OCS Study 

MMS 95-0063 

Symposium Proceedings : 

Gulf of Mexico and Caribbean Oil Spills in 

Coastal Ecosystems : Assessing Effects, 

Natural Recovery, and Progress in 

Remediation Research 

New Orleans, July 14-15,1994 

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U.S. Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 
OCS Study 

MMS 95-0063 

Symposium Proceedings : 

Gulf of Mexico and Caribbean Oil Spills in 

Coastal Ecosystems: Assessing Effects, 

Natural Recovery, and Progress in 

Remediation Research 

New Orleans, July 14-15,1994 

Editors 

C . Edward Proffitt 

Louisiana Environmental Research Center 

McNeese State University 

Lake Charles, Louisiana 

and 

Pasquale F. Roscigno 

Minerals Management Service 

Gulf of Mexico OCS Region 

New Orleans, Louisiana 

Prepared under MMS Cooperative Agreement 

14-35-0001-30690 

by 

Louisiana Environmental Research Center 

McNeese State University 

P .O . Box 90220 

Lake Charles, LA 70609 

Published by 

U.S. Department of the Interior New Orleans Minerals Management Service 

Gulf of Mexico OCS Region April 1996 
DISCLAIMER 

This report was prepared under contract between the Minerals Management Service 

(MMS) and McNeese State University . This report has been technically reviewed by the 

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

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

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

exempt from review and compliance with MMS editorial standards . 

AVAILABILITY 

Copies of this report may be obtained from the Public Information Unit at the 

following address: 

U.S . Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region 

Public Information Unit (MS 5034) 

1201 Elmwood Park Boulevard 

New Orleans, Louisiana 70123-2394 

Telephone : 1-800-200-GULF 

1-504-736-2519 

SUGGESTED CITATION 

Proffitt, C.E . and P.F . Roscigno (eds .) .1996. Proceedings: Gulf of Mexico and Caribbean 

Oil Spills in Coastal Ecosystems : Assessing Effects, Natural Recovery, and Progress 

in Remediation Research. OCS Study/MMS 95-0063 . U.S . Department of the 

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

LA. 245 pp. 

COVER ILLUSTRATION 

The cover illustration was provided by the MMS Gulf of Mexico OCS Region. 

iii 
PREFACE 

This volume is the proceedings of a symposium entitled Gulf of Mexico and 

Cairbbean Oil Spills in Coastal Ecosystems: Assessing Effects, Natural Recovery, and 

Progress in Remediation Research held in New Orleans on July 14-15, 1994 . Both the 

symposium and these proceedings were supported under a cooperative agreement between 

MMS and McNeese State University . The papers in this report were provided by the invited 

symposium speakers. They have been reviewed editorially, but have not been subjected to 

peer review. Included at the end of the report are outline summaries of discussion sessions 

held near the end of the symposium. 

ACKNOWLEDGMENTS 

The editors, McNeese State University, and the Minerals Management Service wish to 

thank all invited contributors and discussion leaders for their efforts . Thanks are also due to 

Ms . Ruth Harper of McNeese State University for assisting at the symposium and in early 

stages of editing this report . In addition, we thank Ms. Libby Klekowski, Ms. Dana Wetzel, 

and Dr . Peter Sherblom for taking copious notes during the discussion sessions . We also 

acknowledge the University of New Orleans Office of Conference Services for handling 

many of the symposium logistics. 

v 
NOTE TO READERS 

There are many instances in which oil spills have adversely affected ecosystems and 

wildlife . Many scientists and environmental managers have approached various aspects of the 

problem for decades. Despite advances in science and the technology of cleanup and 

remediation, our understanding of the effects of oil on ecosystems, the rates of natural 

degradation of oil once in these systems, and effective techniques for remediation of adverse 

environmental effects is marginal, at best. 

For this reason, the Minerals Management Service (MMS) and the Louisiana 

Environmental Research Center at McNeese State University (LERC) organized and hosted 

this symposium of invited papers . This proceedings includes a number of papers discussing 

on-going research on the ecological and genetic effects of oil on biota, bioremediation, and 

in-situ marsh burns. Other papers provide summaries and syntheses of states-of-knowledge 

on oil effects and various remediation techniques . 

To further address the problems, MMS and LERC are holding follow-up workshopstyle meetings to focus on specific problems identified during the symposium. From these 

workshops a series of technical papers on specific topics will be authored by participants and 

published by MMS. These technical papers will contain reviews of specific topics and 

opinions by the invited experts on research needs and best management practices . The 

workshop on Mangroves and Oil Spills has already been held (August 1995, at McNeese 

State University) and the technical paper is in preparation. An additional workshop will be 

held during 1996 . 

We hope that these efforts will result in significant advances in our understanding of 

oil spill effects and how to respond to them in ways that minimizes effects on coastal, 

estuarine, and marine wildlife and ecosystems. 

The Editors : 

Dr. C. Edward Proffitt 

Associate Professor and Director 

Louisiana Environmental Research Center 

McNeese State University 

P .O . Box 90220 

Lake Charles, LA 70609-0220 

proffittoacc . mcneese. edu 

Dr. Pasquale F. Roscigno 

U.S . Department of the Interior 

Minerals Management Service 

Gulf of Mexico OCS Region(MS 5430) 

1201 Elmwood Park Blvd . 

New Orleans, LA 70123-2394 

pasquale roscigno@smtp .mms .gov 

vii 
TABLE OF CONTENTS 

Page 

PREFACE v 

NOTE TO READERS vii 

SESSION I - Experiments and Case Studies on the Effects of Oil Spills on 

Seagrass, Tidal Marsh, and Mangrove Ecosystems: Chair, Dr. Edward Proffitt 1 

Experimental Analysis of the Effects of Oil on Mangrove Seedlings and 

Saplings and the Mangrove Gastropod Melampus coffeus L. 

Donna J . Devlin and Edward Proffitt 3 

The 1993 Tampa Bay Spill : Preliminary Assessment of Natural Resources 

Jane S. Urqhart-Donnelly 24 

Environmental Distribution of Oil-Related Hydrocarbons Following a Spill 

of Number 6 Fuel Oil in Tampa Bay 

Dana L. Wetzel, P.M. Sherblom, E .S. Van Vleet, R.P. Pierce, M.S . 

Henry, and D. Kelly 32 

Effects of Oil on Salt Marshes 

James W. Webb 55 

The Applicability of Predictions Made from Other Spills to the 1986 Bahia 

Las Minas, Panama, Crude Oil Spill : Seagrass Communities 

Michael J. Marshall 65 

The 1986 Bahia Las Minas Oil Spill: Summary Results from the Red 

Mangrove (Rhizophora mangle) Fringe 

Sally C. Levings, S.D . Garrity, and K.A . Burns 80 

Is Genetic Degradation of Mangroves a Consequence of Petroleum? 

Edward J. Klekowski, Jr. and J . Corredor 99 

Session II. Remediation techniques: Reviews and Current Research: 

Chair, Pasquale F. Roscigno 107 

Bioremediation: Statistical and Analytical Needs 

W. James Catallo 109 

Toxicology Research: An Update on EPA Methods for the Evaluation of 

Oil Spill Dispersants 

Carol B. Daniels 130 

ix 
Page 

Remediation Techniques: An Overview 

William A. Kucharski and Paul Kostecki 136 

Responding to Oil Spills in Marshes: The Fine Line Between Help 

and Hindrance 

Rebecca Hoff 146 

Session III. An Overview of Bioremediation Studies in the Gulf of Mexico: 

Chair, Irving A. Mendelsshon 163 

Evaluation of Commercial Bioremediation Products for Oil Biodegradation 

in Salt Marshes 

Richard W. Weaver, B. Crites, S. Neralla, A. Wright, and J. W. Webb 165 

The Development of Bioremediation for Oil Spill Cleanup in Coastal 

Wetlands : Product Impacts and Bioremediation Potential 

Irving A. Mendelsshon, Q. Lin, K. Debusschere, C.B. Henry, E.B. 

Overton, S . Penland, R.J . Portier, N.N . Rabalais, and M.M. Walsh 174 

Bioremediation Studies - Effects on the Marsh Infaunal Community 

Nancy N. Rabalais and N. Atilla 188 

In-Situ Burn as an Oil Spill Response Technique 

Gus Stacey, III 191 

Evaluation of Burning as an Oil Spill Clean-up Technique in a High Marsh 

Community Along the South Texas Coast 

Beau Hardegree, D.W . Hicks, and J . W. Tunnell, Jr. 195 

Fate of Oil in Salt Marsh Sediments and Stabilization of Oil Residue 

Edward B. Overton, C.B. Henry, and P. Roberts 213 

Session IV. Group Discussions : Chair, Edward Proffitt 233 

Oil Spills and Mangroves 

Donna J. Devlin and Sally C. Levings 235 

Oil Spills and Marshes 

Irving A. Mendelsshon and James W. Webb 237 

x 
Page 

Oil Spills and Seagrass 

Michael J . Marshall 239 

Oil and Dispersants 

Carol B. Daniels 240 

Agenda for the Symposium: Gulf of Mexico and Caribbean Oil Spills in 

Coastal Ecosystems: Assessing Effects, Natural Recovery, and Progress in 

Remediation Research. July 14-15, 1994 . New Orleans, LA 243 

xi 
Session I. Experiments and Case Studies on the Effects of Oil Spills on 

Seagrass, Tidal Marsh, and Mangrove Ecosystems 

Chair: Dr. C. Edward Proffitt 

Presentation Author / Affiliation 

Experimental Analyses of the Effects of Oil 

on Mangrove Seedlings and Saplings and the 

Mangrove Gastropod Melampus coffeus L. 

The 1993 Tampa Bay Spill : Preliminary 

Assessment of Natural Resources 

Environmental Distribution of Oil-related 

Hydrocarbons Following a Spill of Number 

6 Fuel Oil in Tampa Bay 

Effects of Oil on Salt Marshes 

Ms. Donna J. Devlin 

Department of Biology 

University of Southwestern Louisiana 

Dr. C. Edward Proffitt 

Associate Professor and Director 

Louisiana Environmental Research 

Center 

McNeese State University 

Ms. Jane S. Urquhart-Donnelly 

Florida Department of Environmental 

Protection 

Bureau of Emergency Response 

Ms. Dana L. Wetzell 

Dr. Peter M. Sherblom2 

Dr. Edward S. Van Vleetl 

Dr . Richard H. Pierce2 

Mr. M.S. Henry' 

Dr . D. Kelly2 

1 University of South Florida 

Department of Marine Science 

2 Mote Marine Laboratory 

Dr. James W. Webb 

Marine Biology Department 

Texas A&M University at Galveston 

The Applicability of Predictions made from Dr. Michael J. Marshall 

Other Oil Spills to the 1986 Bahia Las Minas Mote Marine Laboratory 

Panama, Crude Oil Spill: Seagrass 

Communities 

1 
The 1986 Bahia Las Minas Oil Spill : 

Summary Results from the Red Mangrove 

(Rhizophora mangle) Fringe 

Is Genetic Degradation of Mangroves 

a Consequence of Petroleum? 

Dr. Sally C. Levingsl 

Dr. Stephen D. Garrity' 

Dr. Kathryn A. Burns' 

1 Coastal Zone Analysis, Inc. 

2 Australian Institute of Marine Science 

Dr. Edward J. Klekowski, Jr. 

Biology Department 

University of Massachusetts 

Dr. Jorge Corredor 

Department of Marine Science 

University of Puerto Rico 

2 
Experimental Analyses of the Effects of Oil on Mangrove Seedlings and 

Saplings and the Mangrove Gastropod Melampus coffeus L. 

Donna J . Devlin' and C. Edward Proffitt2 

1 Biology Department 

University of Southwestern Louisiana 

Lafayette, LA 

2 Louisiana Environmental Research Center 

McNeese State University 

P.O . 90220 

Lake Charles, LA 70609 

proffitt@acc .mcneese.edu 

INTRODUCTION 

Mangroves dominate about 75 % of the world's low energy coastline between 25° N 

and 25° S latitude . Mangroves also occur well outside this range along eastern North 

America and other coasts where cold temperatures are buffered by warm water currents . 

Many trade routes, ports, petroleum storage and refining facilities, and naturally occuring oil 

fields are located in these same regions, making mangrove communities epecially susceptable 

to contamination from oiling . 

There are numerous documentations of death, defoliation, genetic, and other damage 

to mangroves and their associated communities after exposure to oil (Baker et al. 1981 ; 

Baker 1982 ; Dicks 1986 ; Duke 1991 ; Garrity et al. 1994; Getter et al. 1981 ; Gilfillan et 

al. 1981 ; Jackson et al. 1989 ; Kahn 1992 ; Klekowski et al. 1994 ; Jacobi and SchaefferNovelli 1990; Lewis 1983 ; Proffitt et al. 1993, 1995 ; Snowden and Ekweozor 1987) . 

Once contamination has occured, characterization of the effects of oils on living 

organisms is difficult . Oils vary in composition, toxicity and viscosity . These factors are 

secondarily affected by the environment as the oils breakdown or "weather" (Proffitt et al. 

1995) . 

Assessing the effects of crude or refined petroleum in mangrove forests is particularly 

challenging . The intertidal location and complex structure of mangrove forests provides 

habitat for diverse faunal assemblages. The canopy supports large suites of birds, arthropods 

and other invertebrates. Submerged roots provide surfaces for colonization by encrusting 

organisms including oysters, barnacles, sponges, tunicates, algae and other species ; as well 

as refuge and foraging habitat for numerous fish and crustaceans. Burrowing and epibenthic 

crustaceans, molluscs and other invertebrates live the soft substratum and litter on the forest 

floor. Algae and salt tolerant herbaceous plants are also common. 

Damage to mangrove forests varies with the amount and toxicity of the spilled oil 

product(s) ; tidal height and range; the oil residence time, the season of the oiling event, and 

other factors. Spilled oil may coat both plant and animal life and/or be absorbed by 

3 
substratum. The rate of subsequent degradation of oil in the sediment is influenced by the 

sediment type, oxygen content and bacterial component of the sediment; availability and level 

of nutrients in the sediment and at the oil/soil interface ; and the depth to which the oil has 

penetrated . 

A primary cause of death in oiled mangroves is reported to be the disruption of gas 

exchange when aerial roots are coated with oil and can no longer supply oxygen to root 

tissues below ground in hypoxic soils (Teas et al. 1993) . Getter et al. (1981, 1985) found 

that hydrocarbons can enter mangroves through the root system, be translocated to the leaves 

and accumulate in the stomata. They speculate that the hydrocarbons may interrupt 

transpiration or poison biochemical pathways. Page et al. (1985) demonstrated that petroleum 

can disrupt root membranes and allow lethal concentrations of salt to accumulate in 

mangrove tissues . 

Toxicity varies with the composition of the oils and in combination dispersants. 

Getter et al. (1985) report that light crudes and No . 2 fuel oil decreased foliage production 

by mangroves more than the heavier Bunker C oil, while dispersants decreased toxicity of the 

bunker C oil but increased the toxicity of light oils . 

Effects also differ with life history stage, and may effect the growth forms of young 

trees. Duke (1991) found that 1-2 year old Rhizophora mangle L. survived oiling by 

medium weight crude while surrounding mature trees died . Getter (1982) found that 

seedlings took up oil more rapidly than did larger trees . Seedlings growing in oiled 

sediments sometimes have a modified growth form . There is also some evidence suggesting 

that stands in areas near the physiological tolerance limits for the species or in other stressful 

environments, may be more vulnerable to oil damage than forests in less stressful 

environments (Proffitt et al. 1995) . 

Lewis (1983) suggests that natural recolonization of an mangrove habitat oiled during 

the Zoe Colocotroni spill "appears to be successful ." However, he also states that other 

mangrove experts (A. Lugo and G. Cintron) have testified that the plants colonizing this site 

will likely remain stunted or die . Getter et al. (1985) opined that the tall, spindly seedlings 

noted growing in at the Zoe Colocotroni spill site may be less able to withstand storm 

winds. 

Studying the effects of spills in mangrove systems is often difficult. Mangals around 

the world have divergent suites of species and different levels of biological diversity . 

Mangals are protected by law in some areas which often precludes manipulative field 

experiments on oil effects . Especially poorly understood are the effects of oil contamination 

on mangrove fauna and food webs ; and, on ecological functions such as detrital 

decomposition and transport . 

Here we summarize experiments, some of which are on-going at time of this 

symposium, of the effects of oil on growth and survival of Rhizophora mangle seedlings and 

saplings . Complete results of this study will be presented in a paper that is in preparation at 

time of publication of this document. We also present limited experimental data on survival 

of the mangrove-dwelling gastropod, Melampus coffeus L. when exposed to oiled seagrass . 

Two oils, No . 6 fuel oil (both fresh and weathered) and Louisiana crude, were used in 

different studies. 

4 
METHODS 

EXPERIMENT 1 (fresh No. 6 fuel oil) : Rhizophora mangle propagules were collected at 

War Veteran's Park on Boca Ciega Bay, a part of the Tampa Bay estuary system. Twohundred eighty propagules varying from 15 to 25 cm in length were selected for use. Two 

treatments 50% oiled and 100% oiled and a control were established . For the oil treatments, 

propagules were either dipped halfway (50%) or completely immersed (100%) in fresh No. 6 

fuel oil . Small amounts of the oil flowed from the propagules into the sediment for several 

hours after planting . A control group received no oil . 

EXPERIMENT 2 (spilled and weathered No . 6 fuel oil): R. mangle propagules and blades 

of the seagrass Thallasia testudinum coated with No. fuel oil were collected from a beach in 

Tampa Bay (south Pinellas County) in July of 1991 when an oil slick came ahore . The fuel 

oil had leaked from a pipe at Port Manatee several days previously. R. mangle propagules 

were scored as lightly oiled (< 50% cover) or heavily oiled (~: 50% cover). Unoiled 

control propagules were collected from the driftline of a nearby cove not affected by the 

spill. Data from a second type of "control" group (a "cohort control") consisting of 

propagules all from one parent tree are not presented here since these seedlings had very 

different growth patterns than any (oiled or unoiled) taken from the driftline . 

All propagules from the two fuel oil experiments were planted in commercial potting 

media and watered with fresh water when necessary . Water levels in external containers were 

maintained at approximately 1 - 2 cm below the surface of the sediment. Plants were kept at 

ambient temperatures in a shaded site . Experiments 1 and 2 were not run concurrently . 

EXPERIMENT 3 (Effects of weathered No . 6 fuel oil on M. coffeus) : Oiled T. 

testudinium blades were placed on the floor of an uncovered aquaria in which 20 M. coffeus 

had been kept for several months for feeding observations . In a second aquarium, 20 M. 

coffeus were presented with unoiled seagrass blades . There was approximately 1-2 mm of 

water on the floor of both aquaria . An unoiled food supply of mangrove leaves was available 

in Petri dishes placed on the floor of both aquaria . This was a simple, unreplicated 

experiment-of-convenience resulting from our having collected a small amount of oiled 

seagrass during the spill discussed in Experiment 2 and also having a number of M. coffeus 

available and acclimated to aquaria . 

EXPERIMENT 4 (Effects of Louisiana crude oil on 34 month old R. mangle saplings: In 

this study, plants surviving Experiment 2 were re-potted and allowed to acclimate for two 

months in a greenhouse water table at McNeese State University in Lake Charles, Louisiana. 

Three experimental groups with 16 replicates per group were established: an unoiled control, 

a low crude oil treatment (1 .6 L/mz) and a high crude oil treatment (16 L/m2) . Oil was 

applied to the sediment. At the date of the symposium this on-going study has been in 

progress for about 4 months and preliminary growth data for 92 days are presented . Survival 

data include the entire year-long study period as these data were available prior to 

finalization of the paper for the proceedings . At time of publication of this proceedings, a 

5 
paper analyzing data from exeriments 2 and 4 together is being submitted for publication 

(Proffitt and Devlin in prep). 

MEASUREMENTS: In each mangrove experiment, survival, primary stem growth and 

lateral branch growth of all treatment and control plants were measured to the nearest mm 

with vernier calipers . Numbers of leaves, leaf scars and attached leaves by degree of 

senesence were recorded. Primary stem growth was measured from the tip of the hypocotyl 

to the base of the apical leaf primordium . Lateral branch growth was measured from the 

point of formation of the axillary branch to the base of the leaf primordium at the tip of the 

branch. Total leaf production was calculated as follows : 

( L,2 +LS,2 ) - (Lt, + LSJ 

Where L and LS are numbers of leaves and numbers of leaf scars at times 1 and 2. 

For the Louisiana crude oil study, primary stem lignification was also measured and 

plants were ranked as to general condition: good, fair or poor. Condition was determined by 

acessing the following indicators of plant stress : leaf yellowing, browning, and wilting ; 

production of deformed leaves ; growing tip necrosis ; lateral branch death, primary stem 

death ; and plant death. Data on lignification and condition are preliminary and not presented 

here . One goal of this on-going experiment is to assess effects of oiling on first reproduction 

since red mangroves can flower and produce propagules as early as 3 years of age. As yet, 

no plant has reproduced so data on this is not presented . 

RESULTS 

EXPERIMENT 1 (Fresh No. 6 Fuel Oil): 

Approximately 80% of unoiled R. mangle propagules produced their first leaves 

between 50-80 days . The majority of propagules in the 50% and 100% oil treatments did 

not produce their first leaves until 80-120 days . By the end of the study (12 months), 90-

100% of seedlings in all groups had survived and produced leaves (Fig . 1) . 

At 12 months the control group had significantly greater stem growth (Fig . 2) and 

leaf production (Fig. 3) than both oil treatments (ANOVA and Tukey multiple comparison 

tests [p < 0.05]) . There were no significant differences between the 50% oil treatment and the 

100% oil treatments . 

EXPERIMENT 2 (Spilled and Weathered No. 6 Fuel Oil) : 

Survival of treatment and control plants was >_ 80% at 10 months, with a slight 

trend of reduced survival with greater surface area oiled (Fig. 4) . At 32 months, survival 

remained at 83 % for the control, but declined to 71 % for the low oil treatment, and 60% 

for the high oil treatment. 

6 
There were no significant differences in total stem growth among control and 

treatments throughout the study (Fig. 5). Lateral branch growth in the high oil treatment 

plants was greater at 32 months (One Way ANOVA and Tukey Multiple Comparisons Test, 

P < 0.05) than the low oil group, but not the control group (Fig. 5) . 

Total leaf production was lowest in the low oil treatment (One Way ANOVA and 

Tukey Multiple Comparisons Test, P < 0 .05) (Fig. 5) . Lateral branch leaf production was 

also greater (P < 0.05) in the high oil treatment (Fig . 5) . Leaf production on the primary 

stem was virtually identical for treatment and control groups. 

EXPERIMENT 3 (Effects of Weathered No. 6 Fuel Oil on Melampus coffeus): 

Changes in Melampus coffeus behavior occurred nearly immediately upon exposure 

to the oiled Thallasia testudinum blades . Most (85 %) quickly moved as far away from the 

oil as possible by climbing the aquaria sides. Three individuals were overtaken by the 

spreading oil leachate and upon contact, fell limp and hung out of their shells . Mortality of 

all 20 gastropods in the oil treatment occurred within 17 days (Fig. 6). There was no 

mortality in the unoiled control group during the same 17 day time frame or over the ensuing 

8 weeks . 

EXPERIMENT 4 (Effects of Louisiana Crude Oil on R. mangle Saplings): 

At experiment initiation there were no significant differences among control and 

treatments in height, primary stem length, lateral branch length, numbers of leaves on the 

plants or numbers of leaf scars . 

Survival 

There was a lag time of about 30 days before any detrimental effects of oil were 

noted. At 30 days, wilting and necrosis was evident in some leaves of the high oil treatment. 

At 92 days reduced survival (78%) was recorded in the high oil treatment (Fig . 7) . At 379 

days, survival was 31 % in the high oil treatment and 100 % in both the control and low oil 

treatment (Fig . 7) . 

The trend in mortality is best described by an exponential model . Since this is an ongoing study, it is unclear if mortality in the high oil treatment will continue or level-off. 

Thus, we present two preliminary alternative models that encompass these two possibilities: 

a linear regression model of percent survival on days and an exponential regression model of 

ln(proportion surviving) on days. 

These provided the following models of survival . 

Linear Regression Model : 

Percent Survival = - 0.176 x Days + 89 .436 

R2=0.861,n=17 

7 
Exponential Regression Model: 

Proportion Surviving = e(-o .oos z days) + 4 .562 

R2=0.943,n=17 

It should be emphasized that these are preliminary emperical fits of linear and 

exponential models to the data and should not be used to exptrapolate mortality outside the 

379 days of data . 

Growth 

At 62 and 92 days, there was significantly less total stem growth, primary stem 

growth and lateral branch growth in the high oil treatment relative to the control and low oil 

treatment (Fig. 8) . Growth data analyses for time periods > 92 days and analyses assessing 

prior oiling history of the plants is provided in Proffitt and Devlin (in prep.) . 

There is a trend toward fewer leaves on the high oil plants at 62 and 92 days (Fig . 

9) . Statistically significant differences occur only for leaf number on primary stems . There 

is extensive within-group variability in numbers of leaves among replicates on lateral 

branches . 

There are significant differences between the high oil treatment and other groups for 

numbers of leaves produced, leaves dropped and leaves on saplings at both 62 and 92 days 

(Table 1) . The high oil treatment produced fewer new leaves (2 .Sx less) ; dropped more 

leaves (at least 3 x more) and had fewer leaves (net) at 62 days. Net leaf production was 

very low in the high oil treatment (9-10 x less than control and the low oil treatment) and by 

92 days, net leaf production in the high oil treatment was negative (i .e ., more leaves were 

being dropped than produced) . 

DISCUSSION 

Effects of No. 6 Fuel Oil 

The similar mortality over the first year in the weathered oil and fresh oil experiments 

was unanticipated since fresh oil is generally considered to be more toxic because of a 

greater proportion of low molecular weight fractions Baker (1970) . The differences in 

suvivorship between control and heavily oiled propagules in the weathered oil study first 

occurred at 10 months (12% lower survival in the heavily oiled plants) and increased to a 

23% difference between treatments by 32 months . The fresh oil experiment showed 10% 

lower survival in the highly oil cover group at 12 months but was not followed longer . 

Results of the experiment with weathered oil suggest that some effects may be long term and 

that experimental studies on oil effects should be lengthened in order to accurately determine 

differences among treatments and controls . 

8 
Effects of Louisiana Crude Oil 

Mortality was greater in the high oil (16 1/m2) treatment and the surviving saplings 

exhibited characteristics which are indicative of stress, including lower growth rates, 

decreased numbers of leaves, and lower net leaf production (total leaf production-leaf drop) . 

The means of application in this experiment was designed to mimic a fresh oil slickcoming 

ashore in a Rhizophora mangle stand, with oil remaining in the sediment and ponding in low 

areas . These results are consistent with those reported by Getter et al. (1985) that mortality 

and stress in R. mangle probably represent responses to uptake of oil and subsequent 

poisoning of transpiration or blockage of metabolic activity . 

Survival of all saplings in the low oil treatment indicates that there is some threshold 

amount of oiling below which mortality of this age class does not occur. However, further 

studies are required to support this contention and quantify the threshold since our 

experiment did not utilize natural environmental conditions such as a salt water medium or 

winter cold. Environmental growing conditions have been shown to modify outcomes of oil 

effects in mangroves (Proffitt et al. 1995). 

The manner of leaf necrosis in this experiment was interesting . Leaf browning 

usually began at the distil tip of the leaf and progressed toward the point of attachment at the 

proximal end of the leaf. A few pairs of leaves browned along one side. Generally a pair, or 

two pairs of leaves located close together, browned simultaneously and at similar rates. 

Observations continue in this on-going study. 

Potential Mechanisms of Oil Stress in Red Mangroves 

Snowden and Ekweozor (1987) found that after a spill of Nigerian crude oil, 

mangrove seedlings oiled over an average of 32% of their surface area survived less than 3 

months. Getter et al. (1985) suggest that the toxic effects of oil on mangroves are short 

term, occurring within 4 months . The results of our weathered oil experiment and the 

Louisiana crude experiment are not consistent with the hypothesis that effects of oiling are 

short term. In these experiments, new mortalities in the High Oil treatment occurred nearly a 

year after application of crude oil; and, in the weathered No. 6 fuel oil study differences in 

leaf production were not noted at 10 months but were found at 32 months . 

Getter et al. (1985) found that application of oil to the waxy stem of the R mangle 

seedlings resulted in less toxicity than when oil was applied to the roots or leaves . They 

suggest that the thick waxy covering of the stem may protect the plant from the oil . Other 

authors have reported that a coating of oil blocks gas exchange in red mangrove prop roots 

and can cause mortality (Teas et al. 1993) . Jimenez et al. (1985) cite several instances 

where mass mangrove mortalities occurred when aerial roots are covered for too long a 

period with water, interrupting gas exchange. In our experiment with weathered oil, the 

medium was thicker and more sticky than the fresh oil and may have acted to block oxygen 

intake through the lenticels. However, we observed that at some time after the No . 6 fuel oil 

coatings in both fresh and weathered experiments had hardened, a brown slightly raised lip 

formed around the lenticels of surviving plants and the lenticels appeared to reopen. This 

phenomenon requires further study. 

9 
Proffitt et al. (1995) suggest that mangrove forests in stressful environments such as 

areas near the physiological tolerance limits for the species, may be more vulnerable to oil 

damage than those in less stressful environments. They also show in experiments using 

lubricating oil that significant interaction terms between oil treatments and environmental 

growing conditions can confound the prediction of effects of oil on red mangrove seedlings. 

Several researchers have noted that in some cases oil seems to act as a growth enhancer, 

resulting in increased stem growth or elongation of mangroves in some oiled sites. It has 

been suggested that the mechanism of growth enhancement may be the release of nutrients as 

oil degrades or increased metabolic rates resulting from oiled (dark) propagules being 

warmer than the unoiled area . We suggest that it is more likely that the increased growth 

resulting in abnormal tree architecture may occur as a result of stress . The increased lateral 

stem growth and associated leaf production may occur as a result of damage to apical 

meristems followed by induced growth of lateral stems. 

Melampus coffeus and Spilled No. 6 Fuel Oil 

The leachate from weathered oil was lethal to adult Melampus coffeus. In the field, 

M. coffeus larger than ca. 4 mm shell length avoid tidal waters by climbing trees to a height 

above the high tide level or onto floating debris . They tend to stay in a relatively small area, 

often climbing up the same or nearby tree for several consecutive days or weeks 

(unpublished data). Since M. coffeus in an aquarium avoided the No. 6 fuel oil which was 

weathered by natural processes, it is probably reasonable to assume that the larger snails 

would also avoid patches of oil in the forest . Juvenile M. coffeus, less than about 4 mm in 

length seldom climb to escape flooding tides, but rather remain in the debris on the forest 

floor. Eggs are enclosed in small gelatinous masses attached to leaves or woody debris and 

are also covered by incoming tides (pers. obs .) . Larvae are released into the water column 

(Apley 1968) . Eggs, small individuals on the forest floor and larger individuals on floating 

debris would be the most likely be killed at the time of the initial oiling . Individuals on trees 

may be able to temporarily avoid contact with the oil . It seems clear that unless > 4mm M. 

coffeus are adaptable enough to change their habitat, and are physiologically able to remain 

out of the water for long periods of time, that they would not survive a spill event that oiled 

extensive portions of the mangrove forest floor. If this is the case, all life stages within the 

affected area would be exterminated if a No. 6 oil spill contaminated much of their mangrove 

forest habitat. Recolonization would have to occur through larval settlement after oil had 

degraded to the point where it would no longer be toxic to the juvenile snails . The time 

period required for oil degradation to levels not toxic to M. coffeus is unknown. 

REFERENCES 

Apley, M.L. 1968. Field and experimental studies on pattern and control of reproduction in 

Melampus bidentatus (Say). Ph .D . Dissertation . Syracuse Univ ., Syracuse, N.Y . 154 

ppBaker, J .M . (1970) . The effects of oil on plants . Environ. Poll. 1 : 27-44 . 

10 
Baker, J .M . (1982) . Mangrove swamps and the oil industry . Oil and Petrochem. Poll. 1 : 5-

22 . 

Baker, J .M ., LM Suryowinoto, P. Brooks, and S . Rowland. (1981) . Tropical marine 

ecosystems and the oil industry : With a description of a post oil spill survey in 

Indonesian mangroves . pp 679-701 . In, Petroleum and the Marine Environment -

Petromar 80 - Eurocean. Graham and Trotman, Ltd., London. 

DeLaune, R.D . , R.P. Gambrell, J .H . Pardue, and W.H. Patrick. (1990) . Fate of petroleum 

hydrocarbons and toxic orgaincs in Louisiana coastal environments . Estuaries 13: 72-

80. 

Dicks, B. (1986) . Oil and the Black Mangrove, Avicennia marina in the Northern Red Sea. 

Mar. Pollut. Bull. 7: 500-503 . 

Duke, N. (1991) . Mangrove Forests . pp 153-178, In, B. Keller and J.B .C . Jackson, (eds) . 

Lon,a-term assessment of the oil spill at Bahia Las Minas Panama. Interim Report. 

Vol. II : Technical Report. U.S . Dept. of the Interior, Minerals Mgmt. Serv . OCS 

study MMS 90-0031 450 pp . 

Estevez, E. and L. Mosura . (1985) . Emergent vegetation . pp 248-278. In, S.F . Treat, J .L . 

Simon, R.R . Lewis, and R.L. Whitman (eds) . Proceedings: Tampa Bay Area 

Scientific Information Symposium . Sea Grant Project No . IR/82-2. Bellwether Press . 

Garrity, S .D ., S .C. Levings, and K.A. Burns. (1994) . The Galeta oil spill I . Long-term 

effects of the physical structure of the mangrove fringe . Estuarine Coastal and Shelf 

Science 38: 327-348 . 

Getter, C.D . (1982) . Oil spills and mangroves : a review of the literature, field and lab 

studies . pp . 303-318 In, Land and Water Issues Related to Energy Development . 

P.J . Rand (ed). Ann Arbor Science, Ann Arbor, MI . 

Getter, C.D ., G.I . Scott, and J . Michel . (1981) . The effects of oil spills on mangrove 

forests : A comparison of five oil spill sites in the Gulf of Mexico and the Caribbean 

Sea . pp. 535-540, In, Proceedings of the 1981 oil spill conference . Amer. Petrol . 

Inst ., Washington, D.C . 

Getter, C.D ., T.G . Ballou, and C.B. Koons. (1985) . Effects of dispersed oil on mangroves . 

Synthesis of a seven-year study . Mar. Pollut. Bull. 16 : 318-324. 

11 
Gilfillan, E.S ., D.S . Page, R.P . Gerber, S . Hansen, J. Cooley, and J. Hothan. (1981) . Fate 

of the Zoe Colocotroni oil spill and its effects on infaunal communities associated 

with mangroves . pp . 353-360. In, Proceedings of the 1981 oil spill conference . Amer . 

Petrol . Inst ., Washington, D.C. 

Jackson, J.B .C., J.D. Cubit, B.D. Keller, V. Batista, K. Burns, H.M . Caffey, R.L. 

Caldwell, S.D . Garrity, C.D. Getter, C. Gonzalez, H.M. Guzman, K.W. Kaufmann, 

A.H . Knap, S.C . Levings, M.J . Marshall, R. Steger, R.C . Thompson, and E. Weil . 

(1989) . Ecological effects of a major oil spill on Panamanian coastal marine 

communities . Sci . 243 : 37-44. 

Jacobi, C.M. and Y. Schaeffer-Novelli . (1990) . Oil spills in mangroves : a conceptual model 

based on long-term field observations . Ecol. Modeling 52 : 53-59 . 

Jimenez, J .A., A.E. Lugo, and G. Cintron. 1985 . Tree mortality in mangrove forests. 

Biotropica 17: 177-185 . 

Kahn, N. A. (1992) . Impacts of the Giant Intentioanal Oil-spill on Jubail, Saudi Arabia . 

Environ. Conserv. 19 : 259-261 . 

Klekowski, E.J ., J.E . Corredor, J.M . Morell, and C.A. Del Castillo . (1994) . Petroleum 

pollution and mutation in mangroves . Mar. Pollut . Bull . 28 : 166-169. 

Lewis, R.R. (1983) . Impact of oil spills on mangrove forests . pp 171-183 . In, H.J . Teas 

(ed .) Biology and Ecology of Mangroves . Tasks for Vegetation Science 8. W. Junk, 

The Hague . 188 pp . 

Page, D.S ., E.S . Giliffan, J .C . Foster, J.R. Hotham, and L. Gonzalez . 1985 . Pages 391-

393 . in, Mangrove leaf tissue sodium and potassium ion concentrations as sublethal 

indicators of oil stress inmangrove trees . Proceedings of the 1985 Oil Spill 

Conference, Amer. Petrol . Inst ., Washington, D.C . 

Proffitt, C.E. and D.J . Devlin. (In preparation) . Are there cumulative effects in mangroves 

of oil spills during seedling and sapling stages? 

Proffitt, C.E ., D.J . Devlin, and M.L. Lindsey. (1993) . Mixing oil and Mangroves: Survival 

and growth of seedlings . pp 795, In. M.C . Landin (ed), Wetlands : Proceeding 

the 13th Annual conference, Society of Wetland Scientists . Publ . by South Central 

Chapter, Soc . of Wed. Sci. 

Proffitt, C.E., D.J . Devlin, and M.L. Lindsey . 1995 . Effects of Oil on Mangrove 

Seedlings Grown Under Different Environmental Conditions . Mar. Pollut . Bull. 30: 

788-793 . 

12 
Snowden, R.J . and I.K .E. Ekweozer . (1987) . The impact of a Minor Oil Spillage in the 

Estuarine Niger Delta. Mar. Pollut . Bull. 18: 595-599 . 

Spooner, M. (1970) . Oil spill in Tarut Bay, Saudi Arabia. Mar. Pollut. Bull. 1 : 166-167. 

Teas, H.J ., R.R. Lessard, G.P . Canevari, C.D. Brown, and R. Glenn. 1993 . Saving Oiled 

Mangroves using a new Non-dispersing Shoreline Cleaner. pp 147-151 . In, The 

proceedings of the conference on assessment of ecological impacts of oil shills . Amer. 

Inst . Biol . Sci., Washington, D.C . 

13 
Table 1 

Sapling Rhizophora mangle numbers of new leaves produced, dropped, and net (ProductionDrop) at 62 and 92 days following experimental exposure to Louisiana sweet crude oil 

applied to the sediment and base of plant . Values are means (1 standard deviation) . Letters 

indicate no significant differences among treatments (one-way ANOVA and Tukey multiple 

comparisons tests) . 

Numbers of Numbers of Net Leaf 

New Leaves Leaves Dropped Production 

Produced 

62 DAYS 

Control 3 .9(3 .3) A 0.1(0.3) A 3 .9(3 .3) A 

Low Oil 4.5(3 .8) A 0.1(0.3) A 3 .8(3 .7) A 

High Oil 1 .4(2 .0) B 0.9(1 .3) B 0.4(2.3) B 

92 DAYS 

Control 6.1(4 .7) A 0.3(0.8) A 5 .8(4 .2) A 

Low Oil 6.3(4 .4) A 0.8(1 .2) A 5 .5(4 .4) A 

High Oil 2.4(2 .8) B 2.9(1 .8) B -0.5(1 .9) B 

14 
50 

D 

a 

to 

q 

v 

b 

0 

ti 

a 

to 

b . .., 

'd 

w 

O 

D 

.. 

40 - 

01--~ 0000 

0000P 

OW 

60 

~~~ i 

30 

- 

20 - 

l 

10 ~ T 

0 

0 40 80 120 160 200 240 280 320 360 400 

z 

DAYS 

Legend 

Control (no oil) 

50 % of Surface 

Area Oiled 

" 100 90 of Surface 

Area Oiled 

Figure 1 . Rhizophora mangle cumulative numbers of seedlings producing 

leaves after experimental oiling of propagules with unweathered 

No . 6 fuel oil . 
200 

160 

`r 120 

0 

80 

40 

0 

C L H C L H 

105 DAYS :398 DAYS 

Figure 2. Rhizophora mangle Seedling propagule stem 

growth under different experimental treatments 

of unweathered No . 6 fuel oil applied to the 

surface of the propagules . Values are means and 

1 S.D . Letters indicate significant differences (oneway ANOVA and Tukey multiple comparisons tests, 

p<0 .05. 

16 
O V 

° 

a 

o 

Z a) 

r_4 > 

cd 

0 1_4 

E-4 

00 OOF 

OF ae 

/ ~ . 

0 

L40;00T I 

O 

5 10 

Months 

Sig . Diff . 

CONTROL A 

LOW(50%) B 

HIGH(100%) B 

Figure 3 . R. mangle seedling propagule leaf production 

under different experimental treatments of unweathered 

No . 6 fuel oil applied to the surface of the propagules . 

Values are means and 1 S .D . Letters indicate significant 

differences (one-way ANOVA and Tukey multiple 

comparisons test, p<0 .05) . 

17 
r 

100 

10 - ' - - " - - - _~ Control (No oil) 

so ~ ~ - , 

-V Low Oil <50%

6 0 ~---~ High Oil (>50 

40 

U 

20 

0 

0 5 10 15 20 25 30 35 

Months 

Figure 4. Percent of R. mangle seedling propagules surviving being oiled during 

a spill of No . 6 fuel oil (weathered several days prior to coming ashore). 

Controls had no oil cover, Low Oil had <50 % of surface area covered 

with oil, and High Oil had >50 % surface area cover by oil . 
r 

Stem Growth (mm) 

a 900 

.,, 

+ 600 

q ., ., 

300 

0 

400 

300 

200 

q 

m 100 

0 

m 500 

400 

300 

200 

., 100 

0 

0 

NSD 

KSD 

3D 

Lish 011 t 

oatrol A,H 

Low oil H 

Total Leaf Production 

60 

'd 

rn 4 0 

Q 20 m 

0 

30 

.~ z o 

.,p ., 10 

m 

0 

16 

12 

8 

'd .r.,4 

0 

0 

3D 

;ish Oil A 

:oatrol 

Low oil 

xsn 

3D 

31gh 011 t 

Low Oil H 

Control B 

Figure 5 . Stem growth and leaf production of R. mangle seedlings following oiling 

by a spill of No . 6 fuel oil . Controls had no oil cover, Low Oil had <50% 

surface area cover, and High Oil had >50 % cover with oil . NSD = No 

significant difference among groups . SD = significant difference at p<0 .05 

and letters indicate differences among means (one-way ANOVA and Tukey 

multiple comparisons. Main+Sides =total growth . 

10 20 30 

Months 

10 20 30 

Months 
0 

100 

80 

., ., 

D 

60 

b 

U 40 

20 

0 

Control 

Exposed 

DAYS (continual exposure) 

Figure 6 . Percent survival of the mangrove forest gastropod Melampus coffees L. 

following exposure in aquaria to seagrass oiled by a No . 6 fuel oil spill 

in Tampa Hay, FL . 

Cm ", 

0 5 10 15 20 
Lour Oil 

100 

T 

Control 

80 

6 0 

U 4 0 " . " 

it 

~-~ High Oil 

20 

0 

0 50 100 150 200 250 300 350 

Days 

Figure 7 . Percent survival ~f R. mangle saplings exposed to no oil (Control), 

Low Oil (1 .6 L/m ), or High Oil (16.0 L/m ) . The oil used is south 

Louisiana sweet crude. 
10-1 30 

b 20 

o 

10 

0 

30 30 AAH AAB 

o 

20 20 

A A B A A H 

10 -010 

a 

~d 

0 C L H C L H C L H C L H 

62 DAYS 92 DAYS 62 DAYS 92 DAYS 

Figure 8. R. mangle sapling stem growth following 

experimental exposure to Louisiana sweet crude 

oil . C=control (no oil), L=low oil (1 .6 L/m 

z 

), 

H = high oil (16 L/m2 ) . Top graph is total stem 

growth . The bottom two graphs give the breakdown 

of total growth into main stem growth and lateral 

branch growth . Values are means and 1 S.D . Letters 

indicate signficant differences (one-way ANOVA and 

Tukey multiple comparisons tests) . 

22 

C L H C L H 

62 DAYS 92 DAYS 
25 

m 

~ 20 

a 

w 

° ,b 1 5 

z + io 

P-4 0 

. .. 

0 

E+ 

0 

A A D A A H 

0 20 NSD NSD (U 

.x' 15 15 Q 

0-4 In A,B A B 

CCU 

A A B b 

p " ~ 10 ~ 10 

cd 

0 

~ 5 5 

z o 

0 a 0 

C L H C L H C L H C L H 

62 DAYS 92 DAYS 62 DAYS 92 DAYS 

Figure 9. R. mangle sapling numbers of leaves at 62 and 92 

days follfowing experimental exposure to Louisiana 2 

sweet crude oil . C~ control (no oil), L=low (1 .6 L/m ) 

H=high (16.0 L/m ) . The top graph is total numbers. The 

of leaves per plant. The bottom two graphs give the 

breakdown of the total into leaves on main stems and 

leaves on lateral stems . Values are means and 1 S .D . 

Letters indicate significant differences (one-way ANOVA 

and Tukey multiple comparisons tests) . 

23 

C L H C L H 

62 DAYS 92 DAYS 
The 1993 Tampa Bay Spill: 

Preliminary Assessment of Natural Resources 

Jane S . Urquhart-Donnelly 

Florida Department of Environmental Protection 

Bureau of Emergency Response 

2909 Bay-to-Bay Blvd. Suite 404 

Tampa, FL 33629 

INTRODUCTION 

At 5 :50 am on August 10, 1993, two tank barges and a phosphate freighter collided at 

the mouth of Tampa Bay, between Egmont Key and Fort DeSoto Park. The collision caused 

an explosion igniting a fire on the Maritrans Barge Ocean 255, which continued to burn for 18 

hours . Before they abandoned ship, the crew on the burning barge grounded the vessel at Ft 

Desoto Park, thereby saving the vessel and most of the nine million gallons of petroleum 

onboard. Approximately 300,000 gallons of mixed light product (diesel, jet A and gasoline) was 

missing from the Maritrans barge when it was lightered off. An estimated 30,000 gallons of this 

was discharged into Tampa Bay. The remainder allegedly consumed by the 18 hour fire onboard . 

The Barge B-155, owned by Bouchard Transportation, was struck by the Balsa 37 in the #1 port 

tank sustaining a rupture the size of a three story building, causing an instantaneous release of 

an estimated 328,440 gallons of the 5 million gallons of No. 6 fuel oil . The phosphate freighter 

Balsa 37, owned by the Tsacaba Shipping company of the Philippines sustained major damages 

to its starboard side . It was grounded off Egmont Key to prevent its sinking . 

Initially, oil came ashore at Fort Desoto Park and Egmont Key impacting beaches, 

seagrass beds and mangroves . But the vast majority of the oil was carried up to 13 miles 

offshore and remained off Pinellas County for several days, before west winds carried the oil 

onshore the 14th of August. The oil was deposited above the mean high water line along 14 

miles of beaches . It was also carried through several tidal passes up the Pinellas County 

coastline impacting commercial, residential and environmentally sensitive areas. 

Immediate impacts included the closure of the Port of Tampa, portions of the IntraCoastal Waterway, Fort DeSoto Park, Egmont Key State Park, and 14 miles of recreational 

beaches . Natural resource damages included the impacts to the water column, fisheries 

resources, mangroves, salt marshes, seagrass beds, birds, and sea turtles. 

The most visible portion of the cleanup effort was focused on the beaches . Over 1,900 

cleanup workers and hundreds of graders, bulldozers and dump trucks were on the beach at one 

time . The gross contamination was removed by hand with subsequent reworking by heavy 

equipment. The beaches were officially declared clean by Sept 6th for the Labor Day Weekend. 

Since that time 12 reoilings have occurred in response to storm fronts from the west. 

Subsequent cleanup efforts have taken from 2 to 7 days. 

24 
The back beach cleanup continued long past the Sept 6th date. Cleanup crews hot 

washed approximately 21 miles of seawall, innumerable docks and cleaned hundreds of vessels. 

Experienced crews were detailed to work the environmentally sensitive areas. Cleanup crews 

worked the John's Pass area until December . Areas of submerged oil have continued to be 

discovered, with the latest oil recovery operations occurring in June . 

The Oil Pollution Act of 1990 (OPA 90) provides for the designation of natural resource 

trustees to act on behalf of the public to recover damages to natural resources. The Department 

of Environmental Protection as trustee for the State of Florida, the National Oceanic and 

Atmospheric Administration (NOAA) and the U.S . Department of the Interior (DOI) as Federal 

trustees entered into a Memorandum Of Understanding to jointly perform a Natural Resource 

Damage Assessment (NRDA) in accordance with OPA 90. Under applicable laws the trustees 

are allowed to develop their own assessment strategies for each event. Florida's Pollution 

Discharge and Prevention Control Act provides a compensation schedule to calculate the natural 

resource damages for discharges less than 30,000 gallons. For spills greater than 30,000 gallons 

the responsible parties (RPs) have the option to request a formal damage assessment. Each 

vessel owner involved has opted for the formal scientific damage assessment. 

The assessment approaches discussed were developed by the trustees, with participation 

and comment by the Potential Responsible Parties (PRPs) technical and legal consultants . 

Nothing in this document is meant to reflect a final determination of the facts of this incident 

or the final assessment, as the assessment activities are ongoing. 

METHODS AND MATERIALS 

Injury categories were identified as : mangroves, water column (finfish, plankton), birds, 

sea turtles, seagrasses, salt marshes, shellfish beds (biological and recreational use closures), 

bottom sediment injury, beach physical injury, shoreline lost use value, and surface water 

access . 

Extensive amounts of baseline data on the natural resources of Tampa Bay exist. State 

and Federal environmental programs have collected and synopsized data concerning floral and 

faunal distribution, abundance, and population trends in Tampa Bay. Current land use, wetlands 

mapping, aerial photography, population and recreational use data were available from a variety 

of sources. At the time of the spill State and Federal studies pertaining to surf zone fishes, 

invertebrates, seagrass beds, turtle nesting activity, zooplankton and larval fish were ongoing . 

These studies were identified and the principal investigators contacted so that these studies could 

be expanded to include assessing the impacts of the oil spill . The National Pollution Fund 

Center made available video of the spill and associated response. 

Most components of the damage assessment will be quantified using site specific 

information and analysis . However, for some injury components, conducting detailed site 

specific studies was determined not to be cost effective . These assessments will be determined 

through the use of applicable models . 

25 
Impacted habitats and their pre-spill condition was initially documented using historic 

aerial photographs . Since the spill two series of aerial real color and infrared photographs have 

been taken to document initial contact and post spill condition of mangroves, saltmarsh, 

seagrass, and shellfish systems. 

A professional survey was performed to precisely measure the extent of impact. DEP 

coordinators flagged the extent of oiling for the survey crews . Lightly oiled areas were not 

included in the professional survey to minimize the impacts of survey activities . 

SHORELINE RECREATION, SHELLFISH RECREATIONAL HARVESTING, SURFACE 

WATER AND PORT CLOSURES 

The trustees have contracted for studies to assess the injuries resulting from the lost 

public use and/or nonuse of recreational beaches, recreational shellfish harvesting, surface water 

access and port closure . Preliminary studies will conclude in August, with the full study and 

final report scheduled to be completed in December 1995 . 

BIRDS 

Injuries from oil included direct injury as a result of oiling, ingestion, and stress 

resulting from capture and cleaning, and indirect injury through habitat loss and disruption of 

nesting and foraging activities . Bird rescue efforts accounted for the recovery of 371 oiled birds 

of which 53 individuals were recorded dead on arrival, euthanized or died in treatment. 318 

birds were released after rehabilitation. The trustees estimate that at least twice that number 

have been affected to date. 

TURTLES 

Four (4) loggerhead sea turtle (Caretta caretta) (federally threatened) hatchlings were 

killed . Twelve loggerhead sea turtles and one juvenile green sea turtle (Chelonia mydas, 25 cm 

carapace length) (federally endangered) were recovered oiled, cleaned, rehabilitated and 

released . 

At the time of the spill, there were 115 known loggerhead nests on the Pinellas County 

beaches . Of these 96 nests were at risk . Fourteen nests had to be protected from oil by 

trenching and booming. Subsequently two nests were inundated by oil . Evaluation of the two 

oiled nests revealed that they contained a total of 176 unhatched and 9 hatched eggs . A third 

nest was partially destroyed by heavy cleanup equipment, resulting in the destruction of five 

loggerhead sea turtle eggs . 

Twenty-nine nests hatched during the spill response . Hatchlings from 23 of these nests 

(about 1530 turtles) were restrained after nest emergence and released at oil free sites. About 

413 hatchlings from 6 nests were not restrained and entered the water at sites where surface 

waters may have contained oil . 

26 
Although the number of sea turtles directly observed to be affected was small, these 

species are listed as Federal and State endangered or threatened species. Restoration options 

include funding of sea turtle management activities or stranding network activities . 

MANGROVE 

Mangrove impacts occurred in two areas; Bonne Fortune Key at Ft Desoto Park and on 

four keys inside John's Pass in Boca Ciega Bay. The mangroves impacted were within mature 

forests which included black mangroves (Avicennia germinans), red mangroves (Rhizophora 

mangle), white mangroves (Laguncularia racemosa) and buttonwood (Conocarpus erectus) . 

The trustees propose using a habitat replacement analysis to determine the amount of 

necessary restoration . The analysis provides an estimate of the amount of new mangrove 

acreage that will have to be created in order to compensate the public for both direct injury and 

the ecological services lost prior to the restored mangrove areas reaching baseline (pre-discharge) 

productivity . The biological parameters needed for the habitat replacement analysis include: 

extent of oiling ; percent of ecological services lost initially ; number of years to full natural 

recovery ; the functional form (shape) of the recovery curve ; years to full ecological service flow 

after creation; functional form (shape) of the "maturity" curve for the created habitat; relative 

productivity of created vs. natural mangrove habitat ; and costs to create mangrove habitat. The 

inputs for these parameters will involve a combination of field measurements, literature values 

and professional judgment . Specific data needs were identified and contracts have been entered 

into to meet these requirements. 

Prior to the commencement of the professional survey, DEP coordinators, Florida Game 

Fresh Water Fish Commission biologists, the survey project manager and the RP's biological 

representatives met onsite to discuss the methods and constraints on the survey due to nesting 

and roosting colonial waterbirds . DEP coordinators flagged the extent of oiling for the survey 

crews . Lightly oiled areas were not included in the professional survey to minimize the impacts 

of survey activities on the rookery. At least 5 .5 acres of mangroves were either moderately or 

heavily oiled. 

NOAA contracted with Coastal Zone Analysis (pers . com.) for a study to estimate the 

amount of injury to the mangrove islands directly or indirectly caused by the oil. Further to 

document the extent and nature of the injury, predict the long-term impacts and evaluate possible 

restoration alternatives . Since August field work has included: 

1) Documenting percent of cover of oil and epibiota on submerged red mangrove prop 

roots, root shape and size and root density. Black mangrove pneumatophores were 

collected and length, percent cover of oil and epibiota recorded for each. Leaves were 

collected from the canopy for each species of mangrove and pressed . 

2) Extent of oil penetration from the fringe inward was recorded . 

27 
3) Forest structure was recorded for both Eleanor and Rookery Key. 

4) Seedling and sapling mortality was examined by marking juvenile red, black and white 

mangroves (n=650 plants tagged) . 

5) Toxicity of oiled sediments was examined by using common garden plot experiments 

(n=29 paired replicates, 522 propagules planted) . 

The University of South Florida and Mote Marine Laboratory (pers . com.) under contract 

with DEP will commence a study to assay the toxicity of the sediments to further address the 

ability to proceed with restoration activities . Five cores will be collected from oiled areas, as 

well as three cores from unoiled areas, and will be divided into two equal sections for analysis . 

Hydrocarbons will be extracted and separated into aliphatic and aromatic fractions using methods 

currently in use by USF and Mote . 

WATER COLUMN 

Over the course of its trajectory, the discharged oil cumulatively contacted approximately 

300 square miles of open Gulf waters and 27 square miles of embayment waters . Elevated Total 

Petroleum Hydrocarbon (TPH) levels were recorded during the days following the discharge in 

water samples from several of the bay areas (Mote Marine Lab, pers. com.) . 

Due to the extremely difficult and expensive task of directly measuring injury to water 

column organisms, the trustees propose that models, including the Type A Model, be considered 

to assess water column injuries (e .g ., finfish, plankton, etc.) . DEP has collected a large amount 

of pre- and post-discharge data applicable to this injury . To the extent possible, site specific 

information will be used to validate the predictions of the model selected . 

SALTMARSH 

The discharge resulted in 0.85 acres of salt marsh vegetation being exposed to heavy 

oiling, including marsh vegetation within Boca Ciega Bay from mouth of John's Pass to 

Gulfport. Field surveys in April indicated that 0.75 acres were damaged. 

SEAGRASS 

The discharge resulted in the loss of approximately 2 .5 acres of seagrasses from exposure 

to oil mats and response activities . Most of the heavy to moderate oiling of seagrasses occurred 

in Boca Ciega Bay in the area near John's Pass and southward. Additionally, 255 acres near 

Mullet Key, Egmont Key, and in Boca Ciega Bay near John's Pass, are known to have been 

exposed to the floating oil slick from the discharge . 

DEP's professional survey of impacted seagrass beds included a number of different 

elements. Those areas which had been manually cleaned (vacuumed) prior to the survey . Areas 

28 
where oil was still present as patchy mousse patties within the seagrass beds (often covered by 

silt) and areas mechanically denuded by the boat\barges and other cleanup equipment and 

activities . All three of these area types were included within the seagrass survey . 

The Technical Working Group attempted to evaluate the extent of remaining submerged 

oil within seagrasses in early January 1994 by transect survey methods . While trace amounts 

of oil were noted during the survey, no areas of gross contamination were detected at that time. 

Subsequent to that survey submerged patties have been documented in the area and four different 

cleanup efforts initiated by the RPs. This month the USCG has contracted with Oceans Systems 

for a diving survey of Blind Pass to document and map the submerged patties in the channel . 

Submerged oil remains a persistent problem. 

Aerial photography, historical and ongoing research activities are being used to further 

document seagrass bed loss . Comparison of historical and post-discharge studies of seagrass 

community structure may be used to evaluate the significance of the floating oil exposure for the 

additional 255 acres . 

Prior to the spill, Hall and Bell (pers . com.) had an ongoing research project with sites 

within the spill trajectory . At the trustees request these investigators revised their sampling dates 

and sampled sites within the spill area on August 13th . Observations made suggested that 

Egmont Key was the site most directly affected by oil although an oil sheen was present at Ft. 

Desoto (east beach site) . Thalassia testudinum was the seagrass present at all sites except for 

Bunces Pass and Ft. Desoto where Halodule wrightii was dominant. All sites were sampled 

August 13th and midday December 14-January 27 1994. At each site samples were collected 

for fish, macroepifauna and blade dwelling meiofauna . Three throw traps were haphazardly 

tossed into each site . From within each trap, three samples of seagrass blades were collected 

according to the methods of Hall (1988) . Fish and macroepifauna were collected by dipnetting 

and seining both with a 3 .2 mm mesh net. Repetitive dipnetting was conducted until five dipnets 

in a sequence failed to capture any fish . Approximately 95% of all shrimp are also collected 

by this procedure (Bell and Fonseca, unpubl .) . After dipnetting the traps were seined until three 

successive passes failed to capture any fish . This technique efficiently captures both the 

macroepifauna and the small (15-60 mm standard length) size class of fish in seagrass beds. In 

addition to these samples, three benthic cores were collected from each trap and archived . 

SHELLFISH BEDS 

Preliminary shellfish studies focused on public health concerns involving shellfish 

consumption. Three areas within the projected spill trajectory were closed to shellfishing on 

August 10. Lower Tampa Bay (Manatee Co.) remained closed until September 23, 44 days after 

the spill . At that time clams in the Mullet Key area were found to still have continued elevated 

levels of hydrocarbon contamination so that the south Boca Ciega Bay shellfishing area remained 

closed until November 30, 112 days after the spill. The oyster sample collected in John's Pass 

was found to be grossly contaminated by oil (Sherblom and Pierce 1993). This organism had 

significant tissue burdens of not only the n-alkanes, but also polycyclic aromatic hydrocarbons 

29 
and other cyclic compounds. The body burden of these organisms was thought to be of 

sufficient concentration that detrimental effects were likely to be observed in the impacted 

population . The oil related components found in this sample were not only potentially toxic to 

the oysters themselves, but would also be detrimental to any organisms preying on the stressed 

oysters . 

The University of South Florida and Mote Marine Laboratory under contract with DEP 

will commence a study to assay the residual oil within the oyster bed to help address the ability 

to proceed with restoration activities . Live oysters and shell hash will be collected at three 

places on each of two oyster beds . Live oyster tissue will be analyzed for contamination and 

shell hash will be analyzed for residual oil within the oyster bed . 

BEACH PHYSICAL INJURY 

Beaches from Indian Shores in central Pinellas Co. to Egmont Key on the southern tip 

of Pinellas Co. were oiled. As a result of cleanup activities associated with this oiling at least 

39,827 cubic yards of sand were removed from public beaches . Beach impacts were 

documented via the State survey, aerial real color photos and video . Under a State permit issued 

during the spill response, the cost of sand replacement must be paid by the responsible party . 

Natural resources associated with beach oiling impacts are assumed to be short term in nature 

and the replacement of the sand on the beaches will fully compensate for these impacts . Other 

impacts are being assessed indirectly by a surf zone fish study which was in progress at the time 

of the spill and is still in progress . 

SEDIMENTS 

Several areas of submerged oil in contact with the subtital sandy sediments just off 

Pinellas County beaches, as well as in mudflats and in deeper areas of Boca Ciega Bay were 

documented. Surveys conducted during spill response indicated that at least 58,540 square feet 

(1 .3 acres) of subtidal sediments had been covered by submerged oil patties or mats . Subsequent 

reoilings on the beach and within Boca Ciega Bay indicate that submerged oil continues to 

spread and move, exposing and re-exposing additional areas. This oil is well weathered and 

relatively insoluble, thus minimizing toxicity from external exposure, but physical smothering 

in areas of these deposits would result in injury to sediment associated biota. Ingestion of oil 

particles or oil contaminated sediments would also result in injury to the sediment associated 

biota . 

The trustees have determined that it is not technically feasible to determine by direct 

survey the extent of the remaining submerged oil in the Gulf of Mexico and Boca Ciega Bay. 

Alternative assessment approaches include : 1) calculation of the potential amount of oil 

remaining unaccounted for, using a mass balance approach, or 2) applying specific oil fate 

models which can be used to estimate the amount of injury to the biota, as well as the value of 

the injury if appropriate. 

30 
REFERENCES 

Hall, M.O. 1988 . Dynamics and interactions of epiphytic meiofauna on the seagrass Thalassic 

testudinum. Ph. D Dissertation . University of South Florida, Tampa, Fl. 170 pp. 

Sherblom, P.M . and R.H . Pierce . 1993 . Analysis of shellfish samples from the Tampa Bay area, 

Following the August 10th oil spill, technical report . Fl. DEP #S 3700 431111, Mote 

Marine Laboratory Technical Report No. 335, Sarasota, Fl ., 20 pp. 

31 
Environmental Distribution of Oil-Related Hydrocarbons Following a 

Spill of Number 6 Fuel Oil in Tampa Bay 

D.L . Wetzelj-, P.M. Sherblom$', E.S. Van Vleetj-, R.H. Pierce, M.S . Henry* and D. Kelly. 

fiUniversity South Florida 

Department of Marine Science 

St. Petersburg, FL 

$Mote Marine Laboratory 

Sarasota, FL. 

'Present address : Department of Environmental and Occupational Health, MDC-056, University 

of South Florida, 13201 Bruce B. Downs Blvd ., Tampa, Florida 33612-3805 . 

INTRODUCTION 

In the early morning on August 10, 1993, approximately 1 .2 million liters (320,000 gal) 

of Bunker C (No. 6) fuel oil spilled from the fuel tanker Bouchard 155 after it collided with the 

jet fuel barge Ocean 255, and the phosphate freighter Balsa 37 in a shipping channel at the 

entrance to Tampa Bay, Florida . The position of the leaking tanker was N 27°36.41', 

W 82°40 .30' at 0600 hours on that morning . The collision caused explosions, fire and a 27 km 

long oil spill . 

The Balsa 37, carrying 6000 tons of phosphate, was outbound in a shipping channel 

leading from Tampa Bay, Florida, the nation's seventh busiest port. It cut left across the bow 

of the Ocean 255, carrying 30 million liters (7 .9 million gallons) of jet fuel, which was passing 

to the left of the Bouchard 155. Both vessels were headed inbound when the collision occurred 

with all three vessels . The Ocean 255 exploded and burned sending flames over 100 feet in the 

air. The highly volatile jet fuel quickly burned or vaporized apparently leaving no lingering 

fuel . The Balsa 37 sustained no serious damages and no phosphate cargo discharge. However, 

the Bouchard ISS suffered severe injury, and spilled 7600 barrels of highly viscous, high 

molecular weight Bunker C fuel oil . The barge began leaking at the point of impact, but came 

to rest near the Sunshine Skyway Bridge which spans the mouth of Tampa Bay, Florida. 

Although winds and currents carried the majority of the spilled oil out of Tampa Bay and into 

the Gulf of Mexico, significant quantities were deposited on nearby beaches and in mangrove 

and seagrass habitats. Subsequent changes in wind direction brought the oil back to Gulf 

beaches and estuarine habitats north of the mouth of Tampa Bay. 

The distribution and fate of oil entering the marine environment depends on properties 

of the oil and the environmental conditions . The complex mixture of petroleum components is 

altered (weathered) through processes such as evaporation, dissolution, vertical dispersion, 

emulsification, sedimentation, photo- and microbial degradation (Farrington 1980, NRC 1985, 

Volkman et al. 1992) . Weathering of the entire mixture of compounds occurs simultaneously, 

however, the hydrocarbon profile changes over time due to differential degradation dissolution 

of the various chemical compounds . Petroleum hydrocarbon alteration from weathering can be 

summarized as follows: loss of low boiling (< nC22) hydrocarbons through evaporation and 

dissolution, biodegradation of the n-alkanes with a proportional increase in the percent of the 

32 
unresolved complex mixture (UCM) and polycyclic aromatic hydrocarbons (PAH's), followed 

by a subsequent shift in the relative abundance within the (UCM) towards higher molecular 

weight compounds (Farrington 1980, Van Vleet et al . 1984, Pierce et al. 1986, Burns et al. 

1993) . 

On August 11, 1993 (one day following the Bunker C fuel oil spill from the Bouchard 

ISO, a cooperative University of South Florida (USF), Florida Institute of Oceanography (FIO), 

United States Geological Survey (USGS) cruise was carried out in the area to collect sediments 

from the area of the spill . At the same time, Mote Marine Laboratory of Sarasota, Florida, was 

carrying out a similar study in the area on water and shellfish. USF has continued a year long 

monitoring of sediments in some of the affected areas, particularly Eleanor Island, a protected 

mangrove island inside Boca Ciega Bay. In addition, Mote Marine and USF have entered into 

a joint post-spill assessment of this island . 

METHODS AND MATERIALS 

Water Sampling Sites and Collection 

Distribution and transport of the oil in the water column was investigated by collecting 

near-surface (0.3 m depth) water samples from 20 sites throughout the mouth of Tampa Bay and 

the near-shore Gulf of Mexico on August 12, 1993 (Figure 1). Samples were also collected 

from 2 m depth at three of the sites, to assess the potential for vertical mixing of the oil . Near 

surface water samples were collected from an additional 12 sites through out Bunces Pass and 

Johns Pass on August 17, 1993, to observe redistribution of the oil by wind and surface 

currents . A patch of the spilled oil with associated seawater was collected on each of the above 

dates to assist in identification of the source material . A sample of the barge oil was obtained 

from The National Oceanic and Atmospheric Administration, Office of Damage Assessment, for 

comparison with environmental samples. 

Water samples were collected by siphoning through precleaned silicone (silastic) tubing 

into clean, 4-liter amber glass bottles . Surface tar ball and oil slick samples were collected by 

submersing the mouth of the bottle half-way into the slick water to skim the oil and associated 

water from the surface. 

Water Sample Extraction and Analyses 

Samples were stored over ice for transport to the laboratory, spiked with recovery 

surrogates (octadecene, C,g :, for aliphatics, and deuteratedp-terphenyl for aromatics), and stored 

under refrigeration until extraction. Storage time was less than 24 hours for all water samples 

except the two oil-water mixed samples, which were refrigerated for several days before 

extraction. For the oil-water samples, the aqueous phase was separated from the overlying oil 

either by passing it through a pre-cleaned glass wool plug (August 12), or by carefully pipetting 

the water into a separatory funnel, avoiding the transfer of any visible oil droplets (August 17). 

Oil solutions were prepared for chromatographic analysis by diluting a weighed amount of oil 

(4-6 mg) with hexane in a 10 ml volumetric flask. 

All water samples were extracted three times with dichloromethane (DCM). Extracts 

were reduced in volume using rotary evaporation ; samples which still contained water were 

placed in small separatory funnels and the aqueous phase was rinsed (3x) with DCM, which was 

collected and further reduced in volume. The concentrated extracts were passed over anhydrous 

33 
sodium sulfate and exchanged into hexane . The hydrocarbon fraction was isolated using 

combined silica gel/alumina columns (12 g/6 g) slurry packed into chromatography columns. 

The extract was applied to the column in 0 .5 ml hexane and the hydrocarbons were eluted using 

20% DCM in hexane . 

The hydrocarbon fraction was reduced to near dryness with N2 and taken up in a solution 

containing a quantitation standard (docosene, C22:, and o-terphenyl) and analyzed by capillary 

gas chromatography with flame ionization (GC/FID) . Chromatographic analyses were 

performed with a Varian 6000 gas chromatograph with a flame-ionization detector . The column 

was a 30 m J&W DBS, with He carrier gas and a temperature program of 45°C to 280°C at 

6°C/min, holding at 280°C for 30 min, interfaced with a Perkin-Elmer/Nelson 2600 

chromatography data system and a 486 computer for data compilation, analysis and presentation . 

Efficiency of hydrocarbon extraction and recovery from the water samples was 

determined by comparison to the known amounts of reference surrogates (RS) added to each 

water sample prior to extraction. Quantitation of the extractable hydrocarbons was provided by 

normalization to the known amounts of quantitation standards (QS) added after extraction. 

Selected confirmatory analyses were performed with a Varian Saturn II ion trap GCMS using 

a J&W DBS-MS capillary column. 

Sediment Sampling Sites and Collection 

Surface sediments (approximately top 5 cm) were collected near the spill site in lower 

Tampa Bay on August 11, 1993 (1 day following the spill) and on September 1, 1993 

(approximately three weeks after the spill) . Twelve different sampling sites were chosen (six 

each day) for sediment collection in order to investigate the transport of oil to sediments near 

the spill (Figure 2B). Four days after the spill (August 14, 1993), oil began to wash ashore 

along Pinellas County beaches located to the north. Oil was also carried through John's Pass 

into Boca Ciega Bay where it fouled several mangrove islands. The island that was oiled most 

was Eleanor Island, located just inside John's Pass (Figure 2A). Oil globs were first collected 

along this island on August 25, 1993 (approximately two weeks after the spill) . Oil globs were 

then collected from this same site approximately every 2 weeks through June 10, 1994. The 

purpose of this portion of the study was to investigate the chemical weathering of the Bunker 

C fuel oil over time in this subtropical environment. As of the June 10 collection date, intact 

oil patches (1-3 cm thick) were still widely distributed along this portion (and along other 

portions) of the island . 

Sediment Extractions and Anal 

Approximately 100 g (wet weight) of each sediment sample collected near Egmont Key 

were extracted by refluxing with 2:1 (v/v) dichloromethane:methanol. Internal standards (Saandrostane and o-terphenyl) were added to each sample prior to extraction for quantitative 

hydrocarbon analysis . The extracts were separated into F1 (aliphatics/saturated) and F2 

(aromatics/unsaturated) fractions by silica gel-alumina column chromatography, and eluted with 

hexane for the F1 fraction and 1 :1 hexane : toluene for the F2 fraction. Each oil (tar) sample 

collected from Eleanor Island was dissolved in hexane, in the presence of an internal standard, 

and separated by column chromatography as above . 

All hydrocarbon fractions were analyzed by high resolution gas chromatography (GC) 

using a Shimadzu GC-14A equipped with a 25 m DB-5 fused silica column and flame ionization 

34 
detector, using hydrogen as the carrier gas . Oven temperature was programmed from 80°C to 

280°C at 4°C/min and held at 280°C for 10 minutes . The peaks in the F1 fraction were 

identified by comparing peak retention times with a known alkane standard or by co-injection 

with authentic standards . A sample of the Bunker C fuel oil taken from the Bouchard 155 by 

the Coast Guard, was analyzed by GC for matching the alkane characteristics of the Bunker C 

fuel oil with those found in the samples. Total F2 hydrocarbon fractions were analyzed by GC 

and quantitated by comparison of the total F2 area with the area of the internal standard. 

Selected F2 fractions were analyzed by combined gas chromatography-mass spectrometry 

(GCMS) for qualitative and quantitative identification of individual PAH's. Samples were 

analyzed by electron impact ionization (70 eV) using a Finnigan INCOS-50 GCMS system 

interfaced with a Hewlett Packard 5890 gas chromatograph. Gas chromatographic conditions 

were the same as those used above, however helium was used as the carrier gas . The mass 

spectrometer was scanned from mass 40-500 in 0.5 sec . All mass spectral data was compared 

to spectra produced by authentic standards and by comparison to previously published spectra . 

RESULTS AND DISCUSSION 

Water Samples 

Characterization of the oil is provided by a gas chromatographic (GC) hydrocarbon 

profile of the No. 6 fuel oil collected from the barge, Bouchard 155 . The results of the total 

hydrocarbon (THC) profile are shown in Figure 3, along with the profile of a tarball collected 

from the mouth of Tampa Bay 8/12/93, and a sample of a larger oil patch collected in the Gulf 

8/17/93 . The original oil sample exhibited a n-alkane distribution from nClo to nC32, with the 

most abundant n-alkanes in the range of nC,b to nC22. The UCM, consisting of branched and 

cyclic alkanes and aromatic/olefinic hydrocarbons was most pronounced throughout the nC24 to 

nC3Z n-alkane range. These chromatograms show that the tarball and oil patch samples had lost 

some of the lower molecular weight hydrocarbons (< nC,4) observed in the original No . 6 fuel 

oil sample, while maintaining the higher molecular weight components, characteristic of the 

original oil. 

Although the tar ball and oil patch samples retained most characteristics of the source oil, 

changes in hydrocarbon composition in water, due to rapid dilution and complex weathering 

processes, hinder the ability to definitively characterize the oil . This is exemplified in the 

hydrocarbon composition of the two aqueous phases collected with the above oil samples (Figure 

4) . The aqueous water samples show completely different hydrocarbon profiles from the 

overlying oils and from each other, representing different mechanisms for oil dispersion into the 

water column. The sample collected on the 12th of August contained primarily the lower 

molecular weight fractions (nC12 nC22), with a predominance of the UCM and no definitive nalkane homologous series . This sample is representative of the water-soluble fraction of the oil 

with the majority of the n-alkane homologous series degraded. The August 17th sample shows 

a higher molecular weight distribution of the alkanes and the UCM than that exhibited in the 

August 12 sample. Comparison of the aqueous phase hydrocarbons with the overlying oil 

reveals loss of the lower molecular weight n-alkanes as well as the lower boiling components 

of the UCM. The presence of predominantly higher molecular weight compounds in the water 

would suggest the presence of weathered oil particles dispersed in the aqueous phase (possibly 

35 
colloidal) . The peak labels in these chromatograms indicate the following compounds: RS l : 

1-Octadecene; QS 1 : o-terphenyl ; QS 2: 1-Docosene ; RS 2 : p-terphenyl-D14. 

The distribution and concentrations of total extractable hydrocarbons from water samples 

are given in Figure 5 for samples collected August 12, and in Figure 6 for samples collected 

August 17 . These results show that the spatial distribution of oil-related hydrocarbons was 

patchy, ranging from purely biogenic hydrocarbons to a predominance of petrogenic 

hydrocarbons. The total hydrocarbon concentration is shown for each sample . Those 

representative of primarily biogenic hydrocarbons are indicated with a B. Biogenic 

hydrocarbons are distinguished by discrete sets of alkanes such as pristane, pentadecane and 

heptadecane . Petroleum hydrocarbons are identified by a homologous series of n-alkanes, with 

no predominance of odd or even carbon numbers, approximately equal ratios of pristane and 

phytane and numerous aromatic and olefinic hydrocarbons exemplified by an unresolved complex 

mixture (UCM) on the chromatographic trace (Farrington 1980, Van Vleet et al. 1984, NRC 

1985, Pierce et al. 1986). 

Examples of hydrocarbon profiles in water samples are illustrated in Figure 7 . The 

hydrocarbon profiles in Figure 7 are indicative of marine biogenic hydrocarbons with no 

petroleum impact, dissolved-weathered oil with a predominance of the UCM, and a high 

molecular weight distribution of n-alkanes, indicative of weathered oil particles as opposed to 

dissolved hydrocarbons, respectively, top to bottom. 

Of the 23 samples collected from twenty sites on the 12th of August, three contained 

below detectable limits of hydrocarbons (<0.5 jig/L), six had predominantly biogenic (B) 

hydrocarbons with concentrations < 5 Ag/L. The remaining sixteen samples contained primarily 

petroleum hydrocarbons exhibiting dissolved/dispersed hydrocarbons and hydrocarbon profiles 

representing suspended particles of weathered oil in concentrations up to 46 /Lg/L. 

Vertical distribution of the oil was observed at three stations by collecting samples from 

both 0.3 m and 2 m water depths . Stations 13 and 17 exhibited higher hydrocarbon 

concentrations at depth, demonstrating that the deeper waters were also impacted by oil . Station 

15 showed petroleum hydrocarbons in the near-surface water while biogenic hydrocarbons were 

found at the 2 m depth. The profiles observed at these stations (oil and weathered oil) indicated 

that oil was well-dispersed into the water column at certain sites. 

Subsurface currents flowing in different direction from surface movement could have led 

to separation between the surface oil slick and hydrocarbons in the lower water column, resulting 

in a wider distribution of hydrocarbon contamination than could be observed by following the 

movement of the surface slick. The contrary is also true, water movement under the surface 

slick could bring water with low hydrocarbon content into areas visibly impacted by the surface 

slick. Thus, an area bathed in low hydrocarbon content water when sampled would not 

necessarily avoid exposure during a different tidal cycle . 

The water samples collected on August 17th gave a wide range (from < 0.5 to 39 ltg/L), 

similar to that observed for the August 12 samples. The John's Pass area was visibly oiled and 

high concentrations of weathered oil were observed in water samples from the west side of 

Eleanor Island, with lower concentrations found in the water at other locations (Figure 6) . 

Bunces Pass had no visible oiling, however, there were stations with hydrocarbon concentrations 

and profiles indicating contamination by suspended oil particles (Figure 6) . Patchy 

contamination of the benthic environment was evident from globules floating just above the 

bottom among the seagrass beds in Johns Pass, however, these oil globules were not collected 

for this study . 

36 
The presence of petroleum hydrocarbons in water samples throughout the mouth of 

Tampa Bay and the near-shore Gulf of Mexico following the oil spill provide an indication of 

the oil transport and potential for short term ecological impact in the water column. Clams 

(Mercenaria merceneria) were collected from the Bunces Pass area on September 29, 1993, to 

assess shellfish contamination from oil distributed in the water as opposed to direct oiling . The 

high molecular weight distribution of n-alkanes was observed in several of the clams, indicating 

uptake of oil-containing particulates (Sherblom and Pierce, unpublished data). 

Sediment Samples 

Petroleum hydrocarbons were present in both fractions (F1 and F2) in all sediments 

collected near Egmont Key following the spill . Alkanes in the range from nC,S to nC3Z were 

quantified separately in order to estimate the contribution of Bunker C fuel oil to the sediments . 

These alkane concentrations characteristic of Bunker C ranged from 8 Itg/g to 41 /1g/g (dry 

weight sediment; Figure 2B) . n-Alkanes derived from the Bunker C fuel oil comprised 

approximately 30-90% of the total F1 hydrocarbons in these samples. The contribution of 

Bunker C fuel oil n-alkanes to sediments taken on August 11 (1 day after the spill) averaged 

28 .8 f 13 .2 /Ag/g while those collected on September 1 (three weeks post-spill) averaged 14.5 

f 4.1 /Ag/g. While the hydrocarbon concentrations found three weeks after the spill were lower 

than those found the day after the spill, this does not necessarily represent a temporal decrease 

in the concentrations of hydrocarbons in the sediments resulting from the Bouchard 155 spill. 

The differences in hydrocarbon concentrations may have resulted from collecting the samples 

in slightly different areas. 

Previous studies on sediments from the mouth of Tampa Bay have indicated that 

background levels of hydrocarbons in sediments from this area average less than 10 /Ag/g and 

normally show a hydrocarbon pattern characteristic of biogenic contributions with little 

petrogenic input to sediments in this area (Van Vleet and Reinhardt, 1983 ; Van Vleet et al. 

1986). A gas chromatogram of the hydrocarbons isolated from sediments collected on August 

11 is shown in Figure 8 . Although the alkane distribution is clearly petrogenic, this 

chromatogram shows that n-alkanes below nC2o were not incorporated into the sediments . 

Visible oil was not observed in these sediments (i.e. no large tar particles or globs) . Transport 

of hydrocarbons to these sediments appears to have resulted from adsorption to particles in the 

water column with subsequent transport to the bottom. Lower carbon-numbered n-alkanes are 

more soluble and less readily adsorbed to particles than the longer chain alkanes . Hence it is 

not unusual that the lower carbon-numbered alkanes are preferentially removed prior to 

deposition, and the n-alkane maximum has shifted from nC2, to nC26 (Farrington 1980, Burns 

et al. 1993, Volkman et al . 1992) . Due to the lack of any significant petrogenic signal in 

sediments reported by other studies from this area, and also due to the sheer mass of oil present 

at the time of the spill, the petrogenic hydrocarbons observed in these sediments can be 

attributed to release from the Bouchard 155. 

Approximately four days after the initial spill (August 14, 1993), oil washed ashore and 

coated the mangroves of Eleanor Island just inside John's Pass (Figure 2A). The distribution 

of oil visible in surface sediments along the mangrove fringe decreased through December, 

1993, but then appeared to remain fairly constant through March (R.A. Davis, unpublished 

data) . Samples were collected approximately biweekly since the spill at one of the most heavily 

37 
oiled sites along the mangrove fringe (northern face of island's northeast quadrant) to investigate 

chemical changes in the oil due to weathering in a subtropical sediment . 

Gas chromatograms of the F1 fraction of oil collected from Eleanor Island in December, 

1993, and June, 1994, are shown in Figure 9 along with a chromatogram of the F1 fraction of 

the Bouchard ISS's Bunker C fuel oil prior to spillage. From these chromatograms, it can be 

seen that much of the lower carbon-numbered n-alkanes have been weathered from the oil, 

although the n-alkane maximum remains at nC2, throughout the 10 months following the spill. 

The reason for the difference in the n-alkane maximum in the bulk oil versus the oil found in 

the sediments taken near Egmont Key is likely due to the mode of transport and preservation . 

The deposition of oil in the sediments near Egmont Key appears to have been by adsorption onto 

particles followed by deposition, a process which will preferentially enrich the sedimentary 

hydrocarbons in higher carbon-numbered alkanes. The oil present on Eleanor Island, however, 

is simply the remains of the original oil following dissolution, evaporation, and microbial 

degradation. There was a direct transport of the intact oil to these intertidal sediments; hence 

there was no preferential enrichment due to adsorptive transport processes. Clearly, the bulk 

portion of the oil has retained a large portion of its n-alkanes even though it has been exposed 

to tidal flushing and water temperatures as high as 31'C . Although higher temperatures might 

be expected to increase the solubility and volatilization of the hydrocarbons, as well as to 

increase microbial degradation rates, it is clear that the bulk of the oil, which is unexposed, is 

protected against these enhanced rates and the chemical nature of the oil is largely retained . 

Figure 10 shows the gas chromatogram of a sample taken from the outer surface of an 

oil glob collected on April 5, 1994 . This suggests that the n-alkanes in the outer surface of the 

tar have been preferentially microbially degraded relative to the isoprenoids pristane and 

phytane . This preferential degradation of n-alkanes has been shown to occur in several other 

studies of petroleum degradation (NRC 1985) . The percentage that nC28 comprises of the total 

alkanes in the nC,S-nC32 range is shown in Figure 11 . As can be seen from this figure, the nC28 

percentage falls into two general ranges, those making up approximately 14-19% and those 

making up approximately 3-7% . Samples with nC28 percentages falling into the higher range 

(14-19%) were all found in samples where the bulk oil was dissolved and analyzed. Samples 

with nC2g percentages falling into the lower range 3-7%) were all found in samples taken from 

the outer surface of an oil glob. These percentages result from the fact that the nC28 and other 

n-alkanes are being degraded relative to the isoprenoid and branched alkanes on the outer portion 

of the tar. This further illustrates that the outer portion of the oil is preferentially degraded 

while the inner, bulk portion of the oil retains more of its original chemical signature. 

Combined gas chromatography-mass spectrometry was used to investigate the distribution 

of polycyclic aromatic hydrocarbons in the oil obtained from Eleanor Island following the 

Bouchard ISS spill. Although several other PAH's were investigated, the most abundant PAH's 

observed in the oil were the Co C4 homologs of naphthalene, fluorene, phenanthrene, pyrene, 

and chrysene. The Co C4 homolog distribution of each of these were very similar in the bulk 

oil obtained from Eleanor Island following the spill to the Bunker C fuel oil obtained directly 

from the Bouchard ISS. Even the most volatile naphthalene series was still present with 

approximately the same relative homolog distribution throughout the study (Figure 12) . 

However, relative to the higher four-ring PAH series (pyrene and chrysene), the two and three 

ring aromatic hydrocarbon series (napthalene, phenanthrene, and fluorene) decreased in relative 

concentration throughout the study (Figure 13) . Nonetheless, significant concentrations of all 

PAH's were still present in the oil for at least 10 months following the spill . 

38 
Several other spills of Bunker C fuel oil have occurred in the marine environment, 

however most of these spills took place in temperate or cold water climates . These include the 

Arrow spill (1 .3 million liters) in Chedabucto Bay, Nova Scotia (Michalik 1971, Scarratt 1972, 

Vandermeulen 1977, Vandermeulen et al. 1977, Keizer et al. 1978), the Metula spill (2 .1 

million liters of Bunker C spilled with 53 million liters of crude oil) in the Strait of Magellan 

(Harm 1977), the San Francisco Bay spill (3 .2 million liters ; Chan 1977), the Sansinena spill 

(5 .1 million liters) in outer Los Angeles Harbor (Soule et al. 1978), the Blue Magpie spill (0 .3 

million liters) in Yaquina Bay, Oregon (Kemp et al. 1986), and the Nestucca spill (0 .9 million 

liters) off the Washington coast (Strand et al. 1992). No reports have been found of major spills 

of Bunker C fuel oil in subtropical or tropical environments prior to the Bouchard 155 spill 

investigated in this study. 

In studies following several of the spills in cold water environments, acute toxicity and 

lethal effects of Bunker C fuel oil were observed . Effects on the softshell clam, Mya arenaria, 

following the Arrow spill, included lower total numbers, fewer mature adults, lower tissue and 

shell growth rates, lower carbon assimilation rates, and poor recovery (Gilfillan and 

Vandermeulen 1978) . Following the Sansinena spill, Soule and Oguri (1978) observed reduced 

phytoplankton productivity and reduced benthic populations . Kemp et al. (1986) observed 

reduced populations and lowered recruitment of the amphipod, Rhepoxynius abronius following 

the Blue Magpie spill . In addition, in a laboratory study on the toxicity of Bunker C fuel oil to 

cod eggs and larvae, Kuhnhold (1978) observed reduced survival, retarded growth, loss of 

buoyancy, abnormal development and lower heartbeat rates . 

Based upon the persistence of the aromatic hydrocarbons in the Bunker C fuel oil recovered 

10 months after the Bouchard 155 spill in the present study, it is clear that the toxicity of the 

oil can persist in the Tampa Bay environment for at least several months . Since there was no 

indication of a significant reduction of these PAH's in the bulk oil found in the intertidal 

sediments, it appears that this oil may remain toxic in the environment for substantially longer 

than the 10 months observed in this study. The higher annual temperatures found in this 

subtropical environment do not seem to mediate the degradation, dissolution, or volatilization 

of the oil when deposited in large masses . Studies are continuing to assess the longer term fate 

of this oil . 

ACKNOWLEDGMENTS 

Portions of this work (ESV & DLW) were supported by grants from the U.S. Geological 

Survey Division of Coastal Geology (#759204) and Florida Sea Grant (#PD-93-10) . These 

authors also wish to thank Ms. Pam Sutton for assistance in collection of sediment samples. 

Water and shellfish analyses were supported by the Florida Department of Environmental 

Protection Office of Coastal Protection (Contract #C-8274) . 

REFERENCES 

Burns, K.A., S.D. Garrity, and S.C . Levings . 1993 . How many years until mangrove 

ecosystems recover from catastrophic oil spills . Mar. Pollut . Bull . 26 : 239-248 . 

39 
Chan, G.L. 1977 . The five-year recruitment of marine life after the 1971 San Francisco oil 

spill. pp . 543-545 . In : 1977 Oil Spill Conference . American Petroleum Institute. Publ. 

4284 . 

Farrington, J.W . 1980 . In: Petroleum in the Marine Environment. L. Petraleis, F.T . Weiss, 

eds ., Advances in Chemistry, Series No . 185, American Chemical Society, Washington, 

DC, pp. 1-22 . 

Gilfillan, E.S . and J .H . Vandermeulen. 1978. Alterations in growth and physiology of softshell clams, Mya arenaria, chronically oiled with Bunker C from Chedabucto Bay, Nova 

Scotia, 1970-76. J. Fish. Res. Bd. Can. 35 : 630-636 . 

Hann, R.W ., Jr. 1977 . Fate of oil from the supertanker Metula. pp.465-468 . In: 1977 Oil 

Spill Conference . American Petroleum Institute . Publ. 4284. 

Keizer, P.D., T.P . Ahern, J. Dale, and J .H . Vandermuelen. 1978 . Residues of Bunker C oil 

in Chedabucto Bay, Nova Scotia, 6 years after the Arrow spill. J. Fish. Res. Bd. Can. 

35 : 528-535 . 

Kemp, P.F ., R.C . Swartz, and J .O . Lamberson. 1986. Response of the phoxocephalid 

amphipod, Rhepoxynius abronius, to a small oil spill in Yaquina Bay, Oregon. Estuaries 

9 : 340-347 . 

Kuhnhold, W.W. 1978 . Effects of the water soluble fraction of a Venezuelan heavy fuel oil 

(No. 6) on cod eggs and larvae . pp . 126-130 . In: In the Wake of the Argo Merchant: 

Proceedings of a Symposium. University of Rhode Island, Center for Ocean Management 

Studies. 

Michalik, P.A. 1971 . Concentration of Bunker C fuel oil in the waters of Chedabucto Bay, 

April 1971 . J. Fish. Res. Bd. Can. 28 : 1912-1914. 

National Research Council . 1985 . Oil in the Sea: Inputs, Fates, and Effects. Steering 

Committee for the Petroleum in the Marine Environment Update. Board on Ocean 

Science and Policy . Ocean Sciences Board. Commission on Physical Sciences, 

Mathematics, and Resources . National Research Council . National Academy Press. 

Washington, D.C. 601 pp . 

Pierce, R.H., R.C . Brown, E.S . Van Vleet, and R.M . Joyce. 1986 . Hydrocarbon 

contamination from coastal development. In: Organic Marine Geochemistry, M.L. Sohn, 

Ed., ACS Symposium Series, No . 305, pp. 229-246. 

Scarratt, D.J . 1972. Bunker C oil in sediments and benthic animals from shallow depths in 

Chedabucto Bay, N.S. J. Fish. Res. Bd. Can. 29 : 1347-1350. 

40 
Soule D.F ., M. Oguri, J.K. Dawson, R. Osborn, L.R. McGlade, C.R. Feldmeth, M.K. 

Wicksten, J.D. Soule, R.W. Smith, D. Dabbelstein, S. Kurtz, and F. Edmands. 1978 . 

The significance of the Sansinena incident . p .295 . In, Siva-Lindstedt, J. (ed) . 

Energy/Environment '78 : A Symposium on Energy Development Impacts : Proceedings. 

University of Southern California, Institute of Marine and Coastal Studies, Spec. Publ. 

258 pp . 

Soule, D.F . and M. Oguri. 1978 . Marine studies of San Pedro Bay, California : Part 15 : The 

impact of the Sansinena explosion and Bunker C spill on the marine environment of outer 

Los Angeles Harbor . University of Southern California Institute of Marine and Coastal 

Studies, Spec. Publ . 258 pp. 

Strand, J .A ., V.I . Cullinan, E.A . Crecelius, T.J . Fortman, R.J . Citterman, and Fleischmann, 

M.L. 1992. Fate of Bunker C fuel oil in Washington coastal habitats following the 

December 1988 Nestucca oil spill. Northwest Sci. 66: 1-14 . 

Vandermeulen, J .H . 1977 . The Chedabucto Bay spill - Arrow, 1970 . Oceanus 20 : 31-39. 

Vandermeulen, J.H., P.D . Keizer, and W.R. Penrose. 1977 . Persistance of non-alkane 

components of Bunker C oil in beach sediments of Chedabucto Bay, and lack of their 

metabolism by molluscs. pp .469-473 . In: 1977 Oil Spill Conference . American 

Petroleum Institute. Publ . 4284 . 

Van Vleet, E.S ., R.H . Pierce, R.C . Brown, and S .B . Reinhardt . 1984. Sedimentary 

hydrocarbons from a subtropical marine estuary . Org. Geochem . 6 : 249-257 . 

Van Vleet, E.S . and S.B. Reinhardt. 1983 . Inputs and fates of petroleum hydrocarbons in a 

subtropical marine estuary. Environment Internat . 9 : 19-26 . 

Van Vleet, E.S ., R.M. Joyce and M.R. Sherwin. 1986. Comparison of anthropogenic 

hydrocarbon inputs to two subtropical marine estuaries . Sci. Total Environ . 56: 221-230. 

Volkman, J.K ., D.G . Holdsworth, G.P . Neill, and H.J . Bavor, Jr . 1992 . Identification of 

natural, anthropogenic and petroleum hydrocarbons in aquatic sediments. Sci. Tot. 

Environ. 112 : 203-219 . 

41 
_ 28 

29 0 

.,.~ 

Water 8/12/93 

27 26 a Water 8/17/93 

D John X Oil Patches 

Pass 

St. Petersburg 

UVV 

0 

O 

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25 

10 

9a 

15 

11 

O 

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13 

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., 

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Figure 1 . Location of water sample collection sites in the vicinity of the 8/10/93 Tampa Bay 

oil spill. 

42 
A 

STA 4 

ELEANOR 

v"_ex<a-:~JSIAND 

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PASS 

A 

ST. PETERSBURG 

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Figure 2. Locations of sampling sites for sediments collected (A) near the spill, and (B) in 

the mangrove island intertidal sediments. Concentrations are shown for each site 

in terms of Ag Bunker C fuel oil/g dry weight sediment. 

43 
10 20 ~ 60 

Oil Tarball 

8/12J93 

v 1 I I I II 

UCM 

Figure 3 Comparison of total hydrocarbon chromatograms (GC-FID) for oil from the 

barge, Brouchard ISS, oil patches collected from the mouth of Tampa Bay 

(8/12/93), and from near-shore Gulf of Mexico (8/17/93). 

44 

10 ?A 
10 20 r 60 

14 Water under a 

Tarball 

ell 8/12/93 a 

scale x 2 

G. 

. . 

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Figure 4. Comparison of total hydrocarbon chromatograms (GC-FID) for water samples 

collected along with a tarball from the mouth of Tampa Bay (8/12/93) and with 

an oil patch from near-shore Gulf of Mexico (8/17/93) . 

45 
1 B Scale 

50 

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Figure 5 . Total hydrocarbon (THC) concentrations in water samples collected 8/12/93, 

reported as jig/L. 

46 
28~ 

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reported as Ag/L. 

47 
10 Z~ C1' ~ 60 

Water Sample 1 a " oa 

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Biogenic 0.2 m ~ y 

scale x 2 

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oil particles 

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Figure 7 . Comparison of total hydrocarbon chromatograms (GC-FID) representative of 

water samples collected throughout the Tampa Bay oil spill area. 

48 
0 

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Figure 8. Gas chromatogram of F 1 (alkane) fraction of hydrocarbons isolated from 

sediments near Egmont Key one day after the spill. IS = Internal Standard. 

49 

v -` 
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Figure 9 . Gas chromatograms of F1 (alkane) fraction of hydrocarbons isolated from (A) 

Bunker C fuel oil carried by the Bouchard ISS, (B) tar taken from Eleanor Island 

on December 17, 1993, and (C) tar taken from Eleanor Island on June 10, 1994 . 

IS = Internal Standard . PR = Pristane . PH = Phytane . 

50 
-o 

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Figure 10. Gas chromatogram of F1 (alkane) fraction of hydrocarbons isolated from the 

surface of tar taken from Eleanor Island on April 5, 1994. IS = Internal 

Standard . PR = Pristane . PH = Phytane . 

51 
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Figure 11 . Percentage of nC28 in the nC,s-nC32 n-alkane range isolated from tar taken from 

Eleanor Island on different sampling dates. Asterisks indicate samples taken from 

surface of tar. All other samples were of the composite bulk tar. 

52 

0 0 0 0 0 0 0 0 0 

O 00 C~ Nt N O CO tD ~! N O 

N r T r T r 

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24/93 

/93 

14 

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2/25/94 

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9/24/93 

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d a v U v 

U 

Figure 12 . Co-C4 homolog distributions of naphthalenes, phenanthrenes, and pyrenes in F2 fractions of tar collected on 4 sampling 

dates throughout the study (see legend) . The homolog distributions are also shown for Bunker C fuel oil for 

comparison . 
v v 

U 

C ~ `-

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Figure 13 . Concentrations (in Ag PAH/g oil) in samples taken on February 25, 1994 and 

June 10, 1994 . Concentrations in the intact Bunker C fuel oil carried by the 

Bouchard 155 are also shown for comparison . 

54 

In %-' rN 
Effects of Oil on Salt Marshes 

James W. Webb 

Marine Biology Department 

Texas A&M University at Galveston 

Galveston, Texas 77553-1675 

INTRODUCTION 

Coastal salt marshes are valuable resources. Salt marshes are composed of various 

plant communities and associated bay water, bayous and tidal creeks with many animal 

inhabitants. The lower intertidal zone dominated by smooth cordgrass (Spartina alterniflora) 

is one of the most important plant and animal communities of a tidal marsh because of its 

importance to estuarine processes. Because of daily tidal flooding it is a habitat that is often 

impacted by oil spills originating from tankers, pipelines, or storage tanks. Thus, an 

understanding of the effects oil spills may have on the habitat and functions of marshes is 

important. 

It is valuable as a nursery habitat because young and juvenile stages of fish and 

shellfish utilize this plant community zone for protection and to derive nutrition (McHugh 

1968; Lindall and Saloman 1977 ; Peters et al. 1978 ; Herke 1971 ; Zimmerman and Minello 

1984) . Some scientists estimate that from 63 to 99 percent of the commercially important 

fish and shellfish of the southern Atlantic and Gulf Coasts utilize estuaries and their 

associated wetlands during their life cycle (McHugh 1968) . Some species such as brown 

shrimp (Penaeus aztecus) strongly select for the smooth cordgrass habitat (Zimmerman and 

Minello 1984; Zimmerman et al. 1984) . 

The smooth cordgrass habitat is important in protection of shorelines from wave 

erosion (Webb 1977 ; Woodhouse et al . 1972) . This species grows in the lower intertidal 

zone where wave action can erode shorelines . The plant biomass produced ranks as one of 

the highest in the world . The biomass produced appears to provide significant amounts of 

detritus to the estuarine ecosystem (Odum et al. 1972) . The detritus provides the base to an 

energy pathway that is important in many estuarine systems. It also enhances water quality 

through immobilization of nutrients and filtering of heavy metals and toxic materials from the 

water column (Getter et al. 1984) . 

Despite the high priority for protection in oil spill response plans (Lindstedt-Siva 

1977; Gundlach and Hayes 1978), salt marshes are frequently impacted by oil spills (Crow 

1974 ; Hershner and Moore 1977 ; Hampson and Moul 1978 ; Webb et al. 1981) . The reason 

for the frequent oil spill impacts is that the Gulf Coast of the U.S. is a highly utilized tanker 

transportation route, a high exploration and producing zone, an area with many refineries, 

and an area with many oil storage tanks . 

Since the marshes have high value and the U.S . Gulf Coast has high oil exploration 

and production activities an understanding of the effects of oil on salt marshes is important in 

planning for spill events . Plants form the habitat in which animals live, therefore, an 

understanding of the response of plants to oil is imperative in any planning . This paper 

55 
reviews the past work by the author and others in development of an understanding of plant 

response to oil spills . 

METHODS 

Our first evaluations of the effects of oil spills occurred in 1977 as crude oil flowed 

into a Galveston Bay smooth cordgrass marsh following a barge collision at the junction of 

the GIWW and the Houston Ship Channel (Webb et al. 1981) . Experimental studies in 

smooth cordgrass marshes were conducted from 1981 through 1986 by spraying oil on 1 m2 

plots. Effects of type of oil, seasonal effects, and height of coverage of plants were 

evaluated (Alexander and Webb 1985 ; Webb et al. 1985) . Specific effects of No. 2 fuel oil 

and residual toxicity effects on smooth cordgrass were evaluated by recording initial response 

and regrowth into center and edge portions of large plots in 1983 (Webb and Alexander 

1991) . Clean-up techniques were evaluated in a separate study from 1985 to 1986 (Kiesling 

et al. 1988) . The effects of various amounts of crude oil on sections of a salt marsh along 

Dickinson Bayou were evaluated in 1986 (Alexander and Webb 1987) . In 1991 the effects of 

the Apex oil spill, clean-up, and oil-remediation were evaluated (Webb 1993). 

RESULTS 

Types of Oil 

Oil types that can affect salt marshes vary from crude oil to light refined oils . Four 

general types are recognized. Three of the four types were evaluated in experimental 

studies. 

Crude oils and heavy fuel oils can vary in specific gravity, amount of sulfur, and 

other properties . However, they are generally the same in overall effects on plants (Figure 

1) . Oils that have been evaluated include Arabian Crude, Libyan Crude, Isthmus (Mexico) 

crude, and No . 6 fuel . Little toxic effects to plants appear to occur unless oil penetrates into 

the soil and chronic toxicity to the plants occurs as roots are continuously exposed to oil . 

Oil spill studies at Dickinson Bayou indicated that in actual spills the oil may accumulate in 

the soil causing long-term effects on growth. 

Lighter and more refined oils such as No . 2 fuel oil are extremely toxic to smooth 

cordgrass. This type oil acts as a contact herbicide with some translocation capabilities to 

the rootstock. 

Amount of Plant Coverage 

Tidal conditions can greatly affect the oil coverage on plants and the amount of oil 

dispersion throughout a marsh system. The amount of plant coverage is very important in 

determination of effects on plants and animals . 

With crude oils smooth cordgrass is affected primarily by coverage of the surface of 

plants . Respiration and photosynthesis are blocked when oil coats plants . The aboveground 

portion of smooth cordgrass is generally killed only when oil covers all plant surfaces . 

56 
Regrowth from rootstock generally will occur soon after death of aboveground portions of 

the plants (Figure 2) . Plant recovery can become a problem if new shoots must penetrate a 

continuous mass of oil or sediment contamination by oil occurs in significant amounts. 

In experimental studies No . 2 fuel oil was applied to 4-m2 plots of smooth cordgrass 

as four treatments (control, sediment only, sediment plus lower plant surfaces, and sediment 

plus entire plant surfaces) . Damage to plants was much greater with complete coverage of 

plants (Figure 3). With complete coverage of foliage by oil, above-ground plant material 

died rapidly and regrowth from rootstock did not occur. With partial coverage of stems, 

some discoloration of plants occurred but little difference in stem density occurred between 

controls and treated plots. When oil was applied to the sediment alone, stem density was 

only slightly reduced. The reduction in stem density apparently resulted from oil penetrating 

the soil to the roots. No accumulation of hydrocarbons in the sediments occurred . 

Regrowth of smooth cordgrass did not occur from the rootstock when plants were 

killed by complete foliar coverage of the No. 2 fuel oil. Regrowth did occur with lower 

stem coverage and sediment only coverage by oil . The conclusions were that No . 2 fuel acts 

as a contact herbicide . Some oil accumulation in roots and rhizomes after spraying of 

complete foliage indicates that some translocation of the oil from foliage to roots and 

rhizomes can occur, preventing regrowth from rootstock in many instances . 

Seasonal Effects 

Seasons play a role in determination of damage to salt marshes . Damage to smooth 

cordgrass was more detrimental during the spring than fall . During the spring plants are 

actively growing and have presumably used available stored nutrients . During the fall plants 

are beginning their dormancy and many flowering stems are dying. Regrowth the following 

spring does not appear to be greatly reduced by the oil spill . 

Oil Amounts 

Most of our studies were designed to test initial effects of an oil spill . Sufficient oil 

was applied to completely cover sediments and/or plants, generally 1 to 2 liters per m2, 

depending on whether coverage was intended for sediments or plants and sediments. Oil 

generally dispersed with tides, leaving little to penetrate sediments and cause long-term 

damage . In actual spills the oil often accumulates on shorelines in large quantities . 

Complete death of large areas of smooth cordgrass generally occurs only when high levels of 

crude and heavy fuel oils accumulate in the sediments or remain within the marsh for long 

periods of time (Holt et al. 1978 ; Alexander and Webb 1987; Krebs and Tanner 1981) . As 

indicated in our studies of plant coverage, the constant presence of oil can coat new stems 

and cause chronic effects on plants . Refined oils such as No. 2 fuel oil spilled in large 

amounts can destroy large salt marsh plant communities (Hershner and Lake 1980 ; Hampson 

and Moul 1978) . 

57 
Oil Spill Cleanup 

Following a spill that impacts a salt marsh, the logical question is what must be done 

to remove the oil and return the marsh to its full functioning capabilities . Studies in 1985 

and 1986 on marsh plots attempted to provide necessary information. 

Cleanup techniques implemented 18-24 hours after the application were not effective 

in removing oil that had penetrated the surface . When oil remained on the sediment surface, 

flushing techniques were most effective at removal, reducing levels of oil by 73 to 83 

percent. When dispersants were added to the water during flushing, oil removal was only 

slightly enhanced . Clipping of vegetation followed by sorbent pad application to sediments 

was moderately effective, reducing added oil by 36 to 44 percent. Burning had a negative 

effect on oil removal ; oil increased in sediments of burned plots compared to controls . 

Consideration should be given to natural flushing, evaporation, and natural microbial 

breakdown of the oil. When large amounts of oil are present in the marsh, clean-up 

measures may be necessary to remove oil and return the marsh to its natural state. Damage 

from trampling can be severe, causing damage to plants and forcing oil into sediments (Webb 

1993) . Where possible trampling and destructive damage to the marsh should be avoided. 

CONCLUSIONS 

Type of oil is important in determination of effects . Light refined oils kill on contact . 

Crude oils block photosynthesis and respiration. Amount of oil and amount of plant 

coverage are important. Coating of entire plant causes death of aboveground material . 

Plants can regenerate from rootstock with crude oils . Roots are killed by light refined oils, 

including number 2 fuel oil. Oil remaining in the sediments can cause long-term effects on 

plants . Season can be important . Plants are least affected by oils during late fall and winter 

when plants are dormant or approaching dormancy. 

Clean-up and restoration techniques must be based on oil type, plant and marsh 

coverage, and amount of oil. Cleanup decisions following a spill must be based on 

judgements of the long-term damage projected for the impacted marsh . The type and amount 

of oil must be carefully judged . The do-nothing alternative should be carefully considered . 

Flushing is effective when narrow marshes are impacted. Clipping and use of sorbents are 

moderately successful, but trampling can cause damage and force oil into the sediment. 

Burning may be ineffective. 

ACKNOWLEDGMENTS 

Experimental research performed between 1981 and 1986 was done in conjunction 

with Dr. Steve Alexander, who is co-author on many of the papers cited in this summary 

publication. Experimental work testing clean-up techniques cited in this paper was done in 

conjunction with Russell Kiesling, who is a former graduate student. Funding for various 

aspects of the studies were provided by the Center for Energy and Mineral Resources at 

Texas A&M University, Harris and Eliza Kempner Fund, National Wildlife Federation, 

58 
American Petroleum Institute, and the Texas Water Commission. Oils and dispersants were 

supplied by Exxon USA. Sorbent pads were supplied by 3M Company. 

REFERENCES 

Alexander, S .K. and J.W . Webb. 1985 . Seasonal response of Spartina alterniflora to oil. pp. 

355-357 . In, Proceedings 1985 Oil Spill Conference. American Petroleum Institute, 

Washington, D. C. 

Alexander, S.K. and J.W . Webb . 1987 . Relationship of Spartina alterniflora to sediment oil 

content following an oil spill. p. 445-449 . In, Proceedings 1987 Oil Spill Conference . 

American Petroleum Institute, Washington, D.C. 

Crow, S.A. Jr. 1974 . Microbial aspects of oil intrusion in the estuarine environment. Ph . D. 

Thesis, LSU, Baton Rouge, La. 179 pp. 

Getter, C.D., G. Cintron, B . Dicks, R.R. Lewis III and E.D . Seneca . 1984. The recovery 

and restoration of salt marshes and mangroves following an oil spill. pp 65-113 . In, J . 

Cairns, Jr. and L. Buikema, Jr. eds. Restoration of Habitats impacted by oil spills . 

Butterworth Publications, Boston, Massachusetts . 

Gundlach, E.R. and M.O . Hayes. 1978. Vulnerability of coastal environments to oil spill 

impacts . Marine Technology Society Journal. 12: 18-27 . 

Hampson, G.R. and E.T. Moul . 1978 . No . 2 fuel oil spill in Bourne, Massachusetts : 

immediate assessment of the effects on marine invertebrates and a 3 year study of 

growth and recovery of a salt marsh. Journal of the Fisheries Research Board of 

Canada. 35 : 731-734. 

Hershner, C. and J . Lake. 1980. Effects of chronic pollution of a salt marsh grass 

community . Marine Biology . 56: 163-173 . 

Hershner, C. and K. Moore. 1977 . Effects of the Chesapeake Bay oil spill on salt marshes of 

the lower bay . pp. 529-533. In, Proceedings 1977 Oil Spill Conference . American 

Petroleum Institute, Washington, DC . 

Herke, W.H. 1971 . Use of natural and semi-impounded, Louisiana tidal marshes as nurseries 

for fishes and crustaceans . PhD Thesis . Louisiana State University, Baton Rouge, 

Louisiana . 242 pp. 

Holt, S ., S . Rabalais, N. Rabalais, S . Cornelius and J.S . Holland . 1978 . Effects of an oil 

spill on salt marshes at Harbor Island, Texas: I : Biology . pp. 344-352 . In, 

Proceedings of Conference on Assessment of Ecological Impacts of Oil Spills . 

American Institute of Biological Sciences, Washington, DC . 

59 
Kiesling, R. W., S . K. Alexander, and J.W . Webb. 1988. Evaluation of alternative oil spill 

cleanup techniques in a Spartina alterniflora salt marsh. Environmental Pollution 55 : 

221-238 . 

Krebs, C.T . and C.E . Tanner. 1981 . Cost analysis of marsh restoration through sediment 

stripping and Spartina propagation. pp . 375-385 . In Proceedings 1981 Oil Spill 

Conference . American Petroleum Institute, Washington, DC . 

Lindall, W.N . Jr. and C.H. Saloman. 1977. Alteration and destruction of estuaries affecting 

fishery resources of the Gulf of Mexico . Marine Fisheries Review. 39(9) : 1-7 . 

Lindstedt-Siva, J . 1977 . Oil spill response planning for biologically sensitive areas . In 

Proceedings 1979 Oil Spill Conference, Amer. Petrol . Inst ., Wash ., D.C . pp 111-

114 . 

McHugh, J .L . 1968 . Are estuaries necessary? Commercial Fisheries Review. 30(11): 37-34 . 

Odum, W.E., J.C . Zieman and E.J . Heald. 1972 . The importance of vascular plant detritus 

to estuaries. pp.93-112 . In, R.H . Chabreck ed . Proceedings of the Coastal Marsh and 

Estuary Management Symposium. Louisiana State University, Baton Rouge, 

Louisiana. 

Peters, D.S ., D.W . Ahrenholz and J.T . Rice . 1978 . Harvest and value of wetland associated 

fish and shellfish. In, P.E. Greeson, J.R. Clark, and J .E. Clark, eds . Wetland 

Functions and Values : the State of our Understanding. American Water Resources 

Association. Urbana, Illinois . 606 pp. 

Webb, J. W. 1977. Establishment of vegetation for shoreline stabilization in Galveston Bay, 

Texas . Ph. D. Thesis . Texas A&M U., College Station. Texas . 136 pp . 

Webb, J. W. 1993 . Final Report: Oil Spill Impacts and restoration evaluation of Marrow 

Marsh resulting from the Apex Barge spill in Galveston Bay, Texas . Texas A&M U. 

at Galveston, Galveston, 51 pp. 

Webb, J .W., S .K . Alexander and J.K. Winters. 1985 . Effects of autumn application of oil 

on Spartina alterniflora in a Texas salt marsh . Environmental Pollution, Series A. 

38(4) : 321-337 . 

Webb, J. W. and S . K. Alexander. 1991 . No. 2 fuel oil effects on Spartina alterniflora in a 

Texas salt marsh. Contrib. in Marine Science 32 : 9-19. 

60 
Webb, J.W ., G.T . Tanner and B.H. Koerth. 1981 . Oil spill effects on smooth cordgrass in 

Galveston Bay, Texas . Contributions in Marine Science. 24 : 107-114. 

Woodhouse, W. W., E. D. Seneca, and S. W. Broome. 1972. Marsh building with dredge 

spoil in North Carolina. North Carolina Agri. Exp. Sta. Bull. 445 . 28 pp . 

Zimmerman, R.J . and T.J . Minello. 1984. Fishery habitat requirements: utilization of 

nursery habitats by juvenile penaeid shrimp in a Gulf of Mexico salt marsh. pp. 371-

383 . In B.J . Copeland, K. Hart, N. Davis, and S . Friday, eds. Proceeding on 

Research for Managing the Nation's Estuaries. National Sea Grant College Program. 

Zimmerman, R.J ., T.J . Minello and G. Zamora, Jr. 1984. Selection of vegetated habitat by 

brown shrimp, Penaeus aztecus in a Galveston Bay salt marsh. Fishery Bulletin . 

82(2) : 325-336 . 

61 
OIL TYPE EFFECTS 

ABOVEGROUND BIOMASS (GRAMS/SQUARE METER) 5 MONTHS AFTER APPLICATION 

sso 

soo 

250 

200 

iso 

ioo 

so 

0 

AUTUMN APPLICATION 

00 LITERS 

Ell LITER 

D 1 .5 LITERS 

02 LITERS 

C=SIGNIFICANTLY 

DIFFERENT 

Figure 1 . Oil type effects on smooth cordgrass aboveground biomass (g/m2) five months after 

application of crude, heavy fuel, and light fuel oils to a salt marsh . 

62 

ARABIAN LIBYAN N0.6 FUEL NO. 2 FUEL 
REGROWTH IN OILED PLOTS 

NO. OF NEW STEMS PER METER SQUARE 

300 

250 

200 

150 

100 

50 

0 

D O LITERS 

~ 1 LITER 

D 1 .5 LITERS 

0 2 LITERS 

C=SIGNIFICANT 

DIFFERENCE 

Figure 2. Regrowth (no . of new stems/m" in smooth cordgrass plots sprayed with crude, 

heavy fuel, and light fuel oils . 

63 

ARABIAN LIBYAN N0.6 N0.2 
NO. 2 FUEL OIL EFFECTS (INITIAL AND RESIDUAL) 

NUMBER LIVE STEMS PER METER SQUARE 

60 

50 

40 

30 

20 

10 

0 

R] 1 YEAR 

F-1 7 MO. 

DONE MO. 

TEST OF ROOT STOCK REGROWTH AND SEDIMENT CONTAMINATION 

Figure 3 . Initial and residual effects of No . 2 fuel oil on live stem density of smooth 

cordgrass plots at 1, 7, and 12 months . 

64 

CONTROL SEDIMENT BOTTOM COMPLETE 
The Applicability of Predictions Made from Other Oil Spills to the 1986 

Bahia Las Minas, Panama, Crude Oil Spill: Seagrass Communities 

Michael J. Marshall 

Mote Marine Laboratory 

1600 Thompson Parkway 

Sarasota, Florida 34236 

INTRODUCTION 

The general ecological role of seagrasses throughout the world has been documented by 

numerous authors . Seagrass beds are important nursery grounds for many species of fish and 

crustaceans, they stabilize sediments, they act as sediment traps, they provide substrata for 

many species of epiphytes and epifauna, and they provide food as both green leaves and 

detritus for many small invertebrates and juvenile fish species. Damage to or the loss of a 

seagrass meadow may have ecological effects which extend well beyond the boundaries of 

that particular meadow. Seagrass communities can also be strongly perturbed by factors that 

do not kill or otherwise affect seagrass standing crop . 

Seagrasses and their associated animal communities, in Panama (as described in Heck 

1977 ; Marshall et al. 1990) and in other areas, are susceptible to many types of man-induced 

(Jacobs 1980; Phillips 1980; Williams 1988; Thayer et al. 1975 ; Zieman et al. 1986) 

perturbations . The response of seagrass communities to oiling (Zieman et al . 1986; Marshall 

et al. 1990) seems to be strongly dependent on the elevation of individual seagrass beds 

within the littoral zone . Plants within deep, subtidal seagrass beds are less likely to be killed 

than are seagrasses in intertidal areas . Local climatic and oceanographic conditions at the 

time of oil exposure and many other factors also undoubtably play a role in the degree of 

oiling . Sediment texture, degree of exposure to waves and currents, tidal flushing, seasonal 

timing of recruitment for affected species, suspended sediment loads, initial seagrass density, 

etc . may all have a role in determining the severity of the initial impact and the rate of the 

recovery process . Certain heavy fractions of crude oil sink when they are emulsified and 

mixed with sediment particles through turbulence under rough seas or coastal breakers . 

Emulsified oil droplets were seen on numerous occasions, at the deep edges of reef-protected 

seagrass beds near the Bahia Las Minas refinery, during the early months of the Panama oil 

spill (Marshall et al. 1990). 

Seagrass meadows elsewhere in the tropics, subtropics, and temperate zone have been 

contaminated with oil from tanker wrecks and intentional discharges from tankers (Marshall 

et al. 1993) . Despite an omnipresent oil spill threat to seagrass meadows and despite a 

currently perceived world-wide decrease in seagrass acreage little is known about their 

recovery potential from oiling (Zieman et al. 1986; Thorhaug and Marcus 1987) . 

The Amoco Cadiz spill off the coast of France oiled temperate Zostera meadows 

(denHartog and Jacobs, 1980; Jacobs 1980) . Panama's tropical seagrass beds and the French 

Zostera marina meadows contain many groups in common at higher taxonomic levels . 

65 
Species compositions are probably completely different but the initial spill effects on common 

groups, such as the Amphipoda, Tanaidacea, and Ophiuroidea, proved to be similar in the 

two areas (denHartog and Jacobs 1980; Jacobs 1980; Marshall et al . 1993) . The French 

studies continued for one year after the spill event; they were based on prespill studies 

undertaken at the oiled seagrass beds approximately one year before the Amoco Cadiz 

occurred. Several major groups virtually disappeared after the spill but quickly recovered. 

Twenty six species of Amphipoda disappeared from the oiled Zostera beds and after one year 

only one species had returned . 

The Bahia Las Minas refinery spill in Panama presented an opportunity to observe 

both the amount of damage done by various degrees of oiling to numerous, spatially 

separated seagrass meadow communities and to observe their resilience to this type of 

damage under a range of environmental conditions . Comparisons between the effects of the 

Amoco Cadiz spill and the Panama spill are instructive for the shared faunal groups but there 

are many plant and animal taxa in the tropical seagrass beds of Panama that are not present 

in the French Zostera beds . 

At present there is a continuing debate about the advisability of allowing oil and gas 

exploration and development on the continental shelf off southwestern Florida (Marshall et 

al., 1990) . Tankers passing through the Florida Straits provide a present and continuous 

threat of oil spills to shallow marine habitats if they run aground, rupture a tank, sink, or 

pump their bilges in this area . Several predictions (Table 1), about the potential effects of 

oil on Panama's Bahia Las Minas seagrass meadows, were made from a survey of the 

reported effects of oil on seagrass meadows oiled by other spills (Marshall et al. 1990) . This 

summary of the effects of the Bahia Las Minas spill's effect on seagrass communities is 

aimed at deciding whether or not these predictions applied to the Panama spill . 

RESULTS AND DISCUSSION 

Certain Organisms Are More Oil Sensitive than Others 

Epifauna were sorted to the major taxa listed in Table 2 . Responses to initial oiling 

and recovery patterns varied widely between taxa . Gastropods (Fig . 1) existed in similar 

densities at oiled and unoiled sites throughout most of the 36 months covered by this study . 

Ophiuroidea (Fig . 1) were never abundant in oiled seagrass beds. Fish (Fig . 1) densities 

were initially widely different but trends at oiled and unoiled sites eventually converged. 

Amphipod (Fig . 1) densities were initially widely different between sites types but the 

long-term population trends quickly converged. Amphipoda oiling x time interactions were 

significant and amphipod counts were consistently higher at unoiled sites until the last 9 

months of our three year long study . Mysids (Fig . 1) were consistently most abundant at 

oiled sites while isopods were nearly equally abundant in oiled and unoiled sites . Tanaidacea 

(Fig. 1) were consistently absent or rare at oiled sites but showed seasonal spikes of 

abundance in unoiled seagrass beds . 

Amphipod temporal trends in oiled Panamanian seagrass meadows fit the pattern 

displayed by amphipods in French Zostera meadows following the Amoco Cadiz oil spill 

(denHartog and Jacobs, 1980) . In both locations amphipods proved to be highly oil 

sensitive and slow to recover from spill effects . 

Ophiuroids were quickly killed and had not recovered after almost three years 

(infaunal data) in Panamanian seagrass beds . In France they were reduced in numbers but 

66 
were not totally eradicated by the Amoco Cadiz oil spill . Surface dwelling species of 

Ophiothrix and Ophiocoma, those species most common in pushnet samples, may have been 

killed by direct contact with oil. The oil sensitivity of ophiuroids and other echinoderms 

suggests that they may serve as excellent indicator organisms of oil effects on faunal 

communities in tropical seagrass meadows . Our pushnet and core samples were extremely 

expensive to sort . Large, easy to count echinoderm species may provide a means of rapidly 

determining where oil toxicity has had an effect on seagrass communities. 

Oil Sensitivity Depends on Feeding Type and Filter Feeders Are the Most Oil Sensitive 

Density trends of numerous polychaete families and epifaunal taxa suggested a 

wide-spread sensitivity to oil. Populations of other taxa appeared to be insensitive . Some of 

the "insensitive" taxa may have been able to recover before this study began (at five months 

post spill) . Hydrocarbon analyses of seagrass bed sediments (Burns 1993 ; this report) 

demonstrated that the oil present in those sediments was highly weathered by five months 

after the spill (September 1986) . Oil washing out from the mangrove forests of Bahia Las 

Minas, considering its relatively unweathered condition (Burns 1993) could have an effect on 

sensitive surface dwelling species for years after the spill . 

Density changes of polychaete families through time suggested that oil effects were 

much the same for all feeding types (Marshall et al. 1993). Feeding type categories are 

based on a polychaete family-level, guild classification scheme developed by Fauchald and 

Jumars (1979) . Initial densities were lower at oiled than at unoiled sites for 12 of the 13 

most abundant families . Recovery, defined by convergence of densities at oiled and unoiled 

sites, was seen in 9 of the 13 families . No consistent patterns of significant oiling x time 

interactions were apparent within or between feeding strategies . 

Seajzrass Plants Shelter Infauna from Oil Exposure by Preventing Oil from Mixing into the 

Sediments 

Early reports of Thalassia intertidal bed die-offs (Jackson et al . 1989) after the 1986 

Panama spill suggested that oil might harm or kill very shallow seagrass beds if they are 

oiled during low tide exposures . Not all of the oiled, intertidal seagrass beds died after 

contact with oil (J . Cubit STRI, personal communication and personal observation) . Subtidal 

Thalassia, which had been exposed to crude oil (Jackson et at. 1989; Marshall et al . 1993) 

was not killed . This supports laboratory results (Thorhaug and Marcus 1987) which suggest a 

high level of oil tolerance for this species. Syringodium biomass appeared to decrease in 

oiled areas while undergoing seasonal fluctuations in unoiled seagrass meadows. This 

finding, and toxicity tests (Thorhaug and Marcus 1987), suggest that Syringodium is sensitive 

to oiling and dispersants. 

Chronic oiling after a spill, the situation in Panama, has never been considered in 

laboratory or field experiments) with seagrasses . Oil seeping from the rocks beneath the 

refinery and washing out from oil-saturated sediments in the shoreline mangrove forests 

(Garrity and Levings 1993), after the initial exposure to "fresh" crude oil, apparently did not 

kill Thalassia, away from the shoreline in deeper water, but it may have damaged 

Syringodium populations . Seagrass meadow edges slowly receded from oiled mangrove 

shorelines suggesting that the oil concentrations reached during chronic re-oiling events were 

toxic to seagrasses . It is also possible that high concentrations of weathered oil in sediments 

67 
near the shoreline slowly killed Thalassia plants . A general thinning of subtidal Thalassia at 

oiled and unoiled sites, as observed in our study, was not attributable to oil exposure. 

Ultraviolet fluorescence (UVF) and GC/MS analyses of a set of deep sediment 

samples (Table 4) demonstrated that, unlike Zostera marina in French grassbeds, the root and 

rhizome mats of Panama's seagrasses did not prevent oil penetration into deep sediment 

layers . Oil concentrations were higher in deep sediments, at 8-lOcm and at 18-20 cm, than 

at the sediment water interface (0-2 cm). UVF analysis of sediment surface scrapes showed 

that oil concentrations in some areas (especially LREN) remained high through 1987 . After 

that date surface sediment oil concentrations decreased by an order of magnitude . 

Chromatograms in Burns (1993) and in Marshall and Sherblom (1994) show a continued 

weathering of oil throughout the study for surface scrape sediment samples collected from 

seagrass beds in Bahia Las Minas . Seagrass did not protect infauna from oil. 

Opportunistic Species Become More Abundant in Oil Exposed Sediments 

Capitellid polychaetes, usually considered to be a family of mostly opportunistic 

species and which have both been seen to increase in numbers following other oil spills, did 

follow this pattern at oiled sites in Panama. Capitellids were far more abundant at oiled sites 

(Table 4) but they were not the most abundant polychaete family . They were outnumbered by 

the serpulidae, which live attached to seagrass blades above the sediment surface . The 

serpulids were more abundant at oiled sites than at unoiled sites . Perhaps this was a 

response to lowered predation intensities by other animal taxa (fish, crabs, snails, etc .) that 

were affected by the crude oil . Cirratulids were about equally abundant at oiled and unoiled 

sites. 

Densities of Sensitive Organisms Should Be Inversely Correlated to the Oil Content of the 

Sediment 

Weathered oil remained at high concentrations in seagrass bed sediments throughout 

this study (Fig . 2) . Thus the recovery patterns seen for many organisms happened despite 

the presence of crude oil . The major changes in oil constituents, and presumed lowering of 

oil toxicity, were perhaps more important than the total oil content of the sediment. 

Reproductive and Recruitment Processes Are Often Affected by Exposure to Oil 

Caribbean caridean shrimp species typically show continuous reproduction coupled 

with high temporal and spatial variation in recruitment patterns (Bauer, 1987) . The apparent 

lack of an effect on the development, reproductive output, and recruitment of Hippolyte 

zostericola and Latreutes fucorum (Fig. 3) beginning from the first post-spill collection, 

suggested that the biological activity of the weathered oil was low for these shrimp if they 

survived or recruited to the grassbeds after the initial exposure to crude oil. It is assumed 

that the density responses to oiling shown by species at oiled and unoiled sites were mostly 

due to the initial toxic effects of the oil concentrations experienced in oiled grassbeds soon 

after the spill began. Oil effects on reproduction in other taxa were not observed and no 

generalizations can be made . 

68 
SUMMARY 

Oil appeared to have a transitory effect on Panamanian subtidal seagrasses and a 

lasting effect on some animal taxa . The faunal component of oiled seagrass meadows 

remained highly altered over the time span covered by the infaunal and epifaunal studies . It 

was apparent, that the oil effect was quickly overcome by species with high reproductive 

potentials and/or by those with highly mobile planktonic stages . A more exact statement on 

oil sensitivity cannot be made until more hydrocarbon analyses are fully completed. It is 

important to realize that, despite the existence of strong faunal and floral affinities between 

Caribbean Panama's and other shallow seagrass meadows in the Caribbean and the Gulf of 

Mexico, there are numerous differences between these areas that could drastically affect the 

outcome of a major oil spill . Since the oil spill project was funded, by the U.S . Minerals 

Management Service and Marine Spill Response Corporation, because of its relevance to 

shallow tropical ecosystems on Florida's southern coast, it seems appropriate to direct 

attention to the differences between these two areas . Vast expanses of shallow seagrass 

meadows exist on mud banks within Florida Bay. The mud banks support over 1/2 of the 

standing crop of seagrasses in Florida Bay (Powell et al. 1989) . Fleshy algae are also much 

more important in Florida Bay (Lapointe 1989) than in Panama. The bank tops are nearly 

exposed, with seagrass blades protruding through the water surface, on extreme tides . 

Flushing rates, a factor that can alter oil removal rates (Burns et al. 1991), are slow in 

Florida Bay because tidal flow is restricted by the numerous mud banks (Holmquist et al. 

1989). 

The Panamanian seagrass beds included in this study are all in lagoons that are 

bordered by subtidal coral reefs and which lie adjacent to mangrove lined shores . They are 

tiny in comparison to south Florida's seagrass meadows, they are rarely exposed on low 

tides, and they are flushed by relatively strong tidal and/or wind-generated currents . It 

would be a mistake assume that the effects of the Panama spill on seagrass beds would be 

identical to what might happen in Florida Bay. Mud bank flow restriction and seagrass 

location and other differences in hydrodynamics, topography, and ecology between our study 

sites in Panama and in Florida Bay could lead to a much different result . 

The fauna of seagrass meadows can also be highly variable from site to site . In 

seagrass beds amphipod abundance tends to decrease with latitude and caridean species 

composition varies greatly between seagrass beds within the tropics and subtropics (Bauer 

1987) . These studies and the present report each identify different numerically dominant 

species of caridean shrimp in Thalassia meadows. Latreutes fucorum, an oil-sensitive species 

in our study, accounted for 57% of the total numbers of carideans in Puerto Rican Thalassia 

beds. It was much less abundant in Bahia Las Minas and at the unoiled control sites in 

Panama . The total impact of an oil spill can only be predicted from a thorough knowledge 

of by the assemblage of oil sensitive and tolerant species within individual seagrass meadows. 

It is not safe to assume that the effects of a spill, of a similar oil type, over shallow seagrass 

beds of the same plant species would be the same in any other area. 

69 
REFERENCES 

Bauer, R.T. 1987 . Testing generalizations on latitudinal variation in the relationship between 

spawning pattern and recruitment in crustaceans . Int. Council for the Exploration of the 

Sea . 

Burns, K.A ., J. MacPherson, J. Tierney, and G. Kananen . 1991 . Hydrocarbon Analyses, 

Chapter 9, Long-term assessment of the oil spill at Bahia Las Minas, Panama, interim 

report, Volume II : technical report . OCS Study MMS 90-0031 . U.S . Department of the 

Interior, Minerals Management Service, Gulf of Mexico OCS Regional Office, New 

Orleans, La . xxxiv, 450 pp . 

Burns, K.A . 1993 . Hydrocarbon chemistry, pp . 51-130 . In, B.D . Keller, and J.B .C .Jackson, 

eds ., Long-term assessment of the oil spill at Bahia Las Minas, Panama, synthesis report, 

volume II : technical report . OCS Study MMS 93-0048 . U.S. Department of the Interior, 

Minerals Management Service, Gulf of Mexico OCS Region, New Orleans, La . 1,017 

PP. 

denHartog, C. and R.P.W.M. Jacobs. 1980. Effects of the "Amoco Cadiz" oil spill on an 

eelgrass community at Roscoff (France) with special reference to the mobile benthic 

fauna . Helgolander Meeresunters. 33 : 182-191 . 

Fauchald, K. and P.A. Jumars . 1979. The diet of worms: a study of polychaete feeding guilds . 

Oceanogr. Mar. Biol. Ann. Rev. 17: 193-284 . 

Garrity, S. and S . Levings . 1993 . Patterns of damage and recovery from a major oil spill: the 

mangrove fringe and the epibiota of mangrove roots, pp. 535-792 In, B.D . Keller and 

J.B.C. Jackson, eds., Long-term assessment of the oil spill at Bahia Las Minas, Panama, 

synthesis report, volume II : technical report . OCS Study MMS 93-0048 . U.S. 

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

New Orleans, La. 1,017 pp . 

Heck, K.L., Jr. 1977 . Habitat complexity and invertebrate species richness and abundance in 

tropical seagrass meadows. J. Biogeogr. 4: 135-142 . 

Holmquist, J.G., G.V.N. Powell, and S .M . Sogard. 1989. Sediment, water level, and water 

temperature characteristics of Florida Bay's grass-covered mud banks. Bull. Mar. Sci. 

44 : 348-364 . 

70 
Jackson, J.B .C., J.D . Cubit, B.D. Keller, V. Batista, K. Burns, H.M . Caffey, R.L. Caldwell, 

S.D . Garrity, C.D . Getter, C. Gonzalez, H.M. Guzman, K.W . Kaufmann, A.H . Knap, 

S.C . Levings, M.J . Marshall, R. Steger, R.C . Thompson, and E. Weil . (1989) . 

Ecological effects of a major oil spill on Panamanian coastal marine communities. Sci . 

243, 37-44. 

Jacobs, R.P .M .W. 1980 . Effects of the "Amoco Cadiz" oil spill on the seagrass community at 

Roscoff with special attention to the benthic infauna . Mar. Ecol. Prog. Ser. 2: 207-212 . 

Lapointe, B.E. 1989. Macroalgal production and nutrient relations in oligotrophic areas of 

Florida Bay. Bull. Mar. Sci. 44 : 312-323 . 

Marshall, M.J ., S .C . Snedaker, and C.D . Getter . 1990. The sensitivity of South Florida 

environments to oil spills and dispersants, Chapter 15, pp. 559-607, In : N.W . Phillips 

and K.S . Larson (eds), Synthesis of available biological, geological, chemical, 

socioeconomic, and cultural resource information for the South Florida area. Continental 

Shelf Associate,Inc . Prepared for U.S . Dept. of the Interior, Minerals Management 

Service, Contract No . 14-12-0001-30417, 657 pp . + 2 appendices . 

Marshall, M.J ., V.A. Batista, and D. Matias. 1993 . Effects of the 1986 Bahia Las Minas . 

Panama, oil spill on plants and animals in seagrass communities, pp . 793-832, in B .D. 

Keller and J.B .C . Jackson, eds., Long-term assessment of the oil spill at Bahia Las 

Minas, Panama, synthesis report, volume II: technical report. OCS Study MMS 93-

0048 . U.S . Department of the Interior, Minerals Management Service, Gulf of Mexico 

OCS Region, New Orleans, La . 1,017 pp. 

Marshall, M.J . and P.A. Sherblom. 1994. Effects of the 1986 Bahia Las Minas, Panama, oil 

spill on seagrass communities . Technical Report Series . Marine Spill Response 

Corporation, Washington, D.C . 

Phillips, R.C . 1980. Responses of transplanted and indigenous Thalassia testudinum ex Konig 

and Halodule wrightii Aschers to sediment loading and cold stress . Contr. Mar. Sci. 23 : 

79-87. 

Powell, G.V .N ., J .G. Holmquist, and S .M . Sogard . 1989 . Physical and environmental 

characteristics of Florida Bay with emphasis on mud banks. Bull. Mar. Sci. 44 : 522 

(abstract) . 

Thayer, G.W., D.A. Wolfe, and R.B . Williams . 1975 . The impact of man on seagrass systems . 

Am. Sci. 63 : 288-296 . 

Thorhaug, A. and J. Marcus . 1987 . Oil spill clean-up : the effect of three dispersants on three 

subtropical/tropical seagrasses . Mar. Poll. Bull. 18 : 124- 126. 

71 
Williams, S.L. 1988 . Thalassia testudinum productivity and grazing by green turtles in a highly 

disturbed seagrass bed. Mar. Biol. 98: 447-455 . 

Zieman, J.C ., R. Orth, R.C . Phillips, G. Thayer, and A. Thorhaug . 1986 . The effects of oil 

on seagrass ecosystems, pp. 37-64 . In J . Cairns, Jr. and A.L. Buikema, Jr., eds . 

Restoration of habitats impacted by oil spills . Butterworth Publications, Stoneham, MA. 

72 
Table l . 

Observations of oil spill effects on seagrass beds from other 

studies from around the world . 

1) Certain .organisms are more oil sensitive than others . 

2) Oil sensitivity depends on feeding type with filter feeders 

being the most oil sensitive . 

3) Seagrass plants shelter infauna from oil exposure by preventing 

oil from mixing into the sediment . 

4) Opportunistic species become more abundant in oil exposed 

sediments . 

5) Densities of sensitive organisms should be inversely correlated 

with the oil content of the sediment . 

6) Reproduction and recruitment are often affected by oil 

exposure . 

73 
Table 2 . 

Total counts of epifaunal taxa from November 1986 through April 

1989 . Percents are based on the overall total number of organisms 

collected by pushnetting as described in the text . 

Taxonomic UNOILED SITES OILED SITES 

Group Count Percent Count Percent 

Shrimp (Caridea and 

Penaeidea) 89,248 58 .1 59,573 59 .4 

Tanaidacea 18,055 11 .8 714 0 .7 

Amphipoda 12,561 8 .2 9,647 9 .6 

Gastropoda 7,793 5 .1 3,788 3 .8 

Paguroidea 6,342 4 .1 12,136 12 .1 

Bracyhura 5,613 3 .7 4,767 4 .8 

Fish 4,061 2 .7 1,455 1 .5 

Isopoda 2,483 1 .6 1,527 1 .5 

Ophiuroidea 2,188 1 .4 106 0 .1 

Cumacea 2,104 1 .4 987 1 .0 

Mysidacea 1,105 0 .7 3,566 3 .6 

Pycnogonida 558 0 .4 804 0 .8 

Stomatopoda 484 0 .3 893 0 .9 

Holothuroidea 251 0 .2 7 <0 .1 

Echinoidea 80 <0 .1 9 <0 .1 

Totals 

Site Type 153,533 100,337 

Overall Total 253,870 

74 
Table 3 . 

Hydrocarbons in seagrass sediment surface scrapes (4a) and at 

depths (4b) as determined by ultraviolet fluorescence (UVF) and by 

gas chromatograph (GC-URE) analysis . Units are ug/g dry wt . Site 

categories, heavy, moderate and unoiled are based on oiling levels 

based on knowledge of the spill path and on oil observed at each 

site . 

Station 1986 1987 1988 1989 

UVF GC-URE WF GC-URE WF GC-URE WF GC-URE 

(4a .) Surface Scrape Samples 

Heavily 

Oiled Sites : 

LREN 4020 2021 

LRS 792 111 

MINS/N 1499 151 

PGN 127 50 

Moderately 

Oiled Site : 

NARC 596 82 

Unoiled 

Sites : 

DONT 0 0 

PALN 0 0 

LINE 5 0 

BNV 9 0 

6683 203 658 60 277 18 

1198 137 501 51 263 50 

957 75 607 52 747 128 

211 19 188 11 143 71 

98 7 

6 0 0 0 0 2 

1 0 0 0 0 9 

102 14 4 0 0 11 

6 0 0 4 

(4b .) Subsurface Oil 

LREN 

0-2cm 4020 2021 

8-lOcm 

18-20cm 

6683 203 391 19 

665 64 

553 39 

75 
Table 4 . 

Total counts of polychaete families from September 1986 through 

April 1989 . 

Family Unoiled Sites Oiled Sites 

Count Rank Count Rank 

Sabellidae 22,547 1 18,150 3 

Syllidae 19,855 2 11,210 4 

Paraonidae 15,161 3 4,423 6 

Capitellidae 9,103 4 16,103 2 

Spionidae 4,857 5 7,894 5 

Eunicidae 3,576 6 1,547 9 

Dorvilleidae 3,541 7 1,697 8 

Cirratulidae 3,190 8 2,855 7 

Serpulidae 2,380 9 25,765 1 

Onuphidae 2,208 10 1,303 11 

Orbiniidae 2,106 11 674 12 

Nereidae 2,092 12 1,428 10 

Amphinomidae 724 13 16 31 

Terebellidae 617 14 128 18 

Ampharetidae 589 15 745 13 

Glyceridae 537 16 107 19 

Maldanidae 466 17 27 28 

Opheliidae 346 18 433 14 

Polynoidae 202 19 53 21 

Lumbrinereidae 179 20 150 17 

Arabellidae 156 21 192 16 

Chaetopteridae 143 22 34 26 

Hesionidae 107 23 254 15 

Chrysopetalidae 106 24 12 33 

Magelonidae 76 25 28 29 

Trichobranchidae 62 26 1 36 

Oweniidae 59 27 50 22 

Phyllodocidae 41 28 37 25 

Sigalionidae 26 29 22 30 

Poechilochaetidae 22 30 68 20 

Pilargidae 17 31 45 23 

Pectinariidae 16 32 - - 

Arenicolidae 11 33 16 31 

Bogueidae 9 34 - - 

Polyodontidae 8 35 - - 

Goniadidae 4 36 3 34 

Flabelligeridae 6 37 42 24 

Aphroditidae 1 38 - - 

Total 95,150 95,567 

76 
Gastropods 

iao 

ios ,a 

as 

52 24 

26 12 

0 

0 3 6 912151821242730333639 0 3 6 9 12151821242730333639 

N 

Fish Amphipoda 

40 250 

yZ 200 

24 150 

0 1 6- 100 

e SO 

Q 

p 0 

0 1 6 9 72 15 1E 21 24 27 30 73 36 79 0 1 6 9 12 15 18 21 24 27 30 33 36 39 

Mysidaceoe Tanaidacea 

400 

48 320 

36 240 

24 160 

12 80 

0 0 

0 1 6 9 12 15 18 21 24 27 30 33 76 39 0 3 6 9 12 15 IS 21 24 27 30 33 36 39 

Months since spill 

Figure l . Total counts of six epifaunal taxa collected by pushnet 

at oiled and unoiled sites, September 1986 through April 

1989 . Standard error bars were back-transformed from 

ln(x+l) . Results of repeated measures ANOVAs are : Os = 

significant difference (P< .05) between oiled and unoiled 

sites, T = significant difference through time, Os x T = 

significant interaction between oiling and time, and all 

NS = no significant differences . 

77 

Ophiuroidea 

so 
Combined oil and biogenic hydrocarbons 

in surface scrape sediment samples by GC 

4 r0 PGN 

o LREN 

o, 0\ o MINN 

°' 3 \ 

u 

O \ 

O 

u ~ 0\ 

C V0 2 r`~ ~ ~\~ 

i 

c 

U 

C 

O \ 

U v 

3 6 9 12 15 18 21 24 27 30 33 36 39 

Surface scrape sediment oil 

concentration by UVF 

s 

E 

0 

4 

a 

0 

0 

v 

c 

0 

v 

3 6 9 12 15 18 21 24 27 30 33 36 39 

Months after spill (April 1986) 

Figure 2 . Oil concentrations at oiled sites from September 1986 

through April 1989 . Methods used to measure oil 

concentrations were gas chromatography (GC) and 

ultraviolet fluorescence (UVF) . 

78 
Hippolyte zosteri.cola 

ioo Ovigerous females 

O 

eo 

N 

vo so 

.~ 

O 

40 

w 

O 

20 

T, Os xT 

U t. . 0 

N 

d 

ioo r 

Undifferentiated eggs 

eo 

(n 60 

D 

so 

N 

r20 

T, Os xT 

O 

o 

0 Ovigerous females with oocytes 

v0 

eo T,OsxT 

C 

so 

ao 

zo 

Undifferentiated eggs 

T, Os xT 

Ovigerous females with oocytes 

O, Os xT 7 

o . . . . . . . 

0 3 6 9 12 13 10 21 24 27 3O J3 36 39 0 3 6 9 12 15 18 21 24 27 30 33 36 39 

Months after spill (April 1986) Months after spill (April 1986) 

Figure 3 . Reproductive patterns for two hippolytid shrimp 

(Hippolyte zostericola and Latreutes fucorum) based on 

egg and ovarian developmental stages as described in 

Marshall and Sherblom (1994) . 

79 

Latr¢ufes JucansTn 
The 1986 Bahia Las Minas Oil Spill: 

Summary Results from the Red Mangrove (Rhizophora mangle) Fringe 

Sally C. Levings,l Stephen D. Garrityl and Kathryn A. Burns' 

1 Coastal Zone Analysis 

P . O. Box 97 

Sopchoppy FL 32358-0097 USA 

2 Australian Institute of Marine Science 

TMB 3, Townsville 

Queensland 4810 

AUSTRALIA 

INTRODUCTION 

In the Caribbean and portions of the Gulf of Mexico, red mangroves (Rhizophora 

mangle) fringe most mangrove shorelines (West 1977) . Red mangroves are characterized by 

the presence of numerous prop roots which grow from the lower part of the stem, anchoring 

the tree at multiple points . At the edge of the shore, submerged prop roots grow into the 

water, hanging in the water column until they grow into the substrate. This shoreline edge is 

known as the red mangrove fringe . The red mangrove fringe is an ecologically important 

habitat. Submerged prop roots are often the only hard surfaces in areas of soft sediments 

where mangroves grow. The thickets of submerged prop roots serve as substrate for a 

complex assemblage of attached plants and animals (the epibiota) and are critical habitat for 

many mobile, associated species (Odum et al. 1982, Rutzler and Feller 1987, Odum and 

McIvor 1990) . Species such as spiny lobsters, larval fishes, crabs and shrimp spend some or 

all of their life cycle among the submerged prop roots of the red mangrove fringe ; these in 

turn are eaten by higher order predators like birds and large fish (Odum et al. 1982, Hatcher 

et al. 1989) . Some species dependent upon the mangrove fringe are commercially or 

recreationally important (i .e . shrimp, spiny lobsters, snook, Lewis et al. 1985) . The red 

mangrove fringe and the complex of associated species are a major component of the 

mangrove nursery grounds . The productivity of these nursery areas is directly related to the 

abundance and persistence of submerged prop roots. Damage to this biogenic habitat after an 

oil spill could have prolonged negative ecological effects. 

In 1986, the rupture of an oil storage tank spilled an estimated 75,000 - 100,000 

barrels of medium weight crude oil into Bahia las Minas on the Caribbean coast of Panama 

(Cubit et al. 1987, Jackson et al. 1989) . For five years, we studied the effects of this major 

80 
oil spill on fringing red mangroves (Rhizophora mangle) and the plants and animals that live 

attached to submerged mangrove roots. Results of this study have now been published in 

technical reports, in summary overviews and in a series of technical articles (Appendix 1, in 

References). We here briefly summarize our major findings, both chemical and biological, 

from the point of view of natural recovery patterns and the biological processes which 

control recovery. We examine the direct negative effects of the oil spill and how long we 

estimate they will last . We then discuss some indirect effects of oiling, estimating habitat 

losses for associated species. Physical factors that affected oil deposition patterns, and their 

general importance in interpreting the results of case studies, are presented. Finally, we 

suggest areas where further information is needed. 

SUMMARY RESULTS 

Initial Effects 

Immediately after the spill, there were massive die-offs of plants and animals attached 

to submerged mangrove roots (Cubit et al. 1987, Jackson et al. 1989, Garrity and Levings 

1993a) . Oil coated roots repeatedly as tides rose and fell and slicks circulated throughout the 

bay. Thus the mechanical effect of oil (smothering) extended through the intertidal to shallow 

subtidal portions of roots, while species attached deeper on submerged roots were exposed 

only to dissolved petroleum hydrocarbons (toxicity) . Most plants and animals directly coated 

with oil died and subsequently sloughed off submerged prop roots . Some plants and animals 

growing deep on roots survived, at least until defoliation resulted in roots lifting from the 

water ; survivors then died from heat and desiccation stress . This process continued for 

almost a year, as oil moved through the bay, entering previously unoiled areas and reoiling 

sites previously oiled. It would not have been possible to estimate the full extent of losses for 

attached plants and animals for 6 months to one year after the spill. 

The Pattern of Mangrove Mortality 

After oil coated roots and soaked into sediments where mangroves were rooted, dieoffs of red mangrove trees began (Table 1) . The time course of defoliation, death and 

collapse of dead trees varied, depending upon location in the bay (Garrity et al. 1994) . 

Damage was heaviest in sheltered, interior sections of the bay and lighter at the edges of the 

bay where oceanic waves washed the fringe . In general, where leaf loss began first, damage 

to the fringe was most severe five years later . Within the bay, sheltered drainage streams 

drained uplands and mixed species stands of mangroves . Here, overall damage was highest, 

most trees in the mangrove fringe were defoliated within 6-9 months, and collapse following 

death began in less than 2 years. An average of 66% of fringing mangroves died. In channels 

and lagoons, which comprised most of the shoreline of the bay, about 23 % of the fringe 

died . At the mouth of the bay and on the open coast, where mangroves grew behind reef 

flats, approximately 13% of the fringe died. Defoliation took longer to occur in channels and 

lagoons and on the open coast than in streams, with new defoliation up to 2 years after the 

spill . Most collapse of dead trees occurred between 2.5 and 4 years after oiling . Based on 

81 
our observations, it would not have been possible to estimate the full extent of damage to the 

mangrove fringe throughout the bay for approximately 3 years. 

Five years after the spill and after considerable natural recruitment and planting of 

propagules behind the original fringe (Teas et al. 1989), some new trees were beginning to 

grow into the fringe (Duke and Pinzon 1993) . However, in channels and lagoons and on the 

open coast, < 1 % of the fringe had regrown ; reestablishment was so low on the open coast 

that sections of the fringe were expected to be permanently lost (Duke and Pinzon 1993) . In 

sheltered drainage streams, trees had recruited along -- 5 % of the original fringe . For all 

areas, the estimated time for the fringe to regrow to its pre-spill state was on the order of 

decades rather than years. 

Lon -t~ erm Structural Changes in the Mangrove Fringe 

Even in surviving portions of oiled mangrove fringe, both the physical structure of the 

trees and environmental conditions in and around submerged prop roots changed (Table 1) 

(Garrity et al. 1994) . First, there were fewer submerged prop roots at oiled than unoiled sites 

within areas of surviving fringe . Second, submerged prop roots of fringing mangroves were 

shorter at oiled than unoiled sites on the open coast and in drainage streams, but not in 

channels. Third, throughout the bay, more submerged prop roots were dead at oiled sites . 

Fourth, surviving oiled trees were partially defoliated up to 5 years post-spill when our 

observations ended, resulting in increased light reaching root level. 

These finer scale alterations to the habitat in turn further affected associated species, 

already negatively affected by the absolute loss of major sections of the fringe . Lowered 

density of roots per unit shoreline and decreased root length per root reduced the total area 

of submerged root surfaces, thus quantitatively reducing the amount of available habitat for 

both sessile and mobile species . Qualitatively, at oiled sites, increased levels of light reaching 

root level, increases in the proportion of dead vs . live submerged prop roots and decreases in 

the depth of submergence (depth of submergence is dependent on root length) created a 

different habitat for the plants and animals that live attached to submerged prop roots and for 

the species that live or feed among submerged prop roots. These changes will likely persist 

until the mangrove fringe is fully re-established; this process will probably take decades . 

Lon -tg erm Reductions in Plants and Animals Encrusting Submerged Prop Roots 

In an attempt to factor out the effects of habitat loss from those of oiling itself, we 

compared the cover of plants and animals on remaining submerged prop roots at oiled sites 

to that on similar roots at unoiled sites . These analyses showed that the cover of plants and 

animals on submerged prop roots decreased significantly after oiling (Garrity and Levings 

1993b, Levings et al. 1994) . Restricting our discussion to major groups of sessile 

invertebrates, oiling reduced cover for at least 4-5 years (Figure 1) . 

On the open coast, sessile invertebrates on submerged prop roots included sponges, 

corals, anemones, tunicates, bryozoans, vermetids and hydroids. Cover was significantly 

reduced for four years after oiling, but did not differ significantly between oiled and unoiled 

sites in the fifth year after the spill . However, some groups (e.g. corals, anemones and 

82 
tunicates) remained rarer at oiled than unoiled sites in year 5 post-spill . In channels and 

lagoons, roots were typically encrusted with oysters (Crassostrea virginica) . Oyster 

abundance dropped by approximately an order of magnitude after oiling . Although cover 

increased over time at oiled sites, differences between oiled and unoiled sites remained 

significant through five years post-spill, when observations ceased. In drainage streams, the 

false mussel Mytilopsis sallei typically covered more than 25 % of the space on submerged 

prop roots . Within three months after oiling, false mussels had almost disappeared from oiled 

drainage streams . False mussels were significantly less abundant at oiled than unoiled streams 

for five years post-spill . Unlike the partial recovery of oysters in channels, there was little 

evidence of recovery in drainage streams by 1991 . 

Reductions in the cover of abundant sessile invertebrates on remaining prop roots thus 

persisted through at least 4-5 years after oiling . The full extent of the damage was evident 

within approximately six months to one year after the spill. Full recovery remains to be 

documented in any habitat. 

Estimated Reductions in Standing Crop 

We estimated reductions in standing crop by combining data on the reduction in 

surface area on submerged prop roots with the reduction in percent cover of groups of sessile 

invertebrates at oiled as compared to unoiled sites (Garrity et al. 1994, Levings et al. 1994). 

On the open coast, area of submerged root surfaces was reduced 33 % five years post-spill, 

but there was no statistically significant difference in percent cover of sessile invertebrates at 

oiled as compared to unoiled sites . Thus we estimate that standing crop was reduced by 

--- 33 %, caused by a reduction in the amount of habitat available. In channels and lagoons, 

surface area on submerged prop roots was reduced -- 38 % and cover of oysters was reduced 

44% at oiled as compared to unoiled sites. Combined, we estimate a reduction of 65% in 

standing crop of oysters five years post-spill . In drainage streams, surface area on submerged 

prop roots was reduced by 74% and false mussels covered 96% less space on roots . 

Combined, the net reduction in standing crop was estimated to be -99% in drainage 

streams . The severity of estimated losses in standing crop five years post-spill illustrates the 

strength and persistence of negative effects from the 1986 Bahia las Minas oil spill. 

Chronic Oiling and the Continued Presence of Toxic Hydrocarbons in the Environment 

Initial weathering processes removed most volatile hydrocarbons and all marker 

alkanes in oil adsorbed to surface sediments within six months after the spill (Burns et al. 

1994) . This initially fast rate of biodegradation was not maintained in the rate of 

disappearance of aromatic hydrocarbons over time. Anoxic mangrove muds served as longterm reservoirs for toxic hydrocarbons, causing chronic contamination of contiguous coastal 

communities for over five years. 

We documented chronic oiling by recording the incidence and thickness of oil slicks 

and the amount of oil deposited on artificial prop roots (dowels) at quarterly intervals 

(Levings et al. 1994). On the open coast, relatively little oil was deposited on dowels, except 

during occasional wet season washouts. The frequency and thickness of oil slicks also 

83 
declined at oiled sites, with most slicks recorded as iridescence or silvery sheen by five years 

post-spill ; slicks were seen at five of nine visits in May 1991 . In channels and lagoons, 

pulses of oil were frequently recorded, with the greatest washouts occurring from February -

August 1989 (approximately 2.5 years post-spill) . The frequency of slicks did not decline 

over time and some black oil was observed in May 1991 . In drainage streams between 1987 

and 1991, oil slicks were seen on 128/129 visits and ranged from black oil to iridescent 

patches . 

Oil leaching out of heavily contaminated sediments was bioaccumulated by oysters in 

channels and false mussels in drainage streams for at least five years after the spill. Both 

species accumulated the whole range of alkylated polynuclear aromatic hydrocarbons in the 

naphthalene through benzoperylene elution range, seemingly in proportion to what was 

leached from sediments (Burns and Yelle-Simmons 1994). Levels of oil in bivalve tissues 

were high enough to reduce significantly the growth and reproductive rate of both species 

examined (Bayne et al. 1982) . Continuing contamination of oysters and false mussels 

attached to submerged mangrove prop roots suggests the possibility that oil may contaminate 

near-shore food chains and/or local fisheries. More data are needed to examine this 

possibility. 

There was a change in the composition of aromatic hydrocarbons in the fifth year 

post-spill ; this indicated the depletion of the most soluble and acutely toxic hydrocarbons in 

readily teachable reservoirs . We anticipate that over the next 5 - 10 years, impacts will 

probably grade from acutely lethal to sublethal levels . However, some sediment cores 

retained significant levels of the more volatile and toxic aromatic hydrocarbons through year 

six post-spill (Burns and Yelle-Simmons 1992), indicating the persistence of some sediment 

reservoirs of highly toxic hydrocarbons . These results are in contrast to expectations that oil 

residues will degrade quickly under tropical conditions . 

Indirect Effects of Oilin : Estimated Long-term Effects on Associated Species 

We estimated the effects of the 1986 Bahia las Minas oil spill using (1) direct 

measures of the abundance of wood-boring isopods and (2) losses of epibiota used as shelter, 

settlement and juvenile habitat by spiny lobsters (Panulirus argus, Levings and Garrity 

1994) . For boring isopods in sheltered channels and lagoons, there was no significant 

difference in isopod abundance on suitable (live) roots at oiled and unoiled sites . However, 

suitable (live) submerged prop roots were less abundant at oiled sites, leading to a reduction 

of over 60% in the number of submerged prop roots containing isopods at oiled as compared 

to unoiled sites 5 years post-spill . We estimated effects on non-boring species using two 

groups of epibiota (foliose red algae and arborescent hydroids and bryozoans) used as 

juvenile habitat by spiny lobsters . We estimated the amount of habitat for juvenile spiny 

lobsters in the mangrove fringe was reduced -40-50% five years after the oil spill on the 

open coast and in sheltered channels and lagoons . Such reductions may have effects on local 

populations of mobile species associated with the mangrove fringe . 

84 
Factors Important in Generalizing from our Results 

Case histories are used routinely to estimate possible damages from future spills . 

However, the generality of results depends in part upon the probability that patterns of oil 

deposition would be similar during other spills . For maximum usefulness for planning, 

results from any spill must be put into a broader context than the particular physical 

conditions that prevailed during that spill. In particular, variability in pertinent physical 

factors must be examined . 

Movement and deposition of oil slicks were studied using aerial and ground 

observations of the oil spill, hydrographic and meteorological data from environmental 

monitoring, and freshwater runoff modeling (Cubit and Levings 1993). The spatial pattern of 

oiling, and therefore the habitats and biota affected, was dependent on weather conditions at 

the time of the spill, and would have been predictably different in other seasons. Conditions 

at the time of the 1968 Witwater spill were used to predict patterns of oil deposition ; data on 

damage to reef flat biota and mangroves were consistent with our predictions of the spatial 

pattern of damage. Use of this, and other case studies, requires the consideration of other 

possible patterns of oil accumulation that would have been produced by other combinations 

of conditions . Such considerations must be included in predictions of potential risks of future 

oil spills . If they are not, oil spill contingency plans might be inadequate . 

DISCUSSION 

Patterns of Man uove Mortality 

Sediment oil concentrations were of the same order of magnitude (104-105 ug/g dry 

weight) at all oiled sites. However, there were order of magnitude differences in the percent 

of the mangrove fringe that died among sites . The amount of damage to a site was probably 

related to the pattern of oil deposition, the persistence of the oil both on prop roots and in 

sediments, and the particular physical characteristics of the site . Depth and type of substrate 

appeared to be of importance . In streams and channels, most trees rooted entirely in the 

intertidal zone died, while trees with some or most prop roots anchored in subtidal sediments 

often survived. On the open coast, trees rooted in coarse sediments like sand and coral 

rubble survived better than trees rooted in mud or peat; depth was also important. Death of 

mangroves after oil coating of gas exchange surfaces has been reported (e.g . Cintron and 

Schaeffer-Novelli 1983, Odum and Johannes 1975); survival of the outer fringe in spills that 

killed interior mangroves has also been noted (Baker et al. 1980, Cintron et al. 1981, 

Nadeau and Berquist 1977) . Getter et al. (1981, 1984) presented a model of oil impact on 

fringing mangroves based upon topography and forest type, suggesting that maximum 

damage occurs in shallow waters near the berm (unless oil is carried over the berm during 

high tides)(see also Lewis 1983, Jacobi and Schaeffer-Novelli 1990). 

In our study, more mangroves died where (1) prop roots were heavily coated with oil 

for at least 18 months and (2) sediments were soaked with oil. Survival was variable (and 

often high) unless both sediments and prop roots were oiled. However, knowledge of the 

85 
effects of oil on mangroves is far from complete ; we suggest further study of the biological 

mechanisms controlling mangrove mortality. 

Natural Recovery 

Oil spills are distinct from natural disasters such as hurricanes in that chemical 

contamination may be long-lasting . Recovery from a hurricane may take many years (Smith 

et al. 1994), but will not be slowed by the presence of toxic compounds . Hydrocarbons 

deposited in soft sediments may persist for decades and have negative effects when leached 

from sediment reservoirs (Bayne et al. 1982, Corredor et al. 1990, Teal et al. 1992) . We 

know of no way to remove oil from soft sediments without harming or destroying the habitat 

itself. 

Understanding the biological basis of recovery processes, both with and without 

toxicants, is the key to effective contingency planning and mitigation. Biogenic habitats, that 

is those created by their constituent plants or animals, are especially vulnerable to negative 

impacts of oil spills . Examples of biogenic habitats include salt marshes, seagrass beds, 

coral reefs and mangrove forests . Damage to the structuring organism can cause loss of the 

habitat (i .e. erosion of the salt marsh), with cascading effects on the suite of associated 

species (loss of salt marsh crab populations and the birds that eat them) . Biogenic habitats 

thus by their nature are uniquely susceptible to stressors that affect the major structuring 

organisms . In contrast, communities occurring in non-biogenic habitats (such as on rocky 

shores) may be devastated by oiling, but the habitat remains, ready to be repopulated. 

Recovery processes may be prolonged and ecologically complex (e .g . Southward and 

Southward 1978), but the potential habitat itself (rock surfaces) has not been destroyed . 

Recovery in biogenic habitats is linked to repopulation of the structuring organism(s) and 

associated species. 

Five years after the 1986 Bahia las Minas oil spill, trees were beginning to regrow 

into the mangrove fringe, but occupied < 5 % of the fringe at any site . Regrowth was lowest 

on the exposed open coast, where drift logs crushed recruits . Duke and Pinzon (1993) 

predicted that sections of the fringe on the open coast would probably be lost due to this 

natural source of disturbance. Thus prospects for regrowth may actually be lowest where 

damage from the oil spill was least overall. Until we understand the factors controlling 

regrowth of mangroves after natural or anthropogenic damage (e .g . Smith et al. 1994), it 

will be difficult or impossible to predict the time course required for repopulation . 

With respect to species associated with the mangrove fringe, structural changes had 

reduced the amount of habitat (submerged root surfaces) at all oiled sites. Only on the open 

coast did sessile invertebrates cover as much space on a per root basis at oiled and unoiled 

sites . There were additional reductions in percent cover of oysters and false mussels in 

channels and streams that may have been related to release of toxic hydrocarbons from 

sediments. Reductions in standing crop of between 33-99% were estimated 5 years post-spill . 

However, epibiota were returning in all habitats, especially growing on prop roots just 

entering the water. In this case, regrowth of the fringe and return of associated species were 

occurring at the same time, even though there were significant differences in the percent 

cover of major groups between oiled and unoiled sites in channels and streams. 

86 
Mitigation and Natural Recovery 

Many methods of clean-up or mitigation may actually slow recovery when considered 

in the light of what is known about the biology of plants and animals affected by oil . For 

plants or animals that recolonize by regrowth from surviving fragments (i .e . some algae and 

corals), at least partial protection of the existing population may be crucial to the recovery 

process . This was the major mechanism for repopulation on reef flats after the Bahia las 

Minas oil spill (Cubit and Connor 1993a, b) . Cleanup methods such as dispersants or hot 

water may kill surviving fragments and slow repopulation . Even for species that recolonize 

by settlement and growth of spores or larvae, prospects for recovery may be better if local, 

parent populations persist . In the case of the mangrove fringe, we recommend protection of 

at least some sections (1) to serve as a potential source for mangrove seedlings that can 

recolonize bare areas after oiling, and (2) to slow erosion, limiting deposition of oily 

sediments in adjacent habitats, like subtidal grass beds or coral reefs . Such protected sections 

of fringe could also (3) serve as sources for larvae and spores of species that live attached to 

submerged prop roots, speeding the recovery of associated species and returning food sources 

for higher order predators . Thus, even if it is not possible to keep oil completely out of 

mangroves, protection of at least sections of the fringe will probably assist natural recovery. 

Other factors, such as gregarious settlement (Levings et al. 1994) or the absence of 

settlement cues, may also substantially affect the dynamics of the recovery process. On one 

hand, we know too little of the dynamics of dispersal and settlement to assume that 

recolonization from distant sources will be sufficient to repopulate an area after a major spill. 

On the other, well-meaning attempts to assist recovery may actually slow the process ; 

clearing and replanting of dead areas appears to have slowed repopulation of mangroves after 

the Bahia las Minas spill (Duke and Pinzon 1993) . The need for much additional research is 

clear. Prior planning and approval of clean up and mitigation procedures after detailed 

consideration of possible direct and indirect effects is highly recommended. 

Factors Important in Generalizing from our Results 

Case studies are routinely used to estimate possible damage from future oil spills . 

However, results from studies of the 1986 Bahia las Minas oil spill cannot be accurately used 

unless the biological basis of injury and recovery patterns are understood. In addition, 

physical factors control the spread and persistence of oil and must be taken into account . As 

the best studied tropical oil spill, results of the Bahia las Minas oil spill are likely to be 

widely cited. However, damage would have been predictably different under different 

physical conditions because oil would have been deposited differently along the shore. For 

example, if more oil had been deposited deep in mangrove forests, there might have been 

less damage to corals and sea-grass beds, and more damage to interior mangrove forests . 

Repopulation would then have followed a different (and probably slower) course in interior 

mangroves, with more oil sequestered in sediments with little water exchange . Because 

seagrass beds died only where sediments were oil-soaked, it is unlikely that any seagrass 

beds would be killed if oil came ashore at higher water levels . As is shown by the 

potentially wide-ranging effects of weather and sea conditions on oil deposition, the use of 

87 
this case study requires taking into account the possible patterns of oil deposition that would 

have been produced by other combinations of conditions. 

SUMMARY 

In April 1986, an estimated 75,000 -100,000 barrels of medium-weight crude oil 

spilled into Bahia las Minas on the Caribbean coast of Panama. As part of a five year study 

of this spill, we examined the habitat formed by the outer shoreline fringe of red mangroves 

(Rhizophora mangle) and the plants and animals encrusting the submerged prop roots of these 

mangroves. Submerged prop roots serve as hard substrata for algae and sessile invertebrates, 

a limited resource where mangroves grow. Thickets of submerged prop roots and plants and 

animals living on the roots are nursery grounds for many ecologically and economically 

important species. The productivity of these nursery areas is directly related to the abundance 

and persistence of submerged prop roots. 

Evidence from our studies shows that damage from an oil spill was much longer 

lasting than the initial rapid and massive die-offs of oil-coated plants and animals . Five years 

after the Bahia las Minas spill, there were significant reductions in the total length of 

shoreline fringed by red mangroves . In areas where red mangroves survived or regenerated, 

submerged prop roots were fewer and extended less deeply into the water. Oysters and false 

mussels collected from submerged prop roots between 1986 and 1991 had continued high 

tissue levels of oil residues, which were associated with reduced populations of oysters and 

false mussels during the five year study. Release of oil from sediments caused chronic 

reoiling ; virtually undegraded oil residues were found in some heavily oiled sediments 6 

years post-spill . These data also indicated possible oil contamination of the near-shore food 

chain . Additionally, we estimated that this spill reduced the number of roots bored by 

isopods by over 60% and the amount of habitat for post-larval spiny lobsters (Panulirus 

argus) by 40-50% . 

Workers attempting to generalize our results must carefully consider short-term, 

seasonal and annual variation in physical conditions (e .g. weather, sea, and runoff . During 

this spill, the spatial pattern of oiling, and therefore the habitats and biota affected, was 

dependent upon conditions at the time of the spill, and would have been predictably different 

in other seasons. 

Considering that more than half of the tropical and subtropical shorelines of the world 

are fringed with mangroves, oil spills have the potential to cause severe and persistent 

damage to the ecologically and economically important species dependent upon these critical 

coastal habitats . This potential must be carefully studied as part of the contingency planning 

process . It is critical that we understand the biological processes underlaying the type of 

damage observed. In the case of mangroves, data are not presently available to determine 

fully the biological causes of oil-related mortality. Until we understand the processes causing 

mortality after oiling, we cannot develop better risk and damage assessments or more 

effective cleanup and mitigation strategies . 

88 
CONCLUSIONS 

1 . It can take months to years to estimate how much habitat will be lost, even as a direct 

effect of oiling . Less obvious direct and indirect negative effects may be subtle and/or 

difficult to identify . 

2 . Recovery of the trees (biogenetic substrate) and reestablishment of the structure and 

environment of the mangrove fringe will probably take decades or longer . 

3. Toxic hydrocarbon compounds will probably persist for at least 20 years, and 

continue to affect the plants and animals of the mangrove fringe . Transmission of 

toxic compounds up the food chain or to surrounding habitats is possible, but has not 

been documented. 

4. Contingency planning should combine knowledge about patterns of damage from 

oiling with estimates of where oil will penetrate. These estimates should be based on 

seasonal and annual variation in weather and sea conditions that affect oil deposition . 

ACKNOWLEDGMENTS 

R. Carney, J. Cubit, and R. Green provided essential advice throughout the project; 

J. J. Kendall of MMS helped in many ways over the course of this long-term project. Data 

collection was funded by the Smithsonian International Environmental Sciences Program and 

by contracts 14-12-001-30355 and 14-12-0001-30393 between the Minerals Management 

Service of the U.S . Department of the Interior and the Smithsonian Institution. Facilities 

were provided by the Smithsonian Tropical Research Institute. We thank Recursos Marinos 

of the Republic of Panama for permission to work in Panama. 

89 
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API/EPA/USCG, Washington, D. C. 

90 
Cubit, J . D. and J. L. Connor . 1993b . Effects of the 1986 Bahia las Minas oil spill on reef 

flat sessile biota, algal-turf infauna, and sea urchins. pp . 131-242., In, Long-term 

assessment of the oil spill at Bahia las Minas, Panama, Synthesis Report, Volume II, 

Technical Report. OCS Study MMS 93-0048. Keller, B. D, and J . B. C. Jackson, 

eds . U. S . Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office, New Orleans, LA . 

Cubit, J . D., C. D. Getter, J. B. C. Jackson, S. D. Garrity, H. M. Caffey, R. C. 

Thompson, E. Weil and M. J. Marshall. 1987. An oil spill affecting coral reefs and 

mangroves on the Caribbean coast of Panama . In, Proceedings of the 1987 Oil Spill 

Conference pp . 401-406, API/EPA/USCG, Washington, D. C. 

Cubit, J . D. and S. C. Levings. 1993 . Weather, sea conditions and topography affecting oil 

deposition during the 1986 Bahia las Minas oil spill. pp. 25-49 . In, Long-term 

assessment of the oil spill at Bahia las Minas, Panama, Synthesis Report, Volume II, 

Technical Report. OCS Study MMS 93-0048, Keller, B. D. and J. B. C. Jackson, 

eds . U. S . Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office . New Orleans, LA. 

Duke, N. C. and Z. Pinzon. 1993 . Mangrove forests . pp. 447-533, In, Long-term 

assessment of the oil spill at Bahia las Minas, Panama, Synthesis Report, Volume II, 

Technical Report. OCS Study MMS 93-0048, Keller, B. D. and J. B. C. Jackson, 

eds . U. S . Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office, New Orleans, LA. 

Garrity, S . D. and S. C. Levings. 1993a. Effects of an oil spill on some organisms living on 

mangrove (Rhizophora mangle L.) roots in low-wave energy habitats in Caribbean 

Panama . Marine Environmental Research 35: 251-271 . 

Garrity, S . D. and S. C. Levings. 1993 . Patterns of damage and recovery from a major oil 

spill : the mangrove fringe and the epibiota of mangrove roots . pp. 535-792. In, 

Long-term assessment of the oil spill at Bahia las Minas, Panama, Synthesis Report, 

Volume II, Technical Report . OCS Study MMS 93-0048, B. D. Keller and J. B. C. 

Jackson, eds ., U. S . Department of the Interior, Minerals Management Service, Gulf 

of Mexico, OCS Regional Office, New Orleans, LA. 

Garrity, S . D., S . C. Levings and K. A. Burns . 1994. The Galeta oil spill I. Long-term 

effects on the physical structure of the mangrove fringe . Estuarine Coastal and Shelf 

Science 38: 327-348 . 

Getter, C. D., G. I. Scott and J . Michel . 1981 . The effects of oil spills on mangrove forests : 

a comparison of five oil spill sites in the Gulf of Mexico and the Caribbean Sea. In, 

Proceedings of the 1981 Oil Spill Conference, pp. 535-540, API/EPA/USCG, 

Washington, D. C. 

91 
Getter, C. D., G. Cintron, B. Dicks, R. R. Lewis III and E. D. Seneca. 1984 . The recovery 

and restoration of salt marshes and mangroves following an oil spill. pp . 65-111, In: 

Restoration of habitats impacted by oil spills (ed. J . Cairns and A. L. Buikema Jr.) 

Butterworth, Boston. 

Hatcher, B. G., R. E. Johannes and A. I. Robertson . 1989. Review of research relevant to 

the conservation of shallow tropical marine ecosystems. Oceanography and Marine 

Biology Review 27 : 337-414. 

Jackson, J. B. C., J . D. Cubit, B. D. Keller, V. Batista, K. A. Burns, H. M. Caffey, R. L. 

Caldwell, S. D. Garrity, C. D. Getter, C. Gonzales, H. Guzman, K. W. Kaufmann, 

A. H. Knap, S . C. Levings, M. J. Marshall, R. Steger, R. C. Thompson and E. 

Weil. 1989. Ecological effects of a major oil spill on Panamanian coastal marine 

communities. Science 243 : 37-44. 

Jacobi, C. M. and Y. Schaeffer-Novelli . 1990. Oil spills in mangroves : a conceptual model 

based on long-term field observations . Ecological Modeling 52: 53-59. 

Lewis, R. R. III 1983 . Impact of oil spills on mangrove forests . pp. 171-183, In: Biology 

and ecology of mangroves . H. J. Teas, ed . Dr. W. Junk Publishers, The Hague . 

Lewis, R. R. III, R. G. Gilmore Jr ., D. W. Crews, and W. E. Odum. 1985 . Mangrove 

habitat and fishery resources of Florida. pp . 281-336, In, Florida aquatic habitat and 

fishery resources . W. Seaman Jr ., ed. Florida Chapter of the American Fisheries 

Society, Kissimmee, Florida. 

Levings, S . C. and S . D. Garrity. 1994. Effects of oil spills on fringing red mangroves 

(Rhizophora mangle) : losses of mobile species associated with submerged prop roots. 

Bulletin of Marine Science 54: 782-794. 

Levings, S . C., S. D. Garrity and K. A. Burns . 1994. The Galeta oil spill III . Chronic 

reoiling, long-term toxicity of hydrocarbon residues and effects on epibiota in the 

mangrove fringe . Estuarine Coastal and Shelf Science 38: 365-395 . 

Nadeau, R. J. and E. T. Berquist . 1977. Effects of the 18 March 1973 oil spill near Cabo 

Rojo, Puerto Rico, on tropical marine communities . pp. 535-538 . In, Proceedings of 

the 1977 Oil Spill Conference. API/EPA/USCG . 

Odum, W. E. and R. E. Johannes . 1975 . The response of mangroves to man-induced 

environmental stress . pp. 52-62, In, Tropical Marine Pollution, eds . E. J. Ferguson 

Wood and R. E. Johannes . Elsevier Scientific Publishing Company, Amsterdam . 

92 
Odum, W. E. and C. C. McIvor. 1990. Mangroves . pp. 517-548 . In, Ecosystems of Florida. 

R. L. Myers and J . J. Ewel, eds. University of Central Florida Press, Orlando . 

Odum, W. E., C. C. McIvor and T. J . Smith, III . 1982 . The ecology of mangroves of South 

Florida: a community profile. FWS/OBS-81/24 . U. S. Fish and Wildlife Service, 

Office of Biological Services . 144 pp. 

Rutzler, K. and C. Feller . 1987 . Mangrove swamp communities. Oceanus 30(4) : 16-24 . 

Smith, T. J . III, M. B . Robblee, H . R. Warless and T. W. Doyle. 1994. Mangroves, 

hurricanes, and lightning strikes . Bioscience 44: 256-262 . 

Southward, A. J. and E. C . Southward. 1978. Recolonization of rocky shores in Cornwall 

after use of toxic dispersants to clean up the Toney Canyon spill . J. Fisheries 

Research Board of Canada 35 : 682-706 . 

Teal, J . M., J. W. Farrington, K. A. Burns, J. J . Stegeman, B. W. Tripp, B. Woodin and 

C. Phinney. 1992 . The West Falmouth oil spill after twenty years : Fate of fuel oil 

compounds and effects on animals . Marine Pollution Bulletin 24 : 607-614 . 

Teas, H. J., A. H. Lasday, E. Luque, R. A. Morales, M. E. De Diego and J. M. Baker. 

1989. Mangrove restoration after the 1986 Refineria Panama oil spill. Proceedings of 

the 1989 Oil Spill Conference pp. 433-437 . API/EPA/USCG, Washington, D. C. 

West, R. C. 1977. Tidal salt-marsh and mangal formations of Middle and South America, 

pp. 193-213, In: V. J. Chapman, ed., Ecosystems of the world 1 : Wet coastal 

ecosystems. Elsevier Scientific Pub., Amsterdam. 

Appendix 1 

Publications : Studies of effects of the 1986 Bahia las Minas oil spill on the mangrove fringe 

Journal Articles 

Burns, K. A., S . D. Garrity, D. Jorissen, J . MacPherson, M. Stoelting, J . Tierney and L. 

Yelle-Simmons. 1994. The Galeta oil spill II . Unexpected persistence of oil trapped in 

mangrove sediments . Estuarine Coastal and Shelf Science 38 : 349-364. 

Burns, K. A., S . D. Garrity and S . C. Levings . 1993 . How many years until mangrove 

ecosystems recover from catastrophic oil spills? Marine Pollution Bulletin 26: 239-

248. 

93 
Burns, K. A. and L. Yelle-Simmons . 1994. The Galeta oil spill IV. Relationship between 

sediment and organism hydrocarbon loads . Estuarine Coastal and Shelf Science 38 : 

397-412 . 

Garrity, S . D. and S . C. Levings. 1993 . Effects of an oil spill on some organisms living on 

mangrove (Rhizophora mangle L.) roots in low-wave energy habitats in Caribbean 

Panama. Marine Environmental Research 35 : 251-271 . 

Garrity, S. D., S. C. Levings and K. A. Burns . 1994. The Galeta oil spill I. Long-term 

effects on the physical structure of the mangrove fringe . Estuarine Coastal and Shelf 

Science 38 : 327-348. 

Jackson, J. B. C., J. D. Cubit, B. D. Keller, V. Batista, K. A. Burns, H. M. Caffey, R. L. 

Caldwell, S . D. Garrity, C. D. Getter, C. Gonzales, H. Guzman, K. W. Kaufmann, 

A. H. Knap, S. C. Levings, M. J. Marshall, R. Steger, R. C. Thompson and E. 

Weil. 1989 . Ecological effects of a major oil spill on Panamanian coastal marine 

communities. Science 243 : 37-44 . 

Levings, S . C. and S . D. Garrity . 1994 . Effects of oil spills on fringing red mangroves 

(Rhizophora mangle) : losses of mobile species associated with submerged prop roots. 

Bulletin of Marine Science 54 : 782-794 . 

Levings, S. C., S . D. Garrity and K. A. Burns . 1994. The Galeta oil spill III. Chronic 

reoiling, long-term toxicity of hydrocarbon residues and effects on epibiota in the 

mangrove fringe . Estuarine Coastal and Shelf Science 38 : 365-395 . 

Technical Reports 

Burns, K. A. 1993. Hydrocarbon chemistry. pp. 51-129. In, Long-term assessment of the oil 

spill at Bahia las Minas, Panama, Synthesis Report, Volume II, Technical Report. 

OCS Study MMS 93-0048, Keller, B. D. and J. B. C. Jackson, eds. U. S. Dept. of 

the Interior, Minerals Management Service, Gulf of Mexico OCS Regional Office, 

New Orleans, LA. 

Burns, K. A. and L. Yelle-Simmons . 1992. Final report : Hydrocarbon chemistry. Long-term 

assessment of the Bahia las Minas (Panama) oil spill year 6 . Marine Spill Response 

Corporation, Washington, D. C. 

94 
Cubit, J. D., J . B. C. Jackson, K. Burns, S . D. Garrity, H. Guzman, K. W. Kaufmann, A. 

H. Knap, S . C. Levings, M. J. Marshall, R. C. Thompson, and E. Weil. 1988. 

Effects of an oil spill on mangrove, seagrass, reef flat and coral communities on the 

Caribbean coast of Panama. pp . 109-112. In, Proceedings of the eighth annual Gulf of 

Mexico information transfer meetings, OCS Study/MMS 88-Q035, U. S . Department 

of the Interior/ Minerals Management Service, Gulf of Mexico OCS Regional Office, 

New Orleans, LA . 

Cubit, J . D. and S. C. Levings . 1993 . Weather, sea conditions and topography affecting oil 

deposition during the 1986 Bahia las Minas oil spill. pp. 25-49. In, Long-term 

assessment of the oil spill at Bahia las Minas, Panama, Synthesis Report, Volume II, 

Technical Report. OCS Study MMS 93-0048, Keller, B. D. and J . B. C. Jackson, 

eds . U. S . Dept. of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office, New Orleans, LA . 

Garrity, S . D. and S. C. Levings . 1991 . Effects of the April 1986 oil spill at Isla Payardi on 

the epibiota of mangrove (Rhizophora mangle L.) roots . pp . 179-260. In, B. D. 

Keller and J . B. C. Jackson, eds . Long-term assessment of the oil spill at Bahia las 

Minas, Panama. Interim report volume II, OCS Study MMS 90-0031 . U.S . 

Department of the Interior, Minerals Management Service, Gulf of Mexico, OCS 

Regional Office, New Orleans, LA. 

Garrity, S . D. and S. C. Levings. 1993 . Patterns of damage and recovery from a major oil 

spill : the mangrove fringe and the epibiota of mangrove roots . pp . 535-792 In, Longterm assessment of the oil spill at Bahia las Minas, Panama, Synthesis Report, 

Volume II, Technical Report. OCS Study MMS 93-0048, B. D. Keller and J . B. C. 

Jackson, eds., U. S. Department of the Interior, Minerals Management Service, Gulf 

of Mexico, OCS Regional Office, New Orleans, LA. 

Keller, B. D., J . B. C. Jackson, J. D. Cubit, J. D. Brawn, K. A. Burns, R. L. Caldwell, N. 

C. Duke, S. D. Garrity, H. M. Guzman, K. W. Kaufmann, S . C. Levings, M. J. 

Marshall, R. Steger, and R. C. Thompson. 1990. Panama oil spill: biological effects. 

pp . 300-304 . In, Proceedings of the tenth annual Gulf of Mexico information transfer 

meetings, OCS Study MMS 90-0027, U. S . Department of the Interior/ Minerals 

Management Service, Gulf of Mexico OCS Regional Office, New Orleans, LA. 

Keller, B. D., J. B. C. Jackson, J. D. Cubit, S . D. Garrity and H. M. Guzman. 1993 . 

Introduction . pp . 1-24 In, Long-term assessment of the oil spill at Bahia las Minas, 

Panama, Synthesis Report, Volume II, Technical Report . OCS Study MMS 93-0048, 

B. D. Keller and J. B. C. Jackson, eds, U. S. Department of the Interior, Minerals 

Management Service, Gulf of Mexico, OCS Regional Office, New Orleans, LA. 

95 
Levings, S. C. and S. D. Garrity. 1992 . Fringing mangroves and the epibiota of their roots: 

Effects of the Bahia las Minas oil spill during the first five years after the spill. pp . 

419-420 . In, Proceedings of the 12th Information Transfer Meetings, Gulf of Mexico 

Region, November 1991 . Minerals Management Service, Department of the Interior. 

OCS Study MMS 92-0027. 

Summary Overviews and Conference Proceedings 

Cubit, J . D., C. D. Getter, J . B. C. Jackson, S . D. Garrity, H. M. Caffey, R. C. 

Thompson, E. Weil and M. J. Marshall. 1987. An oil spill affecting coral reefs and 

mangroves on the Caribbean coast of Panama. In, Proceedings of the 1987 Oil Spill 

Conference pp . 401-406, API/EPA/USCG, Washington, D. C. 

Garrity, S . D., S. C. Levings and K. A. Burns. 1993 . Chronic oiling and long-term effects 

of the 1986 Galeta oil spill on fringing mangroves. In, Proceedings of the 1993 Oil 

Spill Conference pp . 319-324 . API/EPA/USCG, Washington, D. C. 

Garrity, S . D., S. C. Levings and K. A. Burns. Five years of oil spill effects on fringing red 

mangroves: Summary results from the 1986 Bahia las Minas oil spill. In, Proceedings 

of the Third International Conference on the Effects of Oil on Wildlife, in press. 

96 
Table 1 

Changes in the mangrove fringe five years after the Bahia las Minas oil spill : 

Comparisons of oiled vs . unoiled sites 

Open Coast Channels and Lagoons Drainage Streams 

Quantitative changes : 

Percent of fringe lost - 13% -23% -66% 

Percent reduction in density -24% -20% - 16 

of submerged prop roots 

Percent change in root length -5% no change - 32% 

Total area of submerged root - 34% - 38% -74% 

surfaces 

Qualitative changes : 

Percent increase in the + 63% + 950% + 750% 

proportion of dead roots 

Percent increase in light + 46% + 46% + 164% 

transmission to the water 

surface 
30 

20 

10 

U 

T 

W 

U 

N 

0 

Channels - Oysters 

40- 

30 ,~ 

20 .s.. 

1 

10 

0 

Drainage streams - False Mussels 

50 -1 

40 

30- 

20 

10 

0 

A N F M A N F M A N F M A N F M A N FM 

1986 1987 1988 1989 1990 1991 

Monitoring date 

Figure 1 . Mean percent cover of major sessile animals . Among site means ± one 

standard error (n = 3 - 5 sites/point) . Open symbols = unoiled sites, 

filled symbols = oiled sites . Quarterly monitoring began in August 

1986, three months after the oil spill . Lines are broken where site 

locations were changed one year after monitoring began. Note that 

scales differ among panels . 

98 

Open Coast - Sessile Invertebrates 
Is Genetic Degradation of Mangroves a Consequence of Petroleum? 

Edward J. Klekowski, Jr. l and Jorge Corredor' 

Biology Department 

University of Massachusetts 

Amherst, Massachusetts 01003 USA 

z Department of Marine Sciences 

University of Puerto Rico 

P.O . Box 5000 

Mayagiiez, Puerto Rico 00681 

INTRODUCTION TO THE PROBLEM 

The detection of dispersed mutagens in ecosystems involves overcoming a number of 

obstacles : generally the chemical nature of the mutagen or mutagens is unknown; these 

unknowns are quite often in low concentration and may be episodic with reference to their 

presence in the environment; and finally, the mutagenic material may be restricted to, or 

more concentrated in, a specific portion of the environment (for example, in a marine 

environment the mutagens may be in the water or bound to organic material or clay 

micelles) . Because of these complexities the employment of a single assay protocol to screen 

ecosystems for dispersed mutagens runs a high risk of generating "false negatives," i. e. not 

detecting mutagenic activity when mutagens are present . Thus satisfactory screening of an 

ecosystem must be based upon diversity of assay protocols . 

Four general approaches appear feasible for mutagens. These four assays either 

concentrate mutagens from an ecosystem by physical or biological means or detect mutational 

damage in test organisms by the dispersed mutagens. The following list will illustrate these 

assays : 

(1) Sampling and concentrating a fraction of the environment (atmosphere, water, 

and soil) and assaying formutagenicity with a laboratory based assay (Pelon et 

al. 1977) ; 

(2) Introducing the mutagen assay organism into the 

environment for a period of tune and monitoring changes in mutation rate 

(Schairer et al . 1978) ; 

(3) Using indigenous bioconcentrators to accumulate material from the ecosystem 

and then testing extracts of these organisms with laboratory based mutagen 

assays (Parry et al. 1976 ; Barnes and Klekowski 1978) ; 

99 
(4) Measuring genetic damage in selected populations of organisms naturally 

occurring in the ecosystem, an in situ bioassay (Klekowski 1978). This 

communication will consider red mangrove (Rhizophora mangle) as an in situ 

bioassay organism. 

Mangrove-fringed coasts are a common sight along many tropical shores . In the 

Caribbean and the Gulf of Mexico the red mangrove, Rhizophora mangle, often forms large 

forests between the land and the sea. These arborescent flowering plants are one of the few 

tree species that has the necessary adaptations to grow in sea water. In addition, red 

mangroves possess reproductive traits that permit the easy detection of nuclear and 

cytoplasmic mutations in the field. Because of these reproductive characteristics, coastal 

mangrove forests may be assayed for genetic damage in the same way as colonies of bacteria 

or yeasts are screened for mutation (Lowenfeld and Klekowski 1992) . The difference 

between mangroves and microbes is one of scale ; mangroves are larger, have longer life 

cycles, and are exposed to environmental mutagens for greater periods of time (i . e. years 

rather than hours) (Klekowski et al. 1994 a, b, c). 

GENETIC ENDPOINTS 

An in situ mutagen bioassay is based upon the detection of genetic damage (mutation) 

in selected components of the genetic system of an indigenous bioassay species . 

Measurements of mutation may be based on a variety of genetic endpoints . In red mangrove 

two genetic endpoints are convenient to measure in the field: 

(1) A suite of approximately 300 nuclear gene loci that in some way control the 

presence of chlorophyll in the chloroplasts (Corredor et al. 1995 ; Klekowski 

1992) . 

(2) A variety of mutations of the plastid genome that result in chloroplasts that 

lack chlorophyll (Klekowski et al. 1994 a, b, c) . 

Nuclear Mutations 

The key features of red mangroves that allow for genetic screening are vivipary and 

frequent self-fertilization . Red mangrove is one of those rare flowering plant species with a 

sexual viviparous life cycle. In the majority of flowering plants, pollination and fertilization 

are followed by the development of an embryo that remains dormant within the seed while 

the seed matures within the ovary of the flower . Upon ovary (fruit) maturity the seeds are 

dispersed, germinate and the next generation seedling begins to grow . In viviparous plants a 

number of these post-fertilization stages are either omitted or modified. 

In red mangrove the embryo that develops after fertilization does not enter a period of 

dormancy, but rather continues to grow and develop within the ovary. A seed never 

develops . The ovary remains attached to the parental plant throughout the growth of the 

embryo. Eventually the embryo ruptures through the stigma end of the ovary and continues 

100 
growth, sometimes reaching a length of approximately 20 cm. During this period of 

viviparous growth the embryo obtains almost all of its nourishment and important metabolites 

from the maternal parent . Thus vivipary permits the survival and growth of metabolically 

defective mutant offspring genotypes. 

In addition to enhancing the survival of mutant offspring, vivipary results in the longterm (-6 months) retention of families of sibs attached to their maternal trees ; thus families 

of embryos may be scored for mutant traits while they are still attached to their maternal 

trees. Segregation ratios for mutant and wildtype embryo phenotypes can be readily 

determined; 3 :1 ratios for wildtype to mutant phenotypes indicate that the tree is a 

monohybrid and that self-fertilization occurred. 

In red mangroves the most prominent portion of the viviparous embryo is the green 

hypocotyl . Mutations which result in embryos unable to produce chlorophyll are easily 

detectable. These mutant embryos are albino or chlorophyll-deficient in appearance. If a 

tree is heterozygous for a chlorophyll-deficient allele (mutation), self-fertilization will result 

in a random pattern of green and albino viviparous embryos hanging from the tree . 

Consequently vivipary and frequent self-fertilization allow for the easy recognition of trees 

heterozygous for individual chlorophyll-deficient alleles (Klekowski and Godfrey 1989; 

Klekowski et al. 1994 a, b, c) . 

The nuclear-inherited chlorophyll-deficient genotype is due to a mutant allele at any one 

of a suite of nuclear genes that controls the synthesis or stabilization of chlorophyll or the 

development of a chloroplast. In flowering plants this suite contains approximately 300 

different nuclear genes (Klekowski 1992) ; chlorophyll-deficient mutations represent, 

therefore, a mutational endpoint that monitors genetic damage at 300 genes . Because of the 

number of genes screened, chlorophyll deficiency is a mutational endpoint that can be used 

successfully to screen relatively small populations (ca. 1,000 trees) (Klekowski et al. 1994b) . 

In natural populations two different manifestations of heterozygosity for chlorophylldeficiency may occur: 

(1) The mutant allele may have arisen in a previous generation and have been 

passed on to the zygote. In this case all of the cells of the tree are 

heterozygous for the genetic defect, and, consequently, recessive homozygous 

viviparous embryos together with wildtype viviparous embryos occur randomly 

on all branches of the tree ; 

(2) Mutations may also occur within the somatic cells of a growing mangrove 

tree ; such trees are chimeras . If the mutant cells give rise to apical or Hillary 

buds, there is some chance that these cell lineages may give rise to 

reproductive cells (pollen in the anthers and/or eggs in the ovary of the 

flower) . Trees with such post-zygotic mutations have a distinctive phenotype. 

One branch system will segregate for green and albino viviparous embryos 

while the rest of the tree forms only green viviparous embryos . Such 

chimeras are the hallmark of recent mutational events, i. e. events that have 

occurred after the tree was established . 

101 
Cytoplasmic Mutations 

All plant cells have their genetic material partitioned into three subcellular compartments : 

the nucleus, the mitochondria, and the plastids . In red mangrove it is comparatively easy to 

detect mutations of the genetic material of the plastid (plastid genome) . Although all plant 

cells have plastids, the visual recognition of plastid genome mutations is easiest in those 

tissues in which chloroplasts develop . Chloroplasts with defective genomes are not green but 

are white or yellow, depending upon the mutational lesion . During mitotic cell divisions the 

chloroplasts divide and are randomly sorted into the two daughter cells. Cells that contain 

mutant and wildtype chloroplasts are termed heteroplasmic; cells with either all mutant or all 

wildtype chloroplasts are homoplasmic. 

A homoplasmic cell containing only mutant chloroplasts has a white or yellow color in 

contrast to the surrounding green cells. Homoplasmic cells in the apical meristems (stem tips 

and axillary buds) may give rise to cell lineages in the leaves that have conspicuous and 

relatively predictable patterns (Klekowski 1988) . Plastid genome mutations occur as 

chimeras on trees, i. e. one branch system will have variegated leaves and the other branches 

of the tree will have nonvariegated green leaves . Plastid genome mutations are not usually 

transmitted sexually since the resulting offspring are inviable . A branch system of variegated 

leaves typically represents a single post-zygotic mutational event of the plastid genome. 

Population Analysis 

Screening red mangrove populations for an increased incidence of nuclear-based 

chlorophyll-deficient mutations is conceptually straight forward. One must simply screen 500 

to 1,000 trees that have each formed 10 or more viviparous embryos and determine the 

frequency of trees with green and albino embryos . The trees with green and albino embryos 

are usually heterozygous for a chlorophyll-deficient mutation. Of course actually screening a 

mangrove forest often requires some ecological ingenuity. One method is to survey the 

forest edge from a slow-moving, small boat and score and count trees . 

In situations where the incidence of somatic mutation has increased during the lifetimes 

of the mangroves, i. e. the trees are chimeras for either nuclear or plastid genome mutations, 

the frequency of mutational events is simply the frequency of branch systems exhibiting 

mutational changes (chlorophyll-deficient embryos or variegated leaves) . Each mutant 

branch system ultimately originates from a single mutational event. For comparative 

purposes between populations, one useful metric is simply the number of single-origin mutant 

branch systems per tree . 

CASE STUDY 

Petroleum Pollution in Puerto Rico 

The relationship between sediment hydrocarbon loads and mangrove albinism at sample 

sites along the southwestern coast of Puerto Rico was studied (Klekowski et al. 1994 b,c) . 

For each site sediment samples were analyzed for biogenic and petrogenic hydrocarbons and 

102 
the frequency of red mangrove trees heterozygous for chlorophyll-deficient mutations was 

determined. A positive correlation was found between the concentration of polycyclic 

aromatic hydrocarbons (PAH) and the frequency of nuclear mutations in the mangroves 

growing in the contaminated sediments (Klekowski et al. 1994 c) . Although controversy still 

exists regarding the occurrence of biogenic PAHs, consensus is that biosynthesis of such 

compounds is rare. On the other hand, petrogenic hydrocarbons exhibit a characteristically 

high PAH content. 

LIMITATIONS AND ADVANTAGES 

Limitations 

As in all bioassays, the key problems are false positives, i.e . increased mutation for 

reasons not related to environmental pollution, and false negatives, i. e. failure to respond to 

an environmental mutagen. An example of a false positive is already in the literature; the 

spontaneous mutation rate for San Salvador Island and Puerto Rico differs by a factor of two 

(Klekowski et al. 1994 b, c). This problem of geographic differences in spontaneous 

mutation rate is easily resolved by using control populations and establishing a dose response 

relationship between mutagen and mutation (e .g. Klekowski et al. 1994 b, c) . 

The false negative problem is more significant in most bioassays . In red mangroves one 

can speculate on a number of scenarios for false negatives . The sensitivity of mangroves to 

mutagens is dependent upon the ability of foreign chemicals (xenobiotics) to enter the xylem 

stream and be translocated to the apical meristems. It is only when the apical initials are 

mutated that mutant phenotypes will be manifested either in the embryos or in clear patterns 

in the leaves . 

Many xenobiotics must be modified by cellular metabolism before they are active 

mutagens, i. e. promutagen activation . The extent to which plant metabolisms can activate 

promutagens and to what degree this process mimics similar metabolism in mammals is an 

area of active research (Sandermann 1988 ; 1992 ; Higashi 1988 ; Plewa et al. 1988) . In this 

regard, the capacity of mangrove metabolism to activate different promutagens is unknown. 

Advantages 

The majority of human carcinogens have mutagenic activity . Probably the most 

significant attribute of the mangrove bioassay is that it screens for mutagens and thus may 

document the occurrence of pollutants that negatively impact on human health . Related to 

this point are the immediate socio/economic implications ; the bioassay documents the genetic 

effects of environmental mutagens on the indigenous biota of the contaminated environment 

at environmental concentrations and exposures . Thus the results cannot be dismissed as 

laboratory artifacts that only occur at artificially high doses or exposures . 

Finally, members of the genus Rhizophora are pan tropical . Thus although we have 

developed this bioassay for Caribbean populations of red mangrove, R. mangle, other species 

of the genus Rhizophora may also be potential bioassay organisms . The red mangrove 

103 
bioassay is inexpensive, is very low tech, and can be taught to technicians with only a 

rudimentary knowledge of plant biology . If other species of Rhizophora share similar genetic 

characteristics with the red mangrove (R. mangle) then the mangrove in situ environmental 

mutagen bioassay have broad utility in tropical coastal environments . 

ACKNOWLEDGMENTS 

We thank Libby Klekowski, Michael Hill, and Paul Godfrey for field assistance and 

Ronald Beckwith for greenhouse supervision. This work is a result of research sponsored by 

NOAA National Sea Grant College Program Office, Department of Commerce, under Grant 

Numbers R/ER-40-14 and R/PS-41-13 from the University of Puerto Rico Sea Grant 

Program and the Conservation and Research Foundation, New London, Connecticut. The 

U.S . Government is authorized to produce and distribute reprints for governmental purposes 

notwithstanding any copyright notation that may appear hereon. 

REFERENCES 

Barnes, W. and E.J . Klekowski, Jr . 1978 . Testing the environment for dispersed mutagens : 

Use of plant bioconcentrators coupled with microbial mutagen assays . Environ. 

Health Perspect. 27: 61-67 . 

Corredor, J .E., J.M . Morell, E.J . Klekowski, Jr . and R. Lowenfeld. 1995 . Mangrove 

genetics III . Most albinos may not be caused by mutations directly affecting 

photosynthetic pigments. Int. J. Plant Sci. 156 : 55-60 . 

Higashi, K. 1988 . Metabolic activation of environmental chemicals by microsomal enzymes 

of higher plants . Mutation Res. 197: 273-288. 

Lowenfeld, R. and E.J . Klekowski . 1992 . Mangrove genetics . I . Mating systems and 

mutation rates in Rhizophora mangle in Florida and San Salvador Island, Bahamas. 

Int. J. Plant Sci. 13 : 394-399. 

Klekowski, Jr ., E.J . 1978 . Detection of mutational damage in fern populations: An in situ 

bioassay for mutagens in aquatic ecosystems. Vol. 5, pp . 79-98. In, Hollaender, A., 

de Serres, F. (eds.) .New York: Plenum Press. 

Klekowski, Jr., E.J . 1988 . Mutation, developmental selection, and plant evolution. 

Columbia University Press, New York. 

Klekowski, Jr., E.J . 1992. Mutation rates in diploid annuals : are they immutable? Int. J. 

Plant Sci. 153 : 462-465 . 

Klekowski, Jr., E.J . and P.J . Godfrey . 1989 . Ageing and mutation in plants . Nature 340: 

389-391 . 

104 
Klekowski, Jr ., E.J ., R. Lowenfeld and P.K . Hepler. 1994a. Mangrove genetics II . 

Outcrossing and lower spontaneous mutation rates in Puerto Rican Rhizophora . Int. J. 

Plant. Sci . 155 : 373-381 . 

Klekowski, Jr., E. J. , J. E. Corredor, J. M. Morell and C. A. Del Castillo . 1994b. Petroleum 

pollution and mutation in mangroves. Mar. Pollut . Bull. 28 : 166-169. 

Klekowski, Jr ., E.J ., J.E . Corredor, R. Lowenfeld, E.H . Klekowski and J.M. Morell. 

1994c. Using mangroves to screen for mutagens in tropical marine environments. 

Mar. Pollut. Bull. 28: 346-350 . 

Parry, J.M., D.J . Tweats and M.A .J . Al-Mossawi. 1976 . Monitoring the marine 

environment for mutagens . Nature 264 : 538-. 

Pelon, W., B.F . Whitman and T.W. Beasley . 1977 . Reversion of histidine-dependent 

mutant strains of Salmonella typhimurium by Mississippi River water samples . 

Environ. Science Technol. 11 : 619-623 . 

Plewa, M. A., E.D . Wagner and J .M. Gentile . 1988 . The plant cell/microbe coincubation 

assay for the analysis of plant-activated promutagens. Mutation Res. 197: 207-219. 

Sandermann, H ., Jr. 1988 . Mutagenic activation of xenobioticsby plant enzymes . Mutation 

Res. 197 : 183-194 . 

Sandermann, H ., Jr. 1992 . Plant metabolism of xenobiotics. TIBS 17 : 82-84. 

Schairer, L. A., J. Van't Hof, C.G. Hayes, R.M. Burton and F.J . de Serres . 1978 . 

Exploratory monitoring of air pollutants for mutagenicity with the Tradescantia 

stamen hair system. Environ . Health Perspect. 27 : 51-60. 

105 
Session II . Remediation Techniques: Reviews and Current Research 

Chair: Dr. Pasquale Roscigno 

Presentation Author / Affiliation 

Bioremediation : Statistical and Analytical 

Needs 

Toxicology Research: An Update on EPA 

Methods for the Evaluation of Oil Spill 

Dispersants 

Remediation Techniques : an Overview 

Dr. W. James Catallo 

Louisiana State University 

Dr. Carol B . Daniels 

Environmental Research Laboratory 

U.S . Environmental Protection Agency 

Dr . William A. Kucharski 

Louisiana Department of Environmental 

Quality 

Dr. Paul Kostecki 

University of Massachusetts 

Responding to Oil Spills in Marshes: Ms. Rebecca Z. Hoff 

The Fine Line Between Help and Hindrance NOAA Hazardous Materials Response 

and Assessment Division 

107 
Bioremediation : Statistical and Analytical Needs 

W. James Catallo 

Laboratory for Ecological Chemistry and Toxicology 

SVM, Louisiana State University 

Baton Rouge, LA 70803 

INTRODUCTION 

The techniques employed for biodeterioration and "bioremediation" studies typically 

are diverse and technically complicated (Blumer 1975 ; Catallo and Gambrell 1995 ; Grady 

1989 ; Smith et al. 1978; US Environmental Protection Agency 1979; US Environmental 

Protection Agency 1993a; Wolfe 1977) . Laboratory and field work addressing the effects of 

biological processes and human manipulations on chemical fates in environmental systems 

rely on procedures from microbiology, analytical chemistry, soil science, aquatic chemistry, 

and multivariate statistics . While there is no doubt that naturally occurring micro- and 

macro- organisms can degrade or transform organic chemicals under a range of conditions 

(Catallo 1991 ; Grady 1989; US Environmental Protection Agency 1979; Wolfe 1977), the 

principle appeal of bioremediation techniques is the claim that pollutant degradation rates are 

significantly enhanced by biotreatment approaches, and that the toxicity of chemical mixtures 

is reduced concomitantly (Catallo 1991) . This claim has been applied not only to simple 

mixtures of labile hydrocarbons (e .g ., n-alkanes in jet fuels), but to virtually every kind of 

pollutant chemical class and mixture of concern including chlorinated pesticides, petroleum 

and petrochemicals, chlorinated solvents, halogenated biphenyls and their congeners, 

heterocycles, and polynuclear aromatic hydrocarbons in soils, sediments, surface water, and 

ground water (Grady 1989 ; Hazardous Materials Control Research Institute 1989 ; US 

Environmental Protection Agency 1993 a) . 

Critical evaluation of the analytical and statistical methods of many bioremediation 

studies suggest otherwise: as a result of a) inherent complexity and variability of 

environmental systems, b) the extreme complexity of many pollutant mixtures of concern 

and, c) important (and sometimes fatal) experimental method limitations, the effects of 

biotreatment on pollutant degradation rates and toxicity frequently cannot be decided with 

confidence, even in cases where large differences are reported (Bragg et al. 1994 ; Catallo 

1991 ; US Environmental Protection Agency 1993 b). In general, the method limitations of 

primary concern are those relating to a) experimental design and statistical analysis of 

laboratory and field data, b) the analytical chemistry of environmental mixtures, c) 

recognition of method limitations, propagation of errors, and sources of bias and, d) rules of 

deduction for developing conclusions from frequently incomplete experimental data (Bain and 

Engelhardt 1992 ; Davis 1986 ; Poole and Poole 1991 ; Snedecor and Cochran 1980) . 

Recent reviews of the use of basic statistical models and techniques by environmental 

scientists have provided noteworthy results. For instance, a critical analysis of 151 papers in 

seven prestigious journals showed that only 12% of the papers were free from basic errors in 

109 
design, selection of tests, execution of analysis, and interpretation of results (Underwood 

1981) . Similarly, there has been consistent criticism of the ways in which the handling, 

extraction, and analysis of chemical and microbiological samples have been performed as 

well as increasing dissatisfaction with interpretational problems caused by inappropriate 

sampling designs (Harmsen 1986 ; Kirchmer 1983 ; Taylor 1986; Thomas 1994) . Some 

workers have concluded that estuarine research has stopped progressing, largely as a result of 

these problems (Schoer and Duwe 1986) . Related developments have included "reevaluation" of long-term biological data sets in light of new data on the effects of extreme 

environmental variability which was insufficiently addressed by sampling designs (Cullinane 

and Whelan 1983 ; Steimle and Caracciolo-Ward 1989) . 

Although it would be easy to find a large complement of statistical and analytical 

flaws in recent bioremediation papers (most of which are found in venues not subject to 

rigorous peer review, e .g ., Catallo 1991), it is doubtful that this would have any positive 

effect on the way these studies are performed and evaluated . Rather, it seems more 

productive simply to indicate several of the major challenges that are involved in the design 

and implementation of a statistically robust and analytically sound bioremediation study. 

This will include a brief overview of experimental design and general systems theory from 

the chemometric standpoint, a discussion of the assumptions and limitations of prominent 

analytical techniques used widely in bioremediation experiments, and consideration of the 

effects of error propagation, bias, poor replication, and insufficient sample size on the 

conclusions of bioremediation studies . Although these topics will be segregated where 

possible, statistical principles apply not only to design and analysis of experimental systems, 

but also to the routine operation and data handling associated with extraction and 

instrumental analysis of chemicals from soils, water, or tissues. As a result, statistical and 

analytical procedures are integral parts of the deductive process in bioremediation 

experiments, and the effects of their cumulative assumptions and errors can have significant 

impacts on what may be concluded, even when things appear obvious or straightforward . 

What follows is a series of concepts that hopefully will serve as heuristic tools for the design 

and evaluation of future work. In keeping with the format of these proceedings, statistical 

and analytical postulates given below are stated rather than proved, with rigorous handling to 

be found in the references (Aldrich and Nelson 1984 ; Bain and Engelhardt 1992; Blackburn 

1989 ; Davis 1986 ; Deming and Morgan 1987 ; Edwards and Hamson 1989 ; Harmsen 1986; 

Kirchmer 1983 ; Lande and Arnold 1983; Perko 1991 ; Ruhla 1992 ; Snedecor and Cochran 

1980; Taylor 1986; Thomas 1994 ; Underwood 1981) . 

EXPERIMENTAL DESIGN 

A fundamental difference between science and "common sense" is that scientific 

conclusions rely on controlled experimentation, replication of results, and statistical methods 

of inference . Statistical inference is governed by mathematically consistent rules and 

procedures for tracking the sources and flows of error in experimental systems and for 

determining differences (with specified levels of uncertainty) between groups of observations 

being compared (Bain and Engelhardt 1992 ; Davis 1986; Perko 1991) . In general, these 

110 
mathematical rules apply to specific experimental configurations and data types (Aldrich and 

Nelson 1984) and are invalid when used outside their domain. The most widely used system 

is the general linear models family of techniques, including ordinary least squares regression, 

probit, and logit (Aldrich and Nelson 1984) . These models are invalid if used to compare 

classes of data not conforming to the so-called Gauss-Markov Assumptions (Aldrich and 

Nelson 1984 ; Bain and Engelhardt 1992). Briefly, these assumptions require that a) 

independent variables not be collinear, b) no superfluous independent variables are 

incorporated in the analysis, but all relevant variables are included (see below) and c) 

random error is not correlated with any independent variables and has a mean of zero. It is 

no surprise that experimental biology generally, and bioremediation specifically, deals with 

processes that are influenced by a large number of factors ( many of which are nonlinear, 

highly correlated and/or unknown) and variability of important properties tends to be large 

and uneven (Aldrich and Nelson 1984; Davis 1986 ; Lande and Arnold 1983 ; Ruhla 1992, 

Thomas 1994) . Application of linear statistical models to these studies can be problematic, 

particularly when input and output variables (below) can be complex and numerous . 

An essential first step to valid statistical inference is to develop a model of the system 

under consideration (Deming and Morgan 1987; Edwards and Hamson 1989) . As shown in 

Fig 1 . , the experimental system is a group of interacting elements behaving as a unit. 

Among other things, it is necessary to characterize the system at least conceptually, and 

estimate the character and likely extent of variability within the experimental units (study 

sites, analytical configurations) . A design can then be made that allows for robust and 

powerful statistical treatment of data. 

Although there are inherent or self-evident characteristics that aid system 

identification and delimitation (e .g ., open water vs . wetlands vs . uplands), system boundaries 

tend to be chosen more or less at will. Ideally, the experimental system should be 

approximately homogenous in its properties, and its dimensions should be large enough so 

that important processes are not altered by the boundaries (e.g., as when surface area to 

volume ratios of microorganisms decrease to such an extent that adsorption phenomena at the 

surface of the system are significantly relative to adsorption on sediments) (Blackburn 1989) 

or significantly perturbed by experimental conditions (e .g ., field workers stomping around 

marsh plots, see Bender et al. 1981) . Input variables impinging on the system are called 

"factors" if they exert a real effect on the system . Typical input factors in bioremediation 

might include experimental treatments such as use of nutrients, bacteria, and tilling as well as 

natural physicochemical processes affecting the recovery of analyte chemicals being treated 

(e .g ., volatilization, plant root processes, sediment properties, photochemical oxidation, 

leaching, complexation or acid-base reactions followed by phase transfer) (Parris 1980; 

Ponnamperumma 1972 ; Rapaport and Eisenreich 1984 ; Smith et al . 1977) . In each setting, 

these input factors can be known , unknown, controlled (i .e ., limited experimentally by one 

value or a predetermined range) or uncontrolled . It is necessary to know all factors of 

importance to processes under study, and account for as many as possible in the experimental 

design . 

Similarly, the system outputs (measurable responses to inputs) can be known, 

unknown, important or unimportant . The importance of individual outputs frequently 

depends on the kind of problem being addressed. For example, flavinoid derivatives 

111 
generated in the brewing of beer may be significant in a chemical sense, but not of concern 

to brew masters who assay for taste and color . This output would be considered known but 

unimportant. If, however, these compounds caused allergic reactions in beer drinkers, this 

output becomes known and important . Clearly, it is important to fully realize the set of 

outputs from experimental systems so that they can be prioritized with respect to importance, 

and appropriate measurement techniques can be deployed . Another important type of output 

is called a feedback: a system output that influences the system as an output (e .g ., 

accumulation of enzymatic products that inhibit further enzyme activity) . Feedbacks are 

widespread control elements in environmental and biological systems, and tend to give rise to 

threshold and nonlinear behavior in the system . 

Experimental design of both laboratory and field bioremediation experiments should 

account for important input and output variables through controls and replication . As shown 

in Fig 2, mistakes, omissions, or oversimplifications can have a range of consequences, from 

virtually benign to disastrous . For example, if important input variables are accurately 

identified, and insignificant variables are discounted, then the desirable results in blocks A 

and D can be achieved (Fig . 2) . If an input variable is incorrectly identified as true and 

important (block C), the experimental data set can become unnecessarily large and labor 

intensive, but this mistake can wash out of a correctly executed study . The failure to identify 

a true and important input variable (block B) can have negative consequences, ranging from 

loss of statistical power to virtually complete vitiation of the worth of the results . Extremes 

of this problem occur readily in field work, but also can be found in laboratory experiments, 

e .g ., when adequate controls are not established . 

Under-specification of output variables can have a range of consequences (Fig . 3) . 

As with input factors, accurate and complete specifications of responses can give rise to 

results that are powerful and elegant (i .e ., shaved by Occam's Razor, blocks A and D) . An 

erroneous claim that a response is true and important (block C) may cause no problems, 

because analysis of output data frequently will show no significant relationships between an 

unimportant response and the input factors . But, underspecification of true responses can 

have very unfortunate consequences, as when drugs designed for specific purposes have 

unforeseen, toxic side effects . Another example would be remediation techniques that give 

rise to toxic materials of high mobility that escape the treatment system unmonitored (more 

on this below, see Catallo and Gambrell 1995 ; Catallo 1993 ; Corke et al. 1979 ; Grady 1989 ; 

Pieper et al. 1992). 

A CASE STUDY 

Consideration of the general material above suggests some elements that should be 

looked for when designing a bioremediation study or evaluating the results and conclusions of 

completed work. Primary issues include whether the appropriate input and output variables 

have been identified, measured, and controlled and whether sources of bias have been 

rigorously prosecuted in the design. For example, consider an experiment recently 

conducted in my laboratory on the effects of biological treatment on benzo(flquinoline 

(I ., below) in estuarine water. 

112 
I . Estuarine water was spiked with 20 ug/g of benzo(f)quinoline in sealed glass flasks, 

followed by perturbation with three controlled inputs (microbial inocula, inorganic trace 

nutrients, oxygenation) . The output variable monitored was the concentration of 

benzo(f)quinoline, as determined using solvent extraction followed by GC and GC-MS. 

Several identical treatment chambers (replicates) and an equal number of controls (sterile 

estuarine water receiving benzo(f)quinoline, oxygen and nutrients) were established . During 

the experiment, precautions were taken against competing processes (volatilization, 

photochemical modification) and the analytical approach was "tight " (good recovery, 

acceptably low systemic error) . After some weeks it was found that the magnitude of the 

output variable (benzo(flquinoline concentration) of the treatments decreased in time relative 

to little decrease in the controls (Fig . 4A). It was concluded that the addition of the 

microbes promoted removal of the benzo(f)quinoline relative to sterile controls . Fortunately, 

data from other experiments suggested that this system was under-controlled in an important 

sense: passive adsorption of benzo(f)quinoline to microbial cells without degradation could 

have occurred thereby limited recoveries so as to look like removal from the system. 

Unchecked, this case of unconscious bias could have resulted in wasted time and effort in a 

pilot or field experiment. In order to determine causality in this system, it was necessary to 

re-design the experiment: the input variable combinations were permuted vs. appropriate 

controls with replicates, and "killed" biomass controls were added . Hence, every nontrivial 

treatment combination was tested vs . controls, including a set of controls obtaining dead 

biomass to examine the effect of non-metabolic biosorption on time course recovery of the 

analyte . As shown in Fig. 413, time-dependent biosorption was in fact very significant to 

benzo(f)quinoline recovery : as the least squares regression lines and 95% confidence 

intervals for control, killed control, and estuarine microbes show, passive biosorption and 

systematic analytical error had the effect of looking like degradation in the killed controls . 

In fact, the confidence intervals showed that only the last few time points in the live microbe 

treatments were clearly distinguishable from the killed control function . Luckily, the 

expanded design contained the adequate controls, and this indicated that product analysis also 

should be incorporated at each time point. This allowed for a sound conclusion to be 

reached: benzo(f)quinoline is degraded slowly by estuarine microflora to an epoxide product 

(II ., below) that is stable for extended periods, mobile, and probably mutagenic (Catallo and 

Gambrell 1995) . This was confirmed using data from pathway studies using deuterated 

benzo(f)quinoline synthesized in this laboratory . A competing process is quasi-reversible or 

irreversible sorption of the analyte to organic matrices (colloids, micelles, cells) . Further 

degradation of the epoxide can occur via microbial and chemical action (Catallo and 

Gambrell 1995) . These processes are very slow, and residual benzo(f)quinoline and its 

transformation products can be detected in water and sediments for months to many years, 

depending on conditions . One wonders how often processes such as sorption to surfaces and 

biogenic matter (e .g ., large amounts of microbial biomass that are dumped into field sites to 

be bioremediated) limit recoveries in this way and pass for biodegradation of the analyte. 

It can be seen that demonstrating causality and generating accurate interpretations 

even in this simple system involved a large amount of multidisciplinary work (microbiology, 

synthetic organic chemistry, analytical chemistry, statistics) . The addition of other variables 

(e .g ., sediments, redox potentials, plants) and compounds (complex mixtures such as 

113 
petroleum) to these studies adds to the complexity and labor needed to provide defensible 

results . It is important to note that the error of each procedure and analytical technique in 

these complex experimental systems is roughly multiplicitive . Hence, a five step sampling, 

extraction, analytical, data reduction hierarchy involving 5 % experimental error at each step 

(an almost unbelievably low level of error in real settings) has a total experimental error as 

high as (0.95)5 or about 23% . The random errors at each step also introduce further 

increases in absolute error, especially if there is inadequate replication . This is another 

major reason why extensive replication and adequate controls are needed in experimental 

biology, and why results from extremely precise and accurate analyses (e .g ., quantitative 

chemical analysis) can frequently provide very little help in resolving subtle effects between 

treatments : total error running through complex experimental systems can be so large as to 

"swamp" the deductive power of very precise analyses . Replication adds power to 

procedures that may have large experimental errors, and can reduce significantly the random 

error. When field experiments are considered, the ability to control or even anticipate 

important input variables becomes limited. The disappearance of target chemicals frequently 

results from factors not related to microbial metabolism, and large variabilities within 

experimental units can make things look conclusive (Bragg et al. 1994; Catallo 1991 ; 

Cullinane and Whelan 1983 ; Schoer and Duwe 1986; Smith et al. 1977 ; Steimle and 

Caracciolo-Ward 1989; Taylor 1986 ; US Environmental Protection Agency 1993 b) . The 

notes on chemical analyses given below suggest that total analytical error alone can limit 

interpretations to order-of-magnitude changes . The best way to compensate for this is to 

have a large enough set of random samples and replicates to overcome the effect of natural 

variances, and to measure explicitly all known significant input variables . The addition of 

exhaustive controls also is critical to the success of field approaches . The entire enterprise 

usually requires multivariate statistical designs and analyses (e .g ., structural equation 

modeling) (Davis 1986 ; Lande and Arnold 1983). 

Consideration of the laboratory example above also illustrates some major differences 

between laboratory and field studies . In conclusive laboratory work, the system is well 

defined (i .e ., true replication is possible), the data have homogenous variances or nearly so, 

and the input factors are known and are largely controllable . Under these conditions, a well 

implemented experimental approach (i .e ., with adequate sample size, no bias, requisite true 

controls, and true replication) can determine causality, usually after a great deal of work . 

Conversely, field systems frequently are not well delimited, there are high degrees of internal 

variability, true replication frequently is problematic, and input-output factor sets are 

complex, not well known and/or "lurking", and largely uncontrollable . Hence, results from 

field work generally end up being correlative. The confidence that can be ascribed to 

correlations in field data is greatly influenced by experimental design and analytical protocols 

as well as the definitiveness of the corresponding laboratory work. Also involved is the 

assumption (hardly ever examined) that the results of well constructed laboratory studies 

(microcosms) bare some straightforward relationships to analogous experiments in closely 

related field settings (macrocosm) ; 

P(A)m a k P(A')M 

114 
where the probability P of some complex event(s) A measured in the microcosm m is 

proportional to the probability of the corresponding event(s) A' in the macrocosm M 

multiplied by some weighting k. We are far from measuring these weighting terms 

systematically, or testing this mapping with respect to complex sets of variables . In general, 

we hope that the true impact of k is minimal or at least predictable. 

Without any abstraction, it seems clear that determining the efficiency of 

bioremediation in field settings (hazardous waste sites, oil spills) is a task requiring adequate 

statistical design, multidisciplinary expertise, and analytical savvy . The experimental system 

must be known, the winnowing of input and output variable sets to a manageable monitoring 

scheme must be accurate and unbiased, and the field experiments must be well controlled, 

highly replicated, randomly sampled, and analyzed with accuracy . It follows that the results 

of field evaluation projects with a small number of experimental units (e.g., 1 - 3 plots), few 

or no true replicates, multiple uncontrolled inputs and unmonitored outputs will be difficult to 

assess with any power. In fact, a large proportion of bioremediation pilot projects under the 

EPA Superfund Innovative Technologies Evaluation (SITE) program suffer from these kinds 

of limitations [11] . Other "showcases" are similarly limited, with adequate controls lacking 

or altered during the experiments, sparse replication, and QA on site selection, analyses, and 

sampling difficult to evaluate (Bragg et al. 1994) . 

EXTRACTION AND INSTRUMENTAL ALAYSIS OF CHEMICALS 

An area of continuing difficulty in the interpretation of environmental data is 

analytical chemistry in general, and the sciences of chromatography and mass spectrometry 

in particular (Harmsen 1986 ; Kirchmer 1983 ; Poole and Poole 1991 ; Thomas 1994) . In the 

last two decades, a revolution in separation technologies and microelectronics has made 

sensitive analytical instrumentation and reasonably friendly data handling available to most 

laboratories . Of particular interest here is the identification and "quantification" of 

semivolatile organic chemicals using some form of internally standardized chromatography 

followed by mass spectrometry . The industry standard is capillary column gas 

chromatography (GC) followed by mass spectrometry (usually quadrupole "mass selective 

detection") or GC-MS. Chromatography with other detection systems such as the flame 

ionization or electron capture detection are two dimensional techniques : for each time point 

in the separation (x), there is a detector response value (y) that is proportional to compound 

concentration. Compounds in environmental matrices can be tentatively identified using 

these 2-D techniques, but further characterization is needed for conclusive work because of 

problems such as co-elution (particularly in complex environmental or biological mixtures). 

Mass spectrometry adds a third dimension to 2-D GC: for each x,y pair, a mass spectrum 

(z) is acquired . The mass spectrum can provide definitive information on identity of the 

analyte even in cases of co-elution. Hence, conclusive demonstration of the presence of a 

chemical can result without further analysis . Also, integration and comparison of mass 

spectral intensities from analytes and known standard curves can allow for semiquantitative 

or quantitative analyses to be performed (Table 1) . 

115 
A popular, and frequently mandatory, approach to documenting the presence and 

concentrations of organic chemicals is EPA Method 625 CAP and a modifications/extensions 

thereof. In bioremediation studies, these methods frequently are used to document the 

"removal" of target analytes (e .g ., PAHs given in the EPA Toxic Substances List) using 

selective ion monitoring (SIM) . SIM approaches are appropriate for monitoring low levels of 

selected analytes and providing macro-driven data analysis (e .g ., so-called "fingerprinting" 

approaches), but information falling outside SIM windows is irrevocably lost (Fig. 5) . The 

power of GC-MS for qualitative and semi-quantitative identification of unknown compounds 

in mixtures has promoted a tendency among bioremediation workers to spuriously regard 

these methods as conclusive and accurate for detecting differences of a few percent in 

complex samples. In addition to many fallacies promoted by this widespread "black box" 

attitude, there are many systemic limitations to GC-MS techniques as commonly deployed 

that are germane to the valid interpretation of bioremediation data: 

1) The EPA 625 CAP and related methods are semiquantitative at best with 

respect to many selected ions of interest . Quantitative analysis (Table 1) 

would require a) a broad series of internal and surrogate standards many of 

which are not commercially available and must be synthesized, b) isotopic 

dilution approaches for each analyte to be quantitated, c) double blind 

intercalibration, and d) extremely well-maintained and monitored instrumental 

conditions . In cases where moderate (> six/day) or large sample loads are 

processed, this level of effort and quality assurance simply is not sustainable in 

most commercial and academic settings . Indeed, the EPA Method 625 CLP 

document states : "These extraction and preparation procedures were developed 

for rapid and safe handling. . . of hazardous wastes . The design . . . does not 

stress efficient recoveries or low levels of quantitation . Rather, procedures 

were designed to screen, at moderate recovery and sufficient sensitivity, a 

broad spectrum of organic chemicals. " In other words, this disclaimer 

suggests that semi-quantitation may be the best that can be expected for realworld analysis of selected compounds on the EPA Toxic Substances List (for 

which these methods were developed to detect) with virtually everything else 

missed. It is useful to consider what "order-of-magnitude" means with respect 

to propagation of errors (above) and the facile conclusion that biodegradation 

has occurred in samples showing small differences. Although trained chemists 

with adequate leisure, support, and facilities can quantitate organic chemicals 

in defined systems, the effort required is, quite simply, enormous and unlikely 

to be sustained in most settings . In this regard, it is noteworthy that numerous 

lawsuits have been filed against EPA certified contract labs for corner-cutting 

on the execution of Method 625 CLP. 

2) The selection of target analytes to be monitored at bioremediation sites usually 

is driven by regulatory requirements, not by data on the presence, 

environmental significance, and toxicity compounds. In other words, these 

methods "see what they look for, and look for what they can see ." For 

116 
instance, in bioremediation of creosote and heavy asphaltic waste oils, the 

concentrations of PAHs e .g ., naphthalene, anthracene/phenanthrene, and 

pyrene (on the List) are monitored routinely and changes in their measured 

concentrations are used as evidence of the effectiveness of the remediation 

effort . These compounds and their known degradation products are not 

mutagenic or carcinogenic in bacterial or mammalian assays [6] . Heterocyclic 

congeners in these mixtures (i .e ., quinoline, acridine/ benzo(c)quinoline, and 

azapyrene) are mutagens/carcinogens and are transformed to mobile 

oxygenated products that probably are biologically deleterious (Catallo and 

Gambrell 1995 ; Rostad et al. 1984) . But these hardly ever are included in 

analytical monitoring during remediation of creosote because they are not on 

the List. (Another reason is that these heterocycles are notoriously difficult to 

biotreat. More than one site manager has told the author "we don't need any 

more problems ." This meant that unexamined outputs, such as the escape of 

undegraded, unregulated toxic chemicals from the site had no legal 

significance and therefore could be regarded as nonexistent ipso facto . The 

equation of unexamined outputs with unimportant ones on this basis is a fallacy 

that impedes true R&D as aggressively as it does mechanistic understanding, 

cf. ref. Grady 1989) . 

3) Potentially very significant transformation products of the target analytes in 

bioremediation studies are not examined. Hence, the modification of 

benzo(a)pyrene (BaP) to a phenol or diol would be interpreted as "removal" of 

BaP because the oxygenated products have different chromatographic and mass 

spectrometric properties (i .e ., they fall outside the mandated SIM window) . 

But the removal of BaP coincided with the generation of a mobile and 

available mutagen. As above with the undegraded heterocyclyes, this 

unidentified, uncontrolled output from the system could have both regulatory 

and toxicological significance . 

While these limitations clearly need to be addressed (i .e ., new protocols need to be 

developed for analysis of compounds not on the Toxic Substances List, transformation 

pathways need to be documented and evaluated, and sites to be delisted should be detoxified 

as well as "cleaned up" from a regulatory standpoint) they do not in themselves preclude a 

good field bioremediation study from being performed. With attention to the experimental 

design features and interpretational limitations discussed above, semi-quantitative analyses of 

complex environmental mixtures can provide very compelling evidence in support of 

remediation. The addition of full scan analyses of each extract subjected to SIM analysis can 

add valuable insight to processes of concern, as can multi-tier toxicity evaluation over the 

course of the treatment. What is needed beforehand is adequate, unbiased design and explicit 

recognition of method strengths and limitations . 

117 
CONCLUSIONS 

As suggested above, the importance of several design and analytical elements of 

experiments cannot be minimized. The work of Huff (Huff) provides an accessible set of 

touchstones for evaluating scientific claims that are applicable to the subjects of concern 

here. When confronted with research designs or conclusions in bioremediation work, the 

following grid of questioning is called for: 

1 . "Who says so?" When this is asked (even by editors), a typical response is to 

produce a list of publications . The point, however, is not to judge data by 

reputations, but the other way around . It is always appropriate to look for 

conscious bias (e.g., the intentional citing of controls and treatments that are 

most likely to give anticipated results, the selection of chemical or statistical 

analyses that miss or obscure important limitations of the approach, attempts to 

over interpret marginal results, or under value the limitations of techniques) . 

Conflicting interests (business affiliations), institutional pressures (agency 

deadlines and funding requirements), and other concerns (i .e ., rushing work in 

order to pass tenure review, gain a promotion, or limit a fine or damage 

settlement) also can cause bias, and should be examined where possible . It is 

equally important to account for unconscious bias (e.g ., under specification of 

the input and output variables ; under controlling experiments, other conceptual 

gaps) . Accountability (rather than deniability) should be stressed. This means 

that system models, site selections, experimental and analytical configurations, 

raw data, assumptions, error estimates, and statistical approaches should be 

available and made part of the deliverables provided to the funding 

organization . 

2. "How does he know?" Is the sample large enough to permit a conclusion, is 

the system specified adequately and correctly, are there adequate true 

replications, what real bearing does previous work have on current claims 

(e.g., are past mistakes or shortcomings recognized and rectified in current 

work)? Does the design and implementation of the study clearly support 

claims, or is there unwarranted subjectivity in the conclusions? 

3 . "What's missing?" Are controls adequate and appropriate, is there true 

replication, are raw numbers presented, or only "crunched" values, do we 

have access to information on the original work, the sites, and detailed 

descriptions of operating conditions, has error been addressed specifically and 

can it be found stated in plain form? 

4 . "Did somebody change the subject?" Confusing correlation with causality, or 

changing the statement "x changes with y" to "x changes because of y" ; under 

valuing the importance of variability, competing processes, and systemic error . 

118 
After this gauntlet has been run, detailed evaluation of the effectiveness of a 

bioremediation technology may begin. As rude and invasive as this approach may seem, it is 

an integral part of the critical scientific method and should be welcomed rather than shunned . 

In all critical analysis, arguments ad hominem (to the man), ad verecundiam (from authority), 

ad ignorantium (from ignorance) and ad baculum (from threat) are discounted immediately as 

fallacious and flawed in form. Only the data may speak through an argument ad judicium: a 

grid of unbiased statistics and logical rules of deduction and inference . To identify scientific 

flaws, or huge bodies of flaws (Underwood 1981) is no attack (i .e ., ad hominem), it is 

among the most constructive things critical people can do for one another and their 

institutions. Even in the emerging age of forced "tech transfer" and mandatory "industry 

partnerships", the only truly lethal mistake for researchers is international fraud . Objectivity 

is safeguarded when scientists open their approaches to dispassionate, disinterested critique . 

Once done, even experiments that are highly flawed methodologically can be found to 

contain useful information. While it is best to submit experimental designs to statisticians for 

critique before initiating work, statisticians also can perform triage on finished studies in 

order to extract valid, if not very powerful, interpretations . Other insights can be gained on 

appropriate ways to compare past results, or those from other studies, to issues under 

investigations . When the mainstream of environmental scientists, managers, and regulators 

(Particularly those interested in bioremediation) remember this, much productive work is 

likely to result. 

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119 
Catallo, W.J . 1991 . Use of indigenous and adapted microbial assemblages in the removal of 

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PP 

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intermediates of in the microbial transformation of chloranilines to chlorinated 

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Raton, FL. 277 pp. 

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120 
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121 
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122 
Table 1 . 

Working Definitions of Selected Terms 

Bias : Conscious or unconscious deviations from randomness in design (selection of 

experimental groups, locations, sampling patterns, etc .) so that certain outcomes are favored 

or enhanced in the data set. Introduction of a "tilt" to data through unsound design or 

execution. 

Calibration Curves: Curves of compound concentration vs. detector response constructed 

using known standards prior to sample analyses . The slopes of these curves correspond to a 

number of factors including detector response factor, type of integration, instrument tune . 

Integrals of analytes in samples are referenced to these curves, and concentrations are 

determined accordingly . 

Internal Standard: A compound or series of compounds added in known amounts to finished 

extracts prior to analysis by chromatography or GC-MS. These standards are used to correct 

for sample loss in the analytical system (in the injection port, on the column, or at the 

detector) . 

Locality : A property of biased data in which values collected and statistical results derived 

from them are valid only for the limited area sampled. 

n: Number of observations in the experimental population . 

Nonlocality : Property of unbiased design in which sufficient random data have been collected 

so that statistics generated are good estimators of population values for the whole system. 

Power: Refers to the ability of a statistical procedure to correctly reject false hypotheses, 

such as spurious difference between experimental treatments . In subjects of concern here, 

power can be increased by decreasing system variability and/or increasing sample sizes . 

Psuedoreplicate : Multiple samples taken from an experimental system, each of which are 

treated (erroneously) as separate observations from different populations. e .g., two tanks 

used for biotreatment of compound R. One receives fertilizer, the other does not (control) . 

At intervals, three samples are drawn from each tank, and are analyzed . The three values 

from each tank are then averaged and compared . These are pseudo-replicates (see 

"replicate") if used in statistical comparisons as "n" values . In order to be true replicates, 

three tanks would be necessary each for control and treatments (six total) . 

123 
Table 1 (continued) 

Quantitative : Refers to analytical procedures having the ability to discriminate between 

chemical concentrations differing by <25% . These analyses typically feature calibration 

curves of five points or higher, use of large numbers (e.g., > 12) of internal and surrogate 

standards, and auxillary procedures and measurements including intercalibration, 

determination of time-dependence of surrogate recoveries, and double-blind quality 

assurance. 

Replicate : Single samples taken from multiple experimental systems under tha same 

conditions (i .e ., treatments) . In a sense, replicates are separate observations from different 

populations exposed to the same input variable set that are sampled and analyzed without 

bias . 

Robustness: Refers to techniques that are powerful for examining a wide range of population 

types, or cases where large measurement errors occasionally are encountered . 

Sample : A randomly selected element of an experimental population . 

Semiquantitative : Refers to environmental chemical analyses with the ability to discriminate 

between chemical concentrations differing by an order of magnitude or more (see 

"quantitative") . 

Surrogate Standard: A compound or series of compounds added to the sample matrix (soil, 

water ,tissue) prior to extraction and used to monitor recovery . They also can be used to 

correct for loss of analytes during sample preparation (volume reduction, chemical drying, 

fractionation) . Sometimes called "recovery standard" . 

124 
Known 

Factor 

Known 

SYSTEM : Response 

Unknown 

Factor 

------------------- 

Regularly interacting or interdependen 

Controlled group of items acting as a unified 

Factor whole (includes borders, inputs, 

transforms, and outputs) Unknown 

Response 

Uncontrolled 

Factor 

Figure 1 . Schematic representation of an experimental system with selected input and 

output factors. 

125 
Specification of Input Variables 

Identified as Factor Not Identified as Factor 

statistical 

r 

Is a True Factor effects 

loss of power 

Is Not a True 

Factor 

Figure 2. Probable results of adequate and inadequate specification of input variables in 

experimental systems. 

A B 

Appropriate experimental Poor design ; loss of power 

design ; valid statistical inference invalid or misleading 

procedu e~nference ; worthless 

(assuming adequate N and 

results; failure to attribute 

no bias) to important input variables 

C p 

Unnecessary prol'aity, 

Occam's razor 

Possible 

(Is overcome by proper 

design, adequate N, and 

safeguards against bias) 

126 
Specification of Output Variables 

Identified as Response Not Identified as Response 

f 

Is a True 

Response 

f 

Is Not a True Adequate 

Response 

important) 

A 

Possibility of serious 

Adequate design ; appropriate consequences 

and powerful statistical (e .g ., generation of 

inference tout and available 

transformation products) 

C D 

Unnecessary data Occam's razor, 

(but information is available design and 

later if the system evolves 

and the response becomes statistical inference 

Figure 3 . Probable results of adequate and inadequate specification of output variables in 

experimental systems . 

127 
50 

A 

a 

a 

40 

o, 

c 

U 

0 30 

U 

c 

o 

c 

~ 20 

0 N 

C 

m \ Sterile Control 

\ Estuarine 

0 10 20 30 40 50 60 70 Microbes 

Time (Days) 

65 

B 

55 ° ov .: . . 

c o 

76 45 

c 

U 

0 35 i 

c 

. c 25 

a

w 

N 

C 15 ~ ~ Sterile Control 

m ~ Killed Control 

Estuarine 

0 10 20 30 40 50 60 70 80 Microbes 

Time (Days) 

Figure 4. Effects of under-controlling a laboratory biodegradation study. A.) Apparent 

degradation of benzo(flquinoline by estuarie microbes vs . sterile conditions . 

B.) Effect of killed biomass control and system variability on the apparent 

degradation of benzo(f)quinoline (ellipses are 95% confidence bands on the 

least squares linear regression lines, n=3) . 

128 
Full Scan 

Intensity 

LIL L, Ala 

Time 

SIM 

Intensity 

. 

L==L 

Time 

Figure 5. Effect of SIM approaches on GC-MS data sets . Full scan shows approximately 60 

resolved compounds and unresolved envelopes while SIM data provides only selected ions (c . 

20) within preselected elution ranges . 

129 
Toxicology Research: An Update on EPA Methods for the Evaluation of 

Oil Spill Dispersantsl 

Carol B. Daniels 

U.S . Environmental Protection Agency 

Environmental Research Laboratory, Gulf Breeze 

1 Sabine Island Drive 

Gulf Breeze, Florida 32561-5299 

INTRODUCTION 

Change is the hallmark of progress . In science, progress, i.e . change, is typically 

denoted by the advance of technology. The evolution of each new technology, encourages 

the stabilization and, in some instances, the demise of other related technologies . 

Development of bioremediation as a technology for oil spill abatement, is a clear example of 

waning interest in one technology, chemical dispersants, and the increasing interest in 

another . 

Oil spill research at the Environmental Protection Agency (EPA) has followed a 

similar trend of expansion and stabilization, with funding of dispersant research declining in 

recent years . The nutrient enrichment study conducted in Alaska subsequent to the 

grounding of the EXXON Valdez was a significant event which spurred the advancement of 

other spill response technologies including bioaugmentaion. Since that time, research on 

bioremediation processes has moved forward, while research on oil spill dispersants has 

plateaued within the federal, state and private sectors. 

Although bioremediation remains as the primary focus of EPA's research program in 

Oil Spill Pollution, studies have been conducted to enhance our knowledge of dispersants and 

to minimize potential hazards associated with their use. Within the Agency (EPA), the 

current effort on dispersants is focused primarily in three areas: (1) spill response and 

contingency planning; (2) re-evaluation of regulatory test methods for efficacy and toxicity ; 

and (3) risk estimation. This discussion will highlight toxicological research on dispersants 

as it relates to the latter two categories, regulatory test methods and risk estimation . 

Review of Re u~latory Test Methods 

The bioassays currently described in Subpart J of the National Oil and Hazardous 

Substances Pollution Contingency Plan (NCP) and used to evaluate the toxicity of dispersants 

'Contribution No. 910 from the Environmental Research Laboratory, Gulf Breeze, FL. 

The research described in this article has been subjected to Agency Review. The views 

expressed in the article are that of the author, and no official endorsement should be 

inferred . Use of trade names in this publication does not constitute endorsement by the U.S . 

Environmental Protection Agency. 

130 
and other oil cleaning agents have remained relatively unchanged since written (49 FR 

29192; July 18, 1984) . The last changes were promulgated March 18, 1990 (55 FR 8666) . 

The standard dispersant toxicity test (SDTT) protocol requires use of a saltwater fish, 

Fundulus heteroclitus, and an invertebrate species, Anemia salina, in acute bioassays 

designed to screen dispersants and other chemical agents for potential effects on the survival 

of aquatic species. Lethality data from the SDTT is required for the inclusion of a dispersant 

on the NCP product schedule. These organisms are exposed to a dispersant in a gradedseries of dispersant concentrations for a period of 96h under static-flow conditions . The 

relevance of the toxicity tests described in the SDTT protocol has come into question since 

Anemia saliva and Fundulus heteroclitus are used as test species and have been reported in 

some cases to lack sensitivity to crude oils . Use of Fundulus poses some limitations on the 

quality of the test methods employed relative to reproducibility and variability in the data 

since these organisms are generally not reared in the laboratory . 

Concern over the lack of sensitivity of Anemia to oil and related by-products has 

prompted research on determining the sensitivity of other marine test species to oil 

contaminants. Data derived from routine use of cultured organisms such as the inland 

silverside (Menidia beryllina) and mysid shrimp (Mysidopsis bahia) for other forms of 

regulatory testing (e.g., National Pollution Discharge Elimination System (NPDES) testing in 

the case of mysids) coupled with toxicological data on pure chemicals (e.g., pesticides, 

industrial agents, etc .) has lead to extensive toxicological databases describing the relative 

sensitivity of these organisms to various contaminants (Hemmer et al. 1992; Cripe 1990; and 

Cripe and Cripe 1990) . Despite limited information on the effects of oil on these two 

species (Daniels and Whiting 1993 ; Daniels and Whiting 1992) collection of comparative data 

on the sensitivity of M. beryllina and M. bahia to fuel oils and chemical dispersants has been 

encouraged by regulatory agencies and industry groups relative to other test organisms 

(Anemia and Fundulus) . 

To address concerns about the sensitivity of the test species and to accommodate State 

requests for incorporation of regional test species into the SDTT protocol : EPA scientists 

conducted more than forty acute toxicity tests to evaluate the comparative sensitivities of five 

species, the sheepshead minnow (Cyprinodon variegatus), inland silverside (Menidia 

beryllina), mysid shrimp (Mysidopsis bahia), brine shrimp (Anemia saliva) and killifish 

(Fundulus heteroclitus) using API#2 fuel oil and the dispersants, Corexit 9527 and 7664, in 

the SDTT protocol for dispersant toxicity . The results of these tests are the focus of this 

presentation . 

96h static acute tests were performed according to the SDTT protocol (48 FR 29192) 

using the five species noted above (Brizeno et al. 1992), The data indicate that the two Gulf 

of Mexico species, M. beryllina and M. bahia, were more sensitive to these agents than were 

Fundulus, Anemia or Cyprinodon . Seven-day (7d) chronic-estimator tests were performed 

subsequent to the 96h tests, to assess the benefits of performing longer duration tests with the 

more sensitive test organisms, M. beryllina and M. bahia (Whiting et al. 1992) . Protocols 

for chronic-estimator tests were also modified to incorporate use of oil-water dispersions 

(OWD) and water-soluble fractions (WSF) of the API#2 fuel oil. Comparative data on the 

toxicity of oil, dispersants and oil-dispersant mixtures were also derived. 

131 
Chronic toxicity test data indicated that mean 7d LC50 values derived from the 

chronic-estimator tests were not significantly (p < 0 .05) different from mean 96h LC50 

values from acute tests for either M. bahia or M. beryllina. Sensitivity of organisms in the 

7d tests was dependent on the toxicant, and the rank order for toxicity indicates oil-dispersant 

mixtures were more lethal than were either API#2 fuel oil or dispersant alone . Growth and 

reproductive effects, where observed, typically occurred at a concentration just below that 

noted for a significant change in mortality. 

These data provided the Agency's regulatory staff (EPA, Office of Solid Waste and 

Emergency Response) with the information necessary to recommend use of Menidia and 

Mysidopsis as alternatives to the less sensitive Fundulus and Anemia in the NCP dispersant 

toxicity test . The revisions to the proposed changes (revised standard dispersant toxicity 

test ; RSDTT) were published in the Federal Register in October, 1993 (58 FR 54702) . 

These changes, coupled with the proposed 45 percent cut-off for efficacy are expected to 

provide an effective screening mechanism for On-Scene Coordinators and other decision 

makers seeking safer and more effective agents . 

Risk Estimation 

Although regulatory test methods play a significant role in the Agency's risk 

assessment paradigm, supplementary data on the sublethal effects of dispersants to marine 

species help to define the hazards associated with use of oil spill dispersants in coastal and 

marine habitats . Toxicological data on the growth, reproduction and developmental success 

of a species provide key information in the evaluation of ecological hazards for these agents. 

Shrimp represent a significant economic resource in the Gulf of Mexico region. Despite this, 

limited toxicity data are available on the effects of dispersants on the development of shrimp 

(Anderson et al. 1987 ; Anderson et al. 1981 ; Tatem et al. 1978 and Shuba and Heikamp 

1989) ; a fact often related to the unavailability of laboratory reared organisms. Use of 

organisms of similar genetic stock reduces variability within a bioassay making for a more 

toxicologically-sound test. 

Shrimp Embryo Toxicity Test 

A toxicity test was developed by EPA researchers, using grass shrimp (Palaemonetes 

pugio) embryos, with the intent of minimizing genetic variation within the test (Fisher and 

Foss, 1993). Developing eggs from a single ovigerous female were exposed to different 

concentrations of two dispersants (Corexit 9527 and Corexit 7664), a water-soluble fraction 

of API #2 fuel oil, and combinations of oil plus dispersant, and monitored for survival and 

hatch . Although several females were used for a series of experiments, eggs from a single 

brood were employed for each independent event which was found to greatly enhance the 

reproducibility of a test . 

Data from these developmental tests indicated that oil-dispersant mixtures were 

generally one order of magnitude more toxic to developing shrimp embryos than was the 

dispersant alone (Fisher and Foss 1993) . Toxicity of the oil-dispersant mixtures was found 

to be temperature- and salinity- dependent, with elevation of temperature causing a shift in 

132 
onset of mortality to an earlier age . In cases where hatching was observed (i .e ., control, 

10% water soluble fraction of oil (WSF) and 10% WSF plus Corexit 9527), it was relatively 

synchronous with the onset of hatch which occurred between days 11 and 14. 

Wetland Plants 

Like the shellfish industry, coastal wetlands are integral to the vitality of the Gulf of 

Mexico. Their importance as a nursery for coastal and marine fishes has long been 

recognized . However in ecological risk assessments, the significance of plants associated 

with these wetland communities, is frequently overshadowed by concern for vertebrate and 

invertebrate species inhabiting these ecosystems. Preliminary studies were initiated to 

determine the effect of impact of dispersant use on wetland vegetation . Measures of effect 

(survival and growth) were assessed for wetland species Sesbania macrocarpa (river hemp) 

and Spartina alterniflora (smooth cordgrass) following exposure to a Louisiana crude oil and 

oil-dispersant mixtures (Weber et al. unpublished) . Studies to assess the potential impact of 

a highly refined Alaskan oil on the assimilative capacity of microorganisms associated with 

the rhizomes of Spartina alterniflora were also initiated (Frederick et al., 1993) . Because of 

the preliminary nature of these studies, the data will not be presented here . However, the 

potential significance of these data and that of others (Mendelssohn and Hester 1990; Webb 

and Alexander 1991) derives from the fact that these studies may be used to assess the 

impact of clean-up technologies on wetland vegetation. This type of research may assist in 

spill response activities by providing a greater understanding of the effectiveness and 

consequences of clean-up strategies in wetlands . These studies may also emphasize the need 

for preservation of wetland habitats . 

This presentation provides a brief synopsis of toxicological studies currently underway 

at EPA's Environmental Research Laboratory, Gulf Breeze to enhance EPA oil spill response 

programs . Toxicity data on mysids, M. bahia, and silversides, M. beryllina, reviewed here, 

provided in part, the basis for changes to the dispersant toxicity test described as part of the 

National Oil and Hazardous Substances Pollution Contingency Plan, Final Rule (FRL-5028-6 ; 

59 FR 47384) . Information from studies with oil spill dispersants and aquatic species, P. 

pugio, S. alterniflora and S. macrocarpa, can help to broaden our understanding of the 

effectiveness and ecological consequences of this clean-up technology . 

In the current risk assessment paradigm, constant-exposure studies such as those with 

the mysid and silverside serve as effective tools for hazard identification in a regulatory 

framework. Despite their current usefulness, research should be expanded to include studies 

of discontinuous/episodic exposures to enhance the realism of the exposure regimes used in 

dispersant testing protocols . Expansion of the protocol to include freshwater species has 

been suggested by some. Performance of field studies is encouraged to judge the true impact 

of dispersants on marine organisms and to assess the predictive nature of these short-term 

tests . 

133 
ACKNOWLEDGMENTS 

The author gratefully acknowledges the contributions of D. Whiting, C. Head, J . 

Brizeno, J . Moore, and others for thier technical expertise in the implementation of this 

project. The assistance of D. Weber, A. McErlean and S. Howard for their review of the 

manuscript is also appreciated. Financial support for this project was through the U.S . EPA, 

Office of Solid Waste and Emergency Response . 

REFERENCES 

Anderson, J.W ., R. Riley, S. Kiesser and J. Gurtisen. 1987 . Toxicity of dispersed and 

undispersed Prudhoe Bay crude oil fractions to shrimp and fish . pp 235-239 . In, 

Proceedings, 1987 Oil Spill Conference, American Petroleum Institute, Washington, 

D.C . 

Anderson, J.W ., S. Kiesser, R.M . Bean, R.G. Riley, and B.L. Thomas. 1981 . Toxicity of 

chemically dispersed oil to shrimp exposed to constant and decreasing concentrations 

in a flowing system. pp 235-239 . In, Proceedings, 1981 Oil Spill Conference, 

American Petroleum Institute, Washington, D.C . 

Brizeno, 7., W.J . McKee, J.R . Clark, D.D . Whiting and C.B. Daniels . 1992. Relative 

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with dispersants . Presented at the 13th Annual Meeting of the Society of 

Environmental Toxicology and Chemistry, 8-12 Nov., Cincinnati, OH. 

Cripe, G. 1990. Comparison of the sensitivity of post larvae of pink shrimp, Penaeus 

duorarum, and mysids, Mysidopsis bahia to selected chemicals . EPA/600/X-90/285 . 

U.S . Environmental Protection Agency, Gulf Breeze, FL. 7pp . 

Cripe, G. and C.R . Cripe. 1990. Comparative acute sensitivity of selected estuarine and 

marine crustaceans to toxic chemicals . EPA/600/X-90/358 . U.S . Environmental 

Protection Agency, Gulf Breeze, FL. 7pp. 

Daniels, C.B. and D. D. Whiting. 1992. Acute and chronic toxicity of oil samples from the 

Mega Borg tanker to mysid (Mysidopsis bahia) and penaeid (Penaeus setiferus) 

shrimp . EPA/600/X-92/080 . U.S . Environmental Protection Agency, Gulf Breeze, 

FL. 7pp . 

Daniels, C.B. and D. D. Whiting. 1993 . Acute toxicity of oil from the from the Apex oil 

spill to four Gulf of Mexico species : Mysidopsis bahia, Penaeus setiferus, Penaeus 

duorarum and Menidia beryllina. EPA/600/X-92/101 . U.S . Environmental 

Protection Agency, Gulf Breeze, FL. 

134 
Fisher, W. S . and S. S. Foss . 1993. Simple test for the toxicity of number 2 fuel oil and 

oil dispersants to embryos of grass shrimp, Palaeomonetes pugio. Mar. Poll. Bull. 

26(7) : 385-391 . 

Frederick, B. A., D. E. Weber, and J. E. Lepo . 1993 . Ecological impact of oil spills on 

Spartina alterniflora and on the diversity of their rhizosphere microflora in artificial 

sediments. Presented at the 1993 Annual Meeting of the American Society for 

Microbiology, 16-20 May 1993, Atlanta, GA. 

Hemmer, M. J ., D.P. Middaugh and V. Comparetta . 1992. Comparative acute sensitivity 

of larval topsmelt, Atherinops affinis, and inland silverside, Menidia beryllina, to 11 

chemicals. Environ. Toxicol. Chem. 11 : 401-408. 

Mendelssohn, I .A. and M.W . Hester . 1990. The effect of a Louisiana crude oil discharge 

from a pipeline break on the vegetation of a southeast Louisiana brackish marsh. Oil 

Chem. Pollut . 7(1) : 1-15 . 

Shuba, P.J . and A. J . Heikamp, Jr. 1989. Toxicity tests on biological species indigenous to 

the Gulf of Mexico. pp 309-316. In, Proceedings of the 1987 Oil Spill Conference, 

American Petroleum Institute, Washington, D.C. 

Tatem, H. E. , B . A. Cox and J. W. Anderson. 1978. The toxicity of oils and petroleum 

hydrocarbons to estuarine crustaceans . Estuar. Coastal Mar. Sci. 6: 365-373 . 

Webb, J.W . and S.K . Alexander . 1991 . No.2 fuel oil effects on Spartina alterniflora in a 

Texas salt marsh. Contributions in Marine Science 32 : 9-19. 

Whiting, D.D ., J.R. Clark, J. Brizeno, and C.B . Daniels . 1992 . A comparison of sevenday chronic toxicity test endpoints using mysids (Mysidopsis bahia), silversides 

(Menidia beryllina), #2 fuel oil, and oil dispersant products . Presented at the 13th 

Annual Meeting of the Society of Environmental Toxicology and Chemistry, 8-12 

Nov., Cincinnati, OH. 

135 
Remediation Techniques: An Overview 

William A. Kucharskil and Paul Kostecki2 

' Secretary 

Louisiana Department of Environmental Quality 

Baton Rouge, LA 

Z University of Massachusetts 

Amherst, MA 

INTRODUCTION 

Remediation is a word widely used in conversation and technical journals but you will 

not find it in an American dictionary because it is actually a newly created word . The root of 

the word, remedy, can be found however. A reme is defined as "A means of counteracting 

or removing an error. to make right, correct. " Even if American dictionaries do not contain a 

definition of remediation, the term is used to mean an applied remedy. Since this section covers 

an overview of remedial technologies, the starting point for the section is a definition of the 

topic . For the purposes of this paper, the term Remediation will be defined more precisely as 

follows : 

The application of a process or technology to a mixture of materials such that the 

problem or hazard associated with the mixture is counteracted or removed . 

There are three physical principles that form the basis of all remedial technologies and 

designs . These principles are physical separation , physio-chemical reactions and 

chemical/biochemical reactions. The second law of thermodynamics states that all natural 

processes take place so as to increase entropy, that is, the universe tends toward a state of 

equilibrium, randomness or sameness . This principle is illustrated by this simple question: which 

requires more energy and effort, spilling oil on the ground or removing the oil from the soil? 

This law of nature that it is easier to make a problem than it to fix one, defines the basic 

challenge of any remedial technology : how do we engineer the separation of two types of 

materials once they have become mixed? In the alternate, if we do not separate the materials, 

how can the mixture be stabilized, contained, modified or reused? When we include in this 

discussion the nature of a petroleum product, which after all is a mixture of hundreds of specific 

chemical compounds, the potential solutions become both more numerous and simultaneously, 

more difficult. 

136 
The remainder of the paper will describe several different remedial technologies that 

have been applied to petroleum contaminated soil and ground water. As the various types of 

remedial technologies are described, the basic principal that drives the technology will be 

discussed . The technologies will be grouped and discussed by these principles. 

Physical separation 

The process of physical separation can be thought of as a separation based on physical 

differences between the mixture components and equilibrium differences of these components 

in liquid and vapor phases . More precisely, a separation process takes a combination of 

chemical species and by applying physical or chemical principles, creates two or more separate 

products which differ in composition. Most, if not all of these separation processes are based on 

an equilibrium principle . The refining of crude oil into different products is a direct application 

of basic chemical engineering separation processes . When petroleum products have been spilled 

or deposited on the ground or in a water source, we utilize the identical principles that were 

applied in the original refining process to separate that petroleum from either the earth or the 

water. This we call remediation. 

There are several examples of physical separation processes that will be discussed in this 

section, but two brief examples follow . Vapor extraction works by utilizing vapor pressure 

differences between petroleum and water or petroleum and soil . Soil washing (solvent extraction) 

on the other hand, is a process in which the difference in the solubility of petroleum and the 

soil in water (usually enhanced by the addition of a surfactant), is the equilibrium principle that 

drives the process . Other examples of this principle would be air stripping, thermal desorption, 

microwave enhanced vapor extraction or air sparging . Each of these remedial technologies uses 

equilibrium driving forces as the primary separation mechanism . 

Physio-Chemical Reactions 

Physio-chemical processes are remedial technologies that do not result in the separation 

of materials . The process principles consist of a change in the chemical bonding or structure of 

the material required to be treated . This type of process may include the immobilization of the 

material, such as in a solidification fixation process . Other physical reaction methods would be 

adsorption or the oxidation of the material during incineration . Another such process is asphalt 

incorporation of petroleum contaminated soils . Each of these mechanisms depends on a bonding 

phenomenon or structural decomposition through non-biological oxidation. 

Chemical / Biochemical Reactions 

The third major remediation technique used for petroleum contaminated media is 

biological activity as a means of oxidation reduction of petroleum. Selected microorganisms 

ingest various hydrocarbon groups and the resultant decomposition by-products are then ingested 

by other groups (and types) of organisms . Under ideal aerobic conditions, carbon dioxide and 

137 
water are the ultimate residuals from this microbial process . The molecular material ingested by 

these microorganisms provides the energy necessary to maintain the life of these organisms . 

Here is the listing of the technologies to be reviewed and discussed: 

Physical separation 

SOILS 

Thermal Desorption 

Thermal desorption consists of heating the contaminated soils with an external heat source 

such as heated air flow, or with an internal heat source such as an oil heated screw feeder . The 

major difference between thermal desorption and incineration is that in thermal desorption, the 

volatilized materials are either captured or combusted away from the soil substrate. The 

limitations on soil size and moisture content relate to the amount of energy that must be added 

to the desorber to volatilize the hydrocarbons in the soils . While many systems usually operate 

at 400°to 600° F, thermal desorbers are operated at temperatures as high as 1200° F. In order 

to determine the temperature at which a thermal desorber is to be operated, the boiling point 

range of the treated petroleum mixtures should be considered . 

Gasoline volatilizes at 105° -440° F (40°-225° C); Kerosene at 350°-640° F (180°-300° 

C) ; Diesel at 390°-640° F (200°-340° C) ; Lubricating oil and crude oil has constituents that 

volatilize at high temperatures, i .e ., greater than 800° F. The volatilized gases can be either 

released to the atmosphere untreated or be combusted, condensed or adsorbed in an activated 

carbon system. 

Thermal desorbers have been designed and operated using several different designs. 

Rotary drum dryers utilize either co-current or counter current heated air flow, while thermal 

screw designs use hollow screw feeders that usually contain hot oil as the heat source . The 

thermal screw design has one inherent advantage ; it can maintain a low oxygen atmosphere in 

the chamber. Conveyor furnaces move the soil through a heated chamber on a metal belt. It is 

similar to the rotary dryer in principle . 

Factors for Consideration (US EPA 1994) : 

Soil Particle size : <4.4 cm dia . 

Moisture Content: 10%-25% 

Heating Value of Soil/Petroleum Fraction: < 2000 BTU/lb 

Composition of Fraction: Boiling Point < 1200° F 

Types of systems : 

Rotary Dryer, Thermal Screw, Conveyor Furnace 

138 
Vacuum Extraction 

Vacuum extraction is a process that utilizes the volatility of the petroleum constituents 

and equilibrium concentrations between the liquid and vapor phase as the primary method of 

remediation. Normal slotted wells are placed in the vadose zone of the soil, in or around the 

contaminated soil . The well is sealed at the surface and connected to a vacuum pump . The 

resultant vacuum in the extraction wells causes a subsurface air flow to pass over the adsorbed 

soil/petroleum matrix . Utilizing vapor phase equilibrium as the driving force, volatile 

components are moved from the liquid phase into the vapor phase and removed via the vacuum 

extraction system. Low soil permeability and high soil moisture both inhibit air flow and 

therefore petroleum constituent recovery. In a wet soil, the soil is usually desiccated before there 

is significant recovery of the petroleum constituents . This process can be enhanced by injecting 

heated air or by applying microwaves to increase the temperature, and therefore the volatilization 

of the petroleum constituents . 

The process is generally utilized to remediate the more volatile petroleum products such 

as gasoline and aviation fuel but it can be used to reduce the mobility and hazard of diesel, 

kerosene and some heating oils by removing the more volatile fractions from the soil . 

Soil vapor extraction is usually limited to material with a boiling point less than 480° F or 250° 

C and high vapor pressure (greater than 0 .5 mm Hg) . Henry's Law constant is a measure of the 

volatility of compounds dissolved in water. Compounds with a Henry's law constant greater than 

100 atmospheres tend to be removable from water using vapor extraction. 

The efficacy of this technology is enhanced whenever the temperature of the constituents/soil can 

be increased . Techniques that provide this increased temperature include microwaves, heated and 

injected air and steam injection. 

Vacuum pressures can be as high as 200 inches of H2O in very tight soils . Most systems 

operate between 30 and 60 inches of water and 20-cfm air flow from each well . In shallow 

aquifers, those less than ten feet from the surface, horizontal extraction wells can be installed . 

Factors for Consideration (US EPA 1994) : 

Intrinsic Soil Permeability : k (cm2) > 10-8 

Depth to Groundwater : > 10 ft 

Vapor Pressure of Petroleum Fraction : > 0 .5 mm's Hg 

Henry's Law Constant: > 100 atm 

Composition of Fraction: Boiling Point: <250° C, 480° F 

Types of Systems 

Microwave Enhanced, Heated Air Injected, Steam Injected, High Vacuum 

139 
Soil Washing (Solvent Extraction) 

Solvent extraction - This process operates on the principle of differential solubilities of 

materials . There are processes that utilize extracting solvents such as triethylamine, carbon 

dioxide or propane. For general heavy oil recovery however, water with an added surfactant, 

is the most common processing solvent. In this process, contaminated soils are usually excavated 

(although in situ soil flushing systems do exist) and the soil screened to remove large rocks and 

materials. If there are large amounts of clay or other very fine soil particles, soil washing can 

be limited by the ability of the soil particle to settle after the washing/extraction has been 

accomplished. Early surfactants were simple laundry detergents. These detergents work by 

attaching a hydrophilic molecule (a molecule that "likes" water, therefore dissolves in it), to and 

insoluble particles (dirt grease) thereby making that particle soluble . The detergent allowed the 

dirt particle to remain in solution, producing what we know as dirty water. When this principle 

is applied to soil washing, the problem with the detergent type surfactant is that the oil/water 

emulsion must be treated and the soil must be separated from the solution . Newer surfactants 

have been developed that do not increase the solubility of the petroleum constituent in water, but 

form a separate phase that is easily separated from the soil/water phase. If there are many fine 

(e .g ., clay) particles in the soil, mechanical separation of the soil from the liquid phase may be 

instituted in order to remove the water from the soil . Some new surfactants also contain many 

of the base nutrients necessary to support microbiological activity . A major impediment to using 

soil washing as a remediation technique has been the inability of the process to remediate fine 

particle substrates and to treat the wash water in a cost-effective way. 

Factors for Consideration (EPRI et al. 1988) : 

Soil Characteristics : < 30 % Clays 

Depth of Contaminated Soil : <25 ft 

Characteristic of Solvent: Treatability, separation characteristics 

Types of Systems 

Excavated with mechanical washing/extraction, in situ soil flushing 

WATER 

Air Stripping (Sparging) 

Air Stripping/Air Sparging - This process is based on the principle of enhancing the 

volatilization of dissolved petroleum constituents in the water phase. A stripper utilizes air, 

which is added to the base of a packed tower; contaminated water is added to the top . As the 

air moves upward and the contaminated water phase moves down, the air/water interface 

increases the mass transport potential and drives the vapor phase equilibrium to favor the 

transfer of the dissolved constituent into the vapor phase . The contaminant is then captured in 

the vapor phase and either recovered or combusted. Air sparging utilizes the same principles . 

140 
A well is constructed into contaminated groundwater and air is pumped into the well. An air 

sparging unit creates fine bubbles so that the air is distributed into the soil/groundwater matrix . 

This enhances the volatilization of dissolved constituents . Air sparging is often used in 

conjunction with a vapor extraction system or an in situ bioremediation process . The probable 

efficacy of air sparging is evaluated in a similar manner to the evaluation of a vapor extraction 

process. High levels of iron in the ground water may pose a problem. If the Fe" is contacted 

by air, the iron may oxidize and precipitate, thereby reducing the permeability of the effected 

area. When this sparging technique is used in conjunction with bioremediation, the process is 

termed Bioventing. 

Factors for Consideration (US EPA 1994) : 

Intrinsic Soil Permeability : k (cm2) > 10-9 

Iron concentration in Groundwater: Fe" < 10 mg/1 

Volatility of Petroleum Fraction: Boiling Point <250* C, 480° F 

Henry's Law Constant: > 100 atm 

Tunes of Systems 

Packed tower, in situ air sparging 

Physical Reaction / Incorporation 

Solidification 

Solidification - This process combines a solidification material such as Portland cement 

or a calcium rich pozzolanic material such as coal fly ash with a soil contaminated with a 

petroleum product. The process simply renders the soil and the petroleum constituents immobile. 

Construction materials such as bricks may be manufactured from contaminated soils, the volatile 

constituents being removed during the baking/curing process. Solidification is usually chosen 

when it is necessary to decrease the leachability (i .e ., mobility) of the contaminants on the soil . 

Very fine soils may inhibit the solidification process. 

Factors for Consideration (Western States Petroleum Association 1989): 

Soil Particle size : >200 mesh 

Petroleum Constituents : Semi-volatiles < 10,000 ppm, cyanides < 3,000 ppm 

Metals in soil or petroleum : Mn, Sn, Zn, Cu, Pb and sodium salts 

Future Land use 

Types of Systems 

Cement based, pozzolanic (fly ash), Chemical fixation 

141 
Asphalt Incorporation 

Asphalt Incorporation - This process has been used for many years as a means of using 

petroleum contaminated soils in a productive manner . Hot batch asphalt plants remove volatile 

components from contaminated soils in the initial combustion chamber and utilize the heavy ends 

in the asphalt itself . The lighter ends are volatilized in the asphalt dryer (400°-500° F) and 

combusted in the process. The soil bound to the heavy ends make very good aggregate 

replacement if thesoil particle size is large enough. A recent process design has been developed 

that can utilize large quantities of very fine soil particles with heavy petroleum residues 

(weathered lubricating oils were used in the study) . This process has great promise for the 

utilization of such contaminated soils . If the soil has even a small organic/humic content, asphalt 

incorporation becomes very difficult. Both hot rolled asphalt and cold batched asphalt processes 

are available . 

Factors for Consideration (EPRI et al. 1988) : 

Soil Particle Size: <200 mesh < 10% 

Soil Organic content: Limited 

Addition to normal aggregate : Limited to 5 % 

Petroleum Constituents : Volatiles limited 

Tines of Systems 

Hot batch, cold batch 

Incineration 

Incineration - This process utilizes an external source of energy (natural gas or fuel oil) 

to combust the petroleum residues and the soil substrate to which these constituents are 

adsorbed. The more volatile the petroleum product and the dryer the soil, the less expensive the 

process. Soils containing large sized particles are a problem because of the greater heat 

capacities of the solids, thereby requiring more energy in the process. Incinerators use various 

designs to combust contaminated soils. Rotary kilns, fixed hearths and fluidized beds are typical. 

Wastes with an intrinsic thermal value greater than 5000 BTU/lb are considered incinerable. 

Incinerators generally operate at combustion temperatures of 600°-1000°C (1100°-1800°F) . The 

volume of material able to be processed is dependent upon the resultant residence time of the 

waste in the combustion chamber at a given chamber temperature. Liquids and sludge wastes 

can also be incinerated but these forms usually contain large amounts of water and therefore 

require greater amounts of external energy to be added to the system. Air emissions are 

generally required to be treated if the soil contains significant quantities of chlorine or volatile 

metals such as mercury. 

142 
Factors for Consideration (EPRI et al . 1988) : 

Soil Particle size : ( < 2 inch's dia.) 

Moisture Content: 

Metals content of Soil : (As, Hg, Pb, Sn) 

Heating Value of Soil/Petroleum Fraction 

Composition of Petroleum Fraction 

Types of systems: 

Rotary Kiln, Fluidized Bed 

Vitrification 

Vitrification - This process uses large quantities of electrical energy to physically melt 

the contaminated soil . This also provides for the oxidation of any organic associated with the 

soil . The process cannot be used in situ if there are high percentage of volatile organics in the 

soil as this type of material tends to advance before the melt zone, that is, the rate of 

volatilization and resultant movement is more rapid than the advancement of the melt itself . This 

phenomenon can therefore spread the contamination. The melt vitrifies, or makes the soil into 

a glass like substance. This will encapsulate any metals contained in the melt for many hundreds 

of years . The in situ trials have produced problems, but there are facilities that can vitrify soils 

above ground in engineered containers . 

Factors for Consideration (EPRI et al. 1988) : 

Petroleum Constituents : < 15%, volatiles 

Soil Permeability: > 10-9 cm/sec 

Availability of Electric Power: Average 3,200 kW 

Depth of Contamination: 30 foot maximum 

Moisture Content: <25% 

Types of Systems 

In situ, excavated/engineered 

Chemical / Biochemical Reactions 

Bioremediation 

Bioremediation - This process is a natural phenomenon that has been used since time in 

memorial to recycle materials on the earth. Simply, aerobic microorganisms ingest petroleum 

143 
hydrocarbon molecules and excrete carbon dioxide and water. Different species utilize different 

portions of the petroleum mix. Bonds are cleaved and new compounds are thereby formed. To 

be successful, every aerobic bioremediation process requires several basic elements, oxygen, 

phosphorus, nitrogen and sulfur . If any of these things are missing, the process will not go on. 

There are also anaerobic organisms that will ingest petroleum in the absence of oxygen. 

The end products for these organisms are usually methane, water and hydrochloric acid . Most 

commercial processes are aerobic however. By monitoring the level of dissolved oxygen in 

ground water, or the levels of carbon dioxide in soil, one can determine if microbiological 

activity is occurring. Generally, the addition of oxygen, water and base nutrients to a food 

supply, such as petroleum, will encourage the growth of a microbiological colony. The positive 

thing about this process is that when the food is gone (the petroleum), the organisms also die . 

Microbiological systems can be designed to treat soils or ground water in situ or after 

excavation. The excavated soil can be land farmed or placed in a Bioreactor for treatment. 

Every successfully engineered aerobic bioremediation process must create an environment where 

there are sufficient oxygen and nutrients and where the buildup of waste products such as carbon 

dioxide, water and dead cells can be controlled. All of the techniques described in this section 

contain the same elements . 

There are two basic methods of ensuring an adequate microbial colony . One is to encourage the 

growth of indigenous colonies and the second is to separate and select a colony of 

microorganisms that are then nurtured in the laboratory to preferentially ingest the waste to be 

remediated . After the desired colonies have been selected and grown, the cells are reintroduced 

into the natural environment. Both techniques have been used successfully . 

Factors for Consideration (US EPA 1994) : 

Microbial Population : > 1,000 CFU/GM 

Soil pH : Between 6 and 8 

Moisture Content of soil : >40% 

Petroleum fraction composition: TPH < 50,000 ppm 

Rainfall : < 30 in/yr 

Types of systems : 

In Situ - Land farming, Bioreactor, Bioventing, Biopiles 

GOALS 

Before any cleanup process can be selected, there must have been consideration as to why 

the cleanup is occurring and what the cleanup is designed to effect . In other words, if an area 

is to be cleaned up because it poses a threat to human health, how much and therefore, how you 

clean up will be very different from if the cleanup is occurring to return a contaminated area to 

how it was before the contaminant was released . If the cost of the remediation is not the primary 

144 
issue, the determination of the ultimate goal of the remediation is usually agreed upon before 

any remediation process is selected . On the other hand, if a total cost for the cleanup has been 

set, then alternative technologies can be evaluated to determine what can be done for the amount 

of money allocated for the cleanup . It is important to have this decision made before choosing 

a specific remediation path. 

REFERENCES 

Calabrese, J., P. Kostecki, and C. Bonazountas . 1994 . Hydrocarbon Contaminated Soils, 

Volume IV, Perspectives, Analysis, Human Health and Risk Assessment, Remediation, 

Amherst Scientific Publishers . 

Cole, G . and Mattney. 1994. Assessment and Remediation of Petroleum Contaminated Sites, 

Lewis Publishers . 

King, C. and M. Judson. 1971 . Separation Processes, McGraw-Hill Book Company. 

Shell Development. 1993 . Soil Remediation Workshop, Shell Oil Company. 

United States Environmental Protection Agency. 1994. How to Evaluate Alternate Cleanup 

Technologies for Underground Storage Tank Sites, EPA 510-B-94-003. 

Western States Petroleum Association. 1989 . Onsite Treatment, Hydrocarbon Contaminated 

Soils. 

EPRI, EEI, Roy F. Weston, Inc., University of Massachusetts . 1988. Remedial Technologies 

for Leaking Underground Storage Tanks, Lewis Publishers . 

145 
Responding to Oil Spills in Marshes: 

The Fine Line Between Help and Hindrance 

Rebecca Z. Hoff 

NOAA 

Hazardous Materials Response and Assessment Division 

7600 Sand Point Way N. E. , Seattle, WA 98115 

INTRODUCTION 

There is general understanding that marsh environments are highly sensitive to oiling and 

thus receive high priority for protection. Lessons from past spills have also documented that 

response activities have the potential to cause additional harm to oil-impacted marshes. Less 

clear is how to determine when cleanup is desirable, when it should stop, and which methods 

should be employed. 

The basic lessons about impacts of oil and subsequent response activities in marshes 

have been known for years (Mattson et al. 1977; Westree 1977 ; McCauley and Harrel 1981) . 

The Amoco Cadiz spill in France taught us the complications from sediment removal at the 

Ile Grande marsh, when such activities greatly increased erosion of the marsh and 

substantially delayed vegetative recovery (Baca et al. 1987 ; Vandermeulen et al. 1981) . 

However, in cold temperate environments, it has also been clearly documented that heavily 

oiled marshes where oil is not removed may be impacted for decades (Table 1) . The Metula 

spill in Chile is an extreme example of slow recovery after 20 years, little change has 

occurred (Baker et al. 1993; Teal et al. 1992 ; Vandermeulen and Jotcham 1986) . At some 

spills occurring in warmer regions less severely impacted by crude oils, very limited clean-up 

has constituted a successful "response" (e.g., Neches River Unocal spill ; NOAA 1993) . 

Additional monitoring studies conducted in oil-impacted marshes, as well as experimental 

research during the past two decades have documented the complexity of marsh ecology and 

the numerous parameters that affect the severity of impact to these systems (DeLaune et al. 

1984, de la Cruz et al. 1981, Alexander and Webb 1985) . This knowledge complicates 

decisions regarding cleanup in marshes, because we now know that such parameters as 

substrate type, plant species, season of impact, oil type and climate may all affect the 

eventual recovery of an oil-impacted marsh (Table 3) . 

A myriad of questions await responders faced with an oiled marsh . Under what 

circumstances is cleanup appropriate not only in removing oil, but in speeding recovery of 

the marsh? If the decision is made to respond in a marsh, what methods should be employed 

and how should these be chosen? Where is the line where cleanup should cease lest it cause 

more harm than good? How can seemingly conflicting resource needs be balanced in cleanup 

decision making (marsh cleanup is often suggested as a way to prevent oiling of birds or 

other animals, or to prevent oil from moving to other sensitive environments)? To develop 

some general guidelines for answering these questions, I have perused numerous follow-up 

studies after oil spills, and reviewed the scientific literature on this subject. 

146 
CLEANUP DECISION MAKING 

A simple starting point for determining whether cleanup is appropriate for an oiled marsh 

is to assess the severity of the impact, and attempt to estimate the time-frame for recovery. 

Predictions of future recovery times will, of course, be approximations, but can provide a 

general sense of whether impacts are likely to be short term (less than 1 year), medium-term 

(1-3 years), or long-term (greater than 3 years) . Having an idea of the likely time frame for 

recovery without cleanup allow us to assess whether undertaking some response is likely to 

speed the natural recovery process or impede it . 

Defining recovery 

Recovery is an easily misunderstood and difficult term to define, but the concept is a 

necessary endpoint for environmental monitoring studies . Generally, recovery is used to 

denote a return to some un-impacted state of the environment in question. Ecological 

communities are not static and undergo changes based on environmental perturbations both 

naturally occurring and human caused. It is common to measure recovery by comparing oil 

impacted sites with nearby 'control' (un-impacted) sites. When these sites resemble each 

other in important ecological parameters (such as percent cover of vegetation for marshes) 

they can be considered to be recovered . 

For marsh studies, the most commonly measured parameter is the percent cover of 

vegetation, sometimes accompanied by diversity indices or height and weight of plants . 

However, each follow-up study is different, and may measure additional indices . For the 

purposes of this paper, recovery will refer to vegetative cover, largely because percent cover 

is measured by a number of different studies . Commonly, some measurable concentration of 

petroleum hydrocarbon remains in sediments of marshes that appear to be "recovered" from 

looking only at the vegetation . It is important to remember that vegetative recovery may not 

include measurements of subtle differences in species diversity or use of the habitat by other 

organisms. 

Timelines for "recovery" 

Documented recovery times for oiled marshes range from a few weeks to decades (Tables 

1-3) . As might be expected, the cases on the extreme ends of this spectrum are the easiest to 

delineate . On the worst case side, are several well-studied marsh sites where recovery times 

ranged from 5 years to greater than 20 years . These include two sites in Buzzard's Bay 

Massachusetts, the Miguasha spill in Quebec, the Metula in Chile and the Amoco Cadiz in 

France (Table 1) . These examples share the following characteristics: 

north-temperate (cold) environments, 

sheltered location 

heavy oiling 

spills of fuel oils (bunker C or No. 2 fuel) 

in some cases intensive cleanup methods delayed recovery 

147 
In contrast, recovery times of two years or less have been documented for sites at the 

following spills (examples are taken from Gulf of Mexico) : Neches River, Texas (Esso 

Bayway), Harbor Island, Texas pipeline, and the Shell pipeline in SE Louisiana (Table 2) . 

These marshes showing quicker recovery share the following characteristics: 

warm climate 

light to moderate oiling 

spills of light to medium crude oil 

variety of cleanup methods used 

(often no cleanup resulted in fastest recovery time) 

Based on these examples, it is easy to conclude that marshes lightly oiled in warm 

climates have a good potential for natural recovery in a comparatively short period of time, 

and that cleanup may be more of a hindrance rather than a help . However, decisions to 

implement a "no response" option may be complicated by other concerns, such as potential 

oiling of birds or other animals or concerns about leaching of oil to nearby environments. 

In contrast, heavily oiled marshes in colder climates have the potential to be impacted for 

many years, depending on the type of oil spilled and the degree of penetration of the oil into 

the marsh substrate, among other parameters (Vandermeulen and Singh 1994). Cleanup 

activities in these situations have a higher potential for accelerating the recovery of the 

marsh, if only because of the expected long residence time of oil if left to weather naturally. 

Between these two extremes, however, lies the vast middle ground of spills with less 

clear-cut solutions to the cleanup question . These include moderate to heavy impacts in 

marshes in warm climates, spills of medium crude oils or refined oils, and issues involving 

conflicting resource uses . Deciding when cleanup activities are appropriate and what cleanup 

methods to use are challenging issues that usually must be made on a site-specific basis . 

Since all cleanup techniques have some detrimental impact associated with them, choosing 

any particular techniques requires a balancing of the expected gains versus the costs . Many 

techniques can be applied in a very judicious manner, thus minimizing their detrimental 

impacts. 

MARSH CLEANUP TECHNIQUES 

Historically, most techniques available for oil spill cleanup have been tried at one time or 

another in marshes. Table 5 summarizes the advantages and disadvantages of several 

techniques that are currently either commonly used, or are of strong research interest . 

Natural Degradation/No Response 

No response at all is an ideal approach when natural weathering and biodegradation are 

expected to occur quickly (see Table 4 for more details) . Choosing natural degradation/no 

response is the only way to completely eliminate physical impacts resulting from workers or 

mobilization of equipment. Natural degradation is often used as the last stage of a response 

where physical removal has already been implemented, since most physical removal methods 

148 
will reach a point where oil can no longer be effectively removed, leaving some level of 

residual oiling . The no response option has a cost when oiling is heavy and/or degradation is 

expected to be very slow (greater than 1-2 years) . Asphalt pavements may form from heavy 

layers of oil left undisturbed (in very sheltered areas or when oil strands in the upper or 

supratidal zone) . Such pavements were found at the Metula spill, in experimental "set-aside" 

plots at the Exxon Ualdez, and were observed from historic spills in the Persian Gulf. In 

these cases, initial efforts to remove thick layers of oil (or manually remove asphalt after 

hardening) are warranted. 

To ensure that areas left to degrade naturally do not contaminate adjacent sites, sorbents 

may be used to collect sheen or other mobile oil . 

Vacuum/Pumping 

Physical removal of pooled oil on marsh sediment or water surfaces using vacuum or 

pumping apparatus have been quite successful at a number of marsh spills . Large quantities 

of oil can be removed, though at some point, residual oiling will remain after most of the 

heavy oil is collected. Use of vacuum removal in conjunction with low pressure flushing can 

also be very successful . 

Two main environmental impacts from using this technique are the physical impact of 

deploying the equipment and the workers to operate it, and the potential to inadvertently 

remove plants along with oil . Careful monitoring of the use of this technique in the field is 

important to ensure that impacts are minimized . Access to remote sites may also be difficult, 

although vacuums can be deployed from barges as was done at the Tampa Bay spill to clean 

an area of oiled mangroves . 

Low Pressure Flush 

Low pressure flushing is usually used to assist in moving oil towards collection points 

where other removal equipment, such as vacuums or boom/skimmer collection operate . 

Flushing can also be helpful in lifting oil off the sediment surface during times when the 

marsh is not flooded . 

Flushing may be difficult to apply correctly, since slight changes in water pressure can 

turn a low-impact technique into a high impact one . Thus, workers must be carefully 

supervised and it is a good idea to undertake trials to work out the details of application. 

Access by workers will physically impact the marsh, and this should be minimized, either by 

working from boats during high tide, or by using board walkways. 

Vegetation Cutting 

Cutting of oiled vegetation has been tried in numerous spills, many times with quite 

drastic consequences, i.e . death of plants, increased erosion, and permanent loss of marsh. 

When oil covers sediment surfaces, cutting near the base of the plant can increase penetration 

of oil into the sediment, damaging plant roots . Studies that monitor oiled marshes where 

cutting has been used show that non-cut areas may recover as fast or faster (e.g ., Esso 

149 
Bayway spill and the American Petrofina pipeline spill) . However, cutting impacts in many 

of these studies were confounded with impacts from physical trampling by workers (Hershner 

and Moore 1977; Mattson et al. 1977; Holt et al. 1978; McCauley and Hanel 1981) . 

In general, cutting should be avoided except in special circumstances, since the likelihood 

of killing the plants and causing permanent damage to the marsh is high. Special 

circumstances include concerns about potential oiling of birds from residual oiling on plant 

fronds, or aesthetic considerations in high public use areas. At the Candian Liberty spill on 

the Delaware River, careful cutting of Phragmites and Scirpus was used to minimize risk to 

birds using the marsh. Follow-up monitoring 3 months after cutting found that plants from 

cut sites appeared similar to control sites, and no obvious adverse impacts were observed 

(NOAA 1993) . 

Burning 

Burning of marsh grasses has been practiced as a vegetation management technique for 

many years, but burning of oiled marshes is relatively new. Two recent incidents where 

burning was used to remove oil in freshwater marshes in Texas and Maine has sparked 

increased interest in this response option . Burning of oil in marshes has the potential to 

remove large quantities of oil quickly while potentially minimizing physical impacts. 

However, the technique has not yet been well documented and many questions remain 

about the specific conditions (different from the two recent examples) under which burning 

can be successfully used in marshes. Both of the recent burns in Texas and Maine were 

conducted while the marshes were inundated, and the Maine burn was conducted under ice 

and snow conditions. What degree of inundation of the marsh is necessary to minimize 

impacts to plant roots and rhizomes? Information on the effects of burns on a variety of 

plant species as well as particulars about recovery of marshes after burning are topics for 

further research . 

Bioremediation 

Bioremediation is similar to burning in its stage of development with respect to 

application in marshes . There is great interest in using the technique, and positive data from 

laboratory studies, but little information on its successful use in oiled marshes. From 

experimental data we can infer that bioremediation would be a potential low-impact cleanup 

technique for residual oiling of marsh sediments . Questions remain about the potential for 

eutrophication of marsh environments, and potential limitations to degradation from lowoxygen conditions in marsh sediments . 

Sediment Removal/Replanting 

Sediment removal followed by replanting can be considered more of a remediation 

technique than an actual response, since it is in many ways, a technique of last resort . It 

may be the only option for some cases where sediments are very heavily oiled . However, 

this is indeed an example of destroying the marsh to save it, since existing vegetation and 

150 
roots would be removed along with sediment . There is great potential for increased erosion 

and a danger that if sediments are not replaced, changes in elevation will prevent regrowth of 

plants . Several of the long term impact case studies (e .g . Miguasha and Amoco Cadiz) 

provide examples of unsuccessful use of this technique (Vandermeulen and Jotcham 1986 ; 

Baca et al. 1987) . Therefore, it should be considered a last resort option, and proceeded 

with very cautiously. 

A less intrusive related technique is tilling of contaminated sediments to try and break up 

heavily oiled sediments, providing aeration and possible channels for seeds to reach cleaner 

soil . Again, there is little data on successful use of this technique at field sites. 

SUMMARY/CONCLUSIONS 

Deciding how to respond in an oiled marsh is clearly a complex issue for which there 

cannot be a single answer. Decisions will need to be made on a case by case basis, and 

usually with a degree of uncertainty . However, the lessons of the past give us a good deal of 

guidance at least about what techniques to avoid and where to tread cautiously . The 

following guidelines give a simple outline for making these decisions . 

Begin by evaluating the impact, oil residence time and general situation : 

(1) Assess the impact of oil by conducting a field survey . Estimate what percentage 

of the marsh is oiled, how heavily, whether the species impacted are known to be 

sensitive or more tolerant. 

(2) Estimate the likely oil residence time by considering the potential for natural 

weathering and biodegradation, along with the characteristics of the marsh, such 

as the deposition rate, the type of vegetation, etc . (Table 4) . 

(3) Consider other cleanup concerns, such wildlife that may be at risk of being oiled, 

whether the area is used by the public or has other special concerns associated 

with it . 

Review whether cleanup is necessary or desirable. Clean-up in a marsh appears to be 

justified when oil can be removed with minimal impact, when other resources are at high 

risk of being oiled (such as migrating birds) and when unassisted recovery is likely to be 

very slow (greater than 2-3 years) . 

Natural (unassisted) recovery may be the best option in cases where oiling is light and 

natural recovery is likely to occur in a short time frame (such as one year or less), where 

cleanup activities would detrimentally impact the marsh and where wildlife are at low risk of 

being oiled . 

If choosing to proceed with cleanup options, review the site limitations, consider the 

options that seem appropriate, keeping in mind the need to minimize the physical impacts on 

the marsh. In many cases, trial applications of cleanup techniques will help determine if the 

technique is appropriate at a given site . Trials can also refine techniques such as low 

pressure flushing to make sure they are having the desired effect . Most responses rely on a 

151 
combination of cleanup techniques . And always keep the ultimate objectives of the response 

in mind : to minimize adverse impacts of oil on the marsh itself, on the organisms that use it 

for habitat, and to speed its ecological recovery . 

REFERENCES 

Alexander, S . K. and J. W. Webb, Jr. 1985 . Seasonal response of Spartina alterniflora to 

oil . pp. 355-357 . In, Proceedings 1985 Oil Spill Conference . American Petroleum 

Institute, Washington, DC. 

Alexander, S . K. and J. W. Webb, Jr. 1987 . Relationship of Spartina Alterniflora growth 

to sediment oil content following an oil spill. pp. 445-449 . In, Proceedings 1987 Oil 

Spill Conference . American Petroleum Institute, Washington, DC. 

Baca, B. J ., Lankford, T. E. and E. R. Gundlach . 1987 . Recovery of Brittany coastal 

marshes in the eight years following the Amoco Cadiz incident . pp . 459-464 . In, 

Proceedings 1987 Oil Spill Conference . American Petroleum Institute, Washington, 

DC. 

Baker, J. M., Guzman, L. M., Bartlett, P. D., Little, D. I ., and C. M. Wilson. 1993 . 

Long-term fate and effects of untreated thick oil deposits on salt marshes . pp. 395-

399. In, Proceedings 1993 Oil Spill Conference. American Petroleum Institute, 

Washington, DC . 

Bender, M. E., Shearls, E. A., Ayres, R. P., Hershner, C. H. and R. J . Huggett. 1977 . 

Ecological effects on experimental oil spills on eastern coastal plain estuarine 

ecosystems . pp . 505-509 . In, Proceedings 1977 Oil Spill Conference . American 

Petroleum Institute, Washington, DC . 

Burns, K. A. and J . M. Teal . 1979 . The West Falmouth oil spill: hydrocarbons in the salt 

marsh ecosystem. Estuar. and Coastal Mar. Sci. 8 : 349-360. 

Day, D. 1979. Report of Exxon tanker Esso Bay Way oil spill Port Neches, Texas . 

NOAA unpublished report, NOAA-OMPA-MESA NSTL Station, MS 3929, April 5, 

1979 . 17 p. 

de la Cruz, A. A., Hackney, C. T. and B. Rajanna . 1981 . Some effects of crude oil on a 

Juncus tidal marsh . J. Elisha Mit. Sci. Soc. 97(1) : 14-28 . 

DeLaune, R. D., Smith, C. J ., Patrick, W. H. Jr., Fleeger, J. W. and M. D. Tolley . 1984. 

Effect of oil on salt marsh biota: methods for restoration . Environ. Poll. 36: 207-

227 . 

152 
Fischel, M., Grip, W. and I . A. Mendelssohn. 1989. Study to determine the recovery of a 

Louisiana marsh from an oil spill. pp . 383-387 . In, Proceedings 1989 Oil Spill 

Conference . American Petroleum Institute, Washington, DC . 

Gonzalez, M. F. and G. A. Lugo . 1994 . Texas marsh burn, removing oil from a salt 

marsh using in -situ burning . Paper presented at In situ burning oil spill workshop, 

January 26-28, 1994, Lake Buena Vista Florida . 

Hampson , G. R., and E. T. Moul . 1978 . No. 2 fuel oil spill in Bourne, Massachusetts: 

immediate assessment of the effects on marine invertebrates and a 3-year study of 

growth and recovery of a salt marsh. J. Fish. Res. Board Can. 35 : 731-744. 

Hershner, C. and K. Moore. 1977 . Effects of the Chesapeake Bay oil spill on salt marshes 

of the lower Bay. pp. 529-533 . In, Proceedings 1977 Oil Spill Conference . 

American Petroleum Institute, Washington, DC . 

Holt, S ., Rabalais, S . Rabalais, N., Cornelius, S . and J. S. Holland . 1978. Effects of an 

oil spill on salt marshes at Harbor Island, Texas . I. Biology . 1978 . In Proceedings 

of the Conference on Assessment of ecological impacts of oil spills, 14-17 June, 

1978, Keystone, Colorado, American Institute of Biological Sciences . 

McCauley, C. A. and R. C. Harrel . 1981 . Effects of oil spill cleanup techniques on a salt 

marsh. In, Proceedings 1981 Oil Spill Conference . American Petroleum Institute, 

Washington, DC ., pp. 401-407. 

Mattson, C. P., Vallario, N. C., Smith, D. J., Anisfield, S . and G. Potera . 1977. 

Hackensack estuary oil spill: cutting oil-soaked marsh grass as an innovative damage 

control technique . pp. 243-246. In, Proceedings 1977 Oil Spill Conference . 

American Petroleum Institute, Washington, DC . 

Mendelssohn, I . A., M. W. Hester, and C. Sasser . 1990 . The effect of a Louisiana crude 

oil discharge from a pipeline break on the vegetation of a southeast Louisiana 

brackish marsh. Oil and Chemical Pollution 7 : 1-15 . 

Meyers, R. J . 1981 . Response to the Esso Bayway oil spill. pp. 409-412 . In, 

Proceedings 1981 Oil Spill Conference . American Petroleum Institute, Washington, 

DC. 

Neff, J. M., Sharp, M. S . and W. L. McCulloch. 1981 . Impact of the Esso Bayway oil 

spill on salt marsh macro fauna. pp. 413-418 . In, Proceedings 1981 Oil Spill 

Conference . American Petroleum Institute, Washington, DC. 

153 
NOAA Hazardous Materials Response and Assessment Division (Hazmat) . 1993 . 

Vegetation cutting along the Delaware River following the Candian Liberty oil spill, 

post cutting field report, 9 April, 1993 . 7600 Sand point way NE, BIN C 15700, 

Seattle, WA 98115 . 37 p . 

Teal, J. M., Farrington, J . W., Burn, K. A., Stegeman, J. J., Tripp, B. W., Woodin, B. 

and C. Phinney . 1992. The West Falmouth oil spill after 20 years: fate of fuel oil 

compounds and effects on animals . Mar. Poll. Bull., 24 : 607-614. 

Tunnel, J. W. and D. W. Hicks. 1994. Environmental impact and recovery of the Exxon 

pipeline oil spill and burn site, upper Copano Bay, Texas. Unpublished second 

quarterly report FY 1994 (year 2) submitted to : Texas General Land Office, Office of 

Oil spill prevention and response, 1700 N. Congress Ave., Room 740, Austin , Texas 

78701, 1 March, 1994. 5 p. 

Vandermeulen, J. H. and J . G. Singh . 1994 . Arrow oil spill, 1970-90: persistence of 20-yr 

weathered bunker C fuel oil . Can. J. Fish. Aquat. Sci. 51 : 845-855 . 

Vandermeulen, J. H. and J. R. Jotcham. 1986 . Long-term persistence of bunker C fuel oil 

and revegetation of a north-temperate saltmarsh: Miguasha 1974-1985 . In, 

Proceedings of the Ninth Annual Arctic and Marine Oil spill Program Technical 

Seminar, Environment Canada, June 10-12, 1986, Edmonton, Alberta. 

Vandermeulen, J . H., B. F. N. Long, F. D'Ozouville . 1981 . Geomorphological alteration 

of a heavily oiled saltmarsh (Ile Grande, France) as a result of massive cleanup . pp . 

347-351 . In, Proceedings of the 1981 Oil Spill Conference, American Petroleum 

Institute, Washington, D. C. 

Webb, J .W ., Alexander, S . K. and J . K. Winters . 1985 . Effects of Autumn application of 

oil on Spartina alterniflora in a Texas salt marsh. Environ. poll. (A) 38 : 321-337. 

Westree, B. 1977 . Biological criteria for the selection of cleanup techniques in salt 

marshes . pp. 231-235 . In, Proceedings of the 1977 Oil Spill Conference, American 

Petroleum Institute, Washington, D. C. 

154 
Webb, J.W ., Alexander, S . K. and J . K. Winters. 1985 . Effects of Autumn application of 

oil on Spartina alternifZora in a Texas salt marsh. Environ. poll. (A) 38: 321-337. 

Westree, B. 1977 . Biological criteria for the selection of cleanup techniques in salt 

marshes . pp . 231-235. In, Proceedings of the 1977 Oil Spill Conference, American 

Petroleum Institute, Washington, D. C. 

155 
Table 1 . 

Examples of oil-impacted marshes with recovery times of five years or more, 

documented by follow-up studies . 

Location Vegetation Oil type Date of Cleanup 'Recovery 

oiling time' 

Chile 

Metula ' 

Quebec 

Miguasha Z 

Salicornia ambigua Arabian crude 

Suaeda argentinensis Bunker C 

Spartina alterniflora, Bunker C 

Spartina patens 

Brittany, France Sa/icornia Arabian light, 

Amoco Cadiz ' Suaeda Iranian light 

Halimione crude 

Bunker C 

West Falmouth, Spartina a/ternif/ora, No. 2 fuel 

MA , Florida ` Salicornia europaea, 

Spartina patens 

Buzzard's Bay, Spartina a/ternif/ora, No. 2 fuel 

MA, Salicornia virginica 

Bouchard 65 5 

1) Baker et al. 1993 

2) Vandermeulen and Jotcham 1986 

3) Baca et al. 1987 

4) Burns and Teal 1979; Teal et a/ . 1992 

5) Hampson and Moul 1978 

Aug, 1974 none >20 yr 

Sept. 1974 sediment > 11 yr 

removal 

manual <11 yr 

burning 

digging 

March, sediment 5 - > 8 yr 

1978 removal 

Sept ,1969 ? > 8 yr 

Oct, 1974 ? > 3 yr 

156 
Table 2. 

Examples of oil-impacted marshes with recovery times of 3 years or less, documented 

by follow-up studies. 

Location Vegetation Oil type Date of Cleanup 'Recovery 

oiling time' 

Hackensack Spartina alterniflora No . 6 fuel May, 1976 none 

estuary, NJ cutting 

Wellen tank 

farm' 

Galveston Bay, Spartina alterniflora light crude Jan, 1984 none 

TX, Dickinson Juncus roemerianus sorbents 

Bayou pipeline Z flushing 

Harbor Is ., TX Spartina alterniflora crude oil Oct, 1976 none 

Am Petrofina Avicennia germinans sorbents 

pipeline 3 burning 

clipping 

Aransas River Spartina alterniflora S. Texas light Jan, 1992 burning 

Chilitpin Creek ` crude 

Neches River, Spartina patens Arabian crude Jan, 1979 none 

TX sorbents 

Esso Bayway 5 flushing 

burning 

cutting 

8 mos -

> 2 .5 yrs 

6 mos-

> 6 mos 

> 2 yr 

7 mos 

> 7 mos 

Neches River, Spartina alterniflora light crude April, 1993 none ? 

TX sorbents 

Unoca/ 6 flushing 

Nairn, LA Spartina patens Louisiana crude April, 1985 flushing < 1 .5 yr 

She// pipe/ine ' Spartina alterniflora trampling 

Distichlis spicata 

1) Mattson et al. 1977 

2) Alexander and Webb 1987 

3) Holt et al . 1978 

4) Tunnell and Hicks 1994, Gonzalez and Lugo 1994 

5) McCauley and Harrel 1981, Meyers 1981, Neff et al . 

1981 

6) NOAA 1993 

7) Mendelssohn et al . 1990, Fischel et al . 1989 

157 
Table 3 . 

Data from field studies on impacts to marsh vegetation from experimental, singledose oiling . 

Location Vegetation Oil type Time of Cleanup 'Recovery 

oiling time' 

Galveston Bay, Spartina alterniflora Arabian crude Nov. none 1 yr 

TX (1) Libyan crude 1 yr 

No . 6 fuel 1 yr 

No . 2 fuel 2 yr 

Louisiana (2) Spartina alterniflora S. La . crude June none 3 mos 

flushing 3 mos 

cutting 2 .5 yr 

York River, VA Spartina altemiflora S. La . crude: Sept . none > 1 yr 

(3) fresh 

/weathered 

St . Louis Bay, Juncus roemerianus Empire Mix March none 1-3 yr 

MS (4) crude 

Saudi crude 

1) Webb et al. 1985 

2) DeLaune et al . 1984 

3) Bender et al . 1977 

4) de la Cruz et al. 1981 

158 
Table 4. 

Factors to consider when evaluating whether impacts to marshes from spilled oil are 

likely to be short-term (1-2 years) or longer . 

Evaluation factors 

Severity of impact 

oil persistence & toxicity 

Examples 

oil type 

surface area covered, thickness 

of plant oiled 

oil penetration in sediment 

type of marsh vegetation 

season of impact 

Oil residence time without cleanup 

weathering 

biodegradation "potential" 

Ability of marsh to self-recover 

sedimentation over oiled layer 

recolonization 

elevation 

environmental stresses 

substrate type, coarseness 

oil viscosity 

sensitivity of plants 

(annuals, perennials) 

growing season vs . dormant season 

exposure, tidal flushing 

precipitation 

oil type 

temperature/climate 

previous exposure to oiling 

deposition rate 

intact adult plants nearby 

reproductive strategy 

ideal for species or marginal? 

heavy rainfall, 

cold temperatures, 

drought 

159 
Table 4. con't 

Other cleanup concerns 

use of site 

(over short & long term) 

species of special concern 

impacts to adjacent areas 

human users 

ecological users 

migrants, endangered species 

mobility of remaining oil 

sensitivity of adjacent habitats 

160 
Table 5. 

Cleanup techniques used in marshes and their advantages and disadvantages. 

Advantages Disadvantages 

No response 

minimal impact potential oiling of birds or wildlife 

(if oil degrades quickly) oil may impact adjacent areas 

no physical impact heavy oils may degrade slowly or 

form asphalt 

Vacuum/pumping 

can remove large quantities of oil access /deployment of equipment 

physical impacts 

Low pressure flushing 

assists in removal by herding oil requires careful monitoring 

lifts oil off sediment surface pressure must be controlled 

physical impacts 

Burning 

recent successes : Maine, Texas little known about specific conditions 

potential to remove oil quickly (season, inundation of marsh, plant species) 

minimizes physical impacts air pollution 

regulatory concerns 

Sediment removal 

may be only remediation for heavily oiled "destroy marsh to save it" 

sediments increased erosion potential 

elevation changes may impede 

regrowth of plants 

replanting necessary 

Vegetation cutting 

leaves most of plant intact may kill plant 

prevents oiling of birds potential for increased erosion 

must be monitored 

Bioremediation 

great theoretical potential few case studies available 

low impact potential for nutrient enrichment 

oxygen may be limiting 

161 
Session III. An Overview of Remediation Studies in the Gulf of Mexico 

Chair: Dr. Irving A. Mendelsshon 

Presentation Author / Affiliation 

Evaluation of Commercial Bioremediation 

Products for Oil Biodegradation in Salt 

Marshes 

The Development of Bioremediation for 

Oil Spill Cleanup in Coastal Wetlands: 

Product Impacts and Bioremediation 

Potential 

Bioremediation Studies: Effects on the 

Marsh Infaunal Community 

In-Situ Burn as an Oil Spill Response 

Technique 

Dr. R.W. Weavers 

Mr. B. Critesl 

Mr. S. Nerallal 

Mr. A. Wright' 

Dr . James Webb2 

1 Texas A&M University College Station 

2 Texas A&M University Galveston 

Dr. Irving A. Mendelssohnl 

Ms. Qianxin Linl 

Ms. Karolien Debusschere2 

Mr. Charles B. Henry, Jr.' 

Dr. Edward B. Overtone 

Dr. Shea Penlandl 

Dr. Ralph J. Portierl 

Dr. Nancy N. Rabalais3 

Ms. Maude M. Walshl 

1 Louisiana State University 

2 Coastal Environments, Inc. 

3 Louisiana Universities Marine 

Consortium 

Dr. Nancy N. Rabalais' 

Ms. Nazan Atilla2 

1 Louisiana Universities Marine 

Consortium 

2 Louisiana State University 

Mr. Gus Stacey 

Marine Spill Response Corp. 

163 
Evaluation of Burning as an Oil Spill 

Cleanup Technique in a High Marsh 

Community Along the South Texas 

Coast 

Fates of Oil in Salt Marsh Sediments 

Mr. Beau Hardegree 

Mr. David W. Hicks 

Dr. John W. Tunnell, Jr. 

Center for Coastal Studies 

Texas A&M University Corpus Christi 

Edward B. Overton, Charles B. Henry 

and Paulene Roberts 

Louisiana State University 

164 
Evaluation of Commercial Bioremediation Products for Oil Biodegradation 

in Salt Marshes 

R.W. Weaver', B. Critesl, S. Neralla', A. Wright', and J. Webb2 

1 Texas A&M University 

College Station, TX 

2 Texas A&M University 

Galveston, TX 

INTRODUCTION 

Bioremediation requires large populations of microorganisms to be effective in rapidly 

degrading high concentrations of organics. Often soil contains the necessary microorganisms for 

degrading compounds formed in nature (Alexander 1994) . Sometimes the microorganisms may 

not be present or are present but at population levels that are too low. In such cases it may be 

useful to bioaugment the populations to enhance the rate of bioremediation. Products that provide 

microorganisms or nutrients are commercially available to stimulate oil bioremediation . 

Studies on the role of bioaugmentation in the enhancement of biodegradation indicate some 

promise (Leahy and Colwell 1990) . Microbial degradation of oil appears to be the major process 

through which petroleum hydrocarbons are removed from the sediment environment (Zobell 

1946) . Some predominant hydrocarbon degrading bacteria found in soils are Pseudomonas, 

Achromobacter, Bacillus, Flavobacterium, and Nocardia (Leahy and Colwell 1990) . Inoculating 

a known oil-degrading strain of Pseudomonas resulted in increased biodegradation of oil (Atlas 

and Busdosh 1976). Antai (1990) reported that Bacillus sp. and Pseudomonas sp . were suitable 

for application in oil spill cleanup of the Nigerian terrestrial ecosystem . However, Venosa et al. 

(1992) found that indigenous Alaskan microorganisms were primarily responsible for the 

biodegradation of the weathered Alaska north slope crude oil. Dott et al. (1989) reported varying 

abilities of commercial cultures to degrade fuel oil . Introduction of new microorganisms into a 

polluted site does not always yield successful results . The potential success of inoculation in 

bioremediation depends on factors such as inoculant formulation, adaptation, inoculant 

concentration, and the availability of ecological niches (Pritchard 1992). 

Considerable oil transportation occurs along the Gulf Coast of Texas because of oil 

production and processing facilities (Geyer 1980) . Oil spills that occur in coastal marsh 

environments are difficult to remediate because they are fragile ecosystems which are susceptible 

to physical disturbances . The question arises as to whether commercial inoculants enhance the 

rate of bioremediation in coastal marsh environments. Such a question cannot be easily answered 

because relatively little data are available regarding the kinetics of bioremediation in marsh 

environments and the need for additional microorganisms . Each product must be evaluated on 

its own merit and under conditions that allow it to perform. Conditions must be suitable for 

microbial survival and development of biomass . Complete evaluation of any product is beyond 

the means of most laboratories and only preliminary investigations can be undertaken to see if 

there seems to be potential for using the products . 

165 
Because of environmental regulations it was not possible to intentionally spill oil in a 

marsh environment to test products, and it became necessary to approximate field conditions under 

laboratory and glasshouse conditions . The results of testing only pertain directly to the conditions 

under which the tests were performed and extrapolation to field conditions is limited . It is 

generally thought, however, that field conditions would be more rigorous and affect product 

performance . 

MATERIALS AND METHODS 

Soil 

Soil was collected from a salt marsh near Galveston, TX and is classified as a Follet 

series . The soil is a Hyperthermic Typic Haplaquent . For the laboratory experiment, soil was 

collected and screened wet to remove large debris . After screening, the soil was thoroughly 

mixed so that it would be homogeneous. For glasshouse experiments, soil was collected and 

placed directly into 7.5 L pots. 

Oil 

Arabian lubes crude oil was used for experimentation since it is commonly transported 

along the Gulf Coast . Oil was artificially weathered before experimentation so that it would more 

accurately mimic weathered oil that would be remaining for bioremediation following an actual 

spill. Oil was heated at 150°C for 8 h. Heating reduced the volume considerably and further loss 

by volatilization during experimentation was negligible . 

Bioremediation Products 

Ten commercial products from the list of products prepared by the US EPA as part of the 

National Contingency Plan Product Schedule were chosen for the investigation. The products 

used were Oppenheimer Formula I (Oppenheimer Environmental Corp., Austin, Texas) ; Munox712 (Osprey Biotechnics, Sarasota, Florida) ; Micro-Blaze Out (Verde Environmental Inc ., 

Houston, Texas) ; BioGEE HC Concentrate (BioGEE International, Inc., Houston, Texas) ; WMI 

2000 (Waste Microbes Inc ., Houston, Texas); Marine-D (Environmental Remediation, Inc ., 

Baton Rouge, Louisiana) ; Alpha Biosea (Alpha Environmental, Inc., Austin, Texas) ; Hydrobac 

(Polybac Corp., Bethlehem, Pennsylvania) ; Oil Spill Eater-II Concentrate (OSEI Corp., Dallas, 

Texas) ; and Mycobac-Tx 20 (Mycobac Inc ., Houston, Texas) . The products were numbered P1 

through P10 in the order mentioned. The products were prepared and applied according to the 

literature provided by the manufacturers. Larger quantities of products were prepared for 

application than were actually used so that a more representative sample of the product would be 

applied. 

166 
Enumeration of Hydrocarbon-Degrading Microorganisms 

Populations of hydrocarbon-degrading microorganisms were determined using a modified 

Sheen Screen Method (Brown and Braddock 1990). Basically it is a most probable number 

procedure (MPN). The diluent was a solution of 8.5 g NaCl L-1 . Serial dilutions of 10 with 

three tubes for each dilution were employed. Bushnell Haas medium (Bushnell and Haas 1941) 

was used in the tubes and the same weathered crude oil used in the experiments provided the 

carbon source . Tubes were considered positive if there was obvious turbidity due to microbial 

growth or if the oil layer was clearly dispersed or reduced. Tubes were incubated for 

approximately 1 month before final readings were made . 

Microcosm Experiment in the Laboratory 

The objective of this experiment was to determine the ability of commercial products to 

enhance oil bioremediation in flooded soil . Microcosms consisted of 0.47 L glass canning jars 

containing 60 g of soil and were kept flooded with approximately 1 cm of water above the soil 

surface. Oil was added to the surface of the water column to provide a layer approximately 0.5 

mm thick (1 .0 g oil) . A completely randomized experimental design was used with a factorial 

arrangement of treatments . Incubation temperatures were 10 and 30°C . Two control treatments 

were included and consisted of not applying fertilizer and applying 110 mg ammonium nitrate 

and 45 mg potassium phosphate to the water column. Duplicate microcosms of each treatment 

were processed at 21 d to determine the population of hydrocarbon-degrading microorganisms . 

The contents of the entire container were mixed with 200 ml of saline (8 .5 g NaCl L-') and 

placed on a reciprocating shaker for 30 minutes . Dilutions were made and populations enumerated 

as already described . 

At 90 d, oil and grease (O&G) and total petroleum hydrocarbons (TPH) were determined 

on duplicate microcosms of all treatments . Total oil and grease was extracted from the samples 

using dichloromethane . Oil in the water column and on the soil surface was extracted by adding 

20 ml of dichloromethane and rinsing the surface of soil and decanting. Oil in the soil was 

extracted by adding 20 ml of dichloromethane to the microcosm and thoroughly mixing into the 

soil and decanting. A second extraction was made and all extractions were combined. A portion 

of the final mixture (10 ml) was evaporated to dryness to gravimetrically determine oil and grease 

content. Total petroleum hydrocarbons were determined by dissolving oil and grease (obtained 

by evaporating 1 ml of the final mixture) in freon and passing it through a silica gel column and 

analyzing by infrared spectrophotometry . 

Mesocosm Experiments in the Glasshouse 

The objective of this experiment was to determine if addition of bioremediation products 

would aid in the bioremediation of oil in mesocosms. Mesocosms consisted of Spartina 

alterniflora growing in 7 .5 L pots that had been acclimated in a marsh for two months for the 

plants to become established under natural conditions before they were transported to the 

glasshouse . Pots containing the plants were placed inside 19 L containers and flooded with 

enough water for a 3 .5 cm layer over the soil surface . Water was added as needed to keep the 

167 
pots continuously flooded . Two experiments were conducted, one beginning in December and 

the other beginning in May so that a cool season and a warm season would be represented . The 

same bioremediation products were used in both experiments . 

Oil was added at a rate of 28 ml to each pot and formed a layer approximately 0.5 mm 

thick. A completely randomized experimental design was used with two replications . Treatments 

consisted of five commercial bioremediation products being applied singly and fertilized and nonfertilized controls . In the cool season, only ammonium sulfate was added for the fertilizer 

control treatment and it was added to the water column at a rate of 1 .12 g of N pot-1 . Nitrogen 

was applied in four equal split applications beginning the day after oil application. For the 

experiment conducted during the warm season, the fertilizer source for the control treatment was 

Max BacO CB24-89, a granular slow release commercial nutrient source for bioremediation, with 

an analysis of 25-5-0 (N-P-K) . It was obtained from Grace-Sierra Horticultural Products Co ., 

Milpitas, CA . The product is a mixture of ammonium nitrate, calcium phosphate, ammonium 

phosphate, and urea. It was added at a rate of 2 .24 g pot-1 (providing 0 .56 g N and 0.112 g P) 

to the surface of the water and it settled to the bottom of the water column onto the soil surface . 

Supplemental P was added as sodium phosphate to the water column to increase the amount of 

P by 20 kg ha' (0 .112 g P pot') . 

Populations of hydrocarbon-degrading microorganisms were determined at the time of 

harvest for the cool season experiment and at two and four weeks after the start of the warm 

season experiment. The determinations were made on water samples collected from various 

locations in the water column the day after water additions were made to maintain the water level . 

Mesocosms were destructively harvested on March 15 for the cool season experiment and 

on June 19 for the warm season experiment to collect residual oil . Plants were removed at the 

water level by clipping . Oil on the plant tissue was collected by rinsing tissue in dichloromethane 

and oil floating on the water surface was skimmed off. Some oil adhered to the sides of pots and 

was scraped off and combined with oil skimmed from the water surface and collected from plant 

material . The quantity of oil recovered was determined gravimetrically and percent TPH was 

determined by infrared spectrophotometry as described for the microcosm experiment . 

RESULTS AND DISCUSSION 

The fertilized control treatment incubated at 30°C contained the lowest quantity of TPH 

at 90 d (Fig . 1) . Only 17% of the TPH remained for this treatment while 74% remained for the 

unfertilized control treatment . Similar increases in oil biodegradation by fertilization were also 

reported by other workers (Dibble and Bartha 1979; Jobson et al . 1972) . Fertilization was not 

as beneficial for the microcosms incubated at 10°C since 60% of the TPH remained in the 

fertilized control treatment and 79% in the unfertilized treatment at 90 d . 

Only Product 4 significantly reduced the TPH below that of the unfertilized control when 

microcosms were incubated at 10°C but did not significantly reduce the TPH below that of the 

fertilized control (Fig . 1) . All products except Products 2 and 3 reduced the TPH below that of 

the unfertilized control when incubated at 30°C but no product was as effective as the fertilized 

control treatment in reducing TPH. Considerably more bioremediation occurred when microcosms 

were incubated at 30'C rather than 10'C . 

168 
The number of hydrocarbon degrading microorgansisms in treatments receiving products 

was not significantly larger at 21 d of incubation than the no product treatment at either 10 or 

30°C (data not shown) . The population size was not significantly different for the two 

temperatures . Addition of oil increased the populations from approximately 3 x 104 to 1 x 105 

cells g-1 soil . 

Neither product nor fertilizer application reduced the quantity of oil that remained in 

mesocosms at the end of the glasshouse experiment conducted during the cool season (Fig . 2). 

On average, 24% of the added oil remained at the end of the experiment. The second mesocosm 

experiment was conducted during the warm season and visual inspection indicated that the oil 

began disappearing more rapidly than in the cool season experiment . Therefore, the incubation 

time was reduced from 98 d of the previous experiment to 33 d to better reveal which products 

increased bioremediation most rapidly . No product reduced the quantity of oil remaining at 33 

d significantly more than that in the fertilized control treatment (Fig. 3) . The percentage of oil 

remaining for the fertilized control treatment was 33 and the average percentage of oil remaining 

for the other treatments was 51 . In this experiment both N and P were provided as fertilizer 

because in the cool season experiment no response was obtained to nitrogen fertilization alone . 

Perhaps P was needed more than N. Products contained both N and P, but the quantity provided 

was much lower than that provided for the fertilized control treatment. Populations of 

hydrocarbon-degrading microorganisms were not influenced by treatments except that addition of 

oil to mesocosms increased populations of hydrocarbon-degrading microorganisms by 

approximately 10 times. 

SUMMARY 

Experiments were conducted under laboratory and glasshouse conditions to evaluate 

effectiveness of commercial products in enhancing bioremediation of oil spilled onto water 

columns over soil . One product of ten increased oil bioremediation in the laboratory in 

comparison to the unfertilized control but no product was as effective as the fertilizer in the 

fertilized control treatment. The population size of hydrocarbon-degrading microorganisms was 

not influenced by bioremediation products. The experiment conducted during both cool and warm 

seasons in the glasshouse indicated that the products did not significantly enhance bioremediation . 

Disappearance of oil during the warm season was more rapid than during the cool season . Soil 

from the Gulf Coast apparently contained adequate populations of hydrocarbon-degrading 

microorganisms necessary for bioremediation . 

REFERENCES 

Alexander, M. 1994 . In, Biodegradation and bioremediation . California : Academic Press, Inc . 

Antai, S.P . 1990. Biodegradation of bonny light crude oil by Bacillus sp . and Pseudomonas sp. 

Waste Management 10 : 61-64 . 

169 
Atlas, R.M . and M. Busdosh. 1976. Microbial degradation of petroleum in the Arctic . pp . 79-

86 . In, J .M . Sharpley and A.M . Kaplan (eds .) . Proceedings of the Third International 

Biodegradation Symposium. London: Applied Science Publishers Ltd. 

Brown, E.J . and J .F . Braddock. 1990 . Sheen screen, a miniaturized most-probable-number 

method for enumeration of oil-degrading microorganisms . Appl. Environ. Microbiol. 56 

(12) : 3895-3896 . 

Bushnell, L.D ., and F.F . Haas . 1941 . The utilization of certain hydrocarbons by 

microorganisms. J. Bacteriol . 41 : 653-673 . 

Dibble, J.T ., and R.Bartha. 1979 . Effect of environmental parameters on the biodegradation of 

oily sludge . Appl. Environ . Microbiol. 37 : 729-739. 

Dott, W., D. Fiedieker , P. Kampfer, H. Schleibinger, and S . Strechel . 1989. Comparision of 

autochthonous bacteria and commercially available cultures with respect to their 

effectiveness in fuel oil degradation. J. Ind. Microbiol. 4 : 365-374. 

Geyer, R.A. 1980 . Introduction. pp . 1-18 . In, R.A . Geyer (ed.) . Marine Environmental 

Pollution, Vol . 1, Hydrocarbons . Amsterdam: Elsevier Scientific Publishing Co . 

Jobson, A., F.D. Cook, and D.W.S . Westlake . 1972. Microbial utilization of crude oil . Appl. 

Environ. Microbiol. 23 : 1082-1089 . 

Leahy, J .G. and R.R. Colwell. 1990. Microbial degradation of hydrocarbons in the 

environment. Microbiol. Rev. 54(3) : 305-315 . 

Pritchard, P.H. 1992 . Use of inoculation in bioremediation . Current Opinion in Biotechnology 

3 : 232-243 . 

Venosa, A., J.R. Haines, W. Nisamaneepong, R. Govind, S . Pradhan, and B. Siddique . 1992 . 

Efficacy of commercial products in enhancing oil biodegradation in closed laboratory 

reactors . J. Ind. Microbiol. 10: 13-23 . 

Zobell, C.E. 1946. Action of microorganisms on hydrocarbons. Bacteriol. Rev. 10 : 1-49. 

170 
rn 

c 

c 

E 

Z 

a 

N 

v 

v 

v 

Q 

100 

90 

SO 

70 

60 

50 

40 

30 

20 

10 

0 

C CF P1 P2 P3 P4 PS P6 P7 P8 P9 P10 

Treatment 

Figure 1 . Percentage of added total petroleum hydrocarbons (TPH) remaining in 

microcosms that were unfertilized (C), fertilized (CF), and those treated with 10 

bioremediation products (P1-P10) 90 d following incubation at 10 and 30° C. 

171 
40 

30 

c 

A 

E 

p~ 20 

O 

10 

0 

LSD = 20 

C CF P1 P3 P4 P7 P9 

Treatment 

Figure 2. Percentage of added oil remaining at 98 d in mesocosms that were 

unfertilized (C), fertilized (CF), and those treated with bioremediation products 

(P 1, P3, P4, P7 and P9) and maintained in a glasshouse during the cool season . 

172 
60 

c 

40 

E 

p~ 30 

20 

0 

LSD = 14 

50 

10 

C CF P1 P3 P4 P7 P9 

Treatment 

Figure 3 . Percentage of added oil remaining at 33 d in mesocosms that were 

unfertilized (C), fertilized (CF), and those treated with bioremediation products 

(P 1, P3, P4, P7 and P9) and maintained in a glasshouse during the warm season . 

173 
The Development of Bioremediation for Oil Spill Cleanup in Coastal 

Wetlands : Product Impacts and Bioremediation Potential 

Irving A. Mendelssohn', Qianxin Linl, Karolien Debusschere2, 

Charles B. Henry, Jr.', Edward B. Overton3, S. Penland4, 

Ralph J. Portier', Nancy N. Rabalaiss, and Maude M. Walsh3 

1 Wetland Biogeochemistry Institute 

Center for Coastal, Energy and Environmental Resources 

Louisiana State University 

Baton Rouge, Louisiana 70803 

2 Coastal Environments, Inc. 

1260 Main Street 

Baton Rouge, LA 70802 

3 Institute for Environmental Studies 

Center for Coastal, Energy and Environmental Resources 

Louisiana State University 

Baton Rouge, Louisiana 70803 

4 Coastal Studies Institute 

Center for Coastal, Energy and Environmental Resources 

Louisiana State University 

Baton Rouge, Louisiana 70803 

5 Louisiana Universities Marine Consortium 

8124 Highway 56 

Chauvin, LA 70344 

Note : This paper has been published in the 1995 Proceedings of the International Oil Spill 

Conference and is reprinted with permission of the American Petroleum Institute . 

INTRODUCTION 

The northern Gulf Coast of the United States is a region of intense oil exploration, 

production and transmission . Consequently, coastal states, such as Louisiana, are subject to 

oil spills resulting from shipping accidents, production-related incidents, and pipeline 

ruptures . Since these incidents often occur in the nearshore environment, coastal salt marshes 

are frequently the first wetland habitats to be subjected to the oil. As a result, a large 

number of investigations have documented the effect of petroleum hydrocarbon spills on the 

dominant salt marsh plant species, Spartina alterniflora (for example, Hershner and Lake 

1977 ; Lee et al. 1981 ; Alexander and Webb 1983 ; Ferrell et al. 1984 ; Mendelssohn et al. 

1990). In addition, some investigations (e.g., DeLaune et al. 1984) have evaluated the 

174 
impact of oil cleanup procedures in salt marshes . Not only can petroleum hydrocarbons have 

detrimental impacts on coastal marshes, but additionally, the cleanup of the oil from these 

highly sensitive environments is often more damaging that the oil itself . Hence, it is more 

important to develop less intrusive oil spill cleanup procedures that exert little or no impact 

on wetland ecosystems . 

Bioremediation, the act of adding materials to contaminated environments, such as oil 

spill sites, to cause an acceleration of the natural biodegradation process (U.S . Congress 

1991) is a promising means by which oil released into salt marshes, as well as other wetland 

types, can be removed with little or no impact to the habitat . Bacteria, cultured and selected 

for high rates of oil degradation, and fertilizers, which enhance native microbial activity, are 

two types of bioremediation products that can be added to oil contaminated wetlands . 

Although data in the scientific literature demonstrating the relative effectiveness of 

bioremediation as an oil cleanup procedure in wetlands is lacking, a number of studies have 

demonstrated, in general, the potential for enhanced oil degradation as a result of 

bioremediation, especially through nutrient additions (for example, Tabak et al. 1991 ; 

Safferman 1991 ; Lee and Levy 1987 ; Lee and Levy 1991 ; Bragg et al. 1993 ; Lee et al. 

1993) . Specifically for wetlands, Schemer and Mille (1990) confirmed enhanced degradation 

of oil in a West Indies mangrove swamp after the addition of an oleophilic fertilizer. 

Similarly, Lee and Levy (1991) found enhanced degradation of oil, this time in salt marsh 

sediments, treated with inorganic nutrients . However, critical evaluations of oil 

bioremediation potential, based on oil chemical analyses that can unequivocally identify 

enhanced biodegradation, in wetland environments are lacking in the published literature. 

Microbial seeding as a means of enhancing oil biodegradation, has even greater 

uncertainties associated with it, especially in systems such as wetlands where hydrocarbon 

degrading bacteria are naturally prevalent. For example, microbial seeding was used in an 

experimental mode to test its effectiveness in cleaning up an oil spill in a marsh (Marrow 

Marsh) in Galveston Bay. The reported results did not indicate that the microbial seeding 

significantly degraded oil at this marsh site (Mearns 1991) . In a recent investigation (Venosa 

et al. 1992) two microbial products, which exhibited enhanced biodegradation of Alaska 

North Slope crude oil in shaker flask tests, did not accelerate biodegradation in a field 

experiment conducted on an oiled beach in Prince William Sound, although the high 

variability in the data, the highly weathered nature of the oil, and a lack of sufficient time for 

biodegradation were cited as possible reasons for the lack of response. Regardless of these 

equivocal results, many microbial products have been commercialized . If added microbes, 

per se, are not effective in increasing oil degradation, the high costs of microbial 

amendments may not be warranted. Oil response agencies, both public and private, require a 

critical evaluation of microbial seeding in enhancing oil biodegradation . Finally, the 

ecological impacts of these amendments, microbial as well as fertilizer, must be identified . 

A multi-disciplinary, multi-investigator research program has been initiated to address 

the question: Is bioremediation, via fertilizer or microbial seeding, an effective and 

ecologically safe means of oil spill cleanup in coastal wetlands? The specific objective of 

this paper is to summarize the overall scope of the study and to present some preliminary 

findings concerning marsh plant response to the bioremediation agents . 

175 
PROJECT GOAL AND APPROACH 

The overall goal of the proposed project is to determine the potential for the use of 

bioremediation as a oil-spill cleanup technique in wetlands . Specifically, we shall determine 

the effects of both fertilization and microbial seeding on (1) petroleum hydrocarbon 

degradation and (2) the impacts, if any, of these spill cleanup methods on the wetland. To 

accomplish the preceding goal, we have divide the project into three phases (Figure 1) : 

Phase 1 . Project Design - This component, whose objective was to design the Phase 2 

efforts, was funded by Exxon and has been completed ; this paper is the result of that 

effort . 

Phase 2. Greenhouse Bioremediation Trials - The present paper describes the first 

experiment within the Phase 2 effort to determine the potential for oil spill 

bioremediation in wetland mesocosms . This phase of the research consists of four 

tasks described below and is being funded jointly by Exxon USA and the Minerals 

Management Service's Coastal Marine Institute at Louisiana State University . 

Phase 3 . Field Demonstration Project - If the greenhouse experiments indicate a 

potential for bioremediation of oil spills in wetlands, a field demonstration will be 

conducted . 

PROJECT DESCRIPTION 

Controlled greenhouse experiments, as well as field trials, are planned to test the 

efficacy and ecological safety of microbial seeding and fertilization as enhanced 

biodegradation methodologies. This three year study is designed to test the following aspects 

of bioremediation in coastal marshes : 

(1) Product Toxicity: Determine if the maximum allowable loading rate (as 

defined by the product manufacturer) of the selected bioremediation products 

generates adverse impacts on the wetland plants, infaunal animals and 

microbial communities . This experiment is required to ensure that the product 

loading rate suggested by the manufacturer is not toxic to wetland plants and 

estuarine animals . Only products on the National Contingency Plan (NCP) 

list, with defined maximum loading rates, will be used in this study . 

(2) Biode,gradation Potential : Determine the effect of fertilizer and microbial 

seeding on oil biodegradation in salt marsh soil mesocosms . This experiment 

is essential to determine the potential for enhanced oil degradation via 

bioremediation in salt marsh substrates and is the first step before large scale 

field trials . 

176 
(3) Marsh Soil Type : Determine to what extent product-enhanced oil 

biodegradation is modified by marsh soil type. Salt marsh soils, depending on 

their texture and specific microbial communities, may exhibit different 

capacities for bioremediation which must be quantified in order to access the 

variability in bioremediation potential of salt marshes. 

(4) Product Reapplication: Determine (a) if product reapplication is required to 

maintain an enhanced rate of biodegradation and, thus, to maximize total 

hydrocarbon degradation and (b) whether reapplication rate is a function of the 

initial oil dosage. Reapplication of the fertilizer bioremediation product is 

likely during a real cleanup operation . Thus, the efficacy of reapplication as a 

means of maintaining maximum biodegradation rates at a different oil dosing 

levels will be evaluated . 

(5) Field Bioremediation Trial: Determine, under real-world conditions, the degree 

to which the potential for bioremediation demonstrated in the greenhouse 

marsh mesocosms is realized in the field. This experiment will be designed to 

assess bioremediation in both streamside salt marshes, where subsurface 

hydrology is a relatively active, and immediately adjacent inland salt marshes, 

where subsurface hydrology is minimal . Both bioremediation efficacy and 

ecological safety will be evaluated . 

The effectiveness of bioremediation and its ecological safety will be assessed in the 

above experiments by evaluating the following : (1) petroleum hydrocarbon chemistry to 

identify and quantify the degree of oil biodegradation (Overton and Henry), (2) oil 

morphology, which will be related to oil chemistry, as an inexpensive means of evaluating 

oil biodegradation (Debusschere), (3) soil microbial response to determine the effect of the 

bioremediation products on the microbial communities that are performing the oil 

biodegradation (Portier and Walsh), (4) soil chemistry to determine the effect of the 

bioremediation products on those factors that limit the growth of microbes and plants (e .g. 

nutrients, soil reducing conditions and soil toxins) (Mendelssohn), and (5) plant and infaunal 

response to evaluate the combined effects of the oil and products on plant and animal 

components of the marsh system (Mendelssohn and Rabalais) . 

IDENTIFICATION OF PRODUCT TOXICITY AT MAXIMUM LOADING RATE 

Objective and Rationale 

This experiment is designed to determine if the maximum allowable loading rate of 

the selected bioremediation products generate adverse impacts to wetland plants, infaunal 

animals and microbial communities . We specifically ask the question : Can bioremediation be 

used for oil spill cleanup without causing negative impacts to wetland structure and function? 

Selected plant and soil responses are presented. 

177 
Experimental Design and Methods 

Sods of marsh (soil and vegetation intact), approximately 28 cm in diameter (0.06 m2) and 

30 cm deep, were collected from the inland zone (approximately 5 m from the creekbank 

natural levee) of a Spartina alterniflora dominated salt marsh located west of Cocodrie, 

Louisiana and used as the experimental units. Inland sods were chosen because the inland 

zone comprises the largest aerial extent of most salt marshes. We recognize that soil type 

will likely influence bioremediation, and, thus, this factor will be examined in future 

research . Spartina alterniflora is the dominant intertidal salt marsh grass along the Atlantic 

and Gulf Coasts of the United States and thus result from this study will be generally 

applicable to many other salt marshes . 

In the greenhouse, the following treatments were randomly assigned to the collected 

sods: (1) fertilizer product, (2) seeding product, and (3) control (Table 1) . The experimental 

design was a randomized block with a 3 x 2 factorial treatment arrangement (three 

bioremediation types [mentioned above] and two oil dosage levels [oiled with 11/m2 (lmm of 

oil thickness) and control) (Table 1) . Each treatment combination was replicated five times 

for a total of 30 sods of marsh. Analysis of variance was used to test for statistically 

significant differences (P < 0 .05) among the treatments . 

A reduced crude with nC-13 and below removed in order to stimulate oil spilled in 

open water and subsequently transported into a salt marsh by winds or tides was added to the 

surface water of the mesocosms. The water was then drained from the bottom of the pots to 

allow the oil to come in contact with the surface of the sods. The bioremediation products 

utilized were those proven to be most successful in enhancing oil biodegradation from marsh 

sediment-microcosm experiments performed by Ms . Sara McMillen of Exxon Production 

Research, Houston as part of Phase I of this project. This work employed both respirometry 

and oil chemistry (GC-FID) to identify enhanced oil biodegradation . The results indicated 

that Customblen, a fertilizer product used during the Valdez Spill and Petrobac, a microbial 

product, show promise as bioremediation agents . Thus, we used these two products in the 

present experiment. 

The Costomblen used in this study contained 28% N and 8 % P as ammonium nitrate, 

calcium phosphate and ammonium phosphate (Bragg et al . 1992) . Petrobac contains 

microbes, without any fertilizer, selected for hydrocarbon degradation in a saline medium (R. 

Drake, Polybac Corp., personal communication). The products were applied to the soil 

surface in a manner similar to that during a field application and following the 

manufacturer's specifications (Customblen : 93 g M-2; Petrobac :0.8331 M-2 of inoculum [46 g 

of Petrobac 1-' of deionized water]) . The sod-mesocosms were kept moist, but drained by 

maintaining an average water level at 5 cm below the soil surface . Water levels were 

allowed to fluctuate due to evapo-transpiration, but they were reflooded daily with deionized 

water to 5 cm below the soil surface to maintain relatively constant salinities . 

Plant responses were measured during a three month period (at 0, 1, 2, 4, 8, and 12 

weeks after product addition) to determine the effect , if any, of product addition on plant 

growth and photosynthesis (a highly sensitive indicator of plant response to stress) . Soil 

respiration was determined with an infra-red gas analyzer by measuring carbon dioxide 

production in a flow through respiration chamber placed over the soil surface . Microbial, 

178 
infaunal, and soil chemical responses were also evaluated and will be presented in future 

publications . 

RESULTS 

The effect of the bioremediation products and oil on the growth response of Spartina 

alterniflora was assessed by determining leaf elongation and photosynthetic (leaf C02 

exchange) rates . Bioremediation had a significant effect on both leaf elongation (Figure 2) 

and photosynthesis (Figure 3) . The bioremediation effect was due to the fertilizer product 

which significantly increased leaf elongation and net C02 exchange rates (photosynthesis) 

above the control, regardless of the presence of oil (Figures 2 and 3) . The addition of the 

microbial product had no significant effect on the plant growth responses (Figures 2 and 3) . 

These results demonstrate that the bioremediation agents tested were not toxic to the 

vegetation . In fact, the fertilizer product, Customblen, stimulated plant growth , a response 

that was not unexpected. The addition of a reduced crude oil to the marsh mesocosms had 

no significant impact on plant responses (Figures 2 and 3), and there was no significant 

interaction between bioremediation products and the oil . 

In situ respiration was measured in order to identify if the bioremediation agents were 

affecting the metabolism of the soil community . The living soil community is composed of 

bacteria, fungi, invertebrates and roots of Spartina alterniflora . The fertilizer treatment had 

a significant positive effect on soil respiration compared to both the control and the microbial 

treatments (Figure 4) . The soil respiration of the microbial treatment, however, was not 

significantly different from that of the control (Figure 4) . Oil addition also had a significant 

effect on soil respiration, with the oiled mesocosms exhibiting significantly higher soil 

respiration than the unoiled mesocosms (Figure 5) . The increase in soil respiration due to 

the fertilizer and oil treatments could be a response to either increased microbial activity or 

to greater root density within the soil . Although we presently cannot separate the two, soil 

cores have been collected from the sods and root density will be evaluated in an attempt to 

separate these factors . 

SUMMARY AND CONCLUSIONS 

l . The fertilizer product significantly increased the growth response of Spartina 

alterniflora and the rate of soil respiration, while the microbial product did not 

significantly affect either of these processes . 

2. Oil significantly increased soil respiration, but had no influence on plant 

growth. 

3 . The bioremediation products tested did not negatively impact plant growth 

response, and , therefore they appear to have no toxic affect to the application 

rates used in this investigation. 

4. The results of this investigation, in conjunction with our findings from ongoing 

179 
bioremediation experiments, will help to determine if bioremediation is a 

suitable oil spill cleanup technique in the wetland environment. 

REFERENCES 

Alexander, S.K. and J.W . Webb, Jr . 1983 . Effects of oil on growth and decomposition of 

Spartina alterniflora . pp . 529-532 . In, Proceedings of 1983 Oil Spill Conference, 

American Petroleum Institute, Washington, D.C. 

Bragg, J.R.,R.C . Prince, J.B . Wilkinson and R.M . Atlas. 1992 . Bioremediation for shoreline 

cleanup following the 1989 Alaska oil Spill . Exxon Company, USA, Houston, TX . 

94pp . 

Bragg, J.R., R.C . Prince, E.J . Harner, and R.M. Atlas . 1993 . Bioremediation effectiveness 

following the Exxon Valdez spill . pp.435-447 . In, Proceedings of the 1993 Oil Spill 

Conference, American Petroleum Institute, Washington, D.C . 

Delaune, R.D ., C.J . Smith, W.H . Patrick, Jr.,J. W. Fleeger and M.D . Tolley . 1984. Effect 

of oil on salt marsh biota : Methods for restoration. Environ. Pollut . 36 : 207-227 . 

Ferrell, R. E. , E. D. Seneca, and R. A. Linthurst. 1984. The effects of crude oil on the 

growth of Spartina alterniflora Loisel and Spartina cynosuroides (L.)Roth . Journal of 

Experimental Marine Biology and Ecology 83 : 27-29 . 

Hershner, C. and J. Lake . 1977 . Effects of chronic oil pollution on a salt marsh grass 

community . Marine Biology 56 : 163-173 . 

Lee, R.F ., B. Dornseif, F. Gonsoulin, K. Tenore and R. Hanson. 1981 . Fate and effects of 

a heavy fuel oil spill on a Georgia salt marsh . Marine Environmental Research 5 : 

125-143 . 

Lee, K, and E.M . Levy . 1987 . Enhanced biodegradation of a light crude oil in sandy 

beaches . pp. 411-416 . In, Proceedings of the 1987 Oil Spill Conference, American 

Petroleum Institute . Washington,D .C. 

Lee, K and E.M . Levy . 1991 . Bioremediation: waxy crude oils stranded on low-energy 

shorelines. pp . 541-524 . In, Proceedings of 1991 Oil Spill Conference, American 

Petroleum Institute, Washington, D.C. 

Lee, K, G.H . Tremblay and E.M . Levy . 1993 . Bioremediation: Application of slow release 

fertilizers on low-energy shorelines. pp . 449-454 . In, Proceedings of the 1993 Oil 

Spill Conference, American Petroleum Institute, Washington, D.C. 

180 
Mearns, A. 1991 . Observations of an oil spill bioremediation activity in Galveston Bay, 

Texas . NOAH Technical Memorandum NOS OMA 57, Seattle Washington, 38 p. 

Mendelssohn, I .A., M.W . Hester, and C. Sasser . 1990. The effect of a Louisiana crude oil 

discharge from a pipeline break on the vegetation of a southeast Louisiana brackish 

marsh. Oil and Chemical Pollution 7 : 1-15 . 

Safferman, S.I . 1991 . Selection of nutrients to biodegradation for the remediation of oil 

spilled beaches . pp . 571-576. In, Proceedings of the 1991 Oil Spill Conference, 

American Petroleum Institute, Washington, D.C . 

Schemer, P. and G. Mille . 1990. Biodegradation of crude oil in experimentally-polluted 

clayey and sandy mangrove soils . Oil and Chemical Pollution 6: 163-176 . 

Tabak, H.H., J.R. Haines, A.D. Venosa, and J.A . Glaser . 1991 . Enhancement of 

biodegradation of Alaskan weathered crude oil components by indigenous microbiota 

with the use of fertilizers and nutrients . pp . 583-590. In, Proceedings of the 1991 

Oil Spill Conference, American Petroleum Institute, Washington,D.C . 

U.S. Congress, Office of Technology Assessment . 1991 . Bioremediation for marine oil spills 

- Background paper . OTA-BP-O-70, Washington, D.C . U.S . Government Printing 

Office . 32 pp . 

Venosa, A.D ., J.R. Haines, and D.M. Allen. 1992. Efficacy of commercial inocula in 

enhancing biodegradation of weathered crude oil contaminating a Prince William 

Sound beach. J. Industrial Microbiology 10 : 1-11 . 

181 
Table 1 . 

Experimental design for Task 1 . The three bioremediation treatments (fertilizer, microbial 

seeding, and control) were applied to both oiled and unoiled marsh sods . 

Fertilizer Microbial Seeding Control 

No Oil 5 replicates 5 replicates 5 replicates 

Oil 5 replicates 5 replicates 5 replicates 

182 
PHASE 1 . PROJECT DESIGN 

Objective : Design bioremediation 

trials for Phase 2 and 3 . 

PHASE 2. GREENHOUSE BIOREMEDIATION TRIALS 

Objective: Design comprehensive multi-experimental 

investigation to test the safety and efficacy of bioremediation. 

Task 1 . Identification of Product Toxicity at Maximum 

Loading Rates 

Task 2. Effect of Bioremediation on Oil Biodegradation 

Task 3. Effect of Soil Type on Oil Biodegradation 

Task 4 . Effect of Product Reapplication on Oil Biodegradation 

PHASE 3. FIELD DEMONSTRATION PROJECT 

Objective: Test bioremediation efficacy 

and safety under field conditions . 

Figure 1 . The overall project was designed in three phases : Phase I - Project Design has 

been completed ; Phase 2 - Greenhouse Bioremediation Trials are ongoing ; 

Phase 3 - Field Demonstration Project will be pursued if the greenhouse trials 

indicate a potential for bioremediation . 

183 
3 

r 

C 

CZ 

C 

O 

CO 

C 

O 

W 

J 

0 

Bioremediation Treatments 

Figure 2. The response of leaf elongation rate to bioremediation and oil treatments 

(C=no bioremediation product, M=microbial product, F=fertilizer product; 

+ indicates oil added, - indicates no oil) . Means of 5 replicates and standard 

error bars are presented. 

184 

G C+ M- M+ F- F+ 
20 

15 

N 

E 

x ~ 10 

w 

N 

U 

5 

Treatments 

Figure 3 . The effect of bioremediation and oil treatments on net leaf C02 exchange rate 

(C=no bioremediation product, M=microbial product, F=fertilizer product; 

+ indicates oil added, - indicates no oil) . Means of 5 replicates and standard 

error bars are presented. 

185 

C- C+ M- M+ F- F+ 
1 .6 

1 .2 T 

O N 

-i~ E 

L 

Q N 0. U) 0 

°) U 

'o 

v) o 

E 0.4 

Bioremediation Treatment 

Figure 4. The effect of the bioremediation products, averaged over oil treatments, on 

soil respiration rate (C=no bioremediation product, M=microbial product, 

F=fertilizer product; + indicates oil added, - indicates no oil) . Means of 10 

replicates and standard error bars are presented. 

186 

M C F 
1 .6 

T 

C 

z- O N I 

. Co 

L. 

~Q. N 

N O 

U 0 .8 

-o 

cn o 

E 

0 

Oil Treatment 

Figure 5 . Soil respiration as a function of oil addition (+Oil, -Oil) . Means of 15 

replicates and standard error bars are presented. 

187 
Bioremediation Studies - Effects on the Marsh Infaunal Community 

Nancy N. Rabalaisl and Nazan Ati11a2 

' Louisiana Universities Marine Consortium 

2 Louisiana State University 

INTRODUCTION 

Wetland habiats, when subjected to oil spills, may be impacted either directly by the 

petroleum hydrocarbons or by physical or chemical removal of the oil through various 

cleanup attempts. Bioremediation, the act of adding materials to contaminated sediments, 

such as oil spill sites, to cause an acceleration of the oil biodegradation process is a 

promising methodology for restoring oil contaminated environments . 

The studies of the effects of chemical discharges, oil spills and bioremediation 

treatments for oil spills have necessarily focused on the benthos, because (1) they are 

relatively sedentary, (2) their life spans, depending on the organism, may be long enough to 

integrate water/sediment quality conditions or short enough to respond to changes in the 

environment, (3) different species or taxonomic gropups exhibit different tolerances to stress, 

(4) they are an important component of the food web, and (5) they function in the cycling of 

nutrients and other chemicals between the sediment and water column . 

A comprehensive, multi-disciplinary experimental program (I . Mendelssohn et al .) is 

underway as part of the Louisiana State University, Coastal Marine Institute, to examine 

microbial seeding and fertilizers as a means of oil spill cleanup in coastal salt marshes. 

During the first year's effort, currently in progress, controlled greenhouse experiments are 

being used to determine product toxicity on wetland plants, infaunal organisms, and 

microbial communities. The objectives of our research are to determine the effects of the 

bioremediation products, the oil, and/or the interaction of the bioremediation products with 

the oil on the indigenous salt marsh meio- and macroinfaunal communities. 

STUDY DESIGN 

Sods of marsh grass (Spartina alterniflora) were collected from an inland marsh west 

of the LUMCON Marine Center in Cocodrie, Louisiana and transported to a greenhouse at 

Louisiana State University . In the greenhouse, randomly assigned treatments were set up in 

a 3 x 2 factorial design to test for the effects of oil vs. no oil, and for the effects of fertilizer 

addition, microbial seeding, or no treatment. Five replicates of each treatment were 

established and are shown in the following chart. 

188 
Fertilizer Microbial Control 

Seeding 

No Oil 5 replicates 5 replicates 5 replicates 

Oil 5 replicates 5 replicates 5 replicates 

Macroinfauna will be collected in 3-in diameter core tubes to a depth of 10 cm. Five 

replicates from similarly treated plots were taken prior to the beginning of the experiment. 

One core from each replicate plot will be taken at the termination of the experiment. 

A series of studies are being conducted on the meiofaunal component of the 

experiment . A comparison of meiofauna cores taken from the marsh will be compared to 

cores taken from acclimated plots in the greenhouse, to determine the effects of acclimation 

period on the meiofauna community. Fifteen replicates from the field will be compared to 

15 of the 30 replicates in the greenhouse plots. These cores will also quantify the variability 

in meiofaunal communities. 

A simple experiment was conducted on extra greenhouse plots to determine where the 

majority of the meiofauna were distributed vertically in a core. Splits of cores were made at 

0-1, 1-2, 2-3, and 3-4 cm. We determined that most of the meiofauna were in the upper 3 

cm of the cores ; this protocol was used for the remainder of the experiment. 

For the definitive experiment, meiofauna were collected with a bulk density coring 

device, approx . 2-cm diameter, to depth of 3 cm at day 0, 1 week, 2 weeks, 4 weeks and 

12 weeks. When a meiofuana core is removed from a greenhouse plot, a core from a 

similarly treated plot is used to replace it . The area of the replaced core is not resampled on 

subseuqent dates. 

Time Table for Experiment: 

Sod collection from marsh - March 22, 1994 

Vertical distribution of meiofauna, post-acclimation effects - May 2, 1994 

Day 0 - post-acclimation effects, initial status - May 12, 1994 

1 Week - May 20, 1994 

2 Week - May 27, 1994 

1 Month - June 10, 1994 

3 Month - August 5, 1994 

Standard meiofauna and macroinfauna processing techniques will be used to determine 

taxonomic composition and abundance of organisms . Benthos responses will be tested by 

determining changes in abundance, species composition, diversity, population structure (adult 

vs. juvenile, presence of eggs), taxonomic composition, and, possibly, size of nematodes . 

189 
RESULTS 

As can be seen from the above schedule, the experiment is currently in progress . 

Preliminary results from a limited number of meiofauna cores indicates no dramatic toxicity 

of any treatment within one week of experiment initiation . Expected effects may be seen in 

an initial toxicity of oil to copepods, but possibly not nematodes . There may be an organic 

stimulation of the meiofaunal community from either oil, microbes, or microbes stimulated 

by fertilizer additions . 

ACKNOWLEDGMENTS 

Acknowledgments are due to the U. S. Minerals Management Service and Exxon 

Corporation funding to the Louisiana State University, Coastal Marine Institute, for project 

funding and to the Louisiana Universities Marine Consortium Foundation, Inc . for a 

Graduate Student Research Grant to Ms . Nazan Atilla . Dr . John Fleeger, LSU, has provided 

expertise and insight into the conduct of the meiofaunal sampling . 

190 
In-Situ Burn as an Oil Spill Response Technique 

Gus Stacey, III' 

Marine Spill Response Corp. 

Lake Charles, LA 

Current Address : 

Louisiana Oil Spill Institute 

P.0 .42411 

University of Southwestern Louisiana 

Lafayette, LA 

The Marine Spill Response Corp. (MSRC) is a national, not-for-profit corporation 

formed by the major oil companies and the American Petroleum Institute following the 

Alaskan- Exxon Valdez oil spill in 1989. MSRC will respond to catestrophic oil spills in 

certain U.S . coastal waters up to 200 miles offshore . 

In-situ burning is the deliberate ignition and controlled combustion of spilled oil "in 

place," or, under special circumstances, the allowing of an accidental burn to continue to 

burn. Prior to the early 1980s and the development of the fire resistent boom, the 

effectiveness of burning depended on other structures or forces such as docks, breakwaters, 

shorelines, winds, or ice to keep the oil thick enough to support combustion. 

After the advent of the fire-resistant boom, it was possible to collect spilled oil on the 

water and burn large quantities of oil with great efficiency . Experimental burns including 

small scale, meso-scale, and a few large-scale burns were under taken to learn more about 

this response technique . Three large-scale field burns, two experimental and one actual spill 

makeup the bulk of our present day knowledge about in-situ burning in a real world 

environment. These were the Trondheim, Norway experimental burn of 500 gallons in 1988; 

the Newfoundland Offshore Burn Experiment experimental burn involving two burns totaling 

approximately 20,000 gallons in 1994 ; and the burning of 15-20,000 gallons in Prince 

William Sound, Alaska after the wreck of the Exxon Valdez in 1989. 

In the 1967 grounding of the Torry Canyon off the English coast, 1,000-pound high 

explosive bombs, napalm bombs, rockets, and other tecniques were used in unsuccessful 

attempts to ignite the oil . 

Since the development of fire-resistant boom, many small scale laboratory burns, a 

number of meso-scale field burns, and at least three large-scale burns have demonstrated the 

effectiveness of burning in eliminating large volumes of oil from the water. Oil removal 

efficiency rates in access of 95% are routinely reported . The small amount of residue 

remaining is a small fraction of the original oil volume; it is lighter, more toxic components 

have been removed; and it is easy to handle.These factors greatly reduce storage and disposal 

requirements . 

Numerous experimental burns and the few field burns that have been done have 

reported elimination rates of 95-99% . Since oil spill responders work to prevent spilled oil 

191 
from impacting sensitive areas and resources concentrated on or near the shoreline, in-situ 

burning has the potential to mitigate environmental impacts from catastrophic oil spills 

In-situ burning is relatively simple in terms of logistics: a basic unit consists of a fire 

boom towed in a "u" shaped configuration by two vessels of opportunity and an ignition 

source . The burn residue is normally easy to handle and might require a gill net, shrimp 

net, or other device for collection . Efficiency of the burn operation would be improved with 

aerial support from an airplane or helicopter for the observation of slick movements, smoke 

plumes, safety factors, response activities, and resources at risk . Another operational 

advantage is the storage and disposal requirements inherent in mechanical cleanup are 

minimized with in-situ burning . 

Probably the major reason for the reluctance to accept in-situ burning as a major 

response option is the large amount of black smoke generated by the burn and the resultant 

air pollution. Combustion of oil produces a number of compounds, paticulates and gases that 

could constitute a health threat to humans or wildlife directly in the path of the smoke plume. 

The tradeoffs involve the rapid removal of oil from the surface of the water by 

burning, preventing shoreline impacts, contact of wildlife with floating oil, and 

environmental impacts of the slow evaporation and weathering of spilled oil weighed against 

concerns for worker safety, and environmental impacts associated with air emissions, heating 

of the water, and residue from the burn. 

Safety considerations are the number one priority in assessing the option of in-situ 

burning . Considerations include: worker safety training, safe boom handling, planning for 

the possibility of unwanted ignition and secondary fires, personnel exposure, and proximity 

issues. 

The combustion of oil on water produces an abundance of thick, black smoke which 

contains emissions that are potentially harmful to the environment. Of primary concern are 

PM,os ( particulate matter < 10 microns in size), PAHs ( polycyclic aromatic hydrocarbons), 

VOCs ( volatile organic compounds), gases ( such as carbon monoxide, carbon dioxide,and 

sulphur dioxide), metals, and exotic organics . 

The recent Newfoundland Offshore Burn Experiment (NOBE), the largest most 

comprehensive experimental burn conducted to date, indicated that emissions from the two 

burns were less than expected. At a distance of 200 meters from the fire, all measurements 

of emissions were below health concern levels . At 500 meters, very little was detected . 

Water under the burn was analyzed and observed and no compounds of concern were 

detected and no measurable increase in water temperature was found . The residue did not 

sink, was easy to recover, contained no detectable acutely toxic compounds, and comprised 

only a small percentage the original oil volume. 

The major sponsors of the NOBE were : U.S . Minerals Management Service, 

Environment Canada, Canadian Coast Guard, U.S . Coast Guard, U.S. Environmental 

Protection Agency, Canadian Association of Petroleum Producers, MSRC, American 

Petroleum Institute, 3-M Corp ., and the Canadian Petroleum Products Institute . 

The experimental burn involved 234 people at sea, 22 ships and boats, 7 aircraft, and 

over 200 sensors and samplers . ignition source for the burns was a helitorch. A number of 

special sampling techniques including remote controlled boats, submersables, helicopters and 

other aircraft were developed to collect the desired data . 

192 
Due to the rapid emulsification of spilled oil on the open ocean, the window of 

opportunity for the successful use of burning is narrow, typically ranging from only a few 

hours to a day or two . The narrow window of opportunity makes preapproval by the 

Regional Response Teams (RRT) a necessity if the FOSCs and responders are to have the 

use of this valuable tool. 

On January 7, 1994, Regional Response Team VI which covers the Gulf Coast, 

approved a plan that allows the FOSC to approve the use of burning three miles or farther 

off the coasts of Louisiana or Texas . This landmark action is the first preapproval for in-situ 

burning in the continental U.S . and was presented to the RRT by MSRC on behalf of the 

response industry and its clients. The approval will encourage response community members 

to acquire fire boom to begin to work out the operational details and conduct the training 

necessary to conduct safe burns . 

In spite of all the current interest in in-situ burning and the promising results from the 

NOBE, much needs to be done before this technique becomes a widely accepted and utilized. 

Due to the rapid emulsification of spilled oil on the open ocean, the window of 

opportunity for the successful use of burning is narrow, typically ranging from only a few 

hours to a day or two. The narrow window of opportunity makes preapproval by the RRTs 

a necessity if the FOSCs and responders are to have the use of this valuable tool. 

The approval process involved encouraging comments from the numerous federal and 

state agencies involved in the RRT approval process and responding to these comments. Of 

most concern to the resource agencies commenting were: air emissions, burn residue issues, 

and monitoring . 

Concerns about air emissions were answered by establishing a 3 mile limit to burning . 

Previously reported research results and the recently completed NOBE indicated that 3 miles 

at least tripled the safe distance for the measuring of levels of concern. 

Residue concerns were addressed primarily by the establishment of exclusion zones to 

prevent Gulf of Mexico sensitive biological communities associated with "hard" bottom from 

being contacted by sinking residue . 

Monitoring became a big issue. It was finally decided that a concurrent proposal by 

the U.S . Coast Guard to monitor for dispersants and in-situ burning be included as a part of 

the burn plan. The Special Response Operations Monitoring Program (SROMP) was 

developed by the Coast Guard and will be carried out by the Gulf Strike Team. 

The Strike Team will be monitoring real time during a burn operation to report PMIo 

levels directly to the FOSC. When levels of cocern are read, the FOSC will be advised to 

terminate operations . 

However, much needs to be done before in-situ burning becomes a widely accepted 

and utilized response technique. Operational techniques and methods need to be worked out 

and improved. Boom towing must be praticed before crews become proficient with the 

technique . Training of this type can be done in pre-planning courses and drills . however, 

there is still a need to practice in-situ burning with oil deliberated spilled and ignited for that 

specific purpose . 

Research is needed on the ignition of weathered oil, on rates of weathering of 

various types of oil and the effects of oil chemistry on other aspects of burning . In a broader 

193 
scope, research needs to be done on burning in wetlands where mechanical cleanup would 

result in more damage to this fragile resource. 

From the results summarized above, as well as other reseasrch on burning spilled oil, 

it is felt that in-situ burning can be used as a safe response technique . Its use in combination 

with the other response tools, dispersants and mechanical recovery, will allow responders to 

mitigate environmental damage from catestrophic oil spills . 

194 
Evaluation of Burning as an Oil Spill Cleanup Technique in a High 

Marsh Community along the South Texas Coast 

Beau Hardegree, David W. Hicks, and John W. Tunnell, Jr. 

Center for Coastal Studies 

Texas A&M University-Corpus Christi 

INTRODUCTION 

A rupture in a 40cm diameter underground oil transfer pipeline on January 7, 1992, 

resulted in the spillage of approximately 2,950 barrels (469 m3) of API gravity 37 south 

Texas light crude oil into 15 .5 ha of a high marsh community near Chiltipin Creek, San 

Patricio County, Texas (Strand and Schultz 1992) . Because this high marsh is part of a 

natural drainage system of upland farmland that flows towards the confluence of Chiltipin 

Creek and the Aransas River, approximately 0.8 km to the N.E., there was concern that oil 

would enter the river possibly affecting a greater area. This concern was elevated by the fact 

that the marsh was inundated with several centimeters of water from recent heavy rain falls 

and continuing precipitation was predicted. Therefore, the situation required rapid oil 

removal and on January 9, 1992, the Texas General Land Office (designated On-SceneCoordinator), after consultation with other resource agency personnel, authorized the burning 

of the oil as the primary cleanup technique . Other agency personnel included representatives 

of the Texas Natural Resource Conservation Commission, Texas Railroad Commission, U.S . 

Fish and Wildlife Service, Texas Parks and Wildlife Department, and the U.S . Coast Guard. 

Their rationale was based on the conclusion that trampling of marsh plants during mechanical 

removal techniques might result in the total loss of the existing marsh, and it was believed 

that the below-ground root and rhizome systems of the marsh vegetation would be protected 

against burn injury by the layer of standing water inundating the marsh, therefore allowing 

regrowth in the spring . The burn was initiated at 1820 hrs on January 11, 1992, by using 

varisol as a propellent and within two hours flames were in excess of 46 m high (Strand and 

Schultz 1992) . The primary burn persisted for more than 18 hours after which minor 

pockets of unburned oil were ignited . Post-burn inspection revealed that burned oil residue, 

consisting of a waxy paraffin, as well as a brown and black mousse-like material, remained 

in significant quantities throughout the marsh . It was decided that if plants were to recover 

in the spring this residue would have to be removed by manual cleanup efforts . To minimize 

trampling of plants, work crews were required to strategically place plywood walkways 

throughout the marsh and remain on these walkways during the cleanup. Manual cleanup 

techniques included low pressure, high volume flushing and pumping, sorbent booms, pads, 

and pour pours . Final estimates for recovered oil were 1,250 bbls (198 .7 m3) from the blowout hole, 500 bbls (79 .5 m3) were pumped from the marsh, and 50 bbls (8 m3) were 

extracted with sorbent booms, pads and pour pours . Of the 1,150 bbls (183 m3) that were 

unaccounted for, it was estimated that 350 bbls (56 m3) probably evaporated into the air, 

leaving 800 bbls (127 m3) either burned or remaining in the marsh. Of the 15 .5 ha 

195 
surrounded by sorbent booms roughly half, 6 .6 ha, were burned to the ground, causing 

extensive bare area throughout the impacted site . 

The great value of coastal tidal wetlands or salt marshes is well established, including 

characteristic functions such as habitat, feeding, and nursery grounds for a variety of species, 

high productivity, shoreline stabilization, reduction of coastal flooding, and enhancement of 

water quality through immobilization of nutrients and filtering of heavy metals and toxic 

materials from the water column (for example, Lindall and Saloman 1977 ; Mitsch and 

Gosselink 1993 ; Rabalais 1980 ; Getter et al . 1984) . Because of these important ecologic and 

economic values, as well as their high environmental sensitivity, salt marshes receive the 

highest priority for protection in oil spill contingency and response plans for coastal areas 

(Lindstedt-Siva 1979; Gundlach and Hayes 1978) . However, despite their environmental 

sensitivity and priority for protection, salt marshes are still occasionally impacted by oil via 

accidental discharges from barge traffic (Hershner and Moore 1977; Ayers 1978 ; Hampson 

and Moul 1978 ; Sanders et al. 1980 ; Webb et al . 1981), oil transfer pipelines (Crow 1974 ; 

Holt et al. 1978; Kiesling et al. 1988), and oil storage tanks (Mattson et al. 1977). 

After oil enters a marsh, the method(s) of cleanup, as well as assessment of 

environmental impacts, must be determined . Kiesling et al. (1988) and Alexander and Webb 

(1985, 1987) have thoroughly reviewed oil spill cleanup techniques and their impacts on salt 

marshes along the upper Texas coast. Their field work on actual oil spills and experimental 

test plots, as well as a careful review of the literature reveal multiple clean-up technologies 

available and varied results depending upon the ecological setting and the type and volume of 

oil spilled . Of the clean-up methods, including absorption, flushing, clipping, burning, or 

doing nothing, any could be chosen as appropriate, depending on the spill scenario . 

Generally, the most accepted ideas are to : 1) do nothing in the case of light to moderate 

oiling and adequate tidal flushing, because trampling of the marsh can cause more damage in 

the long-term than the oiling itself ; 2) use flushing and absorption with heavier oiling or 

deeper penetration into the marsh; 3) use clipping when heavy oil cannot be effectively 

removed from vegetation by flushing ; 4) do not use burning because it enhances oil 

penetration into the sediment and causes substantial initial plant damage . Additionally, it was 

noted that lighter fuel oils were more damaging to the salt marsh vegetation than heavier 

crude oils . 

Alexander and Webb (1985) identified three spill situations where impact was long-term: 

1) spillage of No . 2 fuel oil ; 2) penetration of large quantities of oil into the sediment; and 3) 

complete oil coverage of plant surfaces during active growth periods . When any of these 

three situations are identified, the above-mentioned clean-up responses are recommended. In 

contrast to Alexander and Webb (1985, 1987), Holt et al . (1978) did find burned and clipped 

areas to have slightly better recovery than non-cleaned areas in a 1976 Harbor Island, 

Redfish Bay pipeline spill . 

All of the above mentioned studies and reviews dealt with low salt marshes dominated by 

Spartina alterniflora distributed in the intertidal zone of estuarine shorelines . None of them 

were concerned within the supratidal, high marsh zone and none considered burning as the 

primary clean-up strategy . 

In situ burning is viewed with growing interest as a response tool and has distinct 

advantages over other techniques . It offers the potential to rapidly convert large quantities of 

oil into its primary combustion products, carbon dioxide and water, with small percentages 

196 
of other unburned and residue by-products (Evans et al. 1992) . The removal of oil from 

environmentally sensitive areas, such as high marshes, by burning is very rapid and may 

prove less damaging (long term) to vegetation than physical removal techniques, where 

trampling of plants is inevitable . This rapid removal of the oil also reduces the likelihood of 

it spreading into other sensitive areas . In-situ burning also requires minimal equipment and 

less labor than other removal techniques, and because the oil is converted to gaseous 

products of combustion by burning, the need for physical collection, storage, and transport of 

recovered fluids is reduced to a few percent of the original spill volume (Evans et al. 1992) . 

Obvious disadvantages of burning oil are that it produces a visible smoke plume giving rise 

to public health concerns related to the chemical content of the smoke plume and the 

downwind deposition of particulates (Evans et al. 1992) and in vegetated areas, causes 

substantial initial plant damage. 

The purpose of this study is to evaluate the effectiveness of burning oil as a clean-up 

method in a high marsh habitat by measuring changes in the marsh plant community and soil 

Total Petroleum Hydrocarbon (TPH) content over time (Tunnell et al. 1994). 

STUDY AREA 

The impacted high marsh area is located in San Patricio County, Texas, at approximate 

coordinates 28°04'09" N, 97°16'01" W (Fig . 1) . 

The study area is characterized by typical south Texas middle and high marsh plant 

species, small unvegetated areas usually covered by blue-green algal mats, and several 

ephemeral brackish-water ponds . Two sampling areas for study are located in the marsh, 

one impacted by the oil and burn and the other unimpacted . The adjacent unimpacted site 

was used as the control site for this study (Fig . 2) . 

The climate in the area is considered to be semi-arid, receiving approximately 89 cm 

of precipitation annually. Average temperatures range from 8 .3 °C in the winter to 33 .3 ° C 

in the summer (Brown et al. 1976) . Persistent southeast winds occur from March through 

September, while northeasterly winds occur with frontal passages from October through 

February (Behrens and Watson 1973 .) 

As a high marsh this area is rarely covered with water but because at the time of the 

spill this location was in a period of above normal rainfall there was 10 to 15 cm of water 

inundating the marsh. Throughout the spill and clean up efforts, rainy conditions persisted. 

METHODS 

Methodology for evaluating the effectiveness of burning oil as a cleanup method 

included a marsh plant frequency and biomass study as well as a study of soil TPH. 

Frequencies for marsh plants was obtained utilizing a line-point intercept transect technique. 

Twenty 30 m transects were systematically located in both the impacted and control areas of 

the marsh with points examined every 0 .5 m. The plant species touching or immediately 

below the point being examined was recorded. The frequency of plant species was 

determined by totaling the number of times a given species was recorded for each transect, 

yielding a maximum mean frequency of 60. The 20 transects were used as replicates for 

197 
analyses in comparisons between impacted and control areas . Marsh plant frequency 

sampling was initiated in October 1992, and transects were repeated once in July 1993, 

during the first year of the study, after which sampling was conducted quarterly (October 

1993, January 1994, and April 1994) . 

Marsh plant biomass was obtained by clipping all above-ground tissue without regards 

to species composition from 100 randomly located 25 cm2 quadrats in each area. All plant 

tissue removed from the quadrats with electric hedge trimmers was placed in marked brown 

paper bags and returned to the lab. The aggregate plant samples were dried for 72 hours in a 

drying oven before being weighed to the nearest mg . Plant biomass samples were taken 

seasonally for the first year of the study (March, April, and May for cool season plants and 

June, July, September, and October for warm season plants) . Beginning in October 1993, 

biomass was taken quarterly along with plant frequency sampling . Mean dry weight biomass 

was compared by independent t-test analysis after each sampling date . 

Because little is known about high marsh vegetation species and their tolerance to fires, 

a separate investigation was begun to test the initial premise that marsh plants would continue 

to grow after having all of their above-ground tissue destroyed . In February 1994, two 1 m 

square quadrats were established in monotypic stands of Borrichia frutescens, Salicornia 

virginica, Monanthochloe littoralis, and Distichlis spicata. All above-ground tissue was 

removed by clipping and the remaining stubble was burned to ground level utilizing a pear 

burner. Prior to burning, the plants within the quadrats were isolated from clones outside 

the quadrat by cutting around the edges to a depth of 40 cm with a shovel . A 15 .2 cm wide 

plastic garden edging was placed around each quadrat to prevent roots and rhizomes from 

regrowing into the isolated quadrats. Regrowth was qualitatively observed and 

photographed. 

Soil for TPH analysis was collected in December 1992 and repeated one year later in 

December 1993 . Initially, seventy core samples (8 cm length X 5 cm diameter), fifty from 

the impacted area and twenty from the control, were randomly collected using lexan cores 

and sent to the Texas Parks and Wildlife laboratory in San Marcos, Texas, for analysis . 

Areas found to have TPH values higher than 100 ppt were resampled in the subsequent 

sampling period . Because spiked recovery rates were different (91 .6% in 1992 compared to 

81 .0 % in 1993) results were normalized to 100% spiked recoveries and then analyzed using 

a paired samples t-test . 

RESULTS AND DISCUSSION 

Thirteen species of plants were identified inhabiting the marsh area (Table 1) . Of 

these thirteen, Distichlis spicata, Batis maritima, Salicornia virginica, Borrichia frutescens, 

Monanthochloe littoralis, and Scirpus maritima, along with bare area accounted for over 90 

of the observed frequencies along the line-point intercept transects. Although species 

richness was similar in the impacted and control areas, the relative abundance of each species 

was found to be different. 

Approximately 16 .4 acres were burned to the ground in the cleanup effort . This newly 

created bare area was for the most part rapidly recolonized by invasive pioneering species 

(Distichlis spicata and Scirpus maritima) . Distichlis spicata, which accounts for 

198 
approximately 80% of the frequencies of the impacted area, is regarded as a disturbancedependent species whose success is a product of its ability to tolerate and recover from 

disturbance in high salt marsh habitats (Bertness and Ellison 1987 ; Bertness et al. 1992 ; 

Hartman 1988) . Scirpus maritimus thrives in standing water, the condition that was 

predominant throughout the first growing season . The bare areas resulting from the burn, 

made ideal habitat for Scirpus maritimus, whose only competition was from Distichlis 

spicata. The combined frequencies of Distichlis spicata, Scirpus maritima, and bare area 

account for 85 .5% of the total observed frequencies of the impacted area between October 

1992 and April 1994, compared to 50 .3 % in the control area (Figs. 3 and 4). The other 

half of the control area is for the most part comprised of climax perennial vegetation with 

mean combined frequencies averaging 27 .68 compared to the impacted area where these 

perennial species made up 12 .7% of the total combined frequencies (Figs . 5 and 6) . There 

is no clear observable trend in the combined mean frequencies for vegetation patterns in the 

control area, unlike that of the impacted site . In the impacted site combined perennial climax 

vegetation frequencies are steadily increasing at approximately the same rate that combined 

pioneering species and bare area are decreasing . Regressions based on these trends yield 

estimates of between 10 and 12 years from initiation of the study in October 1992, until 

vegetation patterns resemble those observed in the control site . Although the changes in the 

impacted area are not expected to remain linear, it is believed that the predicted recovery 

times does illustrate how slow recovery of climax perennial vegetation lost due to the burn is 

likely to be . 

These trends are also reflected in species diversity. In the control area, species 

diversity values have remained fairly constant over time . In the impacted area, as Distichlis 

colonized bare patches, the overall dominance was shifted to one species, and the diversity 

index value decreased. This decrease in diversity values continued until increases in 

frequency of Borrichia frutescens and Scirpus maritimus, at the expense of Distichlis spicata, 

between January and April 1994, caused the diversity index value to rise (Fig. 7) . 

Plant dry weight biomass was significantly higher (P < 0 .05) in the control area in all 

months sampled . Seasonal trends apparent in the control area were masked by steadily 

increasing biomass in the impacted area until June 1993 when the two areas began tracking 

fairly closely (Fig . 8) . 

Results from the qualitative burning experiment show that all plots had new growth and 

by June 1994 Distichlis spicata plots were nearly indistinguishable from surrounding areas. 

Only Salicornia virginica plots were severely lagging behind others in regrowth. Although 

the Borichia frutescens plants were obviously shorter in burned plots, the number of plants 

within the plots is similar to that observed outside. The isolated plots of Monanthocloe 

littoralis also showed considerable regrowth and other than the obvious loss of the understory 

detrital buildup, would be indistinguishable from the surrounding area. 

TPH values for the 20 samples collected from the control area in December 1992, 

ranged from 16 .4 to 72 .0 ppm (x = 50.5, SE = 2.9) . Of the 50 TPH samples randomly 

collected in the impacted area, 20 were found to have TPH values greater than 100 ppm. 

These twenty ranged from 108 .0 to 4538 .51 ppm (x = 1064 .3, SE = 256.7) The twenty 

impacted site samples were repeated in December 1993 . TPH values for the repeated 

samples ranged from 29 .38 to 4440.4 ppm (x = 897 .1, SE = 258.1) The overall decrease, 

199 
in mean TPH values, was not significant by paired sample t-test analysis . Although the TPH 

values have remained much higher than those of the control area (x = 50.5), it is not clear if 

they are at a level that would be detrimental to plant recovery . Levels of TPH < 5 ppt were 

found to have little effect on Spartina alterniflora marshes in Texas (Alexander and Webb 

1987) . 

SUMMARY 

The most significant disadvantages of burning as a clean-up method appears to be the 

substantial initial plant damage, especially to climax perennial vegetation . Residual 

hydrocarbon levels in the sediment remain elevated even after two years . Kiesling et al. 

(1988), during studies evaluating oil spill cleanup techniques, demonstrated that burning 

actually increased oil content in sediment by 27-72% . 

Results of the qualitative burning experiment lead to concluding that the initial premise 

was not flawed, and that most high marsh plants could regenerate above-ground parts from 

below-ground tissue . The loss of the climax perennial vegetation in the impacted area was 

either a result of intense heat from the fire caused by the oil, or hydrocarbons were forced 

into the sediment from the heat, killing the roots and rhizomes . Because of the rapid rate at 

which the area was recolonized by Distichlis spicata it is not believed that toxins are 

preventing the regrowth of perennial climax species, rather the roots of perennials were 

probably killed by the intense heat transferred by the water covering the plants . Heat from a 

fire producing flames > 46 m high and persisting for > than 18 hours would certainly 

penetrate into the shallow root and rhizome layer of the marsh plants . 

The combined mean frequencies of perennial climax species are slowly increasing over 

time at about the same rate as the combined mean frequencies of Distichlis spicata, Scirpus 

maritime and bare area are decreasing . Estimates of recovery are from 10 to 12 years based 

on regressions of trends in combined mean frequencies of perennial climax and pioneering 

vegetation in the impacted area . 

It is obvious that burning oil as a clean-up method has merit but it should be used with 

caution. In this situation there was almost no other choice, the spill was to large to be left to 

degrade naturally, and manual cleanup efforts would have only served to trample the plants 

as well as push crude oil into the sediment. Fear of the oil washing into the nearby Aransas 

River also played an important role in the decision to burn the oil . From this study it should 

be realized that the damage to plants is severe and with respect to perennial climax 

vegetation, long term. In the future this long-term plant damage should be considered in 

burn decision making . 

ACKNOWLEDGMENTS 

The authors would like to thank the Texas General Land Office for funding this 

important three year study of injury evaluation in high marsh community due to an oil spill 

and ensuing burn. With the support of the GLO it is our goal to expand scientific knowledge 

of high salt marsh communities and assess their ability to recover from oil spills and to 

evaluate the use of burning as a cleanup procedure . We would like to acknowledge and 

200 
thank the following people and agencies for their support, expertise, and time in making this 

study possible : Dr. Lynn Drawe, Welder Wildlife Foundation, and Dr. C.P. Onuf, U.S . 

Fish and Wildlife Service, for their help and guidance in project design; Dr. Mike Speed, 

Center for Statistical & Quality Improvement Services, TAMU-CC, for help and advise with 

data analysis ; Mr . Alan Strand and Ms . Teresa Barrera, U.S . Fish and Wildlife Servise, for 

help with photographs of the spill; TAMU-CC Center for Coastal Studies graduate students 

and employees Mr. Dennis Rocha, Mr. Carl Beaver, Ms . M.C . Lee, Ms . Christi Adams, 

Ms . Tamara Teas, Dr . Roy Lehman, for assistance in the field and Mr. Jeff Foster for 

technical computer assistance . We would also like to thank Mr. H.G. Richie Jr. who owns 

the land where the spill occurred, and without whose support and permission this study 

would not be possible . 

LITERATURE CITED 

Alexander, S.K. and J .W. Webb . 1985 . Oil in the salt marsh: What have we learned? pp . 

49-62. In, C.F . Bryan, P.J . Zwank, and R.H . Chabreck (eds.), Proceedings of the 

Fourth Coastal Marsh and Estuary Management Symposium, Louisiana State 

University, Baton Rouge, Louisiana . 

Alexander, S.K. and J.W. Webb. 1987. Relationship of Spartina alterniflora growth to 

sediment oil content following an oil spill . pp . 445-449 . In, Proceedings of the 1987 

Oil Spill Conference, American Petroleum Institute, Washington, D.C. 

Ayers, R.W. 1978 . The effects of the barge STC-101 oil spill on shallow water 

invertebrates of lower Chespapeake Bay. pp. 280-318. In, Proceedings of the 

Conference on Assessment of Ecological Impacts of Oil Spills, American Institute of 

Biological Science, Arlington, Virginia. 

Behrens, E.W. and R.L. Watson. 1973 . Corpus Christi water exchange pass: A case 

history of sedimentation and hydraulics during its first year. U.S. Army Corps . 

Engineers Coastal Research Center, Final Report, Contract No . DACW 72-72-6-

0027 . 

Bertness, M.D . and A.M . Ellison. 1987 . Determinants of pattern in a New England salt 

marsh plant community. Ecological Monographs. 57(2) : 129-147. 

Bertness, M.D ., L. Gough, and S . W. Shumway. 1992 . Salt tolerances and the distribution 

of fugitive salt marsh plants . Ecology . 73(5) : 1842-1851 . 

Brown, L.F ., Jr., J.L . Brewton, J .H . McGowen, T.J . Evans, W.L. Fisher, and C.G. Groat. 

1976 . Environmental geologic atlas of the Texas coastal zone-Corpus Christi area. 

University of Texas at Austin, Bureau of Economic Geology, Austin . 123 pp . 

201 
Crow, S.A. 1974 . Microbiological aspects of oil intrusion in the estuarine environment. 

Ph.D Dissertation, Louisiana State University, Baton Rouge, Louisiana . 

Evans, D.D ., W. D. Walton, H.R. Baum, K.A. Notarianni, J.R. Lawson, H.C . Tang, K.R. 

Keydel, R.G. Rehm, D. Madrzykowski, R. H. Zile, H. Koseki, and E.J . Tennyson. 

1992 . In-situ burning of oil spills : mesoscale experiments. pp 593-657 . In, 

Proceedings of the Fifteenth Arctic and Marine Oil Spill Program, Edmonton, 

Alberta. 

Getter, C.D., G. Cintron, B. Dicks, R.R. Lewis and E.D. Seneca. 1984 . The recovery and 

restoration of salt marshes and mangroves following an oil spill. pp . 65-113 . In, J. 

Cairns and A.L. Buikema (eds .), Restoration of habitats impacted by oil spills . 

Butterworth Publishers, Boston. 

Gundlach, E.R. and M.O. Hayes . 1978 . Vulnerability of coastal environments to oil spill 

impacts . Marine Technology Society Journal. 12(4) : 18-27 . 

Hampson, G.R. and E.T. Moul . 1978 . No. 2 fuel oil spill in Bourne, Massachusetts: 

Immediate assessment of the effects on marine invertebrates and a three-year study of 

growth and recovery of a salt marsh. J. Fish. Res. Board Canada 35: 731-744. 

Hartman, J .M . 1988. Recolonization of small disturbance patches in a New England salt 

marsh. American J. of Botany . 75(11) : 625-1631 . 

Hershner, C. and K. Moore. 1977 . Effects of the Chesapeake Bay oil spill on salt marshes 

of the lower bay . pp . 529-533 . In, Proceedings of the 1977 Oil Spill Conference, 

American Petroleum Institute, Wash. D.C. 

Holt, S ., S . Rabalais, N. Rabalais, S . Cornelius, and J.S . Holland. 1978 . Effects of an oil 

spill on salt marshes at Harbor Island, Texas. I . Biology. pp. 344-352. In, 

Proceedings of Conference on Assessment of Ecological Impacts of Oil Spills . 

American Institute of Biological Science, Arlington, Virginia . 

Kiesling, R.W., Alexander, S.K. and J.W . Webb. 1988 . Evaluation of alternative oil spill 

clean-up techniques in a Spartina alterniflora salt marsh. Environmental Pollution. 

55 : 221-238 . 

Lindall, W.N . and Saloman, C.H . 1977 . Alteration and destruction of estuaries affecting 

fishery resources of the Gulf of Mexico . Marine Fisheries Rev. 39(9) : 1-7 . 

Lindstedt-Siva, J . 1979. Ecological impacts of oil spill clean-up: Are they significant? pp . 

521-524. In, Proceedings of the 1979 Oil Spill Conference, American Petroleum 

Institute, Wash. D.C . 

202 
Mattson, C.P . N.C. Vallario, D.J . Smith, S. Anisfield, and G. Potera . 1977. Hackensach 

estuary oil spill : Cutting oil-soaked marsh grass as an innovative damage control 

technique . pp. 243-246 . In, Proceedings of the 1977 Oil Spill Conference, American 

Petroleum Institute, Wash. D.C . 

Mitsch, W.J . and J.G . Gosselink. 1993 . Wetlands. Van Nostrand Reinhold, New York, 

722 pp. 

Rabalais, N.N. 1980 . Ecological values of selected coastal habitats. In P.C . Fore and R.D. 

Peterson (eds.), In, Proceedings of the Gulf of Mexico coastal ecosystems workshop, 

U.S . Fish and Wildlife Service, FWS/OBS - 80/30, pp. 191-209 . 

Sanders, H.L., J .F . Grassle, G.R. Hampson, L.S . Morse, S . Garner-Price, and C.C. Jones. 

1980. Anatomy of an oil spill : Long-term effects from the grounding of the barge 

Florida off West Falmonth, Massachusetts. J. Marine Res. 38 : 265-380. 

Strand, A.M. and T.W. Schultz. 1992. Field investigation report Exxon Pipeline/Chiltipin 

Creek oil spill January 7, 1992, San Patricio County, Texas. U.S . Fish and Wildlife 

Service, Region 2 Report . 18 pp . 

Tunnell, J.W . Jr. and D.W . Hicks, and B. Hardegree . 1994. Environmental impact and 

recovery of the Exxon Pipeline oil spill and burn site, upper Copano Bay, Texas : 

Year One. CCS Study TAMU-CC-9402-CCS . Center for Coastal Studies, Texas 

A&M University, Corpus Christi, Tx . 75 pp . 

Webb, J.W ., G.T. Tanner, and B.H . Koerth . 1981 . Oil spill effects on smooth cordgrass in 

Galveston Bay, Texas . Contributions in Marine Science. 24 : 107-114. 

203 
Table 1 . 

A taxonomic list of plants inhabiting Chiltipin Creek marsh . 

Division Spermatophyta 

Class Angiospermae 

Subclass Monocotyledoneae 

Order Najadales 

Family Ruppiaceae 

Ruppia maritima L. 

Wigeongrass 

Family Cyperaceae 

Scirpus maritimus L, 

Bulrush 

Family Gramineae 

Distichlis spicata L. 

Saltgrass 

Moncmthochloe littoralis Engelm. 

Key grass 

Spartina spartinae (Trin.) Hitche. 

Gulf Cordgrass 

Sporobolus virginicus (L.) Kunth . 

Seashore Dropseed 

Order Caryophyllales 

Family Chenopodiaceae 

Salicornia bigelovii Torr. 

Annual Glasswort 

S. virginica L. 

Perennial Glasswort 

Suaeda linearis (Ell .) Moq. 

Seablite 

Order Bataceae 

Family Bataceae 

Batis maritima L. 

Saltwort 

Order Primulales 

Family Plumbaginaceae 

Limonium nashii Small 

Sea Lavender 

Order Polemoniales 

Family Solanaceae 

Lycium carolinianum Walt. 

Wolfberry 

Order Asterales 

Family Asteraceae 

Borrichia frutescens (L.) DC. 

Sea Ox-eye Daisy 

204 
Bayside 

- 

~er 

i Co pano Bay 

Figure 1 . Location of the Chiltipin Creek marsh study site on the Texas coast 

205 
N 

O 

.. . 

va 

N 

y 

r~r 

lY 

F~+y~ 

Fr 

n 

'L7 

n ., 

0 

s. 

OQ 

rr 

`S 

N 

F+ 

ro 

R 

m 

a 

n 

0 

..* 

M 

M 

CD 

A~ 
Figure 3 . Combined mean frequencies of pioneering species and bare area observed in the 

impacted Chiltipin Creek marsh site, along with estimated time for levels to decrease to 

those observed in the control site 

207 
Distichlis spicata 

Scirpus maritimus 

Bare Area 

40 

X = 30.22 

35 

777 77777 

30 

25 

a- 20 ' ; 

15 

10 

5 

_ 

0 

OCT92 JUL93 OCT93 JAN94 APR94 

Figure 4. Combined mean frequencies of pioneering species and bare area observed in the 

control site of the Chiltipin Creek marsh. 

208 
Figure 5. Combined mean frequencies of climax vegetation species observed in the control 

site of the Chiltipin Creek marsh. 

209 
D Batis maritima 

~ Salicornia virginica 

~ Borrichia fiutescens 

Monanthochloe linora/is 

" Approximate Mean Frequency in Year 2004 

12 ` 30 

Adjusted R' = 0.749 

P = 0.036 

10 25 

U 3 U 

Q 

CJ 8 - o~ 20 

w 

6 X 15 ~, 

'b 

a~ 

'b 

;? 

N 

4 10 ;2 

O a 

5 

0 

OCT92 JUL93 OCT93 JAN94 APR94 YEAR 2004 

Figure 6. Combined mean frequencies of climax vegetation species observed in the 

impacted area of the Chiltipin Creek marsh, along with prediction of estimated time for 

levels to increase to those observed in the control site . 

210 
1 . 6 

~ 1.4 

w 1 .2 

o 1 .0 

i 

0.8 --0- _- Impacted 

Control 

0 . 6 

Oct-92 Jul-93 Oct-93 Jan-94 Apr-94 

Figure 7 . Shannon Diversity (H') values for the impacted and control areas of the Chiltipin 

Creek marsh. 

211 
60 

50 

r. 

°"y° 40 

a 

c4 30 - ---

.25 

3 Zo 

Impacted 

q ~- Control 

5 10 

e5 

0 

'fir 9 'ff~ G ~ ~ d 9 

.q °~ d .o 

.9~ ~~ ;fly ~O~ `fly 

Figure 8. Mean plant dry weight biomass for the impacted and control areas of the 

Chilripin Creek marsh. 

212 
Fates of Oil in Salt Marsh Sediments and Stabilization of Oil Residue 

Edward B . Overton, Charles B . Henry and Paulene Roberts 

Institute for Environmental Studies 

Louisiana State University, Baton Rouge LA 

The natural composition of crude oils is very complex and, to some extent, varies 

between petroleum reservoirs . In general, crude oil is a complex mixture of hydrocarbons 

(molecules made up of only carbon and hydrogen) and nonhydrocarbons (molecules made up 

of carbon, hydrogen, and other elements such as sulfur, nitrogen, and oxygen) produced 

from the partial decomposition of biogenic material . The slow breakdown process deep 

within the earth, known as diagenesis, produces a range of molecular structures significantly 

altered from the structures found in the original biomass. Understanding petroleum 

chemistry is important in understanding the fate of spilled oil in the marine environment. 

The ultimate fate of most spilled oil is microbial degradation in which the indigenous 

decomposing community attack the oil in much the same manner as any other detridal carbon 

source . Oil chemistry and oil degradation are the focus of this paper. 

Composition of Crude Oils 

Each petroleum reserve is a unique combination of biomass breakdown products. Hence, 

each crude oil has a unique compositional complexity with variations occurring within the 

individual petroleum reservoir (Speight 1991) . Libraries of these compositional variations, 

known as molecular fingerprint patterns, have been developed using analytical methods for 

selective petroleum compound analysis . A gas chromatograph/mass spectrometer (GC/MS) 

is one such analytical system commonly used for analysis of complex petroleum hydrocarbon 

mixtures. A GC/MS system is capable of isolating individual compounds within the complex 

crude mixture. Separated compounds are then identified by electron impact mass spectra and 

ion fragment pattern recognition. Analytical data are stored in a computer and displayed in 

various formats that allow researchers to identify and quantify specific molecular components 

of crude oils . These data displays are frequently in the form of gas chromatograms of 

components with the same molecular weight (that is, mass chromatograms) . Detailed 

analyses of specific components and their ion patterns provides insight into the quantitative 

differences in the makeup of individual components in these oils . As a general rule, all 

crude oils are complex mixtures composed of the same compounds however the quantities of 

the individual components differ in crude oils from different locations. This rule of thumb 

implies that the quantities of some compounds can be zero (extremely limited or reduced) in 

a given mixture of components that comprise a crude oil from a specific location, yet 

abundant in oil from a different location. 

The nomenclature for petroleum-based hydrocarbons focuses primarily on the carbon 

bond and several of its structural formations . The following classification scheme breaks 

petroleum components into five major groups . The subcategories are based on the majority 

of the compounds in that subcategory, but many more classifications could exist. 

213 
Petroleum Composition Classification 

Saturates normal paraffins (straight-chain hydrocarbons), isoparaffins (branchedchain hydrocarbons), cycloparaffins or naphthenes (cyclic saturated and 

partially saturated hydrocarbons) 

Aromatics aromatic hydrocarbons (AH), polynuclear aromatic hydrocarbons (PAH) 

and their C1 to C4 alkyl homologs 

Polar sulfur-containing aromatic compounds, nitrogen-containing aromatic 

compounds, oxygen-containing aromatic compounds 

Porphyrins Complex large cyclic carbon structures derived from chlorophyll and 

characterized by the ability to contain a central metal atom. Trace metals 

are commonly found within these compounds . 

Asphaltenes Composition is dependent upon source . Asphaltenes and resins have the 

highest individual molecular weight of all crude oil components and are 

basically colloidal aggregates . 

The saturated carbon bond, or carbon bound to four other atoms, in hydrocarbon 

molecules can be arranged as either straight-chained, branched, or cyclic hydrocarbon 

structures . The straight-chain compounds are found as a homologous series (same molecular 

structure separated by only CHZ groups) in most crude oils, with carbon numbers ranging 

from 5 up to 30 and often more . Saturated hydrocarbon compounds are generally the major 

components of crude oil . Branched-chain compounds, or isoparaffins, are primarily 

methylated straight-chain hydrocarbons. From nine carbons and higher, many isoparaffins 

are isoprenoids originating from a side chain of the chlorophyll molecule with methyl group 

attached to every third carbon in the chain. Branched and isoprenoids hydrocarbons are 

generally slower to degrade by microorganisms than the normal paraffins . Two common 

paraffins found in most petroleum are heptadecane, a straight 17-carbon chain molecular 

structure, and pristane, a branched 19-carbon chain isoprenoid structure . Both components 

have similar boiling points and gas chromatographic retention times . Their microbial 

degradation rates in the environment are very different. Heptadecane rapidly degrades in the 

environment, while pristane remains and is often used as a biomarker for weathering and 

degradation studies . 

Another abundant structure in most fresh crude oils is cyclic hydrocarbons. The two 

basic cyclic structures are cyclohexane and cyclopentane, with five and six carbon rings, 

respectively . Through combinations of these two ring structures assembled with up to five 

rings, many complex molecules are formed during petroleum diagenesis . Two of the larger 

structures commonly used in characterizing and fingerprinting oil are the triterpanes and the 

steranes, with a subclassification of hopanes . Hopane is not degraded by microorganisms to 

any appreciable extent and is often used as a degradation biomarker (Prince et al. 1994). 

214 
Carbon atoms that are bound to three or fewer other atoms in a hydrocarbon molecule 

are referred to as unsaturated and their physical structure may be a straight, branched, or 

aromatic form. As with the saturate petroleum hydrocarbons, aromatic ring structures in 

crude oils commonly range from one to five ring combinations . Two or more five- or sixmember carbon rings are fused together to form polycyclic aromatic compounds (PACs) . 

Petroleum aromatic hydrocarbons have abundant alkyl group substitution on their ring 

structures . The alkyl groups generally have from one to four saturated carbon atoms and 

thus can produce many different structural isomers and homologs for each aromatic 

hydrocarbon family . The most abundant aromatic hydrocarbon families generally have two 

and three fused rings with one to four carbon atom alkyl group substituents . Oil toxicity is 

primarily associated with exposure to these aromatic structures, many of which are known 

mammalian carcinogens. The most acutely toxic compounds are the single aromatic ring 

variations, including benzene, toluene, and the xylenes . All are volatile compounds with 

relatively high water solubility for insoluble compounds. The dibenzene ring structures, or 

naphthalene and its homologous series, are less acutely toxic than benzene but are more 

prevalent for a longer period of time during oil spills (Overton et al. 1994) . 

The polar compounds in oil are classified as nonhydrocarbons . For these compounds, the 

primary functional group is associated with nitrogen, sulfur, or oxygen atoms. The classification 

applies to sulfur compounds such as cyclic sulfides and thiophenes, basic and neutral nitrogen 

compounds, and oxygen compounds, primarily naphthenic acids. The porphyrins, asphaltene, 

and resin compounds in petroleum are considered the residual oil, or residuum. During 

weathering processes, this fraction is the last to degrade, and its persistence in the environment 

over years has been noted (L.eahy and Colwell 1991) . 

Weathering of Crude Oils 

"Weathering" encompasses the physical and chemical changes that crude oils undergo as 

a result of interaction with the environment. The fate of oil in an environment, as 

determined by weathering, is governed by the cumulative physical and chemical properties of 

the individual constituents in the bulk oil (Payne and McNabb 1984) . The factors affecting 

the fate and transport of oil spilled or released in a water environment include : evaporation, 

dissolution, emulsification, absorption and photochemical and microbial degradation. 

Figure 1 outlines the affects of weathering on spilled crude oils . The ultimate fate of 

petroleum spilled in the marine environment is degradation, primarily biological and, to a 

lesser extent, photolytic degradation. The rate at which these processes occur is controlled 

by many factors, such as the physical properties and chemical composition of the oil, the 

exposure to physical processes, abiotic environmental factors, and the existence or absence of 

hydrocarbon-degrading microorganisms (bacteria, mold, yeast, and fungus) and essential 

nutrients . Most chemical breakdown processes affecting whole oil occur at the oil/water 

interface . Chemical actions in aquatic systems include biodegradation and photolytic 

degradation, which are surface-active processes. Therefore, the amount of surface area 

affects the rate of degradation. Certain factors hinder degradation; one factor is 

emulsification, which slows biodegradation because the stable "mousse" formed has a 

smaller surface area compared to very thin oil sheens . Another factor, cooler weather, often 

215 
results in slower rates of microbial activity, which results in less consumption or degradation 

of the oil (Malins 1987) . Microbes utilize the oil as a carbon source which is converted to 

energy, biomass, carbon dioxide, and water (Fig. 1) . Physical processes, such as high 

energy storms, increase the dispersion of oil, thus increasing surface areas and generally 

reducing the persistence of oil spilled in the environment. 

Weathered crude oil can be distinguished from fresh or unweathered crude oil by the 

loss of the low-molecular-weight constituents such as the normal hydrocarbons less than nC,2, the alkylbenzenes and, to some extent, naphthalene and its alkyl homologs. These initial 

changes are primarily due to evaporative losses and, to a lesser degree, dissolution (less than 

5 % of benzene is generally lost to dissolution, while more than 95% is lost to evaporation) . 

The low-molecular-weight constituents are more volatile and more water soluble than the 

constituents with high molecular weight . The rate and extent at which the components 

evaporate and undergo dissolution, sedimentation, and degradation are factors which affect 

persistence and environmental toxicity of crude oils . 

Figures 2 and 3 compare the composition, from capillary GC/MS analysis, of a fresh 

sample and a sample of seven day evaporatively weathered crude oil, south Louisiana crude 

(SLC). Oil was placed in a beaker of water (100 ml oil and 900 ml water) . Samples were 

taken for analysis a day 0 and 7. The oil residue was dissolved in hexane and analyzed by 

GC/MS. As seen from examining these data, the fresh oil contains normal hydrocarbons 

with carbon numbers from 9 (retention time = 6 min.) to 30 ( RT = 51) . Eluting between 

the normal hydrocarbons are the branched and cyclic hydrocarbons. Pristane and n-C 17 are 

the doublet that elutes near 28 min. while phytane and n-C 18 elutes near 31 min. 

Evaporative weathering has changed the composition in a very predictable fashion causing 

loss of the volatile components below n-C 12. The relative composition of the crude oil 

above n-C 15 remains unchanged . Examination of the data in Figure 3 shows similar results 

for the composition of the aromatic hydrocarbons, from naphthalene (MW =128) and its 

alkyl homologs bibenzo (a,h) anthracene (MW=278) . (Note that the data on the one ring 

aromatic hydrocarbons in crude oils is not shown in this figure .) Evaporation for seven days 

causes loss of the volatile naphthalene and C1-naphthalenes while the less volatile aromatics 

are retained in the weathered residue essentially unchanged in composition. 

Figures 4, 5, 6, and 7 show SLC GC/MS data analysis after 7 day laboratory evaporative 

weathering and after 28 day microbial weathering. The microbial weathering involves 

placing 0.5 g of oil in a shaker flask with 100 ml sea water and agitating the mixture for 28 

days . The samples were analyzed by GCMS in a similar fashion to the samples shown 

previously . Examining the data in Figure 4, it is evident that microbial degradation causes 

loss by molecular composition rather than by component volatility . For example, virtually 

all of the normal hydrocarbons, out to n-C30, have been microbially degraded and, 

consequently, lost, while the less degradable isoprenoid hydrocarbon, with carbon numbers 

from 14 (RT=20 min) to 20 (RT=31 min.) have not been degraded and remain in the oil 

residue . Note the ratio of pristane (RT=29 min.) to phytane (RT=31 min.) remains 

virtually unchanged when compared to this ratio in fresh oil. Clearly, microbial degradation 

is selective in the process of hydrocarbon metabolism . 

A similar conclusion can be drawn from examining the aromatic hydrocarbon data in 

Figure 5 . As a general rule, the parent aromatic hydrocarbon structure and its C 1 alkyl 

216 
homolog isomers are more readily degraded than the C2 and C3 homologs . For example, 

the heavily degraded residue stilled contained C3 (MW =170) and C4 naphthalenes 

(MW =184) but none of the larger phenthrene (MW =178), dibenzothiophene MW =184, 

and their respective C 1 homologs (MW =192 and 196) . Even some pyrene (MW =202) 

degraded by microbial attack . Clearly, microbial degradation is selective and dependent on 

molecular structure . Figure 6 shows the compositional profile of compounds that are not 

subjected to microbial degradation, the hopanes and triterpanes. These compounds, 

commonly called biomarkers, are saturate hydrocarbons with fused multiple rings. Data 

clearly shows the complete lack of degradation for these compounds in a sample that was 

heavily weathered by microbial processes. This lack of microbial degradation of these 

cyclic structures is the justification for the use of the so called "biomarker normalization" 

data treatment method when studying the progress of microbial weathering of oils in the 

environment (Prince et al. 1994) . 

It is important to remember the factors that affect microbial degradation and their impact 

on the fate of oil in the environment . These factors include the existence of microbial 

colonies adapted to the degradation of petroleum hydrocarbons, nutrients, oxygen, and a 

mechanism for exposing the microbes to the oil. Exposing the microbes to oil implies 

significant surface contact between the oil and microbe bearing aerated waters. In salt 

marshes, significant colonies of microbes exist that have adapted to degrade the hydrocarbons 

associated with the vegetative matter in the marsh . These hydrocarbons are predominately 

the long chained saturated compounds . Consequently, the colonies in salt marshes readily 

degrades the normal hydrocarbons over other substituents in oils . 

Figure 7 shows a comparison of the saturate hydrocarbons in the Exxon Yaldez oil to the 

oil extracted from an intertidal salt marsh near surface sediment sample collected five years 

after the spill . The saturates are heavily degraded with only the isoprenoid hydrocarbons 

remaining in the sample extract . Figure 8, on the other hand, shows data on the aromatic 

hydrocarbon composition from the same two oil extracts. Microbial attack has removed the 

parent and C 1 aromatic hydrocarbons but significant quantities of the higher homologs 

remain. Even the relatively volatile naphthalenes and fluorenes are still found in the near 

surface sediment five years after the spill . This is very surprising considering the fact that 

near surface sediments are generally considered to be aerated, not anoxic . 

We believe colonies adapted to degrade the naturally occurring hydrocarbons in marsh 

grasses readily degrade the saturate hydrocarbon from the spilled oil but are not suitable for 

degradation of the aromatics. With plenty of biomass containing saturated hydrocarbons 

available from biogenic sources, microbial colonies never adapted to significantly degrade the 

aromatic components of the spilled oil . This same pattern of preferential degradation of the 

saturate verses aromatic hydrocarbons is common for oil spilled into environments rich in 

naturally occurring biogenic saturated hydrocarbons . 

Figures 9, 10, 11, and 12 show data from samples collected 3 and 5 years respectively 

after the Exxon Ualdez spill . However, these samples were collected from a rocky shoreline 

which contained little or sporadic levels of background biogenic hydrocarbons. The near 

surface sample (Figures 9 and 10), collected 3 years after the spill, contained an oily residue 

that was heavily degraded in terms of both its saturate and aromatic hydrocarbon content . 

High energy beaches, which provide abundant mixing energy for oil and aerated water 

217 
contact, are environments where all fractions of the exposed oil are readily degraded. This 

degradation pattern is in sharp contrast to the selective degradation pattern seen in the salt 

marsh samples as shown in Figures 7 and 8 . 

Figures 11 and 12 show an oil extracted from the same general area as the sample used 

in Figures 9 and 10; however, this sample was collected 60-65 cm subsurface five years after 

the spill. The sample was only moderately weathered in terms of both its saturate and 

aromatic fractions. Altered ratios of the normal to isoprenoid content indicates some 

microbial degradation but evaporative/dissolution processes clearly have contributed 

significantly to the weathering of this sample . We believe this example represents a case 

where the oil was trapped in an anoxic zone are removed from vigorous aerobic microbial 

degradation. Clearly, the location contained colonies capable of degrading oil as 

demonstrated in the surface sample . However, an essential ingredient of microbial attack, 

oxygen, may have been lacking . Subsurface oil removed from the active microbial 

degradation communities will remain essentially undegraded for many years after a spill . 

In conclusion, careful study is needed to determine the fates of oil spilled into various 

environments . In addition to the normal weathering processes, the composition of microbial 

communities often are determined by substrate or detritus available at the scene of the spill 

and is an important factor in determining the speed and extent of natural degradation for 

spilled oils . Mixing energy also has a large influence on the speed and selectivity of 

environmental degradations. The combination of these variables in various environments 

lead to the persistence or rapid elimination of hydrocarbons . 

REFERENCES : 

Leahy, J.G. and R.R. Colwell. 1991 . Microbial degradation of hydrocarbons in the 

environment. Microbiological Review 54 : 305-315 . 

Malins, D.C . 1987 . Effects of Petroleum on Arctic and Subarctic Marine Environments and 

Organisms, Vol. 1, Nature and Fate of Petroleum . Academic Press, Inc ., 

New York. 

Overton, E.B., W.D. Sharp, and P.O . Roberts . 1994 . Toxicity of Petroleum, Chapter 5 of 

Basic Environmental Toxicology . CRC press, pp. 133 - 156 . 

Payne, J .F ., and D.G. McNabb, Jr . 1984 . Weathering of petroleum in the marine 

environment. MTS Journal 18: 24-42 . 

Prince, R.C. , D.L . Elmendorf, J .R . Lute, C.S . Hsu, C.E. Haith, J .D . Senius, G.J . 

Dechert, G.S . Douglas, and E.L. Butler . 1994. 17-alpha (H), 21-beta (H)-

hopane as a conserved internal marker for estimating the biodegradation of 

crude oil. Environmental Science and Technology. 28 : 142-145 . 

218 
Speight, J .G . 1991 ., The Chemistry and Technology of Petroleum, 2nd ed . Marcel Dekker, 

Inc ., New York 1991 . 

ACKNOWLEDGMENTS: 

The authors wish to thank Dr. Robert Wong who aided in displaying the GC/MS data, 

and NOAA Hazardous Materials Response and Assessment Division for supporting our oil 

spill research programs . 

219 
IMPLICATIONS OF WEATHERING 

Weathering Process 

FRESH 

Non viscous liquid 

Smelly 

Toxic 

Flammable 

Degradable 

Recoverable 

------------------------------------------------- > RESIDUE 

------------------------------------------------- > Solid 

------------------------------------------------- > No odor 

------------------------------------------------- > Non toxic 

------------------------------------------------- > Non flammable 

------------------------------------------------- > Non degradable 

------------------------------------------------- > Non recoverable 

Figure 1 . Weathering process diagram . 

220 
Abundance 

70000 

60000 

50000 

40000 

30000 

20000 

10000 

Time--> 

Abundance 

90000 

80000 

70000 

60000 

50000 

40000 

30000 

20000 

10000 

Time-- 

00 

00 

Figure 2. Chromatographic comparison of We 85 for unweathered South Louisiana crude oil 

(top) and the oil which has undergone initial weathereing (bottom) . 

221 

Fresh South Louisiana Crude Oil 

.....i- _ or_ c" ..~. . . . .~ ..,. 

Evaporatively Weathered South Louisiana Crude Oil 
1 .8E+03 

1 .5E+03 

1 .2E+03 

1 .0E+03 

~ 7.5E+02 

5 .0E+02 

2.5E+02 

0.0E+00 

1.8E+03 

1.5E+03 

1 .2E+03 

1 .0E+03 

~ 7.5E+02 

5.0E+02 

2.5E+02 

0.0E+00 

Fresh South Louisiana Crude 

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zzzzz ~NM .-NM aaaa - N aUUU~~~WO ~N 

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U 

VV~ ~N a~ 

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South Louisiana Crude, Initial Weathering Only 

zzzz xxx EEz-- >0 ~.~, ~aa ..a ~ ZN a 

¢¢Q¢¢r~.u,tz,r~.AL1AA~x~x z z NM Z ~~ zzz aaa¢x~xr~a1 qaaw~ N 

~ N M ~ N M a a N M ~ N M ~ N U U U r F7 

UUUU 

UUU UUU 

UUU UUU~ UV ~ UU 

Figure 3 . Aromatic hydrocarbon profile of unweathered South Louisiana Crude oil (top) and 

the same oil after being initially weathered on water (bottom) . The oil has 

undergone an enrichment of semivolatile aromatic hydrocarbons caused by the 

evaporation of the volatile "gasoline" fraction and a dilution of the aromatic 

hydrocarbons shown due to the formation of a water-in-oil emulsification ; the two 

effects nearly cancel each other relative to the net concentration of the constituents 

shown. 

222 
Abundance 

90000 

80000 

70000 

60000 

50000 

40000 

30000 

20000 

10000 

Time-- 

Abundance 

25000 

20000 

15000 

10000 

5000 

Time--> 

00 

Figure 4. Chromatographic comparison of m/e 85 for slightly weathered South Louisiana crude 

oil (top) and the same oil after extensive microbial degradation (bottom) . 

223 

Evaporatively Weathered South Louisiana Crude Oil 

Microbially Weathered South Louisiana Crude Oil 

m/7 - Rc~ Rah ire+nc 
1 .8E+03 

1 .5E+03 

1 .2E+03 

1 .0E+03 

~ 7.5E+02 

5.0E+02 

2.5E+02 

0.0E+00 

4.0E-01 

3.0E-01 

bA 

2.0E-01 

b0 

1.0E-01 

0.0E+00 

South Louisiana Crude, Initial Weathering Only 

~aaa~,aaaaa~~~r~azwww a!¢aa¢~~~'~AOAA~xxx 

zzzzz ~NM ~NM aaaa 

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UU 

Highly Weathered South Louisiana Crude 

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zzzz

QQ

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Figure 5. Aromatic hydrocarbon profile of a slightly weathered South Louisiana Crude oil 

(top) and the same oil after being heavily biodegraded (bottom) . 

224 
Abundance 

2800 

2600 

2400 

2200 

2000 

1800 

1600 

1400 

1200 

1000 

800 

600 

400 

200 

Time-->0 

Abundance 

1800 

1600 

1400 

1200 

1000 

800 

600 

400 

200 

Time-- 

Figure 6. Chromatographic comparison of hopane series for slightly weathered South Louisiana 

crude oil (top) and the same oil after extensive microbial degradation (bottom) . 

225 

South Louisiana Crude Oil Initial Weathering Only 

Highly weathered South Louisiana Crude Oil 
Abundance 

22000 

20000 

18000 

16000 

14000 

12000 

10000 

8000 

6000 

4000 

2000 

Abundance 

3000 

2500 

2000 

1500 

1000 

500 

Time--> 00 

Figure 7. Chromatographic comparison of the alkane profile for the Exxon Valdez reference oil 

(top) and oil extracted from surface marsh sediments 5 years after being impacted by 

the Exxon Valdez spill (bottom) . 

Exxon Valdez Reference Crude Oil 

m/z = 85 Saturates 

10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 

226 

Marsh Core Composite 

m/z = 85 Saturates 
3.0E+03 

2.5E+03 

pip 2.0E+03 

~ 1 .5E+03 

1 .0E+03 

5.0E+02 

0.0E+00 

1.0E+01 

8.0E+00 

boo 6.0E+00 

~ 4.0E+00 

2.0E+00 

0.0E+00 

Exxon Valdez Ref. 

~Q¢¢a~~w~oocA~xxx 

zzzzz --NM ~NM awaa 

NM-'T UUU UUU 

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V V CA r. N f1~ G 

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as a aawaaaa 

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. . . UUSUUNa~ a~pZ 

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Figure 8. Aromatic hydrocarbon profile Exxon ValdeZ Reference Oil (top) and slight to 

moderately weathered oil extracted from an intertidal marsh sample collected 5 years 

after the spill (bottom) . The marsh sample is a composite of the upper 2.5 cm from 5 

different cores. 

227 
Abundance 

22000 

20000 

18000 

16000 

14000 

12000 

10000 

8000 

6000 

4000 

2000 

Abundance 

100000 

90000 

80000 

70000 

60000 

50000 

40000 

30000 

20000 

10000 

Time-->5 

.00 

Figure 9. Chromatographic comparison of the alkane profile for the Exxon Valdez reference oil 

(top) and oil extracted from surface beach sediments 3 years after being impacted by the 

Exxon Valdez spill (bottom). 

Exxon Valdez Reference Crude Oil 

m/z = 85 Saturates 

10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 

228 

Surface Sediment ( 0-5 cm ) 

mh -_ RF, Pati iratac 
3.0E+03 

2.5E+03 

pp 2.0E+03 

~p,p 1 .5E+03 

1 .0E+03 

5.0E+02 

0.0E+00 

2.5E-01 

2.0E-01 

b0 1 .5E-01 

r-, 1 .0E-01 

5.0E-02 

0.0E+00 

Exxon Valdez Ref. 

x~xxx~~~~HHHHzzzz~~~~~ axx~~.~>. * aa,~ ~~x 

www ~~~ xrxxw ~v~ W O4 

~ZZZ~~Z awa.,lxxx~aaa,WQ 04 

zzzzz ~NM .-NM aaaa, ~N ~ UUU -- 

NM~ UUU UUU ; Nr; ~ 

NM VV~ i Naa a~ 

UUUU UUU UUU~ UU 

Surface Sediment (0-5 cm) 

W W a~~~~ ¢~¢¢¢~¢f~kLk~~CaGG1Ga~C~~~~~zP4fzPQZ aaa ~xxx wmrsac~:a zzzzz ; NM ; NM aaaa 7N cUUU 

NM~ UUU UUU ; NM ~ NM~ 

UU~ ...cam QW 

UUUU UUU UUU~ UU 

Figure 10. Aromatic hydrocarbon profile Exxon Valdez Reference Oil (top) and heavily 

weathered oil extracted from intertidal surface sediment, or gravel, collected 3 years 

after the spill (bottom). 

2 29 
Abundance 

22000 

20000 

18000 

16000 

14000 

12000 

10000 

8000 

6000 

4000 

2000 

Time-- 

Abundance Subsurface Sediment ( 60-65 cm ) 

m/z - 85 Saturates 

65000 

60000 

55000 

50000 

45000 

40000 

35000 

30000 

25000 

20000 

15000 

10000 

5000 

00 

10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00 50.00 

Figure 11 . Chromatographic comparison of m/e 85 for the Exxon Valdez reference oil (top) 

and the oil extracted from a subsurface sediment sample collect at a depth of 60-65 

cm (bottom) . 

2,30 

Exxon Valdez Reference Crude Oil 
3.0E+03 

2.5E+03 

~ 2.0E+03 

~ 1 .5E+03 

1 .0E+03 

5.0E+02 

0.0E+00 

2.0E+01 

1 .5E+01 

bA 

ND 1 .0E+01 

5.0E+00 

0.0E+00 

Exxon Valdez Ref. 

r r 

W W W W 

w w w tx R: fx ~+ ~+ ~+ * a a -~c4 n: 

~¢¢¢¢~'wwwQr~caQxx~~~~a.o.a,~~xx~~,caxa.~N 

zzzzz 2zzz IRI UUU ^NM~ UUU UUU --11 r,~ 

UU= -caw a~Qw UUUV UUU UUUw UU 

Figure 12 . Aromatic hydrocarbon profile Exxon Valdez Reference Oil (top) and slight to 

moderately weathered oil extracted from intertidal subsurface gravel sediments 

collected 5 years after the spill (bottom) . 

231 

~aG~aG~aaaar-~rrr~zzzz 

aaaaaaaaaamaaaa 

a.a.aF-ci!a:x ~~~u" aa,~a a 

a¢¢¢¢wwwwAQOr~~xx~~~z www ~~-'~-'H ~" ~" ~ rxxx .~~~~~~Zw 

z z ~aaa ~xxxaaa,r~xa.w N zzzzz .-NM ~NM aa.aa 

UUU UUU ' ' NM~ . . r.NM 

UUU~-~ UU~UUU a~QW UUUU UUU pa 
Session IV. Group Discussions 

Chair: Dr. C. Edward Proffitt 

Discussion Sections Leaders 

Oil Spills and Mangroves Ms. Donna J. Devlin 

Department of Biology 

University of Southwestern Louisiana 

Dr. Sally Levings 

Coastal Zone Analysis, Inc. 

Oil Spills and Marshes Dr. Irving A. Mendelsshon 

Wetland Biogeochemistry Institute 

Louisiana State University 

Dr. James Webb 

Marine Science Department 

Texas A&M at Galveston 

Oil Spills and Seagrasses Dr. Michael Marshall 

Mote Marine Laboratory 

Oil and Dispersants Dr. Carol B. Daniels 

U.S. Environmental Protection Agency 

233 
The Following Are Outline Summaries of Notes from the Discussion 

Sessions . 

I . Man,grOVe Discussion Group: Group Leaders - Ms . Donna J. Devlin and Dr. Sally 

Levings 

The mangrove workshop determined that several research priorities exist. 

1 . Not enough basic biology of the mangroves is known to allow a proper understanding of 

oil effects and remediation . Basic research needs include: 

A. Physiological ecology 

1 . root zone aeration 

2 . subsurface roots 

3 . adventitious buds 

4. other areas 

B. Tree growth 

C. Genetics 

D. Anatomy of plant uptake mechanisms . This is of special concern when 

dispersants are used since the mangroves inhabit impact areas . 

2. The oil death studies done thus far have been superficial ones for two reasons: 

A. Measuring effects based on leaf deaths are not accurate because in some 

cases the leaves die from the tip back and in other situations, there is a 

general wilting of the green leaves before they turn brown and die. 

B. Mode of death is dependent on the type of exposure or oil type . 

3 . Thus, a test is needed across the oil types that plots the causes of death. The following 

exposure cases should be considered : 

A. Oil floating on the tide so that the mangroves and the sediment are slightly 

coated and some die. 

B. Oil settles in the sediment and coats the plants and all die . 

235 
4. There is a window of time in any clean-up situation after which cleanup efforts are 

ineffective or even harmful . How long is that time window and how is it influenced by 

other parameters such as fisheries and wildlife? Baseline data need to be collected before 

a clean-up. 

5 . How effective are chemical oxidants in degrading oil in sediment or standing oil in a 

forest? Since oxygen diffuses slowly, oxidants may not be effective in large areas. 

6. How are resident organisms such as crabs and snails impacted by oil in the mangroves? 

7 . How beneficial are fertilizers in breaking down oil in mangrove systems? 

8. What are the sublethal versus the lethal effects of oil and dispersants? 

9. How does oil affect stressed versus healthy plants? 

10. Fundamental experiments need to be conducted to provide a baseline before 

extrapolation to field areas can be accurate . 

11 . In making on site decisions, certain pieces of information would be helpful : 

A. When should the situation be left alone? 

B. When is our interference a help? 

C. When is our interference a hindrance? 

12 . As a result of the mangrove discussions, some recommendations were made: 

A . The study of root physiology in all mangroves needs to be a research priority. 

B. The mode of injury of dead mangroves needs to be determined . 

C. The basic biology and genetics of mangroves needs to be studied. 

D. The effects on the community need to be studied and recorded so that in a spill 

event the effects can be predicted based on the type of oil and mode of oiling . 

The window of time must also be established. 

E. The effects of artificial additives, i.e . fertilizers and oxidants, needs to be studied . 

236 
II . Marsh Discussion Group: Group Leaders - Dr. Irving A. Mendelsshon and Dr. James 

W. Webb 

The workshop on marshes resulted in the following recommendations being made: 

1 . Experimental spills should be conducted for scientific research . 

2 . Oil spill remediation methodologies in wetlands need to be investigated thoroughly ; 

included in these studies should be : 

A. The efficiency and effects of physical removal 

1 . both natural and man-made sorbents 

2. vacuum removal 

3 . flushing 

B. Burning 

l . the effects of the residue 

2 . factors controlling success 

C. Bioremediation 

1 . microbes vs nutrients 

2 . the effects of varying 

a. oil types 

b. marsh and sediment types 

c. tidal energy 

3 . spills of opportunity should be used to test these techniques . 

3 . Mechanisms that enable the response agencies to incorporate scientific evaluations of the 

effects of the chosen response should be in place a prior. 

State and Federal agencies should be responsible for directing the funds needed for these 

evaluations . 

4. Research to understand the processes (biological, physical, chemical etc.) that are altered 

by oil should be conducted. 

237 
5 . Strong statistical approaches need to be developed so that all levels of oil pollution (i .e 

the spill, field research,and lab research) can be evaluated. 

6 . Sensitive environments need to be identified and the use of GIS needs to be expanded . 

238 
III . Seagrasses Discussion Group: Group Leader - Dr . Michael Marshall 

1 . The seagrass discussions resulted in the identification of several areas of research that 

were lacking. Some of the questions that the group would like to see scientifically 

answered are : 

A. What are the effects on the seagrass at the ecosystem level when it is directly 

impacted by oil? 

B. What are the impacts of physical disturbances? 

C. How do location and other physical characteristics influence the impacted 

seagrass? 

D. What happens in the long run ( > 3 years) if the oil is not removed? 

E. What are the differences in spill situations? How does exposure affect the 

seagrass i .e . oil trapped in nearby mangroves may affect the seagrass differently 

than an oilslick that floats over and by the seagrass . 

2 . The recommendations that were made are as follows : 

A. Due to the lack of controlled studies of impacts and long term studies at the 

habitat level more microcosm studies are called for. 

B. Dispersant toxicity to seagrasses and other fauna need to be studied . 

C. It should be a priority in response situations to keep the oil away from shallow 

habitats by : 

1 . burning to prevent movement to shallow water 

2. booming to prevent contact 

D. A clean up manual needs to be developed that accounts for specific oil types, 

seagrass species and the physical characteristics of the habitat . 

E. Protection priorities need to be defined. 

239 
IV . Toxicity of Dispersants Discussion Group: Group Leader - Dr. Carol B. Daniels 

1 . Problems with current knowledge: 

A. The research is always done in a laboratory with constant concentrations over a 

96-hour period . Are these 96 hour toxicity tests going overboard? In a real life 

situation, the oil concentrations would not remain constant for 96 hours. 

B. Several questions remain unanswered. 

1 . Where to use which dispersant? 

2. Are the water soluble components of the dispersants staying behind when the 

oil is gone? 

3 . How does the depth of the water affect the toxicity of the dispersants? 

2 . What actions are needed : 

A. More realistic protocols that could reflect dilution in the marine environment . 

B . Tests that are capable of mimicking currents (for example, flow through versus 

static renewal) . 

C. To determine the length of time the concentration remains high. This could be 

accomplished by monitoring the concentrations of dispersants where the oil is, not 

where it is going . 

D. When monitoring an oil spill, two issues need to be determined 

1 . What was the damage done by the oil 

2. Would the application of dispersants be worse than the alternatives? 

3 . Areas of active research : 

A. When oil is dispersed, do the water soluble particles increase or is the oil being 

broken down into microscopic particles so that suspended oil concentrations 

increase? This would indicate whether the toxicity is persistent or not . 

B. The life history regional species . At what stage are the organisms found in the top 

of the water column? 

C. The chemical properties of dispersed oil 

1 . When the oil is chemically dispersed can the suspended oil reach the 

bottom of a 30 foot water column? 

2. What is the buoyancy of this suspended oil? 

3 . How is this buoyancy effected by 

a . adsorption to particulate matter in the water 

240 
b . water currents 

c . microbial activity 

D. How persistent is the toxicity of dispersants in shallow water? Which is more 

toxic, dispersants or the alternatives? 

4. Future research needs 

A. Field research for a better understanding of the ecological effects. 

B. Develop probes to identify the hazards in situ and to monitor the recovery of survivors 

C. Develop toxicity tests which incorporate more realistic exposure regimes 

D. Standardization of testing methods for after the spill and standardized terminology . 

E. Better studies of mode of action of the dispersant relative to the toxicity . 

5 . Recommendations 

A. Prepare experimental design for follow-up studies prior to a spill 

1 . groups to conduct early studies need to be identified 

2 . funding needs to be set aside for R&D outside of clean-up 

3 . research data need to be shared 

a. spill of opportunity research should be circulated 

b. data from European countries that have been using 

dispersants in shallow water should be obtained 

4. Test spills need to be conducted to see what actually happens in the 

environment so that lab tests can be developed to accurately model real 

life 

6 . There were a few final questions: 

A. How do we go about getting test spills? It was stated that a test spill has not been 

allowed thus far because an "adequate plan" has not been submitted to the EPA. 

The bounds of what an "adequate plan" need to be determined. It was decided 

that the test spill would be a good subject for the MMS information transfer 

meeting. 

241 
B. What if we try to disperse oil and it is not effective? How will that effect 

mechanical clean ups? i .e . How effective are other clan up techniques subsequent 

to the use of an ineffective dispersant? 

C. What about biosurfacants? Should they be promoted? Will the organisms produce 

the material rapidly enough to be effective? 

242 
Gulf of Mexico and Caribbean Oil Spills in Coastal Ecosystems : 

Assessing Effects, Natural Recovery, and Progress in Remediation 

Research 

July 14-15, 1994 

Hotel Inter-Continental, New Orleans, LA 

Agenda 

Thursday July 14, 1994 

8 :15-8:30 Welcome and Introduction 

Dr. Edward Proffitt 

Louisiana Environmental Research Center 

McNeese State University 

Session I. Fxneriments And Case Studies on the Effects of Oil Sills on SeaQrass. Tidal 

Marsh, and Mangrove Ecosystems 

Chair, Dr. Edward Proffitt, McNeese State University 

8 :30-9:00 Experimental Analysis of the Effects of Oil on Mangrove Seedlings and Saplings 

Edward Proffitt' and Donna J . Devlin2 

'McNeese State University and 'University of Southwestern Louisiana 

9 :00-9 :30 The 1993 Tampa Bay Spill: Preliminary Assessment of Natural Resources 

Jane Urqhart-Donnelly and George Henderson 

Florida Marine Research Institute 

9:30-10 :00 The 1993 Tampa Bay Spill : Tracking the Fate of Oil Richard P. Pierce', E.S. 

Van V1eet2, D.L. Wetzel2, P.M . Sherblom', and M. Henry' 

'Mote Marine Laboratory and 'Dept. of Marine Science, University of South 

Florida 

10 :15-10 :45 Effects of Oil on Salt Marshes 

James Webb 

Texas A&M University at Galveston 

10 :45-11 :15 The Panama Spill: Effects of Oil and Natural Recovery : Seagrass Communities 

Michael Marshall 

Mote Marine Laboratory 

11 :15-11 :45 The Panama Spill: Effects and Natural Recovery : Mangroves 

Sally Levings 

Coastal Zone Analysis, Inc . 

243 
Session II. Remediation techniques: Reviews and Current Research 

Chair, Dr. Pasquale F. Roscigno, Minerals Management Service 

1 :30-2 :00 Evaluating Remediation Performance: Statistical and Analytical Needs 

James Catallo 

Louisiana State University 

2 :00-2:30 Dispersants : Current Toxicology Research 

Carol Daniels 

U.S . Environmental Protection Agency 

2 :30-3 :00 Critique of Upland Soil Remediation Techniques and their Applicaiton to Marine 

Spill Situations 

Paul Kostecki 

University of Massachusetts, Amherst 

3 :00-3 :30 Cleanup Techniques in Marshes : The Fine Line Between Help and Hindrance 

Rebecca Hoff 

NOAA 

Session III. An Overview of Bioremediation Studies in the Gulf of Mexico 

Chair, Dr. Irving A. Mendelsshon, Louisiana State University 

3 :45-4 :15 Fate of Oil in Salt Marsh Sediments and Stabilization of Oil Residue 

Edward Overton 

Louisiana State University 

4:15-4 :45 Microbial Inoculants for Oil Bioremediation Evaluated Using Salt Marsh 

Mesocosms 

Richard Weaver', B Crites', S. Nerallal, A. Wright', and J. Webb' 

'Texas A & M University (College Station) and 'Texas A & M Univ . at 

Galveston 

4:45-5 :15 Mitigating and Oil Spill in Timbalier Bay, LA: NOAA's Damage Assessment and 

Restoration program in Action 

Thomas Osborn, Erik Zobrist, Richard D. Hartman, B. Julius, and M. Newell 

NOAA 

244 
Friday July 15, 1994 

Session IV. (Continued) Overview of Bioremediation Studies in the Gulf of Mexico 

Chair, Dr. C. Edward Proffitt, McNeese State University 

8 :30-9 :00 Enhancement of Growth of the Marsh Natural Microbial Community 

Ralph Portier 

Louisiana State University 

9:00-9 :30 A Preliminary Assessment of the Toxicity of Bioremediation Agents on Salt 

Marsh Mesocosms : Vegetation 

Irving A. Mendelsshon 

Louisiana State University 

9:30-9 :45 Effects on the Marsh Infaunal Community 

Nancy Rabalais 

Louisiana Universities Marine Consortium 

9:45-10 :15 Use of In Situ Burning as an Oil Spill Remediation Technique 

Gus Stacey, III 

Marine Spill Response Corp . 

10:15-10 :45 Evaluation of Burning as an Oil Spill Clean-up Technique in a High Marsh 

Community Along the South Texas Coast 

Beau Hardegree, D.W. Hicks, and J . W. Tunnell, Jr . 

Center for Coastal Studies 

Texas A&M University, Corpus Christi 

Session V. Discussion and Planning: Recommending the Best Approaches for the Study o the 

Effects and Remediation of Oil Spills in Coastal Ecos sy tem 

Chair, Dr. Edward Proffitt, McNeese State University 

11 :00-1 :00 Discussion Groups 

Marshes 

Mangroves 

Seagrass 

Toxicology of Dispersants 

Facilitators 

Mendelsshon and Webb 

Devlin and Levings 

Marshall 

Daniels 

1 :30-2 :00 Group Summaries by Facilitators - General Discussion 

2:00 Closing Remarks and Adjournment 

Dr . C. Edward Proffitt 

McNeese State University 

245 
"T F ry~y~ The Department of the Interior Mission 

a i } r ~ p As the Nation's principal conservation agency, the Department of the Interior has responsibility for 

g 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 

_. p9 environmental and cultural values of our national parks and historical places; and providing for the 

4ACH 3 ~9 enjoyment of life through outdoor recreation . The Department assesses our energy and mineral 

resources and works to ensure that their development is in the best interests of all our people by 

encouraging stewardship and citizen participation in their care . The Department also has a major 

responsibility for American Indian reservation communities and for people who live in island territories 

under U.S . administration . 

The Minerals Management Service Mission 

As a bureau of the Department of the Interior, the Minerals Management Service's (MMS) primary 

responsibilities are to manage the mineral resources located on the Nation's Outer Continental Sh lf 

' 

e 

(OCS), collect revenue from the Federal OCS and onshore Federal and Indian lands, and distribute 

s those revenues . °? ~a 

~~,,,~Eru~ 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 Royalty Management Program meets its responsibilities by ensuring the efficient, timely and 

accurate collection and disbursement of revenue from mineral leasing and production due to Indian 

tribes and allottees, States and the U.S. Treasury . 

The MMS strives to fulfill its responsibilities through the general guiding principles of: (1) being 

responsive to the public's concerns and interests by maintaining a dialogue with all potentially affected 

parties and (2) carrying out its programs with an emphasis on working to enhance the quality of life for 

all Americans by lending MMS assistance and expertise to economic development and environmental 

protection .