U.S. Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 

OCS Study 

MMS 2005-066 

Proceedings: 

Twenty-Third Gulf of Mexico 

Information Transfer Meeting 

January 2005 

Editors 

Melanie McKay 

Copy Editor 

Judith Nides 

Production 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

December 2005 
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. and J. Nides, eds. 2005. Proceedings: Twenty-third Gulf of Mexico information 

transfer meeting, January 2005. U.S. Dept. of the Interior, Minerals Management Service, 

Gulf of Mexico OCS Region, New Orleans, La. OCS Study MMS 2005-066. 612 pp. 
v 

TABLE OF CONTENTS 

Page

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

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

ACKNOWLEDGMENTS ........................................................................................................... xxi 

INTRODUCTION .....................................................................................................................xxiii 

SESSION 1A ENVIRONMENTAL FATES AND EFFECTS OF DISCHARGES..................... 1 

Co-Chairs: Margaret C. Metcalf, Minerals Management Service 

Jill Leale, Minerals Management Service 

SESSION 1B NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT 

AND BENTHIC ECOLOGY STUDY RESULTS, PART I ........................................................ 25 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

SESSION 1C OFFSHORE OIL ORAL HISTORY PROJECT .................................................. 51 

Chair: Harry Luton, Minerals Management Service 

Co-Chair: Kimberley Cook, Minerals Management Service 

SESSION 2A ACOUSTICS IN THE MARINE ENVIRONMENT ........................................... 81 

Chair: Bill Lang, Minerals Management Service 

Co-Chair: Ron Brinkman, Minerals Management Service 

SESSION 2B NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT 

AND BENTHIC ECOLOGY STUDY RESULTS, PART II..................................................... 147 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

SESSION 2C SOCIOECONOMIC STUDIES.......................................................................... 171 

Chair: Asha Luthra, Minerals Management Service 

Co-Chair: Kristen Strellec, Minerals Management Service 

SESSION 1D EFFECTS OF OIL AND GAS EXPLORATION & DEVELOPMENT AT 

SELECTED CONTINENTAL SLOPE SITES IN THE GULF OF MEXICO, PART I............ 201 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: Margaret C. Metcalf, Minerals Management Service 
vi 

SESSION 1E DEEPWATER TECHNOLOGY ........................................................................ 227 

Chair: Mike Conner, Minerals Management Service 

Co-Chair: Elizabeth Komiskey, Minerals Management Service 

SESSION 1F SPERM WHALE SEISMIC STUDY ................................................................. 253 

Chair: Bill Lang, Minerals Management Service 

Co-Chair: Colleen Benner, Minerals Management Service 

SESSION 2D EFFECTS OF OIL AND GAS EXPLORATION & DEVELOPMENT AT 

SELECTED CONTINENTAL SLOPE SITES IN THE GULF OF MEXICO, PART II .......... 295 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: Margaret C. Metcalf, Minerals Management Service 

SESSION 2E AIR QUALITY ................................................................................................... 309 

Chair: Robert Cameron, Minerals Management Service 

Co-Chair: Richard McNider, University of Alabama Huntsville 

SESSION 2F SPERM WHALE SEISMIC STUDY, PART II.................................................. 377 

Chair: Deborah Epperson, Minerals Management Service 

Co-Chair: Carol Roden, Minerals Management Service 

SESSION 1G PLATFORM ECOLOGY................................................................................... 409 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

SESSION 1H SENSITIVE BIOLOGICAL HABITATS OF THE GULF OF MEXICO: 

WETLANDS TO CORAL REEFS............................................................................................. 447 

Chair: James Sinclair, Minerals Management Service 

Co-Chair: Herb Leedy, Minerals Management Service 

SESSION 1I DEEPWATER PHYSICAL OCEANOGRAPHY INITIATIVE, PART I .......... 477 

Chair: Alexis Lugo-Fernandez, Minerals Management Service 

Co-Chair: Carole Current, Minerals Management Service 

SESSION 2G DEEP GULF OF MEXICO CHEMOSYNTHETIC COMMUNITIES: 

CURRENT KNOWLEDGE FOR SITES BELOW 1,000 METERS......................................... 499 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

SESSION 2H LOUISIANA OIL SPILL RESEARCH AND DEVELOPMENT 

PROGRAM (OSRADP) ............................................................................................................. 525 

Chair: Rusty Wright, Minerals Management Service 

Co-Chair: Don Davis, Louisiana State University 
vii 

SESSION 2I DEEPWATER PHYSICAL OCEANOGRAPHY INITIATIVE, PART II......... 547 

Chair: Alexis Lugo-Fernandez, Minerals Management Service 

Co-Chair: Carole Current, Minerals Management Service 

INDEX ........................................................................................................................................ 579 

ATTENDEES ............................................................................................................................. 583 
ix 

LIST OF FIGURES 

Page

Figure 1A.1. Solubility of barite—static test.................................................................................. 6 

Figure 1A.2. Solubility of trace metals—static test........................................................................ 7 

Figure 1A.3. Solubility of trace metals—static test (continued). ................................................... 7 

Figure 1A.4. Amounts of barium lost from the solid phase in ug/g. (Results provided by 

John Trefry, FIT.) ................................................................................................................... 8 

Figure 1A.5. Amounts of cadmium lost from the solid phase in ug/g. (Results provided by 

John Trefry, FIT.) ................................................................................................................... 8 

Figure 1A.6. Amounts of zinc lost from the solid phase in ug/g. (Results provided by John 

Trefry, FIT.)............................................................................................................................ 9 

Figure 1A.7. Dissolution of barite after burial (porewater)............................................................ 9 

Figure 1A.8. Concentrations of ester and olefin SBF surrogates during incubation in MP299 

near field sediment at 4°C and at atmospheric pressure or pressurized to 97 psi hydraulic 

pressure. ................................................................................................................................ 12 

Figure 1A.9. Concentrations of sulfate in control and spiked GC112 near field sediments 

incubated at 4°C and at atmospheric pressure or pressurized to 97 psi hydraulic pressure.. 13 

Figure 1A.10. Toxic unit results of experiments with S. knabeni combining a mixture of 

metals with phenanthrene. .................................................................................................... 22 

Figure 1A.11. Toxic unit results of experiments with S. knabeni combining Cd with 

phenanthrene. Results suggest a greater-than-additive effect............................................... 22 

Figure 1B.1. Selected station data showing salinity versus density (top) and depth (bottom)..... 31 

Figure 1B.2. Record-length mean speed (solid) and plus and minus one standard deviation 

(dashed) of currents measured using a bottom-moored downward-looking 300-kHz 

ADCP during four deployments in 2001. ............................................................................. 32 

Figure 1B.3. Contours of sea surface height from satellite altimeter data and near-surface 

velocity vectors from shipboard ADCP during August 2002............................................... 34 
x 

Figure 1B.4. Top panel: Three year climatology of biweekly composited SeaWiFS ocean 

color data 1998–2000 at the nine DGoMB stations in water depth > 2000 m in the 

western Gulf of Mexico. Bottom panel: The average annual cycle of chlorophyll at 

these western Gulf of Mexico deepwater stations, illustrating the typical annual range 

from summertime lows of about 0.1 mg m-3 to November–February highs of about 

0.3 mg m-3. ............................................................................................................................ 38 

Figure 1B.5. Three year climatology of biweekly averaged SeaWiFS ocean color data 1998–

2000 at the DGoMB stations east of 91oW in the eastern Gulf of Mexico........................... 39 

Figure 2A.1. Chart of Northern Gulf of Mexico indicating the position of the EARS buoys 

near Green’s Canyon............................................................................................................. 85 

Figure 2A.2. Illustration of the mooring showing the two co-located EARS buoys.................... 85 

Figure 2A.3. Illustration of the tracks of the M/V KONDOR in relation to the EARS buoy 

position.................................................................................................................................. 86 

Figure 2A.4. Plots of data from Shot 248 on the 0m offset line near the point of closest 

approach to the EARS buoy illustrating the shot before and after calibrations have 

been applied. ......................................................................................................................... 87 

Figure 2A.5. Maximum pressures in dB re 1 μPa versus shot number for each of the five 

lines....................................................................................................................................... 88 

Figure 2A.6. Voltage versus time for the shot of the closest point of approach for Line 1.......... 89 

Figure 2A.7. Sound Exposure Level in dB sec re 1 μPa2 sec for a 200 ms sliding window 

for the shot of the closest point of approach for Line 1 as shown in Figure 2A.6................ 89 

Figure 2A.8. Maximum Sound Exposure Levels over a 200 ms window for each shot on 

Lines 1, 2, and 3, in dB sec re 1 μPa2

 sec. ............................................................................ 90 

Figure 2A.9. Sound pressure density level spectrogram of airgun shots, but with shot number 

on the horizontal axis rather than time.................................................................................. 90 

Figure 2A.10. Expected arrival time behavior for direct, reflected, and refracted energy. ...........92 

Figure 2A.11. Flattening of second arrival at large offsets, indicating refracted arrival 

overtaking reflected energy................................................................................................... 92 

Figure 2A.12. Difference between second and first arrival vs. horizontal range (offset)............. 93 

Figure 2A.13. The propagation modeling workflow. ................................................................... 94 

Figure 2A.14. Array-buoy coordination system. .......................................................................... 95 
xi 

Figure 2A.15. Waveguide model.................................................................................................. 95 

Figure 2A.16. Green’s function generated by RAM..................................................................... 96 

Figure 2A.17. Model output versus experimental data................................................................. 97 

Figure2A.18. Chart of storm system tracks during the summer of 2001 and 2002 relative 

to the EARS deployment site and the NDBC weather buoys............................................. 102 

Figure 2A.19. Illustration of the ambient noise results for EARS 1 during Hurricane Lili........ 103 

Figure 2A.20. Illustration of the ambient noise results for EARS 1 during Tropical Storm 

Isidore. ................................................................................................................................ 104 

Figure 2A.21. Satellite image of Tropical Storm Isidore illustrating banding. .......................... 105 

Figure 2A.22. Spectrogram of the ambient noise results for EARS 1 during Tropical Storm 

Isidore illustrating effects of banding. ................................................................................ 106 

Figure 2A.23. Illustration of the ambient noise results for EARS 1 during Tropical Storm 

Isidore (black) compared to Wenz curves (blue) and rain curves (red).............................. 107 

Figure 2A.24. Map shows whale symbols at sperm whale sightings and black dots for oil 

platforms. ............................................................................................................................ 112 

Figure 2A.25. 800m mooring data extracted from a 60sec segment beginning at Julian 

Day 213, Zulu 0 hr, 9 min, 37 sec. Figures. 2A.25 (a) – (d) each give four seconds 

of data.................................................................................................................................. 114 

Figure 2A.26. Voltage amplitude versus time plots for all the clicks in one coda (a), and in 

another coda (b). ..................................................................................................................115 

Figure 2A.27. Each graph is an overplot of the Fourier magnitude spectra for all the clicks 

in one coda. ......................................................................................................................... 116 

Figure 1A.28. Three pairs of overplotted spectra of clicks within a coda, one in each of 

(a), (b), and (c). ................................................................................................................... 117 

Figure 2A.29. Temporal structure of arrivals on the 740 m deep EARS buoy for the mammal 

depth of 50 m and the ranges of 510, 1020, 2041, 5000 m from the receiving buoy. ........ 118 

Figure 2A.30. Temporal structure of arrivals on the 740 m deep EARS buoy for the 

mammal depth of 400 m and the ranges of 510, 1020, 2041, 5000 m from the 

receiving buoy..................................................................................................................... 119 
xii 

Figure 2A.31. 1-second fragment of the LADC data rich in the sperm whale phonations 

with the 4-msec window spectrograms on the right for all three buoys (the 1000 m 

contour buoy is on the top). ................................................................................................ 121 

Figure 2A.32. Similarity analysis results for: (a) echolocation clicks, (b) communication 

signals. ................................................................................................................................ 122 

Figure 2A.33. SOM example...................................................................................................... 123 

Figure 2A.34. Top: Time series data for one minute. Middle and Bottom: Spectrogram 

of data.................................................................................................................................. 124 

Figure 2A.35. Four representative codas. ................................................................................... 125 

Figure 2A.36. Top: 43 representative clicks, 1 per coda. Middle: FFT amplitude, and 

Bottom: Wavelet transform, of data shown at top. ............................................................. 126 

Figure 2A.37. SOM classes using time series data..................................................................... 127 

Figure 2A.38. SOM classes using FFT amplitude data. ............................................................. 128 

Figure 2A.39. SOM classes using db4 wavelet transform data. ................................................. 128 

Figure 2A.40. A sample of data with a click embedded in a slowly varying background. ........ 131 

Figure 2A.41. The discrete derivative of the data in Figure 2A.40, the first step in the 

automated click detection algorithm................................................................................... 132 

Figure 2A.42. EARS Buoy shot line geometry.......................................................................... 138 

Figure 2A.43. Hydrophone geometry. ........................................................................................ 139 

Figure 2A.44. An emission angle of 70o is shown in Figure 2A.44a. Figure 2A.44b 

represents a ray diagram where the white ray creates the strong peak, and the two 

red rays create the trough.................................................................................................... 140 

Figure 2A.45. The white ray represents the first break arrival, and the red rays represent 

the pulse from the air-gun array traversing the water column, reflecting off the 

seafloor, and being received at the hydrophone.................................................................. 140 

Figure 2A.46. Time domain shot record 736 meters away (mostly above) from 

hydrophone. ........................................................................................................................ 141 

Figure 2A.47. Sound pressure/Hz versus frequency................................................................... 141 

Figure 2A.48. Sound pressure density spectrum. ....................................................................... 142 
xiii 

Figure 2A.49. Sound pressure density spectrogram. .................................................................. 143 

Figure 2B.1. Biplot of the canonical correspondence analysis with the distribution patterns 

of the mollusk species by depth and geographic region. .................................................... 162 

Figure 2B.2. The area of study and the sampling stations located at 3,000m or more in the 

Sigsbee abyssal plain. ......................................................................................................... 164 

Figure 1D.1. Location map showing major lease areas of the northern Gulf of Mexico 

continental slope and specific sites addressed in this study................................................ 207 

Figure 1D.2. Sampling sites in the Gulf of Mexico with background sedimentation rates 

in cm yr-1............................................................................................................................. 213 

Figure 1D.3. Concentrations of Ba (markers show means and lines show standard deviations) 

 in sediments at nearfield (NF) and farfield (FF) stations for pre-exploration and/or 

post-exploration surveys at sites VK 916, GB 516, GB 602 and MC 292 (notation in 

parentheses after site identifies cruise when sampling occurred)....................................... 214 

Figure 1D.4. Vertical profiles for dissolved oxygen, pH and redox potential (Eh) for 

(a) farfield (FF) and (b) nearfield (NF) sediments at site GB 516 where drilling 

discharges had occurred...................................................................................................... 215 

Figure 1D.5. Means and standard deviations for integrated amounts of dissolved oxygen 

and levels of total organic carbon (TOC) in sediments from site VK 916 for nearfield 

(NF), discretionary (DS) and farfield (FF) stations during pre- (cruise 1B) and postdevelopment (cruise 3B) sampling. .....................................................................................216 

Figure 1E.1. Subsea HIPPS manifold system............................................................................. 235 

Figure 1E.2. Study scope. ........................................................................................................... 241 

Figure 1E.3. Gas export scenarios. ............................................................................................. 242 

Figure 1E.4. FPSO with gas handling process............................................................................ 242 

Figure 1E.5. Assessment focus. .................................................................................................. 243 

Figure 1E.6. Gas-handling process steps. ................................................................................... 243 

Figure 1F.1. Comparison of the frequencies in 5 km classes of the observed distribution of 

distances (<25 km) between whales and active seismic vessels with expected values 

assuming a random distribution (n=12). ............................................................................. 269 

Figure 1F.2. Dive profile of a sperm whale from the Gulf of Mexico. ...................................... 274 

Figure 1F.3. Acoustic exposure cycles. ...................................................................................... 278 
xiv 

Figure 1F.4. (A) Waveform of the first arrival (direct) and a bottom bounce/bottom ducted 

second arrival as received by a sperm whale at 30 meters depth. (B) Spectrogram of 

the waveform of A. ............................................................................................................. 279 

Figure 1F.5. Airgun signal in the 2002 D-tags data.................................................................... 282 

Figure 1F.6. A simple energy model of the sperm whale showing energy input from food, 

and various energy outputs for locomotion (green), basal metabolism (blue), and 

energy for growth and reproduction which are critical for maintenance of the health 

of an animal population (red).............................................................................................. 285 

Figure 1F.7. Two error types. ..................................................................................................... 290 

Figure 2D.1. Cruise 1 sampling sites.......................................................................................... 307 

Figure 2E.1. Comparison of emissions from platform, oil-related non-platform, and other 

offshore sources operating in the Gulf of Mexico for 2000................................................ 321 

Figure 2E.2. Coastal areas of interest for assessment of on-shore impacts................................ 322 

Figure 2E.3. GCOS/WFOS UAM-V5 modeling domain used for the MMS OCS 2000 

modeling analysis................................................................................................................ 322 

Figure 2E.4. Simulated maximum hourly ozone impacts (ppb) from OCS oil-related 

emission sources for 8 August 1999. .................................................................................. 323 

Figure 2E.5. Simulated maximum eight-hour average ozone impacts (ppb) from OCS 

 oil-related emission sources for 8 August 1999 for grid cells with simulated eighthour concentrations in the base case greater than 85 ppb (preliminary draft platform 

VOC inventory (409 tpd) in lieu of final platform inventory (163 tpd).)........................... 325 

Figure 2E.6. Comparison of simulated eight-hour ozone exceedance exposure (ppb) for 

grid c, the offshore portion of grid c, and the onshore portion of grid c, comparing 

the base case with the OCS zero-out sensitivity simulations (3–8 August 1999). ............. 325 

Figure 2E.7. (a) Max eight-hour ozone apportioned by NOX emissions (ppb) for 7 August 

1999. Showing contributions from onshore and offshore emissions. (b) Max eighthour ozone apportioned by VOC emissions (ppb) for 7 August 1999. Showing 

contributions from onshore and offshore emissions. .......................................................... 327 

Figure 2E.8. (a) Max eight-hour ozone apportioned by NOX emissions (ppb) for 7 August 

showing contributions from onshore and offshore emissions (Scenario MT-2). (b) 

Max eight-hour ozone apportioned by VOC emissions (ppb) showing contributions 

from onshore and offshore emission (Scenario MT-2)....................................................... 328 

Figure 2E.9. Simulated contributions (ppb) from each offshore source category to the 

total offshore contribution to the daily average maximum eight-hour ozone 
xv 

concentrations in the offshore area of grid 2 from sources located in offshore areas 

of the Gulf Coast (OPTM Scenario MT-2 for 3–8 August 1999). ..................................... 329 

Figure 2E.10. CAMx nested grid modeling domain and layer structures for the TexAQS 22 

August to 6 September 2000 ozone episode in the Houston area....................................... 333 

Figure 2E.11. Episode maximum eight-hour ozone impacts of the 2000 GWEI for the 

12-km grid........................................................................................................................... 334 

Figure 2E.12. 158 m level wind rose for the period of 15 October through 16 November 

2004 as recorded by the LUMCON profiler....................................................................... 338 

Figure 2E.13. LUMCON radar profiler site................................................................................ 349 

Figure 2E.14. Example graphical NPN wind display from LUMCON profiler......................... 350 

Figure 2E.15. Planned NAS Pensacola profiler site configuration............................................. 351 

Figure 2F.1. Root Mean Square (rms) displacement for the 12 groups of female immatures 

that were followed for more than 10 hours (11 to 50 hours). ............................................. 386 

Figure 2F.2. Illustration of 2004 3-D deployment off R/V Gyre, using a tandem array 

specifically built for the project. Top: side view of tandem array during S-tag 

deployment. Bottom: View of S-tag array deployment from above, showing how 

tandem and ecologic array were deployed in parallel, which permits bearings of 

sounds to be determined without a port/starboard ambiguity............................................. 396 

Figure 2F.3. Spectrograms of data collected during 2004 3-D tracking experiment, as 

viewed with a MATLAB graphical user interface.............................................................. 397 

Figure 2F.4. Acoustic track of diving sperm whale on 16 June 2004: Top: Whale depth vs. 

local time using “A,” “B,” and single-phone tracking algorithms; Middle: Whale range 

vs. time for same algorithms; Bottom: Ship course and speed. Note divergence of “B” 

(black) algorithm once ship turns. ...................................................................................... 398 

Figure 2F.5. Correspondence axes 1 and 2 for 23 trawls and 116 taxa. ..................................... 406 

Figure 2F.6. Correspondence axes 1 and 2 for 3 trawls (0–400 meters) and 55 taxa................. 407 

Figure 1G.1. Map showing the starting and ending points for the seven red snapper 

that were recaptured at locations other than their release sites........................................... 412 

Figure 1G.2. Predicted probability of presence at release location for both native and 

relocated red snapper. ......................................................................................................... 412 

Figure 1G.3. Periodogram for South Timbalier 135-M showing the period and the power 

of the sine functions describing red snapper movement away from the platform.............. 413 
xvi 

Figure 1G.4. Predicted distributions of adult yellowfin tuna in the study area from January 

through December............................................................................................................... 420 

Figure 1G.5. Predicted distributions of larval yellowfin tuna in the study area during May, 

June, and September. .......................................................................................................... 422 

Figure 1G.6. Comparison of the mean differences of the 17 elements between oil and gas 

platforms and artificial reefs in Louisiana. ......................................................................... 426 

Figure 1H.1. Flower Garden Banks Region of the Northwestern Gulf of Mexico......................451 

Figure 1H.2. Habitat Map of the Flower Garden Banks Region, showing distribution of 

hard-bottom and patch reefs, as interpreted from bathymetry and acoustic backscatter 

data.......................................................................................................................................452 

Figure 1H.3. Coral Reef Cap of the West Flower Garden Bank, interpolated at 0.5m 

resolution..............................................................................................................................453 

Figure 1H.4. Coral Reef Cap of the East Flower Garden Bank, interpolated at 0.5m 

resolution..............................................................................................................................454 

Figure 1I.1. General study area for NW Gulf Study – American Sector.................................... 480 

Figure 1I.2. Placement of American Sector Moorings (filled red circles), and PIES (filled 

green triangles).................................................................................................................... 481 

Figure 1I.3. Eddy Zapp with a frontal eddy/filament within the study area............................... 483 

Figure 1I.4. Historical current measurement in eastern GOM vs. study area location............... 484 

Figure 1I.5. Mooring (M1–M4) and PIES (P1–P7) deployment locations................................. 486 

Figure 1I.6. Bathymetric contour map of the Sigsbee Escarpment and the location of the 

LSU mooring from 31 July 2001 to 2 June 2002. .............................................................. 492 

Figure 1I.7. Graphic showing stick vectors of low-pass filtered currents at selected depths 

from 31 July 2001 to 2 June 2002....................................................................................... 494 

Figure 1I.8. Color enhanced GOES SST composite imagery superimposed with contours 

of SSH data for (top panel) 16 April 2002 and (bottom panel) 15 March 2002................. 496 

Figure 2G.1. Compilation of satellite remote sensing targets indicating robust oil seepage 

(solid dots) and sites where seafloor collections have confirmed the occurrence of 

chemosynthetic fauna (circles). .......................................................................................... 502 
xvii 

Figure 2G.2. Dip section across the western coast of Louisiana illustrating the changing 

structure and salt geometrics from onshore to the deep Gulf of Mexico basin floor 

(modified from Peel et al. 1995)......................................................................................... 505 

Figure 2G.3. The area of study in the southwestern Gulf of Mexico. ........................................ 515 

Figure 2G.4. Image of a soft sediment type of habitat with chemosynthetic activity. ............... 517 

Figure 2G.5. Image of a hard substrate rubble with associated chemosynthetic fauna.............. 518 

Figure 2H.1. The Louisiana Oil Spill Database opening screen................................................. 537 

Figure 2H.2. Location of currently active WAVCIS stations along the northern Gulf of 

Mexico. ............................................................................................................................... 544 

Figure 2I.1. 40-hour low pass filtered ADCP and current meter data at each instrument 

on the Deep Gulf Mooring for the period April 2003–June 2004. ..................................... 550 

Figure 2I.2. Vertical profile of current speed (mean and maximum) measured during the 

deployments one and two and deployment three................................................................ 552 

Figure 2I.3. Hourly current meter data at 2,000 m, 3,000 m and 3,200 m on the Deep Gulf 

Mooring in July 2003.......................................................................................................... 552 

Figure 2I.4. Hourly temperature data at 2,000 m in July 2003................................................... 553 

Figure 2I.5. Hourly salinity data at 2,000 m in July 2003. ......................................................... 553 

Figure 2I.6. Hourly temperature measured at 1,500 m during deployments one and two.......... 554 

Figure 2I.7. Hourly temperature measured at 2,000 m during deployment three....................... 554 

Figure 2I.8. Hourly temperature measured at 2,500 m during deployments one and two.......... 555 

Figure 2I.9. Map of mooring positions for the Exploratory, SEBCEP (Industry) and LSU 

programs. ............................................................................................................................ 557 

Figure 2I.10. Contours of 40-HLP mean kinetic energy, overlaid with 40-HLP mean 

velocity vectors, for near bottom current meter data.. ........................................................ 559 

Figure 2I.11. Kinetic energy spectra of 40-HLP currents at selected depths below 1,000 m 

for the tall moorings L3, L5 (LSU) and L4. ....................................................................... 560 

Figure 2I.12. First frequency domain EOF modes shown as amplitude ellipses (red) where 

 the relative phase is given by the arrowhead. .................................................................... 561 

Figure 2I.13. Smoothed Lagrangian RAFOS trajectories for the indicated floats...................... 562 
xviii 

Figure 2I.14. Three arrays of inverted echo sounders equipped with pressure gauges (PIES) 

 have been deployed in the Gulf of Mexico. Western Gulf array deployed October 

2004 with an anticipated recovery August 2005. Central Gulf array deployed March 

2003 and recovered April 2004. Eastern Gulf array deployed December 2004 with an 

anticipated recovery December 2005.................................................................................. 565 

Figure 2I.15. The pressure-recording inverted echo sounder (PIES) is an ocean-bottom 

instrument housed in a single 17” glass sphere containing the controller/data logger, 

acoustic release, and relocation radio/strobe light. ............................................................. 565 

Figure 2I.16. Upper four panels compare PIES-estimated (blue) and directly-measured 

temperatures (red) at the L1 mooring whose location is shown in the bottommost 

panel by the red circle......................................................................................................... 567 

Figure 2I.17. Mapped temperature at 300 dbar shows frontal cyclones along the periphery 

of the Loop Current and Loop Current ring and a small anticyclone generated during 

ring development. ................................................................................................................568 
xix 

LIST OF TABLES 

Page

Table 1A.1. Concentration of elements in barite samples and Gulf of Mexico (GOM) shelf 

sediment, ug/g (ppm) dry weight............................................................................................ 5 

Table 1B.1. Locations, dates, and times of deployment of the moored ADCP............................ 30 

Table 1B.2. Summary of remotely-sensed chlorophyll concentrations, 1998–2000.................... 37 

Table 2A.1. Airgun calibration lines............................................................................................. 84 

Table 2A.2. Average noise levels for bands of TS Isidore compared to calculated rainfall 

amounts............................................................................................................................... 106 

Table 2A.3. Data set number and the class for each of the codas for each of the three 

inputs................................................................................................................................... 129 

Table 2B.1. Mean values of macrofauna abundance, taxa groups, H’ (Shannon-Weiner), 

 and evenness for DGoMB study stations (non-seep) and SETTI stations (seep).............. 156 

Table 2B.2. Number of species/ records of deep sea specimens from the Gulf of Mexico, 

including DGoMB-JSSD cruises, deposited in the Mexican National Collections and 

included in CONABIO database..........................................................................................160 

Table 2C.1. Summary Statistics of Quarterly Macroeconomic and E&P Data, 1977–2000. ..... 189 

Table 2C.2. Decomposition of the variance of Louisiana employment. .................................... 190 

Table 2C.3. Price elasticity of employment ............................................................................... 190 

Table 2C.4. Quantitative estimates of the effects of maximum price ‘shock’ in 2002............... 191 

Table 2C. 5. Changes in per capita personal income and its components, 1969–2000.............. 191 

Table 1D.1. Geophysical surveys. .............................................................................................. 209 

Table 1F.1. 2002-2004 Cruises conducted for and related to the Sperm Whale Seismic 

Study. .................................................................................................................................. 257 

Table 1F.2. Tabulation of the number of occurrences in each distance class for the observed 

data set and the expected number for an area-normalized randomly distributed data set 

(n=12)...................................................................................................................................268 

Table 1F.3. Summary of cruise results. ...................................................................................... 273 
xx 

Table 2D.1. Sediment ATP concentrations (ng g-1 dry wt) for all near-field and far-field 

sites. .................................................................................................................................... 304

Table 2E.1. Gulfwide inventory platform and non-platform emission estimates....................... 314 

Table 2E.2. Breton inventory platform and non-platform emission estimates........................... 314 

Table 2F.1. Results of seismic line starts and ends tests. ........................................................... 380 

Table 2F.2. Results of correspondence analysis runs for selected subsets of data. .................... 405 

Table 1I.1. Statistics of currents at selected depths. ................................................................... 495 

Table 2G.1. Section of a worksheet that shows image identification in the Image field, and 

types of seafloor habitats identified and coded by the presence (1) or absence (0) of the 

feature for a later qualitative analysis. ................................................................................ 516 

Table 2H.1. The 30 variables used in the database..................................................................... 537 
xxi 

ACKNOWLEDGMENTS 

The Minerals Management Service (MMS) thanks all the participants who made this Information 

Transfer Meeting a success. In particular, we thank the speakers for their informative 

presentations. The meeting would not be possible without the team effort of the chairpersons and 

co-chairpersons who are responsible for the agenda. We thank the University of New Orleans 

(UNO) Conference Services for planning and conducting the workshop logistics and the staff at 

the Hilton Hotel for their support efforts and excellent refreshments. In particular, we thank 

Patricia Arteaga of UNO for making the planning process seem effortless. We also thank 

Melanie McKay and Judy Nides for the production of the final product. Finally, we thank the 

support of all those who attended and participated in the discussions for making this truly a 

transfer of information meeting. The MMS Environmental Studies Program funded this 

workshop. 
xxiii 

INTRODUCTION 

Every year for over twenty years, and now every other year, the Information Transfer Meeting 

(ITM) brings together people from all over the country and the world to discuss the various 

topics funded by the Environmental Studies Program and related areas of interest to the Minerals 

Management Service (MMS). As always, the ITM provides a forum where interchange on topics 

of current interest relative to environmental assessments of the offshore oil and gas industry can 

occur. The accomplishments of the MMS Environmental Studies Program for the Gulf of 

Mexico and of other research programs or study projects were presented. The ITM is a place to 

foster an exchange of information of regional interest among scientists, staff members, and 

decision-makers from MMS, other Federal or State governmental agencies, regionally important 

industries, and academia. 

The 23rd ITM focused on several topics from benthic ecology of the deep sea to deepwater 

technology. One highlight this year was the presentation of research funded through the 

Louisiana Oil Spill Research and Development Program. Interesting stories about the pioneers of 

the oil industry were shared along with many old photos. Again, three sessions focused on 

acoustics and marine mammals, particularly the Sperm Whales in the Gulf of Mexico. Physical 

Oceanographers presented their most recent findings of the movement of currents in deepwater 

using various models. The results from the most complete evaluation of deep sea ecology were 

presented. Other sessions focused on air quality, operational discharges, and deepwater 

technology. Once again, the meeting reflected the broad areas of interest to MMS and the 

excellent scientists studying these topics. 

Following are the summaries of the presentations that were given by all the excellent speakers. 
1 

SESSION 1A 

ENVIRONMENTAL FATES AND EFFECTS OF DISCHARGES 

Co-Chairs: Margaret C. Metcalf, Minerals Management Service 

Jill Leale, Minerals Management Service 

MINERALOGIC AND COMPOSITIONAL STUDIES OF BARITE SAMPLES 

James P. McKinley ......................................................................................................................... 3 

BARITE SOLUBILITY AND THE RELEASE OF TRACE COMPONENTS 

TO THE MARINE ENVIRONMENT Eric Crecelius, Brenda K. Lord-Lasorsa, and 

Jill Brandenburger........................................................................................................................... 5 

BIODEGRADATION OF SYNTHETIC-BASED DRILLING FLUIDS Alan H. Nguyen 

and Deborah J. Roberts................................................................................................................. 11 

CHARACTERIZATION OF MICROBIAL POPULATIONS SUBSISTING UPON 

SYNTHETIC-BASED DRILLING FLUIDS Kavita Swaminathan and Deborah J. Roberts..... 15 

UNDERSTANDING THE PROCESSES THAT MAINTAIN THE OXYGEN LEVELS IN 

THE DEEP GULF OF MEXICO Ann E. Jochens ...................................................................... 18 

TOXICOLOGICAL INTERACTIONS BETWEEN METALS AND POLY-NUCLEAR 

AROMATIC HYDROCARBONS IN THE BENTHIC COPEPOD SHIZOPERA KNABENI 

John W. Fleeger, Sidney J. Marlborough, Kevin R. Carman, and Soraya J. Silva....................... 21 
3 

MINERALOGIC AND COMPOSITIONAL STUDIES OF BARITE SAMPLES 

James P. McKinley, Battelle Marine Sciences Laboratory 

Three barite samples of different provenance were studied using several characterization 

methods. The samples were received with the designations FIT-Blend (FIT), High Metal Barite 

(MI-High), and Low Metal Barite (MI-Low), along with compositional data for the elements Cd, 

Cr, Cu, Fe, Hg, Mn, Pb, and Zn. Cu was present at 100–200 ppm, Hg at 0.4–7 ppm, and Pb at 

250–1,400 ppm; the FIT sample consistently included the highest concentrations of these 

elements. Additionally, small samples of the barites were provided that had been acid-leached to 

remove trace-element bearing phases. 

The samples were initially examined as grain mounts by X-ray diffraction (XRD) and scanning 

electron microscopy (SEM) to determine bulk mineralogy and grain sizes. Only barite (BaSO4) 

was observed in XRD patterns. Image analysis of grains scattered on a conductive planchette 

indicated that the grain sizes for the FIT and MI-High samples were similar but that the MI-Low 

samples consisted of smaller grains. Specific equivalent diameters for each sample were FIT, 

5.62 μm; MI-High, 4.75 μm; MI-Low, 1.35 μm. 

The barites were prepared as thin sections by a commercial laboratory and examined using 

electron and X-ray beam instruments. The sample powders were imbedded in epoxy and the 

resultant solid was affixed to a glass slide and ground and polished to a uniform thickness. The 

slides were carbon coated to assure electrical conductivity in the electron beam instruments. 

Sample analysis in the form of compositional imaging used several methods that provided 

complementary information. The general variation in mineral components was imaged in the 

SEM and electron microprobe (EMP) using a backscattered electron (BSE) detector. BSE 

detectors rely on the correlation between the electron backscatter coefficient and the sample’s 

average atomic number to provide an image of atomic number contrast in solid phases. The 

resolution is at a sub-μm spatial scale. Compositional imaging in the EMP with respect to 

individual elements of interest used wavelength-dispersive spectrometers (WDS), tuned 

individually to those elements. The samples were moved under the electron beam and the 

characteristic X-ray flux from the tuned spectrometers was composited into a false-color map for 

each element at μm scale, with a detection limit of approximately 200 ppm. For imaging with a 

lower detection limit, the X-ray microprobe (XMP) capability at the Advanced Photon Source 

was used. The samples again were moved under the beam consisting of focused X-rays at high 

flux. The experiment was conducted in air, using an energy dispersive detector (EDS), which 

detected characteristic fluorescent X-rays. The detection limit was approximately 1 ppm, but the 

spatial resolution was 5–10 μm, and the instrument was insensitive to low-Z elements (e.g., Si, 

S). The energy dispersive detector provided simultaneous collections of elemental abundances. 

Elemental abundance maps from EMP and XMP instruments were overlain on BSE images 

using Photoshop. This procedure allowed the direct identification of individual grains containing 

relatively high concentrations of the elements of interest. Qualitative compositional information 
4 

for single grains was collected using an EDS detector in the scanning electron microscope. In the 

electron beam instruments, this detector can provide compositional information at the μm scale, 

with a detection limit of approximately 1000 ppm; this method is thus ideal for identifying 

minerals that include trace elements detected by more sensitive means. The combined methods 

(in acronyms, SEM, EMP, XMP, EDS, WDS, and BSE!) provided a complementary set of 

detection capabilities to localize and identify the hosts for trace elements, particularly Pb, Hg, 

and Cu. 

The samples included minute, broadly dispersed grains of lead sulfide, and an unidentified Pb 

phase that did not include sulfur or phosphorous. Because the samples were imbedded in an 

organic substrate and carbon coated, the identification of carbonate phases was difficult: the 

unidentified phase may have been a lead carbonate. In the FIT sample, Hg was found within a 

subset of the Pb sulfide grains, along with Cu, and a Sr sulfide was observed. Fe was present in 

all samples, as an oxide and a sulfide. The Fe sulfides were much less abundant in the MI-High 

and MI-Low samples. Also in the MI-High and MI-Low samples, Cu was observed as a sulfide 

without associated Pb. Finally, Cr, present at 7 and 15 ppm, respectively, in the MI-High and 

MI-Low samples, was observed as sub-μm oxide particles in the MI-High sample and as a 

chromium oxide component of Fe-rich, >10 μm lithic fragments in the MI-Low sample. 

The detected trace metals in the barite samples were components of very minor discrete mineral 

phases within the more abundant barite grains. Abundant inclusions of Fe oxides, sulfides, and 

quartz were also observed. 

James P. McKinley joined Battelle in 1987 and is currently a Senior Research Scientist in the 

Environmental Dynamics and Simulation Group. He earned a Ph.D. in geology from the 

University of New Mexico in 1990, an M.S. in geology from the University of New Mexico in 

1983, and a B.S. in geology from California State University in 1977. His professional 

experience includes geochemical experimentation with metal adsorption, field investigations of 

anaerobic biogeochemical systems, combined laboratory-field investigations of vadose and 

saturated sites contaminated with radionuclides and metals, and electron microscopy and 

spectroscopy applications to geochemical problems. He has authored peer-reviewed papers on 

biogeochemical processes, groundwater evolution, adsorption phenomena, and lunar 

geochemistry. 
5 

BARITE SOLUBILITY AND THE RELEASE OF TRACE COMPONENTS 

TO THE MARINE ENVIRONMENT 

Eric Crecelius, Brenda K. Lord-Lasorsa, and Jill Brandenburger, 

Battelle Marine Sciences Laboratory 

This is a synopsis of the presentation given by Eric Crecelius on 11 January 2005 in New 

Orleans at the MMS meeting on Environmental Fate and Effects of Discharges. 

During the last 18 months Battelle and the Florida Institute of Technology (FIT) have been 

conducting a research project for MMS to address the solubility of barite and solubility of trace 

metals contained in barite when barite is discharged into the marine environment. The scope of 

work is divided into the following six tasks. James McKinley presented the synopsis of Task 4; 

Task 5 was conducted by John Trefry at the Florida Institute of Technology. 

• Task 1: Determine the solubility of barite 

• Task 2: Determine the amount of trace metals released from barite 

• Task 3: Determine the rate at which barite dissolves 

• Task 4: Determine the trace metal species within the barite structure 

• Task 5: Evaluate the effects of acidic environments on the solubility of barite and release 

of selected metals into solution 

• Task 6: Evaluate the dissolution of barite after burial 

The composition of the three types of barite and the Gulf of Mexico (GOM) sediment used in 

these tasks are listed in the Table.1A.1 The concentrations of trace metals in these barite samples 

includes “Low Metal Barite” that has environmentally acceptable concentrations of mercury (< 1 

ug/g) and cadmium (<3 ug/g), two barite samples that exceed the mercury (Hg) criteria, and one 

sample that exceeds the cadmium (Cd) criteria. 

Table 1A.1. Concentration of elements in barite samples and Gulf of Mexico (GOM) shelf sediment, ug/g 

(ppm) dry weight. 

Hg Cd Ba Cr Cu Fe Mn Pb Sr Zn 

Low Metal 

Barite (MI Low) 0.44 0.35 538000 15 98 6603 625 318 5940 35

High Metal 

Barite (MI 

High) 

5.90 0.77 524000 6.5 88 9267 541 243 103000 167

Lab Blend 

Barite (FIT) 6.70 7.00 507000 11 189 29623 1321 1368 73380 1211

 

Clean Barite 

(GOM Criteria) 1.00 3.00 — — — — — — — —

GOM Shelf 

Sediment 0.05 0.33 713 55 17 27300 442 21 156 86
6 

The solubility of barium (Ba) and several other metals were determined in seawater under 

conditions that are expected to occur in the GOM. Figure 1A.1 shows the concentration of 

dissolved Ba over time in one liter of seawater containing 20 g of barite. The Ba concentrations 

ranged from about 40 ug/L, approximately the solubility of Ba in seawater, to 10 ug/L. 

• Static 20°C, 1 atm

• Solids 20g/L

• GOM Seawater 31.2 0/00

• pH 7.3 and 8.3

Static Test - Barium (pH 8.3)

0

5

10

15

20

25

30

35

40

2 24 168 690 2160 4320

Time (hrs)

Concentration ug/L

FIT

MIHigh

MILow

Static Test - Barium (pH 7.3)

0

10

20

30

40

50

2 24 168 690 2160 4320

Time (hrs)

Concentration ug/L

FIT

MIHigh

MILow

Figure 1A.1. Solubility of barite—static test. 

The solubility of several metals, including Hg, Cd, and zinc (Zn) in seawater at two pH 

concentrations are show in the Figures 1A.2 and 1A.3. The concentrations of these metals tended 

to increase with time for at least several months. The concentrations of metals were greatest at 

pH 7.3 and for the FIT-Blend barite, which contained the greatest concentration of these three 

metals. 

Experiments were conducted at FIT to determine the solubility of metals in acidic water. The 

following Figure 1A.4, 1A.5, and 1A.6 show the concentrations of Ba, Cd and Zn at several 

different pH concentrations for three barite samples. Very little Ba dissolved, less than 0.01%. 

However, most of the Cd dissolved and about a third of the Zn dissolved. Very little of the Hg 

dissolved, less than 0.1%. 
7 

• Static 20°C, 1 atm

• 20g/L Barite

• GOM Seawater 31.2 0/00

• pH 7.3 and 8.3

Static Test - Mercury (pH 8.3)

0

5

10

15

20

25

30

2 24 168 690 2160 4320

Time (hrs)

Conccentration ng/L

FIT

MIHigh

MILow

Static Test - Mercury (pH 7.3)

0

10

20

30

40

50

60

70

2 24 168 690 2160 4320

Time (hrs)

Concentration ng/L

FIT

MIHigh

MILow

Figure 1A.2. Solubility of trace metals—static test. 

Static Test - Cadmiun (pH 7.3)

0

5

10

15

20

25

30

35

2 24 168 690 2160 4320

Time (hrs)

Concentration ug/L

FIT

MIHigh

MILow

Static Test - Cadmium (pH 8.3)

0

5

10

15

20

25

30

35

2 24 168 690 2160 4320

Time (hrs)

Concentration ug/L

FIT

MIHigh

MILow

Static Test - Zinc (pH 7.3)

0

100

200

300

400

500

600

700

2 24 168 690 2160 4320

Time (hrs)

Concentration ug/L

FIT

MIHigh

MILow

Static Test - Zinc (pH 8.3)

0

50

100

150

200

250

300

2 24 168 690 2160 4320

Time (hrs)

Concentration ug/L

FIT

MIHigh

MILow

Figure 1A.3. Solubility of trace metals—static test (continued). 
8 

Figure 1A.4. Amounts of barium lost from the solid phase in ug/g. (Results provided by John Trefry, FIT.) 

Figure 1A.5. Amounts of cadmium lost from the solid phase in ug/g. (Results provided by John Trefry, FIT.) 
9 

Figure 1A.6. Amounts of zinc lost from the solid phase in ug/g. (Results provided by John Trefry, FIT.) 

The solubility of barite in anoxic sediment was examined. Relatively high concentrations of Ba, 

1000 to 7000 ug/L, were measured in the porewater of anoxic sediment that contained barite, as 

shown in the Figure 1A.7. Relatively low concentrations of other metals were in the porewater. 

Experiments are continuing with barite in sediment. 

Barium in Porewater

0

1000

2000

3000

4000

5000

6000

7000

8000

44 50 68 77 116

Days of Exposure

GOMA FIT, 10%

GOMA Control, 10%

GOMA + MIH, 10%

GOMA + MIH 1%

Figure 1A.7. Dissolution of barite after burial (porewater). 
10 

Eric A. Crecelius, Technical Group Manager, of Battelle Marine Sciences Laboratory, received 

his B.S. in general science at Oregon State University in 1967; his M.S. in oceanography at the 

University of Washington in 1970; and his Ph.D. in oceanography at the University of 

Washington in 1974. He manages a staff of 18 involved in chemistry projects. Dr. Crecelius has 

over 30 years’ experience in freshwater and marine geochemistry with emphasis on the 

concentration, speciation, and fate of trace elements in marine ecosystems. He has been the 

project manager of research contracts that required collecting and analyzing water, sediment and 

organisms, and seawater samples for butyltins, trace metals, and organic compounds, including 

nine years of analyses of NOAA Mussel Watch bivalve and sediment samples. Dr. Crecelius is 

internationally recognized in the field of marine pollution and trace metal analysis. He is 

frequently an invited participant or session chairman for workshops or scientific meetings that 

deal with arsenic speciation, marine monitoring, and the fate of contaminants in coastal waters. 

He has authored or coauthored nearly 80 journal articles and nearly 75 technical reports that 

apply geochemistry to diverse environmental issues. 

Brenda K. Lord-Lasorsa, Research Scientist V, Marine Chemistry & Ocean Processes at Battelle 

Marine Sciences Laboratory, received her B.S. in geology at Ohio State University in 1983 and 

her M.S. in geology at Ohio State University in 1986. Ms. Lasorsa is responsible for ongoing 

analyses as well as methods development for mercury and sulfide analysis. Experience includes 

assisting in development of both total and methyl mercury analysis systems and analysis of 

mercury in various media including tissues and sediment at the ng/g level and water at the ng/L 

level by cold vapor atomic fluorescence. Ms. Lasorsa has applied these speciation methods to a 

wide variety of matrices including tissue, sediment, hair, and water samples. She has also been 

responsible for the development of an acid volatile sulfide analysis system and appropriate 

sample handling methods associated with the system. The analytical experience with acid 

volatile sulfides includes an interlaboratory calibration study with the U.S. EPA in Duluth on 

sediments from three freshwater lakes in Minnesota, analyses of samples including experimental 

work on the quantity of metals released during oxidation of acid volatile sulfides (AVS) for the 

EPA, and analysis of dissolved sulfides and AVS in fly-ash pond sediments for EPRI. 

Jill Brandenberger, Research Scientist, Marine and Environmental Chemistry, Battelle Marine 

Sciences Laboratory, received her B.S. marine sciences at Texas A&M University, Galveston in 

1993 and her M.S. in environmental sciences at Texas A&M University, Corpus Christi, in 2001. 

She has a strong background in water quality issues, having been awarded a grant by the Texas 

Water Resources Institute to characterize arsenic concentrations in water resources of the Nueces 

River basin, including surface and ground waters. She designed and implemented a research 

project to characterize the water quality of Lake Corpus Christi Reservoir, Texas, as a function 

of temporal and event-driven cycling of trace metals with respect to present water chemistry and 

historical trends derived from sediment cores data. Ms. Brandenberger manages programs 

involving sediment evaluations in support of dredging operations. She specializes in trace-level 

mercury analysis, including the collection, preparation, digestion, and analysis of all sample 

matrices for mercury speciation. She also analyzes sediment and water for acid volatile sulfides 

(AVS/SEM). 
11 

BIODEGRADATION OF SYNTHETIC-BASED DRILLING FLUIDS 

Alan H. Nguyen and Deborah J. Roberts, 

Department of Civil and Environmental Engineering, University of Houston 

Introduction 

Offshore drilling operations in the Gulf of Mexico (GOM) generate cuttings that are 

contaminated with synthetic based fluids. Synthetic based fluids (SBF) are used in the drilling 

mud compounds to aid in the deep water drilling operation to lubricate the drill bit, control 

pressure, and carry cuttings to the surface. While the majority of the drilling mud is separated 

from the cuttings and recovered for reuse, residues left on the cuttings are discharged back to the 

sea floor. 

The overall objective of this study is to model the natural attenuation of SBF in the deep-sea 

sediments. A conceptual model has been developed based on advection-diffusion-reaction 

equations and has been previously presented (MMS ITM 2002). The calibration of the model is 

performed by splitting up each term and designing experiments that isolated each term. Based on 

simulations using the uncalibrated model, the anaerobic reaction term (sulfate reducing reaction) 

was believed to be the term of most variability that directly affects the fate of SBF in the 

sediment. The results of the experiments designed to isolate the anaerobic SBF degradation 

reaction term are presented here. 

Experimental 

Samples of sediments from various depths in the GOM ranging from 66 m to 1135 m were 

selected for the experiments. The sediments were collected from both near-field and far-field 

locations surrounding the drilling platforms represented contaminated and uncontaminated 

conditions. All samples were incubated at 4o

C and under either atmospheric pressure or at 

pressurized conditions relevant to the depth of collection. 

In this study, ethyl oleate was spiked into the sediments to serve as an ester surrogate component 

of SBF, and tetradecene was used as an olefin surrogate component of SBF. Sulfate and SBF 

surrogate concentrations were monitored using Ion chromatography or extraction and GC 

analysis, respectively. 

Results 

The results from this study indicate that the bacteria present in the Gulf sediments had the 

capability to degrade SBF. Similar decay curves for both ethyl oleate and tetradecene were 

obtained when the sediments were incubated under pressurized or atmospheric conditions 

(Figure 1A.8). There was no significant barometric effect on the degradation of SBF in GOM 

sediments. The anaerobic degradation of SBF in the sediments occurs simultaneously with 

sulfate removal, implying the activities of sulfate reducing bacteria (Figure 1A.9). In all 

experiments, biodegradation of the ester-based fluids occurs sooner and at a faster rate than that 

of the olefin based fluids. 
12 

Figure 1A.8. Concentrations of ester and olefin SBF surrogates during incubation in MP299 near field 

sediment at 4°C and at atmospheric pressure or pressurized to 97 psi hydraulic pressure. The 

data points represent the average of triplicate samples and the error bars represent one 

standard deviation. 

All experiments in this study showed anaerobic biodegradation of SBF surrogates. The 

biodegradation of SBF could be modeled as a first order decay with various lag times. In general, 

ethyl oleate decayed at the rate of 0.12 week-1 in the uncontaminated far-field sediments and at 

the rate of 0.21 week-1 in the contaminated near-field sediments. Olefin surrogates decayed at 

much slower rate (k = 0.04 week-1) and also required a longer lag time in near field sediments. 

Tetradecene has not been shown to be degraded in far field (uncontaminated) sediments to date 

(75 weeks of incubation). 
13 

Figure 1A.9. Concentrations of sulfate in control and spiked GC112 near field sediments incubated at 4°C 

and at atmospheric pressure or pressurized to 97 psi hydraulic pressure. The data points 

represent the average of triplicate samples and the error bars represent the average of triplicate 

samples and the error bars represent one standard deviation. 

Conclusion 

Sulfate reducing reaction is a primary mechanism in the degradation of SBF. Furthermore, there 

is no significant barometric effect seen in the degradation rates of SBF in GOM sediments. 

A lag period is required for sulfate bacteria to acclimate to the ester or olefin based fluids before 

biodegradation begins, this lag time is more extended in uncontaminated sediments where the 

bacteria have not been previously exposed to the compound. Therefore, a lag phase must be 

considered when modeling the degradation of olefin and ester base fluids. 

The decay rates of k = 0.12 week-1 can be used to model Ester based-fluids and k = 0.04 week-1

can be used to model Olefin based-fluids. 
14 

Alan H. Nguyen obtained a B.S. in chemistry and an M.S. in analytical chemistry from Lamar 

University – Beaumont, Texas. From 1994 to 1999, he was a Research Scientist at Southwest 

Research Institute. In 2002, he joined the University of Houston’s Civil and Environmental 

Engineering Department and is pursuing a Ph.D. in environmental engineering. He currently 

develops experiments to calibrate the model for predicting the attenuation of synthetic-based 

drilling fluids in the Gulf of Mexico sediments. 

Deborah Roberts received her B.S. and Ph.D. in microbiology from the University of Alberta. 

She is currently an associate professor in the Department of Civil and Environmental 

Engineering at the University of Houston. 
15 

CHARACTERIZATION OF MICROBIAL POPULATIONS SUBSISTING UPON 

SYNTHETIC-BASED DRILLING FLUIDS 

Kavita Swaminathan and Deborah J. Roberts, 

Department of Civil and Environmental Engineering, University of Houston 

Introduction 

The environmental impact of cuttings contaminated with oil-based drilling mud has resulted in 

severe restrictions of their use in many parts of the world and has led to the development of more 

environmentally friendly, synthetic-based drilling fluids (SBF). 

During biodegradation in the deep-sea, SBF are used as carbon sources and electron donors by 

microorganisms. Initially oxygen is used as an electron acceptor. Since oxygen is limited to only 

a few centimeters of the sediment, the next most abundant electron acceptor under marine 

conditions, sulfate, will be used followed by carbon dioxide. In terms of anaerobic 

biodegradability, theory suggests that ester-based synthetic fluids will be the first to undergo 

degradation under anaerobic conditions followed by alpha olefins and then internal olefins. The 

least degradable would be the paraffins. The possible SBF degraders include aerobes (which are 

mainly Eubacteria) and anaerobes (which are mainly sulfate reducing bacteria (Eubacteria) and 

methanogens (Archaebacteria). 

This research focuses on the study of some anaerobic populations in deep-sea sediments obtained 

from pristine as well as oil exploration impacted areas of the Gulf of Mexico (GOM). The 

objective is to examine the changes in the microbial populations of GOM sediment upon 

exposure to SBF. This will be achieved by the use of both growth-based and molecular tools to 

enumerate the microorganism present in the sediment. 

Sediment from sites identified as MP299 (~65m), GC112 (~500m), and VK916 (~1,100m) were 

used for the microbial tests. Samples of fresh sediment from near-field and far-field locations as 

well as the far-field samples after incubation with SBF surrogate ethyl oleate were analyzed by 

both the molecular-based fluorescent in situ hydrization technique (FISH) and the growth-based 

most probable number technique (MPN). 

Fluorescent In-Situ Hydrization (FISH) 

The use of FISH allows the visualization and quantification of whole microorganisms based on a 

partial sequence of 16S rRNA, unique to the organisms by species, genus or other genetic 

groupings. The cell envelopes are first weakened and then oligonucleotide probes which are 

fluorescently labeled are added to the samples. The probes adhere to the 16S rRNA. The cells are 

collected on a membrane filter and observed and counted using an epifluorescent microscope. 

The total number of cells present in the sample is determined using a non-specific DNA stain 

DAPI (4'-6-diamidino-2-phenylindole dihydrochloride). Probes used in this study were 

complementary to sulfate reducing bacteria (SRB385), all Eubacteria (EUB338), Clostridia 

(Clost I) and Archaebacteria (methanogens) (Arch915). 
16 

Most-probable number (MPN) Technique 

The most-probable number growth-based technique was used to enumerate general anaerobes 

(using a general organic rich medium), sulfate reducing bacteria (using a sulfate medium with 

acetate as the electron donor), aerobic hydrocarbon degrading bacteria (using a C14 overlay on 

mineral salts medium), and methanogenic organisms (using a mineral salts medium with H2 and 

acetate as electron donors). The media were tested for their usefulness using shoreline sediments 

before use with the deep Gulf sediments. A shoreline sediment was used as a control in all 

incubations. 

Results 

FISH

The application of the FISH technique to the sediment samples from the GOM was problematic. 

There was significant interference from organic material present in the sediment that could not 

be separated from the cells without significant loss of cell numbers. The detritus interference 

resulted in the operator having to exercise a lot of personal judgment. 

All of the counts from FISH analysis were in the 108

 range regardless of the sediment history. 

The total counts were not very different from the Eubacterial counts or SRB counts, suggesting 

that the eubacteria and SRB are being over counted or that the total counts are too low. Even 

though our confidence in the absolute numbers obtained is not high, examining the results in 

terms of the objectives suggest that the FISH analysis showed that NF (contaminated) sediment 

had slightly higher numbers of total counts and SRB for GC 112. This was not apparent for 

VK916 or MP299. 

A more direct measure of the response of sediment microbes to SBF is the comparison of the 

numbers before and after incubation with ethyl oleate. The DAPI (total counts) increased for 

both the GC112 (from 9 x 107

 to 1 x 109) and VK916 (1 x 108 to 7 x 108) sediments after 

exposure to ethyl oleate for 50 and 44 weeks respectively. The FISH analysis of SRB showed 

only slight increases in SRB if any increases at all. 

One confounding factor in the FISH analysis is that the control cultures (not spiked with ethyl 

oleate) also showed increases in numbers in most of the phylogenetic groups examined. 

MPN 

The lower limit of the number of organisms to be observed in the case of MPN depends of the 

dilution series selected for the different nutritional groups. Analysis of the MPN results indicate 

that at time T=final there was an increase in the number of sulfate reducers when compared to 

those present at time T=0 (numbers). The general anaerobes at T= final also showed an increase 

in numbers except for VK916FF. 

Conclusions 

 1. FISH is not the best tool to use to examine GOM sediments. 
17 

 2. The analysis shows that the SRB population is increasing due to the exposure of the 

sediments to SBF. 

 3. Both FISH and MPN gave similar numbers of SRB after incubation with ethyl oleate. 

This suggests that the SRB in the sediment are present up to 108

 cells/g dry sediment but 

are not all active until they are stimulated by the addition of carbon substrate. This 

contradicts the idea that the FISH probe is only measuring active organisms. 

Kavita Swaminathan received her B.S. in Chemical Engineering from Bangalore University in 

India. She is currently pursing a Master of Science in the Department of Civil and Environmental 

Engineering at the University of Houston. She has been working on this project since 2003. 

Dr. Deborah Roberts received her B.S. and Ph.D. in microbiology from the University of 

Alberta. She is currently an associate professor in the Department of Civil and Environmental 

Engineering at the University of Houston. 
18 

UNDERSTANDING THE PROCESSES THAT MAINTAIN THE OXYGEN LEVELS IN 

THE DEEP GULF OF MEXICO 

Ann E. Jochens, Texas A&M University 

The Minerals Management Service (MMS)-sponsored study, “Understanding the Processes that 

Maintain the Oxygen Levels in the Deep Gulf of Mexico,” began in July 2002. Scientists with 

expertise in physical and biogeochemical oceanography from Texas A&M University conducted 

the research. The study area is the deepwater Gulf of Mexico (GOM), defined as that part of the 

Gulf in water depths of 400 m or more. Vertically the study area extended from sea surface to 

sea floor. 

The objectives were to assemble and quality control the historical dissolved oxygen data base in 

the study area and to synthesize and re-analyze the data to understand the processes occurring in 

the deep GOM that effect and maintain the levels of dissolved oxygen. An evaluation was made 

of the effects of oil and gas activities on the dissolved oxygen levels. A simple box model was 

developed. Data and knowledge gaps were identified, including an evaluation of the quality of 

the data and how representative the data base is of the Gulf’s basin environment. Methods for 

filling the data gaps were recommended. 

Dissolved oxygen data were acquired from MMS, other state and federal agencies, national 

laboratories, universities, Mexican institutions, and the private sector. Two types of data were 

acquired: titrated measurements of water-bottle samples and measurements from oxygen sensor 

sensors. Dissolved oxygen data from bottle samples were obtained at nearly 4,000 stations from 

approximately 270 cruises in the GOM. Data from oxygen sensors were obtained for 

approximately 1,800 stations. It is not clear whether the sensor data were properly calibrated, so 

these data were not used in the analyses. The dissolved oxygen data were collected from 1922 

through 2001, when this study ceased data assembly. Waters at or below 1,500 m are not well 

sampled, with less than 650 stations sampling from only a few bottles at those depths. Only the 

decades of the 1960s and 1970s had station coverage throughout the Gulf basin. 

The GOM is a semi-enclosed sea with its major inflow at the Yucatan Channel and major 

outflow at the Florida Straits. The Yucatan Channel has a sill depth of ~2,000 m, which is deep 

enough to allow transport of oxygen-rich deep-source waters from the Atlantic Ocean into the 

Gulf from the Caribbean Sea. The Yucatan Current, which becomes the Loop Current, brings 

these waters in. The Florida Straits sill is shallow enough (~800 m) that the deep oxygen rich 

waters can mix into the interior of the Gulf rather than flowing directly out with the Loop 

Current. 

The sources of dissolved oxygen in the upper waters (~100-200 m) in the GOM are from 

exchanges with the atmosphere everywhere at the sea surface, mixing mainly by wind and wave 

action, and local contributions from photosynthesis in the photic zone. Oxygen-rich water masses 

are transported into the GOM from the Caribbean Sea through the Yucatan Channel. There is no 
19 

water mass formation in the GOM to replenish the deep oxygen concentrations. So, the deep 

circulation of the Gulf, which itself is not well-understood, and its associated mixing are the 

mechanisms that replenish the deep oxygen. The simple box model also found that the 

distribution of dissolved oxygen is primarily controlled by extra-basin effects, i.e., the source of 

dissolved oxygen to the deep waters is the transport and mixing of oxygen-rich water masses into 

the GOM through the Yucatan Channel. 

The major sink of oxygen in the Gulf, as elsewhere in the world's oceans, is oxidation of organic 

matter. The organic matter consists of living organisms, detritus from living organisms (fecal 

pellets, secretions, dead organisms, etc.), natural hydrocarbon seeps that are prevalent in the 

Gulf, continental detritus washed into the ocean through river runoff, and anthropogenic inputs 

(water-borne or air-borne organic pollutants as well as inputs from hydrocarbon extraction, 

transportation, and consumption). The rate of oxygen consumption by organic material has not 

been measured in the GOM and is not easily measured in the world's ocean. However, these rates 

are known to decrease exponentially with increasing depth. 

Early studies, using known high quality data sets, found that below approximately 1,500 m there 

was “no clearly discernable horizontal variation in dissolved oxygen in these waters” and “only 

slight vertical oxygen gradients” (Nowlin et al. 1969). Analysis of the additional data sets used in 

this study suggests the deep Gulf waters may have slightly different oxygen values in three 

different regions: the southeastern Gulf with mean dissolved oxygen concentrations of 4.99 

mL·L-1, the northern Gulf with a mean of 4.95 mL·L-1, and the southwestern Gulf with mean of 

4.87 mL·L-1. However, the quality of the data sets is variable enough that this finding is not 

definitive. 

Comparison of data sets from the 1970s with those from 2000/2001 indicates that there has not 

been any discernible change in the vertical or horizontal distribution of dissolved oxygen in the 

GOM. This suggests that the transport mechanisms that replenish the oxygen are adequate to 

balance the oxygen consumption from decay of organic matter, including that from oil seeps and 

anthropogenic sources. 

NRC (2003) reports that an estimated 140,000 ± 60,000 tons of hydrocarbons are introduced into 

the GOM from natural seeps each year. This seepage begins at the sea floor and rises through the 

water column to the surface, so potentially it can affect the total water column. Although this 

natural leakage of hydrocarbons into the Gulf has been occurring for millions of years, results of 

this study show dissolved oxygen levels throughout the water column have been stable over the 

period during which measurements are available. No significant large-scale perturbations in the 

dissolved oxygen content of the deep Gulf waters have been observed to result from this input. 

NRC (2003) also reports that anthropogenic sources of hydrocarbons to the GOM are estimated 

at approximately 2000 tons from extraction (1,700 tons of which are from produced waters), 

1,600 tons from transportation, and 6,800 tons from consumption. These inputs are widespread 

throughout the Gulf. A comparison was made between the dissolved oxygen content of selected 

reservoirs in the deep Gulf and the dissolved oxygen that would be consumed if all the 
20 

hydrocarbons from these sources were totally oxidized within each reservoir. The results show 

that the impact of anthropogenic hydrocarbons on dissolved oxygen concentrations is negligible 

over the large scale in the deepwater GOM. Localized effects, however, might be measurable at 

discharge sites, but data are insufficient to evaluate these potential effects. Most of these 

anthropogenic discharges occur at or near the sea surface, so there would be essentially no effect 

on the dissolved oxygen concentrations of the deep waters. 

Catastrophic oil spills can introduce hydrocarbons at two to three times the rate of the natural 

seeps. The effect of such spills on the dissolved oxygen concentrations would depend on many 

factors, including chemical characteristics of the spilled material, location in the water column 

and nature of the spill, residence time in the water column of labile components of the 

hydrocarbon as the spilled material rises toward the sea surface, and environmental conditions at 

the spill site, including sites to which the material may be transported. In the large scale, the 

impact is expected to be minimal. Effects on dissolved oxygen concentrations are expected to be 

local but potentially could be severe for short periods. Effects on dissolved oxygen 

concentrations in the deepwater Gulf of anthropogenic hydrocarbon discharges likely would be 

most substantial at the sediment-water interface at a discharge site or at the sea surface reached 

by the plume, not within the water column itself. Further study is needed to examine such effects 

because they are localized and complex. 

References 

National Research Council (NRC). 2003. Oil in the Sea III: Inputs, Fates, and Effects. 

Washington D.C National Academy Press. 280 pp. 

Nowlin, Jr., W.D., D.F. Paskausky, and H.J. McLellan. 1969. Recent dissolved-oxygen 

measurements in the Gulf of Mexico deep waters. Journal of Marine Research. 27 (1) 39–

44. 

Ann Jochens is an Associate Research Scientist in the Department of Oceanography at Texas 

A&M University and Program Manager for SWSS. She has a B.S. in Mathematics and Statistics 

with Honor from Southern Methodist University (1974), a D.J. with background specialty in 

ocean law from the University of Oregon (1977), and an M.S. and a Ph.D. in oceanography from 

Texas A&M University (1989; 1997). Her research focus is in physical oceanography with 

specific interests in processes at the boundary of the coastal and open oceans; integration of 

physical and biogeochemical observations to analyze circulation and property transports through 

the ecosystem with emphasis on coastal environments; meso- and large-scale ocean circulation 

and property distributions with emphasis on shelf and slope regions; Gulf of Mexico physical 

oceanography; and development of ocean observing systems. 
21 

TOXICOLOGICAL INTERACTIONS BETWEEN METALS AND POLY-NUCLEAR 

AROMATIC HYDROCARBONS IN THE BENTHIC COPEPOD SHIZOPERA KNABENI

John W. Fleeger, Sidney J. Marlborough, Kevin R. Carman, and Soraya J. Silva, 

Louisiana State University 

The mixture toxicology of sediment-bound contaminants (i.e., phenanthrene, lead, cadmium and 

mercury) frequently associated with offshore oil production platforms was investigated with the 

estuarine meiobenthic harpacticoid copepod Schizopera knabeni. Adult females were exposed to 

sediment amended with single contaminants and in combinations of each in 96-h LC50 lethality 

bioassays. Sublethal assays were carried out using a feeding-rate endpoint following Lotufo 

(1997). Contaminant effects in mixtures were delineated using toxic unit (TU) methodology and 

factorial experiments. 

LC50 values for single-contaminant exposures to phenanthrene (342 mg kg-1) and Cd (230 mg 

kg-1) and a mixture of Pb, Hg, and Cd in a ratio of 5:3:2 (1,462 mg kg-1) suggest that adult S. 

knabeni are very tolerant to these compounds. No significant mortality above controls was 

expressed by exposure to Hg and Pb below sediment saturation concentrations. However when 

Pb, Cd, and Hg were combined with phenanthrene, a greater than additive toxic response with a 

TU of 0.65 was demonstrated; the mixture was 1.54 x more toxic than predicted by separate 

exposures (Figure 1A.10). In addition, joint Cd and phenanthrene exposures exhibited a TU of 

0.42 (2.83 x more toxic than predicted by separate exposures, Figure 1A.11). A TU50 was 

expressed at combined equi-toxic concentrations (162 mg kg-1) that may be ecologically 

relevant. An antagonism between Hg, Pb and Cd was also apparent, and this antagonism may 

have moderated the observed Cd-phenanthrene synergism. A Cd-phenanthrene synergism was 

also observed in aqueous exposures suggesting that the synergism was dose, rather than 

exposure, related. Cd did not influence phenanthrene toxicokinetics (based on experiments using 

14C labeled phenanthrene) suggesting that phenanthrene does not interfere with Cd sequestration. 

Feeding rate decreased with increasing concentrations of the metal mixture and with increasing 

concentrations of phenanthrene. However in combination (a single concentration of 

phenanthrene was added to increasing metal concentrations), effects appeared additive. Effects 

on feeding rate do not appear to explain the strong synergism between Cd and phenanthrene. 

Results suggest that an increasing diversity of contaminants increases uncertainty in predicting 

mixture effects and that complex synergisms and antagonisms may be common in metalhydrocarbon mixtures. Our work also suggests that published sediment quality criterion for 

phenanthrene and cadmium are protective of adult S. knabeni, however the strong observed 

synergism between Cd and phenanthrene suggests that these criteria may be not be protective in 

sediments with mixtures of metals and hydrocarbons, especially for the more sensitive juvenile 

stages. 
22 

Figure 1A.10. Toxic unit results of experiments with S. knabeni combining a mixture of metals with 

phenanthrene. Results suggest a greater-than-additive effect. 

Figure 1A.11. Toxic unit results of experiments with S. knabeni combining Cd with phenanthrene. Results 

suggest a greater-than-additive effect. 
23 

References 

Lotufo, G.R. 1997. Toxicity of sediment-associated PAHs to an estuarine copepod: Effects on 

survival, feeding, reproduction and behavior. Marine Environmental Research 44:149–

166. 

John W. Fleeger is a George C. Kent Professor of Biological Sciences at Louisiana State 

University. Dr. Fleeger (Ph.D. University of South Carolina 1977) is a benthic ecologist who 

conducts research on population dynamics and community structure of macrofauna and 

meiofauna. He also conducts research in the area of ecotoxicology, especially the effects of 

metals, hydrocarbons and mixtures. Current research projects examine the effects of nutrient 

addition and predators on salt-marsh communities, the effects of carbon dioxide sequestration on 

benthic communities in the deep sea and the effects of contaminant bioavailability on deposit 

feeders. His publications include over 100 articles in professional journals and chapters in books. 

Sidney J. Marlborough is a research associate III with Dr. John Fleeger’s lab at Louisiana State 

University in Baton Rouge. He conducts aquatic toxicity testing with benthic invertebrates as 

well as manages the research lab. He has four years of environmental and regulatory experience 

with the Louisiana State Department of Environmental Quality. He received both his 

undergraduate and graduate degrees from Louisiana State University in environmental 

management systems and environmental science (toxicology), respectively. 

Kevin R. Carman is a professor at the Department of Biological Sciences, Louisiana State 

University. Dr. Carman (Ph.D. Florida State University 1989) is a biological oceanographer 

whose research interests include coastal marine foodwebs and the ecotoxicological effects of 

contaminants on estuarine communities. He is also conducting deep-sea research to examine the 

potential effects of CO2 sequestration on deep-sea benthos. Dr. Carman teaches Principles of 

Ecology and Introductory Biology at the undergraduate level; he also teaches a graduate class on 

the topic of invertebrate-microbe interactions. He has published over 40 articles in peer-reviewed 

journals and books. 

Soraya J. Silva is a Ph.D. student at the Department of Oceanography and Coastal Studies at 

Louisiana State University. Her research focuses in the study of the effects of diesel and copper 

contaminants on benthic microalgae community composition. Soraya received a masters degree 

in microbiology at the University of Zulia, Venezuela (1996), where she studied the effects of 

copper on the growth of diatoms in culture. She has been involved in several research projects 

related to the improvement and maintenance of a microalgae culture collection, and the 

coordination and performance of toxicity assays using microalgae as test organisms. 
25 

SESSION 1B 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT AND 

BENTHIC ECOLOGY STUDY RESULTS, PART I 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

DEEP GULF OF MEXICO BENTHOS INTRODUCTION Gilbert T. Rowe ........................... 27 

PHYSICAL OCEANOGRAPHY OBSERVATIONS OF THE GULF OF MEXICO DURING 

DGoMB: 2000–2002 Steven F. DiMarco, Ann E. Jochens, and Matthew K. Howard ............... 29 

SeaWiFS OCEAN COLOR AT DGoB STATIONS Douglas C. Biggs, Chuanmin Hu, and 

Frank E. Müller-Karger ................................................................................................................ 36 

GEOLOGY William Bryant ........................................................................................................ 43 

CONTAMINANT CHEMISTRY: POLYCYCLIC AROMATIC HYDROCARBONS (PAH) 

AND TRACE ELEMENTS Terry L. Wade, Gary A. Wolff, and Bobby J. Presley................... 44

BIOGEOCHEMISTRY OF THE NORTHERN GULF OF MEXICO SEDIMENTS: 

A COMPONENT OF THE DEEP GULF OF MEXICO BENTHOS (DGoMB) PROJECT 

John Morse.................................................................................................................................... 49 

SEDIMENT BACTERIA ABUNDANCE, BIOMASS, RESPIRATION AND PRODUCTION: 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE AND ABYSSAL PLAIN 

Jody Deming and S. Carpenter ..................................................................................................... 50 
27 

DEEP GULF OF MEXICO BENTHOS INTRODUCTION 

Gilbert T. Rowe, Texas A&M University 

The Deep Gulf of Mexico Benthos (DGoMB) study has been focused on the characteristics, 

faunal composition, and general well-being of sea-floor ecosystems of the deep Gulf of Mexico 

(GOM) in anticipation of continued extension of oil and gas exploration and production into 

deep-water environments. Faunal community structure is being used to test hypotheses about 

what controls the distribution of animal communities. Community function/dynamics is being 

investigated by measuring critical fluxes in the near-bottom food web. The field work has 

covered the entire northern GOM continental margin from depths of 200 to greater than 3,700 

meters (almost two miles) in Mexican waters out on the Sigsbee and Florida abyssal plains. 

DGoMB was designed to improve the ability to predict variations in the structure of animal 

assemblages in relation to depth, geographic location, year-to-year time-dependence, small-scale 

physiographic features (basins, canyons, etc.), surface-water primary production, and association 

with methane seeps. The structural characteristics measured were diversity, similarities in 

taxonomic composition between geographic locations (zonation, for example, with depth), 

variations in biomass and abundance, and mean size of individuals within functional size 

categories. An underlying premise has been that deep-sea communities are all food limited. A 

second assumption is that community dynamics and community structure are interdependent. An 

initial broad survey of community structure in the year 2000 followed by an investigation of 

community dynamics in 2001 and 2002. The studies of community function were limited to a 

seven targeted sites, with specific locations being selected on the basis of extremes in standing 

stocks. 

Principal investigators included William Bryant (geology), a host of physical oceanographers 

from TAMU, John Morse and Luis Cifuentes (biogeochemistry), Bobby Joe Presley and Terry 

Wade (contaminant chemistry), Paul Montagna (meiofauna), Richard Haedrich (multivariate 

analyses of faunal data), Joan Bernhard (forams), Rowe and Fain Hubbard (macrofauna), Rowe 

(photography), Doug Biggs (remote sensing), Ian MacDonald (mapping), Gary Wolff (data 

management) and Jody Deming (bacteria). Mahlon C. Kennicutt was the Associate Program 

Manager. 

Detailed taxonomic analyses have been conducted on the polychaete annelids (Fain Hubbard and 

Yuning Wang), the aplacophoran mollusks (A. Scheltema), the bivalve mollusks (Min Chen, Roe 

Davenport, and Mary Wicksten), the amphipod crustaceans (John Foster and Yousra Soliman), 

the isopod crustaceans (George Buz Wilson), the harpacticoid copepods (Yonsol Lee, Jeff 

Baguley, and Paul Montagna), the tanaid crustaceans (Richard Heard and Kim Larsen), the 

megafauna (Mary Wicksten, Daphne Fautin and associates) and the demersal fishes (John 

McEachran and Richard Haedrich). These are supplemented by quantitative estimates of the 

standing stocks of the bacteria (Jody Deming), foramiferans (Joan Bernhard), meiofauna, 
28 

macrofauna, megafauna and fishes; and extensive measurements of the physico-chemical 

environment. 

Dr. Gilbert T. Rowe completed his B.S. in zoology and M.S. in oceanography at Texas A&M 

before receiving a Ph.D. in zoology at Duke. He worked for 11 years as a research scientist at 

WHOI and eight years as a research scientist at the Brookhaven National Lab on Long Island. In 

1987 he returned to Texas A&M to become Head of the Oceanography Department. He 

transferred to the Galveston campus in 2002 as Head of Marine Biology. Since 1999 he has been 

the Program Manager of MMS’s Deep Gulf of Mexico Benthos project (DGoMB), now nearing 

completion. 
29 

PHYSICAL OCEANOGRAPHY OBSERVATIONS OF THE GULF OF MEXICO 

DURING DGoMB: 2000–2002 

Steven F. DiMarco, Ann E. Jochens, and Matthew K. Howard, 

Texas A&M University 

Introduction 

The earliest attempt at a comprehensive synthesis of the physical oceanography of the Gulf of 

Mexico (GOM) is found in Capurro and Reid (1972). Since then, and particularly in the last 15 

years, the study of the physical oceanography of the GOM has greatly accelerated. Much, if not 

most, of this increased study has been funded by the MMS acting in response to intense energy 

exploration and production activities on the shelf, slope, and rise. 

The GOM is a semi-closed basin with both broad and narrow continental shelves surrounding a 

deep abyss reaching ~3,800 m. Nowlin et al. (2001) examined the available measurements of 

currents in the deepwater GOM and determined the background currents by extracting the 

maximum, mean, and standard deviation for each instrument. They found that the highest 

maximum and mean current speeds were near the sea surface with maxima reaching up to 200 

cm·s

-1 in the eastern Gulf and 100 cm·s-1 in the western Gulf. Current speeds decreased with 

depth tending toward a minimum near 1,000 m. Current speeds increased somewhat with depth 

below that level, likely due to bottom intensification of currents. 

Wind stress forcing is second only to the forcing by the Loop Current system in providing energy 

to the circulation in the Gulf. Wind forcing occurs both as low-frequency regional circulation 

patterns forced by low-frequency regional wind patterns and as episodic currents forced by high 

frequency atmospheric events including tropical cyclones, extratropical cyclones, cold air 

outbreaks, and other frontal passages. 

The world’s third largest river, the Mississippi River, and dozens of lesser rivers discharge 

tremendous volumes of fresh water into the GOM. This affects stratification over large areas and 

enhances wind-driven coastal jets along frontal boundaries. Thus, thermohaline forcing is 

important over the Gulf shelves, e.g., buoyancy forcing by river discharge affects the nearshore 

coastal currents over the shelves. However, no thermohaline forcing of consequence is known to 

occur in the deepwater Gulf. 

Data 

Standard physical oceanographic instrumentation and sampling procedures were used to collect 

measurements on the DGoMB cruises. All such sampling was done to the same standards and 

using similar types of equipment as used on the MMS-sponsored programs LATEX-A and 

NEGOM-COHS. Data taken consisted of four types—continuous profiles, discrete 

measurements, ADCP measurements (shipboard and moored), and supplementary underway 

measurements. Continuous vertical profiles were collected for seawater conductivity/salinity, 

temperature, pressure/depth, fluorescence, light transmission, optical backscatterance, 
30 

downwelling irradiance, and dissolved oxygen. Discrete water samples were taken for analysis of 

dissolved oxygen and nutrients (phosphate, silicate, nitrate, nitrite, ammonium, and urea), 

phytoplankton pigments, particulate matter, and particulate organic carbon at most stations and 

salinity at selected stations. 

CTD stations (60 total) were taken on the May/June 2000 (DG1), June 2001 (DG2), and June 

2002 (DG3A) cruises. None were taken on the August 2002 (DG3B) cruise. Water samples were 

collected at the CTD stations. 

ADCP measurements were made along track on DGoMB cruises in May/June 2000 (DG1), June 

2001 (DG2), and June 2002 (DG3A). Although not paid for by the contract, ADCP data were 

collected on the August 2002 (DG3B) cruise as a complementary data set. Either a 150-kHz 

broadband (S/N 1183) ADCP or a narrow-band (S/N 355) ADCP was operated simultaneously 

with an Ocean Surveyor 38 kHz (OS-38) ADCP (S/N 8). No 38 kHz data were collected on the 

June 2001 cruise. All ADCP instruments were manufactured by RD Instruments (RDI) of San 

Diego, California. The OS-38 is on loan from the U.S. Navy. 

A 300-kHz Workhorse ADCP (Model 300S Sentinal rated to 6,000 m) was deployed during the 

June 2001 and 2002 cruises at selected experimental stations. The instrument was lowered and 

left at the sea floor at the beginning of each experimental station. Locations, dates, and times of 

deployment are given in Table 1B.1. 

Table 1B.1. Locations, dates, and times of deployment of the moored ADCP. 

Name Start Date/Time End 

Date/Time 

Latitude 

(°N) 

Longitude 

(°W) 

Depth 

(m) 

Station 

Name 

 

2001-1 03 June 2001 04 June 2001 28.2210 89.4991 935 MT3 

2001-2 06 June 2001 07 June 2001 28.2501 88.4168 755 S42 

2001-3 09 June 2001 12 June 2001 28.9200 87.6690 1823 S36 

2001-4 13 June 2001 14 June 2001 26.9999 88.0000 1740 MT6 

2002-1 03 June 2002 05 June 2002 25.0000 90.0000 3525 Sigsbee 

2002-2 10 June 2002 11 June 2002 24.2500 85.5000 3410 Low_curr2 

Although not contractually required, one or two thermosalinographs were operated intermittently 

during the DGoMB cruises. One system collected data from approximately 2.5-m depth; the 

other from about 3.5-m depth. The systems logged temperature and conductivity continuously at 

approximately 1- or 2-minute intervals on DGoMB cruises DG1, DG2, and DG3A. 

Water Properties 

Temperature and salinity measurements were made on the DGoMB cruises in May/June 2000, 

June 2001, and June 2002. Measurements of nitrate, phosphate, silicate, and dissolved oxygen 

concentrations were made on the cruises in 2000 and 2001. The vertical patterns of these water 

properties were analyzed. The station spacing did not allow detailed or meaningful examination 

of horizontal patterns. However, the vertical patterns were related to features in the circulation 

field shown by the sea surface height fields. 
31 

The general salinity pattern for all stations consists of four major characteristics. Most notable is 

lack of horizontal variability in salinity below depths of approximately 1000 m. This is present in 

all station CTD data. Second is a salinity maximum. This maximum erodes the farther from the 

source waters the station is located. However, this is not simply a function of distance from the 

Loop Current. The third characteristic of the salinity profiles is the salinity minimum at about 

500–1,000 m or σ θ of 27.3-27.5 kg·m-3. This is associated with the Antarctic Intermediate Water 

that is brought into the Gulf by the Loop Current. The depth at which this minimum occurs is 

variable. It appears to be related to the type of eddy feature the station sampled or the proximity 

to the bathymetric effect of the slope. The fourth characteristic is the variability in the nearsurface salinity values. Here are considered the salinities in the upper 50–100 m. These upper 

waters have lower salinity concentrations at that depth. Part of this, of course, is related to the 

presence of the salinity maximum. However, part of the variability is due to the mixing of low 

salinity water discharged from the Mississippi River with the near-surface oceanic waters. Of the 

selected stations shown in Figure 1B.1, the lowest near-surface salinity values occur at S36, 

which is located southeast of the Mississippi River. Other stations west as well as east of the 

Mississippi River mouth exhibit low salinity. In the cases examined, there were circulation 

features adjacent to the Mississippi River mouth that likely transported shelf water, which had 

been diluted by mixing with river water, to the slope regions adjacent to the river. This situation 

has been observed in other programs (Belabbassi et al. 2004). 

Figure 1B.1. Selected station data showing salinity versus density (top) and depth (bottom). Shown are 

stations RW6 (2000) in a Loop Current Eddy in the western Gulf, S36 (2000) in a cyclonic eddy 

in the eastern Gulf, GK-Furrows (2001) at the edge of a Loop Current Eddy in the central Gulf, 

S4 in the Loop Current, S2 at the edge of a Loop Current Eddy in the south central Gulf, and 

S5 at the edge of a cyclone in the eastern Gulf. 
32 

Moored Current Observations 

During the 2001 summer cruise, a 300-kHz ADCP was deployed at each of four process stations 

(MT3, S42, S36, and MT6). The instrument was placed 35 m above bottom in a downwardlooking configuration. The deployments were short, ranging from 20–60 hours. Because of the 

short deployment period, these observations should be considered as a representative snapshot of 

the physical conditions that existed while each process station was occupied. The current 

observations should not be considered as the climatology of currents possible at each location. 

To determine the current climatology, a much longer current meter record is required. 

The near-bottom currents at the four process stations during summer of 2001 were generally 

weak with record-length mean speeds of about 2.5, 7.5, 2.5, and 5 cm/s at stations, MT3, S42, 

S36, and MT6, respectively (Figure 1B.2). Mean directions were generally aligned along local 

bathymetry. Vertically, current speeds decreased slightly with closeness to the bottom. Standard 

deviations of speed were generally consistent for all four deployments at 1-2 cm/s. The sea 

temperature at the ADCP transducer head was nearly constant throughout each deployment at 

5.0°, 6.0°, 4.1°, and 4.2°C. Vertical and error velocities (an indicator of the amount of horizontal 

inhomogeneity of currents in the water column) were small (1-2 cm/s) for all deployments. 

Figure 1B.2. Record-length mean speed (solid) and plus and minus one standard deviation (dashed) of 

currents measured using a bottom-moored downward-looking 300-kHz ADCP during four 

deployments in 2001. Instrument was 35 mab. Deployment sites are: MT3 (top left), S42 (top 

right), S36 (bottom left), and MT6 (bottom right). 
33 

At S42, there was some vertical structure as the record-length mean cross-slope velocity changed 

sign at about 20 m above bottom; down-slope below 20 m and upslope above 20 m. There was 

no change in the along-slope component. Both velocity components were dominated by a neardiurnal oscillation with amplitude of about 7 cm/s and about 6 hours out of phase. Because of the 

short deployment, it is not possible to determine whether this oscillation is due to tidal forcing or 

of inertial origin. Diurnal oscillations were also present at stations MT3, S36, and MT6, although 

significantly weaker then at S42, i.e., amplitudes of 2–3 cm/s. 

Shipboard Current Observations 

Shipboard ADCP observations of near-surface currents along the cruise track of each cruise were 

obtained using 150 kHz and 38 kHz ADCPs. During the summer of 2002, the track of both 

cruises extended from the northern Gulf to the Loop Current. During Cruise 4 in June 2002, the 

cruise track passed through or near several energetic circulation features including the Loop 

Current, a detached Loop Current Eddy (24°N, 94°W), a strong cyclone northwest of the Loop 

Current, and other weaker features. In general, currents were aligned with altimeter contours of 

sea surface height. The strongest observed currents during this cruise were associated with the 

Loop Current and the currents associated with anticyclonic features. In the Loop Current, 

currents exceeded 135 cm/s in the upper 100 m and 100 cm/s in the upper 150 m. Useful 

observations were limited to the upper 200 m because of the operation frequency (153-kHz) of 

the ADCP used (the 38-kHz ADCP failed to produce useful data). 

Currents in the weak anticyclone near 27°N, 90°W peaked above 60 cm/s and averaged greater 

than 30 cm/s in the upper 200 m. Similar values were found on the eastern limb of the Loop 

Current Eddy. Mean currents in the upper 200 m of the water column ranged from 38 cm/s at 10 

m depth to 13 cm/s at 200 m. The standard deviation similarly ranged from 25 cm/s at 10 m to 10 

cm/s at 200 m. 

During Cruise 5, August 2002, the central GOM was nearly devoid of energetic circulation 

features as evidenced by a nearly flat SSH field (Figure 3). The dominant feature was the Loop 

Current, which extended slightly further northward than seen in June 2002. Currents in the Loop 

Current exceed 180 cm/s to 50 m depth and 120 cm/s to 150 m (Figure 1B.3). The standard 

deviation of currents while in the Loop Current is nearly constant with depth at about 13 cm/s. 

Record length mean currents for this cruise decay from about 30 cm/s at the surface to about 10 

cm/s at 200 m. 

Acknowledgments 

The authors thank Ou Wang (now of JPL) and Yue Fang (TAMU) for ADCP data processing. 

This work was sponsored by the U.S. Minerals Management Service under Contract No. 1435-

01-99-CT-30991. 
34 

Figure 1B.3. Contours of sea surface height from satellite altimeter data and near-surface velocity vectors 

from shipboard ADCP during August 2002. SSH data are from 8 August 2002 and courtesy of 

R. Leben (CU). 

References 

Belabbassi, L., W.D. Nowlin, Jr., A.E. Jochens, D.C. Biggs, and P. Chapman. 2004. Summertime nutrient supply to near-surface waters of the northeastern Gulf of Mexico: 1998, 

1999, and 2000. In preparation. 

Capurro, L. R.A., J.L. Reid, eds. 1972. Contributions on the Physical Oceanography of the Gulf 

of Mexico. Galveston, Texas: Texas A&M University Oceanographic Studies. 288 pp. 

Nowlin, Jr., W.D., A.E. Jochens, S.F. DiMarco, R.O. Reid, and M.K. Howard. 2001. Deepwater 

Physical Oceanography Reanalysis and Synthesis of Historical Data: Synthesis Report. 

U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, 

New Orleans, LA. OCS Study MMS 2001-064. 528 pp. 
35 

Steve DiMarco is an Associate Professor at Texas A&M University. His professional interests 

include physical oceanography of the Gulf of Mexico and the southwest Indian Ocean, hypoxia 

of the northern Gulf of Mexico, ocean observing systems, nonlinear surface wave interaction and 

impact of extreme wind events on shelf circulation 

Ann Jochens is an Associate Research Scientist in the Department of Oceanography at Texas 

A&M University and Program Manager for SWSS. She has a B.S. in Mathematics and Statistics 

with Honor from Southern Methodist University (1974), a D.J. with background specialty in 

ocean law from the University of Oregon (1977), and an M.S. and a Ph.D. in oceanography from 

Texas A&M University (1989; 1997). Her research focus is in physical oceanography with 

specific interests in processes at the boundary of the coastal and open oceans; integration of 

physical and biogeochemical observations to analyze circulation and property transports through 

the ecosystem with emphasis on coastal environments; meso- and large-scale ocean circulation 

and property distributions with emphasis on shelf and slope regions; Gulf of Mexico physical 

oceanography; and development of ocean observing systems. 

Matthew Howard is an Assistant Research Scientist in the Department of Oceanography at Texas 

A&M University. 
36 

SeaWiFS OCEAN COLOR AT DGoB STATIONS 

Douglas C. Biggs, Department of Oceanography, Texas A&M University 

Chuanmin Hu and Frank E. Müller-Karger, 

College of Marine Science, University of South Florida 

Synopsis 

The amount of particulate organic carbon reaching the seabed is set by the annual primary 

production in near-surface waters, less losses from grazing and/or remineralization in the water 

column. Because primary production covaries as the time rate of change in phytoplankton 

biomass in near surface waters, we used SeaWiFS ocean color data to calculate biweekly 

averages of the chlorophyll concentration (CHL) in surface waters at each of the 44 DGoMB 

stations in the northern Gulf of Mexico (GOM). In a previous ITM presentation, we described 

the annual cycle of CHL at a typical deep water DGoMB location, and we also showed how in 

the northeastern GOM this deepwater cycle is modified when slope eddies often entrain and 

transport Mississippi River water eastward and off margin. For this year’s ITM presentation, we 

review these patterns and summarize how the 1998–2000 time series that we’ve presented 

previously has been extended using SeaWiFS data through September 2004, and by follow-on 

field surveys of the 1,000 m isobath in the NE GOM in summers 2001–2003. 

Introduction 

Phytoplankton pigment concentration in the first optical depth in the deepwater GOM undergoes 

a well-defined seasonal cycle that is generally synchronous throughout the region. Müller-Karger 

et al. (1991) reviewed monthly climatologies of near-surface phytoplankton pigment 

concentration from multiyear series of coastal zone color scanner (CZCS) images for the period 

1978–1985. They reported that highest near-surface CHL occurs between December and 

February and lowest values occur between May and July. They also reported there is only about 

a three-fold variation between the lowest (~0.06 mg m-3) and highest (0.2 mg m-3) deepwater 

near-surface CHL. 

At the previous ITM (January 2003), we reported our analysis of 1998–2000 ocean color data 

collected during the follow-on Sea viewing Wide-Field Sensor (SeaWiFS) mission (Biggs et al. 

2003). At the 22 DGoMB stations over the continental slope in the western GOM (west of 

91o

W), we saw essentially the same annual cycle in magnitude and phase of CHL that was 

reported from the predecessor CZCS mission. However, at the 22 DGoMB stations over the 

continental slope in the eastern GOM (east of 91oW), we reported there were large biweekly 

variations in both magnitude and phase of the mean CHL concentration. These variations were 

correlated with the presence of mesoscale eddies that occur along or near the continental slope in 

the eastern GOM. Because especially in summer these slope eddies can entrain low salinity, high 

CHL Mississippi River water, and transport this green water off shelf and into the deepwater of 

the eastern GOM, the highest near-surface CHL concentrations in the NE Gulf were not present 

exclusively in December–February; rather, they reached annually highest levels in May–July. 
37 

Results and Discussion 

Table 1B.2 summarizes the annual mean CHL at western versus eastern northern GOM DGoMB 

stations for the three-year period 1998–2000. Note that the annual mean averages 4.9 times 

higher in the east than in the west, and that there is greater variability about the mean in the east 

as well. These relative differences are best seen by animating the biweekly scenes, as we did at 

the previous ITM (January 2003) to show the year-year period as a movie that runs January 1998 

through December 2000. In that animation, the biweekly-composite scenes clearly show the 

periodic entrainment and transport offshore of high-CHL Mississippi River water by mesoscale 

eddies in the eastern GOM. An extension of these SeaWiFS biweekly composites through 

September 2004 has recently been completed, which shows that the off-margin transport of green 

water in the NE Gulf continued in summers 2001, 2002, and 2003 (Biggs et al. 2005). The full 

seven-year time series, October 1997 through September 2004, will be available in CD-ROM 

format to an appendix to a monograph on “New Developments in the Circulation of the Gulf of 

Mexico.” That monograph is expected to be published later in 2005. 

Table 1B.2. Summary of remotely-sensed chlorophyll concentrations, 1998–2000. 

DGoMB region Mean SeaWiFS CHL Number of Stations Std Dev of Mean CHL 

W of 91oW and N of 26oN 0.19 22 0.03 

E of 91oW and N of 26oN 0.93 22 0.59 

Figure 1B.4 shows the seasonal cycle of CHL at the nine deepest of the “Deepwater Stations” in 

the western GOM (RW6, AC1, W5, W6, NB5, B1, NB4, B2, and B3). Water depth at each of 

these nine stations was greater than 2 km. The top panel in Figure 1 shows the average biweekly 

CHL at each of the nine stations for the three years 1998–2000, while the bottom panel graphs 

the average biweekly concentration (averaged for the three years). In the top panel, each of the 

three-year time series were fit station-by-station using spline fits. In the bottom panel, the annual 

cycle has been summarized by a quadratic fit to the averages of three years of biweekly data at 

the westernmost deepwater station, RW6. Both of these visualizations show the pattern 

previously reported from analysis of the CZCS archives by Müller-Karger et al. (1991): 

deepwater CHL is lowest in spring-summer (Julian Days 100–250) and highest November–

February (Julian Days 330–60). 

East of 91o

W, the “typical” deepwater annual cycle in CHL was often swamped by unusually 

high CHL, especially during summertime. Figure 1B.5 shows that high surface CHL in 

summertime was evident at the three stations along the Eastern Transect (S44, S43, S42), at five 

of the six stations on the Mississippi Trough Transect (MT1-MT5), and at the three stations 

farthest upslope along the Central Transect (C1, C7, C4). High summertime CHL generally 

occurred, as well, at three of the stations farthest upslope along the DeSoto Canyon Transect 

(S35, S36, S37). Because of this, the annual mean CHL concentration at the 22 DGoMB stations 

east of 91o

W averaged 0.9 rather than 0.2 mg m-3 (Table 1B.2). 
38 

Figure 1B.4. Top panel: Three year climatology of biweekly composited SeaWiFS ocean color data 1998–2000 

at the nine DGoMB stations in water depth > 2000 m in the western Gulf of Mexico. Bottom 

panel: The average annual cycle of chlorophyll at these western Gulf of Mexico deepwater 

stations, illustrating the typical annual range from summertime lows of about 0.1 mg m-3 to 

November–February highs of about 0.3 mg m-3. 
39 

Figure 1B.5. Three year climatology of biweekly averaged SeaWiFS ocean color data 1998–2000 at the 

DGoMB stations east of 91o

W in the eastern Gulf of Mexico. Ocean color was converted to 

chlorophyll concentration (mg m-3) using SeaDAS4.4 software. 

A combination of remote sensing altimetry data and hydrographic data collected from R/V Gyre

in support of the Northeastern GOM Chemical Oceanography and Hydrography program 

(NEGOM) has provided the explanation why this occurs. Both ship and altimetry data show that 

in summers 1998, 1999, and 2000, warm slope eddies (WSEs) were centered over the deepwater 

of the DeSoto Canyon. In general, anticyclonic eddies with SSH > 25 cm are considered to be 

strong WSEs, while those with SSH of just 10–20 cm are considered to be weaker WSEs. A 

strong WSE that was centered south of 28oN in summer 1999, as well as less strong WSEs 

located farther north on the slope in summers 1998 and 2000, all acted to entrain low salinity, 

high CHL “green water” from the Mississippi River and transport this green water plume 

seaward into deepwater. As a result, high surface CHL in summertime was evident at most of the 

DGoMB stations on the Mississippi Trough Transect (MT1-MT5), and at the three stations 

farthest upslope along the Central Transect (C1, C7, C4), and at the three stations farthest 

upslope along the DeSoto Canyon Transect (S35, S36, S37). High summertime CHL occurred, 

as well, at three of the stations along the Eastern Transect (S44, S43, S42). 

That WSEs in deepwater of the eastern GOM do indeed entrain low salinity Mississippi River 

water and transport it off margin has been verified by Belabbassi (2001), from analysis of near-
40 

surface salinity data collected during R/V Gyre NEGOM cruises in summers 1998, 1999, and 

2000. By carrying out high performance liquid chromatography (HPLC) analyses of the 

phytoplankton pigments collected from R/V Gyre in these low salinity plumes during these same 

cruises, Qian et al. (2003) verified that this low salinity water had locally high CHL standing 

stocks. 

Colored dissolved organic matter (CDOM) fluorescence and light absorption coefficient were 

also measured along with surface salinity and chlorophyll during most of the R/V Gyre NEGOM 

cruises conducted in 1998–2000. Strong correlations between the CDOM absorption coefficient 

(ag443) and CDOM fluorescence (330 nm excitation and 450 nm emission filters) were 

consistently observed (Nababan 2005). Relatively high ag443 (> 0.1 m-1) was generally observed 

inshore (inner shelf) near the major river mouths, but this ag443 also decreased rapidly with 

distance from shore except when riverine waters were entrained and transported offshore by 

WSEs. Because CDOM as well as CHL contributes to the ocean color signal measured by 

SeaWiFS, in our time series of biweekly composites we have likely over-estimated CHL at the 

shallower DGoMB stations. Specifically, the CHL spikes > 10 mg m-3 shown in Figure 2 at 

stations MT1 and MT2 close off the Mississippi River delta may be overestimated by perhaps 

30–50%. 

Slope eddies contribute biological and physical heterogeneity along the continental margin of the 

northern GOM. Temporal and spatial variations in the geometry of the eddy field along the 

middle slope determine whether low salinity green water flows off-margin or high salinity blue 

water flows on-margin. We hypothesize that more surface primary production sinks out from 

green water than from blue water regions. We also hypothesize that green water features that 

persist for weeks to months in time likely are the most important in the export of POC from 

surface waters. 

How much phytoplankton production of these surface waters reaches the seabed? If on average 

10% of the primary production sinks out of the photic zone, and if 3–10% of this flux in turn 

reaches the seabed, then at a western GOM deepwater location just 100–360 mg C m-2 y

-1 might 

reach the benthos. However, productivity in “hot spots” of locally higher nutrient concentrations 

over the continental slope can be more than an order of magnitude higher than the typical 100–

150 mg C m-2 d-1 (Biggs and Ressler 2001). Specifically, we hypothesize that in such “hot spots” 

and at most of the stations in water depths < 2,000 m along central and eastern DGoMB transects 

C, MT, and S, POC input rates to the benthos are likely to be at least 0.93/0.19 = 4.5 times 

higher-than-average. 

Acknowledgments 

TAMU support came from MMS contracts 1435-01-97-CT-30851, 1435-01-99-CT-30991, and 

1435-01-02-CA-85186. USF support came from NASA contracts NAS5-97128 and NAG5-

10738. SeaWiFS data are property of Orbimage Corporation and data use here is in accordance 

with the SeaWiFS Research Data Use Terms and Conditions Agreement of the SeaWiFS project. 
41 

References 

Belabbassi, L. 2001. Importance of Physical Processes on Near-Surface Nutrient Distributions in 

Summer in the Northeastern Gulf of Mexico. M.S. Thesis, Department of Oceanography, 

Texas A&M University, College Station, TX. 85 pp. 

Biggs, D.C., A.E. Jochens, M.K Howard, S.F. DiMarco, K.D. Mullin, F.E. Müller-Karger, and 

C. Hu. 2005. Eddy-forced variations in on-margin and off-margin summertime 

circulation along the 1000 m isobath of the northern Gulf of Mexico, 2000–2003, and 

links with sperm whale distributions along the middle slope. In: New Developments in 

the Circulation of the Gulf of Mexico. American Geophysical Union. 

 

Biggs, D.C., A.W. Remsen C. Hu, and F.E. Müller-Karger. 2003. Ocean color climatology of 

chlorophyll at DGoMB stations in 1998, 1999, and 2000, and its use as a proxy for POC 

flux to the seabed. Proceedings, Information Transfer Meeting, January 2003. U.S. Dept. 

of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New 

Orleans, LA. OCS Study MMS 2004-067. 

Biggs, D.C. and P.H. Ressler. 2001. Distribution and abundance of phytoplankton, zooplankton, 

ichthyoplankton, and micronekton in the deepwater Gulf of Mexico. Gulf of Mexico 

Science. 19:7–35. 

Müller-Karger, F.E., J.J. Walsh, R.H. Evans, and M.B. Meyers. 1991. On the seasonal 

phytoplankton concentration and sea surface temperature cycles of the Gulf of Mexico as 

determined by satellites. Journal of Geophysical Research 96:12645–12665. 

Nababan, B. Bio-optical Variability of Surface Waters in the Northeastern Gulf of Mexico. 2005. 

Ph.D. Dissertation, Department of Marine Science, University of South Florida, St. 

Petersburg, FL. 124 pp. 

Qian, Y., A.E. Jochens, M.C. Kennicutt II, and D.C. Biggs. 2003. Spatial and temporal 

variability of phytoplankton blooms and community structure over the continental margin 

of the northeast Gulf of Mexico based on pigment analysis. Continental Shelf Research 

23:1–17. 

Douglas Biggs is a Professor of Oceanography at Texas A&M University. In addition to his 

service as a co-PI on DGoMB, Biggs was a co-PI on MMS-sponsored NEGOM-COH and 

GulfCet-II projects and he is presently working to define the oceanographic habitat use by 

cetaceans in the NE Gulf of Mexico as part of an interagency MMS-ONR-NSF study known as 

the Sperm Whales Seismic Studies program (SWSS). 

Chuanmin Hu is a research scientist and Executive Director of the Institute for Marine Remote 

Sensing (IMaRS) at the College of Marine Science University of South Florida. He has 
42 

participated in the NASA sponsored SIMBIOS and MMS-sponsored NEGOM projects. He is 

working on ocean color remote sensing in coastal waters and is principal investigator on several 

NASA and USGS funded projects. 

Frank Müller-Karger is Professor and Director of IMaRS at the College of Marine Science, 

University of South Florida. Müller-Karger’s research focuses on primary production in the sea, 

and he uses remote sensing (ocean color, SST, SSH) to study the importance of continental 

margins, including areas of upwelling and river discharge in the global carbon budget. 
43 

GEOLOGY 

William Bryant, Texas A&M University 

The deep Gulf of Mexico (GOM) surface sediment that affects the deep-living biota is composed 

for the most part of terrigenous lutite. A carbonaceous sand fraction, composed of pelagic foram 

tests, can reach 20 to 30% by weight at eastern sites on the Florida margin but remains below 

10% west of the Mississippi Cone. Deep sites on and below the Sigsbee and Florida Escarpments 

are often etched by deep furrows the size of buses. These furrows are parallel to the bathymetry 

and are or have been formed by strong currents, presumably, although direct evidence for this is 

as yet lacking. Intermittent meso-scale (5 to 10 km diameter) basins and mounds are the product 

of halokinesis, or the remolding of subseafloor salt deposits. These basins may create unique 

habitats for benthic biota by trapping sedimenting POC. Some are characterized by hydrocarbon 

seeps. No evidence exists thus far that such basins without seeps contain any sort of peculiar 

faunal assemblages. An effect of small-scale topographic variation within the basins on 

biological distributions has yet to be established, but ought to be considered in future studies. 

Vertical profiles of sediment physical properties appear to vary between sites across the entire 

northern GOM. It is suggested that the variability of shear strength within cores is directly 

proportional to bioturbation intensity. 

Dr. William Bryant is the Enron Professor in the Department of Oceanography at Texas A&M 

University, College Station, TX. He recently initiated a program in archaeological oceanography 

in collaboration with the Institute of Nautical Archaeology and the Department of Anthropology 

at Texas A&M. 
44 

CONTAMINANT CHEMISTRY: POLYCYCLIC AROMATIC HYDROCARBONS (PAH) 

AND TRACE ELEMENTS 

Terry L. Wade, Gary A. Wolff, and Bobby J. Presley, Texas A&M University 

 

Introduction 

The concentrations of polycyclic aromatic hydrocarbons (PAH) and trace elements were 

determined for the surface (top 2 cm) sediment samples collected from the Gulf of Mexico 

(GOM) on DGoMB cruises 1, 2, 3a, and 3b. These samples represent 50 stations. Some of the 

trace elements determined are known to be major constituents of drilling fluids (Ba, Cr), others, 

such as antimony, arsenic, beryllium, cadmium, copper, lead, manganese, mercury, 

molybdenum, nickel, silver, tin, thallium, vanadium, and zinc are of environmental concern. In 

addition, aluminum, calcium, iron and silicon were determined to facilitate recognition of 

sediment trace metal natural variations, differences in sediment texture and mineralogy. All PAH 

and trace element analyses had acceptable spike recoveries and acceptable results for standard 

reference materials which validate the analytical results. 

Results and Discussion: PAH 

PAH are major toxic components of petroleum. The sources of PAH to offshore sediments 

include natural petroleum seepage, production platform operations, atmospheric deposition and 

spills. Previous studies of production platforms indicate that the sediments close to the platform 

(<500m) contain elevated concentrations of PAH and selected trace elements (Ag, Ba, Cd, Hg, 

Pb, and Zn). PAH and trace elements at the platform sites were below concentrations expected to 

cause biological effects in biota. None of the sites reported here were within 500 m of any 

platforms. Concentrations for total PAH ranged from not detected (ND) to 1,033 ng/g with a 

mean of 140 ng/g. Some sites were sampled and analyzed as replicates from one cruise. Some 

sites were sampled during more than one cruise. 

Perylene is a PAH produced by biological processes as well as by combustion. Perylene is often 

detected as the major PAH in sediments from relatively pristine areas. In the sediment samples 

analyzed for this study, the percentage of perylene of total PAH ranged from 0 to 63%. Perylene 

concentrations ranged from ND (<1 ng/g) to 110 ng/g with a mean of 17 ng/g. Other PAH are 

predominantly from anthropogenic sources. The geographic pattern of perylene concentrations is 

complex, and it does not co-vary with the total PAH distribution. The six (6) highest perylene 

concentrations are at sites S26, MT1, C1, B2, NB4, and RW6. These sites are found through the 

sample area with no discernable geographic pattern. 

Sites with higher concentrations of total PAH include MT1, MT3, and C1. These sites, based on 

their PAH distribution, can be divided into two types of sites with PAH predominantly from oil 

and those with PAH predominantly from combustion sources. For sites MT1 and MT3, oil 

appears to be the major source of PAH. For C1, combustion sources predominate. Combustion 

PAH in the sampling area may be discharged from ships or platforms (e.g., bilge pumping) or 

come from atmospheric deposition of PAH from onshore industrial areas or sediments 
45 

transported from coastal areas. The ship/platform operations are the most likely sources as 

atmospheric deposition would be expected to produce similar PAH concentrations over large 

regions. The geographic distribution of PAH indicates a possible input from PAH in transported 

sediments from the Mississippi River. 

When the frequency distributions for total PAH found in this study are compared to those for 

near shore studies (NOAA NS&T and EPA-EMAP-NC), the median PAH concentrations for this 

study are lower by about a factor of four. Total sediment PAH concentrations greater than 4,000 

ng/g are expected to elicit a biological effect 10% of the time (Long and Morgan 1990). The 

highest total PAH concentration found in sediments from this study (1,033 ng/g) is four times 

less than the biological effects level. Therefore, it is unlikely that the PAH at any of these sites 

are having a major effect on the associated biota. 

Results and Discussion: Trace Elements 

The sedimentation rates at the abyssal plain Gulf sites, as well as the source, mineralogy, and 

grain size of the sediments there, are different from those at the continental shelf and slope sites. 

For this reason, trace element data for these two areas are discussed separately. Average 

concentrations of the potential contaminant metals Ag, Cd, Cu, Hg, Pb, and Zn in the shelf and 

slope samples are similar to average crustal abundances and to average values for areas of the 

northern Gulf of Mexico thought to be low in anthropogenic metals. Average values are not the 

best way to evaluate this data due to the relatively small number of samples and the considerable 

variability in the data. It is better to consider the slope of a best-fit line through the data for each 

element versus Al or Fe scatter plot. Either Al or Fe can be used to normalize trace metal 

concentrations in these samples, as these two elements exhibit a strong co-variance. Trace metal 

concentrations strongly co-vary with Al and Fe in “normal” sediments. Data points that fall 

above a best-fit line on these plots imply anthropogenic influence or some mineralogy or 

biogeochemical processes. 

When concentrations of several elements in the DGoMB continental shelf and slope samples are 

plotted against Al, most data points are close to a best-fit line and have almost the same slope as 

plots for Mississippi River Delta sediments. This is expected because the Mississippi River is the 

most likely source of most of the silicate fraction of the sediments at these sites. A good line fit is 

found for Be, Co, Cr, Fe, Si, Tl, V, K, Mg and Zn, all of which have positive slopes on the metal 

versus Al plots and for Ca and Sr, which have negative slopes. Thus, for these metals there is no 

indication of additions from human activity or other geochemical processes. Rather, the metal 

concentrations in a particular sample are a function of the relative amounts of trace metal rich 

Mississippi River derived silicate material and trace metal poor plankton derived carbonate in the 

sample. The interpretation is more complicated for the elements Ni, Pb, Cd, As and especially 

Cu whose concentrations show considerable scatter on the metal versus Al plots. Furthermore, 

the slopes suggest a general enrichment in these elements of 25 to 50% over Mississippi River 

derived material. 

Concentrations of Mn are more variable and much more elevated over Mississippi Delta material 

than are concentrations of any of the other elements. It is very unlikely that this observed Mn 
46 

enrichment is due to human influence. Rather, it is likely the result of remobilization of Mn from 

depths in the sediment column where reducing conditions exist. The Mn released at depth 

diffuses up through the sediment column and re-deposits in near-surface sediment when it 

encounters oxidizing conditions. This phenomenon has been well documented for northern GOM 

sediments (Trefry and Presley 1982). Other metals have been shown to respond to the same 

remobilization and precipitation process that affects Mn (e.g., Presley et al. 1992) and it seems 

likely that these processes are functioning in the DGoMB area. Even though there is not a strong 

correlation between Ni, Pb, Cd and Cu concentrations and Mn, it seems likely that all have been 

affected by similar biogeochemical processes. The variable between these metals may result 

from intensity of reducing conditions at the different sites and by differences in the amounts of 

available sulfide, which would more readily precipitate some metals than others. 

In contrast to the elements discussed above, barium (Ba) concentrations at selected sites are 

higher than those of average clay-rich sediments but are typical of sediments from near oil well 

platforms in the northern Gulf of Mexico. In the case of Ba, it seems likely that the enrichments, 

as high as a factor of ten, are due to disposal of oil well drilling mud. Drilling mud can contain 

90 % Ba (Boothe and Presley 1985). Thus, small amounts of mud could account for the Ba 

enrichments seen in the sediments. The Ba-enriched samples are from the three shallowest water 

sites in the Mississippi Trough (sites MT1, 2 and 3) and from site C1 and WC5 just to the west 

of these. All are in an area of intense petroleum exploration and development. Previous studies 

have found even greater enrichments of Ba near drilling platforms (e.g., Boothe and Presley 

1989). Even at the most Ba-enriched sites in the present study, the concentration is well below 

that thought to adversely affect organisms (e.g., Neff et al. 1989). 

The four abyssal plain sites sampled in this study were widely separated geographically. These 

deep water samples were typically about 10% Ca (mostly from CaCO3) compared to the 1% Ca 

in shelf sediments. This additional CaCO3 diluted the clay in these sediments, resulting in a 

reduction in Fe and Al concentrations. There was considerable variation in the concentrations of 

the major elements, Ca, Fe. Al and Si, between sites and between replicate cores at a given site 

showing the “patchiness” of surface sediment lithology (i.e., CaCO3 content) in the deep Gulf. 

Nickel, and especially Cu and Mn concentrations are higher in the deep Gulf samples than would 

be expected for shelf samples with equivalent Fe and Al concentrations, but this was not true for 

Cr and Zn. One could propose that the carbonate phase of these deep samples is enriched in Cu 

and Mn, but it seems more likely that these metals have been mobilized by reducing conditions 

at depth, have migrated up through the pore water, and been re-oxidized and precipitated in the 

near surface sediments resulting in an enrichment there. This is the same process that affected 

some slope sediments, as was discussed above. 

Silicon and Ti in the deep samples have been diluted by the added carbonate by about the same 

percentage that Fe and Al have, as would be expected. Strontium is much higher in the deep 

samples, again as would be expected based on the carbonate content. However, Mg does not 

seem to be enriched. The carbonate in these deep samples is about 5% Sr except for anomalously 

low Sr at site S1. We have no explanation for the low Sr values or the lack of Mg enrichment but 

assume it is related to the type of carbonate present at the different sites. 
47 

Summary 

The concentrations of PAH measured for the DGoMB project from offshore sites are low, as 

expected. Perylene, a PAH with a biogenic source, is the major PAH detected at many locations 

indicating a biological origin. Sites that have higher PAH concentrations (MT3, MT1 and C1) 

also have high barium concentrations. This indicates that drilling operations in the vicinity of 

these sites is one likely source of PAH. Total sediment PAH concentrations at all sites were less 

than 1,033 ng/g. It is unlikely that the PAH concentrations found at any of these sites would have 

a major adverse effect on the biota living in these sediments. The carbonate-rich deep Gulf 

(abyssal plain) samples collected on DGoMB differ in metal concentrations from the clay-rich 

shelf and slope samples. However, there is no indication that these deep sediments have been 

affected by human activity. Rather, natural depositional and biogeochemical processes are 

responsible for the differences found. The shelf, slope, and abyssal plain samples analyzed for 

this project were a mixture of carbonate and terrigenous silicate materials and thus varied 

considerably in major element (aluminum, calcium and iron) concentrations. Trace metal 

concentrations also varied considerably, as would be expected with a varied mineralogy. In the 

shelf and slope samples, concentrations of the elements Al, Ca, Sr, Na, K, Mg, Be, Co, Hg, Cr, 

Ti, V, and Zn were normal for coastal Gulf of Mexico sediments with equivalent Fe 

concentration. Copper, As, Cd, Pb, Ni and especially Mn concentrations were found to be 

somewhat higher than those in Mississippi Delta and shallow GOM samples but were not 

unexpectedly high considering the deeper water from which the present samples came. The 

enrichments are likely due to complex natural transport and biogeochemical processes, not to 

human activity. The strong Ba enrichments of up to almost a factor of ten in a few samples are 

likely due to the presence of residues of oil well drilling muds discharged from the many drilling 

platforms in the area. Based on literature data, none of the metal concentrations in the study area 

sediments are high enough to adversely affect marine organisms. 

References 

Boothe, P.N. and B.J. Presley. 1985. Distribution and behavior of drilling fluids and cuttings 

around Gulf of Mexico drilling sites. American Petroleum Institute, Washington, DC. 

140 pp. 

Boothe, P.N. and B.J. Presley. 1989. Trends in sediment trace element concentrations around six 

petroleum drilling platforms in the northwestern Gulf of Mexico. In: Proceedings, 1988 

International Conference on Drilling Wastes, Calgary, Canada, 5–8 April. Pp. 3–21. 

Long, E.R. and L.G. Morgan. 1990. The Potential for Biological Effects of Sediment-Sorbed 

Contaminants Tested in the National Status and Trends Program. NOAA Technical 

Memorandum NOS OMA 52. Seattle, WA: U.S. Dept. of Commerce, National 

Oceanographic and Atmospheric Administration. 215 pp. 

Neff, J.M., R.J. Breteler, and R.S. Carr. 1989. Bioaccumulation, food chain transfer, and 

biological effects of barium and chromium from drilling muds by flounder 

(Pseudopleuronectes americanus) and lobster (Homarus americanus). In: Engelhardt, 
48 

F.R., J.P. Ray, and A.H. Gilliam, eds. Drilling Wastes. London: Elseveir Applied Science 

Publishers. Pp. 439–460. 

Presley, B.J., R.J. Taylor, and P.N. Boothe. 1992. Trace metal concentrations in sediments of the 

eastern Mississippi Bight. Marine Environmental Research 33:267–282. 

Trefry, J.H. and B.J. Presley. 1982. Manganese fluxes from Mississippi Delta sediments. 

Geochimica et Cosmochimica Acta 46:1715–1726. 

Dr Terry L. Wade received his Ph.D. in oceanography in 1978 from the University of Rhode 

Island. Dr Wade is the Deputy Director for Environmental Sciences with the Geochemical and 

Environmental Research Group and an Adjunct Professor in the Oceanography Department at 

Texas A&M University. 

Dr. Gary A. Wolff and Dr. Bobby J. Presley have recently retired from their positions at Texas 

A&M University. 
49 

BIOGEOCHEMISTRY OF THE NORTHERN GULF OF MEXICO SEDIMENTS: 

A COMPONENT OF THE DEEP GULF OF MEXICO BENTHOS (DGoMB) PROJECT 

John Morse, Texas A&M University 

A wide variety of related biogeochemical features were measured in association with the 

DGoMB project. Solid phase and pore water constituents included organic carbon and nitrogen, 

DOC, inorganic nutrients, DIC, stable carbon isotopes, and terminal electron acceptors iron, 

manganese, sulfate and sulfide, oxygen and nitrate/nitrite. Organic carbon varied from a fraction 

of a percent on the abyssal plain to just over 1% in the Mississippi Trough, which is a 

remarkably small range. Lower values were encountered in the sandy sediments in the eastern 

region than in the central area adjacent to the Mississippi River outflow. Population densities of 

bacteria, meiofauna and macrofauna correlated with organic carbon in the sediments. Oxygen 

penetration depth into the sediments (OPD) was minimal in areas of high biomass (Mississippi 

Trough) near shore but extensive in deep water offshore (abyssal plain), reflecting low 

respiration rates in areas with low organic enrichment. Sulfate reduction was not encountered at 

any site. Manganese reduction was observed in the Mississippi Trough on the upper slope, but 

nowhere else. Bioturbation rates, measured using radionuclide tracers, correlated with 

macrofaunal biomass. Sediment oxygen consumption, measured with a free-vehicle lander 

carrying incubation chambers, declined exponentially with water depth. 

John Wilbur Morse was born in Fort Dodge, Iowa. His education included a B.S., Institute of 

Technology, University of Minnesota (geology) , and an M.S. and Ph.D. from Yale. He served 

on the faculties at the University of Miami and Florida State University prior to joining Texas 

A&M. He is an Associate Editor of Marine Chemistry and the Editor-in-Chief Aquatic 

Geochemistry. His research interests include application of chemical thermodynamics, surface 

chemistry, and chemical kinetics to the study of natural waters and sediments; sedimentary 

biogeochemistry of carbonate and sulfide minerals; chemistry of trace metals in anoxic 

sediments; benthic fluxes; mechanism of vein filling of fractures and carbonate reactions in the 

subsurface, chemical evolution of early oceans on Earth and Mars. 
50 

SEDIMENT BACTERIA ABUNDANCE, BIOMASS, RESPIRATION AND 

PRODUCTION: NORTHERN GULF OF MEXICO CONTINENTAL SLOPE 

AND ABYSSAL PLAIN 

Jody Deming and S. Carpenter, 

School of Oceanography, University of Washington 

Bacteria were sampled from replicate box cores during the Deep Gulf of Mexico Benthos 

(DGoMB) studies in order to map distributions as a function of water depth, physiographic 

features, and sediment biogeochemical properties. Counts of living bacteria were made in the 

sediments using a combination of acridine orange and DAPI stains. As a result, the densities of 

bacteria in surficial sediments can be mapped across the entire area. Highest numbers were 

encountered in the upper Mississippi Trough and the De Soto Canyon. Surprisingly, there was no 

statistically significant relationship with depth, when all the data were lumped together, due to 

high densities on the abyssal plain. At the six process sites, incubations were conducted using 

C-14 labeled dissolved free amino acids at in situ temperature and pressure to determine uptake, 

respiration and production as a function of depth in the sediments. Production was also measured 

using tritiated thymidine incubations. 

Bacterial biomass was the highest of all the living components of the benthos at all sites, and the 

relative importance of the bacteria relative to the invertebrates increased with increasing depth 

and distance from shore. This high biomass suggests that the bacteria function as an important 

intermediate between relatively unreactive organic detritus in the sediments and the metazoans at 

higher levels of the food web. Because the respiration and production rates for the bacteria 

measured experimentally using tracers were considerably below the entire sediment community 

oxygen consumption (based on in situ chamber incubations), the role of the bacteria in organic 

matter cycling in deep-sea sediments however remains equivocal. 

Dr. Jody Deming grew up in Houston on the outskirts of River Oaks. She did her undergraduate 

work at Smith College in Springfield MA and her Ph.D. under Dr. Rita Colwell at the University 

of Maryland. Following post-doctoral work at Scripps with Dr. Art Yayanos, she took a position 

on the faculty at the University of Washington, where she is now a Professor in the School of 

Oceanography. Her ground-breaking work on bacterial processes in extreme environments led to 

her election to the National Academy of Sciences in 2003. 

Ms. Shelly Carpenter is an accomplished researcher who has worked with Dr. Deming for more 

than a decade. 
51 

SESSION 1C 

OFFSHORE OIL ORAL HISTORY PROJECT 

Chair: Harry Luton, Minerals Management Service 

Co-Chair: Kimberley Cook, Minerals Management Service 

THE OFFSHORE OIL AND GAS HISTORY PROJECT: INTRODUCTION TO THE 

SESSION Harry Luton and Diane Austin ................................................................................... 53 

TERREBONNE PARISH AND THE OIL SERVICE INDUSTRY: THE CASE OF 

FLOATPLANE AVIATION James L. Sell................................................................................. 56 

A SOCIAL HISTORY OF MORGAN CITY Jamie Christy ...................................................... 62 

PLATFORM DISASTERS AND CHANGING INDUSTRY MINDSETS OF HEALTH 

AND SAFETY ISSUES Tyler Priest........................................................................................... 65 

WOMEN IN THE GULF OF MEXICO OFFSHORE OIL AND GAS INDUSTRY: 

OVERLOOKED BUT NOT FORGOTTEN Diane Austin......................................................... 73 

USING ORAL HISTORY TO UNDERSTAND IMPACTS ON COMMUNITIES Tom 

McGuire and Diane Austin ........................................................................................................... 77 
53 

THE OFFSHORE OIL AND GAS HISTORY PROJECT: 

INTRODUCTION TO THE SESSION 

Harry Luton, Minerals Management Service, Gulf of Mexico OCS Region 

Diane Austin, Bureau of Applied Research in Anthropology, University of Arizona 

This is the second ITM that included a session on the MMS Offshore Oil and Gas History 

Project, and it will probably be the last since the History Project is nearing conclusion. The MMS 

Studies Program in the Gulf supports many and varied socioeconomic research efforts, but even 

so the History Project is unusual. 

Its budget totals nearly a million dollars, more that twice that of the next largest socioeconomic 

study and five or six times their average cost. Oceanographic and biological studies are 

expensive; socioeconomic ones tend not to be. 

The History Project has also drawn on the efforts of an unusual number of institutions. 

Organizations that have played significant roles include 

• LSU Center for Energy Studies 

• University of Arizona Bureau of Applied Research in Anthropology 

• University of Houston Department of History and History International, LLC 

• ULL Public History Program and Sociology Department 

• Nicholls State Archives 

• Louisiana Technical Colleges 

The History Project is more humanities-oriented than the average socioeconomic study that 

MMS funds; it collects reminisces of individuals rather than data that directly supports economic 

or social analysis. The History Project stresses the collection of information rather than its 

analysis; indeed, it was intentionally designed to collect more than it was budgeted to analyze. 

MMS funds applied research—research that provides information and analysis that supports 

management decisions on the OCS—and while the History Project may be unusual in applied 

socioeconomics, these characteristics express the very reasons the study was funded. 

The offshore petroleum industry is a complex multitude of businesses engaged in finding, 

producing, transporting, and marketing oil and gas from beneath the ocean that make up an 

enormous and dynamic piece of the worldwide economy. However, offshore oil began small, in 

coastal Louisiana, and what it has become is due in large measure to the hard work, 

inventiveness, and entrepreneurship exhibited by south Louisiana residents in adapting landbased activities to ocean environments. This transformation is one of the more poorly 

documented and understood chapters in the history of the industry. This dearth of information 

led the agency to fund the History Project for several reasons: 
54 

• Knowing this history would provide the agency with a better understanding of the types 

and causes of social and economic effects that the industry has had. 

• The study would serve as “scoping” for environmental assessments; the people that have 

experienced the industry would be identifying salient impacts from their points of view. 

• The study would provide a form of “mitigation”; by providing to the public the material it 

collects, it will be giving back to impacted communities a thing of value. 

• The founders of the industry are in their 70s, 80s and 90s. If the information was to be 

collected, someone had to begin soon. 

The fourth reason actually ties the others together and helps explain the History Project’s focus 

on data collection, the earliest decades of the industry, and MMS’s commitment to moving 

forward with adequate support. Although this study, like all agency-funded studies, is applied, 

agency personnel from the top down also saw it as the right thing to do. 

The History Project has been active for almost three years, and during that time it has 

accomplished a great deal. It has emphasized the collection of oral histories. To date: 

• Over 450 people have been interviewed. 

• All interviews are being transcribed. 

• All interviews are being summarized and catalogued. 

These interviews reflect the agency’s applied aims and other concerns. They 

• Focus on 1940s, 1950s, and 1960s 

• Focus on highly impacted communities 

• Include people from a wide range of sectors and companies 

In addition to the interviews, the study team has digitized historic photographs offered by the 

interviewees as well as interviewee descriptions of each. To date: 

• Over 900 digital copies of photos have been collected. 

• A database describing each photo has been developed. 

• Interviews and transcripts to accompany photos have been included. 

While the History Project has focused on these collections, it has a large analytical component as 

well: 

• An interim report of analytical essays is available. 

• A final report is due in the summer of 2005. 

• Conference papers and presentations have been given. 

• Journal articles have been published. 
55 

Finally, the History Project includes a substantial public educational and outreach component. 

The study team and MMS are making efforts to get the word out: 

• A traveling exhibit will open 23 January 2005 at the Southdown Plantation Home in 

Houma, LA. From there it will probably move next to Lafourche. 

• The study team is working in collaboration with National D-Day Museum to archive 

interviews and film interviewees for permanent exhibit on connections between WWII 

and the offshore oil and gas industry. 

• Educational websites and accompanying materials will be completed by summer 2005. 

MMS sees the History Project as providing a valuable resource to the community. All the 

interviews and photos that have been collected include waivers allowing for their noncommercial use. MMS plans to place all these materials into the public domain, in places were 

they will be easily accessible. The agency is proud of what the History Project has accomplished. 

However, one hope has yet to materialize—the hope that the agency’s actions will stimulate 

other institutions to continue this work. For more information go to the following web site: 

www.gomr.mms.gov/homepg/regulate/environ/history_louisiana.html 

Harry Luton was born in Michigan. He received his undergraduate degree from the University of 

Michigan, a master’s degree from the University of Pennsylvania, and his doctorate from the 

University of Michigan. Since 1982, he has worked in MMS’s environmental assessment branch, 

first in Alaska, then Headquarters and, for the last nine years, the Gulf of Mexico OCS Region. 

Diane E. Austin is an assistant research anthropologist in the University of Arizona’s Bureau of 

Applied Research in Anthropology (BARA). She specializes in the development of communitybased participatory research methodologies and coordinates BARA’s internship program. Her 

major interests include environmental anthropology; social impact assessment; environmental 

justice; community development; and research methods and analysis. She began studying the 

impacts of the offshore oil and gas industry on southern Louisiana in 1996. 
56 

TERREBONNE PARISH AND THE OIL SERVICE INDUSTRY: 

THE CASE OF FLOATPLANE AVIATION 

James L. Sell, University of Arizona 

This is a discussion of how the oil industry can affect the historical development of a 

community. My area of operation was Terrebonne Parish, which is very much in the center of the 

Louisiana coastal oil field. Its development is complementary to much of the rest of the area. I 

say complementary, rather than parallel, because of certain distinctive features in its history. 

The most distinctive aspects of Terrebonne Parish were its 

 1. Land base, which was accessible for both land and water transport. 

 2. The large oil fields inshore of the barrier islands, which led to its concentration on 

inshore rather than offshore activities. 

 3. The role of Texaco as the major producer in the parish, which was the major employer of 

oil workers and service businesses. 

 4. The development of a large set of oil service industries that, at first served the inshore 

fields, and later had to adapt from a local to a global business model as inshore gave way 

to offshore production. 

Our primary approach is through oral history, which has some effects on the information 

received. The most evident effect is the creation of “chains of informants” that comes from the 

final interview question—“Who else should I talk to?” One of the clusters of people in our set of 

interviews about Terrebonne Parish happened to be floatplane pilots. This shouldn’t come as a 

surprise, considering the watery nature of the Parish oil fields, but I hope to use the rise and fall 

of the floatplane industry as an example of the way oil-field service businesses needed to cope 

with changes in the industry. 

The view of the early oil fields that comes from the interviews has been one of a free-wheeling 

work environment, in which certain problems arise that need rapid solution, such as the need for 

mud to hold down gas pressure, casing to shore up loose rock strata, and fishing tools to recover 

lost equipment. The oil service businesses develop as people see a need and either adapt an 

existing technology or develop a new one to meet that need. Within that field, some businesses 

succeed and others fail as technologies and conditions change. It is also easy to assert, that to 

some extent, the problems solved in the inshore fields were necessary precursors to the move 

offshore. 

The problem addressed by the aviation industry is the isolation of the oil fields. 
57 

Business Climate 

The climate in which business was conducted was one of 

 1. Remote, Mobile Drilling Sites. Not only were many of the areas isolated, but the drillers 

themselves were on mobile drilling barges, moving along channels dredged in the 

wetlands. 

 2. Dispersed Decision Power. The primary decision maker for drilling business (at least 

before 1980) was the toolpusher at the drilling site. Sales and service people had to 

approach this supervisor directly. 

 3. Money Secondary to Production. The primary need was speed in getting the wells ready 

for production. The high cost of drilling a well meant that any problem that stopped the 

process was expensive; therefore, the toolpusher on the spot had a large budget. 

So as CJ Christ noted, this decision power was a huge responsibility for someone who rose 

through the ranks from roughneck to driller to toolpusher: 

Here’s a guy, a lot of times with no formal education, he got all of his experience 

on the drilling rig ... and he’s got a budget of millions. His basic instruction is to 

go out there and drill that well—“You know the area. You know the problems 

you are likely to encounter. You know the people you can count on. Just go out 

there and drill that well.” That puts a big responsibility on his shoulders because 

now he is lavishly entertained all the time, and there was a lot of profit in this 

business, a lot of profit (Christ 2003). 

Terrebonne Parish is about 60 miles south-southwest of New Orleans. As this land use map 

shows, it’s mostly wetland. The planning department notes that the parish has 8% buildable land 

(dry land) and 92% “environmentally sensitive” land (read waterlogged—marshland, wetland, 

and swamp). 

This is a view of the “landscape” today. Once, much of the area was forested, but now the forest 

is mostly gone, from a combination of over-cutting and saltwater intrusion. This gives a good 

impression of the waterlogged oil field environment and shows why floatplanes were so useful. 

Pilots who were primary informants for the study include: 

• Lloyd Geist. 1945–92. He fell in love with flying after riding with barnstormers who 

came to Houma in 1930. A fighter pilot in Europe during WWII, he returned home after 

the war and set up a charter service and flying school in Houma in 1946. Lloyd is the 

dean of floatplane pilots. He was one of the first to replace wheels with pontoons and 

qualify himself as a floatplane pilot, because nobody else had any experience when he 

started. He started the first seaplane base in Houma in 1950. 

• CJ Christ. 1956–89. He was a Korean War B-29 pilot. He worked as a mud engineer for 

Magnet Cove Barium until they found a need to train mud engineers as pilots to make 
58 

their rounds easier; so he worked as Chief Pilot for them until 1964. Then he opened 

Houma Aviation Services at the Houma Airport from 1964–89. Caught in the 80s Bust, 

he stayed in operation long enough to pay off his debts. Then he closed down the 

business and went to work as a boat captain at age 61. 

• Charlie Hammonds. 1956–. The son of an oil worker, he started working for Lloyd Geist 

in the 1950s, washing planes. He soon graduated to pilot status and opened Hammonds 

Air Service. His company grew to the point that it was running a passenger service to oil 

towns along the Gulf as well as providing basic oil field service—checking pipelines, 

flying personnel and needed equipment, collecting reports. Charlie was able to survive 

the 80s Bust and now runs a scaled-down charter service. The other pilots cite Charlie as 

the most experienced floatplane pilot in Louisiana, and possibly in the United States. 

• Ken Perry. 1976–. He started as a “flying salesman” in the 1970s. After years of sales 

work, he “went pro” and opened an operation at the Patterson Airport. 

In the early days (oil was first discovered in Terrebonne Parish in 1928), it became obvious that 

seaplanes were needed to allow quick access to the oil fields. Texaco set up an airstrip for 

amphibious aircraft (or “flying boats”) about 1934. This would later become the Houma Airport. 

Since the flying boats landed on land or water, they were well suited for the district 

superintendent to use to check on his far-flung drillers. Lloyd Geist noted the first plane Texaco 

based at Houma was a Vintage Keystone, which was a biplane attached to the top of a boat. Later 

would come the Goose and Mallard flying boats, used for transporting managers. 

The real progress came after Geist put pontoon floats on a light Cessna and opened his seaplane 

base on the Gulf Intracoastal Canal. The floatplanes opened up access to people doing sales and 

service calls. Now they could cover a large area quickly: 

My first flying job in 1976 was a floatplane and I was a salesman. I flew out to 

production facilities and drilling facilities inshore along the Mississippi River 

down to the mouth of the River and the bays along the coastline and sold 

chemicals, treating chemicals for wells and cleaning chemicals and we did 

compressor valve repairs and starter repairs on these big compressors that 

compressed the gas... You used your seaplane like a pickup truck (Perry 2003). 

Flying in the wetlands was a challenge in many ways, including taking off on the busy 

Intracoastal Canal. But these floatplanes had no fixed landing strip, had to land on the water in 

all sorts of directions, and had to yield right of way to all sorts of heavy shipping. Naturally, the 

floatplanes had no brakes and had to stop in the water by colliding with their target. It required a 

special set of operations and a real sense of judgment and timing: 

Well, you’ve got currents to contend with. A lot of times you’ve got to land cross 

wind. A lot of time you have to land down wind. You don’t have a choice, you 

know? And then tying up ... to these drilling rigs and barges and boats. So you 
59 

had to know time, when to stop the engine. But you had to hurry. Get out on the 

float and go hold it off so you didn’t bang into something. And to catch and be 

able to tie to whatever you were going to moor to. Cross winds and currents I 

guess were the biggest thing in the water. Rough water and smooth is all different 

(Geist 2003). 

Clearly, the floatplanes were out-muscled by the drilling barges and practically anything else on 

the water. This led to a lot of damage to the aircraft, as the planes were often battered by wind 

and current. Ken Perry mentioned the hard use of the aircraft: 

The big part, the hard part about the floatplanes is the docking and undocking, 

especially if you are a salesman and you are by yourself most of the time. Planes 

want to weather-vane into the wind and you are always banging wing tips and 

running into something. So they are not very pretty after they have been worked 

for a while. They are good tough airplanes, but you’d beat the hell out of them 

(Perry 2003). 

At the peak, in the late 70s it was estimated that there were about 400 floatplanes operating in 

southern Louisiana, 90 in Houma. A decade later, 90% of them were gone. Charlie Hammonds 

made this comment: 

In the heyday, I speak of the heyday being especially during the mid 70s for us, 

we had nine float planes. There were 90 float planes, 90 float planes based here in 

Houma and just to give you a comparison, now we have three; we really need 

two. And there are only seven seaplanes left here in Houma as we speak. So it 

went from 90 down to seven. So it just gives you an idea of the dramatic 

downturn in the industry as it pertains to us (Hammonds 2002). 

The Bust came in the early 1980s as Texaco sold off inshore to go offshore, and an oil glut 

dropped prices below $10 per barrel. Like many other oil businesses, the aviation industry was 

over-leveraged and hit hard. Charlie Hammonds had expanded greatly and was caught by 

surprise: 

I had built this particular facility here at a cost of about $750,000. I built that 

hangar next door for a couple of hundred thousand. I bought some very expensive 

airplanes to run the commuter because we just had such a demand. I can 

remember and I questioned myself as I look back on my life, you know, buying 

brand new airplanes, paying an interest rate of something like 23%, but the 

demand was just, was there. And it was the most phenomenal thing that I could 

ever see or could ever imagine. It was just, everything was just blow and go and 

we, like everybody else in Houma, thought it would continue for a long time and 

when it stopped, it was like turning a valve off. And I know in our own business 

where we made a lot of money in one year, we just, we lost $2–3–4 million and 

we are a small operator (Hammonds 2002). 
60 

While the general downturn was terrible for all businesses, the floatplane aviators were 

not able to recover along with everyone else because they could not operate in the Gulf 

itself. The sea outside the barrier island was too rough to land and take off, and even so, 

tying onto the high steel offshore platforms would hammer the plane to pieces. The rise 

of the helicopter really dates from the shift to offshore and the building of helipads right 

on the platforms. 

Hammonds and Perry weathered the downturn and have scaled down operations. Geist had 

retired by then, and Christ closed his company by 1989. At age 61, CJ went back to work as a 

boat captain; his love for the sea was as big as his love of the air. 

Besides making the inshore oil rigs accessible, the low price of the floatplanes made it possible 

for people to go into business without a major investment. This is indicative of one of the major 

qualities of oil work in this pioneering period: People without major financial backing could go 

into business for themselves and make a success of it. As Perry noted, floatplanes were more cost 

effective than helicopters: 

So it was you could buy ten float planes for what you could buy 1 helicopter .... 

You could set up a pilot and usually you got a plane, a company car, an expense 

account and then the whole thing, even if you bought a brand new airplane, you 

probably had less than $75,000 invested in it in the first year. And it didn’t take a 

lot of sales to get that money back from that and so that was, a small company 

could compete with a big company back then. You know, you could level the 

playing field pretty well (Perry 2003). 

The shift away from floatplanes was a shift toward more expensive helicopters, with insurance 

and maintenance needs that required professional training. Most helicopter pilots are trained by 

the military because of the great expense. The cost really required corporate backing, so 

businesses like PHI (Petroleum Helicopters Incorporated) are listed on the New York Stock 

Exchange and have a very sophisticated maintenance and traffic control system. 

The floatplanes’ heyday of is over. But an examination of their history really shows their 

function. While the drilling barges enabled the oil drillers to spread out and drill quickly over a 

wide area of operation, the floatplanes served as the glue that held that field of operations 

together: 

 1. They provided the ability for sales and service personnel to move rapidly around the 

work area. 

 2. They provided critical communications between the field and the district headquarters–

picking up drilling and production reports, well logs, and survey information. This, in the 

days when radio was the only other way to maintain information exchange. 

 3. They moved personnel and key pieces of equipment back and forth, far more quickly 

than possible by boat. 
61 

 4. And they formed a link in the informal communication between workers and between 

workers and their families back home. Charlie Hammonds is especially known for flying 

passengers back for free, if he had an extra seat. This is a critical function in building a 

sense of community in the oil fields. 

We can see the floatplane aviators creating a niche in the oil industry that was later taken up by 

the helicopters when the industry moved offshore. The floatplanes, then, were a necessary step in 

the development of oil field aviation. 

We can also see that they represented a time when oil field operation was more informal and the 

playing field was more level than is the case today. A person could buy an airplane, learn to fly it 

at a reasonable cost, and use these skills to enter oil work without taking on a major debt burden. 

This person was, more often than not, a salesman or service specialist rather than a professional 

pilot. 

The history of oil development can be seen as a set of puzzles that needed solutions. The 

problem-solvers often created businesses to sell their solutions. In this case the early isolation of 

the oil fields was offset by the floatplane aviators. Now the wide spread of the offshore platforms 

is offset by the helicopter aviators. The technology is different, but the need is much the same. 

James Sell received a Ph.D. in geography, with a minor in psychology, from the University of 

Arizona in 1983. He has been engaged in teaching, research, and planning consulting in the 

geography and landscape architecture programs at the University of Arizona. He was engaged to 

work on the BARA/MMS Oil History Project in 2002. He is currently teaching geography and 

planning at Northern Arizona University. Interested in public perception and landscape, he has 

published work on the Mt. St. Helens eruption, landscape perception, and perception of 

environmental change. 
62 

A SOCIAL HISTORY OF MORGAN CITY 

Jamie Christy, University of Houston 

Although most people think of Morgan City, Louisiana as strictly a twentieth-century boom-andbust oil town, the city has a long history whose cumulative impacts prepared it for the arrival of 

the petroleum industry. It is important to recognize that past not only for historical reasons but 

also because the aggregate of these past events laid the groundwork for the eventual entrance and 

predominance of the oil industry. 

Morgan City’s location at the mouth of the Atchafalaya River and the Gulf of Mexico (GOM) 

and as the western terminus of the New Orleans Opelousas Great Western Railroad (NOOGW) 

has always been a determining factor in its evolution. This terminus was the reason for the Union 

invasion of 1862. The Federals, dubbing this area the land of milk and honey, determined early 

on to take Morgan City (then named Brashear for a local sugar planter of Dr. Brashear) and close 

off and destroy the potential of its vast sugar cane plantations, railway, and port, as part of 

Winfield Scott’s Anaconda plan to “strangle” southern resistance. 

After the Civil War, the large plantations held by a few wealthy families for centuries were 

broken up and sold off to former Union soldiers and land speculators. Northerners like Cornelius 

Vanderbilt and Charles Morgan realized the town’s potential and invested in rail lines and 

steamship ports in the area. Morgan spent over $2 million to improve the NOOGW, and also 

dredged a deeper channel through the Atchafalaya Bay to accommodate his fleet of steamboats. 

Brashear, forced to rely on the capital of outsiders, was renamed for the Connecticut-born 

Morgan in 1876. Many locals noted that Morgan rarely set foot in the city that bore his name and 

gave nothing to the town in the way of a park, public building, or large donation. Indirectly, 

however, he was the community’s benefactor since the enterprises in which he engaged to earn a 

fortune for himself also made the area a booming port and rail city and laid the groundwork for 

future growth and development. 

Following the war and the southern defeat, Morgan City’s residents, now lacking material wealth 

and rapidly losing their farms and plantations, relied on hunting and trapping for survival. Local 

hunters and trappers began to leave their homes and families for extended periods to go into the 

swamps to procure the animals that were their livelihood. They were accustomed to hard work 

and to spending the majority of their time outdoors. These men possessed a thorough knowledge 

of the swamps, bayous, and rivers. They could navigate south Louisiana’s treacherous waterways 

and currents and understood the severe storms and fog that often bewildered foreign captains and 

swallowed unsuspecting vessels. 

At the turn of the century, timber became Morgan City’s main industry. Logging, like hunting 

and trapping, was rough work and required workers to spend extended periods of time away 

from home. Those who felled trees for the lumber mills usually lived out in the swamps and 

marshes and only returned to their families on their off-time. The lumber industry was 
63 

dangerous, and laborers in the swamps and in the mills lost fingers, toes, arms, and legs, and 

work-related deaths were not uncommon. The men who worked for the lumber companies were 

denied insurance, workmen’s compensation, or any sort of retirement. They lived in camps or on 

boats, were paid in script, and were forced to shop at the company store. Labor unions were 

strongly discouraged and none were ever able to successfully organize in Morgan City. 

Lumber companies bought up large tracts of land at an incredible rate, again concentrating the 

land in the hands of a few. Thus, companies like Norman-Beaux, Waddell-Williams, and 

Brownell and Drews acquired huge amounts of property along the water, and this land ultimately 

proved to be some of the area’s richest oil fields. 

Two of Morgan City’s largest landowners, Hugh and Byrnes Young, who had been leasing 

acreage to the lumber mills, realized the industrial potential of their bayou-side property and 

offered their land for use during both world wars. The federal government was particularly 

interested in Morgan City’s excellent port facilities during World War II. The United States 

government awarded it lucrative government contracts to build war vessels for the United States 

Navy. The defense industry began to pour money into Morgan City during the 1940s and when 

Chicago Bridge and Iron Works constructed dry docks on Bayou Boeuf, the town was 

established as a fabricating area. 

In the late 1930s, another industry began to take hold in Morgan City when large quantities of 

shrimp were discovered off of Louisiana’s coast. Morgan City’s citizens and administration 

realized that the increased channel traffic that resulted from this booming industry warranted a 

re-dredging of the channel and convinced Congress to declare this an emergency project. The 

work was completed in 1940. 

In the 1940s there was a huge influx of families from the east coast determined to take advantage 

of the new deep-sea shrimping industry that had emerged in south Louisiana. These new 

shrimpers combined with the workers who moved to the community to man the dry docks for 

Chicago Bridge and Iron caused a housing shortage in this area bounded by water and strained 

Morgan City’s inadequate municipal facilities. The city was forced to expand west into Berwick, 

Bayou Vista, and Patterson and east to the Bayou Boeuf and Amelia. Roads were paved, bridges 

were constructed, public services improved, and the channel dredged ever deeper. 

The interviewees that were chosen for this project are representative of the preceding aspects of 

Morgan City’s history. They are the descendants of sugar planters, farmers, and ex-slaves 

displaced after the Civil War. They were hunters, trappers, and shrimpers, who grew up on the 

water, some speaking French as their first language and some still unable to read or write at the 

time of their interview. They were former cypress mill employees, welders, and World War II 

veterans. These men had toiled under the toughest of conditions with poor treatment and 

compensation at their various occupations and were happy to have the work the oil companies 

provided. Locals like Jerrel Frederick, whose father had been the foreman at Norman-Breaux 

Lumber Company and who also worked at the mill and then served with Patton’s Third Army, 

were overjoyed at the opportunities the oil industry provided. They could not believe their luck 
64 

to receive benefits, insurance, and retirement plans. Interviewees like Richard Davis and John 

Written proudly called themselves “Texaco men” and “Shell men” while loyal employees like 

Rene Seneca and Alden Vining remembered driving miles out of their way to buy gas at their 

Texaco or Shell station. 

With the entrance of companies such as the Texas Company, Shell, Humble, Mobil, Gulf, 

Phillips, Sun, Kerr-McGee, and many others, local men continued to traverse the swamps, 

bayous, and eventually the GOM to seismograph, haul pipe, and drill wells. As the work moved 

offshore, they converted shrimp boats to crew boats and guided, serviced, and played host to the 

companies in ever deeper water. A few Morgan Citizens like Parker Conrad, Victor Guarisco, 

and Red Adams made fortunes with service companies that they started from nothing. Most of 

the locals, whether successful service company owners or roughnecks, viewed the coming of the 

oil companies as the best thing that could have happened to Morgan City. 

The arrival and success of the oil companies in Morgan City cannot be taken out of historical 

context; the lens of history is vital to understanding the industry. The southern defeat and 

removal and redistribution of the lands of the great sugar planters, the expansion of the port and 

railroad by investors like Morgan and Vanderbilt, the loss of control over the economy by local 

residents, the knowledge gained of the waterways and boats by trappers and shrimpers, the 

acclimation to difficult and dangerous industrial work gained from working at Chicago Bridge 

and Iron and the cypress mills, the inability of labor unions to organize in the area, the 

consolidation of lands in the hands of a few lumber mill owners, the population booms of the 

1930s and 1940s due to shrimping and industry that led to the eastward and westward expansion 

of Morgan City, the appreciation that men who had been exploited by the lumber mills felt at 

being treated fairly by the oil companies, and the optimism that local rags to riches stories gave 

to the community are all vital to understanding the oil industry in this area. 

The oral histories of these successful businessmen, geologists, and engineers, combined with 

those of seismic crews, drillers, gaugers, roustabouts and roughnecks, and their wives are 

important because they represent the cumulative history of Morgan City in particular and the oil 

industry in general. The memories and stories that they have shared with this project are the 

history of oil in southern Louisiana. 

Jamie Christy is a native of Morgan City, Louisiana. She received her undergraduate degree at 

Louisiana State University and is pursuing her doctorate at the Graduate Studies in History 

Department of the University of Houston. Her current interests focus on Mexico’s oil industry 

and U.S. expatriate workers and companies involved in that industry. 
65 

PLATFORM DISASTERS AND CHANGING INDUSTRY MINDSETS OF 

HEALTH AND SAFETY ISSUES 

Tyler Priest, Director of Global Studies, 

C.T. Bauer College of Business, University of Houston 

This paper explores the changing nature of health and safety problems in the GOM offshore 

industry, focusing on the hazards of offshore operations during the early years and identifying 

when and how the industry really got serious about safety questions. 

It is difficult to measure trends in accident frequency, injury rates, fatalities, etc. on the OCS 

from easily accessible data. Individual company statistics are confidential, and neither the MMS 

nor the Offshore Operators Committee historically has required the reporting of incidents in a 

consistent manner which would allow calculations of injury frequencies. Furthermore, statistics 

have not been compiled in a way that offers easy comparisons with other occupations and 

industries. 

Records are much worse, of course, for the early years, before 1970. The USGS did produce a 

series of monthly engineering reports during the years 1954–1966, which I’ve examined in the 

National Archives. There is some reporting in these reports that you don’t find in press accounts. 

However, they are incomplete. I counted 90 reported fatalities during these years, which is most 

certainly low, and there was virtually no reporting on non-fatal accidents. Many of the oral 

histories we have collected fill in these gaps with first-hand and anecdotal perspectives on the 

risks and dangers of working offshore. The MMS also maintains an “events file” on injuries and 

accidents. I haven’t looked at this, but I have reviewed studies that did analyze these events for 

the 1970s and 1980s (after 1985, events lists only those injuries directly associated with 

blowouts, explosions, fires, significant pollution incidents or major accidents). 

I retired with a little over 30 years of service and I have still got all of my fingers 

and all of my toes. And if you look at a lot of old oil field hands, people that have 

worked in the oil field back in the old days, you look and they do not have all of 

their fingers and all their toes, particularly the people who worked on drilling rigs. 

The people who worked on drilling rigs, fingers and toes and hands and feet, they 

were just a commodity that you had to learn to live without because you were not 

going to keep them very long (Written n.d.). 

The quote from Mr. J.H. Written testifies to the fact that offshore oil is and has long been a very 

dangerous business. The oil business in general has long been dangerous. In any business or 

occupation that involves people working with extremely heavy equipment, such as drill pipe, 

combustible materials, such as oil and natural gas, and imperfect technology, there are going to 

be accidents and, unfortunately, fatalities. Oil operations offshore, of course, have faced added 

challenges from the marine environment. Just figuring out how to build and operate structures to 

drill and produce in the ocean, not to mention a part of the ocean that was exposed to hurricane-
66 

force wind and waves, have called for untested designs in drilling vessels, platforms, and wells. 

These conditions have led to a host of problems that engineers and oil-rig workers had never 

encountered before World War II. In addition to the awful physics of the machinery itself, 

workers had to contend with bad weather, dangerous boarding procedures, drilling mishaps, 

fires, and explosions far from land. 

Hazards presented themselves in different forms in different phases of operation in the early 

offshore industry. During the early years, from the late 1940s through the mid-1950s, one of the 

biggest safety issues was personnel transfer from crew boats to platforms during rough weather. 

This could be an exciting, if not terrifying, experience. One of the first methods tried and used 

with “moderate success,” in the words of John Donhaiser, a Pure Oil official, was an 

overhanging ramp extending out from the platform deck with a Jacob’s ladder reaching down to 

the water level. Numerous accidents, resulting from the ladder is becoming fouled in the ship’s 

rigging led companies to experiment with the so-called a “swinging-rope boarding method,” in 

which a person is hatched by hooks to a rope that would be swung by a cantilevered beam from 

the boat to a landing platform (Donhaiser 1995). Other companies had employees throw their 

gear into a cargo net and hang on to the outside, “jumping on it like a bunch of monkeys,” as one 

witness described it (Pugh n.d.). Back injuries, often contracted in transferring from boat to 

platform, were among the most common afflictions from working offshore. “Getting off those 

platforms in rough weather onto a boat was an interesting experience,” said Sam Paine, a Shell 

production executive. “You would swing out on this rope, try to catch the boat at its peak and 

then drop off on it. I wouldn't do it again! But I was young in those days.” Paine saw two 

Halliburton employees killed this way trying to board the jack-up vessel, Mr. Gus, when the 

crew boat drifted and the rope pulled them up through the mast and rigging, knocking them off 

about 20 or 30 feet above the boat (Paine n.d.). 

First introduced in 1948, but not widely adopted until the mid-1950s, helicopters provided 

greater economies of speed and safety in transferring crews, saving workers from the sicknessinducing 8- to 12-hour rides that often left them in no shape to work for an entire day after they 

arrived on board. On the other hand, helicopters posed their own risks. The USGS monthly 

engineering reports from the late 1950s and 1960s are littered with deadly helicopter crashes. In 

1958 alone, there were 14 reported fatalities from helicopter accidents in the Gulf of Mexico 

(GOM) OCS. Over time, Gulf helicopter travel appears to have been less safe than commercial 

airliners, but more safe than private civilian aircraft. Although not common, relative to the 

number of man-hours flown, helicopter accidents in bad weather and during night travel 

happened regularly (12 fatalities in 2003, deadliest in last two decades) (USGS 1954–1966; 

Houston Chronicle 2004). 

Early marine seismic work also proved to be dangerous business. Before the introduction of 

Vibroseis pulsing systems, the sound source came from dynamite, and deaths and injuries from 

on-board explosions did occur, especially when crews tried to speed up operations by making up 

more than one charge at a time. “When the boats are moving along at, say, six or seven knots, 

and you are trying to do all of this, you do not have a lot of time,” remembered Aubrey Bassett, 

who worked on some of Shell Oil’s earliest offshore seismic crews. “Two hundred feet goes by 
67 

in a hurry and you are just back there wildly putting all of this stuff together.” Sometimes this 

meant that the wrong charge was detonated (Bassett n.d.). 

The early years of offshore development also saw some spectacular mobile drilling vessel 

disasters. During 1955–1957, four major vessels overturned with the loss of 13 lives. The worst 

was the capsizing of the Golden Meadow Drilling company’s Mister K off the South Pass of the 

Mississippi River in April 1957, in which nine lives were lost. Operators blamed human error for 

the disasters, but it was clear that these mobile drilling vessels, especially jack-ups like Mr. Gus, 

which capsized two weeks before the Mister K off of Texas’s Padre Island, had design flaws 

(Calvert 1957). Billy Pugh, a young boat captain hired to ferry crews to Mr. Gus was not 

convinced of that vessel’s seaworthiness when he attended its christening. He said: “The thing 

was built in two pieces. It was latched together with some 2-inch cables and 20-inch pipe. I had 

been at sea long enough to know that it wouldn’t even get out of the mouth of the Sabine Pass 

.... The president of Bethlehem Steel got up and made a speech that night, saying ‘we have 

conquered the sea with this jack-up barge.’ I said, ‘Oh man, he hadn’t been to sea much.” After 

the death of the two Halliburton employees, Jimmy Storm, a partner in Glasscock Drilling, called 

Pugh up in the middle of the night to design a better solution. This led to the development of the 

Billy Pugh Personnel Transfer Net, which became standard in offshore operations in the Gulf 

and around the world (Pugh n.d.). 

 

Drilling was the most dangerous work offshore, and the most fearsome problem for drilling 

operations was the blowout. Unlike on land, blowouts could mean complete disaster on isolated 

offshore barges and platforms. Modern blowout prevention systems received special attention 

early on from offshore operators, but the loss of well control was still an inevitable fact of life in 

the Gulf, leading to fires, explosions, casualties, property damage, and pollution. The most 

common cause of blowouts in the Gulf was in exploratory drilling that encountered highpressured and undetected shallow natural gas. In 1959–1960, following the mobile rig disasters, 

were many dramatic blowouts in both the shallow and deeper waters of the Gulf. The most tragic 

one occurred on a CATC group (Continental, Atlantic Refining, Tidewater, and Cities Service) 

platform in the West Delta, which exploded in October 1958, killing seven and seriously injuring 

the remaining 29 workers who had to escape the flame-engulfed structure by jumping 50 to 60-

feet in the water (Calvert 1959). 

 

One can make the case that the relatively dangerous and hazardous nature of offshore operations 

was inherent in the adjustment from taking land-based technologies, equipment, and practices 

into the marine environment. Almost everything had to be redesigned and rethought. Marine 

engineering and construction advanced by improvisation and trial-and-error, and error could be 

harmful to the environment and debilitating or fatal to workers. In the first decades after World 

War II, booming demand for petroleum products in the United States made growth a top priority. 

Safe processes and designs either did not exist or remained untested ideas in the minds of 

researchers. Facilities engineering was a novel concept. Platforms were often stick-built with 

equipment squeezed or slapped together on the deck with little concern for worker safety . Crew 

quarters, for example, could be placed right next to a compressor building (Arnold n.d.). 

Workers were trained and drilled about safe operating practices, but they were really not trained 
68 

to manage safety or manage change in safe ways. Said one retiree: “older guys could tell you, 

you know, ‘watch this’ or ‘watch that’ but there was nobody watching you and telling you, ‘you 

had better do this,’ or ‘you had better do that (Viater n.d.). 

The result was that safety took a back seat to growth and productivity. “We talked safety but we 

were really not that much into safety,” said Lou Trosclair, longtime Shell Oil employee and 

manager. “Of course, we tried not to hurt anybody, don’t get me wrong—I mean, we were not 

barbaric or anything—but it seemed like the work had to be done and you did it as fast as you 

could.” Cliff Hernandez, another Shell veteran, had a more frank assessment: “When I first 

started working, they didn’t care whether they killed you or not! In other words, ‘we are going to 

get it done regardless.’ There was no suing like people are suing now. Back then, if you got hurt, 

they just pushed you to the side and put somebody else in. I mean, a lot of people got hurt and 

did not get paid for it. Crippled” (Viater n.d.; Hernandez n.d.) 

Oil, drilling, and service companies did not completely disregard safety and environmental 

protection, but they had near autonomy in defining what words like “safe” and “clean” meant. 

Companies learned from the series of mishaps, blowouts and fatalities of the late 1950s, and they 

continued to improve drilling, blowout prevention, and production technology.1

 Overall, 

however, little really changed in the industry’s approach to safety or in government regulation or 

oversight to insure greater safety or protection of the environment.2

 Between 1958 and 1960, the 

USGS issued OCS orders 2–5, requiring procedures for drilling, plugging and abandoning wells, 

determining well producibility, and installing subsurface safety devices, or “storm chokes.” In 

1958 and 1960, the Offshore Operators Committee, however, was able to dilute Order 5 to 

permit waivers on requirements for storm chokes (USGS 1954–1966). Most significantly, the 

orders did not have any test requirements. Companies had to have certain equipment, but they 

did not have to test it to see if it worked (Arnold n.d). 

 

Furthermore, the USGS did not inspect installations on a regular basis. Enforcement was lax. 

State and federal regulatory bodies were underfunded and understaffed. Some supervisors were 

political appointees, and even those with the appropriate training and competence often had 

neither the requisite experience in the oil business nor a grasp of its changing technological 

capabilities. As one consulting geologist observed in the late 1960s, “Each oil well has its own 

personality, is completely different than the next and has its own problems .... It takes good 

experienced personnel to understand the situation and to cope with it. If an “employee doesn’t 

know a ‘cat-head’ from a ‘bull-plug,’” he continued, “how can they be expected to enforce these 

rules and regulations?” Too often on drilling structures, he complained, one found inexperienced 

supervisors, employees who overlooked rules and regulations, the purpose of which they did not 

understand, and sometimes orders from bosses to cut corners, all of which created conditions for 

 

1

 The CATC disaster led to safety precautions when welding was done on OCS platforms. 

2

 In July 1959, the USGS issued an order requiring facility inspectors, for the first time, to make a report for the files 

of what facility they inspected and what deficiency they noted or action taken. “To keep such reports realistic, an 

inspection is defined as an official, critical, close examination at the wellhead or lease facility.” USGS. 1959. 

Monthly Engineering Reports. Gulf Coast Region. Volume 131. July. 
69 

an “explosive situation.” “Disaster might not strike the first time, but it will come!” (Etson 

1970). 

Disaster struck often in the 1960s—blowouts (22 deaths on the C.P. Baker catamaran drilling 

vessel in 1964), helicopter crashes (11 in one crash in 1966), freighters colliding into platforms, 

among other accidents3—but not until 1969–1970 did industry and government finally get 

religion on safety issues. This was due, of course, first to the January 1969 blowout at Union 

Oil’s Platform A-21 in the Santa Barbara Channel, which spilled 50,000 to 70,000 barrels of oil, 

catalyzed the national environmental movement, and set the stage for the passage of the National 

Environmental Policy Act (NEPA). These developments created a new and potentially hostile 

climate for Gulf Coast operators whose practices in the past had rarely been examined or 

challenged. 

As the industry protested and resisted a new stringent set of OCS regulations handed down by 

Interior Secretary Walter Hickel in August 1969, disaster struck operators in the Gulf. In 

February 1970, Chevron’s Platform C on Main Pass block 41 blew out and caught fire. Oil 

pollution from that blowout postponed a federal lease sale, damaged wildlife, and drew a $31.5 

million suit against the company by Louisiana oyster fisherman and a $70 million suit from the 

shrimp fishermen. A U.S. District Court also fined Chevron $1 million for failing to maintain 

storm chokes and other required safety, the first prosecution under the 1953 Outer Continental 

Shelf Lands Act, and the Justice Department proceeded to obtain judgments against other major 

oil and gas companies for similar violations (Reifel 1976). And then in December, Shell Oil 

Company suffered a major blowout on a giant platform in the Bay Marchand area, killing four 

men and injuring more than 30 others. It took 136 days to bring eleven wild wells under control, 

at a cost of $30 million. 

These events changed industry and government mindsets on safety issues and committed 

industry to improving safety technologies and designs. Public expectations on safety and the 

environment had already shifted massively, and these catastrophic blowouts, with all the national 

media attention and legal and political fallout from them, forced the most radical changes to 

operating practices in the U.S. offshore industry’s history. The government regulatory program 

was expanded and strengthened. Most OCS orders and leasing and operating regulations were 

rewritten, mandating the installation of more sophisticated safety hardware and shutdown 

systems. Orders now specified minimum requirements for wellhead controls and testing 

procedures. The USGS tripled its number of inspectors and engineers, introduced a more 

standardized inspection program, and stopped using industry-furnished transportation for 

inspection purposes (Standley 1972). 

The new approach to safety, however, was not something the federal government foisted on an 

uncooperative industry. In fact, the Offshore Operators Committee and the API Offshore Safety 

 

3

 In September 1966, the USGS reported that a Louisiana Air National Guard jet narrowly missed an ODECO rig in 

crashing in the West Delta area. “Add another hazard to the Pandora’s box of problems associated with offshore 

operations! wrote the USGS Monthly Engineering Report from the Gulf Coast Region. USGS. 1966. Monthly 

engineering reports. Gulf Coast Region. Volume 159. September. 
70 

and Anti-Pollution Equipment Committee worked closely with the USGS not only in advising 

changes in the OCS orders but in drafting, in a period of about six months, a new set of API 

“recommended practice documents” for the selection, installation, and testing of various kinds of 

safety devices (Arnold et al. 1989). As Ken Arnold, a former facilities engineer for Shell and 

founder of Paragon Engineering, put it: “We changed in a period of very few years and got most 

people to buy into it. Then, the operating people had to maintain them, which was important, and 

the suppliers started to supply better gizmos, better three-way valves, better sensors, and we 

learned how to incorporate these sensors into designs in ways that they actually worked and did 

not give false signals” (Arnold n.d.). The industry effort proved that sometimes the best way to 

get industry to change its behavior is not regulation so much as it is the threat of regulation. 

The offshore oil industry’s safety record in the Gulf improved significantly after the introduction 

of new regulations and practices. Both the incidence and rate of fatalities and injuries in the OCS 

declined. Although the total number of drilling man-hours reported for the OCS increased from 

26 million to 105 million between 1962 and 1977, the accident frequency for the same period 

declined from 14.9 to 9.3 accidents per 100 man-years. In other words, there was a fourfold 

increase in exposure-hours, but a 38 percent decrease in accident frequency (Committee 1981). 

During the 1970s and 1980s, the industry did not achieve a significant reduction in blowout 

frequency, largely because of serious limitations in methods for controlling shallow gas influxes. 

However, there was a sharp decline in the number of catastrophic blowouts and a significantly 

lower number of casualties and fatalities (Danenberger 1993). 

To be sure, accidents and casualties continued. In the late 1980s, several industry accidents 

increased scrutiny of safety in the industry. However, by most accounts, these events did not 

reflect a problem with technology or noncompliance with industry safety standards, but had more 

to do with human error stemming from inadequate training and supervision, rote reliance on 

regulations, and generally poor operating practices. As had always been the case, most accidents 

involved entry-level workers. Contributing to this problem was the increasing turnover rate in the 

offshore labor market, the growing use of contract personnel, and the emergence of smaller, 

independent operators without the necessary organizational structure for managing safety. 

According to Peter Velez, manager of regulatory affairs for Shell Offshore in the early 1998, 

during the first 40 years of the offshore industry, “80% of the efforts to improve safety and the 

environment were focused on equipment design, operational considerations, and prescriptive 

regulations,” whereas today “80% of the accidents and injuries are due to human error” (Velez 

1998). 

This does not mean that workers are to blame for their own injuries. The point is that the industry 

in the early 1970s, pressured by larger changes in society and prompted by their own failures, 

took unprecedented steps to bring greater safety into technology, process, and design, and that as 

offshore technology and organization has become increasingly complex, the challenge has been 

to improve the so-called “human” side of the business to keep up with the technological side. 
71 

References 

Arnold, K. n.d. Interview. 

Arnold, K.E. P.S. Kosezela, and J.C. Viles. 1989. Improving safety of production operations in 

U.S. OCS. Proceedings, Twenty-first Annual Offshore Technology Conference, May 1–

4, Houston, Texas, OTC Paper 6079. 

Bassett, A. n.d. Interview. 

Calvert, J.W. 1957. The Mobile rig disasters. World Petroleum. (June):30–33. 

Calvert, J. W. 1959. Disaster of Platform ‘E.’ World Petroleum. (January):42–49. 

Committee on Assessment of Safety of OCS Activities. 1981. Safety and offshore oil. 

Washington, DC: National Academy Press, 134. 

Danenberger, E.P. 1993. Outer Continental Shelf drilling blowouts, 1971–1991. Proceedings, 

Twenty-fifth Annual Offshore Technology Conference, May 3–6, Houston, Texas, May, 

OTC 7248. 

Donhaiser, J.N. 1995. Offshore fire and safety protection. Paper presented to the API Offshore 

Operating Symposium, Southwestern District, Production Division, Houston, Texas, 

March. 

Etson, N.R. to President Nixon. 1970. RG 57, Central Classified Files, 1968–1974, Box 71, 

March 18. 

Hernandez, C. n.d. Interview. 

Houston Chronicle. 2004. Copter tragedy ‘just shattering,’ rise in Gulf accident raises industry 

concern. March 25. 

Paine, S. n.d. Interview. 

Pugh, B. n.d. Interview. 

Reifel, M.D. 1976. Offshore blowouts and fires. In: ETA Offshore Seminars, Inc. The 

Technology of Offshore Drilling, Completion and Production. Tulsa: The Petroleum 

Publishing Company. Pp. 239–57. 

Standley, E.W. Interior Liaison Representative to Jack W. Boller, Assistant Executive Secretary, 

Marine Board, National Academy of Engineering 1972. RG 48. Records of the Secretary 

of Interior, Central Reports. Gulf Coast Region. Classified Files, 1969–1972, Box 136, 

Part 13. February 15. 
72 

USGS. 1954–1966. Monthly Engineering Reports Volumes 109–160. Record Group 57, Records 

of the U.S. Geological Survey, Conservation Division, Oil and Gas Leasing Branch, 

National Archives and Records Administration (NARA), College Park, MD. 

Velez, P. 1998. Safety and environment protection: a collaborative approach. MMS Today. 

8(3):5. 

Viater, K. n.d. Interview. 

Written, J.H. n.d. Interview. 

Ty Priest is an independent scholar and partner in History International, LLC, a consulting firm 

specializing in corporate histories. He received his Ph.D. in history from the University of 

Wisconsin-Madison and has taught at Middlebury College and the University of Houston. A 

specialist in the history of the oil and gas industry, he is the co-author, with Joseph Pratt and 

Christopher Castaneda, of Offshore Pioneers: Brown & Root and the History of Offshore Oil and 

Gas and the author of a forthcoming history of the Shell Company. He is currently researching 

the history of oil and gas exploration in the Gulf of Mexico. 
73 

WOMEN IN THE GULF OF MEXICO OFFSHORE OIL AND GAS INDUSTRY: 

OVERLOOKED BUT NOT FORGOTTEN 

Diane Austin, Bureau of Applied Research in Anthropology, University of Arizona 

Introduction 

In 1901, oil was discovered in Jennings, Louisiana. Decades later, in 1947, the industry 

successfully moved offshore into the Gulf of Mexico (GOM). From those beginnings to now, the 

oil and gas industry in southern Louisiana has undergone significant changes—in machinery, 

processes, and work culture. Yet, despite numerous apparent differences in their circumstances 

as oilfield wives and as workers, the experiences women describe over the years are remarkably 

similar. 

In general, U.S. women entered the workforce in significant numbers during World War II, were 

displaced from most jobs when men returned from the war in large numbers, and then returned to 

out-of-the-home workplaces during the 1970s and 1980s. In the 1980s and 1990s, dramatic 

changes in U.S. corporations and society reshaped the work-family patterns that had been 

established in previous decades, and by the end of the 20th century, economic distress, amid the 

downsizing of government and the restructuring of corporations, again brought attention to 

questions of women and work. 

In contrast to many other industries, the U.S. oil industry has severely restricted women’s 

participation. Even during World War II, when many jobs were opened to women, work on rigs 

and platforms was confined to men. Men working offshore recalled the frustration of being kept 

home from the war because their jobs were deemed critical to national security. Situated in the 

U.S. South, where the cultural images of both “woman as homemaker” and as “lady” remain 

powerful in defining the proper role for a woman as wife and mother (Middleton-Keirn and 

Howsden-Eller 1986; Mathews 1989; Dillman 1989), women seeking employment in the 

offshore oil and gas industry have faced significant challenges. 

When the doors to offshore employment in all sectors were finally opened in the 1970s, some 

women took the chance to earn higher pay. Many of these women pioneers met resistance and 

even hostility. Those who persevered watched many others come and go. During the downturn of 

the 1980s, both men and women workers with little seniority were laid off or had their hours 

reduced. By the mid-1990s, when activity picked up again, it did so at a time of significant 

industry restructuring when the total number of workers had been reduced. Even into the 21st

century there are few women working on rigs and platforms or in fabrication and shipyards, the 

most visible signs of the industry in the GOM region. Yet, despite their apparent absence, 

women contribute to the industry in numerous ways. 
74 

Women and the Offshore Industry 

Within what has become an international offshore oil and gas industry, the GOM has been 

distinguished by its “cowboy” culture.1

 Reliable figures on the offshore workforce are hard to 

obtain—though petroleum companies fill some positions themselves, they rely on a large array 

of contract companies to supply seismograph crews, drillers, cooks, truckers, divers, mechanics, 

and a multitude of other people necessary for finding, reaching, and producing oil and gas from 

the U.S. Outer Continental Shelf. Throughout this vast industrial landscape, and largely invisible, 

are substantial numbers of women. These women support the industry in their roles as blue-, 

pink-, and white-collar workers, and as relatives of men who work offshore (Austin 2005). 

The move offshore began when rigs were erected first on pilings and then on barges in the 

marshes and lakes of southern Louisiana. For many oil companies, the initial transition from land 

to water was gradual. Nevertheless, the move into the GOM initiated a significant change in the 

lifestyle patterns of oilfield workers. No longer were workers required to physically move their 

homes and families to the sites of exploration and production. For the first time, some oilfield 

families could settle down in one community while the worker commuted to and from ports and 

docks to be transported to rigs and platforms. In addition, people already living in the Gulf 

region could take jobs that would enable them to remain in their native communities. Under 

these circumstances, two groups of women came together—migrants from places like Texas and 

Oklahoma with a history in the oilfields and locals exposed to the industry for the first time. The 

all-male culture of the onshore oil industry was transferred offshore. The concentrated 

scheduling of offshore work (7 days on and 7 days off, 14 and 14, or combinations such as 21 

and 7) meant that workers were absent from home for long periods of time. Thus, wives 

continued to have significant responsibility for managing nearly all aspects of the household and 

to face potential isolation; like their predecessors who moved from place to place, women used 

their social networks to get by (e.g., Schrag-James 2002). 

At the same time, and though largely hidden, women were to do more than manage households 

in the new industry. As relatives of men who worked in the industry, they have helped perform 

the tasks required of employees. In addition, women have held their own jobs, onshore in both 

typical “pink-collar” jobs and nontraditional “blue-collar” jobs, and offshore as well. The 

industry received a significant boost at the end of World War II when men and equipment 

became available in southern Louisiana. Women, too, who had gained skills in wartime 

employment in factories and shipyards, could put those to work. They filled clerical and 

secretarial positions for oil companies and those that provided service to them. As the onshore 

infrastructure for the offshore industry grew, many small businesses were formed, and women 

played a critical role in creating many of these. Thus, long before the 1970s when oil and gas 

companies were forced by federal civil rights laws to begin hiring women in offshore jobs, 

women were intimately involved with the industry. Yet, as the offshore industry developed, even 

 

1

 Movies like Giant, Hell Fighter or Thunder Bay, and books like Louisiana Blue, characterize the oil field as the 

new Wild West. Scholars working in the North Sea and Canada have argued that workers from the Gulf of Mexico 

brought with them a cowboy culture that was highly resistant to change (e.g., Lewis, Porter, and Shrimpton 1988, 

Røyrvik 2000). 
75 

in support sectors such as supply boats that evolved locally, the distinction between men’s and 

women’s work and the separation of youth from adults was reinforced. 

The routes by which women have come to the industry and their experiences in it are many. 

They have been motivated by good wages, familiarity, confronting stereotypes, and the pursuit of 

challenging and interesting work. For some, the work has provided freedom and opportunities 

not otherwise available. For others, it has simply been a mechanism for survival. Though 

women’s support had been critical to small and large companies for decades, the forced entry of 

females into specific nontraditional jobs in the 1970s generally was not welcome. Coming in the 

wake of other personnel changes, their entry challenged the all-male work culture that had 

prevailed throughout the oil and gas industry for more than 50 years and marked a period of 

transition in workforce culture. 

Through their attitudes and behaviors, individual women have been able to influence their 

acceptance or rejection at their workplaces, and organizations such as Desk and Derrick Clubs 

offered them some support. However, despite the successes, the numbers and position of women 

in the industry have changed little over the past 30 years. Through this period, the U.S. trend 

toward greater workforce participation by women has been thwarted by both stereotypes of 

Southern women and of oilfield workers. 

References 

Austin, D.E. 2005. The offshore oil and gas industry in southern Louisiana: Impact on women’s 

lives. Research in Economic Anthropology. Forthcoming. 

Dillman, C.M. 1989. Southern women: In continuity or change? In: Mathews, H.F., ed. Women 

in the South: An Anthropological Perspective. Athens: The University of Georgia Press. 

Pp. 8–17. 

Lewis, J., M. Porter, and M. Shrimpton. 1988. Women, Work and Family in the British, 

Canadian and Norwegian Offshore Oilfields. London: Macmillan. 

Mathews, H.F. 1989. Introduction: What does it mean to be a woman in the South today? In: 

Mathews, H.F., ed. Women in the South: An Anthropological Perspective. Athens: The 

University of Georgia Press. Pp. 1–7. 

Middleton-Keirn, S. and J. Howsden-Eller. 1986. Reconstructing femininity: The woman 

professional in the South. In: Mathews, H.F., ed. Women in the South: An 

Anthropological Perspective. Athens: The University of Georgia Press. Pp. 57–70. 

Røyrvik, E. 2000. Cowboys and rebels in the North Sea. (Summary of Smith-Solbakken, M. 

1997. Offshore Workers: History of Cowboys and Rebels. Nr. 17. NTNU: Historisk 

Institutt.) Gemini, an online publication of Norges Teknisk-Naturvitenskapelige 

Universitet (NTNU). http://www.ntnu.no/gemini/2000-01e/13.html. 
76 

Schrag-James, J. 2002. Offshore employment as lifestyle and culture: Work and family in New 

Iberia. In: Austin, D.E. and T.R. McGuire, eds. Social and Economic Impacts of OCS 

Activities on Individuals and Families: Volume 2: Case Studies of Morgan City and New 

Iberia, Louisiana. Report prepared for the Gulf of Mexico Region of the Minerals 

Management Service. Pp. 5–56. 

Diane E. Austin is an assistant research anthropologist in the University of Arizona’s Bureau of 

Applied Research in Anthropology (BARA). She specializes in the development of communitybased participatory research methodologies and coordinates BARA’s internship program. Her 

major interests include environmental anthropology; social impact assessment; environmental 

justice; community development; and research methods and analysis. She began studying the 

impacts of the offshore oil and gas industry on southern Louisiana in 1996. 
77 

USING ORAL HISTORY TO UNDERSTAND IMPACTS ON COMMUNITIES 

Tom McGuire and Diane Austin, 

Bureau of Applied Research in Anthropology, University of Arizona 

Although researchers have documented the social impacts of the offshore oil and gas industry on 

workers, families, and communities in the late 20th century (Austin et al. 2002, Austin and 

McGuire 2002), documentation of impacts over the industry’s nearly 60-year history is sparse. 

Given the lack of written documentation, oral history provides a mechanism for obtaining 

information about the early industry and its effects on southern Louisiana. 

In addition, oral history is particularly effective in uncovering the meaning that those who were 

affected attributed to impacts and in providing opportunities for many voices and perspectives to 

be represented. By gathering the stories of a diverse sample of workers, family members, and 

community leaders whose lives were directly affected by this industry, we acknowledge that 

there is no single story or interpretation of what happened. 

One important benefit of the collection of oral histories is the opportunity we have to understand 

community response to OCS development. Differential impacts of the industry on southern 

Louisiana communities can be attributed to 1) the community’s history and political economy; 2) 

the sociocultural context within which the community evolved; 3) the natural features that define 

the community; 4) the footprint of industrial activity; and 5) the duration of that activity. 

Five Communities 

• New Iberia 

• Morgan City 

• Houma 

• Golden Meadow 

• Venice 

New Iberia 

⎯ Sweetest, oiliest, saltiest, hottest; land tied up in agriculture 

⎯ Spanish, French, Senegambian slaves, Acadians 

⎯ Located along Bayou Teche, water access via Vermillion Bay and Intracoastal 

Canal 

⎯ Port of Iberia 

⎯ Offshore from 1970s to present 

Harold Dugas, “My parents were born and raised around this area, in southwest Louisiana, in this 

parish here. My daddy was a sugarcane farmer .... The last junior and senior year of high school, 

daddy had to pull me out of school for six weeks to help him on the farm .... I had no concept of 

the oil—I just didn’t know hardly anything about it .... All we knew was sugarcane farming with 

the little schooling we had....” 
78 

Morgan City 

⎯ Railroad brings commerce; lumber industry, shrimping 

⎯ Cosmopolitan 

⎯ Located on Tiger Island, water access via Atchafalaya River and Bayou Boeuf 

⎯ Bulkheads along the bayou 

⎯ Oil discovered in marshes in 1920s; World War II; first offshore well in 1947 

Pete Rogers “These companies had been exploring, and there was quite a number of oilfields. 

When I worked for this timber company, we pulled timber with a pull boat in back of White 

Castle, and Shell Oil Company at that time—I think it was back in the early 30s—Shell had a 

field in back of White Castle, and the oil was loaded in wooden barges.” 

Houma 

⎯ Oyster Capital; agriculture, fishing, trapping 

⎯ Acadian base with large influx due to oil industry 

⎯ Convergence of five bayous at Houma 

⎯ Ideal land base for inshore development 

⎯ First well drilled onshore in 1928; World War II; oil service industries dominate 

Annie Weaver “At one time this was the oyster capital of Louisiana and before we came, they 

had something they called ‘turtle camps’ down on the bayou and people got turtles, I guess to 

eat. And then of course we have always had the cane .... We were looked down on at first. I 

went to a coffee at one of the elderly ladies’ in my neighborhood and she said, ‘Please don’t tell 

anybody you are with the oil field.’” 

Golden Meadow 

⎯ Only incorporated town in South Lafourche; fishing, trapping 

⎯ Populated by Acadians with Houma Indians segregated in lower Golden Meadow 

⎯ Bayou Lafourche 

⎯ Shipyards, offshore vessel companies; Port Fourchon established in 1960 

⎯ Oil rigs throughout town in 1930s 

Chester Cheramie, “When the [trapping] season’s over you split what you make. So all the time 

you never had any money... So until you started in the oil field back in the late 30s, that’s when 

people started having a little money because they would come here and they’d spud into the oil 

well.... So a lot of these people would get a $200–300 dollar check a month. That was a lot of 

money for those people because they did not have nothing before.” 

Venice 

⎯ Trapping, citrus, oyster fishing 

⎯ Croatians 

⎯ Mississippi River 

⎯ “The Jump” 

⎯ Oil discovered in the mid-1930s; companies established camps 
79 

Myrtle Phillips, “At one point and time before I was ever born, it was all fresh water. Then you 

know eventually the salt water came in and killed, there were cypress trees on both sides of the 

bayou and all they’ve got now is the stumps. When the tide goes real low you can see the 

stumps.” 

Summary 

• Each community experienced the oil and gas industry uniquely 

• Collective memories of conditions, attitudes, and events contribute to our 

understanding of the industry and its impacts 

• Interviewees introduce numerous themes and topics for further study 

References 

Austin, D.E., K. Coelho, A. Gardner, R. Higgins, T.R. McGuire. 2002. Social and Economic 

Impacts of OCS Activities on Individuals and Families: Volume 1. Report prepared by 

the University of Arizona, Bureau of Applied Research in Anthropology. U.S. Dept. of 

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

OCS Study MMS 2002-022. 

Austin, D.E. and T.R. McGuire, eds. 2002. Social and Economic Impacts of OCS Activities on 

Individuals and Families: Volume 2: Case Studies of Morgan City and New Iberia, 

Louisiana. Report prepared by the University of Arizona, Bureau of Applied Research in 

Anthropology. U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico 

Region. New Orleans, LA OCS Study MMS 2002-023. 

Tom McGuire received his Ph.D. in anthropology from the University of Arizona and is 

currently an associate research anthropologist in the Bureau of Applied Research Anthropology 

(BARA) at the University of Arizona. In addition to his research on the historical development 

and social impact of the oil and gas industry along the Gulf of Mexico, Dr. McGuire has 

conducted work on the fisheries of the Gulf of California, Native American water rights and 

resource use in the Southwest, and cattle reaching on the Ft. Apache Reservation in Arizona. 

Diane E. Austin is an assistant research anthropologist in the University of Arizona’s Bureau of 

Applied Research in Anthropology (BARA). She specializes in the development of communitybased participatory research methodologies and coordinates BARA’s internship program. Her 

major interests include environmental anthropology; social impact assessment; environmental 

justice; community development; and research methods and analysis. She began studying the 

impacts of the offshore oil and gas industry on southern Louisiana in 1996. 
81 

SESSION 2A 

ACOUSTICS IN THE MARINE ENVIRONMENT 

Chair: Bill Lang, Minerals Management Service 

Co-Chair: Ron Brinkman, Minerals Management Service 

CALIBRATION OF THE KONDOR ARRAY USING THE LDEO SPAR BUOY 

Maya Tolstoy and John Diebold.............................................................. Document Not Submitted 

CALIBRATION AND ANALYSIS OF SEISMIC AIRGUN DATA FROM AN EARS 

BUOY Joal J. Newcomb, William M. Sanders, James M. Stephens, Christopher D. Walker, 

Benjamin Brack, Grayson H. Rayborn, Natalia A. Sidorovskaia, Arslan M. Tashmukhambetov, 

George E. Ioup, Juliette W. Ioup, and Sean R. Chapin................................................................. 83 

BOTTOM-MOORED HYDROPHONE MEASUREMENTS OF AMBIENT NOISE 

DURING STORMS IN THE GULF OF MEXICO Joal J. Newcomb, Mark Snyder, 

Wesley R. Hillstrom, and Ralph Goodman ................................................................................ 101 

ANALYSIS OF BOTTOM-MOORED HYDROPHONE MEASUREMENTS OF GULF 

OF MEXICO SPERM WHALE PHONATIONS George E. Ioup, Juliette W. Ioup, 

Natalia A. Sidorovskaia, Rachel T. Walker, Stan A. Kuczaj, Christopher D. Walker, 

Grayson H. Rayborn, Benjamin Brack, Andrew Wright, Joal Newcomb, and Robert Fisher ... 109 

AIR-GUN ARRAY CALIBRATION STUDIES IN THE GULF OF MEXICO 

Jack Caldwell.............................................................................................................................. 137 

MANTA: THE MARINE ANIMAL TRACKING APPARATUS Thomas F. Norris.............. 145 
83 

CALIBRATION AND ANALYSIS OF SEISMIC AIRGUN DATA 

FROM AN EARS BUOY 

Joal J. Newcomb and William M. Sanders, 

Naval Research Laboratory 

James M. Stephens, Christopher D. Walker, Benjamin Brack, and 

Grayson H. Rayborn, University of Southern Mississippi 

Natalia A. Sidorovskaia and Arslan M. Tashmukhambetov, 

University of Louisiana at Lafayette 

George E. Ioup, Juliette W. Ioup, and Sean R. Chapin, 

University of New Orleans 

Abstract 

In the summer of 2003, during the Sperm Whale Seismic Study (SWSS), two Environmental 

Acoustic Recording Systems (EARS) buoys were deployed in the northern Gulf of Mexico 

(GOM) by the Littoral Acoustic Demonstration Center (LADC), an Office of Naval Researchfunded consortium consisting of the University of New Orleans, the University of Southern 

Mississippi, the Naval Research Laboratory, and the University of Louisiana at Lafayette. The 

buoys were co-located and recorded ambient noise and seismic airgun array shots up to 

approximately 25 kHz. The gains and hydrophone sensitivities were set such that one EARS 

buoy could record the seismic shots without clipping and the other could record ambient noise. 

The M/V Kondor towed an airgun array on linear tracks with horizontal closest points of 

approach to the buoy of 0, 500, 1000, 2000, and 5000 m. Experimental data are available for a 

wide range of horizontal distances (up to 7 km) and arrival angles. The raw data were calibrated 

in post processing using the EARS system parameters to produce calibrated pressure time series 

for each shot. These data are analyzed in both the time and frequency domains. Maximum 

pressures for each shot as well as sound exposure levels (pressure squared integrated over time 

for 200 ms in this case) for the shots on the first three tracks are presented. Also presented is a 

spectrogram analysis for a fixed window length in terms of shot number rather than time. The 

maximum time-domain peak pressure recorded was 200 dB re 1 μPa when the array was 736 m 

from the buoy. The maximum sound exposure level was 177 dB sec re 1 μPa2

 sec 

Arrival times for direct path, reflected path and critically refracted events from the series of five 

parallel survey lines are discussed. Near uniform sound speed in the survey area allowed for 

classification of first-break and secondary arrivals as direct arrival and either reflected or 

refracted path arrival, respectively, using simple propagation geometries. Beyond a certain 

horizontal range (approximately 4.5 km), the critically refracted arrival overtook the reflected 

arrival. In the survey line farthest from the recording buoy (approximately a 5 km closest point 

of approach), the refracted arrival arrives prior to the seafloor reflection in every shot record and 

actually begins to precede the direct arrival. These data allow for estimates of the critical angle 

and sound propagation speed in the seafloor sediment layer. 
84 

The identification of different types of arrivals (direct pulse, surface ghost, bottom reflected, etc.) 

and evaluation of their frequency content depending on the azimuth angles, emission angles, and 

distance to the array for the subsequent numerical studies are discussed. The numerical modeling 

of the recorded temporal arrivals from a broadband (10–25,000 Hz) two-dimensional seismic 

exploration array (the M/V Kondor 31-gun, 3,590 cubic-inch array) by the standard underwater 

acoustic parabolic equation model RAM (Range-dependent Acoustic Model) subject to the 

actual propagation conditions in the northern GOM is presented. The comparison of the recorded 

arrival patterns with the expected ones due to the waveguide propagation is given. The 

complexity of propagation and source models required to predict the identified arrivals are 

discussed. (This work was supported by the Industry Research Funders Coalition.) 

Introduction 

The Littoral Acoustic Demonstration Center (LADC) is an Office of Naval Research-funded 

consortium consisting of the University of New Orleans, the University of Southern Mississippi, 

the Naval Research Laboratory, and the University of Louisiana at Lafayette. LADC deployed 

two Environmental Acoustic Recording System (EARS) buoys in the northern GOM during June 

2003 (see Figure 2A.1) in conjunction with the Sperm Whale Seismic Study (SWSS). The 

objective was to obtain calibrated sound pressure levels in an effort to understand the spatial 

character of seismic airgun emissions. EARS buoys (developed by the Naval Oceanographic 

Office) are autonomous, self-recording buoys capable, in this configuration, of more than 19 

days continuous recording of a single channel at a 78.125 kHz sampling rate. The two buoys 

were co-located on the same mooring (see Figure 2A.2) near Green’s Canyon in the Northern 

GOM. One buoy (labeled E3) was designed to record ambient noise and the other (labeled AG) 

designed to record airgun emissions without clipping the data. The hydrophone of each buoy was 

approximately 250m from the bottom in a water depth of about 983m. Only the data from the 

AG EARS buoy will be discussed in this paper. 

The M/V Kondor towed a seismic airgun array on five parallel linear tracks with horizontal 

closest points of approach to the EARS buoy position of 0, 500, 1000, 2000, and 5000m (see 

Figure 2A.3). These tracks provide a wide range of arrival angles and horizontal distances (up to 

7 km, see Table 2A.1 (Fontana 2003) from the airgun to the EARS buoys. 

Table 2A.1. Airgun calibration lines. 

Line Number Lateral Offset Emission Angles Horizontal Range 

1 (0.2) 0 m 80° – 6°- 80° 4800m – 63m 

2 (500.0) 500 m 81° – 31°- 81° 4900m – 860m 

3 (1000.0) 1000 m 82° – 53°- 82° 5200m – 1250m 

4 (2000.0) 2000 m 82° – 70°- 82° 5300m – 2100m 

5 (5000.0) 5000 m 84° – 82°- 84° 7000m – 5050m 
85 

Figure 2A.1. Chart of Northern Gulf of Mexico indicating the position of the EARS buoys near Green’s 

Canyon. 

Figure 2A.2. Illustration of the mooring showing the two co-located EARS buoys. 
86 

Figure 2A.3. Illustration of the tracks of the M/V KONDOR in relation to the EARS buoy position. 

Calibrations 

To report absolute sound pressure levels, it is important that the equipment calibrations be fully 

understood. Two methods of calibration were used for the AG EARS buoy. The first method 

involves injecting a single narrowband sine wave (CW) into the electronics downstream of the 

hydrophone. The input voltage of the injected CW signal is compared to the output voltage. This 

is repeated for many different frequencies to obtain the transfer function of the equipment across 

a broad frequency band. This method is often called a frequency domain solution. 

The other method injects a very temporally short (4.7μsec wide) signal into the electronics 

downstream of the hydrophone. The characteristics of this “impulse” are such that a very wide 

band of frequencies are represented. The output was recorded and supplied the impulse response 

of the equipment. This is often called the time domain solution. Theoretically, the impulse 

response of the equipment and the transfer function of the equipment are equivalent. A 

comparison of the two methods for the AG yielded the same results between 6 Hz and 25 kHz. 

For ease of calculation all final calibrations were performed using the frequency domain 

solution. The hydrophones were new and calibrated at the manufacturer. 

Figure 2A.4 is an illustration of the data from shot 248 along the 0 m offset line. Shot 248 is near 

the closet point of approach (CPA) to the EARS buoy. Figure 2A.4 illustrates only 200 ms of 

data corresponding to the “direct” arrivals. The upper plot is the raw data in Volts and the bottom 

plot is the same data in μPa after all the calibrations have been applied. The EARS response is 

nearly flat from 6 Hz to 25 kHz so that the two plots have very little differences except in units. 
87 

Figure 2A.4. Plots of data from Shot 248 on the 0m offset line near the point of closest approach to the EARS 

buoy illustrating the shot before and after calibrations have been applied. 

Airgun Calibration Data Analysis 

Three approaches are used initially to analyze airgun calibration data. 

 1. The simplest is the maximum instantaneous airgun pressure for each shot at a given 

range, azimuth, and depth. This measure is important but it does not give signal duration 

or energy transfer. 

 2. The second is the Sound Exposure Level (SEL), the sum of the squared pressures 

multiplied by the sampling interval for a given time window, which includes the effects 

of signal duration. A 200 ms window is used because there seems to be a consensus 

developing that this is the appropriate integration time for sperm whale hearing. 

 3. The third is the sound pressure density spectrum, which gives the distribution of intensity 

over frequency. 

The plots in Figure 2A.5 show the maximum peak pressures in dB re 1 μPa versus shot number 

for each of the five lines. If instead of a single peak pressure we had used the peak-to-peak 

difference, these numbers would be increased by less than 3 dB. Although one might be tempted 

to make isopleths, i.e., contours of constant pressure, based on these data, it is not possible to do 

so. It must be remembered that these measurements are in three dimensions, not two, and they 

are far too sparse to determine contours. These contours can be determined by modeling, 

however, and the measurements can be used to validate the models. 
88 

Figure 2A.5. Maximum pressures in dB re 1 μPa versus shot number for each of the five lines. 

Figure 2A.6 is a graph of the voltage recorded for the shot of CPA for Line 1. The sound 

exposure level in dB sec re 1 μPa2 sec for a 200ms window slid over the shot is shown in Figure 

2A.7. The maximum SEL for every shot in Lines 1, 2, and 3 (in red, blue, and green, 

respectively) is shown in Figure 2A.8, plotted versus shot number. The gaps occur during ship 

turns. For some analyses, SEL is given for 90% of the total SEL. This is done when it is difficult 

to distinguish where the airgun shot starts and finishes relative to the background ambient noise. 

For the AG EARS buoy, the signal-to-noise ratio is high enough that background ambient noise 

does not contribute to the SEL. Therefore 100% of the SEL calculated over the 200 ms window 

can be used (Madsen 2005). 

Finally, Figure 2A.9 contains what can be regarded as a spectrogram, except that the horizontal 

axis is shot number rather than time. The sound pressure density spectrum level in 

dB re 1 μPa2

/Hz is shown for all calibration shots sequentially along each of the five lines, one 

line after the other. There are a total of 587 shots (including the shots made while the ship was 

turning between lines). The window for each shot is 1.28 sec. The frequency to 25 kHz is shown 

on the vertical axis, and the line number on the horizontal axis. The intensity is indicated by the 

color bar, ranging from 60 to 160 dB. Very faint intensity lines can be seen at regular intervals at 

18 kHz. These are caused by the ship’s echosounder. 

One-third octave bands are close to reflecting the way that animal hearing integrates sound. 

Therefore this analysis is important. This calculation and appropriate normalization are currently 

in process. 
89 

Figure 2A.6. Voltage versus time for the shot of the closest point of approach for Line 1. 

Figure 2A.7. Sound Exposure Level in dB sec re 1 μPa2 sec for a 200 ms sliding window for the shot of the 

closest point of approach for Line 1 as shown in Figure 2A.6. 
90 

Figure 2A.8. Maximum Sound Exposure Levels over a 200 ms window for each shot on Lines 1, 2, and 3, in 

dB sec re 1 μPa2

 sec. 

Figure 2A.9. Sound pressure density level spectrogram of airgun shots, but with shot number on the 

horizontal axis rather than time. Plot shows intensity by color for 0 to 25 kHz for each shot 

number sequentially along each line. The intensity scale goes from 60 to 160 dB for sound 

pressure density level given in dB re 1 μPa2

/Hz. 
91 

Arrival Time Analysis 

Assuming a constant sound speed in the water column, both direct and reflected arrivals exhibit 

hyperbolic moveout: the arrival time vs. horizontal range (offset) curve is a hyperbola in each 

case. At some critical distance, Xc, the refracted arrival begins to appear. The refracted ray 

precedes the reflected array for all offsets greater than Xc, and will—in principle—eventually 

overtake the direct ray. The arrival time vs. offset curve for the refracted ray is a straight line, 

with sound propagation speed in the seafloor layer appearing as the inverse slope. This expected 

behavior is depicted in Figure 2A.10. If distinct arrival events can be recognized in the time 

series, a plot of arrival time vs. horizontal offset can be used to determine the onset of refracted 

arrival, as well as estimate the critical angle and sound speed in the seafloor layer. 

A plot of the second event arrival vs. offset exhibits hyperbolic character for small offsets, as this 

event, presumably, is the reflected path arrival, but will flatten out at offsets equal to or greater 

than Xc. At this distance the refracted arrival overtakes the reflected energy and follows a linear 

relationship with horizontal offset. An example is seen in Figure 2A.11. To make the deviation 

from hyperbolic moveout more apparent, we plot the difference in first arrival (first break) and 

second arrival times vs. offset. When the first break corresponds to the direct arrival, and the 

second arrival is the reflected signal arrival, the difference plot asymptotically approaches a horizontal line. With the appearance of refracted energy in the second arrival, the difference plot will 

drop sharply from the expected asymptotic behavior. This effect is clearly seen in Figure 2A.12, 

at an offset of approximately 4,500 m. In all the data this effect—attributed to the appearance of 

the refracted wave—manifests itself at 4,500 m, which we take as our estimate of Xc. 

From elementary geometry, the critical angle can be determined from Xc, 

⎟

⎠

⎞ ⎜

⎝

⎛

+ = −

d h

Xc

c

1 θ tan

. (1) 

The quantities d and h are the heights of the seismic source and hydrophone above the seafloor, 

respectively. The sound speed in the seafloor layer, u, may now be determined as 

c

c

u

sinθ =

, (2) 

where c is the sound speed (assumed constant) in the water column. In the experiment, 

d = 983 m, and h = 250 m. If the (nearly constant) sound speed in the water column is taken as 

1,500 m/s, the resulting value for u is approximately 1,550 m/s. 

The large offset portion of the second arrival vs. offset plot should, in principle, provide a second 

means to determine the speed in the seafloor layer; it is the reciprocal of the slope of this linear 

portion. Linear regression on the data yielded results that were not self-consistent, which we 

interpret to be due to the small number of data points for offsets larger than Xc. Additionally, in 

one of the survey lines the CPA was greater than 4,500 m, so the second arrival should have 

exhibited a linear relationship with offset and, indeed, should have overtaken the direct arrival at 

some point. Analysis of this line was problematical; however, apparently the discrete arrival 

events could not be identified and separated as easily as might have been hoped. 
92 

Figure 2A.10. Expected arrival time behavior for direct, reflected, and refracted energy. 

Figure 2A.11. Flattening of second arrival at large offsets, indicating refracted arrival overtaking reflected 

energy. 
93 

Figure 2A.12. Difference between second and first arrival vs. horizontal range (offset). Dip at approximately 

4500 m is a deviation from the expected asymptotic behavior when second arrival corresponds 

to reflected path. 

Acoustic Energy Propagation Modeling 

Two main objectives of the acoustic propagation modeling of the LADC calibration experiment 

were 1) the generation of a three-dimensional acoustic energy distribution in the oceanic volume 

of interest based on the successful fit of the modeled data to the EARS recordings and 2) the 

prediction of three-dimensional acoustic energy distribution variations due to anticipated changes 

in the geographical position of a future survey, ocean environmental conditions, and source 

configuration without conducting additional costly calibration experiments. 

The propagation modeling workflow is illustrated on Figure 2A.13. Source frequency or 

temporal signature, source-receiver geometry, and oceanic waveguide model (bathymetry, sound 

speed profile, bottom layering) are inputs into propagation model, which is basically a wave 

equation solver. The simulated acoustic signature at the EARS location as an output of the 

propagation code is compared to the experimental one. If an adequate fit is achieved, then the 

primary objectives can be addressed by changing the input parameters and analyzing the 

simulated output. Otherwise, the accuracy of the inputs should be adjusted, and the modeling 

should be repeated. 
94 

Figure 2A.13. The propagation modeling workflow. 

The standard underwater acoustic model RAM (Range-dependent Acoustic Model) (Collins 

1993) was used to simulate the acoustic signature at the EARS location. The code was modified 

to generate the response from a broadband multi-source seismic array. To describe the sourcereceiver geometry, a spherical coordinate system was utilized. The origin of the system is in the 

center of the seismic array. The EARS position is described by the vertical angleΘ , the horizontal angleφ , and the horizontal range, which represents the projection of the direct distance 

from the center of the array to the hydrophone into the horizontal plane (see Figure 2A.14). 

The water column waveguide model used in the simulations was constructed from the 

experimental data of pressure, salinity, and temperature of the water collected by XBT casts 

performed concurrently with the experiment. The bottom model based on an historical database 

consists of three layers: a 10 m deep layer of soft silty-clay, a 1 km deep layer of sand, and a 

rock foundation (Hamilton 1980). The waveguide model is presented in Figure 2A.15. 

According to the constructed sound speed profile in the water column, the seasonal surface duct 

is apparent in the first 10 m of water. The surface duct should generate a unique series of early 

acoustic arrivals (precursors) at the receiver position as indicated in previous studies (Monjo and 

DeFerrari 1993, Sidorovskaia 2004). The effects of the energy redistribution in the water column 

from the directional seismic source due to a seasonal surface duct are under study and will be 

addressed in future publications. 

The frequency domain representation of the transfer function (Green’s function) generated by 

RAM for two different shot points is presented in Figure 2A.16. Each color line corresponds to 

the individual transfer function from a particular airgun to the EARS buoy. The seismic 

exploration array consists of 31 spaced or single airguns with volumes ranging from 20 to 
95 

Figure 2A.14. Array-buoy coordination system. 

Figure 2A.15. Waveguide model. 
96 

Figure 2A.16. Green’s function generated by RAM. 

250 cubic inches, giving a total volume of 3,950 cubic inches. The difference in the individual 

source powers corresponds to the variation in sound pressure density spectral levels. The lowfrequency interference structure in the Green’s function is due to the surface reflection. The fine 

structure of the transfer function is determined by the first bottom reflection and multiples. 

The measured seismic exploration array signature in the frequency domain is modeled by the 

sum of the products of the transfer, ( f ) i G

, and source, ( f ) i

S

, functions for each airgun: 

= ∑ ⋅

( )

( ) ( ) ( )

i airguns

f i f S i f G EARS p

. (3) 

Figure 2A.17 shows the comparison of the experimental and modeled signatures for two 

different array positions relative to the EARS buoy. For this plot, the frequency signatures of the 

individual airguns are modeled as flat over the entire frequency band of interest (10-1000 Hz). It 

is obvious from the comparison that this model reflects the actual airgun design only in the lower 

part of the spectrum (up to 250 Hz) where satisfactory agreement is reached. The experimental 

spectra indicate faster attenuation of the high frequencies than modeled ones. 
97 

Figure 2A.17. Model output versus experimental data. 

The modeling has demonstrated that a more advanced signature of the individual sources should 

be implemented to account for the high-frequency attenuation (Ziolkowski 1970). Once a better 

match is achieved for the high-frequency components, three-dimensional acoustic energy 

distribution maps will be generated. 

Acknowledgments 

This research was supported by the Industry Research Funding Coalition. 

References 

Collins, M.D. 1993. A split-step Pade solution for parabolic equation method. Journal of the 

Acoustic Society of America. 93:1736–1742. 

Fontana, P. 2003. Private communication. 

Hamilton, E.L. 1980. Geoacoustic modeling of the sea floor. Journal of the Acoustic Society of 

America. 68(5):1313–1340. 
98 

Madsen, P. 2005. Private communication. 

Monjo, C.L. and H.A. DeFerrari. 1994. Analysis of pulse propagation in a bottom-limited sound 

channel with a surface duct. Journal of the Acoustic Society of America. 95:3129–3148. 

Sidorovskaia, N. 2004. Systematic studies of pulse propagation in ducted oceanic waveguides in 

normal mode representation. The European Physical Journal, Applied Physics 25(2):113–

131. 

Ziolkowski, A. 1970. A method for calculating the output pressure waveform from an air-gun. 

Geophysical Journal of the Royal Astronomical Society 21:137–161. 

Joal J. Newcomb received a B.S. degree in physics and mathematics from Southwestern 

Oklahoma State University, an M.S. in atomic physics from Kansas State University, and a Ph.D. 

in experimental atomic physics from Kansas State University. He is currently a research 

physicist in the Acoustics, Simulations, Measurements & Tactics Branch of the Naval Research 

Laboratory at the John C. Stennis Space Center, Mississippi. Dr. Newcomb was the chief 

scientist of OUTPOST SUNRISE, a major acoustic measurement program, and has been 

principal investigator of several projects to study underwater ambient noise, broadband and 

narrowband signal propagation, and basin reverberation. Dr. Newcomb is an internationally 

recognized expert in underwater ambient noise and shipping noise. 

William M. Sanders has conducted research in underwater acoustics at the Naval Research 

laboratory since 1998. His areas of specialty are ambient noise, propagation modeling, data 

fusion and signal processing. He earned his Ph.D. from the University of Miami in 1998 in 

applied marine physics. He conducted research in underwater acoustics and signal processing for 

private industry between 1985 and 1992. He is a member of the Acoustical Society of America. 

James M. Stephens is a research faculty member of the Department of Physics and Astronomy at 

the University of Southern Mississippi (USM). Dr. Stephens holds a B.S. from Rice University, a 

Master’s degree from the University of Southern Mississippi, and a Ph.D. from the Georgia 

Institute of Technology, all in physics. Prior to joining USM, he was employed by WesternGeco 

in Houston as a project geophysicist and processing geophysicist. Dr. Stephens attended Rice 

University on an NROTC scholarship, and served as an officer in the United States Navy for 

nine years, including a tour at the Naval Oceanographic Office, located on the National Space 

Technology Laboratories (now Stennis Space Center), Mississippi. 

Christopher D. Walker received a B.S. in physics in 2002 from the University of Southern 

Mississippi. He is pursuing a graduate degree at the University of Southern Mississippi where he 

is also employed as a full-time staff research scientist. His research experience includes laser 

spectroscopy, signal processing, acoustics, modeling, simulation, and visualization. 
99 

Benjamin Brack earned a B.S. in physics from University of Southern Mississippi and worked at 

the USM Signal Research Center studying seismic airgun emissions and whale vocalizations. 

Grayson H. Rayborn received a B.S. in physics from the Rensselaer Polytechnic Institute and a 

Ph. D. in physics from the University of Florida. After a year on the faculty of Old Dominion 

University he joined the physics faculty of the University of Southern Mississippi where, except 

for a sabbatical year at the University of Nebraska, he remained until he retired from the faculty 

as Professor of Physics and Astronomy. He continues to pursue his research interests in signal 

processing, experimental atomic physics, and underwater acoustics as Professor Emeritus at the 

University of Southern Mississippi Signal Research Center. 

Natalia A. Sidorovskaia received a M.S. in radiophysics from the Gorky (presently Nizhny 

Novgorod) State University, an M.S. in physics from the University of New Orleans, and a Ph.D. 

in engineering and applied science from the University of New Orleans. After a two-year career 

in the oil industry with Landmark Graphics Corporation, Halliburton Company, she joined the 

Department of Physics, University of Louisiana at Lafayette where she is now an Assistant 

Professor. Her research interests include numerical modeling of sound propagation through 

oceanic waveguides; theoretical methods in scattering from objects; depth imaging techniques in 

seismic signal processing; seismic data management; methods of presentation and processing of 

deterministic and random signals, including the adaptive processing of highly noisy experimental 

data; methods of solutions of hydrophysical inverse problems (noise source imaging, ocean 

acoustic tomography). 

Arslan M. Tashmukhambetov received his B.S. degree in plasma physics from the Kazakh State 

University, and he is now a physics graduate student at the University of Louisiana at Lafayette. 

His research interests include digital signal processing, computational acoustics, solid state 

physics, and plasma physics. 

George E. Ioup received an S.B. in physics from the Massachusetts Institute of Technology and a 

Ph.D. in physics from the University of Florida. After one-year appointments as a postdoctoral 

fellow at the University of Connecticut and as an assistant professor of physics at the U. S. Coast 

Guard Academy, he joined the Department of Physics, University of New Orleans (UNO). He is 

now University Research Professor of Physics and Geophysics. He currently serves as Director 

of UNO at Stennis Space Center and has been president of the Southeastern Geophysical Society 

(SGS). His research interests include acoustic, geophysical, and aerospace signal analysis and 

processing; deconvolution, mathematical digital filtering, and spectral estimation; Fourier and 

wavelet transforms; higher order correlations and spectra; underwater acoustics; modeling and 

simulation; and computational physics. 

Juliette W. Ioup received a B.S. and M.S. in physics from the University of Florida and a Ph.D. 

in physics from the University of Connecticut. She has been a professor of physics at Xavier 

University of Louisiana, a geophysicist data processor at Texaco in New Orleans, and is 

presently a professor of physics, geophysics, and electrical engineering at the University of New 
100 

Orleans. Her research interests include geophysical, acoustic, and aerospace signal analysis and 

processing; deconvolution, mathematical digital filtering, spectral estimation; Fourier and 

wavelet transforms; neural networks; higher order correlations and spectra; underwater acoustics; 

modeling and simulation; and computational physics. She is a Fellow of the Acoustical Society 

of America and a member of ASA, SEG, AGU, IEEE, APS, AWIS, and SGS. 

Sean R. Chapin received a BS in Physics from Western Michigan University. After working as a 

research scientist in the Scientific Research Laboratory at Ford Motor Company, he obtained an 

MS in Applied Physics from the University of New Orleans (UNO). He is currently a physicist at 

the Naval Surface Warfare Center in Dahlgren, Virginia and is concurrently working on a PhD in 

Engineering and Applied Science from UNO. His research interests include underwater 

acoustics, radar, electro-optic sensors, modeling and simulation, signal and image processing, 

and track processing. 
101 

BOTTOM-MOORED HYDROPHONE MEASUREMENTS OF AMBIENT NOISE 

DURING STORMS IN THE GULF OF MEXICO 

Joal J. Newcomb, Naval Research Laboratory 

Mark Snyder and Wesley R. Hillstrom, Naval Oceanographic Office 

Ralph Goodman, University of Southern Mississippi 

Abstract 

The Littoral Acoustic Demonstration Center (LADC) deployed three Environmental Acoustic 

Recording System (EARS) buoys in the northern Gulf of Mexico (GOM) during the summer of 

2002 (LADC 02). The hydrophone of each buoy was approximately 50m from the bottom in 

water depths of 645m to 1,034m. During LADC 02, Tropical Storm Isidore and Hurricane Lili 

passed within approximately 73nmi and 116nmi, respectively, west of the EARS buoys. The 

proximity of these storm systems to the EARS buoys, in conjunction with wind speed data from 

three nearby NDBC weather buoys, allows for the direct comparison of underwater ambient 

noise levels with high wind speeds. These results are compared to the G.M. Wenz (Wenz 1962) 

spectra at frequencies from 1 kHz to 5.5 kHz. Anomalously high levels of ambient noise may be 

due to banding effects of the storms. Results of the ambient noise analysis will be presented. 

(Research supported by ONR). 

Introduction 

The Littoral Acoustic Demonstration Center (LADC) is an Office of Naval Research-funded 

consortium consisting of the University of New Orleans, the University of Southern Mississippi, 

the Naval Research Laboratory, and the University of Louisiana at Lafayette. LADC deployed 

three Environmental Acoustic Recording System (EARS) buoys in the northern GOM during the 

summer of 2002 (LADC 02) to study ambient noise and marine mammals. The LADC EARS 

buoy (developed by the Naval Oceanographic Office) is an autonomous, self-recording buoy 

capable of more than 66 days continuous recording of a single channel at an 11.7 kHz sampling 

rate. The hydrophone of each buoy was approximately 50m from the bottom in water depths of 

1,034m to 645m along an upslope track. The buoys were labeled EARS 1 (deepest), EARS 2, 

and EARS 3 (shallowest). Oceanographic data (CTD and XBT data) were obtained during each 

deployment along a longer upslope track and along a cross slope track centered at EARS 1. 

Bottom information for these tracks was obtained during LADC 01 (summer of 2001) from sidescan sonar data. 

During LADC 02, Tropical Storm Isidore and Hurricane Lili passed within approximately 73nmi 

and 116nmi, respectively, west of the EARS buoys. The proximity of these storm systems to the 

EARS buoys, in conjunction with wind speed data from three nearby National Data Buoy Center 

(NDBC) weather buoys (see Figure 2A.18), allows for the direct comparison of underwater 

ambient noise levels with high wind speeds. 
102 

Figure2A.18. Chart of storm system tracks during the summer of 2001 and 2002 relative to the EARS 

deployment site and the NDBC weather buoys. 

Ambient Noise Results 

The storm systems’ tracks were obtained from positional data published by the National 

Hurricane Center (NHC) indicated by the solid circles connected with straight lines in Figure 

2A.18. Wind speed estimates at the EARS location were obtained from an examination of wind 

speed and wave height measurement data obtained from the NDBC weather buoys. Ambient 

noise results were obtained from a spectral analysis of the EARS raw acoustic data. 

Hurricane Lili at closest approach passed about 116nmi west of the EARS buoys. All three 

NDBC buoys were used to estimate wind speed for each time period except for the time period 

where Hurricane Lili passed very close to NDBC buoy 42041. 

Figure 2A.19 illustrates the ambient noise results for Hurricane Lili for EARS 1 from 1 kHz to 

5.5 kHz. The closely grouped spectra are the noise levels for the time periods corresponding to 

published positions of Hurricane Lili and represent estimated wind speeds of 20 to 47kts. The 

much lower-level spectrum represents the results for a time period during which there were no 

storm systems in the GOM and is presented only for comparison. As expected, when Hurricane 
103 

Lili approached EARS 1, the wind speeds increased and the corresponding noise levels 

increased. Superimposed upon these results are the Wenz curves for Beaufort Wind Forces 

(BWF) of 5 and 8 (solid black lines) and the projected upper limit of prevailing noise. As can be 

seen from Figure 2A.18, the measured spectra agree well with the slope and levels of the BWF 8 

curve for wind speeds of 34kt to 40kt. Results from the EARS 3 buoy have overall higher 

spectral levels, but otherwise are very similar. 

Figure 2A.19. Illustration of the ambient noise results for EARS 1 during Hurricane Lili. 

Tropical Storm Isidore was less organized and weaker than Hurricane Lili. She was also a very 

large storm geographically. As can be seen from Figure 2A.18, TS Isidore passed approximately 

43nmi closer to the EARS buoys than Hurricane Lili at closest approach (73nmi west of EARS 

buoys). Consequently, the spectrum levels for TS Isidore are about the same as the spectrum 

levels for Hurricane Lili. All three NDBC buoys were used to estimate wind speed for each time 

period except for the time period where TS Isidore passed very close to NDBC buoy 42041. 

Figure 2A.20 illustrates the ambient noise results for TS Isidore from 1 kHz to 5.5 kHz for 

EARS 3. The closely grouped spectra correspond to the published positions of TS Isidore and 

represent estimated wind speeds of 21 to 55kt. The much lower level spectrum represents the 

results for a time period during which there were no storm systems in the GOM and is for 

comparison only. As expected, and similarly to the results for Hurricane Lili, when TS Isidore 

approached EARS 3, the wind speeds increased and the corresponding noise levels increased. 
104 

Figure 2A.20. Illustration of the ambient noise results for EARS 1 during Tropical Storm Isidore. 

There were some anomalous time periods during TS Isidore where the noise levels were much 

higher than those expected from the wind speed estimates (e.g., upper red curve in Figure 

2A.20). In those cases, acoustic data from 30 minutes before or after the original time period 

yielded results in line with wind speed estimates. 

Superimposed upon the results for TS Isidore are the Wenz curves for Beaufort Wind Forces 

(BWF) of 5 and 8 (solid black lines) and the projected upper limit of prevailing noise. As can be 

seen from Figure 2A.20, the measured spectra agree well with the slope and levels of the BWF 8 

curve for wind speeds of 34kt to 40kt, the sole exception being the anomaly noted previously. 

It is postulated that these anomalies might be due to the banding nature of tropical storm 

systems. Figure 2A.21 is a composite satellite photograph of TS Isidore clearly illustrating two 

major bands of the storm. In these bands, localized severe weather conditions are common (e.g., 

rain squalls, high wind speeds, tornadoes, etc.). 

If the anomalously high ambient noise levels were due to banding effects, it would be expected 

that they occurred periodically throughout the passage of the storm. Figure 2A.23 is a 

spectrogram of the ambient noise for a 24-hour period during TS Isidore. There are four 

broadband regions of high-level ambient noise starting near hour 12. Examined closely, these 

four bands do not have the characteristic scalloping associated with shipping noise. Further, they 

lack the low-frequency content and have more high-frequency content than the noise from a 
105 

Figure 2A.21. Satellite image of Tropical Storm Isidore illustrating banding. 

 

passing ship (e.g., high-level noise seen near hour 3, Figure 2A.22). An aural examination of the 

four broadband regions reveals no indication of shipping noise. 

Figure 2A.23 is an illustration of a six-minute average of the ambient noise during the first of the 

four bands of high level noise near hour 12 (upper data curve) and during a time period that does 

not contain a band (lower data curve). The ambient noise levels are superimposed upon the Wenz 

curves for BWF 5 and 8 and the upper limit of prevailing wind noise. As can be seen from Figure 

2A.23, the measured spectrum for the lower data curve agrees well with the slope and levels of 

the BWF 5 and 8 Wenz curves. The higher-level data is well above the BWF 8 Wenz curve and 

in fact is above the upper limit of prevailing wind noise. 

Also in Figure 2A.23 are the curves representing the noise levels expected from heavy and 

moderately heavy precipitation. The high-level data clearly agree well with the Wenz curve for 

heavy precipitation for frequencies below about 1,500Hz. Above 1,500Hz the data diverge from 

the heavy precipitation curve and fall off in a manner similar to the Wenz wind curves although 

at highly elevated levels. This would seem to indicate that the noise is some combination of 

noise due to wind and rain. 
106 

Figure 2A.22. Spectrogram of the ambient noise results for EARS 1 during Tropical Storm Isidore 

illustrating effects of banding. 

Jeffrey Nystuen at APL Washington has developed a mathematical relationship between rainfall 

amounts and recorded noise levels (Nystuen 2001). Table 2A.2. displays the rainfall amounts for 

the four bands based on the average noise levels of the bands. Rainfall amounts are displayed in 

mm/hour and in in/hour. 

Table 2A.2. Average noise levels for bands of TS Isidore compared to calculated rainfall amounts. 

Band Average Noise 

SPL (dB) 

Rain Rate 

(mm/hour) 

Rain Rate 

(in/hour) 

1 70.7 68.8 2.71 

2 69.6 58.4 2.30 

3 72.8 94.2 3.71 

4 71.4 76.4 3.01 
107 

Figure 2A.23. Illustration of the ambient noise results for EARS 1 during Tropical Storm Isidore (black) 

compared to Wenz curves (blue) and rain curves (red). 

Summary 

Ambient noise results in the frequency range of 1 kHz to 5 kHz from the LADC 2002 

experiment during Hurricane Lili and TS Isidore, with notable exceptions, are in good agreement 

with expected wind trends. They also agree well with the Wenz curves. The exceptions can be 

attributed to banding effects of the storms and are at least partially due to heavy precipitation. 

Acknowledgments 

This research was supported by ONR Program Element 62435N. 

References 

Nystuen, J.A. 2001. Listening to raindrops from underwater: An acoustic disdrometer. Journal of 

Atmospheric Ocean Technology 18:1640–1657. 

Wenz, G.M. 1962. Acoustic ambient noise in the ocean: Spectra and sources. Journal of the 

Acoustic Society of America 34:1936. 
108 

Joal J. Newcomb received a B.S. degree in physics and mathematics from Southwestern 

Oklahoma State University, an M.S. in atomic physics from Kansas State University, and a Ph.D. 

in experimental atomic physics from Kansas State University. He is currently a research 

physicist in the Acoustics, Simulations, Measurements & Tactics Branch of the Naval Research 

Laboratory at the John C. Stennis Space Center, Mississippi. Dr. Newcomb was the chief 

scientist of OUTPOST SUNRISE, a major acoustic measurement program, and has been 

principal investigator of several projects to study underwater ambient noise, broadband and 

narrowband signal propagation, and basin reverberation. Dr. Newcomb is an internationally 

recognized expert in underwater ambient noise and shipping noise. 

Mark Snyder received a B.S. degree in physics from the University of Illinois and an M.S. in 

physics from the University of New Orleans, where he is currently a Ph.D. candidate. He has 

worked as a geophysicist for Shell Oil Company in New Orleans. For the past twenty years he 

has worked as an oceanographer/physicist for the Naval Oceanographic Office (NAVOCEANO). 

He currently works in the Ocean Projects Department at NAVOCEANO. 

Wesley R. Hillstrom received a B.S. degree in geology from Wayne State University, Detroit, 

and an M.S. degree in marine science from the University of Southern Mississippi. Since 1979 

he has been a geophysicist with the Naval Oceanographic Office, currently involved in 

underwater acoustics with the Undersea Warfare Division. Mr. Hillstrom is a member of the 

American Geophysical Union, the Marine Technological Society, the Mississippi Academy of 

Sciences and Sigma Xi. 

Ralph R. Goodman received B.S. degrees in mathematics and physics, an M.S. degree in 

physics, and a Ph.D. in theoretical physics from the University of Michigan. His specialties in 

physics are solid-state physics and underwater acoustics. Dr. Goodman has served as Professor 

of Physics at Colorado State University, Associate Director of the Naval Research Laboratory, 

Director of the Naval Ocean Research and Development Activity, Director of NATO’s 

SACLANT Research Centre, Director of NCPA, and Professor of Acoustics at Pennsylvania 

State University. He is currently a Research Professor at the University of Southern Mississippi. 
109 

ANALYSIS OF BOTTOM-MOORED HYDROPHONE MEASUREMENTS OF GULF OF 

MEXICO SPERM WHALE PHONATIONS 

George E. Ioup and Juliette W. Ioup, University of New Orleans 

Natalia A. Sidorovskaia, University of Louisiana at Lafayette 

Rachel T. Walker, Stan A. Kuczaj, Christopher D. Walker, Grayson H. Rayborn, 

and Benjamin Brack, University of Southern Mississippi 

Andrew Wright, University of Wales, Bangor 

Joal Newcomb and Robert Fisher, Naval Research Laboratory – 

Stennis Space Center 

Abstract 

The Littoral Acoustic Demonstration Center (LADC) is an Office of Naval Research-funded 

consortium consisting of the University of New Orleans, the University of Southern Mississippi, 

the Naval Research Laboratory, and the University of Louisiana at Lafayette. LADC deployed 

three Environmental Acoustic Recording System (EARS) buoys in the northern Gulf of Mexico 

(GOM) during the summers of 2001 (LADC01) and 2002 (LADC02) to study ambient noise and 

marine mammals. The LADC EARS buoy (developed by the Naval Oceanographic Office) is an 

autonomous, self-recording buoy capable of 36 days (summer 2001) or 66 days (summer 2002) 

of continuous recording of a single channel at an 11.7 kHz sampling rate (bandwidth to 5859 

Hz). The hydrophone of each buoy was approximately 50m from the bottom in water depths of 

about 1,000m (EARS1), 800m (EARS2), and 600m (EARS3) along an upslope track. 

This paper contains recent analysis results for the sperm whale phonations measured on these 

LADC EARS buoys. The three topics treated and the four sections pertaining to the first topic, 

are as follow: 

 1. Identification of individual sperm whales from their clicks 

a) Acoustic properties of sperm whale clicks as a basis for individual whale identification 

b) Propagation modeling for sperm whale phonations 

c) Quantitative studies of the null pattern similarity in sperm whale phonations 

d) Self-organizing maps for sperm whale identification 

 2. Effects of passing vessels on sperm whales 

 3. Automated detection of sperm whale clicks 

Spectrograms of LADC northern GOM data containing sperm whale click codas strongly suggest 

that regularly spaced clicks in a coda have a spectral pattern that persists across all the clicks in 

that coda. These patterns are most simply described as nulls which persist across the successive 

click spectra in a coda and which vary from coda to coda. A conclusion is that each coda 

originates from a single whale and that all codas with similar properties come from the same 

whale. 
110 

Each sperm whale click can contain several separate pulses, i.e., peaks in the plot of click 

pressure versus time. It is quite possible that the spacing and other properties of the component 

pulses of a click could lead to the patterns observed in the click spectra. It is also possible that 

the patterns could be due to the interference of multiple arrivals at the hydrophone from a single 

click, due to reflections from the top and/or the bottom of the water column. These arrivals must 

be spaced within four msec of each other since that is the duration of these clicks. Propagation 

modeling is used to show that it is unlikely that the patterns in the spectra are due to the 

interference of multiple arrivals. 

All the individual click plots of pressure versus time for a single coda have similar character, 

which can be different from the character of the clicks in other codas. This suggests that a 

classification of individual sperm whales could be done based on the pressure versus time plots 

of a coda as well as based on the click spectra of a coda. 

Although echolocation clicks may seem to be less likely candidates for identifying individual 

whales due to the highly directional nature of these clicks, the results of Mohl et al. (2003) are 

analyzed to show that these clicks might also be used in identification. 

Attempts to match by eye spectral plots of different codas to associate them with individuals 

make it clear that automated quantitative methods are needed. The first method given is based on 

a similarity measure which evaluates numerically how alike two click spectra are. This method is 

applied to both coda click spectra and echolocation click spectra. The echolocation click spectra 

studied have an even greater similarity to each other than the coda click spectra considered. The 

similarity function analysis distinguished about 15 similar echolocation clicks in the time interval 

of 10 sec. The average click production rate is estimated as one click per second, which is 

consistent with the reported rate for deep sperm whale dives. Two similar null-pattern coda 

events are identified at the mid-buoy with a separation time of about 40 sec. 

The data used for the self-organizing map analysis consist of three sequential minutes recorded 

by LADC01 on the EARS2 buoy. These three minutes are selected because they contain 43 

sperm whale codas. Self-organizing maps (SOMs) are used to compare and classify the time 

series, the magnitudes of the Fourier transforms, and the wavelet transforms of each coda in 

order to determine how many whales are present, assuming that similar coda clicks would be 

produced by the same whale. The results show that SOMs can be used to classify underwater 

acoustic signals from sperm whales. For the 43 codas tested, SOMs of the time series data and 

wavelet transform coefficients agree for all 43 codas. The SOMs of the Fourier transform 

magnitudes agree with them for 40 codas. The time series and wavelet transform SOMs indicate 

that four whales are present while the Fourier SOM has five whales. All SOMs show that the 

whale in class 1 vocalizes much more than the others. 

Five weeks of continuous acoustic recording from the summer of 2001 (LADC01) are examined 

to assess the potential impact of vessel noise on sperm whale diving behavior. Sperm whale 

acoustic activity is defined by the number of clicks detected in Ishmael (version 1.0; Mellinger 

2001). A noise event is defined as a period during which a broadband spectrum noise level of ≥
111 

65 dB re: 1μPa, normalized to 1 Hz bands, across frequencies of 2-5.5 kHz, is achieved. Only 

noise events that are confirmed to be related to vessel traffic are used for analysis. 

Boat noise events were significantly more likely to occur at the EARS 1 site when compared to 

either the EARS 2 or the EARS 3 site, and there was a significant difference in the average 

duration of boat noise at the three buoys. Sperm whale acoustic activity was then compared for 

the periods 1, 5, and 15 minutes before and after each boat noise event. At the EARS 1 site, 

significant sign tests revealed sperm whale acoustic activity decreased after noise events for the 

5- and 15-minute comparisons, but not for the 1-minute periods. There was also no significant 

difference in sperm whale activity at the EARS 2 and EARS 3 sites for any of the time samples. 

Similar control comparisons are made to determine whether there are any differences in sperm 

whale acoustic activity before and after a period approximately equal to the average duration of 

recorded noise events (15 minutes) that contain no boat noise. Sign tests indicate no change in 

sperm whale activity for 1, 5, or 15 minutes before and after non-noise events at any site, suggesting noise was a possible factor for change in sperm whale acoustic behavior at the EARS 1 

location. It should be noted that the criteria for classification as a boat noise event is arbitrary and 

may not accurately reflect levels or frequencies that could elicit responses in sperm whales. 

The background noise on the LADC01 buoys tends to vary slowly compared to the abrupt 

changes in level due to clicks from sperm whales. The discrete derivative or finite difference of 

the time series seems is a good method of filtering the data for click detection. When the level 

rises above a threshold value, a possible click is detected. After using the discrete derivative to 

filter the data, standard pulse detection techniques are applied to locate and count sperm whale 

clicks in the data. 

Introduction 

The Littoral Acoustic Demonstration Center (LADC) is an Office of Naval Research-funded 

consortium consisting of the University of New Orleans, the University of Southern Mississippi, 

the Naval Research Laboratory, and the University of Louisiana at Lafayette. LADC deployed 

three Environmental Acoustic Recording System (EARS) buoys in the northern (GOM) during 

the summers of 2001 (LADC01) and 2002 (LADC02) to study ambient noise and marine 

mammals. The LADC EARS buoy (developed by the Naval Oceanographic Office) is an 

autonomous, self-recording buoy capable of 36 days (summer 2001) or 66 days (summer 2002) 

of continuous recording of a single channel at an 11.7 kHz sampling rate (bandwidth to 5859 

Hz). The hydrophone of each buoy was approximately 50m from the bottom in water depths of 

about 1,000m, 800m, and 600m along an upslope track. The buoys were labeled EARS 1 

(deepest), EARS 2, and EARS 3 (shallowest). Oceanographic data (CTD and XBT data) were 

obtained during each deployment along a longer upslope track (from 1100m to 200m depth) and 

along a cross slope track centered at EARS 1. Bottom information for these tracks was obtained 

during LADC 01 from chirp sonar data (Turgut et al. 2002). Figure 2A.24 shows the upslope and 

cross slope survey tracks. The whale symbols in the figure represent sperm whale sightings. Note 

that the buoys were deployed in the region of the greatest number of sightings. 
112 

Figure 2A.24. Map shows whale symbols at sperm whale sightings and black dots for oil platforms. Cross 

slope and upslope tracks for LADC01 and LADC02 are shown in red. Upslope track ends at 

the 200m contour. Cross slope track is at the 1000m contour. Hydrophones are placed at the 

600m, 800m, and 1,000m contours. Oceanographic surveys were done along the upslope and 

cross slope lines. 

This paper contains recent analysis results for the sperm whale phonations measured on these 

LADC EARS buoys. The three topics treated and the four sections pertaining to the first topic 

are as follow: 

 1. Identification of individual sperm whales from their clicks 

a) Acoustic properties of sperm whale clicks as a basis for individual whale identification 

b) Propagation modeling for sperm whale phonations 

c) Quantitative studies of the null pattern similarity in sperm whale phonations 

d) Self-organizing maps for sperm whale identification 

 2. Effects of passing vessels on sperm whales 

 3. Automated detection of sperm whale clicks 

As stated, Topic A is treated in four sections. In the first, the possibility of acoustically 

identifying individual sperm whales from the properties of their clicks is discussed. This 

approach requires that click properties not be primarily due to effects of acoustic propagation 

through the water column. The second section presents acoustic propagation modeling to 
113 

illustrate the effects of propagation. The third section is devoted to a similarity technique that 

associates sperm whale clicks from a single individual. Finally for this part of the analysis, the 

fourth section describes the use self-organizing maps to group the codas from individual whales. 

The fifth section addresses the second topic and explores the effects of shipping noise on sperm 

whale click rates. The sixth section is for the third topic and presents a computational automated 

sperm whale click detector. 

Identifying Individual Sperm Whales from the Acoustic Properties of Their Clicks 

Spectrograms of LADC northern GOM data containing sperm whale click groups strongly 

suggest that regularly spaced clicks in a group have a spectral pattern that persists across all the 

clicks in that group. These patterns are most simply described as nulls that persist across the 

successive click spectra in a group. A preliminary conclusion is that each group of clicks 

originates from a single whale and all groups with similar properties come from the same whale. 

In this and the following three sections, this idea is developed. Preliminary analysis has been 

presented at a meeting of the Acoustical Society of America (Ioup et al. 2004). 

In Figures 2A.25(a)–(d), the first four 4-second spectrograms are shown from one minute of data 

under consideration. The minute was taken from the data measured by the EARS 2 buoy in 

LADC01 and is very rich in groups of sperm whale clicks. The top graph shows the voltage 

versus time. The voltage is proportional to the pressure measured by the hydrophone. The middle 

spectrogram goes from zero to 5,859 Hz, showing the full spectrum of the recorded data. The 

bottom figure displays only from zero to 1,000 Hz. It shows the strong ambient noise at low 

frequencies, mainly occurring below 100 Hz except in Figure 2A.25(c). Between 8.5 and 9.5 

seconds, the red part of the spectra goes above 200 Hz due to an airgun shot 67 miles away. 

From the middle plot in each of the Figures 2A.25(a)–(d), one can see the groups of clicks 

referred to earlier and the null patterns that persist across the groups of clicks. These patterns 

vary from being quite striking to being subtle and not as consistent across the clicks in a group. 

An important point to note is that the null patterns change from group to group. It is the existence 

of these null patterns that strongly suggests the possibility of identifying individual whales. 

 

Zimmer (2004) has analyzed similar data from LADC EARS buoys in the Mediterranean Sea. 

He believes that the groups of clicks are sperm whale codas used for communication and 

generally emitted by the whales in the top 100m of the water column. A group of clicks is 

therefore referred to as a coda in the remainder of this discussion. 

Norris and Harvey (1972), Gordon (1981), and Mohl et al. (2003) discuss the time structure of 

individual sperm whale clicks. Each click can contain several separate pulses (peaks in the plot 

of click pressure versus time). It is possible that spacing and other properties of the component 

pulses of a click could lead to the patterns observed in the click spectra. Dougherty (1999) has 

investigated techniques for identifying sperm whales acoustically from the properties of their 

clicks. It is possible that the patterns could be due to interference of multiple arrivals at the hydrophone from a single click, due to reflections from the top and/or bottom of the water column. 
114 

Figure 2A.25. 800m mooring data extracted from a 60sec segment beginning at Julian Day 213, Zulu 0 hr, 9 

min, 37 sec. Figures. 2A.25 (a) – (d) each give four seconds of data. They give sequentially the 

first four 4-sec segments of data for the 60 sec of data being investigated. In each, the top plot is 

the voltage (proportional to pressure) amplitude versus time. The middle and bottom graphs of 

(a) – (d) are spectrograms. All frequencies up to 5859Hz are shown in the middle graphs and 

frequencies up to 1,000Hz are shown in the bottom graphs. Broadband transform lines in the 

middle graphs are sperm whale clicks and closely spaced clicks are codas. The red peak in the 

bottom graph of (c) is the seismic airgun. Since it is 107km away from the EARS buoy, 

significant reverberation is present. 
115 

To gain insight into these possibilities, it is helpful to examine the voltage (pressure) amplitude 

versus time plots for the clicks within a coda. Figures 2A.26(a) and (b) show the click amplitude 

versus time for the clicks in two different codas, respectively. The voltage amplitudes of each 

click of a coda are offset by a different constant so they can all be observed on one plot. There 

are two important details to note in Figure 2A.26. The first is that most of the significant 

amplitude for each click occurs within 4 msec. This means that if different propagation path 

arrivals are to interfere to give the spectral patterns, they must arrive within 4 msec of each other. 

This subject is explored in detail in the next section. 

The second important detail is that all the click plots of amplitude versus time for a single coda 

have similar character, which is different from the character of the clicks of the other coda, as is 

manifest in the contrast between the click plots of Figure 2A.26(a) and those of Figure 2A.26(b). 

This suggests that a classification of individual sperm whales could be done based on the 

pressure versus time plots of a coda as well as based on the click spectra of a coda. This is 

discussed in the section on self-organizing maps. 

Figure 2A.26. Voltage amplitude versus time plots for all the clicks in one coda (a), and in another coda (b). 

Voltage in each click is offset for clarity. 

To gain a clearer picture of the spectral similarity of the clicks within a coda, it is helpful to overplot the magnitude of the Fourier spectrum of each of the clicks of a single coda. In the minute of 

interest there are 15 codas. Figures 2A.27(a)–(c) show all 15, with five codas to a figure. Most of 

the codas show fair to excellent consistency among the individual click spectra of a coda. There 

are a very few outliers, which presumably are due to another whale clicking while the coda was 

in progress. These can easily be edited out. One can look at the fifteen coda plots to try to pick 

pairs by eye that could belong to the same whale. Figures 2A.28(a)–(c) give the results. In Figure 

2A.28(a) the overplotted click spectra of two different codas, chosen because of their click 

spectra similarity, are shown in the top and bottom plots, respectively. These two coda click 

spectral overplots very closely resemble each other. If this method is valid, it can be concluded 
116 

Figure 2A.27. Each graph is an overplot of the Fourier magnitude spectra for all the clicks in one coda. Five 

different codas are shown in each of (a), (b), and (c). 

with little doubt that these codas came from the same whale. The next pair selected, shown in 

Figure 2A.28(b), are similar to each other but the resemblance is not as striking as the first pair. 

These two codas probably come from the same whale, but the conclusion is reached with less 

confidence. Finally, the pair shown in Figure 2A.28(c) is selected. For this pair there is even less 

confidence that the pair of codas came from the same individual. It is a reasonable assumption 

that human qualitative judgments are not the best way to do these pairings. Automated, 

quantitative methods are needed. Two possible methods are discussed in the third and fourth 

sections of this paper, on similarity analysis and on self-organizing maps, respectively. 

Thus far the discussion has focused on communication clicks within codas. These clicks may be 

somewhat omni-directional, to serve the communication function. Echolocation clicks, in 

contrast, are known to be highly directional, as discussed by Mohl et al. (2003) and the 

references cited therein. The dominant p1 peak (pulse) is much stronger than the other peaks onaxis, and the on-axis p1 peak is much stronger than all the peaks of a click measured 

significantly off-axis. Figure 2A.29 of Mohl et al. is an important one. It shows the spectra of 

over 100 successive p1 pulses of an echolocating whale versus click number. The frequencies go 

to 25 kHz. Presumably because of the directionality of the clicks, the spectra vary markedly from 

click to click. This suggests that it might be difficult to identify whales by their echolocation 

clicks. This was assumed to be the case until the similarity analysis indicated otherwise. 
117 

Figure 1A.28. Three pairs of overplotted spectra of clicks within a coda, one in each of (a), (b), and (c). Each 

pair could be from the same whale; i.e., (a), (b), and (c) each show a pair of codas from a 

different whale. 

Closer inspection of Figure 2A.29 of Mohl et al. gives insight into why it might also be possible 

to use the echolocation clicks to identify individual whales acoustically. For the somewhat offaxis clicks (the first 102 clicks of the 108 in the figure), the click-to-click changes are all 

happening above about 5 kHz. Since the EARS data only go to 5,859 Hz, the current analysis is 

only considering the part of the spectrum which is distinctive and fairly robust against changes in 

direction as long as the click is somewhat off-axis. A preliminary suggestion then is to filter 

somewhat off-axis echolocation clicks down to a 5 to 6 kHz upper limit (if higher frequencies 

have been measured) before using them for acoustic identification of individuals. The on-axis p1 

pulses (the last 6 of the series of 108 in Mohl et al. Figure 2A.29, also shown in Mohl et al. 

Figure 2A.32, labeled p1) do have spectra which are different in character from the of-axis p1 

spectra, even below 5,000 Hz, and not as distinctive. These clicks may or may not be useful for 

identifying individuals. In any case, the similarity analysis of the third section of this paper is 

applied to both coda and echolocation clicks. 
118 

Figure 2A.29. Temporal structure of arrivals on the 740 m deep EARS buoy for the mammal depth of 50 m 

and the ranges of 510, 1020, 2041, 5000 m from the receiving buoy. 

Propagation Modeling for Sperm Whale Phonations 

At this point, a reasonable question to ask is whether the spectral interference structure is caused 

by propagation effects and could be utilized for localization of a sperm whale, or if it is caused 

by the particular features of a whale phonation apparatus and could be an attribute for the 

individualization of sperm whales. This section addresses this question. 

The environmental parameters measured during the experiment (sound speed profile in the water 

column, bottom properties) were input in the ray-propagation model Bellhop to generate the time 

sequence of direct and reflected arrivals for different hypothetical mammal locations 

(http://www.hlsresearch.com/oalib/Rays/; Sidorovskaia et al. 2004). Figure 2A.29 shows the 

temporal structure of arrivals on the 740 m deep EARS2 hydrophone for a mammal depth of 50 

m, where coda signals can be produced. The horizontal ranges to the EARS buoy are 510, 1020, 

2041, and 5000 m, respectively. It can be seen from the presented plots that the delay between 

the direct and first reflected (Surface Reflected, SR) arrivals varies from 50 msec to 18 msec for 

ranges from 500 to 2,000 m, with a train duration of the first four arrivals between 100 msec to 

45 msec at the 740 m deep EARS hydrophone. The direct and surface reflected arrivals are 
119 

overlapping for the range of 5,000 m. The bottom reflected arrivals are significantly attenuated 

for smaller grazing angles (ranges > 2,000 m). The next set of simulation results (Figure 2A.30) 

is produced for a mammal depth of 400 m which would correspond to the temporal structure of 

direct and reflected arrivals from an animal descending to foraging depths. In the mid-depth 

echolocation clicks the separation between the direct and first reflected arrival (Bottom 

Reflected, BR) varies from 40 msec to 10 msec for ranges from 500 to 5,000 m. The direct and 

bottom reflected arrivals do not overlap up to 5 km in range. The bottom reflected arrivals are 

significantly attenuated for smaller grazing angles (range > 1,000 m). Another foraging depth 

(about 700 m deep source location) echolocation signal temporal structure was previously simulated (Sidorovskaia et al. 2004) and also supports the conclusions stated in the next paragraph. 

Figure 2A.30. Temporal structure of arrivals on the 740 m deep EARS buoy for the mammal depth of 400 m 

and the ranges of 510, 1020, 2041, 5000 m from the receiving buoy. 

Thus, propagation modeling suggests that the null pattern structure for the short-time click 

spectra (4 msec) and relatively close positioning of an animal could be interpreted as being due 

to distinct features of a mammal phonation apparatus for any type of phonations (clicks, shortrange clicks, and clicks within codas). Independent algorithms are needed for sperm whale 

individualization based on the acoustic signature from single hydrophone recordings to confirm 
120 

the hypothesis that the null pattern or other features could be efficient tools in sperm whale 

acoustic individualization. The research on this topic is now in progress, and some of the results 

are discussed below. 

Quantitative Studies of the Null Pattern Similarity in Sperm Whale Phonations 

As the first step in developing automatic tools for associating sperm whale clicks with similar 

null patterns, a similarity analysis algorithm was implemented. Figure 2A.31 shows 1-second 

fragment of the LADC data rich in the sperm whale phonations with 4-msec window 

spectrograms on the right for all three buoys (the 1,000 m contour EARS1 buoy is on the top). 

Two types of phonation events can be distinguished in these data sets: the communication, 

“coda-like” event on the middle buoy and regular echolocation clicks on the shallow buoy. The 

arrows on Figure 2A.31 identify two clicks from two different events whose spectra were taken 

to be reference spectra, ( ) ref i s f . One minute of data for all three buoys was processed to find 

clicks with identical or similar null patterns. The similarity function is introduced as: 

1 ; S {s( fi) }, R {sref ( fi) } S R

S R SIM = = ⋅• = − r r r r

r r

, (1) 

where R

r

 is a multi-dimensional (frequencies treated as independent dimensions) vector 

containing the amplitudes of spectral components present in the reference spectrum, S

r

 is a 

vector of amplitudes of the instant 4-msec windowed spectrum from 60 seconds of data, • is the 

scalar product of two vectors. If two spectra have a similar null pattern, the normalized scalar 

product of two vectors will be close to one. The thresholds for identifying two phonation events 

as having a similar null pattern were set to be a 1% difference from one in the scalar product for 

echolocation clicks and to be 5% for codas. The results of the analysis are shown in Figure 

2A.32. The right-hand graphs are the temporal histograms of the number of clicks that were 

identified as having similar null patterns. The similarity function analysis distinguished about 15 

similar echolocation clicks in the time interval of 10 seconds. The histogram statistics represents 

the mix of direct and reflected arrivals (refer to Figure 2A.32(a)). The average click production 

rate could be estimated as 1 click per second, which is consistent with the reported rate for deep 

sperm whale dives (Goold and Jones, 1995). The absence of other picks could be speculatively 

attributed to the high directionality of the echolocation clicks (Mohl et al. 2003). Two similar 

null-pattern coda events are identified at the mid-buoy with a separation time of about 40 

seconds (refer to Figure 2a.32(b)). Presumably, the communication signals are omni-directional; 

consequently, we could identify the same animal at a later time. There are also some coda-like 

events on the deep buoy with the same null pattern as the reference one that requires more 

detailed analysis. In conclusion, the similarity function is shown to be an efficient quantitative 

algorithm to single out similar null pattern clicks. 
121 

Figure 2A.31. 1-second fragment of the LADC data rich in the sperm whale phonations with the 4-msec 

window spectrograms on the right for all three buoys (the 1000 m contour buoy is on the top). 

Self-Organizing Maps for Sperm Whale Identification 

Self-Organizing Maps 

A self-organizing map (SOM) is the “result of a nonparametric regression process that is mainly 

used to represent high-dimensional, nonlinearly related data items in an illustrative, often twodimensional display, and to perform unsupervised classification and clustering” (Kohonen, 

1997). 

The inputs to a SOM, the features or attributes, may be numerical values or binary (1’s and 0’s 

indicating the presence or absence of a particular feature or attribute). The weight values may be 

initialized as all zeros, all ones, selected data values, random numbers, or other values relevant to 

the particular data set. Each feature set is presented to the SOM, and the “distance” from each 

node computed. The distance can be the Euclidian distance of each data set from each node in 

the one- or two-dimensional weight matrix. The minimum distance determines the winning node. 

The winning node and the nodes in a specified neighborhood of the winner are updated by 
122 

Figure 2A.32. Similarity analysis results for: (a) echolocation clicks, (b) communication signals. 

increasing their weights. The amount of the update and the neighborhood size decrease with the 

number of iterations. Repeated presentations of the input data sets train the weight matrix so that 

one node (or some few adjacent nodes) is most responsive to a particular input. This node 

determines the classification of the output. 

Figure 2A.33 is a two-dimensional plot illustrating the use of a SOM. In the upper left diagram, 

two groups of blue points are easily separated by the human eye. All the initial “centers” for the 

SOM are chosen to be at the origin and are marked with red circles. The upper right plot shows 

the results after one iteration. One red “center” has moved to the middle of the plot, and the 

remaining two are still at the origin. After two iterations, shown in the lower left plot, one red 

“center” is located at the center of the upper group of blue points and the other at the center of 

the lower group of blue points. There is no change after three iterations, shown in the lower right. 

There were only two groups of blue points, so the initial third red center was not needed and has 

not moved from the origin. 
123 

Figure 2A.33. SOM example. 

SOMs are used here for classification of underwater acoustic signals that contain sequences of 

clicks made by sperm whales (Ioup and Ioup 2004). A one-dimensional SOM with numerical 

inputs is used to separate the signals into classes with similar properties, and results are presented 

in both graphical and tabular form. 

Underwater Acoustic Data 

The data used here consist of three sequential minutes recorded by LADC01 on one of three 

EARS buoys (EARS2) in the northern Gulf of Mexico during the summer of 2001. These three 

minutes were selected from more than three months of data (more than one month on each buoy) 

because there were many instances of sperm whale clicks. 

Figure 2A.34 shows the middle minute of data referred to in the first section of this paper. The 

top plot gives the signal amplitude versus time in seconds. The middle plot is the spectrogram of 

this time series, with the frequency axis vertical. Frequencies up to 5,859 Hz are shown. The 

bottom plot is the same with frequencies shown only up to 1,000 Hz. The large amplitude red 

“lumps” at the low frequencies are a seismic airgun conducting a survey 67 miles away from the 
124 

EARS buoy. Frequencies below 300 Hz will be filtered out for the subsequent processing. The 

broadband clicks of the sperm whales can be seen well, both single isolated clicks and in groups 

called codas. The codas will be used in the research described in this section. 

Figure 2A.34. Top: Time series data for one minute. Middle and Bottom: Spectrogram of data. 

Codas are usually used for communication when the whales are near the ocean surface. Since 

each coda could be assumed to be made by one whale, only the short times (about 0.6 sec) for 

each coda were selected out of each minute for processing. There were 43 codas in the three 

minutes, each containing from three to 15 clicks. Self-organizing maps are used to compare the 

time series, the Fourier transforms, and the wavelet transforms of each coda in order to 

determine how many whales are present, assuming that similar coda clicks would be produced 

by the same whale. 

Four representative codas are shown in Figure 2A.35. The time axis is horizontal to the right and 

the amplitude is shown vertically. Each click in the coda is displaced slightly into the page 

according to the time it was emitted during the coda. 

The discrete Fourier transform (DFT) is computed using a Fast Fourier Transform (FFT) 

algorithm (Bracewell 2000). 
125 

Figure 2A.35. Four representative codas. 

Wavelet Transforms 

Any function y(x) may be expanded in a linear combination of basis functions 

 y(x) = Σ ask wsk(x) , (2) 

where the ask are the amplitudes of the individual basis functions wsk(x) which have 

mathematically desirable features (Daubechies 1992; Strang and Nguyen 1996; Mallat 1998). 

The two parameters s and k describe the scaling and shifting of the mother wavelet. The discrete 

wavelet transform (DWT) is used in the same fashion as the DFT. 

The choice of the wavelet to use is data dependent. The most common wavelet families are the 

Daubechies (including the Haar wavelet), coiflet, biorthogonal, symmetric, Morlet, and Mexican 

hat, although there are many more. Wavelets used here include the haar, db4, sym4, coif2, 

bior6.8, which produced identical classes; and bior2.2, bior3.9, which had classes similar to the 

others. All were at level one using the MATLAB DWT function. 
126 

Results 

Trace editing was performed by hand to remove clicks from each coda that were obviously much 

different from the rest. These extraneous clicks were probably individual clicks from another 

whale received during the time that the coda was recorded. 

The self-organizing map procedure was used to find a representative click from each coda. Five 

iterations were performed. The result obtained is the same as the average of the clicks in that 

coda. 

 

The 43 representative clicks (one from each coda) were collected together. Figure 2A.36 shows 

the time series in the top plot, the magnitude of the Fourier transform coefficients in the middle 

plot, and the wavelet transform coefficients using a Daubechies db4 wavelet in the bottom plot. 

Each representative click is displaced slightly along the axis into the paper and plotted with a 

different color to distinguish it. The DFT coefficients were lowpass filtered at 300 Hz to remove 

low-frequency noise such as the airgun signals. 

 

Figure 2A.36. Top: 43 representative clicks, 1 per coda. Middle: FFT amplitude, and Bottom: Wavelet 

transform, of data shown at top. 
127 

The self-organizing mapping procedure was applied to each of the three groups of signals. The 

order of presentation did not matter since identical results were produced using either the first or 

the last signal as the initial input. Twenty iterations were used (forty for the FFT). Six to twentyfive classes were allowed in different trials. 

 

Figure 2A.37 shows results obtained with the time series. There are six possible classes (whales). 

Signals from each class are plotted together, using the colors from the previous figure. It can be 

seen that only the first four classes are populated, indicating that there are probably four whales 

present. The whale in class 1 vocalizes much more than the others. 

Figure 2A.37. SOM classes using time series data. 

 

Figure 2A.38 presents the results using the SOM with the Fourier transform magnitudes. Five 

classes contain signals, and although the colors seem to indicate a large disagreement with the 

classes of the time series, there are only three codas differing, as will be shown below with the 

table of classes (Table 2A.3). 

 

Figure 2A.39 presents the results using the db4 wavelet transform coefficients. It can be seen that 

the signals are sorted into the same four classes as they were using the time series. 
128 

Figure 2A.38. SOM classes using FFT amplitude data. 

Figure 2A.39. SOM classes using db4 wavelet transform data. 
129 

Table 2A.3 shows the data set number and the class for each of the codas for each of the three 

inputs. In general, there is excellent agreement. The time series and the DWT coefficient inputs 

give results that agree on classes for all 43 codas. The Fourier transform magnitudes give results 

that agree for 40 codas. The three which disagree are marked with an asterisk. 

Table 2A.3. Data set number and the class for each of the codas for each of the three inputs. 

Set Time FFT DWT Set Time FFT DWT 

* 1 4 5 4 23 1 1 1 

 2 1 1 1 24 1 1 1 

 3 4 4 4 25 3 3 3 

 4 3 3 3 26 1 1 1 

 5 3 3 3 27 3 3 3 

 6 1 1 1 28 1 1 1 

 7 3 3 3 29 1 1 1 

 8 1 1 1 30 2 2 2 

 9 1 1 1 31 1 1 1 

 10 1 1 1 32 1 1 1 

 11 1 1 1 33 1 1 1 

 12 1 1 1 34 2 4 2 

 13 1 1 1 35 1 1 1 

 14 1 1 1 36 1 1 1 

 15 1 1 1 37 1 1 1 

 16 3 3 3 38 1 1 1 

* 17 4 5 4 39 1 1 1 

 18 2 2 2 40 1 1 1 

 19 2 2 2 41 2 2 2 

 20 2 2 2 42 1 1 1 

 21 1 1 1 43 2 2 2 

 22 1 1 1 

Conclusions 

This study has shown that self-organizing maps can be used to classify underwater acoustic 

signals from sperm whales. For the 43 codas tested here, the time series data and wavelet 

transform coefficients agree for all 43 codas. Fourier transform magnitudes agree with them for 

40 codas. This data set is small, however. Furthermore, other features (including but not limited 

to the interpulse interval) should be included in the SOM procedure. 

Reactions of Sperm Whales to Passing Vessels as Determined Through Remote 

Acoustic Recordings 

Five weeks of continuous acoustic recording from the summer of 2001 (LADC01) were 

examined to assess the potential impact of vessel noise on sperm whale diving behavior. Sperm 

whale acoustic activity was defined by the number of clicks detected in Ishmael (version 1.0; 

Mellinger 2001). A noise event was defined as a period during which a broadband spectrum 

noise level of ≥ 65 dB re: 1μPa, normalized to 1 Hz bands, across frequencies of 2–5.5 kHz, was 

achieved. Only noise events that were confirmed to be related to vessel traffic were used for 
130 

analysis. Other events were excluded, such as if the threshold was exceeded by sound produced 

by sperm whales. 

There were 171 boat noise events identified at EARS 1, 103 at EARS 2, and 113 at EARS 3. 

Boat noise events were significantly more likely to occur at the EARS 1 site when compared to 

either the EARS 2 site, χ2

 = 16.87, p < 0.01, or the EARS 3 site, χ2 = 11.84, p < 0.01. There was 

a significant difference in the average duration of boat noise at the three buoys (one-way 

ANOVA, F = 5.866, p < 0.05). Sperm whale acoustic activity was then compared for the periods 

1, 5, and 15 minutes before and after each boat noise event. At the EARS 1 site, significant sign 

tests revealed that sperm whale acoustic activity decreased after noise events for the 5- and 15-

minute comparisons (Z = -0.2069, p = 0.039; Z = -2.625, p = 0.009), but not for the 1-minute 

periods. There was also no significant difference in sperm whale activity at the EARS 2 and the 

EARS 3 site for any of the time samples. 

Similar control comparisons were made to determine if there were any differences in sperm 

whale acoustic activity before and after a period approximately equal to the average duration of 

recorded noise events (15 minutes) that contained no boat noise. Sign tests indicated no change 

in sperm whale activity for 1, 5, or 15 minutes before and after non-noise events at any site, 

suggesting noise was a possible factor for change in sperm whale acoustic behavior at the EARS 

1 location. An additional comparison was then made at this site, contrasting the clicks detected in 

5-minute periods before and after the noise event that was separated from the event by 20 

minutes (i.e., the period 25-20 minutes prior to event onset was compared to the period 20–25 

minutes after event conclusion). A significant sign test revealed that there continued to be a 

reduced level of clicks detected as long as 25 minutes after noise events at EARS 1. 

Estimates of the number of whales present proved to be largely inaccurate when determined 

using our detection criteria in Ishmael. Instead the five minutes periods before and after each 

vessel noise event at each EARS site were manually examined, and coded to reflect the number 

of whales contributing to the clicks recorded. They were coded as 0 for no sperm whale activity, 

1 for one whale, or 2 for more than one whale. A significant decrease in the perceived number of 

whales was observed after noise events at EARS 1, indicating fewer whales producing clicks 

(Z = -3.40, p = 0.001), but this was not the case at either the EARS 2 or EARS 3 sites. 

In conclusion, the most noise events related to vessels were detected at the EARS 1 location, 

which was also the site at which the events were typically longest in duration. Additionally, there 

were fewer clicks, and whales, detected after boat noise events at the EARS 1 site, with effects 

lasting at least 25 minutes after the conclusion of an event. It should be noted, however, that the 

criteria for classification as a boat noise event was arbitrary and may not accurately reflect levels 

or frequencies that could elicit responses in sperm whales. Consequently, further analysis of this 

data, and data from LADC02, are needed to investigate the possibility of effects similar to those 

observed at EARS 1 at either the EARS 2 or EARS 3 sites, using different noise event criteria. 

Additional work is also required to determine if the effects currently seen at EARS 1 are acoustically mediated. Finally, additional analyses may potentially be able to differentiate between 

whale movement and changes in their acoustic behavior. 
131 

Automated Detection of Clicks 

The LADC data from 2001 are digitally sampled recordings of the ambient noise of the northern 

GOM. The background tends to vary slowly compared to the abrupt changes in level due to 

clicks from sperm whales. The discrete derivative or finite difference as given in Equation (3) of 

the time series seems to be a good method of filtering the data for click detection. 

f '(x) = f (x +1) − f (x) (3) 

Figure 2A.40 shows a sample of data with a click embedded in a slowly varying background. 

Figure 2A.41 is the discrete derivative of the data in Figure 2A.40, the first step in the automated 

click detection algorithm. When the level rises above a threshold value, a possible click is 

detected. After using the discrete derivative to filter the data, standard pulse detection techniques 

may be applied to locate and count sperm whale clicks in the data. 

Figure 2A.40. A sample of data with a click embedded in a slowly varying background. 
132 

Figure 2A.41. The discrete derivative of the data in Figure 2A.40, the first step in the automated click 

detection algorithm. 

Acknowledgments 

The authors gratefully acknowledge support from the Office of Naval Research, PE #62435N, 

Program Officer Dr. Mel Briscoe. They also greatly appreciate the development of the EARS 

buoy and other technical support by the scientists and engineers of the Naval Oceanographic 

Office. They are indebted to many experts in sperm whale acoustics for helpful discussions. 

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Presented at the Acoustical Society of America, New York, 24–28 May and abstracted in 

Journal of the Acoustical Society of America 115:2556. 

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Mohl, B., M. Wahlberg, P.T. Madsen, A. Heerfordt, and A. Lund. 2003. The monopulsed nature 

of sperm whale clicks. Journal of the Acoustical Society of America 114:1143–1154. 

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sperm whale. NASA SP-262:397–417. 

Sidorovskaia, N.A., G.E. Ioup, J.W. Ioup, and J.W. Caruthers. 2004. Acoustic propagation 

studies for sperm whale phonation analysis during LADC experiments. High-frequency 

Ocean Acoustics, M.B. Porter, M. Siderius, W.A. Kuperman, eds. AIP Conference 

Proceedings 288–295.

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Proceedings, MTS/IEEE OCEANS2002 Conference. Pp. 2248–2252. 
134 

Zimmer, W. 2004. Personal communication. NATO SACLANT Undersea Research Center, La 

Spezia (SP), Italy. 

George E. Ioup received an S.B. in physics from the Massachusetts Institute of Technology and a 

Ph.D. in physics from the University of Florida. After one-year appointments as a postdoctoral 

fellow at the University of Connecticut and as an assistant professor of physics at the U. S. Coast 

Guard Academy, he joined the Department of Physics, University of New Orleans (UNO). He is 

now University Research Professor of Physics and Geophysics. He currently serves as Director 

of UNO at Stennis Space Center and has been president of the Southeastern Geophysical Society 

(SGS). His research interests include acoustic, geophysical, and aerospace signal analysis and 

processing; deconvolution, mathematical digital filtering, and spectral estimation; Fourier and 

wavelet transforms; higher order correlations and spectra; underwater acoustics; modeling and 

simulation; and computational physics. 

Juliette W. Ioup received a B.S. and M.S. in physics from the University of Florida and a Ph.D. 

in physics from the University of Connecticut. She has been a professor of physics at Xavier 

University of Louisiana, a geophysicist data processor at Texaco in New Orleans, and is 

presently a professor of physics, geophysics, and electrical engineering at the University of New 

Orleans. Her research interests include geophysical, acoustic, and aerospace signal analysis and 

processing; deconvolution, mathematical digital filtering, spectral estimation; Fourier and 

wavelet transforms; neural networks; higher order correlations and spectra; underwater acoustics; 

modeling and simulation; and computational physics. She is a Fellow of the Acoustical Society 

of America and a member of ASA, SEG, AGU, IEEE, APS, AWIS, and SGS. 

Natalia A. Sidorovskaia received a MS in radiophysics from the Gorky (presently Nizhny 

Novgorod) State University, a MS in physics from the University of New Orleans, and a Ph.D. in 

Engineering and Applied Science from the University of New Orleans. After a two year career in 

the oil industry with Landmark Graphics Corporation, Halliburton Company, she joined the 

Department of Physics, University of Louisiana at Lafayette where she is now an Assistant 

Professor. She has published more than 20 scientific publications including contributions to two 

books on ocean acoustics. She received two Bill Good Awards from the Physics faculty of the 

University of New Orleans in recognition of outstanding research in Physics and a Distinguished 

Graduate Research Award at the Doctoral Level from the University of New Orleans. She was 

selected to be published in the 14th Edition of “Who’s Who in the World”. Her research interests 

include numerical modeling of sound propagation through oceanic waveguides; theoretical 

methods in scattering from objects; depth imaging techniques in seismic signal processing; 

seismic data management; methods of presentation and processing of deterministic and random 

signals, including the adaptive processing of highly noisy experimental data; methods of 

solutions of hydrophysical inverse problems (noise source imaging, ocean acoustic tomography). 

She is a member of ASA, SEG, SGS, and Sigma Pi Sigma National Physics Honor Society. 

Rachel T. Walker received her M.S. in biology in 2001 from the University of Southern 

Mississippi where she is completing her Ph.D. in experimental psychology. She is also a visiting 
135 

faculty member of the Psychology Department at the University of Southern Mississippi. She is 

a member of several professional organizations including the American Psychological Society, 

the American Psychological Association, the Society of Marine Mammalogy and the 

Comparative Cognition Society. 

Stan Kuczaj received his B.A. in psychology in 1972 from the University of Texas at Austin and 

his a Ph.D. in child psychology in 1976 from the University of Minnesota. After serving as 

professor and chair for the Department of Psychology at Southern Methodist University, he 

joined the Department of Psychology as professor and chair at the University of Southern 

Mississippi in 1996. He currently serves as an associate editor of the British Journal of 

Developmental Psychology and First Language. He is a founding fellow of the American 

Psychological Society, a founding member of the Comparative Cognition Society and a fellow of 

the American Psychological Association. He is also a member of numerous professional 

organizations, including the Acoustical Society of America, the Animal Behavior Society, and 

the Society of Marine Mammalogy. 

Christopher D. Walker received a B.S. in physics in 2002 from the University of Southern 

Mississippi, where he is currently pursuing a graduate degree. He is also employed as a full-time 

staff research scientist. His research experience includes laser spectroscopy, signal processing, 

acoustics, modeling, simulation, and visualization. 

Grayson H. Rayborn received a B.S. in physics from the Rensselaer Polytechnic Institute and a 

Ph. D. in physics from the University of Florida. After a year on the faculty of Old Dominion 

University he joined the physics faculty of the University of Southern Mississippi where, except 

for a sabbatical year at the University of Nebraska, he remained until he retired from the faculty 

as Professor of Physics and Astronomy. He continues to pursue his research interests in signal 

processing, experimental atomic physics, and underwater acoustics as Professor Emeritus at the 

University of Southern Mississippi Signal Research Center. 

Benjamin Brack earned a B.S. in physics from USM and worked at the USM Signal Research 

Center studying seismic airgun emissions and whale vocalizations. 

Andrew J. Wright received a B.Sc. in marine biology in 1997 from the University of NewcastleUpon-Tyne and then joined a variety of research and rehabilitation programs, working with a 

range of animals from bat fish and sea turtles, to manatees and pygmy sperm whales. He 

completed a M.Sc. in 2004 in marine mammal science from the University of Wales, Bangor, 

undertaking research at the University of Southern Mississippi in Hattiesburg for his thesis on 

“The Effects of a Tropical Storm on the Use of Clicks by Sperm Whales in the Northern Gulf of 

Mexico.” Currently on a short-term contract with the Marine Mammal Commission, his research 

interests include bioacoustics and behavioral ecology. Andrew is a member of the SMM, ECS, 

ABS and SCB. 

Joal J. Newcomb received a B.S. degree in physics and mathematics from Southwestern 

Oklahoma State University, an M.S. in atomic physics from Kansas State University, and a Ph.D. 

in experimental atomic physics from Kansas State University. He is currently a research 
136 

physicist in the Acoustics, Simulations, Measurements & Tactics Branch of the Naval Research 

Laboratory at the John C. Stennis Space Center, Mississippi. Dr. Newcomb was the chief 

scientist of OUTPOST SUNRISE, a major acoustic measurement program, and has been 

principal investigator of several projects to study underwater ambient noise, broadband and 

narrowband signal propagation, and basin reverberation. Dr. Newcomb is an internationally 

recognized expert in underwater ambient noise and shipping noise. 

 

Robert A. Fisher received a B.S. degree in biology from Jacksonville University in 1974 and an 

M.S. degree in marine science from the University of South Florida in 1979. He is an 

oceanographer in the Acoustic Simulations, Measurements and Tactics Branch at the Naval 

Research Laboratory, Stennis Space Center, MS. While at NRL, he has conducted research in 

biological volume reverberation, arctic acoustics and oceanography, and shallow water 

oceanography. Volume reverberation work focused on understanding changes in swimbladder 

volumes of midwater fishes that undergo vertical migrations. Arctic studies concentrated on 

measuring and understanding environmental acoustic parameters of under-ice propagation and 

ambient noise in major arctic environments. Cooperative arctic research with the Defence 

Research Establishment Pacific, Canada, resulted in a multi-year environmental acoustic site 

selection and characterization for the Spinnaker project. He currently conducts and interprets 

oceanographic measurements made in support of acoustic studies in shallow water and is a 

member of NRL’s Scientific Dive Team. 
137 

AIR-GUN ARRAY CALIBRATION STUDIES IN THE GULF OF MEXICO 

Jack Caldwell, 

International Association of Geophysical Contractors, Houston, Texas 

The oil and gas industry in general and the seismic contractors in particular have known for 

many years what their air-gun arrays emit, in the frequency band from approximately 3 Hz to 

approximately 800 to 900 Hz. As interest in the issue of ocean noise and marine mammals has 

grown, so has the interest in finding out what the air-gun arrays emit at frequencies above 900 

Hz or so. Making quality measurements for frequencies between 1,000 Hz and 25,000 Hz and 

higher is difficult, requiring specialized recording equipment and software systems, as well as infield measurement hardware. The calibration of the in-field sensors, as well as the recording 

equipment, is a necessary step in making these quality measurements and is a step not trivially 

done. This paper presents the overall results from one of three air-gun array experiments 

conducted during the Summer of 2003 in the Gulf of Mexico (GOM) where broad-band (~ 10 

Hz–25,000 Hz) data were collected. Related papers presented in these Proceedings are those by 

Newcomb et al., Tolstoy and Diebold, and Madsen. 

Questions about air-gun array outputs fundamentally involve 1) the received pressure levels, and 

2) the received energy levels, at different distances from the array, at different emission angles 

(angles measured from the vertical), and for different azimuths (different map directions from the 

source), for different frequency bands. To answer these questions, two experiments were 

conducted using an air-gun array representative of those routinely used by the oil and gas 

industry, the M/V Kondor 31-gun, 3,590-cubic-inch array. One experiment used the SPAR buoy 

from Lamont-Doherty Earth Observatory as the in-water recording hardware, and the 

measurements were made in the Mississippi Canyon area along the continental slope where 

water depths ranged from about 1,000 meters to around 820 meters. The SPAR buoy was free to 

move with the currents and did. Some results from this experiment are presented in the paper by 

Tolstoy and Diebold. A D-tag (see Madsen) was also attached to the SPAR buoy, the intent 

being to compare the output of the SPAR buoy system to the D-tag system. The second 

experiment was conducted in the Green Canyon area, using an Environmental Acoustic 

Recording System (EARS) buoy deployed by the Littoral Acoustic Demonstration Center 

(LADC). (See Newcomb et al. for details not presented in this paper.) 

It was hoped, when the SPAR buoy and the EARS buoy experiments were designed and carried 

out, that the following questions would be answered: 

 1. What pressure levels, and energy levels, are generated in different frequency bands 

between 10 Hz and 25 kHz? 

 2. What frequencies are dominant in the waves emitted at different angles from the vertical 

up to the horizontal, and in particular, those waves traveling mostly vertically versus 

those traveling mostly horizontally, and what are the pressure levels and energy levels in 

those frequency bands? 
138 

 3. In conjunction with (2), how do the pressure and energy levels vary with azimuth from 

the array? 

 4. Given that there are non-uniform velocity structures in the water column, and in the 

sediments beneath the seafloor, at what offset does the refracted wave come in earlier 

than the direct water-borne wave? 

 5. How do the responses of the three different systems (the SPAR buoy, the D-tag, and the 

EARS buoy) compare to each other? 

Environmental conditions put limits on the usefulness of the SPAR buoy and D-tag data, so 

quantitative information about the horizontally traveling waves was not obtained during these 

experiments. The EARS buoy data did provide, however, quantitative information about the 

waves traveling vertically (0o) to those waves traveling at emission angles up to about 20o below 

horizontal (an emission angle of 70o - emission angles [Θ] are measured with respect to vertical, 

as indicated in Figure 2A.44a). That information is summarized here, but further analysis is 

needed to provide more in-depth information about those waves. 

For the EARS buoy experiment, the anchored hydrophone was located in 990 meters of water 

and positioned 251 meters above the seafloor. Figure 2A.42 indicates the geometry of the five 

source lines with respect to the location of the EARS buoy. Figure 2A.43 shows the geometry of 

the hydrophone with respect to a source passing directly overhead. In actuality, the source line 

passing closest to the hydrophone was offset 200 meters (see Newcomb et al. for more details). 

Figure 2A.42. EARS Buoy shot line geometry. 
139 

Figure 2A.43. Hydrophone geometry. 

Figure 2A.46 illustrates a typical record of an air-gun pulse that was recorded nearly vertically 

736 meters above the EARS-buoy hydrophone. Air-gun arrays are constructed so that the output 

is focused downward, and consequently, upward, as well. This leads to a strong peak, followed 

immediately by a very similar-looking trough that is the reflection of the peak from the air-water 

interface (Figure 2A.44b shows a cartoon of a ray diagram where the white ray creates the strong 

peak, and the two red rays create the trough). That is labeled the “first break” in Figure 2A.46. 

The second major event is the “seafloor reflection.” The cartoon of Figure 2A.45 shows how it 

occurs: the white ray represents the first break arrival, and the red rays represent the pulse from 

the air-gun array traversing the water column, reflecting off the seafloor, and being received at 

the hydrophone (for simplicity, the detail of the first break division into the rays contributing to 

the peak and trough are omitted, so only a single white ray indicating the first break arrival is 

shown). The last identified event on the record in Figure 2A.46 is the energy from the 18 kHz 

echosounder. This record is known as a “time domain” record since it depicts the amplitude of 

pressure along the vertical axis versus time along the horizontal axis (although in this display, 

only the relative amplitude is shown, rather than the absolute amplitude). 

The same record can be viewed in the “frequency domain,” where amplitude per Hertz is shown 

along the vertical axis, and frequency is displayed along the horizontal axis (Figure 2A.47). In 

this figure, absolute amplitude per Hertz is displayed on the vertical axis, and the duration of the 

signal that is used in the analysis is 100 milliseconds beginning just before the arrival of the first 

break energy. Reference to Figure 2A.46 will demonstrate that 100 milliseconds will include all 

of the high amplitudes associated with the first break energy. Figure 2A.47 shows that the 

maximum amplitude of approximately 158 dB/Hz re 1 μPa occurs very close to 62 Hz, and that 

an amplitude of about 107 dB/Hz re 1 μPa occurs close to 1,000 Hz. The salient point here is that 

the high pressures in an air-gun pulse occur in the 10-100 Hz frequency band, and the pressure 

levels drop quite rapidly with increasing frequencies. Generally, a 30 to 50 dB drop in amplitude 

is observed between 100 Hz and 1,000 Hz for the shot records acquired in the EARS buoy 

experiment. The amplitudes continue to drop between 1,000 Hz out to around 8,000 Hz or so 

where the noise floor of the recording system is reached. 
140 

Figure 2A.44. An emission angle of 70o is shown in Figure 2A.44a. Figure 2A.44b represents a ray diagram 

where the white ray creates the strong peak, and the two red rays create the trough 

Figure 2A.45. The white ray represents the first break arrival, and the red rays represent the pulse from the 

air-gun array traversing the water column, reflecting off the seafloor, and being received at the 

hydrophone 

Figure 2A.48 shows sound pressure density (sound pressure squared per Hertz) versus frequency 

and makes it clearer that there is no energy at levels higher than 80 dB re 1 μPa from the air-gun 

array in the vertical lobe of the radiation pattern at frequencies higher than 4,000 Hz at a distance 

of 736 meters from the hydrophone. Figure 2A.48 is an analysis from a single shot record. 
141 

Figure 2A.46. Time domain shot record 736 meters away (mostly above) from hydrophone. 

Figure 2A.47. Sound pressure/Hz versus frequency. Note rapid drop-off above 100 Hz. 
142 

Figure 2A.48. Sound pressure density spectrum. 

Figure 2A.49 is a more inclusive look at the EARS buoy data because it includes all of the shot 

records that were recorded in the EARS buoy project. This figure is a spectrogram: frequency is 

plotted on the vertical axis, shot record is implied along the horizontal axis, and color indicates 

sound pressure density (pressure squared per Hertz), an entity related to amplitude, and the color 

scale is indicated on the right side of the plot. There are about 100 shot records associated with 

each of the five source lines acquired in the EARS buoy project, and the records associated with 

each line are indicated along the horizontal axis. A window of 1.28 seconds was taken for each 

shot record, and the window began about 50 milliseconds before the first break. 

Figure 2A.49 shows how the pressure levels increase as the source moves first towards the 

hydrophone for each line, and then away from the hydrophone, so you get a mound-like 

appearance along the horizontal axis: Line 1 is the left-most group of traces on the plot, and the 

left-most trace will be the farthest trace to the southwest of the hydrophone, and then each 

subsequent trace to the right will be closer and closer to the hydrophone until the source is 

essentially directly over the phone, and then the source begins to move away from the phone to 

the northeast, until the end of Line 1 is reached. Then the traces of Line 2 begin, etc. 

All of the reds and yellows in Figure 2A.49 occur at less than 1/10 of the way up to 5,000 Hz, so 

below 500 Hz. The pale greens are gone by about 1/5 of the way to 5,000 Hz, which is 50 dB 

down at 1,000 Hz (dark red is 160 dB, pale green is 110 dB). The pale blue (60 to 70 dB below 
143 

the levels at the peak frequencies) in Figure 2A.49 is broadly distributed across all five lines for 

frequencies below 4,500 Hz. The pale blue occurs for narrowing groups of shots up to around 

23,000 Hz for Lines 1 and 2, the two lines that go almost directly over the hydrophone. The pale 

blue is also visible in regular tick marks parading across the plot at around 18,000 Hz: this is the 

signal from the echosounder and is not present in the analysis window on all of the shot records. 

Figure 2A.49. Sound pressure density spectrogram. See text for description. 

The calibration studies done using the M/V Kondor in the GOM taught us a number of lessons. 

 1. Efforts to measure sound from acoustic sources should be careful to address the 

following areas to ensure the quality of the recorded measurements: 

 a) Recording system characteristics, such as dynamic range and frequency response 

 b) Uncertainties associated with the position of receivers relative to the source 

 c) Physical properties of the environment where the data are acquired. 

 2. The amplitude spectrum of the M/V Kondor air-gun array, while relatively flat between 

10 and 100 Hz, has a peak at around 62 Hz, and the output levels are 30 to 50 dB lower at 

1,000 Hz than the levels at 100 Hz, for distances 736 meters and greater to the receiver, 

and for emission angles between 0o and ~70o. 
144 

 3. The output levels continue to decline from 1,000 Hz to 5,000 Hz, where the levels are 60 

to 70 dB lower than the levels at 100 Hz, for distances 736 meters and greater to the 

receiver, and for emission angles between 0o and ~70o. 

 4. The EARS buoy dataset provides detailed information on the output that a standard 

industry air-gun array emits at vertical and sub-vertical emission angles. 

 5. Results show that, for odontocetes, current mitigation exclusion zones are conservative 

with respect to potential for physical impacts from high frequency emissions from 

industry seismic surveys 

A well-documented, broad-band (10 Hz to 25,000 Hz), and precisely acquired data set with 

horizontally propagating waves is still needed by the oil and gas industry. Additionally, the 

vertical and sub-vertical output of an industry array, over the same broad bandwidth, needs to be 

measured at a distance of around 200 meters. Collaborative efforts will continue with other 

research groups to make optimum use of existing data and limited resources. 

I would like to acknowledge the support of several groups and individuals who made this project 

and its results possible: the Industry Research Funders Coalition, Littoral Acoustic 

Demonstration Center (LADC), International Association of Geophysical Contractors (IAGC), 

SWSS, Lamont-Doherty Earth Observatory (L-DEO), and Woods Hole Oceanographic 

Institution (WHOI); Joal Newcomb, George & Juliette Ioup, Jim Stephens, Greyson Rayborn, 

and Natalia Sidorovskaia (all from LADC), Mike Jenkerson, Rodger Melton, and Andy Wigton 

(all from ExxonMobil), Phil Fontana (Veritas DGC), Chip Gill (IAGC), Bill Lang (MMS), John 

Diebold and Maya Tolstoy (both from L-DEO), and Mark Johnson (WHOI). 

Jack Caldwell, a geophysical consultant, has been in the oil and gas industry as a technicallyoriented geoscientist for 27 years. He received a B.S. in mathematics from Davidson College and 

a Ph.D. in geophysics from Cornell University. He worked two and a half years in research for 

Texaco, almost seven years in various positions for Marathon Oil, and 15 years in numerous 

technical and managerial positions for Schlumberger. Since 1996, he has spent extracurricular 

time involved with the issue of sound in the ocean and its effect on marine mammals. He has 

organized several industry workshops on this issue, and has written several articles to help the oil 

and gas industry better understand this issue’s different aspects. He served on the U.S. National 

Research Council of the National Academy of Sciences Committee on Potential Impacts of 

Ambient Noise in the Oceans on Marine Mammals that published its report entitled Ocean Noise 

and Marine Mammals in 2003. He was awarded the U.S. Minerals Management Service 

Corporate Leadership award in 2000 for his work on this issue, and in 2002 was awarded 

lifetime membership in the Society of Exploration Geophysicists largely as a result of his efforts 

to get the oil and gas industry more involved in addressing this issue. 
145 

MANTA: THE MARINE ANIMAL TRACKING APPARATUS 

Thomas F. Norris, Marine & Environmental Sciences Division, 

Science Applications International Corp. 

ABSTRACT 

MANTA is a marine animal tracking and data-telemetry system which integrates acoustic 

transponder, underwater modem, data-logging, GPS, and VHF telemetry technologies. This 

system differs from existing tag-based, marine animal tracking technologies in that it 

incorporates several complementary technologies allowing tagged marine animals to be tracked 

underwater in real-time, three-dimensionally and at very high spatial resolution (i.e. +/- a few 

meters). The primary application of MANTA is detailed real-time monitoring and data-collection 

of animal movements, behaviors (including vocalizations), and physiology, as well as for 

collection of oceanographic data directly from tagged marine vertebrates (e.g. whales, pinnipeds, 

elasmobranchs, sea turtles etc.). Location information is processed in real-time on a “surface 

station” located onboard a tracking vessel. Location data includes the animal’s latitude, 

longitude, and depth (+/- 1m) and can be updated every few seconds. Standard VHF telemetry 

allows animals to be tracked while at the surface and when they are beyond the tracking range of 

the acoustic system. In addition, data can be collected from up to six sensors (e.g. accelerometer, 

thermistor, etc.) that can be integrated on the tag. Furthermore, data from the MANTA tag can be 

acoustically telemetered (at limited bit-rates) to the surface via an underwater modem and/or 

logged internally on FLASH memory modules. The current version of the tag has an integrated 

accelerometer (to derive pitch & roll). A prototype acoustic “event detector” also has been 

developed, and improvements to processing and data-storage capabilities are planned. Examples 

are provided of data collected from test deployments on blue whales in Monterey Bay, California 

(work funded by ONR). 
147 

SESSION 2B 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT AND 

BENTHIC ECOLOGY STUDY RESULTS, PART II 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

DGoMB MEIOFAUNA STUDIES Jeff Baguley, Paul Montagna, and Wonchoel Lee .......... 149 

DGoMB MACROFAUNA G. Fain Hubbard and Gilbert T. Rowe .......................................... 151 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT AND 

BENTHIC ECOLOGY STUDY RESULTS: MEGAFAUNA Mary K. Wicksten ................... 154 

MACROBENTHIC COMMUNITY STRUCTURE AND TOTAL SEDIMENT 

RESPIRATION AT COLD SEEPS IN THE NORTHERN GULF OF MEXICO 

Clifton C. Nunnally..................................................................................................................... 155 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT AND 

BENTHIC ECOLOGY STUDY RESULTS PART II: MEXICAN COMPONENT 

Elva Escobar-Briones.................................................................................................................. 158 

DEEP GULF OF MEXICO BENTHOS: SUMMARY AND SYNTHESIS 

Gilbert T. Rowe .......................................................................................................................... 169 
149 

DGoMB MEIOFAUNA STUDIES 

Jeff Baguley and Paul Montagna, Texas A&M University 

Wonchoel Lee, Hanyang University, Seoul, Korea 

Meiofauna are ubiquitous in deep-sea soft sediments and exhibit high abundance compared to 

larger-sized invertebrates (e.g., macrofauna). The northern Gulf of Mexico (NGOM) deep sea is 

characterized by topographical contrasts, with the flat topography of the Florida slope followed 

by the precipitous depth increase of the Florida escarpment; the complex Texas/Louisiana slope 

with numerous basins and knolls; and numerous canyon features such as the Mississippi Trough 

and DeSoto Canyon. To better understand the distribution of meiofauna and how they respond to 

topographic, geochemical and physical forcing in the NGOM, meiofauna abundance and 

environmental variables were analyzed in a hypothesis-based univariate and multivariate design. 

Meiofauna abundance is significantly related to water depth but also exhibits significant 

longitudinal differences resulting from proximity to Mississippi River outflow. Canyon features 

in proximity of Mississippi River outflow were found to greatly enhance meiofauna abundance. 

The Florida Escarpment interacts with Mississippi River inflow and the Loop Current to enhance 

meiofauna abundance at stations lying directly above and below the escarpment. Multivariate 

comparisons of meiofauna abundance with environmental variables reveal a strong Mississippi 

River influence. River outflow alters local sediment characteristics and interacts with loop 

current eddies and dynamic slope topography to increase POM flux in the northeastern region, 

thus creating areas of higher than normal meiofauna abundance. 

Harpacticoida (Copepoda) are the second most abundant taxon within the meiofauna and an 

important component of deep-sea meiofaunal communities. However, regional species pools, 

processes structuring communities on various scales, and distributions of organisms in response 

to topographic, geochemical, and physical oceanographic forcing is largely unknown for deepsea environments. The NGOM is a dynamic environment with complex continental shelf 

topography and longitudinal gradients of water column primary production due to Mississippi 

River outflow. Harpacticoid copepod community structure was analyzed at 43 stations in the 

NGOM deep sea to test regional and bathymetric patters of diversity. Harpacticoid copepod 

diversity is significantly related to depth and longitude. Most stations have unique species 

compositions, suggesting high regional (2,700 species) and global (105

 - 106 species) diversity by 

extrapolation. Although highest diversity, in terms of expected number of species (rarefraction), 

is found at approximately 1,200 meters, average taxonomic and average phylogenetic diversity 

continue to increase with depth, indicating greater morphological or functional diversity. 

Multivariate analysis reveals significant inverse relationships between diversity and POM flux, 

which are confirmed by a significant region-scale depth and longitude differences. However, 

within- versus between-station variability suggests an interaction between small and region-scale 

processes maintaining high diversity. 
150 

Meiofauna exhibit high biomass in deep-sea soft sediments, compared to larger invertebrates 

(e.g. macro- and megafauna), and play an important role in the global carbon cycle. However, 

deep-sea meiofauna community function (grazing, respiration, etc.) has only been sparsely 

investigated. In the present study, meiofauna biomass was calculated at 51 stations using a newly 

developed, semi-automated, digital microphotographic method, and meiofauna mass-dependent 

respiration was estimated at 51 stations using an allometric power law. Strong relationships exist 

between biomass and meiofauna community respiration with depth. Highest biomass and 

respiration occurred in the proximity of high particulate organic matter flux where surface 

currents interact with Mississippi River inflow complex slope topography. Allometric estimates 

indicate that meiofauna require 7% of their biomass per day to meet their metabolic energy 

budget and are therefore not food limited with respect to sediment bacterial biomass. Meiofauna 

account for 10-25% of whole sediment community respiration indicating their importance in 

global biogeochemical cycles. 

Jeffrey Baguley received his Ph.D. in December 2004 from the University of Texas at Austin. He 

is now a research assistant professor in the Baruch Institute for Marine and Coastal Sciences at 

the University of South Carolina, Columbia campus. Dr. Baguley’s main research interests are in 

the field of meiofauna ecology, but more specifically, harpacticoid copepod ecology, deep-sea 

diversity, meiofauna community energetics, and harpacticoid molecular population structure. 

Paul Montagna, Ph.D., is a Research Professor at the University of Texas at Austin, Marine 

Science Institute and Project Coordinator for the proposed Texas National Estuarine Research 

Reserve. He has more than 30 years’ experience as a benthic ecologist. 

Wonchoel Lee, Ph.D., is an associate professor in the Department of Life Sciences, Hanyang 

University, Seoul, Korea. He is a professional taxonomist specializing in the order of the 

Harpacticoida (Copepoda) and has published descriptions of several new species and genera. 
151 

DGoMB MACROFAUNA 

G. Fain Hubbard and Gilbert T. Rowe, Texas A&M University 

Nearly 175,000 macrofauna specimens were found, predominantly composed of polychaetes 

(64,627; 37.3%). Extraordinary numbers of amphipods occurring at MT1, MT2, and MT3 

skewed their relative abundance (34,385; 19.8%). Harpacticoids, tanaidaceans, bivalves, 

ostracods, aplacophoran mollusks, and cumaceans followed in that order. 

The faunal groups that were further identified as close to species level as possible were the 

polychaeta, amphipoda, tanaidacea, bivalvia, isopoda, aplacophora, and cumacea. These 

accounted for 126,505 specimens representing 504 genera and 968 species. 

Macrofaunal density by transect and depth are shown for the combined cruises. Density 

decreases with depth with infrequent inconsistencies, e.g., NB4, 5 < B1; GKF < WC12. 

Macrofaunal Shannon-Wiener Diversity (log2) was quite uniform throughout both transect and 

depth, with appreciable reduction only on the abyssal plain. 

Expected number of species for a macrofauna population of 180 individuals [E(S180)] was also 

remarkably uniform with certain notable exceptions: Mississippi Trough stations MT1 and MT2, 

the High Productivity (HP) station, Green Knoll Furrows (GKF), and Sigsbee Abyssal Plain 

stations S1, S2, and S3 were all quite low. The graph of expected number of species (N=180) 

plotted versus depth yielded a hyperbolic curve with an apex occurring around 1,500 m. 

Macrofaunal similarity was demonstrated on a map with different colored circles on a 

dendrogram with the same similarity zones denoted by the same colors and by transect versus 

depth with “fence” diagrams, all illustrating the shifting of grouping by depth as well as some 

east-west component. 

Polychaete densities were shown by transect and depth and illustrate the same general decrease 

with depth pattern as the macrofauna as a whole. Polychaete Shannon-Wiener diversity showed a 

somewhat more evident decrease with depth than did the macrofauna as a whole. The expected 

number of species (N=100) appeared to decrease steadily with depth, with any maximum 

occurring above the depth of the samples. Similarity was again illustrated by map and by 

transect/depth “fence” diagram, again demonstrating grouping by depth with some east-west 

influence. 

Amphipod densities were uniformly low at all stations except MT1 and MT2 and slightly at C7. 

The photograph of the sea floor near MT1 shows a shag carpet appearance due to the presence of 

thousands of amphipod tubes on and in the surface. Station bathymetry shows the vicinity of the 

core samples and the photography and the apparent homogeneity of the area. Amphipod 

expected number of species (N=5) for the 49 stations at which amphipods were found show a 
152 

slight apex about 800 m. Amphipod similarity map and transect/depth “fence” diagram show 

grouping by depth with slightly more erratic east-west confusion. Individual stations not 

grouping with any others were MT1, S39, and S3. 

Bivalve densities, while rather low at most stations, showed remarkable abundances at stations 

MT1, MT2, HP, GKF, and S5. Expected numbers of species (N=50) showed an apparent peak at 

about 1,500 m. Bivalve similarity by map and transect/depth “fence” diagram show a grouping 

trend with depth with some east-west influence. 

Isopod densities follow the trend of the macrofauna in general with exceptionally high values at 

stations BH, S35, S36, S3, and S5. Expected numbers of species (N=20) showed an apparent 

peak at about 1,750 m. Isopod similarity by map and transect/depth “fence” diagram show a 

grouping trend with depth with little east-west influence. 

Bottom photography of stations S2, with the lowest macrofaunal populations on the abyssal 

plain, and S5, with the highest, shows the great similarity in the overt appearance of the two. 

Aplacophoran mollusk densities followed the trend of the macrofauna in general with 

exceptionally high values at stations MT2, MT3, and S35. Expected numbers of species (N=5) 

showed a slight peak at about 1,100 m. Aplacophoran similarity by map and transect/depth 

“fence” diagram show a grouping primarily by depth with some clutter caused by the relatively 

small number of organisms overall and independent stations at S41 and S43. 

Cumacean densities followed the macrofauna in general with exceptionally high values at 

stations MT2, MT3, and S35. Expected numbers of species (N=5) showed no peak low R2

 of 

0.34. Cumacean similarity by map and transect/depth “fence” diagram showed grouping by 

depth, erratic influence by the relatively small number of organisms overall, and independent 

stations at RW4, RW5, S1, GKF, C14 and MT6. 

Harpacticoid densities exhibited exceptionally high values at C12, S5, MT3, S35, S36, S37, and 

perhaps S38. Expected numbers of species (N=185) showed no obvious peak below the shelf. 

The Harpacticoid similarity map showed a grouping trend with depth with little east-west 

influence. 

Expected number of species diagrams (N=5) for amphipoda, aplacophora, isopoda, and cumacea 

illustrate that the greater the number of stations (49 or 51 rather than 29 or 22) the greater 

reliability of the R2

 values for the graph curves (0.66 or 0.72 rather than 0.32 or 0.34, 

respectively). Expected number of species values for bivalvia, (E(S50) with N=48 and R2

=0.68 

and harpacticoidea, E(S180) with N=43 and R2

-0.22, seem to indicate that neither the number of 

stations represented nor the population maximum of the estimate may have that much effect. 

Expected number of species for polychaeta at E(S50) with N=50 and R2

=0.61 and E(S100) with 

N=50 and R2

=0.71 seem to indicate that given the same number of stations, estimations based on 

higher population sizes are more reliable. This may also show that comparing between 
153 

populations of different taxa and between different population sizes of the same taxa may be like 

comparing oranges and bananas. 

Conclusions derived from this study: 

 1. Density, diversity, and numbers of species decrease and species change with depth; 

 2. Faunal composition differs east and west of DeSoto Canyon; 

 3. Upper Mississippi Trough fauna are unique in species and density; 

 4. Western fauna are similar to basin/non-basin as well as to central fauna; and 

 5. Basin and non-basin stations differ only by depth. 

Dr. G. Fain Hubbard obtained his Ph.D. from Texas A&M University, College Station. He is 

now a Faculty Lecturer at Texas A&M University, Galveston. 

Dr. Gilbert T. Rowe completed his B.S. in zoology and M.S. in oceanography at Texas A&M 

before going to Duke for a Ph.D. in zoology. That was followed by 11 years as a research 

scientist at WHOI and eight years as a research scientist at the Brookhaven National Lab on 

Long Island. In 1987 he returned to Texas A&M to become Head of the Oceanography 

Department. He transferred to the Galveston campus in 2002 as Head of Marine Biology. Since 

1999 he has been the Program Manager of the MMS Deep Gulf of Mexico Benthos project 

(DGoMB), now nearing completion. 
154 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT AND 

BENTHIC ECOLOGY STUDY RESULTS: MEGAFAUNA 

Mary K. Wicksten, Department of Biology, Texas A&M University 

Megafaunal invertebrates, with a size greater than 10 mm, include sponges (phylum Porifera), 

sea anemones and their relatives (Cnidaria), various larger worms, mollusks, crustaceans and 

echinoderms. Feeding modes range from passive filtration to active predation; metabolic levels 

range from sluggish to rapid. Species may be solitary or colonial. 

During the DGoMB study, megafaunal invertebrates were taken by trawl and weighed and sorted 

on ship. Final identification was made in the laboratory. At least 185 species were taken. Species 

richness was greatest at site S35 (De Soto Canyon). Other species-rich sites were C4, MT5, S38 

and S41. Species diversity was highest at Site MT6 (Mississippi Trough) followed by site MT5. 

Lowest species diversity was at sites on the upper slope (MT1, S42, S43 and S44), basins (B1, 

B2 and B3) and sites dominated by small sponges (NB4 and S37). 

Biomass was highest at sites in the De Soto Canyon (S35, S37, S38 and S41) and also MT3. 

Much of the biomass was due to wet weight of holothuroids. Single heavy animals, such as large 

squid or crabs, were not included in the biomass per site. The greatest number of individuals was 

at S37 (1,612 individuals, mostly small sponges). Other sites with more than 300 individuals 

were MT1, MT5, MT6, NB5 and S38. The mussel Amygdalum politum was more abundant in 

canyon sites than elsewhere, but other records suggest that the mussel is not confined to canyons. 

Crustaceans were more diverse and abundant in the De Soto Canyon than in the Mississippi 

Trough. A more detailed study of zoogeography of decapods in the Gulf of Mexico suggests that 

the De Soto Canyon has the most diverse decapod fauna (63 species out of 129 total species). 

The northeastern and eastern Gulf of Mexico has a more diverse decapod fauna, including the 

golden crab Chaceon fenneri, than other parts of the Gulf. Ten species, supposedly endemic to 

the Gulf, are rare and may have been overlooked elsewhere. The Gulf is particularly rich in 

craylets, Munidopsis spp, with 25 species. The fauna of the Straits of Florida is distinct and 

should not be considered to be part of that of the Gulf. Most of the megafauna ranges from the 

Gulf of Mexico into the Caribbean and western Atlantic. 

Mary Wicksten received her B.A. in Biology from Humboldt State College, California in 1970 

and her M.A. in 1972. She received her Ph.D. from the University of Southern California in 1977 

and spent three years of further study there before coming to Texas A&M University in 1980. 

She is a professor in the Department of Biology. An active diver and field biologist, she has 

participated in numerous research cruises in the Gulf of Mexico and eastern Pacific. She is a 

specialist on decapod crustaceans, having published over 100 papers in refereed journals and 

having described 34 new species. 
155 

MACROBENTHIC COMMUNITY STRUCTURE AND TOTAL SEDIMENT 

RESPIRATION AT COLD SEEPS IN THE NORTHERN GULF OF MEXICO 

Clifton C. Nunnally, Texas A&M University, Galveston 

Cold seeps in the Gulf of Mexico (GOM) have been intensely studied since they were first 

described by Paull et al. (1984) and Kennicutt et al. (1985), but little of the ecology has focused 

on associated sediment infauna. Structural and functional characteristics of benthic macrofaunal 

communities were studied to gain a better understanding of the broader influence of cold seeps in 

the northern Gulf of Mexico (NGOM). Density of macrofauna at seeps does not decrease with 

depth and proves to be greater than at most any other site surveyed. Diversity has shown to 

increase with water depth in the benthos (Hessler and Sanders 1967; Sanders 1968). Two seeps, 

Garden Banks 425 (GB 425) and Green Canyon 234 (GC 234) exhibit decreased diversity when 

compared to sites within a similar depth range. Sediment community oxygen consumption, 

determined using in situ benthic flux chambers, exhibited much higher rates of SCOC than from 

the continental shelf and slope away from seeps, suggesting a supplemented supply of carbon to 

the benthos. 

H07: Proximity to organic input causes bioenhancement. 

Stations: Bush Hill 

Cold seeps in the GOM provide an additional source of carbon to benthic fauna communities that 

are typified by high biomass and low diversity (Brooks et al. 1987, Agard et al. 1993). The larger 

megafauna that inhabit cold hydrocarbon seeps (tube worms, clams and mussels) utilize 

endosymbiotic bacteria to mediate methane and petroleum (Aharon 2000, Brooks 1987, Sassen 

et al. 1993). This symbiotic relationship thus only occurs near seeping fluids and limits the 

spatial extent of the vent community (Aharon 2000, Hecker 1985). Bioenhancement is not 

limited to the megafauna and bacteria; benthic infauna were also affected by the additional food 

found at cold seeps. 

Sediment cores taken from GOM cold seeps were higher in abundance of macrofauna and 

exhibited lower diversity (Nunnally 2003). The mean abundance of macrofauna found at the cold 

seeps, Garden Banks 425 and Green Canyon 234, was 28,774 individuals per square meter 

(N/m2

). The mean abundance of DGoMB sites within similar depth ranges (200–1,000 meters) 

was significantly less at 8,883 individuals per square meter. The diversity of taxonomic groups at 

these seeps was also lower than similar DGoMB stations, a mean of ten groups at seeps 

compared to 21 groups. The mean Shannon-Weiner index of diversity (H’) for cold seeps was 

1.355 and 1.790 for DGoMB stations, a significant difference. The only community attribute 

measured in which cold seeps and DGoMB stations did not differ significantly was Eveness, 

where cold seeps had a value of 0.635 and DGoMB stations has a value of 0.584. 
156 

The Bush Hill station was added during the field program to specifically test the hypothesis of 

organic input by cold seeps. It is located two kilometers from a large cold seep known as Bush 

Hill. The macrofauna community at the Bush Hill station showed no differences from the other 

sites tested. Bush Hill had mean values of 4,006 N/m2

, 19 taxa groups, an H’ of 1.8880 and an 

Evenness of 0.6379. These values of macrofauna community structure did not vary significantly 

from the other DGoMB stations studied. The low abundance and high diversity of taxonomic 

groups indicated that at two kilometers distance from an active seep, the benthos shows no 

recognizable bioenhancement within the macrofauna. 

Enhancement of the benthos by cold hydrocarbon seeps in the GOM appears to be a localized on 

the scale of five meters or less from the seepage a fluids. Cold seeps do concentrate a 

significantly large biomass reservoir in the midst of a low biomass habitat. Diversity at such seep 

sites is diminished due to the competition for resources. This competition for an excess of food 

in a food-limited environment assures that little of the labile carbon ever leaves the vicinity of a 

cold seep. 

Descriptive statistics are shown in Table 2B.1. 

Table 2B.1. Mean values of macrofauna abundance, taxa groups, H’ (Shannon-Weiner), and evenness for 

DGoMB study stations (non-seep) and SETTI stations (seep). 

 TYPE Mean Std. Deviation N 

Taxa Groups non-seep 21 4.2 92 

seep 10 0.5 4 

Abundance (N/m2) non-seep 8883 5616 92 

seep 28774 9738 4 

H’ non-seep 1.80 .3054 92 

seep 1.35 .0354 4 

Eveness non-seep .584 .0936 92 

seep .635 .0071 4 

References 

Agard, J., J. Gobin, and R. Warwick. 1993. Analysis of marine macrobenthic community 

structure in relation to pollution, natural oil seepage and seasonal disturbance in a tropical 

environment (Trinidad, West Indies). Marine Ecology Progress Series 92:233–243. 

Aharon, P. 2000. Microbial processes and products fueled by hydrocarbons in submarine seeps. 

In: Riding, R. and S. Awaramik, eds. Microbial Sediments. Berlin: Springer –Verlag. Pp. 

270-281. 
157 

Brooks, J., M. Kennicutt, C. Fisher, S. Macko, K. Cole, J. Childress, R. Bidigare, and R. Vetter. 

1987. Deep-sea hydrocarbon seep communities: Evidence for energy and nutritional 

carbon sources. Science 238:1138–1142. 

Hecker, B. 1985. Fauna from a cold sulfur-seep in the Gulf of Mexico: Comparison with 

hydrothermal vent communities and evolutionary implications. Biological Society of 

Washington 6:465–473. 

Hessler, R. and H. Sanders. 1967. Faunal diversity in the deep-sea. Deep-Sea Research 14:65–

78. 

Kennicutt II, M.C., J. Brooks, R. Bidigare, R. Fay, T. Wade, and T. McDonald. 1985. Vent-type 

taxa in a hydrocarbon seep region on the Louisiana slope. Nature 317:351–352. 

Nunnally, C. 2003. Macrobenthic community structure and total sediment respiration at cold 

hydrocarbon seeps in the northwestern Gulf of Mexico. M.S. Thesis, Dept. of 

Oceanography, Texas A&M University. 44 pp. 

Paull, C., B. Hecker, R. Commeau, R. Freeman-Lynde, C. Neumann, W. Corso, S. Golubic, J. 

Hook, E. Sikes, and J. Curray. 1984. Biological communities at the Florida Escarpment 

resemble hydrothermal vent type taxa. Science 226:965–967. 

Sanders, H. 1968. Marine benthic diversity: A comparative study. The American Naturalist 102: 

243–282. 

Sassen, R., H. Roberts, P. Aharon, J. Larkin, E. Chin, and R. Carney. 1993. Chemosynthetic 

bacterial mats at cold hydrocarbon seeps, Gulf of Mexico continental slope. Organic 

Geochemistry 20:77–89. 

Clifton C. Nunnally is a Graduate Teaching Assistant at Texas A&M University at Galveston 

and is currently pursuing a Ph.D. in biological oceanography. He obtained his B.S. in biology 

from Abilene Christian University in 1998 and M.S. in oceanography from Texas A&M 

University in 2003. His thesis title was “Macrobenthic Community Structure and Total Sediment 

Respiration at Cold Hydrocarbon Seeps in the Northern Gulf of Mexico.” 
158 

NORTHERN GULF OF MEXICO CONTINENTAL SLOPE HABITAT AND BENTHIC 

ECOLOGY STUDY RESULTS PART II: MEXICAN COMPONENT 

Elva Escobar-Briones, 

Universidad Nacional Autónoma de México, 

Instituto de Ciencias del Mar y Limnología 

Introduction 

The tropical oceanic environments have been recognized as geographic locations that have low 

primary productivity, have reduced phytoplankton biomass characterized by small sizes and 

display a low seasonality that leads to efficient energy transfer in the water column and hence a 

low export of biogenic carbon to the abyssal plain benthic communities. The expected 

distribution pattern of the abundance and biomass should display low variability at the large 

scale and a large variability at the local scale. The ability to recognize the factors that act as the 

main promoters of change in the natural environment can help to establish the baseline levels and 

distinguish man induced changes on the seafloor from those naturally occurring. It can help as 

well to understand how both interact and can magnify and act over the biological communities. 

The present study has as main objective to describe the density, biomass, and taxonomic richness 

patterns that characterize the benthic communities in the Gulf of Mexico exemplified by the 

studies carried out by UNAM in the abyssal southwestern Gulf of Mexico. The results from the 

study of specimens collected in the scavenger traps, of the assemblage composition of 

megafaunal, macrofaunal and meiofaunal components, and the composition and characterization 

of POC in the offshore habitats are addressed in this document. 

Results from Scavenger Traps 

Abundance and Growth 

A total of 128 specimens of the amphipod Eurythenes gryllus (Crustacea: Amphipoda: 

Lyssianassidae) were collected at six sampling sites in the abyssal plain of the central Gulf of 

Mexico, 26 in June of 1997; 60 in June and 47 in August of 2002. The total length and the 

biomass in E. gryllus in the Gulf of Mexico was W = 0.0232L2.87. The elemental composition of 

the amphipod’s muscle tissue varied from 40.7 to 47.1% C and 11.9 to 15.5% N. The C/N ratio 

ranged from 3.02 to 3.47. Potential diet sources included carcasses and plant debris. The 

elemental composition in these materials ranged between 41.31 and 49.83%C and 12.97 to 

17.21%N and 41.81 to 67.25%C and 1.25 to 2.58%N. The conceptual model proposed includes 

three boxes, a detritus/carcass box, the scavenger standing stock and the biomass of potential 

predators on the amphipods. Arrows arrive to the detritus/carcass box from the water column and 

connect with the scavenger standing stock box, the arrow that pulses the carcass availability will 

be interlinked with the water column productivity and pelagic food web length displayed in a 

separate water column section. The potential diet arrives from the pelagic system as recorded by 

their isotopic signature that ranges between δ13C –24-64 to 21.98 o/oo. The C sources that 

contribute to the scavenger diet are a mixture of exported demersal carcasses and autochtonous 

materials in the sediment. These results suggest that the geographical variability of the 
159 

abundance in the scavenger amphipods is a response to food availability and that the growth 

patterns and population structure are similar to those of other abyssal scavenger populations. 

Mitochondrial 16S rRNA Sequences 

The molecular characterization of the amphipods considered specimens of three locations on the 

abyssal plain of the Gulf of Mexico and tested isolation from the Atlantic populations in the Gulf 

of Mexico. The sequences determined of the mitochondrial 16S rRNA gene showed small 

differences when compared with the corresponding sequences from other Eurythenes amphipods 

of the Atlantic Ocean (3.6 to 3.9%) and Pacific Ocean (4.0 to 4.1%). Larger differences were 

recorded (4.2 to 9.5%) in sequences for specimens from shallower sites (<500m), e.g. in 

seamounts from the Pacific Ocean. The largest differences (18%) were observed when the 

sequence was compared with that of Eurythenes sp. from the Tongue of the Ocean, whose 

sequences suggest a different species. The differences with the external genus Abyssorchomene

were 25%, suggesting that the abyssal scavenger amphipods of the E. gryllus species in the Gulf 

of Mexico still maintain a continuous genetic flow with the north Atlantic amphipod populations. 

Their predominant swimming behavior allows the populations to move horizontally along the 

abyssal water masses in the region. This study concluded that in spite of the morphological 

differences found a similar genetic composition to the populations from the Northern Atlantic 

exists, suggesting connectivity through the deeper passages between the Western Atlantic and 

the Caribbean and the latter through the Yucatan Channel with the deep Gulf of Mexico. 

Assemblage Composition of Megafaunal Components 

The Megafaunal Database 

A total of 1,583 specimens were captured in the database using the BIÓTICA 4.1 software. The 

Biótica information System (Biótica ©) is curatorial, nomenclatural, geographical, 

bibliographical, and ecological in nature. Biótica © was developed by the Mexican conservation 

agency (CONABIO) in a modular form to assist, reliably and simply, in the capture and updating 

of the data. This software helps link the information from the databases to information managed 

for diverse applications (images, sounds, web pages, spreadsheets, genetic databases). The 

version 4.1 was used to create the database for the deep-sea megafauna and was divided into nine 

modules (Database, Directory, Nomenclatural, Curatorial, Ecology, Georeferenciation, 

Bibliography, Tools and Help). The catalogs included in Biótica © are the names of biological 

groups up to genus or species, the names of authors of taxons, the information of the collections 

and institutions, the states and municipalities according to INEGI for Mexico, the priority 

hydrological, marine and land regions of Mexico, according to CONABIO, the catalogues that 

can be related to the sample and are personalized by the user such as types of vegetation, forms 

of nutrition, forms of life, habits, etc., the catalogue of population parameters that can be 

personalized by the user, and the nomenclatural types. 

The records and information of 92 families, 133 genera, 147 identified species and two 

infraspecies of megafaunal components can be consulted through the dynamic reports that can be 

constructed by the user-defined format according to the needs of researches, students and 

managers. The database includes 55 records with size information of the specimens and form. 
160 

The input for a each species includes the full scientific name, the taxonomic category, relations 

among taxons (synonymy, etc.) and common name, in addition to the physical and 

environmental factors and references. All megafaunal specimens have been physically located in 

six national collections (Table 2B.2) and each specimen is identified by a reference code 

provided by the collection curators. A total of 352 maps were produced and included in the 

database to display the occurrence of each species in the different regions of the southwest Gulf 

of Mexico. 

Table 2B.2. Number of species/ records of deep sea specimens from the Gulf of Mexico, including DGoMBJSSD cruises, deposited in the Mexican National Collections and included in CONABIO 

database. 

Collection 

Code 

Collection Name Institution

Code 

Institution Name No. of 

species/ 

records 

No. of 

specimens

CNCR Colección Nacional de 

Crustáceos (Crustacea) 

IBUNAM Departamento de 

Zoología, Instituto 

de Biología, UNAM

160 561 

CNMO Colección Nacional de 

Moluscos (Mollusks) 

IBUNAM Departamento de 

Zoología, Instituto 

de Biología, UNAM

29 72 

CNP Colección Nacional de Peces 

(Fish) 

IBUNAM Departamento de 

Zoología, Instituto 

de Biología, UNAM

73 260 

ICML Colección Nacional de 

Equinodermos Mexicanos 

"Dra. María Elena Caso 

Muñoz" (Echinoderms) 

ICML Instituto de 

Ciencias del Mar y 

Limnología, 

UNAM, Unidad 

Distrito Federal 

45 486 

ICML Colección Nacional del 

Phylum Porifera "Gerardo 

Green" (Sponges) 

ICML Instituto de 

Ciencias del Mar y 

Limnología, 

UNAM, Unidad 

Distrito Federal 

17 40 

ICML-CMP Colección de Mar Profundo 

(other invertebrates) 

ICML Instituto de 

Ciencias del Mar y 

Limnología, UNAM, 

Unidad Distrito 

Federal 

28 164 

The connection of the system to the database is made every time information is included; the 

configuration of fields allows introduction of new records to the data. The software Biótica © 

can be used both in a single-user environment as well as in a multi-user environment (network). 

Distribution Patterns of Species Richness, Abundance, and Diversity of the Fish 

The distribution pattern, abundance, diversity, and species richness of fishes that belong both to 

the classes Actinopteriyii and Chondrichthyes collected in trawls in the central and southwest 

Gulf of Mexico are reported here. The results obtained showed increasing diversity values at mid 

depth on the continental slope and decreased to the abyssal plain. This pattern has been 
161 

previously recorded for the northern Gulf of Mexico (NGOM) and North Atlantic (Merrett and 

Haedrich 1997). The largest diversity and evenness values (H’= 2.90 to3.55; J’= 0.58 to 0.66) 

were recorded in stations from the upper slope (548m depth) in contrast to the lowest values (H’ 

= 0.43 to 2.27; J’= 0.12 to 0.41) recorded in the abyssal plain (3725m depth). These larger values 

are related to the high species richness (98 species). 

The three geographic regions show different values of diversity; the highest values occur in the 

Campeche Bank (H’ = 3.64; J’= 0.56) with a total of 101 species. 

Distribution Patterns of Species Richness, Abundance, and Diversity of Mollusks 

The species composition and richness and abundance of mollusks of the classes Bivalvia, 

Gastropoda and Scaphopoda were analyzed in samples from cruises (SIGSBEE IV in 2001, 

SIGSBEE V in 2002, SIGSBEE VI in 2003 and DGoMB-JSSD in 2002) in the southwest Gulf of 

Mexico. The samples were collected on the continental shelf, the upper continental slope, and the 

abyssal plain and a total of 56 species were identified in 486 specimens. The largest abundance 

was recorded in class Gastropoda (43 specimens) grouped in 19 specimens on the continental 

shelf, 29 in the upper continental slope. Gastropods were absent in the abyssal plain samples and 

were replaced by eight species from class Bivalvia. The largest diversity values were recorded in 

the upper continental slope (H’ = 2.52) correlated to the increasing number of species. The 

diversity values of the abyssal plain samples responded to the large evenness values (J’ = 0.84). 

The lowest diversity and evenness values occurred in the continental shelf (H’ = 1.99; J’ = 0.68). 

A canonical correspondence analysis (Figure 2B.1) allowed us to recognize that 16% of the 

distribution patterns of the mollusk species are attributed to depth while 20.5% of the species 

have an affinity to specific geographic regions (Bank of Campeche, Mexican Ridges, and the 

Sigsbee abyssal plain). Only 6.9% of the species are related to both factors, depth and geographic 

region as described by the environmental factors from the bottom water mass and the sediment. 

Variability of Species Composition, Richness, and Abundance in the Macrocrustacean 

The first deep-sea specimens collected in the abyssal plain of the Gulf of Mexico and deposited 

in Mexican formal collections belong to the joint collaborative effort between UNAM and Texas 

A&M. Previous work on deep-sea crustaceans carried out by Mexican researchers date back to 

the mid 1980s and are related to the abundance and composition (Soto et al. 1999); the biology 

of the isopod Bathynomus giganteus (Barradas-Ortiz et al. 2003); the description of new species 

and records by Vázquez-Bader and Gracia (1994) and Gómez-Ponce and Gracia (2003); and the 

shrimp fishery and incidental discards with records of Chaceon quinquidens by Navarrete del 

Proo and Gracia (1996), Arreguín et al. (1997), and Gómez-Ponce and Gracia (2003). All studies 

include records solely from the continental shelf and slope, none from deeper habitats. 

The objective of the study was to describe the species composition of the macrocrustacean 

assemblage collected by bottom-trawl gear during the DGoMB-JSSD cruises in the Sigsbee 

abyssal plain and compare with ongoing sampling in the outer continental shelf and upper slope 

at cruises SIGSBEE.5, 6 and 7 in the western and southwestern sectors of Gulf of Mexico. 
162 

Figure 2B.1. Biplot of the canonical correspondence analysis with the distribution patterns of the mollusk 

species by depth and geographic region. 

At all cruises the samples were collected with bottom-trawling gear (OTSB otter trawl) with the 

following specification: 12m length, 9m width, 2.5 inches mesh size, cod-end. Each trawl lasted 

25 minutes of bottom contact, at speeds that varied from 1.3 to 3.5 knots, covering distances 

from 1.85 to 7.49 km. The samples collected on the outer continental shelf and upper slope in the 

Mexican Ridges and Campeche Bank regions were collected onboard UNAM’s R/V Justo Sierra

in cruises SIGSBEE.5 (6 stations, June 2002), SIGSBEE.6 (5 stations, July 2003) and 

SIGSBEE.7 (5 stations, June 2004). The samples collected in the abyssal plain (5 stations, 

August 2002) were collected in the DGoMB-JSSD cruise onboard the R/V Gyre. The specimens 

were fixed in ethanol, identified to species level where possible, counted and deposited in the 

National Crustacean Collection, and the records inserted in the Biotica information system with 

an identification catalog number. The ecological indexes were determined using the 

Biodiversity–Pro.5 software, the similarity between the different sampling sites based in the 
163 

species composition. Its presence and absence was determined by the Bray Curtis similarity 

index using average single linkage to classify the assemblage and display the results as a 

dendrogram. 

A total of 107 species of macrocrustacea was identified belonging to the orders Lophogastrida, 

Isopoda and Decapoda. The species were group into 39 families. The largest number of species 

and abundance occurred in the upper continental slope (61 species; 793 specimens). The shrimps 

of the infraorder Caridea were highly diversified with 12 species and 142 specimens occurring 

mostly in the slope and abyssal plain with 13 species and 19 specimens. The largest species 

richness was recorded in the upper slope. The region with the largest number of species was the 

Campeche Bank (CB) with 48 species. Several species co-occur in two of the three regions, none 

occur in all three geographical regions or depth zones. 

The abundance followed a similar trend with depth as the species richness; the largest abundance 

was recorded in the upper continental slope. The region with the largest abundance was the CB 

where the group with the largest abundance was attributed to the superfamily Penaeoidea. 

Densities in the abyssal plain were low, with 1,002 ind km-2, in comparison with the shallower 

sites and contributed to the largest diversity values (H= 3.27). The most frequent species were 

Nephropsis rosea and Bathyplax thypla followed by the scavenger isopod Bathynomus 

giganteus. 

The H ́ values were as low as 0.42 (Sta. E1 SIGSBEE.5) the trend increasing with depth 

characterized the area of study. The species had a low abundance and this even pattern 

contributed to the large evenness values recorded with increasing depth where the largest values 

(J ́= 0.822) occurred in the abyssal plain in contrast to those that occur in the slope (J ́= 0.487) 

and the outer continental shelf (J ́= 0.325). The evenness is the factor that defines the pattern 

observed in the diversity in the crustacean assemblage. 

Assemblage Composition of Macrofaunal Components 

The Abyssal Macrofauna 

The objective of the macrofaunal sampling was to establish the variability in the large scale of 

stations located in the abyssal plain in the central Gulf of Mexico. The information obtained 

provides a list of the taxonomic groups and abundances found in each of five replicates at each 

sampling station during SIGSBEE.6 cruise at which additionally environmental factors were 

measured such as dissolved oxygen, temperature, pH, salinity of the bottom water mass, 

chlorophyll in a six-water column strata, depth, sediment grain size, elemental organic carbon 

and nitrogen, and pigment concentration in the superficial sediment. Samples were collected for 

this purpose from every latitude and longitude within a grid at depths below 3000m in the central 

Gulf of Mexico (Figure 2B.2), the maximum depth in the basin being 3,850m. 
164 

96 94 92 90 88

18

20

22

24

26

28

30

32

E-01

E-02

E-04 E-03

E-05

E-07 E-06

E-08

E-10 E-09

E-11

E-13 E-12

E-14

E-15

E-16 E-16bis E-16bis

-3500 m

-2000 m

-500 m

L

atitud

e

N

Longitude W

Gulf of Mexico

Figure 2B.2. The area of study and the sampling stations located at 3,000m or more in the Sigsbee abyssal 

plain. 

The average values for both the taxonomic richness and abundance of the stations (n=5) sorted 

show a large variability both within station as well between station. The larger values can be 

found on the northwest section of the grid in contrast with the stations located in the southeast 

corner of the grid. A parallel sampling program provided insight on the effect of canyons on the 

macrobenthic community composition and density. 

The Campeche Canyon. The macrofaunal samples collected from the Campeche canyon in the 

southwestern Gulf of Mexico were sampled along the main axis of the canyon to answer the 

question whether canyons are different and are affected by different processes. A total of 20 taxa 

were grouped in ten phyla, 12 classes, one subclass, two suborders and six orders. The 

polychaete and nematode worms were dominant components in the canyon in contrast with the 

shallower habitats where polychaete worms were abundant. A diminishing trend with increasing 
165 

depth and distance from the coast was recorded. The hydroids contributed significantly. The 

biomass values near the head of the canyon reached values of 27.44 mg C.m-2. The distribution 

patterns of both the density and biomass values are defined in the Campeche canyon by the 

content of organic carbon and nitrogen in sediment in addition to depth and distance from the 

coast. 

The Amphipod Diversity 

As part of the macrofauna the amphipod Crustacea from the Gulf of Mexico have been reported 

for diverse habitats recording a total of 101 benthic species. The results of this study increased 

this value to 275 species that were grouped into 146 genera, 53 families and 4 suborders. The 

order Gammaridea contributed 73% (200 species), the Hyperiidea contributed 21% of the total 

number of species in the basin and species from the families Caprellidea and Ingolfiellidea 

contributed jointly a 6%. Most of the gammarid amphipods that occur in the Gulf of Mexico are, 

together with the caprellid and ingolfiellid amphipods benthic dwellers (79%). Of the 

gammaridean families the most diversified, were the Corophiidae-Ischyroceridae (24 species), 

Ampeliscidae (13 species), Lysianassidae (12 species), Colomastigidae (11 species) and 

Melitidae (8 species). In contrast, the suborder Caprellidea was poorly diversified and each 

recorded amphipod family in the Gulf of Mexico was represented by one, or at most two species. 

The largest number of records occurred in shallower habitats (75% of the records). In contrast, 

the outer continental shelf, the continental margin and upper slope displayed a low number of 

records (5%). Species from these depth zones remain gaps in our knowledge of amphipods in the 

region. Results from samples collected in the Sigsbee and DGoMB cruises recognized the 

families Ampeliscidae, Phoxocephalidae, Corophiidae and Caprellidae as dominant components 

of the amphipod assemblage off Tamaulipas and in the Campeche Bay, which host differences in 

species richness and with density that are significant (Kruskal-Wallis H = 18.19, p = 0.0027; H = 

30.26, p = 0.0001). Gammarid amphipods of the genus Pseudharpinia sp, Podocerus sp and 

Stenothoe sp. and the Caprellidae Caprella sp, Caprella danilevskii and Caprella equilibra are 

distributed in a depth range of 2,001 to 3,700 m. The species Deutella sp, Hemiaegina minuta,

Paracaprella pusilla, Byblis sp, Hourstonius tortugae, Apocorophium simile, Monocorophium 

insidiosum, Ericthonius sp, Concarnes sp, Concarnes concavus, Halice sp, Syrrhoe sp y

Protohaustorius sp., Caprella penantis, Apocorophium acutum, Ericthonius brasiliensis,

Stenothoe gallensis and Monocorophium acherusicum occur in the abyssal plain. Other species 

have a wider distribution range. 

The northern and eastern sectors of the Gulf of Mexico have been studied intensively and have 

accounted for 73% of the total number of amphipod records, in contrast to the 27% of records 

corresponding to the southern and western sectors. Probably the southeastern and southwestern 

sectors are the least explored with fewer records. The identification of the different families of 

amphipods that inhabit the deep-sea central region was composed by a large number of yet 

undescribed genera and species and will contribute to the amphipod diversity in the Gulf of 

Mexico in the near future. 
166 

Assemblage Composition of Meiofaunal Components 

The deep-sea benthic community in tropical latitudes responds to the oligotrophic condition of 

the primary production in the water column with lower abundances and smaller body sizes that 

approximate the sediment grain size, making the process of sorting specimens difficult (Duplisea 

and Dgras 1999). The meiofauna constitutes food supply for higher trophic levels (Longhurst and 

Pauly 1987) and limited in motility responds to short-term effects caused by sea-floor 

disturbances (deBovée et al. 1990, Coull and Chandler 1992). Studies of the flux of materials and 

energy in benthic communities have recognized the importance of the sediment fauna in the use 

of detritus transported to the seafloor (Rowe et al. 1990). The meiofaunal biomass in the NGOM 

is larger than that of the macrofauna (Pequegnat et al. 1990). This pattern is the reverse of that 

occurring in higher latitudes (Gray 1981). We compared two sorting methods, the manual and 

centrifuge density gradient, for meiofaunal samples of sediments from the abyssal plain (3,720 to 

3,830 m) to define whether sorting methods had an effect on the distribution patterns of deep-sea 

meiofaunal samples. Community structure factors (taxonomic composition, abundance, and 

biomass) allowed us to recognize differences between the two sorting methods. The manual 

sorting method produced more taxonomic groups and larger abundance and biomass values than 

the centrifuge sorting method. The biomass values recorded with the manual sorting method 

were larger in abyssal plain samples 26.75 mgC.m–2, than the samples sorted with the centrifuge 

method, which contained on average 1.85 mgC.m–2. The results obtained from the two sorting 

methods suggest that distribution patterns of deep-sea meiofaunal samples can be a result of the 

sorting method chosen. 

Composition and Characterization of POC 

The geochemical characterization of the particulate organic carbon (POC) was determined 

through the analysis of relative abundances of stable isotopic carbon ratios (δ13CVPDB). Scanning 

electron microscope images (SEM) helped to interpret and confirm the composition and some of 

the resulting signatures. The sampling strategy included the offshore waters of Tamaulipas with 

stations located on the abyssal plain and on the continental slope and the Campeche canyon with 

samples from six depth levels in the water column in the mixed layer, the top of thermocline, the 

deep chlorophyll maximum, the bottom of thermocline, below the thermocline, and the bottom 

water mass. The δ13CVPDB POC values in the three depth zones ranged from -25.39 to -20.95‰ 

and were identified within the range of values of marine phytoplankton (-18.00 to -30.5‰). The 

POC in the Campeche canyon showed significant differences (p=0.01) with the offshore stations. 

Differences were recorded among levels in the water column with 13C enriched with increasing 

depth. Major differences occurred between the maximum chlorophyll level and the bottom water 

mass. The differences in isotopic composition were related to the changing phytoplankton 

assemblages both from one location to another, among regions and with depth. The depleted 

values recorded with increasing depth were attributed to a larger proportion of suspended 

refractory material and to the residence time of the organic particles in the water column.

The SEM images confirmed that coccolithophore species characterized the offshore samples. 

Diatoms of genera Bacteriastrum and Chaetoceros dominated the samples collected on the 

continental slope. Diatoms of genus Nitzchia and Thalassiosira, as well as some species of 
167 

dinoflagellates of genus Oxytoxum, Dinophysis and Ceratium characterized the POC samples 

from the Campeche canyon. The size of most particles ranged between 5 and 50μm.

Acknowledgments 

Grants: Deep Gulf of Mexico Benthos Study(DGoMBS) – Joint US/Mexico Studies of the 

Sigsbee Deep (JSSD) MMS Contract 1435-01-99-CT-30991 TAMU; PAPIIT IN224503; 

IN211200; CONABIO BE013, SEP-CONACyT 2002 Code 40158; CONACyT G-27777B and 

CONACYT-G35442-T 

Colleagues and student collaborators to the study of specimens collected in the scavenger traps: 

E. Nájera Hillman, P. Acuña, F. Alvarez; the assemblage composition of megafaunal: A.B. 

Jiménez Brito, H. Espinoza, L. Alvarez, E. Naranjo; A. Gaytán, J.L. Villalobos; the macrofaunal 

components: I.P. Plaza, E.L. Estrada, I. Winfield; the meiofaunal components: C. Díaz, P. 

Legendre; composition and characterization of POC in the offshore habitats: M. González. 

Institutional support ICML and the crew of UNAM’s R/V Justo Sierra. 

References 

Arreguín, F., L. Schultz-Ruiz, A. Gracia, J. Sánchez-Chávez, and T. Alarcón-Fuentes. 1997. Las 

Pesquerías de Camarón de alta mar: explotación, dinámica y evaluación. In: FloresHernández, D., P. Sánchez-Gil, J.C. Seijo, and F. Arreguín-Sánchez, eds. Análisis y 

Diagnóstico de los Recursos Pesqueros Críticos del Golfo de México. EPOMEX Serie 

científica 7:145–172. 

Barradas-Ortiz, C., P. Briones-Fourzán, and E. Lozano-Álvarez. 2003. Seasonal reproduction 

and feeding ecology of giant isopods, Bathynomus giganteus, from the continental slope 

of the Yucatán Península. Deep Sea Research I. 50:495–513. 

Coull B.C. and T. Chandler. 1992. Pollution and meiofauna: Field, laboratory and mesocosm 

studies. Oceanography Marine Biology Annual Review 30:191–271. 

de Bovée, F., D.G. Laurence, and J. Soyer. 1990. Quantitative distribution of deep-sea 

meiobenthos in the northwestern Mediterranean Gulf of Lions. Continental Shelf 

Research 10:1123–1145. 

Duplisea, D.E. and A. Drgas. 1999. Sensitivity of a benthic, metazoa biomass size spectrm to 

differences in sediment granulometry. Marine Ecology Progressive Series 177:73–81. 

Gómez-Ponce, M.A. and A. Gracia. 2003. Distribution and abundance of larvae and adults of 

Solenocera (Decapoda, Solenoceridae) in the southwestern Gulf of Mexico. Crustaceana 

76(6):681–698. 

Gray, J.S. 1981. The ecology of marine sediments. Cambridge Studies in Modern Biology 2. 

Cambridge University Press. 
168 

Longhurst, A.R. and D. Pauly. 1987. Ecology of tropical oceans. In: Biological Communities of 

Tropical Oceans. Academic Press, Inc. USA. Pp. 62–104. 

Merrett, N.R. and R.L. Haedrich. 1997. Deep-sea Demersal Fish and Fisheries. New York: 

Chapman and Hall. 

Navarrete del Proo, A. and A. Gracia. 1996. La pesquería de camarón en Alta Mar. Golfo de 

México y Caribe Mexicano. In: Instituto Nacional de la Pesca, SEMARNAP. Pesquerías 

relevantes de México, XXX Aniversario del INP. México, Tomo 1:29–63. 

Pequegnat, W.E., B.J. Gallaway, and L.H. Pequegnat. 1990. Aspects of the ecology of the deepwater fauna of the Gulf of Mexico. American Zoology 30:45–64. 

Rowe, G.T., M. Sibuet, J. Deming, J. Tietjen, and A. Khripounoff. 1990. Organic carbon 

turnover time in deep-sea benthos. Progressive Oceanography 24:141–160 

Soto, L.A., S. Manickchand-Hileman, E. Flores, and S. Licea. 1999. Processes that promote 

decapod diversity and abundance on the upper continental slope of the SW Gulf of 

Mexico. In: Von Vaupel Klein, J.C. and F.R. Shram, eds. The Biodiversity Crisis and 

Crustacea. Rotterdam: A.A. Balkema. Pp. 385–400. 

Vázquez-Bader, A. and A. Gracia. 1994. Macroinvertebrados bénticos de la plataforma 

continental del suroeste del Golfo de México. Instituto de Biología UNAM. Publicación 

especial 12:1–113. 

Elva G. Escobar-Briones has been a Professor with the Institute of Marine Sciences and 

Limnology (ICML) of the National Autonomous University of Mexico (UNAM) since 1993. Dr. 

Escobar-Briones received an undergraduate degree in biology from the Metropolitan 

Autonomous University (UAM) in 1981, completed a master’s degree in fisheries and ocean 

sciences at UNAM in 1984 and defended a doctoral dissertation in biological oceanography in 

1987, also from UNAM, on the structure and function of benthic communities in the southwestern Gulf of Mexico. Dr. Escobar-Briones has been recognized on the study of the biology of 

benthic communities with some 55 peer-reviewed articles and over 50 reports and articles on 

related topics co-authored with both Mexican students and colleagues and international collaborators. Dr. Escobar-Briones has been the Head of the Academic Unit in Coastal and Ocean 

Systems since 1999 and is active teaching graduate and undergraduate levels at UNAM and 

coordinates the research program in deep-sea benthos of the southwestern Gulf of Mexico at 

ICML UNAM, program that is financed by UNAM’s program PAPIIT and the Mexican funding 

agency CONACyT. This project has been carried out in collaboration with Texas A&M 

University. 
169 

DEEP GULF OF MEXICO BENTHOS: SUMMARY AND SYNTHESIS 

Gilbert T. Rowe, Texas A&M University 

The DGoMB project can claim several firsts. Maps can be constructed of individual species distributions, recurrent groups (zones), species diversity for the entire northern Gulf of Mexico, 

(NGOM) from the outer margin of the continental shelf out across the abyssal plain, from 

Mexico to Florida. There is no other area of the deep ocean where such maps can be drawn. 

Features of community structure can now be correlated with dynamic processes, such as 

sediment community oxygen consumption. Nine different recurrent groups can be identified in 

the macrofauna, based on percent species shared between sites. Four of these are related to depth 

but overlap in depth with several other “zones “ that occur on the Florida slope or a canyon. The 

most dynamic sites are the upper Mississippi Trough, located just off the Mississippi Delta, and 

the De Soto Canyon, located below a region of high surface water productivity in the northeast 

Gulf of Mexico. The lowest rates were found on the abyssal plain, as expected. Diversities in all 

groups reached a maximum on the upper continental slope at depths of 1 to 2 km. The species 

diversity was lower, in general, in the Mississippi Trough than at equivalent depths on the slope, 

because, we suggest, of an increased input of organic matter and unpredictable nature of 

sedimentary processes. Species richness overall, however, was higher in the Trough, we assume, 

due to its greater physical complexity. Standing stocks of invertebrates and fishes and SCOC all 

declined by about two orders of magnitude from the continental shelf to the abyssal plain, similar 

to other ocean margins. The decline of bacteria density with depth was less pronounced and not 

statistically significant. If this pattern is real, it suggests that the relative role of bacteria in the 

processing of organic matter is increased with depth, perhaps due to a decline in the quality of 

organic matter as depth and distance from shore increase. The standing stock information has 

been coupled with the SCOC data to construct foodweb carbon budgets for two end-member 

sites: the head of the Mississippi Trough and the abyssal plain. This allows a comparison of how 

organic matter is cycled among the living components at the high and low extremes in standing 

stocks and carbon cycling. The foodweb budgets, in terms of stocks and fluxes between stocks at 

steady state, have been put into a dynamic simulation that illustrates how each stock responds to 

variations in carbon input from the water column. The model allows experiments to be 

performed that portray how carbon is cycled at radically different levels of input. 

Recommendations for future work include 1) model validation experiments, 2) studies of deep 

corals, and 3) studies of the steep Florida, Sigsbee and Campeche escarpments. 

Dr. Gilbert T. Rowe completed his B.S. in zoology and M.S. in oceanography at Texas A&M 

and his Ph.D. in zoology at Duke. That was followed by 11 years as a research scientist at WHOI 

and eight years as a research scientist at the Brookhaven National Lab on Long Island. In 1987 

he returned to Texas A&M to become Head of the Oceanography Department. He transferred to 

the Galveston campus in 2002 as Head of Marine Biology. Since 1999 he has been the Program 

Manager of MMS Deep Gulf of Mexico Benthos project (DGoMB), now nearing completion. 
171 

SESSION 2C 

SOCIOECONOMIC STUDIES 

Chair: Asha Luthra, Minerals Management Service 

Co-Chair: Kristen Strellec, Minerals Management Service 

SOCIOECONOMIC RESEARCH ISSUES FOR THE GULF OF MEXICO OCS REGION 

Harry Luton................................................................................................................................. 173 

DEMOGRAPHIC CONSEQUENCES OF THE OFFSHORE PETROLEUM INDUSTRY 

John Petterson, Roger M. Olien, and F. Carson Mencken.......................................................... 176 

ENVIRONMENTAL JUSTICE IN SOUTHEAST LOUISIANA: A COMPARATIVE 

PERSPECTIVE Scott A. Hemmerling and Craig E. Colten ..................................................... 185 

EFFECTS OF OIL AND NATURAL GAS PRICES AND PRODUCTION ON 

LOUISIANA EMPLOYMENT LEVELS: RESULTS FROM A VECTOR AUTO 

REGRESSION (VAR) ANALYSIS Omowumi Iledare and Williams O. Olatubi ................... 188 

ACCOUNTING FOR CHANGE IN THE GULF OF MEXICO ECONOMY: 

DEVELOPING A COMPARATIVE CONTEXT FOR REGIONAL ECONOMIC 

ANALYSIS AND HISTORY Allan Pulsipher.......................................................................... 193 

A COLLABORATIVE INVESTIGATION OF BASELINE AND SCENARIO 

INFORMATION FOR ENVIRONMENTAL IMPACT STATEMENTS 

David E. Dismukes ..................................................................................................................... 198 
173 

SOCIOECONOMIC RESEARCH ISSUES FOR THE GULF OF MEXICO OCS REGION 

Harry Luton, Minerals Management Service 

Background 

The Gulf of Mexico Region Workshop on Socioeconomic Research Issues, held in New Orleans 

in February 2004, is a sequel to a workshop held a decade before, but its story begins earlier still. 

The nationwide OCS leasing program was established in the late 1970s, and the social impact 

assessment (SIA) methods federal agencies were applying at that time to energy developments 

stimulated little consideration of the socioeconomic consequences of the Gulf’s offshore 

industry. 

These SIA methods were developed for new projects in rural areas and assumed that projects 

would increase labor demand, causing in-migration which would lead to other social problems. 

In the Gulf, the industry was large and long-lived and projects were without noticeable 

demographic effects. Thus, the industry had few socioeconomic consequences that were relevant 

to the assessment methods that were being applied. 

The trauma of the 1980s oil price collapse convinced people in the Gulf of the relevance of the 

industry’s socioeconomic effects. MMS began holding ITM workshops and funding several 

small studies addressing the bust. In 1992, the National Research Council reviewed the MMS 

Studies Program and noted that the lack of socioeconomic research in the Gulf was unfortunate 

since the Gulf’s history made it a “natural laboratory” for studying OCS socioeconomic effects. 

That same year, the Gulf Region, building on the natural laboratory idea, held its first 

socioeconomic agenda-setting workshop from which a robust set of socioeconomic studies 

emerged. 

Workshop Objectives 

Over the next decade, some 35 studies that flowed from this workshop were completed, and 20 

are still ongoing. The 2004 Workshop on Socioeconomic Research Issues was held in response 

to this wide-ranging research. Studies were at a juncture; the vision of the last decade was 

concluding and MMS wanted advice on how to build on it. MMS provided participants with 

descriptions of past studies, a critique of SIA based on labor demand and demographic change, a 

history of offshore oil development, and a list of challenges facing Gulf socioeconomic 

assessment including: 

 1. The lack of an unaffected baseline uncomplicated by regional and national trends; 

 2. A situation where the main effect of OCS leasing is to maintain the status quo; 

 3. An enormous affected area (coastal counties of all Gulf states); 

 4. A multiplicity of industries that find, extract, process, and market petroleum; and, 

 5. A problem with locating local effects prior to local development plans. 
174 

Workshop Organization and Breakout Groups 

This workshop included a half-day introductory plenary session, one and one-half day breakout 

groups, and a half-day plenary session to share results. MMS identified some people for each 

breakout to ensure a mix of local, academic, and industry expertise. Groups brainstormed, 

categorized and identified topics, and developed study proposals. Breakout groups included: 

 1. Industry trends and dynamics, chaired by Kristen Strellec and Diana Olien, 

 2. Community-level impacts, chaired by Asha Luthra and Barbara Wallace, and 

 3. Cultural impacts, chaired by Kimberley Cook and Dianne Austin. 

Industry Trends Breakout 

Generally, SIA focuses on the construction industry as the cause of other effects. By contrast, 

GOMR studies emphasize characteristics of the petroleum industry itself. This focus began with 

economic modeling and attempts to regionalize effects in the Gulf. A study of sour gas in 

Alabama, particularly, highlighted the importance of variability in industry demand, by showing 

significant differences between it and the Gulf offshore industry average. 

The industry session developed many study ideas that exhibited two basic themes: First, the 

group emphasized the need to develop a good picture of each major industry sector, its size, 

distribution, labor force, internal dynamics, etc. Related to this was the priority need for better 

data on all sectors and the suggested development of a set of variables to monitor the industry. 

The second theme was the need to understand industry activity in the Gulf of Mexico (GOM) 

within a larger global context. 

Community Impacts Breakout 

The Family Study greatly influenced Gulf SIA by using industry sectors in the analysis of social 

impacts. Since sectors make different demands on labor, host communities, and the environment, 

they also have different socioeconomic consequences. Because sector dynamics differ, each 

sector’s effects are changing in different ways. While past SIA used demography to drive 

change, the Gulf stresses differential effects of industry dynamics. 

Two themes run through the group’s study ideas that will likely inform future research. First, 

while SIA looks at rural landscapes, oil support activities occur in urban areas. Houston is a 

successful oil boomtown, New Orleans a declining one. The group emphasized the analysis of 

urban effects and a city’s effects on surrounding rural areas. Second, the group suggested 

typologizing adaptations to the oil industry—the types of relationships between government, 

communities and/or individuals and industry, and the possible outcomes inherent in these 

relationships. 

Cultural Impacts Breakout 

SIA seldom addresses culture and, when it does, it usually focuses on attitudes (e.g., toward risks 

or the environment). Cultural questions interest agency staff but are generally too off-topic or 

ideological (e.g., “Cajun oil-field yard art” or “oil wealth as a symbol of corruption”). We 

addressed cultural impacts to see how the topic might be developed. 
175 

Participants emphasized current difficulties with defining culture groups, noting that, while 

individuals may still self-identify as Cajuns or Yugoslavians, the localized social and economic 

distinctions that existed 50 years ago have largely disappeared. They noted that some recently 

immigrated groups (e.g., Vietnamese) are national rather than cultural groups. Participants 

suggested alternatives to culture groups including populations of large geographic areas (e.g., 

“southwest Louisiana” or “Cajun country”) and membership in occupational, religious, and other 

types of groups. Participants explored the use of geographical areas for sociocultural analysis, 

suggesting the importance of formal, data-intensive methods in defining areas. Participants also 

explored the use of industry sectors in the analysis of cultural effects. Since the move from 

shallow to deepwater affects various industry sectors differently, this move affects various 

workforces and host communities differently. All breakout sessions emphasized land loss issues. 

Conclusions 

The workshop confirmed the importance of industry sectors as a driver of effects and as an 

organizing principle of analysis. Various methods and significant studies effort will be employed 

to describe, measure, and project the industry. All three breakout groups emphasized the 

differential social and economic consequences of various parts of the oil industry. Thus, some 

MMS research will focus on particular sectors or on communities dominated by them. However, 

many industry consequences have diffuse and/or aggregate causes unrelated to a particular 

sector. Therefore, a standard list of SIA effects (e.g., labor demand, demography, fiscal, 

infrastructure, etc.) will also direct future plans. 

All three breakout groups raised complex issues regarding geographic variation in industry 

activities and their OCS effects. This problem, too, will be addressed as a component of the 

industry sector and SIA foci, and through case studies of particular places. Participants suggested 

that this geographic variation might be defined in terms of variable boundaries or epicenters. 

Participants noted that similar difficulties inherent in identifying OCS effects in urban areas also 

needed to be addressed. 

While the workshop breakouts distinguished between the sociological and anthropological, 

immediate studies planning will not. Instead, cultural effects will be addressed by expanding 

goals and methodologies of particular studies. For example, a standard SIA study of education 

would include fiscal and demographic impacts. Cultural effects might be addressed including 

questions of educational content (e.g., school-to-work or job training programs). 

The workshop addressed all the challenges we identified except one: the problem of linking sale 

effects to industry effects remains a basic challenge to SIA of the OCS leasing program. 

Harry Luton was born in Michigan. He received his undergraduate degree from the University of 

Michigan, a Masters from the University of Pennsylvania, and his doctorate from the University 

of Michigan. Since 1982, he has worked in MMS’s environmental assessment branch, first in 

Alaska, then Headquarters and, for the last nine years, the Gulf of Mexico OCS Region. 
176 

DEMOGRAPHIC CONSEQUENCES OF THE OFFSHORE PETROLEUM INDUSTRY 

John Petterson, Impact Assessment Inc. 

Roger M. Olien, University of Texas-Permian Basin 

F. Carson Mencken, Baylor University 

Project Goal 

Develop a systematic understanding of the GOMR petroleum industry’s demographic effects, the 

distribution of these effects, their causes, their changing trends, and the differences between 

onshore and offshore activities. 

Project Objectives 

 1. To provide a coherent description of such changes in demographic effects through time 

and the reasons behind these changes through the analysis of a coherent set of research 

questions developed from the study objectives; 

 2. To provide a general understanding of the industry’s demographic effects and causes of 

those effects over time. As the industry and society have evolved, these effects have 

changed. For example, while early onshore hydrocarbon discoveries often led to localized 

“boomtowns,” the recent large discoveries in deepwater have not; 

 3. To provide a general understanding of variation (state and sub-state) in those effects and 

the causes of this variation. For example, the demographic consequences of the 1980s oil 

price collapse were different for Texas than for Louisiana. MMS seeks a coherent 

description of the reasons behind such variation; and 

 4. To provide a differentiated and well documented data system that would allow a 

continuous monitoring of demographic changes in the future. 

Research Team 

• John S. Petterson, Ph.D., Anthropologist, PI 

• Carson Mencken, Ph.D., Sociologist, Co-PI 

• Roger Olien, Ph.D., Oil Historian; Co-PI 

• Michael Irvin, Ph.D., Demographer, Co-PI 

• Charles Tolbert, Ph.D., Sociologist, Co-PI 

Quality Review Board 

• Joachim Singelmann, Ph.D., Sociologist 

• Norval D. Glenn, Ph.D., Historical Demographer 

• Richard Forstall, Ph.D., Demographer 

• Joseph Pratt, Ph.D., Historian 
177 

Research Objectives 

Objective 1 

Describe and analyze the petroleum industry’s demographic consequences. Sections I, II, and IV 

in the demographic analysis meet this criteria. In Section I, we describe total and contextual 

population trends for each decade between 1900 and 2000. In Sections II and IV we disaggregate 

population growth trends between different levels of geography, from macro (national) to micro 

(county/parish). In Section IV we propose a more robust attempt (e.g. regression models) to link 

micro-level demographic changes since 1950 to direct and indirect changes in the petroleum 

industry. In Section IV we also propose to analyze the journey-to-work patterns in Texas and 

Louisiana coastal areas prior to, during, and following the growth and decline periods in the 

petroleum industry. 

Objective 2 

Describe and analyze differences between offshore and onshore industries. Section III, the spatial 

clustering analysis of county/parish unique population effects, will be useful in this objective. 

Working from the assumption that onshore and offshore activities did not occur in the same time 

or place (particularly in Texas), the spatial analysis will help to differentiate the unique effects of 

these two processes by locating the clusters of petroleum-related demographic changes in both 

time and space. 

Objective 3 

We describe and analyze the short- and long-term demographic effects of the industry’s volatility 

in Texas and Louisiana. The first three sections of the proposed demographic analysis address 

some component of this objective. Section I describes demographic change over time, Section II 

helps to identify the factors and conditions that affect the magnitude of change by examining 

population dynamics within each decade (1950–2000) and by locating the impact of local unique 

characteristics on decade-specific demographic change. Section III is a formal test of spatial 

distribution and clustering of these effects in Texas and Louisiana. The off-shore petroleum 

industry is not randomly distributed throughout these two states. This analysis will better locate 

time and place effects. 

Objective 4 

Describe and analyze the consequences that the industry has had on the demographic 

characteristics of the Louisiana and Texas workforce. The shift-share analysis in Section II will 

provide valuable insight into the effects of population change related to the petroleum industry 

on the composition of the states and communities. It allows us to document growth and/or 

decline in sex/age/race/ethnicity specific populations. The analysis of journey-to-work patterns 

for 1960–2000 will demonstrate how changes in the petroleum industry affected county/parish 

level commuter patterns. 

Objective 5 

Describe and analyze current demographic effects. The analysis in Sections I and II for the 1990s 

will provide an understanding of how the changes in the petroleum industry after the bust of the 
178 

1980s affected the demographic structure of petroleum industry communities as reflected in the 

2000 Census. 

Objective 6 

Provide a framework that can be used for ongoing monitoring of demographic change. The shiftshare is an analytical tool that can both describe what has happened in the past and make future 

projections about demographic composition and change. The multilevel modeling can be used as 

a guide to the relative importance of different spatial levels (nation, state, CZ, county/parish, 

place). 

Research Design 

Multi-Level Demographic Analysis Plan 

We divide the demographic analysis into four sections. Each section provides a unique analysis 

to describe and understand population change in size and composition from 1900 to 2000. Each 

section progressively moves toward providing a better link between the petroleum industry and 

population dynamics at different levels of geography. 

Levels of Geography Defined 

We perform demographic analysis at multiple levels of geography. Local and regional 

population change is not independent of state, regional, and national trends. Any endeavor to 

understand demographic change at the local level must take the macro-level processes into 

account. The definitions of national and state are clear. We incorporate other levels of analysis: 

regional, which we define as the five Gulf of Mexico (GOM) states; sub-state, which we define 

as Commuter Zones (CZs) based on commute to work patterns, and local, which we define as 

county/parish. We will use the place as a level of geography and explore trends at this level in 

limited context. We prefer using CZs as a sub-state geographical unit because they represent a 

more substantively meaningful sub-division. They are based on journey-to-work patterns. 

The first analysis is a descriptive account of demographic change for multiple levels of 

geography. A descriptive analysis provides a base-line understanding of when and where 

population change took place, and how local patterns in the geographic areas of interest correlate 

with and deviate from national, state, and regional trends. We perform the descriptive analysis 

for all decades between 1900 and 2000. However, there are more detailed data available, 

particularly regarding age, race, ethnicity and sex breakdowns, from 1950 forward. 

 I. Description of Population Change 1900–2000 

In this section we describe general population trends for each decade between 1900 and 

2000 at multiple levels of geography: 

 a) the national level, 

 b) the regional level (defined as all GOM states), 
179 

 c) the state level (Louisiana, Texas, and Florida for comparison), 

 d) the commuter zone level (sub-state level), and 

 e) the county/parish level (local level—includes all counties/parishes in Louisiana, 

Texas, and Florida for comparison). 

At each level, we provide 

 a) The population change for each decade between 1900 and 2000 

 b) A detailed description for age/sex/race/ethnicity composition and change for each 

decade between 1950 and 2000 

There are approximately 400 places in the Texas and Louisiana coastal counties/parishes 

along the GOM. We provide demographic descriptive statistics for those coastal places 

for years in which data are available. 

We are particularly interested in the GOM coastal economy counties/ parishes. These are 

defined by whether or not the county/parish is in a labor market area that borders the 

GOM. We expect that these counties/parishes are embedded within economies that are 

the most off-shore petroleum industry-intensive. To better understand the effects of the 

off-shore petroleum industry, we compare population change in this cluster of 

counties/parishes to other counties/parishes within these states. In Texas and Louisiana 

these counties and parishes include: 

 a) Texas counties: Aransas, Austin, Brazoria, Brooks, Calhoun, Cameron, 

Chambers, Duval, Fort Bend, Galveston, Hardin, Harris, Jackson, Jasper, 

Jefferson, Jim Wells, Kenedy, Kleberg, Liberty, Madagorda, Montgomery, 

Newton, Nueces, Orange, Polk, Refugio, San Jacinto, San Patrico, Tyler, Victoria, 

Waller, Washington, Willacy. 

 b) Louisiana parishes: Allen, Assumption, Beauregard, Calcasieu, Cameron, Iberia, 

Jefferson, Jefferson Davis, Lafourche, Orleans, Plaquemines, St. Bernard, St. 

Charles, St. James, St. John the Baptist, St. Mary, St. Tammany, Terrebonne, 

Vermilion, Vernon. 

 II. Demographic Shift-Share Analysis of Population Growth 

In this section we plan to use demographic shift-share analysis to make multiple 

comparisons of population growth rates (by age, race, ethnicity, sex). Demographic 

changes at the local level are not independent of transformations at higher levels of 

analysis. Since 1920, western economies have undergone industrial transformations from 

agriculture to manufacturing and subsequently from manufacturing to services 
180 

(Singelmann 1978). Each of these transformations has had an impact on key demographic 

variables (family size, residency patterns/mobility, fertility, etc.). These national trends 

are independent of changes in the petroleum industry during the same time period. 

Therefore, to understand the effects of the petroleum industry on sub-national levels (i.e. 

state, county), we must separate local demographic changes from those that occur as a 

result of national shifts in the primary mode of production (agriculture to manufacturing 

to services). Demographic shift-share analysis provides a multi-level analysis and 

attributes demographic change in a local area to three sources 1) local population change 

associated with overall population growth or decline in the region (usually defined as a 

state, group of states or nation), 2) local population change associated with the interaction 

between regional growth and the specific demographic composition in a local area (the 

share of demographic change associated with the local mix of age/race/sex/ethnicity 

groups), and 3) patterns of demographic change not shared with the larger state or region, 

that are attributed to the unique conditions of each locality (shift)—the ‘unique effect’ of 

each locality. The advantage of this method is that it specifies multi-level/micro-macro 

links between local population growth and larger demographic patterns. It will also 

provide to us, for each decade between 1950 and 2000, an assessment of the population 

growth (by age, race, ethnicity, sex) that a) is due to the national growth rate, b) is due to 

the demographic composition of a local area associated with national patterns of growth 

and decline, c) that which is due to the unique conditions of the local area, such as the 

industry structure of the local area. 

 a) National vs. State Level Shift-Share Analysis: This analysis will differentiate state 

population growth (by age, race, ethnicity, sex) into state-level growth that is due 

to national growth rates, that which is due to the demographic composition of the 

state, and that which is due to the unique conditions of the state. This analysis will 

be performed for each decade between 1950 and 2000 and include the 48 

contiguous states. One benefit of this analysis to the overall project is that the 

shift component will identify the ‘unique effects’ for the states in question 

(Louisiana, Texas) or the population growth in these states during each decade 

that is attributable to the unique conditions of the state. This analysis will be 

performed for each decade between 1950 and 2000. If the petroleum industry had 

a unique effect on the population dynamics of Louisiana and Texas at the state 

level, then these effects should manifest during some of the decades under 

consideration (most likely the 1970s and 1980s). 

 b) County/Parish vs. National Level Shift-Share Analysis: This analysis will differentiate county/parish population growth (by age, race, ethnicity, sex) into 

county/parish level growth that is due to national growth rates, that which is due 

to the demographic composition of the county/parish, and that which is due to the 

unique conditions of the counties/parishes. One benefit of this analysis to the 

overall project is that the shift component will identify the ‘unique effects’ for the 

counties/parishes in the study area. We expect that the petroleum industry 

counties/parishes have different demographic change patterns in different time 
181 

periods than other counties/parishes. This analysis will be performed for each 

decade between 1950 and 2000. The magnitude and character of these unique 

effects is expected to vary across time and space in ways associated with activity 

levels of the petroleum industry. 

 c) Commuter Zones vs. State Level Shift-Share Analysis: This analysis will 

differentiate sub-state (commuter zones) regional population change (by age, race, 

ethnicity, sex) into population change that is due to state growth rates, that which 

is due to the demographic composition of the commuter zone, and that which is 

due to the unique conditions of the commuter zone. This analysis will be 

performed for each decade between 1950 and 2000 and will identify regional 

effects within Texas and Louisiana. 

 d) County/Parish vs. State Level Shift-Share Analysis: This analysis will differentiate county population growth in Texas (by age, race, ethnicity, sex) and parish 

population growth in Louisiana into county/parish level growth that is due to state 

growth rates, that is due to the demographic composition of the county/parish, and 

that is due to the unique conditions of the counties/parishes. This analysis will be 

performed for each decade between 1950 and 2000. The shift component can be 

of further use to understand the spatial distribution of population change (in size 

and composition) within Texas and Louisiana. 

 e) Place Effects: We also propose to decompose for those places in the coastal 

counties/parishes in Texas and Louisiana demographic change between 1970 and 

2000 at the place level. We intend to analyze the shift-component ‘unique effect’ 

using hierarchical linear modeling (see below). 

 f) Petroleum Industry Effects: Based on previous research we have a good sense of 

the time and place where the components of the petroleum industry were located, 

including those industries directly related to oil and gas exploration/production, 

and those industries indirectly connected to oil and gas production (e.g. 

fabrication of oil field equipment in the Houston, Lafayette, and Beaumont 

regions, petroleum refining in Lake Charles region). At the county/parish level, 

we descriptively and statistically compare the ‘unique effect’ total population and 

age/race/ethnicity/sex-specific population growth. The population change due to 

the ‘unique effect’ of local counties/parishes relates directly to issues of 

migration. A negative shift value indicates potential county out-migration, while a 

positive shift value indicates possible in-migration. Furthermore, a positive shift 

effect for age/race/ethnicity/sex-specific population growth indicates positive inmigration of a particular social group. The in-migration is attributed to the unique 

characteristics of the county/parish. 

At the county, CZ, and state level we will calculate, map, and describe the ‘unique effect’ 

of total population change, as well as age/race/ethnic/sex-specific change for each decade 
182 

between 1950 and 2000. This will allow us examine the effect of local unique characteristics on age/race/ethnicity/sex-specific population change. This will allow us to 

explore the role of the petroleum industry on contextual (i.e. age/race/sex-specific) 

population dynamics, with important implications for population migration and retention. 

Furthermore, by knowing the time line of the petroleum industry growth and decline 

periods, we can use the shift-share analysis comparison of state vs. national population 

growth to explore the impact of the petroleum industry (and the effects of petroleum 

industry counties/parishes) on state population dynamics. 

 III. County/Parish Level Spatial Clustering Analysis 

The shift component of the shift-share analysis will generate a ‘unique effect’ of 

population growth (by age, race, ethnicity, sex) for each of the decades between 1950 and 

2000. This unique effect represents the population change in the county/parish that is due 

to the unique characteristics of that county/parish. We propose to use a local indicator of 

spatial autocorrelation (LISA) statistics (particularly Moran’s I and Geary’s C) to examine (and map) spatial clustering in the county/parish ‘unique effects’ for each of the 

decades between 1950 and 2000. The off-shore petroleum industry is not randomly 

distributed throughout these two states. If the boom-and-bust pattern in the petroleum 

industry had an effect on the population composition of the counties/parishes, then we 

should see time-specific spatial clustering of county/parish population change that is 

attributable to the unique characteristics of the county/parish. Furthermore, working from 

the assumption that onshore and offshore activities did not occur in the same time or 

place, the spatial analysis will help to differentiate the unique effects of these two 

processes. 

 IV. Regression Analysis with the Unique Shift Effect 

While the shift-share analysis provides data to perform interesting descriptive analysis, 

we also employ pooled time-series cross-sectional regression models within each decade 

between 1950 and 2000 to better understand the role of the petroleum industry in 

explaining the county/parish ‘unique effect’ population growth in Louisiana and Texas 

counties/parishes. We treat the county/parish population growth ‘unique effect’ as a 

dependent variable in a regression model, while including inter-census industry employment growth measures in mining, manufacturing, construction, services, and unique 

institutional structures of each area (associations, third places, churches) as predictors, 

along with standard socioeconomic control measures (previous decade population 

change, age composition, education measures, income measures). The pooled time-series 

cross-sectional approach permits us to decompose change into temporal and spatial 

components. 

This analysis will tell us, over time, which industry sectors (if any) are most responsible 

for the county/parish ‘unique effect’ total population growth, and age, race, ethnic, sexspecific population growth. Furthermore, in order to address the issue of what conditions 
183 

demographic impacts have led to the kinds of problems hypothesized by customary social 

impact assessment, we perform further regression analysis. In the second set of regression 

models we utilize the ‘unique effect’ population growth during each decade as an 

independent variable to predict standard county/parish level measures of socioeconomic 

conditions (poverty rates, median and per capita income levels, female-headed 

households, and crime rates) at the end of each decade. 

We also propose in our Section IV regression analysis to employ the new class of 

multilevel statistical models known as hierarchical linear modeling (Raudenbush and 

Bryk 2002). The lowest level (level one) of the model would be specified as attributes of 

places nested within counties and parishes. The second level would be characteristics of 

the counties themselves. Like other regression approaches, these models permit us to 

assess the effects of level-one (places) on the unique demographic effects derived in the 

shift-share analysis. Unlike other approaches, the hierarchical models also permit us to 

make sound statistical assessments of the effects of second-level (and other higher-order) 

effects. Moreover, this multilevel modeling approach allows for cross-level interaction 

effects which reveal how the attributes of counties affect place-level relationships. We 

might find at the first level, for example, that places with large mining labor force 

components exhibit more out-migration than other places (a positive relationship between 

mining employment and net out-migration). However, it is conceivable that a secondlevel measure of civic climate (e.g., per capita churches or per capita associations) has an 

attenuating cross-level effect on the place-level relationship between employment and 

migration. Simply put, counties with more civic institutions show less of a relationship 

between mining employment and out-migration. In statistical terms, the cross-level 

coefficient reduces the positive first-level coefficient. Since multilevel time-series 

estimators are not well developed, we propose to develop cross-sectional models for 

years in which place-level data are available. 

 a) Coastal Commuter Zone Analysis: We propose to analyze changes in the coastal 

Commuter Zones between 1960 and 2000. We will compare the journey-to-work 

patterns in the 1980 CZs to the 1970 and 1960 journey-to-work patterns in the 

Texas and Louisiana coastal CZs. This analysis will provide an assessment of 

how the growth period in the petroleum industry affected the journey-to-work 

patterns in these coastal areas. We will also compare the 1980 journey-to-work 

patterns to the 1990 and 2000 journey-to-work patterns in the coastal CZs. This 

analysis will inform how the downturn in the petroleum industry affected the 

journey-to-work patterns in coastal areas along the GOM. 

 b) Data Source: The data for this project come from two primary sources. 

Demographic and socioeconomic condition, institutional data are from the decennial census for each decade between 1900 and 2000. From 1950 to 2000, detail 

age/race/ethnicity/sex data are available at the county/parish level. Prior to 1950, 

more general measures of population and composition are available. Industry 

employment data are from the BEA Regional Economic Information Systems. 
184 

References 

Raudenbush, S.W. and A.S. Bryk. 2002. Hierarchical Linear Models: Applications and Data 

Analysis Methods. Second Edition. Newbury Park, CA: Sage. 

Singelmann, J. 1978. From Agriculture to Services: The Transformation of Industrial 

Employment. Beverly Hills CA: Sage Publications. 

John Petterson has served as the PI on about 20 prior MMS socioeconomic studies—in the 

GOMR, in Alaska, and the Atlantic. He has also led the impact assessments of the proposed 

high-level nuclear waste repositories at Hanford, Washington, and then later, at Yucca Mountain, 

Nevada. He was also the PI for the state of Alaska socioeconomic impact assessment of the 

Exxon Valdez oil spill, as well as studies of the Shetlands Islands, La Coruña, Spain, and Genoa, 

Italy oil spills, as well as the sinking of the P-36 deepwater oil platform off the coast of Brazil. 

He is also conducting the follow-up study of the Exxon Valdez oil spill for the Alaska MMS 

office. 

Roger M. Olien earned his Ph.D. in history and political science from Brown University in 1973 

and is regarded among the leading U.S. historians with respect to the history and evolution of oil 

development in the U.S. He is currently the J. Conrad Dunagan Professor of Regional and 

Business History at the University of Texas-Permian Basin. The present study focuses on 

questions that have been central to his professional career. Dr. Olien has written several of the 

seminal historical works on oil development, including Oil Booms: Social Change in Five Texas 

Towns (1982), Wildcatters: Texas Independent Oil Men (1986), Life in the Oil Fields (1986), 

Easy Money: Oil Men and Investors During the Jazz Age (1990), Oil and Ideology: The Cultural 

Creation of the American Petroleum Industry (2000), Oil in Texas: The Gusher Age, 1895-1945 

(2002), and Black Gold: The Petroleum Industry in Texas (2003), and Oil in Texas: The Mature 

Age, 1945 to the Present (2004). 

F. Carson Mencken earned his Ph.D. in sociology at Louisiana State University and is an 

associate professor of sociology and anthropology at Baylor University. Dr. Mencken specializes 

in the sociology of regional processes in primary sector economies—that is, economies with 

significant concentrations of agriculture and/or mining (coal and oil/natural gas). In addition to 

advancing the conceptual issues of regional processes, Dr. Mencken has extensive experience 

and expertise performing spatial analysis (over time) on county and labor market area data. Dr. 

Mencken has published 11 articles on this topic in peer-reviewed journals in the last five years, 

and recently completed the analysis of labor market analyses for coastal LMAs in the five GOM 

states on the MMS projects entitled Effects on Local Human Communities Of OCS Mineral 

Extraction in Frontier Areas and Deepwater Program: Benefits and Burdens of OCS Activities 

on Selected Communities and Public Institutions. 
185 

ENVIRONMENTAL JUSTICE IN SOUTHEAST LOUISIANA: 

A COMPARATIVE PERSPECTIVE 

Scott A. Hemmerling and Craig E. Colten, Louisiana State University 

This project employs a geographic perspective to compare the relative degree of environmental 

justice impacts found in different sectors of the vertically integrated oil extraction and processing 

industry. In particular, it builds upon methods recently developed to investigate environmental 

justice concerns associated with outer continental shelf (OCS) oil and gas extraction 

(Hemmerling and Colten 2003). Given its offshore location, OCS presents few potential impacts 

at the extraction site; points of potential impacts lie, instead, along transportation corridors 

(surface or pipeline) or proximate to service-related industries. Further reducing impacts is the 

low population density in the Louisiana coastal zone, where wetlands inhibit urbanization and 

many workers and their families live far from the actual embarkation sites. Moreover, minority 

and low-income families are not heavily concentrated near nodes of activity associated with the 

extraction industry. Populations living nearby face a range of potential impacts—explosions, 

accidental releases on site, transportation related releases, or fires. 

Our methodology allows us to compare findings across these different sectors and develop 

generalizations about levels of relative risk to low-income and minority populations. We 

incorporate toxicity values into the new hazardscape models and are thus able to develop a 

relative comparison between the different types of facilities. When we use a cumulative hazardscape weighted by toxicity, we are able to compare all facilities in our entire study area on a 

single sliding scale. For federal agencies, such as MMS, such a methodology will allow 

researchers to more effectively gauge, classify, and possibly ameliorate, instances of environmental injustice. 

The current research explores the environmental justice implications in three individual case 

study parishes, each focusing on one particular aspect of the petrochemical industry. The intent is 

to compare the environmental impacts of extensive onshore and offshore oil and gas development in three Louisiana coastal parishes and to examine any socioeconomic inequality patterns 

in their distributions. The chosen parishes all represent different stages of historical petroleum 

development in Louisiana. Lafourche Parish, for example, is a coastal Louisiana parish that 

serves as the primary land-based supply center for the majority of the Outer Continental Shelf 

(OCS) oil activity occurring in the Gulf of Mexico (GOM). Because of its role in OCS activity, 

Lafourche Parish is uniquely impacted by the industry. 

Jefferson Parish is a highly urbanized parish with over 455,000 residents. Its total minority 

population of 152,636 (33.5%) closely mirrors the state proportion (35%). Studies have shown a 

greater concentration of environmental inequity in urban locations, and it is essential to consider 

one such parish in coastal Louisiana for comparative purposes. Jefferson Parish’s population 

living in poverty in 2001 (18.9%) was nearly the same as the state’s percentage (18.2). Thus, 

Jefferson Parish has a much larger population that might be susceptible to exposure to impacts 
186 

from the highly dispersed activity of oil extraction than Lafourche does. Moreover, the 

distribution of minorities and low-income residents in Jefferson is much higher than in 

Lafourche. With a total of 236 active wells in 2002, there is considerable on-shore activity in 

Jefferson Parish. 

Like the other two parishes, St. Bernard is a coastal parish. Among its 67,000 residents, 14.5% 

represent a minority population and 13.2% live in poverty according to the census bureau’s 2001 

estimates. With two refining operations, employing over 500 workers, St. Bernard provides a 

good site for examining refining activity. In the case of an oil refinery, the activity is highly 

concentrated and the potential for exposure spatially compressed, but the degree of hazard is 

high due to the risk of explosion or toxic release. The minority and impoverished population for 

St. Bernard is similar to that of Lafourche and will enable a reasonable cross-sector comparison. 

The susceptible populations are highly concentrated in the areas along the natural levee, so risk is 

ever present in the relatively small territory occupied by human settlements. 

In all, we see many differing patterns of environmental justice in our case study parishes, from 

the impact of shipyards and gas plants on the Houma Indian population to the locating of 

petroleum bulk storage in the heavily urban areas of Jefferson Parish’s westbank. We have 

created a number of localized hazard models, geared specifically to each sector of the oil 

industry. But, what do these models tell us about the relative hazardousness of each sector of the 

oil industry? How OCS-related hazards, for example, compare to onshore and refinery-related 

hazards? 

As would be expected, the refining district in St. Bernard Parish dominates the overall 

hazardscape. Nonetheless, when we explore the risk surface statistically, localized high points 

around Marrero, the Barataria Fields, and the gas plants in rural St. Bernard Parish still stand out, 

despite low relative values. Though the localized high-hazard areas in Lafourche are still 

significant, they are statistically much less than those in the other two regions. 

Of the three sectors of the oil industry explored in this study, we found that OCS-related hazards 

are the most dispersed, and thus the least overtly hazardous. This is because the actual extraction 

sites are located far offshore, away from the parish itself. As a result, industries have fewer 

constraints on where to locate their facilities. While Port Fourchon, for example, is clearly the 

most convenient place for industry to located, relative to proximity to the offshore wells, it is 

also economically feasible for facilities to be located further upstream. Thus, we see shipyards 

located all along Bayou Lafourche, from Fourchon to Golden Meadow, up through Larose and 

Lockport. Petroleum bulk storage facilities are located in many communities across south 

Lafourche, with a larger facility in north Lafourche. In the case of some industries, such as 

platform and pipeline fabrication, facilities are even located in adjacent parishes, reducing the 

overall hazardousness of the region. 

The other two sectors are much more constrained economically, geographically, and politically. 

In Jefferson Parish, the onshore-related infrastructure must necessarily be placed in the 

immediate vicinity of the oil fields. Thus we see a much greater clustering of facilities and 
187 

hazardousness than in other locations. Petroleum refining requires large-scale facilities and a 

large labor force as well as transportation infrastructure and easy access to large amounts of 

water for reactive and cooling purposes. In coastal Louisiana, the potential siting locations for 

large refineries are extremely limited, not to mention the political incentives and disincentives 

involved in siting such a potentially hazardous facility. 

It is the flexibility in locating new facilities that results in OCS-related infrastructure being lower 

on the potential hazardousness scale than both the onshore extraction and petroleum refining 

industries. The more dispersed the industries, the less the cumulative potential toxicity of the 

region. Despite these findings, it is important that agencies with oversight, such as MMS, remain 

vigilant and assure that no one area comes to dominate the hazardscape of the region, especially 

if that area is home to a disproportionately large minority or low-income populations. 

References 

Hemmerling, S.A. and C.E. Colten. 2003. Environmental Justice Considerations in Lafourche 

Parish, Louisiana. Final Report. U.S. Dept. of the Interior, Minerals Management 

Service, Gulf of Mexico OCS Region, New Orleans, LA OCS Study MMS 2003-038. 

354 pp. 

Craig E. Colten is Carl O. Sauer Professor of Geography at Louisiana State University. After 

completing his Ph.D. at Syracuse University in 1984, he spent a dozen years working for the 

Illinois Department of Natural Resources and in private-sector consulting investigating the longterm implications of hazardous wastes. In 2000, he joined LSU and has overseen research for the 

Minerals Management Service, U.S. Geological Survey, and the National Park Service. He 

recently published An Unnatural Metropolis: Wresting New Orleans from Nature (LSU Press, 

2005). 

Scott A. Hemmerling is a doctoral candidate in the Department of Geography and Anthropology 

at Louisiana State University. He received his B.S. in environmental studies from the State 

University of New York at Buffalo and his M.S. in applied urban anthropology in the College of 

Urban and Public Affairs at the University of New Orleans. 
188 

EFFECTS OF OIL AND NATURAL GAS PRICES AND PRODUCTION ON 

LOUISIANA EMPLOYMENT LEVELS: RESULTS FROM A VECTOR AUTO 

REGRESSION (VAR) ANALYSIS 

Omowumi Iledare2 and Williams O. Olatubi, 

Louisiana State University, Center for Energy Studies 

Abstract 

This study finds that changes in oil and gas prices affect Louisiana employment in a statistical 

sense. The results indicate that negative shocks to natural gas prices, ceteris paribus, have a more 

distressing impact on Louisiana gross employment trend in the short run than equivalent shocks 

to oil prices in terms of elasticity estimates. The opposite is the case in the long run. However, in 

quantitative employment terms, the impact of an 18% positive shock to oil price (about $4.15 per 

Bbl) is estimated as 10,000 jobs in the short run or 26,600 jobs if the shock persists for a long 

period. Whereas, the quantitative impact of a 20% shock to natural gas price ($1.45 per Mcf) is 

estimated as 28,500 jobs in the short run or 45,600 jobs in the long run, ceteris paribus. 

Introduction 

Most boom-and-bust economic cycles in oil and natural gas rich states such as Louisiana, Texas, 

and Oklahoma have been linked to developments in the oil and natural gas markets, which 

invariably center on changes in oil and natural gas prices. As Brown and Yucel (1995) reported, 

such price movements in the oil and natural gas markets in the 1970s and 1980s led many to 

suggest that energy is “the tail that wags the dog.” Increasing energy prices may spur higher 

activities in the oil and gas sectors as well as sectors such as banking as investors demand more 

funds, which in turn leads to higher levels of demand as employment rises. On the other hand, a 

price that is too high may hinder the refinery and petrochemical sectors, for example, as cost of 

inputs rises substantially, bringing a potential loss of jobs (Scott 2002). The focus of this study 

on Louisiana is motivated by the role of the state in meeting U.S. oil and gas consumption needs. 

In this study, a time-series econometric model is developed to examine the impact of changes in 

crude oil prices on both the oil industries and relevant Louisiana macroeconomic aggregates. The 

analysis is restricted to the interactions among oil and gas prices, petroleum production from 

Louisiana offshore waters, and Louisiana state employment. 

Theoretical Model Specification 

A VAR modeling methodology is adopted in this study. In its generalized formulation, every 

dependent variable is modeled as a function of its immediate past values and the past values of 

other dependent variables in the system. Independent or exogenous variables may also be 

included in the system equations as explanatory variables. The general mathematical formulation 

of a VAR system/model usually takes the form:3

 

2

Synopsis of the paper presented at the 23rd MMS Information Transfer Meeting (ITM), Kenner LA, 11–13 January 

2005. The views expressed herein are those of the authors. They are not to be taken as the official view of the LSU 

Center for Energy Studies. 

3 See Iledare & Olatubi (2004) for a brief overview of the VAR procedure. 
189 

t t p t p Bxt t y = A y + + A y + + ε − − ..... 1 1 (1) 

Where yt is a vector of k dependent variables, xt is a vector of m independent variables, A1...Ap

and B are matrices of coefficients to be estimated. The term, εt, is a vector of innovations that 

may be contemporaneously correlated with each other but is not correlated with their immediate 

past values and other variables on the right-hand-side. 

Descriptive Data Analysis 

Table 2C.1 presents summary statistics of the data analyzed in the paper. The table shows that oil 

production appears to exhibit far less variability than gas production, and expectedly, real natural 

gas prices appear to show more variability than real oil prices over this period. The table also 

shows that gross employment levels in Louisiana display some relative stability over the study 

period. Nearly all the measures we examined for the E&P sector are significantly dispersed 

around the mean value. Again, using coefficient of variation (COV) for this comparison, we 

found that E&P employment level is highly dispersed with a COV of 27%. The COV for natural 

gas production is also high, just as the COV for natural gas prices reveal the existence of some 

degree of instability over the period. 

Table 2C.1. Summary Statistics of Quarterly Macroeconomic and E&P Data, 1977–2000. 

 Unit Mean Maximum Minimum Std. Dev. COV

Macroeconomic Statistics 

 Unemployment Rate % 8.02 13.38 4.22 2.35 0.29

 Total Employment Thousand 1,741 1,969 1,379 133 0.08

E&P Data Statistics 

 E&P Sector Employment Thousand 62 100 43 17 0.27

 Wellhead Gas Price 1982$/Mcf 3.25 8.56 1.17 1.44 0.44

 Crude Oil Price 1982$/Bbl 31.42 42.05 21.55 4.15 0.13

 State Offshore Liquid Production MMBbl 6.054 8.696 3.285 1.138 0.19

 State Offshore Gas Production Bcf 64.301 129.114 32.300 28.824 0.45

 State Offshore Pet. Production* MMBOE 16.771 30.078 9.521 5.730 0.34

* MMBbl = 6 Bcf, COV= the ratio of the standard deviation to the mean of a random variable. 

The VAR Model Results 

The variance decomposition results reported in Table 2C.2 were derived from estimating the 

system of equations in (1) for employment in combination with each resource type—oil or gas—

one at a time and by using the variance decomposition procedure. The largest source of variation 

in employment is changes in oil price. Real oil price accounts for as much as 44% of the 

observed variation in employment over time. State offshore oil production accounts for no more 

than 2.78% over the same period. The variation in employment that was explained by 
190 

autonomous oil production ranges from 0.70–2.78. In addition, 23.8–34.1% of the observed 

variation in employment is explained by changes in natural gas prices. However, no more than 

10.6% of the observed variation in Louisiana jobs is explained by changes in autonomous natural 

gas production. Further statistical analyses of the results show that the effects of gas prices on 

employment are statistically significant over the period of estimation. 

Table 2C.2. Decomposition of the variance of Louisiana employment. 

Period (Years) Equations/Variables 

1 2 4 6 8 10 

State Offshore Oil System Equations 

Employment 

 Oil Production 0.0088 0.0070 0.0167 0.0239 0.0266 0.0278

 Real Oil Price 0.2800 0.4390 0.4245 0.4183 0.4161 0.4150

State Offshore Gas System Equations 

Employment 

 Gas Production 0.0064 0.0694 0.9500 0.1054 0.1052 0.1058

 Real Gas Price 0.2381 0.3357 0.3317 0.3283 0.3283 0.3281

Economic Interpretations 

Table 2C.3 shows elasticity estimates derived from estimating the system equations in (1) terms 

of the short- and long-run response of Louisiana employment to relative changes in oil and gas 

prices. As expected, long-run elasticity is generally larger than short-run because in the long run 

economic agents have more opportunities to adjust to changes than is possible in the short run 

(See column 3, Table 2C.3). The response of employment to changes in oil and gas prices is 

analogous and significant statistically. The corresponding quantity estimates resulting from a 

percentage change in prices are reported in Table 2C.4. These are restrictive or conditional 

equivalence of a 20 and 18% oil and gas price shocks using the 2002 oil and gas price data, 

respectively. According to the results reported, the number of jobs provided as a result of an oil 

price shock could reach 26,600. The effects of a natural gas price shock on the employment level 

follows a similar pattern of oil price effects. The only difference is the magnitude, which appears 

to indicate that, on the long-term basis, economic activities in the state benefit slightly more from 

a shock in oil price than from a similar shock to gas prices. The opposite appears to hold in the 

periods closer to the shock. For example, the difference would have been as much as 25% more 

jobs created as a result of oil price shock than under the gas price shock scenario in the long run. 

Table 2C.3. Price elasticity of employment *.

Short Run 

(SR) 

Long Run 

(LR) 

Relative Size 

(SR/LR) 

State Offshore Oil System Equation 

 Employment 0.04 0.10 2.5 

State Offshore Gas System Equation 

 Employment 0.05 0.08 1.6 

Note: * Denote non-significance at 95%. 
191 

Table 2C.4. Quantitative estimates of the effects of maximum price ‘shock’ in 2002. 

Short Run 

(SR) 

Long Run 

(LR) 

State Offshore Oil System Equations 

 Employment (Million) 0.0106 0.0266 

State Offshore Gas System Equations 

 Employment (Million) 0.0285 0.0456 

Summary and Conclusions 

This study examines the interrelationships between petroleum price changes and Louisiana 

employment conditional on the dynamics of oil and natural gas production in the state offshore 

waters. The empirical results show that as prices increase (assumed positive shock), more oil and 

natural gas are produced. To produce more oil and gas, more workers are hired. Because such 

price shocks often occur in boom periods in the oil and natural gas industry, competition in the 

labor market forces up the wage rate. In the long run, this shock may lead to a decline or even 

recession in the U.S. economy, which implies a reduced demand for goods and services, 

including oil and gas. The result of such a development is the reverse of the previous scenario—

job losses. 

In an overall sense, the study finds that, at least in the case of Louisiana, oil and gas prices are 

still important in short-term fluctuations in employment. In addition, the results indicate that 

while there are some differences between oil and gas prices, the pattern of effects on the 

economy is similar in many respects. Not withstanding this finding, it is noted that inferences 

from the dynamic paths of adjustment support an assertion of gas prices having a more 

destabilizing effect on the economy in the long run than oil prices. It is also obvious from this 

paper that only a sustained, relatively high positive movement in petroleum prices can have a 

long-lasting impact on Louisiana employment. Finally, an additional significance from the paper 

is that, in the absence of price movements, autonomous changes in production in state offshore 

waters no longer play a prominent role in Louisiana employment growth. 

References 

Brown, S.P.A. and M.K. Yucel. 1995. Energy prices and state economic performance. Economic 

Review, Federal Reserve Bank of Dallas (Second Quarter):13–23. 

Iledare, O.O. and W. Olatubi. 2004. The impact of changes in crude oil prices and offshore oil 

production on the economic performance of U.S. coastal gulf states. The Energy Journal 

25:97–113. 

Scott, L. 2002. The ‘Energy’ Sector: Still a Giant Economic Engine for the Louisiana Economy. 

Louisiana Mid-Continent Oil and Gas Association, Baton Rouge, LA. 
192 

Wumi Iledare is an Associate Professor of petroleum economics and policy research at Louisiana 

State University’s Center for Energy Studies, Baton Rouge, Louisiana. He is also an adjunct 

Professor of petroleum economics at Craft and Hawkins Department of Petroleum Engineering 

and an Associate Graduate Faculty member of the Department of Environmental Studies. Wumi 

holds a Ph.D. in mineral economics from West Virginia University. He is an active member of 

the Society of Petroleum Engineers International (SPEI) and a former council member and 

secretary-treasurer of the United States Association for Energy Economics (USAEE). Wumi 

currently serves as the editor of the USAEE Dialogue, a quarterly newsletter published by the 

USAEE. 

Williams O. Olatubi is an expert in modeling regional economic impacts, particularly those 

associated with natural resource extraction, energy, and agriculture. Dr. Olatubi served as a postdoctoral research fellow and research associate at the Center for Energy Studies, Louisiana State 

University for three years. Dr. Olatubi is currently an Assistant Vice President with the Custom 

Modeling and Risk Analytics Group of Washington Mutual. Dr. Olatubi received his B.S. and 

M.Sc. in agricultural economics from the University of Ibadan, Nigeria, two M.S. degrees 

(environmental studies, economics), and a Ph.D. (resource economics) from the Louisiana State 

University. 
193 

ACCOUNTING FOR CHANGE IN THE GULF OF MEXICO ECONOMY: 

DEVELOPING A COMPARATIVE CONTEXT FOR REGIONAL 

ECONOMIC ANALYSIS AND HISTORY 

Allan Pulsipher, Center for Energy Studies, Louisiana State University 

Objectives 

The objectives of the part of the project reported here are to 

 1. Facilitate analysis of cumulative socioeconomic effects that are relevant to OCS activities 

in the Gulf of Mexico (GOM) by providing an accessible context to disentangle the 

economic and demographic factors associated with economic change in the region; 

 2. Help compare regional with national economic experience as well as compare regional 

forecasts with the economic history of the region. 

Method 

The rate of growth in per capita personal income was allocated among the principal factors 

contributing to it, for each of 19 coastal parishes and 45 non-coastal parishes using the growth 

accounting framework developed and used by analysts at the Bureau of Economic Analysis of 

the U.S. Department of Commerce.1

 The period studied was from 1969 to 2000. It was divided 

into four cyclical phases based on behavior of personal income in Louisiana. The four periods 

roughly coincide with 1) the period of relatively rapid growth in petroleum exploration, 

production and energy price escalation that occurred from 1969 to 1980; 2) the period during 

which world oil prices collapsed, 1981 to 1985; 3) the recovery during 1986–1990, and 4) the 

period of slow but sustained growth from 1991 to 2000. The contribution of each component 

during each of these four periods was computed for each parish using the formula: 

FI

TPI

E

FI

N

J

H

E

J

H

N

TPI = × × × × (1) 

where TPI is total personal income, N is total population, H is hypothetical earnings, J is the 

number of jobs, E is earnings, and FI is factor income (property income plus earnings). In terms 

of percent change, we have the following formula: 

 percent change ( )

 change ( ) percent change ( )

change ( ) change ( ) percent change ( )

FI

TPI

E

FI

N

J

percent

H

E

J

H

percent N

TPI

percent

+

+ +

= +

 (2) 

 

1

 For a review of this literature see Daniel Garnick. Accounting for regional differences in per capita income growth: 

An update and extension. Survey of Current Business 70(1990):29–40. 
194 

• The industry-mix (H/J) component measures the contribution to growth in per capita 

personal income attributable to industries paying higher wages growing faster relative to 

industries paying lower wages in the parish. 

• The relative wage component (E/H) measures the extent to which wages in the parish 

increased or decreased relative to the average wage paid nation wide, with the mix of 

industries kept constant. 

• Labor force participation (J/N) refers to changes in personal income attributable to 

changes in the proportion of the population that participates in the paid labor force. 

• Transfer payments (TPI/FI) include social insurance, public assistance, and various other 

income supplements not dependent upon participation in the labor force. 

• Property income (FI/E) comes from payments to individuals from interest, rent, and 

dividends. 

The overall growth rate was allocated among these five components for each parish. A 

normalized standard deviation or “Z score” was calculated for each contributor in each parish 

based on the distribution of the value among all the parishes in the state. The means for the 

overall growth rate and for each of the five contributors were computed, and means for the group 

of 19 coastal parishes were compared to the corresponding means of the 45 non-coastal parishes 

for each of the four time periods. The results are summarized in Table 2C.5. 

Table 2C.5. Changes in per capita personal income and its components, 1969–2000. 

Period 

Group 

Δ Personal 

Income/ 

Person 

Industry 

Mix 

Relative 

Wage 

Effect 

Lab Force 

Part. 

Transfer 

Payment 

Ratio 

Property 

Income 

Ratio 

1969–80 

Coastal 10.06 6.68 1.28 2.40 0.23 -0.53 

Non-C 9.14 6.43 0.82 0.68 1.91 -0.70 

1981-85 

Coastal 2.38 4.24 -1.96 -2.29 1.93 0.46 

Non-C 4.66 4.41 -0.83 -0.04 0.82 0.30 

1986-90 

Coastal 4.57 3.56 -1.09 2.33 -0.18 -0.05 

Non-C 4.67 3.70 -0.47 1.16 0.19 0.09 

1990-00 

Coastal 3.67 3.36 -1.10 0.91 0.47 0.05 

Non-C 3.69 3.37 -1.12 1.32 0.28 -0.10 

1969-00 

Coastal 6.49 5.24 -0.47 1.03 0.84 -0.16 

Non-C 6.64 5.22 -0.20 0.83 0.98 -0.19 
195 

Discussion of results 

 I. 1969 to1980: Rising petroleum prices and production in coastal Louisiana. 

 a. In retrospect, a period of exceptional improvement in both coastal and non-coastal 

parishes, but despite the near equivalence of their overall growth rates, the 

components of the growth were discernibly different in the two groups. 

 b. About two-thirds of the growth was attributable to an improvement in industry mix, 

i.e., higher wage industries grew relative to lower wage industries, using average 

national wage levels to define high- and low-wage industries. This was true for both 

groups of parishes. 

 c. The contribution of the other major factors differed significantly between the two 

groups: 

i. Keeping the mix of industries constant, wages increased relative to the 

national average in both coastal and non-coastal parishes, but they 

increased in coastal parishes twice as rapidly as in non-coastal parishes. 

The regional wage effect was small relative to industry mix 

improvements, however, contributing 1.28 percentage points or about 13% 

of the total in coastal parishes and 0.82 points or about 9% of the total in 

non-coastal parishes. 

ii. Change in the extent to which the population participated in the labor 

force contributed 2.4 percentage points to the growth rate of personal 

income in the coastal parishes but only 0.7 percentage points in noncoastal parishes. 

iii. Conversely, changes in transfer payments contributed 1.9 percentage 

points to the growth rate in non-coastal parishes but only 0.2 percentage 

points in coastal parishes. 

 d. Thus, increases in relative regional wages, and, especially, increased labor force 

participation increased growth rates in coastal parishes, while transfer payments 

offset much more modest regional wage and labor force participation gains in 

non-coastal parishes. 

 II. 1981 to 1985: Regional repercussions of collapsing oil prices. 

 a. The collapse in world oil prices reduced growth rates in both coastal and noncoastal parishes, but the drop was about twice as deep in the coastal parishes. 

 b. The positive contribution of a better industry mix continued but declined among 

both groups of parishes and by about the same magnitude. 

 c. The contributions of the other factors more or less reversed the relationships 

evident in the previous period of quite rapid growth. 

i. Wages declined relative to the nation in both groups of parishes, but 

declined twice as much in coastal parishes, where only Orleans parish 

experienced a small relative improvement. 

ii. Decreased labor force participation was a major factor holding down 

growth in coastal parishes, making a negative contribution of -2.3 

percentage points relative to an overall rate of only 2.4. The decline in 
196 

non-coastal parishes was very small, only –0.04 compared to an overall 

rate of 4.7. 

iii. Transfer payments constituted a major source of support for personal 

income in the coastal parishes adding 1.9 percentage points to the overall 

growth rate of 2.4. In non-coastal parishes the contribution was about half 

as large. 

 d. Thus, falling relative wages, and decreased labor force participation were 

principal avenues of adjustment to falling world oil prices in coastal parishes, 

their negative effects on income modified significantly by increases in transfer 

payment. In non-coastal parishes both the negative and positive contributors 

were much weaker and the overall growth rate was not quite twice as fast as it 

was in the coastal parishes. 

 III. 1986-1990: Modest recovery in coastal Louisiana 

 a. The recovery from the collapse of world oil prices was apparent only among the 

coastal parishes where the overall growth rate increased by about 90% and 

parity with non-coastal parishes was regained. But both groups of parishes grew 

at significantly slower rates than they had achieved during the boom of the 

1970s. 

 b. Improvements in industry mix maintained their steady course but fell below 

levels exhibited during the bust for both coastal and non-coastal parishes. 

 c. Wages continued a modest decline relative to the rest of the nation in both 

groups of parishes. 

 d. Increased participation in the labor force was the principal evidence of 

continued recovery among the coastal parishes, adding 2.3 percentage points to 

the 4.6 overall growth rate. The contribution in non-coastal parishes was 

positive but only half as large. 

 e. Transfer payments did not make nearly as large a contribution as they did in the 

previous two periods for either group of counties. 

 f. Thus, the recovery from the oil price collapse was moderate at best. Few 

divergences from the pattern evident during the collapse are evident for the noncoastal parishes with the sizable increase in labor force participation being the 

principal avenue of improvement for the coastal parishes. 

 IV. 1991-2000: Sustained but slower growth. 

 a. Almost no analytically or statistically significant differences are apparent 

between the two groups in terms of either the total growth rates or the 

components of the growth. 

 b. The decline in the rates of growth observed in the previous two periods 

continued in the period. 
197 

Implications 

If the contribution from changes in industry mix are regarded as an indicator of longer-term 

economic growth and changes in the contributions from the other components as indicators of 

shorter-term adjustments to the business cycle, then the stability and close equivalence of the 

contribution from improvements in industry mix in both the coastal and non-coastal parishes—

through boom, bust and recovery periods—suggests that offshore oil and gas activities had 

limited if any long-term, cumulative, economic effects on residents of coastal parishes during the 

study period. Further, the persistent decline in regional wages relative to the nation since the 

1970s boom—in both coastal and non-coastal parishes—suggests that offshore oil and gas 

activity does not increase wage costs for other industries in coastal parishes. 

Relationships between income and population growth are discussed elsewhere in the study. 

Allan G. Pulsipher is the Executive Director and Marathon Oil Company Professor of Energy 

Policy in the Center for Energy Studies at Louisiana State University. He has been with the 

Center for Energy Studies since 1990. Prior to coming to LSU, he worked as the Chief 

Economist for the Congressional, Monitored Retrievable Storage Review Commission (1988–

89); the Chief Economist of the Tennessee Valley Authority (1980–88); a Program Officer with 

the Ford Foundation's Division of Resources and the Environment (1977–80); as a Senior Staff 

Economist with the President's Council of Economic Advisers (1973–75); and on the faculties of 

Southern Illinois and Texas A&M Universities. He has a B.A. from the University of Colorado 

and a Ph.D. from Tulane University, both in economics. He currently is working on issues 

created by the changing oil and gas industry, especially those affecting the offshore part of the 

industry. He retains an active interest in policy issues related to the storage and disposal of highlevel nuclear waste and the restructuring of the electricity industry-especially as it affects the 

Tennessee Valley Authority. 
198 

A COLLABORATIVE INVESTIGATION OF BASELINE AND SCENARIO 

INFORMATION FOR ENVIRONMENTAL IMPACT STATEMENTS 

David E. Dismukes, Center for Energy Studies, Louisiana State University 

Introduction 

The Environmental Impact Statement (EIS) process is both data-intensive and dynamic. Over the 

years, the depth and scope of the socioeconomic analyses included in the EIS have changed 

considerably, becoming both more rigorous and more detailed. This is particularly true in the 

examination of economic impacts and industry relationships and ties from the Gulf of Mexico 

(GOM) to its onshore communities. Expectations are that economic impact models will continue 

to become more developed and attempt to reach even greater levels of sector and geographic 

detail. 

However, despite the increase in detail and refinement of many EIS socioeconomic analyses, 

there are still a large number of areas that are 1) not well understood; and/or 2) where detailed 

data and information is exceptionally difficult to obtain. 

An example of the first problem rests with the existing MMS economic impacts models. While 

these models include considerable sectoral detail regarding industry expenditures, there are still 

areas where large percentages of offshore activities are assigned to broad industry categories (or 

sectors) that are intended to represent outsourcing and contracting. Where those dollars go within 

those contracted services category is, at this time, a black box. 

The second problem (difficulty in obtaining detailed data) continues to be a source of frustration 

in attempting to “populate” the detailed models envisioned for EIS purposes. Much of the 

information needed for these models can be irregularly reported, inconsistent in scope, considered proprietary by industry, and in some instances, simply unobtainable. This quickly 

devolves the research project into a “scavenger hunt.” Further, considerably more effort is being 

put into the collection of this data and information than in the actual analysis. 

The goal of the Collaboratives Process is an attempt to use more reasonable methods to answer 

the general question of how offshore activities impact the communities of the GOM. 

Project Approach and Current Activities 

There are a number of options that MMS could consider to collect the baseline and scenario data 

and information needed for EIS purposes. One approach would be to initiate new and rigorous 

reporting requirements under its regulatory authority much like the Department of Energy 

(DOE), Federal Energy Regulatory Commission (FERC), or the Federal Communications 

Commission (FCC). This seems like an unlikely and unreasonable option for MMS. The second 

approach would be to continue the current process of scavenging for information and data and to 

maintain the status quo. Again, this is also an unreasonable conclusion and inefficient process for 

MMS. The third approach, which is the subject of this project, is to develop a more 
199 

“collaborative” process for collecting and examining information associated with the offshore 

industry. 

The collaboratives approach would be less structured and 

• Is more fluid that traditional methods and takes into account the “big picture.” 

• Recognizes that not all trends and scenarios can be quantified explicitly. 

• Is willing to accept some data limitations and rely more on professional and subject 

matter expert judgment. 

• Sets up structure for getting the best professional judgment by collaborating with others 

to get specific answers to specific questions. 

Conclusions 

The Collaboratives Research Project is attempting to collect needed baseline and scenario 

information for MMS in a reasonable and practical manner. The project is moving in two 

concurrent tracks. First, attempting to obtain additional information on the subcontracted and 

outsourced activities that have bedeviled earlier analysis of the industry and its relationships with 

onshore communities. Second, the project is attempting to examine current informational need 

for MMS, and develop a process by which this information can be obtained from various subject 

matter experts. Hopefully, this approach will lead to more practical and efficient ways and 

getting answers to questions needed to be addressed in future EIS. 

David E. Dismukes is the Associate Director and an Associate Professor at the Center for Energy 

Studies, Louisiana State University. His research interests are in the analysis of economic, 

statistical, and public policy issues in energy and regulated industries. He has completed several 

projects for MMS including the original economic impact cost models used in the MMS EIS and 

the deepwater infrastructure factbook and GIS database. 

 
201 

SESSION 1D 

EFFECTS OF OIL AND GAS EXPLORATION & DEVELOPMENT 

AT SELECTED CONTINENTAL SLOPE SITES IN THE 

GULF OF MEXICO, PART I 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: Margaret C. Metcalf, Minerals Management Service 

BACKGROUND AND STUDY DESIGN Alan D. Hart.......................................................... 203 

GEOPHYSICAL CHARACTERIZATION OF STUDY SITES: VK916, MC292, GB602, 

AND GB512 Harry H. Roberts.................................................................................................. 207 

METALS, TOTAL ORGANIC CARBON AND REDOX CONDITIONS IN SEDIMENTS 

John H. Trefry, Robert P. Trocine, Michelle L. McElvaine and Robert D. Rember.................. 213 

SEDIMENT AND TISSUE HYDROCARBON CHEMISTRY Thomas J. McDonald and 

James M. Brooks......................................................................................................................... 218 

SEDIMENT PROFILING IMAGERY Robert Diaz ................................................................. 224 

MACROFAUNAL IMAGE ANALYSIS Robert S. Carney ..................................................... 225 
203 

BACKGROUND AND STUDY DESIGN 

Alan D. Hart, Continental Shelf Associates, Inc. 

In recent years, a remarkable increase in oil and gas exploration, development, and production 

has occurred in the deepwater Gulf of Mexico (GOM) (Cranswick and Regg 1997; Baud et al. 

2000; Richardson et al. 2004). Over the last decade, the number of wells drilled in the deepwater 

Gulf has increased dramatically, with much of the activity in water depths of 450 to 1,500 m 

(Richardson et al. 2004). In early 2004, over one half of the active leases in the GOM were in 

deepwater (Richardson et al. 2004). Contributing factors to this revitalization of exploration and 

development in the GOM include favorable economics, the development of innovative 

technologies, the announcement of large deepwater discoveries, the passage of the Deep Water 

Royalty Relief Act, and the opportunity to lease new prospects. (Ward 2000; Richardson et al. 

2004). 

Deepwater operations are significantly different from conventional operations on the continental 

shelf because they are farther from shore, encounter different environmental conditions, are 

technologically more sophisticated, and may involve much higher production rates. These 

differences present many technical and regulatory challenges (Minerals Management Service 

[MMS] 2000, 2004). This study was conducted to address one challenging aspect of deepwater 

operations: the impacts of drilling activities on the benthic environment around wellsites. The 

objectives of this multi-year study, which was conducted by Continental Shelf Associates, Inc. 

and its subcontractors/consultants, were to assess the physical, chemical, and biological impacts 

of oil and gas development at selected exploration and development wellsites on the GOM 

continental slope. The findings from this study will assist the MMS in conducting environmental 

analyses, as well as developing mitigative measures and regulations specifically tailored to 

deepwater operations. Specific objectives were to document 1) drilling mud and cuttings 

accumulations; 2) physical modification/disturbance of the seabed due to anchors and their 

mooring systems; 3) debris accumulations; 4) physical/chemical modification of sediments; and 

5) effects on benthic organisms. 

Four sites were sampled during the study: 

• Viosca Knoll Block 916 (VK 916) was an exploration site sampled before and after 

drilling of a single exploration well. 

• Garden Banks Block 516 (GB 516) was an exploration/development site that was 

sampled once after exploration drilling and again after several development wells were 

drilled. 

• Garden Banks Block 602 (GB 602) and Mississippi Canyon Block 292 (MC 292) were 

post-development sites sampled once after several exploration and development wells 

had been drilled. 
204 

VK 916 and GB 516 were located in water depths of about 1,000 m. MC 292 and GB 602 were 

located in water depths of about 1,100 m. Both water-based and synthetic-based muds (SBM) 

were used in the drilling of the exploration and post-development wells. 

Geophysical characterizations of the sites were conducted to determine (1) the areal extent and 

accumulation of muds and cuttings; (2) the physical modification or disturbance of the sea bed 

due to impacts from anchors and their mooring systems including chains or wire ropes; and 

(3) the accumulation of debris attributable to oil and gas development activity. Bathymetric, 

side-scan sonar, and subbottom profile data were collected at each site, and these data were used 

to construct broad-scale images of the seafloor, which were interpreted to map possible anchor 

scars and accumulations of cuttings and drilling fluids. To encompass the anchor patterns for 

typical moored drilling units in this water depth, an area within a radius of approximately 3,000 

m was surveyed at each site. Cruise 1A was conducted from 10 November 2000 to 1 January 

2001 using a high-resolution deep-tow system aboard the R/V OCEAN SURVEYOR, a 

geophysical survey vessel. It was originally intended that all of the sites would be sampled 

during Cruise 1A; however, VK 916 was the only site surveyed due to extended weather delays, 

as well as equipment, software, and vessel problems. Cruise 2A was conducted from 24 June to 7 

July 2001 at both post-development sites (GB 602 and MC 292), and a post-drilling survey was 

conducted at GB 516 following the completion of development drilling there. Cruise 2A was 

conducted aboard the M/V RIG SUPPORTER using the C&C Technologies Autonomous 

Underwater Vehicle (AUV), the HUGIN 3000. The post-drilling survey of the VK 916 site, 

Cruise 3A, was conducted from 7 to 12 August 2002, following the completion of exploration 

drilling there. This survey also was conducted aboard the M/V RIG SUPPORTER using the 

HUGIN 3000 AUV. 

To assess physical/chemical modification of sediments and the effects on benthic organisms, 

chemical/biological sampling was conducted at each site. GB 516 and VK 916 were sampled 

during Cruise 1B, which was conducted from 23 October to 17 November 2000. Sampling at 

both post-development sites (GB 602 and MC 292) and at the GB 516 site after the completion 

of development drilling there was conducted during Cruise 2B (8 to 25 July 2001). Cruise 3B 

was a post-drilling survey of the VK 916 site following the completion of exploration drilling 

there and was conducted from 4 to 14 August 2002. 

Each study site was defined as a circle of 500 m radius around the drilling location. This radius 

was selected because concentrations of synthetic based fluids (SBFs) most likely would not be 

detectable beyond 500 m from the discharge point, and SBF concentrations exceeding 1 ppm (an 

apparent threshold for biological effects; Neff et al. 2000) are most likely to occur within 300 m 

of the discharge point. Six circular far-field sites (or “reference areas”) also were designated for 

each study site. The locations of these reference areas were selected to be at 10 to 25 km away 

from the near-field site and at about the same depth as the near-field site. The total area of six 

far-field sites combined was equal to that of the near-field site, and the number of samples was 

allocated so that the sampling intensity was the same between the near-field site and the 

reference areas. 
205 

For the chemical/geological sampling, samples and data were collected with four types of 

equipment: 

• Box core sampler (to obtain samples of sediment, microbiota, meiofauna, and 

macroinfauna). 

• Sediment profile imaging (SPI) camera (to obtain cross-sectional images of the upper 

sediment column). 

• Still camera on a towed/dragged sled (to obtain photographs of the seafloor and 

megafauna). 

• Baited traps (to obtain animals for tissue analyses). 

Box cores were to be collected at 12 randomly selected locations within the 500-m radius at each 

study site and at 12 far-field locations (two locations selected randomly within each of six farfield sites). Camera sled and SPI transects were not randomized, and the transects were 

conducted as drifts across each site based on prevailing currents. The still camera was 

programmed to take photographs at regular five-second intervals. Still photographs of the 

seafloor and megafauna were collected along three transects at each site and along one transect at 

each of three far-field sites. The SPI system was repeatedly lowered to take as many sediment 

profiles as possible during each transect. Sediment profile photographs were to be collected 

along three drift transects in the near-field and along one transect at each of three far-field sites. 

The baited traps were to be deployed at the two post-development sites to collect organisms for 

tissue analyses. For each site, eight traps were deployed in the near-field, and four traps were 

placed at each of two corresponding far-field sites. 

References 

Baud, R.D., R.H. Peterson, C. Doyle, and G.E. Richardson. 2000. Deepwater Gulf of Mexico: 

America’s Emerging Frontier. U.S. Dept. of the Interior, Minerals Management Service, 

Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 2000-022. 89 pp. 

Cranswick, D. and J. Regg. 1997. Deepwater in the Gulf of Mexico: America’s New Frontier. 

U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, 

New Orleans, LA. OCS Study MMS 97-004. 43 pp. 

Minerals Management Service. 2000. Gulf of Mexico Deepwater Operations and Activities: 

Environmental Assessment. U.S. Dept. of the Interior, Minerals Management Service, 

Gulf of Mexico OCS Region, New Orleans, LA. OCS EIS/EA MMS 2000-001. 

Minerals Management Service. 2004. Moving into Deepwater: The Challenges of Development 

in the Gulf of Mexico. MMS Ocean Science 1(2):4–5. March/April 2004. 

Neff, J.M., S. McKelvie, and R.C. Ayers, Jr. 2000. Environmental Impacts of Synthetic Based 

Drilling Fluids. Report prepared for MMS by Robert Ayers & Associates, Inc., August 
206 

2000. U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region, New Orleans, LA. OCS Study MMS 2000-064. 118 pp. 

Richardson, G.E., L.S. French, R.D. Baud, R.H. Peterson, C.D. Roark, T.M. Montgomery, E.G. 

Kazanis, G.M. Conner, and M.P. Gravois. 2004. Deepwater Gulf of Mexico 2004: 

America’s Expanding Frontier. U.S. Dept. of the Interior, Minerals Management Service, 

New Orleans, LA. OCS Report MMS 2004-021. 

Ward, E.G. 2000. Deepwater technology, Chapter 2. In: Continental Shelf Associates, Inc. 

Deepwater Gulf of Mexico Environmental and Socioeconomic Data Search and 

Literature Synthesis: Volume 1, Narrative report. U.S. Dept. of the Interior, Minerals 

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

2000-049. 

Dr. Alan Hart is the Science Director of Continental Shelf Associates, Inc., located in Jupiter, 

Florida. He has 30 years of experience in marine environmental science, including major 

research programs for federal, state, and industrial clients. He has been involved in 

characterization and monitoring studies covering a wide range of human activities in the marine 

environment, including oil and gas operations, dredged material disposal, beach restoration, and 

sewage outfalls. Dr. Hart received his B.S. degree in zoology from Texas Tech University in 

1973 and his Ph.D. Degree in biological oceanography from Texas A&M University in 1981. 
207 

GEOPHYSICAL CHARACTERIZATION OF STUDY SITES: 

VK916, MC292, GB602, AND GB512 

Harry H. Roberts, Coastal Studies Institute, Louisiana State University 

Geologic Framework 

This study focuses on the effects of oil and gas exploration and development at four selected 

sites on the continental slope of the northern Gulf of Mexico (GOM). The study sites are located 

in the world’s most mature deepwater hydrocarbon exploration-production province. The 

continental slope offshore of the northern Gulf states is also perhaps the most geologically 

complex continental slope in today’s oceans. The shaded relief map of Figure1D.1 reflects the 

complexity of the slope’s surface topography, a reflection of an equally complex subsurface 

geology. 

Figure 1D.1. Location map showing major lease areas of the northern Gulf of Mexico continental slope and 

specific sites addressed in this study. 

Our present knowledge base for both the surface and subsurface geology of the northern Gulf’s 

continental slope is largely a product of the search for and production of oil and gas. Since the 

late 1970s when the exploration front moved to the upper continental slope, an enormous data 
208 

base of 3D-seismic, bathymetry, high resolution geohazard-scale acoustic data, and sediment 

core data has been compiled for deep water. These data sets confirm the geologic complexity of 

this province and support the idea that the slope’s geologic configuration derives from the 

interdependency of terrigenous clastic sedimentation and salt tectonics (Humphris 1978). 

Research conducted in the early and mid 1990s emphasizes that variations in sedimentation rate 

affect the growth of salt bodies. Salt deformation in turn exerts a strong control on the locations 

and orientations of intraslope minibasins and associated fault networks (Talbot 1993; Vendeville 

and Jackson 1993; Weimer et al. 1994; Diegel et al. 1995; Rowan 1995; Rowan et al. 1995). 

The northern GOM continental slope covers an area of over 120,000 km2

 and is defined by the 

shelf edge at roughly the 200 m isobath to the upper limit of the continental rise at an 

approximate depth of 2,600 to 2,750 m (Bouma and Roberts 1990). The most complex part of 

the basin’s continental slope occurs opposite east Texas and Louisiana. In this province, regional 

topography is dominated by domes or knolls associated with salt in the shallow subsurface and 

intervening basins, as discussed above and as illustrated by Figure 1D.1. Seafloor slopes 

associated with these regional-scale features range from less than 1o on the dome tops and along 

the basin floors to over 20o on the side of domes and on basin flanks. Observable on this regional 

topography of domes and basins are smaller-scale geologic features that are associated with high 

variability in sediment type and local relief. Near-surface geology and topography of the upper 

continental slope in the northern GOM is highly influenced by cyclic episodes of shelf edge 

progradation and sediment input to deep water. In addition to filling mini-basins and mobilizing 

salt, sediment loading during periods of lowered sea-level activates faults. Faulting creates 

abrupt relief and steep slopes (some near vertical) on the modern ocean floor of the slope. Faults 

function as avenues of transport for fluids and gases to or near the modern seafloor. The process 

of fluid and gas expulsion has an important impact on the present surficial geology of the slope. 

Expulsion of large volumes of fluidized sediment results in the formation of mud volcanoes and 

mud flows (Neurauter and Roberts 1992; Kohl and Roberts 1994). Seepage and venting results in 

the development of highly populated communities of chemosynthetic organisms (Kennicutt et al. 

1985), creation of brine pools and pock marks (McDonald et al. 1990), gas hydrate mound 

formation (Brooks et al. 1985), and precipitation of carbonates and other exotic minerals to form 

hardgrounds, chimneys, and mound-like buildups (Roberts and Aharon 1994). These various 

seafloor responses are all products of vertical flux of hydrocarbon gases, crude oil, and other 

formation fluids migrating to the ocean floor along faults. 

The Mississippi River, which feeds a delta that has nearly prograded to the shelf-edge, makes a 

comparatively small impact on modern slope sedimentation. In response to a lack of siliciclastic 

sediment input during the present highstand of sea-level, a thin hemipelagic sediment unit drapes 

slope topography. These sediments are composed of numerous calcareous pelagic foraminifera 

tests in a matrix of hemipelagic clay. When studied carefully using X-ray radiography, sediments 

of the hemipelagic drape have a massive character, rarely display bedding, are highly 

bioturbated, and frequently show the effects of early diagenesis. 

On the upper continental slope the hemipelagic drape is frequently missing from the tops of 

regional domes and knolls. Sedimentologists with experience in the GOM consider this 
209 

relationship a product of dome top erosion by Loop Current intrusions directly on the slope or 

the impact of Loop Current eddies that transit from east-to-west along the shelf-slope break. The 

Loop Current can impact the seafloor to depths of nearly 1,000 m (Hamilton 1990). Dome tops 

on the upper continental slope within this depth range frequently exhibit seafloor erosion 

exposing older sediments and frequently deformed sediments. Both slumping due to 

oversteepening on salt dome flanks and faulting associated with salt movement frequently cause 

dome flank and dome top sediment deformation. 

In contrast to seafloor covered with a hemipelagic drape deposit, there are vast areas of slope 

impacted by fluid and gas expulsion. These areas appear much more complex, both visually and 

on geophysical records, than the former areas. 

Data Collection Schedule and Instrumentation 

The data collection plan as originally drafted included the acquisition of geophysical data (sidescan sonar, subbottom profiles, and bathymetry) from four sites within the upper continental 

slope province of the northern GOM, Figure 1D.1. As initially planned, these data sets were to be 

collected with a high resolution deep-tow system. Delays associated with weather and 

instrumentation problems mandated a rethinking of the data collection schedule and equipment 

to be focused on the data collection program. Ultimately, one exploration site, Viosca Knoll 

Block 916 (VK 916), was completed with the deep-tow system between November 2000 and 

January 2001 (Cruise 1A) and resurveyed with different instrumentation in May 2002 

(Cruise 3A). The other three sites—Mississippi Canyon 292 (MC 292), Garden Banks 602 

(GB 602), and Garden Banks 516 (GB 516)—were surveyed in June-July 2001 (Cruise 2A). 

Table 1D.1 summarizes the dates of data collection, locations, and types of data collection 

systems used. Figure 1D.1 illustrates the general areas of the continental slope where specific 

sites were surveyed. 

Table 1D.1. Geophysical surveys. 

Cruise Dates Location Survey Timing Equipment*

1A 11–12 Nov. 2000 VK 916 Pre-drilling Deep-Tow 

 29–30 Nov. 2000 VK 916 Pre-drilling Deep-Tow 

 6 Dec. 2000 VK 916 Pre-drilling Deep-Tow 

 9–10 Dec. 2000 VK 916 Pre-drilling Deep-Tow 

 Dec. 30, 2000 VK 916 Pre-drilling Deep-Tow (fathometer only) 

 1 Jan. 2001 VK 916 Pre-drilling Deep-Tow 

2A 25–29 June 2001 MC 292 Post-drilling AUV 

 2–4 July 2001 GB 602 Post-drilling AUV 

 5–7 July 2001 GB 516 Post-drilling AUV 

3A 16–18 May 2002 VK 916 Pre-drilling AUV 

* Deep-Tow (two boats): Edgetech side-scan sonar, Edgetech subbottom profiler, ODOM 

deep-water echotrac (single-beam), and cesium magnetometer. AUV (HUGIN 3000): Edgetech 

side-scan sonar, Edgetech subbottom profiler, and Simrad EM2000 multibeam bathymetry 
210 

The pre-drilling survey at VK 916 (Cruise 1A) was the only one conducted for this project with 

the deep-tow system. The data collection systems in the deep-tow fish included: (a) a dual 

frequency EdgeTech side-scan sonar that operated at center frequencies of 120 kHz and 

420 kHz, (b) an EdgeTech chirp sonar with a frequency bandwidth of 2-10 kHz, and (c) a deepwater precision depth sensor. An electro-hydraulic winch with approximately 6,400 m of cable 

controlled the depth of the fish above the bottom. 

Although the VK 916 site was initially surveyed using a deep-tow system, it was decided that 

data quality would be better and data collection schedules could be met more efficiently for other 

sites using the C&C Technologies Autonomous Underwater Vehicle (AUV), the HUGIN 3000. 

The post-exploration survey of VK 916 (Cruise 3A) also used the AUV (Table 1D.1). 

Results and Conclusions 

Side-scan sonar and chirp sonar subbottom records were useful in mapping deposits of drilling 

mud and cuttings around the wellsites. A combination of a smooth seafloor (little backscatter on 

side-scan sonar records) and a high amplitude response at the seafloor on high resolution 

subbottom profiles was used to identify areas of probable drilling mud deposition. Areas where 

side-scan sonar showed high reflectivity extending in a radial pattern around the wellsites were 

interpreted as cuttings. Cuttings are derived from subsurface sediments that are much more 

compacted and therefore denser than surface hemipelagic sediments that drape most of the 

northern Gulf continental slope. When deposited over hemipelagic sediments, cuttings create an 

acoustic impedance difference that translates into a higher amplitude reflection on subbottom 

profiler records. Although the mapping conservatively identified these areas as cuttings, other 

processes produce high reflectance patterns on side-scan sonar records including seafloor 

disturbances (grooves, furrows, etc.) caused by the process of setting anchors and the dropping 

of sediment clumps to the seafloor from the anchor cables as they are pulled into place. 

Generally, areas mapped as drilling muds were identified within about 100 m of wellsites. Areas 

mapped as cuttings typically extended several hundred meters from wellsites, with the greatest 

extent (about 1 km from the wellsite) observed at GB 602 and GB 516. Anchor scars extended to 

the limit of the surveyed area (about 3 km radius) around the wellsites. 

Persistent cuttings and/or anchor scars from previous activities at nearby wellsites were also 

evident. At VK 916, cuttings and anchor scars were present from two previous wells drilled in 

nearby VK 872 in November to December 1998, about 3.5 years prior to Cruise 3A. At the 

MC 292 site, cuttings deposits and anchor scars were evident around a wellsite in the adjacent 

block MC 291 from drilling between August and October 1997. Within the GB 602 survey area, 

anchor scars and mud/cuttings were evident from three wells drilled between April and August 

1996, about 5 years prior to Cruise 2A. In the GB 516 area, the mapping showed drilling deposits 

around a previous wellsite drilled between September 1995 and July 1996, about 5 years prior to 

Cruise 2A. 
211 

References 

Bouma, A.H. and H.H. Roberts. 1990. Northern Gulf of Mexico continental slope. Geo-Marine 

Letters 10:177–187. 

Brooks, J,M., M.C. Kennicutt II, R.R. Bidigare, and R.A. Fay. 1985. Hydrates, oil seepage, and 

chemosynthetic ecosystems on the Gulf of Mexico slope. EOS, Transactions, American 

Geophysical Union 66:106. 

Diegel, F.A., J.F. Karlo, D.C. Schuster, R.C. Shoup, and P.R. Tauvers. 1995. Cenozoic structural 

evolution and tectono-stratigraphic framework of the northern Gulf Coast continental 

margin. In: Jackson, M.P.A., D.G. Roberts, S. Snelson, eds. Salt Tectonics: A Global 

Perspective. AAPG Memoir 65:109–151. 

Hamilton, P. 1990. Deep currents in the Gulf of Mexico. Journal of Geophysical Research 

20:1087–1104. 

Humphris, Jr., C.C. 1978. Salt movement on the continental slope, northern Gulf of Mexico. In 

Bouma, A.H., G.T. Moore, and J.M. Coleman, eds. Framework, Facies, and Oil-trapping 

Characteristics of the Upper Continental Margin. American Association of Petroleum 

Geologists Studies in Geology 7:69–86. 

Kennicutt II, M.C., J.M. Brooks, R.R. Bidigare, R.A. Fay, T.L. Wade, and T.J. McDonald. 1985. 

Vent-type taxa in a hydrocarbon seep region on the Louisiana slope. Nature 317:351. 

Kohl, B. and H.H. Roberts. 1994. Fossil foraminifera from four active mud volcanoes in the Gulf 

of Mexico. Geo-Marine Letters 14:126–134. 

McDonald, I.R., J.F. Rilly, II, N.L. Guinasso, Jr., J.M. Brooks, R.S. Carney, W.A. Bryant, and 

T.J. Bright. 1990. Chemosynthetic mussels at a brine-filled pockman in the northern Gulf 

of Mexico. Science 248:1096–1099. 

Neurauter, T.W. and H.H. Roberts. 1992. Seismic and visual observation of seepage-related 

structures on the continental slope, northern Gulf of Mexico, Proceedings, Twenty-fourth 

Offshore Technology Conference, Houston, Texas, OTC 6850. Pp. 355–362. 

Roberts, H.H. and P. Aharon. 1994. Hydrocarbon-derived carbonate buildups of the northern 

Gulf of Mexico continental slope: A review of submersible investigations. Geo-Marine 

Letters 14:135–148. 

Rowan, M.G. 1995. Structural styles and evolution of allochthonous salt, central Louisiana outer 

shelf and upper slope. In: Jackson, M.P.A., D.G. Roberts, S. Snelson, eds. Salt Tectonics: 

A Global Perspective. AAPG Memoir 65:199–228. 
212 

Rowan, M.G., P. Weiner, B. McBride, P. Varnai, Z. Acosta, F. Budhijanto, R. Martinez, A. 

Navarro, T. Villamil, and J.C. Fidnk. 1995. Interactions between salt tectonics and 

sedimentation in the Louisiana Offshore: Preliminary results. In Travis C., et al., eds. 

SaH, Sediment, and Hydrocarbons: Gulf Coast Section. Society of Economic 

Paleontologists and Mineralogists Foundation, Sixteenth Annual Research Conference 

Proceedings. Pp. 235–244. 

Talbot, C.J. 1993. Spreading of salt structures in the Gulf of Mexico. Tectonophysics 228:151–

166. 

Vendeville, B.C. and M.P.A. Jackson. 1993. Rates of extension and deposition determine 

whether growth faults or salt diapirs form. In Armentrout, J.M., R. Bloch, H.C. Olson, 

and B.F. Perkins, eds. Rates of Geologic Processes. Gulf Coast Section, Society of 

Economic Paleontologists and Mineralogists Foundation, Fourteenth Annual Research 

Conference Proceedings. Pp. 263–268. 

Weimer, P., P. Varnai, Z.M. Acosta, F.M. Budhijanto, R.E. Martinez, A.F. Navarro, M.G. 

Rowan, B.C. McBride, and T. Villamil. 1994. Sequence stratigraphy of Neogene turbidite 

systems, northern Green Canyon and Ewing Bank, northern Gulf of Mexico. Gulf Coast 

Section Society of Economic Paleontologists and Mineralologists, Fifteenth Annual 

Research Conference Proceedings. Pp. 383–396. 

Harry H. Roberts was for 10 years director of Coastal Studies Institute at LSU, a member of the 

Department of Oceanography and Coastal Sciences, and a Boyd Professor. He has had a career 

in marine geology that spans more than 30 years and has worked in many foreign countries as 

well as in the United States. Recently, he has focused his research on two areas: (a) deltaic 

sedimentation and processes and (b) surficial geology of the northern Gulf’s continental slope. 

The latter research thrust has concentrated on building an understanding of the impacts of fluid 

and gas expulsion on the surficial geology and biology of the slope. Gas hydrates constitute one 

of the unusual consequences of fluid and gas migration and expulsion in deep water. 
213 

METALS, TOTAL ORGANIC CARBON AND REDOX CONDITIONS IN SEDIMENTS 

John H. Trefry, Robert P. Trocine, Michelle L. McElvaine and Robert D. Rember, 

Florida Institute of Technology

Introduction 

As part of an MMS study of the effects of oil and gas exploration and development at selected 

sites on the continental slope in the Gulf of Mexico (GOM), our group at Florida Institute of 

Technology used several chemical parameters to help identify spatial and temporal trends in the 

presence of drilling discharges and in redox conditions in sediments at each site. The supporting 

data set is quite diverse and includes the following: (1) data for 13 metals [aluminum (Al), 

arsenic (As), barium (Ba), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), 

manganese (Mn), nickel (Ni), lead (Pb), vanadium (V) and zinc (Zn)] and total organic carbon 

(TOC) in sediments, (2) data for 11 metals (As, Ba, Cd, Cr, Cu, Fe, Hg, Ni, Pb, V and Zn), in 

Bathynomus giganteus (a large isopod) and Chaceon quinquedens (a crab), (3) sedimentation 

rates, (4) vertical profiles for dissolved oxygen, pH and redox potential (Eh) in sediment, and (5) 

data for selected redox-active chemicals in interstitial water. 

The following four sites at water depths of ~1,000 m were investigated: (1) Site GB 516 (1036 

m) was sampled twice, in both cases after drilling, (2) Site VK 916 (1,006 m) was sampled 

before and after exploratory drilling, (3) Site GB 602 (1,124 m) was sampled once postdevelopment and (4) Site MC 292 (1,118 m) was sampled once post-development (Figure 1D.2). 

Results from site VK 916 provide the best perspective of pre- and post-development conditions. 

 

LOUISIANA

MISSISSIPPI ALABAMA

Gulf of Mexico Gulf of Mexico

0 25 50 75 100 NAUTICAL MILES

Houston

Galveston

Cameron New

Orleans

96o 94o 92o 90o 88o

30o

28o

26o

Corpus

Christi

N TEXAS

2000 m

1000 m

3000 m

2000 m

1000 m

3000 m

GB 602 GB 602 0.04

GB 516 GB 516 0.07

MC 292 MC 292 0.14

Legend: Legend:

= Exploration site = Exploration site

= Post-development site = Post-development site

VK 916 

0.06

VK 916 

0.06

Figure 1D.2. Sampling sites in the Gulf of Mexico with background sedimentation rates in cm yr-1. 
214 

Results and Discussion 

Random samples were collected at multiple locations within 1,000 m of the drilling sites (nearfield) and at >10km from the drilling site (far-field). Samples also were collected at a few 

discretionary stations sited at fixed nearfield locations. 

Sedimentation rates (Figure 1D.2) based on vertical profiles for excess 210Pb were 0.04 to 0.07 

cm yr-1 for sites GB 516, GB 602 and VK 916 and higher at 0.14 cm yr-1 nearer the Mississippi 

River (site MC 292) where the 137Cs profile supported results for excess 210Pb. At near-field (NF) 

locations, maximum levels of Ba in sediment were 35% at GB 516, 17% at VK 916, 15% at GC 

602 and 15% at MC 292, relative to levels of 0.1 to 0.2% at far-field (FF) stations. At site VK 

916, concentrations of Ba in sediments from the NF zone increased by ~30 fold, from an average 

of 0.11% to 3.6%, for pre-exploration and post-exploration samples, respectively (Figure 1D.3). 

At site GB 516, some discharges had occurred prior to the planned pre-exploration sampling. 

Concentrations of Ba in sediments collected during the post-exploration phase averaged double 

those found during the pre-development phase, showing a continued increase in the presence of 

drilling residues. At sites, GB 602 and MC 292, levels of Ba in sediments at NF stations were 

~60 fold and ~12 fold greater, respectively, than at FF stations. Concentrations of syntheticbased mud (SBM) did not correlate well with Ba because of differences in mud mixture, 

behavior after discharge and the occurrence of water-based mud (i.e., Ba and other components, 

but not SBM). 

0.05

0.1

1

10

30Ba (%)

N F FF NF FF

VK916 (1B) VK916 (3B)

0.087 0.098

3.32

0.108

Pre-Exploration Post-Exploration

0.1

1

10

30

Ba (%)

NF FF NF FF

GB 516 (1B) GB 516 (2B)

Pre-Exploration Post-Exploration

0.128 0.148

2.45

5.90

0.05

0.1

1

10

30

Ba (%)

NF FF NF FF

GB 602 (2B) MC 292 (2B)

0.085 0.076

0.90

5.08

Figure 1D.3. Concentrations of Ba (markers show means and lines show standard deviations) in sediments at 

nearfield (NF) and farfield (FF) stations for pre-exploration and/or post-exploration surveys at 

sites VK 916, GB 516, GB 602 and MC 292 (notation in parentheses after site identifies cruise 

when sampling occurred). In some cases, the standard deviation is smaller than the marker. 
215 

Mean concentrations of Hg, Pb, As, Cd and other metals in sediments were not statistically 

different at NF versus FF stations at site VK 916 for pre-drilling and post-drilling expeditions. 

Overall, metal concentrations (excluding Ba) in the 132 NF sediments, from all four sites, were 

within the range of values observed for FF stations in 85 to 100% of the samples, depending on 

the metal considered. Several instances of elevated levels of Hg (n = 10 at > 0.15 μg/g) and Pb (n 

= 17 at >40 μg/g) were observed, primarily from one discretionary station (DS) at site GB 516. 

Concentrations of metals in tissues from isopods (Bathynomus giganteus) and crabs (Chaceon 

quinquedens) showed large standard deviations and no significant differences between NF and 

FF samples. Concentrations of total Hg in isopods ranged from 0.6 to 15.7 μg/g (dry weight) 

with an average of 4.2 ± 3.9 μg/g (n = 22 from NF + FF). 

Vertical profiles for dissolved oxygen in the sediment were generated at 1-mm intervals and pH 

and Eh were measured at 2-cm intervals. In general, concentrations of dissolved oxygen 

decreased to zero at shallower depths in sediment from NF sites following drilling than at FF 

stations. The redox potential also tended to be lower (less oxidizing, more reducing) at NF sites 

during post development sampling. For example, at site GB 516, dissolved oxygen could be 

detected to a depth of ~3.5 cm in FF sediment relative to <0.5 cm in NF sediment (Figure 1D.4). 

In addition, Eh levels at the FF site showed oxidizing conditions (400 mV) relative to anoxic, 

highly reducing conditions (-150 mV) at some NF stations (Figure 1D.4). 

(a) 

GB516 FF6-B01

0 50 100 150 200 250

Oxygen (μM)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Sediment Depth (cm)

6789

pH

-200 100 400 700

Eh (mV)

0

5

10

15

20

25

30

Sediment Depth (cm)

pH

Eh

Far Field (background) Far Field (background)

(b) 

GB516 NF-B02

0 50 100 150 200 250

Oxygen (μM)

0.0

0.5

1.0

1.5

2.0

2.5

Sediment Depth (cm)

6789

pH

-200 100 400 700

Eh (mV)

0

5

10

15

20

25

30

Sediment Depth (cm)

pH

Eh

Near Field (drilling discharge impact) Near Field (drilling discharge impact)

Figure 1D.4. Vertical profiles for dissolved oxygen, pH and redox potential (Eh) for (a) farfield (FF) and (b) 

nearfield (NF) sediments at site GB 516 where drilling discharges had occurred. Scales on 

oxygen profiles (4.0 and 2.5 cm) are much smaller than on the Eh profiles (30 cm). 

To simplify comparisons among sites, the amount of dissolved oxygen in the sediment column 

was integrated as nmoles cm-2. This integrated amount of dissolved oxygen in the sediment was 

lower at NF stations following development. For example, at site VK 916, the mean, integrated 

amount of oxygen in the sediment column during the pre-development sampling was statistically 
216 

the same at FF and NF stations (Figure 1D.5). Following development, the mean value remained 

essentially the same at the FF stations and decreased by ~2 fold at NF stations and ~8 fold in 

sediments at discretionary stations (Figure 1D.5). 

NF MF FF NF MF FF

0

30

60

90

120

150

Integrated O2 (nmol/cm2

)

VK 916

Pre-Exploration

86

44

11

84

Post-Exploration

NF FF DISC NF FF

86 90

0

1

2

3

TOC (%)

NF FF N F FF

VK 916 (1B) VK 916 (3B)

1.44 1.54

1.99

1.54

Pre-Exploration Pos t-Exploration

Figure 1D.5. Means and standard deviations for integrated amounts of dissolved oxygen and levels of total 

organic carbon (TOC) in sediments from site VK 916 for nearfield (NF), discretionary (DS) and 

farfield (FF) stations during pre- (cruise 1B) and post-development (cruise 3B) sampling. 

At site GB 516, the amounts of integrated oxygen were ~10 fold and 7 fold lower at DS and NF 

stations, respectively, relative to FF stations during the post-exploration phase. During the predevelopment sampling, when some discharge had occurred, only 20% lower values were 

observed at NF versus FF stations. The observed shift during post-development was directly 

related to increased amounts of drilling discharges. 

Rapid deposition of several centimeters of more organic-rich material from drilling discharges at 

some stations in the NF zone led to an increased rate of bacterial activity with resulting depletion 

of dissolved oxygen. For example, concentrations of TOC in NF surface sediments at site VK 

916 during the post-exploration cruise averaged about one-third greater than found in FF samples 

or NF samples from the pre-exploration cruise (Figure 1D.5). The maximum value for TOC in 

FF or NF samples at site VK 916 from the pre-development cruise was 1.9%. Four NF samples 

and the three DISC samples collected during the post-development cruise at site VK 916 

contained >2% TOC with a maximum level of 3.45%. Each of the seven samples with >2% TOC 

contained >3% Ba. 

 

The thicknesses of layers containing drilling discharges observed during the post-exploration 

cruise at site VK 916, based on concentrations of Ba and TOC, were ~4 cm in each of the three 

DS cores collected. This rapidly deposited, thin layer of material promoted depletion of 

dissolved oxygen in the sediments and a distinct decrease in redox potential as previously 

described. The apparent impact on the chemical composition of the interstitial water seemed 

limited to the top few centimeters of the core and was most obvious for concentrations of 

dissolved ammonia and Mn2+. Concentrations of dissolved ammonia were below detection limits 
217 

(<1 μM) in the top of the core from station FF 3 at site VK 916, increasing to ~50 μM at 25 cm. 

Dissolved ammonia levels of 16 to 40 μM were found in the top 4 cm of the core from station 

DS 2 at site VK 916, with maximum levels downcore of 70 μM. A somewhat similar comparison 

was observed for Mn2+ at site VK 916 with low Mn2+ levels of 10 μM at the top of the core from 

station FF 3 relative to 200 to 500 μM at station DS 2. No sulfate reduction was discernible in 

either core; and, the vertical profiles for Fe2+ were similar in both cores. Overall, the shift in 

redox state was readily discernible, yet limited to the top few cm of the sediment column. 

John H. Trefry is a Professor of Chemical Oceanography at Florida Institute of Technology 

where he has been on the faculty for 26 years. He earned his Ph.D. at Texas A&M University. 

John’s areas of research include trace element geochemistry and pollution, material fluxes to the 

oceans via rivers, and the geochemistry of hydrothermal solutions and deposits at mid-ocean 

ridges. He is presently active in studying the environmental aspects of offshore oil activities in 

the Alaskan Arctic and the Gulf of Mexico. 

Robert P. Trocine is a Senior Research Associate at Florida Institute of Technology where he has 

specialized in trace metal analysis for 25 years. He earned B.S. and M.S. degrees in cell and 

molecular biology from Florida Institute of Technology. His research interests include 

development of new techniques for the analysis of trace metals in water and suspended particles 

at extremely low levels. 

Michelle L. McElvaine is a recent graduate of Florida Institute of Technology with an M.S. 

degree in chemical oceanography. She received a B.S. degree from Bradley University in Peoria, 

Illinois. Michelle has extensive experience with the collection and analysis of sediment 

interstitial water and the used of probes for MMS study. 

Robert D. Rember is a Research Scientist at Florida Institute of Technology where he received 

his Ph.D. in chemical oceanography. He received a B.S. in chemistry at Mount Allison 

University in New Brunswick, Canada. His research interests include chemical weathering and 

transport of dissolved and particulate metals by rivers. 
218 

SEDIMENT AND TISSUE HYDROCARBON CHEMISTRY 

Thomas J. McDonald and James M. Brooks, TDI-Brooks International 

Introduction 

During three cruises, sediments were collected for hydrocarbon analysis from four deepwater 

sites in the northern Gulf of Mexico (GOM): 

• Viosca Knoll Block 916 (VK 916) – exploration site 

• Garden Banks Block 516 (GB 516) – exploration/development site 

• Garden Banks Block 602 (GB 602) – post-development site 

• Mississippi Canyon Block 292 (MC 292) – post-development site 

Cruise 1B (October/November 2000) was the pre-drilling survey for GB 516 and VK 916. 

Cruise 2B (July 2001) was the post-drilling survey for GB 516 and the two post-development 

sites (GB 602 and MC 292). Cruise 3B (August 2002) was the post-drilling survey at VK 916. 

Sediment samples were collected at 12 near-field stations and 12 far-field stations at each site. In 

addition to these routinely collected sediments, three discretionary box-core samples were 

located in drilling mud and cuttings depositional areas mapped during geophysical surveys. All 

of the sediment samples were analyzed for the presence of polycyclic aromatic hydrocarbons 

(PAH) by gas chromatography-mass spectrometry (GC/MS) and synthetic based mud (SBM) by 

gas chromatography-flame ionization detection. 

Two species of deep-water organisms, the isopod Bathynomous giganteus and the crab Geryon 

quinquedens, were collected during the July 2001 (Cruise 2B) using traps located at both the near 

field and far field locations at two of the well locations (GB 602 and MC 292). Both species 

were analyzed for the presence of polycyclic aromatic hydrocarbons. 

Polycyclic aromatic hydrocarbons are widely used as an indicator of petroleum input in 

environmental samples. PAHs containing condensed rings and simple alkylations (naphthalenes, 

fluorenes, phenanthrenes, dibenzothiophenes, fluoranthenes, and chyrsenes, etc.) are generally 

the analytes of interest. PAHs are ubiquitous in the marine environments and can have multiple 

sources such as petroleum, early diagenesis, coals, combustion, immature/mature sediments, and 

anthropogenic inputs. 

Synthetic hydrocarbons used in SBMs include linear-α-olefins, poly-α-olefins, and internal 

olefins. They resemble petroleum alkanes except that they contain one or more carbon-carbon 

double bonds. 
219 

Results – Sediments 

Viosca Knoll Block 916 – Exploration Site 

Sediments from the near-field and far-field stations at the VK 916 location were sampled during 

Cruise 1B (October/November 2000) and Cruise 3B (August 2002). In addition to the box cores 

collected at the near-field and far-field locations, three discretionary box cores were located in 

suspected SBM depositional areas during Cruise 3B. These box cores were sampled in 2-cm 

intervals from 0-cm to 10-cm. 

The SBM concentration in the Cruise 1B near-field sediments ranged from 2.4 to 6.6 μg/dry g 

and the far-field sediments ranged from 4.3 to 7.2 μg/dry g. The SBM concentration in the 

Cruise 3B near-field sediments ranged from 7.5 to 47,920 μg /dry g and the far-field sediments 

ranged from 2.2 to 111 μg/dry g. The total PAH concentration in the Cruise 1B near-field 

sediments ranged from 159 to 294 ng/dry g and the far-field sediments ranged from 175 to 

388 ng/dry g. The total PAH concentration in the Cruise 3B near-field sediments ranged from 

244 to 275 ng/dry g and the far-field sediments ranged from 181 to 399 ng/dry g. Four of the 

Cruise 3B near-field locations could not be analyzed for PAH due to the high concentrations of 

SBM in the sediments. 

Using the Tukey’s HSD test, there was no significant difference among the sediment SBM 

concentrations at Cruise 1B near-field stations, Cruise 1B far-field stations, and the Cruise 3B 

far-field stations. However, a significant difference was detected between the sediment SBM 

concentrations in Cruises 1B and 3B near-field stations (the post-drilling concentrations were 

higher). There was no significant difference among the sediment PAH concentrations at the nearfield stations and far-field stations during both cruises. 

Sediment SBM concentrations in the three discretionary box-core samples all displayed high 

concentrations (>10,000 μg/dry g) in the 0-2 cm section. The SBM concentration decreased with 

depth in all three box cores. The sediment PAH concentrations in discretionary box-cores 

generally decreased with depth but all of the 0-2 cm sections could not be analyzed due to the 

high SBM concentrations. 

Garden Banks Block 516 – Exploration/Development Site 

Sediments from the near-field and far-field stations at the GB 516 location were sampled during 

Cruise 1B (October/November 2000) and Cruise 2B (July 2001). In addition to the box cores 

collected at both the near-field and far-field locations, three discretionary box cores were located 

in suspected SBM depositional areas during Cruise 2B. These box cores were sampled in 2-cm 

intervals from 0-cm to 10-cm. 

The SBM concentration in the Cruise 1B near-field sediments ranged from 5.4 to 

25,131 μg/dry g and the far-field sediments ranged from 2.0 to 9.4 μg/dry g. The SBM 

concentration in the Cruise 2B near-field sediments ranged from 7.0 to 29,167 μg/dry g and the 

far-field sediments ranged from 3.0 to 7.0 μg/dry g. The total PAH concentration in the 

Cruise 1B near-field sediments ranged from 194 to 3470 ng/dry g and the far-field sediments 
220 

ranged from 115 to 444 ng/dry g. The total PAH concentration in the Cruise 2B near-field 

sediments ranged from 142 to 431 ng/dry g and the far-field sediments ranged from 152 to 

250 ng/dry g. 

Using the Tukey’s HSD test a significant difference was detected between the sediment SBM 

concentrations at near-field and far-field stations during both cruises. Near-field concentrations 

were higher than far-field concentrations on both cruises. There was no significant difference 

between the sediment PAH concentrations at the near-field and far-field stations during both 

cruises. 

Sediment SBM concentrations in the three discretionary box-core samples all displayed high 

concentrations (>5,000 μg/dry g) in the 0-2 cm section. The SBM concentration generally 

decreased with depth in all three box cores although two of the discretionary box cores had 

significant (>1,000 μg/g dry) SBM concentration even 10-cm. The sediment PAH concentrations 

in discretionary box-cores generally decreased with increasing depth. The sediment PAH 

concentrations in DC-B2 had elevated levels ranging from 23,840 ng/dry g at 0-2 cm to 

1,667 ng/dry g at 8-10 cm. The naphthalenes, biphenyl, and acenaphthene dominated the total 

PAH in these samples. The source of these PAHs is suggested to be from some other 

contaminant from the drilling activity as SBM does not contain PAHs. 

Garden Banks Block 602 

Sediments from the near-field and far-field sampling stations at the GB 602 location were 

sampled during Cruise 2B (July 2001). In addition to the box cores collected at both the 

near-field and far-field locations, three discretionary box cores were located in suspected SBM 

depositional areas. These box cores were sampled in 2-cm intervals from 0-cm to 10-cm 

The SBM concentration in the Cruise 2B near-field sediments ranged from 462 to 

13,792 μg/dry g and the far-field sediments ranged from 3.0 to 10.0 μg/dry g. The total PAH 

concentration in the Cruise 2B near-field sediments ranged from 132 to 552 ng/dry g and the 

far-field sediments ranged from 93.8 to 143 ng/dry g. 

Using the Tukey’s HSD test, a significant difference was detected between the sediment SBM 

concentrations in the Cruise 2B near-field and far-field stations (near-field concentrations were 

higher). There was no significant difference between the sediment PAH concentrations in the 

Cruise 2B near-field and far-field stations. 

Sediment SBM concentrations in the three discretionary box-core samples all displayed high 

concentrations (>900 μg/dry g) in the 0-2 cm section. The SBM concentration generally 

decreased with depth in all three box cores. The sediment PAH concentrations in discretionary 

box cores generally decreased with increasing depth. 
221 

Mississippi Canyon Block 292 

Sediments from the near-field and far-field sampling stations at the MC 292 location were 

sampled during Cruise 2B (July 2001). In addition to the box cores collected at both the 

near-field and far-field locations, three discretionary box cores were located in suspected SBM 

depositional areas during Cruise 2B. These box cores were sampled in 2-cm intervals from 0-cm 

to 10-cm. 

The SBM concentration in the Cruise 2B near-field sediments ranged from <1.4 to 

2,408 μg/dry g and the far-field sediments ranged from <1.4 to 19.0 μg/dry g. The total PAH 

concentration in the Cruise 2B near-field sediments ranged from 174 to 743 ng/dry g and the 

far-field sediments ranged from 210 to 745 ng/dry g. 

Using the Tukey’s HSD test a significant difference was detected between the sediment SBM 

concentrations in Cruise 2B near-field and far-field stations. No significant difference was 

detected between the sediment PAH concentrations in Cruise 2B near-field and far-field 

locations. 

Sediment SBM concentrations in the two of three discretionary box-core samples displayed 

elevated concentrations (>600 μg/dry g) in the 0-2 cm section. The first discretionary box-core 

samples displayed concentrations slightly above background (>50 μg/dry g) in the 0-2 cm 

section The SBM concentration generally decreased with depth in all three box cores. The 

sediment PAH concentrations in discretionary box-cores generally decreased with increasing 

depth. 

Results – Tissue Samples 

Two species of deep-water organisms, the isopod Bathynomous giganteus and the crab Geryon 

quinquedens, were collected during the July 2001 (Cruise 2B) using traps located at both the near 

field and far field locations at two of the well locations (GB 602 and MC 292). Three organisms 

from each of the sampling locations were selected at random. The internal organs were removed, 

combined, and homogenized into one sample. Both species were analyzed for the presence of 

polycyclic aromatic hydrocarbons. 

PAH body burden concentrations ranged from 38.6 to 416 ng/g dry. Using the student t-test no 

significant difference was found between the total PAH body burden concentrations in the two 

deepwater organisms (α= 0 .05). No significant difference was also found between the total PAH 

body burden concentrations at near-field and far-field stations (α= 0 .05). 

Discussion 

The lateral distribution and concentrations of SBMs in the deep-sea sediments during this study 

were the direct result of drilling activities. The lateral distribution and concentration of the SBMs 

in the sediments was extremely heterogeneous. This patchy distribution of SBMs in marine 

sediments has been reported in other studies (McIlroy 1998; Terrens et al. 1998; Gallaway et al. 

1997; Fechhelm et al. 1999). It has been suggested that the cuttings discharge depth, rate and 
222 

total mass of discharge, currents, and storm currents are the main determinants of the dimension 

of the cuttings piles near offshore platforms (Neff et al. 2000). 

 

One way to assess the significance of the PAH contaminant load in sediments is to compare the 

concentrations measured in the near-field and far-field locations with previous MMS studies and 

the National Oceanic and Atmospheric Administration (NOAA) Status and Trends Mussel 

Watch Program (Brooks et al. 1989). The sediment PAH values detected at the four deepwater 

sites are similar to the concentrations that were detected in the sediments collected during the 

GOOMEX Study (Kennicutt et al. 1996) and an American Petroleum Institute study (Brooks et. 

al. 1989). The concentration ranges of the detected PAHs in the near-field and far-field locations 

were similar, suggesting that the concentrations of PAHs in the sediments was not significantly 

increased due to drilling. However, there was a significant increase in the concentration of PAHs 

in the second discretionary box core from GB 516 during Cruise 2B. Also, some samples from 

VK 916 near-field locations on Cruise 3B could not be analyzed for PAH due to the high 

concentrations of SBM in the sediments. 

The total PAH body burden concentrations in the two test species of deep-water organisms, the 

isopod Bathynomous giganteus (152 ng/dry g ± 109 ng/dry g) and the crab Geryon quinquedens

(110 ng/dry g ± 45.5 ng/dry g) collected during Cruise 2B from the near-field and far-field sites 

in GB 602 and MC 292 were similar in concentration to other benthic samples collected during 

the GOOMEX Study (Kennicutt et al. 1996). Even though the concentrations of the majority of 

the individual PAH analytes were at or below the MDL, the presence of contaminants in the 

internal organs does represent exposure to mature hydrocarbons. The PAH contaminants 

detected in the internal organs of these two species is probably due to their intimate relationship 

with the sediments. 

References 

Brooks, J.M., M.C. Kennicutt II, T.L. Wade, A.D. Hart, G.J. Denoux, and T.J. McDonald. 1989. 

Hydrocarbon distributions around a shallow water multiwell platform. Environmental 

Science and Technology 24(7):1079–1085. 

Fechhelm, R.G., B.J. Galaxy, and J.M. Farmer. 1999. Deepwater sampling at a synthetic drilling 

mud discharge site on the outer continental shelf, northern Gulf of Mexico. In: 1999 

SPE/EPA Exploration and Production Environmental Conference. SPE 52744. Austin, 

TX 28 February–3 March. Society of Petroleum Engineers. Richardson, TX. Pp. 509–

513. 

Gallaway, B.J., R.G. Fechhelm, G.F. Hubbard, and S.A. MacLean. 1997. Opportunistic sampling 

at a synthetic drilling fluid discharge site on the continental slope of the northern Gulf of 

Mexico: The Pompano development. Report by LGL Ecological Research Associates, 

Inc. for BP Exploration, Inc., Houston, TX. 

Kennicutt II, M.C., R.H. Green, P. Montagna, and P.F. Roscigno. 1996. Gulf of Mexico Offshore 

Operations Monitoring Experiment (GOOMEX), Phase I: Sublethal responses to 
223 

contaminant exposure—Introduction and overview. Canadian Journal of Fisheries and 

Aquatic Science 53:2540–2553. 

McIlroy, W. 1998. Review of BHP’s experience into the persistence of drilling fluid pollutants. 

In: International Workshop on Drilling Fluids Exotoxicology and Biodegradation. Curtin 

University, Perth, Western Australia, 8–9 October. Pp. 121–134. 

Neff, J.M., S. McKelvie, and R.C. Ayers, Jr. 2000. Environmental impacts of synthetic based 

drilling fluids. Report prepared for MMS by Robert Ayers & Associates, Inc., August 

2000. U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region, New Orleans, LA. OCS Study MMS 2000-064. 118 pp. 

Terrens, G.W., D. Gwyther, M.J. Keough and R.D. Tait. 1998. Environmental assessment of 

synthetic based drilling mud discharges to Bass Strait, Australia. In: 1998 SPE 

International Conference on Health, Safety, and Environment in Oil and Gas Exploration 

and Development. Caracas, Venezuela, 7–10 June. SPE 46622. Society of Petroleum 

Engineers, Inc. Richardson, TX. Pp. 1–14. 

Dr. Thomas J. McDonald received his Ph.D. in oceanography from Texas A&M University in 

1988. His main are of interest is in hydrocarbon chemistry and is currently a Senior Project 

Manager at TDI-BI. 

Dr. James M. Brooks is President of TDI-Brooks and a Director of B&B Labs. Dr. Brooks has 

been a Project Director on numerous federal projects for NOAA, EPA, ONR, MMS, NSF, 

USFWS, and other agencies, he has extensive experience in the management of large 

environmental and oceanographic projects as well as the technical competency in these areas. He 

has academic credentials consisting of 200 peer-review publications and chairman of 19 M.S. 

and Ph.D. committees. He is a member of the Graduate Faculty at Texas A&M University in the 

Faculty of Toxicology. This academic position is strictly to support graduate student research 

and pursue research-oriented projects. 
224 

SEDIMENT PROFILING IMAGERY 

Robert Diaz, Virginia Institute of Marine Science 

Sediment profile cameras were used to characterize bottom sediments for physical and biogenic 

features. At Garden Banks 516, areas of poor habitat quality were observed in vicinity of 

platforms on both cruises. Extensive areas of thin RPD layer associated with azoic conditions, 

microbial mats and sulphidic deposits, indicative of hypoxia, were present at Nearfield stations. 

Mats not observed in post-drilling survey; however, transects were not the same. Overall, there 

was little or no bioturbating macrofauna present. By contrast, Farfield stations had better habitat 

quality than Nearfield stations. At Viosca Knoll 916, RPD depths were about 1.0 cm with no 

azoic conditions observed. 

Stage I-III Successional stage fauna dominated Nearfield and Farfield stations. Both Nearfield 

and Farfield stations had high benthic habitat quality. At the post-development Garden Banks 

602 site nearly all Nearfield stations appeared to be impacted by oil and gas development 

activities. Multiple layers of darker gray sediments were present and likely associated with 

drilling muds and cuttings. Farfield stations were reddish-brown over light grayish clayey 

sediment and appeared to represent ambient sediment conditions. 

Based on RPD layer depth, bottom-water dissolved oxygen may have been low at some 

Nearfield and Farfield stations. Neither Nearfield or Farfield stations appeared to have well 

developed bioturbating macrofauna communities. At the post-development Mississippi Canyon 

292 site, 82% of Nearfield stations had reddish-brown surficial sediments overlaying light 

grayish clayey sediments with 18% of Nearfield stations having darker gray layers that might 

contain drilling muds and cuttings. All Farfield stations were reddish-brown over light grayish 

clayey sediment and appeared to be ambient sediments. Based on RPD layer depth, bottom-water 

dissolved oxygen may have been low at some silty-clay Nearfield stations, Neither Nearfield or 

Farfield stations appeared to have well developed bioturbating macrofauna communities. 

Possible causes for the degraded benthic habitats at these four sites were sediment disturbance 

from oil/gas activities, sedimentation from oil/gas activities, “Ponded” hypersaline water, 

ebullition of natural gas or oil seeps, historical discharge from past drilling events, and low 

dissolved oxygen events. 

Dr. Robert Diaz is a Professor at the Virginia Institute of Marine Science. Dr. Diaz’s research 

interests focus on understanding organism-habitat interactions and trophic dynamics within 

ecosystems from estuaries to the deep-sea. Recently he has focused on organism-habitat 

interaction on the inner continental shelf to predict how sand dredging will affect fish and 

invertebrate communities. He also developed methods for mapping benthic habitat that would be 

useful for quantifying essential fish habitat and assessing potential impacts from disturbance. 
225 

MACROFAUNAL IMAGE ANALYSIS 

Robert S. Carney, Louisiana State University 

Bottom images were taken during 37 deployments of a towed camera sled at a series of nearfield 

and farfield sites on the upper slope of the Gulf of Mexico (GOM) at Vioska Knoll 916, Garden 

Banks 516, Garden Banks 602, and Mississippi Canyon 292. A total of 16,770 images were 

subjected to a three-aspect content analysis: fauna, color, and texture in an effort to increase the 

information yield from the images. Only 1,147 images contained fauna; sessile cnidarians were 

most abundant, followed by shrimp, ophiuroids, fish, crabs, and gastropods. The low counts were 

due to the small area of the seafloor imaged, 0.22 m2

. These close-up images did not reveal 

smaller fauna. Only two statistically significant faunal results emerged. Fish were more abundant 

in the nearfield images and ophiuroids in the farfield. These results may reflect actual abundance 

or behavior differences. Color analysis found a very consistent relationship between surficial 

sediment hue and proximity to activity. Sediments in drilled areas were gray to black and often 

supported bacterial mats. Subjectively, there were textural differences between sites and within 

tows, but simple statistical evaluation of texture did not capture that variation. In the future, 

similar content analysis of high-resolution digital images should replace more cumbersome filmbased surveys. 

Dr. Robert Carney is a biological oceanographer in the Coastal Ecology Institute and Department 

of Oceanography and Coastal Sciences at Louisiana State University. He works broadly in 

benthic ecology with special emphasis on deep margin systems, cold seeps, and oil & gas related 

environmental issues. He has participated in numerous research cruises in the Atlantic, Pacific, 

and Gulf of Mexico, beginning in 1967. He began deep submersible research in 1975. He 

received a B.S. in zoology from Duke (1967), an M.S. in oceanography from Texas A&M (1971) 

following military service, and a Ph.D. in oceanography from Oregon State (76). Professionally, 

he has been a Smithsonian Fellow, director of Biological Oceanography at NSF, director of 

Coastal Ecology at LSU, and director of the joint MMS/LSU program, Coastal Marine Institute. 

He has participated in several MMS projects in the Gulf, off California, and in Panama. Most 

recently, he has been appointed U.S. coordinator for CoMargE, an international effort in 

Continental Margin Ecology. 
227 

SESSION 1E 

DEEPWATER TECHNOLOGY 

Chair: Mike Conner, Minerals Management Service 

Co-Chair: Elizabeth Komiskey, Minerals Management Service 

OVERVIEW OF DEEPWATER TRENDS IN THE GULF OF MEXICO Richie D. Baud 

and Ronald C. Bowser ................................................................................................................ 229 

ADVANCES IN SUBSEA PROCESSING Larry D. Forster.................................................... 231 

SUBSEA HIGH INTEGRITY PRESSURE PROTECTION SYSTEMS (HIPPS) 

Christopher Lindsey-Curran ....................................................................................................... 234 

SCRs IN HPHT APPLICATIONS Thanos Moros .................................................................... 237 

TECHNICAL ASSESSMENT OF OPTIONS FOR HANDLING ASSOCIATED GAS 

FROM DEEPWATER FPSO DEVELOPMENTS IN THE GULF OF MEXICO 

E.G. Ward, A.J. Wolford, M.B. Mick, L. Tapia, W. Hauser, and A.J. Verret............................ 241 

UPDATE ON U.S. COAST GUARD ACTIVITIES LCDR Jeff Ramos.................................. 246 
229 

OVERVIEW OF DEEPWATER TRENDS IN THE GULF OF MEXICO 

Richie D. Baud and Ronald C. Bowser, Minerals Management Service 

Deepwater hydrocarbon exploration and development in the Gulf of Mexico (GOM) have grown 

immensely over the past decade and continue to show great promise. Most of the active GOM 

leases are in water depths greater than or equal to 1,000 ft, and over half of these deepwater 

leases are in water depths greater than 5,000 ft. 

Since the first deepwater well was drilled in 1975, there has been a steady progression of drilling 

into deeper and deeper waters. As wells are drilled in deeper waters, discoveries and 

development projects progress outward into the GOM, expanding the infrastructure with each 

new deepwater facility. This expanding infrastructure creates opportunities to develop marginal 

deepwater fields that would not have been economically feasible just a few years ago. 

The average deepwater oil well completion produces at about 20 times the rate of a shallowwater well, and the average deepwater gas well completion produces at about eight times the rate 

of its shallow-water counterpart. The GOM now accounts for about 30% of the nation’s domestic 

oil production and 25% of the nation’s gas production. Deepwater oil and gas production 

continue to increase, making the deepwater GOM the crown jewel in the nation’s domestic 

energy portfolio. 

Numerous deepwater projects come online each year, and several massive projects, such as Mad 

Dog, Atlantis, and Thunder Horse, are coming online soon. As a result of these and other new 

projects, deepwater GOM oil production is expected to rise to record levels within the next few 

years. Although production from individual fields typically declines after a brief ramp-up period, 

the Minerals Management Service forecasts that GOM production can be sustained at these 

record-high rates with continued exploration and development from deepwater operators. 

References 

Melancon, J.M., R.D. Baud, A.G. Boice, R. Bongiovanni, T. DeCort, R. Desselles, E.G. Kazanis. 

2004. Gulf of Mexico Oil and Gas Production Forecast: 2004–2013. U.S. Dept. of the 

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

OCS Report MMS 2004-065. 27 pp. 

Richardson, G.E., L.S. French, R.D. Baud, R.H. Peterson, C.D. Roark, T.M. Montgomery, E.G. 

Kazanis, G.M. Conner, and M.P. Gravois. 2004. Deepwater Gulf of Mexico 2004: 

America’s Expanding Frontier., Minerals Management Service, Gulf of Mexico OCS 

Region, New Orleans, LA. OCS Report MMS 2004-021. 150 pp. 
230 

Richie Baud is a supervisor in the Minerals Management Service’s Office of Production and 

Development, Gulf of Mexico OCS Region. He holds a B.S. degree in geophysics from Bowling 

Green State University and an M.S. in geophysics from Purdue University. Richie has authored 

numerous publications and has 16 years of Gulf of Mexico experience between the MMS and 

industry. 

Ronald Bowser is a section chief in the Minerals Management Service’s (MMS) Office of 

Production and Development, Gulf of Mexico Outer Continental Shelf (OCS) Region. He holds 

a B.S. degree in geology with a minor in environmental science from Elizabeth City State 

University in North Carolina. Ronald has 28 years of experience with MMS and United States 

Geological Survey working in the Atlantic and Gulf of Mexico OCS. 
231 

ADVANCES IN SUBSEA PROCESSING 

Larry D. Forster, Shell Exploration & Production Co., New Orleans 

Subsea Processing is a newly developing technology—it has not been deployed in the Gulf of 

Mexico (GOM) as yet—which involves active conditioning of the wellstream or injected fluids, 

on the seabed, or in a well. Subsea processing adds value to oil and gas projects in several areas: 

by pressure boosting to enable or accelerate certain projects or to increase ultimate recovery; by 

de-bottlenecking topsides facilities by moving separation and related equipment off the topsides 

and onto the seabed. By pressure boosting and/or dealing with flow assurance issues at the 

seabed, subsea processing can enable long offset projects, subsea wells which are located 

multiple miles from the respective hosts. Finally, subsea processing can assist in gas 

dehydration/dewpointing, and EOR support, such as providing heating for heavy oil recovery. 

The key technologies involved in subsea processing include first of all, pumping, single-phase or 

multiphase (twin screw or centrifugal,) two-phase or three-phase separation, gas compression, 

and gas processing (e.g., dehydration.) Certain supporting technologies are key to the success of 

subsea processing systems: power distribution (cable, connectors, and variable speed drives) to 

provide high power over potentially long distances; heavy lift systems (some of the equipment 

components/packages may weigh in the 70- to 100-ton range), and the subsea architecture, to 

package the equipment so that deploying the equipment to the seabed is done efficiently; so that 

operating and maintaining the equipment and diagnosing problems can be performed on a system 

basis; and so that retrieving equipment for repair can be performed quickly and efficiently when 

necessary. 

System concepts for pressure boosting systems for oil applications are beginning to take several 

forms. Some system concepts are akin to “artificial lift” systems such as riser base gas lift 

(continuous gas lift), and blowcase systems (intermittent gas lifting in a cyclic mechanism.) 

Electrical (or hydraulic) submersible pumps (ESP/HSP) are under consideration as boosting 

system alternatives, either in-well or in a caisson-based dummy well. Lastly, single-phase or 

multiphase pumping systems utilize either the centrifugal or positive displacement (twin screw) 

pump systems installed on mudline based deployment systems. The use of dummy well or 

caisson systems offers a simple yet innovative form of separator. Petrobras has developed and 

piloted a Vertical Annular Separation and Pumping System (VASPS) which includes helical 

guides in the upper portion of the caisson to improve separation performance. 

As previously stated at the beginning, the actual applications to date have been outside the GOM, 

and many of the further design efforts are aimed beyond the U.S. region. The Ormen Lange gas 

project in 1,100 meters of water in the Norwegian North Sea is developing concepts and 

qualifying key components of a gas compression facility (which would be operational by 2015). 

Developments here are being eyed by others for potential applications elsewhere, but several 

years will be required to perfect the technology. Qualification depends on two factors: proof of 

sufficient reliability and of suitability for the marine environment. 
232 

Key elements of subsea gas compression systems include 

• The compressors themselves, wet-gas and dry-gas versions 

• Separator/scrubbers 

• Variable speed drives 

• Controls systems 

• Electrical cables, connectors and penetrations 

• Coolers/valving 

Separation has seen a pilot application at the Norsk Hydro Troll gas field, in which separated 

water was reinjected into an injection well near the equipment site, while oil and gas were 

produced back to the Troll host. This pilot application was primarily for host de-bottlenecking, to 

add more water handling equipment off the topsides facility. A gravity separation concept with 

cyclonic internal features to enhance the gas/liquid separation was utilized here. Design concepts 

for subsea separation are including novel internal schemes to reduce size and weight of the 

separation equipment. In particular, a Gas to Liquid Cylindrical Cyclone (GLCC) and a Liquid to 

Liquid Cylindrical Cyclone have been under evaluation at the University of Tulsa. 

Risks have been recently evaluated for subsea processing schemes as opposed to topsides. The 

former pose lower risk to personnel than the latter, due to equipment installed remotely on the 

seabed, but somewhat higher environmental risk due to the increased number of leak paths in 

subsea equipment. No show stoppers have been envisaged since the underlying philosophy 

behind subsea processing is that the flow stream is a closed system, with no planned discharge 

into the environment. 

So where might subsea processing be applied? Where has it been applied already? First to see 

application are likely to be riser-base separation and pumping systems as well as multiphase 

pumping systems. Applications have become apparent for boosting and/or separation to increase 

production for oil fields whose water content has risen to significant levels. Non-geopressured 

fields, particularly with long offsets, and also heavy and/or viscous oils will require boosting to 

either enable the projects or enhance recovery. Fields such as the Amerada Hess Ceiba field in 

Equatorial Guinea, will likely see additional use of centrifugal pumping systems. Agip, in the 

Balmoral field, has recently applied twin-screw multiphase pumping in shallow water of the 

North Sea, and Santos Mutineer also applied helicoaxial multiphase pumping in shallow water 

offshore Australia, in the latter part of 2004. 

So what are the focus areas to get this technology where it needs to be? Specific programs are 

underway for 1) riser base separation and pumping, particularly for ultradeep water; 2) low cost, 

moderate depth light oil pumping; 3) gas compression (with Ormen Lange as a key driver); and 

lastly, 4) flow assurance issues associated with long offset production. 

Other issues remain, particularly with supporting technologies, such as control and measurement 

systems and the deployment and retrievability related to the subsea architecture issues mentioned 

previously. For an emerging technology, however, the focus needs to be on the basics of 
233 

pumping and separation, ensuring the concepts are viable, and finally with attention to 

enhancements. Piloting will no doubt point to further issues which can be uncovered in no other 

way. We thus hope to see successful installations, in the GOM and elsewhere, in the not-toodistant-future, as new fields approach and as existing fields age, both presenting new challenges 

for the technology. 

Larry Forster is a Staff Facilities Engineer with Shell Exploration & Production Co., working in 

Technology Planning and Implementation in New Orleans, Louisiana. He has been involved in 

subsea systems for most of his twenty-one years with Shell, working on the early design 

concepts for deepwater, and operationalizing the systems in the Gulf of Mexico. Prior to his 

recent involvement with Subsea Processing Systems, he worked on a special assignment to 

achieve faster project execution times for subsea projects. 
234 

SUBSEA HIGH INTEGRITY PRESSURE PROTECTION SYSTEMS (HIPPS) 

Christopher Lindsey-Curran, British Petroleum 

Some of BP’s prospects in the GOM are expected to have shut-in pressures and reservoir 

temperature near or in excess of 12.5 ksi and 250 °F (i.e. as in BP’s Thunder Horse field) 

combined with water depths of up to 10,000 ft. BP’s experience in HPHT (High Pressure, High 

Temperature) design has demonstrated that the industry may be at the limits of thick flowlines 

and risers (design, procurement, and welding) for such developments. 

One new technology, which is seen as a key enabler, is subsea HIPPS (High Integrity Pressure 

Protections Systems). Subsea HIPPS safely isolate downstream flowlines and risers from the 

high tubing shut-in pressure (SIP) and therefore allow the facilities to be designed to more 

conventional pressures. A small number of subsea HIPPS have been used in or are under 

consideration for North Sea and GOM projects at lesser pressures, temperatures and water 

depths. To date no subsea HIPPS have been employed in the GOM. Furthermore, no subsea 

HIPPS have yet been used in deepwater or for developments tied-back to floating production 

vessels (FPV). 

HIPPS Overview 

What is HIPPS? 

HIPPS (High Integrity Pressure Protection Systems) are Safety Instrumented Systems (SIS) 

which isolate downstream facilities from an overpressure, upset condition developing upstream. 

The initiation of the overpressure can be from upstream (loss of control of a well or pump) 

and/or downstream (process trip, inadvertent valves closure, hydrate or other blockage). In the 

event of a high-pressure event, the HIPPS should isolate the flowline and/or riser from the high 

pressure source. Therefore downstream flowlines, risers etc. can be rated for a lower pressure 

than the full Shut-In Pressure (SIP) of the upstream well or pump. Subsea HIPPS systems can 

either be located at individual wellheads or at a commingled location such as a subsea manifold. 

In the latter case the upstream facilities must be fully rated to the SIP. 

HIPPS is an additional isolation layer within the existing pressure protection layers which may 

include downhole valves, wellhead valves, manifold valves, SSIV (Subsea Isolation Valves). As 

such HIPPS should not be regarded as a single safety system but part of a series of isolation 

systems that protect lower-rated downstream facilities from the source of high pressure. 

HIPPS generally comprise initiators (pressure transducers), controllers (logic solvers) and final 

elements (valves). HIPPS must achieve very high levels of reliability; the required reliability is 

expressed as a Safety Integrity Level (SIL) or probability of failure on demand (PFD). SIL levels 

typically range from SIL1 to SIL4; with the SIL4 giving the lowest PFD. Subsea HIPPS are 

likely to be required to achieve SIL2 or more probably SIL3. Such high SIL levels will typically 

require high integrity and high availability coupled with redundancy (fault tolerance), remote 

communications, autonomous shutdown functions, and regular testing and monitoring. 
235 

To date a small number of subsea HIPPS have been installed or are under consideration in the 

North Sea. These are 

• Shell Kingfisher 

• Statoil Gullfaks 

• Shell Penguins 

• BG Juno (operated by BP) 

• BP Rhum (under construction) 

• Statoil Kristin (under construction) 

HIPPS Components 

The basic components of a subsea HIPPS are illustrated by a typical manifold system shown in 

Figure 1E.1. 

Figure 1E.1. Subsea HIPPS manifold system. 

The system comprises HIPPS valves located on the manifold header, pressure transducers and a 

HIPPS safety controller. 

Pressure Transducers. The figure indicates dual banks of three pressure transducers 

located between the valves. The number of transducers and their voting systems are a 

function of required reliability and fault tolerances. 

HIPPS Controller. All HIPPS requires an autonomous controller which monitors the 

pressure transducers. The controller closes the HIPPS valves if a high-pressure event is 

detected. The controller should allow operational testing to be performed. 
236 

HIPPS Valves. The HIPPS valves comprise the final elements which isolate the high 

pressure hazard. The figure indicates two HIPPS valves which would be typical of a SIL3 

rating. An upstream test valve is also shown to allow operational testing by pressuring the 

section between the test valve and the HIPPS valve(s). 

A test valve may be required to allow operation testing. The test valve is generally 

immediately upstream of the HIPPS valve but could be located immediately downstream. 

The test valve is often of identical specification to the HIPPS valves. 

Testing and Bypass Facilities. Any SIS must include facilities for allowing frequent, 

effective testing. Subsea HIPPS generally utilize a hydrate suppressor (e.g. methanol) 

injection system to induce pressure between the HIPPS and the upstream test valve, 

thereby tripping the HIPPS system. If required, the system may be configured to allow 

valve leakage rates to be measured. 

HIPPS in GOM 

HIPPS is essential to the development of deepwater HPHT fields (> 12.5 ksi) and should be 

regarded as a priority item for development. HIPPS will also be required to enable existing 

pipeline infrastructure to be utilized. 

For HPHT prospects at 12.5 ksi to 20 ksi, a no HIPPS pipe-in-pipe solution capable of resisting 

full shut-in pressure is impractical. The required wall thicknesses are well beyond current 

manufacturing practices, and welding may not be feasible at these thicknesses; this is combined 

with installation loads becoming prohibitively high. Even for fields with shut-in pressure of less 

than 15 ksi, HIPPS may well offer a better engineering solution than the conventional heavy-wall 

flowline designs. 

Christopher Lindsey-Curran has over 26 years’ experience of subsea systems, concentrating 

primarily on subsea production systems. Experience includes shallow water and deepwater 

systems from around the world, including North Sea, Asia, Australia and Gulf of Mexico. 

Christopher has a degree in physics from Bristol University and is the founding Chairman of the 

Society for Underwater Technology’s Houston Branch. 
237 

SCRs IN HPHT APPLICATIONS 

Thanos Moros, British Petroleum 
238 
239 
240 

Thanos Moros is a Chartered Mechanical Engineer with extensive expertise in the areas of 

subsea floating and riser systems, fluid transport, and safety engineering. He is the Riser Systems 

Team Leader for BP’s Thunder Horse Development in the Gulf of Mexico. Thanos has been 

involved in the coordination of various Industry forums and JIPs both in Europe and the U.S. and 

he has published over 35 technical papers in journals and conferences. He holds a Ph.D. in 

mechanical engineering from the University of Cambridge, UK. 
241 

TECHNICAL ASSESSMENT OF OPTIONS FOR HANDLING ASSOCIATED GAS 

FROM DEEPWATER FPSO DEVELOPMENTS IN THE GULF OF MEXICO 

E.G. Ward, OTRC/TAMU 

A.J. Wolford, A.J .Wolford & Associates 

M.B. Mick and L. Tapia, Paragon Engineering 

W. Hauser, Minerals Management Service 

A.J. Verret, Offshore Operators Committee 

Goal 

The goal of the project is to conduct a technical assessment of options for handling associated 

gas for deepwater oil developments in the Gulf of Mexico (GOM). The MMS plans to use the 

results to review the readiness and safety of gas handling options proposed for deepwater 

development projects. Results could also be useful for studies pertaining to deepwater oil and gas 

development in the GOM. 

Scope 

The project assumes a deepwater oil development from an FPSO and considers various options 

for handling the associated gas (see Figure 1E.2). Gas-handling technology options that are being 

studied include export via pipeline (the base case); processes such as LNG, CNG, and GTL that 

convert the gas to another state or product for export via shuttle tanker; generation of electricity 

for transmission to shore; and injection and deferred production. FPSO production developments 

in depths of 6,000 ft and 10,000 ft are being studied with various export destinations for the gas 

or gas-product (see Figure 1E.3). A range of gas rates are considered for each gas handling 

technology. 

Figure 1E.2. Study scope. 
242 

Figure 1E.3. Gas export scenarios. 

Figure 1E.4 schematically illustrates the FPSO with oil processing and gas processing systems. 

A previous study determined that risks for an FPSO development utilizing shuttle tankers to 

export oil and a pipeline to export gas were similar to the risks of existing deepwater systems in 

the GOM (TLP’s, spars, platforms serving as a hub/host for deepwater production) that use 

pipelines to export both the oil and gas. Thus, the gas pipeline case is considered to represent a 

baseline for this study. The technical assessment reported on here is focused on the incremental 

or additional risks and readiness issues posed from the different gas-handling systems being 

operated on the FPSO (see Figure 1E.5). Figure 1E.6 illustrates the gas handling process steps. 

Figure 1E.4. FPSO with gas handling process. 
243 

Figure 1E.5. Assessment focus. 

Figure 1E.6. Gas-handling process steps. 
244 

Technical Assessment 

The technical assessment is addressing 

• Technical and regulatory readiness. Key readiness challenges and estimates of the years 

to “project ready” status for each challenge are identified. 

• HSE risks. Key hazards and potential consequences are identified. These hazards and 

consequences reflect the HSE risks being considered in this assessment, i.e., risks of 

fatalities and damage to the environment. A risk matrix is used to rank the severity and 

likelihood of consequence and determine a risk level. 

• Costs. The incremental CAPEX and OPEX are being estimated to illustrate the feasibility 

of a particular technology for a given production scenario. These costs are over and 

above the costs associated with installing and operating the FPSO and the shuttle tankers 

exporting the oil. 

• Efficiency. The overall Process Efficiency is being estimated. This efficiency is defined 

as BTUs delivered to sales or transfer point divided by the BTU content of the associated 

gas produced. 

Workshops 

The assessment of each gas-handling technology is being addressed in a separate workshop. 

Invited workshop attendees include gas technology and marine experts, representatives for the 

MMS and industry, members from the steering committee, and representatives from class 

societies. The goal of the workshop is to develop a consensus assessment for that gas-handling 

technology. A preliminary assessment for the technology is prepared prior to each workshop. At 

the workshop, presentations by invited experts provide additional detailed information on the 

overall process or specific components. The preliminary assessment and presented material are 

discussed and are used as the basis for completing a consensus assessment for that technology. 

Status 

Workshops to gather information to assess the Pipeline, LNG, CNG, and GTL gas-handling 

options have been completed. The Gas-to-Electricity and Reinjection options will be completed 

this spring, and the overall assessment will then be documented and published.

Acknowledgments 

We acknowledge and appreciate the Minerals Management Service sponsorship and 

participation, the support and participation by the Offshore Operators Committee, and 

participation by the industry experts and class societies in the workshops. 

Dr. E.G. (Skip) Ward joined the Offshore Technology Research Center at Texas A&M 

University as the Associate Director following his retirement from Shell Oil Company in 1998. 

He is responsible for planning and coordinating the OTRC research program to meet the needs of 

the industry and Minerals Management Service. Skip had thirty years of experience with Shell, 
245 

including research, managing technology development and applications for deepwater structures, 

and managing deepwater structure design. 

Dr. A.J. Wolford is founder and President of Risknology Inc. in Houston, a firm specializing in 

risk-informed approaches to technology issues in the production, energy and power industries. 

He has directed risk applications on a diverse range of engineered systems, including offshore 

and onshore oil and gas installations, mobile offshore drilling units, marine and land-based 

transportation systems, chemical and nuclear fuel processing plants, nuclear power and test 

reactors, and the Space Shuttle. He is an accomplished and highly-experienced risk analyst, 

having worked in the field of industrial risk assessment for the past 19 years. 

M.B. (Skip) Mick is Vice President, Deepwater / Special Projects for Paragon Engineering 

Services. Skip has more than 30 years’ varied experience in the oil and gas industry. Prior to his 

career at Paragon, he worked at Marathon Oil Co. for nearly 25 years, most recently as the 

Deepwater Development manager. He began his industry career and spent six years at Exxon. He 

earned B.S. in chemical engineering from the University of Dayton, his M.S. in chemical 

engineering from the University of Florida, and his M.B.A. from Texas A&M in Kingsville, 

Texas. He is a registered professional engineer in the state of Ohio, and is a member of the SPE 

and AIChe. 

Luis Tapia has an M.S. in petroleum engineer from Texas A&M and an M.S. in petroleum 

economics and management from IFP. He has extensive expertise in technical and business 

matters of the oil and gas industry. He worked for Occidental Oil & Gas as operations engineer 

and is now working for Paragon Engineering Services as flow assurance specialist. 

William Hauser is a petroleum engineer with the Minerals Management Service. He is currently 

the Chief of the Regulations and Standards Branch, which is responsible for managing the 

assessment, development, and promulgation of OCS regulations related to the exploration and 

development of oil, gas, and other minerals. For several years, he was responsible for managing 

MMS’ drilling research activities and revising MMS’ drilling regulations. Mr. Hauser has 

worked with MMS and the Department of the Interior since 1978. 
246 

UPDATE ON U.S. COAST GUARD ACTIVITIES 

LCDR Jeff Ramos, USCG, Eighth Coast Guard District, New Orleans, LA 

Inspections Overview—Regulated OCS Activities 

The Coast Guard conducts safety inspections of several activities occurring on the Outer 

Continental Shelf (OCS). Our inspections range from certificating Floating Offshore Installations 

(FOIs) to certificating Offshore Supply Vessels that support the offshore industry. We ensure 

that these vessels are built, manned and operated to applicable standards. We also ensure that 

they are equipped with adequate firefighting and lifesaving equipment. 

Over the past several years, the Coast Guard has seen a dramatic increase in the construction of 

FOIs for deepwater operations and in the applications for developing LNG Deepwater Ports. 

Currently, there are approximately 28 FOIs operating in the GOM, and in the past year, we have 

received approximately six new applications for LNG Deepwater Ports for the GOM. We have 

met this increase in workload by increasing the number of OCS inspectors at certain units, 

especially overseas where a number of these FOIs are being built. Our Coast Guard Headquarters 

has also established a new branch, G-MSO-5, which is dedicated to handling deepwater port 

applications. 

New Construction Projects under NVIC 10-82 

The Coast Guard continues to work with the American Bureau of Shipping (ABS) in the new 

construction of FOIs by using Navigation and Vessel Inspection Circular (NVIC) 10-82 as a 

guideline. This NVIC allows ABS to perform plan review & inspection items on behalf of the 

Coast Guard. ABS approves hull structure, marine engineering, electrical engineering, and 

piping systems. The Coast Guard approves stability, fire control, and lifesaving systems. Coast 

Guard & ABS continue to work in close cooperation by scheduling formal and informal 

meetings to discuss issues of concern. 

In-Service Inspection Program (ISIP) for FOIs 

The Eighth Coast District (D8) has promulgated several policy letters during this past year, 

which are applicable to deepwater operations. One of these policy letters addresses the InService Inspection Program (ISIP) for FOIs. An ISIP Plan describes the hull exam procedures to 

be conducted while the FOI remains on-station. Our Headquarters previously approved these 

plans; however, they have now delegated this approval to the local Officer in Charge, Marine 

Inspection (OCMI). The plan requires 40% of the hull to be inspected annually (equivalent to 

twice-in-five years), and allows a reduction of the hull exam to 20% annually (once-in-five) 

under certain circumstances. This reduction is called a “Modified Inspection Program.” 

In May 2004, D8 developed a policy to clarify “circumstances” for placing FOIs in the Modified 

Inspection Program. The criteria for allowance into the Modified Inspection Program are as 

follows: 
247 

 a) Not “novel” or “unconventional” design class, 

 b) No history of design problems within last five years, 

 c) No problems with quality of company inspection procedures, and 

 d) No unique operating conditions. 

Use of Hose Reels on FOIs 

Another policy letter D8 recently promulgated addresses the use of hose reels on FOIs. 46 CFR 

108.425 requires hoses to be: 1 1⁄2 or 2 1⁄2 inches in diameter, and 50 ft in length. They must also 

meet UL-19 Standard (collapsible). However, our headquarters (G-MSE-2) has approved certain 

hard-rubber non-collapsible hoses (hose reels) for limited use as long as they meet UL-92 

Standard or Mil Spec H24580. 

D8 policy letter dated September 2004 allows the use of these hose reels subject to the following: 

 a) Hose reels can only be installed on open decks; or inside columns, pontoons, & 

machinery spaces if not congested; 

 b) They can not be installed inside accommodation spaces; and 

 c) If there are no fire stations inside the accommodation spaces, the accommodation module 

size is limited to 70 ft x 40 ft. 

This policy letter replaces the policy letter issued in May 2004, which had required hose ports to 

be installed in exterior doors of accommodation spaces if there were no internal fire stations 

installed. These hose ports are now not required. 

Guardrails & Storm Rails on FOIs 

In December 2004, D8 promulgated a policy letter on the installation of guardrails and storm 

rails on FOIs. 33 CFR 143.110 (OCS Facilities) requires a 42” rail height, and 46 CFR 108.217 

(MODUs) requires a 39” rail height. D8 will allow either of the above designs as long as it is 

consistent throughout the facility. The maximum horizontal distance between vertical guardrail 

sections must also be minimized. And finally, due to the absence of adverse movements in FOIs, 

internal storm rails are not required. 

Revision of Crane Regulations 

46 CFR 107.309 and 107.259 currently require the Coast Guard to certify and conduct tests of 

offshore cranes in accordance to API 2C and 2D. However, Coast Guard inspectors do not have 

the expertise to physically examine these cranes. D8 is currently revising regulations to allow 

qualified third parties, i.e., other class societies and companies certified by crane manufacturers, 

to conduct crane certifications & tests on behalf of the Coast Guard. The Coast Guard will still 

maintain oversight authority. 

MOU between MMS/USCG 

The Coast Guard has enjoyed a great working relationship with the Minerals Management 

Service (MMS). A new Memorandum of Understanding (MOU), signed on 30 September 2004, 

is an overlapping bridging document, which will be supported by technical annexes known as 
248 

Memorandum of Agreements (MOAs). These MOAs will be formulated and sequentially 

numbered as needed by working groups incorporating regulatory and industry representation. 

MOA #OCS-01, which is already part of the MOU, restates the 1998 MOU as a starting point for 

guidance on which agency has overall responsibility on certain systems on board a MODU or 

fixed/floating facility. Basically, the CG is responsible for the marine systems, and MMS is 

responsible for the production & drilling systems. We also share responsibility where the 

systems overlap (i.e. mooring systems, evacuation plans). 

Future MOAs will be developed to address other emerging issues, such as security, fixed 

facilities, floating facilities, MODUs, FPSOs, and casualty investigations. Once these MOAs are 

completed, they will become part of the main MOU. 

Floating Storage & Offloading (FSO) Systems 

After Hurricane Ivan, a number of pipelines were damaged, preventing oil from being transferred 

to shore. FSOs were proposed as an alternative in bringing oil ashore. Since there were no 

regulations in place for this type of operation, the Coast Guard worked closely with MMS in 

developing a Regulatory Model. The offshore industry has since determined that it may be more 

cost-effective to repair its pipelines. Therefore, no written proposals have been received to date. 

U.S. & Mexico Joint Response Agreement (MEXUS) 

The Eighth District is one of two Districts in the U.S. that borders Mexico. The Mexico-U.S. 

(MEXUS) Initiative provides for bilateral cooperation in response to pollution incidents that 

could seriously affect the coastal waters and coastal region of one or both countries, or in cases 

where the impact of the incident in one country’s maritime zone would be of such magnitude that 

would justify the request to the other country for coordinated assistance. The signing of the 

MEXUS Plan in February of 2000 and its supporting geographical annexes - MEXUS Gulf and 

MEXUS Pacific (MEXUS PAC)—in February 2003 marked a significant advancement in 

Mexico-U.S. joint collaboration for protection of the coastal marine environments of both 

nations. In April 2004, a MEXUS activation took place as part of an oil spill exercise in the 

Pacific Ocean. In May of 2004, the first MEXUS Gulf notification was initiated by the Mexican 

Navy to notify all involved parties of the finding of significant amounts of tar balls on Mexican 

beaches near the U.S. border. The Coast Guard, the State of Texas and NOAA responded 

accordingly to the notification. 

The recently jointly signed MEXUS “Strategic Work Program Through Goals to Be Achieved in 

Five Years” delineates a road map to maintain a common focus for a progressive approach and 

advancement of the joint cooperation. 

Domestic Security Requirements 

33 CFR Subchapter H – “Maritime Security” 

The Maritime Transportation Security Act (MTSA) regulations were published as final rules on 

22 October 2003. They are the U.S. equivalent to the ISPS Code, which was adopted by IMO as 

an amendment to SOLAS in December 2002. 
249 

33 CFR Part 101 establishes the criteria for alternative security programs, establishes and defines 

Maritime Security or MARSEC levels, prescribes communications between the Coast Guard 

Captain of the Ports (COTPs) and industry to communicate threat information (MARSEC level 

attainment, notifications of suspicious activity, breaches of security, and notifications of 

transportation security incidents), and establishes control measures that the COTPs can use on 

vessels and facilities that are not in compliance with the regulations. 

33 CFR Part 103 focuses on area maritime security and is intended to identify and protect critical 

port infrastructure; identify risk in terms of threats, vulnerabilities and consequences; determine 

mitigation strategies; and determine security measures for the MARSEC levels. Part 103 

designates COTPs as Federal Maritime Security Coordinators. Under this authority they 

establish, convene and direct Area Maritime Security Committees; appoint members; develop, 

maintain, and exercise Area Maritime Security Plans. The Area Maritime Security Plan specifies 

operational and physical security measures in place at all MARSEC levels and addresses 

evacuation, communication, and jurisdiction. 

33 CFR Parts 104, 105 and 106 pertain to vessels, facilities and OCS facilities, respectively. 

They contain similar security requirements for each entity, including specifying the 

responsibilities of owners and operators for compliance with the MTSA regulations and detailed 

security requirements including Declarations of Security, drills and exercises, communications, 

measures for access control, restricted areas, security assessments and security plans. 

Offshore Facilities 

Offshore facilities pose unique security challenges. They are both manned and unmanned, 

surrounded by water, and are located up to 100 + miles from shore. Most also have limited 

security forces onboard. 

33 CFR Part 106 applies to all fixed and floating facilities, including Mobile Offshore Drilling 

Units and transmission hubs, if they meet any of the following criteria: 

 1. Hosts greater than 150 personnel onboard for 12 hours or more in a 24-hour period, 

continuously, or for 30 days or more. 

 2. Produces oil in an amount greater than 100,000 barrels per day. 

 3. Produces gas in an amount greater than 200 million cubic feet per day. 

Of the 4,000 oil and gas facilities in the GOM, there are presently 49 that meet these regulatory 

thresholds. 

The regulations for deepwater ports (Oil or LNG) were recently amended (Interim Federal Rule 

effective 6 January 2004). Although MTSA does not directly apply to the deepwater ports 

(DWPs), the DWP regulations (33 CFR 148-150) require their security plan to contain the same 

elements as the regulations for OCS facilities in 33 CFR Part 106. DWP Operations Manuals are 

reviewed and approved by Commandant (G-M). 
250 

It is important to note that the offshore oil and gas industry was the only regulated community 

that met all security plan submission deadlines and required no enforcement action. All regulated 

OCS facilities were issued final approval letters by 31 December 2004. 

Area Maritime Security Committees 

One of the key components of the MTSA regulations is that it required the formation of Area 

Maritime Security Committees (AMSCs). Late in the regulatory project, it was decided that the 

GOM would be handled as a single “port” with the District Commander as the Federal Maritime 

Security Coordinator (FMSC). As such, he was charged (on short order) with establishing an 

AMSC for the “port” of the GOM. 

The current AMSC membership includes USCG, FBI, MMS, FAA, API, and industry 

representatives from the OSV, drilling, production, helicopter, commercial and recreational 

fishery, offshore lightering, offshore towing, pipeline, and LNG industries. 

Some of the issues that the AMSC are working on include: 

 

 a. AMS Assessment: For the purpose of the GOM Area Maritime Security Plan (AMSP), 

the protected resources include 49 regulated OCS facilities, all DWPs (currently one with 

approximately six LNG applications filed), offshore lightering zones (four OPA-90 and 

six traditional), cruise ships, and other deep draft shipping. 

 b. Communication: A process to quickly communicate with AMSC members, Security 

Officers and other persons with a security interest has been developed. This system has 

been used regularly (six times to date) and continues to be improved. The AMSC is 

looking into new communications technologies that will automate and improve the 

communication process. 

 c. OCS Boundary: For the purpose of the GOM AMSP, the area of responsibility will 

include all D8 GOM waters outside of the state boundaries out to the extent of the EEZ 

(200 miles). 

 d. Future Dissemination of Sensitive Security Information (SSI): In the past, companies 

were required to go to a local Marine Safety Office to pick up MARSEC Directives and 

other sensitive security information. In September, we advised our offshore security 

community that our headquarters is close to rolling out a new web portal known as 

“Homeport.” This system will provide each user with a unique password and will allow 

individuals to access classified information over the web. Persons with a need-to-know 

will be identified by the FMSCs (including D8 for the OCS). 

Lieutenant Commander Jeff Ramos graduated from the U.S. Merchant Marine Academy in 1989 

with a B.S. degree in marine transportation. After graduating, he served in various positions at 
251 

Marine Safety Offices in Honolulu, Hawaii; Singapore; and Mobile, Alabama. Afterwards, he 

spent three years as the Coast Guard Liaison Officer at the Merchant Marine Academy in Kings 

Point, New York. In 1999, he was assigned to the Marine Safety Unit in Galveston, Texas and 

served as Chief, Merchant Vessel Safety Department, and later as Chief, Port Operations 

Department. In August of 2003, Lieutenant Commander Ramos assumed his current position as 

Chief, Compliance Branch, at the Eighth Coast Guard District in New Orleans, Louisiana. 
253 

SESSION 1F 

SPERM WHALE SEISMIC STUDY 

Chair: Bill Lang, Minerals Management Service 

Co-Chair: Colleen Benner, Minerals Management Service 

INDUSTRY REMARKS Chip Gill..........................................................Document not submitted 

OVERVIEW OF THE SPERM WHALE SEISMIC STUDY IN THE GULF OF MEXICO 

Ann E. Jochens............................................................................................................................ 255 

SEASONAL MOVEMENTS, RANGE, AND ASPECTS OF SPERM WHALE DIVING 

BEHAVIOR Bruce Mate ........................................................................................................... 259 

SOCIAL STRUCTURE OF SATELLITE-TRACKED SPERM WHALES IN THE GULF 

OF MEXICO Joel Ortega-Ortiz, Bruce Mate, and Dan Engelhaupt ......................................... 263 

HABITAT CHARACTERIZATION OF SATELLITE-TRACKED SPERM WHALES 

IN THE GULF OF MEXICO Joel Ortega-Ortiz, Bruce Mate, Robert R. Leben, Douglas C. 

Biggs, and Matthew K. Howard ................................................................................................. 265 

SEISMIC SURVEY ACTIVITY AND THE PROXIMITY OF S-TAGGED WHALES 

Martha H. Winsor and Bruce Mate............................................................................................. 267 

BRIEF OUTLINE OF SPERM WHALE AIRGUN CONTROLLED EXPOSURE 

EXPERIMENTS (CEES) Peter L. Tyack.................................................................................. 271 

DIVING, FORAGING, AND VOCAL BEHAVIOR OF SPERM WHALES Stephanie L. 

Watwood, Mark P. Johnson, Peter T. Madsen, Peter L. Tyack, and Patrick J.O. Miller ........... 274 

THE SOUNDS OF AIRGUNS AS RECORDED ON SPERM WHALES AND METHODS 

TO QUANTIFY ACOUSTIC EXPOSURE Peter T. Madsen, Mark P. Johnson, 

Peter L. Tyack, and Patrick J.O. Miller ...................................................................................... 277 

PRELIMINARY MODELING OF D-TAGS ACOUSTIC ARRIVALS FROM THE 

GULF OF MEXICO IN 2002 AND 2003 James F. Lynch, Stacy DeRuiter, 

Peter L. Tyack, Arthur Newhall, and Ying-Tsong Lin............................................................... 281 

(continued on next page) 
254 

CONTROLLED SEISMIC AIRGUN EXPOSURES: EFFECTS ON THE MOVEMENT 

AND FORAGING BEHAVIOR OF SPERM WHALES Patrick J. O. Miller, 

Mark P. Johnson, Peter L. Tyack, Peter T. Madsen, and Stephanie L. Watwood...................... 284 

D-TAG/CEE CONCLUDING REMARKS Peter L. Tyack...................................................... 289 
255 

OVERVIEW OF THE SPERM WHALE SEISMIC STUDY IN THE GULF OF MEXICO 

Ann E. Jochens, Texas A&M University 

The Sperm Whale Seismic Study (SWSS) is a cooperative study of sperm whales in the Gulf of 

Mexico (GOM), their habitat, and their response to man-made noise. SWSS is sponsored by the 

Minerals Management Service in cooperation with the Industry Research Funders Coalition 

(IRFC), National Science Foundation (NSF), and Office of Naval Research (ONR). The study is 

being conducted by scientists from Oregon State University (OSU), Scripps Institution of 

Oceanography (SIO), Texas A&M University (TAMU), Texas A&M University-Galveston 

(TAMUG), University of Colorado (CU), University of Durham (UD), University of St. 

Andrews (UStA), Woods Hole Oceanographic Institution (WHOI), and Ecologic Ltd. A Science 

Review Board is established to provide review and comment on the Synthesis Report. This board 

consists of five members: one from the federal government (NOAA), one from industry, one 

retired from the Marine Mammal Commission, and two from the academic community. All 

activities involving sperm whales are performed under the terms of valid permits from NOAA 

Fisheries. 

In 1991, MMS began a series of environmental studies to investigate cetaceans in the GOM. In 

the 1990s, the MMS-sponsored GulfCet Study used ships and aircraft to survey the western and 

eastern parts of the northern Gulf to determine seasonal variability in the occurrence and 

distribution of marine mammals (Davis and Fargion 1996; Davis et al. 2000). In 1999, MMS 

hosted a Gulf of Mexico Protected Species Workshop (McKay et al. 2001) to review past 

research, evaluate new issues, and recommend research priorities. MMS, ONR, and the National 

Marine Fisheries Service (NMFS) then sponsored the Sperm Whale Acoustic Monitoring 

Program (SWAMP) in fiscal years 2000 and 2001. SWAMP was a pilot study that developed 

methods and began documenting a baseline on "usual" behavior of sperm whales in the GOM. 

This study, as well as earlier survey results, indicated that sperm whales tend to be most likely 

observed near the 1,000-m isobath. 

As oil and gas activities in the deepwater GOM increase and move into deep water, the potential 

increases for them to occur in regions frequented by the endangered sperm whale. At the 1999 

MMS Workshop, a panel of experts identified the potential effects of noise from seismic 

operations on sperm whales as a key research priority. During the January 2002 MMS 

Information Transfer Meeting, the International Association of Geophysical Contractors (IAGC; 

now part of the IRFC) hosted a meeting to discuss future acoustic research relevant to seismic 

operations, and in particular, as related to understanding the effects of seismic exploration on 

sperm whales in the GOM. IAGC offered its support for sperm whale research through 

contribution of a seismic source vessel for controlled exposure experiments. In response, SWSS 

was proposed and approved by MMS in April 2002 under a Cooperative Agreement between 

MMS and the scientists. 
256 

The study consisted initially of three years of field research with analysis and synthesis. Plans 

now extend this study to provide for an additional year of field work and to conduct several 

interactive meetings in 2006 with SISS researchers to complete the final synthesis report. The 

study area is primarily the northern GOM, with focus on the region immediately off the 

Mississippi River Delta. The objectives of SWSS are three-fold: 

 1. establish the "normal" behavior of sperm whales in the northern GOM, 

 2. characterize habitat use, and 

 3. determine possible changes in behavior of sperm whales when subjected to man-made 

noise, particularly from seismic airgun arrays. 

In addition to program management (TAMU), SWSS consists of six components: S-tag (OSU), 

D-tag (WHOI, UStA), mesoscale population behavior (TAMUG, Ecologic, UStA), genetic 

analyses (UD), habitat characterization (TAMU, CU), and passive acoustics research (SIO). 

MMS provides fiscal support, project oversight, and cruise participants under the Cooperative 

Agreement. ONR provides funding for development of both the S-tags and D-tags used in this 

study. IRFC provides the seismic source vessel and its crew for the controlled exposure 

experiments in field years one and two, as well as funding to support the Mesoscale Population 

Study and purchase of the 3-D passive acoustic tracking array in field year three. NSF provides 

the R/V Maurice Ewing as the science vessel for the controlled exposure experiment in field year 

two, as well as support for other, non-SWSS acoustics studies. 

The S-tag component monitors seasonal changes in distribution of sperm whales in the GOM and 

identifies behaviors, summer and other seasonal habitats, and, in coordination with the habitat 

characterization task, associations with oceanographic features. The D-tag component quantifies 

diving behavior and vocalizations in Gulf sperm whales on short time scales (hours) and 

conducts controlled exposure experiments to measure reactions of these whales to controlled 

airgun sounds. The Mesoscale Population Study uses photo identification, photogrammetry, and 

passive acoustics to study sperm whale group behavior and coda analyses; in year three this work 

was conducted aboard a quiet sailboat so that specific whale groups could be studied over several 

days. The genetic analyses component allows study of groups of sperm whales in terms of 

relatedness through DNA analyses of skin/tissue samples. The habitat characterization 

component merges biological oceanography, physical oceanography, and remote sensing data to 

provide an interdisciplinary description of the oceanographic habitat in which sperm whales are 

encountered. Passive acoustic experiments are conducted to estimate 3-D whale locations 

underwater from their sounds. 

During SWSS 2002-2004, there were three S-tag cruises, two D-tag cruises with controlled 

exposure experiments using airguns on seismic vessels provided through IRFC, one cruise for a 

sperm whale survey and habitat characterization study conducted concurrently with the D-tag 

cruise for that year, and one mesoscale population study cruise aboard a 46' Hunter sailboat. In 

Table 1F.1 gives the cruise type, ship name, and cruises dates for all three years. 
257 

Table 1F.1. 2002-2004 Cruises conducted for and related to the Sperm Whale Seismic Study. 

Ship Cruise Dates 

2002 

R/V Gyre S-tag 06/20/2002 - 07/08/2002 

R/V Gyre D-tag 08/19/2002 - 09/15/2002 

M/V Rylan T/Speculator CEE1

 with Gyre 08/29/2002 - 09/12/2002 

2003 

R/V Gyre Whale & Habitat Survey 05/31/2003 - 06/21/2003 

R/V Maurice Ewing D-tag 06/03/2003 - 06/24/2003 

M/V Kondor Explorer CEE with Ewing 06/07/2003 - 06/22/2003 

R/V Gyre S-tag 06/26/2003 - 07/14/2003 

2004 

R/V Gyre S-tag 05/24/2004 - 06/19/2004 

Summer Breeze MPS2

 06/20/2004 - 08/15/2004 1

CEE is the controlled exposure experiment using airguns of the seismic source vessel 

2

MPS denotes the Mesoscale Population Study cruise from the 46' Hunter sailboat 

The Summary Report for SWSS 2002–2004 will become available in late 2005. Planning is 

proceeding among the scientists and sponsors to extend the SWSS Cooperative Agreement to 

allow field work in summer 2005 and 2006 and additional analysis and synthesis in 2006. The 

Synthesis Report from such work is targeted for spring/summer 2007. The extent and nature of 

any follow-on work would be determined after the recommendations of the Marine Mammal 

Commission Advisory Committee on Acoustic Impacts on Marine Mammals become available 

(see http://mmc.gov/sound/. 

References 

Davis, R.W. and G.S. Fargion, eds. 1996. Distribution and abundance of cetaceans in the 

northcentral and western Gulf of Mexico: Final Report. Volume I: Executive. U.S. Dept. 

of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New 

Orleans, LA. OCS Study MMS 96-0026. 

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 I: 

Executive Summary. U.S. Dept. of the Interior, Geological Survey, Biological Resources 

division, USGS/BRD/CR-1999-0006 and Minerals Management Service, Gulf of Mexico 

OCS Region, New Orleans, LA, OCS Study MMS 2000-002. 27 pp. 

McKay, M., J. Nides, W. Lang, and D. Vigil, eds. 2001. Gulf of Mexico Marine Protected 

Species Workshop, June 1999. U.S. Dept. of the Interior, Minerals Management Service, 

Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 2001-039. 171 pp. 

Ann Jochens is an Associate Research Scientist in the Department of Oceanography at Texas 

A&M University and Program Manager for SWSS. She has a B.S. in Mathematics and Statistics 
258 

with Honor from Southern Methodist University (1974), a Doctor of Jurisprudence with 

background specialty in ocean law from the University of Oregon (1977), and an M.S. and a 

Ph.D. in oceanography from Texas A&M University (1989; 1997). Her research focus is in 

physical oceanography with specific interests in processes at the boundary of the coastal and 

open oceans; integration of physical and biogeochemical observations to analyze circulation and 

property transports through the ecosystem with emphasis on coastal environments; meso- and 

large-scale ocean circulation and property distributions with emphasis on shelf and slope regions; 

Gulf of Mexico physical oceanography; and development of ocean observing systems. 
259 

SEASONAL MOVEMENTS, RANGE, AND ASPECTS OF 

SPERM WHALE DIVING BEHAVIOR 

Bruce Mate, Oregon State University 

The broad-scale objective of the SWSS satellite-monitored radio tagging program describes the 

seasonal distribution of sperm whales in the northern Gulf. The specific objectives of the S-tag 

program include: 1) identification of habitats, especially high-use areas, and possible migration 

routes in conjunction with the genetics sampling program led by Dan Englehaupt; 2) 

characterization of habitat environmental variables; 3) correlation of information directly related 

to sex-specific movements; and 4) analysis of tagged whale movements with seismic vessel 

activity that is funded separately by the Industry Research Funding Coalition (IRFC). 

Papers on the habitat characteristics, sex-specific social structures and seismic work are 

presented independently in these proceedings. 

Materials and Methods 

This tagging program grew from the earlier efforts of SWAMP, which included the tagging of 

four sperm whales in 2001. One of these whales was tracked for 137 days. Subsequently, 39 

sperm whales have been tagged during field efforts in 2002, 2003, and 2004. The latter three 

field seasons have been conducted from the Texas A&M R/V Gyre as a principal platform. 

Visual observers maintained watch during suitable weather and daylight hours using big-eye 

binoculars located on the Gyre’s flying bridge. An acoustics team maintained 24-hour/day 

monitoring of two towed arrays, which provided an important means of identifying whales in 

their long dive cycles during the night and periods of inclement weather. When whales were 

found, one or two rigid-hulled inflatable boats (RHIBs) were launched from the Gyre with teams 

for tagging, photo identification, genetic sampling, behavioral observation, and tagging followup. 

The tagging boat generally consisted of five people—a driver, tagger, biopsy person, 

videographer, and photo ID person. Whales were typically approached at low speed; tagging and 

biopsying were done from a bowsprit pulpit mounted on the front of a 6.4-meter RHIB. 

The implantable tags were developed at Oregon State University with the Office of Naval 

Research Support and have been used successfully on a variety of baleen whale species. The tag 

includes a coating of long-term dispersant antibiotic to help prevent infection as the whale’s 

tissue encapsulates the tag over time. During the course of this project, two significant 

developments have made the application of these tags on sperm whales much more successful—

the modification of the way attachments are fastened to the tag itself, and the use of an airpowered applicator. The latter consistently provided for nearly flush deployment of the tag, 

which has external stops to prevent inward migration. While the duty cycle of tags has varied 

from year to year, in general it provided for transmissions every third or fourth day to extend the 

operational life of the tags themselves and to provide multi-season coverage. Because tags only 
260 

reach the satellite during these periods of active transmission, when whales are at the surface and 

coinciding with satellite passage, the number of satellite-determined locations per day can vary 

considerably. Sperm whales take long dives. If satellite passage occurs during such a long dive, 

no messages are recorded by the satellite. However, when satellite coverage coincides with the 

whale’s 7- to 10-minute surfacing to recover oxygen between dives, a large number of messages 

can be obtained. This results in a higher proportion of high-quality locations than for other whale 

species tracked to date. In fact, 46% of all the locations acquired to date have been location class 

1, 2, and 3, which have estimated accuracies of one kilometer, 350 meters, and less than 150 

meters respectively. This outstanding performance has provided high levels of confidence in the 

resulting location and characterization studies. 

In an effort to insure the highest quality information and the least interpretive error, we use only 

location class 1, 2, and 3 locations for the most sensitive analyses. However, for seasonal 

movement information, we also find it useful to include 0 Class locations but apply screening 

criteria to avoid including inappropriate locations. These screening criteria involve around 

acceptable travel speeds between previous and next consecutive location. Because over 95% of 

the whale movements we have monitored fall within a speed category of under 6 km/hr, we have 

tended to favor this category as our screening criteria. It must be kept in mind that because of the 

longer period of time often elapses between locations because of duty-cycle issues, the distances 

measured between locations are conservative estimates of the whale’s movements. The lines 

seen on maps should not be interpreted as the whale’s track during these movements; they 

merely link chronological locations together. 

The skin biopsies taken by Dan Englehaupt during the course of tagging or in follow-up 

observations have allowed an analysis of genetic relatedness among individuals when tags have 

been applied to animals in social groups. The sample also provides analysis of differences in 

movements and seasonal preferences by sex. 

Results 

To date, the longest tracking period has been 610 days. This male whale provides an example of 

how this type of tracking can reveal heretofore unknown activities that include: 1) the use of 

different summer areas, 2) the return to a common wintering area in both years, 3) the extensive 

use of offshore deep waters, and 4) the movement out of the Gulf of Mexico (GOM) and into the 

North Atlantic for two months and an apparent avoidance of heavy weather generated by 

Hurricane Isabelle. 

It would be fair to characterize the movements of animals tagged off the Mississippi River Delta 

as concentrating along the northern slope edge and portions of the slope itself. Locations in deep 

water represented less than 10 percent of all locations. Although two females ventured out into 

deep water for short periods of time, the offshore movements tended to be primarily the 

movements of males or those of unknown sex (where a biopsy sample was not obtained or 

recovered, sloughed skin proved inadequate for DNA characterization). This characterization of 

the activity along the upper Gulf Slope was true for all four years of tagged whale activity. A 

considerable concentration of locations along the western edge of the northwest Gulf in 2002 
261 

was largely the result of a single male’s activity over 6 months off the Brownsville, Texas 

region. The average duration and distances traveled by transmitting whales by year was 345 days 

and 1,906 km in 2001, 225 days and 3,547 km in 2002, 224 days and 3,719 km in 2003, and 

through October, 98 days and 722 km for the 2004 field program that is still in progress at this 

writing. In general, the tags on males and unknown-sex animals lasted longer than those of 

females. Through October 2004, whales have been tracked for a total distance of 143,728 km, 

with over 1.5 million dives being enumerated during the course of this effort. 

An analysis of home range shows the monthly movements of the population’s “core” proceeding 

from winter off the Mississippi River Delta to more of the central upper slope during spring 

months, summering again off the Delta, and moving in the fall off to the western portions of the 

upper Gulf. 

In an effort to analyze the effects of tags on whales, we re-photographed tagged whales when we 

encountered them during the course of subsequent year tagging efforts. Six whale tags have 

transmitted beyond a single year and led us to areas of whale abundance for subsequent tagging 

efforts the following year. These efforts to relocate and photograph tagged whales have been 

gratifying. We saw no examples of whales that appeared emaciated or behaved abnormally. In 

general, animals that had lost tags showed little evidence of having been tagged, with no tissue 

sloughage or skin necrosis. One tag was encountered that had migrated about 3/4 of its length out 

of the animal and still maintained a good attachment while continuing to transmit locations. 

The Future 

We have begun designing a tag suitable for measuring the dive-depth of sperm whales. These 

tags can provide a description of the three-dimensional habits of the species record for an 

extended period of time, including seasonal, diurnal, and geographic differences. We propose 

using these tags in future SWSS efforts to 1) improve our knowledge of the whales’ dive habits, 

2) model the whales’ potential exposure to sound, and 3) reveal how the whales’ foraging habits 

may vary due to the possible diurnal behavior of their primary prey, squid. Further, this 

information may ultimately help develop seasonal time of day and/or behavior-specific 

probabilities of sightings, which may be used as correction factors to improve population 

estimates from ship and aerial surveys. These satellite-linked depth tags were tested in 2004 on 

blue whales; the data showed a conspicuous diurnal dive pattern. 

We hope future research efforts will also include some emphasis on assessing the biomass of 

prey species to better understand the distribution of whales. This may also be important in 

evaluating whether animals potentially displaced from an area find similar or inferior prey 

concentrations in the area to which they move. Relative to assessing squid biomass during 

cruises, we hope to correlate the abundance of squids with specific oceanographic features or 

acoustically detected day-and-night sperm whale activity. We would like to reveal more about 

the diurnal migratory behavior of squids, and thus sperm whales. 

The development of a GPS-linked satellite tag is also underway, using IRFC funding, to provide 

extremely accurate whale locations (ultimately, with dive and acoustic data). Such a tag would 
262 

allow us to conduct long-term observations to evaluate possible sound exposure responses based 

on precise distances from anthropogenic sources. 

Overall, our goal to date has been to understand how environmental variables contribute to 

changes in habitat choice and behavior (natural variability), and use this information in the future 

to develop a predictive model to help plan surveys, research, or mitigation (if needed). Our 

current technology provides months’ or seasons’ worth of broad-scale, low-resolution location 

data to identify movements and seasonal habitats. Our intent for the future is to provide 

intermediate scale data on a geographic basis and very fine detail on movements in proximity to 

sound through controlled and experimental periods. The GPS development activity should result 

in testable prototypes by the 2006 field season. 

Dr. Bruce Mate holds an endowed chair at Oregon State University, where he directs the OSU 

Marine Mammal Program at the Hatfield Marine Science Center. He has served as a Scientific 

Advisor to the U.S. Marine Mammal Commission and the U.S. Department of the Interior’s 

Outer Continental Shelf Development Program, a scientific expert to the International Whaling 

Commission and the United Nation Environmental Program, and a member of the International 

Union for the Conservation of Nature’s Species Survival Commission. He has studied the 

migrations of marine mammals since 1968 and pioneered the tracking of manatees, dolphins and 

large whales with satellite-monitored radio tags. With collaborators, his research group has 

tracked ten stocks of seven large endangered whale species in six different oceans/seas, including 

temperate, equatorial, Arctic, and Antarctic regions. His specialty is the identification and 

characterization of seasonal critical habitats for endangered whales and how they migrate 

between them. An applied aspect of his research focuses on trying to reduce potential impacts of 

human activities on recovering endangered species. 
263 

SOCIAL STRUCTURE OF SATELLITE-TRACKED SPERM WHALES 

IN THE GULF OF MEXICO 

Joel Ortega-Ortiz and Bruce Mate, Oregon State University 

Dan Engelhaupt, University of Durham, England 

Sperm whales are known to have a complex social structure. Females, calves and immature 

males inhabit tropical waters while mature males relocate to high latitudes and only visit the 

lower latitudes to breed. Female and immature whales form cohesive social units that have been 

reported to last for years. We used satellite telemetry to determine associations between sperm 

whales in the Gulf of Mexico (GOM) and compared social structure to genetic relatedness of the 

monitored individuals. Geographic location of tagged sperm whales was used to estimate 

distance between individuals during simultaneous satellite transmissions. Association between 

individuals was determined from the distance between individuals. Two whales were considered 

associated in a particular day if the distance between their simultaneous locations was ≤ 20 km. 

Simple ratio coefficients of association were calculated between individuals. Additionally, 

genetic analyses of skin samples were conducted to determine gender of the individuals and 

relatedness among them. A social unit was identified among the whales tagged in 2002. No 

significant correlation was observed between genetic relatedness and association between 

individuals. Sperm whale social structure observed in the Gulf is similar to that described for 

other tropical regions (i.e. Galapagos Islands). Our results indicate that sperm whale social units 

in the GOM are not strictly matrilineal. 

Acknowledgments 

We are grateful to the cruise participants and the crew of the R/V Gyre. This ongoing research is 

supported by the Minerals Management Service under MMS Contract 1435-01-02-CA-85186. 

Dr. Joel Ortega is a post-doctoral research associate at the Oregon State University Marine 

Mammal Program. He received his Ph.D. from Texas A&M University in 2002. 

Dr. Bruce Mate holds an endowed chair at Oregon State University, where he directs the OSU 

Marine Mammal Program at the Hatfield Marine Science Center. He has served as: a Scientific 

Advisor to the U.S. Marine Mammal Commission and the U.S. Department of the Interior’s 

Outer Continental Shelf Development Program, a scientific expert to the International Whaling 

Commission and the United Nation Environmental Program, and a member of the International 

Union for the Conservation of Nature’s Species Survival Commission. He has studied the 

migrations of marine mammals since 1968 and pioneered the tracking of manatees, dolphins and 

large whales with satellite-monitored radio tags. With collaborators, his research group has 

tracked ten stocks of seven large endangered whale species in six different oceans/seas, including 

temperate, equatorial, Arctic, and Antarctic regions. His specialty is the identification and 

characterization of seasonal critical habitats for endangered whales and how they migrate 
264 

between them. An applied aspect of his research focuses on trying to reduce potential impacts of 

human activities on recovering endangered species. 

Dan Engelhaupt completed his Ph.D. at the University of Durham, England. His field of study 

includes the assessment of population structure and social structure for endangered species, with 

a particular emphasis on sperm whales. Over the past five years, as part of the Minerals 

Management Service sponsored SWAMP and SWSS projects, he has examined the genetic 

variation and social structure of endangered sperm whales with a particular focus on putative 

‘populations’ in the northern GOM, Mediterranean Sea and the North Atlantic Ocean using a 

suite of molecular techniques. Dr. Engelhaupt is collaborating with a number of other researchers 

to provide an accurate sperm whale dataset so that management can effectively oversee sperm 

whale populations that exist in areas of anthropogenic noise. 
265 

HABITAT CHARACTERIZATION OF SATELLITE-TRACKED SPERM WHALES IN 

THE GULF OF MEXICO 

Joel Ortega-Ortiz and Bruce Mate, Oregon State University 

Robert R. Leben, University of Colorado 

Douglas C. Biggs and Matthew K. Howard, Texas A&M University 

Physical habitat of sperm whales in the northern Gulf of Mexico (GOM) was studied by 

analyzing environmental variables for locations of individuals tracked with the aid of satellite 

transmitters. The present analysis includes data from 39 whales: 18 tagged in 2002, 15 in 2003, 

and six in 2004. Time between deployment and last satellite location ranged from 17 to 607 days 

and number of locations per tag ranged from three to 183. 

Movement paths of satellite-tracked whales were characterized, and each location was assigned 

to either one of two categories: meandering or transit. Ocean bottom depth and slope were 

determined for each satellite-determined whale location and comparisons were made between 

sex classes and movement types. Statistically significant differences were observed in the 

median values of bottom depth at locations for females and males (W = 5,0930, p-value < 0.01, n

= 798 and 214, Median = 884 and 1,171 meters, respectively). Median values of bottom slope 

were also different between females and males (W = 6,8546, p-value = 0.013, Median = 3.06 and 

2.39 degrees, respectively). Significant differences were observed in the median depth for 

locations assigned to meandering and transit move types (W = 11,9942, p-value < 0.01, n = 853 

and 338, Median = 895 and 698 meters, respectively). Median bottom slope was not different 

between meandering and transit. No significant differences were found in sea surface height 

(SSH) values between females and males. However, the median value of SSH was different 

between meandering and transit locations (W = 98,475, p-value < 0.01, Median = -3.86 and -7.12 

dynamic centimeters, n = 818 and 326, respectively). The mean value of SSH for all satellite 

locations (–4.64 dynamic cm) coincides with previous studies that found a higher occurrence of 

sperm whales in areas of cyclonic circulation and areas of confluence between cycloneanticyclone. Satellite-tracked female sperm whales were located more frequently on the upper 

continental slope of the northern GOM. Males were also located in this last region, but some 

tracked males moved into the central Gulf or over deeper waters with less steep bottom slope 

(i.e. lower continental slope and abyssal plain). The statistical differences observed in SSH at 

locations of meandering and transit move types could indicate that sperm whales have 

differential use for areas of the Gulf. Moreover, home range analysis showed that, although most 

of the tracked whales were tagged near and frequented the Mississippi Canyon (MC) and the 

Mississippi River Delta (MRD), there are differences between males and females, as well as 

among individuals, in the specific areas frequented during the year. A trend was observed for 

satellite-tracked whales to aggregate near the MC and MRD in the summer. While some 

individuals may spend several months in those areas, others disperse in different directions the 

rest of the year. 
266 

Acknowledgments 

We are grateful to the cruise participants and the crew of the R/V Gyre. This ongoing research is 

supported by the Minerals Management Service under MMS Contract 1435-01-02-CA-85186. 

Dr. Joel Ortega is a post-doctoral research associate at the Oregon State University Marine 

Mammal Program. He received his Ph.D. from Texas A&M University in 2002. 

Dr. Bruce Mate holds an endowed chair at Oregon State University, where he directs the OSU 

Marine Mammal Program at the Hatfield Marine Science Center. He has served as: a Scientific 

Advisor to the U.S. Marine Mammal Commission and the U.S. Department of the Interior’s 

Outer Continental Shelf Development Program, a scientific expert to the International Whaling 

Commission and the United Nation Environmental Program, and a member of the International 

Union for the Conservation of Nature’s Species Survival Commission. He has studied the 

migrations of marine mammals since 1968 and pioneered the tracking of manatees, dolphins and 

large whales with satellite-monitored radio tags. With collaborators, his research group has 

tracked ten stocks of seven large endangered whale species in six different oceans/seas, including 

temperate, equatorial, Arctic, and Antarctic regions. His specialty is the identification and 

characterization of seasonal critical habitats for endangered whales and how they migrate 

between them. An applied aspect of his research focuses on trying to reduce potential impacts of 

human activities on recovering endangered species. 

Robert Leben is an Associate Research Professor in the Department of Aerospace Engineering 

Sciences at the University of Colorado, Boulder. His research interests are satellite oceanography 

and computational fluid dynamics. 

Douglas Biggs is a Professor of Oceanography at Texas A&M University. In addition to his 

service as a co-PI on DGoMB, Biggs was a co-PI on MMS-sponsored NEGOM-COH and 

GulfCet-II projects and he is presently working to define the oceanographic habitat use by 

cetaceans in the NE Gulf of Mexico as part of an interagency MMS-ONR-NSF study known as 

the Sperm Whales Seismic Studies program (SWSS). 

Matthew Howard is an Assistant Research Scientist in the Department of Oceanography at Texas 

A&M University. 

 
267 

SEISMIC SURVEY ACTIVITY AND THE PROXIMITY OF S-TAGGED WHALES 

Martha H. Winsor and Bruce Mate, 

Marine Mammal Program, Oregon State University 

Introduction 

Researchers from Oregon State University’s Marine Mammal Program tagged sperm whales in 

the Gulf of Mexico (GOM) with satellite-monitored radio tags (S-tags) during June/July 2002 

and July 2003. The Argos Data Location and Collection System was used to obtain position data 

from the S-tags (Mate et al. 1997). These whale locations from the S-tags were compared to 

positions of active seismic vessels in the GOM in an attempt to determine whether satellitetracked sperm whales occurred less frequently than expected in the vicinity of active seismic 

vessels (a possible indication of vessel avoidance). High-quality locations (N=1,167) from S-tags 

on 33 sperm whales were correlated with 6,821 seismic lines from 6 June 2002 through 16 

August 16 2004. Seismic vessel information was provided by International Association of 

Geophysical Contractor members and included the start and end times and locations of central 

shot points for each seismic line. 

Methods 

Argos classifies high-quality locations as LC1, LC2, and LC3 with resolutions such that 68% of 

calculated locations are predicted to be within 350–1,000 m, 150–350 m, and <150 m, 

respectively, of the true position (Harris et al. 1990). All high-quality locations from the 33 Stagged whales were edited to eliminate erroneous data. Positions resulting in speeds between 

locations more than 15 k/h were eliminated as being above the maximum capability of the 

animal, and therefore suspect in validity. When a whale location occurred between the start and 

end time of a seismic line, the position of the central shot point at the time of the whale location 

was interpolated from the start and end locations; then the distance between the whale and 

central shot point was calculated. Only locations within 25 km of an active vessel were 

considered in this analysis under the assumption that behavioral changes would be more apparent 

closer to the vessels. 

We hypothesize that if there is no behavioral response to an active vessel, the distances between 

whales and seismic vessels should be randomly distributed. Conversely, if the distribution is 

non-random, it may be an indication of a response of the whales to the presence of an active 

seismic vessel. The distribution of distances was tested for randomness in two ways. The first 

method compared observed distances with expected distances, normalized to area, using a chisquare test for a significant deviation from randomness. The second method employed a Monte 

Carlo simulation of equivalent random data sets to compare with the observed data. Assumptions 

inherent in this analysis are that whale location accuracies are within Argos criteria and that 

temporal variation and vessel differences do not affect responses in significant ways. Also vessel 

speeds and headings were assumed to be constant so that interpolated positions between start and 

end locations were accurate. 
268 

Results 

A total of 30 high-quality locations from 12 animals were determined to be within 25 km of an 

active vessel (consisting of 53% LC1, 30% LC2 and 17% LC3 locations). The time differences 

between start of the seismic line and whale location varied from 0.65 h to 4.8 h (mean = 2.2 h; sd 

= 1.24 h). Distances were tabulated into 5 km classes (Table 1F.2). No distances were less than 5 

km and five of the 30 locations were 5 - 10 km from a vessel. When more than one observation 

was obtained from an individual, its contribution to the distance class was inversely weighted by 

the total number of observations for that animal. This weighting addressed possible effects of 

pseudoreplication (Machlis et al. 1985) maintaining a total sample size of 12 animals yet 

utilizing all the observations. 

Table 1F.2. Tabulation of the number of occurrences in each distance class for the observed data set and the 

expected number for an area-normalized randomly distributed data set (n=12). The mean and 

standard deviation of each distance class from a Monte Carlo simulation of randomly distributed 

locations (1,000 sets of 12 distances) and the number of sets with the same number of class values 

as the observed. 

Distance class 0-5 km 5-10 km 10-15 km 15-20 km 20-25 km 

Observed data set 

count (n=12) 

0 1.33 0.83 4.25 5.58 

Area-normalized 

randomly distributed 

count (n=12) 

0.48 1.44 2.4 3.36 4.32 

Mean (std dev) of 

Monte Carlo sets 

(n=1000) 

0.5 (0.71) 1.4 (1.16) 2.4 (1.41) 3.3 (1.5) 4.4(1.66) 

Monte Carlo sets1 

with value x 

597 

x=0 

330 

x=1 

196 

x=1 

206 

x=4 

128 

x=6 1

Number of simulated data sets out of 1,000 with same number of class values as the observed 

data set rounded to an integer 

Applying the first method, the expected number of observations out of 12, in each 5 km class, 

was calculated by normalizing to the proportion of area the class represented in a 25 km radius 

circle (Figure 1F.1). A chi-square test was performed comparing the observed frequencies with 

the normalized expected frequencies. There was no evidence (p-value = 0.71) that the data were 

non-randomly distributed. 

For the Monte Carlo simulation, 1,000 sets of 12 randomly created locations within a 25 km 

radius of a central point were tabulated into 5 km classes. Using 1,000 simulations is considered 

a realistic number of randomizations for determining significance at the 5% level (Manly 1997). 

A sample size of 12 was used instead of modeling the weighting of the observed data set so that 

comparisons could be made with discrete values. The number of sets, containing the same 

number of values as observed (rounded to the nearest integer value), was calculated. The average 

for each class was also compared (t-test) with the observed value (Table 1). There was no 

evidence that the observed set came from a non-random distribution of distances since all 

simulated set proportions were greater than 5% and all t-tests were non-significant (p-values > 

0.05). 
269 

Figure 1F.1. Comparison of the frequencies in 5 km classes of the observed distribution of distances (<25 km) 

between whales and active seismic vessels with expected values assuming a random distribution 

(n=12). 

Because of the relatively small sample size (12) used in the analysis, it is important to consider 

the potential power of the statistical tests. To determine if 12 values are sufficient to detect a 

non-random distribution, additional Monte Carlo simulations of varying sample sizes were 

performed. By increasing sample size, the percent of simulated data sets with the same value as 

the observed set decreases. Results indicate that a sample size of at least 75 is required to 

produce less than 5% of the sets with no distances less than 5 km; therefore, if an observed set of 

data consisting of 75 distances had no values less than 5 km, the data set would be considered 

non-randomly distributed at the 5% significance level. For the other distance categories, a 

sample size of at least 25 was required to produce less than 5% with values the same as the 

observed results. 

Discussion and Conclusions 

Although distances between whales and active vessels appear to be randomly distributed, these 

results cannot refute a possible behavioral response because of a lack of sufficient sample size. 

The number of individuals would need to be doubled to have the power to detect a non-random 

distribution from 5km and further. A much larger sample size (75) is needed for analysis closer 

than 5 km. An additional source of uncertainty is the lack of controlled positional errors from the 

Argos-derived locations. Future studies would greatly benefit from the use of GPS derived 

locations and expanded sampling efforts. 

0

3

6

0-5 5-10 10-15 15-20 20-25

Radial distance from Vessel (k)

Number of whale locations

Observed

Expected
270 

References 

Harris, R.B., S.G. Fancy, D.C. Douglas, G.W. Garner. S.C. Amstrup, T.R. Mccabe and L.F. 

Pank. 1990. Tracking wildlife by satellite: Current systems and performance. U.S. Fish 

and Wildlife Services, Fish and Wildlife Technical Report #30. 52pp. 

Machlis, Z., P.W.D. Dodd and J.C. Fentress 1985. The pooling fallacy: Problems arising when 

individuals contribute more than one observation to the data set. Zeitschrift für 

Tierpsychology 68:201–214. 

Manly, B.F.J. 1997. Randomization, Bootstrap and Monte Carlo Methods in Biology. 

Washington, DC: Chapman and Hall/CRC. 399 pp. 

Mate, B.R., S.L. Nieukirk and S.D. Kraus. 1997. Satellite-monitored movements of the northern 

right whale. Journal of Wildlife Management 61:1393–1405. 

Martha H. Winsor has been a research assistant for the Marine Mammal Program of Oregon 

State University for 18 years specializing in statistical analysis and GIS. She also worked as an 

oceanographer with the U.S. Naval Oceanographic Office for eight years and contracted as a 

statistician with the U.S. Environmental Protection Agency. Her education includes a Sc.B. in 

aquatic biology from Brown University and a M.S. in applied statistics from Oregon State 

University. 

Dr. Bruce Mate holds an endowed chair at Oregon State University, where he directs the OSU 

Marine Mammal Program at the Hatfield Marine Science Center. He has served as: a Scientific 

Advisor to the U.S. Marine Mammal Commission and the U.S. Department of the Interior’s 

Outer Continental Shelf Development Program, a scientific expert to the International Whaling 

Commission and the United Nation Environmental Program, and a member of the International 

Union for the Conservation of Nature’s Species Survival Commission. He has studied the 

migrations of marine mammals since 1968 and pioneered the tracking of manatees, dolphins and 

large whales with satellite-monitored radio tags. With collaborators, his research group has 

tracked ten stocks of seven large endangered whale species in six different oceans/seas, including 

temperate, equatorial, Arctic, and Antarctic regions. His specialty is the identification and 

characterization of seasonal critical habitats for endangered whales and how they migrate 

between them. An applied aspect of his research focuses on trying to reduce potential impacts of 

human activities on recovering endangered species. 
271 

BRIEF OUTLINE OF SPERM WHALE AIRGUN CONTROLLED 

EXPOSURE EXPERIMENTS (CEES) 

Peter L. Tyack, Biology Department, Woods Hole Oceanographic Institute 

There are two classes of adverse impacts that sound may have on marine mammals. If an 

individual is close to an intense source, it may be injured with hearing loss or other trauma. 

Behavioral or more subtle physiological responses to sound may occur at lower exposure levels 

and greater ranges. Injury can best be studied with captive animals under controlled settings 

using harmless experimental methods such as Temporary Threshold Shift. Once safety zones 

have been established, the primary method for protecting animals from injury involves 

monitoring and preventing harmful exposures. Behavioral disturbance is more difficult to 

monitor and mitigate. If exposure to noise reduces the effectiveness of foraging or 

communication by a few tens of percent for much of the population for much of the time, it 

could hinder the recovery of endangered populations or reduce the growth of other populations 

without injuring any individuals. 

Before the SWSS research was initiated, there were several reports indicating that sperm whales 

avoided airguns at ranges of 50 km (Mate et al. 1994) and might reduce their vocalization rates at 

ranges of 600-1,000 km (Bowles et al. 1994). These anecdotal accounts raise concern, but are 

problematic for the following reasons: 

• Bias in animals available for study: 

⎯ Would anyone publish cases of no reaction? 

⎯ Lower probability of detecting animals by passive acoustic monitoring if animals 

have reacted by silencing 

• Exposure at the animal can seldom be accurately measured or estimated 

• Difficulty in structuring observations to assess how response may vary with exposure 

• Scarcity of information to assess biological significance of any reactions observed 

• Difficulty in assessing statistical power of study when no reactions observed 

Tyack et al. (2004) describe an experimental method using controlled exposures to resolve some 

of the problems from uncontrolled observations. Many of these controlled exposure experiments 

have the following features: 

• Selection of subject randomly prior to exposure 

• Use of specific protocol to test for specific kinds of reaction related to adverse impact 

• Measurements of behavior pre-, during, and post- exposure. Individual is its own control 

• Use of low exposure levels at beginning, with increase after evaluation of reaction 

indicates low risk 

• Avoid exposures high enough for risk of injury 
272 

Johnson and Tyack (2003) describe a new tag, called the D-tag, that was designed to sample 

sound and behavior of the tagged whale. The tag was also designed to enable CEEs to deep 

diving toothed whales by allowing experimenters to 

 1. Track behavioral responses of marine mammals, especially deep divers, throughout their 

dives 

 2. Measure acoustic exposure directly at the whale 

 3. Improve understanding of functions and costs of behaviors to infer biological significance of behavioral disruption 

 4. Develop dose:response function by measuring received level of stimulus at whale while 

also measuring behavioral and physiological responses 

The initial WHOI D-tag/CEE proposal to SWSS involved the following elements: 

Initial Proposed Plan 

• Three-year: one 6-week or two 3-week cruises per year 

• Stimuli: Two control: nothing or codas; Primary airgun: soft start or ramp up 

• In ten days of seismic vessel, hope for four to six experiments with one to two subjects 

• Start RLs in 120–140 dB range. Move up if only minor responses observed 

• Locations: Include diversity of sites. Need to move to ensure new subjects 

The actual research completed involved the following for comparison: 

Actual Research 

• Two 3-week cruises total 

• One coda playback prime focus on airguns 

• Four airgun CEE subjects per year for each of two years 

• RLs primarily in <120-147 dBrms range 

• Problems finding new whales away from ongoing commercial seismic 

It is impossible for any experiment or monitoring method to prove that there was no adverse 

impact to marine mammals, because many potential impacts are very difficult to detect. What 

CEEs can do is test specific hypotheses about potential impacts. We selected measures based 

upon likely biological significance to the population. The critical parameters of individuals that 

affect populations are habitat usage, growth, survival, and reproduction. Some of the behavioral 

parameters intimately linked to these parameters include avoidance, foraging, and mating. The 

WHOI D-tag CEEs under SWSS were designed to evaluate effects of airguns on avoidance, 

foraging, and communication of sperm whales in the northern Gulf of Mexico (GOM). Other 

members of the WHOI team will discuss baseline behavior of sperm whales, how we measured 

acoustic exposure, modeling of acoustic propagation to explain unexpected properties of airgun 

sounds, and reactions to airguns in CEEs. 

Table 1F.3summarizes the results of the cruises providing data for these presentations: 
273 

Table 1F.3. Summary of cruise results. 

Acknowledgments 

We thank the field teams and ship crews of SWAMP, SWSS, Sirena and RV Delaware cruises, 

the staff of IAGC, LDEO, MMS, NATO Undersea Research Centre, NOAA, TAMU and WHOI. 

We regret that too many people were involved to allow them to be named individually. Work 

supported by contract #1435-01-02-CA-85186 from the U.S. Minerals Management Service, 

ONR and WHOI internal funds for tag development, NSF for RV Ewing support, NOAA for RV 

support, IAGC and industry for providing source vessels. PJOM Fellowship support from the 

Royal Society. Work conducted under NMFS research permits 981-1578 and 981-1707-00 

issued by the U.S. National Marine Fisheries Service to Peter L. Tyack. The Woods Hole 

Oceanographic Institution Animal Care Use Committee approved this research. 

References 

Bowles, A.E., M. Smultea, B. Würsig, D. DeMaster, and D. Palka. 1994. Relative abundance and 

behavior of marine mammals exposed to transmissions from the Heard Island Feasibility 

Test. Journal of the Acoustical Society of America 96:2469–2484. 

Johnson M. and P. L. Tyack. 2003. A digital acoustic recording tag for measuring the response 

of wild marine mammals to sound. IEEE Journal of Oceanic Engineering 28:3–12. 

Mate, B.R., K.M. Stafford, and D.K. Ljungblad. 1994. A change in sperm whale (Physeter 

macrocephalus) distribution correlated to seismic surveys in the Gulf of Mexico. Journal 

of the Acoustical Society of America 96(5, part 2):3268–3269. 

Tyack, P, J. Gordon, and D. Thompson. Controlled exposure experiments to determine the 

effects of noise on large marine mammals. 2004. Marine Technology Society Journal 

37(4): 41-53. 

Peter Tyack is Senior Scientist and Walter A. and Hope Noyes Smith Chair in the Biology 

Department of the Woods Hole Oceanographic Institution. He has an A.B summa cum laude 

from Harvard College and a Ph.D. from Rockefeller University. His research focuses on acoustic 

communication and social behavior of cetaceans. 

Cruise Swss 02 Swss 03 Swss RV 

Delaware Total 

Whales tagged 19 11 12 42 

Hours 76 69 28 173 

# Dives 65 50 18 133 

CEEs 2; 4 subjects 3; 4 subjects NA 5; 8 subjects 

Max RLs 134–144 dBrms 146–147 dBrms NA 
274 

DIVING, FORAGING, AND VOCAL BEHAVIOR OF SPERM WHALES 

Stephanie L. Watwood, Mark P. Johnson, Peter T. Madsen, and Peter L. Tyack, 

Woods Hole Oceanographic Institution 

Patrick J.O. Miller, St. Andrews University, Scotland 

Digital recording tags (‘D-tags’) were used to describe the diving and vocal behavior of sperm 

whales during 198 complete and partial foraging dives made by 37 individual whales in the 

North Atlantic Ocean, Gulf of Mexico (GOM), and Ligurian sea. Figure 1F.2 shows a typical 

sperm whale dive profile recorded from the D-tag. Overall, there was little difference in general 

diving and foraging behavior among regions, but high individual variability within regions. 

Whales dove to average maximum depths of 985 (124.3) m in the North Atlantic, 644 (123.4) m 

in the GOM, and 827 (60.3) m in the Ligurian sea. The deepest dive was to 1,202 m by a whale 

in the North Atlantic. An average dive cycle consisted of a 45- (6.3) minute dive with a 9- (3.0) 

minute surface interval, with no significant differences among regions. Whales spent 72% of 

their time in foraging dive cycles in the North Atlantic and GOM, as compared to 98% of their 

time in the Ligurian sea. This was due to limited observed social behavior in the Ligurian sea. 

Figure 1F.2. Dive profile of a sperm whale from the Gulf of Mexico. 
275 

The vocal behavior of sperm whales was used as an indication of foraging activity. The 

production of regular clicks was used to determine when sperm whales could be searching for 

prey patches. Regular clicks have properties suited for long range sonar suited for detection of 

cephalopod prey (Madsen et al. 2002), and modeling with the sonar equation suggests that sperm 

whales may be able to detect prey patches at a range of more than 500 m (Møhl et al. 2003). 

Whales produced regular clicks for 81 (4.1) % of a dive and 64 (14.6) % of the descent phase. 

The occurrence of buzzes (originally coined “creaks”) was used as an indicator of the foraging 

phase of a dive (Miller et al. 2004). Sperm whales descended a mean of 392 (144) m in depth 

from the start of regular clicking to the first buzz, which supports the hypothesis that regular 

clicks function as a long-range biosonar. There were no significant differences in foraging phase 

duration (28 (6.0) minutes) or percentage of the dive duration in the foraging phase (62 (7.3) %) 

between the three regions, with an overall average diving efficiency of 0.53 (0.05). Whales 

maximized their time in the foraging phase by minimizing transit time to and from the foraging 

depth. The similarity in foraging and diving behavior reported here suggests that general patterns 

of sperm whale behavior are similar in different regions. However, the data analyzed here only 

provide a brief image of the behavior of individual sperm whales during a limited time frame. 

These data do not provide information on differences in long-term foraging success, overall 

fitness of individuals, or the health of populations in different regions. 

Acknowledgments 

The authors wish to thank the science parties on the research cruises during which these data 

were collected (unfortunately too numerous to list), and to Dan Englehaupt and Amy Beier for 

tissue handling and genetic analysis. The data were collected during collaborative work with 

NOAA Fisheries Southwest Science Center and NATO Undersea Research Centre. Tom Hurst, 

Alex Shorter, and Jim Partan were instrumental in developing D-tag hardware and software. 

Funding was provided under the Office of Naval Research grant numbers N00014-99-1-0819 

and N00014-02-10187, Minerals Management Service Cooperative Agreements numbers 1435-

01-02-CA-85186 and NA87RJ0445, and the Strategic Environmental Research and Development 

Program (SERDP) grant number D8CA7201C0011. PJOM was supported by a Royal Society 

Fellowship. All approaches to the animals for tagging were made following the conditions of 

NMFS research permits 981-1578 and 981-1707. This research was approved by the Woods 

Hole Oceanographic Institution Animal Care and Use Committee. 

References 

Madsen, P.T., M. Wahlberg, and B. Møhl. 2002. Male sperm whale (Physeter macrocephalus) 

acoustics in a high-latitude habitat: Implications for echolocation and communication. 

Behavioral Ecology and Sociobiology 53:31–41. 

Miller, P.J.O., M.P. Johnson, and P.L. Tyack. 2004. Sperm whale behaviour indicates the use of 

rapid echolocation click buzzes “creaks” in prey capture. Proceedings of the Royal 

Society of London, B. 271:2239–2247. 

Møhl, B., M. Wahlberg, P.T. Madsen, A. Heerfordt, and A. Lund. 2003. The monopulsed nature 

of sperm whale clicks. Journal of the Acoustical Society of America 114:1143–1154. 
276 

Stephanie Watwood completed her Ph.D. in the MIT/Woods Hole Oceanographic Institution 

Joint Program with Peter Tyack in 2003. Her thesis work focused on the social behavior and 

vocal communication of male bottlenose dolphins in long-term stable alliances. She is currently a 

post doc at Woods Hole studying the diving and social behavior of sperm whales. 

Dr. Patrick Miller received a Ph.D. in Biological Oceanography jointly from the Massachusetts 

Institute of Technology and the Woods Hole Oceanographic Institution in 2000 with a thesis on 

the acoustic communication of fish-eating killer whales. After the Ph.D., Patrick had joint 

postdoctoral positions at MIT and WHOI during which he worked closely on the D-tag project. 

In 2002, Patrick was awarded a Royal Society International Research Fellowship to study the 

effects of sound on the ecology of deep-diving mammals at the University of St. Andrews in 

Scotland. Patrick has worked on several studies of the effects of noise on marine mammals, 

including the Haro Strait project, the LFA Scientific Research Program, and SWSS; and he is 

author of several papers on sperm whale behavior and physiology. 

Mark Johnson is a Research Engineer at Woods Hole Oceanographic Institution. Dr. Johnson has 

a Ph.D. in electrical engineering from the University of Auckland, New Zealand. His research 

interests include real-time digital signal processing for acoustics applications in communications, 

environmental monitoring, and marine mammology. 

Peter T. Madsen graduated from University of Aarhus in 2002 after studying physiological 

acoustics under Dr. Bertel Møhl. He was post doc in Dr. Roger Payne’s lab in 2002–2003, and 

went on as a post doc to Dr. Peter Tyack’s lab at the Woods Hole Oceanographic Institution in 

2003. His areas of research includes biosonar, physiological acoustics and effects of man-made 

noise on marine mammals. 

Peter Tyack is Senior Scientist and Walter A. and Hope Noyes Smith Chair in the Biology 

Department of the Woods Hole Oceanographic Institution. He has an A.B. summa cum laude 

from Harvard College and a Ph.D. from Rockefeller University. His research focuses on acoustic 

communication and social behavior of cetaceans. 
277 

THE SOUNDS OF AIRGUNS AS RECORDED ON SPERM WHALES AND METHODS 

TO QUANTIFY ACOUSTIC EXPOSURE 

Peter T. Madsen, Mark P. Johnson, and Peter L. Tyack, 

Woods Hole Oceanographic Institution 

Patrick J.O. Miller, St. Andrews University, Scotland 

Sound energy radiated off the axis of an airgun array may be insignificant when compared to the 

peak pressures generated on the acoustic axis, and may accordingly be dismissed as having little 

effect on marine mammals. However, the absolute values of these by-products may be of 

considerable magnitude and at frequencies that are significantly higher than those of the 

idealized on-axis pulse. So what is considered a relatively low level horizontal by-product from 

an operational perspective may have absolute levels at frequencies for which the auditory system 

of the exposed animal is most sensitive and thereby may lead to fitness reduction through 

threshold shifts, behavioral disruption or masking. Here we report from an ongoing analysis of 

acoustic data recorded by onboard D-tags on sperm whale (Physeter macrocephalus) during 

feasibility tests of using controlled exposures in concert with sound recording tags. This study 

provides the first data on the actual sound field received by free-ranging toothed whales during 

exposure to an anthropogenic noise source. We demonstrate that sperm whales receive several 

pulses with very different temporal and spectral properties for each firing cycle of the airgun 

array. 

All tags were calibrated before and after deployment. The pre-whitening filter was compensated 

for during analysis yielding a flat (within ±1dB) frequency response from 0.045 kHz to 16 kHz, 

respectively. Received levels (RL) for mitigation of cetacean sound exposure are often given by 

root-mean-square sound pressure levels (RLrms). This measure, however, does not represent the 

energy of the noise pulse, and it does not prevent exposure to high-peak pressures, so we have 

also quantified the seismic pulses by peak-peak (RLpp), and sound exposure level (RLE). For 

calculation of rms levels of a transient signal, we have adopted the 90% energy approach. The 

relative energy is computed in a window around the seismic pulse, and the duration (τ) is defined 

by the sample interval (0:T) containing 90% of the energy content in the window. 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

∫ p t dt

T

T

( ) 1 10log

0

2

 [p(t)=instantaneous pressure] 

The sound exposure level (also called energy flux density) (RLE) is given by the rms intensity 

integrated over the duration τ: 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

∫ p t dt

T

10log ( )

0

2

 [p(t)=instantaneous pressure]
278 

Not all CEEs rendered a sufficient SNR to allow for analysis of all pulses, and some pulses were 

discarded due to overlap with sperm whale clicks. In an attempt to accommodate how a 

mamalian ear process transients, all pulses have been filtered according to the NMFS Gweighting criterion for mid-frequency odontocetes. Figure 1F.3 provides the distribution of 

received levels in c-weighted rms levels for all pulses analyzed. 

Figure 1F.3. Acoustic exposure cycles. 

The acoustic exposure of the animal consists of two or more temporally separated pulses with 

different properties for every duty cycle of the air gun array. These are the result of a direct 

arrival followed by a series of pulses generated by multipath propagation in water and sediment. 

Figure 1F.4a provides an example of such a multipulsed event recorded on a sperm whale at 15 

meters depth. The first arrival is a well-defined transient with a short duration of around 50 μsec 

and with most energy between 0.5 and 2.5 kHz (Figure 1F.4b). Note how there is energy all the 

way up to the Nyquist frequency at 16 kHz. The second arrival is a much more reverberant pulse 

that arrives some 500 msec after the first arrival. The waveform is smeared out in time and is 

likely the combined effect of a bottom reflection and energy traveling in the sediment. While this 

pulse also contains energy at high frequencies, it is dominated by energy below 200 Hz. 
279 

Figure 1F.4. (A) Waveform of the first arrival (direct) and a bottom bounce/bottom ducted second arrival as 

received by a sperm whale at 30 meters depth. (B) Spectrogram of the waveform of A. FFT size 

1024, Hann windowed data, 90% overlap. 

Thus, it is demonstrated that sperm whales are exposed to a series of pulses with different 

spectral, energetic and temporal properties for each duty cycle of the air gun array. The analysis 

shows that some of the direct arrivals when the whale is close to the surface have dominant 

energy at much higher frequencies than currently reported or modeled for air gun arrays. While 

this energy is radiated off the axis of the array, the absolute levels of these high frequency pulses 

may reach levels of more than 140 dB re 1μPa (rms). This points to a hereto overlooked potential 

problem of airguns producing significant energy at frequencies that may evoke significant 

sensation levels in toothed whales that all have their most sensitive range of hearing outside the 

0-1,000 Hz band modeled by the industry, and therefore not normally considered sensitive to 

airgun pulses. 

Peter T. Madsen graduated from University of Aarhus in 2002 after studying physiological 

acoustics under Dr. Bertel Møhl. He was post doc. in Dr. Roger Payne’s lab in 2002–2003, and 

went on as a post doc to Dr. Peter Tyack’s lab at the Woods Hole Oceanographic Institution in 

2003. His areas of research includes biosonar, physiological acoustics and effects of man-made 

noise on marine mammals. 
280 

Mark Johnson is a Research Engineer at Woods Hole Oceanographic Institution. Dr. Johnson has 

a Ph.D. in electrical engineering from the University of Auckland, New Zealand. His research 

interests include real-time digital signal processing for acoustics applications in communications, 

environmental monitoring, and marine mammology. 

Peter Tyack is Senior Scientist and Walter A. and Hope Noyes Smith Chair in the Biology 

Department of the Woods Hole Oceanographic Institution. He has an A.B. summa cum laude 

from Harvard College and a Ph.D. from Rockefeller University. His research focuses on acoustic 

communication and social behavior of cetaceans. 

Dr. Patrick Miller received a Ph.D. in Biological Oceanography jointly from the Massachusetts 

Institute of Technology and the Woods Hole Oceanographic Institution in 2000 with a thesis on 

the acoustic communication of fish-eating killer whales. After the Ph.D., Patrick had joint 

postdoctoral positions at MIT and WHOI during which he worked closely on the D-tag project. 

In 2002, Patrick was awarded a Royal Society International Research Fellowship to study the 

effects of sound on the ecology of deep-diving mammals at the University of St. Andrews in 

Scotland. Patrick has worked on several studies of the effects of noise on marine mammals, 

including the Haro Strait project, the LFA Scientific Research Program, and SWSS; and he is 

author of several papers on sperm whale behavior and physiology. 
281 

PRELIMINARY MODELING OF D-TAGS ACOUSTIC ARRIVALS FROM 

THE GULF OF MEXICO IN 2002 AND 2003 

James F. Lynch, Stacy DeRuiter, Peter L. Tyack, Arthur Newhall, and 

Ying-Tsong Lin, Woods Hole Oceanographic Institution 

The modeling effort we discuss centers on observations from summer 2002 and summer 2003 

controlled exposure experiments in the Gulf of Mexico (GOM). The goal of the experiments was 

to investigate the effects of seismic airgun noises on sperm whale foraging behavior. Data were 

collected by placing D-tag recording devices on the backs of free-ranging sperm whales before, 

during, and after controlled exposure to airgun array sounds. Acoustic data from the GOM study 

include recordings of airgun noises at various ranges and water depths. Initial analyses of the 

data indicate variable frequency content and variable relative amplitude of the airgun arrivals 

recorded on the D-tags. We have attempted to explain these observations using acoustic models 

which include ray theory, narrowband normal mode theory, and broadband and narrowband 

parabolic equation codes. 

We first discuss the 2002 data. During summer 2002, the sound speed profile, as measured both 

by CTDs and XBTs, showed the presence of a strong and persistent surface acoustic duct 

extending down to ~30m. Such ducts are capable of efficiently transmitting high frequency 

sounds between sources and receivers within the duct, and indeed that seemed to be the case in 

2002. The source was at about 7m depth, well within the duct. Spectrograms of airgun sounds 

recorded when whales were near the surface (see Figure 1F.5) showed high frequency (~500–

5,000 Hz) first arrivals, while recordings from deeper depths did not. Moreover, the first arrival 

did not show significant energy below 300 Hz, which we calculated from normal mode theory 

was the cutoff frequency for the lowest frequency mode trappable by the duct. Theory and 

experiment thus agree well for the ducted arrival in this case. Using simple ray theory, we also 

predict a single bottom reflected arrival 0.3 seconds after the ducted arrival, which is seen clearly 

in the data. This arrival should not show much high frequency content, and indeed (looking at 

Figure 1F.5) it does not. There is also a second (in time) arrival seen in the data, which has both 

high and low frequency content, and this might be a head wave, which our simple modeling does 

not include to date. This will be an interesting arrival to model. 

We next discuss the 2003 data. In this case, there is no significant surface duct, and indeed 

spectrograms of the D-tags arrivals do not show the high frequency content in the arrivals that 

one sees in the 2002 data. Simple ray theory and also broadband parabolic equation calculations 

seem to be adequate to describe the arrival structures that are seen in the D-tags data. As these 

data were from greater range, we do not see a head wave arrival, either, as this type of wave 

decays more rapidly with range. 

Looking toward the future, we will be examining not just the arrival time structure with our 

models, but the amplitude structure as well. Interesting phenomena such as head waves will be 
282 

examined, and we will certainly be investing more serious efforts into looking at the effects of 

near-surface oceanographic sound ducts. 

Due to surface

ducting effect, 

low-frequency 

sound is cut off.

One bottom bounce 

Figure 1F.5. Airgun signal in the 2002 D-tags data. 

James F. Lynch is Senior Scientist in the Acoustical Oceanography Group of the Department of 

Applied Ocean Physics and Engineering at Woods Hole Oceanographic Institution and holds the 

Robert Morse Senior Scientist Chair at WHOI. He has a B.S. from Stevens Institute of 

Technology and a Ph.D. from the University of Texas. His research interests are in underwater 

acoustics, shallow water acoustics, arctic acoustics, acoustic tomography, and high frequency 

backscatter from particles. 

Stacy DeRuiter is a graduate student in the MIT/WHOI Joint Program in oceanography and 

oceanographic engineering. 

Peter Tyack is Senior Scientist and Walter A. and Hope Noyes Smith Chair in the Biology 

Department of the Woods Hole Oceanographic Institution. He has an A.B. summa cum laude 

from Harvard College and a Ph.D. from Rockefeller University. His research focuses on acoustic 

communication and social behavior of cetaceans. 
283 

Arthur Newhall is a Research Specialist in the Acoustical Oceanography Group at Woods Hole 

Oceanographic Institution. He has a B.S. in mathematics from the University of Maine. His 

research interests include underwater acoustics, acoustic propagation modeling, acoustical 

oceanography, acoustic backscattering, data analysis, and computer programming and 

administration. 

Ying-Tsong Lin is a Postdoctoral Scholar in applied ocean physics and engineering at Woods 

Hole Oceanographic Institution. He has a Ph.D. in engineering science and ocean engineering 

from National Taiwan University. His research interests include acoustical oceanography; 

geoacoustic inversion; underwater acoustic modeling and signal processing; and uncertainty 

analysis. 
284 

CONTROLLED SEISMIC AIRGUN EXPOSURES: EFFECTS ON THE MOVEMENT 

AND FORAGING BEHAVIOR OF SPERM WHALES 

Patrick J. O. Miller, St. Andrews University, Scotland 

Mark P. Johnson, Peter L. Tyack, Peter T. Madsen, and Stephanie L. Watwood, 

Woods Hole Oceanographic Institution 

We conducted a set of five controlled exposure experiments (CEEs) on eight sperm whales 

tagged with D-tags (four in 2002; four in 2003). After the tags were attached, a pre-exposure data 

collection period ensued, followed by a half-hour ramp-up period, then a full-array period when 

all the airguns were firing, and finally a post-exposure period when all guns were turned off. We 

included pre- and post-exposure data within 90 minutes of an airgun firing. For 2002 data, one to 

two dives were recorded after tag attachment, while in 2003 ramp-up started after three to eight 

dives were made after the tag was attached. Here we report on the whales’ movement relative to 

the source vessel and the foraging behavior of the tagged sperm whales by exposure condition. 

Data recorded by the tag were converted to animal orientation, whale-frame pitching (which 

reflect fluking movements by the whale; Miller et al., 2004b), calibrated depth, and the 

associated audio record (Johnson and Tyack, 2003). Combining the continuous orientation 

record with an estimate of whale speed and current speed and direction, we constructed a 3-D 

pseudotrack of the whales’ movement during the experiments. The accuracy of the track was 

checked against whale fixes made from the observation vessel and was good in all cases except 

one, where insufficient sightings of the shale were obtained and for which some data blocks at 

the start of the tag record were not decodable due to a software error. The vocal behavior of 

sperm whales was used as an indication of foraging activity, with the production of buzzes 

(“creaks”) indicative of a prey-capture attempt (Miller et al. 2004a). As reported by Madsen, 

maximum received sound levels at the whales ranged from 142-147 dB re 1μPa RMS, corrected 

for the predicted hearing sensitivity of the sperm whale with NMFS c-weighting. 

To test whether whales avoided the airgun source, the direction-of-movement of each whale was 

scored over a 30-minute period in pre-exposure, ramp-up and full-array conditions. Circular 

statistics were used to compare the movements of each relative to the airgun source vessel and to 

each whale’s previous direction of movement (Zar 1984). Movement before exposure relative to 

that during ramp-up was non-randomly distributed (Rayleigh r = 0.92, z = 5.9, P<0.001), but was 

statistically identical to movement in the pre-exposure intervals (mean difference 95% CI -12.2o 

to 36.0o). Likewise, movement during full-array conditions was statistically equivalent to that in 

combined pre-exposure and ramp-up intervals (Rayleigh r = 0.94, z = 6.1, P<0.001) mean 

difference 95% CI (-18.3o to 31.9o). In contrast, whale movement was distributed randomly 

relative to the source bearing in both ramp-up (Rayleigh r = 0.58, P>0.10) and full-array 

conditions (r = 0.46, P>0.20). 

Seven of the eight whales made at least one deep dive in all three conditions, while the remaining 

whale (sw173b) rested at the surface for an unusually long interval, diving immediately 
285 

following the final airgun transmission in that experiment. Resting bouts as made by sw173b 

have been observed on ten other occasions, with durations never exceeding two hours while the 

bout made by sw173b was over four hours duration. This whale also received the most intense 

received levels of the source. One other whale (sw253a) switched to a non-foraging shallow dive 

that lasted until the transmissions stopped, after which it resumed deep diving. These 

observations suggest that some whales might respond to sound exposure by disrupting their 

foraging dives and resting at the surface. 

Foraging behavior of the seven whales that made at least one deep dive in all conditions was 

assessed as a function of exposure condition. We used an energy-budget model to define 

response parameters likely to be of biological significance (Figure 1F.6). Whale-specific pitching 

energy reflects fluking movements of the whale and was therefore used as a measure of 

locomotion cost (Miller et al. 2004b), while buzz-rates (“creaks”) as a metric of prey-encounter 

and thereby feeding rate (Miller et al. 2004a). 

Figure 1F.6. A simple energy model of the sperm whale showing energy input from food, and various energy 

outputs for locomotion (green), basal metabolism (blue), and energy for growth and 

reproduction which are critical for maintenance of the health of an animal population (red). 

Analysis of buzz-rates and whale-specific pitching energy from all D-tag deployments on sperm 

whales revealed that both were significantly reduced during the first dive after tag attachment 

relative to subsequent dives. Data were only recorded for one to two dives following tagging 

before playback starting during the CEEs conducted in 2002, so the pre-exposure period for 

those subjects was not long enough to represent post-tagging baseline. Because of this problem, 

and to assure that equal sample sizes were represented in all conditions, we had to remove the 
286 

pre-exposure condition entirely from the analysis. Ramp-up as an exposure condition was also 

not considered as it consists of a mix of very low-level transmissions at the start increasing to 

full array over a 25-30 minute period. Therefore, all of our analyses only compared full-array 

versus post-exposure conditions. The bottom-phase of foraging dives was divided into blocks of 

roughly ten-minute duration, as autocorrelation analyses determined that ten-minute blocks were 

sequentially independent. The effect of exposure condition was statistically tested using a mixedmodel two-way ANOVA in which whale id was treated as a random factor (reflecting the fact 

that whales were chosen at random from the population) while exposure condition was treated as 

a fixed factor (Zar 1984). 

Whale-specific pitching energy was 11% lower in the full-array condition relative to the 

subsequent post-exposure condition (F1,6 = 6.80, P < 0.05). Similarly, buzz rates were 24% lower 

in the full-array condition relative to post-exposure, but this effect was not statistically 

significant at the 0.05 level (F1,6 = 2.62, P = 0.16). 

The results of these analyses of the CEE data suggest that reduced foraging effort invested by 

sperm whales coincided with the presence of seismic airgun transmissions. Two of the eight 

whales appeared to avoid making deep foraging dives for some interval during the exposure 

period, and across all subjects, whale-specific pitching energy during the bottom phase of dives 

was lower during the full-array condition than in the post-exposure condition. Prey-encounters 

during the bottom phase of deep dives, as measured by buzzes, also had lower rates during the 

full-array condition, but more variability was observed for this effect and we cannot reject a null 

hypothesis of no effect at the 0.05 level. The tested whales did not show horizontal avoidance of 

the airgun sources during transmissions, though, but continued along their previous direction of 

movement. 

In subsequent work, we will analyze whale-specific pitching energy and buzz rates to describe 

more fully these metrics of foraging activity, and attempt to relate these metrics more precisely 

to predicted energy flows into and out of a whale. We will also combine the foraging effort and 

prey-encounter rates of both deep-diving and non deep-diving subjects to obtain a more complete 

understanding of how the energy flows changed in relation to the presence or absence of airgun 

transmissions. Finally, we plan to explore how short-term changes in foraging energetics (which 

can be measured in controlled experiments such as the CEEs reported here) might have broader 

population-level consequences (NRC 2005). 

Acknowledgments 

The authors wish to thank the science parties on the research cruises during which these data 

were collected (unfortunately too numerous to list), and to Dan Englehaupt and Amy Beier for 

coordination of ship movement during the CEEs, tissue handling, and genetic analysis. Tom 

Hurst, Alex Shorter, and Jim Partan were instrumental in developing D-tag hardware and 

software. PJOM was supported by a Royal Society Fellowship. All approaches to the animals for 

tagging were made following the conditions of NMFS research permits 981-1578 and 981-1707. 

This research was approved by the Woods Hole Oceanographic Institution Animal Care and Use 

Committee. 
287 

References 

Johnson, M. and P.L. Tyack. 2003. A digital acoustic recording tag for measuring the response 

of wild marine mammals to sound. IEEE Journal of Oceanic Engineering 28:3–12. 

Miller, P.J.O., M.P. Johnson, and P.L. Tyack. 2004a. Sperm whale behaviour indicates the use of 

rapid echolocation click buzzes “creaks” in prey capture. Proceedings of the Royal 

Society of London, B. 271:2239–2247. 

Miller, P. J. O., M.P. Johnson, P.L. Tyack, and E.A. Terray. 2004a. Swimming gaits, passive 

drag, and buoyancy of diving sperm whales (Physeter macrocephalus). Journal of 

Experimental Biology 207:1953–1967. 

NRC (National Research Council). 2005. Marine Mammal Populations and Ocean Noise: 

Determining when Noise Causes Biologically Significant Effects. Washington, DC: 

National Academies Press. 

Zar, J. H. 1984. Biostatistical Analysis. Englewood Cliffs, NJ: Prentice-Hall. 

Dr. Patrick Miller received a Ph.D. in Biological Oceanography jointly from the Massachusetts 

Institute of Technology and the Woods Hole Oceanographic Institution in 2000 with a thesis on 

the acoustic communication of fish-eating killer whales. After the Ph.D., Patrick had joint 

postdoctoral positions at MIT and WHOI during which he worked closely on the D-tag project. 

In 2002, Patrick was awarded a Royal Society International Research Fellowship to study the 

effects of sound on the ecology of deep-diving mammals at the University of St. Andrews in 

Scotland. Patrick has worked on several studies of the effects of noise on marine mammals, 

including the Haro Strait project, the LFA Scientific Research Program, and SWSS; and he is 

author of several papers on sperm whale behavior and physiology. 

Mark Johnson is a Research Engineer at Woods Hole Oceanographic Institution. Dr. Johnson has 

a Ph.D. in electrical engineering from the University of Auckland, New Zealand. His research 

interests include real-time digital signal processing for acoustics applications in communications, 

environmental monitoring, and marine mammology. 

Peter Tyack is Senior Scientist and Walter A. and Hope Noyes Smith Chair in the Biology 

Department of the Woods Hole Oceanographic Institution. He has an A.B. summa cum laude 

from Harvard College and a Ph.D. from Rockefeller University. His research focuses on acoustic 

communication and social behavior of cetaceans. 

Peter T. Madsen graduated from University of Aarhus in 2002 after studying physiological 

acoustics under Dr. Bertel Møhl. He was post doc in Dr. Roger Payne’s lab in 2002–2003, and 

went on as a post doc to Dr. Peter Tyack’s lab at the Woods Hole Oceanographic Institution in 
288 

2003. His areas of research includes biosonar, physiological acoustics and effects of man-made 

noise on marine mammals. 

Stephanie Watwood completed her Ph.D. in the MIT/Woods Hole Oceanographic Institution 

Joint Program with Peter Tyack in 2003. Her thesis work focused on the social behavior and 

vocal communication of male bottlenose dolphins in long-term stable alliances. She is currently a 

post doc at Woods Hole studying the diving and social behavior of sperm whales. 
289 

D-TAG/CEE CONCLUDING REMARKS 

Peter L. Tyack, Biology Department, Woods Hole Oceanographic Institute 

Summary of CEE Results 

The two CEE responses presented at this ITM were avoidance and foraging (effect of exposure 

on communication is being analyzed and is not ready for presentation). We are working on 

methods to analyze responses as a function of Received Level for each individual, but this work 

is in progress. 

Avoidance 

Miller (this volume) presented a case of possible vertical avoidance of an oncoming seismic 

survey vessel, but we have found no evidence for horizontal avoidance. No horizontal avoidance 

was detected either during ramp-up or full array seismic CEEs at ranges of 1-11 km. The 

complex way in which sounds propagate from airgun arrays, as presented by Lynch (this 

volume), may complicate analysis of avoidance. If a whale is moving down a local sound 

gradient, its motion may not be directly away from the vessel. There is no justification from the 

D-tag/CEE work that sperm whales show horizontal avoidance of oncoming seismic vessels. The 

D-tag/CEE data provide no support for the assumption that behavioral avoidance will reduce the 

risk of injury at close range. This was not studied at ranges of <1km, but 1 km is only twice the 

current mitigation range, and whales would have little time to move far from a vessel as it closed 

from 1,000 to 500 m. 

Foraging 

The study design for the first-year CEE cruise was set for tag durations available three years ago. 

The pre-exposure data from year one was affected by the response to tagging, so we concluded 

that longer pre-exposure periods are required. A major redesign of the tag and attachment was 

made between years one and two of SWSS, and these improvements enabled sufficient preexposure periods in year two by improvements in attachment, but if we are to include year one 

data it is only possible to compare exposure to post-exposure data. These modifications also 

improve the noise floor of acoustic sampling from the tag. 

Data from the seven whales that did deep foraging dives during CEE exposure show a significant 

(p<0.05) change in fluking effort comparing exposures at <120-147 dBrms re 1 μPa (see Madsen 

this volume for details on calculating exposure) to the post-exposure interval. Judging by 

changes in buzz rates, there was also a 25% reduction of foraging comparing exposures at <120-

147 dBrms re 1 μPa to the post-exposure interval. If the whales did not immediately return to 

baseline once the exposure stopped, this comparison would underestimate the effect. We can cast 

the results from the first two years of CEEs under SWSS as leading to the hypothesis that sperm 

whales exposed to 120-147 dBrms re 1 μPa have a 25% reduction of foraging. From a frequentist 

statistical point of view, we cannot reject the null hypothesis of no difference between exposure 

and post-exposure buzz rates at the α<= 0.05 level. However, modern statisticians point out the 
290 

critical need for statistical power analysis if Ho is rejected, especially in this kind of study used 

for management (Peterman 1990). Figure 1F.7 from Miller’s ITM presentation introduces the 

two types of error one may make in deciding whether or not a data set indicates an effect. 

REALITY

YES NO 

Yes 

Study 

Conclusions 

No 

Congratulations!! You have 

correctly concluded that 

seismics affect foraging 

OOPS!! You wrongly concluded 

effect that doesn’t exist 

TYPE I ERROR 

OOPS!! You wrongly concluded 

no effect when it does exist 

TYPE II ERROR 

Congratulations!! 

You have correctly concluded 

that seismics do NOT affect 

foraging 

Figure 1F.7. Two error types. 

The critical issue for the buzz rate effect is type II error. Statistical analyses of the buzz rate data 

indicate that if you conclude no effect, there are roughly 85% odds of a Type II error. If on the 

other hand, you conclude the effect is true, data suggest 16% odds of a Type I error. The odds of 

a type II error are 5.6 times higher than those of the type I error. Ellison (1996) interprets this 

odds ratio as substantial positive evidence for the effect. From the perspective of environmental 

decision-making, there is a need now for an interim decision about whether the CEE data 

indicating a reduction in foraging correctly defines the effect. There has been discussion among 

ecologists about different situations suggesting different acceptability of Type I vs. Type II 

errors. Peterman and McGonigle (1992) make a specific suggestion for “cases in which the Ho

was not rejected but the study had low statistical power for the effect size deemed important. In 

these latter cases, especially where the confidence interval on the effect size is large, regulatory 

action to reduce emissions should be recommended as a precautionary measure in case an 

important effect exists.” (p. 232) From the industry perspective, a type I error might lead to the 

expense of unnecessary monitoring and mitigation measures. From the conservation perspective, 

the endangered status of sperm whales in the U.S. would suggest a low tolerance for type II 

errors, especially for such a large reduction in foraging. Peterman (1990) points out that decision 

makers often must weigh the costs of type I vs type II errors. Purely on the basis of the odds 
291 

ratio, regulators would have to weigh the costs to industry of the type I error 5.6 times higher 

than those to endangered sperm whales to justify not adopting interim acceptance of the effect. 

There has been considerable discussion in ecology that a Bayesian approach is more appropriate 

to estimate responses of wildlife to anthropogenic stressors (Ellison 1996, Harwood 2000). From 

this perspective, the SWSS D-tag/CEE work can establish a priori probabilities for specific 

hypotheses about the effect of airguns on foraging. This analysis suggests that a sample size of 

about 50-60 CEEs would be required to reach near 80% level of statistical power to test for the 

same 25% reduction in feeding. The low statistical power and sample size of the D-tag/CEE 

work under SWSS must be evaluated taking into account decisions on the part of MMS and 

industry to reduce the initial request for six weeks/year to three weeks/year and the decision after 

the second cruise to cancel the planned third D-TAG/CEE cruise and to redirect cruise funds to 

other components of SWSS. Miller’s power analysis of the CEE results on foraging shows that 

while the sample size resulting from two three-week cruises is low, the original WHOI proposal 

for three six-week or six three-week field efforts would likely have yielded a power of close to 

0.5, while a 0.8 level is often used as a benchmark in study design for statistical power. 

One of the surprises of recording airgun signals from whales at a distance from the source ship 

was how different the signals were from the initial predictions. While the bottom bounce 

contained the low frequency energy predicted, the direct path arrival was much broader band. 

There is enough overlap of the spectrum from airgun arrays with the dolphin audiogram that 

airgun sounds are detectable to dolphins at many km, as has been pointed out previously by 

Goold and Fish (1998). Surface ducts sometimes supported efficient propagation of midfrequency energy, while not supporting low frequencies. This concentration of mid-frequency 

sound in surface ducts raises concern for other toothed whales. The presence of mid-frequency 

sound energy in surface ducts has been raised as a risk factor for strandings of beaked whales 

(Evans and England 2000). Airguns put considerably less sound energy into these ducts than 

mid-frequency military sonars, but until safe exposures are determined, there is cause for 

concern. 

Considerations for Future Work 

The difference between measurements and predictions of the spectrum, directionality, and 

propagation of sounds from airgun arrays was a surprise, and interfered with execution of CEEs. 

A better understanding is required of how sound propagates from airgun arrays. Propagation 

should be calculated out to large enough ranges to predict exposures to whales at levels of 120 

dBrms or below. Data on sound propagation should be linked to models of sound exposure for 

different species (e.g. AIM) in order to predict the amount of time sperm whales and other 

species are exposed to different levels of airgun sounds as they move in three dimensions. 

Sperm whales in the northern Gulf of Mexico (GOM) hear airguns much of the time. It is 

unlikely that whales behaving as described by Mate et al. (1994) and Bowles et al. (1994) would 

have been found for the GOM CEEs, given the intensity of ongoing commercial surveying. This 

raises concerns about whether the sample of sperm whales in the northern Gulf may already be 

biased—are they the least responsive members of a larger population? The GOM CEE data 
292 

cannot be extrapolated to other areas with fewer seismic surveys; but it is reasonable to predict 

that less habituated animals may be more responsive than those in the studies. Future airgun CEE 

work should include other areas with fewer seismic surveys. A problem for the GOM CEEs was 

finding new groups of sperm whales far enough from ongoing commercial surveys that their 

selection would not bias the sampling. Better field sites with less commercial survey activity and 

more evenly distributed whales may increase the number of experiments achievable per cruise 

It was difficult to achieve received levels much > 150 dBrms on tagged whales using the airgun 

arrays provided for these experiments. We doubt that there is much need for higher exposure 

levels until further CEEs resolve the effect of exposure at 120-150 dBrms re 1 μPa. If work is to 

involve much higher levels, the following are required: 

• Better specification of the sound field around airgun arrays and better propagation 

modeling 

• Better real-time monitoring of location and range of subject whale 

• Smaller, more cohesive groups for easier monitoring and mitigation (large dispersed 

groups typical of Gulf complicate approach of tagged subjects) 

 

These improvements will be crucial for studies to evaluate horizontal avoidance of sperm whales 

at close range (<1 km) to either ramp up or full arrays. 

Acknowledgments 

We thank the field teams and ship crews of SWAMP, SWSS, Sirena and RV Delaware cruises, 

the staff of IAGC, LDEO, MMS, NATO Undersea Research Centre, NOAA, TAMU and WHOI. 

We regret that too many people were involved to allow them to be named individually. Work 

supported by contract #1435-01-02-CA-85186 from the U.S. Minerals Management Service, 

ONR and WHOI internal funds for tag development, NSF for RV Ewing support, NOAA for RV 

support, IAGC and industry for providing source vessels. PJOM Fellowship support from the 

Royal Society. Work conducted under NMFS research permits 981-1578 and 981-1707-00 

issued by the U.S. National Marine Fisheries Service to Peter L. Tyack. The Woods Hole 

Oceanographic Institution Animal Care Use Committee approved this research. 

References 

Bowles, A.E., M. Smultea, B. Würsig, D. DeMaster, and D. Palka. 1994. Relative abundance and 

behavior of marine mammals exposed to transmissions from the Heard Island Feasibility 

Test. Journal of the Acoustical Society of America 96:2469–2484. 

Ellison, A.M. 1996. An introduction to Bayesian inference for ecological research and 

environmental decision-making. Ecological Applications 6:1036-1046. 

Evans W. and G England. 2001. Joint interim report: Bahamas marine mammal stranding event 

of 15–16 March 2000. U.S. Dept. of Commerce, National Oceanic Atmospheric 

Administration. National Marine Fisheries Service, Secretary of the Navy, Assistant 

Secretary of the Navy, Installations and Environment. 61 p. 
293 

Goold, J.C. and P.J. Fish. 1998. Broadband spectra of seismic survey air-gun emissions, with 

reference to dolphin auditory thresholds. Journal of the Acoustical Society of America 

103:2177–2184. 

Harwood, J. 2000. Risk assessment and decision analysis in conservation. Biological 

Conservation 95:219–226. 

Mate, B.R., K.M. Stafford, and D.K. Ljungblad. 1994. A change in sperm whale (Physeter 

macrocephalus) distribution correlated to seismic surveys in the Gulf of Mexico. Journal 

of the Acoustical Society of America 96(5, part 2):3268–3269. 

Peterman R.M. 1990. Statistical power analysis can improve fisheries research and management. 

Canadian Journal for Fisheries and Aquatic Sciences 47:2–15 

Peterman R.M. and M. McGonigle. 1992. Statistical power analysis and the precautionary 

principle. Marine Pollution Bulletin 24:231–234. 

Peter Tyack is Senior Scientist and Walter A. and Hope Noyes Smith Chair in the Biology 

Department of the Woods Hole Oceanographic Institution. He has an A.B. summa cum laude 

from Harvard College and a Ph.D. from Rockefeller University. His research focuses on acoustic 

communication and social behavior of cetaceans. 
295 

SESSION 2D 

EFFECTS OF OIL AND GAS EXPLORATION & DEVELOPMENT 

AT SELECTED CONTINENTAL SLOPE SITES IN THE 

GULF OF MEXICO, PART II 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: Margaret C. Metcalf, Minerals Management Service 

MEIOFAUNA AND MACROINFAUNA Barry A. Vittor....................................................... 297 

EFFECTS OF OFFSHORE OIL AND GAS DEVELOPMENT ON THE GENETIC 

DIVERSITY OF HARPACTICOID COPEPODS Christopher S. Gregg, David W. Foltz, 

and John W. Fleeger ................................................................................................................... 300 

SEDIMENT MICROBIAL BIOMASS Paul A. LaRock .......................................................... 302 

CHARACTERIZATION OF NORTHERN GULF OF MEXICO DEEPWATER HARD 

BOTTOM COMMUNITIES WITH EMPHASIS ON LOPHELIA CORAL 

Stephen T. Viada......................................................................................................................... 307 
297 

MEIOFAUNA AND MACROINFAUNA 

Barry A. Vittor, Barry A. Vittor & Associates 

Responses of benthic organisms to offshore Gulf of Mexico (GOM) petroleum exploration and 

production have been studied extensively on the continental shelf. Some studies have addressed 

meiofaunal and macroinfaunal community structure and detected acute and chronic effects on 

these organisms by surveying around drilling/production sites of varied duration. However, few 

studies have been designed to focus on sublethal effects on benthos. The Gulf of Mexico 

Offshore Operations Monitoring Experiment (GOOMEX) investigated potential chronic, 

sublethal, and long-term oil and gas production effects on meiofauna and macroinfauna as well 

as other ecosystem components on the continental shelf (Montagna and Harper 1996). That 

program detected changes in benthic assemblages due to both organic enrichment and toxicity of 

drilling muds and cuttings discharged to the bottom. The present investigation employed many of 

the methods used in GOOMEX but was designed to assess meiofaunal and macroinfaunal 

community responses to discharges of synthetic drilling muds in deep-sea environments in the 

GOM. 

Benthos were sampled at selected wellsites before to and after drilling to detect short-term 

(acute) effects of exploratory and development activities. Benthic community responses were 

intended to be detected through enumeration of individual abundance among major groups 

(Order or higher taxonomic level in most cases) of meiofauna and macroinfauna. Twenty-four 

stations were selected for more in-depth taxonomic macroinfauna identification (i.e., to Lowest 

Practical Identification Level or LPIL). Family-level censusing of meiofaunal nematodes was 

performed for selected sites sampled during the July 2001 survey to determine changes in 

trophics among these taxa. Harpacticoid copepod reproductive condition was also noted at 

selected locations to detect potential sublethal effects of synthetic drilling muds. 

Meiofauna 

Meiofaunal assemblages at GB 516 stations differed significantly with respect to both cruise 

(pre-drilling vs. post-drilling) and area (nearfield vs. farfield). Nematodes, ostracods, and 

polychaetes were more abundant during November 2000 (pre-drilling) compared to July 2001 

(post-drilling), but harpacticoid copepod abundance did not differ between pre- and post-drilling 

surveys. Ostracod abundance was significantly greater at farfield stations, whereas polychaetes 

were significantly more abundant at nearfield stations. At VK 916 stations numbers of 

harpacticoid copepods, polychaetes, and nematodes were significantly more abundant predrilling; however, there were no differences between areas (nearfield vs. farfield) for these taxa. 

There were no nearfield vs. farfield differences in meiofaunal assemblages at GB 602 or MC 292 

stations. 

We observed a very wide range in meiofaunal abundance among the four study sites and 

between surveys. Average meiofauna densities (19 to 608 per 10 cm2

) were much lower than 

found by Montagna and Harper in shelf waters (734 to 2571 per 10 cm2

). This difference was 
298 

consistent with the widely reported inverse relationship between water depth and meiofauna 

abundance. Sediments at VK 916 were reported to be carbon-rich, with extensive foraminiferan 

composition. After drilling, deposition, and disturbance were detected close to the wellsite 

(within about 30 m). At the other wellsites drilling muds extended outward about 150 m. 

Nearfield stations had higher abundances than farfield stations at all four sites. While these 

increases appeared to be due in part to higher numbers of nematodes, harpacticoids also occurred 

at higher abundances at most nearfield stations. Elevated organic content at GB 516 did not elicit 

nematode abundance increases; rather, post-drilling nematode abundance was slightly lower at 

nearfield stations than at farfield stations. The similarity of nearfield meiofaunal abundance at 

GB 602 to other post-drilling sites was surprising because of what sediment profile imagery 

indicated to be a bacterial mat on the surface, with no apparent infauna. 

Synthetic based muds (SBM) did not appear to affect meiofauna abundance or numbers of 

nematodes or harpacticoids. In an attempt to detect longer-term effects of SBM on harpacticoid 

reproduction, female copepod reproductive condition was recorded for samples obtained at MC 

292 and GB 602 (where SBM discharges had occurred at least two years earlier). However, the 

numbers of harpacticoids observed were very small and the data are not considered to be 

conclusive. Potential shifts in nematode feeding types were also considered, but nearfield and 

farfield stations were similar with respect to numbers of deposit feeders and numbers of 

predators. 

Macroinfauna 

Macroinfaunal abundance was significantly greater pre-drilling at GB 516 for amphipods, 

harpacticoid copepods, and nematodes. Bivalves, gastropods, and polychaetes were more 

abundant at nearfield stations. At VK 916 stations, most taxa were more abundant prior to 

drilling than after. Annelids were more abundant during post-drilling and decapods showed no 

between-cruise difference. Except for ostracods and rhynchocoels, there were no abundance 

differences between areas (nearfield vs. farfield) at VK 916. At GB 602, aplacophorans, 

bivalves, gastropods, harpacticoid copepods, polychaetes, and rhynchocoels were more abundant 

at nearfield stations, while nematodes and tanaids were more abundant at farfield stations. At 

MC 292, bivalves, harpacticoid copepods, and polychaetes were more abundant at nearfield 

stations. 

Macroinfauna results corresponded well with prior observations of deep-water macoinfaunal 

community structure. Some probable drilling effects were reflected in the data, though drillingrelated disturbance was not evident in most assemblage patterns at the wellsites. Highest average 

macroinfaunal densities occurred at nearfield stations at GB 516, MC 292, and GB 602, all in 

post-drilling surveys. Abundance of ostracods and tanaids was greater at GB 516 farfield 

stations, whereas bivalves, gastropods, and polychaetes were more abundant at nearfield stations, 

potentially a reflection of drilling-related effects according to the paradigm suggested by 

Montagna and Harper (1996). They found that polychaete density increased near wellsite 

platforms, and there was a corresponding decline in abundance and diversity of certain 

crustaceans (amphipods and harpacticoid copepods) near platforms. At VK 916 stations, 

amphipods and harpacticoid copepods were more abundant before drilling than after drilling, 
299 

while polychaetes were more abundant after drilling. These differences between cruises may 

indicate drilling-related effects; however, except for ostracods and rhynchocoels, there were no 

differences between nearfield and farfield stations at VK 916. Furthermore, at GB 602, which 

was surveyed only after drilling, harpacticoid copepods were more abundant at nearfield stations. 

At MC 292, harpacticoid copepods also were more abundant at nearfield stations, but 

amphipods, ostracods and tanaids did not exhibit differences in abundance between nearfield and 

farfield stations. 

References 

Montagna, P.A. and D.E. Harper, Jr. 1996. Benthic infaunal long-term response to offshore 

production platforms in the Gulf of Mexico. Canadian Journal of Fisheries and Aquatic 

Science 53:2567–2588. 

Dr. Barry Vittor is President of Barry A. Vittor & Associates, Inc. a consulting firm that has 

specialized in coastal and marine benthic ecosystem studies since 1977. Dr. Vittor has over 30 

years’ experience in assessing the effects of offshore oil and gas exploration/production activities 

on benthic communities. 
300 

EFFECTS OF OFFSHORE OIL AND GAS DEVELOPMENT ON THE GENETIC 

DIVERSITY OF HARPACTICOID COPEPODS 

Christopher S. Gregg, David W. Foltz, and John W. Fleeger, 

Louisiana State University 

The deep sea in the northern Gulf of Mexico (GOM) is an increasingly active area for 

exploration of oil resources, but there are currently no data on the effects of oil exploration and 

production on genetic diversity of deep-sea infauna. Sites adjacent to (near field) and distant 

from (far field) oil-drilling platforms were sampled at two locations in the northern GOM off the 

coast of Louisiana both at depths of ≈ 1,100 m. The sites were located at Garden Banks Area 

Block 602 (GB602) and Mississippi Canyon Area Block 292 (MC292). Near-field sites were 

characterized by low species diversity and high dominance. Many specimens of a single species 

in the family Cletopsyllidae, Cletopsyllidae gen. nov. sp. nov. (R. Huys pers comm.; referred to 

as Cletopsyllidae sp.), were recovered from box cores at near-field sites. Far-field sites were 

characterized by high species diversity and low dominance, more typical of deep-sea 

communities. Because no single harpacticoid species was found in high abundance at both nearand far-field sites, the objectives of the present study were modified to examine the relationship 

between sediment disturbance and abundance as well as genetic diversity of Cletopsyllidae sp. at 

the two exploration sites. Additionally, DNA sequence data was used to determine if the 

harpacticoids examined were a single species or a complex of cryptic species. We examined 

DNA sequence variation of the mitochondrial cytochrome c oxidase subunit I (COX I) gene. The 

patterns of genetic diversity and structure or the presence of cryptic species were used to 

determine how Cletopsyllidae sp. may have responded to the environmental disturbance. 

Cletopsyllidae sp. was the most abundant harpacticoid at both the GB602 and MC292 near-field 

sites. Only one Cletopsyllidae sp. was observed at the far-field sites. Observations of the 

distribution of cuttings from the drilling process indicated that level of disturbance was not 

uniformly distributed throughout the near-field sites. We, therefore, examined the relationship 

between a measure of disturbance, total petroleum hydrocarbons in the synthetic-based mud 

range (TPH; data from Tom McDonald), and copepod abundance. When TPH levels were below 

2,500 μg dry g-1, there was a significant positive linear relationship between TPH concentration 

and Cletopsyllidae sp. abundance at both sites (GB602 - R2

 = 0.45; MC292 – R2 = 0.92). At 

GB602 four out of 12 boxcores had TPH concentrations greater than 2,500 μg dry g-1. Copepod 

abundance at GB602 showed a decline when TPH concentrations were above this concentration 

suggesting there was a threshold level of disturbance, above which copepods cannot survive. 

Cletopsyllidae sp. may have responded directly to petroleum hydrocarbons or to an indirect 

effect associated with disturbance caused by oil production activities. Therefore, the 

identification of the cause of this pattern requires further study 

Genetic analysis of the two populations revealed two important observations. First, divergence at 

the COX I gene was within the range expected (maximum 1.6%) for intraspecific variability. 

Thus, the Cletopsyllidae sp. populations sampled at the two production sites were a single 
301 

species and not a complex of cryptic species. Second, low genetic diversity indicated the 

Cletopsyllidae sp. populations were not in genetic equilibrium, indicating that they have 

undergone population fluctuations, such as a founder event and population expansion. Haplotype 

diversity was 0.61 (SD ± 0.089) and 0.89 (SD ± 0.033) and nucleotide diversity was 0.0020 (SD 

± 0.0014) and 0.0066 (SD ± 0.0038) at GB602 and MC292, respectively. The low haplotype and 

nucleotide diversities observed in the present study were comparable to those seen in populations 

of other harpacticoid copepods in the genus Cletocamptus, which are known to undergo 

population fluctuations, and populations of the species Microarthridion littorale, which are 

found in disturbed habitats. 

The present study suggests that the harpacticoid copepod Cletopsyllidae sp. responds to 

disturbance by rapidly increasing in abundance in response to disturbance in the deep sea. First, a 

positive correlation between abundance of this copepod species and total petroleum 

hydrocarbons (TPH) was observed up to a TPH concentration of 2,500 μg dry g-1. Second, low 

genetic diversity suggests that the harpacticoid population has undergone population 

fluctuations, such as a founder event and rapid population expansion. Further study of this 

species is required to confirm these results and to determine the mechanisms by which it 

colonizes and tolerates hydrocarbon-rich sediments. If further sampling at other deep-sea oil 

platforms and organically enriched habitats shows similar results, then Cletopsyllidae sp. may 

prove to be a useful indicator of disturbance or hydrocarbon enrichment in deep-sea sediments. 

Christopher Gregg is a post-doctoral student working with David Foltz and John Fleeger at 

Louisiana State University. 

David Foltz is a Professor in the Department of Biological Sciences, Louisiana State University. 

He obtained his Ph.D. from the University of Michigan in 1979. His research is concerned with 

the molecular evolutionary genetics of marine invertebrate species. The questions addressed 

concern rates of evolution, patterns of lineage splitting and extinction, and the roles of geological 

events and various life history factors in shaping the population genetic structures of these 

species. Organisms studied include marine bivalves, other marine and freshwater molluscs, 

echinoderms, and crustaceans. Other ongoing related projects include a study of pollution 

tolerance in a cryptic species complex of harpacticoid copepods. 

John Fleeger is a Professor in the Department of Biological Sciences, Louisiana State University. 

He obtained his Ph.D. at the University of South Carolina in 1977. His research focuses on the 

ecology, evolution and ecotoxicology of benthic invertebrates. His interests include factors that 

control the abundance patterns of meiofauna (benthic metazoans <1 mm in body length) and 

small macrofauna. His recent projects focus on the joint effects of nutrient addition and fish 

exclusion on the benthos of tidal creeks, the effects of CO2 disposal (to mitigate the greenhouse 

effect) on deep-sea benthos and contaminant ecotoxicology including issues related to the effects 

of contaminant mixtures, assimilation efficiency and bioavailability. 
302 

SEDIMENT MICROBIAL BIOMASS 

Paul A. LaRock, School of the Coast and Environment, 

Department of Oceanography and Coastal Sciences, Louisiana State University 

Introduction 

The thrust of the current effort was to determine the effects of oil drilling activities on 

sedimentary microbes using adenosine triphosphate (ATP) determinations as the primary 

analytical tool. ATP serves as a useful measure of bacterial colonization and survival in extreme 

or altered environments as it is directly tied to the physiological functioning of the community. 

The nature and magnitude of the sedimentary bacterial community have been the subject of a 

number of studies. The initial approach to quantify sedimentary bacteria was to separate them 

from the sediment matrix and count the resultant cells using epifluorescent microscopy. A 

consensus developed that the size of the bacterial community was inversely proportional to 

sediment grain size (Dale 1974; DeFlaun and Mayer 1983; Yamamoto and Lopez 1985), and that 

it also varied directly with organic carbon. The reasoning for the increase in bacterial numbers 

with decreasing grain size was the greater availability of sediment surface area for colonization. 

Early experiments at sediment oxygen uptake indicated that more oxygen was consumed by 

small grain-size sediments than by coarser materials. However, the experiment was carried out 

by suspending less than a gram of material into 28 ml BOD bottles and following oxygen loss 

(Hargrave 1972). This approach ignores in situ conditions and the fact that very fine materials 

may have more pore space, but the pores are so small that flow into the sediments is greatly 

inhibited thus limiting the introduction of nutrients and oxygen into the sediment matrix (Maier 

et al. 2000). The work of Yamamoto and Lopez (1985) revealed that increased surface was only 

one aspect of microbial colonization and recognized that the size and shape of sediment particles 

affect sediment packing. Larger, more sorted particles, as found in sands, would actually make 

nutrients more available to the sedimentary bacterial community. Both DeFlaun and Mayer 

(1983) and Yamamoto and Lopez (1985) noted that clays were a poor substrate for bacterial 

attachment. 

The ATP assay offers considerable advantage over conventional microbiological methods when 

assessing the effect of the environment on microbial communities because it is non-cultural, 

avoids the issue of nutrient limitations and reflects the in situ properties of the community. ATP 

is present in physiologically active cells and thus offers a means of assessing the relationship 

between the microbial community and the suitability of the prevailing habitat. Environmental 

ATP determinations can, therefore, provide quantification of the effects of toxicants, nutrient 

enrichment or other alteration of the environment. A few of the more recent applications of ATP 

technology have been to examine issues in marine ecology (Karl 1986; Karl 1993; Bjorkman and 

Karl 2001), to study the effects of nutrient loading in coastal waters (Malin et al. 2001), to 

quantify hydrothermal communities (Atkinson et al. 2000), to assess river water and sediment 

quality (Dutka et al. 1991), to follow the toxic effects of zinc released from trout farms 
303 

(Martinez-Tabche et al. 2000), to determine the toxicity of pollutants on waste water treatment 

(Dalzell and Christofi 2002; Dalzell et al. 2002), and to assess the effects of wastewater-borne 

heavy metals in mangroves (Yim and Tam 1999). 

As the ATP assay became more widespread it became evident that there were substances that 

resulted in a loss of ATP during extraction and had to be compensated for. It was shown that 

suspended material in water samples, for example, was capable of reducing ATP quantification 

by either affecting the extraction efficiency or by inhibiting the luciferin-luciferase reaction. To 

overcome these deficiencies we employed radiolabeled ATP as an internal standard to assess 

losses encountered during extraction and a stable ATP internal standard to correct for 

interference during the counting phase. 

Sediments from the study sites were predominantly clay with a mean sedimentary particle 

diameter ranging from about 1 to 3 μm. Over 80% of the sediment consisted of components 

smaller than 10 μm. Thus we were dealing with materials that are very fine-grained, highly 

porous but very impermeable (Maier et al. 2000). 

Additionally, a bioluminescent assay using the dinoflagellate Pyrocystis lunula was used to test 

the relative inhibitory effects of sediment extracts in the pre- and post-drill materials. A detailed 

methodology for the luminescent assay may be found in ASTM protocol E 1924, and the 

procedure as reported here was performed by the Lumitox Co., Slidell, LA who developed the 

technique 

The ATP results for all stations and cruises are summarized in Table 2D.1 and although there is 

spatial variation, they show that for all the post-drilling conditions the ATP is significantly 

reduced relative to the pre-drill materials. A comparison of the pre- and post-drilling ATP values 

at GB 516 and VK 916, on the average, show a marked decrease of from five- to fifteen-fold 

after drilling. At GB 516, the average ATP concentration on Cruise 1B was 44.2 ng g-1 for the 

NF site and 43 ng g-1 for the FF sites. The Cruise 2B averages were 4.3 ng g-1 for the NF site and 

2.5 ng g-1 for the FF sites. At VK 916, the average pre-drilling ATP concentration was 32 ng g-1

for the NF site and 36 ng g-1 for the FF sites. The post-drilling averages for VK-916 NF (7.7 ng 

g-1) and FF (7.1 ng g-1) indicate a five-fold reduction in the microbial ATP biomass although it 

should be noted that again there is spatial heterogeneity in the data. The difference between the 

pre-drilling and post-drilling ATP concentrations is statistically significant (p< 0.0001 for 

GB 516 and p< 0.0002 for VK 916). Statistically there was no significant difference between the 

near field and far field ATP levels for either GB 516 or VK 916 (p<0.137 for GB 516 and 

p<0.157 for VK 916). 

Our findings show that drilling does affect the sedimentary microflora, but what happens when 

drilling ceases? Unknown at the time the project was designed was the fact that GB 516 had 

exploratory wells drilled the year prior to our sampling, thus GB 516 was not a pristine site but 

rather a recovered site. What this indicates is that while there may be an initial impact as a result 

of development the sedimentary microflora does recover and at a relatively rapid rate. 
304 

Table 2D.1. Sediment ATP concentrations (ng g-1 dry wt) for all near-field and far-field sites. 

GB 516 VK 916 GB 602 MC 292 Site Samplea

Cruise 1B Cruise 2B Cruise 1B Cruise 3B Cruise 2B Cruise 2B 

NF B01 288.3 2.1 47.5 <1.7b

 -- 4.5 

 B02 418.2 0.6 42.1 <1.3b 3.4 1.2 

 B03 13.1 7.9 30.2 <1.8b

 3.3 1.4 

 B04 27.9 0.5 34.5 <1.8b

 2.3 0.9 

 B05 26.4 1.1 29.3 15.3 14.1 4.4 

 B06 -- 11.9 48.3 25.6 4.7 4.4 

 B07 33.5 4.4 30.1 41.5 2.3 1.1 

 B08 104.1 1.5 21.9 <0.3b

 17.6 5.4 

 B09 39.2 9.6 25.1 1.1 2.7 1 

 B10 29.2 0.7 23.3 1.3 15.2 1.6 

 B11 56.3 5.1 23.4 <1.5b

 16.2 5.5 

 B12 68.7 6.8 29.1 1.1 ND 1.7 

 

FF1 B01 28.7 5.5 -- 61.1 2.1 2.9 

 B02 43.4 5.8 -- 1.1 1.1 -- 

FF2 B01 102.4 2.3 57.9 1.3 1.7 2.5 

 B02 25.3 2.8 61.4 1.1 1.9 66.6 

FF3 B01 92.3 0.5 34.2 2.7 3.6 1.7 

 B02 35.3 3.1 29.6 <1.5b

 2.4 2.8 

FF4 B01 29.1 5.4 19.7 2.7 1.1 2.1 

 B02 38.1 1.1 28.4 2.3 2.2 0.7 

FF5 B01 64.4 0.5 24.5 2.3 3.2 1.1 

 B02 14.2 0.6 -- 2.7 216.3 2.2 

FF6 B01 29.3 1.4 36.4 0.9 2.6 1.5 

 B02 16.7 0.8 32.1 5.6 2.7 1 a

 Sample locations were randomly selected on each cruise; therefore, the pre- and post-drilling 

samples at GB 516 and VK 916 are not paired samples from the same location. 

b

 A < symbol indicates that interference reduced the sensitivity of the assay to the value indicated; 

thus, ATP may be present at a lower concentration but be undetectable. 

Toxicity Bioassay 

In order assess possible causes for the post-drill decrease in ATP levels, a toxicity bioassay was 

performed that measured the relative changes in light output of the dinoflagellate P. lunula as it 

was exposed to extracts made from the various pre and post-drilling sediments. The addition of 
305 

SDS, either 10 or 20 μl was used as a positive control to elicit a measurable response that can be 

compared to the negative control (P. lunula with no additives). The results obtained for VK 916 

indicated that all of the pre-drilling materials yielded the same response as the unamended P. 

lunula control, but the post-drilling samples exhibited some inhibition with the NF sediments 

being more inhibitory than the FF sediments. Bear in mind that the design of these tests was only 

to indicate the relative effects of the various sediments and that only a small aliquot of the extract 

was used which does not indicate the full inhibitory potential of the materials. 

The results for GB 516 essentially paralleled those obtained for VK 916: the post-drilling 

samples were inhibitory with the NF materials exerting a stronger effect than the FF samples did. 

Tests on GB 602 post-drilling sediments showed some inhibition in the bioassay, but the results 

for MC 292 indicated no inhibition whatsoever. This rather curious finding may reflect 

circulation within the Mississippi Canyon itself. Submarine canyons are known to support 

upwelling and therefore flush the region, thus removing foreign material. 

References 

Atkinson, T., S. Gairns, D.A. Cowan, M.J. Danson, D.W. Hough, D.B. Johnson, P.R. Norris, N. 

Raven, C. Robinson, R. Robson, and R.J. Sharp. 2000. A microbiological survey of 

Montserrat Island hydrothermal biotopes. Extremophiles. 4:305–313. 

Bjorkman, K.M. and D.M. Karl. 2001. A novel method for the measurement of dissolved 

adenosine and guanine triphosphate in aquatic habitats: applications to marine microbial 

ecology. Journal of Microbiological Methods. 47:159–167. 

Dale, N.G. 1974. Bacteria in intertidal sediments: Factors related to their distribution. Limnology 

and Oceanography 19:509–518. 

Dalzell, D.J.B. and N. Christofi. 2002. An ATP luminescence method for direct toxicity 

assessment of pollutants impacting on the activated sewage sludge process. Water 

Research 36:1493–1502. 

Dalzell, D.J.B., S. Alte, E. Aspichueta, A. de La Sota, J. Etxebarria, M. Gutierrez, 

C.C. Hoffmann, D. Sales, U. Obst, and N. Christofi. 2002. A comparison of five rapid 

direct toxicity assessment methods to determine toxicity of pollutants to activated sludge. 

Chemosphere. 47:534–545. 

DeFlaun, M.F. and L.M. Mayer. 1983. Relationships between Bacteria and Grain Surfaces in 

Intertidal Sediments. Limnology and Oceanography 28:873–881. 

Dutka, B.J., K.K Kwan, S.S. Rao, A. Jurkovic, R. Mcinnis, G.A. Palmateer, and B. Hawkins. 

1991. The use of bioassay to evaluate river water and sediment quality. Environmental 

Toxicology and Water Quality 6:309–327. 
306 

Hargrave, B.T. 1972. Aerobic decomposition of sediment and detritus as a function of particle 

surface area and organic content. Limnology and Oceanography 17:583–596. 

Karl, D.M. 1986. Determination of the in situ microbial biomass, viability, metabolism, and 

growth. Bacteria in Nature. 2:85–176. 

Karl, D.M. 1993. Total microbial biomass estimation derived from the measurement of 

particulate adenosine-5’-triphosphate. In: Kemp, P.F., B.F. Sherr, E.B. Sherr, and J.J. 

Cole, eds. Handbook of Methods in Aquatic Microbial Ecology. Pp. 359–368. 

Maier, M.A., I.L. Pepper, and C.P. Gerba. 2000. Environmental Microbiology. Academic Press. 

585 pp. 

Malin, M.A., L.B. Cahoon, D.C. Parsons, and S.H. Ensign. 2001. Effects of nitrogen and 

phosphorus loading on plankton in coastal plain blackwater rivers. Journal of Freshwater 

Ecology 16:455–466. 

Martinez-Tabche, L., I.G. Cabrera, L.G. Olivan, M.G. Martinez, and C.G. Faz. 2000. Toxic 

effects of zinc from stout farm sediments on ATP, protein, and hemoglobin 

concentrations of Limnodrilus hoffmeisteri. Journal of Toxicological Environmental 

Health-Part A.59:575–583. 

Yamamoto, N. and G. Lopez. 1985. Bacterial abundance in relation to surface area and organic 

content of marine sediments. Journal of Experimental Marine Biology and Ecology 

90:209–220. 

Yim, M.W. and N.F.Y. Tam. 1999. Effects of wastewater-borne heavy metals on mangrove 

plants and soil microbial activities. Marine Pollution Bulletin 39:179–186. 

Paul LaRock is a professor of biology in the School of the Coast and Environment of Louisiana 

State University. His primary research interests are estuarine pollution, microbiology, geomicrobiology, and oceanography. 
307 

CHARACTERIZATION OF NORTHERN GULF OF MEXICO DEEPWATER HARD 

BOTTOM COMMUNITIES WITH EMPHASIS ON LOPHELIA CORAL 

Stephen T. Viada, Continental Shelf Associates, Inc. 

Continental Shelf Associates, Inc. and its subcontractors/consultants are conducting a multi-year 

study to characterize the types of non-chemosynthetic megafaunal and macroinfaunal 

communities that live on deepwater hard-bottom substrate areas of selected study sites and to 

investigate and describe environmental conditions that are correlated with the observed 

distribution and development of these high-density biological communities, particularly 

extensive areas of the scleractinian coral Lophelia pertusa. Six study sites were selected for 

investigation during the first field sampling effort (Cruise 1). The selection of these sites was 

based upon an analysis of existing data, using the following criteria: where the presence of the 

coral Lophelia pertusa and other significant hard-bottom megafaunal assemblages have been 

confirmed; where unidentified corals and other non-chemosynthetic megafauna have been 

reported; where corals or other megafauna have been collected; and from supportive geophysical 

data. From this selection process, six sites were chosen within the following lease area blocks: 

Viosca Knoll 826 (VK 826), Viosca Knoll 862 (VK 862), Mississippi Canyon 885 (MC 885), 

Mississippi Canyon 709 (MC 709), Green Canyon 234 (GC 234), and Green Canyon 354 (GC 

354) (Figure 2D.1). 

LOUISIANA

MISSISSIPPI ALABAMA

Gulf of Mexico

Cameron New

Orleans

N

2000 m

1000 m

2000 m

1000 m

3000 m

Gulfport

Port

Fourchon

GC 234

GC 354

MC 709

MC 885

VK 862

VK 826

30o

28o

0 25 50 NAUTICAL MILES

FLORIDA

92o 90o 88o

Figure 2D.1. Cruise 1 sampling sites. 
308 

The program has three components: physical oceanography studies; geological characterization; 

and biological characterization and studies. The objectives of the physical oceanography studies 

are to obtain information on the horizontal and vertical transport of suspended organic material 

and to investigate potential dispersal patterns for Lophelia larvae released at the study sites. The 

objectives of the geological characterization component are to provide detailed information 

pertaining to the landscape geology, geomorphology, and subsurface geology of each study site 

and to collect and interpret existing regional scale geologic data. The objectives of the biological 

characterization and studies component are 1) to provide qualitative and quantitative descriptions 

of the hard-bottom megafaunal assemblages found on each of the study sites; 2) to determine 

whether these assemblages are established on authigenic hard-bottom; 3) to determine if 

chemosynthetic/methanotrophic production is important for Lophelia nutrition; 4) to determine if 

these coral communities are similar to tubeworm-associated communities; 5) to determine 

tolerance limits of adult Lophelia to a range of temperatures, sediment loads, and food supply; 

6) to help define the environmental constraints of suitable Lophelia habitat; and 7) to determine 

the flux of sediment and zooplankton within habitat type which, in the case of sediment, may 

inhibit larval settlement or smother corals and, in the case of zooplankton, may indicate a lack of 

suitable food. 

Cruise 1 was conducted between 20 and 28 July 2004. Acceptable areas for study were located 

and surveyed at all of the proposed sites except MC 709, where no exposed hard bottom habitat 

or associated megafaunal assemblages were located. Current meter arrays were deployed at two 

sites (VK 826 and GC 234). Other tasks completed during Cruise 1 included video transects, 

photomosaics, quantitative collections using the Bushmaster sampling device, collections of 

organisms and carbonates for stable isotope analyses and taxonomic vouchers, collections of 

water samples for total petroleum hydrocarbon analyses, collections of living Lophelia colony 

fragments for laboratory experiments, collections of sediment core samples for sediment grainsize analyses, sediment trap deployments, Lophelia in situ staining, and Lophelia transplant 

deployments. 

Stephen Viada is a Senior Staff Scientist with Continental Shelf Associates, Inc., located in 

Jupiter, Florida. He has 24 years of experience in marine environmental science, including major 

research programs for federal, state, and industrial clients. He has been involved in 

characterization and monitoring studies covering a wide range of human activities in the marine 

environment, including oil and gas operations, naval ship shock trials, and coastal development 

activities. Mr. Viada received his B.S. degree in zoology from Texas A&M University in 1978 

and his M.S. in biological oceanography from Texas A&M University in 1980. 
309 

SESSION 2E 

AIR QUALITY 

Chair: Robert Cameron, Minerals Management Service 

Co-Chair: Richard McNider, University of Alabama Huntsville 

AIR QUALITY ISSUES FOR THE GULF OF MEXICO Robert Cameron ............................ 311 

BRETON EMISSIONS INVENTORY (BOADS) GULFWIDE EMISSIONS INVENTORY, 

2000 (GOADS 2000) Darcy Wilson and Richard Billings........................................................ 312 

YEAR 2005 GULFWIDE INVENTORY STUDY Darcy Wilson and Richard Billings.......... 316 

A PRELIMINARY ASSESSMENT OF ON-SHORE AIR QUALITY IMPACTS FOR 

THE EASTERN GULF COAST (LOUISIANA TO FLORIDA) USING THE 2000 

GULFWIDE EMISSIONS INVENTORY Jay L. Haney and Sharon G. Douglas.................... 320 

2000 GULF-WIDE EMISSIONS INVENTORY – OCS ON-SHORE IMPACTS 

MODELING (TEXAS), A PRELIMINARY LOOK Greg Yarwood, Gerard Mansell, 

Michele Jimenez, and Steven Lau .............................................................................................. 332 

SIMULTANEOUS VISIBILITY, MIXING HEIGHT AND PARTICULATE MATTER 

MEASUREMENTS FOR THE BRETON NATIONAL WILDLIFE AREA S. A. Hsu 

and Brian W. Blanchard.............................................................................................................. 336 

THE CURRENT STATUS OF THE SO2 AND NO2 INCREMENT ANALYSIS FOR 

THE BRETON NATIONAL WILDERNESS AREA Neil Wheeler and David Stauffer......... 340 

SATELLITE DATA ASSIMILATION INTO METEOROLOGICAL/AIR QUALITY 

MODELS Richard T. McNider and Arastoo P. Biazar ............................................................. 344 

COASTAL ATMOSPHERIC DATA GATHERING ENHANCEMENTS Gary S. Zeigler.... 347 

ENHANCEMENTS TO THE CALPUFF MODELING SYSTEM FOR OCS 

APPLICATIONS Joseph Scire, David Strimaitis, and Francoise Robe.................................... 353 
311 

AIR QUALITY ISSUES FOR THE GULF OF MEXICO 

Robert Cameron, Minerals Management Service 

Introduction 

The Minerals Management Service (MMS) has jurisdiction over Outer Continental Shelf (OCS) 

sources in the Gulf of Mexico (GOM), west of 87.5 degrees longitude. The OCS Lands Act 

established MMS’ authority and responsibility for OCS sources and established the requirement 

to comply with onshore national ambient air quality standards (NAAQS), as specified in the 

1990 Clean Air Act amendments. MMS promulgated air quality regulations (30 CFR, Part 250) 

governing oil and gas related operations on the OCS. 

Goals and Strategies 

The overarching goal of the air quality program is to comply with the governing regulations as 

outlined above. To accomplish the objective it is necessary to assess onshore air quality impacts 

to insure that operations under the regulatory authority of the MMS do not harm the 

environment. To this end, MMS evaluates OCS operator plans, collects air quality data, conducts 

air quality studies, and partners with other federal and state agencies to minimize duplication of 

effort and effectively leverage available resources. 

Bob Cameron is a senior air quality meteorologist for the Minerals Management Service (MMS) 

in New Orleans. He is currently working on MMS air pollution issues that may affect the air 

quality for states surrounding the GOM. He has previously been employed as a meteorologist in 

several other economic sectors—private, state government, and the military. In the private sector 

he worked as a television weathercaster in Omaha, Nebraska, with state government, he 

performed meteorological data analysis and modeling that was used in air quality models to 

assess Texas air pollution problem areas. His military weather jobs were varied, and ranged from 

aviation weather forecasting to instructing weather courses to managing a forecast team at a 

centralized weather forecasting facility. 
312 

BRETON EMISSIONS INVENTORY (BOADS) 

GULFWIDE EMISSIONS INVENTORY, 2000 (GOADS 2000) 

Darcy Wilson and Richard Billings, Eastern Research Group, Inc. 

Introduction 

The MMS’ Gulf of Mexico Outer Continental Shelf Regional office sponsored two recently 

completed air quality emissions inventory projects, the Gulfwide Emission Inventory for the 

Regional Haze and Ozone Modeling Effort (Wilson et al. 2004), and the Data Quality Control 

and Emissions Inventories of OCS Oil and Gas Production Activities in the Breton Area of the 

Gulf of Mexico (Billings and Wilson 2004). These studies build upon the Gulf of Mexico Air 

Quality Study (GMAQS) (U.S. DOI, MMS 1995) to assess the potential impacts of air pollutant 

emissions from offshore oil and gas exploration, development, and production sources in the 

Outer Continental Shelf (OCS). 

The Gulfwide Inventory is a base year 2000 air pollution emissions inventory for all OCS oil and 

gas production-related sources in the Gulf of Mexico (GOM), including non-platform sources. 

Pollutants covered in this inventory are the criteria pollutants—carbon monoxide (CO), nitrogen 

oxides (NOx), sulfur dioxide (SO2), particulate matter-10 (PM10), PM2.5, and volatile organic 

compounds (VOC); as well as greenhouse gases—carbon dioxide (CO2), methane (CH4), and 

nitrous oxide (N2O). The Breton Inventory covers SO2 and NOx emission sources, from 

September 2000 through August 2001, within 100 kilometers of the Breton National Wildlife 

Refuge/Wilderness Area (BNWA), which is a Prevention of Significant Deterioration Class I 

Area. 

Methodology 

To develop the inventories, the Breton Offshore Activities Data System (BOADS) and the 

Gulfwide Offshore Activities Data System (GOADS) were used to collect monthly activity data 

from platform sources. The activity data were combined with the most recent emission factors 

published by the U.S. Environmental Protection Agency (U.S. EPA) and Emission Inventory 

Improvement Program (EIIP) emission estimation methods to develop comprehensive criteria 

pollutant emissions inventories. Non-platform emission estimates were developed for sources 

such as the Louisiana Offshore Oil Platform (LOOP), commercial marine vessels, and 

helicopters. For the most part, the emission factors used to calculate the emissions from all of the 

engines for these sources were obtained from the U.S. EPA’s Office of Transportation and Air 

Quality (OTAQ) in Ann Arbor, Michigan. The resulting non-platform emission estimates are 

disaggregated to MMS lease blocks. 

In the Gulfwide Inventory, nearly 2,900 oil and gas production platforms submitted monthly 

equipment activity data files. The platform equipment surveyed includes 
313 

• Amine units • Loading operations 

• Boilers/heaters/burners • Mud degassing 

• Diesel engines • Natural gas engines 

• Drilling equipment • Natural gas turbines 

• Flares • Pneumatic pumps 

• Flashing losses • Pressure/level controllers 

• Fugitive sources • Storage tanks 

• Glycol dehydrators • Vents 

Non-platform sources covered in the inventory are: 

• Biogenic/geogenic sources • Pipe laying operations 

• Commercial fishing • Platform construction and removal vessels 

• Commercial marine vessel • Support helicopters 

• Drilling rigs • Support vessels 

• The LOOP • Survey vessels 

• Military vessel operations • Vessel lightering 

In the Breton Inventory, data for nearly 600 platforms were submitted. Platform equipment 

surveyed excluded equipment that does not emit SO2 or NOx. Non-platform sources were 

excluded if they were outside of the 100 km radius (i.e., the LOOP and vessel lightering). 

Results 

Technical reports and inventory data files for both inventories can be found at: 

http://www.gomr.mms.gov/homepg/regulate/environ/requirements.html#Air%20Quality 

Tables 2E.1 and 2E.2 summarize the emission estimates developed in each study. The technical 

reports provide details on the quality assurance/quality control (QA/QC) and emission estimation 

methods, compare the inventories to previous studies, and discuss their limitations. The 

inventory files are provided in U.S. EPA’s National Emissions Inventory (NEI) Input Format 

(NIF). A follow-on study, the Year 2005 Gulfwide Emission Inventory Study, is now underway. 
314 

Table 2E.1. Gulfwide inventory platform and non-platform emission estimates.

Equipment/ 

Source Category 

CO 

Emissions 

(tpy) 

NOx

Emissions 

(tpy) 

PM10

Emissions 

(tpy) 

SO2 

Emissions 

(tpy) 

VOC 

Emissions 

(tpy) 

Total Platform Emissions 92,144 78,049 789 3,472 59,536 

Drilling Rigs 2,862 27,270 677 4,587 263 

Helicopters 6,060 1,438 107 177 2,285 

Pipelaying Vessels 1,877 17,887 444 3,009 173 

Platform Construction and 

Removal Vessels 474 3,637 91 620 49 

Support Vessels 5,104 37,118 929 6,352 542 

Survey Vessels 19 188 5 32 2 

Total OCS Oil/Gas 

Production Source 

Emissions 

108,540 165,587 3,042 18,249 62,850 

Total Non-OCS Oil/Gas 

Production Source 

Emissions 

13,536 49,923 1,371 9,280 24,444 

Total Emissions (tpy) 122,076 215,510 4,413 27,529 87,294 

Table 2E.2. Breton inventory platform and non-platform emission estimates.

Equipment/Source Category NOx Emissions (tpy) SO2 Emissions (tpy) 

Total Platform Emissions 21,617 503.33 

Drilling Rigs 3,908 659 

Helicopters 51 6 

Pipelaying Vessels 3,228 542 

Platform Construction and 

Removal Vessels 135 22 

Support Vessels 3,275 560 

Survey Vessels 4 1 

Total OCS Oil/Gas Production 

Source Emissions 32,218 2,293.33 

Total Non-OCS Oil/Gas 

Production Source Emissions 8,368 1,519 

Total Emissions (tpy) 40,586 3,812.33 

References 

Billings, R.S. and D.L. Wilson. 2004. Data Quality Control and Emissions Inventories of OCS 

Oil and Gas Production Activities in the Breton Area of the Gulf of Mexico: Final 

Report. U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region, New Orleans, LA. OCS Study MMS 2004-071. 94 pp. 
315 

U.S. DOI, Minerals Management Service (MMS). 1995. Gulf of Mexico Air Quality Study: 

Final Report, Volumes I-III. U.S. Dept. of the Interior, Minerals Management Service, 

Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 95-0038, 95-0039, 

and 95-0040. 

Wilson, D.L., J.N. Fanjoy, and R.S. Billings. 2004. Gulfwide Emission Inventory Study for the 

Regional Haze and Ozone Modeling Effort: Final Report. U.S. Dept. of the Interior, 

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

Study MMS 2004-072. 273 pp. 

Darcy Wilson is a Senior Program Manager with Eastern Research Group (ERG) with over 17 

years of experience. Her expertise includes air pollutant emission factor and emission inventory 

development, technical writing, database development, and quality assurance/quality control. 

She has been serving as the Program Manager on several MMS Air Quality Emissions Inventory 

Studies since 1999. 

Richard Billings has an M.S. in environmental science and engineering from Virginia Tech, and 

has worked with Eastern Research Group (ERG) for 12 years. His work has focused on the 

quantification of air emissions in support of regulatory decision making and development of 

control strategies; it includes development of criteria pollutant and hazardous air pollutant 

emission factors and emission inventories for a variety of emission sources, with particular 

attention to mobile sources such as marine vessels and support helicopters. He has also 

developed emission estimates for platform emission sources and marine biogenic and geogenic 

sources. 
316 

YEAR 2005 GULFWIDE INVENTORY STUDY 

Darcy Wilson and Richard Billings, Eastern Research Group, Inc. 

Introduction 

The MMS’ Gulf of Mexico Outer Continental Shelf Regional Office is sponsoring this project to 

develop a gulfwide, base-year 2005, emissions inventory for criteria pollutants and greenhouse 

gases. This study builds upon several previous emissions inventory efforts in the Gulf of Mexico 

(GOM) designed to assess the potential impacts of air pollutant emissions from offshore oil and 

gas exploration, development, and production sources in the Outer Continental Shelf (OCS). In 

particular, this study will serve as an update to the base year 2000 Gulfwide Emission Inventory 

Study for the Regional Haze and Ozone Modeling Effort (Wilson et al. 2004). 

MMS published Notice to Lessees and Operators (NTL) 2004-G17 to introduce the “Production 

Activities Information Collection and Reporting for Calculations of Air Emissions in the 

Western Gulf” requirements for lessees and operators of federal oil, gas, and sulfur leases in the 

Gulf of Mexico OCS Region. A workshop was held in New Orleans, Louisiana, 13 October 2004 

to discuss and explain the 2005 Gulfwide Offshore Activities Data System (GOADS-2005) 

information collection and reporting procedures, the pollutants to be covered in the study, and 

why the 2005 GOADS study was being undertaken. Much of the information provided is 

available on the GOADS website: 

http://www.gomr.mms.gov/homepg/regulate/environ/airquality/goad.html 

Information posted on this website by MMS includes: 

• The NTL issued informing operators about the 2005 Gulfwide Inventory Study and 

telling them about the 13 October 2004 workshop. 

• Technical support with information on how they can obtain their 2000 data sets to use as 

a starting point for the 2005 inventory. 

• The GOADS-2005 data collection software and User’s Guide. 

• Frequently Asked Questions (FAQs) and a link to an ERG listserv website developed so 

platform operators can submit questions and get technical responses directly from the 

ERG and MMS inventory development team. 

• The 13 October 2004 workshop presentation. 

Similarities to the 2000 Gulfwide Inventory Study 

The development of the 2005 Gulfwide Inventory will be similar to that of the 2000 Gulfwide 

Inventory in a number of ways: 
317 

• Emission estimates will be developed for criteria pollutants—carbon monoxide (CO), 

nitrogen oxides (NOx), sulfur dioxide (SO2), particulate matter-10 (PM10), PM2.5, and 

volatile organic compounds (VOC); and greenhouse gases—carbon dioxide (CO2), 

methane (CH4), and nitrous oxide (N2O). 

• The inventory will cover the western Gulf of Mexico (OCS west of 87° 30’ west 

longitude and north of 25° 15’ North latitude). 

• Both platform and non-platform sources will be included in the inventory. 

• Monthly activity data and stack parameters for platform equipment will be collected 

electronically with the Visual Basic GOADS-2005 software. 

• The activity data will be combined with emission factors published by the U.S. 

Environmental Protection Agency (U.S. EPA), and Emission Inventory Improvement 

Program (EIIP) emission estimation methods. 

• Emission estimates for amine units will be developed with AMINECalc. 

• Emission estimates for glycol dehydrators will be developed using regression equations 

for typical operating conditions. 

• Activity data for 2005 will be collected for all non-platform emission sources such as 

support vessels, the Louisiana Offshore Oil Platform, and pipelaying operations. 

• The emission factors used to calculate the emissions from all of the engines for the nonplatform sources will be those developed by the U.S. EPA’s Office of Transportation and 

Air Quality (OTAQ) in Ann Arbor, Michigan. 

• The resulting non-platform emission estimates will be disaggregated to MMS lease 

blocks. 

• Diurnal emission curves will be revised or developed for all source categories. 

• Files for use in air quality modeling and other studies will be provided in U.S. EPA’s 

National Emissions Inventory (NEI) Input Format (NIF) and supporting GIS data sets. 

Details on the quality assurance/quality control (QC/QC) and emission estimation methods, and 

the inventory data files for the 2000 Gulfwide Inventory can be found at: 

http://www.gomr.mms.gov/homepg/regulate/environ/requirements.html#Air%20Quality 
318 

Improvements Over the 2000 Gulfwide Inventory Study 

As the 2000 Gulfwide Inventory was being developed, several areas for improvement were 

noted. For the 2005 Gulfwide Inventory, the following improvements will occur: 

• The GOADS-2005 data collection software has been improved to make the program 

operate faster and more efficiently. We worked closely with members of the Offshore 

Operators Committee (OOC) to identify and implement these improvements. 

• An on-line GOADS-2005 FAQ forum (the GOADS-2005 listserv) has been established 

for platform operators to directly submit questions and receive responses related to 

technical and software issues encountered. 

• The emission estimates will be developed using up-to-date emission factors as needed, 

and any additional recommended emission estimation improvements will be 

implemented. 

• In-depth surveys will be conducted to improve the activity data collected for support 

helicopters, support vessels, and survey vessels. 

• Commercial marine vessel shipping lanes will be mapped using the latest GIS tools in 

conjunction with detailed vessel data from the U.S. Army Corps of Engineers. 

• The diurnal emission curves will be reviewed and revised as needed, especially those 

developed for support helicopters and vessels. 

Results 

The Year 2005 Gulfwide Emission Inventory Study will be completed by June 2007. Deliverables 

associated with the project will include a technical report detailing the QA/QC and emission 

estimation approaches used for platform and non-platform sources located in the Western GOM. 

Files for use in air quality modeling studies will be provided in U.S. EPA’s National Emissions 

Inventory (NEI) Input Format (NIF). The users of the data files include U.S. EPA, state and local 

agencies, and Regional Planning Offices (RPOs) studying regional haze and ozone 

nonattainment issues, as well as scientists studying the impact of greenhouse gas emissions and 

the contribution of sources in the GOM. Oil and gas industry personnel may also benefit by 

reviewing the data to identify and quantify sources of profitable natural gas losses and 

prioritizing research into loss product prevention methods. 

References 

Wilson, D.L., J.N. Fanjoy, and R.S. Billings. 2004. Gulfwide Emission Inventory Study for the 

Regional Haze and Ozone Modeling Effort: Final Report. U.S. Dept. of the Interior, 

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

Study MMS 2004-072. 273 pp. 
319 

Darcy Wilson is a Senior Program Manager with Eastern Research Group (ERG) with over 17 

years of experience. Her expertise includes air pollutant emission factor and emission inventory 

development, technical writing, database development, and quality assurance/quality control. 

She has been serving as the Program Manager on several MMS Air Quality Emissions Inventory 

Studies since 1999. 

Richard Billings has an M.S. in environmental science and engineering from Virginia Tech, and 

has worked with Eastern Research Group (ERG) for 12 years. His work has focused on the 

quantification of air emissions in support of regulatory decision making and development of 

control strategies; it includes development of criteria pollutant and hazardous air pollutant 

emission factors and emission inventories for a variety of emission sources, with particular 

attention to mobile sources such as marine vessels and support helicopters. He has also 

developed emission estimates for platform emission sources and marine biogenic and geogenic 

sources. 
320 

A PRELIMINARY ASSESSMENT OF ON-SHORE AIR QUALITY IMPACTS FOR 

THE EASTERN GULF COAST (LOUISIANA TO FLORIDA) USING 

THE 2000 GULFWIDE EMISSIONS INVENTORY 

Jay L. Haney and Sharon G. Douglas, Systems Applications International, LLC 

Introduction and Background 

This paper summarizes the results of a photochemical modeling analysis conducted to provide a 

preliminary assessment of impacts from offshore emission sources on the coastal areas of 

Louisiana, Mississippi, Alabama, and Florida using a newly developed offshore emission 

inventory for 2000 for the Central and Western Planning Areas of the Gulf of Mexico (GOM) 

region. 

The Minerals Management Service of the U.S. Department of Interior has jurisdiction over the 

activities involved in the exploration and development of mineral resources in the Outer 

Continental Shelf (OCS) of the GOM. The agency’s responsibility includes, among other things, 

the assessment of the environmental effects of such activities in both offshore and onshore areas. 

During 1992–1995, the MMS conducted the Gulf of Mexico Air Quality Study (GMAQS), 

which was specifically mandated by Congress in the Clean Air Act Amendments of 1990 to 

assess air quality impacts in onshore ozone nonattainment areas from emission sources located in 

the Western and Central Planning Areas of the OCS (Systems Applications International et al. 

1995). The study included the development of a comprehensive inventory of emission sources in 

OCS waters for 1993, which was recently updated for 2000 through the development of the 

Gulfwide Offshore Activities Data System (GOADS). 

Since the conclusion of GMAQS, three regional ozone modeling studies, involving the 

application of the variable-grid Urban Airshed Model (UAM-V) modeling system, have been 

conducted to address one-hour and potential eight-hour ozone issues in coastal areas of the 

eastern GOM. These include the Gulf Coast Ozone Study (GCOS), the Baton Rouge ozone SIP 

modeling analysis, and the follow-on study to GCOS, known as the West Florida Ozone Study 

(WFOS). From these studies, six episodes (September 1997, August 1997, May 1996, July 1998, 

1–8 August 1999, and 13–26 July 2000) were available, and the 1–8 August 1999 period was 

selected as the period exhibiting the largest potential for emissions from offshore sources to 

affect ozone concentrations in the coastal areas of Louisiana, Mississippi, Alabama, and Florida. 

Offshore Emissions Inventory 

The first major task involved the acquisition and processing of the new Gulfwide 2000 emission 

inventory, as developed by ERG (2003) into a format that could be merged with the existing 

modeling inventories for the 1–8 August 1999 period using EPA’s UAM Emission Preprocessor 

System, Version 2.5 (EPS 2.5). (It should be noted that a preliminary inventory was obtained and 

used in this modeling analysis, and that, subsequent to the completion of this study, large errors 

in platform VOC emissions were discovered and corrected by MMS in the final release of the 

inventory which is presented in the report “Gulfwide Emissions Inventory Study for the Regional 
321 

Haze and Ozone Modeling Effort,” October 2004, OCS Study MMS 2004-072. The preliminary 

inventory platform VOC emissions totals are 409 tpd, while the final emissions are 163 tpd). The 

2000 inventory included emissions from OCS oil-production related platform and non-platform 

sources as well as from non-oil-related sources, such as commercial marine vessels, a 

comparison of which is presented in Figure 2E.1. 

Daily Emissions for 2000

0

100

200

300

400

500

NOx VOC CO

tpd

Platform Other OCS-oil Other Offshore

Figure 2E.1. Comparison of emissions from platform, oil-related non-platform, and other offshore sources 

operating in the Gulf of Mexico for 2000. (Preliminary draft platform VOC inventory (409 tpd) 

in lieu of final platform inventory (163 tpd).). 

Emissions from oil-related sources are substantially larger than those associated with non-oil 

related activities in this area. One objective of this modeling analysis is to assess impacts of 

offshore emissions on onshore areas of interest in Louisiana, Mississippi, Alabama, and Florida. 

Figure 2E.2 depicts the parishes and counties that make up the Baton Rouge, New Orleans, 

Mississippi coastal counties, Mobile, and Pensacola areas. 

Air Quality Modeling Approach 

Once the new offshore inventory was processed and merged with the existing onshore inventory, 

the second major task of this analysis involved the application of the UAM-V photochemical 

model with the Carbon Bond 5 chemical mechanism (UAM-V5) using the grid configuration of 

the Gulf Coast Ozone Study (Figure 2E.3) and includes 36-, 12-, and 4-km resolution grids 

encompassing the offshore and onshore areas of interest. After the new 2000 offshore emissions 

inventory was prepared, processed, and incorporated into the modeling inventory for the August 

1999 episode, the base case simulation, one emission reduction simulation, and two simulations 

in which the precursor emissions were tagged or tracked using the Oxidant and Precursor 

Tagging Methodology (OPTM) feature of UAM-V5 were completed for the 2000 OCS inventory 

impact assessment: 
322 

Baton Rouge Area

New Orleans Area

MS Gulf Coast Area

Mobile Area

Pensacola Area

Bay County Area

Baton Rouge Area

New Orleans Area

MS Gulf Coast Area

Mobile Area

Pensacola Area

Bay County Area

Baton Rouge Area

New Orleans Area

MS Gulf Coast Area

Mobile Area

Pensacola Area

Bay County Area

Figure 2E.2. Coastal areas of interest for assessment of on-shore impacts 

Horizontal Grid Resolution Is Approximately 36 km for Grid 1, 12 km for Grid 2, 4 km for Grids A, B, and C. 

Figure 2E.3. GCOS/WFOS UAM-V5 modeling domain used for the MMS OCS 2000 modeling analysis. 
323 

• M-1 2000 Base case simulation with no oil-related offshore emissions 

• MT-1 2000 Base case with geographic emissions tags (OPTM simulation) 

• MT-2 2000 Base case with source category emission tags (OPTM simulation) 

In the sensitivity simulation (M-1), emissions from all OCS oil-related sources were zeroed out. 

Figure 2E.4 presents differences of simulated daily maximum one-hour concentrations for Grid 

C for 8 August 1999 showing the “impacts” from all oil-related offshore sources. Because of the 

prevailing wind conditions, there are very few impacts in the onshore coastal areas of interest 

during the first few days of the episode. With the change in the winds to a more southerly 

direction, the magnitude and inland extent of the impacts are larger on 7–8 August, with impacts 

generally less than 10 ppb reaching the Alabama and Florida panhandle areas on 8 August. 

MAX: 20.7 ppb

MIN: -0.2 ppb

-10 -5 -2.5 -1 1 2.5 5 10

Figure 2E.4. Simulated maximum hourly ozone impacts (ppb) from OCS oil-related emission sources for 8 

August 1999. (Preliminary draft platform VOC inventory (409 tpd) in lieu of final platform 

inventory (163 tpd)). 

Impacts were assessed at a number of in-land monitoring sites in the areas of interest. The results 

indicate that there are no impacts at these monitors on 3–5 August, that there are some impacts at 

a few monitors on 6 August, and that OCS impacts occur at most sites on 7–8 August, with the 

largest impacts occurring on 8 August, when the prevailing flow along the coast is southerly. 

Although the largest impacts occur on 8 August (as much as 7 ppb), this is a clean-out day and 

observed and simulated one-hour concentrations are lower throughout the Grid C area compared 

to 7 August. 

In addition to the impacts on simulated one-hour average concentrations, differences of 

simulated daily eight-hour maximum concentrations for Grid C show that the maximum 

simulated concentrations are located offshore (within Grid C) for each of the simulation days and 
324 

that the simulated eight-hour impacts are quite similar in spatial characteristics to the one-hour 

concentration impacts, with the maximum impacts occurring on 7–8 August. The results indicate 

that, as with the one-hour concentrations, there are no impacts at these monitors on 3–5 August, 

that there are some impacts at a few monitors on 6 August, and that OCS impacts occur at most 

sites on 7–8 August, with the largest impacts occurring on 8 August. Although the largest 

impacts to eight-hour averages occur on 8 August (as much as 6.6 ppb), this is a clean-out day 

and observed and simulated eight-hour concentrations are lower throughout the Grid C area than 

for 7 August. An examination of impacts at monitoring sites located in Grid C indicates that the 

OCS emissions contribute to a simulated exceedance at eight sites in the Baton Rouge area on 7 

August, with contributions less than 1 ppb. There are a few sites on 8 August (Capitol, French 

Settlement, and Grosse Tete, Louisiana) for which the simulated maximum eight-hour 

concentrations are greater than 85 ppb, and the simulated contributions of the OCS emissions to 

ozone concentrations are on the order of 2–3 ppb. However, there were no observed eight-hour 

exceedances at these sites on 8 August, and therefore, this metric should not be considered for 

this day. 

Another way of assessing impacts from the zero-out sensitivity simulations is to evaluate the 

effects in terms of 1- and eight-hour ozone exceedance exposure. As noted above, these metrics 

provide a summary of the amount of one-hour average ozone in each grid cell greater than 124 

ppb, and the amount of eight-hour average ozone in each grid cell greater than 85 ppb. For this 

analysis, the 1- and eight-hour exposure metrics were computed for all hours of all non-startup 

days of the episode (3–8 August 1999). For this particular metric, the oil-related sources 

contribute about 7.4% to the total one-hour exceedance value in Grid C, about 9% to this metric 

in the offshore portion of Grid C, and less than 1% to this metric in the onshore areas of Grid C. 

Figure 2E.5 presents differences in simulated eight-hour average concentrations for 8 August for 

grid cells where simulated concentrations are greater than 85 ppb. The results indicates that 

offshore oil-related emissions contribute to simulated eight-hour exceedances in the onshore 

areas of interest on 4–6 August with contributions of 1 ppb or less. However, on 7 and 8 August, 

the impacts to simulated eight-hour exceedances in the Baton Rouge area are on the order of 1–6 

ppb. For eight-hour exceedance exposure, the oil-related sources contribute about 8% to the total 

eight-hour exceedance value in Grid C; about 11% to this metric in the offshore portion of Grid 

C, and about 2% to this metric in the onshore areas of Grid C. Figure 2E.6 presents eight-hour 

exceedance exposure values for these areas. 

Oxidant Tagging Simulations 

Another way of assessing impacts is to use the UAM-V5’s Ozone and Precursor Tagging 

Methodology (OPTM) approach and tag the offshore precursor emissions. OPTM provides 

estimates of the contribution of emissions from specified source categories or source regions to 

the simulated ozone concentrations. The estimates are made for the existing conditions within the 

simulation and do not require that the system be perturbed (e.g., zeroed out) in order to make the 

estimate. In addition, estimates for several categories can be made in a single simulation. The 

OPTM system tracks the amount of oxidant (the sum of NO2 and ozone) formed from various 

tagged source categories as a method of estimating the contributions to ozone. 
325 

MAX: 4.4 ppb

MIN: 0.1 ppb

-10 -5 -2.5 -1 1 2.5 5 10

Figure 2E.5. Simulated maximum eight-hour average ozone impacts (ppb) from OCS oil-related emission 

sources for 8 August 1999 for grid cells with simulated eight-hour concentrations in the base 

case greater than 85 ppb (preliminary draft platform VOC inventory (409 tpd) in lieu of final 

platform inventory (163 tpd).). 

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

Grid C Offshore Onshore

ppb

Base No Platforms No OCS oil

Figure 2E.6. Comparison of simulated eight-hour ozone exceedance exposure (ppb) for grid c, the offshore 

portion of grid c, and the onshore portion of grid c, comparing the base case with the OCS 

zero-out sensitivity simulations (3–8 August 1999). Preliminary draft platform VOC inventory 

(409 tpd) in lieu of final platform inventory (163 tpd).). 
326 

OPTM Scenario MT-1 

For this first scenario, the assignment of the tags focused on the offshore areas and the emissions 

contained in the four key Gulf Coast states. The first tag tracked emissions from anthropogenic 

emissions in Louisiana; the second tracked emissions from Mississippi; the third tagged 

emissions from Alabama; and the fourth tag tracked emissions from Florida. A fifth tag tracked 

emissions from all offshore sources beyond state waters. A sixth tag tracked emissions from all 

other areas, including biogenic emissions. 

The OPTM results are displayed in Figure 2E.7 and depict the contribution to simulated eighthour average ozone from NOx and VOC, respectively, corresponding to emissions tagged for 

each geographic area for 1700 EST for 7 August 1999. This is one of the key high ozone days for 

monitoring sites located along the eastern Gulf Coast. The “footprint” of the contribution to 

simulated ozone for NOX indicates that for this day and time, offshore sources of NOx contribute 

to the ozone concentrations in onshore areas of southern Louisiana and coastal Mississippi. The 

contributions from VOC emissions are smaller and are confined to southern Louisiana. 

An analysis of the contributions to eight-hour ozone concentrations in the offshore portion of 

Grid 2, the largest contributor to eight-hour concentrations, is from biogenic emissions and 

sources located onshore in states other than the four Gulf Coast states. Moderate contributions 

are shown for Louisiana and Mississippi emissions, with offshore sources showing a nonnegligible contribution. 

OPTM Scenario MT-2 

For the second tagging scenario, individual tags were placed on NOx and VOC emissions of all 

offshore/OCS oil-related platform sources, all offshore/OCS oil-related non-platform sources, all 

offshore non-oil related sources, all sources operating in state waters, and all other sources in the 

modeling domain. Figure 2E.8 depicts the contribution to simulated maximum eight-hour 

average ozone from NOx and VOC, respectively, corresponding to emissions tagged for each tag 

for 7 August 1999. For these figures, the contributions from the two offshore source tags were 

combined. The figures show the relative contributions from both oil-related and non-oil related 

offshore sources, including those in state waters. For this particular day, contributions from the 

offshore oil-related NOx sources are found in the southern Louisiana and along the coastal areas 

of Mississippi and are larger than contributions from non-oil related and state waters sources. For 

VOC emissions, small contributions are seen in southern Louisiana from oil-related sources. 

Figure 2E.9 shows the individual contributions to the average maximum eight-hour concentrations in the offshore area of Grid 2 for the period 3–8 August 1999. The figure depicts the contribution from NOx and VOC emissions from each offshore source categories to the total offshore 

contribution to the maximum eight-hour concentrations. The figure indicates that when the average maximum eight-hour ozone is considered over the key episode days, for VOC emissions, the 

major contributors to the offshore portion of the maximum eight-hour average ozone concentrations in the offshore area of Grid 2 are platform sources, and for NOx emissions, the largest contributors are non-oil related sources followed by sources in state waters and platform sources. 
327 

(a) 

Louisiana anthropogenic emissions (max: 78.6 ppb) MS+AL+FL anthropogenic emissions (max: 52.4 ppb)

Offshore emissions (max: 28.8 ppb) All other emissions (max: 80.1 ppb)

2 5 15 25 35 45 55 65 75

(b) 

Louisiana anthropogenic emissions (max: 20.2 ppb) MS+AL+FL anthropogenic emissions (max: 8.4 ppb)

Offshore emissions (max: 11.3 ppb) All other emissions (max: 111.0 ppb)

2 5 15 25 45 55 65 75 85

Figure 2E.7. (a) Max eight-hour ozone apportioned by NOX emissions (ppb) for 7 August 1999. Showing 

contributions from onshore and offshore emissions. (b) Max eight-hour ozone apportioned by 

VOC emissions (ppb) for 7 August 1999. Showing contributions from onshore and offshore 

emissions. (Preliminary draft platform VOC inventory (409 tpd) in lieu of final platform 

inventory (163 tpd).) 
328 

(a) 

Oil-related emissions (max: 23.7 ppb) Non-oil related offshore emissions (max: 12.6 ppb)

State water emissions (max: 4.9 ppb) All other emissions (max: 125.7 ppb)

2 5 15 25 45 55 65 75 85

(b) 

Oil-related emissions (max: 11.0 ppb) Non-oil related offshore emissions (max: 2.8 ppb)

State water emissions (max: 0.2 ppb) All other emissions (max: 126.4 ppb)

2 5 15 25 45 55 65 75 85

Figure 2E.8. (a) Max eight-hour ozone apportioned by NOX emissions (ppb) for 7 August showing 

contributions from onshore and offshore emissions (Scenario MT-2). (b) Max eight-hour ozone 

apportioned by VOC emissions (ppb) showing contributions from onshore and offshore 

emission (Scenario MT-2). (Preliminary draft platform VOC inventory (409 tpd) in lieu of 

final platform inventory (163 tpd).) 
329 

0123456

NOx

VOC

ppb

Total Offshore O/G platform O/G non-platform Non O/G State waters

Figure 2E.9. Simulated contributions (ppb) from each offshore source category to the total offshore 

contribution to the daily average maximum eight-hour ozone concentrations in the offshore 

area of grid 2 from sources located in offshore areas of the Gulf Coast (OPTM Scenario MT-2 

for 3–8 August 1999). (Preliminary draft platform VOC inventory (409 tpd) in lieu of final 

platform inventory (163 tpd).) 

Summary 

In this study, a photochemical modeling analysis was conducted to assess the impacts of offshore 

sources located in the Central and Western Gulf of Mexico OCS areas on onshore areas of 

interest in the states of Louisiana, Mississippi, Alabama, and Florida, using the newly developed 

(although draft) 2000 Gulfwide offshore emission inventory. 

After the base case was re-run with the new offshore inventory, a simulation involving the 

omission of platform sources and all oil-related sources was conducted. The results indicate that 

for this particular modeling episode, the onshore impacts from all offshore oil-related sources are 

less than 10 ppb. The contribution to grid cells in which the one-hour average simulated 

concentration is greater than 124 ppb was assessed to determine whether the offshore emissions 

possibly contributed to exceedances of the one-hour standard. For this episode, simulated onehour exceedances occurred on 6–7 August in the Baton Rouge area, and the contribution of 

offshore emissions was 2 ppb or less. An examination of impacts at monitoring sites located in 

Grid C indicates that the OCS emissions contribute to a simulated exceedance of the one-hour 

standard at only one site on one day: the LSU, Louisiana site on 7 August, with a very small 

contribution of 0.3 ppb. Similarly, the contribution to grid cells in which the eight-hour average 
330 

simulated concentration is greater than 85 ppb was examined to determine whether the offshore 

emissions possibly contribute to an exceedance of the eight-hour standard. The results indicate 

that offshore oil-related emissions contribute to simulated eight-hour exceedances in the onshore 

areas of interest on 4–6 August with contributions of 1 ppb or less. However, on 7 and 8 August, 

the impacts to simulated eight-hour exceedances in the Baton Rouge area are on the order of 1–6 

ppb. An examination of impacts at monitoring sites located in Grid C indicates that the OCS 

emissions contribute to a simulated exceedance at eight sites in the Baton Rouge area on 7 

August, with contributions less than 1 ppb, and at three sites (Capitol, French Settlement, and 

Grosse Tete) on 8 August, with impacts of 2–3 ppb. Although there are simulated exceedances of 

the eight-hour standard at these sites, there were no observed exceedances at these sites on 8 

August, so the OCS impacts are being affected by an overestimation of ozone by the model in 

the Baton Rouge area on this particular day. 

Ozone exceedance exposure metrics were also computed for one- and eight-hour ozone. The 

results indicate that oil-related offshore emissions contribute about 7.4% to the total one-hour 

exceedance exposure in Grid C, about 9% to this metric in the offshore portion of Grid C, and 

less than 1% to this metric in the onshore areas of Grid C. For eight-hour exceedance exposure, 

the offshore oil-related sources contribute about 8% to the total eight-hour exceedance value in 

Grid C, about 11% to this metric in the offshore portion of Grid C, and about 2% to this metric in 

the onshore areas of Grid C. 

In addition to the emission reduction simulations, two simulations were conducted using the 

OPTM feature of UAM-V5, which allows one to tag and track the contributions from specific 

source categories or regions to simulated ozone concentrations in the modeling domain. The 

results of these simulations indicate that, for this particular modeling episode, the contribution to 

simulated ozone in the onshore areas of interest from offshore oil-related sources is small. It 

should be noted that, in light of the use of an incorrect preliminary VOC platform inventory 

containing 50% more emissions than the final inventory, the simulated impacts on one- and 

eight-hour concentrations may be less than reported here. 

References 

ERG. 2003. Gulfwide Emission Inventory for the Regional Haze and Ozone Modeling Effort. 

Final Report. ERG Inc. 

Systems Applications International, Sonoma Technology, Inc., Earth Tech, Alpine Geophysics, 

and A.T. Kearney. 1995. Gulf of Mexico Air Quality Study, Final Report. Volume I: 

Summary of Data Analysis and Modeling. U.S. Dept. of the Interior, Minerals 

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

MMS95-0038. 654 pp. 

Sharon G. Douglas is a Project Manager in Atmospheric Sciences for Systems Applications 

International Inc. (SAI), a She has an M.S. in meteorology from Penn State University. 
331 

Ms. Douglas has more than 17 years of experience at SAI/ICF and has been principally involved 

in the development and application of innovative data analysis techniques and meteorological 

and air quality modeling tools. 

Jay L. Haney is Group Vice President and Director of the Air Quality Modeling Group at 

Systems Applications International (SAI), a wholly-owned subsidiary of ICF Consulting. He is a 

Certified Consulting Meteorologist and has an M.S. in meteorology from Saint Louis University. 

He as 25 years of experience in the refinement of data analysis and modeling techniques applied 

to the study of tropospheric ozone, carbon monoxide, and particulate matter. 
332 

2000 GULF-WIDE EMISSIONS INVENTORY – OCS ON-SHORE IMPACTS 

MODELING (TEXAS), A PRELIMINARY LOOK 

Greg Yarwood, Gerard Mansell, Michele Jimenez and Steven Lau, 

ENVIRON International Corporation 

The MMS oversees exploration and production of mineral resources in the Gulf of Mexico 

(GOM) including oil and gas activities on the outer continental shelf (OCS). Air emissions from 

OCS oil and gas related activities include ozone precursors, namely nitrogen oxides (NOx), 

volatile organic compounds (VOCs) and carbon monoxide (CO). There are several urban areas 

near the Gulf Coast that exceed the National Ambient Air Quality Standard (NAAQS) for ozone. 

Ozone levels in these ozone non-attainment areas depend both upon local emissions and 

transport of ozone and precursors from upwind areas. The MMS and Gulf Coast States share an 

interest in evaluating the influence of OCS emissions on ozone levels in NAAs near the Gulf 

Coast. 

The MMS completed an emission inventory for year 2000 called the Gulf-Wide Emissions 

Inventory (2000 GWEI). This study provides a preliminary assessment of impacts of the 2000 

GWEI on ozone levels in the Houston area of Texas. Houston was chosen because the 

Houston/Galveston/Brazoria (HGB) non-attainment area has the most severe ozone problem in 

Texas and is adjacent to the GOM. The Texas Commission on Environmental Quality (TCEQ) is 

responsible for air quality planning in Texas and uses photochemical modeling to develop State 

Implementation Plans (SIPs) for the HGB ozone non-attainment area. This study used ozone 

models and modeling tools used by the TCEQ for SIP planning in the Houston area (TCEQ 

2004). Ozone modeling used the CAMx air quality model (ENVIRON 2004) with an 22 August– 

6 September 2000 episode period. The CAMx modeling domain had two-way nested grids with 

36-km, 12-km, 4-km and 1-km resolution and 15 to 24 vertical layers as shown in Figure 2E.10. 

FINDINGS 

This assessment used a preliminary version of the 2000 GWEI in which the VOC emissions from 

platform sources were more than 50% higher than they should have been: This fact should be 

taken into account in considering the reported ozone impacts. The main findings on modeled 

impacts of OCS emissions in the 2000 GWEI on ozone levels in the Houston area are 

• The 2000 GWEI emissions produce similar episode average impacts for 1-hr and 8-hr 

ozone in the 11 county Houston/Beaumont area of 2.3 ppb and 2.2 ppb, respectively. 

• The average impacts of OCS emissions on ozone levels in the Houston area are smaller 

(and negative in the case of 1-hr ozone) when the analysis is restricted to ozone levels 

above the NAAQS. 

• The average impact of the 2000 GWEI emissions on eight-hour ozone levels above 85 

ppb in the 11 county Houston/Beaumont area is 0.2 ppb. 
333 

36-km, 12-km, 4-km and 1-km Grids 

15 Layers for 

36 and12 km Grids 

24 Layers for 

4 and 1 km Grids 

Figure 2E.10. CAMx nested grid modeling domain and layer structures for the TexAQS 22 August to 6 

September 2000 ozone episode in the Houston area. 

Larger ozone impacts occur over the GOM. The episode maximum impacts of the 2000 GWEI 

emissions on eight-hour ozone are shown in Figure 2E.11 for the CAMx 12-km grid. The ozone 

impacts were estimated using the “zero-out” method that measures the change in ozone when the 

2000 GWEI emissions are removed. 

The ozone impacts from the 2000 GWEI were compared to impacts from the GMAQS emission 

inventory being used by the TCEQ in current modeling studies. The average impact of the 

GMAQS emissions on eight-hour ozone above the level of the eight-hour standard in the 

Houston area is 0.6 ppb, which is three times larger than the impact of the 2000 GWEI. 

A sensitivity test was conducted to investigate the relative roles of NOx vs. VOC emissions in 

the 2000 GWEI ozone impacts. This analysis indicates that the ozone impacts of OCS emissions 

are limited by the VOC emissions over the GOM. The finding that the ozone impacts of OCS 

emissions are limited by VOC emissions is potentially important since it suggests that the most 

effective way of managing OCS impacts on ozone in the GOM will be to control VOC 

emissions. Other analyses should be undertaken to independently confirm this finding. 

ACKNOWLEDGMENT 

The emissions modeling staff of the TCEQ assisted this study by preparing certain emissions 

data for use in the ozone modeling. The graphics for Figure 2E.10 were provided by the TCEQ. 
334 

Figure 2E.11. Episode maximum eight-hour ozone impacts of the 2000 GWEI for the 12-km grid. Preliminary 

modeling/assessment using draft platform VOC emissions that were more than 50% higher 

than they should have been. 

REFERENCES 

ENVIRON. 2004. User's Guide, Comprehensive Air Quality Model With Extensions (CAMx), 

Version 4.00. ENVIRON International Corporation. Novato, CA. January. 

http://www.camx.com. 

TCEQ. 2004. HGB Mid-Course Review SIP Narrative. Texas Commission on Environmental 

Quality. June 23. http://www.tnrcc.state.tx.us/oprd/sips/june2004hgb_EDrec.html#docs. 

Dr. Greg Yarwood is a Principal with the ENVIRON Air Sciences group in Novato, California. 

He is an international expert in photochemical modeling and atmospheric chemistry. He designs 

the Comprehensive Air Quality model with extensions (CAMx) which is a public domain 

photochemical grid model for ozone, fine particulate and visibility modeling developed by 

ENVIRON. 
335 

Dr. Gerrard Mansell is a Senior Consultant with the ENVIRON Air Sciences group in Novato, 

California. He is an expert in GIS, emissions modeling and air quality modeling. He developed 

GIS-based ammonia and dust models currently being used for regional haze modeling. 

Ms. Michele Jimenez is an expert in emissions modeling for photochemical air-quality modeling 

with the ENVIRON Air Sciences group in Novato, California. She was an original developer of 

the EPS2 emissions processing system and now is developing the CONCEPT emissions 

modeling system based on open-source SQL tools suitable for cluster computing. 

Mr. Steve Lau is an air quality modeler with the ENVIRON Air Sciences group in Novato, 

California. He is proficient with many air-quality modeling systems including CAMx, CMAQ, 

CalPuff/CalMet and UAM. 
336 

( )

( )( ) L

T U

T T B

air z

sea air

= − +

− +

2732

100 1 0 07

2 .

.

( )

( ) L

T U

T T

air z

air sea

= +

−

2732

62

2 .

B TT = − 0146( sea air )

0 49 . .

SIMULTANEOUS VISIBILITY, MIXING HEIGHT AND PARTICULATE MATTER 

MEASUREMENTS FOR THE BRETON NATIONAL WILDLIFE AREA 

S. A. Hsu and Brian W. Blanchard, Coastal Studies Institute, 

Louisiana State University 

Introduction 

In response to regulations imposed by the 1999 Regional Haze Rule, a visibility and 

meteorological monitoring station has been established within the Delta National Wildlife 

Refuge at Pass-A-Loutre (PAL, 29°7.133'N 89°12.296'W). The station has been operational 

since April 2004, and the data return rate has been excellent. Two other visibility stations are 

also being maintained, offshore at LSU WAVCIS CSI-3 and CSI-6 (see www.wavcis.lsu.edu for 

more information). Data sets from all stations are being compiled, and research continues on 

occurrences of reduced visibility (fog and haze), and associated characteristics of the 

atmospheric boundary layer. This presentation summarizes some preliminary findings, including 

a restricted visibility case study and observations of winds above the 100 m level over the 

Louisiana coast. 

Regional Conditions 

In mid-September 2004, Hurricane Ivan moved through the eastern Gulf of Mexico (GOM) and 

made landfall along the Alabama coast. Our PAL station recorded very high winds 

(approximately 28 m/s) and a minimal pressure of about 980 mb. It was later determined that the 

relative humidity sensor was damaged during this event. Therefore, the summer period of May 

through August 2004 is discussed here. 

The atmospheric boundary layer is generally classified as either unstable, near-neutral, or stable. 

The buoyancy length scale L is a parameter used to determine the stability by describing the 

relative importance between the buoyancy effect (or thermal turbulence) and the wind shear (or 

mechanical turbulence) (see Panofsky and Dutton, 1984). Hsu and Blanchard (2004) have shown 

that for unstable conditions (when Tsea > Tair), 

(1) 

and for stable conditions (Tsea < Tair), 

(2) 

where B is the Bowen ratio provided by (see Hsu, 1999) 

(3) 
337 

Z L i = + 828 4

Z TT i air dew = − 125( )

This criterion was applied to the hourly records from the National Data Buoy Center buoys 

42007 to the north of the PAL location, and buoy 42040 to the east. It is found that during May 

and June, neutral conditions prevail over unstable at both stations; about 65% of the time at 

42007 and 74% at 42040. However, in July and August, unstable conditions occurred almost as 

frequently as neutral, about 52% at 42007 and 53% at 42040. Less than ten hours per month 

were identified as stable at both stations. 

In air pollution studies, estimation of the mixing height (Zi) is essential to determine the vertical 

limit for pollution dispersion. For unstable conditions, according to Hsu (2004) 

(4) 

where L is obtained from Eqs. (1) and (3). In neutral conditions (see Hsu 1998) 

(5) 

The average monthly mixed heights computed for buoy 42007 increase from 664 m in May to 

823 m in August. Similarly, heights at 42040 increase from 533 m in May to 767 m in August; 

slightly higher values occur at 42007 each month. 

Haze Episode 

A modified version of the ASOS Obstructions to Vision Algorithm is applied to our PAL data 

record such that when the visibility drops below 7 miles, the dew-point depression (DPD) is 

checked to distinguish between fog (DPD ≤ 2.2 °C) and haze (DPD > 2.2 °C). An eight-hour 

period of haze is identified at PAL from 18 Z 23 May to 01 Z 24 May 2004. The southeastern 

U.S. is under the influence of a high pressure ridge, and winds over south Louisiana are light to 

moderate from the south-southeast. NOAA satellite imagery depicts scattered fair clouds, and 

restricted visibility is indicated over the Delta area. CSI-6 also reports reduced visibility, but the 

DPD is lower there. Stability at buoys 42007 and 42040 is neutral, and computed mixed heights 

rise from about 600 m to peak around 800 m. This is in reasonable agreement with the estimated 

afternoon mixed height of 866 m derived from the 12 Z 23 May Slidell rawinsonde. The 

Louisiana Department of Environmental Quality has several PM stations operating in the New 

Orleans area, but data is not yet available for this period. 

Wind Observations 

According to Huang (2004), the Louisiana coastal and OCS region may provide a suitable 

environment for the harvest of wind energy. Large wind turbines (about 80 m hub height) could 

be deployed on existing platforms to take advantage of the support and maintenance facilities 

already in place. Measurements of winds at this altitude over the Gulf are necessary to estimate 

the performance and design of the wind energy system. As a first look, we employ data recorded 

by the Vaisala Profiler installed at LUMCON, Cocodrie, Louisiana in early October 2004. The 

distribution of the 158 m level winds during the period of 15 October through 16 November 

2004 is shown in Figure 2E.12. Winds are most often from the southeast, with a secondary 

maximum from the southwest. The average speed is 6.3 m/s, with many hours exceeding 10 m/s. 
338 

Figure 2E.12. 158 m level wind rose for the period of 15 October through 16 November 2004 as recorded by 

the LUMCON profiler. 

References 

Hsu, S.A. 1998. A relationship between the Bowen ratio and sea-air temperature difference 

under unstable conditions at sea. Journal of Physical Oceanography 28:2222–2226. 

Hsu, S.A. 1999. On the estimation of overwater Bowen ratio and sea-air temperature difference 

under unstable conditions at sea. Journal of Physical Oceanography 29:1372–1373. 

Hsu, S.A. 2004. A parameterization of overwater mixing height in unstable conditions. 

Submitted to Environmental Fluid Mechanics. 

Hsu, S.A. and B.W. Blanchard. 2004. On the estimation of overwater buoyancy length from 

routine measurements. Environmental Fluid Mechanics. 
339 

 

Huang, C.H. 2004. Some air quality and meteorological issues confronting the Minerals 

Management Service. In: Proceedings of the Seventh International Marine Environmental 

Modeling Seminar, Washington D.C., pp. 36–45. 

Panofsky, H.A. and J.A. Dutton. 1984. Atmospheric Turbulence. New York: Wiley. 

S. A. Hsu received his Ph.D. in meteorology from the University of Texas at Austin. He has been 

a Professor at Louisiana State University since 1969. His research interests are coastal and 

marine meteorology, air-sea interaction, and pollution transport physics. Dr. Hsu has published 

extensively, including a textbook entitled Coastal Meteorology. 

Brian Blanchard was awarded his B.S. degree in atmospheric sciences from Northeast Louisiana 

University in 1983. He has been a Research Associate at Louisiana State University for over 20 

years, and has contributed to many meteorological studies. He is the co-author of several journal 

articles and technical reports. 
340 

THE CURRENT STATUS OF THE SO2 AND NO2 INCREMENT ANALYSIS FOR THE 

BRETON NATIONAL WILDERNESS AREA 

Neil Wheeler, Sonoma Technology, Inc. 

David Stauffer, Pennsylvania State University 

Project Background 

The Breton National Wilderness Area (BNWA) is surrounded by onshore sources of oxides of 

sulfur (SOx) and oxides of nitrogen (NOx) to the north and west and offshore sources to the south 

and east. The Clean Air Act Amendments limit how sulfur dioxide (SO2) and nitrogen dioxide 

(NO2) concentrations may increase over areas such as the BNWA. These limits are referred to as 

increments. The Minerals Management Service (MMS) has funded several studies to provide the 

emissions and meteorological databases needed to support a modeling-based cumulative 

increment analysis for the BNWA. The most recent study involves collecting meteorological and 

air quality data from October 2000 through September 2001 (year 2000–2001), and provides the 

final data needed to perform the increment analysis. The databases from these prior studies will 

be used to perform air quality modeling for past and present years. The model results will be 

used to evaluate the contribution of Outer Continental Shelf (OCS) emission sources to SO2 and 

NO2 levels over the BNWA and determine the amount of increment consumed. 

Technical Approach and Current Status 

Episode Selection 

Episode selection was based on an analysis of air quality (Miller et al. 2003) and the synoptic 

weather types used by the Louisiana Office of State Climatology (2003). Five of the episodes 

selected had high SO2 or NO2 concentrations and a distribution of weather types similar to the 

annual distribution. One episode had low concentrations and was selected to test the models’ 

ability to predict non-episodic conditions. The following periods were selected for episodic 

modeling: 8–13 November 2000; 1–6 December 2000; 30 December 2000 through 4 January 

2001; 2–8 March 2001; 9–14 July 2001; and 8–13 August 2001 (low concentration period).

Meteorological Modeling 

Meteorological modeling is being performed with the Penn State/NCAR Mesoscale Model, 

MM5 (Dudhia 1993; Grell et al. 1994). The modeling strategy includes the use of Kain-Fritsch 2 

convective parameterization; the Gayno-Seaman planetary boundary layer scheme; an explicit 

moisture scheme; the column cloud radiation scheme; satellite-derived sea surface temperatures 

for lower boundary conditions; and a multi-scale four-dimensional data assimilation technique 

developed by Stauffer and Seaman (1994) involving analysis nudging, surface analysis nudging, 

and observational nudging with routine and special observational data. Modeling of the 36-km 

and 12-km domains has been completed for the episodes and the annual simulation is in 

progress. Two of the episodic periods will be modeled with a 4-km nest to investigate the 

importance of horizontal grid spacing on model performance. Annual modeling will be 

performed only on the 36- and 12-km domains for 1 October 2000 through 30 September 2001. 
341 

Emission Inventory Preparation 

Three emission inventories are being prepared: The current year (2000–2001) inventory, the SO2

baseline year (1977) inventory, and the NO2 baseline year (1988) inventory. The Breton 

Offshore Activity Data System (BOADS [Billings and Wilson 2004]), the Gulfwide Offshore 

Activity Data System (GOADS [Wilson et al. 2004]), and the National Emission Inventory 

(NEI) are being used. STI has consolidated the databases and performed checks for 

completeness, duplication, and reasonableness. Emissions have been speciated, non-point 

sources have been spatially allocated, and model-ready emissions files have prepared for the 

2000–2001 year. 

Episodic Air Quality Simulations 

The purpose of the episodic simulations is to assess air quality model performance and select the 

final model to be used in the cumulative increment analysis. Episodes are currently being 

modeled using both an Eulerian photochemical model, CMAQ (U.S. Environmental Protection 

Agency, 1999) and a Lagrangian puff model, CALPUFF (Scire et al. 1998), with the 

meteorological fields prepared using MM5. A model performance evaluation is being undertaken 

for each episode and model combination. Sensitivity simulations will be an integral part of the 

model performance evaluation. The model inputs will be modified based on estimates of 

uncertainty and air quality model simulations will be performed. 

Annual Air Quality Simulations 

These simulations will be used to establish baseline and current year concentrations of SO2 and 

NO2 for use in the increment analysis. Annual simulations of NO2 and SO2 with year 2000–2001 

emissions will be performed. The results of these simulations will be evaluated for model 

performance both statistically and graphically using the same methods as used for evaluating the 

episode-type simulations. Annual simulations of SO2 with year 1977 OCS-related emissions and 

of NO2 with year 1988 emissions will be performed to establish the baseline concentrations. 

Onshore and non-OCS related offshore emissions will be estimated for 1977 and 1988 using 

emission inventory trends data. 

Air Quality Assessment 

An air quality assessment will be performed to determine the amount of increment that has been 

consumed in the BNWA. Receptors in the BNWA will be identified and the annual average NO2

concentrations at each receptor in the BNWA will be calculated from the 2000–2001 year and 

the 1988 baseline year simulations. Annual, daily, and three-hour average SO2 concentrations at 

each receptor in the BNWA will be calculated from the current (2000–2001) year and the 1977 

baseline year simulations. 

References 

Billings, R.S. and D.L. Wilson. 2004. Data Quality Control and Emissions Inventories of OCS 

Oil and Gas Production Activities in the Breton Area of the Gulf of Mexico: Final 

Report. U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region, New Orleans, LA. OCS Study MMS 2004-071. 94 pp. 
342 

Dudhia J. 1993. A nonhydrostatic version of the Penn State-NCAR mesoscale model: Validation 

tests and simulation of an Atlantic cyclone and cold front. Monthly Weather Review 

121:1493–1513. 

Grell G.A., J. Dudhia, and D.R. Stauffer. 1994. A description of the fifth-generation Penn 

State/NCAR Mesoscale Model (MM5). NCAR Technical Note-398. National Center for 

Atmospheric Research, Boulder, CO. 

Louisiana Office of State Climatology. 2003. Monthly Newsletter. 

http://www.losc.lsu.edu/newsmonthly.html. 

Miller D.S., P.T. Roberts, and C.P. MacDonald. 2003. Breton Aerometric Monitoring Program 

Data Analysis. Executive summary prepared for Offshore Operators Committee and 

Minerals Management Service, Dept. of the Interior, New Orleans, LA, by Sonoma 

Technology, Inc., Petaluma, CA, STI-999479-2267-ES2, August. 

Scire, J.S., D.G. Strimaitis, and R.J. Yamartino. 1998. A User’s Guide for the CALPUFF 

Dispersion Model (Version 5.0). Concord, MA: Earth Tech, Inc. 

 

Stauffer D.R. and N.L. Seaman. 1994. On multi-scale four-dimensional data assimilation. 

Journal of Applied Meteorology 33:416–434. 

U.S. Environmental Protection Agency. 1999. Science Algorithms of the EPA Models-3 

Community Multiscale Air Quality (CMAQ) Modeling System. Byun, D.W. and J.K.S. 

Ching, eds. EPA/600/R-99/030, USEPA, ORD, Washington, DC 20460. 

Wilson, D.L., J.N. Fanjoy, and R.S. Billings. 2004. Gulfwide Emission Inventory Study for the 

Regional Haze and Ozone Modeling Effort: Final Report. U.S. Dept. of the Interior, 

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

Study MMS 2004-072. 273 pp. 

Mr. Neil J. M. Wheeler is Vice President for Atmospheric Modeling and Information Systems at 

Sonoma Technology, Inc. (STI). He has more than 30 years of practical experience in the 

atmospheric sciences and 22 years experience with the development, application, and evaluation 

of meteorological and air quality models for regulatory purposes. Before joining STI, Mr. 

Wheeler was Chief of Environmental Applications at the North Carolina Supercomputing Center 

and Manager of Control Strategy Modeling at the California Air Resources Board. He is a 

Certified Consulting Meteorologist. 

Dr. David R. Stauffer is a Senior Research Associate and Associate Professor of Meteorology in 

the Department of Meteorology at the Pennsylvania State University where he directs graduatelevel research and teaches undergraduate and graduate-level courses. Professor Stauffer has over 

23 years of related experience in meteorology, software development and management, 
343 

mesoscale numerical modeling and data assimilation in support of hydrodynamics, transport and 

dispersion. Dr. Stauffer is a principal developer of the Penn State University/National Center for 

Atmospheric Research MM5 Modeling System, which has become the most widely used 

mesoscale modeling system in the world. Dr. Stauffer is widely recognized for his expertise in 

mesoscale numerical weather prediction and data assimilation and is the author of more than 100 

scientific papers. 
344 

SATELLITE DATA ASSIMILATION INTO METEOROLOGICAL/AIR 

QUALITY MODELS 

Richard T. McNider, University of Alabama in Huntsville 

Arastoo P. Biazar, University of Alabama in Huntsville 

Introduction 

Surface moisture availability and surface heat capacity are critical to accurate temperature and 

boundary layer prediction overland. Regional-scale air quality models require specification of 

these variables on grids down to scales near four kilometers. Unfortunately, there are not routine 

observations of these variables available on these scales. Even current state-of-the-art 

meteorological models have difficulty in predicting correctly the space, time and optical depth 

clouds. Yet, clouds in places such as the Gulf Coast have a critical role in the development of 

surface temperatures and photolysis rates due to cloud shading. In the coastal environment under 

weak synoptic forcing, proper simulation of temperature is especially critical since the thermal 

contrast between land and ocean controls the strength and timing of sea and land breezes. At 

higher latitudes and near cold ocean currents such as New England or California, the cold sea 

surface temperatures dominate the thermal contrast. In places like the Gulf Coast, relatively 

warm water, high sun angles, and large variation in surface thermal characteristics make the 

simulation of the land temperature important in the thermal contrast. Use of GOES satellite 

imagery and sounding information have the potential to specify more accurately these critical 

parameters—moisture, heat capacity and cloud radiative characteristics in regional models than 

other present techniques. These are discussed below. 

Moisture Availability 

Moisture availability in current models is generally specified using land use characteristics and 

land surface parameterization schemes. In the southeast, however, moisture due to plant 

transpiration can dominate moisture availability, and specifying root zone moisture and 

transpiration characteristics a priori is difficult. In the satellite assimilation technique, the 

morning rate of change of satellite-observed surface skin temperature is used as a constraint to 

adjust moisture availability (McNider et al. 1994). Basically, if the satellite shows a rate of 

change that is larger (smaller) than the model grid rate of change then surface moisture is 

adjusted downwards (upwards) through an analytical inversion of surface similarity relations. 

Surface Heat Capacity 

Specifying heat capacity for single soil types and soil moisture is relatively easy. However, 

model grid boxes are made up of a variety of materials from vegetation to bare soil to manmade 

structures. Heat capacity is a critical parameter in temperature prediction, especially at night. 

Using evening skin tendencies observed by GOES as a constraint, improved specification of 

model grid surface heat capacity can be made. 
345 

Solar Insolation and Photolysis Rates 

As mentioned above, models have great difficulty predicting clouds. Since models in air quality 

studies such as those being addressed are used in a retrospective mode, observed cloud cover by 

satellites can be used. The recovery of solar insolation can be accomplished very directly from 

measures of GOES broadband reflectivity (Gautier et al. 1980). Additionally, the retrieval of 

cloud transmittance from this process can be used along with satellite observed cloud top 

pressures to provide the necessary cloud characteristics needed in photolysis calculations 

(McNider et al. 1998). 

Specification of Land/Water Boundaries 

An issue that creates difficulty when modeling coastal areas like Louisiana, previously identified 

in MMS modeling studies, is the correct determination of the land/sea boundary. MM5 Model 

water specification (all or none) can cause difficulty along complex coastlines. Additionally, 

geometric definition for complex coastlines in marshy or tidal areas can be problematic for land 

use models. The satellite assimilation methodology for recovering moisture availability and heat 

capacity makes the coast line determination in a natural way. 

Application to East Texas Sea Breezes 

The East Texas Gulf Coast has been the focus of air quality studies over the past two decades 

because of the ozone attainment problem in the Houston/Galveston area. These are relevant 

because of the large petrochemical and refining facilities in part supported by the large offshore 

production along the Texas and Louisiana coasts. As part of a current MMS study currently 

underway, the role of satellite data in improving the strength, time, and characteristics of the East 

Texas sea breezes is under way. The following reports on a preliminary evaluation of the impact 

of satellite assimilation on sea breezes in the Houston/Galveston area. 

Model Configuration 

The MM5 model was run for the Texas Gulf Coast. Four grid nests were used, ranging from a 

96km continental scale to a 4 km nest over the Houston/Galveston area. The 4 km grid results, 

which more effectively capture the coastal configuration, are emphasized here. The model 

options were chosen based on the guidance of the Texas modeling group. The cases to be 

presented employed an analysis nudging procedure. Three model cases will be presented. The 

first is the “Control Case” and does not employ satellite assimilation. Land-use characteristics 

from the default MM5 data sets for moisture availability, and heat capacity were employed for 

this case. Second, a “Moisture Availability Case” is presented that included satellite insolation 

assimilation and moisture availability assimilation. A third case that employed satellite insolation 

assimilation, moisture availability and heat capacity assimilation was also carried out. 

Model Performance 

As part of previous analyses of model performance of the satellite assimilation, model 2-m 

temperatures were compared against National Weather Service observations. The satellite 

retrieval of moisture availability improved day-time temperatures by increasing them over those 

of the control case. This occurred as the model dried the surface. The heat capacity simulation 

improved the day and night-time performance of the model. 
346 

Sea Breeze Impacts 

The drying out of the surface produces a much higher temperature over land and corresponding 

larger gradient between the land and sea. As might be expected, the strength of the sea breeze is 

much stronger. Interestingly, in the moisture assimilation case, the area ahead of the developing 

sea breeze has lighter winds than the control case. In cooperation with MMS additional detailed 

analyses of these cases will be carried out. 

Acknowledgments 

This work was sponsored in part by a Cooperative Agreement between the Minerals 

Management Service and the University of Alabama in Huntsville. 

References 

Gautier, C., G.R. Diak, and S. Mass, 1980: A simple physical model for estimating incident solar 

radiation at the surface from GOES satellite data. Journal of Applied Meteorology 

19:1005–1012. 

McNider, R.T., A.J. Song, D.M. Casey, P.J. Wetzel, W.L. Crosson, and R.M. Rabin. 1994. 

Toward a dynamic-thermodynamic assimilation of satellite surface temperature in 

numerical atmospheric models. Monthly Weather Review 122:2784–2803. 

McNider, R.T., W.B. Norris, D. Casey, J.E. Pleim, S. Rosell, and W. Lapenta, 1998. 

Assimilation of satellite data in regional scale models. Air Pollution Modeling and Its 

Application. New York: Plenum Press. Pp. 25–35. 

Richard T. McNider began his professional career with the Alabama Air Pollution Control 

Commission in 1973. He obtained his Ph.D. from the University of Virginia in 1981. He has 

been a Professor of Atmospheric Science and Mathematics at the University of Alabama in 

Huntsville for 25 years, where he helped found the Atmospheric Science Department. His 

interest is in developing mathematical models of geophysical phenomena. He is currently 

Distinguished Professor Emeritus at UAH. He is also a Fellow of the American Meteorological 

Society. 

Arastoo Biazar is a Senior Research Associate in the Earth System Science Center at the 

University of Alabama in Huntsville. He received his Ph.D. in atmospheric sciences from the 

University of Alabama in Huntsville. Mr. Biazar’s interest is in addressing air pollution and 

atmospheric chemistry issues. This includes both addressing physical/chemical problems as well 

as building/improving the numerical models of the atmosphere. He has worked with a wide 

range of air quality models from simple regulatory models to research grade three-dimensional 

models on scales from local to global. He has developed a chemical transport model and has 

been involved in the development of the EPA’s Models3/CMAQ and CRCSHM’s global 

chemical transport model. 
347 

COASTAL ATMOSPHERIC DATA GATHERING ENHANCEMENTS 

Gary S. Zeigler, Vaisala Inc. 

This paper provides a status report on initiatives to redeploy two LAP®-3000 radar profilers 

owned by the Minerals Management Service (MMS) Gulf of Mexico (GOM) Region to sites 

along the GOM coastline to enhance available meteorological measurements for use in air 

quality assessments. 

Background 

Air pollution studies using air quality models have established the crucial need for 

meteorological data in determining the contribution of pollution impacts from various sources. 

Meteorological data from the GOM coastal zone are necessary in assessing what contribution, if 

any, Outer Continental Shelf sources make to existing or projected future visibility impairment to 

the Breton National Wildlife Area and the other three Class I areas in the GOM Region. 

History of Use of Radar Profilers by MMS 

Upper-air meteorological measurements using radar profilers have been collected by the MMS 

GOM Region as part of two previous air quality studies initiated in 1993 and 1997. During the 

summer ozone season in 1993, data were collected for a six-month period from six leased LAP®-

3000 profilers sited at four coastal land sites in Texas and Louisiana, and on two off-shore 

platforms. For the study that began in 1997, MMS purchased two used LAP®-3000 profilers and 

deployed them to two off-shore platform sites. Surface and upper-air data were subsequently 

collected for a 40-month measurement period at the two platform sites, starting in June 1998 and 

concluding in October 2001. During this collection period, data were retrieved hourly through 

the GOES satellite communications network. At the end of the measurement period in October 

2001, MMS had the two LAP®-3000 profilers placed in storage at the contractor’s facility, 

pending planned redeployment by MMS for further use in enhancing meteorological data 

availability in the GOM coastal zone. 

Upper-Air Meteorological Measurement Capabilities of LAP® -3000 Profilers 

The LAP®-3000 radar profiler is a vertically-pointing, pulsed Doppler radar that operates in clear 

air, reporting meteorological data up to approximately 3 kilometers above ground level. It 

includes an indoor suite of electronics that controls the radar hardware and processes the data 

measurements, as well as an outdoor antenna that remotely senses the atmosphere. The 

technology for the radar profiler was developed by the U.S. National Oceanic and Atmospheric 

Administration (NOAA). The manufacturer of the profiler is Vaisala Inc. The LAP®-3000 gives 

information for successive strata of the atmospheric boundary layer, producing measurements of 

wind and virtual temperature in vertical profile above the system’s transmitting and receiving 

antenna. Pulsed radio frequency (RF) signals are transmitted at an operating frequency of 915 

MHz. A portion of the transmitted energy is reflected back to the antenna from small-scale 

turbulence in the atmosphere which moves with the speed and direction of the wind. These 

returned signals are time/height gated and are individually analyzed for Doppler frequency shifts 
348 

that yield horizontal wind direction and speed measurements. Wind data are typically available 

from about 150 meters above the antenna, in approximately 60-meter to 200-meter intervals, up 

to a height of about 3 kilometers above the antenna. The LAP®-3000 also provides virtual 

temperature measurements from about 150 meters above the antenna, in approximately 60-meter 

height intervals, up to about 500 to 1,000 meters above the antenna. Virtual temperature profile 

measurements are achieved by directing an audio signal vertically and tracking it with the 

vertical RF beam of the radar. Using the Doppler shift information for each height increment 

from this acoustic wave tracking, the profiler is able to calculate the speed of sound in the 

atmosphere as a function of height, and then to convert that information into atmospheric virtual 

temperature measurements as a function of height. The maximum sensing height for virtual 

temperature measurements is much less than for wind measurements because virtual temperature 

measurements rely on sound propagation, which is much more height limited due to atmospheric 

attenuation than is RF energy propagation. Virtual temperature measurements are also heightlimited by strong wind conditions, which can rapidly transport the acoustic wave out of the 

vertical view of the RF antenna. Wind measurements by the LAP®-3000 profiler are normally 

available up to about 3km unless atmospheric conditions below that altitude limit the availability 

of turbulent eddies to act as RF reflectors. 

Initiatives in Progress to Redeploy MMS Radar Profilers to Gulf Coast Sites 

In 2002, the MMS, assisted by Vaisala Inc., began efforts to locate suitable sites for 

redeployment of the two MMS-owned profilers to GOM coastal sites. Following a series of site 

surveys, MMS decided to re-establish one of the profiler sites used in the 1993 MMS study, near 

Cocodrie, Louisiana at the Louisiana Universities Maritime Consortium (LUMCON) facility. For 

the other profiler, MMS worked in coordination with VISTAS (Visibility Improvement – State 

and Tribal Association of the Southeast) in deciding to establish a new data collection site on 

Naval Air Station (NAS) Pensacola, Florida. 

LUMCON Site Implementation 

In early 2004, MMS contracted with LUMCON for necessary site preparation work at their 

Cocodrie facility, and with Vaisala Inc. for installation, operation and maintenance of the profiler 

at that site for a planned three-year data measurement period. Vaisala completed the profiler 

installation and system readiness checks on 8 October 2004, and the LUMCON profiler site 

became operational as of that date. 

Site Configuration 

The LUMCON radar profiler site is shown in Figure 2E.13, looking toward the west. The large 

white fiberglass structure on the cement pad is the vertically-pointing RF antenna, and the white 

cylinders surrounding it are the audio generators for virtual temperature sensing. The small, 

elevated building in the background is the shelter for the profiler electronics. An underground 

cable connects the antenna to the electronics in the equipment shelter. Not shown in Figure 

2E.13 is the LUMCON 10-meter meteorological tower about 125 ft to the north and the main 

LUMCON building about 600 ft to the east. A radio link connects the 10-meter tower to the 

communications center in the LUMCON building, and a wireless LAN connects the profiler 

computer to the LUMCON communications center. 
349 

Figure 2E.13. LUMCON radar profiler site. 

Data Generation and Distribution 

Measured wind and virtual temperature profiles are generated hourly at the LUMCON site and 

are appended to daily files on the profiler’s computer within a few minutes past each clock hour. 

Each daily file is named “DYYJJJ.CNS, where D is the data type (i.e., W for wind and T for 

virtual temperature), YY is the last two digits of the year (e.g., “04” for 2004), JJJ is the Julian 

date, and CNS (i.e., short for “Consensus”) is the file extension. At midnight, the daily W file 

and daily T file are closed and a new one of each type is opened for the succeeding day. 

Throughout each day, the current W file and T file that are being appended to each hour, as well 

as all W and T files from preceding days, are available through the LUMCON web site, at 

http://weather.lumcon.edu. Surface weather data are accessed on the LUMCON web site by 

clicking on the word “LUMCON” either on or below the map. Profiler data are available by 

clicking on “New Doppler Wind Profiler” below the map. On the “Wind Profiler at LUMCON” 

page, clicking on the applicable bullet items in the “Data” section provides access to the currentday and past-days profiler data, as well an explanation of the data format of both wind and 

virtual temperature files. Clicking on the “Graphical View” bullet in the “Data” section, brings 

up a time-height plot of current LUMCON profiler wind data by linking to the NOAA Profiler 

Network (NPN) web site. While both the alpha-numeric and graphical data files from the 

LUMCON profiler can be printed or downloaded when accessed through the LUMCON web site 

as described above, it is important to note that the hourly file time convention is different for 

these two data formats. The alpha-numeric files use the EPA convention of showing the start

time of each hourly data report, and are in Central Standard Time (CST) year around. The 

graphical displays use the NOAA convention of showing the end time of each hourly data report, 

and are in Universal Time (UTC) year around. An example of LUMCON wind profile data 

displayed graphically on the NPN web site is shown in Figure 2E.14. Any missing data hours are 
350 

because the LUMCON profiler data at those times were not available to the NPN web site either 

because of equipment or communications problems. 

Figure 2E.14. Example graphical NPN wind display from LUMCON profiler. 

NAS Pensacola Site Implementation 

Under MMS sponsorship and direction, Vaisala performed an initial site survey at NAS 

Pensacola, Florida in June 2002, and subsequently worked with VISTAS representatives to firm 

up planning for installing an MMS profiler at that location. Unfortunately, a number of delays 

were encountered in this process, including a time-consuming frequency compatibility study by 

the U.S. Navy and a number of schedule disruptions caused by hurricane hits or near misses in 

the NAS Pensacola area. As a result, the planned installation of the MMS profiler at NAS 

Pensacola necessarily slipped until early 2005. Site preparation work is being handled by 

VISTAS through its Florida DEP representative, who is arranging for an equipment shelter and 

for power and telephone service to be installed at the planned NAS Pensacola site. Under 

contract to VISTAS and Southern Company Services, Inc., Vaisala will install the MMS profiler 

system at the site and operate and maintain it for a planned three-year measurement period. A 

local site operator will be provided by Florida DEP to assist Vaisala in performing maintenance 

activities. 

Planned Site Configuration. Figure 2E.15 shows the planned layout of the profiler site on NAS 

Pensacola, near the existing 10-meter meteorological tower adjacent to the runways. 
351 

Figure 2E.15. Planned NAS Pensacola profiler site configuration. 

Planned Data Generation and Distribution. Hourly wind and virtual temperature measurements 

will be generated by the NAS Pensacola profiler. These data will be retrieved through the GOES 

satellite data communications system and will be posted on the NOAA Profiler Network web 

site. 

Summary 

MMS is in the process of redeploying its two LAP®-3000 radar profilers to GOM coastal sites. 

One of the MMS profilers became operational at the LUMCON facility near Cocodrie, Louisiana 

in early October 2004 and hourly measurements from that site are now routinely available on the 

LUMCON web site. The second MMS profiler is planned to become operational at NAS 

Pensacola, Florida in early 2005, under a cooperative effort between MMS and VISTAS. When 

implemented, the NAS Pensacola site will generate hourly measurements to be made available 

on the NOAA Profiler Network web site. Upper-air wind and virtual temperature profile data 

planned for the next three years from these two new radar profiler sites are expected to significantly enhance available meteorological measurements for air quality assessments in the GOM 

coastal zone. 
352 

Mr. Gary Zeigler is the Operations Manager of the Wind Profiler Business Unit at Vaisala, Inc., 

Boulder, Colorado. He is a career meteorologist with extensive experience in meteorological 

remote sensing. Mr. Zeigler has provided contractor project management support to MMS field 

studies employing wind profilers since 1993. He is currently the contractor project manager for 

two new field measurement programs employing MMS radar wind profilers. 
353 

 ENHANCEMENTS TO THE CALPUFF MODELING 

SYSTEM FOR OCS APPLICATIONS 

Joseph Scire, David Strimaitis and Francoise Robe, Earth Tech, Inc. 

Outline

• Improvements in datasets for OCS applications

– Enhanced interface (MM5) and new interfaces (RUC, Eta, RAMS) 

• 3d and 2d datasets

– High resolution SST data

– Standard one-year MM5 meteorological dataset 

• Ease-of-use enhancements

– Graphical user interfaces

– Graphics – vectors, isopleths, animations

• Technical enhancements to CALPUFF modeling system

– COARE algorithms 

– Improve mixing height algorithm over water including buoyancy effects

– Option for AERMOD-like turbulence profiles

– Subgrid-scale coastline treatment and TIBL growth

– Non-Boussinesq numerical plume rise for all sources

– Platform adjustments to building downwash algorithms

Background

• CALPUFF is a Lagrangian, non-steady-state puff dispersion model

• Achieved status as a U.S. EPA Guideline Model (Federal Register, 

15 April 2003)

• Recommended by IWAQM (1998) for long-range transport 

applications

• Recommended by FLAG (2000) for Class I impact assessments 

and air quality related value impact evaluation
354 

CALPUFF Modeling System

Postprocessing

Dispersion modeling

Meteorological modeling

Meteorological & 

geophysical data 

preprocessors

MM5/ETA/RUC2/RAMS

meteorological 

models

CALPOST

postprocessor

CALPUFF

dispersion model

Utility programs

APPEND, CALSUM

KSP

Particle model

PRTMET

postprocessor

CALGRID

photochemical

model

CALMET

meteorological

model

POSTUTIL

postprocessor

CALMET Model

• CALMET boundary layer modules

– Computes mixing heights, surfaces fluxes, stability and 

turbulence fields

– Overland PBL model uses an energy balance approach

– Overwater PBL model uses a profile method

• CALMET 3-D diagnostic wind field module

– Uses observations and/or gridded prognostic meteorological 

fields

– Wind fields adjusted for fine-scale terrain effects and massconsistency

• Slope flows, kinematic effects, terrain blocking effects

• Divergence minimization 

• Objective analysis procedure to assimilate observational data
355 

CALPUFF Model

• CALPUFF non-steady-state Lagrangian puff model

– Uses 3-D wind and turbulence fields for transport and dispersion

– Near-source effects such as building downwash, transitional 

plume rise, partial plume penetration

– Subgrid-scale terrain and coastal interaction module

– Longer range effects such as chemical transformation, overwater 

transport and dispersion, wet and dry deposition

– Special non-Boussinesq plume rise model designed for very hot 

plumes such as from flares

Improvements in Datasets

• High resolution satellite data in defining SST 

• Prognostic model to define conditions, especially in data 

sparse offshore areas

• Gridded air-water temperature structure (gridded

SEA.DAT file)

• Introduction of “no-observations” mode in CALMET 

– Closer coupling of CALMET with prognostic meteorological models

• New interfaces to additional prognostic models such as 

RUC, Eta, RAMS in addition to MM5
356 

Hybrid Approach to Meteorological Models

• Mesoscale prognostic model output on larger scale

• Includes synoptic and mesoscale features

• ~1 km – 20 km grid spacing

• Provides information on conditions offshore

• Diagnostic model on fine grid (CALMET)

• Includes mesoscale model output + optional observations

• Fine grid spacing (0.25 km-3 km)

• Terrain effects on fine scale

• Provides high-resolution PBL parameters for dispersion model

• Reasonable run time

Standard Meteorological Dataset

• Standard dataset for regulatory applications

– Consistency of meteorological fields across applications

– Substantial savings of effort

– Evaluated dataset with known performance

• MM5 dataset being developed under separate MMS contract for the 

GOM area

– One year period (1 October 2000–30 September 2001)

– Three nests: 36km, 12km and 4km grid spacings

– High-resolution SST data

• Additional years with MM5 or output from other models

– New programs developed to interface CALMET to RUC, Eta

and RAMS
357 
358 

Summary of Eta/RUC Operational Runs

Model

Horizontal

Resolution

(km)

Vertical

Resolution

Run

Frequency

Output Interval

Forecast 

Analysis Forecast Length

ETA 12 60 Levels 4 per day 6-hours 3-

hours

84 Hours

ETA 8 60 Levels 4 per day 6-hours 3-

hours

48 Hours

RUC 20 50 Levels 24 per 

day

1-hour 1–3 

hours

12-Hours

Satellite SST Datasets

• Final Analysis Data (FNL) 

– 1 deg x 1 deg data

– Available 4 times daily

– Data assimilation

• Real-time, global SST Analysis (RTG)

– 0.5 deg x 0.5 deg

– Available daily

– Analysis of satellite measurements, surface obs and 

interpolation

• Moderate Resolution Imaging Spectroradiometer

(MODIS)

– 4km data

– Daily and weekly

– Satellite measurements
359 

Development of MODIS SST Dataset

• Any given satellite pass has potentially large amounts of 

missing data due to clouds

• Procedure being tests:

– Base: Satellite data for Day: n

– Composite: Fill missing cells iteratively with data for day n+1,

n-1, n+2, n-2, n+3, n-3

– Composite + weekly: Fill missing cells with data from weekly 

MODIS dataset

– Composite + weekly + RTG: Fill any remaining missing data with 

daily RTG data
360 
361 

Surface Layer Parameters

• OCD

– Bulk aerodynamic principles and surface layer formulas 

using measured T(10m), Ts, RH, u(10m)

• z0 = 2.0e-06 (u10)2.5

• CuN = (0.75+0.067 u10) 10-3 = (u*/u10)2

• L = 196.2 θv (CuN)1.5 u10

2 / (θv - θvs)

– MOST profiles estimate 10m values

– Iteration refines u*, L

Surface Layer Parameters

• CALMET

– OCD methods are used to obtain local surface parameters 

for each grid cell

– Meteorological data for each cell is assumed to be at 10m 

(first model layer top is 20m)

– SST and air-sea T obtained from buoys (or from remote 

sensing and model delta T calculation)
362 

Surface Layer Parameters

• COARE

– Refined bulk aerodynamic and surface layer 

formulas, with submodels for:

• sea surface skin temperature

• diurnal warm layer temperature structure

• wind-wave roughness adjustments

– Iterative solution retained to balance profile 

extrapolations with surface fluxes

– z0 = αu*

2 /g + 0.11ν / u*

– Charnock α ~ 0.011 increases with wind speed 

greater than 10 m/s

– Deep sea formulation, adjustments for shallow 

water
363 

Surface Layer Parameters

• COARE module added to CALMET

– Calculated roughness length z0 with COARE is significantly 

smaller than OCD/CALMET, especially for wind speeds > 3 m/s

• Behavior at low wind speeds may need adjustment

– Differences in u* and L result in differences in overwater 

turbulence characterization

• COARE reduces friction velocity by about 10%

• Monin-Obukhov length from COARE about 25% higher 

(convective conditions) and about the same for stable conditions

– Wave information from buoys and remote sensing can be 

incorporated when data are available

Current Overwater Mixing Height

• Overwater mixing height

– either specified by the user (SEA.DAT)

– or computed internally: (Blackadar and Tennekes 1968)

where

CW is a constant (~0.16)

f is the Coriolis parameter (~10-4 s-1)

h C u

f w ater

W = ⋅ ∗
364 

Problems with Overwater Mixing Heights

• MMS Boundary Layer Study (STI) suggests 

underprediction of mixing heights by CALMET during 

light wind speed conditions (100-200m vs 600m 

observed)

• Lack of consideration of buoyancy effects over water

• Testing new method for computing overwater mixing 

heights that includes both mechanical and convective 

mixing processes

Mixing Height

• Maximum of mechanical or convective mixing heights

• Convective mixing height

• Modified Carson method (Maul 1980)

t dt

i

p

h

i t i t d d z t

c

Q E dt

z z + + Θ +

⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ Θ − + = + ( ) 2 (1 ) 2 ( ) ( ) ( )

1/2

1 1

2

1

ψ ρ ψ

( ) ( )/( ) [ ] /d EQ t c Θ Δ t dt h + = 2 1 p

1 2

ψ ρ
365 

Numerical Plume Rise

• Numerical solution to conservation and state equations 

in non-Boussinesq form (used for high temperature 

sources such as flares or fires)

• Initial properties at release

– temperature

– effective vertical velocity

– effective radius

• Explicitly accounts for vertical structure of atmosphere

– wind speed profile

– wind direction profile

– temperature (density) profile
366 

Numerical Plume Rise Conservation Equations

• Mass

• Momentum - along-wind

• Momentum – vertical

• Energy

d

ds

ur r u u r u sc a sc a a a ( ) cos sin ρ αρ φ βρ φ 2 = −+ 2 2

dz

du

u r u u r w

ds

d a ρ sc z ρ 2 2 ( ( − ))=−

d

d s u r w gr sc a ( )() ρ ρρ 2 2 = −

[ ] ( ) ( ) d

d s

ur T T d T

d z

g

c sc a wr R r T T a

p

ρ ρ p a 2 2 44 − =− +

⎛

⎝

⎜ ⎞

⎠

⎟ − −
367 

Downwash

• OCD

– Based on empirical fit to API wind tunnel data for a ‘large’

offshore oil platform (Petersen 1986)

• Platform A

• W = 55m; Hb (above water) = 48m

• X/Hb = 2.2, 12.6, 25.0, 37.5 

• Horizontal release (180o wind direction)

– Wind tunnel fit modified to remove ‘ambient’ turbulence, 

leaving downwash sigma (σd) component

– σd is added in quadrature to ambient sigma at all distances 

(σd at 12.6 Hb used for x > 12.6 Hb)

– Controlling parameters are platform width and total height; 

adjustment factor is applied for release height

– Downwash sigmas included in dilution radius for plume rise 

(as in BLP)
368 

Petersen Sigma-y Figure

Downwash

• CALPUFF - ISCST3 methods

– Buildings are treated as solid structures

– Controlling parameters are building width and height, 

provided for each 10o of flow direction; adjustment factor is 

applied for release height

– Downwash sigmas (σd) used up to 10 L, and σd(10 L) is 

converted to a virtual distance for x > 10 L (L is smaller of Hb

and W)

– Downwash sigmas used to define a dilution radius for plume 

rise (as in BLP)
369 

Downwash – PRIME Method

• Includes:

– Source-building separation effects

– Explicit streamline ascent/descent

– Velocity deficit due to presence of building

– Integrated cavity (near-wake) and far-wake modules

– Effects of downwash on plume rise and turbulence (spatiallyvarying)

– Partial capture of plume into cavity allowed

– Enhancement of sigma y and sigma z
370 

Downwash Model Performance

Platform Downwash

• Testing suggests that the CALPUFF equations are as 

effective as the algorithm in OCD in simulating the 

effect of platform downwash

• Existing CALPUFF modules retained for platforms 

with addition of a modified structure height and height 

above the water surface
371 

Plume Fumigation

TIBL

• OCD

– Piece-wise linear mixed layer height is prescribed along the 

direction from the source to a receptor with distance 

measured from the coast

– h = 0.1 x for x ≤ 2000m

– h = 200 + 0.03 (x-2000) for x ≥ 2000m)

– Designed to approximate a generic TIBL without inputs for 

wind speed, heat flux, marine layer lapse rate
372 

TIBL

• CALMET

– Two-step mixing height procedure

– (1) Gridded mixing height field computed using local gridcell properties

– (2) Advective averaging scheme controlled by user inputs 

smoothes transitions by averaging heights along flow

– Provides robust treatment of coastal-zone transitions, 

recognizing difference in along-shore / on-shore / off-shore 

situations

TIBL

• CALPUFF

– Sub-grid TIBL option refines the gridded mixing height 

structure in coastal zones using the TIBL model of Garrett 

(1992)

– Model is applied along the puff trajectory using local grid cell

properties. 

– For steady conditions,

c uh

H

dx

dh

p γρ

(1 + 2β ) =

x

c u

H h

p γρ

2(1+ 2β ) =
373 

TIBL

• CALPUFF (Coastal Zone Representation)

– Gridded land use includes wetlands and inland water bodies

– Properties tied to land use includes roughness length and Bowen 

Ratio

– Sensible heat flux (H) is proportional to Bowen Ratio

– Computed TIBL growth rate will respond to coastal zone 

properties:

c uh

H

dx

dh

p γρ

(1 + 2β )

=
374 

Computed Mixing Heights (m) 1300 LST

-40 -20 0 20 40

Easting (km)

-40

-20

0

20

40

Northing (km)
375 

Mixing Heights along X=-30km

0

200

400

600

800

1000

1200

1400

1600

-50 -40 -30 -20 -10 0 10 20 30 40 50

Northing (km)

Mix Ht (m)

x= -30km (1300 LST)

x= -30km (0400 LST)

Conclusions

• Improvements made in datasets for OCS applications

– Use of prognostic datasets important in data-sparse areas offshore

– Enhancements to allow better use of prognostic meteorological datasets 

– Addition of new interfaces to allow new options for data sources (MM5 + 

RUC, Eta, RAMS) 

– High resolution SST data developed based on MODIS 4km data

– Standard one-year MM5 meteorological dataset to be prepared for regulatory 

use

• Enhancements made to facilitate use of CALPUFF for regulatory 

applications

• Technical enhancements to CALPUFF modeling system

– COARE algorithms 

– Improve mixing height algorithm over water including buoyancy effects

– Option for AERMOD-like turbulence profiles

– Subgrid-scale coastline treatment and TIBL growth

– Non-Boussinesq numerical plume rise for all sources

– Platform adjustments to building downwash algorithms
376 

Joseph Scire is a Vice President and the manager of Earth Tech’s Atmospheric Studies Group. 

He has over 26 years’ experience in the design, development, and application of research and 

regulatory air quality models. He has played a major role in the development of several widelyused models including the CALPUFF modeling system, the CALGRID photochemical model, 

the Buoyant Line and Point Source (BLP) model, the MESOPUFF II mesoscale puff dispersion 

model, the building downwash algorithm in the Industrial Source Complex (ISC) model, a new 

building downwash model called PRIME, and the FOG cooling tower model. He has taught 

more than 45 training courses on the CALPUFF model for government agencies, private industry 

and universities in the United States and abroad. He has taught several modeling courses for the 

Air &Waste Management Association. Mr. Scire has served as an expert witness in projects 

involving CALPUFF modeling, building downwash and the deposition of toxic pollutants. 

David Strimaitis is a research meteorologist and senior air quality consultant with over 26 years 

of experience in developing and evaluating air quality models. He is one of the principal 

developers of the CALPUFF modeling system. Mr. Strimaitis served as manager of the EPRI 

Atmospheric Sciences Data Center contract for over ten years, during which time the Center 

moved from a mainframe computing environment to a web-based distribution environment. He 

developed a modified version of EPA’s ISCST model to include wet and dry deposition and the 

refined building downwash model PRIME. He implemented a dry deposition scheme for 

mercury compounds into the MESOPUFF II model. As a principal investigator in EPA’s 7-year 

Complex Terrain Model Development program, Mr. Strimaitis developed the modules central to 

the Complex Terrain Dispersion Model (CTDM). Mr. Strimaitis has applied many of the dense 

gas and air toxics models currently available for acute exposure analyses, and has evaluated their 

performance against existing data from field experiments. To facilitate these evaluations, he 

contributed to the design of a Modelers Data Archive of these datasets. He has also developed a 

number of model evaluation tools, including a SAS-based program that employs the jackknife 

resampling technique to assess the statistical significance of evaluation measures. 

Francoise Robe is an air quality modeling specialist with over 12 years’ experience in advanced 

meteorological and dispersion modeling. She is one of the authors of CALMET, the 

meteorological model of the US regulatory CALPUFF modeling suite. She has taught 18 

CALMET-CALPUFF training courses for the US-EPA, universities, consultants and industry 

around the world. She has also managed and conducted numerous air quality studies worldwide 

with the MM5, CALMET, and CALPUFF models. She is the author of over 30 technical reports 

and scientific articles, and has presented several papers at international scientific conferences. 

She has previously worked in the oil and gas industry and is familiar with upstream and 

downstream air quality issues. 
377 

SESSION 2F 

SPERM WHALE SEISMIC STUDY, PART II 

Chair: Deborah Epperson, Minerals Management Service 

Co-Chair: Carol Roden, Minerals Management Service 

MESOSCALE SPERM WHALE STUDIES IN THE GULF OF MEXICO I: RESPONSES TO 

SEISMIC LINE STARTS, ACOUSTIC LENGTH MEASUREMENTS, CODAS AND 

CULTURAL ORGANIZATION Jonathan Gordon, Ricardo Antunes, Nathalie Jaquet, Bernd 

Würsig, and Luke Rendell .......................................................................................................... 379 

SPERM WHALES IN THE NORTHERN GULF OF MEXICO: ABUNDANCE, HABITAT 

USE, AND ASPECTS OF SOCIAL ORGANIZATION Nathalie Jaquet,Bernd Würsig, and 

Jonathan Gordon ......................................................................................................................... 384 

GULF OF MEXICO SPERM WHALES – A GENETIC PERSPECTIVE Dan Engelhaupt.... 392 

THREE-DIMENSIONAL TRACKING OF SPERM WHALES USING PASSIVE 

ACOUSTICS Aaron Thode ....................................................................................................... 395 

PHYSICAL ENVIRONMENT OF THE NORTHERN GULF OF MEXICO DURING 

SUMMERS 2002–2004 Ann E. Jochens, Matthew K. Howard, Steven F. DiMarco, and 

Douglas C. Biggs ........................................................................................................................ 400 

ANALYSIS OF THE MESOPELAGIC COMMUNITY IN AREAS OF FEEDING AND 

NON-FEEDING BY SPERM WHALES IN THE NORTHERN GULF OF MEXICO 

John H. Wormuth........................................................................................................................ 403 
379 

MESOSCALE SPERM WHALE STUDIES IN THE GULF OF MEXICO I: 

RESPONSES TO SEISMIC LINE STARTS, ACOUSTIC LENGTH 

MEASUREMENTS, CODAS AND CULTURAL ORGANIZATION 

Jonathan Gordon and Ricardo Antunes, Ecologic, Newport on Tay, Fife and 

Sea Mammal Research Unit, University of St. Andrews, Scotland 

Nathalie Jaquet and Bernd Würsig, Texas A&M University–Galveston 

Luke Rendell, Sea Mammal Research Unit, University of St. Andrews, Scotland 

Introduction 

This is the first of two presentations about what has come to be called the “mesoscale” project. It 

gained this epithet because within it, information is often collected and analyzed at scale 

intermediate between the large scale satellite tagging and fine scale from the D-tag observations. 

However, it has often also involved the application of what must now be considered the 

“traditional” approach to sperm whale behavioral research involving methods such as 

observation, photo-identification, photogrammetry and passive acoustic monitoring from small 

research vessels. 

Fine Scale Movements in Response to Seismic Line Starts 

This work involved an analysis of data on whale headings and surface behavior collected by the 

visual team on the Gyre during 2002 S-tag and 2003 habitats cruises and a database of seismic 

survey activity collected and kindly made available for restricted use by IAGC. During SWSS 

cruises on the Gyre, a visual team maintained watch from the flying bridge on a rolling rotation 

with a minimum of three observers on effort at any one time. Two were usually searching using 

big-eye binoculars and the third supplemented search effort with hand-held binoculars and 

entered data on search effort and sightings into the “Logger” data collection program (IFAW). 

Once a group of whales had been acquired, the visual team’s main role was to track whale 

groups and guide researchers in rigid hull inflatable boats close to whales on the surface for 

tagging, photo-id or biopsy research. Data on the range, bearing, heading, group size and 

behavior of all groups were entered into Logger and used to create real time maps to assist with 

tracking. The seismic survey dataset consisted of the start and end time and location of most 

seismic lines shot in the northern Gulf of Mexico (NGOM) during 2002 and 2003. 

By integrating these two datasets we were able to observe whale tracks and headings on logger 

maps for periods before and after line starts and line ends. We also calculated the mean whale 

heading relative to the bearing to the seismic line (0o

, 180o away), surface time and surfacing 

rates for all whale sightings for the two hours before and the two hours after line starts and ends. 

These were compared statistically as a series of matched pairs using Wilcoxson’s signed rank 

non-parametric matched pairs technique for all encounters within 25, 50, and 100 miles of a 

seismic survey; results from these tests are summarized in Table 2F.1. Neither the inspection of 

the logger maps nor the statistical tests provided any suggestion of responses by whales to line 

starts or ends. 
380 

Table 2F.1. Results of seismic line starts and ends tests. 

Seismic Line 

Starts 

Before 

Mean 

(n) 

After 

Mean 

(n) 

Significance 

(2 tailed) 

Range to 

Seismic Vessel 

(N. Miles) 

Relative Heading 108 

(28) 

102 

(28) 

.524 <100 

Surface Time 

(secs) 

905 

(23) 

460 

(23) 

.125 <100 

Sighting Rate 

(Sighting hr-1) 

11.1 

(27) 

11.29 

(27) 

.962 <100 

Relative Heading 106 

(16) 

108 

(16) 

.717 <50 

Surface Time 

(secs) 

457 

(14) 

403 

(14) 

.470 <50 

Sighting Rate 

(Sighting hr-1) 

11.1 

(16) 

12.1 

(16) 

.756 <50 

Relative Heading 121 

(6) 

124 

(6) 

.463 <25 

Surface Time 

(secs) 

450 

(5) 

386 

(5) 

.138 <25 

Sighting Rate 

(Sighting hr-1) 

10.1 

(6) 

11.7 

(6) 

.917 <25 

Seismic Line 

Ends 

Before 

Mean 

(n) 

After 

Mean 

(n) 

Significance 

(2 tailed) 

Range to 

Seismic Vessel 

(N.Miles) 

Relative Heading 105 

(30) 

111 

(30) 

.309 <100 

Surface Time 

(secs) 

571 

(23) 

720 

(23) 

.753 <100 

Sighting Rate 

(Sighting hr-1) 

11.8 

(29) 

15.7 

(29) 

.214 <100 

Relative Heading 101 

(17) 

110 

(17) 

.332 <50 

Surface Time 

(secs) 

420 

(15) 

403 

(15) 

.910 <50 

Sighting Rate 

(Sighting hr-1) 

12.8 

(16) 

17.8 

(16) 

.469 <50 

Relative Heading 82 

(5) 

77 

(5) 

.893 <25 

Surface Time 

(secs) 

418 

(4) 

298 

(4) 

.273 <25 

Sighting Rate 

(Sighting hr-1) 

13.6 

(5) 

22.6 

(5) 

.225 <25 
381 

Several caveats should be kept in mind, however. Most exposures were at substantial ranges: the 

shortest distance was 6.7 miles, and there were only three ranges less than 20 miles. The 

observational techniques used were not very precise and there was substantial scope for the 

animals in this area to have become habituated. This analysis would have been impossible 

without the IAGC database of seismic activity, and it indicates the value of that initiative. It 

would be worth repeating the analysis including the tracking data collected on all the Gyre 

cruises completed during SWSS. 

Small Boat Studies in 2004 

In 2004 a 46' motor sailor was chartered and used to complete four cruises totaling 37 days at 

sea. Vessels of this type have been used extensively to conduct the majority of sperm whale 

behavioral research offshore in other areas; they have a number of generic advantages. Being 

small, quiet, independent and highly maneuverable, they are ideal platforms for tracking groups 

of sperm whales for several days at a time using passive acoustic techniques and for approaching 

individual animals for photo-id, observation, and biopsy. They can be run and maintained by a 

small team of sailor scientists, are reasonably comfortable and stable, and have proven a highly 

cost-effective method of working safely and independently offshore. We found that we generally 

matched or exceeded the rate of collection of key data we had achieved on the Gyre but with a 

much smaller team and at a much lower cost. 

Acoustic Monitoring and Habitat Use 

Passive acoustic monitoring of streamlined stereo hydrophones towed on cable lengths of 100-

400m has been the principle method of finding sperm whales on both the Gyre and the motor 

sailor. Search/survey tracks were chosen according to predetermined rules to provide a 

reasonable coverage of the study area, and detailed records of search effort, maintained on 

Logger, allow periods when searching meets the criteria for being considered legitimate survey 

(full effort and survey tracks random with respect to any knowledge of whale distributions) to be 

identified. Though these data cannot be analyzed to determine absolute density estimates, we 

have been with spatial modeling techniques with general additive models (GAMS) to calculate 

surfaces of relative densities in the study area. This work is ongoing but results so far are 

encouraging, with highest detection rates in water depths between 500 and 1,500m and at 

intermediate angles of slope. We hope to incorporate other potential predictors, such as oceanographic factors and bottom type into future models. 

Acoustic Length Measurement 

The body length of sperm whales can be determined by measuring the time interval between 

sound pulses in each click and scaling this information to body size using empirically-derived 

equations. While the principles behind the techniques are now well established and accepted, 

making inter-pulse interval (ipi) measurements from field recordings can be problematic; 

existing methods may require a lot of operator interaction and/or be prone to negative bias. To 

overcome this problem, we have been developing a new analysis method based on temporal 

integration of click waveforms for series of clicks from individual whales. The results are 

encouraging, but more work is needed to better quantify the technique’s performance. Acoustic 

measures of length made in 2003 and 2004 agree well with photogrammetric measures of the 
382 

same animals (see below). Acoustic length measurement is both complimentary to photogrammetric techniques and particularly useful in situations where photogrammetric methods 

cannot be used, but is also potentially capable of measuring length with sufficient precision to 

allow the growth rate of individuals to be measured between years. When both photographic and 

acoustic measures are available, the relative proportions of head length and body length, which 

are known to vary with sex and age, can be determined for individuals. 

Coda Analysis 

Codas are stereotyped patterns of clicks typically heard from groups of sperm whales resting or 

socializing at the surface. They are thought to be important for communication. Recent analysis 

of coda repertories from different sperm whale groups has revealed a level of social organization 

called “clans.” Sperm whale social units that have similar coda repertoires are considered 

members of the same clan. Although clans may be sympatric, social units only associate with 

other units that are members of the same clan. Further, clans have been shown to behave differently in other ways related to movement and foraging behavior. Codas are presumed to be 

learned socially and have been taken as indicative of culture in sperm whales. The culturally 

mediated social organization indicated by coda analysis could have a number of important 

implications for management. 

We have analyzed codas recorded from mixed groups encountered in the NGOM during 

SWAMP and SWSS cruises (a total of 3,129 codas) and compared these to codas recorded 

during other studies in the Azores (5,092), the Mediterranean (543) and the Caribbean (121) 

using a multivariate measure of similarity. Coda repertories from the Gulf of Mexico (GOM) 

cluster out as a discrete unit suggesting that NGOM mixed groups belong to a single discrete 

clan whose members are rarely encountered in other areas. This analysis is ongoing; future work 

will incorporate the substantial new recordings made in 2004 and, where possible, allocate 

recordings to identified social groups based on photo-identification data. These findings support 

those from other parts of the SWSS project which suggest that the female and immature male 

components of the GOM is a small discrete sub-population that should be considered a 

management unit. 

Jonathan Gordon has studied sperm whales for the last 25 years. He did his Ph.D. work with 

sperm whales in the Indian Ocean with Hal Whitehead developing methods of working offshore 

from small boats that have now become the “traditional techniques” for observational studies of 

sperm whales. He ran a research boat for IFAW for many years, and this provided further 

opportunities for developing passive acoustic monitoring methods, many of which are being 

adapted and adopted as part of mitigation monitoring during seismic surveys. He has been 

involved as a consultant and a PI on both the SWAMP and SWSS research projects in the Gulf 

of Mexico and is currently based as the Sea Mammal Research Unit at the University of Saint 

Andrews. 
383 

Nathalie Jaquet is currently a Research Scientist at Texas A&M University at Galveston, TX. 

She completed her honor’s degree in natural sciences at Lausanne University, Switzerland in 

1986 and an M.S. in marine ecology at Aberdeen University, Scotland in 1988. She completed 

her Ph.D. with Dr Hal Whitehead at Dalhousie University, Halifax, Canada in 1996. From 1997 

to 2001, she conducted post-doctoral studies at Otago University, Dunedin, New Zealand. She 

investigated the impact of whale-watching activities on the sperm whale population off 

Kaikoura, New Zealand. During this time she also initiated a research project on sperm whale 

distribution, abundance, and behavior in relation to jumbo squid density in the Gulf of 

California, Mexico. In 2001 she joined Texas A&M University at Galveston as a TIO postdoctoral fellow where she worked with the SWSS project. 

Ricardo Antunes received a degree in marine biology and fisheries from the University of the 

Algarve, Portugal. During the past five years he has worked as a cetacean researcher in the 

Whale Museum in Madeira, and on other cetacean research projects in the Azores, the 

Mediterranean Sea, Norway and the Gulf of Mexico. He is currently a Ph.D. student at the 

University of St. Andrews, studying sperm whale coda communication in the Atlantic. 

Luke Rendell is an NERC Research Fellow at the Gatty Marine Research Institute at the 

University of St. Andrews in the UK. He has studied aspects of vocal behavior in various 

cetacean species since 1995 but his Ph.D. and postdoc research have focused on the sperm 

whale, Physeter macrocephalus, a fantastic yet still surprisingly mysterious animal. He is 

interested in the behavioral ecology and evolution of communication systems and how these 

relate to social learning and culture in humans and other animals. He also maintains broader 

based interests in ecology, behavior and conservation. 

Bernd Würsig is Professor of Marine Biology at Texas A&M University at Galveston. He 

received his Ph.D. from the State University of New York at Stony Brook. His research interests 

focus on the behavioral ecology of marine mammals. 
384 

SPERM WHALES IN THE NORTHERN GULF OF MEXICO: ABUNDANCE, 

HABITAT USE, AND ASPECTS OF SOCIAL ORGANIZATION 

Nathalie Jaquet and Bernd Würsig, Texas A&M University–Galveston 

Jonathan Gordon, Sea Mammal Research Unit, 

University of St. Andrews, Scotland 

The mesoscale population cruise finished on the 17 August 2004. Thus, only four months have 

been available to analyze the large data set collected during summer 2004 and to integrate it to 

the data collected in 2002 and 2003. Therefore, the following results and discussions are 

considered preliminary. The next several months will be used to analyze these results in depth 

and to prepare peer-reviewed publications. It is possible that some of the results and conclusions 

outlined below will change once the data set is analyzed in greater detail. 

Distribution and abundance 

In 2004, sperm whales were found in the entire study area, along the west coast of Florida, in the 

De Soto Canyon, in the Mississippi Canyon and in the area south of the Mississippi River Delta. 

In 2004, because methodology and search patterns were consistent during the two-month field 

season, the relative abundance of sperm whales was measured using search time (Kahn et al. 

1993). The mean search time for the entire study area was 7.4 hours with a maximum of 22 hours 

between 2 encounters; never more than 22 hours were spent without encountering one or several 

sperm whales. Search time was then compared between the “Florida-De Soto Canyon” area and 

the “Mississippi” area. The mean search time for the Florida-De Soto Canyon was 8.16 hrs (SE = 

1.50) and for the Mississippi area 6.99 hrs (SE = 0.87). A t-test between these two mean 

encounter rates was not statistically significant (t = 0.690, p = 0.4932, df=50, NS), suggesting 

that, although the mean time spent between two encounters in the Florida-De Soto area was 

slightly larger than in the Mississippi area, both areas had roughly similar relative abundance of 

sperm whale encounters. 

Out of the 27 visual encounters, four were with lone sperm whales, six were with small dispersed 

groups of whales, likely bachelors’ groups; 16 were with groups of females and immature, and 

one was undetermined. There was a strong segregation in distribution between males and 

females. All groups of female/immature sperm whales were found in the Mississippi River 

Delta-Mississippi Canyon area, while the lone males and groups of bachelor males were mainly 

found in the De Soto Canyon-West Florida area. Such segregation had never been described 

before and could be due, for example, to differences in foraging behavior or in diet. 

Sperm whale absolute abundance for the entire SWSS study area was calculated using markrecapture techniques (Hammond 1986). As most of the identification photographs came from a 

short period of time, three weeks each in 2002 and 2003, and seven weeks in 2004, the full open 

model described by Whitehead (1990) could not be applied; a simple open model was fit to the 

data (SOCPROG, Whitehead 1999). The results indicate that approximately 398 individuals 

utilized our study area (95% confidence interval = 253 to 607). This result is consistent with 
385 

previous estimates of population size for this area. All mean estimates are within the 95% 

confidence intervals of the other estimates. 

Large Scale Movements 

Geographic population structure is a result of large-scale movements, and thus understanding the 

large-scale movement of Gulf of Mexico (GOM) sperm whales will give us an understanding of 

stock identity and indicate whether there are important movements between the GOM and other 

areas of the Atlantic Ocean. To investigate large-scale movements, we compared our SWSS 

catalogue (199 individuals) to about 2,500 sperm whales identified in the Atlantic in the last 15 

years. No matches were found, suggesting few movements between the GOM and the rest of the 

Atlantic. 

Small Scale Movement Patterns and Feeding Success 

Sperm whales are near the top of a long food chain, and in general, the diet of female and 

immature sperm whales consists almost exclusively of deep-living squid (Kawakami 1980; 

Clarke 1986). There is little knowledge on sperm whale diet in the GOM or on the distribution of 

deep-living squid; thus, no information is available on the amount of food resources available to 

sperm whales. It is important for management to understand why sperm whales occur in areas 

close to platforms and whether other areas have similar feeding potential. It has been shown that 

sperm whale small-scale movement patterns change with feeding success, with sperm whales 

traveling in a relatively straight line when feeding success is poor and zig-zagging over a smaller 

area when feeding conditions are good (Jaquet and Whitehead 1999; Whitehead 2003). 

Therefore, small-scale movement patterns provide an indication of feeding success in particular 

areas. During 2004, we had 16 independent encounters with groups of females/immature sperm 

whales that were followed closely days and nights from 5.75 hrs to 52.5 hrs with a mean of 23.3 

hrs. Twelve of the encounters lasted for over 10 hours, and small-scale movements and 

displacements were calculated for these 12 different encounters. Figure 2F.1 shows the root 

mean square (rms) displacement in kilometers against time lag for these 12 encounters. For any 

time lag of x hours, the rms is the average straight-line distance between the position of the 

group at time t and its position at time t+x. Horizontal displacement is the straight line distance 

and does not take into account zig-zag movements. 

Figure 2F.1 shows that on average, sperm whales move at a speed of 3.3 km per hour in the 

Mississippi area. This speed is consistent with what has been found in other areas of the world 

and is likely an optimum speed that minimizes the cost of transport and maximizes the rate of 

finding and acquiring food (Whitehead 2003). Figure 2F.1 also shows that in this area, sperm 

whales have an average horizontal displacement of about 35 km in 24 hours and 40 km in 48 

hours. It has been shown that, in general, the smaller the daily horizontal displacement, the 

higher the feeding success (Whitehead 2003); however, daily horizontal displacement will also 

be related to types of prey as well as to the aggregative behavior of the squid prey. Therefore, 

large differences in daily horizontal displacement were found in different areas of the world (45 

km in the Galápagos, 65 km in Peru/Ecuador, 70 km in Chile and 85 km in the Western Pacific: 

Whitehead 2003). Our results in the GOM suggest that the Mississippi area has good feeding 

conditions for sperm whales and that the patches of squid may be smaller (less horizontal 
386 

displacement) but denser or longer-lasting (as they zig-zag over this area for at least more than a 

day instead of just a few hours, as in Chile) than in areas of the South Pacific where small-scale 

movements have been investigated. These results give us a first insight into the northern GOM 

foraging conditions and prey aggregations. rms displacement in km

0

5

10

15

20

25

30

35

40

45

0 10 20 30 40 50

Time in hours

Figure 2F.1. Root Mean Square (rms) displacement for the 12 groups of female immatures that were followed 

for more than 10 hours (11 to 50 hours). 

Index of reproductive success 

During 2002 and 2003, few first-year calves were observed, raising concerns for the health of the 

GOM sperm whale population. However, the platforms used to study sperm whales in 2002 and 

2003 (R/V Gyre and Rhibs) were not very appropriate for this task, and calves were likely 

missed due to the difficulty of observing them from a large vessel and due to the inability to 

follow a group over more than 10 hours. In 2004, we found that eight groups out of 11 had one 

or two calves with them. This provides an overall proportion of calves of 11.5%. This proportion 

of calves is of similar magnitude as what has been found in different areas of the South Pacific 

(Whitehead 2003) and is only slightly smaller than what has been found in the Gulf of California 

(Jaquet et al. 2003; Jaquet 2004). 

Population characteristics 

Social Organization 

Because social organization is thought to be important for the survival and wellbeing of sperm 

whales, particularly females and young, knowledge of social organization of sperm whales in the 

northern GOM population is important for management. Sperm whales have highly developed 

societies (Caldwell et al. 1966) and their strong social organization allows them communally to 

take care of calves and defend against predators. Females and immature sperm whales form 
387 

long-term (>decades) associations of on average 10-12 individuals called units (Whitehead et al. 

1991; Christal et al. 1998). These units usually associate with another unit for about one week to 

form what is commonly called the group or the nursery group (Whitehead et al. 1991; Christal et 

al. 1998). 

To determine the pattern of sperm whale social organization in the GOM, we used the software 

SOCPROG (Whitehead 1999), especially developed for this purpose. The use of SOCPROG 

requires a large number of sperm whales photo-identified over a time span of several years. 

Although the SWSS project has now been running for three years, few identification photographs 

were taken in 2002; thus, most of the identification photographs were taken during a three-week 

period in 2003 and a seven-week period in 2004. Furthermore, in 2002 and 2003, it had not been 

possible to follow groups over consecutive days. Few individual whales were resighted during 

the course of the field season. Therefore, the data from 2004 are the only data that can be used to 

investigate the internal structure of groups and whether sperm whales follow the constant 

companions/casual acquaintances models found in the Pacific (Whitehead 2003). Therefore, the 

use of SOCPROG is still limited for our data set and the results are to be taken with caution. The 

results from SOCPROG using all SWSS identification photographs suggest that, in the GOM, 

sperm whales best fit a “constant companion” model. 

Group size 

Estimating group size in the field is difficult, as foraging sperm whales are spread over several 

nautical miles, and spend about 75% of their time underwater. Therefore, group size is usually 

estimated using identification photographs, and experience shows that, on average, two days are 

required for most individuals in a group to be identified (Whitehead 1999; pers. obs). Group 

sizes were very consistent; all groups followed for more than 10 hours had 9 to 11 individuals. 

This number is substantially smaller than in other areas where group size has been shown to be 

about 20 to 25 individuals (Whitehead 2003). Group size may be related to the size of prey 

patches that can be efficiently exploited. The analysis of fine-scale movements presented above 

is indicative of smaller prey patches, which is consistent with the smaller group size found here. 

Aggregations (=two or more groups associating together for time periods of hours) were never 

seen in 2004, and only one aggregation was observed in 2003 (on the 18 July). Aggregations are 

thought to be related to large patches of food that are exploited simultaneously by several groups 

of sperm whales (Jaquet 1996). The absence of aggregations also suggests that prey patches in 

the northern GOM are small. 

Length distribution 

Knowledge of whale size (as related to age) is important to most ecological studies. Length 

measurements of individual whales can provide information on growth rate and allow estimation 

of population parameters such as pregnancy rate and age at maturity (Waters and Whitehead 

1990). Measurement data can also reveal size-class segregation (Cubbage and Calambokidis 

1987). Furthermore, changes in length distribution in whale populations can be used to indicate 

the degree of depletion of a stock, as highly exploited populations are likely to have fewer older 

and thus larger animals (Cooke and de la Mare 1983). 
388 

Over the three years of SWSS study, 153 good measuring photographs were taken of 78 different 

individuals. Therefore, we have obtained length measurements for almost half of the individuals 

that we have identified. Out of these 78 individuals, three were lone males and two were from a 

group of whales that was likely composed of bachelor males. The average length for these 73 

females/immatures was 8.5 m (SD=0.85). This is much smaller than what would have been 

expected from the literature (Rice 1989). The length distribution for the GOM was then 

compared to the length distribution of female/immature of the Gulf of California (using the very 

same technique), and it was found that the whales in the GOM were on average two meters 

smaller than the one in the Gulf of California (average=10.5m, SD=0.85, n=154), and a t-test 

showed that the difference was highly significant (t-test: p<0.001). 

Differences in length distribution can be due to a variety of factors, such as 1) differences in 

whaling histories; 2) closeness of the population to carrying capacity; 3) food resources and 

feeding conditions in an area; and 4) genetic differences. Sperm whales have not been hunted 

during the modern whaling period, and thus no whaling took place after the late 1800s. This 

whaling history is very similar to the one in the Gulf of California, and thus it is unlikely to be 

the cause of this size difference. We do not have enough data to determine whether the sperm 

whale population of the GOM is close to carrying capacity; therefore, we cannot yet comment on 

this hypothesis. Further data on population dynamic and foraging behavior will help in 

answering this question. Food resources in the GOM are very different from those in the Gulf of 

California. The Gulf of California is a very productive marginal sea, with some of the highest 

surface nutrient concentrations of any ocean of the world, while the deep waters of the GOM are 

characterized by lower primary and secondary productivity. However, the pattern of small-scale 

movements suggests high feeding success in the northern Gulf. It is possible that genetic 

differences are responsible for this difference in size, as it has been shown for other species of 

cetaceans. Preliminary results suggest that sperm whales in the GOM are different from all other 

populations which have been studied in details: their group size is about half the size of groups 

elsewhere, mature males seem to have either a different behavior or a different seasonality, 

groups of females/immature have a very high site fidelity comparable to bachelor males off 

Kaikoura but never described elsewhere for females/immatures, and they have significantly 

higher incidence of markings on their flukes compared to areas in the Pacific Ocean (annual 

report 2003). Furthermore preliminary genetic analyses suggest differences between individuals 

from the GOM and the rest of the Atlantic Ocean, and similarly, preliminary analyses of codas 

suggest differences in repertoires between the GOM and the rest of the Atlantic. 

Acknowledgments 

Funding for this study was provided by MMS, IAGC, IRFC and NFWF. We wish to thanks 

Ricardo Antunes, Steve Brown, Raul Diaz, Thomas Gordon, Christoph Richter, Trudi Webster 

as well as all the Gyre’s visual and acoustic observers who greatly helped with the field work. 

This work was performed under NMFS OPR permit #821-1855-00. 
389 

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Whitehead, H. 2003. Sperm Whales: Social Evolution in the Ocean. Chicago: University of 

Chicago Press. 

Whitehead, H., S. Waters, and T. Lyrholm. 1991. Social organization of female sperm whales 

and their offspring: constant companions and casual acquaintances. Behavioral and 

Ecological Sociobiology 29:385–389. 

Nathalie Jaquet is currently a Research Scientist at Texas A&M University at Galveston, TX. 

She completed her honor’s degree in natural sciences at Lausanne University, Switzerland in 

1986 and a M.S. in marine ecology at Aberdeen University, Scotland in 1988. She completed her 

Ph.D. with Dr Hal Whitehead at Dalhousie University, Halifax, Canada in 1996. From 1997 to 

2001, she conducted post-doctoral studies at Otago University, Dunedin, New Zealand. She 

investigated the impact of whale-watching activities on the sperm whale population off 

Kaikoura, New Zealand. During this time she also initiated a research project on sperm whale 

distribution, abundance, and behavior in relation to jumbo squid density in the Gulf of 

California, Mexico. In 2001 she joined Texas A&M University at Galveston as a TIO 

postdoctoral fellow where she worked with the SWSS project. 

Jonathan Gordon has studied sperm whales for the last 25 years. He did his Ph.D. work with 

sperm whales in the Indian Ocean with Hal Whitehead developing methods of working offshore 

from small boats that have now become the “traditional techniques” for observational studies of 

sperm whales. He ran a research boat for IFAW for many years, and this provided further 

opportunities for developing passive acoustic monitoring methods, many of which are being 

adapted and adopted as part of mitigation monitoring during seismic surveys. He has been 

involved as a consultant and a PI on both the SWAMP and SWSS research projects in the Gulf 

of Mexico and is currently based as the Sea Mammal Research Unit at the University of St. 

Andrews. 
391 

Bernd Würsig is Professor of Marine Biology at Texas A&M University at Galveston. He 

received his Ph.D. from the State University of New York at Stony Brook. His research interests 

focus on the behavioral ecology of marine mammals. 
392 

GULF OF MEXICO SPERM WHALES – A GENETIC PERSPECTIVE 

Dan Engelhaupt, University of Durham 

Background 

Several fundamental genetic related aspects for endangered sperm whales occurring in the 

northern Gulf of Mexico (GOM) were assessed during the 2000–2004 SWAMP and SWSS 

cruises. A deeper understanding of the population structure and social structure of sperm whales 

using genetic techniques is presently being integrated with a variety of ongoing research projects 

such as digital acoustic recording tagging (D-tag), satellite-monitored radio tagging, distribution 

and abundance estimates, habitat use patterns and behavioral information to help establish 

realistic conservation and management strategies for these whales. In addition to providing 

important gender information for whales that have been satellite and D-tag tagged, our project 

provides essential data on social and population structure required to fully assess the impacts that 

the oil and gas industry and seismic exploration may or may not have on endangered sperm 

whales occupying potentially critical habitat areas in the northern Gulf. Sperm whales are highly 

social whales that occur in small clusters to large aggregations, in many cases, maintaining longterm bonds between female group members. Their dependence on acoustic communication 

between members and use of echolocation when feeding at depth make them vulnerable to 

anthropogenic noise. Could an outside noise influence disturb the dynamics of the group, or on a 

much larger scale, the population over time? The quantity and quality of knowledge gained from 

the combination of genetic (via degrees of relatedness among associates), satellite-monitored 

radio tagging, and behavioral studies provides the essential components to accurately describe 

social structure on a detailed scale. The original designation of a single Gulf sperm whale stock 

that is separate from the adjacent Atlantic and Caribbean is thought to be conservative. Stocks 

must be defined using several parameters including genetics. Once stocks are defined, humancaused disturbances or mortalities that occur to a stock can be managed appropriately. Such 

information is vital for creating meaningful management strategies for these animals in general, 

and relative to petroleum exploration and production in particular. 

SWAMP & SWSS Cruise Sample Analyses 

Tissue samples were collected during both SWAMP and SWSS cruises throughout 2000, 2001, 

2002, 2003 and 2004. Overall, 117 individuals (including satellite-tagged, D-tag tagged, opportunistic, and stranded whales) were genotyped using both mtDNA and microsatellite techniques. 

Gender was determined for nearly all of these samples using molecular sexing techniques. 

Results 

Population Structure 

A comparative analysis of matrilineal mtDNA and biparentally inherited nuclear genetic markers 

(microsatellites) have begun to show population structure for female lineages, which is expected 

given previous findings on social and reproductive behavior in this species. Nuclear DNA 
393 

variation across oceans is generally non-significant, suggesting that males disperse and spread 

their genes to the more site-faithful females. 

Group Structure 

Members of ‘groups’ were predominately females, although some groups appeared to contain 

only males (suggesting that bachelor groups may reside in the Gulf). During the 2002 SWSS 

cruise, multiple members from two groups of whales (Group 3 & 5) were tagged with satellite 

transmitters and subsequently biopsy sampled for genetic analyses. Relatedness levels for each 

satellite-tagged group (and groups in general) suggest that the overall group is often unrelated, 

although groups did contain highly related whales (ex. parent/offspring). mtDNA analyses 

showed that groups are comprised of both single and multiple matrilines, which combined with 

the relatedness levels, may provide additional evidence to the idea of that sperm whale groups 

are composed of both ‘constant companions and casual acquaintances.’ 

Future Recommendations 

Genetic techniques supply a powerful set of detailed data that can be directly integrated with 

both the movements of satellite-monitored tagged whales and the dive profile data of D-tagged 

whales. The gender of a tagged whale may prove crucial to improving our understanding of 

movement patterns and dive profile data (i.e. do males and females react differently to 

anthropogenic noise influences?). Future work should continue to build on previous year’s 

population and social structure results by incorporating biopsy sampling with both satellitetagging and opportunistic sampling of whales (particularly focusing on whales of sexually 

mature size). This population has already been subjected to many years of human activity, and 

there is likely to be major oil-related activity offshore here for many years to come. Social 

organization is an important component for sperm whale survival yet seems vulnerable to 

disruption by disturbance. Understanding sperm whale social organization in this putative 

population before it is exposed to any more disturbance and exploring whether it is affected by 

offshore activity is thus a priority. To increase the resolution for population structure analyses, 

we recommend sampling sperm whales located in additional geographic areas like the Caribbean 

Sea and western North Atlantic Ocean in addition to sampling whales in the eastern, western, 

southern and northern GOM during the winter winter/spring months when large sexually and 

physically mature males may be present. A continuation of the genetic components previously 

described will maintain both the quality and quantity of information required for management 

purposes. 

Dan Engelhaupt completed his Ph.D. at the University of Durham, England. His special field of 

study includes the assessment of population structure and social structure for endangered species, 

with a emphasis on sperm whales. Over the past five years, as part of the Minerals Management 

Service sponsored SWAMP and SWSS projects, he has examined the genetic variation and 

social structure of endangered sperm whales with a particular focus on putative ‘populations’ in 

the northern Gulf of Mexico, Mediterranean Sea, and the North Atlantic Ocean using a suite of 

molecular techniques. Mr. Engelhaupt is collaborating with a number of other researchers to 
394 

provide an accurate sperm whale dataset so that management can effectively oversee sperm 

whale populations that exist in areas of anthropogenic noise. 
395 

THREE-DIMENSIONAL TRACKING OF SPERM WHALES 

USING PASSIVE ACOUSTICS 

Aaron Thode, Scripps Institution of Oceanography 

Introduction and Summary 

Sperm whales are a very vocally active species, and detecting their signals, or “clicks,” using 

towed passive acoustic arrays has become a standard procedure for locating and monitoring for 

the presence of these animals (Gillespie 1997; Gillespie and Leaper 1997; Barlow and Taylor 

1998). Most passive array systems can also estimate the direction from which a particular sound 

is arriving by measuring the signal’s arrival time difference at two hydrophones spaced a few 

meters apart. The range to a whale can be estimated by measuring how the measured bearings 

from a particular animal shift over time while the observation platform is moving. If the velocity 

of the platform is much larger than that of the animal, then the bearings will converge to a 

particular range over a 3–10 minute interval. Unfortunately, the speed of seismic vessels is not 

much greater than sperm whale swimming speeds, so at present there is no reliable way for 

ranging sperm whales using standard mitigation procedures. In addition, knowledge of the 

animal’s depth becomes important for mitigation purposes whenever the animal of concern is 

deep-diving and the acoustic source is highly directional at certain frequencies, as is the case 

with seismic airgun arrays. 

In 2003 and 2004 the SWSS project supported efforts to develop a three-dimensional tracking 

method for sperm whales using various combinations of towed acoustic gear. All methods rely 

on the fact that sperm whale sounds have such a short time duration that the surface-reflected 

acoustic path can often be distinguished in time from the direct path arrival. The basic concept 

was first demonstrated during the 2002 SWSS D-tag cruise, using data from two towed arrays 

(Thode 2004). Based on these results, both MMS and the International Association of 

Geophysical Contractors (IAGC) provided funds to build a dedicated towed array to demonstrate 

routine 3-D tracking of sperm whales during the 2004 SWSS S-tag cruise. The 400 m long 

“tandem” towed-array system was successfully deployed from the R/V Gyre during the entire 

cruise, and over two weeks of acoustic data were recorded, and a near real-time ranging 

algorithm was assembled in the field. Some initial 3-D tracks have been analyzed and their 

veracity checked using a variety of methods. The effects of ray-refraction from a depthdependent sound speed profile have also been evaluated and to date seem to be negligible for 

ranges of 1 km or less. Aspects of these algorithms have been published in the peer-reviewed 

literature (Thode 2004), and currently plans are underway to develop and test a real-time 

tracking system during SWSS 2005. 

Equipment 

The MMS 3-D tracking effort uses signals collected across a large-aperture PAM system to 

estimate animal ranges and depths, while making no assumptions about an animal’s signal 

characteristics. The total “tandem” array is comprised of six hydrophones on a single cable, 

arranged as two sub-arrays of three phones each, with the sub-arrays separated by 200m (Figure 
396 

2F.2) and the sub-array element spacing 1 m. Each sub-array also has a pressure transducer that 

permits the depth of each sub-array to be logged independently. 

Figure 2F.2. Illustration of 2004 3-D deployment off R/V Gyre, using a tandem array specifically built for the 

project. Top: side view of tandem array during S-tag deployment. Bottom: View of S-tag array 

deployment from above, showing how tandem and ecologic array were deployed in parallel, 

which permits bearings of sounds to be determined without a port/starboard ambiguity. The 

total configuration permitted 3-D tracking data to be collected without interfering with S-tag 

requirements. Round circle: calibrated hydrophone; blue diamonds: pressure (depth) sensors; 

red square: underwater connector that would permit array aperture to be extended in 2005. 

Concept 

There are actually two separate algorithms for tracking the range and depth of a sperm whale 

using this array system. Technique “A” requires only two hydrophones, and was tested in 2002 

and 2003 (Thode 2004). Technique “B,” requires a third hydrophone, but seems considerably 

more robust to ship noise and uncertainties in hydrophone depths; was the focus of work in 2004. 

The “B” algorithm is described here. Figure 2F.3 illustrates the three measurements that permit 

tracking: the differences between the arrival times of the direct and surface-reflected paths(Pds,R)

on the rear (R) hydrophone, the arrival time difference between the direct paths on both 

200 m 

Direct paths

Surface 

2 knots 

200 m

200 200 

Tandem 

Ecologic 

Underwater connector 

Pressure sensor 
397 

hydrophones (Pdd), and an estimate of the direct path bearing on the rear hydrophone (d). Given 

this information one finds the slant range from the forward hydrophone site to be 

dd d

dd d dd

d F P L

LP L P P

η

η

cos

2 cos

2

1 2 2

, −

− − ⎟

⎠

⎞ ⎜

⎝

⎛ =

 (1) 

from which the whale depth can be determined from 

( )

a R

ds R d F ds R

w z

P P P

z

,

, , ,

4

2 + =

 (2) 

Figure 2F.3. Spectrograms of data collected during 2004 3-D tracking experiment, as viewed with a 

MATLAB graphical user interface. The top spectrogram displays a hydrophone of the forward 

sub-array, and the bottom spectrogram displays a hydrophone in the rear sub-array. The 

arrival-time differences indicated in the diagram can be used to obtain animal range and 

depth, if both array depths are known. Occasionally, bottom returns appear, which permit an 

independent check of the tracking algorithm. If the bearings of at least one the direct-path 

signals can be measured, then the direct-surface time-of-arrival (TOA) difference on the 

forward hydrophone is not required (i.e. tracking method “B” can be used instead of “A”). 
398 

The method assumes that the local tilt of the rear subarray is equivalent to the effective tilt of the 

entire cable between the forward and rear hydrophone (i.e. the towed array cable is effectively 

straight between the forward and rear hydrophone). If this is not the case, expanded forms of 

Eq. (1) can be derived. The expression in the denominator of Eq. (1) indicates that the method 

will work as long as the animal is close enough such that the “wavefront” defined by the pulse is 

curved. Put another way, Eq. (1) should work as long as an acoustic bearing measured from the 

front hydrophone site differs from a bearing measured at the rear site. 

Example 

On the evening of 16 June a whale began a dive descent near the vessel. An example of data 

collected during this dive is shown in Figure 2F.3. In Figure 2F.4 the animal depth and range is 

shown for the two tracking algorithms, along with single-hydrophone fixes made by exploiting 

bottom multipath(Thode et al. 2002). All the methods agree until the ship changes course, as 

seen in the bottom plot, and Algorithm “B” becomes inaccurate. 

Figure 2F.4. Acoustic track of diving sperm whale on 16 June 2004: Top: Whale depth vs. local time using 

“A,” “B,” and single-phone tracking algorithms; Middle: Whale range vs. time for same 

algorithms; Bottom: Ship course and speed. Note divergence of “B” (black) algorithm once ship 

turns. 
399 

References 

Barlow, J. and B.L. Taylor. 1998. Preliminary abundance of sperm whales in the northeastern 

temperate pacific estimated from a combined visual and acoustic survey. Cambridge: 

International Whaling Commission. 

Gillespie, D. 1997. An acoustic survey for sperm whales in the Southern Ocean Sanctuary 

conducted from the RSV Aurora Australis. Reports of the International Whaling 

Commission 47:897–907. 

Gillespie, D. and R. Leaper. 1997. Detection of sperm whales (Physeter macrocephalus) clicks, 

and discrimination of individual vocalisations. Research Cetaceans 10:87–91. 

Thode, A. 2004. Tracking sperm whale (Physeter macrocephalus) dive profiles using a towed 

passive acoustic array. Journal of the Acoustic Society of America 116(1):245–253. 

Thode, A., D.K. Mellinger, S. Stienessen, A. Martinez K. Mullin. 2002. Depth-dependent 

acoustic features of diving sperm whales (Physeter macrocephalus) in the Gulf of 

Mexico. Journal of the Acoustic Society of America 112(1):308–321. 

Aaron Thode earned his Ph.D. at Scripps Institution of Oceanography in 1999, with his thesis 

work involving the acoustic tracking of blue whales. After a post-doc in the MIT Ocean 

Engineering Department, he attained his current research position at Scripps in 2002. That year 

he obtained the Office of Naval Research Acoustic Entry Level Faculty Award, currently being 

used to develop new types of passive acoustic tracking systems for marine mammals. In late 

2004 he was awarded the A.B. Wood Medal by the UK Institute of Acoustics and the Acoustical 

Society of America, “for distinguished contributions in ocean acoustics/signal processing and 

marine mammal acoustics.” 
400 

PHYSICAL ENVIRONMENT OF THE NORTHERN GULF OF MEXICO 

DURING SUMMERS 2002–2004 

Ann E. Jochens, Matthew K. Howard, Steven F. DiMarco, and Douglas C. Biggs, 

Texas A&M University 

The Sperm Whale Seismic Study (SWSS) is a cooperative study of sperm whales in the Gulf of 

Mexico (GOM), their habitat, and their response to man-made noise. Scientists at Texas A&M 

University and the University of Colorado are conducting the habitat characterization study 

component of SWSS. Data collection includes in situ data during the cruises and remote sensing 

data before, during, and after the cruises. The in situ data, which are collected by the authors on 

the SWSS cruises, consist of currents from 153 kHz and 38 kHz acoustic Doppler current 

profilers (ADCP); temperature and salinity profiles using both conductivity-temperature-depth 

(CTD) sensors and expendable bathythermograph (XBT) probes; continuous, near-surface 

temperature, salinity, and fluorescence observations; and discrete chlorophyll data for calibration 

of fluorescence measurements into chlorophyll data. Remote sensing data consist of sea surface 

height (SSH) fields from satellite altimeter (Robert Leben of the University of Colorado), as well 

as ocean color fields from SeaWiFS (courtesy of Chuanmin Hu of the University of South 

Florida). 

Data from the 2002–2004 field cruises were used to examine the dynamics of the circulation 

over the slope of the northern GOM, which has been the focus of the SWSS study area, and to 

consider the interaction of physical and biological components of the ecosystem. The circulation 

in the upper 1,000 m or so of the water column is forced mainly by mesoscale features such as 

the Loop Current, which enters at the Yucatan Channel and exists at the Florida Straits, Loop 

Current eddies (LCEs) that separate from the Loop Current, and slope eddies that are both 

anticyclonic (clockwise) and cyclonic (counterclockwise) circulating features. Wind-forcing of 

currents generally is weaker than that of the mesoscale forcing except during energetic 

atmospheric events such as hurricanes. Tidal currents in the Gulf are weak. Buoyancy driving 

from river input is significant on the northern shelves, but not over the slope or in deeper waters 

(see Nowlin et al. 2001 for a detailed discussion of the deepwater circulation in the GOM). 

The fine-scale resolution of the ship surveys, when combined with the mesoscale resolution of 

remote sensing surveys of sea surface height and ocean color, document the summer-to-summer 

variability in the intensity and geographic location of Loop Current eddies, warm slope eddies, 

and areas of cyclonic circulation over the middle slope region of the northern GOM. These 

variations forced striking year-to-year differences in the locations along the 1,000-m isobath 

where there was on-margin and off-margin flow, and in locations where sperm whales were 

encountered along the 1,000-m isobath. 

In summer 2002, an anticyclonically circulating warm slope eddy was present between 89°W 

and 91°W over the slope. Maximum speeds were about 70 cm/s near surface and decreased to 

30–40 cm/s at 200 m. Flows at the eastern side of the anticyclone were directed off-margin and 
401 

moved low salinity shelf waters out into deeper waters. The water here was green-brown, 

indicating biological productivity, rather than the oceanic blue water that occurred along most of 

the cruise track. A second region of off-margin flow was located west of 88°W and was 

associated with a weaker warm slope eddy located in the deepwater of DeSoto Canyon. Sperm 

whales were locally abundant in Mississippi Canyon and off the delta (see also Jochens and 

Biggs 2003). 

In contrast, in summer 2003, a strong Loop Current eddy, LCE Sargassum, was moving onto the 

slope of the eastern Gulf during June. This resulted in very strong flows at the northern limb of 

the eddy as it encroached onto the slope. Maximum currents were about 120 cm/s near surface, 

50 cm/s at 300 m, and 30 cm/s at 800 m. Over the Mississippi Canyon area, these flows resulted 

in the displacement of the usual lower-salinity, higher-chlorophyll waters with low-nutrient, lowchlorophyll "ocean desert" water of Caribbean origin. In July, the LCE moved back into deep 

water away from the slope taking the Caribbean-type waters with it. When there was strong onmargin flow into the Mississippi Canyon region in early summer 2003, sperm whales were very 

rarely seen or heard there. It is hypothesized that sperm whales usually seen in this area moved 

west and/or east out of this area during the time, in June 2003, that the LCE reached farthest 

north along the margin (see Jochens and Biggs 2004 for additional discussion). 

For four weeks in May–June 2004, XBT probes were deployed and ADCP and 

fluorescence/temperature/salinity data were logged continuously while carrying out visual and 

passive-acoustic search for sperm whales as R/V Gyre surveyed along the 1,000-m isobath of the 

northern GOM. Several CTD casts were made, particularly when and where the XBT and ADCP 

data indicated that the ship track was passing into or out of the region of surface flow confluence 

set up by an anticyclonic-cyclonic slope eddy pair. The fine-scale resolution of the ship survey, 

when combined with the mesoscale resolution of remote sensing surveys of sea surface height 

and ocean color, indicated that this slope eddy pair entrained low salinity, high chlorophyll 

Mississippi River water, and carried this surface water off margin between 90°W and 88°W. 

Most of the 37 groups of sperm whales that were seen or heard in 13 different geographic 

locations in May–June 2004 were encountered in or near this off-margin flow, where SSH 

generally ranged from +2 to -4 cm. In contrast to most of the sperm whale encounters in previous 

years 2000–2003, however, only a few of the whale encounters were well inside the region of 

lower SSH that was representative of the interior of the cyclonic eddy (<-5 cm). Moreover, in 

summer 2004, most whales were encountered where surface chlorophyll was no higher than the 

0.3 μg/L ensemble average along the 1,000-m isobath between 91°W–86°W. 

References 

Jochens, A.E. and D.C. Biggs, eds. 2003. Sperm whale seismic study in the Gulf of Mexico; 

Annual Report: Year 1. U.S. Dept. of the Interior, Minerals Management Service, Gulf of 

Mexico OCS Region, New Orleans, LA. OCS Study MMS 2003-069. 139 pp. 
402 

Jochens, A.E. and D.C. Biggs, eds. 2004. Sperm whale seismic study in the Gulf of Mexico; 

Annual Report: Year 2. U.S. Dept. of the Interior, Minerals Management Service, Gulf of 

Mexico OCS Region, New Orleans, LA. OCS Study MMS 2004-067. 167 pp. 

Nowlin, W.D., Jr., A.E. Jochens, S.F. DiMarco, R.O. Reid, and M.K. Howard. 2001. Deepwater 

Physical Oceanography Reanalysis and Synthesis of Historical Data: Synthesis Report. 

OCS Study MMS 2001-064. U.S. Dept. of the Interior, Minerals Management Service, 

Gulf of Mexico OCS Region, New Orleans, LA. 528 pp. 

Ann Jochens, Matt Howard, Steve DiMarco, and Doug Biggs are the Co-Principal Investigators 

(co-PIs) for characterization of biological and physical oceanography processes in the SWSS 

study area. They are from the Department of Oceanography at Texas A&M University (TAMU). 

They have collaborated as co-PIs on previous MMS-sponsored projects NEGOM, and DGoMB. 

Jochens, Howard, and DiMarco are physical oceanographers who also were co-PIs for the MMSsponsored LATEX, Deepwater Historical Data Reanalysis, and Processes Maintaining Oxygen 

Levels in the Deepwater studies of the Gulf of Mexico. Biggs was a co-PI on the MMSsponsored GulfCet-II project and helped define the oceanographic habitat of cetaceans for an 

MMS-NOAA-ONR study in summers 2000 and 2001 of Gulf of Mexico Sperm Whales and 

Acoustic Monitoring Program (SWAMP). 
403 

ANALYSIS OF THE MESOPELAGIC COMMUNITY IN AREAS OF FEEDING AND 

NON-FEEDING BY SPERM WHALES IN THE NORTHERN GULF OF MEXICO 

John H. Wormuth, Department of Oceanography, Texas A&M University 

Introduction 

The objectives of the midwater trawling component of the Sperm Whale Seismic Study (SWSS) 

were to sample the potential prey fields at depths where sperm whales are known to feed and to 

sample areas where whales are actively feeding as well as areas where they are not observed to 

be feeding. In order to achieve these objectives, we used a 14.8 m2

 Isaacs-Kidd midwater trawl 

with an inner liner mesh of 4 mm terminating in a 0.333 mm mesh plankton net. The fishing 

intervals chosen were 0–400 m, 400–600 m and 600–800 m. The two deeper intervals were 

selected to partition the feeding depths of whales recorded in the previous field year. The 0–400 

m interval was chosen to look at those components the trawl would sample on its way down to 

the deeper intervals. Depth and temperature were recorded with a Sea Bird TDR Model 39. 

Volume filtered was measured with a General Oceanics flow meter. 

Tows were taken at night following the days’ completion of over-the-side operations. This 

limited our ability to sample in “non-whale” areas, but reduced time lost to reacquiring whales 

prior to dawn. A total of 24 successful trawls were completed in cyclonic, anticyclonic and 

“other” regions. Samples were sorted into fish, crustaceans, and cephalopods. Displacement 

volumes (DV) were measured for each component. Temperature profiles for each of the three 

categories were plotted and showed a high degree uniformity with each category. 

Previous reports have discussed analyses of the DV values, fishing characteristics of the trawl, 

and volumes filtered in the three depth intervals sampled. This report discusses results from the 

taxonomic work completed within the past year. A total of 84 crustacean taxa, 29 cephalopod 

taxa, and 11 fish taxa have been identified and counted. Crustacean and cephalopod taxonomy is 

completed. Fish taxa are incomplete, mainly in the Myctophidae. In this family there are 53 

species in 17 genera that occur in the Gulf of Mexico (GOM). The identifications are going 

slowly, but the learning curve is getting less steep. In addition, there are many other fish in these 

samples, but their occurrence is very sporadic and unlikely to affect the analyses. In most of the 

correspondence analyses, the taxa that were the “outliers” were the infrequent taxa. 

Results 

Examination of the two temperature profiles that represented the extremes of the cyclone and the 

anitcyclone (IKMT #15 and IKMT #22) show only a small difference at the surface, maximum 

differences from 100–200 meters and less than 1.3 o

C below 400 meters. Previously presented 

data also show no statistical differences in zooplankton biomass below 100 meters between 

cyclones and anticyclones (Wormuth et al. 2000). 

The taxonomic data matrix is 123 taxa by 24 trawls. Correspondence analysis (CA) was selected 

as the statistical tool to handle such a large matrix (Greenacre 1993, Palmer 1993). Ordination 
404 

techniques evolved from Principal Component Analysis through Factor Analysis to CA. The 

main advantage of CA is that the method of vector analysis allows both row and column categories to be plotted on the same set of eigenvalue axes. In Factor Analysis this cannot be done. 

Eight different analyses are summarized in Table 2F.2. The tabled values are the proportion of 

the total variance in each data set that is accounted for by the first, second, and third eigenvalues. 

The values for each of the first two eigenvalues for each taxa and trawl are then plotted. A visual 

inspection can help determine why a particular trawl or subset of trawls may differ from others. 

The first analysis in Table 2F.2 used all trawls except #4, which briefly hit the bottom. Because 

of the sediment picked up, the specimens were quite damaged and most identifications were not 

possible. For the other 23 trawls, 116 taxa (of the total of 124 taxa) were used. Several taxa were 

combined because they were males and females of the same species. The total amount of 

variance explained by the first three eigenvalues was low (27%). Figure 2F.5 shows a plot of the 

first two axes of correspondence. Only trawls #12 and #24 stand out from the other trawls. 

Analyses #2–4 in Table 2F.2 are for just the trawls from each of the three depth strata. Taxa that 

did not occur in any of the three trawls were eliminated from the analysis. Analysis #2 for the 

three 0–400 meter trawls show the trawls to be distinct from each other (Figure 2F.6). There is a 

cluster of taxa associated with each trawl with most other taxa falling inside the triangle formed 

by the trawls. Trawl #20 was in a cyclone, #21 was in an anticyclone, and #25 was in “other.” 

Analysis #3 for the six trawls from 0–600 meters separates trawl #12 (“other”) from the other 

five, but #14 and #23 are positive on CA2 as is #12. The other three (#6, #16 and #17) are all 

negative on CA1 and CA2 and are all cyclonic. There appear to be no discernable trends in 

Analysis #3. 

Analysis #5 in Table 2F.2 is for 23 trawls and the 74 most abundant taxa with average 

concentrations > .04 indiv./ 1000 cubic meters water filtered. Trawls #12 and #24 group by 

themselves (both “other”), trawl #21 (anticyclone) is well separated from #12 and #24 and is 

somewhat separated from the rest of the trawls. Again, the amount of variance explained by 

CA1–CA3 is low, only 26%. 

Analysis #6 in Table 2F.2 is also for 23 trawls; however, the species that were collected in the 

three 0–400m tows have been removed, leaving 83 taxa. The results are very similar to those of 

Analysis #5 with only slightly more variance explained. Analysis #7 is for 23 trawls with the 

restrictions of Analyses # 5 and 6 imposed. This left 50 taxa in this analysis. Again, trawls #12 

and 24 separated themselves, but with no improvement in the amount of variance explained. 

Analysis #8 is for only the 0–800 meter trawls and all of the less frequent (< 4 occurrences out of 

the 13 trawls) were eliminated. This left only 41 taxa. The first three eigenvalues accounted for a 

total of 44% of the total variance, the highest of all analyses. Only trawls #10 and 24 stood out 

from the others. The taxa that separated from the “central mass” of points were all euphausiids 

species with nut one exception. 
405 

Table 2F.2. Results of correspondence analysis runs for selected subsets of data. 

ANALYSIS #1

Correspondence analysis Eigenvalues 1 2 3 

Percent Variance Explained 10 9 8 All 23 Trawls 

Cumulative Percent 10 19 27 116 Taxa 

 

ANALYSIS #2

Correspondence analysis Eigenvalues 1 2 0-400 meters 

Percent Variance Explained 52 48 3 Trawls 

Cumulative Percent 52 100 55 Taxa 

 

ANALYSIS #3

Correspondence analysis Eigenvalues 1 2 3 400-600 meters 

Percent Variance Explained 31 22 18 6 Trawls 

Cumulative Percent 31 53 71 80 Taxa 

 

ANALYSIS #4

Correspondence analysis Eigenvalues 1 2 3 600-800 meters 

Percent Variance Explained 16 12 11 13 Trawls 

Cumulative Percent 16 28 39 101 Taxa 

 

ANALYSIS #5

Correspondence analysis Eigenvalues 1 2 3 All 23 Trawls 

Percent Variance Explained 10 9 8 74 Taxa 

Cumulative Percent 10 18 26 <.04 Averages Removed 

 

ANALYSIS #6

Correspondence analysis Eigenvalues 1 2 3 23 Trawls (-#4) 

Percent Variance Explained 12 10 9 0-400m Taxa Removed 

Cumulative Percent 12 22 31 83 Taxa 

 

ANALYSIS #7

Correspondence analysis Eigenvalues 1 2 3 23 Trawls (-#4) 

Percent Variance Explained 11 11 9 50 taxa 

Cumulative Percent 11 22 31 0-400m Taxa Removed 

 <.04 Averages Removed 

ANALYSIS #8 

Correspondence analysis Eigenvalues 1 2 3 13 Trawls (-#4) 

Percent Variance Explained 16 15 12 41 taxa 

Cumulative Percent 16 32 44 0-400m Taxa Removed 

 Freq <30% Removed 
406 

-3

-2

-1

0

1

2

3

-1 0 1 2 3 4

Correspondence Axis 2 (9%)

Correspondence Axis 1 (10%)

GROUP 1

PAIR 1

GROUP 2

GROUP 3

GROUP 4

TRAWL #24

TRAWL #12

TRAWL #25

Euphausia

 similis

Octopus

 neilsonii

Bentheuphausia

 ambylops

Gennadas

 bouvieri

Funchalia Sergia villosa

Figure 2F.5. Correspondence axes 1 and 2 for 23 trawls and 116 taxa. Group 1 includes Sergestes atlanticus, 

Sergestes pectinatus (sergestid shrimp) and Ommastrephidae unidentified (a squid family). Pair 

1 consists of Dantecia caudani (an ophlophorid caridean) and Pterygioteuthis sp (a squid genus). 

Group 2 includes Meningodora vesca, Oplophorus spinosus, Plesionika grandis (crustaceans), 

Galaiteuthis sp., and Sandalops sp. (squid). Group 3 includes Systellapsis cristata, Sergestes 

‘alanticus group’ sp 1, Euphausia brevis, and Euphausia tenera (all crustaceans). Group 4 is 

composed of Sergestes sp., Euphausia mutica, Euphausia pseudogibba (crustaceans), and 

Haliphron mollis (squid). 

Discussion 

With the exception of Analysis #2, the amount of variance explained by these analyses was 

disappointingly low. It is obvious from Table 2F.2 that the number of trawls is much more 

important than the number of taxa in determining the amount of variance explained. Further 

analyses with justified smaller sets of trawls have been undertaken. The analyses have shown, 

however, that a few trawls that stand out from the others. These distinctions will be pursued. 

Overall, these results suggest that below 400 meters, the water masses are homogeneous and that 

differences in community structure do not exist for the most part. This is not surprising 

considering that analyses of zooplankton samples from the upper 200 meters in cyclones, 

anticyclones, and in other regions of the northern GOM show that differences exist, but only in 

the upper 100 meters of the water column (Wormuth et al. 2000). 
407 

-1

-0.5

0

0.5

1

1.5

2

-1 -0.5 0 0.5 1 1.5

Correspondence Axis 1 (52%)

Correspondence Axis 2 (48%)

GROUP 1

TRAWL #21

TRAWL #20

TRAWL #25

GROUP 3

GROUP 2

Helicocranchia

 papillata

Sergia

 splendens

Figure 2F.6. Correspondence axes 1 and 2 for 3 trawls (0–400 meters) and 55 taxa. Group 1 includes 

Systellaspsis pellucida, Gennadas bouvieri total, Thysanopoda monocantha (Crustaceans), 

Abralia atlantica, Heteroteuthis sp., Pyroteuthidae, Stenoteuthis pteropus (squid), and Sternoptyx 

diaphana (fish). Group 2 consists of Meningodora vesca, Oplophorus spinosus, Plesionika 

grandis, Sergia sp., Thysanopoda tricuspidata (Crustaceans), Galaiteuthis sp., Pyroteuthis 

margaritifera, Sandalops sp., and Squid unidentified. Group 3 includes Acanthephyra gracilipes, 

Sergia robustus, Sergia tenuiremi, Nematoscelis gracilis, Nematoscelis microps, Stylocheiron 

abbreviatum, Thysanopoda aequalis, Thysanopoda obtusifrons (Crustaceans), Cranchiidae, 

Histioteuthis arcturi, and Pterygioteuthis giardi (squid). 

From the standpoint of trophodynamics in the 400–800 meter community, the weights of the 

larger organisms are probably more important than their concentrations. Size frequency and 

weight data for hatchet fishes and Gonostoma have been completed. Weights have been 

measured on myctophids and Cyclothoe, but only as single values per trawl. These data will be 

supplemented with weights of other deep living species. 

A set of trawls was made in October 1996 in the eastern area of the 2003 SWSS cruise using a 4 

m2 MOCNESS with 4mm mesh. Each trawl collected seven discrete samples in the upper 400 

meters of the water column. The data from these trawls will be used to further eliminate those 

taxa that occur in the upper 400 m. 
408 

The intriguing question that these results raise is: “Why do the whales occur more frequently in 

the cyclones when there appear to be no differences in the micronekton and nekton in the depths 

at which they feed?” 

References 

Greenacre, M.J. 1993. Correspondence Analysis in Practice. London: Academic Press. 

Palmer, M.W. 1993. Putting things in even better order: the advantages of canonical 

correspondence analysis. Ecology 74:2215–30. 

Wormuth, J.H., P.H. Ressler, R.B. Cady and E.J. Harris. 2000. Zooplankton and micronekton in 

cyclones and anticyclones in the Northeast Gulf of Mexico. Gulf of Mexico Science 

18:23–34. 

Dr. John Wormuth earned his Ph.D. from the Scripps Institution of Oceanography. After a oneyear post-doc at Scripps, he came to Texas A&M as an Assistant Professor. He has led and 

participated in studies on zooplankton, pteropods, krill and squid in the North Atlantic, the Gulf 

of Mexico and the Antarctic. He has graduated twelve Ph.D. and eight M.S. students while at 

Texas A&M. 
409 

SESSION 1G 

PLATFORM ECOLOGY 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

THE FIDELITY OF RED SNAPPER (LUTJANUS CAMPECHANUS) TO PETROLEUM 

PLATFORMS AND ARTIFICIAL REEFS IN THE NORTHERN GULF OF MEXICO 

Megan B. Peabody Westmeyer and Charles A. Wilson ............................................................. 411 

THE BUCCANEER GAS AND OIL FIELD “RIGS TO REEFS” 1977–2004 Benny J. 

Gallaway, Larry R. Martin, John G. Cole, Robert G. Fechhelm, Charles A. Wilson, 

Yvonne Allen, and Mark Miller.................................................................................................. 415 

POTENTIAL SPATIAL AND TEMPORAL VULNERABILITY OF PELAGIC FISH 

ASSEMBLAGES IN THE GULF OF MEXICO TO SURFACE OIL SPILLS ASSOCIATED 

WITH DEEPWATER PETROLEUM DEVELOPMENT Mark C. Benfield and 

Richard F. Shaw.......................................................................................................................... 419 

DETERMINATION OF TRACE ELEMENTS IN RED SNAPPER, LUTJANUS 

CAMPECHANUS, OTOLITHS USING ICPMS TO EVALUATE THEIR AFFINITY 

FOR OIL AND GAS PLATFORMS Lauren Mione, James H. Cowan, Jr., Richard F. Shaw, 

Robert Gauldie, and Eric DeCarlo.............................................................................................. 424 

DISTRIBUTION OF CORALS COLONIZING OIL AND GAS PLATFORMS IN THE 

NORTHWESTERN GULF OF MEXICO: A PRELIMINARY REPORT 

Paul W. Sammarco, Amy D. Atchison, and Gregory S. Boland ................................................ 429 

GENETIC AFFINITIES BETWEEN CORALS ON THE FLOWER GARDEN BANKS VS. 

OIL/GAS PLATFORMS IN THE NORTHERN GULF OF MEXICO: IMPLICATIONS 

FOR DISPERSAL Amy D. Atchison, Paul W. Sammarco, and Daniel A. Brazeau................. 438 
411 

THE FIDELITY OF RED SNAPPER (LUTJANUS CAMPECHANUS) TO PETROLEUM 

PLATFORMS AND ARTIFICIAL REEFS IN THE NORTHERN GULF OF MEXICO 

Megan B. Peabody Westmeyer and Charles A. Wilson, 

Department of Oceanography and Coastal Sciences, 

School of the Coast and Environment, Louisiana State University 

The habitat value of petroleum platforms for red snapper, Lutjanus campechanus, is poorly 

understood; however, it is widely recognized by both scientists and fishermen that the presence 

of platforms in the northern Gulf of Mexico (GOM) has affected the distribution and perhaps the 

abundance of red snapper by the addition of hard substrate habitat. The red snapper is the target 

of lucrative and heavily managed commercial and recreational fisheries, and the petroleum 

industry in the GOM is economically important to several of the Gulf States and the United 

States as a whole. The promulgation of effective management regulations both for the red snapper fisheries and for the petroleum industry must include information about the habitat 

preferences of red snapper as they relate to platforms. It is evident that platforms and artificial 

reefs (often toppled platforms) act as some sort of essential habitat for red snapper in the 

northern GOM, but the absolute importance of these artificial habitats to the red snapper population is as yet undetermined. To manage this species successfully, we must consider its use of 

platforms as habitat and determine the level of importance of these platforms to the ecology of 

red snapper. Advances in acoustic telemetry have resulted in a valuable technology that permits 

continuous tracking of specimens and yields more detailed and accurate information on red 

snapper usage of platforms. To address the question of the importance of petroleum platform 

habitats to red snapper, we monitored the fidelity of red snappers to standing and toppled 

platforms with acoustic telemetry. 

In May 2003, 125 red snapper were captured with hook and line at several platforms in a 35 km2

portion of the South Timbalier oil and gas lease blocks, 50 km south of Port Fourchon, Louisiana 

(Figure 1G.1). Following anesthetization with MS-222, an individually coded acoustic pinger 

(V8SC-2H from VEMCO Ltd., 100 Osprey Drive, Shad Bay, Nova Scotia, Canada B3T 2C1) 

was surgically implanted into the peritoneal cavity of each fish. Each fish was also fitted with a 

Floy® internal anchor tag (FM-95W) bearing a contact number and offer of reward for returned 

tags. The incisions were sutured and sealed with veterinary glue. After a short recovery period, 

the red snapper were released at five platforms in the study area. Presences of individual snapper 

were recorded with omnidirectional acoustic receivers attached to seven platforms and to one 

artificial reef, a toppled platform. 

The majority of tagged snapper did not exhibit movement between or among receiver locations 

on a daily, weekly, or even a monthly basis, leading to a conclusion of high site fidelity over the 

short-term. A small number of tagged red snapper were recaptured outside the study area and 

displayed little movement in a uniform direction (Figure 1G.1). Of the red snapper that moved, 

those at liberty longer moved greater distances, as though they gradually dispersed from their 

area of origin over time. The results of a logistic regression on the probability of a red snapper 
412 

being present at its site of release suggest that the longer-term (over a period of six months) site 

fidelity of red snapper is much lower than the short-term fidelity, perhaps approaching zero 

(Figure 1G.2). This result differs from previous studies that reported high fidelity over long time 

spans, though none of these studies were conducted at platforms off the Louisiana coast. 

Figure 1G.1. Map showing the starting and ending points for the seven red snapper that were recaptured at 

locations other than their release sites. The unconfirmed location where one or two other red 

snapper may have been captured and released east of the study area is also shown. 

Predicted Probability of Presence

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Period

Probability

Native Relocated Native Conf. Int. Relocated Conf. Int.

Figure 1G.2. Predicted probability of presence at release location for both native and relocated red snapper. 

Dashed lines are 95% confidence intervals. 
413 

A Fourier analysis revealed a diel pattern of movement away from the structures at night, most 

likely for offsite foraging on benthic organisms in the surrounding area (Figure 1G.3). A LOESS 

procedure revealed that this diel pattern took the form of a crepuscular movement, with red 

snapper moving away from the structures just before sunrise and at sunset. The red snapper 

appeared to take advantage of the overlap of diurnal and nocturnal organisms by venturing on 

intense feeding forays at dawn and dusk, with intermittent feeding forays throughout the night. 

Figure 1G.3. Periodogram for South Timbalier 135-M showing the period and the power of the sine functions 

describing red snapper movement away from the platform. 

Knowledge of red snapper fidelity to and movement around petroleum platforms will lead to 

more effective management of this species by clarifying both the specific function of these 

structures as habitat and their importance to the red snapper population in the GOM. There is 

much debate as to whether or not petroleum platforms should be toppled and left in the GOM as 

artificial reefs or removed completely. As this study has shown, red snapper are attracted to 

platforms and probably derive benefits from them; therefore, removal may hinder the recovery 

and rebuilding of this heavily exploited population. On the other hand it is important to 

remember that the catchability of red snapper at platforms may be higher than at natural hardbottom because of the ease with which fishermen may locate platforms; an increase in 

catchability would likely lead to an undesirable increase in fishing mortality. If catchability is 
414 

increased, platforms may not be as beneficial to the red snapper population as is currently 

thought by many. The effect of platform removal on the fisheries must also be considered: the 

decrease in easily available fishing opportunities could cause economic stress in the commercial 

and recreational fishing industries, both of which are very important to the states bordering the 

GOM. 

Megan B. Peabody Westmeyer holds a B.S. degree from the University of South Carolina (2001) 

and an M.S. degree from Louisiana State University (2004). Her diverse background includes 

research on the climatological records preserved in the sediments of Lake Baikal, Russia, on the 

benthic eco-toxicology of pesticides on estuarine amphipods, on sea turtle nesting in North 

Carolina, and on the life history of important marine fishes. Megan is currently employed as the 

Program Coordinator for the Sustainable Seafood Education Project at the South Carolina 

Aquarium in Charleston (POB 130001, Charleston, SC 29413-9001). 

Charles A. Wilson, III, is a Professor both in the Department of Oceanography and Coastal 

Sciences (DOCS) and in the Coastal Fisheries Institute, School of the Coast and Environment, 

Louisiana State University. During his twenty-year tenure at LSU, Dr. Wilson has also served as 

Chair of DOCS (1995–2002), Director of the Coastal Ecology Institute (2001–2002), and Vice 

Provost in the Office of Academic Affairs (2003–present). His diverse and rigorous research 

program on the biota of the northern Gulf of Mexico has resulted in over 70 publications in the 

primary literature and scores of technical reports. 
415 

THE BUCCANEER GAS AND OIL FIELD “RIGS TO REEFS” 1977–2004 

Benny J. Gallaway, Larry R. Martin, John G. Cole, and Robert G. Fechhelm, 

LGL Ecological Research Associates, Inc. 

Charles A. Wilson, Yvonne Allen, and Mark Miller, Louisiana State University 

Introduction 

The project “Platform Debris Fields: Extent, Composition and Biological Utilization” is being 

jointly funded by the Minerals Management Service (MMS) and the Texas Parks and Wildlife 

Department (TPWD). The study is being conducted by Louisiana State University (LSU) and 

LGL Ecological Research Associates, Inc. (LGL). Our objectives have been to conduct highresolution side-scan sonar surveys of debris field associated with two sites where obsolete oil and 

gas platforms installed in the mid-1960s have been topped and left in place as artificial reefs. 

These surveys are being supplemented with ROV and hydroacoustic surveys to determine fish 

and megafaunal abundance associated with the debris fields. The sites are unusual in that 

extensive historical environmental and ecological investigations were conducted at these 

platforms in the late 1970s (Middleditch 1981). 

Study Area and Methods 

The structures in question (Platforms GA288 and GA296) are located about 27 nmi south of 

Galveston, Texas in 70 ft of water. Each site contained a 12-pile structure or production platform 

that was once attached by a catwalk to a four-pile structure that served as a quarter’s platform. 

The structures were reefed using mechanical cutting methods. The decks were removed and 

transported to shore. The structures were cut at a depth of about 15 m (50 ft), and the top 

portions were cut into smaller sections that were placed within and around the base sections left 

in place. Each reef site is marked by a lighted buoy maintained by the TPWD. 

We planned on conducting side-scan sonar, hydroacoustic and ROV surveys of the reef sites in 

the summer/fall period of 2003 and summer of 2004. The first cruise was conducted as planned 

in October 2003. Complete side-scan and hydroacoustic surveys were made at each reef site and 

at a nearby ridge thought to contain relict shell beds, habitat which is attractive to juvenile red 

snapper. ROV surveys began at the shell-ridge and documented that the area was mostly sand 

and shell-hash, not relict shell beds. The site did not have the habitat attributes attractive to 

juvenile red snapper. ROV surveys were not made at the reef sites due to adverse weather 

conditions which then prevailed for an extensive time period. 

We next returned to the sites in August of 2004 and conducted hydroacoustic and synoptic ROV 

surveys at each reef. We plan to revisit the study area in spring or summer of 2005 and conduct 

side-scan, hydroacoustic, and ROV surveys at each artificial reef site. 
416 

Results 

Below we summarize the side-scan sonar results from October 2003, hydroacoustic survey 

results from October 2003 and August 2004 and ROV survey results from August 2004. We also 

describe the fish communities present at the GA288 site in September 2003 based upon TPWD 

diver-surveys conducted by TPWD shortly after the rigs were topped and placed on the bottom. 

Side-Scan Sonar Surveys. We obtained 100% side-scan coverage of the two sites in October 

2003. Two debris fields are present at each site, one at the location of the 12-pile structure, and 

one at the location of the four-pile structure. Riprapp material covered a partially-buried segment 

of old pipeline at a location about 20- to 55-m east of the main debris pile at the GA296 site. 

At GA288, bottom depth was on the order of 23 m, and the highest point of the debris field was 

on the order of 18-m deep. Maximum relief was thus about 5 m. Slightly greater relief was 

observed at GA296 (6 m) where the bottom depth was 22 m and the highest point of the debris 

field was about 16-m deep. At the GA288 site, the main debris field was mostly encompassed 

within a circle having a radius of 100 m whereas the four-pile structure debris field was largely 

contained within a circle having a radius of 50 m. Similarly, the main debris pile at GA296 site 

was contained within a radius of about 83 m, and the debris field at the old quarters platform at 

this site was within a radius of 55 m. Thus, the sites are similar in terms of size and relief. 

Hydroacoustic Surveys 

The hydroacoustic surveys showed that the debris fields comprised “islands” of relief extending 

above a relatively flat plain. “Clouds” of fishes hovered within and above the debris fields. The 

surrounding flat bottoms were virtually devoid of fish. Fish were abundant immediately above 

the reefs, and abundance declined rapidly within a 100-m distance away from the reefs. Fish 

targets were present throughout most of the water column. The population estimates at GA288 

and GA296 in October 2003 were 8,292 fish (95% CI = 5,655 to 10,928) and 7,558 (95% CI = 

5,461 to 9,654) respectively. In August 2004, 4,837 (95% CI = 2,799 to 6,874) fish were 

estimated to have been present at GA288, and 7,352 (95% CI = 5,596 to 9,109) were estimated 

to have been present at GA296. 

ROV and Diver Surveys 

We did not obtain ROV surveys at the study area reef sites in October 2003, but the small debris 

pile at the GA288 site was surveyed by TPWD divers in September 2003 shortly after the 

structures had been reefed. Five TPWD divers performed roving surveys at site GA-288. They 

initially dove to the bottom and worked their way to the surface recording the relative abundance 

of fishes observed. The abundance categories ranged from sightings of single fish of a species to 

an observation of groups of a species numbering from a few (2-10 fish), to many (11-100 fish) to 

abundant (>100 fish of a species). “Abundant” fishes included only the tomtate Haemulon 

aurolineatum whereas species represented in the “many” category included the sheepshead 

Archosargus probatocephalus, Atlantic spadefish Chaetodipterus faber, grey triggerfish Balistes 

capriscus, red snapper Lutjanus campechanus, and grey snapper Lutjanus griseus. Species in the 

“single” or “few” categories included the ling Rachycentron canadum, Almaco jack Seriola 

rivoliana, greater hammerhead shark Sphryna mokarran and the blue runner Caranx crysos. 
417 

The fish population at GA288 in August 2004 was dominated by red snapper (70%), sheepshead 

(12%), and grey triggerfish (6%). Tomtate and Atlantic spadefish, which had been highly 

abundant in September 2003, were scarce at this site in August 2004. This apparent decline 

corresponds to an overall population decline that was observed at GA288 between October 2003 

and August 2004. 

References 

Middleditch, B.S. ed. 1981. Environmental effects of offshore oil production, the Buccaneer Gas 

and Oil Field study. Marine Science 14. Plenum Press, New York. 

Benny J. Gallaway, Ph.D. is President of LGL Ecological Research Associates, Inc. His 

experience in the Gulf of Mexico spans more than three decades. Research interests have 

included artificial and natural reef ecology, continental shelf and slope ecology, and fisheries 

management. Dr. Gallaway has over 50 publications in the peer-reviewed literature and is author 

of hundreds of research reports. 

Larry R. Martin is a marine biologist and diving scientist with LGL Ecological Research 

Associates, Inc. His Gulf of Mexico experience includes ecosystem analysis in relation to 

petroleum production activities, coral reef monitoring, ecological studies of the continental slope, 

and assessing effects of commercial shrimping on endangered and other key species taken as 

bycatch in that fishery. 

John G. Cole has been a Vice-President and Data Analyst at LGL Ecological Research 

Associates, Inc. for the past 25 years. His research interests center around database design, and 

data integrity, review, and analysis. In recent years his work has been almost exclusively in the 

Gulf of Mexico, where he has consolidated data from various sources to create georeferenced 

data sets for the data from the LGL-led Gulf of Mexico continental slope study conducted in the 

1980s, turtle interactions with the shrimping fleet, electronic logbook records of shrimp fleet 

activity and historical shrimp fleet observer data. 

Robert G. Fechhelm, Ph.D. is a fisheries biologist/ecologist with LGL Ecological Research 

Associates, Inc. He has 24 years of experience conducting environmental research in the Gulf of 

Mexico. Research interests have included continental slope and shelf ecology, the effects of 

synthetic drilling fluid disposal, sea turtle ecology, fisheries, and bycatch issues. Dr. Fechhelm 

has authored 67 reports and technical documents for clients in industry, and state and federal 

agencies, and has published 25 papers in peer-reviewed scientific journals. 

Charles A. Wilson, III, is a Professor both in the Department of Oceanography and Coastal 

Sciences (DOCS) and in the Coastal Fisheries Institute, School of the Coast and Environment, 

Louisiana State University (LSU). During his twenty-year tenure at LSU, Dr. Wilson has also 

served as Chair of DOCS (1995–2002), Director of the Coastal Ecology Institute (2001–2002), 

and Vice-Provost in the Office of Academic Affairs (2003–present). His diverse and rigorous 
418 

research program on the biota of the northern Gulf of Mexico has resulted in over 70 

publications in the primary literature and scores of technical reports. 

Yvonne Allen is a research associate in the Coastal Fisheries Institute at Louisiana State 

University. Ms. Allen received her M.S. degree in water resource management from the 

University of Wisconsin-Madison in 1990. Since then, she has worked on a variety of projects 

including large-scale food web manipulation, thermal habitat in large lakes, and invasive species 

in the Mississippi River. 

Mark Miller is a research specialist in the Coastal Fisheries Institute at Louisiana State 

University. In his nine years there he has acquired extensive dive experience, ROV operations, 

and sonar experience. Mr. Miller also has had eight years’ experience studying fish populations 

associated with oil and gas platforms. 
419 

POTENTIAL SPATIAL AND TEMPORAL VULNERABILITY OF PELAGIC FISH 

ASSEMBLAGES IN THE GULF OF MEXICO TO SURFACE OIL SPILLS 

ASSOCIATED WITH DEEPWATER PETROLEUM DEVELOPMENT 

Mark C. Benfield and Richard F. Shaw, 

Department of Oceanography and Coastal Sciences, Coastal Fisheries Institute, 

Louisiana State University, School of the Coast and Environment 

Introduction 

As petroleum exploration expands into and beyond the waters of the OCS, the potential exists, 

via accidental spills, to adversely impact pelagic recreational and commercial fisheries. Surface 

petroleum spills in pelagic waters of the OCS will primarily impact those species of fishes and 

crustaceans that inhabit the epipelagic zone of the open ocean. Members of this group include 

several species that command a high monetary and socio-economic value, as well as ecologically 

important or indicator species. Spills in the surface waters are also likely to impact floating 

Sargassum communities, which contain a diverse and often unique faunal assemblage of fishes 

and invertebrates and which also serve as important nursery habitats for many fishes. 

Relatively little is known about the susceptibility of pelagic fishes from the Gulf of Mexico OCS 

to petrochemical spills. The magnitude of any impact will depend upon the spatial and temporal 

scale of the incident as well as the chemical properties of the spilled material. The spatial scale 

(location, depth and extent) of the spill combined with the temporal scale (timing and duration) 

will combine to determine the species and life history stages that are likely to be present in the 

impacted area. Unfortunately, information on the spatial and temporal distributions of pelagic 

fish stocks in the OCS is not readily available and is generally scattered throughout the peerreviewed and non-peer-reviewed technical literature and databases. 

This study was undertaken to synthesize what is known about the spatio-temporal distribution 

patterns of selected pelagic fish species. We have attempted to provide an estimate of what life 

history stages of these target species are likely to be present within the OCS waters on a seasonal 

(monthly) basis. 

Methods 

We delineated a study region of the north central Gulf of Mexico (GOM) that includes waters 

above the 200–2,000 m isobaths south to 26 oN latitude. The study area was divided into four 

zones: western zone (96.4 oW–92.0 oW, 26.0 oN–28.0 oN), central zone (92.0 oW–88.0 oW, 26 

oN–28 oN), eastern zone (88 oW–84.3 oW, 26.0 oN–28.0 oN), and a triangular northern zone with 

a base from 90.7 oW-84.3 oW at 28 oN, and an apex at 87 oW, 30 oN (Figure 1G.4). The western, 

central and eastern zones correspond broadly to the MMS western, central and eastern planning 

areas. Species selected for study were: bluefin tuna (Thunnus thynnus), yellowfin tuna (T. 

albacares), blackfin tuna (T. atlanticus), blue marlin (Makaira nigricans), white marlin 

(Tetrapturus albidus), wahoo (Acanthocybium solanderi), dolphinfish (Coryphaena hippurus), 

two species of flyingfishes: Cypselurus melanurus and C. furcatus, blue runner (Caranx crysos), 
420 

Ocean sunfish (Mola mola), and Sargassum community fauna: sargassumfish (Histrio histrio), 

planehead filefish (Monocanthus hispidus), tripletails (Lobotes surinamensis). 

Figure 1G.4. Predicted distributions of adult yellowfin tuna in the study area from January through 

December. The presence of individuals in each grid cell is coded as confirmed (), reasonable 

inference () or unreported ().
421 

In addition to a comprehensive literature search of the available peer-reviewed literature, gray 

literature, and Internet websites, this report drew heavily on two datasets: the National Marine 

Fisheries Service (NMFS) long-line database and the Southeast Area Monitoring and 

Assessment Program (SEAMAP) ichthyoplankton surveys. Reported observations were sorted 

by month into a 10’ longitude by 10’ latitude grid (approximately 100 nautical miles2

 or 343 

km2

). The potential presence of a particular stage in any of the cells within the grid was ranked 

according to three categories: confirmed, reasonable inference, and unreported. Confirmed 

presence was assigned when a physical sample of the relevant stage of a particular taxon had 

been reported as being present within a cell. Reasonable inference was assigned to any cells 

within which there was no confirmed presence, providing the cells were located within a radius 

of two cell distances (for adults) or one cell distance (for larvae/juveniles) of a cell with a 

confirmed presence. Reasonable inference was also assigned to any cells that were bounded by 

four or more cells also designated with the reasonable inference category. Finally, any regions 

within the study area that were completely surrounded by cells designated as confirmed or 

reasonable inference were also assigned reasonable inference. Finally, all cells that did not fall 

into the confirmed or reasonable were assigned an unreported category. 

For each species, we have summarized the available distributional data on a monthly basis and 

have attempted to predict the distributions of larvae, adults, and juveniles (when possible) within 

the study region. Companion software in the form of Microsoft Excel spreadsheets allow the user 

to query the data to obtain probable distributions within specific locations defined by their 

longitude and latitude. 

Results and Discussion 

Distributional data are predicted for each month for adults and larvae/juveniles where possible. 

An example of these results is provided for yellowfin tuna. Comparable predictions are provided 

in the report but are not summarized here for the other taxa in the study. 

Adult yellowfin tuna are likely present throughout the majority of the study area during all 

months of the year (Figure 1G.4). During winter, the majority of confirmed landings were in the 

western and western halves of the central and northern zones. By April, yellowfin expand their 

distribution in the northern zone towards the northeast, and this movement pattern continues 

through May and June. During April there is also an apparent movement into waters deeper than 

200 m in the southeastern edge of the northern zone and the northeastern edge of the eastern 

zone. In summer, adults are present throughout most of the three zones, and during fall and early 

winter the epicenter of confirmed records shifts back to the western and central zones. The 

SEAMAP dataset contains extremely limited numbers of confirmed yellowfin larvae that were 

only present during May, June, and September. Predictions of larval distributions based on this 

dataset are restricted to these three months and do not provide much utility for estimating larval 

distributions. Limited data suggest that most spawning occurs near the Mississippi River plume 

frontal region with larval and juvenile yellowfin tuna present seaward and downstream 

(southwest) of the plume along the 200 m (Figure 1G.5). In the absence of juvenile distributional 

data, it is likely that their distributions overlap with the larvae. 
422 

Figure 1G.5. Predicted distributions of larval yellowfin tuna in the study area during May, June, and 

September. These were the only months in which confirmed larvae were present. The presence 

of individuals in each grid cell is coded as confirmed (), reasonable inference () or 

unreported ().

Data for each taxon and stage is provided in a Microsoft Excel spreadsheet with separate 

worksheets for each taxon and life history state. A series of files are provided for each month of 

the year. There is one set for adults and a second set for larvae/juveniles. Within each file there 

are worksheets for each species containing latitude and longitude coordinates, and a matrix of 

cells containing distributional data are encoded with values of 2 (confirmed), 1 (reasonable 

inference), or 0 (unreported). The cells corresponding to the study area are colored yellow. 

Within each monthly Excel spreadsheet for either larvae/juveniles or adults there is a worksheet 

called Distribution Calculator that provides a means of querying the data. Individual worksheets 

for each taxon are accessible via tabs at the bottom of the spreadsheet page. The Distribution 

Calculator worksheet allows the user to enter the western and southern coordinates of the 

location to be queried. The calculator will query each taxon for the month in question and return 

the predicted distribution of adults or larvae/juveniles of each taxon at the location of interest. 

It is clear that for many taxa, substantial gaps exist in our understanding of their spatial and 

temporal distributions. Prediction of the distributions of larvae and juveniles is particularly 

problematic due to the limited amount of spatially explicit data available for these life history 

stages. Estimation of vertical distributions was also problematic for most stages and taxa. This 

study represents a useful first step for predicting the potential presence of target taxa and for 

identifying knowledge gaps to guide future studies. 
423 

Acknowledgments 

The authors are extremely grateful to Elizabeth Burroughs-Loden for her diligent pursuit of the 

literature and data relevant to this project. We appreciate the assistance of Mr. Mark McDuff, 

National Marine Fisheries Service (NMFS) for providing access to the SEAMAP dataset and Dr. 

Jean Cramer, NMFS for providing access to the longline database for the GOM. Dr. Richard 

Pitman, NMFS generously provided access to his flyingfish data. Ms. Kathy Lang, NMFS 

provided data on distributions of larval yellowfin tuna. We thank the NMFS Library Staff in 

Miami for their assistance with our literature searches. 

Mark C. Benfield is an Associate Professor in the Department of Oceanography and Coastal 

Sciences and the Coastal Fisheries Institute at Louisiana State University. He received his B.Sc. 

from the University of Toronto, an M.Sc. from the University of Natal, and a Ph.D. from Texas 

A&M University. He was a Postdoctoral Investigator in the Department of Biology at the Woods 

Hole Oceanographic Institution where he currently holds an appointment as a Guest Investigator. 

His research focuses on zooplankton ecology, feeding ecology of zooplanktivorous fishes, and 

the integration of optical, acoustical and direct sampling techniques to understand the ecology of 

zooplankton. 

Richard F. Shaw is a Professor in the Department of Oceanography and Coastal Sciences and the 

Coastal Fisheries Institute at Louisiana State University. He received his B.A. from Merrimack 

College at Andover and his Ph.D. from the University of Maine at Orono. His research examines 

the early life histories of marine and estuarine fishes, larval transport, and the ecology of fishes 

in relation to natural and artificial reefs. 
424 

DETERMINATION OF TRACE ELEMENTS IN RED SNAPPER, LUTJANUS 

CAMPECHANUS, OTOLITHS USING ICPMS TO EVALUATE THEIR AFFINITY FOR 

OIL AND GAS PLATFORMS 

Lauren Mione, James H. Cowan, Jr., and Richard F. Shaw, 

Coastal Fisheries Institute, Louisiana State University 

Robert Gauldie and Eric DeCarlo, Department of Oceanography, 

University of Hawaii at Manoa 

The Magnuson-Stevens Fishery Conservation and Management Act, the 1996 revision and 

reauthorization of the 1976 Public Law 94-265 (Act), requires that fishery management plans 

include an identification and description of essential fish habitat (EFH), adverse impacts on EFH 

(including the effects from fishing), and actions to conserve and enhance EFH (Gallaway et al. 

1999). One of the most pressing federal fisheries management concerns in the Gulf of Mexico 

(GOM) region is the overfished status of red snapper Lutjanus campechanus (Schmitten, 1999). 

Red snapper support the most economically valuable finfish fishery in the GOM and are among 

the most targeted fishes by commercial and recreational fishers (Goodyear 1995). It has been 

demonstrated that as red snapper mature they show strong preferences for natural and artificial 

habitat with vertical relief. Examples of this habitat include coral, rocks, banks, outcrops, and 

manmade submerged objects such as oil and gas platforms and artificial reefs (Workman and 

Foster 1994). It is these areas that are considered by many to constitute red snapper EFH. 

In the waters of the northern GOM there are over 4,000 functioning oil and gas platforms 

(Stanley and Wilson 1998). Due to the noted presence of red snapper around oil and gas 

platforms, recreational and commercial fishing efforts for red snapper have continually been 

concentrated in those areas. Artificial reefs, such as oil and gas platforms, may be useful tools for 

fishery managers if they increase fisheries production, but many researchers question whether or 

not they are a positive influence on reef stock dynamics. There have been doubts about whether 

or not they produce or attract fish and the resolution to this question is essential to the 

management of reef fish stocks. If they indeed constitute EFH for red snapper, then they can be 

considered as viable management tools. If they are simply attracting fish to the area, they may be 

merely promoting overfishing. 

Existing oil and gas platform operations and their prior history of drilling operations are likely to 

produce trace amounts of residues of Lead (Pb), Barium (Ba), and Lanthanum (La) whose 

isotope ratio signatures will differ from those typical of the GOM seafloor. This can be used as a 

harmless ‘tag’ in the otoliths of the juvenile fish that have spent time in close association with oil 

and gas platforms. Fish otoliths have traditionally been used as a hard part to age fish, but more 

recent research indicates that they may also serve as ideal natural markers of individual fish or 

fish populations (Campana et al. 1994) The main objective of this study was to test whether 

association with oil and gas platforms impart a detectable “trace element fingerprint” in the 

otoliths of juvenile red snapper using Inductively Coupled Plasma-Mass Spectrometry (ICPMS). 
425 

Methods 

A total of 115 red snapper were collected by hook and line on recreational charter boats from the 

fall of 2002 to the spring of 2004. Of those 115 red snapper, 35 were captured off coastal 

Louisiana on oil and gas platforms in the South Timbalier and Grand Isle Lease Blocks; 35 were 

captured from artificial reefs off Louisiana in the same location; and 45 were captured on 

artificial reefs off coastal Alabama in the Hugh Swingle Permit Area south of Mobile Bay. 

Multiple attempts were made to collect red snapper on oil and gas platforms off of coastal 

Alabama, but no fish could be caught. Upon collection measurements of fork length, total length, 

dorsoventral height, and sex were taken. Once specimens were returned to the dock, the heads 

were removed and returned to LSU. Otoliths were then removed in a clean laboratory in a 

HEPA-filtered air module, packaged, and sent to the University of Hawaii (UH) for ICPMS 

analysis. At UH the otoliths were dissolved in quartz-distilled nitric acid (HNO3) using an MDS 

2100 Microwave Digestion System. Once the otolith samples were dissolved they were 

processed in a VG PlasmaQuad mass spectrometer. A suit of 17 trace elements were analyzed in 

the otoliths. These consisted of Vanadium 51, Nickel 58, Cobalt 59, Nickel 60, Nickel 62, Zinc 

64, Copper 65, Zinc 66, Silver 107, Silver 109, Cadmium 110, Cadmium 111, Cadmium 114, 

Lead 206, Lead 207, Lead 208 and Uranium 238. Raw data from the mass spectrometer was then 

standardized for use. 

Currently, only the two red snapper samples collected from coastal Louisiana have been 

processed using ICPMS. Therefore, those 61 otolith samples were the only ones used in this 

analysis. Of those 61 observations, 30 were otoliths from oil and gas platforms and 31 were 

otoliths from artificial reefs. A number of statistical methods were used to analyze the 

standardized data. First, a simple linear regression was used to determine the relationship 

between otolith weight and fish weight. A multivariate analysis of variance (MANOVA) was 

used to determine the equality of the means of each element between the two different sites (site 

1 = oil and gas platforms, site 2 = artificial reefs). A discriminant function analysis was 

performed to determine if the observations could be allocated to one or another set of classes 

(site 1 and site 2) in an optimal way with the least amount of misclassifications. A stepwise 

discriminant function was performed to determine the most influential elements in discriminating 

between oil and gas platforms and artificial reefs off of coastal Louisiana. 

Results 

Results from the simple linear regression showed a positive linear relationship between otolith 

weight and fish weight, which was to be expected. The regression had a high r-square value of 

0.9507. When comparing the equality of the means of each element for each of the two sites it 

was determined that eight of the seventeen elements had significantly different means between 

oil and gas platforms and artificial reefs (Figure 1G.6). Zinc 64 (p=0.0061) and Zinc 66 

(p=0.0006) were significantly higher on artificial reefs that on oil and gas platforms off of coastal 

Louisiana. Vanadium 51 (p<0.0001), Silver 107 (p=0.0005), Silver 109 (p<0.0001), Lead 206 

(p=0.0086), Lead 207 (p=0.0108), and Lead 208 (p=0.0109) were all found to be significantly 

higher on oil and gas platforms off of coastal Louisiana. 
426 

Means for Louisiana Platforms and Reefs

0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

V51

Ni58

Co59

Ni60Ni62

Zn64

Cu65

Zn66

Ag107Ag109

Cd110Cd111Cd114

Pb206Pb207Pb208

U238

Elements

Parts Per Billion

Oil and Gas Platforms Artificial Reefs

Figure 1G.6. Comparison of the mean differences of the 17 elements between oil and gas platforms and 

artificial reefs in Louisiana. 

Discriminant function analysis was successful in differentiating between our two sites using all 

17 elements that were analyzed with otolith microchemistry. Two approaches were used in the 

discriminant function analysis to estimate the misclassification rate of the 61 observations into 

site 1 (oil and gas platforms) and site 2 (artificial reefs). The first was the resubstitution 

approach. It correctly classified 29 of the 30 observations from site 1 but misclassified one 

observation into site 2. This approach also correctly classified all 31 observations from site 2. 

Therefore, this approach only had a misclassification rate of 1.67%. However, the resubstitution 

approach is known in general to be overly optimistic and the second approach used, the crossvalidation approach, gives a more realistic misclassification rate. The cross-validation approach 

correctly classified 25 of the 30 observations from site 1 and misclassified five of them into site 

2. It correctly classified 27 of the 31 observations form site 2 and misclassified 4 observations 

into site1. This approach has a more realistic misclassification rate of 14.78%. A stepwise 

discriminant function was then performed on the 61 observations, and it identified the most 

influential elements used to discriminate between oil and gas platforms and artificial reefs in 

Louisiana. The elements identified as the most important in the analysis were Silver 109, Zinc 

66, Vanadium 51, Uranium 238, Lead 206 and Nickel 58. Using only these six elements to rerun 

the original discriminant analysis yielded a cross-validation approach misclassification rate of 

only 5%, reduced from the original estimate of 14.78%. 
427 

References 

Campana, S.E., A.J. Fowler, and C.M. Jones. 1994. Otolith elemental fingerprinting for stock 

identification of Atlantic cod (Gadus morhua) using laser ablation ICPMS. Canadian 

Journal of Fisheries and Aquatic Sciences 51:1942–1950. 

Gallaway, B.J., J.G. Cole, R. Meyer, and J.P. Roscigno. 1999. Delineation of essential habitat for 

juvenile red snapper in the northwestern Gulf of Mexico. Transactions of the American 

Fisheries Society 128:713–726. 

Goodyear, C.P. 1995. Red snapper in U. S. waters of the Gulf of Mexico. National Marine 

Fisheries Service, Southeast Fisheries Science Center, Miami Laboratory, Miami MIA95/96-05. 

Schmitten, R.A. 1999. Essential fish habitat: Opportunities and challenges for the next 

millennium. American Fisheries Society Symposium 22:3–10. 

Stanley, D.R. and C.A. Wilson. 1998. Spatial variation in fish density at three petroleum 

platforms as measured with Dual-Beam hydroacoustics. Gulf of Mexico Science 16:73–

82. 

Workman, I.K. and D.G. Foster. 1994. Occurrence and behavior of juvenile red snapper, 

Lutjanus campechanus, on commercial shrimp fishing grounds in the northeastern Gulf 

of Mexico. Marine Fisheries Review 56:9–11. 

Lauren Mione is a Master’s degree student in the Department of Oceanography and Coastal 

Sciences and the Coastal Fisheries Institute at Louisiana State University. Her major advisor is 

Dr. James Cowan, Jr. She received her B.Sc. (marine biology) from Auburn University in 2001. 

James H. Cowan, Jr. is a Professor in the Department of Oceanography and Coastal Sciences and 

the Coastal Fisheries Institute at the Louisiana State University. He received B.Sc. (biology) and 

M.Sc. (biological oceanography) degrees from Old Dominion University, and M.Sc. 

(experimental statistics) and Ph.D. (marine sciences) degrees from the Louisiana State 

University. He has almost 20 years of experience conducting fisheries research in marine and 

estuarine ecosystems. 

Richard Shaw is the Director of the Coastal Fisheries Institute and a Professor in the Department 

of Oceanography and Coastal Sciences at LSU. He has worked with ichthyoplankton since 1973 

and received his Ph.D. in biological oceanography from the University of Maine in Orono in 

1981. 

Dr. R W Gauldie in 1977 published a paper looking at otolith chemistry as a potential stock 

marker. Some 100 publications later, he suspects that the core problem of otolith chemistry is 
428 

that all otoliths have the same chemistry in differing proportions, related to the physiology of 

individual fish and only in unusual circumstance related to the environment. The rig-recruit 

situation may well be the unusual circumstance in which otolith chemistry is sufficiently 

correlated to environment to overcome the background physiological noise in the chemistry of 

the otolith. 

Dr. Eric Heinen De Carlo is a Research Professor in the Department of Oceanography 

at the University of Hawaii at Manoa. He is a faculty affiliate with the Honolulu District U.S. 

Geological Survey in Hawaii. He received a Ph.D. in chemistry in 1982 from the University of 

Hawaii at Manoa. 
429 

DISTRIBUTION OF CORALS COLONIZING OIL AND GAS PLATFORMS IN THE 

NORTHWESTERN GULF OF MEXICO: A PRELIMINARY REPORT 

Paul W. Sammarco and Amy D. Atchison, Louisiana Universities Marine 

Consortium (LUMCON) and Department of Oceanography and Coastal Science, 

Louisiana State University 

Gregory S. Boland, Environmental Section, Minerals Management Service 

Abstract 

The Flower Garden Banks (FGB), Gulf of Mexico (GOM), are highly isolated corals reefs. The 

surrounding continental shelf possesses ~3,800 oil/gas platforms. Questions: To what degree are 

corals expanding their geographic range through the Gulf via these platforms, and what are their 

genetic affinities to neighboring systems. Thirteen platforms were surveyed initially in the 

vicinity of the FGB. Coral settlement racks were deployed to determine levels of recruitment. 

Tissue samples of dominant corals were collected for genetic analysis and analyzed via AFLP. 

Recruitment on the platforms was compared with that from similar racks implanted on the FGB. 

Two cross-shelf transects were also taken off Port Aransas, Texas and Lake Sabine, Louisiana, to 

assess corals on platforms. Eleven coral species were found—nine hermatypic, and two 

ahermatypic—the most abundant being Madracis decactis and Diploria strigosa, and Tubastraea 

coccinea, respectively. Most species were characteristic of later sere communities; Agaricia and 

Porites spp. were notably rare or absent, respectively. There was no relationship between coral 

abundance and distance from the FGB. Abundance and diversity were correlated with platform 

age. Coral recruitment was high on the FGB but rare on the platforms. Spat species composition 

was normal on the FGB (Agaricia and Porites spp.) but atypical on platforms near the FGB, 

characterized by Tubastraea coccinea and Madracis decactis. The western limit of scleractinian 

corals on platforms occurred ~60 km SE of Port Aransas, Texas, at the shelf edge, but 

ahermatypic corals were abundant throughout this region. Ahermatypic corals abounded starting 

~120 km offshore, with hermatypes occurring 180–210 km, near the shelf edge. No corals were 

found between 60 and 120 km offshore. Populations of D. strigosa on the FGB and platforms 

were highly self-contained, with minimum genetic connectivity. M. decactis populations were 

more genetically homogeneous. Contrary to current larval dispersal theory, this brooder was 

highly effective at dispersing to neighboring habitats; the broadcaster was not. 

Introduction 

Thirty-eight hundred oil and gas platforms are currently deployed in the northern GOM (Knott 

1995; Dauterive 2000). They provide hard substratum which extends through the upper euphotic 

zone, where hard substratum has been rare in recent geological time (Curray 1965; Blum et al. 

2001). The Flower Garden Banks (FGB) are coral reefs located 110 nm S-SE of Galveston, 

Texas (Rezak et al. 1985). Platforms surrounding these banks have recently been shown to 

possess scleractinian corals and other reef organisms (Bright et al. 1991; Adams 1996; Boland 

2002; Sammarco and Atchison 2003; Sammarco et al. 2003, 2004; K. Deslarzes, pers. comm.). 

Here, we attempt to 1) determine the degree to which corals have colonized these platforms; 2) 

determine levels of coral settlement on the platforms in comparison with those on the FGB; 3) 
430 

determine how these coral community variables relate to distance from the FGB, platform age, 

and depth; 4) determine their genetic affinities between the platforms, and between platforms and 

the FGB; and 5) determine the degree of coral colonization on platforms in the western GOM. 

Materials and Methods 

Coral distribution and abundance data were collected through visual surveys performed by 

SCUBA divers on 13 drilling platforms near the FGB, occurring within an ellipse extending 15 

km W, 45 km E, and 15 km N of the banks. Coral recruitment was studied on the platforms by 

deploying two coral settlement racks (see Sammarco 1991) with terracotta plates (Harriott and 

Banks 1995; Maida et al. 1995) made of galvanized steel on each platform jacket at depths of 11-

16 m. Nine similar racks were deployed on the East-FGB in sets of three, >10 m apart from each 

other, in a circular pattern. Plates were processed with a dissecting microscope. Coral spat were 

identified to genus and species. Information on platform age and area (for standardization 

purposes) was obtained from the platform owners. 

Coral tissue was collected for DNA analysis from adults of the three dominant scleractinian 

corals—Madracis decactis, Diploria strigosa, and Montrastraea cavernosa—on the platforms 

and the FGB. Samples were analyzed for genetic affinity between populations using AFLPs—a 

DNA finger-printing technique recently applied to corals (Sammarco and Brazeau 2001; Barki et 

al. 2003; Brazeau et al., submitted). AMOVA (Excoffier et al. 1992) and AFLPOP (Duchesne 

and Bernatchez 2002) were used to analyze molecular genetics data. 

Results 

Distribution and Abundance 

Twelve coral species were found on the platforms, including nine hermatypes and three 

ahermatypes. The most abundant species were Tubastraea coccinea, Madracis decactis, Diploria 

strigosa, and Montrastraea cavernosa. The others were Colpophyllia natans, Madracis formosa, 

Millepora alcicornis, Oculina diffusa, Phyllangia americana, Porites astreoides, Stephanocoenia 

intersepta, and S. michelinii. Most species were characteristic of later sere communities. 

Agaricia spp. were absent. 

Relationship to Distance from the FGB 

Coral community variables were generally not related to distance from the FGB, including 

density of all corals, Madracis decactis, and D. strigosa, as well as coral species diversity.

Relationship to Platform Age 

Except for D. strigosa density, the above coral community variables were associated with 

platform age, increasing significantly with platform age in both depth categories. 

Depth Distribution 

All corals exhibited a significantly non-uniform depth distribution on the platforms. Total coral 

and D. strigosa density peaked at 10 and 20 m depth. Madracis decactis, however, peaked at >

27 m, and Tubastraea coccinea at 15-18 m. Some species extended down to >36 m. 
431 

Coral Recruitment 

Coral recruitment on the platforms was rare. Only nine spat were found—Tubastraea coccinea

and Madracis decactis. No spat of pioneer species, e.g. Agaricia or Porites spp., were found. 

Genetic Affinitie 

Madracis decactis, a brooder, was widely represented on seven platforms in the vicinity of the 

FGB. AMOVA analysis indicated that there was no significant difference between the 

populations of the two banks. In many cases, there was no significant difference between 

populations on the FGB and the platforms or between the platforms themselves. The geographic 

pattern of non-significant differences was represented in a variety of directions (E, W, and N). 

Diploria strigosa (broadcaster) was only represented on three platforms and Montastraea 

cavernosa (broadcaster) on one; both species were represented on the FGB. AFLP analyses 

demonstrated that the populations were, on the whole, significantly different between the 

platforms and the FGB, and between the platforms themselves. 

Coral Distribution in the western GOM 

Three ahermatypic corals were commonly found SE of Port Aransas, extending to the shelf edge, 

60 km offshore - Oculina verrucosa, Phyllangia americana, and Tubastraea coccinea. The only 

hermatype found there was Madracis decactis—only at the shelf edge, and very few at that. 

Many corals, both ahermatypic and hermatypic, were found off Lake Sabine. The above three 

ahermatypes were abundant starting 120 km offshore, but hermatypes were not evident until 150 

km offshore. No corals were found between 60-120 km offshore. 

Discussion and Conclusions 

The coral species found on the platforms were all Caribbean, representing a subset of those 

occurring on the FGB (Rezak et al. 1985; Gittings 1992; Bright et al. 1984, 1991). The absence 

of common pioneer species was extraordinary when compared to those found on natural reefs. 

Due to the correlation between abundance of Madracis decactis and platform age, this species 

may be considered an indicator of stage of succession; Diploria strigosa, occurring at all stages 

of community development, may not. The presence of corals on the platforms indicates a 

geographic expansion of corals in this region (Sammarco et al. 2004). The lack of the 

relationship between coral abundance, diversity, etc. and distance from the FGB may be 

explained by the random distribution of platform age around those banks. 

The varied depth distribution of these corals on the platforms may be due to several factors. 

Firstly, the preferred depth of larval settlement may vary between species (see Stake and 

Sammarco 2003) and settlement cues may vary with depth (Baird et al. 2003). Secondly, most 

corals occurred at depths <26-m. This is important because, although federal law requires 

platform removal one year after cessation of production, other related joint federal/state 

legislation allows conversion of retired platforms to artificial reefs through the “Rigs-to-Reefs” 

program, including removing the upper portion to 26 m depth and leaving the remainder in place. 

The extraordinarily low levels of coral recruitment on the platforms are unusual for both coral 

recruitment levels and species composition when compared to the FGB (Sammarco et al. in 
432 

progress), Caribbean reefs (Sammarco 1982, 1987), and Indo-Pacific reefs (Sammarco and 

Carleton 1982; Sammarco 1991, 1994, 1996). This anomaly may be partially due to the distance 

of the platforms from the FGB and the resultant effect of diffusion on the larvae after their 

release from that area. A comparison with data derived from the Helix Experiment on the Great 

Barrier Reef demonstrated that even those platforms closest to the FGB were sufficiently distant 

to invoke strong diffusional effects (Sammarco and Andrews 1988, 1989; Okubo 1994). 

AFLP data suggest that Madracis decactis is highly effective at expanding its range and 

colonizing nearby habitats separated by kms to tens of kms, using an “island hopping” strategy 

(Futuyma 1998; Williams et al. 2003). By planulating up to ten times per year (Vermeij et al. 

2003), its larvae may utilize a variety of multi-directional, seasonal currents, facilitating 

dispersal. Larvae from the broadcasting species, on the other hand, utilize a single spawning 

period, single current regime, and propagules that require days for development to settlement 

competency (Harrison and Wallace 1990; Sammarco 1994, 1996). They appear to be less 

effective for short-range dispersal (also see Atchison et al. 2004). 

At a time when coral populations are suffering high levels of mortality on a global scale 

(Sammarco 1996; Pandolfi et al. 2003; Bellwood et al. 2004; McClanahan et al., in press), these 

oil and gas platforms, often considered an environmental liability (Birnie 1978; Menzie 1983; 

Ajao et al. 1996), may have become important environmental assets by providing habitat for 

settlement of corals in the GOM. 

Acknowledgments 

Many thanks to the people and organizations who assisted us in this study: US-DOI-MMS—S. 

Childs, L. Dauterive, T. Dempre, H. Leedy, J. Sinclair; LSU-CMI—L. Rouse; Anadarko 

Petroleum; Apache Oil; Coastal Oil and Gas; Devon Oil; Dominion Exploration and Production; 

El Paso Energy; Forcenergy/Forest Oil; Kerr-McGee Oil and Gas; Merit Energy; Newfield 

Exploration; Noble Energy; Offshore Energy; UNOCAL; Samedan Oil; Chevron-Texaco 

Exploration and Production; W&T Offshore; LSU-Oceanography—K. Wheelock, D. Woodall; 

Gulf Diving, Inc.—K. Bush, J. Byron, P. Combs, L. DeWeese, J. Dibble, D. Fanning, K. Foster, 

J. Heiser, Jason, S. Kerr, T. Kilpatrick, R. Widaman; USAF/NASA—Lt. Col. D. Perrenod; 

United Space Alliance—A. Knight; LUMCON—A. Barker, J. Collins, W. Hebert, C. Luke, S. 

Parrott, C. Salmonsen; GB-Undersea, Inc.—G. Bunch; Texas A&M at Galveston—J. 

Culbertson; Aquarium of the Americas—A. Sebastian; SUNO—D. Hill-House; C. Gentry, D. 

Marcel. Thanks to J. Benzie for the suggestion to use AFLPs on corals. We especially thank the 

U.S. Department of the Interior, Minerals Management Service, the Louisiana State University 

Coastal Marine Institute, and LUMCON for their support of this project through MMS Contract 

No. 1435-01-99-CA-30951. 

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Marine Larval Dispersal, American Geophysical Union, Washington, DC. Pp. 35–72. 

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Dr. Paul W. Sammarco is a professor at the Louisiana Universities Marine Consortium 

(LUMCON) and also an adjunct professor in the Department of Oceanography and Coastal 

Sciences at Louisiana State University. His background is in ecology and evolution, and he has 

been working in the field of coral reef science for many years. His research interests are 

interdisciplinary and include the interface of ecology (grazing, larval dispersal and recruitment 

processes, etc.) with physics (physical oceanography), chemistry (chemical ecology and natural 

products chemistry), geology (bioerosion, stable isotope geochemistry), and mathematics 

(modeling of competition in coral populations). He also has interests in environmental policy and 

science administration. 
437 

Amy Atchison is an M.Sc. student in the Department of Oceanography and Coastal Sciences at 

Louisiana State University and is working with Dr. Paul W. Sammarco at LUMCON. Her 

interests are in the areas of molecular genetics as applied to the population level; larval dispersal 

and recruitment processes, particularly in corals; and the impact of oil and gas platforms on coral 

populations in the Gulf of Mexico. 

Gregory S. Boland is a biological oceanographer with the Department of Interior’s Minerals 

Management Service (MMS) in New Orleans, Louisiana. His areas of interest include deep-sea 

biology, coral reef ecology, artificial reef ecology, and fishery biology. He began his research 

career at Texas A&M University in 1974 while pursuing his M.S. degree. Prior to his current 

position with MMS, he served as a principal investigator on numerous large Gulf of Mexico 

studies at LGL Ecological Research Associates in Bryan, Texas including offshore platform 

studies, deep-sea biology and coral reef monitoring projects. He also worked ten years with Gil 

Rowe at Texas A&M University’s Department of Oceanography on a variety of benthic ecology 

studies worldwide, including the development and operation of a deep-sea benthic lander. 
438 

GENETIC AFFINITIES BETWEEN CORALS ON THE FLOWER GARDEN BANKS 

VS. OIL/GAS PLATFORMS IN THE NORTHERN GULF OF MEXICO: 

IMPLICATIONS FOR DISPERSAL 

Amy D. Atchison and Paul W. Sammarco, Department of Oceanography and 

Coastal Science, Louisiana State University and 

Louisiana Universities Marine Consortium (LUMCON) 

Daniel A. Brazeau, Pharmaceutical Genetics Laboratory, University of Buffalo 

Introduction 

The introduction of oil and gas platforms into the Gulf of Mexico (GOM) has provided 

substratum for colonization of a variety of marine organisms (Shinn 1973; Driessen 1989). 

Platforms extend through the euphotic zone, providing hard substrate in open water (Shinn 1973, 

1974), that would otherwise be unavailable to sessile, epibenthic organisms, allowing them to 

expand their normal range of distribution. Several coral species (Diploria sp., Porites astreoides, 

Madracis decactis, etc.) have been found on GOM platforms (Bright et al. 1991; Sammarco and 

Atchison, 2004; Sammarco et al., 2003, 2004). 

The Flower Garden Banks (FGB) are coral reefs that have developed on the surface of salt 

diapers. The banks are located in the NW GOM, ~110 miles SE of Galveston, Texas, and 

comprise two banks: the East and West Banks (Rezak et al. 1983) possessing 20 coral species 

(Bright et al. 1984; Gittings et al. 1992). Three hermatypic species found there dominate the 

coral community on the platforms surveyed in the vicinity of the FGB (Sammarco et al. (2003, 

2004): Madracis decactis Lyman 1859, Diploria strigosa Dana 1846, and Montastraea 

cavernosa Linnaeus, 1767. 

Madracis decactis, a hermaphroditic brooder (Diekmann et al. 2001; Vermeij et al. 2003), uses 

internal fertilization, and embryos develop within the parent for several weeks before they are 

released (Carlon 1999). Brooders typically planulate monthly, releasing larvae up to ten times a 

year (McGuire 1998). Diploria strigosa and Montastraea cavernosa are broadcast spawners, 

which release eggs and sperm for external fertilization and development. Both of these species 

participate in an annual mass spawning of gametes (Hagman et al. 1998a, b), occurring over 

seven to ten evenings during August and occasionally September (depending on mean SSTs). 

To determine the level of inter-connectedness of corals in this offshore environment, we 

examined the degree of genetic affinity between populations of adult hermatypic corals on the 

FGB and seven platforms surrounding them (numbered here 1–7, W to E), using the above three 

dominant species – Madracis decactis, Diploria strigosa, and Montastraea cavernosa. We used 

AFLPs—a molecular genetic DNA-fingerprinting technique—to accomplish this. 
439 

Materials and Methods 

Sample Collection 

Adult coral tissue samples were collected from the three species from 0–30 m depth. The total 

number of samples collected per species varied between platforms, depending on abundance. 

SCUBA divers collected samples with a hammer and chisel from the edge of each colony. On 

shipboard, tissue samples were preserved in bags containing a high-salt buffer. Samples were 

stored at room temperature in ice chests and returned to the laboratory for DNA analysis. 

Laboratory Procedures 

In the lab, tissue was removed from the colonies with a scalpel and placed into 1.7 ml labeled 

centrifuge tubes. The DNA was isolated and purified using the Wizard® SV Genomic DNA 

Purification System (Promega Corp), following manufacturer’s instructions for animal tissue. 

Pre-processed samples were then capped and stored at -20oC. 

AFLP analysis was performed according to the protocol of Vos et al. (1995). Complete 

procedural details may be found in Brazeau et al. (submitted). Products of the selective PCR 

were separated on a 5% polyacrylamide (sequencing) gel, and the banding patterns were 

analyzed using a Kodak Digital Image analysis software (Eastman Kodak Co. Scientific Imaging 

Systems). 

Statistical Analyses 

Two statistical analyses were used to analyze the banding data: Analysis of Molecular Variance 

(AMOVA, Excoffier et al. 1992), and AFLPOP (Duchesne and Bernatchez 2002). AMOVA 

estimates population differentiation directly from molecular data and tests hypotheses about such 

differentiation. AFLPOP uses AFLP data to calculate log-likelihood values for individuals 

derived from a reference population, based on banding patterns. A minimal log-likelihood 

difference of one was used in these AFLPOP analyses, indicating that the program will only 

allocate individuals to a particular population only if it is ten times more likely to occur or 

belong in that population than in any other. It is a conservative setting and often results in 

individuals not being assigned to any population. 

Results 

AMOVA 

Madracis decactis. Nine populations were analyzed—from Platforms 1–7, and the East and West 

FGB—using a bootstrap analysis of 1000 iterations. Firstly, the two FGBs were found to be 

genetically homogeneous. The M. decactis population from Platform 1 (platform furthest west) 

was significantly different from all others. The population from Platform 2 was significantly 

different from Platforms 1, 3, 5, 6, and 7. The West FGB was genetically homogeneous with all 

populations, except Platform 1. Platform 3 (located between the two banks) was significantly 

different from Platforms 1, 2, 4, and 6. The East FGB and Platform 4 were significantly different 

from Platforms 1, 6, and 7. Platform 5 was significantly different from Platforms 1, 2, and 6. The 

population from Platform 6 was significantly different from all populations, except the West 
440 

FGB. Platform 7 (platform furthest east) was significantly different from all populations, except 

the West FGB and Platforms 3 and 5. 

Diploria strigosa. D. strigosa populations from the East and West FGB as well as Platforms 3, 5, 

and 7 were analyzed here. Again, the two FGBs were found to be genetically homogeneous. 

AMOVA analysis demonstrated that the West FGB population was significantly different from 

those on Platform 3. The population on Platform 3 was highly significantly different from those 

on the West FGB and Platform 5. In addition, Platform 7 was significantly different from 

Platform 5. The East FGB was genetically homogeneous with all other populations. 

Montastraea cavernosa. Three M. cavernosa populations, East and West FGB and Platform 7, 

were analyzed. The two FGBs were highly significantly different from one another. Platform 7 

was found to be homogeneous only with the West FGB. 

AFLPOP 

Madracis decactis. In comparison to Diploria strigosa and Montastraea cavernosa, a higher 

portion of the Madracis decactis colonies were identified as being heterogeneous when 

comparing populations at other sites, indicating high connectivity between sites. The EAST and 

West FGB had two of the lowest percentages of allocation of colonies back to the reef of origin, 

approximately 26% and 32% respectively. Platforms 1 and 6 exhibited the lowest levels of 

genetic affinity between M. decactis populations at their reference site vs. other sites; these 

populations were also shown to be significantly different from all other populations via the 

AMOVA analysis. They also had the lowest percentages of non-allocated individuals 

(individuals who were not assigned to any population), approximately 6% and 3% respectively. 

The populations on Platforms 3 and 4 had approximately 38% of the colonies allocated back to 

their respective reference populations, with 59% of the colonies not allocated to any population. 

Diploria strigosa. By contrast, AFLPOP analysis allocated most of the Diploria strigosa

colonies considered here back to their reference populations, indicating very low genetic affinity 

with other sites. Populations from the EAST and West FGBs showed the lowest degree of 

genetic affinity with D. strigosa populations at their reference site vs. other sites. D. strigosa at 

the two banks also had the highest percentage of non-allocated colonies, approximately 64%. 

Platforms 5 and 7, well to the east, were unique and had 100% allocation of colonies back to 

their respective reference populations. 

Montastraea cavernosa. The Montastraea cavernosa had the highest percentages of colonies 

allocated back to the reference population when analyzed via AFLPOP. Both FG banks had a 

much higher rate of self-allocation than the other two species considered here. The population at 

Platform 12 had 74% of the colonies allocated to its population of origin with approximately 

25% of the colonies not assigned to any population. 
441 

Discussion and Conclusions 

When examining these three sets of genetic affinity patterns, one must take into account the 

reproductive mode that each uses in nature. Madracis decactis is a brooding species that releases 

fully developed larvae, swimming planulae once a month for up to eight to ten months of the 

year. In contrast, Diploria strigosa and Montastraea cavernosa are broadcast spawners that 

release eggs and sperm for external fertilization once per year via mass spawning during the late 

summer. Current coral larval dispersal theory would predict that the broadcast spawning species 

should be found over a greater geographic range than the brooders. This is because broadcast 

larvae should be able to colonize over long distances more readily than brooders, but this 

hypothesis was not borne out. The genetic signatures of D. strigosa and Montastraea cavernosa

on the FGB and the platforms clearly indicated that populations at those sites were highly selfcontained, with a minimum of genetic connectivity between them. This was indicated by the 

proportion of colonies that were allocated back to the reference population in each case. Only a 

nominal number of colonies were identified as similar at other sites. 

Brooded larvae are expected to have shorter dispersal capabilities than to broadcast larvae due to 

the amount of time the latter larvae are obligated to spend in the water column. Brooders can 

settle within > four hours, while broadcasters must spend a minimum of two to three days in 

embryonic development before they are competent to settle. Our results, however, do not support 

this concept. Here, the genets derived from a brooding species were found to be more widely 

dispersed throughout the ecosystem than those of a broadcasting one—at the meso-scale. The 

broadcast larvae, despite their ability to disperse widely over long distances, do not appear to be 

as effective as the brooded ones in colonizing broadly. 

These results imply that a brooding species of coral is more effective in dispersing its progeny 

over a wider region than a broadcasting species by utilizing the “stepping stone” strategy 

(Kimura and Weiss 1964; MacArthur and Wilson 1967). That is, brooders, on the whole, release 

fewer larvae per planulation period and disperse their larvae over shorter distances in the short 

term. Since neighboring settlement sites are nearby, however, (within kms to tens of kms), they 

have a higher probability of successfully locating suitable substrata within a short period of time. 

Broadcast larvae, however, by the time they are competent to settle, have not only been dispersed 

through advection (currents) but have experienced strong diffusional effects as well (Okubo 

1994; Sammarco 1994). Thus, the density of larvae will have been decreased greatly. 

Based on these results, we conclude that, counter to current theory regarding larval dispersal in 

corals, populations of brooding species such as Madracis decactis are highly effective at 

dispersing their larvae over a wide region where suitable habitats are inter-dispersed at distances 

on the order of kms to tens of kms. They are able to carry this dispersal out via the “stepping 

stone” strategy common in many populations of organisms. Species such as this one appear to be 

more effective at this type of dispersal than broadcasting species, e.g. Diploria strigosa or 

Montastraea cavernosa. Future studies over a larger geographic range, e.g. hundreds to 

thousands of kms, will indicate whether broadcast larvae are more effective at dispersing over 

larger distances. 
442 

We also conclude that AFLPs are an appropriate and powerful tool by which to conduct DNAfingerprinting studies on scleractinian corals and determine degrees of genetic affinity between 

populations within a species. 

Acknowledgments 

Special thanks to G. Boland, G. Bunch, C. Chauffe, J. Conklin, J. Culbertson, L. Dauterive, B. 

DeFelice, T. Dempre, D. Dowdy, T. Empey, S. Kolian, L. Logan, K. de Mutsert, G. Rainey, G. 

Speyrer, and J. Van der Ham for assistance in sample collection, Crew of the M/V Fling (Gulf 

Diving, Inc.), and Anadarko Petroleum, Apache Oil, Coastal Oil and Gas, Devon Oil, Dominion 

Exploration and Production, El Paso Energy, Forcenergy/Forest Oil, Kerr-McGee Oil and Gas, 

Merit Energy, Newfield Exploration, Noble Energy, UNOCAL, Samedan Oil, Chevron-Texaco 

Exploration and Production, and W&T Offshore. Thanks to J. Benzie for the suggestion to use 

AFLPs on corals. This project is funded in part by U.S. Department of Interior, Minerals 

Management Service, Louisiana State University Coastal Marine Institute, Louisiana 

Universities Marine Consortium (LUMCON), and J. Bennett Johnston Science Foundation. 

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Amy Atchison is an M.Sc. student in the Department of Oceanography and Coastal Sciences at 

Louisiana State University and is working with Dr. Paul W. Sammarco at LUMCON. Her 

interests are in the areas of molecular genetics as applied to the population level; larval dispersal 

and recruitment processes, particularly in corals; and the impact of oil and gas platforms on coral 

populations in the Gulf of Mexico. 

Dr. Paul W. Sammarco is a professor at the Louisiana Universities Marine Consortium 

(LUMCON) and also an adjunct professor in the Department of Oceanography and Coastal 

Sciences at Louisiana State University. His background is in ecology and evolution, and he has 

been working in the field of coral reef science for many years. His research interests are 

interdisciplinary and include the interface of ecology (grazing, larval dispersal and recruitment 

processes, etc.) with physics (physical oceanography), chemistry (chemical ecology and natural 

products chemistry), geology (bioerosion, stable isotope geochemistry), and mathematics 

(modeling of competition in coral populations). He also has interests in environmental policy and 

science administration. 

Dr. Daniel A. Brazeau is the Director of the Pharmaceutical Genetics Laboratory, Department of 

Pharmaceutical Sciences, University of Buffalo. His research interests lie in directing a lab that 

provides training and research support for a wide array of molecular genetic techniques to 

address a broad range of questions, including gene expression, bioinformatics, and genotyping in 

a broad array of organisms. His expertise includes the following techniques: Restriction fragment 
445 

length polymorphisms (RFLPs), multilocus fingerprinting (AFLPs, ISSRs), single nucleotide 

polymorphisms (SNPs), microsatellites, mRNA differential display, northern analysis, serial 

analysis of gene expression (SAGE), DNA microarrays, and real-time PCR. 
447 

SESSION 1H 

SENSITIVE BIOLOGICAL HABITATS OF THE GULF OF MEXICO: 

WETLANDS TO CORAL REEFS 

Chair: James Sinclair, Minerals Management Service 

Co-Chair: Herb Leedy, Minerals Management Service 

SEAFLOOR MAPPING IN THE FLOWER GARDEN BANKS REGION, NORTHWESTERN 

GULF OF MEXICO Douglas C. Weaver, Emma L. Hickerson, George P. Schmahl, 

Christine Taylor, Troy Holcombe, and Shepherd Smith ............................................................ 449 

LONG-TERM REEF MONITORING OF THE EAST AND WEST FLOWER GARDEN 

BANKS: NEW SURPRISES William F. Precht, Martha L. Robbart, Richard B. Aronson, 

Ken J. P. Deslarzes, and Les Kaufman ....................................................................................... 456 

MONITORING AT THE FLOWER GARDEN BANKS: METHODOLOGY, EVOLUTION, 

AND FUTURE Richard B. Aronson and William F. Precht..................................................... 459 

FEASIBILITY OF USING REMOTE SENSING TECHNIQUES FOR SHORELINE 

DELINEATION AND COASTAL HABITAT CLASSIFICATION FOR ENVIRONMENTAL 

SENSITIVITY INDEX (ESI) MAPPING Katherine Born-Phillips, Chris Locke, 

Jacqueline Michel, and DeWitt Braud........................................................................................ 462 

PIPELINE AND NAVIGATION CANAL IMPACTS AND MITIGATION EFFECTS 

ON WETLAND HABITATS OF COASTAL WESTERN AND CENTRAL GULF OF 

MEXICO James Johnston, Donald Cahoon, Megan LaPeyre, Philippe Hensel, and 

Thomas McGinnis....................................................................................................................... 466 

THE ASSOCIATION OF SALINITY PATTERN AND LANDSCAPE CONFIGURATION 

WITH OCS OIL AND GAS NAVIGATIONAL CANALS IN COASTAL LOUISIANA 

Gregory D. Steyer, Brian C. Perez, Charles Sasser, Glenn Suir, Elaine Evers, and 

Erick Swenson ............................................................................................................................ 470 

LOUISIANA COASTAL VEGETATIVE TYPE CHARACTERIZATION MAPS 

Greg Linscombe, John Barras, and Steve Hartley ...................................................................... 475 
449 

SEAFLOOR MAPPING IN THE FLOWER GARDEN BANKS REGION, 

NORTHWESTERN GULF OF MEXICO 

Douglas C. Weaver, Emma L. Hickerson, and George P. Schmahl, 

Flower Garden Banks National Marine Sanctuary, 

National Oceanic and Atmospheric Administration 

Christine Taylor, National Marine Sanctuary Program, 

National Oceanic and Atmospheric Administration 

Troy Holcombe, Department of Oceanography, Texas A&M University 

Shepherd Smith, NOAA Ship Thomas Jefferson, NOAA Office of Coast Survey 

The Flower Garden Banks National Marine Sanctuary (FGBNMS), which includes East and 

West Flower Garden Banks (FGB), is located approximately 185 km south of the 

Texas/Louisiana border. East and West FGB harbor the northernmost living coral reefs (17–

50m) on the continental shelf of the United States and a diversity of deepwater (50 to 150m) 

marine habitats. The FGBNMS was designated in 1992 under the jurisdiction of the National 

Oceanic and Atmospheric Administration (NOAA). The FGB were first mapped in the 1930s, 

and have been the subject of geological and biological investigations since the 1950s. During the 

1960s and 1970s, expeditions to the FGB by scuba divers and submersibles, funded by the 

Houston Museum of Natural Science, the Flower Gardens Ocean Research Center, and later by 

the Bureau of Land Management, led to the discovery of many unique features within the 

sanctuary, including remnants of drowned reefs, numerous natural gas seeps, and a modern brine 

lake and overflow canyon at East Flower Garden Bank. 

Mapping efforts at the FGB began in 1937 by the U. S. Coast and Geodetic Survey, using 

leadlines. Contour maps of increasing resolution were produced over the next 60 years using 

single beam echosounders, with topographic detail increasing with decreased line spacing and 

more advanced equipment. During December 1997, The U.S. Geological Survey, the Ocean 

Mapping Group at the University of New Brunswick, and C&C Technologies conducted sea 

trials in the northwestern Gulf of Mexico using a Konsberg Simrad EM300 high-resolution 

multibeam echosounder (MBES). This survey provided the first complete coverage of the 

FGBNMS, including East and West Flower Garden Bank, and Stetson Bank, to water depths of 

150m. New discoveries identified by the resulting high-resolution maps included a deep, 

anticline rim of patch reefs circling Stetson Bank, vast fields of patch reefs surrounding East and 

West FGB, various deepwater mounds associated with the banks, and extensive faulting that 

extended beyond the existing sanctuary boundaries. While the multibeam maps provided new 

insights into habitat distribution at FGBNMS, the area between the banks remained unmapped by 

detailed single beam or multibeam surveys. 

Contour maps of the FGBNMS region produced by colleagues at TAMU, using existing single 

beam echosounder and leadline data archived in NOAA-NGDC data sets, identified numerous 

topographic features occurring between East and West FGB, and in deeper waters south of the 
450 

region. These features corresponded with reported areas of drowned and buried patch reefs, salt 

diapirs and faults occurring between EFGB and West Flower Garden Bank. Despite the 

occurrence of these unique geological features, no detailed maps were available for this region. 

Bathymetric surveys of EFGB, WFGB, and Stetson Bank have been conducted since the 1930s 

using single beam echosounders, and were surveyed in the 1990s using high-resolution 

multibeam echosounders (MBES). However, areas of the outer shelf and upper slope 

surrounding the sanctuary were poorly mapped, and deepwater reef communities between East 

and West FGB were unknown. 

During April 2004, a hydrographic survey was conducted aboard the NOAA Ship THOMAS 

JEFFERSON to provide information on habitat distribution and classification to the FGBNMS, 

and provide a source of bathymetry for updating existing National Ocean Service (NOS) charts. 

Data were acquired by the NOAA Ship THOMAS JEFFERSON using a Simrad EM1002 MBES 

and GPS-aided inertial navigation system. NOAA launches 1014 and 1005 acquired multibeam 

data with GPS-aided inertial navigation systems and RESON 8125 and RESON 8101 MBES, 

respectively. 

High-resolution multibeam mapping of the mid- to outer continental shelf resulted in the 

discovery of previously unknown features on the seafloor. A series of mud volcanoes, a deep 

reef escarpment, a submarine canyon, and over 2,000 deep-patch reefs were identified, providing 

a continuous network of deep-reef communities between East and West FGB (Figures 1H.1 and 

1H.2). Multibeam surveys of the coral cap also resulted in extremely detailed views of coral 

distribution (Figures 1H.3 and 1H.4). Multibeam bathymetry data were incorporated into 

Arcview 3.2 projects as geo-tiffs, and as 3D maps using Fledermaus Interactive Visualization 

Systems. Habitat polygons were visually traced in Arcview 3.2 to identify distribution of habitat 

types, and estimate total area of habitat types within the sanctuary and the region (Figure 1H.2). 

Acknowledgments 

We would like to thank the captain and crew of the NOAA ship Thomas Jefferson for their 

tremendous enthusiasm and efforts during the 2004 multibeam survey. We thank Dr. Jim 

Gardner, University of New Hampshire (formerly of USGS), for providing supplemental 

multibeam data. Figure 1H.1 was provided courtesy of International Mapping Associates, Ellicot 

City, MD and the National Marine Sanctuary Program Headquarters, Silver Spring, MD. 
451 

Figure 1H.1. Flower Garden Banks Region of the Northwestern Gulf of Mexico. 
452 

Figure 1H.2. Habitat Map of the Flower Garden Banks Region, showing distribution of hard-bottom and 

 as interpreted from bathymetry and acoustic backscatter data. 
453 

Figure 1H.3. Coral Reef Cap of the West Flower Garden Bank, interpolated at 0.5m resolution.
454 

Figure 1H.4. Coral Reef Cap of the East Flower Garden Bank, interpolated at 0.5m resolution.
455 

Douglas C. Weaver is a research biologist/GIS specialist at the Flower Garden Banks National 

Marine Sanctuary. He has over 18 years of experience in research in marine ecosystems. He has 

participated in over 50 research cruises as Research or Chief Scientist, including three multibeam 

mapping surveys, and has conducted over 800 SCUBA dives in the Gulf of Mexico and Florida. 

Mr. Weaver received his B.S. in marine biology from Millersville University, PA and his M.S. in 

zoology from the University of Florida. His main research interests are reef fish biology and 

ecology, seafloor mapping/ habitat characterization, and landscape ecology. 

Emma Hickerson has held the position of research coordinator of the Flower Garden Banks 

National Marine Sanctuary since 1997. She began her career at the Sanctuary while still a 

graduate student at Texas A&M University, conducting satellite tracking studies on loggerhead 

sea turtles living on the reef. During her tenure in the current position with the Sanctuary, she has 

coordinated over 50 research cruises, including SCUBA, ROV, and submersible operations. Her 

interests have expanded beyond sea turtles, to include most ecological and biological aspects of 

the Sanctuary, with recent efforts being placed on the deepwater habitats of the Sanctuary, and 

adjacent areas. 

G.P. Schmahl. has been the manager of the Flower Garden Banks National Marine Sanctuary 

since March 1999. Prior to that he served for eight years as the Lower Keys Regional Manager of 

the Florida Keys National Marine Sanctuary in Key West, Florida. As Sanctuary manager, he is 

involved with a broad array of Marine Protected Area management issues including research, 

education and resource protection. After obtaining a graduate degree in zoology from the 

University of Georgia, G.P. has held a variety of positions relating to marine research, coastal 

management, resource planning and environmental regulation. His primary interest is the 

ecology and management of coral reefs and associated ecosystems, and he has specific interest 

and expertise in the biology and ecology of marine sponges. 
456 

LONG-TERM REEF MONITORING OF THE EAST AND WEST FLOWER 

GARDEN BANKS: NEW SURPRISES 

William F. Precht and Martha L. Robbart, Ecological Sciences Division, PBS&J 

Richard B. Aronson, Dauphin Island Sea Lab 

Ken J. P. Deslarzes, Marine Sciences Group, Geo-Marine Inc. 

Les Kaufman, Center for Ecology and Conservation, Boston University 

The Flower Garden Banks (FGB) coral reef monitoring program has been continuously funded 

since 1988 by the Minerals Management Service (MMS) and in partnership with NOAA’s 

National Marine Sanctuary Program since 1996. Two sites, each 100 m x 100 m and 18–25 m 

deep, have been monitored over that period: one on the East FGB and the other on the West 

FGB. The two sites remain in excellent condition. Their status contrasts with reports of reefs in 

crisis throughout the southern Gulf of Mexico, the western Atlantic, and the Caribbean region. 

Across the Caribbean, regional disease outbreaks have changed the structure and function of 

reefs over relatively short time scales, and while scientists observed the changes, they still do not 

completely understand the causes. Beginning in the 1970s and continuing up to the present, 

diseases or disease-like syndromes have appeared in many coral species throughout the western 

Atlantic and Caribbean. Although coral diseases are present on the FGB, their prevalence is low 

compared to that on most other reefs that have been surveyed. The short- and long-term impacts 

of coral diseases on populations remain difficult to assess, but disease is clearly a factor in the 

mortality of some corals on the FGB. 

In addition to disease, widespread coral bleaching in response to anomalously high summerseason temperatures has become more frequent since the early 1980s. Bleaching episodes on 

reefs in the western Atlantic-Caribbean region, including the FGB, have generally been followed 

by recovery of most of the affected coral colonies (Hageman and Gittings 1992; Aronson et al. 

2002). Other causes of coral mortality on the FGB include concentrated spot-biting by parrotfish, 

resulting in large lesions on head corals, as well as the impacts of damselfish territories, which 

result in patchy areas of coral mortality and algal growth on affected colonies. 

Remarkably, no significant long-term changes have been detected in coral reef populations, total 

coral cover, or coral species diversity at the FGB since quantitative surveys of the reefs began in 

1988. Percent coral cover on these reefs is among the highest measured at present in the entire 

region. Probable reasons for the exceptional condition of the FGB include 1) the water depth of 

the reefs, which buffers them from the effects of storm waves and anomalously high sea 

temperatures; 2) the lack of acroporid corals, which have suffered catastrophic levels of 

mortalities throughout the Caribbean; 3) the remote, offshore location of these reefs, which 

provides a water column characterized by oligotrophic, oceanic water; 4) healthy fish 

populations that include all trophic guilds; and 5) protective Federal regulations, which prevent 

hydrocarbon-related impacts, and impacts caused by fishing and recreational diving activities. 
457 

Corals are the dominant cover on both reefs, accounting for over 50% cover in both cases. A 

category comprising bare rock and turf-covered rock is the second-most prevalent at ~ 25%, 

followed by crustose coralline algae at ~15%. Macroalgae and filamentous algae are next in 

abundance at ~5%, followed by sponges, which account for ~1% of total cover. In addition to 

assessing benthic community structure, we are also measuring coral growth rates, incidence of 

coral mortality, associated mobile fauna, fish population structure, and water quality parameters. 

New additions to the monitoring program include the establishment of deep reef stations at the 

East Bank in 31–40m depth. 

Recent surprises at the FGB include the first known colony of Acropora palmata, the first 

sighting of the exotic coral Tubastraea coccinea, the initial recovery of the sea urchin Diadema 

antillarum on the West Bank, and occasional outbreaks of plague-like coral diseases. As 

previously mentioned, reef condition at the FGB is currently exceptional and shows essentially 

no difference in species composition or total coral cover from early monitoring studies. 

Therefore, understanding the role of these reef environments in the context of the greater 

Caribbean is of critical importance. Continued long-term monitoring of these reefs will enhance 

our knowledge of community dynamics at the FGB in particular and provide insight about coral 

reefs in general. 

William F. Precht is a carbonate sedimentologist by training, and has been studying coral reefs 

since 1978. His research interests include combining ecological and geological methodologies to 

decipher “change” in reef communities through time and space. Using this integrated approach, 

he (with collaborators Richard B. Aronson and Ian Macintyre) has been able to assess the 

geological and ecological novelty of many of the recent maladies affecting Caribbean coral reefs. 

This assessment includes deciphering local anthropogenic signals from overarching global 

effects. Specific research has included the effects of coral disease and coral bleaching on the 

trajectories of reef coral communities. Since completing his graduate degree in marine geology 

and geophysics from the University of Miami’s Rosenstiel School of Marine and Atmospheric 

Science, Bill has worked as an environmental scientist specializing in the ecology of coastal 

systems. Presently, he is the chief scientist overseeing the long-term reef monitoring at the 

Flower Garden Banks National Marine Sanctuary. In addition, he developed cutting edge 

assessment and restoration strategies for reefs impacted by various anthropogenic sources, 

including providing expert assistance to a wide array of both national and international clients. 

Richard B. Aronson received his A.B. in biological sciences from Dartmouth College in 1979 

and his Ph.D. from Harvard University in biology in 1985. He is currently Senior Marine 

Scientist at the Dauphin Island Sea Lab in Alabama. Rich has been working on coral reefs for 

decades, focusing on disease, climate change, and other large-scale factors that cause turnover of 

reef faunas. He pioneered the use of videographic methods for surveying coral reefs, and he 

developed the univariate and multivariate statistical approaches needed to analyze the data. 

Rich’s techniques are now being used by reef managers throughout the western Atlantic and 
458 

Caribbean region. Rich’s research combines survey and monitoring work with paleoecology to 

understand the history, present status and future of coral reefs. 

Dr. Ken Deslarzes is a Senior Marine Ecologist at Geo-Marine Inc. and has extensive experience 

in coral reef science with an emphasis on resource assessment studies conducted since 1988 

(nine studies). His Ph.D. research while at Texas A&M was conducted at the Flower Garden 

Banks: “Long-term monitoring of reef corals at the Flower Garden Banks (northwest Gulf of 

Mexico): reef coral population changes and historical incorporation of barium in Montastrea 

annularis.” Dr. Deslarzes has 32 publications (refereed papers, theses, reports, conference 

products), 23 of which are directly related to the FGB coral reefs. His most recent coral reef 

research dealt with identifying the source of luminescent banding in Montastraea faveolata at the 

Flower Gardens (submitted to Coral Reefs) and the dispersal of coral larvae from the Flower 

Gardens (2001 Continental Shelf Research). 

Dr. Les Kaufman works on the scientific underpinnings for marine conservation and 

sustainability of the human enterprise in the world’s oceans. Specifically, Dr. Kaufman’s 

research has focused on the ecology of coral reef fisheries. These fisheries have had a profound 

impact not only on edible species but also on entire marine nearshore communities as well, via 

the cascading ecological effects of the removal of target biomass. In a series of studies, Dr. 

Kaufman’s lab is developing the scientific basis for a shift from data-poor, single-species impact 

management, to information-rich, ecosystem-based management. One focus of this work 

includes field studies of fish movements in and out of protected areas using acoustic telemetry. 

To this end, Dr. Kaufman is studying the movements of individual cod and haddock in and 

around the Western Gulf of Maine Closure in the Stellwagen Bank National Marine Sanctuary 

(Massachusetts Bay) and in and out of Special Protected Areas in the Florida Keys National 

Marine Sanctuary. He is also conducting experiments on fish-habitat relationships, population 

modeling, and the development of non-demographic parameters for assessing the health of 

marine communities that support important fisheries. His work on nearshore fisheries has been 

supported by the Packard Foundation, the Pew Charitable Trusts, and NOAA. Dr. Kaufman is 

particularly interested in the movements of reef fish in and around the reefs of the Flower Garden 

Banks. 

Martha L. Robbart is a scientist at PBS&J and has experience in coral reef biology, biochemistry 

and ecology. Her M.S. degree in biology from Smith College investigated thermal tolerance in 

scleractinian corals as expressed in heat shock proteins. With a strong background in coral reef 

ecology, she has been involved in coral reef assessment in Belize, San Salvador Bahamas, and 

now the Flower Garden Banks National Marine Sanctuary. 
459 

MONITORING AT THE FLOWER GARDEN BANKS: 

METHODOLOGY, EVOLUTION, AND FUTURE 

Richard B. Aronson, Dauphin Island Sea Lab 

William F. Precht, Ecological Sciences Division, PBS&J 

The coral reefs of the Flower Garden Banks (FGB) are among the most sensitive biological 

communities in U.S. federal waters of the Gulf of Mexico. In 1973, the Minerals Management 

Service (MMS) established a program of protective activities at those reefs. Two sites, each 100 

m x 100 m and 17–26 m deep, have been monitored since 1988: one on the East FGB and the 

other on the West FGB. MMS has been monitoring the coral populations at these sites on a longterm basis to detect incipient changes caused by oil and gas activities. The results are also 

helping to explain the rampant degradation of reef ecosystems observed in the wider Caribbean 

region over the last few decades. 

The percent coverage of living coral within the study sites was assessed visually from 1978–

1982 using the linear point-intercept (LPI) method. A diver swam along transect lines, recording 

the substratum components at set intervals. During the period 1988–2002, coral cover was 

estimated by taking still photographs along randomly placed, 10-m transects. In this technique, 

the estimates were derived by planimetry of the photographs. As part of a transition to digital 

imaging, beginning in 2002–03 we videotaped randomly positioned transects and derived 

estimates of coral cover from point counts on individually captured video frames. To compare 

the methods, we also estimated coral cover in 2002–03 using the LPI technique and planimetry 

of still photographs. 

The total area analyzed from the videotapes was 30.24 m2

 per site per year (14 transects x 20 

frames/transect x 1080 cm2

/frame). In contrast, the photographic technique covered more than 

twice the area, at 65.97 m2

 per site per year (14 transects x 17 frames/transect x 2,772 

cm2

/frame). The LPI design is unidimensional, so there is no ‘area’ covered. Despite these 

differences in area covered and analytical technique, comparison of the videographic, 

photographic and LPI methods in 2002–03 showed that the three approaches gave very similar 

mean estimates of coral cover. Repeated measures analysis of variance (ANOVA) showed no 

significant differences among the estimates. 

This result demonstrates that the three methods are interchangeable. A methodological change in 

the long-term monitoring program to digital videography, for which the analysis is far less laborintensive than planimetry of still photographs, is entirely justified and will not compromise the 

utility of previous years’ data. On the contrary, it is legitimate to compare estimates of coral 

cover from 2002–03 and future videographic transects to existing records from still images, and 

from the early LPI transects, without confounding our understanding of coral dynamics at the 

Flower Garden Banks. 
460 

Based on the video transects, the mean coverage of living hard corals exceeded 50% at the two 

banks in 2002–03, consistent with estimates of coral cover from the LPI data and still 

photographs in previous years. To determine the sensitivity of the videographic technique, we 

calculated δ, the minimum difference in coral cover detectable by ANOVA. The significance 

level was set at the conventional α = 0.05 and the desired power at the conventional (1-β) = 0.80. 

For videographic surveys of two sites over two years, with 14 transects per site per year, δ = 

0.074. In other words, we can expect to be able to detect a 7.4% change in coral cover between 

any two years at the Flower Garden Banks, or a 7.4% difference in cover between the two banks 

in a two-year study. 

The calculated δ agrees with values of 5.2–9.8% obtained using the videographic method to 

compare four sites in Florida and the Caribbean, with 10 transects per site and coral cover 

varying from 3–21%. The δ calculated in the present study is a few percent higher than the 

minimum detectable difference of 2.4–3.8% calculated for a comparison of three sites in the 

Florida Keys; however, that study used 30 transects per site and the sites had extremely low 

cover, both of which reduced the error variance and, therefore, reduced δ. 

We also compared our results from 2002–03 to data collected during the same period on 

protected reefs within the Florida Keys National Marine Sanctuary. Low values of coral cover on 

the reefs in Florida illustrate how recent, catastrophic mortality of the formerly dominant 

Acropora spp. has led to the degradation of coral assemblages in the Caribbean. The FGB have 

remained in exceptionally good condition largely for reasons of physical geography. Their 

northern location has excluded the cold-sensitive acroporids, so the loss of acroporids throughout 

the region in the 1980s and 1990s did not affect coral cover at the FGB. A single colony of A. 

palmata has now appeared on the FGB, coincident with warming temperatures in the subtropical 

western Atlantic and northward expansion of acroporids along the east coast of Florida. The 

continuing, multidecadal baseline of reef condition generated by the monitoring program will 

enable managers to make informed decisions in the event of future changes to the biota of the 

Flower Garden Banks. 

Richard B. Aronson received his A.B. in biological sciences from Dartmouth College in 1979 

and his Ph.D. from Harvard University in biology in 1985. He is currently Senior Marine 

Scientist at the Dauphin Island Sea Lab in Alabama. Rich has been working on coral reefs for 

decades, focusing on disease, climate change, and other large-scale factors that cause turnover of 

reef faunas. He pioneered the use of videographic methods for surveying coral reefs, and he 

developed the univariate and multivariate statistical approaches needed to analyze the data. 

Rich’s techniques are now being used by reef managers throughout the western Atlantic and 

Caribbean region. Rich’s research combines survey and monitoring work with paleoecology to 

understand the history, present status and future of coral reefs. 

William F. Precht is a carbonate sedimentologist by training, and has been studying coral reefs 

since 1978. His research interests include combining ecological and geological methodologies to 
461 

decipher “change” in reef communities through time and space. Using this integrated approach, 

he (with collaborators Richard B. Aronson and Ian Macintyre) has been able to assess the 

geological and ecological novelty of many of the recent maladies affecting Caribbean coral reefs. 

This assessment includes deciphering local anthropogenic signals from overarching global 

effects. Specific research has included the effects of coral disease and coral bleaching on the 

trajectories of reef coral communities. Since completing his graduate degree in marine geology 

and geophysics from the University of Miami’s Rosenstiel School of Marine and Atmospheric 

Science, Bill has worked as an environmental scientist specializing in the ecology of coastal 

systems. Presently, he is the chief scientist overseeing the long-term reef monitoring at the 

Flower Garden Banks National Marine Sanctuary. In addition, he developed cutting edge 

assessment and restoration strategies for reefs impacted by various anthropogenic sources, 

including providing expert assistance to a wide array of both national and international clients. 
462 

FEASIBILITY OF USING REMOTE SENSING TECHNIQUES FOR SHORELINE 

DELINEATION AND COASTAL HABITAT CLASSIFICATION FOR 

ENVIRONMENTAL SENSITIVITY INDEX (ESI) MAPPING 

Katherine Born-Phillips, Chris Locke, and Jacqueline Michel, 

Research Planning, Inc. 

DeWitt Braud, Coastal Studies Institute, Louisiana State University 

Introduction 

Environmental Sensitivity Index (ESI) mapping refers to a shoreline classification and sensitivity 

ranking system that has been a vital component of oil spill contingency planning and marine 

environmental assessment programs nation wide for 25 years (Halls et al. 1997). The U.S. 

Minerals Management Service (MMS) currently uses ESI data and the ESI classification scheme 

for environmental assessment studies related to Outer Continental Shelf (OCS) activities. 

Traditional ESI data development includes the interpretation of aerial photographs and mapped 

observations by coastal geologists during overflights. This method has been applied successfully 

to the majority of the U.S. coastline. The complex, rapidly changing shoreline of Louisiana, 

however, has made ESI mapping extremely difficult using traditional techniques. As a result, a 

coast-wide ESI shoreline classification has never been developed for Louisiana. This represents a 

major information gap, as oil spill risk and environmental consequences in Louisiana are great. 

ESI classification efforts in Louisiana in the late 1980s relied on remotely sensed imagery with 

spatial resolution of 20-30 meters (Jensen et al. 1990). Although a useful land-use/land cover 

classification was achieved, the detail associated with the linear nature of shoreline features 

could not be resolved, and a true ESI shoreline classification was not possible. More recently, the 

barrier island beaches and other outer-coast features of Louisiana were classified using 

traditional ESI methods, as part of the Gulf-Wide Information System (G-WIS) project (MMS et 

al. 2001; Zengel and Hanifen 2001; Zengel et al. 2002). This effort was possible due to the linear 

configuration of the outer coast. Beyond this, most of the Louisiana coast remains unclassified 

and cannot reasonably be completed using traditional methods. Newer, high-resolution satellite 

imagery offers the best opportunity for coast-wide ESI shoreline mapping and classification in 

Louisiana and other similar areas with highly complex, rapidly changing shorelines. 

The primary objective of this research was to develop remote sensing classification procedures to 

support ESI mapping efforts in Louisiana and elsewhere. Several questions comparing remote 

sensing techniques and traditional classification methods were of interest including: 

 1. Are remote sensing methods reliable, more cost and time effective, and do they provide 

as much information as traditional methods? 

 2. Is the spectral and spatial resolution of the IKONOS satellite imagery chosen for the 

project appropriate? Is the use of archived imagery for cost savings appropriate? 

 3. Can a viable land/water interface be created from the imagery? And finally, 
463 

 4. Can an ESI-style product useful for spill response and coastal management be produced? 

The saline areas of the Louisiana coastline from Port Fourchon to Lake Barre were chosen as the 

study site. Salinity boundaries were obtained from the 1997 Louisiana Coastal Marsh Vegetative 

Type Map (LDWF 1997) which included values of brackish, fresh, intermediate, saline, and 

water. In this data set saline was defined as salt marsh having typical vegetation of oystergrass 

(Spartina alterniflora), glasswort (Avicennia germinans), and saltgrass (Distichlis spicata). This 

area of coastal Louisiana has experienced high rates of land loss and rapid shoreline change that 

have made traditional ESI classification techniques difficult. However, the presence of extensive 

oil and gas infrastructure and highly sensitive habitats and natural resources in this area 

emphasizes the need for up-to-date maps for oil spill planning and response. 

Methods of Study 

The study methodology consisted of the following tasks: image acquisition, land/water interface 

production, in situ data collection, image classification, vector shoreline transfer, validation 

overflight, and an accuracy assessment. In contrast, a traditional ESI project methodology would 

consist of: identification of existing digital land/water or shoreline, overflight classification on 

topographic quads, field classification accuracy assessment, and on-screen ESI attributing of the 

digital shoreline. 

Results 

The results section describes ten ESI habitat types that were observed during the field work and 

traditional overflights. For each ESI habitat type, the habitat characteristics are described, and the 

technical performance of the imagery and classifications techniques are discussed. The text is 

followed by a sub set of the IKONOS imagery where the ESI habitat is present, a second images 

shows the imagery with the shoreline classification. An oblique aerial photograph, taken during 

the overflights, is shown for the same general area of the imagery, and finally a representative 

ground photograph is provided for each ESI habitat. 

Results 

The spatial and spectral resolutions of IKONOS imagery adequately captured four broad habitat 

classes but did not extract the same level of detail as traditional ESI mapping methods. The 

usefulness and applicability of these broad ESI classifications are dependent on the question at 

hand. For oil spill response, the relatively current imagery provides a valuable base map that is 

greatly improved over other available maps. This feature is particularly important in coastal areas 

experiencing rapid shoreline change. One of the biggest challenges of responders in these areas 

is access to maps that accurately reflect current conditions so that equipment and personnel can 

be deployed to appropriate cleanup sites. Currently, responders obtain oblique digital photography during overflights then print out the photographs to use as base maps for use in deploying 

equipment and mapping the distribution of oil. Recent imagery would provide a more uniform 

base map. A high resolution shoreline vector was also extracted from the imagery and served as 

the base for shoreline classes. Creation of an actual shoreline is also of value to spill responders, 

since miles of shoreline oiled is a common metric used to measure the spill impact on linear 

shoreline types and track cleanup progress. 
464 

Both archived and new-collect imagery were used in this study. The average price for archived 

imagery was $6.85 per km2 whereas the average price for new-collect imagery was $12.89 per 

km2. The archived imagery is significantly cheaper; however, the seasons and tides cannot be 

chosen and fieldwork cannot coincide with the collection of the imagery. On the other hand, it is 

still difficult to predict and plan for new-collect satellite imagery to coincide with the desired 

seasons, tides and cloud-free days, and the small swath width of the IKONOS satellite cannot 

collect imagery for a large area in a single pass. 

General recommendations to improve the classification of all ESI habitat types include the use of 

more robust sensors, sensors that can extract vertical structures, ancillary elevation data, texture 

analysis, and an exposure index. The Compact Airborne Spectrographic Imager (CASI and CASI 

2) and Light Detecting and Ranging (LiDAR) are robust airborne sensors that have the potential 

to extract ESI classes with greater detail. Larsen and Erickson (1998) used the CASI sensor to 

distinguish between substrate types such as course sand, mud, and gravel beaches and man-made 

features. LiDAR collects elevation data, which may be useful in classifying vertical structures. 

Applying an exposure index to the shoreline can further define the modified classes into 

sheltered and exposed. 

References 

Halls, J., J. Michel, S. Zengel, J.A. Dahlin, and J. Petersen. 1997 Environmental sensitivity index 

guidelines, version 2.0. NOAA Technical Memorandum NOS ORCA 115, Seattle, WA. 

79 pp. plus appendices. 

Louisiana Department of Wildlife and Fisheries, Fur and Refuge Division, U.S. Geological 

Survey, Biological Division’s National Wetlands Research Center, and Department of 

Geology and Anthropology, Louisiana State University. 1997. 1997 Louisiana Coastal 

Marsh Vegetative Type Map NAD83, LDWF, NWRC, LSU (1997) [salinity]. Lafayette, 

LA: Louisiana Department of Wildlife and Fisheries, Fur and Refuge Division and the 

U.S. Geological Survey’s National Wetlands Research Center. 

Minerals Management Service, Louisiana State University, Louisiana Department of Wildlife 

and Fisheries, and Research Planning Inc. 2001. Gulf-wide information system, 

Louisiana: outer coast environmental sensitivity index (ESI). U.S. Minerals Management 

Service, New Orleans, LA . Arc/Info coverage and metadata. 

Zengel, S. and J. Hanifen. 2001. Louisiana G-WIS: ESI, Wildlife, and Fisheries Components. 

17th Annual Louisiana Remote Sensing and GIS Conference, Baton Rouge, LA, April 2–

4, 2001. 

 

Zengel, S., Z. Nixon, C. Plank, J. Hanifen, D. Sa, and D. Braud. 2002. Environmental Sensitivity 

Mapping and GIS: The Louisiana G-WIS Database. Fourth Biennial Freshwater Spills 

Symposium, Cleveland, OH, March 19–20, 2002. 
465 

DeWitt Braud is a researcher in the Louisiana State University Coastal Studies Institute. He has 

specialized in GIS and remote sensing research and applications involving major projects in 

Louisiana for over 20 years. 

Katherine Phillips is a GIS/Remote Sensing Analyst at Research Planning, Inc. Katherine has a 

B.S. from the University of Western Australia and an M.S. in marine science from the University 

of South Carolina. Her expertise is in integrating coastal science and policy with spatial 

technologies for the comprehensive planning and management of limited coastal resources. 

Jacqueline Michel is a geochemist specializing in terrestrial and marine pollution studies, coastal 

geomorphology, and environmental impact assessments. She is President of Research Planning, 

Inc., an environmental consulting firm with offices at the University of New Orleans and in 

Columbia, South Carolina, that offers services in Spill Response and Planning, Natural Resource 

Damage Assessment, and Geographic Information System Design and Analysis. 

Chris Locke is a Geographic Information Systems and Remote Sensing Analyst with Research 

Planning, Inc. in Columbia, South Carolina. Over a ten-year span at RPI, he has worked on a 

variety of spatial and image applications for oil and gas emergency preparedness, risk planning, 

and environmental damage assessment. He received his B.A. and M.S. in geography from the 

University of South Carolina. 
466 

PIPELINE AND NAVIGATION CANAL IMPACTS AND MITIGATION EFFECTS ON 

WETLAND HABITATS OF COASTAL WESTERN AND CENTRAL GULF OF MEXICO 

James Johnston, Donald Cahoon, Megan LaPeyre, Philippe Hensel, and 

Thomas McGinnis, U.S. Geological Survey, 

National Wetlands Research Center, Lafayette, LA 

Project Goals and Approach 

The study goal was to prepare a factual array of data and data analyses in order to quantitatively 

determine any direct and indirect effects of OCS pipelines and navigation canals on land loss and 

wetland habitat change in the western and central planning areas of the Gulf of Mexico. Specific 

goals included 1) to estimate changes in land area (land versus open water) and extent of fresh 

and non-fresh marsh in relation to OCS pipelines and navigation canals, and 2) to discuss 

construction and mitigation techniques used to mediate OCS pipeline and navigation canal 

effects on land loss through literature review and qualitative analyses of selected case studies. 

The project was organized into four major components 1) literature review, 2) GIS analysis: 

collection and collation of spatial data on locations and habitats of OCS pipelines and navigation 

canals, as well as generation of land loss and habitat change data sets within the immediate 

vicinity of pipelines and navigation canals, 3) analysis of land loss and habitat change: statistical 

analyses of trends in land loss, habitat change, and pipeline and navigation canal construction 

effects, and 4) mitigation effectiveness: an evaluation of mitigation techniques for ameliorating 

pipeline and navigation canal impacts. 

The study area boundaries incorporated the coastal Western and Central Planning Areas of the 

Gulf of Mexico as designated by the Minerals Management Service. The study area was divided 

into five subareas based on geologic and political features: Texas Barrier Islands (TBI), Texas 

Chenier Plain (TCP), Louisiana Chenier Plain (LCP), Louisiana Delta Plain (LDP), and 

Mississippi/Alabama (MS/AL). Geographic Information System (GIS) investigations of habitat 

changes were performed using historical aerial photography, coupled with a literature review and 

interviews with agency and industry personnel. GIS data sets were obtained from the U.S. 

Geological Survey and U.S. Army Corps of Engineers. For each of the five subareas, habitats 

within the immediate vicinity of pipelines and navigation canals were analyzed over two time 

intervals (e.g., 1956 – 1978 and 1978 – 1988/90). Habitat change was determined among fresh 

marsh, non-fresh marsh, and open water. Two data sets were developed and analyzed: 1) subarea 

trend of land/wetland loss and habitat change within 300 m (150 m either side) of every pipeline 

and 1,000 m (500 m either side) of every navigation canal, 2) subwatershed trend of change in 

wetland habitats/open water located within 3,000 m (1,500 m either side) for three to five 

pipelines and two navigation canals in each subarea, subdivided into non-overlapping zones 

located at increasing distances from the centerline. Two statistical models were used: YEAR 

comparing fixed time intervals and PHASE comparing pre- and post-construction changes. If the 

PHASE model provided a better fit, changes in habitat were more likely related to pipeline 

construction than other time-dependent processes. 
467 

Summary of Findings 

Finding 1. Land loss in Louisiana was consistently higher in the vicinity of all pipelines and 

navigation canals compared to subarea trends. This analysis was made only for Louisiana where 

regional loss data were available for comparison. In the LDP, the annual land loss rate (%) was 

two- to three-fold greater in the vicinity of pipelines (0.89 vs. 0.33, P = 0.003, 1956–1978; 0.74 

vs. 0.28, P = 0.007, 1978–1988/1990) and navigation canals (1.08 vs. 0.33, P = 0.006, 1956–

1978; 0.50 vs. 0.28, P = 0.056, 1978–1988/1990). In the LCP, the annual land loss rate (%) was 

50–100 % greater in the vicinity of pipelines but only significantly greater for the 1978–1990 

interval (0.41 vs. 0.19, P = 0.059). For navigation canals, the annual land loss rate (0.09–0.14 %) 

was not significantly different (P > 0.801). These findings suggest that pipelines and canals 

impacted regional land loss, although there are constraints to the data (see below). 

Finding 2. The influence of pipelines and navigation canals on land/wetland loss and habitat 

change differed among the five subareas. In the LDP, LCP, TCP, and TBI, the high loss rates and 

changes in habitat were apparently related, in part, to pipeline and canal construction, although 

other time-dependent phenomena (e.g., subsidence) also influenced the trends. In Louisiana, 

local conditions (e.g., subsidence rates) likely influenced high loss rates in the LDP because 

pipeline numbers were high in both areas, and the same array of construction methods was used 

in each. In Texas, the difference in loss rates between the TCP and TBI was likely related, in 

part, to the pipeline construction/mitigation techniques used and local conditions (e.g., 

directional drilling in the TBI and higher subsidence in the TCP). In contrast to Louisiana and 

Texas, pipeline construction in MS/AL apparently had little or no effect on trends in habitat 

change or land loss, however, navigation canals apparently affected patterns of habitat change 

and land loss, although not to the extent they did in Louisiana and Texas. In MS/AL, pipeline 

impacts were negligible with only 10 pipelines constructed, mostly in a corridor with other 

pipelines to localize impacts or directionally drilled under the wetland habitats. 

Finding 3. In Louisiana and Texas, habitat changes were more often related to pipeline construction date than to some other time-dependent variable, suggesting that pipelines had an effect on 

habitat change in those cases. Considered together, Findings 1,2, and 3 strongly suggest that 

pipelines affected wetland habitats in many instances. In Mississippi/Alabama, both YEAR and 

PHASE analyses indicate that pipelines likely had little effect on trends in wetland habitat 

change, although canals were associated with habitat change in some cases. However, our level 

of certainty regarding pipeline and canal construction influences on the trends in habitat change 

is constrained by a lack of knowledge of the regional trends in habitat change. 

Finding 4. The effectiveness of mitigation techniques on land/wetland loss and habitat change 

differed by subarea. Some differences may be due to the variation in land loss by subarea. 

Pipelines in Mississippi/Alabama appear to have had little or no effect on trends in habitat 

change or loss, although three construction and three mitigation techniques were used. Of note, 

unlike the other subareas, most pipelines in Mississippi/Alabama were built within one of several 

pipeline corridors. In Texas, impacts varied by subarea, with less noticeable impacts in the 

Barrier Island subarea due to the construction techniques used, as both directional drilling and 

more mitigation were required in the more sensitive barrier islands. In Louisiana, with its high 
468 

loss rates and changes in habitat, pipeline effects were difficult to tease apart from other 

phenomena (e.g., subsidence, marsh management, marsh restoration, development). Qualitative 

analyses were either inconclusive due to confounding effects of other phenomena along the 

pipeline route or showed potential evidence of saltwater intrusion and increased open water areas 

mostly from un-backfilled pipelines. In many cases, however, the 300 m reference and pipeline 

zones showed similar trends in habitat change. 

Dr. James B. Johnston is the Section Chief, Spatial Analysis Branch of the National Wetlands 

Research Center in Lafayette, Louisiana. He serves as the Regional Coordinator for the 

Louisiana Coastal Ecosystem Program and principal advisor to the Regional Director and other 

Regional-level staff, and Departmental officials regarding multi-agency scientific investigations 

in Louisiana. In this position, he consults with high-level officials on the federal and state agency 

Louisiana Task Force on coastal restoration. 

Dr. Megan La Peyre is Assistant Unit Leader of the Louisiana Cooperative Fish and Wildlife 

Research Unit at LSU. Her research interests include restoration and management of 

coastal/estuarine ecosystems, quantifying/identifying characteristics of fish habitat, and ecology 

of coastal vegetation. 

Dr. Donald R. Cahoon is a research ecologist with the U.S. Geological Survey, Patuxent Wildlife 

Research Center located in Beltsville, MD. He received his B.A. with Honors in botany, from 

Drew University (1972), and his M.S. (1975) and Ph.D. (1982) degrees in Wetland Plant 

Ecology from the University of Maryland. His professional interests include wetland plant 

ecology, wetland accretionary processes, and wetland restoration and management. His research 

program is focused on three objectives: 1) determining the impacts of sea-level rise on long-term 

marsh stability through evaluations of marsh accretionary processes, 2) identifying the processes 

of wetland loss, submergence, and soil erosion in both natural and managed coastal marshes, and 

3) evaluating the effectiveness of wetland restoration and management techniques. He worked on 

coastal management and research issues in Louisiana for 19 years before moving to Maryland in 

2001. 

Dr. Philippe F. Hensel is an ecologist with the U.S. Geological Survey, Patuxent Wildlife 

Research Center located in Beltsville, MD. He received his B.S. in biology degree, maxima cum 

laude, from the Catholic University of America (1988), his M.S. degree in marine, estuarine, and 

coastal sciences from the University of Maryland (1992), and his Ph. D. in oceanography and 

coastal sciences from Louisiana State University (1998). His main areas of interest include: 1) 

coastal wetland ecology, especially sediment dynamics and mangrove ecology, and 2) the 

development of analytical and statistical tools to field-based studies, especially regarding spatial 

components of variation. 

Mr. Thomas E. McGinnis, II, a native of south Louisiana, is a General Biologist II with Johnson 

Controls, Inc. (JCI), contracted to the U. S. Geological Survey – National Wetlands Research 
469 

Center (NWRC) in Lafayette, LA. He earned a B.S. (aquatic and fisheries biology, 1994) and an 

M.S. (biology, 1997) from the University of Louisiana at Lafayette (ULL) where he developed 

an interest in geomorphologic processes in coastal marshes. After his M.S. degree, Mr. McGinnis 

continued at ULL as a research associate studying how oil-spill clean-up chemicals affect salt 

marsh soil function. He then joined NWRC as a JCI contractor (1999) to research the effects of 

OCS pipeline and navigation canals on coastal ecosystems. Mr. McGinnis has remained at 

NWRC researching the effects of global climate change and hurricanes on coastal wetlands in 

the tropics (mangroves) and sub-tropics (coastal marshes). 
470 

THE ASSOCIATION OF SALINITY PATTERN AND LANDSCAPE CONFIGURATION 

WITH OCS OIL AND GAS NAVIGATIONAL CANALS IN COASTAL LOUISIANA 

Gregory D. Steyer and Brian C. Perez, USGS National Wetlands Research Center, 

Coastal Restoration Field Station 

Charles Sasser, Louisiana State University Agricultural Center and 

The School of the Coast and Environment 

Glenn Suir, Louisiana State University Agricultural Center, 

Department of Agronomy 

Elaine Evers and Erick Swenson, Louisiana State University, 

Coastal Ecology Institute 

Coastal Louisiana is a dynamic and ever-changing landscape. In the past 50 years, over 310,000 

hectares of coastal wetlands have been lost due to a combination of natural and human-induced 

causes (LCWCRTF 1993). Subsidence, sea-level rise, freshwater and sediment deprivation, 

saltwater intrusion, the dredging of oil and gas canals, navigational canals, shoreline erosion, and 

herbivory are all contributors to wetland loss in Louisiana. Separating the influences of each of 

these factors is extremely difficult because of the wide range of spatial and temporal scales over 

which they occur. Direct impacts associated with an immediate physical conversion of habitat 

have been well described for coastal Louisiana (Boesch 1982; Turner and Cahoon 1988); 

however, the indirect impacts that are subtle and operate over longer time horizons (such as 

salinity intrusion) have been difficult to discern. 

The degree of connectivity of the landscape influences movement of water from primary sources 

(canals, bayous, lakes, bays, etc.) to interior estuarine marshes and, can greatly influence 

vegetation distributions. Saltwater intrusion into marshes can be increased by the location of 

straight and deep canals that connect the coast with the interior marshes (Gosselink 1984). Thus, 

the extent of connectivity, percentage of water in the marsh, and the configuration of water 

bodies within the marsh landscape are useful indicators to evaluate marsh conditions (Sasser et 

al. 2002). 

Ten major federal navigation canals up to 45 feet deep and 1,000 feet wide have been 

constructed in coastal Louisiana since the mid-1800s (Good et al. 1995). These channels are 

partly responsible for the severity of coastal wetland loss Louisiana is experiencing via 

direct/primary losses and by indirect/secondary losses including saltwater intrusion, hydrologic 

disruption, and shoreline erosion. Louisiana Department of Natural Resources (LDNR) has 

estimated that approximately 57,000 acres of coastal wetland habitat have been lost via shoreline 

erosion of the ten major federal navigation canals, a figure much greater than the original direct 

loss associated with construction (Good et al. 1995). Maintenance dredging and the deepening of 

existing channels to accommodate increased and larger vessel traffic also increases the 

movement of more saline waters farther inland (Wang 1988) further exacerbating the problem. 

Because of the adverse impacts of canals and OCS-related activities, there is a need to better 
471 

quantify the secondary impacts of navigation canals as well as to gain a better understanding of 

the patterns of change and wetland loss to minimize future impacts. 

The objective of this project is to perform a comprehensive evaluation of the extent that OCS 

waterways and navigation canals have contributed to changes in salinity and wetland landscape 

patterns in coastal Louisiana. Our approach includes 1) assembling and synthesizing all available 

salinity data, salinity management studies, and salinity models for coastal Louisiana; 2) 

conducting temporal and spatial analyses of available salinity data to determine changes in those 

variables relative to pre- and post-navigational canal construction and subsequent deepening 

events; and 3) relating salinity changes to hydraulic connectivity and associated habitat changes 

over time in selected study areas. The last element of our approach includes developing a water 

body configuration classification and fragmentation index to classify the study area marshes into 

multiple categories based on estimates of percentages of marsh and water, configurations of 

water bodies within the marsh, and connectivity of water bodies with selected OCS-related 

navigation canals. 

Two study sites have been selected for analysis in this project: the Houma Navigation Canal 

(HNC) and the Freshwater Bayou system. The HNC study site is located in the Terrebonne Basin 

bordered on the north by the Gulf Intracoastal Water Way (GIWW), the south by the Gulf of 

Mexico, the west by Bayou DuLarge, and the east by Bayou Terrebonne. HNC construction 

began in 1958 and was completed in 1962 and extends from the GIWW at Houma to the Gulf of 

Mexico. The canal dimensions were originally 15 feet deep by 150 feet wide, and in 1974, the 

lower reaches near Terrebonne Bay were enlarged to 18 feet deep by 300 feet wide. The 

Freshwater Bayou site is bordered on the north by the GIWW, the south by the Gulf of Mexico, 

the west by Highway 82, and the east by the McIlhenny Canal. Construction of Freshwater 

Bayou was completed in 1968 and extends from the GIWW to the Gulf of Mexico. The 

authorized dimensions of the navigation channel were 12 feet deep and 125 feet wide, with 

approval to increase width to 250 feet in the Gulf approach. 

A literature search of previous studies regarding salinity influence and patterns on the coastal 

Louisiana landscape has been completed. Variables investigated include forcing functions such 

as meteorological, climatological, freshwater input, and river discharge. These studies were used 

to evaluate coastwide and local patterns of salinity intrusion and effects of navigation canals on 

historic salinity patterns, wetland change, and wetland loss. The effects of salinity and the 

influence on vegetation establishment and spatial distribution have also been summarized. 

Historic salinity data have been collected from as many long-term stations as possible (125 to 

date) in the identified study areas to determine patterns and pulses over different spatial and 

temporal scales. These data are being analyzed within natural and man-made channels and also 

in both channel types that have been dredged and not dredged. 

Available information on the historic dredging activity of navigation canals within the selected 

study sites was obtained from various sources. These data sets and supporting attribute 

information (e.g., river mile locations), were processed and digitized into a geo-rectified vector 
472 

layer. An assessment is under way that will try to discern if any salinity changes can be attributed 

to specific dredging events. 

Photography and imagery will be used to evaluate land change and wetland landscape patterns as 

influenced by the OCS waterways HNC and Freshwater Bayou. Ideally, aerial photography 

selected for analysis will consist of dates that bracket canal construction and any major dredging 

activity (widening or deepening), will closely coincide with dates of supporting data (e.g. 

vegetation zones), and exhibit adequate quality, coverage, and ease of rectification. 

Methods for establishing percentage of water, with configuration and connectivity of water 

bodies, within the marsh landscape are under development for evaluating the effects of OCSrelated navigation canals on salinity and wetland landscape patterns. A water body configuration 

classification and fragmentation index will be used to classify study area marshes into multiple 

landscape categories. A search of habitat fragmentation and patch connectivity literature revealed 

numerous successful utilizations of fragmentation and patch analysis software, which described 

and predicted habitat patterns and change. Though this review produced important information 

regarding the feasibility of a “typical” fragmentation study, along with the accepted standard in 

fragmentation and patch analysis software (FRAGSTATS), it did not produce any literature on 

fragmentation analysis methods for a marsh landscape. Therefore, one of the purposes of this 

project is to establish, evaluate and improve methods of analyzing and classifying marsh 

fragmentation and configuration. Three test methods were proposed for this study 1) a holistic 

manual interpretation method, 2) a holistic computer-interpretation method, envisioned as a 

“moving window” class boundary delineation method, and 3) a FRAGSTATS grid-based 

method. Due to the shortcomings of both holistic approaches, we are currently working to 

develop a grid-based method of determining configurations using the FRAGSTATS computer 

software program. While the grid-based approach cannot be used to make determinations on the 

landscape as a whole, but as individual non-related tiles, it does provide reproducibility and 

potential as a packaged management tool. The FRAGSTATS grid method utilizes a land/water 

classified image and a two-part classification system 1) ratio of water to land, and 2) marsh water 

configuration and connectivity. 

Scale emerged as a major factor in metric output and classification accuracy. A 1/8 km2

 scale 

process provided the most accurate results and seemed to better satisfy the one 

water/configuration class-per-grid tile criteria. Of the FRAGSTATS output statistics that were 

available and tested for suitability, three primary metrics appeared to demonstrate the greatest 

and most accurate control over class designation. These metrics are largest patch index, patch 

cohesion index, and clumpiness index. Largest patch index quantifies the percentage of total 

landscape area comprised by the largest patch. As such, it is a simple measure of dominance, 

with values represented as a percentage. Patch cohesion index measures the physical 

connectedness of the corresponding patch type, reported as a percentage. The clumpiness index

shows the frequency with which different pairs of patch types (including like adjacencies 

between the same patch type) appear side-by-side on the map, varying from -1 (totally 

disaggregated class) to 1 (maximally clumped). Besides using these stand-alone FRAGSTATS 

values, output variables were combined in an attempt to more accurately differentiate between 
473 

configuration classes. Some combinations increased the precision of the classification, while 

others decreased the accuracy and were therefore discarded. The set of secondary metrics that 

appear to add precision to the classification scheme are adjusted patch density, ratio of number of 

patches to clumpiness index, and landscape shape index. Assessments continue to determine the 

most appropriate primary and secondary metrics for this study. 

References 

Boesch, D.F., ed. 1982. Proceedings of the Conference on Coastal Erosion and Wetland 

Modification in Louisiana: Causes, Consequences and Options. U.S. Fish and Wildlife 

Service, Washington D.C. FWS/OBS-82/59. 256 pp. 

Good, B., J. Buchtel, D. Meffert, J. Radford, K. Rhinehart, and R. Wilson, eds. 1995. Louisiana’s 

Major Coastal Navigation Channels. Unpublished report. Baton Rouge: Louisiana. 

Department of Natural Resources, Coastal Restoration Division. 57 pp. 

Gosselink, J.G. 1984. The Ecology of Delta Marshes of Coastal Louisiana: A Community 

Profile. U.S. Fish and Wildlife Service, Washington D.C. FWS/OBS-84/09. 134 pp. 

Louisiana Coastal Wetlands Conservation and Restoration Task Force (LCWCRTF). 1993. 

Louisiana Coastal Wetlands Restoration Plan: Main Report and Environmental Impact 

Statement and Appendices. U.S. Army Corps of Engineers, U.S. Department of 

Agriculture, U.S. Department of Commerce, U.S. Department of the Interior, U.S. 

Environmental Protection Agency, and Louisiana Department of Natural Resources, 

Baton Rouge, LA. 256 pp. 

Sasser, C.E., D.E. Evers, J.G. Gosselink, G.O. Holm, Jr., E.M. Swenson, and J.M. Visser. 2002. 

Ecological Evaluation of the CWPPRA Central and Eastern Terrebonne Basin Freshwater 

Delivery Project. Louisiana Department of Natural Resources, Baton Rouge, LA. 113 pp. 

Turner, R.E. and D.R. Cahoon. 1988. Causes of Wetland Loss in the Coastal Central Gulf of 

Mexico. U.S. Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region, New Orleans, LA. OCS Study MMS 87-0120. 400 pp. 

Wang, F.C. 1988. Dynamics of saltwater intrusion in coastal channels. Journal of Geophysical 

Research 93:6397-6946. 

Gregory D. Steyer received his B.S. from the University of Maryland in 1985, his M.S. in 1988 

from the University of Louisiana in Lafayette and is currently a Ph.D. candidate at Louisiana 

State University in the Department of Oceanography and Coastal Studies. For the past 16 years 

he has worked for state and federal governments developing and implementing wetland 

mitigation plans, wetland vegetation planting programs, wetland restoration projects, and 

monitoring programs for the evaluation of wetland restoration projects. Greg is currently a 
474 

wetland ecologist for the USGS National Wetlands Research Center, and his research is focused 

on developing ecological indicators, adaptive management approaches and ecological and 

landscape models for use in natural resource decision support. 

Charles E. Sasser’s professional preparation includes a B.A. in 1972, an M.S. in 1977 (both from 

LSU), and a Ph.D. in 1994 from the University of Utrecht. Charles has conducted environmental 

research at the LSU Coastal Ecology Institute, School of the Coast & Environment for over 25 

years, focusing on ecology and management of coastal wetlands. 

Brian C. Perez received his B.S. from the University of Alabama in 1992 and his Ph.D. from 

Louisiana State University in 2000 in the Department of Oceanography and Coastal Sciences. 

Brian is currently a wetland ecologist with the USGS National Wetlands Research Center where 

his research interests include wetland sedimentation and accretion dynamics, nutrient and 

sediment transport and retention within estuarine and wetland systems, coastal restoration and 

management, and the role that storms and other episodic event play in coastal management and 

sustainability. 

Erick M. Swenson received his B.S. in geology in 1975 and his M.S. in earth sciences 

(oceanography concentration) in 1978, both from the Universality of New Hampshire. He joined 

the Coastal Ecology Institute, a research unit within the School of the Coast and Environment at 

Louisiana State University, as a Research Associate in 1978 as a Field Hydrologist. His research 

interests have focused on the investigations of the hydrologic regime of coastal wetland systems 

and their response to natural drivers and human impacts. Research interests include measurement 

(monitoring design, QA/QC) and analysis of water flows, water levels, and salinity in shallow 

water, coastal and estuarine systems. Mr. Swenson has worked on the analysis of long-term 

climate, water level, and salinity in the Louisiana coastal ecological systems with emphasis on 

wetland restoration and management. Mr. Swenson also serves as an academic advisor to the 

Environmental Working Group for the Coastal Wetlands Planning, Protection, and Restoration 

Act (CWPPRA). 

Elaine Evers received her B.S. in 1977 from the University of Houston and her M.S. in 1990 

from LSU. She has worked for the past 26 years as a wetland ecologist with LSU, including 

benthic ecology and ecological work using GIS systems, including mapping vegetation species 

composition of flotant and non-floating marshes and wetland change over time. 

Glenn M. Suir received his B.S. from the University of Louisiana at Lafayette in 1999 and his 

M.S. in 2002 from LSU, where he is currently a Ph.D. candidate in the Department of 

Oceanography and Coastal Studies. For the past five years he has worked for state and federal 

governments providing data management and spatial analysis support for wetland vegetation 

planting programs, wetland restoration projects, and coast-wide monitoring programs. Glenn is 

currently a research associate for Louisiana State University Agricultural Center Department of 

Agronomy, where his research is focused on water quality monitoring and modeling, and the use 

of GIS to assess landscape patterns and develop ecological and landscape models. 
475 

LOUISIANA COASTAL VEGETATIVE TYPE CHARACTERIZATION MAPS 

Greg Linscombe, Louisiana Department of Wildlife and Fisheries 

John Barras and Steve Hartley, USGS National Wetlands Research Center 

Introduction 

Coastal Louisiana has numerous data sets to conduct marsh change analyses. Most of these 

studies have used either the National Wetlands Inventory Data (1956, 1978, 1988) or the 

Vegetative Type Maps (1949, 1968, 1978, 1988, 1997) (Chabreck et al. 2001). Recently, the 

United States Geological Survey (USGS) Biological Resources Division (BRD)/National 

Wetlands Research Center (NWRC) and the Louisiana Department of Wildlife and Fisheries Fur 

and Refuge Division (LDWF) completed the development of the 2001 Vegetative Type Map for 

Louisiana. This data set and others are a cumulative effort to map and portray the ever-changing 

coastal vegetative types. Because of the technology used in the past to map the vegetative types, 

however, we can not reflect, within reason, the “true” amount of marsh acreages. To make better 

use of the 2001 and other (1978, 1988, 1997), a new methodology must be adopted to calculate 

marsh acreages. 

Proposal Synopsis 

Geographic information systems (GIS) will be used to develop a comprehensive land/water 

interface for coastal Louisiana using the 1998 Digital Ortho-Quarter Quadrangles (DOQQs). We 

propose to use this land/water interface and ancillary photography to classify LANDSAT 

imagery to the closest available corresponding vegetative marsh type map dates. The classified 

land/water data sets would then be merged with each corresponding vegetative marsh type map 

to produce improved vegetative data sets, which then could be used to show “true” marsh 

acreage changes. 

Objectives 

• Develop improved vegetative type databases and maps for 1978, 1988, 1997, and 2001 

Louisiana coastal areas. 

• Develop a detailed coast-wide land/water interface that can be used by numerous studies 

relating to habitat loss, pipeline erosion, and navigable waterways. 

• Provide information that resource managers can utilize in a variety of applications related 

to their mission, such as: 

⎯ Environmental Impact Statement Preparation 

⎯ Pipeline Assessments 

⎯ Natural Resource Damage Assessments 

⎯ Vegetative Assessments 

⎯ Navigable Waterway Assessments 
476 

Products 

• Maps showing marsh types for each time period with associated acreage tables. 

• Map showing marsh type change analysis. 

• Visual animation file of coastal marsh change. 

• Complete coverage of land/water interface digitized from the 1998 DOQQs. 

• Digital copy of all classified and raw TM data. 

References 

Chabreck, R.H., G. Linscombe, S. Hartley, J. Johnston, and A. Martucci. 2001. Coastal 

Louisiana Marsh-vegetative Types: Report to Coastal Wetlands Planning, Protection and 

Restoration Act and the Louisiana Dept. of Wildlife and Fisheries. US Geological 

Survey, National Wetlands Research Center, Lafayette, LA. 

Steve Hartley is a Senior Geographer at the USGS National Wetlands Research Center. He 

received his B.S. degree in 1985 from Louisiana Tech University and his M.S. in geology from 

the University of Louisiana at Lafayette in 2000. He is responsible for the installation, 

configuration and overall maintenance of software, hardware and networking for GIS operations. 

His specific duties include managing and coordinating GIS projects, performing image analysis, 

developing prototype GIS products, troubleshooting, quality control, personnel management and 

training, and client-interfacing and correspondence. 

John Barras is employed as a Senior Geographer at the USGS National Wetlands Research 

Center. He received his B.S. in geology from Nicholls State University in 1984 and his M.N.S. in 

geography from LSU in 1991. He is responsible for managing the NWRC’s Coastal Restoration 

Field Station (CRFS), housed on the Louisiana State University Campus in Baton Rouge, 

Louisiana. The CRFS provides applied GIS and remote sensing support for several state, federal, 

and academic partners involved in coastal wetland restoration and natural resource management 

activities via staff at LSU or on-site staff collocated with the partner agency. 

Greg Linscombe has been employed by Louisiana Department of Wildlife and Fisheries since 

1972 and is currently a Program Manager for the Fur and Refuge Division. He received his B.S. 

degree in forestry and wildlife management from LSU in 1970 and his M.S. in wildlife 

management from LSU in 1972. During his career he has been responsible for management on 

230,000 acres of public wetlands (refuges and wildlife management areas) and is currently 

responsible for marsh ecology on 420,000 acres of these lands. He has published over 40 

scientific papers dealing with furbearers and wetlands ecology and has produced four vegetative 

type maps of coastal Louisiana. 
477 

SESSION 1I 

DEEPWATER PHYSICAL OCEANOGRAPHY INITIATIVE, PART I 

Chair: Alexis Lugo-Fernandez, Minerals Management Service 

Co-Chair: Carole Current, Minerals Management Service 

SURVEY OF DEEPWATER CURRENTS IN THE NW GULF OF MEXICO – 

AMERICAN SECTOR Evans Waddell..................................................................................... 479 

SURVEY OF DEEPWATER CURRENTS IN THE EASTERN GULF OF MEXICO 

Jeffrey M. Cox ............................................................................................................................ 483 

A CLIMATOLOGY OF OCEAN FEATURES IN THE GULF OF MEXICO 

Fred Vukovich ............................................................................................................................ 489 

CURRENTS AT THE SIGSBEE ESCARPMENT Nan D. Walker, Steven P. Anderson, 

Robert R. Leben.......................................................................................................................... 491 
479 

SURVEY OF DEEPWATER CURRENTS IN THE NW GULF OF MEXICO – 

AMERICAN SECTOR 

Evans Waddell, Science Applications International Corporation 

In September 2003, the MMS awarded a contract to Science Applications International 

Corporation (SAIC) to conduct a 40-month study of circulation patterns and processes in the 

deepwater of the northwestern Gulf of Mexico (GOM). 

Program Objectives 

 1. To collect current data to increase our deepwater database and knowledge of the deep 

circulation in the northwestern GOM. 

 2. To gather information to estimate oceanographic parameters needed to make 

experimental designs of full-scale physical oceanography studies in deepwater. 

 3. To provide information for use in oil-spill analyses, including the emerging deep-spill 

analysis and other ongoing studies; to help evaluate exploration plans; and to contribute 

to the preparation of NEPA documents. 

To help focus the analysis and interpretation effort, the project science team identified 11 

potential hypotheses that can be evaluated to support reaching the above goals. 

The study area boundaries are defined by the EEZ on the south (approximately 26°N), the 200 m 

isobath on the west and north, and 93°W on the eastern edge (Figure 1I.1). The one-year ongoing 

measurement program began in March 2004 and is composed of thirteen full-depth instrumented 

moorings placed in various water depths. The instrumented moorings are supported by 

coordinated altimetry, radiometry and visual band remote sensing. After the program was 

initiated, the MMS chose to fund a proposed option involving placement of approximately ten 

Inverted Echo Sounders with Pressure (PIES) at appropriate locations relative to both the 

moorings and altimetry tracklines in the study area.(Figure 1I.2). 

Using an empirically based analysis method, Gravest Empirical Mode (GEM), the travel time 

measured by the PIES can provide estimates of the depth of temperature, salinity, and density 

surfaces. Using density profiles and bottom pressures, geostrophic velocities can be computed 

and referenced with near-bottom velocities measured on the moored arrays. The directly 

measured and PIES-based information will combine to provide well-resolved characterizations 

of the temperature and salinity field within which the measured currents are occurring. 
480 

Figure 1I.1. General study area for NW Gulf Study – American Sector. 

The general vertical placement of instruments is as follows: 

Currents: Each full-depth moorings has an ADCP to measure currents in the upper portions of 

the water column. In water depths > 500 m, 75 kHz ADCPs are used. On the three 500 m 

moorings, 300 kHz ADCPs are used. Below the ADCPs and above 1,000 m, current meters are 

placed at ∆z ≤ 250 m,; below 1,000 m, current meters are placed at ≈ 500 m spacing. Depending 

on water depth, the lowest/deepest current meter is always approximately100 m above the local 

bottom. 

Temperature and Conductivity: Appropriate sensors are attached to the wire above the ADCPs. 

All moorings have temperature sensors at ≈100, 150, 250, 375, and 500 m. All current meters/ 

profilers provide temperature sensors. Conductivity is measured with a MicroCat or SeaCat at 

150 m in an effort to define the presence of the subsurface salinity maximum. 
481 

Figure 1I.2. Placement of American Sector Moorings (filled red circles), and PIES (filled green triangles). 

PIES: PIES are self contained and positioned in a cradle on the bottom. Observations being made 

include acoustic round-trip travel time from the instrument to the water surface and precise 

bottom pressure measurements. 

Key Project Team Members 

Science 

• Dr. Peter Hamilton – SAIC 

• Dr. Robert Leben – University of Colorado 

• Dr. Randy Watts – University of Rhode Island 

• Dr. Kathleen Donohue – University of Rhode Island 

Project 

• Dr. Evans Waddell – SAIC 
482 

• Mr. James Singer – SAIC 

• Mr. Paul Blankinship – SAIC 

Science Review Group 

• Dr. John Bane – University of North Carolina 

• Dr. Tony Sturges – Florida State University 

• Mr. David Driver – BP 

Dr. Evans Waddell has worked at SAIC for approximately 28 years, most often as the manager 

of larger field measurement and analysis programs, often in the Gulf of Mexico. He is presently 

the Project Manager for the above program as well as the ongoing, MMS-funded Exploratory 

Study of Deepwater Currents in the Gulf of Mexico, which involves a broadly-based team of 

scientists involved in the acquisition, analysis, and interpretation of an extensive set of 

measurements over the deeper slope of the north central Gulf. He is also an Assistant Vice 

President and a Senior Oceanography for SAIC. Dr. Waddell received a B.A. and M.A. from the 

University of Virginia and a Ph.D. in marine science (physical oceanography) from Louisiana 

State University (1973). Prior to joining SAIC in 1977, he was an Assistant Professor of Marine 

Science at Purdue University and a Visiting Researcher at the Coastal Engineering Laboratory of 

the University of Tokyo. 
483 

SURVEY OF DEEPWATER CURRENTS IN THE EASTERN GULF OF MEXICO 

Jeffrey M. Cox, Evans-Hamilton, Inc. 

Recent deepwater oil and gas leases in the eastern Gulf of Mexico (GOM) extend beyond water 

depths of 1,600 m in an area that is periodically strongly influenced by the Loop Current (LC), 

Loop Current Eddies (LCEs), and associated LCE features such as frontal eddies and filaments. 

Bathymetry in the study area permits probably the most northerly movement of these features 

within the GOM (Figure 1I.3). Preliminary results presented by Dr. Peter Hamilton from the 

Exploratory Study in the central GOM also suggest that this area may be either a potential source 

region for certain wavelengths of topographic Rossby waves (TRWs) or an area traversed by 

them. 

Figure 1I.3. Eddy Zapp with a frontal eddy/filament within the study area. 

This area is sparsely measured for currents where water depths exceed 1,500 m (Figure 1I.4). For 

the MMS to fulfill its regulatory function proactively, more data on currents and a better 

understanding of the circulation in this area are needed. Specific study objectives are therefore to 

conduct measurements of deepwater currents using moorings to increase MMS’s and the 

scientific community’s database of ocean currents in the eastern GOM, and to improve 

understanding of the regional oceanography to help design future studies as well as to assist in 

the modeling of trajectories of released oil and its dispersion in this area. 
484 

Figure 1I.4. Historical current measurement in eastern GOM vs. study area location. 

Study Area 

The study area is that area of the Eastern Gulf Lease Sale 181. This area lies off the mouth of 

DeSoto Canyon and is bounded approximately by the following coordinates: 

NW Corner: 28.848o

N, 87.918oW NE Corner: 28.850oN, 87.523oW 

SW Corner: 27.453o

N, 87.907oW SE Corner: 27.455oN, 87.516oW 

The study area has multiple interesting bathymetric features potentially affecting circulation in 

this region, including that: 

• The area is bounded to the north and northwest by slopes incised by hills and valleys. 

• The steep West Florida Escarpment intersects a portion of the eastern boundary of the 

study area. 
485 

• The entrance to DeSoto Canyon lies adjacent to the northeast corner of the study area. 

• Area contains primarily NNE to SSW oriented isobaths, rather than E-W isobaths. 

• Area contains the farthest northward extent of the 2,000 m isobath in the GOM. 

• The area lies within the area of the largest separation between the 2,000 and 3,000 m 

isobaths within the GOM. This area has a large, relatively flat bottom. 

Circulation Processes of Interest 

Following are the key circulation processes considered in the experimental design as potentially 

affecting the circulation in the study area: 

• Loop Current (LC) & Loop Current Eddy (LCE) intrusions 

• LCE frontal cyclonic and anti-cyclonic eddies 

• Midwater jets 

• LC/LCE dynamics 

• Eddy-eddy interactions 

• Eddy-topography interactions 

• Baroclinic instabilities 

• Geostrophic turbulence 

• TRW Genesis by LC northward movement vs. LCE shedding 

• TRW Propagation, Refraction & Reflection from Deep Water onto Slope 

• Coupling or interactions between upper & lower layers 

Measurement Program 

The measurement program is designed to obtain an integrated set of current, hydrography, 

remote sensing, and ancillary measurements that will permit an excellent understanding of the 

regional scale circulation features affecting the study area. The hydrographic measurement 

program was also designed to be able to sample small scale (10–25 km) features should they 

occur in the study area during mooring deployment and hydrographic sampling cruises. All 

aspects of the measurement program are being coordinated with other MMS researchers to insure 

consistency in measurement instrumentation, techniques, and sampling intervals so as to 

maximize the inter-comparability of the measurements between MMS studies. 

The measurement program consists of the follow key components: 

• Three tall moorings reaching from 70 m depth to bottom at 2,600 or 2,800 m depths 

• One short mooring reaching from bottom at 2,750 m depth to 2,500 m depth 

• Seven PIES deployed surrounding and interspersed with the moorings 

• Three hydrographic surveys (during deployment, servicing, and recovery cruises) 

• Remote sensing altimetry and AVHRR imagery 

• Ancillary measurements from NDBC buoys, local river runoff 
486 

Locations of the moorings and PIES (Figure 1I.5) were selected to maximize coverage of the 

study area while maintaining scales to conduct along and across isobath coherence analysis. 

Locating one mooring as far south as possible to maximize measuring the effects of the LC, or a 

LCE, ACE, or frontal eddy, was also a priority. The northernmost mooring was placed to also 

assess the potential intensification of the current along the Florida escarpment.

Figure 1I.5. Mooring (M1–M4) and PIES (P1–P7) deployment locations. Mooring M4 is the short mooring. 

The current meter moorings were designed to provide excellent vertical resolution of currents 

throughout water column and to provide excellent temperature structure in the upper 500 m so as 

to measure the presence and strengths of LCE and ACE events to correlate to the remote sensing 

data. Instrumentation on the tall moorings consists of: 

• Three moorings containing upward looking 75 kHz ADCP at 500 m depth, InterOcean S4 

current meters at 750 m, and Aanderaa RCM7/8 meters at 1,000, 1,250, 1,500, 2,000, 

2,500, & bottom +100m depths. Temperature is also measured on all current meters. 
487 

• All 3 moorings contain T/C/P measurements at 75, 150, and 225 m depths. 

• All 3 moorings also contain T only measurements at 100, 190, 225, and 325 m depths, 

thus providing T measurements at a total of 14 depths per mooring. 

The short mooring consists of two Aanderaa current meters placed at 100 m above the bottom 

and at 2,500 m depth for consistency with the three tall moorings. 

Hydrographic measurements will be collected with a combination of CTD casts and XBTs. Deep 

CTD casts (to near-bottom) will be obtained at each mooring location, as well as each PIES 

location. Shallower (to 1,200 m depth) casts will be obtained at multiple additional locations. 

XBT’s will be launched between CTD stations to provide ~10 km resolution of temperature. 

Remote sensing data will be viewed prior to each cruise to plan CTD and XBT measurement 

locations that can best cover any interesting circulation feature in the study are at the time of the 

cruise. 

Shipboard ADCPs aboard the R/V Pelican will be operated during each mooring cruise to 

provide a better horizontal perspective of the circulation in the upper 500 m during the period of 

the cruises. 

Study Schedule 

PIES deployments occurred during December 19-22, 2004. The deployment of the four moorings 

and first hydrographic survey are scheduled for January 17-24, 2005. These have been 

successfully completed. Servicing of the moorings and the second hydrographic survey are 

scheduled for August 17-24, 2005. Recovery of the moorings and the third hydrographic survey 

are scheduled for late January 2006. 

Study Team 

The study team consists of the following key scientists. While the complete measurement data 

set will be made available to all PIs on the team, and all PIs will assist in interpreting the 

complete data set, there particular areas of responsibility are also listed below. 

• Mr. Jeff Cox (EHI) – Project Manager 

• Mrs. Carol Coomes (EHI) – Assistant Project Manager, Data Manager 

• Mr. Keith Kurrus (EHI) – Chief Scientist on cruise, Sr. Instrumentation Specialist 

• Dr. Peter Hamilton (SAIC) – PI – Upper/lower layer interactions, formation and effects 

of TRWs 

• Dr. Robert Leben (University of Colorado) – PI – Remote sensing 

• Dr. Steve DiMarco (Texas A&M) – PI – LCE/ACE/frontal eddy effects, upper/lower 

layer interactions 

• Dr. George Forristall – PI – LCE/ACE/frontal eddy effects, slope intensification of 

currents, oil industry perspectives 
488 

• Drs. Randy Watts & Kathleen Donahue (University of Rhode Island) – PI – PIES, 

geostrophic flow 

The study team was built to provide MMS consistency in the analysis of measurements between 

its major GOM measurement programs, as well as the historical data reanalysis project. The team 

also provides extensive knowledge of oil and gas industry perspectives. Initial results from this 

study will be available at the next MMS Information Transfer Meeting in 2007. 

Jeffrey M. Cox is President and a Senior Oceanographer at Evans-Hamilton, Inc. He joined 

Evans-Hamilton in 1977, and has 27 years of experience conducting physical oceanographic, 

meteorological, and coastal water quality studies. Mr. Cox’s present responsibilities include 

overall business development and company operations, as well as the planning and oversight of 

large complex and multidisciplinary physical oceanographic projects. 
489 

A CLIMATOLOGY OF OCEAN FEATURES IN THE GULF OF MEXICO 

Fred Vukovich, Science Applications International Corporation 

A climatology of certain ocean features in the Gulf of Mexico (GOM) was developed using 

satellite remote sensing data sets that span periods as long as 32 years and in-situ data and 

information. The satellite data that are used in this study include sea-surface temperature (SST) 

data from radiometers aboard TIROS-M, HCMM, SEASAT and the numerous NOAA polar 

orbiting satellites; ocean color data from the CZCS, which was aboard the Nimbus polar orbiting 

satellite, SeaWiFS, and MODIS; and altimeter data from the TOPEX/Poseiden and the ERS 

systems. These data were supplemented with in-situ data from ships of opportunity, from field 

programs in the GOM, and from the projects managed by the various oil and gas companies. 

Twelve (12) separate statistics were created, some of which described characteristics of the Loop 

Current, while others are involved with warm core rings that separate from the Loop Current and 

cold core rings. The specific statistics are: 

 1. Spatial frequency of Loop Current water in the Eastern GOM (EGOM). [Database 

period: 1976–2003]; 

 2. Spatial frequency of warm water associated with major WCRs in the Western GOM. 

[Database period: 1977–2003] 

 3. Spatial frequency of centers of WCRs in the GOM (based on the location of the centers 

of both major and minor WCRs). [Database period: 1977–2003] 

 4. Frequency of the path of major WCRs in the Western GOM (based on three potential 

ring-path subdivisions [i.e., northern path, central path, and southern path]). [Database 

period: 1976–2003] 

 5. Frequency of the speed of major WCRs in the Western GOM [Database period: 1972–

2003] 

 6. Mean decay of the size of the major WCRs (Ring Dissipation) [Database period: 1976–

2003] 

 7. Frequency of the separation of major eddy shedding periods from the Loop Current. 

[Database period: 1972–2003] 

 8. Periods of oscillation of the Loop Current’s Northern Boundary. [Database period: 

1977–2003] 

 9. Frequency of the orientation of the Loop Current. [Database period: 1976–2003] 

 10. Spatial frequency of Loop Current water in the EGOM not directly associated with the 

Loop Current or with major WCRs (This water mass is, for the most part, associated 

with minor WCRs and with the advection of warm Loop Current water by cold core 

rings [CCRs]). [Database period: 1976–2003] 

 11. Spatial frequency of intrusions of Loop Current water onto the West Florida Shelf. 

[Database period: 1976–2203] 

 12. Spatial frequency of centers of CCRs in the GOM. [Database period: 1992–2003] 
490 

The principal data set, but, however, not the only data set, used to derive the statistics is monthly 

analyses of the fronts in the GOM, which were created using an integral of available satellite 

clear-sky images (i.e., satellite SST, ocean color, and altimetry imagery) and of any available 

information on ocean features and/or analyzed in-situ data for the month in question. These 

analyses provided the “characteristic” position of the fronts in the GOM for a given month. The 

LC front in these analyses was the approximate average front for the month unless a WCR 

separated from the LC during that month. Then, it was the position of front after separation has 

occurred. WCR fronts are the approximate average front for the month. If warm LC water mass 

not directly associated with the LC or with major WCRs was found in the EGOM in a given 

month, then it was represented in the frontal analysis by its most widespread effect in the EGOM 

for that month. If an intrusion of warm LC water onto the West Florida Shelf was found in the 

EGOM in a given month, then it was also represented by its most widespread effect on that shelf 

for that month. 

It is hoped that the information derived from this integrated climatology may be useful in 

planning field programs, to marine biologists and oceanographers for processes studies in the 

GOM, and as background information for environmental impact statements (EISs). It has also 

been shown that the information from a climatology can useful in evaluating and directing 

improvements for models that calculate the ocean dynamics in the GOM. 

Dr. Fred Vukovich is a Chief Scientist for Science Applications International Corporation. He 

has been involved in oceanographic studies using remote sensing data from satellites such as 

TIROS-N, NIMBUS, NOAA, HCMM, , GOES, TOPEX, SEASAT, ERS-1, ERS-2, SeaWiFS, 

and MODIS, for thirty years. His research has focused on the Gulf Stream off the southeast coast 

and on the Gulf of Mexico. For the last twenty-five years, he has focused on studies in the Gulf 

of Mexico. 
491 

CURRENTS AT THE SIGSBEE ESCARPMENT 

Nan D. Walker, Coastal Studies Institute and Department of Oceanography and 

Coastal Sciences, Louisiana State University 

Steven P. Anderson, Horizon Marine, Inc. 

Robert R. Leben, Center for Astrodynamics Research, University of Colorado 

Abstract 

During the August 2001 through May 2002 period, strong surface currents (> 100 cm s-1) 

resulted from an intrusion of the Loop Current over the mooring site, the separation and passage 

of Loop Current warm-core eddies, and flow intensification due to cyclone/anticyclone 

interactions. Relatively strong bottom currents were experienced nearly simultaneously with 

many of these dynamic surface current events. The timing of the bottom current events varied, as 

some occurred nearly simultaneously with surface events while others lagged the surface events 

by several days. During most events, flow direction was similar from surface to bottom. The 

integration of GOES SST composite imagery with contoured SSH data revealed that some of the 

strong southwestward currents at the bottom along the escarpment occurred when Loop Current 

frontal eddy cyclones moved rapidly into regions of well-developed cyclonic circulation near the 

mooring site. Other events appeared to be closely linked with rapid movements of the Loop 

Current toward the escarpment. The strongest bottom currents in the opposite direction, to the 

northeast, occurred as warm-core eddies moved southwestward, south of the mooring site. Thus, 

the bottom-currents, at least during this period, were closely linked with surface processes. The 

potential effects of bottom trapped topographic Rossby waves were not clearly revealed by this 

analysis and bottom currents were not as strong as those discussed by Hamilton and LugoFernandez (2001) farther to the east along the escarpment. 

Introduction 

On 31 July 2001 a full water column mooring was deployed at a depth of 2,960m seaward of the 

southern section of the Sigsbee Escarpment at 26° 20.23’N and 90o 45.93’W (Figure 1I.6). 

Measurements included current speed/direction, temperature, conductivity, and pressure at 

eighteen discrete depths. The main objective of this research project is to characterize current 

behavior near the bottom as well as to investigate the relationships between the bottom 

circulation and surface circulation. Additional measurements obtained from satellites and drifting 

buoys are being used to interpret the current information. Remote sensing data include GOES 

night-time sea surface temperature (SST) composite images, satellite altimeter data of sea 

surface height (SSH), and ocean color measurements from Orbview-2 SeaWiFS and Oceansat-1 

OCM. An extension to the project enabled the collection of an additional fourteen months of data 

from 19 April 2003 to 6 June 2004. This paper focuses on the first series of measurements that 

were made from 31 July 2001 2 to June 2002. 
492 

Figure 1I.6. Bathymetric contour map of the Sigsbee Escarpment and the location of the LSU mooring from 

31 July 2001 to 2 June 2002. 

Data Collection and Analysis 

Current speed and direction were measured using Acoustic Doppler Current Meters (ADCPs) 

and Aanderaa RCM-7 and RCM-8 instruments. Upward-looking ADCPs were deployed at 

depths of 136m and 614 m. Ten Aanderaa current meters were deployed at depths of 146, 633, 

878, 1128, 1378, 1628, 1878, 2128, 2578, and 2878m. Microcats were deployed at water depths 

of 148, 635, 978, 1278, 1630, and 2130m. Data return and data quality were excellent, and little 

editing of the data was needed. The currents were low-pass filtered using a 40-hour Butterworth 

filter to remove tidal and inertial frequencies. Data processing was performed using MATLAB 

and other graphic software. 
493 

Satellite imagery from the GOES GVAR, SeaWiFS, and OCM were obtained in real time and 

processed at the LSU Earth Scan Laboratory (http://www.esl.lsu.edu). GOES night-time SST 

composites were used extensively to detect and track ocean features with daily updates. The 

night-time compositing process enables removal of substantial cloud contamination by using a 

ten hour sequence of imagery (Walker et al. 2003) and the result is a daily update of SST 

information. Additional imagery from SeaWiFS and OCM revealed pigment patterns that were 

often helpful in detecting flow fields associated with eddies. Sea surface height (SSH) 

measurements from Dr. Bob Leben were superimposed on the SST composites as an aid to 

interpretation of eddy locations. In addition, an ongoing collaborative project with Horizon 

Marine Inc. has enabled the use of drifting buoy data that is also an important aid to 

interpretation of rapid changes in the eddy field at the study site. 

Results and Discussion 

The entire time series of low-pass filtered currents from all instruments are displayed in Figure 

1I.7. Strongest currents were measured near the surface, where a speed maximum of 133 cm s-1 

occurred in mid- February 2002. Surface current speeds exceeded 100 cm s-1 during four separate 

events in the February through April 2002 period. These strong currents resulted from the 

northwestward surge of the Loop Current over the study site and separation of Loop Current 

eddies, ‘Pelagic’ and ‘Quick,’ in rapid succession. 

The graphic of current vectors (Figure 1I.7) clearly shows a coherence of currents in the top 

650m of the water column, with minimum flow at 1,128 m. Near-surface currents for the 40–

60m depth range averaged 38 cm s -1 over the entire time series. At 1,128m, currents averaged 

5.9 cm s -1. Current behavior was also quite coherent between 1,378m and 2,878m and weak 

bottom intensification was noted. At 2,878m, the mean current speed was 11.1 cm s -1 and the 

maximum speed was 37.4 cm s -1. Current statistics, computed from the unfiltered data, are 

tabulated for selected depths in Table 1I.1. 

Most of the bottom-current variability was in the northeast-southwest direction, an alignment 

that followed the escarpment, but not the bottom topography. The orientation of surface currents 

was variable in nature, with no dominant principal axis. 

Ten along-escarpment bottom-flow events to the northeast and eleven to the southwest were 

observed in the record (Figure 1I.7). Bottom current reversals along the escarpment occurred 

every 14 days, on average. Several surface-intensified high-velocity flow events occurred during 

this time period, which were associated with a northwestward surge of the Loop Current, the 

separation of Loop Current eddies over the mooring, and associated cyclones. 

The strongest surface and bottom currents occurred in early December 2001 and between midJanuary and the end of May 2002, when the Loop Current, warm-core eddies, and cyclones were 

most prevalent in the study area. During several events, accelerations in bottom flow were 

correlated with surface flow and, in a few cases, current direction was consistent from surface to 

bottom. A brief discussion of six events follows. 
494 

Figure 1I.7. Graphic showing stick vectors of low-pass filtered currents at selected depths from 31 July 2001 

to 2 June 2002. The 50, 100, 200, 300, 500m bins are 20m averages from the ADCP 

measurements, that were adjusted for mooring blow-over. The blue lines depict alongescarpment flow events to the northeast and red lines depict along-escarpment flow events to the 

southwest. 
495 

Table 1I.1. Statistics of currents at selected depths. Scalar and vector speeds are in cm s-1. No filtering or axis 

rotation was performed. Positive ‘U’ components show eastward flow and positive ‘V’ 

components show northward flow. The ‘n’ indicates number of observations. The 50, 100, 200, 

300, and 500 m depths are 20m averages of ADCP currents. 

Strongest bottom currents were measured in the along-escarpment direction, to the northeast 

(Figure 1I.7). During the two main events (labeled 1 and 6 on Figure 1I.7) warm-core eddies and 

associated cyclones passed in close proximity to the mooring. During event 1 in early December 

2001, the center of a warm core eddy was located north of the mooring, and westward surface 

flow was experienced. Cyclones were located south of the eddy and farther west along the 

escarpment. Acceleration in surface and bottom currents occurred nearly simultaneously. Surface 

currents reached 78 cm s-1 and bottom currents reached 30 cm s-1. During event 6 in May 2002, a 

larger warm-core eddy passed south of the mooring and surface currents were not much stronger 

than the bottom currents (46 and 36 cm s-1, respectively). During event 1, bottom and surface 

currents were in opposition, whereas in event 6 they flowed in the same general direction. 

During event 5, in the latter part of April, acceleration in bottom currents lagged acceleration at 

the surface by about one week. This event coincided with the southwestward movement of Quick 

Eddy south of the mooring site (Figure 1I.8a). Geostrophic currents at the mooring site were 

maximized as a well developed cyclone abutted with the large warm-core eddy on its northwest 

margin. It is interesting to note that the currents within the 630 to 1,378m depth range were 

unusually strong (compared with the rest of the record) from mid-April to late May. 

The strongest along-escarpment currents, to the southwest, occurred from January through 

March 2002. Two events (3 and 4 in Figure 1I.7) were short-lived events (3-days) and were 

characterized by speeds of 25–30 cm s-1 at 2,878m (Figure 1I.7). During both events, 

southwestward flow occurred throughout the water column, and surface and bottom flow 

intensified nearly simultaneously. The first of these short-lived events (event 3) was characterized by a rapid transition from northeast to southwest flow. The GOES image sequence from 

24 to 27 February revealed a surge of the Loop Current towards the escarpment just prior to the 

onset of southwestward flow that was relatively strong from 27 Feb to 2 March 2002. 

 
496 

Figure 1I.8. Color enhanced GOES SST composite imagery superimposed with contours of SSH data for (top 

panel) 16 April 2002 and (bottom panel) 15 March 2002. The mooring site is shown with a red 

dot. Positive SSH are solid and negative SSH are dashed. The top panel shows Quick Eddy with 

a center southeast of the mooring and the bottom panel shows both Pelagic Eddy (to the west) 

and Quick Eddy, separated by a large cyclone. 
497 

The second of these short-lived events (event 4 in Figure 1I.7) was also studied in detail using 

GOES SST composites in tandem with SSH data. In mid-March 2002, the mooring was situated 

on the northeast flank of a cyclone (Figure 1I.8b). Strong geostrophic currents were indicated by 

the SSH data as the cyclone was adjacent to Quick Eddy, that had just recently separated from 

the Loop Current. A time history of GOES SST image composites revealed rapid northward 

movement of a frontal eddy cyclone along the western side of Quick Eddy. The GOES SST/SSH 

image for 15 March shows the location of Quick Eddy and the cyclone in relationship to the 

mooring site that is depicted with a red dot (Figure 1I.8b). The frontal eddy cyclone, located 

along the western margin of Quick Eddy, appears as a warm meander at the surface due to the 

entrainment of warm water away from the eddy. Strong bottom currents, to the southwest, 

occurred as the frontal eddy cyclone moved over the mooring, soon after intensification of 

surface flow. This event was relatively short-lived at the bottom, as southwestward currents 

lasted from 17 to 20 March. 

Prior to these two strong short-lived events, a prolonged period of southwestward flow was 

experienced from 25 December to 22 January. It was associated with the extreme westward 

intrusion of the Loop Current and separation of Pelagic Eddy. 

References 

Hamilton, P. and A. Lugo-Fernandez. 2001. Observations of high speed deep currents in the 

northern Gulf of Mexico. Geophysical Research Letters 28(14):2867–2870. 

Walker, Nan, S. Myint, A. Babin, and A. Haag. 2003. Advances in satellite radiometry for the 

surveillance of surface temperatures, ocean eddies and upwelling processes in the Gulf of 

Mexico using GOES-8 measurements during summer. Geophysical Research Letters 

30(16):1854, doi:10.1029/2003GL-17555. 

Dr. Nan D. Walker is an Associate Professor in the Department of Oceanography and Coastal 

Sciences and Director of the LSU Earth Scan Laboratory. She has 24 years of experience in the 

field of satellite remote sensing of coastal and ocean processes. Her research interests include 

estuarine-shelf circulation, coastal upwelling, Loop Current and eddy circulation, coastal sediment transport, physical-biological interactions, and ocean climatology. She received her B.S. in 

marine zoology from Duke University, M.S. in marine science from Louisiana State University, 

and Ph.D. in physical oceanography from the University of Cape Town, South Africa. 

Dr. Steven P. Anderson is Chief Scientist at Horizon Marine, Inc. Dr. Anderson’s research 

interests include air-sea interaction, upper ocean dynamics and ocean observing systems. Dr. 

Anderson received a B.S. in mechanical engineering from Lafayette College and a Ph.D. in 

applied ocean sciences from the Scripps Institution of Oceanography, University of California, 

San Diego. 
498 

Dr. Robert R. Leben received the B.S., M.S., and Ph.D. degrees in aerospace engineering 

sciences from the University of Colorado, Boulder in 1981, 1982 and 1986, respectively. Since 

1986, he has been employed at the Colorado Center for Astrodynamics Research at the 

University of Colorado, Boulder, where he is an Associate Research Professor. His research 

interests include satellite altimetry and its application to monitoring ocean circulation. 
499 

SESSION 2G 

DEEP GULF OF MEXICO CHEMOSYNTHETIC COMMUNITIES: 

CURRENT KNOWLEDGE FOR SITES BELOW 1,000 METERS 

Chair: Greg Boland, Minerals Management Service 

Co-Chair: James Sinclair, Minerals Management Service 

HYDROCARBON SEEP REGIMES IN THE GULF OF MEXICO CHEMOSYNTHETIC 

COMMUNITIES, REMOTE SENSING, BIOGEOGRAPHY Ian R. MacDonald................... 501 

CHALLENGES FOR INTERPRETATION OF SEAFLOOR GEOLOGY-BIOLOGY IN 

DEEP AND ULTRA-DEEP WATER, GULF OF MEXICO Harry H. Roberts....................... 504 

BIOGEOGRAPHY AND BIODIVERSITY OF COLD SEEPS IN THE GULF OF MEXICO 

Charles R. Fisher and Erik E. Cordes ......................................................................................... 508 

DEEP GULF OF MEXICO CHEMOSYNTHETIC COMMUNITIES: CURRENT 

KNOWLEDGE FOR SITES BELOW 1,000 METERS. RECENTLY DISCOVERED 

ASPHALT VOLCANO AND ASSOCIATED CHEMOSYNTHETIC COMMUNITIES 

IN THE SOUTHERN GULF OF MEXICO Elva Escobar-Briones.......................................... 514 

RECOVERY OF DISTURBED DEEP-SEA COMMUNITIES Craig M. Young.................... 521 

DEEPEST GULF OF MEXICO HYDROCARBON SEEP CHEMOSYNTHETIC 

COMMUNITY IN BLOCK AC 818 AND OTHER ROV OBSERVATIONS IN 

THE DEEP GULF Dan Allen.................................................................................................... 523 
501 

HYDROCARBON SEEP REGIMES IN THE GULF OF MEXICO CHEMOSYNTHETIC 

COMMUNITIES, REMOTE SENSING, BIOGEOGRAPHY 

Ian R. MacDonald, Texas A&M University – Corpus Christi 

Twenty years of research in the northern Gulf of Mexico (GOM) have assembled an unequaled 

overview of the benthic chemosynthetic communities supported by fluid seepage in a marine 

basin. Sources of the chemical substrata these communities require include conate fluids, CH4 in 

free, dissolved, and clathrate form and high-molecular weight hydrocarbons in liquid and solid 

form. Recent findings from the Gulf document structural and taxonomic affinities that now span 

the entire basin. 

Communities of tube worms including and undescribed escarpid and seep mussels 

(Bathymodiolus heckeri) were discovered among jointed carbonates and associated rubble at the 

base of the Florida Escarpment (3,270m water depth) in 1984 (Paull et al. 1984). In 1990, the 

similar species were found in a very similar setting, but on the opposite side of the basin at 

2,800m in Alaminos Canyon (Brooks et al. 1990). Discovery of asphalt volcanism and associated 

chemosynthetic communities in the Campeche Knolls (3,000m) document a new seep process 

(MacDonald et al. 2004), but appears to have taxonomic affinity with the Florida Escarpment 

and Alaminos Canyon sites. Interestingly, the Campeche Knoll findings were partially 

anticipated by a 1971 photograph from the Sigsbee Knolls in the GOM abyss (Pequegnat and 

Jeffrey 1978). In contrast, the seeps of the Green Canyon in the northern at slope depths (500–

2,000m) appear to comprise a distinct zoogeographic province, a broad depth range, and distinct 

geologic styles. 

Satellite remote sensing of the GOM hydrocarbon system is a tool for filling in these gaps and 

extending the Gulf seep model to analogous areas in the Caribbean and West Africa. The current 

compilation of remote sensing targets—many of which having been confirmed by seafloor 

collections—confirm the basin-wide distribution (Figure 2G.1). They also illustrate that 

hydrocarbon seeps support a remarkable ecosystem. Major questions that are the subject of 

active research include determining the role of this ecosystem in the global and region carbon 

cycle. In other ocean settings, microbiologists are investigating the magnitude the so-called 

“deep, hot biosphere.” The GOM hydrocarbon reservoirs should be investigated in this context. 

Finally, the role that the GOM basin has played in the evolutionary history of chemosynthetic 

fauna requires additional research. 

 

From a management perspective, regulatory agencies can be confident that they have developed 

robust models to describe the variety and distribution of upper slope seep communities. 

However, preliminary findings indicate that there is a major gap in the occurrence of lush tube 

worm communities between ~1,000 and 2,000 m. This issue needs to be tested with additional 

survey and biogeochemical investigations. 
502 

Figure 2G.1. Compilation of satellite remote sensing targets indicating robust oil seepage (solid dots) and sites 

where seafloor collections have confirmed the occurrence of chemosynthetic fauna (circles). 

References 

Brooks, J.M., D.A. Wiesenburg, H. Roberts, R.S. Carney, I.R. MacDonald, C.R. Fisher, N.L. 

Guinasso, Jr., W.W. Sager, S.J. McDonald, R.A. Burke, Jr., P. Aharon, and T.J. Bright. 

1990. Salt, seeps, and symbiosis in the Gulf of Mexico. A preliminary report of 

deepwater discoveries using DSV Alvin. EOS, Transactions, American Geophysical 

Union 71(45):1772–1773. 

MacDonald, I.R., G. Bohrmann, E. Escobar, F. Abegg, P. Blanchon, V. Blinova, W. Brückmann, 

M. Drews, A. Eisenhauer, X. Han, K. Heeschen, F. Meier, C. Mortera, T. Naehr, B. 

Orcutt, B. Bernard, J. Brooks, and M. de Faragó. 2004. Asphalt volcanism and 

chemosynthetic life in the Campeche Knolls, Gulf of Mexico. Science 304:999–1002. 
503 

Paull, C.K., B. Hecker, R. Commeau, R.P. Freeman-Lynde, C. Neumann, W.P. Corso, S. 

Golubic, J.E. Hook, E. Sikes & J. Curray. 1984. Biological communities at the Florida 

Escarpment resemble hydrothermal vent taxa. Science 226:965–967. 

Pequegnat, W.E. and L.M. Jeffrey. 1978. Petroleum in deep benthic ecosystems of the Gulf of 

Mexico and Caribbean Sea. Contributions in Marine Science 22:63–75. 

Ian R. MacDonald, Ph.D. is Professor of Environmental Science with the Physical and Life 

Sciences Department of Texas A&M University – Corpus Christi. After receiving simultaneous 

undergraduate degrees in environmental science from Friends World College in Huntington, NY, 

and Telemark District College in Norway, he was then employed by the International Ocean 

Institute and the Food and Agriculture Organization of the United Nations at postings in Malta 

and Rome. He completed his M.S. in fisheries sciences in 1984 from Texas A&M and then his 

Ph.D. in 1990. His doctoral dissertation was on the ecology of communities that flourish at 

natural oil seeps. Dr. MacDonald’s research has entailed extensive use of such deep-diving 

submarines as Johnson Sea-Link, Alvin, and the Navy nuclear submarine NR-1. His particular 

interest is the application of advanced imaging technology to marine research; this includes 

satellite detection of oil slicks, as well as application of satellite image processing techniques to 

analyze images collected from submarines. 

Samantha Joye (University of Georgia at Athens) and William Sager (Texas A&M University) 

contributed to this presentation. 
504 

CHALLENGES FOR INTERPRETATION OF SEAFLOOR GEOLOGY-BIOLOGY IN 

DEEP AND ULTRA-DEEP WATER, GULF OF MEXICO 

Harry H. Roberts, Coastal Studies Institute, Department of Oceanography and 

Coastal Sciences, Louisiana State University 

Geologic Framework and Need for a Deep Water Study 

The northern Gulf of Mexico (GOM) continental slope covers an area of over 120,000 km2 and 

is defined by the shelf edge at roughly the 200 m isobath to the upper limit of the continental rise 

at an approximate depth of 2,600 to 2,750 m (Bouma and Roberts 1990). The most complex part 

of the basin’s continental slope occurs opposite east Texas and Louisiana. In this province, 

regional topography is dominated by domes or knolls associated with salt in the shallow 

subsurface and intervening basins. Seafloor slopes associated with these regional-scale features 

range from less than 1° on the dome tops and along the basin floors to over 20° on the side of 

domes and on basin flanks. Observable on this regional topography of domes and basins are 

smaller-scale geologic features that are associated with high variability in sediment type and 

local relief. Near-surface geology and topography of the upper continental slope in the northern 

GOM is highly influenced by cyclic episodes of shelf edge progradation and sediment input to 

deep water. In addition to filling mini-basins and mobilizing salt, sediment loading during 

periods of lowered sea-level activates faults. Faulting creates abrupt relief and steep slopes (some 

near vertical) on the modern ocean floor of the slope. Faults function as avenues of transport for 

fluids and gases to or near the modern seafloor. The process of fluid and gas expulsion has an 

important impact on the present surficial geology of the slope. Expulsion of large volumes of 

fluidized sediment results in the formation of mud volcanoes and mud flows (Neurauter and 

Roberts 1992; Kohl and Roberts 1994). Seepage and venting results in the development of highly 

populated communities of chemosynthetic organisms (Kennicutt et al. 1985), creation of brine 

pools and pock marks (McDonald et al. 1990), gas hydrate mound formation (Brooks et al. 

1985), and precipitation of carbonates and other exotic minerals to form hardgrounds, chimneys, 

and mound-like buildups (Roberts and Aharon 1994). These various seafloor responses are all 

products of vertical flux of hydrocarbon gases, crude oil, and other formation fluids migrating to 

the ocean floor along faults. They have been documented over the slope’s full depth range. 

However, well-studies sites the deep (mid-slope) and ultra-deep (lower slope-basin floor) are 

few. 

Since the mid-1980s, researchers working on the continental slope of the northern GOM have 

studied the impacts of hydrocarbon seeps and vents on both the slope’s surficial geology and 

biology. Although a few programs have spanned the full depth range of the slope (e.g. Brooks et 

al. 1990), most have been confined to the upper slope (< 100 m water depth). The reason for an 

upper slope focus relates to the availability of data for analyzing the surficial geology and also 

the availability of manned submersibles for directly observing, sampling, and deploying in situ 

instrumentation at seep and vent sites. In the early 1980s, vast amounts of geophysical and 

geotechnical data were collected to evaluate the upper slope for both oil-gas exploration and 

production. By the mid-1980s the exploration front had moved beyond the upper slope and 3D-
505 

seismic was being acquired in large tracks in mid and lower slope areas. At this same time, 

several manned submersibles, limited to a diving depth of 1,000 m, became available at a 

reasonable cost for the study of hydrocarbon seeps and their unusual chemosynthetic 

communities. Deeper diving submersibles, particularly ALVIN, were and still are difficult to 

schedule for GOM research. 

The oil and gas exploration front has now moved to the deepest parts of the continental slope and 

deeper water of the continental rise. Studies of seafloor geology and biology related to 

hydrocarbon seeps and vents, that have characterized the upper slope for the last two decades, 

now need to be extended to deeper parts of the slope. As Figure 2G.2 clearly illustrates, geology 

of the continental slope changes from an extensional regime at the shelf-slope transition to a 

contractional setting at the lower slope to basin floor region. Fault patterns, intraslope basins, and 

salt masses all change as one progresses from the shelf edge to deep basin floor. 

Figure 2G.2. Dip section across the western coast of Louisiana illustrating the changing structure and salt 

geometrics from onshore to the deep Gulf of Mexico basin floor (modified from Peel et al. 

1995). 

Differences Between the Shallow and Deep Slope 

The shallow and deep parts of the northern GOM continental slope differ both in their geologic 

configuration as well as their oceanographic setting. The slope to a depth of approximately 1,000 

m is periodically impacted by thermal and current forcing associated with direct contact with the 

Loop Current and its eddies. These Loop Current intrusions have been shown to destabilize 

surface and shallow subsurface gas hydrate deposits as well as erode sediments from the tops of 

salt-supported topographic highs. The upper slope is also characterized by deep-cutting growth 

faults and counter regional faults driven by sediment input from the shelf edge during sea level 

lowstands and by salt mobility. Salt masses range from stocks to canopies while the lower slope 

is dominated by salt nappes. Intraslope basins of the upper slope house thick sedimentary 

sequences that are not usually salt-floored. Most basins extend well unto the zone of 

overpressure. Breaches in this zone cause fluid and gas expulsion that occurs primarily at the 

flanks of these basins. Salt masses at the basin flanks focus fluids and gases to modern seafloor. 

In the lower slope province, intraslope basins commonly house comparatively thin sedimentary 

sequences, and the basins are generally salt-floored. Where they are not salt-floored, salt welds 
506 

are evident. The compressional setting for the lower slope results in various types of anticlinal 

structures in the subsurface. Some of these structures become breached and thereby develop as 

obvious “leak points” to the modern seafloor. The recognition of bottom simulating reflectors 

(BSRs) running through the stratigraphy of the lower slope strongly suggests the presence of gas 

hydrate. However, mound-like features at the seafloor that could represent surface expressions of 

gas hydrate, as occur in the upper slope, are not commonly associated with the lower slope. 

At the base of the slope, salt nappes extend over the basin floor creating the Sigsbee Escarpment. 

Slope instabilities and brine seeps are common. Whether the brine seeps also contain 

hydrocarbons and therefore support chemosynthetic organisms remains as a research question. 

Also, can “leak points” for hydrocarbons originating from beneath the salt nappes be clearly 

identified and perhaps recognized as being different from brine seeps associated with salt 

dissolution? 

Greatest Challenges for Seep-Research in Deep and Ultra-Deep Water 

The geologic framework for hydrocarbon seepage and venting clearly changes from the upper 

slope to the Sigsbee Escarpment at the continental slope-to-continental rise transition. So, in 

order to be successful in a study that focuses on surficial expulsion geology and related biology 

of the deep slope, the unique geologic framework of the lower slope must be understood from a 

petroleum systems point of view. Technology exists for collecting excellent data sets from deep 

water. However, data collection systems for deep and ultra-deep water are expensive and some 

systems, such as ALVIN, have very limited accessibility. Research in the deep slope 

environment is an expensive undertaking. Without a substantial financial commitment, a 

comprehensive and field-based deep water research program for both academic and government 

researchers cannot be truly successful. 

References 

Bouma, A.H. and H.H. Roberts. 1990. Northern Gulf of Mexico continental slope. Geo-Marine 

Letters 10:177–187. 

Brooks, J.M., M.C. Kennicutt II, R.R. Bidigare, and R.A. Fay. 1985. Hydrates, oil seepage, and 

chemosynthetic ecosystems on the Gulf of Mexico slope, EOS, Transactions, American 

Geophysical Union 66:106. 

Brooks, J.M., D.A. Wiesenburg, H. Roberts, R.S. Carney, I.R. MacDonald, C.R. Fisher, N.L. 

Guinasso, Jr., W.W. Sager, S.J. McDonald, R.A. Burke, Jr., P. Aharon, and T.J. Bright. 

1990. Salt, seeps, and symbiosis in the Gulf of Mexico. A preliminary report of 

deepwater discoveries using DSV Alvin. EOS, Transactions, American Geophysical 

Union 71(45):1772–1773. 

Kennicutt, II, M.C., J.M. Brooks, R.R. Bidigare, R.A. Fay, T.L. Wade, and T.J. McDonald. 

1985. Vent-type taxa in a hydrocarbon seep region on the Louisiana slope. 

Nature 317:351. 
507 

Kohl, B. and H.H. Roberts. 1994. Fossil foraminifera from four active mud volcanoes in the Gulf 

of Mexico. Geo-Marine Letters 14:126–134. 

McDonald, I.R., J.F. Rilly, II., N.L. Guinasso, Jr., J.M. Brooks, R.S. Carney, W.A. Bryant, and 

T.J. Bright. 1990. Chemosynthetic mussels at a brine-filled pockman in the northern Gulf 

of Mexico. Science 248:1096–1099. 

Neurauter, T.W. and H.H. Roberts. 1992. Seismic and visual observation of seepage-related 

structures on the continental slope, northern Gulf of Mexico. In: Proceedings: Twentyfourth Offshore Technology Conference, Houston, Texas, OTC 6850. Pp. 355–362. 

Peel, F.J., C.J. Travis, and J.R. Hossack. 1995. Genetic structural provinces and salt tectonics of 

the Cenozic offshore U.S. Gulf of Mexico: A preliminary analysis. In: Jackson, M.P.A., 

D.G. Roberts, and S. Snelson, eds. Salt Tectonics: A Global Perspective: American 

Association of Petroleum Geologists Memoir 65:153–195. 

Roberts, H.H. and P. Aharon. 1994. Hydrocarbon-derived carbonate buildups of the northern 

Gulf of Mexico continental slope: A review of submersible investigations. Geo-Marine 

Letters 14:135–148. 

Harry H. Roberts is the former director of Coastal Studies Institute (for 10 years) at LSU, a 

member of the Department of Oceanography and Coastal Sciences, and a Boyd Professor. He has 

had a career in marine geology that spans more than 30 years and has worked in many foreign 

countries as well as in the United States. Recently, he has focused his research on two areas: (a) 

deltaic sedimentation and processes, and (b) surficial geology of the northern Gulf’s continental 

slope. The latter research thrust has concentrated on building an understanding of the impacts of 

fluid and gas expulsion on the surficial geology and biology of the slope. Gas hydrates constitute 

one of the unusual consequences of fluid and gas migration and expulsion in deep water. 
508 

BIOGEOGRAPHY AND BIODIVERSITY OF COLD SEEPS IN THE GULF OF MEXICO 

Charles R. Fisher and Erik E. Cordes, Pennsylvania State University 

Chemosynthetic communities are found wherever reduced chemicals (most often sulfide and/or 

methane) and oxygen co-occur. Environments range from mudflats and sewage outfalls to deepsea hydrothermal vents and cold seeps. All chemosynthetic communities include free-living 

chemoautotrophic and/or methanotrophic bacteria, and often the communities include one or 

more species of metazoan (animal) that harbor chemoautotrophic and/or methanotrophic bacteria 

as symbionts. The easily visible fauna that comprise the chemosynthetic communities can be as 

simple as a bacterial mat or a few scattered clams, or as spectacular as the giant vestimentiferan 

tubeworm aggregations found at many of the worlds cold seeps and hydrothermal vents. 

Defining a cold seep is somewhat problematic, as there are a wide range of chemosynthetic 

environments that could qualify for this designation. Some are actually warm (hydrothermal), 

some are more vent-like (high flow), and the geological drivers also differ in different places. 

For purposes of this summary, “cold-seeps” will refer to places where fluids containing reduced 

chemicals exit the sea floor as a result of geological processes other than superheating of pore 

fluids associated with magmatic interactions. Some of the first deep sea cold seeps to be 

discovered were in the Gulf of Mexico (GOM), on the Florida Escarpment and on the Upper 

Louisiana Slope (ULS) (Paull et al. 1984; Kennicutt et al. 1985). Since that time cold seeps have 

been discovered and sampled from most of the world’s oceans and will likely be discovered in 

many other places yet to be explored (Sibuet and Olu 1998). 

Cold-seep animal communities are most often dominated by one of three groups of animals with 

chemoautotrophic symbionts; vesicomyid clams (with sulfur oxidizing symbionts), siboglinid 

polychaetes or tubeworms (with sulfur oxidizing symbionts), or bathymodiolid mussels (with 

methanotrophic and/or sulfide oxidizing symbionts). Globally, vesicomyid clam communities are 

the most common, followed by mussels and then tubeworms (Sibuet and Olu 1998). Although 

macrofaunal communities associated with clam communities are not nearly as well studied as the 

communities associated with mussels or tubeworms, photographs and anecdotal reports suggest 

that clam-associated communities are not nearly as diverse or substantial as those associated with 

mussels and tubeworms (Gebruk et al. 2000; Levin et al. 2003). Communities associated with 

mussels at both vents and seeps have been quite well described, including those at the Florida 

Escarpment, Alaminos Canyon, and numerous sites on the ULS of the GOM (Turnipseed et al. 

2003; Bergquist et al. 2005). Quantitative studies of the community ecology of seep tubeworm 

aggregations are largely limited to studies on the ULS (Bergquist et al. 2002; 2003a; 203b). 

As a result of MMS, NOAA, and NSF funding over the past 20 years, the cold seeps of the upper 

Louisiana Slope of the GOM are arguably the best understood of any seep communities in the 

world. The physiology of the ULS mussels and tubeworms is better studied than that of any other 

seep fauna (for example Fisher et al. 1987; 1988; Page et al. 1989; Kochevar et al. 1992; Lee et 

al. 1992; Fisher and Childress 1992; Streams and Fisher 1998; Julian et al. 1999; Freytag et al. 
509 

2001), as is their life history (Nix 1995; Fisher et al. 1997; Young et al. 1996; Smith et al. 2000; 

Bergquist et al. 2000; Cordes et al. 2003; 2005) and community ecology (Bergquist et al. 2002; 

2003a; 2003b; 2004; in press). Because the known vesicomyid clam communities on the ULS 

are much more sparse and rare than the mussel and tubeworm communities, much less is known 

about these communities. These clams are thought to dominate the deepest seep communities 

(Sibuet and Olu 1998), and a large dense bed of what appeared to be vesicomyid clams was seen 

about 500 meters from the main Alaminos Canyon seep site during the last two minutes of the 

last dive of a 1991 dive series; unfortunately, no time remained to obtain a sample (C. Fisher, 

pers. obs). It is quite possible that as we better explore the GOM seeps at depths greater than 

1,000 meters, we will discover significant vesicomyid clam communities. 

In the final report of the MMS Chemo II project and related publications, a qualitative model for 

the establishment, persistence, and succession of seep communities on the ULS is presented 

(Bergquist et al. 2000; MacDonald et al. 2002; Bergquist et al. 2003a). That model has since 

been expanded, and aspects such as the proposed successional sequences verified experimentally 

(Bergquist et al. 2003b; Bergquist et al. 2005). In addition, quantitative mathematical models of 

tubeworm aggregation establishment, growth, longevity, and interactions with free-living 

microbial consortia have been developed (Cordes et al. 2003; 2005). These models place 

constraints on the types of environments that will support rich and long-lived chemosynthetic 

communities, indicate the most important parameters to quantify to understand the systems, and 

also provide a variety of testable predictions concerning the communities of animals and bacteria 

associated with the tubeworms and mussels. This rich body of literature and knowledge provides 

a firm foundation for the design of surveys and experiments to provide a first-order 

understanding of chemosynthetic communities in the deeper waters of the GOM. 

Although only a few communities from the lower slope (LS) chemosynthetic habitats of the 

GOM have ever been studied, and quantitative collections from below 1,000 meters in the GOM 

are sparse, some general trends (and testable hypotheses) are evident from these collections. 

There is very little overlap in the species composition between the communities on the ULS and 

the LS of the GOM. Our preliminary data suggests five potential shared species greater than one 

mm (of the 116 from the ULS seep communities and the 48 from the LS). However of these five, 

one (B. childressi) is represented by two distinct genetic populations (Craddock et al. 1995), 

three are undescribed species, and the last is a sipunculid with little easily apparent 

morphological criteria for distinguishing between species. Confirmation that any of these species 

are the same from both depths must await further molecular investigations, and the shallow and 

deep communities may prove to be completely genetically isolated from one another. On the 

other hand, there is significant species overlap between the communities at the Florida 

Escarpment (3,300 m depth) and Alaminos Canyon (2,200 m depth) where 13 of 21 common 

species are apparently shared. Interestingly, brittle stars (Ophioroidea), a group that are largely 

absent from collection on the ULS, dominated the associated fauna in several collections from 

the LS. In general, community diversity and evenness declines with depth, endemicity increases 

with depth, and the biomass of the associated faunal communities (standardized to habitable 

surface area) is similar across the depth gradient studied. Unlike the general trend for the 

background fauna, body size does not show any trends with depth, increasing in some taxa and 
510 

decreasing in others. Together, our existing knowledge of the ULS and our preliminary surveys 

of LS chemosynthetic communities provide a substantial foundation for targeted research in the 

deep waters of the GOM. 

References 

Bergquist, D.C., F.M. Williams, and C.R. Fisher. 2000. Longevity record for deep-sea 

invertebrate. Nature 403:499–500. 

Bergquist, D.C., I.A. Urcuyo, and C.R. Fisher. 2002. Establishment and persistence of seep 

vestimentiferan aggregations from the upper Louisiana slope of the Gulf of Mexico. 

Marine Ecology Progressive Series 241:89–98. 

Bergquist, D.C., T. Ward, E.E. Cordes, T. McNelis, R. Kosoff, S. Hourdez, R. Carney, and C.R. 

Fisher. 2003a. Community structure of vestimentiferan-generated habitat islands from 

upper Louisiana slope cold seeps. Journal of Experimental Marine Biology and Ecology 

289:197–222. 

Bergquist, D.C., J. Andras, T. McNelis, S. Howlett, M.J. van Horn, and C.R. Fisher. 2003b. 

Succession in upper Louisiana slope cold seep vestimentiferan aggregations: the 

importance of spatial variability. PSZN Marine Ecology 24:31–44. 

Bergquist, D.C., C. Fleckenstein, E. Smith, J. Knisel, and C.R. Fisher. 2004. Environment drives 

physiological variability in the cold seep mussel Bathymodiolus childressi. Limnology 

and Oceanography 49:706–715. 

Bergquist, D.C., C. Fleckenstein, J. Knisel, B. Begley, I. R. MacDonald, and C.R. Fisher. In 

press. Variations in seep mussel bed communities along physical and chemical 

environmental gradients. Marine Ecology Progressive Series. 

Cordes, E.E., D.C. Bergquist, K. Shea, and C.R. Fisher. 2003. High hydrogen sulfide demand of 

long-lived vestimentiferan tube worm aggregations modifies the chemical environment at 

deep-sea hydrocarbon seeps. Ecology Letters 6:212–219. 

Cordes, E.E., M.A. Arthur, K. Shea, and C.R. Fisher. 2005. Modeling the mutualistic interactions 

between tubeworms and microbial consortia. Public Library of Science, Biology 3:e77. 

Cordes, E.E., S. Hourdez, B.L. Predmore, M.L. Redding, and C.R. Fisher. Submitted. Succession 

of hydrocarbon seep communities associated with the long-lived foundation species 

Lamellibrachia luymesi. Marine Ecology Progressive Series. 

Cordes, E.E., B.L. Predmore, C. Jones, P. Deines, G. Telesnicki, and C. R. Fisher. Submitted. 

Impact of ecosystem engineering tubeworms on the hydrocarbon seep habitat. Ecology. 
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Craddock, C., W.R. Hoeh, R.G. Gustafson, R.A. Lutz, J. Hashimoto, R.J. Vrijenhoek. 1995. 

Evolutionary relationships among deep-sea mytilids (Bivalvia: Mytilidae) from 

hydrothermal vents and cold-water methane/sulfide seeps. Marine Biology 121:477–485. 

Fisher, C.R., J.J. Childress, R.S. Oremland, and R.R. Bidigare. 1987. The importance of methane 

and thiosulfate in the metabolism of the symbionts of two deep-sea mussels. Marine 

Biology 96:59–71. 

Fisher, C.R., J.J. Childress, and N.K. Sanders. 1988. The role of vestimentiferan hemoglobin in 

providing an environment suitable for chemoautotrophic sulfide oxidizing 

endosymbionts. Symbiosis 5:229–246. 

Fisher, C.R. and J.J. Childress. 1992. Organic carbon transfer from methanotrophic symbionts to 

the host hydrocarbon-seep mussel. Symbiosis 12:221–235. 

Fisher, C.R., I. Urcuyo, M.A. Simpkins, and E. Nix. 1997. Life in the slow lane: growth and 

longevity of cold-seep vestimentiferans. PSZN Marine Ecology 18:83–94. 

Gebruk, A.V., P. Chevaldonne, T. Shank, R.A. Lutz, R.C. Vrijenhoeck. 2000. Deep-sea 

hydrothermal vent communities of the Logatchev area (14 degree 45'N, Mid-Atlantic 

Ridge): diverse biotopes and high biomass. Journal of the Marine Biological Association 

of the United Kingdom 80:383–393. 

Julian, D., F. Gaill, E. Wood, A.J. Arp, and C.R. Fisher. 1999. Roots as a site of hydrogen sulfide 

uptake in the hydrocarbon seep vestimentiferan Lamellibrachia sp. Journal of 

Experimental Biology 202:2245–2257. 

Kennicutt M.C., J.M. Brooks, R.R. Bidigare, R.R. Fay, T.L. Wade, T.J. McDonald. 1985. Venttype taxa in a hydrocarbon seep region on the Louisiana slope. Nature 317:351–353. 

Kochevar, R.E., J.J. Childress, C.R. Fisher, and E. Minnich. 1992. The methane mussel: Roles of 

symbiont and host in the metabolic utilization of methane. Marine Biology 112:389–401. 

Lee, R.W., E.V. Thuesen, J.J. Childress, and C.R. Fisher. 1992. Ammonium and free amino acid 

uptake by a deep-sea mussel containing methanotrophic bacterial symbionts. Marine 

Biology 113:99–106. 

Levin, L.A., W. Ziebis, G.F. Mendoza, V.A. Growney, M.D. Tryon, K.M. Brown, C. Mahn, J.M. 

Gieskes, A.E. Rathburn. 2003. Spatial heterogeneity of macrofauna at northern California 

methane seeps: Influence of sulfide concentration and fluid flow. Marine Ecology 

Progressive Series 265:123–139. 

MacDonald, I.R., N.L. Guinasso, G.A. Wolff, M.C. Kennicutt, R. Sassen, J.W. Morse, R. 

Arvidson, W. Sager, S. Macko, D.C. Nelson, E. Powell, R. Carney, P. Montagna, S. Joye, 
512 

C.R. Fisher, S. Schaeffer. 2002. Stability and change in Gulf of Mexico chemosynthetic 

communities. Report for U.S. Department of Interior, Minerals Management Service. 

Contract #1435-01-96-CT-30813. 

Nix, E., C.R. Fisher, K.M. Scott, and J. Vodenichar. 1995. Physiological ecology of a mussel 

with methanotrophic symbionts at three hydrocarbon seep sites in the Gulf of Mexico. 

Marine Biology 122:605–617. 

Page, H.M., C.R. Fisher, and J.J. Childress. 1989. Filter-feeding and the nutritional biology of a 

deep-sea mussel with methanotrophic symbionts. Marine Biology 104:251–257. 

Paull, C.K., B. Hecker, R. Commeau, R.P. Freeman-Lynde, C. Neumann, W.P. Corso, S. 

Golubic, J.E. Hook, E. Sikes, J. Curray. 1984. Biological communities at the Florida 

Escarpment resemble hydrothermal vent taxa. Science 226:964–967. 

Sibuet M. and K. Olu. 1998. Biogeography, biodiversity and fluid dependence of deep-sea coldseep communities at active and passive margins. Deep-Sea Research II 45:517–567. 

Smith, E.B., K.M. Scott, E.R. Nix, C. Korte, and C.R. Fisher. 2000. Growth and condition of 

seep mussels (Bathymodiolus childressi) at a Gulf of Mexico Brine Pool. Ecology 81: 

2392–2403. 

Streams, M. and C.R. Fisher. 1997. Incorporation of methane by methanotrophic symbionts and 

symbiont digestion by their host mussel. Marine Biology 129:465–476. 

Turnipseed M., K.E. Knick, R.N. Lipcius, J. Dreyer, and C.L. Van Dover. 2003. Diversity in 

mussel beds at deep-sea hydrothermal vents and cold seeps. Ecology Letters 6:518–523. 

Young C.M., E. Vázquez, A. Metaxas, and P.A. Tyler. 1996. Embryology of vestimentiferan 

tube worms from deep-sea methane/sulphide seeps. Nature 381:514–516. 

Charles Fisher is a Professor of Biology and Chair of the Graduate Program in Biology at the 

Pennsylvania State University. He received his BA from Michigan State University and his MS 

and PhD from the University of California in Santa Barbara. He is currently the Chair of the NSF 

Ridge 2000 Program steering committee and serves on numerous national and international 

committees including: the steering committees for the international mid-ocean ridge research 

coordinating program (InterRidge) and the Census of Marine Life Chemosynthetic Ecosystems 

(ChEss) program, the oversite committee for the Endeavour Ridge Marine Protected Area 

(Canada), and advisory boards for the NSF Centers for Ocean Science Education Excellence 

(COSEE) program and for the 11,000 meter Hybrid ROV (HROV) project. He has made 122 

dives in research submersibles, spent 57 days at sea working with ROVs, participated in 53 
513 

oceanographic research expeditions and published more than 90 peer-reviewed papers on the 

biology of hydrothermal vent and cold seep animals. 

Erik Cordes is a post-doctoral researcher at the Pennsylvania State University. He received his 

BS from Southampton College, his MS from Moss Landing Marine Laboratories, and his PhD 

from the Pennsylvania State University. He has accepted a post-doctoral position at Harvard 

University with Dr. Peter Girguis to study the microbial ecology of Juan de Fuca hydrothermal 

vents. He has participated in 9 research cruises over the past 10 years and has made 23 

submersible dives, and has published 6 papers on the biology and ecology of cold seep and deepsea coral communities, with 4 more in preparation or review. 
514 

DEEP GULF OF MEXICO CHEMOSYNTHETIC COMMUNITIES: 

CURRENT KNOWLEDGE FOR SITES BELOW 1,000 METERS. 

RECENTLY DISCOVERED ASPHALT VOLCANO AND ASSOCIATED 

CHEMOSYNTHETIC COMMUNITIES IN THE SOUTHERN GULF OF MEXICO 

Elva Escobar-Briones, Universidad Nacional Autónoma de México, 

Instituto de Ciencias del Mar y Limnología 

Introduction 

The Gulf of Mexico (GOM) is an important hydrocarbon basin where salt tectonism controls 

development of hydrocarbon reservoirs. Efforts on the northern continental slope have 

extensively documented chemosynthetic life in association with hydrocarbon seeps, mud 

volcanism, gas hydrates and salt lakes. Over thirty years ago, cores containing hydrocarbons and 

asphalt pieces were collected and an asphalt deposit was photographed from the seafloor deep 

salt domes in the southwestern GOM and several other records of potential sites where petroleum 

could occur in deep benthic ecosystems of the GOM and the Caribbean (Pequegnat & Jeffrey 

1979). 

Materials and Methods 

The preliminary results of this study are based on images from the abyssal seafloor of the 

southwestern GOM where an ocean floor observation system (OFOS) was deployed with the 

objective to visually locate active seep sites and identify potential seeps and chemosynthetic 

communities at abyssal depths. The OFOS system, a TV-guided sled equipped with a B/W video 

camera, two xenon lamps, a Benthos camera with flash, a SeaSnap 990 digital camera system for 

LLC high resolution images, three laser pointers and a CTD, was deployed in the Campeche 

Knoll area (Figure 2G.3) at sites where oil spills were detected by satellite imaging during five 

deployments (Stas. SO 174/2- 126 to 138 [re. OFOS 10 to 14]). The locations studied were 

defined guided by data from satellite imagery that showed evidence for persistent oil seeps in the 

region and where mapping with the German ship RV SONNE revealed isolated salt diapirs 

shaped as elongated 'pillows' averaging 5 by 10 km and having 450 to 800m of relief and slopes 

in an average of 10% (MacDonald et al. 2004). 

The photo-sled revealed extensive surface deposits of solidified asphalt at some of the cratered 

knolls. The site with a large asphalt spill, named Chapopote was selected for this purpose and 

extensively documented. This seafloor observation program procedure included lowering OFOS 

to a few meters above the seafloor and towing the sled along a pre-defined track by the ship at a 

speed less than 1 kn. The distance between the seafloor and sled was manually controlled with 

the winch with the pictures taken in the manual option of the operating system. UTC time, ship 

position were recorded using the protocol software (Eisenhauer, et al. 2004). 
515 

Figure 2G.3. The area of study in the southwestern Gulf of Mexico. 

The Benthos camera held film roles of 800 slides each. Onboard every image recorded was 

logged in log and relevant features recorded with the UTM protocol software and added to a 

map. The film was processed in Germany and later on stripes cut and pictures scanned to 

893x591 pixels with a Nikon CoolScan 4.0 ED with color activation. The scanned pictures were 
516 

saved as individual files in TIF-format .tif with homogene size 1.71 MB each and ID coded by 

cruise number e.g. SO_174 station number e.g. STAT_138 and OFOS deployment number 

OFOS_140 followed by the picture number i.e. 12 (i.e. SO_174_STAT_138_OFOS_14012.tif). 

The pictures were qualitatively analyzed with Windows image viewer and a file with diverse 

worksheets (Table 2G.1) generated that recorded the following: 

 1. The type of bottom with six categories ranging from the relatively homogeneous soft 

bottom to the heterogeneous asphalt as the example of the presence of chemosynthetic 

activity, the relative occurrence of these two bottom types, the presence of bacteria. 

 2. The prevalence of biological activity with six categories of the presence, in the size and 

density of tracks, pellets and burrows. 

 3. The nature of materials exported from the coastal and pelagic zones with six categories 

and types. 

 4. Evidence of chemoautotrophic activity with five categories ranging from the presence of 

oil, bacterial mats their color and extension, gas bubbles, and fauna previously 

recognized for other chemosynthetic communities in the basin, associated to whale 

carcasses or hydrothermal vent sites (e.g. tubeworms, mollusk and squat lobster 

aggregations). 

 5. The presence of the diverse megafaunal groups to major taxa and group levels with 25 

categories that were recorded both by their abundance and by their presence/absence. 

A classification analysis based on the presence and absence (1/0) of features was performed in an 

initial phase to identify and classify the types of habitats and communities with potential 

chemosynthetic activity based on the resolution of the images. 

Table 2G.1. Section of a worksheet that shows image identification in the Image field, and types of seafloor 

habitats identified and coded by the presence (1) or absence (0) of the feature for a later 

qualitative analysis. 

Image BSoft BAsph BSoft+Asph BAsph+Soft BGranul BDark LBurr

14324 1 0 0 0 0 0 1 

14323 0 0 1 0 0 0 0 

14322 1 0 0 0 0 0 0 

14321 0 0 1 0 0 0 0 

14320 0 0 1 0 0 0 0 

14319 1 0 0 0 0 0 1 

14318 1 0 0 0 0 0 0 

14317 1 0 0 0 0 0 0 
517 

Results and Discussion 

The seafloor visualization program in the Campeche knolls area recorded deeply-cratered salt 

domes with extensive slumps and mass-wasting at depths of more than 3,000m where abundant 

chemosynthetic life occurred associated to the deep soft sediment, the massive lava-like flowfields of solidified asphalt and the ecotones found amid. 

The levels of resolution of the visualization method allowed to processes images and classify 

them to community, types of habitats and major taxonomic group presence/absence. 

The largest number of deployments concentrated in the area south of central crater. The total 

number of images analyzed was 1,469 for the five OFOS deployments where almost half of the 

images recorded asphalt and hydrocarbon seep related features. 

The soft sediments and the hard substrates were the two types of communities recorded. The soft 

sediments were subdivided as non-chemosynthetic and as chemosynthetic (Figure 2G.4). The 

former were characterized by non-perturbed hemipelagic type of sediment and by bioturbated 

hemipelagic with a series of tracks and burrows. The latter were of four types black (dark) 

sediments, oily bacterial mats, granulated bottoms and soft sediments with shell deposits. 

Figure 2G.4. Image of a soft sediment type of habitat with chemosynthetic activity. It depicts a yellow type of 

bacterial mat and a few open bivalve shells. 
518 

The hard substrates recorded in the images were subdivided into those hard substrates (asphalt) 

that were in contact with soft sediments and those where hard substrate or asphalt prevailed. The 

soft sediment to asphalt ratio and size of these hard substrate formations was quantified at each 

image as percentage coverage and was of relevance and had influence to the type and abundance 

of associated fauna (Figure 2G.5). The hard substrates that were in contact with soft sediments 

were identified as fields with pillow formation, predominance of rubble, large boulders, and 

blocks. The hard substrate formations were identified by their roughness, relief and texture as 

primary flow dikes, secondary flow blankets, surfaces with high relief and texture, and hard 

substrates without relief or texture. 

Figure 2G.5. Image of a hard substrate rubble with associated chemosynthetic fauna. 

The asphalt deposits varied in appearance and coverage in relation to the typical abyssal softbottom topography, establishing diversity at the landscapes, community, habitat levels. Samples 

obtained from these habitats recorded the occurrence of subsurface thick, liquid petroleum 

dispersed in veins and pockets throughout, the presence of plates of authigenic carbonates with 

layers of oil pooled beneath and gas hydrate many of which were associated to the diversified 

substrates where white films of bacterial mats resembling Beggiatoa occur (MacDonald et al. 

2004). Among the megafaunal groups recognized are bacterial mats in different forms, colors 

and extension over the seafloor and asphalt, sponges, epizoid hydroids, corals, free living 

anemone, spaghetti worms, tubeworm aggregations, bivalve clusters, limpets, scaphopods, 
519 

gastropods, shrimps, crabs, asteroids, crinoids, ophiuroids holothurids tunicates, several types of 

fish and others not identified. 

The biological characterization of the communities associated to this asphalt volcanism suggest 

chemosynthetic activity and complex biogeochemical interactions through the presence of 

chemosynthetic fauna identified i.e. vestimentiferan tubeworms (c.f. Lamellibrachia sp.) that 

aggregate at the sediment/asphalt interphase under bitumen deposits or down into fractures 

within flow fields in densities that vary from single specimens scattered on the soft sediments 

near asphalt rubble fields to mostly small clusters and larger aggregations with over 50 

individuals on the edges and folds of massive asphalt flows. Shells and living specimens of 

chemosynthetic mussels (c.f. Bathymodiolus sp., cf. Vesicomyidae, trails and tracks and a few 

living individuals of clams (c.f. Calyptogena, sp.) Samples recovered from these locations 

provided with specimens of bivalves of the genus Solemya sp heavily coated in oil. 

Heterotrophic fauna represented by galatheid crabs (Munidopsis sp., shrimp resembling 

Alvinocaris sp., and other non-endemic deep-sea invertebrates (i.e. sponges, tunicates, hydroids, 

dense aggregations of echinoderms of the genera Benthodytes sp., Psychropotes sp., Pterasterias 

sp. that seem to feed on bacterial mats) and abyssal fish. From the photographs on the seafloor, it 

is clear that the asphalt site is an oasis of life with a large diversity of habitats generated by the 

asphalt flow. From the results we can preliminarily identify that communities are similarly 

assembled to other communities occurring in the basin where chemosynthetic activity has been 

recorded. Similar functional components occur among habitats and have a wide range in size, i.e. 

tubeworms and were less abundant in these abyssal habitats than when found at upper slope 

seeps. The ecotones (asphalt/soft sediment borders) between communities play an important role 

in structuring the chemosynthetic faunal components and their complexity. The bacteria were 

less prevalent on rocks and/or soft sediments. A large number of filter feeder epizoids and other 

free living forms co-occurring on the asphalt formations suggest resuspension or export of 

biogenic carbon to seafloor. 

Acknowledgments 

This study was financially supported by the German Federal Ministry of Education and Research 

(Bundesministerium für Bildung und Forschung; grant nos. 03G0174A and 03G0566A); the 

NOAA Office of Ocean Exploration, NSF grant no. OCE-0085548, the Harte Research Institute; 

the U.S. Department of Energy, National Energy Technology Laboratory, and PAPIIT UNAM 

grant IN. 224503 and support SEP-CONACyT 2002 no. 40158. People I would like to 

acknowledge: G. Bohrman, GEOMAR and I. MacDonald, TAMUCC. 

References 

Eisenhauer, A., I. MacDonald, F. Abegg, and O. Pfannkuche. 2004 Visual seafloor observation. 

In: Bohrmann, G. & S. Schenck, eds. RV SONNE cruise report SO 174 OTEGA II 

Gashydrate im Geosystem. GEOMAR. 108pp. 

MacDonald, I.R., G. Bohrmann, E. Escobar, F. Abegg, P. Blanchon, V. Blinova, W. Brückmann, 

M. Drews, A. Eisenhauer, X. Han, K. Heeschen, F. Meier, C. Mortera, T. Naehr, B. 
520 

Orcutt, B. Bernard, J. Brooks, and M. De Farago. 2004. Asphalt volcanism and 

chemosynthetic life in the Campeche Knolls, Gulf of Mexico. Science 304:999–1002 

Pequegnat, W.E. and L.M. Jeffrey. 1979. Petroleum in deep benthic ecosystems of the Gulf of 

Mexico and the Caribbean. Contributions in Marine Science 22:63. 

Elva G. Escobar-Briones has been a Professor with the Institute of Marine Sciences and 

Limnology (ICML) of the National Autonomous University of Mexico (UNAM) since 1993. 

Dr. Escobar-Briones received an undergraduate degree in biology from the Metropolitan 

Autonomous University (UAM) in 1981, completed a master’s degree in fisheries and ocean 

sciences at UNAM in 1984, and defended a doctoral dissertation in biological oceanography in 

1987, also from UNAM, on the structure and function of benthic communities in the 

southwestern Gulf of Mexico. Dr. Escobar-Briones has been recognized on the study of the 

biology of benthic communities with some 55 peer-reviewed articles and over 50 reports and 

articles on related topics co-authored with both Mexican students and colleagues and 

international collaborators. Dr. Escobar-Briones has been Head of the Academic Unit in Coastal 

and Ocean Systems since 1999 and is active teaching graduate and undergraduate levels at 

UNAM. She coordinates the research program in deep-sea benthos of the southwestern Gulf of 

Mexico at ICML UNAM, a program that is financed by UNAM’s program PAPIIT and the 

Mexican funding agency CONACyT. 
521 

RECOVERY OF DISTURBED DEEP-SEA COMMUNITIES 

Craig M. Young, Oregon Institute of Marine Biology, University of Oregon 

Because populations only increase when birth and immigration exceed death and emigration, 

reproductive rate (know variously as fecundity, birth rate, clutch size, etc.) is a major component 

of all population models. Indeed, the familiar Leslie matrix models, which predict the number of 

individuals in each age class, life-history stage or time increment, require age- or stage-specific 

knowledge of two kinds of transitions: survival and reproduction. Most marine populations, 

including those occupying deep-sea chemosynthetic ecosystems, are best modeled as fragmented 

metapopulations in which local persistence depends on rates of immigration from other source 

populations in the region. It follows that recovery potential is greatest in a regional system with 

numerous potential sources of migrants. Thus, predicting the recovery of a deep-sea population 

depends on a knowledge of 1) regional reproductive rate and 2) dispersal potential of offspring. 

In marine animals, migrants are generally microscopic larvae that drift in the water column for 

hours, weeks, or months. In shallow water, small feeding (planktotrophic) larvae virtually always 

disperse much more widely than non-feeding (lecithotrophic) larvae. This greater dispersal 

capacity of feeding larvae confers greater longevity in evolutionary time and wider distributions 

in geographic space. Because planktonic algal foods are absent or rare in deep water, it has long 

been predicted that deep-sea animals should produce non-feeding larvae. Exceptions are known 

(e.g., some abyssal snail larvae migrate all the way to the euphothic zone to feed), but 

planktotrophic development is nevertheless the exception in deep water. One is tempted to infer 

from this that dispersal distances (and therefore geographic ranges and species longevities) 

should also be lower in deep water, but biogeographic evidence indicates that many deep-sea 

species with lecithotrophic larvae have very broad geographic distributions. The unexpectedly 

high dispersal potential of deep-sea lecithotrophic larvae can probably be attributed to lower 

metabolic demands in cold water. A case in point is the dispersal potential of vestimentiferan 

tubeworms. The yolky eggs of all known species are very similar in volume and energy content, 

yet the larvae of the vent worm Riftia pachyptila, which disperses at 2o

C, remains in the water 

column 40% longer than the larvae of the seep tubeworm Lamellibrachia luymesi, which 

disperses at 8-15o

C. 

In the relatively well-studied chemosynthetic communities of the bathyal Gulf of Mexico (GOM) 

(less than 1,000m), many species have planktotrophic development and planktotrophic larvae. 

These include the mussel Bathymodiolus childressi, the snail Bathynerita naticoidea, the “ice 

worm” Hesiocaeca methanicola, and the seep orbinid Methanoaricia dendrobranchiata. Notable 

lecithotrophic species include the vestimentiferan worms and file shells of the genus Acesta. 

Many species at slope depths reproduce seasonally like their shallow-water counterparts. 

Surprisingly, this includes some seep species, such as Bathymodiolus childressi, that have access 

to a continuous source of chemical energy. This seasonality can probably be explained by 

mixotrophy; these mussels are known to supplement methanotrophic nutrition by filtering 
522 

ultraplankton and seston. Most seasonal animals from cold seeps in the GOM breed in midwinter and produce planktotrophic larvae that presumably take advantage of the spring plankton 

bloom. The known lecithotrophic species are mostly, but not all, continuous breeders. It is 

expected that the incidence of continuous breeding will increase with depth in the GOM as it 

appears to in other systems, but empirical data in support of this hypothesis are not available. 

In general, fecundity decreases with depth, presumably because photosynthetic food becomes 

less abundant in deeper water. For example, the gonadal indices of sea urchins (gonad weight as 

a proportion of total body weight) are one to two orders of magnitude higher in shallow-water 

species than in slope species. However, this generalization probably does not hold for deep-sea 

species with access to continuous sources of chemical energy. Thus, tubeworms breed 

continuously and produce hundreds of thousands of eggs at any given time. Moreover, some of 

the seep tubeworms from the GOM may produce eggs for hundreds of years. We suspect that 

these may have some of the highest lifetime fecundities of any marine organisms. 

Like other biological rates, the rate of gametogenesis (egg production) might be expected to 

decline with lower temperatures in the deep sea. However, recent work with the electron 

microscope reveals that many deep-sea species, including a number of species from the GOM, 

have specialized mechanisms for fast egg production. Such mechanisms include blood vessels, 

trabeculae and ovarian acini that transport nutrients directly to eggs for the production of yolk. 

Mechanisms that facilitate rapid egg production, which appear to be especially common in vent 

species, are also found in highly disturbed intertidal environments (e.g, sabellariid polychaetes 

and some limpets on rocky shores) and may be adaptive responses to variable environments. 

In summary, life-history studies give us reasons to suspect that deep-sea chemosynthetic animals 

might be particularly resilient to local environmental perturbations. Assuming that 

chemosynthetic communities are sufficiently widespread in the deep GOM to form substantial 

regional pools of larvae, we can hypothesize that the life-history attributes of high dispersal 

potential, continuous breeding, high fecundity, and rapid gametogenesis could facilitate the rapid 

reestablishment of perturbed chemosynthetic metapopulations in this region. These ideas require 

testing, and such tests would best be done in conjunction with studies on growth rates, survival 

and community assembly. 

Craig Young received his B.S. and M.S. from Brigham Young University and his Ph.D. from the 

University of Alberta in 1982. After a three-year stint on the faculty at Florida State University, 

he moved to Harbor Branch Oceanographic Institution in Florida, where he worked as a research 

scientist and professor for 17 years. His appointment as the new director of the Oregon Institute 

of Marine Biology began in June 2002. He has published more than 120 scientific papers and has 

edited several books. Professor Young currently serves as an Honorary Fellow at the 

Southampton Oceanography Center in the UK, as Visiting Professor of Biology at Kings College 

London, as a member of the NSF Ridge-2000 Steering Committee, as a member of the board of 

directors of the Pacific Institutes of Marine Science, and as a member of the steering committee 

for CHESS, the chemosynthetic ecosystems program of the Census of Marine Life. 
523 

DEEPEST GULF OF MEXICO HYDROCARBON SEEP CHEMOSYNTHETIC 

COMMUNITY IN BLOCK AC 818 AND OTHER ROV OBSERVATIONS 

IN THE DEEP GULF 

Dan Allen, ChevronTexaco Gulf of Mexico Operations 

In February 2004 operator ChevronTexaco captured video images of the deepest chemosynthetic 

community observed to that time in the Gulf of Mexico (GOM). The community was observed at 

the Tiger prospect in Alaminos Canyon Block 818 at a water depth of ~2,749 m. The well was 

drilled from the Transocean drill ship Discoverer Deep Seas, and the video imagery was 

recorded by a camera aboard the Subsea 7 ROV Hercules operating from the ship. The work 

class Hercules is a 120 hp unit powered and controlled via an umbilical tether which limits the 

effective reach of its watch circle to ~200 m from the well location. 

What appears most noticeable about the Tiger community is its similar composition to other 

chemosynthetic communities found at considerably shallower water depths in the GOM. Though 

this community is patchy, species include mussels, vestimentiferan tube worms, sponges, soft 

corals, crabs, starfish, holothurians, isopods, sea urchins and anemones frequently encountered 

elsewhere in the Gulf. Sediments across the site are fine sands littered with shell hash and 

abundant foraminiferan shells. 

In addition to the chemosynthetic community at Tiger, the author also showed video clips of 

other animals not previously known in the GOM or, in one case, one never before observed 

alive. The latter, a long-nosed chimaerid fish, Harriotta raleighana, was filmed in Mississippi 

Canyon at a depth of approximately 2,130 m. The specimen’s length, estimated at 2 m, makes it 

the largest specimen known, and it is the only one known to be seen alive. 

At a different location in Mississippi Canyon in November 2003 a sleeper shark, tentatively 

identified as the Greenland sleeper (Somniolus microcephalus) was observed at a water depth of 

about 2,650 m. The specimen was estimated to be about 3–4 m long. The nearest previous record 

of this species was from a 1988 ROV sighting off the coast of Georgia in 2,200 m of water. That 

specimen was estimated at 6 m in length. 

At a 3,048 m site in Alaminos Canyon an as-yet unnamed squid was captured on video. The 

squid is unusual in that it appears to swim using two very large fins. It also carries ten identical 

arms angling downward and away from the axis of its body at about 45°; trailing from the tip of 

each arm is a long, delicate tentacle which appears to be coated with a sticky mucous, as they 

have been observed to appear to get stuck when they come into contact with subsea structures. 

There have been numerous sightings of similar squid in most of the world’s oceans in the past 

few years, and they are thought to represent mature specimens of a species recently named 

Magnapinnida pacifica from some juveniles caught off Hawaii. The specimen we observed was 

estimated to be about 4–5 m long. 
524 

In closing, oil and gas activities, in the deep GOM have illuminated biological discoveries during 

routine ROV operations and at least some operators have actively contributed them to the 

scientific community. Hopefully such sharing will become more commonplace as informationexchange networks between operators and scientists mature and grow more robust. 

Dan Allen is a marine biologist who has been with ChevronTexaco (CVX) for twenty-four years. 

He has worked on many projects related to interactions between oil and gas exploration, 

production and transportation activities and the marine environment, including FADs, rigs-toreefs, use of active facilities by fish and sea turtles, mariculture, and effects of anthropogenic 

sounds on marine animals. Since 1997 he has supported CVX’s deep water Gulf of Mexico 

development where he has also been able to acquire many ROV video images of chemosynthetic 

communities and other deep sea life and share them with the broader scientific community. 
525 

SESSION 2H 

LOUISIANA OIL SPILL RESEARCH AND 

DEVELOPMENT PROGRAM (OSRADP) 

Chair: Rusty Wright, Minerals Management Service 

Co-Chair: Don Davis, Louisiana State University 

SURVEY OF LOUISIANA SEABIRD COLONIES TO ENHANCE OIL SPILL 

RESPONSE Jenneke M. Visser................................................................................................. 527 

LOUISIANA PETROCHEMICAL PIPELINES: STATUS OF AN INVENTORY OF 

GAS, AND HAZARDOUS MATERIALS PIPELINES IN THE STATE Robert Paulsell...... 529 

CHEMICAL ADDITIVES IN OILED FRESHWATER LABORATORY MICROCOSMS: 

TOXICITY TO AQUATIC ORGANISMS, RELATIONSHIP BETWEEN HYDROCARBON 

MEASUREMENTS AND TOXICITY, AND THE INFLUENCE OF CHEMICAL 

ADDITIVES ON HYDROCARBON DISAPPEARANCE Paul L. Klerks.............................. 534 

HISTORICAL ANALYSIS OF OIL SPILLS IN LOUISIANA George Wooddell.................. 536 

AERIAL VIDEO SURVEYS ON INTERACTIVE DVDs 2001 COASTAL LOUISIANA 

AND THE LOWER MISSISSIPPI RIVER – ARKANSAS TO THE GULF OF MEXICO 

Karen A. Westphal...................................................................................................................... 539 

DISPERSANT EFFECTS ON MARSH VEGETATION: TOXICITY EVALUATION 

AND OIL REMEDIATION Qianxin Lin.................................................................................. 541 

DESIGN, IMPLEMENTATION, OPERATION AND MAINTENANCE OF AN OCEAN 

OBSERVING SYSTEM OFF COASTAL LOUISIANA AND APPLICATION TO OIL 

SPILL CONTINGENCY Gregory Stone................................................................................... 543 
527 

SURVEY OF LOUISIANA SEABIRD COLONIES TO ENHANCE 

OIL SPILL RESPONSE 

Jenneke M. Visser, Coastal Ecology Institute, 

School of the Coast and Environment, Louisiana State University 

Louisiana’s coastal marshes and barrier islands support significant breeding populations of 

colonial seabirds. Because seabird nesting habitat is highly vulnerable to erosion from tropical 

and winter storms, the locations of these seabird (particularly Black Skimmer, Least Tern, and 

Forster’s Tern) colonies are subject to annual changes. Due to their location and ground nesting 

habits, seabird colonies are also extremely vulnerable to oil spills during the nesting season. The 

locations of seabird colonies along the Louisiana coast have been surveyed in 1976 1983 by the 

U.S. Fish and Wildlife Service, and in 1990 by the Louisiana Department of Wildlife and 

Fisheries. Other partial surveys (1993, 1994, 1995, 1996; unpublished) are incorporated in the 

GIS database of the Louisiana Natural Heritage Program (LNHP) of LDWF. However, these 

recent surveys are based solely on aerial observations. Aerial surveys provide good estimates of 

colony size and nesting activity for wading bird colonies but are less reliable for seabird colonies 

because nesting birds cannot always be distinguished from resting birds. 

We performed a ground survey of nesting seabirds in Louisiana in 1997 and compiled a database 

of Louisiana seabird colonies from 1976 to 1997. The number of breeding birds of each species 

was estimated by taking the average of the estimate of two independent observers. The number 

of nesting adults present at the colony closely mirrors the number of breeding pairs for most 

species. Because not all birds start nesting at the same time, our estimates for the total number of 

breeding birds is a conservative one. Additional notes were taken on habitats and parts of islands 

used. The period in which the colony was used by breeding birds, and was therefore most 

vulnerable to harm from oil spills, was based on the species present in 1997 and the activity 

window reported for these species. 

We surveyed a total of 215 colonies and found 101 active colonies, of which 18 were new. 

Eighty-three historic colonies were inactive in 1997 and 30 historic colonies had disappeared, 

since they were located on islands that no longer exist. We found 11 different species of seabirds, 

of which the Herring Gull has set a new breeding record in Louisiana. The Laughing Gull was 

the most abundant seabird nesting in Louisiana in terms of total number of nesting birds 

(137,808) as well as number of colonies (52). The Common Tern was found at only one colony 

on a mud lump near the Mississippi River Delta’s South Pass with an abundance of 400 nesting 

birds. The Common Tern was previously only found with one pair of nesting birds on Curlew 

Island in 1988. The Sooty Tern, a species that has previously nested at Curlew Island in 1988, 

was not found during our survey. Colony size varied from a minimum of ten to a maximum of 

48,530 nesting seabirds. Approximately half (51%) of the colonies were smaller than 500 birds, 

with 21% of the colonies containing less than 100 birds each. Seabirds in Louisiana use four 

habitats: 1) vegetation, 2) wrack, 3) shell, and 4) sand. Forster’s Tern and the Common Tern 

were always found nesting on wrack. The Brown Pelican, Herring Gull, and Laughing Gull were 
528 

almost always found nesting in vegetation. The Gull-billed Tern showed the least consistent use 

of habitat, although half of the Gull-billed Tern colonies were found on shell. The Black 

Skimmer, Least Tern, Royal Tern, Caspian Tern, and Sandwich Tern were always found using 

either shell or sand for nesting habitat. 

The six largest colonies are all located on relatively large barrier islands, and these islands 

represent the majority (69%) of all seabirds nesting in Louisiana. An oil spill on any of these 

islands during the nesting season would be a disaster. Only the Least Tern, Black Skimmer, 

Forster’s Tern, and Laughing Gull are located in more than 15 colonies. These species are, 

therefore, less likely affected by the loss of one colony than other species. All other seabird 

species contain at least 10% of their Louisiana breeding population in each colony. The loss of a 

colony containing Royal Tern, Caspian Tern, Gull-billed Tern, Sandwich Tern, Brown Pelican, 

Herring Gull, or Common Tern would therefore have a much larger impact. 

The atlas of Louisiana seabird colonies compiled in this study should help remediators make 

informed decisions about how to protect nesting seabirds from oiling. Although we hesitate to 

give advice about where to concentrate oil spill response efforts, we suggest that measures be 

taken to prevent oiling of active colonies. For planning purposes, colonies that have been present 

in at least one of the last ten years should be considered active. Colonies that have not been 

active for more than ten years, probably reflect unsuitable habitat at the present. Due to the 

ephemeral nature of many seabird colonies, we recommend that the Louisiana Oil Spill 

Coordinator’s Office fund an aerial survey each year to verify the compiled seabird data. We also 

recommend that a ground survey be conducted every fifth year. 

Jenneke Visser is an Associate Professor Research in the Coastal Ecology Institute of the School 

of the Coast and Environment at Louisiana State University. She holds a Ph.D. in marine 

sciences from Louisiana State University and the equivalent of a M.Sc. in biology from the 

University of Amsterdam. Her research interests include Louisiana wetland restoration, wetland 

ecology, and seabirds. 
529 

LOUISIANA PETROCHEMICAL PIPELINES: STATUS OF AN INVENTORY 

OF GAS, AND HAZARDOUS MATERIALS PIPELINES IN THE STATE 

Robert Paulsell, Louisiana Geological Survey, Louisiana State University 

These digital pipeline data are intended to supplement emergency response and planning for 

hazardous materials spills emanating from petrochemical transmission pipelines within the state 

of Louisiana. The thousands of miles of pipelines within the state constitute a major source for 

oil spill and other pipeline related emergencies. Assessment of digital petrochemical pipeline 

data is crucial for effective energy planning, environmental monitoring, disaster prevention, and 

emergency preparedness. 

Any pipeline leak, large or small, can be dangerous to the public. These dangers include the 

obvious, volatile commodities exploding to inhalation hazards, and the not-so-obvious, small 

leaks that can seep through the permeable geology that lie beneath the pipelines and into the 

aquifer systems. The resulting damage could be irreversible and detrimental to potable water 

supplies throughout the region. The data developed can be used for emergency response as well 

as environmental and urban planning. 

Accurate pipeline maps and a Geographic Information System (GIS) will enable increased 

response efficiency by allowing emergency response teams to quickly assess the product, 

diameter, and operator of specific pipelines. In addition to oil, gas, and refined product 

transmission pipelines, chemical and other hazardous materials transported by pipeline have been 

included in the GIS spatial data. Emphasis was on transmission pipelines rather than those 

associated with gathering or distribution systems. Generally, the investigators considered 

transmission pipelines to be those with diameters of three or four inches and greater. 

Documentation on pipelines is difficult to acquire due mostly to the attacks on the United States 

by terrorists. Also, many operators feel their data is proprietary and opt not to share data. 

The Louisiana Geological Survey (LGS) has been compiling a digital pipeline database for the 

state for many years. Numerous maps and other geographic data concerning pipelines have been 

collected and cataloged. Most of these data have been in hard copy format, maps and other 

diagrams submitted by pipeline operators. Many of these submissions have poor spatial control 

and are not suitable for input into a GIS. Those data with good control were digitized. All 

submitted maps were helpful reference materials in the development of the spatial data. 

Source data gathered by the LGS fell into three categories: large-scale or engineering diagrams 

with geographic control suitable for digitization, maps of small scale and poor geographic 

control that were not digitized (useful as reference material), and undocumented pipelines. Some 

1,600 operator submitted maps are cataloged in the LGS inventory. One source of hard copy 

data, however, was found to be very helpful in route planning and pipeline feature development. 

The DTC Industrial Atlas, Houston, Texas, clearly shows most of the pipeline infrastructure 

within the parishes. The small scale of these maps, however, introduces errors of up to half a 
530 

mile in some areas. These maps are copyright protected and were used solely as reference 

material. Other hard copy references were of limited use for they were out of date. 

A method to digitally correct and create pipeline features has been developed by the LGS, 

utilizing Global Positioning System (GPS) technology. Point data were collected on pipeline 

witness posts locations that were observed near pipeline crossings of public roads. These records 

contained accurate positional data, information on pipeline operator, emergency contact 

telephone number, and information on the commodity transported by the pipeline. These data 

were compared to existing hard copy maps and digital pipeline data. Those data that did not 

conform to project guidelines were brought into compliance by comparison with GPS point data 

and aerial imagery. Pipeline features were developed utilizing aerial and satellite imagery, GPS 

point data, digital and hard copy maps or diagrams submitted by operators, and reliable third 

party maps. 

Creating a GIS of hazardous materials pipelines is detail intensive. The initial task was to 

determine the scope of in-house data. Evaluating the existing digital and hard copy data 

submitted by pipeline operators was first on the list of many tasks. Digital as well as traditional 

hard copy maps were intensively examined to determine spatial integrity. Third-party maps were 

very useful in determining location of and commodities transported by many pipelines. Most of 

the existing LGS pipeline data needed to be further developed to conform to the digital mapping 

standards set forth by the National Pipeline Mapping System (NPMS). These data standards were 

adopted by the LGS for our pipeline mapping efforts. 

The U.S. Department of Transportation, Office of Pipeline Safety, had created the National 

Pipeline Mapping System to “support the development of a reasonably accurate digital pipeline 

system” (www.npms.rspa.dot.gov). Generally, these data have very good spatial control; 

however, some data sets were found to contain errors, spatially and in their feature tables. 

However, the NPMS will not release or allow the LGS to release any of their data. Much concern 

has been placed on pipeline safety, and the Department of Homeland Security considers 

pipelines as part of our critical national infrastructure. This obstacle required the investigators to 

develop data that were initially to be included in deliverables “as submitted” by pipeline 

operators. 

The initial focus was to develop nonexistent data, but data acquisition problems and spatial 

uniformity problems (mostly feature segmentation) required feature development for all pipeline 

operators (i.e. all pipeline features were developed by the investigators with no operator 

developed data in the deliverables). The LGS uses the digital NPMS data and operator submitted 

data as reference materials only. We have developed digital pipeline data uniformly for all 

operators following guidelines created by the NPMS. Also, the NPMS is concerned with 

interstate pipelines, while the data developed at the LGS include intrastate lines also. 

Cooperation from pipeline operators has varied and is reflected in the available research data. 

The standards for data submission created by the NPMS allow for no more than a 500-foot 

margin of spatial error for pipeline data. The standards request that data be provided in digital 
531 

format with accompanying metadata. If digital data are not available, then the operator may 

submit hard-copy data. All submissions are to contain geospatial data (location data), attribute 

data (descriptive information), and metadata (description of the content, quality, condition, and 

other characteristics of the submitted data). 

Through funding from the Oil Spill Research and Development Program (OSRADP), a method 

to develop pipeline features and to adjust any spatially incorrect data has resulted in 

comprehensive petrochemical pipeline spatial data for East Baton Rouge, Calcasieu, and 

Ouachita Parishes along with the Greater New Orleans and Shreveport areas. These densely 

populated areas are considered high consequence areas (HCA) by the U.S. Department of 

Homeland Security. Spatial data covering pipeline crossings of navigated waterways is also 

being developed with this methodology. OSRADP projects include metropolitan pipeline data as 

well as river crossing pipeline data, also considered an HCA for the transportation infrastructure. 

These mapping efforts include cooperative pipeline GIS development with Dr. Michael Camille 

of the University of Louisiana at Monroe (ULM). Dr. Camille and his team have developed 

pipeline data for the Monroe and the Shreveport metropolitan areas. 

The following outlines the method used in digital pipeline feature development. 

 I. Data collection route planning. 

 A) Study existing data for potential stops (design a route plan) 

 B) Examine aerial imagery for confirmation or other stops 

 C) Review traffic scenarios (try not to be a hazard to the public or yourself) 

 II. GPS data collection and compilation 

 A) Compile data dictionary 

 B) Complete route plan 

 C) Ensure that all data is collected and documented thoroughly 

 III. Data projection and conversion 

 A) Upload GPS point data to GIS 

 B) Export features as ArcGIS Shapefile 

 C) Load shapefiles into ArcGIS Project 

 IV. Spatial feature GIS overlay and analysis 

 A) GPS point data theme 

 B) LGS digital pipelines theme 

 C) NPMS digital pipeline data 

 D) DOQQs and other themes from LaGIS CD to aid in analysis 

 V. Database normalization and quality assurance 

 A) Review digital attribute tables 

 B) Ensure database integrity (Quality Control) 
532 

 VI. Create CD and hard copy (report and maps) 

 VII. Assessment of spatial accuracy of digital pipeline data 

 A) Load digital point and linear pipeline data per operator into one view 

 1. GPS point data shapefiles developed per operator/commodity 

 2. Pipeline features, LGS and NPMS, per operator 

 3. Analysis unique to each operator and commodity 

 B) Develop pipeline features for data utilizing DOQQs, GPS point data, and third 

party maps 

Group layers within ArcMap were created for each operator and populated with requisite aerial 

imagery, GPS point data, existing digital pipeline data, road data, and other helpful themes. 

Pipeline features were created utilizing heads-up digitizing technology in ArcMap. Referencing 

digital and hard copy data, attributes were carefully populated into the pipeline feature tables. 

The analysis of digital pipeline data revealed many problems with spatial data accuracy. The 

most notable problems are a result of inadequate data. Most of the problems encountered were 

with submitted maps of inadequate scale and detail level. Data digitized at less than 1:24,000 

scale lead to excessive spatial displacement. In some areas, this displacement has been close to a 

mile. The many corporate mergers, acquisitions, and divestures in the pipelines industry also 

created difficulties in resolving data collection issues. Many observed witness posts did not 

match any digital or hard-copy data. 

The compilation and spatial analysis of digital pipeline data for the state of Louisiana is a 

complex process that will take years to accomplish. Although funding is the biggest obstacle to 

pipeline GIS development, the quantity and quality of data sources and the unique geographic 

parameters of each inhibit rapid development of a full-scale pipeline GIS for the state. 

Assessment of digital data, field investigations and the development of undocumented data are 

important to the statewide implementation of a pipeline GIS. The most prominent problem with 

existing digital data is spatial accuracy. Other problems have arisen through the conflicts 

between operator-supplied data and warning-post data in regard to transported commodities. 

Most of the digital data, digitized by the LGS or submitted by the operators, were incorporated 

into the GIS and displayed numerous problems associated with spatial accuracy. These issues 

were addressed by developing each pipeline feature utilizing GPS technology for spatial control. 

The GPS point data were also used to verify pipeline operator’s names, commodities transported, 

and emergency contact telephone numbers. 

The data developed through this and future pipeline mapping projects will eventually provide a 

comprehensive pipeline GIS for the state of Louisiana. As more operators develop and submit 

pipeline data and as the LGS and cooperative partners develop pipeline GIS, we will eventually 

have a comprehensive pipeline GIS for the state. However, no plans exist for the maintenance 

and updating of these critical data. With the constant corporate restructuring and economic 

growth, these data will need regular updating at least once a year. 
533 

GPS technology is very useful in pipeline mapping. Eventually, with this and other pipeline 

mapping efforts sponsored by OSRADP and other agencies/programs, the puzzle of pipelines in 

Louisiana will be put together. 

Robert Paulsell is a Research Associate 4 with the Louisiana Geological Survey, LSU. He 

graduated from LSU with a B.S. degree in geography with emphasis in mapping. He has been 

with the survey for fourteen years and has been active in pipeline mapping for eight years. 
534 

CHEMICAL ADDITIVES IN OILED FRESHWATER LABORATORY MICROCOSMS: 

TOXICITY TO AQUATIC ORGANISMS, RELATIONSHIP BETWEEN 

HYDROCARBON MEASUREMENTS AND TOXICITY, AND THE INFLUENCE OF 

CHEMICAL ADDITIVES ON HYDROCARBON DISAPPEARANCE 

Paul L. Klerks, Department of Biology, University of Louisiana at Lafayette 

1) Toxicity and temporal changes in toxicity of freshwater-marsh-microcosms containing South 

Louisiana Crude (SLC) or diesel fuel and treated with a cleaner or dispersant were 

investigated using Chironomus tentans, Daphnia pulex, and Oryzias latipes. Bioassays used 

microcosm water (for D. pulex and O. latipes) or soil slurry (for C. tentans) taken 1, 7, 31, 

and 186 days after treatment. SLC was less toxic than diesel, and both chemical additives 

enhanced oil toxicity (with the dispersant being more toxic than the cleaner). Toxicities 

decreased gradually over time. Toxicities were higher in the bioassay with the benthic 

species than in those with the two water-column species. A separate experiment showed that 

C. tentans’ sensitivity was intermediate to that of Tubifex tubifex and Hyallela azteca. 

Freshwater organisms, especially benthic invertebrates, thus appear seriously affected by oil 

under the worst-case-scenario of our microcosms. Moreover, the cleaner and dispersant 

tested were poor response options under those conditions. 

2) This research investigated the extent to which various common hydrocarbon measures can be 

used to predict toxicity to freshwater aquatic organisms due to fouling by oil. Actual toxicity 

results on laboratory freshwater marsh microcosms using two water-column species and a 

benthic species were described earlier. The hydrocarbon measures used were TPHg, TPHFID, 

TPHMS, TTAH (sum of 41 target aromatic hydrocarbons), principal components of 41 TAHs, 

and each individual TAH. In general, toxicity was more closely related to TPHMS levels than 

to TPHFID and (especially) TPHg levels. The strongest relationships were found for TTAH 

levels and for the principal components of the TAHs. Regressions of toxicity on many 

individual TAHs were also strong, with a single group of compounds explaining as much as 

59% of the variation in survival. While the various regressions were highly significant 

statistically and at times able to accurately predict broad differences in toxicity, the high 

variation in survival at a specific hydrocarbon concentration indicates that these hydrocarbon 

measures can not substitute for actual toxicity determinations in accurately ranking the 

toxicity of samples from oiled freshwater marshes. 

3) We evaluated the effects of a cleaner and a dispersant on changes in hydrocarbon 

concentration over time in 288 microcosms containing freshwater marsh soils. Microcosms 

received no hydrocarbons, South Louisiana crude, or diesel; and no additive, dispersant, or 

cleaner. Microcosms were divided into water and sediment fractions 1, 7, 31, or 186 days 

later so that hydrocarbons could be extracted with dichloromethane. We determined the 

concentrations of four gross hydrocarbon measures and 44 target hydrocarbons to assess 

temporal changes and effects of additives on hydrocarbon concentrations. Hydrocarbon 

concentrations declined 24% to 97% after six months, but were unaffected by additives. This 
535 

study indicated that Corexit 9500 and Corexit 9580 should not be used to accelerate 

hydrocarbon disappearance, but could be used without fear that they subsequently slow 

hydrocarbon disappearance, in wetland soils dominated by Panicum hemitomon, which occur 

throughout South America and the southeastern United States. 

Paul L. Klerks is Associate Professor of Biology at the University of Louisiana at Lafayette. He 

obtained his Ph.D. from SUNY Stony Brook in 1987 and joined UL Lafayette after post-docs at 

the University of Toledo and the Chesapeake Biological Lab. He is an ecotoxicologist focusing 

on the long-term effects of environmental contaminants in aquatic systems. 
536 

HISTORICAL ANALYSIS OF OIL SPILLS IN LOUISIANA 

George Wooddell, University of Louisiana – Lafayette 

Decision makers in government and industry need fast access to the facts about oil spills. But, 

current databases of oil spill characteristics are huge and unwieldy. The Louisiana Oil Spill 

Coordinator’s office has sought to rectify that situation. Thus, the current work is to present a 

simple, fast, self-contained, free CD database program for desktop computers that makes 

accessible to non-technical users massive amounts of information about actual oil spills. This 

paper describes the program its use and its uses. The data are a modified version of those 

collected by the National Response Center. 

For some years the authors have been studying Louisiana oil spills. Lately we have been 

immersed in massive and complex databases that must be manipulated by expensive and 

difficult-to-master database programs installed on high-end computers. Even with all of that, 

these databases have often crashed our machines and sometimes our brains. Still, we have 

learned a great deal by sifting through hundreds of thousands of records of spills. 

Most decision makers in matters of oil spill preparedness and prevention are not as well 

equipped as the authors and not so peculiarly trained. Yet the more we learned the more we saw 

that the daily decision makers in industry and government are the very people who need most to 

access and analyze this particular information about oil spills. Thus we are now trying to make 

the facts more widely available by means of a simple, intuitive, free computer program on a CD. 

This presentation introduces a simple, free, stand-alone computer program that makes the data 

accessible to a broad variety of oil spill decision makers. Starting sometime in 2004, those who 

ask the Louisiana Oil Spill Coordinator will be given the program on a CD (Figure 2H.1). This 

stand-alone program enables interested parties to query a large database of hazardous spills, to 

generate tables, and to do their own customized analyses. We submitted the program to the 

Office of the Louisiana Oil Spill Coordinator in August of 2003. 

Two years ago (2001) the authors downloaded and reassembled the data of the National 

Response Center (NRC), creating a relational database of seven tables, each composed of 

detailed descriptions of hazardous spills—including petroleum spills—from 1992 through 1999. 

As mentioned, it was big and complex. While we had it in that form we added latitudes and 

longitudes to about 87% of the spills that had occurred in Louisiana so that we could map them 

on computers. We converted the spill amounts to gallons, added an “Fyear” (file year) variable to 

denote the year designation on the downloaded NRC files, standardized county (parish) names 

and did some other superficial cleaning up. 
537 

Figure 2H.1. The Louisiana Oil Spill Database opening screen. 

Table 2H.1. The 30 variables used in the database. 

Received Parish 

Complete Zip 

Call Type Rad 

Resp. Company Bio 

Resp. City Oil 

Description FYear 

Spill Type Longitude 

Cause Latitude 

Date CHRIS CO 

Location CAS Number 

Address UN Number 

Street1 Gallons 

Street 2 AMT 

Nearest City Unit 

State Name 
538 

To make the data for the CD we drew thirty variables from multiple tables in the larger database 

and merged them into a single table, as shown in Table 2H.1, for use by the CD program. The 

variables were drawn from the NRC data (described more fully in the Appendix) and the 

latitudes and longitudes table developed by the authors for the Louisiana Oil Spill Research and 

Development Program. Along with the appendix in this document, the “About” and “Help” 

buttons in the program (pictured in Figure 2H.1) should answer most questions the user is likely 

to have. 

Dr. George Wooddell is an Associate Professor of Sociology in the Department of Sociology and 

Anthropology at the University of Louisiana at Lafayette in Lafayette, Louisiana. He has served 

as principal investigator on research projects with the Louisiana Applied Oil Spill Research and 

Development Program (OSRADP). His areas of research interest are environmental sociology, 

minority groups, crime, and risk analysis. He obtained his B.A. in sociology from the University 

of Southwestern Louisiana in 1983, his M.A. from Louisiana State University in 1993, and his 

Ph.D. from Louisiana State University in 1999. 
539 

AERIAL VIDEO SURVEYS ON INTERACTIVE DVDs 2001 COASTAL LOUISIANA 

AND THE LOWER MISSISSIPPI RIVER – ARKANSAS TO THE GULF OF MEXICO 

Karen A. Westphal, Louisiana State University 

For 20 years, the LSU Aerial Video Survey Program (AVSP) has been collecting aerial video 

imagery of a part of the northern Gulf Coast for use in shoreline change studies, oil spill 

contingency planning, and environmental studies or resource management. Historically, the 

imagery has been collected and disseminated on analog video tapes, requiring large amounts of 

storage and time to find and view selected footages. Through OSRADP, the AVSP developed a 

methodology for digitizing these analog records and organizing them on interactive DVDs to 

make storage and access less cumbersome and to provide a more efficient reference tool. 

 

Three surveys were committed to DVDs in this manner: 2001 imagery of coastal Louisiana, 

1996 imagery of the lower Mississippi River from Baton Rouge to the Gulf of Mexico, and 2003 

imagery of the lower Mississippi River from Baton Rouge to the Louisiana/Arkansas state line. 

 

The oblique, aerial videotape imagery was acquired from a helicopter in SVHS format. On the 

bottom of the video image, realtime navigation data from a Global Positioning System unit 

(GPS) was presented so that each image was referenced with latitude, longitude, compass 

heading of the aircraft, date and time. On-board audio was recorded to provide additional 

information or clarify features observed. The analog video imagery was then converted to digital 

data, compressed, and divided into manageable segments. 

 

The 2001 coastal video data was a simple, one-shoreline system and was divided into sections 

based on geography to fit on eight DVDs. The GPS data acquired during videotaping was 

downloaded and used as the data line from which video segments were indexed and chosen. 

Clicking within delineated areas on an image of the Louisiana coastline brings up subdirectories 

for that area showing a section of the coastline with place names. Clicking on a specific spot 

along the subdirectory shoreline initiates a digital playback of imagery for that area of the 

shoreline. 

The 1996 and 2003 video data of the lower Mississippi River was a more complex project 

involving a two-shoreline system. This two-year project produced a set of DVDs containing 

easily accessed aerial video imagery of both banks of the Mississippi River from the 

Arkansas/Louisiana state line to the Gulf of Mexico. Whenever possible, imagery of pipelines, 

facilities and other features were identified and linked to maps and lists by River Mile. Both 

banks were linked, so that either side can be viewed at a particular stretch of the river. 

 

Although the realtime navigation data from a GPS unit was presented on the bottom of the video 

image, location along the river was more difficult to determine. An additional label was added on 

the video image near the GPS line at every half-mile to indicate which bank of the river was 

being viewed, the approximate half-mile, and the direction of river flow to the Gulf of Mexico. 
540 

Because the 2003 video includes both Louisiana and Mississippi shorelines, the label on the 

2003 imagery includes place names and state affiliation of the river shoreline. At every mile and 

major crossing, a link has been provided to the other side of the river at that location. A series of 

tables that lists features of interest along the Mississippi River is linked to the video imagery to 

provide an alternate method of accessing the data. 

Karen Westphal earned her B.S. in zoology from LSU in 1978. She is now a coastal scientist and 

the manager of the LSU Aerial Video Survey Program at the School of the Coast and 

Environment Special Programs, Baton Rouge, Louisiana. She has been working with coastal 

issues and aerial video within the Louisiana coastal zone for over 25 years, with research efforts 

aimed at coastal change, coastal vegetation, bio-geomorphology, and habitat delineation. 
541 

DISPERSANT EFFECTS ON MARSH VEGETATION: 

TOXICITY EVALUATION AND OIL REMEDIATION 

Qianxin Lin, Wetland Biogeochemistry Institute, Louisiana State University 

Oil spills in nearshore or estuarine environments may eventually move into coastal marshes by 

currents, tides and winds, strand inside marshes, and impact coastal marsh organisms. Preventing 

oil from stranding and coating coastal sensitive habitats is an important step in protecting these 

habitats. Dispersants, which have received considerable attention for open, deep water oil spills, 

may be a candidate, but require evaluation for oil spill countermeasure in the nearshore and in 

wetlands. One strategy for habitat protection and oil remediation might be to apply dispersants to 

the spilled oil before the oil drifts into coastal marshes. However, little information is available 

on the toxicity and effects of dispersants on marsh habitats and the strategy of dispersant-use in 

the nearshore to protect sensitive coastal habitats. 

The overall goal of the project was to determine the potential use of dispersants as an oil spill 

countermeasure in nearshore environments in which spilled oil may move into coastal marshes 

and impact these sensitive habitats. Specifically, the objectives of this study were to 1) evaluate 

the toxicity of dispersants on coastal marsh plants by determining the dose-response of plants to 

dispersants, per se; 2) evaluate different dispersed oils (crude oil and diesel fuel) on coastal 

marsh plants by determining the dose-response of plants to dispersed oils in the soil; and 

3) compare the effect of dispersed oils (diesel and crude) in simulated nearshore dispersant 

application on marsh habitat protection. 

Dispersants used today are more effective and much less toxic than those used previously. In this 

research, we used dispersant JD-2000. The dispersant JD-2000, manufactured and marketed by 

Van Waters and Rogers in 2001 and listed in the National Contingency Plan, is especially 

effective for South Louisiana crude oil for both salt and fresh water. The dose-response of the 

fresh marsh plant Sagittaria lancifolia and salt marsh plant Spartina alterniflora to the dispersant 

JD-2000 indicated that plant tolerance to dispersants, per se, was relatively high. The marsh plant 

S. lancifolia was not impacted by the dispersant JD-2000 at dosages ≤ 4,000 ppm based on plant 

photosynthetic rate, plant mortality rate, and plant aboveground biomass. Sagittaria lancifolia

and Spartina alterniflora were able to recover at dispersant dosages as high as 16,000 ppm 

because the toxicity of the dispersant decreased during time the ten-month experiment. 

In the experiments that determined the dose-response relationship and toxicity of dispersed oils 

to the fresh marsh plant Sagittaria lancifolia and salt marsh grass Spartina alterniflora, different 

concentrations of the JD-2000 dispersed diesel or crude oil (at the dispersant to oil ratio of 1:20) 

were applied to the soil. The plant photosynthetic rate, plant mortality rate, and plant 

aboveground biomass were negatively affected by the JD-2000 dispersed diesel applied to the 

soil substrate at high concentration. The LC50 (6 weeks) of dispersed diesel to Sagittaria lancifolia

was estimated at 20,000 ppm. The LC50 (6 weeks) of dispersed diesel to Spartina alterniflora was 

estimated at 14,000 ppm. However, dispersed south Louisiana crude oil did not detrimentally 
542 

affect Sagittaria lancifolia even at an oil dosage of 145,800 ppm. This indicated that the toxicity 

of the dispersed oil primarily resulted from the oil itself, not from the dispersants. 

In an experiment that simulated oil dispersed before coming in contact with marshes, the 

dispersant JD-2000 greatly relieved the adverse effect of both diesel and crude oil. When both 

diesel and crude oil without the dispersant contacted the leaves, photosynthetic rate was 

significantly decreased and mortality increased even at a 50-ppm dosage. Two thousand ppm of 

diesel without the dispersant resulted in > 60% mortality of aboveground components of fresh 

marsh plant Sagittaria lancifolia. In addition, one thousand ppm of diesel without the dispersant 

resulted in > 90% mortality of aboveground components of salt marsh grass Spartina 

alterniflora. In contrast, neither the dispersed crude nor dispersed diesel significantly affected 

Sagittaria lancifolia and Spartina alterniflora compared to the no-oil control. 

Therefore, dispersant application greatly reduced oil impact on marsh vegetation, indicating the 

potential of using dispersants as an alternative countermeasure for oil spills in nearshore or 

estuarine environments. 

Qianxin Lin is the Assistant Professor, Wetland Biogeochemistry Institute, Louisiana State 

University. His research primarily focuses on fates, effects, and remediation of oil spill in coastal 

wetlands, particularly in bioremediation, phytoremediation, in-situ burning, dispersant 

application and remediation of oil spills in wetlands. 
543 

DESIGN, IMPLEMENTATION, OPERATION AND MAINTENANCE OF 

AN OCEAN OBSERVING SYSTEM OFF COASTAL LOUISIANA AND 

APPLICATION TO OIL SPILL CONTINGENCY 

Gregory Stone, Coastal Studies Institute, Louisiana State University 

Here we present the WAVCIS (WAVe-Current-Surge Information System) program and its 

usefulness for oil spill contingency. We emphasize the development of the program to assist in 

oil spill related issues, an important facet of a multi-faceted application. We also concentrate on 

further developing data processing techniques, product creation, quality control, data archiving 

and dissemination on the World Wide Web, integrative GIS web design and integration with 

other data bases, all of which are important for oil spill contingency along coastal Louisiana. 

Data obtained during tropical cyclones (Claudette and Bill), are also summarized as a gauge of 

the success of the program during extremely hazardous conditions in the Gulf of Mexico (GOM). 

New products discussed will provide numerous benefits to LOSCO, including enhancement of 

trajectory and circulation modeling, quantification of local currents required for the use of 

alternative technologies such as dispersants and in-situ burning, provision for rapidly obtaining 

critical information that would otherwise take precious hours to obtain by the conventional 

methods of aerial observations, and drifter buoy deployments. 

WAVCIS measurements include wave height, wave period, wave direction, directional wave 

spectra, current speed, current direction, conductivity, turbidity, water depth, surge, sea 

temperature, air temperature, wind speed, wind direction, visibility, humidity, salinity, chlorine, 

and dissolved oxygen. Data measured offshore are transferred to the WAVCIS data processing 

laboratory via satellite cellular telecommunication. After post-processing, the data are archived 

in a SQL database and available to users via the World Wide Web in near/real-time basis. The 

WAVCIS array is also being developed to serve as a workbench for numerical wave, current and 

surge models for the scientific and engineering community. However, identified WAVCIS users 

include federal and government agencies, military, the scientific and engineering communities, 

students, the offshore industry, and recreation and sports groups. Usage has exceeded 50,000 

logons over a five-hour period during tropical cyclone activity. 

At present, six stations are online off the Louisiana coast (Figure 2H.2), and additional funding 

has been secured through federal agencies to support and expand the instrumentation array and 

necessary hardware. The ultimate objective of WAVCIS is to support Louisiana’s ability to 

anticipate and prepare for emergencies offshore (oil spills, hurricanes, winter storms, shipping 

accidents, etc.), enhance homeland security, and assist numerical modeling efforts during storm 

events by measuring important oceanographic and meteorological information and making it 

available in real time, or, after archiving for 24-hour and one-month options, as a time series. 

The short-term goal, however, is to develop an online program that will be consistent with the 

needs of LOSCO. The entire effort is being coordinated with several other ocean observatories in 

the GOM to enhance geographic coverage. Current efforts are to continue refining a workbench 

for multiple applications and fine tuning this effort for oil spill contingency. 
544 

Figure 2H.2. Location of currently active WAVCIS stations along the northern Gulf of Mexico. 

Dr. Gregory W. Stone is an expert in coastal processes and coastal erosion issues in Louisiana 

and elsewhere along the northern Gulf of Mexico. His doctoral research was conducted at the 

University of Maryland and focused on coastal morphodynamics. He has studied coastal 

problems for over two decades and is actively engaged in several erosion mitigation projects in 

coastal Louisiana. He is also an expert in measuring coastal processes and beach impacts due to 

storms and hurricanes. Dr. Stone is the Director of the Coastal Studies Institute at Louisiana 

State University where he was recently named the James P. Morgan Distinguished Professor. He 
545 

is also a Professor in the Department of Oceanography and Coastal Sciences at LSU and Director 

of the WAVCIS (Wave-Current-Surge Information System—(www.wavcis.lsu.edu)) ocean 

observing system. He has published over 150 scientific papers/reports on coastal systems and 

serves as Deputy-Editor-in-Chief of the Journal of Coastal Research. 
547 

SESSION 2I 

DEEPWATER PHYSICAL OCEANOGRAPHY INITIATIVE, PART II 

Chair: Alexis Lugo-Fernandez, Minerals Management Service 

Co-Chair: Carole Current, Minerals Management Service 

DEEPWATER MOORING AT 87°W AND 25.5°N Masamichi Inoue, Susan E. Welsh, 

and Lawrence J. Rouse, Jr........................................................................................................... 549 

DEEPWATER EULERIAN OBSERVATIONS OF CURRENTS Peter Hamilton.................. 557 

PIES MEASUREMENTS IN THE DEEP GULF OF MEXICO Kathleen Donohue, 

D. Randolph Watts, and Karen L. Tracey................................................................................... 564 

DEEPWATER LAGRANGIAN OBSERVATIONS OF CURRENTS IN THE GULF OF 

MEXICO Kevin D. Leaman ...................................................................................................... 570 

HIGH RESOLUTION MODELING OF THE GULF Susan E. Welsh and 

Masamichi Inoue......................................................................................................................... 573 
549 

DEEPWATER MOORING AT 87°W AND 25.5°N 

Masamichi Inoue, Susan E. Welsh, and Lawrence J. Rouse, Jr., 

Department of Oceanography & Coastal Sciences and 

Coastal Studies Institute, Louisiana State University 

Introduction 

In the Gulf of Mexico (GOM), the upper-layer circulation is dominated by the Loop Current 

(LC) in the eastern GOM and the Loop Current eddies (LCE) in the central and western GOM. 

Despite the fact that the deepwater in the GOM is isolated below the sill depths (~800 m in the 

Florida Strait and ~1,900m in the Yucatan Channel), deepwater in the GOM appears to be well 

ventilated, suggesting some energy propagation from the upper layer to deepwater inside the 

GOM. Cyclonic eddies in deepwater (e.g., Hurlburt and Thompson 1982) and topographic 

Rossby waves over the northern continental slope region (e.g., Hamilton 1990; Hamilton and 

Lugo-Fernandez 2001) have been suggested as agents of energetic forcing in deepwater in 

various numerical model studies as well as in observations. As a continuing effort to measure 

and monitor variability in energy level and water mass characteristics in the deep eastern GOM, 

a third deployment of a deepwater mooring was successfully completed, and the preliminary 

results are presented here. 

Methods 

A deep-water mooring strategically located to monitor the LC rings on their generally westward 

journey toward the western GOM was deployed at 87°W and 25.5°N at a water depth of 3,356 

m. The mooring was equipped with two ADCPs, one upward-looking at 140 m and the other 

downward-looking at 3,200 m, and six Aanderra current meters set at 155, 750, 1500, 2500, 

3000, and 3200 m to sample the entire water column. The initial deployment took place on 1 

June 2000. The mooring was successfully turned-around in 1 August 2001, and was subsequently recovered on 3 June 2002. The third deployment took place on 19 April 2003, and the 

mooring was successfully recovered on 11 June 2004. 

Results 

Data from the third deployment show the dominance of the LC in the upper layer (Figure 2I.1). 

The water column sampled behaves basically like a two-layer system with an interface located 

near 750~1,000 m. In comparing to the altimeter data archived at the University Colorado 

(TOPEX/ERS-2 observations), several energetic events observed in the upper layer correspond 

to the time when the high-speed core of LC was sweeping past the mooring site. Currents in the 

lower layer are generally weaker than those in the upper layer and often appear to be decoupled 

from the upper layer currents. Currents in the lower layer are vertically coherent below the 

interface. Deep currents can typically reach speeds of 30~ 40 cm/s. Deepwater currents were 

significantly stronger during deployment three than deployments one and two (Figure 2I.2), 

while the upper layer currents appear to be comparable between one, two, and three. 
550 

Figure 2I.1. 40-hour low pass filtered ADCP and current meter data at each instrument on the Deep Gulf 

Mooring for the period April 2003–June 2004. 
551 

For the first time, very strong currents exceeding 50 cm/s speeds were observed in deepwater in 

the eastern GOM. This two-day extreme event occurred between 18 and 20 July 2003, when 

currents in the upper and lower layers were well coupled, i.e., vertically uniform one-knot 

currents appeared to extend well into the upper layer. As a result, the entire water column at the 

mooring site was moving northward. The near-surface currents were significantly faster than one 

knot. However, it is difficult to estimate the actual current speeds near the surface due to a 

notable blow over of the mooring exceeding 300 m. Concurrent TOPEX/ERS-2 observations 

suggest that this extreme event coincided with the passage of the western wall of the LC over the 

mooring site. Current speeds measured at three different depths in deepwater (Figure 2I.3) 

suggest that currents at 2,000 m strengthen first, followed by currents at progressively deeper 

depths (3,000 m and 3,200 m). This extreme event resulted in the introduction of a colder and 

saltier water mass at 2,000 m (Figures 2I.4 and 2I.5). The vertical extent of the newly-introduced 

water mass in deepwater cannot be estimated due to the lack of temperature and salinity 

measurements with sufficient resolution below 2,000 m. Abrupt replacement of water mass 

extended into the upper layer, and colder and saltier water appeared even at 800 m. At 300 m and 

150 m, this extreme event coincided with cooling and freshening of water mass, indicating that 

the mooring moved outside of the LC. At 2,000 m, the newly-introduced colder and saltier water 

appears to persist for more than two weeks, while water mass characteristics at shallower depths 

appear to rebound quicker. The characteristics of the newly-introduced water mass at 2,000 m 

suggest this type of extreme event might represent a mechanism to introduce colder and saltier 

inflow of deepwater from the Caribbean Sea that presumably takes place near Cuba at Yucatan 

Channel (McLellan and Nowlin 1963) into the interior region of the eastern GOM. 

In terms of variability of water mass properties in deepwater, significant differences are observed 

between above sill depths (~1,900m) and below. Figure 2I.6 shows temperature measurements at 

1,500 m during deployments one and two. Significant low frequency variability (20 days ~ 

several months) is present at 1,500m located above sill depths. Near sill depths at 2,000 m, less 

low frequency energy is observed (Figure 2I.7). At 2,500 m well below sill depths, most of the 

energy is contained in shorter frequency variability with significant short bursts of strong events 

(Figure 2I.8). These observations suggest that below sill depths, mixing of water mass is 

dominated by short-duration (lasting ~ 2 days) events, while above sill depths horizontal 

advection of different water masses (presumably flowing in from the Caribbean Sea) passing the 

mooring site manifests itself as longer frequency (20 days to several months) variability of water 

masses. Identity of the short-duration energetic events in deepwater still needs to be established. 

Conclusions 

The first direct observations of extreme currents exceeding one knot in deepwater were made in 

the central eastern GOM below the LC. This extreme event coincided with the passage of the 

western wall of the LC over the mooring site. This event lasted only two days. However, during 

this event, the entire water column was moving northward. Moreover, this event resulted in the 

introduction of colder and saltier water mass in deepwater. It appears that these extreme events 

might represent a mechanism by which to introduce colder and saltier inflow of deepwater from 

the Caribbean Sea into the interior region of the eastern GOM. 
552 

Figure 2I.2. Vertical profile of current speed (mean and maximum) measured during the deployments one 

and two and deployment three. During deployment three, deepwater currents were much 

stronger in both mean and maximum than deployments one and two. 

Figure 2I.3. Hourly current meter data at 2,000 m, 3,000 m and 3,200 m on the Deep Gulf Mooring in July 

2003. 
553 

Figure 2I.4. Hourly temperature data at 2,000 m in July 2003. 

Figure 2I.5. Hourly salinity data at 2,000 m in July 2003. 
554 

Figure 2I.6. Hourly temperature measured at 1,500 m during deployments one and two. 

Figure 2I.7. Hourly temperature measured at 2,000 m during deployment three. 
555 

Figure 2I.8. Hourly temperature measured at 2,500 m during deployments one and two. 

These observations suggest that interannual variability of deepwater currents in the eastern GOM 

can be significant, and in order to establish climatology of deepwater currents extended 

measurements of deepwater currents are required. 

References 

Hamilton, P. 1990. Deep currents in the Gulf of Mexico. Journal of Physical Oceanography 

20:1087–1104. 

Hamilton, P. and A. Lugo-Fernandez. 2001. Observations of high-speed deep currents in the 

northern Gulf of Mexico. Geophysical Research Letters 28(14):2867–2870. 

Hurlburt, H.E. and J.D. Thompson. 1982. The dynamics of the Loop Current and shed eddies in 

a numerical model of the Gulf of Mexico. In: Nihoul, J.C.J., ed. Hydrodynamics of SemiEnclosed Seas. Elsevier. Pp. 243–298. 

McLellan, H.J. and W.D. Nowlin. 1963. Some features of the deep water in the Gulf of Mexico. 

Journal of Marine Research 21:233–245. 
556 

Dr. Masamichi Inoue has worked at Florida State University and at Australian Institute of 

Marine Science. He has been at Louisiana State University for the past 17 years and is Associate 

Professor in the Department of Oceanography & Coastal Sciences and at the Coastal Studies 

Institute. His research interests include ocean circulation and transport processes. Dr. Inoue 

received his B.E. in naval architecture from Tokai University, M.S. in ocean engineering from 

University of Rhode Island, M.E. in civil engineering and Ph.D. in oceanography from Texas 

A&M University. 

Dr. Susan Welsh has worked in the Coastal Studies Institute for the past 15 years as a scientific 

programmer/modeler, a graduate assistant, a post-doctoral researcher, an assistant professorresearch and presently as a Research Associate. Her areas of research are physical oceanography, 

numerical ocean models, and Gulf of Mexico circulation. Dr. Welsh received her B.S. in earth 

and planetary sciences from the Johns Hopkins University, her M.S. in oceanography from the 

Florida State University, and her Ph.D. in geology from Louisiana State University. 

Dr. Lawrence Rouse is the director of the Coastal Marine Institute and Chair of the Department 

of Oceanography & Coastal Sciences at Louisiana State University. He is also an Associate 

Professor in the Department of Oceanography & Coastal Sciences and at the Coastal Studies 

Institute. His research interests are in coastal and shelf circulation, estuarine-shelf exchange, and 

remote sensing analysis of these processes. He received his Ph.D. in physics from Louisiana 

State University in 1972. 
557 

DEEPWATER EULERIAN OBSERVATIONS OF CURRENTS 

Peter Hamilton, Science Applications International Corporation 

Introduction 

The observational part of the yearlong MMS Exploratory Program was completed in April 2004. 

The moored array was located over the central part of the northern Gulf of Mexico (GOM) slope, 

between water depths of 1,000 and 3,000 m, and consisted of 27 Inverted Echo Sounders with 

Pressure (PIES), 15 short lower-layer and 4 full-depth current meter moorings. Six near-bottom 

current meter moorings, deployed by the oil industry across the Sigsbee Escarpment, and two 

single full-depth moorings, deployed by CICESE and LSU, respectively, supplemented this array 

(Figure 2I.9). The study also has extensive remote sensing and deep Lagrangian float program 

elements designed to observe the large-scale phenomena influencing the fixed position array. In 

this paper, only the measurements that pertain to deep lower-layer flow events are discussed. 

Figure 2I.9. Map of mooring positions for the Exploratory, SEBCEP (Industry) and LSU programs. The top 

and bottom of the escarpment are separated by about 500-m depth. 
558 

Previous current observations below 1,000 m in the GOM have established that flows are 

dominated by Topographic Rossby waves (TRW) (Hamilton 1990; Hamilton and LugoFernandez 2001). TRWs are dispersive planetary waves, controlled by the slope of the local 

seabed, that have periods of ~ 7–100 days, wavelengths of ~ 100–200 km, and propagate at ~ 

10–20 km d-1 in a direction such that shallower water is to the right (e.g. westward in the 

northern Gulf). Motions are highly coherent in the vertical and bottom intensified. When upperlayer eddy activity is minimal, TRW motions can penetrate weakly up to within a few 100 m of 

the surface (Hamilton 2005). Normally, however, the vigorous eddy circulations in the upper 800 

to 1,000 m of the Gulf have little apparent connections with the deep TRWs. Model studies 

indicate that TRWs are generated by Loop Current (LC) fluctuations and the translation of LC 

anticyclones across the central and western Gulf. The processes of TRW genesis are yet to be 

elucidated and have not been clearly observed. It is suspected, in analogy with the Gulf Stream in 

the Northwest Atlantic, that the LC is a major source of TRWs with wave energy propagating 

towards the slope of the northern central Gulf. The steep Sigsbee escarpment (500 m depth 

change in 10 to 20 km) meanders across the study region with depths at the bottom of the slope 

ranging from 2,000 m in the east to 3,000 m in the west (Figure 2I.9). This major topographic 

feature must influence the propagation of the TRWs by refraction and/or reflection, and different 

period waves will have different propagation characteristics. A central question is whether the 

escarpment acts as barrier to energetic motions on the middle and upper northern Gulf slope, by 

reflecting deep TRWs south into the deep Gulf basin. This topic is the main subject of the 

preliminary analysis reported here. 

Deep Currents 

Previous studies established that the region near 90°W at the base of the escarpment (near M1 in 

Figure 2I.9) had high energy current fluctuations (a near-bottom maximum of 90 cm/s was reported by Hamilton and Lugo-Fernandez (2001)) that were interpreted as TRWs with unusually 

short periods (~ 10 to 12 days) and wavelengths (~ 70 km) compared to deep basin measurements further west, which had dominant periods ~ 20–30 days and current magnitudes of 10–20 

cm/s (Hamilton 1990). Furthermore, current measurements above the escarpment at 90°W 

showed the strong flows rarely penetrated into shallower water. Thus, it appeared that the escarpment was blocking the transfer of wave energy to the slope above the escarpment. Therefore it 

was concluded that most TRW energy at these short periods was reflected from the escarpment 

with the possibility of some being transferred to enhanced mean flows over the escarpment. The 

present study sheds more light on this process by placing it in a regional context. 

The fluctuation kinetic energy was calculated from the yearlong velocity records that have been 

filtered with a 40-hour low pass (HLP) Lanczos kernel, as is shown in Figure 2I.10. The majority 

of the records were about 100 m from the bottom; however, for a few moorings, velocities at 500 

m above the bottom were used. There is a clear reduction in energy from east to west across the 

escarpment, and there are two regions on the deep side of the escarpment with high variance: one 

in the northeast corner (L1, M1 & N2), and the second further west around O3 and N4. 

Furthermore, mean velocities close to the escarpment are enhanced and directed along the 

escarpment towards the west. This kind of westward deep mean current along the base of the 

continental slope has been observed in model studies. Industry measurements at S3 were the only 
559 

ones made above the boundary layer in the middle of the escarpment slope, and compared to 

nearby mean flows above (at S6) and below (at L4) the escarpment, the mean current is more 

than twice as strong (~ 14 cm/s). Examination of the 40-HLP velocity record at S3 shows that the 

fluctuations are directed westward and parallel to the slope and rarely reverse, unlike lowerlayer, low-frequency fluctuations at other locations. Therefore, over this transect at ~ 91°8’W, 

there is a westward directed jet centered over the escarpment, which is probably a result of 

transfer of a portion of the fluctuation kinetic energy of the TRWs to the mean. 

Figure 2I.10. Contours of 40-HLP mean kinetic energy, overlaid with 40-HLP mean velocity vectors, for near 

bottom current meter data. Averaging interval is one year. 

The kinetic energy spectra, in variance preserving form where equal areas under the curve 

represent equal variances, are shown for lower layer currents at three of the tall moorings in 

Figure 2I.11. All three moorings show increases in energy with increasing depth of the 

measurement, except for the 2,925 m currents at the L5 (LSU) mooring, which is probably 
560 

within the bottom boundary layer. This bottom intensification is typical of TRW motions. The 

spectra at the different locations have different characteristics and energy levels. In the southeast 

corner at L3, the major peak is at 12.5 days, with less energetic peaks at ~18 and 40 days. At L5, 

which is further west and close to the base of the escarpment, the ~20 day peak dominates 

though there is also substantial energy at ~ 40 days. The 12.5-day motions are largely absent. In 

the southwest of the array at L4, only the ~ 40 day peak is present, and it shows much less 

variance than at L5. Kinetic energy spectra for the other moorings (not shown) show similar 

changes in the periods of the dominant motions for differing locations as well as the changes in 

total variance across the escarpment seen in Figure 2I.10. Generally short period motions of ~ 8 

to 14 days periods are important on the east side of the array and not observed in the west, where 

longer period fluctuations dominate. At M1, large amplitude fluctuations with periods ~ 10 days 

dominate similar to previous measurements in this region reported by Hamilton and LugoFernandez (2001). 

Figure 2I.11. Kinetic energy spectra of 40-HLP currents at selected depths below 1,000 m for the tall 

moorings L3, L5 (LSU) and L4. 

An explanation of the complex mixture of periods that dominate the currents in different parts of 

the array that is south of the escarpment is that TRWs of different frequencies have different 

paths and possibly different sources. Thus, long period waves propagate more nearly parallel to 

the isobaths and are unable to penetrate into shallower water depths. The short-period waves 

propagate across the isobaths and appear to be trapped in the northeast corner of the array. This 

is illustrated in Figure 2I.12 where near-bottom current fluctuations in two frequency bands are 

analyzed using frequency domain EOFs. The first-mode fluctuations, which account for ~ 50% 

of the total variance of all the data, describe the dominant coherent signals along with their phase 
561 

propagation. The lowest frequency band, which has most of the variance at L4, indicates that 

most of the fluctuations with the largest amplitudes are in the southern part of the array with little 

penetration above the escarpment and east of ~ 90.5°W along the escarpment. Wavelengths of 

TRWs were calculated from the phase differences of the mode using the four locations in the 

southeast corner (L3, O1, O2 and Q2) and a propagation path calculated using the ray tracing 

equations (Pickart 1995). Rays were calculated both backward and forward of the initial position 

for the center frequency of the mode. The result is shown in Figure 2I.12 and shows that the 

refraction keeps the energy in the southern part of the array. The ray path, however, is predicted 

to cross the escarpment. If the wave is reflected when it reaches the escarpment, the path, given 

by the dashed line, is more in accordance with the energetic fluctuations observed along the 

bottom edge of the escarpment. If this long period wave is traced backwards, then it shows that 

its origin could have been under the Loop Current about 10 to 15 days earlier. The EOF analysis 

of the short period (17–11 day) motions show that the higher amplitudes are found on the eastern 

side of the array and along the escarpment east of ~ 91°W (Figure 2I.12). It is noted that the 

major axes of the fluctuation ellipses are parallel to the escarpment for the locations immediately 

below the steep slope and perpendicular to the escarpment at M3 and N5 above the slope. This 

indicates that this short period TRW has different characteristics above and along the escarpment 

and again along the TRW ray path, initialized using the M1, M2 and N3 phase differences, 

corresponds better to the observations if the wave is reflected at the slope. The 13.4-day period 

ray paths are halted when the bottom slope becomes small south of the 3,000-m isobath. This 

seems to indicate that short period, short-wavelength TRWs are generated fairly locally to 90°W 

and remain trapped by the topography in this region (Hamilton 2005). 

Figure 2I.12. First frequency domain EOF modes shown as amplitude ellipses (red) where the relative phase 

is given by the arrowhead. LH panel: 335-33 day motions; RH panel: 17-11 day motions. The 

heavy black lines are TRW propagation paths calculated by ray tracing forward and 

backwards from the blue dots using the indicated periods and wavelengths as initial conditions. 

Arrow heads on the paths are at five-day intervals. 
562 

Figure 2I.13. Smoothed Lagrangian RAFOS trajectories for the indicated floats. The deployment depths of 

the floats are indicated and the arrowheads are at 10-day intervals. 

The spatial variability of the low-frequency content of the lower-layer current observations have 

been discussed in terms of propagating dispersive planetary waves. It would be difficult to 

explain these observations in terms of lower-layer eddies moving through the region, because 

even if the eddies were steered by the topography of the escarpment, the signal content at the 

different positions south of the escarpment would be very similar, contrary to the observations. 

One crucial difference between eddies and waves is that westward propagating eddies transport 

mass as well as momentum. If this were the case, then the deep Lagrangian float trajectories 

would translate westward accompanied by cyclonic or anticyclonic circular or elliptical rotations 

similar in manner to surface floats deployed in Loop Current anticyclones. Lagrangian 

trajectories of deep TRW motions would be similar to the elliptical or rectilinear vector 

hodographs in Figure 2I.12 with little translation in the mean unless mean currents are large, 

such as at S3 over the escarpment. Four trajectories from the RAFOS float program are given in 

Figure 2I.13. One pair remains south of the array and the other pair east of the array for the ~ 

5months of data coverage. Even though the floats are at different depths, each of the pairs had 

similar paths. For the eastern pair the 1,000-m float has smaller amplitude displacements than the 
563 

deeper 1,500-m float, as is expected for bottom-intensified fluctuations. For the southern pair, 

the displacements are similar in magnitude and both floats have initial westward displacements 

caused by the mean flow over the escarpment. The trajectories have similar period fluctuations, 

which are both cyclonic and anticyclonic, to those found in the nearby current meter records, 

discussed above (e.g. L4 for floats 0456 and 0476, and L3 for 0470 and 0466 (Figure 2I.13)). 

Thus, the float displacements, in the region of the moored array, have more in common with 

TRWs than translating lower-layer eddies. 

References 

Hamilton, P. 1990. Deep currents in the Gulf of Mexico. Journal of Physical Oceanography 

20:1087–1104. 

Hamilton, P. 2005. Deep current variability near the Sigsbee Escarpment in the Gulf of Mexico. 

Journal of Physical Oceanography. 

Hamilton, P. and A. Lugo-Fernandez, 2001. Observations of high speed deep currents in the 

northern Gulf of Mexico. Geophysical Research Letter 28:2867–2870. 

Pickart, R.S. 1995. Gulf Stream-generated topographic Rossby waves. Journal of Physical 

Oceanography 25:574–584. 

Dr. Peter Hamilton is a Senior Oceanographer with Science Applications International 

Corporation. He has served as a Principal Investigator on many MMS programs in the Gulf of 

Mexico and other coastal seas. He received his Ph.D. from the University of Liverpool (UK) in 

1973. 

 
564 

PIES MEASUREMENTS IN THE DEEP GULF OF MEXICO 

Kathleen Donohue, D. Randolph Watts, and Karen L. Tracey, 

Graduate School of Oceanography, University of Rhode Island 

Introduction 

A mesoscale-resolving array of twenty-seven inverted echo sounders with pressure gauges 

(PIES) and fifteen deep current meters deployed in March 2003 and recovered in April 2004 

constitute part of the Exploratory Study of Deep Water Currents in the Gulf of Mexico funded by 

Mineral Management Services (Figure 2I.14). Round-trip acoustic travel time measured by the 

inverted echo sounder is converted to vertical profiles of temperature, salinity, and density via an 

empirical relationship determined by historical hydrography. Comparisons between estimated 

and directly-measured mooring temperatures indicate that the empirical relationship holds well 

in the Gulf of Mexico (GOM). Key circulation processes in a deep-water region in the GOM are 

identified by quantitative mapping of the regional circulation. Coherent deep-eddy structures are 

associated with shifts in the Loop Current and Loop Current eddies. During the measurement 

time period, the Loop Current extended northward into the eastern portion of the array. In June, a 

Loop Current Eddy formed and subsequently reattached to the Loop Current by the end of the 

month. Another Loop Current Eddy, Eddy Sargassum, formed in late July and remained 

detached. Immediately after Eddy Sargassum detached the deep pressure field shows a burst of 

strong eddy activity comprising topographic Rossby waves and cyclones and anticyclones. 

Elevated deep energy levels occur at this time. 

PIES Instrumentation 

PIES is a bottom-mounted instrument which emits 12 kHz sound pulses, measures round trip 

travel times of acoustic pulses to sea surface and back and measures bottom pressure. A PIES 

mooring consists of a 17" glass sphere with a 150 lb anchor stand (Figure 2I.15). A sample burst 

of twenty-four 12-kHz pings is transmitted every half hour; the quartile value of each travel time 

burst becomes the tau measurement. Experience has shown that pressure drift is greatly reduced 

by preconditioning. The sensors were subjected to pressures of 3,000 dbar for one to two months 

in the laboratory prior to the first deployment. Tides are removed from the pressure records. 

Finally, an exponential-plus-linear drift curve is determined by a least-squares fit and then 

removed from the measurements. Within the array, the maximum drift was 0.25 dbar, fifteen 

PIES had drifts less than .05 dbar and twenty PIES had drifts less than 0.1 dbar. 

The PIES are capable of acoustic pulse-delay telemetry. This method encodes the data as the 

delay in arrival time between two acoustic pulses. Advantages include low power requirements 

and high reliability balanced against the disadvantage of relatively slow speed. The instrument 

internally processes data using typical post-processing techniques and saves the processed value 

for each 24-hour day. One day of yearday, pressure, and tau measurements takes about 20 

seconds to transmit between the instrument and the acoustic receiver aboard the ship. Data were 

successfully telemetered mid-experiment (September 2003) during mooring turn-around. The 

internally saved processed data and the telemetered data agree well with post-processed data. 
565 

Figure 2I.14. Three arrays of inverted echo sounders equipped with pressure gauges (PIES) have been 

deployed in the Gulf of Mexico. Western Gulf array deployed October 2004 with an 

anticipated recovery August 2005. Central Gulf array deployed March 2003 and recovered 

April 2004. Eastern Gulf array deployed December 2004 with an anticipated recovery 

December 2005. Satellite altimetry tracks are superimposed on the bathymetry from Smith 

and Sandwell (1997) which is contoured every 1,000 m depth. 

Figure 2I.15. The pressure-recording inverted echo sounder (PIES) is an ocean-bottom instrument housed in 

a single 17” glass sphere containing the controller/data logger, acoustic release, and relocation 

radio/strobe light. The PIES is released from the ocean bottom after it receives a coded acoustic 

command. The anchor stand is dropped; the PIES returns to the surface and emits an acoustic 

beacon—a relocation radio and a strobe flasher—for tracking. 
566 

PIES Array 

The mesoscale-resolving array consists of twenty-seven PIES and fifteen deep-current meters. 

Near-bottom current meters deployed between the PIES in “triangles” allow the bottom-pressure 

records to be leveled. One constant is determined for each bottom-pressure record under the 

requirement that the mean leveled pressure records agree with the streamfunction determined 

from the mean near-bottom currents. PIES were placed along satellite altimetry tracks and at 

cross-over points to allow direct comparison between satellite- and PIES-derived sea surface 

height and to evaluate the baroclinic and barotropic components of sea surface height. The broad 

extent of the array, nominally 92W to 88W, 26N to 28N, and the eddy-resolving PIES spacing 

enables a quantitative mapping of the regional circulation. 

Gravest Empircal Mode—A Look-Up Table 

Experience in strong-jet environments such as the Gulf Stream and Antarctic Circumpolar 

Current indicates that a strong empirical relationship exists between tau and vertical profiles of 

temperature, salinity, and density. This relationship is coined Gravest Empircal Mode, or GEM, 

and yields a look-up table between tau and various ocean variables. We have created a GEM 

field for the GOM; the methodology is described below. 

First, a regional hydrographic data set was assembled. We utilized CTD hydrocasts from the 

MMS-funded Deepwater Reanalysis supplemented with CTD data from SAIC. The northwestern 

GOM is well sampled; hydrocasts represent about 20 years of sampling; hydrocasts sample most 

of the annual cycle, except December; the bulk of casts extend between 1,000 to 2,000 dbar with 

relatively few casts below 2,000 dbar. 

Second, a reference tau index was chosen to be the round-trip travel time between 1,000 dbar to 

100 dbar. The lower limit was determined by the historical data set. The upper limit was chosen 

to be below the mixed layer to avoid contamination from the seasonal cycle. Future work will 

include a seasonal correction in the GEM field. 

The hydrographic data (temperature, salinity, and specific volume anomaly) were sorted by the 

tau index, linearly interpolated to a uniform 25 dbar grid, and at each pressure level a cubic 

smoothing spline was fit to the hydrography (temperature, salinity and specific volume anomaly) 

as a function of the tau index. Root-mean-square residual, rms, for each curve provides an 

indication of the departure any individual profile might have from the GEM curve. The rms 

values for temperature, salinity, and specific volume anomaly are small and decrease with 

increasing pressure. There is little structure in the temperature and salinity GEM fields below 

about 1,000 dbars and this reflects the uniform deep water properties observed on the GOM. The 

GEM field provides a look-up table; given a reference tau value profiles of temperature, salinity, 

and specific volume anomaly can be determined. 

The PIES-measured taus are then converted to the same index as the look-up table. We assume 

that tau at any deep pressure is linearly related to tau at any other deep pressure. Historical 

hydrography established the slope and calibration CTDs taken during turn-around telemetry 

cruise determined the intercept of this linear relationship. 
567 

Comparisons with Observations 

Four tall moorings embedded within the PIES array directly measured temperature, salinity, and 

current at discrete depths during the experiment. Only one PIES was coincident with a tall 

mooring, so temperature estimated from the PIES was mapped to tall mooring locations and then 

compared to mooring measurement. Figure 2I.16 shows one set of comparisons for the tall 

mooring L1 located in the northeastern portion of the array. Here the comparison is excellent: 

estimated and measured temperature time series track each other well and the variance explained 

is greater than 84%. Considering all four moorings, the percent variance explained in 

thermocline is 83%. 

Figure 2I.16. Upper four panels compare PIES-estimated (blue) and directly-measured temperatures (red) at 

the L1 mooring whose location is shown in the bottommost panel by the red circle. The rootmean-square difference between the records is noted in the upper right corner of each panel 

and can be compared to the root-mean-square of the historical hydrography used to construct 

the GEM field. 
568 

Initial Results 

Tau measured by the PIES shows strong coherence between nearby sites, and multiple space and 

time scales are evident. This multiplicity of scales was expected as upper-ocean eddies have a 

range of length and time scales: Loop Current and Loop Current Eddies range 200–500 km, 

slope eddies scales are 100–150 km, and frontal cyclonic eddies scale near 50–150 km. Maps of 

the upper-ocean circulation provide a framework in which the observations can be interpreted. 

For example, mapped temperature at 300 m (Figure 2I.17) shows frontal cyclones along the 

periphery of the Loop Current/Loop Current Eddy and a small anticyclone generated during ring 

pinch-off. 

Figure 2I.17. Mapped temperature at 300 dbar shows frontal cyclones along the periphery of the Loop 

Current and Loop Current ring and a small anticyclone generated during ring development. 

In addition, several deep features are revealed. A coherent 16-day oscillation in deep pressure 

with 5 cm peak-to-peak amplitude exists throughout the array. 

There is increased variability south of escarpment and during the detatchment of Eddy 

Sargassum. There are clearly westward propagating topographic Rossby waves along the 

escarpment, but locally generated features are also apparent. Scales in the deep ocean are smaller 

than those in the upper ocean indicating that deep scales are set by the interaction of the upperocean circulation with complicated topography in the region. 
569 

Future Work 

Future analysis of the central Gulf PIES array includes developing a better understanding of the 

upper-lower layer coupling, comparison between altimeter and PIES sea-surface height, and 

combining maps and float trajectories. Currently, there are two PIES arrays in the Gulf. In the 

Western Gulf 10 PIES centered near 26.7N, 95W will be recovered in late summer 2005 after an 

approximately six-month deployment. In the Eastern Gulf 7 PIES centered near 27.9N, 87.7W 

have been deployed in December 2004 and will be recovered in December 2005. 

References 

Smith, W.H.F. and D.T. Sandwell. 1997. Global sea floor topography from satellite altimetry and 

ship depth soundings. Science 277:1956–1962. 

Kathleen Donohue received a Ph.D. degree in physical oceanography from the University of 

Rhode Island in 1995. She has worked as an assistant Marine Research Scientist at the Graduate 

School of Oceanography, University of Rhode Island, since 2000. 

D. Randolph Watts received a Ph.D. degree in physics from Cornell University in 1973. He is a 

Full Professor at the Graduate School of Oceanography, University of Rhode Island. 

Karen L. Tracey received her M.S. degree in marine sciences from the University of North 

Carolina, Chapel Hill in 1981. She has worked at the Graduate School of Oceanography, 

University of Rhode Island as a Marine Research Specialist since 1981. 
570 

DEEPWATER LAGRANGIAN OBSERVATIONS OF CURRENTS 

IN THE GULF OF MEXICO 

Kevin D. Leaman, Division of Meteorology and Physical Oceanography, 

Rosenstiel School of Marine and Atmospheric Science, University of Miami 

As part of the MMS-funded exploratory study of deep currents in the Gulf of Mexico (GOM), 

two types of subsurface, acoustically tracked Lagrangian drifters were launched into the central 

GOM for trip durations of up to one year. The first type of drifter, called RAFOS, was deployed 

in two groups: 1) an initial set of 30 drifters to be tracked for one year; and, 2) a special set of six 

drifters to be deployed as an “event” experiment. The initial set were deployed along three 

longitudes: 089° 00’W, 089° 45’W, and 090° 30’W from roughly 26° N to 28° N. These floats 

were deployed at depth intervals of 500m from 1,000m to 3,000m where topography permitted. 

At the end of their voyage they surface and transmit pressure, temperature, and acoustic tracking 

data via ARGOS. All RAFOS floats for this experiment were ballasted isobarically (that is, to 

stay on a given pressure, as opposed to density, surface). 

The second set was deployed along 090° 30’W at depths of 1,500m and 2,500m “upstream” of 

the Sigsbee Escarpment, with a planned trip duration of seven months. Three floats were 

deployed at each depth with close horizontal separations. The intent of this experiment was to 

watch the progress of the floats as they moved through the complicated “downhill” topography 

of the Escarpment. 

The second type of float, named “PALFOS,” was acoustically tracked similarly to the RAFOS 

floats. However, these floats include a CTD sensor that will operate in a profiling mode; every 

ten days these floats will surface while making a CTD profile at vertical resolutions of from 50m 

(from the 1,000m rest depth to which they were deployed to 250m) to 10m (from 250m to the 

surface). While on the surface, the floats transmit CTD and acoustic tracking data to shore via 

ARGOS and are in turn navigated by ARGOS. After transmission the floats sink back to their 

rest depth. Two floats were deployed on each of the longitudes indicated above during March 

and April 2003 at the start of the experiment. Three of these floats are still functioning and 

transmitting data to shore. One float “escaped” from the GOM and “hopped” its way up the 

Straits of Florida, where it appears to have been finally picked up by a local boater. Since its 

transmitter disappeared from view, we suspect it is sitting in the 

boater’s garage. 

Acoustic tracking was provided by commercially manufactured sound sources moored at three 

locations in the northern GOM during the initial mooring cruise. These sources transmit every 

eight hours in a staggered pattern; extremely accurate clocks on the floats and sources permit 

range information to be determined. Unfortunately, two of the three sources failed partway 

through the experiment due to a mechanical failure, thereby resulting in the loss of several 

months of tracking data in the middle of the experiment. However, since the PALFOS floats 

were transmitting to ARGOS every ten days, positions of these floats could still be determined at 
571 

ten-day intervals. Fortunately, we were able to borrow two sources from a colleague, Dr. Walter 

Zenk at the Institut fur Meereskunde in Kiel, Germany, allowing us to complete the last six to 

seven months of tracking, including complete tracking of the “event” floats. 

Several general observations can be made from an inspection of the float tracks: 

 1. Floats tended to migrate preferentially to the east or west; very few remained in the 

central portion of the GOM, and those that did were usually deployed in the deeper 

(southern) part of the basin; 

 2. Once floats moved to the east or west, they exhibited long residence times over the 

Sigsbee Plain (west) or over the eastern basin. (This region appears not to have a 

formal name; however, we are referring to the deep region east of the north-south 

topographic restriction at about 088° W.); 

 3. A moderate majority of the floats moved to the west. However, there is little 

correlation between the direction floats moved, and the deployment line (east-middlewest). That is, some floats deployed along the easternmost line moved west, and vice 

versa; 

 4. Floats that moved eastward tended to exhibit eddying motions in the interior of the 

eastern basin, with no tendency to crowd the steep topography on the eastern side of 

the basin. Conversely, floats moving to the west tended to follow topographic 

contours and “funnel” along the western, steep-walled boundary. A few floats tracked 

along the walls of bathymetric features in the west, such as the Alaminos Canyon; 

 5. Floats near shallow topography showed more eddying behavior and cross-isobath 

flow (a few, in fact, ran aground); 

 6. Floats in the central region are clearly responding to spatial variability on extremely 

small scales. Two floats launched less than 15nm apart at 1,500m during the event 

experiment went in exactly opposite directions, one east and one west. 

The picture that emerges from the above is that the deep circulation in the GOM is characterized 

by two large counter-rotating gyres, a stronger, cyclonic gyre with westward intensification in 

the western Sigsbee Basin (also seen by others), and a weaker, anticyclonic gyre in the eastern 

basin. Considerable small-scale horizontal, turbulent exchange may be taking place in the central 

part of the basin, in the region where the floats were launched. The eastern gyre shows a much 

more broadly distributed eddy activity across the eastern basin. Over the course of one year no 

floats managed to exit the basin via the Yucatan Channel, although other (e.g., current meter) 

data suggest that backflow into the Caribbean is taking place in this channel at deeper levels. 
572 

Dr. Kevin Leaman received his B.S. and M.S. degrees in meteorology and oceanography from 

the College of Engineering at the University of Michigan in 1970 and 1972, respectively. He was 

awarded a Ph.D. in physical oceanography in 1975 in the Joint Program in Oceanography of the 

Woods Hole Oceanographic Institution and the Massachusetts Institute of Technology. He has 

worked at the University of Miami’s Rosenstiel School of Marine and Atmospheric Science 

since 1976, where he is now Professor of Physical Oceanography. He served as Chair of the 

Division of Meteorology and Physical Oceanography from 1995 to 2000. He has served for the 

last four years as the Co-Chief Editor of the Journal of Atmospheric and Oceanic Technology of 

the American Meteorological Society. His research interests have included oceanic internal 

waves, large-scale ocean circulations, western boundary currents, deep water formation, and 

biophysical interactions. He has also been involved with the development and design of 

oceanographic instrumentation. In the process of carrying out this research he has served as 

Chief Scientist on more than forty research cruises in the North and South Atlantic Oceans, 

Pacific Ocean, Caribbean Sea, Gulf of Mexico, Straits of Florida and the Mediterranean Sea. He 

has also developed and carried out bilingual training programs for oceanographic technicians and 

scientists from Latin America. 
573 

HIGH RESOLUTION MODELING OF THE GULF 

Susan E. Welsh and Masamichi Inoue, Coastal Studies Institute, 

School of the Coast and Environment, Louisiana State University 

Introduction 

The outer continental shelf and slope of the Gulf of Mexico (GOM) provide valuable economic 

and environmental resources including fisheries, oil and gas production, hydrocarbon seeps, and 

gas hydrates. Offshore oil and gas exploration and production in the GOM have moved seaward 

into water depths greater than 300 m, which is defined as ‘deepwater’ for the creation of 

operating regulations. In the last decade there has been a continued increase in deepwater 

exploration, drilling, and production. There is a commitment by industry to continue exploring 

the outer continental shelf and slope for mineral resources and to develop and improve 

technology for safe operation of deepwater facilities. Current meter measurements made near the 

2,000-m and 3,000-m isobaths in the northern GOM indicate occasional strong flows of least 50 

cm⋅s

-1. To the west of the Mississippi Delta in water depths of approximately 3,000 m, deep 

furrows have been observed on the continental rise. The size, morphology, and orientation of 

these sedimentary furrows may be attributed to strong currents (near 1 m⋅s

-1) near the bottom. 

Numerical simulations of the GOM circulation predict deep strong flows near the boundaries 

resulting from energetic eddies impinging along steep topography. 

Previous Modeling Studies 

Recent current data sets in water depths of nearly 2,000 m to greater than 3,000 m (Oey and 

Hamilton 2000) are being analyzed as part of an MMS-funded program entitled, ‘Modeling and 

Data-Analyses of Subsurface Currents on the Northern Gulf of Mexico Slope and Rise: Effects 

of Topographic Rossby Waves and Eddy-Slope Interaction.’ This ongoing study is one of four 

major modeling programs funded by MMS and is designed primarily to look at the energetics of 

deep wave and eddy fields. A numerical study of TRW propagation in the northern GOM by Oey 

and Hamilton (2000) indicated that there is a concentration of kinetic energy in the 20 to 100 day 

band along the 3,000-m isobath extending westward from under the LC. There is a concentration 

of relatively high-eddy kinetic energy in bands along the slope below 2,200 m in the model study 

of Welsh and Inoue (2002). Slight bottom intensification of the kinetic energy in these bands is 

consistent with TRW propagation. Detailed analysis of the model 15-year mean velocity and 

hydrographic fields at each level in the deep also suggests mean cyclonic flow around the 

perimeter of the central and western GOM. 

Welsh and Inoue (2002) implemented the Lagrangian technique of seeding and tracking tracer 

particles in the model to examine detailed transport and mixing processes and to identify 

potential processes responsible for ventilation of the deep water. The model was seeded with tens 

of thousands of inert particles that drift freely within the model domain in response to the 

velocity field. Several different experiments were designed with different starting positions of 

the tracer particles corresponding to the region or process of interest. The positions of the tracers 

were recorded and later analyzed to identify characteristic flow paths and to assess the effects of 
574 

physical processes on the individual particles. This same method will be employed in the present 

study, but we will focus on the behavior of the particles near the boundaries. This will be 

facilitated by using a much smaller horizontal grid size and five-fold increase in the vertical 

resolution. 

Methods 

The numerical model to be employed in this study has now been in use for over 30 years and was 

first described by Bryan (1969) and programmed by Cox (1984); thus, it has been referred to as 

the “Bryan-Cox Model.” MOM1 (Pacanowski et al. 1991), which succeeded the Bryan-Cox 

model, retains the basic physics of the Bryan-Cox code but was modified for more efficient use 

with a UNIX operating system and included faster, more efficient numerical solvers. The model 

grid will be derived from the Global Sea Floor Topography with two-minute horizontal 

resolution (Smith and Sandwell 1997). The data have already been acquired for free and are 

superior in accuracy to the bathymetry that has been employed in our previous GOM modeling 

efforts. In order to simulate realistic deep cyclones, it is necessary to resolve important smallscale bottom topographic features, such as a narrow deep channel connecting the eastern and the 

central basins. We propose to use a model grid with at least 7.5 km horizontal resolution and 

lower values for viscosity and diffusivity (≤ 50 m2

 s-1). There will be 100 vertical levels with 20 

m thickness in the upper 10 levels and 40 m thickness in the lower 90 levels. The fine horizontal 

resolution combined with extremely high vertical resolution in the model grid will greatly reduce 

the potential for topographically-induced numerical noise in the model fields. 

The model will be initialized with the Levitus 3-D temperature and salinity fields for the GOM 

and western Caribbean. The Levitus surface salinity data will be used for the surface boundary 

condition on salinity. A more realistic surface temperature field derived from AVHRR estimates 

will be used for the surface boundary condition on temperature (which will coordinate in time 

with the wind stress field). The model domain includes the entire Caribbean west to 59°W and 

north to 31°N. A natural inflow condition through the Yucatan Channel is accomplished by 

forcing the flow through the eastern Caribbean at approximately 65°W to acquire the observed 

seasonal variation in the shear and geostrophic transport of the Caribbean Current. In order to 

implement a realistic vertical shear of the inflow, the temperature and salinity fields used to force 

the inflow will be examined. The Levitus climatology in the Venezuela Basin will be compared 

to all available hydrographic data. Adjustments in the vertical profiles will be made if the 

comparison turns out be unrealistic. Realistic shear in the Caribbean Current will directly 

improve the vertical structure of the LC rings in the GOM. 

Incorporating the entire Caribbean will greatly improve the natural variability of the inflow to the 

GOM, as well as the generation of LC rings. Not only will the internal boundary for generating 

the Caribbean Current be moved far from the Yucatan Channel, but wind-forced circulation in 

the Caribbean can be incorporated. Oey et al. (2003) have proven the importance of the windforcing and eddy-forcing on the shedding behavior of LC rings using a numerical model of the 

northwest Atlantic Ocean. Results from this model indicate that shorter shedding intervals can 

result from wind-induced transport fluctuations through the Greater Antilles. Oey et al. (2003) 

also observed that longer shedding intervals can result from the arrival of Hispaniola eddies at 
575 

the Yucatan Channel. The Hispaniola eddies are generated by the local wind-stress curl and have 

a characteristic time scale of 100 days. 

The previous model study by Welsh and Inoue (2000) featured Hellerman and Rosenstein 

monthly wind forcing, which resulted in realistic seasonal variations in many surface circulation 

features. The proposed model will continue to use the Hellerman and Rosenstein winds for the 

spin-up of the model. For the production runs of the model, either the ETA winds (Black 1994), 

NCEP or ECMWF re-analysis winds will be implemented over a multi-year period (at least five 

years). The purpose of using real winds is to have realistic variability in the time and space scales 

associated with the surface momentum flux. This variability, which is not inherent in the 

climatological winds, may be important in producing more realistic LC ring separation and 

migration. 

The method used to track the particles (Pacanowski 1995) features 3-D interpolation of each 

particle position at each time step followed by integration of the particle position in space using 

the 3-D components of velocity. Velocity at the position of a particle is constructed by 3-D linear 

interpolation. The particle trajectory is integrated forward for one time step taking convergence 

of meridians into account. Any component of the trajectory is prevented from entering land by 

resetting it to its previous value if it does cross over to land, thereby simulating free slip 

conditions. The analysis of the tracer particles will include both Lagrangian particle motion and 

Eulerian particle displacements. The vertical velocity will be examined to differentiate between 

vertical advection of the particles and Stokes drift. 

Summary 

The initial goals of this project are to develop a high-resolution OGCM of the GOM and 

compare and contrast the model deep circulation at high resolution to previous modeling studies. 

We will examine current-topographic interaction along the slope and rise of the GOM. Both 

energetics of the velocity field and the transport of Lagrangian particle tracers in the deep layer 

will be studied. We will determine the probability of mean cyclonic flow in the deep central and 

western portion of the GOM. 

The proposed model will improve on the previous study by using smaller grid size to resolve 

small-scale topographic features on the shelf and slope, real winds, and a greatly expanded 

domain to improve the inflow condition. The expanded domain will hopefully result in more 

realistic inflow through the Yucatan Channel by including exchange through the Greater 

Antilles, as well as wind-driven eddies formed in the Caribbean. The expanded domain also 

provides the opportunity to move the artificial forcing of the Caribbean Current to the far eastern 

Caribbean and expand the region acted on by the wind stress—which is considerably stronger in 

the Caribbean. The enhanced vertical resolution to 100 levels will greatly improve the ability to 

represent the bottom topography, as well resolve the flow in the transition region between the 

surface and deep layers. 
576 

References 

Black, T.L. 1994. The new NMC mesoscale Eta model: Description and forecast examples. 

Weather and Forecasting 9:265–278. 

Bryan, K. 1969. A numerical model for the study of the world ocean. Journal of Computational 

Physics 4:347–376. 

Cox, M.D. 1984. A Primitive Equation Three-dimensional Model of the Ocean. Technical 

Report #1. Geophysical Fluid Dynamics Lab, NOAA. Princeton, NJ. 250 pp. 

Oey, L.-Y. and P. Hamilton. 2000. Modeling and data analyses of subsurface currents on the 

northern Gulf of Mexico slope and rise: Effects of topographic Rossby waves and eddyslope interaction. In: Proceedings of the Workshop on the Physical Oceanography Slope 

and Rise of the Gulf of Mexico. 12–14 September 2000. U.S. Dept. of the Interior, 

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

Oey, L.-Y., H.-C. Lee, and W. Schmitz. 2003. Effects of winds and Caribbean eddies on the 

frequency of Loop Current eddy shedding: A numerical model study. Journal of 

Geophysical Research 108:3324. 

Pacanowski, R., K. Dixon, and A. Rosati. 1991. The GFDL Modular Ocean Model User’s Guide 

Version 1.0. GFDL Ocean Group Technical Report #2. Princeton, NJ. 

Pacanowski, R. 1995. MOM 2 Documentation, User’s Guide, and Reference Manual, Version 

1.0. GFDL Ocean Group Technical Report #3. Princeton, NJ. 

Smith, W.H.F and D.T. Sandwell, 1997. Global sea floor topography from satellite altimetry and 

ship depth soundings. Science, 277:1956–1962. 

Welsh, S. and M. Inoue, 2000. Loop Current rings and the deep circulation in the Gulf of 

Mexico. Journal of Geophysical Research 105:16,951–16,959. 

Welsh, S.E. and M. Inoue. 2002. A particle tracing study of circulation, transport, and vertical 

exchange in the Gulf of Mexico. U.S. Dept. of the Interior, Minerals Management 

Service, Gulf of Mexico OCS Region, New Orleans, LA. OCS Study MMS 2002-064. 

Pp. 51. 

Dr. Susan Welsh has worked in the Coastal Studies Institute for the past 15 years as a scientific 

programmer/modeler, a graduate assistant, a post-doctoral researcher, and an Assistant Professor/ 

Research. She is presently working half-time as a Research Associate V. Her areas of research 

are physical oceanography, numerical ocean models, and Gulf of Mexico circulation. Dr. Welsh 

received her B.S. in earth and planetary sciences from the Johns Hopkins University, her M.S. in 
577 

oceanography from the Florida State University, and her Ph.D. in geology from Louisiana State 

University. 

Dr. Masamichi Inoue has worked at the Florida State University and at the Australian Institute of 

Marine Science. He has been at Louisiana State University for the past 17 years and is Associate 

Professor at the Coastal Studies Institute and in the Department of Oceanography & Coastal 

Sciences. His research interests include ocean circulation and transport processes. Dr. Inoue 

received his B.E. in naval architecture from Tokai University, M.S. in ocean engineering from 

University of Rhode Island, M. E. in civil engineering and Ph. D. in oceanography from Texas 

A&M University. 
579 

INDEX 

A

Allen, Dan..............................................499, 523, 524 

Allen, Yvonne........................................409, 415, 418 

Anderson, Steven P................................477, 491, 497 

Antunes, Ricardo ...........................377, 379, 383, 388 

Aronson, Richard B. ......447, 456, 457, 459, 460, 461 

Atchison, Amy D...................................409, 429, 438 

Austin, Diane.........................................51, 53, 73, 77 

B

Baguley, Jeff............................................27, 147, 149 

Barras, John ...........................................447, 474, 475 

Baud, Richie D. .............................................227, 229 

Bauer, C.T. ..............................................................65 

Benfield, Mark C. ..................................409, 419, 423 

Biazar, Arastoo P...........................................309, 344 

Biggs, Douglas C...............25, 36, 253, 265, 377, 400 

Billings, Richard....................309, 312, 315, 316, 319 

Blanchard, Brian W. ..............................309, 336, 338 

Boland, Gregory S. ................................409, 429, 437 

Born-Phillips, Katherine................................447, 462 

Bowser, Ronald C..........................................227, 229 

Brack, Benjamin ..........................81, 83, 99, 109, 135 

Brandenburger, Jill ................................................1, 5 

Braud, DeWitt........................................447, 462, 464 

Brazeau, Daniel A..................................409, 438, 444 

Brooks, James M. ..................................201, 218, 223 

Bryant, William ...........................................25, 27, 43 

C

Cahoon, Donald.............................................447, 465 

Caldwell, Jack..........................................81, 137, 144 

Cameron, Robert............................................309, 311 

Carman, Kevin R. ..........................................1, 21, 23 

Carney, Robert S............................................201, 225 

Carpenter, S. ......................................................25, 50 

Chapin, Sean R. .........................................81, 83, 100 

Christy, Jamie ..............................................51, 62, 64 

Cole, John G. .........................................409, 415, 417 

Colten, Craig E. .....................................171, 185, 187 

Cordes, Erik E. ..............................................499, 508 

Cowan, Jr., James H. .............................409, 424, 427 

Cox, Jeffrey M.......................................477, 483, 488 

Crecelius, Eric .......................................................1, 5 

D

DeCarlo, Eric.................................................409, 424 

Deming, Jody...............................................25, 27, 50 

DeRuiter, Stacy......................................253, 281, 282 

Deslarzes, Ken J. P. .......................................447, 456 

Diaz, Robert...................................................201, 224 

Diebold, John...................................................81, 144 

DiMarco, Steven F.............................25, 29, 377, 400 

Dismukes, David E................................171, 198, 199 

Donohue, Kathleen ........................481, 547, 564, 569 

Douglas, Sharon G.................................309, 320, 330 

E

Engelhaupt, Dan ............253, 263, 264, 377, 392, 393 

Escobar-Briones, Elva ...................147, 158, 499, 514 

Evers, Elaine..........................................447, 469, 473 

F

Fechhelm, Robert G...............................409, 415, 417 

Fisher, Charles R. ..........................................499, 508 

Fisher, Robert ..................................................81, 109 

Fleeger, John W.............................1, 21, 23, 295, 300 

Foltz, David W. .............................................295, 300 

Forster, Larry D. ............................................227, 231 

G

Gallaway, Benny J.................................409, 415, 417 

Gauldie, Robert..............................................409, 424 

Gill, Chip .......................................................144, 253 

Gordon, Jonathan...................377, 379, 382, 384, 390 

Gregg, Christopher S. ....................................295, 300 

H

Hamilton, Peter..............481, 483, 487, 547, 557, 563 

Haney, Jay L..........................................309, 320, 331 

Hart, Alan D. .................................................201, 203 

Hartley, Steve ........................................447, 474, 475 

Hauser, W......................................................227, 241 

Hemmerling, Scott A.............................171, 185, 187 

Hensel, Philippe.............................................447, 465 

Hickerson, Emma L.......................................447, 449 

Holcombe, Troy.............................................447, 449 

Howard, Matthew K. .........25, 29, 253, 265, 377, 400 

Hsu, S.A.................................................309, 336, 339 

Hu, Chuanmin............................................36, 41, 400 

Hubbard, G. Fain ...................................147, 151, 153 

I

Iledare, Omowumi.........................................171, 188 

Inoue, Masamichi ..................547, 549, 556, 573, 577 

Ioup, George E.............................81, 83, 99, 109, 134 

Ioup, Juliette W. ..........................81, 83, 99, 109, 134 
580 

J

Jaquet, Nathalie .....................377, 379, 383, 384, 390 

Jimenez, Michele...................................309, 332, 335 

Jochens, Ann E. .......1, 18, 25, 29, 253, 255, 377, 400 

Johnson, Mark P. ...................253, 254, 274, 277, 284 

Johnston, James .............................................447, 465 

K

Kaufman, Les ........................................447, 456, 458 

Klerks, Paul L........................................525, 534, 535 

Kuczaj, Stan A.................................................81, 109 

L

LaPeyre, Megan.............................................447, 465 

LaRock, Paul A. ............................................295, 302 

Lau, Steven....................................................309, 332 

Leaman, Kevin D...........................................547, 570 

Leben, Robert R.....................253, 265, 477, 491, 498 

Lee, Wonchoel...............................................149, 150 

Lin, Qianxin...........................................525, 541, 542 

Lin, Ying-Tsong ....................................253, 281, 283 

Lindsey-Curran, Christopher .................227, 234, 236 

Linscombe, Greg ...................................447, 474, 475 

Locke, Chris ..........................................447, 462, 464 

Lord-Lasorsa, Brenda K. .................................1, 5, 10 

Luton, Harry ........................51, 53, 55, 171, 173, 175 

Lynch, James F......................................253, 281, 282 

M

MacDonald, Ian R..................................499, 501, 503 

Madsen, Peter T.... 253, 254, 274, 276, 277, 279, 284, 

287 

Mansell, Gerard .............................................309, 332 

Marlborough, Sidney J. .................................1, 21, 23 

Martin, Larry R......................................409, 415, 417 

Mate, Bruce ... 253, 259, 262, 263, 265, 266, 267, 270 

McDonald, Thomas J.............................201, 218, 223 

McElvaine, Michelle L. .........................201, 213, 217 

McGinnis, Thomas ........................................447, 465 

McGuire, Tom .............................................51, 77, 79 

McKinley, James P............................................1, 3, 4 

McNider, Richard T...............................309, 344, 346 

Mencken, F. Carson...............................171, 176, 184 

Michel, Jacqueline.................................447, 462, 464 

Mick, M.B. ....................................................227, 241 

Miller, Mark ..........................................409, 415, 418 

Miller, Patrick J.O. ................................253, 274, 277 

Mione, Lauren .......................................409, 424, 427 

Montagna, Paul................................27, 147, 149, 150 

Moros, Thanos.......................................227, 237, 240 

Morse, John .................................................25, 27, 49 

Müller-Karger, Frank E. ....................................25, 36 

N

Newcomb, Joal J..................81, 83, 98, 101, 108, 135 

Newhall, Arthur.....................................253, 281, 283 

Nguyen, Alan H.............................................1, 11, 14 

Norris, Thomas F.............................................81, 145 

Nunnally, Clifton C. ..............................147, 155, 157 

O

Olatubi, Williams O...............................171, 188, 192 

Olien, Roger M......................................171, 176, 184 

Ortega-Ortiz, Joel ..................................253, 263, 265 

P

Paulsell, Robert......................................525, 529, 533 

Perez, Brian C........................................447, 469, 473 

Petterson, John.......................................171, 176, 184 

Precht, William F...................447, 456, 457, 459, 460 

Presley, Bobby J. .........................................25, 44, 48 

Priest, Tyler .......................................................51, 65 

Pulsipher, Allan .............................................171, 193 

R

Ramos, LCDR Jeff ........................................227, 246 

Rayborn, Grayson H....................81, 83, 99, 109, 135 

Rember, Robert D..................................201, 213, 217 

Rendell, Luke ........................................377, 379, 383 

Robbart, Martha L. ................................447, 456, 458 

Robe, Francoise .....................................309, 353, 376 

Roberts, Deborah J. .......................................1, 11, 15 

Roberts, Harry H............201, 207, 212, 499, 504, 507 

Rouse, Jr., Lawrence J. ..................................547, 549 

Rowe, Gilbert T. ..........25, 27, 28, 147, 151, 153, 169 

S

Sammarco, Paul W. .......409, 429, 436, 437, 438, 444 

Sanders, William M.....................................81, 83, 98 

Sasser, Charles...............................................447, 469 

Schmahl, George P. .......................................447, 449 

Scire, Joseph..........................................309, 353, 376 

Sell, James L......................................................51, 56 

Shaw, Richard F. ...........................409, 419, 423, 424 

Sidorovskaia, Natalia A...............81, 83, 99, 109, 134 

Silva, Soraya J. ..............................................1, 21, 23 

Smith, Shepherd ............................................447, 449 

Snyder, Mark ...........................................81, 101, 108 

Stauffer, David ......................................................340 

Stephens, James M. .....................................81, 83, 98 

Steyer, Gregory D..................................447, 469, 472 

Stone, Gregory...............................................525, 543 

Strimaitis, David....................................309, 353, 376 

Suir, Glenn.....................................................447, 469 

Swaminathan, Kavita.....................................1, 15, 17 

Swenson, Erick ..............................................447, 469 
581 

T

Tapia, L..........................................................227, 241 

Tashmukhambetov, Arslan M. ....................81, 83, 99 

Taylor, Christine............................................447, 449 

Thode, Aaron.........................................377, 395, 399 

Tolstoy, Maya.........................................................81 

Tracey, Karen L.....................................547, 564, 569 

Trefry, John H. ......................................201, 213, 217 

Trocine, Robert P...................................201, 213, 217 

Tyack, Peter L. ..... 253, 254, 271, 273, 274, 277, 281, 

284, 289, 292 

V

Verret, A.J. ....................................................227, 241 

Viada, Stephen T. ..........................................295, 307 

Visser, Jenneke M..........................................525, 527 

Vittor, Barry A.......................................295, 297, 299 

Vukovich, Fred ......................................477, 489, 490 

W

Waddell, Evans..............................477, 479, 481, 482 

Wade,Terry L. .............................................25, 44, 48 

Walker, Christopher D.................81, 83, 98, 109, 135 

Walker, Nan D.......................................477, 491, 497 

Walker, Rachel T.....................................81, 109, 134 

Ward, E.G......................................................227, 241 

Watts, D. Randolph ...............................547, 564, 569 

Watwood, Stephanie L. .................253, 254, 274, 284 

Weaver, Douglas C................................447, 449, 455 

Welsh, Susan E......................................547, 549, 573 

Westmeyer, Megan B. Peabody.............409, 411, 414 

Westphal, Karen A. .......................................525, 539 

Wheeler, Neil.................................................309, 340 

Wicksten, Mary K..........................................147, 154 

Wilson, Charles A..................409, 411, 414, 415, 417 

Wilson, Darcy........................309, 312, 315, 316, 319 

Winsor, Martha H..................................253, 267, 270 

Wolff, Gary A..............................................25, 44, 48 

Wolford, A.J. .........................................227, 241, 245 

Wooddell, George..................................525, 536, 538 

Wormuth, John H. .........................................377, 403 

Wright, Andrew...............................................81, 109 

Würsig, Bernd........................377, 379, 383, 384, 391 

Y

Yarwood, Greg ......................................309, 332, 334 

Young, Craig M.............................................499, 521 

Z

Zeigler, Gary S. .............................................309, 347 
583 

ATTENDEES 

Jarvis B. Abbott 

MMS 

381 Elden Street, MS 4023 

Herndon, VA 20170 

(703) 787-1866 

jarvis.abbott@mms.gov 

Thomas E. Ahlfeld 

MMS 

Environmental Sciences Branch (4041) 

381 Elden Street 

Herndon, VA 20170-4817 

(703) 787-1711 

thomas.ahlfeld@mms.gov 

Dan Allen 

Ecologist 

Chevron Texaco 

935 Gravier St., Room 1454 

(504) 592-6769 

allj@chevrontexaco.com 

David T. Allen 

University of Texas 

Center for Energy and Environment 

10100 Burnet Road 

Austin, TX 78758 

(512) 232-6470 

allen@che.utexas.edu 

Yvonne Allen 

LSU 

Baton Rouge, LA 70808 

(225) 578-6507 

allenyc@lsu.edu 

Tasha D. Anderson 

MMS, ITD/TSB 

381 Elden Street 

Herndon, VA 20170 

(703) 787-1501 

tasha.anderson@mms.gov 

Thomas R. Armstrong 

USGS 

150 National Center 

Reston, VA 20192 

(703) 648-6917 

tarmstrong@usgs.gov 

Richard B. Aronson 

Dauphin Island Sea Lab 

6704 Dorchester Drive 

Dauphin Island, AL 36528 

(251) 861-7567 

raronson@disl.org 

Amy D. Atchison 

LUMCON 

8124 Hwy. 56 

Chauvin, LA 70344 

(985) 223-7416 

aatchison@lumcon.edu 

Diane E. Austin 

Researcher 

University of Arizona 

Bureau of Applied Research in Anthropology 

Anthropology Bldg., Room 316 

Tucson, AZ 85701 

(520) 621-6282 

daustin@u.arizona.edu 

Buddy Ayers 

127 Carina Circle 

Slidell, LA 70458 

(504) 232-1878 

budbon@charter.net 

Alyson Azzara 

Texas A&M University 

College Station, TX 77845 

Arturo J. Baez 

T. Baker Smith & Sons 

P O Box 2266 

Houma, LA 70361 

(985) 223-9265 

arturob@tbsmith.com 

Jeff Baguley 

University of Texas 

Marine Science Institute 

750 Channel View Drive 

Port Aransas, TX 78373 

(361) 749-6817 

jeffb@utmsi.utexas.edu 
584 

Kyle P. Baker 

DOC / NOAA / NMFS 

9721 Executive Center Drive North, Suite 102 

Saint Petersburg, FL 33702 

(727) 570-5312 

kyle.baker@noaa.gov 

William Bankston 

LSU 

126 Stubbs Hall 

Dept. of Sociology 

Baton Rouge, LA 70803 

(225) 578-5103 

sobank@lsu.edu 

Jim A. Barkaszi 

GeoCet 

7341 Glenwood Rd. 

Cocoa, FL 32927 

(281) 325-1080 

jim@geocet.com 

Mary Jo A. Barkaszi 

GeoCet 

7341 Glenwood Road 

Cocoa, FL 32927 

(281) 325-1080 

maryjo@geocet.com 

Carrie S. Barry 

NOAA Fisheries 

3209 Frederic Street 

Pascagoula, MS 39567 

(228) 762-4591 

carrie.barry@noaa.gov 

Kevin P. Barry 

NOAA Fisheries 

3209 Frederic Street 

Pascagoula, MS 39567 

(228) 762-4591 

kevin.barry@noaa.gov 

Mike Barton 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2555 

Warren J. Barton 

Environmental Scientist 

MMS 

1201 Elmwood Park Blvd., MS 5440 

New Orleans, LA 70123 

(504) 736-2731 

warren.barton@mms.gov 

Melissa A. Batum 

MMS 

1520 North Pointe Drive, Apt. 002 

Reston, VA 20194 

(703) 787-1646 

melissa.batum@mms.gov 

Richie Baud 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

richie.baud@mms.gov 

Toni E. Bazer 

Arthur J. Gallagher of LA 

111 Veterans Blvd., Suite 1130 

Metairie, LA 70005 

(504) 888-1100 

toni.bazer@ajg.com 

Steve Bech 

Project Engineer 

Chevron Environmental Management Company 

935 Gravier St 

New Orleans, LA 70112 

(504) 592-6670 

sbech@chevrontexaco.com 

Charles A. Bedell 

Murphy Exploration & Production Company 

P.O. Box 61780 

131 S. Robertson St. 

New Orleans, LA 70161-1780 

(504) 561-2449 

chuck_bedell@murphyoilcorp.com 

Mark Benfield 

LSU Coastal Fisheries Institute 

2179 Energy, Coast & Environment Bldg. 

Baton Rouge, LA 70803 

(225) 388-6372 

mbenfie@lsu.edu 
585 

Lee Benner 

Oceanographer 

MMS 

6508 Summerton Way 

Springfield, VA 22150 

(703) 787-1710 

lee.benner@mms.gov 

James F. Bennett 

MMS 

381 Elden Street, MS 4320 

Herndon, VA 22070 

(703) 787-1660 

jbennett@mms.gov 

Richard Bennett 

Biologist 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2853 

richard.bennett@mms.gov 

Loretta Y. Beoh 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

loretta.beoh@mms.gov 

Landry J. Bernard 

National Data Buoy Center 

1100 Balch Blvd 

Stennis Space Center, MS 39529 

(228) 688-3394 

landry.bernard@noaa.gov 

Douglas C. Biggs 

Professor 

Texas A&M University 

Dept. of Oceanography 

TAMU Mail Stop 3146 

College Station, TX 77843-3146 

(979) 845-3423 

dbiggs@ocean.tamu.edu 

Richard S. Billings 

Eastern Research Group, Inc. 

1600 Perimeter Park Drive 

Morrisville, NC 27560 

(919) 468-7812 

richard.billings@erg.com 

Thomas W. Bjerstedt 

Geoscientist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-5743 

tom.bjerstedt@mms.gov 

Dr. John P. Blaha 

Oceanographer 

Naval Oceanographic Office 

1002 Balch Blvd 

Bay Saint Louis, MS 39522-5001 

(228) 688-5187 

blahaj@navo.navy.mil 

Brian Blanchard 

Research Associate 

LSU Coastal Studies Institute 

Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 578-2961 

bblanc5@lsu.edu 

Earl Boatman 

LNC 

4931 Morano Road 

New Orleans, LA 70129 

(504) 258-2592 

Mary Boatman 

Oceanographer 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2781 

mary.boatman@mms.gov 

Del Bohnenstiehl 

Lamont Doherty Earth Observatory 

P.O. Box 1000 

61 Route 9W 

Palisades, NY 10964 

(845) 365-8382 

del@ldeo.columbia.edu 

Gregory S. Boland 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2740 

gregory.boland@mms.gov 
586 

Ronald C. Bowser 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2640 

ronald.bowser@mms.gov 

Brian E. Boyer 

Vice President 

COMM Engineering, Inc. 

P.O. Box 53463 

Lafayette, LA 70508 

(337) 237-4373 

brian@commengineering.com 

Cosmin V. Bozenovici 

University of New Orleans Conference Services 

1610 Robert E. Lee, Apt. 20 

New Orleans, LA 70122 

(504) 288-7841 

aquire44@hotmail.com 

Vernessa J. Bradford 

Shell E&P Co. 

P.O. Box 61933, Suite 2900 

New Orleans, LA 70139 

(504) 728-4426 

vernessa.bradford@shell.com 

DeWitt H. Braud 

LSU Coastal Studies Institute 

331 Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 578-6177 

dbraud1@lsu.edu 

Darice Breeding 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2966 

darice.breeding@mms.gov 

Gary D. Brewer 

Biologist 

U.S. Geological Survey 

11700 Leetown Rd 

Kearneysville, WV 25430 

(304) 724-4507 

gary_brewer@usgs.gov 

Ron Brinkman 

Geophysicist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2720 

ronald.brinkman@mms.gov 

James M. Brooks 

TDI-Brooks Int'l Inc. 

1902 Pinon Drive 

College Station, TX 77845 

(979) 696-3634 

drjmbrooks@aol.com 

Robert “Allen” Brooks 

USGS 

7920 NW 71st St. 

Gainesville, FL 32653 

(352) 264-3478 

allen_brooks@usgs.gov 

Harmon Brown 

LSU Coastal Fisheries Institute 

Baton Rouge, LA 70803 

(225) 326-8016 

hbrow11@lsu.edu 

Patricia Bruce 

Regulatory Specialist 

Devon Energy Corporation 

1200 Smith Street, Suite 3300 

 Houston, TX 77002-4313 

(713) 286-5861 

patricia.bruce@dvn.com 

William R. Bryant 

Professor 

Texas A&M University 

Dept. of Oceanography 

Texas A&M University 

(979) 845-7211 

wbryant@ocean.tamu.edu 

Carolyn Burks 

Biologist 

National Marine Fisheries Service 

3209 Frederic St. 

Pascagoula, MS 39567 

(228) 762-4591x 286 

carolyn.m.burks@noaa.gov 
587 

Daewon W. Byun 

University of Houston 

Dept. of Geosciences, College of NSM 

312 Science & Research Bldg. 1 

Houston, TX 77204-5007 

(713) 743-0707 

dbyun@mail.uh.edu 

Donald R. Cahoon 

USGS, Patuxent Wildlife Research Center 

11510 American Holly Drive 

Laurel, MD 20708 

(301) 497-5523 

don_cahoon@usgs.gov 

Jack Caldwell 

Geophysical Consultant 

314 Greenpark Drive 

Houston, TX 77079-6414 

(281) 679-6716 

jgcaldwell@sbcglobal.net 

Robert W. Cameron 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2766 

bob.cameron@mms.gov 

Jereld Cammack 

University of New Orleans Conference Services 

New Orleans, LA 70148 

Manuel L. Cano 

Shell Chemicals LP 

3333 Highway 6 South 

Houston, TX 77082 

(281) 544-7897 

manuel.cano@shell.com 

Jane M. Carlson 

105 Montgomery Circle 

Stephens City, VA 22655 

(540) 869-7220 

carlsonja@adelphia.net 

Robert S. Carney 

LSU Coastal Ecology Institute 

Coast, Energy & Environment Bldg. 

Baton Rouge, LA 70810 

(225) 578-6511 

rcarne1@lsu.edu 

Anthony Chasar 

GeoCet 

1735 Bluebird Ct. 

Melbourne, FL 32935 

(440) 364-1323 

tony@geocet.com 

Dennis Chew 

Chief, NEPA/CZM Unit 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

(504) 736-2793 

dennis.chew@mms.gov 

Charles Christ 

CJ Christ Consultant 

P.O. Box 10037 

Houma, LA 70363 

(985) 872-2843 

cjcuboat@netscape.net 

Joe Christopher 

Chief, Environmental Assessment Sec 

MMS 

1201 Elmwood Park Blvd., MS5400 

New Orleans, LA 70123 

(504) 736-2759 

joseph.christopher@mms.gov 

Jamie Christy 

University of Houston 

1313 Peden 

Houston, TX 77006 

(713) 942-9086 

jamiechristy@hotmail.com 

James Cimato 

Oceanographer 

MMS 

Environmental Services Branch 

381 Elden St., MS 4041 

Herndon, VA 20170 

(703) 787-1721 

james.cimato@mms.gov 

Rodney E. Cluck 

Sociologist 

MMS 

381 Elden St., MS 4042 

Herndon, VA 20170 

(703) 787-1087 

rodney.cluck@mms.gov 
588 

Doris Cochennic 

Schlumberger 

Cut Off, LA 70345 

(985) 693-3661 

Joffery Cochennic 

Schlumberger 

Cut Off, LA 70345 

Craig E. Colten 

LSU Dept. of Geography & Anthropology 

Baton Rouge, LA 70806 

(225) 578-6180 

ccolten@lsu.edu 

Rick R. Combs 

Science Applications International Corporation 

1140 Eglin Parkway 

Shalimar, FL 32579 

(850) 609-3459 

combsro@saic.com 

Richard E. Condrey 

LSU Dept. of Oceanography and Coastal Studies 

2161 Energy, Coast and Environment 

Baton Rouge, LA 70803 

(225) 578-6456 

coecnd@lsu.edu 

Mike Conner 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2663 

george.conner@mms.gov 

Kimberley Cook 

MMS 

1201 Elmwood Park Blvd., MS 5411 

New Orleans, LA 70123 

(504) 736-1720 

kimberley.cook@mms.gov 

James J. Corbett 

University of Delaware 

305 Robinson Hall 

Newark, DE 19716 

(302) 831-0768 

jcorbett@udel.edu 

Vicki Cornish 

DOC / NOAA / NMFS 

9721 Executive Center Drive North, Suite 102 

Saint Petersburg, FL 33702 

(727) 570-5312 

vicki.cornish@noaa.gov 

Daniel P. Costa 

University of California Long Marine Lab 

100 Shaffer Road 

Santa Cruz, CA 95060 

(831) 459-2786 

costa@biology.ucsc.edu 

David Cottingham 

Marine Mammal Commission 

4340 East West Hwy., Suite 905 

Bethesda, MD 20814 

(301) 504-0087 

dcottingham@mmc.gov 

James Cowan 

LSU Coastal Fisheries Institute 

Baton Rouge, LA 70803 

(225) 570-9400 

jhcowan@lsu.edu 

Jeffrey M. Cox 

Evans-Hamilton, Inc. 

4608 Union Bay Pl. NE 

Seattle, WA 98105 

(206) 526-5622 

jeff@evanshamilton.com 

Eric Crecelius 

Battelle Marine Sciences Lab. 

1529 West Squim Bay Road 

Coastal Resource & Ecosystem M 

Sequim, WA 98382 

(360) 681-3604 

eric.crecelius@uh.edu 

John Crusius 

USGS 

384 Woods Hole Road 

Woods Hole, MA 02543 

(508) 457-2353 

jcrusius@usgs.gov 
589 

Eurico J. D'sa 

Louisiana State University 

320 Howe-Russell Geoscience Complex 

Coastal Studies Institute 

Baton Rouge, LA 70803 

(225) 578-0212 

ejdsa@lsu.edu 

Donald W. Davis 

Administrator 

LA Oil Spill R&D Program 

258A Military Science Bldg 

LSU 

(225) 578-3481 

osradp@attglobal.net 

Gary DeMarsh 

Director 

DEMEX 

7144 Dummyline Rd 

P O Box 156 

(228) 255-7584 

gary@demex.us 

Yeshavant Desai 

Environmental Engineer 

MMS 

1201 Elmwood Park Blvd., MS 5231 

New Orleans, LA 70123 

(504) 736-2623 

yeshavant.desai@mms.gov 

Steven F. DiMarco 

Associate Research Scientist 

Texas A&M University 

Dept. of Oceanography, 3146 TAMU 

College Station, TX 77843-3146 

(979) 862-4168 

sdimarco@tamu.edu 

Janet Diaz 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

janet.diaz@mms.gov 

Robert Diaz 

Virginia Institute of Marine Science 

P.O. Box 1436 

Route 1208 Greate Road 

Gloucester Point, VA 23062-1346 

(804) 684-7364 

diaz@vims.edu 

Sue Dickson 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

(504) 736-3224 

sue.dickson@mms.gov 

John Diebold 

Lamont-Doherty Earth Observatory 

61 Rte 9W 

Palisades, NY 10964 

(845) 365-8367 

marscico@ldeo.columbia.edu 

Blaine Dinger 

Mariner Energy Inc 

580 Westlake Park Blvd 

Houston, TX 77079-2638 

(281) 584-5588 

bdinger@mariner-energy.com 

David Dismukes 

LSU, Center for Energy Studies 

Baton Rouge, LA 70803-0301 

(225) 578-4343 

dismukes@lsu.edu 

C.J. Doiron 

McMoRan Oil & Gas 

New Orleans, LA 70112 

(504) 852-1873 

CJ_Doiron@fmi.com 

Doughty Dominique 

207 Bellaire Dr. 

Houma, LA 70360 

(985) 876-0551 

Marilyn Dominique 

207 Bellaire Dr. 

Houma, LA 70360 

(985) 876-0551 

Kathleen A. Donohue 

University of Rhode Island 

Graduate School of Oceanography 

215 South Ferry Road 

Narragansett, RI 02882 

(401) 874-6625 

kdonohue@gso.uri.edu 
590 

David A. Dougall 

Eni Petroleum Company, Inc. 

1201 Louisiana 

Suite 3500 

Houston, TX 77002 

(713) 393-6122 

david.dougall@enipetroleum.com 

Sharon Douglas 

Systems Applications International 

Fairfax, VA 220311207 

David B. Driver 

Metocean Specialist 

British Petroleum 

501 Westlake Park Blvd 

Houston, TX 77079 

(281) 366-2699 

driverdb@bp.com 

Bart Dupre 

T. Baker Smith & Sons 

P.O. Box 2266 

Houma, LA 70361 

(985) 223-9274 

bartd@tbsmith.com 

Mark Eckl 

MMS 

381 Elden Street. MS 2100 

Herndon, VA 20170 

(703) 787-1070 

mark.eckl@mms.gov 

Randy E. Edwards 

University of South Florida 

600 4th St. S. 

Saint Petersburg, FL 33701 

(727) 803-8747x 3069 

redwards@usgs.gov 

William Engelhardt 

Biologist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

(504) 736-2474 

bill.engelhardt@mms.gov 

Dan Engelhaupt 

University of Durham, England 

P.O. Box 197 

Picton, New Zealand 

NEW ZEALAND 

(03 ) 573-8802 

danengelhaupt@xtra.co.nz 

Holli Ensz 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

(504) 736-2536 

holli.ensz@mms.gov 

Deborah Epperson 

MMS 

1201 Elmwood Blvd. 

New Orleans, LA 70123 

Elva Escobar-Briones 

Universidad Nacional Autonoma Mexico 

Instituto Oceanografico y Limnologia 

Cuidad Universitaria 

Mexico, DF 04510 

(525) 550-5865 

escobri@mar.icmy1.unam.mx 

Donald P. Evans 

Murphy Exploration & Production Company 

131 South Robertson St. 

New Orleans, LA 70112 

(504) 561-2497 

don_evans@murphyoilcorp.com 

Caryl Fagot 

Staff Assistant 

MMS 

1201 Elmwood Park Blvd., MS 5000 

(504) 736-2590 

caryl.fagot@mms.gov 

James T. Fahey 

RD Instruments 

9855 Businesspark Ave. 

San Diego, CA 92131-1101 

(858) 693-1178 

jfahey@rdinstruments.com 
591 

Graham Feld 

Fugro GEOS Inc. 

6100 Hillcroft 

Houston, TX 77081 

(713) 346-3606 

g.feld@geos.com 

Dagmar Fertl 

Biologist 

Geo-Marine, Inc. 

550 East 15th Street 

Plano, TX 75074 

(972) 423-5480 

dfertl@geo-marine.com 

James Fields 

University of Arizona 

306 Park Drive 

70301 

Tucson, AZ 85712 

(720) 839-6561 

jlf722@msn.com 

Charles R. Fisher 

Pennsylvania State University 

Department of Biology 

Office 219 Muller 

State College, PA 16804 

(814) 865-3365 

cfisher@psu.edu 

John W. Fleeger 

LSU Dept. of Biological Sciences 

146 Thomas Boyd Hall 

Baton Rouge, LA 70803 

(225) 578-1738 

zoflee@lsu.edu 

James G. Flocks 

USGS 

600 4th Street South 

Saint Petersburg, FL 33701 

(727) 803-8747 

jflocks@usgs.gov 

Philip Fontana 

Geophysical Manager, Marine Data Acquisition 

Veritas, DGC 

10300 Town Park Drive 

Houston, TX 77072 

(832) 573-3732 

pmf52@earthlink.net 

Larry D. Forster 

Shell Exploration & Production Co. 

P O Box 61933 

New Orleans, LA 70161 

(504) 728-4505 

Craig Forsyth 

University of Louisiana at Lafayette 

P.O. Box 41652 

Lafayette, LA 70504 

(337) 482-5372 

gf5719@louisiana.edu 

Adam S. Frankel 

Marine Acoustics, Inc. 

706 Giddings Ave. 

Suite 2A 

Annapolis, MD 20764 

(410) 626-1662 

adam.frankel@marineacoustics.com 

James K. Frederick 

Offshore Operator’s Committee/Unocal 

14141 Southwest Freeway 

Sugar Land, TX 77478 

(281) 287-6044 

jfred@unocal.com 

Paul E. Frederick 

The Obrien's Group 

645 Codifer Street 

Slidell, LA 70458 

(985) 781-0804 

paul.frederick@theobriensgroup.com 

Stacey L. Frickey 

Shell E&P Company 

701 Poydras St., Room 2944 

New Orleans, LA 70160 

(504) 728-4989 

stacey.frickey@Shell.com 

Sandi Fury 

Chevron USA Production Co. 

935 Gravier St., Room 1364 

New Orleans, LA 70112 

(504) 592-6095 

sfur@chevrontexaco.com 
592 

Patrick C. Gallacher 

Naval Research Laboratory 

Code 7330, NRL/SSC 

Stennis Space Center, MS 39529-5004 

(228) 688-5315 

gallacher@nrlssc.navy.mil 

Benny Gallaway 

Ecological Research Assoc. 

1410 Cavitt St 

Bryan, TX 77801 

(409) 775-2000 

bgallaway@lgl.com 

Wayne Garitty 

Bay-Tech Companies 

1253 First Avenue 

Harvey, LA 70058 

(504) 328-6456 

wgaritty@baytechrentals.com 

James A. Garrison 

SAIC 

1140 Eglin Parkway 

Shalimar, FL 32579 

(850) 609-3417 

james.garrison@saic.com 

Roger Gentry 

NMFS Acoustics Team 

NOAA Fisheries 

1315 East-West Hwy., SSMC3, Room 13602 

Silver Spring, MD 20910 

(301) 713-2327 

roger.gentry@noaa.gov 

Robert A. George 

Manager, Geophysical Interpretation 

C & C Technologies, Inc. 

730 East Kaliste Saloom Road 

Lafayette, LA 70508 

(337) 261-0660 

dd@cctechnol.com 

Chip Gill 

President 

IAGC 

2550 North Loop West, Suite 104 

(713) 957-8080 

chipgill@iagc.org 

Bob Gisiner 

Office of Naval Research 

800 North Quincy St. 

BCT-1, ONR Code 341 

Arlington, VA 22217-5660 

(703) 696-2085 

gisiner@onr.navy.mil 

Gregg Gitschlag 

NOAA Fisheries 

4700 Avenue U 

Galveston, TX 77551 

(409) 766-3513 

gregg.gitschlag@noaa.gov 

Angie D. Gobert 

Petro Engineer 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2876 

angie.gobert@mms.gov 

Gary D. Goeke 

MMS 

1201 Elmwood Park blvd 

New Orleans, LA 70123 

(504) 731-3233 

gary.goeke@mms.gov 

Jonathan C.D. Gordon 

Ecologic UK 

7 Beechwood Terrace West 

Newport on Tay, Fife 

Fife, DD6 8JH 

UNITED KINGDOM 

(441) 382-5401x54 

jg20@st-and.ac.uk 

Gerald A. Grau 

USGS, National Wetlands Research Center 

700 Cajundome Blvd. 

Lafayette, LA 70506 

(337) 266-8501 

jerry_grau@usgs.gov 

Mike P. Gravois 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-5768 

mike.gravois@mms.gov 
593 

Christopher S. Gregg 

LSU Department of Biological Sciences 

Life Sciences Bldg. 

Baton Rouge, LA 70803 

(225) 578-7651 

cgregg2@lsu.edu 

Norman L. Guinasso, Jr. 

Texas A&M University 

GERG 

833 Graham 

College Station, TX 77845 

(979) 862-2323 

guinasso@tamu.edu 

Sarah C. Hagedorn 

NOAA Fisheries 

1315 East-West Highway 

Silver Spring, MD 20910 

(305) 361-4487 

sarah.hagedorn@noaa.gov 

John Hall 

Halliburton/Baroid 

3000 N Sam Houston Pkwy E 

Humble, TX 77345 

(281) 871-6046 

john.hall@halliburton.com 

Peter Hamilton 

SAIC 

615 Oberlin Road, #100 

Raleigh, NC 27605 

(919) 832-7242 

peter.hamilton@saic.com 

Robert P. Hamilton 

Woods Hole Group 

81 Technology Drive 

East Falmouth, MA 02536 

(508) 495-6229 

bhamilton@whgrp.com 

Jay Haney 

Systems Applications International 

ICF Consuting 

9300 Lee Highway 

Fairfax, VA 22031-1207 

(703) 934-3603 

jhaney@icfconsulting.com 

Sandra M. Harris 

Shell Oil Company 

701 Poydras Street 

New Orleans, LA 70139 

(504) 728-4625 

sandra.harris@shell.com 

Alan D. Hart 

Continental Shelf Associates, Inc. 

759 Parkway Street 

Jupiter, FL 33477 

(561) 746-7946 

ahart@conshelf.com 

Sharon M. Hartdegen 

Shell E&P Company 

701 Poydras 

New Orleans, LA 70139 

(504) 728-3310 

sharon.hartdegen@shell.com 

Charles Hays 

Retired, Exxon 

213 Dahlia St 

New Iberia, LA 70563 

David Hedgeland 

PGS Court 

Walton-on-Thames 

Surrey, KT12 1RS 

UNITED KINGDOM 

(019) 322-6643x4 

david.hedgeland@pgs.com 

A.J. Heikamp 

MSRC 

980 W. Lincoln Road 

P O Box 4870 

Lake Charles, LA 70606 

(337) 475-6410 

heikamp@msrc.org 

Scott A. Hemmerling 

LSU Dept. of Geography & Anthropology 

539 Park Blvd., #3 

Baton Rouge, LA 70806 

(225) 343-8613 

shemme1@lsu.edu 
594 

Dirk C. Herkhof 

MMS 

381 Elden Street 

Herndon, VA 20171 

(703) 787-1735 

dirk.herkhof@mms.gov 

Kathryn Herzog 

Louisiana Department of Wildlife & Fisheries 

2000 Quail Drive 

Baton Rouge, LA 70808 

(225) 765-2396 

kherzog@wlf.louisiana.gov 

Emma Hickerson 

Research Coordinator 

Flower Garden Banks National Marine Sanctuary 

National Marine Sanctuary 

1200 Briarcrest Dr., Suite 4000 

Bryan, TX 77802 

(979) 846-5942 

emma.hickerson@noaa.gov 

Brad C. Hoffman 

Chevron Texaco North America Upstream 

1500 Louisiana St. 

Houston, TX 77002 

(832) 854-3613 

Robert J. Hoffman 

DOC / NOAA / NMFS 

9721 Executive Center Drive North 

Suite 102 

Saint Petersburg, FL 33702 

(727) 570-5312 

robert.hoffman@noaa.gov 

Robert Hofman 

Marine Mammal Commission 

7102 Brennon Lane 

Chevy Chase, MD 20815 

(301) 652-8236 

rjhofman@erols.com 

George Hofmeister 

MADCON Corporation 

131-A Industrial Drive 

Slidell, LA 70460 

(985) 690-9993 

ghofmeister@madconcorp.com 

Kenneth R. Hollingshead 

NOAA Fisheries 

F/PR2-Room 13600 

1315 East-West Highway 

Silver Spring, MD 20640 

(301) 713-2289x 128 

ken.hollingshead@noaa.gov 

Matthew K. Howard 

Assistant Research Scientist 

Texas A&M University 

Department of Oceanography 

3146 TAMU 

College Station, TX 77843-3146 

(979) 862-4169 

mkhoward@tamu.edu 

S.A. Hsu 

Professor 

LSU Coastal Studies Institute 

Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 388-2962 

sahsu@lsu.edu 

Chester Huang 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-3248 

chester.huang@mms.gov 

Fain Hubbard 

Oceanography Department 

Texas A&M University 

College Station, TX 77843 

(979) 845-1327 

fhubbard@ocean.tamu.edu 

Jesse L. Hunt, Jr. 

Geologist 

MMS 

1201 Elmwood Park Blvd., MS 5121 

(504) 736-2440 

jesse.hunt@mms.gov 

Betty Hutcherson 

Louisiana Department of Wildlife & Fisheries 

2000 Quail Drive 

Baton Rouge, LA 70808 

(225) 765-2396 

bhutcherson@wlf.louisiana.gov 
595 

Deborah R. Hutchinson 

U.S. Geological Survey 

384 Woods Hole Road 

Woods Hole, MA 02543 

(508) 457-2263 

dhutchinson@usgs.gov 

Omowunmi Iledare 

Center for Energy Studies 

Louisiana State University 

Energy, Coast and Environment Building 

Nicholson Drive Extension 

Baton Rouge, Louisiana 70803 

(225) 578-4552 

wumi@lsu.edu 

Masamichi Inoue 

Assoc. Professor 

LSU Coastal Studies Institute 

331 Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 388-2521 

coiino@lsu.edu 

George Ioup 

Professor 

University of New Orleans 

Dept. of Physics 

New Orleans, LA 70148 

(504) 280-6715 

geioup@uno.edu 

Juliette Ioup 

Professor 

University of New Orleans 

Dept. of Physics 

New Orleans, LA 70148 

(504) 280-6715 

jioup@uno.edu 

Erin W. Janes 

Geoscience Earth & Marine Services, Inc. 

10615 Shadow Wood Drive, Suite 200 

Houston, TX 77043 

(713) 468-1410 

emwilliams@gemsinc.com 

Nathalie Jaquet 

Texas A&M University 

5007 Ave U 

Galveston, TX 77551 

(409) 741-4329 

jaquetn@tamug.edu 

Ewa Jarosz 

Naval Research Laboratory 

Code 7332 

Bay Saint Louis, MS 39529-5004 

(228) 688-4292 

ewa.jarosz@nrlssc.navy.mil 

Michael R. Jenkerson 

Data Acquisition Researcher 

ExxonMobil Upstream Research Co. 

P.O. Box 2189 

Houston, TX 77252-2189 

(713) 431-6907 

mike_jenkerson@exxonmobile.com 

Grant Jennings 

RD Instruments 

9855 Businesspark Avenue 

San Diego, CA 92131 

(858) 693-1178 

gjennings@rdinstruments.com 

Ann E. Jochens 

Texas A&M, Dept. of Oceanography 

3146 TAMU 

College Station, TX 77843-3146 

(979) 845-6714 

ajochens@tamu.edu 

Bonnie L. Johnson 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2855 

bonnie.johnson@mms.gov 

James B. Johnston 

Supervisory General Biologist 

USGS, National Wetlands Research Center 

700 Cajundome Blvd 

Lafayette, LA 70506 

(337) 266-8556 

jimmy_johnston@usgs.gov 

Alvin Jones 

Sr. Environmental Scientist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-1713 

alvin.jones@mms.gov 
596 

Michael J. Kaluza 

Geoscience Earth & Marine Services, Inc. 

10615 Shadow Wood Drive, Suite 200 

Houston, TX 77043 

(713) 468-1445 

mjkaluza@gemsinc.com 

Jeffery A. Keay 

U.S. Geological Survey 

7920 NW 71st Street 

Gainesville, FL 32653 

(352) 264-3515 

jeff_keay@usgs.gov 

Sean F. Keenan 

Grad Assist 

LSU Coastal Fisheries Institute 

218 Wetlands Resource Bldg 

Baton Rouge, LA 70803 

(225) 388-8306 

skeenan@lsu.edu 

Matt Keith 

Tesla Offshore 

36499 Perkins Road 

Prairieville, LA 70769 

(225) 673-2163 

keithm@teslaoffshore.com 

Christina Kellogg 

U. S. Geological Survey 

600 Fourth St. S. 

Saint Petersburg, FL 33701 

(727) 803-8747 

ckellogg@usgs.gov 

James J. Kendall 

Chief, Environmental Sciences Section 

MMS 

381 Elden St MS 4023 

Herndon, VA 20170 

(703) 787-1591 

james.kendall@mms.gov 

Jan L. Kenny 

DEMEX International, Inc. 

16222 Halpern Falls Lane 

Cypress, TX 77429 

(281) 246-4738 

jan@demex.us 

John Kenny 

Boh Bros. Construction LLC 

1207 North Freeway, Suite 592 

Houston, TX 77060 

(281) 872-7860 

Terry E. Ketler 

Interactive Educational Network 

3245 Clay Street, #4 

San Francisco, CA 94115 

(415) 922-6189 

tketler@interactivenetwork.org 

Mi Ae Kim 

NOAA 

1315 East-West Hwy 

F/PR3 

Silver Spring, MD 20910 

(301) 713-1401x 159 

mi.ae.kim@noaa.gov 

Jack L. Kindinger 

USGS 

600 4th Street South 

Saint Petersburg, FL 33701 

(727) 803-8747x 3018 

jkindinger@usgs.gov 

Shana Kinsey 

Florida Dept. of Environmental Protection 

3900 Commonwealth Blvd., MS 47 

Tallahassee, FL 32399 

(850) 245-2163 

shana.kinsey@dep.state.fl.us 

Paul L. Klerks 

University of Louisiana at Lafayette 

P O Box 42451 

Lafayette, LA 70504 

(337) 482-6356 

klerks@louisiana.edu 

Elizabeth Komiskey 

MMS 

1201 Elmwood Blvd. 

New Orleans, LA 70123 

Gregory J. Kozlowski 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70115 

(504) 736-2512 

greg.kozlowski@mms.gov 
597 

Paul LaRock 

Louisiana State University 

Ronald J. Lai 

MMS 

381 Elden Street 

MS 4041 

Herndon, VA 20170 

(703) 787-1714 

ronald.lai@mms.gov 

Manuel Lam 

LA Department of Natural Resources 

P.O. Box 44156 

Baton Rouge, LA 70804-4156 

(225) 342-8919 

manuell@dnr.state.la.us 

Dietrich K. Landis 

ECL/Geocet 

9801 Westheimer, Suite 1060 

Houston, TX 77042 

(713) 784-5800 

d.landis@ecqc.com 

Connie Landry 

Environmental Studies Program Specialist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

(504) 736-2864 

connie.landry@mms.gov 

Randy C. Landry 

T. Baker Smith & Sons 

P O Box 2266 

Houma, LA 70361 

(985) 223-9222 

randyl@tbsmith.com 

William H. Lang 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123-2394 

(504) 736-2866 

bill.lang@mms.gov 

Jennifer N. Latusek 

SAIC 

1140 Eglin Parkway 

Shalimar, FL 32579 

(850) 609-3479 

jennifer.n.latusek@saic.com 

Jill E. Leale 

MMS 

1201 Elmwood Park Blvd., MS 5413 

New Orleans, LA 70123 

(504) 736-5705 

jill.leale@mms.gov 

Kevin Leaman 

Professor 

University of Miami 

4600 Rickenbacker Causeway 

Miami, FL 33149 

(305) 361-4058 

kleaman@rsmas.miami.edu 

Steve Leathery 

NOAA National Marine Fisheries Service 

Office of Protected Resources, F/PR1 

1315 East-West Hwy. 

Jefferson, MD 21755 

(301) 713-2289 

steve.leathery@noaa.gov 

Griff C. Lee 

Griff C. Lee, Inc. 

6353 Carlson Dr. 

New Orleans, LA 70122 

(504) 288-5824 

griff_c_lee@yahoo.com 

Herb Leedy 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2776 

daniel.leedy@mms.gov 

Christina Leza 

University of Arizona 

Tucson, AZ 85712 

leza@u.arizona.edu 

Qianxin Lin 

LSU Wetland Biogeochemistry Institute 

School of the Coast and Environment 

Baton Rouge, LA 70803 

(225) 578-8889 

comlin@lsu.edu 

Christopher Lindsey-Curran 

British Petroleum 

lindc7@bp.com 
598 

Greg Linscombe 

USFWS 

(337) 373-0032 

Linscombe@apwireless.com 

Brian C. Lombard 

MMS 

381 Elden Street 

Herndon, VA 20170 

(703) 787-1773 

brian.lombard@mms.gov 

Isis Longo 

Biologist II (Marine) 

Louisiana Department of Wildlife & Fisheries 

2000 Quail Dr. 

Baton Rouge, LA 70808 

(225) 765-2381 

kherzog@wlf.louisiana.gov 

Alexis Lugo-Fernandez 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123-2394 

(504) 736-2593 

alexis.lugo.fernandez@mms.gov 

Jay N. Lustig 

Scientific Solutions, Inc. 

99 Perimeter Road 

Nashua, NH 03063 

(603) 880-3784 

jlustig@scisol.com 

Asha D. Luthra 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 731-7850 

asha.luthra@mms.gov 

Harry Luton 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2784 

harry.luton@mms.gov 

James Lynch 

Woods Hole Oceanographic Institution 

98 Water Street, MS 11 

Woods Hole, MA 02543 

(508) 289-3292 

jlynch@whoi.edu 

Michael Lyons 

LAMOGA 

801 N. Blvd., Suite 201 

Baton Rouge, LA 70802 

(225) 387-3205 

lyons@lmoga.com 

Ian R. MacDonald 

Texas A&M University 

727 Graham Rd 

College Station, TX 77845 

(409) 862-2323x-119 

ian@gerg.tamu.edu 

Peter T. Madsen 

Woods Hole Oceanographic Institution 

Woods Hole Rd. 266 

Caryn House #44 

Woods Hole, MA 02543 

(508) 289-3292 

pmadsen@whoi.edu 

Leslie A. March 

Sierra Club 

67017 Dolan Street 

Mandeville, LA 70471 

(985) 871-6695 

lesliemarch@hotmail.com 

Bruce Mate 

Oregon State University Marine Science Center 

2030 SE Marine Science Drive 

Newport, OR 97367 

(541) 867-0202 

bruce.mate@oregonstate.edu 

Jason Mathews 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2886 

jason.mathews@mms.gov 
599 

Haru Matsumoto 

Oregon State University & NOAA/PMEL 

2115 SE OSU Drive 

Newport, OR 97365 

(541) 867-0272 

haru.matsumoto@noaa.gov 

Megan Cope Mattson 

NOAA, National Marine Fisheries Services 

3209 Frederic Street 

Pascagoula, MS 39567 

(228) 762-4591x X235 

megan.mattson@noaa.gov 

Tom McDonald 

Senior Project Manager 

TDI - Brooks International 

1902 Pinon Drive 

College Station, TX 77845 

(979) 693-3446 

tommcdonald@tdi-bi.com 

Jamie McKee 

Biologist 

SAIC 

1140 Eglin Parkway 

Shalimar, FL 32579 

(850) 609-3418 

mckeew@saic.com 

James P. McKinley 

Pacific Northwest National Laboratory 

MS K8-96 

P.O. Box 999 

Richland, WA 99352 

(509) 376-6573 

james.mckinley@pnl.gov 

Kevin McKone 

LSU 

P.O. Box 649 

Wesson, MS 39191 

(601) 643-8450 

kevin.mckone@colin.edu 

Robert McMillan 

Oceans Technology, Inc. 

3836 Spencer Street 

Harvey, LA 70058-5090 

(504) 340-4601 

linden@oceanstechnology.com 

Richard T. McNider 

University of Alabama in Huntsville 

Atmospheric Sciences Dept. 

320 Sparkman Dr. NSSTC 3051 

Huntsville, AL 35899 

(256) 961-7756 

mcnider@nsstc.uah.edu 

David Mellinger 

Oregon State University & NOAA/PMEL 

2030 SE Marine Science Drive 

Newport, OR 97365 

(541) 867-0372 

david.mellinger@oregonstate.edu 

David Meloy 

Louisiana Department of Natural Resources 

P.O. Box 2827 

Baton Rouge, LA 70821-2827 

(225) 342-6119 

davidm@dnr.state.la.us 

Roger Melton 

ExxonMobil 

P.O. Box 2189 

Houston, TX 77252 

(713) 431-4485 

rogermelton@exxonmobil.com 

Carson Mencken 

Baylor University 

Box 97326 One Bear Place 

Waco, TX 76798 

(254) 710-4863 

carson_mencken@baylor.edu 

Robert J. Menzie 

Eni Petroleum Company, Inc. 

1201 Louisiana, Suite 3500 

Houston, TX 77002 

(713) 393-6312 

robert.menzie@enipetroleum.com 

Stacie Merritt-Hendon 

Physical Scientist 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-3276 
600 

Margaret C. Metcalf 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123-2394 

(504) 731-7801 

margaret.metcalf@mms.gov 

Thomas Meyer 

Physical Scientist 

MMS 

1201 Elmwood Park Blvd., MS 5232 

DOI/MMS 

(504) 736-3247 

tom.meyer@mms.gov 

Jacqueline Michel 

RPI Louisiana, Inc. 

CERM Bldg. University of New Orleans 

2045 Lakeshore Drive 

New Orleans, LA 70122 

(504) 280-4085 

jmichel@researchplanning.com 

Lillian Miller 

Mind's Eye Productions 

200 Ziegler Avenue 

Houma, LA 70360 

(985) 876-1810 

llillian@sw.rr.com 

Mark W. Miller 

Research Specialist 

LSU Coastal Fisheries Institute 

2137 Energy, Coast & Environment Bldg. 

Baton Rouge, LA 70803 

(225) 578-9411 

mmill16@lsu.edu 

Patrick Miller 

University of Saint Andrews, Gatty Marine Lab 

Saint Andrews, Fife KY16 8LB 

UNITED KINGDOM 

Lauren K. Mione 

LSU Coastal Fisheries Institute 

10720 Linkwood Court, Apt. 514 

Baton Rouge, LA 70810 

(225) 578-7920 

lmionel@lsu.edu 

Douglas A. Mitchell 

Naval Research Laboratory 

Stennis Space Center, MS 39529 

(228) 688-4865 

dmitchell@nrlssc.navy.mil 

Heather R. Monroe 

Louisiana DNR, Technology Assessment Division 

P.O. Box 44156 

Baton Rouge, LA 70804-4156 

(225) 342-8232 

heather.monroe@la.gov 

Dave Moran 

Environmental Scientist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2896 

dave.moran@mms.gov 

Michelle V. Morin 

Environmental Scientist 

MMS 

1201 Elmwood Park Blvd 

MS 5412 

(504) 736-2797 

michelle.morin@mms.gov 

Thanos Moros 

British Petroleum 

Cheryl L. Morrison 

USGS Leetown Science Center 

Aquatic Ecology Branch 

11649 Leetown Road 

Kearneysville, WV 25430 

(304) 724-4464 

cheryl_morrison@usgs.gov 

John L. Morse 

RPS Hydrosearch 

16800 Greenspoint Park Drive, Suite 165-S 

Houston, TX 77060 

(281) 646-0120 

morsej@rpsplc.com 

John Morse 

Texas A&M University 

Dept. of Oceanography 

College Station, TX 77843-3146 

(979) 845-9630 

jmorse@ocean.tamu.edu 
601 

Toni Mosleh 

University of New Orleans Conference Services 

New Orleans, LA 70148 

George Mullen 

Devon Energy Corporation 

1200 Smith Street, Suite 3300 

Houston, TX 77002 

(713) 286-5836 

george.mullen@dvn.com 

Keith Mullin 

NOAA Fisheries 

3209 Frederic Street 

Pascagoula, MS 39567 

(228) 762-5491x 275 

keith.d.mullin@noaa.gov 

Thomas W. Neurauter 

Marine Geologist 

Geoscience Earth & Marine Services, Inc. 

10615 Shadow Wood Drive, Suite 200 

(713) 468-1410 

twneurauter@gemsinc.net 

Joal J. Newcomb 

Naval Research Laboratory 

NRL Code 7185 

Stennis Space Center, MS 39529 

(228) 688-5234 

newcomb@nrlssc.navy.mil 

Alan H. Nguyen 

University of Houston 

Dept. Civil & Environ. Engineering 

Bldg. 1-Rm N107 

4800 Calhoun 

Houston, TX 77204-4003 

(713) 743-4267 

youhaa@yahoo.com 

David L. Nieland 

Research Associate V 

LSU Coastal Fisheries Institute 

CCEER Wetlands Bldg 

Baton Rouge, LA 70803 

(225) 388-6373 

dniela@lsu.edu 

Thomas Norris 

Senior Scientist/Marine Vertebrate Biologist 

SAIC 

10260 Campus Pt. Dr., MS D-4 

San Diego, CA 92121-1578 

(760) 632-6344 

thomas.f.norris@saic.com 

Arlette C. Nunez 

Shell E & P 

701 Poydras St. 

New Orleans, LA 70139 

(504) 728-6188 

arlette.nunez@shell.com 

Clifton Nunnally 

Texas A & M at Galveston 

5007 Avenue U, Room 354 

Galveston, TX 77551 

(409) 740-5001 

David Ohara 

GeoCet 

One Sugar Land Center Blvd., Suite 355 

Sugar Land, TX 77478 

(281) 325-1080 

davidohara@geocet.com 

Roger Olien 

Impact Assessment Inc. 

2166 Avenida de la Playa 

La Jolla, CA 92037 

(858) 459-0142 

iai@san.rr.com 

Joel Ortega 

Oregon State University 

Hatfield Marine Science Center 

2030 SE Marine Science Drive 

Newport, OR 97365 

(541) 867-0354 

joel.ortega@oregonstate.edu 

Bernard Padovani 

Int'l Association of Geophysical Contractors 

2550 North Loop West 

Suite 104 

Houston, TX 77092 

(713) 957-8080 

bpadovani@iagc.org 
602 

David R. Palmer 

NOAA/AMOL/Ocean Chemistry Dept. 

4301 Rickenbacker Cswy. 

Miami, FL 33149 

(305) 361-4416 

david.r.palmer@noaa.gov 

Michael E. Parker 

Environmental Advisor 

Exxon Mobil Production Company 

P.O. Box 2180 

RM 4289 EMB 

Houston, TX 77541 

(713) 656-3563 

michael.e.parker@exxonmobil.com 

Roy E. Parr 

Retired, Exxon 

P.O. Box 273 

Baldwin, LA 70514 

Robert Paulsell 

LSU 

LA Geological Survey 

Baton Rouge, LA 70803 

(225) 578-8655 

rpaulsell@lsu.edu 

Megan B. Peabody Westmeyer 

Louisiana State University 

225 Muirfield Parkway 

Charleston, SC 29414 

(843) 579-8502 

mpeabo1@lsu.edu 

Kathleen Peneguy 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

Brian Perez 

USGS, National Wetlands Research Center 

700 Cajundome Blvd. 

Lafayette, LA 70506 

(337) 266-8556 

John S. Petterson 

President 

Impact Assessment, Inc. 

2166 Avenida de la Playa, Suite F 

(858) 459-0142 

iai@san.rr.com 

Elizabeth A. Peuler 

Supervisor, Physical Science Unit 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2581 

elizabeth.peuler@mms.gov 

Neal W. Phillips 

Senior Scientist 

Continental Shelf Associates, Inc. 

308 Southway 

Baltimore, MD 21218 

(410) 889-7811 

nwphillips@att.net 

Jonathan T. Phinney 

NOAA-Ocean Exploration 

1315 East West Hwy. 

10th Floor (R/OE) 

Silver Spring, MD 20910 

(301) 713-9444 x 117 

jonathan.phinney@noaa.gov 

Ric Pincomb 

Research Associate 

LSU Center for Energy Studies 

1 East Fraternity Circle 

Baton Rouge, LA 70803 

(225) 578-4545 

rpincom@lsu.edu 

Tim I. Pinnington 

Seamap, Inc. 

10801 Hammerly Blvd., Suite 206 

Houston, TX 77043 

(713) 690-2228 

tim.pinnington@seamap.com 

Monica Powers 

University of North Carolina - Chapel Hill 

Institute of Marine Science 

3431 Arendell- Moorehead City 

Chapel Hill, NC 27514 

mjanepowers@hotmail.com 

Sean Powers 

University of South Alabama 

101 Bienville Blvd. 

Dauphin Island, AL 36528 

(251) 861-7591 

spowers@disl.org 
603 

William F. Precht 

Ecological Sciences Program Manager 

PBS&J 

2001 NW 107th Avenue 

Miami, FL 33172 

(305) 514-3488 

bprecht@pbsj.com 

Tyler Priest 

History International, LLC 

1817 Oxford St. 

Houston, TX 77008 

(713) 868-4039 

tpriest@houston.rr.com 

Kimberly A. Puglise 

NOAA's Undersea Research Program 

1315 East-West Highway 

R/NURP 

Silver Spring, MD 20910 

(301) 713-2427x 199 

kimberly.puglise@noaa.gov 

Allan G. Pulsipher 

LSU Center for Energy Studies 

1 East Fraternity Circle 

Baton Rouge, LA 70803 

(225) 388-4550 

agpul@lsu.edu 

Christina Quijano 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2702 

chris.quijano@mms.gov 

Jeff Ramos 

Lt. Commander 

U.S. Coast Guard 

500 Poydras 

New Orleans, LA 70130 

(504) 589-2455 

jmramos@d8.uscg.mil 

James Randolph 

DOC/NOAA/NMFS 

4700 Avenue U 

Galveston, TX 77551 

(409) 766-3505 

james.randolph@noaa.gov 

Robert N. Ranney 

DOI/MMS 

201 Energy Parkway, Suite 410 

Broussard, LA 70518 

(337) 289-5108 

robert.ranney@mms.gov 

James P. Ray 

Oceanic Environmental Solutions, LLC 

16606 Aldenham Place 

Spring, TX 77379 

(713) 992-1523 

jray@houston.rr.com 

Grayson Rayborn 

Professor 

University of Southern Mississippi 

Signal Research Center 

6971 Lincoln Road Extension 

Hattiesburg, MS 39402 

(601) 268-2681x-34 

grayson.rayborn@usm.edu 

Michael Rex 

University of Massachusetts Boston 

100 Morrissey Blvd. 

Boston, MA 02125 

(617) 287-6678 

michael.rex@umb.edu 

Julie A. Reynolds 

DOI/MMS 

381 Elden Street, MS 4001 

Herndon, VA 20170 

(703) 787-1208 

julie.reynolds@mms.gov 

Harry I. Rich 

Clean Gulf Associates 

P.O. Box 51239 

New Orleans, LA 70151 

(504) 593-7597 

harry_i_rich@dom.com 

Blake A. Richard 

University of Louisiana at Lafayette 

301 Manchester Circle 

Lafayette, LA 70506 

(337) 983-2361 

bar7737@ull.edu 
604 

G. Ed Richardson 

MMS 

139 Deerlake Drive 

Asheville, NC 28803 

(828) 277-5887 

ed.richardson@mms.gov 

W. John Richardson 

LGL Ltd., Environmental Research Associates 

22 Fisher St. 

P.O. Box 280 

King City, ON L7B 1A6 

CANADA 

(905) 833-1244 

wjr@lgl.com 

Rian S. Riche 

Shell Offshore, Inc. 

P.O. Box 61933 

New Orleans, LA 70161-1933 

(504) 728-6012 

rian.riche@shell.com 

Thomas Riches 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-5790 

thomas.riches@mms.gov 

Deborah J. Roberts 

Associate Professor 

University of Houston 

Engineering Building 1 

Houston, TX 77204-2162 

(713) 743-4281 

djroberts@uh.edu 

Harry Roberts 

LSU Coastal Studies Institute 

335 Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 578-2964 

hrober3@lsu.edu 

Prince Robinson, Jr. 

Louisiana Department of Wildlife & Fisheries 

2000 Quail Drive 

Baton Rouge, LA 70808 

(225) 765-2381 

probinson@wlf.louisiana.gov 

Carol L. Roden 

MMS 

1201 Elmwood Park Blvd., MS 5432 

New Orleans, LA 70123 

(504) 736-2377 

carol.roden@mms.gov 

Robert Rogers 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2898 

Robert.Rogers@mms.gov 

Terry Rooney 

Coordinator 

BP Deepwater Development 

501 WestLake Park Blvd., Room 20.180 

Houston, TX 77079 

(281) 366-5703 

rooneyt@bp.com 

Pasquale F. Roscigno 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2752 

pasquale.roscigno@mms.gov 

Zeta Rosenberg 

Vice President 

ICF Consulting, Inc. 

9300 Lee Highway 

Fairfax, VA 22031 

(703) 934-3949 

zrosenberg@icfconsulting.com 

Lawrence J. Rouse 

Director 

LSU Coastal Marine Institute 

Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 578-6308 

lrouse@lsu.edu 

Mark Rouse 

Sr. Staff Assistant 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2594 

mark.rouse@mms.gov 
605 

Gil Rowe 

Professor 

Department of Oceanography 

Texas A&M University, MS 3146 TAMU 

College Station, TX 77845 

(409) 845-4092 

growe@ocean.tamu.edu 

M. J. Samaha 

117 Mcallen Drive 

Houma, LA 70360 

(985) 872-3768 

Mary Samaha 

117 Mcallen Drive 

Houma, LA 70360 

(985) 872-3768 

Paul W. Sammarco 

Professor 

LUMCON 

8124 Hwy. 56 

Chauvin, LA 70344 

(985) 851-2876 

psammarco@lumcon.edu 

Timothy R. Sampson 

API 

1220 L Street NW 

Washington, DC 20005 

(202) 682-8153 

sampson@api.org 

Scott Sanders 

BHP Billiton 

1360 Post Oak Blvd, Suite 150 

Houston, TX 77056-3020 

(713) 961-8420 

scott.s.sanders@bhpbilliton.com 

Bob J. Sandilos 

ChevronTexaco Upstream 

1111 Bagby Street 

Houston, TX 77002 

(713) 752-6356 

rjsa@chevrontexaco.com 

Kathryn M. Scanlon 

U.S. Geological Survey 

384 Woods Hole Rd 

Woods Hole, MA 02543 

(508) 457-2323 

kscanlon@usgs.gov 

William B. Schill 

USGS-Leetown Science Center 

11649 Leetown Road 

Kearneysville, WV 25430 

(304) 724-4438 

bane_schill@usgs.gov 

William Schroeder 

Professor 

University of Alabama 

Dauphin Island Sea Lab 

101 Bienville Blvd 

(251) 861-7528 

wschroeder@disl.org 

Joseph S. Scire 

Earth Tech, Inc. 

196 Baker Avenue 

Concord, MA 01742 

(978) 371-4270 

jss@src.com 

Paul D. Scott 

Marathon Oil Company 

5555 San Felipe Drive 

Houston, TX 77056 

(713) 296-2217 

pscott@marathonoil.com 

John Seip 

Environmental Specialist 

Crescent Technology, Inc. 

1615 Poydras Street 

New Orleans, LA 70112 

(504) 582-4314 

john_seip@fmi.com 

James Sell 

University of Arizona 

P.O. Box 310030 

Tucson, AZ 85721-0030 

(520) 626-3898 

Barun K. Sen Gupta 

Louisiana State University 

Dept. of Geology & Geophysics 

Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803-4101 

(225) 578-5984 

barun@geol.lsu.edu 
606 

Cheryl Sephus 

University of New Orleans 

P.O. Box 1014 

New Orleans, LA 70148 

(504) 283-5370 

midsea20@hotmail.com 

Jack L. Shanks 

MMS 

1201 Elmwood Park Boulevard 

New Orleans, LA 70123-2394 

(504) 736-2951 

jack.shanks@mms.gov 

Brian Shannon 

Principal Environmental Scientist 

B.E. Shannon/Environment Consultant 

2915 Sunset Ridge 

McKinney, TX 75070-4217 

(972) 542-9622 

b.e.shannon@comcast.net 

Richard F. Shaw 

Director 

LSU Coastal Fisheries Institute 

CCEER Wetlands Bldg 

Baton Rouge, LA 70803 

(225) 578-6734 

rshaw@lsu.edu 

William W. Shedd 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2497 

william.shedd@mms.gov 

Andrew N. Shepard 

NOAA Undersea Research Center 

UNCW/CMS 

5600 Marvin Moss Lane 

Wilmington, NC 28409 

(910) 962-2446 

sheparda@uncw.edu 

Frank S. Shipley 

Center Director 

USGS Bio. Resources 

909 First Avenue, Suite 800 

Seattle, WA 98104-1055 

(206) 220-4608 

frank_shipley@usgs.gov 

Natalia A. Sidorovskaia 

University of Louisiana at Lafayette 

Physics Department 

UL Box 44210 

Lafayette, LA 70504-4210 

(337) 482-6274 

nsidorovskaia@louisiana.edu 

Earl R. Sims 

IAGC 

5912 Davenhill Court 

Plano, TX 75093 

(972) 781-0690 

earlrsims@aol.com 

James E. Sinclair 

MMS 

1201 Elmwood Park Blvd., MS 5432 

New Orleans, LA 70123 

(504) 736-2789 

james.sinclair@mms.gov 

Joachim Singleman 

LSU Dept. of Sociology 

126 Stubbs Hall 

Baton Rouge, LA 70803 

(225) 578-1635 

joachim@lsu.edu 

Kimberly A. Skrupky 

Marine Acoustics, Inc. 

4100 Farifax Dr., Suite 730 

Arlington, VA 22203 

(703) 465-8404 

kimberly.a.skrupky@marineacoustics.com 

Scott E. Slaughter 

The Center for Regulatory Effectiveness 

11 DuPont Circle, NW, Suite 700 

Washington, DC 20036 

(202) 265-2383 

slaughter@mbsdc.com 

Gregory J. Smith 

USGS, National Wetlands Research Center 

700 Cajundome Boulevard 

Lafayette, LA 70506 

(337) 266-8501 

gregory_smith@usgs.gov 
607 

Lorene E. Smith 

Research Associate 

LSU Museum of Natural Science 

119 Foster Hall 

Baton Rouge, LA 70803 

(225) 578-2296 

lsmit18@lsu.edu 

Tim D. Smith 

NOAA Fisheries 

166 Water Street 

Woods Hole, MA 02543 

(508) 495-2251 

tim.smith@noaa.gov 

Mark Snyder 

Naval Oceanographic Office 

1002 Balch Blvd. 

Stennis Space Center, MS 39522 

(228) 689-8019 

snyderm@navo.navy.mil 

Tom Soniat 

Professor 

Nicholls State University, Dept. of Biology 

Thibodaux, LA 70310 

(504) 448-4865 

tom.sonait@nicholls.edu 

Shashidhar Sorakayala 

University of New Orleans Conference Services 

New Orleans, LA 70148 

Randy Soulier 

Arthur J. Gallagher of Louisiana 

235 Highlandia Dr., Suite 200 

Baton Rouge, LA 70810 

(800) 605-6102 

randy.soulier@ajg.com 

Jesse H. Spence 

Noise Control Engineering 

799 Middlesex Turnpike 

Billerica, MA 01821 

(978) 670-5339 

jesse@noise-control.com 

Tony R. St. Clair 

Ecology and Environment, Inc. 

220 W. Garden Street, Suite 404 

Pensacola, FL 32501 

(850) 435-8925 

tstclair@ene.com 

David R. Stauffer 

Pennsylvania State University 

503 Walker Building 

University Park, PA 16802 

(814) 863-3932 

stauffer@meteo.psu.edu 

Peter J. Stein 

Scientific Solutions, Inc. 

99 Perimeter Road 

Nashua, NH 03063 

(603) 880-3784 

pstein@scisol.com 

James Stephens 

University of Southern Mississippi 

6971 Lincoln Road 

Hattiesburg, MS 39402 

(601) 268-2681 

james.stephens@usm.edu 

Gregory Stone 

Louisiana State University 

Dept. of Oceanography/Coastal Science 

CSI - E111 Howe-Russell Geoscience Complex 

Baton Rouge, LA 70805 

(225) 578-6188 

gagreg@lsu.edu 

Joanna Stone 

University of Arizona 

Tucson, AZ 85721 

(520) 621-6282 

jostone@arizona.edu 

Bill Streever 

British Petroleum 

P.O. Box 196612 

900 E. Benson Blvd. 

Anchorage, AK 99519-6612 

(907) 564-4383 

streevbj@bp.com 

Kristen L. Strellec 

MMS 

1201 Elmwood Park Blvd., MS 5411 

New Orleans, LA 70123 

(504) 736-2465 

Kristen.Strellec@mms.gov 
608 

Michael G. Strikmiller 

Marketing Manage 

Environmental Enterprises USA, Inc. 

58485 Pearl Acres Road, Suite D 

(985) 646-2787 

mstrikmiller@eeusa.com 

Glenn M. Suir 

USGS / LSU AgCenter 

P.O. Box 25098 

Baton Rouge, LA 70894 

(225) 578-7203 

gsuir@usgs.gov 

Ken Sulak 

Research Fish Biologist 

USGS 

Florida Caribbean Science Center 

7920 NW 71st St. 

Gainesville, Florida 32653 

(352) 378-8181 

ken_sulak@usgs.gov 

Kavita Swaminathan 

University of Houston 

9900 Broadway Street, #1933 

Pearland, TX 77584 

(713) 743-4267 

kavita.swaminathan@mail.uh.edu 

David Szabo 

Fugro GEOS, Inc. 

6100 Hillcroft 

Houston, TX 77081 

(713) 346-3609 

d.szabo@geos.com 

Bruce A. Tackett 

ExxonMobil 

3225 Gallows Road 

Room 07D0427 

Fairfax, VA 22037 

(703) 846-3764 

bruce.a.tackett@exxonmobil.com 

Arslan M. Tashmukhambetov 

University of Louisiana at Lafayette 

2509 Johnston Street, Apt. 2-1 

Lafayette, LA 70503 

(337) 232-3502 

arsupisemnet@yahoo.com 

William J. Teague 

Oceanographer 

Naval Research Laboratory 

Stennis Space Center, MS 39529 

(228) 688-4734 

teague@nrlssc.navy.mil 

Bill Terrebonne 

Regulatory Specialist 

Shell E&P Company 

701 Poydras St., Office 3410 

P O Box 61933 

New Orleans, LA 70130 

(504) 728-7281 

william.terrebonne@shell.com 

Aaron M. Thode 

University of California, San Diego 

Scripps Institute of Oceanography 

9500 Gilman Drive - 0238 

La Jolla, CA 92093-0238 

(858) 822-4864 

thode@mpl.ucsd.edu 

Ian M. Threadgold 

BP 

502 Westlake Park Blvd. 

Houston, TX 77079 

(281) 366-3647 

threadim1@bp.com 

Wilfred W. Times 

MAU-Visual Information Specialist 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2762 

wilfred.times@mms.gov 

Maya Tolstoy 

Lamont-Doherty Earth Observatory 

61 Route 9W 

Palisades, NY 10964-8000 

(845) 365-8791 

tolstoy@ldeo.columbia.edu 

Cy Toups 

T. Baker Smith & Sons 

P.O. Box 2266 

Houma, LA 70360 

(985) 223-9224 

cyt@tbsmith.com 
609 

John H. Trefry 

Florida Institute of Technology 

Dept. of Marine & Environmental Sys. 

150 W. University Blvd. 

Melbourne, FL 32901 

(321) 674-7305 

jtrefry@fit.edu 

Debby Tucker 

Program Consultant 

Florida Dept. of Environmental Protection 

3900 Commonwealth Blvd., MS 47 

Tallahassee, FL 32301 

(850) 245-2163 

debby.tucker@dep.state.fl.us 

Kim Turner 

ChevronTexaco 

935 Gravier Street 

New Orleans, LA 70112 

(504) 592-6894 

kturner@chevrontexaco.com 

David C. Twichell 

U. S. Geological Survey 

384 Woods Hole Road 

Woods Hole, MA 02543-1598 

(508) 457-2266 

dtwichell@usgs.gov 

Peter L. Tyack 

Woods Hole Oceanographic Institution 

9 Maury Lane, MS 44 

Woods Hole, MA 02543 

(508) 289-2818 

ptyack@whoi.edu 

Sunil Kumar Vallur 

University of New Orleans Conference Services 

New Orleans, LA 70148 

Allen J. Verret 

Exec. Director 

Offshore Operators Committee 

P.O. Box 50751 

New Orleans, LA 70150-0751 

(504) 561-2427 

allen_verret@murphyoilcorp.com 

Stephen Viada 

Sr. Staff Scientist 

Continental Shelf Associates, Inc. 

328 Aris Ave 

Metairie, LA 70005 

(504) 837-6253 

sviada@gs.net 

Debra Vigil 

MMS 

1201 Elmwood Park Blvd., MS 5431 

New Orleans, LA 70123 

(504) 736-2406 

debra.vigil@mms.gov 

Jenneke Visser 

LSU Coastal Ecology Institute 

Baton Rouge, LA 70803 

(225) 578-6377 

comvss@lsu.edu 

Barry Vittor 

Barry A. Vittor & Associates, Inc. 

8060 Cottage Hill Rd 

Mobile, AL 36695 

(334) 633-6100 

bvittor@bvaenviro.org 

Latonia Viverette 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2433 

latonia.viverette@mms.gov 

Michael Vogel 

Sr. Research Engineer 

Shell E&P Company 

3737 Bellaire Blvd 

Houston, TX 77025 

(713) 245-7454 

michael.vogel@shell.com 

Jon H. Volstad 

Versar, Inc. 

9200 Rumsey Road 

Columbia, MD 21045 

(410) 740-6085 

jvolstad@versar.com 
610 

Fred M. Vukovich 

Science Applications International Corporation 

615 Oberlin Road, Suite 100 

Raleigh, NC 27605 

(919) 836-7563 

fvukovich@raleigh.saic.com 

Terry Wade 

Texas A&M University 

GERG -TAMU Mail Stop 3149 

833 Graham Rd 

College Station, TX 77845 

(979) 862-2323x-134 

terry@gerg.tamu.edu 

Jack B. Waide 

U.S. Geol. Survey-Biological Resources Discipline 

12201 Sunrise Valley Drive, MS 301 

Reston, VA 20192 

(703) 648-4053 

jwaide@usgs.gov 

Christopher D. Walker 

University of Southern Mississippi 

Hattiesburg, MS 39406 

(601) 268-2681x 39 

christopher.walker@usm.edu 

Nan Walker 

LSU Coastal Studies Institute 

Dept of Oceanography 

Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 578-5331 

nwalker@lsu.edu 

Michael B. Wallace 

MMS 

1201 Elmwood Park Blvd. 

New Orleans, LA 70123 

(504) 736-2423 

michael.wallace@mms.gov 

Ellen N. Walz 

MMS 

381 Elden Street, MS 4010 

Herndon, VA 20170 

(504) 787-1275 

ellen.walz@mms.gov 

Dr. E.G. Ward 

Texas A&M University 

Offshore Technology Research Center 

1200 Mariner Dr 

College Station, TX 77845 

(409) 862-2288 

egward@tamu.edu 

Douglas Wartzok 

Florida International University 

University Park, PC 230 

Miami, FL 33199 

(305) 348-2455 

wartzok@fiu.edu 

Stephanie L. Watwood 

Woods Hole Oceanographic Institution 

266 Woods Hole Road 

Caryn House MS 44 

Woods Hole, MA 02543 

(508) 289-3643 

swatwood@whoi.edu 

Douglas C. Weaver 

Marine Biologist/GIS Specialist 

Flower Garden Banks National Marine Sanctuary 

1200 Briarcrest Drive, Suite 4000 

Bryan, TX 77802 

(979) 846-5942 

doug.weaver@noaa.gov 

Chih-Lin Wei 

Texas A&M University at Galveston 

5007 Avenue 

Galveston, TX 77551 

(409) 741-7124 

weic@tamug.edu 

Susan E. Welsh 

LSU Coastal Studies Institute 

331 Howe-Russell Geoscience Complex 

Baton Rouge, LA 70803 

(225) 578-0439 

swelsh@lsu.edu 

Karen A. Westphal 

LSU/SL&E Special Programs 

921 Magnolia Wood Ave 

Baton Rouge, LA 70809 

(225) 766-5046 

kwestph@lsu.edu 
611 

Dana Wetzel 

Mote Marine Laboratory 

1600 Ken Thompson Parkway 

Sarasota, FL 34236 

(941) 388-4441 

dana@mote.org 

Nick Wetzel 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70448 

(504) 739-2419 

nick.wetzel@mms.gov 

Neil J.M. Wheeler 

Sonoma Technology, Inc. 

1360 Redwood Way, Suite C 

Petaluma, CA 94954-1169 

(707) 665-9900 

neil@sonomatech.com 

Mary Wicksten 

Texas A & M Dept. of Biology 

3258 TAMU Butler Hall, Room 202 

College Station, TX 77843 

(979) 845-3388 

wicksten@mail.bio.tamu.edu 

Andrew T. Wigton 

ExxonMobil 

P.O. Box 2189 

URC-GW3-866B 

Houston, TX 77252-2189 

(713) 431-7025 

andrew.t.wigton@exxonmobil.com 

Charles A. Wilson 

LSU 

Louisiana Sea Grant 

Baton Rouge, LA 70803 

(225) 578-6283 

cwilson@lsu.edu 

Darcy Wilson 

Program Manager 

Eastern Research Group, Inc. 

1600 Perimeter Park Drive 

Morrisville, NC 27560 

(919) 468-7860 

darcy.wilson@erg.com 

Judith M. Wilson 

Marine Biologist 

MMS 

381 Elden Street 

Herndon, VA 20170 

(703) 787-1075 

judy.wilson@mms.gov 

Susan Wilson 

British Petroleum 

200 Westlake Park Blvd. 

Houston, TX 77079 

(281) 366-0969 

wilson4@bp.com 

Debra Winbush 

Public Affairs Specialist 

MMS 

1201 Elmwood Park Blvd., MS 5000 

New Orleans, LA 70123 

(504) 736-2597 

debra.winbush@mms.gov 

Martha Winsor 

Research Assistant 

Oregon State University 

Hatfield Marine Science 

Corvallis, OR 97331 

(541) 867-0288 

martha.winsor@oregonstate.edu 

Mark Witten 

Sr. Advisor - HSE 

ChevronTexaco 

935 Gravier St. 

New Orleans, LA 70112 

(504) 592-6336 

mswi@chevrontexaco.com 

Jeff F. Wolfe 

U.S. Coast Guard 

Coast Guard District Eight, Room 1341 

500 Poydras 

New Orleans, LA 70130-3396 

(504) 589-6260 

jwolfe@d8.uscg.mil 

George Wooddell 

University of Louisiana at Lafayette, Dept. of Sociology 

Mouton 219 

Lafayette, LA 70504 

(337) 482-5373 

wooddell@louisiana.edu 
612 

John H. Wormuth 

Texas A&M University, Dept. of Oceanography 

College Station, TX 77843 

(979) 845-7132 

jwormuth@ocean.tamu.edu 

Andrew Wright 

LADC 

(202) 271-0293 

marinebrit@netscape.net 

Rusty Wright 

MMS 

1201 Elmwood Park Blvd 

New Orleans, LA 70123 

(504) 736-2529 

Greg Yarwood 

ENVIRON International Corporation 

101 Rowland Way, Suite 220 

Novato, CA 94945 

(415) 899-0700 

gyarwood@environcorp.com 

Craig M. Young 

University of Oregon 

Oregon Institute of Marine Biology 

P O Box 5389 

Charleston, OR 97420 

(541) 888-2581x 299 

cmyoung@uoregon.edu 

John V. Young 

ExxonMobil Exploration Company 

222 Benmar 

Corp. GP8-734 

Houston, TX 77060 

(281) 654-4298 

john.v.young@exxonmobil.com 

Gary S. Zeigler 

Vaisala Inc. 

P.O. Box 3659 

Boulder, CO 80307-3659 

(303) 402-4700 

gary.zeigler@vaisala.com 

Steve D. Ziman 

ChevronTexaco Energy Technology Company 

100 Chevron Way 

Richmond, CA 94802 

(510) 242-1530 

sdzi@chevrontexaco.com 
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.