determine a correction factor. The resulting slope

was 0.775 (Figure 29; Appendix Table1), indicating an over-counting bias by the automated

fish tracking algorithm for this set of DIDSON files. Daily raw counts for Period 2 were

multiplied by 0.775 to account for this estimated bias.

Twenty-two 5-minute subsamples from west bank SL DIDSON data were analyzed to

determine a correction factor. There was no detected bias between manual and Echoview

counts (Figure 29; Appendix Table 1); therefore, no adjustment to raw counts were

necessary.

Species Composition

A total of 27 fish species were captured boat electrofishing, bottom-set gill nets, and

drift nets (Table 2). Pumpkinseed Lepomis gibbosus and redbreast sunfish L. auritus were

the only species captured in 2010 that were not captured in 2011. American shad, American

eel Anguilla rostrata, and warmouth L. gulosus were captured in 2011but absent from 2010

samples. Striped bass and gizzard shad Dorosoma cepedianum were the most numerous

species in electrofishing samples in 2010 and 2011 respectively. White catfish Ameriurus

catus were most numerous in bottom-set gill net catch in 2010 and hickory shad were most

numerous in 2011 drift gill nets. Target anadromous fish composed 48% and 49% of total

electrofishing catches in 2010 and 2011 respectively. Anadromous fish made up 28% of

bottom-set gillnets in 2010 and 74% of drift net catches in 2011. In general, the progression

of spawning runs began with hickory shad, followed by alewife, white perch, blueback

herring, striped bass, and American shad (Tables 3-6; Figure 30). For each target

28

anadromous species, with the exception of striped bass, mean total length was larger for fish

captured in gill netting than electrofishing (Tables 7-8).

Electrofishing— Electrofishing captured 22 species, totaling 3,006 fish (1,597 non-

target fish, 1,409 upstream migrating target species) in 31 h of effort during 2010 (Table 2).

Electrofishing CPUE was similar for target and non-target species over the entire season but

daily estimates of target CPUE declined sharply in May (Table 9; Figure 31) Hickory shad

dominated electrofishing samples in March, with peaks during April attributed to blueblack

herring, striped bass, and white perch (Figure 32).

In 2011, 28 h of electrofishing effort captured 25 species, totaling 2,743 fish (1,536

non-target fish and 1,207 upstream migrating target fish) (Table 2). As in 2010, CPUE was

similar for the entire season for target versus non-target species, but daily CPUE of target

species declined strongly in May (Table 9, Figure 33). A peak in CPUE for target species

during late March can be attributed to high catch rates of alewife and peaks in mid-April are

from high catches of striped bass and blueback herring (Figure 34).

Gill netting— Bottom-set gill net sampling in 2010 began on March 2 and ended on

May 19, with only one day of effort missing (second week of gill net sampling) and one extra

day of sampling (first week of gill net sampling). Gill nets captured 16 species, totaling 205

fish (147 non-target fish, 57 upstream migrating target fish) in 186.6 h of effort in 2010

(Table 2). Daily total CPUE (mean 1.0 fish/h; Table 10) was markedly lower than for

electrofishing. As with electrofishing, target species CPUE declined sharply in May (Figure

35-36). CPUE was highest for white perch and for 9-cm mesh nets (Table 11). Due to high

29

loads of debris fouling and damaging nets, 13 net sampling days were missing at least one

mesh size, including 2 days missing 2 nets. Seven net sampling days were missed by the 14

cm mesh net and 2 sample days each were missed by the 9, 10, and 11.5 cm nets.

The total drift gill net catch for 2011 was 424 fish (16 species; 178 non-target fish,

246 upstream migrant target fish) in 448 drifts (112 drifts per mesh size or drift-sets) (Table

2). Missed drift net sampling days in 2011 were March 10 and April 28 due to severe

weather. Drift gill net catches were predominately target species until late May (Figure 37).

CPUE was highest in early March (due primarily to hickory shad) and mid-April when

striped bass dominated drift net catch (Figure 38). The 7 cm mesh size was the only net to

capture all anadromous species, but the 9 cm net had the highest catch rates, mainly due to

high catches of striped bass and hickory shad (Tables 12).

Run Size Estimates

The estimated total number of upstream migrants from February 23 to May 20, 2010

was 2,373,000 (95% credible interval 2,264,000 to 2,493,000), with a daily peak on March

15, 2010 (Table 13; Figure 39). For 2011, the run size estimate with 95% credible intervals

was 4,174,000 upstream migrants (95% CI 3,907,000 to 4,446,000) with a daily peak on

April 13, 2011(Table 13; Figure 40). For comparison, the DL DIDSON-only model for 2011

produced a median estimate of 4,260,000 individuals (95 % CI 3,779,000 to 4,957,000). The

2010-2011 estimates and most of the species-specific estimates (see below) were larger than

previous hydroacoustics estimates (Figure 41-42). The 2011 model estimated a gear

multiplier, relative to 1.0 for DL DIDSON, of 0.55 and 0.66 for SL DIDSON in strata 1 and

30

2 respectively, and 0.19 and 0.99 for split-beam in strata 1 and 4 respectively (Table 14),

consistent with mean observed counts by gear in each stratum (Table 15).

Daily mean count·h-1

·m-2

by sonar deployment and stratum supports the assumption

of DL DIDSON as the most efficient gear (Table 15). In both years, split-beam was far less

effective in detecting upstream migrants than DL DIDSON in stratum 1, but relatively

similar in stratum 4. Examining Stratum 1 split-beam and SL DIDSON counts (standardized

to count·h-1

·m-2

) outside of the model indicates split-beam counts were roughly 10-40% of

SL DIDSON counts for most of the season with increased efficiency (35-80%) during mid-

April (Figure 43). The relative effectiveness of the split-beam sonar appeared to be related

to the position of fish within the water column. The split-beam:SL DIDSON ratio (Figure

43) was significantly correlated with the distance off-bottom for fish at the outer-most DL

DIDSON location (R2=0.22, p<0.001). The 2010 stratum effect was highest for stratum 1

(east), followed by 2 (west), 4 (upper channel), and 3 (bottom 1m). The estimated stratum

effect and therefore run size by strata in 2011 was highest for stratum 2 (west bank),

followed by 1 (east), 3 (bottom 1 m) and 4 (upper channel) (Table 14; Appendix Figure 9)).

Run size estimates for anadromous species in 2010 were highest for striped bass and

white perch followed by alewife and blueback herring (Table 13; Figures 41, 44). Estimates

in 2011 were highest for striped bass then blueback herring, white perch, and alewife (Table

13, Figures 41, 44). Consistent with in-river sampling, modeled proportions of ―other‖

species (non-targets) for 2010 and 2011 were greatest at the end of the season (Figures 47-

48). The estimated probability of American shad run-size being less than 20,000 individuals

31

was 0.70 in 2010 and 0.001 in 2011. The ratio of striped bass to American shad estimates

was 18.0 in 2010 and 19.0 in 2011, compared to a mean of 13.9 for 1991-2011 from NCDMF

catch data (range 3.1-37.1).

DISCUSSION


Fixed-location hydroacoustic surveys have been used extensively to monitor

migratory fishes in rivers (Daum and Osbourne 1998; Ransom et al. 1998; Enzenhofer and

Cronkite 2000; PACE 2003; Burwen et al. 2007; Maxwell and Grove 2007). Advantages

include the ability to monitor continuously over the entire field season and the capability in

some systems to provide real-time abundance estimates. Unfortunately, not all rivers are

created equal when it comes to feasibility of monitoring migratory fishes with

hydroacoustics. Challenges in the Roanoke, as with many southeastern rivers, include

unfavorable channel morphology (i.e., steep or unevenly sloped banks), fluctuating water

levels, excessive suspended and embedded debris, and many species that overlap in size and

run-timing. Another challenge in this study was not having enough hydroacoustic gear to

cover both banks continuously, which is the recommended approach for bank-oriented

migratory fishes (Enzenhofer and Cronkite 2000).

The approaches used to address these challenges have evolved as experience has been

acquired and as new hydroacoustic equipment became available. Monitoring in 2004-2005

(Mitchell 2006) was done at a site near Halifax (~rkm 190) that was downstream of

American shad and striped bass spawning areas and had electric power at the river‘s edge,

32

but lacked a suitable channel morphology for monitoring nearshore zones. The site used in

2006-2011 (rkm 64) required batteries and generators for power, but it had a gradually

sloping bank on one side and was much closer to the river mouth (Magowan 2008).

Monitoring in 2006-2007 was done only on the east bank, making the untested assumption

that fish densities were similar on the unmonitored west bank. A DIDSON sonar became

available prior to the 2008 season. It was used in a mid-channel SL deployment in 2008,

which proved ineffective (J. Hightower, NCSU, personal communication). In 2009, it was

used in the DL deployment which provided some coverage of the entire channel cross-

section as well as the vertical distribution of upstream migrants (Waine 2010). The addition

of SL DIDSON monitoring in 2011 substantially improved coverage of the nearshore strata.

Model estimates from both years show differences in numbers of fish that migrated along the

west bank compared to the east bank, which illustrates the risk of assuming the same passage

rates on both banks (Daum and Osborne 1998).

An important benefit of combining sonar technologies is that upstream passage rates

can be compared in order to estimate the relative effectiveness of different sonars. Waine

(2010) estimated a gear bias (lower detection rate of upstream migrants) for split-beam sonar

compared to DL DIDSON. My results for 2010 and 2011 indicate a lower efficiency for

split-beam not only compared to DL DIDSON, but SL DIDSON as well. A higher efficiency

for SL DIDSON versus split-beam would be expected close to shore because of the narrow

beam width of the split-beam sonar (Maxwell and Grove 2007). For example, my split-beam

sonar had a beam width of 1.22 m at 10 m compared to a beam width of 5 m for the DIDSON

33

with 28o spreader lens. A disadvantage of the narrow beam width at near-range for split-

beam sonars is that fish may be larger than the beam itself, making determination of direction

of travel impossible (Maxwell and Grove 2007). Another potential cause of undercounting

with split-beam sonars is the presence of ‗blind-spots‘ near bottom caused by bank slope

unevenness (Daum and Osbourne 1998; Xie 2005; Enzenhofer and Cronkite 2000). A lower

effectiveness for split-beam compared to DIDSON monitoring would at least partly account

for the lower run size estimates in 2004-2007 (when only split-beam data were used). The

lower effectiveness in 2011 for SL versus DL DIDSON may be due to the lack of

background clutter in the DL deployment, which makes it easier to detect fish. Field trials

with tethered and free-swimming fish would be helpful for comparing these two DIDSON

deployments.

Down-looking DIDSON samples at fixed cross-channel locations provide important

spatial information, in addition to the count data used in run-size modeling (Waine 2010; this

study). Spatial results in 2010 and 2011 were consistent with previous hydroacoustic

findings, showing upstream migrants are shore- and bottom-oriented (Magowan 2008; Waine

2010). The degree to which fish are shore oriented appears to vary as a function of water

velocity, presumably as a strategy for conserving their energy reserves (Leonard 1999;

Standen et al. 2004).

Counts from DL DIDSON monitoring were substantially lower in 2010-2011

compared to 2009, despite more than triple the 2009 effort. Lower counts at channel

locations in 2010 might be expected due to the above and near flood stage water levels.

34

However, river flows do not explain the lower DL DIDSON counts in 2011 in comparison to

2009, so there may simply have been fewer upstream migrants in 2011. (Note that

comparisons of 2010-2011 and prior run size estimates may be misleading because the prior

year estimates do not include SL monitoring of the nearshore zone where highest densities of

upstream migrants were found. Also, 2004-2007 estimates are based solely on SB data and

do not include any adjustment for gear bias.) Observed peaks in DL DIDSON counts in

2010 and 2011 were consistent with peaks in other sonar deployment counts (SL DIDSON

and split-beam) as well as anadromous species sampling CPUE.

Automatically processing files allows for entire data sets to be used in analysis rather

than extrapolating data from a subset of files. Although much less time is needed to auto-

process files, concerns regarding misclassification (undercounting or overcounting) must be

addressed. I found no evidence of a consistent bias when comparing automatically processed

split-beam and west bank SL DIDSON counts versus manually processed subsets of files.

East bank SL DIDSON counts unfortunately did not correlate as well with manual counts for

a few reasons. As mentioned previously (see Methods), large schools of longnose gar were

observed ‗milling‘ during low water levels in 2011 (March 1-11) creating double- or

multiple-counting problems. Also, schools of tightly packed smaller fish (probably smaller

river herring indicated by electrofishing observations) and non-directed movement (e.g., back

and forth in beam) caused detection and double-counting errors (Boswell et al. 2008). The

east bank is the shallower, flatter bank, experiencing less current velocity (Waine 2010) and

therefore fish may not ―actively‖ pass the sonar site to the degree previously assumed

35

(Magowan 2008; Waine 2010), especially during low flows. Improving misclassification

rates may be accomplished by additional filtering and scrutiny of upstream target variables,

such as target thickness, time in beam, or tail-beat patterns (Maxwell and Grove 2007;

Mueller 2010), but further investigation is needed to determine if these filters are appropriate

for fish in the Roanoke River.

An advantage of DIDSON technology applied to fisheries research is the capability to

estimate fish length. The DL DIDSON deployment produced size distribution of upstream

migrants that were similar to electrofishing in both years. Size distributions from the 2011

east and west bank SL DIDSON deployments were similar to electrofishing results but all

three distributions showed a higher proportion of small fish (< 35 cm) compared to 2011 drift

gill net samples (likely due to the low drift-gill net catch of blueback herring and alewives).

Ground-truthing studies or in situ trials of known fish lengths at different ranges would be

helpful for verifying the accuracy of DIDSON size estimates (Burwen et al. 2010).

Species Composition

Acoustic variables such as target strength (TS), spatial or temporal differences, size

differences, or even tailbeat patterns can occasionally be used to identify fish to species

(Love 1977; Simmonds and MacLennan 2005; Burwen et al. 2010; Mueller et al. 2010).

The much more common situation, however, is that species-level identification is infeasible

(Horne 2000; Fleischman and Burwen 2003), and physical sampling or visual confirmation

(Pedersen and Boettner 1992; Baldwin and McLennan 2008; Hartman et al. 2000; Kucera

2009) is necessary to proportionate acoustic count data. My gill net and electrofishing

36

species composition sampling captured the progression of different anadromous spawning

runs. Peaks in CPUE for anadromous fishes corresponded with peaks in hydroacoustic

counts, supporting our method of apportioning counts by species. For example, the most

anadromous fish captured in a single week by electrofishing and netting in 2011 was 247 fish

(week 7; April 11-17), which corresponds with high hydroacoustic counts and lower

proportions of non-target species. In both years, low catches of anadromous fishes towards

the end of the season corresponded to lower hydroacoustic counts and high proportions of

resident (non-target) species.

Apportioning counts by physical capture techniques are only as accurate as the

methods used to capture fish. Gear and size selectivity for different species, low sample

sizes, and variable catch rates can greatly influence partitioning of counts and therefore run-

size estimates. In both years, fish captured in gill nets were larger than those collected

through electrofishing, with few river herring captured in gill nets. Electrofishing seemed to

catch all sizes well, including river herring, but has been relatively ineffective for American

shad for all years at the current sonar site (Magowan 2008; Waine 2010; this study). In an

assessment of vertical distribution of American shad in the Connecticut River, Witherell and

Kynard (1990) found most were captured in the lower (deeper) portions of the water column.

To effectively capture American shad during their migration up the Roanoke River, efficient

near-bottom sampling is needed. Although drift nets were used to fish near-bottom regions,

high water or bottom obstructions decrease the ability to drift nets along bottom, resulting in

low to zero catch rates of fish migrating near-bottom. I pooled weekly species composition

37

data for both gears to increase sample size and reduce size and species selectivity, but

undoubtedly some biases due to gear type remain.

Incorporating NCDMF netting data as prior information regarding species

composition appeared to be effective in reducing uncertainty caused by low and variable

sample sizes. Having prior information helped stabilize species specific run-size estimates

when in-river catches were low, but had much less influence during peaks in run size when

in-river catches were high. Potential improvements in this approach would be to obtain data

on a finer time scale (i.e., weekly or daily) and to use an analysis to estimate the appropriate

lag (rather than basing it on inspection).

Run Size Estimates

The combination of counts from multiple sonars, modeled using a Bayesian

framework that accounted for gear and spatial (stratum) differences, suggests much larger

run sizes than previously reported (Mitchell 2006; Magowan 2008; Waine 2010). Although

my total run size estimates varied between years (2010 and 2011), they were ~1 million

individuals more than previous years (2004-2009). As noted above, run size estimates for

2004-2007 were based only on split-beam monitoring and did not account for split-beam gear

bias. Estimates for 2008-2009 adjust for the lower effectiveness of split-beam but did not

include nearshore monitoring (Strata 1 and 2) by a SL deployment, which in 2010-2011

showed high densities of fish moving upstream just beyond the weir. There was one DL

DIDSON location in each nearshore stratum in 2010-2011 (and those two locations had

highest upstream counts), but it was not possible to monitor as close to shore with a DL

38

deployment. Fish passing just beyond the weir were likely difficult to detect in split-beam

monitoring because of the small beam diameter close to shore. Additional evidence that

split-beam monitoring is less effective in the first few meters is in the spatially explicit plots

for 2008-2009 monitoring, showing highest split-beam densities a few meters offshore

(Waine 2010). In both 2010 and 2011, split-beam counts were much less than DL DIDSON

in the nearshore stratum, but much more similar to DL DIDSON in the mid-channel stratum

where the split-beam‘s beam width is much greater than nearshore. Modeling gear

effectiveness by stratum enables the model to better distinguish gear effectiveness versus a

stratum effect. For example, SL DIDSON monitoring was done only in the two nearshore

strata so high passage rates in strata 1 and 2 might be misinterpreted by the model as a gear

effect if the model estimated an overall gear effectiveness (i.e., not by individual strata).

The total run size estimates for 2010-2011 were relatively precise compared to the

previous Bayesian model (2008-2009 results). The improved precision may be due to

stratifying the river cross-section into broad zones with consistent relative densities of fish

(e.g., high, medium, low). Stratification should reduce uncertainty by having more consistent

counts within (compared to among) strata. Estimates of the stratum effect (spatial

distribution) were consistent with simple means from DL DIDSON sampling as well as

results from previous years (Magowan 2008; Waine 2010). Waine (2010) also modeled

spatial patterns of upstream migrants, but used a finer scale (1 by 2 m cells) and estimated

parameters for distance off shore and off bottom. Distance off bottom can be estimated for

fish detected using split-beam and DL DIDSON sonars, but cannot be estimated for the SL

39

DIDSON deployment used in 2011. Another factor that might account for improved

precision in 2010-2011 might be the SL DIDSON deployment, which covered a high

percentage of the nearshore strata exhibiting greatest fish passage (Strata 1 and 2). Similar

median estimates, but much wider credible intervals (639,000 total increase), from the DL

DIDSON only model supports increased precision with the inclusion of SL DIDSON.

Further improvements in precision would occur if those nearshore strata could be monitored

continuously, rather than rotating a single DIDSON sonar among DL and SL deployments. It

would also be an improvement to have a balanced design, with all three sonar deployments

used in all strata. Unfortunately deployment of SL DIDSON in mid-channel strata or placing

the split-beam sonar on the far bank does not appear to be feasible at the current sonar

location.

Run size estimates for striped bass in 2010-2011 (333,600 and 630,400) were much

greater than previous hydroacoustic estimates (range 118,778-226,094) (Mitchell 2006;

Magowan 2008; Waine 2010). All the hydroacoustic estimates are less than a preliminary

2011 mark-recapture estimate (730,000) (J. Harris, NCSU, personal communication).

Substantially higher estimates have been produced for Albemarle Sound/Roanoke River

(A/R) striped bass, using stock assessment models with fishery dependent and fishery

independent data. Results are not yet available for 2010-2011, but age 3+ abundance from

2004-2008 was estimated at approximately 1 million individuals (Takade-Heumacher 2010).

These assessments, conducted by NCDMF, are based on a forward projecting catch at age

model called the Age Structured Assessment Program (ASAP2; Takade-Heumacher 2010).

40

It is not possible to determine which of these estimates is more accurate, but there are some

indications that the ASAP2 model may be over-estimating Roanoke River striped bass

abundance. The assessment produced record estimates of age 3+ fish in 2008 (1.2 million)

and ages 1+ in 2007 (2.1 million), but the recreational fishing quota for the Roanoke River

and Albemarle Sound Management Areas has not been met since 2004 (Takade-Heumacher

2010). Also, despite increased angler effort on the Roanoke River in 2007, striped bass

harvest declined 24% (Thomas et. al 2008). Other uncertainties about interpreting our

estimates relative to the A/R assessment results are the proportion of striped bass that spawn

annually and the proportion of the A/R stock that spawns in the Roanoke River. Both of

these proportions are likely to be high, but anything less than 100% would reduce the

expected Roanoke River run size relative to the ASAP2 estimate (and would reduce the gap

between those assessment estimates and my 2010-2011 hydroacoustic estimates). A

potential source of error in my hydroacoustic estimates is through use of the NCDMF gill net

data as a source of prior information regarding species composition. If some other species

(e.g., white perch) made up a higher percentage of the anadromous group in Albemarle

Sound than in the Roanoke River, that could lead to an underestimate of striped bass run size

in the river. Estimates for all the anadromous species are also affected by the estimated

proportion of ―other‖ species, based on in-river sampling. If, for example, shoreline

electrofishing results in an overestimate in the proportion of other species, that causes all

anadromous species to be underestimated.

41

My run size estimates for American shad (18,360-33,250) were greater than all but

one previous year of hydroacoustic monitoring on the Roanoke (35,483 in 2006; Magowan

2008). The higher 2010-2011 estimates are likely due to the increases in total run-size based

on accounting for gear bias, and to improved species composition estimates using both in-

river and NCDMF samples. In-river collections of American shad have been very low and

variable throughout the eight-year hydroacoustic study and run size estimates for 2004-2009

have varied accordingly. For example, the difference between my estimate for 2010 and

2011 would be much greater if based only on in-river sampling, since none were collected in

2010. If drastic year to year changes in run size were occurring, they should be detectable by

annual CPUE monitoring, which is useful for detecting large (>50%) abundance changes

(Pine et al. 2003). However, NCWRC CPUE estimates for American shad at Roanoke

Rapids (Wynne et al. 2011) suggest that the population has remained relatively stable, a

finding consistent with other population estimates (Harris 2010, this study). Harris (2010)

produced a Roanoke River estimate of 5,200 adult females based on ratios of wild to juvenile

American shad from 2004-2008 (Harris 2010). Harris (2010) noted several parameters in

need of further investigation to better evaluate the accuracy of her model, including

fecundity, differences in survival between hatchery and wild fish, and natural mortality of

young American shad specific to the Roanoke River.

The hydroacoustic estimates of American shad run size have important management

and restoration implications. As noted above, the FERC license for the Roanoke Rapids dam

requires additional restoration efforts (such as fish passage) to be considered once two annual

42

run size estimates exceed 20,000. My results suggest a slight probability (0.30) that the 2010

estimate is greater than 20,000 individuals, but very likely in 2011 (probability = 0.99) when

SL DIDSON counts and drift gill net sample gear were used. The ratio of striped bass to

American shad run-size estimates in 2010 and 2011 were slightly higher, but well within

reason of the striped bass to American shad ratio in NCDMF survey data. The estimates

were not independent since NCDMF data were used as a prior distribution in my analysis,

but the large sample sizes from the NCDMF survey support its use to stabilize my estimates.

Aside from hydroacoustic monitoring, no direct stock assessment or population

monitoring is conducted for river herring, hickory shad, or white perch in the Roanoke,

making reliability of my estimates difficult to assess. Estimates of hickory shad in 2010-2011

were comparable to previous hydroacoustic estimates (although as noted above, estimates

from 2004-2009 are likely low). Alewife estimates for 2010 -2011 were similar to 2007-

2009 estimates from the current sonar site. Alewives were not collected by Mitchell (2006)

at the Halifax site. My blueback herring estimates were much greater than previous

hydroacoustic estimates, likely due to the combination of higher overall run size estimates

and high in-river catches. Hydroacoustic estimates for blueback herring were not produced

by Mitchell (2006) for the Halifax site because of relatively low catches. My high 2010-

2011 estimates of white perch run size relative to previous years may be a reflection of high

abundance in NCDMF catches. White perch are more of an estuarine, semi-anadromous

species with an unknown portion of the population migrating past our sonar site to spawn.

Further investigation into the proportion of white perch migrating past our sonar site would

43

help in determining whether white perch run size is overestimated (and whether other species

might be underestimated).

CONCLUSIONS

Incorporating multiple sonars and deployment strategies has resulted in improved

abundance estimates for anadromous fishes in the Roanoke River. The combination of DL

and SL DIDSON deployments showed that nearshore areas have substantially higher

densities of upstream migrants than do the main channel strata. Monitoring both shorelines

and stratifying the river cross-section decreased uncertainty of extrapolated counts,

improving confidence in the model. These changes, along with modeling gear effectiveness

by stratum, considerably increased the magnitude of run size estimates. The 2010-2011

estimates for American shad should be helpful in developing a restoration plan. The much

higher 2010-2011 striped bass estimates reduce the discrepancy between the hydroacoustic

estimates and NCDMF stock assessment results, and are closer to a preliminary estimate

from an independent mark-recapture study. Apportioning hydroacoustic counts by species

has been, and continues to be, an area of needed improvement. In-river sample sizes need to

be larger. Use of NCDMF gill net data as prior information in our model is believed to have

improved species-specific estimates, but finer resolution of NCDMF catch data (e.g., weekly

or daily catches) would improve these estimates further. Barring some improvement in in-

river fish sampling methods, the best approach for allocating sonar counts by species may be

to incorporate DIDSON-generated length estimates into a size-stratified model. Similar size

information was obtained from electrofishing and DIDSON monitoring, even using DIDSON

44

length estimates from automated processing. On-site trials to evaluate DIDSON size

estimates for fish of various sizes and species at all ranges within the field of view should be

done to ground-truth the DIDSON size estimates. The methods developed for the Roanoke

River should be helpful in designing hydroacoustic surveys of other coastal rivers.

45

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53

Table 1. Total number, mean length and standard error, and median distance off bottom for

all observed upstream migrants in DL DIDSON samples in 2010 and 2011 by location.

Locations are cross-channel station numbers (see Figure 5)

2010 2011

Location N

Mean

Length

(cm)

Std.

Error

(cm)

Median dist.

Off Bottom

(m) (Max.)

N

Mean

Length

(cm)

Std.

Error

(cm)

Median dist.

Off Bottom

(m) (Max.)

1 132 32.97 0.88 0.2 (2.7) 448 33.74 0.54 0.3 (2.3)

2 89 33.20 1.15 0.3 (4.6) 297 33.46 0.58 0.6 (5.0)

3 29 35.22 1.94 0.4 (4.1) 60 30.87 0.89 0.5 (5.4)

4 11 39.32 2.98 0.6 (5.2) 108 32.73 0.72 0.2 (5.6)

5 7 37.86 6.56 1.0 (5.5) 131 36.28 0.96 0.1 (2.3)

6 33 34.08 1.24 0.1 (2.2) 212 34.68 0.68 0.1 (3.7)

7 191 32.60 0.55 0.1 (4.5) 327 31.77 0.57 0.4 (1.9)

Total 492 33.28 0.42 0.2 (5.2)

1,583 33.44 0.26 0.3 (5.6)

54

Table 2. Total catch by species and gear in 2010 and 2011 in the Roanoke River, NC.

Highlighted species indicate target anadromous fish species classified as upstream migrants.

Anadromous fish determined to be post-spawn were classified as ‗spent‘ and assumed to be

out-migrating (downstream migrants), and are excluded from this catch table and further

analysis.

Common name Species Electrofishing

Set-gill

nets

Drift-gill

nets

2010 2011 2010 2011

Striped bass (adult) Morone saxatilis 507 216 15 52

Gizzard shad Dorosoma cepedianum 458 537 9 101

Striped mullet Mugil cephalus 451 118 1 2

Blueback herring Alosa aestivalis 396 484 - 12

White perch Morone americana 252 109 33 12

Longnose gar Lepisosteus osseus 247 291 1 17

Hickory shad Alosa mediocris 209 89 2 114

Common carp Cyprinus carpio 190 185 - 1

Largemouth bass Micropterus salmoides 80 86 1 -

Bowfin Amia calva 63 43 2 9

Alewife Alosa pseudoharengus 45 308 7 32

White catfish Ameriurus catus 38 37 67 3

Channel catfish Ictalurus punctatus 17 36 11 3

Notchlip redhorse Moxostoma collapsum 17 8 2 -

Blue catfish Ictalurus furcatus 8 3 20 17

Shorthead redhorse Moxostoma macrolepidotum 8 25 31 24

Chain pickerel Esox niger 5 2 - -

Atlantic needlefish Strongylura marina 4 3 - -

Redear sunfish Lepomis microlophus 4 21 - 1

Bluegill Lepomis macrochirus 3 4 - -

Black crappie Pomoxis nigromaculatus 2 9 - -

Pumpkinseed Lepomis gibbosus 2 - - -

American shad Alosa sapidissima - 1 - 24

Striped bass (immature) Morone saxatilis - 119 - -

Yellow perch Perca flavescens - 3 1 -

Redbreast sunfish Lepomis auritus - - 1 -

American eel Anguilla rostrata - 5 - -

Warmouth Lepomis gulosus - 1 - -

Totals 3006 2743 204 424

55



sampling.

Species First

Capture

Last

Capture

Max.

Capture

Max.

CPUE

Temperature (ºC)

First, last, (max.)

Alewife March 22 May 20 March 31 16.0 11, 22, (13)

Blueback herring March 22 May 11 April 19 37.0 10, 22, (17)

Hickory shad March 1 April 16 March 16 18.0 6, 16, (10)

Striped bass February 24 May 12 April 6 50.0 6, 21, (15)

White perch February 24 May 5 March 31 48.0 6, 21, (13)



sampling.

Species First

capture

Last

capture Max. Capture

Max.

CPUE

Temperature (ºC)

First, last, (max.)

Alewife March 3 April 13 March 15 84.0 11, 15, (11)

American shad April 18 April 18 April 18 2.0 16, 16, (16)

Blueback herring March 9 May 5 April 21 90.0 11, 21, (17)

Hickory shad March 4 April 11 March 14 18.0 11, 14, (11)

Striped bass March 7 May 6 April 25 66.0 11, 21, (18)

White perch March 15 May 20 April 19 24.0 11, 21, (16)

Table 5. Bottom-set gill net dates of first, last, and maximum catches, CPUE (fish/net-hour),

and corresponding water temperatures for first, last, and maximum captures during 2010

sampling.

Species First

Capture

Last

Capture

Max.

Capture

Max.

CPUE

Temperature (ºC)

First, last, (max.)

Alewife March 23 April 5 March 25 0.68 10, 14, (12)

Hickory shad March 19 March 31 March 29 0.18 10, 12, (12)

Striped bass April 2 April 30 April 19 1.05 13, 19, (17)

White perch March 19 April 30 April 9 0.98 10, 19, (16)

56

Table 6. Drift-gill net CPUE (fish∙drift-1

-set-1

) summary statistics and associated water

temperature in the Roanoke River, NC from February 24 to May 20, 2011

Species First

capture

Last

capture

Max.

Capture

Max.

CPUE

Temperature (ºC)

First, last, (max.)

Alewife March 2 April 13 March 4, 7 3.0 10.7, 15.1,

(11.0, 11.2)

American shad March 3 May 12 May 3 1.5 10.8, 21.0,

(11.8)

Blueback herring March 25 April 19 April 14 1.5 11.3, 16.6,

(16.6)

Hickory shad March 2 April 15 March 2, 8, 15 7.0 10.6, 15.8,

(11.9, 11.8, 10.8)

Striped bass April 11 May 9 April 13 11.0 10.7-20.7,

(15.1)

White perch March 2 May 3

March 4, 8,

May 3

1.0 10.7, 20.7,

(11.8, 11, 20.0)

57

Table 7. Mean length (mm) of anadromous species by gear during 2010 on the Roanoke

River, NC.

Electrofishing Bottom-set Gill nets

N Mean length SE Range N Mean length SE Range

Alewife 42 276 1.9 235-295 7 285 3.6 269-296

Blueback herring 396 251 0.8 203-307 0 - - -

Hickory shad 209 378 2.0 275-472 2 413 32.5 380-445

Striped bass 487 464 3.3 326-981 13 418 14.0 356-519

White perch 249 248 1.3 203-336 33 269 2.5 230-293

Table 8. Mean length (mm) of anadromous species by gear in during 2011 on the Roanoke

River, NC.

Boat Electrofishing Drift gill nets

N Mean length SE Range N Mean length SE Range

Alewife 308 280 1.0 220-333 32 297 2.1 273-312

American shad 1 364 - - 24 438 8.6 344-509

Blueback herring 484 244 0.9 200-297 12 269 3.0 255-287

Hickory shad 89 379 3.8 305-450 114 404 2.8 311-485

Striped bass 216 478 4.3 256-700 52 447 4.4 373-509

White perch 109 244 2.5 200-309 12 277 6.8 234-304

Table 9. Minimum, maximum, and mean daily CPUE (fish/h) for electrofishing in 2010 and

2011 on the Roanoke River, NC.

2010 2011

Min Max Mean Min Max Mean

Target species 0.0 189.9 47.2 0.0 172.0 43.1

Non-target species 0.0 145.8 51.9 8.0 175.4 54.7

Total catch 6.0 257.6 99.2 10.0 217.9 97.8

58

Table 10. Minimum, maximum, and mean daily bottom-set gill nets CPUE (fish/net hour)

and drift nets (fish/drift-set) 2010 and 2011 on the Roanoke River, NC. Drift set is defined

as one-200 m drift of each mesh size; two drift sets of four mesh sizes were conducted daily

and total catch was divided by 2 to calculate fish·drift-1

-set-1

.

2010 Bottom-set gill nets 2011 Drift gill nets

Min Max Mean Min Max Mean

Target species 0.0 1.5 0.3

0.0 16.0 2.2

Non-target species 0.0 2.3 0.7

0.0 6.0 1.6

Total catch 0.0 2.3 1.0 0.0 20.5 3.8

Table 11. Bottom-set gill net catch by species and mesh size captured in the Roanoke River,

NC from February 24 to May 20, 2010. Anadromous fish species include only those

classified as upstream migrants. Species titled ‗Other‘ refer to all non-target species

captured. ALE=alewife, HSH=hickory shad, STB=striped bass, WPR=white perch,

OTH=other non-target species.

Mesh

Size Effort ALE HSH STB WPR OTH

Anadromous

Species

Total

Catch

7 41.12 7 1 7 21 15 36

9 40.13 1 12 23 32 36 68

10 36.93 3 51 3 54

11.5 36.97 1 2 32 3 35

14 31.23 11 0 11

Totals 186.58 7 2 15 33 147 57 204

59

Table 12. Drift-gill net catch by species and mesh size from March 2 to May 20, 2011 in the

Roanoke River, NC. All drift gill nets were fished with equal effort. Anadromous fish

species include only those classified as upstream migrants. Species titled ‗Other‘ refer to all

non-target species captured. ALE=alewife, ASH=American shad, BBH=blueback herring,

HSH=hickory shad, STB=striped bass, WPR=white perch.

Mesh Size ALE ASH BBH HSH STB WPR Target

Species Other

Total

Catch

7 28 1 9 9 3 3 53 12 65

9 4 17 0 88 39 8 156 114 270

10 0 5 3 16 10 1 35 49 84

14 0 1 0 1 0 0 2 3 5

Total 32 24 12 114 52 12 246 178 424

Table 13. Modeled run size estimates and 95% credible intervals for 2010 and 2011.

2010 2011

Median

2.5 %

Quantile

97.5 %

Quantile Median

2.5 %

Quantile

97.5 %

Quantile

Alewife 201,600 178,400 226,700 308,900 277,900 344,000

American shad 18,360 13,350 25,030 33,250 24,840 43,450

Blueback herring 198,000 180,600 216,700 521,700 471,800 575,900

Hickory shad 172,700 150,000 196,300 151,300 130,500 175,100

Striped bass 333,600 307,300 361,100 630,400 576,200 690,800

White perch 307,600 280,300 337,400 415,600 375,100 460,800

Other 1,141,000 1,066,000 1,220,000 2,110,000 1,958,000 2,267,000

Total Run Size 2,373,000 2,264,000 2,493,000 4,174,000 3,907,000 4,446,000

60

Table 14. Modeled parameter estimates and 95% credible intervals of intercept, gear

multipliers (SonarGear), and strata (XStrata) for 2010 and 2011. ―DL‖ = down-looking,

―SL‖ = side-looking.

Description

Model

Parameter Mean

Std.

Deviation Median

2.5 %

Quantile

97.5 %

Quantile

2010

log(Intercept) Intercept -0.769 0.057 -0.766 -0.884 -0.661

DL DIDSON SonarGear ---Not estimated, fixed value (1.0)---

Split-beam (stratum 1) SonarGear 0.380 0.010 0.380 0.360 0.401




log(Stratum 1) XStrata 2.805 0.028 2.805 2.750 2.861



log(Stratum 4) XStrata ---Not estimated, fixed value (0.0)---

2011

log(Intercept) Intercept -0.635 0.059 -0.629 -0.775 -0.537

DL DIDSON SonarGear ---Not estimated, fixed value (1.0)---

SL DIDSON (stratum 1) SonarGear 0.553 0.028 0.553 0.498 0.608


SL DIDSON (stratum3) SonarGear 0.504 0.289 0.511 0.021 0.975









log(Stratum 4) XStrata ---Not estimated, fixed value (0.0)---

61

Table 15. Mean daily sonar count by stratum and overall mean count (standard error),

standardized to count∙m-2

∙d-1

, and ratio comparisons between sonar gears co-occurring in

strata. Abbreviations: DL= down-looking DIDSON, SL= side-looking DIDSON, and SB=

split-beam.

----------------------Strata--------------

Year Sonar Type 1 2 3 4 Overall Mean

(SE)

2010

DL DIDSON 116.98 93.65 21.01 2.57 27.63 (3.09)

Split-beam 81.46 - - 13.16 47.31 (3.62)

Ratio SB:DL 0.70 - - 5.11 -

2011

SL DIDSON 151.10 255.69 - - 195.66 (127.28)

DL DIDSON 265.05 350.80 111.43 10.33 102.04 (204.35)

Split-beam 48.67 - - 15.46 32.06 (28.51)

Ratio SB:DL 0.18 - - 1.50 -

Ratio SL:DL 0.57 0.73 - - -

62

Figure 1. Location of sonar and fish sampling sites in 2010 and 2011 on the Roanoke River,

NC. Starting points for electrofishing transects are denoted by EF 1, EF 2, EF 3, and EF 4.

High current velocities and net fouling issues prompted the relocation of bottom-set gill nets

site #1 upstream to the inside bend of site #2 on March 17, 2010.

63

Figure 2. Cross sectional view of the river profile, at hydroacoustic monitoring site (rkm

64)on the Roanoke River, NC. At full-bank river stage (shown), river width is 80 m. A

reference stake, used for standardizing fish detections from shore, was placed 80 m from the

west bank. .

-12-11-10-9-8-7-6-5-4-3-2-10

0 10 20 30 40 50 60 70 80

Dep

th (

m)

Distance from West Bank (m)

West Bank East Bank

64

Figure 3. Plot illustrating approximate split-beam deployment from February 24-May 20

2010. Split-beam was aimed cross channel, along river bottom for a 45-m range. Analyses

were restricted to 30 m to minimize effects of surface or bottom interference. Position of

split-beam unit moved inshore and out from shore as river level fluctuated. A fish diversion

fence (illustrated by black hatching from 65-80 m) was used to prevent fish from swimming

behind sonar. River level is illustrated at full-bank.

-12

-11

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

0 10 20 30 40 50 60 70 80

Dep

th (m

)


65

Figure 4. Plot illustrating approximate split-beam deployment from March 1-May 20 2011.

Split-beam was aimed cross channel using a 55-m range. Analyses were restricted to 30 m to

minimize effects of surface interference. Location of split-beam unit (red dot) was 19.05 m

from reference stake (~61 m from west bank) for the entire season. A fish diversion fence

was used to prevent fish from swimming behind sonar (illustrated by black hatching from 60-

80 m). River level is illustrated at full-bank.

-12

-11

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

0 10 20 30 40 50 60 70 80

Dep

th (m

)


66

Figure 5. Illustration of DL DIDSON samples during 2010 and 2011 on the Roanoke River,

NC. Seven cross-channel samples were taken each weekday, 10 m apart, for 10 minutes

each. Sample locations are numbered 1-7, beginning closest to the west bank. Note, down-

looking DIDSON site is approximately 30 m downstream of split-beam site and river width

is 10 m wider than split-beam site. River level is illustrated at full-bank.

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

0 10 20 30 40 50 60 70 80 90

Dep

th (

m)


1 2 3 4 5 6 7

67

Figure 6. Plot showing approximate location and beam location of SL DIDSON deployed on

the east bank of the Roanoke River, NC during 2011. DIDSON was tripod mounted, 17.5 m

from the reference stake, and observed a range of 10 m beyond fish diversion fence with

bottom visible throughout window extent. River level illustrated at full-bank.

Figure 7. Plot illustrating approximate location of west bank SL DIDSON monitoring. A 10

m window length was achieved, looking down the west bank slope with bottom visible from

2 m to window extent. Plot represents river at full-bank. Note, west bank SL DIDSON was

deployed at the same location as the DL DIDSON samples, approximately 30 m downstream

of split-beam and east bank DIDSON monitoring. No fish diversion fence was used on west

bank. River level illustrated at full-bank.

-12-11-10-9-8-7-6-5-4-3-2-10

0 10 20 30 40 50 60 70 80

Dep

th (

m)


-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

0 10 20 30 40 50 60 70 80 90

Dep

th (

m)


68

Figure 8. Location of bottom-set gill nets in the Roanoke River, NC during 2010. High

current velocities and net fouling issues prompted the move of bottom-set gill nets site #1

upstream to the inside bend of site #2 on March 17, 2010. Red dot indicates location of sonar

site (inset map).

Bottom-set gill net

site # 2, 2010

Bottom-set gill net

site #1, 2010

Gill net location

69

Figure 9. Illustration of cross-channel river profile (at full-bank water level) sectioned into 4

strata used to model count data from 2010 and 2011.

-12-11-10-9-8-7-6-5-4-3-2-10

0 10 20 30 40 50 60 70 80

Dep

th (

m)


14

3

2

70

Figure 10. Approximate placement of all sonar gear types in 2011 with respect to river strata

(red numbers 1-4) for analysis of count data. Legend abbreviations are SL DIDSON = SL

DIDSON and DL DIDSON = down-looking DIDSON. For display purposes, DL DIDSON

beams are not drawn, but location of sample is represented by orange ovals and sample

location denoted by black numbers 1-7. Fish diversion fence illustrated by black hatching

from 60-80 m.

-12-11-10-9-8-7-6-5-4-3-2-10

0 10 20 30 40 50 60 70 80

Dep

th (

m)


1 4

3

2 1 2 3 4 5 6 7

SL DIDSON

DL DIDSON Split-beam

71


discharge at Roanoke Rapids Dam, measured in cubic meters per second (m3/s), from

February 24 to May 20, 2010.


discharge at Roanoke Rapids Dam, measured in cubic meters per second (m3/s), from March

1 to May 20, 2011.

0

100

200

300

400

500

600

700

0

1

2

3

4

Riv

er D

isch

arge

(m3/s

)

Gag

e H

eight

(m)

Gage HeightRiver Discharge

0

100

200

300

400

500

0

1

2

3

4

Riv

er D

isch

arge

(m3/s

)

Gag

e H

eight

(m)

Gage Height

River Discharge

72

Figure 13. Surface water temperature (ºC) measured during sampling days in 2010 and 2011

on the Roanoke River.

0

5

10

15

20

25

Wate

r T

emp

eratu

re (

Cel

siu

s)

2010

2011

73

Figure 14. Daily split-beam counts, standardized to count·m

-2·day

-1 by split-beam sonar

from February 24 to May 20, 2010 on the Roanoke River, NC.

Figure 15. Daily split-beam counts, standardized to count·m

-2·day

-1 by split-beam sonar

from March 1 to May 20, 2011 on the Roanoke River, NC. Estimated count for day 48

(April 17; no sonar coverage) is included and indicated by the open circle and dashed line.

0

20

40

60

80

100

120

Count·

m-2

·day

-1

Total fish = 154,977

0

10

20

30

40

50

60

70

80

Co

unt·

m-2

·day

-1

Total fish = 89,102

74

Figure 16. Percent frequency of upstream fish tracks by hour detected by split-beam sonar in

2010 (solid black) and 2011 (dashed gray).

Figure 17. Daily counts standardized to count/h to account for unequal sample time (i.e.,

missed sample location) of upstream migrants from DL DIDSON samples from February 23,

2010 to May 20, 2010. A total of 492 upstream migrants were observed.

0

1

2

3

4

5

6

7

8

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Fre

quen

cy (

%)

Hour

2010 (N=154,977)

2011 (N=87,098)

0

5

10

15

20

25

Count/

h

N = 492

75

Figure 18. Percent frequency of upstream migrants by location observed by DL DIDSON

samples from February 23, 2010 to May 20, 2010. Upstream migrants observed during days

with missed sampled locations were removed (N=38). Locations began 10 m from west bank

and progressed cross-channel at 10 m intervals.

Figure 19. Distance off bottom distribution of upstream migrants observed with DL

DIDSON samples from February 23 to May 20, 2010.

0

5

10

15

20

25

30

35

40

45

1 2 3 4 5 6 7

Fre

quen

cy (

%)

Location

N = 454

0

10

20

30

40

50

60

70

80

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4+

Fre

quen

cy (

%)

Distance off bottom (m)

N = 492

76

Figure 20. Length frequency comparison of 2010 electrofishing and gill net captured fish

versus DL DIDSON images of upstream migrants, manually measured using SMC software.

Figure 21. Daily counts, standardized to count/h to account for unequal sample time (i.e.,

missed sample location), of upstream migrants from DL DIDSON samples from March 1,

2011 to May 20, 2011. A total of 1,583 upstream migrants were observed.

0

5

10

15

20

25

30

35

40

20 25 30 35 40 45 50 55 60 65 70 75 80+

Fre

quen

cy (

%)

Length Class (cm)

DL DIDSON N=492

Electrofishing N=3,001

Gill net N=204

0

10

20

30

40

50

60

70

80

Count/

h

N = 1,583

77

Figure 22. Cross-channel distribution of observed upstream migrants from DL DIDSON

samples in 2011. Upstream migrants observed during days with missed sampled locations

were removed (N=4). Locations began 10 m from west bank and progressed cross-channel at

10 m intervals.

Figure 23. Distance off bottom distribution of upstream migrants observed with down-

looking DIDSON samples from March 1 to May 20, 2011.

0

5

10

15

20

25

30

1 2 3 4 5 6 7

Fre

quen

cy (

%)

Location

N = 1,579

0

10

20

30

40

50

60

70

80

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4+

Fre

quen

cy (

%)

Distance off bottom (m)

N = 1,583

78

Figure 24. Length frequency comparison for 2011 of electrofishing and gill net captured fish

versus DIDSON images of upstream migrants. Down-looking DIDSON images were

manually measured using SMC software. Length estimates from SL DIDSON images were

obtained through automated Echoview processing.

0

5

10

15

20

25

30

35

20 25 30 35 40 45 50 55 60 65 70 75 80+

Fre

quen

cy (

%)

Length Class (cm)

EB DIDSON N=311,781

WB DIDSON N=54,872

DL DIDSON N=1,583

Electrofishing N=2,790

Drift gill net N=424

79

Figure 25. Corrected upstream migrant counts, from east bank (top) and west bank (bottom)

SL DIDSON, standardized to number of fish·hour-1

·m-2

to account for differences in

monitoring efforts across days in 2011.

0

5

10

15

20

25

30

35

0

5

10

15

20

25

Fis

h·h

-1·m

-2

East

bank

West

bank

80

Figure 26. Snapshot image of east bank SL DIDSON monitoring on the Roanoke River, NC

during 2011. DIDSON data were recorded in high frequency (1.8MHz) at 7 frames·sec-1

, a

window start of 2.5 m, and a window length of 10 m. Bottom substrate is visible throughout

the entire field of view (left frame), eliminating concern of ‗blind spots‘ in sampled range.

Background subtraction (within SMC software) is enabled on the right frame.

81

Figure 27. Frequency (%) of daily counts by hour (accounting for unequal sample effort

(days) across hours) from uncorrected east bank SL DIDSON monitoring during 2011.

Uncorrected counts were used to plot hourly passage because corrected counts were adjusted

on a daily scale, not hourly.

0

1

2

3

4

5

6

7

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Fre

quen

cy (

%)

Hour

82

Figure 28. Snapshot image of SL DIDSON monitoring the west bank on the Roanoke River,

NC during 2011. DIDSON data were recorded in high frequency (1.8MHz) at 8 frames/sec,

a window start of 0.42 m, and a window length of 10 m. Substrate along the bank and

bottom is visible from 2 m to end of window length in left pane. Background subtraction

(within SMC software) is enabled in the right panel to better illustrate fish in the frame.

83

Figure 29. Correction factor analysis based on automated counts (Echoview‘s fish tracking

algorithm) versus manual counts: Panel A, 2010 split-beam; Panel B, 2011 split-beam; Panel

C, east bank SL DIDSON period 1; Panel D east bank SL DIDSON period 2; Panel E, east

bank SL DIDSON period 2 re-fit; Panel F, west bank SL DIDSON. Counts for which the

regression intercept was not statistically different than zero and slope not statistically

different than 1.0 were not corrected (panels A, B, F). There was no detectable relationship

between automated and manual counts from east bank SL DIDSON during Period 1 (March

1-11; Panel C); therefore average manual count (accounting for time and area sampled) were

applied to all days during Period 1. Automatic counts from east bank SL DIDSON (EB

DIDSON) during Period 2 (March 12-May 20; Panel E) were corrected using the estimated

slope from the refit regression. Red-dotted line represents one-to-one line and black line

represents fitted regression.

0

20

40

60

80

100

120

140

0 20 40 60 80 100 120 140

y= -0.1661 + 0.778x

R2 = 0.818

p < 0.0001

D

0

20

40

60

80

100

0 10 20 30 40 50 60

y= -4.1373 + 1.1539x

R2 = 0.888

p < 0.0001

F

0

5

10

15

0 20 40 60 80 100

y= 8.7587 - 0.0567x

R2 = 0.117

p = 0.16

C

0

20

40

60

80

100

0 20 40 60 80 100

y= 2.6026 + 0.9108x

R2 = 0.937

p < 0.0001

B

0

50

100

150

200

0 50 100 150 200

1 to 1 line

Linear (line fit)

y= -3.1370 + 1.0203x

R2 = 0.932

p < 0.0001

A

0

20

40

60

80

100

120

140

0 20 40 60 80 100 120 140

Ey = 0.775x

R² = 0.8182

p < 0.0001

Man

ual

Co

unt

Auto Count

84

Figure 30. Proportion of species captured by electrofishing and bottom-set gill nets from

February 23-May 20, 2010 (top panel) and electrofishing and drift gill nets from February

28-May 20, 2011 (bottom panel) on the Roanoke River, NC. Species abbreviations are:

ALE=alewife, ASH=American shad, BBH=blueback herring, HSH=hickory shad,

STB=striped bass, WPR=white perch, OTH=other.

0.0

0.2

0.4

0.6

0.8

1.0

Pro

port

ion o

f C

atch

OTH

WPR

STB

HSH

BBH

ASH

ALE

0.0

0.2

0.4

0.6

0.8

1.0

Pro

port

ion o

f C

atch

OTH

WPR

STB

HSH

BBH

ASH

ALE

85

Figure 31. Electrofishing CPUE (fish/h) for targeted anadromous species and non-target

species from February 24 to May 20, 2011 in the Roanoke River, NC.

Figure 32. Electrofishing CPUE (fish/h) of targeted anadromous fish species from February

24 to May 20, 2010. Species abbreviations are: ALE=alewife, ASH=American shad,

BBH=blueback herring, HSH=hickory shad, STB=striped bass, WPR=white perch.

0

20

40

60

80

100

120

140

160

180

200

CP

UE

(fi

sh/h

)

Target species

Non-target species

0

20

40

60

80

100

120

140

160

180

200

CP

UE

(fi

sh/h

)

WPR

STB

HSH

BBH

ASH

ALE

86

Figure 33. Boat electrofishing CPUE (fish/h) for targeted anadromous species and non-target

species from March 1 to May 20, 2011 in the Roanoke River, NC.

Figure 34. Electrofishing CPUE (fish/h) of targeted anadromous fish species from March 1

to May 20, 2011. Species abbreviations are: ALE=alewife, ASH=American shad,

BBH=blueback herring, HSH=hickory shad, STB=striped bass, WPR=white perch.

0

20

40

60

80

100

120

140

160

180

200

CP

UE

(fi

sh/h

)

Target speciesNon-target species

0

20

40

60

80

100

120

140

160

180

200

CP

UE

(fi

sh/h

)

WPR

STB

HSH

BBH

ASH

ALE

87

Figure 35. Bottom-set gill net CPUE (fish/net-hour) of target and non-target species during

2010 on the Roanoke River, NC. Net site #1 was fished through March 16, 2010. From

March 17-May 19 all nets were set at net site # 2.

Figure 36. Bottom-set gill net CPUE (fish/net hour) for individual target species during 2010

on the Roanoke River, NC. Species abbreviations are: ALE=alewife, HSH=hickory shad,

STB=striped bass, WPR=white perch.

0.0

0.5

1.0

1.5

2.0

2.5

CP

UE

(fi

sh/n

et h

our)

Non-target species

Target species

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

CP

UE

(fi

sh/n

et h

our)

WPR

STB

HSH

ALE

88

Figure 37. Drift gill net CPUE (fish/drift-set) of target anadromous species and non-target

species from March 2-May 20, 2011 in the Roanoke River, NC. Drift-set is equivalent to

each mesh size drifted once on a given day.

Figure 38. Individual species‘ drift gill net CPUE (fish/drift-set) of target anadromous

species and OTH (non-target species) from March 2-May 20, 2011 in the Roanoke River,

NC. Drift-set is equivalent to each mesh size drifted once on a given day.

0.0

5.0

10.0

15.0

20.0

25.0

CP

UE

(fi

sh/d

rift

-set

)

Non-Targets

Target Species

0.0

5.0

10.0

15.0

20.0

25.0

CP

UE

(fi

sh/d

rift

-set

)

OTHWhite perchStriped bassHickory shadBlueback herringAmerican shadAlewife

89


credible intervals (dotted lines) for targeted anadromous fish in 2010.


credible intervals (dotted lines) for targeted anadromous fish in 2011.

0

10

20

30

40

50

60

70

80

90

Run S

ize

(thousa

nds)

0

20

40

60

80

100

120

140

160

180

200

Run S

ize

(thousa

nds)

90

Figure 41. Hydroacoustic species specific run-size estimates for all eight years of




intervals were available for 2004 estimates.

Ru

n S

ize

Est

imat

e (t

ho

usa

nd

s)

0

200

400

600

800 Alewife

0

10

20

30

40

50American shad

0100200300400500600700 Blueback herring

0

50

100

150

200

250

300 Hickory shad

0

200

400

600

800 Striped bass

0

100

200

300

400

500 White Perch

91

Figure 42. Hydroacoustic total upstream migrant run-size estimates for all eight years of




intervals were available for 2004 estimates (Mitchell 2006).

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Run-s

ize

Est

imat

e (m

illi

ons)

92

Figure 43. Ratio of standardized counts (black line; fish·hour-1

·m-2

) between split-beam and

east bank (stratum 1) SL DIDSON during 2011. Blue line indicates water level (m),

measured at USGS gage 02081054 at Williamston, NC.

0

0.5

1

1.5

2

2.5

3

3.5

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Gag

e hei

ght

(m)

Spli

t-bea

m:E

ast

ban

k D

IDS

ON

SB:SL DIDSON

Gage height

93


credible intervals for targeted anadromous fish in 2010. Note y-axis not uniform between

species.

0

5

10

15

20Alewife

0

1

2

3American shad

0

2

4

6

8

10

12Blueback herring

0

5

10

15

20Hickory shad

0

5

10

15

20White perch

0

5

10

15

20Striped bass

Ru

n S

ize

Est

imat

e (t

ho

usa

nd

s)

94

Figure 45. Daily median (solid line) modeled run size estimates in thousands with 95%

credible intervals for targeted anadromous fish in 2011. Note y-axis not uniform.

Ru

n S

ize

Est

imat

e (t

ho

usa

nd

s)

0

5

10

15

20

25

30

35Alewife

0

1

2

3American shad

0

10

20

30

40

50

60Blueback herring

0

2

4

6

8

10

12 Hickory shad

0

5

10

15

20

25

30

35Striped bass

0

5

10

15

20White perch

95


modeled estimate (green) with 95% credible intervals during 2010.


modeled estimate (green) with 95% credible intervals during 2011.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1 2 3 4 5 6 7 8 9 10 11 12 13

Pro

port

ion

Week

NCSU

Model Estimate

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1 2 3 4 5 6 7 8 9 10 11 12

Pro

port

ion

Week

NCSU

Model Estimate

96

APPENDICES

97

Appendix Table 1. Correction factor analysis based on automated counts (Echoview‘s fish

tracking algorithm) versus manual counts. Counts for which the regression intercept was not

statistically different than zero and slope not statistically different than 1.0 were not

corrected. There was no detectable relationship between automated and manual counts from

east bank SL DIDSON (EB DIDSON) during Period 1 (March 1-11); therefore average

manual count (accounting for time and area sampled) were applied to all days during Period

1. Automatic counts from east bank SL DIDSON (EB DIDSON) during Period 2 (March 12-

May 20, 2011) were corrected using the estimated slope from the refit regression.

Correlation

Coefficient (R2)

Term Estimate Std. Error t Ratio Prob>|t|

2010 Split-beam

(N = 26) 0.932

Intercept -3.14 2.58 -1.22 0.24

Slope 1.020 0.06 18.11 <.0001

2011 Split-beam

(N = 24) 0.937

Intercept 2.60 1.45 1.80 0.09

Slope 0.911 0.05 18.13 <.0001

2011 EB DIDSON

Period 1

(N = 18)

0.117

Intercept 8.76 1.78 4.93 0.0002

Slope -0.057 0.04 -1.46 0.1645

2011 EB DIDSON

Period 2

(N = 30)

0.818

Intercept -0.17 3.25 -0.05 0.96

Slope 0.778a 0.07 11.23 <.0001

2011 EB DIDSON

Period 2

Refit (no-intercept)

Slope 0.775* 0.05 17.21 <.0001

2011 West Bank

DIDSON

(N = 22)

0.888

Intercept -4.14 2.83 -1.46 0.16

Slope 1.154 0.09 12.62 <.0001

a Slope significantly different

from 1

* Correction factor applied to counts

98

Appendix Figure 1. Image showing west bank SL DIDSON deployment. The DIDSON as

mounted to a pole on the stern of the boat and aimed down along the bank slope.

99

Appendix Figure 2. Snap shot images taken from DL DIDSON samples in the Roanoke

River. Panels 1 and 2 represent large fish (~70 and 77 cm respectively). Panel 3illustrates a

school of small fish (~25-30 cm) and Panel 4 represents a small school of slightly larger fish

(~30-40 cm). Panel 5 is more than likely a longnose gar, based on length (107 cm) and body

shape, and as well as the fish in Panel 6 (length = 90 cm).

2

3

4

5

6

1

100

Appendix Figure 3. Processing template used within Echoview software to analyze SL

DIDSON data. The data flow is as follows: 1) a ping subset is drawn from raw data (Sv

frames) to calculate and subtract background noise (i.e., river bottom substrate), 2)

smoothing filters (median and dilation) are applied, 3) multibeam target detection applied,

4)a target length threshold to filter out fish less estimated to be less than 20 cm, 5) Single

target conversion to convert data into single target data that enables use of fish track

detection algorithm.

1

2

3

4

5

101

Appendix Figure 4. Side-looking DIDSON images illustrating a large school of suspected

longnose gar milling in the sonar‘s field of view. All images are of the same school at the

same time. Panel 1A and 1B are echogram displays and Panels 2A and 2B are snapshots of

the recording view in DIDSON SMC software. Panels 1A and 2B do not have background

subtraction enabled, in contrast to Panels 1A and 1B which use background subtraction and

cluster data.

1A 1B

2A 2B

102

Appendix Figure 5. Roanoke River run size model for 2010. Hydroacoustic sampling

parameters include 88 days (alpha), two sonar gears/deployments (SonarGear), and four river

cross sectional strata (XStrata).

104

Appendix Figure 6. Roanoke River run size model for 2011. Hydroacoustic sampling

parameters include 81 days (alpha), three sonar gears/deployments (SonarGear), and four

river cross sectional strata (XStrata).

106

Appendix Figure 7. Proportion of species in in-river sampling, ―NCSU‖, (electrofishing and

gill nets), North Carolina Department of Marine Fisheries gill net survey, and the Bayesian

modeled estimate of proportion of species used to apportion sonar counts in 2010.

107

0.00

0.20

0.40

0.60

0.80

1.00Week 2 DMF (prior) N= 91

NCSU N=8Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00Week 3

DMF (prior) N= 91

NCSU N=59

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00Week 4

DMF (prior) N= 266

NCSU N=66

Model Estimate

0.00

0.20

0.40

0.60

0.80



0.00

0.20

0.40

0.60

0.80


NCSU N=196

Model Estimate

0.00

0.20

0.40

0.60

0.80


NCSU N=312

Model Estimate

0.00

0.20

0.40

0.60

0.80


NCSU N=237

Model Estimate

0.00

0.20

0.40

0.60

0.80



Pro

po

rtio

n o

f S

pec

ies

108

0.00

0.20

0.40

0.60

0.80

1.00

Week 9DMF (prior) N= 239

NCSU N=342

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00


NCSU N=141

Model Estimate

0.00

0.20

0.40

0.60

0.80


NCSU N=31

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00


NCSU N=3

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00

Week 13 DMF (prior) N= 104

NCSU N=5

Model Estimate

Pro

port

ion o

f S

pec

ies

109

Appendix Figure 8. Proportion of species in in-river sampling, ―NCSU‖, (electrofishing and

gill nets), North Carolina Department of Marine Fisheries gill net survey, and the Bayesian

modeled estimate of proportion of species used to apportion sonar counts in 2011.

110

0.00

0.20

0.40

0.60

0.80

1.00Week 1 DMF (prior) N = 131

NCSU N = 53

Model Estimate

0.00

0.20

0.40

0.60

0.80


NCSU N = 87

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00

Alewife A. shad Blueback

herring

Hickory

shad

Striped

bass

White

perch

Week 3 DMF (prior) N = 131

NCSU N = 220

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00Week 4

DMF (prior) N = 268

NCSU N = 138

Model Estimate

0.00

0.20

0.40

0.60

0.80


NCSU N = 107

Model Estimate

0.00

0.20

0.40

0.60

0.80

1.00


herring

Hickory

shad

Striped

bass

White

perch


NCSU N = 165

Model Estimate

Pro

po

rtio

n o

f S

pec

ies

111

0.00

0.20

0.40

0.60

0.80


NCSU N = 247Model Estimate

0.00

0.20

0.40

0.60

0.80



0.00

0.20

0.40

0.60

0.80

1.00


herring

Hickory

shad

Striped

bass

White

perch

Week 9 DMF (prior) N = 112NCSU N = 125Model Estimate

0.00

0.20

0.40

0.60

0.80



0.00

0.20

0.40

0.60

0.80



0.00

0.20

0.40

0.60

0.80

1.00


herring

Hickory

shad

Striped

bass

White

perch


NCSU N = 8

Model Estimate

Pro

po

rtio

n o

f S

pec

ies

112

Appendix Figure 9. Estimated total run size (median) for strata in 2011. High run size

estimates for shoreline (Strata 1-2) versus mid-channel (Strata 3-4) regions illustrate the

importance of effectively monitoring nearshore regions.

0

20

40

60

80

100

120

140

160

180M

edia

n E

stim

ate

(thousa

nds)

Stratum 2

Stratum 4

Stratum 3

Stratum 1

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