OCS Study 

MMS 2003-029 

 

Coastal Marine Institute 

Importance of Zooplankton in the Diets 

of Blue Runner (Caranx crysos) Near 

Offshore Petroleum Platforms 

in the Northern Gulf of Mexico 

Cooperative Agreement

Coastal Marine Institute 

Louisiana State University 

U.S. Department of the Interior

Minerals Management Service 

Gulf of Mexico OCS Region 
U.S. Department of the Interior Cooperative Agreement 

Minerals Management Service Coastal Marine Institute 

Gulf of Mexico OCS Region Louisiana State University 

OCS Study 

 MMS 2003-029 

 

Coastal Marine Institute 

Importance of Zooplankton in the Diets 

of Blue Runner (Caranx crysos) Near 

Offshore Petroleum Platforms 

in the Northern Gulf of Mexico 

Authors 

Sean F. Keenan 

Mark C. Benfield 

July 2003 

Prepared under MMS Contract 

1435-01-99-CA-30951-17802 

by 

Coastal Fisheries Institute 

Louisiana State University 

Baton Rouge, Louisiana 70803 

Published by 
iii

DISCLAIMER

This report was prepared under contract between the Minerals Management Service (MMS) and

the Coastal Fisheries Institute (CFI), Louisiana State University (LSU). This report has been

technically reviewed by the MMS and it has been approved for publication. Approval does not

signify that the contents necessarily reflect the view and policies of LSU or the MMS, nor does

mention of trades names or commercial products constitute endorsement or recommendation for

use. It is, however, exempt from review and compliance with the MMS editorial standard.

REPORT AVAILABILITY

Extra copies of the report may be obtained from the Public Information Office (Mail Stop 5034)

at the following address:

U.S. Department of the Interior

Minerals Management Service

Gulf of Mexico OCS Region

Public Information Office (MS 5034)

1201 Elmwood Boulevard

New Orleans, Louisiana 70123-2394

Telephone: (504) 736-2519 or

 1-800-200-GULF

CITATION

Suggested citation:

Keenan, S.F. and M.C. Benfield. 2003. Importance of zooplankton in the diets of Blue Runner

(Caranx crysos) near offshore petroleum platforms in the Northern Gulf of Mexico.

Prepared by the Coastal Fisheries Institute, Louisiana State University. U.S. Dept. of the

Interior, Minerals Management Service, Gulf of Mexico OCS Region, New Orleans, LA.

OCS Study MMS 2003-029. 129 pp.

ABOUT THE COVER

The underwater photograph of blue runner beneath a platform was provided by Greg Boland,

Minerals Management Service, New Orleans, LA.
v

ACKNOWLEDGMENTS

This report encompasses much of the thesis research of Sean Keenan and therefore he

would like to thank committee members, Dr. Sam Bentley, Dr. Jim Cowan and Dr. Richard

Shaw and the co-author, for their support, helpful comments and advice. We are also grateful to

all the faculty and staff in the Department of Oceanography and Coastal Sciences and the Coastal

Fisheries Institute for providing support throughout his graduate career.

The foundation of this project stemmed from an undergraduate research project funded

by Louisiana State University/Louisiana Sea Grant – Undergraduate Research Opportunities

Program. Funding for the research cruises to VK203A and MP140A was provided to the authors

from a LSU – Minerals Management Service Coastal Marine Institute grant (1435-01-99-CA30951, Task Order 17802). We are indebted to Dr. Richard Shaw and his laboratory for

providing the resources and logistical support for trips to GI94B and MP259A. We also want to

thank Dr. Bob Downer for advice on statistical procedures. In addition, Sean Keenan received

travel support from the Department of Oceanography and Coastal Sciences and the LSU

Graduate School to present this research at meetings in Key West, Florida and Honolulu, Hawaii.

Fieldwork would not have been possible without the help of the crews of GI94B and

MP259A, and the captain and crew of the Admiral Semmes (Capt. Jim Skinner, Rene Barletter,

and Joseph Dardar). Dave Lindquist, Jim Ditty, and John Plunkett helped collect data on

platform trips and Aaron Adamack and Allan Keenan provided valuable assistance on cruises.

LSU students Paula Deland and Candace Johnson provided a great deal of help in sorting

plankton samples. I am also greatly indebted to Hongsheng Bi and Shane Harrell who donated a

monumental amount of time and effort both on research cruises and in the laboratory. This

project would not have been possible without their valuable assistance.
vii

ABSTRACT

Blue runner (Caranx crysos), common around offshore petroleum platforms in the Gulf

of Mexico, were found to forage extensively on meso- and macro-zooplankton during the

summer months. Larval decapods and stomatopods, hyperiid amphipods, pteropods, and larval

and juvenile fishes were common components of their diet. Feeding periodicity results suggest

that blue runner around platforms were capable of feeding throughout the night at the same

intensity as the day. Size selectivity indicated that larger prey, such as fish were consumed

during the night and smaller decapod crustaceans were consumed during the day. Blue runner

collected from open waters away from platforms also consumed decapods and larval fish as well

as other abundant zooplankton such as chaetognaths. Although certain zooplankton taxa

exhibited increased densities near the platform during some cruises, plankton net sampling did

not demonstrate consistently elevated densities of zooplankton in proximity to petroleum

platforms. Zooplankton density was generally greater during the night samples, however a

platform enhancement effect was not observed. Results from ADCP surveys suggested that

zooplankton and ichthyoplankton contributed to the measured volume backscattering strength.

Diel and between-cruise changes in zooplankton density were correlated with changes in

acoustic scattering levels during acoustic surveys conducted around the platforms. These

surveys demonstrated the utility of an ADCP to examine small-scale patterns in sound scattering

layers in surface waters around platforms, however preliminary analysis did not establish that

elevated (or reduced) levels of scattering existed near platforms. Examination of more surveys

along with including data on current velocity will provide further insight into the localized

effects of these structures. The net and acoustic data collected in this study suggested that more

intensive sampling closer to platforms is needed to understand how these structures support large

aggregations of fishes such as blue runner.
ix

TABLE OF CONTENTS

Page

Acknowledgments ...........................................................................................................v

Abstract ........................................................................................................................ vii

List of Figures ............................................................................................................... xi

List of Tables.............................................................................................................. xvii

Chapter I. General Introduction......................................................................................1

Chapter II. Zooplanktivory by Blue Runner (Caranx crysos) I: A

Potential Energetic Subsidy to Gulf of Mexico Fish

Populations at Petroleum Platforms ...............................................................5

Chapter III. Zooplanktivory by Blue Runner (Caranx crysos) II: A

Comparison Between Platform-Associated and NonPlatform-Associated Fish ............................................................................21

Chapter IV. Spatial Variability of Meso- and Macro-Zooplankton

in Surface Waters Near Offshore Petroleum

Platforms in the Northern Gulf of Mexico .................................................53

Chapter V. General Summary .....................................................................................113

Literature Cited............................................................................................................117

Appendix: Letter of Permission ...................................................................................127

Vita .............................................................................................................................129
xi

LIST OF FIGURES

Figure Page

1. Location and images of platforms sampled in 1996 (GI94B)

and 1999 (MP259A).............................................................................................7

2. Numerical proportion and gravimetric proportion for the prey

items in the diets of blue runner from the two platforms

sampled..............................................................................................................11

3. Gravimetric proportion of zooplankton occurring in the

diets of blue runner over all sizes collected from GI94B and

MP259A ............................................................................................................12

4. Stomach fullness values for blue runner collected over the

summer at GI94B and MP259A .........................................................................15

5. Length frequency distributions for decapods taken from A)

surface plankton net, B) stomachs of concurrently captured

blue runner, and C) chi-square analysis for biased size

selection during June 1999 at the MP259A platform...........................................16

6. Length distributions of hyperiid amphipods collected from a

surface plankton net and from blue runner stomachs in June

1999 at MP259A ................................................................................................17

7. Geographical location and images of platforms for summer

2000 sampling trips............................................................................................24

8. Temperature depth diagrams for each trip during a) day and b)

night...................................................................................................................30

9. Numerical proportion and gravimetric proportion for the prey

items in the diets of blue runner from the summer 2000

sampling trips.....................................................................................................31

10. Fullness index for blue runner collected during the diel

sampling trip (1–3 August 2000) to VK203A .....................................................34

11. Difference in weight contribution to the diet during the diel

sampling trip for fish and decapod/stomatopod prey...........................................34

12. Daytime size selection for decapod/stomatopod prey from blue

runner during the 12–16 June trip (MP140A) .....................................................37
xii

LIST OF FIGURES (continued)

Page

13. Daytime size selection for decapod/stomatopod prey of blue

runner from 26–29 June trip (MP140A)..............................................................38

14. Daytime size selection for fish prey of blue runner from the

12–16 June trip (MP140A).................................................................................39

15. Daytime size selection for fish prey of blue runner from the

26–29 June trip (MP140A).................................................................................40

16. Daytime Chesson's alpha selectivity test for a) decapods and b)

fish for blue runner pooled over 12–16 June and 26–29 June

trips to MP140A.................................................................................................41

17. Nighttime size selection for decapod/stomatopod prey by blue

runner during the 12–16 June trip (MP140A) .....................................................42

18. Nighttime size selection for decapod/stomatopod prey by blue

runner during the 26–29 June trip (MP140A) .....................................................43

19. Nighttime size selection for fish prey by blue runner during the

12–16 June trip (MP140A).................................................................................44

20. Nighttime size selection for fish prey by blue runner during the

26–29 June trip (MP140A).................................................................................45

21. Nighttime Chesson's alpha selectivity test for a) decapods and

b) fish for blue runner pooled over 12–16 and 26–29 June trips

to MP140A ........................................................................................................46

22. Size selection for decapod/stomatopod prey by blue runner

caught from open waters during 6–9 August 2000..............................................47

23. Size selection for fish prey by blue runner caught from open

waters during 6–9 August 2000 ..........................................................................48

24. Example of one set of samples designed to evaluate the

influence of a platform on the density of zooplankton up-current

and down-current of a platform ..........................................................................56

25. Two-dimensional GPS plot of a typical survey around a

platform .............................................................................................................59

26. Daytime density of zooplankton categories during summer 2000

cruises................................................................................................................61
xiii

LIST OF FIGURES (continued)

Page

27. Nighttime density of zooplankton categories during summer

2000 cruises .......................................................................................................62

28. Total zooplankton density from plankton net samples during

each daytime set of net hauls during each cruise.................................................63

29. Fish density from plankton net samples during each daytime set

of net hauls during each cruise ...........................................................................64

30. Decapod/Stomatopod density from plankton net samples during

each daytime set of net hauls during each cruise.................................................65

31. Amphipod density from plankton net samples during each

daytime set of net hauls during each cruise.........................................................66

32. Chaetognath density from plankton net samples during each

daytime set of net hauls during each cruise.........................................................67

33. Pteropod density from plankton net samples during each

daytime set of net hauls during each cruise.........................................................68

34. Copepod density from plankton net samples during each

daytime set of net hauls during each cruise.........................................................69

35. Gelatinous zooplankton density from plankton net samples

during each daytime set of net hauls during each cruise......................................70

36. Egg density from plankton net samples during each daytime set

of net hauls during each cruise ...........................................................................71

37. Total zooplankton density from plankton net samples during

each nighttime set of net hauls during each cruise ..............................................72

38. Fish density from plankton net samples during each nighttime

set of net hauls during each cruise ......................................................................73

39. Decapod/Stomatopod density from plankton net samples during

each nighttime set of net hauls during each cruise ..............................................74

40. Amphipod density from plankton net samples during each

nighttime set of net hauls during each cruise.......................................................75

41. Chaetognath density from plankton net samples during each

nighttime set of net hauls during each cruise.......................................................76
xiv

LIST OF FIGURES (continued)

Page

42. Pteropod density from plankton net samples during each

nighttime set of net hauls during each cruise.......................................................77

43. Copepod density from plankton net samples during each

nighttime set of net hauls during each cruise.......................................................78

44. Gelatinous zooplankton density from plankton net samples

during each nighttime set of net hauls during each cruise ...................................79

45. Egg density from plankton net samples during each nighttime

set of net hauls during each cruise ......................................................................80

46. Regression of taxa density from day net samples versus distance

from VK203A during the 5–8 June cruise ..........................................................82

47. Regression of taxa density from day net samples versus distance

from MP140A during the 12–16 June cruise.......................................................83

48. Regression of taxa density from day net samples versus distance

from MP140A during the 26–29 June cruise.......................................................84

49. Regression of taxa density from day net samples versus distance

from VK203A during the 17–20 July cruise .......................................................85

50. Regression of taxa density from night net samples versus

distance from VK203A during the 5–8 June cruise.............................................86

51 Regression of taxa density from night net samples versus

distance from MP140A during the 12–16 June cruise .........................................87

52. Regression of taxa density from night net samples versus

distance from MP140A during the 26–29 June cruise .........................................88

53. Regression of taxa density from night net samples versus

distance from VK203A during the 17–20 July cruise..........................................89

54. Regressions of volume backscatter to logarithm of density for

each taxon identified from the daytime during the 5–8 June

cruise to VK203A ..............................................................................................91

55. Regressions of volume backscatter to logarithm of density for

each taxon identified from day 1 during the 12–16 June cruise

to MP140A ........................................................................................................92
xv

LIST OF FIGURES (continued)

Page

56. Regressions of volume backscatter to logarithm of density for

each taxon identified from the day 2 sampling during the 12–16

June cruise to MP140A ......................................................................................93

57. Regressions of volume backscatter to logarithm of density for

each taxon identified from the nighttime sampling during the

5–8 June cruise to VK203A................................................................................94

58. Regressions of volume backscatter to logarithm of density for

each taxon identified from the night 1 sampling during the

12–16 June cruise to MP140A............................................................................95

59. Regressions of volume backscatter to logarithm of density for

each taxon identified from the night 2 sampling during the

12–16 June cruise to MP140A............................................................................96

60. Volume-specific total wet weight of zooplankton taxa taken

from 12–16 June trip ..........................................................................................97

61. Linear regressions of logarithm of biomass to volume

backscatter for each zooplankton category during the day and

night net tows of 12–16 June (MP140A) ............................................................98

62. Three-dimensional perspective of the daytime acoustic survey

during the 5–8 June cruise to VK203A.............................................................100

63. Two-dimensional perspective of Sv through time during the

daytime acoustic survey of the 5–8 June cruise (VK203A) ...............................101

64. Three-dimensional perspective of the nighttime acoustic survey

conducted during the 5–8 June cruise to VK203A ............................................102

65. Two-dimensional perspective of Sv through time during the

nighttime acoustic survey of the 5–8 June cruise (VK203A).............................103

66. Three-dimensional perspective of the daytime acoustic survey

conducted during the 12–16 June cruise to MP140A ........................................104

67. Two-dimensional perspective of Sv through time during the

daytime acoustic survey of the 12–16 June cruise (MP140A) ...........................105

68. Three-dimensional perspective of the nighttime acoustic survey

conducted during the 12–16 June cruise to MP140A ........................................106
xvi

LIST OF FIGURES (continued)

Page

69. Two-dimensional perspective of Sv through time during the

nighttime acoustic survey of the 12–16 June cruise (MP140A).........................107
xvii

LIST OF TABLES

Table Page

1. Regressions fitted for three prey categories commonly

consumed by blue runner....................................................................................... 9

2. Summary of the diets of blue runner taken during each

sampling trip to GI94B and MP259A .................................................................... 13

3. Summary of sampling activities associated with quantification

of blue runner diets for each cruise during summer 2000

research trips in the northern Gulf of Mexico ........................................................ 25

4. Summary of blue runner diets for all sampling trips to

VK203A and MP140A.......................................................................................... 32

5. Daytime prey type selectivity showing average alpha values

for each prey category during samples with n > 5 blue runner ............................... 35

6. Combined prey type selectivity data for time of day from

platform and open water blue runner ..................................................................... 35

7. Summary of sampling activities associated with surface

zooplankton collections and acoustic sampling for each cruise

during summer 2000 research trips in the northern GOM ...................................... 59
1

Chapter I

General Introduction

The offshore petroleum platforms in the northern Gulf of Mexico have been described as

the largest unplanned artificial reef complex in the world (Kasprzak 1998, Stanley and Wilson

2000b). There are over 4,000 platforms

(http://www.gomr.mms.gov/homepg/fastfacts/WaterDepth/WaterDepth.html; as of June 2002) in

the northern Gulf of Mexico where the majority of substrate is clay, silt, or sand (Parker et al.

1983). Platforms provide an additional 12 km2 of “reef” habitat (Stanley and Wilson 1997) to

the estimated 2,571 km2

 (737 – 6,388 km2; 95% CL) of natural hard bottom habitat from

Pensacola, Florida and Pass Cavello, Texas (Parker et al. 1983). What they lack in surface area,

platforms make up with a unique vertical orientation that extends the benthic community into the

water column. The three-dimensional structure of platforms provides substrate for encrusting

organisms such as corals and sponges as well as habitat for many species of demersal fishes. In

addition to the reef community found near platforms, pelagic fish species (i.e., jacks, spadefish,

mackerels, and tunas) are often associated with these structures (Seaman et al. 1989) and schools

often reach many thousands of individuals (Stanley and Wilson 2000a). How platforms affect

fish assemblages remains an important question in understanding how these structures function

as productive artificial reefs.

Studies on fish populations around platforms began in the mid 1970’s and primarily

included qualitative surveys of adult fish and encrusting communities (Hastings et al. 1976;

Gallaway 1980; and Sonnier et al. 1976). These studies utilized diver visual surveys to evaluate

species composition and abundance. With expansion of underwater video equipment and ROV

technology, surveys were conducted over longer time spans and into deeper waters (Seaman et

al. 1989; Stanley 1994; Love et al. 1999 and 2000). Love et al. (1999) utilized ROVs to evaluate

vertical distribution of platform associated fishes off the California coast to depths of 224 m.

Advances over this “snapshot” view of platform-associated fauna came about with the

emergence of hydroacoustics (Jennings et al. 2001). Gerlotto et al. (1989) evaluated relative

densities of fishes near platforms off Cameroon Africa by using towed hydroacoustics. Stanley

(1994) pioneered the use of stationary dual-beam hydroacoustics along with ROV surveys to

evaluate fish populations near a platform in the northern Gulf of Mexico. He estimated that

between 2,000 and 28,000 fishes covering 19 different species were associated with a given

structure at any one time and noted that abundance varied greatly with season. Fish densities

were shown to decrease significantly beyond a 16 m radius around the structure and further

research by Stanley and Wilson (1997) reported fish densities beyond 30 m were similar to

ambient, open-water densities.

In addition to platforms, research has demonstrated increased fish densities near drifting

objects (Gooding and Magnuson 1967; Druce and Kingsford 1995), fish attracting devices

(FADs; Klima and Wickham 1971; Ibrahim et al. 1996) and artificial reefs (Bohnsack 1989;

Lindquist and Pietrafesa 1989). Many hypotheses have been proposed to explain increases in fish

abundance near structures. These include shelter from predation, increases in recruitment habitat,

increase feeding efficiency, or merely altered behavior leading to attraction (Gooding and

Magnuson 1967; Bohnsack 1989). The central question regarding the ecological significance of

platforms and other structures pertains to whether structures provide critical habitat needed to
2

increase productivity or if they simply serve to attract existing fish from surrounding waters

(Bohnsack 1989; Shipp 1999). Known as the attraction-production issue, this question remains a

debate among reef managers, users, and scientists.

Evaluating trophic dynamics of organisms in proximity to artificial structures is crucial to

understanding why these habitats are successful in attracting fishes (Deudero 2001). Enrichment

of food resources near floating structures has been hypothesized to explain how these structures

attract fishes (Gooding and Magnuson 1967). Observation of diet shifts of fishes near structures

may suggest a connection between structure-related productivity and the associated fish

community. Studies examining the diets of fishes near artificial reefs and FADs, however, have

been inconclusive in demonstrating effects of the structure. For example, the diets of yellowfin

tuna (Thunnus albacares) showed a shift towards deep-water oplophorid shrimps near Hawaiian

FADs in contrast to the piscivorous diet of non-FAD associated tuna (Brock 1985). Brock

reported no evidence, however, of an influence from the FAD on the distribution of these shrimp.

Ibrahim et al. (1996) compared the epifaunal organisms taken from Malaysian FADs with

stomach contents of fish collected near the FADs and concluded that the fish were feeding

primarily in the water column and not on encrusting organisms. Donaldson and Clavijo (1994)

examined the diet of a pelagic carangid (Decapterus punctatus) common on North Carolina

artificial reefs and reported these fish did not feed on organisms associated with the reefs but

instead on pelagic crustaceans. Studies on trophic relationships of artificial reef and FAD

associated fishes remains an important component in developing management strategies based

on resource allocation within the reef associated community (Nelson and Bortone 1996). A

single study was found on the feeding habits of fishes associated with offshore petroleum

platforms in the northern Gulf of Mexico (Gallaway 1980).

Stanley and Wilson (2000b) reported nine out of 26 fish species found near three offshore

platforms were carangid jacks and the most abundant of these was the blue runner (Caranx

crysos). In a study near the Buccaneer platform complex off Texas, Gallaway (1980) described

blue runner as “warm-season pelagic predators” attracted solely by the structure. Stanley (1994)

also reported blue runner occurring near Louisiana’s West Cameron 352 platform primarily

during warmer months and that schools reached up to 10,000 individuals. Adult blue runner are

considered to be primarily piscivorous (Randall 1967; Christmas et al. 1974), however, the

stomach contents of one fish taken near a platform in May 1996 contained large numbers of

hyperiid amphipods. The occurrence of small (2–5 mm) zooplankton in the stomach of a fairly

large (250 mm standard length) fish suggested a potential trophic linkage between the platform

and surrounding fish community. This formed the basis of an Undergraduate Research

Opportunities Program grant from the LSU Sea Grant College Program to investigate the

relationship between blue runner and zooplankton prey near Louisiana offshore petroleum

platforms. The results from that pilot project led to the thesis research presented here.

The subsequent chapters are organized as follows: Chapter 2 describes the feeding habits

of adult blue runner near two platforms sampled during the summers of 1996 and 1999. This

includes preliminary examination of diel feeding periodicity and prey size selection for decapod

and amphipod prey. Limited zooplankton abundance data were collected from a passively

fished, 60 cm diameter plankton net (335 μm) deployed in surface waters (2 m) directly beneath

the platform structure. Chapter 3 further examines the diets of blue runner near platforms and
3

also contrasts the feeding habits of blue runner near platforms with fish captured from open

waters away from platforms. Blue runner and zooplankton samples were collected during a

series of cruises to two platforms east of the Mississippi Delta. Zooplankton were collected by a

0.865 m2 rectangular plankton net (1000 μm) towed obliquely from 15 m to the surface.

Evidence of prey type selectivity and prey size selectivity are presented as well as prey switching

during the diel cycle. Chapter 4 evaluates zooplankton prey distribution near platforms through

use of the plankton net collections. I also attempted to provide evidence that volume scattering

strength measured by an acoustic Doppler current profiler (ADCP) is related to the abundance of

zooplankton in the ensonified water. Finally, I present evidence demonstrating the ability of an

ADCP to map the distribution of sound scattering particles (i.e., zooplankton) in the surface

waters around platforms. Chapter 5 contains a final summary section. The chapters in this thesis

were written as manuscripts for publication in peer-reviewed journals. Therefore, each chapter

contains separate Introduction, Methods, Results and Discussion sections. As a result of

duplication of references between chapters, a single literature cited section has been placed after

Chapter 5.
5

Chapter II

Zooplanktivory by Blue Runner (Caranx crysos) I:

A Potential Energetic Subsidy to Gulf of Mexico Fish Populations at Petroleum Platforms1

Introduction

The majority of the substrate off the coast of Louisiana and Texas consists of sand and

silt (Parker et al. 1983; Stanley 1994) with approximately 293 km2

 of known reef and hard

bottom habitat (Stanley and Wilson 2000a). There are over 4000 offshore petroleum platforms in

the northern Gulf of Mexico, which increase available reef-like habitat by an additional 12 km2

(Kasprzak 1998). Unlike natural reefs in the same area, which are largely low relief features,

platforms are three-dimensional structures extending throughout the water column. Platforms

provide substrate for encrusting organisms and this fouling community in turn, provides habitat

for a variety of demersal and pelagic fish species. The platforms in the northern Gulf have been

described as the largest unplanned artificial reef complex in the world (Stanley and Wilson

1998). High concentrations of fishes around platforms have stimulated attempts to quantify the

distribution and abundance of associated fish assemblages. Stanley and Wilson (1996; 1998;

2000b) utilized hydroacoustics and video surveys to estimate densities and distributions of fishes

associated with platforms. Their findings suggested that 10,000 to 30,000 fishes were associated

with each of the manned platforms they examined.

Artificial reef design and management is centered on the often controversial “attraction

versus production” issue (e.g., Grossman et al. 1997; Lindberg 1997; Bohnsack et al. 1997). Our

research utilized platforms to address the question: do platforms serve as functional, productive

habitat capable of supporting high fish biomass? This is an important question in evaluating the

relationship between platforms and fishes. While data exist on densities and distributions of

platform-associated adult fishes, relatively little is known about how such assemblages are

sustained. Understanding the trophic ecology of platform-associated fishes may help evaluate the

degree to which platform production is transferred to fish, and assist in developing strategies for

converting decommissioned platforms into productive artificial reefs.

One of the most common pelagic fish species in the Gulf is the blue runner Caranx

crysos. This coastal pelagic carangid is found in the western Atlantic from Nova Scotia to Brazil

(McKenney et al. 1958), throughout the eastern Atlantic and Mediterranean and has been

recorded in waters of the United Kingdom (Swaby et al. 1996). This medium sized fish,

commonly attaining 400 mm fork length, (Cervigón et al. 1993) is generally found in large

schools in the open waters of the Gulf of Mexico. Blue runner are frequently the most abundant

species in the surface waters around offshore platforms (Sonnier et al. 1976, Stanley and Wilson

2000a&b). For example, at a mid-shelf platform off Louisiana (Grand Isle 94B), Stanley and

Wilson (2000b) found that blue runner numerically constituted up to 94% of the fish assemblage

present.

Blue runner are likely major components of the diets of larger predatory fish that are

associated with platforms (e.g., barracudas, groupers, cobia and other large jacks) as well as

 1

 Reprinted by permission of the Transactions of the American Fisheries Society
6

predators that frequently visit platforms (e.g., king mackerel, billfish and tunas). Blue runner are

potentially important trophic links in platform food webs, however, relatively little is known

about their diet. Some data exist on feeding habits of larval and juvenile blue runner, while

accounts of adult feeding habits are anecdotal. McKenney et al. (1958) and Schekter (1972)

stated that blue runner less than 160 mm standard length (SL) were carnivorous planktivores that

primarily consumed calanoid and cyclopoid copepods. The size range of prey in the diets of

larger juveniles increases to include zooplankton such as hyperiid amphipods, decapod and

stomatopod larvae, and ichthyoplankton (McKenney et al. 1958). Randall (1967) quantified the

stomach contents of 17 mature (190–520 mm FL) blue runner from reef habitats in the West

Indies. All but two of these had “small silvery schooling” fish in their stomachs, while two fish

(222 and 250 mm FL) contained 40% planktonic organisms with the remaining contents being

fish. The stomachs of two adult male blue runner (365 and 370 mm SL), collected in Mississippi

coastal waters, contained anchovies and two mantis shrimp (Squilla empusa) of unstated

developmental stage (Christmas et al. 1974).

Observations of adult blue runner that appeared to be feeding on zooplankton at night

beneath a mid-shelf petroleum platform motivated the present study. My research was designed

to quantify the diet of blue runner at mid-shelf petroleum platforms off the coast of Louisiana.

The objectives of my study were to: (1) describe the food habits of, and monthly variability in

the diet of blue runner over summer months; and (2) evaluate the diel periodicity in feeding. In

addition, I analyzed a limited dataset to evaluate evidence for size selection of prey items by blue

runner.

Methods

Study Sites

The diets of blue runner were investigated at two offshore platforms, one located west

and one east of the Mississippi delta. Grand Isle 94B (GI94B) is a mid-shelf platform located

west of the Mississippi River (28.5267°N, 90.0983°W) in 63 m of water (Fig. 1). Samples were

collected from GI94B during 28-30 June, 28 July - 1 August, and 12-15 August 1996. Main Pass

259A (MP259A) is a outer-shelf platform located east of the Mississippi River (29.2833°N,

88.0333°W) in approximately 130 m of water. Sampling trips were made to MP259A during 11-

14 June, 9-12 July and 24-27 September 1999.

Fish Sampling

Each sampling trip lasted approximately three days during which time fish were collected

opportunistically using hook and line angling with artificial lures. The weight of each blue

runner was measured with a digital balance to the nearest 0.1 lb (± 45 g). Fork length and total

length were measured to the nearest millimeter. Sex and time of capture were also recorded for

each fish. Blue runner were anesthetized in an ice bath, which also served to arrest digestion and

then sacrificed by severing the spinal cord behind the head. Stomachs were then removed by

severing the esophagus and the duodenum below the pyloric sphincter. Stomachs were injected

with 95% ethanol, stored in 70% ethanol preservative, and transported to the laboratory.
7

Figure 1. Locations and images of platforms sampled in 1996 (GI94B) and 1999 (MP259A).
8

Enumeration of Stomach Contents

Stomach contents were examined with a dissecting stereoscope (7X) and placed in the

following taxonomic categories: fish, adult and larval decapods and stomatopod larvae, hyperiid

amphipods, chaetognaths, other invertebrates (e.g., cephalopods, pteropods, copepods, ostracods)

and unidentified material. The number of prey in each category was counted and wet weights

recorded to the nearest milligram. Wet weights were obtained by gently blotting surface fluid

from the prey items before weighing (Bowen 1996). Numbers consumed and prey weights

provided numerical and wet -weight based estimations of the contributions of each prey category

to the diet.

Plankton Sampling

A surface zooplankton sample was collected beneath MP259A using a passively-fished,

60 cm diameter ring net equipped with a 333 μm mesh net and a General Oceanics Model 2030

flow meter. The net was attached to a vertical monorail and mounted within a gimbaled frame

fitted with a current vane so that the mouth of the net faced the prevailing current. The net was

fished for 30 min from 17:45-18:15 h on June 12, 1999. Plankton were preserved in 5% formalin

for 24 h before being transferred to 95% ethanol. The sample was sorted and classified into the

same groups as for the dietary analysis.

Data Analysis

For this study, the term zooplankton includes decapods and larval stomatopods, hyperiid

amphipods, chaetognaths, and other invertebrates excluding cephalopods. The weight of

zooplankton in the diet was used to evaluate zooplanktivory over the size range of blue runner

sampled. Blue runner were grouped into 20 millimeter size classes (range of 150–450 mm) for

analysis. For each fish, percent zooplankton was computed by dividing the total zooplankton

weight by the total weight of all stomach contents.

An index of relative importance (IRI; Bowen 1996; Cortes 1997) was used to evaluate

monthly variation in blue runner feeding. The IRI values were estimated for each prey category

(i) using:

IRI N M FO i ii i =+ × (% % ) % (1)

Where Ni is the numerical proportion (%) of the ith prey category in the stomach, Mi is the

gravimetric proportion not including unidentified (%) of the ith prey item, and FOi is the

frequency of occurrence expressed as the number of stomachs containing prey category (i)

divided by the number of stomachs containing at least one prey item of any category (Hyslop

1980). The IRIs for each prey item were then converted to %IRI using:

% IRI IRI

IRI i

i = × ∑ 100 (2)

Feeding Periodicity

Diel feeding periodicity was estimated using a stomach fullness index modified from

Juanes and Conover (1994). Stomach fullness was computed for each fish by:

Stomach Fullness = Total prey wet weight

Wet weight of empty stomach (3)
9

A stomach fullness index was estimated by dividing the fullness value for each fish by the

maximum fullness value observed from all fish collected at the particular platform sampled. Blue

runner were grouped over each platform, since it was not possible to capture blue runner from all

hours of the day on any single trip. Fish were grouped into eight sequential three-hour time

blocks. Differences in daily feeding periodicity were statistically evaluated for fish collected at

the MP259A platform; however, the total number of fish collected at GI94B (n=38) was too low

to permit a statistical evaluation of differences in stomach fullness over time. I evaluated the

null hypothesis that stomach fullness indices among the three-hour time blocks within each

composite day were not different using a Kruskal-Wallis test. A non-parametric test was used

because stomach fullness values were not normally distributed and their distribution could not be

rendered normal via transformation. A posteriori statistical differences among mean stomach

fullness indices within each of the three-hour time blocks were evaluated using a nonparametric

Tukey-Kramer test (Sokal and Rohlf 1981).

Prey Size Selection

A preliminary examination of prey size selection was evaluated from the MP259A

platform during the June 1999 trip. Size selection was estimated by comparing the size

distributions of some of the zooplankton taxa in the plankton net with the pooled contents of the

stomachs of all fish (n=4) collected within ± 1 h of the plankton tow. After identification and

enumeration, photographs were taken of prey items and samples from the net using a digital

camera/microscopy system. These were analyzed with image processing software (NIH Image

1.62) to determine zooplankton body lengths. Fragmentation of zooplankton in stomachs

generally precluded direct measurement of length. Certain body sections were more resistant to

digestion and the relationships between the lengths of body parts and total length were used to

estimate their original dimensions (Table 1).

Table 1. Regressions fitted for three prey categories commonly consumed by blue runner. These

relationships were used to reconstruct whole body length (B.L.) from characteristic body sections

of organisms taken from stomachs.

Taxa/Organism Body Section Equation r2

Hyperiid amphipods Eye depth (ED) B.L. = 2.353 x ED + 0.481 0.64

Lucifer spp. Eye Length (ELa) B.L. = e1.523 x EL1.01 0.92

Small shrimp Carapace Length (CL) B.L. = e1.31 x CL0.63 0.75

a

 This measurement is defined as the distance from the distal tip of the eye to the base of the

eyestalk.

Decapods and hyperiid amphipods from the net and from the stomachs of the blue runner

were binned into size classes (0.5 mm for decapods and 0.25 mm for amphipods). Size selection

was statistically evaluated for decapod prey using a chi-square analysis. Size selection for

hyperiid amphipods was not evaluated statistically because of the limited number of size classes
10

common to both the net and stomach samples. For the decapods, I tested the null hypothesis that

the frequency of individuals within each size class did not differ significantly between the

plankton net and blue runner stomachs. In this test I must assume that the net collected a

representative sample of all sized decapods encountered by the blue runner. Expected

frequencies in each size class were computed as the product of the fraction of individuals in each

size class from the plankton net and the total number of individuals from the pooled blue runner

stomach sample. A chi-square statistic (1 degree of freedom) was computed for each size class i

using:

χi

i i

2

i

j j

2

j

observed - expected )

expected

observed - expected )

expected

2 = + ( ( (4)

where i is the size class of interest and j is all remaining size classes. Organisms less than 2.5

mm and greater than 12.5 mm were pooled so that at least 5 observations occurred in each size

frequency category.

Results

The stomachs of 37 fish collected from GI94B in 1996 contained prey items, while 81

blue runner from MP259A in 1999 contained prey items. Regurgitation of prey was considered

absent since no stomachs were everted or found empty with distended lining and examination of

the contents of the ice bath did not reveal the presence of regurgitated prey. Barotrauma

commonly associated with deep-water fish caught with hook and line (DeMartini et al. 1996)

was not considered a factor, since most of the fish were caught within the upper 10-20 m of the

water column.

Dietary analysis indicated a high degree of zooplanktivory in blue runner collected from

both platforms (Fig. 2). Numerically, zooplankton constituted approximately 62% of the

identifiable diet contents at GI94B in 1996 and 78% at MP259A in 1999. Zooplankton prey

items were dominated by decapod crustaceans and larval stomatopods, however, chaetognaths

and hyperiid amphipods comprised 20-30% of the diet. When diets were evaluated on the basis

of prey weight, zooplankton made up 28% of the diet at GI94B and 44% of the diet at MP259A.

While pteropods made up most of the individuals within the other invertebrate category,

cephalopods contributed the majority by weight. The stomachs of fish from both platforms

contained unidentifiable amorphous tissue, which constituted 42% and 29% of the overall diets

at GI94B and MP259A, respectively.

Blue runner ranged in size from 255 – 445 mm FL at the GI94B platform and 165–449

mm FL at the MP259A platform. This size range indicated that most were at or approaching

sexual maturity (Goodwin and Finucane 1985). Further, many fish contained developing or

mature gonads. The diets of nearly all blue runner contained a large proportion of zooplankton

regardless of fish size. From GI94B, all the fish below 330mm FL contained approximately 50%

zooplankton by weight (Fig. 3). Similar trends were observed from the MP259A platform, where

a broader size range of fish was collected. Approximately 40-50% of the diet of blue runner up to

330 mm FL consisted of zooplankton (Fig. 3). A decrease in zooplankton was seen in fish greater

than 330 mm except for one 440 mm fish from GI94B with many amphipods, decapods and

thecosomate pteropods in the stomach. There were, however, only four fish caught over 370 mm

from both platforms.
11

 

Fish

Amphipods

Decapods/Stomatopods

Chaetognaths

Other Invertebrates

Unidentified

Numerical Proportion Gravimetric Proportion

GI94B

(n = 37)

MP259A

(n = 81)

Figure 2. Numerical proportion (left column) and gravimetric proportion (right column) for the

prey items in the diets of blue runner from the two platforms sampled. The

proportions are pooled over the three trips to each of the platforms: June, July and

August 1996 (GI94B) and June, July and September 1999 (MP259A).
12

Figure 3. Gravimetric proportion of zooplankton (± SE) occurring in the diets of blue runner

over all sizes collected from GI94B (top) and MP259A (bottom). Blue runner were

placed into 20 mm size classes and fish were pooled over all months. The number

above each bar indicates the number of blue runner per size class.
13

Table 2. Summary of the diets of blue runner taken during each sampling trip to GI94B (1996)

and MP259A (1999). Expressed as numerical proportion (%N), gravimetric proportion (%W),

and frequency of occurrence (%F.O.). Also included is an index of relative importance (I.R.I.),

which is the sum of %N and %W multiplied by %F.O.

Month

Blue Runner

caught

Prey

category % N % W % F.O. I.R.I. value % I.R.I.

GI 94B (1996)

June 23 Decapods/Stomatopods 40.1 27.1 87.0 7777.8 60.8

Hyperiid Amphipods 19.5 7.3 82.6 2824.9 22.1

Chaetognaths 24.5 6.5 52.2 1832.2 14.3

Fish 2.2 1.4 17.4 123.5 1.0

Other Invertebrates 13.7 10.6 6.8 232.6 1.8

Unidentified - 47.1 - - -

July 3 Decapods/Stomatopods 61.1 27.8 100 12770.0 72.6

Hyperiid Amphipods 19.0 4.2 66.7 1880.9 10.7

Chaetognaths 0 0 0 0 0

Fish 0 0 0 0 0

Other Invertebrates 19.9 12.6 66.7 2941.5 16.7

Unidentified - 55.4 - - -

August 11 Decapods/Stomatopods 5.5 0.3 27.3 163.8 1.0

Hyperiid Amphipods 0 0 0 0 0

Chaetognaths 0 0 0 0 0

Fish 93.6 70.4 81.8 15795.6 98.9

Other Invertebrates 0.9 0.1 11.0 9.9 0.1

Unidentified - 29.2 - - -

MP 259A (1999)

June 14 Decapods/Stomatopods 34.3 24.9 85.7 5296.3 34.7

Hyperiid Amphipods 36.7 26.7 92.9 5917.7 38.7

Chaetognaths 13.0 6.2 28.6 580.6 3.8

Fish 9.1 35.2 64.3 2899.9 19.0

Other Invertebrates 6.9 1.9 64.3 585.1 3.8

Unidentified - 5.1 - - -

July 50 Decapods/Stomatopods 58.2 37.6 84.3 9753.5 68.1

Hyperiid Amphipods 7.1 2.7 51.0 581.4 4.1

Chaetognaths 14.6 4.1 49.0 1009.4 7.0

Fish 14.2 17.0 56.9 1951.7 13.6

Other Invertebrates 5.9 10.2 56.9 1024.2 7.2

Unidentified - 28.4 - - -

September 17 Decapods/Stomatopods 60.0 30.5 81.3 10097.5 79.5

Hyperiid Amphipods 3.5 0.6 31.3 153.4 1.2

Chaetognaths 4.5 0.7 25.0 175.0 1.4

Fish 20.9 14.7 31.3 1324.0 10.4

Other Invertebrates 11.1 3.6 43.8 946.1 7.5

Unidentified - 49.9 - - -
14

The composition of blue runner diet changed over the course of both summers (Table 2).

The IRI values indicate adult and larval forms of decapods and stomatopod larvae were a

substantial component of the diet at GI94B during June and July. In August, the IRI indicated

that fish, primarily a codlet, Bregmaceros spp., replaced decapods and stomatopods in the diet.

Chaetognaths and a variety of hyperiid amphipods contributed to the diets of blue runner at

GI94B in June and declined in importance over the summer. Cephalopods in the diets during

July at GI94B raised the importance of other invertebrates during this month.

Decapod/stomatopods and hyperiid amphipods were both important in the diets during June at

MP259A, however, unlike the pattern observed at GI94B, decapods and stomatopods increased

in importance during July and September. Fish prey from MP259A declined in importance over

the summer, from 19% in June to 10% in September.

Gut fullness indicates that blue runner appeared to feed at low levels throughout the

daylight hours and exhibited a peak in feeding activity in the pre-dawn and early morning hours

(Fig. 4). They were capable of feeding after dark, however, at levels comparable to those

observed during the day. The number of fish collected at GI94B was insufficient to construct a

complete picture of the feeding periodicity of blue runner. The pattern at GI94B, however, was

similar to that observed at MP259A where a larger number of fish produced a less ambiguous

picture of feeding periodicity. Evidence for early morning feeding at GI94B was based on a

single fish; however, the existence of a feeding pulse beginning sometime after midnight and

extending past dawn was supported by the data from MP259A (Fig. 4). The Kruskal-Wallis test

indicated time of day had significant effect (p < 0.01) on stomach fullness values at the MP259A

platform. Multiple comparisons showed that fullness values from 02:00–05:00h and 05:00–08:00

h were significantly greater (p < 0.05) than 14:00–17:00 h, while gut fullness from 02:00–05:00

h was also significantly greater than during 23:00–01:00 h. This indicates nocturnal and early

morning feeding.

Blue runner appear to preferentially avoid small zooplankton and in some cases, the

length of prey exceeded the size ranges that were present in our net sample. The size

distributions of decapod prey in the stomach overlapped the upper end of the size distribution for

this group in the net (Fig. 5). Small zooplankton such as crab megalopae and crab zoea were

absent from or rare in the stomachs. Chi-square analysis indicated significant (see Fig. 5 for pvalues) size selection for decapod prey with organisms greater than 11.5 mm being positively

selected for and decapod prey less than 9.5 mm being avoided. Similarly, figure 6 indicates that

blue runner appeared to forage on hyperiid amphipods larger than those collected in the net (prey

median length = 3.2 mm; net median length = 2.3 mm).
15

Figure 4. Stomach fullness values for blue runner collected over the summer at GI94B (top) and

MP259A (bottom). Fish were pooled over all months and binned into three-hour time

blocks. Nighttime hours are indicated by a black bar below the time block legends.

The number of fish caught in each block appears above the bars. Error bars indicate ±

1 SE on the mean.
16

Figure 5. Length frequency distributions for decapods taken from A) surface plankton net, B)

stomachs of concurrently captured blue runner (n=4), and C) chi-square analysis for

biased size selection during June 1999 at the MP259A platform. Positive (+) selection

and negative selection or avoidance (-) is indicated above each size class.
17

Frequency

0

5

10

15

20

25

30

Plankton Net Amphipods

123456

0

5

10

15

20

25

30

Stomach Content Amphipods

Frequency

Size Class (mm)

Figure 6. Length distributions of hyperiid amphipods collected from a surface plankton net (top)

and from blue runner stomachs (below) in June 1999 at MP259A.

Discussion

Zooplankton comprised an important part of the diets of mature blue runner in proximity

to petroleum platforms during summer months. Blue runner up to 350 millimeters FL appeared

to consume large numbers (50% by weight) of holoplanktonic and meroplanktonic, meso- and

macro-zooplankton. This is contrary to existing literature that characterized mature individuals of

this species (> 270 mm) as primarily piscivorous (Randall 1967; Goodwin and Finucane 1985).

There appeared to be a monthly shift in diet over the course of the study at both platforms that

may reflect changes in the abundance of prey, shifts in preference by blue runner, or some

combination of these two effects. While the dietary patterns displayed by blue runner differed

between the two sites, the presence of relatively large zooplankton in the form of hyperiid

amphipods, chaetognaths, decapods and stomatopod larvae was a consistent feature. Blue runner

are likely opportunistic feeders and the shift towards the fish Bregmaceros spp. at GI94B in

August may have been a response to a local increase in the abundance of this prey type.

The relative contribution to the diets of different prey types (e.g., fish versus

zooplankton) is complicated by variable evacuation rates (Andersen 1999). Studies of the

evacuation rates of whiting (Merlangius merlangus) showed that small shrimp (Crangon

vulgaris) were digested at rates that were approximately three times slower than those of small

sized Atlantic herring prey, Clupea harengus, (Singh-Renton and Bromley 1996). Andersen
18

(1999), also working with whiting, found that brown shrimp (Crangon crangon) were evacuated

more slowly than fish prey, however, softer-bodied euphausiids (Meganyctiphanes norvegica)

were evacuated at similar rates to fish prey. In contrast, Temming and Herrmann (2001) reported

similar evacuation rates for brown shrimp (C. crangon), smelt (Osmerus eperlanus) and herring

in the diet of horse mackerel (Trachurus trachurus). The same study demonstrated that

evacuation rates of euphausiids and mysids (Neomysis integer) by horse mackerel were slightly

greater than the above three prey. This result was explained primarily by differences in prey size

and energy density (i.e., evacuation rates were negatively correlated with energetic value of prey

items). The observations that horse mackerel digest crustacean and fish prey at different rates

have relevance to my study on blue runner. In general, the diet of horse mackerel consists

primarily of crustacean zooplankton and ichthyoplankton (Macer 1977). Thus, blue runner and

horse mackerel, both comparably sized carangids, have similar life histories and feeding habits.

Many of the zooplankton taken from my blue runner stomachs possessed relatively soft bodies

(Lucifer spp., chaetognaths) and were smaller than fish or cephalopod prey. If such prey were

digested at greater rates than fish, this could have led to underestimation of zooplankton weight

contribution. Further information on the digestion rates of different prey types by blue runner

will be required to evaluate this hypothesis.

Gut evacuation rates are also positively correlated with temperature in temperate (Popova

and Sierra 1985; Buckel and Conover 1996) and cold water fish (Singh-Renton and Bromley

1996). Increased digestion rates by blue runner in the warm surface waters of the Gulf may have

rapidly rendered many of the zooplankton prey unidentifiable. Haywood (1995) examined the

digestion rates of penaeid postlarvae by a carnivorous fish Monocanthus chinensis held in warm

water (25.3–28.5°C). Haywood estimated that after 3 h, rapid digestion could lead to a 33%

underestimate in the number of postlarval prey in the stomach and a 75% underestimate in their

dry weight. Rapid digestion may also lead to underestimation of the nutritional value of

zooplankton prey in fish diets (Cortes 1997). Some fraction of the unidentifiable matter from

blue runner stomachs that could not be associated with either zooplankton or fish prey likely

came from zooplankton that were in advanced stages of digestion, however, correlation analysis

would be required to evaluate this hypothesis.

At both platforms there was evidence that blue runner fed during the night and increased

their feeding activity into the early morning. The daily feeding periodicity of blue runner does

not appear to have been previously described. Other comparably sized, zooplanktivorous visual

predators such as Atlantic mackerel (Scomber scombrus) reduce feeding rates with diminishing

light intensity (Macy et al 1998). A reduction in light intensity decreased the reactive distance of

Lepomis macrochirus, a zooplanktivorous particulate feeder, over a range of prey sizes (Vinyard

and O’Brien 1976). All manned, and larger unmanned satellite platforms in the Gulf are

equipped with large floodlights that illuminate the surrounding waters. This artificial light field

may be sufficient to permit blue runner to extend their feeding into the night, since gut fullness

values at night were comparable with those observed during the day.

Based on my statistical evaluation of the size selection for decapods, blue runner appear

to consume more of the larger individuals present. These findings are limited, however, to the

sizes of decapods and hyperiid amphipods collected by the surface plankton net. My examination

of size selection was restricted to decapods because this was the only group of prey for which
19

there was a broad overlap in the size distributions in both the plankton net and in blue runner

stomachs. Preferential selection of larger individuals of other prey types also appeared to take

place, however, it could not be evaluated statistically. For example, larger hyperiid amphipods

commonly found in blue runner stomachs are relatively strong swimmers and were absent from

the net, presumably due to avoidance. Large chaetognaths were common in both the stomachs

and the net, however, they were usually fragmented in the gut and I was not able to develop a

reliable allometric regression to reconstruct intact lengths from fragments. Small zooplankton

such as ostracods and copepods were present in the net samples but absent from stomachs further

suggesting that blue runner actively select for large prey. Positive size selection for larger

individuals follows precepts of optimal foraging theory, since larger prey items generally provide

greater energetic value (Gerking 1994).

The appearance of zooplankton in the diets of blue runner does not directly establish a

trophic linkage between the platform and their prey. Most of the plankton taxa consumed by blue

runner were from holoplanktonic or meroplanktonic groups that likely were carried beneath the

platform from pelagic waters rather than originating from the platform fouling community.

Hyperiid amphipods are known for their association with gelatinous zooplankton (Bowman and

Gruner 1973), but have not been reported to be associated with fouling communities. Little is

known about the responses of amphipods and other zooplankton to the structure of a platform

when encountered in the pelagic zone although, as discussed subsequently, many of these taxa

are attracted to light.

While the predominant taxa in the diets of blue runner are not direct associates of

platforms, there may still be a connection between the platforms and the prevalence of

zooplankton in the diets of blue runner. Evidence for passive entrainment has been observed via

flotsam, Sargassum and foam, which frequently accumulate beneath platforms. This is probably

due to reduction in the current velocity and an increase in flow complexity as the prevailing

current interacts with platform structure. Forristall (1996) measured the degree of current

blockage near the Bullwinkle (GC65) platform in the Gulf with acoustic Doppler current

profilers arranged in an outward looking horizontal plane at 18 meters depth. His findings

indicated that the mean current velocity inside the platform structure was approximately 80% of

the unimpacted up-current velocity, and reductions were even greater directly behind dense

conductor casings. Decreases in current velocities coupled with an increase in eddy formation

and vertical shear could allow zooplankton to extend their residence time beneath a platform,

which would lead to an increase in the local zooplankton prey field.

The lights of large platforms may further increase zooplankton concentrations at night

and enhance the effect due to currents alone. Many zooplankton, such as amphipods, display

positive phototaxis and actively swim towards light. Light traps have proven to be an effective

collection gear for zooplankton and ichthyoplankton around platforms (Ditty et al. 2000,

Hernandez 2001) and the same organisms that predominate in blue runner stomachs (decapods,

hyperiid amphipods, chaetognaths and small fish) are the dominant constituents of light trap

samples. Comparisons of the catch per unit effort of hyperiid amphipods in light traps placed

beneath, and down current from a large platform suggest that this group can accumulate beneath

the platform at night (Keenan et al. 2000). The combined influence of the artificial light field and

reduced current may cause platforms to act as large, passive zooplankton accumulators. Thus the
20

platforms may provide blue runner with enhanced densities of prey and an opportunity to feed

around the clock. Such conditions could explain how large densities of blue runner and their

predators can be sustained in the waters around platforms.
21

Chapter III

Zooplanktivory by Blue Runner (Caranx crysos) II:

A Comparison Between Platform-Associated and Non-Platform-Associated Fish

Introduction

The pelagic and reef-associated fishes found near offshore oil and gas platforms in the

northern Gulf of Mexico (Gulf) draw large numbers of recreational anglers and SCUBA divers

(Stanley and Wilson 1990). Reggio (1987) estimated over 70% of all recreational angling trips

in the Exclusive Economic Zone (over 3 miles from shore) off Louisiana were to petroleum

platforms. A logbook survey indicated many reef and pelagic species were taken by recreational

anglers, which included: snappers (Family Lutjanidae), red drum (Sciaenops ocellatus), greater

amberjack (Seriola dumerili), mackerels (Scomberomorus spp.), cobia (Rachycentron canadum)

and many species of sharks (Stanley and Wilson 1990). It remains unclear why large numbers of

fishes aggregate near platforms, however, Hastings et al. (1976) hypothesized a trophic linkage.

They proposed predation on smaller baitfish (e.g., Decapterus punctatus, Harengula pensacolae,

and Sardinella spp.) caused part of the attraction of larger pelagic species.

Platforms functioning as artificial reefs are hypothesized to enhance secondary

productivity by increasing growth and survival of new individuals in a habitat-limited

environment (Bohnsack 1989; Stanley and Wilson 1991). An alternative hypothesis is that

platforms (and other artificial structures such as fish aggregating devices, FADs) merely attract

and aggregate fishes from surrounding waters potentially leading to overexploitation. The

attraction-production issue remains a debated theme in artificial reef design and management

(Grossman et al. 1997; Lindberg 1997; Bohnsack et al. 1997; Shipp 1999). Ongoing research

into fish movement patterns, site fidelity (Patterson et al. 2001), growth and trophic dynamics are

addressing this issue on a species-specific basis. Mechanisms hypothesized to increase

productivity through trophic linkages around structures include that they: 1) provide additional

food; and/or 2) increase feeding efficiency of associated fish (Bohnsack 1989). Understanding

the trophic dynamics of fishes near platforms is essential in evaluating the function of these

structures as productive artificial reefs. Few studies have evaluated the feeding habits of the

highly abundant species of fish around offshore petroleum platforms in the Gulf and none have

focused on pelagic species.

The blue runner (Caranx crysos) is a pelagic species commonly found in waters around

offshore platforms as well as in open waters of the Gulf (Sonnier et al. 1976; Stanley and Wilson

2000a). This medium-sized carangid (common to 400 mm fork length (FL)) is often found in

large schools and ranges from Nova Scotia to Brazil (McKenney et al. 1958). A limited fishery

exists in the U.S. with approximately 300 metric tons collected commercially and 763 metric

tons from recreational fisheries during 1999-2000 (National Marine Fisheries Service 2000). In

addition, they are harvested by an artisanal fishery in South America and marketed as food

(Cervigón et al. 1993). Recreational anglers near Louisiana platforms frequently use blue runner

as baitfish because of their abundance, hardiness, and attractiveness to larger gamefish. Stanley

and Wilson (2000a) found that blue runner numerically constituted up to 94% of the fish

assemblage found near a mid-shelf platform (GI94B) off Louisiana and school sizes commonly

reached over 10,000 individuals.
22

Blue runner appear to play an important role in the diets of larger fish, however, little is

known about adult blue runner feeding habits. Studies of larval and juvenile blue runner (up to

160 mm standard length) report that they fed on zooplankton, primarily cyclopoid and calanoid

copepods (McKenney et al. 1958; Sckhekter 1972). Adult blue runner (greater than 190 mm FL)

were considered primarily piscivorous (Randall 1967; Christmas et al. 1974), however, both

studies were limited to anecdotal observations. Two adult (365 and 370 mm standard length

(SL)) blue runner collected off Mississippi coastal waters contained anchovies and two mantis

shrimp (Squilla empusa) while the stomachs of 17 mature fish (190-520 mm) from West Indies

reef habitats contained “small silvery schooling” fish. In a recent feeding study of adult blue

runner collected near two Louisiana mid-shelf platforms during 1996 and 1999, I found that

macro-zooplankton comprise a large portion of their diet (Chapter 2).

I hypothesize that platforms may provide blue runner with an enhanced feeding

environment. Blue runner are likely visual particulate planktivores that forage during daylight

hours in ambient light. Platforms are well illuminated at night and this artificial light field

allows blue runner to forage around the clock. In addition, these large, lighted structures may

attract different prey taxa at night and this may influence blue runner feeding intensity and/or

prey selectivity over the course of the diurnal cycle. The following objectives were formed to

address these related hypotheses. The objectives of this study were: 1) to describe the food

habits of platform-associated and open water adult blue runner; 2) to evaluate diel feeding

periodicity and daily variations in blue runner feeding habits; and, 3) to examine prey type and

prey size selectivity of platform-associated and open water fish.

Methods

Sites

Blue runner were collected during a series of cruises in the northern central Gulf from

June to August 2000. Two platforms served as primary sampling sites for blue runner (Fig. 7),

while one cruise was devoted to collecting blue runner in open waters. The three to four day

cruises were made aboard an 11.3 m charter-fishing vessel, the C/V Admiral Semmes. This

vessel was equipped with a global positioning system (GPS). GPS position was logged by a

laptop computer at approximately 1s intervals. Vertical water column temperature profiles were

measured with a VEMCO temperature-depth recorder (model TDR-8) and a CTD (YSI Model

6920 sonde).

Viosca Knoll 203A (VK203A) is a mid-shelf platform located approximately 70 km

south of Dauphin Island, Alabama (29.7816 °N, 88.3330 °W) in 37 m of water. This platform is

a four-leg structure with a complex wellhead adjoining the platform (Fig 7). Cruises were made

to VK203A during 29 May – 1 June, 5–8 June, 17–20 July 2000. Main Pass 140A (MP140A) is

an eight-leg structure in 45 m depth and is located approximately 30 km east of Venice,

Louisiana (29.2947 °N, 88.8612 °W). Cruises were made to MP140A during 12–16 June and

26–29 June 2000. Another cruise was made to VK203A during 1–3 August 2000 to evaluate the

diel feeding periodicity of blue runner by collecting replicate fish for 24 h at two-hourly

intervals. An additional cruise from 6–9 August 2000 was designed to locate and catch blue

runner from waters away from platforms. This cruise covered a large expanse of mid-shelf water
23

east of the Mississippi delta. In addition to collecting blue runner, during two trips to each of the

platforms as well as in open waters, zooplankton samples were collected to evaluate prey

availability. A summary of each trip is provided in Table 3.

Fish Collection

Blue runner were collected opportunistically using hook-and-line angling with artificial

lures. The date and time of capture were recorded for each fish. Immediately following capture

blue runner were anesthetized in a seawater ice bath for 15 minutes, which also served to slow

digestion. Fish then were sacrificed by severing the spinal cord immediately posterior of the

opercle. Fish weight was measured with a digital balance to the nearest 0.1 lb (± 45g) and fork

length (FL) and total length (TL) were measured to the nearest millimeter. The abdominal cavity

was opened to determine sex of the fish (based on gonadal morphology and color) and to remove

the stomach. Stomachs were removed by cutting at the posterior end of the esophagus and the

pyloric sphincter. The stomach was injected with 10% buffered formalin and placed in a labeled

jar containing formalin. All stomachs were transported to the laboratory, where they were rinsed

and transferred to 70% ethanol preservative within two days after completion of each cruise.

Diet Evaluation

The contents of each stomach were flushed into a petri dish and examined under a

dissecting stereomicroscope (70X). Prey items were categorized as hyperiid amphipods, larval

and adult decapods and larval stomatopods, chaetognaths, cephalopods, fish, other invertebrates

(e.g., thecosomate pteropods, copepods, ostracods, and polychaetes), and unidentified material.

Taxa were assigned into the other invertebrate category when their contribution to the diets of all

fish sampled was less than 1% by weight of the pooled weight of all prey items. Therefore, taxa

in the other invertebrate category remained the same over the course of the study. The number

of individuals for each prey taxa was recorded to estimate numerical contribution to the diet for

each non-empty blue runner stomach. Wet weights were obtained by blotting surface fluids from

the prey before weighing (Bowen 1996) and weight were recorded to the nearest milligram

(±0.1mg). This provided estimates of weight contribution to the diet (Hyslop 1980) for all nonempty stomachs. Percent frequency of occurrence was also recorded for each category and is

defined as the number of stomachs in which one or more items of a given food type was present

expressed as a percentage of all non-empty stomachs examined (Bowen 1996). Unidentified

material was defined as any amorphous tissue that could not be identified into any particular

category above. The weight from this tissue was included in weight contribution to the diet, but

was not included in numerical contribution or frequency of occurrence. An index of relative

importance (IRI) for each prey taxa was computed for each blue runner by equation 1 (Chapter

2). A mean IRI for each prey taxa was computed by averaging the IRI values from blue runner

caught during each cruise. The IRI for each prey item were then converted to %IRI using

equation 2 (Chapter 2).

Open Water Blue Runner Diet

In addition to being found in large numbers around platforms, Cervigón et al. (1993)

noted that blue runner travel in open water schools throughout the Gulf, an observation that I

confirmed during research cruises. To evaluate whether there was a platform affect on prey

selection, blue runner were caught in waters away from the influence of platforms. Blue runner

were considered to be collected in open water if they were over 2.40 km from the nearest
24

Figure 7. Geographical location and images of platforms for summer 2000 sampling trips.

Sampling occurred near VK203A on 5–8 June, 17–20 July, 1–3 August, and trips to

MP140A were during 12–16 June and 26–29 June 2000.
25

Table 3. Summary of sampling activities associated with quantification of blue runner diets for

each cruise during summer 2000 research trips in the northern Gulf of Mexico.

Date Destination Objective (n = no. of blue runner collected)

30 May – 1 June VK203A Preliminary cruise, test equipment, identify suitable platforms

5–8 June VK203A Plankton net tows (1 day set, 1 night set), blue runner collection (n=20)

12–16 June MP140A Plankton net tows (2 day sets, 2 night sets), blue runner collection (n=21)

26–29 June MP140A Plankton net tows (2 day sets, 2 night sets), blue runner collection (n=25)

17–20 July VK203A Plankton net tows (2 day sets, 2 night sets), blue runner collection (n=22)

1–3 August VK203A Diel feeding study (n=117), open water blue runner collection (n=1)

6–9 August Open water Open water blue runner trip (n=13)

platform. This distance criterion was based on an estimate of the product of an estimated

optimal cruising speed of 2*body lengths sec-1 (Videler 1993) for a 30 cm blue runner and an

estimate of the time for prey breakdown (60 min). The latter value was based on measurements

of the digestion time for postlarval penaeid shrimp by another planktivorous species held

between 25°C and 28.5°C (Haywood 1995). The product of these swimming velocities and prey

digestion time (2.16 km) were increased by 10% to provide a more conservative estimate of

digestion time and space. This was to ensure that blue runner that may have fed near a platform

and were subsequently captured, would have digested any prey items that were consumed at the

platform. Fishing for open water blue runner occurred during transit to and from the platform.

Blue runner were detected by observing bird activity or visually observing a school at the

surface. The final cruise (6–9 August) was devoted to searching for open water schools. The fish

were processed following the standard protocol and stomach contents were evaluated in the same

manner as fish collected near platforms.

Zooplankton Sampling at Platforms

Zooplankton and micronekton were collected with a rectangular frame 92 cm X 94 cm

(0.865 m2) net (3 m length), equipped with 1 mm mesh and a flow meter (General Oceanics

Model 2030). The net was lowered vertically over the stern of the boat to 15 m with the vessel

pointed into the current and then the boat steamed up-current at approximately one knot while

the net was retrieved using an electric winch. Each oblique tow lasted approximately three

minutes and approximately 70–80 m3

 of water was filtered. A Vemco temperature-pressure

datalogger (Model TDR-8) was fixed to the vertical midpoint of the net frame to record net

trajectory. A set of net tows consisted of three replicate tows into the prevailing surface current

on the up-current side of the platform. The tows were conducted during the first and second day

and the first and second night of each platform trip. Two plankton samples also were collected

near an open-water school by making tows on the up-current side of a surface drogue deployed

near the center of the school. Plankton samples were preserved in 5% buffered formalin. After

being transported to the laboratory, samples were transferred to 70% ethanol before being sorted

and classified into the following taxonomic categories: hyperiid amphipods, larval and adult

decapods and larval stomatopods, chaetognaths, fish and other invertebrates (e.g., thecosomate
26

pteropods, copepods, ostracods, polychaetes and cephalopods). Cephalopods were rarely seen in

plankton net tows and were therefore placed into the other invertebrate category.

Feeding Periodicity

Diel feeding periodicity was evaluated in the same manner as that described in Chapter 2,

however, during one cruise to VK203A from 1–3 August, continuous sampling of blue runner

permitted an evaluation of feeding periodicity over a complete 24 hour cycle. During this cruise,

approximately ten fish were caught every two hours and the stomachs were removed following

the standard protocol. A modified stomach fullness index was computed from a gut fullness

model adapted from Juanes and Conover (1994). Stomach fullness was computed by dividing

the wet weight of all the prey taken from each stomach by the corresponding weight of the empty

stomach. A stomach fullness index was then computed by dividing the fullness value of each

fish by the maximum fullness value observed during the sampling. Therefore, a completely full

stomach received a value of 1.0 and empty stomachs were assigned 0. The null hypothesis that

stomach fullness indices did not vary during the diel sampling was tested using a Kruskal-Wallis

test (proc npar1way, SAS v. 6.12). This non-parametric test was required because the residuals

from the fullness values within two-hour blocks could not be normalized via transformation.

Stomach fullness was evaluated for the open water fish caught during the 6–9 August cruise in

the same manner as the fish collected during the diel feeding study. The maximum fullness

value observed from the diel feeding study was used to compute the stomach fullness index for

open water fish, since these two trips occurred within 5 days of one another. Fullness values

from the open water fish were compared with those of platform blue runner caught during the

same two-hour block.

In addition, the gravimetric percentage contribution of two predominant prey categories

(fish and decapods/stomatopods) was computed for each blue runner within every two-hour time

block during the diel feeding study. The difference between weight contribution was calculated

for each blue runner by subtracting the weight contribution of decapods/stomatopods from the

weight contribution of fish prey. If the prey were fed upon in equal quantities, the differences in

weight contribution were expected to be zero and deviations from zero would indicate

preferential selection for either prey. The differences within each two-hour block were tested

against zero by using a t-test in the SAS proc means statement (SAS v. 6.12). The difference in

gravimetric percentage contribution of fish and decapods/stomatopods were also computed for

open water blue runner.

Prey Type Selectivity

Prey selectivity in blue runner was evaluated by comparing the numerical proportion of

each prey item in the stomachs to the numerical proportion of the same prey items from the

plankton nets. Numerical proportion in the plankton samples was determined from the mean

proportions of the three replicate collections within a sample set. Selectivity was computed for

five prey categories: hyperiid amphipods, decapods/stomatopods, chaetognaths, fish, and other

invertebrates (e.g., pteropods, copepods, ostracods, polychaetes and cephalopods). These prey

items were selected because they occurred frequently in both the plankton net (with the

exception of cephalopods) and in blue runner stomachs. Feeding selectivity was evaluated for

any time where at least five blue runner were caught within ± 1 h of corresponding plankton

samples. Chesson’s index (Chesson 1983) was used to examine prey type selectivity:
27

αi

i

i

j

j

r

p

r

p

= for j 1 to m





 





=

∑

 (5)

where αi is the selectivity for the ith prey type for an individual blue runner; ri is the numerical

proportion of the ith prey type in an individual blue runner stomach; pi is the numerical

proportion of the ith prey type in the environment; and m is the number of prey types

(categories).

Mean alpha values for each prey category were calculated by averaging individual alpha

values for all blue runner caught during corresponding plankton net sets. Non-selective feeding

occurs when αi = 1/m = 0.2, positive selection when αi > 1/m, and negative selection (avoidance)

when αi < 1/m. Significance was evaluated using a t-test comparing mean αi with 1/m for each

prey category within each blue runner/zooplankton collection (Chesson 1983). In addition to

analyzing selectivity for blue runner groups of 5 or more, all platform-associated blue runner

caught during daytime plankton sampling and during the nighttime plankton sampling were

pooled, respectively, to estimate the influence of time of day on feeding selectivity. This

analysis included blue runner that were not analyzed as a group because fewer than five were

collected during corresponding plankton net tows. Further, open water blue runner caught

during the 6–9 August cruise were compared to the net tows conducted in the vicinity of the fish

school and selectivity was evaluated and compared to that of platform associated fish.

Prey Size Selection

Size-selective feeding on zooplankton and fish prey was evaluated by comparing the size

distributions of fish and decapod/stomatopod prey items taken from blue runner stomachs to the

size frequency of decapod/stomatopod and fish taken from plankton net sets. Only blue runner

collected within ± 1 h of plankton net tows were used in this analysis. The number of blue

runner used for this analysis varied because not every blue runner that was collected during

plankton net tows contained fishes, decapods, or a combination of both prey types. For the

12–16 June trip, decapod prey lengths were taken from 14 blue runner caught during the daytime

and four during the nighttime, while decapods from six daytime and five nighttime blue runner

were measured from the 26–29 June trip. Measurements of fish prey were recorded for three

daytime and two nighttime blue runner from 12–16 June, and from one daytime and two

nighttime blue runner during the 26–29 June trip. From the open water trip, decapod prey was

measured from six blue runner and fish prey were measured from four blue runner.

Decapods/stomatopods and fishes collected from plankton nets and blue runner stomachs

were measured using a digital camera/microscopy system (Pixera VCS 1.2.3) and image

processing software (NIH Image 6.12, see Chapter 2 for further detail). Organisms were placed

into 0.5 mm size classes, with the exception of decapods smaller than 2.5 mm and larger than 14

mm, and fish smaller than 4 mm and larger than 14 mm, which were pooled to assure adequate

sample sizes in all prey size categories. Measurements were recorded for over 400 decapods and

100 fish that were collected from each of the daytime and nighttime plankton net sets from each

trip.
28

Size selection for decapod and fish prey were examined using: Chi-square test and

Chesson’s alpha test. These analyses provided two methods for testing the null hypothesis that

the proportion of prey items within each size class did not differ significantly between the

plankton net and blue runner stomachs. The chi-square test is a traditional approach to

evaluating goodness of fit between two frequency distributions (Sokal and Rohlf 1981), whereas

the Chesson’s alpha test evaluates the “preference” for particular food types for each individual

predator and allows an estimate of variability. The chi-square test was the same as that

explained in Chapter 2. The expected frequency of prey in each size class was computed as the

product of the fraction of individuals in the size class from the plankton net and the total number

of individuals from pooled blue runner stomach samples within a particular sampling period (i.e.,

daytime or nighttime). A Chi-square statistic (df=1) was computed for the ith size class using

equation 3. There were instances where organisms within a particular size class were not

observed in plankton nets and consequently, a Chi-square value could not be calculated for these

size classes even if organisms within the size class were observed in blue runner stomachs.

Chesson’s index of selectivity also was used to examine prey size selectivity for

decapods and fish prey (Chesson 1983; Buckel et al. 1999). The use of this index was similar to

its use in the prey type selectivity calculations; however, size class was substituted for prey type.

αi

i

i

j

j

r

p

r

p

= for j 1 to m





 





=

∑

 (6)

Where αi is the selectivity for the ith size class for an individual blue runner, ri is the numerical

proportion of the ith size class in an individual blue runner stomach, pi is the numerical

proportion of the ith size class in the environment, and m is the number of size classes.

Alpha values for each size class were averaged among all blue runner caught during

corresponding plankton sets. The same αi criteria used for prey type selection (non-selective,

positive and negative selection) were used to evaluate prey size selectivity. Prey size

selectivities were statistically evaluated using a t-test, comparing mean αi with 1/m for each size

class (1/m = 0.040 for decapods/stomatopods and 1/m = 0.048 for fishes) within each blue

runner/zooplankton collection (Chesson 1983). Size selectivity was evaluated for blue runner

caught from each platform trip and from the open water trip. To further examine the influence of

time of day on size selection, blue runner collected during the daytime and nighttime hours were

each pooled.

Results

Fish Collection

A total of 205 blue runner were caught near platforms, while 14 were taken from open

water environments. Relatively few open water blue runner were collected because high sea

states made it difficult to locate surface schools during most trips and fish in surface schools that

were located were generally difficult to catch, possibly because of avoidance reactions to the

vessel. Mean blue runner lengths were 282.0 mm FL (±2.8 mm SE) from platform waters and

301.8 mm FL (±7.4 mm SE) from open waters. These mean lengths were not significantly
29

different (t-test p > 0.05, proc glm SAS). Catches of blue runner at platforms varied among trips.

At least 20 blue runner were collected during each platform trip, however, the majority of fish

(n=117) were collected during the diel sampling study during 1–3 August.

Hydrography

During every trip except one, the upper 15 m of the water column appeared thermally

well mixed (Fig. 8). The 17–20 July trip to VK203A showed evidence of thermal stratification

above 9–10 m and a thermocline below this zone with temperature decreasing from 28 °C at 9 m

to 22 °C at 15 m. From other platform trips temperature did not vary more than three degrees

from 1 m to 15 m during day or night. The average daytime surface temperature increased

approximately four degrees over the course of the summer from 26°C in early June to 30°C in

early August. The open water trip showed slightly higher surface temperatures than three out of

the four platform trips, but comparison of the surface temperature of the open water trip to the

mean of the platform trips showed no significant difference (t-test p > 0.05, df=3; Sokal and

Rohlf 1981).

Diet Evaluation

The majority of blue runner diets consisted of zooplankton. Based on the stomach

contents of blue runner collected during all 6 trips, zooplankton made up 81%, 90% and 97% of

the numerical composition of blue runner diets at VK203A, MP140A and open waters,

respectively (Fig. 9). Percent composition by prey weight also indicated that zooplankton

constituted a large portion of the diet. Excluding unidentified prey, zooplankton formed 43% of

the weight of blue runner diets at VK203A and MP140A, respectively, and 56% of the weight of

the diets of the open water fish. The majority of zooplankton prey weight consisted of decapods

and larval stomatopods for both platform and open water fish. Open water blue runner, however,

had greater amounts of chaetognaths in their stomachs (20% by weight) than platform blue

runner. Unidentified tissue, which could not be placed into a specific prey category, remained

relatively consistent between platforms and open water fish (approximately 30–40% of total prey

weight).

The IRI values indicate that the diet of blue runner remained relatively consistent

between platforms and did not vary greatly among trips (Table 4). Larval and adult decapods

and larval stomatopods were the most important prey category over all platform sampling trips,

although during the 1–3 August trip to VK203, there was an increase in the importance of fish

and cephalopods (Table 4). Decapods/stomatopods and chaetognaths dominated the diet of blue

runner at open water sites, while fish were less prevalent on both a numerical and a gravimetric

basis (Table 4). Chaetognaths increased in importance in the diet of open water fish, compared

to platform associated blue runner, because 11 out of 13 fish stomachs contained numerous

individuals of this prey category. The percent IRI value for chaetognaths during the open water

trip (33.8%) was much greater than was observed for platform-associated fish (~1% over all

trips).
30

Figure 8. Temperature depth diagrams for each trip during a) day and b) night. BR2: 5–8 June

(VK203A); BR3: 12–16 June (MP140A); BR4: 26–29 June (MP140A); BR5: 17–20

July (VK203A) and Open Water corresponds to the 6–9 August trip near an open

water school. All trips show upper 15m well mixed, with the exception of BR5, which

showed temperature stratification at approximately 9–10m.
31

Figure 9. Numerical proportion (left column) and gravimetric proportion (right column) for the

prey items in the diets of blue runner from the summer 2000 sampling trips. The

proportions are pooled over all blue runner from the two trips each to VK203A and to

MP140A.
32

Table 4. Summary of blue runner diet for all sampling trips to VK203A and MP140A.

Numerical proportion (%N), Weight proportion (%W), Frequency of Occurrence (%F.O.) and

Index of Relative Importance (I.R.I.) values are indicated for each prey category.

Trip

Blue Runner

(empty

stomachs)

Prey

category % N % W % F.O. I.R.I. value % I.R.I.

Summer 2000

5–8 June 20 (0) Decapods/Stomatopods 66.8 41.4 100.0 14003.0 78.1

(VK203) Hyperiid Amphipods 13.1 2.1 90.0 1573.3 8.8

Chaetognaths 2.9 1.0 25.0 122.7 0.7

Fish 5.7 4.2 60.0 833.7 4.7

Other Invertebrates 10.0 3.4 75.0 1287.0 7.2

Cephalopods 1.5 4.7 15.0 97.9 0.5

Unidentified 43.2

12–16 June 20 (1) Decapods/Stomatopods 66.2 36.2 95.0 13264.9 83.8

(MP140A) Hyperiid Amphipods 10.5 0.9 55.0 668.4 4.2

Chaetognaths 0.6 0.2 10.0 8.8 0.1

Fish 5.3 10.8 30.0 491.3 3.1

Other Invertebrates 17.4 2.9 45.0 1393.1 8.8

Cephalopods 0.0 0.0 0.0 0.0 0.0

Unidentified 49.0

26–30 June 22 (3) Decapods/Stomatopods 80.0 41.7 95.5 14586.9 91.2

(MP140A) Hyperiid Amphipods 0.7 0.2 31.8 32.5 0.2

Chaetognaths 5.3 3.9 36.4 382.3 2.4

Fish 6.4 8.5 45.5 704.0 4.4

Other Invertebrates 0.5 0.1 22.7 25.1 0.2

Cephalopods 7.1 11.9 13.6 259.9 1.6

Unidentified 33.7

17–20 July 20 (2) Decapods/Stomatopods 79.1 52.7 95.0 15670.3 89.2

(VK203A) Hyperiid Amphipods 4.3 0.4 60.0 327.3 1.9

Chaetognaths 0.5 0.1 20.0 12.5 0.1

Fish 9.3 8.2 55.0 1128.8 6.4

Other Invertebrates 6.8 1.0 50.0 422.3 2.4

Cephalopods 0.0 0.0 0.0 0.0 0.0

Unidentified 37.6

1–3 August 113 (4) Decapods/Stomatopods 53.0 32.3 82.3 8942.5 67.1

(VK203A) Hyperiid Amphipods 12.9 2.6 54.0 941.8 7.1

(Diel feeding Chaetognaths 7.3 4.3 31.9 433.4 3.3

 periodicity) Fish 21.0 25.2 54.9 2819.9 21.2

Other Invertebrates 4.3 0.7 30.1 165.9 1.2

Cephalopods 1.5 1.8 5.3 18.0 13.5

Unidentified 33.1

6–9 Aug 13 (1) Decapods/Stomatopods 41.7 33.4 100.0 9979.1 53.6

Openwater Hyperiid Amphipods 4.9 0.5 84.6 480.5 2.6

Chaetognaths 45.4 20.1 84.6 6286.2 33.8

Fish 3.2 4.6 92.3 1066.4 5.7

Other Invertebrates 4.8 1.9 92.3 797.4 4.3

Cephalopods < 0.1 < 0.1 7.7 0.4 < 0.1

Unidentified 39.5
33

Diel Feeding Periodicity

Blue runner did not exhibit a statistically significant peak in feeding during the diel

sampling trip (Fig. 10), however, the pattern of gut fullness values indicated elevated feeding

intensity during early evening and pre-dawn hours. Gut fullness values during the 02:00–03:00 h

(0.186 ± 0.096) and 04:00–05:00 h (0.139 ± 0.039) suggested that blue runner are capable of

feeding during nighttime at levels that can exceed daytime levels. The gut fullness value during

18:00–19:00 h (0.142 ± 0.084) also indicated that blue runner feed at dusk. Time of day had a

significant effect on gut fullness values (proc npar1way, p < 0.002, df=11), however, multiple

comparison tests were unable to determine which times of day (2 h blocks) were significantly

different. Stomach fullness from the 14 fish caught during the open water trip had comparable

fullness values (0.105 ± 0.018) to blue runner caught during 18:00–19:00 h on the diel trip (Fig.

10).

Fish and decapod/stomatopod prey predominated the diets of blue runner caught during

the diel sampling study (Table 4, %W), however, the gravimetric contribution of these two prey

groups shifted over the course of 24 hours (Fig. 11). Decapods and stomatopod larvae were

more prevalent as prey in the diet during daytime hours with a shift towards fish prey during the

night (Fig. 10). Fish prey comprised a significantly greater weight component of the diet than

decapods/stomatopods from 22:00 to 01:00 h. Blue runner from the open water trip (n = 11)

contained similar gravimetric proportions of fish and decapod/stomatopod prey as blue runner

collected during the same time of day from the diel sampling study at VK203A.

Prey Type Selectivity

There was no clear evidence of a platform-specific pattern in prey selectivity. Daytime

prey selectivity indicated that blue runner near platforms frequently selected prey

disproportionately to their relative abundance in the environment; however, these selection

patterns were often non-significant (Table 5). For example, during daytime samples from the

platforms, decapods/stomatopods were positively selected for, however, in only one instance was

this selection significant (12–16 June, α = 0.414, t-test vs. 0.2, p< 0.05). Amphipods were

positively selected for during all daytime collections, however, alpha values did not indicate

significant selection (Table 5). Fish were significantly avoided in three out of the five trips

where daytime blue runner were collected near platforms. Chaetognaths and other invertebrates

were significantly avoided during three of the five daytime samples. These prey type selectivity

patterns were generally consistent during similar times of the day among sampling trips to each

platform.
34

Figure 10. Fullness index for blue runner (n=117) collected during the diel sampling trip (1–3

August 2000) to VK203A. The horizontal black bar indicates nighttime and error bars

are SE.

Figure 11. Difference in weight contribution to the diet during the diel sampling trip for fish and

decapod/stomatopod prey. Positive difference signifies diet dominated by fish prey

and negative differences indicate decapod/stomatopod prey. Significant differences (p

< 0.05) in weight contribution to the diet by hour are indicated by asterisks (*).
35

Table 5. Daytime prey type selectivity showing average alpha values for each prey category

during samples with n≥ 5 blue runner. Significance of feeding selectivity was evaluated with a ttest to determine whether selection was positive (+, α > 1/m) or negative (–, α < 1/m). The

12–16 June and 26–29 June samples were from MP140A and 17–20 July was from VK203A.

Prey Type

12–16 June

Day

(n=14)

26–29 June

Day 1

(n=6)

26–29 June

Day 2

(n=9)

17–20 July

Day 1

(n=5)

17–20 July

Day 2

(n=5)

Fish 0.058 ± 0.038 (–) 0.029 ± 0.029(–) 0.308 ± 0.091 0.017 ± 0.017 (–) 0.158 ± 0.058

Decapods/

Stomatopods 0.414 ± 0.091 (+) 0.524 ± 0.154 0.352 ± 0.126 0.510 ± 0.201 0.354 ± 0.078

Amphipods 0.260 ± 0.091 0.131 ± 0.131 0.248 ± 0.103 0.472 ± 0.194 0.393 ± 0.162

Chaetognaths 0.019 ± 0.018 (–) 0.210 ± 0.127 0.064 ± 0.040 (–) 0.000 ± 0.000 (–) 0.057 ± 0.031 (–)

Other Inverts 0.248 ± 0.099 0.105 ± 0.105 0.029 ± 0.015 (–) 0.002 ± 0.002 (–) 0.039 ± 0.025 (–)

Selectivity for prey was affected by time of day and presence of a platform. Prey type

selectivity was evaluated for 39 pooled blue runner during the day and 18 at night near platforms

while 11 blue runner were evaluated from open waters (Table 6). During daytime, platformassociated blue runner significantly selected for decapods/stomatopods (α = 0.421, t-test vs. 0.2,

p < 0.001). These fish also significantly avoided fish, chaetognaths, and other invertebrates and

were non-selective of hyperiid amphipods. During the night around platforms, this pattern

changed when blue runner significantly avoided decapods/stomatopods (α = 0.077, p < 0.05) and

begun to show positive selection for fish prey (α = 0.353, 0.10 > p > 0.05) and other

invertebrates (α = 0.277, p > 0.10), although variability among fish rendered the latter two trends

non-significant. Open water blue runner significantly selected only for amphipods (α = 0.534, p

< 0.01), while showing avoidance of decapods/stomatopods (α = 0.094, p < 0.01) and other

invertebrates (α = 0.012, p < 0.01). Open water blue runner were non-selective in feeding on

fish prey (α = 0.152, 0.10 > p > 0.05) and chaetognaths (α = 0.208, p > 0.10).

Table 6. Combined prey type selectivity data for time of day from platform and open water blue

runner. Alpha values are averaged over all blue runner collected during noted times of day.

Selective feeding was examined with a t-test to determine if selection was positive (+, α > 1/m),

negative (–, α < 1/m) or neutral (no sign).

Prey Type Day

(n = 39)

Night

(n = 18)

Open water

(n = 11)

Fish 0.119 ± 0.031 (–) 0.353 ± 0.101 0.152 ± 0.030

Decapods/

Stomatopods 0.421 ± 0.055 (+) 0.077 ± 0.055 (–) 0.094 ± 0.018 (–)

Amphipods 0.282 ± 0.055 0.293 ± 0.094 0.534 ± 0.053 (+)

Chaetognaths 0.061 ± 0.024 (–) 0.000 ± 0.000 (–) 0.208 ± 0.043

Other Invertebrates 0.117 ± 0.041 (–) 0.277 ± 0.097 0.012 ± 0.002 (–)
36

Prey Size Selection

Blue runner around platforms exhibited size selective feeding for intermediate sized

decapods and smaller fish prey during the day. Blue runner selected for 9.5–12.5 mm decapods

for both the 12–16 June and 26–29 June platform trips (Fig. 12, 13). The Chesson’s alpha test

indicated significantly positive selection (α = 0.13 vs. 1/m (0.04), t = 2.17, df = 24, p < 0.05)

only for the 9.0 mm (June 26–29) and 9.5 mm (June 12–16) size categories. Further, the Chisquare test showed significant negative selection for many of the smaller decapods (3.5–7.5 mm)

collected by the plankton net. Evaluation of the selection for different sized fish prey was

constrained because fewer blue runner stomachs contained fish prey during the day. Where it

could be evaluated, selectivity was opposite to that observed for decapod prey with primarily

smaller fish selected during the day. Daytime blue runner from both platforms fed on 4–8 mm

ichthyoplankton (Fig. 14, 15), which represented the small to intermediate size range collected

by the net. Chi-square and Chesson’s alpha indicated significant positive selection from the June

26–29 cruise, although this result is based solely on the stomach contents of the only blue runner

with fish prey (Fig. 15). When pooled over platforms (Fig. 16), Chesson’s alpha showed that

blue runner fed on the intermediate sized decapods (9–12.5 mm) and smaller sized fish prey (<9

mm) during the day.

During night foraging around platforms, both Chi-square and Chesson’s alpha test

indicated decapods greater than 14 mm were highly selected (Fig. 17, 18). Decapod/stomatopod

prey below 12 mm in length were generally not observed in blue runner stomachs at nighttime.

Blue runner from each platform fed on larger sized fish and generally fish prey larger than that

collected by the net (Fig. 19, 20). Pooled alpha values increased the sample size to nine blue

runner with decapod prey and four with fish prey (Fig. 21). The results were similar for both

decapod and fish prey with larger (>14 mm) prey consumed by blue runner.

From open water fish, positive selection was shifted to smaller sized decapods (3.5–5.5

mm), although many of the larger size classes present in blue runner stomachs were not sampled

by the plankton net (Fig. 22). Decapods/stomatopods between 6 and 10 mm were significantly

avoided by open water blue runner. Open water blue runner did not display distinct size

selectivity patterns for fish prey (Fig. 23) and feeding was observed for both larger (>14 mm)

and smaller (<7 mm) fish. Significant selection for any particular size of fish prey was not

detected by the Chesson’s alpha test suggesting random or non-selective feeding. Thus, the size

selectivity displayed by blue runner in open waters was similar to that observed at platforms

during the day.
37

Figure 12. Daytime size selection for decapod/stomatopod prey from blue runner (n=14) during

the 12–16 June trip (MP140A). The chi-square test is shown in upper panel and

Chesson's alpha test is shown in the lower panel. Significant selection or avoidance is

indicated with a (+) or (–), respectively.
38

Figure 13. Daytime size selection for decapod/stomatopod prey of blue runner (n=6) from 26–29

June trip (MP140A). The chi-square test is shown in upper panel and Chesson's alpha

test is shown in the lower panel. Significant selection or avoidance is indicated with a

(+) or (–), respectively. The zeros (0) indicate when this size class did not occur in a

blue runner stomach and the N/A indicates this size class was not observed in the

plankton net.
39

Figure 14. Daytime size selection for fish prey of blue runner (n=3) from the 12–16 June trip

(MP140A). The chi-square test is shown in upper panel and Chesson's alpha test is

shown in the lower panel. Significant selection is indicated with a (+). The zeros (0)

indicate when this size class did not occur in the blue runner stomachs and the N/A

indicates this size class was not observed in the plankton net.
40

Figure 15. Daytime size selection for fish prey of blue runner (n=1) from the 26–29 June trip

(MP140A). The chi-square test is shown in upper panel and Chesson's alpha test is

shown in the lower panel. Significant selection is indicated with a (+). The zeros (0)

indicate when this size class did not occur in the blue runner stomachs and the N/A

indicates this size class was not observed in the plankton net.
41

Figure 16. Daytime Chesson's alpha selectivity test for a) decapods (n=20 blue runner) and b)

fish (n=4 blue runner) for blue runner pooled over 12–16 June and 26–29 June trips to

MP140A. Significant selection or avoidance is indicated with a (+) or (–),

respectively. The zeros (0) indicate when this size class did not occur in the blue

runner stomachs and the N/A indicates this size class was not observed in the

plankton net.
42

Figure 17. Nighttime size selection for decapod/stomatopod prey by blue runner (n=4) during

the 12–16 June trip (MP140A). The chi-square test is shown in upper panel and

Chesson's alpha test is shown in the lower panel. Significant selection is indicated

with a (+). The zeros (0) indicate when this size class did not occur in a blue runner

stomach and the N/A indicates this size class was not observed in the plankton net.
43

Figure 18. Nighttime size selection for decapod/stomatopod prey by blue runner (n=5) during

the 26–29 June trip (MP140A). The chi-square test is shown in upper panel and

Chesson's alpha test is shown in the lower panel. Significant selection or avoidance is

indicated with a (+) or (–), respectively. The zeros (0) indicate when this size class

did not occur in a blue runner stomach.
44

Figure 19. Nighttime size selection for fish prey by blue runner (n=2) during the 12–16 June trip

(MP140A). The chi-square test is shown in upper panel and Chesson's alpha test is

shown in the lower panel. Significant selection is indicated with a (+). The zeros (0)

indicate when this size class did not occur in a blue runner stomach.
45

Figure 20. Nighttime size selection for fish prey by blue runner (n=2) during the 26–29 June trip

(MP140A). The chi-square test is shown in upper panel and Chesson's alpha test is

shown in the lower panel. Significant selection is indicated with a (+). The zeros (0)

indicate when this size class did not occur in a blue runner stomach and the N/A

indicates this size class was not observed in the plankton net.
46

Figure 21. Nighttime Chesson's alpha selectivity test for a) decapods (n=9 blue runner) and b)

fish (n=4 blue runner) for blue runner pooled over 12–16 and 26–29 June trips to

MP140A. Significant selection or avoidance is indicated with a (+) or (–),

respectively. The zeros (0) indicate when this size class did not occur in the blue

runner stomachs and the N/A indicates this size class was not observed in the

plankton net.
47

Figure 22. Size selection for decapod/stomatopod prey by blue runner (n=6) caught from open

waters during 6–9 August 2000. The chi-square test is shown in the upper panel and

the Chesson's alpha test is in the lower panel. Significant selection or avoidance is

indicated with a (+) or (–), respectively. The zero (0) indicates when this size class

did not occur in blue runner stomachs and the N/A indicates this size class was not

observed in the plankton net.
48

Figure 23. Size selection for fish prey by blue runner (n=4) caught from open waters during 6–9

August 2000. The chi-square test is shown in the upper panel and the Chesson's

alpha test is in the lower panel. The zeros (0) indicate when this size class did not

occur in blue runner stomachs and the N/A indicates this size class was not observed

in the plankton net.
49

Discussion

Diet Evaluation

Zooplankton comprise a large proportion of the diets of adult and sub-adult blue runner

near offshore petroleum platforms as well as in open waters of the Gulf during summer months.

Dietary analyses supported previous observations of zooplanktivory by blue runner at other

platforms in the northern Gulf (Keenan et al. in press, and Chapter 2). Although fish are

components of the diet, the present study suggests that earlier reports that adult blue runner

(>270 mm) are primarily piscivorous (Randall 1967; Smith-Vaniz 1986) may be incorrect. Blue

runner collected from open waters also appeared to forage mostly on zooplankton, however, the

proportions of zooplankton taxa in the diet differed (e.g., dominance of chaetognaths) from

platform-associated fish. The limited number of blue runner collected from open waters

precluded definitive conclusions about the diets of these fish. It should be noted that the

majority of open water fish were taken from one school, and therefore may not be representative

of the feeding habits of other open-water schools. Preliminary examination of plankton samples

indicated that chaetognaths were greater in abundance near this open water school compared to

the daytime concentrations measured near the two platforms. In addition, the relative

abundances of decapods and fish prey were lower in the vicinity of the open-water school than

were observed in the vicinity of platforms suggesting a diet shift to more available chaetognath

prey.

My observations of blue runner foraging on holoplanktonic zooplankton are supported by

records for other pelagic carangids commonly found around artificial structures. Donaldson and

Clavijo (1994) examined the diets of round scad (Decapterus punctatus) on artificial versus

natural reefs off North Carolina and determined that this carangid fed primarily on calanoid and

cyclopoid copepods at both sites. They concluded that Decapterus were likely using the reefs as

protection from predation pressure instead of a food source. Ibrahim et al. (1996) collected

fishes (including D. maruadsi and Atule mate) from around FADs near Malaysia as well as their

associated sessile organisms, and concluded that fishes were primarily feeding on pelagic

crustaceans in surrounding waters rather than on encrusting organisms. Deudero (2001)

examined the diets and interspecific trophic relationships of fishes, including five species of

carangids near FADs in the Mediterranean. Three of the carangids were small-sized (40–100

mm) pelagic planktivores (Trachurus mediterraneus, T. picturatus, and T. trachurus), which fed

primarily on copepods. Larger carangids (50–300 mm) such as pilotfish (Naucrates ductor) and

greater amberjack (Seriola dumerili) each had similar diets comprised of larger organisms such

as hyperiid amphipods and fishes. Greater amberjack, studied near artificial reefs in the Gulf,

were defined as “reef-associated open water feeders” foraging primarily on schooling fishes and

squid (Manooch and Haimovici 1983; Nelson and Bortone 1996). However, Gallaway (1980)

noted that greater amberjack and almaco jack (S. rivoliana) near platforms off the Texas coast

often consumed blennies, which are associated with the biofouling community.

Food Enrichment in the Vicinity of Platforms

Enrichment of food resources has been proposed as one hypothesis for increased numbers

of fishes near structures like FADs, artificial reefs and offshore petroleum platforms (Gooding

and Magnuson 1967; Gallaway et al. 1981, Deudero 2001). Following a diet study on FAD

associated fishes, Deudero and Morales-Nin (2001) sampled meso-zooplankton near
50

Mediterranean Sea FADs; however, they failed to show plankton densities were greater around

FADs compared to ambient concentrations. In a study of the feeding habits of yellowfin tuna

(Thunnus albacares) near FADs off Hawaii, Brock (1985) found that these fish exhibited a

dietary shift to oplophorid shrimps when compared to non-FAD-associated tuna, which fed

primarily on fish. Brock stated, however, that sonar surveys did not indicate that oplophorid

shrimps aggregated beneath the FAD. In my study, the feeding habits of blue runner in open

waters were generally consistent with those associated with platforms, although my sample size

and temporal scope for open water fish was limited. Differences in diets between open water

and platform-associated blue runner will be discussed later. Blue runner from both open waters

and near platforms foraged primarily on larval and adult decapods and larval stomatopods

although chaetognaths, hyperiid amphipods and fish prey were also important in the diet.

Greater amberjack from open waters of the Mediterranean Sea (Andaloro and Pipitone 1997) and

south Atlantic Ocean (Mannoch and Haimovici 1983) possessed similar diets compared to

amberjack associated with artificial reefs in the northern Gulf (Nelson and Bortone 1996). In

contrast to artificial reefs and FADs, however, offshore petroleum platforms possess a complex

sub-surface architecture and powerful lights, which illuminate surrounding waters at night.

These factors may influence prey distributions and facilitate blue runner foraging around these

structures, especially at night. This topic will be explored further in Chapter 4.

Diel Periodicity

Blue runner are likely visual predators, however, my results indicate that they are capable

of feeding throughout the night near platforms. Although a statistically significant nocturnal

peak in feeding was not observed during the 24h-sampling trip, gut fullness levels were greatest

during dawn and pre-dawn hours suggesting nocturnal feeding. This was consistent with

previous feeding intensity studies for platform associated blue runner (Keenan et al. in press and

Chapter 2). Another peak in feeding during the diel sampling occurred near dusk, which was not

observed in my previous research. Other carangids display great variations in daily feeding

periodicity. Hobson (1968) observed sub-adult Caranx marginatus (200–300 mm) feeding at

night on crustaceans and “herring-like fishes” off of California, whereas larger C. hippos (>400

mm) were more crepuscular predators feeding primarily on fishes. Young black jack (C. ruber)

in Cuban waters were reported to have morning and evening peaks in their daily feeding rhythm

(Popova and Sierra 1985). Platform associated blue runner do not appear to be constrained to

forage at any one time during the day. There was a new moon during the 24h-sampling trip,

which may have influenced the feeding intensity pattern; because the large floodlights on

platforms could have locally enhanced blue runner feeding intensity. Two other cruises occurred

near full moon events and fullness values of blue runner caught at night were lower than blue

runner taken at night during the diel feeding study. Open water blue runner, collected during the

late afternoon and early evening (18:00 to 19:00 h) had gut fullness values similar to fish

collected at the same time of day but 5 days earlier near VK203A. Although my study was

undertaken with the objective of contrasting the diets of blue runner at platforms and in open

waters, it proved extremely difficult to locate and collect fish away from platforms.

Blue runner collected during the diel study shifted their diet from large proportions (by

weight) of decapods during the daytime to primarily fish at night. The decapods consumed

during the daytime were mostly crab zoea, Lucifer spp., and larval shrimp. The forage fishes that

blue runner consumed at night included but are not limited to the following families: Clupeidae
51

(herrings), Bregmacerotidae (codlets), Stromateidae (butterfish), Carangidae (jacks), Scombridae

(mackerels), Synodontidae (lizardfishes), Bothidae (flatfishes), and Balistidae (filefishes). While

these fishes are not identified as platform-dependent (Hernandez 2001) the lights from platforms

may attract these fish making them more susceptible to predation. Blennies (family Blenniidae),

commonly associated with the platform community, were also observed in the diets of blue

runner.

Other carangid species showed diel variations in their diets. Starck and Davis (1966)

reported a shift in the diet of a jack (species not named) from daytime feeding on fishes to

zooplankton at night. Blue-spotted trevally (C. bucculentus) caught in Albatross Bay, Australia

did not show diel variations in fish, crab or molluscan prey, however large trevally (276-335

mm) consumed more penaeid shrimp during the night than during the day (Brewer et al. 1989).

This shift was reported as a response to an increase in availability of nocturnal penaeid species.

In my study, net tows were not conducted during the diel sampling trip, although preliminary

evidence from other trips indicates that fish are more abundant in net collections at night than

during the daytime (Chapter 4). Due to difficulty locating open water blue runner, the diets of

these fish at night remain uncertain.

Prey Type Selection

Blue runner around platforms selected for decapods/stomatopods and hyperiid amphipods

consistently during the daytime, although levels of selection varied between days and among

trips. The greater amount of ambient light during the day may allow blue runner to detect

decapod and amphipod prey more easily, and at longer ranges than at night. In addition, hyperiid

amphipods possess a robust body and are often pigmented (Vinogradov et al. 1996) which may

make them more conspicuous to visual predators. It’s unclear why blue runner demonstrated

avoidance of fish during daytime hours, although net tows indicated that they are much less

abundant than decapods (Chapter 4). At nighttime, blue runner around platforms altered their

diet by selecting for fish, amphipods and other invertebrates (primarily thecosomate pteropods

and cephalopods) and significantly avoided decapods and chaetognaths. Lower light levels

likely favor predation on larger or more conspicuous targets (Hunter 1968; Vinyard and O’Brien

1976). My net tow data show that both fish and amphipods were more abundant at night than

during the day. The open water blue runner significantly selected for hyperiid amphipods and

showed positive selection for chaetognaths. Decapods were less abundant in the net samples

from open waters than from tows near platforms, which may suggest a switch to a more available

prey, since chaetognaths were more abundant in the vicinity of the open water school than near

platforms. Hyperiid amphipods, however, generally were less abundant in the open water

plankton samples than those taken near platforms, which indicate that open water blue runner

may have actively selected for this less common prey type.

Prey Size Selection

During the daytime, platform blue runner fed on decapods and fish within the size range

collected by the 0.865 m2 plankton net. Selectivity tests from daytime feeding indicated that

decapods below 8 mm are generally consumed in proportion to their availability in the water

column and those between 8 mm and 12.5 mm may experience positive selection. Decapods fed

upon by blue runner included crab and shrimp larvae, however, holoplanktonic shrimp (Lucifer

spp.) predominated this category, which is consistent to findings reported in Chapter 2. Daytime
52

blue runner foraged on all sizes of fish encountered, although only one fish above 8 mm was

observed in a blue runner stomach. This indicated that during the daytime, platform-associated

blue runner positively selected small to intermediate sized fish prey. Blue runner may have

avoided the larger sized fish due to greater availability of decapod/stomatopod prey.

The size selectivity pattern changed for nighttime blue runner, which fed upon larger

sized decapod and fish prey. Platform associated blue runner fed actively on larger decapods

(>14 mm) such as adult shrimp and larger larval stomatopods. Larger fish prey such as herrings

and codlets were common prey items observed in blue runner collected at night. The larger prey

organisms were likely able to avoid the plankton net and preliminary observation of net sizefrequency histograms showed that decapods and fish over 15 mm were less abundant. Under

low light, larger prey may be more visible to blue runner. In addition, prey species may be

attracted to the platform lights at nighttime making them more available to blue runner. This will

be explored further in Chapter 4.

Open water blue runner selected for smaller decapods and selected for all sized fish that

were collected during the open water plankton net tows. Since the time of capture for the open

water blue runner was during early evening, only a qualitative size-selection comparison of open

water to platform feeding based on time of day was possible. Open water blue runner selected

for smaller sized decapods (3.5–5 mm) compared to both daytime and nighttime platform blue

runner. Decapod prey from open water blue runner consisted primarily of zoea and megalopae

crab and shrimp larvae and larval stomatopods. All sizes of fish prey that were collected by the

plankton nets were fed upon by open water blue runner, however, the greatest positive selection

was for the largest-sized fish prey. This range of selection falls in between the daytime and

nighttime platform selectivity patterns. The time these fish were caught (18:00–19:00h) may

indicate a transition phase from feeding on smaller organisms during the daytime to feeding on

larger prey when light levels decrease. The nocturnal feeding habits of open water blue runner

remains unknown.
53

Chapter IV

Spatial Variability of Meso- and Macro-Zooplankton in Surface Waters

Near Offshore Petroleum Platforms in the Northern Gulf of Mexico

Introduction

One hypothesis set forward to explain the attraction of fishes to artificial structures is an

enrichment of food resources (Gooding and Magnuson 1967; Hastings et al. 1976; Deudero and

Morales-Nin 2001). Many commercially-important predatory fishes (e.g., greater amberjack,

king mackerel, cobia) found near offshore petroleum platforms in the Gulf of Mexico (Gulf) are

believed to be attracted to large schools of baitfish such as herrings and sardines (Gallaway

1980), which find protection amongst the legs of the structure. Other common fishes, such as

gray triggerfish, sheepshead and blennies forage on the encrusting organisms and epifauna living

on the structure itself. The previous chapters have focused on the feeding habits of a pelagic fish

species, Caranx crysos, commonly found around platforms. These fish, which are often found in

large schools, forage extensively on zooplankton. This raises the question: are there linkages

between the platforms and the availability of zooplankton?

Studies on prey distributions around artificial structures have primarily focused on

flotsam and fish attraction devices (FADs). Gooding and Magnuson (1967) observed large

numbers of planktivorous juvenile and adult fishes (including Caranx spp.) near an underwater

observation chamber in the Pacific Ocean, however, they failed to see an increase in zooplankton

prey near the chamber. They believed that protection from predation explained the attraction

rather than increased prey resources. Similarly, Ibrahim et al. (1996) examined stomach contents

of fish associated with fish attraction devices (FADs) off Malaysia and found only

holoplanktonic organisms such as copepods, Lucifer spp. and shrimps instead of encrusting

organisms or epifauna growing on the FAD. Deudero and Morales-Nin (2001) collected

zooplankton near FADs in the Mediterranean Sea using vertically towed nets and did not detect

differences in plankton densities near these structures compared with open water control stations.

The surface areas of large artificial reefs and petroleum platforms may influence

zooplankton prey distributions to a greater extent than smaller structures such as FADs.

Lindquist and Pietrafesa (1989) examined the currents and fish distributions around a tugboat

wreck in Onslow Bay, North Carolina. They determined that currents were slower on the

upstream side of the tugboat due to deflection; and that round scad (Decapterus punctatus) were

more abundant in this area during periods of high current velocity in ambient water. Reasons

explaining this pattern included: that fish may aggregate in areas of lower current speeds to

conserve energy; or that prey encounter rates may be higher since plankton would be entrained in

upstream current vortices; or a combination of the two factors. Petroleum platforms, which

provide a large amount of sub-surface structure, also create current disturbances (Dicks 1982;

Taylor 1991). Forristall (1996) measured the amount of current reduction on the Bullwinkle

platform in the Gulf during strong current events. He reported that currents in the wake of the

platform were 20% lower than freestream currents and that current speed in the wake of a dense

group of well conductors was lowered by 83%. In addition, platforms are equipped with large

floodlights that illuminate the surrounding waters at night. Many zooplankton species are

positively phototaxic and may be affected by the light from the structure. These characteristics
54

could influence zooplankton distribution, providing a potential increase in feeding efficiency for

pelagic planktivores such as blue runner.

Several techniques exist for measuring zooplankton abundance and distribution

dependent on the spatial scale and purpose (Skjoldal et al. 2000). The use of high frequency

acoustics in combination with net sampling allows for resolution of fine-scale (centimeters to

hundreds of meters) patterns as well as a physical sample for verification (Holliday and Pieper

1995; Greene et al. 1998; Foote and Stanton 2000). For frequencies on the order of 103 kHz, the

particles responsible for acoustic backscattering are assumed to be zooplankton and micronekton

(Heywood et al. 1991; Holliday and Pieper 1995). Thus, relating backscattering from a volume

of water to numbers or biomass of sound-scattering organisms in that volume is the simplest way

to evaluate sound scatter distributions through field measurements (Ressler 2001). Acoustic

Doppler current profilers (ADCPs) are commonly used by physical oceanographers to examine

the velocity of near-surface currents. The ADCP also measures the intensity of the backscattered

acoustic returns which is proportional to the number and backscattering cross sections of sound

scattering particles such as zooplankton (Foote and Stanton 2000; Ressler 2001). Recent studies

have demonstrated the application of ADCPs in examining patterns of zooplankton and

micronekton structures in the Gulf in proximity to physical features such as warm- and cold core

eddies (Zimmerman and Biggs 1999; Wormuth et al. 2000; Ressler 2001).

In this study, I used a vessel-mounted ADCP in conjunction with obliquely towed

plankton nets to examine zooplankton distributions around offshore petroleum platforms in the

Gulf. Refer to Benfield et al. (in prep) for information on the calibration procedure and technical

properties of the particular ADCP used in this study. By evaluating the distribution of

zooplankton near these massive structures, I have attempted to determine whether the platforms

provide enhanced prey resources for platform-associated fishes, such as blue runner.

The objectives of this research were to use plankton net tows in conjunction with acoustic

backscattering strength data from the ADCP. The objectives were to: 1) evaluate zooplankton

composition and abundance near two petroleum platforms; 2) examine relationships between

zooplankton density and wet mass from plankton nets and backscatter strength from the ADCP;

and, 3) demonstrate the utility of acoustics to visualize the spatial patterns of sound scattering

particles near platforms. My null hypotheses examined, included that: 1) zooplankton

abundance does not vary from the up-current to the down-current sides of platforms and density

does not vary with distance from the structure, 2) there is no relationship between density and

wet mass of zooplankton and volume backscatterering strength, and 3) fine-scale spatial patterns

of sound scattering particles do not exist around platforms.

Methods

Sampling Sites

Zooplankton collection and acoustic sampling was conducted during a series of cruises in

the northern Gulf from early June to mid-July 2000. Cruises aboard the 11.3 m C/V Admiral

Semmes lasted approximately three to four days. The vessel was equipped with a global

positioning system (Magellan GPS NAV 5000DX), which logged to a laptop computer at
55

approximately 1 Hz. A conductivity/temperature/depth (CTD) recorder (YSI Model 9320)

measured hydrographic parameters (temperature and salinity).

Sampling was conducted near two petroleum platforms east of the Mississippi River.

Viosca Knoll 203A (VK203A) is a mid-shelf platform located approximately 64 km south of

Dauphin Island, Alabama (29.7816oN, 88.3330oW) in 37 m of water. This platform is a four-leg

structure with a complex wellhead adjoining the platform (Fig. 7). Cruises were made to

VK203A during 5–8 June and 17–20 July 2000. Main Pass 140A (MP140A) is an eight-leg

structure in 45 m depth located approximately 32 km east of Venice, Louisiana (29.2947oN,

88.8612o

W). Cruises were made to MP140A during 12–16 June and 26–29 June 2000. The

order of platform sampling was determined by a coin toss.

Zooplankton Sampling

Zooplankton and micronekton were collected with a rectangular frame plankton net

(1000 μm) towed obliquely from 14 m to the surface. Further description of the net system and

deployment can be found in Chapter 3. A set of net hauls (n=12) consisted of three replicate

tows conducted at four locations: up-current and down-current of the platform and up-current

and down-current of a fixed open-water point located within 1000 m of each study platform,

referred to as the reference site (Fig. 24). During each cruise, two sample sets were collected at

night and two during the day. Prior to determining sampling sites, current direction was

evaluated by observing movement of a surface drogue placed in the water near the platform.

Plankton net tows from the reference sites allowed for comparison of natural levels of

zooplankton variability at two points separated by similar distance as tows from the up-current

and down-current sides of the platform. The order of net tows was randomized among all four

possible locations.

Zooplankton Enumeration

Zooplankton were fixed in 10% formalin and transported to the laboratory, where

samples were transferred to 70% ethanol before being sorted and identified. A Folsom plankton

splitter was used to sub-sample the total plankton sample. Organisms were sorted and identified

using a dissecting stereo-microscope (70X). Zooplankton were classified into the following

taxonomic categories: fish, larval and adult decapods and larval stomatopods, hyperiid

amphipods, chaetognaths, thecosomate pteropods, copepods, gelatinous invertebrates (e.g., salps,

doliolids, siphonophores) and fish eggs. An additional category, termed “other invertebrates,”

contained organisms such as ostracods, polychaetes, and insects, which were relatively rare and

not represented here. Splitting was limited so that the most numerous group,

decapods/stomatopods, produced over 100 individuals. For less abundant groups, samples were

split fewer times, so that at least 100 individuals were counted. When the total number of

individuals present in a sample was less than 100, all individuals were enumerated without

splitting.
56

Figure 24. Example of one set of samples designed to evaluate the influence of a platform on the

density of zooplankton up-current and down-current of a platform. A total of twelve

net samples were collected: three replicate tows up-current of a platform, three tows

up-current of a reference site located within 1000 m of the platform, three tows downcurrent of the platform and three tows down-current of the reference site. Each tow

was an oblique haul from 14 m to the surface using a 0.865 m2 net and the order of

net hauls was randomized.

Zooplankton concentrations (individuals / m3) were computed by multiplying the number

of individuals counted in each taxonomic category (corrected for the split factor) and then

dividing by the volume filtered. A three-way analysis of variance (proc glm, SAS v. 6.12) was

conducted to determine whether there was a statistically significant relationship between

zooplankton abundance (total and by taxon) and: cruise date (5–8 June, 12–16 June, 26–29 June

and 17–20 July), current direction (up-current vs. down-current), and site (platform vs. reference)

for either day or night samples. The site-by-current-direction interaction (proc glm, lsmeans

procedure, SAS v. 6.12) was used to examine density changes among the four sampling sites

(i.e., platform up-current, platform down-current, reference up-current, reference down-current)

during each cruise. The assumption of normality of the residuals was examined using a SAS

procedure (proc univariate, SAS v. 6.12) and the data were transformed (log +1) if this

assumption was violated. If the transformation did not correct the violation, a non-parametric

Kruskal-Wallis test was conducted (Sokal and Rohlf 1986).

Owing to changes in current direction during sampling, and sea states that limited vessel

maneuverability, the exact position of the net tow sites could not be replicated during the net tow
57

collections; therefore, I also tested distance from the platform as a factor influencing density. A

Matlab (v. 5.2) program was written to calculate the distance of each net tow from the platform

whenever sufficient GPS data were available. Regressions of plankton density versus distance to

the platform were done for each replicated day and night set for each cruise to the two platforms

(i.e., 7 net collections during the day and 7 at night) for each taxon identified. Again,

transformations (log+1) of raw density values were performed when the error residuals of the

data were not normally distributed.

Acoustics

The distributional patterns of sound scattering particles (e.g., zooplankton) were

evaluated using a RD Instruments BroadBand 1200 kHz ADCP. The ADCP was mounted on the

side rail of the boat and positioned at approximately 1.0 m below the waterline. The ADCP’s

four transducers were orientated downward with each beam 20o

 from vertical. An external cable

provided power to the ADCP and was connected to an onboard laptop computer. The ADCP

transmitted at 2 Hz and measurements of backscattering intensity were averaged into 10 s

ensembles representing 20 pings. The effective range of the sound pulse for this frequency was

approximately 14 m and data were recorded in 0.5 m depth cells. Volume backscattering

strength (Sv) was calculated following procedures described in Benfield et al. (in prep).

Although differential GPS was not available, selective availability had been disabled and

positional data were recorded concurrently with acoustics. GPS data were edited to remove

outliers and the trackline was smoothed using a five point running mean.

The ADCP recorded concurrently with plankton net tows near each platform, therefore it

was possible to examine the relationship between ADCP volume scattering strength and net tow

contents. During each cast, acoustic ensembles were selected that corresponded with the time

period when the net was being retrieved. Volume backscatter was averaged from the lowest

depth the net reached (determined from the net Temperature/Depth/Recorder, Chapter 3) to

approximately 2 m below the surface. Acoustic data were not used for the upper 2 m of the

water column because the ADCP data began at 1.5 m and the first 0.5 m cell was corrupted by

side-lobe returns from the vessel’s hull. Acoustic data beyond 14 m were not available because

of attenuation and consequently the net was rarely deployed to this depth. For each net cast, the

mean volume scattering strength was estimated as the average of all volume backscattering

coefficients (sv) from 2–14 m for the duration of the tow. Mean sv was then converted to volume

scattering strength (Sv) using the equation (Wiebe et al. 1996):

S s v v =10 10 log ( ) (7)

where Sv is volume scattering strength (dB re 1 m-1 4π-1). Relationships between volume

scattering strength and the logarithm of zooplankton density and wet weight were conducted

following procedures adopted from Zimmerman and Biggs (1999) and Wormuth et al. (2000).

Volume backscatter values were computed for 24 net tows from the 5–8 June cruise to VK203A

and 46 net tows from the 12–16 June cruise to MP140A. Analyses were conducted separately

for day and night net tows.

Backscatter and Density

Simple linear regressions of the logarithm of plankton density (individuals/m3) as a

function of volume scattering strength (Sv) were conducted using SAS (proc reg, v. 6.12).
58

Separate regressions were performed for complete day and night net tow sets from 5–8 June

(VK203A) and 12–16 June (MP140A). Regressions were computed for each taxon sorted from

the plankton net including total zooplankton.

Backscatter and Wet Weight

A preliminary examination of relationships between zooplankton wet mass and volume

backscattering strength was also attempted. Linear regressions were conducted on the logarithm

of wet weight per unit volume (mg / m3) for each taxon collected from plankton samples on

volume scattering strength. Wet weight was computed following methods in Postel et al. (2000),

where all individuals from specific taxon were placed onto a pre-weighed paper filter disc and

then vacuum filtered to remove excess fluid. Each taxonomic category was then weighed to the

nearest milligram (AND, Inc., GR-120 microbalance). Wet weights were measured from 12 net

tows from 12–16 June (day 2) and 11 net tows from 12–16 June (night 1).

Acoustic Surveys

Acoustic surveys were conducted around the platforms as a series of concentric boxes

beginning at approximately 500 m away from the platform, getting nearly 200 m closer during

each circuit (Fig. 25). Surveys lasted approximately 1 h and were conducted during both the day

and night for each cruise. The surveys usually followed the series of net tows, however, this

varied among cruises. The goals of these surveys were to examine the distributional patterns of

Sv in relation to the platform. Surveys during the first day and night of the 5–8 June cruise

(VK203A) and the first day and second night of the 12–16 June cruise (MP140A) were

processed for this section. The complete analysis of these surveys will be the subject of a

separate investigation. Consequently, this chapter contains a preliminary, and largely qualitative

analysis of the acoustic survey data.

Outliers were identified and deleted from GPS data because a differential GPS receiver

was not used when recording location. A smoothed survey trackline was produced using a 5 s

running mean before positions were re-calculated at 10 s intervals to correspond with the

frequency of the acoustic record. Local time, recorded by both the GPS and the ADCP, was used

to merge volume scattering strength data with positional data and the resultant data were

visualized in two (time and depth) and three dimensions (latitude, longitude, depth) using

Matlab.

Results

Plankton Net Sampling

A total of 168 plankton net tows were conducted; 84 during the day and 84 at night

(Table 7). Four complete sets of tows representing four days and four nights were completed at

MP140A (n=48 day and 48 night) while only three sets representing three days and nights were

done near VK203A (n=36 day and 36 night). The discrepancy in the collection resulted from

inclement weather during the first trip to VK203A (5–8 June). All plankton samples were

collected between 100–1000 m of the respective platform. All plankton samples were identified

and enumerated into the taxonomic categories.
59

Figure 25. Two-dimensional GPS plot of a typical survey around a platform (indicated by the

square in the middle of the graph). The successive loops depicted by the numbers: outer

loop (points 1 to 2), middle loop (3 to 4), inner loop (points 5 to 6), and near-platform

pass (7 to 8).

Table 7. Summary of sampling activities associated with surface zooplankton collections and

acoustic sampling for each cruise during summer 2000 research trips in the northern GOM.

Date Destination Objective

30 May – 1 June VK203A Preliminary cruise, test equipment, identify suitable platforms

5–8 June VK203A Plankton net tows: 1 day set (n = 12), 1 night set (n = 12),

Acoustic survey (1 day and 1 night)

12–16 June MP140A Plankton net tows: 2 day sets (n = 24), 2 night sets (n = 24),

Acoustic survey (2 day and 2 night)

26–29 June MP140A Plankton net tows: 2 day sets (n = 24), 2 night sets (n = 24),

Acoustic survey (2 day and 2 night)

17–20 July VK203A Plankton net tows: 2 day sets (n = 24), 2 night sets (n = 24),

Acoustic survey (2 day and 2 night)

Differences in zooplankton densities were dominated by among cruise variability (Fig.

26, 27) and the patterns did not appear to be related to specific platforms or time of day. During

the day, the total zooplankton abundance category was greatest during the 12–16 June cruise to

MP140A, however, there were no significant difference among the other three cruises (Fig. 26).
60

The high number of gelatinous organisms (e.g., salps, doliolids, and calycophore siphonophores)

during the day sampling of the 12–16 June trip likely contributed to this result. Fish, amphipods,

pteropods, copepods, and gelatinous organisms also were significantly greater (p < 0.05) during

12–16 June (MP140A) than the other three cruises (Fig. 26). The density of

decapods/stomatopods and fish eggs were also greater during this cruise, but the differences were

not statistically significant (Fig. 26).

Total zooplankton densities were generally elevated at night relative to daytime samples.

There was no evidence of a platform effect when platform sites were compared to controls. Blue

runner forage on small fish during the night and fish abundances from my net tows indicated

lower fish densities on the down-current side of platform in relation to the up-current side on five

of the seven nights sampled (Fig. 38). This difference was statistically significant (p = 0.002) on

the second night of the 26–29 June trip. Results for decapods/stomatopods, which were

abundant at night, did not indicate a platform effect (Fig. 39). The majority of decapods sampled

were small (1-4 mm) holoplanktonic species such as Lucifer, with limited locomotion powers.

The other taxa sampled showed high variability among the four sampling sites, which made it

difficult to identify any platform effect. During the second night of sampling for the 12–16 June

cruise there were large number of fish eggs collected in the platform down-current samples,

which suggested a spawning event near, or at the platform (Fig. 45).
61

 

0

75

150

a. Total

A

B

B

B

0

1

2

b. Fish

0

40

80

c. Decapods/

Stomatopods

BR2

A

B B

B

A A

B

AB

BR3 BR4 BR5

Density (# / m3)

0

0.5

1

A d. Amphipods

C C

B

0

6

12

e. Chaetognaths

A

AB

A

B

BR2 BR5 BR3 BR2 BR5 BR4 BR3 BR4

0

2

4

f. Pteropods

C C

A

B

BR2 BR5 BR3 BR4

0

5

10

g. Copepods

A

D

C

B

0

40

80

h. Gelatinous

 zooplankton

C C

A

B

0

1.5

3

i. Eggs

A*

A*

B* B*

BR2 BR5 BR3 BR4

BR2 BR5 BR3 BR2 BR5 BR4 BR3 BR2 BR5 BR4 BR3 BR4

BR2 BR5 BR3 BR4

Density (# / m3) Density (# / m3)

Figure 26. Daytime density of zooplankton categories (a–i) during summer 2000 cruises: BR2

(5–8 June, VK203A), BR3 (12–16 June, MP140A), BR4 (26–29 June, MP140A),

BR5 (17–20 July, VK203A). Letters indicate significant difference (p < 0.05) from

Tukey's mean test. Asterisks (*) indicate significance tested with Kruskal-Wallis

non-parametric test (p < 0.01).
62

 

0

2.5

5

d. Amphipods A

B BC C

0

20

40

e. Chaetognaths A

B B

C

0

2

4

f. Pteropods

A

B

D

C

0

200

400

a. Total

A

B

BC

C

0

3

6

b. Fish

A*

C*

AB*

B*

0

150

300

c. Decapods/

A Stomatopods

C C

B

BR2 BR5 BR3 BR2 BR5 BR4 BR3 BR4

0

2.5

5

g. Copepods

A

C

B

C

0

20

40

h. Gelatinous

 zooplankton

A

B

A

C

0

20

40

A* i. Eggs

B* D* C*

BR2 BR5 BR3 BR4

BR2 BR5 BR3 BR2 BR5 BR4 BR3 BR4 BR2 BR5 BR3 BR4

BR2 BR5 BR3 BR2 BR5 BR4 BR3 BR2 BR5 BR4 BR3 BR4

Density (# / m3) Density (# / m3) Density (# / m3)

Figure 27. Nighttime density of zooplankton categories (a–i) during summer 2000 cruises: BR2

(5–8 June, VK203A), BR3 (12–16 June, MP140A), BR4 (26–29 June, MP140A),

BR5 (17–20 July, VK203A). Letters indicate significant difference (p < 0.05) from

Tukey's mean test. Asterisks (*) indicate significance tested with a Kruskal-Wallis

non-parametric test (p < 0.01).
63

 

0

25

50

a. 5–8 June (Day)

 p = 0.66

0

150

300

b. 12–16 June (Day 1)

 p = 0.26

0

100

200

c. 12–16 June (Day 2)

 p = 0.95

0

100

200

d. 26–29 June (Day 1)

 p = 0.48

0

75

150

e. 26–29 June (Day 2)

 p = 0.93

PlatUp PlatDown RefUp RefDown

0

30

60

f. 17–20 July (Day 1)

 p = 0.85

PlatUp PlatDown RefUp RefDown

0

75

150

g. 17–20 July (Day 2)

 p = 0.02

Density (# / m3

)

Density (# / m3

) Density (# / m3) Density (# / m3)

Total zooplankton - Daytime sampling

Figure 28. Total zooplankton density (# / m3) from plankton net samples during each daytime

set of net hauls (a–g) during each cruise. There were 12 net hauls during each set of

tows: Platform Down-current (n=3), Platform Up-current (n=3), Reference Downcurrent (n=3), Reference Up-current (n=3). P-values indicate site-by-current

interaction.
64

 

0

0.25

0.5

a. 5–8 June (Day)

 p = 0.64

0

1

2

b. 12–16 June (Day 1)

 p = 0.83

0

1

2

c. 12–16 June (Day 2)

 p = 0.36

0

0.25

0.5

d. 26–29 June (Day 1)

 p = 0.73

0

0.5

1

e. 26–29 June (Day 2)

 p = 0.42

PlatUp PlatDown RefUp RefDown

0

0.25

0.5

f. 17–20 July (Day 1)

 p = 0.06

PlatUp PlatDown RefUp RefDown

0

0.5

1

g. 17–20 July (Day 2)

 p = 0.97

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Fish - Daytime sampling

Figure 29. Fish density (# / m3) from plankton net samples during each daytime set of net hauls

(a–g) during each cruise. There were 12 net hauls during each set of tows: Platform

Down-current (n=3), Platform Up-current (n=3), Reference Down-current (n=3),

Reference Up-current (n=3). P-values indicate site-by-current interaction.
65

 

0

20

40

a. 5–8 June (Day)

 p = 0.67

0

50

100

b. 12–16 June (Day 1)

 p = 0.46

0

50

100

c. 12–16 June (Day 2)

 p = 0.69

0

75

150

d. 26–29 June (Day 1)

 p = 0.46

0

50

100

e. 26–29 June (Day 2)

 p = 0.95

PlatUp PlatDown RefUp RefDown

0

25

50

f. 17–20 July (Day 1)

 p = 0.46

PlatUp PlatDown RefUp RefDown

0

50

100

g. 17–20 July (Day 2)

 p = 0.02

Density (# / m3

)

Density (# / m3) Density (# / m3) Density (# / m3

)

Decapods/Stomatopods - Daytime sampling

Figure 30. Decapod/Stomatopod density (# / m3) from plankton net samples during each

daytime set of net hauls (a–g) during each cruise. There were 12 net hauls during

each set of tows: Platform Down-current (n=3), Platform Up-current (n=3), Reference

Down-current (n=3), Reference Up-current (n=3). P-values indicate site-by-current

interaction.
66

 

0

0.4

0.8

a. 5–8 June (Day)

 p = 0.96

0

1

2

b. 12–16 June (Day 1)

 p = 0.65

0

1

2

c. 12–16 June (Day 2)

 p = 0.81

0

0.1

0.2

d. 26–29 June (Day 1)

 p = 0.33

0

0.5

1

e. 26–29 June (Day 2)

 p = 0.54

PlatUp PlatDown RefUp RefDown

0

0.1

0.2

f. 17–20 July (Day 1)

 p = 0.43

PlatUp PlatDown RefUp RefDown

0

0.25

0.5

g. 17–20 July (Day 2)

 p = 0.30

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Amphipod - Daytime sampling

Figure 31. Amphipod density (# / m3) from plankton net samples during each daytime set of net

hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
67

 

0

5

10

a. 5–8 June (Day)

 p = 0.75

0

10

20

b. 12–16 June (Day 1)

 p = 0.26

0

7

14

c. 12–16 June (Day 2)

 p = 0.53

0

10

20

d. 26–29 June (Day 1)

 p = 0.52

0

10

20

e. 26–29 June (Day 2)

 p = 0.61

PlatUp PlatDown RefUp RefDown

0

3

6

f. 17–20 July (Day 1)

 p = 0.23

PlatUp PlatDown RefUp RefDown

0

10

20

g. 17–20 July (Day 2)

 p = 0.47

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Chaetognath - Daytime sampling

Figure 32. Chaetognath density (# / m3) from plankton net samples during each daytime set of

net hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
68

 

0

0.25

0.5

a. 5–8 June (Day)

 p = 0.85

0

3

6

b. 12–16 June (Day 1)

 p = 0.10

0

3

6

c. 12–16 June (Day 2)

 p = 0.48

0

0.05

0.1

d. 26–29 June (Day 1)

 p = 0.77

0

0.3

0.6

e. 26–29 June (Day 2)

 p = 0.49

PlatUp PlatDown RefUp RefDown

0

1

2

f. 17–20 July (Day 1)

 p = 0.58

PlatUp PlatDown RefUp RefDown

0

1

2

g. 17–20 July (Day 2)

 p = 0.61

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Pteropod - Daytime sampling

Figure 33. Pteropod density (# / m3) from plankton net samples during each daytime set of net

hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
69

 

0

5

10

a. 5–8 June (Day)

 p = 0.99

0

5

10

b. 12–16 June (Day 1)

 p = 0.86

0

5

10

c. 12–16 June (Day 2)

 p = 0.24

0

2

4

d. 26–29 June (Day 1)

 p = 0.69

0

5

10

e. 26–29 June (Day 2)

 p = 0.11

PlatUp PlatDown RefUp RefDown

0

0.5

1

1f. 7–20 July (Day 1)

 p = 0.52

PlatUp PlatDown RefUp RefDown

0

2

4

g. 17–20 July (Day 2)

 p = 0.29

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Copepods - Daytime sampling

Figure 34. Copepod density (# / m3) from plankton net samples during each daytime set of net

hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
70

 

0

4

8

a. 5–8 June (Day)

 p = 0.48

0

100

200

b. 12–16 June (Day 1)

 p = 0.38

0

15

30

c. 12–16 June (Day 2)

 p = 0.78

0

4

8

d. 26–29 June (Day 1)

 p = 0.65

0

6

12

e. 26–29 June (Day 2)

 p = 0.47

PlatUp PlatDown RefUp RefDown

0

5

10

f. 17–20 July (Day 1)

 p = 0.02*

PlatUp PlatDown RefUp RefDown

0

10

20

g. 17–20 July (Day 2)

 p = 0.54

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Gelatinous zooplankton - Daytime sampling

A

AB AB

B

Figure 35. Gelatinous zooplankton density (# / m3) from plankton net samples during each

daytime set of net hauls (a–g) during each cruise. There were 12 net hauls during

each set of tows: Platform Down-current (n=3), Platform Up-current (n=3), Reference

Down-current (n=3), Reference Up-current (n=3). P-values indicate site-by-current

interaction; asterisks indicate significant difference between sites and letters indicate

which sites are different from a Tukey test (proc glm, SAS v 6.12).
71

 

0

0.5

1

a. 5–8 June

 p = 0.99

0

1

2

b. 12–16 June (Day 1)

 p = 0.20

0

5

10

c. 12–16 June (Day 2)

 p = 0.10

0

0.5

1

d. 26–29 June (Day 1)

 p = 0.23

0

0.5

1

e. 26–29 June (Day 2)

 p = 0.31

PlatUp PlatDown RefUp RefDown

0

0.5

1

f. 17–20 July (Day 1)

 p = 0.31

PlatUp PlatDown RefUp RefDown

0

0.5

1

g. 17–20 July (Day 2)

 p = 0.61

Density (# / m3

)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Fish Eggs - Daytime sampling

Figure 36. Egg density (# / m3) from plankton net samples during each daytime set of net hauls

(a–g) during each cruise. There were 12 net hauls during each set of tows: Platform

Down-current (n=3), Platform Up-current (n=3), Reference Down-current (n=3),

Reference Up-current (n=3). P-values indicate site-by-current interaction.
72

 

0

300

600

a. 5–8 June (Night)

 p = 0.86

0

150

300

b. 12–16 June (Night 1)

 p = 0.86

0

150

300

c. 12–16 June (Night 2)

 p = 0.04

0

150

300

d. 26–29 June (Night 1)

 p = 0.15

0

100

200

e. 26–29 June (Night 2)

 p = 0.87

PlatUp PlatDown RefUp RefDown

0

150

300

f. 17–20 July (Night 1)

 p = 0.93

PlatUp PlatDown RefUp RefDown

0

200

400

g. 17–20 July (Night 2)

 p = 0.31

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Total zooplankton - Nighttime sampling

Figure 37. Total zooplankton density (# / m3) from plankton net samples during each nighttime

set of net hauls (a–g) during each cruise. There were 12 net hauls during each set of

tows: Platform Down-current (n=3), Platform Up-current (n=3), Reference Downcurrent (n=3), Reference Up-current (n=3). P-values indicate site-by-current

interaction.
73

 

0

4

8

a. 5–8 June (Night)

 p = 0.14

0

1

2

b. 12–16 June (Night 1)

 p = 0.16

0

1

2

c. 12–16 June (Night 2)

 p = 0.19

0

3

6

d. 26–29 June (Night 1)

 p = 0.03*

0

3

6

e. 26–29 June (Night 2)

 p = 0.002*

PlatUp PlatDown RefUp RefDown

0

1

2

f. 17–20 July (Night 1)

 p = 0.07

PlatUp PlatDown RefUp RefDown

0

3

6

g. 17–20 July (Night 2)

 p = 0.28

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Fish - Nighttime sampling

A

AB AB

B

A

A A

B

Figure 38. Fish density (# / m3) from plankton net samples during each nighttime set of net hauls

(a–g) during each cruise. There were 12 net hauls during each set of tows: Platform

Down-current (n=3), Platform Up-current (n=3), Reference Down-current (n=3),

Reference Up-current (n=3). P-values indicate site-by-current interaction; asterisks

indicate significant difference by site and letters indicate which sites are different

from a Tukey test.
74

 

0

200

400

a. 5–8 June (Night)

 p = 0.94

0

100

200

b. 12–16 June (Night 1)

 p = 0.78

0

100

200

c. 12–16 June (Night 2)

 p = 0.11

0

150

300

d. 26–29 June (Night 1)

 p = 0.20

0

100

200

e. 26–29 June (Night 2)

 p = 0.94

PlatUp PlatDown RefUp RefDown

0

150

300

f. 17–20 July (Night 1)

 p = 0.98

PlatUp PlatDown RefUp RefDown

0

200

400

g. 17–20 July (Night 2)

 p = 0.29

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Decapods/Stomatopods - Nighttime sampling

Figure 39. Decapod/Stomatopod density (# / m3) from plankton net samples during each

nighttime set of net hauls (a–g) during each cruise. There were 12 net hauls during

each set of tows: Platform Down-current (n=3), Platform Up-current (n=3), Reference

Down-current (n=3), Reference Up-current (n=3). P-values indicate site-by-current

interaction.
75

 

0

4

8

a. 5–8 June (Night)

 p = 0.09

0

1

2

b. 12–16 June (Night 1)

 p = 0.93

0

1

2

c. 12–16 June (Night 2)

 p = 0.18

0

1

2

d. 26–29 June (Night 1)

 p = 0.21

0

0.5

1

e. 26–29 June (Night 2)

 p = 0.63

PlatUp PlatDown RefUp RefDown

0

0.5

1

f. 17–20 July (Night 1)

 p = 0.31

PlatUp PlatDown RefUp RefDown

0

1

2

g. 17–20 July (Night 2)

 p = 0.45

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Amphipods - Nighttime sampling

Figure 40. Amphipod density (# / m3) from plankton net samples during each nighttime set of

net hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
76

 

0

50

100

a. 5–8 June (Night)

 p = 0.35

0

25

50

b. 12–16 June (Night 1)

 p = 0.13

0

10

20

c. 12–16 June (Night 2)

 p = 0.20

0

20

40

d. 26–29 June (Night 1)

 p = 0.28

0

15

30

e. 26–29 June (Night 2)

 p = 0.77

PlatUp PlatDown RefUp RefDown

0

10

20

f. 17–20 July (Night 1)

 p = 0.17

PlatUp PlatDown RefUp RefDown

0

10

20

g. 17–20 July (Night 2)

 p = 0.13

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Chaetognaths - Nighttime sampling

Figure 41. Chaetognath density (# / m3) from plankton net samples during each nighttime set of

net hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
77

 

0

3

6

a. 5–8 June (Night)

 p = 0.97

0

1

2

b. 12–16 June (Night 1)

 p = 0.95

0

0.5

1

c. 12–16 June (Night 2)

 p = 0.28

0

0.15

0.3

d. 26–29 June (Night 1)

 p = 0.01

0

0.5

1

e. 26–29 June (Night 2)

 p = 0.97

PlatUp PlatDown RefUp RefDown

0

1

2

f. 17–20 July (Night 1)

 p = 0.82

PlatUp PlatDown RefUp RefDown

0

1.5

3

g. 17–20 July (Night 2)

 p = 0.37

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Pteropods - Nighttime sampling

Figure 42. Pteropod density (# / m3) from plankton net samples during each nighttime set of net

hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
78

 

0

3

6

a. 5–8 June (Night)

 p = 0.46

0

2

4

b. 12–16 June (Night 1)

 p = 0.78

0

2

4

c. 12–16 June (Night 2)

 p = 0.12

0

2

4

d. 26–29 June (Night 1)

 p = 0.50

0

1

2

e. 26–29 June (Night 2)

 p = 0.31

PlatUp PlatDown RefUp RefDown

0

1

2

f. 17–20 July (Night 1)

 p = 0.26

PlatUp PlatDown RefUp RefDown

0

1.5

3

g. 17–20 July (Night 2)

 p = 0.60

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Copepods - Nighttime sampling

Figure 43. Copepod density (# / m3) from plankton net samples during each nighttime set of net

hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
79

 

0

15

30

a. 5–8 June (Night)

 p = 0.86

0

40

80

b. 12–16 June (Night 1)

 p = 0.99

0

10

20

c. 12–16 June (Night 2)

 p = 0.02*

0

10

20

d. 26–29 June (Night 1)

 p = 0.28

0

5

10

e. 26–29 June (Night 2)

 p = 0.52

PlatUp PlatDown RefUp RefDown

0

10

20

f. 17–20 July (Night 1)

 p = 0.14

PlatUp PlatDown RefUp RefDown

0

10

20

g. 17–20 July (Night 2)

 p = 0.27

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Gelatinous zooplankton - Nighttime sampling

A

AB AB

B

Figure 44. Gelatinous zooplankton density (# / m3) from plankton net samples during each

nighttime set of net hauls (a–g) during each cruise. There were 12 net hauls during

each set of tows: Platform Down-current (n=3), Platform Up-current (n=3), Reference

Down-current (n=3), Reference Up-current (n=3). P-values indicate site-by-current

interaction; asterisks indicate a significant difference among sites and letters indicate

which sites are different from a Tukey test.
80

 

0

2

4

a. 5–8 June (Night)

 p = 0.40

0

5

10

b. 12–16 June (Night 1)

 p = 0.94

0

100

200

c. 12–16 June (Night 2)

 p = 0.04

0

0.5

1

d. 26–29 June (Night 1)

 p = 0.84

0

0.5

1

e. 26–29 June (Night 2)

 p = 0.86

PlatUp PlatDown RefUp RefDown

0

1

2

f. 17–20 July (Night 1)

 p = 0.74

PlatUp PlatDown RefUp RefDown

0

1

2

g. 17–20 July (Night 2)

 p = 0.55

Density (# / m3)

Density (# / m3

) Density (# / m3

) Density (# / m3

)

Fish Eggs - Nighttime sampling

Figure 45. Fish Egg density (# / m3) from plankton net samples during each nighttime set of net

hauls (a–g) during each cruise. There were 12 net hauls during each set of tows:

Platform Down-current (n=3), Platform Up-current (n=3), Reference Down-current

(n=3), Reference Up-current (n=3). P-values indicate site-by-current interaction.
81

Zooplankton density from daytime net tows did not show consistent trends with distance

from the platform; however, for certain taxa and on some trips, there were significant

relationships between density and distance from the platform. During the 5–8 June cruise to

VK203A, the densities of total zooplankton, fish and decapods/stomatopods declined towards the

platform, however none of the taxa displayed regressions with slopes that were significant (Fig.

46). On the 12–16 June cruise to MP140A total zooplankton densities also declined toward the

platform, significantly so on the second day (Fig. 47). The total zooplankton density was driven

primarily by the density of decapods/stomatopods on the second day and this taxon also had a

significant declining slope toward the platform (Fig. 47). On the 26–29 June and 17–20 July

cruises, total zooplankton densities increased towards the platform, with a significant regression

on day one of the former trip (Fig. 48). Decapod/Stomatopod density decreased closer to the

platform during many daytime collections and this patterns was near significant at the 9% level

for the 5–8 June trip (Fig. 46) and again on day one of the 12–16 June cruise (p=0.01; Fig. 47).

However, on 26–29 June, decapods/stomatopods showed significant negative relationship

between distance from the platform and density (Fig. 48).

Linear regression slopes of fish abundance decreased near the platform during 5–8 June

(Fig. 46), however, they increased or showed no pattern in all other daytime samples (Fig.

47–49). Slopes were not significantly different from zero for fish on all trips. Of the remaining

taxa, the slope of chaetognaths density increased significantly towards MP140A on 26–29 June

(day 2), and also increased towards VK203A on day two of the 17–20 July cruise (p = 0.07; Fig.

49). Copepods increased towards MP140A on day one of the 12–16 June cruise (Fig. 47).

For nighttime samples, the slopes of the regressions were non-significant for all cruises,

although trends in total zooplankton densities were generally opposite to those noted during the

daytime sampling. Densities appear to increase closer to the platform for the first two cruises

(Fig. 50, 51) and decrease for the second two (Fig. 52, 53). Fish showed decreasing abundance

or no trend near the platform for all nighttime collections. Decapods/Stomatopods, amphipods,

chaetognaths and pteropods did not show distinct trends during the night sampling (Fig. 50-53).

Copepods showed a significantly positive slope with increasing distance from the platform on

night one of the 12–16 June cruise. Fish eggs were higher in abundance nearer to the platform

only during the night 2 sampling of 12–16 June trip to MP140A (Fig. 51).
82
83
84
85
86
87
88
89
90

Acoustic Results: Volume Scattering Strength and Plankton Density

Within each cruise, positive relationships existed between volume scattering strength and

the logarithm of density for many taxa. During the daytime, those taxa capable of producing

strong acoustic returns (i.e., fish and thecosomate pteropods) showed a positive relationship

between volume scattering strength and density (Fig. 54–56). These regressions were significant

for thecosomate pteropods during the 12–16 June (day 2) cruise (Fig. 56), but were not for fish

during any of the daytime collections. The total zooplankton category failed to show a clear

positive relationship with scattering. Results for moderately strong scatters such as

decapods/stomatopods and amphipods suggested that their densities were not well correlated

with the volume scattering strength during the day (Fig. 54–56). The densities of weakly

scattering organisms such as chaetognaths, copepods, gelatinous plankton and fish eggs were not

related to the volume scattering strength with the exception of fish eggs on the second day of

sampling during the 12–16 June cruise when there was a significant negative relationship

between egg density and volume scattering strength (Fig. 56).

At night, the relationship between density and Sv varied from generally positive and often

significant regressions for 5–8 June (Fig. 57) to very weak and variable relationships on the first

night of 12–16 June (Fig. 58), and neutral or negative relationships on the second night of 12–16

June (Fig. 59). Strong scatterers such as fish and pteropods did not significantly and positively

associate with Sv (Fig. 58, 59). Moderately strong scatterers (decapods/stomatopods,

amphipods) were significantly and positively related to Sv on 5–8 June (Fig. 57). On 12–16 June

(night 1) there was no apparent relationships for decapods/stomatopods although amphipod

densities were still significantly and positively related to Sv (Fig. 58). By the second night of

12–16 June, the densities of both groups were not significantly related to Sv (Fig. 59). Weakly

scattering organisms demonstrated interesting, if contradictory results. Gelatinous zooplankton

densities were significantly and positively related to Sv on 5–8 June and on 12–16 June (night 1)

the relationship was positive but significant only at p = 0.14 (Fig. 58). By the next night,

gelatinous zooplankton densities were significant but negatively related to Sv (Fig. 59). There

was never a significant relationship between copepod densities and Sv for any of the nights (Fig.

57-59). Fish egg densities were positively related to Sv only on the second night of 12–16 June

(Fig. 59).

Acoustic Results: Volume Scattering Strength and Wet Weight

Volume-specific total wet weight for six taxa in a sample (mg/m3) were greater during

the 12–16 June night net tows than day tows, four taxa significantly so (Fig. 60). Amphipods,

pteropods, and copepods, however, showed a significant decrease in weight during the night

tows relative to the day. The overall increase in wet weight was associated with a minor increase

in Sv computed from the net tows (Fig. 61). Fewer net tows (n=23) were examined for

correlation between backscattering strength and logarithm of wet weight, which made it difficult

to evaluate relationships. During the day 2 net samples, only pteropods were significantly (p =

0.05, r2 = 0.33) correlated with scattering (Fig. 61). Fish eggs collected during these samples

showed a negative relationship with Sv, which is similar to the trends seen from egg density

during the same day (Fig. 56). At night, fish, amphipod, copepod, and gelatinous zooplankton

wet weight was positively correlated with Sv (Fig. 61), however only amphipod (p = 0.001, r2

 =

0.71) and gelatinous zooplankton wet weight were significant (p = 0.03, r2 = 0.43).
91

Figure 54. Regressions of volume backscatter (dB) to logarithm of density (# / m3) for each

taxon identified (a–i) from the daytime sampling during the 5–8 June cruise to

VK203A (n = 12 tows).
92

Figure 55. Regressions of volume backscatter (dB) to logarithm of density (# / m3) for each

taxon identified (a–i) from the day 1 sampling during the 12–16 June cruise to

MP140A (n = 12 tows).
93

Figure 56. Regressions of volume backscatter (dB) to logarithm of density (# / m3) for each

taxon identified (a–i) from the day 2 sampling during the 12–16 June cruise to

MP140A (n = 12 tows). Asterisks (*) indicate significant relationship (p < 0.05).
94

Figure 57. Regressions of volume backscatter (dB) to logarithm of density (# / m3) for each

taxon identified (a–i) from the nighttime sampling during the 5–8 June cruise to

VK203A (n = 12 tows). Asterisks (*) indicate significant relationship (p < 0.05).
95

Figure 58. Regressions of volume backscatter (dB) to logarithm of density (# / m3) for each

taxon identified (a–i) from the night 1 sampling during the 12–16 June cruise to

MP140A (n = 11 tows). Asterisks (*) indicate significant relationship (p < 0.05).
96

Figure 59. Regressions of volume backscatter (dB) to logarithm of density (# / m3) for each

taxon identified (a–i) from the night 2 sampling during the 12–16 June cruise to

MP140A (n = 12 tows). Asterisks (*) indicate significant relationship (p < 0.05).
97

Figure 60. Volume-specific total wet weight (mg / m3) of zooplankton taxa (a–i) taken from

12–16 June trip. Taxon weights were recorded for 11 samples from the night and 12

from the day. P-values indicate significance test from analysis of variance for each

taxon.
98

Figure 61. Linear regressions of logarithm of biomass (mg / m3) to volume backscatter for each

zooplankton category (a–i) during the day (green) and night (black) net tows of 12–16

June (MP140A). Asterisks (*) indicate significant relationship between the variables.

Acoustic Surveys

The acoustic surveys conducted during the June 5–8 cruise indicated that sound scattering

was more intense during the night survey compared to the day (Fig. 62, 64). There was a large

increase in zooplankton density between the day net tows and the night net tows during the same

cruise (BR2; Fig. 26, 27). Day net tows averaged less than 50 organisms per m3, however, night

tows averaged over 250 organisms per m3

. The concentration of strong scatterers such as

pteropods and larval fish also increased. Figure 63 illustrates the Sv record of each loop from the

5–8 June day survey around VK203A. Scattering appeared to be more intense from the inner

and near-platform loops, which were both closer to the structure than the majority of net tows.
99

During the night, the pattern of scattering was more intense overall and less variable closer to the

platform (Fig. 64, 65). Unlike the day survey a near-platform loop was not conducted at night.

The dark bands observed during each loop were artifacts produced when the vessel made a turn.

Interestingly, Sv appeared to be stronger during particular sections of each loop (i.e., northeastern

and northwestern bearings), which was consistent within each loop from this survey. Our ADCP

did not have bottom-tracking capability and the vessel was not equipped with a gyrocompass.

The quality of our GPS data was insufficient to estimate current velocities from the ADCP.

Thus, in the absence of data on current direction, it was difficult to hypothesize about the

observed trend in Sv.

In contrast with the 5–8 June studies at VK203A, the surveys conducted during the 12–16

June (MP140A) cruise did not reveal a large increase in Sv from day to night surveys (Fig. 66,

68). This was supported by the zooplankton density results, which also failed to show a large

increase between the day 1 and night 2 plankton net tows (approximately 135 and 141 total

organisms / m3, respectively; Fig. 28, 37).

The 12–16 June cruise was distinguished by a distinct scattering layer apparent from

within both day and night surveys (Fig. 66, 68). During the day, the layer was concentrated

between 3 and 5 m in the outer and middle loops, however, for the inner loop it reached 6-7 m

(Fig. 67). The near-platform loop contained very high spikes in scattering, which was likely due

to fish schools near the structure. At night, scattering occurred at 2-2.5 m and also from 4-9 m

for all loops of the survey (Fig. 69). Fish schools were not apparent from the near-platform loop,

further supporting that fish dispersed at night. There did not appear to be a distinct change in

scattering distribution around the platform for either survey, however, information on current

velocity is needed to evaluate a potential platform-effect.
100
101
102
103
104
105
106
107
108

Discussion

Plankton net sampling

The purpose of this project was to determine if zooplankton distribution was altered by

the presence of a platform. If zooplankton were aggregating around platforms then density

and/or biomass would have been greater from the platform net tows compared to the reference

open water sites. This pattern was evident for some taxonomic groups during some trips,

however, it was not observed as a consistent trend. In addition, high levels of predation from

platform-associated fishes, such as blue runner would likely have produced lower levels of

zooplankton in platform down-current net tows, which also was not observed. Through this

project, I observed both large-scale (cruise) and small-scale (platform up-current vs. platform

down-current) variability in zooplankton distributions, however, net sampling failed to reveal

clear evidence of a platform effect in the form of localized and consistent changes in

zooplankton abundance. Cruise was the most important variable associated with zooplankton

variability during sampling near the two platforms. These differences were compounded by

within-cruise shifts in abundance of particular taxa, however the relative change varied from trip

to trip. For example fish were most abundant during the daytime of the 12–16 June trip to

MP140A, however, night abundances from this same trip were the lowest when compared to the

other three trips. These discrepancies also occurred for other taxa such as

decapods/stomatopods, pteropods, and amphipods. Thus, zooplankton density was not

consistently greater near a particular platform and density often fluctuated widely between

sampling sets within a single cruise.

Densities were generally greater during nighttime sampling, however, is likely due to

vertical migration of many of the taxa sampled. Diel vertical migration is a common factor

contributing to the change in zooplankton abundance in surface waters between day and night

and can vary widely between sampling stations (Checkley et al. 1992). Avoidance of the net also

may have been more prevalent during the day sampling. My sampling occurred in relatively

shallow (approximately 40 m), mid-shelf areas and contained both oceanic zooplankton (Lucifer

spp., hyperiid amphipods, chaetognaths) and meroplanktonic forms (crustacean zoea and

megalopae larvae and larval fish). Most taxa increased in abundance during the night, except for

pteropods and copepods, in which cases, densities were low (approximately 5 /m3) and varied

little. Interestingly, these taxa are both documented vertical migrators (Boltovskoy 1999)

suggesting their density could have been more affected by fine-scale patchiness. Temperature

profiles indicated that the upper 15 m was well mixed (Fig. 8, Chapter 3), except during the

17–20 July (VK203A) cruise where there was a steep thermocline between 6 m (30 °C) and 15 m

(22 °C). This, however did not appear to have a large influence on zooplankton abundance.

The daytime net tows taken at the four sampling stations associated with each platform

showed little evidence of a platform influence on zooplankton distribution, however, the spatial

patterns varied for each taxa. The total zooplankton abundance category showed trends of

decreasing abundance in daytime platform down-current tows from the VK203A trips, but this

pattern was not evident from the trips to MP140A. The total zooplankton category is driven by

the abundance of decapods and stomatopods, which are common prey for blue runner during the

daytime. Deudero (2001) suggested that high densities of fishes near FADs in the Mediterranean

Sea could negatively affect zooplankton biomass near these structures in a manner similar to the
109

“wall of mouths” hypothesis, whereby zooplanktivorous fish forage on the upstream side of a

structure such as a coral reef, and clear the plankton before it reaches the reef (Hamner et al.

1988). During each of my trips, blue runner were observed schooling near the surface, upcurrent of the platform and feeding on zooplankton, however, platform down-current densities

were not consistently lower as seen from the plankton net sampling.

There may be more of a platform enhancement on zooplankton distribution at nighttime,

due to the influence of the light field. The light field may have a greater influence on

photopositive zooplankton, such as some species of larval fish, hyperiid amphipods,

decapods/stomatopods, chaetognaths, and copepods (Land 1992). Ditty et al. (2000) captured

higher numbers of larval and juvenile fish in light trips fished beneath a platform than light traps

positioned 20 m down-current of the structure. In a similar study, hyperiid amphipods collected

from surface light traps taken beneath a platform were observed to increase in abundance over

the course of a night, while decreasing in density from “off-rig” light traps that sampled downcurrent waters (Keenan et al. 2000). Hyperiid amphipods also are common parasites on

gelatinous organisms such as medusae and siphonophores and little is known of how they would

react to a structure such as a platform. When they were highest in density (5–8 June), hyperiid

amphipods were more abundant from the platform up-current samples than platform downcurrent. This may be due to the platform functioning as a large, passive light-trap or increased

predation was negatively affecting down-current density. Larger forms of these amphipods or

juvenile fish may be able to retain position beneath the platform (Land 1992) especially if

current velocity is reduced within the jacket structure as was observed by (Forristall 1996).

Current velocity may greatly affect the degree to which plankton may interact and

aggregate with the platform structure, however, this factor has not been evaluated in this study.

Likely, there were large differences in current velocity among the cruises, which may have

confounded results. Under low current velocities, plankton may be more capable of retaining

position at least temporarily beneath the structure, whereas high current flow likely causes

zooplankton to more immediately pass through the structure. Current velocity can also affect the

foraging response or effectiveness of predators. Lindquist and Pietrafesa (1989) observed

schools of scad (Decapterus punctatus) aggregated on the up-current side of an artificial reef

only under sufficient current velocities (0.25 to 0.50 m/s) whereas, when currents subsided, they

rose to the surface.

Blue runner are active predators during the night around platforms and forage primarily

on fish such as herrings, codlets, and also larval species and larger decapods (shrimp), however

also feed to a lesser extent on other invertebrates (e.g. hyperiid amphipods and pteropods).

Larval fish taken from the plankton net samples were often an order of magnitude more abundant

during the night than day. Compared to the three other sites, however, fish densities were lower

from platform down-current sites, which may be due to blue runner and other predators.

Hastings et al. (1976) did not observe blue runner during night observations near platforms off

Panama City, Florida and suggested that blue runner disperse during the night to feed in

surrounding waters. During my nighttime sampling, however, blue runner were commonly

observed and caught near the platform. Blue runner caught at night fed on larger

decapods/stomatopods and fish prey than observed during the day (Fig. 16, 21). Stanley (1994)

noted that target strengths of fishes near platforms generally were greater during low light
110

periods (i.e., dusk, night, dawn) suggesting that larger fishes visit the platform during these

hours. This may contribute to increased predation pressure on large zooplankton such as larval

fish, decapods/stomatopods, and hyperiid amphipods.

Platforms may function as more than just areas of increased predation. They have been

cited as potential spawning areas (Ditty et al. 2000) and my sampling supports this platformspawning ground concept. There were a large number of fish eggs collected during the 12–16

June trip to MP140A primarily from the platform down-current site during night sampling. This

suggested nocturnal spawning activity of platform-associated fish. Studies of blue runner

reproductive habits indicate the peak times of spawning occur during June, July and August in

the northern Gulf, however, I did not record the state of gonadal tissue during blue runner

dissection. Fish spawning is often related to lunar phase (Lam 1983; Crabtree 1995) and there

was a full moon during this trip. Further examination of the fish eggs would be required to

identify if they were from blue runner.

Distances from the platform revealed inconsistent relationships with zooplankton

densities that varied among cruises and between day and night sampling. While density of

certain taxa decreased near one platform, the same taxa increased in abundance closer to the

other platform; and this pattern often changed from cruise to cruise. The 5–8 June trip to

VK203A showed decreased zooplankton density closer to the platform during the day, while the

17–20 July trip indicated the opposite. Since evaluating the distance from the platform was not

an objective of these cruises, the exact tow locations (and therefore distance) varied from cruise

to cruise. Most of the tows from the 17–20 July cruise were conducted between 100 and 500 m

from VK203A, while many tows from the 5–8 June cruise were over 600 m away. The patterns

observed may be more difficult to detect due to inconsistencies in tow distance among the

cruises.

Both platforms possessed many floodlights, which produced a light field at night,

however, the influence of this light field was not apparent from plankton net samples. All the

tows were conducted over 100 m from the structure, which was generally beyond the light field

and it was unclear to what extent the light field would affect plankton density. With the

exception of one trip, fish density from plankton nets decreased closer to the platforms at night.

This trend, albeit non-significant at the 5% level, may have been due to increased predation

pressure from predators such as blue runner. However, the fish potentially could have been

attracted closer to the structure than my nets reached. Other phototaxic organisms such as

decapods/stomatopods and amphipods only showed greater numbers around the platform during

the 5–8 June trip to VK203A. My observations during the trips were that the lights from the

VK203A platform appeared brighter than the MP140A platform, however, the light field was not

evaluated quantitatively. Larger zooplankton that may be attracted to the platform lights likely

can also detect and avoid the plankton net, creating a bias in the net results. The high variability

in natural density of zooplankton distribution as well as net avoidance is documented and likely

influenced results (Fleminger and Clutter 1965; Omori and Hamner 1982). Non-invasive

sampling methods such as high frequency acoustics provide a way to address this bias.
111

Acoustic Relationships

The use of ADCPs as high frequency echosounders has become very common to evaluate

large scale patterns of sound scattering particles (e.g., Flagg and Smith 1989; Zhou et al. 1998)

and these scattering particles are presumed to be zooplankton and micronekton (Stanton et al.

1994). ADCPs have been used with success to evaluate patterns in zooplankton distribution in

warm- and cold-core eddies and in relation to Mississippi River input in the Gulf (Zimmerman

and Biggs 1999; Wormuth et al. 2000; Ressler 2001). Heywood et al. (1990) used an ADCP to

examine zooplankton distributions around an oceanic island and determined that zooplankton

were more abundant on the down-current side of the island. In addition to using the ADCP, the

above studies also incorporated traditional net sampling. Wiebe et al. (1996) stated that using

acoustics alone to estimate overall plankton biovolume was problematic without knowledge of

the taxonomic composition of the ensonified water. Relationships between taxon-specific

zooplankton density and mass were suggested as the most appropriate method to form predictive

models (Wiebe et al. 1996). Regression between zooplankton biomass or volume and acoustic

backscattering strength (Sv) are most common in ADCP studies (Heywood et al. 1991; Flagg and

Smith 1989; Wiebe et al. 1996), however, studies also have shown acoustic backscattering

strength positively correlated with zooplankton concentration (Ressler 2001).

Through examination of a subset of my plankton net samples, I observed mixed results in

relationships between Sv and net tow contents. The concentration of organisms such as fish,

decapods/stomatopods, thecosomate pteropods, and hyperiid amphipods were often positively

related to Sv as expected, however this result was not consistent during sampling. Significant (p

< 0.05) positive relationships occurred rarely and sometimes there were opposite trends (e.g.,

Fig. 58 f, pteropods). In addition I observed significantly positive relationships from weak

scattering taxa such as gelatinous organisms (e.g., salps, doliolids, siphonophores) during the

night sampling from the 5–8 June cruise, which is difficult to explain. The siphonophores were

not physonect taxa, which possess a gas inclusion and are strong acoustic scatterers (Warren et

al. 2001). Although the calycophore siphonophores are not considered to be strong scatterers,

Ressler (2001) also observed significant correlation (p = 0.002, Spearman’s rank correlation)

between Sv and calycophore siphonophores, common components of my gelatinous zooplankton

category.

Overall zooplankton wet mass doubled from daytime net tows to night tows, however,

backscattering strength increased only 1-2 dB, a factor associated with a 1.3–1.6 fold increase.

Not all taxa increased in wet mass between the two sampling sets, which could contribute to

discrepancies in Sv measurements. One of these taxa, pteropods, was more abundant during the

day (>4 mg/m3) and exhibited significant positive correlation with Sv during this sampling set.

When pteropod wet mass (and concentration) decreased in night samples, however there was no

relationship to Sv, which indicates that scattering was due to another source. The only positive,

significant relationships observed during night sampling were for amphipods and gelatinous

zooplankton. It is likely that many of the organisms that contributed to scattering were large

enough to avoid my net, leading to an underestimation of the biomass of these strong scatterers.

Scattering is affected greatly by the size, orientation, and material properties of the

organism causing the reverberation of sound (Stanton et al. 1994; Wiebe et al. 1996).

Thecosomate pteropods are termed elastic-shelled organisms and contribute orders of magnitude
112

more to sound scattering than weaker scattering organisms such as gelatinous salps, fish eggs, or

decapods. Ressler (2001), however, did not detect significant relationships between pteropod

concentration and Sv. Since my project did not classify organisms beyond general taxonomic

categories, further identification of strong scattering net plankton may be required to refine

predictive relationships. Additional information on length frequency distributions of the

collected zooplankton would also provide inputs to develop scattering models (Stanton et al.

1994). These considerations are planned for future investigations.

Acoustic Surveys

Results from the acoustics surveys generally agreed with the density results from the

corresponding plankton net tows. The sharp increase in total zooplankton density between day

and night net tows from the 5–8 June cruise was complimented by an increase in Sv between day

and night surveys. Net tows occurred not more than 4 hours prior to, and within the same area

covered by the acoustic survey. Further, when there was not much change in zooplankton

density as seen during day and night tows from 12–16 June (MP140A), the acoustic record

showed little variation. These results suggest that the source of scattering was most likely

attributable to zooplankton. It was not the goal of this project, however, to predict zooplankton

density or biomass from backscatter intensity patterns.

Evidence for a platform effect on zooplankton density was difficult to evaluate from the

surveys, however, increased scattering near the platform was evident from one of the four

surveys (5–8 June day survey). This trend was not anticipated, since more of a platform effect

was expected during the night due to influence of the platform light field. It is unclear why

scattering would be elevated around a platform during the day. It is possible that the elevated

scattering close to the platform was due to averaged-down echoes from fish, however, this is

unlikely for two reasons. First, the most enhanced region of scattering is in the form of a

uniform layer from 2-6 m and if this layer were fish, they would have avoided the vessel and

should not have appeared in the echogram. Second, the returns from individual transducers on

the ADCP were highly consistent suggesting that the targets producing the elevated returns were

broadly distributed – something consistent with zooplankton but not with individual fishes. The

two night surveys did not demonstrate conclusive increasing or decreasing scattering close to the

respective platform as scattering in each night survey was similar in the near-platform and the

outer loop. Unfortunately, data on current velocity was not available for this analysis, thus the

influence of current cannot be evaluated here. This is another aspect that will be examined in the

future.
113

Chapter V

General Summary

Blue runner in proximity to offshore petroleum platforms feed primarily on holo- and

mero-planktonic, meso- and macro-zooplankton during the day and macro-zooplankton and fish

at night. The feeding results were comparable from the four platforms studied, however the

seasonal shifts from decapods/stomatopods to fish that were observed in 1996 at GI94B were not

observed at the other platforms. Blue runner in open waters appeared to forage on similar

organisms as platform-associated fish as well as other abundant taxa (e.g., chaetognaths). The

sample size of open-water blue runner was extremely limited, making it difficult to draw

definitive conclusions about their diets. This aspect of their feeding dynamics requires further

examination. Based on the results I have gathered for platform-associated fish, it is clear that

zooplankton and ichthyoplankton are important dietary components. This raised the question of

whether or not the availability of prey is enhanced around platforms.

One way that platforms may provide an enhanced foraging resource for a visual predator

such as blue runner is by providing an opportunity to extend their feeding period beyond daylight

hours. My results clearly show that blue runner near platforms feed after dark. There was

evidence that their feeding strategy varied over the diel cycle. Results from prey type selectivity

and size selectivity suggest that platform-associated blue runner consume larger, potentially

more conspicuous organisms during the night when light levels are low. Feeding periodicity

results show, however, that stomach fullness levels are comparable throughout the day and night,

indicating that blue runner feed on smaller but more numerous organisms during the day

(decapod and stomatopod crustaceans) and larger, less abundant organisms at night (larval and

juvenile fishes). This pattern suggests a shift from a daytime “searcher” feeding strategy to a

nighttime “pursuer” strategy as described by Optimal Foraging Theory (Hughes 1980). Blue

runner were often seen schooling near the surface on the up-current side of platforms during the

day, where they exhibited feeding behavior such as striking the surface where they were likely

striking at prey that contrasted against the water’s surface. Blue runner schools disperse into

surrounding waters at night and likely alter their feeding behavior to pursue larger organisms

while also evading increased number of nighttime predators such as king mackerel

(Scomberomorus cavalla), jack crevalle (Caranx hippos), and barracuda (Sphyraena barracuda).

Both platform and open water blue runner appear to be generalists that can feed

opportunistically. The open water blue runner exhibited stomach fullness values and weight

proportions of fish and decapod prey comparable to platform-associated blue runner caught

during the same time of day. Open water specimens differ from platform fish, however, via

increased proportions of chaetognaths in their stomachs. The tenfold increase in chaetognath IRI

values over platform-associated blue runner was driven by the increased frequency of occurrence

of this prey (85% of fish caught in open waters contained this prey). Preliminary examination of

plankton tows indicated that chaetognaths were greater in abundance near the open water school

compared to daytime concentrations near platforms, while decapod and fish prey were much

lower. This may suggest a dietary response to exploit patches of more available prey. It also

may explain the dietary shift from decapods/stomatopods to fish observed in 1996 at GI94B,

though without concurrent zooplankton abundance data, this is speculative. Blue runner are

considered particulate feeders and while prey and size-selectivity has been demonstrated, a non-
114

discriminate ram filter-feeding strategy should not be ruled out, since literature exists on ram

suspension feeding in other medium-sized carangids (Sanderson et al. 1996 and Sazima 1998).

Ram suspension feeding occurs when a fish swims with open mouth and flared opercles for

periods from a second to several minutes (Sazima 1998). No studies were found on behavioral

observations in blue runner feeding.

Another mechanism by which platforms may provide an enhanced foraging environment

is through localized accumulation of blue runner prey. During the day, this may occur through

passive entrainment within eddies beneath the platform. At night a combination of

hydrodynamic entrainment, vertical shear, and active attraction to the platform light field may

enhance prey densities. Plankton net sampling was able to demonstrate significant differences in

meso-zooplankton abundance and composition between cruises and between day and night

within particular cruises. The patterns of zooplankton abundance were not linked to the two

platforms sampled (VK203A & MP140A) as abundance was not consistently greater near either

platform. The collections made at the four sites in relation to the platform and prevailing surface

current did not indicate a significant platform effect on zooplankton distribution. Data from the

net samples did not clearly demonstrate accumulation of zooplankton at the platforms relative to

the reference sites, however plankton sampling generally occurred greater than 100 m from the

platform. This may have been beyond the range of detecting a platform-associated enhancement

effect.

During the night, the light field of platforms may combine with possible hydrodynamic

influences to further enhance zooplankton accumulation. Again, the net tow data did not provide

definite evidence of a platform effect. Night fish densities were generally lower in net tows

conducted closer to the platforms, however, the minimum distance (100 m) may have been far

enough to mask a localized impact. While the lights likely attract photopositive organisms, it is

also possible that increased predation pressure may have offset any concentration of prey. This

suggests that future net tows be conducted closer to the platform.

Blue runner tend to aggregate on the up-current side of the platform during the day.

Predation by blue runner might be expected to reduce prey densities on the down-current side of

the platform, which may also be detectable at night if blue runner are feeding close to the

platform. My platform down-current net tows did suggest decreased fish densities down-current

of the platform in the majority of nighttime samples, however, the results during the day were

ambiguous. Hyperiid amphipods, commonly consumed by blue runner at night, were also less

abundant in platform down-current tows. These organisms, however, have been documented to

increase in abundance beneath a platform as the night progressed (Keenan et al. 2000), likely due

to attraction to the lights.

Although a reduction in prey densities down-current of the platform might be expected, if

blue runner are actively removing prey from the water that flows past the platform, it is worth

estimating whether the reduction might be measurable given the level of sampling that I

conducted. Data collected during day one of the 12–16 June cruise (MP140A) show

approximately 50 decapods/stomatopods per m3

 pass through the platform. I estimated the

platform area of influence (20 m depth X 100m wide = 2000 m2) and current velocity (0.15 m/s).
115

prey influx = density X area X current velocity = 5.40 X 10 decapods / h 7 (8)

Fourteen blue runner caught during the same time the net was collected averaged 29 decapods in

their stomachs and I estimated 1h for evacuation. Stanley and Wilson (2000a) reported blue

runner density to range from 2,200 to 62,000 near GI94B during 1996-1997. The low-end of the

range was used here to form a conservative estimate.

feeding rate = No. of blue runner X prey consumed / h = 6.38 X 10 decapods / h 4 (9)

A percentage reduction of decapods/stomatopods from predation can be estimated by:

% predation effect feeding rate

prey influx == = reduction 6 38 105 40 10

100 0 18

4

7

.

. . % XX

X (10)

This suggests that predation by blue runner would potentially reduce decapod/stomatopod

density by much less than 1%. For a 25% reduction of decapod/stomatopod prey, over 400,000

blue runner would be required. It should be noted that these values are conservative estimates

because some blue runner examined have contained over 200 decapods in their stomach.

Although the net measurements may not have been conducted sufficiently close to the

platforms to detect an enhancement signal, the hydroacoustic surveys provide an alternative

methodology for examining this signal. The inner and near-platform loops around the structure

were generally closer to the platform than the net tows. Volume scattering strength

measurements, collected with a 1200 kHz ADCP, were used to examine the distribution of sound

scattering particles in waters around VK203A and MP140A. Hydroacoustic data are inherently

ambiguous because of differences in the material properties of biological and abiotic sources of

scattering. My data suggests that zooplankton and ichthyoplankton were contributing to the

measured Sv. Positive relationships were observed between Sv and total zooplankton density and

biomass and as expected these correlations were most convincing for the strong scattering

pteropods, hyperiid amphipods, and larval fish. This was expected because the morphological

characteristics of these organisms (i.e., hard shell, swim bladder) provide a stronger density and

sound velocity contrast that produces a disproportionately strong echo compared to organisms

that contain tissue that is closer in density to water (e.g., salps, doliolids, and fish eggs). Diel and

between-cruise changes in zooplankton density were detected by acoustic surveys conducted

around the platforms. These surveys demonstrated the utility of an ADCP to examine smallscale patterns in sound scattering layers in surface waters around platforms. The preliminary

analysis of the acoustic surveys presented here did not demonstrate consistently elevated (or

depleted) levels of scattering near the platform (<100 m). It is unfortunate that the ADCP

current velocity data could not be reliably analyzed. Such data are essential for determining the

up-current and down-current sides of the platform in each depth stratum. A lower frequency

ADCP (e.g., 300 kHz) would provide sufficient range for bottom tracking while still detecting

organisms of the size range consumed by blue runner. Examination of more surveys along with

including data on current velocity will provide further insight into the localized effects of these

structures.
116

Future Considerations

Through this project, I’ve demonstrated that adult blue runner in proximity to offshore

petroleum platform supplement their diet with zooplankton, however, I was unable to detect

consistent trends of enhanced prey distribution around these structures. Further examination of

blue runner diets from open waters would contribute to the understanding of diet shifts. Shortterm movement patterns of platform-associated blue runner would provide greater detail on

residence time near these structures. Determining the degree to which these fish utilize

platforms seems a difficult, but ultimately manageable and intriguing question to address.

Further examination of the net contents and measurement of size frequencies and material

properties would provide variables needed for additional acoustic modeling. This will help to

further address the question of which taxa are responsible for the Sv measured by the ADCP.

Additional acoustic surveys as well as data on current velocities would be useful to evaluate the

distribution of sound scatterers in relation to platforms. Spatial interpolation procedures such as

kriging (Maynou et al. 1996) would provide a better image of fine-scale patterns of scattering

near platforms.
117

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127

Appendix: Letter Requesting Permission
128

Appendix: Letter Granting Permission
129

VITA

Sean Francis Keenan was born on January 19, 1974, in Leesburg, Florida. He is the son

of Phyllis B. Keenan and Francis D. Keenan and the brother of Allan Keenan and Debbie Almy.

Sean graduated as valedictorian from Mount Dora High School in 1992. He moved to Baton

Rouge, Louisiana, and received a Bachelor of Science degree in zoology with a marine science

concentration from Louisiana State University in December 1996. Sean worked as a research

associate under the direction of Dr. Kenneth Brown in the Department of Biology at Louisiana

State University until August 1999 when he became a graduate assistant under Dr. Mark C.

Benfield in the Department of Oceanography and Coastal Sciences at Louisiana State University.

Sean received a Master of Science degree in oceanography and coastal sciences in August 2002.
131

The Department of the Interior Mission

As the Nation's principal conservation agency, the Department of the Interior has responsibility

for most of our nationally owned public lands and natural resources. This includes fostering

sound use of our land and water resources; protecting our fish, wildlife, and biological diversity;

preserving the environmental and cultural values of our national parks and historical places;

and providing for the enjoyment of life through outdoor recreation. The Department assesses

our energy and mineral resources and works to ensure that their development is in the best

interests of all our people by encouraging stewardship and citizen participation in their care.

The Department also has a major responsibility for American Indian reservation communities

and for people who live in island territories under U.S. administration.

The Minerals Management Service Mission

As a bureau of the Department of the Interior, the Minerals Management Service's (MMS)

primary responsibilities are to manage the mineral resources located on the Nation's Outer

Continental Shelf (OCS), collect revenue from the Federal OCS and onshore Federal and Indian

lands, and distribute those revenues.

Moreover, in working to meet its responsibilities, the Offshore Minerals Management Program

administers the OCS competitive leasing program and oversees the safe and environmentally

sound exploration and production of our Nation's offshore natural gas, oil and other mineral

resources. The MMS Minerals Revenue Management meets its responsibilities by ensuring the

efficient, timely and accurate collection and disbursement of revenue from mineral leasing and

production due to Indian tribes and allottees, States and the U.S. Treasury.

The MMS strives to fulfill its responsibilities through the general guiding principles of: (1) being

responsive to the public's concerns and interests by maintaining a dialogue with all potentially

affected parties and (2) carrying out its programs with an emphasis on working to enhance the

quality of life for all Americans by lending MMS assistance and expertise to economic

development and environmental protection.