OCS Study 

MMS 2002-063 

Deepwater Program: 

Northern Gulf of Mexico Continental 

Slope Habitats and Benthic Ecology 

Interim Report - Year 2 

MMS U.S. Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 
Deepwater Program: 

Northern Gulf of Mexico Continental 

Slope Habitats and Benthic Ecology 

Interim Report - Year 2 

Authors 

Gilbert T. Rowe 

Mahlon C. Kennicutt II 

Prepared under MMS Contract 

1435-01-99-CT-30991 

by 

Texas A&M University 

Texas Engineering Experiment Station 

College Station, Texas 77843-3146 

Published by 

U.S. Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 

New Orleans

December 2002
iii 

DISCLAIMER

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

Texas A&M University. This report has been technically reviewed by the MMS and approved 

for publication. Approval does not signify that the contents necessarily reflect the views and 

policies of the Service, nor does mention of trade names of 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 the report may be obtained from the Public Information Office (Mail Stop 5034) 

at the following address: 

 U.S. Department of the Interior 

 Minerals Management Service 

 Gulf of Mexico OCS Region 

 Public Information Office (MS 5034) 

 1201 Elmwood Park Boulevard 

 New Orleans, Louisiana 70123-2394 

 Telephone Number: (504) 736-2519 

 1-800-200-GULF 

CITATION

Suggested Citation: 

Rowe, G.T. and M.C. Kennicutt II. 2002. Deepwater Program: Northern Gulf of Mexico 

Continental Slope Habitat and Benthic Ecology. Year 2: Interim Report. U.S. Department 

of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, New 

Orleans, Louisiana. OCS Study MMS 2002-063. 158 pp. 
v 

TABLE OF CONTENTS

PAGE

 List of Figures............................................................................................................ vii 

 List of Tables ............................................................................................................. xiii 

 Executive Summary................................................................................................... 1 

1.0 Introduction................................................................................................................ 1-1 

 1.1 Program Objectives........................................................................................ 1-3 

 1.2 The Program................................................................................................... 1-5 

2.0 A Conceptual Model of the Deep-Sea ....................................................................... 2-1 

 2.1 Biotic Variables ............................................................................................. 2-3 

 2.2 Community Structure..................................................................................... 2-5 

 2.3 Community Function ..................................................................................... 2-6 

 2.4 Geochemistry ................................................................................................. 2-7 

 2.5 The Water Column......................................................................................... 2-10 

 2.6 Community “Health” ..................................................................................... 2-10 

3.0 Program Design ......................................................................................................... 3-1

 3.1 General Design Considerations ..................................................................... 3-1 

 3.2 Working Hypotheses and Station Selection................................................... 3-2 

 3.3 Dependent and Independent Variables .......................................................... 3-10 

 3.4 Statistical Analyses........................................................................................ 3-12 

 3.4.1 Univariate Analyses........................................................................... 3-12 

 3.4.2 Power Analysis .................................................................................. 3-16 

 3.4.3 Multivariate Analyses........................................................................ 3-16 

 3.5 Revision of Taxonomic Level of Analysis .................................................... 3-17 

4.0 Field Activities........................................................................................................... 4-1 

 4.1 Cruise 1 .......................................................................................................... 4-1 

 4.2 Cruise 2 - Process Cruise ............................................................................... 4-2 

 4.3 Year 3 Field Activities................................................................................... 4-2 

5.0 Program Status and Preliminary Results ................................................................... 5-1 

 5.1 Task 1 - Re-Examination of Previous Studies ............................................... 5-1 

 5.2 Task 2 - Field Sampling................................................................................. 5-2 

 5.3 Task 3 - Sample Data Processing and Analysis............................................. 5-2 
vi 

 5.3.1 Physical Oceanography...................................................................... 5-2 

 5.3.2 Remote Sensing: Ocean Color Climatology...................................... 5-19 

 5.3.3 Geology.............................................................................................. 5-26 

 5.3.4 Geochemistry ..................................................................................... 5-26 

 5.3.4.1 Metals.................................................................................. 5-34 

 5.3.4.2 Trace Organic Contaminants .............................................. 5-38 

 5.3.4.3 Biogeochemistry ................................................................. 5-44 

 5.3.4.4 Geochemical Processes....................................................... 5-46 

 5.3.5 Biological Studies .............................................................................. 5-50 

 5.3.5.1 Microbiota........................................................................... 5-50 

 5.3.5.2 Benthic Foraminifera .......................................................... 5-62 

 5.3.5.3 Meiofauna ........................................................................... 5-64 

 5.3.5.4 Macrofauna ......................................................................... 5-68 

 5.3.5.5 Megafauna........................................................................... 5-72 

 5.3.5.6 Demersal Fish ..................................................................... 5-74 

 5.3.5.7 ADCP Detection of Mobile Near-Bottom Fauna................ 5-79 

 5.4 Community Function/Processes and Model Development............................ 5-84 

 5.5 Task 4 - Data Interpretation, Synthesis, and Reporting................................. 5-86 

6.0 Preliminary Observations and Summary ................................................................... 6-1 

7.0 Literature Cited.......................................................................................................... 7-1 
vii 

LIST OF FIGURES 

PAGE

Figure 1. A general model of a sediment-associated food-web .................................... 3 

Figure 2.1 A conceptual model of the deep-sea Gulf of Mexico .................................... 2-2 

Figure 2.2 The macrofauna submodel of a system carbon food chain model................. 2-3 

Figure 2.3 Sediment submodel of functional bacterial groups as defined by 

 utilization of different terminal electron acceptors........................................ 2-9 

Figure 3.1 Benthic survey stations in the northwestern GOM........................................ 3-4 

Figure 3.2 Benthic survey stations across the Florida Escarpment................................. 3-5 

Figure 3.3 Benthic stations along the Mississippi Trough (MT1-MT6)......................... 3-6 

Figure 3.4 Physiographic settings for benthic survey stations in the Central GOM....... 3-7 

Figure 4.1 Benthic survey stations for DGoMB Cruise 1............................................... 4-3 

Figure 4.2 Benthic survey stations for DGoMB Cruise 2............................................... 4-4 

Figure 5.1 Vertical profiles of temperature, salinity, percent light transmission, 

 fluorometer voltage, and sigma-theta for DGoMB station MT1 ................... 5-7 

Figure 5.2 Vertical profiles of temperature, salinity, percent light transmission, 

 fluorometer voltage, and sigma-theta for DGoMB station GKF ................... 5-8 

Figure 5.3 Scatter plot of temperature versus salinity for DGoMB Cruise 1.................. 5-9 

Figure 5.4 Scatter plot of nitrate versus phosphate for DGoMB Cruise 1...................... 5-10 

Figure 5.5 Bottle salinity versus sigma-theta for DGoMB Cruise 1 and a 

 combination of DGoMB Cruise 1 and data from LATEX A and 

 NEGOM......................................................................................................... 5-11 

Figure 5.6 Dissolved oxygen versus sigma-theta for DGoMB Cruise 1 and 

 a combination of DGoMB Cruise 1 and data from LATEX A and 

 NEGOM......................................................................................................... 5-12 

Figure 5.7 Nitrate versus sigma-theta for DGoMB Cruise 1 and a combination 

 of DGoMB Cruise 1 and data from LATEX A and NEGOM ....................... 5-13 

Figure 5.8 Phosphate versus sigma-theta for DGoMB Cruise 1 and a 
viii 

 combination of DGoMB Cruise 1 (pluses) and data from LATEX A 

 and NEGOM .................................................................................................. 5-14 

Figure 5.9 Silicate versus sigma-theta for DGoMB Cruise 1 and (right) a 

 combination of DGoMB Cruise 1 and data from LATEX A 

 and NEGOM .................................................................................................. 5-15 

Figure 5.10 Sea surface height field for 14 May 2000 based on analyzed height 

 anomaly of TOPEX and ERS-2 altimeter data added to mean sea surface 

 height field ..................................................................................................... 5-16 

Figure 5.11 Broad-band 150 kHz ADCP current vectors at average depth of 12.4 m 

 on DGoMB leg 1 Cruise, 3-23 May 2000 ..................................................... 5-17 

Figure 5.12 Sea surface height field for 10 June 2000 based on analyzed height 

 anomaly of TOPEX and ERS-2 altimeter data added to mean surface 

 height field ..................................................................................................... 5-18 

Figure 5.13 Narrow-band 150 kHz ADCP current vectors at average depth of 11.6 m 

 on DGoMB let 2 Cruise, 21 May-21 June 2000 ............................................ 5-20 

Figure 5.14 Two-year time series of SeaWiFS chlorophyll concentration at deep 

 water DGoMB stations > 2600 m water depth in north-central and 

 northwestern Gulf of Mexico......................................................................... 5-22 

Figure 5.15 Two-year time series of SeaWiFS chlorophyll concentration for 

 DGoMB stations along Western (W) Transect and on Louisiana Slope ....... 5-23 

Figure 5.16 Two-year time series of SeaWiFS chlorophyll concentration for 

 DGoMB stations along Central (C) Transect and Mississippi Trough (MT) 

 Transect.......................................................................................................... 5-24 

Figure 5.17 Two-year time series of SeaWiFS chlorophyll concentration for DGoMB 

 stations in DeSoto Canyon and along Eastern Transect ................................ 5-25 

Figure 5.18 The sediment geotechnical properties of cores (5 replicates) taken 

 at the NB3 location ........................................................................................ 5-27 

Figure 5.19 The sediment geotechnical properties of cores (5 replicates) taken 

 at the MT6 location........................................................................................ 5-28 

Figure 5.20 A map showing the locations of the stations that have highly variable 

 geotechnical properties .................................................................................. 5-29 

Figure 5.21 Boxcore 134 at station W4 illustrating sediment that has almost no 

 significant bioturbation.................................................................................. 5-30 
ix 

Figure 5.22 Boxcore 12 at station MT5 illustrating sediment that has undergone a 

 slight to moderate degree of bioturbation...................................................... 5-31 

Figure 5.23 Boxcore 111 at station RW5 illustrating a high degree of bioturbation ........ 5-32 

Figure 5.24 A map showing the degree of sediment bioturbation present at the survey 

 sites ................................................................................................................ 5-33 

Figure 5.25 Variations in total sediment calcium (A), chromium (B), zinc (C), and 

 vanadium (D) concentrations as a function of changes in sediment 

 mineralogy (as indicated by sediment aluminum levels)............................... 5-36 

Figure 5.26 Variations in total sediment cadmium (A), copper (B), nickel (C), and 

 lead (D) concentrations as a function of changes in sediment 

 mineralogy (as indicated by sediment aluminum levels)............................... 5-37 

Figure 5.27 The concentration of perylene in sediments .................................................. 5-40 

Figure 5.28 The concentration of total polycyclic aromatic hydrocarbons (PAH) 

 without perylene in sediments ....................................................................... 5-41 

Figure 5.29 The total PAH concentration without perylene versus barium 

 concentration.................................................................................................. 5-42 

Figure 5.30 Frequency distribution of total PAH and total PAH without perylene 

 concentrations versus cumulative percentage................................................ 5-43 

Figure 5.31a Mean - HSiO3 and 2- H ( PO4 μM) concentrations at survey stations............... 5-46 

Figure 5.31b Mean - NO3 and - NO ( 2 μM) concentrations at survey stations ..................... 5-47 

Figure 5.31c Mean + NH and urea ( 4 μM) concentrations at survey stations....................... 5-48 

Figure 5.32 Depth-concentration profiles for DGoMB process stations .......................... 5-49 

Figure 5.33 Mean DOC concentrations (mg/L) and DIC stable carbon isotope (‰) 

 values at process stations ............................................................................... 5-51 

Figure 5.34a Variation in - HSiO3 and 2- H concentrations with depth in the core ....... 5-52 PO4

Figure 5.34b Variation in - HSiO3 and 2- H concentrations with depth in the core PO4

 at process stations .......................................................................................... 5-53 
x 

Figure 5.34c Variation in + NH and urea concentrations with depth in the core 4

 at process stations .......................................................................................... 5-54 

Figure 5.35 Variations for DOC concentrations (mg/L) and DIC stable 

 carbon isotope composition (‰) with depth in the core at 

 process stations .............................................................................................. 5-55 

Figure 5.36 Total inorganic nitrogen (TIN; μM) and phosphate (HPO4

=

; μM) 

 concentrations ................................................................................................ 5-56 

Figure 5.37 Benthic bacterial abundance as a function of depth ...................................... 5-59 

Figure 5.38 Benthic bacterial abundance for the east to west Gulf of Mexico................. 5-59 

Figure 5.39 Benthic bacterial abundance comparisons for basins, non-basins, 

 and canyons.................................................................................................... 5-60 

Figure 5.40 Benthic bacterial abundance as a function of water depth (no WC, B, 

 NB, or AC stations) ....................................................................................... 5-60 

Figure 5.41 Benthic bacterial abundance related to primary productive (low vs high).... 5-61 

Figure 5.42 Benthic bacterial abundance on the Sigsbee Escarpment (shallow vs 

 deep)............................................................................................................... 5-61 

Figure 5.43 Relationship between meiofaunal abundance and water depth ..................... 5-65 

Figure 5.44 Relative meiofaunal abundance at each station ............................................. 5-65 

Figure 5.45 Relationship between meiofaunal biomass and depth ................................... 5-66 

Figure 5.46 Relative meiofaunal biomass (g ww/m2

) at each station ............................... 5-66 

Figure 5.47 Relationship between major meiofaunal taxa diversity (Hill’s number, 

 N1) and depth................................................................................................. 5-67 

Figure 5.48 Relative major meiofaunal taxa diversity (N1) at each station...................... 5-67 

Figure 5.49 Relationship between meiofaunal and bacterial abundance .......................... 5-68 

Figure 5.50 Total macrofaunal densities by depth with the regression line and 

 formula, R-squared value, and number of samples involved......................... 5-70 

Figure 5.51 Total macrofaunal densities by depth except samples from the Mississippi 

 Trough (MT) and eastern (S) Gulf................................................................. 5-70 

Figure 5.52 Total macrofaunal densities by depth plotting all sorted samples from 
xi 

 the Mississippi Trough (MT)......................................................................... 5-71 

Figure 5.53 Total macrofaunal densities by depth plotting all sorted samples from 

 the eastern Gulf of Mexico (S) ...................................................................... 5-71 

Figure 5.54 Bottom photograph from Station MT1 at the head of the Mississippi 

 Canyon ........................................................................................................... 5-72 

Figure 5.55 Zonation and diversity (H’) in demersal fishes ............................................. 5-80 

Figure 5.56 Species richness in demersal fishes ............................................................... 5-81 

Figure 5.57 Abundance of demersal fishes by depth zone................................................ 5-82 

Figure 5.58 Maps of relative occurrences of trawl-caught trash and relative abundance 

 of macrofaunal sized nematodes (CPUE is catch per unit efforts) ................ 5-83 

Figure 5.59 Raw ADCP backscatter intensity from deployments 2 (755 m) and 

 3 (1,823 m) at the 14 m depth bin (21 m off bottom) .................................... 5-85 

Figure 5.60 The SCOC from the western GOM continental shelf down across the 

 slope to the abyssal plain is characterized by a log-log relationship 

 with depth ...................................................................................................... 5-86 

Figure 6.1 Conceptual model of a hypothetical deep benthos foodweb illustrating 

 that the input of organic carbon controls the web’s structure and 

 dynamics ........................................................................................................ 6-3 
xiii 

LIST OF TABLES 

PAGE

Table 1.1. Program Team - Key Personnel..................................................................... 1-4 

Table 3.1 Summary of benthic survey experimental design: null hypotheses, station 

 selection criteria, number of stations, and number of samples...................... 3-10 

Table 3.2 Independent variables fixed by the sampling plan design ............................. 3-11 

Table 3.3 Dependent variables to be measured ............................................................. 3-11 

Table 3.4 Ancillary variables to be measured at Survey and Experimental Stations .... 3-12 

Table 4.1 Summary of sampling conducted during Cruise 1......................................... 4-5 

Table 4.2 Summary of sampling conducted during Cruise 2......................................... 4-6 

Table 5.1 Samples collected during DGoMB Cruise 1.................................................. 5-3 

Table 5.2 Summary of samples collected during DGoMB Cruise 2 ............................. 5-4 

Table 5.3 Summary of the two-year average chlorophyll a concentrations (CHL) and 

 the standard deviation about the two-year mean at each of the stations........ 5-21 

Table 5.4 Summary of preliminary results..................................................................... 5-56 

Table 5.5 Foraminifera extracted for ATP..................................................................... 5-63 

Table 5.6 Larger invertebrate species from trawls......................................................... 5-73 

Table 5.7 Geographic squares in the Gulf of Mexico.................................................... 5-75 

Table 5.8 Fish characteristics by capture and location .................................................. 5-77 

Table 5.9 East to west faunal comparison (shelf/upper slope depths) including the 

 Canyon ........................................................................................................... 5-77 

Table 5.10 East to west faunal comparison (lower slope/rise depths)............................. 5-78 

Table 5.11 Basin to non-basin faunal comparison........................................................... 5-78 

Table 5.12 Canyon to non-canyon faunal comparison (lower slope/rise depths)............ 5-78 

Table 5.13 Backscatter averaged from the 14-m depth bin (21 m off bottom) in 

 four deployments ........................................................................................... 5-79
1 

EXECUTIVE SUMMARY 

 A research program has been initiated by the Minerals Management Service (Contract 

No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep 

Gulf of Mexico entitled “The Deepwater Program: Northern Gulf of Mexico Continental Slope 

Habitat and Benthic Ecology.” This report provides a summary of the progress to date at the end 

of the second year of the program. At this stage of the program, sample analyses are in progress 

with only partial data sets finalized. The program is on schedule and planning is in progress for 

the final year’s field program which includes a major extension of the sampling and analysis 

efforts into the deepest regions of the southern Gulf of Mexico. 

 Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea 

prompted the Minerals Management Service of the U.S. Department of the Interior to support an 

investigation of the structure and function of the assemblages of organisms that live in 

association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or 

DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 

300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward 

of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the 

most likely targets of future resource exploration and exploitation. However, to develop a Gulfwide perspective of deep-sea communities, sampling in areas beyond those thought to be 

potential areas for exploration has been included in the study design. A major enhancement in 

the program is the extension of the transects onto the abyssal plain of the central Gulf of Mexico 

through collaborative studies with Mexican scientists. This additional work effort will allow 

assessment of benthic communities structure and function throughout the basin by sampling the 

deepest habitats in the region. 

 The program is designed to gain a better ability to predict variations in the structure and 

function of animal assemblages in relation to water depth, geographic location, time and 

overlying water mass. Biological studies are integrated with measurements of physical and 

chemical hydrographic parameters, sediment geochemical properties and geological 

characteristics that are known to influence benthic community distributions and dynamics. Eight 

(8) hypotheses are being tested on the basis of measures of benthic community structure. It is 

hypothesized that community structure varies as a function of: 

1) water depth, 

2) geographic location (east vs. west), 

3) association with canyons, 

4) association with mid-slope basins, 

5) sea surface primary productivity, 

6) proximity to hydrocarbon seeps, 

7) time (seasonal and interannual scales), and 

8) association with the base of escarpments. 

 Measures of community structure used to test the hypotheses are variations in diversity, 

similarities in assemblage composition (at the species level), variations in biomass and 

abundance, and the mean size of individuals within specific size categories. 

 The underlying premise of the hypotheses to be tested is that deep-sea communities are 

food limited. This premise leads to the hypothesis that variations in community structure in time 
2 

and space are a function of the input of food to the seafloor. In other words, community 

dynamics and structure are dependent on the availability and quality of food resources. Corollary 

hypotheses test the possibility that each independent variable is related in some way to how 

organic matter from multiple potential sources is utilized by the benthic community. 

After defining community structure, the next set of objectives uses the information to 

infer the flux of organic carbon into and through the ecosystem. The conceptual model assumes 

that community structure and function are tightly coupled. Presently there is little reason to reject 

this generalization, but direct evidence for it in the deep-sea is at best fragmentary. 

 The conceptual model represents each of the principal size categories of the living 

components as standing stocks at each study site in the survey. The model includes demersal 

fishes, megafauna, scavengers, macrofauna, meiofauna, and heterotrophic bacteria. This model 

(Figure 1), of a sediment-associated food web, can be coupled with a model of fossil 

hydrocarbon utilization by chemoautotrophic organisms including large invertebrates that house 

endosymbionts. This linkage is yet to be explicitly established and is the basis for one of the 

hypotheses being tested. The boxes in the model represent standing stocks which have units of 

biomass (organic carbon per unit area) whereas the arrows represent flux between boxes and 

hence have units of organic carbon per unit area per unit time. For consistency, the units are mg 

C m-2 and mg C m-2 day-1. Data from the survey portion of the program quantifies standing 

stocks across the survey area. Respiration rates are estimated on the basis of organism size and 

temperature from established relationships in the published literature. The fluxes represent 

transfers between components and are calculated by difference to balance respiratory losses at 

steady state. Burial loss of carbon is organic carbon (detrital) concentration times sediment 

accumulation rate. Input to the bottom is assumed to be equal to the sum of the respiration and 

burial losses at steady state. 

 The second phase of the project is designed to test the model. Direct measurements will 

be made of fluxes on cruises that conduct process experiments at selected locations. The model 

is tested based on results from process experiments completed in June of 2001 and future process 

experiments to be performed in 2002. Total sediment community respiration is determined by 

benthic lander and incubation chambers. Total respiration is partitioned by measuring bacterial 

activity in pressure chamber incubations at in situ temperatures. Uptake and respiration are 

determined using mixed amino acids labeled with radiocarbon. Sulfate reduction rate are 

measured using radio-labeled sulfate incubation of sediment. Lander/chamber flux 

measurements include oxygen, dissolved inorganic carbon, inorganic nitrogen, phosphate, and 

silicate. Scavenger domains of occupation are estimated using baited traps, time-lapse cameras 

and an ADCP to calculate vertical and horizontal eddy mixing and mean current direction. Stable 

isotopes of carbon and nitrogen are used to determine the food chain’s structure and linkages. 

Physical and biological mixing are estimated using a suite of natural radionuclides characterized 

by an appropriate range of decay rates. Data from the second and third field year are used to 

adjust model parameters. The locations of the experimental sites were chosen based on model 

outputs, sampling results, and on-going testing of programmatic hypotheses. Experiments during 

the third field year are designed to further validate revised model rates and parameters. 

Additional sampling sites will be selected as needed to improve the resolution of the models and 

advance the testing of the hypotheses. 
3 

DEADFALLS RAIN OF POC

SARGASSUM

ADVECTED POC

CARCASSES SEDIMENT 

ORGANICS

FISH SCAVENGERS

HETEROTROPHIC 

MICROBIOTA

MEGAFAUNA

MEIOFAUNA

MACROFAUNA

SEEP FAUNA 

AND 

SYMBIONTS

CHEMOTROPHS

FOSSIL 

HYDROCARBONS

METHANE

SULFIDE

METHANE

? ?

Figure 1. A general model of a sediment-associated food-web. 
1-1 

1.0 INTRODUCTION

 The topography, geology, geophysics, currents, hydrography, chemistry and biota of the 

continental slope are much less well known than those of the continental shelf. The earliest 

information on the deep-sea biota of the Gulf of Mexico come from studies that used benthic 

trawling and photography (TerEco 1976, 1983). The largest study, The Northern Gulf of Mexico 

Continental Slope Study (NGOMCS), concentrated on geologic features, water circulation, 

chemistry, and biological communities (LGL and TAMU 1988). New scientific findings in the 

area, including chemosynthetic communities and a better understanding of the geological 

complexity of the region, have significantly altered our view of the GOM deep-sea (MacDonald 

1998; MacDonald et al. 1996). Rapid expansion of energy industry activities into the deep-sea 

has occurred over the past decade. It is expected that this trend will continue and that deep-sea 

regions of the GOM will be the site of energy exploration and development activities for decades 

to come. 

 An MMS workshop report on the deepwater GOM concluded that there was a need for 

additional information on the composition and structure of benthic communities, the associated 

biogeochemical processes, habitat heterogeneity and physiography, trophic interactions, and the 

biological “health” of the region (Carney 1998). The deep-sea is a setting within which benthic 

communities survive and propagate in the northern GOM. The deep-sea is characterized by total 

darkness, low temperature, nearly featureless mud, sparse food resources, predictable biomass 

patterns, unusual diversity patterns, and poorly defined couplings to topography, 

biogeochemistry, and currents. 

 The DGoMB program will provide a better understanding of: 

1) the present condition of biological communities in the study area, 

2) the distribution and patterns of deep-sea biota, 

3) the biological and physical processes that control the environmental setting, and 

4) the effects that these processes have on the character of benthic and benthopelagic 

communities. 

 The program emphasizes understanding the make-up and variability of soft-bottom 

biological communities with a secondary effort to characterize the important biological and 

abiotic processes that sustain or change the observed patterns. The study will: 

1) detail the composition and structure of slope biological communities, 

2) infer the relationship between these communities and local conditions and forcing 

factors, 

3) characterize the “health” and functioning of deep-sea communities, and 

4) compare and contrast the GOM region with similar oceanic basins. 

 The DGoMB program design was developed based on historical knowledge of deep-sea 

communities in the GOM. The interdisciplinary nature of the scientific objectives was 

recognized and the study design balances the benthic survey aspects of the program with 

experimental (or “process”) oriented studies needed to understand the deep-sea community’s 

structure and function. A careful analysis of previous information was used to focus the study on 
1-2 

the most relevant areas and those areas which will provide the greatest likelihood of establishing 

generalities about the structure and function of deep-sea benthic communities. The program will 

provide a predictive capability for areas not directly sampled or observed. This predictive 

capability is a framework for ascertaining the potential for, and the most likely impact from, 

fossil fuel exploration and exploitation in the deep-sea. 

 Each work element is nested in an integrated design that links data collection to a 

coherent spatial framework that provides maximum complementary information based on a 

detailed model of the system. Survey station results were used to choose experimental stations. 

Experimental stations will be a subset of reoccupied survey stations tightly linking all 

observations and data in space and time. Each measurement is taken to provide quantitative 

estimates of unknown elements of the model, to improve the quantitative accuracy of the model, 

and/or to test and refine the fundamental assumptions. 

 A review of previous studies, particularly the NGOMCS study provided valuable insights 

for designing the new study (LGL and TAMU 1988). The program design incorporated the 

following strategic conclusions: 

1. An equal sampling effort must be concentrated at different water 

depths to determine if “zones” exist. Site selection emphasized equally 

spaced depth intervals and replication at the treatment level (sites that are 

mostly similar except for depth) recognizing that gradients in ecosystem 

properties are more likely than “zones”. 

2. Depth dependence in community structure and composition must be 

evaluated in the context of other recently recognized confounding 

factors such as seafloor topography and currents. 

3. Sampling sites must be chosen based on characteristics believed to be 

important in establishing biological patterns such as detrital flux to the 

seafloor as influenced by near surface patterns of primary productivity. 

4. Proximity to the Mississippi River and Fan is an important spatial 

consideration. 

5. Benthic communities are nestled in different topographic and 

sedimentologic settings that are influenced by slope failure and varying 

inputs of terrigenous materials. 

6. Sampling sites must be selected to compare benthic communities 

associated with known physical features such as the thermohalocline, the 

oxygen minimum, and high current regimes. 

7. The program should be designed to provide flexibility and allow 

revision and rethinking of the underlying strategy and design on a 

regular basis in response to collection of new data and re-evaluation of 

historical data. 
1-3 

8. Temporal variations in community structure and composition are 

important and can be quantified by reoccupying historical sites and 

visiting a subset of sites during each of the three planned field seasons.

9. An improved understanding of community structure and composition 

requires better and more refined measurements of biomass for input 

into the conceptual model. 

10. Improved estimates of the megafaunal role in the ecosystem are 

important and include a three pronged approach to surveys: trawling (with 

improved quantitative methodologies), photosurveys, and baited traps. 

11. The number of sites sampled and the intensity of sampling must be 

increased over that of previous studies.

12. Replication and the size of the sample must be increased over that of 

previous studies to ensure that the total number of animals collected 

adequately samples the diversity of the communities being studied. 

13. The data must be meticulously managed so that it will be readily 

available for future reassessment as our understanding of the deep-sea 

evolves (this includes the use of standard and accepted methods in all 

aspects of the program and placement of data in a GIS framework). 

 The program receives added value by its close linkages with previous and on-going 

MMS efforts in the GOM. Many members of the Team participated in programs such as the deep 

water literature survey and review, the northeastern GOM hydrography and chemical 

oceanography program, the deep water physical oceanography re-analysis program, the 

Mississippi-Alabama pinnacles program, and chemosynthetic community studies (Table 1.1). 

The methods and approaches adopted for this program are the same, or compatible with, the 

methods of these other programs allowing for the integration of new results with the results of 

other programs in the final synthesis. This will produce a holistic evaluation of the GOM deepsea benthos and the linkages between abiotic and biotic processes that control complex 

ecological patterns in deep-sea benthos. 

1.1 Program Objectives 

 The structure and function of deep-sea benthic communities is the end-result of complex 

interactions between and among the biota and the topography, geology, currents, hydrography, 

chemistry, and physical setting. The NGOMCS study attempted to describe the geology, water 

circulation, chemistry, and biologic communities on the northern GOM continental slope regions 

(LGL and TAMU 1988). The current project builds on, improves, and supplements this study. A 

reassessment of continental slope ecosystems, in the context of intensive oil and gas exploration 

and exploitation in the region, is considered essential for the management and protection of 

biological resources in the deep-sea. 
1-4 

Table 1.1 Program Team - Key Personnel* 

Name Discipline Role Institution 

 

• Gilbert T. Rowe • Deep-sea Benthic 

Ecology 

• Project Manager • Texas A&M University 

 • Principal Scientist 

• Chief Scientist 

• Group Leader-Deep-sea 

Ecology 

• Mahlon C. Kennicutt II • Environmental • Deputy Program Manager • Texas A&M University 

 Chemist Contaminant Chemist 

• Gary A. Wolff • Data Management • Data Manager • Texas A&M University 

• Jody Deming • Microbiology • Co-PI Ecology • University of Washington 

• Paul Montagna • Benthic Ecologist • Co-PI Ecology • University of Texas 

 • Study Design 

• Richard Haedrich • Bottom Fishes • Co-PI Ecology • Memorial University 

• Megafauna • Data Analysis 

• Richard Heard • Macrofauna Taxonomy • Co-PI Ecology • University of Southern 

Mississippi 

• John Morse • Inorganic • Geochemistry • Texas A&M University 

 Geochemist Group Leader 

• William Bryant • Geological • Geology • Texas A&M University 

 Oceanographer Group Leader 

• Worth Nowlin • Physical • Oceanography • Texas A&M University 

 Oceanography Group Leader 

• Joan Bernhard • Foraminifera • University of South 

Carolina 

• Norman Guinasso • Physical Oceanography 

Field Program 

• Texas A&M University 

• Bob J. Presley • Metal Contaminants • Texas A&M University 

• Terry L. Wade • Organic Contaminants • Texas A&M University 

• Steven DiMarco • Physical Oceanography • Texas A&M University 

 

• Michael Rex • Community Structure • Science Review Board • University of 

Massachusetts-Boston 

• Kenneth L. Smith, Jr. • Community Dynamics • Science Review Board • Scripps Institution of 

Oceanography 

• William W. Schroeder • Gulf of Mexico Ecology • Science Review Board • Dauphin Island Marine 

Laboratory, University of 

Alabama 

*Does not include taxonomists. 

 The overarching goals of DGoMB are to: 

• determine in greater detail the composition and structure of slope bottom 

biological communities and to infer relationships between biological patterns 

and major controlling processes and 

• characterize the area as to its present “health” and function and compare and 

contrast the region with similar oceanic regions. 

 Specific DGoMB objectives are to: 

• improve the conceptual model that serves as the guide for the design and overall 

conduct of the study and to test specific hypotheses related to the models; 
1-5 

• compile and synthesize data from existing databases and on-going programs to 

interpret new results; 

• conduct field collections to describe the distribution and structure of benthic 

communities on the continental slope of the GOM and elucidate the functional 

interactions among them in known environmental settings; 

• characterize the hydrographic structure and measure the dissolved and 

particulate water column nutrient concentrations, primary productivity, and 

chlorophyll a at the study sites; 

• characterize the sediments at the study sites including grain size and 

hydrocarbon, metal, carbonate, and organic carbon concentrations; 

• characterize the basic attributes of the benthic microbiota and biomass at the 

study sites; 

• characterize the soft-bottom macro- and megafauna at the study sites; 

• relate variations in benthic biotic patterns to sedimentary processes and to the 

chemical and physical setting; 

• define basic levels of animal and bacterial activity and production and describe 

interactions between and among benthic biota, the several ecological/biological 

compartments, and the abiotic environment; and 

• compare and contrast the GOM benthic marine environment and communities 

with those in other basins of similar depth ranges and oceanic settings. 

 The program is to be conducted over a 48-month period of performance. Major 

oceanographic cruises are to be conducted, one in each of the first three years of the program. 

The final year of the program is dedicated to completing sample analyses begun in the first three 

years, data management and interpretation, model refinement, and production of the Synthesis 

Report. The field surveys will document the biota, the abiotic character of the slope and the 

important biotic and abiotic forcing factors. Study site selection criteria included consideration 

of anticipated zonation, water depth, distance from shore, abiotic variables, physiography and 

topography, geochemical environment, anthropogenic effects, and present and future leasing 

trends. 

1.2 The Program 

 The program consists of four tasks: 

 TASK 1 - Re-examination of Existing Data and Field Study Design 

 All available scientific records and databases have been identified, collected, and reexamined. Previous studies of particular importance are the TerEco Corporation synthesis (1976 
1-6 

and 1983), the MMS NGOMCS (LGL and TAMU 1988), and chemosynthetic ecosystem studies 

(MacDonald 1998 and MacDonald et al. 1996). Industry data, MMS leasing history and 

production data, USGS Gloria data, NODC data, governmental holdings of results of various 

MMS physical oceanography programs (LATEX, NEGOM Deepwater), and other information 

will be integrated with the new findings. These data formed the basis for final recommendation 

of study sites to the Contracting Officer Technical Representative (COTR) and the Scientific 

Review Board (SRB). Historical information was used to describe the study sites to justify how 

each site contributes to the overall program design and to verify important features of the 

conceptual model. 

 TASK 2 - Field Sampling 

 The R/V Gyre was and will be used to conduct all cruises. Conventional sampling 

methodologies are used for the community structure survey and innovative experimental 

approaches are used for process studies and experiments. Year II and III cruises sample those 

sites selected on the basis of information produced in Year I and II, respectively. The goal of the 

sampling program is to describe the benthic communities in distinct and identifiable settings in 

time and space. A phased-in approach concentrated the benthic survey portion of the work in 

Year I allowing ample time to process samples and analyze data. Year II and III provide infilling 

with additional survey stations based on programmatic results to better test hypotheses. 

Experimental stations address key questions related to processes and forcing factors and are 

sampled during cruises in years two and three of the program. Experimental stations have been 

chosen based on existing knowledge and Cruise I results. The experimental stations are a subset 

of survey stations providing for a close integration of all data collected. Water column sampling 

provides descriptive hydrography and water column chemistry (designed similar to the NEGOM 

program) at all sites. Seafloor sampling of sediments for benthic and benthopelagic fauna 

(designed similar to the GOOMEX program) is the main activity at the survey stations. Basic 

ecological processes such as microbial activity; sources and fates of nutrients and detrital 

material; feeding habits; the relative importance of feeding guilds and taxa; and the presence of 

potential contaminants are studied at experimental stations. A major modification of the field 

program has led to a revision of plans for field efforts in the third year of the project. 

 TASK 3 - Sample and Data Processing and Analysis 

 All samples and data are being processed as specified by contract. The quality of data and 

samples is ensured by a comprehensive data management plan (i.e., the Program Management 

Plan). Chain-of-custody and sample tracking activities guarantee the integrity and quality of the 

samples and data from shipboard collection to final synthesis. All parameters that can be 

reasonably measured onboard the ship (nutrients, salinity, oxygen, etc.) are measured using 

standard protocols. Sample and data processing include descriptive hydrography and water 

chemistry; sediment properties, chemical contaminants, and sediment geochemical properties; 

benthic microbiota, meiofauna, macrofauna, megafauna, and fishes; and measurements of basic 

ecological processes. Experimental stations studied in Years II and III were planned in 

consultation with the COTR and the SRB. 
1-7 

 TASK 4 - Data Interpretation, Synthesis and Reporting 

 Two (2) narrative Interim Reports and a Synthesis Report will have been produced. This 

report is the second interim report. The reports will contain an assessment of historic 

information, the data collected, descriptions of methods and analyses, interpretations of the 

analyzed information, and the results and discussions of the findings. Models will be refined and 

recast as warranted in light of new information. The present “health” of the area will be assessed. 

These reports contain appropriate charts, maps, or schematics that portray faunal and habitat 

variability and the major forcing factors related to community structure and function in the deepsea GOM as data becomes available. Topics to be covered in these reports include relevant 

historical information; the hydrography and oceanography of the region; the biological, 

chemical, geological, and physical processes and interactions in the water column and at the 

sediment-water interface; the effects of biotic and abiotic forcing factors on slope biota; 

concentrations and sources of hydrocarbon and metal contaminants in the area including an 

assessment of potential biological effects; and the likely effects of OCS petroleum exploration 

and development and other human activities on biotic resources in the study area. The COTR, 

CO, and SRB are kept informed of progress in the program by monthly status reports. 
2-1 

2.0 A CONCEPTUAL MODEL OF THE DEEP-SEA 

 A conceptual model of the deep-sea, its living and non-living components, has been 

constructed to represent the interacting stocks of organisms that make-up a typical benthic 

boundary layer community (Figure 2.1). A biological boundary layer is defined as approximately 

1 m deep into the sediments, extending up through the mixed layer of the water column to 

approximately 100 m above bottom. This biological boundary layer thus conforms to that 

previously used to describe the principal interacting components of a deep-sea benthic 

community (Smith 1992). This conceptual model has been drawn in software called STELLA II. 

The software allows flexibility in reformulating the structure and internal relationships within 

the system. The formulation presented is a modification of the model used by Smith (1992) and 

represents a deep-sea food chain. The modifications consist of defining every stock variable, 

living or non-living, as a “box” and every process, such as predation or respiration, as an 

“arrow”. Thus all interactions between the biota and the sources and sinks of organic matter are 

explicit either as “boxes” or “arrows”. On the other hand, “physical” processes are not explicitly 

represented. These implicit factors affect the “arrows” between the “boxes”. Each “box” has a 

“size” in terms of concentration, biomass or abundance that is the sum of the “arrows” entering 

the “box” minus the “arrows” leaving the “box”. At steady-state, each “box” does not change 

with time, and thus the inputs equal the outputs or losses. An important process, respiration, has 

been omitted in this conceptual food chain. Each stock can be taken separately in a submodel 

(Figure 2.2). Macrofaunal biomass, for example, is a function of what it consumes, what 

consumes it, respiration, and feces production. The contents of each stock can be expressed as a 

differential equation. The set of differential equations of all the stocks can be used to simulate 

the behavior of the entire food chain over time. The problem with doing this in the deep-sea is 

that data to quantify the stocks and processes are sparse at best. While considerable information 

exists on the stocks in a few locations and a few data exist on the rates of processes in others, the 

locations where both stocks and fluxes are known, even in the most minimal sense, are quite 

limited. One exception is a study of the central North Pacific, but even this study treated the 

sediment dwelling biota as one functional group due to a lack of detailed information on the 

foodweb (Smith 1992; Smith and Kaufmann 1999). 

 An advantage of this model is that with adequate data it can be used to simulate how the 

ecosystem will function under different conditions. Previously this approach has been used in an 

oligotrophic upper continental slope environment off eastern Greenland (Rowe et al. 1997). 

Boxcore standing stocks of the components represented were coupled with measures of 

community respiration (using a bottom lander with benthic chambers) and laboratory measures 

of bacterial activity to simulate the variations in biomass over time in response to a single 

seasonal pulse of organic matter related to a short ice-free period. In a purely hypothetical 

situation, the bioenhancement of infauna due to the disposal of organic rich material, such as 

sewage sludge or dredge spoils, was modeled, based on a simplified rendition of the Smith 

(1992) model (Rowe 1998). By adding organic matter in a pulse, the community “shifted up” to 

higher biomass and higher respiration and the alteration predicted by the model was validated by 

actual data at Deepwater Dumpsite 106 on the continental rise in the northwest Atlantic Ocean. 

This feature of “shifting” up or down in response to different input terms will be an important 

tool for interpreting the response of community structure and function in the deep-sea GOM in 

reaction to inputs from oil and gas exploration and production activities. The two most relevant 

inputs at platforms are organic enrichment due to a “reef” effect and the introduction of 
2-2 

contaminants. 
2-3 

CARCASSES

SEDIMENT ORGANICS

DISSOLVED ORGANICS

MICROBIOTA

MEIOFAUNA

CHEMOTROPHS

HIGH MOLECULAR WEIGHT HYDROCARBONS

MACROFAUNA

MEGAFAUNA

FISHES

Scavenging1

Deadfalls

Scavenging2

Predation3

Predation2

Deposit Feeding3

Deposit Feeding2

Bactivory3

Bactivory1

Assimilation1

Lysis & Dissimilation

Advected Organic Detritus

Deposit Feeding1

Bactivory2

Predation1

Chemotrophy

Seeps of HMWHC

Vertical Rain of POC

Figure 2.1. A conceptual model of the deep-sea Gulf of Mexico. 

= fluxes 

= standing stocks of the state variables 

= losses from and inputs to the system 

Key 
2-4 

Figure 2.2. The macrofauna submodel of a system carbon food chain model. 

2.1 Biotic Variables 

 The details of the conceptual model can be described as a number of biotic (living and 

non-living) and abiotic variables. In addition, the model is described in terms of various derived 

variables related to community structure and function. In-the-end, an understanding of the model 

components and their interactions are used to select the set of variables to be quantified that best 

describe the functioning of the system being studied. These inferences are then ground-truthed 

by in-the-field observations and the model is revised as needed. The biotic variables include the 

microbiota, meiofauna, macrofauna, megafauna, and fishes. These groups of biota make up the 

overall stocks of the system which are estimated through conventional quantitative sampling as 

described in Sections 6.0 and 7.0. 

Microbiota. The microbiota are the “bottom” of the food chain. Microbiota are 

represented by the bacteria and protists, including benthic foraminifera. Their principal food 

source is thought to be dissolved organic matter, although particulate material can be directly 

utilized if the biota can produce exoenzymes to mobilize particles. The protists can engulf and 

assimilate particulate material as well. The bacteria generally have a density of about 109

 per mL 

of wet sediment, measure about a micrometer in size, and can have very short turnover rates in 

the presence of reactive organic substrates. The protists can be much larger and occur in far 

MACROFAUN

A

Deposit Feeding

Bactivory

Predation on Meiofauna

Predation

Respiration

Feces

(see Key in Figure 2.1.) 
2-5 

fewer numbers than the bacteria. Protists are thought to be important components of ecosystems 

in areas of reduced oxygen. With the exception of the forams, microbiota have rarely been 

evaluated in the deep-sea. 

 Bacteria that are specially adapted to utilizing methane and sulfide are common in areas 

characterized by petroleum seeps (MacDonald et al. 1996; MacDonald 1998). Many of these are 

symbiotic, living in the tissues of large invertebrates. While these specialized associations are 

explicit in this model, they are presumed to be confined to “seep” areas. 

 Foraminifera are shelled protozoans. Foraminfera are large, often the size of metazoan 

meiofauna. Few studies have compared foraminiferal biomass to other benthos in the deep-sea, 

but biomass can exceed the meiofauna (Coull et al. 1977) and abundances commonly exceed the 

meiofauna plus the macrofauna (Snider et al. 1984; Gooday 1986). Although little is known 

regarding foraminiferal energetics, it has been shown that foraminiferal metabolism is markedly 

increased by organic enrichment (Linke 1992). Therefore, accurate deep-sea carbon and energy 

budgets should include the foraminifera. 

Meiofauna. In this model, meiofauna are defined as metazoans that are retained on a 63 

micron sieve. Meiofauna include nematode worms, harpacticoid copepods, and several other 

taxa. In some studies benthic forams are also included, but in this model, forams are considered 

part of the microbiota because they are single-celled organisms, rather than metazoans. Most 

meiofauna feed on small particles consisting of detritus, bacteria, other meiofauna, and small 

protozoa such as ciliates and flagellates. Turnover rates for meiofauna can be as short as a few 

days when temperatures are high and food is plentiful. No reliable generalizations can be made 

about their turnover times or growth rates in the deep-sea, but it is assumed that both are 

substantially slower than in shallow water due to food limitation and cold water temperatures. In 

shallow waters meiofauna biomass is less than that of the macrofauna, but in the deep-sea this 

appears to be reversed. 

 The finding that meiofauna biomass is higher than macrofauna biomass in the northern 

GOM (Pequegnat et al. 1990) indicates that meiofauna may be responsible for much of the 

organic matter metabolism in deep-sea sediments. Therefore, a survey of meiofauna community 

density and biomass is needed to characterize this energetically important group. In shallow 

coastal systems, meiofauna remove bacteria at a rate that equals sediment bacterial production 

(Montagna 1995). This indicates meiofauna are most likely responsible for maintaining bacterial 

populations in log-phase growth cycles and are therefore indirectly responsible for maintaining 

rates of nutrient recycling. Despite the apparent importance of meiofauna in deep-sea energetics, 

there is no knowledge of the rates at which these processes occur. Therefore, process studies are 

needed to assess meiofaunal consumption rates. Techniques to measure meiofaunal bacterial 

feeding rates on bacteria have only been used in shallow water (Montagna 1995). 

Macrofauna. Macrofauna, in this model, are the invertebrates retained on a 300 micron 

sieve. The principal organisms are polychaete worms (≈50%), bivalve molluscs, and crustaceans 

in the groups Isopoda, Amphipoda, and Tanaidacea. The production to biomass ratio of the 

macrofauna in shallow water communities is often assumed to be unity, but this can vary widely. 

In the deep-sea, it is assumed the ratio is much lower but there is little evidence for this one way 

or the other. Biomass and densities decline sharply with depth in most ocean basins. Macrofauna 
2-6 

consume microbiota, meiofauna and organic detritus. Macrofauna are preyed upon by megafauna 

and fishes. 

Megafauna. The megafauna are organisms that are routinely sampled by trawls with 2.5 

cm stretch mesh or organisms that can be seen easily in bottom photographs, usually about 1 cm 

or so in diameter. They are composed for the most part of decapod crustaceans and echinoderms. 

Cnidaria, such as sea pens, soft corals and anemones, are also common in the megafauna. 

Megafauna can be suspension feeders, predators, scavengers or deposit feeders. For the purpose 

of the model, the swimming scavengers that consume carcasses, such as the large amphipod 

Eurythenes gryllus, are included in this group. Megafauna have been extensively observed with 

photographic techniques. 

Fishes. Demersal fishes are defined as those species that live on or near the bottom. 

Fishes are both predators and feed on dead falls, megafauna and macrofauna. 

2.2 Community Structure 

 Community structure, in the context of this model, has two interpretations. It is 

represented explicitly in the conceptual model as the standing stocks of the living components of 

the ecosystem as discussed above, and as such it represents the relative and absolute importance 

of the stocks in terms of biomass and rates of processes in the model. Secondly, community 

structure refers to the parameters that quantify the living stocks, as described below. 

Biomass. A measure of the standing stock in some currency of mass per unit area of 

seabottom is biomass. Wet weight is a common measure. It can also be measured as dry weight, 

ash-free dry weight or carbon. The model currency is carbon, so the ideal measure is in terms of 

carbon. Biomass tends to be inversely related to depth, in a log-normal fashion. Within the entire 

community, the highest biomasses are found in the total bacterial counts, both in shallow and 

deep water. All the size fractions in the deep-sea have biomass values that are somewhat lower 

that 1 g C/m2

. In shallow water, each fraction can have biomasses of 10's of g C/m2 in unusually 

fertile conditions. This is not expected in the deep-sea. 

Abundances. A surrogate for biomass, that is often measured in ecosystem studies, is 

animal abundance or density. However, mean sizes can vary. In the GOM, mean size seems to 

decrease with depth. Common abundances for the organismal groups in the model are bacteria, 

109

/mL wet sed.; meiofauna, 0.25 to 1.5 x 106/m2; macrofauna, 102 to 104/m2; megafauna and 

fishes, several hundred to a thousand per hectare. The abundances of each group are 

hypothesized to be a function of the input of carbon and energy to the stock. If the relationship of 

numbers to biomass is known, these abundances can be used in the model. The NGOMCS 

studies used conversion factors from the studies of Rowe (1971) to calculate biomass from 

densities. 

Diversity. Measurements of the numbers of different species are expressed as diversity 

values. Diversity has been assessed on macrofauna, megafauna, and fishes. Diversity indices 

attempt to lessen the effects of sample size, to aid comparisons between regions of differing 

animal densities. Common indices of diversity are Sanders Rarefaction, Hurlburt's expected 

species number and the information function H'(s). The GOM appears to be somewhat different 
2-7 

from large ocean basins in that maximum diversity is not found on the deep slope or upper rise, 

but rather on the upper slope or outer shelf. Thus it is similar to other isolated “mediterranean” 

basins where diversity declines with depth down the slope. It is expected that intense inputs of 

organic matter will decrease diversity due to competitive exclusion. Diversity is not calculated 

by the model. 

Zonation. The degree to which individual species and groups of species are isolated 

across isobaths (zonation), between geographic regions, or any other physico-chemical gradient 

is referred to as zonation. Zonation by groups of species as a function of depth has been 

measured by “rates of species change” across depth intervals or measures of percent similarity 

between depths. These can be measured on meiofauna, macrofauna, megafauna, and fishes. 

Groups of species appear to occur in zones, but considerable overlap has been observed as well, 

with few distinct, immutable boundaries. On the other hand, some individual species of 

megafauna tend to have a shallow water boundary that is sharp and severe and a deeper water 

boundary that is a slow decline in numbers with depth. Zonation down slope is hypothesized to 

be a function of competition along a gradient of declining food supplies. Zonation is not 

calculated by the model but can be addressed through hypothesis testing. 

2.3 Community Function

 The processes, or arrows, in the model encompass a wide range of interactions amongst 

the model’s components. 

Microbial activity. The respiration and the assimilation of organic substrates by the 

microbiota are dependent on inputs of organic matter and temperature. In the model this can be 

either sedimenting POC or hydrocarbons. The sedimenting POC can be derived from several 

sources, as indicated above. A basic assumption is that, in general, smaller organisms are 

consumed by larger organisms because it is more energy efficient. If the organic matter is 

reactive, the food web will compete for the organic matter. If the organic matter is highly 

refractory then it is assumed that a food chain will dominate in which the bacteria remobilize the 

organics in order to make it available to metazoans. Predation is represented as arrows between 

the living components of the model as indicated. It is assumed that large organisms will 

preferentially take large prey rather than small prey because it is more energy efficient. 

Macrofauna are assumed to be deposit feeders. Heterotrophic bacteria are assumed to consume 

sediment organic matter. Scavengers consume carcasses and are included in the megafauna. 

Fishes consume megafauna and carcasses. Respiration is one of the most important measures for 

each organismal group because it dominates the carbon cycle. However, respiration is not 

explicit in the conceptual model. Most carbon that is consumed (50 to 90%) is recycled to 

metabolic carbon dioxide. Respiration is estimated from animal size and temperature for the 

larger organisms based on literature values. 

Growth, reproduction and recruitment. The rates of growth, reproduction, and 

recruitment are poorly known in deep-sea organisms. The model can calculate growth by 

fundamental or size group. Reproduction and recruitment are not well known. It is assumed that 

growth, reproduction and recruitment can be seasonal in some species but this kind of 

information for the GOM slope is inferential at best. It should be noted that in the NGOMCS 

study’s central transect, it did appear that there were about 1.5 times as many macrofauna 
2-8 

individuals on the upper slope in the spring than in other sampling periods, suggesting that some 

type of growth, reproduction, and/or recruitment had occurred, but the mechanism that gave rise 

to this observation is unclear. 

2.4 Geochemistry

 Non-living model variables include the “fuel” for the system and those processes that 

supply carbon and energy to the ecosystem. Inputs of carbon are critical to the functioning of the 

ecosystem and are often present in limiting amounts in the deep-sea. On the GOM slope, labile 

organic matter is transported to the communities from primary productivity (either directly 

settling to the site or being laterally advected), fossil sources of carbon (oil and gas to support 

chemosynthesis), and potentially from large animal carcasses and sinking Sargassum. 

 Sedimentary organic matter includes a suite of natural organic compounds found in deepsea sediments. Organic matter is derived mostly from the slow rain of particulate organic matter 

(POM) originating from dead cells, crustacean molts, and fecal pellets produced by plankton in 

the overlying photic zone. Some POM sinks very slowly but aggregates and pellets can rapidly 

reach the seafloor. The composition of organic matter that reaches the sediment is largely 

unreactive and poorly characterized. POM is extensively reworked in the water column either 

being remineralized or transformed to dissolved organic matter (DOM). The amount of POM 

that reaches the sediment, its ultimate repository, is affected by many factors but, in particular, 

the water depth. POM concentrations in the sediments of the deep-sea are low. Relatively 

refractory terrigenous-sourced organic matter is an increased percentage of the POM close to 

shore and river discharge points. POM is usually inversely proportional to grain size, but does 

not correlate well with the biomass of the living components. In spite of its meager reactivity, it 

is assumed to be the basis of the deep-sea food chain except at hydrocarbon seep sites. 

 Three sources of sediment organic matter are possible in the deep-sea and two are 

explicit in the model: vertical transport from the photic zone and lateral export from the 

continental margin. The third source is slumping of material from organic matter-rich areas upslope and its importance is unknown. 

 The discovery of chemosynthetic communities with large megafaunal communities 

dependent, through their symbionts, on methane and sulfide derived from natural seeps has 

highlighted a non-photosynthetic source of carbon and energy for deep-sea GOM organisms. 

Hydrocarbons migrate to near-surface sediments from deep subsurface reservoirs of oil and gas. 

The hydrocarbons can then serve as substrates for communities of organisms adapted to methane 

and sulfide utilization. “Seeps” support high biomass but its influence on biota outside of the 

immediate vicinity of the seeps is largely unknown. Recent chemical evidence indicates that the 

biogeochemical influences of seeps in sediments tend to be localized (John Morse, pers. comm.). 

The oil and gas is often degraded by bacteria inducing anoxic conditions in the adjacent 

sediments producing sulfidic environments. 

 A poorly quantified input of organics to the deep-sea are falls of carcasses that die or are 

killed in the water column, usually near the surface. Carcasses can range in size from a few 

centimeters to a whale of several tons. The relative importance of this source of organic matter is 

not well established. It is known that scavengers exist that can take advantage of such sources, if 
2-9 

and when they are available. Similarly, Sargassum, Thallasia, wood, etc. has been observed on 

the bottom as well. 

 There are a range of abiotic variables that have been shown to influence biotic patterns in 

marine environments. One type are those related to the physical texture of the sediment and 

include properties such as grain size, permeability, porosity, and organic and inorganic carbon 

content. As the substrate that supports the benthos, variations in these physical properties are 

important in understanding biotic patterns. In addition, it is known that influxes of organic matter 

and contaminants can cause changes in community structure and abundance. Introductions of 

labile carbon will cause opportunistic animals to flourish and others to do less well. Organic 

matter enhancement also leads to anoxic conditions that produce a range of toxic chemicals such 

as sulfides. Organisms are also known to be selectively sensitive to chemical contamination from 

hydrocarbons and trace metals. Some animals can tolerate exposure better than others causing 

shifts in populations when communities are exposed to pollution. In addition, hydrocarbons, 

particularly aliphatics can be metabolized by microbes and may actually enhance sedimentary 

microbial populations rather than exert a toxic effect, though as mentioned above, oxygen and 

sulfate consumption can produce toxic chemicals. 

 Explicit in the model is microbial biomass but functional groups of bacteria are not 

defined. All of the bacteria and protists are assumed to be heterotrophs, as opposed to possible 

chemoautotrophs in the “chemotrophs” stock. However, the terminal electron acceptors 

(oxidants) of heterotrophs can differ. In the oligotrophic central gyre areas of the deep-sea where 

sediments are oxic, all the bacteria are assumed to be aerobes. In sediments on continental 

margins, this is probably not true. Below the sediment-seawater interface the functional bacterial 

groups are defined by the terminal electron acceptor (TEA) they use (Figure 3.3). Few 

comparisons of the importance of the different TEA's (oxidants) have been made, but in rapidly 

accumulating sediments near the Mississippi delta, oxygen and sulfate were of equal importance. 

However, as oxygen declined and became limiting, sulfate reduction dominated heterotrophic 

metabolism (Rowe et al. in press). These processes are measured by examination of the 

porewater chemistry with depth in the sediment. These processes are important in situations 

where organic loading depletes oxygen in surficial sediments, thus forcing deeper living 

bacterial assemblages to depend on other oxidants. As the loading continues, the utilization of 

these other TEA's increases in intensity and rises up closer and closer to the sediment water 

interface. Profiles of TEA's are good indicators of organic loading to the sediment community.

Ammonium is a principal excretory product of invertebrates and bacteria. The ammonium 

produced by the benthic community can be oxidized to nitrate by nitrifying chemoautotrophs, 

but it can then be used, along with nitrate diffusing in from the bottom water, as a metabolic 

oxidant. This can be measured with benthic chamber incubations and sediment pore water 

profiles of ammonium and nitrate. The importance of this process can be significant relative to 

oxygen consumption. Oxidized metals can also be used as oxidants. Comparisons with other 

oxidants is limited, but in some situations this process is thought to be important. In sediments 

containing even modest amounts of reactive organic compounds, sulfate reduction can become 

the dominant respiratory process, even greater than oxygen. This is because sulfate is the fourth 

most abundant ion in seawater, having a concentration that is 140 times that of oxygen at 

saturation. Lin and Morse (1991) have made a series of cross slope transects around the GOM in 

which they derived 
2-10 

Figure 2.3. Sediment submodel of functional bacterial groups as defined by utilization of 

different terminal electron acceptors. 

integrated sulfate reduction rates down core. Highest rates were near the Mississippi River. 

Lowest rates were in oligotrophic areas of the southern GOM. Methane can be produced as a 

breakdown product of metabolism of large carbon compounds and it can be formed when carbon 

dioxide is used as the oxidant. Methane can then be used as an energy source by bacteria. This 

methanotrophy occurs in methane seeps near hydrocarbon seeps. Therefore, characterization of 

the geochemical properties at a location is important for ascertaining the basic metabolic 

processes that are important to the base of the food chain. Significant alteration of the inputs to 

the system, in particular carbon, can result in large shifts in bacterial populations and metabolic 

strategies. In addition, the rate of sediment accumulation and the intensity of bioturbation 

DETRITAL ORGANICS

POC Input

Burial

MACROFAUNA

MEIOFAUNA

CHEMOTROPHS

Mn REDUCERS

Fe REDUCERS

SRBS

Deposit Feeding1

Deposit Feeding2

AEROBIC BACTERIA

Assimilation3

Assimilation4

Assimilation6

Predation

DIC

CaCO3

Shell Burial

Aerobic Respiration1

Aerobic Respiration2

Chemosynthesis

Sulfate Reduc tion

Fe Reduc tion

Mn Reduc tion

Dissolution

DIC Loss

DENITRIFIERS

Aerobic Respiration3

Denitrific ation

Assimilation1

Bac tivory

Prod uc tion

Assimilation2

(see Key in Figure 2.1.) (SRBS=Sulfate Reducing Bacterias) 
2-11 

(mixing) are important in establishing the sediment redox conditions and provide insight into the 

reactivity of sedimentary organic matter. 

2.5 The Water Column 

 The currents in the overlying water column are important when considering biotic 

patterns. Near-bottom currents are in part responsible for establishing the sediment properties by 

transport to the site and also winnowing/erosion of sediments. The water column is also the 

media through which the overlying primary productivity is transported to the sediment. The 

currents serve as a mechanism for transport of larvae and juveniles throughout the system. So 

any model of the deep-sea must take into account the dynamic nature of the physical 

oceanography and the hydrography of the water masses that overlie and interface with seabottom 

habitats. 

2.6 Community “Health”

 While widely discussed, the concept of ecosystem “health” remains elusive. Due to the 

complex nature of natural ecosystems an overall assessment of health is difficult to define. 

Specific portions of an ecosystem can be characterized by parasite infestation, pathologies, 

reproductive success, demographics (age distribution), and the presence of measurable responses 

to stress (such as stress proteins and the inducement of P450 detoxification enzymes) to name 

just a few potential indicators of “health”. However, a mechanism or approach to provide an 

overall integrated assessment of the community “health” has yet to be agreed to. For example, in 

the past it was thought that simple increases in biomass were positive for a group of organisms, 

but now it is recognized that these biomass increases can be accompanied by significant changes 

in community structure. Is this positive or negative for the community and is the community 

“healthy”? Acute deterioration of a community, such as massive mortalities or disappearance of 

species, is easily recognizable, but over longer time frames it has become clear that some of the 

more intractable issues related to sublethal effects are often difficult to quantify or even 

recognize in the early stages of change. For example, loss of biodiversity is seen as a 

deterioration in ecosystem health, but the natural processes that also effect biodiversity are not 

well understood. 

 Ecosystem “health” may be measured by such things as community structure, e.g., the 

classic view that a healthy benthic community is one of high diversity and high productivity. 

Therefore, unhealthy ecosystems share a number of properties - lessened productivity, declining 

biodiversity, dominance by lower trophic levels and others. It has also been suggested that 

systems degraded beyond a certain point cannot recover (Rapport and Whitford 1999; Rapport 

et. al. 1998; Rowe and Haedrich 1979; Haedrich et al. 1980; Haedrich and Maunder 1985; 

Snelgrove and Haedrich 1985; Haedrich and Merrett 1988; Merrett and Haedrich 1997). 

Therefore “health” can be inferred from community composition, abundances, and size 

frequencies. “Health” will be assessed by comparisons of the structure of similar ecosystems 

world-wide that have been subjected to varying degrees and types of disturbance. 

 At the individual level, “health” has been inferred from physiological responses such as 

disease incidence, size and condition, and reproductive state. Parasites, and the diseases they 

cause, are often important determinants of population health. Measurable effects include 
2-12 

mortality, decreased reproductive effort, decreased condition, and reduced or aberrant growth. 

The outgrowth of these effects are increased morbidity, decreased fecundity and even effects on 

predator/prey relationships. 

 From another point of view, “health” may be a measure of response to the stresses a 

population experiences due to anthropogenic disturbances. As a first order indication of this 

exposure, inventories of chemicals in sediments and biological tissues are measured. While this 

is at least an indication that the potential for impact is present, simply documenting the presence 

of contaminants is not sufficient to infer biological effect in most instances. However, a range of 

biological effects criteria for sedimentary concentrations of contaminants have been used to infer 

the possibility of effects. Once the potential for exposure has been verified, first-order biological 

responses to contaminant exposure are often important variables to monitor. These include a 

range of responses including production of contaminant metabolites, the induction of 

detoxification enzyme systems, and molecular level indications of genetic damage, to name a 

few indicators of sublethal biological response to contaminant exposure. 
3-1 

3.0 PROGRAM DESIGN 

 The design of the sampling program involved a series of steps that relied on basic design 

principles, a thorough knowledge of the current understanding of the system to be observed, 

formulation of working hypotheses, application of appropriate statistical analyses (both 

univariate and multivariate), linkage of findings with model revision and update, and an 

objective approach to evaluate the utility of data being collected as the program acquires new 

data. Taking these issues into account, the program design includes those factors believed to be 

most important in characterizing the biological communities. Testable null hypotheses were 

formulated and the appropriate temporal and spatial scales and locations for sampling were 

chosen. All of these elements are essential for a full integration of the diverse interdisciplinary 

measurement program being undertaken. 

3.1 General Design Considerations

 Several general principles guided the development of the overall sampling plan. 

 First, treatments, or in this case similar stations, were chosen that will falsify the null 

hypothesis. That is, contrasts that don’t delineate differences were avoided as unproductive. Due 

to resource limitations and the large geographic area to be studied, it is impossible to measure 

everything, everywhere. However, it is relevant to measure what are judged to be the most 

important variables at the most important sites. 

 Second, pseudoreplication was avoided, i.e., replication is at the treatment level. A 

treatment is a factor level, or combination of factor levels, applied to a sampling unit. Sampling 

units are stations or replicate samples within stations where all other variables but the variable to 

be tested are as similar as possible. The generic form of all null hypotheses is that the treatment 

level effect equals zero, i.e., the stations themselves are not fundamentally different by other than 

the variable being tested. For example, if each treatment is only represented by a single station, 

then in the end you only know that the stations are different, not why the stations are different. 

 Third, station locations were optimized to test more than one hypothesis. This is a cost 

reduction technique. For example, stations along a transect to test for depth differences can be 

paired with stations in specific habitats to test a second hypothesis. 

 Fourth, confounding factors were minimized. A common problem is that more than one 

variable is changing at a given station. For example, two stations could differ by water depth, 

distance from shore, and distance from the Mississippi River. In the end, you don’t know which 

variable (or if an interaction of the variables) is causing the observed differences and thus 

generalities are difficult, if not impossible, to discern. Therefore, stations are chosen where 

comparisons can be based on differences in a single or related set of variables. 

 Fifth, balanced sampling designs were used. An uneven distribution of sampling effort 

causes distortion of sample means when there is a difference in the number of observations 

between the datasets being contrasted. 
3-2 

 Sixth, a design of appropriate power was used. Power is the ability to detect change. The 

first five design considerations primarily protect at the α level against Type I errors (rejecting 

the null hypothesis when it is true). But, type II errors protected at the β level must also be 

considered (accepting the null hypothesis when it is false). Replication must be sufficient to 

detect the amount of change that is expected given variations in the variable of interest. A large 

multi-factorial design with little replication has many interactions terms that are often 

significant, thus limiting the interpretation and robustness of tests for the most important effects. 

In this case, previous studies suggest that a minimum of five replicate boxcores were needed at 

each station to adequately sample within-station heterogeneity. 

 Finally, there will be a meta-analysis (or synthesis) in the end. Most programs measure 

values for hundreds of dependent variables at hundreds of observational points (be they spatial, 

temporal, or random replicates). When assembled in its entirety, this meta-data set contains 

information that does not exist within the individual analyses. In-the-end, all of the stations and 

replicates are only surrogates for the environmental factors that regulate biological processes 

leading to the observed patterns of faunal composition. Therefore, measurements are made 

synoptically at locations or subsamples (replicates) are taken within a location so that a metadata set can be created for the synthesis and integration of the overall study results. 

3.2 Working Hypotheses and Station Selection 

 A sampling design is most effectively developed from a series of testable null 

hypotheses. The hypotheses are derived from the conceptual model which describes the current 

understanding of the system being observed (i.e., deep-sea communities). Hypotheses are then 

used to select stations so that the hypotheses are testable with sufficient power to detect 

differences in the dependent variables being measured (i.e., abundance, biomass, diversity, 

analyte concentrations, etc.). The null hypotheses were based on the current understanding of 

deep-sea benthic community structure and function and knowledge of the types of habitats that 

occur in the GOM. 

 The following characteristics are judged to represent a significant portion of the deep-sea 

GOM habitat and will be used to identify one area as being different from another: 

1) water depth (transects perpendicular to isobaths); 

2) geographic location - juxtaposition to the Mississippi River (east-west transects) and 

distance from shore; 

3) physiographic position - in a basin, in a canyon, on an escarpment, and in a low relief 

area; 

4) influx of organic carbon - primary productivity derived carbon, petroleum seep and 

chemosynthetic derived carbon; 

5) energy level of the physical environment - high versus low bottom current velocity, 

juxtaposition to semi-permanent physical features (nitrocline, thermohalocline); 

6) temporal changes -time series sampling; and 

7) location of historical sampling sites. 

 The sampling design tests hypotheses rather than simply conducting a traditional 

geographic survey with closely spaced stations. This approach was adopted to establish 
3-3 

generalities about communities in the study area and because the area to be covered is so large 

that sampling everywhere is cost prohibitive. The hypothesis testing allows a prediction of when 

and where particular types of communities, both in terms of structure and function, will or will 

not be encountered. Hypothesis testing provides a powerful tool for either increasing or limiting 

sampling intensity in time and space as new data is collected and historical data is re-interpreted. 

Each hypothesis, as described below, explores mechanisms believed to explain much of the 

variation in community structure and function in the deep-sea GOM. Some mechanisms are well 

established, others are not. 

 Based on the above considerations the following kinds of contrasting environments or 

habitats were sampled for comparisons: 

• Depth. 

- Water depth is probably the single most important gradient in determining 

faunal compositions and forcing factors in the study area (Hypothesis 

HO1). Comparisons were made along a series of transects. Stations: RW1-

RW6, W1-W6, C1-C12, MT1-MT6, S35-S44 (see Figures 3.1-3.3). 

• Nutrients (organics) 

- The input of organic nutrients from Mississippi River discharge causes an 

east to west gradient in faunal compositions and forcing factors 

(Hypothesis HO2). Comparisons were made along isobaths at similar 

distances from shore at varying distances from the Mississippi River. 

Stations: RW1-RW6, C1-C12, S37-S42 (see Figures 3.1-3.3). 

• Basins. 

- The common mesoscale basins found on the slope, unless influenced by 

seeps, have the same faunal compositions and forcing factors as the 

“normal” slope because the entire slope is draped in a similar Holocene 

“blanket” of silt and clay within which the biological communities live 

(Hypothesis HO3). Comparisons were made within and outside of basins at 

comparable water depths and distances from the Mississippi River and 

shore. Stations: WC12, B1-B3, NB2-NB5 (see Figures 3.3 and 3.4).

• Canyons. 

- Faunal compositions and forcing factors are the same in or out of submarine 

canyons (Hypothesis HO4). Comparisons were made between stations within 

and outside of canyons at comparable depths and distances from the 

Mississippi River and shore. Stations: MT1-MT6, W5, W6, RW6 (see 

Figures 3.1-3.4). 
3-4 

Figure 3.1. Benthic survey stations in the northwestern GOM (for regional context see Figure 

4.1). 
3-5 

Figure 3.2. Benthic survey stations across the Florida Escarpment (for regional context see 

Figure 4.1). 

N 
3-6 

Figure 3.3. Benthic stations along the Mississippi Trough (MT1-MT6). Historical sites from the 

NGOMCS study are also included (C1-C14; for regional context see Figure 4.1). 
3-7 

Figure 3.4. Physiographic settings for benthic survey stations in the Central GOM. Historical 

stations from the NGOMCS study are also included (W1-W6, WC-5, and WC-12; 

for regional context see Figure 4.1). 
3-8 

• Steep Escarpments. 

- Faunal compositions and forcing factors are the same on the “normal” 

slope as they are at the base of the Sigsbee Escarpment (Hypothesis HO5). 

Comparisons were made between stations on the slope and at the base of 

the Sigsbee escarpment at similar water depths. Stations: S39-S42 (see 

Figure 3.2). 

• Productivity. 

- Cyclonic and anticyclonic features in the surface waters consistently alter 

surface primary productivity and this results in differing seafloor fauna 

compositions and forcing factors (Hypothesis HO6). Comparisons were 

made between stations that underlie areas of historically documented 

differences in sea surface primary productivity, holding other variables as 

constant as possible. Stations: RW1-RW6, S35-S36 (see Figures 3.1 and 

3.2). 

• Hydrocarbon Seeps. 

- Hydrocarbon seeps have a major effect on energy and carbon supplies 

contributing to different faunal compositions and forcing factors 

(Hypothesis HO7). This is tacitly true since chemosynthetic fauna are 

restricted to seep sites. Rather than a direct test, inputs of chemosynthetic 

carbon to the foodweb will be recognized by stable isotopic tracer studies. 

Data produced from the chemosynthetic community studies will also be 

contrasted with equivalent non-seep data. Explicit testing by paired 

stations will not be attempted. Questions of “how close is close” are still 

difficult to resolve even in studies concentrated at seep sites. The decision 

to address this question in a limited way is in recognition of the fact that 

the MMS is already supporting extensive studies at seep sites and that the 

primary focus of this program is non-seep environments. 

• Temporal Changes. 

- Standing crops of benthic fauna vary with time (Hypothesis HO8). 

Comparisons were made at a subset of survey stations sampled during 

each of the three planned cruise activities. In addition, to provide a longer 

timeframe for comparisons, historically sampled sites will be reoccupied. 

The intercomparibility of data between studies will be explicitly addressed 

to ensure whether inter- program comparisons are valid. Stations: W1-

W6, WC6, C1-C12 (see Figures 3.3 and 3.4). 
3-9 

 The above comparisons have been translated into testable null hypotheses (Table 3.1). A 

critically important part of program design is selection of the most appropriate locations to 

conduct the measurement program to test the hypotheses. This is especially true for this program 

because the area to be characterized is large, the area contains a wide range of habitats and there 

are several important forcing factors that tend to confound delineation of cause and effect 

relationships. As summarized in the introductory materials, the northern GOM represents one of 

the most complex geological and oceanographic settings in the world. The challenge is to 

classify wide stretches of the slope into recognizable subregions that can then be sampled to test 

if the extant biological communities are different from area to area. Additional factors explicitly 

considered during the selection of proposed sampling sites include the location of historical 

sampling (to extend time series observations), the current and future trends in energy resource 

exploration and exploitation, and possible anthropogenic effects related to proximity to existing 

production facilities (primarily accommodated by screening all locations for contaminants). The 

study stations are explicitly tied to the hypothesis testing as listed above. 

 Survey stations were chosen to sample the broadest possible range of conditions at depths 

between 300 m and 3000 m and within the EEZ boundary with Mexico (Figures 3.1-3.4). The 

site selection spans the range of known conditions providing the best tests of the hypotheses 

posed. Thus, sampling occurs along a transect just north of the Mexican border (RW1-RW6) 

over to one transect across the Florida escarpment (S37-S42; see Figures 3.1-3.2). This inclusive 

range of conditions enables us to gain an understanding of the whole GOM deep-sea benthos, 

rather than isolated parts. The smooth upper slope of the northern Florida slope is contrasted 

with the heterogeneous topography off Texas. A transect down the Mississippi Trough (MT1-

MT6) provides a sampling of the effect of particulate and nutrient input from a large river 

(Figure 3.3). The basins on the upper slope can be categorized according to their structure and 

how they were formed, testing whether or not physiographic setting affects the biota (WC12, B1-

B3, NB2-NB5; see Figure 3.4). Two locations at the upper end of the DeSoto Canyon (S36, S35) 

were chosen because one is frequented by whales and the other is characterized by high nitrate 

concentrations semi-permanently in the euphotic zone (see Figure 3.2). 

 Experimental, or “process” stations, were chosen to reflect the greatest range in 

community dynamics, as inferred from the benthic survey data. The survey site selection was 

based on inferences about where the greatest variations in community structure will be observed 

based on the model. The next step was to place the experimental stations where the greatest 

ranges in community structure are actually observed during the study. For example, a 

comparison of places with high and low total biomass is important. Observations of processes, 

such as sulfate reduction or aerobic community respiration, provide comparison of sites where 

biogeochemical cycling rates are different. Potential sites at mid-depths in the Mississippi 

Trough (C14, C12) are believed to experience high velocity current events below the Sigsbee 

Escarpment (Figure 3.4). The central line of the earlier slope study (C1, C7, C4, C14, C12) 

appears to be characterized by a seasonal signal in the biotic community (see Figure 3.3). If the 

statistical tests suggest that slope basins contain enhanced biomass, then rates of metabolic 

processes are expected to be enhanced as well making a basin a candidate for an experimental 

site. Experiments designed to determine the causes of bioenhancement were considered to be 

important. The location of experimental stations allowed the community structure documented 

during the survey, to guide site selection in the context of historical data. The type and placement 

of experimental stations was carefully considered in consultation with the COTR and the SRB. 
3-10 

Table 3.1. Summary of benthic survey experimental design: null hypotheses, station selection 

criteria, number of stations, and number of samples. (The number of samples is based 

on five replicates per station.) 

Null Hypotheses Design Criteria No. 

Stations 

No. 

Samples 

 

HO1: Variation in benthic fauna is 

explained by depth 

3 Replicate transects over 7 depths; 

occupy historical stations and others 

21 105 

HO2: Faunas exhibit an East to West 

gradient 

Additional transect to HO1; remove 

confounding geological effects and 

water mass effects 

7 35 

HO3: Basin faunas are different from 

non-basin faunas 

3 salt bottom and 3 salt surrounded 

basins 

6 30 

HO4: Canyon fauna is different from 

slope fauna 

4 Canyons to be compared to noncanyon and non-basin biota from 

HO1-HO3

8 40 

HO5: Fauna below escarpments 

different from slope 

Add sta. below escarpment in 

addition to HO1- HO4 in area of 

furrows 

7 35 

HO6: Surface primary production 

explains faunal differences 

Add sta. to (HO1-HO2) in “hot spot” 

defined by historical water column 

data 

7 35 

HO7: Proximity to organic input 

causes bioenhancement 

Add sta. in proximity to 

“geochemical anomalies” (hydrates, 

brine pools, methane seeps) 

8 40 

HO8: No variation in benthic fauna 

over time. 

6 stations (or other elements of the 

design, HO1 -HO7) over 2 years 

12 60 

 

 The first interim meeting in February 2001 was used to up-date the hypotheses based on 

Survey Cruise data, select sites to be repeated, add new sites to strengthen comparisons and 

identify sites for process studies. The process sites selected were MT3, S36, S42, and MT6. New 

sites to be added were in the furrows below Green Knoll on the top of Green Knoll, a site 

between the Mississippi Trough and the DeSoto Canyon, and hear the Bush Hill seep. 

3.3 Dependent and Independent Variables 

 Based on the various hypotheses described in the previous section, a series of dependent 

and independent variables were chosen that will provide the set of observations at each station to 

test the validity of the null hypotheses. Variable selection was based on a knowledge of the 

system being observed, a current understanding of how the system functions, and an estimate of 

the relative importance of forcing factors as described in the conceptual model (see Section 4.0). 

 The set of variables measured at the survey stations are organized around the 

characteristics that define the system including physiographic setting, time, water masses, 

geographic location, abiotic and biotic water column properties, sediment properties, chemical 

contaminants in sediments, indicators of biogeochemical processes, community structure, and 

community function (Tables 3.2-3.4). These variables also quantify stocks and processes for 

input to the model. 
3-11 

Table 3.2. Independent variables fixed by the sampling plan design. 

Physiographic Characteristics 

Water Depth 

Basins underlain by salt 

Basins surrounded by salt 

Basins subjected to slumping/erosion 

Basins overlain by an undisturbed drape of Holocene silt and clay 

Canyons 

Escarpments 

Proximity to seeps 

Basin slope angle 

Time 

Months 

Years 

Water Masses 

Loop Current 

Consistently “cool” water between eddies 

Warm eddies 

Geographic Location 

East vs West 

Distance from shore 

Table 3.3. Dependent variables to be measured. 

Community Structure

Bacterial density Macrofaunal species composition 

Bacterial biomass Megafaunal density 

Foraminiferal biomass Megafaunal biomass 

Meiofaunal density Megafaunal diversity 

Meiofaunal biomass Megafaunal species composition 

Meiofaunal composition to major group Fish density 

Macrofaunal density Fish biomass 

Macrofaunal biomass Fish diversity 

Macrofaunal diversity Fish species composition 

Community Function

Bacteria growth rates Fish respiration1

Bacteria respiration Fish predation on megafauna2

Bacteria response to different substrates Fish scavenging on carcasses2

Foraminiferal respiration1 Nutrient Regeneration 

Foraminiferal feeding rates1 Denitrification rate 

Meiofaunal respiration1 Sediment mixing rates (bioturbation)2

Meiofaunal feeding rates on bacteria Sediment accumulation rate2

Macrofaunal respiration1 Sedimentary community oxygen consumption 

Macrofauna growth rates2 Sulfate reduction rate 

Macrofauna predation rates2 Foodweb studies 

Macrofauna predation rates on meiofauna, bacteria, and organic matter 

Megafaunal respiration rates2 

Megafaunal predation rate on megafauna, meiofauna, bacteria, and organic 

matter2

Megafaunal scavenging on carcasses2 

1-calculated based on size and temperature 

2-estimated from sub-model 
3-12 

Table 3.4. Ancillary variables to be measured at Survey and Experimental Stations. 

 

Water Column Profiles Sediment Properties

 

• Depth • Grain Size 

• Temperature • Porosity 

• Salinity • Elemental composition (organic carbon, 

• Oxygen nitrogen, sulfur) 

• Nitrate and Nitrite • Percent inorganic carbon (TIC) 

• Ammonium • Permeability 

• Silicate • Shear Strength 

• Phosphate • Bulk Density 

• Particulate Matter (PM) 

• Particulate Organic Carbon (POC) Geochemistry1

• Light 

• Currents • Nutrients 

• Dissolved Organic Carbon (DOC) 

Biotic Water Column Profile • SO4

=

/Cl- 

• Dissolved Inorganic Carbon (DIC) 

• Photosynthetic Pigments • δ13C DIC 

• Primary Production • Sulfate Reduction Rate 

• pH 

• H2S 

• O2

• Reactive Fe 

• Reactive Mn 

Chemical Contaminants • Acid Volatile Sulfide 

 

• Hydrocarbons 

• Metals 

 1

Composite sample at survey station, profiles for fluxes at experimental station.

3.4 Statistical Analyses 

 Statistical analyses to test for differences among treatment means are performed using 

parametric, general linear models. Prior to analysis, data are transformed, generally by natural 

logarithm, to achieve homogeneity of error variance, normality of residual errors, and additivity 

of effects. A data set of residual errors is created for each model and tested for normality. Both 

untransformed and transformed residuals are computed, and the datasets that are normally 

distributed with means of zero are used for analyses. 

 The models that follow describe the relationships among the independent design 

variables only. The measured dependent variables are described in the methods sections. The 

notation used follows conventions described by Kirk (1982). 

 3.4.1 Univariate Analyses 

 Univariate analyses will be used to test each hypothesis based on the following models. 

The stations to be used to test each hypothesis are summarized in Table 3.1. 

 The first two hypotheses are as follows: 
3-13 

HO1: There is no variation in benthic fauna with depth, and 

HO2: There is no difference in fauna along an east to west gradient. 

 The effect of depth is tested with stations along transects. Multiple transects were 

necessary to replicate at the treatment level. Transects should also hold constant nuisance 

variables such differences in circulation, bottom complexity, or other physical factors. The effect 

of longitude is tested with stations on an east - west gradient along isobaths, so this design tests 

two major hypotheses. The experiment is a two-way completely random factorial analysis of 

variance (ANOVA) that is described by the following model: 

Yijk = μ + αj + βk + αβjk + ∈i(jk)

where Yijk is the measurement for each individual replicate, μ is the overall sample mean, αj is 

the main effect for transects and j=1-4, βk is the main effect for depths and k=1-7 (300, 750, 

1200, 1650, 2100, 2550, and 3000 m), αβjk, is an interaction term, and ∈i(jk) is the random error 

for each replicate measurement and i=1-5. 

 The third hypothesis is: 

HO3: There is no difference between basin fauna and non-basin fauna. 

 Geological complexity exists in the northern GOM. One expression of this complexity is 

basins. Basins may cause changes in current flow such that water masses are altered as they pass 

across the mouth of the basin or impact a sill. This could affect benthos. One station within a 

basin will be paired with two nearby stations already sampled for HO1 and HO2 above to test for 

basin effects. Station pairing is necessary to control for distance from shore and depth. For 

example, a station selected for HO1/HO2 at 1200 m may have a nearby basin at 1650 m, so stations 

generally distant from shore and in the same water depth would be compared against the basin 

stations. The entire experiment is replicated at 6 different sites, so each location is a blocking 

effect. The experiment is a two-way completely random factorial ANOVA that is described by 

the following model: 

Yijk = μ + αj + βk + αβjk + ∈i(jk)

where Yijk is the measurement for each individual replicate, μ is the overall sample mean, αj is 

the main effect for replicate sites and j=1-6, βk is the main effect for treatments and k=1-3 (basin, 

non-basin same distance from shore, and non-basin same depth), αβjk, is an interaction term, and 

∈i(jk) is the random error for each replicate measurement and i=1-5. Differences between sites are 

not of interest because they replicate the basin effect, so it doesn’t matter if that test is 

significant. The main test of interest is a multiple comparison tests among treatment levels if 

there is a significant difference among treatments. 

 The fourth hypothesis is: 

HO4: There is no difference between canyon fauna and non-canyon fauna. 

 Another form of geological complexity in the GOM is canyons. Often sediment slumping 

occurs in canyons in addition to alteration in near-bottom current patterns. One station within a 
3-14 

canyon will be paired with nearby stations at similar depths that are not in a canyon. The entire 

experiment is replicated at four (4) different sites. The experiment is a two-way completely 

random factorial ANOVA that is described by the following model: 

Yijk = μ + αj + βk + αβjk + ∈i(jk)

where Yijk is the measurement for each individual replicate, μ is the overall sample mean, αj is 

the main effect for replicate sites and j=1-4, βk is the main effect for treatments and k=1-2 

(canyon and non-canyon), αβjk, is an interaction term, and ∈i(jk) is the random error for each 

replicate measurement and i=1-5. 

 The fifth hypothesis is: 

HO5: There is no difference between escarpment fauna and non-escarpment fauna. 

 Another form of geological complexity in the GOM is escarpments. These steep walls 

may be different from more gently sloping areas. One station adjacent to the base of an 

escarpment will be paired with nearby stations at a similar depth that are not adjacent to an 

escarpment. The entire experiment is replicated at 7 different sites. The sites will be chosen 

based on pairing stations with samples already taken to test HO1-HO5. The experiment is a twoway completely random factorial ANOVA that is described by the following model: 

Yijk = μ + αj + βk + αβjk + ∈i(jk)

where Yijk is the measurement for each individual replicate, μ is the overall sample mean, αj is 

the main effect for replicate sites and j=1-7, βk is the main effect for treatments and k=1-2 

(escarpment and non-escarpment), αβjk, is an interaction term, and ∈i(jk) is the random error for 

each replicate measurement and i=1-5. Depending on exact location of samples, this design may 

be altered to take into account distance from shore. In that case, the same model as that used for 

basins (HO3) will be used. 

 The sixth hypothesis is: 

HO6: There are no differences in benthos in areas with different amounts of water 

column primary production. 

 The sites will be chosen based on pairing stations with samples already taken to test HO1-

HO5. The design is nested as a completely random hierarchical design described by the model: 

Yijk= μ + αj + βk(j)+ ∈i(jk), 

where: μ = overall sample mean, αj = main effect of treatments and j=1-3 (high, medium, and 

low productivity), αk(j) = nested effect for replicate stations and k =1-7, and ∈i(jk) is the random 

error for each replicate measurement and i=1-5. The appropriate F-test for treatments is to use 

the mean square error for stations as the denominator. Another approach to analyze this design is 

analysis of covariance, where actual values indicating primary production (e.g., measured values 

or chlorophyll standing stock) are used as covariates. 
3-15 

 The seventh hypothesis is: 

HO7: There is no difference in benthic fauna near and far from seeps. 

 Another form of geological complexity in the GOM is organic and inorganic inputs in 

geochemically anomalous environments, e.g., hydrocarbon or brine seeps. Eight (8) stations are 

added to pair with existing non-seep stations. The station pairs will be in 4 site regions. The sites 

will be chosen based on pairing stations with samples already taken to test hypotheses HO1-HO6. 

The experiment is a two-way completely random factorial ANOVA that is described by the 

following model: 

Yijk = μ + αj + βk + αβjk + ∈i(jk)

where Yijk is the measurement for each individual replicate, μ is the overall sample mean, αj is 

the main effect for replicate sites and j=1-4, αk is the main effect for treatments and k=1-4 (brine 

seep, hydrocarbon seep, control for distance from shore, control for depth), αβjk, is an interaction 

term, and ∈i(jk) is the random error for each replicate measurement and i=1-5. Differences 

between sites are not of interest because they are replicating seep effects, so it doesn’t matter if 

that test is significant. The main test of interest is a multiple comparison test among treatment 

levels if there is a significant difference among treatments. 

 The eighth hypothesis is: 

HO8: There are no differences in benthic fauna among different sampling dates. 

 Six of the stations sampled for HO1-HO7 will be chosen for reoccupation in years 2 and 3 

so that there will be a time series for at least 3 years. In addition, attempts will be made to 

include several stations that were occupied in previous studies, extending the time series to 5 or 

6 sampling periods. Assuming depth and site (i.e., east-west) gradients, these two factors must be 

incorporated into the design. The experiment is a three-way completely random factorial 

ANOVA that can be described by the following model: 

Yijkl = μ + αj + βk + αβjk + γl + αγjl + βγkl + αβγjkl + ∈i(jkl)

where Yijkl is the measurement for each individual replicate, μ is the overall sample mean, αj is 

the main effect for sampling periods and j=1-3, βk is the main effect for sites and k=1-2, γl is the 

main effect term for depths and l=1-3 (shallow, mid-depth, deep), αβjk, αγjl, βγkl, and αβγjkl are 

interaction terms, and ∈i(jkl) is the random error for each replicate measurement and i=1-5. 

 Hypotheses will be re-evaluated as data is collected and recast as needed. Year II and III 

will provide the opportunity to collect additional new survey station if needed to infill the dataset 

to increase the power of statistical tests. 

 3.4.2 Power Analysis 
3-16 

 Power analysis is performed to determine the detectable change in the population at a 

given power (1-β and sample size (n) Power is calculated by: 

X

n

2 (t t ) x SD x α + β

∆=

where ∆ is the percent change in the population, SD is the pooled standard deviation, tα and tβ

are tabled values for a two-tailed test assuming a pooled estimate of variance from a large 

sample size, and X is the sample mean. Values of α=0.05, and powers of 0.95, 0.80, 0.50 were 

used in the analysis. 

 3.4.3 Multivariate Analyses 

 A meta-analysis (or synthesis) will be performed at the end of the study. The goal of the 

synthesis is to merge all data sets of response variables to create one large data set. All the 

ANOVA’s listed above can be analyzed in multivariate mode (MANOVA) to test the null 

hypothesis that the vector of population means equals zero. Without the jargon, test to find out if 

all measured variables respond to the dependent variables in the design in a similar fashion. The 

advantage of MANOVA is that multivariate error is controlled. That is, error rates are controlled 

at α across all response variables. 

 Once the meta-data set is assembled other questions can be queried. It can be tested if 

benthic fauna respond to abiotic environmental factors and which factors control distributions of 

responses. As stated previously, all stations and replicates are simply surrogates for the 

environmental factors that regulate biological processes at different scales. These scales vary 

greatly from small- (replicate boxcores), meso- (across transects, basins, or nearby stations) to 

large- (across the entire GOM). In addition, there is a temporal scale to the variation in all 

measurements. Multivariate analysis can be used to test the meta-data set for correlation or 

covariation among the independent variables that are measured. Two multivariate techniques 

will be employed: a parametric method (principal components analysis, PCA), and a nonparametric methods (multidimensional scaling, MDS). 

 Multidimensional scaling is a non-parametric multivariate technique for examining 

similarity or dissimilarity between stations, replicates, or other dependent variables in the 

experimental design. First, a similarity or dissimilarity index is computed for elements of the 

design (e.g., stations) and then a plot of the distance among points is created. The plot enables us 

to identify unknown variables that affect the similarity or dissimilarity between stations. Because 

the MDS procedure is based on non-parametric (Kruskal-Wallis like) models, it is very popular 

among European benthic ecologists, but has rarely been used among American benthic 

ecologists. It is most useful to summarize biotic data (e.g., community structure), but new 

variables are not created, nor can one reduce the variables in a dataset. 

 Principal components analysis is a parametric variable reducing technique that makes a 

new set of uncorrelated variables in order of decreasing variance. Analysis of abiotic variables 

can be used to summarize the co-varying environmental influences on different levels of 

replications, i.e., different spatial and temporal scales. Factor loading scores are generated for 

abiotic summaries of observations (rows), which can be used in other analyses. For example, 

during GOOMEX several hundred environmental variables were reduced with PCA and the new 
3-17 

PCA scores were shown to correlate with average macrofauna and meiofauna abundance and 

toxic responses. This allowed us to detect subtle sub-lethal effects within 100 m of platforms that 

could not be detected with univariate analysis of variance (Green and Montagna 1996). Also, the 

methods demonstrated functional responses of benthic fauna to abiotic variables, while 

separating confounding influences in the study related to differences in the natural background in 

which platforms were located. The same approach will be used in the deep-sea study to provide 

an understanding on how environmental influences regulate benthic communities. 

3.5 Revision of Taxonomic Level of Analysis

 Analysis of benthic infaunal communities has been widely used in environmental 

assessment and monitoring studies. The use of species level data is powerful, but expensive due 

to the level of expertise and labor intensive effort required. This has inspired efforts to determine 

if species level data is really necessary. For both meiofauna and macrofauna, a promising 

prospect is identification to only the suborder or family level. At the Group of Experts on Effects 

of Pollutants (GEEP) workshop, all levels of biological organization were studied from the 

molecular to the community, and all biological components from bacteria to macrofauna were 

included in both mesocosm and field experiments (Bayne et al. 1988). In the GEEP field study, 

diversity indices did not detect the pollution gradient, but community structure differences were 

distinct and species level data gave no more information for discrimination than did nematode 

suborder or harpacticoid family groupings (Heip et al. 1988). Macrofauna family groupings also 

were just as good for distinguishing the pollution gradient as was species level data (Warwick 

1988). Higher level identifications were found to be just as good as species identifications to 

detect pollution gradients in the Southern California Bight (Ferraro and Cole 1990). During the 

GOOMEX study around Gulf of Mexico production platforms, it was not sufficient to analyze at 

the family level for either meiofauna or macrofauna to describe differences among platforms or 

distances from platforms (Montagna and Harper 1996). LGL data and Year I sampling data has 

been reanalyzed at both species and family levels to determine if a reduction in taxonomic effort 

is adequate to characterize communities in different environmental settings. 
4-1 

4.0 FIELD ACTIVITIES 

 The Field Program was designed to collect a range of discrete samples and deploy 

continuous measuring sensors at a large number of stations in the northern GOM. The Field 

Program includes three cruises in each of the first three years of the program. The first cruise 

concentrated on the benthic survey objectives of the program and the following two cruises will 

be a mixture of survey and experimental stations. The survey field effort (Cruise 1) included 

boxcoring, trawling, photosurveys, and hydrocasts. Experimental process stations include a 

variety of specialized sampling efforts designed to identify important processes and forcing 

factors at a limited number of selected survey stations. 

 The details of the field and laboratory methods have been provided in the original 

proposal and the first Interim Report and will not be repeated here. 

4.1 Cruise 1 

 Cruise 1 was devoted to a survey of deep-sea communities of the northern GOM. Each 

standard survey station consisted of the following activities: 

 A. One (1) CTD: The CTD was deployed with the starboard hydrowinch using 

conductor cable (the CTD remains attached to the conducting cable for the entire 

cruise, unless problems are encountered); 

 B. Five (5) Boxcores: The boxcore was deployed with the hydraulic winch on the nonconducting cable. A pinger was attached to the wire above the boxcore at depths of 1 

km and greater. Otherwise wire out and tension was adequate to determine bottom 

contact. 

 C. One (1) Camera Lowering: The camera system was deployed with the nonconducting cable on the starboard hydrowinch. A pinger was attached to the frame to 

determine bottom contact and distance to the bottom. The camera takes up to 50 

exposures. 

 D. One (1) Bottom Trawl: The otter trawl was deployed with the heavy-duty winch on 

the fantail. 

 The shipboard scientific crew operated on watches of 12 hours on and 12 hours off. 

Between stations, the trawl samples were sorted to species and fixed in jars by those assigned to 

trawling. The five sievers on watch fixed and bottled the material and then assisted with the 

trawl sorting, displacement volume measurements (for biomass), preservation and labeling. 

Shipboard marine technicians analyzed samples for oxygen, nutrients, and salinities between 

stations. 

 Each watch was assigned a “watch chief” who had the duty of keeping records, notifying 

the Chief Scientist when problems arose, notifying the watch when the ship was on station, 

waking the new watch at the appropriate hour, and notifying the bridge when station activities 

were completed. The watch chief maintained a log in the main laboratory on the main deck that 

documented each activity in chronological order. Comments on the success or failure of the 

activity and inventory of all samples taken were kept. The watch chief and assistant ensured that 

the station logs on the bridge agreed with those in the laboratory. Each “watch chief” reported 
4-2 

directly to the Chief Scientist. The “watch chief” communicated between the bridge and 

scientists on the deck. 

4.2 Cruise 2 - Process Cruise 

 Plans for the first process cruise were made during the first interim meeting in February 

2001. The plans were made on the basis of findings to date. Extremes of high and low densities 

in bacteria, meio- and macrofauna were used as station selection criteria. The sites chosen were 

MT3, S35, S42, and MT6. High densities characterized MT3 and S36 at 1000 and 1850 m depth 

in the Mississippi and DeSoto Canyons, whereas low densities were found at S42 and MT6 at 

750 and 2750 m depth. 

 Other sites chosen for re-occupation were MT1, C7, and S41. New sites added were 

“HIPRO”, “furrows”, “Green Knoll”, “Bush Hill”, and “Fe Stone”. 

 Eleven sites were occupied during Cruise II (Figure 4.2). The lander was used 

successfully at S42 and MT3, providing estimates of total community respiration rates measured 

in situ. Shipboard incubations were made of total community oxygen uptake, sulfate reduction, 

thymidine incorporation into bacteria and bacteria grazing by meiofauna at four sites: MT3, S36, 

S42, and MT6. The process and survey data are being processed. 

4.3 Year 3 Field Activities

The revised Year 3 field program replaces the 20 day cruise scheduled for June 2002, with two 

15-day trips: one in June and one in August. In addition, two shorter supplemental cruises are 

proposed to be completed when ship time is available between December, 2001 and May, 2002, 

probably in transit back to the homeport of Galveston. 

Revised Cruise 3 - 2 to 4 days (return from Panama City, FL). Activities: box coring, 

trawling, photosurvey, CTD, and lander deployment. 

 Revised Cruise 4 - 2 to 4 days (return from Panama City, FL). Activities: box coring, 

trawling, photosurvey, CTD, and lander deployment. (Note: The strategy for these two trips will 

be to utilize transits from the eastern gulf back to Galveston to fill in shallow site sampling 

needed for hypothesis testing and model development. A small team of investigators will take 

the lander, box core and trawl to meet the ship, probably in Panama City, FL. However if transit 

ship time is not available back from Panama City, then a single trip will be substituted during 

which the above work will be accomplished (Figure 2.3). In this case, the trip will be in and out 

of Galveston. 

Revised Cruise 5 - 15 days in June, 2002. Activities - combination of survey and process 

sampling at 6 to 8 sites indicated, with emphasis on process studies; Staffing - 20 scientists, 

students, and observers, with 6 berths reserved for Mexican participants. The process stations 

would be emphasized on the June trip. 

Revised Cruise 6 - 15 days in August, 2002. Activities: the cruise would be principally 

devoted to survey activities (CTD, box cores, trawls and cameras), but would accommodate any 

process studies not completed during the June cruise. 20 scientists, students, and observers, with 

6 berths again reserved for Mexican participants.
4-3 

Figure 4.1. Benthic survey stations for DGoMB Cruise 1. 
4-4 

Figure 4.2. Benthic survey stations for DGoMB Cruise 2. 
4-5 

Table 4.1. Summary of sampling conducted during Cruise 1. 

Station Trawl Boxcore Camera CTD 

 

RW1 1 5 1 1 

RW2 1 5 1 1 

RW3 0 5 1 1 

RW4 0 5 1 1 

RW5 0 5 1 1 

RW6 1 5 0 1 

AC1 0 5 1 2 

W6 1 5 1 1 

W5 0 5 1 1 

W4 0 5 0 1 

W3 1 5 1 1 

W2 0 5 1 1 

W1 1 5 1 1 

WC5 1 5 1 1 

WC12 0 5 1 1 

B1 1 5 1 1 

NB2 1 5 1 1 

NB3 1 5 1 1 

B2 3 5 1 1 

NB4 1 5 0 2 

B3 1 5 1 0 

NB5 1 5 1 1 

C12 1 4 1 1 

C14 1 5 1 1 

C4 1 5 1 1 

C7 1 5 1 1 

C1 1 5 1 1 

S36 1 5 1 1 

S37 1 5 1 1 

S38 1 5 1 1 

S35 1 5 1 1 

S44 1 5 1 1 

S43 1 5 1 1 

S42 1 5 1 1 

S41 1 5 1 1 

S40 1 5 1 1 

S39 1 5 1 1 

MT6 1 5 1 1 

MT5 1 5 1 1 

MT4 1 5 1 1 

MT3 1 5 1 1 

MT2 1 5 1 1 

MT1 1 5 1 1 

 
4-6 

Table 4.2. Summary of sampling conducted during Cruise 2. 

Station CTD B.C. P.B.C S.B.C. Camera Trawl Lander ADCP 

 

MT1 1 5 0 0 1 1 0 0 

MT3 1 5 4 1 0 0 1 1 

HiPro 1 5 0 0 1 0 0 0 

S42 1 5 3 0 0 1 1 1 

S41 1 4 0 0 1 0 0 0 

S36 1 5 3 0 0 0 1 1 

MT6 1 5 3 0 1 0 0 1 

GKF 1 5 0 0 1 0 0 0 

GKT 1 1 0 1 1 0 0 0 

C7 1 5 0 0 1 0 0 0 

BH 1 5 0 0 1 0 0 0 

Total 11 50 13 2 8 2 3 4 

 

B.C= Boxcores sampled 

P.B.C. = Process Boxcore 

S.B.C. = Special Boxcore (stable isotope analysis) 
5-1 

5.0 PROGRAM STATUS AND PRELIMINARY RESULTS 

Preliminary results are presented for each work element and the progress to date on each 

task is summarized. Any conclusions are preliminary and based on partially complete data sets. 

In general interpretations are kept descriptive and overall synthesis will only be possible when 

the entire data sets are complete. 

5.1 Task 1 - Re-Examination of Previous Studies 

 Several sources of information were readily available to review and assess. These can be 

categorized as theses and dissertations of students of Willis E. Pequegnat; the MMS-supported 

slope study overseen by LGL Ecological Research Associates, Inc. (NGOMCS); and the peerreviewed literature. Practically all of this material has been included in a review of the deep 

GOM environmental information conducted by Continental Shelf Associates under contract with 

the MMS. DGoMB personnel participated in that review (G. Rowe, W. Nowlin, W. Bryant, D. 

Biggs, and M.C. Kennicutt II). That report should be consulted for specific details on individual 

studies. 

 All megafauna, macrofauna, megafauna, meiofauna and sediment raw data files from 

NGOMCS were supplied to DGoMB by LGL Ecological Associates, Inc.. The files have been 

sorted by discipline and restored as individual Microsoft Excel files. These files are available on 

the internet to DGoMB principal investigators. Megafauna and fish distributions have been 

plotted to assess the effect of depth and east-west gradients on species composition. Macrofaunal 

polychaete diversity (Ph.D. dissertation, G. Fain Hubbard) using several complementary indices 

has been plotted with depth by transect to consider potential internal GOM gradients (E to W, 

depth, etc.) and for comparison with other ocean basins. 

 Several conclusions were derived from earlier studies: 

1. biomass and densities of the size groups studied decrease in general as a 

function of water depth down the continental slope, but with frequent 

exceptions to this rule; 

2. densities of macrofauna differed between sampling dates on the C transect 

(for Central), with high densities in the spring and low densities in the fall; 

3. three depth zones can be tentatively defined based on species composition: the 

upper slope, the mid slope and deep water; 

4. the continental slope in the western GOM is different in species composition 

(macrofauna and megafauna) from the eastern GOM; 

5. sediments contained contaminant levels (low or non-detectable) typical of the 

deep-sea environment; 

6. diversity maxima are encountered on the upper slope (as opposed to the lower 

slope/upper rise, in other basins); and 

7. biomass and densities of the different size groups studied are lower than 

observed on most other ocean basin margins. 
5-2 

5.2 Task 2 - Field Sampling 

 For an update on field activities, see Section 4.0 Field Activities. Summaries of the 

samples collected on Cruise 2 and 2 are provided in Tables 5.1 and 5.2 

5.3 Task 3 - Sample Data Processing and Analysis 

 Standard survey data were collected at each site during each DGoMB cruise: physical 

and chemical properties of the water column, geological characteristics of the sediments, 

geochemistry of the sediments, and kinds and numbers of organisms present (Tables 5.1 and 

5.2). The status of these datasets are described along with preliminary interpretations. 

 5.3.1 Physical Oceanography 

 The physical oceanography preliminary report consists of two parts. The status of 

QA/QC and processing of the physical and filter data are reviewed. Secondly, a few plots of 

processed data are presented as illustrations of the types of information now available. 

 The status of QA/QC and data processing are as follows: 

• Filter data from the first cruise have been received and QA/QC has been performed. 

• Filter data from cruise 2 is being processed. Samples for total suspended particulate 

material and pigments have been analyzed. POC samples are expected to be 

completed soon. 

• QA/QC and processing of all continuous profile data from Cruise 1 have been 

completed. 

• The continuous data from the CTD unit for Cruise 2 have been received. QA/QC is 

completed on these data, with the exceptions of data from the OBS backscatter and 

continuous dissolved oxygen sensors. Correlations between percent light percent 

transmission and TSM (total suspended material) for Cruise 2 and the conversions of 

vertical profiles of percent transmission to profiles of TSM are being processed. 

• QA/QC of the bottle nutrient, oxygen and salinity data from Cruise 1 have been 

completed. All data from this cruise have been merged into a single cruise file. 

• Cruise 2 bottle-trip data files for the CTD upcasts are being processed. 

• Shipboard ADCP data from Cruise 1 are processed and QA/QC has been performed. 

• The QA/QC of shipboard ADCP data from Cruise 2 is in the process of being 

performed. 
5-3 

Table 5.1. Samples collected during DGoMB Cruise 1. 

Biology Samples Water Column Samples Sediment Samples Geoch

Bacterial 201 Depth 44 Grain Size 212 Nutrients Meiofaunal 208 Temperature 44 Porosity 212 Dissolved OrganMacrofaunal 212 Salinity 44 Elemental composition (organic 

carbon, nitrogen, sulfur) 

212 SO4=/Cl- 

Megafaunal 43 Oxygen 44 Percent inorganic carbon (TIC) 212 Dissolved InorgaFish 43 Nitrate and Nitrite 44 Permeability 212 δ13C DIC 

“Trash” 43 Ammonium 44 Shear Strength 212 Sulfate Reduction  Silicate 44 Bulk Density 212 pH  Phosphate 44 H2S 

 Particulate Matter (PM) 44 Hydrocarbons 212 O2  Particulate Organic Carbon (POC) 44 Metals 186 Reactive Fe  Light 44 Reactive Mn  Currents 44 Pore water 209 Acid Volatile Su

 Photosynthetic Pigments 44 O2, H2S, Fe and Mn 209 

 Primary Production 44 Total CO2 (DIC) 209  Sulfate and chloride 209  pH 209  Nutrients 209  Dissolved organic C (DOC)  209 

Sediment Solids 209 

 C stable isotopes 209  Porosity 209  CHNS 209  Reactive Fe and Mn 209  Carbonate carbon 209  Metals  Hydrocarbons 209  Biologic 209  Radioisotopes  SO42- reduction rate 

4 bacterial aliquots (0, 5, 10, 15) per sample 2 meiofaunal aliquots per sample filtered samples (POC, pigments, and PM) at three (3) different depths (bottom, chl max or mid, and surface water) 
5-4 

Table 5.2. Summary of samples collected during DGoMB Cruise 2. 

Biology Samples Water Column Samples Sediment Samples Geo

Bacterial (0,5,10,15 cm) 

113 Depth 11 Grain Size 49 Nutrient

Foraminiferal (times sampled) 

24 Temperature 11 Porosity 49 Dissolve

Carbon (D

Meiofaunal (0-1; 1-3) 111 Salinity 11 Elemental composition 

(organic carbon, nitrogen, sulfur) 

49 SO4=/Cl

Macrofaunal 49 Oxygen 11 Percent inorganic carbon 

(TIC) 

49 Dissolve

Carbon (D

Megafaunal 2 Nitrate and Nitrite 11 Permeability 49 δ13C DIC 

Fish 2 Ammonium 11 Shear Strength 49 Sulfate R"Trash" 0 Silicate 11 Bulk Density 49 pH  Phosphate 11 49 H2S 

 Particulate Matter (PM) 11 Hydrocarbons 49 O2  Particulate Organic Carbon (POC) 11 Metals 46 Reactive  Light 11 Pore water Reactive  Currents 11 O2, H2S, Fe and Mn 4 Acid Vo

 Photosynthetic Pigments 11 Total CO2 (DIC) 4 

 Primary Production 11 Sulfate and chloride 4 

pH 4 

ADCP deployed 4 Nutrients 4 Survey Camera 8 Dissolved organic C 

(DOC) 

4 

Lander 2 Sediment Solids  C stable isotopes 2  Porosity 47  CHNS 47  Reactive Fe and Mn 47  Carbonate carbon 47  Metals 46  Hydrocarbons 45 
5-5 

Table 5.2. Summary of samples collected during DGoMB Cruise 2 (Cont). 

Biology Samples Water Column Samples Sediment Samples Geo

Biologic 

 Radioisotopes 9  SO42- reduction rate 10 

 BMIC sampling 5  BAMS 5  Foraminifera ATP 4  Bacteria T-Thymidine 

uptake 

4 

 Meiofauna T-Thymidine 

uptake 

4 

 Megafauna respiration 1 
5-6 

 Vertical profiles of properties measured at two CTD/rosette stations on Cruise 2 are 

shown in Figures 5.1 and 5.2. Station MT1 is an example of a relatively shallow water station 

which does not reach the base of the main thermocline. Notable are the chlorophyll maximum at 

50-70 m (as seen in the fluorometer voltage) and some evidence of a weak nephloid layer near 

100 m, as seen in the percent light transmission. The latter may indicate transport of water off 

the continental shelf at that depth. A deep station, GKF, is shown in Figure 5.2. Again, the 

chlorophyll maximum is clear. In this case there appears to be a pronounced near-bottom 

nepheloid layer. 

 A scatter plot of temperature versus salinity for DGoMB Cruise 1 is shown in Figure 5.3. 

The variance is small below about 16°C, indicating reasonable data quality. The scatter plot of 

nitrate versus phosphate for Cruise 1 is shown in Figure 5.4 and indicates the expected linear 

relationship. 

 Plots of sigma-theta versus the discrete water sample properties salinity, dissolved 

oxygen, nitrate, phosphate, and silicate are shown in Figures 5.5 to 5.9. In each figure, values 

from DGoMB Cruise 1 are plotted on the left side of the graph. The curves shown indicate the 

mean and + 2.3 standard deviations based on a combination of data from DGoMB Cruise 1, 

LATEX A, and NEGOM. These limits would include 98% of the points, if the data had a normal 

distribution about the mean as a function of density. In the right frame of each figure are 

displayed DGoMB Cruise 1 data (pluses) and, for comparison, data from LATEX A and 

NEGOM (dots). The data from DGoMB are representative of information expected from the 

Gulf of Mexico and are of good quality. 

 The shipboard ADCP measurements recorded during both legs of DGoMB Cruise 1 are 

of good quality. Comparisons of the near-surface (40-60 m) currents measured simultaneously 

by the 38 and 150 kHz instruments are favorable. No large gaps exist in the data set; however, 

short gaps due to GPS dropout and computer down time for data backups exist. The short gaps 

do not affect the overall data quality. 

 Based on TOPEX/ERS-2 sea surface height anomaly (SSHA) plots, the Loop Current 

was hammer-shaped during leg 1 of Cruise 1, intruding northward of 27°N and westward to 

89°W. The SSHA field for June 10, 2000 is shown in Figure 5.10. Thus, the Loop Current was 

east of the study region during that leg. However, two Loop Current Eddies were present in the 

western Gulf and their presence is seen in the ADCP vector fields. Current vectors at a vertical 

bin centered at 12.4 m depth are shown in Figure 5.11. The weaker of the two eddies was 

centered at 91.5°W, 24°N. The leg 1 Cruise 1 track passed through the northern limb of this eddy 

at 26°N between 90°W and 91°W. The stronger eddy was centered at 94.5°W, 26°N. The 

anticyclonic current field is clearly seen in the horizontal vector stick plots along the cruise 

track. Particularly strong southward currents (of order 100 cm/s) are seen along the eastern side 

of this eddy at around 93.5°W. 

 During leg 2 of Cruise 1, the stronger LCE drifted west about 0.5° of longitude. The 

SSHA field for June 10, 2000 is shown in Figure 5.12. The anticyclonic structure of the stronger 

eddy is again seen in the leg 2 ADCP data. ADCP vectors for a vertical bin centered at 11.6 m 

during leg 2 are shown in Figure 5.12. The westward movement of the eddy is also seen in the 

data as the strongest southward currents are located at 94°W and are reduced in amplitude about 

50-70 cm/s. The cruise track of leg 2 Cruise 1 was well north of the weak LCE, centered at that 

time near 92°W, 23°N. 
5-7 

Figure 5.1. Vertical profiles of temperature, salinity, percent light transmission, fluorometer 

voltage, and sigma-theta for DGoMB station MT1. 
5-8 

Figure 5.2. Vertical profiles of temperature, salinity, percent light transmission, fluorometer 

voltage, and sigma-theta for DGoMB station GKF. 
5-9 

Figure 5.3. Scatter plot of temperature versus salinity for DGoMB Cruise 1. 
5-10 

Figure 5.4. Scatter plot of nitrate versus phosphate for DGoMB Cruise 1. 
5-11 

Figure 5.5. Bottle salinity versus sigma-theta for (left) DGoMB Cruise 1 and (right) a combination of DGoM

and data from LATEX A and NEGOM (dots). Curves shown are mean and + 2.3 standard dev

combination of data from DGoMB Cruise 1, LATEX A, and NEGOM. 
5-12 

Figure 5.6. Dissolved oxygen versus sigma-theta for (left) DGoMB Cruise 1 and (right) a combination o

(pluses) and data from LATEX A and NEGOM (dots). Curves shown are mean and + 2.3 standard 

a combination of data from DGoMB Cruise 1, LATEX A, and NEGOM. 
5-13 

Figure 5.7. Nitrate versus sigma-theta for (left) DGoMB Cruise 1 and (right) a combination of DGoMB C

data from LATEX A and NEGOM (dots). Curves shown are mean and + 2.3 standard dev

combination of data from DGoMB Cruise 1, LATEX A, and NEGOM. 
5-14 

Figure 5.8. Phosphate versus sigma-theta for (left) DGoMB Cruise 1 and (right) a combination of DGoM

and data from LATEX A and NEGOM (dots). Curves shown are mean and + 2.3 standard d

combination of data from DGoMB Cruise 1, LATEX A, and NEGOM. 
5-15 

Figure 5.9. Silicate versus sigma-theta for (left) DGoMB Cruise 1 and (right) a combination of DGoMB C

data from LATEX A and NEGOM (dots). Curves shown are mean and + 2.3 standard de

combination of data from DGoMB Cruise 1, LATEX A, and NEGOM. 
5-16 

Figure 5.10. Sea surface height field for 14 May 2000 based on analyzed height anomaly of 

TOPEX and ERS-2 altimeter data added to mean sea surface height field. 

Anticyclonic (cyclonic) circulation features have clockwise (counterclockwise) 

currents and positive (negative) sea surface height values. Courtesy of Robert 

Leben (University of Colorado). 
5-17 

Figure 5.11. Broad-band 150 kHz ADCP current vectors at average depth of 12.4 m on 

DGoMB leg 1 Cruise, 3-23 May 2000. 
5-18 

Figure 5.12. Sea surface height field for 10 June 2000 based on analyzed height anomaly of 

TOPEX and ERS-2 altimeter data added to mean sea surface height field. 

Anticyclonic (cyclonic) circulation features have clockwise (counterclockwise) 

currents and positive (negative) sea surface height values. Courtesy of Robert 

Leben (University of Colorado). 
5-19 

 During leg 2 of Cruise 1, the Loop Current did not intrude into the Gulf as far north as 

27°N (see Figure 5.13), and thus did not influence directly the currents along the cruise track. 

However, a weak LCE centered at 90°W, 26°N and a stronger cyclonic eddy centered at 87°W, 

27°N are both seen in SSHA plots and in the ADCP data. 

 5.3.2 Remote Sensing: Ocean Color Climatology 

 During Year Two, a time series of SeaWiFS chlorophyll (CHL) at each of the stations 

was compiled by colleagues at the University of South Florida (Andrew Remsen, Chuan Min 

Hu, Frank Muller-Karger). All available SeaWiFS imagery from the Gulf of Mexico for 1998 

and 1999 was composited into biweekly bins and some time early in 2002, this two-year series of 

biweekly data files will be continued and extended for year 2000. 

 The average CHL concentration was extracted for each of the DGoMB stations from all 

52 biweekly scenes (104 weeks) of the 1998-1999 data series. The “average” CHL for each of 

the DGoMB stations, in turn, is the mean of a 5 pixel x 5 pixel grid centered on the specified 

latitude and longitude of each of the DGoMB stations. Since each SeaWiFS pixel has 2.8 x 4.1 

km resolution, the effective area around each DGoMB station that is being averaged at each 

biweekly interval computes to be 287 km2

. 

 A table that summarizes the two-year average CHL (SeaWiFS mean; μg/L) and also the 

standard deviation about the 2-year mean at each of these stations is shown as Table 5.3. This 

has been posted to the DGoMB password-protected website. Plots of the biweekly averages have 

also been made; composites are presented as Figures 5.14-5.17. 

1) The annual cycle of CHL at the four deepest of the “deepwater stations” (RW6, W6, 

B3, C12) shows the pattern previously reported from analysis of the CZCS archives 

by Muller-Karger et al (1991) and by Melo-Gonzalez et al (2000): deepwater CHL is 

lowest in spring-summer and highest November-February. 

2) The annual cycle of CHL at the western stations (W1-W6) and at the Louisiana Slope 

Stations (the cluster of 9 stations between 93W and 91W) shows the “deepwater” 

pattern. 

3) The annual cycle of CHL at the far western stations (RW1-RW6) generally follows 

the “deepwater” pattern, but there are several periods of the year in which CHL at the 

shallower stations (RW1 and RW2) exceeds 0.5 μg/L. These maxima occur 

throughout the year. 

4) East of 91W, however, the “typical” deepwater annual cycle in CHL is swamped by 

unusually high summertime CHL. In both summer 1998 and summer 1999, a warm 

slope eddy, that NEGOM-COH fieldwork showed, was centered over DeSoto 

Canyon, acted to entrain low salinity, high chlorophyll “green water” from the 

Mississippi River and transport this plume seaward into deepwater. High surface 

CHL in summertime is evident at all stations on the Mississippi Trough Transect 

(MT1-MT6), and at the 3 stations farthest upslope along the central transect (C1, C7, 

C4) 
5-20 

Figure 5.13. Narrow-band 150 kHz ADCP current vectors at average depth of 11.6 m on DGoMB leg 2 Cru

June 2000. 
5-21 

Table 5.3. Summary of the two-year average chlorophyll a concentrations (CHL) and the 

standard deviation about the two-year mean at each of the stations. 

Station Longitude Latitude Depth (m) SeaWiFS mean SeaWiFS std dev 

 

RW1 96.00 27.50 300 0.33 0.21 

RW2 95.75 27.25 800 0.23 0.09 

RW3 95.50 27.00 1300 0.20 0.07 

RW4 95.25 26.75 1600 0.21 0.10 

RW5 95.00 26.50 1800 0.18 0.05 

RW6 94.50 26.00 3000 0.18 0.06 

AC1 94.42 26.50 2400 0.18 0.07 

W1 93.55 27.58 300 0.23 0.09 

W2 93.34 27.42 800 0.21 0.07 

W3 93.32 27.18 1300 0.19 0.06 

W4 93.32 26.74 1800 0.19 0.06 

W5 93.32 26.28 2700 0.17 0.05 

W6 93.32 26.00 3100 0.17 0.06 

 

WC5 91.77 27.78 800 0.23 0.09 

WC12 91.55 27.32 1300 0.20 0.07 

NB2 92.00 27.13 1500 0.18 0.06 

NB3 91.83 26.55 2000 0.18 0.06 

NB5 91.22 26.25 2100 0.18 0.06 

B1 91.42 27.22 2200 0.19 0.07 

NB4 92.40 26.25 2400 0.17 0.04 

B2 92.23 26.55 2600 0.18 0.05 

B3 91.80 26.20 2600 0.18 0.06 

 

C1 90.25 28.06 300 0.94 1.95 

C7 89.98 27.73 1000 0.34 0.47 

C4 89.78 27.45 1400 0.24 0.16 

C14 89.58 26.92 2600 0.20 0.09 

C12 89.24 26.38 2800 0.18 0.06 

 

S35 87.05 29.33 700 0.60 0.70 

S36 87.67 28.92 2000 0.87 1.37 

S37 87.77 28.55 2300 0.43 0.42 

S38 87.25 28.28 2300 0.24 0.10 

 

S44 85.75 28.75 200 0.37 0.28 

S43 86.08 28.50 400 0.39 0.44 

S42 86.42 28.25 900 0.28 0.25 

S41 86.58 28.00 2800 0.24 0.15 

S40 86.75 27.83 3000 0.22 0.08 

S39 87.00 27.50 3200 0.21 0.07 

 

MT1 89.83 28.54 300 4.91 2.26 

MT2 89.67 28.45 600 3.68 5.42 

MT3 89.49 28.22 1000 1.42 1.07 

MT4 89.17 27.83 1400 0.62 1.45 

MT5 88.67 27.33 2200 0.25 0.19 

MT6 88.00 27.00 2700 0.19 0.06 
5-22 

Figure 5.14. Two-year time series of SeaWiFS chlorophyll concentration at deep water 

DGoMB stations > 2600 m water depth in north-central and northwestern Gulf 

of Mexico. Data extend from January 1, 1998 through December 30, 1999. 

SeaWiFS data are courtesy of orbimage and NASA; data compositing and 

processing were done at the College of Marine Science, University of South 

Florida. 
5-23 

Figure 5.15. Two-year time series of SeaWiFS chlorophyll concentration for DGoMB 

stations along Western (W) Transect and on Louisiana Slope. Data coverage 

and source same as for Figure 5.14. 
5-24 

Figure 5.16. Two-year time series of SeaWiFS chlorophyll concentration for DGoMB

stations along Central (C) Transect and Mississippi Trough (MT) Transect. 

Data coverage and source same as for Figure 5.14, but note that y-axis ranges 

are greater than those of Figure 5.14. 
5-25 

Figure 5.17 Two-year time series of SeaWiFS chlorophyll concentration for DGoMB 

stations in DeSoto Canyon and along Eastern Transect. Data coverage and 

source same as for Figure 5.14, but note that y-axis ranges are greater than 

those of Figure 5.14. 
5-26 

and at the 3 stations farthest upslope along the DeSoto Canyon transect (S35, S36, 

S37). High summertime CHL is evident, as well, at 3 of the stations along the eastern 

transect (S44, S43, S42). 

5) Biweekly average CHL have been extracted at each of the 12 stations where SAIC 

moored current meters in April 1997 to March 1999 in support of the DeSoto Canyon 

Eddy Intrusion Study. There is a robust correlation between the time of year in which 

there was highest CHL in surface waters and the time of year in which there was 

highest ADCP backscatter (Scott 2001). These data indicate that traditional 

“nutrients-phytoplankton-zooplankton (NPZ)” paradigm seems to apply in the 

deepwater NEGOM, at least in the upper 90 m of the water column where the ADCP 

backscatter is able to image. 

 5.3.3 Geology 

 Two hundred and forty five cores, 30 to 35 cm in length, were recovered from 43 stations 

during the survey. Each core was analyzed at 1 cm intervals for bulk density, porosity, water 

content, p-wave velocity, void ratio and impedance. That analysis resulted in 48,500 individual 

measurements of geotechnical properties. All cores were split and photographed and shear 

strength measurements were attempted but the surficial sediments have shear strengths lower 

than our instruments could measure. 

 An example of the data generated is illustrated in Figure 5.18. All 5 cores at Location 

NB3 had very similar measurements between the geotechnical properties and depth within the 

cores. In contrast to the uniformity found in cores taken at Location NB3, the cores recovered at 

Location C7 display a wide variation in properties with depth within each core (Figure 5.19). 

The location of sites that have large variations in geotechnical properties between cores taken at 

the same location are shown in Figure 5.20. 

 All cores were examined for the degree of bioturbation that the cores has undergone. 

Figure 5.21 is a photograph of a split core taken at Location W4. The sediment at Location W4, 

has under gone very little to no bioturbation. In contrast, the core from Location MT5 (Figure 

5.22) illustrates a high degree of bioturbation. A core from Location RW5 (Figure 5.23) 

illustrates sediment that has under gone slight to a moderate degree of bioturbation. Figure 5.24 

illustrates the degree of bioturbation of the sediments at all locations of the year 2000 cruises. 

There is a very distinct and significant boundary between sediments consisting of slight to no 

bioturbation and those that are highly bioturbated. 

 5.3.4 Geochemistry 

 The geochemical studies consist of measurements of sediment solid phase and pore water 

chemical properties. They include determination of bacterial sulfate reduction rates and are 

interfaced with benthic lander flux measurements. As with the other components of the program, 

the geochemical studies are divided into a set of measurements for survey sites and a more 

comprehensive array of measurements at survey sites selected for the study of benthic processes. 
5-27 

Figure 5.18. The sediment geotechnical properties of cores (5 replicates) taken at at the NB3 

location. Note the compact arrangement of the various properties with depth in 

the core that indicate a uniformity of the sediment at location NB3. 
5-28 

Figure 5.19. The sediment geotechnical properties of cores (5 replicates) taken at the MT6 

location. Note the dispersed arrangement of the various properties with depth in 

the core that indicate a wide variety of sediment types at location MT6. 
5-29 

Figure 5.20. A map showing the locations of the stations that have highly variable geotechnical pr
5-30 

Figure 5.21. Boxcore 134 at station W4 illustrating sediment that has almost no sediment 

bioturbation. 
5-31 

Figure 5.22. Boxcore 12 at station MT5 illustrating sediment that has undergone a slight to 

moderate degee of bioturbation. 
5-32 

Figure 5.23. Boxcore 111 at station RW5 illustrating a high degree of bioturbation. 
5-33

Figure 5.24. A map showing the degree of sediment bioturbation present at the survey sites

 SLIGHT TO NO BIOTURBATION MODERATELY BIOTURBATED HIGHLY BIOTURBATED 
5-34 

 At the survey sites selected metal and organic compounds were determined as an 

indication of the presence of natural and anthropogenic contaminants that might influence 

community ecology. Additionally, a limited number of pore water (e.g., SO4

2-, DOC, nutrients) 

and solid phase (organic-C) bioreactive components are determined to estimate relative biologic 

activity. The process sites are subject to a more comprehensive set of measurements generally 

performed down core to provide depth profiles. Of special note are the additional measurements 

made with microelectrodes, sulfate reduction rate measurements using 35SO4

2-, and 

determination of sediment accumulation and mixing rates based on a variety of radioisotopes. 

 All analyses associated with the survey sites from Cruise 1 have been completed. The 

analysis of samples from Cruise 2 are incomplete as of this report. Limited commentary will be 

offered on the results to date, however, it should be taken with the precaution that until the work 

is complete and more fully integrated with other components of the program it is preliminary. 

 5.3.4.1 Metals 

 Major and minor metal analyses of the surface sediment samples collected on the first 

DGoMB cruise (0-2 cm, N=43) have been completed. Much, but not all, of the analytical work 

on samples from the second cruise is also complete. Location maps show that some of the 

sampling sites are within areas with numerous offshore drilling and production platforms. This 

includes areas around sampling sites C1, MT1, 2, 3 and WC5. On the other hand, many of the 

sampling sites are many kilometers from present-day intensive petroleum development. It has 

been previously shown (Boothe and Presley 1989) that significant metal contamination of 

sediments by off-shore drilling and production is restricted to within a few hundreds of meters of 

platforms. Therefore it is not expect that sediments would be contaminated at the DGoMB 

stations. 

 For this study, elements were determined known to be major constituents of drilling 

fluids (Ba, Cr) as well as some of environmental concern which are antimony, arsenic, 

beryllium, cadmium, copper, lead, manganese, mercury, molybdenum, nickel, silver, tin, 

thallium, vanadium, and zinc. Metals were measured to assess if petroleum activities in the study 

area might affect the benthos. In addition, aluminum, calcium, iron and silicon were determined 

to facilitate recognition of sediment trace metal variations caused by natural (non-anthropogenic) 

differences in sediment texture and mineralogy. A total of 20 elements were determined in all 

sediment samples. Second cruise data for the elements which can be determined by INAA and 

ICP are complete and are given here. Data produced by GFAA will be available soon. 

The data sets for the two cruises agree well in almost all cases with only a few 

differences of more that 10% between individual data points. This, along with the good spike 

recoveries and good results for analysis of standard reference materials gives confidence in the 

analytical results. Many of the trace elements were in low concentration in these samples, but all 

elements in almost all samples were above the detection limits of the methods used. Both Al and 

Fe were used for this report to normalize trace metal concentrations, as they exhibit a strong 

covariance. Trace metal concentrations that fall above a best fit line through the data are of 

interest, assuming that most of the data are background values. 
5-35 

 Average concentrations of potential pollutant metals; Ag, Cd, Cu, Hg, Pb, and Zn; in the 

study area samples are similar to average crustal abundances and to average values for areas of 

the northern Gulf of Mexico thought to be low in pollutant metals. Average values may not, 

however, be the best way to evaluate this data because of the relatively small number of samples 

and the considerable variability in the data, some of which is due to the variable CaCO3 content 

of the samples. It is better to compare the slope of a best fit line through the data for each 

element on an element versus Al or Fe scatter plot to that expected for Mississippi River Delta 

material. The Mississippi River is the most likely source of most of the silicate fraction of the 

sediments at the study sites. 

 When concentrations of several elements are plotted against Al (Figures 5.25 and 5.26), 

most data points not only lie near a best fit line but the line has almost the same slope as one 

drawn through data for Mississippi River Delta sediment. This is true for Be, Co, Cr, Fe, Si, Tl, 

V and Zn (plus K and Mg not reported here) which have positive slopes on the metal versus Al 

plots and for Ca and Sr (not reported here) which have negative slopes. Thus, for these metals 

there is no indication of additions from human activity. Rather, the metal concentrations in a 

particular sample are determined by the relative amounts of Mississippi River derived silicate 

material and plankton derived carbonate in the sediment. The picture is less clear for the other 

elements. Ni, Pb, Cd, As and especially Cu concentrations show more scatter on the metal versus 

Al plots than do the elements discussed above. Furthermore, the slopes suggest a general 

enrichment in these elements of 25 to 50% over Mississippi River derived material. 

 A few points on each of the metal vs Al plots are also far enough off the general trend 

line to suggest possible human influence. On the other hand, Mn concentrations are more 

variable and much more elevated over Mississippi Delta material than are those of any of the 

other elements. It is very unlikely that this Mn enrichment is due to human influence. Rather, it 

is due to remobilization of Mn from buried reduced sediment. The Mn then diffuses up through 

the sediment column and redeposits in near the surface sediment under oxidizing conditions. 

This phenomenon has been well documented for northern GOM sediments by Trefry and Presley 

(1982) and others. 

 Other metals have been shown to undergo the same diagenetic remobilization process 

that affects Mn (e.g., Presley et al. 1992) and it seems likely that this process is at work in the 

DGoMB area. The fact that there is not a good correlation between Ni, Pb, Cd and Cu 

concentrations and Mn does not mean that all have been unaffected by similar diagenetic 

processes. The situation is complicated by the intensity of reducing conditions, the relative 

amounts of available sulfide which would precipitate metals, and variable metal sulfide 

solubilities. In short, it seems likely that the somewhat anomalous Ni, Pb, Cd and Cu 

concentrations in the DGoMB area are due to natural diagenetic and transport processes rather 

than to human activity. In any case, all of the concentrations are well below levels that would be 

expected to have harmful effects on organisms. 
5-36 

y = 21.7x - 

R2 = 

0

2468

10121416

0 1 2 3 4 

ICP Aluminum (% dry 

Vanadium (ppm dry weight)

y = 9.97x + 3.20

R2 = 0.85

0

123456789

0 1 2 3 4 

ICP Aluminum (% dry 

Chromium (ppm dry weight)

y = -5.06x + 36.8

R2 = 0.894

05

112233

0 1 2 3 4 5 6 7

ICP Aluminum (% dry 

Calcium (% dry weight)

y = 9.97x + 3.20

R2 = 0.85

0

123456789

0 1 2 3 4 5 6 7

ICP Aluminum (% dry 

Chromium (ppm dry weight)

Figure 5.25. Variations in total sediment calcium (A), chromium (B), zinc (C), and vanadium (D) concentra

of changes in sediment mineralogy (as indicated by sediment aluminum levels) measured by i

plasma spectrometer (ICP).

A B 

C D 
5-37 

y = 0.0189x + 0.0996

R2 = 0.0762

0.00.10.20.30.40.50.6

0 1 2 3 4 5 6 7

ICP Aluminum (% dry 

Cadmium (ppm dry weight) y = 2.12x + 15.88 R2 = 0.11

05

1122334

0 1 3 4 

ICP Aluminum (% dry 

Copper (ppm dry weight)

y = 4.13x + 17.0

R2 = 0.24

0

12345678

0 1 2 3 4 5 6 7

ICP Aluminum (% dry 

Nickel (ppm dry weight)

y = 3.99x - 3.21

R2 = 0.74

05

11223

0 1 2 3 4 

ICP Aluminum (% dry 

Lead (ppm dry weight)

Figure 5.26. Variations in total sediment cadmium (A), copper (B), nickel (C), and lead (D) concentrati

changes in sediment mineralogy (as indicated by sediment aluminum levels). 

A B

C D 
5-38 

 In contrast to the elements discussed above, barium (Ba) shows a few values that are 

higher than those of average crustal material and average clay-rich sediments but are typical of 

near-platform sediments from the northern GOM. In the case of Ba, it seems likely that the 

enrichments, which are up to almost a factor of ten, are due to disposal of oil well drilling mud. 

Up to 90% of the dry weight of drilling muds can be Ba (Boothe and Presley 1985) so 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 

some drilling platforms in the northern Gulf of Mexico. Barium concentrations of tens of 

thousands of ppm have been found in many samples (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. 1969) 

 In summary, the samples analyzed for this project were a mixture of carbonate and 

terrigenous silicate materials and thus varied considerably in aluminum, calcium and iron 

concentrations. Trace metal concentrations also varied considerably, as would be expected with a 

varied mineralogy. Concentrations of the elements Al, Ca, Sr, Na, K, Mg, Be, Co, Hg, Cr, Ti, V, 

and Zn were as expected 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 almost 

certainly due to complex natural transport and diagenetic processes, not to human activity. The 

strong Ba enrichments of up to almost a factor of ten in a few samples are almost certainly 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. 

 5.3.4.2 Trace Organic Contaminants 

 Polynuclear aromatic hydrocarbons (PAH) are a major toxic component of petroleum. It 

is important to determine the sediment concentrations of PAH in order to see if they are present 

at levels that might be expected to cause biological effects. The major sources of PAH in 

offshore sediments include natural petroleum seepage, offshore production platform operations 

and spills. Previous studies around production platforms showed that sediments close to 

platforms (<500 m) contained discharged drilling muds and cuttings. Hydrocarbons, including 

PAH and trace metals (Ag, Ba, Cd, Hg, Pb, and Zn) contaminants, were associated with these 

coarse-grained sediments (Kennicutt et al. 1996). However, contaminant concentrations 

including PAHs close to platforms were below concentrations thought to induce biological 

responses. 

 Sediment samples collected on the shakedown cruise were analyzed for PAH. A total of 

five sediment samples were collected, four with the GOOMEX boxcorer and one with an 

USNEL spade corer. The total PAH concentrations ranged from 47 to 159 ng/g with a mean of 

113 ng/g and a relative standard deviation of 37%. These total PAH concentrations are low. The 

PAH concentration in samples collected with the USNEL spade corer was 108 ng/g and was 

close to the mean indicating the sampler type does not bias PAH results. The relative standard 

deviation of 37% is expected for the combined effects of analytical uncertainty (~10%) and the 
5-39 

natural inhomogeneity of sediments. These samples were collected at about 23.5 km (14.5 miles) 

southwest of Station W1 and 35.5 km (22 miles) west of Site W2. Samples collected at Site W2 

had a total PAH concentration of 53 ng/g and W3 a concentration of 41 ng/g which is within or 

slightly below the lower end of the range of total PAH concentrations from the shakedown 

cruise. 

 A total of 43 sediment samples were analyzed for PAH from DGoMB Cruise 1. These 

samples represent 41 stations with two sampling sites (W6 and MT3) being analyzed in 

duplicate. Concentrations for total PAH ranged from not detected (ND) to 1032 ng/g with a 

mean of 128 ng/g and a median of 59 ng/g. There were only nine samples (21%) with total PAH 

concentrations above 130 ng/g and only four (9.3%) with concentrations above 400 ng/g. Two of 

the samples with concentrations in the highest range (OC-615, 1033 ng/g and OC-618, 404 ng/g) 

were collected from MT-3. 

 The concentration of perylene is depicted for the sampling sites in Figure 5.27. Perylene 

is a PAH produced by biological processes. 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. Perylene is also produced from combustion or processing of fossil 

fuels (e.g., perylene is present in creosote made from the heating of coal). Due to its 

anthropogenic as well as biogenic origins, the total PAH data for this report is discussed both 

with and without perylene. Other PAH are predominantly from anthropogenic sources. The 

pattern of perylene concentrations (Figure 5.27) is not understood but it does not co-vary with 

the total PAH distribution. 

 The concentration of total PAH without perylene is depicted in Figure 5.28. Several sites 

had relatively high concentrations. These sites include MT1, MT3 (duplicate), C1, B1, and RW6. 

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 

MT3 (both), MT2, and B1, oil appears to be the major source of PAH. For RW6 and C1, 

combustion sources predominate. Combustion PAH in the sampling area may be discharged 

from ships or platforms (e.g. bilge pumping) or atmospheric deposition of PAH from onshore 

industrial 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 total PAH concentration without perylene is plotted versus barium concentration in 

Figure 5.29. Most of the sites plot near the origin because they have low PAH and low barium 

concentrations. Five sites have high barium concentrations (MT2, MT1, MT3, C1, and WC5). 

Four of these sites also have high PAH concentrations [MT3 (duplicate), MT1 and C1]. Barium 

is a tracer of drilling muds from platform operations. The elevated barium and PAH at the MT1, 

MT2, MT3, and C1 sites are likely due to inputs from platform operations in the vicinity of these 

sites. 

 A frequency distribution for total PAH and total PAH without perylene concentrations 

are plotted versus cumulative percentage (Figure 5.30). The concentrations are plotted on a log 

scale. It is apparent that the distributions are similar “S” shaped curves. The addition of perylene 

causes a slight increase in concentrations over the entire range. The median concentration for 

total PAH 
5-40 

Figure 5.27. The concentration of perylene in sediments. 
5-41 

Figure 5.28. The concentration of total polycyclic aromatic hydrocarbons (PAH) without perylene in 
5-42 

Figure 5.29. The total PAH concentration without perylene versus barium concentration. 

Ba ppm 
5-43 

Figure 5.30. Frequency distribution of total PAH and total PAH without perylene concentrations versus cumu
5-44 

is 59 ng/g and for total PAH without perylene is 45 ng/g. This indicates the relative importance 

of perylene, especially at low concentrations. Similar frequency distributions for total PAH were 

reported for the GOOMEX program (Kennicutt et al. 1996) and the cumulative curves had 

similar shapes. The concentrations of PAH found in close proximity to production platforms 

ranged from 10 to 6400 ng/g with the highest concentrations close to the platforms. However, 

most concentrations were less than 1000 ng/g (Kennicutt et al. 1996). The frequency distribution 

for total PAH for the GOOMEX study (Kennicutt et al. 1996) is similar to the distribution found 

here with the exception of the few concentrations that exceeded 1000 ng/g in this study. When 

the frequency distributions found in this study are compared to those for nearshore studies 

(NOAA NS&T and EPA-EMAP-NC), the median PAH concentrations for this study is lower by 

about a factor of four. Total sediment PAH concentrations greater than 4000 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 (1032 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. 

 In summary, concentrations of PAH measured for the DGoMB project from offshore 

Gulf of Mexico sites are low, as expected. Perylene, a PAH with a biogenic source, is the major 

PAH detected at many locations. Four sites that have high PAH concentrations [MT3 

(duplicate), MT1 and C1] also have high barium concentrations. This indicates that drilling 

operations in the vicinity of these sites is a likely source of PAH. Total sediment PAH 

concentrations all sites were less than 1040 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. 

 5.3.4.3 Biogeochemistry 

 Survey samples from DGoMB Cruise 1 have been completed, but survey samples from 

the Cruise 2 are only partially processed at this time. The geochemical data from Cruise 1 has 

been provided to the central DGoMB database. Discussion will be limited to issues arising from 

the data that are of specific interest to the assessment of future sites and parameters to be studied 

in the “experimental” phase of the program. 

 Approximately one-third of the sites exhibited clear (>~4%) sulfate reduction, with a 

few sites showing extensive sulfate reduction. Unlike most sulfidic sediments, there were not 

accompanying elevated concentrations in other bioreactive components such as nutrients, DOC 

and organic-C. This raises the question as to why no readily apparent correlation exists among 

these chemical components. One speculative possibility is that normal infalling particulate 

organic carbon from overlying waters is not the dominant source of metabolizable organic 

matter at these sites. This area is well known for its hydrocarbon seeps that may locally form 

the basis of the food web for benthic communities at these sites (e.g., MMS CHEMO program). 

The biologic oxidation of hydrocarbon gases does not contribute dissolved nutrients. Also, their 

presence may not significantly contribute to total organic or dissolved organic carbon pools. It 

is recommended that future studies add measurements of hydrocarbon gases such as methane to 

the program to test this hypothesis as it could be important in determining the distribution and 

composition of benthic communities. 

In only one sample (MT3) was the weight percent calcium carbonate relatively low 

(6%). In most other samples it ranged between 20% to 60%. It is interesting that there is no 
5-45 

readily apparent pattern in the geographic distribution of calcium carbonate. This calls into 

question the hypothesis that there could be an east to west influence of sedimentary carbonate 

on benthic community structure. A possible explanation for the observation is that the carbonate 

is primarily derived from pelagic sources such as forminifera that are relatively evenly 

distributed. 

 Differences in mean concentrations were observed for silicate, nitrite, ammonia and urea, 

but averages were surprisingly constant for nitrate and phosphate (Figure 5.31a,b,c). DOC mean 

concentrations were also variable, but standard deviations were high. Isotopic ratios of DIC were 

similar at all stations except MT3. 

 5.3.4.4 Geochemical Processes 

Results indicating the highest possible sulfate reduction rates are based on estimates, so 

they should be taken with extreme caution. At all stations, sulfate reduction rates were low but 

fall within the expected range as noted by a previous study of ~100 mmol/m2

*day (Lin and 

Morse 1991). S36 shows the highest rates at 132 mmol/m2

*day, while MT3 and MT6 were close 

to each other at 63 and 59 mmol/m2

*day respectively, and finally S42 was at 35 mmol/m2*day. 

 Microelectrode cores measurements were also made at the processes stations and the data 

are now complete. At site MT3 a good profile was obtained with strong evidence of manganese 

reduction (Figure 5.32). Profiles were measured every 2 mm from water-sediment interface to 2 

cm, then measured every 5 mm to 15 cm sediment depth. Values for pH were similarly profiled 

with typical values around 8.0. Oxygen concentrations were depleted to zero soon below the 

water-sediment interface. After oxygen disappears, manganese and sulfide concentrations begin 

to increase. Highest manganese concentrations occurred at depths of 3-8 cm. After 8 cm, 

manganese concentrations decrease indicating a possible layer change. No iron was detected 

throughout the core. At site MT6 oxygen concentrations were significantly higher in both the 

water column and in sediment porewaters. Oxygen was present to 8 cm in the core. This was a 

result of the top 2-3 cm being high in water content. The oxygen may have oxidized any reduced 

manganese or iron present in the core. Sulfide concentrations however co-existed with oxygen 

for part of the profile. A possible explanation presumes that bacterial respiration rates for sulfate 

reduction must have been faster than the rate of sulfide oxidation. Sulfide values were very low, 

and sulfide appeared around 2.5 cm. At site S36 oxygen concentrations penetrated to a depth of 

around 4 cm. There was slight overlap between sulfide and oxygen concentrations. The profile 

was similar to MT6, however, there was a small increase in sulfide concentrations between 4 and 

7 cm depth. Even the highest sulfide concentrations were low, averaging around 2μM. No iron or 

manganese was detected. Site S42 was profiled with success and characterized by deeper oxygen 

penetration depths and low sulfide concentrations (>2.0 μM). Oxygen penetrated to about 3 cm, 

where low sulfide concentrations began to occur. This site appeared similar to the other sites. No 

iron or manganese was detected here either. pH was profiled using a Cole-Parmer semimicroelectrode. Hansson’s buffer was used to calibrate the electrode at around 8.3. The sediment 

may have had adverse effects on the electrode, creating inaccurate readings. A side experiment 

was performed using squeezed porewater to measure pH as opposed to sediment porewater 

profiling. 

 Analyses of nutrients, dissolved organic carbon (DOC) and dissolved inorganic carbon 

(DIC) isotope ratios (δ13C) at process stations have been completed, but DIC concentration and 

elemental analyses of sediments are yet to be completed. Site MT3 was most active, showing 
5-46 

Figure 5.31a. Mean HSiO3

-

 and HPO4

2- (μM) concentrations at survey stations (see Figure 

4.1 for station locations). 
5-47 

Figure 5.31b. Mean NO3

-

 and NO2

-

 (μM) concentrations at survey stations (see Figure 4.1 

for station locations). 
5-48 

Figure 5.31c. Mean NH4

+

 and urea (μM) concentrations at survey stations (see Figure 4.1 

for station locations. 
5-49 

Figure 5.32. Depth-concentration profiles for DGoMB process stations (see Figure 4.2 for station lo

Oxygen (uM)Mn (II+) (uM)Fe (II+) (uM)S (II-) (uM)

0 50 100 150 200 250

0 2 4 6 8 10

MT6 

Fe (II+) and S (II-) (uM)

O2 and Mn (II+) (uM)

-20

0

20406080

100120140160180200

0 50 100 150 200 250

0 2 4 6 8 10

MT3

Depth (mm)

O2 and Mn (II+) (uM)

Fe (II+) and S (II-) (uM)

0 50 100 150 200 250

0 2 4 6 8 10

S36

O2 and Mn (II+) (uM)

Fe (II+) and S (II-) (uM)

0 50 10

0 2 4 

O2 and 

Fe (II+) a
5-50 

strong trends with depth, particularly for phosphate, ammonium and urea (Figure 5.33). Depth 

profiles for DOC were similar at all sites, but evidence for mineralization of organic matter was 

provided by the δ13C of DIC at stations MT3 and MT6 (Figures 5.34a,b,c and 5.35). The 13Cdepleted value measured at station S42 may be an outlier. Finally, comparison of total inorganic 

nitrogen (TIN) and phosphate with the expected slope of 16:1 suggests loss of nitrogen to 

denitrification (Figure 5.36). 

 The radiochemistry group is processing the radiochemical samples. Four sediment cores 

were thawed in the laboratory, sectioned at 0.5 cm intervals down to 4 cm, at 1 cm intervals 

down to 20 cm at 1 cm intervals, and below that, at 2 cm intervals. All samples were initially 

weighed, dried, then reweighed, in order to calculate the porosity of the sediments. Preliminary 

gamma counting results for 210Pb, 226Ra, 7

Be, 137Cs, and 234Th are available. 210Pb have been 

alpha counted using a method that yields more accurate results. 137Cs and 7

Be activities were low 

in all the samples and will not yield useful results. 210Pbxs profiles are produced by sedimentation 

and mixing, and require an independent mixing tracer to derive sedimentation rates. Profiles of 

239,240Pu will be required, since 137Cs activities are too low. 239,240Pu analyses are in progress. 

Preliminary results indicate mixing depths varying from 1 to 6 cm. The extent of excess210Pb (210Pbxs) penetration into surface sediments (Table 5.4) also varies over an order of 

magnitude, ranging from 2 to 18 cm for the four stations. This layer, which contains sediments 

which had accumulated or have been mixed downward over the past century or so roughly 

coincides with a layer of the greatest porosity gradient. 

 5.3.5 Biological Studies 

 All size categories of the sediment-associated biota were sampled on Cruises 1 and 2. 

These included 1) microbiota, 2) meiofauna, 3) macrofauna, 4) megafauna and 5) demersal 

fishes. Each fraction was fixed and labeled aboard ship as described above and distributed to 

respective PI’s immediately at the end of the cruise. Analyses of the biological samples are 

continuing. 

 5.3.5.1 Microbiota 

 The bacterial component of the overall project includes assessments of benthic bacterial 

abundance throughout the study region (survey stations) and benthic bacterial biovolume at 

selected stations (to convert abundance to biomass in a region-specific manner, rather than using 

published conversion values). Procedures for determining bacterial abundance and biomass rely 

on established methods in epifluorescence microscopy in all cases. Microscopic methodologies 

have been consistent between sampling Cruises in 2000 and 2001, and will be continued in the 

future, so that the results can be easily compared not only on spatial scales, between stations, but 

also on temporal scales, between sampling efforts. 

 Deviations from the original plan include a change in the method for assessing bacterial 

production. The use of 14C-labeled amino acids was proposed to estimate the rates of bacterial 

carbon incorporation (biomass maintenance and increase, an indirect measurement of 

production) and respiration (loss as CO2) in the presence of labile or readily consumable organic 
5-51 

substrates. 
5-52 

Figure 5.33. Mean DOC concentrations (mg/L) and DIC stable carbon isotope isotope (‰) 

values at process stations (see Figure 4.2 for station locations). 
5-53 

Figure 5.34a. Variation in HSiO3

-

 and HPO4

= concentrations with depth in the core (see 

Figure 4.2 for station locations). 
5-54 

Figure 5.34b. Variation in HSiO3

-

 and HPO4

= concentrations with depth in the core at 

process stations (see Figure 4.2 for station locations). 
5-55 

Figure 5.34c. Variation in HSiO3

-

 and HPO4

=

 concentrations with depth in the core at 

process stations (see Figure 4.2 for station locations).
5-56 

Figure 5.35. Variations for DOC concentrations (mg/L) and DIC stable carbon isotope 

composition (‰) with depth in the core at process stations (see Figure 4.2 for

station locations). 
5-57 

Table 5.4. Summary of preliminary results. 

Station # Boxcore # Sample ID # Bioturbation Depth (cm) 210Pbxs

 234Thxs 210Pbxs layer depth (cm) 

 

MT3 P-2 1 6 6 17 

S36 P-2 11 1 4 18 

MT6 P-1a 15 1 1 2 

S42 P-2 9 2 2.5 10 

 

Figure 5.36. Total inorganic nitrogen (TIN; μM) and phosphate (HPO4

=

; μM) 

concentrations. The 16:1 line is shown. 
5-58 

After additional consultation regarding modeling goals and ways to maximize bacterial and 

meiofaunal activity measurements, it was decided to use 3

H-thymidine to directly measure 

bacterial growth on the process cruises. This approach incorporates labeled thymidine into the 

DNA fraction of the resident cells presumably directly reflecting new cell production, regardless 

of what naturally available organic substrates are being consumed. Measuring bacterial 

production in this manner thus circumvents assumptions required to convert activity based on 

labile 14C-substrates to total activity based on the in-situ suite of naturally available organic 

compounds. Incorporation of 3H-thymidine also effectively labels growing cells so that their fate 

as prey for meiofauna can be tracked, supporting the modeling goal to link one class of 

organisms to the next. There is precedent for use of the 3

H-thymidine approach to measure 

bacterial activity in deep-sea sediments, so comparable results are available in the literature. 

3

H-thymidine was originally proposed because the laboratory sample-processing scheme 

is more complex. Labeled DNA must be extracted and separated from other components of the 

sample using a more time-intensive protocol than is involved with 14C-amino acid experiments 

and the team is not experienced in the new methods. However, advice from practitioners ensured 

success. Because of original interests in bacterial respiration, as well as production, a simple 

protocol was added that assesses the fraction of the total bacterial community that is actively 

respiring oxygen. This method relies upon the use of an electron-transport-specific stain (CTC 

stain) for visual discrimination of oxygen-respiring cells under epifluorescence microscopy. 

Thus it was added to the cruise activities without too much additional shipboard sampleprocessing time. The results may allow comment on bacterial respiratory activities, if actual 

production rates appear low. 

 The main goal of DGoMB Cruise 1 was to obtain benthic bacterial abundance 

measurements at each of the survey stations. The plan included sampling subcores from each of 

five boxcores per station at each of four depths (0, 5, 10, and 15 cm), so that abundance values 

could be integrated over depth to obtain a station value in terms of number of bacteria per square 

cm. By determining mean biovolume in selected samples and using a carbon conversion value 

from the literature, total bacterial abundance can be converted to total bacterial biomass. 

 Of the 832 samples collected, 565 samples or 68% have been analyzed for bacterial 

abundance by epifluorescence microscopy, scaled to a cubic centimeter of sediment. Sediment 

dry weight analyses have also been completed on these samples, if scaling to that parameter 

ultimately proves desirable. The remaining 32% of the samples have been archived and will not 

likely be analyzed. They represent primarily the fourth or fifth subcores collected per station and 

do not provide significant statistical improvement of the mean value already obtained from 

triplicate samples. Thus, 100% of the samples required to meet the main goal of obtaining depthintegrated values for bacterial abundance per station are completed. Of the 48 samples selected 

to date (four depths, each in triplicate, from each of the four process stations) for biovolume 

analyses, 25% have been analyzed. As this work is particularly tedious, complete results should 

be available by the end of 2001. At that time, abundance measurements will be converted to 

biomass. 

 In advance of the biovolume data, a preliminary analysis of the benthic bacterial 

abundance measurements has been conducted in terms of the proposed hypotheses. In general, 

bacterial abundance decreased with depth in the sediment at any given station; the only station 

where a subsurface peak was observed, was station NB5, indicative on little bioturbational 
5-59 

mixing (see Section 5.3.3 and Figure 5.24). A plot of mean benthic bacterial abundance at each 

station (bacteria per cm2

, 0-15 cm depth integration) versus station depth (Figure 5.37; where 

error bars represent the standard deviation of the mean value from triplicate core data) reveals 

only a slight trend towards an inverse relationship (r2

 = 0.095). This trend becomes slightly 

stronger (r2

 = 0.173), if the stations representing unusual topographic features (WC, B, NB, or 

AC station designations) are omitted from the analysis (Figure 5.40). As the data set is sizeable 

(and the most extensive of its kind), additional station or sampling density would not likely 

improve the trend. However, future analyses based on data conversions to biomass, or logtransformed data, may yield a more compelling test of the hypothesis that water depth 

determines benthic bacterial community size in the Gulf of Mexico. 

 There is no support, based on preliminary analyses, for the hypothesis that an east-west 

gradient in bacterial biomass exists along the sampling sites (Figure 5.38), but the analysis to 

date is only cursory. In a comparison of basin, non-basin and canyon stations, canyon stations 

may have slightly lower bacterial abundances, but more data analysis (and perhaps a greater 

sampling density at such stations in the future) is required to determine whether the trend is 

significant (Figure 5.39). Following the overall slight inverse relationship between bacterial 

abundance and water depth, deep stations along the Sigsbee sampling section support lower 

numbers of bacteria than do the shallow stations, though again, further statistical analyses are 

required to confirm the significance of the trend (Figure 5.42). Although the data set for testing 

the hypothesis of higher benthic biomass underlying regions of higher primary production is 

limited, a trend (r2

 = 0.545, the strongest trend among our preliminary analyses) was observed in 

support of the hypothesis (Figure 5.41). At this time, the testing of the remaining hypotheses is 

not possible. 

 Of the 189 samples collected for bacterial abundance determinations on DGoMB Cruise 

2, none have been analyzed in deference to processing samples from the 3

H-thymidine rate 

measurement experiments. All bacterial counts (and sediment dry weights) from Cruise 2 will be 

available by the end of 2001. The extra samples taken for CTC-stain analyses will be processed 

prior to the total counts, due to sample storage issues, and should be available in October, 2001. 

Of the samples from the thymidine experiments, 75% of them have been processed in the 

laboratory. The remaining 25% will be completed by the end of September, 2001. The data will 

then be analyzed and rates calculated by the end of October, 2001. 

 Although comment is not possible on absolute rates until all of the samples and related 

controls have been processed and analyzed, enough of the raw data is available to make the 

following observations. Injection of 3

H-thymidine into whole-core samples of the sediments, the 

approach most closely mimicking in-situ conditions, yielded detectable and, by visual inspection, 

significant increases in thymidine incorporation into DNA over the course of the shipboard 

incubation experiments. Rates for each of the four stations should thus be available when all of 

the analyses are completed; i.e., the method was successful. The various experiments performed 

on sediment dilutions have so far provided equivocal results with apparently little detectable 

activity. Additional analyses may allow retrieval of information from these experiments, but at 

the moment, it is anticipated that future cruise work will center on whole-core injection 
5-60 

Figure 5.37. Benthic bacterial abundance as a function of depth. 

Figure 5.38. Benthic bacterial abundance from the east to west Gulf of Mexico. 
5-61 

Figure 5.39. Benthic bacterial abundance comparisons for basins, non-basins, and 

canyons. 

Figure 5.40. Benthic bacterial abundance as a function of water depth (no WC, B, NB, 

or AC stations). 
5-62 

Figure 5.41. Benthic bacterial abundance related to primary productivity 

(low vs high). 

Figure 5.42. Benthic bacterial abundance related to Sigsbee Escarpment (shallow vs. 

deep). 
5-63 

approach. If the thymidine approach can be streamlined, then it may be possible to add protocols 

that use 14C-amino acids as well. Having both types of measurements strengthens any 

conclusions eventually drawn regarding growth versus respiration. 

 In designing the thymidine approach, experiments were conducted with and without the 

application of in-situ hydrostatic pressures during the shipboard incubation period. Again, 

comment on absolute rates cannot yet be made, but a comparison of relative increases in raw 

data (cpm from the scintillation counter printout over incubation time) makes clear that the only 

case of a positive pressure effect (faster uptake under pressure) occurred at the deepest of the 

four process stations (MT6 at 3000 m). At the next deepest station (S36 at 1800 m), the pressure 

effect appears to be minimal. At the two shallow stations (MT3 at 1000 m and S42 at 750 m), 

pressure appears to have a negative effect; i.e., rates are faster at atmospheric pressure. As a 

practical matter, these results indicate that pressure equipment is only needed for deep water 

stations. As a scientific matter, these preliminary results fit predictions from pure culture work 

that positive pressure effects (barophily) should not be detected at depths shallower than 2000 m. 

This data set represents the first field test of this concept across a suitable range of station 

depths. 

 5.3.5.2 Benthic Foraminifera 

A total of 984 foraminifera were extracted for ATP on the DGoMB Cruise 2 (Table 5.5). 

When combined with the 324 specimens extracted during the R/V Atlantis cruise in October 

2000, a total of 1308 foraminifera have been extracted for ATP. Samples were taken at all 

process stations as well as at an additional two stations during the process cruise (C-7 and Bush 

Hill). Only the top cm was processed for the survey site cores. At S36 there was an abundant 

community of arborescent foraminifera (up to 5 cm in height), six of which were analyzed for 

ATP although none occurred in the foraminiferal biomass core. It is likely that these comprise a 

major portion of biomass at this station. 

Each ATP extract has been analyzed with the luciferin-luciferase reaction and data is 

being processed. It is expected that final results (i.e., mg C/m2

 per station) will be available by 

the end of 2002. It is too early to make any predictions about data outcome and the relative 

contribution of the foraminifera to benthic biomass. 

 Although the original plan was for five replicate cores to be analyzed per process station, 

this proved to be unrealistic due to (1) time constraints on coring for “process samples” and (2) 

shipboard space for additional personnel. As originally agreed, 50 foraminifera were individually 

extracted for ATP from each of three sediment depth intervals per core. The interval depths 

changed slightly from the original plan in order to correspond with those being analyzed for 

meiofauna. The depth intervals analyzed were 0-1, 1-3, and either 9-10 or 14-15 cm, depending 

on core length. The depth of 9-10 cm was required since some cores were short. In all cases, the 

deepest interval was located below a change in sediment fabric and the apparent redox boundary. 

The original depth intervals proposed were 0-1, 4-5, and 9-10 cm. 

 The temperature of the overlying water in the boxcores was often quite high (>18°C). 

Given that ambient temperatures at the sites are <10°C, this thermal difference could be 

detrimental to the foraminifera. Some of the foraminifers may have expired in the time it took for 
5-64 

boxcore recovery and subsampling. Water overlying the boxcores was also murky sometimes 

indicating that the boxcore had been disturbed. If serious discrepancies in in situ respiration rates 

and shipboard analyses on box-cored material occur, the thermal shock and disturbance may 

account for such differences. 

Table 5.5. Foraminifera extracted for ATP. 

Station Depth Interval 

(cm) 

Number Extracted 

 

Process Stations 

MT3 0-1 53 

 1-3 50 

 14-15 50 

MT3 Replicate 0-1 50 

 1-3 50 

 9-10 50 

S42 0-1 50 

 1-3 50 

 9-10 50 

S36 0-1 75 

 1-3 50 

 14-15 50 

“tree” forams from other boxcores 6 

MT6 0-1 50 

 1-3 50 

 9-10 50 

 

Non-Process Stations 

C7 0-1 50 

 1-2 50 

Bush Hill 0-1 50 

 1-2 50 

 

Total for DGoMB 2 984 

Atlantis Cruise (10/00) 

Farnella Canyon 

(Alvin dive 3628) 

0-1 130 

 

Green Canyon 66 

(Alvin dive 3629) 

0-1 28 

 

Green Canyon 67 

(Alvin dive 3629) 

0-1 40 

 

N. Florida Escarpment 

(Alvin dive 3634) 

0-1 

2-3 

100 

26 

 

Total for Atlantis cruise 324 
5-65 

 5.3.5.3 Meiofauna 

 A general linear relationship is observed between meiofauna abundance (n/m2) and water 

depth (Figure 5.43). However, there is variability in the regression (R2

 = 0.4042), indicating 

factors other than depth also influence abundance. The main factor appears to be spatial variation 

of meiofaunal abundance as well as the relationship with depth (Figure 5.44). The deeper 

stations in the northwestern Gulf of Mexico have high abundance. The highest meiofaunal 

abundance values are found in relatively shallow depths in the Mississippi Trough and DeSoto 

Canyon. 

 Biomass also generally decreased with depth (Figure 5.45); however this relationships is 

weaker (R2

 = 0.3267) than for abundance. The spatial variation from station to station is 

heterogeneous for biomass (Figure 5.46). However, some stations in the eastern transects were 

not complete with respect to biomass, and completion of these samples will likely change any 

conclusions. Highest meiofaunal biomass was observed at stations C4, WC12, and W3. The 

eastern Gulf will likely have high biomass values associated with the Mississippi Trough and 

DeSoto Canyon corresponding to high abundance measurements. 

The relationship of major taxa diversity to depth is weak (Figure 5.47, R2 = 0.126). 

Higher diversity was observed in the western Gulf than the eastern Gulf (Figure 5.48). Highest 

diversity values appear to occur at mid-water depths along transects. Harpactcoid species 

identifications are not yet sufficiently complete to make preliminary conclusions based species 

level diversity. 

There was a weak linear relationship (R2

 = 0.2874) between bacterial abundance and 

meiofaunal abundance (Figure 5.49). There was significant deviation from the regression and 

considerable heterogeneity of variance. A relationship between meiofaunal and bacterial 

abundance would be expected if there were a strong trophic coupling between these two 

components. 

The goal of this program is to provide an understanding of relationships between the 

biological, chemical, physical and geological factors that are regulating structure and function of 

benthic communities. Community ecologists have argued for years over whether biological or 

physical factors in the environment are responsible for shaping benthic communities. Both 

factors are important. It is only in recent years it has been realized that there are significant 

interactions between the biotic community and that the physical, chemical and geologic 

environment. Thus, this program seeks to uncover these interactions. 

 The importance of depth in shaping meiofaunal communities is one of the primary 

hypotheses of this program. In general meiofaunal abundance, biomass, and major taxonomic 

diversity decrease with depth. Depth is evidently important; however other factors also influence 

ecology in the deep-sea. 

 Topographic features such as the Mississippi Trough and the DeSoto Canyon appear to 

have higher abundance and biomass, but lower major taxonomic diversity. These may be areas 

where POC accumulate, fueling increased productivity. These features are located in the eastern 
5-66 

Gulf where eutrophic conditions in overlying waters could be fueling more productive benthic 
5-67 

Meiofaunal Abundance vs. Depth

R2 = 0.4042

0

100000

200000

300000

400000

500000

0 500 1000 1500 2000 2500 3000 3500

Depth (m)

Abundance (n/m 2)

Figure 5.43. Relationship between meiofaunal abundance and water depth. 

Figure 5.44. Relative meiofaunal abundance at each station. 
5-68 

Meiofauna Biomass vs. Depth

R2 = 0.3267

0.0

0.1

0.2

0.3

0.4

0.5

0 1,000 2,000 3,000

Depth (m)

Biomass (g ww/m2

)

Figure 5.45. Relationship between meiofaunal biomass and depth. 

Figure 5.46. Relative meiofaunal biomass (g ww/m2) at each station. Note, small 

dots indicate no data. 
5-69 

Figure 5.47. Relationship between major meiofaunal taxa diversity (Hill’s number, 

N1) and depth. 

Meiofaunal Taxa Diversity vs. Depth

R2 = 0.126

2.00

2.50

3.00

3.50

4.00

4.50

0 500 1000 1500 2000 2500 3000 3500

Depth (m)

Major Taxa Diversity (N1,

pooled replicates)

Figure 5.48. Relative major meiofaunal taxa diversity (N1) at each station. 
5-70 

communities. It is common for diversity to be lower in trophically enriched environments 

(Peterson et al. 1996). Higher major taxa diversity was observed in the western Gulf than the 

eastern Gulf. Conversely, abundance and biomass were lower in the western Gulf. This trend in 

the more oligotrophic waters in the western Gulf is consistent with the “trophic enrichment” 

hypothesis. 

A weak relationship between bacterial and meiofaunal abundance is surprising. Several 

explanations of this observation are possible. This may indicate that bacteria are not an important 

food source for meiofauna in the deep-sea, or conversely that meiofaunal communities are 

controlled by predation. It is likely that both processes are important. 

 In regards to the original eight hypotheses, trends in preliminary data for the meiofauna 

community indicate depth is important, there are east/west differences, and there are differences 

due to the influence of canyons. Clearly, several environmental factors collectively control 

meiofaunal community structure and these variables are interrelated. 

 5.3.5.4 Macrofauna 

 A total of 215 GOMEX boxcores were taken during DGoMB Cruise 1 to provide detailed 

information about the communities of organisms that live in continental slope communities. The 

samples were sieved at sea using a 300 micrometer mesh and then preserved in 10% buffered 

formalin and sea water solution. In the laboratory they are then sorted to major taxonomic group, 

switched to an alcohol preservation, and then distributed to various taxonomists around the 

world for identification to species (list of taxonomists). 

 The quantitative information on macrofauna from the boxcores is being analyzed to test 

several of the eight hypotheses that were proposed originally in this project. This is an initial 

consideration of the data that are presently available. Since considerably more information will 

eventually be developed, all these initial assessments must be taken with caution. Nonetheless, 

there is no reason to expect that the general patterns presented here will change as more data are 

accrued. Regressions of macrofauna animal density as a function of depth for the entire data set 

Figure 5.49. Relationship between meiofaunal and bacterial abundance. 

Meiofauna Abundance vs. Bacterial 

Abundance

R2 = 0.2874

0

50000

100000

150000

200000

250000

300000

350000

3.0E+08 8.0E+08 1.3E+09 1.8E+09

Bacterial Abundance (cells/cc sediment)

Meiofauna Abundance

(n/m2

)
5-71 

indicate that mean density declines with depth from about 10,000 down to about 3,000 ind./m2

 at 

the base of the escarpment (~3,000 m; Figure 5.50). The variability of these values is extremely 

high, however, from estimates of more than 30,000 down to less than a 1,000 ind./m2

. Variability 

seems to decline with depth. As the highest densities were found in eastern GOM at the S 

locations or in the MT sites (Mississippi Trough), it is worth noting that if these sites are 

excluded from the analysis, then the extreme highs are eliminated and the mean at the shallow 

sites goes down to just less than 8,000 ind./m2

 (Figure 5.51). The Mississippi Trough (MT) sites 

plotted by themselves as a function of depth down the canyon (Figure 5.52) illustrate that the 

extreme highs nearshore are found at the canyon head. However, the tendency for the canyon to 

have higher values lessens with depth (MT5 and MT6). The mean at the shallow station was 

approximately 16,000 ind./m2

, or well above the average mean for the entire set of data. MT5 

and 6 are both characterized by quantities of iron stone material mixed into the sediments. It was 

sampled with the box core and the trawl and it is visible in bottom photographs. It does not form 

a pavement, however, as has been observed in deeper waters, but appears as a bumpy, redcolored material in irregular patches at the sediment surface. 

 The sites in the eastern GOM illustrate several features that are unique to that area 

(Figure 5.53). The samples have been partitioned between those lying east and those lying west 

of the DeSoto Canyon axis. Those to the east form a series of samples across the west Florida 

slope and steep escarpment. Those on the west side lie on the eastern margin of the Mississippi 

cone. While the eastern samples form a general pattern that declines with depth, with a mean 

trend line that more or less mimics that of the entire sample set, the macrofauna at sites west of 

the axis do not follow the typical pattern with depth. All of the macrofaunal abundance values 

are higher than their eastern counterparts and the highest values are at S36 at a depth of 1850 

meters. The high density macrofauna at this intermediate depth suggests that the site is unique 

among the sites sampled to date. 

 The patterns of macrofaunal abundance can be used to infer the locations where the input 

of organic matter is accentuated within the study area. In general, the western GOM is 

characterized by lower densities than the eastern GOM, leading to the assumption that the 

organic matter available to the deep benthos is less in the west than in the eastern GOM. This is 

unexpected since the Mississippi River generally flows to the west and the eastern GOM is 

characterized by the warm relatively unproductive waters of the loop current. The high 

abundance values in the upper reaches of the Mississippi Trough reflect larger inputs of organic 

matter that can be assumed to be related to the Mississippi River. This could either be direct 

input from river-borne material or enhanced primary production that accumulates in the trough 

where it intersects the continental shelf just west of the delta. The differences in the densities on 

the two sides of the DeSoto Canyon suggest that in general Mississippi cone sediments are 

enriched in carbon compared to those off Florida. The cone sediments are primarily terrigenous 

and it might be assumed richer in organics than the predominantly carbonate sediments off west 

Florida. The high numbers at S36 near the canyon axis suggest that perhaps this is a location of 

organic matter accumulation. It is also worth noting that the surface water over and just inshore 

of S36 is thought to be characterized by unusually high productivity for the GOM, probably due 

to the incursion of high nitrate water onto the upper slope and continental slope. 
5-72 

y = -2.92x + 10613

R2

 = 0.30; N = 109

0

10,000

20,000

30,000

40,000

0 1000 2000 3000 4000

Depth (m)

Number m-2

Figure 5.50. Total macrofaunal densities by depth with the regression line and formula, 

R-squared value, and number of samples involved. 

y = -2.19x + 8045

R2

 = 0.46; N = 71

0

10,000

20,000

0 1000 2000 3000 4000

Depth (m)

Number m-2

Figure 5.51. Total macrofaunal densities by depth except samples from the Mississippi 

Trough (MT) and eastern (S) Gulf. 
5-73 

MT1-3

MT1-2

MT1-1

MT3-1

MT3-3

MT3-2

MT4

MT5

MT2

MT6

y = -7.02x + 19477

R2

 = 0.51; N = 15

0

10,000

20,000

30,000

40,000

0 1000 2000 3000 4000

Depth (m)

Number m-2

Figure 5.52. Total macrofaunal densities by depth plotting all sorted samples from the 

Mississippi Trough (MT). 

Figure 5.53. Total macrofaunal densities by depth plotting all sorted samples from the 

eastern Gulf of Mexico (S). Samples from the western side of DeSoto Canyon 

are indicated by the closed circles ( ); those from east of DeSoto Canyon are 

indicated by open circles ( ). 

S35

S36

S44 S37

S43

S42 S38 S39, 40, 41

West of DeSoto Canyon

y = -2.17x + 15806

R2 = 0.14; N = 9

East of DeSoto Canyon

y = -2.12x + 8491

R2 = 0.60; N = 14

0

10,000

20,000

30,000

40,000

0 1000 2000 3000 4000

Depth (m)

Number m-2
5-74 

 The taxonomic composition of the macrofauna has not proved to be unique with only one 

exception that appears to also be related to animal densities. While the macrofauna of the entire 

GOM is dominated by polychaete annelid worms and macrofaunal sized nematode worms, in 

general, the macrofauna in the shallow head of the Mississippi Trough (MT1) is dominated in all 

the replicates by tube-dwelling amphipod crustaceans. Macrofauna-sized nematode worms are 

almost non-existent in the MT1 samples; those that were encountered are small in size. The 

surface of the sediments is characterized by the numerous tubes that the amphipods inhabit 

(Figure 5.54). At S36, another site of generally high animal densities, the nematodes were much 

more abundant and larger. The dominant macrofaunal taxon was the polychaetes, which is 

typical for fine-grained sediments. 

 5.3.5.5 Megafauna 

 Trawl samples were split into three components aboard ship: trash, invertebrates and 

fishes. Each animal was identified to the lowest possible taxon, weighed by taxon (by volume 

displacement) and preserved as appropriate in 5 gallon plastic tubs. Geographic location of the 

start and end of each trawl, ship's speed and time on bottom were all recorded and thus estimates 

can be made of the area covered by each trawl. A comparison can thus be made of animal 

densities in the trawl samples. The trash was not preserved but was stored wet sealed in 5 gallon 

plastic buckets. When there was too much for one container, it was photographed, weighed 

(when possible), discarded over the side (biodegradable material), or stored aboard ship for land 

disposal. During the cruises completed to date, 6,961 invertebrate specimens of at least 160 

species were collected in 36 beam and otter trawl samples. The majority were echinoderms and 

crustaceans (Table 5.6). 

Figure 5.54. Bottom photograph from Station MT1 at the head of the Mississippi 

Canyon. The odd, lumpy nature of the sediments is caused by dense 

populations of tube-dwelling amphipods that are characteristic of this 

unique environment. Depth is approximately 475 m. 
5-75 

Table 5.6. Larger invertebrate species from trawls. 

Taxonomic Group Number of Species 

 

Porifera (sponges) 4 

Cnidaria (corals, sea anemones, etc.) 12* 

Nemertea (ribbon worms) 1+ 

Polychaeta (marine segmented worms) 4*+ 

Pogonophora (beard worms) 1 

Crustacea (shrimp, crabs, etc.) 65 

Mollusca (clams, snails, etc.) 48 

Brachiopoda (lamp shells) 1 

Echinodermata (sea stars, etc.) 27* 

Urochordata (sea squirts) 1 

 

* indicates an estimate +indicates a group in which body size usually is too 

small to be caught in a trawl 

 Of the species taken, all have been given at least provisional assignments to species. 

However, at least one species each of sea anemone and tunicate are undescribed--not yet 

formally named by a biologist. Identification to species of some of the sponges, octocorals and 

sea anemones at present is not possible due to the need for a thorough revision of certain poorly 

studied groups. Although the echinoderms have been given provisional identifications, the 

identifications will be double-checked by Gordon Hendler, Natural History Museum of Los 

Angeles County. 

 The maximum number of specimens taken at a single trawl site was at site S-37, where 

1,614 specimens of 20 species were collected. Of these, 600 were a single species of sponge, 650 

were probably one species of brittle star and another 201 were the soft sea urchin, Phormosoma 

placenta. The most diverse site was MT-5, with 39 species and 477 specimens. Other diverse 

sites were C-4 (277 specimens, 31 species), NB-5 (321 specimens, 31 species) and S-41 (302 

specimens, 31 species). Sites with less than 50 specimens per trawl were C-1, B-2 (May), NB-2, 

RW-2, W-3 and WC-5. 

 Three of the crustaceans represented significant range extensions. The shrimp Sabinea 

hystrix and Benthesicymus carinatus, and the barnacle Neoscalpellum debile, have not been 

reported previously from the Gulf of Mexico. Munidopsis geyeri has not been reported 

previously from the northeastern Gulf of Mexico. 

 A list was compiled of all decapod crustacean species known at 200-3000 m in benthic 

environments of the Gulf of Mexico. For purposes of this study, the Gulf of Mexico was defined 

as having its southeastern boundary at the Dry Tortugas Islands, Florida. Species reported from 

“the southeastern Gulf of Mexico”, but never collected outside of the Straits of Florida, were not 

included. For all other species, historic records from the literature, cruise reports (including the 

DGoMB Cruise 1 sampling) and specimens in collections were compiled. One hundred forty-six 

species were reported in the area. 

 A data matrix was constructed by giving a numerical code to each two-by-two degree 

square of latitude and longitude in the Gulf of Mexico, starting with “1” for the northern tip of 

the Yucatan Peninsula, Mexico and going clockwise to “27” off the southern tip of Florida 
5-76 

(Table 5.7). Each species known from at least 10 individuals in the Gulf of Mexico, a total of 76 

species, was entered into a data matrix by squares in which it occurred. The data matrix contains 

the total number of stations and individuals taken per square per species, including all historical 

data. From this data matrix, all squares having at least 10 species per square were compared by 

presence/absence of species. (Some squares had fewer than 10 recorded species, probably due to 

a lack of sampling). The results indicate maximum species diversity and abundance from 

western Louisiana to the DeSoto Canyon. Square 21, containing the head of the DeSoto Canyon, 

had the greatest number of species (69 out of 76) and specimens. 

 Data for the larger crustaceans were also analyzed by cluster analysis by site. Except for 

some similarity by depth range, there were no discernable patterns of distribution of decapod 

crustaceans by sites. Sites C-4, MT-5 and S35 each had 13 species of large crustaceans, and 148, 

42 and 164 crustacean specimens, respectively. 

 Correlation of numbers and distributions of larger invertebrates with physical factors, 

geology and distribution of smaller organisms will be incorporated into the final program report. 

Previous studies have shown distributions related to depth. There is some indication of 

replacement of decapod crustaceans by other invertebrates, especially echinoderms, at deeper 

slope depths. 

 5.3.5.6 Demersal Fish 

All of the fish samples that were collected during DGoMB Cruise 1 (summer 2000) are 

processed, the historical benthic fish database of the Texas Cooperative Wildlife Collection 

(TCWC) for the northern Gulf of Mexico continental slope was proofed, and data were entered 

into a MS Excel data base. Taxonomic, numerical, and volumetric data for the fish specimens 

collected on the first summer cruise were sent to data management and for analysis. The 

historical fish data base for the study area consists of specimens collected on numerous fisheries 

surveys in the Gulf of Mexico over the last 60 years, including surveys by the research vessels 

Combat, Pelican, Silver Bay, Oregon, Oregon II, Gus III, Alaminos, Gyre, and numerous 

chartered commercial shrimp vessels. Most of these records included latitude and longitude 

coordinates, depth of capture, date of collection, vessel, and time of day. 

A total of 1073 individual fishes, representing 121 species and 142 families of benthic 

fishes, were collected. The families Macrouridae (grenadiers or rattails), with 21 species; 

Ophidiidae (cuskeels), with 15 species; and Alepocephalidae (slickheads), with eight species 

dominated the samples. Families of secondary importance are: Halosauridae (halosaurs), with 

four species, Ipnopidae (tripodfishes), with four species, Moridae (morid cods), with two or three 

species; and Trichiuridae (cutlassfishes) with two or three species. Discrepancies in number of 

species within families are due the inability to identify some fishes to species. Cluster analyses 

revealed that the fish fauna is zoned by depth (Powell, et al. unpubl. ms.). Species richness and 

abundance were highest on the upper slope (315-785 m) and decreased with depth (Powell et al. 

unpubl. Ms.). 
5-77 

Table 5.7. Geographic squares in the Gulf of Mexico 

Square Number Degrees North Degrees West Description 

 

1 22-24 88-90 N. Yucatan 

2 22-24 90-92 NW Yucatan 

3 22-24 92-94 SW Yucatan 

4 20-22 92-94 Paraiso 

5 18-20 92-94 Veracruz 

6 18-20 94-96 Veracruz 

7 20-22 94-96 Tuxpan 

8 20-22 96-98 Tuxpan 

9 22-24 96-98 Tampico 

10 24-26 96-98 N. Mexico 

11 24-26 94-96 N. Mexico 

12 26-28 96-98 S. Texas 

13 26-28 94-96 S. Texas 

14 28-30 94-96 Galveston 

15 26-28 92-94 Lake Charles 

16 28-30 92-94 Lake Charles 

17 28-30 90-92 Morgan City 

18 26-28 90-92 Morgan City 

19 28-30 88-90 Miss. Delta 

20 26-28 88-90 Miss. Delta 

21 28-30 86-88 Pensacola 

22 26-28 86-88 Pensacola 

23 28-30 84-86 Apalichicola 

24 26-28 84-86 Apalichicola 

25 28-30 82-84 Crystal River 

26 26-28 82-84 Tampa 

27 24-26 82-84 SW Florida 

 

Notes: Squares 19 and 20 supposedly are the zoogeographic “cut-off” 

or “boundary” area. In square 27, locations must be north of 

24o

 30'N, the southeastern boundary of the Gulf of Mexico. 

(Anything taken south of the Dry Tortugas is not considered to 

be in the Gulf of Mexico). 

 The TCWC has over 3,000 samples of fishes captured at depths greater than 300 m from 

the northern Gulf of Mexico between 84° and 96° W longitude. Proofing the data base was time 

consuming because about one quarter of the samples had missing data fields, including latitude, 

longitude, and depth. These data had to be located in survey data records such as Springer and 

Bullis (1956), Bullis and Thompson (1965), and Chittenden and Moore (1976); in cruise records 

of the Alaminos and Gyre; and in field notes housed in the TCWC. Also, because dates of 

capture and initial identifications ranged over a 60 year period, many of the identifications and 

much of the nomenclature had to be updated. It took several passes through the 3,000 records to 

rectify the data. The proofing process reduced the fish records to 2,296 for which missing data 

fields could be reconstructed and for which specimens could be reliably identified at least to 

genus. 

Based on DGoMB Cruise 1 and the holdings of the TCWC, the northern slope of the Gulf 

of Mexico has a diverse fish fauna of 364 species representing 108 families; however, 74 species 
5-78 

representing 12 families, are epipelagic or mesopelagic, and likely were caught in the water 

column prior to or after the sampling gear reached the bottom. The families Macrouridae, with 

37 or 38 species; Ophidiidae, with 24 or 25 species; and Alepocephalidae, with 14 or 15 species 

are represented by the most species and individuals. Families of secondary importance are 

Rajidae (skates), with nine or ten species; Ipnopidae, with seven or eight species, Triglidae 

(searobins), with seven or eight species; Squalidae (dogfish sharks), with six species, and 

Scyliorhinidae (catsharks), with five or six species. 

Species composition varied with depth of capture. A total of 149 species representing 64 

families were captured between 300 m and 500 m; however, 30 species representing 12 families 

were epipelagic or mesopelagic and were probably captured in the water column. The families 

represented by the most species were Macrouridae, with 18 species; Triglidae, with six species; 

Rajidae, with six species; and Scorpaenidae (scorpion fishes), with five species. Families of 

secondary importance were Squalidae, with four species; Ophidiidae, with four species; 

Moridae, with four species; and Ogcocephalidae (batfishes), with three species. 

Between 500 and 1000 m, 208 species representing 72 families were captured; however, 

48 species representing 12 families, were epipelagic or mesopelagic and were probably captured 

in the water column. The families represented by the most species were Macrouridae, with 26 or 

27 species; Ophidiidae, with 10 species; and Rajidae, with seven species. Families of secondary 

importance are Synaphobranchidae (cutthroat eels), with six species; Alepocephalidae, with five 

species; and Nettastomatidae (duckbill eels), with four species. 

Between 1000 and 2000 m, 114 species representing 43 families were captured; however, 

24 species representing nine families were epipelagic or mesopelagic and were probably 

captured in the water column. Families represented by the most species were Macrouridae, with 

22 species; Ophidiidae with 13 species; and Alepocephalidae, with 10 species. Families of 

secondary abundance were Ipnopidae, with four species, and Rajidae, Halosauridae, and 

Synaphobranchidae, with three species each. 

Between 2000 m and 3000 m, 71 species representing 33 families were captured; 

however, 25 species representing 10 families were epipelagic or mesopelagic and were probably 

captured in the water column. Families represented with the most species were Ophidiidae, with 

11 species, Ipnopidae with six species; and Alepocephalidae, with four species. 

 The historical data base includes the great majority of the benthic fishes either known or 

thought to inhabit the slope of the northern Gulf of Mexico (McEachran and Fechhelm 1998, 

unpubl. ms.). These data reveal, as did Powell et al. (unpubl. ms.), that the fish fauna is zoned by 

depth. The families Macrouridae, Triglidae, Rajidae, and Ophidiidae dominate the upper slope 

(300 to 500 m). The families Macrouridae, Ophidiidae, and Rajidae dominate the middle slope 

(500 to 1000 m). The families Macrouridae, Ophidiidae, and Alepocephalidae dominate the 

lower slope (1000 to 2000 m). The families Ophidiidae, Alepocephalidae, and Ipnopidae 

dominate the lower slope-continental rise (2000 to 3000 m). Although macrourids were the most 

diverse family in three of the four depth strata, the taxonomic composition within the family 

varies with depth. The genera Hymenocephalus and Malacocephalus, and species Caelorinchus 

caelorhincus and C. caribbaeus are most common on the upper and mid slope. The genus 

Coryphaenoides and species Cetonurus globiceps, Sphagemacrurus grenadae, and Squalogadus 
5-79 

modificatus are most abundant on the mid to lower slope. Species composition of Ophidiidae, to 

a lesser degree, also varies with depth.

The demersal fish data is further examined in the light of the hypotheses being tested. In 

each table below, CPUE (number/hr) is a measure of abundance, ‘Species’ is the number of 

demersal fish species taken, H’ diversity is the Shannon-Wiener information function, and % 

overlap is the percentage similarity between the region where the region in question and the next 

region (i.e., directly below, the overlap between the Shelf and the Upper Slope fauna is 3.2%; 

Table 5.8). 

Table 5.8. Fish characteristics by capture and location. 

Depth Zones (n=34) Shelf Upper slope Mid-slope Lower slope Rise 

 

CPUE 52.8 170.9 74.8 5.0 5.5 

Species 16 53 37 18 17 

H' Diversity 0.80 1.45 1.13 1.16 1.09 

% overlap 3.2 9.7 8.1 15.4 

 

 The Upper Slope has the highest abundance, species number, and diversity. The 5 zones 

indicated in the table are well-defined and the overlap at all levels is small (the greatest, 15.4%, 

is where one would expect the least difference -- Lower Slope to Rise). This suggests that the 

largest faunal differences are due to differences in water depth. 

 Because the fauna is zoned with depth, two comparisons were conducted to test east/west 

trends in the data (Table 5.9). In the shallow water comparison (shelf/upper slope), the Canyon 

samples were deleted (Table 5.10). Abundance was highest in the Canyon site and least at the 

West sites. Diversity was lowest in the Canyons and Central sites. Each region was rather 

distinct, as shown by the generally lower values in percent overlap (the last value of overlap, 

16.9%, is for East-West). These data do not support the hypothesis of a regular east/west trend 

on fish distributions, particularly because the Canyon is so different. 

Table 5.9. East to west faunal comparison (shelf/upper slope depths) including the Canyon. 

Shelf / Upper Slope (n=11) East Canyon Central West 

 

CPUE 148.0 234.0 196.0 65.3 

Species 42 27 15 36 

H' Diversity 1.32 1.14 0.81 1.28 

% overlap 33.4 13.4 9.9 16.9 

 
5-80 

Table 5.10. East to west faunal comparison (lower slope/rise depths). 

Lower Slope/Rise (n=15) East Central West 

 

CPUE 8.1 4.0 3.4 

Species 21 10 17 

H' Diversity 1.23 0.94 1.13 

% overlap 30.8 24.1 51.1 

 

 The Canyon site is not as distinct on the lower slope and rise (and is furthermore 

explicitly dealt with below), so we only recognized a central zone (Table 5.10). The low species 

number and diversity in the Central region is interesting because it was unexpected. East and 

West are more similar (PS = 51.1%) than either is to the nearer Central region. These data 

weakly support the hypothesis. 

 The basin/non-basin comparison showed little difference in overall community 

parameters, although the non-basin values were a bit higher than the basin ones (Table 5.11). 

Abundance was relatively low and species were few, as would be expected for this more western 

region. There is some difference between the two regions in respect to faunal composition, as 

indicated by the percent overlap of 33.1%. This is weak support for the hypothesis. 

Table 5.11. Basin to non-basin faunal comparison. 

Lower slope (n=6) Basin Non-basin 

 

CPUE 2.3 4.0 

Species 6 8 

H' Diversity 0.73 0.86 

% overlap 31.3 

 

 The comparisons of canyon and non-canyon sites were made at depth, the shallower 

situation having been addressed (Table 5.12). Community parameters were quite similar in and 

out of the canyons (MT stations), but the species composition was different. Percent overlap was 

only 12.5%. But this is also a part of the central region, where, as noted above, the number of 

species was rather low, and this could influence the percent overlap. This is weak support for the 

hypothesis that canyon and non-canyon sites are different. 

Table 5.12. Canyon to non-canyon faunal comparison (lower slope/rise depths). 

Lower Slope/Rise (n=3) Canyon Non-Canyon 

 

CPUE 3.6 5.3 

Species 6 6 

H' Diversity 0.75 0.72 

% overlap 12.5 

 
5-81 

 The spatial distribution information is shown on maps (Figures 5.55-5.58). A re-analysis 

of the older Pequegnat data in terms of the several megafaunal groups represented is planned. 

These data include information on echinoderms, crustaceans, polychaetes and various 

miscellaneous species in addition to fishes. 

 Too few stations were made in and out of both basins and canyons to be able, with the 

fish data, to come to firm conclusions. It would be useful to compare results from other faunal 

groups, when the data become available, to see if better support for some hypotheses can be 

found. For this reason, it is important to complete biogeographic studies based on a number of 

groups. 

 5.3.5.7 ADCP Detection of Mobile Near-Bottom Fauna 

On DGoMB Cruise 2, four deployments of the free-vehicle ADCP were made. From 

these deployments 29, 16, 70, and 26 hours of usable ADCP backscatter data were collected (see 

Table 5.13). The water depths in which the ADCP was recording data were 935 m in the first 

deployment, 755 m in the second deployment, 1,823 m in the third deployment, and 2,740 m in 

the fourth deployment (see Table 5.13). For each deployment, the downward looking ADCP was 

moored 35 m off the bottom and data were logged every 15 minutes by two meter depth bins. 

Measurements collected within 4 m of the ADCP's transducers (35-4 = 31 m off bottom) were 

too close to the instrument to give accurate data, and at and below approximately 28 m from the 

instrument (35-28 = 7 m off bottom), the bottom echo was too high to allow accurate data. Thus, 

there were a total of 11 usable depth bins (from 35-6 = 29 m off bottom to 35-26 = 9 m off 

bottom). 

Table 5.13. Backscatter averaged from the 14-m depth bin (21 m off bottom) in four 

deployments. 

 Date/Time 

(local time) Location Water Depth 

Average 

Backscatter (read 

data as counts) 

 

Deployment 1 

MT-3 

6/3/01 - 6/4/01 

12:00 pm-3:00 pm 

Lat 28°13.3N 

Long 89°30.0W 

935 m 129 

Deployment 2 

S-42 

6/6/01 - 6/7/01 

6:15 pm-2:00 pm 

Lat 28°15.0N 

Long 86°25.0W 

755 m 146 

Deployment 3 

S-36 

6/9/01 - 6/12/01 

9:45 am-7:30 am 

Lat 28°55.2N 

Long 87°40.1W 

1,823 m 120 

Deployment 4 

MT-6 

6/12/01 - 6/14/01 

11:00 pm-12:30 am 

Lat 27°00.0 N 

Long 88°00.0W 

2,740 m 111 

 

 Mean backscatter intensity was higher in the shallower ADCP deployments. The highest 

intensities were seen in deployment two, where the water depth was 755 m, and the lowest in 

deployment four, where water depth was 2,740 m. Higher current velocities in general 

correspond to lower backscatter intensities. Summary data from the four deployments is shown 

in Table 5.13. There was no apparent phase change seen in the data collected during the four 

deployments to indicate diel vertical migration of scavengers or zooplankton. However, at least 3 
5-82 

Zones are defined by: = deep shelf; = Upper Slope; = Mid-slope; = Lower 

Slope; = Rise 

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Rise

Lower slope

Middle slope

Upper slope

Shelf

Shannon-Weiner Index, H'

Figure 5.55. Zonation and diversity (H’) in demersal fishes. 
5-83 

Gyre fishes - richness by depth zone

0 10 20 30 40 50 60

Rise

Lower slope

Middle slope

Upper slope

Shelf

Number of species

Figure 5.56. Species richness in demersal fishes. 

 High Species Richness 

 Medium Species Richness 

 Low Species Richness 
5-84 

0 50 100 150 200

Rise

Lower slope

Middle slope

Upper slope

Shelf

Number/station

Figure 5.57. Abundance of demersal fishes by depth zone. 

 High Abundance 

 Medium Abundance 

 Low Abundance 
5-85 

Figure 5.58. Maps of relative occurrences of A) trawl-caught trash and B) relative abundance 

of macrofaunal sized nematodes (CPUE is catch per unit efforts). 

A 

B 

 High Relative Occurrence 

 Medium Relative Occurrence 

 Low Relative Occurrence 
5-86 

of the four depths sampled were below depths at which light should penetrate to give a day/night 

cue. Light penetration data from the Optical Backscatter Sensor (OBS) on the CTD will later be 

obtained to check for a possible diel light signal. 

 To analyze the ADCP measurements, the initial binary data were transcribed into ASCII 

format using the program BBlist (downloaded from the RDInstruments website). Preliminary 

graphs of backscatter intensity versus time and current velocity versus time for each of the depth 

bins from 6-26 m were then created to look for patterns in the data. The time series for 

deployments 2 and 3 is shown in Figure 5.59. Analysis continues using PV-Wave and programs 

created by Steve DiMarco and Rebecca Scott to convert the intensity which was collected in 

relative counts to decibels and to use 40 hour lowpass filters to smooth the data. This will allow 

inner comparison of data among the four deployments as well as comparison with moored data 

from near surface time series. Completion of the ADCP data analysis from DGoMB Cruise 2 is 

expected at the end of February, 2002. For the next and final field season (summer 2002), it is 

planned to return to two of the deployment sites and open a baited trap midway through the 

ADCP deployment period. The trap will be opened using timed burnwires and used to look for 

any associated changes in backscatter intensity. 

5.4 Community Function/Processes and Model Development 

Process studies began on DGoMB Cruise 2. Few results are finalized from that field 

work, but a summary of preliminary observations can be presented to illustrate the trends that are 

emerging. Total sediment community oxygen consumption (SCOC) is estimated from 

incubations of sediments with overlying water. The decline in oxygen concentration in the 

chambers as a function of time is used as a measure community respiration (SCOC). In situ

incubations were conducted at two lander sites and ship-board laboratory incubations were 

carried out at five sites at in situ temperatures. Additional data have been generated by sending 

DGoMB researchers out with the Johnson Sea-Link submersible to sites on the continental slope. 

The locations are not DGoMB sites, but they add to the database for the slope environment in the 

GOM. In addition to these slope sites, shallow water continental shelf incubations were 

conducted at locations of studies by the MMS-supported GOOMEX program off Port Aransas, 

Texas and in the fine carbonate sands adjacent to the coral banks at the Flower Gardens National 

Sanctuary. Two SCOC values at two abyssal plain sites have been taken from the literature 

(Hinga et al. 1979; eastern GOM abyssal plain) and Rowe et al. (in press, western GOM abyssal 

plain). So far, therefore, a total of 14 values can be presented as representative of the GOM 

continental margin in the region of oil and gas development on the continental slope. To this, 

five (5) continental shelf sites and two (2) deep abyssal plain sites have been added. This 

database thus allows us to characterize the general nature of SCOC in the western Gulf of 

Mexico. This database does not include numerous values available near or adjacent to the 

Mississippi River plume as they tend to be affected by a number of processes associated with the 

river that are atypical of the GOM as a whole. 

 The SCOC from the western GoM continental shelf down across the slope to the abyssal 

plain can be characterized by a log-log relationship with depth (Figure 5.60). The units of 

measure are mmoles O2 m-2 d-1. Thus, rates decline from about 30 mmoles O2 m-2d-1 on the shelf 

down to less than 1 on the abyssal plain. This would account for a turnover of organic carbon by 
5-87 

Figure 5.59. Raw ADCP backscatter intensity from deployments 2 (755 m) and 3 (1,823 

m) at the 14 m depth bin (21 m off bottom). The intensity was read in 

counts and was averaged for the ADCP's four beams. 
5-88 

these communities of about 300 down to less than 10 mg C m-2 d-1 over the depth range of the 

data available. These values are typical for most continental margins where similar studies have 

been conducted. It is worth noting at this point that the variation at any particular depth down the 

slope is high. This is because a wide range of divergent types of habitats have been included in 

the study to get as broad a range of conditions as possible. Ensuing studies will be attempting to 

use the characteristics of the biota to explain why the rates of SCOC vary from site to site. 

Contrasting different SCOC values among the different environments will constitute an 

important approach to differentiating between habitats. 

5.5 Task 4 - Data Interpretation, Synthesis, and Reporting 

 A preliminary interpretation of data is provided in Section 6.0. 

1 2 3 4

-1

0

1

2

Log Depth (m)

Log SCOC (mmoles/m^2-day)

y = 2.34 - 0.68x R^2 = 0.75

Figure 5.60. The SCOC from the western GOM continental shelf down across the slope 

to the abyssal plain is characterized by a log-log relationship with depth. 
6-1 

6.0 PRELIMINARY OBSERVATIONS AND SUMMARY 

 The progress in the present program to date has been focussed along narrow subdisciplinary lines, as reported in Section 5.0 The study however has been designed to be 

interdisciplinary, composed of parallel measurements of a wide variety of environmental 

variables that could play roles in or have effects upon the communities of organisms that live in 

association with the deep ocean floor in the northern GoM. In the reports presented in Section 

5.0, little attempt has been made to compare or synthesize results because they are incomplete 

and preliminary. The individual investigators have not yet had the opportunity to make 

comparisons among the on-going parallel studies. The purpose of this section is to call attention 

to those areas of overlap and interaction that are beginning to emerge from the data sets, even 

though most of them are as yet preliminary. It is important to point out these relationships now 

because the field program and the thrust of the process studies is intended to be iterative. The 

choice of sites, the activities at each site, the details of the experimental protocols, and the onboard sampling will be rehashed as the information in Section 5.0, and the synthesis attempted 

here, are considered and discussed among the principal investigators. 

 A long-held paradigm in deep-sea biology is that depth, or some correlate with it, has 

over-riding control over benthic community structure and dynamics. As a result all the biological 

size groups have been plotted against depth, but with somewhat different results. The abundance 

of metazoans (meiofauna and macrofauna) living within the sediments correlated negatively with 

depth, but with rather wide variations at any depth along the gradient (Figures 5.43 and 5.50). 

The bacteria densities did not decline in nearly as consistent a fashion with depth, however 

(Figure 5.37). When anomalously high values were excluded from the different regressions, the 

coefficients all increased measurably (Figures 5.51 and 5.52). In each case, the anomalous values 

came from many of the same sites for each group: the Mississippi Trough and the DeSoto 

Canyon. This coherence between the high values in each group suggests that these sites are all 

characterized by exceptionally high inputs of organic detritus. The gulf, we might conclude, can 

be partitioned into regions of high biomass and low biomass. Thus other factors besides depth 

influence deep ocean biomass. The decline in sediment community oxygen consumption 

(SCOC), as measured by in situ incubations (Figure 5.60), declined with depth as expected, but 

values at the mid-slope experimental site in the Mississippi Trough (MT3) were above the 

regression line, reinforcing the suggestion in standing stocks that the trough is an enriched 

region. The SCOC regression did not include sites that were within methane seep communities. 

The effect of seeps will be considered when more samples near seeps have been analyzed. 

 The stations were distributed on the survey to provide broad geographic coverage with a 

wide variety of environmental and biological standing stock data. As anticipated, those data 

fields can be mapped across broad horizontal regions of the continental slope. For many of the 

data fields, no such information has ever existed before. Thus, this program will be generating 

maps of entirely new biogeographic information that will eventually be published in the peerrefereed literature. In general, deep-ocean studies sample along transects across depth gradients. 

While this provides useful analyses of the responses of variables to depth, they do not provide 

information that can be mapped: DGoMB data on the other hand will be amenable to mapping 

across the entire northern GoM. The usefulness of these maps is already emerging in on-going 

DGoMB analyses. For example, the degree of bioturbation, as indicated by the variation in the 

physical properties of sediments in short cores, is minor over vast areas of the western GoM 
6-2 

(Figures 5.19-5.24) but is intense over much of the eastern GoM. Trace organic contaminants, 

while well below values that might affect the biota, have a distribution that can be contoured in a 

pattern that implies that the source is the Louisiana continental shelf or the Mississippi River 

(Figures 5.27 and 5.28). Meiofaunal densities are clearly highest on the upper slope, but the head 

of the Mississippi Trough jumps out as being far higher than any other area (Figure 5.44). The 

fish fauna is partitioned by depth, with different combinations of relatively distinct assemblages 

characterizing the outer shelf, the upper slope, the deep slope and the upper rise, all around the 

northern GoM (Figure 5.55). As each of the different data sets become available, they will each 

be displayed as maps, providing similar insightful conclusions. 

 This project is based on hypotheses that will be used to predict what to expect of bottom 

communities in different environments. Although it is hypothesis based, it is also model driven. 

That is, evolving conceptual models are used to direct an evolving set of process measurements 

that are being used to construct a budget of the carbon stocks and carbon cycling through the 

components of the food web of organisms living on or near the sea floor. One cruise to measure 

processes has now been completed (June 2001). Some of the results are now available and have 

been reported on in Section 5.0. This section of this Interim Report 2 will attempt to identify the 

areas in which these processes appear to agree and interact and the instances in which 

relationships are as yet obscure. 

 The choice of the sites where processes would be studied was based on results of the 

survey of standing stocks. It was reasoned that rates of metabolic processes would be highest, 

input of organic matter would be highest, growth rates would be elevated, etc., at those sites with 

the highest biomass and greatest densities of organisms. And the opposite was also assumed: the 

lowest rates would be found at the sites where abundances and biomass were the lowest. Based 

on these assumptions, the four contrasting sites chosen were MT3 and S36, as representatives of 

sites with high biomass, and MT6 and S42, as representatives of sites with low biomasses and 

thus low rates. In making these choices, we searched for and found conformity between the 

standing stocks of the different size groups being measured: bacteria, meiofauna, macrofauna, 

megafauna and fishes. The sites were chosen based on discussions among the PIs at Interim 

Meeting No. 1, in February, 2001. Maps and locations of these sites can be found in the cruise 

report of the survey cruise in 2000, in the results of the !st Interim Meeting, in the Cruise Plan 

for the first processes cruise, June, 2001, and in the report on that cruise. 

 This portion of the work is model driven, but the models being applied are in a constant 

state of evolution. The earliest conceptual model presented as basis for this study was derived 

from a study of the NW Sigsbee Abyssal Plain, at a depth of 3.65 km (Rowe et al. in press). That 

linear and branched food web analysis (Figure 1) has now been modified for heuristic purposes. 

This new version (Figure 6.1) places organic matter at the center of the system, thus illustrating 

its hypothetical importance as the over-riding forcing function in the processes that characterize 

the system. The main source of organic matter is sinking POC, but other sources are possible 

(import from pelagic food webs and methane seeps). The major fates of organic matter are 

remineralization into metabolic CO2 by each of the size groups and long-term burial within the 

sediments. 
6-3 

Figure 6.1. Conceptual model of a hypothetical deep benthos foodweb illustrating that the 

input of organic carbon controls the web’s structure and dynamics. 

BACTERIA 
6-4 

 Model output is now also available from the Sigsbee study referred to above (Rowe et al. 

in press). The surface concentration of pigments is known to vary seasonally by a factor of two. 

If this degree of variation is transferred to the rate of POC input needed to support the sediment 

biological fates, then the sea floor values will vary accordingly. As Rowe et al. point out, there is 

a temporal lag in maximum biomass for each size group, as the organic pulse is transferred up 

the food web (Figure 6.1). These recognizable patterns in standing stocks have been modeled in 

other systems, but validating the seasonality has not yet been possible. It has been observed that 

POC input varies by season, but how this affects biomass is unknown. The values we present are 

only theoretical so far. 

 The general pattern of metabolic intensity does appear to follow the pattern we predicted. 

For example, the oxygen concentration gradient is steepest at MT3 and the least at MT6. This 

pattern is similar to that found for bioturbational mixing, as reflected in the radionuclide 

distributions, with the caveat that biomass should be proportional to POC input. If bioturbation is 

a function of biomass, and the biomass is highest at MT3, then why is oxygen penetration the 

least at MT3? This appears to be a contradiction. Shouldn't oxygen penetration be greatest where 

mixing is the greatest? We assume at this point that our presumption that mixing is a function of 

biomass is true, but that the oxygen declines precipitously because metabolic consumption, 

which is also accentuated by high POC input, outpaces oxygen penetration. 

 The most important data to date is our increasing ability to predict sediment community 

oxygen consumption (SCOC) rates as a function of depth (Figure 5.60). This illustrates the 

overall decline in metabolic processes as a function of depth. While the line is significant and 

confirms the steep rate at which community metabolism declines with depth and distance from 

shore, the variation around the line is large, almost an order of magnitude. A next step will be to 

determine the internal consistency between the various different approaches to estimating 

community metabolism and the rates of the separate individual components within the 

assemblage of organisms. This cross checking is now underway. These rates will eventually be 

the ground truth against which the model-generated values are compared. The regression is very 

preliminary and will be supplemented by lander deployments to be made during ensuing field 

work described in the earlier chapters of this document. 
7-1 

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170. 
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. 

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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 

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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.