OCS Study

MMS 2002-004

Proceedings:

Gulf of Mexico Fish and Fisheries:

Bringing Together New and Recent Research

October 2000

U.S. Department of the Interior

Minerals Management Service

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

Minerals Management Service

Gulf of Mexico OCS Region

OCS Study

MMS 2002-004

Proceedings:

Gulf of Mexico Fish and Fisheries:

Bringing Together New and Recent Research

October 2000

Editors

Melanie McKay

Copy Editor

Judith Nides

Production Editor

Debra Vigil

Editor

Prepared under MMS Contract

1435-00-01-CA-31060

by

University of New Orleans

Office of Conference Services

New Orleans, Louisiana 70814

Published by

New Orleans

February 2002
iii

DISCLAIMER

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

University of New Orleans, Office of Conference Services. This report has been technically

reviewed by the MMS and approved for publication. Approval does not signify that contents

necessarily reflect the views and policies of the Service, nor does mention of trade names or

commercial products constitute endorsement or recommendation for use. It is, however, exempt

from review and compliance with MMS editorial standards.

REPORT AVAILABILITY

Extra copies of this 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 Park Boulevard

New Orleans, Louisiana 70123-2394

Telephone Numbers: (504) 736-2519

1-800-200-GULF

CITATION

This study should be cited as:

McKay, M., J. Nides, and D. Vigil, eds. Proceedings: Gulf of Mexico fish and fisheries: bringing

together new and recent research, October 2000. U.S. Dept. of the Interior, Minerals

Management Service, Gulf of Mexico OCS Region, New Orleans, La. OCS Study MMS

2002-004. 674 pp.

ABOUT THE COVER

Blue angelfish, Holacanthus bermudensis taken on a Gulf of Mexico platform. Photo by Gregory

S. Boland.
v

TABLE OF CONTENTS

Page

LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix

ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxvii

SESSION 1: PLENARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

SESSION 2: OUTER CONTINENTAL SHELF AND DEEPWATER MARINE ECOLOGY

Moderators: Mark Benfield & Gilbert Rowe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

SESSION 3: OFFSHORE PLATFORMS AND THEIR MULTIPLE USER GROUPS

Moderators: Ron Lukens & Villere Reggio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

SESSION 4: PRESENT AND FUTURE FISHERIES MANAGEMENT I

Moderators: Hal Osborne & Bob Shipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

SESSION 5: OFFSHORE PLATFORM COMMUNITIES I

Moderators: Benny Gallaway & Gregg Gitschlag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167

SESSION 6: PRESENT AND FUTURE FISHERIES MANAGEMENT II

Moderators: Hal Osborne & Bob Shipp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281

SESSION 7: OFFSHORE PLATFORM COMMUNITIES II

Moderators: Benny Gallaway & Gregg Gitschlag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355

SESSION 8: EVALUATION OF NATURAL AND/OR ARTIFICIAL REEF PRODUCTIVITY I

Moderators: Kathy Scanlon & Quenton Dokken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497

SESSION 9: EVALUATION OF NATURAL AND/OR ARTIFICIAL REEF PRODUCTIVITY II

Moderators: Kathy Scanlon & Quenton Dokken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599

INDEX TO AUTHORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661

ATTENDEES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665
vii

LIST OF FIGURES

No. Page

1.1. Distribution of Gulf of Mexico oil and gas platforms visited by scientists from

1985 – 2000.............................................................7

1.2. Estimated number of fish around platforms and reef sites. ........................9

2.1. Bacterial abundance (per gram dry sediment); and ammonium and nitrate

concentrations (micromoles) in sediment pore waters as a function of depth (cm)

into the sediments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.2. Conceptual model and carbon budget of the benthic food web on the western

Sigsbee Deep abyssal plain, at a depth of 3.65 km. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

2.3. Variations in biomass of the bacteria (top), meiofauna (middle), and macrofauna

(bottom) as a function of time in response to a seasonal input of organic matter

(POC) from the water column. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

2.4. Deepwater production systems in the Gulf of Mexico. . . . . . . . . . . . . . . . . . . . . . . . . . . 69

2.5. Spatial distribution of surface longline sets made in the Gulf of Mexico during

1998 (Source: National Marine Fisheries Service longline logbook data 1999). . . . . . . 70

3.1. Representation of the Gulf of Mexico Offshore Aquaculture Consortium Ocean

Spar Sea Station and single-point mooring (SPM) design. . . . . . . . . . . . . . . . . . . . . . . . 80

3.2. Hypothetical illustration of a lift-barge potentially designed for offshore

aquaculture operations (courtesy of Dennis Good, Goodstreak Marine, Slidell,

LA). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

3.3. Platform distribution in the northern Gulf of Mexico. . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

3.4. Gulf of Mexico platform distribution by depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

3.5. Gulf of Mexico platform removals by depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

4.1. Map of Florida and shelf waters showing the location of Madison-Swanson,

Steamboat Lumps, and Oculina MPAs and the proposed routes for Buccaneer and

Gulfstream gas pipelines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

5.1. Mean Ucrit (BL s-1) of Florida pompano before and after a 24 h exposure to 3.0%

ethylene glycol (treatment), and before and after sham exposure (control). . . . . . . . . . 177

5.2. Sites sampled during the course of the study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193

5.3. Mean Shannon-Weiner diversity indices (with standard error bars) for plankton

net (GC 18, GI 94, and ST 54) or pushnet (Belle Pass) collections (upper panel)

and light-trap collections (lower panel) from each sampling site. . . . . . . . . . . . . . . . . . 243
LIST OF FIGURES

(continued)

No. Page

viii

5.4. Total length frequency histograms for red snapper Lutjanus campechanus from

the northern Gulf of Mexico: (top) 1,109 specimens from the commercial harvest

of 1998; (middle) 663 specimens from the recreational harvest, April-August

1999; and (bottom) 300 specimens from among mortalities subsequent to the

explosive removal of an oil and gas platform located in Ship Shoal Block 209,

July 1998. The stippled area indicates those TL below the 381 mm (15 inch) TL

minimum size which applied to the commercial fishery through out 1998 and to

the recreational fishery through 3 June 1999. The hatched area delimits the 457

mm (18 inch) TL minimum under which the recreational fishery operated from 4

June to 29 August 1999. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274

5.5. Age frequency histograms for red snapper Lutjanus campechanus from the

Northern Gulf of Mexico: (top) 1,095 specimens from the commercial harvest of

1998; (middle) 646 specimens from the recreational harvest, April-August 1999;

and (bottom) 295 specimens from among mortalities subsequent to the explosive

removal of an oil and gas platform located in Ship Shoal Block 209, July 1998. . . . . 275

5.6. Scattergram of total length (mm) at age (yr) for 295 red snapper Lutjanus

campechanus sampled from the mortalities subsequent to the explosive removal

of an oil and gas platform located in Ship Shoal Block 209, July 1998. . . . . . . . . . . . . 276

6.1. The occurrence of Peprilus burti at the stations sampled in this study . . . . . . . . . . . . . 290

6.2. The occurrence of Etrumeus teres at the stations sampled in this study . . . . . . . . . . . . 291

6.3. The occurrence of Trachurus lathami at the stations sampled in this study. . . . . . . . . . 292

6.4. The occurrence of Loligo sp. at the stations sampled in this study. . . . . . . . . . . . . . . . . 293

6.5. The occurrence of Scomber japonicus at the stations sampled in this study . . . . . . . . . 294

6.6. The occurrence of Stenotomus caprinus at the stations sampled in this study . . . . . . . 297

6.7. The occurrence of Chloroscombrus chrysurus at the stations sampled in this study . . 298

6.8. The occurrence of Engraulis eurystole at the stations sampled in this study . . . . . . . . 299

6.9. The occurrence of Decapterus punctatus at the stations sampled in this study . . . . . . . 301

6.10. The occurrence of Sardinella aurita at the stations sampled in this study. . . . . . . . . . . 302

6.11. The occurrence of Diaphus sp. at the stations sampled in this study. . . . . . . . . . . . . . . 303

6.12. The occurrence of Anchoa hepsetus at the stations sampled in this study. . . . . . . . . . . 304

6.13. The occurrence of Steindachneria argenta at the stations sampled in this study . . . . . 305

6.14. The occurrence of Trichiurus lepturus at the stations sampled in this study . . . . . . . . . 306
LIST OF FIGURES

(continued)

No. Page

ix

6.15. The occurrence of Micropogonias undulatus at the stations sampled in this study . . . . 307

6.16. Length frequency distribution of S. aurita across the depth strata in this study . . . . . . 311

6.17. Length frequency distribution of C. chrysurus across the depth strata in this study . . . 312

6.18. Length frequency distribution of D. punctatus across the depth strata in this study . . . 312

6.19. Length frequency distribution of A. hepsetus across the depth strata in this study . . . . 313

6.20. Length frequency distribution of E. eurystole across the depth strata in this study . . . . 313

6.21. Length frequency distribution of Diaphus sp. across the depth strata in this study . . . . 315

6.22. Length frequency distribution of S. caprinus across the depth strata in this study . . . . 315

6.23. Length frequency distribution of Loligo sp. across the depth strata in this study . . . . . 316

6.24. Length frequency distribution of P. burti across the depth strata in this study . . . . . . . 316

6.25. Length frequency distribution of M. undulatus across the depth strata in this study . . . 317

6.26. Length frequency distribution of E. teres across the depth strata in this study . . . . . . . 317

6.27. Length frequency distribution of T. lepturus across the depth strata in this study . . . . . 318

6.28. Length frequency distribution of T. lathami across the depth strata in this study . . . . . 318

6.29. Length frequency distribution of S. japonicus across the depth strata in this study . . . 319

6.30. Length frequency distribution of S. argentea across the depth strata in this study . . . . 319

6.31. Location of Texas recreational headboat sets in August and September 1999. . . . . . . . 337

6.32. Fishing depth by port for recreational headboat sets in August and September

1999. A. Galveston; B. Port Aransas; C. Port Isabel (August); D. Port Isabel

(September). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 338

6.33. Size distribution of red snapper caught and measured during Texas recreational

headboat sets in August and September 1999. A. Summary; B. Galveston (August

only); C. Port Aransas (August only); D. Port Isabel (August); E. Port Isabel

(September). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341

6.34. Depth and condition (when brought on board) of red snapper caught and

measured during Texas recreational headboat sets in August and September 1999

by fishing port. A. Galveston; B. Port Aransas; C. Port Isabel. . . . . . . . . . . . . . . . . . . . 343

6.35. Fate of red snapper caught and measured during Texas recreational headboat sets

in August and September 1999 by fishing port. A. Summary; B. By port and

month. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345
LIST OF FIGURES

(continued)

No. Page

x

6.36. Depth and fate of red snapper caught and measured during Texas recreational

headboat sets in August and September 1999 by fishing port. A. Galveston; B.

Port Aransas; C. Port Isabel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

6.37. Size and fate of red snapper caught and measured during Texas recreational

headboat sets in August and September 1999 by fishing port. A. Galveston; B.

Port Aransas; C. Port Isabel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348

7.1. Map of study sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361

7.2. Schematic of sampling design showing transect lines, circular surveys, and

sampling area under platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362

7.3. Red snapper assessment results, including platform removals, using Data Set E

(represents arbitrary doubling of moderate to high estimate of red snapper

mortality at platforms) compared to base case assessment (base). . . . . . . . . . . . . . . . . 368

7.4. Appearance of Mobile High Island A389-A platform on 21 October 1981. . . . . . . . . . 375

7.5. Juvenile gray triggerfish recruited to the platform prior to Survey 1. . . . . . . . . . . . . . . 375

7.6. Typical appearance of platform structure three weeks after installation. . . . . . . . . . . . . 378

7.7. Similar location as Figure 7.6 photographed during Survey 2, seven months (211

days) after installation with now noticeable epifaunal community development

evident. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378

7.8. Diverse fish community around well casing area at horizontal cross member

level, Survey 3, ten months (308 days) after installation. . . . . . . . . . . . . . . . . . . . . . . . 380

7.9. Small spiny lobster at Figure 7.8 site, Survey 3, ten months (308 days) after

installation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380

7.10. Atlantic pearl oyster (Pinctada radiata) with attached anemones during Survey 4,

13 months (389 days) after installation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382

7.11. Acorn barnacles (Megabalanus antillensis) with attached anemones during

Survey 4, 13 months (389 days) after installation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382

7.12. Well-developed fouling community on HI A389-A during Survey 5 in October

1992 (4,020 days after installation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383

7.13. Well-developed fouling community on HI A389-A during Survey 5 in October

1992 (4,020 days after installation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383

7.14. Colony of Porites astreoides documented from horizontal support at depth of 9

m, June 1992. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
LIST OF FIGURES

(continued)

No. Page

xi

7.15. The same colony of Porites astreoides as in Figure 7.14, taken August 1995,

colony measuring 42 by 38 cm with mortality in center approximately 8 by 6 cm. . . . 385

7.16. Colony of Diploria strigosa at depth of 15.5 m. Photographed August 1995 when

the coral measured 19 by 16 cm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386

7.17. The same colony of Diploria strigosa as in Figure 7.16. Photographed August

1998. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386

7.18. View of 53-m horizontal support and descending diagonal on HI A389-A

platform from depth of 58 m. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 387

7.19. Location of eight platforms sampled on MS/AL shelf during a pilot study on fish

assemblages associated with oil and gas platforms in 1995. . . . . . . . . . . . . . . . . . . . . . 397

7.20. Water column transmissivity for the eight oil and gas platforms surveyed on the

MS/AL shelf during 1995. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401

7.21. Transmissometer profile from platform 4 (MP-202-A) during a pilot study of oil

and gas platforms on the MS/AL shelf in 1995. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402

7.22. Number of taxa observed by each gear from pilot study of oil and gas platforms

on the MS/AL shelf in 1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405

7.23. Number of taxa observed within each platform and outside each platform from

pilot study of oil and gas platforms on MS/AL shelf in 1995 . . . . . . . . . . . . . . . . . . . . 406

7.24. Mean density of selected taxa recorded by the Aimed Video gear during a pilot

study of oil and gas platforms on the MS/AL shelf in 1995 . . . . . . . . . . . . . . . . . . . . . 407

7.25. Mean density of selected taxa recorded by the Pan & Tilt and 4-Camera Array

video gears during a pilot study of oil and gas platforms on the MS/AL shelf in

1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407

7.26. Mean density of all fish observed at each depth for P&T, AV and 4-C video gears

combined, during a pilot study of oil and gas platforms on the MS/AL shelf in 1995 . 409

7.27. Mean density of red snapper by depth for the P&T, AV and 4-C video gears

combined, during a pilot study of oil and gas platforms on the MS/AL shelf in

1995. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410

7.28. Mean density of gray snapper by depth for the P&T, AV and 4-C video gears

combined, during a pilot study of oil and gas platforms on the MS/AL shelf in

1995. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411

7.29. Mean number of fish per 100 m3

 (+/- SE) for each oil and gas platform surveyed

during a pilot study on the MS/AL shelf in 1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412
LIST OF FIGURES

(continued)

No. Page

xii

7.30. Mean density of total fish versus dominant attached epifauna from eight oil and

gas platforms surveyed during a pilot study on the MS/AL shelf in 1995 . . . . . . . . . . . 413

7.31. Mean densities of snappers versus dominant attached epifauna from eight oil and

gas platforms surveyed during a pilot study on the MS/AL shelf in 1995 . . . . . . . . . . . 413

7.32. Schematic view of stationary hydroacoustic transducer deployment to measure in

situ target strength and density of fishes throughout the water column on each

side of the platform for the three study sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424

7.33. Schematic view of stationary hydroacoustic transducer deployment to measure

horizontal relative density of fishes associated with petroleum platforms. . . . . . . . . . . 425

7.34. Mean fish density (number of fish/m3) by year at Green Canyon 18 (GC18) and

Grand Isle 94 (GI94) from July 1994 to March 1997 and South Timbalier (ST54)

from August 1995 to February 1997. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429

7.35. Mean fish density (number of fish/m3

) by season at Green Canyon 18 (GC18) and

Grand Isle 94 (GI94) from July 1994 to March 1997 and South Timbalier 54

(ST54) from August 1995 to February 1997. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429

7.36. Mean fish density (number of fish/m 3) by time of day from Green Canyon 18

(GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997 and South

Timbalier 54 (ST54) from August 1995 to February 1997. . . . . . . . . . . . . . . . . . . . . . 430

7.37. Mean fish density (number of fish/m 3) by platform side from Green Canyon 18

(GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997 and South

Timbalier 54 (ST54) from August 1995 to February 1997. . . . . . . . . . . . . . . . . . . . . . . 430

7.38. Mean relative fish density (number of fish/m 3

) by distance from the platform at

Green Canyon 18 (GC18) and Grand Isle 94 (GI94) from July 1994 to March

1997 and South Timbalier 54 (ST54) from August 1995 to February 1997. . . . . . . . . . 432

7.39. Mean fish density (number of fish/m3) by depth at Grand Isle 94 (GI94) from July

1994 to March 1997 and South Timbalier 54 (ST54) from August 1995 to

February 1997. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 434

7.40. Estimated number of fishes for each quarterly sample period at Green Canyon 18

(GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997 and South

Timbalier (ST54) from August 1995 to February 1997. . . . . . . . . . . . . . . . . . . . . . . . . 441

7.41. Mean fish density (number of fish/m3) by depth at Green Canyon 18 from

October 1994 to March 1997. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444

7.42 Map of the sites surveyed in June 1999 and 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474
LIST OF FIGURES

(continued)

No. Page

xiii

7.43. Mean fish energy/m3 (antilog of volume backscattering) by depth stratum for HI

A350 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478

7.44. Estimated mean fish density (fish/m3) at depth for HI A350 . . . . . . . . . . . . . . . . . . . . . 479

7.45. Line drawings of WC 617A (toppled platform) and HI A355 (partially removed

platform with a small four leg section to the southwest). . . . . . . . . . . . . . . . . . . . . . . . 481

7.46. Plot of vessel track (dotted lines) over WC 617A (A) and HI A355 (B) for

surveys conducted June 1999 and June 2000. Bathymetry contour show depths at

each reef site and indicate the platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 482

7.47. Acoustic depth profiles of WC 617A and HI A355 based on a geo-referenced

plot of depth from the hydroacoustic survey conducted in June 1999 and 2000 . . . . . . 484

7.48. Estimated mean fish energy /m3 (antilog of volume backscatter) at distance from

reef site for WC 617A (A) and HI A355 (B) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485

7.49. Estimated mean target strength (dB) at depth stratum for WC 617A (A) and HI

A355 (B) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487

7.50. Estimated mean fish density (fish/m3) by depth stratum for WC 617A (A) and HI

A355 (B) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 488

8.1. Numerical proportion (upper row) and gravimetric proportion (bottom row) for

the prey items in the diets of blue runner from the two platforms sampled . . . . . . . . . . 504

8.2. Monthly variation in Index of Relative Importance (IRI) for dominant prey taxa

from the two platforms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 505

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

and MP259A (below) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 506

8.4. Length frequency distributions for decapods taken from surface plankton net and

stomachs of concurrent captured blue runner (n=4) during June 1999. . . . . . . . . . . . . . 507

8.5. Length distributions of hyperiid amphipods collected from a surface plankton net

and from blue runner stomachs in June 1999 at Main Pass 259A. . . . . . . . . . . . . . . . . 508

8.6. Specifications for the modified quatrefoil light-trap used in this study. . . . . . . . . . . . . 517

8.7. Mean plankton net densities (a) and light-trap CPUEs (b) with standard errors for

each sampling trip at Green Canyon 18 (1995-96) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 520

8.8. Mean plankton net densities (a) and light-trap CPUEs (b) with standard errors for

each sampling trip at Grand Isle 94 (1996) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524

8.9. Mean plankton net densities (a) and light-trap CPUEs (b) with standard errors for

each sampling trip at South Timbalier 54 (1997) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 526
LIST OF FIGURES

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No. Page

xiv

8.10. Mean pushnet densities (a) and light-trap CPUEs (b) with standard errors for each

sampling trip at Belle Pass (1997) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527

8.11. Mean plankton net densities (a) and light-trap CPUEs (b) with standard error bars

for depths/locations within each platform site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528

8.12. Size distributions of fish collected with light-traps (shaded bars) and plankton

nets (open bars) at the Green Canyon site (1995-1996) . . . . . . . . . . . . . . . . . . . . . . . . . 529

8.13. Size distributions of fish collected with light-traps (shaded bars) and plankton

nets (open bars) at the Grand Isle site (1996) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531

8.14. Size distributions of fish collected with light-traps (shaded bars) and plankton

nets (open bars) at the South Timbalier site (1997) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 534

8.15. Size distributions of fish collected with light-traps (shaded bars) and a pushnet

(open bars) at the Bell Pass site (1997) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537

8.16. Mean plankton net density (a) and light-trap CPUE (b) with standard error bars

for each lunar phase sampled at Grand Isle 94 (Apr-Sep 1996) . . . . . . . . . . . . . . . . . . 540

8.17. Mean plankton net density (a) and light-trap CPUE (b) with standard error bars

for each lunar phase sampled in May 1996 at Grand Isle 94 . . . . . . . . . . . . . . . . . . . . . 541

8.18. Mean plankton net density (a) and light-trap CPUE (b) with standard error bars

for each lunar phase sampled at South Timbalier 54 (Apr-Sep 1997) . . . . . . . . . . . . . . 542

8.19. Mean pushnet density (a) and light-trap CPUE (b) with standard error bars for

each lunar phase sampled at Belle Pass (Apr-Sep 1997) . . . . . . . . . . . . . . . . . . . . . . . . 543

8.20. Mean Shannon-Weiner diversity indices (with standard error bars) for each gear

type and sampling location for each sampling site . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545

8.21. Southeast Area Monitoring and Assessment Program (SEAMAP) survey areas

sampled during Summer Groundfish, Fall Plankton, Fall Groundfish and Spring

Plankton cruises. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556

8.22. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the

1982 to 1996 Summer Groundfish Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558

8.23. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the

1986 to 1994 and 1996 Fall Plankton Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559

8.24. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the

1986 to 1995 Fall Groundfish Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560

8.25. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the

1982 to 84 and 1986 to 1996 Spring Plankton Surveys . . . . . . . . . . . . . . . . . . . . . . . . . 561
LIST OF FIGURES

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8.26. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid

larvae by year and area for the 1982 to 1996 Summer Groundfish Surveys. . . . . . . . . . 563

8.27. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid

larvae by year and area for the 1986 to 1994 and 1996 Fall Plankton Surveys. . . . . . . 564

8.28. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid

larvae by year and area for the 1986 to 1995 Fall Groundfish Surveys. . . . . . . . . . . . . 565

8.29. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid

larvae by year and area for the 1982 to 1984 and 1986 to 1996 Spring Plankton

Surveys. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 567

8.30. Overall frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid

larvae by SEAMAP survey and area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 568

8.31. Occurrence of labrid and scarid larvae in relation to surface salinity for the 1992

to 1994 Summer Groundfish, Fall Plankton and Fall Groundfish surveys . . . . . . . . . . 569

8.32. Occurrence of labrid and scarid larvae in relation to surface transmissivity for the

1992 to 1993 Summer and Fall Groundfish surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . 570

8.33. Distribution and abundance of labrid and scarid larvae during Oregon II, Cruise

203 in relation to sear surface height. Black vectors are relative geostrophic

currents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572

8.34. Distribution and abundance of labrid and scarid larvae in relation to sea surface

height during the Spring Plankton survey from April 19 to May 19, 1993. White

vectors represent relative geostrophic currents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573

8.35. Distribution and abundance of labrid and scarid larvae in relation to sea surface

height during the Spring Plankton survey from May 20 to June 19, 1993 . . . . . . . . . . 574

8.36. Map of the sites surveyed in June 1999 and 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583

8.37. Recorded track lines of the WFGB hydroacoustic survey conducted in June 2000. . . . 587

8.38. Echogram of WFGB survey conducted June 2000. (A). Screen image includes dB

color scale on left and depth on the right side; red box highlights an area of high

acoustic reflectance presumed to be fish and plankton. (B). Magnified image of a

gentle slope onto the upper Terrace (@40m); arrows highlight fish targets. . . . . . . . . . 588

8.39. Echograms from June 2000 hydroacoustic survey of the WFGB. (A) Linear

changes in reflectance illustrate the value of hydroacoustics in characterizing

bottom type. (B) Large areas of low reflectance on the bottom are thought to be

gas seeps on the lower terrace. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589
LIST OF FIGURES

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8.40. An image of the relative horizontal acoustic reflectance over a bathymetry outline

of the WFGB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591

8.41. An image weighted by depth of the relative horizontal acoustic reflectance over a

bathymetry outline of the WFGB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591

8.42. Estimated density of fish (fish/m3) over the West Flower Garden Bank based on a

dual beam hydroacoustic survey conducted in June 2000 . . . . . . . . . . . . . . . . . . . . . . . 592

8.43. Mean target strength (dB) by Terrace over the West Flower Garden Bank based

on a dual beam hydroacoustic survey conducted in June 2000 . . . . . . . . . . . . . . . . . . . 592

9.1. Relationship between temperature and standing stock for the amphipods

Gammarus sp. and Corophium sp. at EB165A and HI389A. . . . . . . . . . . . . . . . . . . . . 605

9.2. Relationship between temperature and standing stock for the amphipods

Corophium biglovia and Corophium louisiana at EB165A and HI389A. . . . . . . . . . . . 606

9.3. Relationship between temperature and standing stock for the amphipod Caprella

equlibris at EB165A and HI389A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607

9.4. Artificial Reef Study Site. High Island A-532. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617

9.5. Monitoring station locations: stations 1 through 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619

9.6. Digital images of upper 50 cm of stations 1 through 5. . . . . . . . . . . . . . . . . . . . . . . . . . 620

9.7. Average growth measured at station 1 from 5/11/00 - 8/8/00 . . . . . . . . . . . . . . . . . . . . 622

9.8. Average growth measured at station 3 from 5/11/00 - 8/8/00 . . . . . . . . . . . . . . . . . . . . 622

9.9. Summary of growth measurements taken at station 1 from 5/11/00 - 8/8/00. . . . . . . . 623

9.10. Summary of growth measurements taken at station 3 from 5/11/00 - 8/8/00 . . . . . . . . 624

9.11. Average growth measured at station 1 from 8/8/00 – 9/13/00 . . . . . . . . . . . . . . . . . . . . 624

9.12. Average growth measured at station 2 from 8/8/00 – 9/13/00 . . . . . . . . . . . . . . . . . . . . 625

9.13. Average growth measured at station 3 from 8/8/00 – 9/13/00 . . . . . . . . . . . . . . . . . . . . 626

9.14. Average growth measured at station 4 from 8/8/00 – 9/13/00 . . . . . . . . . . . . . . . . . . . . 626

9.15. Map of existing petroleum platforms in the U.S. Gulf of Mexico (source: U.S.

Department of Interior, Minerals Management Service, http://www.mms.org). . . . . . . 635

9.16. Map of artificial reef permit areas off the coast of Alabama in the northern Gulf

of Mexico. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635

9.17. Map of the State of Alabama’s Hugh Swingle permit area for artificial reef

deployment with nine artificial reef sites over which red snapper were tagged. . . . . . . 636
LIST OF FIGURES

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9.18. Distribution of total length at tagging of red snapper tagged in this study. . . . . . . . . . . 641

9.19. Distribution of total length at recapture of terminal recaptures at tagging sites

(black bars, n = 192) and measured terminal recaptures from fishers (gray bars,

n = 97). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641

9.20. Distribution of number of recaptures made on tagging trips over time and fitted

non-linear decay models for A. all terminal recaptures (n = 191), B. terminal

recaptures not at liberty during hurricanes (n = 149), C. terminal recaptures not

transported prior to release (n = 172), and D. terminal recaptures not at liberty

during hurricanes or transported prior to release (n = 139) . . . . . . . . . . . . . . . . . . . . . . 642

9.21. Spatial distribution of recaptures reported by fishers (n = 251) . . . . . . . . . . . . . . . . . . . 642

9.22. Delta method estimates of mean distance and mean velocity of movement . . . . . . . . . 643
xix

LIST OF TABLES

No. Page

1.1. The number of platforms incorporated in Rigs-to-Reefs programs in the GOM

compared to numbers present by water depth from 1987-1999. ....................6

1.2. Estimates of research support and value provided by the GOM oil and gas

industry ................................................................9

2.1. Standing stocks of benthic biota at 3.65 km depth site in the NW Gulf of Mexico . . . . 28

2.2. Landings of tunas and wahoo from the Gulf of Mexico in 1998 (Source: NMFS). . . . . 58

3.1. Comparison of marine aquaculture strategies as categorized by degree of

exposure operation to natural oceanographic and storm events. . . . . . . . . . . . . . . . . . . . 76

3.2. Open Ocean Aquaculture (OOA) Symposia allowing open dialogue and

promotion of international development of open ocean aquaculture. . . . . . . . . . . . . . . . 77

3.3. Growth performance index (M’)a

 calculated from cited L4 (cm) and K values for

potential aquaculture species indigenous to the northern Gulf of Mexico . . . . . . . . . . . 79

3.4. Permits acquired to deploy an aquaculture cage on a single-point mooring (SPM)

in Gulf of Mexico federal U.S. waters and conduct Year 1 oceanographic research

(upper portion of table) and potentially necessary for Year 2 aquaculture research

(lower portion of table). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

3.5. Comparison of scenarios for integration of oil and gas (O&G) platforms in the

development of offshore aquaculture in the Gulf of Mexico. . . . . . . . . . . . . . . . . . . . . . 82

3.6. Simplistic outline of potential expenses experienced for each of the offshore

aquaculture strategies outlined in Table 3.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

4.1. Total estimated private boat fishing trips near oil and gas structures. . . . . . . . . . . . . . . 146

4.2. Total estimated charter boat fishing trips near oil and gas structures. . . . . . . . . . . . . . . 147

4.3. Total estimated party boat fishing trips near oil and gas structures. . . . . . . . . . . . . . . . 147

4.4. Total estimated dive trips near oil and gas structures. . . . . . . . . . . . . . . . . . . . . . . . . . . 148

4.5. Total economic impact of combined annual trip and equipment expenditures for

fishing and diving near oil/gas structures in coastal counties by state and mode. . . . . . 149

4.6. Target species for fishermen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

4.7. Average catch per trip for selected species: Private boats in Alabama. . . . . . . . . . . . . . 151

4.8. Average catch per trip for selected species: Private boats in Mississippi. . . . . . . . . . . . 151

4.9. Average catch per trip for selected species: Private boats in Louisiana. . . . . . . . . . . . . 151
LIST OF TABLES

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4.10. Average catch per trip for selected species: Private boats in Texas. . . . . . . . . . . . . . . . 152

5.1. Daily schedule for swimming performance tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173

5.2. Weight (g), fork length (mm), pre-exposure Ucrit and post-exposure Ucrit (cm s-1,

BL s-1) for treatment and control Florida pompano. . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

5.3. Estimated LC50 values for several fish species exposed to ethylene glycol. . . . . . . . . . 178

5.4. Summary of the commonly observed adult fish assemblages associated with

natural reefs or offshore oil and gas platforms by depth zones as reported in

Gallaway et al. (1980) and subsequently modified by Gallaway (1981) . . . . . . . . . . . . 188

5.5. Number of samples collected at each site by date, gear type, and depth/location.

No lunar phase information was recorded for West Cameron 352 . . . . . . . . . . . . . . . . 197

5.6. Total plankton net density (fish/100 m3

) and light-trap CPUE (fish/10 min) for

fish collected at Green Canyon 19 with standard error (SE), rank, percent of total

catch (%), and months collected for each taxa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200

5.7. Total plankton net density (fish/100 m3) and light-trap CPUE (fish/10 min) for

fish collected at Grand Isle 94 with standard error (SE), rank, percent of total

catch (%), and months collected for each taxa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209

5.8. Total plankton net density (fish/100 m3

) and light-trap CPUE (fish/10 min) for

fish collected at South Timbalier 54 with standard error (SE), rank, percent of

total catch (%), and months collected for each taxa . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

5.9. Total mean light-trap CPUE (fish/10 min) and pushnet density (fish/100 m3) for

fish collected at Belle Pass with standard error (SE), rank, percent of total catch

(%), and months collected for each taxa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

5.10. Total plankton net density (fish/100m3

), pushnet density (fish/100m3), and lighttrap CPUE (fish/10 min) for reef-dependent (RD) and reef-associated (RA)

families of fish collected at each site with standard error (SE) . . . . . . . . . . . . . . . . . . . 236

5.11. Schoener’s Index of Niche Overlap for all sampling sites. Values range from 0-1

and include taxa (at least to the level of genus) from all gears used at each site . . . . . . 242

5.12. Results of a canonical correlation analysis on log-transformed plankton net

densities (15 most dominant taxa) and environmental variables for Green

Canyon 18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244

5.13. Results of a canonical correlation analysis on log-transformed light-trap CPUEs

(18 most dominant taxa) and environmental variables for Green Canyon 18 . . . . . . . 246

5.14 Results of a canonical correlation analysis on log-transformed plankton net densities

(15 most dominant taxa) and environmental variables for Grand Isle 94 . . . . . . . . . . . 247
LIST OF TABLES

(continued)

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5.15. Results of a canonical correlation analysis on log-transformed light-trap CPUEs

(16 most dominant taxa) and environmental variables for Grand Isle 94 . . . . . . . . . . . 248

5.16. Results of a canonical correlation analysis on log-transformed plankton net

densities (15 most dominant taxa) and environmental variables for South

Timbalier 54 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

5.17. Results of a canonical correlation analysis on log-transformed light-trap CPUEs

(16 most dominant taxa) and environmental variables for South Timbalier 54 . . . . . . 250

5.18. Results of a canonical correlation analysis on log-transformed pushnet densities

(15 most dominant taxa) and environmental variables for Belle Pass jetty . . . . . . . . . 251

5.19. Results of a canonical correlation analysis on log-transformed light-trap CPUEs

(15 most dominant taxa) and environmental variables for Belle Pass jetty . . . . . . . . . 252

6.1. Summary of trawling effort for this study. Latitudes and longitudes are in degrees

and minutes North and West respectively. Gear size is the headrope length, in

meters, of the trawl. SysRdm=systematic random, 2DSys=two-dimensional

systematic, StratRdm= stratified random. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287

6.2. Summary of mean CPUE (No./hr, kg/hr) of the major fish in the coastal pelagics

complex. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288

6.3. Mean (+/- S.E.,in No. hr-1) of these species in each GOMEX zone . . . . . . . . . . . . . . . . 295

6.4. Species with the most biomass or most occurrences predominating in the different

regions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296

6.5. Mean catch (+/- S.E., in No. hr-1) of squid across depth (m) strata . . . . . . . . . . . . . . . . 308

6.6. Species with biomass or occurrence predominant at the different depths . . . . . . . . . . . 309

6.7. Mean length (cm) and weight (g) of major pelagic species. . . . . . . . . . . . . . . . . . . . . . 310

6.8. Number of trips and sets sampled from Texas recreational headboats in August

and September 1999 by fishing port. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336

6.9. Frequency distribution (A. Total %; B. Cumulative %) for total length (mm) of

red snapper measured during Texas recreational headboat sets in August and

September 1999. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339

6.10. Percentage of red snapper measured greater than or equal to 450, 425, 400, and

375 mm (18, 17, 16, and 15 inches) total length caught during Texas recreational

headboat sets in August and September 1999. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342
LIST OF TABLES

(continued)

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6.11. Mean depth (m) and frequency for condition (when brought on board) of red

snapper measured during Texas recreational headboat sets in August and

September 1999. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344

6.12. Mean depth (m) and frequency for discard fate of red snapper measured during

Texas recreational headboat sets in August and September 1999. . . . . . . . . . . . . . . . . 347

6.13 Mean total length (mm) and frequency for discard fate of red snapper measured during

Texas recreational headboat sets in August and September 1999 . . . . . . . . . . . . . . . . . 347

6.14. Discards and landings (numbers) of red snapper measured from Texas

recreational headboat sets in August and September 1999 by fishing port. . . . . . . . . . 349

6.15. Discards and landings (whole weight, kg) of red snapper measured from Texas

recreational headboat sets in August and September 1999 by fishing port . . . . . . . . . . 349

6.16. Discards and landings (mean total length, mm) of red snapper measured from

Texas recreational headboat sets in August and September 1999 by fishing port . . . . . 350

7.1. Estimated mortality and descriptive statistics by species and platform. . . . . . . . . . . . . 359

7.2. Estimated mortality of the five most impacted species. . . . . . . . . . . . . . . . . . . . . . . . . . 363

7.3. Recapture rates (100 x number of tags recovered/number of tags released) for tagrecapture study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364

7.4. Population estimates by species and platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364

7.5. Mortality rates (100 x estimated mortality / population estimate) by species and

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364

7.6. Comparison of red snapper mortalities collected at the surface (floaters) with

estimated mortality from the sea floor (sinkers). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366

7.7. Comparison of total length of positively (floater) and negatively (sinker) buoyant

red snapper by platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366

7.8. Species list and estimated abundance above 37 m depth at platform HI A389-A . . . . . 376

7.9. Location, depth and date sampled, of each oil and gas platform surveyed on the

MS/AL shelf during the 1995 pilot study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396

7.10. Video sampling effort by depth at eight oil and gas platforms surveyed during

1995 on the MS/AL shelf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399

7.11. Sampling volume of video cameras used to survey oil and gas platforms on the

MS/AL shelf, during 1995. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400
LIST OF TABLES

(continued)

No. Page

xxiii

7.12. Families observed in all video samples combined from oil and gas platform pilot

study on the MS/AL shelf during 1995. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403

7.13. Percent occurrence of all taxa observed at eight oil and gas platforms with all

video gears from a pilot study on the MS/AL shelf in 1995 . . . . . . . . . . . . . . . . . . . . . 404

7.14. RBD ANOVA (block on platform side) results of vertical log fish density log

(fish density/m3) with platform side, year, season, time of day, depth, current

vectors, temperature, salinity, dissolved oxygen, and selected interactions at the

ST54 petroleum platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428

7.15. RBD ANOVA (block on platform side) results of horizontal log relative fish

density (log (fish density/m3) with platform side, year, season, time of day,

distance from the platform, and selected interactions at the ST54 petroleum

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431

7.16. Mean estimated number of fish by species and mean number enumerated and

percent species composition by depth strata at South Timbalier 54 for all research

trips from July 1995 to March 1997 from hydroacoustic and visual point count

surveys. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433

7.17. RBD ANOVA (block on platform side) results of vertical log fish density

(log(number of fish/m3

) with platform side, year, season, time of day, depth,

current vectors, temperature, salinity,dissolved oxygen, and selected interactions

at the GI94 petroleum platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436

7.18. RBD ANOVA (block on platform side) results of horizontal relative log fish

density (log(number of fish/m3

) with platform side, year, season, time of day,

distance from the platform, and selected interactions at the GI94 petroleum

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437

7.19. Mean estimated number of fish by species and mean number enumerated and

percent species composition by depthstrata at Grand Isle 94 for all research trips

from July 1994 to March 1997 from hydroacoustic and visual point count

surveys. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439

7.20. RBD ANOVA (block on platform side) results of vertical log fish density

(log(number of fish/m3) with platform side, year, season, time of day, depth,

current vectors, temperature, salinity, dissolved oxygen, and selected interactions

at the GC18 petroleum platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443

7.21. RBD ANOVA (block on platform side) results of horizontal log relative fish

density (log(number of fish/m3) with platform side, year, season, time of day,

distance from the platform, and selected interactions at the GC18 petroleum

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445
LIST OF TABLES

(continued)

No. Page

xxiv

7.22. Mean estimated number of fish by species and mean number enumerated and

percent species composition by depth strata at Green Canyon 18 for all research

trips from August 1994 to March 1997 from hydroacoustic and visual pointcount

surveys. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 446

7.23. RBD ANOVA (block on platform side) results of vertical target strength (dB)

with platform side, year, season, time of day, depth, current vectors, temperature,

salinity, dissolved oxygen, and selected interactions at the ST54 petroleum

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450

7.24. Mean target strengths (dB), with Tukey’s studentized means test results by season

at South Timbalier 54. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451

7.25. Mean target strengths (dB) with Tukey’s studentized means test results by time of

day at South Timbalier 54. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451

7.26 Mean target strengths (dB) with Tukey’s studentized means test result by platform

side at South Timbalier 54 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451

7.27. Mean target strength (dB) with Tukey’s studentized means test by water depth

(m) at South Timbalier 54. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452

7.28. RBD ANOVA (block on platform side) results of vertical target strength (dB)

with platform side, year, season, time of day, depth, current vectors, temperature,

salinity, dissolved oxygen, and selected interactions at the GI94 petroleum

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453

7.29. Mean target strength (dB) with Tukey’s studentized means test by year at Grand

Isle 94. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453

7.30. Mean target strength (dB) with Tukey’s studentized means test by season at

Grand Isle 94. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454

7.31. Mean target strength (dB) with Tukey’s studentized means test by time of day at

Grand Isle 94. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454

7.32. Mean target strength (dB) with Tukey’s studentized means test by platform side

at Grand Isle 94. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454

7.33. Mean target strength (dB) with Tukey’s studentized means test by water depth

(m) at Grand Isle 94. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455

7.34. RBD ANOVA (block on platform side) results of vertical target strength (dB)

with platform side, year, season, time of day, depth, current vectors, temperature,

salinity, dissolved oxygen, and selected interactions at the GC18 petroleum

platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456
LIST OF TABLES

(continued)

No. Page

xxv

7.35. Mean target strength (dB) with Tukey’s studentized means test by time of day at

Green Canyon 18. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456

7.36. Mean target strength (dB) with Tukey’s studentized means test by platform side

at Green Canyon 18. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457

7.37. Mean target strength (dB) with Tukey’s studentized means test by water depth

(m) at Green Canyon 18. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457

7.38. Species common names and scientific names, numbers of individuals by stratum,

totals, and percent composition from visual point counts using video from a

remotely operated vehicle (ROV) from High Island A350, June 1999. . . . . . . . . . . . . 480

7.39. Species common names and scientific names along with numbers of individuals

by stratum, totals, and percent composition from visual point counts using video

from a remotely operated vehicle (ROV) from a toppled platform (West Cameron

617A) June 1999. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489

7.40. Species common names and scientific names along with numbers of individuals

by stratum, totals, and percent composition from visual point counts using video

from a remotely operated vehicle (ROV) from a partially removed platform (High

Island A355), June 1999 and 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490

8.1. Regressions fitted for three prey categories commonly consumed by blue runner . . . . 502

8.2. Number of samples, total individuals, families, and taxa collected at each site

with a passive plankton net, light-trap, and plankton pushnet . . . . . . . . . . . . . . . . . . . . 519

8.3. Size ranges (SL in mm) and percent of the total catch by gear for dominant taxa

(>1%) collected by at least one gear type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521

8.4. Schoener’s Index of Niche Overlap values for different surface gear and location

comparisons. (OL) off-platform light-trap, (SL) surface light-trap, (SN) surface

net, (TL) total light-traps, (TN) total nets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 544

8.5. SEAMAP surveys sampling effort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557

8.6. Logistic analysis results of fish energy (antilog of volume backscatter) with class

variables terrace level (Terrace), depth stratum (Stratum), and time of day (TOD)

at WFGB. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 582

8.7. Species common names and scientific names along with numbers of individuals

by stratum, totals, and percent composition from visual point counts using video

from a remotely operated vehicle (ROV) from the West Flower Garden Banks,

June 2000. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 594
LIST OF TABLES

(continued)

No. Page

xxvi

9.1. Cohort Statistics for the amphipod Gammarus sp. at HI389A from March 1995-

August 1995 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 608

9.2. Cohort Statistics for the amphipod Corophium sp. at EB165A, September 1996-

July 1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 608

9.3. Cohort Statistics for the amphipod Corophium biglovia at EB165A, September

1996-April 1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 610

9.4. Cohort Statistics for the amphipod Corophium louisiana from EB65A, October

1996-April 1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 610

9.5. Cohort Statistics for the amphipod Caprella equlibris at EB165A,

September1996-April 1997 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 611

9.6. Composition and total volume of the nine artificial reef tagging sites . . . . . . . . . . . . . 637

9.7. Dates of tagging trips, tagging sites samples, and number of red snapper tagged. . . . . 640

9.8. Literature review of some red snapper diet studies relevant to the present study. . . . . . 657
xxvii

ACKNOWLEDGMENTS

Dr. Ann Scarborough Bull, a former Gulf of Mexico Region staff member, came up with the idea

to have this fisheries workshop. It was her goal to have a comprehensive document of fisheries

research conducted in the Gulf of Mexico.

The success of this meeting is credited to all participants, especially the speakers and moderators

for the time spent preparing for each session. Moderators and speakers are listed by name at the

beginning of each session. 

The University of New Orleans, Office of Conference Services, was the contractor responsible for

logistics of the meeting. The dedicated staff and subcontractors play an integral role in the execution

of this meeting and the compilation of the proceedings. Their efforts are greatly appreciated.

The staff of the Hilton New Orleans Airport was professional and attentive to our needs.
1

SESSION 1: 

PLENARY

Date: October 24, 2000

Presentation Author/Affiliation

Welcome Ann Scarborough Bull

Minerals Management Service

David Stanley

Beak International Incorporated

Rigs to Reefs: A Cooperative Effort Among

Government, Industry, and Academia

Charles A. Wilson

Department of Oceanography &

Coastal Sciences and

Coastal Fisheries Institute

Louisiana State University

Richard A. Kasprzak

Louisiana Department of Wildlife & Fisheries

Bringing Together New and Recent

Research

Andrew J. Kemmerer

National Marine Fisheries Service

Ocean Policy Roger McManus

U.S. Department of the Interior
3

WELCOME

Ann Scarborough Bull

Minerals Management Service

David Stanley

Beak International Incorporated

Offshore petroleum platforms are uniquely designed to span from the bottom of the ocean through

the wave-swept surface. From the beginning in 1947, platforms influenced the marine community

and resource utilization of the Gulf of Mexico region. Domestic energy development increased the

number of offshore platforms to the present level of over 4,000 structures in outer continental shelf

waters. Along with the expansion of hydrocarbon extraction over this period, harvest and

exploitation of fisheries resources also intensified. Prior to oil and gas development (1945 to 1950)

in the Gulf of Mexico, commercial landings of finfish and shellfish in Louisiana and Texas ranged

from 185 to 413 million pounds. As the petroleum industry expanded so did commercial fishery

catches from the Gulf, peaking in the mid-1980s at about 1,700 million pounds. The current

commercial landings are around 1,200 million pounds per year.

Offshore platforms and fisheries of the Gulf of Mexico continue to coexist. Over 90% of commercial

red snapper landings (approximately 4 million pounds per year) originate in Louisiana waters, and

while the exact amount harvested at petroleum platforms is unknown, it is known to be a significant

portion of the harvest. In addition to the commercial fishers frequenting offshore structures,

recreational fishers and SCUBA divers are common platform visitors. Surveys of recreational use

found that 70% of all fishers in coastal Louisiana utilized petroleum platforms as fishing

destinations and catches of anglers at these structures were the highest in the published scientific

literature.

The use of offshore structures by marine organisms and the utilization of these resources by

commercial and recreational fishers and SCUBA divers came long before scientific study of

platform communities. While recreational and commercial users may not have understood the

scientific relationship between the structures and species abundance, they were knowledgeable of

the resources at these sites. As the importance of these structures became evident, scientific

examination of how and why they impact the ecosystem in the Gulf of Mexico began.

Initially, research focused on possible impacts from the discharge of materials and the potential

harm from hydrocarbon spills. Much later the scientific community realized that the actual physical

presence of these structures could be affecting the abundance and distribution of marine organisms

in the region. This later issue has been the focus of recent research.

Through the lay and scientific knowledge gained over the past 40 years, the common perception is

that the 4,000 structures in the region constitute the largest artificial reef complex in the world. A

typical four-pile platform jacket (the underwater support structure of an offshore platform) provides

two to three acres of living and feeding habitat for thousands of underwater species. It is
4

hypothesized that artificial reefs and platforms improve and/or diversify habitat, increase resources,

modify the assemblages of organisms in the region, or concentrate existing resources. The placement

of these defacto reefs has impacted the regional marine community and, with assessments of the

assemblages, modeling of discharges, and research into the non-target use of these structures,

information exists as to the how and why these structures have impacted the marine ecosystem of

the region.

Despite the long-term relationship between the Gulf of Mexico and hydrocarbon production, a

compendium of the results from fisheries-related research does not exist. It is the goal of this

meeting to bring together 30 years of widely spread investigations from the offshore waters of the

Gulf of Mexico. Although we highlight the relationship between petroleum production and the

environment, we include studies well beyond the scope of that topic. The 48 presentations at this

meeting represent the culmination of research by academic, state, federal and private sector

scientists from all areas of the Gulf. A lesson learned from the sessions was that, while many issues

have been resolved for every question answered, new and important investigations result. Thus,

while this may be the first summary of the impact and relationship between offshore structures, the

marine ecosystem and fisheries, it will not be the last.

We acknowledge the efforts and guidance of the many people who contributed to the workshop and

this document. First, we would like to thank the Minerals Management Service (MMS) for

sponsoring the workshop and a large portion of the research presented. We would also like to thank

Ms. Debra Vigil (MMS), Ms. Anne O’Heren Jakob and Ms. Patricia Artega (University of New

Orleans) for the organization, logistics and managing both the workshop and this document. Finally,

we acknowledge the efforts of the authors and their efforts in the laboratory and field resulting in

a better understanding of our interaction with the marine environment of the Gulf of Mexico.

Ann Scarborough Bull, Ph.D.

Minerals Management Service

770 Paseo Camarillo

Camarillo, CA 93010

E-mail:Ann.Bull@mms.gov

Phone:(805) 389-7855

David Stanley, Ph.D.

Beak International Incorporated

14 Abacus Road

Brampton, ON, Canada. L6T 5B7

E-mail:DStanley@beak.com

Phone:(905) 794-2325
5

RIGS TO REEFS: A COOPERATIVE EFFORT AMONG

GOVERNMENT, INDUSTRY, AND ACADEMIA

Charles A. Wilson

Department of Oceanography & Coastal Sciences and

Coastal Fisheries Institute

Louisiana State University

Richard A. Kasprzak

Louisiana Department of Wildlife & Fisheries

This paper provides an introduction to Rigs-to-Reefs and associated research activity in the Gulf of

Mexico (GOM). Herein, we provide a summary of that activity with emphasis on Louisiana and

present some new information on the role and value of the cooperation between industry, academia,

and government in pursuit of science.

Most proponents of the Rigs-to-Reefs program know the story about the evolution of the oil and gas

industry offshore. It began in the early 1940s as technology and demand for hydrocarbon took the

United States into progressively deeper waters of the GOM and other parts of the world. The first

offshore structures were in the Ship Shoal area. These old wooden structures have since been

replaced by large steel towers, but even as early as the 1940s, the fishing value of this “new habitat”

was realized by local fishers.

By the late 1970s and early 1980s, several grass roots organizations and officials within the Minerals

Management Service (MMS) began to raise awareness of the pending loss of fishing hot spots that

fishers had come to enjoy. Then Secretary James Watt and Mr. Villere Reggio of the MMS began

to advocate the concept of Rigs-to-Reefs. Dr. Bob Ditton of Texas A&M, working with Mr. Reggio,

used platform-based volunteers to record the frequency of visits to platforms by fishers. They

showed up to 70% of the trips that venture beyond the Barrier Islands made use of platforms for

fishing activities. This information gave science its first insight into the fisheries’ value and the

economic importance of fish associated with oil and gas platforms (Ditton et al. 1984). 

In the early 1980s, Congressman John Breaux introduced the National Fishing Enhancement Act

(NFEA), which set into place mechanisms by which artificial reefs could be created. This new law

encouraged states to develop well-planned, well-organized artificial reef programs (Stone 1985).

In response to the NFEA and a local interest in preserving the oil and gas platforms to which people

had become accustomed, the Louisiana Artificial Reef Initiative began at Louisiana State University

(LSU) in cooperation with the Louisiana Department of Wildlife and Fisheries (LDWF). This ad hoc

group worked together to develop state legislation that became known as the Louisiana Fishing

Enhancement Act of 1986 and set into motion the first state supported “Rigs-to-Reefs” program. The

act addressed the long-term liability of state funding and called for the development of the State

plan. Later in 1986, a plan was developed by LDWF and LSU, which included input from identified

user groups (commercial, recreational, and industry) and regulatory agencies. Using exclusion
6

mapping, the authors identified areas that were compatible with artificial reef development off

Louisiana, which led to the establishment of nine Planning Areas (Wilson et al. 1987).

Shortly after Louisiana’s efforts to develop a program, Texas set in motion a similar program, and

both states have been very active in turning platforms into reefs. By the end of 1999, 145 oil and gas

structures had been made into artificial reefs in the GOM (Table 1.1). Over the past 12 years,

activity has varied from year to year with as many as 30 platforms being emplaced in one year. At

this point, Rigs-to-Reefs programs are well entrenched within the industry; participants know whom

to call and know the process by which reef permitting and reef establishment takes place. 

Table 1.1. The number of platforms incorporated in Rigs-to-Reefs programs in the GOM compared

to numbers present by water depth from 1987-1999.

Water Depth

(ft)

Oil & Gas

 Structures

Structures

Removed

Artificial Reefs

Gulf of Mexico

0-20 330 230 0

21-100 2335 916 7

101-200 770 220 79

201-400 433 67 59

401+ 70 1 0

TOTAL 3938 1434 145

The public is fairly unaware, however, of the fact that depth limits the logistics of reef creation.

Some 10% of the platforms that have been retired since 1986 have made it into reef programs.

However, most of the platforms in water depths greater than 200 ft., (59 of 67) and nearly half (79

of 220) in water depths between 100 ft. and 200 ft. have been used in reef programs since 1986

(Table 1.1). Unfortunately, in water depths less than 100 ft., liability associated with clearance and

required navigation aids limits their utilization. Our prediction for the future is that there will be a

short-term hiatus in reef development due to new oil and gas recovery technology; however,

removal is inevitable. There are proponents within user groups that say we should keep all structures

in place.

Louisiana recently took a major step in preserving a very popular fish area by converting the

Freeport McMoran Sulfur Rig off Grand Isle, Louisiana, into an artificial reef. This large, unique

design incorporates the platform legs as anchors for the crossmembers and decking laid on the

bottom; a five-point lighting system provides constant navigational aids that are monitored and

maintained by LDWF. This new reef has been shown to harbor a great number of amberjack, cobia,

and mangrove snapper. It is a primary destination for many fishers fishing just offshore of the Grand

Isle area. 
7

Figure 1.1. Distribution of Gulf of Mexico oil and gas platforms visited by scientists from 1985 –

2000. Symbols indicate either bird or fishery research.

Thanks to funds made available to this program through the Sportfish Restoration Act, the Artificial

Reef Trust Fund, and most recently the MMS Coastal Marine Initiative (CMI), we are now learning

a great deal about platforms and the associated life. Scientists at LSU, Texas A&M, and elsewhere

have explored around and under these platforms with divers, videos and hydroacoustic equipment.

For the first time ever, we can put fish numbers to platforms (Figure 1.1). We are now confident that

approximately 10,000-20,000 fish live around each operating platform in depths over 100 ft. and that

desired species such as creole fish, red snapper, and mangrove snapper are abundant. A simple

calculation of the density of red snapper around platforms in water depths of 70-250 ft. yields an

estimate of red snapper in excess of one million red snapper associated with these platforms alone.

This research has only been possible because of the cooperative attitude between industry, academia,

and government. Although funding has been available to conduct this research, it would not have

been possible had certain grass roots elements within the infrastructure of the industry been willing

to take a step (or leap of faith) in working out legal agreements to allow scientists to visit and

conduct research on platforms. Companies like Mobil, BP, Chevron, Amoco, Texaco, and Exxon

are just a few who helped pioneer cooperative agreements and set in motion what will probably

become one of the most successful cooperative research efforts ever.

A number of different researchers have benefitted from industry’s willingness to support research.

As an example of how important this cooperative research is, we offer the following summaries. Dr.

Bob Russell of the Center for Coastal Energy and Environmental Resources at LSU has been
8

actively engaged in tracking the migration of birds across the northern GOM. He has documented

many new species-specific migrations; this research would not have been possible without industry

cooperation. Dr. Russell estimates that his three-year CMI-funded research effort (with 100% in

kind match from industry) would have required eight man-years of ship time. Species of interest

include Prothonortary Warblers, hummingbirds, and Peregrin Falcons. Not only have the sightings

of falcons off platforms dwarfed the previous estimates of population size, but Dr. Russell also

believes that the placement of platforms in the GOM has likely increased the survival of migrating

birds.

Another important example of industry cooperation that exemplifies long-term vision and

cooperation is WAVCIS. This program, established by Dr. Greg Stone of LSU’s Coastal Studies

Institute and the Department of Oceanography, depends upon oil and gas cooperators such as Paul

Broussard of Texaco to establish permanent sea-state monitoring stations on a gridwork of platforms

off Louisiana. These stations were designed and funded to serve as early warning systems for the

projection of tidal surge associated with hurricanes; they are also great aids to fishers heading

offshore. The information associated with this project is particularly important to organizations like

FEMA and even Baton Rouge’s Office of Emergency Preparedness. 

There is still more to come; the Minerals Management Service, through the Coastal Marine Initiative

at LSU, has launched a biotechnology initiative. Scientists are now proposing to study the plethora

of organisms associated with platforms that might be useful in biomedical research. Several projects

have already been funded to archive organisms, the results of which will be later targeted for

medical research.

One can understand the commitment that the oil and gas companies have made to research effort

by looking at a simple map of the Gulf showing where research has taken place. Figure 1.2

illustrates the different sites off Louisiana, Texas, Alabama, and Mississippi that serve on platformbased research projects. Furthermore, Table 2 illustrates the value of that research. We estimate that

over 120 scientists and students have collectively made 400+ trips to platforms since 1985; they

spent a total of 22 platform man-years offshore, logged over 2,000 helicopter hours, and over 250

vessel days. The applied research value (match used by researchers as in-kind support) of this

contribution exceeds $3,500,000. The real cost to duplicate such research platforms would be much

more, considering that research vessels cost over $4,000 per day.

As scientists, we recognize that platforms are unique research stations for oceanography,

meteorology, and now even bird and medical research. We, as benefactors of this cooperation in the

name of science, pose the question, “What can we do to assure that this cooperation will continue

and grow?” We must ask industry, “What can we do to help them continue to make the corporate

commitment to supporting research activities?” The concept of “good corporate citizens” eventually

dwindles with fiscal reality. These potential research platforms are scattered throughout the world;

over 6,000 are currently in use. Future cooperation will not be just limited to the GOM. In addition,

our visions should not be limited to the continental shelf but should include deep water. As the

industry approaches the ocean basin, this cooperative research activity will become even more

valuable.
9

0

5000

10000

15000

20000

25000

30000

22m24m40m60m

100m110m140m220m

Wreck 93m

Partial 100mPartial 100m

Toppled 100m

Number of Fish

Figure 1.2. Estimated number of fish around platforms and reef sites. Depth in meters (m) refers to

water depth of standing platforms. Wreck 93m refers to a drilling rig that sank during

a hurricane, Partial 100m refers to partial removal projects, both in 100m water depth,

and Toppled 100m refers to a platform toppled on its side.

Table 1.2. Estimates of research support and value provided by the GOM oil and gas industry. Data

were provided by Texas A&M and LSU scientists.

Number

of Trips

Platform 

Man Years

Helicopter

Hours

Vessel

Days

Research

Value

406 22.0 2,077 263 $3,600,000

38 Scientists

91 Students

RECOMMENDATIONS 

We encourage MMS to work with industry and interested academic entities to identify mechanisms

to encourage and reward industry for such risk-taking. Since they will incur the expense of

infrastructure support for research, there should be some incentives (tax credits, mitigation) to

continue or even increase industries’ desire to cooperate. As scientists, we want industry to continue

to be our partners, and it is only through active dialogue that we can ensure that this will continue.
10

REFERENCES

Ditton, R., J. Auyong, and V. Reggio. 1984. Fishing Offshore Platforms Central Gulf of Mexico.

Minerals Mgmt. Service OCS Monograph MMS 84-0006.

Stone, R. 1985. National Artificial Reef Plan. NOAA Tech. Mem. NMFS-OF-6. Washington D.C.

Wilson, C.A., V. Van Sickle, and D.L. Pope. 1987. Louisiana Artificial Reef Plan. Louisiana

Department of Wildlife and Fisheries Technical Bulletin 41, Baton Rouge Louisiana.
11

BRINGING TOGETHER NEW AND RECENT RESEARCH

Andrew J. Kemmerer

National Marine Fisheries Service

The ecosystem from the Texas mud flats and Louisiana wetlands to the reefs off Florida then to the

deeper waters of the shelf is truly unique. It supports a broad range of important industries.

Management or conservation strategies associated with this ecosystem simply always involve

uncertainty and risk; the question is how much risk we are willing to accept. We need to minimize

the risks, but at the same time we need to try to maximize the benefits.

After almost a decade of serving as a member of three different fishery management councils, all

at the same time, I am convinced that reasonable people can work together to achieve reasonable

solutions to complex environmental issues as long as these solutions have a firm footing in science.

Good science is key, but unfortunately it will never be quite good enough for some, so there will

continue to be controversy.

The Magnuson-Stevens Act provides the national framework for conserving and managing our

wealth of fishery resources. In 1996, the U.S. Congress acknowledged the importance of habitat in

achieving the full benefits from fishery resources when they enacted the Sustainable Fisheries Act

(SFA). One aspect of the SFA was to refine the focus of fisheries management by emphasizing the

need to protect fisheries habitat. Consistent with this emphasis, Congress required that fishery

management plans identified as “essential fish habitat” (EFH) those areas necessary to fish for their

basic life functions. EFH was defined as “...those waters and substrate necessary to fish for

spawning, breeding, feeding, or growth to maturity.” The areas that may be defined as EFH are

waters of the United States—that is, state and federal waters with the offshore boundary being the

outer limit of the Exclusive Economic Zone (EEZ). EFH only includes water, but indirectly involves

watersheds as well because actions there can affect the waters they drain into.

EFH, probably cannot be considered new any more, except on a relative basis, compared to some

of the other requirements of the Magnuson-Stevens Act. It is, however, controversial and I have

been asked to talk about it in the context of OCS oil and gas development. The effectiveness of EFH

depends on its reasonable application by reasonable people based on good science. The National

Marine Fisheries Service was sued on its implementation of EFH. It is a good topic and one I

struggled with over the last several years.

As most people here are well aware, most of the requirements of the Magnuson-Stevens Act are

being addressed through eight regional fishery management councils, as prescribed by the Act. The

exceptions are the highly migratory species including many of the sharks, billfishes, and tunas,

which are being handled by the Secretary of Commerce through the National Marine Fisheries

Service (NMFS). Congress imposed a deadline of October 1998 for EFH amendments to each of the

fishery management plans, and I believe that all but one of the EFH amendments has been

completed. However, the EFH amendments by three of the fishery management councils were only

partially approved. This approval included the amendments by the Gulf of Mexico Fishery
12

Management Council. The problem with the Gulf Council’s amendments, which I had a part in

preparing, was that they did not fully address all managed species, mainly due to a lack of

information. NMFS is working with the affected councils and we hope that the deficiencies will be

corrected soon.

Overall, the work done by the fishery management councils to respond to the EFH requirements of

the Sustainable Fisheries Act was quite good, and I would strongly recommend that anyone dealing

with marine and estuarine waters get copies of the appropriate amendments. They contain a

tremendous amount of information consisting of maps, lots of tables, and good descriptive

summaries. A high priority for the agency is to get this information into GIS systems so it will be

even more useful and available. Already, this has been done for the New England, Pacific, and North

Pacific Councils.

The best way to conceptualize Essential Fish Habitat is that it is the habitat necessary for federally

managed fish species to complete their life cycles. Generally, EFH for any given fish species

constitutes only a portion of the total available habitat. Usually, this is between 50 and 70% of the

geographic range of a life stage of a managed species. However, once individual EFH designations

for all species in an area are overlaid, the mosaic of designations tends to be inclusive. That is, there

are few marine and estuarine areas in federal and state waters which are not EFH for something.

This designation has caused considerable controversy and has been a principal point of discussion

at a number of Congressional hearings. It is, however, something that should have been expected,

especially considering the number of species and life stages involved. Throughout U.S. waters, we

are talking about more than 700 species each with distinct life stages and habitat requirements.

Interestingly, each of the eight fishery management councils realized essentially the same result with

most of their waters being designated EFH.

At my last count, the Gulf ofMexico Fishery Management Council had seven fishery management

plans for reef fish, red drum, shrimp, coastal migratory pelagics, stone crab, spiny lobster, and coral

and coral reefs. In addition, the Secretary of Commerce, through the NMFS, has two plans including

billfish and highly migratory species such as the tunas and sharks. A substantial number of species

are represented by these plans, each with unique habitat requirements. A number of these species

occur in the Outer Continental Shelf (OCS) area and as a result, their habitat needs have to be

considered through the EFH provisions of the plans in any development of offshore oil and gas.

Because of the expected broad designations of EFH, a provision for designating habitat areas of

particular concern (HAPCs) was used to help focus EFH conservation priorities. These are areas

within EFH that provide extremely important ecological functions and/or are especially vulnerable

to degradation. This designation has caused controversy first because HAPCs were not specifically

mentioned in the Sustainable Fisheries Act and second because some want to limit EFH designations

to HAPCs, which was never the intent. The Gulf Council designated a number of areas in the Gulf

as HAPCs, including the familiar Flower Garden Banks off Texas and Louisiana. These areas tend

to be quite small and environmentally unique. The HAPC designation does not change anything not

already dealt with through an EFH designation, but it does raise a red flag for HAPC areas and for

this reason should help developers and managers alike to be especially careful when dealing with

these areas.
13

Establishing EFH designations was difficult for all of the councils mainly because there is not an

abundance of good habitat information for all managed species. The information tends to be spotty

and limited to the more popular species. To help deal with this problem, the EFH rule identified

information that could be used for the EFH designations at four levels. The first level, for example,

was for situations where information on the distribution of a species was all that was available,

compared to the fourth level where information on production rates by habitat was all that was

available. The North Pacific Council went a step further by defining a “zero” level of information

where even good distributional information was lacking and much of the spatial distribution of a

species had to be assumed. Fortunately, the Gulf Council did not have to go quite this far for their

managed species, for the most part, they were at least able to designate at the first, or distributional,

level. But once again, the Gulf Council’s EFH amendments were only partially approved because

they did not specifically address all managed species.

Probably the most serious misconception about EFH and the EFH rule is that it has created a new

bureaucracy replete with new regulations and requirements, a misconception being promoted by

some who know better. Except in the limited context of fishing effects on EFH, there is very little

regulatory policy about EFH that was not already in effect before the adoption of the Sustainable

Fisheries Act. Prior to EFH, federal agencies had to consult with the NMFS on actions that might

affect fisheries habitat under a host of authorities including the Magnuson-Stevens Act, the Clean

Water Act, the Fish and Wildlife Coordination Act, the National Environmental Policy Act (NEPA),

the Federal Power Act, the Endangered Species Act, and others. Indeed, NMFS was doing well over

10,000 consultations annually, with many of them being done in the Gulf of Mexico, prior to EFH.

The Fish and Wildlife Service, Environmental Protection Agency (EPA), and states provided similar

consultations, and this practice has continued. The major differences before and after EFH are that

now the consulting federal agency has to specifically focus on how their actions might affect

Federally managed species and their habitats, and very importantly, now the consulting agency must

respond in writing to the NMFS recommendations. If the agency disagrees with the NMFS advice,

they have to explain why. In other words, they do not have to accept the advice, only acknowledge

it, though the advice has been accepted over 80% of the time.

The Sustainable Fisheries Act requirement that federal action agencies have to consider how their

actions affect EFH does shift some of the burden from NMFS to the action agencies. So undoubtedly

this shift will increase the agencies’ work load (although one might argue that they should have been

doing this work before in their NEPA analyses). On the other hand, an even better argument is that

NMFS should be doing everything it can to minimize the burden to other federal agencies, which

is exactly what the agency has been trying to do.

Several approaches are outlined in the EFH rule that specifically address this issue of minimizing

the work load for federal agencies, including the NMFS. These are defined in the EFH rule; anyone

in EFH consultations should review them. The most common of these is establishment of a “finding”

between the action agency and NMFS. Usually a “finding” is at the district or regional level. A

finding is nothing more than an agreement between NMFS and the action agency that their existing

process, or their existing process with some agreed upon modification, is adequate to satisfy the

NMFS need for notification and information—that is, it provides the basic information for

consultation.
14

Other approaches include completion of general concurrence or programmatic consultations. The

general concurrence consultation is the easiest, as it asks for a group of current or future similar

actions that may affect EFH, but which are likely to result in no more than minimal adverse effects

individually and cumulatively. Often, reporting requirements exist to allow NMFS to keep track of

what is going on, but most often, little or nothing else is required. The next level is the programmatic

consultation, which allows for a group of similar actions to be evaluated collectively and appropriate

recommendations provided. The best example of such consultations in the Gulf of Mexico is the one

done with the Minerals Management Service (MMS) late last year. This consultation addressed

pipeline rights-of-way, plans for exploration and production, and platform removal on the federal

Outer Continental Shelf It was done through an MMS-prepared EFH assessment, which was based

to a considerable extent on an analysis of past lease sales, MMS funded research, and past

interagency consultation activities. The programmatic consultation contains a number of agreedupon mitigation measures including the protection of live bottoms and a number of other bottom

features, elimination of the Flower Garden Banks from lease sales, oil spill response plans, and

control and removal of pollution. The consultation also includes exceptions for certain types of

activities for which individual consultations will continue to be required, as well as a five-year

review requirement and annual reports.

EFH offers a valuable tool to help protect and conserve habitat vital to the health and well being of

our fishery resources. It is especially important in the Gulf of Mexico because of the importance of

its fishery resources commercially and recreationally, and because of the multitude of other

industries which utilize the Gulf, all of which are important locally and nationally—oil and gas,

shipping, mining, recreation and many others.

Unfortunately, there remains a considerable opposition to EFH from some quarters. Until September

2000, I was unaware of a single instance where an EFH consultation or related requirement caused

an unreasonable delay in any given activity, such as dredging a channel or laying a pipeline. I

believe this is still the case. Yet, some congressional testimony and articles in the trade media

suggest that EFH is the end of any further coastal or offshore development. The data and

information indicate otherwise.

I mentioned at the outset the NMFS was sued over its implementation of EFH. The suit was filed

in 1999 by a consortium of environmental organizations. The suit challenged whether NMFS had

complied with the requirements of the Sustainable Fisheries Act when the agency approved, or

partially approved, the Essential Fish Habitat amendments. The suit specifically addressed effects

of fishing on EFH claiming that not enough was done to minimize these effects. The U.S. Court for

the District of Columbia recently upheld the agency’s approval of the EFH amendments because it

found the decision to approve was reasonable and consistent with the requirements of the Act. That

is the good news. The bad news is that the court also found that the Environmental Assessments, or

EAs, prepared for the amendments, were deficient under NEPA because they failed to examine a

broad enough range of alternatives in dealing with fishing effects. Based on this assessment, the

court issued an injunction prohibiting NMFS from enforcing the EFH amendments until the agency

performs a new and thorough EA or Environmental Impact Statement (EIS) for each amendment.

NMFS is currently evaluating the judge’s order to determine next steps.
15

Should Gulf of Mexico oil and gas structures be considered essential fish habitat? The preamble to

the EFH rule notes that not all human-made structures should be considered essential fish habitat -

only those that meet the EFH criteria and are designated as EFH in an approved amendment. The

Gulf Council took a very broad approach in designating EFH, and unfortunately was not very clear

on this issue. And because of this broad approach and inclusive nature of the Council’s amendments,

one would have to assume that the oil and gas structures in the Gulf do constitute EFH under the

rule. However, I do not believe this necessarily means that all such structures should be considered

good and that NMFS will oppose any removal or modification. This scenario would not make sense.

What it probably means is that each instance of installation, removal, or significant modification will

have to be evaluated at least until more experience is gained and/or the Gulf Council provides

clarification. Overall, I do not see a significant problem. The EFH rule is designed to allow

reasonable people to make reasonable decisions. I am comfortable that this will happen with oil and

gas structures in the Gulf of Mexico.

The NMFS is still operating under an interim EFH rule mainly because the agency wanted to ensure

time for public comment, after some experience with the interim rule. Overall, the experience has

been good and the public comments fairly consistent; therefore, significant changes with the final

rule are unlikely.

Again, I wanted to thank the Minerals Management Services for the invitation to participate in the

conference.
16

OCEAN POLICY

Mr. Roger McManus

U.S. Department of the Interior

One of the accomplishments of the Clinton administration was that it brought more attention to the

marine environment at a higher level within the Executive Branch than any other administration in

the history of the country. The possible exception would be the Johnson Administration in which

Vice President Humphrey and the Stratton Commission conducted the first and only comprehensive

review of national ocean policy. That review took place 30 years ago, and there is plenty of

information to suggest that we should be revisiting the issues studied by Stratton and issues that have

emerged since.

Earlier this year Congress passed the Oceans Act, which would do just that. The act provides

authority for establishing a second oceans Commission, which will have a similar mandate as the

Stratton Commission’s. It will have about 18 months to complete its work and make its

recommendations to the new President and Congress. 

The passage of the Oceans Act may be viewed as the conclusion of a national movement that started

several years ago when the growing need for reform in ocean resource management began to be

recognized. The beginning was the most recent historic reauthorization of the Magnuson Act and

the national media attention that focused on the problems facing America’s fisheries. Other

highlights included the celebratory years of the oceans and the coral reefs, the national Monterrey

conference and the significant preparatory work for it by the Heinz Center, the President’s Ocean

Task Force, and several White House initiatives including executive orders to protect coral reefs and

otherwise to improve the U.S. system of marine protected areas.

Many individuals and institutions have contributed to this progress. Especially important was the

leadership of the President’s Council on Environmental Quality, and within the Council, the work

of Ellen Athas. We all owe Ellen and CEQ a great deal for what they have accomplished. I should

highlight also the work of the Center for Marine Conservation in regard to the Oceans Act and

particularly Eli Weissman for garnering the heavy industry support that proved critical for final

passage.

There have yet been few significant real changes, however, in U.S. ocean policy during this period.

Among the most important was the reauthorization of the Magnuson Act, signifying a change in

Congress’s view of the law as a primarily constituent issue to one of national, natural resource

policy. NOAA is implementing the new changes to Magnuson; it will be a few years before we see

how well they are working.

Among other significant achievements in ocean policy reform was the Department of Defense’s

policy shift that promoted conservation of Right Whales on the east coast and established the
17

Navassa Island National Wildlife Refuge and the red hind closure in the Caribbean. There is time

for more such significant action, but that time is running out.

The lack of real change is understandable when one considers that resistance to changes in current

ocean policy is powerful and entrenched. U.S. ocean policy is largely driven by national security and

international policy concerns. Natural resource management issues have been routinely considered

by the State Department and the Department of Defense as complications to their primary missions,

and they have resisted modifications to allow for routine examination of policy needs. 

That is why we have no cabinet-level mechanism to resolve marine policy issues for resource

management; all such matters are viewed at a national security level. If we are going to manage our

resources better, we must find the means to address the problems as they arise. In the absence of

such mechanisms, we fail to have transparent and public debate about the future of our oceans and

their resources. Energy policy has been a primary victim. Another has been the reconciliation of the

needs to maintain our fisheries and conserve marine biological diversity.

In a recent book on U.S. ocean policy, authors Biliana Cicin-Sain and Robert Knecht have noted that

“U.S. ocean policy is less than the sum of its parts.” They remind us that recent history has seen the

development of single-purpose legal authorities for marine management, but we now need a second

generation policy to guide us in establishing priorities and reconciling conflicts for a comprehensive

management regime. At the end of the Clinton Administration the United States still had no such

comprehensive plan for its Exclusive Economic Zone.

I am honored to be before such a distinguished group today. The Secretariat and the Secretary of the

Interior is very proud of you and MMS and the work you do for the Department and the country. I

am particularly pleased to take talk to marine scientists today.

Good science is essential to marine policy. We need more of your work and that of your colleagues

in and out of government.

Natural resource policy should be informed by the best science available. Nevertheless, there is a

widespread misconception that science can or should dictate policy. As we all know, we use science

to describe and predict how our natural world operates. Human political policy, however, is usually

based on a variety of factors including those that have nothing to do with science or what science

can tell us. Science does not tell us it is a good thing to take care of our environment; it can merely

inform us about the possible results of how we treat that environment. Science cannot tell us how

to be equitable or fair, what to value. We should let science off the hook where it cannot help us and

take responsibility for our philosophies and value judgments.

Unfortunately, policy makers do not approach science that way. They are not trained in scientific

method, and they often misunderstand how science can help them. Sometimes, policy makers even

intentionally misrepresent the role of science to advance their agendas. I was in a meeting recently

in which an administrator was questioning whether one proposed policy was “scientific,” at the same

time acknowledging that the hypothesis she advanced could not be proved. Of course, the issue
18

being discussed was predominantly one of values, not which hypothesis was bearing out best under

experimental testing.

Ideally, of course, we need, particularly for purposes of government work intended to inform policy,

to design our observations and experimental designs to provide answers to carefully thought-out

questions, the answers to which are intended to directly influence policy choices. This happens all

too rarely.

In discussing the role of science in informing policy, I am going to take the opportunity to discuss

a policy problem that has resulted from inattention to some rather basic observational and

experimental information.

Every nation on the planet has the responsibility to help provide for the needs and quality of life for

people. Increasingly, we have recognized that responsibility includes embracing the obligation to

protect the environment. Many people, including myself, believe that obligation includes

responsibility to protect “wildness,” wild places and wildlife. Whether we protect them or not has

huge implications for this and future generations and for how we provide for people and protect the

planet.

The concept of sustainable use has evolved as a goal we can use to achieve both objectives through

balanced mechanism ensuring that our resource use satisfies our needs without undermining future

use. The underlying sustainable use assumption is that you do not have to choose: you can have your

cake and eat it too.

Sustainable use has done a lot of good. In practice, it has promoted environmentally sensitive

management, and the more of that the better. Most of the time, however, development for human

needs alters nature. You cannot have the intensive agriculture, transportation systems, and human

communities people need without making major changes to the sustainability of the natural

environment. You cannot have intensive harvest of timber or grazing or energy development without

significant changes to the sustainability of the natural environment. Such human activities do change

the abundance and diversity of wild living organisms, and they do alter ecological systems. With

respect to those values, in many cases changes are not for the better; they are almost always nonsustainable.

Sustainable use is a fantasy. And, while it has been very useful in promoting environmental

protection, it belongs in the virtual museum of improbable theories such as perpetual motion.

I suggest that the scientific community in particular must contribute to the conversation about

developing a new paradigm for taking care of people and the planet. I propose that this paradigm

have three elements: 

1. That we subscribe to the notion that all human development be conducted in an

environmentally sensitive manner to maintain environmental quality (air, water, soil, noise,

etc.) That the resulting environmental standards be conducive to maintaining the quality of

life for humans and other life forms. 
19

2. That we adopt a proactive strategy for meeting human needs. Already the amount of human

suffering resulting from the lack of basic necessities, clean and healthful living

environments, and the lack of opportunity for productive lives is intolerable. It is a human

tragedy, and a political and environmental powder keg. To the extent that in meeting those

needs, we provide for other life forms as well, that is good and right, but we will accept that

in meeting human needs we are going to sacrifice parts of the planet for ourselves.

3. That we adopt a proactive strategy for protecting wildness. With increasing human numbers,

the days when substantial global wilderness was protected by remoteness are fast receding.

We need to accelerate the protection of such places and their wildlife if we want them

present for future generations. That includes marine places and marine wildlife.

The last topic I want to raise with you is the future of MMS. MMS is an interesting institution. On

the one hand it is the Darth Vader for the environmental community. On the other it is widely

regarded as a professional organization producing practical and credible science and an effective

manager of public resources. MMS is the largest manager of public revenues from marine resources,

and ironically, notwithstanding the Service’s reputation among environmental organizations, it is

a chief source of national conservation funding.

As I noted before, ocean policy experts Biliania Cincin Sain and Robert Knecht have suggested that

we are at the beginning of second generation environmental law where we seek to establish priorities

and reconcile conflict among single uses of marine resources.

I believe MMS has a future as part of this second generation of new authorities. The Service has

taken a major step in this direction with its recent, significant initiatives in marine biotechnology.

I believe that within this century, marine biotechnology products will be the most economically

valuable products we take from the sea. Thanks to the leadership of you and your colleagues,

particularly Ken Turgeon, the Service is well positioned to take a major role in this future.

Here is one more example of what your future role could look like. The most prevalent offshore

structures in this country are navigational aids and oil and gas development structures, the latter

being the most significant in mass and complex in administration. A national debate is now

occurring over how to manage aquaculture structures. In the future, the challenge will be with

renewable energy structures. New uses for offshore structures will increase as they prove to be more

feasible for access to marine resources and as alternative to shore-based facilities. Besides the

authorities provided to MMS for managing oil and gas structures, the only major authority provided

for governing offshore structures is a 19th century law providing for the U.S. Army Corp of

Engineers to judge proposals pertaining solely to navigational concerns. We have a policy and legal

authority vacuum in the face of a clearly coming wave of proposals.

I believe we need a single agency to manage offshore structures, one agency to which a permittee

can apply, an agency to take the lead in NEPA compliance. I would suggest that the substantive

decisions should remain in the domain of the most appropriate agencies, but that conflict resolution

and final siting decisions be with the lead of one agency. I believe that agency should take charge

of collecting revenues for use of the public’s resources. I believe that in designating an agency to
20

take on these responsibilities, we should look to the agency that is most experienced with managing

such structures and most experienced with collecting large revenues from industrial users. I believe

MMS should be that agency.

I urge the MMS to start looking at its basic research and management program and consider what

its expanded role should be as the new oceans act commission starts its work and prepares its

recommendations for the next administration and Congress.
21

SESSION 2: 

OUTER CONTINENTAL SHELF AND DEEPWATER MARINE ECOLOGY

Moderators: Mark Benfield

Gilbert Rowe

Date: October 24, 2000

Presentation Author/Affiliation

Benthic Community Structure and Function

in the Sigsbee Deep, Northern Gulf of

Mexico

Gilbert T. Rowe

Angela Lohse

Fain Hubbard

Texas A&M University

Gregory S. Boland

Minerals Management Service

Elva Escobar-Briones

Universidad National Autonoma de Mexico

Jody Deming

University of Washington

Distribution and Abundance of

Phytoplankton, Zooplankton,

Ichthyoplankton, and Micronekton in the

Deepwater Gulf of Mexico

Douglas C. Biggs

Patrick H. Ressler

Department of Oceanography

Texas A&M University

Deepwater Petroleum Structures as Fish

Aggregating Devices: An In-Progress

Project Report

Randy E. Edwards

Kenneth J. Sulak

Doug Weaver

U.S. Geological Survey

Biological Resources Division

Florida Caribbean Science Center

Habitat Use of Shelf-Edge Topographic

Highs in the Northwestern Gulf of Mexico

by Sharks and Rays (Subclass

Elasmobranchii)

Jeff Childs

Center for Coastal Studies

Texas A&M University-Corpus Christi

(Continued on next page)
22

Presentation Author/Affiliation

Life Along the Edge: the Whale Shark

(Rhincodon Typus) in the Northern Gulf of

Mexico

Jeff Childs

Center for Coastal Studies

Texas A&M University-Corpus Christi

Carolyn M. Burks

Keith D. Mullin

Southeast Fisheries Science Center

National Marine Fisheries Service

NOAA Mississippi Laboratories

John D. Hewitt IV

Aquarium of the Americas

New Orleans

Potential Conflicts Between Deepwater

Fishing and Oil and Gas Operations in the

Gulf of Mexico

David B. Snyder

Luis Lagera

Continental Shelf Associates, Inc.

Peter Arnold

Mandeville, Louisiana

LeRay de Wit

Concord, California

George H. Burgess

Florida Museum of Natural History

University of Florida

Chris Friel

 Florida Marine Research Institute
23

BENTHIC COMMUNITY STRUCTURE AND FUNCTION IN THE

SIGSBEE DEEP, NORTHERN GULF OF MEXICO

Gilbert T. Rowe

Angela Lohse

Fain Hubbard

Texas A&M University

Gregory S. Boland

Minerals Management Service

Elva Escobar-Briones

Universidad National Autonoma de Mexico

Jody Deming

University of Washington

ABSTRACT

The standing stocks and rates of heterotrophic metabolism of the benthos have been estimated in a

joint U.S./Mexican study at a site on the abyssal plain (3.65 km) of the western Gulf of Mexico

(GOM). Total densities and biomass of the principal size categories of the community (bottom

fishes, megafauna, macrofauna, meiofauna and bacteria) were low, as expected from similar studies

in other ocean basins. The total stock sizes, in terms of organic carbon, were lowest in the largestsized organisms and increased in importance as mean size decreased, with the greatest total

biomasses in the bacterial and meiofaunal fractions. The respiration rate of each of the above size

groups was estimated on the basis of mean size, abundance and temperature from established

allometric relationships in the literature. These estimates were incorporated into a carbon budget for

the benthic boundary layer at this site. The total organic carbon remineralization and burial

estimated from the model (10.4 mg C m-2d-1) was more than two times that estimated from the

oxygen consumption in a benthic chamber (ca. 4.0 mg C m-2d-1). A time-dependent numerical

simulation of carbon cycling was constructed from the budget to investigate potential effects of

variations in particulate organic carbon (POC) flux to the sea floor. 

INTRODUCTION

Abyssal plains constitute a significant proportion of the surface of the earth. Although generally

acknowledged as the ultimate sink of detritus from the continents, their biota has long been

considered sparse and depauperate. The abysso-benthic communities of the Sigsbee Deep in the

western GOM, known as one of the flattest surfaces on the deep ocean floor, are less well known

than many other abyssal plains, in spite of its modest depth (3.6 to 3.8 km) and proximity to the

United States and Mexico. Studies in the western basin of the gulf were initiated in the mid-1960s

by Willis E. Pequegnat and his graduate students. This work encompassed the continental slope, rise

and abyssal plain, including what is now well within be the Mexican Exclusive Economic Zone
24

(EEZ). These expeditions aboard R/V ALAMINOS included the Caribbean, as well as the GOM.

Faunal groups studied from the deep gulf included the crustaceans (Pequegnat, L., 1970; Firth 1971),

echinoderms (Carney 1971; Booker 1971), molluscs (James 1972), and fishes (Bright 1968), among

others. Studies included both the megafauna and the macrofauna. Tabulation of fish gut contents

were intended to link the two (Rayburn 1975). Photographs of an “iron stone bottom” north of the

Yucatan Strait suggested deep bottom currents can be strong enough in the eastern Gulf to sweep

large areas free of unconsolidated sediments (Pequegnat 1972). The macrofauna appeared to be

grouped into assemblages that were distributed within zones down the slope onto the abyssal plain

(Kennedy 1976), but no justification was found for separating the abyssal plain fauna into

zoogeographic provinces by latitude or longitude.

Anchor dredge samples across the Sigsbee Deep and van Veen grabs from the northern continental

slope and shelf suggested that the deep benthos was depauperate in numbers and biomass, with

values below those in other ocean basins; the mean size of individual macrofauna was in general

smaller than in the Atlantic at similar depths (Rowe 1971, Rowe and Menzel 1971, Rowe, et al.

1974; Rowe 1983). A log-normal relationship between biomass and depth has been confirmed now

for numerous ocean basins (Rowe 1983), but the decline with depth in the gulf appeared to be

steeper than in most basins. The steep decline was attributed to the gulf’s low primary productivity.

The most extensive sampling of the sediment biota of the continental slope of the northern GOM

was conducted in the 1980s by LGL Ecological Research Associates, with support from the Minerals

Management Service of the Dept. of the Interior. This consisted of paired Gray-O’Hara or GOMEX

box cores (Boland and Rowe 1991), bottom survey camera lowerings and bottom trawling. The

stations studied included three transects down the continental slope off Texas, Louisiana and

Florida. This work stopped at depths just shy of 3 km and therefore did not extend out onto the

abyssal plain. The work on deep-water benthos at Texas A&M beginning in the 1960s up through

the MMS-supported studies of the 1980s has been reviewed in a concise summary by Pequegnat et

al. (1990). However, little information on the abyssal plain was included because the focus was on

the more recent studies of the northern continental slope. Other documentation of the studies of the

slope include reports to MMS (Gallaway 1988 and Gallaway et al. 1988) and a dissertation on the

polychaete annelid worms (Hubbard 1995). 

The Instituto de Ciencias del Mar y Limnologia (ICMyL) of the Universidad National Autonoma

de Mexico (UNAM) initiated extensive studies in the southern GOM with the acquisition of the deep

ocean research vessel JUSTO SIERRA. Mexican biologists are conducting studies of megafauna,

demersal fishes, macrofauna and meiofauna from the continental shelf down across the slope onto

the Sigsbee Abyssal Plain. Stable C and N isotopes have been used to infer pathways through a

benthic food chain (Soto and Escobar-Briones 1995). Deep water studies across the Cordilleras

Mexicanas or “Mexican Ridges” have identified regions that contain enhanced biomass under

surface water masses characterized by accelerated rates of primary production (Escobar-Briones and

Soto 1997; Escobar-Briones et al. 1999). Polychaetes dominated the infauna; they encountered a

mid-slope maximum in abundance similar to that described in the northern gulf (Pequegnat et al.

1990). The fauna could be partitioned into three groups that conformed to depth intervals of > 3 km,

between 1.5 and 3 km, and < 1.5 km. This contrasts with the view of Pequegnat et al. that the slope

in the gulf can be divided into 5 zones. 
25

There are several reasons why the deep-living benthos of the gulf might not be similar to that in the

deep western North Atlantic. For example, their geologic histories are very different. The abyssal

plain of the western GOM began formation on the order of 100 x 106

 ybp when the Yucatan

Peninsula separated from the North American continental plate to form the present deep basin

(Buffler 1978). Much of the abyssal plain is thought to have been formed by turbidity flows of finegrained material originating on the Mississippi Cone. Approximately one to two meters of pelagic

sediments have accumulated since the Holocene. The continental margin south of Texas and

Louisiana and along the western side of Yucatan are both underlain by salt deposits which form

diapiric structures pushing up through the pelagic sediments. Both areas have petroleum deposits

associated with the salt but the degree to which these extend out under the flat sediments of the

abyssal plain is not well-established. Cores from the Sigsbee Knolls in the NE central Sigsbee are

known to be characterized by oily sediments (Rezak et al. 1969).

The western gulf basin has maximum depths of 3.8 km, but this is separated from the Atlantic and

Caribbean by sill depths at 1.5 to 2.0 km stretching between the Yucatan, Cuba and Florida. This

could impede larval dispersal into the GOM at abyssal depths. The deep bottom water of the Sigsbee

Deep is slightly warmer (ca. 4.2oC) than equivalent depths in the Atlantic or Pacific. Thus, all else

being equal, the turnover of organic matter might be slightly faster in the deep gulf than at

equivalent depths in the Atlantic or Pacific Oceans. 

In 1997, a two-ship operation by Texas A&M and UNAM was conducted to add to general

knowledge of the deep gulf biota. The R/V GYRE met the R/V JUSTO SIERRA at a common

station (25°15' N. Lat. x 93°26' W. Long.) on the northern Sigsbee Abyssal Plain, at a depth of 3.65

km. The JUSTO SIERRA traveled up from Tuxpan, sampling along an east - west line across the

Mexican Ridges off Tampico (Escobar Briones et al. 1999), while the GYRE went due south out

of Galveston, directly to the site. According to Escobar-Briones et al. (1999), the sediments at this

site contain 3.8% sand,1.3% organic matter, and 0.17 mg m-3 Chl. a. The near-bottom water contains

6.0 mg L-1 oxygen and 34.8 psu of dissolved salts. As this site is well within the Mexican Exclusive

Economic Zone (EEZ), all sampling conducted from the GYRE was approved a priori by a suite of

Mexican federal agencies. This location in the deep gulf is of potential importance to the economies

of both countries because it lies between, and is potentially underlain by, plentiful offshore fossil

fuel resources (Vargas 1996). The joint study was a component of the longterm Memorandum of

Understanding between UNAM and TAMU. Its specific purpose was to gain a more comprehensive

understanding of community function at a common location in the deep benthic boundary layer of

the GOM. 

METHODS

A large-diameter version of the GOMEX or Gray-O’Hara box core (0.2 m2), as described by Boland

and Rowe (1991), was used to take relatively undisturbed bottom samples. These were subsampled

for meiofauna, bacteria and sediment pore water nutrient analyses with subcores of various

diameters. Plastic hypodermic syringes (20 ml) cut off to make small piston corers were used to

sample bacteria. They extended from the surface of the sediments down to a depth of 8 cm. These

were preserved in 2% formalin and sea water solution filtered through a 0.2 micrometer filter to

exclude contamination. A 20 cm long subcore for nutrient analysis was extruded from the bottom
26

and sectioned at 5 cm intervals. The sections were squeezed through paper filters in a stainless steel

press powered with an hydraulic jack. Blanks were run to determine potential contamination by the

filters. Nutrients were analyzed with an AutoAnalyzer using standard colorimetric reactions. Just

prior to squeezing, the sediments on the top of each section were subsampled for bacteria using a

5 ml plastic hypothermic syringe corer. Two ml were taken at each level sampled. The bacteria

samples were stored at 4° C until return to Seattle, where they were analyzed. Approximately 20 ml

of surface mud was scooped with a single table spoon into a plastic bag and frozen for analyses of

organic and carbonate carbon concentrations. The remainder of each core was sieved through 0.25

and 1.0 mm mesh sieves for estimation of macrofauna species composition, abundance and biomass.

Following laboratory procedures described by Schmidt et al. (1998), the sediment bacteria were

diluted, treated with detergent and sonicated to remove the bacteria from sediment particles for more

even distribution on the counting filter. They were then stained with DAPI and counted under an

epifluorescent microscope.

The meiofauna were sampled by taking 5 replicates from each core with a 60 ml hypodermic syringe

barrel. These were preserved whole with 5% buffered formalin in sea water and Rose Bengal stain

aboard ship. Back in the laboratory these samples were sieved through 175 and 53 micrometer sieves

to remove as much sediment as possible and then sorted to major group using a dissecting

microscope. Lengths and diameters of the harpactoid copepods and nematodes were measured using

an ocular micrometer. Their volumes were calculated and used to estimate wet preserved biomass;

this was converted to carbon biomass from published conversion factors (Rowe 1983).

The macrofauna were sorted to major group in the laboratory using dissecting microscopes.

Individual organisms were removed from the samples and estimates were made of wet weight

biomass by direct weighing using a microbalance or by measuring individual lengths and widths to

determine volume. Organic carbon biomass was calculated from published wet weight to carbon

coversion factors for each of the major taxonomic groups (Rowe 1983). Following sorting to major

taxa and weighing, the animals were transferred to 70% ethanol. The polychaete fraction, which

constituted approximately 65% of the total macrofauna, was sorted to species. 

Total sediment community respiration was measured using a benthic lander containing a pair of

automatically operated benthic incubation chambers. The lander and its operation have been

described previously by Rowe et al. (1994; 1997). Two plexiglass incubation chambers contain

polarographic oxygen electrodes with internally recording data logger to monitor oxygen

concentrations within the chambers continuously. Oxygen consumption by the bottom and its

contained biota is calculated from the decline of oxygen within the chamber over time, the volume

of the chamber (7 l) and the area of the sea floor it covers (0.09 m2

). It was deployed once at the

study site. 

Motile scavengers were sampled by attaching a baited trap to the bottom strut of the lander on the

opposite side from the chambers. The trap used was a commercially available minnow trap

constructed of a plastic cylinder 20 cm in diameter and 40 cm long. Each end of the cylinder was

an inward-facing funnel with a terminal hole measuring 2 cm in diameter. The trap was made of

square mesh measuring 5 mm on a side. The trap was baited with codfish tissue measuring 2 x 7 x
27

7 cm. This muscle tissue had been frozen but was thawed before deployment. This bait was

protected within the trap in a 100 ml plastic jar into which 1 mm diameter holes had been punched

at 1 cm intervals. The purpose of this container was to allow “scent” from the fish flesh to escape

into the bottom water, but prevent the bait from being consumed. This internal container was wired

in place in the center of the cylinder. The trap was wired onto the bottom horizontal aluminum frame

of the lander so that it would be in contact with the sediment when deployed.

No direct quantitative estimate of sedentary megafauna or bottom fishes was made during the joint

study aboard GYRE and JUSTO SIERRA, but earlier work sampled these important size groups

(Pequegnat1983). The principal sampler used was a benthic “skimmer” equipped with an odometer

wheel to estimate area of sea floor covered (Pequegnat et al. 1970). The anterior “mouth” of the

skimmer measured 3 m wide by 1 m high. The anterior frame of the rigid, hour glass-shaped

structure was covered with1.25 cm galvanized wire mesh and its bulbous cod end was covered with

0.6 cm mesh. The original meter wheel data are available in the field notes taken aboard ship at the

time of sampling; distances travelled averaged several kilometers. The notes from Pequegnat’s work

aboard the R/V ALAMINOS are archived at Texas A&M University’s Department of

Oceanography.

Biomass was not measured in the earlier studies. However archived material enabled us to make size

and weight measurements on preserved specimens 30 years after capture. The material used by us

had been dried for storage (ophiuroid and asteroid echinoderms) or retained in 70% ethyl alcohol

(holothuroids). 

The information on the stock sizes and respiration rates of the biota tabulated in the joint study are

put together in a carbon budget to allow a comparison of how carbon is both stored and cycled

within an ecosystem. The respiration of the individual groups of metazoans was estimated

independently from known size and temperature relationships in the literature (Grant and

Schwinghamer 1987; Mahaut et al. 1995; Cruz Kaegi 1998). The rate constants for the size groups

were multiplied by total biomass per square meter to give conversion of organic matter to CO2. The

estimates of respiration for each size category were then used to partition the flow of organic matter

through the food web. Secondary production in the metazoans was assumed to be 10% of the

assimilated carbon (P/R=0.1). For the bacteria however it was assumed that the growth and

respiration are equal (P/R=1). This growth efficiency is somewhat higher than those in previous

studies of deep-sea sediment bacteria reviewed by Deming and Baross (1993), but is similar to

several of the measurements described in Relexans et al. (1996). Using a lower growth efficiency

(a lower P/R) would increase the carbon remineralization relative to biomass production that is

necessary to meet the organic carbon requirements up the food chain. This would increase the total

SOC, thus increasing the disparity between the model estimated SOC and the SOC measured by the

lander. 

Given the information generated on the respiration rates of each of the components above, along

with our assumptions concerning P/R, we calculated predator-prey exchanges required to maintain

steady state. This is a step-wise analysis that has been utilized previously on benthos in the

Demerara Abyssal Plain (Rowe and Deming 1985) and on the continental margin off NE Greenland

(Rowe et al. 1997). The resulting solutions for the predator-prey relationships are not unique, but
28

are based on inferences about how the size classes are most likely partitioning their resources. The

POC input term was assumed to be the sum of the losses to respiration and burial because POC flux

has not been measured in the deep GOM. The simulation of the coupled equations of state for the

standing stocks is solved numerically using the software application program STELLA II.

RESULTS

Bacteria

The standing stocks of the size categories of the biota have been grouped together, in terms of

biomass and numbers per square meter, for comparison (Table 2.1). Bacteria densities (Figure1)

declined from the sediment-water interface into the sediments. The values in the 8 cm deep cores

had a mean value that approximated the mean value over the top 8 cm in the profile. The values in

Table 2.1 are a vertical integration to the bottom of the core. The variation around the mean is the

Standard Deviation of the mean of the 8 cm long cores. The “counting error” of similar studies

conducted on deep-sea sediments by this laboratory is approximately 22%. The biomass is the mean

value (Table 2.1) multiplied by a standard conversion factor for carbon per cell for deep-sea bacteria

(10-14 g C per cell, from Williams and Carlucci 1976) used previously in sediment bacterial biomass

estimates (Rowe and Deming 1985) .

Table 2.1. Standing stocks of benthic biota at 3.65 km depth site in the NW Gulf of Mexico. Values

in parentheses are numbers of replicates (n) and ± standard deviation. 

TAXON ABUNDANCES BIOMASS

Bacteria 6.9 x 108

 cells/ml*

(n=5, ± 1.2 x108

)

408 mg C m-2-20 cm

Meiofauna 2.87 x 105

 ind. m-2

(n=25, ±8 x 104)

83 mg C m-2

(n=25, ±22)

Macrofauna

Total

318 ind. m-2 (macrofaunal taxa)

490 ind. m-2 (meiofaunal taxa)

808 ind. m-2 

32.5 mg C m-2

(n=5, ±15.3 mg C m-2)

Megafauna**

(Asteroid Dytaster insignis (sea star)

and holothuroid Benthodytes typica

(sea cucumber))

10.5 ha-1 0.15 mg C m-2

Scavengers

(Eurythenes grillus, amphipod

crustacean)

21 per 20-hour trap deployment 

* Reported as per gram dry sediment in Figure 2.1; ‘per ml’ used for carbon budget (Figure 2.2).

** from Pequegnat, 1983
29

Figure 2.1. Bacterial abundance (per gram dry sediment); and ammonium and nitrate concentrations

(micromoles) in sediment pore waters as a function of depth (cm) into the sediments.
30

Pore Water Nitrate and Ammonium

The concentrations of nitrate and ammonium in the interstitial water have been plotted as a function

of depth into the sediments (Figure 2.1) along with the bacteria. The NH4

+

 ranged from a low of 25

micromoles at 5 cm up to almost 200 micromoles at the deepest sample. The pattern with depth was

not smooth but erratic. By contrast, the NO3 declined smoothly from a high of 70 micromoles near

the sediment-water interface down to a minimum at the deepest sample, the inverse pattern of NH4

+

,

as expected. The bacterial densities followed much the same pattern relative to sediment depth. The

patterns suggest that nitrification is occurring in the top few cm’s but denitrification is being utilized

in heterotrophic remineralization down to the bottom of the core.

Meiofauna

The mean density of meiofauna-sized organisms was 2.87 x 105 m-2 (s=+8 x 104, n=25). They were

composed primarily of nematodes, accompanied by harpacticoid copepods. Wet preserved weights,

based on volume, had means of 6.8 micrograms for the nematodes and 3.4 micrograms for the

harpacticoids. While it is not unusual for the nematodes to be numerically dominant, it is unusual

for them to be bigger than the crustaceans. Mean biomass was 82.9 mg C m-2 (s=+22, n=25), based

on conversion of the wet weights to carbon (Rowe 1983). 

Macrofauna

The mean macrofauna density was 318 indiv. m-2 (s=+159, n=5), composed of macrofauna taxa

(polychaetes (65%), molluscs (9%) and crustaceans (27%)). In addition, there were 490 ind. m-2

(s=147, n=5) belonging to meiofaunal taxa (harpacticoid copepods, nematodes and ostracods).

Biomass of all taxa retained by the 0.25 mm sieve was 32.5 mg C m-2(s =+15.3, n = 5). The mean

weight therefore was 0.05 mg C ind-1, based on the total of 808 ind. m-2, regardless of taxon. 

Out of a total of 146 individual polychaete annelids in the 5 cores, 96 different species were

encountered. Of these, 61 occurred only once. The highest number for any species was only 8

individuals, a paraonid, possibly Aedicira sp. Only four species out of the total occurred in more

more than one box core. Thus, each box core was almost entirely different from the others. The

mean H’(s) for the polychaetes of individual 0.20 m-2 cores was 2.78 (s=+0.32, n=5). The H’(s)

calculated with the samples lumped together was 4.03. 

Megafauna

The deep gulf summary by Pequegnat (1983) revealed that megafauna on the abyssal plain was

substantially reduced in both numbers and species compared to the continental slope. The

megafauna was dominated by the carnivorous sea star Dytaster insignis and the surficial deposit

feeding sea cucumber Benthodytes typica. Both of these species had wide bathymetric distributions

that extended well up onto the continental slope. Other, less abundant megafauna species were also

observed with some regularity. This included the brittle star Ophiomusium planum, which reached

high densities in isolated locations. Other species observed were the sea cucumber Psychropotes

semperiana and the penaeid crustacean Benthesicymus cereus/iridescens. A number of other large
31

crustacean species were observed in these earlier studies, but it is not clear if they are living near the

bottom or were captured up in the water column (Nematocarcinus ensifer, for example). Information

on the fish populations in the Sigsbee Deep is meagre, with only 4 species listed by Pequegnat for

depths equivalent to or greater than our site. 

The sea star D. insignis, according to Pequegnat, had mean densities of approximately 5 per hectare

at depths of 3.6 km. B. typica reached similar values: from 4 to 7 individuals per hectare. Lower, less

reliable numbers were observed for the large crustaceans B. cereus/iridescens and Nematocarcinus

ensifer and the sea cucumber P. semperiana. It is not known if the crustaceans were caught on the

bottom or in the water column. 

The D. insignis had a mean dry weight of 2.88 g per individual (s=+2.2, n=11). Mean disk diameter

was 23.3 mm (s=+9, n=11). The holothurian B. typica individuals had been preserved in 70%

ethanol and their mean wet preserved weight was 4.04 grams per individual (s=+1.4, n=13). They

had a mean length of 6.6 cm (s=+1.1, n=13) and a diameter of 1.7 cm (s=+0.35, n=13). Thus, the

sea star had a mean dry weight of 14.4 g per hectare and the holothurian had a mean wet weight of

22.2 g wet preserved weight per hectare. The latter value would be equivalent to approx. 3.3 g per

hectare dry weight (Rowe 1983). The two species together would be equivalent to approximately

1.77x10-3 g dry weight m-2. 

Scavengers

In the baited trap, a single species was sampled: the cosmopolitan amphipod crustacean Eurythenes

grillus. A total of 21 were captured, ranging in size from 5 mm to 4 cm. The abundance in the trap

can be compared with other studies as a comparison, but no absolute estimates of abundance are

possible. The trap had been in the water for 20 hours. 

Sediment Community Oxygen Consumption (SOC)

Only one of the two oxygen electrode recorders functioned properly, and the decline in oxygen in

the chamber was equal to a value was 0.186 millimoles O2 m-2hr-1. This is equivalent to

approximately 4.0 mg C m-2d-1(as CO2)

The incubations were not completed because the lander left the bottom prematurely. [A backup

corrosive link dissolved more rapidly than predicted.] As a result, no syringe samples of chamber

water were taken at the end of the incubations. The oxygen demand estimate is based on the data

logged from the oxygen electrode.

DISCUSSION

Food Web Carbon Budget

The information above on stock sizes and respiration rates have been put together as a carbon budget

(Figure 2.2). The total stock size in the detrital organic carbon and bacteria compartment is the sum

of the measured carbon summed over a depth of 20 cm, plus the bacteria integrated to 20 cm. The
32

first step in creating the budget is to calculate respiration rates and growth rates, based on allometric

relationships established in the literature (see Methods). Once the respiration and growth rates are

calculated for each size group, the trophic transfers are calculated from the steady state equations

by forward elimination. The input term is assumed to be the sum of all the loss terms (respiration

and burial). The mean rate was 10.4 mg C m-2d-1. 

The largest total stock sizes were located in the smaller organisms at the bottom of the food web.

The smallest size group, the bacteria, was almost an order of magnitude larger in total mass than the

other size groups. As mean organism size increased, total biomass decreased. Likewise, as size increased, the metabolic rates decreased. In this particular budget, the microbiota have been lumped

with the detrital organic matter because it is not possible to separate the relative contributions of detritus and bacteria in the food web. Almost 50% of the total input was remineralized by the microbial

component. A close second was meiofauna respiration. By comparison, the other respiration flows

were relatively low. Predation by the megafauna and the fishes was estimated to be extremely small

orders of magnitude lower than the fluxes that characterize the bacteria, meiofauna and macrofauna.

Burial of organic carbon was calculated from long-term rates of sediment accumulation.

Approximately one to two meters of Holocene pelagic sediments, composed primarily of foram

ooze, are spread over the entire Sigsbee Deep. Thus, the rate of accumulation is ca. 100 to 200 cm

per 13,000 years; at the time scales of our budget this is ca. 0.0115 cm y-1. Multiplying this by the

concentration in a 1 cm thick layer (22.4 g C m-2-cm) gives a burial rate of ca. 0.7 mg C m-2 d-1. This

is about 7% of the total estimated flux remineralized by the biota.

Deming and Baross (1993) reviewed the relationships between sediment bacteria and depth, organic

carbon and POC input. They found that the best predictor of total bacterial biomass was POC input.

Based on their regression we would estimate that the input of POC at our site would be

approximately 22 mg C m-2 d-1. These estimates can also be compared with values of Relexans et

al. (1996), who measured metabolic rates of sediment bacteria in 3 areas off NW Africa. They

introduced trace quantities of 14C labelled dissolved free amino acid (DFAA) mixtures at in situ

pressures and temperatures. Utilization rates increased from approximately 2 to 6 mg C m-2d-1 as a

function of biomass increases of 150 up to 650 mg C m-2-20 cm. Our biomass (ca. 408 mg C m-2-20

cm) would equate to approximately 3.7 mg DFAA-C m-2d-1 in their regression. This estimate

however does not include other compound classes (lipids and carbohydrates) presumed to be

available to the bacteria in the DOM pool.

A fair number of trawls have been taken across several other continental margins, thus making it

possible to compare densities and biomass of megafauna and fishes with the gulf. Lampitt et al.

(1986) for example plotted log10 biomass of total invertebrate megafauna as a function of depth in

the NE Atlantic. Their regression line predicts that 0.31 g wet weight m-2 should be encountered at

3.7 km depth. Haedrich et al. (1980) measured a wet preserved weight of ca. 0.08 g m-2 of fishes and

0.05 g m-2 of megafaunal invertebrates (echinoderms and crustaceans) between depths of 3.2 and

3.7 km in NW Atlantic, suggesting that the abundance and biomass of these groups is lower there

than in the east Atlantic. The lower value above is appreciably higher than our estimate in the gulf

(0.006 g wet preserved weight m-2= ca. 0.16 mg C m-2, Figure 2.2); thus, compared to the Atlantic,

the deep gulf appears to be relatively depauperate. 
33

Figure 2.2. Conceptual model and carbon budget of the benthic food web on the western Sigsbee

Deep abyssal plain, at a depth of 3.65 km. Values in parentheses are the biomass of each

variable in (mg C m-2) integrated over a sediment depth of 20 cm. No values are given

for the fish because no data are available. Fluxes between boxes are flows of carbon in

units of mg C m-2 d-1.
34

SOC has been measured at a site on the deep abyssal plain in the eastern gulf, and the rate measured

was approximately l.5 times what we measured (Hinga et al. 1979), which is within the usual

experimental error for this type of measurement. These two gulf values are in general near the low

end of comparable sites (Smith and Hinga 1983), being above the west Atlantic (Rowe et al. 1994),

but below the east Pacific (Jahnke and Jackson 1991; Smith 1992; Pilskalin et al. 1996) at

comparable depths. 

Total carbon residence time in both the living and non-living components can be estimated by

dividing the stock size by the flux rate. This gives residence times of 54 days for the living biota and

118 years for the detrital organic carbon, using the sum of the respiration rates based on the size and

temperature model. Based on the lander value, the residence times increase to 131 days for the biota

and 307 years for the non-living fraction because the lander value is less than half model estimates.

Time-Dependent Simulation

The carbon budget above can be put into a set of coupled time-dependent differential equations. The

input term can then be varied in order to investigate the responses of the stock sizes and the fluxes

to changes in the input term. The changes in the input might be natural temporal or spatial variability

or new perhaps alien sources of organic matter such as drilling mud, dredge spoils, etc. 

Each state variable (stock or box) is represented by a differential equation in which the concentration

(stock size) is equal to the flows (arrows) into the stock minus the flows out of the stock. At steady

state, the flows in (+) equal the flows out (-). Because these equations are coupled, they can be

solved simultaneously to estimate the size of each stock over time. Experiments can be run to

estimate the effects of changes in input, growth efficiencies, predation rates, etc., on the biomass of

each stock as a function of time. This includes transient storage as living biomass, transfer between

trophic levels and remineralization into metabolic CO2. A term is also included for long-term burial.

As in the budget above, all units for stocks are mg C m-2 and fluxes are mg C m-2-d-1. Equations for

each stock are

d[Macrofauna]/dt = Deposit feeding + Predation (on meiofauna) - Respiration (by

macrofauna)

d[Megafauna]/dt = Predation (on macrofauna) - Predation (by fishes) - Respiration

(by megafauna)

d[Meiofauna]/dt = Grazing - Predation (by macrofauna) - Respiration (by

meiofauna)

d[Sediment organics and Microbiota]/dt = Input of POC - Longterm burial - Deposit

feeding by macrofauna - Grazing by meiofauna - Respiration(by microbiota)

Initial conditions are defined as the mean values of the stocks represented in Table 2.1 and the boxes

in Figure 2.2. Respiration rates are parameterized as first order decay rates dependent on the size
35

of the stock. Respiration constants, with units of d-1, are calculated by dividing the rate by the stock

size. 

Megafauna Respiration = [Megafauna] * kmegafauna respiration

Microbiota Respiration = [Sediment organics and microbiota] * kOCµbes

Macrofauna Respiration = [Macrofauna] * kmacrofauna respiration

Meiofauna Respiration = [Meiofauna] * kmeiofauna respiration

The respiration rate constants were calculated by dividing the stock size into the flux. The values

follow:

kmegafauna respiration = 0.0019 

kOCµbes =0.01189 

kmacrofauna respiration =0.0169 

kmeiofauna respiration =0.0518 

The units are days (d-1). 

Fluxes attributable to trophic transfers such as predation, deposit feeding, etc., are first-order fluxes

that are functions of donar stock size and a coefficient (listed below) having units of days (d-1), as

follows:

Deposit feeding = [Sediment organics and microbes] * k1

Grazing = [Sediments organics and microbes] * k2

Predation of macrofauna on meiofauna = [Meiofauna] * k3

Predation of megafauna on macrofauna = [Macrofauna] * k4

Predation of fishes on megafauna = [Megafauna] * k5

with the following feeding rate coefficients:

k1 = 2.966E-4

k2 = 0.01159

k3 = 0.00482
36

k4 = 1.23E-5

k5 = 1.91E-4

The largest stock size by far is the detrital carbon in the surficial 20 cm of sediment (approx. 400

to 500 g C m-2-20 cm; Figure 2.2). This is about what would be expected along any continental

margin, based on similar studies (Rowe et al. 1991). The widely-recognized problem with this stock

is that little quantitative information is available on what fraction of the pool can be utilized by the

heterotrophic biota. The assumption was made in earlier models that only a small fraction of the

stock is available, and in earlier models this small fraction was used in the calculation of the donardependent rate constants. If the entire stock is used, then the rate constants are very small and the

effects of variations in the input term on community dynamics are very small. The large pool of

carbon effectively dampens the responses to variations in input. One alternative has been to assume

that the reactive carbon is found only in the top few centimeters of sediment (Khripounoff and Rowe

1985). At our site however nitrate declines continuously throughout the top 20 cm (Figure 2.1), thus

suggesting that degradation of organic matter is not limited to the surface but is continuing to depth

via denitrification (Christensen and Rowe 1984). In the models for our site a full spectrum of

possibilities was run, with the extremes being a pool of detrital carbon in which the entire stock

(400-500 g C m-2-20 cm) was reactive, albeit at extremely low rates, versus a condition in which

only the living carbon (the bacteria) in this stock was reactive. In the latter case the detritus is

effectively non-existent because it is completely unreactive or refractory. We present the results of

the latter extreme, in which the assumption is made that the standing stock of the reactive organic

matter is limited to living bacterial biomass (408 mg C m-2-20 cm). 

As in previous models (Rowe et al. 1997; Rowe 1998), a time-varying function has been used to

represent seasonal changes in primary production in surface waters. The POC input varies over a

365 day cycle from a minimum of 8.4 up to a maximum of 12.4 mg C m-2d-1 . The equation for the

input in the STELLA II code is the following: 

Rain of Organic Particles = IF(Seasonal Variation<0)THEN(8.4)ELSE(8.4+Seasonal

Variation*12.4)

where Seasonal Variation = Sine(pi*days/182.5). This means that during 6 months of the year the

rain into the bottom is 8.4 mg C m-2 d-1, whereas during other 6 months the rain follows a sine curve,

with a maximum of 12.4 mg C m-2 d-1.

Each standing stock has been plotted as a function of time (Figure 2.3). The results suggest that

organic matter input (mg C m-2-d-1) that varies on a seasonal basis will be reflected throughout the

food web. The largest variation is seen in the smallest animals, which also have the highest

respiration and feeding rates. The changes in the larger organisms are small by comparison. A lag

on the order of several weeks can be seen between organic matter in sediments and bacterial

biomass. The lag cascades through the food web such that the largest group, the megafauna, has

peak biomass values at the times when the organic matter in the sediments is lowest. Most of the

organic matter is recycled into CO2, rather than being transferred up the food chain. The mean input

of organic carbon needed to balance the simulated utilization [based on calculated respiration rates]
Figure 2.3. Variations in biomass of the bacteria (top), meiofauna (middle), and macrofauna (bottom) as a functio

response to a seasonal input of organic matter (POC) from the water column. Units are mg C m-2.
38

reflects values that might be encountered at equivalent depths along many continental margins

where similar studies have been conducted. 

The lags in response to the input of organic matter and the translation of lags along the food web

suggest that predicting the times of the year that highest biomass or greatest community respiration

rates will be encountered will not be simple. The works of Muller Karger et al. (1990) and Walsh

et al. (1989) have documented that highest plant biomass occurs in the winter when mixing is

greatest. Thus, according to our analysis, highest biomass and respiration values in deep water

would be encountered during the following summer.

Experiments have also been run to estimate the effects of constant step-like increases. These result

in a ramp up of all rates and biomass values with steady state being reached for each group at

various time periods. The smaller organisms reach steady state in relatively short periods (weeks to

months), but the larger organisms take months to years, depending on the increase in the input term.

This type of shift up could be used to investigate the effects of organic loading from alien sources

such as drilling mud, dredge spoils, etc. 

The model can be validated by measuring changes in biomass over time or by measuring respiration

rates. The lander incubation value can be regarded as an independent assessment of the combined

respiration of the organisms living within and on the sediments. In our single measurement, we

discovered that the mean rate of POC utilization predicted from the simulation is approximately 2.2

times higher than the direct measurements of sediment community respiration obtained using the

benthic lander at this site (9.7 vs. 4 mg C m-2d-1). Thus, the indirect estimates of respiration based

on mean biomass, total biomass and temperature need adjustment.

ACKNOWLEDGMENTS

We thank the Department of Oceanography for support of the Texas-based portion of this project,

as well as for the use of the R/V GYRE. The Instituto Ciencias del Mar y Limnologia studies were

supported by the Universidad National Autonoma de Mexico and the Consejo Nationale de Ciencias

y Tecnologia of Mexico. CONACyT. We thank Rodolfo Dirzo for insightful comments. The crews

of the GYRE and the JUSTO SIERRA deserve our sincere appreciation for conducting the

collaborative studies in close proximity, along with providing hospitable and enlightening exchanges

of samples, students and staff between the ships at sea.

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44

DISTRIBUTION AND ABUNDANCE OF PHYTOPLANKTON ZOOPLANKTON,

ICHTHYOPLANKTON, AND MICRONEKTON IN

THE DEEPWATER GULF OF MEXICO

Douglas C. Biggs

Patrick H. Ressler

Department of Oceanography

Texas A&M University

Phytoplankton distribution and abundance in Gulf of Mexico (GOM) waters has been reviewed at

decadal intervals over the last 30 years, first by Bjornberg (1971), then by Iverson (in Iverson and

Hopkins 1981), and most recently by Vargo (in Vargo and Hopkins 1990). Most of the primary

literature these reviewers cited focused on the continental shelf. Moreover, Vargo, in particular,

noted that much of the information for his review came from studies conducted 10 to 20 years before

1990. In fact, data collected by expeditions in the 1960s and 1970s remain the basis for the general

paradigm that standing stocks and productivity of phytoplankton are both quite low seaward of the

shelf-slope break in the Gulf of Mexico. In the review for this Fish and Fisheries Workshop, we

support that description of the mean state but we also show that research carried out since 1987

indicates “hot spots” in primary production occur when/where nutrient availability is locally

enhanced, even in deepwater seaward of the shelf-slope break. 

In the late 1960s, Soviet scientists characterized the deepwater GOM as very low in standing

plankton biomass and with mean primary productivity of just 100-150 mg C m-2 d-1 (KoblenzMishke et al. 1970). A few years later, extensive surveys of phytoplankton chlorophyll and primary

production that span the period 1964-1971 were summarized by El-Sayed (1972) in atlas format,

as averages within 2° squares of latitude and longitude. In the atlas, low values of primary

production (< 0.25 mg C m-3 h-1) are typical. When integrated from surface to base of the photic

zone, most 2° squares total < 10 mg C m-2 h-1. If there are on average 12 h of sunlight per day, this

rate is equivalent to < 120 mg C m-2 d-1 and so is in good agreement with characterization by

Koblenz-Mishke et al. Allowing for primary production to proceed 300 days a year in the GOM

because of its subtropical climate, this rate of primary productivity is < 36 g C m-2 y-1. As a

consequence, the deepwater GOM is usually placed at the low end of the estimated range of 50-160

g C m-2 y-1 that is generally accepted for the annual gross primary production in open-ocean

ecosystems (Smith and Hollibaugh 1993).

When essential plant nutrients are limiting, any process that increases the nutrient concentrations

available to the phytoplankton in the deepwater GOM will increase primary productivity. It is well

known that freshwater inputs carry high nutrient loads, but in the GOM these high nutrient inputs

are usually measurable only close-in to rivers and estuaries (Lohrenz et al. 1999). An exception

occurs, however, when surface currents set up off-shelf flow that carries the river water seaward past

the shelf-slope break and into deepwater. In mid-summer 1998, low salinity Mississippi River water

was entrained and wrapped clockwise around the periphery of a warm slope eddy that altimetry

showed was centered near 28.5°N, 87°W. A comparison of the salinity and chlorophyll fields shows

that surface chlorophyll concentrations in this river water exceeded 2 mg m-3 and that the patches
45

of highest surface chlorophyll corresponded spatially to the patches of lowest surface salinity. In

fact, NEGOM fieldwork documented similar situations in subsequent summers 1999 and 2000 and

GulfCet II fieldwork documented entrainment of low salinity “green water” and its transport offshelf in the previous summer 1997. We suggest entrainment and transport off shelf may be the rule,

rather than the exception, when/where a warm slope eddy is present in the NE Gulf.

Recently, Wiseman & Sturges (1999) reviewed some large and mesoscale motions that might

enhance the availability of nutrients for primary production. They pointed out that the high velocity

periphery of slope eddies (and other eddies) are regions of high vertical shear and thus might be

expected to be areas of nutrient upwelling as well as regions of nutrient-rich river water entrainment.

In fact, direct measurements of 14C uptake confirm that anomalous high primary production occurs

at stations in the high velocity periphery of warm slope eddies sampled west of the NEGOM field

area. Gonzalez-Rodas (1999), who summarized primary productivity measurements that he made

on six LATEX cruises, reported two prominent hot spots in deepwater primary production ( > 2.5

g C m-2 d-1) on these six cruises. In August 1993 and again in November 1994, productivity near

27.5°N and 92°W was 10-fold or more higher than typical for the oceanic Gulf over the upper

continental slope. In summer 1993, the northern edge of Loop Current Eddy (LCE)-W was

interacting with the continental margin between 91° and 93°W; the locally high shear there

apparently fueled a region of anomalously high deepwater primary production. This eddy had a

diameter of some 250 km; at the location where the productivity was measured, the geopotential

anomaly was about +20 cm and current speeds were about 60 cm sec -1 (see Table 5 in GonzalezRodas 1999). In fall 1994, the northern edge of another anticyclone, LCE-Y, was interacting with

the continental margin again between 91° and 92 °W. This eddy was even larger in diameter (320

km) and presented a geopotential anomaly of +36 cm (from Table 5 in Gonzalez-Rodas 1999).

The deepwater Gulf of Mexico has been considered a biologically impoverished ocean in terms of

zooplankton, ichthyoplankton, and micronekton as well as phytoplankton, since on average the

standing stocks of plankton and fish seaward of the shelf break are lower than those found in

temperate and higher latitude regions. Previous reviewers have reinforced this perception (e.g.

Hopkins, writing in Iverson and Hopkins 1981, and in Vargo and Hopkins 1990). 

However, relegating secondary production in the GOM to oligotrophic status is an

oversimplification, because standing stock levels are not uniformly low but are instead punctuated

by spatial and temporal variation greater than that found in most other oligotrophic oceans. This

variability may be manifested as spatial and temporal “hot spots” of increased biomass. For

example, Khromov (1969a, 1969b) reported that while zooplankton standing stocks in the tropical

oligotrophic Caribbean Sea were almost always low and did not exceed 10 ml wet displacement

volume (WDV) per 100 m3

 in waters offshore of the shelf/slope break, GOM stocks exhibited more

seasonal, interannual, and spatial variability, with biomass levels as high as 35 ml WDV per 100 m3

(range < 5 - 35). Hopkins and Lancraft (1984), who compared integrated wet weight biomass of

zooplankton and micronekton in three tropical-subtropical oceans (Caribbean Sea near Puerto Rico,

Gulf of Mexico at 27°N x 86°W, and Pacific Ocean near Hawaii), found that GOM levels were the

highest in both categories (if large medusae were included in the micronekton total). Although more

recent studies of GOM biomass do generally reveal low standing stocks, reported estimates can vary
46

by a factor of 10 or more from the minima within a given study (Biggs et al. 1988; Richards et al.

1993; Wormuth et al. 2000). 

Finally, the deepwater ichthyoplankton community includes the larvae of commercially important

species such as tuna, mackerel, billfishes, and swordfishes (Vargo and Hopkins 1990), and

commercial fisheries do exist for the adults in the Gulf of Mexico. The deepwater GOM is also

habitat for substantial populations of marine mammals, sea turtles, and seabirds (Davis et al. 2000).

The presence of sizeable populations of such apex predators in the deepwater GOM implies a

reliable supply of lower trophic level prey resources (Biggs et al. 1988) and suggests that underlying

physical processes allow “oases” of biological productivity to develop in the mostly oligotrophic

deepwater GOM.

We suggest that these deepwater “hot spots” of zooplankton, micronekton, and ichthyoplankton

occur when primary production is enhanced by coarse to mesoscale eddies, as described above.

Lamkin (1997) showed that larval fish were associated with the Loop Current and periphery regions

of companion cyclones and anticyclones, and recently Wormuth et al. (2000) documented that

deepwater cyclones had locally higher standing stocks of zooplankton and micronekton than did

LCEs. These features may not be revealed by coarse sampling or averaging of measurements across

large temporal and spatial scales. However, combining alternative techniques such as acoustical and

optical techniques with traditional direct sampling with nets can provide zooplankton-micronektonichthyoplankton data with sufficient resolution to examine temporal and spatial trends in a manner

impossible with net sampling at single discrete locations. This capacity is also useful given the

growing amount of coarse to mesoscale oceanographic data available from satellites. A combination

of net, acoustical, and optical techniques appears to be the optimum way to study variations in

zooplankton and micronekton standing stock biomass, and such a unification of technologies will

lead to better understanding of the interaction of hydrography and ecology in the deepwater Gulf

of Mexico. 

In summary, expeditions in the 1960s and 1970s are the basis for the general paradigm that standing

stocks and productivity of phytoplankton are both low (< 0.1 mg chl m-3; < 150 mg C m-2 d-1)

seaward of the shelf-slope break in the Gulf of Mexico. The present review supports this description

of the mean state (stable state) but also shows “hot spots” in primary production (> 2 g C m-2 d-1)

occur when/where nutrient availability is locally enhanced seaward of the shelf-slope break (Biggs

and Ressler, in review). Fundamental nutrients-phytoplankton-zooplankton (NPZ) food chain theory

(summarized by Lalli and Parsons 1997) forecasts that enhanced primary production, if sustained,

will support increased zooplankton, ichthyoplankton, and micronekton production. Available

evidence from the GOM is that deepwater “hot spots” that are temporally persistent have higher

stocks of zooplankton and micronekton, even when the specific locations of such “oases” are

spatially variable along the continental margin. Continued study and assessment of plankton and

micronekton within these “hot spots” is warranted, since these organisms ultimately serve as food

for higher trophic level predators, including commercially important fish species, federally protected

marine mammals, and seabirds.
47

REFERENCES

Biggs, D.C., and P.H. Ressler (in review). Distribution and abundance of phytoplankton,

zooplankton, ichthyoplankton, and micronekton in the deepwater Gulf of Mexico. Submitted to

Gulf Mex. Sci.

Biggs, D. C., A. C. Vastano, R. A. Ossinger, A. G. Zurita, and A. P. Franco. 1988. Multidisciplinary

study of warm and cold-core rings in the Gulf of Mexico, Memorias Sociedad de Ciencias

Naturales La Salle, 48(3): 11-31.

Björnberg, T. K. S. 1971. Distribution of plankton relative to the general circulation system in the

area of the Caribbean Sea and adjacent regions. In Symposium on Investigations and Resources

of the Caribbean Sea and Adjacent Regions, Willemstad, Curaçao, Netherlands Antilles, 18-26

November 1968, pp. 343-356, United Nations Educational, Scientific, and Cultural Organization

(UNESCO), Paris, France.

Davis, R. W., W. E. Evans, and B. Würsig, eds. 2000. Cetaceans, Sea Turtles and Seabirds in the

Northern Gulf of Mexico: Distribution, Abundance and Habitat Associations. Volume II:

Technical Report. Prepared by Texas A&M University at Galveston and the National Marine

Fisheries Service. U.S. Department of the Interior, Geological Survey, Biological Resources

Division, USGS/BRD/CR-1999-0006 and Minerals Management Service, Gulf of Mexico

Region, New Orleans, LA. OCS Study MMS 2000-003 346 pp.

El-Sayed, S.Z. 1972. Primary productivity and standing crop of phytoplankton. pp 8-13. In V.C.

Bushnell, ed. Chemistry, Primary Productivity, and Benthic Algae of the Gulf of Mexico.

American Geographical Society, New York.

Gonzalez-Rodas, G.E. 1999. Physical Forcing of Primary Productivity in the Northwestern Gulf of

Mexico. Ph.D. dissertation, Department of Oceanography, Texas A&M University, College

Station, TX. 149 pp.

Hopkins, T. L., and T. M. Lancraft. 1984. The composition and standing stock of mesopelagic

micronekton at 27oN 86oW in the eastern Gulf of Mexico, Contrib. In Mar. Sci., 27: 143-158.

Iverson, R. L. and T. L. Hopkins. 1981. A Summary of Knowledge of Plankton Production in the

Gulf of Mexico: Recent Phytoplankton and Zooplankton Research. In Proceedings of a

Symposium on Environmental Research Needs in the Gulf of Mexico (GOMEX), Key Biscayne,

Florida, 30 September – 5 October 1979, vol. IIA, pp. 147-211, Atlantic Oceanographic and

Meteorological Laboratories, Miami, FL.

Khromov, N. S. 1969a. Distribution of plankton in the Gulf of Mexico and some aspects of its

seasonal dynamics, pp 36-55. In Soviet-Cuban Fishery Research (A. S. Bogdanov, ed.).

Translated from Russian by Israel Program for Scientific Translation, Jerusalem, for the U.S.

Department of the Interior and the National Science Foundation (TT 69-59016), U.S.
48

Department of Commerce, Clearinghouse for Federal Scientific & Technical Information,

Springfield, VA.

Khromov, N. S. 1969b. Distribution of plankton in the Caribbean Sea, pp 57-61. In Soviet-Cuban

Fishery Research (A. S. Bogdanov, ed.). Translated from Russian by Israel Program for

Scientific Translation, Jerusalem, for the U.S. Department of the Interior and the National

Science Foundation (TT 69-59016), U.S. Department of Commerce, Clearinghouse for Federal

Scientific & Technical Information, Springfield, VA.

Koblenz-Mishke, O.J., V.K. Volkovinsky, and J.C. Kabanova. 1970. Plankton primary production

of the world ocean. In W.W. Wooster, ed. Scientific Exploration of the South Pacific, National

Academy of Science, Washington, D.C., pp. 183-193.

Lalli, C.M., and T.R. Parsons. 1997. Biological Oceanography: An Introduction. Second edition,

Butterworth-Heinemann, UK. 314 pages.

Lamkin, J. 1997. The Loop Current and the abundance of Cubiceps pauciradiatus (Pisces:

Nomeidae) in the Gulf of Mexico: evidence for physical and biological interaction, Fish. Bull.,

95: 250-266.

Lohrenz, S.A., D.A. Wiesenburg, R.A. Arnone, and X. Chen. 1999. What controls primary

production in the Gulf of Mexico? pp. 151-170. In The Gulf of Mexico Large Marine Ecosystem

(H. Kumpf, K. Steidinger, and K. Sherman, eds.). Blackwell Science, Inc.

Richards, W.J., M.F. McGowan, T. Leming, J.T. Lamkin, and S. Kelley. 1993. Larval fish

assemblages at the Loop Current boundary in the Gulf of Mexico, Bull. Mar. Sci., 53: 475-537.

Smith, S. and J.T. Hollibaugh. 1993. Coastal metabolism and the oceanic organic carbon balance.

Rev. Geophys. 31: 75-89.

Vargo, G. A. and T. L. Hopkins. 1990. Chapter 6: Plankton. In Synthesis of Available Biological,

Geological, Chemical, Socioeconomic, and Cultural Resource Information for the South Florida

Area. Report OCS/MMS90/0019 to the Minerals Management Service by Continental Shelf

Associates (PB90-266685), pp. 195-230, National Technical Information Service (NTIS),

Springfield, VA.

Wiseman, W.J. and W. Sturges. 1999. Physical oceanography of the Gulf of Mexico: Processes that

regulate its biology. Pp. 77-92. In The Gulf of Mexico Large Marine Ecosystem (H. Kumpf, K.

Steidinger, and K. Sherman, eds.). Blackwell Science, Inc.

Wormuth, J.H., P.H. Ressler, R.B. Cady, and L.H. Harris. 2000. Zooplankton and micronekton in

cyclones and anticyclones in the northeast Gulf of Mexico. Gulf Mex. Sci. 18(1): 23-34.
49

Dr. Douglas Biggs and Mr. Patrick Ressler are both in the Department of Oceanography at Texas

A&M University. Professor Biggs received the Ph.D. in oceanography from the MIT-WHOI Joint

Program in Oceanography in 1976 and since 1987 he has been PI or co-PI for various MMSsponsored field programs in the Gulf of Mexico, including SOOP, GulfCet II, NEGOM, and

DGoMB. Mr. Ressler received the B.A. summa cum laude in biology from Bucknell University in

1996 and is making acoustic estimates of zooplankton and micronekton stocks in the Gulf of Mexico

with an ADCP as part of his Ph.D. dissertation research at TAMU.
50

DEEPWATER PETROLEUM STRUCTURES AS FISH AGGREGATING DEVICES:

AN IN-PROGRESS PROJECT REPORT

Randy E. Edwards

Kenneth J. Sulak

Doug Weaver

U.S. Geological Survey

Biological Resources Division

Florida Caribbean Science Center

ABSTRACT

Fish aggregating devices (FADs) have recently been utilized around the world and have been shown

to have large effects on fish and fisheries, particularly tunas and tuna fisheries. Other pelagic fish

species also are aggregated and impacted by FADs. Fishery problems and potential problems have

been identified with FADs, primarily increased relative catch of smaller/younger fish and potential

changes in distribution and migration. FADs also can have positive effects, primarily making fishing

more effective and efficient. Important and valuable commercial and recreational fisheries have been

established by deployment of FADs. The offshore oil and gas industry in the Gulf of Mexico (GOM)

recently has been expanding into deep waters of the outer continental shelf and slope where petroleum structures have the potential to act as FADs. A project is being conducted by the U.S.

Geological Survey – Biological Resources Division (USGS-BRD) in collaboration with the Minerals

Management Service (MMS) to assess and anticipate potential impacts of increased numbers of

deepwater petroleum structures on highly migratory fish species in the GOM. Preliminary review

of scientific literature on FADs suggests that processes and factors involved in fish aggregation by

objects are complex and that the current scientific understanding of FADs is insufficient for prediction of the potential fish aggregating impacts of deepwater petroleum structures in the GOM. Although present understanding of FADs suggests that deepwater structures are likely to have measurable impacts, direct research and study may be needed to assess fully and to estimate such impacts.

INTRODUCTION TO THE IN-PROGRESS PROJECT

The project described below is designed to assist the MMS in assessing the degree to which

petroleum structures in deep waters of the northern GOM may function as FADs and thus may result

in biological impacts on highly migratory species (HMS) and other pelagic fish species in the Gulf.

The project was described at the Gulf of Mexico Fish and Fisheries: Bringing Together New and

Recent Research workshop to disseminate information about project’s existence and its goals, to

contact other GOM fishery scientists and managers, and to involve, in our ongoing work, those with

pertinent information and experience.

WHAT ARE FADs?

The term fish aggregating device (FAD) is usually applied to two categories of floating objects that

attract and aggregate fish. The first is comprised of floating objects that are moored or anchored,
51

while the second consists of those objects that are free drifting. The functioning of the two

categories of FADs, in terms of aggregating fish, is similar, but may be different because of many

factors by which the two types of FADs are inherently different. A complete discussion of FADs

is beyond the scope of this paper. In this paper, we focus on deepwater FADs and associated pelagic

fish species, although FADs in coastal waters may function differently and attract different species.

The following summary is presented to provide context and perspective for our current project. 

The use by fishermen of objects to attract and aggregate fish probably extends back to ancient times.

The earliest FADs were probably anchored, floating rafts of bamboo, locally called payaws, that

were traditionally deployed by artisanal fishermen in the Philippine Islands in the early 1900s

(Anderson and Gates 1996). Payaws were commercialized around 1975, when purse seiners began

to set nets around them (Dickson 1999). The use of anchored FADs similar to payaws soon spread

throughout the region and around the world. Recent moored FADs are constructed of man-made

materials and are often highly engineered. They have been used particularly in oceanic island

nations, where they can be deployed in depths shallow enough for mooring, yet be close to deep

pelagic environments. In places like Hawaii, where there currently are 52 FADs moored at locations

around the island state, FADs are used by both commercial and recreational fishermen (Higashi

1994; Holland 1999). Moored FADS are also widely used in the Mediterranean (D’Anna,

Badalamenti and Riggio 1999). With the exception of experimental midwater FADs studied in

coastal waters (Klima and Wickham 1971; Whickham and Russell 1974) and experimental moored

FADs on the NW coast of Cuba, which were successful in aggregating skipjack tuna (Martin 1999),

the GOM is probably the only large area in which deepwater FADs have not been purposely

utilized.

The other category of FADs, free-floating objects, has become exceedingly important over the last

decade. Tuna fisheries, particularly purse seine fisheries, like those in the eastern tropical Pacific,

have taken advantage of the propensity of tunas to aggregate around floating objects. Originally,

such fisheries caught tunas from around natural objects like logs or even dead marine mammals.

In the Pacific, a large part of the purse seine landings were taken by setting on pods of dolphins,

to which tunas, for still unknown reasons, are attracted and aggregate. Because of concerns about

mortality of dolphins and the advent of so called “dolphin-safe” tuna, the eastern Pacific tuna fleet

shifted away from setting on dolphins and began to concentrate on natural “logs” starting around

1992. At the same time, fishermen began to deploy artificial objects in the open ocean in order to

aggregate tunas (Lennert-Cody, Garcia and Hall 1999). Recently, man-made drifting FADs

technology has become very sophisticated, and some FADs even have radio transmitters, echo

sounders (for detecting schools of tuna) computers (for storing echo sounding data and controlling

radio transmissions to fishing vessels), underwater lights, and satellite tracking (Fonteneau et al.

1999).

The use of FADs (natural and man-made) has accelerated to the point that in 1998, 55% of the

eastern Pacific tuna purse seine effort was expended in setting on schools around FADs or logs

(Tillman 1999). Exact catch statistics are difficult to obtain, but because catch success is much

higher around floating objects, it is clear than the largest part of the eastern Pacific tuna catch

presently comes from around FADs.
52

1

 Euorpean Union press release, 20 October 1999. http://europa.eu.int/ com/ fisheries/news_corner/press/info65-en.htm.

2

Gary Matlock, NOAA, National Marine Fisheries Service, U.S. House of Representatives, House Resources

Subcommittee testimony, 15 July 1999.

FISH SPECIES ASSOCIATED WITH FADS

The fish species that are attracted and aggregated by FADs in deepwater environments are primarily

pelagic species. They can be further subdivided into highly migratory species (HMS) and coastal

pelagic species.

The term HMS is used by the National Marine Fisheries Service to include tunas, marlins, swordfish

and certain pelagic sharks (NMFS 1999). The most important group of fish associated with FADs

are the tunas, particularly skipjack (Euthynnus pelamis), yellowfin (Thunnus albacares), and to a

lesser extent, bigeye (Thunnus obesus) tuna (Freon and Misund 1999). Marlins are considered to

associated with FADs (Hall et al. 1999), and in places like Hawaii and Australia, moored FADs are

favored areas for recreational billfishing. Swordfish, however, have not been reported to be

aggregated by FADs. Several species of sharks have been noted to associate with FADs. Other

oceanic, migratory species (not included in the NMFS HMS definition) such as dolphin

(Coryphaena hippurus) (Leonart et al. 1999) and wahoo (Acanthocybium solandri) (Hall et al. 1999)

are known to associate with FADs.

There are many other species of fish that associate with FADs that can be classified as coastal

pelagics—species that are usually found in coastal and continental shelf environments. They include

several carangids, particularly scads (Decapterus sp.) and amberjacks (Seriola sp.) (D’Anna,

Badalamenti, and Riggio 2000; Deudero et al. 2000). Most of these species or groups and others

(e.g., cobia, Rachycentron canadium; king mackerel, Scomberomorus cavalla) are abundant in the

GOM and may be affected by FADs (Franks 1999). 

PROBLEMS WITH FADS 

Unfortunately, several issues or potential problems are connected with FADs. The first is that tunas

caught from around FADs tend to be much younger and smaller than those caught from freeswimming schools. This is particularly true for yellowfin tuna. Polovina (1991) was one of the first

to point out this problem. He noted that the Philippines tuna fisheries around payaws resulted in an

over 20 times increase in landings, but that over 90% of the tunas caught around those FADs are less

than one year old. He pointed out that reductions in size at entry result in very substantial reductions

in yield estimates made from standard yield models. This problem is well recognized today.

Fonteneau et al. (1999) recently concluded that the current massive use of FADs in worldwide tuna

fisheries is “probably an unsafe fishing mode which needs to be limited to reasonable biological

levels.” In the European Union – Japan High Level Fisheries Consultations, 14-15 October 1999,

the parties expressed their differences in opinions about the use of FADs and discussed developing

a joint research program aimed at improving selectivity of FADs.1

 The International Commission

for the Conservation of Atlantic Tunas (ICCAT), because of concern about the high take of

juveniles, has issued recommendations for restrictions on the use of FADs.2
53

There are other potential problems with FADs. One concern is whether FADs might disrupt normal

movement and aggregation patterns (Kleiber and Hampton 1994). How such changes might impact

stocks, through effects such as changes in spawning area and resultant effects on larval survival and

recruitment are largely speculative at the present time. A related potential general problem is that

of increased catchability of fish associated with FADs and the resultant impact on population

dynamics and stock status. Also, fishing around FADs may result in increased bycatch, because of

simultaneous aggregation of non-target species (Hall et al. 1999). Conflict between user groups

(e.g., between hook-and-line fishermen and purse seiners) is a common, practical problem (Anon.

1982).

POTENTIAL POSITIVE EFFECTS OF FADS

Some of the very same issues that, under some circumstances, might be considered to be problems

can be viewed positively under different circumstances. The main advantage of FADs is that they

do aggregate fish and make them easier to catch than if they were dispersed widely in an oceanic

environment. Similarly, the same factors that result in aggregation of species that may be considered

to be unwanted bycatch in commercial fisheries (e.g., billfishes), under some circumstances can be

viewed by recreational fishermen as highly positive, because they enhance opportunities for offshore

gamefishing.

FADs, including GOM petroleum structures, might even be able to contribute to reduction of the

important problem of commercial bycatch of billfish and undersize swordfish. This could take place

through longline fisheries shifting to fishing around FADs, where tunas are more concentrated

relative to billfish and juvenile swordfish. Also, they may shift their fishing techniques to utilization

of gears (e.g., vertical longlines; or shorter, more-frequently hauled horizontal longlines) that may

significantly reduce bycatch and bycatch mortality (less mortality when fish are on the line for

shorter periods (Berkeley and Edwards 1998)). A situation has been described for the

Mediterranean, where seasonal shift to fishing for dolphin (Coryphaena hippurus) around FADs

could reduce longline catch of juvenile swordfish (Cannizzaro et al. 1999). 

Presence of FADs can make commercial and recreational fishing much more dependable, and often

more economical, because less time and fuel is expended searching for fish, and because smaller

vessels can be used to fish around FADs located close to shore. It is for those kinds of reasons that

moored FADs have been deployed so widely around the world. 

DEEPWATER PETROLEUM ACTIVITIES IN THE GULF OF MEXICO

A major development in offshore petroleum exploration and production in the GOM has occurred

recently. It is detailed it in a recent MMS publication titled Deepwater Gulf of Mexico: America’s

Emerging Frontier (Baud et al. 2000). The following discussion is summarized from that

publication.

MMS defines “deepwater” as water deeper than 1,000 ft. Over the latter part of the last decade, three

factors have come together to result in expansion of petroleum industry activities into deep water:
54

1. discovery that deepwater wells often had enormously high flow rates and, therefore, great

economic return;

2. technological advances, including development of new types of structures that are able to

be used in deeper water, and the use of subsea well completions in deeper water; and 

3. economic incentive arising from the passage of the Deepwater Royalty Relief Act of 1995

in the U.S. Congress.

Deepwater petroleum production has expanded to the point that by 1999, deepwater production

exceeded that of all the shallow water. Because of this expansion, the number of permanent,

deepwater structures in the GOM has currently grown to 27 platforms in 1,000 ft or deeper, with

another 24 platforms in depths between 500 and 1,000 ft. The number of deepwater platforms is

increasing rapidly. 

In view of the large number of deepwater structures of various types that are expected to be

deployed in the next few years, MMS convened the Workshop on Environmental Issues Surrounding

Deepwater Oil and Gas Development (Carney 1997). One of the results from that workshop was that

MMS wisely identified the potential for deepwater petroleum structures to function as FADs. 

PROJECT DESCRIPTION

The U.S. Geological Survey, Biological Resources Division accepted the task of assisting MMS in

assessing this potential situation in which deepwater structures might act as FADs. The project is

in progress and is described briefly below.

The major elements of the project include:

1. survey of existing literature and information on FADs and related topics,

2. synthesis of FADs literature and available information,

3. survey of existing literature on HMS and other important pelagic fish species that potentially

could be impacted by FADs in the GOM,

4 synthesis of HMS literature and available information, and 

5. synthesis of FADs and HMS best available information into conclusions and

recommendations.

We are conducting this work by the following main approaches:

1. comprehensive search of existing literature (published and gray, including international and

foreign language references) on FADs,

2. development of a computerized, searchable, bibliographic data base, including annotations

and key words created directly for the GOM FADs issue,

3. comprehensive search of existing literature on GOM HMS and other potentially impacted

pelagic fish species, and

4. development of a HMS bibliographic data base similar to that for FADs.
55

Additionally, we have organized a technical session and expert panel discussion (to be held at the

22-25 February 2001 Midyear Meeting of the Southern Division of the American Fisheries Society

in Jacksonville, FL) on deepwater structures and FADs. The goals of the session and panel

discussion are to obtain new or unpublished information, bring in researchers with expertise in

FADs from other regions, integrate appropriate fishery management agencies into the process, and

to develop a broad-based consensus of expert opinion about the potential importance of the issue

and about the needs for additional information and research.

PRELIMINARY FINDINGS – FADS

We have found that there is a very large and diffuse body of literature and information on FADs.

Desurmont (1996) listed 134 references in a bibliography of FADs-related literature. The literature

has grown recently, and currently we have over 500 technical references in our bibliographic

database. We also have found several hundred secondary references that are of some, but not first

order, pertinence to FADs, or which have other biological/environmental issues pertinent to

deepwater structures as their subject. The secondary references will be collected opportunistically,

but exhaustive collection and compilation is beyond the scope of this project. 

Despite this large body of literature, a good scientific understanding of why fish aggregate around

objects has yet to be developed. It seems that the literature has so far only begun to dissect the

problem, and that there has been little progress in synthesizing and understanding the phenomenon

of fish aggregation around FADs. This is not surprising, because this is a very complex issue that

is logistically and technically difficult to study.

Kingsford (1999) recently reviewed and listed 19 factors that may affect the affinity of fish for

FADs, and he suggested that they could be the basis of testable hypotheses. We added 13 additional

(20-32) factors. The factors are:

 1. Availability of food

 2. Availability of juvenile fish

 3. Presence of conspecifics (spawning, cannibalism, density effects)

 4. Presence of other species (competition, predation, potential prey)

 5. Availability and nature of shelter (FAD design)

 6. Substrate for undergoing behavioral change

 7. Day versus night

 8. Predation (by residents and vagrants)

 9. Intraspecific and interspecific competition

10. Larval/juvenile drift to “suitable” areas

11. Disturbance, natural (e.g., storms) and anthropogenic (e.g., boat noise)

12. Proximity to shore

13. Location and time (due to larval supply and movements of fishes)

14. Water quality and visibility

15. Design of FADs

16. Size of FADs. (For floating FADs, there seems to be a complicated relationship for medium

size objects (1-6 m max dimension), there seems to be little or no relationship between fish
56

density and size, while smaller and larger objects are less attractive (Hall et al. 1992;

Akishige et al. 1996).)

17. Cluster of FADs

18. Soak time of FADs

19. Combination of pelagic and benthic FADs

20. Visibility of structure (visual reference)

21. Shadow and other natural lighting effects

22. Artificial lighting

23. Movement of moored FADs

24. Oceanographic conditions (currents, and vertical structure of T/S/DO, Langmuir circulation,

potential for upwelling due to structure)

25. Hydrodynamics (vorticity and current fields induced by structure)

26. Visual appearance of FADs (color/patterns/reflectivity)

27. Spatial distribution of FADs (density/nearest neighbor/orientation relative to bathymetry)

28. Anchored versus drifting FADs

29. Species behavior and habitat utilization patterns [intranatants (<0.5 m away), extranatants

(0.5-2.0 m), circumantants (up to 5 –7 nmi) (Fedorayako 1992)

30. Movement of drifting FADs (current or wind)

31. Marine mammals (especially dolphins) presence (association with objects developed through

previously developed association with marine mammals)

32. Sea state (can affect fish’s ability to detect objects by visual or auditory mechanisms, can

affect other factors such as local availability of prey)

It is clear that this list is in no way exhaustive. Very few of these many factors have ever been

rigorously studied.

Similarly, Freon and Misund (1999) reviewed and listed the major hypotheses explaining the

association between fish and floating objects. They included:

1. Concentration of food supply hypothesis (Kojima 1956).

2. Schooling companion hypothesis (Hunter and Mitchell 1967).

3. Substitute environment hypothesis (Hunter and Mitchell 1967).

4. Cleaning station hypothesis (Gooding and Magnuson 1967).

5. Shelter from predator hypothesis (Suyehiro 1952; Soemarto 1960; Gooding and Magnuson

1967).

6. Spatial reference hypothesis (Klima and Wickham 1971).

7. Comfortability stipulation hypothesis (Batalyants 1992).

8. Generic-log hypothesis (and related hypotheses) (Hall 1992).

9. Meeting point hypothesis (Soria and Dagorn 1992; Dagorn 1994, Freon and Misund 1999).

However, after more than three decades of work on this issue, there still is little or no agreement as

to which hypotheses are valid and as to which of them may apply jointly under different

circumstances. Perhaps only one of these has been generally discounted. The concentration of food

hypothesis has been found to be unlikely to explain aggregation of fish like yellowfin tuna around

FADs. Buckley and Miller (1994) found that the diets of FADs associated yellowfin tuna showed
57

little differences betweens non-FADs yellowfin and pre-FADs yellowfin, and Holland, Brill and

Chang (1990) found that movements of yellowfin around FADs indicated that they fed away from

the FADs. Additionally, hydroacoustic surveys have found that the biomass of prey-size fish is

almost always insufficient to support the biomass of predator-size fish normally associated with

FADs (Josse, Bach and Dagorn 1998). Other than the food supply hypothesis being discounted, the

reasons for fish association with FADs remains very uncertain. Factors involved in attractiveness

of floating objects have not been determined. Hall et al. (1992) concluded that as long as objects

were at least one meter in minimum dimension they could not detect significant differences in the

number of fish aggregated to the object. In view of this uncertainty, it seems unlikely that these

factors, hypotheses and the general state of understanding of fish-FADs interactions are adequate

to assess or predict the degree to which various types of deepwater petroleum structures are likely

to act as FADs for various pelagic fish species in the GOM. 

PRELIMINARY FINDINGS – GULF OF MEXICO HMS

Yellowfin tuna are abundant in the GOM. An extensive Japanese longline fishery operated in the

GOM between 1963 and 1981, before leaving the GOM due to severe reductions in CPUE (Wilson

1988). These declines may have been attributable to factors other than the stock being fished down,

such as shift in migratory path, poor year classes, or other unknown factors (Wilson 1998). In any

event, the declines suggest that yellowfin tuna stocks in the GOM can be substantially impacted.

Recently, U.S. longliners have continued to harvest yellowfin tuna from the Gulf, with landings in

1998 totaling 3,784,786 lb with dockside value of $9,263,471 (Table 1). Yellowfin tuna accounted

for 93% of the catch (lb) and 94% of the value of the total tuna catch (including wahoo) from the

GOM in 1998. For all of these reasons, yellowfin tuna should be considered the primary species in

any considerations of FADs effects of deepwater structures.

Surprisingly, GOM skipjack tuna landings are very small, amounting to only slightly over one

thousand pounds landed on the Florida Gulf coast. However, Sakagawa (1986) suggested that the

GOM appeared to be a promising area for development of new skipjack tuna fisheries. Experimental

FADs deployed on the NW coast of Cuba have been found to be effective in aggregated harvestable

concentrations of skipjack, that were caught on pole and line (Martin 1999). Therefore, the extent

to which skipjack tuna are likely to be aggregated and affected by GOM deepwater petroleum

structures is an open question.

The GOM is the only known spawning area for the western Atlantic stock of bluefin tuna (Thunnus

thynnus) (Mather, Mason and Jones 1995). Because its stock status may be precariously low (Safina

1993), even small effects on bluefin tuna could be important. Although bluefin tunas have not been

reported to highly attracted by FADs in other parts of the world, it may be notable that in the western

Atlantic, there is a population of bluefin off of Cape Hatteras, N.C. that seem to aggregate near

wrecks, where they are caught in large numbers (most released) by recreational anglers. The

question as to whether bluefin tuna might be attracted to GOM deepwater structures, and hence

might change migration, and spawning patterns is speculative but is worth consideration.

Additionally, any aggregation could result in increased bycatch of bluefin by fisheries targeting

other species.
58

Table 2.2 Landings of tunas and wahoo from the Gulf of Mexico in 1998 (Source: NMFS).

 Florida Louisiana Texas

 “Species” Pounds Value Price Pounds Value Price Pounds Value Price

Tuna,

Albacore

NR 5,838 $ 3,079 $0.53 NR

Tuna,

Bluefin

2,871 $7,316 $2.55 26,868 $113,605 $ 4.23 NR

Tuna, Little

Tunny

119,169 $35,829 $0.30 108,221 $39,241 $ 0.36 NR

Tuna,

Yellowfin

523,708 $1,233,885 $2.36 2,958,087 $7,338,444 $2.48 302,991 $691,142 $2.28

Tunas,

Misc.

 12,627 $23,555 $1.87

Tuna,

Bigeye

9,677 $24,569 $2.54 19,634 $71,281 $3.63 NR

Tuna,

Blackfin

 27,701 $27,015 $0.98 46,011 $22,425 $0.49 6,424 $5,864 $0.91

Wahoo 37,554 $67,699 $1.80 137,983 $143,740 $1.04 NR

NR – None Reported.

Given the unresolved status of FADs science, and given the fact that there are already 27 deepwater

structures in the GOM and a total of 51 structures in depths over 500 ft, one reasonable conclusion

may be that direct study around existing and future structures is the best and perhaps only way to

assess the degree to which deepwater structures will affect fish. Many methods and approaches have

been used to study fish association with FADs, and most could be adapted to GOM deepwater

structures. Previous studies can be categorized (with examples of each type of study) as follows:

1. Tagging: Hunter and Mitchell (1968); Itano and Holland (1999).

2. Hydroacoustic survey: Stanley and Wilson (1996); Bach et al. (1998); Josse, Dagorn and

Bertrand (1999); Josse, Bertrand and Dagorn (1999).

3. Telemetry, acoustic tracking: Holland, Brill and Chang (1990): Klimley and Holloway

(1996); Marsac, Cayre and Conand (1996); Marsac and Cayre (1998); Brill et al. (1999).

4. Telemetry, network of automated acoustic receivers: Klimley and Holloway (1996).

5. Fishery dependent methods, including recreational catch surveys: Love and Westphal

(1990); Stanley and Wilson (1990 &1991); Cillaurren (1994).

6. Fishery independent hook-and-line fishing CPUE: Friedlander, Beets, and Tobias (1994).

7. Experimental net fishing: Massuti, Morales-Nin and Deudero (1999).

8. Modeling: Hilborn and Medley (1989); Kleiber and Hampton (1994); Daghorn, Bach and

Josse (1997); Sibert and Holland (1999).
59

Kingsford (1999) makes a strong case for sampling before and after to determine the impact of

FADs. This may be something to consider in view of the potential extensive and intensive

deployment of deepwater oil and gas structures in the GOM. In a few years, once petroleum

structures are abundant throughout deepwater areas of the northern Gulf, it may be too late to

directly estimate their effects, because conditions prior to introduction of deepwater structures will

not be able to be estimated.

PRELIMINARY CONCLUSIONS

Based on existing scientific knowledge of FADs and fish attraction, it is not reasonable to discount

the possibility that deployment of large numbers of petroleum structures in the GOM will have

significant and substantial impacts on HMS. Conversely, the state of knowledge is not adequate to

determine or predict that large effects will in fact occur, to estimate the extent to which they will

occur, or to predict what species will be affected. However, the existing knowledge does clearly

show that FADs can have large effects on fish and fisheries.

With this in mind, and the growing number of deepwater structures in the GOM, the preliminary

conclusion is that the situation will probably have to be assessed by direct study of existing and

future structures. There are several research approaches that have been used productively to study

FADs and that could be applied to deepwater oil and gas structures. It is likely that adequate

understanding will require a combination of several of these approaches.

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63(3-4):81-190.

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63

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eds. International Symposium on Tuna Fishing and Fish Aggregating Devices Book of

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64

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65

*

This abstract is provided although the presentation was canceled.

HABITAT USE OF SHELF-EDGE TOPOGRAPHIC HIGHS IN THE NORTHWESTERN

GULF OF MEXICO BY SHARKS AND RAYS (SUBCLASS ELASMOBRANCHII)*

Jeff Childs

Center for Coastal Studies

Texas A&M University-Corpus Christi

ABSTRACT

The continental shelf of the northwestern Gulf of Mexico includes an array of submerged hard-banks

and reefs in addition to a great concentration of offshore petroleum platforms that provide

significant vertical and structural relief in an otherwise level landscape, and are defined as

“topographic highs”. This study investigates the habitat use of shelf-edge topographic highs by

wide-ranging sharks and rays occurring in the northwestern Gulf of Mexico. Three topographic

highs (East and West Flower Garden Banks and the High Island A-389A offshore production

platform) located near the shelf-edge (200 m isobath) were visited from July 1992 through April

1998. Underwater surveys on SCUBA were conducted to gather information on the species

composition, abundance, life history stages, sexes, and social groups of elasmobranchs occurring

at the study sites. Thirteen species were identified that include Ginglymostoma cirratum (nurse

shark), Rhincodon typus (whale shark), Galeocerdo cuvier (tiger shark), Carcharhinus falciformis

(silky shark), Carcharhinus obscurus (dusky shark), Carcharhinus perezi (Caribbean reef shark),

Carcharhinus plumbeus (sandbar shark), Sphyrna lewini (scalloped hammerhead), Dasyatis

americana (southern stingray), Aetobatis narinari (spotted eagle ray), Mobula hypostoma (lesser

devil ray), Mobula tarapacana (sicklefin devil ray), and Manta birostris (manta ray). These species

form three assemblages (winter, summer, and resident) at the Flower Garden Banks. Carcharhinus

falciformis was the only species found utilizing the High Island platform throughout the year. Data

gathered in this study show the Flower Garden Banks function as nursery areas, adult feeding areas,

and possibly as a mating area to these elasmobranch species, while the High Island platform

functions as a secondary nursery area to C. falciformis. Seasonal movements relative to other habitat

areas in the region are also modeled for the sharks and rays observed at shelf-edge topographic

highs.
66

*

This abstract is provided although the presentation was canceled.

LIFE ALONG THE EDGE: THE WHALE SHARK (RHINCODON TYPUS)

IN THE NORTHERN GULF OF MEXICO*

Jeff Childs

Center for Coastal Studies

Texas A&M University-Corpus Christi

Carolyn M. Burks

Keith D. Mullin

Southeast Fisheries Science Center

National Marine Fisheries Service

NOAA Mississippi Laboratories

John D. Hewitt IV

Aquarium of the Americas

New Orleans

ABSTRACT

The whale shark (Rhincodon typus) occurs in the northern Gulf of Mexico though little is known

regarding the behavior and ecology of the largest living fish species. Whale shark sightings amassed

in three independent surveys conducted from the air, sea surface, and underwater, were compiled

with historic sightings and analyzed using geographic information system technology (ArcView).

Sightings data show whale sharks utilize neritic (< 200 m isobath) and oceanic (> 200 m isobath)

waters of the northern Gulf during warmer months (June thru November), however, during colder

months (December thru May) whale sharks chiefly utilize oceanic waters. The majority of sightings

are located in neritic and oceanic waters out to the 2000 m isobath, between Pensacola, Florida and

Brownsville, Texas. The greatest concentration of sightings occurs south of Louisiana and southeast

of Texas in the vicinity of the shelf edge (200 m isobath) where sampling effort is considered

greatest. No sightings were made within the hypoxic zone located south of Louisiana and Texas

during months that hypoxic conditions are known to exist. Solitary sightings were common,

however, 18 % of sightings were of aggregated animals, the largest aggregation consisting of 30

whale sharks. Aggregations occur in the vicinity of shelf-edge banks during August and September

when mass spawning events occur at the Flower Garden Banks, the northernmost hermatypic

tropical coral reefs located on the continental plate of North America. Aggregations also occur along

the shelf-edge and seaward in the vicinity of the Loop Current frontal boundary, indicating that

whale sharks may optimize their foraging effort in areas where plankton is often known to be

abundant.
67

POTENTIAL CONFLICTS BETWEEN DEEPWATER FISHING AND

OIL AND GAS OPERATIONS IN THE GULF OF MEXICO

David B. Snyder

Luis Lagera

Continental Shelf Associates, Inc.

Peter Arnold

Mandeville, LA

LeRay de Wit

Concord, CA

George H. Burgess

Florida Museum of Natural History

University of Florida

Chris Friel

Florida Marine Research Institute

INTRODUCTION

The fishing and offshore energy industries have coexisted amicably for many years in shelf waters

of the northern Gulf of Mexico (GOM). Recently, the offshore energy industry in the GOM has

shifted its interest beyond the shelf and into deeper waters (>200 m). This is evidenced by over

3,800 active leases and about 50 development/production facilities in water depths greater than 200

m. Existing and future structures represent new and evolving technology that could interact with

deepwater (bluewater) fisheries. All phases of industry-geophysical surveys, exploratory drilling,

development/production, and abandonment-could interact with current deepwater fishing practices.

In the northern GOM these practices include trapping for golden crab, trawling for royal red shrimp,

bottom longlining for groupers, snapper, and tilefishes, and surface longlining for sharks, swordfish,

and tunas. 

The potential for interactions between bluewater fishing and deepwater energy industry was raised

as a primary concern by a fisheries subcommittee during a recent deepwater workshop (Carney,

1998) sponsored by the Minerals Management Service (MMS). In 1999, Continental Shelf

Associates, Inc. was awarded a contract to investigate this problem for MMS. The project team

consists of independent consultants with experience in fisheries, oil and gas technology, space-use

problems, and Geographical Information Systems (GIS). 

OBJECTIVES

We are assessing actual and potential interactions between the two industries through the following

objectives:
68

• Determine bluewater fishing endeavors and practices and deepwater outer continental shelf

(OCS) energy development activities;

• Describe and map bluewater fishing and deepwater OCS energy development activities;

• Describe current GOM and relevant worldwide interactions and predict future situations that

may occur in the GOM between bluewater fishing and deepwater OCS energy development

activities; and

• Recommend proactive mitigation measures for MMS and for the fishing and OCS energy

industries.

METHODS

The first two objectives are being addressed by gathering descriptive information and "mappable"

data from a variety of sources for the two industries. Past and current information on the OCS

energy industry will be obtained from MMS data sets that contain active leases, filed Plans of

Exploration (POEs), existing development facilities, and existing pipelines. Existing facility

descriptions will come from filed Development Operations Coordination Documents (DOCDs) or

POEs, U.S. Coast Guard files, and industry operators. Descriptions of exploratory drilling rigs will

come from various drilling rig contractors. Future OCS activity will be projected from the MMS

data sets that include active leases with filed POEs or DOCDs, announced discoveries with filed

POEs or DOCDs, and future pipelines. In addition, an analysis of lease bonuses paid on existing

leases will be made to determine which lease block received high bids. 

The bluewater commercial fishing industry will be described from data obtained from National

Marine Fisheries Service (NMFS) data sets. Several data sets will be examined, including the

longline logbook data set, the shrimp data set, and the reef fish logbook data set. These data sets

provide varying levels of spatial resolution, ranging from latitude/longitude (degrees and minutes)

to large scale (kms) NMFS statistical grids. Catch and effort information will be extracted from the

data sets to characterize spatial and temporal patterns in the northern GOM. Species composition

and life history characteristics will be described for primary deepwater fisheries species.

Current domestic conflicts are being gathered from U.S. Coast Guard, Fishermen's Contingency

Fund, and California Fisheries Liaison Office. Information on international interactions will be

compiled from a variety of sources including Canada-Nova Scotia Offshore Petroleum Board,

Fisheries and Offshore Consultative Group (North Sea), and United Kingdom Offshore Operators

Association Compensation Fund. 

RESULTS

The most common facilities used in deepwater operations are fixed platforms, semi-submersible

floating production systems, compliant towers, tension leg platforms, spars, and subsea completions

(Figure 2.4). The spatial preclusion of seafloor or water column by these facilities depends upon the
69

Subsea System

(300 – 2,150 m)

Semisubmersible-Based

Floating Production

System

(500 – 1,200 m)

Compliant

Tower

(500 - 900 m)

Fixed

Platform

(to 500 m)

Tension Leg

Platform

(500 – 2,150 m)

Spar

(600 – 3,000 m)

Figure 2.4. Deepwater production systems in the Gulf of Mexico.

type of mooring system used and the water depth. For example, catenary moored systems cover

much greater portions of the seafloor than do tension leg systems. 

Presently there are about 3,800 active leases in waters greater than 200 m deep, with approximately

50 platforms currently operating in these water depths. Areas with the future activity are in

Mississippi Canyon, Green Canyon, Garden Banks, and Viosca Knoll lease block areas. Of the 3,800

leases, about 800 received bonus bids exceeding $1 million. With the exception of Corpus Christi

and Port Isabel, where there has been little if any drilling success to date, all OCS areas with less

than 60 leased blocks are either relatively small in overall extent in the deepwater study area or have

experienced legal constraints on leasing. The remaining eight areas have hundreds of leased blocks

each. In most of these areas, between approximately 3 and 6 percent of leased blocks received bonus

bids in excess of $500 per acre. Interestingly, these include both the relatively nearshore area of East

Breaks and Green Canyon, as well as the more distant and deeper water areas of Alaminos Canyon,

Atwater Valley, Keathley Canyon, and Walker Ridge. In fact, the two bluewater blocks which

received bonus bids in excess of $5,000 per acre are of recent vintage (1998) and are in water depths

of approximately 1,500 and 3,000 m. In the Garden Banks area, which saw the first development

in over 600 m, and Mississippi Canyon, which boasts several developments beyond 900 m, twice

the percentage of leases received bonus bids in excess of $500 per acre. 

Current deepwater fishing practices in the northern GOM include trapping for golden crab; trawling

for royal red shrimp; bottom longlining for groupers, snappers, and tilefishes; and surface longlining

for sharks, swordfish, and tunas. The areal extent of these fisheries varies greatly, from widespread

to localized. The royal red shrimp fishery appears to be concentrated in the area south of

Alabama/Mississippi corresponding to statistical grid 10, with minimal effort expended in areas off

the Florida Keys and Texas. Golden crab trapping is most prevalent off of southwestern Florida and
70

Figure 2.5. Spatial distribution of surface longline sets made in the Gulf of Mexico during 1998

(Source: National Marine Fisheries Service longline logbook data 1999).

the Florida Keys, with very few fishers actually participating in this fishery. There is some

speculation that the deepwater crab fishery will expand in the future. The bottom longline fishery

occurs near the shelf break, and is legislatively mandated to remain offshore of the 102 m depth

contour. Most effort by reef fish permit holders for deepwater groupers and tilefishes occurs

offshore of west Florida; however, appreciable effort has been expended offshore of Louisiana and

Texas as well. The pelagic longline fishery is widespread in the open GOM (Figure 2.4). Of these

gear types, the pelagic longline presents the greatest possibility for interactions or space-use

conflicts.

REFERENCES

Carney, R.S. 1998. Workshop on Environmental Issues Surrounding Deepwater Oil and Gas

Development: Final Report. U.S. Department of the Interior, Minerals Management Service,

Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 98-0022. 163 pp.

NMFS. 1999. Pelagic longline logbook data, NMFS, Miami, FL.
71

SESSION 3: 

OFFSHORE PLATFORMS AND THEIR MULTIPLE USER GROUPS

Moderators: Ron Lukens

Villere Reggio

Date: October 24, 2000

Presentation Author/Affiliation

Commercial Fishing Perspective

(Document not submitted)

Jerald Horst

Charter Fishing Perspective

(Document not submitted)

Steve Tomeny

Recreational Fishing Perspective

(Document not submitted)

William Bass

Integration of Offshore Oil & Gas Platforms

and Cage Aquaculture in the Gulf of Mexico

Christopher J. Bridger

Institute of Marine Sciences

Gulf Coast Research Laboratory

University of Southern Mississippi

Barry A. Costa-Pierce

Mississippi-Alabama Sea Grant Consortium

Clifford Goudey

Massachusetts Institute of Technology Sea

Grant College Program

Robert R. Stickney

Texas Sea Grant College Program

J. D. (Dan) Allen

Chevron USA, Inc.

Texas Artificial Reef Programs 2000 Review J. Culbertson

D. Peter

J. Embesi

P. Hammerschmdit

Artificial Reef Program

Texas Parks and Wildlife Department

Rigs-to-Reefs from an Operator’s Viewpoint Dave Dougall

Agip Petroleum Co.
73

INTEGRATION OF OFFSHORE OIL & GAS PLATFORMS AND CAGE

AQUACULTURE IN THE GULF OF MEXICO

Christopher J. Bridger

Institute of Marine Sciences

Gulf Coast Research Laboratory

University of Southern Mississippi

Barry A. Costa-Pierce

Mississippi-Alabama Sea Grant Consortium

Clifford Goudey

Massachusetts Institute of Technology Sea Grant College Program

Robert R. Stickney

Texas Sea Grant College Program

J. D. (Dan) Allen

Chevron USA, Inc.

ABSTRACT

In response to an U.S. Department of Commerce Aquaculture Policy, the Gulf of Mexico Offshore

Aquaculture Consortium (OAC) was formed to create a collaborative, Gulf-wide, interdisciplinary

research and development program to generate primary scientific data and conduct studies in marine

policy, ocean environmental, marine biology and ocean engineering aspects of offshore aquaculture

(www.masgc.org/offshoreconsortium.html). Permission has been provided to moor a 600 m3

 Ocean

Spar Sea Station (OSSS) in U.S. federal waters near a Chevron gas platform off the coast of

Mississippi (29o 58.649'N, 88o 36.297'W). To decrease user conflicts, unintentional damage and

vandalism to grow-out systems, a currently producing gas platform was chosen as the site for the

consortium’s experimental offshore aquaculture operation. The OSSS is not attached to the gas

platform but is moored to the continental shelf on a single-point mooring (SPM) and allowed to

move in a ‘watch circle’ near the Chevron platform. Although providing no investment, Chevron

is a cooperator to the project as a field observer to structural damage and provides passive navigation

protection. Increased liabilities and dependence on oil and gas operations exist with integration of

these industries. An alternative solution to design and manufacture a lift-boat specifically for

offshore aquaculture operations has been proposed to alleviate offshore aquaculture logistics. An

aquaculture lift-boat would eliminate oil and gas liability issues, create complete independence for

the offshore aquaculture operations, and compares economically to integration strategies of

aquaculture with the oil and gas industry. From a preliminary analysis of options, the OAC research

team has concluded that for offshore aquaculture to succeed in the Gulf of Mexico (GOM): (1) an

OSSS design will be required; (2) cobia may be the best candidate species; and (3) a lift-boat

strategy may be most appropriate to alleviate offshore logistics, and is economically comparable to

aquaculture integration with the oil and gas industry.
74

INTRODUCTION

Aquaculture is expanding rapidly in freshwater environments, land-based recirculation facilities,

coastal bays and fjords, and, more recently, in the exposed open ocean. Freshwater expansion is

limited in the U.S. due to the quantity of freshwater resources required for inland aquaculture and

declining groundwater resources of many U.S. areas (Postel 2000). U.S. aquaculture expansion will

likely be limited either to ponds, lakes or reservoirs, or require development of high-cost

recirculation technologies (Ebeling 2000).

Expansion of coastal aquaculture, both land-based and net pen culture in protected bays and fjords,

is also limited. Unlike other regions of the world, such as Norway, Scotland, Chile and Canada, the

U.S. lacks unpopulated bays and fjords that allow expansion of coastal aquaculture, with the

exception of Alaska where commercial fish culture is currently prohibited. Rapid increase of the

nation’s coastal population has formed mega-cities, creating increased pollution and stress to the

environment, all of which limit coastal aquaculture expansion (Edwards 1989). In addition, currently

used U.S. coastal areas will eventually have bottlenecks to future expansion of net pen aquaculture

due to threats of self-pollution by the aquaculture facility (Lumb 1989). As a result, it has been

recognized that perhaps the most appropriate option for expansion of U.S. aquaculture production

is in the open ocean environment within the exclusive economic zone (EEZ). This area has fewer

user conflicts and provides a consistent flow of high quality water for successful aquaculture

operations. In addition, offshore waters may buffer fluctuating temperatures and have more stable

salinities than inshore waters (Waldemar Nelson International Inc., 1997). However, offshore

operations will require large infusions of knowledge, research, capital and logistic support to ensure

success.

On 10 August 1999, the U.S. Department of Commerce approved an Aquaculture Policy to promote

the development of an environmentally sustainable and economically feasible aquaculture industry

with a vision:

“To assist in the development of a highly competitive, sustainable aquaculture

industry in the United States that will meet growing consumer demand for aquatic

foods and products that are of high quality, safe, competitively priced and are

produced in an environmentally responsible manner with maximum opportunity for

profitability in all sectors of the industry.” (U.S. Department of Commerce

Aquaculture Policy 2000)

Specific DOC objectives, by 2025, are to

• Increase the value of domestic aquaculture production from the present $900 million

annually to $5 billion, which will help offset the $6 billion annual U.S. trade deficit in

seafood.

• Increase the number of subsequent jobs in aquaculture from the present estimate of 180,000

to 600,000.
75

• Develop aquaculture technologies and methods both to improve production and safeguard

the environment, emphasizing where possible, those technologies that employ pollution

prevention rather than pollution control techniques.

• Develop a Code of Conduct for responsible aquaculture by the year 2025 and have 100

percent compliance with the code in federal waters.

• Double the value of non-food products and services produced by aquaculture to increase

industry diversification.

• Enhance depleted wild fish stocks through aquaculture, thereby increasing the value of both

commercial and recreational landings and improving the health of our aquatic resources.

• Increase exports of U.S. aquaculture goods and services from the present value of $500

million annually to $2.5 billion.

This long-term approach for aquaculture development, spanning a minimum of three generations

of operators and researchers, will require adherence to the principles of sustainability (Goodland and

Daly 1996). Sustainable development of aquaculture will ensure that an economically and

environmentally sound industry exists for future generations. In addition, development of new

sustainable aquaculture industries will require appropriate levels of market access, high product

demand and supportive government agencies with goal-oriented research (Aarset 1999).

MARINE AQUACULTURE OPERATIONS

Marine aquaculture may be classified into four categories according to the degree of protection

afforded the operation by the site characteristics (Table 3.1). Land-based operations pump the water

to tanks, on-shore, thereby being protected from storm surges and adverse weather conditions. These

operations require large capital investments in infrastructure and are restricted by coastal

development to the extent that future land-based operations may be focused only on hatchery and

processing facilities to complement open ocean grow-out facilities. Similarly, coastal aquaculture

sites are located in protected, remote bays or fjords, away from populated areas and presumably

anthropogenic sources of pollution associated with coastal communities.

In coastal aquaculture, as in the oil and gas industry, farm workers typically rotate in shifts, upwards

of a week, living on-site throughout. Farm workers have their quarters in a cabin either floating on

the water near the cages or on-shore in line-of-sight of the cage flotilla. This close proximity to the

cages and fish stock provides security against losses to vandalism, theft, predators, or adverse

weather. Most logistical issues have been overcome with barges designed to hold large quantities

of feed, regular site visits to change crew and replenish fuel and food, and constant communication

maintained through VHF/UHF radios or cellular telephone. Site protection to the cages allows farm

operators to perform necessary tasks, such as multiple daily feeding, net changing, size grading and

stock sampling, with minimal dependence on mechanization. Such aquaculture does not require the

same degree of infrastructure as more exposed sites.
76

Table 3.1. Comparison of marine aquaculture strategies as categorized by degree of exposure

operation to natural oceanographic and storm events.

Location Advantages Disadvantages

Land-based Facility - Control water quality

- Isolation of operation from

populated areas not required

- Complete protection from storm

surges

- Limited space

- Expensive capital investment

Coastal

Environments

(protected bays and

fjords)

- Less capital investment

- Protected from much of the

natural elements

- Surveillance possible with

minimal investment

- Possible self-pollution

- Limited space for expansion

- Isolation more desirable to be

free of anthropogenic coastal

pollution

- User conflicts exist close to

shore

Exposed Sites - Utilizing environment

previously unexploited

- Consistent and high quantity

water supply

- Visual protection still possible

from nearby land

- Exposed to destructive natural

elements

- Limited space near-shore

- User conflicts exists close to

shore

- Increased infrastructure

necessary with increased

exposure

- Rely more on mechanization

Offshore Sites - Decreasing user conflicts with

increasing distance from shore

- Very consistent water supply

- Large potential for industry

expansion

- Truly exposed with no

protection from either side

- Increased capital costs

associated with increased

technology and mechanization

- Large investments require to

ensure economic feasibility

- Complete isolation from shore

bases with no land in sight

A simple move of the farm to a more exposed environment increases the logistical demands of the

operation. Land is still not far away but the degree of exposure increases the risk of storm damage

to the cage infrastructure and complicates routine farming operations. The aquaculturist must now

rely more heavily on mechanization to allow feeding at set times during the day. Routine operations,

taken for granted in protected sites, now becomes a substantial chore. Exposed sites, not far from

a land base, still enjoy the luxury of visual observation of the cages and stock, and quick response

time to emergency situations that are not present in the offshore environment.
77

Offshore aquaculture operations have all the logistical challenges of both remote coastal and

exposed aquaculture but at an escalated scale. In such instances, the degree of exposure from all

directions is substantial, with the farm being truly exposed to any and all natural elements. Operators

require large infrastructure to produce fish in quantity for economic feasibility. In addition, excellent

husbandry practices are required to ensure a stress free, healthy stock that is growing in a uniform

fashion. Routine operations such as medication and size grading may be impermissible in this

exposed offshore environment. Finally, because of the extreme remote conditions, offshore

aquaculture will require innovative technologies to allow appropriate levels of feeding, long-distance

communication in the absence of cellular phone coverage, and carefully planned levels of response

to emergency situations.

U.S. Open Ocean Aquaculture Development

Truly open ocean aquaculture in highly exposed sites some distance from shore is still a pioneering

enterprise throughout the world. To allow open dialogue and promote international development of

open ocean aquaculture, three symposia have been dedicated to issues and advancements associated

with the development of a sustainable open ocean aquaculture industry. A fourth meeting is set to

convene in St. Andrews, New Brunswick, Canada, 18-19 June 2001 <http://www-org.usm.edu

/~ooa/ooa_iv.html> (Table 3.2).

Table 3.2. Open Ocean Aquaculture (OOA) Symposia allowing open dialogue and promotion of

international development of open ocean aquaculture.

Symposium Themes Locations Major Discussions References

Open Ocean Aquaculture Portland, Maine,

U.S.A.

Engineering, Prospects and

Challenges for Industry

Polk (1996)

Charting the Future of

Ocean Farming

Maui, Hawaii,

U.S.A.

Technological, Biological,

Policy and Industry Successes

Helsley

(1998)

Joining Forces with Industry Corpus Christi,

Texas, U.S.A.

Alternative Uses of Oil and

Gas Platforms and Candidate

Species

Stickney

(1999)

Taking Open Ocean

Aquaculture to a Commercial

Reality

St Andrews,

New Brunswick,

Canada

Policy, Environmental,

Engineering and Candidate

Species

To convene

17-20 June

2001

In addition to these international open ocean aquaculture symposia, two regional open ocean

aquaculture projects have been implemented to develop an environmentally sustainable and

economically feasible industry. The University of New Hampshire is currently involved in an open

ocean demonstration project to develop and commercialize aquaculture off the coast of New

Hampshire near the Isles of Shoals. This project is an integrated, multidisciplinary effort covering

biology, oceanography, engineering, sociology, economics, outreach and education (Bucklin and

Howell 1999; Bub 2000). A comparable research project has been implemented in Hawaii and has
78

successfully grown Pacific threadfin (Polydactylus sexfilis) to a market size off the south shore of

Oahu (Helsley 2000).

In 1999, a third U.S. regional open ocean aquaculture research program was implemented in the

GOM. This program resulted in the formation of the Gulf of Mexico Offshore Aquaculture

Consortium (OAC) <http://www.masgc.org/oac>, creating a collaborative, Gulf-wide interdisciplinary research and development plan to ensure sustainable—economic, social and environmental—

development of an open ocean aquaculture industry for the GOM.

The Gulf of Mexico and Open Ocean Aquaculture

In most aquaculture development projects throughout the world, it has been fairly easy to

accomplish the mere task of raising fish to a marketable size. However, in almost all cases,

sustainable development of these industries, without environmental concerns and threats of selfpollution, have been nearly non-existent. In most cases, environmental and management decisions

have been based upon primary scientific data collected from other regions of the world or models

in an attempt to describe and predict impacts. The OAC plans not only to develop an economically

feasible open ocean aquaculture sector, but also to defend the sustainability of the industry based

on primary scientific data, collected throughout its development and subsequent commercialization,

from the GOM. Primary data collection and industry development will be performed using a

proactive approach from the outset, learning from mistakes made by previous aquaculture

development elsewhere, and in consultation with all GOM stakeholders, regardless of their

perspective.

As with other U.S. regions, the GOM has comparable bottlenecks to development and expansion

of coastal aquaculture. The GOM is the seventh largest marine area in the world and may be

considered a very productive eutrophic sea, described as the “fertile fisheries crescent” (Gunter

1963). This productivity increases the assimilative capacity of the water, thereby reducing the

environmental impacts associated with aquaculture effluents from offshore farms. In addition,

numerous indigenous species to the GOM have been identified as candidate species for aquaculture

with excellent grow-out and market potential characteristics, including red drum (Sciaenops

ocellatus), red snapper (Lutjanus campechanus), cobia (Rachycentron canadum), and greater

amberjack (Seriola dumerili). Numerous criteria are used to select candidate species for aquaculture,

including the growth rate to a market size. A growth performance index (M’ ; Longhurst and Pauly

1987), using L4 and K values from wild stock literature for each of these species in the northern

GOM provide favorable growth attributes for economically feasible grow-out (Table 3.3). With the

subtropical growing conditions, fingerlings for all of these species are anticipated to reach a

consumer-driven market size within a 1-2 year grow-out cycle, increasing the economic feasibility

of open ocean aquaculture ventures in the GOM.

The offshore GOM area appropriate for aquaculture may be very limited. Water depths between 30-

50 m are most desirable. Depths in this range are considered adequate to sink the cages in an attempt

to avoid hurricane damage but remain within safe diving limits to inspect mooring and connections.

Use of remote operated vehicles (ROV) may be economically feasible for such inspections,

extending the water depth (Willoughby 1999). To keep within 30-50 m, much of the GOM is
79

Table 3.3. Growth performance index (M’)a calculated from cited L4 (cm) and K values for

potential aquaculture species indigenous to the northern Gulf of Mexico. Values shown

in parentheses are standard errors.

Species Sex L4 (cm) K M’ Source

Rachycentron

canadum

male 117.07

(2.808)

0.432

(0.046)

3.77 Franks et al. (1999)b

female 155.50

(3.514)

0.272

(0.017)

3.82

Lutjanus

campechanus

combined 95.0

(1.35)

0.175

(0.005)

3.20 Nelson and Manooch

(1982)c

Sciaenops ocellatus combined 91.8

(2.1)

0.422

(0.023)

3.55 Doerzbacher et al.

(1988)d

Seriola dumerili combined 127.2

(N.P)e

0.227

(N.P.)

3.57 Manooch and Potts

(1997)f

a

 M’ = log10K + 2log10L4 (Longhurst and Pauly 1987)

b

 Cobia were caught from northeastern Gulf of Mexico within the recreational hook-and-line

 fishery and aged with sagittal otoliths (male N=170; female N=395)

c

 Red snapper were caught in the commercial hook-and-line fishery off Louisiana and aged 

 with scales (N=403)

d

 Tagged red drum returns from recreational and commercial fishery off Texas and growth

 determined from tag and release measures (N=2010)

e

 N.P. = not provided

f

 Greater amberjack captured from headboats operating in the Gulf of Mexico from Naples,

 Florida, to Port Aransas, Texas and aged with sagittal otoliths (N=340)

excluded from open ocean aquaculture, and may be as far as 40 km from land. In addition to

limitations associated with desirable depth, some areas of the GOM are prone to experience seasonal

hypoxia (Rabalais et al. 1994, 1996). Although this hypoxic layer is generally restricted to the lower

one-third of the water column, large cages or submerged operations may be impacted. An additional

layer commonly experienced in GOM waters is the nepheloid layer developed from resuspension

of fine sea-floor sediment generated from bottom turbulence (Shideler 1981). Little is known of this

layer’s impact on fish health or its seasonal extent in much of the GOM.

Complete hurricane avoidance is unlikely in the northern GOM. However, it may be possible to

decrease hurricane impacts to aquaculture ventures by sinking cages to avoid such storms. With this

strategy comes the risk of exposing the fish stock to larger sediment resuspension that may
80

anchor

chain

rope

Figure 3.1. Representation of the Gulf of Mexico Offshore Aquaculture Consortium Ocean Spar Sea

Station and single-point mooring (SPM) design.

subsequently irritate the gills, create secondary bacterial infections and result in mass mortality

(Sherk et al. 1974, Brown 1993) and subsequent economic loss to the operation. Finally, much of

the GOM has long supported both commercial and recreational fishing. User conflicts must be

carefully considered and dealt with to ensure success of a future open ocean aquaculture industry.

All of these issues limit appropriate sites for open ocean aquaculture in the GOM to some degree.

THE GULF OF MEXICO OFFSHORE AQUACULTURE

CONSORTIUM RESEARCH PLAN

A site was chosen in 26 m of water approximately 35 km off the coast of Mississippi, in federal

waters (29o

 58.649'N, 88o 36.297'W). This distance logistically separates the OAC from the

previously discussed U.S. open ocean aquaculture initiatives by extending operations outside the

sight of land from the aquaculture site. This site is adjacent to a Chevron gas platform, placing the

cage within the minerals lease. During the first year, both the cage and environment will be

monitored to determine the movement and behavior of the cage in the local oceanographic

conditions and to ensure that the selected site is somewhat appropriate for successful aquaculture.

An Ocean Spar Sea Station (OSSS) was chosen for the experimental cage to sustain high energies

in the offshore environment (Loverich and Gace 1998). The OSSS is 600 m3 volume that is retained

by its rigid structure and netting. Recent open ocean aquaculture projects have opted to use the more

common submerged grid mooring system for exposed, open ocean applications (Fredriksson et al.

2000). To decrease mooring costs, system complexity and potential environmental impact, the OAC

OSSS will be moored to the Outer Continental Shelf (OCS) on a single-point mooring (SPM)

(Figure 3.1; Goudey et al. in press). This cage/mooring configuration will be subsequently

monitored with GPS and current meter units to determine the degree of motion with ambient

oceanographic conditions. Specific environmental monitoring will determine the seasonal influence

on the nepheloid layer and hypoxia, and the impact of hurricanes and storm surges on sediment

resuspension. Following this first year of baseline research, one of the candidate species summarized

in Table 3.3 will be stocked in the cage and grown to a market size. It is apparent that this first year
81

is not an aquaculture project, but focused more as an oceanographic and environmental study. Table

3.4 lists the agencies and permits required for Year 1 (oceanographic) and leading into Year 2

(aquaculture) OAC research.

Table 3.4. Permits acquired to deploy an aquaculture cage on a single-point mooring (SPM) in Gulf

of Mexico federal U.S. waters and conduct Year 1 oceanographic research (upper portion

of table) and potentially necessary for Year 2 aquaculture research (lower portion of

table).

Agency Permit/Letter

U.S. Coast Guard Private Aids to Navigation CG-2554

Gulf of Mexico Fisheries Management

Council

Letter of Support

U.S. Army Corps of Engineers Nationwide Permit

National Marine Fisheries Service Letter of Acknowledgment

U.S. Environmental Protection Agency National Pollutant Discharge

Elimination System (NPDES)

National Marine Fisheries Service Exempted Fishing Permit (EFP)

MS Department of Environmental

Quality

Letter of Acknowledgement

MS Department of Marine Resources Coastal Zone Consistency

The OAC cage and Chevron platform are perhaps extended to the outer limit of a relationship with

the current leasing and permitting system imposed on the offshore oil and gas (O&G) industry. In

the absence of models and a legal framework to acquire and maintain a Marine Aquaculture Zone

(MAZ), the relationship consists of the cage having passive protection from nearby marine vessels

and limited visual surveillance to prevent vandalism and storm damage. For Chevron, the benefits

of cooperating with the OAC in this project are minimal, and in fact, their participation might best

be viewed as altruistic. This leads us to pose the questions: would such a relationship exist if this

project were at a commercial scale? and what would it entail? We see four specific scenarios to the

development of offshore aquaculture in the GOM, each with its own set of advantages and

disadvantages (Table 3.5).

INTEGRATION OF OFFSHORE OIL/GAS PLATFORMS AND CAGE AQUACULTURE

With the presence of around 4,000 oil and gas structures in the GOM, it would seem that the use of

the existing platform structures (removing single-well caissons due to lack of appropriate space)

would offset most of the logistic limitations of isolated offshore aquaculture. These platforms could
82

Table 3.5. Comparison of scenarios for integration of oil and gas (O&G) platforms in the

development of offshore aquaculture in the Gulf of Mexico.

Offshore

Aquaculture

Operations Strategy Advantages Disadvantages

O&G Invest into and

Integrate Offshore

Aquaculture Within

Operations

- Increase economic potential of

O&G structure

- Leasing modifications required

- Current platform design will not

allow mooring offshore cages to

the structure and not designed

for safe aquaculture operations

- Future platform design criteria

modified for safe operations

- Potential interference with O&G

operations

Offshore Aquaculture

Investors Lease

Abandoned O&G

Structures

- Offset costs associated with

structure removal

- O&G industry not direct investors

to offshore aquaculture

- Current platform design will not

allow mooring offshore cages to

the structure and not designed

for safe aquaculture operations

- O&G industry will still have

liability issues: 

1. Maintenance of aids to

navigation

2. Structural integrity of the

structure for its life

3. Injuries or property damage

associated with the structure

- O&G original operator may be

responsible for removal if new

operator neglects removal

Near O&G Platform

but as a Separate

Operation

- No transfer of ownership

required

- Passive protection to the cage

facility

- Visual surveillance offered to

vandalism and storm damage

- No benefits of platform to the

aquaculture operator as a ‘shorebase’

- Potentially interfere with O&G

operations

- O&G operator potentially liable

for aquaculture mortality near its

structure

Lift-boat within

Marine Aquaculture

Zone

- Eliminates all O&G concerns to

aquaculture

- Specifically designed for

aquaculture operations

- Avoids storm impact

- Increased user conflicts if

competing for new space with

traditional use
83

provide a stable work base to conduct the day-to-day operations required for an aquaculture venture.

In addition, they could provide deck space for feed storage, lodging for farm workers, necessary

utilities and communications, surveillance against vandalism and storm damage, and passive

protection from other, more traditional, users of the GOM. However, such platforms are built well

above the water column to protect them from storm surges and are designed to last for years

following the expected life of an oil and gas well, approximately 25 years, with 100-year storm

manufacture criteria. With such obvious benefits to the aquaculture sector, is this a logical

integration of two industries? What could be some of the potential constraints to prevent such an

industry ‘marriage’?

Investment by Oil and Gas Companies

Of course, the OAC is not the first organization to attempt offshore aquaculture in the GOM, and

with this, we are not the first to realize existing oil and gas structures could be a valued asset to

expansion of an industry (Stickney 1999). Following placement of a structure on the OCS, it may

also be readily available for alternative uses to enhance the economic potential and offset the costs

of design, construction and deployment. These costs, dependent on the size and water depth, could

range from $10-30 million (Chambers 1998). With the prospects of large economic returns

associated with the economies of scale of offshore aquaculture, such an integration could become

enticing. Previously trained oil and gas employees could also become trained aquaculturists, armed

with advanced technologies and innovation for successful farm production.

Such visions for integration have several constraints to overcome before attaining commercial

reality. Current leasing mechanisms within the Minerals Management Service (MMS) authorize

companies to explore for, develop, produce and transport oil and gas from the OCS. The

involvement of aquaculture will complicate such a lease and add several new layers to this program

in the form of additional approvals required from several other regulatory agencies (Table 3.4).

Platform design would also have to be altered substantially for safe operations as a fish farm facility.

Current designs are appropriate to hold and conduct necessary operation for successful oil and gas

production in a safe and responsible manner. Aquaculturists will require modifications for

deployment of boats, personnel and feed on a regular operational basis. In addition, structures will

have to be modified to provide sufficient deck space for storage of large quantities of feed and work

boats. Current structures are also designed for very specific vertical and horizontal loads that would

have to account for additional stresses associated with mooring cages and net pens to the structure.

An alternative approach, of course, would be to moor the cage system to the OCS as the OAC has

done. However, aquaculture benefits associated with decreased costs for expensive mooring systems

required for holding the cages on the OCS in a very exposed and harsh environment are now absent.

In addition, mooring systems to the OCS may be limited to within 50 m depth to ensure safe diving

limits are adhered to. Finally, aquaculture operations may interfere with routine oil and gas

operations for which the structures are primarily intended.

Use of Abandoned Oil and Gas Structures

A second scenario for use of existing structures for offshore aquaculture involves abandoned

structures from the oil and gas industry. Within one year of production completion, oil and gas
84

operators are required to remove the production equipment and return the site to pre-production

conditions. Such an endeavor in 30-50 m depth averages about $1 million. These costs may be offset

somewhat may acquiring a permit to drop the platform in its place to create an artificial reef, or

those with excellent structural integrity may be hauled to another oil or gas field and reused.

Aquaculture investors could view these costs and regulations as a reason to lease the existing

structure where it is and maintain it as an aquaculture facility. In this case, cages may still not be

attached to the structure due to increased loads associated with its movement and drag.

For the oil and gas company, issues of liability are paramount in this scenario. Although the

structure may be used by another operator, the original company is still liable for maintenance of

aids to navigation and structural integrity of the structure for the life of the facility. In addition, the

original operator may be held liable for all injuries or property damages arising from the offshore

structure except in cases where gross negligence or willful misconduct by the injured party could

be proven, regardless of whether the oil and gas company is actively operating the structure or not.

Finally, in instances where the structure may be sold to an offshore aquaculture investor, the original

oil and gas company is responsible for structure removal if the new operator fails to do so upon

completion of their work. The MMS has implemented a Supplemental Bonding Program requiring

an oil and gas operator to post a bond to offset the cost of abandonment liability of the lease

including structure removal (Kruse 1999). For a future to exist for the use of oil and gas abandoned

structures for offshore aquaculture, the original oil and gas company would have to be released from

its responsibility for structure removal. However, it has yet to be determined whether aquaculture

investors could afford the cost of such bonds from the outset.

Neighboring but Separate Operations

To offset issues regarding transfer of ownership and future status, a third scenario may be utilized

in that the aquaculture investor moors its cage systems near an existing oil and gas company

structure. A comparable situation exists between the OAC cage and the Chevron platform. In this

instance, the benefits for the aquaculture operation would be passive protection from abundant

vessel traffic in the GOM and perhaps surveillance from vandalism and storm damage as discussed

above. However, operating near an oil and gas platform does not benefit the aquaculture operation

by providing an offshore working and storage platform. As previously discussed, the oil and gas

company may not wish to store feed or house aquaculturists on the platform to eliminate liability

risks. In addition, such associations may become unsafe and interfere with the day-to-day operations

of the oil and gas operators, or vice versa, and decrease the time spent for the aquaculture operations

(Wilson and Stanley 1999). Finally, the operating oil and gas company could be held liable for any

tainting, mortality, or other loss of the caged fish stock associated with their operations.

Following this exhaustive list of liabilities and hurdles associated with a relationship between the

oil and gas industry and offshore aquaculture, one has to wonder whether such a future could exist.

Is there another option for the development of offshore aquaculture?
85

Figure 3.2. Hypothetical illustration of a lift-barge potentially designed for offshore aquaculture

operations (courtesy of Dennis Good, Goodstreak Marine, Slidell, LA).

ALTERNATIVE SOLUTIONS TO OFFSHORE AQUACULTURE

LOGISTICAL CHALLENGES

How is an offshore aquaculture industry to develop without an accessible working platform to serve

as a ‘shore-base’? One such alternative is the creation of a Marine Aquaculture Zone (MAZ) with

a lift-boat, specifically designed for aquaculture operations, as its focal point (Figure 3.2). A lift-boat

strategy would alleviate all concerns associated with aquaculture and the oil and gas industry and

does not introduce any new technology to the GOM. A lift-boat would be designed, with

environmentally sustainable criteria, to create a safe working platform for offshore aquaculture.

Such a barge could possess sufficient living quarters for the workers, deck space for feed storage

and a crane capable of lowering and raising a farm work boat and feed. In addition, power could be

supplied with a hybrid system of wind turbines, and photovoltaic cells and wastes could be collected

and disposed of on-shore to minimize the risks of tainting or losing the fish stock. Regular

operational mode would see the lift-boat jacked-up from the water surface, perhaps to 7 m height,
86

to provide a stable working platform. In severe stormy or hurricane conditions, workers would sink

the cages before raising the lift-boat legs and moving to shore.

A concept involving future offshore aquaculture and MAZs cause some concern to other user

groups. Such user groups may include recreational boaters and fishers, traditional wild fishers and

even the oil and gas industry by preventing access to future oil and gas fields. Most use conflicts

may simply be avoided through active dialogue and careful planning and consideration of all

stakeholders. Lift-boats and associated MAZs may be placed in the same zone of a previous

minerals rights lease immediately following removal of the oil and gas structure. This alleviates

concerns from the oil and gas sector as this area has been exploited for its mineral value. In addition,

during operation, the previous oil and gas structure would have prevented successful wild

commercial fisheries. With its immediate replacement by offshore aquaculture, this new industry

is not removing currently utilized and precious space from wild fishers. Finally, following structure

removal, recreational fishers lose a large and valued fish aggregating device (FAD). However,

replacement by offshore aquaculture and a lift-boat will essentially continue the presence of this

valued FAD effect. A strategy could be negotiated whereby recreational fishers could fish near the

lift-boat while respecting the operations of the aquaculturist and not vandalize the cages.

SELECTION OF THE MOST APPROPRIATE OFFSHORE

AQUACULTURE STRATEGY

A list of associated expenses is provided in Table 3.6 to compare the economic environment for each

of the proposed offshore strategies. Such a simplistic analysis is warranted at this time with the

current state of factual knowledge associated with offshore aquaculture operations and the grow-out

of the candidate species considered. With the exception of red drum, knowledge of the biological

aspects – nutrition, stocking density, food conversion ratio, feed quantity, etc. – and feasibility of

raising each of these candidate species is currently limited. In addition, each of these species,

including red drum, has minimal collected data regarding offshore grow-out and associated costs

and returns at a commercial scale. Finally, several of these species either have closed fisheries or

no commercial value and a minimum commercial size limit above the anticipated market demand

size. These factors will alter the expected revenue for an aquaculture product—harvested at a

consumer derived size, of the highest quality possible, and at the time of the highest market

demand—thereby fetching premium prices. Throughout OAC research development, costs and

returns associated with offshore aquaculture will be carefully documented and extrapolated to a

commercial scale to gain better insight of the economic feasibility of commercial offshore

operations.

With increased independence from the oil and gas industry and decreased liabilities (Table 3.5) and

a comparable expense list to the oil and gas investment strategy (Table 3.6), perhaps use of the

‘alternative’ lift-boat solution to the logistical challenges may indeed be the most desirable route for

industry development. This notion is based on the independence of the ‘alternative’ solution, without

the liabilities associated with the oil and gas industry and specific design for the needs of offshore

aquaculture operations. To further substantiate use of a lift-boat, an economic comparison revealed

that each of these strategies, with the exception of using an abandoned oil and gas structure, appear

somewhat comparable with respect to the level of investment required. Direct investment by the oil
87

Table 3.6. Simplistic outline of potential expenses experienced for each of the offshore aquaculture

strategies outlined in Table 3.4.

Offshore Aquaculture Strategy

O&G

Investment

Abandoned

Structure

Separate

but Nearby

Aquaculture

Lift-boat

Capital Expenses

Platform Abandonment Bond 1,500,000

Platform Refurbishment 500,000 500,000

Lift-boat Manufacture 1,000,000

Large Work Boata 500,000

Small Service Boats 100000 100,000 100,000 100,000

Cages (6 x 3000 m3) + mooring systems 600000 600,000 600,000 600000

Total Capital Expenses 1,200,000 2,700,000 1,200,000 1,700,000

Operating Expenses

Supply Boat Runs 150,000 150,000 750,000b 150000

Feedc 315,000 315,000 315,000 315,000

Crewd 315,000 315,000 400,000 315000

Maintenance (platform + equipment) 200000 200,000 100,000f 200000

Insurance (4% of revenueg

) 72,000 72,000 72,000 72,000

Total Operating Expensesh

 1,052,000 1,052,000 1,637,000 1,052,000

Contingencies (10% of operating costs) 105,200 105,200 163,700 105,200

TOTAL EXPENSES 2,357,200 3,857,200 3,000,700 2,857,200

a

 It is assumed that the strategy of being near a current structure would purchase a large work boat due

to increased dependency on it. Other strategies would contract this service out on a weekly basis.

b The strategy of being near a structure but operating from a land-base would require numerous more

trips to the cage, upwards of 3 times per week for security and maintenance operations.

c Quantity of feed delivered is based on a food conversion ratio of 2:1 remaining constant throughout

the grow-out cycle and total growth per year of 450,000 kg, regardless of species, and multiplied by

a feed cost of $350 ton-1.

d Crew is typically calculated from annual salaries of a manager ($75,000), supervisor ($50,000 x 2),

and farm crew ($35,000 x 4).

e More salary would be required for supply boat crew annual salaries of captain ($50,000) and deck

hand ($35,000).

f Fewer maintenance costs required in the absence of a platform to maintain.
88

g Revenue is based upon an estimated ex-vessel price of $4.00 kg-1 of 450,000 kg from the 6 x 3000

m3 cages with a stocking density of 25 kg m-3. Other assumptions include 100% survival and constant

growth giving a 1-year grow-out cycle for each of the species.

h Total Operating Expenses are exempt of additional anticipated expenses, such as office rental,

personnel and supplies, that are considered identical regardless of the strategy used and therefore

not required for this simplistic economic illustration.

and gas company into the aquaculture sector has the greatest economic merit. However, this is

dependent on the degree of interference caused by aquaculture to the oil and gas operations for

production. With a reasonable cost of investment and operations and increased independence, design

and manufacture of a lift-boat specifically for offshore aquaculture seems to be most desirable.

CONCLUSIONS

In the 21st century, offshore aquaculture will be required to grow the necessary biomass of fish to

meet global consumer demands for seafood. This new industry will require substantial efforts,

research, collaboration, and investment to become a commercial reality. Enormous logistical

challenges are present for aquaculture operations with increasing distance from shore. For the GOM,

an obvious solution to such challenges could include the use of currently operating, abandoned, or

future oil and gas structures. However, an aquaculture logistics solution involving the oil and gas

industry will require substantial modifications in both the design of the offshore structure and the

permitting mechanism to allow fish grow-out with oil and gas production. An alternative solution

to enormous offshore aquaculture logistics is the design of a lift-boat for safe aquaculture operations.

A lift-boat would alleviate potential constraints associated with oil and gas industry liabilities and

independence of the aquaculture venture. In addition, following the simplistic economic analysis,

design and manufacture of a lift-boat specifically for offshore aquaculture may be considered

economically comparable to the offshore aquaculture strategies involving the oil and gas industry.

ACKNOWLEDGMENTS

This research is supported by a NOAA/Sea Grant award, contract #NA06RG0071. The GOM

Offshore Aquaculture Consortium would like to express sincere gratitude to Chevron USA for

collaborating during this research. In addition, the authors would like to thank Dennis Good (Good

Streak Marine, Slidell, LA) and George White (Marine Consultant, Slidell, LA) for insight on the

capabilities and design criteria necessary to alleviate some logistical challenges for offshore

aquaculture in the GOM and Ben Posadas for reviewing the economic analysis.

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92

TEXAS ARTIFICIAL REEF PROGRAM 2000 REVIEW

J. Culbertson

D. Peter

J. Embesi

P. Hammerschmdit

Artificial Reef Program

Texas Parks and Wildlife Department.

ABSTRACT

In 1989, the 71st Legislature of Texas directed Texas Parks and Wildlife to develop a State Artificial

Reef Plan to create and enhance reef fish habitat offshore of Texas. The Texas Artificial Reef Plan

provides guidance and flexibility to allow for changes in policy as new information is presented or

becomes available. The goals of the Texas Artificial Reef Plan are to enhance the fishery resources

biologically, commercially, and recreationally. The Program utilizes a ten-person citizen advisory

committee, representing major interest groups in the Gulf of Mexico to create new sites, evaluate

material donations, and minimize user conflicts.

One of the main criteria for the Program is to actively pursue complex, stable, and durable structures

in a form as close to their current form as possible. Oil and gas platforms are the primary reef

building material of choice, since they already serve as artificial reefs in the Gulf of Mexico and also

meet the material criteria of the Program. The Texas Program promotes the use of "partially

mechanically removed" structures to minimize damage to the benthic communities attached to the

structure, and to minimize loss of reef fish from the use of explosives when toppling structures in

place to create artificial reefs. These standing structures allow the maximum biological profile to

remain higher in the water column and still meet safe navigational clearances.
93

RIGS-TO-REEFS FROM AN OPERATOR’S VIEWPOINT

Dave Dougall

Agip Petroleum Co.

ABSTRACT

Oil and gas platforms offshore of the U.S. presently number around 4,000 and some date as far back

as the 1950s. As these structures come to the end of their economic lives, they must be

decommissioned. Since 1988, decommissioning of platforms has occurred at a rate of 100 to 150

per year.

This paper reviews the alternatives available to owners of offshore oil and gas structures for

retirement of these structures and examines the attractiveness of donating those structures to an

artificial reef program.

BACKGROUND

Oil and gas development in the Gulf of Mexico (GOM) began in the 1930s in the tidal lands of

Louisiana. The first oil well out of sight of land was placed in 1947 in about 18 feet of water. Since

then, technology has more or less continuously improved, and development has continued to move

farther from shore and into deeper water. GOM oil and gas platforms are located from shoreline to

200 miles from land and in water depths near 5,000 feet. Figure 3.3 provides insight into the

distribution of platforms in the GOM. This map shows the relatively high density of structures on

the broad shelf area off the coast of Louisiana and Texas. 

Although deepwater drilling and development are currently the focus of substantial attention in the

GOM, the vast majority of existing platforms are located in relatively shallow water (see Figure 3.4).

These are the older sites and, therefore, the locations where most of the removal activity will occur

over the next several years.

DECOMMISSIONING

Steel platforms generally have a useful life of 10 to 30 years; productive oil and gas reservoirs, of

course, may be substantially less: Thus, the need to remove oil and gas structures. 

Oil and gas platforms represent a substantial liability to the owner, in terms of removal cost and

potential damage claims. Removal costs may range into the tens of millions of dollars, depending

on a number of circumstances, such as water depth, platform location, size, complexity, and market

for reclaimed equipment and structure at the time of removal. Damage claims may arise from

personal injury, environmental damage, or property damage. These liabilities are only relieved upon

complete removal of the platform or the transfer of ownership to another responsible party.
94

Figure 3.3. Platform distribution in the northern Gulf of Mexico.

Generally speaking, platforms offshore of the U.S. must be removed within 12 months after lease

production ceases. Present requirements specify that companies must permanently plug and abandon

all the wells, sever all wellheads, casings, pilings, and any other obstructions to a depth at least 15

feet below mudline, remove everything from the lease, and then verify that the site is clean either

by having an independent contractor trawl 100% of the area (twice) or by conducting a sonar survey,

the choice depending on circumstances. Either way, the survey is precisely prescribed, and a written

report must be submitted.

A review of MMS records from 1986 through 1998 shows that a total of 1,255 structures were

removed during that period (an average of 116 per year). Figure 3.5 depicts the distribution of

platforms removed by water depth and confirms that most of the platform removals are from shallow

water. (The spike in 1993 is a reflection of damages caused by hurricane Andrew in August 1992,

and the spike in 1997 of a large removal program by one of the major operators).
95

0

20

40

60

80

100

120

140

160

180

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

no. platforms removed

101-125 m

76-100 m

51-75 m

26-50 m

0 - 25 m

Figure 3.5. Gulf of Mexico platform removals by depth.

0

500

1000

1500

2000

2500

3000

3500

4000

0 to 200 201 to 400 401 to 800 801 to 1,000 1,000+

depth in meters

no. of active platforms

Figure 3.4. Gulf of Mexico platform distribution by depth.
96

RIGS-TO-REEFS

Current rules and liability considerations generally encourage complete removal of platforms at the

end of their useful lives. Top deck structures and equipment are often removed and reused

elsewhere, with remaining decks, equipment, and jacket brought to shore, cut up, and recycled as

scrap. Some offshore structures, however, are donated to the rigs-to-reefs program. These programs

are managed by state agencies to take advantage of the reef-like ecosystems fostered by these

offshore oil and gas structures.

The northern GOM seafloor is predominately mud and sand, with relatively little hard bottom or

natural reef areas. Oil and gas platforms have long been recognized as havens for fish and are

favorites for recreational and commercial fishermen and divers as well. The hard surfaces of

platform members provide attachment for a variety of invertebrates such as barnacles, corals,

sponges, mussels, and anemones. They also provide cover for smaller species of fish. These

structures create ideal communities, supporting populations of reef fish such as snapper and grouper,

and attract transient species like mackerel and shark.

Particularly active rigs-to-reefs programs are in waters offshore of Louisiana and Texas and are

managed by the Louisiana Department of Wildlife & Fisheries and the Texas Parks & Wildlife

Department. These programs include:

• Planning for areas where placement of artificial reef materials are encouraged or excluded.

• Technical evaluation of the configuration the structure will have after it is in place on the

bottom. Of particular concern is adequate clearance above the structure for vessel traffic;

generally at least 85 feet are required. The platform and all piping and equipment left on

board must be thoroughly cleaned and certified by a qualified third party.

• Funding procedures for management of the program and purchase and maintenance of

marker buoys. The owner of the structure provides a comparison of costs associated with the

reefing proposal versus the alternative of transport to shore and disposition. The owner then

makes a monetary donation to the program in the amount of 50% of the estimated savings.

• Transfer of ownership of the structure to the state. The program includes a permit program

and execution of a formal transfer of ownership. Transfer of ownership relieves the previous

owner of further liability.

As indicated above, oil and gas structures generally must be severed below the mud line. However,

beginning in 1987, the state program managers, in consultation with MMS and the U.S. Coast

Guard, began actively to consider and approve “partial removal” of platforms under some

circumstances. In this procedure, the topsides are removed and either placed on the bottom or

transported offsite for reuse elsewhere, and the jacket is cut off at an agreed water depth necessary

to assure vessel traffic safety. Leaving the jacket members partially in place maximizes the amount

of available attachment surface remaining within the depth of biological activity.
97

BENEFITS & LIMITATIONS

Donation of all or part of platforms that are no longer of use is a win/win for everyone.

• Conversion of the structure to an artificial reef decreases that expense that would be involved

in complete removal.

• The owner/operator is released from further liability from the structure.

• A rich habitat area is retained for the benefit of fishing, diving and species propagation.

Given the obvious benefits of donating structures into the rigs-to-reefs program, it would seem that

every decommissioned structure would go into the program. Yet the majority of structures are

removed. As discussed above, by far most of the structures removed are from relatively shallow

water, too shallow to provide the clearance required for safe navigation.

CONCLUSION

Given the number and age of oil and gas structures in the GOM, platform removal activity will

continue to be substantial in the foreseeable future. Wherever feasible, reuse of structures as

artificial reefs is an economic and beneficial alternative to removal and transport to shore.

David A. Dougall is Manager of Environmental Affairs & Safety for Agip Petroleum Company,

with drilling and production operations in the Gulf of Mexico. Mr. Dougall’s background includes

environmental consulting on risk assessments, compliance audits and permitting. His background

also includes corporate and field assignments for a major oil company, including several years

coordinating permitting and compliance efforts in California. He received his M.S. in environmental

science and B.S. degree from the University of Oklahoma. He is a registered professional engineer.
99

SESSION 4: 

PRESENT AND FUTURE FISHERIES MANAGEMENT I

Moderators: Hal Osborne

Bob Shipp

Date: October 25, 2000

Presentation Author/Affiliation

The Artificial Reef Debate: Are We Asking

the Wrong Questions

Robert L. Shipp

Department of Marine Sciences

University of South Alabama

Artificial Reefs: Habitat for Marine

Resources

Ronald R. Lukens

Gulf States Marine Fisheries Commission

Fishery Resources and Oil and Gas

Operations: Potential Conflicts

Christopher C. Koenig

Felicia C. Coleman

Institute for Fishery Resource Ecology

Department of Biological Science

Florida State University

Kathryn M. Scanlon

U.S. Geological Survey

The Role of Fishermen and Other

Stakeholders in the North Sea Rigs-to-Reefs

Debate

Mark Baine

Jon Side

International Centre for Island Technology

Heriot-Watt University

Orkney Islands, Scotland

Fishing Demand, Catch and Effort Data, and

Economic Impacts Associated with

Recreational Fishing Near Oil and Gas

Structures in the Gulf of Mexico

Robert L. Hiett

QuanTech, Inc.

J. Walter Milon

Department of Economics

University of Central Florida

Importance of Geology to Fisheries

Management: Examples from the

Northeastern Gulf of Mexico

Kathryn M. Scanlon

U.S. Geological Survey

Christopher C. Koenig

Felicia C. Coleman

Florida State University

Margaret Miller

National Marine Fisheries Service
101

THE ARTIFICIAL REEF DEBATE: ARE WE ASKING THE WRONG QUESTIONS? 

Robert L. Shipp

Department of Marine Sciences

University of South Alabama

In the last several decades, and especially the last five years, an enormous amount of literature has

been published on artificial reef ecology (e.g., Fifth International Conference on Aquatic Habitat

Enhancement, Bulletin of Marine Science 55: 265-1360, 1994; Special Issue on Artificial Reef

Management, Fisheries 22:17-36, 1997; Bortone 1998; Technology and Management of Artificial

Reefs: An Update, Gulf of Mexico Science 16:31-105, 1998). Although numerous aspects of the

issue have been addressed in these works, such as materials of construction, critical minimum size

of area, and rates of recruitment, the one persistent question that appears to dominate all the synoptic

treatises is do reefs simply attract fishes (and other organisms), or is an actual increased production

of biomass attributable to reefs (Bohnsack 1989; Bohnsack et al. 1997)?

The relevance of this question seems obvious. If the former is true, then reefs may be detrimental

to fish populations, making certain species easier to harvest, thus accelerating the decline of stressed

stocks. This opinion is held by many workers, at least in certain instances (Bohnsack et al. 1997;

Grossman et al. 1997; Lindberg 1997). Therefore, the utility of reefs as a management tool is

discouraged and deemed counterproductive. With the latter hypothesis, increased biomass

productivity is generally regarded as a positive, and unless the productive benefits are overwhelmed

by increased fishing activity, artificial reefs are viewed as a viable and positive management tool.

The current status of the debate seems to have reached a partial “resolution” of sorts, with the

general acceptance that much depends on location. The general agreement seems to be that in areas

with little natural hard bottom, reefs may be beneficial in providing habitat that is limited (Grossman

et al. 1997; Bortone 1998). But in areas where abundant hard bottom is available, thus habitat is not

limiting, placement of additional reefs is, at best, neutral and, perhaps, counterproductive.

ATTRACTION VS PRODUCTION: DOES IT REALLY MATTER?

Although I do not disagree with this consensus, I think it fails to address the attraction vs production

question. For what we really see in the location solution is not that production is necessarily

increased where hard bottom is limited but that there is a fundamental modification of habitat. And

with this, there is a concurrent transformation of biota. For instance, in a flat sandy mud

environment such as is found in the north central Gulf of Mexico shelf, placement of artificial reefs

displaces a fish fauna dominated by small benthic species with larger reef-related forms. A net

change in fish biomass may or may not occur, but does that really matter from a management

perspective? I am not so naïve that I don’t realize that for many workers the production aspect really

means production of desirable reef species (Grossman et al. 1997), but to many, it is a matter of

production per se. Hard bottom is thought to support primary and secondary production, with the

successional sequence of encrusting organisms, increased refuge habitat for prey species, and actual
102

increase in biomass the result (Carter et al. 1985; Pamintuan et al. 1994: also see Stone et al. 1979;

Bohnsack 1989; Lindberg 1997).

THE ALABAMA SHELF: A CASE STUDY

For a case study, I will use the expansive flat inner shelf of the north central Gulf of Mexico off

Alabama. A large portion (4,000 km2 ) has been prepermitted for placement of artificial reef

structure. This area has been previously referenced and its history and current fishery status are well

documented (Szedlmayer and Shipp 1994; Minton and Heath 1998). 

Because this is probably the largest unified artificial reef site in the United States, and possibly in

the world, it lends itself well to this discussion,. During the decade of the 1970s, before

establishment of the 4000 km2+ reef area, we conducted a series of trawling surveys on this portion

of the shelf. The study, designated SAMERI (South Alabama Marine Environmental Resource

Investigation) included nearly 100 trawl samples, of 15-min tow time, with a 30-foot semi balloon

trawl, at 15 fathoms. The sampling was conducted over 3 years. Although the detailed seasonal and

spatial variation and species composition are beyond the scope of this commentary, the fish faunal

elements were dominated by relatively diminutive soft bottom species, reflecting the near total lack

of hard bottom in the area. The few reef species collected were juveniles or subadults (e.g., red

snapper, Lutjanus campechanus ).

The trawled species are almost exclusively of no current economic importance. The dominant

groups are flounders and other flatfishes, cusk-eels, sea robins, and small species of sea basses. The

flounder species all mature at very small sizes (maximum of 200 mm) and are not exploited. The

cusk-eels are a dominant faunal component, primarily fossorial diurnally, but are important prey

species when they forage nocturnally. The other species are also too small to have any commercial

value other than as minor components of the ground fish harvest. All of these species have extensive

ranges over the entire Gulf of Mexico shelf, and many also on the United States Atlantic coast, thus

are in no danger of any imaginable substantial stock depletion.

This trawled bottom now is contained mostly within the heart of the reef permit area. Approximately

20,000 artificial structures have been placed there, constructed of various materials (Minton and

Heath 1998). Included are 100 decommissioned army tanks, cement bridge rubble resulting from

hurricane damage, thousands of buses and automobiles, prefabricated cement modules, and a variety

of other structures. Early in the program, little restraint was placed on materials for reef deployment,

and thousands of reef sites have been removed or destroyed by hurricanes and other natural events.

Nevertheless, because of recent more stringent regulations on reef materials, many thousand likely

remain.

When reef structure is placed in these areas, the reef biota is in sharp contrast to the preexisting

fauna. Previous to the reef building effort, few reef fishes were taken off the Alabama shelf (Minton

and Heath 1998). Although historically Mobile was considered a major market for red snapper, these

fish were harvested primarily from Pensacola southeastward to Tampa (McEachran and Fechhelm

1998) or from the Campeche Banks off Mexico (Albert King, pers. comm.). But Schirrippa (1998)

reported that recently more than a third of recreationally caught red snapper from the Gulf of Mexico
103

came from off Alabama, although this area represents less than 5% of the U.S. Gulf shelf. Similar

statistics are provided by the 1993-96 Southeast Area Monitoring and Assessment Program

(SEAMAP). Thus, the ichthyofauna of a quarter of a century ago has been transformed from an

economically depauprate biomass to one supporting an industry, which, according to Minton and

Heath (1998), is valued at 60 million dollars annually. Has the total biomass increased? We don’t

know. Does it matter in terms of management decisions? I think the citizens of Alabama’s coastal

communities would offer a strong negative. 

RESEARCH NEEDS

Other questions are relevant, even if those regarding absolute biomass changes are not. If, in fact,

there is some dependence on surrounding forage species for the reef residents, this would eventually

become limiting to the carrying capacity of the reefs. Bioenergetic studies to address carrying

capacity are strongly warranted and, in fact, are currently under way in the Alabama setting (James

Cowan, pers. comm.). Likewise, if these large areas do approach maximum carrying capacity, or if

these micro population concentrations centers are disturbed or even destroyed, do the reef residents

move to nearby or even more distant sites, thus becoming de facto emigration resources for other

areas? This latter question was partially answered by Watterson et al. (1998) for the Alabama stocks.

Their data strongly indicated hurricane impacts on the reef structures off Alabama resulted in near

unidirectional migration of red snappers eastward, with many tagged fish from Alabama taken off

the Florida panhandle as far east as Apalachee Bay.

ARTIFICIAL REEFS AS MARINE SANCTUARIES

The issue of marine reserves or marine protected areas (MPAs) is emerging rapidly as a possible

management tool for marine fish stocks. Several papers have addressed this issue recently

(Bohnsack 1994, 1998). The South Atlantic Fishery Management Council is considering creating

reserves in habitat not currently used by fishers. Such a decision seems well founded on the basis

of the Alabama experience. And the success of such an action is not likely to depend on whether

artificial reefs attract fish or actually produce biomass.

SUMMARY

The production-attraction debate has become central to much of the discussion of the utility of

artificial reefs as management tools. This debate seems to have little relevance in areas where

natural hard bottom is sparse or lacking. Rather, in these areas, biomass transformation from “less

valuable” to “more valuable” species is indicated. Nevertheless, in my experience, the preeminence

of the production-attraction issue has often clouded the issue and reflected negatively on artificial

reef benefits. Care should be taken that this debate be clearly reserved for habitats where additional

hard bottom may be of little or no value because of recruitment limitations.

REFERENCES

Bohnsack, J.A. 1989. Are high densities of fishes at artificial reefs the result of habitat limitation

or behavioral preference? Bull. Mar. Sci. 44:631-645.
104

Bohnsack, J.A. 1994. How marine fishery reserves can improve reef fisheries. In: Proceedings of

the 43rd Gulf and Caribbean Fisheries Institute 43:217-241.

Bohnsack, J.A. 1998. Application of marine reserves to reef fish management. Aust. J. Ecol. 23:298-

304.

Bohnsack, J.A., A. Ecklund, and A. M. Szmant. 1997. Artificial reef research: is there more than

the attraction-production issue? Fisheries 22:14-16.

Bortone, S.A. 1998. Artificial reef management perspective – resolving the attraction-production

dilemma in artificial reef research: some yeas and nays. Fisheries 22:6-10.

Carter, J.W., A.L., Carpenter, M. S. Foster, and W. N. Jessee. 1985. Benthic succession on an

artificial reef designed to support a kelp-reef community. Bull. Mar. Sci. 37:86-113.

Grossman, G.D., G..P. Jones, and W. Seaman. JR. 1997. Do artificial reefs increase regional fish

production? A review of existing data. Fisheries 22:17-23.

Lindberg, W.J. 1997. Can science resolve the attraction-production issue? Fisheries 22:10-13.

McEachran, J.D., and J.D. Fechhelm. 1998. Fishes of the Gulf of Mexico. Vol. Univ. Texas Press,

Austin.

Minton, V., and S.R. Heath. 1998. Alabama’s artificial reef program: building oases in the desert.

Gulf Mex. Sci. 16:105-106.

Pamintuan, I.S., P.M. Alino, E.D. Gomez, and R.N. Rollon. 1994. Early successional patterns of

invertebrates in artificial reefs established at clear and silty areas in Bolinao, Pangasinan,

northern Philippines. Bull. Mar. Sci. 55:867-877.

Schirrippa, M.J. 1998. Status of the red snapper in U.S. waters of the Gulf of Mexico: updated

through 1997. NOAA/NMFS Sustainable Fisheries Division Contribution, SFD-97/l9lll8l-30:15-

18.

Stone, R.B., H.L. Pratt, R.O. Parker, and G.E. Davis. 1979. A comparison of fish populations on an

artificial and natural reefs in the Florida Keys. Mar. Fish. Rev. 41:1-11.

Szedlmayer, S.T., and R.L. Shipp. 1994. Movement and growth of red snapper, Lutjanus

campechanus, in the north central Gulf of Mexico: potential effects of hurricanes. Gulf Mex. Sci.

16l:92-104.
105

ARTIFICIAL REEFS: HABITAT FOR MARINE RESOURCES-NATIONAL POLICY?

Ronald R. Lukens

Gulf States Marine Fisheries Commission

THE NATIONAL FISHING ENHANCEMENT ACT AND PLAN IMPLEMENTATION

The National Fishing Enhancement Act of 1984 (Act) established artificial reef development as a

national priority. In doing so, it made a case for the positive benefits from creating habitat for

fisheries and established a number of broad guiding principles that are expected to positively impact

the way in which artificial reefs are developed. The Act directed the U.S. Army Corps of Engineers

(COE) to institute a permitting and regulatory framework within which artificial reefs would be

developed. In addition, the Act mandated that the National Marine Fisheries Service (NMFS)

develop the National Artificial Reef Plan (1985) (Plan), intended to establish national standards and

provide broad national guidance for creating regional and state plans for artificial reef development.

Implementation of the Act and the Plan resulted in a permit and regulatory program under the COE

dredge and fill program. The sole authority provided to the NMFS was development of the Plan,

which was completed one year after enactment of the Act in 1985. True implementation, however,

occurred at the state level, evidenced by the magnitude of artificial reef development activity

undertaken by state programs over the last 16 years, including development of state artificial reef

plans.

IMPETUS FOR NATIONAL PLAN REVISION

Why should the Plan be revised? The Plan itself calls for periodic revisions, recognizing that

progress, including plan development, research, and data collection, would reveal new and better

ways to conduct programs. Such progress has been evident through the variety and frequency of

research and policy publications, periodic international conferences, and regional and local meetings

dealing with all aspects of artificial reef development and management. In addition, since the mid

1980s, the Gulf and Atlantic States Marine Fisheries Commissions have been providing a regional

forum for state artificial reef programs to come together to work on regional and national scope

issues. Finally, the recognition that artificial reefs are tools for fisheries management has contributed

to the need to re-evaluate our current national guidance and policies for artificial reefs.

The combination of these and other factors led the Gulf, Atlantic, and Pacific States Marine

Fisheries Commissions to request from the NMFS in 1996 that the states, through the Commissions,

be given the responsibility to take the lead in revising the Plan. In December 1996, the NMFS

agreed, and by letter encouraged the states to begin revising the Plan. Through a series of meetings,

some sponsored by the NMFS and some sponsored by the Commissions, the revision was completed

in December 1998. Soon thereafter, the three Interstate Marine Fisheries Commissions submitted

the document to the NMFS for consideration to replace the 1985 Plan and establish new national

policy on artificial reef development and management. In addition, the three Interstate Marine

Fisheries Commissions adopted the document as interstate policy, entitling the document Coastal

Artificial Reef Planning Guide (1998).
106

REVISED NATIONAL PLAN

During the process of revising the Plan, the states and commissions recognized the high quality of

the work done by the original plan writers, such that much of the original Plan is embodied in the

revision. Of significance, the National Standards were established by the Act and continue as the

broad principles under which all other policies and recommendations are established. Those

National Standards are as follow:

• enhance fishery resources to the maximum extent practicable;

• facilitate access and utilization by US recreational and commercial fishermen;

• minimize conflicts among competing uses of waters covered under this title and the

resources in such waters;

• minimize environmental risks and risks to personal health and property; and

• be consistent with generally accepted principles of international law and not create any

unreasonable obstruction to navigation.

While the first National Standard admonishes us to “enhance fishery resources,” the primary focus

of artificial reef programs over the past 16 years, and prior, has been enhancing fishing success

through the creation of known locations where fish would be accessible. The revision places a

greater emphasis on the habitat implications of artificial reef development. It should be noted that

the revision does not diminish enhancement of fishing success as an important goal of artificial reef

development, but rather elevates the importance of the habitat implications.

The original plan established four criteria that should be considered when determining the kinds of

materials that should be used in artificial reef development. Those criteria include the following:

1. function-effective habitat for marine organisms;

2. compatibility-compatible with the marine environment;

3. durability and stability- materials should be able to withstand the marine environment for

a desired length of time and remain stable on the bottom where placed; and

4. availability-readily available for use.

These criteria were deemed generally to be applicable, with the exception of “availability.” While

it is important that materials be readily available for use by artificial reef programs, it is inaccurate

to think of availability as a criteria for consideration of using a material, since if it is not available,

it will not be used. The revision has deleted “availability” as a criterion, while continuing to

recognize the importance of availability of suitable materials. In addition, the revision splits

“durability” and “stability,” because it was determined that, while the two are associated, they are

significantly different and should be treated separately. For example, a material can be quite durable

and be inherently unstable in salt water, such as an automobile tire. Conversely, it is possible for a

material to lack durability and yet be relatively stable.

As described above, materials used to create artificial reefs constitute an important programmatic

issue. In recent years, the issue of materials selection has also become quite controversial. Many

have heard the criticisms that artificial reef programs are nothing more than waste disposal
107

programs. Years ago, that criticism had a kernel of truth in it; however, more recently state programs

have strived to move to materials that follow the established criteria. The original Plan went to great

lengths to identify selected materials and describe their attributes. Today, the variety of materials

has increased to the point that it would be unwieldy to continue to address them all within the text

of the Plan. As a result, the revision incorporates, by reference, the document entitled Guidelines

for Marine Artificial Reef Materials (1997), developed by the Gulf and Atlantic States Marine

Fisheries Commissions. That document is currently under revision.

One of the most important issues addressed in the revision is qualifications for holding an artificial

reef permit. Currently, under the COE permitting program, any citizen of the United States can

request and receive an artificial reef permit by following established procedures and showing proof

of liability coverage. Unfortunately, the liability criterion has not been applied in most cases;

consequently, individuals with no capability to withstand a liability suit have been granted permits.

In addition, a fishing organization may be able to qualify, but could easily disband well before the

life expectancy of the reef they build has run its course. Who then is liable? This issue has not been

addressed. The revision recommends that the COE issue permits only to the state agency with

responsibility to manage marine resources. The drafters consider this appropriate because the state

agency 1)is legislatively authorized to exercise stewardship responsibility over marine resources,

2)can ensure compatibility with fishery management planning, and 3)can assume liability for the

life of the artificial reef. The language in the Act does not allow the COE to make this a requirement;

however, its appearance in the revision elevates it as an important issue that the COE should

consider and identifies it as an issue that should be addressed in any future amendments of the Act.

Mitigation has continued to be an issue that involves artificial reef development. Many cases have

emerged in which artificial reefs have been proposed as a way to mitigate for the destruction of

dissimilar habitats. The revision attempts to put in perspective the position of the states in this

regard, stating that if mitigation is to be considered necessary, it should be in kind/in place. The

revision recognizes that this cannot always be done; consequently, the revision strongly recommends

caution when applying artificial reefs as mitigation. For example, an offshore, high salinity artificial

reef should not be acceptable as mitigation for the loss of estuarine marsh.

The revision recommends that the COE require project objectives as a part of the permitting process.

All artificial reef projects should have well defined objectives that are consistent with fishery

management objectives. In addition, in order to determine of projects are successful in meeting

stated objectives, baseline evaluation and monitoring should be conducted, with follow-up

evaluation and monitoring to assess the change brought about by the project. The revision

recognized the importance of specifying compliance monitoring and performance monitoring, as

found in the original Plan. Compliance monitoring is required assure that program activities do not

significantly vary from permit requirements. Performance monitoring, while not required by most

permits, is equally important in determining whether stated objectives are being met, and equally

importantly to assess the overall impact of artificial reef development.

The revision emphasizes the importance of recognizing that artificial reefs should be fishery

management tools. Artificial reefs can be used to restore damaged habitats or can be used to enhance

habitats for selected species. There have been many discussions recently about using artificial reefs
108

to establish sanctuaries, or marine protected areas, as a way of addressing the criticism that

establishing a no-take area penalizes the citizenry by taking away reef areas historically open to

commercial and recreational fishing. In addition, we have many examples of using artificial reefs

as special management areas in which effort control and spatial and use conflict management

measures can be applied.

As mentioned above the draft Plan revision was submitted to the NMFS in late 1998. The draft has

undergone internal review by NMFS, and has been reviewed by the relevant federal agencies.

Currently, NOAA General Counsel is holding approval of the document until the new administration

has had an opportunity to evaluate its impact on federal fisheries policy. The next step is to publish

the document in the Federal Register and get public comment. It is not known when this might take

place.

REFERENCES

Atlantic, Gulf, and Pacific States Marine Fisheries Commissions. 1998. Coastal Artificial Reef

Planning Guide. Gulf States Marine Fisheries Commission, P.O. Box 726, Ocean Springs,

Mississippi 39566-0726. 45pp.

Gulf States Marine Fisheries Commission. 1997. Guidelines for Marine Artificial Reef Materials.

Gulf States Marine Fisheries Commission, P.O. Box 726, Ocean Springs, Mississippi 39566-

0726. 118pp.

Stone, Richard B. 1985. National Artificial Reef Plan. NOAA Technical Memorandum NMFS OF6. USDOC, NOAA, NMFS. 39pp. + appendices.
109

REEF FISH RESOURCES AND GAS PIPELINES ON THE

WEST FLORIDA SHELF: POTENTIAL CONFLICTS

Christopher C. Koenig

Felicia C. Coleman

Institute for Fishery Resource Ecology

Department of Biological Science

Florida State University

Kathryn M. Scanlon

U.S. Geological Survey

ABSTRACT

Marine protected areas (MPAs) placed appropriately provide promising options for the management

of exploited populations by protecting critical habitat, community structure and function, and

spawning populations. They also provide the unique opportunity to experimentally evaluate the

effects of anthropogenic impacts (particularly fishing) on the biotic and physical components of

ecosystems. Recently (19 June 2000), the Gulf of Mexico Fishery Management Council established

two MPAs in the northeastern Gulf of Mexico (GOM). The impetus for establishing these reserves

was strong evidence of fishing-induced changes in the demographics (especially changes in sex

ratio) of several economically important reef fish species. Herein, we discuss proposed construction

of two gas pipelines that would run through both MPAs. We are particularly concerned about the

effects of construction on essential fish habitat (EFH) both within and outside of the reserves. The

pipeline contractors must accurately show the degree of impact from construction activities. We

suggest that the ecological impact study provided by one of the pipeline construction companies has

not adequately shown this impact. Further, we find that in both cases, pipeline construction would

destroy critical habitat, compromise the ecological structure and function of resident biotic

communities, and undermine an otherwise unique opportunity to evaluate fishing effects on shelfedge reef fish populations.

We recommend that the pipelines be rerouted to areas outside of the reserves, and that particular

attention he paid to avoid live-bottom and high-relief habitat to the extent possible. We recommend

that new environmental impact studies be done to provide more realistic profiles of habitat. Further,

we suggest that a team of scientists develop for the Federal Energy Regulatory Commission (FERC)

and the Mineral Management Service (MMS) a standardized format for conducting such studies so

that valid comparisons can be made among different projects and different areas.

INTRODUCTION

Concern over extreme demographic changes in gag (Mycteroperca microlepis) populations of the

southeastern United States—including declines in the proportion of males, declines in the size and

age structure of spawning groups (Coleman et al. 1996, McGovern et al. 1998), and the apparent

occurrence of inbreeding (Chapman et al. 1999)—prompted the Gulf of Mexico Fishery
110

Proposed Pipeline

Routes:

Buccaneer

Gulfstream

Figure 4.1. Map of Florida and shelf waters showing the location of Madison-Swanson,

Steamboat Lumps, and Oculina MPAs and the proposed routes for Buccaneer

and Gulfstream gas pipelines.

Management Council to recommend closing portions of the west Florida shelf edge (50-120 m

depths) to fishing. On 19 June 2000, the National Marine Fisheries Service officially established two

marine protected areas (MPAs) in gag spawning habitat, known as the Madison-Swanson MPA and

the Steamboat Lumps MPA (Figure 4.1). The two areas combined cover over 200 nm2 and will

remain closed for a period of four years. 

Studies within the newly-formed Madison-Swanson and Steamboat Lumps MPAs and associated

control sites are already underway by scientists at a number of different state, federal, and academic

institutions. These studies include side-scan sonar and multibeam mapping, ROV (remotely operated

vehicle) video transect work, and studies of the community and behavioral ecology of resident

populations. Because the whole intent of MPAs is to exclude as many confounding anthropogenic

effects as possible, the reserve and control sites are being monitored to evaluate recovery from

fishing effects. 
111

Gas pipelines proposed to transit the northeastern GOM from Mobile Bay, Alabama, to near Tarpon

Springs, Florida, could cross both MPAs. We reviewed the draft environmental impact statements

that describe the potential effects of construction on Outer Continental Shelf (OCS) habitat. We

were particularly interested in the extent to which construction could disrupt the integrity of critical

shelf-edge habitat and the evaluation of fishing effects in these regions. We first describe the

pipeline construction process, as outlined by the construction companies—Buccaneer Gas Pipeline

Company and Gulfstream Natural Gas System—and then critique those portions of the Draft

Environmental Impact Statements (DEIS) provided by each company’s subcontracting firm,

Continental Shelf Associates (CSA) for Buccaneer, and Sea Byte, Inc., for Gulfstream. The intent

of this paper is to provide recommendations to these companies and to future oil and gas

construction projects on the OCS.

SHELF-EDGE REEF FISH POPULATIONS: A BRIEF REVIEW 

Most of the economically-important reef fish species of the southeastern United States are

overfished (Coleman et al. 2000). Many of them are protogynous hermaphrodites—fish that change

sex from female to male—and a great many of them co-occur in shelf-edge habitat (Koenig et al.

2000). Among the factors hindering effective management of these species are poor catch records,

poor collective memories of the historical state of fished populations, inadequate records of the

unfished condition (Jackson 1997), and a lack of political will to implement appropriate

management practices. 

The reductionist approach of single-species management compounds this problem because it

typically limits inquiry to the population dynamics of one stage in the life cycle of an exploited

species (the adults). It rarely considers other stages (larvae, juveniles, subadults) that are equally

important to population persistence and ignores the fact that exploited species form part of a

complex interacting ecosystem. 

The Magnuson-Stevens Fishery Management and Conservation Act of 1996 (NMFS 1996) provided

for substantive changes to this approach by suggesting that EFH and ecosystem-level processes are

important components of effective fisheries management. Admittedly, the definition of EFH is

broad—defined in the act as “those waters and substrate necessary to fishes for spawning, breeding,

feeding, or growth to maturity” (NMFS 1996). But the mandate is clear that EFH must be protected

and that potentially adverse effects on EFH from fishing and non-fishing activities (which would

include pipeline construction or other oil and gas-related activities) must give way to actions that

encourage habitat conservation. 

One important step toward management in the framework of ecological realities is the use of MPAs

(NMFS 1999, NRC 2000, Bulletin of Marine Science 2000). MPAs not only provide the opportunity

to observe reef fish population parameters and community structure in an unfished state, but they

also provide opportunities to experimentally evaluate the effects of fishing on specific behaviors,

demographics, ecological interactions, and habitat. For example, an MPA allows evaluating the

extent to which fishing that targets gag spawning aggregations selects for males and disrupts the sex

change process. 
112

Of particular interest in the GOM are the shelf-edge (50 – 120 m depth) reefs of west Florida, reefs

that have been fished for over 100 years (Camber 1955). As important as these areas are, neither the

direct nor the indirect effects of fishing on habitat or the associated reef communities have been

evaluated. Direct effects of fishing, in addition to removal of targeted species, include mechanical

damage to habitat due to mobile fishing gear, trapping, and anchoring. Indirect effects include

trophic cascades resulting from the removal of top-level predators (Hughes 1984, Hughes et al.

1987) and potential habitat loss resulting from removal of species that act as geologic agents

(Scanlon et al. in review, Coleman and Williams in review). One need look no further than the

EORR (Experimental Oculina Research Reserve) MPA off central east Florida (Figure 4.1) for an

example of extensive fishing-induced habitat destruction and the effects on benthic communities

(Koenig et al. 2000). 

Gag spawning aggregations occur in these shelf-edge regions from the eastern GOM to North

Carolina (Koenig et al. 1996, McGovern et al. 1998, Koenig et al. 2000). Yet, the area in the

northeastern Gulf between latitudes 280

 and 290 30' N at depths ranging from 50 to 120 m is

considered both the gag population center of abundance and the heart of the commercial fishery

(Schirripa et al. 1999). Many other economically important reef fish species also spawn in this

region, including scamp (Mycteroperca phenax), red grouper (Epinephelus morio), gray snapper

(Lutjanus griseus), red snapper (Lutjanus campechanus), vermilion snapper (Lutjanus

rhomboplites), red porgy (Pagrus pagrus), and others (Coleman et al. 1996, Koenig et al. 2000).

Thus, locating MPAs in this region is particularly important. 

PROPOSED PIPELINES ON THE WEST FLORIDA SHELF

Buccaneer’s proposed pipeline is approximately 411 miles long. It passes through roughly 200 miles

of critical shelf-edge habitat (but see comments below), including some 12 miles in the southwest

portion of the Madison-Swanson MPA. Gulfstream’s proposed pipeline is approximately 420 miles

long, crosses roughly 59 miles of shelf-edge habitat (~53 miles on the west Florida shelf edge and

~6 miles on the Alabama shelf-edge), 3.5 miles of which are in the northeast corner of the

Steamboat Lumps MPA (Figure 4.1). The Buccaneer pipeline is in somewhat shallower water than

the one proposed by Gulfstream. 

Pipeline occurring at depths less than about 61 m must be buried in the substrate. This is an

expensive process with destructive effects on habitat. Pipeline occurring at depths greater than 61

m is neither buried nor anchored to the bottom. However, this does not mean that construction is a

low-impact process at those depths. In order for the 1.0 m diameter pipeline to maintain a smooth

sigmoidal shape as it is laid from the barge to the seafloor, the barge must be secured in place by 12

anchors, eight forward of the barge and four aft. Each anchor measures about 5 x 6 m and weighs

at least 13 tons. The anchors are distributed radially from the barge by cables 7.6 cm in diameter;

the anchors and cables together cover a swath approximately one nautical mile wide. The barge

progresses along the pipeline route by drawing in the fore anchor cables, letting out the aft anchor

cables, and subsequently repositioning the anchors for another round. This action is repeated twice

within each mile, such that there are 24 anchor strikes per mile.
113

The extent of the habitat damage caused by this process is related to the compounded effects of

anchor-cable sweep (the extent to which anchor cables contact the bottom), anchor drag, and seastate. The anchor-cable sweep is greatest near the anchors as the barge is drawn forward due to the

considerable catenary in the cable line. When cables sweep the bottom, they act like trawls or

dredges, but with far greater force, literally raking away all habitat structure. Anchor strikes affect

less area than cable sweep, but an increased sea state will likely increase the damaging effects of

both. Neither company has considered the effects of sea state. 

Each company was responsible for conducting photo-video surveys along portions of the proposed

route and then comparing those videos to geophysical data (side-scan sonar imagery and seismic

reflection profiles) to determine the degree of relationship between the two. The MMS required that

the photo documentation surveys be conducted at depths shallower than 100 meters, even though

the proposed pipelines would cross habitat at greater depths. In the side-scan sonar data, dark,

medium, and light areas correspond to the acoustic properties of the seafloor. For example, a hard

rocky bottom would produce a dark image, and a soft-grained, sediment-covered bottom would

produce a light image. However, other factors (e.g., small-scale roughness of the seafloor, angle of

slope, and state of compaction of sediments) also affect the acoustic properties of the seafloor, and

hence complicate the interpretation of the acoustic image produced. 

CRITIQUE OF ESTIMATED IMPACTS TO SHELF-EDGE HABITAT.

Because we are most interested in the effects of construction on habitat important to reef fish, we

confine our comments to estimates of hard-bottom (carbonate rock either exposed or covered by a

thin veneer of sediment), and specifically “live-bottom” (hard-bottom with sessile epifauna)

coverage made by Sea Byte, Inc., (for Gulfstream) and CSA (for Buccaneer). 

 The ground-truthing exercises conducted by Sea Byte at both shelf (15 – 50 m) and shelf-edge (50

– 100 m, the greatest depth required by MMS for habitat delineation) depths revealed: (1) that areas

with light acoustic reflectivity had 15% live-bottom coverage, (2) that areas with moderate

reflectivity had 21% live-bottom coverage, and (3) that areas with dark reflectivity had 53% livebottom coverage. Although the percentage of live-bottom increased with the degree of

reflectivity—that is, the lower the reflectivity, the lower the percentage of live-bottom—the

relationship was a poor indicator of the presence of live-bottom. For instance, when similar studies

were conducted inshore by Seabyte (1999), they found a high degree of correlation between dark

reflectivity and the presence of live-bottom. This was not the case on the OCS. Based on that

finding, Sea Byte decided that the geophysical data did not adequately represent the extent of livebottom in the OCS. Thus, they relied upon a series of parallel photo-video transects made along the

entire pipeline route (to 100 m depths), interpolating the extent of live-bottom between the transects.

This approach provided nearly 100% coverage of the proposed impact area and gave more realistic

estimates of live-bottom coverage.

The proposed route of the pipeline relative to shelf-edge habitat is ambiguous in the documents

prepared for Buccaneer by CSA. In fact, the documents provide three different proposed pipeline

paths relative to depth: one in which the pipeline appears to be shallower than the 100 meter isobath

over all of its length (CSA 1999, 2000a), one in which it deeper than 100 m in several places (CSA
114

2000b), and yet a third in which the 300 ft. (91 m) isobath and the 100 m (328 ft.) isobath are

indistinguishable (CSA 2000c). If the first route is correct, then the pipeline route covers about 200

miles in shelf-edge depths. If the second route is correct, then it covers about 100 miles. For

purposes of discussion, we used the first map presented in the series for evaluation. This choice was

completely arbitrary because the maps are so confusing.

Continental Shelf Associates, Inc., (Buccaneer) performed photo-video documentation surveys over

75 miles of the shallower pipeline route across the west Florida shelf (from shore to about 50 m

depths). However, they only surveyed about 8% (15 of the nearly 200 miles) of the route through

the more critical shelf-edge habitat, sampling only six sites, four of which were clustered in a 20-

mile segment midway along that line and none of which were deeper than 100 m. Unlike Sea Byte,

CSA found, as stated in their summary, an “exceptionally high degree of correlation” between the

geophysical data and their photo-documentation of live-bottom (CSA 1999) and that the geophysical

data, if anything, overestimated the amount of live-bottom (CSA 2000a). 

This interpretation by CSA is in part due to their assumption that live-bottom only occurred in

geophysically-determined hard-bottom habitat. However, closer examination of their maps shows

that the correlation—much like that found by Sea Byte—is not particularly good for predicting how

much live-bottom exists in an area. Live-bottom exists to some extent in all geophysicallydetermined zones. For instance, in one segment (plot 4 of segment 2 on shelf edge habitat in CSA

1999), live-bottom was found in video transects in “light” areas (not identified in the map legend,

but presumably sediments ranging in texture from silty to fine or medium grained sand, based on

the text), while very little live-bottom is found in “dark” areas, 

We found interpreting CSA’s maps difficult because the terminology in the text and the maps was

unclear. For instance, the self-contradictory phrase “carbonate (limestone) sediment” is used

repeatedly. Limestone, by definition, is a rock, not a sediment. One can only guess what this term

is meant to describe, because it is not defined in the map legend or in the text. Furthermore, the map

legend contains a number of units (e.g., “exposed carbonate (limestone) sediment,” “sediment

veneer over carbonate (limestone) sediment,” “sand covering carbonate (limestone) sediment with

scattered outcrops,” “exposed carbonate (limestone) sediment with areas of outcrops and sand

pockets,” and “scattered outcrops”) which appear to have considerable overlap, are ambiguous or

contradictory, are contrary to common geological usage, and are never defined. As a result, these

maps are of little use either for delineating or for quantifying benthic habitats. 

Considering CSA’s inadequate photo coverage of the shelf-edge habitat and the apparently low

concurrence between the geophysical patterns and their photo-documentation data, we consider that

their report grossly underestimates the extent of shelf-edge live-bottom coverage. Although it is not

unreasonable to quantify biotal coverage and sessile invertebrates potentially impacted, it is more

important to determine construction impacts to the actual habitat, regardless of the density (or biotal

coverage) of the individual benthic species. For example, CSA’s (2000c) quantitative survey states

that about 8% of the construction route is live-bottom habitat, but that only 12.5% of that is covered

by sessile invertebrates. They have interpreted this to mean that 1% (.08 x .125) of the live-bottom

habitat would be destroyed. We caution that the emphasis should be placed on the areal coverage
115

of the habitat, and not on the areal coverage of the individual organisms. The latter leads to an

erroneous perception that vastly underestimates the impact on habitat of pipeline construction.

DISCUSSION AND RECOMMENDATIONS

Considerable concern exists among scientists and conservationists about the rate of habitat loss

worldwide. In fact, habitat loss is considered the primary reason for declines in biodiversity

(Wilcove and Wilson 2000). The litany of agents responsible for the declines include water

diversion projects, hydropower dams, agricultural practices, and urbanization. To these can be added

habitat destruction caused by mobile fishing gears—trawls and dredges—which have devastated

many low-relief live-bottom habitats (Dayton et al 1995, Auster et al. 1996, Watling and Norse

1998). There is strong interest in monitoring these effects and limiting them to the extent possible.

Pipeline construction is just one more effect that should be closely evaluated. Such construction is

not constrained in the same way that mobile fishing gear is because (1) it can affect areas typically

inaccessible to trawls; and (2) it has the potential through sheer force of impact to cause far more

damage to habitat, reducing high relief structure to rubble. 

We are very concerned by the methods used to delimit habitat in the reports of proposed pipeline

construction in the northeastern GOM. The reason that accurate estimates of different habitat types

are so critical is that these numbers are used to evaluate the extent of damage caused by pipeline

construction. For purposes of these studies, the MMS applied the “low-relief live-bottom

stipulation,” which is that those applying for oil and gas leases conduct photo-documentation

surveys of the sea floor within the project area only at depths of 100 m or less (Gulfstream 2000).

The MMS considers live-bottom to be “seagrass communities or those areas which contain

biological assemblages consisting of sessile invertebrates (such) as sea fans, sea whips, hydroids,

anemones, ascidians, sponges, bryozoans, or corals living upon and attached to naturally-occurring

hard or rocky formations with rough, broken, or smooth topography; or areas whose lithotope favors

the accumulation of turtles, fishes, and other fauna.” No surveys are required in areas of greater

depth. 

We find the depth restriction of 100 m not only arbitrary, but exclusive of a number of important

types of marine habitat. Of particular concern are exclusions of deep-water reef fish habitat and coral

and sponge communities. For instance, important reef fish habitat exists at depths greater than 100

m, including essential habitat for tilefish Lopholatilus chamaeleonticeps, blueline tilefish

Caulolatilus microps, Warsaw grouper Epinephelus nigritus, snowy grouper E. niveatus, speckled

hind E. drummondhayi, and yellowedge grouper E. flavolimbatus (Parker and Mays 1998). All four

of the groupers are considered at risk of extinction by the American Fisheries Society (Musick et

al. 2000), and two of them—Warsaw grouper and speckled hind—are now considered threatened

(Coleman et al. 2000), thus requiring special management attention. Extensive live-bottom (65%

coverage) exists at depths of 120 to 160 m off the southwest Florida shelf (Phillips et al. 1990).

Further, beds of the deep-water coral Lophelia pertusa (= L. prolifera) occur in water depths of 439

to 512 m some 40 miles east of the Mississippi delta. Similar banks off Norway and the Faeroe

Islands, which support enormously diverse biota, have suffered tremendous losses (Roberts 1997).

Although little is known of these habitats—or perhaps because so little is known—they should be

quantified in estimates of habitat impacts from oil and gas construction projects. Thus, we
116

recommend that photo-documentation surveys include all depths at which any oil and gas activities

are to occur. 

The most significant source of habitat damage during pipeline construction is due to anchor cable

sweep. Buccaneer (2000) estimated the damage to range from one to one-and-a-half acres per anchor

strike, or about 24 to 36 acres per construction mile. Gulfstream (2000), on the other hand, estimated

that habitat damage would be on the order of 114 acres per construction mile at depths ranging from

61 m (200 ft) to 100 m (328 ft). It would be much greater at shallower depths because the lower

angle of the anchor cable causes more of it to touch the bottom. Thus, the two estimates of habitat

damage due to cable sweep differ three- to nine-fold, depending on the construction depth. The

estimated area of damage provided by Gulfstream is more realistic because it is based on

engineering considerations (e.g., sweep features of each anchor cable and relationship to depth) and

historical observations. 

How could these companies, running parallel analyses along parallel routes, come to such disparate

conclusions about the relationship between the geophysical data and photo ground-truthing, in

estimating anchor-cable sweep damage, and in estimating habitat coverage? Further, why did both

companies choose routes that went specifically through marine protected areas? 

We found it difficult to make comparisons between the habitat quantification documents provided

by the two pipeline construction companies because the methodologies used were not standardized.

In fact, CSA did not even follow standard survey or statistical methodologies, making comparisons

impossible in most cases. To avoid problems of interpretation, we recommend that a team of

scientists develop standard methods and terminology for use by the FERC and the MMS.

Subcontractors should also be required to provide statistically-sound error values in their estimates

of areal habitat coverage.

It is unclear why both Buccaneer and Gulfstream chose pipeline routes that transit MPAs. They

either were wholly unaware of the Gulf Council’s July 1999 recommendation that these sites be set

aside as MPAs or they categorically chose to ignore these boundaries. Regardless which of these

scenarios is true, there is little doubt that significant damage in critical habitat would occur and

experimental studies of reef fish reproductive behavior and the effects of fishing on habitat and

ecosystem function would be compromised. If the boundaries of these MPAs are not respected a rare

opportunity to evaluate fishing effects might be lost. Thus, we recommend that oil and gas

construction projects hold MPAs as sacrosanct and avoid all anthropogenic disruption.

MPAs likely will form an important component of future fisheries management plans. To wit, on

26 May 2000, President Clinton signed an Executive Order calling for the expansion of the system

of MPAs throughout the United States (Federal Register vol. 65, no. 105, pp. 34909-34911). The

intent is to “(a) strengthen the management, protection, and conservation of existing marine

protected areas and establish new or expanded MPAs; (b) develop a scientifically based,

comprehensive national system of MPAs representing diverse U.S. marine ecosystems, and the

nation’s natural and cultural resources; (c) avoid causing harm to MPAs through federally

conducted, approved, or funded activities” (italics ours). This Executive Order sets the tone for
117

future conservation of living marine resources. Our respect for these resources and the MPAs that

contribute to their sustainability translates into a respect for future generations.

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Grace. 2000. Protection of fish spawning habitat for the conservation of warm-temperate reeffish fisheries of shelf-edge reefs of Florida. Bull. Mar. Sci. 66(3):593-616.

McGovern, J. C., D. M. Wyanski, O. Pashuk, C. S. Manooch, III, and G. R. Sedberry. 1998.

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Coast of the southeastern United States during 1976-1995. Fishery Bulletin 96:797-807.

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Sci. of the Gulf and Caribbean. 10(1):125-128.

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Gilmore, J. T. Golden, D. S. Ha, G. R. Huntsman, J. C. McGovern, S. J. Parker, S. G. Poss, E.

Sala, T. W. Schmidt, G. R. Sedberry, H. Weeks and S. G., Wright. 2000. Marine, estuarine, and

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characteristics, catches, and life history summaries. U.S. Dep. Commer. NOAA Tech. Rep.

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Florida shelf. Amer. Zool. 30:65-75.

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Assessment 3.0. Report to the Gulf of Mexico Fisheries Management Council.

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to forest clearcutting. Conservation Biology 12(6):1180-1197.

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THE ROLE OF FISHERMEN AND OTHER STAKEHOLDERS IN THE

NORTH SEA RIGS-TO-REEFS DEBATE

Mark Baine

Jon Side

International Centre for Island Technology

Heriot-Watt University

Orkney Islands, Scotland

ABSTRACT

The North Sea rigs-to-reefs debate has moved forward with the creation of a multi-stakeholder

steering group to oversee development of independent research. Given the sharp division in stakeholder opinion, this group represents a proactive approach to assessing the potential for the

formation of reefs using redundant oil and gas platforms. This paper examines the historical

approach to the concept adopted by major North Sea stakeholders against a background of political

landmarks including the 1995 Brent Spar incident. It examines in detail the reaction of fishermen

to calls for offshore and nearshore reefs, noting in particular the importance of liability, loss of

access, and safety concerns. The fishing industry remains neutral about the benefits of inshore reefs;

the industry remains, however, committed in opposition to offshore reef creation, especially when

combined with a no fishing policy. The environmental group Greenpeace is opposed to any rigs-toreefs initiative, seeing this as a means by which offshore operators can circumvent the OSPAR

Decision 98/3, which requires complete removal of offshore installations. The importance of cost

and the existence of willing reef beneficiaries are highlighted as important to the acceptance and

success of a nearshore rigs-to-reefs venture. Offshore reef creation faces numerous political hurdles.

The importance of a genuine stakeholder dialogue to integrate scientific and political thinking and

avoid the recurrence of an event similar to the Brent Spar, is stressed, the paper concluding that

fishermen hold the key to the success of rigs-to-reefs ventures in the North Sea, their co-operation

and participation essential in the promotion of a concept that has for so long been promoted to them.

INTRODUCTION

The potential for the ‘rigs-to-reefs’ concept to be implemented in the North Sea has always been a

source of contention between scientific, environmental, fishing and offshore sectors. In the wake

of the Brent Spar incident, the concept has come under increasing scrutiny from all stakeholders.

The investigative effort has not been a proactive one amid the more general debate on North Sea

abandonment and sea disposal, but instead a reactionary link among all stakeholders on an issue that

has not been thoroughly evaluated and that is shrouded in suspicion and mistrust.

This concept’s applicability in a North Sea context has been subject to scientific appraisal and

speculation over the past two decades (ICIT 1991; Picken 1992; Side 1992; Aabel et al. 1997; Baine

1995, 1998; Soldal et al. 1999) showing that fish are attracted to platforms, although only with

cautiously mooted biomass estimates (ICIT 1991; Soldal et al. 1999; Picken et al. 2000). Thorough

programs of scientific research have been promoted to bridge the gaps in knowledge (Aabel et al.
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1 Guidelines and Standards for the Removal of Offshore Installations and Structures on the Continental Shelf and in the

Exclusive Economic Zone (developed in response to Article 60(3) of the 1982 United Nations Law of the Sea

Convention).

2 Oslo Commission Guidelines for the Disposal of Offshore Installations at Sea 1991, OSPAR Convention for the

Protection of the Marine Environment of the Northeast Atlantic 1992, UK Petroleum Act 1987, UK Food and

Environment Protection Act 1985.

1997); however, scientific research to date does not induce the confidence needed to justify the

initiation of a rigs-to-reefs program (in any form) against a background of political scepticism.

Many of the social and political issues inherent in the North Sea rigs-to-reefs debate have been

ignored or devalued, much to the dismay of fishermen who see these issues as important as and perhaps more crucial than any program of scientific research. The concerns of fishermen regarding any

form of sea disposal of offshore platforms, for example, have been publicly stated since the early

1970s, yet these concerns are often ignored in contemporary limited scientific evaluation of a

conceptual abandonment option. Indeed, such a concept if it were to proceed would have significant

ramifications for fisheries and environmental management throughout the north-east Atlantic region.

This paper addresses the socio-political issues involved in the debate, concentrating on the relationship between Scottish fishermen (through the Scottish Fishermen’s Federation [SFF]) and offshore

operators. Information here is from direct contact with stakeholder representatives and output from

working groups and workshops. This primary research is supplemented by the analysis of published

literature on abandonment and environmental management, stakeholder policies and legislation. The

paper ends with a discussion of the present status of the rigs-to-reefs debate in the North Sea.

FISHERMEN, OFFSHORE OPERATORS AND THE GOVERNMENT –

A HISTORICAL PERSPECTIVE

With the emergence of petroleum activity in the North Sea in the early 1970s, it was recognized that

fishermen would be inconvenienced. The government, however, assured the fishing industry that

once the oil companies had completed their operations, all installations would be removed and the

seas returned to the fishermen in the condition in which the oil industry had found them. The 1958

Geneva Convention on the Continental Shelf backed this assurance, and fishermen accepted it (Allan

1986, 1992, 1994).

As the years passed, however, the fishing industry looked on with mounting concern, as assurance

of complete removal began to evaporate. The industry was informed that complete removal might

not be possible for reasons including cost, the technical plausibility of complete removal operations,

and the perceived uncertainty of future legislation regulating the abandonment of offshore oil and

gas installations. In response, the fishing industry maintained its argument that promises had been

made as to the complete removal of installations and that those promises should be kept.

The development of the International Maritime Organisation’s 1989 Guidelines1 and other international and UK legislation2

 gradually led to the general acceptance of toppling and partial removal
122

as abandonment options. The fishing industry, while committed to complete removal, believed it

had been forced into instigating a damage limitation exercise. Accordingly, the fishing industry

proposed that it would press for six minimum safeguards (Allan 1994) in the event of a case-by-case

approach to abandonment. In summary, these address the witnessing of removal operations by the

fishing industry; debris clean-up operations; confirmation of debris clearance by side-scan and trawl

operations; regular inspection of abandonment sites; establishment of a compensation fund by the

government for loss of access to fishing grounds; and establishment of an additional compensation

fund for specific gear losses/vessel damage caused by oil debris.

A shift in SFF policy on abandonment, however, occurred in 1994, the main determinant being the

cost to the UK taxpayer of abandonment operations (ICIT 1994). This policy was developed before

the Brent Spar incident and before the “Westhaven” tragedy. In the UK, the percentage of total

abandonment costs borne by the state is estimated to be in the region of 50-70%. From available

estimates of total costs of partial and complete removal of North Sea installations ICIT (1994)

concludes that the government may be able to make savings in the region of £1.25-1.75 billion in

tax revenue if partial removal is adopted as the main abandonment route. There is, therefore, an

obvious economic incentive in considering partial removal options compared with complete

removal. ICIT (1994a) further considers the implications of the above savings in a wider remit

involving the likely cost to fishermen of installations remaining partly in place, namely through loss

of access and damage to fishing gear. In doing so the study utilizes the compensation criterion

suggested by the economists Kaldor (1939) and Hicks (1939), which in summary suggests that a

project is only worthwhile if the financial gain is able to compensate those who lose out from the

project, thus ensuring that no one is worse off as a result of the project (the study notes that the

Kaldor-Hicks principle does not take account of any moral obligation). In this instance ICIT (1994)

postulates that “it is highly unlikely that the cost of loss of access or future losses of gear by

fishermen would exceed £1.25 billion,” the estimated (lower) cost of requiring complete rather than

permitting partial removal. Include the original assurance by the government that the structures

would be entirely removed, the prospect that certain areas of the seabed will be unavailable to the

fishing industry and the potential for damage to fishing gear that may result from the migration of

debris as the partially abandoned structures degrade, it seems reasonable to conclude that by

operating a program of partial removal as opposed to complete removal the government and offshore

operators are set to gain financially to the detriment of the fishing industry. It therefore seems

reasonable that the fishing industry would expect compensation not only from the offshore

operators, but also from the government, bearing in mind that they both gain financially from the

situation. 

Despite the strong moral argument for complete removal of offshore installations, the SFF have no

wish to see the majority of abandonment (complete removal) costs being met by the taxpayer in the

form of lost revenues from Petroleum Revenue and Corporation Tax (ICIT 1994). Whereas

previously the SFF sought complete removal and nothing else, their change in policy recognizes the

financial burden to the taxpayer and accordingly establishes a number of objectives that recognize

partial removal as a possibility. These are:
123

• To minimize risk to fishermen, to their vessels and gear and to minimize the areas of the

seabed that will be lost to fishing in perpetuity as the result of the abandonment of partially

removed structures.

• To ensure adequate compensation to fishermen for any damages or losses incurred as a result

of the abandonment of partially removed structures and to seek the establishment of simple

mechanisms for such settlements.

• To ensure that fishermen, government, the offshore industry and the public understands the

reasons for its change in policy. 

A number of principles have also been established to guide all aspects of this policy (ICIT 1994)

including:

a) The “Polluter Pays Principle”

In this instance the premise is that any costs to the fishermen should be recovered from the

polluter. This policy will depend upon the transfer of liability for abandonment; if to the

government then it should accept responsibility for compensation; however, if not then the

polluter pays principle should apply.

b) Compensation for damage and loss should be in accordance with the “General Principle of

Strict Liability” and should be adequate and no more than adequate

In this instance a call is made for the avoidance of costly and lengthy court actions for claims

in favor of a “formal arrangement...for the consideration of such claims that accords with

the principles of strict civil liability” where the incident has occurred in areas where fishing

is legal. Any encroachment of the safety zone, for example, should not be dealt with in this

manner.

c) That equity between the present and all future generations of fishermen should be a guiding

principle

Any compensation accepted for loss of access in perpetuity must be accepted on behalf of

fishermen now and of fishermen of the future.

FISHERMEN, ARTIFICIAL REEFS, LOSS OF ACCESS AND SAFETY 

It is difficult to glean the attitude of fishermen about the prospects of an artificial reef created from

an abandoned offshore facility without the politics of offshore abandonment in general clouding the

issue. It is also apparent that fishermen’s actions often do not reflect their words, unsurprising in

view of the very contentious nature of the issues involved.
124

At the 1994 conference on “Managing the Environmental Impacts of Decommissioning and

Abandonment Offshore,” Aberdeen, a representative from the Scottish Fishermen’s Federation,

made the following statement:

“We are also somewhat bemused and amused to hear of suggestions that toppled

platforms may become artificial reefs. The main experiences of these have been in

warm climates. The North Sea is totally different in climatic and fishing terms.

However, it is fair to state that one or two Constituent Association members of the

SFF have been prepared to co-operate with artificial reef projects targeted for

nearshore locations.”

This statement is fairly representative of North Sea fishermen’s views on artificial reefs. They do

not recognize any potential benefits from offshore reef creation, whereas in certain situations they

may see some value in placing a reef nearshore. This view reflects recognition of the general

concept of artificial reefs and is not specifically geared towards dismantled offshore installations.

The formation of nearshore reefs has readily identifiable benefits in its nearshore location, most

notably easier accessibility for nearshore fishermen and the greater potential for targeting specific

resources such as lobster and crab. Fishermen also recognize the role that artificial reefs may play

in conservation of nearshore resources, in providing safe havens and/or the exclusion of mobile

fishing gear from an area. Artificial reefs exist in Poole Bay, England and Torness, Scotland, and

have two general points in common: (1) they were both constructed from waste material, and (2)

they were both research-orientated. The Poole Bay artificial reef has shown distinct fisheries

enhancement properties particularly in relation to lobster populations (Jensen and Collins 1995);

however, the program of research has been discontinued on the Torness reef (Todd et al. 1992).

Picken (1992) and Picken et al. (2000) also refer to the attempts to place a reef in the Moray Firth,

Scotland. In 1987, a potential project entitled SPARE (Scottish Pilot Artificial Reef Experiment)

was developed by Aberdeen University with the support of the Scottish Fishermen’s Federation and

the Scottish White Fish Producers Association to research the use of redundant mud modules as

artificial reefs with particular emphasis on the fisheries implications. The project, however, did not

proceed because funds were not sufficient. Aberdeen University is presently still pursuing, with the

support of the same fisheries organizations, the possibility of placing a high-profile steel reef to

mimic the potential effects of placement of dismantled parts of offshore installations nearshore. The

support of fishermen is therefore available for such experimental projects.

The situation becomes confusing when we take a closer look at offshore reef creation. There is very

little support from fishermen for offshore reef deployment. Their doubt in any benefits to fish or

fishermen is normally expressed in response to comparisons between the North Sea and the Gulf of

Mexico, in particular the differences in fishing activity and environmental and climatic factors.

There is a valid argument against such comparison, but the available information from North Sea

studies indicates quite strongly that fish are attracted to offshore installations (ICIT 1991; Picken

1992; Side 1992; Aabel et al. 1997; Baine 1995, 1998; Soldal et al. 1999). This information should

provide a basis for analyzing the prospects of offshore reef creation in the North Sea. Fishermen

have also been known deliberately to fish close to offshore installations and along pipeline routes

to take advantage of what they know is a fish aggregation response to their presence. Picken et al.

(2000) quote one example of the financial benefits associated with such aggregation in the North
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3 OSPAR Decision 98/3 on the Disposal of Disused Offshore Installations 1998

Sea, when “a fishermen was fined £8,000 for repeatedly fishing within the 500m zone around

platforms, during which time over £200,000 worth of fish were caught.”

Fishermen are aware of the fish aggregating properties of offshore installations in the North Sea.

Their distinct opposition to the formation of offshore artificial reefs, however, is based more on

safety and political considerations, and represents a defiant opposition to the offshore industry.

Fishermen also see offshore artificial reef creation as a potential excuse or additional reason offshore

operators could use in their arguments for partial abandonment or toppling of individual

installations. The fact that the structures do attract fish does not help their situation, and has

probably been recognized as such for many years. 

Reef creation, especially offshore, has the same issues of liability associated with partial removal

and toppling, such as loss of access and potential damage to fishing gear and personnel from impact

on abandonment residues. If a platform is toppled or partially removed, the government has

proposed that a 500m “no fishing zone” remain in place for safety purposes (Select Committee

1996). This proposal was made in advance of the recent OSPAR Decision [July 1998]3

, but is still

of relevance in certain scenarios. During the operational lifetime of platforms, fishermen were

excluded from the 500m safety zones, and in the instance of partial removal they will have lost

access in perpetuity to such prescribed zones. The government and offshore operators do not

consider the loss of access claim to be proven (ICIT 1994). The SFF stated to the Select Committee

of 1996 “Where the SFF believes it reasonable it will pursue a claim on behalf of present and future

generations of fishermen for adequate compensation for the loss of access to fishing grounds in

perpetuity...Any settlement will be made into a fund established on the principle of equity for all

fishermen of present and future generations.” The United Kingdom Offshore Operators’ Association

(UKOOA), however, did not favor compensation for loss of access, stating, “we do not see from our

admittedly non-fishing background the problem with the North Sea as being lack of access; we see

the problem as being lack of fish.” The Committee, in its conclusions, agreed with the government

and offshore operators that loss of access was not proven, going so far as to state that “some fishing

free areas, however small, may help to protect dwindling fish populations; in the North Sea the

decline of fish populations is a serious concern.”

It is very difficult to prove the ‘loss of access’ argument, as noted by ICIT (1994). This difficulty

results from the variability of fisheries that are natural systems and the associated variation in

fishermen’s earnings as a result of these fluctuations, but also skill, market price and level of effort.

ICIT (1994) identify that the only possible way of proving ‘loss of access’ is through a process of

argument, related to:

1. the occupation of different grounds by fish throughout a season; these variations are known

to fishermen who then utilize their knowledge to fish grounds which yield the greatest catch

per unit effort;

2. the fact that no loss of earnings will occur through no lack of access; 
126

3. the fact that loss of access to an entire fishing ground will result in loss of earnings

represented by the loss of catch associated with this ground; and

4. postulations surrounding the grey area that lies between points two and three, which suggests

that loss of earnings correlates with the proportion of grounds lost.

One of the major arguments against the ‘loss of access’ claims is that fish move and fishermen

merely need to redirect their effort. The problem with this argument is that although an equivalent

level of catch may be achieved, there may be an increase in effort expended to achieve it, with

fishermen thus fishing at a net loss compared with the situation where there is no ‘loss of access.’

If fishermen expend the same level of effort, it can equally be maintained that there may be a

reduction in catch which again results in a net loss compared with the situation where there is no

‘lack of access.’ ICIT (1994) do, however, warn that given the natural fluctuations that occur in

fisheries, it is again very difficult to relate loss of earnings to ‘loss of access’ and that a “substantial

loss of access would have to occur before this was demonstrable...,” there always existing the

possibility that in some years natural fluctuations will be responsible for loss of earnings.

Other arguments against the ‘loss of access’ claim (ICIT 1994) include the following:

• fishermen achieve their EC quotas so there is no loss of catch. This argument becomes

invalid in light of the above discussions regarding effort;

• platform remains provide a ‘reef effect’ and are a gift either through conservation promise

or aggregation properties. However, fishermen are skeptical of this notion, believing that

fishing such areas, if legal, would present increased risk to personnel and equipment.

Secondly, any aggregation may also be viewed as removing fish from surrounding fishery

and this constitutes an argument for loss of access; and

• platforms create obstacles to fishermen but also provide potential breeding and nursery areas

for fish stocks that have a conservation value which will ultimately benefit the fishermen.

They may provide additional sustainability to a fishery in the same way that prohibition

areas do, but the scale and degree to which this would occur is subject to much speculation,

particularly given the small areas that will exist around platforms.

The SFF also argued to the Select Committee (1996) that compensation was due for damage to

fishing gear and boats and injury or death as a result of offshore installations and associated

residues. The government believes this to be a matter for affected parties and owners. The SFF also

reiterated the difficulty in proving that such debris was responsible for any damage and that it

preferred the establishment of a simple mechanism to deal with compensation. The Select

Committee (1996) agreed with the government that it was a matter for affected parties and owners;

however, it did “agree in principle with the claims for compensation by fishermen.”

The basis for such claims is the ‘polluter pays principle’ and relates to the two situations whereby

such damages and losses occur in areas where fishing remains lawful and those areas where fishing

is illegal, i.e. within the 500m safety zones that are likely to be established upon abandonment. 
127

With the government refusing to accept liability for abandonment residues, the operator becomes

responsible for any damages or losses occurring in areas outside the safety zone, and under the

general principles of strict liability, fishermen need only prove the cause of damage. Compensation

would be sought, therefore, if previous assurances regarding the risk of movement of residues

outside the safety zone were found to be wanting in practice (ICIT 1994). The pursuit of such a

compensation claim through the courts is generally seen as an unfavorable option, both in the

attendant publicity to offshore operators and in the likely event that the cost to fishermen would be

grossly disproportionate to the damage. This explains the preferred establishment of a simple

mechanism to deal with such claims, a mechanism, which at its simplest would involve the provision

of compensation by the operator where such damage is shown to be attributable to abandonment

residues. In the event that no one operator is found attributable such a claim would be best directed

to a collective operator’s fund handled by UKOOA.

Regarding claims for damage within a 500m safety zone, a different process would apply, as fishing

within such zones would be illegal and the vessel skipper would be subject to prosecution. There

are possible defenses of safety zone infringements, including adverse weather conditions, but it is

highly unlikely that a claim would be pursued by fishermen for damage incurred as a result of

infringement especially if a compensatory mechanism was in place for loss of access. Such a claim

would therefore need to be pursued through the courts.

A compensation fund for fishermen was established in 1975 by UKOOA for loss and damage to gear

arising from the presence of non-attributable oil-related debris. This fund also provides for loss of

fishing time as a result of any such damage depending upon the circumstances. When the debris is

attributable to a specific operator, the claim is made directly to the oil company; however, where

non-attributable the claim is made to the fund which is administered by fishing industry

representatives. The average number of claims settled between 1975 and 1990 by the fund was 90%.

In general, the greatest portion of claims is for damage to gear. The value of claims increased from

£15,000 in 1976 to £193,000 in 1990, although much of this can be related to inflationary factors.

Average settlement was approximately £2,000 per claim. No known examples of settled claims

arising from safety zone infringement exist (ERT 1993). 

The safety risk posed to fishermen by the presence of abandonment residues is perhaps best

envisaged when we consider the events surrounding the “Westhaven” tragedy in March 1997 (Side

1999). Four fishermen died after the fishing vessel “Westhaven” capsized while trying to free itself

after its trawl boards slipped under a gap between the seabed and the pipeline running from the Piper

field to Flotta oil terminal in Orkney. The incident, which occurred 100 miles northeast of Aberdeen,

has raised a number of questions regarding the risks posed to fishermen by free-standing areas of

pipeline (spanning). Fishermen called for a wide-ranging review of oil safety in the North Sea after

a sheriff’s inquiry into the disaster, even though the sheriff concluded that no one was to blame for

the tragedy. The sheriff’s recommendations included the initiation of talks between the HSE and oil

and fishing industries on fishing vessel safety around pipelines. Although this was an incident

involving a North Sea pipeline, it is relevant to the issues discussed here, as an indication of the level

of potential risk posed to fishermen from the presence of a structure abandoned at sea.
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OSPAR DECISION 98/3

On 20 June 1995, Shell UK decided to abandon its plans for the deepwater disposal of the Brent

Spar. The proposed deepwater disposal operation, vindicated by the completion of a Best Practicable

Environmental Option statement as required by UK law, had become “untenable” against a

background of activity by environmental activists. Three years were to pass, seeing a moratorium

on the disposal at sea of decommissioned offshore installations, before agreement was reached on

Decision 98/3 under the auspices of the Oslo and Paris Commissions. It entered into force in

February 1999 and is representative of a hardening attitude towards marine pollution and sea

disposal in the northeast Atlantic by member states. Decision 98/3, as we will see however, still

leaves much open to debate, and has perhaps served to focus even greater attention on the option of

rigs-to-reefs.

The preamble to the decision contains an affirmation that disposal should be governed by the

precautionary principle, which takes into account potential effects on the environment; and the

recognition that reuse, recycling or final disposal on land will generally be the preferred option for

the decommissioning of offshore installations. 

In definition, the decision describes a disused offshore installation as “an offshore installation, which

is neither: 

a. serving the purpose of offshore activities for which it was originally placed within the

maritime area, nor

b. serving another legitimate purpose in the maritime area authorised or regulated by the

competent authority of the relevant Contracting Party”

Point (b) of this definition means that an offshore platform which, upon the end of its productive

life, is utilized for some other legitimate purpose (such as an artificial reef), is not classified as a

disused offshore installation and would therefore not be subject to this decision. The OSPAR

Convention 1992 under Article 8, becomes the relevant guiding legislation, requiring that the

contracting party must authorize any placement of a disused installation or pipeline in the maritime

area for a purpose other than that for which it was originally designed or constructed. Such

authorizations is required to be in accordance with relevant applicable criteria, guidelines and

procedures adopted by the Commission, with a view to preventing and eliminating pollution.

The Oslo and Paris Commissions have taken a much stronger position on sea disposal than was

previously envisaged. Although an alternative reuse is still possible, sea disposal in any other form

is tightly restricted. Point 2 of the decision states that “The dumping, and the leaving wholly or

partly in place, of disused offshore installations within the maritime area is prohibited.” Derogation

is possible (Annex 1) provided that the competent authority of a relevant contracting party is

satisfied that an assessment procedure (Annex 2) has provided “significant reasons why an

alternative disposal is preferable to reuse or recycling or final disposal on land.” Categories of

alternative disposal are listed as:
129

4

 A precursor to OSPAR Decision 98/3

• all or part of the footings of a steel installation in a category listed in Annex 1 (i.e. weighing

more than ten thousand tons in air), placed in the maritime area before 9 February 1999;

• a concrete installation in a category listed in Annex 1 (i.e. gravity based concrete

installations, floating concrete installations) or constituting a concrete anchor base; and

• any other disused offshore installation, when exceptional and unforeseen circumstances

resulting from structural damage or deterioration, or from some other cause presenting

equivalent difficulties, can be demonstrated.

The Brent Spar incident has added a new dimension to the decision-making process of

abandonment, that of the power of public opinion; there is a growing view within Europe that the

North Sea should not be used as a ‘dump’ by the offshore oil and gas industry. The decision strongly

indicates that sea disposal has become the least favored option, and will only be allowed to proceed

in the strictest of circumstances. Given this legislative shift towards complete removal, it is not

impossible that the offshore industry and government may well see artificial reefs as a potential

“solution” (Baine 1998), a viable alternative use that will involve little extra expenditure over the

partial removal/toppling options, a situation more pronounced in the creation of an offshore reef.

Indeed, even if there were not a shift towards complete removal, the management of partially

removed/toppled structures such as artificial reefs may well provide a way of alleviating the fears

of those against partial removal and toppling, particularly as abandonment is now fixed in the public

eye. It is difficult to envision the situation where such a change in tactics by the operators and

government will be viewed as genuine, and not just as a cost efficient means of disposal under a

different guise. The ‘dumping in a different guise’ perception is an argument that will almost

certainly be used in the event of reef creation by its opponents. This was highlighted at the Oslo and

Paris Commission/s 1996 Working Group on Sea-Based Activities (SEBA) meeting when

Greenpeace International informed SEBA of the possibility of artificial reefs becoming a “tactic to

circumvent OSCOM Decision 95/14

,” even though the OSPAR Convention 1992 clearly states in

Article 1 (g ii) that ‘dumping’ does not include: “placement of matter for a purpose other than the

mere disposal thereof, provided that, if the placement is for a purpose other than that for which the

matter was originally designed or constructed, it is in accordance with the relevant provisions of the

Convention.” This perception is unfortunate, as the option of artificial reef creation is a viable one.

Kjeilen et al. (1995), for example, well in advance of the Brent Spar incident, studied the possible

deployment of the Odin platform, in the Norwegian sector of the North sea, as an artificial reef. 

In a debate held in March 1997 hosted by the Institution of Civil Engineers (Press Release, 13 March

1997) artificial reefs were on the agenda with the motion, “In the search for sustainability,

abandoned oil platforms are an enhancement to the sea bed,” being passed by delegates 27 to 23

with 4 abstentions. What was remarkable about this debate was that in response to the argument that

a small number of designated reef sites may help in offsetting the decline in North Sea fish stocks,

the Greenpeace representative stated that they were in favor of measures to improve North Sea fish
130

stocks and they were not “averse to the utilization of cleaned structures in designated areas but

oppose toppling platforms in situ.” 

This opposition clearly reiterates Greenpeace’s argument that reef creation may well become an

excuse for toppling, which they would view merely as ‘dumping in a different guise.’ However, it

does lend some weight to the argument of utilizing decommissioned structures or parts thereof as

nearshore artificial reefs or indeed in a specially designated area of the North Sea, similar to the

designated reef zones in the Gulf of Mexico. Greenpeace International, in collaboration with

SustainAbility, also developed the “Beyond Sparring” project, a consultation exercise that aimed

to help in the process of formulating an Integrated Removal Strategy (IRS) for oil and gas

installations (SustainAbility 1997). The lack of participation from the oil and gas industry in this

consultation exercise is notable. Other primary stakeholders were identified as engineering

contractors, local authorities and environmental campaigners. In the consultation document the

authors note the growing perception that offshore sea disposal “whether involving in-site toppling

or by another name (e.g. rigs-to-reefs) – is politically and socially unacceptable.” This position is

very much in contrast to the comments highlighted above. The “Beyond Sparring” project did not

aim to debate the merits of onshore vs. offshore disposal but instead began from the standpoint of

developing onshore re-use and recycling options, bringing all stakeholders together to discuss the

development of a more environmentally, economically and socially sound approach to onshore

disposal. The lack of interest from the oil and gas industry, however, led to Greenpeace’s handing

control of the project early in 1998 to what was perceived as a more neutral organization, the

European Commission. 

The Oslo and Paris Commission’s meeting at Sintra, Portugal which discussed the disposal of

disused installations as one item of a wide-ranging agenda, has been viewed as an historic meeting.

In general, all parties agreed to strive towards zero concentrations of man-made hazardous

substances and artificial radioactive substances in the marine environment. A cessation of

discharges, emissions and losses has a delivery year of 2020. The agreement has been welcomed by

such “green” oriented countries as Denmark and Sweden, and Greenpeace has seen the agreement

as a ‘vindication of decades of campaigning’ (Anon 1998). Indeed, in a press release dated 23 July

1998, Greenpeace stated that it was confident that the decision means no installation will be dumped

and no footings will remain. In the wake of Decision 98/3, Anon (1998) indicates that only 41

stumps of platforms will now even be considered to be covered by the derogation. The UK oil and

gas industry has expressed concern at the deal which it said “appeared to have been based on

political expediency.” Thus, while the OSPAR Decision’s exclusion of legitimate re-uses of offshore

installations from the definition of a “disused offshore installation” leads the way for the

consideration of artificial reef creation as a perfectly viable and legal proposition, the spirit of the

recent Sintra meeting suggests that implementing such a re-use option would require an exceptional

degree of political maneuvering to win acceptance from the remaining members of the Commission

through the procedural and consultation process prescribed in Annexes 2 and 3 of OSPAR Decision

98/3. 
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NEARSHORE AND OFFSHORE REEF CREATION FOR COMMERCIAL FISHERIES 

The common issue of liability remains one of the largest stumbling blocks in the pathway towards

any rigs-to-reefs initiative. The issue of liability (and ownership) in the event of damage caused by

abandonment residues to other sea users, most notably fishermen is a contentious one. As noted in

the 1989 IMO Guidelines and Standards, legal title to installations and structures that have not been

completely removed must be unambiguous, and responsibility for maintenance and liability for

future damages must be clearly established. More recently, OSPAR Decision 98/3 in its

preliminaries acknowledges that the national legal and administrative systems of the relevant

contracting parties need to make adequate provision for establishing and satisfying legal liabilities

in respect of disused offshore installations.

As discussed by Side et al. (1993), UKOOA’s position as highlighted in the Fourth Report of the

House of Commons Select Committee (Select Energy Committee 1991) is that the government

should assume liability. This position relates to the probable influencing of operator’s borrowing

power by such a continued liability, the practicality of such a long-term risk and the possible

sidelining of environmental factors when considering disposal options. The Select Committee

agreed, recommending that the offshore industry “set up a fund to indemnify the government against

civil claims and to cover legal and administrative costs” (Side et al. 1993). The government,

however, was not prepared to act as “defendant in perpetuity.” Liability is certain, therefore, to rest

with the operators with the establishment of an abandonment fund into which all UKOOA members

pay. Mr Eggar, however, addressing the House of Lords Select Committee on the Decommissioning

of Oil and Gas Installations (Select Committee 1996), indicated that the government did not have

a “closed mind on this” but that “we have not seen any compelling reasons as to why they [offshore

operators] should not retain that responsibility.” The Select Committee (1996) in its conclusions and

recommendations, acknowledging that installation remains may survive in the sea for hundreds of

years, noted that if an operator and partners were to disappear then no-one would be responsible for

liability. Also acknowledging the existence of problems associated with quantifying liability in

perpetuity for a structure, the Committee recommended further discussion between government and

the offshore industry on this matter. In Norway, the government will undertake ownership of an

abandoned installation with remuneration for such liability being supplied by the licensee

(Petroleum Committee 1993).

In the event of reef creation, a third possibility arises: the transfer of liability to the reef

beneficiaries. This is more likely to occur with respect to nearshore reef creation, or a designated

offshore site managed by a specific body, as reef beneficiaries or managers will need to be clearly

defined before such a placement occurs. In this instance, the user or manager could assume

ownership with the offshore operator providing some remuneration in lieu of any possible future

liability. This is unlikely to occur with offshore reef creation by toppling in situ (unless in a

designated reef area) as there are no readily identifiable reef beneficiaries who would wish to

assume such liability. In the present climate it is extremely doubtful that commercial fishermen

would consider such a move. 
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Nearshore Reef Creation

Steering away from scientific validation, the placement of any artificial reef for nearshore fisheries

management begs the question of its need, in line with existing and potential future management

options, restrictions and goals. The real benefits will accrue in a habitat-limited fishery where an

increase in biomass may result; through the combination of reef placement and a program of stock

enhancement whereby the reef provides suitable additional habitat to support the potential increase

in exploitable biomass; and where the reef helps as a central area to remove individuals from a

fishery, acting as a reservoir or safe haven, helping to mitigate against over-pressurized fisheries.

In a nearshore UK context, the main fisheries of concern will be those for shellfish such as the

European lobster and edible crab, although one must not forget the recreational fin-fishing industry.

In many studies it has been shown that bottom reefs are the most appropriate for these shellfish

species (e.g. Jensen and Collins 1995) with the provision of adequate space for shelter. The use of

offshore platforms in this context is debatable, particularly with respect to lattice jackets, and one

would again acknowledge the merits of utilizing reefs consisting of e.g. concrete blocks which can

be designed and placed in an optimum way to meet the specific needs of the management situation.

One example of this use of artificial reefs is a proposal to deploy blocks of stabilized quarry

aggregate by-product (from Argyll, Scotland) with cement and fly ash in the creation of an artificial

reef for research and, amongst other possible options, the future management of the local lobster

fishery (Wilding and Sayer 1997).

A nearshore rigs-to-reefs initiative will require a beneficiary who is willing to assume ownership

and liability for the structure. This is amplified by its location, the costs of nearshore reef creation

needing to be at most equal to the cost of onshore disposal (otherwise donation of the structure to

a rigs-to-reefs scheme by an offshore operator has little benefit to operator in comparison with

onshore disposal). The risk of interaction with other sea users also increases in a nearshore context.

Without a beneficiary, a rigs-to-reefs project will have no grounds on which to proceed. The demand

for a nearshore reef and a demonstration of potential environmental and socio-economic benefits

will also be central to:

• its identification as a BPEO (as required by UK law) for the abandonment of a particular

structure;

• the agreement of OSPAR Contracting Parties of its acceptability; and

• the counteracting of any environmental campaign opposed to the use of an offshore structure

as the reef.

Nearshore reef creation does not produce as strong a response from environmental groups and

fisheries representatives as offshore reef creation does. Greenpeace has expressed its opposition to

nearshore reef creation. Although they do not condemn nearshore reef creation in general, they

condemn the use of high-grade steel in their construction, which they maintain would be more

appropriately brought onshore for reuse and recycling.
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Offshore Reef Creation

The only potential purpose of an offshore rigs-to-reefs program is in a fisheries management

context, be it to enable fish aggregation for a sustainable gear-specific fishery or as a conservation

area where fishing is prohibited. There are obvious cost saving incentives for offshore operators

through such an abandonment route, however, fishermen and environmental campaigners strongly

oppose to this option, and the prospects for formation of an offshore artificial reef be it toppled in

situ, moved to a designated site or utilized in combination with a no fishing policy, are not good.

In terms of an individual offshore rigs-to-reefs scenario or small cluster of reefs, such a proposition

faces the following political hurdles, the first being most critical:

• an offshore reef is seen as an impediment and danger to fishermen and their fishing methods,

not a benefit, and even if there is a marginal fishery benefit, the risk posed to safety would

far outweigh these in the overall picture;

• opposition to the concept from fishermen which would almost certainly prevent the adoption

of the concept as the BPEO in a given situation(s) and which ultimately could be used by

other contracting parties to the OSPAR Convention 1992 as a significant reason for not

proceeding;

• opposition to the concept from environmental organizations, most notably Greenpeace, who

see artificial reefs as a “weak link” in abandonment legislation, which could set dangerous

precedents for industrial waste disposal. They also see the rigs-to-reefs option as a panacea

for the offshore industry’s abandonment problems, undermining its responsibility to clean

up its own waste;

• opposition to the concept from contracting parties to the OSPAR Convention who will view

this plan as being in conflict with the spirit of the Sintra agreement; and

• lack of a beneficiary (both the fishing and environmental sectors are opposed to offshore reef

creation) and therefore potential transfer of liability.

A no-fishing area (sanctuary) to help conserve stocks in combination with a rigs-to-reefs program

is also faced by the following hurdles:

• opposition from fishermen centering on:

(i) opposition to the mere presence of a no-fishing zone, never mind the combined

instance;

(ii) the implications for the North Sea fishing industry as it is an area that supports a

mixed fishery; and

(iii) the general imposition of another damaging set of regulations and level of

bureaucracy;
134

• opposition from Greenpeace and OSPAR Contracting Parties (many of which are members

of the EU) to the rigs-to-reefs aspects of the scheme;

• the impracticalities that will exist as a result of the maze of international, EU and national

legislative and administrative procedures that will be required, including the integration of

such a concept within the Common Fisheries Policy;

• lack of sufficient scientific data to justify the use of reefs when a closed zone to fishing may

be enough;

• lack of a beneficiary and therefore transfer of liability;

• difficulty of enforcement; and

• problems with the decommissioning of such a scheme if ineffective or unworkable; or

indeed, if successful, there is the question of access provision and whether the reefs should

be removed or left in place.

STAKEHOLDER DIALOGUE

The International Association of Oil and Gas Producers (OGP), formerly the E & P Forum, initiated

stakeholder dialogue in 1997 to take into account broader interests when shaping future research

initiatives. A workshop held in Brussels in 1997 saw the participation of European fisheries industry

representatives, non-governmental research institutes, offshore industry, environmental interest

groups, EU administration, governmental research bodies and departments, all working together to

identify key issues and questions that need to be addressed in determining the potential for rigs-toreefs in the North Sea (Environment Council 1997). Prioritized questions under the heading of

“social and political aspects” were:

• What are the criteria for [determining] success of artificial reefs?

• How can the objectivity and independence of the research be assured?

• How can we measure direct and indirect benefits compared with other options?

• How could we have rigs-to-reefs without setting a precedent for general dumping?

• How can we ensure that the dialogue continues with all parties and active participation in

existing regulatory processes and management issues?

• Who would own artificial reefs and who would be responsible or liable in perpetuity?

The second point above is of particular note. There has been mistrust over some of the scientific

research as a result of the relationship between main academic rigs-to-reefs proponents and the oil

industry. As a result of the workshop, an independent rigs-to-reefs “steering group” was formed,
135

whose main task is to assess the potential for rigs-to-reefs in the North Sea and to guide ongoing

independent research into need and suitability. The steering group is composed of members from

the fishing industry, academia, research institutions, environmental groups and the European

Commission, who report back to those workshop attendees who expressed a wish to remain in the

dialogue process.

The steering group designed the study process to examine the rigs-to-reefs concept and choose the

most appropriate organization to undertake the research. The OGP’s only input is through funding.

The study process is composed of three stages. Stage one sets two parallel questions: What are the

management, environmental and economic needs of the United Kingdom’s eastern and Norway’s

eastern seaboards (including nearshore and offshore waters)? What functions might artificial reefs

be able to perform in the North Sea context? This research has been completed (Baine and Kerr

2000), and the Steering Group is reviewing the results to determine to what extent the deliverables

identified in the answer to the second question meet the needs identified in the answers to the first,

compared to the other management options available (stage two). If the steering group finds

sufficient evidence to justify further investigation, two more parallel questions will be investigated

(stage three). Firstly, can redundant offshore installations be reused as artificial reefs and if so, at

what cost, and how could the attendant legal, political and environmental issues be resolved?

Secondly, how else might the benefits of artificial reefs be achieved, using what materials, involving

what issues and at what cost? 

At present, therefore, there is a way forward in the rigs-to-reefs debate, one that involves all

stakeholders, although Greenpeace has distanced itself from the steering group. Greenpeace has

declined to join on the basis that the outcome appears, in their eyes, to have been predetermined,

with little quality discussion on whether or not the concept should have been considered any further

before defining research strategies. Their stand embraces the precautionary principle; however,

given that UK waters already feature artificial reefs constructed from waste material, combined with

the informed assumption that any North Sea rigs-to-reefs program will never approach the levels

witnessed in the Gulf of Mexico and the fact that stringent legislative control would be imposed,

there must be scope for Greenpeace to enter the dialogue.

CONCLUSION

The implications of the Brent Spar incident are still being resolved with the emergence of a

landmark OSPAR Decision on abandonment. Although more focused, the future of North Sea

abandonment is still not entirely clear, with the possibility of derogation, the uncertainty over the

disposal of concrete installations, and the momentum that has gathered concerning the rigs-to-reefs

debate. The rigs-to-reefs concept is by no means a trivial one and requires further close examination,

but this can only be achieved through discussion, negotiation and proactive participation from all

the stakeholders involved. Firstly this discussion will enable an integration of scientific and social

thinking, admittedly on a controversial subject, but nonetheless a valid one. An opportunity exists

to comprehensively to examine the deployment of steel lattice jackets (waste material) as a fisheries

management tool in the North Sea. The success of such ventures in the Gulf of Mexico does not

ensure a similar outcome in the North Sea, but it does provide food for thought. Secondly, the

discussion will help us avoid recurrence of the Brent Spar incident. The relationship between science
136

and political motivation is central to the rigs-to-reefs debate; a trusted independent and authoritative

evaluation has to be the preferred goal.

There is no doubting the attractiveness of the rigs-to-reefs concept to offshore operators and the

opposition of a major environmental group. It is fishermen, though, who are the most likely to be

directly affected by the implications of current abandonment legislation. The possibility of steel

platform footings and concrete installations remaining behind on the seabed will entail further

consultation on loss of access and potential damage to fishermen and their gear. Fishermen may well

feel aggrieved at the historical chain of events that resulted in an about-face on the promise of

complete removal. They may well feel that the latest OSPAR Decision 98/3 has gone some way to

alleviate those grievances, but has it gone far enough? Fishermen find themselves in the midst of

contention. They strive for complete removal, yet still find themselves represented on bodies such

as the rigs-to-reefs steering group, an indication of their willingness to participate in dialogue but

also recognition of the instability of their situation. Greenpeace may be pleased with the direction

that the OSPAR Decision has taken, the offshore industry may be dismayed, but it is fishermen who

still require clarification of the future. It is the very nature of this position that provides them with

the key to the success of any rigs-to-reefs venture in the North Sea. Their co-operation and

participation is essential in the promotion of a concept that has been for so long promoted to them.

ACKNOWLEDGMENTS

The author sincerely recognizes the contribution of M. Sutherland of the Scottish Fishermen’s

Federation, S. Reddy of Greenpeace, S. Hain of the Oslo and Paris Commissions and P. Prasthofer,

formerly of the E & P Forum, to discussions regarding rigs-to-reefs in the North Sea. The author

also recognizes the members of the rigs-to-reefs Steering Group, and the International Association

of Oil and Gas Producers, which funded Stage 1 of the rigs-to-reefs study process.

REFERENCES

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decommissioned platforms in the North Sea: review of knowledge and proposed programme of

research, ISBN 82-7220-837-7.

Allan, R. 1986. Abandonment: a fishing industry perspective. Offshore Decommissioning

Conference, London, 25-26 November 1986.

Allan, R. 1992. Abandonment of offshore installations: the Scottish perception. Second International

Conference on Fisheries and Offshore Petroleum Exploitation, Bergen, Norway, 6-8 April, 1992.

Allan, R. 1994. Managing the environmental impacts of decommissioning and abandonment

offshore. Decommissioning Conference, Aberdeen, 18-19 May, 1994.

Anon. 1998. Historic marine protection deal signed. ENDS Daily, 23.07.98.
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Baine, M. 1995. Rigs to reefs in the North Sea. Proceedings of the International Conference on

Ecological Systems Enhancement Technology for Aquatic Environments, Tokyo, October 1995,

Volume 2: 507-512.

Baine, M. 1998. Rigs to reefs, the North Sea Perspective. Pages 275-280 In L.E. Hawkins et al., eds.

The Responses of Marine Organisms to Their Environments, proceedings of the 30th European

Marine Biology Symposium. ISBN 0-904175-31-61.

Baine, M., and S. Kerr. 2000. Research into coastal management of areas in the North Sea. Report

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International Association of Oil and Gas Producers.

Environment Council. 1997. Rigs to reefs: researching the option. Workshop proceedings, 29

September 1997, Brussels.

ERT. 1993. An assessment of the legislative and fisheries implications of abandonment of the Brent

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ICIT. 1991. Survey of fish distribution and contamination. Report of Heriot-Watt University’s

International Centre for Island Technology to the Scottish Fishermen’s Federation.

ICIT. 1994. Review of the background to and development of the Scottish Fishermen’s Federation’s

policy on the abandonment of offshore oil and gas installations. Report of Heriot-Watt

University’s International Centre for Island Technology to the Scottish Fishermen’s Federation.

Jensen, A.C., and K.J. Collins. 1995. The Poole Bay artificial reef project 1989-1994. Biol. Mar.

Medit. 2 (1): 111-122..

Kalder, N. 1939. Welfare propositions of economics and inter-personal comparisons of utility.

Economic Journal 49: 549-552.

Kjeilen, G., J.P. Aabel, V. Hoyvangli, M. Baine, G. Picken, and L. Heaps. 1995. Odin – an artificial

reef study. Report by RF-Rogaland research, Heriot-Watt University and Aberdeen University

to Esso Norge AS.

Petroleum Committee. 1993. Report and proposed new chapter IV in the Petroleum Act, relating to

closing down petroleum operations on the continental shelf.

Picken, G. 1992. Rigs to reefs in the North Sea. Pages 49-52 In M. Baine, ed. Artificial Reefs and

Restocking, proceedings of the 1st British conference held in Stromness, Orkney, 12 September

1992.
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Picken G., M. Baine, L. Heaps, and J. Side. 2000. Rigs to reefs in the North Sea. Pages 331-342 In

A. Jensen, K. Collins, and A. Lockwood, eds. Artificial reefs in European seas. ISBN 0-7923-

5845-7. Kluwer Academic Publishers.

Select Committee. 1996. Decommissioning of oil and gas installations. House of Lords Select

Committee on Science and Technology, Session 1995-96, 3rd Report.

Side, J. 1992. Rigs to reefs: obstacles, responses and opportunities. Pages 53-59 In M. Baine, ed.

Artificial Reefs and Restocking, proceedings of the 1st British conference held in Stromness,

Orkney, 12 September 1992.

Side, J. 1999. Issues arising from the Westhaven tragedy concerning fishing gear and pipeline

interactions. Underwater Technology 29(1): 3-10.

Side, J., M. Baine, and K. Hayes, K. 1993. Current controls for abandonment and disposal of

offshore installations at sea. Marine Policy 17(5): 354-362.

Soldal, A.V., O. Humborstad, S. Lokkeborg, I. Svellingen, and T. Jorgensen. 1999. Etterlatte

oljeplattfromer som kunstige fiskerev. Published by the Institute of Marine Research. ISSN

0071-5638.

SustainAbility. 1997. Decommissioning of offshore oil and gas installations: towards an integrated

removal strategy. A sustainable development consultation paper.

Todd, C.D., M.G. Bentley, and J. Kinnear. 1992. Torness Artificial Reef Project. Pages 15-21 In

M. Baine, ed. Artificial Reefs and Restocking, proceedings of the 1st British conference held in

Stromness, Orkney, 12 September 1992.

Wilding, T.A., and M.D.J. Sayer. 1997. Artificial marine habitats: sustainable community-led

fisheries using aggregate by-products. Programme of research prepared by Dunstaffnage Marine

Laboratory, 20pp.
139

The Ekofisk

Complex (past

and present)

The Videotapes

The Transocean 3

Survey

The Fish

Distribution

Sonar Survey

The Odin

Artificial Reef

Plan

The ODCP

Review

The North Sea

Coastal

Management

Study

Scientific Appraisal and Speculation
140
141
142

Stakeholder Dialogue

1997 Workshop
143
144

FISHING DEMAND, CATCH AND EFFORT DATA, AND ECONOMIC IMPACTS

ASSOCIATED WITH RECREATIONAL FISHING NEAR OIL AND GAS

STRUCTURES IN THE GULF OF MEXICO

Robert L. Hiett

QuanTech, Inc.

J. Walter Milon

Department of Economics

University of Central Florida

ABSTRACT

The purpose of this research project, performed under a Minerals Management Service contract, was

to estimate demand, expenditures, and economic impact associated with recreational fishing and

diving near GOM-based oil and gas structures and artificial reefs created from such structures. The

primary research approach involved a series of sample surveys during 1999 of recreational

fishermen and divers along the Gulf coast including the states of Alabama, Mississippi, Louisiana,

and Texas. Because detailed species information was collected, results are available on target

species and catch. The results of the surveys of recreational fishermen and divers strongly indicated

that the availability of oil and gas structures as well as artificial reefs created from such structures

are extremely important to the coastal counties of the Gulf states. Of the 4.5 million recreational

fishing trips estimated in the Gulf states from Alabama through Texas in 1999, 21.9% were within

300 feet of an oil or gas structure. Of the 83,780 estimated diving trips, 93.6% were within 300 feet

of such a structure. The economic activity associated with these visits was substantial. According

to the analyses performed, there were $172.9 million in direct expenditures during 1999 associated

with recreational visits to oil and gas structures in the Gulf states plus another $640.0 million in

annual equipment-related expenditures. The total economic output in coastal areas associated with

recreational fishing and diving near oil and gas structures in the Gulf was $324.6 million, including

$164.1 million in the value added component and employment estimated at 5,560 full-time

equivalents.

INTRODUCTION

Oil and gas structures, and artificial reefs created from such structures, have proven to provide

shelter and contribute food for benthic, demersal, and pelagic fish. The nearly 5,000 such structures

located in the Gulf of Mexico (GOM) probably constitutes the largest assemblage of artificial reefs

in the world. These structures have influenced the behavior of fishermen as well as fish. To facilitate

decision-making about the future of older structures, MMS contracted for this study of recreational

fishermen and divers. 

This research addressed three study objectives. The first was to assess recreational demand for

fishing and diving associated with offshore oil and gas-related structures and with artificial reefs

resulting from the “rigs-to-reef” programs in Texas, Louisiana, Mississippi, and Alabama. The
145

second objective was to assess the economic impacts resulting from this recreational demand on the

economies of Texas, Louisiana, Mississippi, and Alabama. The last objective was to analyze the

incremental expenses associated with recreational fishing and diving that would not have been

incurred if anglers had no offshore structure fishing or diving opportunities. Although it was not

specifically an objective of the research, information was obtained from recreational fishermen on

their target species and actual catch. These results are also provided in this paper.

The study area covered the states of Alabama, Mississippi, Louisiana, and Texas for the period

January through December of 1999. Recreational activities covered by the project included private

boat fishing, charter boat fishing, party boat fishing, and recreational diving in GOM waters.

METHODS

The data collection methodology for meeting these objectives combined in-person interviewing of

recreational fishermen and divers in the field with follow-up telephone interviewing from a central

dialing facility. The research design involved two basic data collection methods. The first was inperson field interviews in which trained data collectors stationed along coastal areas of the GOM

visited predetermined boat launch sites and conducted interviews with fishermen and divers as they

returned from the day’s activities. The in-person field interviews were conducted with private boat

fishermen, charter boat fishermen, party boat fishermen, and divers. The second method involved

a telephone follow-up interview to collect detailed expenditures information from qualified

respondents identified during the field interviewing.

The field interviews were used to estimate the proportion of fishing and diving trips taken near

GOM oil and gas structures or artificial reefs created from such structures. The follow-up telephone

interviews were used to estimate trip-related costs and capital expenditures associated with

recreational fishing and diving. 

A key methodological issue was that of converting proportions and mean values per individual

recreational fishing and diving trip into total estimates of demand and economic impact. Such

estimates require knowledge of the total number of fishing and diving trips taken. The approach in

this study was not to attempt to make such estimates of total demand as part of this project, but to

rely on estimates developed independently by the National Marine Fisheries Service (NMFS) of the

U.S. Department of Commerce. The NMFS conducts an annual survey of marine recreational fishing

in Alabama, Mississippi, and Louisiana with sample sizes considerably larger than the level of effort

available for the MMS study. The NMFS survey is referred to as the Marine Recreational Fishery

Statistics Survey (MRFSS) and has been conducted in the GOM since 1980. In addition, Texas

conducts its own survey of recreational fishing, and NMFS incorporates the Texas data into its own

estimates. The approach taken in this study, therefore, was to rely upon estimates of total fishing

trips and numbers of participants provided by NMFS and to apply those estimates to the results of

the 1999 MMS data collection to meet the project objectives. 

Trip expenditure data were collected during follow-up phone interviews with oil and gas structure

users who were engaged in recreational fishing from private boats, charter or party boats, or who

participated in recreational diving. Average trip expenditure data for oil and gas structure users were
146

combined with estimates of the total number of trips to oil and gas structures to produce estimates

of the annual expenditures associated with trips near oil and gas structures for each mode of fishing

or diving in the four GOM states. 

Annual equipment expenditure data were also collected during the follow-up phone interviews with

oil and gas structure users. These data were extrapolated by multiplying the average expenditures

for each mode and state times the estimated number of participants using oil and gas structures.

Because equipment expenditures may not be solely related to trips to oil and gas structures, the

expenditure and corresponding impact estimates may overstate the economic activity generated by

fishers and divers who participated in trips near oil and gas structures. 

Trip and equipment data were evaluated to estimate the economic impact in coastal counties of each

state. 

RESULTS

The first objective of the study was to estimate demand by recreational fishermen and divers

associated with oil and gas structures in the GOM and with artificial reefs constructed from such

structures. These demand estimates were generated by combining results of the field survey with

data obtained from the National Marine Fisheries Service MRFSS. Overall, it is estimated that a

total of 980,264 fishing trips were taken within 300 feet of an oil or gas structure or an artificial reef

created from such structures during 1999 out of a total of 4,484,080 marine recreational fishing trips

in the Gulf from Alabama through Texas. In addition, there were 83,780 dive trips near oil and gas

structures out of a total of 89,464 dive trips taken from Alabama through Texas.

A total of 6,845 interviews were obtained in the field with private boat fishermen as they returned

from their fishing trips. Analysis of data for these respondents indicated that, overall, the proportion

of private boat trips taken within 300 feet of oil or gas structures was 20.2%. That is, of the 4.1

million private boat fishing trips taken in these states during 1999, 823,075 were within 300 feet of

an oil or gas structure. This information is shown separately by state in Table 4.1.

Table 4.1. Total estimated private boat fishing trips near oil and gas structures.

State Total Trips

Proportion of Trips

Near Oil/Gas

Structures

Trips Near Oil/Gas

Structures

Alabama 505,635 .414 209,333 

Mississippi 507,545 .197 99,986 

Louisiana 2,067,076 .166 343,135 

Texas 986,250 .173 170,621 

Total 4,066,506 .202 823,075 
147

A total of 1,287 interviews were obtained in the field with charter boat fishermen as they returned

from their fishing trips. Analysis of data for these respondents indicated that, overall, the proportion

of charter boat trips taken within 300 feet of oil or gas structures was 32.3%. That is, of the 298,023

charter boat fishing trips taken in these states during 1999, 96,337 were within 300 feet of an oil or

gas structure. This information is shown separately by state in Table 4.2.

Table 4.2. Total estimated charter boat fishing trips near oil and gas structures.

State Total Trips

Proportion of Trips

Near Oil/Gas

Structures

Trips Near Oil/Gas

Structures

Alabama 71,394 .210 14,993 

Mississippi 49,426 .217 10,725 

Louisiana 73,770 .231 17,041 

Texas 103,433 .518 53,578 

Total 298,023 .323 96,337 

A total of 378 interviews were obtained in the field with party boat fishermen as they returned from

their fishing trips. Analysis of data for these respondents indicated that, overall, the proportion of

party boat trips taken within 300 feet of oil or gas structures was 50.9%. That is, of the 119,551

party boat fishing trips taken in these states during 1999, 60,852 were within 300 feet of an oil or

gas structure. This information is shown separately by state in Table 4.3.

Table 4.3. Total estimated party boat fishing trips near oil and gas structures.

State Total Trips

Proportion of Trips

Near Oil/Gas

Structures

Trips Near Oil/Gas

Structures

Alabama 15,386 .000 0 

Mississippi 0 — 0 

Louisiana 7,913 1.000 7,913 

Texas 96,252 .550 52,939 

Total 119,551 .509 60,852 

A total of 150 interviews were obtained in the field with divers as they returned from their trips.

Analysis of data for these respondents indicated that, overall, the proportion of dive trips taken

within 300 feet of oil or gas structures was 93.6%. That is, of the 89,464 dive trips taken in these

states during 1999, 83,780 were within 300 feet of an oil or gas structure. This information is shown

separately by state in Table 4.4.
148

Table 4.4. Total estimated dive trips near oil and gas structures.

State Total Trips Proportion of Trips

Near Oil/Gas

Structures

Trips Near Oil/Gas

Structures

Alabama 11,124 .489 5,440 

Mississippi 11,166 1.000 11,166 

Louisiana 45,476 1.000 45,476 

Texas 21,698 1.000 21,698 

Total 89,464 .936 83,780 

The second objective of the study was to assess the total economic impact associated with

recreational fishing and diving. Trip expenditure data were collected during follow-up phone

interviews with oil and gas structure users who were engaged in recreational fishing from private

boats, charter or party boats, or who participated in recreational diving. Average trip expenditure

data for oil and gas structure users were combined with estimates of the total number of trips to oil

and gas structures to produce estimates of the annual expenditures associated with trips near oil and

gas structures for each mode in the four GOM states. Trip and equipment data were evaluated to

estimate the economic impact in coastal counties of each state. 

Overall, the survey accounted for a total of $172.9 million in trip related costs for fishing and diving

near oil and gas structures in the Gulf states from Alabama through Texas. Of this number, $13.2

million were trip expenditures for diving with the balance of $159.7 million associated with trip

expenses for recreational fishing.

Annual equipment expenditure data were also collected during the follow-up phone interviews with

oil and gas structure users. These data were extrapolated by multiplying the average expenditures

for each mode and state times the estimated number of participants using oil and gas structures.

Because equipment expenditures may not be solely related to trips to oil and gas structures, the

expenditure and corresponding impact estimates may overstate the economic activity generated by

fishers and divers who participated in trips near oil and gas structures.

The survey accounted for a total of $640.0 million in equipment costs associated with recreational

fishing and diving activities by those who visited oil or gas structures in the Gulf states from

Alabama through Texas during the survey year. Of this number, $0.6 million was equipment

expenditures for diving with the balance associated with equipment expenditures for recreational

fishing.

The expenditure data, distributed according to whether the respondent lived in coastal or noncoastal

areas and according to the location of the expenditure, were then used in the IMPLAN (Impact

analysis for PLANning) input-output modeling framework to produce estimates of economic
149

impacts generated by oil and gas structure users in each state. These impacts include total output,

employment, and personal income (value added) effects in the coastal regions of each state.

This analysis (Table 4.5) indicated that there was a total of $324.6 million in economic output in

coastal counties of the Gulf region associated with fishing and diving activities near oil and gas

structures during the year. The value added component of this number was $164.1 million, with

employment estimated at 5,560 full-time equivalents.

Table 4.5. Total economic impact of combined annual trip and equipment expenditures for fishing

and diving near oil/gas structures in coastal counties by state and mode.

State Mode

Economic

Output (in$)

Value Added

(in $)

Employment

(in FTEs)

Alabama private 42,644,863 17,771,068 609.1

charter 16,853,979 7,860,816 343.0

party 0 0 0.0,

dive 287,090 205,600 7.0

TOTAL 59,785,933 25,837,848 959

Louisiana private 119,975,000 55,735,257 1,822.5

charter 3,149,849 1,507,707 75.5

party 1,431,121 722,706 35.5

dive 10,367,078 6,928,205 249.3

TOTAL 134,923,108 64,893,875 2,183

Mississippi private 24,651,800 14,743,784 459.9

charter 4,630,674 2,924,368 116.6

party 0 0 0.0

dive 2,981,544 1,908,667 56.6

TOTAL 32,264,018 19,576,820 633

Texas private 67,882,962 39,657,080 1,167.6

charter 20,783,038 9,637,829 435.2

party 8,944,989 4,473,820 182.2

dive 0 0 0.0

TOTAL 97,610,989 53,768,348 1,785

Gulf Region TOTAL 324,584,048 164,076,527 5,560
150

The third major objective was to estimate incremental expenses associated with recreational fishing

and diving that would not have been incurred if anglers had no offshore structure fishing or diving

opportunities. In order to estimate this incremental effect of oil/gas structures on angler expenditures

in the GOM region, it is necessary to account statistically for the variety of factors that may

influence these decisions. In evaluating incremental effects, it is important to recognize that

statistical procedures can only establish an association between expenditures and fishing near oil/gas

structures; they can not determine causation.

The sample data indicated that the difference in annual trip and equipment expenditures between

users and nonusers of oil and gas structures was $3,232 per angler across the Gulf region. After

correcting for nonnormality in the distribution of expenditures and self-selection in the choice of

fishing sites, predicted values from a selection model indicated that the difference in expenditures

between the two groups was much smaller. The predicted average expenditures for users were

$4,691 with a 95% confidence interval of $4,198 to $5,183. For non-users, predicted average

expenditures were $3,159 with a 95% confidence interval of $2,721 to $3,597. The resulting

difference of $1,532 per angler is the most reliable estimate of the difference in annual expenditures

between users and non-users of oil and gas structures across the GOM region.

Respondents were asked to provide information on the particular species of fish they were targeting

during their fishing trips. There were important differences observed in the results for those who

fished near oil and gas structures and those who did not. As shown in Table 4.6, those fishing near

oil and gas structures were somewhat more likely to report they were fishing for Red Snapper and

King Mackerel. Those not fishing near such structures were more likely to list Spotted Seatrout and

Red Drum as their target species.

Table 4.6. Target species for fishermen.

Fishing Near Oil/Gas Structure Not Fishing Near Oil/Gas Structure

Target Species Percent Target Species Percent

Spotted Seatrout 29.6 Spotted Seatrout 45.8

Red Snapper 28.1 Red Drum 26.8

King Mackerel 20.3 Southern Flounder 7.6

Cobia 5.1 Sand Seatrout 2.3

Red Drum 4.9 Spanish Mackerel 2.3

Information was also obtained on actual catch of fish by the respondents. These data are reported

separately for those who fished near oil and gas structures in Tables 4.7 through 4.10. In general,

it can be observed that the particular species caught were somewhat different for those fishing near

structures, but the numbers of total fish caught were relatively comparable.
151

Table 4.7. Average catch per trip for selected species: Private boats in Alabama.

Species Near Structure Not Near Structure

Silver Seatrout 1.85 2.26

Red Snapper 0.98 1.08

S. Mackerel 1.18 0.64

Red Drum 0.69 0.21

Bluefish 2.26 0.20

Total 12.02 7.51

Table 4.8. Average catch per trip for selected species: Private boats in Mississippi.

Species Near Structure Not Near Structure

Red Snapper 2.78 0.24

K.Mackerel 1.04 0.01

Cobia 0.38 0.02

Spotted Seatrout 0.37 1.80

Sand Seatrout 0.32 6.01

Total 6.95 10.88

Table 4.9. Average catch per trip for selected species: Private boats in Louisiana.

Species Near Structure Not Near Structure

Spotted Seatrout 5.80 5.99

Red Snapper 1.49 0.01

Sand Seatrout 0.99 0.71

Red Drum 0.77 1.86

Hardhead Catfish 0.59 1.01

Total 12.79 13.40
152

Table 4.10. Average catch per trip for selected species: Private boats in Texas.

Species Near Structure Not Near Structure

Red Snapper 5.05 0.34

K.Mackerel 0.77 0.04

Atlantic Spadefish 0.22 0.00

Spotted Seatrout 0.19 2.55

Sand Seatrout 0.08 1.77

Total 8.23 8.43

DISCUSSION

The results of the surveys of recreational fishermen and divers strongly indicated that the availability

of oil and gas structures as well as artificial reefs created from such structures are extremely

important to the coastal counties of the Gulf states. Of the 4.5 million recreational fishing trips

estimated in the Gulf states from Alabama through Texas in 1999, 21.9% of them were within 300

feet of an oil or gas structure. Of the 83,780 estimated diving trips, 93.6% were within 300 feet of

such a structure.

The results also indicated that multiple structures were generally visited during these recreational

trips. On average, more than two structures were visited per trip, with the total annual structurevisits estimated at 2.2 million annually.

The economic activity associated with these visits was substantial. According to the analyses

performed, there were $172.9 million in direct expenditures during 1999 associated with recreational

visits to oil and gas structures in the Gulf states plus another $640.0 million in annual equipmentrelated expenditures. The total economic output in coastal associated with recreational fishing and

diving near oil and gas structures in the Gulf was $324.6 million, including $164.1 million in the

value added component and employment estimated at 5,560 full time equivalents.

An analysis of the incremental value of oil and gas structures for recreational activities indicated that

the typical angler who visited such structures spent more than those who did not. The most reliable

estimate is that anglers who visited oil and gas structures spent an additional $1,532 annually.

In summary, it can be concluded as a result of this study that there is substantial recreational activity

associated with the presence of oil and gas structures in the GOM from Alabama through Texas and

these activities have a substantial economic impact. Several issues are raised by these findings:
153

• Because the presence of oil and gas structures is important to recreational fishing and diving

in the Gulf, consideration should be given to assuring the continued availability of at least

some of these structures across the range of the Gulf Coast area, even after they are no

longer used for oil or gas extraction.

• Decisions on structure removal must take into account the effects on recreational activities

and the economic value they represent. It is uncertain how fishermen and divers would

respond to the removal of oil and gas structures that are targets of frequent visits. If

participants simply went to other locations, then the impact would be minimal. The decision

to fish and dive at other places, however, may be a complex one involving such factors as

distance from shore, size of structure, number of other participants at the location (i.e.,

crowdedness), and availability of acceptable alternatives (both at other structures and at

nonstructure locations). It is possible that structure removal would result in reduced demand

with a corresponding negative economic impact.

• Fishing and diving occur at oil and gas structures in large part because of the availability of

marine life near such structures. While beyond the scope of the present study and not

included in this report, preliminary indications from the surveys indicated that fishing

success, particularly for preferred species, near oil and gas structures was at least equal to

and in many cases greater than at other locations. There is, therefore, the question of the

effect on marine life of the removal of structures that have been in place for decades. It is

likely that any loss of marine life, or at least a reduction in its density such that fishing or

diving is no longer rewarding, would have a negative impact on recreational fishing and

diving coupled with the loss of economic value associated with those activities.

• The process by which fishermen and divers select the specific oil and gas structures to visit

is not understood. Both the incremental value which was established in this research and the

fact that fishermen and divers visit multiple structures on each trip suggest that there is a

decision process which underlies the selection of particular structures for recreational

activities. If a decision about removal of a specific structure is being considered, it would

be extremely useful to have in hand a set of variables which are known to be associated with

structure recreational usage. These might include such elements as ease of access, distance

from shore, distance from boat launch sites, water depth, size and configuration of structure,

history of “success” at the site, perceptions of safety, availability of recreational alternatives,

and site popularity. Without an understanding of the variables that affect participants’

decisions to use a particular site, decisions on structure removal cannot fully take into

account the needs of recreational fishermen and divers.

• It is important that government and private interests develop and utilize decision-making

processes for structure removal that include consideration of the needs of recreational

fishermen and divers. Fishing and diving interests across the Gulf should be kept informed

about the processes of structure removal and given opportunity to participate in such

decisions. There is considerable potential for local opposition to removal of popular fishing

and diving sites, especially if there are no alternatives available.
154

• Additional research may be required to answer questions raised by the current study:

- How many oil and gas structures can be removed in a particular area without resulting

in a decline in the number of recreational fishing and diving trips being taken?

- Which of the existing structures, if any, are most frequently visited by fishermen and

divers for their recreational activities?

- What are the characteristics of the most preferred structures?

- In the event of selective removal of oil and gas structures, how will the behavior of

fishermen and divers change? Will they shift to other available structures, to

nonstructure locations, or withdraw from the activity?
155
156
157
158
159
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IMPORTANCE OF GEOLOGY TO FISHERIES MANAGEMENT:

EXAMPLES FROM THE NORTHEASTERN GULF OF MEXICO

Kathryn M. Scanlon

U.S. Geological Survey

Christopher C. Koenig

Felicia C. Coleman

Florida State University

Margaret Miller

National Marine Fisheries Service

ABSTRACT

Seafloor mapping of shelf-edge habitats in the northeastern Gulf of Mexico (GOM) demonstrates

how sidescan-sonar imagery, seismic-reflection profiling, video data, geologic mapping, sediment

sampling, and understanding the regional geologic history can enhance, support, and guide

traditional fisheries research and management. New data from the Madison-Swanson and Steamboat

Lumps Marine Protected Areas (MPAs) reveal complex benthic habitats consisting of high-relief

calcareous pinnacles, low-relief karstic hard-bottom, rocky outcrops several kilometers in length,

and variable thickness of fine-grained and apparently mobile coarse-grained sediments. Our data

also show that certain fish alter the landscape by clearing sediment from hard-bottom areas (e.g.,

red grouper, Epinephelus morio) and by burrowing extensively in fine-grained sediment (e.g.,

tilefish, Lopholatilus chamaeleonticeps).

The seafloor imagery and geologic maps show that (a) sea-level fluctuations played a dominant role

in the development of the present day regional geology and (b) habitats (and benthic communities)

are closely tied to geologic character. Understanding the geological setting allowed for efficient and

representative sampling of the biology. The geologic data can be used to set meaningful boundaries

for fishery reserves and to help predict habitats in areas that are not well mapped. This

interdisciplinary work added value to traditional research disciplines by providing management with

integrated tools to make better decisions.

INTRODUCTION

Why should marine biologists and fishery managers care about sidescan-sonar mosaics, geologic

maps, and the geologic history of a region? They should care because fishery resources do not exist

in a vacuum. Habitat is crucial to the viability of the resource, and geology is the framework within

which the habitat exists. Many modern marine geology tools, techniques, and interpretations have

great value to fisheries management, but they are often overlooked by scientists trained in nongeological specialties. Our work in the northeastern GOM shelf-edge habitats demonstrates how

sidescan-sonar imagery, seismic-reflection profiling, geologic mapping, and understanding the
161

***** Use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey.

regional geologic history can enhance, support, or guide traditional fisheries research and

management.

TOOLS OF MARINE GEOLOGY

Some commonly used marine geological research tools (such as sidescan-sonar, multibeam

bathymetry, seismic reflection profiling, and sediment sampling) are directly useful to marine

biologists and fishery managers.

Sidescan-Sonar

Sidescan-sonar systems use sound to provide aerial-photograph-like acoustic imagery swaths of the

seafloor. When collected, processed and mosaicked properly, these systems are perhaps the most

useful geologic tool for fisheries management and research. There are many types of sidescan-sonar

systems with varying resolutions and optimized for a variety of water-depth ranges. In each case,

a trade-off must be made between resolution and the area covered in a given amount of time. For

habitat mapping in shelf-edge areas (water depths 50 to 150 meters), we have found systems such

as the SIS 1000***** and the EdgeTech DF1000*

 to be a good compromise. In about seven days, these

instruments can cover a 100-square-mile area with enough overlap of adjacent swaths for

mosaicking. They can resolve features such as boulders and burrows as small as 1 meter across.

Elongate features, such as trawl marks, also show even if they are less than a meter across, because

they are long in one dimension.

Repeated sidescan-sonar surveys can show changes in seafloor character and habitat. This technique

can be used to monitor changes in the areal extent of certain types of habitat after an event such as

a storm or closure to fishing. These surveys are also useful in assessing impact from human

activities such as bottom trawling or waste disposal.

Multibeam Bathymetry

Multibeam bathymetry systems collect swaths of water-depth data, which can be used to create

bathymetric contour maps. Like sidescan-sonar systems, multibeam systems are available in a wide

variety of resolutions and for various water-depth ranges. These data can be used for threedimensional renderings of seafloor morphology. Software has been developed for some multibeam

systems to allow creation of backscatter maps, similar to sidescan-sonar imagery, as well as depth

contour maps. Backscatter gives information about the seafloor that is not contained in the depth

information, such as hardness, sediment texture, and surface roughness. Multibeam data can be

much more expensive to collect than sidescan-sonar and sometimes requires a dedicated ship. We

have not collected multibeam data in the northeastern GOM, but proposals are pending to do so in

the near future.

Seismic-Reflection Profiles
162

Seismic-reflection profilers provide a cross-sectional view of the seafloor and the sediment and rock

layers beneath it. Higher-frequency sound sources result in higher-resolution profiles; lowerfrequency sources penetrate more deeply into the substrate but provide less resolution. Seismic

profiles reveal the shapes of and relationships between past seafloor environments. This information

is invaluable to understanding the geologic history of a region. It also has direct utility to habitat

studies because it allows us to map the thickness of unconsolidated sediment. In the eastern GOM,

for example, this is important because hard-bottom habitat can be exposed or buried by variable

amounts of mobile sediment, thereby changing the distribution of habitats through time.

Sampling

Sediment sampling can be carried out remotely from a ship with a grab sampler or directly by divers

or submarine. Representative sediment or rock samples must be collected from a study area to

adequately characterize a habitat. Sampling is also a critical “ground truth” for interpreting sidescansonar data. Differences in sediment composition and texture and the presence and roughness of rock

outcrops are among the factors that can affect the intensity of backscatter signal in sidescan-sonar

data. These factors also have a direct effect on the biological community that will inhabit an area.

Putting It All Together: Mapping

Although mapping is not, strictly speaking, a “tool,” maps produce visualizations that are used to

further our understanding of the geologic history of an area. Mapping of the surficial geology of the

seafloor is done by combining interpretation of the sidescan mosaics and seismic profiles with

analyses of sediment and rock samples and observations from ROV or submarine. These maps

provide, for example, the areal extents of sediment of different compositions and hard-bottom

habitats, and are valuable for determining percentages of various habitat types as well as for setting

the boundaries of fishery management reserves. 

GEOLOGIC HISTORY AS A FISHERY MANAGEMENT TOOL

While the utility of the traditionally “geologic” tools discussed above for fishery management

applications is straightforward, fisheries managers may not understand why the geologic history of

a region is important. Beyond the direct uses to fisheries management discussed here these types of

geologic data can be used to provide an understanding of the geologic evolution of an area through

time. Although fisheries management is rooted in the present and affects the future, the past can be

a valuable key to more effective and less expensive management.

A Case History

In March 2000, we collected sidescan-sonar data in the Madison and Swanson MPA and the

Steamboat Lumps MPA and in 1997 in an intervening area we call Twin Ridges. In each case the

sidescan swaths overlap, providing continuous coverage. Using near-real-time processing and

mosaicking techniques developed at the USGS Woods Hole Field Center (Danforth 1997; Danforth

et al. 1991, Paskevich 1992 and 1996), digital mosaics were available within 24 hours to use for fish
163

sampling and siting of video observations. This information provided for more accurate positioning

of the ship, saved time, and most importantly, allowed selection of specific habitat types for station

work.

Using these sidescan-sonar data in conjunction with seismic-reflection profiles, sediment and rock

samples (which give information about past environments of deposition and age) and direct or video

observations, we are now reconstructing the evolution of the shelf-edge habitats through time. We

discovered several long arcuate rocky ridges in 60 to 90 meters of water (Scanlon 2000). Previous

work (Locker et al. 1996) has shown that about 15,000 years ago sea level was 80 meters lower than

it is today. This sea level history has played an important role in the evolution of the West Florida

continental shelf (e.g., Doyle and Holmes 1985; Hine et al. 1988; Hine 1997; Mullins et al. 1988;

Roberts et al. 1999). We interpret our rocky ridges to be the lithified remains of paleo-beaches,

called beachrock, from this sea level lowstand (Scanlon 2000; Thieler et al. 1999). Seaward of the

beachrock outcrops, we found limestone pinnacles, which may be built on drowned patch reefs. The

beachrock and the limestone pinnacles differ not only in the chemical composition of the rocks

themselves and the surrounding sediments derived from them but also in the morphology of the

outcrops. Beachrock is cemented sandstone and tends to occur in tabular slabs with widely spaced

cracks and crevices. The limestone pinnacles are composed of agglomerations of numerous species

of coral and algae and the remains of many sessile and encrusting benthic organisms. The limestone

has dissolved and has been bored by clams and other organisms. These outcrops are replete with

nooks and crannies and holes of all sizes and shapes.

Each of these two rock types (beachrock and pinnacle limestone) afford distinct types of habitat and

can be expected to support distinct benthic communities. Gag (Mycteroperca microlepis) and scamp

(Mycteroperca phenax ) are known to spawn near high-relief outcrops at the edge of the present

continental shelf (Coleman et al. 1996; Koenig et al. 2000). We do not yet know whether they prefer

beachrock or limestone pinnacle sites, but our on-going studies should reveal this. These beachrock

and limestone pinnacle sites are distinctive features associated with changes in sea level and are

expected to be widespread in the GOM near the shelf edge. By understanding the geologic history,

we will be able to predict where the preferred type of outcrop will be found in areas that have not

been well mapped.

In our study areas, we noted that fine-grained sediments correlate with areas shown by the sidescan

data to be extensively pitted by fish burrows (presumed to be made by tilefish, Lopholatilus

chamaeleonticeps). Inexpensive sediment grab sampling could be used to map the extent of the

habitat of this food fish. We also mapped areas using sidescan-sonar data and verified by video

where holes have been excavated under small boulders and sediment has been cleared from small

(a few meters square) hard-bottom areas, presumably by the red groupers (Epinephelus morio) we

observed occupying some of the excavations. Here, a heavily targeted commercially valuable fish

species (E. morio) is acting as a geologic agent and creating a habitat that is attractive to numerous

other species. Repeated sidescan surveys of this area would readily show whether the recent closure

of the area to fishing results in an increase in the areal extent or density of this type of habitat.

By understanding the geologic history of the region, we are now able to make reasonable predictions

about where particular habitats are likely to occur in less well-mapped parts of the eastern GOM.
164

We can also estimate the quantities and areal extents of modern habitats which we know evolved

from particular ancient environments by comparison with modern environments that are similar to

the ancient ones. These estimations are useful for making management decisions. For example, if

we know that an economically important fish species spawns only around beachrock outcrops in a

certain water depth, and that a sea level stillstand occurred at that depth for a long enough time to

produce beachrock, and we know the width of beachrock in modern environments, then we can

estimate the areal extent of beachrock outcrops in the region in question. If protection of this fish’s

spawning habitat is needed, a rational management decision could be made, based on the geologic

history, to create reserves encompassing a certain percentage of the estimated habitat.

CONCLUSIONS

Modern marine geologic tools and maps are directly useful to marine biologists, ecologists, and

fisheries managers. Imagery data can be used to choose sampling and study sites and to document

changes in areal extents of habitats. These data are also valuable for setting meaningful boundaries

for fishery reserves. Seismic-reflection data show thicknesses of unconsolidated sediments and

provide information about the character of the sediment-water interface. Sediment or rock

composition can be correlated with species assemblages.

Even more powerful for fisheries management is understanding the geologic history of a region.

This understanding can be used to predict where certain benthic communities may exist or where

they could be successfully restored. Understanding the geologic history also allows us to make

realistic estimates of the areal extents of certain types of habitat in unexplored areas.

“Multi-disciplinary,” “inter-agency,” and “cooperative” are popular buzzwords and we are

encouraged to use them in our research plans. Although we may agree that since the environment

is naturally “multi-disciplinary,” it makes sense to study it in a multi-disciplinary way, sometimes

it is not so clear whether there is any real benefit to our research in doing so. In our work in the

northeastern GOM, interdisciplinary collaboration has greatly enhanced our research and provided

management with tools to make better decisions. Traditional organization of institutions by

discipline often separates potential collaborators, but the benefits of cross-disciplinary research are

well worth the necessary extra effort. In the case of marine geology and fish ecology/fisheries

management, the benefits are real and can result in better management practices.

REFERENCES

Coleman, F.C., C.C. Koenig, and L.A. Collins. 1996. Reproductive styles of shallow-water grouper

(Pisces: Serranidae) in the eastern Gulf of Mexico and the consequences of fishing spawning

aggregations. Environmental Biology of Fishes 47:129-141.

Danforth, W.W., T.F. O’Brien, and W.C. Schwab. 1991. Near real-time mosaics from highresolution sidescan-sonar - an image processing technique to produce hard-copy mosaics ‘on

site’ proved successful during USGS survey, Sea Technology, V.32, no.1, pp. 54-59.
165

Danforth, W.W. 1997. Xsonar/ShowImage: A complete system for rapid sidescan sonar processing

and display, USGS Open-File Report 97-686, pp. 77.

Doyle, L.J. and C.W. Holmes. 1985. Shallow Structure, Stratigraphy, and Carbonate Sedimentary

Processes of West Florida Upper Continental Slope: Bul. AAPG, v. 69, no. 7, pp. 1133-1144.

Hine, A.C. 1997. Structural and paleo-oceanographic evolution of the margins of the Florida

platform. In Randazzo, A.F. and D.S. Jones, eds. 1997. The Geology of Florida. Gainesville:

University Press of Florida. pp. 169 – 194.

Hine, A.C., D.F. Belknap, J.G. Hutton, E.B. Osking, and M.W. Evans. 1988. Recent geological

history and modern sedimentary processes along an incipient, low-energy, epicontinental-sea

coastline: northwest Florida. Journal of Sedimentary Petrology, v.58, no. 4, pp. 567-579.

Koenig, C.C., F.C. Coleman, C.B. Grimes, G.R. Fitzhugh, K.M. Scanlon, C.T. Gledhill, M Grace.

In press. Protection of fish spawning habitat for the conservation of warm temperate reef fish

fisheries of shelf-edge reefs of Florida: Bulletin of Marine Science.

Locker, S.D., A.C. Hine, L.P. Tedesco, and E.A. Shinn. 1996. Magnitude and timing of episodic

sea-level rise during the last deglaciation. Geology, 24: 827-830.

Mullins, H.T., A.F. Gardulski, E.J. Hinchey, and A.C. Hine. 1988. The modern carbonate ramp

slope of central west Florida. Journal of Sedimentary Petrology, v. 58, no. 2, pp.273-290.

Paskevich, V. 1992. Digital mapping of side-scan sonar data with the Woods Hole Image Processing

System software: U.S. Geological Survey Open-File Report 92-536, 87p.

Paskevich, V. 1996. MAPIT: An improved method for mapping digital sidescan-sonar data using

the Woods Hole Image Processing System (WHIPS) Software: U.S. Geological Survey OpenFile Report 96-281, 73p.

Roberts, H.H., R.A. McBride, and J.M. Coleman. 1999. Outer shelf and slope geology of the Gulf

of Mexico: An overview. In Kumpf, Herb, K.A. Steidinger, and Kenneth Sherman, eds. The

Gulf of Mexico Large Marine Ecosystem, Blackwell Science, Inc, Malden MA, U.S.A. pp.

93-112.

Scanlon, K.M. 2000. Surficial Seafloor Geology of a Shelf-edge Area off West Florida. In Briere,

P.R., K.M. Scanlon, Gary Fitzhugh, C.T. Gledhill, and C.C. Koenig. 2000. West Florida Shelf:

Sidescan-sonar and sediment data from shelf-edge habitats in the northeastern Gulf of Mexico,

U.S. Geological Survey Open-file Report 99-589. CD-ROM.

Thieler, E.R., W.C. Schwab, P.T. Gayes, O.H. Pilkey, Jr., W.J. Cleary, and K.M. Scanlon. 1999.

Paleoshorelines on the U.S. Atlantic and Gulf Continental Shelf: Evidence for sea-level

stillstands and rapid rises during deglaciation. Non-steady state of the inner shelf and shoreline:

coastal change on the time scale of decades to millennia. (abs) Hawaii University, 11/8-12/99.
167

SESSION 5: 

OFFSHORE PLATFORM COMMUNITIES I

Moderators: Benny Gallaway

Gregg Gitschlag

Date: October 25, 2000

Presentation Author/Affiliation

A Preliminary Evaluation of the Effects of

Ethylene Glycol Exposure on the Swimming

Performance of Juvenile Florida Pompano

M. K. Hymel

Department of Oceanography and Coastal

Sciences

Louisiana State University

D. M. Baltz

Department of Oceanography and Coastal

Sciences and

Coastal Fisheries Institute

Louisiana State University

E. J. Chesney

Louisiana Universities Marine Consortium

Chauvin, LA

M. A. Tarr

Department of Chemistry

University of New Orleans

A. S. Kolok

Biology Department

University of Nebraska at Omaha

Effects of the Nepheloid Layer on Biofouling

Communities on Coastal Petroleum Platforms

in the Northwestern Gulf of Mexico

Thomas W. Bates

Q.R. Dokken

Center for Coastal Studies

Texas A&M University-Corpus Christi

Vertical Distribution and Habitat Association

of Four Blenniidae Species on Gas Platforms

in the Northcentral Gulf of Mexico

Marek R. Topolski

Department of Fisheries

Auburn University

Stephen T. Szedlmayer

Department of Fisheries

Auburn University

Gulf Coast Experimental and Research

Center

(continued on next page)
168

Presentation Author/Affiliation

Vertical and Within Platform Spatial

Variability of Larval and Juvenile Fishes

Associated with Petroleum Platforms off

Louisiana

Frank J. Hernandez, Jr.

Department of Oceanography and Coastal

Sciences

Louisiana State University

Richard F. Shaw

Department of Oceanography and Coastal

Sciences and 

Coastal Fisheries Institute

Louisiana State University

The Across-Shelf Larval, Postlarval, and

Juvenile Fish Community Associated with

Offshore Oil and Gas Platforms and a Coastal

Rock Jetty West of the Mississippi River

Delta

Frank J. Hernandez, Jr.1

Richard F. Shaw1, 2

Joseph S. Cope2

James G. Ditty3

Talat Farooqi2

Mark C. Benfield1, 2

1

Department of Oceanography and Coastal

Sciences, Center for Coastal Energy and

Environmental Resources, Louisiana State

University

2

Coastal Fisheries Institute, Louisiana State

University

3

NOAA/NMFS, Southeast Fisheries Science

Center

Red Snapper Recruitment to and

Disappearance from Oil and Gas Platforms in

the Northern Gulf of Mexico

David L. Nieland

Coastal Fisheries Institute

Charles A. Wilson

Coastal Fisheries Institute and

Department of Oceanography and Coastal

Sciences

Center for Coastal, Energy, and

Environmental Resources

Louisiana State University
169

A PRELIMINARY EVALUATION OF THE EFFECTS OF ETHYLENE

GLYCOL EXPOSURE ON THE SWIMMING PERFORMANCE

OF JUVENILE FLORIDA POMPANO

M. K. Hymel

Department of Oceanography and Coastal Sciences

Louisiana State University

D. M. Baltz

Department of Oceanography and Coastal Sciences and

Coastal Fisheries Institute

Louisiana State University

E. J. Chesney

Louisiana Universities Marine Consortium

Chauvin, LA

M. A. Tarr

Department of Chemistry

University of New Orleans

A. S. Kolok

Biology Department

University of Nebraska at Omaha

ABSTRACT

Exposure to ethylene glycol, which is used in the production of crude petroleum, may not be

immediately lethal to fishes, but may affect individual fish through reduced growth, reproduction,

and survival. Florida pompano are common in the Gulf of Mexico (GOM) where petroleum

production platforms or transport pipelines occur, putting them at risk of exposure in the event of

a spill or leakage. Using Blazka-type respirometers, the critical swimming performance of juvenile

Florida pompano was evaluated before and after exposure to a 3.0% ethylene glycol concentration

in 30 ppt sea water at 25 °C. The mean critical swimming speed (Ucrit) was reduced by 14% in

treatment fish from 96.0 ± 1.13 cm s-1 (9.4 ± 0.17 BL s-1) in the pre-exposure trial to 83.0 ± 3.45 cm

s

-1 (8.0 ± 0.26 BL s-1) in the post-exposure trial. The Ucrit of control fish increased by 5%. A

considerable amount of variability was observed between pre- and post-exposure performance of

individuals, suggesting varying degrees of individual tolerance. 

INTRODUCTION

Marine fishes face an array of risks that affect their ability to perform in ecological situations. The

effects of factors producing direct mortality in populations, such as fishing, are often easier to

quantify than factors producing sublethal impacts within a population. Sublethal impacts, while not
170

producing direct mortality, may affect the growth, reproduction, and survival of individuals, which

may have implications on population dynamics. Quantifying sublethal effects at the individual level

is an important step in predicting how a species may respond ecologically to these impacts. 

One possible sublethal impact to marine fisheries is the use of additives in the production of

deepwater petroleum resources. With the development of new petroleum production technologies,

oil and gas is now being produced from waters greater than 305 m (1,000 ft) in the GOM (Minerals

Management Service, www.gomr.mms.gov). The continuing expansion of petroleum exploration and

drilling into deeper reaches of the GOM introduces a new array of risks of environmental impacts

on marine fishes, and creates a pressing need for the ecological evaluation of new practices and

chemicals used in this industry. 

The possible effects of ethylene glycol, a deepwater petroleum additive, on fishes in the marine

environment have yet to be assessed. Ethylene glycol is used in petroleum production and transport

to prevent the formation of gas hydrates. Gas hydrates occur when water molecules crystallize

around one or more guest molecules, such as helium, chlorine, or carbon dioxide, which are often

present in natural gas. As the gas is pumped through deepwater pipelines changes in pressure and

temperature can facilitate the formation of these hydrates, potentially clogging the pipeline

permanently. One process used to inhibit hydrate formation requires large quantities of ethylene

glycol, which decrease the hydrate stability and lower the temperature of hydrate formation

(Anonymous 1996).

The environmental effects of ethylene glycol have been widely studied in relation to its use as an

antifreeze and coolant for automobiles and as a deicing agent for bridges and runways (Barber

1999). The LC50 of ethylene glycol,

 the concentration estimated to kill half of a group of organisms

in a pre-determined amount of time, has been reported for various fresh and brackish-water

organisms (Greene and Kocan 1997, Abdelghani et al. 1989, Pillard 1995). The toxicity of ethylene

glycol to fish has been assessed on only a few species, including rainbow trout (Oncorhynchus

mykiss) and fathead minnow (Pimephales promelas) (Greene and Kocan 1997), bluegill sunfish

(Lepomis macrochirus) (Abdelghani et al. 1989), and goldfish (Carassius auratus) (Bridie et al.

1979). Effects of ethylene glycol exposure have not been assessed for any marine fishes. 

This is the first study to evaluate sublethal effects of ethylene glycol on marine fish. Non-lethal

exposure levels can lead to important effects, which are often measured by diminished performance

(Sprague 1971). Sublethal exposure of fish to contaminants can cause a stress response due to an

altered physiological condition, such as impeded oxygen transfer across the gills. A fish under stress

exhibits a diminished ability to function normally, which suggests potential death or decreased

reproduction of an individual, possibly leading to a declining population (Heath 1995). 

The use of performance indicators to evaluate sublethal effects assumes that the ability to perform

normal life functions has been impaired (Schreck 1990). 

It is important to note the difficulty in using sublethal effects seen at the individual level to

extrapolate effects at the population level (Rose et al. 1993). Mortality can be highly dynamic in fish

populations, and high levels of individual mortality from an episodic event, such as a contaminant
171

spill, may not necessarily have a significant effect at the population level (Houde 1989). Using

individual-based modelling, Rose et al. 1993 found that chronic exposures to contaminants were

more likely to affect recruitment of striped bass than episodic exposures. It was also found, however,

that episodic exposures could potentially have a greater impact if they occurred at or shortly after

a spawning peak. 

Swimming performance has been used as a performance indicator in many studies to assess

sublethal effects of contaminants (Beaumont et al. 1995, Heath 1995, Nikl and Farrell 1993).

Reduced swimming performance of individuals has ecological significance through a reduced ability

to avoid predators and catch prey. Vulnerability to predation is dynamic and could be increased by

exposure to contaminants, due to effects on swimming speed, perception, and behavior. In an active

species, such as Florida pompano, Trachinotus carolinus, a reduction in swimming speed may not

necessarily reduce the likelihood of contact between predator and prey, but may effect the chances

of escape once contact is made. For example, exposure may cause abnormal schooling behavior of

a fish, thereby triggering a strike by a predator. 

There is still much to learn about the effects of low-level exposure of marine organisms to

petroleum-related contaminants. Most studies have concentrated on the mortality effects associated

with major oil spills (Peterson et al. 1996, Howarth 1991, Kennicutt et al. 1996). Some studies have

been conducted, however, regarding low-level exposures of fishes to petroleum or to areas where

production platforms occur. Histological changes have been shown to occur in the gills of fishes

surrounding oil production platforms (Grizzle 1986). The effects of exposure to crude oil on

maximum swimming speed of coho salmon (Oncorhynchus kisutch) have also been examined

(Thomas and Rice 1987). 

The Florida pompano was chosen to assess acute and sublethal effects of ethylene glycol because

it occurs in the vicinity of transport pipelines and deepwater wells in the GOM. Florida pompano

is a marine fish of economic importance found in Atlantic and GOM waters from Massachusetts to

Brazil (Hoese and Moore 1977). Juveniles are abundant in and near the surf zone during summer

months. Adults can be found in inshore and offshore waters; however, it is unclear where spawning

occurs (Gilbert 1986). The Florida pompano is a fast-swimming fish that could move quickly

through an area containing sublethal levels of leaked or spilled contaminants. The short-term

exposure of Florida pompano to contaminants such as ethylene glycol may have long-term

consequences for individuals.

The goal of this study was to assess the sublethal effects of ethylene glycol on juvenile Florida

pompano by comparing individual swimming performance before and after exposure to a sublethal

concentration of ethylene glycol. This study found that the mean swimming performance was

reduced by 14% in individuals following a 24 h exposure to a 3.0% concentration of ethylene glycol.

These results provide valuable information on the possible ecological consequences of a low-level

spill or leakage of ethylene glycol into the environment.
172

METHODS

Respirometer Design

Three Blazka-type swimming respirometers were used in simultaneous swimming performance

tests. Each respirometer consisted of two concentric acrylic cylinders, with the inner cylinder having

an inside diameter of 20.32 cm. The volume of each respirometer was 104 L, and the maximum

water velocity was 1 m s-1. Water flow within the cylinder was generated by a propeller at one end

of the inner cylinder and was controlled by a variable-speed DC motor. A plastic honeycomb grid

was placed at each end of the inner cylinder to contain fish and encourage laminar flow.

Each respirometer was individually calibrated to find the relationship of RPM (revolutions per

minute) to water velocity in the flume (cm s-1) using video analysis of particles moving through the

inner cylinder. The regression relationship between RPM and water velocity (cm s-1) was determined

independently for each respirometer, and was used to solve for RPM at each desired water velocity

used in the swimming trials. 

Swimming Performance

Swimming performance before and after sublethal exposure to ethylene glycol was measured and

compared for individual fish (Kolok et al. 1998). In order to keep track of individuals, 21 juvenile

pompano (23.1 g ± 4.73 SD; 102.8 mm FL ± 6.21 SD) were tagged 11 weeks before the start of the

experiment. After anaesthetizing the fish with MS-222, a scheme of colored latex marks (Northwest

Marine Technology,Inc.) was applied by injection to the dorsal, caudal, and anal fins of each

individual. The fish were held following injection in a 5,000 L recirculating seawater system.

Several days prior to the experiment, the tagged fish were randomly separated into groups of three,

to be swum simultaneously in the three respirometers. Two of seven groups were randomly

designated as the ‘control’ groups, and the remaining five groups were designated as ‘treatment’

groups. Each group was randomly assigned to one of seven 60 L holding tanks, which were

connected as a recirculating system with a total volume of 550 L. The holding system was equipped

with a biofilter and UV sterilizer to maintain water quality. Salinity in the holding system was

maintained at 30 ± 1 ppt, and temperature was maintained at 25 ± 1 /C using 200 W aquarium

heaters in each tank. Each holding tank was individually aerated with an air stone. Amquel®

(HOCH2SO3Na) was added to the holding system to control the ammonia level if it rose to 0.5 ppm.

Each group of three fish was fed 0.25 g of 45% protein pellet feed daily, and uneaten feed and waste

were siphoned daily from each tank. 

The daily protocol for the swimming experiment ensured identical fasting, holding, and acclimation

periods for each group of fish, and required 16 days (Table 5.1). This protocol allowed for a 17 h

acclimation period to the respirometers following exposure and a 41 h fasting period (i.e., 24 h

exposure and 17 h acclimation) before pre- and post-exposure swimming trials. Sham exposures

were carried out in the same manner as actual exposures except for the addition of ethylene glycol.

All fish were sham exposed before the first swimming trial, and only the two control groups were

sham exposed before the second swimming trial. Each exposure was carried out in one of three
173

Table 5.1. Daily schedule for swimming performance tests.

Protocol for swimming performance trials

Day 1 At ~ 1600 h, Group 1 fish were placed in the exposure tank for 24 h at 25

/C and 30 ppt for fasting and sham exposure. 

Day 2 At ~ 1600 h, Group 1 fish were placed in the respirometers for acclimation

(~17 h) at 5 cm s-1 in recirculating mode.

At ~ 1600 h, Group 2 fish were fasted and sham exposed.

Day 3 At ~ 0900 h, recirculating mode was terminated and the pre-exposure

swimming test of Group 1 fish was begun.

Group 1 fish were returned to their assigned holding tank for five days.

At ~1600 h, Group 2 fish were placed in the respirometers for acclimation.

At ~1600 h, Group 3 fish were fasted and sham exposed.

Day 4 Repeat: Pre-exposure swimming test of Group 2, acclimation of Group 3,

and sham exposure of Group 4.

Day 5 Repeat: Pre-exposure swimming test of Group 3, acclimation of Group 4,

and sham exposure of Group 5.

Day 6 Repeat: Pre-exposure swimming test of Group 4, acclimation of Group 5,

and sham exposure of Group 6.

Day 7 Repeat: Pre-exposure swimming test of Group 5, acclimation of Group 6,

and sham exposure of Group 7.

Day 8 Repeat: Pre-exposure swimming test of Group 6 and acclimation of

Group 7.

At ~ 1600 h, Group 1 fish were fasted and exposed in a 3.0% ethylene

glycol solution. 

Day 9 Repeat: Pre-exposure swimming test of Group 7, acclimation of Group 1,

and exposure of Group 2.

Day 10 Repeat: Post-exposure swimming test of Group 1, acclimation of Group 2,

and exposure of Group 3.

Day 11 Repeat: Post-exposure swimming test of Group 2, acclimation of Group 3,

and exposure of Group 4.

Day 12 Repeat: Post-exposure swimming test of Group 3, acclimation of Group 4,

and exposure of Group 5.

Day 13 Repeat: Post-exposure swimming test of Group 4, acclimation of Group 5,

and exposure of Group 6.

Day 14 Repeat: Post-exposure swimming test of Group 5, acclimation of Group 6,

and exposure of Group 7.

Day 15 Repeat: Post-exposure swimming test of Group 6 and acclimation of

Group 7.

Day 16 Repeat: Post-exposure swimming test of Group 7.
174

round fiberglass tanks, filled to 60 L with sea water at a salinity of 30 ppt. The temperature of each

exposure tank was maintained at 25 ± 1 /C with a 200 W aquarium heater and the water was aerated

with two air stones. Treatment groups were exposed to a 3.0% ethylene glycol solution before the

second swimming test. To achieve the appropriate concentration, a volume of 1800 ml of ethylene

glycol was added and the tank volume was adjusted up to the 60 L mark. A water sample was collected from the exposure tank at the beginning and end of each exposure period. All exposed fish

were placed in a bucket of clean sea water for several minutes before being placed in the

respirometers.

During the 17 h acclimation period, the three respirometers were connected to a larger recirculating

system that included a UV sterilizer and biofilter. The entire swimming system was housed in a 25

/C temperature-controlled room. The total recirculating volume of the system was about 765 L.

Following exposure, each fish was placed in one of the respirometers for the acclimation interval

at a velocity of 5 cm s-1. Before the start of each swimming trial, each respirometer was cleared of

bubbles and sealed. Each fish was tested in the same respirometer for the pre-exposure and postexposure swimming trials. 

The experimental protocol tested for changes in the swimming performance of individuals before

and after exposure to ethylene glycol by determining pre- and post-exposure critical swimming

speeds (Ucrit) for each individual. During swimming, the velocity of each respirometer was increased

by 10 cm s-1 every 10 min, with no rest interval between steps. The swimming test was terminated

when the fish could no longer continue swimming and made contact with the back grid for about

2-4 s. 

A pre- and post-exposure Ucrit value was calculated for each fish according to the equation described

by Brett (1964):

Ucrit = ui + (ti/tii x uii),

where ui is the highest velocity maintained for the prescribed period, uii is the velocity increment,

ti is the time that the fish swam at the fatigue velocity, and tii is the prescribed period of swimming.

All fish, which failed to fatigue after 10 min of swimming at the respirometer’s maximum speed

(100 cm s-1), were assigned a Ucrit value of 100 cm s-1. The Ucrit values were expressed in terms of

cm s-1 and body lengths per second (BL s-1).

Although water quality was monitored in the chambers during each swimming trial, equipment

problems resulted in the loss of dissolved oxygen data measured at the end of each velocity interval.

A YSI Tele-Thermometer probe was used to continuously record temperature from one of the

respirometers. After each post-exposure swimming test, the fish were anaesthetized with MS-222,

and weights and fork lengths were measured.
175

RESULTS

Swimming Performance

A 14% reduction in swimming performance was observed in fish exposed to 3.0% ethylene glycol

(Table 5.2, Figure 5.1). The mean (± SE) critical swimming speed of treatment fish was 96.0 ± 1.13

cm s-1 (9.4 ± 0.17 BL s-1) in the pre-exposure trial and 83.0 ± 3.45 cm s-1 (8.0 ± 0.26 BL s-1) in the

post-exposure trial. The mean (± SE) critical swimming speed of control fish was 94.1 ± 3.42 cm

s

-1 (9.2 ± 0.17 BL s-1) in the pre-exposure trial, and 98.2 ± 1.28 cm s-1 (9.6 ± 0.23 BL s-1) in the sham

post-exposure trial. These values are somewhat conservative because the fish (11 out of 21) that did

not fatigue after 10 min of swimming at 100 cm s-1 were assigned a Ucrit value of 100 cm s-1. 

There was considerable individual variation between pre- and post-exposure performance. Of the

15 treatment fish, only one individual showed an increase in Ucrit of 1.38 BL s-1 following exposure.

This change in Ucrit, however, was greater in magnitude than the reductions of nine of the other 14

treatment fish. The reduction in performance for all other treated fish ranged from 0.24 to 4.42 BL

s

-1, with a mean value (± SE) of 1.5 ± 0.36 BL s-1. Of the six individuals in the control group, two

individuals slightly improved their performance by 0.58 and 0.25 BL s-1, and one individual greatly

improved its performance by 2.07 BL s-1. The fourth control fish slightly decreased its performance

by 0.31 BL s-1, and the final two individuals out swam the respirometers in both the pre- and posttrials.

DISCUSSION

A 24 h exposure to a 3.0% concentration of ethylene glycol was found to reduce the swimming

performance of individual juvenile Florida pompano in this study by a mean of 14%. Changes in the

performance of control fish were not meaningful, but mean performance did increase slightly by 5%.

While mean critical swimming speed of the treatment group was found to decrease following

exposure, there was considerable individual variation in performance detected in both the treatment

and control groups. A common method in swimming performance studies looking at sublethal

effects of toxicants has been to compare mean performances of control and treatment groups, an

approach that does not address within-group variation. An experimental design that addresses

within-group variation is useful because swimming performance of individual fish has been shown

to be repeatable over time (Kolok 1992, Kolok et al. 1998, Reidy et al. 2000). In a study involving

the exposure of fathead minnows to a contaminated sediment, Kolok et al. (1998) found that a

reduction in the mean post-exposure swimming performance varied widely between individuals,

with two-thirds experiencing only minor reductions and the remaining fish becoming almost unable

to perform. 

The variation between individuals in the present study suggests that some fish may have a higher

threshold of tolerance to ethylene glycol toxicity. Many studies have estimated threshold values for

fish exposed to contaminants by testing swimming speed at a range of exposure concentrations (Nikl

and Farrell 1993, Peterson 1974). Because this study tested fish at only one concentration of
176

Table 5.2. Weight (g), fork length (mm), pre-exposure Ucrit and post-exposure Ucrit (cm s-1, BL s-1)

for treatment and control Florida pompano.

Pre–exposure 

Ucrit

Post-exposure 

Ucrit

Treatment Fish Weight (g) FL (mm) cm s-1 BL s-1 cm s-1 BL s-1

1 26.26 109 84.98 7.80 100 9.17

2 23.4 104 94.2 9.06 82.05 7.89

3 20.13 99 100 10.10 63.65 6.43

4 21.9 102 93.67 9.18 74.55 7.31

5 36.75 116 100 8.62 94.43 8.14

6 19.93 97 93.45 9.63 63.55 6.55

7 20.51 97 90.6 9.34 88.3 9.10

8 16.1 91 94.95 10.43 54.72 6.01

9 22.25 104 100 9.62 87.75 8.44

10 21.27 102 93.75 9.19 87.43 8.57

11 19.25 96 100 10.42 80.4 8.38

12 26.54 105 95.92 9.14 93.42 8.90

13 28.28 110 100 9.09 93.47 8.50

14 21.77 104 97.73 9.40 85.58 8.23

15 21.44 108 100 9.26 95.13 8.81

Mean 23.05 102.93 95.95 9.35 82.96 8.03

SE 1.26 1.65 1.13 0.17 3.45 0.26

Control Fish Weight (g) FL (mm) cm s-1 BL s-1 cm s-1 BL s-1

1 18.14 96 86.85 9.05 92.37 9.62

2 23.94 104 100 9.62 96.73 9.30

3 22.2 103 100 9.71 100 9.71

4 18.19 94 80.53 8.57 99.98 10.64

5 28.17 106 97.35 9.18 100 9.43

6 29.24 111 100 9.01 100 9.01

Mean 23.31 102.33 94.12 9.19 98.18 9.62

SE 1.94 2.59 3.42 0.17 1.28 0.23
177

7

7.5

8

8.5

9

9.5

10

Pre Post

Ucrit (BL/s)

Treatment

Control

Figure 5.1. Mean Ucrit (BL s-1) of Florida pompano before and after a 24 h exposure to 3.0%

ethylene glycol (treatment), and before and after sham exposure (control).

ethylene glycol, it is not possible to calculate a mean threshold value for this species. Nevertheless,

we can assume from the biological meaningful reduction in swimming speed that the threshold is

at or below the 3.0% ethylene glycol concentration (53% of the estimated LC50 for slightly smaller

fish).

There are several ways in which toxicants, such as ethylene glycol, may cause a reduction in the

swimming performance of fishes. Jones (1971) proposed several possible factors, including an

inability to exchange enough oxygen at the gills, an inability to deliver enough oxygen to the tissues,

and an inability to remove metabolic products or to activate enzymic processes. A reduction in the

ability to transfer oxygen across the gills would effectively decrease the scope for active metabolism

of the fish, thereby reducing the fish’s capacity for sustained swimming activity. It is unclear from

this study whether gill damage was a direct influence on the reduction in swimming performance

of exposed individuals, due to the use of MS-222 before sacrifice. 

Due to the nature of ethylene glycol, the reduction in swimming performance seen in this study may

have been due to the buildup of metabolic products. Studies on mammals have shown that ethylene

glycol is sequentially oxidized in the liver (Chou and Richardson 1978) and involves several

metabolites, with glycolate (glycolic acid) playing a major role in ethylene glycol toxicity. The

increased cost of maintenance to remove these metabolites effectively increases the basal

metabolism, thereby reducing the capacity for activity. Therefore, the reduced Ucrit of the exposed
178

fish in this study may have been a direct result of the increased metabolic costs to remove toxic

metabolites.

The LC50 values reported in other studies (Table 5.3) on ethylene glycol exposure in fish are

generally considered to reflect relatively low toxicity. Fish would be most likely to be exposed to

these concentrations in the event of highly localized, large-scale releases into the environment.

Marine releases of considerable magnitude, however, have been reported. For example, 13,523 L

(3,570 gal) of ethylene glycol leaked into the GOM from an underwater pipeline in June of 1998

(U.S. Coast Guard, National Response Center, Report # 444025). This study shows that sublethal

effects can be manifested after only a short exposure (24 h) to large releases of ethylene glycol. Fish

are more likely to be exposed for a short-term due to the relatively rapid biodegradation of ethylene

glycol. Bio-oxidation of ethylene glycol in the laboratory was 39% in 5 days and 96% in 20 days

(Conway et al. 1983). Dissipation of the chemical in the marine environment would be expected to

be even more rapid. Other factors affecting the toxicity of ethylene glycol must also be considered,

such as additive or synergistic effects when combined with other chemicals. The toxicity of ethylene

glycol was found to increase in fish when sublethal levels of thiram, a component of an agricultural

seed-protectant, were present (Greene and Kocan 1997), and when it was combined with other

chemicals in a deicing agent (Pillard 1995).

Table 5.3. Estimated LC50 values for several fish species exposed to ethylene glycol.

Reference Species Mean Size (g)

Test

Duration LC50 (%)

Abdelghani et

al. 1990

Bluegill sunfish

(Lepomis macrochirus)

0.85 ± 0.60 96 h 2.75

Pillard 1995 Fathead minnow

(Pimephales promelas)

(# 7 days old) 96 h 7.29

Greene and

Kocan 1997

Fathead minnow 0.10 ± 0.01

0.13 ± 0.01

96 h

96 h

6.83

6.95

Rainbow trout

(Oncorhynchus mykiss)

0.71 ± 0.20

1.50 ± 0.50

96 h

96 h

6.08

5.65

Kay 2000 Florida pompano

(Trachinotus carolinus)

7.98 ± 3.20 24 h 5.63

There are several recommendations that can be made for future research in light of this study. First,

the effects of ethylene glycol on the gills need to be examined without the use of the anaesthetic,

MS-222, which may confound the results. It would also be useful to determine if a shorter exposure

than our target concentration, 3.0% ethylene glycol, has significant effects on the gill structures or

swimming performance of Florida pompano. The effects of a short exposure to a lethal

concentration of ethylene glycol, using a range of exposure periods, could also be evaluated. Finally,

by studying the effects of exposure on feeding and growth, more information would be obtained
179

regarding the ecological implications of ethylene glycol exposure on juvenile Florida pompano at

the population level (Rose et al. 1993). 

In summary, we have shown that a marine fish can experience reduced performance when exposed

to sublethal levels of ethylene glycol. The implications of these results include adverse effects on

the ability to perform in ecological situations. While normal cruising speeds of Florida pompano are

not near the high critical swimming speeds observed in this study, the capacity for burst swimming

and endurance are undoubtedly reduced, directly affecting the efficiency of prey capture and

predator avoidance. Understanding sublethal effects such as these is important for the accurate

prediction of the impacts of habitat and environmental changes on fish populations.

ACKNOWLEDGMENTS

We would like to thank Kenny Rose and Jaye Cable for their comments, Marcus Bradley for his help

in conducting the experiments, and Russel Martin for constructing the respirometers. We would also

like to thank the Minerals Management Service for providing the funding for this study.

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182

EFFECTS OF THE NEPHELOID LAYER ON BIOFOULING COMMUNITIES

OCCURRING ON COASTAL PETROLEUM PLATFORMS IN

THE NORTHWESTERN GULF OF MEXICO

Thomas W. Bates

Q. R. Dokken

Center for Coastal Studies

Texas A&M University-Corpus Christi

ABSTRACT

The Texas continental shelf in the Gulf of Mexico is a dynamic region influenced by winds, river,

and offshore currents. The shelf is composed of terriginous sediment that contains varying amounts

of silt and clay. There is a persistent bottom layer of turbid water, a nepheloid layer, which appears

to be derived from both local resuspension of fine sediment and advection in the bottom boundary

layer from coastal sources. Approximately 4000 petroleum production platforms are located in the

Gulf of Mexico with many lying on the shelf where the nepheloid layer is persistent. Offshore

platforms act as artificial reefs, providing critical habitat on large submerged surfaces for

recruitment and settlement of larval sessile organisms. The biofouling community could be directly

related to fisheries associated with platform structures. The purpose of this study is to determine

significant differences caused from the presence of the nepheloid layer in the structure of biofouling

communities on four Texas coastal petroleum platforms. Photographic transects and biomass

samples will be used to describe the biofouling community. Data loggers will be used to record

temperature and light attenuation parameters. Turbidity and physiochemical properties of water will

be sampled in the vicinity of the data loggers. All data will be used to create a model associating

turbidity with the biofouling community of Texas coastal platforms where a nepheloid layer is

persistent for much of the year.
183

VERTICAL DISTRIBUTION AND HABITAT ASSOCIATION OF FOUR BLENNIIDAE

SPECIES ON GAS PLATFORMS IN THE NORTHCENTRAL GULF OF MEXICO

Marek F. Topolski

Department of Fisheries

Auburn University

Stephen T. Szedlmayer

Department of Fisheries

Auburn University

Gulf Coast Experimental and Research Center

ABSTRACT

The abundance of Blenniidae on platforms in the northern Gulf of Mexico may be substantially

underestimated. Previous studies have reported the abundance of blenny species on platforms to

range between 0.6 fish and 16 fish m-2. In this study, we used visual surveys to quantify densities

of four blenny species (Hypsoblennius invemar, Hypleurochilus multifilis, Parablennius marmoreus,

and Scartella cristata) on two gas platforms 14 to 24 km southeast of Dauphin Island, Alabama in

July and August 1999. Our mean Blenniidae densities were substantially higher than those in

previous accounts. Densities of all four species decreased as depth increased from 3 m to 18 m: 10

fish m-2 to 1 fish m-2 (H. invemar), 23 fish m-2 to 6 fish m-2 (H. multifilis), 6 fish m-2 to 2 fish m-2 (P.

marmoreus), and 89 fish m-2 to 0 fish m-2 (S. cristata). Blenny length distributions were estimated

using three 51 mm total length (TL) categories. Eighty percent of H. invemar, 74% of H. multifilis,

49% of P. marmoreus, and 47% of S. cristata were < 51 mm TL. Blennies occupy crevices and

cavities, so, the fouling community on the platform pilings was sampled to predict why blennies <

51 mm TL were so abundant. We measured the abundance of fouling organisms such as barnacles,

mollusks, and sponges that can affect the availability of crevices and cavities. Abundance of the

large barnacle Balanus tintinabulum decreased significantly as depth increased from 3 m to 18 m

(χ2 = 15, p < 0.05), substantially affecting local relief and hence habitat available to blennies.

However, B. tintinabulum abundance was not useful for predicting the abundance of H. multifilis

(r2 = 0.04, p > 0.05) and P. marmoreus (r2 = 0.07, p > 0.05). Balanus tintinabulum abundance did

account for 48% (p < 0.05) of H. invemar and 81% (p < 0.05) of S. cristata variability. The

community structure of non-game fishes, like Blenniidae, can be used to estimate the ecological

success of artificial structures as reefs.
184

VERTICAL AND WITHIN PLATFORM SPATIAL VARIABILITY OF LARVAL

AND JUVENILE FISHES ASSOCIATED WITH PETROLEUM

PLATFORMS OFF LOUISIANA

Frank J. Hernandez, Jr.

Department of Oceanography and Coastal Sciences

Louisiana State University

Richard F. Shaw

Department of Oceanography and Coastal Sciences and 

Coastal Fisheries Institute

Louisiana State University

ABSTRACT

Oil and gas platforms are effective in attracting recreationally- and commercially-important fishes,

but whether these structures contribute to new fish biomass is still debatable. To ascertain the habitat

enhancement value of petroleum platforms, information on supply, distribution, and spatial

variability of larval fishes associated with these structures is needed. We sampled ichthyoplankton

at three petroleum platforms in the northern Gulf of Mexico: Green Canyon 18 (230 m depth),

Grand Isle 94 (60 m depth), and South Timbalier 54 (20 m depth). Fish larvae and juveniles were

collected within the structures (passive plankton net and light-trap fished at depth and near-surface)

and immediately downstream of the platforms (light-trap floated downstream at surface). Overall,

mean light-trap catch per unit efforts (CPUEs) were significantly higher in surface samples,

particularly within the platform, than in sub-surface samples (clupeiforms excluded). Mean plankton

net densities for surface samples were significantly lower than sub-surface samples at two platforms

(clupeiforms excluded). Distributional differences were observed for many species within and

around the platforms. Few taxa were found only in off-platform samples (4 at Green Canyon, 6 at

Grand Isle, and 12 at South Timbalier). Some pelagic species, e.g., Caranx crysos and C.

hippos/latus (Green Canyon) and Euthynnus alletteratus (Grand Isle and South Timbalier) generally

had higher CPUEs in surface waters downstream from the platforms. Several species were collected

only at depth, particularly mesopelagic and benthic taxa, e.g., Chlorophthalmus agassizi (Green

Canyon), Robia legula (Grand Isle), and Ophidion robinsi (South Timbalier). Other taxa

predominantly found at depth included Mugil cephalus (Green Canyon), Symphurus spp. (Grand

Isle), and Ariomma spp. (South Timbalier). Few differences were observed between ShannonWeiner diversity indices calculated by gear and location, with the exception of sub-surface light-trap

samples, which were significantly lower in diversity at two platforms.
185

THE ACROSS-SHELF LARVAL, POSTLARVAL, AND JUVENILE FISH COMMUNITY

ASSOCIATED WITH OFFSHORE OIL AND GAS PLATFORMS AND A COASTAL

ROCK JETTY WEST OF THE MISSISSIPPI RIVER DELTA

Frank J. Hernandez, Jr.1

Richard F. Shaw1, 2

Joseph S. Cope2

James G. Ditty3

Talat Farooqi2

Mark C. Benfield1, 2

1

Department of Oceanography and Coastal Sciences, Center for Coastal Energy and

Environmental Resources, Louisiana State University

2

Coastal Fisheries Institute, Louisiana State University

3

NOAA/NMFS, Southeast Fisheries Science Center

ABSTRACT

The fisheries aggregation value of oil and gas platforms in the continental shelf waters of the

northern Gulf of Mexico (GOM) is well recognized, but the assessment of early life stages

associated with these structures has not been adequately addressed. Ichthyoplankton assemblages

were sampled at three offshore platforms: Green Canyon 18 (GC 18; 230 m depth, shelf slope);

Grand Isle 94 (GI 94; 60 m depth, mid-shelf); and South Timbalier 54 (ST 54; 20 m depth, inner

shelf) with passive plankton nets and light-traps and at a coastal rock jetty (Belle Pass; 3-5 m depth)

with a light-trap and a plankton pushnet. Family richness was highest at GC 18 (52), followed by

GI 94 (43), ST 54 (42), and Belle Pass (41). At the genus level, richness was highest at Belle Pass

jetty (127), followed by GI 94 (114), ST 54 (86), and GC 18 (82). At all sites, clupeiforms

dominated samples, comprising 59-97% of the total catch. Gobiids and blenniids dominated the reefassociated fish assemblages at all sites. Other relatively common reef-associated fish were serranids

and lutjanids (GC 18), pomacentrids and opisthognathids (GI 94), Rhomboplites aurorubens (ST

54), and Lutjanus griseus and L. synagris (Belle Pass). The ichthyoplankton assemblages sampled

at each site were relatively dissimilar, based on Schoener’s Index of Niche Overlap, with the highest

index value for any two sites being 0.45 for GI 94 and ST 54 (0-1 scale; clupeiforms excluded). No

significant difference was observed between mean Shannon-Weiner diversity indices calculated for

plankton net samples at each site. For light-trap samples, diversity was lowest at GC 18,

significantly higher at GI 94, and then decreased inshore. Canonical correlation analyses indicated

that temperature and salinity explained most of the variation in larval abundance for some dominant

taxa at the platforms, while at Belle Pass jetty, dissolved oxygen and turbidity were also important

environmental variables.

INTRODUCTION

The GOM yields about 40% of the U.S. commercial fish landings (NOAA/NMFS 1993) and

supports 33% of the country’s recreational fishery (Essig et al. 1991; Van Voorhies et al. 1992). The
186

region also possesses the vast majority of the nation’s coastal wetlands. Louisiana alone has over

3.8 million acres (>40% of the nation’s total), but these areas are disappearing at an alarming rate,

i.e., Louisiana land loss represents 60-80% of the nation’s total annual coastal wetland loss (Boesch

et al. 1994). The continual loss of GOM estuarine and wetland habitats that serve as the nursery

grounds for a large number of commercially- and recreationally-important fisheries makes

knowledge of the potential nursery function of other habitats critical. Habitat issues have received

increased attention lately, in part due to the Essential Fisheries Habitat Provisions added to the

Federal Sustainable Fisheries Act of 1996 that facilitate the long-term protection of waters and

substrate necessary to fish for spawning, breeding, feeding or growth to maturity (USDOC 1996).

The introduction and proliferation of offshore oil and gas structures in the northern GOM has

undoubtedly affected the marine ecosystem. There are approximately 4,000 oil and gas structures

in the federal waters of the GOM. The central and western GOM is dominated by a mud/silt/sand

bottom with little relief or hard bottom habitat. Parker et al. (1983) reported only 2,780 km2 of

natural available reef in the central and western GOM. Although Gallaway (1998) calculated that

oil and gas platforms in the northern GOM provided 11.7 km2 (or 4.0%) of the total “reef” habitat,

the fact that platforms represent vertical artificial substrate that extends from the bottom to the

surface (photic zone), regardless of location and depth, increases their significance. Since fish

populations are usually limited by available energy, recruitment, or habitat, it is important to

determine whether platforms: 1) provide critical habitat for early life history stages; 2) serve as new

or additional spawning habitat; and 3) influence energy flow through the ecosystem by aggregating

prey.

Oil and gas platforms can enhance fisheries by providing attachment substrate for habitat-limited

sessile invertebrates, thereby creating food and habitat for reef-dependent species that are

trophically-dependent on sessile and motile invertebrates associated with reefs (Gallaway 1981;

Bohnsak and Sutherland 1985; Stephan et al. 1990; Bohnsak 1991). Since reef fish assemblages are

among the most diverse and taxonomically rich in the aquatic biosphere (Sale 1991), platform

communities may significantly enhance biodiversity. In addition, oil and gas structures may offer

refugia for species which are trophically-independent of the biofouling community (i.e., reefassociated species; Choat and Bellwood 1991), but are ecologically-important resident, seasonal,

or transient members of the hard substrate fish community (Gallaway et al. 1980). The extensive

range (latitudinally and longitudinally) of this artificial substrate may also serve as migratory routes

for tropical and subtropical species.

The adult fish communities around natural and artificial reefs are fairly well known (Seaman and

Sprague 1992; Rooker et al. 1997; Stanley and Wilson, 2000) and the fisheries aggregation value

of oil and gas structures is well-recognized in the GOM (CDOP 1985). Despite research efforts,

however, biologists still disagree over the paradigm of whether these artificial reefs (e.g., platforms)

contribute significantly to new fish production or simply attract and concentrate existing fish

biomass(Pickering and Whitmarsh 1997; Bortone 1998). Existing data on adult fishes support both

sides of the debate (Stone et al. 1979, Alevizon et al. 1985). Bohnsak (1989) theorized that reef

effects fall along a continuum between attraction of existing organisms and production, with

increased productivity occurring for reef-dependent species in areas of limited hard substrate habitat.

Since the central and western GOM has little natural reef habitat, we believe that the contribution
187

of artificial reefs to existing reef habitat has enhanced reef fish populations, but the overall or net

impact of this augmentation is not known, especially when corrected for increased fishing mortality

associated with platforms (Stanley and Wilson 1990).

Few baseline ecological ichthyoplankton studies within the oil field have been published (Finucane

et al. 1979a; Finucane et al. 1979b; Bedinger et al. 1980), and none have been published that focus

upon platform infrastructure. The Southeastern Area Monitoring and Assessment Program’s

(SEAMAP) and the National Marine Fisheries Service’s (NMFS) Gulf-wide fisheries surveys, and

the Minerals Management Service Louisiana-Texas (MMS LATEX) Physical Oceanography

Program have not sampled in the immediate vicinity of oil and gas platforms because of the

conservative navigation/safety requirements of their ships. Thus, fisheries-independent assessment

of the abundance of fish life stages within and immediately around these platforms and the role they

might play as essential fisheries habitat is not being adequately addressed in federal waters where

such structures exist. Clearly, additional information is needed on the early life history stages of

fishes associated with petroleum platforms.

ACROSS-SHELF ICHTHYOFAUNAL ZONATION

Gallaway et al. (1980) and Gallaway (1981) reviewed previous descriptions of invertebrate and

vertebrate faunal assemblages from the northcentral GOM’s continental shelf and characterized

differences largely upon different bottom types (fluvial/terrigenous sediments west of the

Mississippi River Delta and carbonaceous sediments to the east), circulation patterns, and related

hydrographic conditions. Climatic differences were also acknowledged as having an important role

in determining faunal distributions, since the inner shelf waters of the northern GOM are warm and

subtropical in the eastern GOM and along the southwestern coast near the Mexican border, but are

warm-temperate from just east of the Mississippi River Delta to Matagorda Bay, Texas (Parker

1960). Reef fish fauna are generally less tolerant of the lower water temperatures that can occur in

the more inshore areas during winter in the northern GOM (Chittenden and McEachran 1976).

Along with temperature, topographical relief is another major factor contributing to the distribution

of reef fish. Although topographical relief is described as extensive throughout the GOM (Bright

et al. 1974), it is also disjunctly distributed, thus potentially isolating reef fish populations. Several

authors attempted to classify shelf ichthyofaunal assemblages based on depth zones and invertebrate

distributions. Defenbaugh (1976), for example, used macroinvertebrate data from trawls to describe

three primary depth zones (4-20 m, 20-60 m, and 60-120 m). In his review, however, Gallaway

(1981) adopted the zonation description of Chittenden and McEachran (1976) who observed that

the distribution of major shrimp species (white shrimp grounds, 3-22 m depth and brown shrimp

grounds, 22-110 m depth) matched quite closely the distribution of sediment types and used this

information, along with bathymetry, to divide demersal fish assemblages into three different zones

characterized primarily by depth.

Table 5.4 summarizes reef or structure-associated fish for Gallaway’s (1981) analysis of previous

studies that addressed demersal and pelagic adult fish off Texas (Chittenden and McEachran 1976)

and adult reef species off Louisiana, including both artificial and natural reefs (George and Thomas

1974; Gallaway et al. 1979; Shinn 1974; Sonnier et al. 1976). Distinct transitions in species

assemblages can be seen in the reef species when analyzed across depths. Overall, the outer shelf
188

Table 5.4. Summary of the commonly observed adult fish assemblages associated with natural

reefs or offshore oil and gas platforms by depth zones as reported in Gallaway et al.

(1980) and subsequently modified by Gallaway (1981). Taxa were reported from

these depth zones as being affiliated with natural reefs (N) or artificial reefs (A).

Ichthyofaunal Assemblage

Gallaway et al. (1980)

Taxa Coastal

(3-27 m)

Offshore

(27-64 m)

Blue Water or Tropical

(>64 m)

Gallaway (1981)

 Inner Shelf

(White Shrimp Ground)

(3-20 m)

Intermediate Shelf

(Brown Shrimp Ground)

(20-60 m)

Outer Shelf

(Tropical)

(>60 m)

Serranidae

 Epinephelus spp.

 (grouper spp.)

N

 Epinephelus itajara

 (jewfish)

A

 Epinephelus nigritus

 (warsaw grouper)

A

 Mycteroperca spp.

 (grouper spp.)

N

 Paranthias furcifer

 (creole-fish)

N, A

Pomatomidae

 Pomatomus saltatrix

 (bluefish)

A A

Rachycentridae

 Rachycentron canadum

 (cobia)

A

Carangidae

 Caranx crysos

 (blue runner)

A A N, A

 Caranx hippos

 (crevalle jack)

A

 carangid spp.

 (jack spp.)

A AN

 Selene setapinnis

 (moonfish)

A

 Selene vomer

 (lookdown)

A A

 Seriola rivoliana

 (almaco jack)

N, A

Lutjanidae

 Lutjanus campechanus

 (red snapper)

 AN
Table 5.4. (continued)

189

Ichthyofaunal Assemblage

Gallaway et al. (1980)

Taxa Coastal

(3-27 m)

Offshore

(27-64 m)

Blue Water or Tropical

(>64 m)

Gallaway (1981)

 Inner Shelf

(White Shrimp Ground)

(3-20 m)

Intermediate Shelf

(Brown Shrimp Ground)

(20-60 m)

Outer Shelf

(Tropical)

(>60 m)

 Lutjanus synagris

 (lane snapper)

A A

 Rhomboplites aurorubens

 (vermilion snapper)

N

Haeumulidae

 Haeumulon melanurum

 (cottonwick)

N

Sparidae

 Archosargus probatocephalus

 (sheepshead)

A A

Kyphosidae

 Kyphosus sectatrix

 (Bermuda chub)

A

Ephippidae

 Chaetodipterus faber

 (Atlantic spadefish)

A A

Chaetodontidae

 butterflyfish spp. A N

Pomacanthidae

 Holacanthus tricolor

 (rock beauty)

A

 pomacanthid spp.

 (angelfish spp.)

A N, A

Pomacentridae

 damselfish spp. A N, A

Cirrhitidae

 Amblycirrhitus pinos

 (redspotted hawkfish)

A

Sphyraenidae

 Sphyraena barracuda

 (great barracuda)

A A

Labridae

 Bodianus rufus A
190

Ichthyofaunal Assemblage

Gallaway et al. (1980)

Taxa Coastal

(3-27 m)

Offshore

(27-64 m)

Blue Water or Tropical

(>64 m)

Gallaway (1981)

 Inner Shelf

(White Shrimp Ground)

(3-20 m)

Intermediate Shelf

(Brown Shrimp Ground)

(20-60 m)

Outer Shelf

(Tropical)

(>60 m)

 (Spanish hogfish)

Decodon puellaris

 (red hogfish)

A

Clepticus parrai

 (creole wrasse) 

N, A

Scaridae

 parrotfish spp. N

Blenniidae

 blenny spp. A

Acanthuridae

 surgeonfish/tang spp. A A

Balistidae

 Balistes capriscus

 (gray triggerfish)

A A

(>60 m depth) reefs appear to be more speciose, followed by the mid-shelf (20-60 m) and then the

inner shelf (3-20 m). More tropical taxa are present on the outer shelf reefs, such as haemulids,

labrids, and scarids, and similar taxa occurred on both natural and artificial reefs. There was some

overlap between reef species on the outer shelf and mid-shelf (chaetodontids, pomacanthids, and

pomacentrids), but the previously mentioned tropical taxa are replaced by more temperate reef

species, such as serranids, Archosargus probatocephalus, pomatomids, and rachycentrids. Also, taxa

that are common on artificial reefs on the mid-shelf are generally common on the inner shelf as well.

In general, Caranx crysos and other jacks were noted as being relatively common reef-associated

species in each zone.

Few studies have attempted to compare the ichthyofaunal assemblages specifically associated with

oil and gas platforms in the northcentral GOM across wide depth zones, and the information that is

available primarily concerns adult fishes and not their early life history stages. Sonnier et al. (1976)

surveyed oil and gas platforms (18-55 m depth) as well as inshore (37-59 m) and offshore (110-155

m) reefs off Louisiana and described the offshore reefs as being more speciose than inshore reefs

or platforms. This greater offshore reef species richness was primarily due to the presence of

southern Gulf-Caribbean taxa (e.g., butterflyfishes, parrotfishes, and cleaning gobies) and taxa

common to reefs in the northwestern GOM off Texas. The authors suggested that the lower

temperatures that occur at the inshore reefs and platforms are a limiting factor in the number of

species, particularly tropicals, which inhabit inshore reef habitats. As one progressed inshore, the
191

tropical fauna was replaced by more temperate reef fish species, including Archosargus

probatocephalus, Selene vomer, and Lutjanus griseus (Sonnier et al. 1976). Twelve species,

including tropicals such as Cantherhines macrocerus, Melichthys niger, and Diodon holocanthus,

were found only at the platform sites. 

ICHTHYOPLANKTON ASSOCIATED WITH OIL AND GAS PLATFORMS

We are aware of only one study that investigated the ichthyoplankton community found in proximity

to petroleum platforms. Finucane et al. (1979b), using bongo and neuston nets, sampled within 30-

90 m of two oil platforms and two satellite (well) jackets in 17 m of water within the Buccaneer Oil

Field, approximately 50 km south southeast of Galveston, Texas. Two far-field, control sites were

also sampled for comparison. Three 2-day cruises (13-14 July 1977; 13-14 October 1977; and 20

and 22 February 1978) collected 15,711 fish larvae, primarily engraulids, sciaenids, and bothids.

Analyses were limited, but species richness was found to be greatest at the platform sites in July and

October and at the satellite structures in February. Overall, of the 68 taxa identified to genus, 38

were associated exclusively with at least one of the structure sites, while another 29 were found near

both structure sites and control sites. Dominant taxa at the platform sites included unidentified

engraulids (26.1%), Anchoa spp. (8.8%), Cynoscion spp. (7.3%), and Syacium spp. (5.9%).

Dominant taxa at the satellite stations were once again unidentified engraulids (32.5%) and Anchoa

spp. (13.4%), along with Micropogonias undulatus (11.2%), Cynoscion spp. (5.5%), and

unidentified clupeids (5.4%). No dominant taxa list was reported for the far-field stations. Based on

eggs and larval abundance, the petroleum field was determined to be an active spawning area for

anguilliforms, callionymids, clupeids, sciaenids, scombrids and soleids, but reef fish eggs and larvae

were not abundant. Noteworthy reef or structure-associated taxa collected during the survey include

Etelis oculatus, Lutjanus campechanus, Centropristis spp., Diplectrum spp., and Serraniculus

pumilio, although Etelis oculatus and Diplectrum spp. were also collected in the far-field control

sites. 

While the Buccaneer Oil Field study did attempt to address larval fish assemblages near petroleum

structures, all of the sites with structure were within a 5 km radius from each other, and all sites,

including the controls, were in 17 m of water, not allowing for any comparisons of different

community regimes across depth zones or large geographic areas. Also, sampling in the oil field

study was limited to only three 2-day cruises. While our study has no replicate platforms within the

Gallaway’s (1981) depth zones, all three zones were sampled intensively, allowing for at least a

preliminary characterization of ichthyoplankton assemblages associated with these artificial habitats

across the continental shelf.

OBJECTIVES

This study focused on three main objectives. The first was to provide much-needed information on

the role that oil and gas platforms (hard substrate habitat) may play as nursery/recruitment grounds

and/or refugia for postlarval and juvenile fish, which could contribute to fish production. Secondly,

we wished to respond to specific requests for more basic biological information on reef fish, e.g.,

larval, postlarval, and juvenile taxonomy, seasonality, lunar periodicity, distribution (vertical and

across shelf), and relative abundance. Finally, as a long-term objective, we wished to evaluate the
192

ecological significance that this artificial habitat building, which has occurred on an unprecedented

scale in the northcentral GOM, may have had on the early life history stages of fish. These

objectives were accomplished by collecting a wide variety of taxa and sizes utilizing two sampling

techniques, light-trap methodology and more traditional techniques (i.e., passive horizontal and

hauled vertical plankton net collections). These methodologies complemented each other, since nets

effectively sample yolk-sac, larval, and some postlarval fishes, whereas light-traps sample

photopositive species at overlapping and larger sizes to give us more complete estimates of sizes

(cohorts or inferred ages) and developmental/early life history stages present (Gregory and Powles

1988; Choat et al. 1993). An integral part of this study, therefore, was the development of an

effective sampling strategy and its subsequent evaluation for collecting larval fish for the first time

within and immediately around platform infrastructure (Hernandez and Shaw this volume).

Data collection and analyses focused on three offshore oil and gas platforms in the northcentral

GOM and at a low-salinity, coastal rock jetty environment, which provided a far-field, non-platform

site, end-member that was equally complex structurally and represented another artificial, reef-like,

hard-substrate habitat. The resultant analyses and synthesis of these efforts and ongoing sampling

efforts east of the Delta (Figure 5.2) are intended to build a practical characterization and synthesis

leading to a much broader understanding of platform ecology and pertinent environment issues over

a larger geographic region. 

MATERIALS AND METHODS

Study Areas

Two pilot studies at oil and gas platforms off the Louisiana-Texas border were conducted, one at

Mobil’s West Cameron (WC) 352 during November 1991-August 1992 and the other at Mobil’s WC

71D in July 1994 (Figure 5.2). West Cameron 352 is located along the Louisiana/Texas border

(28°59'35"N, 93°30'15"W) in about 20 m of water. West Cameron 71D is located off western

Louisiana (29°37.30' N, 93°10.54' W) in approximately 12 m of water. These exploratory studies

were followed by sampling along a transect west of the Mississippi River Delta with site selection

for platforms based upon the work of Gallaway et al. (1980), Gallaway (1981), and Continental

Shelf Associates (1982), who reported that nekton communities around platforms could be

categorized by water depth in the northern GOM. Three communities were characterized: a coastal

assemblage (water depths <27m), an offshore assemblage (water depths 27 to 64 m), and a

bluewater/tropical assemblage (water depths >64m). The platforms selected and the jetty site

encompass all three zones. Mobil’s Green Canyon (GC) 18, which lies in about 230 m of water on

the shelf slope (27°56'37"N, 91°01'45"W), was sampled monthly during new moon phases over a

two- to three-night period during July 1995-June 1996. Mobil’s Grand Isle (GI) 94B, which lies in

approximately 60 m of water at mid-shelf (28°30'57"N, 90°07'23"W), was sampled twice monthly

during new and full moon phases over a three-night period during April-August 1996. During May,

extra samples during the first-quarter and third quarter moon phases were collected, but due to

inclement weather, full-moon collections were cancelled. Exxon’s South Timbalier (ST) 54G, which

lies in approximately 20 m of water on the inner shelf (28°50'01"N, 90°25'00"W), was sampled
Figure 5.2. Sites sampled during and before the course of the study. Open squares are sites of the oil and gas p

coastal jetty sampled during the course of this study. Solid squares represent sites sampled previoustudies. Open circles represent sites of ongoing sampling for future comparisons.
194

twice monthly during new- and full-moon periods during April-September 1997. All platforms had

very similar structural complexity. GC 18 was a very large six pile (column or leg) production

platform, while GI 94 and ST 54 were eight pile production platforms. The stone rubble jetties (2-3

m depth) at the terminus of Belle Pass, a major shipping channel near Fourchon, Louisiana (N 29

03.90, W 90 13.80), were also sampled over a two-night period in 1997 simultaneously with the

sampling of ST 54. The two jetties are approximately 91 m apart and run in a general north-south

direction. The east jetty is approximately 335 m long and the west jetty is approximately 305 m

long. Depths along the jetties ranged from 3-5 m. 

Sampling Procedure

Collections were made at WC 352 within the platform structure during seven sampling periods

between November 1991 and August 1992. All sampling commenced and terminated at least one

hour after sunset and before sunrise, respectively. Each sample was obtained by deploying a

modified quatrefoil light-trap (Hernandez and Shaw this volume) for 10 to 15 minutes, although two

35-minute samples were also collected. Samples were taken concurrently at depths of 1 m (surface)

and 18 m (subsurface) from February-May 1992 only. Surface samples were obtained by lowering

a trap with flotation into the water. Subsurface samples were collected by lowering a trap without

flotation along a stainless steel cable guideline tethered to the bottom. 

Samples were collected at WC 71D over three consecutive nights (21-24 July 1994). All sampling

commenced or terminated at least one hour after sunset and before sunrise. Three light-trap designs,

a modified quatrefoil, a Doherty trap (Doherty 1987), and a cylindrical design (an acrylic model

modified from Riley & Holt (1993), were deployed off a stainless steel cable guideline within the

platform structure. Sampling depths included 1 m (surface) and 8.5 m (night 3 only). In addition,

six vertical plankton haul samples (202- m mesh, 60-cm diameter net) were collected during night

2. The net, mounted on a rigid frame and attached to the central cable, was lowered to the bottom

(effective depth = 8.5 m) and raised at approximately 1 m/s after a five-minute interval to allow the

water column to restabilize. A set of samples included one sample by each of the three light traps,

and there were six sets made each night, except for night 3 when four sets were made near the

surface and four sets were taken at depth. On night 2 only, a vertical net tow was added to each set.

The order of the trap (or vertical net tows) collections was randomized within each set as was the

case with all subsequent platform sampling. 

Sampling protocols for GC 18, GI 94, and ST 54 were similar. At GC 18, eleven monthly sampling

trips were taken over a three-night period coinciding with new moon phases from July 1995-June

1996, with the exception of the month of December (adverse weather). New moon phases were

targeted at this platform because they have been associated with the peak recruitment periods of

many reef-associated fishes (Johannes 1978; Robertson et al. 1988). All sampling began one hour

after sunset and was completed one hour before sunrise. The major sampling station for each

platform was located in the internal central region along a stainless steel, small-diameter guidewire

(monorail) tethered to the first set of the platform’s underwater, cross-member, support structures.

At this central station, replicate trap collections (N = 2) were taken three times each night at nearsurface (1-2 m depth) and at a depth between 15 and 23m, depending upon the individual platform’s

underwater configuration of the first set of cross-member supports. Subsurface samples were
195

collected by lowering a trap without flotation. Light-traps were deployed for 10-minute periods.

Passive, horizontal plankton net collections were taken three times at both depths during each night

at the central station using a metered (General Oceanics flowmeter model 2030 with slow velocity

rotor), 60-cm diameter, 333μm mesh net dyed dark green. The nets had a vane (to help orient into

the current) which was fixed to a gimbled attachment on the net ring, which allowed the net to be

set and retrieved closed for the at-depth deployment. In addition, three collections each night were

made with a floating light-trap that was tethered and free-drifted away (off-platform) from the

platform (approximately 20 m) on the down-current side of the platform. For light-traps sampled

at depth or off-platform, the trap was deployed with the light off, fished with the light on, and then

retrieved with the light off.

Temperature (°C) and salinity (ppt), turbidity (NTU), and current speed and direction were

determined during each set using either a Data Sonde 3 Hydrolab or an Inter Ocean S4 Current

Meter. During each set, a vertical plankton net (20-cm diameter, 63-μm mesh) which was held

rigidly to the guidewire by a frame, was lowered codend first to the bottom of the monorail, left at

depth for 5 minutes for water column restabilization, and then hauled to the surface at approximately

1m/s to ascertain macrozooplankton biomass as a measure of food availability. The samples were

returned to the lab where they were dried in an oven for 24 h at 60°C and then weighed to determine

the dry weight biomass (g/m3

). Also, surface water samples were collected during each set to

determine total suspended sediments, an estimate of turbidity. Water samples were later filtered in

the lab through a pre-weighed, microfiber filter (1.2 μm), dried in an oven for 24 h at 60°C, and

weighed to determine the suspended sediment load (g/500 ml). Both the macrozooplankton biomass

and suspended sediment (turbidity) estimates were used in the canonical correlation analyses (see

below).

At GI 94, a total of 11 sampling trips were taken, and samples were collected twice monthly during

new and full moons for three consecutive nights from April-August 1996 (the peak recruitment

period for most reef associated species in the northern GOM). Sampling at GC 18 and GI 94,

therefore, overlapped monthly from April-June 1996. In May, additional sampling trips were

scheduled to coincide with the first and last quarter moon phases, but the full moon trip was

cancelled due to adverse weather conditions. At ST 54 sampling also occurred twice monthly from

April-September 1997 (eight trips total), during new and full moon periods. Sampling effort was

modified at GI 94 and ST 54 to obtain one (rather than two) replicate subsurface and surface

collection per gear, and one off-platform light-trap collection per set, with still three sets taken per

night.

Samples were collected twice monthly (new and full moon phases) over two-night periods at the

Belle Pass jetties from April-September 1997 (11 trips total) simultaneously with the sampling of

ST 54. For sampling purposes, the sides of the two, north-south oriented channel jetties were labeled

as East Exterior (EE), East Interior (EI), West Interior (WI), and West Exterior (WE). A total of four

sampling stations, one on each side of each jetty, were located approximately at jetty mid-points and

were identified during sampling by distinct rock outcroppings that were sprayed with fluorescent

paint. Two sets of samples were taken each night. A set included a light-trap and a bow-mounted,

pushnet sample at each of the four stations. The order of stations sampled within each set was

chosen using a random number table. Light-traps were equipped with a submersible battery that was
196

secured to the top of the light-trap with bungee cords. At each station, a buoyed mooring was used

to suspend the light-trap approximately 1 m below the surface as close to the jetty as possible, which

was usually within 2 m of the surface-exposed rocks. Light-traps were allowed to fish for 10

minutes. A bow-mounted pushnet (1 m x 1 m, 1,000 :m mesh net dyed green) was pushed at

approximately 1 m/sec just below the surface along the edge of the jetty for 3-5 minutes, depending

upon the density of plankton. A General Oceanics flowmeter (large rotor) was used to determine the

volume of water filtered. Subsurface salinity (ppt), temperature (°C), dissolved oxygen (% saturation

and mg/l), and turbidity (NTU) were measured at each station during each set using a DataSonde

3 Hydrolab and Multiprobe Logger.

All samples collected at WC 352 and WC 71D were preserved in 5% formalin and later changed

over to ethanol. Samples collected at GC 18 and GI 94 were preserved in ethanol and had the ethanol

changed over again within 12-18 hours. Samples collected at ST 54 and Belle Pass were fixed in 4%

buffered formaldehyde and changed over to ethanol within 8-12 hours. Fish were removed from all

samples, enumerated, measured under a dissecting microscope with the aid of an ocular micrometer,

and identified to the lowest taxonomic level possible using primarily the taxonomic classification

of Robins et al. (1991). Large samples were split using a Folsom plankton splitter (Van Guelpen et

al. 1982). In the event that the number of fish in a sample or a split was greater than 50 for any

single species, the largest, smallest and a random subsample of 50 individuals were measured.

Preflexion larvae were measured to the end of the notochord (NL) and all postflexion larvae,

juveniles, and adults were measured to the posterior end of the vertebral column (SL). Light-trap

samples were standardized to catch-per-unit-effort (CPUE) of fish per 10 min. Plankton net and

pushnet samples were standardized to the number of fish per 100 m3

 (density). This core sampling

schedule formed the basis of our sampling protocols at all other platforms. Sea states, adverse

weather, transportation delays and platform safety concerns often forced us to suspend some sample

collections. Only 7 subsurface plankton net collections were taken at ST 54 (April 7-8) because of

problems with the monorail rigging. Similar gear problems reduced the number of subsurface net

samples collected at GC 18. Table 5.5 summarizes the number of samples collected by trip, gear

type, and depth/location for the WC 352 and WC 71D pilot studies and for GC 18, GI 94, ST 54,

and Belle Pass.

Analyses of Data

Data collected at GC 18, GI 94, ST 54, and Belle Pass were used in all analyses where possible. Data

collected in the pilot studies (WC 352 and WC 71D) are included here only in community structure

analyses. Also, due to the very large numbers of clupeiform (Clupeidae and Engraulidae) fishes

collected, particularly in light-trap samples, some analyses were run with and without these taxa,

since these fish are seldom the taxa of interest in studies of hard-substrate habitats and their

abundances tend to overwhelm the trends of other taxa (Choat et al. 1993). All ANOVA, Tukey’s

Studentized Range Tests, and canonical correlations were run with SAS version 6.12 (SAS 1989).

Schoener’s Index of Niche Overlap (Schoener 1970) was calculated for all sites by combining fish

collected by all gears within each site as an indication of the community similarity between sites.

Only fish identified to at least the genus level were used in the similarity analyses. Since this type

of analysis can be heavily influenced by large abundances of a single species, it was done both with
197

Table 5.5. Number of samples collected at each site by date, gear type, and depth/location. No lunar

phase information was recorded for West Cameron 352. (Lunar phases: N, new moon;

F, full moon; 1, first quarter; 3, last quarter)

Vertical

Net

Subsurface

Net

Surface

Net

Subsurface

Light-trap

Surface

Light-trap

Off-platform

Light-trap

Pushnet

West Cameron 352

 Nov 21-22 23

 Dec 16 1 5

 Feb 7-9 8 12

 Mar 24-25 4 12

 Apr 9-10 7 13

 May 26-27 9 13

 August 4-6 15

 Totals 29 93

West Cameron 71D

 Jul 21-23 (F) 6 12 48

 Totals 6 12 48

Green Canyon 18

 Jul 26-29 (N) 0 9 18 18 5

 Aug 25-28 (N) 0 12 18 18 9

 Sep 24-25 (N) 0 12 12 12 6

 Oct 23-25 (N) 9 9 18 18 9

 Nov 21-23 (N) 9 9 18 17 9

 Jan 19 (N) 3 3 6 6 3

 Feb 17-18 (N) 5 5 10 6 4

 Apr 15-18 (N) 0 0 0 0 15

 May 17-20 (N) 2 9 5 5 18

 Jun 18-21 (N) 13 16 14 13 9

 Totals 41 84 119 113 87

Grand Isle 94

 Apr 16-18 (N) 6 6 4 8 8

 Apr 26-29 (1) 18 18 18 18 18

 May 10-12 (3) 10 12 12 12 12

 May 17-20 (N) 18 18 18 18 18
Table 5.5. (continued)

198

Vertical

Net

Subsurface

Net

Surface

Net

Subsurface

Light-trap

Surface

Light-trap

Off-platform

Light-trap

Pushnet

 May 24-26 (1) 12 13 12 13 11

 Jun 14-17 (N) 18 18 18 18 18

 Jun 28-Jul 1 (F) 17 17 13 12 13

 Jul 12-15 (N) 17 17 15 13 16

 Jul 29-Aug 1 (F) 11 13 11 12 12

 Aug 12-15 (N) 16 17 15 17 17

 Aug 26-29 (F) 18 19 18 18 18

 Totals 161 168 154 159 161

South Timbalier 54

 Apr 7-8 (N) 7 7 5 6 8

 May 5-8 (N) 0 15 0 16 12

 May 20-23 (F) 0 18 12 18 10

 Jun 4-5 (N) 0 6 6 6 5

 Jun 20-21 (F) 0 8 6 9 9

 Jul 3-5 (N) 0 5 7 7 3

 Aug 17-20 (F) 0 13 4 12 14

 Sep 3-5 (N) 0 10 9 10 0

 Totals 7 82 49 84 61

Bell Pass

 Apr 4-7 (N) 9 9

 Apr 21-23 (F) 8 8

 May 5-7 (N) 16 16

 May 20-22 (F) 16 16

 Jun 3-5 (N) 16 16

 Jun 20-21 (F) 8 8

 Jul 3-5 (N) 16 15

 Jul 19-21 (F) 12 15

 Aug 1-3 (N) 15 14

 Aug 18-20 (F) 16 16

 Aug 31-Sep 2 (N) 16 16

 Totals 148 149
199

and without the most dominant taxa at each site included. At times, the sampling efforts differed

temporally between sites (Table 5.5), so the samples used for comparisons were limited to only those

months where samples were collected for both sites in a pairing. For example, all comparisons with WC

71D were done using only July samples from the other sites. Comparisons between the WC 352 and three

across-shelf sites (GI 94, ST 54, and Belle Pass) were done using only April and May samples. Comparisons with WC 352 and GC 18 were done using samples from November, December, April, and May.

Only April-August samples were used to compare GC 18 to GI 94, ST 54, and Belle Pass. Full data sets

were used in comparisons between GI 94, ST 54, and Belle Pass. Shannon-Weiner diversity indices

(Magurran 1988) were calculated for each sample collected at GC 18, GI 94, ST 54, and Belle Pass.

Differences in mean diversity between sites were analyzed with ANOVA models using gear as a main

effect. Post-ANOVA tests (Tukey’s Studentized Range, (=0.05) were used to determine which sites were

significantly different. Only fish identified at least to genus level were included in the diversity analyses.

Canonical correlations were used to determine relationships at each site between plankton net or pushnet

densities or light-trap CPUEs for dominant taxa and environmental variables. For GC 18 and GI 94, logtransformed densities of the top 15 taxa (excluding clupeiforms) collected in subsurface and surface

plankton nets combined were analyzed along with temperature, salinity, macrozooplankton biomass, and

total suspended sediments (turbidity). The same analyses were performed for log-transformed CPUEs of

the top 15 taxa collected in subsurface and surface light-traps. Occasionally more than 15 taxa were

analyzed for light-trap data due to ties in the ranking of CPUEs. For ST54, the same analyses were

performed, but only surface plankton net data were used because very few subsurface plankton net

samples were collected at this site (Table 5.4). For Belle Pass, the same analyses were performed, but

included Hydrolab measurements of turbidity and dissolved oxygen, and did not include total suspended

sediments or macrozooplankton biomass estimates. The importance of an environmental variable was

based on the magnitude of its correlation with the environmental variate, with the sign of the correlation

indicating if the variable was directly (positively) or inversely (negative) related to the variate. A species

was considered to be related to the variate if the absolute value of the interset correlation was greater than

0.387 (i.e., the variate predicted 15% or more of the species variation within the model).

RESULTS

A total of 67 families were represented in our plankton net and light-trap collections from the three

platform sites (Tables 5.6–5.9). The number of families represented in passive plankton net collections

decreased from 45 at GC 18 (shelf slope) to 40 at GI 94 (mid-shelf) and 34 at ST 54 (inner shelf). In

contrast, the number of families represented in light-trap collections was fairly consistent, from 37 at GC

18 and GI 94 to 34 at ST 54. 

Overall Abundances and Seasonality

A total of 5,057 fish were collected at GC 18 over the course of the year. Light-traps and plankton nets

collected 1,114 and 3,943 fish, respectively, with a total mean plankton net density of 74.6 fish/100 m3 and

a total mean light-trap CPUE of 2.06 fish/10 min. Plankton nets collected fish from 45 different families,

15 of which were not collected with light-traps (Table 5.6). Light-traps collected fish from 37 different

families, seven of which were only collected with (i.e., unique to) light-traps. Plankton nets collected fish

from 64 taxa (identified at least to genus level), 25 of which were not collected with light-traps, while

light-traps collected fish from 59 taxa with 18 being unique to light-trap collections. Clupeiform fishes,

primarily unidentified engraulids, Opisthonema oglinum, Anchoa nasuta/hepsetus, and Engraulis eurystole
200

Table 5.6. Total plankton net density (fish/100 m3) and light-trap CPUE (fish/10 min) for fish

collected at Green Canyon 19 with standard error (SE), rank, percent of total catch (%),

and months collected for each taxa. (N) indicates taxa collected only with plankton nets.

(L) indicates taxa collected only with light-traps. For ranks, tied values received the

mean of the corresponding ranks. ‡ indicates a value <1.00%.

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

Osteichthyes 

 Unidentified Feb, Apr, Jun, Jul,

Aug, Sep, Oct, Nov

0.85 (0.39)

23 ‡

4.93 (2.73)

6 (1.54)

0.08 (0.04)

7 (3.27)

0.02 (0.01)

41.5 ‡

0.26 (0.16)

4 (8.36)

Elopiformes 

 Elopidae 

 Elops saurus (N)

 (ladyfish)

Oct 0 (0) 0.35 (0.35)

35 ‡

0 (0) 0 (0) 0 (0)

Anguilliformes

 Unidentified

 (eel)

Jul, Oct, Nov 1.57 (0.72)

13 ‡

4.32 (2.46)

9 ‡

<0.01 (0.01)

28.5 ‡

0.02 (0.01)

41.5 ‡

0.01 (0.01)

40.5 ‡

 Moringuidae

 Neoconger mucronatus

 (ridged eel)

Oct 0.21 (0.21)

52 ‡

0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Muraenidae

 Unidentified

 (moray eel)

Jun, Jul, Aug,

Sep, Oct

0.02 (0.02)

85 ‡

0 (0) <0.01 (0.01)

28.5 ‡

0.03 (0.02)

33 ‡

0.02 (0.02)

25 ‡

 Ophichthidae

 Unidentified

 (snake eel)

Jul, Oct, Nov 1.09 (0.71)

19 ‡

2.87 (1.27)

11 ‡

0 (0) 0.05 (0.02)

22 (1.06)

0 (0)

 Myrophis punctatus (L)

 (speckled worm eel)

Feb 0 (0) 0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Ophichthus gomesi (L)

 (shrimp eel)

Jul 0 (0) 0 (0) <0.01 (0.01)

28.5 ‡

0.03 (0.03)

33 ‡

0 (0)

 Congridae

 Unidentified (L)

 (conger eel)

Jul 0 (0) 0 (0) 0 (0) 0.03 (0.02)

33 ‡

0 (0)

Clupeiformes

 Unidentified

 (herring/anchovy)

Jul, Sep 1.08 (0.92)

20 (1.08)

0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Clupeidae 

 Brevoortia patronus

 (gulf menhaden)

 Jan, Feb, Nov 1.12 (0.55)

18 ‡

2.44 (1.21)

12 ‡

0 (0) 0.03 (0.02)

33 ‡

0.02 (0.02)

25 ‡
Table 5.6. (continued)

201

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Etrumeus teres (N)

 (round herring)

Jan, Feb 1.16 (1.05)

16 ‡

0.19 (0.19)

42.5 ‡

0 (0) 0 (0) 0 (0)

 Harengula jaguana

 (scaled sardine)

Jul, Aug 0.06 (0.04)

71 ‡

0 (0) <0.01 (0.01)

28.5 ‡

0.15 (0.06)

11.5 (3.01)

0 (0)

 Opisthonema oglinum

 (Atlantic thread herring)

Jul, Aug, Sep 39.41

(16.26)

1 (38.40)

0 (0) 0.11 (0.06)

4 (4.73)

0.42 (0.11)

3 (8.51)

0.28 (0.11)

2.5 (8.73)

 Engraulidae

 Unidentified

 (anchovy)

Feb, Jun, Jul, Aug,

Sep Oct, Nov

39.21

(12.21)

2 (24.32)

57.18

(26.10)

1 (53.90)

0.46 (0.11)

2 (20.00)

0.51 (0.15)

1 (10.28)

0.28 (0.13)

2.5 (8.73)

 Anchoa spp. (L)

 (anchovy spp.)

Jul 0 (0) 0 (0) 0.07 (0.07)

8 (2.91)

0 (0) 0 (0)

 Anchoa mitchilli

 (bay anchovy)

Jul 0.03 (0.03)

79 ‡

0 (0) 0 (0) 0.15 (0.12)

11.5 (3.01)

0 (0)

 Anchoa nasuta/hepsetus (L)

 (longnose/striped anchovy)

Jul, Aug, Sep, Nov 0 (0) 0 (0) 0.80 (0.31)

1 (34.91)

0.22 (0.12)

8 (4.43)

0.16 (0.10)

8 (5.09)

 Engraulis eurystole

 (silver anchovy)

Jun, Jul, Aug,

Sep, Oct

0.34 (0.30)

42 ‡

8.63 (8.63)

5 (9.45)

0.15 (0.04)

3 (6.55)

0.25 (0.11)

5 (5.14)

0.02 (0.02)

25 ‡

Stomiiformes

 Gonostomatidae

 Cyclothone braueri Jan, May, Jun,

Jul, Oct, Nov

1.01 (0.65)

21 ‡

3.05 (1.55)

10 ‡

0 (0) 0.23 (0.21)

7 (4.61)

0 (0)

 Diplophos taenia (N) Nov 0.29 (0.29)

44.5 ‡

0.41 (0.41)

31 ‡

0 (0) 0 (0) 0 (0)

Aulopiformes

 Chlorophthalmidae

 Chlorophthalmus agassizi (N)

 (shortnose greeneye)

Jun, Nov 0 (0) 0.70 (0.61)

24 ‡

0 (0) 0 (0) 0 (0)

 Scopelarchidae

 Scopelarchoides spp. (N)

 (pearleye spp.)

Jan 0.03 (0.03)

80 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Synodontidae

 Unidentified

 (lizardfish)

Jan, May, Jul, Oct 0.27 (0.16)

46 ‡

0.61 (0.61)

26 ‡

<0.01 (0.01)

28.5 ‡

<0.01 (0.01)

55 ‡

0 (0)

 Saurida brasiliensis

 (largescale lizardfish)

<0.01

(<0.01)

92 ‡

0 (0) 0.03 (0.02)

12.5 (1.09)

0.20 (0.14)

9 (4.08)

0 (0)
Table 5.6. (continued)

202

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Synodus synodus

 (red lizardfish)

Jun 0.29 (0.29)

44.5 ‡

0 (0) 0 (0) 0.03 (0.02)

33 ‡

0 (0)

 Trachinocephalus myops

 (snakefish)

Sep, Oct 0.10 (0.10)

63 ‡

0 (0) 0 (0) 0.04 (0.02)

25 ‡

0.03 (0.02)

19 (1.09)

 Paralepidae

 Unidentified (N)

 (barracudina)

Nov 0.26 (0.26)

47 ‡

0.41 (0.41)

31 ‡

0 (0) 0 (0) 0 (0)

 Paralepis atlantica (L)

 (duckbill barracudina)

Jul 0 (0) 0 (0) 0.02 (0.01)

18 ‡

0 (0) 0 (0)

 Lestrolepis intermedia (L) Jul 0 (0) 0 (0) 0.02 (0.02)

18 ‡

0 (0) 0 (0)

Myctophiformes

 Myctophidae

 Unidentified

 (lanternfish)

Jan, Feb, Apr, May,

Jun, Jul, Sep, Nov

0.83 (0.45)

24 ‡

0.31 (0.22)

36 ‡

0.03 (0.02)

12.5 (1.09)

0.04 (0.02)

27.5 ‡

0.17 (0.06)

7 (5.45)

Gadiformes

 Unidentified (N) Sep, Oct 0.19 (0.15)

55 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Bregmacerotidae

 Bregmaceros cantori

 (codlet)

Jan, May, Aug,

Sep, Oct

1.80 (0.88)

11 (1.08)

2.42 (1.21)

13 ‡

0.03 (0.02)

11 (1.45)

<0.01 (0.01)

55 ‡

0.05 (0.02)

15.5 (1.45)

 Merluccidae

 Unidentified (L)

 (whiting)

Nov 0 (0) 0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Ophidiidae

 Unidentified (N)

 (cuskeel)

May <0.01

(<0.01)

89.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Lepophidium spp.

 (cusk-eel spp.)

Aug, Sep, Oct 0.43 (0.27)

37 ‡

1.30 (0.94)

17 ‡

0.02 (0.01)

18 ‡

0 (0) 0.01 (0.01)

40.5 ‡

 Bythitidae

 Unidentified

 (brotula)

Oct, Nov 0.33 (0.23)

43 ‡

0.41 (0.41)

31 ‡

<0.01 (0.01)

28.5 ‡

<0.01 (0.01)

55 ‡

0.01 (0.01)

40.5 ‡

Lophiiformes 

 Unidentified May, Aug <0.01

(<0.01)

92 ‡

0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)
Table 5.6. (continued)

203

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

Gobiesociformes

 Gobiesocidae

 Gobiesox strumosus (L)

 (skilletfish)

Jul 0 (0) 0 (0) 0 (0) 0.08 (0.08)

16 (1.60)

0 (0)

Atheriniformes

 Exocoetidae

 Unidentified

 (flyingfish)

Jun, Aug, Sep 0.63 (0.40)

31 ‡

0.27 (0.20)

38 ‡

0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Cypselurus cyanopterus (L)

 (margined flyingfish)

Jul 0 (0) 0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Cypselurus furcatus/heterurus (L)

 (spotfin/Atlantic flyingfish)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Parexocoetus brachypterus (L)

 (sailfin flyingfish)

Jul 0 (0) 0 (0) 0 (0) 0.04 (0.02)

27.5 ‡

0 (0)

Beryciformes

 Holocentridae

 Holocentrus spp.

 (squirrelfish)

Jun 0.18 (0.10)

56 ‡

0 (0) 0 (0) 0.07 (0.04)

18 (1.42)

0.11 (0.05)

11 (3.64)

 Melamphaidae

 Melamphaes spp. (N) Jan, Jun 0.05 (0.04)

73 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Scorpaeniformes

 Unidentified (N) Oct 0.24 (0.17)

48 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Scorpaenidae

 Unidentified (N)

 (scorpionfish)

Oct 0.08 (0.08)

68 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Scorpaena spp. (N)

 (scorpionfish spp.)

Jun, Aug 0.09 (0.07)

67 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Triglidae

 Prionotus spp. (N)

 (searobin)

May 0.01 (0.01)

87.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Perciformes 

 Unidentified Jan, May, Jun, Jul,

Aug, Sep, Oct

2.60 (1.27)

9 (1.11)

1.48 (0.64)

16 (1.23)

0.09 (0.05)

5.5 (4.00)

0.03 (0.02)

33 ‡

0.02 (0.02)

25 ‡
Table 5.6. (continued)

204

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Serranidae

 Unidentified

 (sea bass/grouper)

Jan, Jun, Oct, Nov 0.22 (0.14)

50 ‡

1.86 (1.28)

15 ‡

0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Anthinae

 (sea perch)

Apr, May, Jun, Nov 0.46 (0.19)

34 ‡

0.38 (0.23)

33 ‡

0 (0) <0.01 (0.01)

55 ‡

0.02 (0.02)

25 ‡

 Epinephelinae (N)

 (grouper)

May, Jun 0.41 (0.23)

38 ‡

0.23 (0.13)

39 ‡

0 (0) 0 (0) 0 (0)

 Grammistinae (N) Jun 0 (0) 0.14 (0.10)

48 ‡

0 (0) 0 (0) 0 (0)

 Priacanthidae

 Unidentified (N)

 (bigeye)

May, Jun 0.10 (0.07)

64 ‡

0.08 (0.08)

53 ‡

0 (0) 0 (0) 0 (0)

 Priacanthus spp. (L)

 (bigeye/glasseye spp.)

Jun 0 (0) 0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)

Apogonidae

 Unidentified (N)

 (cardinalfish)

May <0.01

(<0.01)

89.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Apogon spp. (N)

 (cardinalfish spp.)

May <0.01

(<0.01)

92 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Pomatomidae

 Pomatomus saltatrix (L)

 (bluefish)

Sep, Oct 0 (0) 0 (0) 0 (0) 0 (0) 0.05 (0.03)

15.5 (1.45)

 Echeneidae

 Unidentified (N)

 (remora)

Jun 0.14 (0.10)

59.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Carangidae

 Unidentified (N)

 (jack)

May, Jun, Jul 0.41 (0.28)

39 ‡

0.23 (0.16)

40 ‡

0 (0) 0 (0) 0 (0)

 Caranx spp.

 (jack spp.)

May, Jun 0 (0) 0.07 (0.07)

56 ‡

0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Caranx crysos

 (blue runner)

Jun, Jul, Aug, Sep 2 75 (1.30)

8 ‡

0.56 (0.49)

27 ‡

<0.01 (0.01)

28.5 ‡

0.24 (0.08)

6 (4.79)

0.30 (0.10)

1 (9.45)

 Caranx hippos/latus

 (crevalle/horse-eye jack)

May, Jun, Jul,

Aug, Oct

1.89 (0.65)

10 (1.85)

4.45 (1.62)

8 (4.31)

<0.01 (0.01)

28.5 ‡

0.08 (0.03)

16 (1.60)

0.22 (0.06)

5 (6.91)

 Chloroscombrus chrysurus

 (Atlantic bumper)

Jun, Jul, Aug, Sep 0.57 (0.24)

33 ‡

0 (0) 0 (0) 0.03 (0.02)

33 ‡

0 (0)
Table 5.6. (continued)

205

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Decapterus punctatus

 (round scad)

Jun, Jul 0.03 (0.03)

77.5 ‡

0 (0) <0.01 (0.01)

28.5 ‡

<0.01 (0.01)

55 ‡

0 (0)

 Elagatis bipinnulata

 (rainbow runner)

May 0.19 (0.12)

54 ‡

0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Selar crumenopthalmus (N)

 (bigeye scad) 

May, Jun 0.02 (0.02)

86 ‡

0.19 (0.19)

42.5 ‡

0 (0) 0 (0) 0 (0)

 Selene vomer (N)

 (lookdown)

Sep 0.24 (0.24)

49 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Seriola spp.

 (jack spp.)

May, Jun, Aug, Oct 0.11 (0.06)

62 ‡

0.44 (0.36)

28 ‡

0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Trachurus lathami

 (rough scad)

Jan, Feb, Apr, May 0.12 (0.07)

61 ‡

0.19 (0.19)

42.5 ‡

0 (0) <0.01 (0.01)

55 ‡

0.02 (0.02)

25 ‡

 Coryphaenidae

 Coryphaena equiselis (N)

 (pompano dolphin)

May 0.01 (0.01)

87.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Coryphaena hippurus (N)

 (dolphin)

Jun, Sep 0.09 (0.07)

65 ‡

0.09 (0.09)

51 ‡

0 (0) 0 (0) 0 (0)

 Lutjanidae

 Unidentified

 (snapper)

Feb, May 0.04 (0.04)

76 ‡

0.03 (0.03)

58 ‡

0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Lutjanus spp.

 (snapper spp.)

Jun 0.14 (0.10)

59.5 ‡

0.19 (0.19)

42.5 ‡

0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Lutjanus apodus/vivanus (L)

 (schoolmaster/silk snapper)

Jul 0 (0) 0 (0) 0 (0) 0.02 (0.01)

41.5 ‡

0 (0)

 Lutjanus campechanus (L)

 (red snapper)

Sep 0 (0) 0 (0) 0 (0) 0.02 (0.02)

41.5 ‡

0 (0)

 Pristipomoides aquilonaris (N)

 (wenchman)

Jun, Oct 0.91 (0.71)

22 ‡

1.95 (0.88)

14 (2.16)

0 (0) 0 (0) 0 (0)

 Rhomboplites aurorubens (N)

 (vermillion snapper)

Jul 0.05 (0.05)

72 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Gerreidae

 Eucinostomus spp. (L)

 (jenny/mojarra spp.)

Jun, Jul, Sep 0 (0) 0 (0) 0 (0) 0.05 (0.02)

22 (1.06)

0.10 (0.07)

12 (3.27)

 Sparidae

 Unidentified (N)

 (porgy)

May 0 (0) 0.07 (0.07)

56 ‡

0 (0) 0 (0) 0 (0)

 Lagodon rhomboides (N)

 (pinfish)

Jan 0.17 (0.14)

57 ‡

0.38 (0.38)

34 ‡

0 (0) 0 (0) 0 (0)
Table 5.6. (continued)

206

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Sciaenidae

 Cynoscion arenarius

 (sand seatrout)

Jul, Aug 1.51 (0.66)

14 (2.09)

0 (0) 0 (0) 0.04 (0.02)

25 ‡

0 (0)

 Leiostomus xanthurus

 (spot)

Jan 0 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Micropogonias undulatus

 (Atlantic croaker)

Oct 0.45 (0.23)

35 ‡

0.30 (0.30)

37 ‡

0.02 (0.01)

18 ‡

<0.01 (0.01)

55 ‡

0.02 (0.02)

25 ‡

 Sciaenops ocellatus

 (red drum)

Sep 4.11 (1.92)

5 (3.70)

0 (0) 0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Mullidae

 Unidentified (L)

 (goatfish)

Jun 0 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Upeneus parvus (L)

 (dwarf goatfish)

Apr 0 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Ephippidae

 Chaetodipterus faber (N)

 (Atlantic spadefish)

May, Jul 0.05 (0.04)

74 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Chaetodontidae

 Unidentified (N)

 (butterfly fish)

Jun 0.03 (0.03)

77.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Pomacentridae

 Pomacentrus spp. (L)

 (damselfish spp.)

Jun, Jul 0 (0) 0 (0) 0.02 (0.01)

18 ‡

0.14 (0.08)

13 (2.84)

0.03 (0.03)

19 (1.09)

 Mugilidae

 Mugil cephalus

 (striped mullet)

Jan, Feb, Oct, Nov 8.27 (4.58)

3 ‡

32.05

(15.62)

2 (5.54)

0 (0) 0.04 (0.02)

25 ‡

0.14 (0.06)

9.5 (4.36)

 Sphyraenidae

 Sphyraena guachancho

 (guaguanche)

Jun, Jul 0.44 (0.39)

36 ‡

0.08 (0.08)

53 ‡

0 (0) 0.03 (0.03)

33 ‡

0.01 (0.01)

40.5 ‡

 Scaridae

 Unidentified

 (parrotfish)

Aug, Oct, Nov 3.01 (1.35)

7 ‡

16.31 (5.64)

3 (3.08)

<0.01 (0.01)

28.5 ‡

0.06 (0.03)

19.5 (1.24)

0 (0)

 Blenniidae

 Unidentified

 (blenny)

May, Jun, Jul,

Sep, Oct

0.34 (0.19)

41 ‡

0.98 (0.98)

19 ‡

0.06 (0.06)

9.5 (2.55)

0.17 (0.15)

10 (3.37)

0.01 (0.01)

40.5 ‡
Table 5.6. (continued)

207

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Hypsoblennius invemar

 (tessellated blenny)

Jun, Oct 0 (0) 0.08 (0.08)

53 ‡

0 (0) 0 (0) (0.01)

40.5 ‡

 Ophioblennius atlanticus

 (redlip blenny)

Jun, Oct 0.65 (0.47)

29 ‡

0 (0) 0 (0) <0.01 (0.01)

55 ‡

0.01 (0.01)

40.5 ‡

 Callionymidae

 Foetorepus agassizi (N)

 (spotfin dragonet)

Aug 0.05 (0.03)

75 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Paradiplogramus bairdi (N)

 (lancer dragonet)

Aug (0.02)

84 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Gobiidae

 Unidentified

 (goby)

Jan, Feb, Apr, Jun,

Jul, Aug, Oct Nov

4.63 (1.78)

4 (2.02)

11.08 (3.87)

4 (4.41)

0.09 (0.04)

5.5 (4.00)

0.44 (0.40)

2 (8.87)

0.05 (0.02)

15.5 (1.45)

 Microdesmidae

 Microdesmus spp. (N)

 (wormfish spp.)

Jun, Aug 0.03 (0.03)

83 ‡

0.75 (0.52)

23 ‡

0 (0) 0 (0) 0 (0)

 Microdesmus lanceolatus (N)

 (lancetail wormfish)

Jun, Jul, Aug 0.65 (0.41)

28 ‡

0.15 (0.11)

47 ‡

0 (0) 0 (0) 0 (0)

 Microdesmus longipinnis

 (pink wormfish)

Jul (0.06)

70 ‡

0 (0) 0 (0) (0.03)

22 (1.06)

0.02 (0.02)

25 ‡

 Scombridae

 Unidentified

 (mackerel)

May, Jun, Jul,

Aug, Sep

1.75 (1.01)

12 (2.73)

0.75 (0.75)

22 ‡

0 (0) (0.01)

41.5 ‡

(0.01)

40.5 ‡

 Acanthocybium solandri

 (wahoo)

Jun 0 (0) 0.09 (0.09)

49.5 ‡

0 (0) 0 (0) 0 (0)

 Auxis spp.

 (mackerel spp.)

May, Jun, Aug,

Sep, Oct

1.41 (0.42)

15 (1.99)

0.94 (0.50)

20 ‡

0.02 (0.01)

18 ‡

0.40 (0.13)

4 (8.16)

0.14 (0.04)

9.5 (4.36)

 Euthynnus alletteratus

 (little tunny)

May, Jun, Jul,

Aug, Sep, Oct

0.65 (0.25)

30 ‡

0.09 (0.09)

49.5 ‡

0 (0) 0.06 (0.02)

19.5 (1.24)

0.18 (0.08)

6 (5.82)

 Scomberomorus cavalla

 (king mackerel)

Aug 0.09 (0.07)

66 ‡

0 (0) (<0.01)

(0.01)

28.5 ‡

0.02 (0.02)

41.5 ‡

(0.03)

19 (1.09)

 Scomberomorus maculatus

 (Spanish mackerel)

Jul, Aug 0.75 (0.42)

26 ‡

0 (0) 0 (0) 0.02 (0.01)

41.5 ‡

0 (0)

 Thunnus spp.

 (tuna spp.)

May, Jun (0.02)

82 ‡

0.17 (0.12)

46 ‡

0 (0) (0.01)

41.5 ‡

(0.01) 40.5 ‡

 Thunnus thynnus (N)

 (bluefin tuna)

Jun (0.07)

69 ‡

0.18 (0.18)

45 ‡

0 (0) 0 (0) 0 (0)

 Stromateidae
Table 5.6. (continued)

208

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Ariomma spp.

 (driftfish spp.)

Apr, May 0.77 (0.52)

25 (2.16)

0.44 (0.36)

29 ‡

0 (0) 0 (0) 0.02 (0.02)

25 ‡

 Nomeidae

 Cubiceps pauciradiatus (N)

 (bigeye cigarfish)

May 0.03 (0.03)

81 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Peprilus burti

 (gulf butterfish)

Jan, Jun, Aug,

Oct, Nov

0.72 (0.34)

27 ‡

1.05 (0.64)

18 ‡

0.02 (0.01)

18 ‡

0.03 (0.02)

33 ‡

0.05 (0.03)

15.5 (1.45)

 Tetragonuridae

 Tetragonurus atlanticus (N)

 (bigeye squaretail)

Nov 0.20 (0.20)

53 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Pleuronectiformes

 Bothidae

 Unidentified

 (lefteye flounder)

Jul, Oct, Nov 0.59 (0.59)

32 ‡

0.81 (0.81)

21 ‡

<0.01 (0.01)

28.5 ‡

0 (0) 0 (0)

 Bothus spp.

 (flounder spp.)

May, Sep, Oct, Nov 0.17 (0.17)

58 ‡

0 (0) 0.02 (0.01)

18 ‡

0 (0) 0.01 (0.01)

40.5 ‡

 Citharichthys spilopterus

 (baywhiff)

Feb, Oct, Nov 1.14 (0.92)

17 ‡

4.85 (1.98)

7 (1.44)

0 (0) <0.01 (0.01)

55 ‡

0 (0)

 Etropus crossotus

 (fringed flounder)

Aug, Nov 0.39 (0.39)

40 ‡

0 (0) 0 (0) 0 (0) 0.01 (0.01)

40.5 ‡

 Monolene sessilicauda (L)

 (deepwater flounder)

Feb 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.01)

40.5 ‡

 Syacium spp.

 (flounder spp.)

Jul, Aug, Sep 0.22 (0.12)

51 ‡

0 (0) 0.02 (0.01)

18 ‡

0.08 (0.05)

16 (1.60)

0.02 (0.01)

40.5 ‡

 Soleidae

 Symphurus spp.

 (tonguefish spp.)

Feb, Jul, Aug,

Sep, Oct

3.03 (1.16)

6 (2.02)

0.70 (0.70)

25 ‡

(0.05)

9.5 (2.55)

0.10 (0.04)

14 (1.95)

0.07 (0.03)

13 (2.18)

Tetraodontiformes

 Tetraodontidae

 Sphoeroides spp. (N)

 (puffer spp.)

May 0 (0) (0.07)

56 ‡

(0) 0 (0) 0 (0)
209

Table 5.7. Total plankton net density (fish/100 m3) and light-trap CPUE (fish/10 min) for fish

collected at Grand Isle 94 with standard error (SE), rank, percent of total catch (%), and

months collected for each taxa. (N) indicates taxa collected only with plankton nets. (L)

indicates taxa collected only with light-traps. For ranks, tied values received the mean

of the corresponding ranks. ‡ indicates a value <1.00%.

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

Osteichthyes

 Unidentified Apr, May, Jun, July,

Aug

0.92 (0.60)

19 ‡

0.78 (0.41)

23 (1.31)

0.28 (0.26)

10 (1.13)

0.13 (0.10)

22 ‡

1.12 (0.94)

9 (4.55)

Anguilliformes

 Unidentified (N)

 (eel)

Jun 0.07 (0.07)

69 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Muraenidae

 Unidentified

 (moray eel)

May, Jun, Jul 0.07 (0.05)

71 ‡

0.44 (0.23)

33 ‡

<0.01 (<0.01)

49 ‡

0 (0) 0 (0)

 Ophichthidae

 Unidentified

 (snake eel)

Jun, Jul, Aug 0.10 (0.05)

55 ‡

0.69 (0.35)

26 ‡

0.04 (0.02)

26.5 ‡

0.02 (0.01)

51 ‡

0 (0)

 Ophichthus spp.

 (snake eel)

Aug 0 (0) 0 (0) 0 (0) 0.03 (0.02)

46.5 ‡

0 (0)

 Ophichthus gomesi (N)

 (shrimp eel)

Jun (0.01)

98 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Nettastomatidae

 Hoplunnis macrurus (L)

 (freckled-pike conger)

May 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

0 (0)

Clupeiformes

 Unidentified

 (herring/anchovy)

Apr, May, Jun, Jul,

Aug

2.38 (2.14)

12 ‡

0.05 (0.04)

69 ‡

<0.01 (<0.01)

58 ‡

<0.01 (<0.01)

81.5 ‡

0 (0)

 Clupeidae

 Unidentified

 (herring)

Apr, May, Aug 0 (0) 0.52 (0.37)

30 ‡

0 (0) (<0.01)

61.5 ‡

0 (0)

 Brevoortia patronus (L)

 (gulf menhaden)

Apr 0 (0) 0 (0) <0.01 (<0.01)

49 ‡

0 (0) 0 (0)

 Etrumeus teres

 (round herring)

Apr 0.08 (0.06)

66 ‡

0.23 (0.16)

44 ‡

(0.01)

32 ‡

0.03 (0.02)

46.5 ‡

(<0.01)51.5

‡

 Harengula jaguana

 (scaled sardine)

Apr, Jun, Jul, Aug 0.61 (0.27 )

25 ‡

0.31 (0.31)

38.5 ‡

0.06 (0.02)

21 ‡

0.69 (0.18)

18 ‡

0.68 (0.15)

11 (2.76)

 Opisthonema oglinum

 (Atlantic thread herring)

Apr, Jun, Jul, Aug 70.99 (35.34)

2 (15.81)

4.81 (1.97)

5 (2.20)

1.26 (0.85)

6 (4.99)

6.04 (1.23)

8 (4.07)

4.11 (1.11)

1 (16.66)

 Sardinella aurita

 (Spanish sardine)

Apr, Jul, Aug 0.08 (0.06)

67 ‡

0.16 (0.16)

54 ‡

0 (0) 0.04 (0.02)

41.5 ‡

0 (0)
Table 5.7. (continued)

210

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Engraulidae

 Unidentified

 (anchovy)

Apr, May, Jun, Jul,

Aug

232.66

(44.32)

1 (62.01)

66.92

(17.27)

1 (24.74)

0.41 (0.09)

7 (1.64)

0.55 (0.12)

20 ‡

0.96 (0.17)

10 (3.92)

 Anchoa spp.

 (anchovy spp.)

Apr, May, Jun, Jul,

Aug

14.23 (8.25)

3 (3.55)

1.21 (0.73)

21 ‡

0.18 (0.17)

15 ‡

0.02 (0.01)

51 ‡

<0.01

(<0.01)

64 ‡

 Anchoa hepsetus

 (striped anchovy)

Aug 0 (0) 0 (0) 0.10 (0.08)

16.5 ‡

0.70 (0.49)

16 ‡

0.50 (0.47)

12 (2.04)

 Anchoa mitchilli

 (bay anchovy)

Jun, Jul, Aug 6.24 (2.37)

6 (1.89)

2.70 (1.03)

11 ‡

0.37 (0.18)

8 (1.46)

1.89 (0.83)

10 (1.27)

0.47 (0.23)

14 (1.91)

 Anchoa nasuta

 (longnose anchovy)

Aug 0 (0) 0 (0) 7.80 (6.15)

1 (30.96)

11.10 (5.93)

4 (7.47)

1.31 (0.70)

6 (5.30)

 Anchoa nasuta/hepsetus

 (longnose/striped anchovy)

Apr, May, Jun, Jul,

Aug

5.64 (2.80)

8 (1.87)

4.59 (1.69)

7 (3.14)

2.73 (0.52)

3 (10.88)

30.11 (12.33)

2 (20.27)

1.45 (0.53)

5 (5.86)

 Anchoviella perfasciata

 (flat anchovy)

Aug 0 (0) 0 (0) 0 (0) 0.07 (0.07)

33.5 ‡

0.09 (0.09)

24 ‡

 Engraulis eurystole

 (silver anchovy)

Apr, May, Jun, Jul,

Aug

1.93 (1.90)

13 ‡

2.43 (1.12)

12 (1.15)

5.72 (1.41)

2 (22.79)

38.79 (13.81)

1 (26.12)

1.25 (0.48)

7 (5.08)

Stomiiformes

 Gonostomatidae

 Cyclothone braueri (N) Apr, Jul 0.02 (0.02)

94 ‡

0.11 (0.08)

60 ‡

0 (0) 0 (0) 0 (0)

 Vinciguerria nimbaria (L) Apr 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

Aulopiformes

 Synodontidae

 Unidentified Apr, May, Jun, Jul,

Aug

0.22 (0.08)

40 ‡

2.11 (0.56)

15 (1.05)

0.10 (0.03)

16.5 ‡

0.90 (0.39)

14 ‡

0.12 (0.06)

21 ‡

 Saurida brasiliensis

 (largescale lizardfish)

Apr, May, Jun, Jul,

Aug

0.81 (0.22)

21 ‡

4.77 (1.26)

6 (4.86)

1.97 (0.42)

5 (7.84)

3.35 (0.51)

9 (2.27)

0.50 (0.14)

13 (2.01)

 Saurida normani (L)

 (shortjaw lizardfish)

Apr, May 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

0 (0)

 Saurida normani/brasiliensis (L)

 (shortjaw/largescale lizardfish)

May 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Saurida suspicio (L)

 

May 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Synodus spp.

 (lizardfish spp.)

May, Jun 0 (0) 0.03 (0.03)

72.5 ‡

 <0.01

(<0.01)

49 ‡

 0.06 (0.06)

37.5 ‡

0.04 (0.03)

35.5 ‡
Table 5.7. (continued)

211

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Synodus foetens

 (inshore lizardfish)

Apr, May, Jun, Jul,

Aug

0.64 (0.26)

24 ‡

2.12 (0.77)

14 (1.20)

 0.20 (0.06)

12 ‡

 22.11 (5.24)

3 (14.92)

0.20 (0.05)

19 ‡

 Synodus poeyi

 (offshore lizardfish)

Apr, May, Jun, Jul,

Aug

0.17 (0.13)

47 ‡

1.35 (0.44)

17 ‡

 0.34 (0.09)

9 (1.36)

 9.98 (1.78)

5 (6.74)

0.13 (0.28)

8 (4.57)

 Synodus synodus (L)

 (red lizardfish)

 May 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

0 (0)

 Trachinocephalus myops (L)

 (snakefish)

 Apr, May, Jun, Aug 0 (0) 0 (0) 0 (0) 0.08 (0.03)

30.5 ‡

<0.01

(<0.01)

64 ‡

 Paralepidae

 Unidentified (N)

 (barracudina)

 May 0.03 (0.03)

88 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Lestrolepis intermedia

 

May, Jun, Aug 0 (0) 0.15 (0.11)

56 ‡

 (0.01)

32 ‡

<0.01 (<0.01)

81.5 ‡

0 (0)

 Lestrolepis spp. (L)

 (barracudina spp.)

Aug 0 (0) 0 (0) <0.01 (<0.01)

49 ‡

 0 (0) 0 (0)

Myctophiformes

 Unidentified (N) Jun 0 (0) 0.21 (0.21)

48 ‡

0 (0) 0 (0) 0 (0)

 Myctophidae

 Unidentified

 (lanternfish)

Apr, May, Jun, Jul,

Aug

 0.09 (0.05)

60 ‡

0.75 (0.41)

25 ‡

 0.03 (0.02)

28 ‡

 0.05 (0.02)

40 ‡

0.06 (0.02)

29.5 ‡

 Gadiformes

 Bregmacerotidae

 Bregmaceros cantori Apr, May, Jun, Jul,

Aug

1.59 (0.42)

16 ‡

16.67 (3.00)

3 (15.06)

 2.18 (1.02)

4 (8.68)

 0.06 (0.02)

35.5 ‡

0.03 (0.02)

38.5 ‡

 Ophidiiformes

 Ophidiidae

 Unidentified

 (cusk-eel)

May, Jun, Jul 0.31 (0.13)

35 ‡

0.21 (0.21)

48 ‡

 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Lepophidium spp. (N)

 (cusk-eel spp.)

Jul 0 (0) 0.13 (0.13)

58.5 ‡

 0 (0) 0 (0) 0 (0)

 Lepophidium profundorum (N)

 (fawn cusk-eel)

Jun 0.03 (0.02)

84 ‡

 0.23 (0.21)

45 ‡

 0 (0) 0 (0) 0 (0)

 Lepophidium staurophor (N) May, Jun, Aug 0.09 (0.06)

59 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Ophidiinae Type A (N)

 (cusk-eel spp.)

Jun 0 (0) 0.02 (0.02)

80 ‡

 0 (0 ) 0 (0) 0 (0)

 Ophidion nocomis May, Jun 0 (0) 0.05 (0.05) 0.01 (<0.01) 0 (0) 0 (0)
Table 5.7. (continued)

212

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

68 ‡ 37 ‡

 Ophidion nocomis/selenops

 (cusk-eel spp.)

May 0.09 (0.06)

63 ‡

0.31 (0.23)

38.5 ‡

 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Ophidion selenops (N)

 (mooneye cusk-eel)

May, Jun 0 (0) 0.19 (0.14)

50 ‡

 0 (0) 0 (0) 0 (0)

Lophiiformes

 Caulophrynidae

 Robia legula (N) Jul 0 (0) 0.09 (0.08)

61 ‡

 0 (0) 0 (0) 0 (0)

Atheriniformes

 Exocoetidae

 Unidentified

 (flyingfish)

Jun 0.14 (0.07)

51 ‡

0.07 (0.07)

64.5 ‡

 0 (0) 0 (0) 0 (0)

 Cypselurus spp.

 (flyingfish spp.)

May, Jun 0 (0) 0.07 (0.07)

64.5 ‡

 0 (0) <0.01 (<0.01)

81.5 ‡

<0.01

(<0.01)

64 ‡

 Cypselurus cyanopterus (L)

 (margined flyingfish)

Jul 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Beryciformes

 Holocentridae

 Holocentrus spp.

 (squirrelfish spp.)

May, Jun, Jul 0.18 (0.08)

44 ‡

0 (0) 0.01 (<0.01)

40 ‡

 0 (0) <0.01

(<0.01)

64 ‡

 Scorpaeniformes

 Scorpaenidae

 Unidentified (N)

 (scorpionfish)

May, Jun 0.01 (0.01)

95 ‡

0.16 (0.16)

54 ‡

 0 (0) 0 (0) 0 (0)

 Scorpaena spp.

 (scorpionfish spp.)

May, Jul, Aug 0 (0) 0.45 (0.34)

32 ‡

 0 (0) 0.01 (<0.01)

61.5 ‡

0 (0)

 Triglidae

 Unidentified (N)

 (searobin)

Jul 0.01 (0.01)

99 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Prionotus spp.

 (searobin spp.)

Apr 0.21 (0.11)

42 ‡

0.09 (0.09)

62 ‡

 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Perciformes

 Unidentified Apr, May, Jun, Jul,

Aug 

 1.74 (0.69)

15 ‡

2.22 (0.76)

13 (1.41)

 0.05 (0.02)

24.5 ‡

 0.09 (0.05)

27 ‡

0.04 (0.02)

34 ‡ 

 Serranidae 
Table 5.7. (continued)

213

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Unidentified (N)

 (seabass/grouper)

Apr, May, Jun 0.08 (0.05)

68 ‡

0.16 (0.13)

52 ‡

 0 (0) 0 (0) 0 (0) 

 Anthinae

 (sea perch)

May 0.17 (0.09)

46 ‡

0.35 (0.24)

36 ‡

 0 (0) 0.01 (<0.01)

61.5 ‡

0 (0) 

 Epinephelinae

 (grouper)

May, Jun 0.07 (0.04)

72 ‡

0 (0) 0 (0) 0.03 (0.01)

43 ‡

0 (0) 

 Grammistinae (N) Jun, Jul 0.04 (0.03)

80 ‡

0.01 (0.01)

81 ‡

 0 (0) 0 (0) 0 (0 ) 

 Serraninae

 (sea bass)

Apr, May, Jun, Aug 0.36 (0.14)

31 ‡

0.95 (0.33)

22 ‡

 <0.01

(<0.01)

49 ‡

 0.08 (0.03)

30.5 ‡

0 (0) 

 Priacanthidae 

 Priacanthus spp. (N)

 (bigeye/glasseye spp.)

May 0 (0) 0.03 (0.03)

74.5 ‡

 0 (0) 0 (0) 0 (0) 

 Pomatomidae 

 Pomatomus saltatrix

 (bluefish)

Apr, May 0.08 (0.06)

65 ‡

0 (0) 0 (0) 0.01 (<0.01)

61.5 ‡

0 (0) 

 Rachycentridae 

 Rachycentron canadum (N)

 (cobia)

May, Jun, Jul 0.14 (0.07)

52 ‡

0.02 (0.02)

78 ‡

 0 (0) 0 (0) 0 (0) 

 Carangidae 

 Unidentified

 (jack)

Jun, Jul 0.17 (0.11)

45 ‡

0.03 (0.03)

72.5 ‡

 0 (0) 0 (0) <0.01

(<0.01)

64 ‡

 Caranx spp. (N)

 (jack spp.)

Jun 0.16 (0.09)

49 ‡

 0 (0) 0 (0) 0 (0) 0 (0) 

 Caranx crysos

 (blue runner)

Jun, Jul, Aug 1.14 (0.41)

17 ‡

0.62 (0.43)

28 ‡

 0.04 (0.03)

26.5 ‡

 0.08 (0.03)

30.5 ‡

0.08 (0.02)

25 ‡ 

 Caranx hippos/latus

 (crevalle/horse-eye jack)

May, Jun, Jul, Aug 0.50 (0.31)

27 ‡

0 (0) <0.01

(<0.01)

49 ‡

 0.11 (0.03)

24 ‡

0.09 (0.03)

23 ‡ 

 Chloroscombrus chrysurus

 (Atlantic bumper)

Jul, Aug 1.00 (0.34)

18 ‡

0.29 (0.18)

40 ‡

 <0.01

(<0.01)

49 ‡

 0.01

(<0.01)

61.5 ‡

0.02 (0.01)

44.5 ‡ 

 Decapterus punctatus (L)

 (round scad)

Apr, May, Jul, Aug 0 (0) 0 (0) 0 (0) 0.06 (0.02)

35.5 ‡

<0.01

(<0.01)

64 ‡

 Oligoplites saurus (N)

 (leatherjack)

Jul 0.16 (0.12)

48 ‡

 0 (0) 0 (0) 0 (0) 0 (0) 

 Selar crumenopthalmus (N)

 (bigeye scad)

Jun, Jul 0.34 (0.15)

34 ‡

0.13 (0.13)

58.5 ‡

0 (0) 0 (0) 0 (0)
Table 5.7. (continued)

214

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Selene vomer (N)

 (lookdown)

Jun, Jul 0.01 (0.01)

96 ‡

0.05 (0.03)

70 ‡

0 (0) 0 (0) 0 (0)

 Seriola spp. (N)

 (jack spp.)

May 0.03 (0.03)

85 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Seriola dumerili/rivoliana (L)

 (greater amberjack/almaco jack)

May, Jun 0 (0) 0 (0) <0.01 (<0.01)

49 ‡

0 (0) 0.02 (0.01)

44.5 ‡

 Seriola fasciata (L)

 (lesser amberjack)

May 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

93 ‡

0 (0)

 Trachinotus carolinus (L)

 (Florida pompano)

Jun 0 (0) 0 (0) 0 (0) 0 (0) 0.01 (<0.01)

51.5 ‡

 Trachinotus falcatus/goodei (L)

 (permit/palometa)

May 0 (0) 0 (0) 0 (0) 0.03 (0.02)

46.5 ‡

0 (0)

 Trachurus lathami

 (rough scad)

Apr, May 0.04 (0.04)

82 ‡

0.15 (0.10)

57 ‡

0.02 (0.01)

32 ‡

0.06 (0.03)

37.5 ‡

0.01 (<0.01)

51.5 ‡

 Coryphaenidae

 Coryphaena equiselis (L)

 (pompano dolphin)

May 0 (0) 0 (0) 0 (0) 0 (0) <0.01

(<0.01)

64 ‡

 Coryphaena hippurus

 (dolphin)

May, Jul 0.03 (0.03)

86.5 ‡

0 (0) 0 (0) 0 (0) <0.01

(<0.01)

64 ‡

 Lutjanidae

 Unidentified

 (snapper)

May, Jun, Jul 0.09 (0.05)

61 ‡

0.06 (0.06)

67 ‡

<0.01 (<0.01)

49 ‡

<0.01 (<0.01)

81.5 ‡

0 (0)

 Lutjanus spp.

 (snapper spp.)

May, Jun, Jul 0.67 (0.24)

22 ‡

0.02 (0.02)

78 ‡

0 (0) 0.01 (<0.01)

61.5 ‡

0.01 (0.01)

51.5 ‡

 Lutjanus campechanus

 (red snapper)

May, Jun, Jul 0.02 (0.02)

93 ‡

0 (0) 0 (0) 0.02 (0.02)

49 ‡

0 (0)

 Rhomboplites aurorubens

 (vermilion snapper)

May, Jun, Jul 0.40 (0.25)

30 ‡

0.37 (0.21)

35 ‡

0.20 (0.06)

13 ‡

0.07 (0.03)

33.5 ‡

<0.01

(<0.01)

64 ‡

 Gerreidae

 Eucinostomus spp.

 (jenny/mojarra spp.)

May, Jun, Jul, Aug 0 (0) 0 (0) <0.01 (<0.01)

49 ‡

<0.01 (<0.01)

81.5 ‡

0.02 (0.01)

41 ‡

 Sparidae

 Unidentified

 (porgy)

Apr, May 0.04 (0.04)

83 ‡

0 (0) 0 (0) 0.01 (<0.01)

61.5 ‡

0.02 (0.01)

44.5 ‡

 Calamus spp. (L)

 (porgy spp.))

May 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Sciaenidae
Table 5.7. (continued)

215

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Unidentified (N)

 (drum spp.)

Aug <0.01

(<0.01)

100 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Cynoscion arenarius

 (sand seatrout)

Apr, May, Jul, Aug 3.12 (1.11)

11 ‡

1.25 (0.88)

19 ‡

<0.01 (<0.01)

49 ‡

0 (0) 0.01 (<0.01)

51.5 ‡

 Menticirrhus spp. (N)

 (kingfish spp.)

Aug 0.15 (0.11)

50 ‡

0.63 (0.63)

27 ‡

0 (0) 0 (0) 0 (0)

 Stellifer lanceolatus (N)

 (star drum)

Aug 0.09 (0.09)

64 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Mullidae

 Unidentified

 (goatfish)

Apr, May, Jul 0.25 (0.14)

38 ‡

0 (0) <0.01 (<0.01)

49 ‡

<0.01 (<0.01)

81.5 ‡

0.05 (0.02)

32 ‡

 Mullus auratus (L)

 (red goatfish)

Apr, May 0 (0) 0 (0) 0 (0) 0 (0) 0.06 (0.02)

27 ‡

 Pseudupeneus maculatus (L)

 (spotted goatfish)

Apr, May 0 (0) 0 (0) 0 (0) 0 (0) 0.06 (0.03)

28 ‡

 Upeneus parvus (L)

 (dwarf goatfish)

May, Jun 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

0.38 (0.09)

15 (1.58)

 Chaetodontidae

 Unidentified (N)

 (butterflyfish)

May 0.02 (0.02)

91 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Pomacentridae

 Unidentified (L)

 (damselfish)

May, Jun 0 (0) 0 (0) <0.01 (<0.01)

49 ‡

(<0.01)

61.5 ‡

0.01 (0.01)

51.5 ‡

 Abudefduf saxatilis (L)

 (sergeant major)

May, Jun, Aug 0 (0) 0 (0) 0 (0) 0 (0) 0.03 (0.02)

38.5 ‡

 Abudefduf taurus (L)

 (night sergeant)

May 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

0 (0)

 Chromis spp.

 (chromis spp.)

May, Jun 0.29 (0.29)

37 ‡

0 (0) (<0.01)

37 ‡

0.37 (0.13)

21 ‡

0.06 (0.02)

31 ‡

 Pomacentrus spp.

 (damselfish spp.)

May, Jun, Jul, Aug 0.09 (0.05)

62 ‡

0.03 (0.03)

74.5 ‡

0.07 (0.02)

20 ‡

0.12 (0.03)

23 ‡

0.30 (0.14)

16 (1.28)

 Mugilidae

 Mugil curema (L)

 (white mullet)

May, Jun 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

(0.01)

41 ‡

 Sphyraenidae

 Sphyraena borealis (L)

 (northern sennet)

May 0 (0) 0 (0) 0 (0) (<0.01)

61.5 ‡

0 (0)

 Sphyraena guachancho

 (guaguanche)

Jun, July, Aug 1.83 (0.60)

14 ‡

0 (0) 0 (0) (<0.01)

61.5 ‡

(<0.01)

57 ‡
Table 5.7. (continued)

216

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Labridae

 Unidentified

 (wrasse)

May, Aug 0.05 (0.05)

78 ‡

0.16 (0.16)

54 ‡

0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Opisthognathidae

 Unidentified

 (jawfish)

Apr, May, Jun 0.46 (0.14)

28 ‡

0.48 (0.33)

31 ‡

0 (0) 0.63 (0.20)

19 ‡

0.06 (0.02)

29.5 ‡

 Opisthognathus spp. (N)

 (jawfish spp.)

May 0.05 (0.05)

77 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Opisthognathus aurifrons

 (yellowhead jawfish)

May 0.06 (0.06)

76 ‡

0 (0) 0 (0) 0.03 (0.02)

44 ‡

0 (0)

 Opisthognathus lonchurus (N)

 (moustache jawfish)

May 0.10 (0.10)

58 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Blenniidae

 Unidentified

 (blenny)

Apr, May, Jun, Jul,

Aug

4.73 (3.95)

9 (1.53)

1.22 (0.69)

20 ‡

0.05 (0.04)

24.5 ‡

0.69 (0.21)

17 ‡

0.04 (0.03)

33 ‡

 Hypsoblennius hentz/ionthas (L)

 (feather/freckled blenny)

May, Jun, Jul 0 (0) 0 (0) 0.02 (0.01)

29 ‡

1.76 (0.57)

11 (1.21)

0.04 (0.01)

37 ‡

 Hypsoblennius invemar

 (tessellated blenny)

Apr, May, Jun, Jul 0.04 (0.04)

81 ‡

0 (0) 0.08 (0.03)

18 ‡

6.33 (1.77)

7 (4.32)

3.58 (0.67)

2 (14.55)

 Ophioblennius atlanticus (N)

 (redlip blenny)

Aug 0.42 (0.42)

29 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Parablennius marmoreus

 (seaweed blenny)

Apr, May, Jun 0.02 (0.02)

92 ‡

0 (0) 0.19 (0.04)

14 ‡

7.20 (1.06)

6 (4.87)

1.62 (0.35)

4 (6.61)

 Scartella/Hypleurochilus

 (blenny spp.)

Apr, May, Jun, Jul 0.06 (0.04)

74.5 ‡

0.21 (0.15)

46 ‡

<0.01 (<0.01)

49 ‡

1.14 (0.24)

12 ‡

0.11 (0.03)

22 ‡

 Callionymidae

 Unidentified (N)

 (dragonet)

Jul 0.03 (0.03)

86.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Gobiidae

 Unidentified Apr, May, Jun, Jul,

Aug

5.75 (0.80)

7 (1.77)

10.73 (1.76)

4 (8.53)

0.21 (0.06)

11 ‡

0.05 (0.02)

39 ‡

(<0.01)

51.5 ‡

 Bollmannia communis (L)

 (ragged goby)

Jun 0 (0) 0 (0) 0.01 (0.01)

37 ‡

0 (0) 0 (0)

 Gobionellus oceanicus

 (highfin goby)

Jun, Aug 0.03 (0.03)

89 ‡

0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Microdesmidae

 Microdesmus spp. (N)

 (wormfish spp.)

Apr, May, Jun, Jul 0.30 (0.11)

36 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Microdesmus lanceolatus Apr, May, Jun, Jul, 0.89 (0.18) 0.77 (0.31) (0.01) <0.01 (<0.01) (<0.01)
Table 5.7. (continued)

217

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 (lancetail wormfish) Aug 20 ‡ 24 ‡ 32 ‡ 81.5 ‡ 51.5 ‡

 Microdesmus longipinnis (N)

 (pink wormfish)

Apr, May, Jul 0.53 (0.18)

26 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Trichiuridae

 Gempylus spp. (N)

 (snake mackerel spp.)

Jul 0 (0) 0.02 (0.02)

78 ‡

0 (0) 0 (0) 0 (0)

 Trichiurus lepturus

 (Atlantic cutlassfish)

Apr, May, Jun, Jul,

Aug

0.35 (0.13)

33 ‡

0.26 (0.13)

43 ‡

0.05 (0.02)

22.5 ‡

0.01 (0.01)

61.5 ‡

<0.01

(<0.01)

64 ‡

 Scombridae

 Unidentified

 (mackerel)

May, Jun, Jul, Aug 0.10 (0.06)

56 ‡

0.43 (0.29)

34 ‡

(<0.01)

37 ‡

0.10 (0.08)

25 ‡

0.04 (0.01)

35.5 ‡

 Auxis spp.

 (mackerel spp.)

Apr, May, Jun, Jul,

Aug

6.61 (2.32)

5 (1.69)

1.26 (0.79)

18 ‡

0.02 (0.01)

32 ‡

0.76 (0.19)

15 ‡

0.24 (0.06)

18 ‡

 Euthynnus alletteratus

 (little tunny)

May, Jun, Jul, Aug 4.55 (1.05)

10 (1.39)

4.10 (1.06)

8 (3.09)

0.08 (0.03)

19 ‡

0.92 (0.17)

13 ‡

2.83 (0.62)

3 (11.54)

 Katsuwonus pelamis

 (skipjack tuna)

May 0.06 (0.04)

74.5 ‡

0 (0) 0 (0) 0.08 (0.03)

30.5 ‡

0 (0)

 Scomber japonicus (L)

 (chub mackeral)

Apr 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

44.5 ‡

 Scomberomorus cavalla

 (king mackerel)

May, Jun, Jul, Aug 0.13 (0.06)

54 ‡

0.07 (0.04)

66 ‡

<0.01 (<0.01)

49 ‡

0.09 (0.03)

26 ‡

0.27 (0.11)

17 (1.11)

 Scomberomorus maculatus

 (Spanish mackerel)

Jun, Jul, Aug 0.36 (0.14)

32 ‡

0.21 (0.21)

48 ‡

0 (0) 0.04 (0.02)

41.5 ‡

0.17 (0.05)

20 ‡

 Thunnus spp. (L)

 (tuna spp.)

Aug 0 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.01)

51.5 ‡

 Thunnus thynnus (L)

 (bluefin tuna)

May 0 (0) 0 (0) 0 (0) 0.01 (0.01)

61.5 ‡

0 (0)

 Stromateidae

 Ariomma regulus (L)

 (spotted driftfish)

Aug 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Centrolophus medusophagus

 (brown ruff)

Apr 0 (0) 0.32 (0.26)

37 ‡

0 (0) <0.01 (<0.01)

81.5 ‡

<0.01

(<0.01)

64 ‡

 Peprilus burti

 (gulf butterfish)

Apr, May 0.07 (0.05)

70 ‡

0.04 (0.04)

71 ‡

<0.01 (<0.01)

49 ‡

0.03 (0.02)

46.5 ‡

0.02 (0.01)

41 ‡

 Peprilus alepidotus (N)

 (harvestfish)

May, Jul, Aug 0.21 (0.11)

43 ‡

2.79 (1.72)

10 ‡

0 (0) 0 (0) 0 (0)

Pleuronectiformes

 Unidentified (N) Aug 0.01 (0.01) 0.08 (0.08) 0 (0) 0 (0) 0 (0)
Table 5.7. (continued)

218

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 (flounder) 97 ‡ 63 ‡

 Bothidae

 Unidentified

 (lefteye flounder)

Apr, May, Jul 0.06 (0.05)

73 ‡

0.17 (0.13)

51 ‡

<0.01 (<0.01)

49 ‡

0 (0) 0 (0)

 Bothus spp. (L)

 (flounder spp.)

May 0 (0) 0 (0) 0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)

 Citharichthys spilopterus

 (bay whiff)

Apr, May, Jul 0.05 (0.04)

79 ‡

0.28 (0.20)

41 ‡

0 (0) 0 (0) <0.01

(<0.01)

64 ‡

 Cyclopsetta spp. (N)

 (flounder spp.)

Jun, Jul 0.10 (0.08)

57 ‡

0.53 (0.47)

29 ‡

0 (0) 0 (0) 0 (0)

 Engyophrys senta (N)

 (spiny flounder)

Jul 0 (0) 0.02 (0.02)

76 ‡

0 (0) 0 (0) 0 (0)

 Etropus crossotus

 (fringed flounder)

Apr, May, Jun, Jul,

Aug

0.65 (0.19)

23 ‡

1.79 (0.54)

16 (1.57)

(<0.01)

37 ‡

<0.01 (<0.01)

81.5 ‡

(<0.01)

51.5 ‡

 Syacium spp.

 (flounder spp.)

Apr, Jun, Jul, Aug 0.25 (0.12)

39 ‡

3.78 (1.14)

9 (2.82)

0 (0) 0.02 (0.01)

51 ‡

<0.01

(<0.01)

64 ‡

 Soleidae

 Achirus lineatus (N)

 (lined sole)

Jun, Jul 0.21 (0.08)

41 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Symphurus spp.

 (tonguefish spp.)

Apr, May, Jun, Jul,

Aug

6.79 (1.18)

4 (1.69)

17.00 (3.82)

2 (14.49)

0.05 (0.02)

22.5 ‡

0.08 (0.02)

28 ‡

0.07 (0.03)

26 ‡

Tetraodontiformes

 Balistidae

 Unidentified (N)

 (leatherjacket)

Jul 0.03 (0.03)

90 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Tetraodontiformes

 Tetraodontidae

 Sphoeroides spp.

 (puffer spp.)

Apr, May, Jun, Jul 0.14 (0.07)

53 ‡

0.28 (0.22)

42 ‡

0 (0) <0.01 (<0.01)

81.5 ‡

0 (0)
219

Table 5.8. Total plankton net density (fish/100 m3) and light-trap CPUE (fish/10 min) for fish

collected at South Timbalier 54 with standard error (SE), rank, percent of total catch (%),

and months collected for each taxa. (N) indicates taxa collected only with plankton nets.

(L) indicates taxa collected only with light-traps. For ranks, tied values received the

mean of the corresponding ranks. ‡ indicates a value <1.00%.

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

Osteichthyes

 Unidentified Apr, May 3.93 (3.66)

12 ‡

0 (0) 0 (0) 0.50 (0.50)

6 (1.20)

0 (0)

Albuliformes

 Albulidae

 Albula vulpes (L)

 (bonefish)

Apr 0 (0) 0 (0) 0 (0) (0.01)

42 ‡

0 (0)

Anguilliformes

 Unidentified

 (eel)

Jun 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Muraenidae

 Unidentified (L)

 (moray eel)

Jun 0.43 (0.41)

40 ‡

0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Ophichthidae

 Unidentified

 (snake eel)

Apr, May, Jun 0.20 (0.18)

52 ‡

0 (0) 0 (0) <0.01 (0.01)

50 ‡

0.02 (0.02)

50 ‡

Clupeiformes

 Unidentified (N)

 (herring/anchovy)

May 1.92 (1.92)

17 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Clupeidae

 Brevoortia patronus (L)

 (gulf menhaden)

Apr 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Etrumeus teres (N)

 (round herring)

Apr 0.04 (0.03)

68 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Harengula jaguana

 (scaled sardine)

Apr, May, Jun, Jul 1.27 (0.50)

24 ‡

0 (0) 0 (0) 0.56 (0.17)

5 (1.29)

0.55 (0.22)

8 (1.43)

 Opisthonema oglinum

 (Atlantic thread herring)

Apr, May, Jun, Jul 3689.84 (1964.23)

1 (96.56)

0 (0) 0.35 (0.14)

3 (7.05)

23.26 (9.41)

1 (54.60)

25.53 (7.93)

1 (66.71)

 Sardinella aurita

 (Spanish sardine)

Apr 0.03 (0.03)

74 ‡

0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Engraulidae

 Unidentified Apr, May, Jun, Jul 146.75 (39.54) 10.73 (7.58) 0.13 (0.06) 1.13 (0.53) 0.90 (0.20)
Table 5.8. (continued)

220

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 (anchovy) 2 (1.49) 2 (46.38) 5 (2.90) 4 (2.71) 4 (2.36)

 Anchoa spp.

 (anchovy spp.)

May 0.61 (0.61)

31 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Anchoa hepsetus (L)

 (striped anchovy)

Jun 0 (0) 0 (0) 0 (0) (0.01)

42 ‡

0 (0)

 Anchoa mitchilli

 (bay anchovy)

Apr, May, Jun, Jul 4.23 (1.61)

11 ‡

0 (0) 0.04 (0.03)

13 ‡

0.38 (0.13)

9 ‡

0.31 (0.17)

11 ‡

 Anchoa nasuta (L)

 (longnose anchovy)

May, Jun 0 (0) 0 (0) 0 (0) 0.06 (0.04)

21 ‡

 (0.03)

 33 ‡

 Anchoa nasuta/hepsetus

 (longnose/striped anchovy)

Apr, May, Jun, Jul 2.27 (0.77)

16 ‡

0 (0) 0.57 (0.20)

2 (11.62)

9.89 (3.63)

2 (23.74)

3.66 (1.49)

2 (9.57)

 Anchoviella perfasciata (N)

 (flat anchovy)

Apr 0.02 (0.02)

77.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Engraulis eurystole

 (silver anchovy)

Apr, May, Jun, Jul 0.22 (0.15)

49 ‡

0 (0) 0 (0) 0.26 (0.07)

11 ‡

(0.02)

33 ‡

Stomiiformes

 Gonostomatidae

 Cyclothone braueri (N) Apr 0.10 (0.06)

60 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Aulopiformes

 Synodontidae

 Unidentified (L)

 (lizardfish)

Apr, May 0 (0) 0 (0) 0 (0) (0.01)

 42 ‡

0.02 (0.02)

50 ‡

 Saurida brasiliensis (L)

 (largescale lizardfish)

May, Jun 0 (0) 0 (0) (0.03)

9.5 (1.24)

0.06 (0.03)

21 ‡

0.08 (0.03)

26.5 ‡

 Saurida suspicio (L)

 

May 0 (0) 0 (0) 0 (0) 0 (0) (0.02)

 50 ‡

 Synodus foetens

 (inshore lizardfish)

Apr, May, Jun 0.21 (0.14)

50 ‡

0.26 (0.26)

11 (1.45)

2.88 (1.55)

1 (58.51)

3.16 (1.25)

3 (7.60)

0.27 (0.10)

12 ‡

 Synodus poeyi

 (offshore lizardfish)

Apr, May 0.23 (0.19)

48 ‡

0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

Myctophiformes

 Myctophidae

 Unidentified

 (lanternfish)

Apr, Jul 0.24 (0.13)

47 ‡

4.09 (3.52)

4 (4.35)

0 (0) 0 (0) (0.2)

 33 ‡

Gadiformes
Table 5.8. (continued)

221

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Bregmacerotidae

 Bregmaceros cantori

 (codlet)

Apr, May 1.85 (0.66)

20 ‡

0.26 (0.26)

11 (1.45)

0.06 (0.03)

9.5 (1.24)

 (0.01)

 42 ‡

0.10 (0.05)

24 ‡

 Ophidiidae

 Lepophidium spp.

 (cusk-eel spp.)

Apr, May 0.41 (0.41)

42.5 ‡

0 (0) 0 (0) 0 (0) (0.02)

 50 ‡

 Lepophidium staurophor (L) Apr 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Ophidion spp. (N)

 (cusk-eel spp.)

Apr (0.03)

72 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Ophidion nocomis/selenops

 (cusk-eel spp.)

May 3.09 (1.77)

13 ‡

0 (0) 0.02 (0.02)

18.5 ‡

0 (0) 0 (0)

 Ophidion robinsi (L)

 (cusk-eel spp.)

May 0 (0) 0 (0) 0.02 (0.02)

18.5 ‡

0 (0) 0 (0)

 Ophidion selenops (L)

 (mooneye cusk-eel)

May 0 (0) 0 (0) 0.02 (0.02)

18.5 ‡

(0.01)

42 ‡

0 (0)

 Bythitidae

 Unidentified (N)

 (brotula)

May 0.41 (0.41)

42.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Gobiesociformes

 Gobiesocidae

 Gobiesox strumosus

 (skilletfish)

Apr, May 0.03 (0.03)

69.5 ‡

0 (0) 0 (0) 0.06 (0.04)

21 ‡

0.03 (0.02)

36 ‡

Atheriniformes

 Exocoetidae

 Unidentified (N)

 (flyingfish)

Apr 0.03 (0.03)

71 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Cypselurus spp. (N)

 (flyingfish spp.)

Apr 0.03 (0.03)

69.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Cypselurus cyanopterus (L)

 (margined flyingfish)

Jun 0 (0) 0 (0) 0 (0) 0 (0) (0.02)

 50 ‡

 Cypselurus furcatus (L)

 (spotfin flyingfish)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Atherinidae

 Unidentified (N)

 (silverside)

Apr 0.29 (0.20)

45 ‡

0 (0) 0 (0) 0 (0) 0 (0)
Table 5.8. (continued)

222

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Membras martinica (L)

 (rough silverside)

Jun 0 (0) 0 (0) 0 (0) 0.02 (0.02)

32 ‡

0 (0)

Gasterosteiformes

 Syngnathidae

 Syngnathus spp. (N)

 (pipefish spp.)

Apr 0.03 (0.03)

74 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Syngnathus louisiana (N)

 (chain pipefish)

Apr 0.02 (0.02)

80.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

Scorpaeniformes

 Scorpaenidae

 Scorpaena spp.

 (scorpionfish spp.)

Apr, Jun 0 (0) 0.26 (0.26)

11 (1.45)

0 (0) 0.02 (0.02)

32 ‡

0.02 (0.02)

50 ‡

 Triglidae

 Prionotus spp.

 (searobin spp.)

Apr 0.58 (0.26)

36 ‡

0 (0) 0 (0) 0.01 (0.01)

42 ‡

0.02 (0.02)

50 ‡

Perciformes

 Unidentified Apr, May, Jun, Jul 10.47 (3.57)

6 ‡

14.29

(14.29)

1 (10.14)

0 (0) 0.02 (0.02)

32 ‡

0.16 (0.07)

17.5 ‡

 Serranidae

 Unidentified (N)

 (seabass/grouper)

Apr 0.06 (0.06)

65 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Epinephelinae (N)

 (grouper)

Apr (0.03)

 74 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Serraninae

 (seabass)

Apr, May 0.34 (0.24)

44 ‡

0 (0) 0 (0) (0.01)

42 ‡

0 (0)

 Priacanthidae

 Priacanthus spp. (L)

 (bigeye spp.)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Carangidae

 Unidentified (N)

 (jack)

Apr, Jun 0.43 (0.28)

41 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Caranx crysos (L)

 (blue runner)

May, Jun, Jul 0 (0) 0 (0) 0.02 (0.02)

23.5 ‡

(0.03)

19 ‡

0.24 (0.08)

14 ‡

 Caranx hippos/latus

 (crevalle/horse-eye jack)

May, Jun, Jul 2.70 (2.44)

14 ‡

0 (0) 0 (0) 0.04 (0.02)

26.5 ‡

0.61 (0.25)

6 (1.60)
Table 5.8. (continued)

223

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Chloroscombrus chrysurus

 (Atlantic bumper)

May, Jun, Jul 30.00 (11.03)

4 ‡

0 (0) 0.02 (0.02)

18.5 ‡

0.09 (0.04)

17 ‡

0.11 (0.06)

22 ‡

 Decapterus punctatus

 (round scad)

Apr, May, Jun 0.02 (0.02)

77.5 ‡

0 (0) 0 (0) 0.02 (0.02)

32 ‡

0.02 (0.02)

50 ‡

 Oligoplites saurus (N)

 (leatherjack)

Jun 0.48 (0.37)

37 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Selar crumenopthalmus (L)

 (bigeye scad)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Selene spp. (N)

 (moonfish/lookdown spp.)

May 0.61 (0.61)

31 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Seriola spp. (L)

 (jack spp.)

Apr 0 (0) 0 (0) 0 (0) (0.01)

49 ‡

0 (0)

 Trachinotus carolinus (L)

 (Florida pompano)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.03 (0.03)

33 ‡

 Trachurus lathami

 (rough scad)

Apr, May 0.02 (0.02)

80.5 ‡

0 (0) 0 (0) (0.05)

18 ‡

0.02 (0.02)

50 ‡

 Lutjanidae

 Unidentified (N)

 (snapper)

Jul 0.17 (0.17)

54.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Lutjanus spp. (N)

 (snapper spp.)

May, Jul 0.61 (0.45)

31 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Lutjanus campechanus

 (red snapper)

May, Jun 0.61 (0.61)

31 ‡

0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Rhomboplites aurorubens

(L)

 (vermilion snapper)

May, Jun 0 (0) 0 (0) 0.12 (0.07)

6 (2.49)

0 (0) 0 (0)

 Gerreidae

 Unidentified (L)

 (jenny/mojarra)

May 0 (0) 0 (0) 0 (0) 0 (0) (0.02)

50 ‡

 Haemulidae

 Unidentified (N)

 (grunt)

May 0.61 (0.61)

31 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Sparidae

 Unidentified (N)

 (porgy)

Apr 0.14 (0.14)

58 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Calamus spp. (N)

 (porgy spp.)

Apr 0.10 (0.10)

61 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Sciaenidae
Table 5.8. (continued)

224

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Unidentified

 (drum)

Apr, May, Jun (0.15)

 57 ‡

0 (0) 0 (0) 0.02 (0.02)

32 ‡

0.02 (0.02)

50 ‡

 Bairdiella chrysoura

 (silver perch)

Jun 0.12 (0.12)

 59 ‡

0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Cynoscion arenarius

 (sand seatrout)

Apr, May, Jun, Jul 42.16 (8.56)

3 ‡

7.99 (3.21)

3 (21.74)

(0.04)

7 (2.07)

0.42 (0.11)

8 (1.03)

0.56 (0.13)

7 (1.47)

 Larimus fasciatus (N)

 (banded drum)

Apr 0.05 (0.04)

66 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Menticirrhus spp.

 (kingfish spp.)

Apr, May, Jun, Jul 1.45 (0.36)

22 ‡

0 (0) 0 (0) 0 (0) (0.02)

33 ‡

 Stellifer lanceolatus (N)

 (star drum)

Apr 0.44 (0.25)

39 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Mullidae

 Upeneus parvus (L)

 (dwarf goatfish)

Apr 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Ephippidae

 Chaetodipterus faber (N)

 (Atlantic spadefish)

May, Jul 0.86 (0.39)

25 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Pomacentridae

 Abudefduf saxatilis (L)

 (sergeant major)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.10 (0.07)

24 ‡

 Pomacentrus spp. (L)

 (damselfish spp.)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Mugilidae

 Mugil cephalus (L)

 (striped mullet)

Apr 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Mugil curema (L)

 (white mullet)

May 0 (0) 0 (0) 0 (0) (0.01)

42 ‡

0.05 (0.04)

29.5 ‡

 Sphyraenidae

 Sphyraena borealis (L)

 (northern sennet)

May 0 (0) 0 (0) 0 (0) (0.01)

42 ‡

0 (0)

 Labridae

 Unidentified (L)

 (wrasse)

Jun 0 (0) 0 (0) 0.02 (0.02)

18.5 ‡

0 (0) 0 (0)

 Scaridae

 Unidentified (N)

 (parrotfish)

Apr (0.02)

77.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)
Table 5.8. (continued)

225

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

Blenniidae

 Unidentified

 (blenny)

Apr, May, Jun, Jul 2.47 (0.90)

15 ‡

1.10 (1.10)

6 (1.45)

0.02 (0.02)

18.5 ‡

0.09 (0.03)

16 ‡

0.08 (0.05)

26.5 ‡

 Hypsoblennius hentz/ionthas

 (feather/freckled blenny)

Apr, May, Jun 0.17 (0.17)

54.5 ‡

0 (0) 0 (0) 0.21 (0.08)

12 ‡

0.48 (0.22)

9.5 (1.26)

 Hypsoblennius invemar

 (tessellated blenny)

Apr, May, Jun 0.61 (0.61)

31 ‡

0 (0) 0 (0) 0.11 (0.05)

15 ‡

0.48 (0.19)

9.5 (1.26)

 Parablennius marmoreus

 (seaweed blenny)

May, Jul 0.20 (0.20)

53 ‡

0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Scartella/Hypleurochilus

 (blenny spp.)

Apr, May, Jun, Jul 1.89 (1.29)

19 ‡

0 (0) 0.06 (0.03)

9.5 (1.24)

0.49 (0.26)

7 (1.17)

0.16 (0.08)

17.5 ‡

 Eleotridae

 Dormitator maculatus (N)

 (fat sleeper)

Apr 0.02 (0.02)

77.5 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Gobiidae

 Unidentified

 (goby)

Apr, May, Jun, Jul 29.96 (12.71)

5 ‡

1.41 (0.96)

5 (4.35)

0.06 (0.03)

9.5 (1.24)

0.03 (0.02)

28 ‡

0.23 (0.08)

15 ‡

 Microdesmidae

 Microdesmus spp.

 (wormfish spp.)

Apr, Jul 0.58 (0.43)

35 ‡

0 (0) 0 (0) 0.01 (0.01)

42 ‡

0 (0)

 Microdesmus lanceolatus

(N)

 (lancetail wormfish)

Jun, Jul 1.28 (0.86)

23 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Trichiuridae

 Trichiurus lepturus

 (Atlantic cutlassfish)

Apr, May, Jun 0 (0) 0.52 (0.52)

8.5 (2.90)

0.18 (0.07)

4 (3.73)

0.01 (0.01)

42 ‡

0 (0)

 Scombridae

 Unidentified (N)

 (mackerel)

Apr, Jul 0.25 (0.18)

46 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Auxis spp.

 (mackerel spp.)

May, Jun, Jul 0 (0) 0 (0) 0 (0) 0.02 (0.02)

32 ‡

0.26 (0.17)

13 ‡

 Euthynnus alletteratus

 (little tunny)

May, Jun, Jul 0.47 (0.27)

38 ‡

0 (0) 0.02 (0.02)

23.5 ‡

0.37 (0.23)

10 ‡

1.08 (0.47)

3 (2.82)

 Scomberomorus cavalla

 (king mackerel)

Apr, May, Jun, Jul 5.39 (3.15)

10 ‡

0 (0) 0.04 (0.03)

13 ‡

0.05 (0.04)

24 ‡

0.10 (0.05)

24 ‡

 Scomberomorus maculatus

 (Spanish mackerel)

Apr, May, Jun, Jul 6.56 (2.09)

9 ‡

0 (0) 0 (0) 0.18 (0.06)

13 ‡

0.81 (0.18)

5 (2.11)
Table 5.8. (continued)

226

Taxa Months Collected Surface

Net

Bottom

Net

Bottom

Light-trap

Surface

Light-trap

Off-platform 

Light-trap

Density (SE) Density (SE) CPUE (SE) CPUE (SE) CPUE (SE)

Rank (%) Rank (%) Rank (%) Rank (%) Rank (%)

 Stromateidae

 Ariomma spp. (N)

 (driftfish spp.)

Apr 0.05 (0.04)

67 ‡

0.52 (0.52)

8.5 (2.90)

0 (0) 0 (0) 0 (0)

 Peprilus burti

 (gulf butterfish)

Apr, May 1.65 (1.23)

21 ‡

0 (0) 0.02 (0.02)

18.5 ‡

0.14 (0.05)

14 ‡

0.13 (0.05)

20.5 ‡

 Peprilus alepidotus

 (harvestfish)

Apr, May, Jul 1.92 (0.77)

18 ‡

0 (0) 0.04 (0.03)

13 ‡

0.04 (0.02)

26.5 ‡

0.15 (0.06)

19 ‡

Pleuronectiformes

 Bothidae

 Unidentified (N)

 (lefteye flounder)

May 0.81 (0.81)

26 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Citharichthys spilopterus

 (bay whiff)

Apr, May, Jun 0.21 (0.13)

51 ‡

0 (0) 0 (0) 0 (0) 0.05 (0.04)

29.5 ‡

 Cyclopsetta fimbriata (L)

 (spotfin flounder)

May 0 (0) 0 (0) 0 (0) 0 (0) 0.02 (0.02)

50 ‡

 Etropus crossotus

 (fringed flounder)

Apr, May, Jun 7.59 (2.94)

8 ‡

0.89 (0.89)

7 (1.45)

0 (0) 0.05 (0.02)

24 ‡

0.13 (0.06)

20.5 ‡

 Syacium spp. (L)

 (flounder spp.)

May 0.61 (0.61)

31 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Soleidae

 Unidentified

 (sole)

Jun, Jul 0.06 (0.06)

63.5 ‡

0 (0) 0.02 (0.02)

18.5 ‡

0 (0) 0 (0)

 Achirus lineatus

 (lined sole)

Apr, May, Jul 0.16 (0.10)

56 ‡

0 (0) 0 (0) 0.02 (0.02)

32 ‡

0 (0)

 Gymnachirus spp. (N)

 (sole spp.)

May 0.09 (0.09)

62 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Trinectes maculatus (N)

 (hogchoker)

Apr, May 0.70 (0.42)

27 ‡

0 (0) 0 (0) 0 (0) 0 (0)

 Symphurus spp.

 (tonguefish spp.)

Apr, May, Jun, Jul 8.84 (3.84)

7 ‡

0 (0) 0 (0) 0.01 (0.01)

42 ‡

0.06 (0.04)

28 ‡

Tetraodontiformes

 Tetraodontidae

 Sphoeroides spp.

 (puffer spp.)

Apr, May, Jun 0.06 (0.06)

63.5 ‡

0 (0) 0 (0) 0.05 (0.03)

24 ‡

0.21 (0.12)

16 ‡

 Sphoeroides parvus (L)

 (least puffer)

Apr 0 (0) 0 (0) 0 (0) 0.01 (0.01)

42 ‡

0 (0)
227

Table 5.9. Total mean light-trap CPUE (fish/10 min) and pushnet density (fish/100 m3) for fish

collected at Belle Pass with standard error (SE), rank, percent of total catch (%), and

months collected for each taxa. For ranks, tied values received the mean of the

corresponding ranks. ‡ indicates a value <1.00%.

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

Osteichthyes

 Unidentified Apr, May, Jun, Jul, Aug 0.14 (0.06)

17 ‡

1.23 (0.65)

20 ‡

Elopiformes

 Elopidae

 Elops saurus

 (ladyfish)

Apr, May, Jun, Jul, Aug <0.01 (<0.01)

48 ‡

0.22 (0.06)

36 ‡

 Megalops atlanticus

 (tarpon)

Aug 0 (0) 0.03 (0.01)

60 ‡

Anguilliformes

 Unidentified

 (eel)

Apr, May, Jun, Jul, Aug <0.01(<0.01)

48‡

0.17(0.08)

41‡

 Ophichthidae

 Unidentified

 (snake eel)

Apr, May, Jun 0.03(0.02)

31‡

0.03(0.03)

57‡

 Bascanichthys spp.

 (sooty/whip eel spp.)

Jun, Jul, Aug 0 (0) 0.13(0.03)

44‡

 Myrophis punctatus

 (speckled worm eel)

Apr, May, Jun, Jul 0.04(0.02)

28‡

0.64(0.31)

27‡

 Ophichthus gomesi

 (shrimp eel)

Jul 0 (0) 0.15(0.07)

42‡

 Ophichthus melanoporus

 (blackpored eel)

Aug 0 (0) <0.01(<0.01)

82‡

 Congridae

 Paraconger caudilimbatus

 (margintail conger)

Jun 0 (0) <0.01(<0.01)

82‡

Clupeiformes

 Unidentified

 (herring/anchovy)

May, Jun, Jul, Aug 0.01(<0.01)

41‡

10.85(3.88)

5(2.05)

 Clupeidae

 Unidentified

 (herring)

Apr, May, Aug 0.07(0.04)

22‡

2.48(1.42)

13‡

 Brevoortia spp.

 (menhaden spp.)

Apr, Aug 0.15(0.08)

16‡

2.77(2.09)

11‡

 Brevoortia patronus

 (gulf menhaden)

Apr, May, Jun, Jul, Aug 0.04(0.03)

27‡

0.60(0.37)

29‡
Table 5.9. (continued)

228

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 Harengula jaguana

 (scaled sardine)

May, Jun, July, Aug 1.12(0.36)

4‡

0.53(0.10)

30‡

 Opisthonema oglinum

 (Atlantic thread herring)

May, Jun, July, Aug 0.28(0.12)

11‡

0.40(0.10)

32‡

 Engraulidae

 Unidentified

 (anchovy)

Apr, May, Jun, Jul, Aug 16.33(7.07)

2(13.47)

138.43(21.12)

2(27.74)

 Anchoa hepsetus

 (striped anchovy)

Apr, May, Jun, Jul, Aug 0.73(0.24)

6‡

1.30(0.50)

18‡

 Anchoa mitchilli

 (bay anchovy)

Apr, May, Jun, Jul, Aug 95.80(37.97)

1(79.07)

153.25(33.48)

1(38.23)

 Anchoa nasuta

 (longnose anchovy)

May, Jun, Jul, Aug 0.24(0.08)

13‡

0.18(0.06)

38‡

 Anchoa nasuta/hepsetus

 (longnose/striped anchovy)

Apr, May, Jun, Jul, Aug 0.64(0.22)

7‡

1.90(0.45)

15‡

Siluriformes

 Ariidae

 Arius felis

 (hardhead catfish)

May, Jul 0 (0) 0.09(0.06)

48‡

 Bagre marinus

 (gafftopsail catfish)

Jul, Aug 0 (0) 0.10(0.08)

46‡

Aulopiformes

 Synodontidae

 Unidentified

 (lizardfish)

May 0 (0) <0.01(<0.01)

88‡

 Synodus spp.

 (lizardfish spp.)

Apr, May 0 (0) 0.02(0.02)

61‡

 Synodus foetens

 (inshore lizardfish)

Apr, May, Jun, Jul, Aug 0.15(0.04)

15‡

0.93(0.14)

23‡

 Paralepidae

 Paralepis atlantica

 (duckbill barracudina)

Apr 0 (0) <0.01(<0.01)

90‡

Gadiformes

 Ophidiidae

 Unidentified

 (cuskeel)

Apr 0 (0) <0.01(<0.01)

89‡

 Lepophidium spp.

 (cusk-eel spp.)

Jun 0 (0) <0.01(<0.01)

108‡

Gobiesociformes

 Gobiesocidae
Table 5.9. (continued)

229

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 Gobiesox strumosus

 (skilletfish)

Apr, May, Jun, Jul, Aug 0.47(0.13)

10‡

1.55(0.25)

16‡

Atheriniformes

 Exocoetidae

 Unidentified

 (flyingfish)

May, Jun 0 (0) 0.01(<0.01)

80‡

 Cypselurus spp.

 (flying fish spp.)

Jun <0.01(<0.01)

48‡

0 (0)

 Hyporhamphus

unifasciatus

 (silverstriped halfbeak)

May, Jun, Jul, Aug <0.01(<0.01)

48‡

0.04(0.01)

55‡

Atherinidae

 Unidentified

 (silverside)

Apr, May, Jun, Jul, Aug 0 (0) 0.18(0.08)

40‡

 Membras martinica

 (rough silverside)

Apr, May, Jun, Jul, Aug 1.30(0.56)

3(1.09)

0.98(0.22)

21‡

 Menidia beryllina

 (inland silverside)

May 0 (0) 0.02(0.02)

66‡

Gasterosteiformes

 Syngnathidae

 Hippocampus erectus

 (lined seahorse)

Jun 0 (0) <0.01(<0.01)

99‡

 Syngnathus spp.

 (pipefish spp.)

Apr, May, Jun, Jul, Aug <0.01(<0.01)

48‡

0.09(0.03)

49‡

 Syngnathus louisiana

 (chain pipefish)

Jul 0 (0) <0.01(<0.01)

111‡

Scorpaeniformes

 Triglidae

 Prionotus spp.

 (searobin spp.)

Jun 0 (0) <0.01(<0.01)

110‡

 Prionotus roseus

 (bluespotted searobin)

Jul 0 (0) <0.01(<0.01)

101‡

 Prionotus tribulus

 (bighead searobin)

Jul 0 (0) <0.01(<0.01)

94‡

Perciformes

 Serranidae

 Epinephelinae

 (grouper spp.)

Apr 0 (0) <0.01(<0.01)

97‡

 Rachycentridae

 Rachycentron canadum

 (cobia)

May 0 (0) <0.01(<0.01)

86‡
Table 5.9. (continued)

230

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 Carangidae

 Unidentified

 (jack)

0 (0) 0.02(0.02)

62‡

 Caranx spp.

 (jack spp.)

Aug 0 (0) 0.64(0.26)

28‡

 Caranx hippos/latus

 (crevalle/horse-eye jack)

Jun, Jul, Aug <0.01(<0.01)

48‡

0.09(0.04)

47‡

 Chloroscombrus chrysurus

 (Atlantic bumper)

Jun, Jul, Aug 0.05(0.02)

23‡

0.28(0.15)

35‡

 Oligoplites saurus

 (leatherjack)

Aug <0.01(<0.01)

48‡

0.02(<0.01)

71‡

 Selene vomer

 (lookdown)

Jul 0 (0) <0.01(<0.01)

98‡

 Selene setapinnis

 (Atlantic moonfish)

Jul 0 (0) <0.01(<0.01)

104‡

 Lutjanidae

 Lutjanus griseus

 (gray snapper)

Jun, Jul, Aug 0 (0) 0.03(0.01)

59‡

 Lutjanus synagris

 (lane snapper)

Jul, Aug 0.01(<0.01)

38‡

0.07(0.02)

51‡

 Lutjanus spp.

 (snapper spp.)

Aug <0.01(<0.01)

48‡

0 (0)

 Gerreidae

 Unidentified

 (jenny/mojarra)

May, Jun, Aug 0.02(0.01)

34‡

0.19(0.07)

37‡

 Eucinostomus spp.

 (mojarra/jenny spp.)

Jun, Aug <0.01(<0.01)

48‡

0.02(0.01)

70‡

 Haemulidae

 Unidentified

 (grunt)

Jul 0 (0) <0.01(<0.01)

102‡

 Sparidae Apr, May

 Unidentified

 (porgy)

0 (0) 0.02(0.01)

63‡

 Sparidae Type B

 (porgy spp.)

May 0 (0) 0.02(<0.01)

68‡

 Sciaenidae

 Unidentified

 (drum)

May, Jun, Jul, Aug 0.02(0.01)

34‡

2.54(0.96)

12‡

 Bairdiella chrysoura

 (silver perch)

Apr, May, Jun, Jul, Aug 0.12(0.08)

19‡

3.07(0.73)

10‡

 Cynoscion arenarius Apr, May, Jun, Jul, Aug 0.59(0.28) 40.74(8.02)
Table 5.9. (continued)

231

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 (sand seatrout) 9‡ 4(7.85)

 Cynoscion nebulosus

 (spotted seatrout)

Apr, May, Jun, Aug 0.01(<0.01)

38‡

0.85(0.21)

24‡

 Cynoscion

nebulosus/arenarius

 (spotted/sand seatrout)

Jul 0 (0) 0.01(0.01)

74‡

 Menticirrhus spp.

 (kingfish spp.)

Apr, May, Jul, Aug 0.03(0.01)

29‡

0.51(0.09)

31‡

 Menticirrhus

americanus/littoralis

 (gulf/northern kingfish)

Jun, Aug 0 (0) 0.02(0.01)

64‡

 Micropogonias undulatus

 (Atlantic croaker)

Apr, Jul 0 (0) 0.04(0.02)

56‡

 Pogonias cromis

 (black drum)

May 0.01(<0.01)

38‡

0.74(0.21)

26‡

 Sciaenops ocellatus

 (red drum)

Aug <0.01(<0.01)

48‡

1.29(0.59)

19‡

 Stellifer lanceolatus

 (star drum)

Apr, Jun, Jul 0 (0) 0.05(0.02)

54‡

 Mullidae

 Unidentified

 (goatfish)

May 0 (0) <0.01(<0.01)

87‡

 Ephippidae

 Chaetodipterus faber

 (Atlantic spadefish)

Jun, Aug 0 (0) 0.05(0.02)

52‡

 Mugilidae

 Mugil cephalus

 (striped mullet)

Apr 0 (0) <0.01(<0.01)

97‡

 Mugil curema

 (white mullet)

Apr, May, Jun 0 (0) 0.02(<0.01)

69‡

 Polynemidae

 Polydactylus octonemus

 (Atlantic threadfin)

Aug 0 (0) <0.01(<0.01)

93‡

 Labridae

 Unidentified

 (wrasse)

Apr 0 (0) 0.01(<0.01)

77‡

 Scaridae

 Sparisoma spp.

 (parrotfish spp.)

Apr 0 (0) 0.01(<0.01)

72‡

 Uranoscopidae

 Unidentified Jun 0 (0) <0.01(<0.01)
Table 5.9. (continued)

232

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 (stargazer) 92‡

 Blenniidae

 Unidentified

 (blenny)

May, Jun, Jul, Aug 0.02(0.01)

35‡

0.03(0.02)

58‡

 Chasmodes spp.

 (striped/Florida blenny)

Apr 0 (0) <0.01(<0.01)

100‡

 Hypleurochilus

bermudensis

 (barred blenny)

Aug 0 (0) <0.01(<0.01)

95‡

 Hypsoblennius spp.

 (blenny spp.)

Jul 0 (0) <0.01(<0.01)

104(<.1.00)

 Hypsoblennius

hentz/ionthas

 (feather/tessellated blenny)

Apr, May, Jun, Jul, Aug 1.04(0.27)

5‡

1.95((0.45)

14‡

 Scartella cristata

 (molly miller)

Apr, May, Jun, Jul, Aug 0.03(0.02)

31‡

0.34(0.08)

33‡

 Eleotridae

 Unidentified

 (sleeper)

Jun, Jul, Aug 0.01(<0.01)

38‡

0.02(0.01)

67‡

 Eleotridae Type A

 (sleeper spp.)

Jun, Aug <0.01(<0.01)

48‡

0.18(0.06)

39‡

 Dormitator maculatus

 (fat sleeper)

Apr, May, Jun, Jul, Aug 0.12(0.06)

18‡

0.96(0.34)

22‡

 Gobiidae

 Unidentified

 (goby)

Apr, May, Jun, Jul, Aug 0.03(0.01)

31‡

0.81(0.23)

25‡

 Bathygobius soporator

 (frillfin goby)

Jun, Jul 0 (0) 0.01(<0.01)

76‡

 Evorthodus

lyricus/Gobionellus

boleosoma

 (lyre goby/darter goby)

Jun, Jul, Aug 0 (0) 0.01(<0.01)

78‡

 Gobionellus oceanicus

 (highfin goby)

Apr, May, Jun, Jul, Aug 0.11(0.06)

20‡

8.82(2.13)

6(1.97)

 Gobiosoma spp.

 (goby spp.)

Apr, May, Jun, Jul, Aug 0.26(0.18)

12‡

1.48(0.43)

17‡

 Gobiosoma bosc

 (naked goby)

Apr, May, Jun, Jul, Aug 0.59(0.16)

8‡

46.88(7.88)

3(10.64)

 Microgobius spp.

 (goby spp.)

May, Jun, Jul, Aug 0.04(0.03)

26‡

4.17(1.30)

9(1.05)

 Microdesmidae

 Microdesmus longipinnis

 (pink wormfish)

Jun, Jul, Aug 0.05(0.02)

24‡

0.14(0.04)

43‡
Table 5.9. (continued)

233

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 Trichiuridae

 Unidentified

 (snake mackerel)

May 0 (0) <0.01(<0.01)

91‡

 Trichiurus lepturus

 (Atlantic cutlassfish)

Apr, Jul 0 (0) 0.01(<0.01)

79‡

 Scombridae

 Unidentified

 (mackerel)

May, Jun 0 (0) 0.01(<0.01)

73‡

 Scomberomorus spp.

 (mackeral spp.)

Aug <0.01(<0.01)

48‡

0 (0)

 Scomberomorus maculatus

 (Spanish mackeral)

May, Aug 0 (0) <0.01(<0.01)

83‡

 Stromateidae

 Peprilus alepidotus

 (harvestfish)

Jun, Jul, Aug 0 (0) 0.01(<0.01)

75‡

 Peprilus burti

 (gulf butterfish)

Apr 0 (0) <0.01(<0.01)

85‡

Pleuronectiformes

 Bothidae

 Unidentified

 (lefteye flounder)

Apr, Jun 0 (0) 0.02(0.01)

65‡

 Citharichthys spp.

 (whiff/sanddab spp.)

Apr, May, Jun, Jul, Aug 0.08(0.03)

21‡

6.53(1.02)

7(1.49)

 Citharichthys spilopterus

 (bay whiff)

Jul 0 (0) <0.01(<0.01)

81‡

 Etropus crossotus

 (fringed flounder)

Jul 0 (0) <0.01(<0.01)

104‡

 Soleidae

 Achirus lineatus

 (lined sole)

Jun 0 (0) <0.01(<0.01)

84‡

 Trinectes maculatus

 (hogchoker)

May, Jun, Jul, Aug 0 (0) 0.07(0.02)

50‡

 Cynoglossidae

 Symphurus spp.

 (tonguefish spp.)

Apr, May, Jun, Jul, Aug 0.05(0.02)

25‡

5.66(0.89)

8(1.27)

 Symphurus plagiusa

 (blackcheek tonguefish)

Jul 0 (0) <0.01(<0.01)

106‡

Tetraodontiformes

 Balistidae

 Monacanthus hispidus

 (planehead filefish)

Jun 0 (0) <0.01(<0.01)

110‡
Table 5.9. (continued)

234

Taxa Months Collected Light-trap Pushnet

CPUE (SE)

Rank (%)

Density (SE)

Rank (%)

 Tetraodontidae

 Unidentified

 (puffer)

May, Jun 0 (0) 0.05(0.02)

53‡

 Sphoeroides spp.

 (puffer spp.)

Apr, May, Jun, Aug 0.01(<0.01)

38‡

0.12(0.04)

45‡

 Sphoeroides parvus

 (least puffer)

Apr, May, Jun, Jul, Aug 0.17(0.06)

14‡

0.34(0.08)

34‡

dominated the total catch for both gear types, particularly the plankton nets where these fishes

comprised 65% and 71% of the total numerical catch for subsurface and surface plankton net

collections, respectively. Gobies, scarids, and Mugil cephalus were among the most common nonclupeiform fishes in the plankton net collections. While the subsurface light-trap collections were

also dominated by clupeiforms (72%), other coastal pelagic taxa such as Caranx crysos, C.

hippos/latus, Euthynnus alletteratus, and Auxis spp. were common in the surface and off-platform

light-trap collections. 

At GI 94, a total of 45,754 fish were collected with light-traps collecting 31,353 fish and plankton

nets collecting 14,401 fish. The total mean plankton net density was 69.6 fish/100 m3 and the total

mean light-trap CPUE was 26.2 fish/10 min. Plankton nets collected individuals from 40 different

families, six of which were not collected by light-traps (Table 5.7). Light-traps sampled fish from

37 families, only three of which were not sampled by plankton nets. Plankton nets collected fish

from 83 taxa (identified at least to the level of genus), 26 of which were not collected in light-traps,

while light-traps collected fish from 90 taxa, 31 of which were not sampled with plankton nets.

Clupeiforms dominated the total catch (66%). The most common taxa collected included Anchoa

spp., A. nasuta, Engraulis eurystole, and Opisthonema oglinum. Among the most common nonclupeiform fishes were synodontids (primarily Synodus foetens and S. poeyi), blenniids

(Hypsoblennius invemar and Parablennius marmoreus), and scombrids (Auxis spp. and Euthynnus

alletteratus).

At ST 54, a total of 97,697 fish were collected, with light-traps collecting 6,116 fish and plankton

nets collecting 91,583 fish (Table 5.8). Total mean plankton net density was 166.0 fish/100 m3 and

total mean light-trap CPUE was 0.6 fish/10 min. Due to problems with deploying the subsurface net

at this site (Table 5.5), the plankton net catch is almost exclusively from the surface. The plankton

nets collected fish from 34 families, eight of which were unique. Light-traps also collected fish from

a total of 34 families, eight of which were not collected with plankton nets. The plankton nets caught

fish from 59 taxa (identified to genus), 19 of which were unique. Light-traps caught fish from 65

taxa, 27 of which were not in plankton net collections. Overall, clupeiforms, primarily clupeids,

dominated the collections at ST 54, comprising 97% of the total catch for both gear types combined.

The only gear and location not dominated by clupeiforms was the subsurface light-traps, in which
235

Synodus foetens was the most common taxon. Of the non-clupeiform fishes collected, sciaenids,

synodontids, carangids, and scombrids were dominant.

At the Belle Pass jetties, the light-trap and pushnet collected 17,949 fish and 111,854 fish,

respectively, with a total mean pushnet density of 136.7 fish/100 m3 and a total light-trap CPUE of

4.6 fish/10 min. Catches by both gear types were dominated by clupeiform fishes that comprised

95.3% of the light-trap total catch and 68.3% of the total pushnet catch (Table 5.9). The pushnet

collected fish from 41 families with 85 taxa identifiable to at least genus. Non-clupeiform taxa

collected by the pushnet that comprised over 1% of the total catch included Gobiosoma bosc,

Cynoscion arenarius, Gobionellus oceanicus, Citharichthys spp., Symphurus spp., and Microgobius

spp. Overall, the light-trap collected fish from 21 families with 42 taxa identifiable to at least the

genus level. Only one non-clupeiform species, Membras martinica, comprised over 1% of the total

light-trap catch. The pushnet collected fish from 20 families and 44 taxa unique to this gear type.

All families and all but three taxa that were sampled with the light-trap were also collected by the

pushnet.

Reef-dependent and reef-associated fish (Choat and Bellwood 1991) made up a relatively small

percentage of the total plankton net and light-trap collections (with clupeiforms removed from the

total catch) at the three platforms (Table 5.10). At GC 18, these groups of fish comprised 18% and

32% of the plankton net and light-trap collections, respectively. Dominant groups included gobiids,

scombrids, and carangids. At GI 94, reef-dependent and reef-associated fishes comprised 10% of

the plankton net catch and 17% of the light-trap catch. Blenniids were prominent in both plankton

net and light-trap collections, as well as gobiids (plankton nets) and scombrids (light-traps). At

ST54, these fishes comprised less than 1% of the plankton net collections and only 8% of the lighttrap collections. Carangids (particularly Chloroscombrus chrysurus), gobiids, and scombrids

dominated plankton net collections, while scombrids and blenniids dominated light-trap collections.

At Belle Pass, reef-dependent and reef-associated fishes comprised approximately 15% and 2% of

pushnet and light-trap collections. Samples by both gears were dominated by gobiids and blenniids,

particularly Gobiosoma bosc and Hypsoblennius hentz/ionthas.

In general, trends in seasonality were consistent for taxa collected at the different sites across the

shelf (Tables 5.6–5.9). Many groups (e.g., clupeiforms, carangids, and scombrids) were present

throughout the sampling periods for GI 94, ST 54, and the Belle Pass jetty, and throughout the

spring-summer at GC 18. At GC 18, the only site that included fall and winter sampling, few taxa

were represented solely during these months, including Etremeus teres (January-February),

Diplophos taenia (November) and Mugil cephalus (October-November and January-February),

among others. 

Similarity and Diversity of Ichthyoplankton Assemblages

Schoener’s Index of Niche Overlap values range from 0 (no similarity) to 1 (identical taxonomic

compositions). Of the 14 comparisons between the six sites (i.e., the three platforms and jetty along

the transect and the two pilot studies), the Belle Pass jetty, with values ranging from 0.01-0.07, and

WC 352 (inner shelf), with values ranging from 0.01-0.16, differed the most from the other sites

(Table 5.11). Inexplicably, from the geographical or depth points of view, the most similar sites
236

Table 5.10. Total plankton net density (fish/100m3), pushnet density (fish/100m3), and light-trap

CPUE (fish/10 min) for reef-dependent (RD) and reef-associated (RA) families of

fish collected at each site with standard error (SE). Densities calculated for the

platforms include both surface and subsurface samples. CPUEs calculated for the

platforms include surface, subsurface, and offplatform samples. † indicates a value

<0.01.

Green Canyon Grand Isle South Timbalier Belle Pass

Taxa Ecology Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Pushnet

density

(SE)

Light-trap

CPUE

(SE)

Anguilliformes

 Muraenidae RA

 Unidentified

 (moray eel)

0.01

0.01

0.02

0.01

0.25

0.12

†

†

0.40

0.38

0.01

0.01

Beryciformes RA

 Holocentridae

 Holocentrus spp.

 (squirrelfish spp.)

0.12

0.07

0.06

0.02

0.09

0.04

0.01

†

Perciformes

 Serranidae RA

 Unidentified

 (seabass/grouper)

0.75

0.43

0.12

0.07

0.05

0.05

 Anthinae

 (sea perch)

0.43

0.15

0.01

0.01

0.25

0.12

†

†

 Epinephelinae

 (grouper)

0.35

0.16

†

†

0.03

0.02

0.01

†

0.03

0.03

†

†

 Grammistinae 0.05

0.03

0.03

0.02

 Serraninae

 (sea bass)

0.65

0.18

0.03

0.01

0.31

0.22

0.01

0.01

 Priacanthidae RA

 Unidentified

 (bigeye)

0.09

0.06

†

†

 Priacanthus spp. 

 (bigeye/glasseye spp.)

0.02

0.02

0.01

0.01

 Apogonidae

 Unidentified

 (cardinalfish)

RA 0.01

0.01

 Apogon spp.

 (cardinalfish spp.)

0.01

0.01

 Rachycentridae RA

 Rachycentron canadum

 (cobia)

0.08

0.04

†

†
Table 5.10 (continued)

237

Green Canyon Grand Isle South Timbalier Belle Pass

Taxa Ecology Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Pushnet

density

(SE)

Light-trap

CPUE

(SE)

 Carangidae RA

 Unidentified

 (jack)

0.35

0.19

0.10

0.06

†

†

0.40

0.26

0.02

0.02

 Caranx spp.

 (jack spp.)

0.02

0.02

†

†

0.08

0.05

0.64

0.26

 Caranx crysos

 (blue runner)

2.03

0.89

0.17

0.04

0.89

0.30

0.07

0.02

0.11

0.03

 Caranx hippos/latus

 (crevalle/horse-eye

jack)

2.72

0.69

0.09

0.02

0.26

0.16

0.07

0.02

2.49

2.25

0.21

0.08

0.09

0.04

†

†

 Chloroscombrus

chrysurus

 (Atlantic bumper)

0.38

0.16

0.01

0.01

0.65

0.20

0.01

0.01

27.64

10.19

0.08

0.03

0.28

0.15

0.05

0.02

 Decapterus punctatus

 (round scad)

0.02

0.02

0.01

†

0.02

0.01

0.02

0.02

0.02

0.01

 Elagatis bipinjulata

 (rainbow runner)

0.13

0.08

†

†

 Oligoplites saurus

 (leatherjack)

0.08

0.06

0.45

0.34

0.02

†

†

†

 Selar

crumenopthalmus

 (bigeye scad)

0.07

0.06

0.23

0.10

0.01

0.01

 Selene spp.

 (moonfish/lookdown

spp.)

0.56

0.56

 Selene vomer

 (lookdown)

0.16

0.16

0.03

0.02

†

†

 Selene setapinnis

 (Atlantic moonfish)

†

†

 Seriola spp. 

 (jack spp.)

0.22

0.12

†

†

0.02

0.02

†

†

 Seriola

dumerili/rivoliana

 (greater

amberjack/almaco jack)

0.01

†

 Seriola fasciata

 (lesser amberjack)

†

†

 Trachinotus carolinus

 (Florida pompano)

†

†

0.01

0.01

 Trachinotus

falcatus/goodei

 (permit/palometa)

0.01

0.01

 Trachurus lathami 0.14 0.01 0.09 0.03 0.02 0.04
Table 5.10 (continued)

238

Green Canyon Grand Isle South Timbalier Belle Pass

Taxa Ecology Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Pushnet

density

(SE)

Light-trap

CPUE

(SE)

 (rough scad) 0.08 0.01 0.05 0.01 0.02 0.02

 Lutjanidae RA

 Unidentified

 (snapper)

0.03

0.03

†

†

0.08

0.04

†

†

0.16

0.16

 Lutjanus spp.

 (snapper spp.)

0.15

0.09

†

†

0.35

0.12

0.01

0.01

0.56

0.42

†

†

 Lutjanus griseus

 (gray snapper)

0.03

0.01

 Lutjanus synagris

 (lane snapper)

0.07

0.02

0.01

†

 Lutjanus

apodus/vivanus

 (schoolmaster/silk

snapper)

0.01

†

 Lutjanus campechanus

 (red snapper)

0.01

0.01

0.01

0.01

0.01

0.01

0.56

0.56

0.01

0.01

 Pristipomoides

aquilonaris

 (wenchman)

1.25

0.56

 Rhomboplites

aurorubens

 (vermilion snapper)

0.03

0.03

0.39

0.17

0.09

0.02

0.03

0.02

 Haemulidae RA

 Unidentified

 (grunt)

0.56

0.56

†

†

 Sparidae RA

 Unidentified

 (porgy)

0.02

0.02

0.02

0.02

0.01

†

0.13

0.13

0.02

0.01

 Sparidae Type B

 (porgy sp.)

0.02

0.01

 Calamus spp. 

 (porgy spp.)

†

†

0.09

0.09

 Lagodon rhomboides

 (pinfish)

0.24

0.16

 Mullidae RA

 Unidentified

 (goatfish)

†

†

0.13

0.07

0.02

0.01

†

†

 Mullus auratus

 (red goatfish)

†

†

0.02

0.01

 Pseudupeneus

maculatus

0.02

0.01
Table 5.10 (continued)

239

Green Canyon Grand Isle South Timbalier Belle Pass

Taxa Ecology Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Pushnet

density

(SE)

Light-trap

CPUE

(SE)

 (spotted goatfish)

 Upeneus parvus

 (dwarf goatfish)

0.13

0.03

0.01

0.01

 Ephippidae RA

 Chaetodipterus faber

 (Atlantic spadefish)

0.03

0.02

0.79

0.36

0.05

0.02

 Chaetodontidae RD

 Unidentified

 (butterflyfish)

0.02

0.02

0.01

0.01

 Pomacentridae RD

 Unidentified

 (damselfish)

0.01

0.01

 Abudefduf saxatilis

 (sergeant major)

0.01

0.01

0.03

0.02

 Abudefduf taurus

 (night sergeant)

†

†

 Chromis spp.

 (chromis spp.)

0.15

0.15

0.15

0.04

 Pomacentrus spp.

 (damselfish spp.)

0.07

0.03

0.06

0.03

0.17

0.05

0.01

0.01

 Sphyraenidae RA

 Sphyraena borealis

 (northern sennet)

†

†

0.01

0.01

 Sphyraena guachancho

 (guaguanche)

0.32

0.27

0.01

0.01

0.94

0.31

0.01

†

 Labridae RD

 Unidentified

 (wrasse)

0.10

0.08

†

†

0.01

0.01

0.01

†

 Scaridae RD

 Unidentified

 (parrotfish)

7.33

2.11

0.03

0.01

0.02

0.02

 Sparisoma spp.

 (parrotfish spp.)

0.01

†

 Opisthognathidae RA

 Unidentified

 (jawfish)

0.47

0.17

0.23

0.07

 Opisthognathus spp.

 (jawfish spp.)

0.03

0.03

 Opisthognathus 0.03 0.01
Table 5.10 (continued)

240

Green Canyon Grand Isle South Timbalier Belle Pass

Taxa Ecology Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Pushnet

density

(SE)

Light-trap

CPUE

(SE)

aurifrons

 (yellowhead jawfish)

0.03 0.01

 Opisthognathus

lonchurus

 (moustache jawfish)

0.05

0.05

 Blenniidae RA

 Unidentified

 (blenny)

0.55

0.34

0.08

0.05

3.02

2.05

0.26

0.07

2.36

0.83

0.07

0.02

0.03

0.02

0.02

0.01

 Chasmodes spp.

 (striped/Florida

blenny)

†

†

 Hypleuorchilus

bermudensis

 (barred blenny)

†

†

 Hypsoblennius spp.

 (blenny spp.)

†

†

 Hypsoblennius

hentz/ionthas

 (feather/freckled

blenny)

0.61

0.19

 0.16

0.16

0.25

0.08

1.95

0.45

1.04

0.27

 Hypsoblennius invemar

 (tessellated blenny)

0.03

0.03

†

†

0.02

0.02

3.35

0.64

0.56

0.56

0.20

0.07

 Ophioblennius

atlanticus

 (redlip blenny)

0.44

0.32

0.01

†

0.22

0.22

 Parablennius

marmoreus

 (seaweed blenny)

0.01

0.01

3.01

0.40

0.19

0.19

0.01

0.01

 Scartella cristata

 (molly miller)

0.34

0.08

0.03

0.02

 

Scartella/Hypleurochilus

 (blenny spp.)

0.14

0.08

0.42

0.08

1.74

1.18

0.28

0.12

 Gobiidae RA

 Unidentified

 (goby) 

6.73

1.75

0.20

0.14

8.18

0.96

0.09

0.02

27.7

11.7

0.10

0.03

0.81

0.23

0.03

0.01

 Bathygobius soporator

 (frillfin goby)

0.01

†

 Evorthodus

lyricus/Gobionellus

 boleosoma

 (lyre goby/darter goby)

0.01

†

 Bollmannia communis

 (ragged goby)

†

†
Table 5.10 (continued)

241

Green Canyon Grand Isle South Timbalier Belle Pass

Taxa Ecology Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Plankton net

density

(SE)

Light-trap

CPUE

(SE)

Pushnet

density

(SE)

Light-trap

CPUE

(SE)

 Gobionellus oceanicus

 (highfin goby)

0.01

0.01

†

†

 Gobiosoma spp.

 (goby spp.)

1.48

0.43

0.26

0.18

 Gobiosoma bosc

 (naked goby)

46.88

7.88

0.59

0.16

 Microgobius spp.

 (goby spp.)

4.17

1.30

0.04

0.03

 Scombridae RA

 Unidentified

 (mackerel)

1.42

0.72

0.01

0.01

0.26

0.15

0.05

0.03

0.23

0.17

0.01

†

 Acanthocybium

solandri

 (wahoo)

0.03

0.03

 Auxis spp.

 (mackerel spp.)

1.26

0.33

0.19

0.05

4.00

1.25

0.34

0.07

0.09

0.05

 Euthynnus alletteratus

 (little tunny)

0.47

0.17

0.07

0.02

4.33

0.74

1.29

0.23

0.43

0.25

0.51

0.18

 Katsuwonus pelamis

 (skipjack tuna)

0.03

0.02

0.03

0.01

 Scomber japonicus

 (chub mackeral)

0.01

0.01

 Scomberomorus spp.

 (mackerel spp.)

0.01

†

 Scomberomorus

cavalla

 (king mackerel)

0.06

0.05

0.02

0.01

0.10

0.04

0.13

0.04

4.97

2.91

0.06

0.02

 Scomberomorus

maculatus

 (Spanish mackerel)

0.51

0.28

0.01

†

0.28

0.12

0.07

0.02

6.05

1.94

0.33

0.07

†

†

 Thunnus spp.

 (tuna spp.)

0.07

0.07

0.01

0.01

†

†

 Thunnus thynnus

 (bluefin tuna)

0.11

0.07

†

†

Tetraodontiformes

 Balistidae RA

 Unidentified

 (leatherjacket)

0.01

0.01

†

†

 Monacanthus hispidus

 (planehead filefish)

†

†
242

Table 5.11. Schoener's Index of Niche Overlap for all sampling sites. Values range from 0-1 and

include taxa (at least to the level of genus) from all gears used at each site. Values

in parentheses represent indices calculated with the most dominant taxa removed

from each site. (BP) Belle Pass, (ST) South Timbalier, (GI) Grand Isle, (GC) Green

Canyon, (WC71D) West Cameron 71D, (WC352) West Cameron 352

GC 18 GI 94 ST 54 BP WC 71D WC 352

GC 18 1 . . . . .

GI 94 0.32 (0.29)a 1. . . .

ST 54 0.53 (0.35)a 0.15 (0.45) 1 . . .

BP 0.07 (0.15)a 0.07 (0.09) 0.02 (0.25) 1 . .

WC 71D 0.52 (0.31)b 0.32 (0.29)b 0.17 (0.17)b 0.01 (0.06)b 1 .

WC 352 0.06 (0.13)d 0.16 (0.06)c 0.01 (0.12)c 0.03 (0.04)c ‡ 1

a

 indices computed with April-August samples only

b

 indices calculated with July samples only

c

 indices calculated with April, May and August samples only

d

 index calculated with November, February, April, May and August samples only

‡ no seasonal overlap in sampling efforts between WC 352 and WC 71D

(0.53) were GC 18 (shelf slope) and ST 54 (inner shelf) followed by GC 18 and WC 71D (inner

shelf/coastal) with a comparative value of 0.52. These relative similarities in taxonomic

compositions changed when the single, dominant taxon from each site were removed from

theanalyses. In many cases, the similarity indices were more reasonable for adjacent sites: GI 94

(mid-shelf) and ST 54 (0.45); GI 94 and GC 18 (0.29); and ST 54 and Belle Pass jetty (0.25). In

other instances, although similarities were dramatically reduced, the values were still relatively high

for sites that were distant from each other or represented large depth differences: ST 54 and GC 18

(0.35); WC 71D and GC 18 (0.31); and WC 71D and GI 94 (0.29). 

The diversity data, however, were much more similar along the transect of the three platforms and

the jetty. There was no significant difference in the diversity of the net samples (passive plankton

net or pushnet) between the sites (platforms or Belle Pass; "=0.05; Figure 5.3). The light-trap

samples at GC 18 had significantly lower mean Shannon-Weiner diversity index values, while GI

94 had significantly higher mean diversity values than the other locations (Tukey’s Studentized

Range test, "=0.05; Figure 5.3). The diversity of light-trap collections at the two more coastal sites,

ST 54 and Belle Pass, were intermediate and not significantly different from one another.

Environmental Variables and Larval Abundances

At GC 18, salinity and temperature were the most useful environmental parameters measured in

describing trends in larval and juvenile fish abundances. For plankton net collections, densities of

Cynoscion arenarius, Scomberomorus maculatus, and Symphurus spp. were negatively associated

with the first environmental canonical variate, which was primarily influenced by salinity (Table

5.12). Densities of Auxis spp., Caranx crysos, C. hippos/latus, Pristipomoides aquilonaris, and
243

Figure 5.3. Mean Shannon-Weiner diversity indices (with standard error bars) for plankton net

(GC 18, GI 94, and ST 54) or pushnet (Belle Pass) collections (upper panel) and

light-trap collections (lower panel) from each sampling site. The same letter above

each bar indicates no significant difference between the sites based on Tukey’s

Studentized Range ("=0.05). Different letters indicate significant differences.
244

Table 5.12. Results of a canonical correlation analysis on log-transformed plankton net densities

(15 most dominant taxa) and environmental variables for Green Canyon 18.

Loadings in bold under statistically significant canonical variates V1 and V2 explain

at least 15% of the variation (interset correlation of 0.387) for that taxon. Loadings

in bold under the environmental canonical variates W1 and W2 indicate the most

influential environmental variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.750369 0.26739839 2.8134 0.0001

2 0.502430 0.61197053 1.3766 0.0680

Taxa Correlations between plankton net densities and their

canonical variates

V1 V2

Ariomma spp. 0.1426 -0.0114

Auxis spp. 0.0857 0.5186

Bregmaceros cantori 0.1748 -0.1150

Caranx crysos 0.2340 0.6215

Caranx hippos/latus 0.1016 0.6166

Citharichthys spilopterus 0.1724 -0.4127

Cyclothone braueri 0.1817 -0.1283

Cynoscion arenarius -0.7049 0.1691

Lepophidium spp. 0.0850 0.0303

Mugil cephalus 0.2068 -0.4356

Peprilus burti 0.1115 -0.2048

Pristipomoides aquilonaris 0.1901 0.4764

Sciaenops ocellatus 0.0597 0.4175

Scomberomorus maculatus -0.7415 0.0507

Symphurus spp. -0.7149 -0.0638

Environmental Variables Correlations between environmental variables and

their canonical variates

W1 W2

Zooplankton Biomass -0.3742 0.1562

Suspended Solids 0.0640 -0.2760

Salinity 0.9829 -0.1659

Temperature -0.5120 0.8549
245

Sciaenops ocellatus were positively associated with the second environmental canonical variate,

which was marginally significant (p=0.068) and primarily influenced by temperature. Densities of

Citharichthys spilopterus and Mugil cephalus were negatively associated with the second

environmental variate. For the dominant taxa collected with light-traps, six taxa, primarily benthic species

such as Saurida brasiliensis, Microdesmus longipinnis, Syacium spp., and Symphurus spp., were

positively associated with the first environmental variate, which was negatively correlated with salinity

and positively correlated with macrozooplankton biomass (Table 5.13). Five taxa, comprised mostly of

pelagic taxa (i.e., Auxis spp., C. crysos, C. hippos/latus, and Eucinostomus spp.) were positively

associated with the second environmental variate, which was primarily explained by temperature.

At GI 94, temperature contributed substantially to our model in describing trends in larval and juvenile

fish abundances. For plankton net collections, densities of Euthynnus alletteratus and Symphurus spp.

were positively associated with the first environmental variate, which was positively correlated with

temperature and negatively correlated with salinity, while Synodus foetens was inversely correlated with

this variate (Table 5.14). The second environmental variate was explained primarily by salinity, and was

positively associated with the scombrids Auxis spp. and E. alletteratus. For dominant taxa collected with

light-traps, abundances of the blenny Parablennius marmoreus and the lizardfishes S. foetens and S. poeyi

were positively associated with the first environmental variate, which was positively correlated with

salinity and negatively correlated with temperature (Table 5.15). A third lizardfish species, Saurida

brasiliensis, and E. alletteratus were negatively associated with the first environmental variate. Synodus

foetens was also negatively associated with the second environmental variate, which was correlated with

low macrozooplankton biomass. The third environmental canonical variate was only marginally

significant (p=0.067) and was positively correlated with macrozooplankton biomass. Abundances of

Caranx crysos, Pomacentrus spp., S. foetens, and S. poeyi were positively associated with this

environmental variate.

At ST 54, the seasonal variables temperature and salinity were again the most correlated with the

environmental canonical variates. For plankton net collections, densities of the pelagic species

Chloroscombrus chrysurus and Scomberomorus maculatus were positively associated with the first

environmental variate, which were marginally significant (p=0.0552) and positively influenced by

salinity and temperature (Table 5.16). Bregmaceros cantori and Etropus crossotus were negatively

associated with the first environmental variate. For light-trap collections, abundances of the carangids

Caranx crysos and C. chrysurus were positively associated with the first environmental variate, which

was positively correlated with temperature and salinity (Table 5.17). Cynoscion arenarius and S.

maculatus were negatively associated with the first environmental variate. A second environmental

canonical variate was marginally significant (p=0.0708) and was also influenced by salinity. Abundances

of Cynoscion arenarius were positively associated with the second environmental variate and Saurida

brasiliensis was negatively associated with the second environmental variate. 

At Belle Pass, temperature and salinity, were still influential environmental variable, but turbidity and

dissolved oxygen were also important in our models. For pushnet collections, three common coastal taxa

(Dormitator maculatus, Gobiesox strumosus, and Hypsoblennius hentz/ionthas) were negatively

associated with the first canonical variate, which was explained primarily by temperature (Table 5.18).

A second environmental variate was positively correlated with dissolved oxygen and negatively

correlated with turbidity. Abundances of Citharichthys spp., Cynoscionarenarius, Cynoscion nebulosus,
246

Table 5.13. Results of a canonical correlation analysis on log-transformed light-trap CPUEs (18

most dominant taxa) and environmental variables for Green Canyon 18. Loadings

in bold under statistically significant canonical variates V1 and V2 explain at least

15% of the variation for that taxon. Loadings in bold under the environmental

canonical variates W1 and W2 indicate the most influential environmental variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.566445 0.50304207 3.1136 0.0001

2 0.413382 0.74070398 1.8532 0.0004

Taxa Correlations between light-trap CPUEs and their

canonical variates

V1 V2

Auxis spp. -0.3640 0.5669

Bregmaceros cantori -0.0579 -0.0234

Caranx crysos -0.1666 0.6483

Caranx hippos/latus -0.1349 0.3970

Cyclothone braueri 0.2205 0.1095

Cynoscion arenarius 0.2667 0.1967

Eucinostomus spp. -0.1460 0.3976

Euthynnus alletteratus 0.4647 0.3416

Gobiesox strumosus 0.1569 0.0549

Holocentrus spp. -0.3507 0.4954

Microdesmus longipinnis 0.3868 0.1855

Mugil cephalus -0.1229 -0.3138

Peprilus burti -0.1153 -0.0422

Pomacentrus spp. 0.5047 0.2425

Saurida brasiliensis 0.4637 0.2239

Syacium spp. 0.4087 0.2510

Symphurus spp. 0.5289 0.2751

Trachinocephalus myops -0.2060 0.2437

Environmental Variables Correlations between environmental variables

and their canonical variates

W1 W2

Zooplankton Biomass 0.5991 0.3731

Suspended Solids -0.1026 -0.2868

Salinity -0.8725 -0.4174

Temperature 0.3657 0.9057
247

Table 5.14. Results of a canonical correlation analysis on log-transformed plankton net densities

(15 most dominant taxa) and environmental variables for Grand Isle 94. Loadings

in bold under statistically significant canonical variates V1 and V2 explain at least

15% of the variation for that taxon. Loadings in bold under the environmental

variates W1 and W2 indicate the most influential physical variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.588892 0.50402811 3.8641 0.0001

2 0.406611 0.77162236 2.0014 0.0002

Taxa Correlations between plankton net densities

and their canonical variates

V1 V2

Auxis spp. 0.0642 0.5517

Bregmaceros cantori 0.0074 0.0583

Caranx crysos 0.3272 0.0475

Chloroscombrus chrysurus 0.3167 -0.2754

Cynoscion arenarius 0.2667 -0.1755

Etropus crossotus -0.1902 0.1164

Euthynnus alletteratus 0.5109 0.5440

Microdesmus lanceolatus -0.1983 0.3366

Peprilus paru 0.2351 0.0501

Saurida brasiliensis 0.1278 0.0595

Sphraena guachancho 0.3473 0.1880

Syacium spp. 0.2955 -0.0865

Symphurus spp. 0.7408 -0.1918

Synodus foetens -0.5515 -0.3527

Synodus poeyi -0.1838 0.0322

Environmental Variables Correlations between environmental variables

and their canonical variates

W1 W2

Zooplankton Biomass 0.0176 -0.3841

Suspended Solids -0.2643 0.0480

Salinity -0.7272 0.6783

Temperature 0.9987 0.0063
248

Table 5.15. Results of a canonical correlation analysis on log-transformed light-trap CPUEs (16

most dominant taxa) and environmental variables for Grand Isle 94. Loadings in

bold under statistically significant canonical variates V1, V2, and V3 explain at least

15% of the variation for that taxon. Loadings in bold under environmental variates

W1, W2, and W3 indicate the most influential environmental variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.727366 0.36024110 8.2854 0.0001

2 0.407126 0.76494371 2.8369 0.0001

3 0.250076 0.91692543 1.4435 0.0647

Taxa Correlations between light-trap CPUEs and their canonical variates

V1 V2 V3

Auxis spp. 0.3411 0.3626 0.0228

Bregmaceros cantori -0.1958 -0.0774 -0.0539

Caranx crysos -0.2602 -0.0894 0.4223

Caranx hippos/latus 0.3000 -0.2098 -0.1797

Chromis spp. 0.1613 0.3585 0.2160

Euthynnus alletteratus -0.4596 -0.0891 0.2976

Hypsoblennius hentz/ionthas 0.2219 0.2988 0.3527

Hypsoblennius invemar 0.2575 0.2320 0.2696

Parablennius marmoreus 0.7294 0.0392 0.1578

Pomacentrus spp. -0.0228 0.3720 0.4550

Rhomboplites aurorubens -0.1795 0.0404 0.1092

Saurida brasiliensis -0.4268 -0.3509 0.0881

Scartella/Hypleurochilus 0.3028 0.2477 0.1846

Symphurus spp. -0.2566 0.0372 0.1930

Synodus foetens 0.4688 -0.5865 0.4341

Synodus poeyi 0.4316 0.0227 0.5475

Environmental Variables Correlations between environmental variables and their canonical variates

W1 W2 W3

Zooplankton Biomass -0.2046 -0.5927 0.7534

Suspended Solids 0.2965 0.0269 0.1712

Salinity 0.8998 0.3507 0.2520

Temperature -0.9412 0.3281 -0.0758
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Table 5.16. Results of a canonical correlation analysis on log-transformed plankton net densities

(15 most dominant taxa) and environmental variables for South Timbalier 54.

Loadings in bold under the statistically significant canonical variate V1 explain at

least 15% of the variation for that taxon. Loadings in bold under environmental

variate W1 indicate the most influential environmental variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.695653 0.29159946 1.3663 0.0552

Taxa Correlations between plankton net densities

and their canonical variates

V1

Bregmaceros cantori -0.4343

Caranx hippos/latus 0.0448

Chaetodipterus faber -0.2547

Chloroscombrus chrysurus 0.7188

Cynoscion arenarius 0.3017

Etropus crossotus -0.5026

Menticirrhus spp. -0.1820

Microdesmus lanceolatus 0.2774

Ophidion nocomis/selenops -0.2217

Peprilus burti -0.1917

Peprilus paru 0.3096

Scartella/Hypleurochilus -0.1934

Scomberomorus cavalla 0.1881

Scomberomorus maculatus 0.4750

Symphurus spp. -0.0072

Environmental Variables Correlations between environmental variables

and their canonical variates

W1

Zooplankton Biomass 0.1809

Suspended Solids 0.4344

Salinity 0.9623

Temperature 0.7410
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Table 5.17. Results of a canonical correlation analysis on log-transformed light-trap CPUEs (16

most dominant taxa) and environmental variables for South Timbalier 54. Loadings

under statistically significant canonical variates V1 and V2 explain at least 15% of

the variation for that taxon. Loadings in bold under environmental canonical variates

W1 and W2 indicate the most influential environmental variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.667016 0.38618143 2.6350 0.0001

2 0.472763 0.69571078 1.3486 0.0708

Taxa Correlations between light-trap CPUEs and

their canonical variates

V1 V2

Caranx crysos 0.4844 0.1927

Chloroscombrus chrysurus 0.3888 0.3043

Cynoscion arenarius -0.4716 0.4499

Etropus crossotus -0.1215 -0.2264

Euthynnus alletteratus 0.1801 0.0141

Gobiesox strumosus -0.3192 0.3644

Hypsoblennius hentz/ionthas -0.2699 0.0054

Hypsoblennius invemar -0.1376 -0.2595

Peprilus burti -0.3591 0.1883

Saurida brasiliensis -0.1630 -0.4101

Scartella/Hypleurochilus -0.1226 -0.1717

Scomberomorus cavalla 0.2114 -0.0868

Scomberomorus maculatus -0.4006 -0.1659

Sphoeroides parvus -0.0846 -0.1286

Synodus foetens -0.3693 -0.2336

Trachinocephalus myops -0.1217 -0.1479

Environmental Variables Correlations between environmental variables

and their canonical variates

W1 W2

Zooplankton Biomass 0.3169 0.1424

Suspended Solids 0.2328 -0.2829

Salinity 0.7209 0.6438

Temperature 0.9880 -0.1033
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Table 5.18. Results of a canonical correlation analysis on log-transformed pushnet densities (15

most dominant taxa) and environmental variables for Belle Pass jetty. Loadings in

bold under the statistically significant canonical variates V1, V2, and V3 explain at

least 15% of the variation for that taxon. Loadings in bold under environmental

variates W1, W2, and W3 indicate the most influential environmental variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.746141 0.12473748 3.3677 0.0001

2 0.709788 0.28140077 2.6115 0.0001

3 0.553340 0.56711076 1.5750 0.0201

Taxa Correlations between pushnet densities and their canonical variates

V1 V2 V3

Bairdiella chrysoura -0.1343 0.3102 -0.1418

Citharichthys spp. -0.0063 0.6759 0.0738

Cynoscion arenarius 0.2336 0.7453 0.3118

Cynoscion nebulosus 0.1423 0.4605 0.1065

Dormitator maculatus -0.6133 0.2318 -0.2055

Gobiesox strumosus -0.7488 0.2128 -0.1829

Gobionellus oceanicus 0.2488 0.2903 0.0099

Gobiosoma bosc -0.3128 0.5788 0.0476

Gobiosoma spp. -0.2878 -0.1962 -0.4318

Hypsoblennius hentz/ionthas -0.3878 -0.1485 0.0130

Membras martinica -0.2631 -0.3167 0.7042

Microgobius spp. 0.2499 -0.3423 -0.2313

Sciaenops ocellatus 0.2969 0.3477 0.2035

Symphurus spp. -0.1966 0.2238 0.2620

Synodus foetens -0.1768 0.3649 -0.2772

Environmental Variables Correlations between environmental variables and their canonical variates

W1 W2 W3

Temperature 0.9097 0.1977 -0.1327

Salinity 0.0587 -0.0616 0.9812

Dissolved Oxygen -0.0430 0.8447 -0.5265

Turbidity 0.3061 -0.5865 -0.4929
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Table 5.19. Results of a canonical correlation analysis on log-transformed light-trap CPUEs (15

most dominant taxa) and environmental variables for Belle Pass jetty. Loadings in

bold under the statistically significant variate V1 explain at least 15% of the variation

for that taxon. Loadings in bold under environmental canonical variate W1 indicate

the most influential physical variables.

Canonical Correlation Likelihood Ratio Approximate F Pr > F

1 0.679900 0.33598275 1.56599 0.0032

Taxa Correlations between light-trap CPUEs and

their canonical variates

V1

Bairdiella chrysoura 0.2172

Chloroscombrus chrysurus 0.1320

Citharichthys spp. -0.1391

Cynoscion arenarius -0.2046

Dormitator maculatus -0.1928

Gobiesox strumosus -0.8280

Gobionellus oceanicus 0.1573

Gobiosoma bosc -0.1403

Gobiosoma spp. -0.1859

Hypsoblennius hentz/ionthas -0.6848

Membras martinica 0.2208

Microdesmus longipinnis 0.0841

Sphoeroides parvus -0.6076

Symphurus spp. 0.0819

Synodus foetens -0.0705

Environmental Variables Correlations between environmental variables

and their canonical variates

W1

Temperature 0.7618

Salinity 0.1838

Dissolved Oxygen -0.2384

Turbidity 0.4234
253

and Gobiosoma bosc were positively associated with the second canonical variate. Abundances of

Gobiosoma spp. were negatively associated with the third environmental variate, which was

positively correlated with salinity, while Membras martinica was positively associated with this

variate. For light-trap collections, three taxa (i. e., G. strumosus, H. hentz/ionthas, and Sphoeroides

parvus) were negatively associated with the first canonical variate, which was positively correlated

with temperature, and to a lesser extent, turbidity (Table 5.19).

DISCUSSION

Overall, reef-dependent taxa (e.g., chaetodontids, pomacentrids, labrids, and scarids) were relatively

rare (Table 5.10). Pomacentrids and chaetodontids were collected only at the shelf slope and midshelf sites, while labrids and scarids were also collected at the inshore sites. Our total of 67 families

collected at oil and gas platforms throughout the course of this study is comparable with previously

published surveys from the GOM (61 families, Ditty et al. 1988; 74 families, Richards et al. 1984),

but is generally less than surveys that included more tropical waters (85 families, McGowan 1985;

91 families, Limouzy-Paris et al. 1994; 96 families, Richards 1984; 100 families, Richards et al.

1993). While reef-dependent fish were uncommon, reef-associated fish (e.g., carangids, scombrids,

blenniids) were much more common and many times represented a significant component of the

community assemblage at each site.

Ichthyoplankton Community Assemblage at GC 18

The ichthyoplankton community at GC 18 (230 m depth on the shelf slope, Gallaway’s outer shelf

of > 60 m) was dominated by coastal pelagic species, particularly engraulids and clupeids which

accounted for 33% and 25% of the total catch by both gear types, respectively (Table 5.6).

Opisthonema oglinum was the dominant species in the mid-to-late summer months, while

unidentified engraulids peaked in November. Engraulis eurystole was also relatively common

throughout the summer and early fall. Another pelagic species, Mugil cephalus, was relatively

common in the fall-winter months and peaked in November. Larvae of M. cephalus are most

commonly found over the outer to mid-shelf (Ditty and Shaw 1996), so their presence at our outer

shelf sampling station is not surprising. Though the adults are common on the continental shelf and

coastally (Hoese and Moore 1977), M. cephalus was not collected at the mid- or inner-shelf

platforms. This is primarily a result of our shortened sampling efforts (April-August or September)

at the other platforms, which did not encompass their spawning season (October through March;

Leard et al. 1995), so its relative larval abundance at these platforms is unknown. The carangids

Caranx crysos and C. hippos/latus were relatively common, and though they are usually considered

pelagic species, they are often associated with platform structures (Table 5.4).

Some of the more abundant demersal taxa included the flatfish Citharichthys spilopterus, Symphurus

spp., and Syacium spp., as well as the sciaenid Sciaenops ocellatus and bregmacerotid Bregmaceros

cantori. While not unique to this site, the mesopelagic species, Cyclothone braueri, was common

in subsurface net collections, and myctophids were present in subsurface light-trap collections.

Though not abundant, other outer shelf species of note include Diplophos taenia, Chlorophthalamus

agassizi, Scopelarchoides spp., Paralepis atlantica, and Lestrolepis intermedia. While the adults
254

are seldom observed, the planktonic nature of the early life history stages of these mesopelagic taxa

made them a significant component of the outer shelf ichthyoplankton assemblage at GC 18.

The most dominant reef-associated fishes at GC 18 were unidentified gobiids. Second in abundance

were serranids, most of which were from the poorly known subfamily Anthiinae. Anthiine adults

are residents of rocky reefs on the outer shelf and are not usually found on shallow, inshore reefs

(Thresher 1984). Other serranids included Epinephelus spp. and Mycteroperca spp. Lutjanids were

also fairly common among the reef fish taxa, primarily Pristipomoides aquilonaris, one of the most

common residents of mid- and outer-shelf reefs (Hoese and Moore 1977). Other noteworthy taxa

included unidentified blennies, Holocentrus spp., (reef-associated) and Pomacentrus spp. (reefdependent).

The relatively low abundance of reef fish larvae and juveniles compared to pelagic species at our

outer platform site is in contrast to the adult community described by Gallaway (1981). However,

the studies cited in Gallaway’s (1981) synthesis were primarily visual surveys interested in adult

fishes associated with the natural and artificial structures, and not necessarily taxa in the surrounding

water column. Pelagic species, therefore, may have been underestimated in those previous studies.

Also, reef fish communities are limited, in part, by the supply of pelagic larvae, usually from

upstream sources rather than the resident populations (Sponaugle and Cowen 1996; Victor 1986).

Reefs and platforms located on the shelf slope would theoretically have significantly fewer upstream

sources of potential recruits than those on the mid-shelf, where other natural hard-bottom or reef

habitats may be more abundant, or where the density of platforms is orders of magnitude greater.

Therefore, the extremely remote location of GC 18 (shelf slope) is probably the limiting factor with

regards to the pool of available larvae to be sampled.

Ichthyoplankton Community Assemblage at GI 94

At GI 94 (60 m depth, Gallaway’s mid-shelf of 20-60 m), pelagic species dominated the catches as

well, but there appeared to be a taxonomic shift in dominance. Clupeiforms again dominated the

collections, but engraulids became more prominent in abundance (57%) than clupeids (9%).

Unidentified engraulids were the most abundant pelagic taxa in the plankton nets, and Engraulis

eurystole were very common in light-trap collections (Table 5.7). Opisthonema oglinum, which was

the most dominant clupeid at GC 18, ranked third in overall abundance. Caranx crysos and C.

hippos/latus were not as dominant at this site as they were at GC 18, but as a family, the carangids

had more species richness at GI 94. Oligoplites saurus, Seriola dumerili/rivoliana, S. fasciata,

Trachinotus carolinus, and T. falcatus/goodei were all present at GI 94, but absent at GC 18.

Similarly, Rachycentron canadum, although not very common, were also collected at GI 94 and not

at GC 18. As with the carangids, R. canadum is also considered to be a reef-associated species. 

Second in abundance to the pelagic forms at GI 94 were demersal taxa, particularly synodontids

which comprised 14.7% of the total catch and were approximately equal to the total catch of all

perciform fishes combined (15.1%). Unidentified synodontids, Saurida brasiliensis, Synodus

foetens, and Synodus poeyi were very common in the late spring and summer months. Like the

carangids, this group was more species rich at GI 94, with seven taxa identified to species as

compared to three at GC 18. Other common demersal taxa included Symphurus spp., Syacium spp.,
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and Bregmaceros cantori. Mesopelagic species were not as speciose and abundant as those at GC

18, but some were collected, including Cyclothone braueri, Vinciguerria nimbaria, and Lestrolepis

intermedia.

Overall, there was greater taxonomic richness among reef fish at GI 94 than GC 18. By far the most

dominant reef-associated fish taxa at GI 94 were blenniids, particularly Parablennius marmoreus

and Hypsoblennius invemar. These fishes are perhaps one of the most common taxa affiliated with

oil and gas platforms, but are probably underestimated in visual surveys due to their small size,

cryptic coloration, and tendency to hide in attached barnacle shells. Some blenniids have been found

to be rather unusual compared to other common reef-associated taxa in that they have demersal eggs

and pelagic, yet fairly competent larvae that appear to be able to feed immediately and are attracted

to light (Thresher 1984). If the same early life history attributes are true for the blennies collected

at our platform sites, then these traits may combine to form a mechanism by which these taxa are

retained and concentrated around platform structures. Other reef taxa that hatch from demersal eggs

and have demonstrated photopositive behavior include gobies and pomacentrids, although these

larvae are not as competent upon hatching (Thresher 1984). At GI 94, unidentified gobiids and

pomacentrids, primarily Chromis spp. and Pomacentrus spp., ranked next in abundance. Unique to

this site was the collection of opisthognathids in surface waters (plankton nets as well as surface and

off-platform light-traps) during the spring-early summer. Adult Opisthognathus aurifrons are

reported to be tropical (south Florida, Bahamas, northern South America) and rarely collected on

the mid-to-outer shelf (Hoese and Moore 1977; Robins et al. 1986). Adult O. lonchurus are also

reported to inhabit the northeast GOM as well as tropical waters (Robins et al. 1986). The presence

of these larvae reinforces the notion that oil and gas platforms may play a role in extending the

ranges of more tropical forms that would otherwise be habitat limited in the northcentral GOM. 

Other taxonomic differences in reef-associated fish composition were observed between GI 94 (midshelf) and GC 18 (outer shelf). At GI 94, lutjanids were also relatively common, with Rhomboplites

aurorubens the dominant species, followed by Lutjanus spp. While Pristipomoides aquilonaris was

the primary lutjanid at GC 18, none were collected at this mid-shelf site. With regards to serranids,

the dominant group was serraniines (e.g., Diplectrum spp., Centropristis spp., and Serranus spp.),

while relatively few anthiines were collected. Also noteworthy was the relatively high abundance

of mullids collected at GI 94 (only one individual was collected at GC 18), particularly Upeneus

parvus, a common species on the mid-to-inner shelf (Hoese and Moore 1977). 

Ichthyoplankton Community Assemblage at ST 54

At ST 54, clupeiform fishes (mostly clupeids) overwhelmed the plankton net and light-trap

collections, and comprised 97% of the total catch (all gears combined). The dominant clupeid was

Opisthonema oglinum, which alone comprised 94% of the total catch (Table 5.8). Harengula

jaguana, though present at GI 94, were more prominent at ST 54. This trend of increasing

dominance of clupeiform fishes continued as our sampling efforts moved inshore. In general, it is

difficult to discuss the abundances of the other taxa except in very relative terms, since no families

of fishes (with the exception of clupeids and engraulids) comprised over 1% of the total catch.

Among pelagic fishes, the reef-associated carangids and scombrids were relatively abundant,

particularly Caranx hippos/latus, Euthynnus alletteratus, and Scomberomorus maculatus.
256

Similar to GI 94, the second most abundant group of fishes at ST 54 was composed of demersal

species. However, unlike GI 94 where synodontids dominated, sciaenids were the most dominant

family, primarily Cynoscion arenarius, which was collected throughout the sampling season. Not

only did the number of sciaenids increase, but the number of their taxa increased as well, from three

at GI 94 to five at ST 54. Cynoscion arenarius dominated the plankton net catches, but synodontids,

primarily Synodus foetens, dominated the light-trap collections. Synodontids were not as prominent

at ST 54 as they were at GI 94, and the number of taxa decreased from 7 to 4. Other demersal taxa

collected included unidentified myctophiforms, Trichiurus lepturus, Symphurus spp., and Etropus

crossotus. 

The most abundant reef/structure-associated fishes were blenniids and gobiids. Unlike GI 94,

Parablennius marmoreus was relatively uncommon. The dominant species at ST 54 were

Scartella/Hypleurochilus spp., Hypsoblennius hentz/ionthas, and H. invemar. Difficulties in

identification prevent us from confidently separating H. hentz from H. ionthas and Scartella spp.

from Hypleurochilus spp., but all of these taxa are common in nearshore areas and hard-bottomed

habitats, such as oyster reefs and pilings (Hoese and Moore 1977). In general, at ST 54, reef fish,

although not abundant, were relatively well represented in terms of number of taxa, rivaling that of

GI 94. However, other than blenniids and gobiids, abundances of other reef fish were very low (less

than a total of 10 individuals collected per taxa) but included Rhomboplites aurorubens and

unidentified pomacentrids, serranids, and ephippids. 

The low reef fish abundances are not surprising, particularly for the more tropical taxa such as

haemulids, labrids, and scarids. The adults of these taxa are more typical of the outer shelf

assemblages (Table 5.4). Similarly with regards to reef fish larvae and juveniles, this trend of

decreasing taxonomic richness towards the more inshore environments is supported somewhat by

our study, particularly with regards to scarids (Tables 5.6–5.8). Even though an inner shelf platform

would be downstream from potentially more offshore sources of larvae and recruits, perhaps the

relatively greater distances involved necessitating extended pelagic larval durations and the

potentially less favorable inshore environmental conditions result in increased mortality (Leis 1991).

Ichthyoplankton Community Assemblage at the Belle Pass Jetties

The jetty at Belle Pass, though different in its structural complexity, vertical height, and

hydrodynamics shared at least one similarity with the platforms in that it was also dominated by

clupeiform fishes (74% of total catch). The taxonomic composition of this group was different,

however, in that engraulids, particularly Anchoa mitchilli, dominated catches (Table 5.9). The trend

of increasing numbers of Harengula jaguana and Brevoortia patronus as the sampling sites moved

progressively inshore continued as well. Another difference was the relatively high abundance of

a different pelagic group, the atherinids, particularly Membras martinica, a common coastal pelagic

species. 

By far the most dominant demersal species was Cynoscion arenarius, and in general, the number

of sciaenid taxa increased from the platform sites. Bairdiella chrysoura was also relatively common.

Micropogonias undulatus, Sciaenops ocellatus, Pogonias chromis, and C. nebulosus were all
257

collected as well, none of which were collected at ST 54 and GI 94, although some M. undulatus

and S. ocellatus were collected at GC 18. The jetty site also commonly had the predominantly

estuarine species, Gobiesox stromosus. The ophichthid eels were most abundant at Belle Pass where

they were also the most speciose taxonomic group, with Myrophis punctatus being the dominant

species. The flatfish Citharichthys spp. and Symphurus spp. were also very common.

The reef/structure-associated fish group was dominated by small, estuarine/coastal species, primarily

Gobiosoma bosc, which comprised 75% of the gobiids collected. This species is very common in

coastal areas of the northern GOM, and the adults are typically found in association with weeds and

oyster beds in protected bays and estuaries (Hoese and Moore 1977; Robins et al. 1986). The second

most abundant gobiid was Gobionellus oceanicus (formerly Gobionellus hastatus) which comprised

14% of the total catch. Adults of this species are common in estuaries but are also found in deeper

waters (22-40 m) on the shelf (Hoese and Moore 1977). Other common gobiid taxa were

Microgobius spp. and Gobiosoma spp. Based on the dominance of estuarine species collected at

Belle Pass within this family, it is likely that the individuals in these two genera are also estuarine

forms, even though these genera contain tropical forms as well. Taxa from a related group, the

eleotrids, were also relatively common in our jetty samples. Blenniids were also a very common

group, particularly Hypsoblennius hentz/ionthas and Scartella spp. Other reef or structure-associated

fish taxa collected at Belle Pass include labrids, ephippids, scarids, and sparids. 

Lutjanus griseus and L. synagris juveniles, though not abundant, were also collected at Belle Pass.

Lutjanus griseus juveniles are more common along the western GOM and Florida coasts where they

are collected in their preferred habitat, relatively high salinity seagrass beds (Pattillo et al. 1997).

However, they have been reported (although less frequently) in association with other structures,

such as pilings, jetties and rocks (Starck 1971). Young L. synagris are also present in coastal areas

(Hoese and Moore 1977). The presence of these species at the jetty is noteworthy because it

indicates that coastal, artificial structures even in relatively low salinity environments may play a

role as nursery areas in absence of other structurally-complex habitats, such as grassbeds in more

high-salinity, oligotrophic estuaries. Many species of reef fish do not settle directly onto reefs but

utilize other coastal habitats as nursery grounds prior to moving to offshore reefs. While habitats

such as high-salinity seagrass beds are important to many reef related species (Connolly 1994), other

structurally-complex habitats have been identified as nurseries (Ferrell and Bell 1991; Bennett 1989;

Ross and Moser 1995). Seagrass beds are often the most common form of shelter available in certain

settlement areas, but experimental evidence suggests that presettlement larvae of a number of

different species select any structurally-complex habitat at the time of settlement (Bell et al. 1987).

Due to the overwhelming influence of the Mississippi River and its distributaries, Louisiana

estuarine and coastal areas are generally low salinity (18-25 ppt at Belle Pass during the course of

this study), turbid, and lacking in seagrass beds and naturally-occurring hard substrate habitats

(except for oyster reefs). Therefore, the role of the artificial habitats such as jetties and breakwaters

may be more important as islands of refuge for individuals that would otherwise be lost to unsuitable

habitat and, therefore, mortality.
258

Taxonomic Similarity Between Sites

In an effort to examine the relative similarity in taxonomic assemblages between the different sites

(including the pilot study sites WC 71D and WC 352) we computed Schoener’s Index of Niche

Overlap for each site. Since all sites sampled during this study were heavily dominated by a single

taxon, for the sake of this discussion we will compare only the similarity values calculated after the

dominant taxa were removed. In general, the index values indicate that the sites were not very

similar, with the highest similarity value between any two sites being 0.45 for GI 94 and ST 54

(mid- and inner shelf). This is not unexpected, since we purposely chose sampling sites in different

depth zones across the shelf where there should be some faunal transitions (Gallaway et al. 1980;

Gallaway 1981), and indeed there were in many instances. The Belle Pass jetty, which was heavily

influenced by the presence of estuarine and coastal pelagic taxa, was very different from the midshelf (GI 94) and outer shelf (GC 18) platforms, where mesopelagic and tropical taxa were

influential. Similarity indices for GI 94 displayed the expected cross-shelf transitional pattern, with

the highest similarity values being for the adjacent sites, ST 54 and GC 18, followed by Belle Pass.

The highest similarity index for GC 18, however, was with ST 54, the inner-shelf platform, whereas

we might have expected GC 18 to most similar to GI 94. This somewhat unexpected result is

probably due to the large number of reef taxa collected at GI 94 that were unique to that site (Table

5.7). Reef fish taxa such as Chromis spp., Abudefduf taurus, Mullus auratus, Ophioblennius

atlantica, Pseudopeneus maculatus, Opisthognathus aurifrons, and Opisthognathus lonchurus were

collected only at the GI 94 platform. Other taxa (ephippids and scarids) were collected at GC 18 and

ST 54, but not at GI 94. 

The more westerly pilot study sampling sites (Figure 5.2) were also included in these analyses and

yielded interesting results. WC 352 (20 m depth) was the least similar to any of the other sites with

values ranging from 0.04-0.13 (April, May, and August samples only; Table 5.11). Within

Gallaway’s three depth zones, we would have expected this site to be relatively similar to ST 54

(approximately 20 m) in taxonomic composition. Between these two sites, 25 taxa were collected

only at WC 352, including relatively large numbers of Archosargus probatocephalus, Cypselurus

cyanopterus, Microdesmus longipinnis, and Kyphosis spp., whereas 41 taxa were collected only at

ST54, including large numbers of Cynoscion arenarius, Scomberomorus maculatus, Harengula

jaguana, and Peprilus burti. While all of these fishes are common inner shelf taxa, it would appear

that the WC 352 site was influenced much more by its proximity to the Flower Gardens and the

influence of the Mexican-Texas Current, which flows from Mexican waters northward along the

Texas coast and seasonally progresses up along the western coast of Louisiana (Cochrane and Kelly

1986) and may be an additional source of reef or hard-substrate oriented fishes. Differences in local

current and temperature regimes, as well as the timing of spawning events between different

populations of the same species along the coast may have also resulted in the observed differences.

Interestingly, WC 71D (12 m) was most similar (0.31) to GC 18 (shelf slope) and least similar to

ST 54 and Belle Pass (0.17 and 0.06, respectively; Table 5.11). This comparison, however, is

confounded by July being the only month used for comparisons and by multiple light-trap designs

being deployed at WC 71D. The dominant taxa at WC 71D were Opisthonema oglinum and Anchoa

spp. (41% and 12% of total catch, respectively). These taxa were also dominant at GC 18 during

July, where O. oglinum and Anchoa spp. comprised 34% and 19% of the total catch for July,
259

respectively, resulting in a relatively high similarity index (0.52) between the two sites initially.

However, this value decreased considerably once O. oglinum was removed from the analysis (0.31).

The dominance by Anchoa mitchilli at Belle Pass (91% of total catch for July) and by other coastal

taxa (Euthynnus alletteratus, Parexocoetus brachypterus, and Mentichirrus spp.) at ST 54 (55% of

total catch for July) resulted in very small similarity indices between these sites and WC 71D.

Differences between the WC stations (352 and 71D) and Belle Pass and ST 54 indicate that

taxonomic assemblages may differ longitudinally along the coast as well as with depth, and point

out the need for replicate platform sampling within each depth zone from different geographic areas.

Ongoing efforts east of the Mississippi Delta may help resolve these issues and give us a more

complete picture of ichthyoplankton assemblages associated with artificial structures across the

northcentral GOM. 

While using a similarity index to characterize assemblages helps to synthesize large amounts of

information, the analyses are confounded by several problems that can make the results difficult to

interpret. First, the index is highly influenced by large numbers of individuals of a single taxon and

confidence intervals can be quite large (Ricklefs and Lau 1980). This is why we chose to discuss the

values from the analyses without the most dominant taxa from each site, which helped to identify

trends that may have otherwise been overwhelmed in the complete data set. Secondly, in any comparison between two sites, we chose only to use samples from each data set where the seasonality

overlapped in sampling efforts so that the same species pool would theoretically be available for collection. However, at times this led to large disparities in sampling effort between sites within a comparison. For example, only April, May, and August, samples were used to compare WC 352 (n=57,

once monthly sampling) and GI 94 (n=331, twice monthly sampling plus the extra May lunar ministudy samples). Finally, taxa utilized in the analyses were limited by our ability to identify the many

larval and juvenile forms collected over the course of the study. Since we were trying to analyze the

taxonomic assemblage at the lowest level possible, we were forced to eliminate large numbers of

fish that could not be identified to genus. Overall, however, we feel the index provides a good idea

of the similarity in community assemblages between sites, but it should only be discussed in relative

terms.

Taxonomic Diversity Between Sites

The mean diversity indices for the plankton net collections taken at the platform sites and the

pushnet collections taken at Belle Pass were not significantly different from each other, ranging

from 0.73-0.83 (Figure 5.3). They were, however, slightly higher than those for the light-trap

collections, with the exception of GI 94. In general, observed statistical differences in ShannonWeiner diversity indices between sites were limited to light-trap collections. The similarity between

the light-trap diversity indices for ST 54 and Belle Pass is not surprising, since both sites were

dominated by large numbers of photopositive clupeiform fishes, which also lowered their diversity

indices. Light-trap collections were significantly more diverse at GI 94, a result of being less

dominated by clupeiform fishes than ST 54 and Belle Pass, and of collecting more taxa, particularly

reef fish species, than GC 18. In general, taxonomic richness in light-traps was highest at GI 94,

with 90 taxa identified to genus as compared to 65 taxa at ST 54, the platform with the second

highest number of taxa. Inshore (particularly estuarine) areas are generally characterized as having

lower diversity than adjacent shelf waters and are dominated by a few highly abundant taxa
260

(Nybakken 1988). This pattern is generally attributed to the fluctuating nature of the nearshore

environment, particularly with regards to salinity and temperature, and the lack of physiological

specializations needed to deal with this estuarine environmental variability (Nybakken 1988). This,

in part, may explain the relatively low diversity indices for ST 54 and Belle Pass, the two inshore

sites. In contrast, species richness and abundance is generally relatively low on the outer shelf, due

to the homogeneity of the bottom substrate (Bond 1996). As previously discussed, topographical

relief is disjunct throughout the northcentral GOM (especially west of the Delta) and the sea floor

is basically dominated by expanses of mud and silt. Again, this homogeneity and the previously

discussed lack of a large amount of upstream supply of larvae may in part explain the low taxonomic

diversity observed in the light-trap collections at GC 18.

Several studies have investigated differences in taxonomic richness between different gear types,

although few, if any, actually calculated taxonomic diversity indices as a comparison. Choat et al.

(1993) collected individuals from more families with a bongo net (63 families), a lighted-seine net

(37 families), neuston net (31 families), Tucker trawl (29 families), and a purse seine (25 families)

than they did with a light-trap (20 families) in a gear comparison study off Lizard Island, northern

Great Barrier Reef, Australia. In the Gulf of California, more reef fish larvae and juveniles from

different families were collected with a diver-steered plankton net (43 families) than with a lighttrap (31 families; Brogan 1994). In Onslow Bay, North Carolina, more fish larvae and juveniles

from different families were collected with a neuston net (24 families) than with either of the two

light-trap designs employed (18 and 21 families; Hernandez and Lindquist 1999) in a study. In each

of these studies, the authors concluded that the taxonomic assemblage collected in their respective

studies was very method-dependent, and the same appears to be true in our study (Hernandez and

Shaw this volume).

Environmental Variables and Larval Abundances

Canonical correlation analyses were used to determine the relationship between the dominant taxa

collected at our sampling sites and measured environmental/biological parameters, i.e., temperature,

salinity, turbidity, dissolved oxygen, and macrozooplankton biomass. At all of our sampling sites,

temperature and salinity appeared to explain most of the variation in larval abundances in our

models for the dominant taxa. This is not surprising as these physical variables change seasonally,

and to some extent across the shelf, as does the availability of larval assemblages. Occasionally, both

temperature and salinity were important factors within a single environmental canonical variate,

which is probably a reflection of seasonality, i.e., in the northern GOM as temperatures increase

during the late spring and into the months of summer and early fall, salinities tend to increase as

well, due to decreased Mississippi/Atchafalaya River runoff and increased evaporation.

Many of these relationships (based primarily on the seasonal variables temperature and salinity)

were consistent with known information on the seasonal occurrences of the different species. For

example at GC 18, where we were able to sample nearly year-round, Mugil cephalus was found to

be negatively associated with temperature in plankton net samples, which is consistent with their

peak periods of abundance (December-February) in the northern GOM (Table 5.12; Ditty et al.

1988). Other species collected in plankton nets at GC 18 were positively associated with temperature

and represent taxa with peak larval abundances in the spring and summer months, such as Auxis spp.
261

(May-September), Caranx crysos (June-August), and C. hippos/latus (April-August; Ditty et al.

1988). Relationships between seasonal variables (temperature and salinity) and larval peaks in

abundance were observed at all sites. For example, positive relationships between abundances and

temperature and salinity were found for species with summer peaks in larval abundance, such as

Auxis spp. (May-September) at GI 94 (Table 5.14) and Chloroscombrus chrysurus (June-September)

and Scomberomorus maculatus (August-September) at ST 54 (Table 5.16). Negative relationships

for species with spring or winter peaks were found as well, such as previously mentioned Mugil

cephalus at GC 18 (Table 5.12) and Gobiesox strumosus (March-May) at Belle Pass (Table 5.18).

While seasonality seems to be an important factor, trends in larval abundances could also reflect the

environmental optima and preferences of some species. Membras martinica, for example, is found

primarily in more saline areas along the coast, as well as offshore areas (Hoese and Moore 1977).

At Belle Pass, pushnet densities for this species were positively associated with salinity (Table 5.18).

Larval and juvenile Caranx crysos prefer warmer, more saline waters (Patillo et al. 1997), and

this species was often positively associated with temperature and salinity in our study (Tables

5.12–5.13 and 5.17).

Differences among relationships at the same site between plankton net and light-trap collections

may be a reflection of biases towards different life history stages, since the plankton nets collected

primarily younger, less competent larvae while light-traps collected larger larvae and juveniles.

At ST 54, for example, net collections of Scomberomorus maculatus were positively associated with

temperature and salinity (Table 5.16), while light-trap collections were negatively associated

with these variables (Table 5.17). These associations are consistent with the known early life history

preferences for this species, as larval S. maculatus require relatively higher temperatures

and salinities than juveniles, which are generally more eurythermal and euryhaline (Patillo et al.

1997).

Dissolved oxygen and turbidity were also important variables at Belle Pass for some species,

but little is known about these requirements or preferences for the early life history stages of many

fishes. Some species which were very photopositive (i.e., Gobiesox strumosus and Hypsoblennius

hentz/ionthas) were also negatively associated with turbidity in our light-trap samples, possibly

because of decreased light-trap efficiency in highly turbid waters. Macrozooplankton biomass

was influential at GC 18 (Table 5.13) and GI 94 (Table 5.15), but only in light-trap collections. This

result is not surprising as light-traps tended to collect larger, more competent postlarvae and

juveniles which would be more likely to be affected by this macrozooplankton prey availability than

smaller, less competent larvae. All significant taxa were positively associated with zooplankton

biomass, and included larval forms such as Euthynnus alletteratus, Saurida brasiliensis, and

Synodus foetens, which have well-developed mouths and teeth at small sizes and are able to feed on

zooplankton.

While canonical correlation analyses were useful in characterizing the environmental correlates for

some species, results for others were confounding. At ST 54, for example, Cynoscion arenarius was

negatively associated with the first environmental variate and positively associated with the second

environmental variate, both of which were positively correlated with salinity. In many instances, our

models did not explain a large amount of the variation (15%) for many species. One possible reason
262

for some of these discrepancies is that spawning seasons and periods of larval abundances for many

species occurred throughout our entire sampling season for many species, particularly at GI 94, ST

54, and Belle Pass, where we sampled only from April-September. This is the case for species such

as Citharichthys spp., Citharichthys spilopterus, Cynoscion nebulosus and others (Ditty et al. 1988).

For other species, particularly small fishes with little economic value such as many of the

lizardfishes (Synodus foetens, S. poeyi, Saurida brasiliensis) and blennies (Hypsoblennius

hentz/ionthas, H. invemar, and Scartella/Hypleurochilus), little information is available on peak

occurrences of these taxa across the shelf. In this respect, our study provides an important

contribution to the life history information on these taxa across the shelf. 

CONCLUSIONS

In many respects, the community assemblages represented in our across-shelf sampling efforts are

similar to the adult communities summarized in Gallaway et al. (1980) and Gallaway (1981). For

example, while we did not collect individuals from as many reef-dependent families (i.e., no

pomacanthids or acanthurids; Table 5.4), the reef-dependent taxa that were collected were primarily

associated with platforms further offshore (pomacentrids and chaetodontids). Also, inner-shelf, reefassociated taxa reported for the adult assemblages, such as carangids and ephippids were present at

our inner-shelf platform, as well as our other sampling sites. However, several taxa reported from

the adult communities as being common primarily further offshore (mid-shelf and shelf slope), such

as serranids, lutjanids, labrids, scarids, and blennies were collected at our inshore sites, ST 54 and/or

the Belle Pass jetties. These results are not surprising, since many reef-associated taxa utilize

estuarine and nearshore environments as nursery areas. In the case of the blenniids, several of the

taxa collected in our study are common in estuarine and coastal environments and probably do not

reflect the presence of more reef-like, tropical taxa. 

This study represents the first comprehensive look at the ichthyoplankton assemblages associated

with oil and gas platforms in the northern GOM and is also a first (yet preliminary) attempt at

comparing such assemblages across different depth zones and geographical regions. It is apparent

that a diverse recently spawned larvae, postlarval, and juvenile fish community can be captured in

the waters within and near platforms (Hernandez and Shaw this volume) and these structures may

therefore be important to reef-associated and -dependent fish. Though many taxa were represented

in our collections, it is difficult to discern the reasons why some fish were present at the artificial

structures. Some, like the clupeiforms, are extremely abundant, very photopositive, and may be

behaviorally attracted to such structures with a large, consistent light-field. Other taxa like blennies

are reef/structure-dependent, and may be attracted to the numerous habitats created by the biofouling

community (e.g., barnacles) on the platform legs and cross-members, as well as the associated

zooplankton food resources. Pelagic species, like carangids and scombrids, have more generalized

habitat requirements, but may also be attracted to the structure (reef-associated) or to concentrations

of zooplankton and forage fish that are inhabiting the platform and immediately surrounding waters.

For whatever reason, based on the results from this study the oil and gas platforms serve a

potentially important function as a hard-substrate habitat, and could therefore lead to increased

production.
263

Our efforts are ongoing, as we are attempting to characterize the ichthyoplankton community at two

other sites, Santa Fe-Snyder Main Pass (MP) 259A and Murphy’s Viosca Knoll (VK) 203 (Figure

5.2). These platforms lie east of the Mississippi River Delta, enabling us to broaden our observations

on a geographic (longitudinal) scale. Also, MP 259A (130 m depth) and VK 203 (30 m depth) gives

us an offshore and mid-shelf replicate for further comparisons with the sites already sampled (Figure

5.2). Additionally, settlement traps are being deployed at VK 203 in an attempt to address questions

concerning size at settlement, habitat selection, and recruitment dynamics. The additional

information from platforms east of the Delta will enable us to develop a larger, more geographically

meaningful and comprehensive characterization of the ichthyoplankton from continental shelf waters

of the northern GOM.

ACKNOWLEDGMENTS

We gratefully acknowledge funding by the Minerals Management Service-Louisiana State

University-Coastal Marine Institute (Contract Number 14-75-0001-30660, Task Order Number

19926) and by the Louisiana Sea Grant Program, part of the National Sea Grant College Program

maintained by the National Oceanic and Atmospheric Administration. We thank David Bunch,

Nathan Craig, Heather Haas, Ross Horton, Robin Hargroder, Sean Keenan, Gregory Lavergne,

David Lindquist, Bradley McDonald, Cory New, Nick Ortego, John Plunkett, and Christopher

Whatley for assistance in the field and/or laboratory. We gratefully acknowledge the assistance of

Drs. Charles A. Wilson and David R. Stanley. We are further indebted to Exxon USA, Inc. and

Mobil USA Exploration and Production, Inc. for access to their offshore oil and gas platforms and

logistical support, and to the crews of Mobil’s West Cameron 352, West Cameron 71D, Green

Canyon 18, and Grand Isle 94 and Exxon’s South Timbalier 54 platforms for their hospitality.

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Stanley, D.R. and C. Wilson. 2000. Seasonal and spatial variation in the biomass and size frequency

distribution of the fish associated with oil and gas platforms in the northern Gulf of Mexico.

OCS Study MMS 2000-005, U.S. Department of Interior, Minerals Management Service, Gulf

of Mexico OCS Region, New Orleans, LA.
269

Starck, W.A. 1971. Biology of the gray snapper, Lutjanus griseus (Linnaeus), in the Florida Keys.

In W. A. Starck and R. E. Schroeder, eds. Investigations on the gray snapper, Lutjanus griseus).

Studies in Tropical Oceanography 10.

Stephan, C.D., B.G. Dansby, G.C. Matlock, R.K. Rieckers, and R. Rayburn. 1990. Texas artificial

reef fishery management plan. Texas Parks and Wildlife Department of Fisheries Management

Plan Serial 3.

Stone, R.B., H.L. Pratt, R.O. Parker, and G.E. Davis. 1979. A comparison of fish populations on an

artificial and natural reef in the Florida Keys. Marine Fisheries Review 41:1-11.

Thresher, R.E. 1984. Reproduction in Reef Fishes. T.F.H. Publications, Inc.

USDOC (United States Department of Commerce). 1996. Magnuson-Stevens Fishery Conversation

and Management Act. NOAA Technical Memorandum, NMFS-F/SPO-23. 

Van Guelpen, L., D.F. Markle, and D.J. Duggan. 1982. An evaluation of accuracy, precision, and

speed of several zooplankton sampling techniques. Journal du Conseil. Conseil Permanent

International pour l’Exploration de la Mer 40:226-236.

Van Voorhies, D.A., J.F. Witzig, M.F. Osborn, M.C. Holliday, and R.J. Essig. 1992. Marine

recreational fishery statistics survey, Atlantic and Gulf coasts, 1990-1991. NOAA/NMFS

Current Fisheries Statistics 9204. 

Victor, B.C. 1986. Larval settlement and juvenile mortality in a recruitment-limited coral reef fish

population. Ecological Monographs 56:145-160.
270

RED SNAPPER RECRUITMENT TO AND DISAPPEARANCE FROM OIL

AND GAS PLATFORMS IN THE NORTHERN GULF OF MEXICO

David L. Nieland

Coastal Fisheries Institute

Charles A. Wilson

Coastal Fisheries Institute and

Department of Oceanography and Coastal Sciences

Center for Coastal, Energy, and Environmental Resources

Louisiana State University

ABSTRACT

The red snapper Lutjanus campechanus is a potentially large and long-lived species which can

achieve ages approaching 60 years and weights of over 22 kg. In the northern Gulf of Mexico, oil

and gas platforms provide the preponderance of both vertical relief and hard substrate habitat for red

snapper and other reef associated fishes. In July 1998, we collected morphometric data and sagittal

otoliths from 300 red snapper randomly selected from among the mortalities manifested subsequent

to the explosive removal of an obsolete gas platform. Ages estimated from counts of otolith annuli

ranged from one to nine years among these specimens. The virtual absence of age-one red snapper

(0.68%) and the preponderance of age-two red snapper (53%) at the platform demonstrates that red

snapper recruit to platforms sometime during their second year. Truncation of the age distribution

results from natural mortality, fishing mortality, and emigration to other habitats after several years

of residency. Assuming this population to be typical, the age distributions of the commercial and

recreational harvests suggest that oil and gas platforms serve as essential habitats for younger red

snapper. Conversely, platforms may make red snapper at ages four, five, and six year more

vulnerable to fishing mortality as they are perhaps being harvested in proportions greater than their

numbers in the population at large.

The management of the red snapper Lutjanus campechanus in the Gulf of Mexico (GOM) remains

among the more problematic issues facing fishery managers of the region. Both the commercial and

recreational red snapper fisheries are limited by size limits, creel or trip limits, seasonal closures,

and quotas as formulated by the Gulf of Mexico Fisheries Management Council (GMFMC) in

response to reports of overfishing (Schirripa and Legault 1999). Shrimp trawlers have also been

required to install bycatch reduction devices in their nets to curtail mortality among juvenile red

snapper. The intent of these regulations is both to achieve a 20 percent spawning potential ratio and

to allow populations to recover. Thus, reliable characterizations of the age and length structure of

red snapper populations in the GOM is essential to monitor year class strength, to conduct stock

assessments, and to demonstrate population recovery.

Since 1995 we have collected otoliths and morphometric data of red snapper landed in the

commercial harvest of the northern GOM off Louisiana. From these materials and data we have been

able to characterize the age and size structure of this harvest (Wilson et al. 1998). However,
271

legitimate questions have been raised as to whether the age and size structure of the commercial

catch is truly representative of the red snapper population as a whole. The regulations applied to the

fishery and the very nature of the fishery itself are the source of these questions. For the past few

years, the minimum legal size for red snapper in the GOM commercial fishery has been 381 mm (15

inches) total length. Furthermore, red snapper commercial fishermen have been allowed a Gulf-wide

quota of 2,114 metric tons (4.65 million lb) two-thirds of which is allocated to a winter season

beginning in February and one-third to an autumn season beginning in September or October.

Additionally, both the winter and autumn seasons have been open to red snapper harvest only for

the first 15 days (pre-1999) or ten days (1999-2000) of each successive month until the quota is

achieved. A trip limit of 0.91 metric ton (2000 lb) for holders of federally issued reef fish permits

and the modest number of available fishing days has resulted in a “derby” fishery that necessitates

maximum catch in a minimum of time. 

To compete in this derby fishery, many red snapper fishermen have concentrated their efforts at the

numerous offshore oil and gas platforms of the northern GOM, particularly those closest to port.

These easily located structures can hold large numbers of red snapper (Continental Shelf Associates

1982; Putt 1982; Stanley and Wilson 1990; Stanley 1994). The usual routine (called “rig hopping”)

involves test fishing at successive platforms until a large and readily caught population of red

snapper is found. Under the appropriate conditions and with some good fortune, a single trip may

last less than one day. 

As part of a continuing investigation into the stock structure of red snapper in the GOM, we also

sampled the 1999 recreational harvest of the species from waters off Louisiana. The recreational

fishery at this time was also restricted by regulations promulgated by the GMFMC. A Gulf-wide

harvest of 2,032 metric tons (4.47 million lb) was allowed during an open season which began on

1 January 1999 and which would close when the quota was achieved or on 31 October, whichever

was earlier. A daily creel limit of four red snapper over 406 mm (16 inches) total length was also

mandated. As in the commercial fishery, recreational fishermen target the populations of red snapper

associated with oil and gas platforms and also employ the rig hopping technique to maximize catch

per effort. 

Given the nature of the red snapper fisheries in the northern GOM, it is highly unlikely that the age

and size structure of either harvest is representative of the entire population. Rather, it more certainly

reflects the age and size distribution of only those red snapper that are both associated with oil and

gas platforms and legal for fishermen to retain. Thus, the patterns of recruitment to and emigration

from oil and gas platforms would also affect the size and age structures of the harvests. We have

speculated that red snapper recruit to platforms at age one or two, occupy these habitats for a few

years, and then emigrate to other habitats. Older, larger red snapper may avoid platforms and

gravitate to other structure such as shipwrecks, sea-bottom depressions or lumps, and natural reefs.

However, there are few fishery-independent studies that have allowed characterization of age and

size of red snapper associated with oil and gas platforms.

Herein we report the fishery-dependent age and length distributions of the 1998 red snapper

commercial and summer 1999 recreational harvests from the northern GOM off Louisiana and those

of a fishery-independent “snapshot” of red snapper randomly sampled among the mortalities
272

resulting from the July 1998 explosive removal of an obsolete offshore gas platform. Our objectives

were to infer important red snapper life history information from these data, such as age and size

at recruitment to oil and gas platforms and the possibility of emigration away from the platforms to

alternative habitats by older individuals later in life. 

METHODS

Red snapper from the 1998 winter and autumn commercial harvests were randomly sampled as they

were landed at two wholesale facilities: USA Fish in Leeville, Lafourche Parish, LA, during

February and March, and at USA Fish in Cameron, Cameron Parish, LA, in October. The vessels

that fish red snapper are generally manned by a captain and two crew. The heavily weighted fishing

lines, which may have 20 or more baited hooks, are deployed vertically from manual, electric, or

hydraulic “bandit” reels, four of which may be in use at any time. Snapper fishermen are

understandably jealous of their catch localities; we asked for little specific catch information.

However, we could infer that most trips took them from 50 to 80 km offshore. 

Red snapper from the recreational catch were sampled sporadically from 18 April to 18 August 1999

at a charter boat dock in Port Fourchon, Lafourche Parish, LA. Through April and May the

recreational fishery operated under a 381 mm minimum size; however, after 4 June and until the

quota was estimated to have been achieved on 29 August, a 457 mm (18 inches) minimum size was

enforced. The four vessels from which fish were obtained specialize in day trips lasting 10-12 hours.

Given their maximum speed of approximately 12 knots, the vessels seldom venture more than 50

km off the coast. The platforms visited are situated in waters of 30-45 m depth; the usual angling

gear is a stout fiberglass pole and a 4-0 reel with a 50 pound monofilament line. Single hooks baited

with whole or cut fish are used exclusively.

To minimize hazards to navigation in the GOM, Coast Guard regulations mandate that offshore oil

and gas platforms be removed once they have ceased production. A fishery-independent population

of red snapper was randomly sampled from among the fish mortalities produced after the explosive

removal of an obsolete oil platform located in Block 209 of the Ship Shoal oil and gas lease planning

area (approx. 185 km SW of New Orleans, LA) on 30 July 1998. The four-pile platform measured

6.1 X 7.6 m at the water’s surface and 12.2 X 13.7 m at the bottom. Water depth at the site was 32

m; thus, the volume of water enclosed by the platform was approximately 3,100 m3

. Following

detonation of plastic explosives placed at 5 m below substrate level in all four piles and in the lone

well conductor, all floating fishes were collected by personnel from the National Marine Fisheries

Service (NMFS) Galveston Laboratory. A representative sample of fishes that had sunk to the

bottom was also retrieved by NMFS SCUBA divers.

Fork length (FL) in mm and both sagittal otoliths were taken from all specimens. Otoliths were

prepared and sectioned for aging analyses as described in Beckman et al. (1988). Counts of

increments (opaque zones) were accomplished by reading along the medial surface of the transverse

section ventral to the sulcus; increments were often inconsistent in other regions of the otolith

section. The appearance of the otolith margin was also coded as either opaque or transparent

(Beckman et al. 1988; Beckman et al. 1990, 1991). Age estimates of red snapper were based on

otolith opaque increment counts and adjusted to accommodate early or late annulus formation.
273

Opaque increments in red snapper otoliths have been demonstrated to be annual in their formation

by Manooch and Potts (1997) and Wilson and Nieland (in press). Based on previous studies of red

snapper reproduction (Render 1995), we assigned a uniform hatching date of 1 July. To compensate

for the various times of the year when the specimens were taken, all ages were rounded to the nearer

integer or, in other words, to the age at the previous or at the following hatching date, whichever was

closer. Fork lengths were converted to total lengths (TL) with the equation TL = 1.073 (FL) +3.56

(linear regression, df = 1,015, P<0.001, r

2

=0.999). The Komolgorov-Smirnov test was used to test

for differences among distributions of TL and age ("=0.05). 

RESULTS

The sampling of 1,109 red snapper from the commercial harvest yielded 1,109 TL measurements

and 1,095 age estimates. Our efforts from the recreational harvest resulted in 666 individuals

sampled; age and TL are available for 646 and 663 of these, respectively. The recovery of fish

mortalities from the Ship Shoal 209 detonation produced 1,005 total specimens dominated by red

snapper, gray snapper L. griseus, lane snapper L. synagris, sheepshead Archosargus

probatocephalus, and Atlantic spadefish Chaetodipterus faber (pers. comm., Gregg Gitschlag,

National Marine Fisheries Service, Galveston, TX). Three hundred TL and 295 age estimates were

obtained from a random sampling of 300 of the 373 red snapper mortalities.

Fishery-Dependent Data

Among red snapper sampled from the commercial catch, TL ranged from 352 to 883 mm (Figure

5.4) with a mean of 510 mm. Modal TL was 425 mm, and 50% of the specimens were less than 475

mm. Ages estimated for these specimens ranged from 1.3 to 48.7 years; however, the vast majority

(93%) of these individuals were age three to six (Figure 5.5) and only six specimens were older than

10 years. Total lengths of the red snapper from the recreational harvest varied from 374 to 983 mm

(Figure 5.4); mean TL, modal TL, and median TL were 558 mm, 475 mm, and 500 mm,

respectively. Ages among the recreational catch ranged from 1.90 to 37.06 years with a mean age

of 4.50 years. Individuals of ages three to six comprised 92% of the sample population (Figure 5.5).

Fishery-Independent Data

Total lengths and age estimates among the red snapper sampled from the Ship Shoal 209 population

evidence radically and statistically different distributions from those seen in the commercial and

recreational catches (Figure 5.4, Figure 5.5). In addition to having both a lesser minimum (255 mm)

and a lesser maximum (791 mm) TL, the TL distribution is distinctly bimodal with a hint of a third

mode at larger size (Figure 5.4). The distribution of ages (1.1-9.1 years) is also severely truncated

and includes a large proportion (53%) of age-two individuals which are not present in the

commercial or recreational landings (Figure 5.5). A plot of TL at age for the Ship Shoal red snapper

population (Figure 5.6) indicates that the first two major TL modes (275-375 mm and 400-500 mm)

are composed largely of individuals at age two years and age three years, respectively. The third

minor mode (635-750 mm) is comprised of red snapper of age four to six years.
274

Figure 5.4. Total length frequency histograms for red snapper Lutjanus campechanus from the

northern Gulf of Mexico: (top) 1,109 specimens from the commercial harvest of

1998; (middle) 663 specimens from the recreational harvest, April-August 1999; and

(bottom) 300 specimens from among mortalities subsequent to the explosive removal

of an oil and gas platform located in Ship Shoal Block 209, July 1998. The stippled

area indicates those TL below the 381 mm (15 inch) TL minimum size which applied

to the commercial fishery through out 1998 and to the recreational fishery through

3 June 1999. The hatched area delimits the 457 mm (18 inch) TL minimum under

which the recreational fishery operated from 4 June to 29 August 1999.
275

Figure 5.5. Age frequency histograms for red snapper Lutjanus campechanus from the Northern

Gulf of Mexico: (top) 1,095 specimens from the commercial harvest of 1998;

(middle) 646 specimens from the recreational harvest, April-August 1999; and

(bottom) 295 specimens from among mortalities subsequent to the explosive removal

of an oil and gas platform located in Ship Shoal Block 209, July 1998. 
276

200

300

400

500

600

700

800

900

0 2 4 6 8 10

Age (yr)

Total length (mm)

Figure 5.6. Scattergram of total length (mm) at age (yr) for 295 red snapper Lutjanus

campechanus sampled from the mortalities subsequent to the explosive removal of

an oil and gas platform located in Ship Shoal Block 209, July 1998.

DISCUSSION

Analysis of the fishery-independent red snapper data gathered from the Ship Shoal 209 detonation

must be tempered with the recognition that it is indeed a chronological “snapshot” of the red snapper

population. Previous reports of red snapper populations associated with oil and gas platforms have

shown conclusively that numbers can vary significantly among seasons (Putt 1982; Stanley 1994).

Red snapper are also known to stratify by size at different depths around platforms; further, larger

individuals are less obligate in their association to platforms than are smaller individuals (Render

1995). Thus, we must assume that red snapper of all sizes and at all depths would be similarly

susceptible to explosive-induced mortality and that mortality is 100% in the near vicinity of the

platform.

The fishery-independent sampling of fishes at Ship Shoal 209 reveals a relatively large population

of red snapper. Fully 37% of the fish mortalities recovered after the explosive detonation were red

snapper. Other fishery-independent surveys of fishes around oil and gas platforms have reported red

snapper populations consisting of 8-52% (Stanley 1994) and 2-4% (Putt 1982) of the total fishes

inhabiting platforms. However, 79% of the Ship Shoal 209 red snapper would have been unavailable
277

for harvest due to the minimum length regulation enforced Gulf-wide. This is amply reflected in the

virtual absence of individuals < 375 mm TL in both the recreational and commercial data sets.

The Ship Shoal 209 red snapper population is also relatively homogeneous in both age and length

distribution. The individuals within the first two large modes of the TL distribution make up 92%

of the total 300 individuals sampled. Further, individuals of age # three years totaled 90% of all red

snapper sampled. This homogeneity is reflected neither in the age nor in the TL distribution of the

commercial catch. Along the size spectrum of platforms in the GOM, the Ship Shoal 209 platform

ranks at the lower end of this distribution. In a hydroacoustic study of the fish population around a

much larger platform (45 m X 20 m; 19,800 m3 volume), Stanley (1994) reported the red snapper

population varying from 1,200 to 8,200 individuals. One could speculate that among such numbers,

older and larger red snapper might be present in appreciable numbers. Commercial and recreational

fishing effort at such structures could provide for the diversity of ages and lengths seen in the

fishery-dependent data.

The truncation of the red snapper size and length distributions at Ship Shoal 209 might also reflect

the life history of red snapper. Juvenile red snapper are known to inhabit shallow water areas devoid

of large structures where they are vulnerable to capture in trawls. This behavior is illustrated in

fishery-independent trawl data from the GOM, specifically the Fall Groundfish Survey and the

Summer SEAMAP Survey, in which the great majority of red snapper captured are age zero and one

(Schirripa and Legault 1999). It has been hypothesized that the disappearance of age-one red snapper from the trawl data represents migration to structures such as oil and gas platforms which

presumably provide refuge from large predators (Render 1995). It might also be postulated that oil

and gas platforms, in the absence of other hard-bottom habitats, are essential habitat for young red

snapper. Both the paucity of individuals of age zero and one and the bounty of age-two and -three

individuals at Ship Shoal 209 assuredly support these hypotheses. The drastic decrease in numbers

of individuals of age > three may represent emigration away from the structure to alternative

habitats, removal from the population through fishing activities and natural mortality, or reduced

recruitment among those cohorts.

The fishery-independent data from Ship Shoal 209 also provide verification of size at age for young

red snapper in the northern GOM. Within the first TL mode (275-375 mm) illustrated in Figure 5.4,

90% of the 150 individuals contained therein are age two. The second mode (400-500 mm FL) in

Figure 5.4 is comprised of 89% (92 of 103) age-three individuals. Such fidelity in the age at size

relations for age two and age three could prove useful in two instances. Red snapper ranging from

275 to 500 mm TL can be aged with relative confidence simply from their length; time consuming

and costly removal, sectioning, and reading of otoliths becomes unnecessary. Further, age

determined from length could be used to confirm age estimates derived from counts of otolith

increments.

Management of the red snapper in the GOM is predicated in part on estimates of relative cohort

strength at age one derived from the fishery-independent trawl surveys mentioned above (Schirripa

and Legault 1999) and on fishery-dependent data such as that reported herein. However, due to the

virtual ubiquity of age zero and one individuals in the trawl catch and to the minimum total length

regulations enforced within both the commercial and recreational fisheries, there is little information
278

on which to gauge cohort strength at age two. Over the past few years, the National Marine Fisheries

Service has undertaken periodic assessment of the effects of explosive platform removal on the

associated fish populations at select sites in the GOM. Such efforts apparently afford the sole

opportunity to monitor red snapper cohort strength at age two and to bridge the data gap between

existing data sources. They also prove to be crucial in our understanding of red snapper recruitment

to and emigration from reefs and other structures such as oil and gas platforms. Continuation of this

program would positively impact the current and future management of red snapper and help assure

the future of the species in the GOM

ACKNOWLEDGMENTS

We are indebted to Jane and Lonnie Black, Joey Trosclair, and many intrepid fishermen for allowing

access to the red snapper landed at the facilities of USA Fish. Captain Steve Tomeny and crews of

Southerner Charters have been our good friends and obliging cooperators for many years. Our

gratitude is also extended to Aly Hakam (Winmar Consulting Services), Spirit Energy, and Gregg

Gitschlag (National Marine Fisheries Service Galveston Laboratory) for their cooperation in our

effort to sample the red snapper population at Ship Shoal 209. Andrew Fischer and Forrest Davis

of our laboratory expertly sectioned the red snapper otoliths and made all the increment counts.

Finally we thank all of the colleagues and students who participated in the sampling trips. This

research was funded in part by the U. S. Department of Commerce Marine Fisheries Initiative

(MARFIN) Program administered by the National Marine Fisheries Service.

REFERENCES

Beckman, D. W., C. A. Wilson, and A. L. Stanley. 1988. Age and growth of red drum, Sciaenops

ocellatus, from offshore waters of the northern Gulf of Mexico. U. S. National Marine Fisheries

Service Fishery Bulletin 87:17-28.

Beckman, D. W., A. L. Stanley, J. H. Render, and C. A. Wilson. 1990. Age and growth of black

drum in Louisiana waters of the Gulf of Mexico. Transactions of the American Fisheries Society

119:537-544.

Beckman, D. W., A. L. Stanley, J. H. Render, and C. A. Wilson. 1991. Age and growth-rate

estimation of sheepshead Archosargus probatocephalus in Louisiana waters using otoliths. U.

S. National Marine Fisheries Service Fishery Bulletin 89:1-8.

Continental Shelf Associates. 1982. Study of the effect of oil and gas activities on reef fish

populations in Gulf of Mexico OCS area. U.S. Department of Interior, Minerals Management

Service, Gulf of Mexico OCS Region, OCS Report MMS 82-10, New Orleans, Louisiana.

Manooch, C. S., III, and J. C. Potts. 1997. Age and growth of red snapper, Lutjanus campechanus,

Lutjanidae, collected along the southeastern United States from North Carolina through the east

coast of Florida. Journal of the Elisha Mitchell Scientific Society 113:111-122.
279

Putt, R. E., Jr. 1982. A quantitative study of fish populations associated with a platform within

Buccaneer oil field, northwestern Gulf of Mexico. Master’s thesis. Texas A&M University,

College Station.

Render, J. H. 1995. The life history (age, growth, and reproduction) of red snapper (Lutjanus

campechanus) and its affinity for oil and gas platforms. Doctoral dissertation. Louisiana State

University, Baton Rouge.

Schirripa, M. J., and C. M. Legault. 1999. Status of the red snapper in U.S. waters of the Gulf of

Mexico: Updated through 1998. National Marine Fisheries Service, Southeast Fisheries Center,

Sustainable Fisheries Division, Contribution SFD-99/00-75, Miami, Florida. 

Stanley, D. R. 1994. Seasonal and spatial abundance and size distribution of fishes associated with

a petroleum platform in the northern Gulf of Mexico. Doctoral dissertation. Louisiana State

University, Baton Rouge.

Stanley, D. R., and C. A. Wilson. 1990. A fishery dependent based study of fish species composition

and associated catch rates around petroleum platforms off Louisiana. U. S. National Marine

Fisheries Service Fishery Bulletin 88:719-730.

Wilson, C. A., J. H. Render, and D. L. Nieland. 1998. Age and size distribution of commercially

harvested red snapper Lutjanus campechanus in the northern Gulf of Mexico. Final report for

1995-1997 to U. S. Department of Commerce, National Marine Fisheries Service, Marine

Fisheries Initiative (MARFIN), Cooperative Agreement NA17FF0383, St. Petersburg, Florida.

Wilson, C. A., and D. L. Nieland. In press. Age and growth of red snapper Lutjanus campechanus

in the northern Gulf of Mexico. U. S. National Marine Fisheries Service Fishery Bulletin.
281

SESSION 6: 

PRESENT AND FUTURE FISHERIES MANAGEMENT II

Moderators: Hal Osborne

Bob Shipp

Date: October 25, 2000

Presentation Author/Affiliation

The Attraction of Age-0 Red Snapper,

Lutjanus Campechanus, to Artificially

Placed Shell Plots Around Gas Platforms,

a Possible Solution to Bycatch Mortality

Stephen T. Szedlmayer

A Comprehensive Survey of Fishes of

Southwest Florida

George H. Burgess

Franklin F. Snelson, Jr.

David B. Snyder

Small Pelagics in the Gulf of Mexico: A

Description of the Abundance, Geographic

Distribution, Size, and Depth Distribution

of Major Pelagic Species

Jason S. Link

Terry A. Henwood

Christopher T. Gledhill

National Marine Fisheries Service

Distribution of Red Snapper Larvae in the

Northern Gulf of Mexico, 1982-1994

D.M. Drass

J. Lyczkowski-Schultz

P.J. Bond

National Marine Fisheries Service

Pascagoula, MS

Red Snapper Discards in Texas Coastal

Waters: A Fishery-Dependent Onboard

Survey of Recreational Headboat Discards

and Landings

Barbara Dorf

Texas Parks & Wildlife

Coastal Fisheries Division

Evaluation of Red Drum (Sciaenops

ocellatus) Stocking Success: GeneMarking of Fingerlings Released into East

Matagorda Bay, Texas

Rocky Ward

Ivonne R. Blandon

William J. Karel

Robert L. Colura

Lawrence W. McEachron

High Resolution of Gulf Sturgeon

Population Sturcture with Multilocus

Microsatellite DNA Genotypes

Tim L. King

Barbara A. Lubinski

Issac I. Wirgin
283

THE ATTRACTION OF AGE-0 RED SNAPPER, LUTJANUS CAMPECHANUS, TO

ARTIFICIALLY PLACED SHELL PLOTS AROUND GAS PLATFORMS,

A POSSIBLE SOLUTION TO BYCATCH MORTALITY

Stephen T. Szedlmayer

Marine Fish Laboratory

Department of Fisheries and Allied Aquacultures

Auburn University

ABSTRACT

In 1998 and 1999, we built 30 4m{+2} reefs of shell and 30 4m{+2} reefs of shell/concrete blocks

at depths of 17 to 21 m, in the Gulf of Mexico, 14 to 25 km south of Dauphin Island, Alabama. Each

year there were 3 sites, 20 reefs each, placed at 20 m intervals. Sites 1 and 2 were centered around

gas platforms. Total mean counts for all red snapper, Lutjanus campechanus, were significantly

different between reef types and years: 14 fish/block, 19 fish/shell in 1998; 20 fish/block, 22

fish/shell in 1999 (P < 0.05). Separated into age-0 and age-1 year classes, few age-0 red snapper

were observed in July, while age-1 were common. In August 1998, age-0 red snapper reached counts

up to 113 fish/reef and 216 fish/reef in August 1999. In 1998, age-0 fish were significantly more

abundant on shell reefs, but in 1999 age-0 fish showed no significant differences between reef types.

In 1998 and 1999, age-1 fish were significantly more abundant on block reefs. In 1998, fish were

significantly more abundant at Site 1, but in 1999 fish were significantly more abundant at Site 2.

These results suggest that artificial shell reefs may attract young red snapper away from areas of

intensive trawl fishing, e.g., gas platforms, thus enhancing survival.
284

A COMPREHENSIVE SURVEY OF FISHES OF SOUTHWEST FLORIDA

George H. Burgess

Florida Museum of Natural History

University of Florida

Franklin F. Snelson, Jr.

Department of Biology

University of Central Florida

David B. Snyder

Continental Shelf Associates

Jupiter, FL

ABSTRACT

Since 1975, we have sampled the ichthyofaunal community of southwest Florida. A wide variety

of habitats were sampled with diverse gear types. This material is vouchered at the Florida Museum

of Natural History (FLMNH). Additional comprehensive fish collections from the state of Florida

recently were transferred to the FLMNH, including the renowned University of Miami holdings and

those of Florida Atlantic University, University of Central Florida, and University of West Florida.

These materials, added to the already extensive collections held at FLMNH, which contains the

former Tropical Atlantic Biological Laboratory and Florida State University collections, constitute

the most complete specimen-based data source on past and present distribution of fishes in Florida

waters. We are in the process of assembling, verifying, and quantifying this database of all fishes

found in brackish and marine waters of the southeastern Gulf of Mexico, Florida Bay, Florida Keys,

and Dry Tortugas at depths to 350 fathoms.

The database currently documents more than 4000 stations spanning a period of 50 years. We have

verified the presence of 1031 fish species in 177 families in the study region, including species not

previously reported from United States continental waters. We plan to continue to verify identifications of existing materials and to update the database as new materials become available.

Eventually we will incorporate data from specimens housed in other museums as well as reliable

literature reports. The database will be incorporated into a GIS system for plotting distributions

relative to habitat type or environmental features. These data will allow a detailed analysis of the

biodiversity and distribution of all fishes in the region and will provide important information for

resource managers and governmental decision-makers. The data also will be converted to an archive

searchable from the web. Unlike most traditional survey results, specimen-supported data represent

a unique resource in that species identification is always verifiable and vouchered specimens

continually provide a rich source of historic life history and ecological information.
285

SMALL PELAGICS IN THE GULF OF MEXICO: A DESCRIPTION OF THE

ABUNDANCE, GEOGRAPHIC DISTRIBUTION, SIZE, AND DEPTH

DISTRIBUTION OF MAJOR PELAGIC SPECIES

Jason S. Link

Terry A. Henwood

Christopher T. Gledhill

National Marine Fisheries Service

Southeast Fisheries Science Center

ABSTRACT

In the 1980s, the National Marine Fisheries Service (NMFS) initiated a program to assess the

distribution and abundance of small, “coastal pelagic” fish within the Gulf of Mexico (GOM),

particularly those species whose range extends beyond the coverage of historical groundfish and

shrimp surveys. Many of the species comprising this pelagic species complex, such as butterfishes

(Stromateidae), herrings (Clupeidae), scads (Carangidae), and squids (Cephalopoda) were identified

as potentially underutilized species. After examining gear and techniques to capture fast-swimming,

schooling species in waters out to over 150 fathoms (278 m), standardized methods were developed.

The pelagic survey cruises spanned the entire GOM and were conducted from 1988 to 1996. Here

we present an analysis of the distribution, abundance, geographic range, catch frequency, and size

composition of the most common species collected during these surveys. This study sampled 911

stations, with mean catch rates of 11,910.8 individuals hr-1and 600.0 kg hr-1.. The top five organisms

collected in this study were gulf butterfish (Peprilus burti), round herring (Etrumeus teres),

longspine porgy (Stenotomus caprinus), rough scad (Trachurus lathami), and long-finned squid

(Loligo sp.). Species composition varied with geographic location in the GOM; as expected, the

eastern Gulf fish community was different from that of the western Gulf. These species are

significant components of the groundfish and shrimp fishery bycatch, but their distributions extend

beyond the range of the fishery into deeper offshore waters. Length frequency analysis demonstrated

that, in general, larger fish occurred in deeper waters. This finding suggests that deeper offshore

waters may serve as a refugia, especially for mature individuals. We briefly discuss the role of these

species in the fisheries of the GOM.

INTRODUCTION

In the early 1980s, the NMFS initiated a program to investigate the abundance and distribution of

a Gulf of Mexico species complex referred to as coastal pelagics. Interest in these species was

prompted by ichthyoplankton survey abundance estimates which suggested that annual potential

yield of these pelagic species in the GOM could exceed 5 million metric tons (Christmas et al. 1985,

Flandorfer & Skupien 1980, Houde 1977a, 1977b, 1977c). Many of the species comprising this

coastal pelagic complex, such as butterfishes (Stromateidae), herrings (Clupeidae), scads

(Carangidae), and squids (Cephalopoda), were identified as potentially underutilized species. The

distributional range of many of these species was suspected to extend well beyond the geographical
286

boundaries of the commercial shrimping grounds where most of NMFS trawling efforts were

concentrated. Thus, specific effort was focused at surveying this pelagic species complex.

Early efforts in this program centered around the development of fishing gear effective at capturing

these pelagic species. The use of standard shrimp/groundfish trawling gear and techniques (12.3 m

headrope length trawls towed at 3 kts over depths ranging from 9 to 95 m) was believed to be

inappropriate for capturing the schooling, fast-swimming pelagics. Trawling gear ranging in size

from 12.3 to 104.6 m headrope length (both bottom and midwater) was tested over the course of this

program. By the late 1980s, gear specialists had determined that large, high-opening trawls offered

the best potential for capturing these fish in deeper waters (Gledhill 1989, Reese 1993).

We provide a description of the major taxonomic groups comprising this pelagic species complex.

Our goal was to extend information on major species beyond the range historically surveyed for the

shrimp/groundfish community to deeper waters and to the eastern GOM where very little trawl

information exists. Because nearshore pelagics play a major role in the GOM fishery (e.g.

Brevoortia patronus , NMFS 1996), we wanted to examine the geographic and depth distribution,

abundance, and size of these species that may be considered as under-utilized resources, especially

since they comprise an important part of the GOM ecosystem. 

MATERIALS & METHODS

Trawling was done with a 27.5 m small pelagics trawl and a 37.5 m Shuman trawl from the NOAA

vessel Chapman. The small pelagics trawl measured 27.5 m on the headrope, had a mesh size from

20 cm at the front leading down to 5 cm at the cod end, had a fish funnel preceding the cod end, a

cod end containing a 0.4 to 2.2 cm mesh liner (varied by cruise), and was fished with 4.5 m2

 “W”

doors. The Shuman trawl measured 37.5 m on the headrope, had a mesh size from 80 cm at the front

to 3 cm at the cod end, had a fish funnel preceding the cod end, a cod end containing a 0.4 to 2.0 cm

liner (varied by cruise), and was fished with 4.0 m2 “Super V” doors.

Sampling designs were either stratified random, two dimensional systematic or systematic random,

spanned the entire GOM, and are discussed in greater detail elsewhere (Gledhill 1989, Reese 1993;

Table 6.1). Most trawls were approximately 30 minute tows, and total catch per unit effort was

standardized to one hour. The minimum and maximum station depths were 10 and 420 m

respectively. Only those trawls that were conducted during daylight hours and were on the bottom

were used in this study. Echograms from acoustic surveys have demonstrated that this species

complex forms compact schools proximal to bottom during daylight whereas they scatter throughout

the water column at night (Gledhill 1989, Reese 1993). Cruises associated with the pelagics program

that were related to gear development or that were directed sampling were also omitted from this

analysis. A comparison between the two types of gear was conducted with paired trawls in 1991.

The stations (26 pairs; Gledhill, unpubl. data) which compared the two gear exhibited no significant

differences in catch rates. Therefore, we do not distinguish between gear types in this analysis.

Once on board, the entire trawl catch was weighed and then subsampled if the catch was greater than

150 kg. Subsamples (or the entire catch if less than 150 kg) were sorted, identified to the lowest
287

Table 6.1. Summary of trawling effort for this study. Latitudes and longitudes are in degrees and

minutes North and West respectively. Gear size is the headrope length, in meters, of the

trawl. SysRdm=systematic random, 2DSys=two-dimensional systematic, StratRdm=

stratified random.

Year 88 89 90 91 92 93 94 95 96

Cruise 88-03 89-04 90-02,90-03 91-01 92-01 93-03 94-02 95-07 96-06

Months 3,4 8,9 3,4,5 1,2 3,4 3,4 3,4 10,11 10,11

Survey Design SysRdm StratRdm SysRdm,2DSys StratRdm SysRdm SysRdm SysRdm StratRdm StratRdm

Cruise 88-08 89-05 90-08 -- 92-06 93-07 -- -- --

Months 10,11 10,11 10,11 -- 10,11 10,11 -- -- --

Survey Design 2DSys SysRdm SysRdm -- SysRdm SysRdm -- -- --

Total # Stations 154 65 118 53 123 158 81 67 92

Max Latitude 30o

59.46' 29o58.48' 30o59.90' 29o59.48' 30o59.84' 29o59.79' 30o59.60' 30o58.12' 29o59.48'

Min Latitude 27o

00.09' 27o00.92' 27o00.15' 29o35.44' 27o00.45' 26o00.01' 27o00.00' 27o00.97' 26o00.41'

Max Longitude 96o

59.95' 91o59.48' 94o58.92' 87o48.58' 93o56.85' 97o59.90' 91o58.50' 97o57.79' 97o59.11'

Min Longitude 83o

00.09' 85o02.69' 85o01.73' 86o19.54' 82o00.30' 88o01.00' 83o00.40' 84o01.83' 84o00.26'

Gear Size 37.5 37.5 37.5 37.5,27.5 27.5,37.5 27.5,37.5 27.5 27.5 27.5

taxon feasible, enumerated, weighed, and measured to the nearest mm following standard NMFS

and South East Area Monitoring and Assessment Program (SEAMAP) protocols.

A total of 15 cruises were conducted from 1988 to 1996, primarily during spring and fall (Table 6.1).

These data are highly unbalanced both spatially and temporally (Table 6.1) due to fiscal constraints,

varying cruise objectives, temporal constraints, mechanical difficulties, and similar logistical

considerations. We present arithmetic means (+/- standard error) of catch per unit effort (number

hour-1) across depths and geographic zones. The GOM geographic zones, which roughly correspond

to SEAMAP faunal zones, were arbitrarily assigned along a longitudinal gradient to partition the

GOM from west to east, distinguishing the Texas Shelf, Louisiana shelf, Mississippi River region,

DeSoto Canyon region, and Florida Shelf. We also examined length frequency distributions (cm)

across depths and zones in the GOM.

RESULTS

There were 911 stations sampled in this study, with a mean total catch of 11,910.8 individuals hr-1

and 600.0 kg hr-1. In total, there were 493 taxa collected in this study. The top five most abundant

species in the small pelagic species complex were gulf butterfish (Peprilus burti), round herring

(Etrumeus teres), longspine porgy (Stenotomus caprinus), rough scad (Trachurus lathami), and

long-finned squid (Loligo sp.) (Table 6.2). The first 20 species accounted for more than 90% of the

individuals and more than 85% of the biomass collected during this program. Other clupeids,
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Table 6.2. Summary of mean CPUE (No./hr, kg/hr) of the major fish in the coastal pelagics

complex.

Mean % of Mean % of # %

Species Common Name No./hr Total Kg/hr Total Stations Frequency Rank

Peprilus burti Gulf Butterfish 2550.3 21.4 189.6 31.6 554 60.8 1

Etrumeus teres Round Herring 1852.8 15.6 38.16 6.4 348 38.2 2

Stenotomus caprinus Longspine Porgy 1554.0 13.0 64.32 10.7 473 51.9 3

Trachurus lathami Rough Scad 1369.2 11.5 76.10 12.7 618 67.8 4

Loligo sp. Longfin Squid 472.59 3.7 9.02 1.5 754 82.8 5

Steindachneria argenta Luminous Hake 385.81 3.2 4.71 0.79 94 10.3 6

Decapterus punctatus Round Scad 316.28 2.7 14.28 2.4 77 8.5 7

Trichiurus lepturus Atlantic Cutlassfish 315.05 2.6 21.84 3.6 347 38.1 8

Diaphus sp. Lanternfish 303.48 2.5 0.816 0.14 62 6.8 9

Chloroscombrus chrysurus Atlantic Bumper 287.98 2.4 17.66 2.9 131 14.4 10

Engraulis eurystole Silver Anchovy 272.45 2.3 0.549 0.092 14 1.5 11

Scomber japonicus Chub Mackerel 262.42 2.2 24.63 4.1 261 28.6 12

Sardinella aurita Spanish Sardine 224.24 1.9 9.26 1.5 43 4.7 13

Anchoa hepsetus Striped Anchovy 170.59 1.4 2.29 0.38 46 5.0 14

Micropogonias undulatus Atlantic Croaker 142.40 1.2 10.41 1.7 140 15.4 15

Parapenaeus sp. Shrimp 101.67 0.85 0.118 0.020 39 4.3 16

Polymixia lowei Beardfish 94.81 0.80 1.88 0.31 74 8.1 17

Lagodon rhomboides Pinfish 93.44 0.78 7.88 1.3 253 27.8 18

Pristipomoides aquilonaris Wenchman 92.17 0.77 11.70 1.9 399 43.8 19

Ariomma bondi Silver Rag 73.08 0.61 5.43 0.91 181 19.9 20

Upeneus parvus Dwarf Goatfish 70.11 0.59 2.40 0.40 242 26.6 21

Mullus auratus Red Goatfish 64.45 0.54 4.16 0.69 140 15.4 22

Trachypeneus sp. Shrimp 62.89 0.53 0.0858 0.014 16 1.8 23

Leiostomus xanthurus Spot 60.19 0.51 6.87 1.1 73 8 24

Macrorhampuhosus scolopax Longspine Snipefish 44.96 0.38 0.144 0.024 26 2.9 25

Anchoa mitchilli Bay Anchovy 40.13 0.34 0.230 0.038 11 1.21 26

Clupeidae Herrings 35.58 0.30 0.004 0.001 1 0.11 27

Saurida brasiliensis Largescale Lizardfish 34.70 0.29 0.608 0.101 100 10.98 28

Caridea Unclassified Shrimp 29.09 0.24 0.027 0.005 10 1.10 29
289

Table 6.2. (continued)

Mean % of Mean % of # %

Species Common Name No./hr Total Kg/hr Total Stations Frequency Rank

Cynoscion arenarius Sand Seatrout 25.60 0.21 3.053 0.509 156 17.12 30

Unid. Fish - 23.48 0.20 0.006 0.001 5 0.55 31

Peprilus alepidotus Harvestfish 20.60 0.17 7.839 1.306 107 11.75 32

Lolliguncula brevis Breif Squid 18.44 0.15 0.099 0.016 26 2.85 33

Harengula jaguana Scaled Sardine 17.74 0.15 0.823 0.137 48 5.27 34

Synodus foetens Inshore Lizardfish 17.73 0.15 2.536 0.423 158 17.34 35

Abralia veranyi Abralia Squid 17.02 0.14 0.062 0.010 58 6.37 36

Opisthonema oglinum Atlantic Thread Herring 16.48 0.14 1.122 0.187 47 5.16 37

Maurolicus muelleri Atlantic Pearlside 15.55 0.13 0.025 0.004 23 2.52 38

Cynoscion nothus Silver Seatrout 14.58 0.12 1.180 0.197 66 7.24 39

Rhomboplites aurorubens Vermilion Snapper 14.27 0.12 1.628 0.271 85 9.33 40

carangids, scombrids, engraulids, sparids, sciaenids, and gadids were the major organisms

comprising this pelagic species complex. For more specific parameters of these major families, see

Appendix A.

Distribution in the Gulf 

Many of the major species were ubiquitous throughout the GOM. P. burti, E. teres, T. lathami,

Loligo sp., and S. japonicus all occurred in most regions of the Gulf (Figures 6.4–6.5; Table 6.3).

P. burti was most abundant in the central GOM, but was widspread throughout the entire Gulf

(Table 6.3, Figure 6.1). E. teres was most abundant in zones 1 and 4, but was also common across

the entire GOM (Table 6.3, Figure 6.2). T. lathami was similarly most abundant in the central GOM

and was widespread across the GOM (Table 6.3, Figure 6.3). Both Loligo sp. and S. japonicus

showed no major difference in abundance between regions in the GOM (Figure 6.4 and 6.5). The

frequency of occurrence of Loligo sp. was the highest of any species in this study (Table 6.2). Other

species that were widely distributed were Lagodon rhomboides and Leiostomus xanthu, among

others (Table 6.4).

S. caprinus, C. chrysurus, and E. eurystole occurred throughout the entire GOM but were more

abundant in the western Gulf than other regions (Figures 6.6–6.8). S. caprinus was abundant in all

regions except zone 5 (Table 6.3, Figure 6.6). C. chrysurus and E. eurystole were most abundant in

zones 1 and 2 (Figures 6.7 and 6.8). Other species that occurred most frequently in the western

GOM were Selene setapinnis, Peprilus alepidotus, and Pristipomoides aquilonaris, among others

(Table 6.4).
Figure 6.1. The occurrence of Peprilus burti at the stations sampled in this study. Solid circles indicate presence o

open circles indicate that a sample was taken but this squid was not present at that station. The zones (to regions of the GOM, from west to east, that have roughly geographic similarities and are to assist wacross the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m depth contoapproximately denoting the continental shelf region.
Figure 6.2. The occurrence of Etrumeus teres at the stations sampled in this study. Solid circles indicate presence 

open circles indicate that a sample was taken but this squid was not present at that station. The zones to regions of the GOM, from west to east, that have roughly geographic similarities and are to assist wacross the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m depth contoapproximately denoting the continental shelf region.
Figure 6.3. The occurrence of Trachurus lathami at the stations sampled in this study. Solid circles indicate prese

species; open circles indicate that a sample was taken but this squid was not present at that station. Thcorrespond to regions of the GOM, from west to east, that have roughly geographic similarities and arsynthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m dapproximately denoting the continental shelf region.
Figure 6.4. The occurrence of Loligo sp. at the stations sampled in this study. Solid circles indicate presence of th

circles indicate that a sample was taken but this squid was not present at that station. The zones (1-5) regions of the GOM, from west to east, that have roughly geographic similarities and are to assist with across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m depth contoapproximately denoting the continental shelf region.
Figure 6.5. The occurrence of Scomber japonicus at the stations sampled in this study. Solid circles indicate prese

species; open circles indicate that a sample was taken but this squid was not present at that station. Thcorrespond to regions of the GOM, from west to east, that have roughly geographic similarities and arsynthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m dapproximately denoting the continental shelf region.
295

Table 6.3. Mean (+/- S.E.,in No. hr-1) of these species in each GOMEX zone. S.E.=std. error,

n=sample size.

Zone 1 2 3 4 5

n 171 180 244 265 51

P. burti 727.3 

(161.3)

2515.9 

(542.1)

3646.1 

(1003.8)

3213.2

 (594.6)

97.5

 (51.7)

E. teres 3047.5 

(1493.0)

642.3 

(254.4)

613.6

 (195.4)

3273.3

 (579.8)

667.4

 (323.5)

S. caprinus 1309.2

(270.60

1539.4

(215.2)

1698.3

(544.5)

1887.1

(470.9)

4.7

(1.8)

T. lathami 627.7 

(120.4)

833.5 

(185.0)

1256.8

 (303.9)

2433.9

 (486.5)

751.2

 (251.5)

Loligo sp. 435.52 

(50.557)

363.103 

(48.956)

375.03

 (56.968)

732.14 

(159.66)

101.49 

(20.137)

S. argenta 0.13

(0.13)

0.1

(0.07)

1407.2

(345.6)

30.5

(12.3)

0

D. punctatus 7.9 

(3.3)

4.3 

(3.2)

18.5

 (9.7)

197.2 

(92.1)

4494.9 

(2226.5)

T. lepturus 57.8

(23.0)

358.1

(77.6)

794.4

(161.1)

71.1

(35.6)

0

Diaphus sp. 2.3

(2.3)

2.0

(1.3)

129.7

(61.7)

671.7

(357.3)

0

C. crysurus 637.9 

(229.7)

466.8 

(242.3)

282.7

 (132.9)

1.0

 (0.4)

0

E. eurystole 11.3

(10.1)

1357.7

(1102.2)

7.7

(7.7)

0 0

S. japonicus 107.7

(40.4)

58.7

(44.3)

489.8

(192.5)

312.0

(99.2)

154.5

(63.8)

S. aurita 1.65 

(1.02)

1.86 

(1.11)

2.67 

(1.75)

260.8 

(214.4)

2625.5

 (1243.0)

A. hepsetus 6.9

(3.1)

56.0

(27.9)

590.6

(291.5)

0.06

(0.06)

0

M. undulatus 6.9

(3.2)

163.8

(85.3)

404.7

(116.1)

1.2

(0.7)

0
296

Table 6.4. Species with the most biomass or most occurrences predominating in the different

regions.

Abundant Species Rarer Species

West GOM West GOM

Stenotomus caprinus

Chloroscombus chrysurus

Engraulis eurystole

Selene setapinnis

Pristipomoides aquilonaris

Upeneus parvus

Peprilus alepidotus

Lagocephalus laevigatus

Central GOM Central GOM

Steindachneria argentea

Trichiurus lepturus

Diaphus sp.

Anchoa hepsetus

Micropogonias undulatus

Polymixia lowei

Anchoa mitchilli

Caranx crysos

Lolliguncula brevis

Abralia veranyi

Cynoscion nothus

Cynoscion arenarius

Pontinus longispinis

Eastern GOM Eastern GOM

Decapturus punctatus

Sardinella aurita

Mullus auratus

Rhomboplites aurorubens

Saurida normani

Widespread Widespread

Etrumeus teres

Loligo sp.

Trachurus lathami

Peprilus burti

Scomber japonicus

Lagodon rhomboides

Leiostomus xanthu

Saurida brasilia

Maurolicus muelleri

Synodus foetens

Ariomma bondi

Synagrops bella

Synagrops spinosus
Figure 6.6 The occurrence of Stenotomus caprinus at the stations sampled in this study. Solid circles indicate pre

species; open circles indicate that a sample was taken but this squid was not present at that station. Thcorrespond to regions of the GOM, from west to east, that have roughly geographic similarities and arsynthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m deapproximately denoting the continental shelf region.
Figure 6.7. The occurrence of Chloroscombrus chrysurus at the stations sampled in this study. Solid circles indic

this species; open circles indicate that a sample was taken but this squid was not present at that station5) correspond to regions of the GOM, from west to east, that have roughly geographic similarities and with synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 contour, approximately denoting the continental shelf region.
Figure 6.8. The occurrence of Engraulis eurystole at the stations sampled in this study. Solid circles indicate pres

species; open circles indicate that a sample was taken but this squid was not present at that station. Thcorrespond to regions of the GOM, from west to east, that have roughly geographic similarities and arsynthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m dapproximately denoting the continental shelf region.
300

D. punctatus and S. aurita were most common in the eastern GOM (Figures 6.9 and 6.10). Both had

their highest abundance in zone 5, with abundances there two to three orders of magnitude greater

than in the rest of the GOM (Table 6.3). Other species that occurred predominantly in the eastern

Gulf were Rhomboplites aurorubens and Saurida normani (Table 6.4).

 The remaining pelagics were most abundant in the central GOM (Figures 6.11–6.15). Diaphus sp.,

A. hepsetus, and S. argentea had a narrow distribution and were not observed in zones 1 and 5

(Figures 6.11–6.13). T. lepturus and M. undulatus similarly were not observed in zone 5, but did

have a broader distribution. All five of these species were most abundant in zone 3 (Table 6.3).

Many other species occurred predominately in the central GOM, including Caranx crysos,

Cynoscion nothus and Cynoscion arenarius (Table 6.4). This was the region with the greatest

biomass and number of fish in the GOM.

Depth Gradients in the Gulf

Loligo sp. and S. japonicus were unique organisms in that they exhibited no peak abundance at a

particular depth (Table 6.5). Both were common throughout the GOM, and occurred on either side

of the shelf slope with regularity (Figures 6.4 and 6.5). Synodus foetens also exhibited no distinct

depth preference (Table 6.6).

Practically all clupeids, all engraulids, most sparids, and most scianids were shallow-water species,

abundant at depths < 50 m (Table 6.5). Many of the species in this study were concentrated at these

depths (Table 6.6). However, some of these shallow water species also occurred at notable levels

of abundance out to depths of 150 m.

Three of the top four most abundant species in this study were most common beyond the range of

normal groundfish and shrimp surveys (Table 6.5). E. teres, P. burti, and T. lathami were most

abundant at depths of 100-200 m. The greatest number and biomass of all pelagics was concentrated

in the 100-150 m depth range.

Diaphus sp. and S. argentea were clearly deep-water species (Table 6.5). The greatest abundance

of each species was over 300 and 200 m respectively. The abundance of Diaphus sp. was two to

three orders of magnitude higher at depths > 200 m than at other depths. Both these species were

concentrated on the abyssal side of the continental slope (Figures 6.11 and 6.13). Other deep-water

species included Ariomma bondi, Illex sp., and Synagrops sp., among others (Table 6.6). Other than

these few examples, most species were rare beyond 200 m.

Length

Mean length for all species was 14 cm. The largest fish we sampled was rough scad (Table 6.7) but

many of the species were frequently less than 10 mm. Very few species averaged individual weights

> 100 g. Although abundant, most of these organisms were not large.

Several of the species were only sampled at depths < 100 m (Table 6.5) and exhibited no notable

change in size across depth (Figures 6.16–6.20). S. aurita (Figure 6.16), C. chrysurus (Figure 6.17)
Figure 6.9. The occurrence of Decapterus punctatus at the stations sampled in this study. Solid circles indicate pr

species; open circles indicate that a sample was taken but this squid was not present at that station. Thcorrespond to regions of the GOM, from west to east, that have roughly geographic similarities and arsynthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the 100 m dapproximately denoting the continental shelf region.
Figure 6.10. The occurrence of Sardinella aurita at the stations sampled in this study. Solid circles indicate pre

species; open circles indicate that a sample was taken but this squid was not present at that station. 5) correspond to regions of the GOM, from west to east, that have roughly geographic similarities with synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the contour, approximately denoting the continental shelf region.
Figure 6.11. The occurrence of Diaphus sp. at the stations sampled in this study. Solid circles indicate presence 

open circles indicate that a sample was taken but this squid was not present at that station. The zoncorrespond to regions of the GOM, from west to east, that have roughly geographic similarities anwith synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the contour, approximately denoting the continental shelf region.
Figure 6.12. The occurrence of Anchoa hepsetus at the stations sampled in this study. Solid circles indicate pre

species; open circles indicate that a sample was taken but this squid was not present at that station5) correspond to regions of the GOM, from west to east, that have roughly geographic similarities with synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the contour, approximately denoting the continental shelf region.
Figure 6.13. The occurrence of Steindachneria argenta at the stations sampled in this study. Solid circles indic

this species; open circles indicate that a sample was taken but this squid was not present at that sta(1-5) correspond to regions of the GOM, from west to east, that have roughly geographic similaritassist with synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line depth contour, approximately denoting the continental shelf region.
Figure 6.14. The occurrence of Trichiurus lepturus at the stations sampled in this study. Solid circles indicate p

species; open circles indicate that a sample was taken but this squid was not present at that station5) correspond to regions of the GOM, from west to east, that have roughly geographic similarities with synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solid line is the contour, approximately denoting the continental shelf region.
Figure 6.15. The occurrence of Micropogonias undulatus at the stations sampled in this study. Solid circles ind

of this species; open circles indicate that a sample was taken but this squid was not present at that zones (1-5) correspond to regions of the GOM, from west to east, that have roughly geographic simare to assist with synthesis across the broad geographic scale of the GOM (c.f. Table 6.1). The solm depth contour, approximately denoting the continental shelf region.
308

Table 6.5. Mean catch (+/- S.E., in No. hr-1) of squid across depth (m) strata. S.E.=standard error,

n=sample size.

Depth 0-50 50-100 100-150 150-200 200-250 250-300 300+

n 216 249 183 118 72 54 19

P. burti 1033.5 

(311.4)

2001.0

 (376.9)

7701.5 

(1495.4)

1518.3

 (358.2)

180.0 

(82.7)

6.8 

(3.4)

0

E. teres 642.2 

(202.6)

1972.6 

(1014.9)

4190.5

 (767.7)

2341.0

 (731.6)

206.6 

(140.8)

0.778 

(0.604)

0

S. caprinus 2996.9 

(648.9)

2015.7

 (298.4)

1405.1

 (566.1)

78.8

 (55.3)

0.05

 (0.05)

0 0

T. lathami 441.7 

(134.1)

1326.0

 (321.1)

3345.18

 (664.5)

1455.7 

(270.0)

509.4 

(193.4)

17.7 

(7.9)

10.8

 (10.7)

Loligo sp. 676.86 

(170.33)

376.80 

(56.087)

334.81 

(91.654)

598.19 

(137.45)

670.24 

(89.814)

179.83 

(48.443)

35.789 

(15.261)

S. argenta 0.5 

(0.5)

103.6 

(50.8)

420.0

 (176.0)

827.7

 (385.4)

1723.7

(880.2)

396.2

(100.7)

290.6

(113.5)

D. punctatus 1169.8 

(540.3)

142.3 

(79.6)

0.12

 (0.12)

0000

T. lepturus 168.2 

(44.3)

658.0 

(136.8)

237.2

 (70.2)

260.5

 (169.3)

141.3

(121.5)

46.4

(21.7)

0.74

(0.51)

Diaphus sp. 0.35 

(0.35)

18.7

 (18.7)

2.5

 (1.7)

23.8

 (22.5)

166.6

(112.0)

2162.2

(1642.1)

3877.4

(1653.2)

C. crysurus 941.0 

(281.5)

237.2 

(107.6)

0.13 

(0.08)

0000

E. eurystole 1111.1 

(918.1)

32.9

 (32.2)

00000

S. japonicus 173.0 

(140.9)

101.7

 (39.2)

548.1 

(194.4)

234.7 

(115.9)

313.6 476.1

(396.0)

4.8

(4.0)

S. aurita 937.5 

(397.5)

7.14

 (3.49)

0.033

 (0.328)

0000

A. hepsetus 702.5 

(329.3)

14.7

 (11.1)

00000

M. undulatus 243.8 

(98.6)

223.1

 (86.8)

117.6

 (63.5)

0000
309

Table 6.6. Species with biomass or occurrence predominant at the different depths. Shallow <100m,

Mid-Depth=100-200m, Deep>200m, Widespread=all depths.

Abundant Species Rarer Species

Shallow Shallow

Stenotomus caprinus

Decapterus punctatus

Trichiurus lepturus

Chloroscombus chrysurus

Engraulis eurystole

Sardinella aurita

Anchoa hepsetus

Micropogonias undulatus

Leiostomus xanthu

Lagodon rhomboides

Lolliguncula brevis

Upeneus sp.

Upeneus parvus

Mullus auratu

Saurida brasilia

Lagocephalus laevigatus

all Clupeids

all Engrualids

most Sparids

most Scianids

Mid-Depth Mid-Depth

Etrumeus teres

Peprilus burti

Trachurus lathami

Abralia veranyi

Saurida normani

Pristipomoides aquilonaris

Deep Deep

Steindacneria argentea

Diaphus sp.

Polymixia lowei

Illex sp.

Ariomma bondi

Synagrops bella

Synagrops spinosus

Mauolicus muelleri

Pontinus longispinis

Widespread Widespread

Loligo sp.

Scomber japonicus

Synodus foetens
310

Table 6.7. Mean length (cm) and weight (g) of major pelagic species.

Species Comman Name Mean Length

(cm)

Min

Length

Max

Length

Mean Wt.

(g)

Peprilus burti Gulf Butterfish 14.1 2.0 26.6 74

Etrumeus teres Round Herring 13.2 2.3 51.2 21

Stenotomus caprinus Longspine Porgy 12.0 0.2 20.8 41

Trachurus lathami Rough Scad 15.3 0.4 75.8 56

Loligo sp. Longfin Squid 7.3 6.0 37.2 20

Steindachneria argenta Luminous Hake 14.4 1.2 30.5 12

Decapterus punctatus Round Scad 14.8 4.8 21.9 45

Trichiurus lepturus Atlantic Cutlassfish 16.7 2.0 53.1 69

Diaphus sp. Lanternfish 5.4 2.3 8.9 2

Chloroscombrus chrysurus Atlantic Bumper 14.3 1.6 31.8 61

Engraulis eurystole Silver Anchovy 6.9 2.1 12.4 2

Scomber japonicus Chub Mackerel 20.0 3.0 35.0 94

Sardinella aurita Spanish Sardine 14.7 8.8 22.0 41

Anchoa hepsetus Striped Anchovy 11.3 4.1 17.8 13

Micropogonias undulatus Atlantic Croaker 18.6 1.6 50.5 73

Parapenaeus sp. Shrimp - - - <1

Polymixia lowei Beardfish 11.3 6.5 42..5 20

Lagodon rhomboides Pinfish 16.0 9.1 46.5 84

Pristipomoides aquilonaris Wenchman 16.3 0.2 29.8 127

Ariomma bondi Silver Rag 16.4 5.3 21.3 74

Upeneus parvus Dwarf Goatfish 12.0 2.6 24.0 34

Mullus auratus Red Goatfish 15.2 2.8 28.5 65

Trachypeneus sp. Shrimp - - - <1

Leiostomus xanthurus Spot 19.9 11.1 30.0 114

Macrorhampuhosus scolopax Longspine Snipefish 10.4 6.5 14.5 3

Anchoa mitchilli Bay Anchovy 5.5 3.6 8.3 6

Clupeidae Herrings - - - -

Saurida brasiliensis Largescale Lizardfish 8.5 0.7 39.5 24

Caridea Unclassified Shrimp - - - <1

Cynoscion arenarius Sand Seatrout 22.7 6.6 40.9 119
311

Figure 6.16. Length frequency distribution of S. aurita across the depth strata in this study. Depth

zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-100

m, etc).

Table 6.7. (continued)

Species Comman Name Mean Length

(cm)

Min

Length

Max

Length

Mean Wt.

(g)

Unid. Fish - - - - -

Peprilus alepidotus Harvestfish 14.8 2.5 20.0 381

Lolliguncula brevis Breif Squid 3.6 1.2 18.5 5

Harengula jaguana Scaled Sardine 13.3 6.7 20.3 46

Synodus foetens Inshore Lizardfish 24.9 5.3 44.6 158

Abralia veranyi Abralia Squid 3.4 0.9 13.6 4

Opisthonema oglinum Atlantic Thread Herring 15.8 3.4 29.8 68

Maurolicus muelleri Atlantic Pearlside 4.6 2.8 5.8 2

Cynoscion nothus Silver Seatrout 20.2 7.2 41.4 81

Rhomboplites aurorubens Vermilion Snapper 17.9 0.2 33.5 114
312

Figure 6.17. Length frequency distribution of C. chrysurus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.18. Length frequency distribution of D. punctatus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).
313

Figure 6.19. Length frequency distribution of A. hepsetus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.20. Length frequency distribution of E. eurystole across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).
314

and D. punctatus (Figure 6.18) showed a bimodal length distribution at shallower depths (< 50 m),

but only a unimodal distribution (no smaller mode) at 50-100 m. A. hepsetus (Figure 6.19) and E.

eurystole (Figure 6.20) exhibited effectively a unimodal distribution.Diaphus sp., S. caprinus, and

Loligo sp. were present at a wide range of depths (Table 6.5), but showed no differences in size

across depth (Figures 6.21–6.23). All three species were unimodal, but Loligo sp. did have a broad

size distribution.

P. burti was also present at a wide range of depths, but showed a subtle increase in size at greater

depths (Figure 6.24). Similarly, M. undulatus, E. teres, T. lepturus, T. lathami, S. japonicus, and S.

argentea (Figures 6.25–6.30) showed notable increases in length at greater depths. P. burti, M.

undulatus, and E. teres were unimodal, whereas the remaining four species were bimodal, with the

smaller mode generally more frequent at shallower depths.

DISCUSSION

Many of these pelagic species are broadly distributed across numerous ecosystems (e.g. Costa &

Fernandes 1993, Crawford and de Villiers 1984, Dawe et al. 1990, Grant 1981, Haimovici et al.

1996, Haimovici et al. 1994, Novikov 1986, Pierce & Guerra 1994, Reintjes 1980, Rountree 1990,

Scoles et al. 1998, Whitaker 1980,Whitehead 1985, Xu & Chiu 1995). In fact, several of these

species are cosmopolitan, with broad distributions across the Caribbean Sea, Mediterranean Sea,

northern and southern Pacific, northern and southern Atlantic, and Indian Ocean. Thus, it is not

surprising that several of these species (e.g. T. lathami, S. japonicus, E. teres, Loligo sp., etc.) are

widely distributed in the GOM. These results generally concur with prior studies of GOM pelagics

(e.g. Geoghegan and Chittenden 1982, Gledhill 1989, Hixon 1980, Houde 1977a, 1977b, 1977c,

Murphy and Chittenden 1991, Nakumrua 1980, Reintjes 1980, Salcedo-Vargas 1991, Shaw and

Drullinger 1990, Voss and Brackoniecki 1985). The pelagic fish and squid assemblage across the

different regions of the Gulf are very similar, distinguished only by a few species that inhabit certain

locations or depths of the Gulf.

Why are some species centered in the eastern or western Gulf? We readily admit that our sampling

may have missed the occurrence of some species, particularly in the eastern GOM, due to low

sample sizes or seasonal migrations. Given that possibility, we assert that the most prominent

patterns observed for some of these organisms are likely more than artifact due to the persistent

occurrence of certain species in certain regions year after year across multiple seasons. For instance,

C. chrysurus is not present east of the DeSoto Canyon region (zone 4). Conversely, although present,

S. aurita is not abundant west of the DeSoto Canyon region. Similar examples exist for other species

(e.g. E. eurystole in the western Gulf and D. punctatus in the eastern Gulf; Table 6.4). Therefore,

the Mississippi River/Mobile Bay physio-chemical environment appears to be a distinct biological

barrier for some of these species. For example, salinity tolerances for clupeid larvae such as H.

jaguana and O. oglinum are much lower than for S. aurita (Shaw & Drullinger 1990); hence we

rarely observe the latter two species far from the Mississippi River region. Additionally, Economidis

& Vogiatzis (1992) have documented a temperature induced fish kill of S. aurita in the

Mediterranean. Thus, the distribution of these clupeids may be a function of the lower salinities and

temperatures associated with the northern GOM. Other studies have demonstrated relationships

between environmental factors such as salinity, temperature, thermocline depth, frontal boundaries
315

Figure 6.21. Length frequency distribution of Diaphus sp. across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.22. Length frequency distribution of S. caprinus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).
316

Figure 6.23. Length frequency distribution of Loligo sp. across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.24. Length frequency distribution of P. burti across the depth strata in this study. Depth

zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-100

m, etc.).
317

Figure 6.25. Length frequency distribution of M. undulatus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.26. Length frequency distribution of E. teres across the depth strata in this study. Depth

zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-100

m, etc.).
318

Figure 6.27. Length frequency distribution of T. lepturus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.28. Length frequency distribution of T. lathami across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).
319

Figure 6.29. Length frequency distribution of S. japonicus across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).

Figure 6.30. Length frequency distribution of S. argentea across the depth strata in this study.

Depth zones are represented as the midpoint of the strata (e.g. 25 is 0-50 m, 75 is 50-

100 m, etc.).
320

and oxygen with the distribution of many of the species in this study (e.g. Hendrix et al. 1981,

Herron et al. 1989, Holliday and Larsen 1979, Laughlin & Livingston 1982, Matthews & Allen

1993, Novikov 1986, Vecchione 1991). Additionally, why is the majority of pelagic biomass and

abundance concentrated near the Mississippi River delta? Very simply, the river plume and Loop

Current combine to focus primary and secondary production at this locale (reviewed in Lohrenz et

al. 1999). Several of the pelagic species are aggregated around these physical features and areas of

high productivity (sensu Herron et al. 1989, Holliday and Larsen 1979).

Many of these pelagic species are concentrated on the more productive continental shelf.

Collectively, the clupeids, engraulids, sparids, and scianids are generally shallow water species and,

with a few exceptions, are effectively not a member of the pelagic species complex deeper than 100

m in the GOM. When caught, these fish are abundant, especially at depths < 25 m. Thus, it is likely

that this group of fish is adequately sampled with the historical groundfish survey (SEFSC, MS

Labs, unpubl. data). However, size overlap between the two surveys may be different due to the lack

of deep water fishes collected in the groundfish survey and the larger size of E. teres at greater

depths. Additionally, schools of herrings, squids, anchovies, porgies and sardines are likely to be

captured more efficiently with the high opening (ca. 15 m) nets used in this study than the lower

profile (ca. 3 m) nets in the groundfish surveys. Thus the small pelagics survey can provide more

representative sampling of these stochastically distributed, schooling fish.

There are several deepwater and mid-depth species that are common in this pelagic community.

Diaphus sp., S. argentea, A. bondi, Illex sp., P. lowei, and M. muelleri are most abuandant at depths

> 200 m and characterize the deepwater pelagic assemblage in the GOM. More notably, E. teres,

P. burti, T. lathami, Loligo sp., S. japonicus and A. veranyi are most abundant at depths > 100 m.

Previous reports have documented similar depth distributions of these and similar species along the

continental shelf slope in the GOM and other ecosystems (e.g. Agafonova and Bukamin 1984, Bullis

et al. 1971, Costa & Fernandes 1993, Gartner et al. 1987, Haimovici & Perez, 1991, Haimovici et

al. 1994, Klima 1971, May and Blaber 1989, Vecchione 1987, Watanabe et al. 1999, Whitehead

1985). Because most of the pelagic community biomass occurs at depths beyond 100 m, these

species are likely missed in other surveys. The importance of the shelf-break pelagic community,

particularly in terms of alternate or potential fishery yields, Gulfwide fish production, and forage

base available for higher trophic levels is hence under appreciated.

Several species were larger at greater depths. Certainly some species do not extend beyond 100 m,

but even some of the shallow water species exhibited an increase in size with depth. It is likely that

these deeper waters serve as a refugia from nearshore predators, including human harvesting, for

larger individuals. It is probable that much of the spawning stock biomass for many of these species

resides in this refugia. It is unclear what the population-level ramifications will be for increased

removal of these offshore, deepwater organisms.

The organisms that did not exhibit any change in size either 1) had a limited depth range, 2) were

mixed species (e.g. Loligo sp., Diaphus sp.), or 3) had little separation between the size of different

year classes. The differences in Loligo size across depth may be the differences noted by Hixon

(1980) between the two species, with the larger L. pealei in deeper waters. Also, many of the

organisms in this study have broad spawning periods (e.g. Brodziak & Macy 1996, Houde 1977a,
321

1977b, 1977c, Jereb & Ragonese 1995, Johnson & Vaught 1986, Pierce & Guerra 1994, Shaw &

Drullinger 1990). Such broad spawning periods produce year classes with a broad range of lengths.

Additionally, these species mature at relatively small sizes and young ages and often have short life

spans (e.g. Brodziak & Macy 1996, Hixon et al. 1981, Houde 1977a, Jereb & Ragonese 1995,

Martinez & Houde 1975, Reintjes 1980). These considerations might mask year class strengths and

produce length frequency distributions that are bi- or unimodal, which is what we observed for the

all of the species in this study. 

There are small, silverish, fusiform, pelagic species in every aquatic ecosystem on the planet. The

sheer abundance of these small pelagics makes them an important component of intermediate

trophic levels in every ecosystem. The mean length and low individual weight make these the major

forage base for many other species. Charismatic megafauna and commercially valuable piscivores

(e.g. numerous marine mammals, scombrids such as tunas and mackerels, coryphaenids, xiphids,

etc.) prey upon these fish and squid (e.g. Bello 1991, DeVane 1978, Gonzalez et al. 1994, Naughton

& Saloman 1981, 1984, Saloman & Naughton 1984, Vega-Candejas et al. 1994) . To better manage

organisms at higher trophic levels, understanding their feeding habits, habitat selection, and the

dynamics of their prey is useful. For example, the distribution of Illex roughly coincides with the

distribution of a major squid predator, the Risso’s dolphin (Grampus griseus; Baumgartner 1997).

Impacts to populations of these pelagics may have ramifications for marine mammals and larger

piscivores.

These small pelagics are primarily planktivores yet are also known to consume fish, larger

crustaceans, and cephalopods, (e.g. Chen et al. 1992, Henwood et al. 1978, Maurer & Bowman

1985, Modde & Ross 1983, Motta et al. 1993, Pierce et al. 1994, Rasero et al. 1996, Santos et al.

1998, Sheridan et al. 1984, Whitehead 1985). Therefore, the small pelagics play a major role in the

energy transfer of an ecosystem by providing a crucial linkage between lower and upper trophic

levels. Additionally, many of these species have notable, perhaps mutualistic relationships with

other organisms. For example, Lolliguncula has strong associations with menhaden and anchovies

in nearshore habitats (Matthews & Allen 1993, Laughlin & Livingston 1982, Pierce et al. 1994).

Lange & Waring (1992) have shown a strong association between Loligo pealei and butterfish.

Tolley (1987) has demonstrated an association between C. chrsurus, other carangids, other gadids,

other stromateids, and the jellyfish Aurelia aurita. It is unclear what the ecosystem level impacts

will be from a drastic change in the biomass and/or composition of the pelagic species complex in

the GOM. It is clear that given the ecological importance of these pelagics, a drastic impact on them

will also alter many other components of the ecosystem.

Prospects for a fishery on many of these under-utilized pelagic species remain (Christmas et al.

1985, Flandorfer & Skupien 1980, Gledhill 1989, Houde 1977a, 1977b, 1977c, Reese 1993,

Vecchione 1987). The advantages of such a fishery are short life cycles for many of these species,

their ubiquitous distributions, and their relatively consistent and high abundance. The disadvantages

of establishing a fishery for these species are the hit-or-miss nature of many of these schools, the

deeper set depths, processing the high number of bycatch (i.e. non-target) species, and the need to

establish or expand markets for many of these organisms. Cautions against initiating a widespread,

far-ranging, over-captilized fishery for these pelagics include alteration of stock structure by

removing adults/spawners in the deeper refugia and removing food for higher trophic level fish,
322

birds and mammals. Certainly further information will be required for standard stock assessment

parameters and estimates of these pelagic species; however, it is clear that a large amount of pelagic

biomass needs to be considered in the management of GOM fisheries.

ACKNOWLEDGMENTS

We thank the crew and officers of the NOAA Vessel Chapman who served on cruises during this

study. We thank M. Grace, R. Ford, and numerous other personnel at the Mississippi Laboratories

who participated in collecting these data over the period of this study. G. Pellegrin provided

statistical advice. J. L-Schultz and anonymous reviewers provided helpful comments on earlier

versions of this manuscript. 

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452.

APPENDIX A

PARAMETERS OF MAJOR PELAGIC FAMILIES

Stromateidae

Peprilus burti, the gulf butterfish, averaged 2,550.3 (+/- 340.3 S.E.) individuals hr-1, comprising

21.4% of the total catch by number and 31.6% of the total catch by weigth. P. burti was the most

abundant fish of all species collected in this study, and was found at 60.8% (554) of the stations

sampled. Average weight of this organism was 0.07 kg, with an average length of 14.1 cm (range

from <1 to 27).

Peprilus alepidotus, the harvestfish, averaged 20.6 (+/- 5.2 S.E.) individuals hr-1, comprising 0.17%

by number and 1.3% by weight of the total catch, ranked as the 32nd most abundant organism in this

study. P. alepidotus was found at 11.7% (107) of the stations sampled. Average weight of this

organism was 0.38 kg, with an average length of 14.8 cm (range from 3 to 20).

As a group, stomateids comprised approximately 22% of the total number and 33% of the total

weight of fish caught during this study. They were by far the most dominant and one of the more

ubiquitous fish of the pelagic species complex.

Clupeidae

Etrumeus teres, the round herring, averaged 1,852.8 (+/- 337.5 S.E.) individuals hr-1, comprising

15.5% of the total catch by number and 6.4% of the total catch by weight. E. teres was the second

most abundant fish of all species collected in this study, and is found at 38.2% (348) of the stations

sampled. Average weight of this organism was 0.02 kg, with an average length of 13.2 cm (range

from 2.3 to 51.2 cm).
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Sardinella aurita, the Spanish sardine, averaged 224.2 (+/- 95.0 S.E.) individuals hr-1, comprising

1.9% by number and 1.5% by weight of the total catch, ranked as the 13th most abundant organism

in this study. S. aurita was caught at 4.7% (43) of the stations in this study. Average weight and

length of this organism were 0.04 kg and 14.7 mm respectively (range from 8.8 to 22 cm).

Harengula jaguana, the scaled sardine, averaged 17.7 (+/- 7.7 S.E.) individuals hr-1, comprising

0.15% by number and 0.14% by weight of the total catch, ranked as the 34th most abundant organism

in this study. H. jaguana was found at 5.3% (48) of the stations in this study. Average weight and

length of this organism were 0.046 kg and 13.4 cm respectively (range from 6.7 to 20.3 cm).

Opisthonema oglinum, the Atlantic thread herring, averaged 16.5 (+/- 6.4 S.E.) individuals hr-1,

comprising 0.14% by number and 0.19% by weight of the total catch in this study, ranking 37th in

abundance. O. oglinum was found at 5.2% (47) of the stations in this study. Average weight and

length of this organism were 0.068 kg and 15.8 cm respectively (range from 3.4 to 29.8 cm).

Other species of clupeids observed in this study but of negligible abundance in these trawls were

Alosa alabamae (25 stations), A. mediocris (1 station), A. crysochlorus (1 station), Brevoortia

patronus (15 stations), and unidentified clupeids (1 station). These smaller clupeids are an excellent

example of the limitations of the mesh size used in this study and the difficulty of trying to assess

fish with “hit-or-miss” abundance and schooling behavior. As a group, clupeids comprised

approximately 18% of the total number and 8% of the total weight of fish caught during this study.

Next to the stromateids, clupeids were the most abundant group in this study.

Sparidae

Stenotomus caprinus, the longspine porgy, averaged 1,554 (+/- 210.9 S.E.) individuals hr-1,

comprising 13.0% of the total catch by number and 10.7% of the total catch by weight. S. caprinus

was the third most abundant organism of all species collected in this study, and was found at 52%

(473) of the stations sampled. Average weight of this organism was 0.04 kg, with an average length

of 12.0 cm (range <1 to 21 cm).

Lagodon rhomboides, the pinfish, averaged 93.4 (+/- 23.2 S.E.) individuals hr-1, comprising 0.78%

by number and 1.3% by weight of the total catch, ranked as the 18th most abundant organism in this

study. L. rhomboides was caught at 27.8% (253) of the stations in this study. Average weight and

length of this organism were 0.08 kg and 160 mm respectively (range from 9 to 47 cm).

Pagrus pagrus, the red porgy, averaged 3.7 (+/- 1.4 S.E.) individuals hr-1, comprising 0.03% by

number and 0.13% by weight of the total catch, ranked as the 77th most abundant organism in this

study. P. pagrus was caught at 5.7% (52) of the stations in this study. Average weight and length

of this organism were 0.20 kg and 223 mm respectively (range from 11 to 47 cm).

Other species of sparids observed in this study but of negligible abundance were Calamus nodosus

(10 stations), C. prorid (5 stations), Archosargus probatocephalus (5 stations), Calumus sp. (4

stations) C. leucosteus (4 stations) and C. bajonado (1 station). As a group, sparids comprised
329

approximately 15% of the total number of organisms caught during this study, ranking 4th in total

abundance. 

Carangidae

Trachurus lathami, the rough scad, averaged 1369.2 (+/- 170.8 S.E.) individuals hr-1, comprising

11.5% of the total catch by number and 12.7% of the total catch by weight. T. lathami was the fourth

most abundant organism of all species collected in this study, and was found at 67.8% (618) of the

stations sampled. Next to Loligo, this was the most ubiquitous species in the Gulf. Average weight

of this organism was 0.06 kg, with an average length of 15.3 cm (range <1 to 76 cm).

Decapterus punctatus, the round scad, averaged 316.3 (+/- 130.8 S.E.) individuals hr-1, comprising

2.7% of the total catch by number and 2.4% of the total catch by weight. D. punctatus ranked as the

7th most abundant organism of all species collected in this study, and was found at 8.5 (77) of the

stations sampled. Average weight of this organism was 0.05 kg, with an average length of 14.8 cm

(range 5 to 22 cm).

Chloroscombus chrysurus, the Atlantic bumper, averaged 288.0 (+/- 73.9 S.E.) individuals hr-1,

comprising 2.4% of the total catch by number and 2.9% of the total catch by weight. C. chrysurus

ranked as the 10th most abundant organism of all species collected in this study, and was found at

14.4% (131) of the stations sampled. Average weight of this organism was 0.06 kg, with an average

length of 14.4 cm (range 2 to 32 cm).

Selar crumenopthalmus, the bigeye scad, averaged 7.49 (+/- 1.21 S.E.) individuals hr-1, comprising

0.06% of the total catch by number and 0.18% of the total catch by weight. S. crumenophthalmus

ranked as the 55th most abundant organism of all species collected in this study, and was found at

13.6 (124) of the stations sampled. Average weight of this organism was 0.14 kg, with an average

length of 19.1 cm (range 2 to 30 cm).

Caranx crysos, the blue runner, averaged 5.14 (+/- 2.46 S.E.) individuals hr-1, comprising 0.04% of

the total catch by number and 0.15% of the total catch by weight. C. crysos ranked as the 68th most

abundant organism of all species collected in this study, and was found at 6.5% (59) of the stations

sampled. Average weight of this organism was 0.17 kg, with an average length of 21.1 cm (range

8 to 40 cm).

Selene setapinnis, the Atlantic moonfish, averaged 4.80 (+/- 1.68 S.E.) individuals hr-1, comprising

0.04% of the total catch by number and 0.07% of the total catch by weight. S. setapinnis ranked as

the 70th most abundant organism of all species collected in this study, and was found at 8.8% (80)

of the stations sampled. Average weight of this organism was 0.09 kg, with an average length of

14.5 cm (range 2 to 28 cm).

Other species of carangids observed in this study but of negligible abundance were Selene vomer

(21 stations), Trachinotus carolinus (20 stations), Seriola dumerili (29 stations), Decapterus tabl

(9 stations), Alectic ciliaris (6 stations), Caranx hippos (5 stations), Seriola fasciata (1 station),

Seriola rivoliana (3 stations), Uraspis secunda (4 stations), and Hemicaranx amblyrhynchus (1
330

station). As a group, carangids comprised approximately 17% of the total number of organisms

caught during this study, ranking 3rd in total abundance. 

Cephalopoda

Loligo sp., both pealei and plei, averaged 473 (+/- 51.1 S.E.) individuals hr-1, comprising 4.0% of

the total catch by number and 1.5% of the total catch by weight. Loligo was the fifth most abundant

organism of all species collected in this study, and is ubiquitous in the GOM, found at 83% (754)

of the stations sampled. Average weight of this organism was 0.02 kg, with an average length of 7.3

cm (range 0.6 to 37.2 cm).

Lolliguncula brevis averaged 18.5 (+/- 6.9 S.E.) individuals hr-1, comprising 1.5% by number and

0.16% by weight of the total catch, ranked as the 33rd most abundant organism in this study.

Lolliguncula was found at only 3.1% (28) of the stations in this study. Average weight and length

of this organism were 0.005 kg and 3.6 cm respectively (range 1.2 to 18.5 cm).

Abralia veranyi averaged 17.0 (+/- 5.9 S.E.) individuals hr-1, comprising 0.14% by number and

0.01% by weight of the total catch, ranked as the 36th most abundant organism in this study. Abralia

was found at 6.4% (58) of the stations in this study. Average weight and length of this organism

were 0.004 kg and 3.4 cm respectively (range 0. 9 to 13.6 cm).

Illex sp., both coindetii and illecebrosus, averaged 6.7 (+/- 2.3 S.E.) individuals hr-1, comprising

0.056% by number and 0.15% by weight of the total catch in this study, ranked 57th in abundance.

Illex was found at 9.8 % (89) of the stations in this study. Average weight and length of this

organism were 0.14 kg and 13.9 cm respectively (range 3.9 to 29.2 cm).

Other species of squid observed in this study but of negligible abundance were Ornithoteuthis sp.

(antillarum; 9 stations), Rossia sp. (5 stations), Semirossia sp. (tenera, equalis; 2 stations), and

Cranchia sp. (scabra; 13 stations). Other cephalopods (i.e. Octopoda) were found at 6 stations. As

a group, squids comprised approximately 6% of the total number of organisms caught during this

study, ranking 5th in total abundance. 

Gadidae

Steindachneria argenta, the luminous hake, averaged 385.8 (+/- 94.7 S.E.) individuals hr-1,

comprising 3.2% by number and 0.8% by weight of the total catch in this study, ranking number 6th

in abundance. S. argenta was found at 10.3 % (94) of the stations in this study. Average weight and

length of this organism were 0.01 kg and 14.5 cm respectively (range 1.2 to 31 cm).

Other gadids observed in this study but of negligible abundance were Urophycis cirrata (35

stations), U. floridana (37 stations), U. regia (3 stations), Merluccius albidus (14), and Laemonema

sp. (1 station).
331

Trichiuridae

Trichiurus lepturus, the Atlantic cutlassfish, averaged 313.1 (+/- 48.2 S.E.) individuals hr-1,

comprising 2.6% by number and 3.6% by weight of the total catch in this study, ranking number 8th

in abundance. T. lepturus was found at 38.1 % (347) of the stations in this study. Average weight

and length of this organism were 0.07 kg and 16.7 cm respectively (range 2 to53 cm).

Other trichiurids observed in this study but of negligible abundance were Benthodesmus tenuis (19

stations), Lepidopus sp. (12 stations), and Evoxymetopon taenia (3 stations).

Myctophidae

Diaphus sp., lanternfish, averaged 303.5 (+/- 105.6 S.E.) individuals hr-1, comprising 2.5% by

number and 0.14% by weight of the total catch in this study, ranking number 9th in abundance.

Diaphus sp. was found at 6.8 % (62) of the stations in this study. Average weight and length of this

organism were 0.002 kg and 5.4 cm respectively (range 2.3 to 8.9 cm).

Maurolicus muelleri, the Atlantic pearlside, averaged 15.6 (+/- 6.8 S.E.) individuals hr-1, comprising

0.13% by number and 0.004% by weight of the total catch in this study, ranking number 38th in

abundance. M. muelleri was found at 2.5 % (23) of the stations in this study. Average weight and

length of this organism were 0.002 kg and 4.7 cm respectively (range 2.8 to 5.8 cm).

Other, unidentified myctophids (10 stations) were observed in this study but were of negligible

abundance and biomass. 

Engraulidae

Engraulis eurystole, the silver anchovy, averaged 272.5 (+/- 218.0 S.E.) individuals hr-1, comprising

2.3% of the total catch by number and 0.09% of the total catch by weight. E. eurystole ranked as the

11th most abundant organism of all species collected in this study, and was found at 1.5% (14) of the

stations sampled. Average weight of this organism was 0.002 kg, with an average length of 6.9 cm

(range 2.1 to 21.3 cm).

Anchoa hepsetus, the striped anchovy, averaged 170.6 (+/- 78.6 S.E.) individuals hr-1, comprising

1.4% of the total catch by number and 0.4% of the total catch by weight. A. hepsetus ranked as the

14th most abundant organism of all species collected in this study, and was found at 5.0% (46) of the

stations sampled. Average weight of this organism was 0.01 kg, with an average length of 11.3 cm

(range 4.1 to 17.8 cm).

Anchoa mitchilli, the bay anchovy, averaged 40.1 (+/- 22.8 S.E.) individuals hr-1, comprising 0.3%

of the total catch by number and 0.04% of the total catch by weight. A. mitchilli ranked as the 26th

most abundant organism of all species collected in this study, and was found at 1.2% (11) of the

stations sampled. Average weight of this organism was 0.006 kg, with an average length of 5.5 cm

(range 3.6 to 8.3 cm).
332

Other engraulids observed in this study but of negligible abundance were Anchoa nasuta (7

stations), A. lyolepis (1 station) and A. lamprotaenia (1 station). 

Scombridae

Scomber japonicus, the chub mackerel, averaged 262.4 (+/- 60.5 S.E.) individuals hr-1, comprising

2.2% of the total catch by number and 4.1% of the total catch by weight. S. japonicus ranked as the

12th most abundant organism of all species collected in this study, and was found at 28.6% (261) of

the stations sampled. Average weight of this organism was 0.09 kg, with an average length of 20.1

cm (range 3.0 to 35.0 cm).

Other scombrids observed in this study but of negligible abundance were Scombermorus maculatus

(101 stations), S. cavalla (108 stations), Sarda sarda (15 stations), Euthynnus allettenatus (3

stations) and Auxis thazard (3 stations).

Scianidae

Micropogonias undulatus, the Atlantic croaker, averaged 142.4 (+/- 35.8 S.E.) individuals hr-1,

comprising 1.2% of the total catch by number and 1.7% of the total catch by weight. M. undulatus

ranked as the 15th most abundant organism of all species collected in this study, and was found at

15.4% (140) of the stations sampled. Average weight of this organism was 0.07 kg, with an average

length of 18.6 cm (range 1.6 to 50.5 cm).

Leiostomus xanthurus, the spot, averaged 60.2 (+/- 20.6 S.E.) individuals hr-1, comprising 0.5% of

the total catch by number and 1.1% of the total catch by weight. L, xanthurus ranked as the 24th most

abundant organism of all species collected in this study, and was found at 8% (73) of the stations

sampled. Average weight of this organism was 0.11 kg, with an average length of 19.9 cm (range

11.1 to 30.0 cm).

Cynoscion arenarius, the sand seatrout, averaged 25.6 (+/- 5.7 S.E.) individuals hr-1, comprising

0.2% of the total catch by number and 0.5% of the total catch by weight. C. arenarius ranked as the

30th most abundant organism of all species collected in this study, and was found at 17.1% (156) of

the stations sampled. Average weight of this organism was 0.12 kg, with an average length of 22.8

cm (range 6.6 to 40.9 cm).

Cynoscion nothus, the silver seatrout, averaged 14.6 (+/- 3.1 S.E.) individuals hr-1, comprising 0.1%

of the total catch by number and 0.2% of the total catch by weight. C. nothus was the 39th most

abundant organism of all species collected in this study, and was found at 7.2% (66) of the stations

sampled. Average weight of this organism was 0.08 kg, with an average length of 20.2 cm (range

7.2 to 41.4 cm).

Other scianids observed in this study but of negligible abundance were Equetus umbrosus (36

stations), E. lanceolatus (8 stations), E. acuminatus (3 stations), Larimus fasciatus (5 stations),

Menticirrhus americanus (9 stations), M. saxatilis (2 stations) Sciaenops ocellatus (5 stations),

Stellifer lanceolatus (3 stations) and Pogonias cromis (6 stations).
333

DISTRIBUTION OF RED SNAPPER LARVAE IN THE

NORTHERN GULF OF MEXICO, 1982-1994

D. M. Drass

J. Lyczkowski-Shultz

P. J. Bond

National Marine Fisheries Service

Pascagoula, MS

ABSTRACT

The red snapper, Lutjanus campechanus, supports important commercial and recreational fisheries

in the Gulf of Mexico (GOM) where stock is managed by size limits and quotas in federal waters.

The National Marine Fisheries Service, Mississippi Laboratories has been investigating the use of

larval fish abundance indices in stock assessments for a number of managed species, including red

snapper. Reliable estimates of abundance and analyses of occurrence data depend on accurate

identifications to the species level. Identification of snapper larvae remains problematic despite

recent descriptions of larval stages, yet it is now possible to consistently identify red snapper larvae

$ 3.5 mm. We have recently examined over 10,000 snapper larvae collected during Southeast Area

Monitoring and Assessment Program (SEAMAP) resource surveys and present here a subset of

those results for the area between Brownsville, TX to Mobile Bay, AL.
334

RED SNAPPER DISCARDS IN TEXAS COASTAL WATERS: A FISHERY

DEPENDENT ONBOARD SURVEY OF RECREATIONAL

HEADBOAT DISCARDS AND LANDINGS

Barbara A. Dorf

Texas Parks & Wildlife

Coastal Fisheries Division

ABSTRACT

Quantity and characteristics of red snapper (Lutjanus campechanus) recreational headboat discards

and landings from three Texas ports (Galveston, Port Aransas, and Port Isabel) were determined in

a fishery dependent study using NMFS-trained onboard observers during August and September

1999. Mean fishing depth during 54 trips (199 sets) was 40.2 m (range, 13.4 – 95.4 m) with 36.5%

of reels sampled. Red snapper less than the 1999 federal minimum size of 450 mm (18 inches) total

length made up 93.4% of the 3,863 snapper collected. Those less than the Texas state minimum size

of 375 mm (15 inches) made up 64.0% of the catch. When brought on board, 70.2% of snapper

appeared normal and 26.1% had protruding stomachs. Of the discarded red snapper, 60.6% were

released alive and swam down, 22.8% swam erratically, 15.2% floated, and 1.4% were discarded

dead. Fish released either dead or floating were caught at greater depths than fish which swam down

or erratically. Galveston had the largest discard:landing ratio (211:1) and smallest mean fish size

(0.7 kg, 343 mm). Port Aransas had the lowest discard:landing ratio (5.2:1) and largest mean fish

size (0.9 kg, 387 mm).

INTRODUCTION

Red snapper (Lutjanus campechanus) is one of the most economically important species in the Gulf

of Mexico reef-fish fishery. In order to manage this widely used resource, the Gulf of Mexico

Fishery Management Council implemented a Reef Fish Fishery Management Plan in 1984 to rebuild

declining reef fish stocks (GMFMC 1981). Recent management measures have been publicly

controversial; particularly regarding bycatch in the shrimp fishery, accuracy of stock assessments,

and possible under-reporting and inaccuracy of commercial and recreational catches. As a result,

an independent scientific assessment of red snapper status in the Gulf of Mexico, as well as a peer

review of all National Marine Fisheries Service (NMFS) stock assessments and fisheries statistics

was completed in 1997 (MRAG Americas 1997). Although supportive of the scientific evaluations,

data limitations were noted. 

One area of concern was monitoring the number and length frequency of discards. Another was the

accurate estimate of discard mortality rates, particularly in relation to depth of capture. In 1999, the

NMFS responded to the 1997 peer review and presented a research plan for red snapper in the Gulf

of Mexico. The plan addressed all phases of the reef-fish fishery, including the directed commercial

fishery, recreational charter boats, and headboats (MRAG Americas 1999). Onboard observers were

suggested as the best way to estimate discard. To estimate discard mortality rates, a “sink or swim”

approach was suggested in which onboard observers would note the short-term fate of discarded red
335

snapper: whether or not the fish swam down out of sight. Another suggested method to determine

mortality rate involved releasing snapper into cages, then lowering them to depth. This method has

been used previously, although at relatively shallow depths (Gitschlag & Renaud 1994, Render &

Wilson 1994). 

Discard of red snapper caught in the recreational headboat fishery are usually due to: catch during

a seasonal closure while fishing for other species, smaller than minimum size, or number in excess

of legal bag limits. The amount and characteristics of this recreational bycatch are poorly

documented, as is its contribution to bycatch mortality in the Gulf of Mexico. Red snapper from

Texas headboats account for 80% of Texas recreational red snapper landings, 85% of Gulf of

Mexico headboat red snapper landings, and 25% of Gulfwide recreational red snapper landings

(Schirripa & Legault 1999). Awareness of the quantity and characteristics of recreational discards

from this important sector of the red snapper fishery can promote the development of improved

stock assessment and management strategies for the Gulf of Mexico.

The goal of this study was to determine the quantity, characteristics, and fate of red snapper from

the directed recreational headboat fishery along the Texas coast from a depth stratified perspective.

Specific objectives included placing NMFS trained observers on board recreational headboats from

three Texas ports (Galveston, Port Aransas, and Port Isabel) to determine the: 1) length, weight, and

condition of all snapper brought on board; 2) condition and short-term fate of all snapper discards;

3) fishery-specific and environmental parameters associated with all catches.

MATERIALS AND METHODS

Headboats were based in one of three Texas ports: Galveston, Port Aransas, and Port Isabel.

Sampling occurred during the months of August and early September 1999. Prior to closure of the

red snapper fishery in federal waters at the end of August, sampling occurred in federal and state

waters, continuing solely in state waters during September. Data were collected following protocols

described in MRAG Americas (1999), FC.1 Reef fish fishery observer program, and Gitschlag &

Renaud (1994). Methodology closely followed already existing NMFS methods to assure data

compatibility. Either one or two NMFS-trained observers were placed aboard all available headboat

trips departing from each of the three ports. 

Catch specific information was collected for each trip and set: date and time, latitude and longitude,

fishing depth (fathoms), bottom type, wave height (feet), fishing gear type (manual or electric reels),

number of fishers and reels, and hours fished. Biological data included length (mm) and weight (kg)

for both discards and landings, condition of snapper brought on board, hooking location, release

method, and discard fate. Catch per unit effort (CPUE) was calculated as: (“#Fish Caught” / “Set

Hours”) / “#Reels Sampled.” 

Condition of snapper when brought on board was categorized as: live – normal appearance, stomach

protruding, eyes protruding, combination of stomach & eyes protruding, dead on arrival, or not

determined. Hooking locations were divided into: maxilla, gill, esophagus, or other. Release

methods were described as: remove hook, cut leader, swim bladder punctured, combination of hook

removal and swim bladder puncture, or combination of cut leader and swim bladder puncture.
336

Discard fate was recorded as: fish kept, discarded alive-swim down, erratic swimming, floating, or

discarded-dead. 

Because there were often more reels on an entire headboat than could be sampled effectively by one

or two observers, each boat was divided into sections as necessary. A trip-specific random table of

numbers was used to determine which boat section to sample during a set. Results represent all reels

sampled.

RESULTS AND DISCUSSION

Forty-eight trips were made aboard four recreational headboats from three Texas fishing ports

(Galveston, Port Aransas, and Port Isabel) during August 1999. Six trips were made aboard one

recreational headboat (Port Isabel) during September 1999 (Table 6.8). Data were collected during

32 days and 2 nights of observations. One hundred ninety-nine sets (170 in August & 29 in

September) were sampled at the locations shown in Figure 6.31.

Mean overall vessel length was 22 m, ranging from 17 to 24 m. All vessels had either fiberglass or

aluminum hulls. Engine power ranged from 700 to 2,120 horsepower, with a mean of 1,232

horsepower. Crew size (not including the captain) ranged from one to six individuals, with a mean

crew size of three. Reels were either manual or electric (although only the Port Aransas headboat

carried electric reels), with 73% of all reels manual.

Mean depth was 40.2 m (20.7 s.d.), ranging from 13.4 to 95.4 m (Figure 6.32). Mean fishing depth

was significantly different between ports in August (F = 220.132, n = 169, df = 2, p < 0.0001) with

the greatest mean depth from Port Aransas (66.0 m, 14.7 s.d.). Fishing depth was shallowest in

Galveston (mean 24.8 m, 6.3 s.d.), with intermediate August values from Port Isabel (mean 48.6 m,

11.9 s.d.). In September, the only samples collected were in state waters from Port Isabel (mean 21.5

m, 3.1 s.d.). Previous discard mortality studies have been carried out in waters shallower than those

commonly fished by Texas headboats. Render & Wilson (1994) carried out their study on a

Louisiana gas production platform in 21 m of water. Surface release studies by Gitschlag & Renaud

(1994) used fish collected at 21 – 40 m depths. Render & Wilson (1996) noted a general trend of

increasing mortality due to physiological stress of unvented snapper collected at depths up to 56 m.

The Texas coast and the greater depths where recreational snapper fishing occurs there are currently

underrepresented in management data collection efforts.

Table 6.8. Number of trips and sets sampled from Texas recreational headboats in August and

September 1999 by fishing port.

Galveston Port Aransas Port Isabel (Aug) Port Isabel (Sept) Total

Trips 20 13 15 6 54

Sets 74 50 46 29 199
337

Figure 6.31. Location of Texas recreational headboat sets in August and September 1999.

The mean number of reels sampled per set was 9.8 (2.5 s.d.), with a range of 1 to 22 reels. This

mean constituted 36.5% of all reels in use (29.7% s.d). Fishing time per set varied from 0.2 to 4

hours with a mean of 0.9 hours (0.6 s.d). The majority of fishing occurred during daylight hours,

although there were 2 night fishing trips from Port Aransas. The majority of sets (62.3%) occurred

in 0 to 0.6 m seas, with 37.7% in 0.9 to 1.5 m seas. Most sets took place over rock bottom (55.6%),

with mud (14.8%), and coral (1.0%) comprising the remainder. Fishing often occurred near

hydrocarbon production platforms and over submerged structures such as wrecks.
338

0

50

100

150

200

250

300

350

400

450

500

Count

0 20 40 60 80 100 120

Depth (m)

Galveston 

N = 74

0

20

40

60

80

100

120

140

160

180

Count

0 20 40 60 80 100 120

Depth (m)

Port Aransas 

N = 50

0

50

100

150

200

250

300

350

Count

0 20 40 60 80 100 120

Depth (m)

Port Isabel (Aug.) 

N = 46

0

100

200

300

400

500

600

700

800

Count

0 20 40 60 80 100 120

Depth (m)

Port Isabel (Sept) 

N = 29

A. Galveston B. Port Aransas

C. Port Isabel (August) D. Port Isabel (September)

Figure 6.32. Fishing depth by port for recreational headboat sets in August and September

1999. A. Galveston; B. Port Aransas; C. Port Isabel (August); D. Port Isabel

(September).

Red Snapper Size Composition

A total of 3,863 red snapper were caught on hook-and-line during the study period. Of these, 3,828

were measured and ranged from 105 to 908 mm (4 to 36 inches) total length (TL) (Table 6.9). The

frequency distribution of snapper examined is shown in Figure 6.33. Mean total length was

significantly different between ports in August (F = 139.308, n = 2,925, df = 2, p < 0.0001). Overall,

snapper 350 – 375 mm (14 - 15-inch) TL comprised the largest proportion (18.1%) of individuals,

although Port Aransas had their largest proportion of snapper (22.8%) in the 375 – 400 mm (15 –

16-inch) TL size (Figure 6.3 3, Table 6.9). 
339

Table 6.9. Frequency distribution (A. Total %; B. Cumulative %) for total length (mm) of red snapper

measured during Texas recreational headboat sets in August and September 1999.

A. Total %

From

(3≥)

To

(<)

Total

Count

Total

%

Galveston,

August

Count

Galveston,

August %

Port

Aransas,

August

Count

Port

Aransas,

August

%

Port Isabel,

August

Count

Port Isabel,

August

%

Port Isabel,

September

Count

Port Isabel,

September

 %

75 100 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

100 125 1 0.03 0 0.00 0 0.00 1 0.11 0 0.00

125 150 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

150 175 1 0.03 1 0.08 0 0.00 0 0.00 0 0.00

175 200 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

200 225 13 0.34 4 0.31 2 0.26 2 0.23 5 0.56

225 250 85 2.22 36 2.83 0 0.00 13 1.49 36 4.00

250 275 196 5.12 64 5.02 4 0.51 52 5.98 76 8.44

275 300 262 6.84 103 8.08 19 2.42 45 5.17 95 10.56

300 325 510 13.32 205 16.09 49 6.25 103 11.84 153 17.00

325 350 688 17.97 256 20.09 110 14.03 136 15.63 186 20.67

350 375 693 18.10 269 21.11 163 20.79 150 17.24 111 12.33

375 400 539 14.08 184 14.44 179 22.83 101 11.61 75 8.33

400 425 374 9.77 105 8.24 119 15.18 68 7.82 82 9.11

425 450 212 5.54 33 2.59 62 7.91 62 7.13 55 6.11

450 475 96 2.51 12 0.94 32 4.08 37 4.25 15 1.67

475 500 65 1.70 1 0.08 18 2.30 40 4.60 6 0.67

500 525 24 0.63 0 0.00 7 0.89 14 1.61 3 0.33

525 550 18 0.47 1 0.08 3 0.38 13 1.49 1 0.11

550 575 6 0.16 0 0.00 1 0.13 5 0.57 0 0.00

575 600 19 0.50 0 0.00 5 0.64 14 1.61 0 0.00

600 625 5 0.13 0 0.00 1 0.13 4 0.46 0 0.00

625 650 5 0.13 0 0.00 2 0.26 2 0.23 1 0.11

650 675 6 0.16 0 0.00 4 0.51 2 0.23 0 0.00

675 700 3 0.08 0 0.00 1 0.13 2 0.23 0 0.00

700 725 3 0.08 0 0.00 0 0.00 3 0.34 0 0.00

725 750 1 0.03 0 0.00 1 0.13 0 0.00 0 0.00

750 775 1 0.03 0 0.00 0 0.00 1 0.11 0 0.00

775 800 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

800 825 1 0.03 0 0.00 1 0.13 0 0.00 0 0.00

825 850 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

850 875 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

875 900 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

900 925 1 0.03 0 0.00 1 0.13 0 0.00 0 0.00

925 950 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

Total 3828 100.00 1274 100.00 784 100.00 870 100.00 900 100.00
340

Table 6.9. (continued)

B. Cumulative %

From

($=)

To

(#=)

Total

 Count

Total

%

Galveston,

August

Count

Galveston,

August

%

Port

Aransas,

August

Count

Port

Aransas,

August

%

Port

Isabel,

August

Count

Port

Isabel,

August

%

Port

Isabel,

 September

Count

Port

Isabel,

 September

%

75 100 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

100 125 1 0.03 0 0.00 0 0.00 1 0.11 0 0.00

125 150 1 0.03 0 0.00 0 0.00 1 0.11 0 0.00

150 175 2 0.05 1 0.08 0 0.00 1 0.11 0 0.00

175 200 2 0.05 1 0.08 0 0.00 1 0.11 0 0.00

200 225 15 0.39 5 0.39 2 0.26 3 0.34 5 0.56

225 250 100 2.61 41 3.22 2 0.26 16 1.84 41 4.56

250 275 296 7.73 105 8.24 6 0.77 68 7.82 117 13.00

275 300 558 14.58 208 16.33 25 3.19 113 12.99 212 23.56

300 325 1068 27.90 413 32.42 74 9.44 216 24.83 365 40.56

325 350 1756 45.87 669 52.51 184 23.47 352 40.46 551 61.22

350 375 2449 63.98 938 73.63 347 44.26 502 57.70 662 73.56

375 400 2988 78.06 1122 88.07 526 67.09 603 69.31 737 81.89

400 425 3362 87.83 1227 96.31 645 82.27 671 77.13 819 91.00

425 450 3574 93.36 1260 98.90 707 90.18 733 84.25 874 97.11

450 475 3670 95.87 1272 99.84 739 94.26 770 88.51 889 98.78

475 500 3735 97.57 1273 99.92 757 96.56 810 93.10 895 99.44

500 525 3759 98.20 1273 99.92 764 97.45 824 94.71 898 99.78

525 550 3777 98.67 1274 100.00 767 97.83 837 96.21 899 99.89

550 575 3783 98.82 1274 100.00 768 97.96 842 96.78 899 99.89

575 600 3802 99.32 1274 100.00 773 98.60 856 98.39 899 99.89

600 625 3807 99.45 1274 100.00 774 98.72 860 98.85 899 99.89

625 650 3812 99.58 1274 100.00 776 98.98 862 99.08 900 100.00

650 675 3818 99.74 1274 100.00 780 99.49 864 99.31 900 100.00

675 700 3821 99.82 1274 100.00 781 99.62 866 99.54 900 100.00

700 725 3824 99.90 1274 100.00 781 99.62 869 99.89 900 100.00

725 750 3825 99.92 1274 100.00 782 99.74 869 99.89 900 100.00

750 775 3826 99.95 1274 100.00 782 99.74 870 100.00 900 100.00

775 800 3826 99.95 1274 100.00 782 99.74 870 100.00 900 100.00

800 825 3827 99.97 1274 100.00 783 99.87 870 100.00 900 100.00

825 850 3827 99.97 1274 100.00 783 99.87 870 100.00 900 100.00

850 875 3827 99.97 1274 100.00 783 99.87 870 100.00 900 100.00

875 900 3827 99.97 1274 100.00 783 99.87 870 100.00 900 100.00

900 925 3828 100.00 1274 100.00 784 100.00 870 100.00 900 100.00

925 950 3828 100.00 1274 100.00 784 100.00 870 100.00 900 100.00

Total 3828 100.00 1274 100.00 784 100.00 870 100.00 900 100.00
341

0

100

200

300

400

500

600

700

800

Count

0 200 400 600 800 1000

TL (mm)

N = 3,828

0

50

100

150

200

250

300

Count

0 200 400 600 800 1000

TL (mm)

Galveston 

N = 1,274

0

20

40

60

80

100

120

140

160

180

200

Count

0 200 400 600 800 1000

TL (mm)

Port Aransas 

N = 784

0

20

40

60

80

100

120

140

160

Count

0 200 400 600 800 1000

TL(mm)

Port Isabel (August) 

N = 870

0

20

40

60

80

100

120

140

160

180

200

Count

0 200 400 600 800 1000

TL (mm)

Port Isabel (Sept.) 

N = 900

A. Summary B. Galveston (August)

C. Port Aransas (August) D. Port Isabel (August)

E. Port Isabel (September)

Figure 6.33. Size distribution of red snapper caught and measured during Texas recreational

headboat sets in August and September 1999. A. Summary; B. Galveston (August

only); C. Port Aransas (August only); D. Port Isabel (August); E. Port Isabel

(September).
342

Red snapper < 450 mm (18 inches, federal minimum size at the time of this study) TL made up

93.4% of snapper caught. Those < 400 mm (16 inches, current federal minimum size) made up

78.1% of snapper caught. Snapper < 375 mm (15 inches, current state minimum size) constituted

64.0% of fish collected (Table 6.9). Port Isabel had the greatest proportion of snapper larger than

425 mm (17+ inches) in August samples, although Port Aransas had the largest proportion of 375

to <425 mm (15 to <17 inches) snapper (Table 6.10). There was no significant statistical relationship

between depth and total length of snapper caught in this survey for any port or all ports combined

(r2 = 0.092). 

Table 6.10. Percentage of red snapper measured greater than or equal to 450, 425, 400, and 375

mm (18, 17, 16, and 15 inches) total length caught during Texas recreational

headboat sets in August and September 1999.

Total Length

(mm) Summary Galveston % Port Aransas%

Port Isabel

(Aug) %

Port Isabel

(Sep) %

450+ 6.6 1.1 9.8 15.8 2.9

425+ 12.2 3.7 17.7 22.9 9.0

400+ 21.9 11.9 32.9 30.7 18.1

375+ 36.0 26.4 55.7 42.3 26.4

N 3,828 1,274 784 870 900

Snapper collected in this study represent a greater size range than those of most previous studies,

reflecting size distribution differences among locations along the Gulf coast. In the surface release

study by Gitschlag & Renaud (1994), southeast of Galveston, Texas, 91% of their snapper were less

than 300 mm FL (324 mm TL; (Parrack 1986)). For their cage studies, tested snapper were # 430

mm FL (463 mm TL), with 35% of their snapper < 300 mm FL (324 mm TL), similar to the present

study where 28% of snapper were under 325 mm TL). Mortality tests by Render & Wilson (1996)

were conducted south of Cameron, Louisiana on fish less than 360 mm FL (388 mm TL). In the

present study, Port Aransas and Port Isabel (August) snapper $ 375+ mm TL accounted for 33% and

31% of the catch, respectively.

Red Snapper Hooking Location and Condition When Brought on Board

Hooking location was determined for 3,849 snapper: 91.8% were hooked in the maxilla, 6.2% in the

esophagus, 0.8% in the gill, and 1.3% in some other area of the body. Condition when brought on

board was determined for 3,844 snapper: 70.2% were normal in appearance, 26.1% had their

stomach protruding from their mouths, 2.8% had protruding eyes, 0.6% had both eyes and stomach

protruding, and 0.3% were brought on board dead. There were significant differences in mean depth

between conditions (F = 109.056, n = 3,840, df = 4, p < 0.0001), although there was no clear trend

evident (Figure 6.34, Table 6.11). Percent of snapper brought to the surface with stomach protrusion

was variable with depth and port, possibly a reflection of variable fish retrieval rates (manual vs. 
343

Count

Depth (m)

Galveston

N = 1,306

Stomach

Normal

Eyes

Eyes & Stomach Dead

10 20 30 40 50 60 70 80 90 100

0

50

100

150

200

250

300

350

Dead

Depth (m)

10 20 30 40 50 60 70 80 90 100

Normal

Stomach Eyes

Eyes & Stomach

Port Aransas

N = 781

0

20

40

60

80

100

120

140

Depth (m)

10 20 30 40 50 60 70 80 90 100

Normal

Stomach

Eyes

Eyes & Stomach

Pt. Isabel

N = 1,772

0 Dead

100

200

300

400

500

600

700

800

Depth (m)

10 20 30 40 50 60 70 80 90 100

Normal

Stomach Eyes

Eyes & Stomach

August

N = 872

0 Dead

20

40

60

80

100

120

140

160

180

Depth (m)

10 20 30 40 50 60 70 80 90 100

Normal

Stomach

Eyes

Eyes & Stomach

September

N = 901

0 Dead

100

200

300

400

500

600

700

A. Galveston B. Port Isabel

C. Port Isabel Port Isabel, August

Port Isabel, September

Figure 6.34. Depth and condition (when brought on board) of red snapper caught and measured

during Texas recreational headboat sets in August and September 1999 by fishing

port. A. Galveston; B. Port Aransas; C. Port Isabel.
344

Table 6.11. Mean depth (m) and frequency for condition (when brought on board) of red snapper

measured during Texas recreational headboat sets in August and September 1999.

Mean Depth (m) [% of catch]

Condition Summary

(n = 3,844)

Galveston

(n = 1,306)

Port Aransas

(n = 781)

Port Isabel,

Aug

(n = 872 )

Port Isabel,

Sep

(n = 901)

Normal 33.8 [70.2] 22.4 [71.1] 64.0 [64.0] 47.0 [46.4] 22.4 [97.1]

Stomach Protruding 43.1 [26.1] 26.9 [28.5] 59.8 [25.3] 50.5 [47.5] 29.1 [2.8]

Eyes Protruding 61.8 [2.8] - 65.7 [9.3] 54.6 [3.9] 25.6 [0.1]

Eyes & Stomach 58.3 [0.6] 34.7 [0.1] 71.3 [0.6] 56.0 [2.1] -

Dead 57.3 [0.3] 27.4 [0.3] 75.6 [0.8] 67.6 [0.1] -

electric reels) by headboat fishers. Gitschlag & Renaud (1994) found that 33% of their cage study

snapper were brought on board with everted stomachs, with 51% showing some sign of capturerelated stress. For their surface release study, stomach protrusion from the mouth was noted in 1%

of fish collected at 21-24 m depth, 56% at 27-30 m and 37-40 m depths. 

Red Snapper Release and Discard Fate

When snapper were discarded, 62.8% were released by removing the hook without puncturing the

swim bladder. The swim bladder was punctured along with hook removal for 36.2% of released

snapper. Discard fate was determined for 3,851 fish, and included 12.9% of the catch that was kept.

Of those that were discarded, 60.6% were released alive and swam down, 22.8% swam erratically,

15.2% floated, and 1.4% were discarded dead (Figure 6.35). There were significant differences in

mean depth between discard fates (F = 66.594, n = 3,353, df = 3, p < 0.0001). Fish released either

dead or floating were caught at greater depths than fish that swam down or swam erratically on

release (Figure 6.36, Table 6.12).

Schirripa & Legault (1999) summarized an observer program in the Gulf of Mexico commercial reef

fish fishery in 1995 that targeted several red snapper trips on handline vessels at similar depths to

the present study (mean 40 m, range 33 – 62 m) located off of Louisiana and east Texas.

Comparable amounts of red snapper were discarded dead (1.6%) and most discards were said to

have either stomachs or eyes protruding. Gitschlag & Renaud (1994) found higher proportions of

snapper swam down (99% at 21-24 m, 90% at 27-30 m, and 56% at 37-40 m) in a study based on

3 single day headboat trips. Researchers rather than headboat patrons caught snapper in their study,

and onboard handling procedures and fish retrieval rates (manual vs. electric reels) may account for

differences in swim down proportion on release. 

There were no significant differences in mean total length between discard fates, excluding those

kept (F = 1.361, n = 3,324, df = 3, p = 0.2527). The only clear trend was that all discard fates had

similar total length distributions except fish > 450 mm which were legally kept (Table 6.13, Figure

6.37). Gitschlag & Renaud (1994) also found that survival of caged fish was unrelated to size.
345

Dead

1.4% Floating

15.2%

Erratic Swimming

22.8%

Swim Down

60.6%

Floating

10.6%

Erratic Swimming

Swim Down 30.0%

57.9%

Dead

1.5% Dead

1.7%

Floating

20.2%

Erratic Swimming

5.4%

Swim Down

72.8%

Dead

2.3%

Floating

26.0%

Erratic Swimming

37.8%

Swim Down

33.9%

Floating

7.3%

Swim Down

83.0%

Erratic Swimming

9.7%

A. Summary

B. By port and month

Figure 6.35. Fate of red snapper caught and measured during Texas recreational headboat sets in

August and September 1999 by fishing port. A. Summary; B. By port and month.
346

Depth (m)

10 20 30 40 50 60 70 80 90 100

0

50

100

150

200

250

300

Galveston

N = 1,274

Swim Down

Erratic Swimmi

Floating

Dead

Depth (m)

10 20 30 40 50 60 70 80 90 100

Swim Down

Erratic Swimmi

Floating

Dead

Port Aransas

N = 785

0

10

20

30

40

50

60

70

80

Depth (m)

10 20 30 40 50 60 70 80 90 100

Swim Down

Erratic Swimmin

Dead

Pt. Isabel

300 N = 1,773

0

50

100

150

200

250

350

400

450

Floating

A. Galveston B. Port Aransas

C. Port Isabel

Figure 6.36. Depth and fate of red snapper caught and measured during Texas recreational

headboat sets in August and September 1999 by fishing port. A. Galveston; B. Port

Aransas; C. Port Isabel.
347

Table 6.12. Mean depth (m) and frequency for discard fate of red snapper measured during

Texas recreational headboat sets in August and September 1999.

Mean Depth (m) [% of catch]

Discard Fate Summary

(n = 3,353)

Galveston

(n = 1,298)

Port Aransas

(n = 655)

Port Isabel,

Aug

(n = 731 )

Port Isabel,

Sep

(n = 669)

Swim Down 34.3 [60.6] 23.3 [57.9] 59.0 [72.8] 47.2 [33.9] 22.1 [83.0]

Erratic Swimming 34.8 [22.8] 24.1 [30.0] 60.8 [5.2] 49.4 [37.8] 23.0 [9.7]

Floating 46.3 [15.2] 24.4 [10.6] 72.4 [20.3] 49.9 [26.0] 23.1 [7.3]

Dead 47.9 [1.4] 26.1 [1.5] 73.0 [1.7] 57.3 [2.3] -

Table 6.13. Mean total length (mm) and frequency for discard fate of red snapper measured

during Texas recreational headboat sets in August and September 1999.

Mean Total Length (mm) [% of catch]

Discard Fate Summary

(n = 3,828)

Galveston

(n = 1,274)

Port Aransas

(n = 784)

Port Isabel,

Aug

(n = 870 )

Port Isabel,

Sep

(n = 900)

Swim Down 343 [52.6] 342 [57.7] 374 [61.1] 351 [28.4] 316 [61.6]

Erratic Swimming 344 [19.8] 345 [30.0] 366 [4.5] 349 [31.7] 305 [7.2]

Floating 348 [13.2] 339 [10.4] 364 [17.0] 352 [21.9] 314 [5.4]

Dead 339 [1.2] 330 [1.5] 350 [1.4] 342 [2.0] -

Kept 459 [12.9] 478 [0.5] 468 [16.1] 518 [15.3] 419 [25.4]

Several snapper were kept from Port Aransas in August that were smaller than 450 mm (18-inches).

These were harvested under a collecting permit for an ongoing research project. Catches from Port

Isabel in September reflected the smaller minimum size requirement for snapper caught in Texas

waters (380 mm, 15 inches) rather than the 450 mm (18-inch) federal minimum size. As a result,

Port Isabel kept a larger proportion of fish than other locations (Table 6.13).

It is likely that large proportions of the snapper that floated or swam erratically died from

physiological stress or were subject to predation soon after release. In addition, some of the snapper

that swam down on release probably died later as a result of gas bladder rupture or other

physiological damage, as summarized in Render & Wilson (1996). It is beyond the scope of this

study to draw such a conclusion, as no specific data were available on the long-term fate of the

released snapper. Survival rates from cage studies must be interpreted carefully when compared to

surface release studies. Cage studies eliminate predation risk and, by forcing submergence, may

enhance the survival of fish that would have otherwise remained at the surface either floating or

swimming erratically.
348

400 500 600 100 200 300 0 Kept Dead

Floating

Erratic swimming

Swim Down

300

275

250

225

200

175

150

125

100

75

50

25

0

Total Length (mm)

Galveston

N = 1,274

400 500 600 100 200 300 0 Kept Dead

Floating Erratic swimming

Swim Down

250

225

200

175

150

125

100

75

50

25

0

Total Length (mm)

Port Aransas

N = 784

400 500 600 100 200 300 0 Kept Dead

Floating Erratic swimming

Swim Down

375

350

325

300

275

250

225

200

175

150

125

100

75

50

25

0

Total Length (mm)

Port Isabel

N = 1,770

400 500 600 100 200 300 0 Kept

Dead

Floating

Erratic swimming

Swim Down

100

75

50

25

0

Total Length (mm)

Pt. Isabel

(August)

N = 870

400 500 600 100 200 300 0 Kept Dead

Floating Erratic swimming

Swim Down

300

275

250

225

200

175

150

125

100

75

50

25

0

Total Length (mm)

Pt. Isabel

(September)

N = 900

A. Galveston B. Port Aransas

C. Port Isabel

Figure 6.37. Size and fate of red snapper caught and measured during Texas recreational headboat

sets in August and September 1999 by fishing port. A. Galveston; B. Port Aransas;

C. Port Isabel.
349

Red Snapper Discards, Landings and CPUE (Catch per Unit Effort)

Overall, 87.1% of the red snapper catch was discarded (Table 6.14). By weight, discarded snapper

made up 75.2% of the catch (Table 6.15). Galveston had the largest discard:landing ratio (211:1),

the smallest mean weight per fish sampled (0.7 kg, 0.3 s.d.), and the smallest mean fish total length

(343 mm, 47.3 s.d.; 13.5 inches, 1.9 s.d) (Table 6.16). Port Aransas had the lowest discard:landing

ratio (5.2:1) along with the largest weight per fish (0.9 kg, 0.7 s.d.), and total length per fish (387

mm, 62.7 s.d.; 15.3 inches, 2.5 s.d.). Estimates of total discards per port are conservative because

of the need to subdivide the boat when the number of fishers was too large for two observers to manage efficiently. Data from the 1995 commercial red snapper hand line observer program (Schirripa

& Legault 1999) indicated that only 40.7% of red snapper were discarded, constituting 18.6% of the

snapper catch by weight. Fish approximately 375 mm (15 inches) or larger were retained.

Mean CPUE for red snapper was 2.8 fish per angler hour (2.19 s.d.). There were no significant

differences in CPUE between ports (p >0.0258). CPUE from the present study is higher than all

values reported in Schirripa & Legault (1999) for the Gulf of Mexico recreational fishery. Their

CPUE measure is derived exclusively from the Marine Recreational Fishery Statistics Survey

(MRFSS) and Texas Parks & Wildlife (TPW) harvest survey data. However, headboat sampling was

discontinued by the MRFSS in 1985, and TPW does not sample headboat landings. The NMFS

Headboat Survey, begun in 1985, includes Gulf of Mexico ports and estimates headboat landings.

Currently, there is no direct measure of discards included in the red snapper stock assessment.

Table 6.14. Discards and landings (numbers) of red snapper measured from Texas recreational

headboat sets in August and September 1999 by fishing port.

Galveston Port

Aransas

Port

Isabel

(Aug)

Port

Isabel

(Sept)

Total

Discards 1,268 658 730 668 3,324

Landings 6 126 133 229 494

Total 1,274 784 863 897 3,818

D:L 211.3 : 1 5.2 : 1 5.5 : 1 2.9 : 1 6.7 : 1

Table 6.15. Discards and landings (whole weight, kg) of red snapper measured from Texas

recreational headboat sets in August and September 1999 by fishing port. Number

in parentheses is the mean weight per fish sampled.

Galveston Port

Aransas

Port Isabel

(Aug)

Port Isabel

(Sept) Total

Discards 879 (0.69) 525 (0.80) 511 (0.69) 344 (0.51) 2,259 (0.68)

Landings 10 (1.69) 207 (1.64) 275 (2.07) 254 (1.11) 746 (1.51)

Total 889 (0.70) 732 (0.93) 786 (0.90) 598 (0.67) 3,005 (0.79)
350

Table 6.16. Discards and landings (mean total length, mm) of red snapper measured from Texas

recreational headboat sets in August and September 1999 by fishing port. Number

in parentheses is the standard deviation of total length.

Galveston Port Aransas Port Isabel

(Aug)

Port Isabel

(Sept) Total

Discards 342 (46.5) 371 (39.6) 351 (52.4) 314.6 (37.1) 344 (48.4)

Landings 478 (23.8) 468 (91.9) 518 (66.6) 419 (31.6) 459 (74.2)

Total 343 (47.3) 387 (62.7) 376 (81.5) 341 (57.9) 359 (65.1)

This study is the first time that observers have been placed on board recreational headboats to

directly document the quantity and characteristics of red snapper discards and landings on the Texas

coast. Texas accounts for 85% of Gulf of Mexico headboat red snapper landings and 25% of

Gulfwide recreational red snapper landings (Schirripa & Legault 1999). If current minimum size

limits had been in effect during the time of this study the discard rate would still have been 78% in

federal waters (400 mm, 16 inch minimum size) and 64% in Texas state waters (375 mm, 15 inch

minimum size), much higher than that reported from the commercial fishery. Although limited in

duration, this study demonstrates the importance of discards to the Texas red snapper fishery as well

as to red snapper stock assessment in the Gulf of Mexico. It would be beneficial to continue,

optimize, and expand this type of study to cover the entire red snapper season in all areas of the Gulf

of Mexico where headboat sampling occurs.

ACKNOWLEDGMENTS

I thank Russell O’Brien for his work in coordinating fishery observers in the field, as well as the

fishery observers, themselves. Headboat captains, crews and recreational fishers in Galveston, Port

Aransas and Port Isabel were essential and voluntary participants in the study, providing willing

access to fish brought on board. Joan Holt provided valuable suggestions at early project stages. The

University of Texas Marine Science Institute provided institutional support. This study was made

possible by the financial support of the Gulf & South Atlantic Fisheries Foundation, Inc., Tampa.

REFERENCES

Gitschlag, G.R. & M.L. Renaud. 1994. Field experiments on survival rates of caged and released

red snapper. North American Journal of Fisheries Management 14: 131-136.

GMFMC. 1981. Environmental Impact Statement and Fishery Management Plan for the Reef Fish

Resources of the Gulf of Mexico. Florida Sea Grant College Gulf of Mexico Fishery

Management Council, Tampa, FL. 154 pp.

MRAG Americas, I. 1997. Consolidated report on the peer review of red snapper (Lutjanus

campechanus) research and management in the Gulf of Mexico. The Office of Science and

Technology, National Marine Fisheries Service. 86 pp.
351

MRAG Americas, I. 1999. NMFS Response to the 1997 Peer Review of Red Snapper (Lutjanus

campechanus) Research and Management in the Gulf of Mexico. National Marine Fisheries

Service, St. Petersburg, FL. 146 pp.

Parrack, N.C. 1986. Review and update of Gulf of Mexico red snapper biometrics: 1. Length-weight

relations, 2. Length-length conversions. NMFS, SEFC, Miami Laboratory, Miami, FL, Miami,

FL. 26 pp.

Render, J.H. & C.A. Wilson. 1994. Hook-and-line mortality of caught and released red snapper

around oil and gas platform structural habitat. Bulletin of Marine Science 55: 1106-1111.

Render, J.H. & C.A. Wilson. 1996. The effect of gas bladder deflation on mortality of hook-and-line

caught and released red snappers: implications for management. Pp. 244-253. In F. ArreguinSanchez, J.L. Munro, M.C. Balgo & D. Pauly (eds.) Biology and culture of tropical groupers and

snappers. ICLARM Conference Proceedings 48.

Schirripa, M.J. & C.M. Legault. 1999. Status of the red snapper in U.S. waters of the Gulf of

Mexico: Updated through 1998. SE Fisheries Science Center, Sustainable Fisheries Division,

Miami, FL. 86 pp. 

Barbara A. Dorf is a Natural Resource Specialist for Texas Parks & Wildlife. She can be reached

at Texas Parks & Wildlife, Coastal Fisheries Division, 702 Navigation Circle, Rockport, Texas,

78382-2779. E-mail: Barbara.Dorf@tpwd.state.tx.us.
352

EVALUATION OF RED DRUM (Sciaenops ocellatus) STOCKING SUCCESS:

GENE-MARKING OF FINGERLINGS RELEASED

INTO EAST MATAGORDA BAY, TEXAS

Rocky Ward

Ivonne R. Blandon

William J. Karel

Robert L. Colura

Lawrence W. McEachron

Coastal Fisheries Division

Texas Parks and Wildlife Department

ABSTRACT

Stocking of artificially spawned fingerlings is an important component of the management program

for red drum in Texas waters. Gene-marking, using an uncommon allele of the dimeric esterase

locus, was employed to examine survival and quantify recruitment of stocked red drum to the total

estuarine population. Between 1993 and 1995 2,049,747 red drum fingerlings were stocked into East

Matagorda Bay, Texas. Of these, approximately 50% were heterozygous and 25% were homozygous

for an uncommon allele of the dimeric esterase locus. Subsequent electrophoretic examinations of

6,081 red drum collected between 1993 and 1997 in routine resource monitoring or in creel surveys

in this bay and in adjacent reaches of neighboring bays found no evidence of increases in the

frequency of the marker-allele in supplemented year-classes. Previous studies have shown

enhancement of red drum populations following stockings in Texas marine waters. Failure to

demonstrate enhancement in the current study may be related to specific conditions under which

stocking efforts were made; including physical conditions at time of stocking, quality of the stocked

cohort, and density of naturally spawned conspecifics.
353

HIGH RESOLUTION OF GULF STURGEON POPULATION STRUCTURE WITH

MULTILOCUS MICROSATELLITE DNA GENOTYPES

Tim L. King

Barbara A. Lubinski

USGS-BRD Leetown Science Center

Aquatic Ecology Laboratory

Kearneysville, WV

Isaac I. Wirgin

Nelson Institute of Environmental Medicine

New York University Medical Center

ABSTRACT

Tandemly repeated DNA simple sequence motif markers, or microsatellite loci, have become the

molecular genetic tool of choice in an increasingly diverse range of studies. Microsatellite DNA

markers offer the potential of high levels of allelic variation per locus, and perhaps a higher degree

of population resolution, even in species of conservation concern characterized by small effective

population sizes. The Gulf sturgeon ( Acipenser oxyrinchus desotoi) was designated as a threatened

species under the U.S. Endangered Species Act in 1991. Recent studies of mitochondrial DNA

variation suggested the presence of significant genetic differentiation in the form of at least four

regional or river-specific populations along the Gulf coast. To assess the utility of microsatellite

markers for delineating population structure in Gulf sturgeon, we determined multilocus (N=7)

microsatellite genotypes in over 220 fish from the Pearl, Yellow, Apalachicola, and Suwannee River

drainages. Significant allelic heterogeneity was observed among all drainage systems surveyed. A

maximum likelihood assignment test was used to identify population structure among Gulf sturgeon

populations. These analyses correctly assigned each fish to its respective drainage in greater than

90% of comparisons. These preliminary results indicate that variation in microsatellite DNA

variation can serve as a powerful discriminator of genetic stock structure among geographically

proximal rivers and that little gene exchange occurs among regional drainages (i.e., the presence of

strong homing fidelity). The results suggest the presence of at least four distinct management units

among the Gulf sturgeon surveyed.
355

SESSION 7: 

OFFSHORE PLATFORM COMMUNITIES II

Moderators: Benny Gallaway

Gregg Gitschlag

Date: October 25, 2000

Presentation Author/Affiliation

Fisheries Impacts of Underwater

Explosives Used in Platform Salvage in

the Gulf of Mexico

Gregg Gitschlag

National Marine Fisheries Service

Southeast Fisheries Center

Galveston, TX

Michael J. Schirripa

National Marine Fisheries Service

Northwest Fisheries Science Center

Newport, OR

Joseph E. Powers

National Marine Fisheries Service

Southeast Fisheries Center

Miami, FL

Fish and Epifaunal Community

Observations at an Artificial Reef Near a

Natural Coral Reef: Nineteen Years at

High Island Platform A389-A, from Bare

Steel to Coral Habitat

Gregory S. Boland

Minerals Management Service

Gulf of Mexico OCS Region

Fish Assemblages Around Oil and Gas

Platforms in the Northeastern Gulf of

Mexico: Developing a Survey Design

Kevin R. Rademacher

Jeffery H. Render

National Marine Fisheries Service

Mississippi Laboratories

Seasonal and Spatial Variation in the

Biomass and Size Frequency Distribution

of Fish Associated with Oil and Gas

Platforms in the Northern Gulf of Mexico

David R. Stanley

BEAK International

Ontario, Canada

Charles A. Wilson

Coastal Fisheries Institute

Center of Coastal, Energy and Environmental

Resources

Louisiana State University

(continued on next page)
356

Presentation Author/Affiliation

Rigs and Reefs: A Comparison of the Fish

Communities at Two Artificial Reefs and a

Production Platform

Charles A. Wilson

Mark Miller

Department Oceanography and Coastal

Sciences

Louisiana State University

Rick Kasprzak

Louisiana Dept of Wildlife and Fisheries

Dave Stanley

Beak International

The Variation of Fish Community

Structure Around Oil and Gas Platforms in

the Northern Gulf of Mexico

(Document not submitted)

James W. Heath

Charles A. Wilson

David Stanley
357

1 Michelle Morin, Minerals Management Service.

2

Provided by first author.

3

Oil, Gas, and Sulphur Operations in the Outer Continental Shelf, 30 CFR (250 series).

FISHERIES IMPACTS OF UNDERWATER EXPLOSIVES USED IN

PLATFORM SALVAGE IN THE GULF OF MEXICO

Gregg R. Gitschlag

National Marine Fisheries Service

Southeast Fisheries Center

Galveston, TX

Michael J. Schirripa

National Marine Fisheries Service

Northwest Fisheries Science Center

Newport, OR

Joseph E. Powers

National Marine Fisheries Service

Southeast Fisheries Center

Miami, FL

INTRODUCTION

As of 31 January 2000 there were 3,967 oil and gas structures1

 in the Gulf of Mexico (GOM).

Federal regulations require removal of platforms within a year of lease termination. According to

data from the National Marine Fisheries Service (NMFS) Platform Removal Observer Program2

 that

includes removals in both federal and state waters, from 1989–98 an annual average of 96 structures

were salvaged using explosives. For the same period, MMS data for federal waters indicate underwater explosives were used in 64% of all removals (submerged wells not included in these data).

MMS regulations require removal of structures to a minimum depth of 5 m below the seafloor.3

Since forty- to fifty-pound explosive charges are commonly used to sever platform pilings, hundreds

of pounds of explosives, primarily Comp-B and C-4, are detonated at most offshore platforms.

Offshore platforms serve as excellent artificial reef habitat attracting a vast array of marine life

(Dugas et al. 1979; Hastings et al. 1976; Lewbel et al. 1987; Scarborough-Bull 1989; Sonnier et al.

1976; Stanley & Wilson 1990). The use of underwater explosives can severely impact fish and other

marine life during the removal process. Of special concern is the commercially and recreationally

important red snapper which is already severely overfished (Goodyear and Phares 1990; Goodyear

1996; Cowan 1998; Schirripa 1998).

This report describes the first comprehensive study to quantitatively assess fisheries impacts of the

explosive removal of offshore oil and gas structures. Mortality estimates from platform removals
358

were calculated and used in stock assessment analyses to determine the relative importance of this

activity compared with other sources of mortality. The results of these analyses provide managers

with information needed to manage fisheries.

METHODS

Between August 1993 and May 1999 data were collected at nine of ten platforms studied to estimate

total fish mortality (Table 7.1, Figure 7.1). Prior to detonation of explosives fish were captured,

tagged and released alive. After explosives were detonated field personnel operating from inflatable

boats used dip nets to collect all dead fish that floated to the surface while divers manually sampled

dead fish that sank to the sea floor. Underwater sampling techniques included transect line surveys,

circular surveys, and sampling frames placed beneath the platform. To increase efficiency,

procedural modifications were made early in the study and only final sampling protocols are

described here (Figure 7.2). Twenty-four circular surveys measuring 6.7 m (22 ft) in diameter and

four 100 m (328 ft) transect lines were sampled. At one platform (WC172), 200 m (656 ft) transect

lines were surveyed. Divers collected discrete samples of dead fish in 25 m (82 ft) increments along

the transect lines. Sampling width was either 1 or 2 m (3 or 6 ft) on either side of the line depending

on underwater visibility. Sampling frames usually provided 20–30% coverage of the footprint area

under the platform. Generally, fish smaller than 8 mm total length were not sampled. Due to time

constraints and safety considerations, not all targeted samples were always collected.

Fish mortality was estimated by multiplying fish density (number of fish in sample divided by area

sampled) by total area for each region of interest (i.e. 0–25 m radius around the platform, 25–50 m,

50–75 m, etc.). Total estimated mortality at each platform was calculated by adding the estimated

fish mortalities at the surface, beneath the platform and in the open water around the platform to a

maximum distance of 100 m. Data from transect and circular surveys were combined to provide one

estimate of fish mortality in the open water area. Population size was estimated for individual

species using direct proportions of tagged to untagged fish present before and after detonation of

explosives:

Nb = Na X Ntb /Nta

Where Nb is the number of live fish present before blasting, Na is the number of dead fish collected

after blasting, Ntb is the number of fish tagged and released before blasting, and Nta is the number of

dead, tagged fish collected after blasting.

RESULTS

Fish < 8 cm TL (Total Length)

With the exception of this section, results describe only fish greater than or equal to 8 cm in total

length. This appeared to be the minimum size which divers routinely collected by hand. At one site

where a large number of very small fish were observed, all fish regardless of size were painstakingly

collected within a single 1.5 X 1.5 m frame on the sea floor beneath the platform. Specimens

included 117 vermilion snapper (Rhomboplites aurorubens), 6 round scad (Decapterus punctatus),
359

Table 7.1. Estimated mortality and descriptive statistics by species and platform.

SPECIES

SMI 23WD 30ST 146SS 158WC 172WC 173WC 181SS 209GA 288TotalMeanStd errorStd devVarlevelconfidence95%

Almaco jack 29 0 1 0 0 0 0 0 0 30 3 3 10 92 7

Atlantic bumper 0 0 0 0 46 201 0 0 0 247 27 22 67 4471 51

Atlantic croaker 0 0 0 0 0 7 0 0 0 7 1 1 2 5 2

Atlantic spadefish 2069 631 698 1689 911 1068 2401 633 2774 12875 1431 275 824 679238 634

Atlantic thread herring 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0

Belted sand bass 11 0 0 0 1 0 17 0 0 29 3 2 6 40 5

Bermuda chub 0 0 0 0 0 0 43 0 0 43 5 5 14 204 11

Black drum 0 19 6 0 2 14 0 0 3 44 5 2 7 48 5

Blue runner 611 33 1592 1069 219 0 684 13 646 4867 541 181 542 294154 417

Bluespotted searobin 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0

Chub mackerel 0 0 0 0 0 0 0 0 4 4 0 0 1 2 1

Cocoa damselfish 0 0 0 0 0 0 4 0 0 4 0 0 1 2 1

Crevalle jack 0 0 0 0 5 0 0 0 0 5 1 1 2 2 1

Cubbyu 0 0 0 0 0 0 0 66 66 7 7 22 487 17

Gag 6 6 2 0 0 0 0 0 0 14 2 1 3 7 2

Gray triggerfish 144 1 16 116 13 0 22 43 44 399 44 17 52 2685 40

Great barracuda 5 0 0 0 0 0 0 0 0 5 1 1 2 2 1

Guaguanche 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0

Gulf toadfish 0 0 0 0 0 0 0 0 24 24 3 3 8 63 6

Hardhead catfish 0 6 0 0 4 397 0 0 0 407 45 44 132 17466 101

Harvest fish 0 0 0 0 0 5 0 00 0 5 1 1 2 2 1

Ladyfish 0 3 0 0 0 0 0 0 0 3 0 0 1 1 1

Lane snapper 34 0 60 0 1 0 0 193 82 371 41 22 65 4197 50

Leopard toadfish 53 0 0 0 0 0 0 0 0 53 6 6 18 317 14

Lookdown 0 3 0 0 0 0 0 0 0 3 0 0 1 1 1

Mangrove snapper 63 364 240 44 1 1 0 324 64 1100 122 49 146 21322 112

Molly miller 0 0 0 0 0 0 4 0 0 4 0 0 1 2 1

Mullet 0 22 0 0 0 0 0 0 0 22 2 2 7 54 6

Ocean triggerfish 0 0 2 0 0 0 0 0 0 2 0 0 1 0 1

Pigfish 23 0 0 0 3 0 0 0 31 57 6 4 12 141 

Pinfish 0 0 0 0 0 3 0 0 17 20 2 2 6 33 4

Planehead filefish 44 0 0 0 0 0 0 0 0 44 5 5 15 213 11

Red drum 0 0 0 35 0 0 0 0 19 54 6 4 12 156 10
Table 7.1. (continued)

360

SPECIES

SMI 23WD 30ST 146SS 158WC 172WC 173WC 181SS 209GA 288TotalMeanStd errorStd devVarlevelconfidence95%

Red snapper 1193 24 298 296 498 709 709 418 487 4632 515 111 332 110174 255

Remora 0 0 0 0 13 0 0 0 0 13 1 1 4 19 3

Rock hind 0 0 9 0 0 0 7 0 5 22 2 1 4 14 3

Scaled sardine 0 0 0 0 8 0 0 0 0 8 1 1 3 7 2

Scamp 3 0 0 0 0 0 0 0 0 3 0 0 1 1 1

Schoolmaster 9 0 0 0 0 0 0 0 0 9 1 1 3 9 2

Scrawled filefish 0 0 0 0 0 0 4 0 0 4 0 0 1 2 1

Sergeant major 0 0 0 0 5 16 0 0 0 21 2 2 5 30 4

Sharksucker 0 0 0 0 0 3 0 0 0 3 0 0 1 1 1

Sheepshead 330 1007 120 395 457 386 968 61 370 4094 455 110 329 108436 253

Silk snapper 0 0 0 39 0 0 0 0 0 39 4 4 13 166 10

Silver trout 0 0 140 0 1 0 0 0 0 141 16 16 47 2173 36

Spanish sardine 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0

Speckled trout 0 3 0 0 0 0 0 0 0 3 0 0 1 1 1

Tomtate 0 0 0 0 0 0 0 0 464 464 52 52 155 23929 119

Unknown damselfish 0 0 0 0 0 0 0 0 16 16 2 2 5 30 4

Unknown eel 0 0 0 0 0 0 0 27 0 27 3 3 9 81 7

Unknown soapfish 0 0 1 0 0 0 0 0 38 39 4 4 13 161 10

Unknown 0 6 0 0 0 0 0 46 0 52 6 5 15 231 12

Whitespotted soapfish 23 0 3 0 4 0 10 5 53 97 11 6 17 302 13

Yellow chub 1 0 0 0 0 0 0 2 5 8 1 1 2 3 1

Yellowtail snapper 6 0 0 0 0 0 0 0 0 6 1 1 2 4 2

Total 4657 2128 3188 3682 2193 2812 4874 1765 5216 30513 3390 429 1288 1658640 990

2 lane snapper (Lutjanus synagris), and 2 scaled sardine (Harengula pensacolae). Mortality of

vermilion snapper measuring < 8 cm TL within the footprint area of this platform was estimated at

approximately 5,900. Estimated mortality of all small fish in the footprint area alone exceeded 6,200

compared with a total estimated mortality (footprint area plus 100 m radius) of approximately 4,900

for fish measuring >8 cm.

Estimated Mortality

Total estimated finfish mortality per platform ranged from 1,765–5,216 with a mean of 3,390,

standard error 429, and 95% confidence level of 990. Four species including Atlantic spadefish
Figure 7.1. Map of study sites. Dark circles represent platforms where fish mortality was estimated from samp

the sea surface and bottom. The white circle represents a platform where only sea surface sampling 
362

Figure 7.2. Schematic of sampling design showing transect lines, circular surveys, and sampling

area under platform.

(Chaetodipterus faber), blue runner (Caranx fusus), red snapper (Lutjanus campechanus), and

sheepshead (Archosargus probatocephalus) accounted for 86% of total estimated mortality (Table

7.2). Mean estimated mortality per platform was 1,431 for Atlantic spadefish, 541 for blue runner,

515 for red snapper, and 455 for sheepshead. Range in estimated mortality by platform was

631–2,774 for Atlantic spadefish, 0–1,592 for blue runner, 24–1,193 for red snapper, and 61–1,007

for sheepshead.

Fish mortality resulting from the use of underwater explosives may be affected by many factors

including but not limited to water depth (<20 m vs >20 m), platform location (<=92o vs >92o),

platform age (<25 year vs >25 year), season (spring vs summer), surface temperature (<30oC vs

>=30oC), surface salinity (<=26 ppt vs >26 ppt), and platform size. Statistical analysis of estimated

mortality by each of these parameters indicated no significant difference from the null hypothesis

for each of the top four impacted species. One exception was the depth analysis for sheepshead

which was marginally significant with a P value of 0.05. Longitude was used as an index of platform

location, and platform size was indexed using the volume of water enclosed within the boundary of

the platform.
363

Table 7.2. Estimated mortality of the five most impacted species.

SPECIES

Total estimated

mortality

% of total estimated

mortality

Atlantic spadefish 12875 42

Blue runner 4867 16

Red snapper 4632 15

Sheepshead 4094 13

Total 86

Population Estimates and Mortality Rates

Pre-detonation population estimates were calculated whenever a minimum of 10 individuals of a

given species were tagged and released. The maximum number of tags released for a single species

at a single platform was 502 for Atlantic spadefish. In most tag/recapture experiments using

conventional techniques, recapture rates of 2–5% are anticipated. Recovery rates as high as 73%

(Table 7.3) attest to the effectiveness of sampling with explosives. Red snapper estimates at 7

platforms ranged from 503–1,943 with a mean of 905 and standard error of 196 (Table 7.4). Atlantic

spadefish estimates at three platforms ranged from 1,432–1,782 with a mean of 1,564 and standard

error of 110. The blue runner population was estimated at 558 at one platform.

Mortality rates (estimated mortality divided by population estimate) were determined for species

and platforms where pre-detonation population estimates were calculated (Table 7.5). Rates for red

snapper varied from 59–88% with a mean of 71% and standard error of 4. Atlantic spadefish rates

ranged from 72–135% with a mean of 108% and standard error of 19 while one rate of 123% was

calculated for blue runner.

Fish Density Around Platforms

Density of fish collected along transect line surveys from eight platforms were analyzed using the

two sample t-test. There was a significant difference (P=0.000) in fish density (log(density + 1)

transformed) for samples collected at 0–25 m (0.027 fish/m3

) and 25–50 m (0.002 fish/m3) distances

from platforms. A significant difference (P=0.003) was also found using data from circular surveys

collected at 0–6.7 m and 18.3–25.0 m from the platform. Fish density was higher closer to the

platform (0.051 fish/m3 vs 0.007 fish/m3). Fish density for transect data collected between 50–75

m and 75–100 m from platforms averaged 0.001 and 0.000 fish/m3.
364

Table 7.3. Recapture rates (100 x number of tags recovered/number of tags released) for tagrecapture study.

Platform

SPECIES SMI 23 ST 146 SS 158 WC 172 WC 173 WC 181 SS 209 GA 288

Almaco jack 25

Atlantic spadefish 13 72 34

Blue runner 29

Gray triggerfish 24 13 30

Red snapper 41 49 73 19 20 62 44

Table 7.4. Population estimates by species and platform.

Platform

SPECIES

SMI 23ST 146SS 158WC 172WC 173WC 181SS 209GA 288MeanerrorStddevStdVarconfidence95%

Almaco jack 28 28 0

Atlantic spadefish 1432 1477 1782 1564 110 190 36258 473

Blue runner 558 558

Gray triggerfish 129 93 63 95 19 33 1092 82

Red snapper 1943 503 597 1091 1048 601 553 905 196 517 267546 478

Table 7.5. Mortality rates (100 x estimated mortality / population estimate) by species and platform.

Platform

SPECIES

SMI 23ST 146SS 158WC 172WC 173WC 181SS 209GA 288MeanerrorStddevStdVarconfidence95%

Almaco jack 104 104 0

Atlantic spadefish 118 72 135 108 19 32 1044 80

Blue runner 123 123

Gray triggerfish 112 125 68 102 17 30 874 73

Red snapper 61 59 83 65 68 70 88 71 4 11 121 10
365

Comparison of Estimated Mortality and Size of Positively and Negatively Buoyant Fish

There was no consistent relationship between the number of red snapper carcasses collected at the

surface and the estimated number of red snapper that sank to the sea floor after detonations (Table

7.6). Results for all fish species combined were also highly variable. Paired t-test of log transformed

ratios of positively (floating) to negatively buoyant (sinking) fish showed a significant difference

between red snapper and all species combined. More red snapper floated to the surface than sank

at four of eight study sites compared with only two of nine for all fish species combined. Ratios of

floating to sinking red snapper ranged from 0.03–6.74 per platform while the range for all species

combined was 0.03–1.47. Extremely low values indicate that few fish floated to the surface. A ratio

of 0.03 means that an estimated 33 times more fish sank to the sea floor than floated to the surface.

Results indicate that more fish generally sink than float and that actual total fish mortality may be

considerably more than what is observed at the surface.

GLM analysis of red snapper length by factors of platform and buoyancy showed a significant

difference (P=0.00) for both factors and interaction. Mann-Whitney tests used to compare length of

floating vs. sinking red snapper at each platform showed mixed results. A significant difference

(P<0.05) in total length of positively vs. negatively buoyant fish was found at four platforms, but

no difference was apparent at four other platforms (Table 7.7). Mean total length was larger for

positively buoyant fish at all platforms except one in 15 m of water where negatively buoyant fish

were significantly larger. Difference between mean lengths of positively and negatively buoyant red

snapper was 2.6 cm (36.7–34.1 cm).

Estimating Red Snapper Impacts Across the U.S. Gulf of Mexico

Using Stock Assessment Techniques

Since results did not show a consistently significant difference between length of positively and

negatively buoyant fish at individual platforms and since the overall difference in mean length of

positively and negatively buoyant fish was small (2.6 cm), it should be acceptable to utilize

historical data from the NMFS Platform Removal Observer Program2

, which is only available for

positively buoyant fish, to enhance the present data set with additional red snapper lengths. This

contributed an additional 13,527 red snapper lengths for a total of 16,510 collected at 116 explosive

structure removals.

Opportunistic surface collections made by the NMFS Platform Removal Observer Program lend

support to the concept of fewer red snapper mortalities at single pile caissons than at multi-leg

platforms which are more structurally complex. Consequently, a moderately high estimate of fish

mortality was obtained by assuming red snapper mortality at all structure types was the same as that

found in the present study. Since no red snapper were collected in the Observer Program at depths

less than 7 m, structures shallower than this were assumed to have no red snapper mortality.

Analysis of the combined data set (present study plus NMFS data) using GLM single factor analysis

and Tukey-Kramer studentized range test for paired comparisons indicated red snapper collected

at platforms in 20–30 m were larger than those at platforms in shallower and greater depths.

Consequently, all length records were sorted into two depth zones (7–20 m and >30 m vs. 20–30 m)
366

Table 7.6. Comparison of red snapper mortalities collected at the surface (floaters) with estimated

mortality from the sea floor (sinkers).

 Platform Floaters Sinkers Total

Ratio

floater/sinker

Percent

floater/total Depth (m)

 WC 172 417 81 498 5.15 84 15

 WC 173 120 589 709 0.20 17 15

 SS 158 10 286 296 0.03 3 17

 WC 181 73 636 709 0.11 10 18

 GA 288 202 285 487 0.71 41 23

 SMI 23 714 479 1193 1.49 60 25

 ST 146 238 58 296 4.10 80 28

 SS 209 364 54 418 6.74 87 32

 Total 2138 2468 4606 46

Table 7.7. Comparison of total length of positively (floater) and negatively (sinker) buoyant red

snapper by platform.

 Platform

Mean TL

floaters N floater

Mean TL

sinker N sinker

MannWhitney P Depth (m)

 WC 172 34.1 416 40.1 17 0.06 15

 WC 173 44.4 120 43.1 83 0.45 15

 SS 158 56.8 10 45.7 23 0.01 17

 WC 181 49.6 73 30.9 138 0 18

 GA 288 31.5 202 25.1 42 0 23

 SMI 23 33.1 714 29.3 81 0.01 25

 ST 146 44.7 238 40.2 5 0.4 28

 SS 209 38.5 361 38 9 0.68 32

as were counts of explosive structure removals. Estimated annual red snapper mortality per structure

(515) was multiplied by the ten year (1989–98) average annual number of explosive structure

removals in each depth zone (from NMFS Platform Removal Observer Program data) to yield an

estimate of red snapper mortality for each depth zone. Since stock assessment analysis requires a

length for each fish record, red snapper lengths in each depth zone were expanded by replication to

construct a data set with the number of records equal to the mortality estimate. To establish an upper
367

limit for impact assessment, this expanded data set was doubled to yield an estimated mortality of

82,400 and used in stock assessment analysis to determine the effect of mortality due to explosive

structure removal on the overall red snapper stock. Despite natural variation in the data and possibly

higher mortality at depths greater than study depths, doubling the moderately high estimate is

expected to provide a value that far exceeds the actual mortality.

Length frequencies of red snapper were converted to age frequencies using Table 7.7.1 of Schirripa

and Legault (1999), the most recent red snapper stock assessment analysis. The additional mortality

at age (1989–98) implied by the doubled estimate was added to each year of the annual fishing

induced mortality at age estimated from other sources: commercial, recreational, discard mortality

and bycatch. The stock assessment analysis in Schirripa and Legault (1999) was then repeated using

the mortality at age including explosive platform mortality for each year, 1989–98.

Impacts on Red Snapper

Results of the refitting of the red snapper assessment including platform removal estimate (arbitrary

doubling of the moderately high estimate of mortality) were compared to the base case assessment

from Schirripa and Legault (1999; Figure 7.3). The impact of including platform removal data was

that abundance estimates were almost indistinguishable from the original assessment (Figure 7.3).

The differences were well within the statistical estimation variances for the original assessment.

Note that these results are for double the estimated number of fish mortalities at explosive structure

removals. Actual impacts are likely to be less.

Impacts on Gag and Red Drum

Of the species encountered in these field studies, in addition to red snapper, only gag and red drum

have stock assessments conducted on them by the NMFS. Annual estimated mortality of gag at

explosive platform removals (using the same assumptions made in the red snapper analysis) was 256

fish per year. Comparison with results from the most recent gag stock assessment (Schirripa and

Legault 1997) indicates this represents 0.04% of the average annual mortality from other sources.

Current methods of assessment would not detect such small changes in magnitude. The annual

estimated mortality of red drum at explosive structure removals (using the same assumptions made

in the red snapper analysis) was 961 fish per year. Comparison with results from the most recent red

drum stock assessment (Porch 2000) show this was 0.03% of the average annual mortality from

other sources. Such a small change is indistinguishable using current methods of assessment. 

Assessing Future Impacts on Red Snapper (1999–2023)

Unlike data from the NMFS Platform Removal Observer Program2

, the MMS data set1 did not

include subsea wells, flare piles or any removals that occurred in state waters. These two data sets

were used in conjunction with Pulsipher et al.’s (in press) forecast of future platform removals to

assess future impacts on red snapper. If explosives continue to be used at approximately 64% of all

removals, then fish populations at 119 platforms and caissons (0.64 x 186 predicted annual platform

removals) will be impacted annually. As of 31 January 2000, 8.8% (351 of 3,967) of structures

present in the GOM were in depths less than about 7 m. Reducing the 119 predicted explosive
368

Figure 7.3. Red snapper assessment results, including platform removals, using Data Set E

(represents arbitrary doubling of moderate to high estimate of red snapper mortality

at platforms) compared to base case assessment (base). The left column gives

numbers at selected ages by year; the right column gives numbers at age for selected

years.
369

removals by this factor yields 109. From 1989–98 NMFS recorded an additional 126 removals in

depths >7 m including submerged wells and flare piles in federal waters and structures of all types

in state waters. This represents 10.8% (126/1172) of all removals (explosive and non-explosive) in

the 1989–98 MMS data base. Assuming that this ratio remains constant in the future, the total

number of explosive structure removals predicted annually will increase by an additional 20 (0.108

x 186) to provide a total of 129 (109 + 20) annual explosive structure removals in depths >7 m. This

moderately high estimate based on all structure types having the same mortality of red snapper

yields a projected annual mortality at explosive structure removals of 66,435 red snapper. This is

considerably less than the 82,400 representing double the average annual estimate for 1989–98.

Consequently, the impact of a projected increase in average annual explosive structure removals is

not expected to be distinguishable from benchmarks assuming other influencing factors remain

constant and removal forecasts are accurate.

DISCUSSION

One obvious finding from this study is the lack of significant difference in estimated mortality as

a function of test parameters including depth, longitude, surface temperature and salinity. This was

due to a variation in fish abundance between platforms, small sample size in some cells, and a

generally narrow range observed for test parameters. For example, there was general consistency

in platform complexity (except for one platform) and a fairly narrow range in depth, surface salinity

and surface temperature. Estimated mortality of fish at a given platform within study depths from

14–28 m ranged from approximately 2,000–5,000 for fish measuring greater than 8 cm TL. In

general, failure to detect a significant difference in various parameters tested in this study does not

indicate that these factors may not affect fish distribution. It does indicate that parameter values

encountered during the study were not dissimilar enough to cause differences in fish distribution

given the small number of platforms studied. For at least some parameters, when a sufficient change

occurs in values beyond the ranges found in this study, fish assemblages and resulting fishery

impacts will undoubtedly change. For example, species distribution in general has been reported to

change as fish move from shallower to deeper water in relation to changing seasons and

temperatures (Bradley and Bryan 1974; Hastings et al. 1976) 

SUMMARY

The most severely impacted fish species in terms of highest numbers of estimated mortalities were

Atlantic spadefish, blue runner, red snapper, and sheepshead. These four species accounted for 86%

of estimated mortality. Of all species collected, the NMFS conducts stock assessments on only three:

red snapper, gag and red drum. For red snapper, even when the mortality estimate was doubled,

impacts were estimated to be small, well within the variation of our current assessments, and would

not alter current determinations of status or current management recovery strategies. Similarly,

current methods of assessment would not detect the even smaller changes in magnitude of gag and

red drum. In general, results indicated no significant difference in estimated mortality of red snapper

by depth, longitude, platform age, season, surface salinity, and surface temperature in the study area

(14–32 m) during May to September. Future impacts to the red snapper stock were predicted based

on forecasts of future structure removals reported by Pulsipher et al. (in press). Estimates of future

mortality were less than the doubled value of current red snapper mortality at explosive structure
370

removals and within the variation of our current assessments. Given the assumptions used in these

forecasts, predicted future mortality would not alter current determinations of status or current

management recovery strategies.

REFERENCES

Bradley, E. and C.E. Bryan. 1974. Life history and fishery of the red snapper (Lutjanus

campechanus) in the northwestern Gulf of Mexico. Proceedings of the Gulf and Caribbean

Fisheries Institute 27:77-106.

Reeffish Stock Assessment Panel. 1998. January 1998 Report of the Reef Fish Stock Assessment

Panel. Gulf of Mexico Fishery Management Council Stock Assessment Report. 

Cowan, J.H., Jr. 1998. January 1998 Report of the Reef Fish Stock Assessment Panel. Gulf of

Mexico Fishery Management Council Stock Assessment Report. 

Dugas, R., V. Guillory and M. Fischer. 1979. Oil rigs and offshore sport fishing in Louisiana.

Fisheries 4(6):2-10.

Goodyear, C.P. 1996. An Update to the Red Snapper Harvest in U.S. Waters of the Gulf of Mexico.

National Marine Fisheries Service, Southeast Fisheries Science Center Report, SFD-95/96-60.

Goodyear, C.P. and P. Phares. 1990. Status of Red Snapper Stocks of the Gulf of Mexico - Report

for 1990. National Marine Fisheries Service, Southeast Fisheries Center, Miami Laboratory,

CRD-89/90-05.

Hastings, R.W., L. H. Ogren and M.T. Mabry. 1976. Observations on the fish fauna associated with

offshore platforms in the northeastern Gulf of Mexico. Fishery Bulletin 74:2:387-402.

Lewbel, G. S., R. L. Howard and B. J. Gallaway. 1987. Zonation of Dominant Fouling Organisms

on Northern Gulf of Mexico Petroleum Platforms. Marine Environmental Research 21:199-224.

Porch, C.E. 2000. Status of the red drum stocks of the Gulf of Mexico. Sustainable Fisheries

Division, 75 Virginia Beach Drive, Miami, FL, 33149, SFD-99/00-85.

Pulsipher, A.G., O.O. Iledare, D.V. Mesyanzhinov, A. Dupont and Q.L. Zhu. Forecasting the

number of offshore platforms on the Gulf of Mexico OSC to the year 2023. Prepared by the

Center for Energy Studies, Louisiana State University, Baton Rouge, LA. OCS Study MMS2001-013. U.S. Department of the Interior, Minerals Management Service, Gulf of Mexico OCS

Region, New Orleans, LA. 52 p.

Scarborough-Bull, A. and J.J. Kendall, Jr. 1990. Mechanisms of outer continental shelf (OCS) oil

and gas platforms as artificial reefs in the Gulf of Mexico. Pages 21-37 in Proceedings of the

American Academy of Underwater Sciences Tenth Annual Scientific Diving Symposium.
371

Schirripa, M. 1998. Status of the Red Snapper in U.S. Waters of the Gulf of Mexico. National

Marine Fisheries Service, Southeast Fisheries Science Center Report, SFD-97/98-30.

Schirripa, M.J. and C.M. Legault. 1997. Status of the Gag Stocks of the Gulf of Mexico: Assessment

2.0. National Marine Fisheries Service, Southeast Fisheries Science Center Report, SFD98/99-6.

Schirripa, M.J. and C.M. Legault. 1999. Status of the Red Snapper in U.S. Waters of the Gulf of

Mexico: Updated Through 1998. National Marine Fisheries Service, Southeast Fisheries Science

Center Report, SFD-99/00-75.

Sonnier, F., J. Teerling and H.D. Hoese. 1976. Observations on the offshore reef and platform fish

fauna of Louisiana. COPEIA 1:105-111.

Stanley, D.R. and C.A. Wilson. 1990. A fishery dependent based study of fish species composition

and associated catch rates around petroleum platforms off Louisiana. Fishery Bulletin

88:719-730.

Gregg Gitschlag has worked for NOAA’s Southeast Fisheries Center, Galveston Laboratory for over

20 years as an oceanographer and fishery biologist. His research interests include sea turtle behavior

and migration as well as recreational and commercial impacts on red snapper. Mr. Gitschlag

completed his B.S. in zoology at the University of Michigan and his M.S. in biological

oceanography at Florida State University.
372

FISH AND EPIFAUNAL COMMUNITY OBSERVATIONS AT AN ARTIFICIAL REEF

NEAR A NATURAL CORAL REEF: NINETEEN YEARS AT PLATFORM HIGH

ISLAND A389-A, FROM BARE STEEL TO CORAL HABITAT

Gregory S. Boland

Minerals Management Service

Gulf of Mexico OCS Region

ABSTRACT

Since its installation 1 October 1981, the platform High Island A389-A has progressed from a bare

steel structure in 125 m of water to a climax bluewater artificial reef community including a number

of hermatypic coral species. The platform is located approximately one nautical mile from the edge

of the well-developed coral reef at the East Flower Garden Bank, Gulf of Mexico. Since 1981, it was

expected this structure would eventually be a site for successful colonization by coral larvae from

the nearby Flower Garden Banks. The platform was surveyed as part of a multidisciplinary National

Marine Fisheries/EPA-funded study over four seasons between October 1981 and October 1982,

beginning just three weeks after installation. Both qualitative and semi-quantitative observations of

fish species and attached epifaunal community are presented from those early surveys. Additional

observations have been obtained periodically between 1982 and 1999. Hermatypic corals were first

observed on the platform by the author and others in November 1990, although their size indicated

that settlement had occurred more than one year previously. The continued development of new

coral colonies and associated thriving reef fish populations has significance for the functionality of

oil and gas structures as artificial reefs and diverse coral habitats. Early observations of fish taxa of

various age classes allows some important statements regarding artificial reef recruitment and

attraction issues. 

INTRODUCTION

Oil and gas platforms in the Gulf of Mexico comprise a substantial artificial reef complex of close

to 4000 structures extending from shallow areas of the shelf into deep continental slope waters. Both

epifauna and fish assemblages at structure depths of less than 30 m have been described since the

early 1970s (Hastings et al. 1976; Gallaway et al. 1981; Gallaway and Lewbel 1982; Putt 1982;

Continental Shelf Associates 1982; Bull and Kendall 1994; Stanley and Wilson 1996; 2000), but in

the past two decades, only a few platforms in the bluewater zone described by Gallaway and Lewbel

(1982) have been investigated (bluewater is defined as water depths deeper than 60 m). This report

describes summaries of opportunistic observations of both fish and fouling community

recruitment/succession at a newly installed bluewater platform near a natural coral reef (the Flower

Garden Banks) in Federal lease block High Island A389. 

During 1981 and 1982, the HI A389-A platform was utilized as a sampling station for a National

Marine Fisheries/EPA-funded study, “Ecological Effects of Energy Development on Reef Fish of

the Flower Garden Banks (Boland et al. 1983), beginning just 3 weeks after platform installation.

These observations are unique due to the timing of the first sampling and repeated observations over
373

4 Ownership of the platform and the HI A389 lease was transferred briefly to Vastar in 1998 (now part of British

Petroleum) and later to W&T Offshore, who is the current operator.

both the short- and long-term. Both qualitative and semi-quantitative observations of fish and

attached epifaunal (fouling) community are presented from early surveys in 1981 and 1982.

Additional observations were obtained periodically between 1982 and 1999. Additional observations

include the first record of scleractinian corals on a platform adjacent to the Flower Garden Banks

and subsequent observations of the growth and additional occurrences of corals on this structure.

MATERIAL AND METHODS

Study Site

The platform structure of HI A389-A (owned by Mobile Exploration and Production U.S. Inc. until

19984) lies in 125 m of water at 27° 54' 02'' North, 93° 34' 38'' West, 191 Km SSE of Galveston,

Texas. Gallaway and Lewbel (1982) defined this distance from shore and water depth as

“bluewater.” The structure lies only 1 nmi southeast of the coral reef zone of the East Flower Garden

Bank (EFGB), now a part of the Flower Garden Banks National Marine Sanctuary. The platform

consists of eight primary support legs (four on each side), with the three shallowest underwater

horizontal support members at 9, 24, and 37 m including typical smaller diameter supplementary

diagonal support structures between. Two principal boat bumper/landing areas were situated in the

center section of each side with 14 small, vertical supports extending approximately 2–3 m above

and below the water line. Using blueprints, the surface area provided by all major platform legs and

supports from the surface to a depth of 37 m was approximately 8,255 m2

. The majority of smallscale structure-associated fish habitat was created by well casings and support collars or guides

located at the horizontal support levels, particularly at 9 and 37 m of depth. The outside dimensions

at horizontal levels were as follows: 19.8 X 44.0 m at 9 m depth; 23.6 X 48.0 m at 24 m depth; and

27.8 X 51.6 m at 37 m depth.

Surveys

Underwater observations were made using SCUBA during a variety of research projects and also

during other opportunities available to the author. The original four surveys and semi-quantitative

census efforts were obtained as a supplemental part of a separate larger Environmental Protection

Agency-funded study to National Marine Fisheries Service, “Ecological Effects of Energy

Development on Reef Fish of the Flower Garden Banks” to LGL Ecological Research Associates

Inc. (LGL), Bryan, Texas (Boland et al. 1983). Surveys were performed on the following dates

followed by the elapsed number of days after platform installation: Survey 1, 21 October 1981/21

days; Survey 2, 29 April 1982/211 days; Survey 3, 4 August 1982/308 days; and Survey 4, 24

October 1982/389. One additional fish survey reported here, Survey 5, was performed on 5 October

1992, 4020 days after original platform installation. All observations were made during daylight

hours. Additional visits to the platform were made by the author throughout the remaining 1990s,

but underwater time was limited and did not permit fish census efforts. However, after 1990,

observations of hermatypic corals were always a primary objective. 
374

Underwater tasks required during the original study (Surveys 1–4) did not permit typical quantitative

diver fish census methods. During the five principal survey periods described above, platform

fouling and fish community surveys were performed as part of other field sampling objectives. Best

estimates of total numbers of fish were determined for the area inside and in very close proximity

of the platform and between the surface and 37 m. These estimates were based on a variety of

circumstances. As opposed to short transect line or volumetric methods, the option was chosen to

attempt to observe the entire structure during each survey and estimate the number of fish for each

observed taxa for the entire structure. Water clarity was generally in excess of 30 m. In the case of

highly mobile pelagic species, it was sometimes evident that the same group of individuals was

moving around the platform (same size individuals, numbers, etc.). In this circumstance, the

estimated total number took into account this judgement and the appearance that the same group of

individuals had been seen more than once. In other instances, for the same pelagic species groups,

it seemed that observations were separate and appeared to be unique individuals. Of course, this was

not a certainty, and as a compromise, a range of estimated numbers was recorded. Total numbers

of reef-associated species were somewhat more reliable due to the limited habitat area provided by

the junctions of platform legs, cross members, and well casing support structures. However, some

of these more cryptic species are also more difficult to observe. Although the effectiveness of a

single diver is limited, it is believed the same level of confidence for estimating total numbers was

similar for all surveys. There is no intention to imply that these semi-quantitative survey results are

highly accurate and it is recognized that many weaknesses are implicit in the methods. However,

specific observations made were significant in context of the time and place. 

Very little diving or remote video census work close to the platform was performed below the 37

m depth during the LGL study (Boland et al. 1983) due both to restrictions of diving depths and

difficulty in maneuvering the camera frame close to platform legs. Some additional observations are

reported from remote video deployments and some deeper diving opportunities after 1982.

RESULTS

The first underwater reconnaissance dive and survey on the partially completed structure was made

by diving scientists (including the author) with the consulting firm, LGL, on 21 October 1981, about

three weeks after its installation. At that time, there were no permanent above-water modules or superstructure and only three well casings had been installed underwater (Figure 7.4). During this first

cruise, only nine species of fish were observed between the surface and 37 m of depth (Table 7.8).

Five of these species were jacks, considered to be wandering, pelagic species. The larger adults of

crevalle (Caranx hippos), almaco (Seriola rivoliana), and amberjacks (Seriola dumerili), may have

been recruited from the nearby East Flower Garden Bank. The other two jack taxa (Blue runner,

Caranx crysos, and a large numbers of unidentified Carangidae) were juveniles and could have been

recruited from the passing water mass. Three of the remaining four species observed during Survey

1 were also small juveniles, and included a single sergeant major (Abudefduf saxatilis), two small

blue tang (Acanthurus coeruleus), and about 200 small gray triggerfish (Balistes capriscus) estimated to range between 100 and 120 mm long (Figure 7.5). The sergeant major observation was the

first reported for the Flower Garden Banks area (Boland et al. 1983). A single greater barracuda

(Sphyraena barracuda) was also observed. The fouling community at this time was virtually nonexistent. The platform structure had obviously never been in seawater for an extended period
375

Figure 7.4. Appearance of Mobile High Island A389-A platform on 21 October 1981.

Figure 7.5. Juvenile gray triggerfish recruited to the platform prior to Survey 1.
376

Table 7.8. Species list and estimated abundance above 37 m depth at platform HI A389-A. All

observations by diver except as noted for grouper from remote video. All adult except

as noted.

Survey Number and Date

Platform age since installation (days)

Species*

1) 21 Oct

1981

2) 29-30

Apr 1982

3) 4-5 Aug

1982

4) 24-29

Oct 1982

5) 2-6 Oct

1992

21 211 308 389 4,020

Silky shark ( Carcharhinus falciformis )

Frogfish ( Antennarius spp.)

Squirrelfish ( Holocentrus rufus )

Longjaw squirrelfish ( H. ascensionis )

Rock hind ( Epinephelus adscensionis )

Warsaw grouper ( Epinephelus nigritus )

Grouper ( Mycteroperca spp.)

Yellowmouth grouper ( M. interstitialis )

Creole-fish ( Paranthias furcifer )

Blue runner ( Caranx crysos )

Crevalle jack ( Caranx hippos )

Horse-eye jack ( Caranx latus )

Bar jack ( Caranx ruber )

Rainbow runner ( Elagatis bipinnulata )

Greater amberjack ( Seriola dumerili )

Almaco jack ( Seriola rivoliana )

Rough scad ( Trachurus lathami )

Unidentified Carangidae

Yellow goatfish ( Mulloidichthys martinicus )

Chub ( Kyphosus spp.)

Reef butterflyfish ( Chaetodon sedentarius )

Angelfish ( Holacanthis spp.)

Blue angelfish ( Holacanthis bermudensis )

Sergeant major ( Abudefduf saxatilis )

Brown chromis ( Chromis multilineatus )

Bicolor damselfish ( Stegastes partitus ) )

Damselfish ( Stegastes spp.)

Redspotted hawkfish ( Amblycirrhitus pinos )

Spotfin hogfish ( Bodianus pulchellus )

Spanish hogfish ( Bodianus rufus)

Unidentified wrasse ( Halichoeres spp.)

Bluehead ( Thalassoma bifasciatum )

Greenblotch parrotfish ( Sparisoma automarium ) 

Redband parrotfish ( Sparisoma aurofrenatum )

Great barracuda ( Sphyraena barracuda )

Unidentified goby (Family Gobiidae)

Seaweed blenny ( Blennius marmoreus )

Crested blenny ( Hypleurochilus geminatus )

Tesselated blenny ( Hypsoblennius invemar )

Blue tang ( Acanthurus coeruleus )

Surgeonfish/doctorfish ( Acanthurus spp.)

Scrawled filefish ( Aluterus scriptus )

Orangespotted filefish ( Cantherhines pullus )

Whitespotted filefish ( C. macrocerus)

Grey triggerfish ( Balistes capriscus )

Ocean triggerfish ( Canthidermis sufflamen )

Porcupinefish ( Diodon histrix )

Sharpnose puffer ( Canthigaster rostrata )

20-30 (juv.)

10

6

40-50

2 K-3 K juv?

1 (juv.)

1

2 (juv.)

200 (juv.)

1

6 (video)

1 (juv.)

50 sm

50

1

10

50

10-20

100-200

14

6

3

3

10-20 (juv.)

2

20

1

3

1

3

20-30

6

3

1

1

10-15

6-10

2 (juv.)

400-500 sm

6

20-30

10-20

3

1

5

6

30

10-20

6

3

5 (juv.)

1

2

40-50

6

3

1

20-30

1 (video)

20-40

3 (juv.)

500

100 (juv.)

25 (juv.)

3-6

10

20

4-10

4-6

3 (juv.)

20-30

10-20

3

3-6

1

3

1

1

50

3

1

3

20-30

30-50

1

2

8

3

100+

20-50

100-500

50+

100-150

20-30

20-30

1000+

10

100+

1K+ few juv

50-100

100’s

8-12

10-30

100

100-500

20-50

50-100

3

2

2 

 Total number of taxa 9 24 23 32 22 

*Common names from AFS (1991); sm = small; juv. = juvenile, year class 0 or 1
377

previous to its transportation and installation at the edge of the EFGB. The only obvious epifauna

seen were a few scattered patches of an unidentified feathery white hydroid down to 18 m of depth

and green filamentous algae present near the surface. The vast majority of the submerged structure

surface area was coated in orange rust with black anoxic corrosion occurring in many areas below

the superficial rust layer (Figure 7.6). 

The second sampling dives (Survey 2) on the platform were made on 29 and 30 April 1982. Total

dive time was 82 minutes. The structure had been in place for a total of about 211 days at that time.

Drilling for the first well had begun on 26 April, three days previous to the dives. The most striking

change to the platform community was the almost complete cover of the legs and cross-members

by fouling organisms. Although the fouling mat was quite thin in most places, it was dramatically

different from the bright orange rust layer that had covered most all the structure surfaces on the

previous survey (Figure 7.7). The number of fish species observed almost tripled with 24 species

represented as compared to nine species before (Table 7.8). Eighteen of these were new species not

observed during Survey 1. Two of the juvenile jack species and the blue tang observed previously

were not re-sighted. Number of barracuda had increased to 20 individuals; both crevalle and

amberjack were represented by approximately 50 individuals each.

An estimated 20–30 moderate-sized (200–250 mm) gray triggerfish were observed during Survey

2, suggesting survivors from the 200 smaller juveniles that had been seen during Survey 1

approximately 26 weeks before. Several tropical species were first observed during Survey 2

including about 50 small creole-fish (Paranthias furcifer), the dominant species on the Flower

Gardens coral reefs reported by Boland et al. 1983) and some representatives of the bicolor

damselfish (Stegastes partitus), an unknown wrasse, 10–20 juvenile spotfin hogfish (Bodianus

pulchellus), two species of filefish (scrawled filefish (Aluterus scriptus) and orangespotted filefish,

Cantherhines pullus), sharpnose puffer (Canthigaster rostrata), an unknown goby, and the seaweed

blenny (Blennius marmoreus). The first grouper species (above 37 m) was also observed during

Survey 2, a single yellowmouth grouper (M. interstitialis).

The fouling community at this time was dominated in some areas by thick mats of filamentous algae

and hydroids, both of which were teaming with several species of amphipods. Large, unidentified

nudibranchs (3–5 cm long) were also seen grazing through these thick mats. These nudibranchs were

never observed after this survey. In other areas, large patches of colonial tunicates dominated the

fouling mat. Near the surface, several of the boat bumpers had become heavily encrusted with

gooseneck barnacles. A single small colony of the octocoral, Telesto riisei was observed at a depth

of 12 m.

Other motile invertebrates were also observed during Survey 2. Two species of sea urchins were

present, small Diadema antillarum and Arbacia punctulata. Fireworms, (Hermodice carunculata),

were abundant at both the 8-m and 37-m levels of horizontal supports. Two crab species were

observed at 37 m, one an unknown xanthid crab, and the arrow crab (Stenorhynchus seticornis),

represented by several individuals. Three small spiny lobsters (Panulirus argus) were seen inside

a well collar surrounding a well casing at the 37-m depth level. One was very small with an

estimated carapace length of about 5 cm.
378

Figure 7.6. Typical appearance of platform structure three weeks after installation.

Figure 7.7. Similar location as Figure 7.6 photographed during Survey 2, seven months (211

days) after installation with now noticeable epifaunal community development

evident.
379

Survey dives were again made on 4 and 5 August 1982 (Survey 3). Total dive time was 93 minutes.

The platform had been on site for about 308 days at that time. During this survey, fewer fish species

were observed than in April 1982, but the total number of individuals seen had generally increased

(higher abundance, lower diversity) (Table 7.8). Of 23 total taxa, 14 species were also observed

during Survey 2. Eight new species were observed during Survey 3 including the longjaw

squirrelfish (Holocentrus ascensionis), tessellated blennies (Hypsoblennius invemar), and numerous

tropical reef species, namely the reef butterflyfish (Chaetodon sedentarius), surgeon/doctor fish

(Acanthurus spp), yellow goatfish (Mulloidichthys martinicus), and rock hinds (Epinephelus

adscensionis) (Figure 7.8). Juvenile blue tang were also observed again after being first observed

during Survey 1 and absent during Survey 2. A single squirrelfish (Holocentrus rufus) was seen for

the first time at 8 m of depth.

The most notable change in the fish community during Survey 3 was the dramatic increase in the

creole-fish population. A best estimate of their numbers to the depth of the 37-m horizontal structure

level was between 400 and 500 individuals. All of these fish were relatively small. Specimens

collected at the platform for a histopathology work unit of the larger study averaged 124 mm and

ranged in size from 85–142 mm in fork length (N = 41) compared to lengths twice that size for

specimens collected from the Flower Garden Banks upper coral reefs (mean = 208 mm, range

105–292 mm, N = 323) (Boland et al. 1983).

The fouling community during Survey 3 was becoming dominated by bivalve mollusks. The thick

hydroid and algal mats were much reduced in comparison to the previous spring survey. The

dominant bivalve occurring on the platform in August 1982 was the Atlantic pearl oyster (Pinctada

radiata). Acorn barnacles (Megabalanus antillensis), though sparse, were prevalent from about 10

m to the surface. Many barnacles had reached approximately 3–4 cm in basal diameter, and the few

which had died provided excellent habitat cavities for the newly recruited tessellated blennies and

the increased numbers of seaweed blennies. Gooseneck barnacles (Lepas sp.) remained abundant

near the surface but were not nearly as thick on boat bumper surfaces as they had been in April.

Encrusting bryozoan patches had increased dramatically in size, and one red species had developed

delicate branches extending several centimeters above the basal part of the colony. 

Motile invertebrates observed included red-banded coral shrimp, (probably Stenopus hispidus)

hiding inside well collars at both 8- and 37-m depths. Arrow crabs and fireworms were again

observed. Spiny lobsters were seen in the same well collar where they had been seen during Survey

2 (Figure 7.9) at the 37-m level. At this time, there were at least six individuals present, and all were

significantly larger than observed during Survey 2, 97 days earlier suggesting residency and growth

of the former.

The final observational survey of the LGL study platform as part of the FGB study Boland et al.

(1983) was made on 24 October, 1982 (Survey 4), some 389 days after its installation. Both the fish

and fouling communities had become surprisingly well established after little more than a year of

colonization beginning from a bare steel structure. The number of fish species observed had

increased to thirty-two (Table 7.8). Six new species were noted during Survey 4, and 17 species

were common to both Surveys 3 and 4. New species included a frogfish (Antennarius spp.), juvenile

angelfish (Holacanthus spp.), brown chromis (Chromis multilineatus), red-spotted hawkfish
380

Figure 7.8. Diverse fish community around well casing area at horizontal cross member level,

Survey 3, ten months (308 days) after installation.

Figure 7.9. Small spiny lobster at Figure 7.8 site, Survey 3, ten months (308 days) after

installation.
381

(Amblycirrhitus pinos), red band parrotfish (Sparisoma aurofrenatum), and one additional blenny

species, the crested blenny (Hypleurochilus geminatus). Several species had increased substantially

in numbers, including the sergeant major which had been represented by five individuals during

Survey 3 as compared to between 20 and 30 individuals on Survey 4. Small groupers (Mycteroperca

spp.) increased from around 6–10 fish to between 20 and 40 individuals. 

Creole-fish remained the numerically dominant species, maintaining a similar population from

Survey 3 to Survey 4 of approximately 500 individuals. Creole-fish appeared to be significantly

larger during Survey 4 as compared to Survey 3. Fish collected for the larger study at this time

suggests these observations were correct. Fork lengths of 23 fish collected at the platform during

Survey 4 ranged from 140–181 mm, having a mean length of 153 mm. This compares to a mean

length of 124 mm for the 41 fish collected during Survey 3 (Boland et al. 1983).

The fouling community had become quite diverse and it was impossible to describe all its

components within the limited time of the few dives made on the platform. In general, the fouling

community had become well established. Many species on the platform were observed for the first

time during this survey. Atlantic pearl oysters had become larger and more numerous (Figure 7.10),

especially on the top surfaces of the horizontal cross members. Numerous rock snails, Thais

haemastoma, and winged oysters, Pteria colymbus, were also seen. The octocoral, Telesto riisei that

had been limited to a single occurrence at 12 m during Surveys 2 and 3 was observed in small

patches at six other locations ranging in depth between about 5 and 16 m. The general fouling mat

consisted primarily of algae, bryozoan, and hydroids of several species. Two taxa of leafy algae

abundant on the Flower Garden Banks (Lobophora and Dictyota) were prevalent on the surfaces of

horizontal supports at both 9- and 37-m depths. Acorn barnacles had become larger and were now

distributed to a maximum depth of about 37 m (Figure 7.11). Encrusting sponge colonies that had

not been previously observed were well established, and in some areas were as large as 30 cm in

diameter. 

One additional fish survey is included in this report performed 2–6 October 1992, 4020 days after

original platform installation and almost ten years after the first survey in 1982. Total effort utilized

to obtain this Survey 5 data included nine dives and 331 minutes of dive time. A total of 22 fish taxa

were observed. Seven species were observed that were not previously seen in 1981/82, all of which

are common species on the Flower Garden Banks. These included the horse-eye jack (Caranx latus),

blue angelfish (Holacanthis bermudensis) (Figure 7.12), Spanish hogfish (Bodianus pulchellus),

bluehead (Thalassoma bifasciatum), whitespotted filefish (Cantherhines macrocerus), greenblotch

parrotfish (Sparisoma automarium), and porcupinefish (Diodon histrix). As opposed to the creolefish reported as the dominant taxa in 1982, the damselfish, Stegastes spp. had become the dominant

reef-associated taxa, estimated as 1000+ in numbers above the 37 m depth level. Several Stegastes

species could not be reliably separated during this survey and were combined under one genus name.

The platform fouling community in 1992 was dramatically different than 10 years earlier. The

overall community had become dominated by massive sponges (Figure 7.12). Towards the surface,

shallower than about 5 m, the fouling community included high relief barnacle mollusk clusters,

similar to platforms in shallower areas of the continental shelf (Figure 7.13). The fouling community

had apparently reached a climax state that has persisted through more recent observations through
382

Figure 7.10. Atlantic pearl oyster (Pinctada radiata) with attached anemones during Survey 4, 13

months (389 days) after installation.

Figure 7.11. Acorn barnacles (Megabalanus antillensis) with attached anemones during Survey

4, 13 months (389 days) after installation.
383

Figure 7.12. Well-developed fouling community on HI A389-A during Survey 5 in October 1992

(4,020 days after installation). Numerous taxa of massive sponges dominating the

community at depth of 20.

Figure 7.13. Well-developed fouling community on HI A389-A during Survey 5 in October 1992

(4,020 days after installation). High-relief mollusk and barnacle community at depths

above 5 m.
384

1999. A detailed description of the highly complex and diverse fouling community is beyond the

scope of this report. A limited investigation of just the sponges was a substantial undertaking and

is published as a technical report and graduate degree thesis (Adams 1996).

Additional Observations

Scleractinian corals: Scleractinian reef-building (hermatypic) corals were expected, but not

observed between 1981 and 1982 during the LGL studies at HI A389-A ending only 13 months after

the platform was installed (Boland et al. 1983). Opportunities were not available to make

observations at the platform again until 1990, several years after Survey 4 in October1982. The

author and others made two dives on HI A389-A on 11 November 1990. Four species of corals were

documented including Madracis decatis, M. asperula, Porites astreoides and Diploria strigosa. ).

These observations were reported in Bright et al. (1991). A single colony of P. astreoides (brooder)

and a small colony of D. strigosa (broadcaster) were notable as they ranked as second and fifth in

dominance of coral cover at the FGB (Gittings et al. 1992; Dokken et al. 1999). The P. astreoides

colony was a substantial size having settled at least several years earlier. Figure 7.14 illustrates the

Porites colony in June 1992, only eight months after its first sighting at a depth of 9 m on a

horizontal cross member. The first Diploria colony observed on HI A389-A at a depth of 23 m was

much smaller, measuring about 6 cm in diameter but certainly had settled more than one year

previous. A number of D. strigosa and the large Porites were followed over the years whenever

opportunities were available. One additional image of the Porites is shown in Figure 7.15 taken in

August of 1995. Measurements were taken at this time showing the dimensions of the colony to be

about 42 by 38 cm. An additional colony of P astreoides was located a short distance away

measuring 11.5 by 14 cm indicating probable successful reproduction of the original adjacent

colony. The same colony of D. strigosa is shown in both Figure 7.16 and Figure 7.17. This particular

colony was not the same as the first observed in 1990, but its size shown in 1995, measuring 16 by

19 cm indicates it could have been a similar size (about 6 cm diameter) as the originally sighted

colony five years previous (theoretical growth rate of 1–1.3 cm in radius per year not unreasonable).

Figure 7.17 depicting the same colony in August 1998, shows substantial growth over the three

years. The diameter was measured in 1998 as approximately 23 cm representing a growth of

between 4–7 cm over three years. 

Observations below 37 meters: Although not a principal subject of this report, a number of other

observations have been made by the author by remote video methods and using SCUBA below the

37-m horizontal structure support on the platform. In Boland et al. (1983), limited observations were

made with a remote stereo-video apparatus deployed from a research vessel tied to the platform

during the LGL study. Boland et al. (1983) reported that below a 40-m depth, fouling organisms

were very sparse. Only a few fish species were reported, most not closely associated with the

platform substrate. These included amberjack, rainbow runner, greater barracuda, and chub. One

species was more remarkable. Large warsaw groupers were recorded on the remote video system

during Surveys 2 and 4. A total of six individuals were seen during Survey 2 just above the interface

of a highly turbid nepheloid layer at a depth of around 90 m. The LGL video system allowed

measurement using paired, parallel cameras and a twin stereo-monitor system. Three of the fish

allowed length measurement while oriented perpendicular to the cameras and had fork lengths of

810, 877 and 919 mm. A single warsaw grouper was observed during the Survey 4 cruise and was
385

Figure 7.14. Colony of Porites astreoides documented from horizontal support at depth of 9 m,

June 1992.

Figure 7.15. The same colony of Porites astreoides as in Figure 7.14, taken August 1995, colony

measuring 42 by 38 cm with mortality in center approximately 8 by 6 cm. Pipe

diameter is 35.5 cm.
386

Figure 7.16. Colony of Diploria strigosa at depth of 15.5 m. Photographed August 1995 when the

coral measured 19 by 16 cm.

Figure 7.17. The same colony of Diploria strigosa as in Figure 7.16. Photographed August 1998.
387

Figure 7.18. View of 53-m horizontal support and descending diagonal on HI A389-A platform

from depth of 58 m. Note high relief of fouling community.

also sighted just above the turbid water layer at a depth of 90 m. This grouper was also measured

using the stereo video system and had a fork length of 1314 mm.

During a research opportunity in 1992, a number of deep SCUBA dives were performed by the

author at HI A389-A allowing first hand observations of platform substrate as deep as 57 m. Limited

time did not allow any comprehensive fish or fouling community descriptions, but it was clear that

the conditions reported from 1982 were much different in 1992. The next horizontal support below

the 37-m level is located at 53 m. Figure 7.18 illustrates the relatively high-relief fouling community

on all structural supports to a depth of 58 m. Although observation time was very limited, structureassociated reef fish were very abundant. Both of these observations are in contrast to the limited

fouling community development and very few fish seen on remote video in 1982. No attempt will

be made here to provide a comprehensive description or comparison of the fish community at this

depth, but one species, the yellowtail reeffish (Chromis enchrysurus), appeared to be the dominant

species represented by many individuals along every meter of all horizontal structure supports at a

depth of 53 m.
388

DISCUSSION

It should again be noted that the fish census data in this report is semi-quantitative at best, and

affected by limited, single-diver observations. A general bias has also been reported in the literature

due to the presence of divers during fish surveys. Mean density of fish declined around platforms

by 41–77 percent when SCUBA divers were present during surveys as estimated by dual-beam

hydroacoustics (Stanley and Wilson 1995). One significant difference with the data reported here

is that virtually all observations were obtained inside the platform structure in contrast to the

hydoracousitc data collected only on the outside of structures by Stanley and Wilson (1995).

Results from most investigations of platform fish assemblages have been difficult to compare due

to problems with limited visibility, lack of standardized methods, diver avoidance or other sampling

gear bias. Any discussion of these results is also limited by the lack of rigorous census techniques

and inconsistent methodologies; however, the observations reported here still represent unique

contributions describing long-term platform recruitment occurring at a Gulf of Mexico bluewater

platform. Faunal studies of bluewater platforms in the Gulf have been and continue to be rare. The

most notable aspect of the surveys reported here was the opportunity to periodically observe the

colonization of a new structure over an extended period. The initial observations are significant due

to the known date of installation and the fact that the structure was essentially new at that time. For

many encrusting forms, a general indication of succession/recruitment was observed, at least for new

substrates. Some insight can also be added to the ongoing debate about the production or attraction

function of artificial reefs. The proximity of the platform to a thriving coral reef is also a unique

situation, particularly for the United States. 

After more than 13 months of recolonization in October 1982, the HI A389-A platform remained

very different than the adjacent coral reef or other habitats on the EFGB. The dominant invertebrates

on the reef, the reef-building corals, had not yet been observed on the platform. Coral recruits would

have been very small after less than one year of development and could have easily been

overlooked. Some large invertebrates were common to both habitats, but there were many

exceptions. Notably, the lobster population on the platform (spiny lobster, Panulirus argus) was not

the same species commonly seen on the coral reef at that time (spotted lobster, Panulirus guttatus).

The majority of the 48 fish species recorded on the platform also occur on the Flower Gardens, but

some did not. Several species were observed on the platform in 1981 or 1982 which had not been

previously reported in the literature of the Flower Garden Banks at that time. These included the

sergeant major, an unidentified frogfish, and three species of blenny, the seaweed, crested, and

newly described tesellated blenny. Overall, the proximity of the HI A389-A platform to the EFGB

seems to have had a limited effect on its attached epifaunal community composition through the

1982 observations. The community at this platform was basically the same as other blue water

platforms well removed from any bank (Gallaway and Lewbel 1982).

In 1990, after nine years of development, the substantially different fouling community on HI A389-

A remained unlike any reef habitats at the EFG. The general nature of the community had reached

what appeared to be a climax community at this time and has not changed drastically since (through

1999). The visual community dominant taxa had become sponges, but mollusks were probably the

biomass dominant, although no biomass samples were taken and there is no data to confirm this
389

statement. Gallaway and Lewbel (1982) also reported that bluewater platform fouling community

biomass is generally dominated by mollusks. 

Although Adams (1996) concluded that the variety of sponges found on HI A389-A were similar

to coral reef systems in general, their diversity and dominance are not characteristic of the Flower

Garden Banks coral reef habitat and are higher in abundance than on coral reefs in general. The platform structure provides many different types of reef environment allowing the recruitment and

development of a very diverse sponge community not found on the FGB. Adams (1996) reported

three dominant species; below a depth of 25 m the spherical species Stelletta kallitetilla was the

dominant, at mid depths between 12.5 to 24.5 m, Tedania ignis dominated, and shallower than 12

m, Desmacella melorata dominated. Overall, these three species comprised nearly half of all substrate area for the platform to a depth of 37 m (Adams 1996). Interestingly, Adams (1996) reported

that several common species on the Flower Garden banks did not occur on the platform, including

the large vase sponge Xestospongia muta and the prominent bright orange sponge Agelas spp.

The number of fish taxa observed in five surveys totaled 48, comparable to other bluewater platform

surveys. Rooker et al. (1997) observed a total number of 43 species above 24 m during diurnal

surveys of 54 ten-meter transects at HI A389-A. The Reef Environmental Education Foundation

database (REEF, http://www.reef.org) documents a total of 52 surveys performed at the HI A389-A

platform in recent years. Using the “expert” category (test results demonstrating a high level of

visual identification expertise) the number of taxa reported totaled 53. While the data in this report

cannot be directly compared to any rigorous quantitative census techniques, the total number of taxa

compares favorably to these other efforts.

The relevance of fish survey data in this report derives from the early timing of the initial observations and repeated surveys during the first year after platform installation. Adult fish observed in or

near the structure a short period after installation were not recruited as juveniles. The first survey,

three weeks after platform installation, demonstrated that adult taxa are recruited from surrounding

areas. Pelagic Carangidae are examples, but the large warsaw groupers, optically measured around

one meter in length, represent very mature reef-associated fish attracted to the platform.

Many observations represent evidence of species recruited as juvenile or very young individuals to

this new habitat. The gray triggerfish observed during Survey 1 are the best example (Figure 7.5).

There is no assurance that juveniles recruited to the platform would not have otherwise ended up

at the EFGB, however, gray triggerfish are very rare on the EFGB but are common on offshore

platforms. Other small individuals were observed during the first survey including a sergeant major

and blue tang. Creole-fish, the numerical dominant on the FGB reported by Boland et al. (1983),

were first seen at a platform age of seven months. Some examples of early recruits, and later

observations of similar numbers but larger individuals, suggest that these groups of smaller fish

remained residents. This is speculation as there was no tagging or other methodology employed to

identify specific individuals. The appearance of large numbers of adult creole-fish on the platform

during Survey 4 could represent recruitment from the nearby EFGB, however, this species is also

reported in high numbers at other bluewater platforms well removed from natural habitat and was

the dominant species at the platform GC 18, (Stanley and Wilson 2000). 
390

Other general observations by the author at HI A389-A (annually between 1993–1998) indicate

extreme variation in both seasonal and annual fish abundance for some species. As one example,

more than one hundred silky sharks (Carcharhinus falciformis) were observed swimming in circles

around the outside of HI A389-A in November of 1990 in contrast to only a single individual

observed during all 5 surveys. These large numbers of silky sharks are not frequently seen. Similar

to the FGB, the abundance of many species may vary substantially from one day to the next. This

is particularly true for pelagic taxa such as the jacks. One notable additional observation not

presented in the results section was a sergeant major tending a substantial egg mass on a horizontal

projection of a platform leg in 1995.

CONCLUSIONS

The overall conclusion of this report is that this new platform structure installed in 1981, in

relatively deep water adjacent to the EFGB, was colonized by a diverse community of epibiota and

fishes where none existed before. Much of the development of the platform community, particularly

the biofouling component, appears to be largely independent of its proximity to the Flower Garden

Banks. Other significant conclusions include:

Early observations at a newly installed “bluewater” platform demonstrate that adult, sub-adult and

juvenile fish are recruited or attracted to a structure within a time frame of less than three weeks, and

perhaps in a matter of days after installation.

Direct observations demonstrated attraction of adult fish to the platform, but also recruitment and

apparent growth of some reef fish species. One taxa, the sergeant major (Abudefduf saxatilis), was

unarguably producing new biomass by nesting on the platform.

Fouling community development is quite rapid but continues through a variety of phases or

succession, until a “climax” community is reached with very high rugosity and other structural

complexity to a depth of more than 60 m. 

Although a nearly complete cover of pioneer fouling taxa was present after seven months, the

sponge-dominated community structure at HI A389-A took many years and probably close to ten

years to become fully established.

Virtually all fish species recorded on the platform have also been recorded on the Flower Garden

Banks. Notable exceptions are the lack of tessellated blenny observations and the lack of any record

of sergeant majors on the FGB prior to the earliest platform surveys.

Hermatypic corals were first observed on HI A-389A in November 1990, nine years after

installation. Two dominant species on the FGB, Diploria strigosa and Porites astreoides, have

continued to grow. 

The brooding coral species Porites astreoides has apparently reproduced successfully after

recruitment to the platform and expanded its colonization on HI A-389A. The numerous colonies

of D. strigosa (broadcast spawner) now growing on the platform are also likely contributing viable
391

larvae into the Gulf of Mexico. Direct observation of these coral heads during an annual mass

spawning event could confirm the potential of artificial reef propagation of hermatypic corals. Most

of the numerous older bluewater platforms located downcurrent of the Flower Garden Banks should

also harbor developing colonies of reef-building corals.

ACKNOWLEDGMENTS

The initial observations at platform HI A389-A between 1981 and 1982 were a part of an EPA

funded study, “Ecological Effects of Energy Development on Reef Fish of the Flower Garden

Banks,” through National Marine Fisheries Service, Galveston, Texas. Contract No. NA80-GA-C00057 (Boland et al. 1983). Some of the latter visits to the HI A389-A platform were opportunistic

during ongoing monitoring at the Flower Garden Banks efforts funded by the Minerals Management

Service to Texas A&M University beginning in 1988. The deep diving opportunities were made

possible by invited participation in a project at HI A389-A from Quenton Dokken at Corpus Christi

State University in 1992 (now Texas A&M University at Corpus Christi). Other observations at HI

A389-A were opportunistic during recreational trips or while serving as a vessel Dive Master on the

Rinn Boats Inc., M/V Fling. Mobil Exploration and Production U.S. Inc. is gratefully acknowledged

for the general permission to LGL Ecological Research Associates Inc. and National Marine

Fisheries to use their new structure for their study, and also for their long-running support of

numerous academic marine science studies based at the platform over many years. All images are

by the author from HI A389-A.

REFERENCES

Adams, C.L. 1996. Species composition, abundance and depth zonation of sponges (Phylum

Porifera) on an outer continental shelf gas production platform, northwestern Gulf of Mexico.

Final report and Master’s Thesis project. Texas A&M University-Corpus Christi, Center for

Coastal Studies. No. TAMU-CC-9601-CCS. 130 pp.

AFS. American Fisheries Society. 1991. Common and Scientific Names of Fishes from the United

States and Canada. Fifth edition. Bethesda, MD. 183 pp.

Boland, G.S., B.J. Gallaway, J.S. Baker, G.S. Lewbel. 1983. Ecological effects of energy

development on reef fish of the Flower Garden Banks. Volume III. In Ecological effects of

energy development on reef fish, ichthyoplankton and benthos populations in the Flower Garden

Banks of the northwestern Gulf of Mexico, 1980-1982. National Marine Fisheries

Administrative Report to Environmental Protection Agency under interagency agreement EPA79-D-X0514. 466 p.

Bright, T.J., S.R. Gittings, and R. Zingula. 1991. Occurrence of Atlantic reef corals on offshore

platforms in the northwestern Gulf of Mexico. Northeast Gulf Science. 12:55-60.

Bull, A. and J.J. Kendall Jr. 1994. An indication of the process; Offshore platforms as artificial reefs

in the Gulf of Mexico. Bulletin of Marine Science. 55:1086 - 1098.
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Continental Shelf Associates. 1982. Study of the effect of oil and gas activities on reef fish

populations in Gulf of Mexico OCS area. Open File Report 82-10. New Orleans, Louisiana. US

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Dokken, Q.R., I.R. MacDonald, J.W. Tunnell, Jr., C.R. Beaver, G.S. Boland and D.K. Hagman.

1999. Long-term Monitoring of the East and West Flower Garden Banks, 1996-1997. OCS study

MMS 99-0005, U.S. Department of the Interior, Minerals Management Service, Gulf of Mexico

OCS Region, New Orleans, Louisiana. 101pp.

Gallaway, B.J., L.R. Martin, R.L. Howard, G.S. Boland, and G.D. Dennis. 1981. Effects on artificial

reef and demersal fish and macrocrustacean communities. Pages 237-299 in B.S. Middleditch,

editor. Environmental effects of offshore oil production: The Buccaneer gas and oil field study.

Marine Science Volume 14. Plenum Press. New York, N.Y.

Gallaway, B.J. and G.S. Lewbel. 1981. The ecology of petroleum platforms in the northwestern Gulf

of Mexico: A community profile. USFWS Office of Biology Services, Washington, D.C. FWS

1OBS-82/27. Open File Report 82-03. 

Gittings, S.R., G.S. Boland, K.J.P. Deslarzes, and B.S. Holland. 1992. Long-term monitoring at the

East and West Flower Garden Banks. OCS Study/MMS 92-0006. U.S. Department of Interior,

Minerals Management Service, Gulf of Mexico OCS Regional Office, New Orleans. 206 p.

Hastings, R.W., L.H Ogren, and M.T. Mabry. 1976. Observations on the fish fauna associated with

offshore platforms in the northeastern Gulf of Mexico. Fishery Bulletin. 54:387-401.

Putt, R.E., Jr. 1982. A quantitative study of fish populations associated with a platform within

Buccaneer oil field, northwestern Gulf of Mexico. M.Sc. Thesis. Texas A&M University.

College Station, Texas.

Rooker, J.R., Q.R. Dokken, C.V. Pattengill, and G.J. Holt. 1997. Fish assemblages on artificial and

natural reefs in the Flower Garden Banks National Marine Sanctuary. Coral Reefs. 16:83-92. 

Stanley, D.R. and C.A. Wilson. 2000 Seasonal and spatial variation in the biomass and size

frequency distribution of the fish associated with oil and gas platforms in the northern Gulf of

Mexico. Final report to U.S. Department of the Interior, Minerals Management Service. OCS

Study MMS 2000-005. 252 pp. 

Stanley, D.R. and C.A. Wilson. 1997. Seasonal and spatial variation in abundance and size

distribution of fishes associated with a petroleum platform in the northern Gulf of Mexico.

Canadian Journal of Fisheries and Aquatic Sciences 54:1166-1177.

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target strength utilizing dual-beam hydroacoustics. Transactions of the American Fisheries

Society 124:946-949.
393

1

 Deceased

FISH ASSEMBLAGES AROUND OIL AND GAS PLATFORMS IN THE

NORTHEASTERN GULF OF MEXICO: DEVELOPING A SURVEY DESIGN.

Kevin R. Rademacher

Jeffery H. Render1

National Marine Fisheries Service

Mississippi Laboratories

ABSTRACT

A pilot survey was conducted in 1995 by the National Marine Fisheries Service, Mississippi

Laboratories (NMFS, ML) to develop a survey design for assessing fishes associated with the

offshore oil and gas platforms in the Gulf of Mexico (GOM). Eight platforms of various sizes,

configurations and depths were sampled with a pan and tilt video camera, stationary video cameras,

and a remotely operated vehicle (ROV). Differences in fish species observed and their abundance

measured by the different gear types were evaluated to determine an optimal sampling design for

large-scale surveys. 

Forty-four taxa from 19 families were observed over all platforms and all gears. The ten most

frequently observed species were: blue runner, Caranx crysos; Atlantic spadefish, Chaetodipterus

faber; gray (mangrove) snapper, Lutjanus griseus; sheepshead, Archosargus probatocephalus; red

snapper, Lutjanus campechanus; great barracuda, Sphyraena barracuda; lookdown, Selene vomer;

the scad complex, Decapterus spp. and/or Trachurus sp.; gray triggerfish, Balistes capriscus; and

blue angelfish, Holacanthus bermudensis. More taxa were observed within the confines of the

platforms and in close proximity to the platforms than were observed away from the platforms.

Camera orientation was important in detecting some species, e.g., groupers were only observed

within the confines of the platforms. The number of taxa observed did not vary with depth or among

platforms, but there were differences in fish density with depth and among platforms. More red

snappers were seen at depths > 25 m, while more gray snappers were found at depths < 20 m. Total

fish densities were lower at platforms with barnacles as the dominant attached fauna and higher at

platforms with higher relief epifauna (octocorals, sponges and bryozoans). Red snapper densities

were higher at platforms with higher relief epifauna and gray snapper densities were higher at

barnacle-dominated platforms. There was no difference observed in fish density with platform age

nor any relationship between platform age and attached faunal types. 

INTRODUCTION

Oil and gas platforms act as de facto artificial reefs, are a major destination for many commercial

and recreational fishermen (Hastings et al. 1976; Gallaway 1984; Witzig 1986; Reggio 1987;

Stanley and Wilson 1988, 1989; Render and Wilson 1994; Kasprizak 1998), and contribute to

available habitat for reef fishes in the northwestern and northern GOM (Gallaway and Lewbel 1982;
394

Gallaway 1984; Render and Wilson 1994; Kasprizak 1998). There is controversy over the effect of

platforms and artificial reefs in general on reef fish populations. Do artificial reefs increase

productivity or just redistribute the available resources to known locations, making them easier for

capture (Stone et al. 1979; Bohnsack and Sutherland 1985; Bohnsack 1989; Grossman et al. 1997;

Borotone 1998)? As this debate continues, there is a need to assess fish populations on artificial

reefs and incorporate the assessment with those obtained from natural habitats for the overall

management of the reef fishes in the GOM.

In late April 1995, the Southeast Area Monitoring and Assessment Program (SEAMAP) Reef Fish

Work Group sponsored a workshop on oil and gas platformsin the GOM. Presentations at the workshop provided useful information regarding data needs for conducting fisheries assessments and

measuring physical processes around platforms and the types of gear required to sample these platforms. Additionally, group discussions were held after the presentations to formulate recommendations for developing a sampling methodology for oil and gas platforms (SEAMAP 1995).

Specific recommendations from the SEAMAP workshop were as follows: 

1) Separate the study area into three zones: coastal, from the shore out to 22 m; offshore, from

23 m to 80 m, and blue water, > 80 m. 

2) Conduct acoustic sampling: including mobile shipboard acoustic passes around a platform,

stationary acoustic sampling around a platform and mobile ROV acoustic passes at depth.

3) Sample visually: including video data collection from an ROV at set depth strata and from

a four-camera array for static visuals at set depth strata.

4) Sample with hook and line to collect hard parts for age, growth and reproductive studies.

5) Sample for plankton in and around platforms.

6) Measure standard hydrographic parameters, including current speed and direction, light

transmissivity and photosynthetically active radiation (PAR). 

Currently, reef fish assessment models used for management are based on landings data from

commercial and recreational fisheries. These models are calibrated using data from NMFS fisheries

independent surveys, e.g., NMFS summer and fall groundfish survey by-catch data (NMFS 1999).

Data from NMFS shark and snapper long-line surveys and the reef fish trap-video survey from

shelf-edge banks could provide additional tuning variables. Missing, however, is fishery independent

data from surveys of oil and gas platforms.

Sample allocation must be determined to develop a broad-scale survey design that effectively assesses fish populations associated with oil and gas structures in the GOM. Should there be more intense

sampling of individual structures with fewer structures sampled or more structures sampled less

intensively? Determination of sample allocation requires estimates of within-platform and betweenplatform variability. Survey development also includes selection of methods to measure fish
395

abundance associated with platforms. At the SEAMAP workshop’s conclusion, the NMFS ML organized a pilot study to determine the effectiveness of selected workshop recommendations and to

answer questions about development of a survey design to sample fishes associated with platforms.

The objectives of this pilot study were

1) to determine whether a small vessel can safely maneuver around and tie up to a structure and

deploy the required gear for sampling,

2) to determine the best gear or combination of gears for sampling fishes associated with

platforms, and

3) to obtain preliminary estimates of fish abundance and distribution by depth, location on the

structure (inside vs. outside) and by platform type.

Most studies involving fish associated with oil and gas platforms in the GOM have been conducted

in the northwestern Gulf, because most oil and gas platforms are located off Louisiana and Texas

(Sonnier et al. 1976; Gallaway 1980; Gallaway and Lewbel 1982; Gallaway 1984; Putt 1984; Witzig

1986; Reggio 1987; Stanley and Wilson 1989, 1990 a and b; Render and Wilson 1994; Stanley 1994;

Scarborough-Bull and Kendall 1994; Render 1995; Stanley and Wilson 1996; Gitschlag et al. 1997;

Rooker et al. 1997; Kasprizak 1998; Stanley and Wilson 1998). The platforms studied for this pilot

survey, conducted in August and October 1995, were located east of the Mississippi River and

represent the first attempt to develop broad-scale oil and gas platform survey protocols, as well as

one of the few studies of platforms in the eastern Gulf.

METHODS

Acoustic, video and fishing experiments were conducted around eight oil platforms on the

Mississippi-Alabama continental shelf (MS/AL shelf) (Table 7.9 and Figure 7.19). Only the video

data from this study are presented here. The platforms varied in structural complexity from a onepile well to large multiple-pile structures. Two platforms were located in 50 – 55 m of water, four

at 30 – 39 m , and two were at 20 – 29 m.

The research platform used for this pilot study was the R/V Caretta, a 17.7-m single screw steel hull

shrimp boat. We were able to operate the various camera systems in close proximity to the

platforms; however, tides, sea state, currents, and wind played a factor in the Caretta’s ability to tieoff and remain tied to platforms. Typically the Caretta was tied-off, stern-to, on the down-current

side of the structure and remained so during the experiments. We were forced to move from two

platforms during the course of the study due to strong tides and currents. 

Water parameter data were collected using a Seabird CTD water profiler to measure depth, water

temperature, salinity and light transmissivity. Currents near the substrate can re-suspend and

transport sediments in the water column, thereby reducing the visibility in the layer of re-suspended

sediments. This layer of the water column has been termed the nepheloid layer (Rezak et al. 1983;

McCave 1986; Dennis and Bright 1988; Brooks 1991). Data from the transmissivitysensor was used
396

2

Mention of trade names or commercial firms does not imply endorsement by the National Marine Fisheries Service,

NOAA.

Table 7.9. Location, depth and date sampled, of each oil and gas platform surveyed on the MS/AL

shelf during the 1995 pilot study. Platform name abbreviations: MP = Main Pass, CA =

Chandeleur Area and VK = Viosca Knoll.

Platform # and name Rig depth (m) Latitude Longitude Date Sampled

1) MP-132-C 52.4 29° 23.50' N 88° 38.75' W 8/8/1995

2) MP-108-2 21.6 29° 32.71' N 88° 39.10' W 8/9,10 & 15/95

3) MP-111-well 1 28.9 29° 30.95' N 88° 39.19' W 8/16/95

4) MP-202-A 50.6 29° 29.94' N 88° 27.05' W 8/17/1995

5) CA-38-A 35.7 29° 44.07' N 88° 28.90' W 8/18/95

6) VK-203-B 36.9 29° 47.23' N 88° 20.94' W 8/18 & 19/95

7) VK-203-A 37.8 29° 46.89' N 88° 20.01' W 8/19/95

8) VK-69 31.1 29° 55.57' N 88° 28.72' W 10/26/1995

to determine the depth of the nepheloid layer. Determination of the nepheloid layer allowed efficient

use of survey time and video tapes because taping was not done in the nepheloid layer.

The video gear included a Pan and Tilt camera system (P&T), a Deep Ocean Engineering2 Phantom

remotely operated vehicle (ROV) and a Four-Camera Array (4-C). The P&T consisted of a black

and white camera mounted on a pan and tilt mechanism housed inside a 1.2 m X 1.2 m angle-iron

cage. The camera had a 0.3 lux, 12.5 mm lens with a 65° viewing angle. The sides of the cage were

labeled A-D, and a fin on one corner prevented spinning at depth. The ROV had a 10 lux, 9 mm lens

color camera with a 56° viewing angle. The 4-C array used four, 3 lux Hi 8 mm Sony color cameras

housed in Amphibico Dive Buddy III housings with a 72.5° viewing angle. The four stationary

cameras were placed orthogonally to each other, providing a nearly 360° view. 

Three video experiments were conducted to examine both within-platform and between-platform

variability. Quadrant-at-depth was the first experiment conducted. The P&T and the 4-C array gear

were used to determine fish abundance at depth. The P&T was used at the first seven platforms and

the 4-C was used at the last platform sampled (Figure 7.19). The differences between the two video

gears were

1) the 4-C array records in four directions (quadrants) simultaneously while the P&T records

only one quadrant at a time by rotation of the camera;
397

Figure 7.19. Location of eight platforms sampled on MS/AL shelf during a pilot study on fish

assemblages associated with oil and gas platforms in 1995. Platform number and

name were as follows: 1 ( MP-132-c), 2 (MP-108-2), 3 (MP-111 well 1), 4 ( MP202-A), 5 (CA –38-A), 6(VK-203-B), 7 (VK-203-A), 8 (VK-69). Platform name

abbreviations: MP = Main Pass, CA = Chandeleur Area and VK = Viosca Knoll.
398

2) the 4-C array used cameras that provided a higher quality picture; and

3) the P&T camera has a lower lux rating than the Hi 8 mm cameras on the 4-C array. The P&T

was deployed to 6.1 m below the surface for the first sample depth.

The P&T camera recorded for 2.5 minutes in each quadrant at each depth. The camera was rotated

approximately 90° before recording the next quadrant. The total time recorded for each depth was

10 minutes. The P&T cage was then lowered to the next sample depth, about 6.1 m deeper, and the

process repeated until the water column was covered, or the visibility was reduced to less than 1 m.

The 4-C array was the only gear deployed at platform eight (Figure 7.19) and the only platform

sampled in October. The array was tied off to the Caretta so that one camera was pointed at the

platform and could not spin during the experiment. The 4-C array sampled every 6.1 m, recording

between 40 - 45 minutes per depth. 

A second experiment was conducted using Aimed Video (AV) in conjunction with a Fisheries

Acoustic System (FAS). The transducer for the FAS was deployed over the side of the Caretta

opposite the side that the P&T video system was being deployed. The P&T camera was aimed to

view the area that was insonified at 6.1 m intervals. The camera was generally positioned so that it

was aimed to view along the side of the structure, usually between 2 – 7 m from the structure. At

times, the view also included a platform leg or the edge of a leg.

In the third video experiment, the ROV was deployed and maneuvered down a platform leg. Since

the ROV was maneuvered closer ( 0-1.5 m) to the legs and cross-members of a platform than the

stationary cameras, it was stopped every 3 m to pan in and out of the platform and up and down the

leg. Being this close to the leg or cross-member, the ROV camera was viewing a smaller portion of

the leg at any time than the stationary video gears were. This procedure continued until the bottom

of the leg or the nepheloid layer was reached. Once the ROV entered the nepheloid layer, depending

upon the visibility and darkness level at depth, the external light was turned on. After viewing along

one leg, the ROV was maneuvered to the next leg. ROV operations varied from platform to

platform. Usually, between 27 and 43 minutes of video were collected, depending upon bottom

depth, currents at depth, turbidity and complexity of the structure. We viewed between one and two

legs and one and two cross-members at each platform sampled. Actual depths sampled for each

platform are given in Table 7.10.

Sampling volume of each camera system was determined to estimate the density of fishes associated

with oil and gas platforms. In 1994, NMFS ML scientists conducted several experiments at different

depths and differing light transmissivities to determine the viewing distance of cameras (Gledhill

and Lyczkowski-Shultz 1994). These experiments determined that at a transmissivity of 75% or

higher, large fish (6") can be identified at least 5 m from the camera and small fishes (<6") can be

identified from 3-4 m. Additionally, Rydene and Kimmel (unpublished manuscript 1994) concluded

that underwater video cameras ‘accurately’ view for a distance of up to 5 m. A conservative estimate

for the distance viewed was 5 m, and the camera’s viewing angle was used to calculate the volume

of the conical area sampled for each camera. The P&T camera has a viewing angle of 65°, thereby

allowing it to view an estimated 53.1 m3

. The cameras on the 4-C array had a 72.5° viewing angle,

giving each camera an estimated 70.4 m3

 of area viewed. The ROV camera had a viewing angle of
399

Table 7.10. Video sampling effort by depth at eight oil and gas platforms surveyed during 1995

on the MS/AL shelf. Platform name abbreviations: MP = Main Pass, CA =

Chandeleur Area and VK = Viosca Knoll.

Platform #

and name

Pan & Tilt

depth (m)

Aimed Video

depth (m)

ROV

depth (m)

4-Camera

depth (m)

1) MP-132-C 9.1,15.2, 24.4 - 6.1, 15.2, 24.4,

52.4

-

2) MP-108-2 3, 6.1, 9.1,

12.2, 15.2,

18.3, 21.3

4.5, 9.1, 13.7,

18.3

6.1, 9.1, 12.2,

15.2, 18.3, 21.6, 

-

3) MP-111-w1 6.1, 12.2, 18.3,

24.4

6.1, 12.2, 18.3,

24.4

- -

4) MP-202-A 6.1, 12.2, 18.3,

24.4, 30.5

6.1, 12.2, 18.3,

24.4, 30.5

6.1, 9.1, 12.2,

15.2, 18.3, 21.3,

24.4, 30.5, 33.5,

50.6

5) CA-38-A 6.1, 12.2, 18.3,

21.3, 24.4

3, 9.1, 15.2,

21.3

3, 6.1, 9.1, 12.2,

15.2, 18.3, 21.3,

24.4, 27.4, 30.5,

35.7

-

6) VK-203-B 6.1, 12.2, 18.3,

24.4

6.1, 12.2, 18.3,

24.4

3, 6.1, 9.1, 12.2, 

15.2, 18.3, 21.3,

24.4, 27.4, 30.5,

35.7, 36.9

-

7) VK-203-A 6.1, 12.2, 18.3,

24.4

6.1, 12.2, 18.3,

24.4

6.1, 9.1, 12.2, 

15.2, 18.3, 21.3,

24.4, 27.4, 30.5,

35.7, 37.8

-

8) VK-69 - - - 6.1, 12.2, 18.3,

24.4
400

56°, making the volume viewed approximately 37 m3 (Table 7.11). Fish density estimates recorded

on video were standardized to 100 m3 for comparing the different video gears. 

Table 7.11. Sampling volume of video cameras used to survey oil and gas platforms on the

MS/AL shelf, during 1995.

Video gear

Camera’s

Viewing

Angle

Distance

Viewed

(m)

Volume

Sampled

(m3)

Pan & Tilt Camera 65 5 53.1

4 - Camera Array 72.5 5 70.4/camera

ROV 56 5 37.0

ANALYSIS

The P&T quadrant-at-depth experiment produced 10 minutes of video for each depth sampled on

a platform with 2.5 minutes per quadrant. The 4-C array taped 40-45 minutes of video for each depth

at platform 8, but only the first 10 minutes of video were used for analysis. Thirty 1-second

randomly selected ‘snapshots’ were selected from the video tapes recorded at each depth from the

P&T system and 4-C array, and all fish were identified to the lowest possible taxonomic level and

counted. The AV experiment initially collected video footage for forty minutes at depth and later

for twenty minutes at each depth. Only the first ten minutes of video for each depth at a platform

were used for analyses. Data collected using the ROV were not used to obtain density estimates but

were used in assemblage structure comparisons using presence/ absence of taxa. The density

estimates could not be determined because the viewing volume was not consistent during ROV

operations for this study. This problem was caused by parts of the platform structure (legs, crossmembers, pipping, etc.) being within the volume viewed during ROV operations, thereby subtracting

an unknown amount of area from the volume viewed. 

RESULTS

Video data collected from the eight platforms by the P&T quadrant-at-depth, AV, and the 4-C

experiments resulted in three-, four- or five-depth strata covered by each gear type. Depth strata

sampled for each experiment varied with platform depth and the presence of a nepheloid layer

(Table 7.10). Varying currents and tides prevented completion of some experiments at any particular

platform. Additionally, stationary video data were not collected at depths within a detected

nepheloid layer. The experiments using the P&T system were all conducted during August. The

P&T quadrant-at-depth experiments were conducted at the first seven platforms. The AV experiment

was conducted at the second through the seventh platform. The 4-C array was the only gear used at

the last platform sampled, which was also the only platform sampled in October. The ROV collected

data from more defined depth strata and sampled deeper than the other video gear, since it sampled
401

Figure 7.20. Water column transmissivity for the eight oil and gas platforms surveyed on the

MS/AL shelf during 1995.

at 3 m intervals and had an external light source. The ROV was not used at platform 3 due to strong

currents. CTD data were collected from the first seven platforms. 

Transmissivity profiles plotted from CTD profiles at each platform indicated that nepheloid layer

depth and thickness varied among platforms (Figure 7.20). An actual profile from platform number

four shows a typical transmissivity trace observed during this study on the MS/AL shelf. The trace

shows that from the surface to about 45 m transmissivities are greater than 80%, with a sudden drop

at 47 m marking the top of the nepheloid layer (Figure 7.21). All platforms had mean

transmissivities above the nepheloid layer ranging from 84% - 97% and were generally greater than

94% (Figure 7.20), while transmissivities in the nepheloid layer, when present, were more variable

ranging from 35% - 86%. Thickness of the nepheloid layer ranged from approximately 1 - 12 m. The

nepheloid layer at platform 2, while present, was very slight (above 75%) and not very thick (about

1 m), still providing visibility above the minimum needed for density estimates. The CTD was not

available for use during the sampling of platform 8, the northern-most platform that was sampled

in October. However, the video footage did not detect a discernable nepheloid layer for the entire

water column.
402

Transmissivity (%)

0 20 40 60 80 100

Depth (m)

-60

-50

-40

-30

-20

-10

0

Figure 7.21. Transmissometer profile from platform 4 (MP-202-A) during a pilot study of oil and

gas platforms on the MS/AL shelf in 1995.

A total of 19 families represented by 44 taxa were observed from video tapes recorded during this

study (Tables 4 and 5). Observed taxa included those associated with natural reefs as well as

artificial reefs such as oil and gas platforms (Sonnier et al. 1976; Gallaway 1980; Lukens 1981;

Stanley and Wilson 1990a; Scarborough-Bull and Kendall 1994; Gitschlag et al. 1997; Rooker et

al. 1997). The ten most frequently observed taxa were Atlantic spadefish, Chaetodipterus faber; blue

runner, Caranx crysos; gray (mangrove) snapper, Lutjanus griseus; sheepshead, Archosargus

probatocephalus; red snapper, Lutjanus campechanus; the scad complex, Decapterus spp. and/or

Trachurus sp.; crevalle jack, Caranx hippos; lookdown, Selene vomer; great barracuda, Sphyraena
403

Table 7.12. Families observed in all video samples combined from oil and gas platform pilot

study on the MS/AL shelf during 1995.

Scientific Name Common Name

Serranidae

Pomatomidae

Rachycentridae

Carangidae

Lutjanidae

Haemulidae

Sparidae

Sciaenidae

Kyphosidae 

Ephippidae

Chaetodontidae

Pomacanthidae

Pomacentridae

Sphyraenidae

Labridae

Blennidae

Acanthuridae

Scombridae

Balistidae

Groupers and Sea basses

Bluefish

Cobia

Jacks

Snappers

Grunts

Porgies

Drums

Sea chubs

Spadefishes

Butterflyfishes

Angelfishes

Damselfishes

Barracudas

Wrasses

Combtooth blennies

Surgeonfishes

Mackerels and Tunas

Triggerfishes

barracuda; and gray triggerfish, Balistes capriscus (Table 7.13). Six species common to all four sets

of video gear were: Atlantic spadefish, blue runner, gray snapper, sheepshead, red snapper, and gray

triggerfish. The ROV viewed farther into the confines of each platform and closer to the platform

structure, which allowed detection of more cryptic, smaller, and more reef-associated species than

any of the other video gear. More taxa (34) were observed on the video from the ROV than any

other video gear (Figure 7.22). Twenty-four taxa were observed with the P&T, 14 taxa with the AV

and 11 taxa with the 4-C array. The number of taxa observed inside the confines of a platform (ROV

data) by depth were compared to the number seen outside (P&T, AV & 4-C data) the platform by

depth. While there were more taxa observed within the platform structure, there was no relationship

between the number of taxa and depth (Figure 7.23).

Density estimates for all taxa, jacks, snappers and groupers were compared from AV, P&T and the

4-C observations (Figures 7.24 and 7.25). The highest mean densities for all taxa were observed with

the AV (34.8 fish/100m3

) and the lowest with the 4-C (1.1 fish/100m3). The large difference in mean

density between the AV and the other gears was due to the high concentrations of jacks (carangids)

that schooled around the platform margins and accounted for most of the fish observed. The P&T

and 4-C were viewed in all four directions while the AV observed the water column near the
404

Table 7.13. Percent occurrence of all taxa observed at eight oil and gas platforms with all video

gears from a pilot study on the MS/AL shelf in 1995 (n = 138, were n = number of

all video frames sampled from P&T, AV, 4-C and ROV).

Common Name Scientific Name % Occurrence % Standard Error

Blue runner Caranx crysos 60.870 4.170

Atlantic spadefish Chaetodipterus faber 49.275 4.271

Gray (mangrove) snapper Lutjanus griseus 43.478 4.235

Sheepshead Archosargus probatocephalus 42.029 4.217

Red snapper Lutjanus campechanus 20.290 3.436

Great barracuda Sphyraena barracuda 18.841 3.341

Lookdown Selene vomer 18.116 33.291

Scad complex Decapterus spp. &/or Trachurus sp. 16.667 3.184

Gray triggerfish Balistes capriscus 11.594 2.735

Blue angelfish Holacanthus bermudensis 10.145 2.580

Sargent major Abudefduf saxatilis 10.145 2.580

Crevalle jack Caranx hippos 9.420 2.496

Scamp Mycteroperca phenax 8.696 2.407

Blenny Blenniidae 6.522 2.109

Damselfish Pomacentrus spp. 5.072 1.875

Grouper Mycteroperca spp. 4.348 1.742

Sea chub Kyphosus spp. 4.348 1.742

Whitespotted soapfish Rypticus maculatus 4.348 1.742

Gag Mycteroperca microlepis 3.623 1.597

Bluefish Pomatomus saltatrix 2.899 1.433

Reef butterflyfish Chaetodon sedentarius 2.899 1.433

Cubbyu Equetus umbrosus 2.899 1.433

Cobia Rachycentron canadum 2.174 1.246

Blackbar drum Equetus iwamotoi 2.174 1.246

Damselfishes Pomacentridae 2.174 1.246

Wrasse Halichoeres spp. 1.449 1.021

Amberjack Seriola spp. 1.449 1.021

Surgeonfish Acanthurus spp. 1.449 1.02

Horse-eye jack Caranx latus 1.449 1.021

Bar jack Caranx ruber 1.449 1.021

Spotfin butterflyfish Chaetodon ocellatus 1.449 1.021

Butterflyfish Chaetodon spp. 1.449 1.021

Rainbow runner Elagatis bipinnulata 1.449 1.021

Molly miller Scartella cristata 1.449 1.021

Spotfin hogfish Bodianus pulchellus 0.725 0.725

Creole-fish Paranthias furcifer 0.725 0.725

Graysby Cephalopholis cruentatus 0.725 0.725

Bank butterflyfish Chaetodon aya 0.725 0.725

Rock hind Epinephelus adscensionis 0.725 0.725

Little tunny Euthynnus alletteratus 0.725 0.725
405

Gear

P&T A/V ROV 4C

Number of Taxa

0

5

10

15

20

25

30

35

40

n=37

n=28

n=53

n=20

7 rigs 6 rigs 6 rigs 1 rig

Figure 7.22. Number of taxa observed by each gear from pilot study of oil and gas platforms on

the MS/AL shelf in 1995. (n = number of video samples. Number of rigs where gear

was used is indicated below each gear.)
406

Figure 7.23. Number of taxa observed within each platform and outside each platform from pilot study of oil and gas platforms

on MS/AL shelf in 1995. The drop video gears did not sample below the nepheloid layer, therefore the graph doesnot exceed 35 m.
407

Figure 7.25. Mean density of selected taxa recorded by the Pan & Tilt and 4-Camera Array video

gears during a pilot study of oil and gas platforms on the MS/AL shelf in 1995.

Numbers in and above histogram are mean number of fish/100 m3 (n = number of

video samples taken by each gear at the number of rigs indicated).

Figure 7.24. Mean density of selected taxa recorded by the Aimed Video gear during a pilot study

of oil and gas platforms on the MS/AL shelf in 1995. Numbers in and above

histogram are mean number of fish/100 m3 (n = number of video samples taken at the

six rigs sampled with the AV).

n = 28

6 rigs

n = 37

7 rigs

n = 20

1 rig
408

platform margins where the jacks were always in view. The density of snappers and groupers

estimated by each video gear were similar.

Differences in total fish density were observed at different depths. There appeared to be a positive

trend with depth; however, this trend was influenced by a single high density of fish observed at 30

m (Figure 7.26). Red and gray snappers also differed in depth distribution (Figures 7.27 and 7.28)

on these eight platforms during this study. More red snapper were observed at depths > 25 m and

typically, they were recorded on the videos at depths > 15 m. Gray snapper were observed more frequently at depths < 20 m, although they were present at all depths. Red snapper were observed to

move away from the confines of the structure while gray snapper did not often range far from it.

Since differences in overall fish density among platforms were observed (Figure 7.29), the

relationship between fish density and the age of the platform and between fish density and the type

of fauna attached to each platform were examined. No significant differences in total fish density

by gear with age of a platform were found using a two-way analysis of variance. Testing was also

done for red and gray snapper, scamp, gray triggerfish, blue runner and scad with no differences

found for them as well. There were differences in fish density with attached faunal type, for all taxa

and some individual taxa. Attached fauna was classified into two groups using the video data:

platforms with > 50% of the surface area covered by barnacles and platforms with > 50% of the

surface area covered by other epifauna (octocorals, gorgonians, sponges and bryozoans). The mean

density of fish was lower at platforms dominated by barnacles (Figure 7.30). Gray snapper densities

were higher at platforms dominated by barnacles and red snapper densities were higher at platforms

dominated by other faunal types (Figure 7.31). There was no obvious relationship from a one-way

analysis of variance, testing whether faunal type varied with platform age. 

DISCUSSION

Our pilot study was designed to evaluate the efficiency of various types of video gear and

methodologies in assessing fish populations on oil and gas platforms. Within-platform and

between-platform variability in fish assemblage composition, vertical distribution and abundance

were examined to develop an optimal broad-scale survey design.

Within-platform variability was examined by three different video gears in four different

configurations. The P&T and 4-C gears looked into the platform, along the margins of the platform,

and away from the platform. The 4-C array viewed in all four directions simultaneously, had a

greater viewing angle, and produced a higher quality image; it was, therefore, considered to be the

best video gear for sampling along platform margins. The P&T and 4-C did not record images far

enough into the confines of the platform to pick up cryptic and smaller species; therefore, the ROV

was used to view these taxa. The AV taped only along the margins of the platforms in one direction

allowing observation of fishes that occurred in close proximity to the platforms, especially those

taxa that circle the platforms, such as carangids. High concentrations of fishes have been detected

in close proximity to platforms using acoustical arrays (Stanley and Wilson 1990b). Survey cameras

need to examine within the confines of the platform and along its margins. Although similar taxa

were found at each platform, more taxa were seen inside the platform structure than outside. Our

limited pilot study indicated that camera orientation was critical for accurate counts of snappers and
409

Depth (m)

0 5 10 15 20 25 30 35

Mean # of Fish / 100 m

3

0

10

20

30

40

Mean # = 1.82 + 0.71(Depth)

r 2 = 0.295 p = 0.09

Figure 7.26. Mean density of all fish observed at each depth for P&T, AV and 4-C video gears

combined, during a pilot study of oil and gas platforms on the MS/AL shelf in 1995.
410

Depth (m)

0 5 10 15 20 25 30 35

 Mean # of Fish / 100 m

3

0

5

10

15

20

25

Mean # = -0.23 + 0.03(Depth)

r 2 = 0.019 

p = 0.0001

n = 85

Figure 7.27. Mean density of red snapper by depth for the P&T, AV and 4-C video gears

combined, during a pilot study of oil and gas platforms on the MS/AL shelf in 1995.
411

Depth (m)

0 5 10 15 20 25 30 35

# of Fish / 100 m

3

0

2

4

6

8

10

12

Mean # = 0.68 - 0.02(Depth)

 r 2=0.04 p = 0.0001

 n = 85

Figure 7.28. Mean density of gray snapper by depth for the P&T, AV and 4-C video gears

combined, during a pilot study of oil and gas platforms on the MS/AL shelf in 1995.
412

Platform Number

012345678

Mean # Fish / 100 m

3

0

20

40

60

80

100

Figure 7.29. Mean number of fish per 100 m3 (+/- SE) for each oil and gas platform surveyed

during a pilot study on the MS/AL shelf in 1995. Mean fish density estimates from

both the P&T and 4-C video gears were combined for platforms 2 - 7. Data from

only the P&T were available for platform 1 and only 4-C array for platform 8.
413

n = 85

Figure 7.30. Mean density of total fish versus dominant attached epifauna from eight oil and gas

platforms surveyed during a pilot study on the MS/AL shelf in 1995. Numbers in and

above histogram are mean number of fish/100 m3.

Figure 7.31. Mean densities of snappers versus dominant attached epifauna from eight oil and gas

platforms surveyed during a pilot study on the MS/AL shelf in 1995. Numbers in and

above histogram are mean number of fish/100 m3.

n = 85
414

groupers. More groupers were observed within and in very close proximity to the platform than

away from the platform. Few groupers were observed during our study; therefore, no broad

conclusions can be made concerning their association with oil and gas platforms. More red snapper

were observed outside the platforms than within, while gray snapper were observed more frequently

inside the platforms than outside. No difference in the number of species present with depth was

observed. Although we observed differences in the abundance of red and gray snapper with depth,

we cannot make any general inferences regarding their depth distributions on all platforms in the

GOM without a larger scale study. Render (1995) noted differences in the depth distributions of

juvenile and adult red snapper from video observations on a single platform. Stanley and Wilson

(1996), using acoustical arrays around oil and gas platforms, noted that total fish density also varied

with depth. The presence of a nepheloid layer limits the ability to view fishes over the entire vertical

extent of platforms and makes it difficult to draw conclusions about the depth distributions of fishes

on platforms from video. 

In general, all the platforms studied had similar taxa around them. The assemblages seen on these

eight platforms east of the Mississippi River were similar in composition to species assemblages on

oil and gas platforms west of the Mississippi River (Sonnier et al. 1976; Gallaway 1980; Stanley and

Wilson 1990a; Gitschlag et al. 1997; Rooker et al. 1997). There were significant differences in mean

fish density among platforms depending on the type of fauna attached to the platform. Total mean

fish densities were lower at platforms dominated by barnacles than at platforms dominated by other

epifauna. Additionally, red snapper densities were higher at platforms where the dominant fauna was

higher-relief growths and gray snapper densities were higher at platforms dominated by barnacles,

i.e., lower-relief growth. This difference may be due to the preferred prey items, habitat, or

differences in the behavior of these two species. While both species seem to be opportunistic

generalists in their feeding behavior, it appears that red snapper feed more frequently on fish than

do gray snapper (Parrish 1987). Starck (1970) characterized the feeding habitat of gray snapper as

being mixed low-relief bottom type and not adjacent flat areas. This is similar to the barnacledominated platforms seen in this survey. Red snapper are known to feed away from reef areas and

platforms on the soft-bottom areas adjacent to these habitats as well as possibly off-bottom (Moseley

1966; Bradley and Bryan 1975; Gallaway 1980). Since they may feed off-bottom, red snapper may

also feed on or in very close proximity to the platforms to some degree, as seen by the high catch

rates of red snapper on platforms by recreational fishers (Stanley and Wilson 1990a). While there

may be many possibilities that would explain these observed differences between the distribution

of red and gray snapper on platforms with attached epifauna, this information needs to be known

and taken into consideration for a survey design of oil and gas platforms. Just as stock assessment

models use the natural history of a harvested species during analyses (NMFS 1999), the

development of resource surveys needs this same understanding of the target species to provide a

scientifically accurate index of abundance. Variance components for sample allocation were not

adequately addressed with this limited study, but we did learn that a survey will probably not be able

to take just a single ‘snapshot’ of a platform for assessing snappers and groupers.

The interface between the clearer surface waters and the bottom nepheloid layer as seen from video

footage is dynamic, undulating at depth, potentially from subsurface currents. The thickness and

mean transmissivity readings within the nepheloid layer can vary greatly, as observed from our

study, even in a small geographic area and over a short time frame. These results and observations
415

are similar to findings from the Mississippi-Alabama Continental Shelf Ecosystem Study (Brooks

1991). Dennis and Bright (1988) stated that the bottom nepheloid layer is the most important

environmental factor in determining the composition of fish assemblages and linked it to low species

richness on natural hard banks in the northwestern GOM. 

RECOMMENDATIONS

 Additional data from platforms located both east and west of the Mississippi River and distributed

across the continental shelf is required before a final survey design can be developed. Differences

in fish assemblages associated with platform size, platform age, side of platform, and attached

epifauna need to be better examined. Nearest neighbors (other oil platforms and shelf–edge banks)

should also be considered as factors that may account for the variability in fish density among

platforms. Acoustic studies indicate that estimates of total fish abundance on a platform are highly

variable from month to month and seasonally (Stanley 1994; Stanley and Wilson 1996, 1998). There

may also be seasonality in the presence of the nepheloid layer in this area and currents may have an

effect on its presence, thickness, and density as well (Brooks 1991). Therefore, the time of year may

also influence the fish assemblages observed on platforms. Another consideration in survey timing

is the time when key resource species (snappers and groupers) recruit to the fishery.

Our pilot study did not adequately describe differences in fish densities inside the confines of the

platform versus densities outside the platform, since the gear we used did not quantitatively sample

within platform structure. We propose that densities of fish inside the platforms be estimated with

the ROV, the 4-C array, and SCUBA divers in any new survey. A SCUBA census should be

included in any follow-up study, since they are routinely used to sample natural and artificial reefs

(Brock 1954; Hastings et al. 1976; Ogden and Ebersole 1981; Sale and Douglas 1981; Brock 1982;

Kimmel 1985; Bohnsack and Bannerot 1986; Parker 1990; Bull and Kendall 1994; Rooker, et al.

2000), and since divers can get inside the structure with ease. Both point-count census and transect

methods can be evaluated, and the best method for platforms can be used. However, there are

limitations to SCUBA including depth, bottom time, and logistical considerations that may not make

it an effective tool for a large-scale survey. Fish avoidance of divers may also be problematic

(Stanley 1984) and needs to be investigated further. However, the data collected by divers is

immediate. Video tapes take longer to process but can be archived for later review and confirmation

of fish identifications.

A method to quantify the ROV data must be developed so that this gear can be compared to the

stationary video gears or divers for density estimates in determining the best gear or combination

of gears to be used for sampling. There are at least two methods for calculating volumetric densities

from the ROV video. One method would hold the ROV stationary at a set depth for a period of time,

imitating the stationary video gears. Submersibles have been used to conduct point-count censussing

of fishes on natural hard bottoms (Shipp et al. 1986). The other method is a transect method.

Submersibles have been used in the past to conduct transects over natural reef areas (Parker and

Ross 1986) as well as oil platforms (Love et al. 2000). Both of these methods may be effective and

necessary to calculate total densities for a platform with an ROV. Putt (1984) also suggested using

ROVs in a three-dimensional sampling strategy with observations at both fixed positions and along

horizontal transects at several depths on a platform. Whatever method chosen would require that the
416

ROV be outfitted with a pair of lasers at a known distance apart to help maintain the desired distance

away from the structure and to obtain fish lengths. This adjustment would help correct the area

viewed for volumetric density estimates. Fish avoidance by ROV/submersibles needs to be

considered in regards to their use to examine fish abundance around platforms (Stanley 1984, Parker

and Ross 1986, Shipp et al. 1986).

While we only presented the results of the video experiments from this small pilot study, an

effective assessment of the fishes associated with oil and gas platforms will most likely involve

some combination of visual, acoustic, and fishing assessment gears and techniques. A combination

of gears and techniques is required due to the vertical nature of oil and gas platforms and the

presence of nepheloid layers over most of the north central and northwestern GOM (Rezak et al.

1983). More work needs to be done with all of these gears and techniques around oil and gas

structures; in addition, we need to study further ways of using the data gathered during oil and gas

platform surveys in population assessment models. 

ACKNOWLEDGMENTS

I would like to acknowledge the following people for their help with the pilot study and the

preparation of this paper. Dr. Jeff Render designed this project but passed away before its

completion. Thanks to Dr. Scott Nichols, Dr. Terry Henwood and the late Dr. Warren Stuntz for

allowing me to finish this pilot survey. Additionally, thanks to Captain Drew Hopper and First Mate

David Callaway for their untiring support and willingness to try new things with the R/V Caretta,

and to Cliff Harper for piloting the ROV.

For guidance in the manuscript and presentation preparation, I am grateful to Chris Gledhill, Dr.

Joanne Lyczkowski-Shultz, David Hanisko, Denice Drass and Carolyn Burks. Statistical analyses

were conducted by Chris Gledhill, although I accept full responsibility for any errors. This study was

funded by the NMFS ML and by MARFIN.

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421

SEASONAL AND SPATIAL VARIATION IN THE BIOMASS AND SIZE

FREQUENCY DISTRIBUTION OF FISH ASSOCIATED WITH OIL AND

GAS PLATFORMS IN THE NORTHERN GULF OF MEXICO

David R. Stanley

BEAK International

Charles A. Wilson

Coastal Fisheries Institute 

Center for Coastal, Energy and Environmental Resources

Louisiana State University

INTRODUCTION

Since the first petroleum platform was placed off the Louisiana coast in 1948, the largest artificial

reef complex in the world was started. To date, approximately 4,000 petroleum platforms are

scattered across the outer continental shelf of the northern Gulf of Mexico (GOM), with the vast

majority off the coasts of Louisiana and Texas. It is hypothesized that artificial reefs and platforms

improve and/or diversify habitat, increase resources, modify the assemblages of organisms in the

region or concentrate existing resources. The placement of these defacto reefs has undoubtedly

impacted the regional marine community although little information is available. Only recently have

assessment methods been developed to test these and other hypotheses concerning artificial reefs.

Scientific investigations of fish assemblages at petroleum platforms did not start until the mid 1970s.

They consisted of visual surveys conducted by SCUBA divers, remotely operated underwater

vehicles (ROV) and stationary cameras; the majority of these projects were short term, often only

“snapshots” of the fishes at each site (Shinn 1974, Sonnier et al. 1976; Gallaway et al. 1981;

Continental Shelf Associates 1982; Gallaway and Lewbel 1982; Putt 1982). The results of this early

research provided insights into structure-associated assemblages including variations in abundance

and species composition with platform, water depth, and time of the year. However, results have

been difficult to compare because of problems with limited visibility, gear bias, diver avoidance, and

a lack of standardized survey methodology. Although visual surveys are the method of choice to

survey natural and artificial reefs (Bortone and Kimmel 1991), the presence of SCUBA divers can

bias the density and possibly species composition of fishes at the site (Sale and Douglas 1981; Brock

1982; Bohnsack and Bannerot 1986; Stanley and Wilson 1995). 

In response to the difficulty in assessing the fisheries resources associated with petroleum platforms

and the biases inherent in visual surveys, Gerlotto et al. (1989) demonstrated that towed

hydroacoustics could be used to measure fish density near petroleum platforms off Cameroon. We

later utilized complimentary sampling methods of visual surveys and quantitative dual beam

hydroacoustic surveys to document the assemblage of fishes associated with petroleum platforms

in the northern GOM (Wilson and Stanley 1991; Stanley and Wilson 1995, 1996, 1997, 2000).
422

Despite the range of methodologies, investigators found that fish abundance and species

composition change dramatically with proximity to platform, location, and time of year (Sonnier

1976; Continental Shelf Associates 1982; Gallaway and Lewbel 1982; Putt 1982; Stanley and

Wilson 1996; 1997). Gerlotto et al. (1989) found that fish densities were 5 to 50 times higher

immediately adjacent to a platform than 50 m away. Stanley and Wilson (1996, 1997, 2000) reported

the near field area of influence of a platform on the continental shelf to be 16-20 m away from the

platform. Fish densities within 20 m of a platform were 3 to 60 times higher than at greater distances

and densities observed at distances greater than 50 m were comparable to background levels of the

open waters of the northern GOM (Stanley and Wilson 1996, 1997, 2000). Long-term studies

reported that fish populations at petroleum platforms were highly variable over time. Putt (1982)

observed fluctuations of a factor of two from month to month in density, while Stanley and Wilson

(1996, 1997, 2000) reported that monthly and seasonal abundances change by up to a factor of five.

Based on these previous research efforts, we know that significant numbers of fishes are found at

these sites, although they do not exhibit a large species diversity and do not appear to have a high

site fidelity. Since many of the common species at platforms are highly sought after by commercial

and recreational users and a large number of platforms exist in the region, it is hypothesized that

platforms have considerable importance to regional fisheries. Despite this hypothesis of the

importance of platforms on the regional fish assemblages, quantifiable censuses of fish assemblages

were not possible until the combined use of dual beam hydroacoustics to enumerate the fishes at

these sites and visual surveys with a remotely-operated underwater vehicle (ROV) to determine

species composition were applied. While the results from previous research provided insights into

the species composition and abundance at platforms, the results were not comparable nor were they

quantifiable. To measure the impact of the presence of platforms on the fisheries resources a

standardized quantifiable methodology must be used. 

The specific objectives of this research were to

1) Measure and compare the species composition, biomass and size frequency distribution of

fish associated with three petroleum structures.

2) Determine the effect of temporal, physical and chemical variables on species composition,

biomass and size distribution of fish associated with platforms.

3) Define the spatial near field influence of each platform on the abundance of fish. 

METHODS

Site Descriptions

Research trips were conducted quarterly (August 1994 to April 1997) to petroleum platforms Grand

Isle 94 (GI94) (located at 28o

31.33 N and 90o05.52 W, water depth 60 m, installed 1975, operated

by Mobil USA Inc.) and Green Canyon 18 (GC18) (located 27o56.48' N and 91o02.28' W, water

depth 219 m, installed in 1988, operated by Mobil USA Inc.) and quarterly (August 1995 and April

1997) to South Timbalier 54 G (ST54) (located 28o50.01'N and 90o22.40' W, water depth 22m,
423

installed 1956, operated by Exxon USA Inc.). The platforms were selected to approximate a transect

extending from the central portion off coastal Louisiana to a distance of 179 km.. Extraction and

production of natural gas and crude oil occurred at each site during research trips. Three reserach

trips were not completed during the project: the spring 1995 surveys to GC18 and GI94 and the fall

1996 survey to ST54.

Three arrays of stationary dual beam hydroacoustic equipment developed through our past research

were used to determine the density of fishes associated with the study sites (Wilson and Stanley

1991; Stanley and Wilson 1995, 1996, 1997,1998, 2000). Arrays 1 and 2 (Figure 7.32) were

designed to measure in situ target strength distribution and density of fishes immediately adjacent

to each side of the platform. Array 1 consisted of four upward-oriented transducers (120 kHz)

suspended approximately 25 m below the surface (at ST 54 they were placed on the bottom), one

on each side of the platform. The upward-facing transducers provided acoustic coverage from the

a depth of 10-15 m to the surface (Figure 7.32). Array 2 consisted of four downward-oriented

transducers (120 kHz) placed approximately 3 m below the surface, one on each side of the

platform. The downward-facing transducers provided acoustic coverage from a depth of 10 m to

within 1-5 m of the substrate depending on the site. The use of four transducers (both upward and

downward orientations) enables the calculation of density throughout the water column on all sides

of the platform. 

Array 3 was designed to estimate the near-field density of fishes associated with the structure and

consisted of four horizontally aligned dual beam transducers (120 kHz) deployed off each side of

the platform at depth of 12 m (Figure 7.33). This arrangement enables relative fish density estimates

to a distance of approximately 80 m from the platform and determination of the near-field area of

influence of each site. 

Total fish abundance estimates at each site were calculated by determining the near-field area of

influence of the platform, then multiplying mean density values for sample and platform side in

number of fish/m3

 by the volume of water on each side of the platform. Fish density in the center

of the platform was calculated by averaging the density estimates of the four sides of the platform.

Fish abundance in the center of the platform was calculated by multiplying the estimated fish density

at the center by the volume of water in the center of the platform. After estimates of the number of

fish were made on each side and center of the structure by strata, these estimates were summed to

calculate the total number of fishes at a site.

Horizontal and vertical acoustic samplings were conducted over three consecutive 24-hour intervals

for each month’s sampling trip; two hours of hydroacoustic data were collected encompassing four

periods (dawn, noon, dusk and midnight) over each 24-hour interval. Hydroacoustic data were

collected sequentially from each of the transducers in five-minute intervals for each trip. 

Acoustic data were collected using a Biosonics model ES2000 scientific echosounder/multiplexerequalizer. The source levels ranged from 218.5 to 220.5 dB re μPa at 1 m depending on the

transducer. The 20 log R system gains ranged from -156.4 to -146.8 dB re V μPa and the 40-log R

system gains ranged from -168.9 to -165.8 dB re V μPa varying with transducer. Sampling rate

ranged from 2 pings s-1 to 10 pings s-1 depending on array and sampling depth. Pulse width was
424

Figure 7.32. Schematic view of stationary hydroacoustic transducer deployment to measure in situ

target strength and density of fishes throughout the water column on each side of the

platform for the three study sites.
425

Figure 7.33. Schematic view of stationary hydroacoustic transducer deployment to measure

horizontal relative density of fishes associated with petroleum platforms.

0.4 ms. Received signals were adjusted for spreading loss by applying a 40 log R time varied gain,

digitized and recorded on digital audio tape (DAT). Reference voltages (approximately 5 V AC)

were recorded on each DAT tape and used to calibrate the acoustic system prior to echo integration

and target strength analyses. During data collection, background noise levels were measured and did

not exceed 40 mV. The voltage threshold used in later analyses was 100 mV corresponding to a

minimum detectable target strength of -56 dB, or a fish of 2.5 cm total length according to Love

(1971).

Digitized hydroacoustic data were processed by a Biosonics model 281 dual-beam processor. Target

strengths and an average backscattering cross section (F) for each depth strata were estimated using

Biosonics TS software, and density estimates were calculated using Biosonics Crunch software with

F for each sample and depth strata. Fish densities were calculated for 5 to 20 m depth vertical

intervals for Array 1 and 2 depending on site. 

Visual point count surveys were performed on each sampling expedition on the downcurrent side

of the platform using a Hydrobotics Orpheus, Benthos MiniRover, or Deep Ocean Engineering HD2

ROV. Visual surveys were performed on nektonic fishes freely swimming within the area of

influence of the platform. Cryptic fishes were not included in the visual surveys since they could not
426

be assessed in the acoustic surveys. Visual surveys done with ROVs were recorded on videocassette

and the point counts performed later identifying individual fish to the lowest taxonomic level.

Estimates of percent species composition for each strata corresponding to the acoustic strata were

calculated from the visual point counts. To estimate the number of fishes by species at each site by

depth strata, the percent species composition data was applied to the quantitative acoustic estimates

of total abundance and confidence intervals for each strata from every sampling trip.

Environmental data consisting of temperature (+/- 0.1 oC), salinity (+/- 0.1 ppt) and dissolved

oxygen (+/- 0.5 ppm) were measured with a Seabird SBE 19 meter. Current speed (+/- 0.1 m/s) and

direction (+/- 1 degree) were measured an Interocean S4 meter during each hydroacoustic data

collection period through the entire water column at each site. 

Data Analysis

Fish density data (number of fish@m-3) from echo integration analysis contained a large number of

zero values, similar to catch data from traditional fisheries sampling techniques (Pennington 1983;

1985; Shaw et al. 1985; Stanley and Wilson 1995; 1996; 1997; 2000). Therefore, hydroacoustic

density data were transformed by log(density + 1) to approximate the normal distribution. 

Two vectors describing current speed and direction to the east-west and north-south were calculated

(Pond and Pickard 1982). Currents from the east and north were scaled to positive values; west and

south currents were scaled to negative values. This scaling provided two vectors which represented

current speed and direction in later analyses.

Randomized block ANOVAs (SAS Institute 1986) were performed for each site with horizontal

log(density + 1) of density data on distance from the platform, time of day (TOD), quarter, year and

their interactions, blocking on side of the platform to examine differences due to these variables.

Tukey’s studentized range tests (Ott 1982) were used to compare the means of significant variables

for horizontal analyses. Statistical tests were reported as significant at the alpha < 0.01 level.

Separate randomized block ANOVAs using SAS (1986) GLM procedures were performed with

vertical target strength data and log (density + 1) of vertical density data for each site on depth, time

of day, quarter, year, temperature, dissolved oxygen level, east and north current vectors, squared

east and squared north current vectors and their interactions, blocking on side of the platform to

examine differences due to these variables. Tukey’s studentized range tests (Ott 1982) were used

to compare the means of significant variables for vertical and horizontal analyses. Tests were

reported as significant at the alpha < 0.01 level. 

The total abundance estimates at the platform were calculated by determining the near-field area of

influence of the platform, then multiplying mean density values (number of fish@m-3) for each month

and platform side by the volume of water on each side of the platform. Fish density in the center of

the platform, not measured with acoustics due to interference by structural members, was assumed

to be the average of the density estimates of the four sides of the platform. Fish abundance in the

center of the platform was calculated by multiplying the estimated fish density of the center by the

volume of water in the center of the platform. 
427

RESULTS

South Timbalier 54

Vertical Density Distribution: Densities of fishes at the ST54 production platform (water depth 22

m) were highly variable over the study period ranging from 0 to over 5.2 fish/m3. A RBD ANOVA

with platform side as a block was used to examine differences in density due to year, season, time

of day, current vectors, temperature, dissolved oxygen, depth, and selected interactions. Density

varied significantly with season, time of day, depth, platform side, east current vector, north squared

current vector, salinity, dissolved oxygen, and the time of day * depth interaction (Table 7.14). 

Temporal differences in fish density were detected between season, time of day and the interaction

of season(time of day (Table 7.14, Figure 7.34). Fish density was highest in 1995 and 1997

(although only one research trip occurred in 1997) indicating annual variation in the fish density at

the site (Table 7.14). Seasonally, fish densities were significantly higher in the fall than in all other

seasons, and lowest densities were found in the spring and summer (Figure 7.35). No overall trend

of fish densities with season and time of day could be detected over the entire study period, but

overall fish densities were significantly higher at midnight than at all other times (Figure 7.36). 

Spatially, fish density varied with platform side, depth and the interactions of depth*time of day and

depth*season. Significantly higher densities were found on the north side of the platform than at all

others (Figure 7.37). With respect to depth, densities were significantly higher in the upper 10 m of

the water column than at all other depth strata, although an increase in density from 20-22 m was

observed when dissolved oxygen levels were greater than 3 ppm (Figure 7.37). While the interaction

of depth*time of day was significant (Table 7.14) in the overall model, examination of fish density

by depth with time of day did not reveal an overall trend with exception of higher fish densities in

the upper 10 m regardless of time of day. The interaction of depth*season was also significant, and

examination of density values by depth for each season revealed significantly lower densities in the

spring and summer from 20-22 m than in the fall and winter. This difference is likely due to the low

oxygen conditions found near the bottom during these periods. 

Environmental conditions also impacted density based on results from the RBD ANOVA (Table

7.14). Fish density was significantly affected by temperature, dissolved oxygen, east current vector

and the north current vector squared (Table 7.14). Fish density decreased slightly with temperature

although this decrease is not consistent, as the highest observed densities were from fall and winter

when temperatures were lowest. A direct relationship between dissolved oxygen and density existed;

highest densities were found at high levels of dissolved oxygen. During the summer 1996 sample,

a hypoxic event was noted, and dissolved oxygen levels were <1 ppm below 15 m. Along with these

low dissolved oxygen levels, fish density was essentially zero from 15-22 m, but higher than average

densities were detected from 0-10 m. The relationship between current speed and fish density, while

significant (Table 7.14), was difficult to interpret. Fish density generally increased with increasing

current speed although the maximum current speeds observed were 43 cm/s. Since the mean current

speed was 11.3 cm/s, most of the speeds observed were likely not high enough to influence the

behavior of the fishes, as the mean size of the fishes was sufficient to negate the influence of low

observed currents.
428

Table 7.14. RBD ANOVA (block on platform side) results of vertical log fish density log (fish

density/m3) with platform side, year, season, time of day, depth, current vectors,

temperature, salinity, dissolved oxygen, and selected interactions at the ST54

petroleum platform.

Source DF SS MS F Prob > F

Model 308 129.00907430 0.41886063 14.09 0.0001

Error 1596 47.44809218 0.02972938

Corrected Total 1904 176.45716648

R-Square C.V. Root MSE LDENSITY Mean

0.731107 87.90991 0.1724221 0.1961350

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 14.78826719 4.92942240 165.81 0.0001

Year 1 0.01226440 0.01226440 0.41 0.5208

Season 3 2.36471052 0.78823684 26.51 0.0001

Diel 3 1.48166178 0.49388726 16.61 0.0001

Depth 4 1.64875440 0.41218860 13.86 0.0001

Temperature 1 0.50166204 0.50166204 16.87 0.0001

Dissolved oxygen 1 0.56616923 0.56616923 19.04 0.0001

Salinity 1 0.02415845 0.02415845 0.81 0.3675

North vector 1 0.17789554 0.17789554 5.98 0.0145

East vector 1 1.28431015 1.28431015 43.20 0.0001

North squared vector 1 0.19835984 0.19835984 6.67 0.0099

East squared vector 1 0.08600079 0.08600079 2.89 0.0892

North * East 1 0.00384716 0.00384716 0.13 0.7191

Season * Diel 9 3.89885440 0.43320604 14.57 0.0001

Diel * Depth 12 4.65341619 0.38778468 13.04 0.0001

Season * Depth 12 8.31623532 0.69301961 23.31 0.0001
429

Figure 7.34. Mean fish density (number of fish/m3) by year at Green Canyon 18 (GC18) and

Grand Isle 94 (GI94) from July 1994 to March 1997 and South Timbalier (ST54)

from August 1995 to February 1997.

Figure 7.35. Mean fish density (number of fish/m3) by season at Green Canyon 18 (GC18) and

Grand Isle 94 (GI94) from July 1994 to March 1997 and South Timbalier 54 (ST54)

from August 1995 to February 1997.
430

Figure 7.36. Mean fish density (number of fish/m 3) by time of day from Green Canyon 18

(GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997 and South

Timbalier 54 (ST54) from August 1995 to February 1997. 

Figure 7.37. Mean fish density (number of fish/m 3) by platform side from Green Canyon 18

(GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997 and South

Timbalier 54 (ST54) from August 1995 to February 1997.
431

Horizontal Density Distribution: Horizontal density of fishes varied temporally and spatially at the

platform. Spatially, horizontal fish density varied with side of the platform and distance from the

platform (Table 7.15). Fish densities were significantly higher in the 2-10 and 10-18m strata than

all others (Figure 7.38). At distances from 18-82 m, fish densities were at only half of those nearer

to the platform (Figure 7.38). Temporally, horizontal fish density varied significantly between years,

seasons, and time of day, reinforcing the temporal variation observed with the vertically oriented

transducer arrays (Table 7.15). Annual variation in horizontal density revealed highest horizontal

density in 1995 and lowest in 1997, while seasonally highest densities were found in the fall with

all other seasons not being significantly different (Table 7.15). Within a 24-hour period,

significantly higher densities were found at noon, while all other times were not significantly

different (Table 7.15). 

Horizontal fish densities were used to measure the near-field area of influence of the platform. Based

on the decrease in fish density with distance from the platform, the near-field area of influence was

estimated at 18 m (Table 7.15, Figure 7.38). Beyond 18 m, fish densities dropped off significantly,

and fish densities were not significantly different from 18 to 84 m (Figure 7.38). 

Table 7.15. RBD ANOVA (block on platform side) results of horizontal log relative fish density

(log (fish density/m3

) with platform side, year, season, time of day, distance from the

platform, and selected interactions at the ST54 petroleum platform.

Source DF SS MS F Prob > F

Model 591 67.26231465 0.11381102 32.41 0.0001

Error 4828 16.95542871 0.00351189

Corrected Total 5419 84.21774337

R-Square C.V. Root MSE LDENSITY Mean

0.798672 104.4581 0.0592612 0.0567321

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 1.93480553 0.64493518 183.64 0.0001

Year 2 0.55152158 0.27576079 78.52 0.0001

Season 3 16.74014333 5.58004778 1588.90 0.0001

Diel 3 3.26312963 1.08770988 309.72 0.0001

Distance 3 2.04846570 0.22760730 64.81 0.0001

Season * Diel 9 7.20927947 0.80103105 228.09 0.0001

Diel * Distance 27 0.93008887 0.03444774 9.81 0.0001

Season * Distance 27 3.16415321 0.11719086 33.37 0.0001

Side * Season * Diel * Distance 508 34.03828042 0.06700449 19.08 0.0001
432

Figure 7.38. Mean relative fish density (number of fish/m 3) by distance from the platform at

Green Canyon 18 (GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997

and South Timbalier 54 (ST54) from August 1995 to February 1997.

Estimated Number of Fish and Species Composition: Examination of visual survey results revealed

interesting and consistent trends in species composition with respect to depth, season, and the

dominance of a few species over the sample period (Table 7.16). A total of sixteen species were

detected by the ROV during visual surveys, but six species including Atlantic spadefish, bluefish,

blue runner, mangrove snapper, red snapper and sheepshead consistently comprised over 95% of

the fishes enumerated at the site (Table 7.16). Less commonly observed species included seasonal

migrants detected in warmer periods; barracuda, Bermuda chub, cobia and tarpon and species found

during cooler water periods; Florida pompano and red drum (Table 7.16).

During all surveys, planktivores were numerically dominant and the most common species observed

were Atlantic spadefish and blue runners (Table 7.16). These species typically constituted over 55%

of the fishes surveyed (Table 7.16), and either species was the most numerically dominant

depending on season. Blue runners were generally more abundant in the warmer surveys with the

exception of the summer of 1996 when they were absent from the survey (Table 7.16). 

Depth also played an important role in the distribution of species at ST54; consistent trends were

observed with respect to the presence of species and depth (Table 7.16). Examination of the depth
433

Table 7.16. Mean estimated number of fish by species and mean number enumerated and percent

species composition by depth strata at South Timbalier 54 for all research trips from

July 1995 to March 1997 from hydroacoustic and visual point count surveys.

Species Summer 95 Fall 95 Winter 96 Spring 96 Summer 96 Winter 96 Mean

Atlantic

Spadefish

35.4

2880.3±377.2

34.7

13305±2611.6

43.4

3796.5±617.3

27.6

1963.4±189.5

21.5

1976.5±258.9

27.5

8327.2±1320.1

33.6

5018.6±482.2

Barracuda 0.2

8.2±1.8

- -

-

- - - 0.0

5.7±0.4

Bermuda

Chub

- - - 

-

- 0.2

9.0±0.9

- 0.0

1.1±0.1

Bluefish 0.2

10.2±2.2

- 13.2

804.1±102.3

0.6

31.8±3.3

- - 2.4

381±32.3

Bluerunner 42.6

2536.9±412.1

19.9

6946.2±1360

1.1

82.1±14.7

6.6

427.0±29.3

- 22.7

6220.5±32.7

20.6

2688.7±274.8

Cobia 0.1

8.3±0.6

0.3

44.9±10.2

0.2

45.0 ± 21.3

0.1

5.1±1.0

0.3

18.0±1.7

0.2

18.0±2.9

0.2

17.4±1.9

Florida

Pompano

- - 1.6

142.6±18.6

- - - 0.3

36.0±2.8

Gray

Triggerfish

0.6

34.7±8.2

0.1

27.4±4.8

0.1

22.9±5.2

0.8

69.9±14.7

0.3

18.0±1.7

- 0.3

35.7±3.6

Jack

Crevalle

0.2

20.4±2.5

0.4

123.7±23.3

1.1

74.5±10.9

0.3

17.8±1.7

- 0.9

203.9±29.5

0.5

67.8±6.2

Lookdown 0.8

56.3±6.8

0.4

78.6±20.7

0.1

11.1±4.5

4.1

240.3±18.9

- 0.4

30.8±5.9

0.7

95.8±9.1

Mangrove

Snapper

1.1

52.8±8.4

13.6

3937.6±787.7

1.1

89.2±12.3

39.9

2411.6±321.2

49.1

2957.4±322.1

13.4

4108.5±531.0

13.1

1774.5±159.2

Red

Snapper

3.9

124.6±29.4

15.5

2560.7±392.2

14.6

1240.9±383.8

1.5

268.1±61.1

3.1

2000.5±228.7

17.9

1832.4±281.9

10.8

995.3±140.5

Red Drum - 0.1

6.4±1.1

- - - 0.4

-

0.1

6.4±1.2

Rockhind 0.1

10.2±2.4

0.1

47.2±7.3

- - - - 0.0

5.2±0.4

Sheepshead 14.8

1404.5±139.7

14.8

4831.1±921.6

23.5

1790.2±377.5

18.4

1828.6±370.6

25.3

754.7±205.9

13.7

4329.9±661.7

17.2

2326.2±229.6

Tarpon 0.0

3.0±0.3

0.1

21.8±3.4

0.1

-

- - 0.5

24.5±4.0

0.1

16.0±1.5

TOTAL 7159.2±992.7 28553.1±6141.3 8052.5±1566.1 7269.4±1013.9 9568.2±1316.5 18121.6±2818.1 13471.9±1346.7

distribution of the six most abundant species showed that Atlantic spadefish and bluefish were found

in the upper water column; mangrove snapper and sheepshead were found throughout the water

column but were most common at mid-depth; red snapper were most abundant in the lower 7 m of
434

Figure 7.39. Mean fish density (number of fish/m3) by depth at Grand Isle 94 (GI94) from July

1994 to March 1997 and South Timbalier 54 (ST54) from August 1995 to February

1997.

the water column, and only blue runner were found evenly throughout the water column (Table

7.16). Trends in depth distribution of the less common species show that barracuda, Florida

pompano and red drum were most common near the bottom while cobia, gray triggerfish, jack

crevelle, lookdown, and tarpon were observed throughout the water column (Table 7.16). 

Seasonal trends in species composition and depth distribution were also observed at ST54. During

the winter sampling trips, bluefish abundance was highest and they were found at mid-depth; blue

runners were uncommon; although overall Atlantic spadefish abundance did not change, they were

found throughout the water column in contrast to their abundance near the surface during other

sampling periods (Table 7.16). During warmer sampling periods, blue runner and mangrove snapper

were more common and generally found in the upper water column (Table 7.16). 

Extrapolating the species composition estimates with the acoustic abundance data for each depth

strata provided estimates of individual species abundance throughout the water column (Table 7.16,

Figure 7.39). By species, Atlantic spadefish or blue runners were the most abundant fish at ST54

with the exception of the spring and summer 1996 samples when mangrove snapper abundance was

slightly higher (Table 7.16). Three- to five-fold fluctuations in abundance for individual species
435

were detected between samples (Table 7.16). The species exhibiting the largest change over the

sample period was mangrove snapper, with abundances changing from approximately 80 individuals

in the summer of 1995 to approximately 4,000 in the fall, then dropping to an estimated 90 fish in

the winter of 1996 and increasing to 2,900 in the spring of 1996 (Table 7.16). Large fluctuations in

abundance by species over longer time periods were observed; an example was the presence of over

2,400 bluefish in the winter 1996 sample while at other times of the year this species was absent

(Table 7.16).

The mean abundance, with 95% confidence intervals, of fishes at ST54 by sample was variable with

a low of 7,159 (+/- 993) fish at in the summer of 1995 and a high of 28,553 (+/- 6,141) fish in the

fall of 1995 (Table 7.16). Averaged over all, the sample periods there were 13,472 (+/- 1,347) fish

at the site (Table 7.16). By depth, 58% of the fishes were found in the upper 10 m of the water

column with the lowest abundance of fish found adjacent to the substrate (Figure 7.39).

Grand Isle 94

Vertical Density Distribution: Densities of fishes at the GI94 production platform (60 m depth) were

variable over the study period ranging from 0 to over 1.1 fish/m3

. A RBD ANOVA with platform

side as a block was used to examine differences in density due to year, season, time of day, current

vectors, temperature, dissolved oxygen, depth, and selected interactions. Density varied significantly

with year, season, time of day, depth, platform side, north current vector, east squared current vector,

dissolved oxygen, and temperature (Table 7.17). 

Temporal differences in fish density were detected between year, season, and time of day (Table

7.17). Fish density was significantly different over all years examined with significantly higher

densities observed in 1997 than in all other years, although only one research trip occurred in 1997

(Figure 7.34). The lowest annual densities were found in 1996 with 1994 and 1995 having

significantly higher annual densities (Figure 7.34, Table 7.17). Seasonally, fish densities were

significantly higher in the winterfollowed by fall, then spring, and lowest in the summer (Figure

7.35, Table 7.17). Mean densities in the winter and fall were on average five to ten times higher than

in the spring and summer (Figure 7.35). While fish densities varied with time of day and were

significantly different (Table 7.17), the differences were much smaller than with any other temporal

variable examined (Figure 7.36). Highest densities were found at dawn and significantly lower

densities were detected at dusk; otherwise, densities were not significantly different (Figure 7.36).

Spatially, fish density varied with platform side and depth (Table 7.17). Significantly higher

densities were found on the north and west side than on the others (Figure 7.37). Lowest densities

were found on the east side of the platform (Table 7.17). Densities varied significantly with depth,

with lowest densities found from 5-20 m and highest near the surface and bottom (Figure 7.39).

Significantly higher densities were found immediately above the bottom (water depth 50-55 m) than

at all other depth strata (Figure 7.39). Other regions of high densities included 0-5 m and 40-60 m

(Figure 7.39).
436

Table 7.17. RBD ANOVA (block on platform side) results of vertical log fish density

(log(number of fish/m3) with platform side, year, season, time of day, depth, current

vectors, temperature, salinity, dissolved oxygen, and selected interactions at the GI94

petroleum platform.

Source DF SS MS F Prob > F

Model 719 658.51165 0.91587 9.51 0.0001

Error 7210 694.42089 0.09631

Corrected Total 7929 1352.93255

R-Square C.V. Root MSE LDENSITY Mean

0.486729 94.61222 0.3103 0.3280

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 34.43292 11.47764 119.17 0.0001

Year 3 1.11 0.37 12.17 0.0001

Season 3 88.32148 29.44049 305.67 0.0001

Diel 3 1.45685 0.48562 5.04 0.0017

Depth 11 20.22683 1.83880 19.09 0.0001

Temperature 1 3.53954 3.53954 36.75 0.0001

Dissolved oxygen 1 4.91742 4.91742 51.06 0.0001

Salinity 1 0.00003 0.00003 0.00 0.9849

North vector 1 1.32898 1.32898 13.80 0.0002

East vector 1 0.23100 0.23100 2.40 0.1215

North squared vector 1 0.42743 0.42743 4.44 0.0352

East squared vector 1 1.98548 1.98548 20.61 0.0001

North * East 1 0.10200 0.10200 1.06 0.3035

Diel * Depth 33 4.48975 0.13605 1.41 0.0590

Side * Season * Diel * Depth 658 226.51339 0.34425 3.57 0.0001

Results from the RBD ANOVA of environmental variables showed significant impact on fish

density due to temperature, dissolved oxygen, north current vector and the east current vector

squared (Table 7.17). Fish density decreased slightly with temperature although this finding is in

conflict to the highest observed overall densities, which occurred in the fall and winter when

temperatures are the lowest (Figure 7.35) and highest observed densities from 40-60 m where

temperatures were generally lowest (Figure 7.39). A positive relationship was detected between

dissolved oxygen and density as density increased with increasing dissolved oxygen levels although

hypoxic conditions were not observed at GI94. The lowest dissolved oxygen levels were found were

4.4 ppm during the fall 1994 survey. The ANOVA results indicated a positive relationship between

current speed and fish density (Table 7.17). While the relationship showed an increase in density
437

with decreasing current speed, less than 5% of the current observations exceeded 20 cm/s, with

mean current speed of 10.0 cm/s and the maximum observed current speed was 39.6 cm/s. Because

of the low number of high current speed observations it is more plausible that the high densities

observed at low current speeds were due to depth; the highest densities were found from 40-60 m

where current speeds were typically the lowest (Figure 7.39). Due to the relatively large size of the

fishes observed at the site, it is probable that the current speeds observed were not great enough to

influence the behavior of the fishes. 

Horizontal Density Distribution: Horizontal density of fishes varied temporally and spatially at the

platform (Table 7.18). Spatially,horizontal fish density varied with side of the platform and distance

from the platform while temporal variation was observed with year and season (Table 7.18). The

interactions of time of day, and distance from the platform, season and time of day and time of day

and distance from the site were also significant (Table 7.18). The spatial relationship of horizontal

density differing with side of the platform reinforced a similar relationship observed in the

significant change in fish density between sides also observed in the vertical density distributions

(Figure 7.38, Table 7.18). With respect to side, the horizontal results were similar to the vertical

density results. Highest densities were found on the north, west, and south sides for both transducer

arrays (Figure 7.37, Table 7.18). 

Table 7.18. RBD ANOVA (block on platform side) results of horizontal relative log fish density

(log(number of fish/m3

) with platform side, year, season, time of day, distance from

the platform, and selected interactions at the GI94 petroleum platform.

Source DF SS MS F Prob > F

Model 612 186.43939327 0.30463953 11.84 0.0001

Error 8327 214.25821327 0.02573054

Corrected Total 8939 400.69760654

R-Square C.V. Root MSE LDENSITY Mean

0.465287 175.7350 0.1604074 0.0912780

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 13.25275329 4.41758443 171.69 0.0001

Year 3 17.72176044 5.90725348 229.58 0.0001

Season 3 17.15944638 5.71981546 222.30 0.0001

Diel 3 0.28291537 0.09430512 3.67 0.0118

Distance 9 6.20883438 0.68987049 26.81 0.0001

Season * Diel 9 3.42185811 0.38020646 14.78 0.0001

Diel * Depth 27 2.01761618 0.07472653 2.90 0.0001

Season * Depth 27 9.13703402 0.33840867 13.15 0.0001

Side * Season * Diel * Distance 528 84.63035253 0.16028476 6.23 0.0001
438

The close association of fishes with platforms observed at shallower depths was not observed at

GI94 (Figure 7.39). Relative fish density was significantly higher from 0-58 m away from the site

than at all other distances examined (Figure 7.38). Lowest observed densities were at distances

greater than 58 m from the site and beyond 58 m fish densities were similar to those acoustically

measured in the open waters of the northen GOM (Figure 7.38). 

Temporally, variation in relative density was found with year and season. Again, the temporal

horizontal density results were similar to the vertical results with significantly higher densities found

in 1997 and 1995 as compared to 1994 and 1996 (Table 7.18, Figure 7.34). With respect to season

highest densities were found in the winter and fall for densities measured with both horizontal and

vertical transducer arrays (Table 7.18, Figure 7.36). The significant interaction terms of distance,

and season, time of day and distance and season and time of day emphasize the variability in the

density of fishes associated with the site. 

Horizontal fish densities were used to measure the near-field area of influence of the platform. The

highest horizontal densities measurements were from 0-18 m, but these densities were not significantly higher than those from 18-58 m (Figure 7.38). Despite measurement of high relative densities

from 18 to 58 m at GI94, we estimated the near-field area of influence at 18 m. While the relationship of fish density with distance from the site was difficult to resolve, we feel that a conservative

area of influence of 18 m best reflects a true population size of fishes at the site (Table 7.18, Figure

7.38). Increased water clarity and pelagic species composition at GI94 likely increased distance the

fishes ranged from the site. However, based on the visual data from the ROV, 18 m best reflects the

distance fishes typically ranged from the site based on the visual observation. Beyond 58 m relative

fish densities measured at GI94 decreased dramatically to levels found at other sites (Figure 7.38).

Estimated Number of Fish and Species Composition: Examination of visual survey results

demonstrated interesting trends in species composition with respect to depth, season, and the

dominance of one species over the sample period (Table 7.19). A total of twenty-four species were

detected by the ROV during visual surveys, but one species, blue runner, comprised on average 87%

of all observed fishes (Table 7.19). By grouping blue runners with the next five most abundant

species, horseeye jack, red snapper, mangrove snapper gray triggerfish, and barracuda, over 95%

of the fishes observed at the site were accounted for (Table 7.19). 

Seasonality in the abundance of fishes was detected at GI94 with cobia, red snapper, almaco jack

and amberjack more common in the spring and summer than during cooler periods (Table 7.19).

During fall and winter we found an increase in the abundance of barracuda and blue runner (Table

7.19). Blue runners exhibited the most dramatic seasonality. Few were found during summer

samples when they constituted <30% of the fishes observed, however during fall, winter, and spring

samples, blue runners were the dominant fish observed and composed 71% to 94% of the fishes

found at the site (Table 7.19). While most other species were found at a relatively narrow depth

range, blue runners were found throughout the water column, although they were slightly more

abundant near the surface. Fishes with higher abundance from mid-depth to the bottom included

greater amberjack, red snapper and scamp. Surface-oriented species included bar jack, Bermuda

chub and rainbow runner while species found throughout the water column included almaco jack,

barracuda, gray triggerfish, horseeye jack, jack crevelle, and mangrove snapper.
Table 7.19. Mean estimated number of fish by species and mean number enumerated and percent species comp

by depth strata at Grand Isle 94 for all research trips from July 1994 to March 1997 from hydroacouvisual point count surveys.

 Species Summer 94 Fall 94 Winter 95 Summer 95 Fall 95 Winter 96 Spring 96 Summer 96 Fall 96 Winter 97 

Almaco Jack 0.1

7.7±1.6

0.2

55.8±7.9

0.1

58.5±5.2

1.4

119.0±16.4

0.5

219.8±35.2

0.2

43.4±3.6

0.0

0.0±0.0

0.6

27.7±8.3

0.2

87.9±14.1

0.1

67.0±4.7

AtlanticSpadefish

- - 0.0

0.0±0.0

- - 0.5

108.5±8.9

0.1

2.38±0.7

- 0.6

263.8±42.3

- 

GreaterAmberjack

4.3

331.7±69.0

5.4

1507.0±214.6

0.1

58.5±5.2

0.7

59.5±8.2

0.8

351.7±56.4

3.0

651.0±53.4

0.7

16.7±5.2

0.6

27.7±8.3

2.4

1055.1±169.1

0.6

402.2±28.2

Bar Jack 0.8

61.7±12.8

0.4

111.6±15.9

0.1

58.5±5.2

2.1

178.5±24.5

- - - - - - 

Barracuda 0.6

46.3±9.6

3.9

1088.4±155.0

0.4

234.0±20.7

1.1

93.5±12.9

2.9

1274.9±204.3

0.6

130.2±10.7

0.2

4.8±1.5

1.5

69.4±20.9

4.6

2022.3±324.0

1.0

670.2±47.0

BermudaChub

3.8

293.1±61.0

8.1

2260.5±322

0.1

58.5±5.2

- 1.2

527.6±84.5

0.2

43.4±3.6

0.1

2.4±0.7

1.5

69.4±20.9

- 0.7

469.2±32.9

Bigeye - - 0.0

0.0±0.0

- - - - - - - 

BlackGrouper

- - 0.0

0.0±0.0

- - - - - - - 

Bluerunner 44.9

3463.2±720.4

27.6

7702.6±1097.0

94.3

55161.5±4879.3

79.5

6757.4±929.1

71.0

3121.3±5001.5

85.0

18446.2±1512.8

94.2

2242.0±697.6

71.9

3324.5±999.5

71.9

31609.0±5064.9

93.0

62334.8±4367

Cobia 0.1

7.7±1.6

- - - - - 0.0

0.0±0.0

0.2

9.2±2.8

- - 

ConeyGrouper

- - - - - - -- - - 

Creolefish 0.1

7.7±1.6

1.7

474.4±67.6

0.0

0.0±0.0

2.1

178.5±24.5

0.1

44.0±7.0

0.0

0.0±0.0

- ` 0.2

87.9±14.1

0.1

67.0±4.7

Gag - - - - - - - - - 0.0

0.0±0.0
Table 7.16 (continued)

 Species Summer 94 Fall 94 Winter 95 Summer 95 Fall 95 Winter 96 Spring 96 Summer 96 Fall 96 Winter 97 

GrayTriggerfish

2.2

169.7±35.3

12.0

3349.0±477.0

1.7

994.4±88.0

6.1

518.5±71.3

0.5

219.8±35.2

0.4

86.8±7.1

0.1

2.4±0.7

0.2

9.2±2.8

1.0

439.6±70.4

0.1

67.0±4.7

HorseyeJack

0.2

15.4±3.2

9.0

2511.7±357.7

- 0.2

17.0±2.3

13.4

5891.0±943.9

2.9

629.3±51.6

3.1

73.8±23.0

7.9

365.3±109.8

11.9

5231.5±838.3

1.4

938.4±65.7

JackCrevalle

1.6

123.4±25.7

7.3

2037.3±290.2

- 0.9

76.5±10.5

0.8

351.7±56.4

0.2

43.4±3.6

0.2

4.8±1.5

8.3

383.8±115.4

2.5

1099.1±176.1

0.2

134.1±9.4

Lookdown 4.1

316.2±65.8

- 0.8

468.0±41.4

- 1.1

483.6±77.5

- 0.4

9.5±3.0

2.3

106.3±32.0

- - 

MangroveSnapper

3.1

239.1±49.7

4.5

1255.9±178.9

0.5

292.5±25.9

1.4

119.0±16.4

2.4

1055.1±169.1

0.3

65.1±5.3

0.2

4.8±1.5

4.4

203.4±61.2

1.7

747.4±119.8

1.3

871.3±61.0

OceanTriggerfish

- - - 0.9

76.5±10.5

- - - - - - 

RainbowRunner

- - 0.0

0.0±0.0

- 0.1

44.0±7.0

0.1

21.7±1.8

- - - - 

RedSnapper

33.2

2560.8±532.7

15.8

4409.5±628.0

1.1

643.5±56.9

3.4

289.0±39.7

4.7

2066.2±331.1

4.9

1063.4±87.2

0.3

7.1±2.2

0.2

9.2±2.8

2.7

1187.0±190.2

1.4

938.4±65.7

Scamp 0.8

61.7±12.8

4.1

1144.2±163.0

0.5

292.5±25.9

0.2

17.0±2.3

0.6

263.8±42.3

1.6

347.2±28.5

0.1

2.4±0.7

0.1

4.6±1.4

0.3

131.9±21.1

0.1

67.0±4.7

VermillionSnapper

- - 0.2

117.0±10.3.00

- - - - - - - 

YellowfinGrouper

- - 0.0

0.0±0.0

- - - - - - - 

TOTAL 7713.2±160.4 27908.0±3974.7 58495.8±5174.2 8499.9±1168.7 43962.5±7044.3 21701.4±1779.8 2380.0±740.5 4623.8±225.2 43962.5±7044.3 67026.7±4696
441

Figure 7.40. Estimated number of fishes for each quarterly sample period at Green Canyon 18

(GC18) and Grand Isle 94 (GI94) from July 1994 to March 1997 and South

Timbalier (ST54) from August 1995 to February 1997.

Extrapolating the species composition estimates with the acoustic abundance data for each depth

strata provided estimates of individual species abundance throughout the water column (Table 7.19).

The total number of fish at the GI94 ranged from a low of 2,380 (+/- 740, 95% confidence interval,

Table 7.19, Figure 7.40) during the spring 1996 sample period to a high of 67,027 (+/- 4,696, Table

7.19, Figure 7.40) during the winter 1997 period with a mean of 28,952 (+/- 1,806) fishes averaged

over all the sample periods. The seven most abundant species (highest to lowest) were blue runner,

red snapper, horseeye jack, mangrove snapper, greater amberjack, barracuda, and grey triggerfish

(Table 7.19). Blue runner dominated the number of fishes observed at the site with an average of

25,188 (+/- 1,571, 95% confidence interval). Their abundance was highly variable with a low of

2,242 (+/- 698) observed in the spring 1996 sample (Table 7.19) to a high of 62,335 (+/-4,367) from

the winter 1997 sample (Table 7.19). The estimated number of blue runner was also variable with

a five- to six-fold change in abundance observed from the fall of 1994 to spring 1995 (Table 7.19).

Generally, their abundance would peak in fall or winter and then drop during other surveys (Table

7.19).
442

The abundance of greater amberjack, horseeye jack, mangrove snapper, and red snapper was

typically highest in fall and winter and lower during spring and summer samples (Table 7.19),

although the second highest number of red snapper observed over the study period was found during

the summer 1994 research trip. Significant changes in the abundance of other individual species

were also noted. Three- to five-fold differences in estimated abundance between sample periods

were common for greater amberjack, horseeye jack, mangrove snapper, and red snapper (Table

7.19). 

Green Canyon 18

Vertical Density Distribution: Densities of fishes at the GC18 production platform (water depth 219

m) were variable over the study period ranging from 0 to over 1.44 fish/m3. A RBD ANOVA with

platform side as a block was used to examine for differences in density due to year, season, time of

day, current vectors, temperature, dissolved oxygen, depth, and selected interactions. Density varied

significantly with platform side, season, depth, north current vector squared, and the interactions of

time of day and depth and season and depth (Table 7.20).

The only significant temporal differences in fish density were detected with season and the

interaction between depth and time of day (Table 7.20). Seasonally, fish densities were significantly

higher in the winter and summer than the fall and spring (Figure 7.35, Table 7.20). Mean densities

in the winter and summer were on average two to five times higher than in the spring and fall

(Figure 7.35). Other differences observed in temporal variables examined (e.g., year and time of

day) were not significant (Figures 3 and 5, Table 7.20). 

Spatially, fish density varied with platform side and depth (Table 7.20). Significantly higher

densities were found on the west side of the platform than at all others, and densities were not

significantly different on the north and south sides (Figure 7.37). Densities on the east side were five

to eight times lower than those on other sides of the platform (Table 7.20, Figure 7.37). The most

dramatic results of the research project was the relationship between fish density and depth at GC18.

A significant and spectacular drop in density with depth was observed at GC18 below 100 m (Table

7.20, Figure 7.41 ). Fish densities from 0-15 m were significantly higher than all other depth strata

and were 4 to 68 times higher than all other depths (Figure 7.41). Densities from 15 to 95 m were

not significantly different but were 3 to 12 times higher than depths from 115 to 210 m (Figure

7.41). From 115 to 210 m fish density was less than 0.002 fish/m3

, essentially zero, and lower than

densities in the open waters of the GOM on the continental shelf (Figure 7.41). 

Environmental conditions did little to impact fish density at GC18 based on results from the RBD

ANOVA (Table 7.20). Fish density was significantly affected only by the north current vector

squared, although temperature and dissolved oxygen were close to significant with a probability of

a greater F of 0.0206 and 0.0283, respectively (Table 7.20). There was an inverse relationship

between fish density and north vector squared as fish density decreased slightly as north vector

squared increased. This decrease is likely due to observations from the summer 1995 sample when

relatively high-current speeds with a northerly component were found. The close to significant

relationship between density and temperature is likely correlated to the significant seasonal
443

Table 7.20. RBD ANOVA (block on platform side) results of vertical log fish density

(log(number of fish/m3) with platform side, year, season, time of day, depth, current

vectors, temperature, salinity, dissolved oxygen, and selected interactions at the

GC18 petroleum platform.

Source DF SS MS F Prob > F

Model 90 2.0053289 0.0222814 20.93 0.0001

Error 5985 6.3729412 0.0010648

Corrected Total 6075 8.3782700

R-Square C.V. Root MSE LDENSITY Mean

0.476178 252.0003 0.0284 0.0113

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 0.2220276 0.0740092 69.50 0.0001

Year 3 0.0115176 0.0382392 3.61 0.0128

Season 3 0.0352252 0.0117751 11.06 0.0001

Diel 3 0.0030421 0.0010140 1.25 0.2884

Depth 10 0.3454644 0.0354464 33.29 0.0001

Temperature 1 0.0051256 0.0051256 4.81 0.0283

Dissolved oxygen 1 0.0051131 0.0051131 5.37 0.0206

Salinity 1 0.0010461 0.0010461 0.98 0.3216

North vector 1 0.0011174 0.0011174 1.05 0.3057

East vector 1 0.0007499 0.0007499 0.07 0.4014

North squared vector 1 0.0079050 0.0079050 7.42 0.0065

East squared vector 1 0.0005933 0.0005933 0.56 0.4554

North * East 1 0.0035980 0.0035680 3.38 0.0661

Diel * Depth 30 0.1210778 0.0040359 3.79 0.0001

Season * Depth 30 0.3375548 0.0112518 10.57 0.0001

relationship documented earlier (Table 7.20, Figure 7.35) with highest densities found in the winter,

although this relationship is confounded by the low densities at depths where temperatures were

lowest (Figure 7.41). The observation of declining density with low dissolved oxygen levels is

probably due to the low fish densities observed below 95 m where dissolved oxygen levels were

lowest (Table 7.20, Figure 7.41). However, no hypoxic events where detected at GC18.
444

Figure 7.41. Mean fish density (number of fish/m3) by depth at Green Canyon 18 from October

1994 to March 1997.

Horizontal Density Distribution: Horizontal density of fishes varied temporally and spatially at the

platform (Table 7.21). Spatially, horizontal fish density varied with side of the platform and distance

from the platform. Temporal variation was observed with season, time of day, and the interactions

of time of day and distance from the platform (Table 7.21). The differences in fish density with side

of the platform observed with the horizontally-oriented transducers reinforces the observed variation

in fish density with platform side from the vertically oriented arrays (Figure 7.37, Table 7.21). The

close spatial association of fishes with platforms at sites on the continental shelf (e.g., ST54) was

more evident at GC18 than GI94 (Figure 7.38). Fish density was significantly higher from 2-10 m

away from the site than at all other distances examined (Figure 7.38). Densities from 10-42 m were

not significantly different from each other, and lowest observed densities were from 50-82 m from

the site (Figure 7.38). 

Temporally, the variation in horizontal fish density found with respect to season is similar to the

variation in fish density with season observed from the vertical density arrays (Table 7.21). Diel

variation was observed in the horizontal density of fish with highest densities found at noon (Table

7.21). This was the only case during this research project where diel variation was observed, and

because it was not observed with the vertical transducer array, it is presumably due to off-site

behavior of fishes in the upper water column since the maximum deployment depth of the horizontal

transducers was 13 m and would not reflect behavior of fishes throughout the water column. 
445

Table 7.21. RBD ANOVA (block on platform side) results of horizontal log relative fish density

(log(number of fish/m3) with platform side, year, season, time of day, distance from

the platform, and selected interactions at the GC18 petroleum platform.

Source DF SS MS F Prob > F

Model 1159 84.788167 0.073156 5.68 0.0001

Error 4870 62.705195 0.012876

Corrected Total 6029 147.493362

R-Square C.V. Root MSE LDENSITY Mean

0.574861 180.3045 0.1135 0.0629

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 21.033569 7.011190 544.52 0.0001

Year 3 0.080941 0.026980 2.10 0.0986

Season 3 3.245408 1.081803 84.02 0.0001

Diel 3 1.460569 0.486856 37.81 0.0001

Depth 9 0.166086 0.018454 1.43 0.1676

Diel * Depth 27 1.195570 0.044280 3.44 0.0001

Year * Season 1 0.35030 0.035030 2.72 0.0991

Side * Year * Season * 

Diel * Depth

1110 50.150390 0.045181 3.51 0.0001

Horizontal densities were used to measure the near-field area of influence of the platform. Densities

were significantly higher within 10 m of the site, and while densities from 10-42 m were high, we

feel that a conservative area of influence of 10 m best reflects a true population size of the fishes at

the site (Table 7.21, Figure 7.38). Beyond 50 m the relative fish densities measured at GC18

decreased dramatically to levels found in the open shelf waters of the GOM (Figure 7.38).

Estimated Number of Fish and Species Composition: Examination of visual survey results revealed

a fairly stable species assemblage at the site with interesting and consistent trends in species

composition with respect to depth, season, and the dominance of a few species over the sample

period (Table 7.22). A total of eighteen species were detected by the ROV during visual surveys but

six species including creolefish, blue runner, Bermuda chub, almaco jack, amberjack, and barracuda

consistently comprised over 90% of the fishes enumerated at the site (Table 7.22). Other species

observed included bar jack, black jack, blackfin tuna, grey triggerfish, horseeye jack, lesser

amberjack, marbled grouper, ocean triggerfish, rainbow runner, scamp and yellowtail snapper. Due

to their scarcity, it is difficult to discern any seasonal patterns (Table 7.22). 

Creolefish was the most common species enumerated at GC18 ranging from a maximum of 67%

of the fishes detected in the summer of 1995 (Table 7.22) to a minimum of 40% in the winter of
Table 7.22. Mean estimated number of fish by species and mean number enumerated and percent species compos

by depth strata at Green Canyon 18 for all research trips from August 1994 to March 1997 hydroacoustic and visual pointcount surveys.

 Species Summer 94 Fall 94 Winter 95 Summer 95 Fall 95 Winter 96 Spring 96 Summer 96 Fall 96 Almaco Jack 18.1

476.5±51.4

2.8

506.0±201

5.7

1069.7±222.9

3.8

308.7±226.1

5.0

1618.6±510.9

3.5

2383.3±691

6.2

2913.3±1321.4

2.9

119.7±58.2

8.3

275.6±63.8

6

Bar Jack 5.5

111.9±77.6

4.8

249.4±106.8

6.4

809.2±138.4

0.9

176.6±23.1

2.0

163.3±33.7

1.6

146.4±25.3

0.2

3.5±1

0.5

60±10

0.3

75. ±1.1

Barracuda 2.9

676.1±86.5

2.0

707.9±218

6.1

554.9±112.1

1.2

334.3±37.5

2.4

176.1±38.9

2.8

252.8±44.3

3.3

102.6±36

1.6

397.3±67.5

6.8

699.9±186.1

Bermuda Chub 4.1

2165.5±206.9

2.8

2193.8±460.8

8.7

1335.3±202.4

4.9

2598±260.6

10.1

1104.4±172.6

11.4

955.2±178.7

6.0

182.3±60.9

4.3

1143.4±187.7

7.4

811±132.5

Black Jack 0.1

-

2.7

135.8±59.7

0.4

42.5±9.5

0.3

7.4±3.4

0.4

32.2±7

- 0.2

34.7±12.9

0.3

8.2±2.5

2.4

121.1±40.6

Blackfin Tuna 8.6

-

- 5.1

705.1±182.2

- - - - - - 

Bluerunner 16.5

8981.9±858

- 4.7

193.7±59.3

15.4

3342.9±387.8

14.3

1311.7±244.2

22.0

1971.3±349.4

33.0

1056.6±388.4

37.3

4289±926.9

16.9

1850.6±302.3

3

Creolefish 31.7

2314.4±308.4

63.9

11424.3±3030.1

39.9

3715.3±885.3

67.3

5464.5±894.9

59.4

4559.9±1059.5

52.1

8034.1±1253.8

43.0

2608.8±965.6

44.8

6065.6±1202.4

45.4

4067.7±1080.2

62

Gray Triggerfish 0.7

60.7±7.3

1.7

86.5±37.6

1.1

211.9±44.6

0.5

7.7±3.5

1.5

103.9±20

0.6

138.2±33.8

0.1

62.1±34.7

0.6

17.8±5.5

0.3

7.5±1.1

4

Greater Amberjack 7.6

1.4±0.6

12.2

471.6±248.4

7.5

2342.5±618

1.9

100.2±69.9

2.1

295.2±103.3

1.1

571.5±155.5

2.1

1020.9±513.5

4.2

483.3±330.4

6.2

368.2±133.7

2

Horseye Jack 4.0

145.4±66.2

4.6

625.3±186.1

8.6

702.7±139.3

2.9

780.2±84.8

1.6

83.2±19.1

1.1

92.6±16.7

5.4

188.9±70.8

2.3

350.7±78

2.1

253±67.2

7
Table 7.22 (continued) Species Summer 94 Fall 94 Winter 95 Summer 95 Fall 95 Winter 96 Spring 96 Summer 96 Fall 96 Lesser Amberjack - - - - 0.3

21.8±3.3

- - - - 

Marbled Grouper - - - - - - - 0.0

1.2±0.4

- 

Ocean Triggerfish - - - - - 0.2

23.1±3.8

- 0.1

19.6±3.2

- 

Rainbow Runner 0.3

7.5±5.2

- 0.2

28.9±4.4

0.4

10.2±4.7

0.2

17.7±27.8

3.1

153.2±42.7

0.2

3.5±1

0.2

70.3±10.4

0.6

64.7±10.6

Scamp 0.1

-

1.4

122.4±30.8

3.4

494.2±123.5

0.4

41.2±31

0.7

705.5±38.3

0.5

231.3±61.1

0.4

143.9±63.4

0.7

19.1±5.9

3.0

136.1±42.9

Unidentified Grouper - - - - --

43.9±10

---

36.7±16.6

Yellowtail Snapper - 1.1

421.1±104.5

2.0

182.7±35.5

- - - - - - 

TOTAL 14941.3±1668.1 16944.1±4683.8 12388.6±2777.4 13171.9±2027.3 10193.5±2278.6 14996±2866.1 8321.1±3469.6 13045.2±2889 8699.5±2078.7 21
448

1995 (Table 7.22); on average, they made up 50% of the fishes observed (Table 7.22). With respect

to depth, creolefish were concentrated in the mid- to upper-water column with approximately 90%

of the individuals found above 60 m (Table 7.22). Seasonally, no consistent trends in creolefish

abundance were found although their numbers tended to increase during fall and winter surveys

(Table 7.22). The next most common species detected was usually blue runner (Table 7.22) making

up an average of 20.5% of the fishes (Table 7.22). However, during the fall 1994, sample blue

runners were absent(Table 7.22) and during the winter 1995 survey, they made up less than 5% of

the fishes observed (Table 7.22). After creolefish and blue runner, no other species observed made

up more than 10% of the fishes at GC18. The next most commonly observed species were Bermuda

chub, almaco jack, greater amberjack, and barracuda (Table 7.22). While Bermuda chub typically

were the third most abundant species observed, there was a large amount of fluctuation in the fourth

through sixth positions (Table 7.22). Within these species it was difficult to discern any seasonal

patterns with the exception of barracuda, as their presence increased during cooler periods (Table

7.22). With respect to depth, barracuda and Bermuda chub were predominately found above 40 m

(Table 7.22). Almaco jack were found from the surface to 160 m but approximately 90% of these

fishes were found from 40 to 100 m (Table 7.22). Greater amberjack were almost exclusively found

from 40 to 100 m with few observed outside of this depth range (Table 7.22).

The ROV survey results below 100 m supported the acoustic findings with almost a complete lack

of fishes (a total of 38 fishes of 4 species) were observed in eleven surveys below 100 m. Almaco

jacks showed the widest depth range of any of the fishes observed at GC18, as they were common

from the surface to mid-depth and one of the few fishes found below 100 m. Typically, most species

exhibited a specific depth range and were less frequently found outside that range. Surface oriented

species included bar jack, barracuda, Bermuda chub, blue runner and horseeye jack. Species

common from 20 to 60 m included black jack, blackfin tuna, creolefish, grey triggerfish, rainbow

runner and yellowtail snapper. Species commonly found from 60 to 100 m were almaco jack, greater

amberjack and scamp, although, as previously mentioned, almaco jack had the widest depth range

of any of the observed species.

Extrapolating the acoustic abundance data using the species composition estimates for each depth

strata provided estimates of individual species abundance throughout the water column (Table 7.22).

The total number of fish at the site ranged from a low of 8,321 (+/- 3,470, 95% CI, Table 7.22)

during the spring 1996 sample to a high of 21,767 (+/- 4,655, Table 7.22) during the winter 1997

sample. Averaged over all sample periods 13,855 (+/- 1,206) fishes were found at GC18 and the six

most abundant species (highest to lowest) were creolefish, blue runner, Bermuda chub, almaco jack,

greater amberjack, and barracuda (Table 7.22). Creolefish dominated the observed fishes at the site.

An average of 4,924 (+/- 445) were estimated at GC18 over the study period, which was twice as

abundant as any other species on average (Table 7.22). The next most abundant species was blue

runner (Table 7.22). As with the other sites, the abundance of blue runner was variable over the

study period ranging from a high of 8,962 in the summer 1994 (Table 7.22) to a low of 0 during the

Fall 1994 survey (Table 7.22). After the initial variability during the summer and fall 1994 surveys,

blue runner abundance appeared to level off and the earlier heterogeneity decreased (Table 7.22).

Examination of the abundance of other dominant species over the study period showed large

changes in the abundance of amberjack, almaco jack and Bermuda chub between sample periods
449

(Table 7.22). The only dominant species that did not undergo extreme changes in abundance over

time was barracuda; however a two-fold decrease in abundance was observed from spring 1996 to

summer 1996 samples (Table 7.22). With respect to a seasonal pattern in abundance, highest

numbers of amberjack and almaco jack were consistently found in the fall and winter surveys while

Bermuda chub estimates were highest during spring and summer surveys (Table 7.22). Barracuda

estimates, as pointed out earlier, were much more stable than the other dominant species, but their

abundance was typically higher in the cooler sampling periods (Table 7.22). 

South Timbalier 54

Target Strength Distribution: The target strengths of the fishes at the ST54 production platform were

variable over the study period and a RBD ANOVA with platform side as a block was used to test

for differences in target strength due to year, season, time of day, current vectors, temperature,

dissolved oxygen, depth, and selected interactions. Target strength varied significantly with season,

time of day, depth, platform side, temperature, east current vector, north current vector, north

squared current vector, east squared current vector, and the interaction terms (Table 7.23). 

Temporal differences in target strength were detected between season, time of day, and the

interaction of season and time of day (Table 7.23). Seasonally, target strengths were significantly

larger in summer, decreased in spring and winter and lowest in the fall (Table 7.24). Two groupings

of target strength with time of day were found with largest target strengths in the dawn and noon

samples and significantly smaller target strengths in dusk and midnight samples (Table 7.25). No

overall trend of target strength with season and time of day could be detected over the entire study

period. 

Spatially, target strength varied with platform side, depth, and the interactions of depth and time of

day and depth and season. Target strengths were significantly different on all sides of the platform

(Table 7.26). Significantly larger target strengths were found on the south side of the platform and

smallest on the west (Table 7.26). With respect to depth, target strengths were larger near the surface

and above the substrate than at mid-depth and immediately adjacent to the bottom (Table 7.27).

While the interactions of depth and time of day and season and depth were significant (Table 7.23),

no consistent trends were observed in these interactions. 

Environmental variables that significantly affected target strength included temperature, northeast

current vector, north squared, and east squared current vectors (Table 7.23). The relationship

between temperature and target strength showed a slight increase in target strengths as temperature

increased. Target strength also increased with north and east current vector and north and east

squared vectors suggesting that at high current speeds, larger fishes were more common. 

Grand Isle 94

Target Strength Distribution: Target strengths of fishes at the GI94 production platform were

variable over the study period and a RBD ANOVA with platform side as a block was used to

examine differences in target strength due to year, season, time of day, current vectors, temperature,

dissolved oxygen, depth, and selected interactions. Target strength varied significantly with year,
450

Table 7.23. RBD ANOVA (block on platform side) results of vertical target strength (dB) with

platform side, year, season, time of day, depth, current vectors, temperature, salinity,

dissolved oxygen, and selected interactions at the ST54 petroleum platform.

Source DF SS MS F Prob > F

Model 206 56386.345015 273.720121 34.40 0.0001

Error 1198 9532.903189 7.957348

Corrected Total 1404 65919.248205

R-Square C.V. Root MSE MEANTS Mean

0.855385 -7.065331 2.8208772 -39.925621

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 6671.413209 2223.804403 279.47 0.0001

Year 1 40.001821 40.001821 5.03 0.0251

Season 2 603.144775 301.572388 37.90 0.0001

Diel 3 367.667924 122.555975 15.40 0.0001

Depth 4 2717.156715 679.289179 85.37 0.0001

Temperature 1 136.785653 136.785653 17.19 0.0001

Dissolved oxygen 1 14.260933 14.260933 1.79 0.1809

Salinity 1 26.135930 26.135930 3.28 0.0702

North vector 1 386.735952 386.735952 48.60 0.0001

East vector 1 70.694892 70.694892 8.88 0.0029

North squared vector 1 203.938224 203.938224 25.63 0.0001

East squared vector 1 352.882525 352.882525 44.35 0.0001

North * East 1 14.301287 14.301287 1.80 0.1803

Season * Diel 6 841.199710 140.199952 17.62 0.0001

Diel * Depth 12 1487.257674 123.938140 15.58 0.0001

Season * Depth 7 2822.349465 403.192781 50.67 0.0001
451

Table 7.24. Mean target strengths (dB), with Tukey’s studentized means test results by season

at South Timbalier 54.

Season Mean Target Strength Tukey’s Means Test

Summer -36.9 A

Spring -39.5 B

Winter -44.8 C

Fall -46.4 D

Table 7.25. Mean target strengths (dB) with Tukey’s studentized means test results by time of

day at South Timbalier 54.

Time of Day Mean Target Strength Tukey’s Means Test

Dawn -39.9 A

Noon -40.1 A

Midnight -42.1 B

Dusk -42.2 B

Table 7.26. Mean target strengths (dB) with Tukey’s studentized means test result by platform

side at South Timbalier 54.

Platform Side Mean Target Strength Tukey’s Means Test

South -38.5 A

East -40.9 B

North -41.6 C

West -43.2 D
452

Table 7.27. Mean target strength (dB) with Tukey’s studentized means test by water depth (m)

at South Timbalier 54.

Depth (m) Mean Target Strength Tukey’s Means Test

5-10 -39.7 A

15-20 -39.8 A

0-5 -40.2 A

10-15 -42.3 B

20-22 -46.2 C

season, time of day, depth, platform side, north current vector, east squared current vector, north

current vector squared, north*east interaction, dissolved oxygen, temperature, season*time of day,

time of day*depth, and season*depth (Table 7.28).

Temporal differences in target strength were detected between year, season, time of day, the

interactions of season*time of day, time of day*depth, and season*depth (Table 7.28). Target

strength was significantly different between three of the four years examined with significantly

larger target strengths found in 1995 than all other years (Table 7.29). Target strengths from 1994

and 1996 were not significantly different from one another and the smallest target strengths were

found in 1997 (Table 7.29). Target strengths were also were significantly different with season

(Table 7.30). Largest target strengths were found in the winter, followed by the spring and summer

and smallest target strengths were found in fall (Table 7.30). While target strengths were

significantly different with time of day, the contrasts were much smaller than in any other temporal

variable examined (Table 7.31). Largest target strengths were found at midnight and dusk; dusk and

noon samples were not significantly different from each other, and noon and dawn samples were not

significantly different (Table 7.31). 

Spatially, fish density varied with platform side and depth (Table 7.28). Target strength varied

significantly on each side of the platform (Table 7.32). Largest target strengths were found on the

south side, followed by the west and north with smallest target strengths on the east side (Table

7.32). Target strength varied significantly with depth and the largest target strengths were found

from 40 to 60 m and from 0 to 5 m (Table 7.33). Intermediate target strengths were detected in the

middle of the water column from 5 to 35 m, while smallest target strengths were found from 15 to

25 m (Table 7.33). 

Environmental conditions also impacted target strengths based on results from the RBD ANOVA

(Table 7.28). Target strengths were significantly affected by temperature, dissolved oxygen, north

current vector, north squared, and east squared current vector (Table 7.28). Target strengths

decreased slightly with temperature indicating larger fishes were found during fall and winter.

Increases in dissolved oxygen, slightly increased target strengths. Target strengths increased with
453

Table 7.28. RBD ANOVA (block on platform side) results of vertical target strength (dB) with

platform side, year, season, time of day, depth, current vectors, temperature, salinity,

dissolved oxygen, and selected interactions at the GI94 petroleum platform.

Source DF SS MS F Prob > F

Model 670 156624.55 233.77 19.54 0.0001

Error 6954 83185.95 11.96

Corrected Total 7624 239810.49

R-Square C.V. Root MSE MEANTS Mean

0.653118 -7.857822 3.4587 -37.015

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 7030.663 2343.554 195.91 0.0001

Year 3 15542.064 5180.688 433.08 0.0001

Season 3 24760.063 8253.354 689.95 0.0001

Diel 3 385.026 128.342 10.73 0.0001

Depth 11 5357.266 487.024 40.71 0.0001

Temperature 1 6116.911 6116.911 511.35 0.0001

Dissolved oxygen 1 2419.286 2419.286 202.24 0.0001

Salinity 1 49.542 49.542 4.14 0.0419

North vector 1 377.012 377.012 31.52 0.0001

East vector 1 7.174 7.174 0.60 0.4387

North squared vector 1 491.833 491.833 41.12 0.0001

East squared vector 1 959.615 959.615 80.22 0.0001

North * East 1 453.694 453.694 37.93 0.0001

Season * Diel 9 801.514 89.057 7.44 0.0001

Diel * Depth 33 2909.926 88.180 7.37 0.0001

Season * Depth 31 6949.762 224.186 18.74 0.0001

Table 7.29. Mean target strength (dB) with Tukey’s studentized means test by year at Grand

Isle 94.

Year Mean Target Strength Tukey’s Means Test

1995 -34.7 A

1994 -36.4 B

1996 -36.9 B

1997 -39.4 C
454

Table 7.30. Mean target strength (dB) with Tukey’s studentized means test by season at Grand

Isle 94.

Season Mean Target Strength Tukey’s Means Test

Winter -32.4 A

Spring -34.7 B

Summer -36.5 C

Fall -38.6 D

Table 7.31. Mean target strength (dB) with Tukey’s studentized means test by time of day at

Grand Isle 94.

Time of Day Mean Target Strength Tukey’s Means Test

Midnight -35.7 A

Dusk -36.0 B

Noon -36.1 B

Dawn -36.3 B

Table 7.32. Mean target strength (dB) with Tukey’s studentized means test by platform side at

Grand Isle 94.

Platform Side Mean Target Strength Tukey’s Means Test

South -34.3 A

West -35.3 B

North -36.7 C

East -37.6 D
455

Table 7.33. Mean target strength (dB) with Tukey’s studentized means test by water depth (m)

at Grand Isle 94.

Depth (m) Mean Target Strength Tukey’s Means Test

50-55 -34.1 A

40-45 -34.6 A B

55-60 -34.9 B

0-5 -35.0 B

45-50 -35.2 B

5-10 -35.3 B C

10-15 -36.0 C D

35-40 -36.3 D E

30-35 -36.9 E F

25-30 -37.2 F

15-20 -38.0 G

20-25 -38.4 G

the north current vector but decreased with north and east squared current vectors. These results

show an increase in fish size with current speed; however, at excessive current speeds when currents

over 40 cm/s were common, it is likely that fish size increased along with density.

Green Canyon 18

Target Strength Distribution: Target strength of fishes at the GC18 production platform varied over

the study period and a RBD ANOVA with platform side as a block was used to examine for

differences in target strength due to year, season, time of day, current vectors, temperature, dissolved

oxygen, depth, and selected interactions. Target strength was significantly different with platform

side, time of day, depth, north current vector, north current vector squared, and the interaction of

time of day and depth (Table 7.34). 

Temporal differences in target strength at GC18 were found with time of day and the interaction of

time of day and depth (Table 7.34). Largest target strengths occurred at dawn, target strengths at

dusk and noon were not significantly different, and smallest target strengths were found at midnight

(Table 7.35). While the differences in target strengths were significant with respect to time of day

the difference in dB was 1.5 dB or approximately 3.5 cm based on estimated fish lengths (Love

1971). With interaction of time of day and depth, no consistent trends were found except that the

largest target strengths were found near the surface at all times. 

Spatially, target strength varied with platform side and depth (Table 7.36). Significantly larger target

strengths were found on the south side of the platform, with the west side second and the east and

north sides smallest and not significantly different from each other (Table 7.36). The target strength

differences between largest and smallest platform side at GC18 was the greatest observed at any of
456

Table 7.34. RBD ANOVA (block on platform side) results of vertical target strength (dB) with

platform side, year, season, time of day, depth, current vectors, temperature, salinity,

dissolved oxygen, and selected interactions at the GC18 petroleum platform.

Source DF SS MS F Prob > F

Model 314 28349.978141 90.286555 12.56 0.0001

Error 3050 21933.357355 7.191265

Corrected Total 3364 50283.335496

R-Square C.V. Root MSE MEANTS Mean

0.563805 -5.393938 2.6816534 -35.716060

Variables DF Type III SS Mean Square F Value Pr > F

Side 3 7498.586156 2499.528719 347.58 0.0001

Year 3 13.604398 4.534799 0.63 0.5952

Season 3 46.340784 15.446928 2.15 0.0921

Diel 3 1059.419025 353.139675 49.11 0.0001

Depth 4 5300.963064 1325.240766 184.28 0.0001

Temperature 1 0.105401 0.105401 0.01 0.9036

Dissolved oxygen 1 0.000581 0.000581 0.00 0.9928

Salinity 1 0.464315 0.464315 0.06 0.7994

North vector 1 69.697543 69.697543 9.69 0.0019

East vector 1 14.455526 14.455526 2.01 0.1564

North squared vector 1 45.138318 45.138318 6.28 0.0123

East squared vector 1 0.069053 0.069053 0.01 0.9219

North * East 1 2.222840 2.222840 0.31 0.5783

Season * Diel 9 20.728956 2.303217 0.32 0.9687

Diel * Depth 12 531.820136 44.318345 6.16 0.0001

Season * Depth 12 92.638315 7.719860 1.07 0.3781

Table 7.35. Mean target strength (dB) with Tukey’s studentized means test by time of day at

Green Canyon 18.

Time of Day Mean Target Strength Tukey’s Means Test

Dawn -37.0 A

Dusk -37.5 B

Noon -37.8 B

Midnight -38.5 C
457

Table 7.36. Mean target strength (dB) with Tukey’s studentized means test by platform side at

Green Canyon 18.

Platform Side Mean Target Strength Tukey’s Means Test

South -35.5 A

West -37.2 B

East -39.2 C

North -39.4 C

the sites and was 4 dB or approximately 12 cm based on estimated fish lengths (Love 1971). Target

strengths were significantly different at all depths examined, and the largest target strengths were

found near the surface (Table 7.37). No target strength data were found below 95 m, in agreement

with the low or zero estimated densities from the same region.

Table 7.37. Mean target strength (dB) with Tukey’s studentized means test by water depth (m)

at Green Canyon 18.

Depth

(m)

Mean Target Strength

Tukey’s Means Test

0-15 -35.5 A

55-75 -37.0 B

15-35 -37.7 C

75-95 -38.3 D

35-55 -39.9 E

Target strengths increased with the north current vector and north squared current vectors. These

results show an increase in fish size with current speed; however, currents speeds rarely exceeded

40 cm/s, and it is unlikely that currents of this scale would alter the size distribution of fishes. 

DISCUSSION

This study demonstrated the utility of merging hydroacoustics and visual survey techniques to study

the fish assemblages at petroleum platforms. The combination of these techniques enabled us to

measure the area of influence of these defacto artificial reefs, estimate abundance, size distribution

and species composition throughout the water column over extended time periods.

Our results demonstrate the variability in the abundance, size distribution, and species composition

of fishes associated with petroleum platforms. Our results were similar to earlier studies as
458

variability in the abundance of fishes is typical at both natural and artificial reefs (Gallaway 1980,

De Martini et al. 1981, Gallaway et al. 1982, Putt 1982, Sale et al. 1984, Chang 1985, Shinn and

Wicklund 1989, Bohnsak et al. 1991, Doherty 1991, Sale 1991, Bull and Kendall 1994, Stanley and

Wilson 1996, 1997, 2000). The variability in density and the size distribution of fishes at petroleum

platforms in this project was linked to temporal, spatial, and environmental variables. 

Spatial variability was consistently observed at all study sites. Fish density and size distribution of

fishes varied significantly with depth, platform side, and distance from the platform at ST54, GI94

and GC18. These results were similar to results from our past research (Stanley and Wilson 1995,

1996, 1997, 2000), findings by Morgan (1996), Gerlotto (1989) and Valdermarsen (1979). During

mobile acoustic surveys of platforms sited as artificial reefs (Morgan 1996) and production

platforms near Cameroon (Gerlotto et al. 1989), densities within 50 m of the sites were three to 10

times higher than in nearby open water. The results of this study showed that the highest densities

of fishes were also observed within 50 m of all study sites; however, differences in the rate of

decline with distance were found between sites of different water depths. At the shallowest site,

ST54, the decline in fish density with distance was precipitous; at distances greater than 18 m, fish

densities were similar to that of the open waters of the northern GOM. Results from this study at

ST54 are similar to those of our earlier work at a site of similar water depth but geographically

separated by over 300 km (Stanley and Wilson 1995, 1996, 1997, 2000). At the deeper sites a drop

in fish density with distance from the site existed; however, fish density was higher to greater

distances from the platform. A decline in fish density with distance did exist at both GI94 and GC18

as after a distance of approximately 50 m density approached those found in the open waters of the

GOM.

The differences in the relationship of fish density with distance from site to site are likely due to the

change in species composition and water clarity between shallow and deeper sites. At deepwater

sites, the water clarity was much greater, allowing visually-oriented species the capacity to range

farther away from the site while maintaining visual contact. Also, carangids were one of the

dominant groups of fishes observed at the deeper sites. While these fishes associate with reefs, they

are pelagic animals and thus much more likely to range farther away from a site. Despite these

complications, hydroacoustics again illustrated its effectiveness in defining “area of influence” of

the platform defined as the effective size of the artificial reef to the fish assemblage. As we defined

it, the area of influence extended 10 m at GC18 and 18 m at GI94 and ST54 as fish densities within

these distances were significantly higher than densities at greater distances. While these figures may

lead to a conservative estimates of total abundance we feel that they more accurately reflect the true

abundance of fishes at the sites. 

The spatial variation observed with target strength and platform side revealed that target strengths

were greatest on the south side of each of the study sites. Otherwise no uniformity was detected with

target strength and platform side. Largest target strengths on the south side were also consistent with

our past research (Stanley and Wilson 1997); however, we are at a loss to explain the rationale for

larger fishes on one side of the platform. In an attempt to decipher the variation in fish density and

target strength with platform side, current speed and direction data were modeled with these

variables. While significant relationships were detected between density, target strength and current

vectors, they did little to clarify the relationships. With respect to target strength, there was a
459

positive relationship at all sites with the north current vector. This relationship suggests that as

current speed from the north increased than target strength would increase. However, based on our

findings that the south side of the platform had significantly larger targets, one would expect a

negative relationship between target strength and north current vectors, indicating that larger targets

were found with southerly oriented currents. A more likely explanation of the larger target strengths

on the south side of the platform may be due to platform design and their influence on fish behavior.

That the most complex construction of structures is found at the north end, the well bay area,

suggests that this area may be a refuge for smaller fishes and explains the smaller target strengths

found on these sides. Past research has demonstrated a relationship between hole size and/or reef

complexity with fish size (Shulman 1984, Hixon and Beets 1989) and since the construction of

platforms on the south end is open with little shelter, larger fishes appear to be more common. 

The last spatial variable examined, and one of the primary questions to be addressed by the research,

was the effect of depth on the density and size distribution of fishes. Similar results with respect to

density and water depth were found for the two sites on the continental shelf, ST54 and GI94.

Highest densities were found adjacent to the surface and the bottom. These results were similar to

those of our earlier research (Stanley and Wilson 1995, 1996, 1997, 2000) and those of Chang

(1985), Shinn and Wicklund (1989) and Rooker et al. (1997). The most dramatic result of the project

was the change in density with depth at the site on the continental slope, GC18. A significant and

striking decrease in fish density with depth was found below 100 m, where only very low fish

densities were detected. Previous research supports these findings as species richness in the Pacific

was negatively correlated with depth, especially in tropical latitudes (Stevens 1996) and bottom

trawl data from the shelf break in the GOM (water depth > 110 m) documented the presence of 69

species; however, low abundances were found and few reef dependent species were captured

(Chittenden and Moore 1977). The concentration of fishes at GC18 near the surface is reflected in

the fact that 88% of the fishes were found in the upper 60 m of the water column. While near-surface

fish densities at GC18 were significantly higher than those below 60 m, the near surface densities

were only one-half to two-thirds of values found at sites on the continental shelf. The decrease is

likely due to the location of GC18 and its distance from the highly productive waters of the

Mississippi River. Both ST54 and GI94 are regularly influenced by the highly productive waters

from the Mississippi River as reflected in the lower surface salinities observed at these sites. The

high salinities observed at GC18 varied little from surface to the bottom, indicative of lowproductivity oceanic waters, and the oligotrophic conditions appear to be reflected in lower fish

densities even near the surface. 

Water depth also influenced the size distribution of fishes represented by low mean target strengths

at the shallowest site (ST54) and largest at the deepest site (GC18). Target strength also varied with

depth at each site. Significantly larger target strengths were found near the surface and then

generally decreased significantly with depth at each site. These results are different than our earlier

research where target strength was shown not to be significantly different with depth (Stanley and

Wilson 1996, 1997). The variation in size distribution with depth is likely due to the change in

species composition with depth detected at each site. 

The environmental variables influenced the density and target strength of fishes at the sites

examined but not to the extent of the spatial and temporal factors. Environmental variables,
460

including temperature, dissolved oxygen, current speed and direction, had their greatest impact on

density and target strength at ST54 and least influence at GC18. The large impact at ST54 may be

due to the large variation in environmental variables observed at the site. Temperatures varied by

over 10 oC from summer to winter, and while a positive relationship exited between temperature and

density, the highest observed densities were found during cooler periods suggesting a bell shaped

relationship where an optima is reached at a middle value with lower density values at the extremes.

A similar relationship between temperature and density existed at GI94. Where a significant

relationship existed between temperature and target strength (ST54 and GI94), divergent results

were found. At ST54, a positive relationship existed between temperature and target strength. This

relationship may be due to the presence of larger migratory species during the summer, including

cobia and tarpon. At GI94, a negative relationship existed between target strength and temperature,

most likely because of the large influx of blue runner, a small carangid, during winter. 

Dissolved oxygen had a significant effect on density at ST54 and GI94 and target strength on GI94.

Due to the location of ST54, it is typically impacted by the hypoxic events common during the

warmer months off Louisiana coast (Rabalais et al. 1985). During sampling trips in early June and

late July of 1996, hypoxia was found at ST54. During June 1996, dissolved oxygen levels were less

than 1 ppm from 20 to 22 m, and in July the hypoxic zone was substantially larger as dissolved

oxygen levels were less than 0.5 ppm from 15 to 22 m. Not surprisingly, fish densities were zero in

these areas and an overall positive relationship existed between dissolved oxygen and density at

ST54. This relationship was reinforced during the winter when high dissolved oxygen levels were

present and densities were highest. An interesting observation during the hypoxic events at ST54

were the elevated fish densities found above the hypoxic layers. When overall fish abundance was

compared between hypoxic and oxic summer sample periods, no significant difference in abundance

was detected. This result suggests that a vertical compression of the fishes into the oxygenated water

column occurred with little or no migration away from the site. Dissolved oxygen also significantly

affected fish density and target strength at GI94. While hypoxia was not observed at GI94 a positive

relationship was found between dissolved oxygen and density. This observation may be due to the

highest densities observed in the winter when dissolved oxygen levels were highest. 

The relationships between current speed and direction with density and target strength were not

consistent and varied with site. At ST54, a positive correlation was found with current speed and

density while at GI94 and GC18, negative relationships were observed. Past research has found that

highest fish densities were up current of petroleum platforms (Continental Shelf Associates 1982,

Putt 1982), while Chang (1985) and Lindquest and Pietrafesea (1989) observed that fishes oriented

down current of artificial reefs. Our earlier research (Stanley and Wilson 1996, 1997) did not

identify a consistent relationship of fishes orienting up or down current of a petroleum platform and

it would appear that results from this project support the conclusion that no consistent relationship

existed between fish orientation and platform side. Since median current speeds ranged from 8 to

19 cm/s at all the sites, observed current speeds were not strong enough to influence the behavior

of nektonic fishes with respect up or down current aggregations (Baxter 1969). 

The temporal variation of density and target strength of fishes demonstrated the lack of consistent

response to these variables. The longest temporal scale variable examined was between years and

was only found to be significant at GI94 for both density and target strength. Highest densities were
461

found in 1997 (although only one sampling trip occurred in 1997) and largest target strengths in

1995 at GI94. Seasonal differences in density and target strength were observed at all sites where

highest fish densities were found during cooler periods, specifically fall and winter. This finding is

similar to our earlier research (Stanley and Wilson 1996, 1997) but contrary to other research at

platforms and artificial reefs in the northern GOM (Gallaway 1980, Lukens 1981, Gallaway and

Lewbel 1982, Putt 1982). These differences as outlined in Stanley and Wilson (1997) are

presumably due to the differing sampling techniques between our research and others. Prior to our

use of hydroacoustics to assess abundance of fishes at petroleum platforms, only visual surveys were

performed. While visual surveys are effective in high-visibility conditions, they can be biased and

underestimate abundance in low visibility conditions (Bohnsak and Bannerot 1986, Charbonnel et

al. 1996). Since visibilities are generally poor during cooler periods in the northern GOM, it is

probable that the earlier visual surveys underestimated the abundance of fishes and did not

accurately reflect the total number of fishes at the sites. 

The seasonal variation in target strengths observed at ST54 and GI94 was not consistent. Largest

target strengths were found in the summer and smallest in the winter at ST54 while the reverse were

detected at GI94. The results from ST54 were similar to those of our earlier research and were

presumably due to the influx of large seasonal migrants such as cobia and tarpon in the summer.

Unlike our earlier research (Stanley and Wilson 1996, 1997) variation due to time of day was

observed at ST54 and GI94 in this study. At ST54, highest densities were found at midnight

indicating some attraction to the site may have occurred due to the presence of high-intensity

artificial lights at the site. At GI94 highest densities were found at dawn and lowest at noon and

dusk. It is difficult to explain our results with classic crepuscular activity of fishes observed at

natural and artificial reefs with highest densities during the day and lowest a night. On natural and

artificial reefs it is hypothesized that as light level decreases, the attraction to sites by fishes may

decrease due to a loss of visual acuity; also off-reef feeding at night is common and would cause a

decrease in abundance of fishes at night (Munz and MacFarland 1973, Hobson 1975, McFarland et

al, 1979, Heffman et al. 1982, Collins and Pettigrew 1988, Thorne et al. 1989). Target strengths

were largest at ST54 during dawn and noon samples while at GI94 the target strengths were largest

at midnight. The presence of high-intensity artificial lights at these sites may influence the behavior

of fishes at these sites and cause the changes from expected patterns common at natural and unlit

artificial reefs. 

Despite the range of depths of the sample sites, many species were common to all the sites. While

approximately 20 species were observed at a site over the study period, 6 species made up over 90%

of the fishes observed on any survey. The dominant six species by site (highest to lowest abundance)

were GC18: creolefish, blue runner, Bermuda chub, almaco jack, greater amberjack, and barracuda;

GI94: blue runner, horseeye jack, red snapper, mangrove snapper, gray triggerfish, and barracuda;

ST54: Atlantic spadefish, bluefish, blue runner, mangrove snapper, red snapper, and sheepshead.

The species observed during this project agreed with the past research in the northern GOM (Sonnier

et al. 1976; Gallaway 1980; Continental Shelf Associates 1982; Gallaway and Lewbel 1982; Putt

1982; Stanley and Wilson 1990, Rooker et al. 1997). Past research (Sonnier et al. 1976, Stanley and

Wilson 1990, Rooker et al. 1997) noted that over 35 species were associated with platforms in the

northern GOM, while we detected a total of 36 species over the three study sites. Despite the
462

disparate methods and temporal differences, there is general agreement in the species composition

between this and past research indicating that platform assemblages are fairly predictable. 

A unique observation from this study was the presence of yellowtail snapper at GC18. It is a

common species on natural reefs in the Caribbean and southern GOM, but it has been rarely reported

on natural reefs and platforms in the northern GOM (Darnell et al. 1982). During research trips in

fall 1994, winter 1995 and spring 1995, yellowtail snapper were relatively common at GC18 but

were not observed on any subsequent surveys. This finding suggests these fishes either migrated

away or experienced significant natural mortality, became extinct at the site and did not recolonize.

The species observed at ST54 were very similar to those found at platforms of similar depth by Putt

(1982) and Stanley and Wilson (1996, 1997). An exception was the observation of tarpon at ST54,

a species not previously reported during any visual observation research at platforms. These fish are

targeted by anglers, however, and caught near petroleum platforms (Stanley and Wilson 1990,

1991). 

Seasonal migrations were common at each of the study sites. Since this research took place

throughout the year, we were able to document the seasonality alluded to by past research but not

well documented (Sonnier et al. 1976, Putt 1982, Rooker et al. 1997). Common seasonal migrations

observed in the winter included an increase in the abundance of Florida pompano and bluefish at

ST54; blue runner and barracuda at GI94 and GC18. Increased abundances during the summer

season included the tarpon and cobia at ST54, cobia, red snapper, greater amberjack, and almaco

jack at GI94, while no summer migrants were observed at GC18. 

Since only six species made up over 90% of individuals at each site on any survey, platform

assemblages could be characterized as not specious but as dominated by a few species. While the

species found at each site were somewhat unique and the dominant species at each site was different,

overlap of observed species existed between sites, especially adjacent sites. Previous researchers

have noted a zonation of the assemblage of fishes associated with platforms and have divided the

shelf waters of the northern GOM into three zones, coastal (water depth < 27 m), offshore (water

depth 27 to 64 m) and bluewater (water depth > 64 m) (Gallaway 1980, Gallaway et al. 1981,

Gallaway and Lewbel 1982). While our results generally agree with the outlined zonation, we feel

that there is a larger crossover between zones than previously described, especially seasonally.

These conclusions were also echoed by Rooker et al. (1997), during a survey of the platform High

Island A389. While Rooker et al. (1997) generally agreed with the zonation as defined by Gallaway

(1980) there are significant differences and considerable overlap with shallower sites, indicating that

it is problematic to define species composition only by depth. Comparison of our research with

species composition from the High Island A389 site (water depth 125 m) surveyed by Rooker et al.

(1997) found the overall species composition was most similar to GC18 (water depth 219 m)

including the dominance of creolefish. Rooker et al. (1997) documented the presence of a large

number of midwater carangids, but due to their study design and emphasis on cryptic reef fishes,

they were not directly enumerated.

Based on our research and examination of the results from past platform studies, there generally is

a keystone species that dominates the composition of fishes at a site, e.g., Atlantic spadefish at
463

ST54, blue runner at GI4 and creolefish at GC18, but after the dominant species, overlap of species

existed between sites. Additionally, large fluctuations in abundance of species were common at all

the sites over the study period. Due to the apparent migration of many of the fishes common at

platforms in the northern GOM, and because of the range of depths and geographical location of

these sites, it is difficult to assign species to a certain zone. It may be more accurate to assign most

species to a platform assemblage grouping with a secondary category on depth. 

The trophic structure of the fishes at all three study sites was similar to results at natural reefs due

to the dominance of planktivorous omnivores (Shaffer and Rosen 1961, Smith and Tyler 1972,

Hobson 1974, 1992). However, while the trophic structure was similar between natural reefs and

platforms, the species composition of planktivores at natural reefs is different from those found at

platforms. At natural reefs, planktivorous Serranids, Chaetodontids, Pomacentrids, Holocentrids,

Priacanthids and Balistids typically dominate the taxa (Starck and Davis 1966, Randall 1967,

Hobson 1974, 1991), while at platforms, only a planktivorous serranid, creolefish, was found only

at GC18. At the other sites planktivores dominate but the species were Atlantic spadefish at ST54,

an Ephippid, and GI94 the dominant planktivore was blue runner, a Carangid. While the species

composition at platforms in the northern GOM is generally different from that of natural reefs, the

trophic structure is similar, as planktivores made 55 to 87% of the fishes observed at a site. This is

similar to the results from natural reefs as planktivores can make up to 98% of the fishes found at

natural reef (Hobson 1974, 1991, Sale et al. 1991). Another similarity between the trophic structure

natural reefs and petroleum platforms is the relatively small proportion of piscivores. At natural

reefs, piscivores make up 10 to 20% of the fishes at a site. This compares favorably with our results

as piscivorous Serranids, Lutjanids and Carangids made up 10 to 24% of the fishes observed. At the

trophic scale it would appear that the assemblage of fishes at petroleum platforms function similarly

to the community of fishes at natural reefs with respect to the dominance of planktivores and the

relative low numbers of piscivores. 

Comparison of our results with other petroleum platform studies from the northern GOM revealed

similarities and significant differences in density and abundance. Comparison of acoustically

derived estimates of density from our past research showed similar density values with those from

this project, especially at ST54 and GI94. Mean densities from our earlier work (Stanley and Wilson

1995, 1996, 1997) at a site in 24 m of water were 0.244 (+/- 0.062, 95% confidence interval)

fish@m-3, while mean densities found during this project were 0.333 (+/- 0.034) fish@m-3 at ST54,

0.496 (+/- 0.017) fish@m-3 at GI94 and 0.029 (+/- 0.003) fish@m-3 at GC18. With the exception of GC

18, these values are consistent with those from Putt (1982) for a platform in 22 m of water off the

Texas coast and an order of magnitude higher than the results of Continental Shelf Associates (1982)

from four platforms surveyed in June 1980. Both Putt (1982) and Continental Shelf Associates

(1982) used only visual surveys, Putt employed stationary cameras, and Continental Shelf

Associates used a ROV for visual surveys. While the densities from previous studies are comparable

to those estimated from our earlier and current research using hydroacoustics, the visual techniques

utilized are of limited value in low visibility by the authors’ admission; their conclusions are limited

to characterizations of fish populations under high-visibility conditions. The densities found at

platforms also are much higher than those from the open waters of the GOM. Morgan (1996)

acoustically measured fish densities at artificial reefs in water depths from 20 to 35 m on the

continental shelf off the Louisiana coast and found mean fish densities were approximately 0.01
464

fish@m-3. Based on all the results to date, it is apparent that large concentrations of fishes are found

around these structures in the northern GOM but the debate continues as to the exact function of

these structures on whether they increase productivity or attract existing organisms. 

Total fish abundance estimates from the platforms in this project fall within the range of estimates

at platforms from our earlier research in the GOM but are higher than those derived by visual-only

surveys. Stanley and Wilson (1995, 1996, 1997) calculated that there were on average a total of

12,473 (+/- 6,522, 95% confidence interval) fishes at a site in 24m of water, while during this

project, estimates of the total number of fish per site were 13,472 (+/- 1,346) at ST54, 28,952 (+/-

1,806) at GI94 and 13,856 (+/- 1,324) at GC18. Visual survey estimates were consistently lower

than those derived using combined hydroacoustics and visual surveys. Putt (1982) estimated that

a platform in 22 m of water had an average of 1,924 fish from July through September while single

point count estimates by Continental Shelf Associates (1982) at four platforms off the Louisiana

coast found 283 to 3,955 fish associated with individual platforms, in water depths from 28 to 31

m. Rooker et al. (1997) performed visual surveys in the upper 24 m of a platform in 125 m of water

and estimated 3,586 fishes were found at the site; however, this number included many cryptic and

reef-associated fishes that we did not include in our results. Moreover, these numbers did not include

the large number of carangids and scombrids observed. The study by Rooker et al. (1997) would

appear to be the best visual estimate of fishes directly associated with a platform as water clarity was

not an issue, and their methodology was superior to that of earlier visual surveys. However, it is

apparent that due to the open construction of platforms, visual surveys alone underestimate the large

number of schooling species at these sites. Other differences may result from the larger near-field

area of influence measured in this study. Earlier researchers did not directly measure the near-field

area of influence and assumed it to be 5 m (Continental Shelf Associates 1982, Putt 1982). The nearfield area of influence measured at ST54 and GI94 was 18 m while at GC18 it was defined as 10 m.

The relationship between density and distance was well defined statistically at ST54 and GI94.

Densities within 18 m of the site were significantly higher than at all other distances measured. At

GC18 the relationship was not as well defined, but based on acoustic-derived density data and visual

observations, the fishes remained close to the structure; 10 m was chosen as the near-field area of

influence. Another possible explanation for the higher total fish abundance estimates from our

research than those of Putt (1982) and Continental Shelf Associates (1982) may be size of the

platform. Previous research (Rousenfell 1972, Ogawa et al. 1973, Grove and Sonu 1983; Rountree

1989; Stanley and Wilson 1990) indicated that fish abundance increased with increasing artificial

reef size. That ST54 and GI94 were larger than three of the four platforms compared in other studies

may explain some of the variation. Another likely explanation of the higher abundances detected

during our research is the utilization of dual-beam hydroacoustics which did not influence fish

behavior, was not limited by visibility, and could determine the area of influence of the reef. The

combination of these factors allows for more accurate assessments of the abundance of fishes at

these sites. 

One of the most interesting results of the project was the comparison of abundance between the

sites. GC18 was three to 10 times larger than the others, but the total abundance estimates were not

significantly different than those of the smallest site (ST54), while the abundance estimates from

GI94 were twice that of the other sites. Since structure size has been shown to affect fish density and

the observation of higher density and abundance at the mid-size platform, it would appear that an
465

optimal reef size may exist. This is consistent with results from our earlier research (Stanley and

Wilson 1991). Previous studies have shown that fish abundance is directly correlated with reef size

to a maximum reef volume of 4,000 m3

 (Ogawa et al. 1973) or 25,000 - 50,000 ft2 (Rousenfell

1972). While the platform with the highest abundance, GI94, is larger than the optima from a reef

volume perspective, due to the open construction of platforms, it is comparable to the optimal

surface areas estimate from Rousenfell (1972). The low abundances observed at GC18 are likely as

a result of its location and the water depth at the site. Fish abundance was essentially zero below 100

m and densities above 100 m were lower than the other sites. These two factors combined to produce

the low abundances observed at the site. Because of the location of GC18, it is not influenced by the

eutrophic waters on the continental shelf and the outflow from the Mississippi River. It is most

influenced by oligotrophic oceanic waters from the Caribbean. The combination of water depth and

oligotrophic conditions likely reduce the abundance of fishes at the GC18. 

The 4,000 petroleum platforms in the northern GOM, provide an estimated 12.1 km2

 of additional

hard substrate (Stanley 1997) to a ecosystem that is dominated by a mud/sand substrate (Parker et

al. 1983). The total area of the Minerals Management Service (MMS) No Activity Zones (which

includes known natural reefs and hard-bottom areas on the continental shelf in the northern GOM)

is 292.81 km2

 (Dr. Ann Bull, personal comm). The additional hard substrate provided by the

petroleum platforms acting as defacto artificial reefs increases the amount of hard-bottom habitat

by 4.1% from Destin, Fl to Brownsville, TX. Off Louisiana, the contribution is greater as the 3,600

platforms off the coast provide an estimated 10.9 km2. The total area of the seventeen MMS No

Activity Zones off the Louisiana coast is 104.5 km2

. Based on these estimates, platforms increase

the hard bottom by 10.4%. The expansion of hard substrate habitat, especially habitat in the upper

water column, has undoubtedly changed the dynamics of energy flow and influenced the utilization

of marine resources, but it has proved difficult to quantify the impact of these structures. Since 1990,

over 90% of the commercial red snapper harvest has occurred off the Louisiana and Texas coasts

(Shirripa and Legault 1997), and while statistics do not exist on the percentage of red snapper caught

at petroleum platforms, it is assumed to be a significant portion. Additional support of the

importance of petroleum structures to fisheries was found in the highest published angler catch rates

at petroleum platforms (Stanley and Wilson 1990). Fishes important to recreational and commercial

fishing were common at the each of our study sites. 

In recognition of the benefits of artificial reefs to marine fisheries in the northern GOM, Louisiana

and Texas created artificial reef programs where retired petroleum platforms are the material of

choice (Wilson et al. 1986, Stephan et al. 1990). The standard deployment of these structures as

reefs involves placing the jacket on its side. However, this deployment minimizes vertical relief. If

a platform such as GC18 were deployed in this manner, it would extend approximately 80 m off the

bottom. Based on our results, a toppled deepwater artificial reef would be utilized by few fishes; a

structure sited in this manner would have limited value as an artificial reef. This project is the first

demonstrating the importance of vertical relief in maximizing the effectiveness of platforms as

artificial reefs, especially with respect to deep water environments. 

There are few assessments of the abundance of fishes at platforms in other areas of the world,

despite the fact that over 2,500 of these structures are found outside the GOM (Aabel et al. 1997).

Estimates of fish abundance at structures in the North Sea based on experimental netting and visual
466

surveys with ROVs have revealed high abundances of platform associated fishes (Valdermarsen

1979, AUMS 1987, ICIT 1991, Cripps and Aabel 1995, Cripps et al. 1995, Aabel et al. 1997). Mean

density and abundance values were comparable to those from the northern GOM as 0.3 fish@m-3 were

detected by Cripps and Abel 1995 and total abundance estimates in the region range from 9,000 to

80,000 fishes varying with water depth, platform size and location (Valdermarsen 1979, AUMS

1987, ICIT 1991, Cripps and Aabel 1995, Cripps et al. 1995, Aabel et al. 1997). These results along

with those from the GOM and the west coast of Africa (Gerlotto et al. 1989) clearly demonstrate

that petroleum platforms are effective artificial reefs in a variety of climates and with various species

assemblages. 

This research confirms the variability of fish assemblages associated with petroleum platforms and

reinforces the need to sample on each side and throughout the water column to obtain an accurate

estimate of fish abundance. It also demonstrates the importance of petroleum platforms to the marine

environment of the northern GOM due to the high abundance of fishes found at the sites. Although

some variance was observed, 10,000 to 30,000 fishes were found at a site at any one time, and since

over 1,000 platforms are found in similar water depths, it is clear that these structures impact the

fisheries of the region. 

This study continues to demonstrate the utility of merging hydroacoustics and visual survey

techniques to study the assemblage of fishes associated with petroleum platforms. The combination

of these techniques allows for the measurement of the area of influence of these defacto artificial

reefs, estimates of abundance, size distribution and species composition throughout the water

column and over long time periods.

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472

RIGS AND REEFS: A COMPARISON OF THE FISH COMMUNITIES AT TWO

ARTIFICIAL REEFS AND A PRODUCTION PLATFORM

Charles A. Wilson

Mark Miller

Department Oceanography and Coastal Sciences

Louisiana State University

Rick Kasprzak

Louisiana Department of Wildlife and Fisheries

Dave Stanley

Beak International

There are approximately 5,500 oil and gas platforms (platforms) in the northern Gulf of Mexico

(GOM), most of which are off the Louisiana coast. Although there is some debate about the

significance of these “artificial reefs”, platforms have a total surface area estimated to be a fraction

(4%) of the 2800 km2 of naturally occurring hard bottom found in the otherwise silty environment

of the northern Gulf (Parker et al. 1983; Stanley and Wilson 1990, 1991, 1997). However, platforms

constitute a larger percentage of the hard substrate off Louisiana due to the general absence of

natural hard substrate. It is safe to say that the oil and gas industry in the GOM has created the most

extensive de facto artificial reef system in the world.

Stanley and Wilson (1996, 1997, 1998, 2000) documented species compositions and abundances

of fishes at several platforms off Louisiana; they concluded that each standing platform seasonally

serves as critical habitat for 10,000-20,000 fishes, many of which are of recreational and commercial

importance. Undoubtedly, this new habitat has influenced fish populations in the GOM. Habitat

provided by petroleum platforms has likely affected processes such as energy (food) availability,

habitat, recruitment, competition, and predation (Menge and Sutherland 1987; Doherty and Williams

1988; Bohnsack et al. 1991; Stanley and Wilson 2000).

The concept of using oil and gas platforms as artificial reefs is generally held in high regard and is

strongly supported by recreational fishers and their respective organizations. However, the scientific

community still questions the real “habitat” value of artificial reefs in general, and the practical

value of retaining platforms as artificial reefs. There are many management oriented questions

involving the effect of water depth, geographic location, and general reef configuration; more

perplexing scientific questions concern attraction versus production and the comparison of artificial

reef fish communities to natural reef fish communities (Seaman and Jensen 2000). These and other

issues must be addressed to determine both the effectiveness of these structures as artificial reefs

and their impacts on the marine ecosystem in the region. 

The general practice for incorporating platforms into reef programs involves two options. The

Louisiana Artificial Reef Program (LARP) has configured many reef sites by laying a platform on

its side (by toppling in place or moving a platform from another location). More recently LARP has
473

followed the Texas Artificial Reef Program by removing the upper 30 m portion of a platform to

comply with Coast Guard regulations (partial removal). Stanley and Wilson (1997) raised questions

about the habitat importance of vertical profile leading us to further examine the practice of partial

removal of platforms for reef site creation as opposed to the more common practice of toppling

(Stanley and Wilson 1997, 1998).

The proximity of the several artificial reef projects in similar water depth afforded us the opportunity

to compare several platform configurations to one another. Therefore the purpose of this study was

to compare the fish communities associated with three platform/artificial reef configurations. Reef

configurations included a production platform, toppled in place as an artificial reef (West Cameron

(WC) 617A), a nearby partially removed platform (HI A355), and an operating production platform

(HI A350). The goals of this study were to identify species composition at each site; to estimate the

fish density/biomass associated with each site; to determine the effects of platform side, depth, and

distance from each site on fish biomass . 

MATERIALS AND METHODS

This research project was designed to compare the fish resources associated with a standing platform

and two artificial reefs located in a similar geographic region in the northern GOM off the

Texas/Louisiana border (Figure 7.42). The standing platform, HI A350 (High Island), owned by

Shell Corporation, is located at 28o

 1.130' north latitude and 93o27.512' west longitude. This eight

pile structure was installed in 1976 in 90 m of water. This standing platform occupies an area in the

water column measuring 90 m in height and has a 68m x 40m footprint.

The toppled platform, WC 617A, formerly owned by Mobil Corporation, is located at 28o 3.664'

north latitude and 93o 18.805' west longitude at a depth of 98 m. It was installed as an eight pile

structure in 1976. In July 1992, the upper deck was removed approximately 3 m above the waterline,

then the jacket was severed below the mudline with explosives, and the remaining structure was

toppled in place. This toppled platform occupies an area in the water column measuring 31 m in

height and has an 84 m x 60 m footprint.

The partially removed platform, HI A355, formerly owned by Occidental Petroleum, is located at

28o 2.491' north latitude and 93o 42.551' west longitude in 90 m water depth. It was installed as an

eight pile structure in 1978. In January 1996 it was partially removed mechanically cutting it at -27.5

m. The upper jacket was split vertically, and a four pile portion (1⁄2 of the upper portion) was placed

on the southeast side of the main structure. This partially removed platform occupies a volume in

the water column measuring 68m high and has a 60m x 40m footprint; the four pile section on the

south side measures 32 m high with a 24m x 18m footprint. 

Survey Designs

Dual beam hydroacoustic surveys (Stanley and Wilson 1997) were accomplished with a stationary

array of four transducers at the standing platform and with towfish mounted single transducer mobile
474

Figure 7.42. Map of the sites surveyed in June 1999 and 2000.

surveys at the two reef sites. The standing platform was surveyed in June 1999 with stationary dual

beam hydroacoustic equipment developed during past research (Wilson and Stanley 1991; Stanley

and Wilson 1995, 1996, 1997,1998, in press). Sampling consisted of three downward-oriented

transducers (120 kHz) placed approximately 3 m below the surface, one on each side of the platform

except the west side due to an equipment failure as described in Stanley and Wilson (1998). The

downward facing transducers provided acoustic coverage from a depth of 5 m to within 1 m of the

substrate. The use of three transducers enabled the calculation of density throughout the water

column on three sides of the platform. Acoustic sampling consisted of two hour time blocks over

a 24 hour interval encompassing four periods (dawn, noon, dusk and midnight). Hydroacoustic data

were collected sequentially from each transducer in five minute intervals. 

A towed transducer was used to estimate the acoustic biomass, density, and size frequency

distribution of fishes associated with the two artificial reef sites. A 120 kHz downward oriented

transducer, mounted on a v-fin tow body was towed from the R/V Pelican (June 1999) and the M/V

Epic Mariner (June 2000). The towfish was held in place 5 m out from the hull and flown 3 m below

the surface at a speed of approximately 2 m/sec. The use of a towed downward oriented transducer

enabled the calculation of density and size distribution of fishes from a depth of 5 m to 1 m from

the bottom or within 1 m of the each structure. Data were georeferenced with a Garmin GPS III

global positioning system (GPS) and a Garmin GB 21 differential beacon receiver. The navigation

data stream, updated once per second, was incorporated into the acoustic data string and then stored

on a PC. 
475

Mobile surveys at the two artificial reef sites consisted of alternating east-west then north south

transects over the target area. In June 1999, a total of 100 transects (50 east-west and 50 north-south)

occurred over each of the artificial reef sites. In June 2000, efforts were reduced to a total of 40

transects (20 east-west and 20 north-south) which produced the same statistical power as the 1999

survey. Transects were conducted out to a distance of 100m from each side of the artificial reef.

Each transect covered a linear distance of approximately 300 m, passing over the top of the artificial

reef site in the center of each transect. 

Acoustic data were collected with 120 kHz transducers which had been factory calibrated to a - 42

dB tungsten sphere and a Biosonics model DT5000 scientific echosounder/multiplexer. All data

were collected with source levels at 223 dB / Pa at 1 m. Sampling rate was 5 pings /sec with a pulse

width of 0.4 ms. Received signals were adjusted for spreading loss by applying a 40 log R time

varied gain, digitized and recorded on the computer hard drive. The data collection threshold was

-55 dB, corresponding to a minimum detection of a 2.5 cm fish (Love 1971).

Digitized hydroacoustic data were processed with Biosonics Visual Analyzer 4.02. Recent software

advances allowed simultaneous estimates of sigma (target strength) and mean volume backscatter

(reflected acoustic energy) for each depth strata. These parameters are used to estimate fish size and

fish density/m3

. Ten meter depth strata were assigned for processing data from each site. Data files

were replayed through Visual Analyzer with the bottom tracking feature turned on; the bottom was

then manually inspected and adjusted to insure that neither the bottom and/or platform were included

in the analyzer window. Bottom correction was not necessary for the standing site as the transducers

were fixed and digitized to exclude the structure during the collection process.

The standing platform data were analyzed in 5 minute blocks for each side as in previous studies

(Stanley and Wilson 1997). Analyzer outputs for the standing platform included volume

backscatter/m3

, fish density/m3, and mean target strength/m3. A Visual Basic program was used to

extract data of interest from analysis outputs and to compile the results into a site specific database

for statistical analysis (Stanley and Wilson 1997).

Mobile transects were analyzed at one second resolution (corresponding to a 2 meters linear

distance) to determine the volume backscatter/m3 and target strength/m3 within each depth stratum

along the transect. Analysis of each one second block of data provided location specific mean

volume back scatter. Individual target strength information was acquired by extracting ping specific

data which could be selectively output as a text file. A Visual Basic program was used to calculate

an average target strength for each target, by strata, and location.

Data Analysis

Fish density (number/m3) was calculated based on the volume backscatter (reflected acoustic

energy) of a known volume (cubic meter) of water divided by the average target strength (reported

as sigma) from that same volume of water. Density estimates are dependent upon accurate estimates

of the mean sigma of the targets within that same volume of water. Analysis of standing platform

data with Visual Analyzer version 4.02 produced useful density estimates. However, analysis of the

mobile data required refinement of TS for accurate density comparisons. The accuracy of target
476

1

Jim Dawson, BioSonics, Inc., personal communication.

strength increases with repeated acoustic hits on the same target (Jim Dawson, pers. com.1). Since

research operations were from a vessel moving at 2 m/s and transmitting acoustic pulses (pings) at

a rate of 4-5 pings per second, the chance of hitting a target multiple times was very low. In many

cases data processing resulted in a volume backscatter, but no sigma for that same volume of water.

In estimating fish densities for mobile surveys, a mean sigma (proxy sigma) was calculated for a 30

m linear distance by stratum. We assumed, that fish size was similar in the same stratum for 30

linear meters. If sigma was missing, but a volume backscatter volume was available, the proxy

sigma was substituted to estimate density. 

Statistical Analysis

Statistical analysis of these data included volume backscatter (reflected acoustic energy-volume

backscatter or SV) as a dependent variable. Volume backscatter is an exponential number provided

by the Biosonics Visual Analyzer and is a per “ping” average of acoustic energy/m3. For

regressional analysis and calculation of means, SV is converted into a “arithmetic form,” called

“Fish Energy,” with the relationship,

 Fish Energy = 10 sv/10

where SV is volume backscatter (reflected acoustic energy) of a known volume of water (cubic

meter) “Fish Energy” should be considered to be an acoustic measurement of fish biomass as it is

based on the average acoustic reflectance/m3. The second dependent variable in our analysis was

density/m3

, which was generated from the Visual Analyzer analysis for HI A350 and calculated for

the mobile surveys of two reef sites using the equation, 

10 SV/10 /10 TS/10 = fish/m3

where SV is the volume backscatter/m3 and TS is the mean sigma assigned (or the proxy sigma

discussed above). 

A randomized block analysis of variance (RBA) was used to examine the main effects of SV and

log transformed density (log10 (fish density + 1)) at HI A350 and TS at all sites as described by

Stanley and Wilson (1997). Class variables included time of day (time of day (TOD): dawn, noon,

dusk, midnight), platform side (north, south, east) ten meter depth strata (strata), and their

interactions. RBA’s were also used to examine the main effects of TS at all sites. Class variables for

TS RBA’s include TOD, strata, platform side, and all two-way interactions. Class variable for WC

617A and HI A355 include TOD, depth strata, reef side, horizontal 10 meter distance intervals away

from the reef structure (away), and all two-way interactions. Tukey's standardized range tests (Ott

1982) were used to compare the means of significant variables. Statistical tests were reported as

significant at the alpha < 0.01 level.
477

Logistic Regression

Traditional parametric analyses were not used for analysis of mobile acoustic data due to the large

number of zero values and the problem of autocorrelation that occurs in mobile acoustic data

(Trexler and Travis 1993). Analysis consists of converting the dependent variable into a discrete

form (e.g. presence/absent, agree/disagree, etc). The regression model then assumes a binomial

distribution of errors (Trexler and Travis 1993, Garrison et al. 2000). A binomial logistic model was

constructed for each site using the presence or absence of "fish energy" to evaluate the probability,

or chance, of finding fish. This analysis was performed on the primary output of acoustic data

analysis which was reported in 1 second intervals. Class variables for the artificial reef sites included

orientation (over the platform, and north, south, east, and west sides), depth strata, away, TOD, year

(1999 or 2000), site (standing or toppled) and transect (ordinal transect number). 

The Statistical Analysis System (SAS 2000) includes a program called Proc Logistic that uses

logistic analysis . When run with the intercept option, it produces a Type III analysis of main effects,

which provides an estimate of the significance of class variables, based on a maximum likelihood

test (Chi Square test of significance p=0.01) that we used to compare class variables. When run

without the intercept, Proc Logistic provides an odds ratio estimate, which is the probability of

finding fish in a given class variable cell compared to another cell. 

Fish Abundance Estimation

Total fish abundance estimates at each site were calculated by determining a 20m near-field area of

influence of each reef site or platform, then multiplying mean density (#/m3

) values by stratum and

side by the volume of water on each side of or over the platform (Stanley and Wilson 1998). Fish

density within the centers of each platform was not measured with acoustics due to interference by

structural members and was assumed to be the average of the density estimates of the four sides of

the platform; it was estimated by multiplying the estimated fish density of the center by the volume

of water in the center of the platform. 

VISUAL SURVEYS

Visual surveys were conducted with a Deep Ocean Engineering Phantom HD2 ROV with standard

visual census techniques and recording video on S-VHF tape (Bohnsack and Bannerot 1986).

Cryptic fishes were not included in the video surveys results since they could not be assessed in the

acoustic surveys. Point counts were conducted to identify individual fish to the lowest taxonomic

level. Results were expressed as percent composition by stratum at each site. 

During mobile surveys, an ROV was deployed from the research vessel anchored near each artificial

reef site. During the survey of HI A355, the ROV was flown down to the bottom, stopping every

10 m for approximately 1 minute. During the survey of WC 617A, the ROV was flown down to the

top of the artificial reef complex and then run along the south side, east side, west side, and over the

top of the toppled platform. Video surveys of HI A350 were conducted directly from the standing

platform. The ROV was flown from the surface to the bottom, stopping every 10 m for

approximately 5 minutes.
478

1.00E-07

2.10E-06

4.10E-06

6.10E-06

8.10E-06

0 10 20 30 40 50 60 70 80 90

Depth Stratum (m)

Fish Energy

Figure 7.43. Mean fish energy/m3 (antilog of volume backscattering) by depth stratum for HI

A350. Error bars are 95% confidence intervals.

RESULTS

HI A350 Results (Standing Platform)

The stationary hydroacoustic survey of HI A350 was conducted in June 1999. A five-day trip was

made to the platform where acoustic data and ROV data were collected.

Volume Backscatter (SV), the measure of the amount of reflected acoustic energy, or fish biomass

/m3

, varied with several of the modeled parameters based on RBAs. SV values ranged from 0.0 to

2.2 x 10-4 /m3

; the mean value at HI A350 was 1.2 x 10-6 /m3. SV was affected by depth and time of

day and the interactions of side and depth. SV was highest at the surface and lowest near the bottom.

The upper two strata were statistically different from one another and both were significantly higher

than the remaining strata (3 - 8) (Figure 7.43). Fish biomass also varied significantly with TOD and

was highest at dusk followed by noon, morning, and midnight. 

Estimates of fish density were based on SV divided by the average target strength (TS) of the fish

in the same volume of water and in general followed SV patterns. Based on RBAs, estimated density

was affected by depth and TOD and their interactions. Estimated fish densities ranged from 0.0 to

0.7 fish/m3

; the mean fish density at HI A350 was 0.015 ± .003 (mean ± std error) fish/m3. Densities

were highest in the upper part of the water column and generally decreased with depth (Figure 7.44).

Density also varied with time of day and was highest at dusk and lowest at midnight. 

Target Strength

Target strength (TS) is an acoustic measure of fish size which was used as a dependent variable to

test for relationships between fish size with TOD, orientation, and depth and their interactions. TS

ranged from -52.46 to -30.75 dB; the average TS at HI A350 was - 40.73 dB which is equivalent to

a 12.5 cm fish. Based on the RBAs, TS at the standing platform was affected by depth and time of

day. Fish were significantly larger near the surface and smaller near the bottom and were

significantly larger in the morning than at noon, dusk, and midnight.
479

Fish Density: HI 350

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

0 10 20 30 40 50 60 70 80 90

Depth (m)

Fish Density 

Figure 7.44. Estimated mean fish density (fish/m3) at depth for HI A350. Error bars are 95%

confidence intervals.

SPECIES COMPOSITION AND ABUNDANCE

The fish community at HI A350 was very similar to previous studies and consisted of pelagic

planktivores near the surface and reef-associated species near the bottom (Table 7.38). Bermuda

chub and blue runner were the most abundant species making up more than 50 percent of the fish

observed on the ROV survey; they were most common near the surface (Table 7.38). Creole-fish,

scamp, and red snapper also were fairly abundant and made up approximately one-third of the

species present. Red snapper and scamp were most numerous near the bottom and creole-fish were

most abundant at mid-depth (Table 7.38). 

Total fish abundance at HI A350 within a 20 m area of influence was estimated to be 7,100. Based

on the percent composition, there were approximately 2,100 blue runner, 1,000 bermuda chub, 1,000

creole fish, 500 scamp, and 400 red snapper. Although the numbers are not absolute, they provide

a relative scale of fish abundance.
480

Table 7.38. Species common names and scientific names, numbers of individuals by stratum,

totals, and percent composition from visual point counts using video from a remotely

operated vehicle (ROV) from High Island A350, June 1999.

Common

 Name

Scientific

Name 0 m 10 m 20 m 30 m 40 m 50 m 60 m 70 m Totals

%

Comp

Almaco jack Seriola rivoliana 5 1 22 9 - 1 - - 38 3.6

Bermuda chub Kyphosus sectatrix 280 - - - - - - - 280 26.8

Bar jack Caranx ruber 1 - - - - - - - 1 0.1

Great

barracuda

Sphyraena barracuda 6 10 2 - - - - - 18 1.7

Blue angelfish Holacanthus

bermudensis

- 6 10 5 - - - - 21 2.0

Blue runner Caranx crysos 92 33 182 - - - - - 307 29.4

Blue tang Acanthurus coeruleus - 2 4 1 - - - - 7 0.7

Creole-fish Paranthias furcifer - - 94 53 - - - - 147 14.1

Crevalle jack Caranx hippos - 9 - - - - - - 9 0.9

French

angelfish

Pomacanthus paru - - 4 3 - - - - 7 0.7

Gag Mycteroperca

microlepis

- - 1 - - 1 - - 2 0.2

Greater

amberjack

Seriola dumerili - 2 4 4 2 8 1 - 21 2.0

Gray

triggerfish

Balistes capriscus 1 - 1 2 4 - - - 8 0.8

Rainbow

runner

Elagatis bipinnulata - - 11 - - - - - 11 1.0

Red snapper Lutjanus

campechanus

- - - - 11 50 - - 61 5.8

Rock beauty Holacanthus tricolor - - - 1 - - - - 1 0.1

Reef

butterflyfish

Chaetodon

sedentarius

- - - - 1 - - - 1 0.1

Scamp Mycteroperca phenax - - 2 17 7 37 10 - 73 7.0

Sergeant major Abudefduf saxatilis 6 1 7 - - - - - 14 1.3

Spanish

hogfish

Bodianus rufus - - 9 1 1 - - - 11 1.0

Squirrelfish Holocentrus

adscensionis

- - 3 - - - - - 8 0.8

WC 617A AND HI A355 RESULTS (TOPPLED AND

PARTIALLY REMOVED PLATFORMS)

Acoustic surveys of these sites (Figure 7.45) were tracked with differential GPS which was

incorporated into the acoustic database; resultant track lines over each site are shown in Figure 7.46.

The actual track lines are evidence that we were successful in keeping the vessel transects over the
481

A.

B

Figure 7.45. Line drawings of WC 617A (toppled platform) and HI A355 (partially removed

platform with a small four leg section to the southwest).
482

A.

B.

Figure 7.46. Plot of vessel track (dotted lines) over WC 617A (A) and HI A355 (B) for

surveys conducted June 1999 and June 2000. Bathymetry contour show depths

at each reef site and indicate the platforms. North is up in both figures.
483

tops of the target sites. A plot of recorded bottom depth of repeated transects at each site resulted

in a detailed 3-dimensional outlines of the platform profile (Figure 7.47) and illustrates the precision

of positioning as well as current reef site bathymetry.

Acoustic data were used to determine fish presence based on SV, to estimate fish density/m3, and

to estimate fish size above, in proximity to, and away from the reef sites. One concern was that

transect number might lead to a decrease in fish density as multiple passes of the vessel over each

site might scare away fish. Including transect number (n=100) as a class variable in the logistics

regression for the 1999 data at both sites indicated a significant effect; however, there was no pattern

indicating a decrease or increase or change in the probability of finding fish with consecutive

transects. We concluded that there was no predictable change in the probability of fish occurring

during consecutive passes of the vessel, so all transects were combined for analysis. 

WC 617A (TOPPLED PLATFORM)

A binomial logistic model was constructed for WC 617A with presence/absence of SV (hence fish)

as the dependent variable with class variables, orientation, stratum, away, TOD, and year and all two

way interactions. All class variables were significant indicating that orientation, time of day, away,

and year influenced the probability of fish occurring. Two-way interactions were evaluated and

determined to be either insignificant or of no biological meaning, then were removed from the model

as they confounded class variable interpretation.

Odds ratio estimates produced in Proc Logistic calculated without an intercept provided insight into

the probability of finding fish varied within each class variable. From the analysis outputs it was

concluded that there was a difference between years as the chance of finding a fish in 1999 was

approximately 2.5 times that in 2000. In addition, there was no influence of orientation as the

probability of finding a fish was the same over and away from the platform. However, there was

higher mean biomass (measured as SV) over the platform than on the sides indicating that when fish

were present, there was greater biomass over the reef site than on any of its sides. Analysis also

indicated that fish occurred more frequently near the bottom along the sides of the platform.

The biological significance of these differences was best appreciated by plotting mean SV (fish

energy) and estimated fish density (+/- 95% confidence intervals) for each significant class variable.

The mean values plotted on these graphs are greatly influenced by the larger number of zero values,

but they allow for comparisons of trends. Mean SV was highest over the platform and declined with

distance from the 617A reef site (Figure 7.48a); mean SV varied with side (orientation), and was

lower on all sides than over the platform. Mean SV reached a minimum beyond 30 m away from

the platform, so we assigned a 20 meter area of influence of this site. Mean SV also varied with

depth and time of day as it tended to be higher near the bottom and higher at midnight.

Target Strength

The relationship between TS and associated class variables was modeled with RBD ANOVAs. TS

was affected by side, depth stratum, and TOD and all interactions. The meaningful part of this

analysis is that fish were, on average, larger over the platform and smallest on the south side. Fish
484

A.

B.

Figure 7.47. Acoustic depth profiles of WC 617A and HI A355 based on a geo-referenced plot

of depth from the hydroacoustic survey conducted in June 1999 and 2000.

Outlines of both structures are evident based on bottom depth.
485

1.00E-09

1.01E-07

2.01E-07

3.01E-07

0 10 20 30 40 50 60 70 80 90

Distance Form Artificial Reef (m)

Fish Energy

1.00E-09

2.01E-07

4.01E-07

6.01E-07

8.01E-07

0 10 20 30 40 50 60 70 80 90

Distance from Artificial Reef

Fish Energy

A

B.

Figure 7.48. Estimated mean fish energy /m3 (antilog of volume backscatter) at distance from

reef site for WC 617A (A) and HI A355 (B). Error bars are 95% confidence

intervals.
486

size decreased with increased distance from the site (Figure 7.49a). Fish size also varied with depth

and targets tended to be larger near the surface and immediately above the structure. Average

acoustic size at WC 617A was - 46 dB (8.6 cm) and ranged from -62 to -26 dB (1.2 to 96 cm) (Love

1971). Target size changed with TOD, and fish were larger at dawn followed by midnight, dusk, and

noon.

Density Estimates

Fish density was calculated based on acoustic volume backscatter and TS (mean target strength/m3

or its proxy described in Materials and Methods). Plots of the mean density values provide actual

density estimates for comparison to earlier studies. Density over and away from WC 617A ranged

from 0 to 0.5 fish/m3 and the overall mean density of the site within 20 m was 0.0015 fish/m3. Mean

density decreased slightly beyond 30 meters and did not vary much. Mean density was slightly

higher over the platform compared to the east, west, north and south sides. Density also varied with

depth and was highest at the surface and immediately above the bottom (Figure 7.50a). Density

varied with time of day and was highest during midnight followed by dusk, noon and morning.

Although density did not vary much, it should be noted that SV was higher over WC 617A where

the fish were also larger.

Species Composition and Abundance

Species present at WC 617A were indicative of a reef-associated community. Seven species made

up 90% of the community (Table 7.39). Red snapper were the most abundant and made up over 45%

of the population followed by greater amberjack, Spanish hogfish, gray triggerfish, and creole-fish.

Total fish abundance at WC 617A within a 20 m area of influence was estimated at 2,700. There

were roughly 1,220 red snapper, and 405 amberjack, followed by 270 Spanish hogfish and 216 gray

triggerfish.

HI A355 (PARTIALLY REMOVED PLATFORM)

A binomial logistic model was constructed for HI A355 with presence/absence of SV (hence fish)

as the dependent variable with class variables orientation, stratum, away, time of day, year and all

two-way interactions. Based on a binomial logistic regression with SV as the dependent variable,

significant effects were found with orientation, away, time of day, and year. Two way interactions

were evaluated and determined to be either insignificant or of no biological meaning, so they were

removed from the model as they confounded the class variables interpretation.

Odds ratio estimates from Proc Logistic run without an intercept provided insight into the

probability of finding fish and then varied within each class variable. From the analysis outputs it

was concluded that there was a difference between years as the chance of finding a fish in 1999 was

roughly 1.3 times higher than that in 2000. A difference in orientation was also found with the

probability of a fish presence was highest on the south side. There was a slightly greater chance of

finding fish within 30 m rather than immediately over the platform. Analysis also indicated that fish

occurred more frequently near the bottom and closer to the platform.
487

-52

-50

-48

-46

-44

-42

-40

0 10 20 30 40 50 60 70 80

Depth Stratum (m)

dB

-52

-50

-48

-46

-44

-42

-40

10 20 30 40 50 60 70 80

Depth Stratum (m)

dB

A.

B.

Figure 7.49. Estimated mean target strength (dB) at depth stratum for WC 617A (A) and HI

A355 (B). Error bars are 95% confidence intervals.
488

0

0.0005

0.001

0.0015

0.002

0.0025

0.003

0.0035

0 10 20 30 40 50 60 70 80

Depth Stratum (m)

Fish Density 

0

0.001

0.002

0.003

0.004

0.005

0.006

0 10 20 30 40 50 60 70 80

Depth Stratum (m)

Fish Density 

A.

B.

Figure 7.50. Estimated mean fish density (fish/m3

) by depth stratum for WC 617A (A) and HI

A355 (B). Error bars are 95% confidence intervals.
489

Table 7.39. Species common names and scientific names along with numbers of individuals by

stratum, totals, and percent composition from visual point counts using video from

a remotely operated vehicle (ROV) from a toppled platform (West Cameron 617A)

June 1999.

Common

Name

Scientific

Name 0m 10m 20m 30m 40m 50m 60m 70m Totals

%

comp

Almaco jack Seriola rivoliana ---- 1 9 4 - 14 7.4

Creole-fish Paranthias furcifer - - - - - - 9 - 9 4.8

Gag Mycteroperca microlepis - - - - - - 3 - 3 1.6

Greater amberjack Seriola dumerili - - - - 2 25 2 - 29 15.4

Gray triggerfish Balistes capriscus - - - - - 8 7 - 15 8.0

Red snapper Lutjanus campechanus - - - - 7 32 46 - 46 45.2

Reef butterflyfish Chaetodon sedentarius - - - - - - 1 - 1 0.5

Scamp Mycteroperca phenax - - - - - 6 6 - 12 6.4

Spanish hogfish Bodianus rufus - - - - - 6 14 - 20 10.6

The biological significance of these differences was best appreciated by plotting mean fish energy

and estimated fish density (with 95% confidence intervals) for each class variable. Mean fish energy

was highest over HI A355 and reached a minimum beyond 30 meters away from the platform; we

assigned a 20 meter area of influence to this site. Mean fish energy declined with distance from the

reef sites and was highest over the platform followed by south, west, east, and north. Mean fish

energy also varied with depth and time of day as it tended to be higher near the surface of the water

column and was higher in the morning.

Target Strength

The relationship between TS and associated class variables was modeled with RBD ANOVAs. TS

was affected by orientation, depth, TOD and all two way interactions. The meaningful part of this

analysis is that fish were, on average, larger over the platform and smallest on the south side. Mean

TS, within 20 meters of HI A355, was -48 dB (equivalent to a 6.7 cm fish); TS ranged from -62 to

-25 dB (1.2 to 108 cm) (Love 1971). Fish size decreased with increased distance from the site. Size

also varied with depth as targets tended to be larger near the surface and decreased in size toward

the bottom. Target size changed with TOD and was greatest in the morning followed by midnight,

dusk, and noon.

Density Estimates

Fish density was calculated based on acoustic volume backscatter and TS (mean target strength /m3

or its proxy value described in Materials and Methods). The results of the density estimates were

basically the same as SV in the previous section, but plots of the mean density values provide actual

density estimates for comparison to this and earlier studies. Density over and away from HI A355

ranged from 0 to 0.55 fish per cubic meter and averaged 0.002 fish per cubic meter within 20 meters
490

of the platform. Mean density varied little with distance. Mean density was slightly higher on the

west side of the platform than the other sides, but there was little difference in mean density among

its four sides. Density also varied with depth and was highest 10 to 20 m above the bottom (Figure

7.50b). Highest density occurred at dusk when compared to noon, morning, and midnight even

though there was little difference among times of day.

Species Composition and Abundance

Species compositions in June 1999 and June 2000 are given in Table 7.40. During both surveys

greater amberjack were the most abundant species. In 1999 greater amberjack made up almost 60%

of the fish community compared to 30% in 2000. Red snapper were the second most abundant

species both years and ranged from 13% in 1999 to 27% in 2000 (Table 7.40).

Table 7.40. Species common names and scientific names along with numbers of individuals by

stratum, totals, and percent composition from visual point counts using video from

a remotely operated vehicle (ROV) from a partially removed platform (High Island

A355), June 1999 and 2000.

High Island A355 June 1999

Common Name Scientific Name 0m 10m 20m 30m 40m 50m 60m 70m Totals % comp

Almaco jack Seriola rivoliana - - - - - 17 - - 17 12.9

Blue angelfish Holacanthus bermudensis - - - - - 7 - - 7 5.3

Creole-fish Paranthias furcifer - - - - - 2 - - 2 1.5

Greater amberjack Seriola dumerili - - - - - 78 - - 78 59.1

Gray triggerfish Balistes capriscus - - - - - 3 - - 3 2.3

Red snapper Lutjanus campechanus - - - - - 17 - - 17 12.9

Scamp Mycteroperca phenax - - - - - 5 - - 5 3.8

Spanish hogfish Bodianus rufus - - - - - 3 - - 3 2.3

High Island A355 June 2000

Common Name Scientific Name 0m 10m 20m 30m 40m 50m 60m 70m Totals % comp

Almaco jack Seriola rivoliana - - 2 7 2 - 2 - 13 6.9

Blackfin tuna Thunnus atlanticus - - 9 - - - - - 9 4.8

Blue angelfish Holacanthus bermudensis - - - 2 5 1 2 1 11 5.9

Creole-fish Paranthias furcifer - - - 11 7 - - - 18 9.6

Crevalle jack Caranx hippos - - 2 1 - - - - 3 1.6

Greater amberjack Seriola dumerili - - - 1 6 22 17 10 56 29.9

Gray triggerfish Balistes capriscus - - - - - - 3 - 3 1.6

Ocean surgeon Acanthurus bahianus - - - 2 - - - - 2 1.1

Red snapper Lutjanus campechanus - - - - 3 12 28 7 50 26.7

Spanish hogfish Bodianus rufus - - - - 18 3 - - 21 11.2

Warsaw grouper Epinephelus nigritus - - - - - - 1 - 1 0.5
491

Total fish abundance at HI A355 within a 20 m area of influence was estimated at 2,850 individuals.

The most abundant fishes at HI A355 were greater amberjack and red snapper . Averaging percent

species compositions for both years, we estimate there were approximately 1,200 greater amberjack

and 500 red snapper followed by 250 Spanish hogfish and 225 creole-fish.

DISCUSSION

This project again demonstrates the utility of dual beam hydroacoustics coupled with visual survey

techniques to study fish assemblages associated with standing platforms and artificial reefs. The

choice of survey sites, which are in close geographical proximity, provided us an opportunity to use

stationary and mobile acoustic survey methods to compare species composition, fish biomass, and

fish densities within and among a standing platform and two artificial reef configurations of retired

oil and gas platforms. Future refinements in the approach to stationary and mobile acoustic studies

will lead to even more accurate assessments of fish habitat. Furthermore, integration of results into

a GIS databases will enable improved management of these resources.

Our results provided direct evidence that fish densities and biomass around standing oil and gas

platforms are the highest per unit area of their artificial sites studied to date. We found fish density

around a standing platform to be greater than the two artificial reef sites. Fish were not only more

abundant around standing platforms, but also they were larger than those found in the open water

habitats. Our results are in support of the findings reported by Stanley and Wilson (2000), that when

a platform is converted into a artificial reef by toppling in place or by partial removal, it loses a

significant portion of the fish community. Most of this “lost” portion is pelagic planktivores such

as blue runner and Bermuda chub. 

Traditional parametric analyses were not used for analysis of mobile acoustic data, due to the large

number of zero values and the problem of autocorrelation that occurs in mobile surveys. The use of

logistic regression in ecological sampling was described by Trexler and Travis (2001) as a nonlinear

way of expressing ecological data. Logistic regression has been shown to be useful with data sets

that have a large number of zero values which are usually not normally distributed. For regression

analysis, the dependent variable was converted into a binomial array of presence/absence of acoustic

reflectance (fish measured as acoustic energy)/m3

 to evaluate the probability or chance of finding

a fish in a given cell. The cell was a one second block (at 2m liner distance) of time divided into 10

m depth strata. Volume backscatter (SV) was used as a dependent variable in performing logistic

regression because SV is the mean measured amount of acoustic energy returned from each acoustic

ping, averaged for a cubic meter of water column. Stanley and Wilson (1997) used fish density

(number of fish/m3) as the dependent variable, but this value is very sensitive to cross-sectional

backscatter also known as sigma (fish size). Sigma accuracy increases with the number of times a

single target is pinged. In our mobile surveys, the chance of hitting a single target, numerous times,

was low. Due to the uncertainty of the accuracy of TS, the accuracy of density becomes uncertain.

This made SV a better proxy for fish presence, hence the primary dependent variable in our models.

If there was a statistically significant affect by a class variable indicated in the logistic regression

analysis, then the procedure was re-run using a no intercept option. The resultant Odds Ratio

Estimates provide a comparison of probabilities of fish occurring within that class variable. The
492

effect of each class variable was visualized by plotting SV and estimated fish density by significant

class variables.

Many factors play an important role in determining fish biomass, density, and species composition

for any fish habitat; certainly oil and gas platforms are no exception. The standing platform, HI

A350, was characterized by the same type of community of fish that Wilson and Stanley (2000)

observed at other structures in similar water depths such as Grand Isle 94. Time of day and depth

stratum affected the fish community as had been reported previously (Stanley and Wilson 2000),

however the density patterns exhibited at different times of day do not follow a predictable pattern

and are likely site-specific. We continue to observe fish density and size being greater near the

surface than the bottom of standing oil and gas platforms. Our results revealed approximately 7,000

fish around HI A350, which is consistent with the estimates of fish communities reported by Stanley

and Wilson (2000, 1997) for platforms in similar water depths, where reports of 10,000 to 20,000

fish inhabiting each of the four oil and gas platforms studied. Species composition at HI 350 was

also similar to that reported by Stanley and Wilson (2000) and included important to recreational

and commercial species such as greater amberjack, red snapper, creole fish, trigger fish, and almaco

jack. Like the results reported herein, Stanley and Wilson (2000) also found a significant pelagic

planktivore community at these high vertical profile sites.

The mobile acoustic surveys of a toppled platform (WC617A) and a partially removed platform

(HIA355) were conducted in 1999 and in 2000. Previous acoustic studies at platforms, as in our

study of HI350 employed a stationary array of transducers. Hence data collection techniques were

different. However the acoustic data are averaged on a per ping basis so data at HI350 in this study

and previous studies by Stanley and Wilson (2000) and Stanley (1994) are comparable to the mobile

acoustic data. 

There was a general pattern at both reef sites of higher probabilities of finding fish in 1999 when

compared to the 2000 survey. We offer no explanation for the between year difference in these

results other than it supports Stanley and Wilson (1997) that fish densities vary seasonally.

Density at the two artificial reef sites ranged from 0 to 0.7 fish/m3. The partially removed platform

had a slightly higher mean fish density than the toppled platform; mean values (within 20m of each

site) of 0.002 vs. 0.0015 respectively. Both sites had highest fish densities near the bottom, which

is opposite the pattern reported at the standing platform. However, the partially removed platform,

HI A355, also had higher estimated densities near the surface resembling fish distribution at a

standing platform. There was little difference in species composition between the two reef

configurations. ROV surveys of HI A355 in June 1999 and in June 2000 indicated that red snapper

and amberjack were the two most abundant species both years, and together they made up over 70

percent of the fish community. Similarly, the survey of WC 617A, conducted in only June 1999,

indicated that greater amberjack, almaco jack, and red snapper were the most abundant species.

Species composition at the two reef sites were similar to species composition at the lower portion

of HI A350 and to previous studies by Stanley and Wilson (1997, 2000). It is of interest that the red

snapper and amberjack populations at the two reef sites were similar in number to the populations

estimated to be at the standing platform in similar water depths. These artificial reef sites, like their

platform predecessors, have significant fishing value since a majority of the species associated with
493

these reef sites are targeted by commercial and recreational fisherman. When a standing platform

is converted into an artificial reef site, it appears that the pelagic planktivores which make up the

greatest biomass is lost; while recreational and commercially important species are retained.

Target strength data revealed information on the size distribution of fishes associated with all these

sites. In general, slightly larger fish are associated with a standing platform, particularly near the

middle water column, compared to a partially removed or toppled platforms, where they are larger

over the reef sites and near the surface (Stanley 1994). The larger species were shown to be pelagic

planktivores and piscivores by Stanley and Wilson (1997).

We found significant effects of orientation and distance with both artificial reefs. The probability

of finding a fish at WC 617A was highest over the platform and within 30 m of the reef; which is

similar to the survey of EI 366 done by Stanley and Wilson (Unpublished report). This is similar to

a reported 16 m area of influence by Stanley (1994) at platforms from 50-100m depths. Platforms

appear to have a finite reef effect that does not extend beyond visual range of the associated species.

The probability of finding a fish at HI A355 was highest around the sides of the platform and within

30 m of the structure, although fish biomass, and therefore density, were highest directly over the

reef site. Stanley and Wilson (Unpublished report) reported higher numbers of fish directly over

another artificial reef (EI 366), and reported the same high fish densities within 30 m of the artificial

reef. The difference in orientation (north, south, east, ands west) at HI A355 could be related to a

section of the jacket being placed roughly 30m away from the partially removed platform on the

southeast side. It is also possible that the small foot print of HI A355 confounded analysis. 

According to survey results from HI A355 and WC 617A, we estimate a loss of approximately 50-80

percent of the fish population when a standing platform is converted into an artificial reef site in 100

m of water. Each artificial reef site harbored approximately 2500 fishes compared to 7000 fishes

around the HI A350 and the 10,000- 20,000 reported by Stanley and Wilson 1998. This decline of

fish numbers was also observed during the survey of EI 313 and EI 367 done by Stanley and Wilson

(Unpublished report). Artificial reef configuration and orientation definitely influence the size of

and species composition of the associated fish community.

Acoustic surveys have been conducted at many artificial reef sites. As mentioned in the introduction,

Stanley and Wilson (2000) conducted a mobile acoustic survey of the Penrod drilling jack-up rig

at EI 313. Although their data were not published, they found approximately 7,000 fish around the

Penrod drilling jack-up rig in EI 313 (Stanley and Wilson 2000). The Penrod drilling rig was located

in shallower water (71.5 m) than these sites reported herein and had a more complex inner-structure

of decking and cross-member material; this more complex structure likely influenced fish

populations. For example, five sections of the Tenneco II platform were deployed off of southern

Florida, the solid deck portion of the platform did not contain the diversity and abundance of fishes

found on the grated surface section of the platform deployed 30m away (Seaman et. al. 1989). The

grating likely afforded more hiding places for small fishes, thereby increasing diversity of small

species and also food supply for predatory species. Also, openings in the grated surface would

permit access to the upper surface for animals living in protected areas under the deck (Seaman et

al 1989). It is likely that the greater number of fish around the Penrod drilling rig was due to the

different type of material such as decking and shallower water depths. Studies suggest that optimal
494

artificial reef configurations exist, but vary, depending on the target species (Stanley and Wilson

1990).

Our results again emphasize the variability in abundance, size distribution, and species composition

of fishes associated with petroleum platforms, particularly those that have been configured as

artificial reefs. Results of previous studies have been well documented in earlier reports done by

Stanley (1994) and Stanley and Wilson (2000), and in general this variability is associated with both

temporal, spatial, and to some extent environmental variables. This research continues to support

the working hypothesis that platforms do make useful artificial reefs since they tend to support a

population of fish that can be 10 to over 1000 times greater in density than the adjacent sand and

mud bottom habitats. 

Completion of this research has provided quantitative data on the effect of vertical profile on fish

abundance, assessed the effectiveness of retired platforms sited as artificial reefs, and presented the

differences in abundance and species composition among sites. Since the reef sites are of similar age

and size, and are located within a radius of 48 km, comparison of the production platform and the

partial removal with the toppled platform has provided valuable insight into the effect of platform

configuration on the assemblage of fishes while minimizing confounding effects.

To date over 150 retired petroleum platforms from Texas to the Atlantic coast of Florida have been

converted to artificial reefs. A variety of removal techniques and placement configurations have

been employed in siting these reefs. While numerous qualitative studies documenting the

colonization and relative abundance of organisms associated with production platform have been

undertaken, it has proven difficult to conduct quantitative studies at artificial reefs; consequently,

little was known regarding the biotic communities associated with these artificial reefs.

Development of artificial reefs has been advocated by all levels of government and within the Reef

Fish Fishery Management Plan of the Gulf of Mexico Fishery Management Council (GMFMC

1989). Several research needs and goals have been outlined including the following: encouraging

general research on the effects of artificial reefs, improving the quantitative assessment techniques

used to describe artificial reef communities, monitoring biological changes at reef sites, assessing

the importance of fish attraction versus fish production, and quantifying the relationships between

reef fish production and habitat.

REFERENCES

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Assessing Community Structure of Coral Reef Fishes. NOAA Technical Report NMFS 41. 15

pp.

Bohnsack, J.A., D.L. Johnson, and R.F. Ambrose. 1991. Artificial habitats for marine and freshwater

fisheries. Ecology of Artificial Reef Habitats. Academic Press. New York, New York. 61-108

pp. 

Doherty, P.J. and D. McB. Williams. 1988. The Replenishment of Coral Reef Fish Populations.

Oceanography and Marine Biology. 26:487-551 pp.
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Garrison, L.P., W. Michaels, J.S. Link, and M.J. Fogarty. 2000. Predation Risk on Larval Gadids

by Pelagic Fish in the Georges Bank Ecosystem. I. Spatial overlap associated with hydrographic

features. Canadian Journal of Fisheries and Aquatic Sciences. 57:2455-2469.

GMFMC (Gulf of Mexico Fisheries Management Fisheries Council). 1989. Amendment 1 of the

Reef Fisheries Management Plan for the Fisheries Resources of the Gulf of Mexico. GMFMC.

Tampa FL. 420pp.

Love, R.H. 1971. Dorsal Aspect Target Strength of an Individual Fish. Journal of Acoustic Society

of America. 62:1397-1403.

Menge, B.A. and J.P. Sutherland. 1987. Community Regulation: Variation in Disturbance

Competition and Predation in Relation to Environmental Stress and Recruitment. American

Naturalist. 130:730-757.

Ott, L. 1982. An Introduction to Statistical Methods and Data Analysis. 2nd Edition. Duxbury Press.

Boston, Mass. 774 pp.

Parker, Jr., R.O. D.R. Colby, and T.P. Willis. 1983. Estimated Amount of Reef Habitat on a Portion

of the U.S. South Atlantic and Gulf of Mexico Continental Shelf. Bulletin of Marine Science.

33:935-940 pp.

SAS Institute Incorporated. 2000. SAS user's guide: Statistics. Version 8. SAS Institute. Cary, NC.

1290 pp. 

Seaman, W. Jr. and Antony C. Jenson. 2000. Purposes and Practices of Artificial Reef Evaluation.

In Artificial Reef Evaluation with Application to Natural Marine Habitats. William Seaman, Jr.,

ed. CRC Press, Boca Raton, p. 1-19.

Seaman, W. Jr., William J. Lindberg, Carte R. Gilbert and Thomas K. Frazer. 1989. Fish Habitat

Provided by Obsolete Petroleum Platforms off Southern Florida. Bulletin of Marine Science.

44(2): 1014-1022.

Stanley, D.R. 1994. Seasonal and Spatial Abundances and Size Distribution Associated with a

Petroleum Platform in the Northern Gulf of Mexico. Dissertation. Louisiana State University.

Stanley, D.R. and C.A. Wilson. 1990. A Fishery-Dependent Based Study of Fish Species

Composition and Associated Catch Rates Around Oil and Gas Structure off Louisiana. Fishery

Bulletin 88(4):719-730.

Stanley, D.R. and C.A. Wilson. 1991. Factors Affecting the Abundance of Selected Fishes Near Oil

and Gas Platforms in the Northern Gulf of Mexico. Fishery Bulletin 89(1):149-159. 

Stanley, D.R., and C.A. Wilson. 1995. Detection of the Effect of Scuba Divers on Fish Density and

Target Strength Utilizing Dual-Beam Hydroacoustics. American Fisheries Society. 124:946-949.
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Stanley, D.R., and C.A. Wilson. 1996. Abundance of Fishes Associated with a Petroleum Platform

as Measured with Dual-Beam Hydroacoustics. ICES Journal of Marine Science. 53: 473-475.

Stanley, D.R., and C.A. Wilson. 1997. Seasonal and Spatial Variation in Abundance and Size

Distribution of Fishes Associated with a Petroleum Platform in the Northern Gulf of Mexico.

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Stanley, D.R., and C.A. Wilson. 1998. Spatial Variation in Fish Density at Three Petroleum

Platforms as Measured with Dual-Beam Hydroacoustics in the Northern Gulf of Mexico.

Proceedings 1997 AFS Artificial Reef Symposium, American Fisheries Society, Monterey CA.

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Stanley, D.R. and C.A. Wilson. 2000. Variation in the density and species composition of fishes

associated with three petroleum platforms using dual beam hydroacoustics. Fisheries. 47: 161-

172.

Stanley, D.R., and C.A. Wilson. Unpublished. Survey of the Fisheries Resources at the Toppled

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497

SESSION 8: 

EVALUATION OF NATURAL AND/OR

ARTIFICIAL REEF PRODUCTIVITY I

Moderators: Kathy Scanlon

Quenton Dokken

Date: October 26, 2000

Presentation Author/Affiliation

Zooplanktivory by Blue Runner: An

Energetic Subsidy to Gulf of Mexico Fish

Populations at Petroleum Platforms

Sean F. Keenan

Department of Oceanography and Coastal

Sciences

Louisiana State University

Mark C. Benfield

Coastal Fisheries Institute

Louisiana State University

Comparison of Plankton and Light-Trap

Methodologies for Sampling Larval and

Juvenile Fishes Associated with Offshore

Petroleum Platforms and a Coastal Jetty

off Louisiana

Frank Hernandez

Department of Oceanography and Coastal

Sciences

Center for Coastal Energy and Environmental

Resources

Louisiana State University

Richard Shaw

Coastal Fisheries Institute

Louisiana State University

Occurrence and Pelagic Habitat of Reef

Fish Larvae in the Gulf of Mexico

David Hanisko

Joanne Lyczkowski-Shultz

National Oceanic and Atmospheric

Administration

National Marine Fisheries Service

Southeast Fisheries Science Center

Comparison of the Fisheries Value of

Platforms Used as Artificial Reefs:

Standing, Toppled, and Partially Removed

Aaron Pierce

Charles A. Wilson

Department of Oceanography and Coastal

Sciences and

Coastal Fisheries Institute

Louisiana State University

(continued on next page)
498

Presentation Author/Affiliation

A Hydroacoustic Assessment of Fish

Density at the Flower Garden Banks with

Emphasis on the West Flower Garden

Bank

Mark W. Miller

Coastal Studies Institute 

Louisiana State University

Charles A. Wilson

Coastal Fisheries Institute and

Department of Oceanography and Coastal

Sciences

Louisiana State University
499

ZOOPLANKTIVORY BY BLUE RUNNER: AN ENERGETIC SUBSIDY TO GULF

OF MEXICO FISH POPULATIONS AT PETROLEUM PLATFORMS

Sean F. Keenan

Department of Oceanography and Coastal Sciences

Louisiana State University

Mark C. Benfield

Louisiana State University

Coastal Fisheries Institute

ABSTRACT

The feeding habits of blue runner, Caranx crysos (Carangidae), were evaluated near offshore

petroleum platforms in the northern Gulf of Mexico (GOM). Fish and plankton samples were

collected at a mid-shelf platform located west of the Mississippi delta (Grand Isle 94B) from June

to August 1996 and at a mid-shelf platform (Main Pass 259A) located east of the delta from June

to September 1999. Meso- and macro-zooplankton comprised a large proportion of blue runner diets

at the two platforms. Decapod crustaceans, chaetognaths, amphipods, other invertebrates as well as

small fishes made up the majority of prey items. Variations in the diet over the sampling periods

may have been due to shifts in predator preference and prey availability. Stomach fullness revealed

that blue runner fed most intensely during night and pre-dawn hours with lower levels of feeding

during the day. Blue runner appeared to select for larger sized prey relative to size distributions

found in our plankton samples. Our hypotheses are that platforms are acting as large plankton

accumulators through hydrodynamic and illumination effects, which provide blue runner with food

and also extends foraging time.

INTRODUCTION

There are over 4,000 offshore petroleum platforms in the northern GOM (Stanley and Wilson 1996),

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

(Parker et al. 1983). The petroleum platforms in the same region have been estimated to provide

roughly 5,000 km2

 of hard substratum (Kasprzak 1998), substantially increasing available reef-like

habitat. This large amount of vertical relief, termed vertical benthos, extends into the photic zone

and serves as a reef habitat for encrusting organisms and many fish species. The platforms in the

northern GOM have been described as the largest unplanned artificial reef complex in the world

(Stanley et al. 1998). High concentrations of fishes around these structures have stimulated attempts

to quantify the distribution and abundance of platform fish assemblages. Stanley and Wilson (1996,

1998, 2000) have utilized hydroacoustics to estimate densities and distributions of fishes associated

with platforms. These latter surveys confirmed the high densities of fishes and estimated that 10,000

to 30,000 fishes were associated with 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). Do platforms
500

merely attract fish from existing natural reefs to an area where they are susceptible to elevated

fishing pressure, or do the platforms serve as functional productive habitat capable of supporting

their high fish biomass? This issue remains an important question in evaluating the relationship

between platforms and fishes. While data exists on densities and distribution of platform-associated

fish, relatively little is known of how these populations are sustained. Understanding the trophic

ecology of platform associated fishes may help us to evaluate the degree to which platform

production is transferred to fish and to develop strategies for converting decommissioned platforms

into productive artificial reefs.

One of the most common pelagic fish species in the GOM is the blue runner, Caranx crysos. This

coastal pelagic species is found in the western Atlantic from Nova Scotia to Brazil (McKenney et

al. 1958), throughout the eastern Atlantic and Mediterranean and has recently been recorded in

British waters (Swaby et al.). This medium-sized fish (common to 350 mm fork length (FL)) may

be found singly or more commonly in large schools in open waters. Blue runner appear to be the

most abundant species in the surface waters around offshore platforms. Stanley and Wilson (2000)

reported that blue runner numerically constituted up to 94% of the fishes found at a mid-shelf

platform off Louisiana.

Blue runner are likely major dietary components of larger predatory fish associated with platforms

(e.g. barracudas, groupers, cobia and other large jacks) as well as predators that frequently visit

platforms (e.g. mackerals, billfish and tunas). Blue runner are likely important trophic links in

platform food webs; however, relatively little is known about the diets of blue runner themselves.

Some data exist on feeding habits of larval and juvenile blue runner, but 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 plankton feeders feeding primarily on copepods.

Larger juveniles of the genus Caranx were noted to have larger organisms in the diets such as hyperiid amphipods, pontellid copepods, and juvenile natantida. Randall (1967) recorded the stomach

contents of 17 mature (190-520mm 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) reportedly contained 40% planktonic organisms with the remaining contents being fish. The

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

waters, were noted to contain anchovies and two mantis shrimp (Squilla empusa) (Christmas et al.

1974).

Observations of adult blue runner apparently feeding on zooplankton at night beneath a mid-shelf

petroleum platform were the motive for the research reported in this paper. Our research was

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

Louisiana. The objectives of our study were to (a) describe the food habits of and monthly

variability in the diet of C. crysos over the summer; (b) evaluate the diel periodicity in feeding; and

(c) compare sizes of prey in the diets of blue runner with size distributions of prey in the

environment.
501

 METHODS

Study Sites

The diets of Caranx crysos were investigated at two offshore platforms located west and east of the

Mississippi delta. Grand Isle 94B (GI94B) (28.5267oN, 90.0983oW) is a mid-shelf platform located

west of the Mississippi River in 63 m of water. Samples were collected from Grand Isle 94B during

28-30 June, 28 July, 1 August, and 12-15 August 1996. Main Pass 259A (MP259A) (29.2833o

N,

88.0333oW) is a mid-shelf platform located east of the Mississippi River standing in approximately

130 meters of water. Monthly sampling trips were made to Main Pass 259A during 11-14 June, 9-12

July and 24-27 September 1999. 

Fish Sampling

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

using hook and line with artificial lures. Mass, length, sex, and time of capture were 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. Stomachs were removed by severing the esophagus and

the duodenum below the pyloric sphincter, injected with 95% ethanol, and stored in ethanol

preservative until they were transported to our laboratory.

Enumeration of Stomach Contents

Stomach contents were examined with a microscope and identified to the following taxonomic

categories: fish, decapod/stomatopod, hyperiid amphipods, chaetognaths, other invertebrates, and

unidentified material. The number of prey in each category were counted and wet masses recorded

to the nearest milligram. These parameters provided numerical and mass 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 0.28 m2

 ring

net equipped with a 333 mm 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 minutes from 17:45-

18:15 hours on 12 June 1999. Plankton were preserved in 5% formalin for 24 hours before being

transferred to 95% ethanol. Samples were sorted and classified into the same groups as for the

dietary analysis.

Data Analysis

The Index of Relative Importance (IRI) was used to evaluate monthly variation in blue runner

feeding. Relative importance (IRI) (Pinkas et al. 1971; Cortes 1997) values were estimated for each

prey category (i) using

IRIi = (Ni + Gi) x Fi (1)
502

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

gravimetric proportion (%) of the ith prey item and Fi 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. Percent IRIs for each prey item were then converted to %IRI

using

%IRI = IRIi / ∑ IRI x 100 (2)

Size Selection

Size selection was evaluated from the Main Pass 259A platform during the June trip by comparing

zooplankton collected from surface currents to those found in blue runner stomachs. After

identification and enumeration, photographs were taken of all prey items and samples from the net

using a digital camera 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 relationship between the lengths of body parts and total length (Table 8.1) was used to estimate

their original dimensions. Zooplankton from the net sample were binned into 0.25 millimeter size

classes and compared with prey from the stomach of four fish collected within an hour of the net

sample. These distributions allowed a qualitative evaluation of the size-selection for prey of

different sizes.

Table 8.1. Regressions fitted for three prey categories commonly consumed by blue runner. These

relationships were used to reconstruct whole body lengths (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 (EL) B.L. = e1.523 x EL1.01 0.92

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

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

Conover (1994). Stomach fullness was computed for each fish by dividing the wet weight of all prey

items in each stomach by the wet weight of the empty stomach. A gut 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. It was not possible to capture blue runner from all hours

of the day on any single trip. A composite pattern of the daily feeding periodicity of blue runner was

developed by grouping all fish collected at each platform into two-hour time bins.
503

RESULTS

The stomachs of 37 of 38 fish collected from Grand Isle 94B in 1996 contained prey items, while

79 of the 88 blue runner from Main Pass 259A in 1999 contained prey items. Blue runner ranged

in size from 255 Ð 445 mm FL at the Grand Isle platform and 165 Ð 499 mm FL at the Main Pass

platform. This size range indicates most were at or approaching sexual maturity (Goodwin and

Finucane 1985). Further, many fish contained developing or mature gonads.

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

platforms (Figure 8.1). Zooplankton constituted approximately 86% numerically of the identifiable

diet contents at Grand Isle 94B in 1996 and 94% numerically at Main Pass 259A in 1999.

Zooplankton were dominated by decapod and stomatopod crustaceans and chaetognaths. When diets

were evaluated on the basis of prey mass, zooplankton made up 15% of the diet at Grand Isle 94B

and 18% of the diet at Main Pass 259A. The large proportion of invertebrates at Main Pass 259A

was contributed primarily by cephalopods. The stomachs of fish from both platforms contained

unidentifiable amorphous tissue which constituted 33% and 8% of the overall diet at Grand Isle 94B

and Main Pass 259A, respectively.

The diets of blue runner changed over the course of the summer, based on shifts in their IRI values.

Adult and larval forms of decapod and stomatopod larvae were a substantial component of the diet

at Grand Isle 94B during June and July (Figure 8.2). In August, the IRI indicates that fish, primarily

Bregmaceros spp., replaced decapods and stomatopods in the diet. Chaetognaths and a variety of

hyperiid amphipods contributed to the diets of blue runner at Grand Isle 94B in June and declined

in importance over the summer. Fish and decapod/stomatopods were both important in the diets

during June at the Main Pass platform (Figure 8.2). Unlike the pattern observed at Grand Isle 94B,

decapods and stomatopods continued to predominate in the diet during July and September at Main

Pass 259A. Fish declined in importance over the summer, while other invertebrates (primarily

cephalopods) assumed greater importance during July.

Blue runner appear to feed at low levels throughout the day and exhibit a peak in feeding activity

in the pre-dawn and early morning hours (Figure 8.3). They are also capable of feeding after dark

at levels comparable to those observed during the day. The number of fish collected at Grand Isle

94B 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 Main Pass 259A where a larger number

of fish produced a better estimate of feeding periodicity. The nocturnal peak feeding at Grand Isle

94B was based on a single fish; however, the presence of a feeding pulse beginning sometime after

midnight and extending past dawn was supported by the data from Main Pass 259A (Figure 8.3).

Blue runner appear to preferentially select for large zooplankton and in some cases, the length of

prey exceeded the size ranges that were present in our net sample (Figures 8.4 and 8.5). The size

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

this group in the net and extended past the upper range collected by the net (Figure 8.4). Small

zooplankton such as crab megalopae and crab zoea were absent from or rare in stomach. Similarly,

blue runner appeared to consume the largest size fractions of hyperiid amphipods present in the net

and also foraged on amphipods larger than those collected in the net.
504

Figure 8.1. Numerical proportion (upper row) and gravimetric proportion (bottom row) 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 (Grand Isle 94B) and June, July and September 1999 (Main Pass

259A).
505

Figure 8.2. Monthly variation in Index of Relative Importance (IRI) for dominant prey taxa from

the two platforms.
506

Figure 8.3. Stomach fullness values for blue runner collected over the summer at GI94B (top)

and MP259A (below). Fish were pooled over all months and binned into two hour

time blocks. The number of fish caught in hour block appears above the bars. Error

bars indicate ± 1 S.E. on the mean.
507

Figure 8.4. Length frequency distributions for decapods taken from surface plankton net and

stomachs of concurrent captured blue runner (n=4) during June 1999.
508

Figure 8.5. Length distributions of hyperiid amphipods collected from a surface plankton net and

from blue runner stomachs in June 1999 at Main Pass 259A.
509

DISCUSSION

Zooplankton appear to comprise a large amount of the diets of blue runner during the summer

months. There appeared to be a seasonal 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 both

phenomena. While the dietary patterns displayed by blue runner differed among 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 Grand Isle 94B in August may have been a response to

a local increase in the abundance of favorable prey. 

The contribution of zooplankton to the diet may be underestimated due to the rapid digestion rates

of these organisms. Gut evacuation rates increase with temperature in temperate fish (Popova and

Sierra 1985; Buckel and Conover 1996). Increased digestion rates in the warm surface waters of the

Gulf may have rapidly rendered the zooplankton unidentifiable and caused an underestimate of their

gravimetric contribution to the diet. Haywood (1995) examined the digestion rates of penaeid

postlarvae by a small carangid Monocanthus chinensis and 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 mass. 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.

Blue runner appear to consume relatively larger zooplankton. We could not conduct a quantitative

evaluation of size-based electivity because many of the largest zooplankton that typically appeared

in blue runner stomachs were able to avoid our passively-fished net. Hyperiid amphipods and the

larger decapods are relatively strong swimmers and their absence from the net was likely due to

avoidance. Large chaetognaths were also common in both the stomachs and our net; however, they

were usually fragmented in the gut and we were not able to develop a reliable allometric regression

to reconstruct their intact lengths from fragments. Small zooplankton such as ostracods, pteropods

and copepods were present in the net samples but absent from stomachs, further suggesting that blue

runner were actively selecting for large prey. Given that our size selection data are based on a single

net and just four fishes, it is clear that further work using different sampling gear will be required

to address the issue of size selection more rigorously.

At both platforms there was evidence that blue runner feed during the night and begin their

maximum feeding activity after dark. This phenomenon is unusual and is probably apparent only

in the vicinity of illuminated petroleum platforms because blue runner are visual predators. Other

comparably-sized, zooplanktivorous visual predators such as Atlantic mackeral Scomber scombrus

reduce feeding rates with diminishing light intensity (Macy et al 1998). Most manned and the larger

satellite platforms in the GOM are equipped with large floodlights that illuminate the surrounding

waters. This artificial light field appears 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. We did not

quantify the light field around platforms because we were restricted to the platforms; however, based
510

on observations of fishing lures and other objects in the water, the illuminated volume of water is

likely restricted to the near-surface region and a radius of 50-100m around the platform.

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

between the platform and the pelagic species. Most of the plankton in the diet were from

holoplanktonic or meroplanktonic groups. Hyperiid amphipods are known for their association with

gelatinous zooplankton (perhaps one of the keys), but not with fouling communities. Little is known

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

encounter one in the pelagic zone. 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. 1998).

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. Flotsam, Sargassum, and foam frequently accumulate beneath platforms. This

accumulation is probably due to a reduction in the current velocity and an increase in flow

complexity as the prevailing current interacts with the platform. Forristall (1996) measured the

degree of current blockage near the Bullwinkle (GC65) platform with acoustic Doppler current

profilers arranged in an outward looking horizontal plane at 18 m depth. His findings indicated that

the mean current velocity inside the platform structure could be about 80% that unimpacted upcurrent velocity and that reductions were even lower directly behind dense conductor casings.

Decreases in current velocities coupled with an increase in eddy formation could allow zooplankton

to extend residence time beneath a platform, which would lead to an increase in the concentrations.

The lights of manned platforms may further increase zooplankton concentrations and enhance the

effect due to currents at night. Many zooplankton, such as amphipods, display positive phototaxis

and actively swim towards light. Light traps are commonly used as collection gear for animals

around platforms by colleagues (Ditty et al. 1998) and the same groups that predominate in blue

runner stomachs (decapods, hyperiid amphipods, chaetognaths and small fish) are the dominant

constituents of light trap samples. The combined influence of the artificial light field and the current

alterations may cause platforms to act as large, passive zooplankton accumulators. Thus the

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

continuously. Such conditions may explain how such large densities of blue runner can be sustained

by the waters around platforms.

To address these hypotheses, we are in the process of analyzing data from research cruises taken

during the summer of 2000. Plankton net tows from a vessel were used to evaluate the zooplankton

distribution on the up-current and down-current sides of different sized platforms. Hydroacoustics

were used to quantify the flow field around platforms and to examine patterns of backscatter from

zooplankton. If plankton are accumulating beneath the structure, we would expect to see lower

densities on the down-current side relative to open water densities. Blue runner were collected both

around platforms and in open waters away from platforms. The results from these studies will likely

provide more information on the trophic linkages between blue runner and zooplankton at offshore

platforms.
511

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COMPARISON OF PLANKTON NET AND LIGHT-TRAP METHODOLOGIES FOR

SAMPLING LARVAL AND JUVENILE FISHES ASSOCIATED WITH OFFSHORE

PETROLEUM PLATFORMS AND A COASTAL JETTY OFF LOUISIANA

Frank J. Hernandez, Jr.

Department of Oceanography and Coastal Sciences

Center for Coastal Energy and Environmental Resources,

Louisiana State University

Richard F. Shaw

Coastal Fisheries Institute

Louisiana State University

ABSTRACT

While sampling ichthyoplankton associated with artificial structures across the continental shelf (3-

230 m depth) of the northern Gulf of Mexico (GOM), we compared passive, 60 cm diameter

plankton net and light-trap methodologies at three offshore petroleum platforms (continental shelf

slope, mid-shelf, and inner shelf) and a 1m x 1m plankton pushnet and a light-trap at a coastal jetty.

Clupeiform fishes dominated collections for all gears (59%-97% of the total catch for nets and lighttraps combined). Plankton nets collected more fish than light-traps at the shelf slope and inner

platforms (plankton net vs. light-trap: 1,404 vs. 659; 3,076 vs. 12,474; and 1,689 vs.1,193), and the

pushnet collected more fish than the light-trap (33,1477 vs. 849) at the jetty. Plankton nets collected

individuals from more families than light-traps at the shelf slope and mid-shelf platforms (plankton

net vs. light-trap: 43 vs. 35; 38 vs. 35; and 32 vs. 32), but only collected more taxa (genus level) than

light-traps at the shelf slope platform (plankton net vs. light-trap: 56 vs. 47; 75 vs. 78; and 50 vs.

56). At the jetty, the pushnet collected more families (39 vs. 19) and taxa (77 vs. 34) than the lighttrap. Results of Kolmogorov-Smirnov length-frequency comparisons of fish collected in plankton

nets vs. light-traps indicated light-traps generally overlapped the net’s smaller sizes, but also

collected significantly larger individuals. At the jetty, greater overlap in size distributions was

observed for comparisons of the pushnet and light-trap. Schoener’s Index of Niche Overlap values

for light-trap and plankton net samples indicated low similarity between gears at two platforms

(0.32-0.38), but higher similarity (0.63) at the inner shelf platform which was most dominated by

clupeiforms. At the jetty, pushnet and light-trap samples had relatively high taxonomic similarity

(0.61). Few significant differences were detected between Shannon-Weiner Diversity Indices for

platform light-trap and plankton net samples, while at the jetty, pushnet samples had significantly

higher diversity than light-trap samples. When significant differences in mean total densities and

mean total CPUEs were found between new vs. full moon phases, four out of five instances had

greater new moon catches. 

INTRODUCTION

Most marine fishes, particularly structure-associated or reef-dependent fishes, have a pelagic early

life history stage (Moser et al. 1984; Leis 1991). Previous studies have indicated that larval source,
515

supply, recruitment, and settlement patterns can greatly influence the adult population dynamics of

reef fish on both natural (Victor 1983 1986; Sponaugle and Cowen 1996) and artificial reefs (Lukens

1981; Stephens et al. 1994). In response to the need for crucial information on reef fish early life

history stages, several methods have been developed to collect larval and juvenile fishes in a variety

of environments. Many reef fish juveniles are at some time associated with structurally-complex

habitats, either while in a nursery area (mangroves, seagrass meadows, oyster reefs) or on the reef

environment itself. While towed sampling gears are effective in open waters, these methods are

usually not suitable for shallow or structurally complex habitats (Brogan 1994).

Different methodologies have been developed to collect fish early life history stages in complex

environments including plankton pumps (Taggert and Legget 1984; Brander and Thompson 1989),

visual censuses (Kingsford and Choat 1989), moored channel nets (Keener et al. 1988; Shenker et

al. 1993), larval purse seines (Murphy and Clutter 1972; Choat et al. 1993), and diver-steered

plankton tows (Marliave 1986; Brogan 1994). Other methods have used light sources to aggregate

fish for collection and include lighted purse seines (Choat et al. 1993), light lift-nets (Dennis et al.

1991; Rooker et al. 1996) and light-traps of various designs (Doherty 1987; Thorrold 1992; Choat

et al. 1993; Brogan 1994; Sponaugle and Cowen 1996; Hernandez and Lindquist 1999; Hickford

and Schiel 1999; Reyns and Sponaugle 1999). All of these methods have different biases,

advantages, and disadvantages and should be chosen to best suit the environment being sampled and

the questions being addressed.

To date, few studies have investigated the ichthyoplankton assemblages associated with oil and gas

platforms in the northern Gulf, in part due to the difficulties in sampling within the complex, mostly

vertical infrastructure of the platforms. Although Gallaway (1998) calculated that oil and gas

platforms in the northern Gulf provided 11.7 km2

 (or 4.0%) of the total “reef” habitat. The fact that

platforms represent vertical artificial substrate that extends from the bottom to the surface (photic

zone), regardless of location and depth, increases their significance (Parker et al. 1983). These and

other artificial structures (e.g., jetties, breakwaters) could represent significant habitats for reef fish,

since the northern Gulf is dominated by a mud/silt/sand bottom with little relief or hard-bottom

habitat. In our attempt to characterize the across-continental shelf ichthyoplankton communities

associated with artificial structures (three offshore oil and gas platforms and a coastal jetty) in the

northern Gulf, we used a variety of gear types to sample the widest range of taxa, size classes, and

cohorts available. This paper reports the results of gear comparisons between a passive plankton net

and light-trap used at the petroleum platforms, and between a bow-mounted, plankton pushnet and

light-trap (the same design) used at the coastal jetty. In our comparisons, we examined the taxa

collected by the different gears, the similarity and diversity of the catches, as well as the size

selectivities of the gears. Our findings will be useful to those designing similar sampling efforts for

larval and juvenile fishes in the vicinity of complex structures. 

STUDY SITES

Data collection and analyses focused on three oil and gas platforms in the northern Gulf and at a

low-salinity, coastal rock jetty environment, which provided a far-field, non-platform site endmember that was equally complex structurally and represented another artificial reef-type, hardsubstrate habitat. Site selection for the three study platforms (west of the Mississippi River Delta)
516

was based upon the work of Gallaway et al. (1980), Gallaway (1981), and Continental Shelf

Associates (1982) who reported that nekton communities around platforms could be categorized by

water depth in the northern Gulf. Three communities were characterized: a coastal assemblage

(water depths <27m), an offshore assemblage (water depths 27 to 64 m), and a bluewater/tropical

assemblage (water depths >64m). The platforms selected and the jetty site encompass all three

zones. Mobil’s Green Canyon (GC) 18, which lies in about 230 m of water on the shelf slope

(27°56'37"N, 91°01'45"W), was sampled monthly during new moon phases over a two to three night

period during July 1995-June 1996. Mobil’s Grand Isle (GI) 94B, which lies in approximately 60

m of water at mid-shelf (28°30'57"N, 90°07'23"W), was sampled twice monthly during new and full

moon phases over a three night period during April-August 1996. In addition, during May, extra

samples during the first quarter and third quarter moon phases were collected, but due to inclement

weather, full moon collections were cancelled. Exxon’s South Timbalier (ST) 54G, which lies in

approximately 20 m of water on the inner shelf (28°50'01"N, 90°25'00"W), was sampled twice

monthly during new and full moon periods in during April-September, 1997. The stone rubble jetties

(2-3 m depth) at the terminus of Belle Pass, a major shipping channel near Fourchon, Louisiana (N

29 03.90, W 90 13.80), were also sampled over a two-night period in 1997 simultaneously with the

sampling of ST 54.

METHODS

Sampling protocols are described in detail elsewhere (Hernandez et al. this volume). In general,

passive plankton nets (60-cm diameter; 333mm mesh dyed green) were used to collect ichthyoplankton at the three platform sites, both at depth (10-20 m for 10-20 min, set and retrieved closed) and

near surface (1-2 m for 10-15 min) within the platform structure. Quatrefoil light-traps were deployed for 10 minutes at depth and near surface within the platform structure, and in addition were

also floated downstream (approximately 20 m) from the platform for off-platform collections. Both

the subsurface and off-platform light-traps were deployed with the light off until the sampling depth/

location was reached, fished, and then retrieved with the light off. At Belle Pass, light-traps were

fished along the jetty walls, as well as a bow-mounted plankton pushnet (1 m x 1 m; 1000 :m mesh

net dyed green; 3-5 min samples). 

The quatrefoil light-trap (Figure 8.6) was modified from Floyd et al. (1984) and Secor et al. (1993).

The main modifications are as follows: acrylic tubes in the main body of the trap were enlarged to

15.24 cm (6") outer diameter; the collection assembly at the bottom of the trap was replaced with

short conical plankton-net (202 μm)and cod-end assembly; four vertical, stainless steel bars were

added to the corners of the trap for additional support; the light source was a Brinkman Starfire II

12-volt halogen fishing light (250,000 candlepower); for surface samples, power was supplied

through an umbilical cord by a 12-volt marine battery located on the lower deck of the platform; for

subsurface collections, either an umbilical cord connected to a 12-volt battery or a submersible

battery was used; the battery was made by placing a 7.0 amp/h rechargeable sealed lead battery in

a 1/4" thick PVC tube with a watertight connector on one end and a complimentary pig-tail on the

end of the cable supplying power to the light.

Due to the very large numbers of clupeiform (Clupeidae and Engraulidae) fishes collected,

particularly in light-trap samples, statistical analyses were run without these taxa, unless otherwise
517

Figure 8.6. Specifications for the modified quatrefoil light-trap used in this study.
518

noted. Clupeiform fishes are seldom the taxa of interest in studies of hard substrate habitats, i.e.,

(artificial) reefs, and their abundances tend to overwhelm the trends of other taxa (Choat et al.

1993). All ANOVA, Tukey’s Studentized Range Tests, and Student’s t-tests were run with SAS

version 6.12 (SAS 1989).

Studentized t-tests ("=0.05) were used to compare overall plankton net densities between locations

(subsurface and surface) within the GC 18, GI 94, and ST 54 sites. Light-trap CPUEs were

compared between locations (subsurface, surface, and off-platform) within each of the platform sites

using an ANOVA model with gear as a main effect. Tukey’s Studentized Range tests were used to

determine which light-trap collections were significantly different. Before testing, plankton net

densities were log transformed (log10(x+1)) to conform to normality and homogeneity of variances.

Analyses on light-trap CPUEs were run on ranked-transformed data.

Kolmogorov-Smirnov (K-S) length-frequency analyses ("=0.05) were performed for selected

species from GC 18, GI 94, ST 54, and Belle Pass to determine if there were any significant

differences between the size distribution of fish collected with light-traps vs. plankton nets (Sokal

and Rohlf 1981). Taxa from each platform site and Belle Pass were chosen for these analyses if at

least 10 individuals were collected by each gear type. All K-S analyses were performed using

SYSTAT version 4 (SPSS 1999). 

Lunar periodicity (full and new moon) was examined for plankton net and light-trap samples

collected at GI 94, ST 54, and Belle Pass using Student’s t-tests ("=0.05). An ANOVA model and

Tukey’s Studentized Range tests were used to analyze the densities and CPUEs of samples collected

in May of 1996 at GI 94 ( third quarter, new, and full moon periods). 

Schoener’s Index of Niche Overlap (Schoener 1970) was calculated for comparisons of fish

collections within the platform structure (surface net and surface light-trap) and farfield collections

(off-platform light-trap) and total net collections vs. total light-trap collections. This same gear

analysis was performed to compare the similarity of light-trap and pushnet collections at Belle Pass.

Only fish identified to at least the genus level were used in the analyses. Shannon-Weiner diversity

indices (Magurran 1988) were calculated for each sample collected at GC 18, GI 94, ST 54, and

Belle Pass. Differences in diversity between gear types at each site were analyzed with ANOVA

models using gear as a main effect. Post-ANOVA tests (Tukey’s Studentized Range, "=0.05) were

used to determine which gear types were significantly different. Only fish identified at least to the

level of genus were included in these analyses. Also, since the intent of the similarity and diversity

indices was to characterize the taxonomic assemblages sampled by each gear type, clupeiform fishes

were included in these analyses.

RESULTS

Overall Abundances

At GC 18, plankton nets and light-traps collected 1,404 and 659 fish, respectively, with a mean total

density of 74.6 fish/100m3

 and a mean total CPUE of 2.1 fish/10 min (Table 8.2). Plankton nets

collected fish from more families than light-traps, 15 of which were exclusively collected with
519

Table 8.2. Number of samples, total individuals, families, and taxa collected at each site with a

passive plankton net, light-trap, and plankton pushnet. Mean total densities (nets) or

CPUEs (light-traps) are also provided for each gear at each site. Values in parentheses

indicate the number of families or taxa (at least to genus level) unique to that gear type.

Gear Type

Number of

samples

Number

of fish

Mean Total Density

and CPUE

Number

of families

Number

of taxa

Green Canyon 18

 Passive Plankton Net 125 1,404 74.6 fish/100m3 43 (15) 56 (25)

 Light-trap 319 659 2.06 fish/10 min 35 (7) 47 (14)

Grand Isle 94

 Passive Plankton Net 329 3,076 69.6 fish/100m3 38 (6) 75 (26)

 Light-trap 474 12,474 26.2 fish/10 min 35 (3) 78 (27)

South Timbalier 54

 Passive Plankton Net 89 1,689 166.0 fish/100m3

 32 (8) 50 (16)

 Light-trap 194 1,193 0.6 fish/10 min 32 (8) 56 (24)

Belle Pass Jetty

 Plankton Pushnet 149 33,147 136.7 fish/100m3 39 (20) 77 (44)

 Light-trap 148 849 4.6 fish/10 min 19 (0) 34 (3)

plankton nets. Light-traps collected fish from seven families which were not collected in plankton

nets. Plankton nets collected fish from 56 taxa (identified at least to genus level), 25 of which were

not collected with light-traps, while light-traps collected fish from 47 taxa with 14 being unique to

light-trap collections. Mean plankton net densities ranged from 3.3-318.0 fish/100 m3

, while lighttrap CPUEs ranged from 0-12.2 fish /10 min (Figure 8.7). Sciaenops ocellatus, Caranx hippos/latus,

and Mugil cephalus were among the most common non-clupeiform fishes in the plankton net

collections (Table 8.3). Coastal pelagic taxa such as Auxis spp., Caranx crysos, and C. hippos/latus

were common in the surface and off-platform light-trap collections. 

At GI 94, plankton nets collected 3,076 fish while light-traps collected 12,474 fish, with a mean total

density of 69.6 fish/100 m3 and a mean total CPUE of 26.2 fish/10 min (Table 8.2). Plankton nets

collected individuals from more families than light-traps, but light-traps collected fish from more

different taxa than plankton nets. Twice as many unique families were collected by plankton nets,

while the number of unique taxa collected by each gear type was nearly identical. Mean plankton

net densities ranged from 16.6-201.0 fish/100 m3, while mean CPUEs ranged from 1.2-197.1 fish/10

min (Figure 8.8). Benthic taxa such as Symphurus spp. and Bregmaceros cantori were common in

plankton net collections, as well as coastal pelagic species such as Auxis spp. and Euthynnus

alletteratus (Table 8.3). Among the most common fishes collected in light-traps were synodontids

(primarily Synodus foetens and S. poeyi) and blenniids (primarily Hypsoblennius invemar and

Parablennius marmoreus). 
520

0

20

40

60

80

100

120

140

160

180

200

Jun 26-29

Aug 25-28

Sep 24-25

Oct 23-25

Nov 21-23

Jan-19

Feb 17-18Apr 15-18

May 17-20

Jun 18-21

Sampling Dates

Density (fish/100 m3

)

Subsurface Net Surface Net

318.0

a.

0

1

2

3

4

5

6

7

Jun 26-29

Aug 25-28

Sep 24-25

Oct 23-25

Nov 21-23

Jan-19

Feb 17-18Apr 15-18

May 17-20

Jun 18-21

Sampling Dates

CPUE (fish/10 min)

Subsurface LT Surface LT Off-platform LT

12.17

b.

Figure 8.7. Mean plankton net densities (a) and light-trap CPUEs (b) with standard errors for

each sampling trip at Green Canyon 18 (1995-96). Arrows above bars point toward

the off-scale mean for that gear. No subsurface plankton net samples were taken

during 26-29 June, 25-28 August, 24-25 September, or 15-18 April. No surface net,

surface light-trap, or subsurface light-trap samples were taken during 15-18 April.

No fish were present in subsurface light-trap samples (n=10) during 17-18 February.
521

Table 8.3. Size ranges (SL in mm) and percent of the total catch by gear for dominant taxa (>1%)

collected by at least one gear type. Note the preponderance of recently-spawned larvae,

late stage postlarvae, or juveniles collected with both gears. Also note the overlap in

sampling efforts for GC 18 and GI 94, and ST 54 and Belle Pass.

Light-trap Plankton net

Taxon Size Range % Size Range %

Green Canyon 18 (July 1995-June 1996)

Cyclothone braueri 3.2-7.2 5.8 4.0-13.0 1.8

Saurida brasiliensis 3.2-9.8 5.8

Trachinocephalus myops 16.2-35.0 1.8

Bregmaceros cantori 1.5-6.7 2.0 1.3-6.8 4.5

Gobiesox strumosus 2.6-3.2 2.0

Holocentrus spp. 6.0-37.5 4.0

Caranx crysos 5.0-65.0 12.0 2.5-16.5 3.3

Caranx hippos/latus 3.0-54.0 6.4 2.0-32.0 10.9

Chloroscombrus chrysurus 1.9-7.0 1.6

Elagatis bipinnulata 2.0-3.5 1.3

Pristipomoides aquilonaris 2.3-40.0 3.9

Eucinostomus spp. 6.5-11.2 3.3

Cynoscion arenarius 2.5-4.5 1.1 2.0-4.4 6.9

Micropogonias undulatus 3.2-4.5 1.1

Sciaenops ocellatus 1.8-3.9 12.3

Pomacentrus spp. 9.0-19.3 4.7

Mugil cephalus 2.4-21.5 3.8 2.2-5.0 9.0

Microdesmus lanceolatus 2.0-11.0 1.5

Microdesmus longipinnis 2.4-4.9 1.8

Auxis spp. 3.3-59.0 13.3 2.2-10.5 7.6

Euthynnus alletteratus 6.2-87.0 5.1 3.0-12.0 2.5

Scomberomorus cavalla 3.0-4.5 1.3

Scomberomorus maculatus 2.0-10.1 2.1

Ariomma spp. 2.1-2.5 7.8

Peprilus burti 1.7-4.2 2.0 1.4-3.3 1.2

Citharichthys spilopterus 3.0-8.0 2.1
Table 8.3. (continued)

522

Light-trap Plankton net

Taxon Size Range % Size Range %

Syacium spp. 3.5-6.5 2.7

Symphurus spp. 2.2-8.0 5.3 2.8-9.0 6.9

Grand Isle 94 (April-August 1996)

Saurida brasiliensis 4.5-55.0 7.9 2.7-22.5 6.2

Synodus foetens 6.0-43.0 30.6 4.2-22.5 1.8

Synodus poeyi 5.3-45.0 15.6 2.0-16.5 1.2

Bregmaceros cantori 2.0-29.0 3.0 2.0-15.5 16.6

Caranx crysos 2.5-15.0 2.1

Chloroscombrus chrysurus 2.1-16.5 1.5

Lutjanus spp. 3.0-5.5 1.0

Cynoscion arenarius 1.9-5.2 2.2

Sphyraena guachancho 2.6-7.3 2.7

Hypsoblennius hentz/ionthas 4.3-12.0 2.5

Hypsoblennius invemar 3.5-14.5 13.8

Parablennius marmoreus 4.4-23.7 12.3

Scartella/Hypleurochilus 3.6-12.5 1.7

Microdesmus lanceolatus 2.4-25.0 2.2

Auxis spp. 4.0-36.0 1.4 2.5-10.3 10.3

Euthynnus alletteratus 3.1-60.0 5.3 2.7-8.7 10.7

Etropus crossotus 2.5-9.0 2.6

Syacium spp. 2.1-8.5 3.0

Symphurus spp. 2.0-12.8 22.5

South Timbalier 54 (April-September 1997)

Saurida brasiliensis 26.4-43.0 1.2

Synodus foetens 9.0-44.5 38.9

Bregmaceros cantori 2.2-11.7 2.1

Caranx crysos 6.5-24.5 2.0

Caranx hippos/latus 5.5-35.0 3.8

Chloroscombrus chrysurus 2.1-16.5 1.5

Lutjanus spp. 3.0-5.5 1.0

Menticirrhus spp. 2.4-5.0 1.9
Table 8.3. (continued)

523

Light-trap Plankton net

Taxon Size Range % Size Range %

Hypsoblennius hentz/ionthas 3.4-12.5 4.4

Hypsoblennius invemar 5.7-13.8 3.6

Scartella/Hypleurochilus 2.0-14.3 5.0

Microdesmus lanceolatus 3.2-20.8 1.3

Microdesmus spp. 2.0-3.3 1.3

Auxis spp. 4.9-25.0 1.7

Euthynnus alletteratus 7.0-22.5 9.1

Scomberomorus cavalla 3.5-20.0 1.1 2.4-4.2 2.9

Scomberomorus maculatus 2.5-40.5 6.0 1.9-10.2 4.4

Peprilus burti 3.5-22.0 1.9 2.1-12.0 1.0

Peprilus alepidotus 2.5-24.7 1.3 1.8-5.0 1.6

Etropus crossotus 2.8-12.7 1.1 3.0-13.1 2.1

Symphurus spp. 2.0-14.5 2.3

Sphoeroides spp. 6.7-16.0 1.6

Belle Pass (April-September 1997)

Synodus foetens 20.0-36.0 2.7

Gobiesox strumosus 7.5-10.1 8.7 4.1-10.6 1.1

Chloroscombrus chrysurus 2.1-16.5 1.5

Lutjanus spp. 3.0-5.5 1.0

Bairdiella chrysoura 2.9-5.1 2.2 2.4-125.0 2.1

Cynoscion arenarius 3.2-8.2 10.8 2.5-41.0 27.5

Hypsoblennius hentz/ionthas 8.3-12.0 19.1 5.1-13.5 1.7

Dormitator maculatus 7.2-10.7 2.2

Gobionellus oceanicus 11.0-13.5 2.0 7.5-35.0 6.9

Gobiosoma bosc 7.7-9.6 10.9 6.5-17.0 37.3

Gobiosoma spp. 4.2-7.6 5.0 4.7-8.1 1.3

Microgobius spp. 4.7-10.1 3.7

Citharichthys spp. 7.9-11.6 1.5 5.2-13.0 5.2

Symphurus spp. 7.3-42.0 4.5

Sphoeroides parvus 9.1-12.5 3.1
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0

50

100

150

200

250

Apr 16-18Apr 26-29

May 10-12

May 17-20May 24-26

Jun 14-17

Jun 28-Jul1

Jul 12-15

Jul 29-Aug 1

Aug 12-15

Aug 26-29

Sampling Dates

Density (fish/100 m3

)

Subsurface Net Surface Net

a.

0

10

20

30

40

50

60

70

80

90

100

Apr 16-18Apr 26-29

May 10-12May 17-20May 24-26

Jun 14-17

Jun 28-Jul1

Jul 12-15

Jul 29-Aug 1

Aug 12-15Aug 26-29

Sampling Dates

CPUE (fish/10 min)

Subsurface LT Surface LT Off-platform LT

169.2 197.1

b.

Figure 8.8. Mean plankton net densities (a) and light-trap CPUEs (b) with standard errors for

each sampling trip at Grand Isle 94 (1996). Arrows above bars point toward the offscale mean for that gear.
525

At ST 54, plankton nets and light-traps collected 1,689 and 1,193 fish, respectively, with a mean

total density of 166.0 fish/100 m3 and a mean total CPUE of 0.6 fish/10 min (Table 8.2). Due to

problems with the deploying the subsurface net at this site (Hernandez et al. this volume), the

plankton net catch is almost exclusively from the surface. Plankton nets and light-traps collected fish

from an equal number of families, but light-traps collected fish from more taxa, including unique

taxa, than plankton nets (Table 8.3). Mean plankton net densities ranged from 15.7-809.7 fish/100

m3, while mean CPUEs ranged from 0-18 fish/10 min (Figure 8.9). Cynoscion arenarius and

Chloroscombrus chrysurus were the most dominant taxa in plankton net samples (Table 8.3). Lighttrap collections were dominated by Synodus foetens and scombrids, particularly Euthynnus

alletteratus and Scomberomorus maculatus.

At Belle Pass, the pushnet and light-trap collected 33,147 and 849 fish, respectively, with a mean

total density of 136.7 fish/100m3

 and a mean total CPUE of 4.6 fish/10 min (Table 8.2). The pushnet

collected fish from approximately twice as many families as the light-trap, including 20 unique

families. The same trend was evident in the number of taxa collected by each gear type. No fish

were collected from families unique to light-traps and only three unique taxa were collected with

light-traps. Mean pushnet densities ranged from 18.7-288.7 fish/100 m3

, while mean CPUEs ranged

from 0-9.7 fish/10 min (Figure 8.10). Pushnet samples were dominated by gobiids, primarily

Gobiosoma bosc, and the sciaenid, Cynoscion arenarius (Table 8.3). Dominant taxa in light-trap

collections included Membras martinica, Hypsoblennius hentz/ionthas, Gobiosoma bosc, and

Cynoscion arenarius.

Within-Site Comparisons of Sampling Gears

No significant differences were detected in mean total plankton net densities between surface and

subsurface collections at GC 18 and GI 94 (Tukey’s Studentized Range Test, "=0.05), although

subsurface densities were generally higher (Figure 8.11). At ST 54, surface nets had significantly

higher mean total densities than subsurface nets. In contrast, light-trap collections from surface

waters (surface and off-platform light-traps) had significantly greater total CPUEs at all three

platforms (Figure 8.11). At GI 94, overall means by depth and location ranged from 0.7-3.2 fish/10

min, with means from surface and off-platform locations being significantly greater than the

subsurface mean (Tukey’s Studentized Range Test, "=0.05). At GI 94 overall light-trap CPUEs were

the greatest of the three platform sites and ranged from 6.5-58.2 fish/10 min with significant

differences detected between all light-trap depths/locations. At ST 54, overall mean CPUEs ranged

from 3.8-7.2 fish/10 min with the off-platform collections being the greatest followed by the midplatform surface then by subsurface collections.

Length-Frequency Analyses

Six taxa from GC 18 met the required criteria for K-S analyses involving the differences in size

frequency distributions between sampling gears (i.e., at least 10 specimens collected by each gear).

In all instances, differences between size distributions for the two gear types were found to be

statistically significant (K-S tests, p#0.05; Figure 8.12). In general, there was some size overlap in

all gear comparisons, although the degree of overlap and shapes of the size distributions differed.

For Auxis spp., Caranx crysos, and Mugil cephalus, the plankton net samples caught predominantly
526

0

50

100

150

200

250

300

350

400

Apr 7-8

May 5-8

May 20-23

Jun 4-5

Jun 20-21

Jul 3-5

Aug 17-20

Sep 3-5

Sampling Dates

Density (fish/100 m3

)

Subsurface Net Surface Net

809.7

a.

0

2

4

6

8

10

12

14

16

18

20

Apr 7-8

May 5-8

May 20-23

Jun 4-5

Jun 20-21

Jul 3-5

Aug 17-20

Sep 3-5

Sampling Dates

CPUE (fish/10 min)

Subsurface LT Surface LT Off-platform LT

37.8

b.

Figure 8.9. Mean plankton net densities (a) and light-trap CPUEs (b) with standard errors for

each sampling trip at South Timbalier 54 (1997). Arrows above bars point toward the

off-scale mean for that gear. Subsurface net samples were only taken during 7-8

April. No subsurface light-traps were taken during 5-8 May. No off-platform lighttrap samples were taken during 3-5 September. No fish were present in subsurface

light-trap samples (n=4) during 17-20 August.
527

a.

0

50

100

150

200

250

300

Apr 7-9

Apr 21-23

May 5-7

May 20-22

Jun 3-5

Jun 20-21

Jul 3-5

Jul 19-21

Aug 1-3

Aug 18-20

Aug 31-Sep 2

Sampling Dates

Density (fish/100m 3

)

0

1

2

3

4

5

6

7

8

9

10

Apr 7-9

Apr 21-23

May 5-7

May 20-22

Jun 3-5

Jun 20-21

Jul 3-5

Jul 19-21

Aug 1-3

Aug 18-20

Aug 31-Sep 2

Sampling Dates

CPUE (fish / 10 min

b.

Figure 8.10. Mean pushnet densities (a) and light-trap CPUEs (b) with standard errors for each

sampling trip at Belle Pass (1997). No fish were present in light-trap samples during

19-21 July.
528

0

20

40

60

80

100

120

140

South Timbalier Grand Isle Green Canyon

Locations Within Sites

Density (fish/100 m3

)

Subsurface Net Surface Net

177.4

A

B

A

A

A

A

a.

b.

0

2

4

6

8

10

12

14

16

18

20

South Timbalier Grand Isle Green Canyon

Locations Within Sites

CPUE (fish/10 min)

Subsurface LT Surface LT Off-platform LT

58.16

A

B

B

A

B

C

A

B C

Figure 8.11. Mean plankton net densities (a) and light-trap CPUEs (b) with standard error bars for

depths/locations within each platform site. Arrows point toward the off-scale mean

for that gear. For mean densities within each location, the same letter above each bar

indicates no significant difference between depths based on t-tests on log-transformed data ("=0.05). For mean CPUEs within each location, the same letter above

each bar indicates no significant difference between depths/locations based on

Tukey’s Studentized Range test on ranked data ("=0.05). Different letters designate

significant differences.
529

0

0.05

0.1

0.15

0.2

0.25

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57

Length (mm)

Frequency

n=60

p<0.001

Ausix.spp.

0

0.05

0.1

0.15

0.2

0.25

0.3

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57

Length (mm)

Frequency

n=67

0

0.02

0.04

0.06

0.08

0.1

0.12

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Length (mm)

Frequency

n=55

p<0.001

Caranx crysos

0

0.05

0.1

0.15

0.2

0.25

0.3

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Length (mm)

Frequency

n=28

0

0.05

0.1

0.15

0.2

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52

Length (m m )

Frequency

n=29

p<0.001

Caranx hippos/latus

0

0.1

0.2

0.3

0.4

0.5

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52

Length (mm)

Frequency

n=97

0

0.02

0.04

0.06

0.08

0.1

0.12

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86

Length (mm)

Frequency

n=19

p<0.001

Euthynnus alleterattus

0

0.05

0.1

0.15

0.2

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86

Length (mm)

Frequency

n=22

Figure 8.12. Size distributions of fish collected with light-traps (shaded bars) and plankton nets

(open bars) at the Green Canyon site (1995-1996). Fish length-frequency

distributions were analyzed with Kolmogorov-Smirnov tests (p-values are

represented in the upper panel of each gear pairing along with each sample size).
530

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 3 5 7 9 11 13 15 17 19 21

Length (mm)

Frequency

n=17

p<0.001

Mugil cephalus

0

0.2

0.4

0.6

0.8

1

1 3 5 7 9 11 13 15 17 19 21

Length (mm)

Frequency

n=80

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

123456789

Length (mm)

Frequency

n=24

p<0.05

Synohurus spp.

0

0.05

0.1

0.15

0.2

0.25

0.3

123456789

Length (mm)

Frequency

n=55

Figure 8.12. (continued)

smaller individuals, while the light-trap samples generally encompassed these smaller sizes as well

as larger larvae and juveniles. For C. hippos/latus and Euthynnus alletteratus there was less overlap

at the smaller sizes and modal size classes for the light-trap samples were generally near the larger

sizes. Only for Symphurus spp. was the modal length of light-trap samples smaller than that for net

collections (p#0.05).

At GI 94, 10 of the 11 taxa analyzed for differences between the two gear types’ size distributions

were highly significant (K-S tests, p#0.001; Figure 8.13). For Auxis spp., Caranx crysos, and

Synodus poeyi there was some overlap in size distributions between gears, with the plankton net

capturing smaller larvae, but modal sizes for light-trap samples were always larger. Size

distributions for Bregmaceros cantori, Scomberomorus cavalla, Synodus foetens, and Trichiurus

lepturus appeared to overlap much more at the smaller sizes, but in each instance the light-trap

samples encompassed a significantly broader range of size classes. Although significantly different,

size distributions for Rhomboplites aurorubens exhibited a similar bimodal distribution for each gear

type. For Scomberomorus maculatus there was no overlap at all in the sizes of larvae captured with

the two gears. With only one taxon, Saurida brasiliensis, were plankton nets able to better catch

small sizes, but also larger size classes as well. Only one dominant taxa, Symphurus spp., did not

exhibit a significant difference in size distribution between gears (p=0.385).

At ST 54 differences between the two gear types’ size distributions for five of the seven taxa analyzed were highly significant (K-S tests, p#0.01; Figure 8.14). In general, light-trap size-frequency

distributions for Peprilus burti, P. paru, and Scomberomorus maculatus encompassed that of the

plankton net distributions, but also included larger sizes. Little overlap in size distributions was

observed for Euthynnus alletteratus, with light-trap collections being much larger. Distributions for
531

0

0.05

0.1

0.15

0.2

0.25

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

Length (mm)

Frequency

n=135

p<0.001

Ausix.spp.

0

0.1

0.2

0.3

0.4

0.5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

Length (mm)

Frequency

n=194

0

0.05

0.1

0.15

0.2

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Length (mm)

Frequency

n=15

p<0.001

Bregmaceros cantori

0

0.05

0.1

0.15

0.2

0.25

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Length (mm)

Frequency

n=317

0

0.05

0.1

0.15

0.2

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Length (mm)

Frequency

n=31

p<0.001

Caranx crysos

0

0.1

0.2

0.3

0.4

0.5

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Length (mm)

Frequency

n=45

0

0.05

0.1

0.15

0.2

1 3 5 7 9 11 13 15 17 19 21 23 25

Length (mm)

Frequency

n=42

p<0.001

Rhomboplites aurorubens

0

0.05

0.1

0.15

0.2

0.25

1 3 5 7 9 11 13 15 17 19 21 23 25

Length (mm)

Frequency

n=14

Figure 8.13. Size distributions of fish collected with light-traps (shaded bars) and plankton nets

(open bars) at the Grand Isle site (1996). Fish length-frequency distributions were

analyzed with Kolmogorov-Smirnov tests (p-values are represented in the upper

panel of each gear pairing along with each sample size).
532

0

0.05

0.1

0.15

0.2

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61

Length (mm)

Frequency

n=812

p<0.001

Saurida brasiliensis

0

0.05

0.1

0.15

0.2

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61

Length (mm)

Frequency

n=122

0

0.05

0.1

0.15

0.2

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Length (mm)

Frequency

n=63

p<0.001

Scomberomorus cavalla

0

0.1

0.2

0.3

0.4

0.5

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Length (mm)

Frequency

n=10

0

0.02

0.04

0.06

0.08

0.1

0.12

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55

Length (mm)

Frequency

n=35

p<0.001

Scomberomorus maculatus

0

0.1

0.2

0.3

0.4

0.5

0.6

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55

Length (mm)

Frequency

n=10

0

0.05

0.1

0.15

0.2

0.25

0.3

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=30

p=0.385

Symphurus spp.

0

0.05

0.1

0.15

0.2

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=450

Figure 8.13. (continued)
533

0

0.02

0.04

0.06

0.08

0.1

0.12

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43

Length (mm)

Frequency

n=801

p<0.001

Synodus foetens

0

0.05

0.1

0.15

0.2

0.25

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43

Length (mm)

Frequency

n=40

0

0.02

0.04

0.06

0.08

0.1

0.12

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43

Length (mm)

Frequency

n=1048

p<0.001

Synodus poeyi

0

0.05

0.1

0.15

0.2

0.25

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43

Length (mm)

Frequency

n=25

0

0.05

0.1

0.15

0.2

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

Length (mm)

Frequency

n=11

p<0.001

Trichiurus lepturus

0

0.1

0.2

0.3

0.4

0.5

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69

Length (mm)

Frequency

n=17

Figure 8.13. (continued)
534

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 2 3 4 5 6 7 8 9 10 11

Length (mm)

Frequency

n=10

p=0.998

Bregmaceros cantori

0

0.05

0.1

0.15

0.2

0.25

1 2 3 4 5 6 7 8 9 10 11

Length (mm)

Frequency

n=30

0

0.05

0.1

0.15

0.2

0.25

0.3

1 3 5 7 9 11 13 15 17 19 21 23 25

Length (mm)

Frequency

n=15

p=0.133

Chloroscombrus chrysurus

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

1 3 5 7 9 11 13 15 17 19 21 23 25

Length (mm)

Frequency

n=199

0

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=12

p<0.01

Etropus crossotus

0

0.05

0.1

0.15

0.2

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=30

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

1 3 5 7 9 11 13 15 17 19 21

Length (mm)

Frequency

n=99

p<0.001

Euthynnus alleterattus

0

0.1

0.2

0.3

0.4

0.5

1 3 5 7 9 11 13 15 17 19 21

Length (mm)

Frequency

n=10

Figure 8.14. Size distributions of fish collected with light-traps (shaded bars) and plankton nets

(open bars) at the South Timbalier site (1997). Fish length-frequency distributions

were analyzed with Kolmogorov-Smirnov tests (p-values are represented in the

upper panel of each gear pairing along with each sample size).
535

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

1 3 5 7 9 11 13 15 17 19 21

Length (mm)

Frequency

n=21

p<0.005

Peprilus burti

0

0.05

0.1

0.15

0.2

0.25

0.3

1 3 5 7 9 11 13 15 17 19 21

Length (mm)

Frequency

n=14

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

1 3 5 7 9 11 13 15 17 19 21 23

Length (mm)

Frequency

n=14

p<0.001

Peprilus paru

0

0.1

0.2

0.3

0.4

0.5

1 3 5 7 9 11 13 15 17 19 21 23

Length (mm)

Frequency

n=22

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Length (mm)

Frequency

n=64

p<0.001

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Length (mm)

Frequency

n=63

Scomberomorus maculatus

Figure 8.14. (continued)
536

Etropus crossotus broadly overlapped but plankton nets collected a wider range of smaller size

classes more frequently. Two species, Bregmaceros cantori and Chloroscombrus chrysurus did not

exhibit a significant difference in size distributions between the two gear types (p=0.998 and

p=0.133, respectively).

In contrast to the platform sites, size distributions at the Belle Pass jetty for pushnet vs. light-trap

collections were significantly different (K-S tests, p<0.05) for only three of the 11 taxa analyzed

(Figure 8.15). There was a good degree of overlap in the size distributions for Gobiosoma spp. and

Hypsoblennius hentz/ionthas, but in each instance the pushnet samples collected larger individuals

with greater frequency. In contrast, the light-trap size distribution for Membras martinica had an

intermediate dominant mode. The other seven taxa analyzed did not have significant differences in

size distributions between gears.

By using multiple gears and methodologies, we were able to confirm the presence of a number of

taxa with a full range of life history stages, ranging from recently-spawned larvae to juveniles,

associated with the platforms. For example, at GC 18 the plankton net collected Euthynnus

alletteratus individuals within a smaller size range (3.0-12.0 mm) than the light-trap (6.2-87.0 mm).

If our plankton net collections were not supplemented with light-trap catches, we would have not

been able to confirm the presence of larger juveniles at this site. 

Lunar Periodicity

At GI 94 during new moon phases, mean total CPUEs for light-traps were significantly higher than

during full moons (Student’s t-test, p#0.0001; Figure 8.16), while mean plankton net densities had

the opposite trend (p#0.01). The special lunar study conducted at GI 94 which compared three lunar

phases (first quarter, new, and third quarter moon phases sampled in May 1996), however, yielded

no significant differences in mean light-trap CPUEs or mean plankton net densities between the

three phases (Tukey’s Studentized Range test, p#0.05; Figure 8.17). At ST 54 there were no

significant difference in CPUEs between new and full moon phases (p=0.5635; Figure 8.18), but

mean total density during new moon phases was significantly higher than full moons (p#0.05); both

results are in contrast to our findings at GI 94. At Belle Pass mean CPUEs and pushnet densities

were significantly higher during new moon periods (Student’s t-tests, p<0.0003 and p<0.0001,

respectively; Figure 8.19). Therefore, when significant lunar differences were found, four out of five

instances had greater new moon catches.

Similarity and Diversity of Ichthyoplankton Assemblages Within Sites

Schoener’s Index of Niche Overlap values range from 0 to 1 (no similarity to identical species

compositions). Within-site comparisons of gears and surface sampling locations indicated that offplatform and surface light-trap collections were more similar to each other (0.45-0.76) than each was

to surface plankton net collections (0.27-0.71), although the disparity between the index gear

comparisons is smaller at ST 54 (0.59-0.71; Table 8.4). Overall, total light-trap collections were

relatively different from total plankton net samples at GC 18 and GI 94 (0.38 and 0.32), but much

more similar at ST 54 and Belle Pass (0.63 and 0.61), the two coastal sites.
537

0

0.1

0.2

0.3

0.4

0.5

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55

Length (mm)

Frequency

n=18

p=1.00

Bairdiella chrysoura

0

0.1

0.2

0.3

0.4

0.5

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55

Length (mm)

Frequency

n=478

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=12

p=0.674

Citharichthys spp.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=1169

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Length (mm)

Frequency

n=72

p=0.084

Cynoscion arenarius

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

1 4 7 10 13 16 19 22 25 28 31 34 37 40

Length (mm)

Frequency

n=1877

0

0.1

0.2

0.3

0.4

0.5

0.6

1 2 3 4 5 6 7 8 9 10 11 12

Length (mm)

Frequency

n=17

p=0.717

Dormitator maculatus

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11 12

Length (mm)

Frequency

n=186

Figure 8.15. Size distributions of fish collected with light-traps (shaded bars) and a pushnet (open

bars) at the Bell Pass site (1997). Fish length frequency distributions were analyzed

with Kolmogorov-Smirnov tests (p-values are represented in the upper panel of each

gear pairing along with each sample size).
538

0

0.1

0.2

0.3

0.4

0.5

0.6

12345678

Length (mm)

Frequency

n=39

p<0.001

Gobiosoma spp.

0

0.1

0.2

0.3

0.4

0.5

12345678

Length (mm)

Frequency

n=309

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10

Length (mm)

Frequency

n=68

p=0.384

Gobiesox stromosus

0

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5 6 7 8 9 10

Length (mm)

Frequency

n=351

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Length (mm)

Frequency

n=88

p=0.527

Gobiosoma bosc

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Length (mm)

Frequency

n=2217

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=153

p<0.05

Hypsoblennius hentz/ionthas

0

0.1

0.2

0.3

0.4

0.5

1 2 3 4 5 6 7 8 9 10 11 12 13

Length (mm)

Frequency

n=456

Figure 8.15. (continued)
539

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86

Length (mm)

Frequency

n=132

p<0.001

Membras martinica

0

0.05

0.1

0.15

0.2

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86

Length (mm)

Frequency

n=204

0

0.1

0.2

0.3

0.4

0.5

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Length (mm)

Frequency

n=25

p=0.116

Sphoeroides parvus

0

0.05

0.1

0.15

0.2

0.25

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65

Length (mm)

Frequency

n=87

0

0.05

0.1

0.15

0.2

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43

Length (mm)

Frequency

n=21

p=0.134

Synodus foetens

0

0.02

0.04

0.06

0.08

0.1

0.12

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43

Length (mm)

Frequency

n=229

Figure 8.15. (continued)
540

0

20

40

60

80

100

120

140

Full Moon New Moon

Lunar Phase

Mean Density (fish/100m3

)

p<0.0055

a.

0

5

10

15

20

25

30

Full Moon New Moon

Lunar Phase

Mean CPUE (fish/10 min)

p<0.0001

b.

Figure 8.16. Mean plankton net density (a) and light-trap CPUE (b) with standard error bars for

each lunar phase sampled at Grand Isle 94 (Apr-Sep 1996). The p-values indicate

statistical significance from t-tests.
541

0

10

20

30

40

50

60

Last Quarter Moon New Moon First Quarter Moon

Lunar Phase

Mean Density (fish/100m 3

)

A

A

A

a.

0

10

20

30

40

50

60

70

80

90

Last Quarter Moon New Moon First Quarter Moon

Lunar Phase

Mean CPUE (fish/10 min)

A

A

A

b.

Figure 8.17. Mean plankton net density (a) and light-trap CPUE (b) with standard error bars for

each lunar phase sampled in May 1996 at Grand Isle 94. The same letter above each

bar indicates no significant difference between the lunar phases based on Tukey’s

Studentized Range tests on ranked data ("=0.05).
542

0

50

100

150

200

250

300

350

Full Moon New Moon

Lunar Phase

Mean Density (fish/100m3

)

p<0.0340

a.

0

1

2

3

4

5

6

7

8

9

Full Moon New Moon

Lunar Phase

Mean CPUE (fish/10 min)

p<0.5635

b.

Figure 8.18. Mean plankton net density (a) and light-trap CPUE (b) with standard error bars for

each lunar phase sampled at South Timbalier 54 (Apr-Sep 1997). The p-values

represent statistical significance from t-tests.
543

0

50

100

150

200

250

Full Moon New Moon

Lunar Phase

Mean Density (fish/100m3

)

p<0.0001

a.

0

1

2

3

4

5

6

7

Full Moon New Moon

Lunar Phase

Mean CPUE (fish/10 min)

p<0.0003

b.

Figure 8.19. Mean pushnet density (a) and light-trap CPUE (b) with standard error bars for each

lunar phase sampled at Belle Pass (Apr-Sep 1997). The p-values represent statistical

significance from t-tests.
544

Table 8.4. Schoener’s Index of Niche Overlap values for different surface gear and location

comparisons. (OL) off-platform light-trap, (SL) surface light-trap, (SN) surface net, (TL)

total light-traps, (TN) total nets.

OL vs. SL OL vs. SN SL vs. SN TL vs. TN

Green Canyon 18 0.53 0.32 0.31 0.38

Grand Isle 94 0.45 0.37 0.27 0.32

South Timbalier 54 0.76 0.71 0.59 0.63

Belle Pass 0.61 0.61‡

‡Calculation is the same as with SL vs. SN since only a surface pushnet and surface

light-trap were used.

There was little difference in the Shannon-Weiner diversity index values from gear and

depth/location samples collected at GC 18 and ST 54 (Figure 8.20). In both instances, only

subsurface light-trap samples had significantly lower diversity values than the other gear and

depth/location combinations ("=0.05). No clear pattern in diversity was discernable at the GI 94 site

other than surface net collections were significantly different from light-trap collections and that off

platform light-trap collections were different from net collections regardless of depth. At the Belle

Pass site, pushnet samples were significantly more diverse than the light-trap samples. 

DISCUSSION

Gear Selectivity

The most obvious trend observed during this study was the overwhelming presence of engraulids

and clupeids at all sites, even on the shelf slope site (Hernandez et al. this volume). Light-trap and

plankton net collections (total catch) were dominated by clupeiform fishes at GC 18 (59%), GI 94

(66%), ST 54 (97%), and Belle Pass (74%). The dominance of these taxa in our collections is not

unexpected, particularly considering the abundances of these fishes in the northern Gulf and the

sampling gears utilized. Clupeiform fishes are often among the most abundant in plankton surveys

of the northern Gulf and are present year-round in shelf waters (Ditty 1986; Ditty et al. 1988;

Finucane et al. 1979). Light-traps are selective sampling devices, and previous studies have

demonstrated that often the catches are dominated by a single taxonomic group (Brogan 1994; Choat

et al. 1993; Sponaugle and Cowen 1996; Thorrold 1992). Clupeiform fishes have been shown to be

particularly photopositive and have dominated the total catches in several studies utilizing lightaggregating collection techniques (Brogan 1994; Choat et al. 1993; Dennis et al. 1989; Rooker et

al. 1996). The pushnet used in this study actively collects fish and was relatively large (1m x 1m).

It has also been shown to be an effective collector of clupeiforms in previous studies (Herke 1969;

Kriete and Loesch 1980; Raynie and Shaw 1994). While the light-trap collects fish based on taxonspecific, photopositive behaviors, and the pushnet actively strains the water mass it samples, the

plankton nets in our platform study collected fish passively with tidal currents. Even so, it was also
545

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 Green Canyon 18 Grand Isle 94

 South Timbalier 54 Belle Pass

Figure 8.20. Mean Shannon-Weiner diversity indices (with standard error bars) for each gear type

and sampling location for each sampling site. The same letter above each bar

indicates no significant difference between the gear types/sampling locations based

on Tukey’s Studentized Range tests ("=0.05). Different letters indicate significant

differences.

very effective in sampling these fishes. This catchability was undoubtedly aided by our nocturnal

sampling design.

These three sampling techniques clearly displayed gear selectivity as evident by differences in

taxonomic richness between gear types (Table 8.2). Passive plankton nets collected fish from more

unique families than light-traps at GC 18 (15 vs. 7) and GI 94 (6 vs. 3), but not ST 54 (8 families

unique to each gear). At Belle Pass, the pushnet collected individuals from 20 unique families, as

well as fish from all families sampled by light-traps. Previous studies comparing light-traps and

plankton nets in marine waters have found similar results (i.e., light-traps collected fewer families

than plankton tows) with only a few instances where light-traps collected unique families. Brogan

(1994) collected 16 unique families with a diver-steered pushnet and only four unique families with

light-traps, but the latter four families, when combined, comprised a very small proportion (<0.08%)

of his total light-trap catch. Likewise, more unique families were collected with a neuston net (10)

than with light-traps (4) when fished simultaneously in Onslow Bay, North Carolina, but the unique

light-trap families comprising only 10% of the total light-trap catch (Hernandez and Lindquist

1999). These results are similar to ours, where unique light-trap families usually made up less than

1% of the total catch at each platform site. However, whereas the previously cited studies each
546

collected only four unique families with their light-traps, we collected seven (GC 18) and eight (ST

54). Neither Choat et al. (1993) nor Hickford and Schiel (1999) reported any families in light-trap

samples that were not present in plankton net samples.

In addition, the large numbers of unique taxa (at least to genus level) collected by light-traps was

also surprising, since this gear is usually considered to be very taxon-specific, and therefore limited

in its sampling scope (Table 8.2). At the genus level, light-traps collected more unique taxa than

plankton nets at GI 94 (27 vs. 26) and ST 54 (24 vs. 16), but not at GC 18 (14 vs. 25). At Belle Pass,

however, the light-traps collected far fewer unique taxa (3) than did the pushnet (44). Such large

numbers of unique taxa have not been previously reported for light-traps in gear comparison studies.

Two studies reported data at the genus level, but found either that all taxa collected by light-traps

were collected by nets (Hickford and Schiel 1999), or that there were more unique taxa in the net

collections than light-trap collections (Hernandez and Lindquist 1999). In our study, light-traps

proved very useful in sampling available taxa that were not collected by plankton nets.

The diversity indices for the plankton net collections taken at the platform sites and the pushnet

collections taken at Belle Pass were not significantly different from each other, but were slightly

higher than those for the light-trap collections, with the exception of GI 94 (Figure 8.20). Several

studies have investigated differences in taxonomic richness between different gear types, although

few, if any, actually calculated taxonomic diversity indices as a comparison. Choat et al. (1993)

collected individuals from more families with a bongo net (63 families), a lighted-seine net (37

families), neuston net (31 families), Tucker trawl (29 families), and purse seine (25 families) than

with a light-trap (20 families) in a gear comparison study off Lizard Island, northern Great Barrier

Reef, Australia. In the Gulf of California, Brogan (1994) collected more reef fish larvae and

juveniles from different families with a diver-steered plankton net (43 families) than with a lighttrap (31 families). Hernandez and Lindquist (1999) collected more fish larvae and juveniles from

different families with a neuston net (24 families) than with either of the two light-trap designs

employed (18 and 21 families) in a study in Onslow Bay, North Carolina. In each of these studies,

the authors concluded that the taxonomic assemblage collected in their respective studies was very

method-dependent, and the same appears to be true in our study. 

Trends in taxon selectivity by gear were supported in the similarity indices between the gear types

within a given site (Table 8.4). At GC 18 and GI 94, there was greater similarity between the lighttrap samples, regardless of location, than there was between the surface light-trap collections (either

off platform or central location) and the surface net collections. Again, this indicates that the

behavioral or developmental responses of different fish taxa influence their susceptibility to different

sampling gears (Hernandez and Lindquist 1999). The trend was not as evident at ST 54, but this is

not surprising as 97% of the total catch by both gears was comprised of clupeiform fishes, which

are very susceptible to both gear types (Schoener’s Similarity Index for total light-trap vs. total net

collections = 0.63). There was also a relatively high similarity index value (0.61) for the pushnet vs.

light-trap comparison at Belle Pass. Again, this site was dominated by clupeiform fishes (74% of

total catch), and light-traps are effective in sampling these fishes.

Since the three sampling gears operate on different sampling principles, differences may be observed

not only between species, but also between different size classes of the same species. Of the 24
547

length-frequency comparisons between passive plankton nets and light-traps involving the dominant

taxa, 21 exhibited statistically significant differences (Figures 7-9). In the instances where no

significant differences were found, the distributions either overlapped substantially (Symphurus spp.,

Figure 8.13 and Bregmaceros cantori, Figure 8.14) or suffered from too few individuals in the larger

size classes for a significant statistical difference to be found (Chloroscombrus chrysurus, Figure

8.14). In general, the light-trap was more effective in sampling larger size classes of the same

species at each location, depth, or site. In some cases, the light-trap collections did not encompass

a significant portion of the plankton net’s smaller sizes, but clearly excelled at capturing the larger

sizes. This was the case, for example, with Caranx crysos and Scomberomorus maculatus (Figure

8.13) and for Euthynnus alletteratus (Figures 7 and 9). In other instances, the light-trap collections

appeared to significantly overlap the smaller sizes of the net collections, but also augmented the

size-frequency distribution with much larger sizes, or in some cases, even additional cohorts, as was

the case for C. crysos (Figure 8.12) and S. cavalla (Figure 8.13). These results further illustrate the

benefits that multiple gear types can bring to ichthyoplankton studies by sampling a more complete

range of size classes, cohorts, ages, and life history stages (Brogan 1994; Choat et al. 1993;

Hernandez and Lindquist 1999). 

Previous studies have demonstrated that pushnets are effective in sampling larger juveniles and

small fishes as well, particularly in coastal areas (Herke 1969; Kriete and Loesch 1980; Raynie and

Shaw 1994). Herke (1969) used a pushnet in Louisiana tidal marshes to collect small estuarine

fishes, primarily in the 25-100 mm range, and emphasized the maneuverability of the gear and its

bow-mounting (free of propeller wash) as major advantages. Kriete and Loesch (1980) used a

different design to collect juvenile pelagic fishes in lower Chesapeake Bay and found the gear was

easy to deploy and able to fish in a controlled manner within shallow water (minimum depth of 1.2

m). These advantages were traits we considered for the edges of the jetty environment which is

structurally complex. We were able to maneuver the boat and pushnet very close to the shallow

slope of the rock wall with relative ease. In general, net avoidance is reduced with pushnets

compared to towed nets (Raynie and Shaw 1994), and we chose a large mesh size (1,000 mm) and

net opening (1 m x 1 m) to minimize the pressure wave in front of the net, minimize net clogging,

and collect larger larvae and postsettlement juveniles. As a result, many of the size distributions

sampled with the pushnet and light-trap at Belle Pass overlapped considerably (Figure 8.15). Only

three of the 11 species analyzed exhibited significant size differences between the gear types. In one

instance, the pushnet collections clearly had a larger size mode than the light-trap (Figure 8.15,

Gobiosoma spp.). While we were targeting the same size classes with the pushnet, its usefulness was

in sampling different taxa. The number of families (39) and taxa identified to the genus level (77)

was approximately double that of the light-traps (19 and 34, respectively), which generated a taxon

diversity for the pushnet collections that was significantly higher than that for the light-trap (Figure

8.20). Once again, multiple gear types allowed for the collection of a more complete representation

of the ichthyoplankton and juvenile communities at the jetty site as well.

Lunar Periodicity

We investigated lunar periodicities because there are many hypotheses on larval biology concerning

lunar reproductive patterns pertaining to propagule dispersal and predation rates that occur both at

the beginning (spawning) and end (settlement) of the planktonic phase (Robertson 1991). Many reef
548

fish, for example, time their spawning events with different lunar cycles (Thresher 1984). Previous

studies have also documented higher rates of fish settlement during darker, new moon periods than

full moon periods (Victor 1986; Rooker et al. 1996), presumably a response to mortality associated

with visual predators. These patterns of spawning, transport, recruitment, and settlement in

association with the local physical oceanographic regime, often result in variable larval supply and

settlement patterns with distinct lunar periodicities. It should be noted, however, that in the northern

GOM tides are dominantly diurnal and their range in tidal height is not often in synchrony with the

phase of the moon (i.e., new and full moon maximum tide ranges vs. first quarter and third quarter

minimums); rather, the total range is in synchrony with the tropical and equatorial phases of the

moon’s elevation (i.e., Tropic of Cancer and/or Capricorn crossing maximum tidal ranges vs.

equatorial crossing minimums; McLellan 1965). In addition, we wanted to investigate the effects

on gear selectivity with respect to ambient light. Since light-traps rely on illumination in the

surrounding water mass to attract fish, then theoretically the contrast in trap-generated illumination

should be greater when there is less ambient light, such as during a new moon phase as opposed to

a full moon (all larval and postlarval supply/availability issues being equal). 

Few studies utilizing light-aggregating devices have addressed gear efficiency within the framework

of lunar periodicities in fish spawning, larval supply (transport) and settlement. Gregory and Powles

(1985) observed higher catches during new moon phases in a freshwater system but didn’t report

a statistical difference. Rooker et al. (1996) used a nightlight lift-net in nearshore habitats in Puerto

Rico and reported that new moon abundances of larval fish were four times higher than the next

most abundant phase (last quarter) during the summer months, and suggested that ambient light

intensities might have played a factor in gear efficiency. The competitive interaction of lunar vs.

light-trap illumination may have played a role in the collection of fish at Belle Pass where

significantly higher CPUEs were observed during new moons (Figure 8.19). Belle Pass pushnet

collections also had significantly more fish during new moons, possibly due to decreased visual

avoidance under lower ambient light conditions. It is difficult, however, to separate the effects of

ambient illumination and gear performance from the supply and/or settlement patterns of the fishes,

so lunar periodicity may still play a role in the occurrence of fishes at this site.

In addition, the situation at petroleum platforms may be equally difficult to discern since the

platforms have many bright lights throughout the structure to illuminate the work areas at night and

to aid ship navigation, which may in effect be attracting fish to the structure (i.e., we are fishing a

light-trap within a giant “light-trap”). We tried to address this issue by sampling away from the

structure (i.e., 20 m downstream), but even these off-platform light-trap collections could still be

within the “halo influence” of the platform’s light field. Still, when significant differences in mean

total densities and mean total CPUEs were found between new vs. full moon phases, four out of five

instances had greater new moon catches (Figure 8.16). The analysis of the May samples at GI 94

taken over three lunar phases was disappointing, however, since it showed very little difference

between the lunar phases for both gears (Figure 8.17). Although these platform results on lunar

periodicity are less than conclusive, there may be several explanations for the lack of a consistently

strong pattern. First of all, the previously mentioned potential competitive interference of large

ambient light-fields may sometimes override any lunar effect that would otherwise be present.

Secondly, some of the species may be responding differently to lunar cues. For example, some peak

recruitment events have also been linked to full moon periods (Johannes 1978; Robertson et al.
549

1988). In addition, the light-traps generally caught more larger sized (and presumably older, more

competent) larvae, whereas plankton net collections were dominated by smaller sized larvae that

could have been displaying different behavioral capabilities. Finally, it is possible that the

abundances of these fish are related to more localized factors such as water mass supply, particularly

at the mid- and inner shelf sites where the coastal current regime can dynamically affect salinity,

temperature, and food patchiness, and where the geographical concentration of upstream platforms

is greatest when compared to the relative isolated shelf slope site.

CONCLUSIONS

In summary, both the light-trap and the passive plankton net were effective in collecting fish larvae

and juveniles within the complex infrastructure of the oil and gas platforms sampled in the north

central GOM. Surprisingly, the light-trap collected individuals from a wide range of taxa, including

many unique taxa that were not collected with the plankton net. As in previous studies, the light-trap

generally collected larger individuals (postflexion larvae and juveniles) than the plankton net but

also performed very well at the smaller sizes. Pushnet collections from Belle Pass were more

taxonomically rich and diverse than light-trap collections, and the pushnet was equally effective in

capturing large individuals as the light-trap. The use of multiple gear types in ichthyoplankton

studies is becoming more common and, in some instances, provides the researcher with a more

complete view of larval fish assemblages. For example, the combination of sampling gears at the

platforms allowed for the collection of a wider range of taxa, size classes, and cohorts (life stages)

than either gear would have provided individually. This enabled us to confirm the presence of both

recently-spawned larvae and larger, near-settlement size postlarvae and juveniles at our sampling

sites. 

At the Belle Pass jetties, however, the pushnet collections contained many more families and taxa

than the light-trap collections, including nearly all of the taxa collected by that gear type, as well as

the same size ranges. In this coastal tidal pass, the light-trap was not as useful as a supplemental gear

type. The differences in the relative performance of the gear types in different habitats stresses the

need for the development of sampling strategies specific to each environment sampled.

ACKNOWLEDGMENTS

We gratefully acknowledge funding by the Minerals Management Service-Louisiana State

University-Coastal Marine Institute (Contract Number 14-75-0001-30660, Task Order Number

19926) and by the Louisiana Sea Grant Program, part of the National Sea Grant College Program

maintained by the National Oceanic and Atmospheric Administration. We thank Mark Benfield,

David Bunch, Joseph Cope, Nathan Craig, James Ditty, Talat Farooqi, Heather Haas, Ross Horton,

Robin Hargroder, Sean Keenan, Gregory Lavergne, David Lindquist, Bradley McDonald, Cory

New, Nick Ortego, John Plunket, and Christopher Whatley for assistance in the field and/or

laboratory. We gratefully acknowledge the assistance of Drs. Charles A. Wilson and David R.

Stanley. We are further indebted to Exxon USA, Inc. and Mobil USA Exploration and Production,

Inc. for access to their offshore oil and gas platforms and logistical support, and to the crews of

Mobil’s West Cameron 352, West Cameron 71D, Green Canyon 18, and Grand Isle 94 and Exxon’s

South Timbalier 54 platforms for their hospitality. 
550

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554

OCCURRENCE AND PELAGIC HABITAT OF REEF FISH LARVAE

IN THE GULF OF MEXICO

David S. Hanisko

Joanne Lyczkowski-Shultz

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Southeast Fisheries Science Center

ABSTRACT

Examination of 3560 ichthyoplankton samples taken during 15 years of annual Southeast Area

Monitoring and Assessement Program (SEAMAP) resource surveys in the U.S. Gulf of Mexico

(GOM), 1982 to 1996, yielded 208 holocentrid, 524 priacanthid, 6606 labrid and 2609 scarid larvae.

Larvae were found more frequently and in higher abundances over the continental shelf of the

eastern Gulf where most reef fish habitat exists. Labrid and scarid larvae were consistently

associated with higher salinity and clearer water on the mid to outer shelf during all seasons.

Increased river discharge in 1993 appears to have limited labrid and scarid larvae to the outer shelf

of the western Gulf, as compared to their more widespread distribution over the shelf in 1992 when

river discharge was near mean levels. A more unexpected result was the consistent and frequent

occurrence of labrid and scarid larvae in open Gulf waters in numbers comparable to abundances

observed at shelf locations. Abundances of labrid and scarid larvae plotted over dynamic sea surface

height measured from satellite imagery in winter and spring of 1993 revealed their apparent

relationship with open Gulf hydrography. In the western Gulf, the highest abundances of labrid and

scarid larvae were associated with the frontal boundary of a Loop Current anticyclone. In the eastern

Gulf, labrid and scarid larvae were found in higher abundances along the frontal boundaries of the

Loop Current (LC), LC/cyclonic eddy confluences and within the interior of the LC. The consistent

occurrence and relative abundance of labrid and scarid larvae in the open Gulf implies that an

exchange and transport of larvae may occur among reefs systems throughout the GOM and from

upstream sources such as the Caribbean Sea. 

INTRODUCTION

The GOM is best known for the richness and productivity of its salt marshes, estuaries, and broad

continental shelf, especially west of the Mississippi River. Yet areas of natural hardbottom, and the

diverse reef fauna that they support occur throughout the Gulf. Additionally, in the northwestern and

north-central Gulf the presence of offshore oil and gas production structures and the placement of

artificial reefs has increased the amount of hard substrate and available reef habitat(Gallaway 1984;

Kasprizak 1998). 

The biota associated with natural and artificial reef habitat is a mix of western Atlantic temperate

and insular tropical species, which becomes increasingly tropical in the more offshore areas (Dennis

and Bright 1988). The tropical nature of these reef communities in the north-central and western

Gulf is dependent upon; geological characteristics of the substrate; regional and local hydrography;
555

winter temperature minimum; riverine influence on salinity and turbidity; depth of substrate; and

depth and thickness of the nepheloid layer (Smith 1976 and Rezak et al. 1990).

The majority of adult reef fishes are sedentary and have an obligate (dependent) relationship with

their habitat. This relationship concentrates them to relatively small areas of suitable habitat. Since

the adult phase of most species are sedentary, populations of reef fishes are established and

maintained by the continuous settlement of pelagic larvae to reef habitat (Sale and Ferrell 1988; Leis

1991). 

Sale (1991) and Cowen and Sponaugle (1997) have noted that there is little information on the

planktonic and early life stages of reef fishes. Although there have been numerous ichthyoplankton

studies from the broad range of marine habitats found in the Gulf of Mexico (Richards et al. 1993),

none have focused on the larvae of reef fishes on a Gulf-wide basis. Ichthyoplankton samples have

been collected since 1982 during Southeast Area Monitoring and Assessment Program (SEAMAP)

ichthyoplankton surveys of the GOM (SEAMAP 2000). Data from these collections on the

distribution and abundance of the larvae of 4 obligate reef fish families: Holocentridae

(squirrelfishes); Priacanthidae (bigeyes); Labridae (wrasses); and Scaridae (parrotfishes) are

summarized. We present data that reveal apparent relationships between larval reef fish distributions

and hydrography in the northwestern and open GOM. 

MATERIALS AND METHODS

Data were taken during four annual SEAMAP surveys: Summer Groundfish, Fall Plankton and Fall

Groundfish in continental shelf waters; and Spring Plankton in the open GOM (Figure 8.21, Table

8.5). Stations are 30 to 60 nautical miles apart in a fixed grid, and sampled at all times of day or

night. Additionally, Oregon II Cruise 203, a marine mammals/plankton survey conducted only in

January and February of 1993 was examined to investigate possible larval associations with

hydrographic features in the open Gulf (Table 8.5). Plankton collections from this cruise were taken

every 10 nm along a transect between the shortest route to the next day’s starting position during

nighttime hours. Larvae for all cruises were captured in oblique tows from near bottom to surface

using a 61-cm bongo net with 0.333 mm mesh nets following standardized SEAMAP collection

procedures (SEAMAP 2000). 

Surface measurements of salinity and turbidity were taken with a SEABIRD SBE25 conductivity

temperature depth (CTD) profiler. Surface salinity contours were generated from the data for the

1992, 1993 and 1994 Summer Groundfish, Fall Plankton and Fall Groundfish cruises. Surface

turbidity (water clarity) contours were generated from data for the Summer and Fall Groundfish

cruises in 1992 and 1993. Contour plots were generated by Surfer® 6 using a Kriging function with

a linear variogram. Labrid and scarid distributions were plotted over the composite salinity and

transmissivity contours to examine possible relationships. TOPEX/ERS1 merged dynamic sea

surface height plots were obtained from the GOM historical data server at the Colorado Center for

Astrodynamics Research: http://www-ccar.colorado.edu/~realtime/gom-historical_vel/
98 97 96 95 94 93 92 91 90 89 88 87

Holocentridae

25262728293031

98 97 96 95 94 93 92 91 90 

Priacanthidae

25262728293031

98 97 96 95 94 93 92 91 90 89 88 87

Labridae

25262728293031

98 97 96 95 94 93 92 91 90 

Scaridae

25262728293031

Figure 8.21. Southeast Area Monitoring and Assessment Program (SEAMAP) survey areas sampled during Summ

Fall Plankton, Fall Groundfish and Spring Plankton cruises. 
557

Table 8.5. SEAMAP surveys sampling effort. Western Gulf of Mexico (West), Texas-Louisiana

Shelf (TX-LA), Mississippi-Alabama Shelf (MS-AL), Florida Shelf (FL) and Eastern

Gulf of Mexico (East). (*) Indicates area not sampled.

Number of samples by area

Survey Time Frame Years West TX-LA MS-AL FL East Total

Summer Groundfish (SG) June-July 1982-96 * 330 39 * * 369

Fall Plankton (FP) Aug.-Oct. 1986-94,

1996

* 507 84 551 * 1142

Fall Groundfish (FG) Oct.-Nov. 1986-95 * 607 95 * * 702

Spring Plankton (SP) April-June 1982-84,

1986-96

511 * * * 836 1,347

Winter Plankton (WP) Jan.-Feb. 1993 * * * * * 102

Labrid and scarid abundances were plotted over sea surface height to examine possible relationships.

Abundance data was subsetted into 30 day periods and plotted over the sea surface height map

corresponding to the mid point of the 30 day sampling period. 

Larvae from SEAMAP collections were sorted and identified by the Polish Sorting and

Identification Laboratory in Szczecin, Poland. Species descriptions of larval development for

tropical reef fishes is lacking but most are identifiable to the family level (Leis and Rennis 1983;

Richards 1985). The families; Holocentridae, Priacanthidae, Labridae and Scaridae were chosen for

this study because they are obligate reef species with pelagic larvae. These larvae are

morphologically distinct from other larvae thus minimizing misidentifications, at least to the family

level. Many species within the families Holocentridae, Priacanthidae and Labridae are known to

have protracted larval stages that could be entrained and transported in ocean currents and eddies.

Although little is known of the ontogeny of the family Scaridae, it is likely that some scarids also

have protracted larval periods similar to the closely related to labrids ( Leis and Rennis 1983). 

RESULTS

Examination of 3560 bongo net samples yielded 208 holocentrid, 524 priacanthid, 6606 labrid and

2609 scarid larvae from annual SEAMAP resource surveys in the GOM, 1982 to 1996 (Table 8.5).

Presence and absence plots generated for each survey depict the pelagic habitat of these families

throughout the GOM (Figure 8.22 through Figure 8.25). Distinct annual and regional differences in

the occurrence and abundance of these larvae were revealed among five regions: TX-LA, MS-AL

and FL shelves, and the western and eastern open GOM. Ranges in percent frequency of occurrence

and abundances show similar annual and regional patterns, therefore only plots of frequency of

occurrence are presented. 
98 97 96 95 94 93 92 91 90 89 88 87

Holocentridae

25262728293031

98 97 96 95 94 93 92 91 90 

Priacanthidae

25262728293031

98 97 96 95 94 93 92 91 90 89 88 87

Labridae

25262728293031

98 97 96 95 94 93 92 91 90 

Scaridae

25262728293031

Figure 8.22. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the 1982 to 1996 Summ

Surveys. Filled circles (C) indicate positive catches of larvae; plus signs (+) indicate zero catch.
98 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80

Holocentridae

1819202122232425262728293031

98 97 96 95 94 93 92 91 90 89 88 87 86 85 

Priacanthidae

1819202122232425262728293031

98 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80

Labridae

1819202122232425262728293031

98 97 96 95 94 93 92 91 90 89 88 87 86 85 

Scaridae

1819202122232425262728293031

Figure 8.23. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the 1986 to 1994 

Plankton Surveys. Filled circles (C) indicate positive catches of larvae; plus signs (+) indicate zero 
98 97 96 95 94 93 92 91 90 89 88 87

Holocentridae

25262728293031

98 97 96 95 94 93 92 91 90 

Priacanthidae

25262728293031

98 97 96 95 94 93 92 91 90 89 88 87

Labridae

25262728293031

98 97 96 95 94 93 92 91 90 

Scaridae

25262728293031

Figure 8.24. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the 1986 to 1995 F

Surveys. Filled circles (C) indicate positive catches of larvae; plus signs (+) indicate zero catch.
98 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80

Holocentridae

1819202122232425262728293031

98 97 96 95 94 93 92 91 90 89 88 87 86 85 84 83 82 81 80

Labridae

1819202122232425262728293031

98 97 96 95 94 93 92 91 90 89 88 87 86 85 

Scaridae

1819202122232425262728293031

98 97 96 95 94 93 92 91 90 89 88 87 86 85 8

Priacanthidae

1819202122232425262728293031

Figure 8.25. Occurrence of holocentrid, priacanthid, labrid and scarid larvae taken during the 1982 to 84 and 

Spring Plankton Surveys. Filled circles (C) indicate positive catches of larvae; plus signs (+) indica
562

The Summer Groundfish surveys (15 years) took samples from Mobile, AL to Brownsville, TX on

the continental between 10 and 110 m generaly in the months of June and July (Figure 8.26).

Holocentrids were taken in only 3 years on the TX-LA shelf, and were never collected on the MSAL shelf. Annual frequency of occurrence (FO) ranged from 0 to 2%; and annual abundance ranged

from 0 to 0.13 larvae/10 m2 on the TX-LA shelf. Priacanthids were collected in 12 years on the TXLA shelf and only 1 year on the MS-AL shelf. Annual FO ranged from 0 to 7% on the TX-LA shelf,

and 0 to 8% on the MS-AL shelf. Annual abundance ranged from 0 to 0.27 larvae/10 m2 on the TXLA shelf and 0.30 larvae/10 m2

 on the MS-AL shelf. Labrids were collected during 14 years on the

TX-LA shelf and 12 years on the MS-AL shelf. Annual FO ranged from 0 to 29% on the TX-LA

shelf and 0 to 100% on the MS-AL shelf. Annual abundance ranged from 0 to 0.13 larvae/10 m2 on

the TX-LA shelf, and 0 to 91.30 larvae/10 m2 on the MS-AL shelf. Scarids were collected during

3 years on the TX-LA shelf and 1 year on the MS-AL shelf. Annual FO ranged from 0 to 4% on the

TX-LA shelf and 0 to 8% on the MS-AL shelf. Annual abundance ranged from 0 to 0.48 larvae/10

m2 on the TX-LA shelf, and 0 to 1.50 larvae/10 m2 on the MS-AL shelf.

The Fall Plankton surveys (11 years) took samples throughout the GOM over the continental shelf

from 10 to 200 m generally in the month of September (Figure 8.27). Holocentrids were collected

during 4 years on the TX-LA shelf, never on the MS-AL shelf, and 8 years on the Florida (FL) shelf.

Annual FO ranged from 0 to 8% on the TX-LA shelf and from 0 to 10% on the FL shelf (Figure

8.27). Annual abundance ranged from 0 to 0.42 larvae/10 m2 on the TX-LA shelf and from 0 to 1.21

larvae/10 m2 on the FL shelf. Priacanthids were collected during 9 years on the TX-LA shelf, 2 years

on the MS-AL shelf, and 8 years on the FL shelf. Annual FO ranged from 0 to 15% on the TX-LA,

0 to 14% on the MS-AL and 4 to 42% on the FL shelf. Annual abundance ranged from 0 to 0.80 ,

0 to 1.63 and 0.18 to 8.5 larvae/10 m2 repsectively for the TX-LA, MS-AL and FL shelves. Labrids

were collected every year on the TX-LA, MS-AL, and FL shelves. Annual FO ranged from 4 to

16%, 22 to 83% and 47 to 83% on the TX-LA, MS-AL and FL shelves respectively. Annual abundance ranged from 0.22 to 3.72, 2.91 to 38.10 and 4.57 to 44.25 larvae/10 m2

 on the TX-LA, MS-AL

and FL shelves respectively. Scarids were collected during 9 years on the TX-LA shelf, 3 years on

the MS-AL shelf, and all 10 years on the FL shelf. Annual FO ranged from 0 to 11%, 0 to 25% and

10 to 50% on the TX-LA, MS-AL and FL shelves respectively. Annual abundances ranged from 0

to 4.67, 0 to 3.13 and 1.42 to 14.97 larvae/10 m2 on the TX-LA, MS-AL and FL shelves.

The Fall Groundfish surveys (9 years) took samples from Mobile, AL to Brownsville, TX on the

continental between 10 and 110 m generally in the months of October and November (Figure 8.28).

Holocentrids were never collected on the TX-LA or MS-AL shelves. Priacanthids were collected

during 4 years on the TX-LA shelf, and 1 year on the MS-AL shelf. Annual FO ranged from 0 to

6% on the TX-LA shelf, and from 0 to 20% on the MS-AL shelf. Annual abundance ranged from

0 to 0.29 larvae/10 m2 on the TX-LA shelf, and 0 to 0.87 larvae/10 m2 on the MS-AL shelf. Labrids

were collected during 8 years on the TX-LA shelf, and 6 years on the MS-AL shelf. Annual FO

ranged from 0 to 11% on the TX-LA shelf and 0 to 33% on the MS-AL shelf. Annual abundance

ranged from 0 to 2.51 larvae/10 m2 on the TX-LA shelf, and 0 to 5.37 larvae/10 m2 on the MS-AL

shelf. Scarids were collected during 7 years on the TX-LA shelf, and 2 years on the MS-AL shelf.

Annual FO ranged from 0 to 13% on the TX-LA and 0 to 20% on the MS-AL shelf. Annual

abundances ranged from 0 to 1.27 larvae/10 m2

 on the TX-LA shelf, and 0 to 1.46 larvae/10 m2 on

the MS-AL shelf. 
Year

H o lo c e n trid a e

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

TX -LAM S -A L

Year

P riaca n th id ae

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 19

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Year

L a b rid a e

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Year

S c a rid a e

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 19

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Figure 8.26. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid larvae by year a

1982 to 1996 Summer Groundfish Surveys.
Year

H o lo c e n trid a e

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

TX -LAM S -A LFL 

Year

P riaca n th id ae

1985

1986

1987

1988

1989

1990

1991

1992

1993

19

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Year

L a b rid a e

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Year

S c a rid a e

1985

1986

1987

1988

1989

1990

1991

1992

1993

19

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Figure 8.27. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid larvae by year a

1986 to 1994 and 1996 Fall Plankton Surveys.
Year

L a b rid a e

1984198519861987198819891990199119921993199419951996

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

TX -LAM S -A L

Year

H o lo c e n trid a e

1984198519861987198819891990199119921993199419951996

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Year

S c a rid a e

19841985198619871988198919901991199219

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Year

P riaca n th id ae

19841985198619871988198919901991199219

F reque ncy of O ccu rrence

(% )

0

2 04 06 08 0

100

Figure 8.28. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid larvae by year a

1986 to 1995 Fall Groundfish Surveys.
566

The Spring Plankton surveys (14 years) took samples throughout the open GOM generally from

April to June (Figure 8.29). Holocentrids were collected during 6 years in the western and all 14

years in the eastern Gulf (Figure 8.29). Annual FO ranges from 0 to 7% in the west, and 0 to 18%

in the east. Annual abundance ranged from 0 to 0.73 larvae/10 m2 in the west and 0 to 4.42 larvae/10

m2 in the east. Priacanthids were collected during 9 years in the western, and all 14 years the eastern

Gulf. Annual FO ranges from 0 to 11% in the west, and 2 to 18% in the east. Annual abundance

ranged from 0 to 0.61 larvae/10 m2 in the west, and 0.08 to 2.42 larvae/10 m2 in the east. Labrids

were collected during 11 years in the western and all 14 years in the eastern Gulf. Annual FO ranged

from 0 to 29% in the west and 15 to 57% in the east. Annual abundance ranged from 0 to 7.08

larvae/10 m2 in the west, and 5.22 to 13.58 larvae/10 m2 in the east. Scarids were collected during

13 years in the western and all 14 years in eastern Gulf. Annual FO ranged from 0 to 40% in the

west and 15 to 50% in the east. Annual abundance ranged from 0 to 2.56 larvae/10 m2 in the west,

and 2.72 to 22.66 larvae/10 m2

 in the east.

Observations over the entire time series were combined in order to get a clearer picture of regional

differences in distribution (Figure 8.30). Overall FO and abundance of all four taxa of reef fishes

was highest on the FL shelf. Labrid occurrence and abundance on the MS-AL shelf were comparable

to observations on the FL shelf, but were low on the TX-LA shelf. The FO and abundance of

holocentrids, priacanthids and scarids was extremely low on the TX-LA and MS-AL shelves.

Distinct differences were also seen in open waters between the western and eastern GOM. Overall

FO and abundance of all four taxa of reef fishes were higher in the eastern than the western GOM

(Figure 8.30). The frequency of occurrence and abundance on the FL shelf and in the eastern gulf

were often greater by an order of magnitude than the TX-LA, MS-AL shelves and the western Gulf.

The frequency of occurrence and abundances of all families were similar in continental shelf and

open ocean waters for both the western and eastern GOM.

Seasonality of larval reef fish occurrence could not be fully evaluated because of uneven regional

sampling over the seasons. However, during the six month time period from early June to late

November labrids decreased in frequency of occurrence and abundance on both the TX-LA and MSAL shelves, while scarids generally increased.

Labrid and scarid distributions were plotted over contoured surface salinity and water clarity

(transmissivity) in order to examine relationships with shelf hydrography (Figure 8.31 and Figure

8.32). A salinity contour of 30 was used to delineate the westward and offshore extent of lower

salinity shelf waters for 1992-1994 Summer Groundfish, Fall Plankton and Fall Groundfish surveys.

Larvae were consistently associated with higher salinity (>30) water on the shelf during all surveys.

The westward and offshore extent of lower salinity (<30) was most variable during Summer

Groundfish surveys, and less so during Fall Plankton and Fall Groundfish surveys. A salinity of 30

generally defined the inshore limit of labrid and scarid occurrence. Turbidity of 60% was used to

delineate the onshore extent of offshore waters for the 1992 and 1993 Summer and Fall Groundfish

surveys. The onshore extension of clear offshore water was variable in both years and both surveys.

However, the presence of larval labrids and scarids was consistently associated with the clearer

offshore waters.
Year

H o lo c e n trid a e

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

F re qu e n cy o f O ccu rre nc e

(% )

05

1 01 52 02 53 03 54 04 55 05 56 0

Year

P ria c an th id a e

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

19

F re qu e n cy o f O ccu rre nc e

(% )

05

1 01 52 02 53 03 54 04 55 05 56 0

W es t E as t 

Year

L a b rid a e

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

F re qu e n cy o f O ccu rre nce

(% )

05

1 01 52 02 53 03 54 04 55 05 56 0

Year

S c a rid a e

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

19

F re qu e n cy o f O ccu rre nce

(% )

05

1 01 52 02 53 03 54 04 55 05 5

Figure 8.29. Annual frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid larvae by year a

1982 to 1984 and 1986 to 1996 Spring Plankton Surveys.
S u rv e y T im e S e rie s a n d A re a SP W EST S G T X -LA F P T X -LA F G T X -LA S G -M S -A L F P M S -A L F G M S -A L FP FLSP E

F re q u e n cy o f O ccu rre n ce

(% )

0

2 04 06 08 0

100

H O L O C E N T R ID A E P R IA C A N T H ID A E L A B R ID A E S C A R ID A E 

Figure 8.30. Overall frequency of occurrence (%) of holocentrid, priacanthid, labrid and scarid larvae by SEAM

area. Plankton Survey designations: Summer Groundfish (SG), Fall Plankton (FP), Fall Groundfish (Plankton (SP).
98 97 96 95 94 93 92 91 90 89 88 87

Summer Groundfish 1992

252627282930

98 97 96 95 94 93 92 91 90 89 88 87

Summer Groundfish 1993

252627282930

98 96 94 92 90 88

Summer Groundfish 1994

252627282930

98 97 96 95 94 93 92 91 90 89 88 87

Fall Plankton 1992

252627282930

98 97 96 95 94 93 92 91 90 89 88 87

Fall Plankton 1993

252627282930

98 97 96 95 94 93 92 91 90 89 88 87

Fall Plankton 1994

252627282930

98 97 96 95 94 93 92 9

Fall Groundfish 1

252627282930

98 97 96 95 94 93 92 9

Fall Groundfish 1

252627282930

98 97 96 95 94 93 92 9

Fall Groundfish 1

252627282930

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38

Salinity

Figure 8.31. Occurrence of labrid and scarid larvae in relation to surface salinity for the 1992 to 1994 Summer G

Plankton and Fall Groundfish surveys. Solid black line delineates a salinity of 30. Filled circles (C) incatches of larvae; plus signs (+) indicate zero catch.
98 97 96 95 94 93 92 91 90 

Fall Groundfish 1992

25262728293031

98 97 96 95 94 93 92 91 90 

Fall Groundfish 1993

25262728293031

98 97 96 95 94 93 92 91 90 89 88 87

Summer Groundfish 1992

25262728293031

0 10 20 30 40 50 60 70 80 90 100

98 97 96 95 94 93 92 91 90 89 88 87

Summer Groundfish 1993

25262728293031

Turbidity (%)

Figure 8.32. Occurrence of labrid and scarid larvae in relation to surface transmissivity for the 1992 to 1993 Su

Groundfish surveys. Solid black line delineates a transmissivity of 60%. Filled circles (C) indicate p

of larvae; plus signs (+) indicate zero catch.
571

Abundances of labrid and scarid from larvae were plotted over dynamic sea surface height in order

to examine relationships with open GOM hydrography. A single 30 day sampling period was

examine from Oregon II Cruise 203 (Figure 8.33). The dominant features in the survey area were

an anticyclone (Eddy “V”)/cyclone (WC) eddy pair centered at 26.5o N, 960 W and a second anticyclone (EA)/cyclone (EC) pair near 26.5O N, 88O W. Labrid and scarid larvae were seldom taken

at stations along the 200 m iso-bath, but were taken frequently at deeper water stations. Larvae were

found more frequently and in higher abundances along the periphery of the anticyclonic eddy in the

western gulf and in the confluence of the EA/EC eddy pair off the mouth of the Mississippi River.

Two 30 day sampling periods were examined from the 1993 Spring Plankton survey (Figure 8.34

and Figure 8.35). The dominant feature in the western GOM was the Eddy “V”/WC pair off the

Texas coast. Dominant features in the eastern GOM survey area were the northern extension of the

Loop Current (LC), a cyclonic eddy (EC1) centered at 28o N and 88o W and a cyclonic eddy (EC2)

along the eastern margin of the LC. In the western GOM labrid and scarid larvae were found more

frequently and in higher abundances along the northern edge of the anticyclonic eddy or within the

confluence of the Eddy “V”/WC pair. In the eastern GOM, labrid and scarid larver were more

frequently found in higher abundances along the frontal boundaries of the LC and cyclonic eddies

or within the confluence of these features.

DISCUSSION

Reef habitat between 18 m and 91 m in the U.S. GOM has been estimated to be 38% of the shelf

area between Pensacola and Key West, Florida and 5% of the shelf between Pensacola, Florida and

the Rio Grande River (Parker et al. 1983). The occurrence and abundance of larval reef fishes in the

families Holocentridae, Priacanthidae, Labridae and Scaridae taken during SEAMAP surveys

reflected this pattern in GOM reef habitat. These larvae were taken throughout the SEAMAP survey

area over continental shelf waters but occurred more frequently and in higher numbers in the eastern

than in the western GOM where more reef fish habitat exists. 

Distinct regional differences in the occurrence and abundance of these larvae were revealed among

the Texas-Louisiana, Mississippi-Alabama and Florida continental shelves. Annual occurrence of

larval holocentrids and priacanthids in the western GOM was highly variable compared to the

occurrence of labrids and scarids in the same region. Although holocentrid and priacanthid larvae

were never as abundant as labrid and scarid larvae, larvae of all four families consistently occurred

in higher numbers in the eastern than in the western GOM. Labrid and scarid larvae occurred 4 to6

more frequently, and were 3 to 10 more abundant in the eastern than in the western GOM. 

Riverine influence on salinity and turbidity has been identified as an important biological control

with regard to establishing and maintaining adult reef fish communities (Smith 1976; Rezak et al.

1990). The inflow of fresh water predominantly from the Atchafalaya, Mississippi and Mobile River

drainages significantly alters salinity and turbidity gradients over the continental shelf of the

northwestern and north-central GOM. This was illustrated in the summer of 1993 when discharge

from the Atchafalaya and Mississippi Rivers reached a 100 flood stage. In contrast, river discharge

in 1992 was near historical means (Arcement et al. 1992; Dantin et al. 1993 and Nowlin et al.

1998a). Increased river discharge in 1993 appears to have confined labrid and scarid larvae to the
LABRIDAE

Larvae / 10m sq

 0.0001 to 5 5 to 10 10 to 20 20 to 40 40 to 80 80 to 160 160 to 320

Eddy V

WC

WA

EC

EA

LC

Figure 8.33. Distribution and abundance of labrid and scarid larvae during Oregon II, Cruise 203 in relation 

height. Black vectors are relative geostrophic currents. Dominant features are labeled: Eddy “V”, w(WC), western anticyclone (WA), eastern anticylcone (EA), eastern cyclone (EC) and the Loop Cu
LABRIDAE

Larvae / 10 m sq

 0.0001 to 5 5 to 10 10 to 20 20 to 40 40 to 80 80 to 160 160 to 320

Eddy V

WC

WA

EC1

LC

EC2

Figure 8.34. Distribution and abundance of labrid and scarid larvae in relation to sea surface height during the S

survey from April 19 to May 19, 1993. White vectors represent relative geostrophic currents. Domare labeled: Eddy “V”, western cyclone (WC), western anticyclone (WA), eastern cyclones one and EC2) and the Loop Current (LC).
SCARIDAE

Larvae / 10 m sq

 0.0001 to 5 5 to 10 10 to 20 20 to 40 40 to 80 80 to 160 160 to 320

Eddy V

WC

WA

EC1

LC

LC

EC2

Figure 8.35. Distribution and abundance of labrid and scarid larvae in relation to sea surface height during the S

survey from May 20 to June 19, 1993. White vectors represent relative geostrophic currents. Dominlabeled: Eddy “V”, western cyclone (WC), western anticyclone (WA), eastern cyclones one and two and the Loop Current (LC).
575

outer shelf as compared to their more widespread distribution on the shelf in 1992. Labrid and scarid

larvae were consistently associated with higher salinity and clearer water on the mid to outer shelf

during all seasons. Salinity and turbidity distributions are useful indicators to delineate outer shelf

and oceanic water masses on the shelf, and therefore the pelagic habitat of larval labrid and scarids.

The Loop Current (LC) is the major driving force of circulation in the open GOM. Large

anticyclonic (clockwise rotation) eddies detach from the LC, migrate westward across the Gulf

where they eventually end up in the westerm GOM and decay (Vukovic and Crissman 1986,

Hamilton 1992). Associated with these large LC eddies are smaller anticyclonic and cyclonic

(counter-clockwise rotation) eddies and rings which form by the degradation of larger eddies,

interaction with other eddies and/or the continental slope and shelf (Vukovich and Crissman 1986;

Vidal et al. 1992; Hamilton 1992).

An unexpected result of our examination of the SEAMAP ichthyoplankton data was the consistent

and frequent occurrence of labrid and scarid larvae in open GOM waters. These larvae were found

in numbers comparable to abundances observed at continental shelf locations. Winter and spring

SEAMAP plankton sampling coincided with two episodic intrusions by LC “Eddy V” on the Texas

shelf in January and May of 1993 (Nowlin et al. 1998a; Nowlin et al. 1998b). The highest

abundances of labrid and scarid larvae captured during the winter and spring SEAMAP surveys in

1993 were associated with the frontal boundary of Eddy “V.” Eddy “V” and its associated cyclonic

ring persisted off the south Texas shelf and slope from December through the summer of 1993 and

was well studied by the oceanographic community (Berger et al. 1996; Sahl et al. 1997; Nowlin et

al. 1998a; Nowlin et al. 1998b and Hamilton et al. 1999). The May intrusion of Eddy “V”

transported Texas/Mexico shelf waters offshore in the convergence of a cyclone (WC)/anti-cyclone

(WA) ring pair located near 23° N and 96° W (Figure 8.35). Shelf water was wrapped around the

southeastern quadrant of the cyclone and was transported onto the Texas shelf by the convergence

of the cyclone and Eddie “V” (Sahl et al. 1997). The water mass then rotated around the northern

portion of Eddy “V” and was transported offshore across the shelf slope break on the eastern side

of the eddy. The January episode was not as well studied, but the eddy system was in a similar

configuration (Figure 8.33). Reef fish larvae may have been transported on or off the shelf in a

‘conveyor-belt’ fashion by these geostrophic flows or larvae may have been entrained in the eddy

depending on their location within the eddy system.

Eddies in the western GOM also drive shelf edge currents and affect shelf waters through exchanges

of mass, energy, and water properties. (Nowlin et al. 1998a). Interaction of counter-rotating eddies

is the major mechanism for water exchange between the shelf and slope (Berger et al. 1996). Nowlin

et al. (1998a) also state that eddies episodically impact the inner shelf, and during such episodes the

exchange between the shelf and open Gulf is substantial. This exchange could be a mechanism for

the transport and/or retention of larvae spawned on reefs located on the mid and outer continental

shelf. Entrainment within an eddy could keep larvae on or near the shelf. Hamilton et al. (1999)

found that the mean rotational period for LC eddies in the northwestern GOM was 10 to 11 days.

A broad survey of 25 reef families indicated that pelagic larval duration of most ranged between 20

to 60 days (Richards and Lindeman 1987). Therefore, entrainment and subsequent transport along

the eddy periphery could result in the return of at least some larvae to shelf edge reefs as they reach

settlement stage.
576

The transient nature and infrequent occurrence of some reef fishes in the northwester GOM may be

caused by unpredictable and variable recruitment from outside the region (Dennis & Bright 1988).

In winter months of 1993, labrid and scarid larvae were rarely taken at stations along the shelf edge

but were frequently taken at stations along open GOM transects. The configuration of the EA/EC

eddy pair located southeast of the Mississippi River between 89° and 87° W longitude resulted in

westward flowing currents (Figure 8.33). Most labrid and scarid larvae were collected at stations

within this westward flow and may have eventually recruited to reefs in the western GOM.

Labrid and scarid larvae were also associated with the LC and cyclonic eddies in the eastern GOM

in the spring of 1993. Larvae were taken at the majority of stations and were found in higher

abundances along the frontal boundaries of the LC and LC/cylconic eddy confluences. Higher

abundances of labrids and scarids were also found within the interior of the LC than at stations

outside the eddy system. 

Labrid and scarid abundances were higher in conjunction with the LC, anticyclonic and cyclonic

eddies, and associated frontal boundaries than elsewhere in the open GOM. This may be related to

increased productivty at the fronts. Cyclonic eddies may lead to high productivity due to the

increased upward nutrient flux along their periphery (Biggs 1992; Biggs and Muller-Karger 1994).

Recently, Wormuth et al. (2000) found zooplanton and micronekton biomass to be higher in

cyclones that in anticyclones, and highest or intermediate in the confluence of an

anticyclonic/cyclonic eddy pair. Lamkin (1997) also found plankton biomass and larval abundance

to be larger in the confluence of the LC and cyclones. Additionally, nutrient rich shelf water may

be entrained by these features, thereby enhancing local production. Biggs and Muller-Karger (1994)

observed the the entrainment and seaward transport of high productivity shelf water up to 200 km

offshore by eddy pair confluences, and hypothesized enhanced fisheries production in these areas.

Similar conditions also exist in the northern GOM with the occasional entrainment of high

productivity shelf and Mississippi River plume water by the LC (Muller-Karger et al. 1991). 

The LC and associated eddies and rings exert a coherent and dynamic influence not only in the open

GOM but on the continental shelf and slope as well. The consistent occurrence and relative

abundance of labrid and scarid larvae in the open GOM implies that reef fish larvae produced on

distant reefs such as the Florida Keys and the Caribbean Sea could supply recruits to reefs in the

northwestern GOM. The probable mechanism of this apparent advection and transport is the Loop

Current and its westward tending system of eddies and rings. Entrainment of larvae produced on

GOM reefs in the Florida Keys, the Flower Gardens in the northwestern Gulf, and off south Texas

and Mexico could also be entrained in Gulf eddies that have arrived in the western Gulf. Locally

produced larvae entrained in eddy systems in the southeastern Gulf (off Florida) or the northwestern

Gulf (off Texas) could lead to either retention and local recruitment or advection to the open Gulf.

Survival and return to favorable habitats may still be possible for reef fish larvae advected offshore

depending on species-specific duration of the precompetent stage and the position of larvae relative

to circulation of the eddy or ring. 

We undertook this examination of the SEAMAP ichthyoplankton database in an attempt to identify

patterns in larval reef fish production and potential ‘sources and sinks’ of recruits to GOM reefs.

Initial data summaries have shown that the larvae of at least two major groups of reef fishes, the
577

wrasses and parrotfishes, may regularly or episodically be transported across the Gulf and become

available as recruits to northern Gulf reefs. Differences between Caribbean and northern GOM reefs

in species composition of labrids and scarids may yield insights into the origin of reef fish larvae

found in the open GOM . We will, therefore, reexamine and attempt species-level identification of

labrid and scarid larvae in these SEAMAP collections. Otolith analysis and age determination of

archived specimens will also be undertaken. Together these new data may yield a less ambiguous

depiction of the source and fate of reef fish larvae. Finally, we plan to utilize Geographic

Informations Systems to examine the SEAMAP time series in relation to hydrographic features in

the open GOM; and determine if a significant statistical relation exist between reef larvae, the Loop

Current, eddies, rings and fronts. 

REFERENCES

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Louisiana water year 1992. U.S.G.S. Water-Report LA-92-1.

Berger, T.J., P. Hamilton, J.J., and R.R. Leben. 1996. Louisiana/Texas Shelf Physical Oceanography

Program: Eddy Circulation Study, Final Synthesis Report. OCS Study MMS 96-0051. United

States Department of the Interior, Minerals Management Service, Gulf of Mexico OCS Region,

New Orleans, Louisiana.

Biggs, D.C. 1992. Nutrients, Plankton and Productivity in a warm-core ring in the western Gulf of

Mexico. Journal of Geophysical Research 97(C2):2143-2154.

Biggs, D.C., and F.E. Muller-Karger. 1994. Ship and satellite observations of chlorophyll stocks in

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Cowen, R.K. and S. Sponaugle. 1997. Relationships between early life history traits and recruitment

among coral reef fishes. Pages 423-449 In C. Chambers and E. A. Trippel, eds. Early life history

and recruitment in fish populations. Chapman and Hall, London.

Dantin, L.J., C.R. Garrison, and W.M. Lovelace. 1993. Water resource data Louisiana water year

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of Mexico. Bulletin of Marine Science 43:280-307.

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Hamilton, P. 1992. Lower continental slope cyclonic eddies in the central Gulf of Mexico. Journal

of Geophysical Research 97(C2):2185-2200.
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Hamilton, P., G.S. Fargion, and D.C. Biggs. 1999. Loop Current eddy paths in the western Gulf of

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Kasprizak, R.A. 1998. Use of oil and gas platforms as habitat in Louisiana’s artificial reef program.

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Leis, J.M. 1991. The pelagic stages of reef fishes: The larval biology of coral reef rishes. Pages 183-

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Leis, J.M. and D.S. Rennis. 1983. The larvae of Indo-Pacific coral reef fishes. New South Wales

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phytoplankton concentration and sea surface temperature cycles of the Gulf of Mexico as

determined by satellites. Journal of Geophysical Research 96(C7):12,645-12,665.

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circulation and transport processes study: Synthesis Report, Volume I: Technical Report. OCS

Study MMS 98-0035. United States Department of`the Interior, Minerals Management Service,

Gulf of Mexico OCS Region, New Orleans, Louisiana.

Nowlin Jr., W.D., A.E. Jochens, R.O. Reid and S.F. DiMarco. 1998b. Texas-Louisiana shelf

circulation and transport processes study: Synthesis Report, Volume II: Appendices. OCS Study

MMS 98-0036. United States Department of the Interior, Minerals Management Service, Gulf

of Mexico OCS Region, New Orleans, Louisiana.

Parker, R.O., Jr., D.R. Colby, and T.D. Willis. 1983. Estimated amount of reef habitat on a portion

of the U.S. South Atlantic and Gulf of Mexico continental shelf. Bulletin of Marine Science

33:935-940.

Rezak, R., S.R. Gittings, and T.J. Bright. 1990. Biotic assemblages and ecological controls on reefs

and banks of the Northwest Gulf of Mexico. American Zoologist 30:23-35

Richards, W.J. 1985. Status of the identification of the early life stages of fishes. Bulletin of Marine

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Richards, W.J. and K.C. Lindeman. 1987. Recruitment dynamics of reef fishes: Planktonic

processes, settlement and demersal ecologies, and fishery analysis. Bulletin of Marine Science

41(2):392-410.
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Richards, W.J., M.F. McGowan, T. Leming, J.T. Lamkin, and S. Kelly. 1993. Larval fish

assemblages at the Loop Current boundary in the Gulf of Mexico. Bulletin of Marine Science

53: 475-537.

Sahl, L.E., D.A. Wiesenburg, and W.J. Merrell. 1997. Interactions of mesoscale features with Texas

shelf and slope waters. Continental Shelf Research 17(2):117-136.

Sale, P.F. 1991. Introduction. Pages 3-11 In P.F. Sale, ed. The ecology of fishes on coral reefs.

Academic Press Inc. San Diego, CA. Academic Press Inc., San Diego.

Sale, P.F. and D.J. Ferrell. 1988. Early survivorship of juvenile coral reef fishes. Coral Reefs 7:117-

124. SEAMAP (Southeast Area Monitoring and Assessment Program). 2000. Environmental and

biological atlas of the Gulf of Mexico 1998, Number 75. Gulf States Marine Fisheries

Commission, Ocean Springs, Mississippi.

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Department of Natural Resources Marine Research Laboratory, Florida Marine Research

Publications Number 19, St. Petersburg, FL.

Vidal, V.M. V., F.V. Vidal and J.M. Perez-Molero. 1992. Collision of a Loop Current anticyclonic

ring against the continental shelf slope of the western Gulf of Mexico. Journal of Geophysical

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Vukovich, F.M. and B.W. Crissman. 1986. Aspects of warm rings in the Gulf of Mexico. Journal

of Geophysical Research 91(C2):2645-2660.

Wormuth, J.H., P.H. Reesler, R.B. Cady, and E.J. Harris. 2000. Zooplankton and micronekton in

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34.
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COMPARISON OF THE FISHERIES VALUE OF PLATFORMS USED AS ARTIFICIAL

REEFS: STANDING, TOPPLED, AND PARTIALLY REMOVED

Aaron Pierce

Charles A. Wilson

Department of Oceanography and Coastal Sciences and

Coastal Fisheries Institute

Louisiana State University

ABSTRACT

Artificial reefs have been embraced as a management tool by a wide range of user groups

(recreational and commercial fishers, recreational divers, and environmental advocacy

organizations), and federal and state resource mangers. While these groups view artificial reefs

positively, little information exists on associated nekton assemblages, particularly at deepwater

artificial reefs.

The purpose of this project is to measure and compare the species composition, abundance and size

frequency distribution of fishes associated with a toppled platform, a partially removed platform and

a standing production platform in the Northern Gulf. Comparison of acoustically derived fish

densities at the artificial reef sites and the open waters of the GOM will answer this question using

a Biosonics model DT5000 scientific echosounder/multiplexer-equalizer and a remotely operated

underwater vehicle for visual census techniques.

Fish density around the standing platform (HI350) varied with both depth and side. We found lowest

densities near the bottom and adjacent to the platform where mean fish density was 0.0001 fish per

cubic meter (FPCM) and highest densities near the surface at .05 fish per cubic meters. Fish

densities around partial removed platform (HI 355) were roughly 2-3 orders of magnitude higher

over the top of the platform. Mean fish density over HI355 was 0.26 fish/m3. Densities around the

toppled platform (WC617), produced similar results to HI355, except that the density at WC 617

was roughly 1⁄2 that of HI355. 

We conclude that fish abundance around oil and gas platforms is much higher than adjacent soft

bottom sediment. The platforms provide critical habitat for many important commercial and

recreational species for Louisiana citizens. Our general impression remains that standing platforms

are the most desirable configuration. We continue to support partial removal in water depths greater

than 200 feet and toppling in place in shallower depths.
581

A HYDROACOUSTIC ASSESSMENT OF FISH DENSITY AT THE FLOWER GARDEN

BANKS WITH EMPHASIS ON THE WEST FLOWER GARDEN BANK

Charles A. Wilson

Mark Miller

Department of Oceanography and Coastal Sciences and 

The Coastal Fisheries Institute

Louisiana State University

The use of oil and gas platforms (platforms) as artificial reefs has been well established. As

mentioned in Wilson et al. (this publication), the basis for this practice is the common user group

knowledge that platforms support superior recreational fishing. This public perception has been

supported through scientific investigations. However, there is little data to suggest that the reef

configurations employed to date are as productive as natural reefs. Stanley and Wilson (1997)

suggested that both toppled and partially removed platforms may not be as productive as standing

platforms or as natural reef systems. The fisheries value of the various artificial reef configurations

needs further investigation with emphasis on their comparison to natural reefs.

The largest natural reef in the northern GOM is the Flower Garden Banks. This complex is

composed of coral reefs that have grown up on top of natural geological formations known as salt

domes. Although fishermen have known about the Flower Garden Banks since the late 1800s, it was

not until 1936 that the banks were officially discovered by the U.S. Coast and Geodetic Survey

during surveys in the GOM to map pinnacles. In 1961 Dr. Thomas E. Pulley documented that the

Flower Gardens were viable coral communities (Elvers and Hill 1985). After nearly two decades

of effort the Flower Garden Banks were designated a marine sanctuary in 1992 (Gittings and

Hickerson 1998). Although several fisheries surveys have been conducted around these geological

features, few scientific investigations have considered a holistic account of the fish population and

fish density beyond the cryptic reef fishes.

To date the most extensive survey of fish assemblages on the Flower Garden Banks was conducted

by LGL Ecological Research Associates during a period from 1980 to 1982. The report (Boland et

al. 1983), funded by the National Marine Fisheries Service, was based on 357 hours of video data

recorded at 1 minute intervals which were used to estimate standing stock of 16 reef fish taxa. The

investigators reported characteristic fish assemblages zoned primarily by depth and/or habitat types

delineated as upper coral reef, algal-nodule sponge zone, shallow drowned reef, deep drowned reef,

and soft bottom. Investigators also estimated species abundance; for example, they estimated that

the population size for creole-fish Paranthias furcifer ranged from 400,000 to 993,948, red snapper

Lutjanus campechanus from 4,000 to 20,000, and groupers Mycteroperca spp. from 20,000 to

47,000 at the Flower Garden Banks.

Biotic zonation of the West Flower Garden Bank (WFGB) was first described by Bright et al. (1974)

who were followed by previous other investigators. They reported on the major biotic elements of

the bank and provided a quantitative baseline assessment of the reef community. They utilized

divers, towed video systems, and manned submersibles to collect seventy days of data during 17
582

cruises between July 1970 and December 1972. Their report included a thorough catalog of fauna.

Bright and C.W. Cashman (1974) reported that 101 fish species were found at the WFGB.

Dennis and Bright later reported three distinct reef fish assemblages at the WFGB (1988) in

association with three major biotic zones (coral reef, algal-sponge, and drowned reef). Species

composition was similar to outer slope Carribean reefs, but the WFGB exhibited much lower

diversity (253 primary species reported at Caribbean reefs versus 84 found at the WFGB). Cluster

analysis of fish assemblages yielded three depth zonations with a distinct species composition in

each of the three zones. Dennis and Bright (1988) reported twenty-eight fish species in the upper

zone (<45m), 45 species in the middle zone (45-85m), and 20 species in the lower zone (>85m).

Rooker et al. (1997) compared fish species richness between the WFGB and a nearby oil platform

(High Island A389A), a marked difference. They reported 54 species and 39 species, respectively,

at the WFGB and HI A389A. Rooker et al. (1997) reported that midwater pelagics such as carangids

and scombrids accounted for over 50% of all taxa enumerated at the platform; 50% of the observed

total fish population at the WFGB was composed of species in the family Pomacentridae.

The proximity of the several artificial reef projects to the natural coral formations of the Flower

Gardens afforded us the opportunity to compare these fish communities to that of a neighboring

natural system. The goals of this study were to identify species composition; and to estimate the fish

density/biomass at the WFGB. We intended to describe the fish community associated with the

WFGB and to compare it to previous studies of fish communities conducted at nearby platforms and

reefs. Reef configurations targeted for comparison included a production platform toppled in place

as a deep water artificial reef (West Cameron (WC) 617A), a nearby partially removed platform (HI

A355), and an operating production platform(HI A350); these are described elsewhere in this

publication (Wilson et al., this publication). 

MATERIALS AND METHODS

The WFGB is located approximately 173 km southeast of Galveston, Texas, on the edge of the outer

continental shelf at 27/ 52.4' north latitude and 93/ 48.8' west longitude (Figure 8.36). The WFGB

was created by the uplift of a salt dome of Jurassic, Louann origin. (Rezak 1981, as in Dokken et

al. 1999). It represents the largest charted calcareous bank in the northwestern GOM and (Bright et

al. 1985 as in Dokken et al. 1999) and the northernmost coral reef on the continental shelf of North

America (Bright et al. 1984 as in Dokken et al. 1999). The living coral cap varies in depth from

approximately 18 to 36 meters. (Rezak et al. 1985 as n Dokken et al. 1999). The major features of

the 137 km2 WFGB are three crests aligned along an east-west axis. The middle crest rises from a

depth of 100 –150 meters to within 18 meters of the surface and supports a coral reef community.

(Rezak et al. 1985 as in Dokken et al. 1999).

A towed 120 kHz transducer was used to estimate the density and size frequency distribution of

fishes associated with the two artificial reef sites. The downward oriented transducer was towed

from the starboard hip of the research vessel R/V Pelican (June 1999) or the M/V Epic Mariner

(June 2000). The towfish was held in place 5 m out from the hull with a telescoping mast and flown

3 m below the surface at approximately 2 m/sec. The use of a towed downward oriented transducer

enabled the calculation of density and size distribution of fishes from a depth of 5 m to 1 m from
583

Figure 8.36. Map of the sites surveyed in June 1999 and 2000.

the bottom. Navigational data were collected with g a Garmin GPS III global positioning system

(GPS) with a Garmin GB 21 differential beacon receiver. The navigation data stream, which updated

once per second, was incorporated into the acoustic data string and then saved on laptop computer.

In order to optimize the navigation accuracy, the antenna for the GPS was mounted directly above

the tow body, thus allowing the data to be processed in a two meter horizontal resolution that was

posted to a GIS database.

The mobile survey of WFGB consisted of twenty-seven transects spaced 500 meters apart running

along the long axis of the WFGB, from northeast to southwest. Transect lines were planned to begin

and end near the outer boundaries of the Marine Sanctuary along the 120 m depth curve. This design

allowed an open water control area to be surveyed at the beginning and ending of every transect line.

The lines varied in length from 2.5 kilometers to 13.5 kilometers. Data were collected along these

transects continuously over a 29 hour period 21-23 June 2000. For analysis purposes, the WFGB

was separated into three biological community “terraces” based on water depth and specified as

upper (20-50 meters), middle (80- 100 meters), and lower (> 100 meters) (Bright and Boland 1985).

A high resolution multi-beam side scan survey assisted the determination of the terraces (Gardner

et al. 1998). These geological terraces have been related to distinct biological zonations (Dennis and

Bright 1998). 
584

Acoustic data were collected with a Biosonics model DT5000 scientific echosounder/multiplexer.

All data were collected with a 120 kHz transducer which had been factory calibrated to a - 42 dB

tungsten sphere. Source levels were 223 dB / Pa at 1 m. Sampling rate was 5 pings /sec with a pulse

width of 0.4 ms. Received signals were adjusted for spreading loss by applying a 40 log R time

varied gain, digitized and recorded on the computer hard drive and later transferred to CD digital

media. The data collection threshold was -55 dB, corresponding to a minimum detection of a 2.5 cm

fish (Love 1971).

Digitized hydroacoustic data were processed with a Biosonics’ Visual Analyzer 4.02. Recent

advances in the software allowed simultaneous estimates of sigma (target strength) and mean

volume backscatter (reflected acoustic energy) for each depth strata. These parameters are used to

estimate fish density/m3 and fish size. Ten meter depth strata were assigned for processing all data.

Data files were replayed through Visual Analyzer with the bottom tracking feature turned on; the

bottom was then manually inspected and adjusted to insure that the bottom was not included in the

analyzer window.

Mobile transects were analyzed at one second resolution (@ 2 meters linear distance) to determine

the volume backscatter and target strength/m3

 within each depth stratum along each transect.

Analysis of each one second block of data provided geographic position and mean volume back

scatter. Individual target strength information was acquired by extracting ping specific data, which

could be selectively output as a text file. A Visual Basic program was used to calculate an average

target strength for each target, by strata, and location.

Processing of acoustic data yields several parameters of interest. Fish density is calculated based on

the volume backscatter (reflected acoustic energy) of a known volume (cubic meter) of water

divided by the average target strength (TS reported as sigma) from that same volume of water.

Density is reported as density/m3

 in this study. Density estimates are dependent upon accurate

estimates of the mean sigma of the targets within that same volume of water. The accuracy of target

strength increases with repeated acoustic hits on the same target (Jim Dawson, Biosonics Inc, pers

com). Given that research operations were from a vessel moving at 4 knots and transmitting acoustic

pulses (pings) at a rate of 5 pings per second, the chance of hitting a target multiple times was very

low. In many cases data processing resulted in a volume backscatter, but no sigma for that same

volume of water. A mean sigma (proxy sigma) was calculated for a 30 m linear distance by stratum,

and used as a proxy for target strength to calculate density. The assumption, in this case, was that

fish size was similar in the same stratum for 30 linear meters. If sigma was missing, but a volume

backscatter volume was available, the proxy sigma was substituted to estimate density. 

Statistical analysis of these data included as volume backscatter (SV), a proxy for fish biomass, as

a dependent variable in our analysis. Volume backscatter is an exponential number provided by the

Biosonics Visual Analyzer and is a per ping average of energy/m3. For regressional analysis and

calculation of means, SV is converted into a “arithmetic form”, called “Fish Energy”, with the

relationship,

 Fish Energy = 10 sv/10, 
585

where SV is volume backscatter (reflected acoustic energy) of a known volume of water (cubic

meter)

The use of volume backscattering avoided the uncertainty of target strength error in density

calculations. “Fish Energy” should be considered to be an acoustic measurement of fish biomass as

it is based on the average acoustic reflectance/m3. The second dependent variable in our analysis was

density/m3, which was calculated with the equation, 

10 SV/10 /10 TS/10 = fish/m3

where SV is the volume backscatter/m3 and TS is the mean target size assigned (or the proxy sigma

discussed above). 

A randomized block analysis of variance was used to examine the main effects of TS as described

by Stanley and Wilson (1997). Due to the larger number of zero values in the mobile survey, logistic

regression was used to analyze the mobile data (Trexler and Travis 2001). 

Logistic Regression

Traditional parametric analysis was not used for analysis of mobile acoustic data given the large

number of zero values for SV and the problem of autocorrelation that occurs in mobile acoustic data.

A binomial logistic model was constructed using the presence or absence of “fish energy” to

evaluate the probability, or chance, of finding fish. This analysis was performed on the primary

output of acoustic data analysis which was reported in 1 second intervals. Class variables for the

WFGB were depth or terrace, stratum, and time of day (TOD). 

The use of logistic regression in ecological sampling was described by Trexler and Travis (2001).

It has been shown to be useful with data that have a large proportion of zero values when error is

usually not normally distributed. In most cases analysis consists of converting the dependent

variable into a discrete form (e.g. presence/absent, agree/disagree, etc). The regression model then

assumes a binomial distribution of errors (Trexler and Travis 2001, Garrison et al. 2000). 

The Statistical Analysis System (SAS 2000) includes a program called Proc Logistic that runs a

logistic analysis . When run with the intercept option, it produces a Type III analysis of main effects,

which provides an estimate of the significance of class variables, based on a maximum likelihood

test (Chi Square test of significance p = 0.01) that is used for comparing within class variables.

When run without an intercept, Proc Logistic provides an odds ratio estimate, which is the

probability of the dependent variable being above zero in a given class variable cell compared to

another cell. The output also includes percent concordance, which is the percent of the time that the

model correctly predicts the outcome. 

Visual Surveys

Visual surveys were conducted with a Deep Ocean Engineering Phantom HD2 ROV with standard

visual census techniques and recording video on S-VHS tape. (Bohnsack and Bannerot 1986).
586

Cryptic fishes (fish length < 10 cm) were not included in the video surveys results since they could

not be assessed in the acoustic surveys. Point counts were conducted to identify individual fish to

the lowest taxonomic level. Results and data were expressed as percent composition by stratum at

each site. 

During mobile surveys the ROV was deployed from the M/V Epic Mariner. Video data from the

WFGB were collected along random transects designed to represent the three major terrace regions

and geologic features located throughout the WFGB. The ROV was flown to the bottom where it

traveled at a speed of 1 knot for 45 minutes along a transect through each of the three major terraces.

RESULTS

The acoustic survey of the West Flower Garden Bank provided valuable insight into the fish

community associated with this unique natural bottom habitat. Twenty-seven survey lines covering

a linear distance ranging from 2.5 to13.5 km were sufficient to cover the WFGB at 500 m intervals.

The survey took 29 hours to cover approximately 160 km of survey lines (Figure 8.37). Survey lines

were generally parallel, but variable sea state, wind and currents caused some slight variations from

the intended track lines. In addition to challenging environmental conditions we also experienced

an equipment malfunction with the transducer cable that caused a corruption of the data collected

along one of the transects over the eastern edge of the upper terrace. 

Analysis of the acoustic data produced some very interesting results reflecting topography, fish

community composition, and general geology. Figure 8.38A is an echogram showing a transition

from the middle to the upper terrace. Figure 8.38B is an enlargement of the area indicated in Figure

38A which shows a dense fish community just above the bottom. The acoustic system, not only

provided quantification of the fish community, but also both provided insight about geological

properties of the bottom (Figure 8.39A) and location natural gas seeps as in Figure 8.39B. Visual

analysis of the echograms would the flat sandy sections of bottom as smooth with high energy

returns and the coral features were equally easy to identify by shape and slightly lower energy

returns. For the purpose of analysis we divided WFGB into three terraces; upper = 20 – 50 m,

middle = 51 – 80 m, lower = 81 – 100 m. Depths greater than 100 m were considered to be open

water in our analysis. 

A binomial logistic regression with the presence/absence of SV as the dependent variable was used

to model the relationship between fish presence and class variables: Terrace, time of day, and

stratum (Table 8.6). All class variables were significant. Using logistic procedures without an

intercept provided insight into the relative differences within the class variables. The chance of

encountering a fish was highest over the upper terrace and lowest over open water. Stratum and

TOD were not significantly different in the variables, but were significant in the model. Illustrations

of the change in acoustic energy with depth can be seen in the horizontal volume backscatter (sum

of mean SV) throughout the water column. Figure 8.40 shows the horizontal backscatter (HSV) to

be highest over the upper terrace and middle terrace areas. When corrected for depth, (HSV/water

depth) as in Figure 8.41, is clear that the highest fish biomass occurs in the shallowest areas. Based

on logistic regression (without intercept), there was a 35 to 100 times greater chance of finding fish

over the upper terrace than over the middle or lower terraces. 
587

Figure 8.37. Recorded track lines of the WFGB hydroacoustic survey conducted in June 2000.
588

A.

B.

Figure 8.38. Echogram of WFGB survey conducted June 2000. (A). Screen image includes dB

color scale on left and depth on the right side; red box highlights an area of high

acoustic reflectance presumed to be fish and plankton. (B). Magnified image of a

gentle slope onto the upper Terrace (@40m); arrows highlight fish targets.
589

A.

B.

Figure 8.39. Echograms from June 2000 hydroacoustic survey of the WFGB. (A) Linear changes

in reflectance illustrate the value of hydroacoustics in characterizing bottom type.

(B) Large areas of low reflectance on the bottom are thought to be gas seeps on the

lower terrace.
590

Table 8.6. Logistic analysis results of fish energy (antilog of volume backscatter) with class

variables terrace level (Terrace), depth stratum (Stratum), and time of day (TOD) at

WFGB.

The Logistic Procedure

 Type III Analysis of Effects 

Effect DF Wald ChiSquarePr > ChiSq

TERRACE 3 5778 <.0001

Stratum 9 4852 <.0001

TOD 3 122 <.0001

Stratum*TOD 27 9329 <.0001

Analysis of Maximum Likelihood Estimates

Parameter DF Estimate Standard Error Chi-Square Pr > ChiSq

Intercept 1 -3.82 1.49 6.56 0.0104

TERRACE 1 1 0.39 0.01 1313.54 <.0001

TERRACE 2 1 0.66 0.01 3116.01 <.0001

TERRACE 3 1 0.18 0.01 273.18 <.0001

Mean fish energy was an order of magnitude higher over the upper terrace compared to the middle

and lower terrace and over open water (Figure 8.42). Fish energy also varied with TOD as energy

over the WFGB was an order of magnitude lower at noon that at other times of day. 

Estimated fish density ranged from 0 to 0 .005 fish/m3

 over the WFGB. When broken down by terrace, fish densities were highest over the upper terrace (Figure 8.42) just above the bottom at a depth

of about 30 meters and just above the bottom of the middle terrace at a depth of about 70 meters.

Similarly, densities on the lower terrace peaked just above the bottom at a depth of 90 meters but

were almost an order of magnitude less than the highest densities observed on the upper terrace.

Using RBD ANOVA to model the effect of class variables on fish size, fish size varied with terrace

and depth and their interactions. Fish were significantly larger over the upper terrace and near the

surface (Figure 8.43). Mean fish size over the WFGB was - 47dB (6.7 cm), and ranged from -65 to

-25 dB (1 to 108 cm) (Love 1971).
591

Figure 8.40. An image of the relative horizontal acoustic reflectance over a bathymetry outline

of the WFGB. These data are not corrected for depth as HSV is the sum of energy

from the surface to the bottom.

Figure 8.41. An image weighted by depth of the relative horizontal acoustic reflectance over

a bathymetry outline of the WFGB. Data are corrected for depth (HSV/depth in

meters).
592

0.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.010

0 2 4 6 8 10

Depth (x10m)

Fish Density

Open

Lower

Middle

Upper

-52

-50

-48

-46

-44

-42

-40

Upper Middle Lower Open 

Terrace

dB

Figure 8.42. Estimated density of fish (fish/m3) over the West Flower Garden Bank based on

a dual beam hydroacoustic survey conducted in June 2000. Error bars are 95%

confidence intervals.

Figure 8.43. Mean target strength (dB) by Terrace over the West Flower Garden Bank based

on a dual beam hydroacoustic survey conducted in June 2000. Error bars are

95% confidence intervals.
593

Species Composition and Abundance

The fish community at the WFGB was very diverse and reflected that of a typical coral reef

community. Creole-fish and Bermuda chub were the most abundant species present followed by

great barracuda and black durgon (Table 8.7). The ROV survey results likely represent only a small

cross-section of the total species present because we did not include cryptic species in the visual

survey.

Fish abundance at the WFGB was estimated around 2,500,000 (Table 8.8). The most abundant fishes

at the WFGB were Bermuda chub and creole-fish . There was roughly 630,000 bermuda chub and

485,000 creole-fish followed by 261,000 great barracuda 130,000 and black durgon.

DISCUSSION

This project again demonstrates the utility of dual beam hydroacoustics coupled with visual survey

techniques to study fish assemblages. The close geographical proximity of several previously

studied platforms, two artificial reef sites, and the WFGB provided us an opportunity to compare

stationary and mobile acoustic survey methods and to compare species composition, fish biomass,

and fish densities within and between platforms, artificial reefs, and a natural reef. Dual beam

hydroacoustics coupled with video surveys provide an efficient tool that is both economical and

environmentally friendly for assessing fisheries resources at these sites. 

Given the large number of zero values and the problem of autocorrelation that occurs in mobile

surveys Traditional parametric analyses were not used for analysis of mobile acoustic data. The use

of logistic regression in ecological sampling was described by Trexler and Travis (2001) as a

nonlinear way of expressing ecological data. Logistic regression has been shown to be useful with

data sets that have a large number of zero values which are usually not normally distributed. For

regression analysis, the dependent variable was converted into a binomial array of presence/absence

of acoustic reflectance (fish measured as acoustic energy)/m3

 to evaluate the probability or chance

of finding a fish in a given cell. Each cell was defined as a one second block of time divided into

10 m depth strata. One second of time equals 2m of linear distance. Volume backscatter (SV) was

used as a dependent variable in performing logistic regression because SV is the mean measured

amount of acoustic energy returned from each acoustic ping, averaged for a cubic meter of water

column. Stanley and Wilson (1997) used fish density (#/m3) as the dependent variable, but this value

is very sensitive to crossectional backscatter also known as sigma (fish size). Sigma accuracy

increases with the number of times a single target is pinged which works well for the standing

platform survey where the transducer is stationary. During the WFGB survey the transducer was

towed along at 2m/sec which significantly reduced the chance of pinging a single target several

times in a row. 

Due to the uncertainty of the accuracy of TS, the accuracy of density becomes uncertain. This made

SV a better proxy for fish presence, hence the dependent variable in our models. If there was a

statistically significant affect by a class variable indicated in the logistic regression analysis, then

the procedure was re-run using a no intercept option. The resultant Odds Ratio Estimates provide
594

Table 8.7. Species common names and scientific names along with numbers of individuals by

stratum, totals, and percent composition from visual point counts using video from a

remotely operated vehicle (ROV) from the West Flower Garden Banks, June 2000.

West Flower Garden Banks June 2000

Common

Name

Scientific

Name 0 m 10 m 20 m 30 m 40 m 50 m 60 m 70 m 80m 90 m Totals %

Almaco jack Seriola rivoliana - - - - - - 2 - - - 2 1.1

Bermuda chub Kyphosus sectatrix - 56 1 - - - - - - - 57 32.0

Bar jack Caranx ruber - 1 1 - - - - - - - 2 1.1

Great Barracuda Sphyraena barracuda - 22 - - - - - - - - 22 12.4

Black durgon Melichthys niger - - 11 - - - - - - - 11 6.2

Black jack Caranx lugubris - 1 - - - - - - - - 1 0.6

Bluehead Thalassoma

bifasciatum

- - 1 - - - - - - - 1 0.6

Blue runner Caranx crysos - - - 8 - - - - - - 8 4.5

Blue tang Acanthurus

coeruleus

- - - 4 - - - - - - 4 2.2

Cocoa damselfish Pomacentrus

variabilis

- - 3 - - - - - 1 - 4 2.2

Creole-fish Paranthias furcifer - - 38 - - - - - - 3 41 23.0

Dog snapper Lutjanus jocu - - 1 - - - - - - - 1 0.6

French angelfish Pomacanthus paru - - - - 2 - - - - - 2 1.1

Grey triggerfish Balistes capriscus - - - - 1 - - - - - 1 0.6

King mackerel Scomberomorus

cavalla

- - - - - - - - 1 - 1 0.6

Knobbed porgy Calamus nodosus - - - - 1 - - - - - 1 0.6

Ocean triggerfish Balistes vetula - 1 - - - - - - - - 1 0.6

Bank butterflyfish Chaetodon aya - - - - - - - - - 6 6 3.4

Scamp Mycteroperca

phenax

- - - - - - 2 - - - 2 1.1

Short bigeye Pristigenys alta - - - - - - - - 1 4 5 2.8

Spanish hogfish Bodianus rufus - - - 1 - - - - - - 1 0.6

Squirrelfish Holocentrus

adscensionis 

- - - - - - - - - 2 2 1.1

Trumpetfish Aulostomus

maculatus

- - - - 1 - - - - - 1 0.6
595

a comparison of probabilities of fish occurring within that class variable. The effect of each class

variable was visualized by plotting SV and estimated fish density by significant class variables.

Our survey of the WFGB affords the first direct acoustic comparison of fish communities between

natural reefs and artificial reefs in the same geographic region. The utilization of hydroacoustics for

this survey allowed data collection around the clock with a minimal use of labor resources thus

allowing the completion of the survey in a relatively short amount of time. The non-invasive manner

of the sonar system enabled comprehensive data of the fisheries population with the least

environmental impact. We recognize some that the absolute estimates of fish numbers are likely

skewed due to the uncertainty of target strength estimates. However these data do provide a basis

for comparisons between the two types of habitats. The highest densities were found over the upper

terrace of the WFGB where they were two to three orders of magnitude greater than the middle or

lower terraces. The fish size was also larger over the upper terrace and smallest over the open water

areas of the WFGB. It is now clear that the fish densities around a standing platform, and the

resultant artificial reef configurations of toppled in place or partially removed platforms, are greater

than that nearby WFGB habitat on a per unit area basis. The WFGB supports well over 2 million

fish that can be detected by acoustics, this fish biomass appears to be rivaled by the fish populations

of some 150 platforms in water depths ranging from 100 to 300 m water depth based on our survey

of HI 350 and the previous surveys.

Not only are we interested in comparing the natural reef to an artificial reef but we also wished to

compare our results to previous studies of the WFGB. The most extensive study of the fish

community and WFGB was conducted by Boland et al. (1983). Boland et al. (1983) utilized divers

and video surveys to document species composition at the both Flower Garden Banks. Most of their

efforts were focused on the more cryptic reef species near the bottom. Of great interest is that our

estimates of the fish populations at WFGB are along the same order of magnitude as those reported

in Boland et al. (1983). For example, Boland et al. (1983) reported from 400,000 - 900,000 creolefish on the WFGB. We estimate that there was 23% of 2,500,000, or 575,000 creole-fish at the time

of our survey. Note that these studies were nearly 20 years apart. Given the techniques used by

Boland et al. (1983), they identified more than twice the number of species that we found as they

included the numerous cryptic reef species. We found 8 of the 16 primary species reported by

Boland et al. (1983) from the WFGB of these 16, seven were cryptic and not targeted in our study.

Fish populations near reefs, both natural and artificial, are highly variable over time and space, and

these variations in abundance are the result of many factors which include, but are not limited to,

competition, seasonality, physical perturbation, ontogenetic changes, predation, recruitment,

emigration and immigration (Sale 1990; Bohnsak et al. 1991; Sale 1991). Reefs are thought to be

nonequilibrial systems with their occupants constantly changing (Sale 1991) thus population

estimates often vary by an order of magnitude over monthly surveys (Sale 1990; Bohnsak et al.

1991; Sale1991; Stanley 1994) and are equally divergent over spacial scales. A reef’s size, structure,

depth, and location all play an important role in the heavily disputed attraction verses production

issue and are also important in determining fish densities at artificial reef sites and natural reefs. 

This research continues to support the working hypothesis that platforms do make useful artificial

reefs since they tend to support a population of fish that can be 10 to over 1000 times greater in
596

density than the adjacent sand and mud bottom habitats and are equal to or even exceed that of the

limited coral reef habitat in the Gulf of Mexico. Densities of fishes away from platforms, the lower

terrace of the WFGB, and open water range from 0 to 0.0001 FPCM and adjacent to standing

platforms and over reef sites range from 0 to 10 FPCM depending upon site.

REFERENCES

Bohnsack, J.A. and S.P. Bannerot. 1986. A Stationary Visual Census Technique for Quantitatively

Assessing Community Structure of Coral Reef Fishes. NOAA Technical Report NMFS 41. 15

pp.

Bohnsack, J.A., D.L. Johnson, and R.F. Ambrose. 1991. Artificial habitats for marine and freshwater

fisheries. Ecology of Artificial Reef Habitats. Academic Press. New York, New York. 61-108

pp. 

Boland, G. S., B. J. Gallaway, J. S. Baker and G. S. Lewbel. 1983. Ecological Effects of energy

development on reef fish of the Flower Garden Banks. Ecological Research Associates, Inc.,

Bryan, Texas. 466 pp.

Bright, Thomas J., John W. Tunnell, Linda H. Pequegnat, Thomas E. Burke, Cara W. Cashman,

Dennis A. Cropper, James P. Ray, R. Christopher Tresslar, Joyce Teerling and J.B. Wills. 1974.

Biotic zonation on the West Flower Garden Bank. Texas A&M University, University of

Southwestern Louisiana and University of Houston. 1-54.

Bright, Thomas J. and Cara W. Cashman. 1974. Fishes. Biotic zonation on the West Flower Garden

Bank. Texas A&M University, University of Southwestern Louisiana and University of

Houston. pp. 340-409.

Brock, R.E. 1982. A Critique of the Visual Census Method for Assessing Coral Reef Fish

Populations. Bulletin of Marine Science. 32:269-276 pp.

Dennis, George D. and Thomas J Bright. 1988. Reef fish assemblages on hard banks in the

northwestern Gulf of Mexico. Bulletin of Marine Science. 43(2): 280-307.

Dokken, Q.R., I.R. MacDonald, J.W. Tunnell, C.R. Beaver, G.S. Boland, and D.K. Hagman. 1999.

Long- Term Monitoring at the East and West Flower Garden Banks,1996-1997. U.S.

Department of the Interior, Minerals Management Service, OCS Study/ MMS 99-0005. 1-7.

Elvers, Douglas J. and Charles W. Hill, Jr. 1985. History of Activities at the Flower Garden Banks.

Pages 3- 10 in The Flower Gardens: A Compendium of Information. U.S. Department of the

Interior, Minerals Management Service, OCS Study/ MMS 85-0024. Bortone, S.A. and J.J.

Kimmel. 1991. Environmental Assessments and Monitoring of Artificial Habitats. Artificial

Habitats for Marine and Freshwater Fisheries. Academic Press, New York, New York. 177-236

pp.
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Gardner, J. V., Larry A. Mayer, John E. Hughes Clarke , Art Kleiner.1998. High- Resolution

Multibeam Bathemetry of East and West Flower Gardens and Stetson Banks, Gulf of Mexico.

Gulf of Mexico Science. Vol.16 No. 2:131-143.

Garrison, L.P., W. Michaels, J.S. Link, and M.J. Fogarty. 2000. Predation Risk on Larval Gadids

by Pelagic Fish in the Georges Bank Ecosystem. I. Spatial overlap associated with hydrographic

features. Canadian Journal of Fisheries and Aquatic Sciences. 57: 2455-2469.

Gittings, Steve R. and Emma L. Hickerson. 1998. Introduction. Gulf of Mexico Science. Vol.16 No.

2: 128.

Grossman, G.D., G.D. Jones, and W.J. Seaman Jr. 1997. Do Artificial Reefs Increase Regional

Fisheries Production? A Review of Excising Data. Fisheries. 22: 17-23.

Love, R.H. 1971. Dorsal Aspect Target Strength of an Individual Fish. Journal of Acoustic Society

of America. 62:1397-1403.

Rooker, J. R., Q. R. Dokken, C. V. Pattengill and G. J. Holt. 1997. Fish assemblages on artificial

and natural reefs in the Flower Garden Banks National Marine Sanctuary, USA. Coral Reefs.

16: 83-92.

Sale, P.F. 1990. Recruitment of Marine Species: Is the Bandwagon Rolling in the Right Direction?

Trends in Evolutionary Ecology 5:25-27 pp.

Sale, P.F. 1991. Reef Fish Communities: Open Nonequilibrial Systems. 564-600pp. 

Sale, P.F. editor. The ecology of fishes on coral reefs. Academic Press. New York, N.Y.

SAS Institute Incorporated. 2000. SAS user’s guide: Statistics. Version 8. SAS Institute. Cary, NC.

1290 pp.

Stanley, D.R. 1994. Seasonal and Spatial Abundances and Size Distribution Associated with a

Petroleum Platform in the Northern Gulf of Mexico. Dissertation. Louisiana State University.

Trexler, J.C. and J. Travis. 2001. Nontraditional Regression Analysis. Ecology. 74(6): 1629-1637.
599

SESSION 9: 

EVALUATION OF NATURAL AND/OR

ARTIFICIAL REEF PRODUCTIVITY II

Moderators: Kathy Scanlon

Quenton Dokken

Date: October 26, 2000

Presentation Author/Affiliation

Secondary Productivity Within Biotic

Fouling Community Elements o Artificial

Reef Structures in the Northwestern Gulf

of Mexico

Carl Beaver

Susan Childs

Quenton Dokken

Center for Coastal Studies

Texas A&M University-Corpus Christi

Settlement of a Colonial Ascidian on an

Artificial Reef in the Gulf of Mexico

Jan Culbertson

Donald E. Harper, Jr.

Artificial Reef Program

Texas Parks and Wildlife Department and

Department of Marine Biology

Texas A&M University at Galveston

Reef Balls TM: How Combining Designed

Reefs with Oil Superstructures Used as

Artificial Reefs Can Help the Overall

Reef System to Better Mimic Natural

Reef Systems

Todd Ryan Barber

President, Reef Ball Development Group, Ltd.

Chairman, Reef Ball Foundation, Inc.

Red Snapper Site Fidelity to, and Speed

of Movement from, Artificial Reef Sites

off Alabama in the Northern Gulf of

Mexico

William F. Patterson

James H. Cowan

Robert L. Shipp

Department of Marine Sciences

University of South Alabama

Abundance, Age Distribution, Growth

Rate, and Mortality Estimations for Red

Snapper, Lutjanus Campechanus, Around

Gas Platforms and Other Artificial

Structures in the Northeast Gulf of

Mexico

Stephen T. Szedlmayer

Carol Furman

Dustin Moss

Marine Fish Laboratory

Department of Fisheries and Allied

Aquacultures

Auburn University

(continued on next page)
600

Presentation Author/Affiliation

Movement, Growth, and Survival of Gray

Triggerfish, Balistes Capriscus,

Inhabiting Artificial and Natural Reefs in

the Northcentral Gulf of Mexico

G. Walter Ingram, Jr.

Robert L. Shipp

Red Snapper (Lutjanus Campechanus)

Diet on Alabama Artificial Reefs

Jessica R. McCawley

Robert L. Shipp

University of South Alabama/

Dauphin Island Sea Lab

James H. Cowan, Jr.

Louisiana State University

Coastal Fisheries Institute
601

SECONDARY PRODUCTIVITY WITHIN BIOTIC FOULING COMMUNITY

ELEMENTS ON TWO ARTIFICIAL REEF STRUCTURES IN

THE NORTHWESTERN GULF OF MEXICO

Carl Beaver

Susan Childs

Quenton Dokken

Center for Coastal Studies

Texas A&M University-Corpus Christi

ABSTRACT

Secondary productivity of two platform artificial reefs was examined seasonally. The study

examined seasonal differences and annual secondary productivity of epifaunal elements associated

with the fouling community, known to be specific to the diets of selected reef fishes. Examination

of the fouling community using cohort-size analysis revealed the annual amphipod production of

3-4 cohorts per species/yr-1. Seasonal variations in amphipod density were striking, ranging from

600 to nearly 12,680 individuals/m2. Densities were correlated with water temperature and depth.

Mean standing stock in mgDW/m2 was used as a measure of productivity and also varied

significantly depending on season and species. Mean standing stock ranged from 16.33 to 1024.6

mgDW/m2. Annual production ranged between 64 and 4100 mgDWAm-2Ayr-1 .

This study has implications for the placement of platform structures for the purpose of productivity

enhancement. It is clear that secondary productivity from the platform structures is significant and

does supplement the diets of reef dependent finfish. 

INTRODUCTION

There is little debate as to the ability of artificial reef to increase productivity of sessile invertebrate

organisms. Several authors (Smith et al. 1979; Gallaway and Lewbell 1982; Jessee et al.; 1985; Bull

1990) have noted and/or described the diverse assemblages of organisms associated with artificial

reef fouling communities, however none have examined the secondary productivity of these

communities. An examination of productivity of fouling community organisms contributing to the

diets of fishes is critical to defining the potential contribution of these reef systems to fish stocks.

The idea that platform reefs increase fouling community biomass in an area is one that generates

little argument. The amount of energy production contributing to or potentially contributing to the

diets of fishes is a point of contention. It is the purpose of this research to characterize composition

and estimate the biomass and energy content of the fouling community potentially contributing to

the diets of selected fishes on platform reefs in the western Gulf of Mexico.
602

This research has identified those elements of the fouling community that comprise a sizeable

portion of the diet of selected reef-dependent fishes and determined the annual production and

energy levels of these elements.

METHODS

Data pertaining to fouling community composition was collected quarterly for seven quarters from

the EB165A platform. Company down-sizing and unmanning of the HI389A by Mobil Exploration

and Production precluded continued sampling at the platform, consequently only five quarterly

samples were collected from this site.

Fouling-community development was quantitatively assessed seasonally using photographic transect

techniques. Photographic transects, as described by Liddell and Ohlhorst (1991), were taken using

a Nikonos V underwater camera and 28mm Nikonos lens mounted on a frame that supports twin

Nikonos SB 102 strobes. Attached to the camera is a steel rod holding a standard of measure and

an electronic depth meter. The standard of measure and depth meter are clearly visible in each

image. This device ensures each image is taken at a predetermined distance from the substrate. The

standard of measure allows for calibrating image size while the depth meter provides a record of

depth for each image. All photo transects were shot using Fujichrome 100 slide film at a fixed

distance of 0.4 m from the substrate. This system produces color transparency images of

approximately 0.20 m2

 of platform substrate. Vertical transects followed the platform structure from

the surface to a depth of 53 m. A photograph was taken approximately every 1.5 m. Transparencies

were projected at a size ratio of 1:1 onto a screen marked with 25 randomly located points. The

image superimposed on each point was identified to the lowest possible taxon and recorded. Images

that were difficult to identify when projected were examined under a stereoscopic microscope. This

technique improves resolution and often aids in identification of the organism in question. A total

of 533 (369 for HI389A and 164 for EB165A) transparencies were analyzed providing 13,325 data

points.

A diversity index was computed for every transparency at each depth on each transect using the

Shannon Diversity Index (Shannon 1948). The diversity of each depth across all transects was

subjected to Analysis of Variance (ANOVA) procedures to determine significant differences in

fouling community diversity along the depth gradient. Tukey’s Mean Separation Test was used to

determine differences in mean species diversity between depth zones.

Rugosity measurements (linear measurements of the relief created by fouling community organisms)

were taken at 2.86 m intervals for all depths from the surface to 53 m. Rugosity was determined by

measuring the relief created by the fouling community organisms between two points set 1m apart.

A mean rugosity was calculated for each 2.86 m depth increment. Rugosity for each increment is

defined as:

R = Σ 3(X+1) -1

3
603

These data were analyzed to determine species diversity, density, richness and evenness of the

sessile fouling community. These data were also used to identify zones of significantly differing

diversity of cryptic fauna within the sessile fouling-community.

Standing stock of benthic invertebrates within the fouling-community was quantitatively assessed

seasonally by examination of biomass samples. Samples were taken every 3 m from a depth of 53

m to the surface at both HI389A and EB165A. Sampling at HI389A was conducted from February

1995 through March 1996. Sampling at EB165A was conducted from September 1995 through July

1997. Seventy-two, 100 cm2

 samples of the fouling community were scraped from the EB165A

platform and forty-seven, 100 cm2 samples were collected from the HI 389A platform.

All samples were scraped from the steel structure and placed into plastic bags. On the surface,

samples were drained of most of the seawater and preserved in a 45% isopropyl alcohol solution for

later examination in the laboratory. Light and water temperature were recorded using Light-Tab

recording light meters and Hobo-Temp thermisters (Onset Instruments Corporation 1995)

In the laboratory, samples were rinsed in tap water and decanted through a 0.4 mm sieve. Samples

were then sorted under a dissecting microscope to remove remaining non-sessile organisms.

Invertebrate organisms were identified and divided into prey organisms and non-selected organisms

through comparison to data obtained from analysis of reef fish stomach contents. An additional 27

samples, 12 from HI389A and 15 from EB165A, were collected and frozen for caloric analysis of

cryptic fouling community diet organisms. Prey organisms were identified, enumerated and

measured to the nearest 0.5 mm. All samples were dried at 60o

 C until a stable weight was obtained.

Population levels per m2 for prey organisms were extrapolated from counts obtained from the

samples. Annual production estimates were calculated using the cohort biomass increment method

(Crisp 1971). This method requires that the number of cohorts be established by size frequency

analysis and that each cohort be analyzed separately. Total production (mgDW •m-2 •yr-1) is

estimated as the sum of production values calculated separately for each cohort based on growth

increments over the life of the cohort such as:

P = Σ fi wi Gi )t

where n = the number of size classes;

fi= the mean number of individuals in the size class i for the period )t,

wi= the mean weight of individuals of size class i and 

Gi

= the weight specific growth rate of individuals of the size class i in period )t.

Caloric values of diet elements were determined from direct calorimetry or by comparison to

published caloric values when available. Direct calorimetry employed the use of a Phillipson

Microbomb Calorimeter. Available energy was determined by multiplying the sum of production

estimates (gDW Am-2 Ayr-1) by the caloric value (kcal/gDW) for each prey organism.
604

RESULTS

Secondary Productivity of Sessile Fouling Community

Four sessile fouling community organisms were found to comprise more than 1% of the diets of any

of the reef fish examined. The bivalves Isognomon bicolor and Pteria colymbus as well as the

barnacles Balanus amphitrite and Balanus reticulata were found in the stomachs of the gray

triggerfish Balistes capriscus. Densities of Isognomon bicolor ranged from 1014 to 4112

individuals/m2

 (mean=2931). Using an ash weight of 10.5% of dry weight and a caloric value of

4.24 kcal/gDW (calculated from Dauvin and Johncourt 1989) we have calculated a standing stock

energy value for I. bicolor of 7692.1 kcal/m2. Pteria colymbus densities were 0.4 /m2 and standing

stock energy values were 11.1 kcal/m2.

For the barnacles Balanus amphitrite and Balanus reticulata, densities were estimated at 312 and

114 individuals/m2

, respectively. Using a measured ash weight of 8.8% dry weight and a caloric

value of 4.39 kcal/gDW, we estimate standing stock energy values to be 3661.7 kcal/m2 for B.

amphritite and 1340.7 kcal/m2

 for B. reticulata..

Secondary Productivity of the Motile Fouling Community

Several species of amphipods were the only organisms among the motile fouling community fauna

to show significant variation in population densities and standing stock levels. Most species

displayed increasing densities throughout the spring and early summer, reaching maximum

population densities by late summer. Densities generally displayed a distinct correlation with water

temperature, with greatest population densities occurring near maximum or minimum annual water

temperatures dependent on species (Figure 9.1, Figure 9.2, and Figure 9.3).

Production Estimates for Amphipods

Length frequency analysis of amphipods suggests that, in all species, several generations are

produced during the year. For Gammarus sp. the life span is approximately 3-4 months during

warmer months and between 4 and 6 months during colder periods. Gammariideans exhibit three

generations per year with one each during the spring and summer then a fall generation that

overwinters. Spring and summer cohorts display rapid growth and experience heavy mortality. The

cool-water generation is longer-lived, but slow growing. 

Population levels also exhibited a negative correlation with depth. Population levels for Gammarus

sp. were greatest within 5m of the surface and decreased with increasing depth to 30m. Population

levels of this amphipod ranged from 390–12,680 individuals/m2

 with a mean of 5887 individuals/m2

(sd 1268). Population levels were greatest during late spring when more than one cohort was

present. Population levels were lowest during late winter-early spring, when a single cohort at the

end of its life span was present.
605

0

100

200

300

400

500

600

700

Fall 1995

Spring 1996

Summer 1996

Fall 1996

Winter 1996

Spring 1997

Summer 1997

Quarter

Standing stock mgDW/m-2

0

5

1 0

1 5

2 0

2 5

3 0

Temperature

Standing Stock 

Temperature

0

100

200

300

400

500

600

Fall 1995

Spring 1996

Summer 1996

Fall 1996

Winter 1996

Spring 1997

Summer 1997

Quarter

Standing stock mgDW/m-2

0

5

10

15

20

25

30

Temperature

Standing Stock 

Temperature

Gammarus sp. 

Corophium sp. 

Figure 9.1. Relationship between temperature and standing stock for the amphipods

Gammarus sp. and Corophium sp. at EB165A and HI389A.
606

0

10

20

30

40

50

60

70

Fall 1995

Spring 1996

Summer 1996

Fall 1996

Winter 1996

Spring 1997

Summer 1997

Standing stock mgDW/m-2

0

5

10

15

20

25

30

Temperature

Standing Stock

Temperature

0

10

20

30

40

50

60

70

Fall 1995

Spring 1996

Summer 1996

Fall 1996

Winter 1996

Spring 1997

Summer 1997

Standing stock mgDW/m-2

0

5

10

15

20

25

30

Temperature

Standing Stock

Temperature

Corophium biglovia 

Corophium louisiana 

Figure 9.2. Relationship between temperature and standing stock for the amphipods

Corophium biglovia and Corophium louisiana at EB165A and HI389A.
607

0

200

400

600

800

1000

1200

1400

1600

1800

Fall 1995

Spring 1996

Summer 1996

Fall 1996

Winter 1996

Spring 1997

Summer 1997

Quarter

Standing stock mgDW/m-2

0

5

10

15

20

25

30

Temperature

Standing Stock 

Temperature

Caprella equlibris 

Figure 9.3. Relationship between temperature and standing stock for the amphipod Caprella

equlibris at EB165A and HI389A.

Mean standing stock was 372.85 mgDW/m2, and total annual production was estimated at 38,791.3

mgDW •m-2 •yr-1 or 38.79 gDW •m-2 •yr-1. Caloric content for this species ranged between 3.6 and

4.12 with a mean value of 3.87 kcal/g (Table 9.1).

There were 3 distinct cohorts of Corophium sp. observed in samples. This species has a life span of

3-4 months during the warmer months and 4-5 months during colder months. Densities ranged from

600–11,010 individuals/m2 with a mean 4082 individuals/m2 (sd 1417). Greatest numbers occurred

during late summer when the spring and summer cohorts were both present. Lowest numbers were

observed during late winter prior to the appearance of the spring cohort. A fall cohort that apparently

over-winters appears between mid October and early November.

This species displayed a disposition for horizontal structure with population levels being

significantly greater on horizontal substrate of the reef structure above 10m depth. Mean standing

stock was estimated to be 222.8 mgDW/m2 (sd 89.4). Three cohorts per year are produced with two

fast growing cohorts appearing in the late spring and another in late summer. A slower growing,

longer-lived, over-wintering cohort appearing in late fall. Estimated annual production of

Corophium sp. was 5467.9 mgDW •m-2 •yr-1. Population levels of Corophium sp. varied

significantly between summer sampling periods. During the summer of 1996 population levels were

estimated to be 552 individuals/m2

, while summer 1997 levels were estimated at 187 individuals/m2

(Table 9.2). Corophium biglovia displayed a density range of 183–1425 individuals/m2 (mean 785,
608

Table 9.1. Cohort Statistics for the amphipod Gammarus sp. at HI389A from March 1995-August

1995. Production estimated using biomass increment method (Crisp 1974).

Cohort 1

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

 15-Mar 2 0.4 4,760 0.006 28.5 

7-Apr 23 3.5 0.7 3,240 0.162 524.8 5.70 2,992.64 

30-Apr 23 4 0.5 2,250 0.197 443.25 1.28 567.00 

9-May 10 4.12 1.1 2,600 0.217 712.4 6.57 3,704.85 

28-May 19 4.91 0.6 390 0.346 182.9 8.63 1,165.15 

 Total 75 8,429.64 

Cohort 2

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

 9-May 10 0.75 0.25 12,680 0.006 76.08 

28-May 19 1.25 0.5 10,500 0.015 157.5 0.49 76.71 

16-Jun 18 1.7 1.1 9,150 0.036 329.4 0.75 247.66 

7-Jul 21 2.3 1.8 7,900 0.071 560.9 14.14 7,930.28 

3-Aug 27 2.9 2.6 5,400 0.132 712.8 1.89 1,352.93 

 Total 95 9,607.59

Table 9.2. Cohort Statistics for the amphipod Corophium sp. at EB165A, September 1996-July

1997. Production estimated using biomass increment method (Crisp 1974).

Cohort 1

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

25-Sep 0.75 0.2 3,475 0.0047 16.3

15-Oct 21 1.9 0.25 2,340 0.041 95.9 1.45 139.52

21-Oct 6 2.1 0.5 2,247 0.055 123.6 1.96 242.92

20-Dec 61 3.25 0.5 1,257 0.157 197.3 1.41 277.54

7-Feb 49 3.75 0.5 600 0.214 128.4 0.98 125.76

Total 137 785.74

Cohort 2

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

15-Mar 36 0.5 0.25 11,010 0.0003 3.3

23-Apr 39 1.75 0.25 9,820 0.051 500.1 1.10 550.67

17-Jul 85 4.25 0.25 1,912 0.376 718.0 3.21 2,308.94

Total 160 2,859.61
609

sd 164). Mean standing stock was estimated to be 33 mgDW/m2 (sd 9.2). C. biglovia is estimated

to produce 3-4 cohorts each year with one each in spring, summer and fall and a slow growing overwintering cohort in the winter. Estimated annual production for this species was the lowest of all

amphipod diet elements at 534.4 mgDW •m-2 •yr-1 (Table 9.3).

Populations of the amphipod Corophium louisiana ranged from 2395–5725 individuals/m2 with a

mean of 4189 (sd 498). Mean standing stock was estimated to be 570.1 mgDW/m2 (sd 132.7). Three

cohorts are produced yearly. Annual production is estimated at 4379.3 mgDW •m-2 •yr-1. This

species displayed a significant difference in population levels within fall sampling periods. Fall 1995

population levels were estimated at 443 individuals/m2 while population levels during the fall 1996

sampling period were estimated to be 213 individuals/m2 (Table 9.4).

Two species of Corophium displayed a positive correlation in standing stock levels with

temperature. Corophium sp. and Corophium biglovia standing stock levels and populations were

greatest during summer and fall sampling periods. Corophium sp. ranged from 3.3 mgDW/m2

 in the

spring of 1996, immediately after mean low water temperature to 718 mgDW/m2 duringthe summer

of that same year, immediately prior to mean maximum water temperature. Corophium biglovia

standing stocks ranged from 7.5 mgDW/m2 during the spring of 1996 to 110 mgDW/m2 immediately

following mean maximum water temperature. Corophium louisiana displayed a negative correlation

with water temperature with standing stocks being greatest during the period of mean minimum

water temperature.

Caprella equlibris, the largest of platform amphipods, had a density range of 612–1,746

individuals/m2 (mean 1105, sd 139). Mean standing stock was estimated to be 775.1 mgDW/m2 (sd

165.0). This large, longer-lived species produces 3 cohorts/yr1

. Estimated annual production is

39,927.8 mgDW •m-2 •yr-1 or 39.98 gDW •m-2 •yr-1. Caprella equlibrus displayed a significant

negative correlation with temperature with the greatest numbers being present prior to minimum

annual water temperatures (Table 9.5).

Total production for the five species was estimated at 89,100.7 mgDW •m-2 •yr-1 or 89.1 gDW •m-2

•yr-1. No significant difference in caloric content was determined between the five species of

amphipods except in the case of gravid females. Mean kcal/g of non-gravid amphipods was 4.31

(N= 11, sd 0.74). Annual amphipod production was determined to be 384.38 kcal •m-2 •yr-1. Caloric

content of gravid female amphipods were not determined due to small sample size.

DISCUSSION

Although similarities existed between the types and species of sessile fouling community organisms,

the degree of development was very different. Both rugosity and diversity were greater at the

HI389A platform mainly due to the presence and numbers of large bodied sponges. The lower

diversity and lack of development of large sponges at the EB165A platform may be due to relatively

strong currents. No data exists on water currents at these two platforms, however on several

occasions, underwater work at EB165A had to be halted or postponed due to the dangers associated

with working in strong currents. It is likely that these strong currents have an adverse effect in the
610

Table 9.3. Cohort Statistics for the amphipod Corophium biglovia at EB165A, September 1996-

April 1997. Production estimated using biomass increment method (Crisp 1974).

Cohort 1

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

25-Sep 2.50 0.25 745 0.065 48.40

15-Oct 21 2.75 0.50 314 0.109 34.20 1.78 60.83

21-Oct 6 2.75 0.50 345 0.118 40.70 1.26 51.44

20-Dec 61 3.25 0.50 183 0.161 29.50 0.59 17.47

Total 88 129.74

Cohort 2

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

20-Dec 61 0.50 0.25 1,425 0.003 4.27 0.04 0.18

7-Feb 49 0.75 0.25 1,250 0.006 7.50 0.05 0.39

15-Mar 36 1.25 0.50 1,075 0.014 15.05 0.02 0.28

23-Apr 39 2.50 0.50 950 0.089 84.55 1.62 136.71

Total 185 137.56

Table 9.4. Cohort Statistics for the amphipod Corophium louisiana from EB65A, October 1996-

April 1997. Production estimated using biomass increment method (Crisp 1974).

Cohort 1

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

21-Oct 6 1.00 0.5 3,215 0.008 25.7

20-Dec 61 2.00 1.0 5,000 0.143 710.0 1.86 1,330.86

7- Feb. 49 3.25 1.0 4,700 0.218 1,024.6 1.29 1,320.45

Total 116 2651.31

Cohort 2

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

7-Feb 49 1.00 0.5 5725 0.091 520.9

15-Mar 36 2.75 1.0 4100 0.150 615.0 0.14 84.73

23-Apr 39 3.50 1.5 2395 0.219 524.5 1.49 780.26

Total 124 864.99
611

Table 9.5. Cohort Statistics for the amphipod Caprella equlibris at EB165A, September1996-April

1997. Production estimated using biomass increment method (Crisp 1974).

Cohort 1

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

 25-Sep 6.5 1.5 1,407 0.49 689.4

15-Oct 21 7.0 1.7 1,312 0.57 747.8 3.23 2,416.76

21-Oct 6 8.8 1.5 1,586 0.62 1221.2 28.08 27,611.58

20-Dec 61 12.5 1.8 1,746 0.98 1711.1 2.89 4,954.31

7-Feb 49 14.0 2.8 685 1.09 746.65 1.89 1,411.29

 Total 137 36,393.94

Cohort 2

Date Days Length

(mm)

SD Estimated

Density

Mean

mgDW

Estimated

mgDW/m2

Growth

Rate

Production

 20-Dec 61 4.2 0.75 1,012 0.38 384.6

7-Feb 49 5.9 1.2 867 0.47 407.5 1.55 630.18

15-Mar 36 8.2 2.75 612 0.67 410.0 0.47 191.51

23-Apr 39 10.0 2.5 723 0.87 629.0 4.31 2,712.23

 Total 185 3,533.92

degree of development of the sessile fouling community. Population levels of certain diet elements

within the sessile fouling community were affected by the presence of sponges as well. Certain

species of encrusting sponges, mainly Neofibularia nolitangere display seasonal growth patterns.

During warmer months this species would encrust large areas of the structure effectively choking

out low relief members of the community such as barnacles and small bivalves. During cooler

months this species would disintegrate leaving large patches of substrate exposed. These areas

would generally be recolonized by faster growing elements such as hydroids, which would then be

displaced if the sponge colony regenerated during the next warming period. Consequently, the

original community of slow growing bivalves and barnacles would be permanently displaced.

The species composition of the sessile fouling community has a direct effect on the production of

certain cryptic faunal diet elements. No amphipods were found in scraping samples that contained

greater than 80% siliceous sponges. Presumably the lack of amphipods in this type of sponge can

be explained by the presence of silicone spicules that give the sponge its structural strength. These

spicules can become lodged between the plates of the carapace of crustaceans causing irritation and

possibly death (Personal observation).

Diversity among the platform’s sessile fouling community is also affected by the configuration of

the structural supports. In both platform communities a significant decrease in diversity was

observed at the level of horizontal supporting structures. Significantly differing diversity was
612

observed approximately 1m above and below the horizontal supports. This reduction occurred at

23m at EB165A and 36.5m at HI389A. The decrease in diversity at these horizontal members is

presumed to be caused by grazing animals associated with the horizontal structure. It is important

to note however, that the diversity of motile invertebrates increased at the horizontal members.

These areas are important to small motile and semi-motile animals as they provide protection from

currents and collect detritus and other food materials as the settle out of the water column (Gallaway

and Lewbell 1982; Bull and Kendall 1994).

Annual production for the three species of Corophium at the platforms ranged from 0.53 gDW •m-2

•yr-1 (C. biglovia) to 5.5 gDW •m-2 •yr-1 (Corophium sp). These estimates are somewhat lower than

production estimates from published studies. Franz and Tanacredi (1992) estimated annual rates of

secondary production of the amphipod Ampelisca abdita (12 -22 gDW •m-2 •yr-1) for Jamaica Bay,

New York, suggesting these levels are higher than most other marine amphipods. Mossman (1978)

and Moller and Rosenberg (1982) estimated the secondary production of the amphipod Corophium

volutator to be 13.4 gDW •m-2 •yr-1, while Birklund (1977) estimated secondary production of

Corophium insidiosum to be 8-60 gDW •m-2 •yr-1. Although these published estimates are higher,

it should be noted that these were monotypic populations from temperate waters.

All three Corophium species on the platforms are benthic, facultative, tube-dwelling amphipods that

showed a distinct preference for horizontal structure. This is likely related to the difficulty associated

with maintaining a hold on vertical surfaces. Generally Corophium tubes are constructed of finegrained sediments bound together by mucus in a hollow tube shape. The tubes are not cemented to

the substrate, but instead, are buried in fine-grained sediments. On platform artificial reefs, these

sediments are generally only found on horizontal structures protected from waves, surge and current.

The lack of suitable habitat i.e., protected, horizontal structure in shallow water covered with fine

grained sediment, make platform artificial reefs a marginal habitat for tube dwelling amphipods.

Conversely, high diversity fouling communities appear to be suitable for the development of other

species of amphipods. Gammarus sp. produced an estimated 38.79 gDW •m-2 •yr-1, while Caprella

equlibris produced an estimated 39.98 gDW •m-2 •yr-1. High levels of production in both species

were common in areas with a moderate to high diversity of fouling community organisms other than

sponges.

Weather conditions and company scheduling negated sampling during the winter of 1995-1996.

Consequently, maximum population levels of winter spawning amphipods i.e. Caprella equlibris

and Corophium louisiana, were based on a single sampling period. We therefore expect error in

these estimates to be higher than for other species in this study.

Two species of amphipods, Corophium sp. and Corophium louisiana displayed significant

differences within a sampling period between years. During the summer of 1996, population levels

of Corophium sp. were nearly three times the estimated levels for that species during the summer

of 1997. Sampling during the summer quarter of 1996 occurred during late August while the

summer 1997 sampling was conducted during mid July. Likewise population levels for Corophium
613

louisiana during the fall of 1995 were twice that of the fall 1996 sample. In this example, sampling

occurred three weeks later in 1995 than in 1996. We suspect that the increased population levels

were evidence of the presence of two or more cohorts during the period. 

REFERENCES

Birklund, J. 1977. Biomass, growth and production of the amphipod Corophium insidiosum

Crawford and preliminary notes on Corophium volutator (Pallas). Ophelia 16:187-203.

Bull, A.S. 1990. Fish assemblages at oil and gas platforms, compared to natural hard/live bottom

areas in the Gulf of Mexico. Coastal Zone 90:979-987.

Bull, A.S. and J.J. Kendall. 1994. An indication of the process: Offshore platforms as artificial reefs

in the Gulf of Mexico. Bull. Mar. Sci. 55:1086-1098.

Crisp, D.J. 1971. Energy flow measurements. Pages 197-279. In N. A. Holme and A.D. McIntyre

eds. Methods for the study of marine benthos. IBP handbook 16, Blackwell Publ. Oxford, U.K.

Dauvin, J.C. and M. Joncourt. 1989. Energy values of marine benthic invertebrates from the western

English Channel. J. Mar. Biol. Assoc. of the U. K. Plymouth. 69:589-595.

Franz, D.R. and J.T. Tanacredi. 1992. Secondary production of the amphipod Ampelisca abdita and

its importance to the diet of juvenile winter flounder (Pleuronectes americanus) in Jamaica Bay,

New York. Estuaries. 15:193-203

Gallaway, B.J. and G.S. Lewbell. 1982. The ecology of petroleum platforms in the northwestern

Gulf of Mexico: a community profile. U.S. Fish Wildl. Serv., Gulf of Mexico OCS Reg.Off.,

Open-file Rept. 82-03. 93 pp.

Jessee, W.N., J.W. Carter, A.L. Carpenter, and E.E. DeMartini. 1985. Density estimates of five

warm-temperate reef fishes associated with an artificial reef, a natural reef, and a kelp forest. In

F. D’Itri, ed. Artificial reefs: marine and freshwater applications. Lewis Publishers, Inc. Chelsea,

Minnesota.

Liddell, D.W. and S.L. Ohlhorst. 1991. Sessile community sampling. Pages 2473-2479. In Magill’s

survey of science: Life science series.

Mossman, D. 1978. Energetics of Corophium volutator. Ph.D. Thesis, University of London.

Onset Instruments Corp. 1998. P.O. Box 3450, Pocasset MA. 02559

Shannon, C.E. 1948. A mathematical theory of communication. Bell Syst. Tech.J. 27:379-423. 

Smith, G.B., D.A. Hensley, and H.H. Mathews. 1979. Comparative efficacy of artificial and natural

reefs as fish attractants. Florida Mar. Res. Publ. 35:1-7.
614

SETTLEMENT OF A COLONIAL ASCIDIAN ON AN

ARTIFICIAL REEF IN THE GULF OF MEXICO 

Jan Culbertson

Donald E. Harper, Jr.

Artificial Reef Program

Texas Parks and Wildlife Department and

Department of Marine Biology

Texas A&M University at Galveston

An obsolete oil production platform, located in 58 m water depths in High Island A- 532, 12 nautical

miles west of Stetson Bank, was converted into an artificial reef in 1997. The upper 27 m of the

structure was mechanically cut off and placed on the sea floor, next to the undisturbed lower section

of the rig. During “pre-construction” biological monitoring, divers observed a thin white encrusting

ascidian colonizing most of the structure below the water line. Divers confirmed that between 1998

and 2000 this ascidian colonized the majority of both portions of the structure from 27 m to below

42 meter depths. Divers have recently observed this same species colonizing other platforms, within

12 nautical miles of this reef site.

Samples of this ascidian were collected and compared to other species found in the Gulf of Mexico

(GOM) and the Pacific. The High Island A-532 Reef’s species was identified by ascidian expert, Dr.

Gretchen Lambert, as Didemnum perlucidum, in the family Didemnidae. This ascidian forms a thin

tunic layer over the colony, less than 1 mm thick, and appears white due to the aster-like spicules

in the tunic. This species of ascidian can colonize structures through sexual reproduction of gametes

and settlement of larvae or through asexual budding of itself. It appears to settle or grow over other

encrusting organisms such as sponges, corals, bryozoans, hydroids, and mollusks.

Monitoring stations on the structure have been set up at this reef site to determine how quickly

Didemnum perlucidum colonizes and what other factors may influence its growth and/or

reproduction. First-quarter observations show that this ascidian can completely re-colonize 100 cm

surfaces that were cleared of all attached organisms. This monitoring study is still in progress, and

environmental as well as seasonal factors are being considered.

INTRODUCTION

There have been few zoogeographical studies of the distribution of ascidians in the GOM. Less than

25 ascidian species have previously been documented for the GOM by Van Name (1945), Rabalais

(1975), and Plough (1978). These benthic encrusting species are not readily observed, unless they

can be differentiated from other epifauna attached to both artificial substrates and natural hardbottom communities. They provide competition for corals, sponges, and other invertebrates and

appear to be an important component of hard-bottom communities (Rabalais 1975, Monniot and

Monniot 1991, and Bak et al. 1996). Rabalais (1975) described 15 new ascidian species forming a

dense mat covering the polychaete tube cases of Physllochaetopterus socialis at Seven and One-Half

Fathom banks on the south coast of Texas. She also described additional species observed on jetty
615

complexes along the Texas coast, in the bays, and on oil production platforms offshore of Port Aransas, Texas. These 21 previously documented species are from three zoogeographical regions: Texas

Transitional Zone (after Van Name 1945, 1954, and Millar 1971); Caribbean Transitional or Carolinian Zone (after Hedgepeth 1953, and Williams 1951); and West Indian or Eastern American Tropical Zone (after Valentine 1963). Although many biological surveys on oil and gas platforms and

natural banks have been done in the offshore waters of this third zone (Dokken et al. 2000, Bright

1985), little information exists on new ascidian species found in the GOM over the past 20 years.

As the range and numbers of oil and gas platform installations have grown since 1945, there has also

been an increase in the available hard-bottom substrate for benthic encrusting organisms in the

GOM. In addition to the numbers of platforms installed, there has also been an increase in the

numbers of platforms removed, towed to shore, reinstalled at other locations, or converted into

artificial reefs (Dauterive per. comm. and MMS database). These platforms provide the perfect

vector for transferring epifauna from one location to another. They also provide available substrate

for settlement of new species passing through the water currents or from ships releasing ballast

water on their way through fairways to major ports (Coles et al. 1999). 

This paper documents observations of a new colonial species, identified as Didemnum perlucidum,

in the Didemnidae family in the GOM. Its origins are unknown at present, but it appears to have

been introduced in the GOM, and is currently dominating a state artificial reef site 74 nautical miles

offshore. Samples of this species were compared with pacific species, collected by Scott Godwin

(Bishop Museum of Natural History), and verified by Dr. Gretchen Lambert (University of

Washington). A full description of this species may be found in Monniot (1983) and Monniot and

Monniot (1987, 1995). These authors have documented its presence in the Caribbean West Indian

Oceans in Guadelope; and from the Pacific Ocean in Micronesia and Papau-New Guinea. This

species has also been documented in the harbor areas near the Hawaiian Islands (Godwin and

Lambert per. comm. 2000). The introduction of this ascidian species in the GOM meets the criteria

for a non-indigenous species described by Chapman (1988) as a “new appearance in a local region,

in association with human mechanisms of dispersal, or in association with other introduced species,

restricted to artificial or disturbed habitat, and from widespread, disjunct geographic ranges.”

Species not demonstratably introduced or native to previously known geographic ranges are

considered to be crytogenic species.

This colonial ascidian was first observed to be covering the entire surface area of an eight-leg (pile)

structure from the water surface interface down to at least 42 m water depth and beyond. Divers

completed a pre-artificial reef construction survey in May 1997 and found a thin white encrusting

organism to be dominating and smothering previously established epifauna. Divers conducted a

post-construction survey 14 months later in August 1998, after the top portion of the jacket was cut

off at 27 m and placed on the bottom next to the standing portion of the jacket to create two reef

structures. They also found this ascidian covering both structures from 27 m down to at least 40 m

and beyond. The upper portion of the original jacket, including 15 m of bare metal previously not

exposed to sea-water, was also covered with the ascidian in that time period. Divers conducted

another post-monitoring survey in September 1999, and found that this organism was so effective

in maintaining dominance that it had covered nearly all living and attached encrusting organisms,

preventing them from normal nutrient uptake and respiration.
616

However, the continued dominance of this colonial ascidian at a Texas artificial reef over the past

three years has piqued the interest and concern of state and federal agencies. Its ability to outcompete native species may be a potential concern if it is transferred to other artificial reefs, either

through currents or by direct movement of surrounding platforms to other areas in the GOM. This

study is a preliminary account of what monitoring protocols have been implemented to estimate the

growth and settlement rates of this species. Further investigation into the factors controlling this

ascidian’s continued dominance and further documentation of its invasion of surrounding artificial

reefs are in progress.

SPECIES DESCRIPTION

A key feature of this species is that it appears to be white due to the white aster-like spicules

embedded in its translucent tunic, covering the entire colony. There appears to be some color

variation, however, when it is in a growth mode. Then, it appears to be a yellow to gray color due

to the lack of spicules on the surface of the tunic. Each zooid adult has four rows of branchial sacs,

with seven to eight stigmata in each row, similar to other Didemnids in the GOM. Each zooid in the

colony has a six-star shaped, oral siphon, where water is pumped from the external environment to

their branchial sacs for respiration and nutrient uptake. Each zooid adult also has a broad cloacal

aperture, that exposes its branchial sacs to the colony’s common areas, where waste is released

through a common exterior siphon.

Each zooid adult is hermaphroditic, and can produce male gametes through a single testis with eight

coiled sperm ducts and oocytes from a single ovary. These gametes are released to the common

areas where fertilization occurs. The tadpole-like larvae are stored in these common areas until they

are mature and ready to be released to the water column. These colonial ascidians can also reproduce

and extend the growth of their colony through asexual reproduction, or budding of their mid-section.

Each colonial unit consists of a “system” of zooids, which share a large exterior siphon, the most

notable morphological feature of each colonial unit. Cloacal canals, which appear as dark

meandering lines in this species, connect the individuals in these colonies to common areas and

exterior siphons.

STUDY SITE

The study site is located 74 nautical miles offshore of Freeport, Texas, in OSC leasing block High

Island A-532 at 28° 05' 56.551"N Latitude, and 94° 30' 43.377"W Longitude. This artificial reef

structure is standing in 58 m of water. In 1997, this obsolete eight-leg jacket structure was converted

into an artificial reef. The upper 27 m of this artificial reef structure was mechanically cut off and

placed on the sea floor, next to the undisturbed lower section of the rig to create two reef structures.

Figure 9.4 shows the location of the High Island A-532 reef and its relative distance from shore and

other Texas Parks and Wildlife artificial reefs. This artificial reef site is also located 12 nautical

miles west of Stetson Bank, a natural hard bottom community, under the protection of the NOAA

Flower Garden Bank National Marine Sanctuary Program. We have also identified this species at

other artificial reef sites within a 12-mile radius of the study site. 
617

P ort

A rth u r

G a lve ston

Fre e p o rt

P ort

O 'C onnor

C o rp u s

C h risti

P ort

M a n sfie ld

B row n sville

Te xa s P a rks & W ild life

A rtific ia l R e e f S ites

HI-A-532

Figure 9.4. Artificial Reef Study Site. High Island A-532.
618

METHODS

In May 2000, divers established two growth-monitoring areas—stations 1 and 3 (see Figure 9.5).

Plastic cable ties (1.5 cm wide) were installed approximately 100 cm apart on two 61 cm diameter

horizontal cross-members of the structure. A digital video camera (Sony TRV900) inside a Stingray

II Light in Motion Underwater Housing was used to record the apparent growth at each station

before and after each sampling effort. Four different colored (10 cm) plastic cable ties were installed

through the end markers to denote north, east, south and west geographic quadrants, to account for

any differences from currents flowing past the rounded surfaces of each station. Four square plastic

station markers (6.4 cm2 ) were also established on a middle cable tie in the center of each quadrant,

at approximately 50 cm from upper and lower end markers as a reference point for digital video

records. All ascidian growth or settlement between these end markers was removed. Established

colonies above and below these scraped areas remain undisturbed so that any growth into scraped

areas could be measured over time.

In August 2000, the apparent growth of these undisturbed colonies was recorded using the previously described digital video camera. Digital images were transferred with an AUTOCAD 14.0

program, used for measuring the distance these colonies had grown from the top and bottom edges

of each station. Figure 9.6 shows the digital images of the upper 50 cm of all five monitoring stations. Only station 5 shows 100 cover because it was left undisturbed. Ten measurements were

drawn on each image in AUTOCAD in each quadrant, starting at the top edge and working down

to the center marker. Ten measurements were also recorded in each quadrant starting at the bottom

edges of each marked area, working up to the center marker. These measurements taken of upper

and lower apparent growth in each quadrant, were compared with each other and between stations.

In August 2000, two additional monitoring stations (see Figure 9.5 for stations 2 and 4 reference

locations) were also set up on other horizontal cross members. These stations were marked using

the same procedures previously established for marking monitoring stations. A control station was

also established and marked with cable ties, 100 cm apart (see Figure 9.5 for station 5 reference

location). This control station will remain undisturbed for the remainder of this study to monitor

continued dominance of this ascidian on the structure. Once video images were recorded, divers

removed all epifauna and ascidian growth from stations 1 through 4.

In addition to scraping these monitoring stations, temperature gauges (OnSet Computers) were

attached to the top of each monitoring station. A YSI-6600-M (Yellow Springs Instruments) multiparameter data sonde, calibrated to record temperature, salinity, pH, dissolved oxygen, turbidity, and

total chlorophyll was installed on an outer vertical leg near station 4. This YSI-6600-M data sonde

will be replaced every three months to transfer water quality data from the study site and to

determine if there are any distinguishing hydrographic features at the 27 meter sampling depth.

In September 2000, the apparent growth at all four stations was recorded using the same digital

video camera previously described. Digital images were transferred into an AUTOCAD 14.0

program for measuring the distance these colonies had grown from the top and bottom edges at each

station. The same procedures were used to measure each quadrant to compare upper and lower

apparent growth at each geographic quadrant and between stations.
619

N

Station 4

Station 3

Station 2

Station 1

Station 5

Data 

Sonde

Figure 9.5. Monitoring station locations: stations 1 through 5.
620

Station 1 Station 2

Station 3 Station 4

Station 5

Figure 9.6. Digital images of upper 50 cm of stations 1 through 5.
621

In October 2000, digital video images from each station at each quadrant were recorded using the

same procedures previously discussed. These images will be transferred into AUTOCAD for

measurement of growth in the near future. Monitoring apparent growth at this study site will

continue on a quarterly basis, until an established pattern has been established. Plans to establish

ascidian larval settlement traps at each station to distinguish settlement versus growth rates are also

being explored. Other biotic factors as well as environmental and hydrological factors will be

evaluated for influences on apparent growth at this study site. Additional stations may also be

installed in the future at platforms in the area to evaluate this ascidian’s growth at other locations.

RESULTS

Three months after the first removal of all growth and encrusting organisms at stations 1 and 3, the

first growth data was recorded. This time period occurred between 11 May and 8 August 2000.

Figures 9.7 and 9.8 show a comparison of the upper and lower growth averages of ten measurements

taken in each quadrant at station 1 and 3 over this time period. Each lightly shaded upper area of the

cylinders in these figures indicates an average of 10 measurements of apparent growth of the colony

down from the undisturbed upper part of the monitoring station in each quadrant. Each dark shaded

area of the cylinders in these figures indicates the average of 10 measurements of apparent growth

of the colony up from the undisturbed lower part of the monitoring station in each quadrant. The

white portion of each cylinder, labeled “other,” denotes data that contains both discontinuous

patches of colonial ascidians and unsettled areas between upper and lower growth areas. These

discontinuous patches of ascidians cannot be specifically identified at this time as growth from the

upper or lower undisturbed colonies, or from settlement of new larvae. These discontinuous patches

have been treated as “other growth” rather than as non-growth areas on this figure and all subsequent

figures.

Figure 9.7 shows that average growth between quadrants ranging between 11.4 cm (west) and 31.9

cm (south) occurred in the upper portion of station 1. Figure 9.7 also shows that average growth

between quadrants ranged between 26.9 cm (south) and 36.1 cm (west) occurred in the lower portion

of station 1.

Figure 9.8 shows that average growth between quadrants ranging between 31.5 cm (west) and 57.1

cm growth (north) occurred in the upper portion of station 3. Figure 9.8 also shows that average

growth between quadrants ranging between 28.8 cm (south) and 43.7 cm (west) occurred in the

lower portion of station 3.

The averages of 10 measurements in each quadrant is somewhat misleading because these averages

conceal the irregular growth rate of the entire colony as it migrates either up or down the station leg.

Figure 9.9 shows that the upper portion of the colony (solid line) grew up to 73.0 cm in some areas

of the south quadrant, but had areas of zero growth in the west quadrant over this same time period.

Figure 9.9 also shows that there were some areas in the lower portion (dotted line) of the west

quadrant that grew up to 76.0 cm and less than 20.0 cm growth in the south quadrant over this same

time period.
622

0.0

20.0

40.0

60.0

80.0

100.0

CM

W est South East North

Direction

Station 1 Av e rage G rowth 5/11/00 - 8/8/00

Upper

Other

Lower

Figure 9.7. Average growth measured at station 1 from 5/11/00 - 8/8/00. Comparison shows

upper and lower growth at monitoring station. X-axis indicates cm of growth over

time. Y-axis indicates four quadrants where measured on each station.

0.0

20.0

40.0

60.0

80.0

100.0

CM

W est South East North

Direction

Station 3 Av e rage G rowth 5/11/00 - 8/8/00

Upper

Other

Lower

Figure 9.8. Average growth measured at station 3 from 5/11/00 - 8/8/00. Comparison shows

upper and lower growth at monitoring station. X-axis indicates cm of growth over

time. Y-axis indicates four quadrants where measured on each station.
623

Station 1 G rowth 5/11/00 - 8/8/00

0.0

20.0

40.0

60.0

80.0

100.0

 W e s t So u th Eas t No r th

Dire ction

CM

Upper

Low er

Figure 9.9. Summary of growth measurements taken at station 1 from 5/11/00 - 8/8/00.

Comparison shows ten measurements of upper and lower growth at monitoring

station. X -axis indicates cm of growth over time. Y-axis indicates four quadrants

where measured on each station.

Figure 9.10 shows that the upper portion of the colony on station 3 (solid line) grew up to 62.7 cm

on the east quadrant and 62.8 cm on the west quadrants in the first three-month time period. Figure

9.10 also shows that the lower portion of the colony on the west side of station 3 (dotted line) grew

63.4 cm, while the other quadrants did not exceed 40 cm of growth in that same time period.

A comparison of Figures 9.7 through 9.10 indicates that there is a difference between stations 1 and

3; there are also differences between quadrants measured. Station 3 appears to have had the greatest

growth over the first three-month period, however, with nearly uniform growth and no specific

quadrant affected by other spatial or environmental parameters. In some cases, there were areas

where the colony grew over itself, and it was difficult to distinguish growth from settlement on this

column.

In September, one month after the second removal of all growth and encrusting organisms at stations

1 and 3 and first removal of all growth at stations 2 and 4, growth data was recorded and evaluated

as previously discussed. This time period occurred between 8 August and 13 September 2000.

Figures 9.11 through 9.14 show a comparison of the upper and lower averages of apparent growth

measurements taken at each quadrant at stations 1 through 4 over this one-month time period.

Figure 9.11 shows that average growth on the upper portion (lighter shaded areas) of station 1

ranged between 4.4 cm in the west quadrant and 18.4 cm in the north quadrant. Figure 9.11 also

shows that average growth on the lower portion (darker shaded areas) of station 1 ranged between

5.3 cm in the south quadrant and 18.0 cm in the east quadrant.
624

Station 3 Growth 5/11/00 - 8/8/00

0.0

20.0

40.0

60.0

80.0

100.0

 W e s t So u th Eas t No r th

Direction

CM

Upper

Lower

Figure 9.10. Summary of growth measurements taken at station 3 from 5/11/00 - 8/8/00.

Comparison shows ten measurements of upper and lower growth at monitoring

station. X -axis indicates cm of growth over time. Y-axis indicates four quadrants

where measured on each station.

0.0

20.0

40.0

60.0

80.0

100.0

CM

West South East North

Quadrant

Station 1 Average Growth 8/8/00-9/13/00

Upper

Other

Lower

Figure 9.11. Average growth measured at station 1 from 8/8/00 – 9/13/00. Comparison shows

upper and lower growth at monitoring station. X-axis indicates cm of growth over

time. Y-axis indicates four quadrants where measured on each station.
625

0.0

20.0

40.0

60.0

80.0

100.0

CM

West South East North

Quadrant

Station 2 Average Growth 8/8/00-9/13/00

Upper

Other

Lower

Figure 9.12. Average growth measured at station 2 from 8/8/00 – 9/13/00. Comparison shows

upper and lower growth at monitoring station. X-axis indicates cm of growth over

time. Y-axis indicates four quadrants where measured on each station.

Figure 9.12 shows that average growth on the upper portion (lighter shaded areas) of station 2

ranged between 7.0 cm in the south quadrant and 17.7 cm in the north quadrant. Figure 9.12 also

shows that average growth on the lower portion (darker shaded areas) of station 2 ranged between

8.3 cm in the south quadrant and 17.3 cm in the north quadrant.

Figure 9.13 shows that average growth in the upper portion (lighter shaded areas) of station 3 ranged

between 6.5 cm in west quadrant and 16.7 cm in east quadrant. Figure 9.13 also shows that average

growth on the lower portion (darker shaded areas) of station 3 between quadrants ranged between

18.6 cm in west quadrant and 20.1 cm in east quadrant. All growth measurements at station 3

appeared to be nearly uniform between upper and lower sampling areas.

Figure 9.14 shows that average growth in the upper portion (lighter shaded areas) of station 4 ranged

between 4.2 cm in the north quadrant and 19.3 cm in the south quadrant. Figure 9.14 also shows that

average growth in the lower portion (darker shaded areas) of station 4 ranged between zero growth

in the north quadrant and 13.0 cm in the south and west quadrants. There was less growth in all four

quadrants of station 4 compared to the other three stations. There may be some other factors

influencing growth at this station, which is discussed below.
626

0.0

20.0

40.0

60.0

80.0

100.0

CM

West South East North

Quadrant

Station 3 Average Growth 8/8/00-9/13/00

Upper

Other

Lower

Figure 9.13. Average growth measured at station 3 from 8/8/00 – 9/13/00. Comparison shows

upper and lower growth at monitoring station. X-axis indicates cm of growth over

time. Y-axis indicates four quadrants where measured on each station.

0.0

20.0

40.0

60.0

80.0

100.0

CM

West South East North

Quadrant

Station 4 Average Growth 8/8/00-9/13/00

Upper

Other

Lower

Figure 9.14. Average growth measured at station 4 from 8/8/00 – 9/13/00. Comparison shows

upper and lower growth at monitoring station. X-axis indicates cm of growth over

time. Y-axis indicates four quadrants where measured on each station.
627

DISCUSSION

Although this preliminary interpretation of the data collected to date only reflects two sampling

efforts and is incomplete, there are some indications of the growth rate over time of this species at

these four sampling stations set up between May and August 2000. The greatest amount of growth

occurred over the three-month time period at stations 1 and 3. These results would be expected in

the GOM between May and August, however, as water temperatures are highest during summer

months and provide the most favorable environment for growth.

Further investigation into the actual location of each sampling station, however, appears to be

causing some variation in the growth measured in each quadrant. Review of the location of each

station shows that the larger diameter outer legs (91 cm in diameter) of the structure may be

influencing growth rates on the quadrant nearest to this interference in current flow or available

sunlight. Figure 9.3 shows that station 1 is situated on the inside horizontal cross-member near the

outer vertical leg on the west side of the reef structure. Any restriction or increase in the current

velocity flowing between the outer vertical leg and the inner horizontal cross-member where

station 1 is situated may be magnified on the west quadrant. A review of the station 1 data from

both sampling periods shows that there was less growth on the west and the south quadrants, which

may or may not be attributed to influences from the outer vertical leg on the west side of the

structure.

Station 3 is located somewhat further away from the influences of the outer vertical leg on the east

side of the structure. Almost uniform growth or over-growth of the colonies occurred at station 3

(Figure 9.4) during the first three-month time period. A review of the data evaluated after the onemonth time period between August and September at station 1 (Figure 9.11) and 3 (Figure 9.13)

shows that these same trends continued.

Stations 2 and 4 are also situated in locations where the outer larger diameter (91 cm) legs of this

eight-leg reef structure might be causing some variation in the growth measured in some quadrants.

Growth on the south side of station 2 was less than growth in other quadrants and may be influenced

by the larger diameter vertical leg on the south-east side of the reef. A comparison of all stations

showed that the least growth occurred at station 4. There was almost no growth in the first month

at station 4 in the north and east quadrants, which may be influenced by the larger diameter vertical

leg on the north-east side of the reef structure. However, the slower growth rate at station 4 may also

be influenced by other variables that we have not explored at this time.

SUMMARY

Average growth on the High Island A-532 Reef appears to be between 20 and 70 cm in

all quadrants, from both upper and lower monitoring areas at stations 1 and 3 during the initial

three-month sampling period. There was between 5 and 20 cm growth in each quadrant at these two

stations during the following one-month sampling period. Average growth at station 2 was

comparable to growth at stations 1 and 3. Station 4 had the least growth of all the stations.

No change in cover or dominance was observed at the control station over the one-month sampling
628

period. Monitoring will continue at these five stations over the next year. Further interpretation of

these data, and future data collected at this reef site will be reported as it becomes available.

ACKNOWLEDGMENTS

This monitoring study has been funded by Texas Parks and Wildlife Artificial Reef Program and

began as routine pre- and post-construction surveys as per Corps of Engineers Permit requirements.

However, the bulk of the underwater video recording has been carried out by Artificial Reef

Biologist Douglas Peter and by Artificial Reef Research Specialist John Embesi, whose invaluable

scientific diving experience and enthusiasm were essential in collecting the data for this growth

study. Both of these artificial reef program staff have significantly contributed to loading the video

data into AUTOCAD, assisting with figures, and providing computer and diving support for the

completion of this report. We would also like to acknowledge other scientific divers from state

agencies who contributed their time to this study: Bryan Eastham, James Sinclair, Chad McNutt, and

Michael Weeks. We would also like to acknowledge the many scientific divers from Texas A&M

University at both Galveston and Corpus Christi who have collected data offshore for the Artificial

Reef Program on this study: Dr. Donald Harper, Sara Williams, Christi McDaniels, David Atkinson,

Gavin Hogge, Tom Turner, Josh Harper, David Costa, Dr. Andre Landry, Dr. Jay Rooker, David

Wells, Dr. Quenton Dokken, Tom Bates and Matthew Campbell. Special thanks go to Scott Godwin

at the Bishop Natural History Museum in Hawaii for collecting Didemnum perlucidum samples for

the comparisons that were made between Gulf and Pacific specimens. Special thanks also go to Dr.

Gretchen Lambert from University of Washington, Friday Harbor Laboratories for her time and

review of all specimens and final verification of this species. And special acknowledgement goes

to Dr. Donald Harper, whose encouragement to study and investigate the effects of an introduced

species to the GOM has been the basis for this study.

REFERENCES

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133: 303-306.

Chapman, J.H. 1988. Invasions of the northeast Pacific by Asian and Atlantic gammaridean

amphipood crustaceans,including a new species of Corophium. J. Crustacean Biol. 8:354-382

Coles, S.L., R.D. Defelice, L.G. Eldredge, and J.T. Carlton. 1999. Historical and recent introduction

of non-indigenous marine species in Pearl harbor, Oahu, Hawaiian Islands. Mar. Bio. 135:147-

158.

Dauterive, L. 2000. Personal communication from Minerals Management Service database and

reports. New Orleans, LA.

Dokken, Q., K. Withers, S. Childs, T. Riggs. 2000. Report Funded by Texas Parks and Wildlife:

Characterization and comparison of platform reef communities off the Texas coast. (TAMU-CC-
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0007-CCS) Texas A&M University, Center for Coastal Studies, Corpus Christi, TX. (September

unpublished)

Godwin, S. 2000. Personal communication on geographic information and collection of pacific

samples of Didemnum perlucidum in Hawaiian harbors. Bishop Natural History Museum of

Science. Oahu, Hawaii.

Hedgepeth, J.W. 1953. An introduction to the zoogeography of the northwestern Gulf of

Mexico with references to the invertebrate fauna. Public. Inst. Mar. Sci. Univ. Texas 3(1):107-

224.

Lambert, G. 2000. Personal communication on identity and range of Didemnum perlucidum.

University of Washington, Friday Harbor Laboratories. 

Millar, R.H. 1971. The biology of the ascidians. Adv. Mar. Bio. 9:1-100.

Monniot, F. 1983. Ascidies littorales de Guadeloupe. I. Didemnidae. Bull. Mus. Natn. Hist. Nat.

Paris. 4(5): 5-49.

Monniot, F. 1995. Ascidies de Nouvelle-Caledonie. XV. Le genre Didemnum. Bull. Mus. Natn.

Hist. Nat., Paris. 4(16): 299-344.

Monniot, C. and F. Monniot. 1987. Les Ascdies de Polynesie Francaise. Mem. Mus. Natn. His. Nat.,

Paris. A. Zool.136:1-156.

Monniot, C. F. Monniot, and P. Laboute. 1991. Coral Reefs of New Caledonia. Editions

De L Orstom. Inst. Francais de Recherche Scientifique pour le Developpment en Cooperation.

Paris. 

Plough, H.P. 1978. Sea Squirts of the Atlantic Continental Shelf from Maine to Texas. Johns

Hopkins University Press, Balt. MD.

Rabalais, N.N. 1975. The ascidians and associated fauna in the Gulf of Mexico along a portion of

the Texas Coast. Unpubl. M.S. Thesis, Texas A&I Univ. Kingsville.

Rezak, R., T. Bright, and L. Peguegnat. 1995. Reefs and Banks of the Northwestern Gulf of Mexico,

Their Geological, Biological and Physical Dynamics. John Wiley & Sons, Inc. New York.

Valentine, J.W. 1963. Biogeographic units as biostratigraphic units. Bull. Am. Assoc. Petro. Geol.

47(3): 457-466.

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474.
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Van Name, W.G. 1954. The tunicata of the Gulf of Mexico. In Gulf of Mexico: Its origin, waters,

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631

*

This abstract is provided although the presentation was canceled.

REEF BALLSTM: HOW COMBINING DESIGNED REEFS WITH OIL

SUPERSTRUCTURES USED AS ARTIFICIAL REEFS CAN HELP THE

OVERALL REEF SYSTEM TO BETTER MIMIC NATURAL REEF SYSTEMS*

Todd Ryan Barber

President, Reef Ball Development Group, Ltd.

Chairman, Reef Ball Foundation, Inc.

ABSTRACT

Reef Balls are state of the art designed artificial reefs used primarily to restore ailing reefs or to

create new reefs for ecological enhancement, fishing, scuba diving, and many other specific end use

goals. Reef Balls have been used in over 1,000 projects worldwide with over 100,000 Reef Balls

deployed and functioning as reef ecosystems. Reef Balls are the most widely used designed artificial

reef system in the world. When combined with higher profile structures, especially superstructures

such as oil platforms and rigs used as artificial reefs, the resulting reef can be turned to more closely

match natural reefs. Reef Balls have been used in the Arabian Gulf and Asia by several oil

companies to help in this regard. Although Reef Balls have been widely used in the Gulf of Mexico,

they have yet to be combined with Oil superstructures to gain the same advantages.

Reef Balls are not artificial reefs, but rather are a new category of reef enhancement called,

“Designed Reefs.” Designing modules to specifically match goals and expectations of scientists, reef

managers and reef builders is afforded by the flexibility of Reef Balls allowing high profile

structures to be augmented to produce, rather than just attract fish. Therefore, when compared to

building an artificial reef from only an oil structure, it is possible to define the expected goals of the

combination of structures and designed materials to best meet specific objectives. In the past, many

reefs were built simply “to improve the marine environment” under the assumption that because fish

and other forms of life were present that the reefs were performing a positive function. Increasingly,

reefs are built for very specific goals because the science of reef building is rapidly advancing. Even

when the goal is simply “to improve the marine environment” we now know an accepted criteria of

measurement is to gauge the species diversity and population densities of all life of nearby natural

reefs as compared to the constructed reefs. Designed reefs combined with larger profile materials

are useful tools to allow scientists, reef managers, and reef builders to achieve this goal. When used

in conjunction with oil rigs and other high profile structures, Reef Balls can effectively provide the

additional habitat required to service the large populations of fish that are attracted to high profile

structures without the associated reef biomass. This can lead to a reef that more closely mimics

natural reefs and therefore is more broadly accepted by scientists, politicians and the public.

Reef Balls are internationally patented and/or copyrighted technologies that allow nearly all natural

reef features to be mimicked. Variables which can be adjusted to meet natural conditions include:

1) stability, 2) void spacing, 3) hole sizing, 4) hole complexity, 5) surface texture, 6) surface
632

chemical composition (i.e. ph, exposed aggregates, etc.), 6) bottom features, 7) subsidence variables,

8) overall weight, 9) size of units in both height and width, 10) interconnection of holes, 12) layout

or spacing on the sea floor, and 13) density of units and proportioning of sizing ratios, and many

other minor factors. In addition to being highly adaptable, Reef Balls are often the least expensive

alternative due to a technology that allows placement without expensive barges, tugs or cranes, high

surface area, and life expectancies of well over 500 years.
633

RED SNAPPER SITE FIDELITY TO, AND SPEED OF MOVEMENT FROM,

ARTIFICIAL REEF SITES OFF ALABAMA IN THE NORTHERN GULF OF MEXICO

William F. Patterson

James H. Cowan

Robert L. Shipp

Department of Marine Sciences

University of South Alabama

ABSTRACT

A tagging study of red snapper Lutjanus campechanus was conducted in an extensive artificial reef

area in the northern Gulf of Mexico (GOM) to estimate their site fidelity to, and movement from,

individual reefs. A total of 2,932 red snapper was tagged with internal anchor tags during 28 tagging

trips made to nine artificial reef tagging sites from March 1995 to July 1998. Recaptures of tagged

fish were made on subsequent tagging trips by the authors (n = 235) and were reported by

recreational and commercial fishers (n = 359 through September 2000). Annual site fidelity of

tagged fish to individual reefs was estimated with non-linear decay models of the decline in

recaptures made at tagging sites over time; site fidelity estimates ranged from 21 to 26 % yr-1.

Unbiased estimates of distance and speed of movement were obtained with the delta method. Mean

distance of movement was 29.1 km and mean speed of movement was 73.9 m d-1. Results indicate

that red snapper demonstrate lower site fidelity to reef sites than previously reported. Low site

fidelity may explain spatial and temporal variability in red snapper biomass observed around

artificial reefs and has important implications for managers considering marine protected areas as

a means to increase red snapper spawning stock biomass. 

INTRODUCTION

Red snapper Lutjanus campechanus are large, piscivorous reef fish that occur as far north as Massachusetts, but generally are found from North Carolina to the Yucatan Peninsula, including the waters

of the GOM but not the Caribbean Sea (Hoese and Moore 1998). Red snapper are valued as both

game and food fish throughout their range and are perhaps the most targeted fish in the U.S. GOM

(Minton and Health 1998; Stanley and Wilson 1989,1990). In the GOM, red snapper are managed

as a single stock that supports economically valuable commercial and recreational fisheries. The

stock is currently estimated to be overfished and has been managed since the early 1990s intensively

to rebuild spawning stock biomass. Despite overfished status, GOM red snapper total landings

averaged (± SE ) 3.96 x 103

 metric tons (± 1.16)from 1995 to 1998 (Schirripa and Legault 1999).

Dating back to the 1800s, it appears that the historic center of GOM red snapper abundance was off

northwest Florida (Camber 1955; Collins 1885; Goodyear 1995; Stearns 1884). The early

commercial fishery followed a pattern of fishing down a given area and seeking new fishing grounds

(Collins 1885; Stearns 1883). By the 1950s about half of reported U.S. commercial landings were

taken from the Campeche Banks off Mexico (Camber 1955; Carpenter 1965; Goodyear 1995), a

trend which continued until Mexico closed the banks to the U.S. fleet in 1980 ( Goodyear 1995). The
634

early development of the recreational fishery is not as well documented; however, by the 1950s a

significant charterboat fishery had developed in northwest Florida (reviewed in Goodyear 1995).

By the early 1970s, recreational fishers GOM-wide were making nearly 4 x 105

 trips per year

targeting red snapper aboard private and chartered fishing boats (Nakamura 1976).

It appears from fisheries-dependent data that there are currently two centers of GOM red snapper

abundance, one in the northwestern GOM off southwest Louisiana (LA) and a second in the north

central GOM off Alabama and Mississippi (ALMS) (Goodyear 1995; Schirripa and Legault 1999).

From 1995 to 1998, the average percentage of total GOM commercial landings (± SE) from waters

off southwest LA was 56.5% (± 0.54) and the average percentage of total recreational landings from

waters off ALMS was 31.1% (± 3.08) (Schirripa and Legault 1999). (Note: Commercial landings

comprised 48% of total GOM landings from 1995 to 1998, while recreational landings comprised

52%.) What makes these two areas unusual as centers of reef fish production is that the seafloor of

both is composed mostly of sand and mud sediments (Curray 1960; Fisk and McFarlane 1955;

Luddick 1964; Parker et al. 1983). The most pronounced seafloor relief is associated with shelf-edge

reef pinnacles and hardground ledges (LA and ALMS), and salt-dome uplifts (LA only), but the

near-shore shelf is generally depauperate of natural reef substrate (Curray, 1960; Parker et al.

1983;Schroeder et al. 1995).

Most of the near-shore reef habitat off LA and ALMS is in the form of artificial reefs (Stanley and

Wilson 1990; Szedlmayer and Shipp 1994). Therefore, the red snapper fisheries in these areas are

prosecuted predominantly over artificial reefs (Minton and Health 1998; Stanley and Wilson

1990,1991; Szedlmayer and Shipp 1994). In the case of LA, over 3,000 offshore petroleum

platforms serve as de facto artificial reefs and have increased the near-shore habitat available to reef

fishes (Figure 9.15) (Bull and Kendal 1994; Gallaway 1984; Stanley and Wilson 1990, 1991).

Reggio (1987) estimated that 70% of LA recreational fishing trips farther than three miles from

shore targeted fishes at petroleum platforms. Stanley and Wilson (1990) reported the composition

of catches made at petroleum platforms off LA shifted from the late 1970s from one predominated

by drums (Family: Sciaenidae) to one predominated by red snapper.

Petroleum platforms are not as concentrated off ALMS as they are in the northwestern GOM (Figure

9.15), but the state of Alabama claims the largest artificial reef program in the U.S. (Minton and

Heath 1998). Off the coast of Alabama exists an area of over 3,100 km2

 that has been designated for

artificial reef construction (Figure 9.16). It is estimated that over 20,000 artificial reefs have been

deployed off Alabama since the start of the program in 1953 (Minton and Heath 1998; Patterson

1999). Proponents of Alabama’s artificial reef program cite high catches of red snapper and a

profitable sport fishing industry as evidence of a successful and beneficial program (Minton and

Heath 1998; Shipp 1999); however, little research has focused on the effect of Alabama’s artificial

reefs on the population ecology of red snapper.

As part of a larger research program aimed at understanding the effect of artificial reefs on the

production and fisheries ecology of red snapper, we conducted a tagging study over artificial reefs

off Alabama. One objective of the study was to sample fixed artificial reef sites repeatedly over a

three-year period to estimate site fidelity of adult red snapper to individual reef sites. A second

objective was to test what factors significantly affected the distance and speed of fish movement
635

Figure 9.15. Map of existing petroleum platforms in the U.S. Gulf of Mexico (source: U.S.

Department of Interior, Minerals Management Service, http://www.mms.org).

Figure 9.16. Map of artificial reef permit areas off the coast of Alabama in the northern Gulf of

Mexico.
636

Figure 9.17. Map of the State of Alabama’s Hugh Swingle permit area for artificial reef

deployment with nine artificial reef sites over which red snapper were tagged.

away from reef sites. Results are discussed in the context of red snapper fisheries ecology and the

potential use of marine protected areas as a management tool.

METHODS

From March 1995 to July 1998, we tagged adult red snapper over artificial reef sites located in the

Hugh Swingle General Permit Area off the coast of Alabama. Reef sites (n = 9) were located

between 20 and 38 km south-southeast of Dauphin Island, Alabama (Figure 9.17). Reefs were

constructed of a variety of materials by a charterboat operator 18 months prior to the start of the

tagging study (Table 9.6). Reefs were deployed in a three-by-three grid, and each was designated

by a compass heading that denoted its orientation within the grid (Figure 9.17). Individual sites were

between 4 and 16 km apart and occupied similar depths within each row of the grid. Sites in the

northern, central and southern rows were in approximately 21 m, 27 m and 32 m of water,

respectively. 
637

Table 9.6. Composition and total volume of the nine artificial reef tagging sites.

Site Composition of Artificial Reef Volume m 3

 NW 5 modules of 3, 209-l plastic drums 3.27 

 N 5 modules of 3, 209-l gallon plastic drums 3.27 

 NE 20 newspaper vending machines 3.78

 W 25 newspaper vending machines 4.72

 C 25 newspaper vending machines 4.72

 E 24 newspaper vending machines 4.53

 SW 20 newspaper vending machines 3.78

 S tractor trailer bed welded into a triangle 23.45

 SE 15 washing machines 5.42

Our sampling platform was a charterboat that docked at Dauphin Island, Alabama. On each tagging

trip, we attempted to visit at least three reef sites. While over each site, red snapper were captured

with rod and reel and placed in holding tanks on deck. Each fish was measured (total length (TL)

mm) and then tagged by inserting an internal anchor tag through a small (< 5mm) incision made

with a scalpel in the abdominal cavity. Tags were yellow Floy FM-89 anchor tags and each was

marked with a tag number, the word “reward,” and a phone number for fishers to report tag

recoveries. We offered a $5 reward for each tag return, with a chance to win $500 in a drawing of

tag returners. Once tagged, red snapper were either released immediately overboard or transported

in holding tanks to other tagging sites for release. 

Tagged fish were recaptured at tagging sites on subsequent tagging trips and were recovered by

recreational and commercial fishers at sites other than tagging sites. Fish recaptured on tagging trips

were measured and released, and as much information as possible was obtained from fishers’

recoveries. Data from fishers’ recoveries included tag number, date of capture, and exact location

of capture (i.e., Loran C or GPS coordinates). TL at recapture also was obtained from fishers’

recoveries when it was possible to measure their carcasses.

Site Fidelity and Movement

To meet the assumption of independence, only data from terminal recaptures of fish recaptured more

than once were used in statistical analyses of site fidelity and movement. A priori, factors of interest

included TL at tagging, time at liberty, and transportation prior to release. An unplanned factor was

added to the study when two strong hurricanes passed near the tagging sites. The center of Hurricane

Opal with maximum winds of 200 km hr-1 passed within 40 km of the tagging sites on 4 October

1995, and the center of Hurricane Georges with maximum sustained winds of 150 km hr-1 passed
638

within 50 km of the tagging sites on 28 September 1998. It became apparent that movement of fish

at liberty during the hurricanes was on a larger scale than fish not exposed to the storms. In

statistical analyses of site fidelity, models were computed with and without fish that were exposed

to hurricanes, and exposure to hurricanes was included as an independent variable to test the effect

of hurricanes on the distance and speed of red snapper movement.

Site fidelity was estimated for all recaptures made at tagging sites, recaptures that were not at liberty

during hurricanes, recaptures that were not transported prior to release, and recaptures that were not

at liberty during hurricanes or transported prior to release. To estimate site fidelity, first the decline

in recaptures made on tagging trips was estimated. Recaptures from all nine sites were grouped in

intervals of days at liberty based on the average time between visits to individual reefs. Because

there were fewer tagged fish available to be recaptured during each subsequent time interval, the

number of recaptures made during a given time interval was adjusted by dividing the number of

recaptures available by the total number of fish tagged. The decline in recaptures was estimated by

fitting the following non-linear decay model to the adjusted distribution of recaptures with PROC

NLIN in SAS (SAS, Inc. 1996):

Nt

 = Nie-Dt (1) 

where: Nt = adjusted number of recaptures made in interval t 

NI = estimated number of recaptures in the initial interval

D = instantaneous rate of decline in recaptures (d-1)

t = time (d)

The units of D were converted from d-1 to y-1 by multiplying by 365 d. The instantaneous rate of

decline in recaptures (D) is equal to the sum of total mortality (Z) and instantaneous emigration (Q).

Total mortality (Z) is the sum of natural mortality (M) and fishing mortality (F); however, we

assumed that no fishing mortality occurred at tagging sites (see discussion). Natural mortality (M)

was estimated following Royce (1972) and Hoenig (1983), assuming a maximum age for GOM red

snapper of 42 y (Szedlmayer and Shipp 1994). 

M = 4.6/(maximum age) (Royce 1972) (2) 

ln(M) = 1.44 - 0.982*ln(maximum age) (Hoenig 1983) (3) 

Having estimates of D and M, we solved for E by subtraction. Finally, annual site fidelity was

estimated with the following equation:

SF = e-(Q) (4) 

Distance of movement for fishers’ recoveries was estimated as the distance between release sites

and the Loran C or GPS coordinates where recoveries were made. Speed of movement was

estimated as distance divided by time at liberty. In this approach, we assumed that each fish moved

in a straight line from release site to recovery site and at a constant rate.
639

There were many zeroes in the distance of movement data (i.e., terminal recaptures made at tagging

sites); therefore, the delta method was employed to obtain unbiased estimates of mean distance and

mean velocity of movement (Aitchison 1955; Pennington 1983). To test the effects of time at liberty,

TL at tagging, exposure to hurricanes, and transportation prior to release on distance of red snapper

movement, and to test the effects of TL at tagging, exposure to hurricanes, and transportation prior

to release on speed of movement, negative binomial regression models were computed with PROC

GENMOD in SAS (Hilbe 1994; SAS, Inc. 1996). Distance and speed models were built using a

forward stepwise approach in which regressions first were computed for each independent variable.

The single variable model with the lowest significant p-value (" = 0.05) was chosen as the base

model. Individual variables were added in order of significance, and improvement of fit was

assessed by testing if adding a variable significantly decreased the deviance of the model to which

it was added (Agresti 1990). The model building process was complete when either no more

significant variables were available to be added, or the addition of a variable did not significantly

improve the fit of the model to which it was added.

RESULTS

From March 1995 to July 1998, we made 28 tagging trips and tagged 2,932 adult red snapper (Table

9.7). Of these fish, 2,053 were released at their tagging sites and 879 were transported to other

tagging sites for release. Mean TL (± SE) of tagged fish was 335.1 mm (± 1.34) (Figure 9.18). From

the start of the project until June 1998, the minimum legal size for possession of GOM red snapper

for both commercial and recreational fisheries was 381 mm (15 inches) TL, but the size limit for the

recreational fishery was increased to 457 mm TL (18 inches) TL from June through August 1998.

Therefore, 80% of tagged fish (n = 2,366) were shorter than the legal size limit at the time of

tagging.

Five hundred ninety-four recaptures of 550 red snapper were made through September 2000. Fortytwo individuals were recaptured twice (23 second recaptures were made by fishers and 19 were

made on tagging trips) and one individual was recaptured three times (all three recaptures were

made on tagging trips). Of the 550 terminal recaptures, 264 fish were not at liberty during at least

one hurricane; mean time at liberty was 623 days for fish exposed to hurricanes and 341 days for

fish not exposed to hurricanes. Four hundred thirty-seven recaptures were not transported prior to

release, and 113 recaptures were transported prior to release. Two hundred fourteen fish were

recaptured on tagging trips, of which 191 recaptures were terminal recaptures. Three hundred fiftynine recoveries were reported by fishers (fishers’ return rate = 12.2%); however, recreational fishers

reported 354 recoveries (recreational return rate = 12.0%) and commercial fishers reported only five

(commercial return rate = 0.2%). Total Length at recapture was measured for all terminal recaptures

made on tagging trips and for 97 (27.0%) recaptures reported by fishers (Figure 9.19).

Site Fidelity and Movement

All non-linear decay models of the decline in recaptures over time were highly significant (p <

0.001; R2

 > 0.97) (Figure 9.20). Estimated natural mortality from both the method of Royce (1972)

and of Hoenig (1983) was 0.11. Estimates of annual site fidelity ranged from 21 to 26% y-1 (Figure

9.20).
640

Table 9.7. Dates of tagging trips, tagging sites samples, and number of red snapper tagged.

Date Tagging Sites Number

Tagged Date Tagging Sites NumberTagged

22Mar 1995 C, SE 94 7 Aug 1996 SE, NE, N 86

3 May 1995 N, NE, NW, C 107 31 Oct 1996 C, W, NW, SW 189

20 Jun 1995 W, S, SW 153 1 Nov 1996 NE, E, SE 152

21 Jun 1995 E, SE, C 118 12 Dec 1996 N, C, S 150

29 Aug 1995 SE, E, NE 129 9 Dec 1996 NE, E SE 122

13 Sep 1995 NW, W, SW 100 26 Mar 1997 NW, N, NE 114

14 Sep 1995 N, C, S 112 27 Mar 1997 SW, S, C 117

30 Nov 1995 S, SE, NW, C 107 29 Apr 1997 NW, N, NE 42

12 Dec 1995 N, SW 73 18 Sep 1997 NW, N, NE, E 147

27 Feb 1996 SW, W, NW 42 23 Sep 1997 C, SE, S 65

22 Mar 1996 N, C, S 41 3 Nov 1997 NW, N, NE 136

29 Mar 1996 NE, SE, E 38 5 Nov 1997 W, SW, S, C 186

1 May 1996 S, SE, C 37 25 Feb 1998 NW, N, NE 147

12 Jun 1996 SW, S, W, N, C 50 20 July 1998 NW, N, NE 104

Location of recapture was reported for 252 (70%) recoveries reported by fishers. The farthest

distance an individual moved was 352 km (Figure 9.21), and the longest time at liberty was 1,501

d. Mean distance moved was 29.4 km (Figure 9.22a), and mean time at liberty was 409 d. Distance

of movement single variable negative binomial regressions were significant for exposure to

hurricanes (P2

d.f = 1 = 9,404.4; p < 0.001), time at liberty (P2d.f = 1 = 25.1; p < 0.001) and TL at tagging

(P2

d.f = 1 = 6.3; p = 0.013), and not significant for transportation prior to release (P2d.f = 1 = 0.21; p =

0.645). The variable time at liberty was added to the single variable regression model testing the

exposure to hurricanes’ effect and lack of fit for the model was not significant (P2

d.f = 443 = 426.0; p

= 0.711). The addition of time at liberty to the exposure to hurricanes model significantly decreased

the model’s deviance (P2

d.f = 1 = 37.1; p < 0.001). Total length at tagging then was added to the

model, but its addition increased the model’s deviance. Therefore, the final model included only

exposure to hurricanes and time at liberty effects:

Distance = e {-20.74 + 21.61*(Cane) + 23.99*(TAL) + ,} (5) 
641

Figure 9.19. Distribution of total length at recapture of terminal recaptures at tagging sites (black

bars, n = 192) and measured terminal recaptures from fishers (gray bars, n = 97).

Figure 9.18. Distribution of total length at tagging of red snapper tagged in this study.
642

Figure 9.21. Spatial distribution of recaptures reported by fishers (n = 251). Open circles

designate fish exposed to hurricanes (n = 147) and closed circles designate fish not

at liberty during hurricanes (n = 104).

Figure 9.20. Distribution of number of recaptures made on tagging trips over time and fitted nonlinear decay models for A. all terminal recaptures (n = 191), B. terminal recaptures

not at liberty during hurricanes (n = 149), C. terminal recaptures not transported

prior to release (n = 172), and D. terminal recaptures not at liberty during hurricanes

or transported prior to release (n = 139). Fitted lines follow the model Nt

 = NIe-Dt,

where D is the instantaneous rate of decline y-1 and t is time in y. All models were

highly significant (p < 0.001; R2 $0.97).
643

Figure 9.22. Delta method estimates of mean distance and mean velocity of movement. Error bars

are standard error of the mean.
644

Mean speed of movement was 73.9 m d-1 (Figure 9.22b). Speed of movement single variable

negative binomial regressions were significant for exposure to hurricanes (P2

d.f = 1 = 2,536.9; p <

0.001) and TL at tagging (P2

d.f=1 = 4.0; p = 0.047), and not significant for transportation prior to

release (P2

d.f = 1 = 2.7; p=0.102). The addition of TL at tagging to the exposure to hurricanes model

significantly increased the model’s deviance. Therefore, the final model included only the hurricane

effect:

Speed = e {-20.78 + 18.541*(Cane) + ,} (6) 

DISCUSSION

Authors of previous tagging studies of GOM red snapper generally concluded that adult red snapper

displayed strong site fidelity and limited movement (Beaumariage 1969; Fable 1980; Szedlmayer

and Shipp 1994; Szedlmayer 1997). Beaumariage (1969) and his colleagues tagged 1,126 red

snapper off northwest Florida (FL) in the 1960s and reported tag returns from 315 fish. Mean time

at liberty of reported recoveries was 113 d and most (90%) were made less than 5 km from release

sites; however, several fish moved over 100 km. Fable (1980) tagged 299 red snapper at petroleum

platforms off south Texas TX and reported 17 tag returns. He reported little movement away from

platforms, but maximum time at liberty was only 253 days. Szedlmayer and Shipp (1994) tagged

1,155 red snapper over artificial reefs off Alabama in the early 1990s. They recovered 146 tagged

fish, but were able to confirm location of recapture for only 37 returns. The greatest distance moved

was 32 km and the maximum time at liberty was 430 days; mean time at liberty for all recaptures

was 113 days. Szedlmayer (1997) released 26 red snapper that were tagged with ultrasonic

transmitters over artificial reefs off Alabama. He was able to detect transmitters up to 1.8 km, and

tracked movements of 19 fish for an average of 118 days before individuals were caught by fishers

(n = 14), lost from the study area (n = 5), or the study ended. Maximum observed movement was

740 m for a fish that was tracked for 71 days before it was lost from the study area. 

While many authors have reported high residence of red snapper on natural or artificial reefs, others

have reported temporal variability in red snapper abundance. Moseley (1966) observed fluctuations

in red snapper abundance on reefs off Texas and hypothesized that passing cold fronts effected

onshore-offshore migrations. Beaumariage and Bullock (1976) reported seasonal variability of fish

abundance off northwest Florida and suggested that fish migrated annually to summer forage

grounds. Stanley and Wilson (1997) estimated fish abundance monthly for one year with

hydroacoustics and video from a remotely operated vehicle at a petroleum platform off Louisiana,

and reported significant variability in red snapper numbers between months. 

Red snapper tagged in our study demonstrated relatively low site fidelity to artificial reefs off

Alabama. While this finding is consistent with studies that have reported temporal variability in red

snapper abundance on natural and artificial reefs (Beaumariage and Bullock 1976; Moseley 1966;

Stanley and Wilson 1997), it is contrary to the widely reported conclusion that red snapper display

strong site fidelity (Beaumariage 1969; Fable 1980; Szedlmayer and Shipp 1994; Szedlmayer 1997).

In our approach, we assumed that no fishing mortality took place at tagging sites. This assumption

was based on the fact that no recoveries were reported as being caught at Loran C or GPS

coordinates that matched those of tagging sites. If fishing mortality did occur at tagging sites, our
645

estimates of site fidelity would be biased low. Estimated F of GOM red snapper ages 3-6 (the

approximate age distribution of recaptured fish, see Szedlmayer and Shipp (1994)) during 1995-

1998 was 0.36 (Schirripa and Legault 1999). If fishing mortality occurred at a similar rate at tagging

sites, estimated annual site fidelity would only increase from 25.3% to 33.2% y-1 for the model that

included all recaptures made at tagging sites. 

Too few individuals transported prior to release and/or exposed to hurricanes were recaptured at

tagging sites to model declines separately for these two factors. We attempted to account for the

effect of these factors on site fidelity by modeling the decline in recaptures with and without fish

transported prior to release and/or exposed to hurricanes. Estimated site fidelity increased slightly

when transported individuals were excluded, which agrees with the findings of Watterson et al.

(1998) and Patterson (1999) that transporting individuals increased their likelihood of movement.

We expected a similar result when individuals exposed to hurricanes were excluded; however,

estimated site fidelity actually decreased when fish exposed to hurricanes were omitted. This result

is due to the fact that more individuals exposed to hurricanes were recaptured at tagging sites during

the second and third time intervals than in the first, which resulted in a steeper function (i.e., a more

rapid decline in recaptures) when fish exposed to hurricanes were omitted. This may indicate that

some fish initially moved away from our reef sites following the storms but later returned.

There were two scales of movement observed for fish that moved away from tagging sites. Fish

exposed to hurricanes moved significantly farther than fish that were not. Time at liberty also

significantly affected the distance fish moved, and the fact that individuals exposed to hurricanes

were at liberty longer than those not exposed may partially explain their greater distances of

movement. However, hurricanes also significantly affected the speed at which recovered fish moved

to their site of recapture. Therefore, distance of movement for fish exposed to hurricanes was not

simply a function of greater time at liberty.

Goodyear (1995) reported that the rapid decline in fishers’ tag recoveries with time at liberty from

previous red snapper tagging studies indicated either high mortality or tag shedding, but in either

case, long-term observations of movement would not be possible. Mean time at liberty was longer

for reported recoveries in the present study than from previous studies, and movement also was on

a larger scale (Beaumariage 1969; Fable 1980; Szedlmayer and Shipp 1994; Szedlmayer 1997).

Furthermore, estimates of mean distance and speed of movement reported here are likely

conservative. Patterson (1999) reported a high rate of tag shedding for red snapper tagged during

the current study; therefore, fish movement may be underestimated because the longer fish were at

liberty, the lower the likelihood they would be recognized as tagged fish. Size limits and other

management regulations also may have caused underreporting by fishers of fish that moved away

from their release sites (Patterson 1999). 

Implications of Red Snapper Movement 

The perception that adult red snapper demonstrate high site fidelity to artificial reef sites has driven

the discussion of the effect of artificial reefs on red snapper fisheries ecology off Alabama.

Szedlmayer and Shipp (1994) concluded that artificial reef areas off Alabama increased production

of red snapper, rather than attracting fish from other areas, based on their findings that fish displayed
646

a high degree of residence on artificial reefs, and that red snapper grew faster and had higher

abundances of juveniles off Alabama than other areas in the GOM. Their conclusion was tenable

given the state of knowledge about GOM red snapper when it was proposed, but recent studies do

not support it. Our results indicated that site fidelity of red snapper to artificial reefs was relatively

low and that movement increased with time at liberty. Patterson (1999) reported that growth of red

snapper captured off Alabama was similar to fish caught in the northwestern GOM. Gallaway et al.

(1999) reported that catch per unit effort and habitat suitability index values for nursery areas off

ALMS were similar to other areas in the GOM.

While it is possible that the creation of artificial reefs off Alabama and the deployment of petroleum

platforms as de facto artificial reefs in the northwest GOM have shifted the center of GOM red

snapper abundance from its historic center off the west coast of Florida (Stearns 1884; Collins 1885;

Camber 1955; Carpenter 1965; Goodyear 1995), to our knowledge no data exist to support the

contention that natural reef habitat currently limits GOM red snapper stock size (Cowan et al. 1999).

The likelihood that artificial reefs have increased production of red snapper in the northern GOM

is further diminished when one considers that this stock is currently estimated to be overfished

(Schirripa and Legault 1999) and that year class strength appears to be driven by natural and

anthropogenic (shrimp trawl bycatch) sources of mortality on juveniles, rather than by adult habitat

availability (Bohnsack 1989; Goodyear 1995; Cowan et al. 1999). An equally plausible explanation

of the role of northern GOM artificial reefs is that they serve as a net sink of red snapper production,

as the period of artificial reef creation off Alabama is coincident with the fishing down of the

northern GOM red snapper stock to the point where spawning potential ratio currently is estimated

to be less than 5% (Schirripa and Legault 1999). 

While the benefits of artificial reefs to fishing, such as aggregating fishes and increasing catch rates,

are well documented (Polovina 1991; Stone et al. 1991), few studies have shown conclusively that

artificial reefs increased production (but see Polovina and Sakai 1989; Butler and Herrnkind 1997).

Pitcher and Seaman (2000), however, proposed that artificial reefs deployed in no-take areas could

help mitigate overfishing and habitat degradation. Fisheries managers have begun to consider the

possibility of no-take marine reserves as a management tool in the GOM (Plan Development Team,

1990; Gulf of Mexico Fishery Management Council (GMFMC) 1999a). In fact, the GMFMC has

proposed creating two no-take marine reserves off the west coast of Florida to preserve and increase

the spawning stock biomass of gag Mycteroperca microlepis and other grouper species (GMFMC

1999b). Holland and Brazee (1993) demonstrated with simulation modeling that no-take marine

reserves could be implemented to increase spawning stock biomass of GOM red snapper. Estimates

of red snapper site fidelity and velocity of movement from this study will benefit decision-makers

faced with estimating the optimal size of marine reserves designed to maintain or increase red

snapper spawning stock biomass. 

ACKNOWLEDGMENTS

Funding for this project was provided by the United States National Oceanic and Atmospheric

Administration through MARFIN grant number NA57FF0054 to R.L.S. The authors thank Mike and

Ann Thierry for deploying artificial reefs used in this study and for allowing us to tag red snapper

onboard their charter fishing vessel Lady Ann. The authors thank Walter Ingram and for advice
647

concerning statistical tests and Yvonne Allen for help with figure preparation. The authors

acknowledge a great debt to all volunteer fishers who helped in the tagging process and to all

commercial and recreational fishers who reported tag recoveries. 

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651

ABUNDANCE, AGE DISTRIBUTION, GROWTH RATE, AND MORTALITY

ESTIMATIONS FOR RED SNAPPER, LUTJANUS CAMPECHANUS,

AROUND GAS PLATFORMS AND OTHER ARTIFICIAL STRUCTURES

IN THE NORTHEAST GULF OF MEXICO 

Stephen T. Szedlmayer

Carol Furman

Dustin Moss

Marine Fish Laboratory

Department of Fisheries and Allied Aquacultures

Auburn University

ABSTRACT

We estimated red snapper Lutjanus campechanus, abundance, age frequency, fecundity, and

mortality, through a fishery independent survey. We tested six capture methods: bandit rigs, gill

nets, fish trap, hook-and-line, drop net, and spear gun. After fishing, we used SCUBA visual counts

to estimate remaining red snapper. All captured fish were weighed, measured, otoliths removed and

ovaries weighed and preserved in Gilsons. We captured 1,147 red snapper at 28 different artificial

reefs. Mean + Sd abundance per reef = 86.3 + 69.4. Estimated population size off Alabama from 15

to 73 m depths = 1.3 million red snapper. Mean size = 279 + 59 mm SL, and mean age was two

years. We captured 442 females with 32 % mature. Spawning duration was 142 d, with peaks from

May through July. Batch fecundity = 83,870 eggs per fish, with annual fecundity = 2.9 million eggs

per fish. Fish trap was the best capture method and SCUBA visual survey was the best abundance

estimator. Females start maturing above 250 mm SL, and GSI peaked May to August. Total

mortality was high (Z = -2.0) over the year classes sampled. Growth rates were 140 mm TL per year.

Abundance estimates may be low, because we sampled only heavily fished reef sites, and future

efforts will be directed at “unpublished” reef sites.
652

MOVEMENT, GROWTH AND SURVIVAL OF GRAY TRIGGERFISH, 

BALISTES CAPRISCUS, INHABITING ARTIFICIAL AND NATURAL

REEFS IN THE NORTH-CENTRAL GULF OF MEXICO

G. Walter Ingram, Jr.

Department of Marine Sciences

 University of South Alabama

Robert L. Shipp

Department of Marine Sciences

University of South Alabama

ABSTRACT

In the Gulf of Mexico (Gulf), the gray triggerfish (GTF) inhabits both natural and artificial reefs.

Due to high site fidelity of GTF, the goal of this study is to determine if GTF may be better managed

with respect to local demographics, including differences between GTF inhabiting natural versus

artificial reefs.

This study consists of two separate tagging projects conducted off the Alabama coast. The first

project (P1) was conducted between June 1995 and December 1997 over nine artificial reefs with

three reefs in each of three depth strata (20, 26, and 36 m). The second and currently ongoing project

(P2) began in October 1997 and is being conducted over a cluster of six natural reefs in 20 m of

water and a cluster of three natural reefs in 32 m of water.

Of the 201 GTF tagged during P1, 50 have been recaptured, with 31 recaptured at the site of release.

Also, of the 500 GTF tagged during P2, 65 have been recaptured, with 49 recaptured at the site of

release. The distribution of fork-length at tagging was significantly different (p<0.00001) between

P1 (0±s=347±57mm) and P2 (297±41mm), which may result from gear bias and/or differences

between reef habitats. Linear and von Bertalanffy growth parameters were estimated from combined

data from both projects (i.e., 0.14 mm/day and L4 =836 mm and K=0.0998, respectively). During

both projects, both magnitude of movement (P1: p=0.0000998; P2: p=0.050) and velocity (P1:

p=0.0002; P2: p=0.049) increased significantly in GTF at large during tropical cyclones. Also, a

trend of decreasing site fidelity with depth was found in both projects. With the majority of

recaptures occurring at the point of initial release, GTF seem to exhibit high site fidelity on both

artificial and natural reefs.
653

RED SNAPPER (LUTJANUS CAMPECHANUS) DIET

ON ALABAMA ARTIFICIAL REEFS

Jessica R. McCawley

Robert L. Shipp

University of South Alabama/Dauphin Island Sea Lab

James H. Cowan, Jr.

Louisiana State University

Coastal Fisheries Institute

ABSTRACT

Red snapper, Lutjanus campechanus, is a highly exploited reef fish in the Gulf of Mexico (GOM)

snapper-grouper complex that occupies both natural hard bottom and artificial habitats throughout

its range. Despite its importance, relatively little is known about its habitat preferences and feeding

habits. Toward this end, I examined the size-specific diet of red snapper collected for gut content

analysis from artificial reefs in the north-central GOM off Alabama between May1999-April 2000.

Thirty-nine to 86 stomachs per month were removed and prey items identified to the lowest possible

taxonomic level. The relative contribution of prey items was determined using percent frequency

of occurrence, percent composition by number, percent composition by weight, and index of relative

importance (IRI). Results suggest that snapper selectively feed on organisms not associated with

reefs, such as mantis shrimp (16% by weight) and portunid crabs (27.3% by weight). Diet changes

seasonally with crabs being the most important in summer and fall (31.4-36.3% W), while mantis

shrimp are important in winter (33.3% W). Pelagic zooplankton are consumed heavily in the spring

(39.1% W). Diet also changes with snapper size, as red snapper get larger, more of their diet is made

up of demersal crustaceans. These diet data ultimately will be used in combination with a bioenergetics budget to estimate prey demand of a red snapper population on Alabama artificial reefs.

INTRODUCTION

Red snapper, Lutjanus campechanus, is a highly exploited finfish in the GOM. It has been harvested

both commercially and recreationally since the late 1800s (Moseley 1966, Goodyear 1995, Schirripa

and Legault 1997). Thus, stocks declined throughout the GOM unitl the early 1990s (Szedlmayer

and Shipp 1994). Since then, regulations that have been put in place by the National Marine

Fisheries Service, including size and bag limits and total allowable catches, have helped the stock

begin to recover (Schirripa and Legault 1997, Patterson 1999). 

The recovery of the stock has also been attributed in part to an increase in structure in the form of

artificial reefs and oil and gas platforms. The Alabama shelf has the largest artificial reef program

in the nation with over 4000 km2

 of reef permit area (Shipp 1999). Perhaps as many as 20,000 artificial reefs have been deployed off the Alabama coast (Patterson 1999); these structures support red

snapper and other reef associated species. However, the role that artificial reefs play in trophic dynamics is largely unknown; some have suggested that they may be energy sinks (Bortone 1998). 
654

In addition, there has been a growing recognition that interacting species, such as those found on

artificial reefs, cannot be managed individually. This idea has led to the development of multispecies

ecosystem models, which has generated the need for more information about the food consumed by

communities of reef fish (Munro 1987, Bohnsack 1998). This study examines the role artificial reefs

may play in red snapper trophic dynamics, focusing on seasonal changes and changes with fish size.

METHODS

Monthly Sampling

Red snapper were collected by hook and line from artificial reefs in the northern GOM off the coast

of Alabama between May 1999 and April 2000. Most fish were caught by recreational fishermen

in the Hugh Swingle General Permit Area. However, some were collected in July 1999 and 2000

from local fishing tournaments. Knowing that red snapper are prone to regurgitation (Parrish 1987),

approximately 39 to 86 fish were collected per month to ensure a significant number of fish with full

stomachs. All snapper were weighed to the nearest 0.01kg, and their total length (TL) and fork

length (FL) determined to the nearest mm before their stomachs were removed. Stomachs were

severed at the esophagus and duodenum below the pyloric sphincter, slit to allow complete

preservation, and then preserved in 10% formalin for at least 48 hours. They then were transferred

to 70% isopropyl alcohol until they could be sorted. Preserved stomachs were opened and contents

removed and sorted to the lowest possible taxonomic level. Prey items were then weighed by taxon

to the nearest 0.01g. Empty stomachs were either labeled as genuinely ‘empty’ or distended

according to the description of Treasurer (1988). 

Enumeration of Stomach Contents

The relative contribution of each of the prey items was determined using four methods: (1) percent

composition by weight, (2) percent composition by number, (3) percent frequency of occurrence,

and (4) index of relative importance. The index of relative importance (IRI) was determined using

the formula: IRI = (%N +%W) x %FO, where N = number, V = volume, and FO = frequency of

occurrence (Pinkas 1971, modified by Hacunda 1981). Percent IRI (% IRI) was also calculated by

dividing the IRI value for each prey category by the sum of the IRI values and multiplying by 100.

These indices were used to describe the overall diet, as well as to evaluate the diet on a seasonal

basis (summer= June, July, and August; fall= September, October, and November; winter=

December, January, and February; and spring= March, April, and May) as well as by red snapper

size class. Red snapper were divided into 5 size classes (200-299mm FL, 300-399mm FL, 400-

499mm FL, 500-599mm FL, and >600mm FL). The identifiable contents of all stomachs combined

were divided into 6 major prey categories; fish, crabs, adult mantis shrimp, penaeid shrimp, squid,

and an ‘other’category. The ‘other’category was further subdivided into pelagic zooplankton and

demersal/benthic associated species, with the exception of larval fish, which were included in the

fish category and crab megalopae and zoea, which were included in the crab category. The diet also

consisted of an ‘unidentified’ category, which was not used in some portions of the analysis because

IRI cannot be determined for this category. 
655

RESULTS

Monthly Sampling

Stomach contents of 656 red snapper ranging from 207 to 913mm FL were examined. Of these, 268

stomachs contained identifiable prey (40.8%), 262 were empty (39.9%), 63 contained only bait

(9.6%), and 63 contained only unidentifiable prey (9.6%). Of the 262 stomachs classified as empty,

169 were considered ‘truly’ empty (65%) and 93 (35%) were considered distended or empty due to

regurgitation. 

The ‘unidentified’ prey category made up the largest proportion of the diet by %W. After exclusion

of the unidentified category, fish, pelagic zooplankton, and crab were the principal components of

red snapper diet when all stomachs were combined. However, no single group was largest by all

indices. Pelagic zooplankton were the largest category by % FO (39.3%) and % N (30.2%), whereas

fish was the largest category by % IRI (30.9%) and % W (28.7%). Unidentified fish, larval fish, fish

of the families Ophicthidae (shrimp eels), and Triglidae (sea robins) contributed largely to the fish

portion of the diet, whereas crabs of the family Portunidae and unidentified crabs were important

in the crab category. Pelagic zooplankton consisted primarily of larval mantis shrimp, amphipods,

and pteropods (Cavolinia sp.). 

Seasonal Diet

An examination of gut contents by season for all stomachs (%W) indicates that while fish were

present in red snapper diet in all seasons (comprising between 25-34% W), fish did not contribute

the greatest amount by weight in any season. The diet in summer and fall was comprised

predominately of crabs (31.4% W in summer and 36.3% W in fall). Winter diet was comprised

predominately of adult mantis shrimp (33.3% W) and spring of pelagic zooplankton (39.1% W).

Demersal crustaceans (crabs and adult mantis shrimp) were present in all seasons, comprising

approximately 50% by weight of the diet in summer, fall, and winter. During the spring, red snapper

fed on high numbers of pelagic zooplankton, which were present at some level in all seasons.

However, the numbers of pelagic zooplankton consumed appeared to be inversely related to

numbers of demersal crustaceans eaten by red snapper. 

Size Class

All stomachs were pooled for an examination of size class differences; the same 7 prey categories

as described above were used. Fish were present in the diet of all size classes of red snapper and

were the largest contributor to the diet of the 200-299mm (36.4% W) and the 500-599mm (40.2%

W) fish. The diet of 300-399mm fish was almost fairly equally proportioned among the prey

categories, however crab made up the largest portion of the diet (25.8% W). Crab was also the most

important prey item of >600mm snapper, making up 51.5% of the diet by % W. The diet of the 400-

499mm snapper was comprised primarily of pelagic zooplankton (35% W). There appears to be a

shift in diet with red snapper size. As snapper get larger they apparently eat more demersal

crustaceans and less pelagic zooplankton and fish.
656

DISCUSSION

Our results show seasonal shifts in red snapper diet on Alabama artificial reefs. These findings are

similar to most other studies of red snapper diet including another off Alabama (Bailey 1995) (Table

9.8). However, Bradley and Bryan (1974) found fish to be the largest category in fall, winter, and

spring, but crabs contributed the most to the summer diet. Specifically in their study, spring was

comprised primarily of eels, mantis shrimp, and Sicyonia sp. (rock shrimp); summer was comprised

primarily of Callinectes danae and S. dorsalis; and winter was comprised primarily of eels. In this

study, eels (Ophicthids) were found in all seasons except fall, but they were never the largest

category by percent weight. In contrast, mantis shrimp contributed the largest percent by weight to

the diet of red snapper off Alabama in winter, and were lowest in spring. Parrish (1987), in his

literature review of snapper and grouper diet’s stated that the principal food groups of snapper in

most studies are fish and decapod crustaceans, which was consistent with the current study.

Anguilliform fishes, like the Ophicthids that we found, were common in the snapper diets he

examined. Parrish (1987) found crabs to be the second most abundant prey category, specifically

with Portunid and Calappid crabs mentioned in several reports, while shrimps and other crustaceans

(especially stomatopods) were the next largest diet category. He also stated that snappers often ate

large plankton, which were an important part of the diet for some Lutjanid species he reviewed,

specifically pteropods, which were found in our study to make up between 13-21% W of the diet

in spring and summer. Larval mantis shrimp, which were also found in the current study in large

amounts in all seasons (highest in summer and winter) are thought to form large swarms in tropical

waters (Morgan and Provenzano 1979). Randall (1967) found that they made up a considerable

portion of the diet of reef fishes in the West Indies.

Our results also show that diet shifts with the size of red snapper. Randall (1967) and Moseley

(1966) found that as snapper get larger their diet is made up of proportionally more fish and less

crustaceans. Our study found the opposite to be true. As red snapper got larger (>600mm), their diet

was increasingly comprised of benthic crustaceans and less fish. However, our results could be

attributable to the fact that many of our larger fish were collected in the summer when these

crustaceans are abundant. In 500-599mm red snapper, which we collected both in spring and

summer, fish did contribute largely to red snapper diet. It is also possible that the way in which we

treated our gut contents data could have contributed to observed differences between our study

results and those of previous studies. We treated each stomach as a replicate and found the

proportion of each of the prey items for that stomach (Bowen 1996), after which we computed a

mean and standard error for each season or red snapper size class across all replicates. Some of the

previous studies do not provide enough information for us to determine how their indices were

calculated, thus making direct comparisons impossible.

Many of the crustaceans we found in the diet are sand/mud inhabitants of the shelf. The Portunid

crabs (swimming crabs such as Portunus gibbesii) as well as the mantis shrimp (Squilla empusa)

inhabit mud or sand substrates (Williams 1984, Wenner and Wenner 1989, Manning and Heard

1997). Hildebrand (1954 cited in Williams 1984) found S. empusa to be the third most abundant

crustacean in the Gulf offshore trawl fishery only following Penaeus sp and Callinectes sp. On the

Alabama shelf, S. empusa can be collected year-round from mud bottom areas, and are the most

abundant stomatopod on the Alabama shelf (Rich Aronson, pers. comm.). Rouse (1970) (cited in
657

Table 9.8. Literature review of some red snapper diet studies relevant to the present study.

Source

Location

of study Fish size

#

Stomachs

Examined

(# w/ food) Description of Results

Moseley 1966 712 (187)

Louisiana juvenile (28) 30% FO of crustaceans, another

sample had 60% Squilla (night

sample), unidentified fish made

up 27% of this sample

adult (46) 44% fish in one sample, 80% fish

and rest crustaceans in another

Texas juvenile (45) 41% crustaceans in one sample,

89% crustaceans in another

adult (68) Fish dominated the diet in all

samples (40-69%), crustaceans

were present in small numbers

Bradley and

Bryan 1974

Texas juvenile and

sub-adult

575 (258) Summer ate shrimp and crabs,

spring and winter ate squid.

Mantis shrimp made up portion of

diet in summer, winter had most

varied diet

adult 1139 (190) Primarily ate fish, but in fall and

winter ate more crustaceans. In

spring 13% of diet was tunicates.

Summer had largest variety and

winter the smallest variety

Bailey 1995 Alabama 330-691 mm

TL

98 Principal prey items in summer

were rock shrimp and crabs, also

ate some eels and unid. fish

Lee 1998 Alabama 10-280mm

SL

1652 (792) Halichoeres sp., Serranus sp. and

Centropristis sp.) and shrimp

(Lysmata sp. and Synalpheus sp.)

and squid. 

 Williams (1984)) stated that P. gibbesii was the most often collected Portunid in the GOM. Other

of the Portunids found in the stomachs, such as P. spinicarpus, P. ordwayii, and C. sapidus were

also cited by Williams (1984) as being found either on mud bottoms or a variety of bottoms, but not

on reefs. Most of the crustaceans we found in the stomachs are associated with mud bottom and are

abundant in the GOM. The same is true for many of the important fish prey species such as

Ophicthid fishes, sea robins, and cusk eels. 
658

Thus, red snapper foraging does not appear to be directly associated with artificial reefs; they may

be gaining little nutritional support from the reefs. The prey species that are abundant on Alabama

artificial reefs, such as, sea basses, tomtates and other grunts (Andy Strelcheck, pers. comm.), were

not found in the diets of red snapper in this study, although they did eat in smaller numbers some

organisms that are associated with reef structure such as Syngnathids (pipe fish and sea horses) and

pinfish. Starck (1968) also lists species that have an affinity to reefs, such as lizardfish, gobies, and

wrasses, which would be expected in the diet, but these fish were not found in the stomachs of the

red snapper we sampled. Thus, we infer that red snapper are selectively or preferentially feeding on

non-reef habitat. 

Other studies of red snapper diet describe foraging habits that support this claim. Moseley (1966),

in a red snapper diet study off of Texas and Louisiana, found that red snapper do not always feed

on reef associated species. He stated that “Based on food habits, there seems to be no particular

reason why red snappers should congregate on reefs or rocky areas... .” Parrish (1987) states that

snapper probably remain within a few meters of the bottom because most of their prey needs to be

captured from the substrate. He classifies L. campechanus as an intermediate depth feeder, which

means they forage anywhere from relatively shallow water up to 100m. He states that such feeders

probably forage widely from shelter over soft bottom to gain food, or either forage by “patrolling

up to several meters off the bottom for nektonic prey as well as periodically foraging on substrate

for fully benthic prey.” Supporting this idea, this study found that snapper consumed some

organisms that reside higher in the water column, such as larval mantis shrimp, fish larvae,

amphipods, and pteropods, and other assorted pelagic zooplankton as well as mud associated

species. Davis and Birdsong (1973) describe coral reefs and other “habitat interfaces” as rich in

diversity saying they “represent ‘cross roads’ between foraging and refuge areas.” Artificial reefs

can be seen in much the same context, as snapper seem to supply their energetic demands from

habitats other than reefs. It is still unclear if red snapper are simply leaving a reef to forage on

nearby mud bottom, or if they are feeding during their transit between reefs, or both. In contrast, Lee

(1998) found snapper over artificial reefs ate reef associated prey, such as fish (Halichoeres sp.,

Serranus sp. and Centropristis sp.) and shrimp (Lysmata sp. and Synalpheus sp.) (although he

examined snapper smaller (10mm – 230mm standard length) than what we studied). Perhaps smaller

red snapper, such as the ones Lee (1998) examined, are more reef dependent than their larger

counterparts. 

The data from this diet study will be used along with information on red snapper diel feeding

patterns, and the caloric content of the prey species to present a complete picture of the foraging

habits of red snapper off of Alabama. That data then will be used along with information on growth

rates of snapper on artificial reefs as well as metabolism values in a bioenergetics model to obtain

a first order estimate of the prey demand of a red snapper population on a reef.

ACKNOWLEDGMENTS

This study was funded by a Mississippi-Alabama Sea Grant Fellowship and the Alabama

Department of Conservation, Marine Resources Division. Special thanks to Julie Prerost for her help

in identifying the invertebrates. 
659

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661

INDEX TO AUTHORS

Allen, J. D. (Dan) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Arnold, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Baine, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

Baltz, D. M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167, 169

Barber, Todd Ryan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631

Bates, Thomas W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

Beaver, Carl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 601

Benfield, Mark C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185, 499

Biggs, Douglas C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Blandon, Ivonne R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

Boland, Gregory S. .................................................... 21, 23, 372

Bond, P.J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

Bridger, Christopher J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Bull, Ann Scarborough . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Burgess, George H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67, 284

Burks, Carolyn M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Chesney, E. J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167, 169

Childs, Jeff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 65, 66

Childs, Susan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 601

Coleman, Felicia C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109, 160

Colura, Robert L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

Cope, Joseph S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Costa-Pierce, Barry A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Cowan, James H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633, 653

Culbertson, Jan .......................................................... 92, 614

de Wit, LeRay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Deming, Jody . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 23

Ditty, James G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Dokken, Quenton R. ..................................................... 182, 601

Dorf, Barbara A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334

Dougall, Dave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Drass, D.M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

Edwards, Randy E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Embesi, J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
662

Escobar-Briones, Elva . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 23

Farooqi, Talat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Friel, Chris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Furman, Carol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651

Gitschlag, Gregg R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357

Gledhill, Christopher T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Goudey, Clifford . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Hammerschmdit, P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Hanisko, David S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554

Harper, Jr., Donald E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614

Henwood, Terry A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Hernandez, Jr., Frank J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184, 185, 514

Hewitt IV, John D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Hiett, Robert L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144

Hubbard, Fain ............................................................ 21, 23

Hymel, M. K. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167, 169

Ingram, Jr., G. Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 652

Karel, William J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

Kasprzak, Richard A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5, 472

Keenan, Sean F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499

Kemmerer, Andrew J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

King, Tim L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353

Koenig, Christopher C. ................................................... 109, 160

Kolok, A. S. ........................................................... 167, 169

Lagera, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Link, Jason S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Lohse, Angela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 23

Lubinski, Barbara A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353

Lukens, Ronald R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Lyczkowski-Shultz, Joanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333, 554

McCawley, Jessica R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653

McEachron, Lawrence W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

McManus, Roger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Miller, Margaret . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

Miller, Mark ........................................................... 472, 581

Milon, J. Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
663

Moss, Dustin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651

Mullin, Keith D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Nieland, David L. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

Patterson, William F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633

Peter, D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Pierce, Aaron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 580

Rademacher, Kevin R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

Render, Jeffery H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

Ressler, Patrick H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Rowe, Gilbert T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 23

Scanlon ,Kathryn M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109, 160

Schirripa, Michael J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357

Shaw, Richard F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184, 185, 514

Shipp, Robert L. ................................................ 101, 633, 652, 653

Side, Jon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120

Snelson, Jr., Franklin F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

Snyder, David B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67, 284

Stanley, David R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3, 421, 472

Stickney, Robert R. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

Sulak, Kenneth, J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Szedlmayer, Stephen T. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183, 283, 651

Tarr, M. A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167, 169

Topolski, Marek F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

Ward, Rocky . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

Weaver, Doug . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Wilson, Charles A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5, 271, 421, 472, 580, 581

Wirgin, Isaac I. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353
665

ATTENDEES

Allen, Dan 

Ecologist

Chevron USA Production Co.

935 Gravier St.

New Orleans, LA 70112

allj@chevron.com

Baine, Mark 

Int'l. Center for Island Tech.

Heriot-Watt University

The Old Academy, Stromness

Orkney Islands, KW163AW

ioemspb@icit.civ.hw.ac.uk

Baltz, Donald M

Professor

LSU Coastal Fisheries Inst.

Baton Rouge, LA 70803

dbaltz@lsu.edu

Bass, William 

Bates, Thomas W

Becker, Gregory T

Principal Environ. Engineer

Becker Engineering Inc.

2386 South Dairy Ashford

Houston, TX 77077

Benfield, Mark 

Coastal Fisheries Inst.

LSU

Baton Rouge, LA 70803

mbenfie@lsu.edu

Benner, Lee 

Oceanographer

MMS

381 Elden St

Herndon, VA 20170

lee.benner@mms.gov

Bennett, Richard 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Biggs, Douglas C

Professor

Texas A&M University

Dept of Oceanography

College Station, TX 77843-3146

dbiggs@ocean.tamu.edu

Blandon, Ivonne R

Boatman, Mary 

MMS

1201 Elmwood Prk Blvd, MS 5433

New Orleans, LA 70123

mary.boatman@mms.gov

Boland, Greg 

Biologist

MMS

2164 Champions Dr

La Place, LA 70068

gregory.boland@mms.gov

Bradley, Marcus 

Research Associate

LUMCON

8124 Hwy 56

Chauvin, LA 70344

mbradley@lumcon.edu

Brewer, Gary 

Biologist

USGS Bio. Resources

1700 Leetown Rd

Kearneysville, WV 25430

gary_brewer@usgs.gov
666

Bull, David 

Audubon Institute

1 Canal St

New Orleans, LA 70118

dlbull@compuserve.com

Burgess, George H

Burkhard, Elizabeth 

Marine Biologist

MMS

381 Elden St., MS 4041

Herndon, VA 20170

Elizabeth.Burkhard@mms.gov

Chesney, Edward 

Associate Professor

LUMCON

8124 Hwy 56

Chauvin, LA 70344

echesney@lumcon.edu

Chew, Dennis 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Childs, Susan 

Christopher, Joe 

Chief, Environmental Assessment Sec

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

joseph.christopher@mms.gov

Codina, Caron 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

caron.codina@mms.gov

Contreras, Suzanne 

Marine Biologist

Texas General Land Office

P.O. Box 12873

Austin, TX 78711-2873

suzanne.contreras@glo.state.tx.us

Costa-Pierce, Barry A

Director

MS-AL Sea Grant Consortium

P.O. Box 7000

703 East Beach Drive

Ocean Springs, MS 39566-7000

b.costapierce@usm.edu

Crabtree, Roy 

Fishery Administrator

NOAA/NMFS, SE Regional Office

9721 Executive Ctr. Dr. North

St. Petersburg, FL 33702-2432

roy.crabtree@noaa.gov

Culbertson, Jan C

Artificial Reef Coordinator

Texas Parks & Wildlife

17629 El Camino Real #175

Houston, TX 77058

jan.culbertson@tpwd.state.tx.us

Current, Carole L

Physical Oceanograph er

MMS

1201 Elmwood Prk Blvd, MS 5433

New Orleans, LA 70123

carole.current@mms.gov

Dauterive, Les 

Sr. Environmental Scientist

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

lester.dauterive@mms.gov
667

David, Andrew 

NMFS

3500 Dellwood Beach Rd

Panama City, FL 32408

david@bio.fsu.edu

DeBose, Jennifer 

Research Assistant

Flower Garden Banks

National Marine Sanctuary

216 W 26th St #104

Bryan, TX 77803

jennifer.debose@noaa.gov

Dennis, George 

Research Fishery Biologist

USGS

7920 NW 71st St

Gainesville, FL 32653

george_dennis@usgs.gov

Dokken, Quenton 

Texas A&M - Corpus Christi

Center for Coastal Studies

6300 Ocean Dr

Corpus Christi, TX 78412

Dorf, Barbara 

Natural Resource Specialist

Texas P&W Coastal Fisheries Div.

702 Navigation Circle

Rockport, TX 78382

barbara.dorf@tpwd.state.tx.us

Dorhauer III, Charles 

Bonnabel High School

4508 Laudun St

Metairie, LA 70006

Dorsett, Chris 

Program Director - Fisheries

Gulf Restoration Network

P.O. Box 2245

New Orleans, LA 70176

cdgrn@igc.org

Dougall, Dave 

HSE Mgr

AGIP Petroleum Co. Inc.

1201 Louisiana, Suite 3500

Houston, TX 77002

david.dougall@agippetroleum.agip.it

Dowdy, Danielle 

REEF Field Station of NWFL

2521 Maureen Ln

Meraux, LA 70075

reefnwfl@aol.com

Drass, D. M. 

Edwards, Randy E

USGS-BRD/JC

600 Fourth St. S.

St. Petersburg, FL 33701-4846

redwards@usgs.gov

Eve, Hammond 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Fagot, Caryl 

Staff Assistant, MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

caryl.fagot@mms.gov

Fletcher, Kristen M

Director

MS-AL Sea Grant Legal Prgm.

518 Law Center

University, MS 38677

kfletch@olemiss.edu

Franks, Jim 

Fisheries Biologist

USM-Institute of Marine Sciences

P.O. Box 7000

Ocean Springs, MS 39566

jim.franks@usm.edu
668

Furman, Carol 

Research Associate

Auburn University

Marine Fish Laboratory

8300 State Hwy 104

Fairhope, AL 36532

cfurman@acesag.auburn.edu

Gallaway, Benny 

Ecological Research Assoc.

1410 Cavitt St

Bryan, TX 77801

cole_johnson@msn.com

Gitschlag, Gregg 

NOAA/NMFS

4700 Avenue U

Galveston, TX 77551

gregg.gitschlag@noaa.gov

Goeke, Gary 

Chief, Eastern Gulf Info. Office

MMS

41 N. Jefferson #300

Pensacola, FL 32501

ggoeke@networktel.net

Gregg, Kurtis 

Environmental Specialist

Florida Dept of Environ. Protection

3900 Commonwealth Blvd, MS 47

Tallahassee, FL 32399-3000

kurtis.gregg@dep.state.fl.us

Hanisko, David 

Research Fisheries Biologist

NMFS\Johnson Controls

3209 Frederic St.

Pascagoula, MS 39567

dhanisko@triton.pas.nmfs.gov

Harmon, David J

LSU Coastal Fisheries Inst.

CCEER Wetlands Bldg

Baton Rouge, LA 70803

Heath, James W

Hernandez, Frank J

Graduate Student

LSU Coastal Fisheries Inst.

CCEER Wetlands Bldg

Baton Rouge, LA 70803-7053

fhernan@lsu.edu

Hickerson, Emma 

Research Coordinator

Flower Garden Banks

National Marine Sanctuary

216 W 26th, St #104

Bryan, TX 77803

ema.hickerson@noaa.gov

Hiett, Robert 

Quan Tech, Inc.

Holder Jr., Samuel 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

samuel_holder@mms.gov

Horst, Jerald 

Sea Grant Extension Prgm

1855 Ames Blvd

Marrero, LA 70072

jhorst@agctr.lsu.edu

Howe, Jeffrey 

Research Associate

Auburn Univ. Research Ctr.

4170 Commanders Drive

Mobile, AL 36615

jchowe132@aol.com

Ingram, Jr., G. Walter 

University of South Alabama

Dept of Marine Sciences

Mobile, AL 36688-0002

wingram@gulftel.com
669

Johnston, James B

Supervisory General Biologist

NWRC

700 Cajundome Blvd

Lafayette, LA 70506

jimmy_johnston@usgs.gov

Kasprzak, Rick 

LA DWF

P.O. Box 98000

Baton Rouge, LA 70898

Kay, Melissa 

Geoscience Specialist

LA DNR

UNO Box 1102

New Orleans, LA 70148

melissak@dnr.state.la.us

Keenan, Sean 

Grad Assist

LSU Coastal Fisheries Inst.

218 Wetlands Resource Bldg

Baton Rouge, LA 70803

skeenan@lsu.edu

Kemmerer, Andrew J

Director

Office of Habitat Conservation

1315 EW Hwy, Room 15147

Silver Spring, MD 20910

andy.kemmerer@noaa.gov

Kenny, Jan 

Offshore Coordinator

DEMEX

401 Whitney Ave, Suite 412

Gretna, LA 70056

demex-nola@msn.com

Kenny, John J

DEMEX

401 Whitney Ave Suite 412

Gretna, LA 70056

demex_nola@usa.com

King, Tim L

USGS Bio. Resources

Leetown Science Center

1700 Leetown Rd

Kearneysville, WV 25430

tim_king@usgs.gov

Koenig, Christopher C

Institute for Fishery Resource Ecology

Florida State Univ.

Dept of Biological Sciences

Tallahassee, FL 32306-1100

koenig@bio.fsu.edu

Landry, Connie 

Procurement Coordinator

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

connie.landry@mms.gov

Lang, William 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Lanich, Troy 

USCG

8930 Ocean Drive

Corpus Christi, TX 78419

Lee, J. Dobbs 

Logistics Manager

Barry A. Vittor & Assc. Inc.

8060 Cottage Hill Rd

Mobile, AL 36695

dlee@bvaenviro.com

Lindquist, David 

Research Associate

LSU Coastal Fisheries Inst.

204 Wetland Resources Bldg

Baton Rouge, LA 70803

davlind@aol.com
670

Link, Jason S

NOAA/NMFS

166 Water St

Woods Hole, MA 02543

Jason.Link@noaa.gov

Locke, Stephen 

Grad Student

UNO Estuarine Research Lab

Lakefront Campus

New Orleans, LA 70148

slocke@uno.edu

Lopez, John 

University of New Orleans

387 Carr Dr

Slidell, LA 70458

Lugo-Fernandez, Alexis 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Lukens, Ronald 

Gulf States Marine Fisheries Comm.

2404 Government Street

Ocean Springs, MS 39564

rlukens@gsmfc.org

Lyczkowski-Shultz, Joanne 

Research Fisheries Biologist

NMFS\Johnson Controls

3209 Frederic St.

Pascagoula, MS 39567

jshultz@triton.pas.nmfs.gov

Maher, Tom 

Environmental Specialist

Florida Fish & Wildlife Cons. Comm.

620 South Meridian St

Box MF-MFM

Tallahassee, FL 32399-1600

mahert@gfc.state.fl.us

Marano Briggs, Kay 

Fisheries Biologist

MMS

381 Elden Street, MS 4042

Herndon, VA 20170

kay.briggs@mms.gov

McCawley, Jessica 

Dauphin Island Sea Lab

101 Bienville Blvd.

Dauphin Island, AL 36258

jrmccawley@aol.com

McIlwain, Tom 

NOAA/NMFS

3209 Frederic St

Pascagoula, MS 39567

tom.mcllwain@noaa.gov

McManus, Roger 

Sr. Advisor for Oceans

MMS

1849 C Street NW, MS 6635

Washington, DC 20240

Meyer, Thomas 

Physical Scientist

MMS

1201 Elmwood Park Blvd

New Orleans, LA 70123-2394

tom.meyer@mms.gov

Miget, Russell J

Environmental Quality Specialist

Texas Sea Grant Program

6300 Ocean Dr NRC 2800

Corpus Christi, TX 78412

rmiget@falcon.tamucc.edu

Miller, Mark W

Research Specialist

LSU Coastal Studies Inst.

3rd Floor Old Geology Bldg

Baton Rouge, LA 70803

mmill16@lsu.edu
671

Milon, J. Walter 

Moran, David 

Environmental Scientist

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Morin, Michelle 

Geographer

MMS

1701 40th St

Kenner, LA 70065

michelle.morin@mms.gov

Nichols, Scott 

Director MS Labs

NMFS

P.O. Drawer 1207

Pascagoula, MS 39568-1207

scott.nichols@noaa.gov

Nieland, David L

Research Associate V

LSU Coastal Fisheries Inst.

CCEER Wetlands Bldg

Baton Rouge, LA 70803-7053

dniela@lsu.edu

O'Connell, Martin 

Post-Doctoral Researcher

University of New Orleans

Dept of Biological Sciences

New Orleans, LA 70148

moconnel@uno.edu

Osburn, Hal 

TPWD- Coastal Fisheries

4200 Smith School Rd

Austin, TX 78744

hal.osburn@tpwd.state.tx.us

Ouzts, Allyson 

Auburn University

13430 County Rd #1

Fairhope, AL 36532

acouzts@hotmail.com

Patterson, William 

Peter, D.

Peuler, Elizabeth 

Supervisor, Physical Sci Unit

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

elizabeth.peuler@mms.gov

Pierce, Aaron 

LSU

Dept of Oceanography and Coastal Studies

Baton Rouge, LA 70803

glis70@aol.com

Piko, Amy 

Auburn University

12 N. Jackson St, Apt B

Mobile, AL 36602

apiko@hotmail.com

Plunket, John 

Research Associate II

LSU Coastal Fisheries Inst.

204 Wetland Resources Bldg

Baton Rouge, LA 70803

jtplunket@aol.com

Rademacher, Kevin R

Research Fishery Biologist

National Marine Fisheries Service

P.O. Drawer 1207

Pascagoula, MS 39568-1207

krademac@triton.pas.nmfs.gov
672

Ray, James P

Equilon Enterprises LLC

3333 Highway 6 South

Houston, TX 77082-3101

jpray@equilon.com

Reggio, Jr., Villere 

Outdoor Recreation Planner

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

villere.reggio@mms.gov

Ressler, Patrick H

Graduate Assistant

Texas A&M University

Dept. of Oceanography

3146 TAMU

College Station, TX 77843-3146

pressler@ocean.tamu.edu

Rigaud, Christopher 

Grad Research Assist

Texas A&M University

6300 Ocean Dr

Corpus Christi, TX 78412

abysmalchris@hotmail.com

Roden, Carol 

NMFS

3209 Frederic St

Pascagoula, MS 39567

croden@triton.pas.nmfs.gov

Rogers, Robert 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Roscigno, Pat 

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

Rowe, Gil 

Professor

Texas A&M University

MS 3146 TAMU

College Station, TX 77843

growe@ocean.tamu.edu

Sammarco, Paul W

Professor

LUMCON

8124 Hwy 56

Chauvin, LA 70344

psammarco@lumcon.edu

Scanlon, Kathryn M

U.S. Geological Survey

384 Woods Hole Rd

Woods Hole, MA 02543

kscanlon@usgs.gov

Scarborough Bull, Ann 

U.S. Fish & Wildlife Service

2493 Portola Rd, Suite B

Ventura, CA 93003

ann_s_bull@r1.fws.gov

Schexnayder, Mark 

Marine Fisheries Agent

LSU Extension/Sea Grant

1855 Ames Blvd

Marrero, LA 70072

mschexnayder@agctr.lsu.edu

Shaw, Richard F

Director

LSU Coastal Fisheries Inst.

CCEER Wetlands Bldg

Baton Rouge, LA 70803-7053

rshaw@unix1.sncc.lsu.edu

Shipp, Robert 

University of South Alabama

Dept of Marine Sciences

Mobile, AL 36688-0002

rshipp@jaguar1.usouthal.edu
673

Snyder, David B

Marine Biologist

Continental Shelf Assoc. Inc.

759 Parkway Street

Jupiter, FL 33477

dsnyder@conshelf.com

Stanley, David 

Fisheries/Acoustic Specialist

Beak International

14 Abacus Rd

Brampton, ON L6T 5B7

dstanley@beak.com

Stanley, Louise 

26 Hammell

Tottenham, L0G 1W0

Stead, Mark 

LUMCON

104 Dr. Hugh St Martin Drive

Chauvin, LA 70344

mstead@lsu.edu

Sulak, Ken 

Research Fish Biologist

U.S. Geological Project

Florida Caribbean Science Ctr.

7920 NW 71st St

Gainesville, FL 32653

ken-sulak@usgs.gov

Szedlmayer, Stephen T

Associate Professor

Auburn University

Marine Fish Laboratory

8300 State Hwy 104

Fairhope, AL 36532

sszedlma@acesag.auburn.edu

Taylor, Marilyn 

Auburn University

2200 East Bay Drive, #50

Daphne, AL 36526

mytmazz@aol.com

Tomeny, Steve 

P.O. Box 659

Golden Meadow, LA 70357

Topolski, Marek F

Research Assistant

Auburn University

Dept. of Fisheries

203 Swingle Hall

Auburn, AL 36849-5419

tpolmf@acesag.auburn.edu

Tsoflias, Sarah L

Physical Scientist

MMS

1201 Elmwood Prk Blvd

New Orleans, LA 70123

sarah.tsoflias

Turpin, Robert 

Chief

Escambia County Marine Resources

Pensacola, FL 32534

Vigil, Debra 

MMS

1201 Elmwood Prk Blvd, MS 5431

New Orleans, LA 70123

debra_vigil@mms.gov

Ward, Rocky 

Genetics Program Director

Texas Parks & Wildlife

HC02 Box 385

Palacios, TX 77465

rocky.ward@tpwd.state.tx.us

Wilson, Charles 

LSU Coastal Fisheries Inst.

Dept of Oceanography

Baton Rouge, LA 70803

cwilson@lsu.edu
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.