OCS Study

BOEM 2019-077

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

Use of Small Shallow Water Oil and Gas

Platforms as Reef Habitat for

Fishes and Fouling Biota
OCS Study

BOEM 2019-077

Published by

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

New Orleans, LA

December 2019

Use of Small Shallow Water Oil and Gas

Platforms as Reef Habitat for

Fishes and Fouling Biota

Authors

Edward J Chesney

Ryan T. Munnelly

David A. Reeves

Donald M. Blatz

Prepared under BOEM Contract

M12AC00015

by

Louisiana Universities Marine Consortium

8124 Highway 56

Chauvin, Louisiana 70344

and

Department of Oceanography and Coastal Sciences

Louisiana State University

Baton Rouge, Louisiana 70803
DISCLAIMER

This report was prepared under Agreement Number M12AC00015 between the Bureau of Ocean Energy 

Management (BOEM) and the Louisiana Universities Marine Consortium. Study collaboration and 

funding were provided by the US Department of the Interior, BOEM, Environmental Studies Program, 

Washington, DC. This report has been technically reviewed by BOEM, and it has been approved for 

publication. The views and conclusions contained in this document are those of the authors and should 

not be interpreted as representing the opinions or policies of the US Government, nor does mention of 

trade names or commercial products constitute endorsement or recommendation for use.

REPORT AVAILABILITY

To download a PDF file of this report, go to the US Department of the Interior, Bureau of Ocean Energy 

Management Data and Information Systems webpage (http://www.boem.gov/Environmental-StudiesEnvData/), click on the link for the Environmental Studies Program Information System (ESPIS), and 

search on 2019-077. The report is also available at the National Technical Reports Library at 

https://ntrl.ntis.gov/NTRL/.

CITATION

Chesney EJ, Munnelly RT, Reeves DA, Baltz DM (Louisiana State University). 2019. Use of small 

shallow water oil and gas platforms as reef habitat for fishes and fouling biota. New Orleans 

(LA): U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Gulf of Mexico OCS 

Region. Study No: OCS Study BOEM 2019-077. Contract No.: M12AC00015. 

ABOUT THE COVER

The collage on the front cover are photos taking during this project by the two graduate students who

conducted most of this research: Ryan Munnelly and David Reeves. From left to right and top to bottom: 

(1) a small platform;(2) a goliath grouper under a small platform; (3) is a small platform;(4) a stone crab 

using the platform structure as a refuge; (5) a video frame of fishes around a small platform; (6) rubble 

under a platform with a young-of-the-year (YOY) mangrove snapper using a stone crab burrow as habitat; 

(7) a collage of five of the most common fishes around nearshore platforms; (8) an underwater view of a 

single pile platform and the fouling and fishes at the surface; (9) a school of YOY snapper on the side of a 

small platform during a hypoxic event.
i

Acknowledgements

This project would not have been possible without funding from the Bureau of Ocean Energy 

Management (BOEM) through the CMI program in the Department of Oceanography and Coastal 

Sciences at Louisiana State University. We thank the many people that helped with this project: research 

assistants William Childress, Kathryn O’Shaughnessy, Claire Windecker, and undergraduate students 

Alexander Jensen, Stephen Parker, Alison White, Nadia Hamed, Osman Fazili, and Caitlyn Williams. 

Their participation in various aspects of this project and a companion project, funded by the Louisiana 

Department of Wildlife and Fisheries, that studied platforms on Ship Shoal, was essential to the success 

of this project. Thank you to Dr. Brian Marx who provided expert guidance on much of the statistical 

analyses. Finally, we would like to thank Bruce Baird, Arie Roth-Kaller, and anonymous reviewers from 

BOEM for their constructive criticism of this report.
ii

Contents

1 Project Introduction .............................................................................................................................13

2 Physicochemical Features of the Louisiana Nearshore Zone: A Fish Habitat Perspective................19

2.1 Introduction..................................................................................................................................19

2.2 Methods.......................................................................................................................................21

2.2.1 Coast-wide Survey ..............................................................................................................21

2.2.2 Hydrographic Analyses .......................................................................................................22

2.3 Results of coast-wide survey ......................................................................................................23

2.3.1 Hydrographic analyses........................................................................................................31

2.4 Discussion...................................................................................................................................36

2.5 Conclusions.................................................................................................................................39

3 Coast-wide Assessment of Fish Assemblages Around Small Oil and Gas Platforms........................40

3.1 Introduction..................................................................................................................................40

3.2 Field Methods..............................................................................................................................42

3.2.1 Video processing.................................................................................................................43

3.3 Statistical Analyses .....................................................................................................................45

3.4 Results ........................................................................................................................................46

3.4.1 Statistical Results................................................................................................................52

3.5 Discussion...................................................................................................................................65

3.6 Conclusions.................................................................................................................................69

4 Habitat Suitability for Fishes Associated Around Small Oil and Gas Platforms..................................70

4.1 Introduction..................................................................................................................................70

4.2 Field Methods..............................................................................................................................71

4.2.1 Video Processing ................................................................................................................72

4.2.2 Statistical Analyses .............................................................................................................72

4.2.3 Habitat Suitability Analyses.................................................................................................73

4.3 Results ........................................................................................................................................75

4.3.1 Statistical Results................................................................................................................76

4.3.2 Habitat Suitability Analyses.................................................................................................79

4.4 Discussion...................................................................................................................................87

4.5 Conclusions.................................................................................................................................89

5 Cross Shelf Differences in Fishes Associated with Small Platforms in the Ship Shoal Area .............91

5.1 Introduction..................................................................................................................................91

5.2 Methods.......................................................................................................................................92
iii

5.2.1 Fish Assemblages Study Design ........................................................................................92

5.2.2 Statistical Analyses: Fish Assemblages..............................................................................93

5.2.3 Fish Grazing Observations..................................................................................................94

5.3 Fish Assemblage Results............................................................................................................95

5.3.1 Summertime Hydrography ..................................................................................................95

5.3.2 Comparison of Fish Assemblages ......................................................................................96

5.3.3 Fish Grazing on Fouling ....................................................................................................101

5.4 Discussion of Cross Shelf Patterns of Fishes Observed at Small Platforms............................103

5.4.1 Depth Distributions of Fishes Near Small Platforms.........................................................104

5.4.2 Seasonal and Locational Differences in Fish Relative Abundances.................................104

5.5 Chapter 5 Conclusions..............................................................................................................105

6 Patterns of Barnacle Settlement and Growth at Oil and Gas Platforms in the Ship Shoal Area......106

6.1 Introduction................................................................................................................................106

6.1.1 Settlement Plate Construction and Deployment ...............................................................107

6.1.2 Settlement Plate Processing.............................................................................................108

6.1.3 Statistical Analyses ...........................................................................................................109

6.1.4 Cross-Shelf Hydrography for Settlement Plate Studies....................................................109

6.1.5 Cross-Shelf and Depth Dependent Patterns of Fouling....................................................111

6.1.6 Cross-Shelf Barnacle Abundances ...................................................................................111

6.1.7 Cross-Shelf Patterns of A. reticulatus Biometrics .............................................................114

6.2 Patterns of Cross Shelf Secondary Production on Platforms ...................................................118

6.2.1 Oceanographic Features that May Influence Barnacle Settlement and Growth...............118

6.3 Conclusions...............................................................................................................................119

6.3.1 Implications of Barnacle Settlement Patterns for Artificial Reef Management .................119

7 Sheepshead and Stone Crab Diets at Small Oil and Gas Platforms................................................121

7.1 Introduction................................................................................................................................121

7.2 Methods.....................................................................................................................................122

7.2.1 Study Area and Field Sampling.........................................................................................122

7.2.2 Gut Contents Analysis.......................................................................................................123

7.2.3 Stable Isotopes Sample Preparation and Analysis...........................................................123

7.2.4 Statistical Analyses ...........................................................................................................124

7.3 Results ......................................................................................................................................125

7.3.1 Sheepshead and Stone Crab Biometrics..........................................................................125

7.3.2 Sheepshead Gut Contents................................................................................................126

7.3.3 Dispersion of δ13C and δ15N Values for Sheepshead and Stone Crab .............................128

7.3.4 Patterns of Source δ13C and δ15N Values and Groupings for Mixing-Models...................129
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7.3.5 Mixing Models ...................................................................................................................130

7.4 Discussion.................................................................................................................................134

7.4.1 Early and Late Summer Feeding Ecology ........................................................................134

7.4.2 Contribution of Platform-Dwelling Prey to Sheepshead and Stone Crab Diets ................136

7.4.3 Potential for Contribution from Benthic Microalgae...........................................................137

7.4.4 Evidence of Sheepshead Migration ..................................................................................137

7.5 Conclusions...............................................................................................................................138

8 Notable Observations On and Around Small Energy Platforms in the Northern Gulf of Mexico......139

8.1 Association of Stone Crabs with Small Platforms.....................................................................140

8.2 Association of Juvenile Snapper with Stone Crabs Burrows ....................................................140

8.3 Use of Platform Shell Rubble by Stone Crabs and Newly Recruited Snapper.........................141

8.4 Observations of Sea Turtles on Ship Shoal..............................................................................142

8.5 Unique Aspects of East Bay......................................................................................................143

8.6 Use of Small Platforms by Sea Birds ........................................................................................144

8.7 Growth of Macro- and Microalgae on Small Platforms .............................................................145

8.8 Sargassum-Platform Interactions in 2014.................................................................................146

8.9 Project Summary Conclusions..................................................................................................147

9 References........................................................................................................................................151
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List of Figures

Figure 1. Video frame of juvenile spadefish, lane snapper, greater amberjack, adult spadefish, yellow 

jack, cobia, and sheepshead around platform WC 148-1...........................................................................14

Figure 2. Total number of federally-managed oil and gas platforms in the northern Gulf of Mexico outer 

continental shelf (A), and net annual change in number of platforms (B) by year from 1942 to 2014. ......16

Figure 3. Examples of the common configurations of small offshore oil and gas structures sampled 

during 2013 and 2014 in the OCS of the northern Gulf off Louisiana.........................................................17

Figure 4. Regions (West, Central, East) of distinctly different hydrography based on all hydrographic data 

collected in 2013 and 2014. ........................................................................................................................21

Figure 5. Interpolated coast-wide surface, midwater, and bottom salinity (upper), and pairwise 

comparisons of salinity (lower) by region (red dashed lines) and by strata (surface, midwater, and bottom) 

for the nearshore coastal zone waters off Louisiana. .................................................................................26

Figure 6. Interpolated coast-wide surface, midwater, and bottom temperature (upper) and pairwise 

comparisons of temperatures (lower) by region and by strata (surface, midwater, and bottom) for the 

nearshore coastal zone off Louisiana. ........................................................................................................27

Figure 7. Interpolated coast-wide surface, midwater, and bottom density (upper), and pairwise 

comparisons of density (lower) by region (red lines) and strata (surface, midwater, and bottom) of the 

nearshore coastal zone waters off Louisiana..............................................................................................28

Figure 8. Interpolated coast-wide surface-to-bottom density difference (upper) and pairwise comparisons 

for surface-to-bottom density difference (lower) by region (red lines) and dominant sediment types (sand 

or mud) for the nearshore coastal zone waters off Louisiana.....................................................................29

Figure 9. Interpolated results of the 2013 coast-wide survey for surface, midwater, and bottom dissolved 

oxygen concentration for platform sites in the nearshore waters off Louisiana..........................................32

Figure 10. Factor analysis showing (upper) all hydrographic station , and (lower) two standard errors 

around the centroid means for the nearshore waters by regions off Western, Central, and Eastern 

Louisiana.....................................................................................................................................................33

Figure 11. Comparison of interpolated coast-wide principal components for Factors 1–3 (upper) and 

pairwise comparisons for Factor 3 (lower) by region (West, Central, East), dominant sediment type (sand 

or mud) and by year (2013–2014). .............................................................................................................34

Figure 12. Pairwise comparison of vertical extent (left) and intensity (right) of hypoxia (defined as less 

than 50% saturation) by region (West, Central, and East) and dominant sediment types (sand or mud) 

around platforms in the nearshore zone off Louisiana................................................................................35

Figure 13. Central region composite interpolations of the principal component factors (1–3) analyzed by 

water depth. ................................................................................................................................................36

Figure 14. Examples of three levels of complexity for small nearshore platforms (A, B, C) and an example 

of larger platforms (D). ................................................................................................................................42

Figure 15. Video frames of the bottom of a small platform (SS 93-66) on two different days in 2014 

showing the differences in visibility at the same site. .................................................................................44

Figure 16. Map of sampling stations and hydrographically distinct zones (West, Central, and East) from 

coastwide surveys of small oil platforms in nearshore waters of the outer continental shelf off Louisiana.

....................................................................................................................................................................44
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Figure 17. YOY greater amberjack and almaco jack (A), adult and YOY cobia (B), YOY blue runner, 

rainbow runner, and bar jack (C), YOY red and lane snapper (D), age 1–2 juvenile red, lane, and gray 

snapper, adult red drum, sheepshead, and spadefish (E), and YOY gag grouper (F)...............................51

Figure 18. Pairwise comparison of species richness (left), and the effective number of species (ENS) 

based on Shannon-Weiner diversity (right) across nearshore Louisiana by region (West, Central, and 

East), dominant sediment type (sand or mud), and in the presence or absence of hypoxia, controlling for 

sediment composition. ................................................................................................................................53

Figure 19. Plot of distance-based redundancy analysis (dbRDA) displaying the assemblage distributions 

in relation to three principle component factors, and four additional variables of importance (longitude, 

year, % sand, and platform complexity)......................................................................................................54

Figure 20. Results of a SIMPER analysis comparing the interregional differences (West, Central, and 

East) in the mean MAXNO pairwise dissimilarities of fish assemblages around small nearshore platforms.

....................................................................................................................................................................58

Figure 21. Results of a SIMPER analysis comparing the interannual differences (2013, 2014) in the 

mean MAXNO pairwise dissimilarities of fish assemblages around small nearshore platforms. ...............59

Figure 22. Results of a SIMPER analysis comparing the relationship between dominant sediment type 

(sand or mud) and the mean MAXNO pairwise fish assemblage dissimilarities around small platforms...60

Figure 23. Results of a SIMPER analysis comparing the relationship between the presence or absence 

of hypoxia (DO < 50% saturation) and the mean MAXNO pairwise dissimilarities of fish assemblage 

around small nearshore platforms. .............................................................................................................61

Figure 24. Results of a SIMPER analysis showing the relationship between platform complexity (1–3) 

and the mean MAXNO pairwise fish assemblage dissimilarities around small nearshore platforms.........62

Figure 25. Location of all platform sampling sites with usable video and hydrographic data (n = 150) that 

were included in the habitat suitability analyses. ........................................................................................72

Figure 26. Scaled photo-collage of the fishes and the submerged structure of platform ST 21-GC plotted 

with salinity, temperature, depth, and DO profiles show fish distribution relative to water quality and water 

quality strata ranging from supersaturated to hypoxic. ...............................................................................74

Figure 27. Pairwise comparisons of the vertical extent the fraction of the nearshore water column is used 

by fishes (A) for all hypoxic sites (n = 64) plotted by region (West, Central, and East), year (2013 and 

2014), and dominant sediment type (sand or mud) with an example of young-of-the-year red and lane 

snapper up in the water column at a nearshore platform in response to hypoxic conditions (B). ..............75

Figure 28. An example of extreme vertical compression of suitable fish habitat around a nearshore 

platform where the entire water column is either oxygen supersaturated or hypoxic except for one small 

layer between 5 and 6 m below the surface. ..............................................................................................79

Figure 29. Microhabitat plot of centroid means (bubbles ±2SEs) describing the environmental use 

patterns of 26 species relative to three principal component factors for hypoxic (DO > 50% saturation) 

(red) and not hypoxic (blue) water columns................................................................................................80

Figure 30. Standardized suitability (SS) for the responses to salinity of 11 fish species observed around 

small nearshore platforms...........................................................................................................................82

Figure 31. Standardized suitability (SS) for the responses to temperature of 11 fish species observed 

around small nearshore platforms. .............................................................................................................83

Figure 32. Standardized suitability (SS) for the responses to DO of 11 fish species observed around 

small nearshore platforms...........................................................................................................................84
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Figure 33. Standardized suitability (SS) for the responses to water depth of 11 fish species observed 

around small nearshore platforms. .............................................................................................................85

Figure 34. Standardized suitability (SS) for the responses to secchi depth of 11 fish species observed 

around small nearshore platforms. .............................................................................................................86

Figure 35. Chart of platform locations where fish assemblages were sampled repeatedly (open circles) 

and sampled once (black circles) during the summer of 2016. ..................................................................92

Figure 36. Bottom water DO (mgl-1) at shoal (black circles) and seaward platforms (white circles) from 

May 31 to September 11, 2016...................................................................................................................93

Figure 37. Centroids of shoal and seaward platforms before, during and after the hypoxia season where 

Factor 1 was interpreted as a freshwater influence gradient, Factor 2 interpreted as an oxygen depletion 

gradient, and Factor 3 interpreted as a temperature gradient. ...................................................................96

Figure 38. Number of species (species richness; A) and Shannon-Weiner Diversity (H’; B) at shoal and 

seaward platforms before, during, and after the hypoxia season...............................................................97

Figure 39. A principal coordinates analysis showing the similarity of fish assemblages at shoal and 

seaward platforms before, during, and after the hypoxia season...............................................................98

Figure 40. Mean MAXNO estimates (±1SE) of gray snapper (A), sheepshead (B), Atlantic spadefish (C), 

blue runner (D), and Atlantic bumper (E) at shoal and seaward platforms before, during, and after the 

hypoxia season. ..........................................................................................................................................99

Figure 41. Distribution of fish counts by 3 m depth bins contrasted with DO profiles at shoal (A&B) and 

seaward (C&D) platforms before, during, and after hypoxia.....................................................................100

Figure 42. A four-second time lapse sequence of a gray triggerfish removing a barnacle from platform 

substrate and chasing the barnacle as it falls...........................................................................................102

Figure 43. Number of grazing behaviors (m-2 h-1) by sheepshead at a series of nine small platforms in the 

Ship Shoal blocks of the nearshore zone. ................................................................................................103

Figure 44. An example of a settling plate before (A) and after (B) a 92-day deployment (August 21–

November 21, 2016). ................................................................................................................................107

Figure 45. Chart of locations of platforms where settling plates were deployed in 2015 and 2016. .......108

Figure 46. Depth profiles of DO (mg l-1), temperature (oC), and salinity (PPT) in 2015 and 2016 at 

platforms on days when settlement plates were deployed or retrieved....................................................110

Figure 47. Patterns of fouling accumulation (g m-2 d-1) for each year-by-depth combination of settlement 

plates (2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 7m) with varying distance to shore. .......................111

Figure 48. Post-spat (A) and spat Amphibalanus spp. abundances (B), post-spat (C) and spat 

Megabalanus tintinnabulum abundances (D) for each year-by-depth combination of settlement plates 

(2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 7m) with varying distance to shore. ..................................112

Figure 49. Amphibalanus reticulatus height (mm day-1; A), width (mm day-1; B), tallness (height/width; 

C) for each year-by-depth combination of settlement plates (2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 

7m) with varying distance to shore. ..........................................................................................................115

Figure 50. Amphibalanus reticulatus total wet weight (mg day-1), and tissue wet weight (mg day-1) for 

each year-by-depth combination of settlement plates (2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 7m) 

with varying distance to shore...................................................................................................................116
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Figure 51. Tissue/Total Wet Weight (percent tissue) of A. reticulus across distance from shore and height 

in 2015 (A) and 2016 (B)...........................................................................................................................117

Figure 52. Map of study area. ..................................................................................................................123

Figure 53. Distance based redundancy analysis (dbRDA) showing the similarity of sheepshead prey at 

shoal and seaward platforms during the early and late summer. .............................................................128

Figure 54. Sheepshead liver (A), sheepshead muscle (B), and stone crabs (C) in bivariate δ13C and δ15N 

with overlaid SIBER ellipses. ....................................................................................................................129

Figure 55. Estimates of the standard ellipse areas for sheepshead liver (A), sheepshead muscle (B), and 

stone crabs (C)..........................................................................................................................................130

Figure 56. Sheepshead liver during the early (A) and late summer (B), and sheepshead muscle in the 

early (C) and late summer (D) plotted in bivariate δ13C and δ15N along with values of sources (sea lettuce, 

barnacles, sediment, filamentous algae). .................................................................................................132

Figure 57. Mixing-models for early (C) and late sheepshead liver (D) showing the percent contribution of 

sources to sheepshead diet. .....................................................................................................................133

Figure 58. Stone crabs during the early (A) and late summer (B) plotted in bivariate δ13C and δ15N along 

with values of sources (sea lettuce, barnacles, sediment, filamentous algae), and mixing-models for early 

(C) and late stone crabs (D) showing the percent contribution of sources to stone crab diet. .................135

Figure 59. Vector plots showing δ15N and δ13C of sheepshead muscle and liver in the early (A) and late 

summer (B). ..............................................................................................................................................136

Figure 60. Use of platform fouling community and platform structure by stone crabs..............................140

Figure 61 a, b, c, d. A composite of four video frames showing a newly settle juvenile snapper retreating, 

first into and then out of a stone crab burrow, when threatened by a diver..............................................141

Figure 62. Juvenile snapper utilizing rubble around the base of a small platform...................................142

Figure 63. Large sea turtle captured on video at the base of a small platform on Ship Shoal................142

Figure 64. An example of one of 4 Goliath grouper caught on video around a small platform in East Bay.

..................................................................................................................................................................143

Figure 65. An example of the unique combination of fouling communities on small platforms of Easy Bay 

near the water surface (A) and bottom (B)................................................................................................144

Figure 66. Two examples of brown pelicans getting caught by the head between the guard rails at a Ship 

Shoal platform (left) and the Ship Shoal lighthouse (right) . .....................................................................145

Figure 67. Examples of brown pelicans (left, right) resting on small unmanned platforms in the nearshore 

zone...........................................................................................................................................................145

Figure 68. Examples of macro and micro algae growing on the intertidal (upper left, right) and subtidal 

(lower) parts of small platforms in the nearshore coastal zone. ...............................................................146

Figure 69. Sargassum caught on a small platform. .................................................................................147

Figure 70. Magnificent frigate birds (Fregata magnificens) atop a well protector in the South Pass 28 

block..........................................................................................................................................................150
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List of Tables

Table 1. Summary of environmental measurements reported as a mean, during the initial coast-wide 

survey (CW) and summer platform surveys of 2013 and 2014 ..................................................................30

Table 2. Rotated factor loadings of 10 environmental variables measured throughout the nearshore zone 

off Louisiana................................................................................................................................................31

Table 3. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type on 

Factor 3 (interpreted as DO depletion in the water column).......................................................................32

Table 4.Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on 

extent of hypoxia.........................................................................................................................................35

Table 5.Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on 

intensity of hypoxia......................................................................................................................................35

Table 6. Distributions, relative abundance and percent occurrence estimates of fishes around small 

platforms sorted by region (West, Central, and East) and year..................................................................47

Table 7. Distributions, relative abundance and percent occurrence estimates of fishes around small 

platforms sorted by region and year ...........................................................................................................48

Table 8. Summary of environmental measurements reported as a mean, during the initial coast-wide 

survey (CW) and summers of 2013 and 2014 ............................................................................................49

Table 9. Summary of environmental measurements reported as a mean, during the initial coast-wide 

survey (CW) and summers of 2013 and 2014 ............................................................................................50

Table 10. Three-way ANCOVA for type III fixed effects of region, year, and hypoxia on species richness, 

controlling for relative volume sampled, and % sand. ................................................................................52

Table 11. Three-way ANCOVA for type III fixed effects of region, year, and hypoxia on Shannon-Weiner 

effective number of species (ENS), controlling for relative volume sampled, and % sand. .......................52

Table 12. Summary of a non-parametric distance-based linear model (distLM) analysis and a distancebased redundancy analysis (dbRDA) of partial correlations relating coordinate axes, orthonormal X 

variables and variation explained................................................................................................................53

Table 13. PERMANOVA for type I fixed effects of region and year, controlling for sediment composition 

(% sand), hypoxia, and relative volume sampled. ......................................................................................55

Table 14. PERMANOVA pairwise comparisons of significant interregional (West, Central, and East) and 

interannual (2013 and 2014) assemblage shifts.........................................................................................55

Table 15. PERMANOVA for type I fixed effects of dominant sediment type (Sed) and hypoxia, controlled 

for longitude (Long), year, and relative volume sampled............................................................................56

Table 16. PERMANOVA pairwise comparisons of significant assemblage shifts for dominant sediment 

type (Sed) (sand or mud) and presence or absence of hypoxia.................................................................56

Table 17. Results of SIMPER pairwise dissimilarities (DISS) analyses for the dominant components of 

the fish assemblages around small nearshore platforms compared across three coastal regions (West, 

Central, and East) off Louisiana..................................................................................................................63

Table 18. Results of SIMPER pairwise dissimilarities (DISS) analyses for the dominant components of 

the fish assemblages observed around small nearshore platforms comparing platforms by sampling year 
x

(2013 and 2014), dominant sediment type (Sed) (sand or mud) and presence or absence of hypoxia (DO 

< 50% saturation)........................................................................................................................................64

Table 19. Results of SIMPER pairwise dissimilarities (DISS) analyses for dominant components of the 

fish assemblages observed around small nearshore platforms comparing three levels of platform 

complexity (1=least complex to 3= more complex).....................................................................................65

Table 20. Three-way ANCOVA for type III fixed effects of region, year, and dominant sediment type 

(Sed) effects on the extent of habitat restriction to fishes, controlling for depth.........................................76

Table 21. Results of a mixed generalized linear model for the physicochemical responses of the 11 

species making up the dominant fish assemblages around small nearshore platforms. ...........................77

Table 22. Results of a mixed generalized linear model for the physicochemical responses of the 11 

species making up the dominant fish assemblages around small nearshore platforms. ...........................78

Table 23. Results of a rotated factor loadings of 6 environmental variables measured during coastal 

surveys around small platforms throughout the nearshore zone off Louisiana. .........................................80

Table 24. Factor loadings for Factors 1–3, eigenvalues, variance explained by each factor and 

cumulative variance explained with bold values representing those that were used for factor 

interpretation. ..............................................................................................................................................95

Table 25. Occurrence (percentage of videos where each individual species was present), mean counts, 

and minimum and maximum counts of each species identified on video around small platforms in summer 

of 2016. .......................................................................................................................................................95

Table 26. Slopes, t-values, and P-values for the effects of Factors 1–3 on species richness, ShannonWeiner Diversity and counts of gray snapper, sheepshead, atlantic spadefish, blue runner, and atlantic 

bumper. .......................................................................................................................................................97

Table 27. Platform names, distances to shore, settlement plate deployment and recovery dates, and the 

total time of deployment (days).................................................................................................................107

Table 28. Model intercepts (Int.), degrees of freedom error (D.F.), and t-values and slopes () for fouling 

community variables included in generalized linear mixed model of fouling accumulation, barnacle 

settlement rates and barnacle biometrics on settling plates located at different platforms, depths and 

deployed in different years........................................................................................................................113

Table 29. Barnacle species and the number of barnacles for each species included in analyses of counts 

and biometrics...........................................................................................................................................114

Table 30. Number of sheepshead and stone crabs, whether platform associated macro algae, barnacles, 

and sediment (sources) where collected, and number of platforms where sheepshead and benthos (stone 

crabs, platform associated algae, barnacles, sediment) were collected at shoal and seaward platforms 

(Sea) in 2016.............................................................................................................................................124

Table 31. Mean percent composition, standard error, and percentage of guts where individual prey items 

occurred for all sampled sheepshead.......................................................................................................127

Table 32. δ13C, SE (standard error) of δ13C, δ15N, SE of δ15N, and sample sizes (n) of filamentous algae 

(red algae, green algae, brown algae), sea lettuce, barnacles, and sediment collected in the early (May 

31 – Jun 20) and late (Aug 19 – Sep 11) summer of 2016.......................................................................131
xi

List of Abbreviations and Acronyms

Short Form Long Form

ANCOVA analysis of covariance

ANOVA analysis of variance

adu. Adult

bird’s foot “Balize” Delta of the Mississippi River

BOEM Bureau of Ocean Energy Management

BSEE Bureau of Safety and Environmental Enforcement

dbRDA distance-based redundancy analysis

coastal zone The coastal waters (including the lands therein and thereunder) and the adjacent 

shorelands (including the waters therein and thereunder), strongly influenced by each 

other and in proximity to the shorelines of the several coastal states, and includes 

islands, transitional and intertidal areas, salt marshes, wetlands, and beaches (Coastal 

Zone Management Act of 1972).

Den denominator

Df degrees of freedom

DISS dissimilarity percentage

distLM distance-based linear model

DO dissolved oxygen

E environmental interval in the habitat suitability formula

ENS effective number of species (back transformed Shannon-Weiner Index)

F presence of species of interest in the habitat suitability formula

FAD fish aggregation device

FAO Food and Agriculture Organization of the United Nations

GLM generalized linear model

Gulf Gulf of Mexico

GBD gas bubble disease

H′ Shannon-Weiner diversity

HAB harmful algal bloom

Head of Passes Southwest Pass, South Pass, and Pass A Loutre of the Mississippi Delta

HSI habitat suitability index

jacket The oil and gas platform support structure extending from below the sediment to the 

topsides decking

juv. juvenile fish; age 1–2

LATEX shelf Louisiana–Texas shelf

LC Loop Current

LCC Louisiana Coastal Current

LCE Loop Current eddy

LDWF Louisiana Department of Wildlife and Fisheries

MANOVA multivariate analysis of variance

MAXNO maximum number of relative abundance estimate for a given species

nGOM northern Gulf of Mexico

NMFS National Marine Fisheries Service

nearshore zone coastal zone of the outer continental shelf between 5–25 m depth

NTU Nephelometric Turbidity Units

Num numerator

OCS outer continental shelf

P relative frequency of occurrence in the habitat suitability formula

PCA principal component analysis

PERMANOVA permutational multivariate analysis of variance

pi The total proportion of the ith species in the Shannon-Weiner diversity formula

psu practical salinity units

platform oil and gas structure

PRIMER Plymouth Routines in Multivariate Ecological Research

S suitability

SD standard deviation

SEDAR Southeast Data Assessment and Review

shallow waters< 18 m depth
xii

Short Form Long Form

SAS Statistical Analysis System

SLR Simple Linear Regression

SIMPER Similarity Percentages

YOY young-of-the-year

Equations

HH′ = −∑i ppilnppi

ENS = exp(HH′) = exp(−∑i ppilnppi)

S = P(E│F) / P(E)
13

1 Project Introduction

Louisiana is home to one of the most productive coastal regions in the United States, in terms of two 

industries of seemingly conflicting interests: fisheries and petroleum extraction. Since the 1950s, annual 

fisheries landings for Louisiana have accounted for ~66% of the catch, and 39% of the market value of 

the Gulf of Mexico (Gulf), making Louisiana the second most productive US fishing state after Alaska 

(Chesney et al. 2000). The majority of these landings occur on the Louisiana outer continental shelf 

between Mississippi and Eastern Texas, known as “the Fertile Fisheries Crescent” (Günter 1963). The 

Louisiana coastline is the site of the largest contiguous tract of wetlands in the US; it is inclusive of > 

25% of all US coastal wetlands (Alexander et al. 1986). Four of the five largest rivers discharging into 

the Gulf drain into Louisiana’s coastal zone (Dahm et al. 2005). Two of these are terminal distributaries 

of the largest river in North America: the Mississippi River. The Mississippi River drains ~41% of the 

US, and some of Canada (Turner and Rabalais 1991), making it the third largest drainage on Earth 

(Milliman and Meade 1983). Within this watershed, 76% of the top ten US cash crops are grown 

(Ribaudo et al. 2001). The high primary productivity of the Fertile Fisheries Crescent system is driven by 

the river-based nutrient discharge (Günter 1963; Nixon et al. 1986) that has been elevated by agriculture 

within the drainage basin (Turner and Rabalais 1991). Thousands of oil and gas structures (platforms) 

have been installed along the Louisiana and Texas coast to exploit the vast oil and gas deposits on the 

continental shelf. Collectively, this extensive infrastructure created the largest “de facto” artificial reef 

network on Earth (Krahl 1986), which exists within one of the highest productivity regions of the US 

coastal zone. This is a truly unique combination that has co-existed for decades.

The unparalleled network of oil and gas platforms throughout coastal Louisiana’s inshore waters extends

to the deep Gulf which adds diversity and another dimension to fish habitat. The many platforms also 

support the extensive pipeline system that stems from the many production structures. As high-relief (or 

“maximum relief”) reef-like features, platforms attract dense aggregations of pelagic, demersal, and 

benthic fishes (Figure 1) that would normally inhabit natural hard bottoms that provide comparatively 

little vertical relief (Parker et al. 1983; Gallaway and Cole 1998). The FAD (fish aggregating device) 

effect of platforms allows fishermen to more efficiently target and exploit reef associated fishes, making 

platforms favored fishing sites for commercial and recreational anglers and divers (Ditton and Graefe 

1978). Although principally driven by high primary productivity and inshore catches, platform fishing 

contributes to the highest recreational catch rates of any US fishery (Stanley and Wilson 1990), and > 

70% of all nearshore recreational fishing occurs at platforms (Witzig 1986). In addition, platforms might 

provide refuges for small fishes vulnerable to trawling.

Platform distribution has been in constant evolution since the onset of coastal drilling in the northern Gulf 

of Mexico (nGOM) began in the 1940’s (BOEM 2015; Figure 2). There was a “building period” from 

1960 to1991, when net annual increases regularly exceeded 100 platforms (mean ~113 ± 12 [95% CI]), 

and the standing platform count grew from 353–3,959 platforms (Figure 2). From 1992 until 2006 the 

count was high and relatively stable with a mean count of ~3,964 ± 26 (95% CI) platforms per year, a 

mean net annual change of −4 ± 11 (95% CI), and a peak count of 4,049 platforms was reached in 2001. 

This peak number represented more than one-half of the coastal platforms globally (Hamzah 2003). 

During this peak period, ~79% of all platforms were small (unmanned and unattended caissons, fixed 

platforms, and well protectors), ~43% were in shallow waters (≤ 15 m depth), and ~37% were both small 

and in shallow water. Currently, platform numbers are rapidly diminishing, with disproportionate 

removal from the nearshore environment (Gallaway and Cole 1998). The net loss of platforms from 

2007–2016 (mean −179 ± 51 [95% CI]) reduced the count from 3,900 platforms in 2006 to 2,130 

platforms in 2016 (BOEM 2017). Of these removals, ~93% were small, ~41% were in shallow water, and 

~39% were small and in shallow water. This change reflects an industry shift into deeper waters where 

less exploited or newly discovered hydrocarbon deposits exist (Hirsch et al. 2005).
14

Figure 1. Video frame of juvenile spadefish, lane snapper, greater amberjack, adult spadefish, yellow jack, 

cobia, and sheepshead around platform WC 148-1. 

The influence of the Mississippi River on the Fertile Fisheries Crescent varies seasonally with river stage 

and annual changes in peak discharge (Günter 1963; Milliman and Meade 1983). Throughout the year 

salinity, temperature, and nutrient loads are directly affected by river inputs (Ho and Barrett 1975; 

Wiseman et al. 1982). During calm summer days the eutrophic parts of Louisiana’s coastal waters can 

stratify and develop intense surface phytoplankton blooms (Pokryfki and Randall 1987; Rabalais et al. 

1991; Justić et al. 1993). When this primary production dies and sinks, hypoxic bottom waters (typically 

defined as dissolved oxygen [DO] < 2.0 mg l−1

) develop and create the second largest hypoxic zone on 

Earth (Rabalais et al. 2002a). Although fisheries of the region have demonstrated remarkable resilience 

(Chesney et al. 2000), water-quality degradation is considered a threat to a healthy ecosystem (Diaz and 

Rosenberg 1995, 2008). One of many attributes of this system that may buffer some of the effects of 

hypoxia is the fact that it is an open shelf system, which can allow mobile fauna to avoid affected areas 

through lateral movement along the coast, or by movement to unaffected depths (Caddy 1993; Chesney 

and Baltz 2001). However, many species remain, especially around platforms and as hypoxia develops 

they adjust vertically in the water column to avoid exposure to low dissolved oxygen (DO) (Stanley and 

Wilson 1990).

In the nGOM, hypoxia is patchy in distribution, and can be ephemeral in nature (Rabalais et al. 1991), 

particularly in nearshore waters (Renaud 1986; Hazen et al. 2009). Much of this variability results from 

bathymetric interactions with freshwater outflow from the Mississippi-Atchafalaya river system, and the 

effects of wind speed and direction on river plume distributions and stratification (Rabalais et al. 1991; 

Hetland and DiMarco 2008; DiMarco et al. 2010). Large sandy shoals on the inner shelf provide 

substantial vertical relief within nearshore waters and may be among the most resistant and resilient 

features of the Louisiana nearshore zone to hypoxia. Because of this, shoals may serve as refuges for 

fishes (Chesney and Baltz 2001; Dubois et al. 2009). Unfortunately, the ecological value of sand shoals 

as fish habitat is not yet fully understood, particularly within an environment experiencing regular 

hypoxic events, such as the nGOM. Instead, sand shoals are seen primarily a resource for barrier island 
15

renourishment projects (Dubois et al. 2009 and references therein). Large-scale dredging of these 

exhaustible features off Louisiana began in 2014 (BOEM 2015).

From a habitat perspective, shoal dredging and platform removals jointly represent a dramatic 

environmental disturbance within the nearshore zone. Both shoals and platforms offer rare types of 

benthic habitat relative to their mud-dominated surroundings. Hard bottom substrates are particularly rare 

in the nGOM (Parker et al. 1983), and platforms offer a variety of ecological services which do not occur 

naturally in abundance within the coastal waters off Louisiana (Gallaway and Cole 1998). Platform 

removal also represents a more immediate and direct disturbance when considering that 75–80% of all 

removals are achieved using explosives (Bull and Kendall 1994; Southeast Data Assessment and Review; 

SEDAR 2013). Explosive removal kills or fatally concusses all aggregated fishes within 50 m of the 

platform (Gitschlag 1997), where fish density and biomass is highest (Stanley and Wilson 1997, 2003).

Current US Coast Guard regulations generally require 85 ft (~ 26 m) of navigational clearance above any 

unmarked submerged structure. Areas frequented by shrimp trawlers are also a consideration for artificial 

reef placement. Consequently, an effective nearshore artificial reef program in the nGOM will require 

careful planning that includes: 1) deploying materials in accessible areas of natural resiliency of fish 

assemblages to hypoxia, 2) sites away from areas of heavy navigation and 3) sites in areas not of interest 

to shrimp fishermen. This is a difficult set of criteria to meet.

Although numerous studies have focused on fishes associated with platforms in the nGOM, no studies 

have focused on the dominant contingent of small, shallow-water platforms. Examples of some of the 

350 structures visited during 2013 and 2014 are shown in Figure 3. The presence of several large sandy 

shoals, and the abundance of platforms located in the nearshore coastal zone creates a dynamic array of 

natural and manmade habitat. The biophysical coupling of river-influenced coastal waters subject to 

variable and periodic hypoxic events within the shallow nearshore zone can create a dynamic and 

occasionally stressful environment for bottom-associated fishes.
16

Figure 2. Total number of federally-managed oil and gas platforms in the northern Gulf of Mexico outer 

continental shelf (A), and net annual change in number of platforms (B) by year from 1942 to 2014.
17

Figure 3. Examples of the common configurations of small offshore oil and gas structures sampled during 

2013 and 2014 in the OCS of the northern Gulf off Louisiana.

The principal objectives of the studies outlined in this report were to:

1) Characterize the fish assemblage(s) associated with small, unoccupied platforms located in the 

nearshore areas of the coastal zone that act as de facto artificial reefs. The 2013–2014 studies were 

especially focused on the use of these structures by young-of-year (YOY) stages of red snapper and 

juveniles of other important fishery species,

2) Identify major regional and intraregional differences in fish assemblages associated with potential 

drivers such as the physicochemical differences throughout the study area (e.g., salinity, temperature, 

depth, dominant sediment type (sand or mud), presence or absence of hypoxia (DO < 50% saturation) or 

differences in platform complexity (single piling, multiple pilings without crossbeams, or multiple pilings 

with crossbeams),

3) Evaluate the inter-annual variation in fish assemblages and water quality parameters around small 

platforms, and
18

4) Evaluate some of the unique ecosystem services that platforms provide for fishes and other biota 

residing around or on platforms in the nearshore zone of the outer continental shelf.

These objectives were implemented through a series of studies of small platforms. In 2013–2014 we 

conducted a coast wide survey of the hydrography and fish assemblages associated with small platform in 

the nearshore zone off Louisiana (Chapter 1–4). In 2015-2016 the research focused on studies of small 

platforms in the area of the Ship Shoal blocks where we documented some of the cross shelf patterns in 

use of small platforms by fishes, the growth rates and composition of the fouling community and grazing 

patterns of sheepshead and other fishes on platform biota (Chapter 5–6).
19

2 Physicochemical Features of the Louisiana Nearshore Zone: A 

Fish Habitat Perspective

2.1 Introduction

According to federally defined coastal boundaries, the Louisiana coastline measures 639 km or, when 

including all tidally influenced coast, 12,426 km (NOAA 1975). This makes it either the fifth or the third 

longest coastline within the United States. With > 25% of the coastal wetlands and 40% of the total salt 

marsh habitat of the continental US (Alexander et al. 1986), this porous landscape is among the most 

productive natural systems on Earth. This vast and productive ecosystem was created by the wandering of 

the Mississippi River and its distributaries and deltas (Coleman and Gagliano 1964). The same process 

also deposited large sand shoals, which offer local bathymetric highs of coarse-grained sediments marbled 

throughout the mud-dominated benthic coastal environment (Penland et al. 1988, 1989). Since European

settlement of the region, the Mississippi River has been constrained within the anthropogenically 

manipulated infrastructure. The river is no longer allowed to wander; discharge is confined to two highly 

regulated primary delta complexes that have minimal and, in many ways, insufficient influence on the 

broader historical floodplains.

Because the Mississippi River accounts for such a large percentage of the drainage of the US, the 

influence of this large amount of freshwater on the coastal ecosystem where it discharges is a significant 

driver of ecosystem dynamics. The mean long-term discharge of the Mississippi dating back to 1817 is 

17,000 m3 sec−1 (Turner and Rabalais 2003), amounting to ~537 km3 of fresh water per year into the 

nGOM. About 70% of this water is discharged with near equal distribution east and west of the Balize 

Delta of the Mississippi River (Bird’s Foot) (Wright 1970), at the Head of Passes, through Southwest 

Pass, South Pass, and Pass A Loutre (Walker et al. 2005). Outflow from the Atchafalaya River is 

controlled not to exceed 30% of total outflows, and takes place at the Atchafalaya and Wax Lake deltas 

within Atchafalaya Bay.

A practical designation of Louisiana’s nearshore zone is defined between the 5–25 m isobaths (Chesney 

and Baltz 2001; Switzer et al. 2006). Most of the Louisiana coastline is adjacent to a broad and shallow 

shelf. Shallow-waters of coastal Louisiana encompass those shelf waters most influenced by the volume 

of fresh, cool, highly-turbid, and nutrient-laden effluent of the Mississippi and Atchafalaya rivers. In 

order to understand the influence of freshwater input to this coastal zone and how it may affect the 

distribution of fishes around small platforms in the nearshore environment, this study focused on 

platforms in the nearshore waters off Louisiana. Throughout this estuarine-marine ecotone, salinity is the 

dominant driver of water density, and regional mixing regimes reflect bathymetric interactions that cause 

water column instabilities or promote stratification.

The Mississippi and Atchafalaya rivers influence the nearshore zone differently. Outflow from South 

Pass of the bird’s foot is ~60 km south, and ~230 km east of the Wax Lake Delta of the Atchafalaya. The 

bathymetry of the shelf is broad in the west and narrows to the east. The Mississippi discharges within 

~15 km of the shelf slope. In contrast, the Atchafalaya lies ~160 km from the slope. Prevailing mixing 

and stratification regimes are driven largely by the interactions between bathymetry and freshwater source 

off Louisiana. To the east, the buoyant river plume is entrained along the surface and does not directly 

interact with the bottom, resulting in a highly-stratified water column. Conversely, to the west, the Wax 

Lake and Atchafalaya deltas are inset within Atchafalaya Bay. River water outflows onto the broad and 

shallow Atchafalaya Shelf, resulting in greater direct interaction with the bottom, and greater mixing and 

reduced stratification throughout the area. These physical traits also have implications for coastal 

hypoxia, creating a dynamic environment of close physical and biological coupling (Wiseman and 

Sturges 1999). From a habitat standpoint, euryhaline distributions and assemblage compositions reflect 
20

individual species (Remmert 1983) or life-stage (Livingston 1988; Baltz and Jones 2003) tolerances to 

many variables. In such an environment, physicochemical variation may take precedence over other 

factors influencing habitat selection within an environmental mosaic (Baltz et al. 1997). Because many 

inshore and offshore species and the various life history stages of ecological and economic importance 

use transition environments such as the nearshore zone, understanding physicochemical variability in this 

area is important for resource management.

The annual hypoxic event on the Louisiana-Texas Shelf is believed to be expanding in response to a 

persistent increase in nutrient input from the Mississippi River drainage. Since 1993, a mean hypoxic 

area of ~15,000 km2

, with peaks upward of 22,000 km2, has established it as the second largest hypoxic 

area on Earth (Rabalais et al. 2002a; Rabalais et al. 2007). The primary source of this excessive nutrient 

load is outflow from the Mississippi and Atchafalaya rivers (Justić et al. 1993; Atwood et al. 1994; Turner 

and Rabalais 1991; Rabalais et al. 2007). River flow typically peaks in early April (Turner and Rabalais 

1991), and, although, discharge typically drops in late summer it remains a significant volume of 

freshwater discharge throughout the summer months,when high temperatures and southwest winds that 

are upwelling-favorable intensify stratification of coastal waters (Pokryfki and Randall 1987; Rabalais et 

al. 1991; Wiseman et al. 1997). Nutrient contributions from Louisiana’s coastal bays and wetlands 

further contribute to developing and sustaining hypoxia through zooplankton export (Dagg et al. 2007) 

and marsh erosion (Wilson and Allison 2008; Bianchi et al. 2008; Bianchi et al. 2009; Bianchi et al. 

2011). Moreover, in-situ processes of nutrient recycling, and primary and secondary production provide 

additional environmental complexity (Lehrter et al. 2012; Lehrter et al. 2013; Fry et al. 2015).

Although the chemical constituents that fuel primary production in the water column are essential to the 

development of hypoxia, the physical environment dictates the nature of stratification and whether 

respiration will be predominantly benthic or water column based. Consequently, understanding the 

physical environment can be highly informative to predicting the areal development and maintenance of 

seasonal hypoxia in the nGOM (Hetland and DiMarco 2008). Estuary-like circulation regimes 

established by river discharge, tide, basin width, and depth (Pritchard 1955), along with coastal currents 

and winds (Pokryfki and Randall 1987; Walker et al. 2005; Walker 2005), affect mixing and light 

penetration (Bierman et al. 1994; Quiñones-Rivera et al. 2007; Lehrter et al. 2009), and influence 

respiration pathways (Bierman et al. 1994; Hetland and DiMarco 2008). Thus, site-specific physical 

attributes are important to local formation and dissipation of hypoxia (Wang and Justić 2009). In 1986, 

Renaud (1986) reported patchy hypoxic conditions in coastal waters off central Louisiana between 9–15 

m deep. In 2010, DiMarco et al. (2010) showed that mesoscale bathymetric interactions with riverinfluenced hydrography create local instabilities in the water column and affect stratification on a fine 

spatial scale. In addition, bathymetry is related to variation in vertical advection of bottom waters above 

the benthic boundary layer which reduces DO concentrations in the midwater (Zhang et al. 2015).

These hydrographic interactions can be of particular importance when considered collectively with 

properties of the sediments themselves. About 73% of lower water column oxygen consumption in 

hypoxic waters of the Louisiana shelf is due to benthic respiration (Quiñones-Rivera et al. 2007). 

Bierman et al. (1994) showed that sediment oxygen demand accounted for 22–30% of oxygen demand in 

the bottom hypoxic layer. This rate also varies with sediment composition. Finer-grained sediments have 

higher organic content than coarser-grained sediments (Pearson and Rosenberg; 1978; Mayer 1994 and 

references therein), particularly where winter sediment deposition is heavy (Turner et al. 2006a). Metal 

content also generally increases with decreasing grain size (Kristiansen et al. 2002, Kristensen et al. 

2003). These characteristics can promote the positive feedback that sustains local hypoxia (Rabalais et al. 

1994). Also, benthic microalgae associated with large, sandy shoals can play an important role in 

biogenic elemental fluxes and re-oxygenation of depleted bottom waters (Jahnke et al. 2000; Grippo et al. 

2009; Lehrter et al. 2009; Baustian et al. 2011, 2013). Wind-driven plume redistribution can subject 

nearshore waters with complex bathymetry, like those of the Atchafalaya shelf, to rapid shifts from 
21

benthic to water column respiration pathways. Consequently, the shelf south of the Atchafalaya River 

outlet has the most variable bottom-water conditions found throughout Louisiana’s nearshore zone.

As a link between inshore estuaries and the offshore marine environment, the nearshore zone offers 

insights into many biogeochemical processes and biological interactions. Hydrography of this nearshore 

environment also holds potential answers regarding the broad biological stumbling point of what exactly 

constitutes estuarine dependence (McHugh 1967). A holistic understanding of the nearshore zone of 

coastal Louisiana is critical to addressing what makes the nGOM such a productive and resilient system in 

the face of diverse and seemingly overwhelming stressors (Chesney et al. 2000).

2.2 Methods

2.2.1 Coast-wide Survey

The initial coast-wide survey, conducted July 12–August 01 of 2013, was intended as an exploratory 

guide for the later studies of environmental responses of the fish assemblages around small oil and gas 

platforms (platforms) throughout the nearshore zone off Louisiana. Sampling was focused in federallymanaged nearshore waters < 18 m deep, during the highly variable summer months. Over 21 days, we 

used a small, seaworthy vessel to rapidly assess environmental conditions around platforms in the study 

area. We used a model 6820 V2 YSI sonde to sample water quality conditions at 118 small oil and gas 

platforms and seven additional non-platform sites in water depths < 18 m (Figure 4). At each site we 

logged salinity (psu), temperature (°C), depth (m), atmospheric pressure (mm Hg), pressure at depth 

(psia), DO (mg l−1 and % saturation), and pH, and took a Secchi disk reading to estimate surface water 

clarity. Vertical water column measurements were to a resolution of one reading every two seconds, from 

~0.2 m below the surface to ~0.2 m above the bottom. We also collected sediment samples with a metal 

scoop to ground truth multisource integrated sediment composition data (Jenkins 2010), managed in a 

geographic information system (Arc 10.4). A majority sediment component coarser than 63 μm was 

considered sand dominated, and used in analyses to indicate the presence of a sand dominated bottom 

(shoals), and a majority sediment component finer than 63 μm was considered mud dominated.

Figure 4. Regions (West, Central, East) of distinctly different hydrography based on all hydrographic data 

collected in 2013 and 2014. 

(n = 343)
22

For platform selection we used a modified random approach intended to characterize environmental 

variation expressed as physicochemical conditions as well configurations of the platforms themselves. 

Routes were planned around the distribution of selected platforms that met the criteria of our primary 

research objective. We worked east to west, and the relatively calm conditions and short time frame of 

the initial survey provided us with an interesting snapshot of Louisiana’s nearshore zone. This snapshot 

allowed us to interpolate surface, midwater, and bottom environmental data for insight into regional 

hydrography.

Once the coast-wide rapid survey was completed, regional sampling continued during two summers (July 

12–September 06, 2013, and July 02–September 12, 2014). During this time we collected a total of 343 

hydrographic profiles in the nearshore zone. In 2013 we collected 181 profiles over 14 days at sea. In 

2014 we collected 162 profiles over 14 days at sea. Daily cruise routes ran from 50–400 km per day and 

between 3–47 km from shore depending on the targeted area and sea state. We collected the same 

environmental information that was collected in the initial coastwide survey, with the exception of pH. 

The YSI was recalibrated at least every two weeks, and the DO membrane was replaced between 

sampling seasons. Winkler titrations (Winkler 1888) validated performance of the DO probe (DO probe 

= 1.0042*Winkler DO − 0.0283; F (1, 12) = 1794.43, P < 0.0001) and the intercept was not significant 

(P=0.8559).

2.2.2 Hydrographic Analyses

For simplification, whole water column continuous profiles were reduced to representative surface, 

midwater, and bottom readings for each variable. Surface readings were taken ~0.2 m from the surface, 

and bottom readings were taken ~0.2 m from the bottom. Midwater readings were selected from the midwater depth of each site. These designations consistently sampled the frequently stratified surface and 

bottom strata, and the waters underlying the dominant halocline, and above the benthic boundary layer. 

Density was calculated for each of three strata (surface, midwater and bottom) for every water column, 

from salinity, temperature, and pressure at depth, using the UNESCO algorithm (Fofonoff and Millard 

1983).

Interpolations were used to produce maps of salinity, temperature, DO, density, density difference, pH, 

and Secchi depth. Most variables were interpolated for surface, midwater, and bottom strata, while 

surface-to-bottom density difference and Secchi depth involved single interpolations. All interpolations 

were produced using a second-power inverse distance weighting method in ArcMap 10.4. Interpretation 

of interpolated maps guided tests of variance among three regions of Louisiana’s nearshore waters (Figure 

4) established based on major transitions of the 10 m, 15 m, and 25 m isobaths.

Two-way ANOVAS (analysis of variance) were used to compare water quality by region and either 

dominant sediment type or strata (surface, midwater, and bottom). Salinity, temperature, and density 

were compared with region (West, Central, and East) and strata as fixed-effect variables. Density 

differences were compared with region and dominant sediment type (sand or mud) as fixed-effect 

variables. Vertical extent and intensity of hypoxia were compared with region and dominant sediment 

type as fixed-effect variables, among all hypoxic sites, which were defined in this study as DO < 50% 

saturation or ~3.3 mg l−1 (Breitburg 2002; Vaquer-Sunyer and Duarte 2008). The rationale for choosing 

50% of saturation as the criteria for hypoxia is because we noted in video observations that fishes avoided 

waters with DO less than this level.

Simple linear regressions (SLR) were used to determine the relationships between pH and DO and 

between Secchi depth and surface salinity. The ANOVAs for salinity, density difference, and intensity of 

hypoxia were fitted with the negative binomial distribution and log link function using the GLIMMIX 
23

procedure of SAS 9.4. The temperature and density ANOVAs did not meet the assumption of constant 

variance, and so in both cases variances were estimated separately, and degrees of freedom were modified 

accordingly using a Satterthwaite adjustment (SAS 2005). The extent of hypoxia ANOVA was rightskewed, and while the negative binomial distribution provided an adequate fit, the gamma distribution 

with log link function was used because it reduced error. Tukey-Kramer post-hoc adjustments were 

applied to determine significant pairwise differences between least-squares means under multiple 

comparisons for all ANOVAs. The SLRs were run in Microsoft© Excel© (14.0).

Further analyses of coastwide hydrography incorporated 12 environmental variables in a factor analysis 

(Proc Factor SAS 9.4): surface, midwater, and bottom measures of salinity, temperature, and DO, distance 

from shore, total depth, and Secchi depth. A varimax rotation was used to normalize the axes and create a 

consistent scale to assimilate all variables into three factors. Partial correlations of controlling factors 

indicated high correlations between surface and midwater temperature, as well as midwater and bottom 

DO. Consequently, these variables were averaged to create two new variables (upper water temperature 

and lower water DO), that accounted for variation provided by the original four, leaving ten variables in 

the final factor analysis. Eigenvalues > 1 indicated that all three orthogonal factors were important in 

resolving overall dimensionality of environmental conditions. Mean factor scores for three axes were 

plotted for the three regions of the coast as centroid means in three-dimensional environmental space. 

Significant differences were estimated by two standard error radii balloons around the centroid means.

To gauge consistency of environmental variation observed in the coastwide survey, further interpolations 

were produced in Arc 10.4 using factor scores associated with all 343 hydrographic samples for Factors 

1–3. For the Central region, interpolations were produced within 1 m depth bins from the 3–18 m 

isobaths, for a total of 15 interpolations per factor. A three-way ANOVA was run on Factor 3 with 

region, year, and dominant sediment type as fixed-effect variables, and using independently estimated 

variances and a Satterthwaite adjustment on the degrees of freedom (SAS 2005). Pairwise comparisons 

were made using Tukey-Kramer post-hoc adjustments.

The vertical extent and intensity of hypoxia were compared using three-way ANOVAs with region, year, 

and dominant sediment type as fixed-effect variables. Comparisons were made among all platforms in 

hypoxic waters (bottom DO < 50% saturation), for West, Central, and East regions, years 2013 and 2014, 

and for sand or mud dominated sediment types. The ANOVA testing the extent of hypoxia was fitted as a 

gamma distribution; intensity of hypoxia was fitted as a negative binomial distribution, both using the log 

link option in the GLIMMIX platform of SAS 9.4. Tukey-Kramer post-hoc adjustments were applied to 

compare least-squares means under multiple comparisons.

2.3 Results of coast-wide survey

Throughout the study area, the water column was always in part diluted below full salinity Gulf water. 

Freshwater influence was highly spatially and temporally variable, not only due to proximity of the 

Mississippi and Atchafalaya river discharges, but also along clear regional divides existing at major 

bathymetric transitions. Three regions of Louisiana’s nearshore zone (Figure 4) were identified based on 

the dominant hydrographic attributes evident in the interpolated salinity, temperature, and subsequent 

density profiles (Figures 5, 6, 7) observed during the initial 2013 coast-wide survey. With relative 

consistency in coast-wide winds, currents, and tides, differences in regional hydrography reflected 

interactions between freshwater input and bathymetry, and were best visualized in terms of stratification 

by density differences (Figures 7, 8). As expected, coastal waters were most highly stratified near the 

mouth of Atchafalaya Bay and around the bird’s foot (Figure 8, upper), and generally became

progressively more stratified from west to east with proximity to the Mississippi River Delta (Figure 8, 

lower). However, the contrasts appeared more sharply defined than a continuous transition with distance 

from river input alone. These abrupt transitions provided a basis that were used to subdivide the coast 
24

into three east to west zones that reflected significantly different regional characteristics that were used to 

understand and compare regional differences in fish assemblages around small platforms. Further 

analyses also explored finer-scale intraregional hydrographic variation by comparing areas dominated by 

sandy sediment to those dominated by mud.

The western region (West) extended from the westernmost platform sampled, near the Texas-Louisiana 

border (longitude -93.9°) to longitude -92.5°. Substrates were predominantly mud within the nearshore 

zone. Sandy sediment increased with distance from shore and to the west. The western region included 

part of the Sabine Shoal complex. The dominant sources of fresh water to this region were the 

Atchafalaya, Sabine, and far-field Mississippi rivers, and Calcasieu Lake. The eastern border of the west 

zone was defined by the notable transitions of the 10 m and 25 m isobaths. At longitude -92.5 ° there is a 

landward transition of the 25 m isobath from ~125–75 km from shore, and a seaward transition of the 10 

m isobath from ~20–50 km from shore.

The central region (Central) extended from longitude -92.5° to -90.4°. These longitudes marked 

transitions of the 10 m and 25 m isobaths from ~75–25 km from shore, and encompassed the sanddominated Atchafalaya shelf. Substrates were primarily sandy, and included the largest sandy shoals 

along the Louisiana coast, namely Ship, Tiger, and Trinity shoals, and the Atchafalaya Shoals. 

Freshwater inflows associated with large rivers such as the Mississippi basin drainage system are known 

to have a strong influence on the dynamics of coastal environments (Goolsby et al. 2001). The dominant 

sources of freshwater to the central region are the far field Mississippi and Atchafalaya rivers, and to a 

lesser extent, outflows within the distributaries of Vermilion, Atchafalaya, and Terrebonne bays (Sklar 

and Browder 1998). The 15 m isobath was relatively consistent across the West and Central regions at 

~50 km from shore.

Finally, the eastern region (East) extended from the Central region boundary (longitude -90.4°) to our 

easternmost platform (longitude -88.75°). In this region the 10 m, 15 m, and 25 m isobaths extended 

approximately 3 km, 20 km, and 25 km from the barrier islands. The sediments in this region were 

mostly mud-dominated. However, there was a patchy sand distribution east of the Mississippi River 

delta, which included building river deposits, part of the St. Bernard Shoal complex and submerged 

segments of the Chandeleur Islands. Freshwater input to this region came from the Mississippi River, as 

well as far-field Atchafalaya River, Terrebonne and Barataria bays west of the bird’s foot, and Breton 

Sound, Chandeleur Sound, the Pearl River, Lake Pontchartrain, and Mobile Bay east of the bird’s foot.

Salinity was the primary driver in density across the coast, and ranged from 0.90–36.74 psu (Table 1). 

Regional comparison of the coastwide salinity profiles by interpolated surface, midwater, and bottom 

strata (Figure 5, upper) showed that salinity in the West was nearly uniform throughout the water column, 

but the Central and East regions were considerably more stratified. Surface salinities were similar 

between the Central and East regions, though midwater and bottom salinities were substantially different. 

Effects for region (F (2, 366) = 26.43, P < 0.0001; Figure 5, lower), strata (F (2, 366) = 46.69, P < 0.0001; 

Figure 5, lower) and the interaction (F (4, 366) = 22.57, P < 0.0001; Figure 5, lower) significantly 

influenced salinity. Pairwise comparisons showed no significant differences among strata in the West 

region, significant differences between the surface and bottom for the Central region, and significant

differences among all three strata in the East region (Figure 5, lower).

Temperature was highly variable, ranging from 24.39–33.38°C, although on average it was much less 

variable (Table 1). Interpolated surface, midwater, and bottom temperatures were not detectably different 

between the West, and Central regions, with the East region standing out as generally cooler (Figure 6). 

The overall effects of region (F (2, 176.1) = 291.14, P < 0.0001; Figure 6), strata (F (2, 177.8) = 117.05, P 

< 0.0001; Figure 6), and their interaction (F (2, 146.6) = 19.50, P < 0.0001; Figure 6) were significant. 

Pairwise comparisons of temperature showed significant variation in the water column for at least one 

stratum for all regions (Figure 6). This suggested that influence of temperature on density stratification 
25

relative to salinity was stronger in the West region than for the Central and East regions. Surface 

temperatures in the East region were as cool as the coolest bottom waters found across the rest of the 

coast, while mid and bottom temperatures in the East were significantly cooler than the rest of the coast 

(Figure 6).

Analyses of density by region and strata indicated a significant region effect (F (2, 129.8) = 87.75, P < 

0.0001; Figure 7), a significant strata effect (F (2, 142.7) = 108.60, P < 0.0001; Figure 7, lower), and a 

significant interaction (F (4, 98.57) = 37.28, P < 0.0001; Figure 7), indicating that overall mixing was 

different among regions. Interpolated surface, midwater, and bottom readings and Tukey pairwise 

comparisons of region and strata showed the least stratification in the West region, increased stratification 

in the Central region, and the highest stratification in the East region (Figure 7).

The three regions differed significantly in stratification and surface-to-bottom mixing (Figure 8, Table 2). 

Pairwise comparisons of variance in mean density differences showed little stratification in the West 

region, a stronger difference in the Central region, and the strongest difference in the East region, and the 

overall effect was highly significant (F (2, 119) = 17.71, P < 0.0001; Figure 8). Though pairwise 

comparison of sand and mud were not significantly different within any region, there was a statistically 

significant trend toward higher density differences overlying mud (F (1, 119) = 5.03, P = 0.0268; Figure 

8). This indicated significant differences in stratification for major (regional) and smaller-scale (localized 

features such as a shoal) bathymetric characteristics, while the lack of an interaction between the two 

suggested a strong, independent relationships (F (2, 119) = 0.07, P = 0.9308; Figure 8).

Interpolation of bottom DO showed a patchy distribution of hypoxia (Figure 9). Interestingly, high 

bottom DO seemed to coincide with areas dominated by sandy sediments. This was particularly true of 

waters overlying large sandy shoals, namely the Sabine Shoals, Tiger, and Trinity shoals, Atchafalaya 

Shoals, Ship Shoal, and St. Bernard Shoals. Comparisons of the vertical extent of hypoxia by region (F 

(2, 50) = 1.64, P = 0.2047; Figure 12) and dominant sediment type (F (1, 50) = 0.70, P = 0.4059; Figure 

8) were not significant, but the interaction between them was significant (F (2, 50) = 4.43, P = 0.0169; 

Figure 8), indicating differences in hypoxia over shoals in relation to major shelf bathymetric 

characteristics.
26

Figure 5. Interpolated coast-wide surface, midwater, and bottom salinity (upper), and pairwise comparisons 

of salinity (lower) by region (red dashed lines) and by strata (surface, midwater, and bottom) for the 

nearshore coastal zone waters off Louisiana. 
27

Figure 6. Interpolated coast-wide surface, midwater, and bottom temperature (upper) and pairwise 

comparisons of temperatures (lower) by region and by strata (surface, midwater, and bottom) for the 

nearshore coastal zone off Louisiana. 
28

Figure 7. Interpolated coast-wide surface, midwater, and bottom density (upper), and pairwise comparisons 

of density (lower) by region (red lines) and strata (surface, midwater, and bottom) of the nearshore 

coastal zone waters off Louisiana.
29

Figure 8. Interpolated coast-wide surface-to-bottom density difference (upper) and pairwise comparisons for 

surface-to-bottom density difference (lower) by region (red lines) and dominant sediment types 

(sand or mud) for the nearshore coastal zone waters off Louisiana.
30

Table 1. Summary of environmental measurements reported as a mean, during the initial coastwide survey (CW) and summer platform surveys of 2013 and 2014

95% confidence interval and the range of observations for surface (Surf.), midwater (Mid.), and bottom (Bot.) 

physicochemical variables for West, Central, and East Louisiana regions of the nearshore zone. 

Variable Depth West Central East

CW 2013 2014 CW 2013 2014 CW 2013 2014

Density 

(kg/m3)

Surf.

1018.4 

(±0.4)

1015.6–

1020.2

- -

1013.5 

(±1.5)

995.5–

1016.4

- -

1010.1 

(±1.7)

996.7–

1017.1

- -

Mid.

1018.9 

(±0.4)

1017.7–

1020.5

- -

1015.5 

(±0.3)

1011.6–

1017.4

- -

1018.3 

(±0.5)

1010.3–

1021.1

- -

Bot.

1019.5 

(±0.3)

1018.1-

1020.6

- -

1017.0 

(±0.6)

1014.7–

1023.1

- -

1021.4 

(±0.3)

1018.2–

1023.7

- -

pH

Surf.

8.2 

(±0.1)

8.0–

8.8

- -

8.5 

(±0.1)

8.2–

9.5

- -

8.6 

(±0.1)

8.0–

9.2

- -

Mid.

8.2 

(±0.1)

8.0–

8.4

- -

8.4 

(±0.1)

8.0–

8.7

- -

8.3 

(±0.1)

7.9–

8.7

- -

Bot.

8.0 

(±0.1)

7.6–

8.2

- -

8.2 

(±0.1)

7.7–

8.6

- -

8.1 

(±0.1)

7.2–

10.8

- -

Secchi 

depth 

(m)

4.10 

(±0.89)

1.47–

9.55

4.13 

(±0.69)

1.47–

10.48

7.19 

(±1.16)

1.25–

12.70

2.54 

(±0.45)

0.47–

7.05

3.24 

(±0.46)

0.47–

8.43

5.16 

(±0.60)

0.96–

11.61

1.88 

(±0.46)

0.27–

7.57

1.71 

(±0.38)

0.27–

7.57

1.90 

(±0.30)

0.60–

4.29

4.10 

(±0.89)

1.47–

9.55

Site 

depth 

(m)

10.87 

(±0.92)

6.71–

15.24

10.95 

(±0.68)

6.71–

15.24

12.14 

(±0.85)

7.32–

16.08

8.07 

(±0.80)

3.66–

15.62

8.31 

(±0.57)

3.66–

15.62

9.57 

(±0.67)

4.42–

16.76

12.41 

(±0.84)

5.79–

17.56

12.04 

(±0.77)

5.49–

17.56

11.72 

(±1.10)

4.33–

17.98

10.87 

(±0.92)

6.71–

15.24

Distance 

from 

shore 

(km)

22.12 

(±5.43)

6.08–

45.86

24.11 

(±4.21)

6.08–

45.86

28.08 

(±5.00)

7.12–

46.56

19.82 

(±2.24)

9.03–

39.13

18.18 

(±1.67)

6.87–

39.14

20.40 

(±1.67)

6.54–

40.87

9.20 

(±1.08)

1.26–

19.40

9.00 

(±0.92)

1.26–

19.40

8.22 

(±1.11)

0.79–

17.43

22.12 

(±5.43)

6.08–

45.86

Percent 

sand

4.10 

(±0.89)

1.47–

9.55

4.13 

(±0.69)

1.47–

10.48

7.19 

(±1.16)

1.25–

12.70

2.54 

(±0.45)

0.47–

7.05

3.24 

(±0.46)

0.47–

8.43

5.16 

(±0.60)

0.96–

11.61

1.88 

(±0.46)

0.27–

7.57

1.71 

(±0.38)

0.27–

7.57

1.90 

(±0.30)

0.60–

4.29

4.10 

(±0.89)

1.47–

9.55
31

Table 2. Rotated factor loadings of 10 environmental variables measured throughout the 

nearshore zone off Louisiana

Note: The sign of each loading indicates whether variables are increasing or decreasing, while the magnitude 

indicates the strength of contribution to each factor. Underlines indicate the loadings used to characterize the 

main factors and guide interpretations about the system as described by these variables.

Environmental Variables Factor 1 Factor 2 Factor 3

Secchi depth 0.83 −0.05 −0.11

Surface salinity 0.82 0.20 0.25

Distance from shore 0.78 −0.21 −0.10

Surface DO −0.72 −0.03 −0.05

Upper water temperature 0.41 −0.79 −0.23

Midwater salinity 0.29 0.79 −0.11

Bottom salinity 0.04 0.76 −0.49

Bottom temperature 0.47 −0.76 0.18

Depth 0.21 0.62 −0.49

Lower water DO 0.11 −0.15 0.88

Eigenvalues 3.01 2.88 1.42

Percent variance explained 30.12 28.80 14.24

Cumulative variance explained 30.12 58.92 73.16

2.3.1 Hydrographic analyses

The three orthogonal factors resulting from the ten variables explained ~73% of the variability in the 

hydrographic data (Table 3). All three components had Eigenvalues > 1, and all ten variables contributed 

to the pattern. Positions along each of the three axes indicated relationships with the three factors, and 

associated variables, and individual factor Eigenvalues expressed variability in the system explained by 

each factor. Factor 1 accounted for ~30% of the variability, loading positively for Secchi depth, surface 

salinity, distance from shore, and negatively for surface DO. Factor 1 was interpreted as a freshwater 

stratification factor. Factor 2 accounted for ~29% of the variability and loaded positively for upper water 

salinity and depth, and negatively for surface and lower temperatures. This factor was interpreted as 

marine bottom-water influence. Factor 3 accounted for ~14% of the variability, and loaded positively for 

lower water DO only. Spheres around centroid means, plotted for the three regions in three-dimensional 

environmental space, did not overlap and indicated significant differences in hydrography among all 

regions. Their relative positions along the factor axes indicated important environmental differences 

among regions (Figure 10).

The centroid for the West region loaded highest on the Factor 1 axis, and moderately on the Factor 2 axis, 

indicating this region had relatively low freshwater stratification, and that marine bottom-water influence 

was intermediate. The Central region centroid loaded moderately on Factor 1 and lowest on Factor 2, 

indicating this region had intermediate freshwater stratification and relatively low marine bottom-water 

influence. The East region centroid loaded lowest on Factor 1 and highest on Factor 2, indicating this 

region was more highly influenced by freshwater stratification and marine bottom water. All regions 

loaded similarly on the Factor 3 axis, indicating comparable susceptibility to lower water column DO 

depletion among the three regions. These results of the factor analysis agreed with those relating to 

interpolations of the coastal snapshot, confirming that regional differences in hydrography were 

consistent throughout the two year study.
32

Table 3. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type 

on Factor 3 (interpreted as DO depletion in the water column). 

Variables

No. of 

Degrees of 

Freedom

Denominator 

Degrees of 

Freedom

F-Values P-Values

Region 2 66.08 7.11 0.0016

Year 1 84.21 15.61 0.0002

Sediment 1 84.21 33.97 < 0.0001

Region x Year 2 66.08 29.55 < 0.0001*

Region x Sediment type 2 66.08 11.63 < 0.0001*

Year x Sediment 1 84.21 5.54 0.0209*

Region x Year x Sed 2 66.08 0.58 0.5631

Note: Asterisks (*) indicate significance of interpretable variables.

Figure 9. Interpolated results of the 2013 coast-wide survey for surface, midwater, and bottom dissolved 

oxygen concentration for platform sites in the nearshore waters off Louisiana. 
33

Figure 10. Factor analysis showing (upper) all hydrographic station , and (lower) two standard errors around 

the centroid means for the nearshore waters by regions off Western, Central, and Eastern Louisiana.

(n = 343), Western (n = 71), Central (n = 162), and Eastern (n = 110)

Interpolations of the factor scores showed consistency in regional differences throughout the two year 

study, both in terms of regional mixing regime (Factors 1 and 2) and DO depletion in the lower water 

column (Factor 3) (Figure 11). The similarities in DO depletion came in spite of apparent pairwise annual 

differences, with a strong trend of significantly lower susceptibility to DO depletion in the lower water 

column over sand-dominated sediments compared to mud-dominated sediments (Figure 11). All main 

effects and double interactions were significant, with no significant triple interaction (Table 4). These 

results lend further support to regional differences at major bathymetric transitions across nearshore 

Louisiana shelf waters, and the consistent function of finer-scale shoal interactions across study years.
34

Although lower water column DO depletion was consistently present among the three regions, significant 

differences were detected in the extent and intensity of hypoxia. The analysis of extent of hypoxia 

indicated significant effects of year, dominant sediment type, and the interaction between region and year 

(P = 0.0221, 0.0162, and 0.0060; Table 4). The analysis of intensity of hypoxia indicated a significant 

year effect and significant interactions between region and year, and year and dominant sediment type (P 

= 0.0030, 0.0003, and 0.0060; Table 5). Pairwise comparisons for extent of hypoxia showed the 

magnitude of the variation largely driven by annual differences and differences over sand and mud 

(Figure 12). Pairwise comparisons for the intensity of hypoxia showed a decreasing intensity from west 

to east (Figure 12).

Figure 11. Comparison of interpolated coast-wide principal components for Factors 1–3 (upper) and pairwise 

comparisons for Factor 3 (lower) by region (West, Central, East), dominant sediment type (sand or 

mud) and by year (2013–2014). 
35

Table 4.Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type 

(Sed) on extent of hypoxia

Variables No. of Degrees of 

Freedom

Denominator 

Degrees of 

Freedom

F-Values P-Values

Region 1 120 5.38 0.0221

Year 2 120 1.78 0.1738

Sed 1 120 5.95 0.0162*

Region x Year 2 120 5.35 0.0060*

Region x Sed 2 120 2.38 0.0974

Year x Sed 1 120 0.75 0.3896

Region x Year x Sed 1 120 1.13 0.2893

Asterisks (*) indicate significance of interpretable variables.

Table 5.Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type 

(Sed) on intensity of hypoxia 

Variables No. of Degrees of 

Freedom

Denominator 

Degrees of 

Freedom

F-Values P-Values

Region 2 120 6.10 0.0030

Year 1 120 2.02 0.1583

Sed 1 120 3.03 0.0844

Region x Year 2 120 8.68 0.0003*

Region x Sed 2 120 0.44 0.6474

Year x Sed 1 120 7.82 0.0060*

Region x Year x Sed 1 120 2.43 0.1217

Asterisks (*) indicate significance of interpretable variables.

Figure 12. Pairwise comparison of vertical extent (left) and intensity (right) of hypoxia (defined as less than 

50% saturation) by region (West, Central, and East) and dominant sediment types (sand or mud) around 

platforms in the nearshore zone off Louisiana.
36

Figure 13. Central region composite interpolations of the principal component factors (1–3) analyzed by 

water depth. 

Composite factor score interpolations for Factors 1 and 2 by depth interval for the central region provided 

similar results to the previous analyses (Figure 13). Factor scores in Figure 13 were interpolated within 1 

m depth bins from the 3–18 m isobaths, for 15 total interpolations for each factor. Composite factor score 

interpolations for Factors 1 and 2 by depth interval for the Central region provided results similar to the 

previous analyses. These results confirmed the strong relationships in mixing with depth to a 1 m 

resolution, and precisely highlighted the shoals of the region as particularly well-mixed. Interestingly, the 

picture for Factor 3 became noisier despite the greater resolution in mixing influences. The 10 m isobath 

seemed to mark a substantial shift in susceptibility to lower water column DO depletion, with consistently 

high susceptibility at depths > 10 m, and generally reduced, though highly variable susceptibility to DO 

depletion at lesser depths.

2.4 Discussion

Due to influence from the five largest rivers in the Gulf (by annual discharge volume) (Dahm et al. 2005), 

Louisiana’s nearshore coastal zone expresses many physically characteristics of a typical estuary. 

Nearshore Louisiana is a functional extension of the network of estuaries inshore of the barrier islands, 

and may be viewed as part of the overall estuarine continuum as defined by McHugh 1967. As for the 

inshore estuary, this nearshore estuarine component has high spatial and temporal variation. Descriptive 

classification of this environment in terms of dominant estuary-like circulation patterns within well-
37

defined regional bounds provides insights useful in considering nearshore species distributions, and 

inshore–nearshore connectivity. Mixing and stratification patterns also exert influence over the 

development and maintenance of hypoxia. Shoals further influence mixing, inshore–nearshore exchange, 

and hypoxia. Although most of the discharge into the coastal zone is into the east region the Central 

region of the nearshore zone is most highly influenced by fresh water because it is discharged into very 

shallow well mixed waters and because the central region has many high-relief sandy shoals. The Central 

region is also relatively resistant to sustained hypoxia above the 10 m isobath, particularly over shoals, 

although the region is susceptible to severe hypoxic events. Hypoxia can extend vertically beyond the 

mid-water column (Rabalais et al. 2002; Rabalais et al. 1991), although such extreme cases were not 

commonly observed in the nearshore zone.

It is difficult to constrain the nearshore environment within geographic coordinates. The nearshore 

estuary is best functionally described by distance from shore in the same way as the river plumes that 

influence it: by temporally variable “salinity coordinates” (Hetland 2005). For most of the year, the 

dominant coastal currents that together form the Louisiana Coastal Current (LCC) within the wind-driven 

50 m isobath (Nowlin et al. 2005) show divergence centered around longitude −92.5°, where shoreward 

shelf circulation intersects the dominant westward flow. Mean shelf turnover is 2–3 months during this 

time (Dinnel and Wiseman 1986; Zhang et al. 2012), thus the extent of freshwater buildup along the coast 

is influenced by seasonal variations of freshwater influxes (McHugh 1967). This pattern begins to break 

down from July to late August or into September when the LCC is weaker, less defined, and 

predominantly easterly in flow (Cochrane and Kelly 1986; Cho et al. 1998; Nowlin et al. 2005). This 

shift is due to upwelling-favorable prevailing winds that also “pool” freshwater outflow on the shelf. This 

creates a flux of continuous fresh and marine water mixing, advancing seaward during the spring and 

summer, and retreating in autumn–winter (Dinnel and Wiseman 1986; Hetland et al. 2012). During 

summer, inshore–nearshore connectivity is facilitated by this brackish-water advance, and potentially by 

the absence of a strong LCC. Absence of a strong LCC might be particularly relevant to fish distributions 

if the LCC acts as an inshore boundary to fish dispersal in the same way it is considered an offshore 

boundary (Shaw et al. 1985). Also, tidal differences across the coast are small (DiMarco and Reid 1998). 

These seasonal consistencies in shelf circulation in nearshore waters emphasize localized mixing as 

shaping regional hydrographic regimes. Regional divides of consistent mixing and stratification patterns 

allow nearshore waters to be described using the same terms that describe the inshore estuary (Pritchard 

1955; Hansen and Rattray 1966), driven primarily by river flow, tidal velocities, basin-width, and depth 

(Pritchard 1955). From this perspective, during summer months, the West region resembled a near 

vertically homogenous, mixoeuhaline estuary, while the Central region resembled a partially-mixed 

polyhaline estuary, and the East region resembled a salt-wedge polyhaline estuary.

Although still highly variable, these descriptive differences in dominant mixing patterns convey a degree 

of intraregional environmental consistency which offers different habitat characteristic features to benthic 

and pelagic organisms. This is important considering the controlled state of the river and the potential for 

shifts in freshwater distribution to impact nearshore waters, and alter the functionality of this nearshore 

component of the estuaries. This is particularly relevant for the Central region of the coast, where 

freshwater influence throughout the water column is greatest. Also, because nearshore salinity directly 

influences inshore salinities (Wiseman et al. 1990), changes in freshwater distribution to the nearshore 

environment can be expected to significantly affect estuarine species and processes. A further 

complication stems from the differences between Mississippi and Atchafalaya nutrient content due to the 

confluence of the Atchafalaya and Red rivers. These considerations are important in the context of 

freshwater diversion plans, as well as the general variability in Atchafalaya discharge, which, although 

capped by management policy at 30% of that of the combined flows of the Red and Mississippi Rivers,

varies between 15–29% (Allison et al. 2000). Further, Atchafalaya River discharge is based on a fraction 

of that of the Mississippi, which is highly variable by volume, and disproportionately affects the Central 

region, and to a lesser extent, the West region due to greater mixing throughout the entire water column.
38

The reduced density difference over sand-dominated sediments intra-regionally (Figure 8) probably 

reflected greater mixing over relatively high-relief shoals. The picture was clearest in the Central region, 

where bottom densities appeared lower over shoals, which were surrounded by higher-density water 

(Figure 7). These results are consistent with literature reporting estuary exchange with the adjacent 

marine environment: low-density estuarine waters outflow over bathymetric highs, while high-density 

marine waters intrude through bathymetric lows (Schroeder 1977; Valle‐Levinson and Lwiza 1995; 

Valle‐Levinson et al. 2003). Shoals thus offer unique habitat conditions both in terms of sediment 

composition, and hydrography, and the complex bathymetry of the Atchafalaya Shelf that generally 

creates greater inshore–nearshore connectivity.

Results reported here support the conclusions of other researchers who have called for a more 

comprehensive approach to the study of hypoxia beyond the familiar nutrient-centric perspective (Bianchi 

et al. 2008; Bianchi et al. 2010). Benthic respiration accounts for ~73% of the total oxygen consumption 

in the hypoxic zone (Quiñones-Rivera et al. 2007), which is typically associated with the benthic 

boundary layer (Wiseman et al. 1997). Advection of nutrients along the seafloor can play an important 

role in sustaining heightened benthic respiration rates which maintain hypoxia (Rydberg et al. 1990; 

Scavia et al. 2003). Advective processes also distribute oxygen-depleted bottom waters above the benthic 

boundary layer, affecting the vertical extent and intensity of the midwater oxygen minima (Zhang et al. 

2015). However, hypoxia is fundamentally a locally developed and maintained phenomenon, which is 

not advected into an area (Hetland and DiMarco 2008). Therefore, a region-wide susceptibility to 

hypoxia cannot be inferred on the basis of nutrient input alone. Careful considerations regarding the 

physicochemical factors influencing local hydrography must be made on a finer scale to make accurate 

predictions about the extent and intensity of the hypoxic zone. 

Understanding of the dynamics of hypoxia follows a logical progression of relating cause and effect, and 

while nutrient supply from the Mississippi and Atchafalaya rivers is the most important variable 

influencing the extent and intensity of hypoxia in the nGOM, the results presented in this chapter support 

the idea that physicochemical factors may play a greater role in determining hypoxia within this system. 

Though the Mississippi River is the larger of the two primary distributors of nutrients along the shelf, 

distance from the Mississippi alone does not wholly explain the patterns of hypoxia development in the 

immediate vicinity of its delta. The major regional differences in stratification capacity between the 

Central and East regions of the nearshore zone (as defined here) have been described in a model by 

Hetland and DiMarco (2008) using similar regional boundaries. These physical constraints play an 

important role in determining whether respiration will be predominantly benthic or water column based. 

The same characteristics that defined dominant regional mixing regimes also separate the coast in terms 

of dominant respiration regimes, with the West and Central regions predominantly inclined toward 

benthic respiration, and the East region inclined toward water column respiration. In addition to regional 

mixing and stratification differences, there was a greater distribution of sand and more shoals in the 

Central region compared to the West and East regions. The greater overall organic content (Pearson and 

Rosenberg; 1978; Mayer 1994 and references therein) and higher metal contents (Kristiansen et al. 2002, 

2003) of fine-grained silt and clay sediments can exacerbate and perpetuate hypoxia through nutrient 

contribution, and redox pathways—both factors that might contribute to reduced overall susceptibility to 

hypoxia over sandy shoals, particularly within regions where bottom respiration is dominant (as for the 

West and Central regions) (Lehrter et al. 2014). Under certain conditions, the sandy shoals in the study 

area also provide highly suitable habitat for benthic microalgae, which can increase lower water column 

DO by producing oxygen during daylight hours within the portion of the water column most susceptible 

to hypoxia (Baustian et al. 2011, 2013; Grippo et al. 2009, 2010). The combination of these effects and 

others, contribute to the patchy distribution of hypoxia observed throughout the nearshore zone over the 

course of these studies.
39

2.5 Conclusions

Many variables affect the nearshore hydrography of the nearshore zone off coastal Louisiana. 

Differences in mixing within the nearshore zone, resulting in differences between dominant estuary-like 

water column circulation regimes, are largely attributable to regional variation in bathymetry and 

proximity to the major passes of the Mississippi and Atchafalaya rivers. Although annual Mississippi 

River discharge is more than twice that of the Atchafalaya, the midwater and bottom salinities and 

temperatures of western and central nearshore Louisiana are more greatly influenced by freshwater 

discharge because of differences in the coastal configurations of the river-ocean confluences for the 

Mississippi and Atchafalaya rivers. This is particularly true of where the Atchafalaya waters mix within 

the extent of the 10 m isobath. This area defines the most estuary-like nearshore environment of coastal 

Louisiana, with some features that make it less susceptible to developing and sustaining hypoxia in 

certain areas. Temporal variation in Atchafalaya discharge probably significantly alters the distribution of 

pelagic and benthic species that occupy the nearshore zone throughout the West and Central regions of 

the coast, while the relatively more consistent sub-halocline conditions of the East region offer a more 

stable physical environment when oxygenated, and may be particularly relevant to the distributions and 

reestablishment of marine benthic organisms when hypoxia subsides.

The influence that nearshore bathymetry has on dominant mixing regimes has further implications for 

hypoxia within the coastal zone. Our field results agree with modeled predictions (Hetland and DeMarco 

2008) that physical properties of the nearshore zone play important roles in the way hypoxia develops off 

Louisiana. These findings suggest that major nearshore bathymetric transitions and features, such as the 

presence of sandy shoals, significantly alters the hydrographic structure of the water column. It also 

affects the stability and capacity for stratification at biologically relevant scales. Though important, depth 

alone did not seem to wholly explain the variability in hypoxia observed during this study. Shoals alter 

mixing, inshore-nearshore exchange, and biogeochemical processes, and are also host to benthic 

microalgae which oxygenate bottom waters under certain conditions. These all can contribute to the 

observed resistance and low intensity and duration of hypoxia around small platforms located on sandy 

shoals as opposed to those located in muddy locations. Hypoxia within the Central region likely develops 

and dissipates more frequently than in the West and East regions due to wind-driven shifts in Atchafalaya 

plume distribution that cause abrupt shifts from benthic to water-column respiration regimes, making this 

area a particularly interesting location for future study.

There is a dynamic interplay among salinity, depth, and DO within the nearshore zone which probably 

drives significant shifts in distributions of marine biota including fishes. Restricted availability of 

bottom-water habitat due to seasonal hypoxia might further alter organism distributions within the highlystratified water column because of the substantial variation of environmental variables that occur within a 

shallow water column. This is important when considering the nearshore zone as a functionally variable 

extension of the coastal estuarine system, which serves as an ecotone between the inshore component of 

the estuary, and the offshore marine environment.
40

3 Coast-wide Assessment of Fish Assemblages Around Small Oil 

and Gas Platforms

3.1 Introduction

The coastal zone off Louisiana supports a diverse assemblage of fishes that are a product of the 

productive coastal wetlands and the high nutrient discharge carried by the Mississippi River that 

discharges sediments and nutrients into the nGOM. While the sediments build wetland habitat, the 

nutrients support the productive fisheries of the Fertile Fisheries Crescent (Günter 1963; Nixon et al. 

1986). For example, Louisiana is second only to Alaska in US fisheries yields (NMFS 2015a). This 

unique combination of habitat and productivity enabled Louisiana to dominate Gulf landings and total 

dollars earned since 1950 (Chesney et al. 2000; NMFS 2015a). Total landings are largely Gulf menhaden 

(Brevoortia patronus), a species that has increased in abundance despite large landings (Vaughan et al. 

1996), and presently ranks 19th among the largest global fisheries (FAO 2014). Although some nGOM

species have experienced relative declines, overall landings aside from menhaden have increased for 

many pelagic and demersal species (Chesney et al. 2000). Additionally, the nGOM leads the US in 

recreational catch for number of trips, with > 39% of the total catch in ~30% of all trips from 1981–2014 

(Chesney et al. 2000; NMFS 2015a). Known as the “Sportsman’s Paradise,” Louisiana is foremost in the 

Gulf in total recreational catch rate per trip (NMFS 2015a).

A distinctive feature of the LATEX Shelf is the unparalleled network of oil and gas platforms (platforms) 

extending from inshore waters to the deep Gulf. Although shell ridges are common in the nGOM (Wells 

and Cowan 2007), natural rock reefs are rare, occupying just 3.3% of bottom waters 18– 91 m depth, 

about one-half of which offers vertical relief > 1 m (Parker et al. 1983). At the peak of oil and gas 

platform development, Gallaway et al. (1997) estimated that platforms provided 0.4% of the total hard 

substrate in the nGOM, but stressed the disparate importance of the vertical relief of platforms, which 

offer reef structure throughout the water column that are distributed throughout areas locally distant from 

natural hard bottom. 

A biologically relevant designation for Louisiana’s nearshore zone is defined as waters between the 5–25 

m isobaths (Chesney and Baltz 2001; Switzer et al. 2006). Although the 2013-2014 study only targeted 

platforms in < 18 m water depth because of diving and other restrictions, they were all located within the 

nearshore zone of the OCS. Platforms attract various benthic, demersal, and pelagic fishes (Gallaway et 

al. 1981; Gallaway and Lewbel 1982), resulting in a diverse and high density assemblage of fishes. 

Platforms also attract commercial and recreational fishermen. This has led to the highest recreational 

catch rates (catch per trip) of any US recreational fishery (Stanley and Wilson 1990), and > 70% of all 

nearshore recreational fishing off Louisiana occurs at platforms (Witzig 1986).

The expansive distribution and abundance of the artificial reef network created by platforms has been in 

constant evolution since the initiation of coastal drilling in 1942 (BOEM 2015). Platform numbers 

peaked from 1992–2006, during which time the number of platforms was relatively stable, with a mean 

count of ~3,964 ± 26 (95% CI) platforms per year, with a mean net annual change of −4 ± 11 (95% CI), 

and a high count of 4,049 platforms in 2001. Throughout this period, ~79% of all platforms were small 

(unmanned and unattended caissons, fixed platforms, and well protectors), ~43% were in shallow waters 

(≤ 15 m depth), and ~37% were small and in shallow water. Since 2006, platform numbers have rapidly 

diminished across the shelf, as oil exploration has moved into deeper water farther from shore. From 

2007–2014 there was a mean net loss of −184 ± 54 (95% CI) platforms per year reducing the platform 

count by ~38%, from 3,900 to 2,426 (BOEM 2015). Of these removals, ~96% were small platforms, 

~42% were in shallow water, and ~41% were small and in shallow water.
41

As of 2015, the Rigs-to-Reefs program (Reggio et al. 1987) had deployed material from 470 platforms 

(BSEE 2015); materials from 370 of t h ose platforms were sited in federal waters of the OCS off the 

coast of Louisiana (LDWF 2015). US Coast Guard regulations require 85 ft (~26 m) of navigational 

clearance for any unmarked submerged structure, with exceptions permitted to 50 ft (~15 m). Therefore, 

the established depth zone for program reefs is 70–350 ft (~21–107 m), falling well outside of the < 18 m 

depth range of this study. Recognizing the rapid loss of reef structure provided by platforms, the LDWF 

Artificial Reef Program announced a plan to expand into nearshore waters (January, 2014). This plan 

defines nearshore to a depth of 100 m, and the Gulf of Mexico Fishery Management Council (2015) 

suggested prioritizing much deeper areas along the shelf edge, and leaving nothing in shallow waters 

where shrimping would be affected.

A related concern for the placement of reef materials off Louisiana is the effect of nutrient enrichment in 

nearshore Louisiana and related development of hypoxia (Rabalais et al. 2002 a,b; Switzer et. al 2006). 

The seasonally ephemeral low oxygen zone (DO < 2.0 mg l−1) that forms along coastal Louisiana is the 

second largest hypoxic area on Earth, and it is believed to be growing in size and volume (thickening) in 

direct relation to increased nutrient inputs from the Mississippi River (Rabalais et al. 2002 a,b; Obenour et 

al 2013). Hypoxia is variable throughout the nearshore zone of the Louisiana coast in relation to 

bathymetry (Hetland and DiMarco 2008; DiMarco et al. 2010; Hazen et al. 2009; Renaud 1986; Chapter 

2). The distribution of sandy shoals, which offer vertical relief, can cause variable circulation patterns 

(DiMarco et al. 2010; Chapter 2). However, most of the nearshore zone is subject to bottom-water 

oxygen depletion associated with eutrophication, and although sand shoals periodically experience severe 

hypoxia episodes, they tend to be less extensive and of shorter duration than over surrounding mud 

bottoms (Craig and Bosman 2013; Reeves 2015).

Though some fish species can avoid the hypoxic area entirely through lateral movements within the 

coastal zone, or by moving outside the affected depth range (Switzer et al. 2006; Switzer et al. 2009), 

many species are able to maintain occupancy within even the most severely impacted areas by moving up 

in the water column (Rabalais et al. 2001; Stanley and Wilson 2004; this study). Platform removal has 

the potential for system-wide negative effects on the associated biota (Krahl 1986; Gallaway and Cole 

1998; Scarborough-Bull et al. 2008), particularly during low oxygen events. For reef-associated species, 

platforms are the only feature prominent enough to offer refuge above underlying hypoxic waters. The 

high-relief (or more accurately “maximum relief”) profiles of platforms extending above the surface 

provide a unique resource that is undeniably important in helping to attract and retain some reefassociated fishes when hypoxia intensifies.

The purpose of the 2013–2014 studies was to characterize the platform-associated fish assemblages 

throughout Louisiana’s shallow nearshore waters. Major regional bathymetric transitions and 

intraregional (sand and mud-dominated sediment types) comparisons were established on the basis of the 

hydrography (Chapter 2), and secondarily based upon the likelihood that fish assemblages were 

statistically associated with different sediments for reasons unrelated to hydrography or sediment type. In 

addition, the 2013–2014 studies assessed inter-annual variation, and evaluated local differences in 

assemblage composition based on platform complexity and the presence and absence of hypoxia (defined 

as DO < 50% saturation).
42

3.2 Field Methods

Sampling was modified random and guided by the architecture of the nearshore network of platforms that 

met our criteria. Platforms were clustered into fields along the coast reflecting the federal block-lease 

contracts that permit drilling operations in federal waters. We used the federal oil and gas platform 

information dataset for the nGOM managed by BOEM to chart locations of caisson, well protector, and 

unmanned fixed structures in < 18m of water (GeoMapApp 3.3.0). Selected sampling sites were 

considered in conjunction with seabed data to create routes that took us through as many fields as 

possible. Priority was given to fields with the intention of encountering a range of environmental variation 

in terms of salinity, temperature, distances from shore, depth, and dominant sediment type. We also 

considered platform complexity, date of deployment, and proximity to other platforms. Complexity levels 

for small platforms were grouped into three categories. Category 1 platforms (Figure 14A) had singlepiling “jackets” (platform legs providing structural support), category 2(Figure 14B) included platforms 

with two piling jackets, or more than two piling jackets without crossbeams, and category 3 platforms had 

three or more piling jackets with crossbeams (Figure 14C). Large, highly complex structures and those 

that discharged waterborne or airborne contaminants, such as produced water or sulfide gas, were avoided 

in the sample design (Figure 14D).

Figure 14. Examples of three levels of complexity for small nearshore platforms (A, B, C) and an example of 

larger platforms (D).

Sampling in 2013 and 2014 entailed 28 single day cruises aboard a 30-foot vessel. Coast-wide sampling 

was spread over two years, with 14 days in 2013, and 14 days in 2014, during summer months between 

July 12 and September 6 of 2013, and July 02 to September 12, 2014. Routes ran 50–400 km per day and 

3–47 km from shore, depending on the targeted platforms and sea state. 
43

An array of four GoPro Hero 3 cameras was lowered from the bow of the boat while maneuvering in 

close proximity to a platform (mean distance of 3.0 m ± 0.20 (95% CI)). Three cameras were mounted 

horizontally at 180° from one another to provide a non-overlapping circular field of view. The fourth 

camera was centrally mounted among the other three and faced down to record fishes swimming under 

the array, reference a depth gauge, and provide benthic substrate images. The cameras were synchronized 

to the same frame number using a wireless remote control to simultaneously start and stop all four 

cameras so it was impossible to see the same fish in more than one camera view.

Hydrographic data were collected at all sampled platforms plus an occasional hydrography only station 

between platform fields throughout the coastal zone. A YSI model 6820 V2 sonde was used to profile 

salinity (psu), temperature (°C), depth (m), atmospheric pressure (mm Hg), and pressure at depth (psia), 

DO (mg l−1 and % saturation), pH, and turbidity (NTU). One reading was made every two seconds on 

descent, between ~0.2 m below the surface to ~0.2 m above the bottom. A Secchi disk was used to 

estimate water clarity (m). We sampled 343 sites, 322 of which were platforms and 21 were 

hydrographic stations between platforms. Of the 343 hydrographic profiles, 181 profiles were sampled in 

2013, and 162 in 2014.

3.2.1 Video processing

Video methods are commonly used to assess fish assemblages and estimate numbers (Ellis and DeMartini 

1995; Gledhill et al. 1996). However, the high primary productivity, plus the input of suspended 

sediments from the rivers cause turbidity in the nearshore coastal zone off Louisiana that can make it 

especially difficult use video to assess fish populations (Figure 15). We were able to overcome the issue 

of limited visibility at most sites by focusing our studies during summertime when turbidity is typically 

lower and by returning to a site if we encounter unacceptable visibility. Video recordings of platform fish 

assemblages selected for analysis were based on initial visibility criteria that required the submerged 

structure of a platform (the jacket) be in view. Minimum visibility was estimated to be ~3.0 m, which 

proved to be an adequate threshold for this study due to the strong association of the species with the 

platforms and the small structural footprint of the platforms we targeted. The effect was a concentrated 

fish assemblage that was more amenable to video-based sampling than prior studies of larger structures 

had reported (Bull and Kendall 1994). In some cases where we had poor visibility we solved that problem 

by returning to sites when visibility was improved (see Figure 14A and14B as an example). In the 2013–

2014 survey, 150 of the 322 platforms visited were both unique (representing independent samples) and 

had water quality conditions with visibility suitable for analyses of the video. A total of 32 useable 

videos were from the West region, 70 useable videos from the Central region, and 48 from the East region 

of the nearshore zone (Figure 16). Of those, 65 videos were from 2013 and 85 from 2014. Additionally, 

63 of those videos were recorded over sand-dominated sediments and 87 were recorded over muddominated sediments. Eighty-four of the analyzed videos were recorded in waters where hypoxia was 

absent while 66 were recorded in the presence of hypoxia (DO < 50% saturation). Finally, 84 videos 

represented platforms of low complexity (category 1), 39 represented platforms of moderate complexity 

(category 2), and 27 represented platforms of higher complexity (category 3) (Figure 14).
44

Figure 15. Video frames of the bottom of a small platform (SS 93-66) on two different days in 2014 showing 

the differences in visibility at the same site.

Figure 16. Map of sampling stations and hydrographically distinct zones (West, Central, and East) from 

coastwide surveys of small oil platforms in nearshore waters of the outer continental shelf off 

Louisiana. 

Videos were analyzed and relative abundance estimates made that did not risk double counting (Ellis and 

DiMartini 1995). The synchronized set of frames for the three outward-facing cameras that contained the 

peak abundance of a particular species of interest was located and recorded as representing the lowest 

estimate for that species abundance at a particular platform on a given date (Priede et al. 1994; Ellis and 

DiMartini 1995; Willis and Babcock 2000; Wells and Cowan 2007). This estimation process was 

repeated for every species that was visible and identifiable on the three outward facing videos. The 

downward-facing camera views were reviewed and used in place of the outward-facing cameras for a 

given species if the counts resulted in a greater abundance estimate. The sampling adequacy for our fish 

data was evaluated for within-comparison groups using rarefaction curves for species richness in 

EstiMateS (Colwell 1997). Species richness reached an asymptote within our sample number across the 

different groups, indicating that our sampling methods were adequate to characterize the fish assemblages 
45

associated with each individual group comparison. Assumptions of all parametric and non-parametric 

statistical tests were met or accounted for as specified. Significance was reported as an alpha (α) of 0.05, 

and error was reported as one standard error from the mean unless noted otherwise.

Of the 150 videos included in the 2013–2014 analyses, 37 camera drops were equipped with one outwardfacing, and one downward-facing synchronized cameras rather than all four. These samples were obtained 

during an initial survey in 2013 and were only included in the analyses if the camera array twisted 

minimally in the water column and maintained a view of the submerged portion of the structure. Thirtyone sets of videos recorded in 2013 with four cameras on the array were used to determine if the 

difference in camera number significantly affected the relative abundance estimates by comparing 

MAXNOs obtained from two of the cameras to those obtained by all four cameras. Species richness and 

Shannon-Weiner diversity were compared between the two camera array configurations using generalized 

linear mixed models (SAS 9.4). Species composition estimates were compared using a PERMANOVA 

(PRIMER). Platform nested by region was included as a random effect in all models while array 

configuration was included as a fixed effect. Array configuration was marginally significant for species 

richness (F (1, 30) = 3.21, P = 0.0834), and was not significant for Shannon-Weiner diversity (F (1, 30) = 

1.02, P = 0.3212) or assemblage composition (pseudo-F = 1.6927, P = 0.184). The disparity in the total 

volume of water sampled between the two and four camera array configurations in addition to variation 

caused by visibility among all platforms were taken into account with a covariate for volume sampled 

(effort) to ensure parity in relative abundance estimates. Midwater turbidity was multiplied by the number 

of outward facing cameras and standardized relative to the lowest value encountered, effectively down 

weighting counts at platforms that sampled a larger volume of water. When effort and the interaction 

between array configuration and effort were included in the model, the likelihood of differences between 

camera array configurations significantly affecting relative abundance estimates was reduced for species 

richness (P = 0.1666), Shannon-Weiner diversity (0.6111), and assemblage composition (P = 0.513). 

Effort was a significant effect for species richness (P = 0.0124) and Shannon-Weiner diversity (P = 

0.0079), but not for assemblage composition (P = 0.212). The interaction between array configuration and 

effort was marginally significant for species richness (P = 0.0986) and assemblage composition (P = 

0.076), and not significant for Shannon-Weiner diversity (P = 0.1676).

3.3 Statistical Analyses

Species richness and Shannon-Weiner diversity were used to compare differences in assemblage 

composition. Species richness reflected the raw total number of species, while Shannon-Weiner diversity 

(H′) also accounted for species evenness and was expressed in terms of the effective number of species 

(ENS) for more meaningful interpretation (Jost 2006): 

ENS = exp(HH′) = exp(-∑i ppilnppi)

where pi was the total proportion of the ith species (Shannon 1948). Regional and annual differences 

were compared for platforms in hypoxic (DO < 50% saturation) and well-oxygenated waters using threeway ANCOVAs for the variables region, year, and presence of hypoxia and included covariates for 

percent sand, platform complexity, and effort (SAS 9.4 Proc GLIMMIX). Tukey-Kramer post-hoc 

adjustments were applied to each ANCOVA to determine significant pairwise differences between leastsquares means under multiple comparisons.

A multivariate multiple regression distance-based linear modeling procedure (distLM) was used to detect 

significant responses of the fish assemblage to site-paired environmental data in PERMANOVA+. 

Species with < 10 observations in the dataset were excluded due to sensitivity of the test to exceptionally 

rare species (Clarke and Gorley 2006). MAXNOs were square-root transformed and a Bray-Curtis 

similarity matrix was computed to determine the percent similarity of the assemblage of each platform 
46

site sampled relative to each other platform and allowed comparison by dissimilarity (Anderson 2001). 

Environmental data, including three principal component factor loadings (Table 2.2), and variables 

longitude, year, percent sand, and platform complexity were normalized and significance of 

environmental data relating to the multivariate species data were determined (Anderson et al. 2008).

Non-parametric permutation based multivariate analyses (PERMANOVA) and percent similarities 

(SIMPER) were compared using PRIMER 6 and PERMANOVA+ from the Bray-Curtis similarity matrix. 

Two-factor permutational MANOVAs (PERMANOVAs) were used to: 1) evaluate interregional and 

interannual differences while accounting for variation in percent sand, bottom DO, and dominant 

sediment types, and 2) evaluate fish assemblage responses to the presence of hypoxia while accounting 

for variation in longitude, year, platform complexity, and effort. For the regional and annual comparison, 

region and year were the main effect variables, and percent sand, bottom DO, platform complexity, and 

effort were covariates. For comparison of dominant sediment type and presence of hypoxia as main 

effect variables, longitude, year, platform complexity, and effort were used as covariates. SIMPER 

analyses indicated species that influenced interregional dissimilarity among the West, Central, and East 

regions, between years 2013 and 2014, between dominant sediment type (sand or mud), presence vs. 

absence of hypoxia, and among platform complexity levels 1–3.

3.4 Results

During the 2013–2014 study, 54 fish species representing 28 families were observed in association with 

small oil and gas platforms throughout the Louisiana nearshore coastal zone (Table 7, 8). However, 

occurrence and abundance of all species associated with small platforms were not all well represented by 

video. Forty fish species belonging to 21 families were identified on video. Of these 40 species, 20 were 

present partially or completely as either young-of-the-year (YOY) or age 1–2 juveniles (Table 9; Figure 

17). For the majority of those species, YOY individuals were underestimated in counts due to their small 

size, cryptic appearance, or evasive behavior. Consequently most YOY were omitted from relative 

abundance estimates. There were another 14 species from seven families that were observed by divers, 

but not on video. Diver observation confirmed these species as a regular and substantial component of 

the fish assemblages. No effort was made to quantify or analyze the distribution of these species: 

flamefish (Apogon maculatus), hardhead catfish (Ariopsis felis), age 1–2 juvenile horse-eye jack (Caranx 

latus) YOY spotfin butterflyfish (Chaetodon ocellatus), a variety of both adult and YOY blennies

(Blenniidae), YOY gag grouper (Mycteroperca microlepis), adult Southern flounder (Paralicthys 

lethostigma), adult and YOY high-hat drum (Pareques acuminatus), adult greater soapfish (Rypticus 

saponaceus; usually in pairs), adult and YOY belted sandfish (Serranus subligarius), Northern puffer 

(Sphoeroides maculatus), and adult and YOY coaco damsel (Stegastes variabilis).
47

Table 6. Distributions, relative abundance and percent occurrence estimates of fishes around 

small platforms sorted by region (West, Central, and East) and year 

Note: Next to each common name are the numbers and % of 150 platforms where each species was observed on 

video. Next to the taxonomic names are the percent of the total no. of fish observed (mean MAXNO of fish per 

platform). MAXNOs represent adult fish unless noted. (*) Indicates where YOY were detected by divers, but absent, 

or under-sampled by the camera array.

Species

West Central East

2013 2014 2013 2014 2013 2014

Sergeant major* (adu./juv.)

Abudefduf saxatilis

4 (33%)

(4%)

16 (80%)

47%

2 (10%)

3%

29 (56%)

40%

0

0

2 (13%)

5%

Unicorn leatherjacket

Aluterus monoceros

0

0

1 (5%)

100%

0

0

0

0

0

0

0

0

Porkfish

Anisotremus virginicus

0

0

0

0

0

0

0

0

0

0

1 (7%)

100%

Sheepshead

Archosargus probatocephalus

12 

(100%)

11%

14 (70%)

8%

17 (85%)

10%

44 (88%)

35%

30 (91%)

11%

14 (93%)

25%

Gray triggerfish* (adu./juv.)

Balistes capriscus

5 (42%)

11%

16 (80%)

25%

11 (55%)

7%

38 (76%)

19%

10 (30%)

5%

10 (67%)

33%

Yellow jack*

Carangoides bartholomaei

2 (17%)

79%

4 (20%)

14%

2 (10%)

4%

3 (6%)

3%

0

0

0

0

Blue runner (adu./juv.)

Caranx crysos

7 (58%)

9%

13 (65%)

22%

16 (80%)

14%

47 (94%)

28%

9 (27%)

7%

8 (53%)

20%

Jack crevalle

Caranx hippos

1 (8%)

2%

3 (15%)

15%

6 (30%)

20%

13 (26%)

16%

6 (18%)

12%

9 (60%)

34%

Jack crevalle (juv.)

Caranx hippos

0

0

2 (17%)

10%

7 (35%)

56%

7 (14%)

31%

1 (3%)

3%

0

0

Bar jack* (juv.)

Caranx ruber

0

0

3 (15%)

100%

0

0

0

0

0

0

0

0

Blacktip shark

Carcharhinus limbatus

0

0

0

0

0

0

1 (2%)

100%

0

0

0

0

Bull shark

Carcharhinus leucas

0

0

0

0

0

0

1 (2%)

100%

0

0

0

0

Atlantic spadefish* (adu./juv.)

Chaetodipterus faber

12 

(100%)

12%

20 (100%)

40%

20 (100%)

12%

50 (100%)

16%

32 (97%)

4%

15 

(100%)

6%

Atlantic bumper (adu./juv.)

Chloroscombrus chrysurus

4 (33%)

1%

16 (80%)

30%

4 (20%

1%

25 (50%)

45%

15 (45%)

12%

2 (13%)

10%

Southern stingray

Dasyatis americana

1 (8%)

43%

0

0

0

0

4 (8%)

41%

1 (3%)

16%

0

0

Rainbow runner*

Elagatis bipinnulata

0

0

2 (10%)

16%

0

0

8 (16%)

62%

0

0

2 (13%

22%

Ladyfish

Elops saurus

3 (25%)

33%

2 (10%)

17%

0

0

6 (12%)

49%

1 (3%)

1%

0

0

Red hind

Epinephelus guttatus

0

0

0

0

0

0

0

0

0

0

2 (13%)

100%

Goliath grouper

Epinephelus itajara

0

0

0

0

0

0

0

0

0

0

1 (6.67%)

100%

Bluntnose jack (juv.)

Hemicaranx amblyrhynchus

0

0

0

0

0

0

1 (2%)

100%

0

0

0

0

Queen angelfish*

Holacanthus ciliaris

0

0

0

0

0

0

0

0

1 (2%)

31%

1 (7%)

69%
48

Table 7. Distributions, relative abundance and percent occurrence estimates of fishes around 

small platforms sorted by region and year 

Note: Next to each common name are the numbers and percentage of 150 platforms where each species was 

observed on video. Next to the taxonomic names are the percent of the total number of fish observed (mean MAXNO 

of fish per platform). MAXNOs represent adult fish unless noted. Asterisks (*) indicate where YOY were detected by 

divers, but absent, or under-sampled by the camera array.

Species

West Central East

2013 2014 2013 2014 2013 2014

Bermuda chub

Kyphosus sectatrix

4 (33%)

6%

13 (65%)

48%

6 (30%)

6%

31 (62%)

37%

1 (3%)

1%

1 (7%)

2%

Pinfish

Lagodon rhomboides

0

0

4 (33%)

38%

1 (20%)

6%

10 (20%)

54%

1 (3%)

1%

0

0

Tripletail

Lobotes surinamensis

0

0

1 (5%)

45%

0

0

0

0

1 (3%)

55%

0

0

Red snapper*

Lutjanus campechanus

3 (25%)

4%

4 (20%)

3%

7 (35%)

6%

18 (36%)

11%

18 (55%)

40%

12 (80%)

36%

Red snapper* (juv.)

Lutjanus campechanus

3 (25%)

33%

5 (25%)

13%

0

0

7 (14%)

13%

10 (30%)

34%

1 (7%)

8%

Gray snapper* (adu./juv.)

Lutjanus griseus

7 (58%)

5%

5 (25%)

2%

19 (95%)

34%

41 (82%)

12%

26 (79%)

15%

14 (93%)

31%

Dog snapper* (adu./juv.)

Lutjanus jocu

0

0

0

0

1 (5%)

27%

0

0

0

0

1 (7%)

73%

Lane snapper* (adu./juv.)

Lutjanus synagris

2 (17%)

72%

3 (15%)

7%

3 (15%)

14%

4 (8%)

4%

1 (3%)

4%

0

0

Striped mullet

Mugil cephalus

0

0

0

0

0

0

6 (12%)

100%

0

0

0

0

Pigfish

Orthopristis chrysoptera

1 (8%)

26%

2 (10%)

68%

0

0

3 (6%)

5%

1 (3%)

1%

0

0

Black drum

Pogonias cromis

2 (17%)

13%

2 (10%)

15%

0

0

7 (14%)

41%

5 (15%)

16%

3 (20%)

15%

Bluefish (adu./juv.)

Pomatomus saltatrix

2 (17%)

8%

13 (65%)

61%

4 (20%)

4%

20 (40%)

24%

5 (15%)

3%

0

0

Lionfish (adu./juv.)

Pterois spp.

0

0

0

0

0

0

0

0

0

0

2 (13%)

100%

Cobia (adu./juv./YOY)

Rachycentron canadum

5 (42%)

11%

11 (55%)

57%

6 (30%)

9%

13 (26%)

10%

5 (15%)

8%

2 (13%)

3%

Red drum

Sciaenops ocellatus

4 (33%)

18%

1 (5%)

3%

2 (10%)

5%

11 (22%)

15%

9 (27%)

33%

3 (20%)

25%

Spanish mackerel

Scomberomorus maculatus

2 (17%)

32%

1 (5%)

2%

0

0

11 (22%)

38%

1 (3%)

21%

1 (7%)

6%

Atlantic lookdown

Selene vomer

2 (17%)

18%

3 (15%)

4%

4 (20%)

35%

6 (12%)

15%

3 (9%)

7%

4 (27%)

20%

Greater amberjack (YOY)

Seriola dumerili

7 (58%)

28%

14 (70%)

40%

2 (10%)

1%

13 (26%)

18%

1 (3%)

1%

3 (20%)

12%

Almaco jack (YOY)

Seriola rivoliana

0

0

10 (50%)

76%

0

0

4 (8%)

7%

0

0

1 (7%)

17%

Planehead filefish

Stephanolepis hispidus

1 (8%)

100%

0

0

0

0

0

0

0

0

0

0

Florida pompano

Trachinotus carolinus

0

0

0

0

4 (20%)

50%

17 (34%)

50%

0

0

0

0
49

Table 8. Summary of environmental measurements reported as a mean, during the initial coastwide survey (CW) and summers of 2013 and 2014

95% confidence interval and range of observed values for surface, Midwater, and Bottom water physicochemical 

variables for West, Central, and East regions of the coastal ocean off Louisiana

Variables Dept

h

West Central East

CW 2013 2014 CW 2013 2014 CW 2013 2014

Salinity 

(psu)

Surf.

30.79 

(±0.67)

26.68–

33.30

31.42

(±0.62)

26.19–

34.22

29.99 

(±0.61)

26.71–

32.79

23.99 

(±1.90)

0.90–

27.84

23.98 

(±1.43)

0.90–

29.30

24.32 

(±0.94)

10.11–

30.08

19.01

(±2.16)

1.18–

28.04

17.02 

(±2.04)

1.18–

28.04

22.99 

(±1.71)

6.02–

30.66

Mid.

31.02 

(±0.55)

29.45–

33.21

31.63

(±0.55)

26.20–

34.26

30.53

(±0.55)

26.93–

32.95

26.38 

(±0.38)

21.38–

28.95

26.23 

(±0.51)

15.24–

29.70

29.09 

(±0.45)

22.47–

33.97

19.01 

(±2.16)

1.18–

28.04

17.02 

(±2.04)

1.18–

28.04

22.99 

(±1.71)

6.02–

30.66

Bot.

31.68 

(±0.42)

29.92–

33.21

32.21

(±0.43)

28.62–

34.52

32.18 

(±0.50)

29.17–

33.95

28.00 

(±0.72)

25.26–

34.85

28.95 

(±0.61)

25.26–

34.85

31.45 

(±0.52)

25.32–

35.54

19.01 

(±2.16)

1.18–

28.04

17.02 

(±2.04)

1.18–

28.04

22.99 

(±1.71)

6.02–

30.66

Temp. 

(°

C)

Surf.

30.13 

(±0.17)

29.50–

31.23

30.11 

(±0.11)

29.50–

31.23

30.54 

(±0.13)

29.93–

31.20

30.07 

(±0.36)

28.79–

33.38

29.98 

(±0.26)

28.15–

33.38

30.69 

(±0.14)

29.33–

32.57

29.18 

(±0.32)

27.83–

32.72

29.20 

(±0.27)

27.83–

32.72

28.69 

(±0.42)

22.89–

30.44

Mid.

29.81 

(±0.08)

29.50–

30.19

29.88 

(±0.08)

29.50–

30.65

30.30 

(±0.06)

29.97–

30.62

29.37 

(±0.11)

28.30–

30.66

29.41 

(±0.13)

28.30–

30.69

29.55 

(±0.18)

27.50–

31.14

27.80 

(±0.09)

26.85–

28.79

27.87 

(±0.08)

26.85–

28.79

25.68 

(±0.73)

22.71–

29.34

Bot.

29.35 

(±0.25)

27.84–

29.99

29.57 

(±0.18)

27.84–

30.27

29.79 

(±0.23)

27.94–

30.62

28.57 

(±0.31)

25.55–

29.46

28.59 

(±0.22)

25.55–

29.85

28.20 

(±0.43)

23.31–

31.15

26.28 

(±0.20)

24.39–

27.46

26.45 

(±0.21)

24.39–

28.19

23.47 

(±0.57)

21.65–

28.80

Dissolve

d oxygen

(mg l−1)

Surf.

7.12 

(±0.31)

5.69–

9.17

7.02 

(±0.21)

5.69–

9.17

6.60 

(±0.15)

5.69–

7.50

8.04 

(±0.64)

6.08–

20.27

8.17 

(±0.50)

5.81–

20.27

7.62 

(±0.32)

6.20–

13.75

9.20 

(±0.76)

5.40–

19.41

9.43 

(±0.66)

5.40–

19.41

9.27 

(±0.48)

6.40–

12.41

Mid.

7.05 

(±0.26)

5.66–

8.54

6.91 

(±0.18)

5.66–

8.54

6.25 

(±0.17)

5.03–

7.09

7.44 

(±0.32)

3.29–

10.52

7.50 

(±0.32)

2.10–

11.57

6.09 

(±0.25)

2.77–

8.40

7.04 

(±0.43)

0.50–

10.98

6.81 

(±0.38)

0.50–

10.98

6.19 

(±0.47)

3.46–

10.25

Bot.

4.29 

(±1.12)

0.12–

6.76

4.83 

(±0.74)

0.12–

7.84

3.75 

(±0.71)

0.19–

6.56

4.30 

(±0.69)

0.23–

8.16

4.06 

(±0.62)

0.19–

8.73

3.73 

(±0.52)

0.08–

7.50

2.73 

(±0.34)

0.17–

5.51

3.06 

(±0.33)

0.17–

6.44

3.81 

(±0.53)

0.15–

9.49
50

Table 9. Summary of environmental measurements reported as a mean, during the initial coastwide survey (CW) and summers of 2013 and 2014

95% confidence interval and range of observed values for surface, Midwater, and Bottom water physicochemical 

variables for West, Central, and East regions of the coastal ocean off Louisiana.

Variables Depth West Central East

CW 2013 2014 CW 2013 2014 CW 2013 2014

Density 

(kg/m3)

Surf.

1018.4 

(±0.4)

1015.6

–

1020.2

- -

1013.5 

(±1.5)

995.5–

1016.4

- -

1010.1 

(±1.7)

996.7–

1017.1

- -

Mid.

1018.9 

(±0.4)

1017.7

–

1020.5

- -

1015.5 

(±0.3)

1011.6

–

1017.4

- -

1018.3 

(±0.5)

1010.3

–

1021.1

- -

Bot.

1019.5 

(±0.3)

1018.1-

1020.6

- -

1017.0 

(±0.6)

1014.7

–

1023.1

- -

1021.4 

(±0.3)

1018.2

–

1023.7

- -

pH

Surf.

8.2

(±0.1)

8.0–

8.8

- -

8.5 

(±0.1)

8.2–

9.5

- -

8.6 

(±0.1)

8.0–

9.2

- -

Mid.

8.2 

(±0.1)

8.0–

8.4

- -

8.4 

(±0.1)

8.0–

8.7

- -

8.3 

(±0.1)

7.9–

8.7

- -

Bot.

8.0 

(±0.1)

7.6–

8.2

- -

8.2 

(±0.1)

7.7–

8.6

- -

8.1 

(±0.1)

7.2–

10.8

- -

Secchi 

depth 

(m)

4.10 

(±0.89)

1.47–

9.55

4.13 

(±0.69)

1.47–

10.48

7.19 

(±1.16)

1.25–

12.70

2.54 

(±0.45)

0.47–

7.05

3.24 

(±0.46)

0.47–

8.43

5.16 

(±0.60)

0.96–

11.61

1.88 

(±0.46)

0.27–

7.57

1.71 

(±0.38)

0.27–

7.57

1.90 

(±0.30)

0.60–

4.29

4.10 

(±0.89)

1.47–

9.55

Site 

depth 

(m)

10.87 

(±0.92)

6.71–

15.24

10.95 

(±0.68)

6.71–

15.24

12.14 

(±0.85)

7.32–

16.08

8.07 

(±0.80)

3.66–

15.62

8.31 

(±0.57)

3.66–

15.62

9.57 

(±0.67)

4.42–

16.76

12.41 

(±0.84)

5.79–

17.56

12.04 

(±0.77)

5.49–

17.56

11.72 

(±1.10)

4.33–

17.98

10.87 

(±0.92)

6.71–

15.24

Distanc

e from 

shore 

(km)

22.12 

(±5.43)

6.08–

45.86

24.11 

(±4.21)

6.08–

45.86

28.08 

(±5.00)

7.12–

46.56

19.82 

(±2.24)

9.03–

39.13

18.18 

(±1.67)

6.87–

39.14

20.40 

(±1.67)

6.54–

40.87

9.20 

(±1.08)

1.26–

19.40

9.00 

(±0.92)

1.26–

19.40

8.22 

(±1.11)

0.79–

17.43

22.12 

(±5.43)

6.08–

45.86

Percent 

sand

4.10 

(±0.89)

1.47–

9.55

4.13 

(±0.69)

1.47–

10.48

7.19 

(±1.16)

1.25–

12.70

2.54 

(±0.45)

0.47–

7.05

3.24 

(±0.46)

0.47–

8.43

5.16 

(±0.60)

0.96–

11.61

1.88 

(±0.46)

0.27–

7.57

1.71 

(±0.38)

0.27–

7.57

1.90 

(±0.30)

0.60–

4.29

4.10 

(±0.89)

1.47–

9.55
51

Figure 17. YOY greater amberjack and almaco jack (A), adult and YOY cobia (B), YOY blue runner, rainbow 

runner, and bar jack (C), YOY red and lane snapper (D), age 1–2 juvenile red, lane, and gray snapper, 

adult red drum, sheepshead, and spadefish (E), and YOY gag grouper (F).

Among the most interesting findings of this study were the fish assemblages associated with East Bay. 

East Bay is located between Southwest and South Pass of the southernmost portion of the Mississippi 

delta (Figure 16). This exposed embayment measures 10 km across at its widest point. Within East Bay 

are hundreds of federal and state-managed oil and gas structures. We confirmed the presence of three 

goliath grouper (Epinephelus itjara) in East Bay, two of which were observed during a dive survey in 

September of 2013, and a third was videoed in July of 2014. A potential fourth goliath was recorded 

during July of 2013, although the image was of low quality. Our sightings in 2013 marked the first 

confirmed identification of goliath grouper in Louisiana waters in over 20 years (LDWF, personal 

communication). Also of note was the presence of two invasive species that were absent in nearshore 

waters across the rest of the Louisiana coastline, the lionfish (Pterois spp.) and sun coral (Tubastarea 

coccinea).

Interestingly, the bottom waters of East Bay were rarely depleted of DO below 50% saturation (only 9% 

of samples), and were never observed to fall below 2.0 mg l−1. Upwelling of well-oxygenated waters 

may reduce the frequency and intensity of East Bay to bottom-water DO depletion, despite the close 

proximity to the point source of eutrophication in the region (i.e., Mississippi river nutrients and strong 

stratification). Well-oxygenated bottom waters made the relatively high salinities, low temperatures, and 

low light levels (due to high surface turbidity) of East bay accessible to fishes which were larger than 

anywhere else on the coast. Although there were clear differences in the occurrence of rare species 

between East Bay and the rest of the East region, they were grouped in the analyses. Many features of 

East Bay embodied the most extreme characteristics that typified the East region: intensely stratified 

waters over a narrow part of the Louisiana shelf. There was a fundamental similarity between the 

common species that occupied both locations, namely abundant red and gray snapper. Also, some 

uncommon species, dog snapper and queen angelfish, were found in both locations, but nowhere else in 

the nearshore coastal zone.
52

3.4.1 Statistical Results

Species richness and Shannon-Weiner diversity (H′) varied significantly across the study area. The threeway ANCOVA for species richness indicated effects for year, percent sand, and the interaction between 

region and hypoxia (P = 0.0001, 0.0422, 0.0384; Table 11). Pairwise comparison of richness showed the 

highest overall richness in the West region, second highest in the Central region, and lowest in the East 

region. Richness was higher in 2014 than 2013 for all regions, and in 2014, richness in the West and 

Central regions were not detectably different. Richness was reduced in the West and Central regions in 

the presence of hypoxia, while in the East region, species richness increased in the presence of hypoxia 

(Figure 18). The three-way ANCOVA for Shannon-Weiner diversity indicated marginal significance for 

region and platform complexity (P = 0.0620, and 0.0572; Table 12). Pairwise comparison of diversity 

showed no significance in pairwise comparisons. The effective number of species (ENS) was similar in 

the West and Central regions, but lower ENS in the East. The ENS was higher in 2013 than 2014 in the 

West and Central regions, and consistent between years in the East region. The ENS was generally lower 

in the presence of hypoxia (Figure 18).

Table 10. Three-way ANCOVA for type III fixed effects of region, year, and hypoxia on species 

richness, controlling for relative volume sampled, and % sand. 

Variables Numerator DF Denominator

DF F P

Region 2 134 2.49 0.0865

Year 1 134 15.87 0.0001*

Hypoxia 1 134 0.02 0.8857

% Sand 1 134 4.21 0.0422*

Complexity 2 134 0.15 0.8635

Effort 1 134 0.82 0.3672

Region x Year 2 134 1.38 0.2559

Region x Hypoxia 2 134 3.34 0.0384*

Year x Hypoxia 1 134 0.73 0.3948

Region x Year x Hypoxia 2 134 0.37 0.6923

Note: Asterisks (*) indicate significance of interpretable variables.

Table 11. Three-way ANCOVA for type III fixed effects of region, year, and hypoxia on ShannonWeiner effective number of species (ENS), controlling for relative volume sampled, and % sand. 

Variables Numerator 

DF

Denominator 

DF F P

Region 2 134 2.84 0.0620~

Year 1 134 1.49 0.22480

Hypoxia 1 134 1.53 0.21870

% Sand 1 134 0.12 0.73060

Effort 1 134 0.52 0.47140

Complexity 2 134 2.92 0.0572~

Region x Hypoxia 2 134 0.48 0.62280

Region x Year 2 134 1.40 0.25130

Year x Hypoxia 1 134 1.25 0.26550

Region x Year x Hypoxia 2 134 1.44 0.24150

Tildes (~) indicate marginal significance of interpretable variables (α < 0.1).
53

Figure 18. Pairwise comparison of species richness (left), and the effective number of species (ENS) based 

on Shannon-Weiner diversity (right) across nearshore Louisiana by region (West, Central, and East), 

dominant sediment type (sand or mud), and in the presence or absence of hypoxia, controlling for 

sediment composition.

Results from the distLM indicated that all seven variables considered in the analysis significantly 

contributed to explaining changes in the fish assemblages; however, the explained variation in the 

assemblage compositions was only 25.4% (Table 13). Distance-based redundancy analysis (dbRDA) 

indicated that most of the variance explained in the model was from dbRDA1 (15.0% of the total), and 

dbRDA2 (4.9% of the total), which were primarily influenced by year and Factor 2, respectively. The 

remaining variance explained by five other variables diminished in order of longitude, Factor 3, percent 

sand, Factor 1, and platform complexity. The dbRDA plot showed how the assemblage at each platform 

changed in response to these variables, and when color coded by region, showed a pattern of regional 

separation across all variables except Factor 3 (increasing bottom- water DO depletion) and platform 

complexity (Figure 18). Interestingly, there seemed to be a convergence in the assemblages across 

regions with an increase in Factor 2 (decreasing surface, midwater, and bottom temperature, increasing 

midwater and bottom salinity, and increasing depth).

Table 12. Summary of a non-parametric distance-based linear model (distLM) analysis and a 

distance-based redundancy analysis (dbRDA) of partial correlations relating coordinate axes, 

orthonormal X variables and variation explained. 

Asterisks (*) indicate significance. Underlines indicate the primary contributors to each dbRDA component.

Variables dbRDA

1

dbRDA

2

dbRDA

3

dbRDA

4

dbRDA

5

dbRDA

6

dbRDA

7

Pseudo

-F P

Year −0.620 0.196 −0.495 −0.403 −0.163 −0.021 0.378 13.37 0.001*

Factor 2 0.099 0.713 −0.133 −0.168 0.576 −0.069 −0.316 4.93 0.001*

Long. −0.422 0.430 0.730 0.121 −0.169 0.222 0.109 12.46 0.001*

Factor 3 −0.355 −0.495 0.189 −0.275 0.633 0.333 −0.079 6.27 0.001*

% Sand −0.481 −0.103 −0.058 0.573 0.214 −0.600 −0.143 9.69 0.001*

Factor 1 −0.238 0.026 −0.337 0.292 −0.253 0.553 −0.611 5.25 0.001*

Complexity 0.118 0.113 −0.227 0.553 0.320 0.410 0.588 2.62 0.020*

Fitted % 

variation 59.1 19.4 9.6 5.4 3.6 2.1 0.9

Total % 

variation 15.0 4.9 2.5 1.4 0.9 0.5 0.2 R2 = 25.4%
54

Figure 19. Plot of distance-based redundancy analysis (dbRDA) displaying the assemblage distributions in 

relation to three principle component factors, and four additional variables of importance (longitude, 

year, % sand, and platform complexity).

PERMANOVA detected significant interregional and interannual differences in the species compositions 

of the fish assemblages. The global test indicated significance of the volume sampled covariate (pseudoF = 13.572, P = 0.001; Table 14), as well as three-way interactions among the main effects region and 

year and the bottom DO saturation covariate (pseudo-F = 2.3865, P = 0.008; Table 14). Pairwise 

comparisons of the main effects indicated significant differences among all regions by year, with the 

exception of the West and East region in 2013 (pseudo-t = 1.6626, P = 0.016; Table 15). There were 

significant intraregional differences between sampling years for the West and Central regions, and no 

significant difference between years in the East region (pseudo-F = 2.6092, 3.566, and 1.3252, P = 0.001, 

0.001, and 0.119; Table 15).
55

Table 13. PERMANOVA for type I fixed effects of region and year, controlling for sediment 

composition (% sand), hypoxia, and relative volume sampled. 

Variable Degrees of 

freedom pseudo-F p Values Unique perms

Region 2 5.9738 0.001 998

Year 1 12.332 0.001 998

% Sand 1 10.437 0.001 999

BDO 1 5.8364 0.001 999

Complexity 1 9.3718 *0.001 999

Effort 1 13.940 *0.001 999

Region x Year 2 3.0895 0.001 998

Region x % Sand 2 5.1365 0.001 998

Region x BDO 2 2.8469 0.001 999

Year x % Sand 1 3.8046 0.003 999

Year x BDO 1 1.9369 0.049 998

% Sand x BDO 1 1.2591 0.256 999

Region x Year x % Sand 2 2.3885 *0.007 998

Region x Year x BDO 2 2.0321 0.127 997

Region x % Sand x BDO 2 2.3808 *0.003 998

Year x % Sand x BDO 2 2.1796 *0.031 999

Region x Year x % Sand x BDO 2 0.6982 0.792 999

Asterisks (*) indicate significance of interpretable variables.

Table 14. PERMANOVA pairwise comparisons of significant interregional (West, Central, and 

East) and interannual (2013 and 2014) assemblage shifts. 

Pairwise comparison Pseudo-t p Values Unique perms

West-Central (2013) 1.8892 *0.001 998

West-Central (2014) 2.0864 *0.001 999

Central-East (2013) 2.3597 *0.001 999

Central-East (2014) 1.9068 *0.001 998

West-East (2013) 1.7922 *0.003 998

West-East (2014) 2.9452 *0.001 999

West-Year 2.5523 *0.001 999

Central-Year 3.6476 *0.001 998

East-Year 1.2097 0.179 999

Asterisks (*) indicate significance of interpretable variables (Bonferroni adjusted α = 0.0083).

Significant differences in compositions of the fish assemblages were also detected between dominant 

sediment type and presence of hypoxia. The global test indicated significance of hypoxia, the volume 

sampled covariate (pseudo-F = 5.8384 and 12.144, P = 0.001 and 0.001; Table 16), and a three-way 

interaction among the main effect dominant sediment type, and longitude and year covariates (pseudo-F = 

2.4768, P = 0.02; Table 14). Pairwise comparison indicated significant differences between dominant 

sediment types in the absence of hypoxia, but not in the presence of hypoxia (pseudo-t = 2.1813 and 

1.0963, P = 0.001 and 0.289; Table 17). There were significant differences among platforms in hypoxic 

waters overlying mud-dominated sediments, but no significant differences between platforms in hypoxic 

waters overlying sand-dominated sediments (pseudo-F = 2.2347 and 1.2456, P = 0.001 and 0.131; Table 

17).
56

Table 15. PERMANOVA for type I fixed effects of dominant sediment type (Sed) and hypoxia, 

controlled for longitude (Long), year, and relative volume sampled.

Variable Degrees of 

freedom pseudo-F p Values Unique perms

Sed 1 5.3916 0.001 999

Hypoxia 1 5.9543 *0.001 998

Year 1 5.6538 0.001 999

Long 1 11.007 0.001 998

Complexity 1 10.559 *0.001 996

Effort 1 6.8294 *0.001* 998

Sed x Hypoxia 1 1.8716 ~0.063 999

Sed x Long 1 1.4265 0.155 997

Sed x Year 1 2.9654 0.007 999

Hypoxia x Long 1 1.6577 0.089 999

Hypoxia x Year 1 1.6885 0.097 999

Long x Year 1 9.5890 0.001 999

Sed x Hypoxia x Long 1 0.7070 0.666 999

Sed x Hypoxia x Year 1 1.5454 0.136 998

Sed x Long x Year 1 2.1495 *0.037 997

Hypoxia x Long x Year 1 1.3607 0.201 999

Sed x Hypoxia x Long x Year 1 0.7253 0.649 998

Hypoxia DO < 50% saturation. Asterisks (*) indicate significance of interpretable variables (α < 0.05). Tildes (~) 

indicate marginal significance of interpretable variables (α < 0.1).

Table 16. PERMANOVA pairwise comparisons of significant assemblage shifts for dominant 

sediment type (Sed) (sand or mud) and presence or absence of hypoxia. 

Pairwise comparison Pseudo-t p Values Unique perms

Sed-No hypoxia 2.1706 *0.001 999

Sed-Hypoxia 0.9838 0.413 999

Hypoxia-Mud 2.2518 *0.001 998

Hypoxia-Sand 1.2532 0.110 999

Hypoxia DO < 50% saturation. Asterisks (*) indicate significance of interpretable variables (Bonferroni adjusted α = 

0.0125).

SIMPER analyses (Figures 20–24) showed that mean dissimilarity among fish assemblages of the three 

hydrographically distinct regions was lowest between the West and Central regions, intermediate between 

the Central and East regions, and highest between the West and East regions (Figure 20). Annual and 

intraregional comparisons of dissimilarity were also high at 64.1% between 2013 and 2014 (Figure 21). 

Fish assemblages over sand and mud were 62.7% dissimilar (Figure 22). Fish assemblages over hypoxic 

and non-hypoxic waters were 61.8% dissimilar (Figure 23). Finally mean assemblage dissimilarities 

among platform complexity levels (1–2, 2–3, and 1–3) were 61.7%, 61.5%, and 60.1%, although there 

were no apparent trends (Figure 24). Regional dissimilarity of fish assemblages was high for all 

comparisons (60.3%, 64.2%, and 68.4%; Table 18). 

Species driving consistent differences in assemblage structure were identified by their contribution to the 

ratio of percent dissimilarity to the standard deviation (Clarke and Warwick 2001). Of the 28 species and 

life history stages included in the analyses, 11 species consistently contributed to dissimilarity of one or 

more comparisons and together accounted for ~93% of all fishes observed. These species were dominant, 

and potentially the most ecologically significant (Gaston 2010) shallow-water nearshore platform species: 

Atlantic bumper (~56%), Atlantic spadefish (~18%), blue runner (~9%), bluefish (~4%), sheepshead 

(~3%), gray snapper (~2%), sergeant major damselfish (~1%), Bermuda chub (< 1%), YOY greater 

amberjack (<1%), gray triggerfish (< 1%), and adult red snapper (< 1%). Atlantic bumper were 

numerically dominant and occurred 44% of 150 platforms evaluated. Atlantic spadefish were second in 

numerical abundance and the most widely distributed species, occurring at > 99% (all but one) of the 

platforms.
57

Regional SIMPER results for the 11 species of the core assemblage showed increasing relative 

contributions from east to west for Atlantic spadefish, bluefish, sergeant major damselfish, Bermuda 

chub, YOY greater amberjack, and gray triggerfish, but gray and adult red snapper decreased from east to 

west. Atlantic bumper, blue runner, and sheepshead relative contributions were highest in the Central 

region, with the second highest contributions from Atlantic bumper and blue runner in the West region, 

and sheepshead in the East region. Intraregional differences between sand and mud-dominated bottom 

sediments (Figure 22) indicated that Atlantic bumper, Atlantic spadefish, bluefish, sheepshead, gray 

snapper, sergeant major damselfish, YOY greater amberjack, and gray triggerfish were the core 

assemblage species that were more common in sand-dominated areas. Blue runner, Bermuda chub, and 

adult red snapper were more common in mud-dominated areas. Species distributions over hypoxic waters 

(Figure 23) were similar to those over mud bottoms, with the exception of higher abundances of 

sheepshead, sergeant major damselfish, and YOY greater amberjack over hypoxic waters than welloxygenated bottom waters. Atlantic bumper, Atlantic spadefish, bluefish, gray snapper, and triggerfish 

made higher contributions in well-oxygenated waters, while blue runner, sheepshead, sergeant major 

damselfish, Bermuda chub, YOY greater amberjack, and adult red snapper all had higher contributions 

over hypoxic waters.
58

Note: Bold font indicates those species which together account for > 90% of interannual fish assemblage dissimilarity. Species order reflects rank order 

abundance.

Figure 20. Results of a SIMPER analysis comparing the interregional differences (West, Central, and East) in the mean MAXNO pairwise dissimilarities 

of fish assemblages around small nearshore platforms. 
59

Note: Bold font indicates those species which together account for >90% of interannual fish assemblage dissimilarity. Percentages over bars indicate 

percent dissimilarity contributions and numbers below the percentages are the ratio of the percent dissimilarity over the standard deviation. Species order 

reflects rank order abundance.

Figure 21. Results of a SIMPER analysis comparing the interannual differences (2013, 2014) in the mean MAXNO pairwise dissimilarities of fish 

assemblages around small nearshore platforms. 
60

Note: Bold font indicates those species which together account for > 90% of dominant sediment type fish assemblage dissimilarity. Percentages above 

bars are percent dissimilarity contributions and the numbers below the percentage is the ratio of the percent dissimilarity over the standard deviation. 

Species order reflects rank order abundance.

Figure 22. Results of a SIMPER analysis comparing the relationship between dominant sediment type (sand or mud) and the mean MAXNO pairwise 

fish assemblage dissimilarities around small platforms.
61

Note: Bold font indicates species which together account for > 90% of hypoxia fish assemblage dissimilarity. Percentages above the bars indicate percent 

dissimilarity contributions, the number below the percentages are the ratio of the percent dissimilarity over the standard deviation. Species order reflects ranked 

order abundance.

Figure 23. Results of a SIMPER analysis comparing the relationship between the presence or absence of hypoxia (DO < 50% saturation) and the mean 

MAXNO pairwise dissimilarities of fish assemblage around small nearshore platforms. 
62

Note: Bold font indicates those species which accounted for > 90% of platform complexity fish assemblage dissimilarity. Species order reflects ranked order 

abundance.

Figure 24. Results of a SIMPER analysis showing the relationship between platform complexity (1–3) and the mean MAXNO pairwise fish assemblage 

dissimilarities around small nearshore platforms.
63

Table 17. Results of SIMPER pairwise dissimilarities (DISS) analyses for the dominant 

components of the fish assemblages around small nearshore platforms compared across three 

coastal regions (West, Central, and East) off Louisiana. 

Pairwise

contrast Species Mean MAXNO MeanMAXNO Diss/SD % Dissim.

WestCentral

60.3%

Mean Diss

West Central

Chloroscombrus chrysurus 98.0±30.6 161.6±46.7 1.13* 22.7

Chaetodipterus faber 59.3±15.0 43.6±4.63 1.32* 10.3

Caranx crysos 16.1±4.0 22.5±3.9 1.14* 10.0

Lutjanus griseus 1.0±0.4 5.5±0.9 1.06* 5.2

Archosargus 

probatocephalus 2.69±0.5 7.8±1.2 1.14* 4.7

Seriola dumerili 4.1±0.8 1.5±0.7 1.05* 4.5

Kyphosus sectatrix 3.1±0.9 2.7±0.6 1.04* 3.9

Balistes capriscus 2.1±0.4 1.7±0.3 1.14* 2.9

CentralEast

64.2%

Mean Diss

Central East

Caranx crysos 1.7±0.3 10.7±4.2 1.20* 12.6

Chaetodipterus faber 43.6±4.6 9.8±1.6 1.54* 12.4

Lutjanus griseus 5.5±0.9 6.0±1.1 1.16* 5.8

Archosargus 

probatocephalus 7.8±1.2 4.3±0.7 1.23* 5.4

Lutjanus campechanus 

(adu) 0.9±0.3 3.7±0.9 1.01* 4.6

Balistes capriscus 1.7±0.3 1.4±0.4 1.15* 3.6

West-East

68.4%

Mean Diss

West East

Chloroscombrus chrysurus 98.0±30.6 58.6±19.4 1.16* 20.5

Chaetodipterus faber 59.3±15.0 9.8±1.6 1.57* 12.5

Caranx crysos 16.1±4.0 10.7±4.2 1.07* 9.9

Lutjanus griseus 1.0±0.4 6.0±1.1 1.10* 6.3

Seriola dumerili 4.1±0.8 0.5±0.3 1.07* 4.8

Abudefduf saxatilis 4.1±0.9 0.2±0.1 1.03* 4.4

Archosargus 

probatocephalus 2.7±0.5 4.3±0.7 1.18* 3.8

Balistes capriscus 2.1±0.4 1.4±0.4 1.10* 3.6

Note: Results shown are species with Diss/SD ratios > 1, indicating consistent contribution to dissimilarity. Species 

with high dissimilarity, but patchy in their distribution, were excluded. 
64

Table 18. Results of SIMPER pairwise dissimilarities (DISS) analyses for the dominant 

components of the fish assemblages observed around small nearshore platforms comparing 

platforms by sampling year (2013 and 2014), dominant sediment type (Sed) (sand or mud) and 

presence or absence of hypoxia (DO < 50% saturation).

Pairwise

contrast Species Mean MAXNO MeanMAXNO Diss/SD % Dissim.

Not

hypoxicHypoxic

61.8%

Mean Diss

Not hypoxic Hypoxic

Chloroscombrus chrysurus 130.9±37.7 94.9±24.9 1.01* 22.9

Caranx crysos 7.9±1.5 29.4±4.8 1.13* 12.1

Chaetodipterus faber 42.7±7.0 27.8±3.1 1.34* 10.8

Lutjanus griseus 5.8±0.9 3.4±0.6 1.06* 5.8

Archosargus probatocephalus 5.2±0.9 6.1±0.9 1.20* 5.1

Balistes capriscus 1.9±0.3 1.5±0.3 1.04* 3.4

2013-2014

64.1%

Mean Diss

2013 2014

Chloroscombrus chrysurus 33.9±9.2 177.2±40.1 1.01* 22.7

Chaetodipterus faber 16.1±2.1 51.5±6.7 1.45* 11.6

Caranx crysos 9.1±1.7 23.7±4.0 1.09* 11.0

Lutjanus griseus 5.7±0.8 4.0±0.8 1.11* 5.7

Archosargus probatocephalus 3.1±0.4 7.6±1.0 1.16* 5.1

Balistes capriscus 0.7±0.1 2.5±0.3 1.11* 3.7

Sand-Mud

62.7%

Mean Diss

Sand Mud

Chloroscombrus chrysurus 200.1±51.5 53.5±14.0 1.06* 24.1

Chaetodipterus faber 57.8±8.6 20.4±2.5 1.42* 11.8

Caranx crysos 12.2±2.1 21.1±3.9 1.14* 10.0

Lutjanus griseus 5.4±1.0 4.2±0.6 1.07* 5.5

Archosargus probatocephalus 6.5±1.2 5.0±0.6 1.14* 4.9

Balistes capriscus 2.0±0.3 1.5±0.3 1.18* 3.3

Note: Results shown are species with Diss/SD ratios > 1, indicating consistent contribution to dissimilarity. Species 

with high dissimilarity, but patchy in their distribution, were excluded. 
65

Table 19. Results of SIMPER pairwise dissimilarities (DISS) analyses for dominant components of 

the fish assemblages observed around small nearshore platforms comparing three levels of 

platform complexity (1=least complex to 3= more complex).

Pairwise

contrast Species Mean MAXNO

Mean 

MAXNO Diss/SD % Diss contribution

Complexity

1-2

61.2%

Mean Diss

1 2

Chloroscombrus chrysurus 75.9±17.7 180.7±75.2 1.05* 25.0

Chaetodipterus faber 35.6±6.0 42.7±8.8 1.31* 11.2

Caranx crysos 15.7±3.1 17.7±5.4 1.12* 10.3

Lutjanus griseus 4.9±0.7 4.7±1.4 1.00* 5.3

Archosargus probatocephalus 6.2±0.9 4.2±0.6 1.08* 4.9

Balistes capriscus 1.9±0.3 1.8±0.3 1.04* 3.2

Complexity

1-3

61.5%

Mean Diss

1 3

Caranx crysos 15.7±3.1 22.0±5.7 1.16* 12.3

Chaetodipterus faber 35.6±6.0 28.3±5.2 1.42* 10.7

Lutjanus griseus 4.9±0.7 4.2±1.2 1.27* 7.1

Archosargus probatocephalus 6.2±0.9 5.9±1.8 1.31* 5.4

Balistes capriscus 1.9±0.3 1.1±0.2 1.04* 3.8

Complexity

2-3

60.1%

Mean Diss

2 3

Chaetodipterus faber 42.7±8.8 28.3±5.2 1.45* 12.0

Caranx crysos 17.7±5.4 22.0±5.7 1.23* 10.7

Lutjanus griseus 4.7±1.4 4.2±1.2 1.21* 6.9

Archosargus probatocephalus 4.2±0.6 5.9±1.8 1.16* 5.5

Balistes capriscus 1.8±0.3 1.1±0.2 1.05* 3.3

Note: Results shown are species with Diss/SD ratios > 1, indicating consistent contribution to dissimilarity. Species 

with high dissimilarity, but patchy in their distribution were excluded. 

Finally, the general trends of inter-annual variation in the fish assemblages described by the SIMPER 

analyses agreed with diver observations. In 2014 we saw higher mean MAXNO relative abundances for 

most species. Interestingly, in 2013 we saw the highest numbers age 1–2 and adult red snapper, gray 

snapper, and lane snapper. Diver detection of YOY red and lane snapper occurred at 42% of platforms 

(selected for diving) in 2013, and 57% of platforms in 2014, with a lot of variability in numbers (tens to 

thousands of fish per platform). Diver detection of YOY gag grouper occurred at 26% of platforms 

(selected for diving) in 2013 and 7% in 2014 where they numbered from one–three fish per platform.

3.5 Discussion

In total, 54 fish species were documented in association with small platforms in the nearshore coastal 

zone, 29 of which included YOY or age 1–2 juveniles. Many of those species are of direct commercial or 

recreational importance and others are significant links in the coastal food web. Eleven fish species 

dominated the coastwide assemblages throughout the two year study, and different relative abundances of 

the core species accounted for most of the variation in the assemblages. Among rarely observed species 

was the goliath grouper, for which mature-sized individuals were observed around small platforms in 

Louisiana waters during both 2013 and 2014. The fish assemblages varied significantly across three 

coastal regions of distinct hydrography and fresh and marine-water mixing. This reflected differences in 

the ways the Mississippi and Atchafalaya rivers interact with coastal circulation driven by winds and 

nearshore bathymetry. The fish assemblages also varied over sandy shoals compared to mud bottoms, 

and in the presence of oxygen stress below 50% saturation. Dissolved oxygen conditions on sandy shoals 

were higher during hypoxic events than surrounding mud habitat, supporting the idea that these features 

may serve as refuges along the coast.

A number of economically important species are associated with nearshore platforms, and platforms are 

regularly used by commercial and recreational fishers and divers to target reef-associated fishes (Ditton et 

al. 1984; Stanley and Wilson 1989, 1990). The 2013 assemblages included species that constitute most of 
66

the non-menhaden, marine finfish commercial and sport fish yields in Louisiana (including all inshore, 

nearshore, and offshore landings both at and away from platforms). The summed commercial and 

recreational harvest of these species for 2013 was ~12,314 metric tons, of which ~73% of the landings 

were harvested recreationally. This amounted to >64% of Louisiana’s total commercial marine finfish 

landings (excluding menhaden), and >60% of Louisiana’s recreational catch (NMFS 2015a). These 

numbers highlight the significant fisheries linked to platforms and their relevance to recreational 

fishermen in particular. Interestingly, the most abundant species observed, Atlantic bumper, and Atlantic 

spadefish are minimally exploited. There is no fishery for the ecologically important forage species 

Atlantic bumper (Shaw and Drulliger 1990), and only recently developed fishery for Atlantic spadefish 

(NMFS 2015a).

Juvenile fishes were highly abundant at small platforms. Age 0, 1, or 2 juveniles, were regularly 

observed for 29 of 54 species including those encountered while diving (Table 7, 8). The most abundant 

among YOY were red and lane snapper, which numbered in the thousands at some small platforms, 

although severe hypoxia seemed to drive the bulk of them from our study sites by August of both summer 

of 2013 and 2014, with a slight rebound in numbers occurring in September after low oxygen subsided. 

Love et al. (2006, 2007) noted the large relative abundance of juvenile fishes at platforms off the 

nearshore Santa Barbara coast of California, including YOY for several species, and reported this as a 

unique attribute setting platforms in their study apart from natural reefs, as well as from the platforms of 

the nGOM. However, observations from this study indicate that small platforms in nearshore waters of 

coastal Louisiana provide a similar nursery function to that observed in California waters.

In addition to serving as habitat for a diversity of juvenile fish species, platforms in East Bay also 

attracted three mature-sized goliath grouper during the peak of Goliath spawning season (Bullock et al. 

1992). Goliath grouper tend to aggregate around high-relief artificial and natural structures during 

spawning season (NMFS 2006; Porch and Eklund 2004; Collins et al. 2015), all of which suggests that 

these fish were aggregating to spawn in this area, although we cannot confirm spawning. Before they 

were overfished, goliath grouper were commonly observed off the Louisiana coast around platforms in 

waters <50 m water depth (Sonnier et al. 1976; Franks 2005). They are now believed to be recovering in 

the nGOM (NMFS 2006; Porch and Eklund 2004; Collins et al. 2015). 

The estuarine nature of nearshore Louisiana is evidenced by the physicochemical characteristics of its 

waters (Chapter 2) and by the apparent nursery role it serves for the diverse assemblage of juvenile fishes 

that occupy it (McHugh 1967; Blabber and Blabber 1980). Most species and life history stages observed 

in this study occurred coast-wide, with the exception of some rare species (such as goliath grouper and 

red lionfish which were only observed in East Bay). Consequently, differences in fish assemblages can 

be attributed to physicochemical differences (salinity, temperature, DO, water clarity, and light 

penetration) throughout the Louisiana nearshore zone. Pritchard (1967) classified estuaries according to 

dominant circulation patterns, but confined his interpretation of estuaries within semi-enclosed basins. 

McHugh (1967) offered a more holistic view, albeit less satisfying in geographic boundary, extending 

estuaries to the outer limits of the coastal shelf receiving freshwater influence. Blabber and Blabber 

(1980) offered important insight, reporting that shelf waters of the tropics may serve many of the roles 

associated with temperate estuaries, and that variables such as turbidity are important in extending the 

nursery function beyond inshore waters.

Within estuarine environments, distributions of marine species and life history stages are influenced by 

tolerances to many physicochemical variables (Remmert, 1983; Baltz et al.1997; Livingston 1988; Baltz 

and Jones 2003), but are particularly sensitive to salinity gradients (Günter 1956). Brackish waters occur 

throughout the Louisiana OCS, but nearshore waters < 18 m deep are influenced well below the surface 

(Chapter 2). However, within this environment, fish habitat is compressed by hypoxia, shrinking the 

vertical water column that is suitable for fishes as DO stress levels exceed tolerances in the lower water 

column (Chapter 4). One effect of this is reduced access to turbid bottom-water refuge for predation-
67

vulnerable benthic-associated species or life history stages, such as YOY red and lane snapper. Because 

patches of low DO are continuously shifting with variation in wind speed and direction, these and other 

site-loyal fishes (Workman et al. 2002) are likely to be forced to stay on the move in response to DO 

gradients that lead to suitably-oxygenated bottom waters.

Intraregional differences in the fish assemblages over sandy shoals may be attributed to a suite of effects. 

Physicochemical differences similar to those among regions occur on a mesoscale over shoals, which 

additionally convey resistance to formation of hypoxia (DiMarco et al. 2010; Chapter 2). Species-specific 

preferences for substrate composition and depth further influence fish distributions. Significant 

PERMANOVA results indicated similar assemblages over sand and mud when hypoxic, but different 

assemblages over mud when well-oxygenated while the assemblages over sand were the same regardless 

of DO levels. This suggests that shoal assemblages are more robust to hypoxic disturbance and exhibit 

greater stability relative to assemblages over surrounding mud-dominated environments. The association 

with sand-dominated sediments by the majority of the core species of the nearshore assemblage further 

suggests that sand shoals are important habitat. Similarities between assemblages around platforms 

overlying sand-dominated sediments and those around platforms in non-hypoxic waters may reflect the 

less frequent and intense influence of DO depletion on shoals and supports the idea that sandy shoals may 

at least periodically serve as refugia for fishes within the hypoxic zone (Chesney and Baltz 2001; Craig 

and Bosman 2013; Reeves 2015).

Some interregional and intraregional effects were likely related. Increased richness in the presence of 

hypoxia in the East region might reflect the fact that the East region has less high-relief shoal area to 

serve as refuge than the West, and Central regions. Evidence for this is the observation that species like 

red drum, black drum, and Southern stingray moved up in the water column around platforms during 

hypoxic events. The greater amount and wider dispersal of high-relief shoal features in the West and 

Central regions offers a more varied setting than in the East region that might favor local avoidance of 

hypoxic waters for some species. This is further supported by the significant positive association between 

higher richness and sandy substrate. 

Though platform complexity significantly affected the fish assemblage structure, its ecological impact 

was not clear. There were no apparent trends in assemblage structure or richness. The marginal 

significance on Shannon-Weiner diversity suggested a reduced ENS with increasing platform complexity 

might reflect the greater dispersal of fishes across the platform, skewing observations toward common 

species. A finer examination of structural complexity might clarify a relationship.

Inter-annual effects were the largest source of variation in the fish distributions for all analyses. Both 

2013 and 2014 were years of high Mississippi-Atchafalaya discharge (Turner and Rabalais 2003; Mead 

and Moody 2010), at ~671 and ~608 km3 yr−1 (Army Corps of Engineers 2015). Altered summer 

circulation throughout the LATEX Shelf result from a shift in prevailing winds, which weaken the 

Louisiana Coastal Current (LCC), and promotes greater freshwater retention in shelf waters (Cochrane 

and Kelly 1986; Dinnel and Wiseman 1986; Hetland et al. 2012). Freshwater outflow from May–August 

2013 was ~297 km3

, when the LCC was weakest (Cochrane and Kelly 1986), compared to ~215 km3

discharged during the same time period in 2014 (Army Corps of Engineers 2015). That represents a 

~28% difference in freshwater discharge influencing the nearshore coastal zone between 2013 and 2014. 

The Atchafalaya fraction of the total discharge was similar between years, at 29.9% and 30% during the 

period from May–August. This hydrographic variability was evident in our sampling as we observed 

significantly lower mean salinities and higher mean temperatures in the Central and East regions in 2013 

than in 2014 (Table 1).

There was a group of fishes that were much greater in abundance at platforms in 2014, and drove regional 

and annual dissimilarity. Several fish species observed around nearshore platforms exhibit early pelagic 

life history stages that associate with ephemeral structure such as Sargassum. The most notable of these 
68

species observed at platforms were blue runner, sergeant major damselfish, Bermuda chub, gray 

triggerfish, and YOY greater amberjack (Dooley 1972; Bortone et al.1977; Wells and Rooker 2004a, 

2004b; Taylor 2015). This group of species may have been associated with a large influx of Sargassum

that was observed throughout the nearshore zone. This occurred through July of 2014 in the Central 

region and parts of the East region west of the Mississippi delta, and through August in the West region. 

In 2013, substantial rafts of living Sargassum were only observed in the West region but not close to the 

magnitude of the 2014 event.

The Gulf has the world’s second largest concentration of Sargassum (Gower et al. 2006; Gower and King 

2011). Sargassum grows in the western Gulf and is advected east by the Loop Current, where some of it 

is delivered to the Atlantic (Gower and King 2008). Loop Current eddies (LCEs) regularly move 

northward, and influence waters on the LATEX shelf (Sturges and Leben 2000), and consequently affect 

the shoreward delivery of offshore water masses (Oey et al. 2005 and references therein), Sargassum

(Zhong et al. 2012), and Sargassum-associated species (Taylor 2015). Within the 50 m isobath, wind 

dominates the velocity of the LCC (Nowlin et al. 2005; Walker 2005), and to a lesser degree, LCC 

interactions with LCEs occur at approximately longitude -92.5° (the boundary separating the West and 

Central regions) and cause additional variability that affects eastward flow (Cho et al. 1998; Nowlin et al. 

2005). Variation in LCE intrusions and the wind-dominated LCC may in part explain the greater 

regularity of Sargassum-associated species observed in the West region and the contrast between the 

summers of 2013–2014 throughout the nearshore zone (particularly in the Central region). It also shows 

that species distributions throughout the nGOM OCS result from complex inshore and offshore origins, 

and that this nearshore environment serves as a different kind of nursery for a variety of fishes.

Since the mid-twentieth century, nearshore Louisiana has been in a state of constant change due to many 

large-scale anthropogenic stressors. The system has proven resilient, owing in part to community-level 

changes in the biota (Chesney et al. 2000; Cowan et al. 2010). Because no previous work has 

documented the fishes associated with small, nearshore platforms in the nGOM, it is impossible to 

determine how these assemblages have changed, although comparisons of assemblages around larger 

platforms in 18–25 m water depths may offer some insights as platform count continues to diminish. The 

construction of 7,147 federally-managed platforms (thousands more exist in state waters) in the nGOM 

from 1942 to 2014 (BOEM 2015) has undoubtedly altered the overall community composition of the 

nGOM (Gallaway and Lewbel 1982; Gallaway and Cole 1998; Krahl 1986; Scarborough-Bull et al. 

2008). As of 2014, there were 2,521 federally-managed platforms (discounting 97 without installation or 

removal date information). This is a dramatic decline from nearly 4,000 platforms in 2006. During the 

course of this study, 23 of the 150 platforms videoed were subsequently removed. We cannot account for 

the potential effect that rapid rig removal has had on the overall reef-fish community. Platform removal 

is a large-scale disturbance to the associated biota, and there is a possibility that the fish distributions we 

observed during this study reflect this disturbance. Numbers of reef and reef-associated fishes in the 

nGOM may decline with continued platform removal (Gallaway and Cole 1998). At a minimum, if 

platforms serve only to attract fishes, then they make good monitoring stations for many species.
69

3.6 Conclusions

Shallow-water platforms in Louisiana’s nearshore zone provide important habitat for many fish species at 

various life history stages. The environment is highly dynamic. Although many of the fishes observed in 

2013–2014 occurred throughout the entire study region, significant shifts in assemblage compositions 

occurred across several sources of variation: regionally, annually, over different sediment types, in the 

presence of hypoxia, and at varying levels of platform complexity.

Large-scale removal of platforms is underway off Louisiana, and plans for nearshore artificial reef 

deployment are under development. The nearshore coastal zone is within navigational depth restrictions 

set by the US Coast Guard that prohibit deployment of unmarked submerged materials. This coastal zone 

is valued by a variety of stakeholders, with potential conflicts of interest, and so careful site selection 

must be a top priority. The vertical relief currently provided by platforms ensures that some level of 

functionality as fish habitat is maintained through even the most severe hypoxic episodes coast-wide. It is 

likely that lower profile artificial reefs will not be as effective throughout the summer months along 

portions of the coastline where hypoxic conditions exceed the vertical dimension of reefed material. 

Sandy shoals along the coast should be considered as candidate sites for deployment due to less pervasive 

DO depletion during the hypoxia-prone summer season. The major shoals across the 10 m contour that 

defines the Atchafalaya shelf, including Tiger and Trinity shoals, the Atchafalaya shoals, and Ship Shoal 

are ideal candidates, of which Ship Shoal is the largest, and most accessible. Additional candidate sites 

worth considering are Sabine Bank off the coast of Cameron and the St. Bernard Shoals, east of the 

Chandeleur Islands.

Unfortunately, the vertical relief provided by platforms probably makes them particularly ecologically 

valuable in locations where it would be impractical to deploy artificial reefs. Just west of the Mississippi 

delta is an area that experiences some of the most severe hypoxia across the coast, and where low-relief 

material might be buried in mud. The higher salinities, lower temperatures, and reduced light levels of 

the midwater and bottom waters due to high surface turbidity also make this region favored by age 1–2 

red and adult red and gray snapper. The only mud-bottom location in this region of the coast where 

artificial reef deployment might be highly effective is East Bay. Bottom waters of East Bay were always 

well-oxygenated, and biofouling of organisms such as soft corals, and the presence of spiny lobster in 

rubble piles at the base of the platforms of East Bay suggest that the hydrodynamics of the bay tend to 

make it resistant to hypoxia development. Another incentive to protect or deploy reef habitat in this area 

is the presence of goliath grouper and the proximity to the fishing port of Venice, Louisiana.
70

4 Habitat Suitability for Fishes Associated Around Small Oil and Gas 

Platforms

4.1 Introduction

The distribution of organisms within the dynamic marine environment of coastal Louisiana’s nearshore 

zone off is driven by a variety of physical and biological factors. Habitat suitability analyses can help to 

define some of these patterns of habitat use in ways that can help managers understand the influence of 

physicochemical variable on fish distributions. For coastal Louisiana temperature, salinity and DO are 

among the most important factors affect the distribution of organisms. DO concentrations play a 

particularly important role controlling the distributions of many fishes in the OCS off Louisiana (Switzer 

et al. 2009). Although tolerances to DO depletion are species-specific, the 2.0 mg l−1 threshold for 

hypoxia has received disproportionate attention in the literature (Breitburg 2002; Vaquer-Sunyer and 

Duarte 2008). For many finfishes, 2.0 mg l−1 is a reliable lethal threshold and a good indicator for 

significant system-wide perturbation (Renaud 1986). Although large fish kills related to low DO are rare 

events in open-water systems (Caddy 1993), low DO (< 50% saturation) can stress fish by restricting 

habitat availability. Many fishes express sub-lethal reactions, such as increased ventilation rates and 

decreased growth at the 50% DO saturation level (Breitburg 2002 and references therein). This level may 

be a more appropriate threshold for behavioral effects and avoidance by fishes than the 2.0 mg l−1

typically used to define hypoxic waters (Breitburg 2002; Eby and Crowder 2002; Craig and Crowder 

2005; Prince and Goodyear 2006). With this in mind, we examined the summertime responses of 

platform-associated fishes to DO <50% saturation (~3.0–3.5 mg l−1 across observed salinities, 

temperatures, and pressures).

Other aspects of eutrophication that can affect fish and invertebrate health are dissolved gases that can 

supersaturate coastal waters due to the primary production of surface algae blooms (Gorham 1899; 

Landsberg 2002 and references therein). Supersaturation of the atmospheric gases nitrogen and oxygen 

can cause gas bubble disease (GBD) in fish (Marsh and Gorham 1905). Gas-supersaturated environments 

can cause diffusion of gases into body tissues, which can cause internal and external lesions throughout a 

fish’s body, disrupt buoyancy control, and, if persistent, can fatally reduce circulation. Lethality is 

primarily a concern in aquaculture settings, and below dams in streams, where bubble injection 

supersaturates shallow environments with nitrogen. Nitrogen has a more potent effect than oxygen 

supersaturation (Nebeker et al. 1978), although total gas pressure is the most important factor controlling 

effects (Colt 1983). Nevertheless, many organisms respond negatively to oxygen supersaturation 

(Nebeker et al. 1978). Because subtropical waters are naturally slightly supersaturated with nitrogen 

(Emerson et al. 1995), total gas pressure is often high in surface waters, a situation that could amplify the 

effects of photosynthetically derived oxygen supersaturation (Crunkilton et al. 1980). However, variation 

in total gas pressure throughout surface waters of the nGOM has not been documented.

Another complicating feature of Louisiana’s outer continental shelf that can influence fish distributions is 

the network of oil and gas platforms (platforms) extends from the bays and marshes outward past the 

continental shelf. A unique aspect of platforms as fish and invertebrate habitat is the vertical hard 

substrate that extends from the seafloor to above the sea surface. This aspect of platforms was best 

expressed by Gallaway and Cole (1998), who stated: “It may be more ecologically accurate to consider 

platform reefs as new and distinct habitat rather than to assume that they are merely additions to existing 

reef systems”. Platforms occupy the upper photic zone, and, in light of the potentially steep vertical 

hydrographic gradients within the waters they occupy, platforms may be viewed as complementary 

features to a region wherein natural reefs are not only rare, but often inaccessible when DO levels fall 

below suitable concentrations.
71

Though many species are able to migrate horizontally to oxygenated areas in response to hypoxia 

(Switzer et al. 2006; Switzer et al. 2009), many demersal and pelagic species first move up in the water 

column where more suitable DO conditions exist (Rabalais et al. 2001; Stanley and Wilson 2004). This 

behavior is difficult to observe and document but the aggregating effects of platforms make it possible to 

document. Thus when suitable conditions for reef-associated species exist in areas with platforms when 

hypoxia is present, those same areas might not provide suitable without the vertical relief that platforms 

provide. However, vertical movement in the water column in response to one environmental variable can 

also result in less favorable conditions for other variables. For example, a fish moving up in response to 

hypoxia might find itself in significantly fresher, warmer waters than it would otherwise select but 

tolerates those conditions rather than moving to an alternative area (Prince and Goodyear 2006). This 

could result in eventual movement of fishes away from the platform in search of more suitable habitat, or 

it might tolerate the less favorable conditions higher in the water column and remain associated with the 

platform. Reasons to stay include shelter and available prey on the upper portion of the platforms. 

Whatever the case, at the least, platforms facilitate study of behaviors in response to environmental 

variable because they aggregate large numbers of reef-associated species that would otherwise be far 

more difficult to observe and might be at dramatically lower densities at sites without platforms, but 

within the hypoxic region.

Responses of mobile fishes to oxygen can be complicated but platforms provided a unique opportunity to 

study them because they act as FADs. While many aspects of hypoxia have been well studied, coincident 

responses of fishes throughout the water column have received relatively little attention (Stanley and 

Wilson 2004). Subsequently, impacts of hypoxia on pelagic species have also been understudied 

(Chesney et al. 2000; Craig and Bosman 2013; Zhang et al. 2009, 2014). More generally, fish responses 

to environmental variation in stratified waters have not been investigated with respect to water-column 

layering and the total availability of suitable physicochemical conditions within each water-column layer 

(layer). This is an important perspective given the dominant influence that physicochemical properties 

play in driving estuarine fish distributions (Baltz et al. 1997). Assemblage compositions in this setting 

are, therefore, likely to reflect interwoven distributions of individual species (Remmert 1983) or life stage 

tolerances to many variables within a complex environment (Livingston 1988; Baltz and Jones 2003). 

This is particularly relevant to the study of fishes in the dynamic and highly productive estuarine 

nearshore nGOM. The objectives of this chapter of the 2013-2014 studies were to 1) assess speciesspecific responses to physicochemical drivers using habitat suitability indices (HSI) and generalized 

linear modeling (GLM), 2) evaluate the effect of hypoxia on species-specific habitat selection, and 3) 

explore some of the potential consequences of displacement in a eutrophic and highly-stratified 

environment.

4.2 Field Methods

Figure 25 shows the location of platforms that has both hydrographic data and useable video that could be 

used for habitat suitability analyses. For the details of the field sampling, see Chapter 2. 

In 2013–2014, 343 sites were sampled, which included 150 unique platforms with video usable for 

analyzing fish assemblages. Of the total platforms with usable video, 65 were obtained in 2013, and 85 in 

2014. Also, 84 of the videos were recorded in the absence of hypoxia while 66 were recorded in the 

presence of hypoxia (DO <50% saturation).
72

4.2.1 Video Processing

For a detailed description of the video processing methods see Chapter 3 (3.2.1Video processing). 

Figure 25. Location of all platform sampling sites with usable video and hydrographic data (n = 150) that 

were included in the habitat suitability analyses.

4.2.2 Statistical Analyses

The extent of habitat restriction from avoidance of the hypoxic layers and supersaturated surface waters 

was evaluated regionally across the coast, as well as by year and dominant sediment type. A three-way 

ANCOVA compared region, year, and dominant sediment type, and included a covariate for depth that 

accounted for the relative consistency in extent of the surface layer relative to total depth (SAS 9.4 Proc 

GLIMMIX). Tukey-Kramer post-hoc adjustments were applied to each ANCOVA to determine 

significant pairwise differences between least-squares means under multiple comparisons.

Species-specific responses to physicochemical conditions were evaluated for 11 species. Mixed GLMs 

were used to predict relative abundances of each species using five environmental variables and the 

presence or absence of hypoxia, while including a covariate to adjust for effort. Year was included as a 

categorical response variable and the presence of hypoxia (DO <50% saturation) was included as a binary 

covariate. Salinity, temperature, DO, depth, and Secchi depth, and their interactions with one another, as 

well as with the presence of hypoxia, were included as continuous covariates. Readings for each distinct 

layer of the water column were modeled without artificially inflating the degrees of freedom (Hurlbert 

1984) by using a repeated statement that blocked clusters of layers by platform nested within year 

(Breslow and Day 1980). Additionally, denominator degrees of freedom were conservatively downscaled 

by fixing them at 126 for each term in the model, despite the repeated blocking structure. Relative 

abundance distributions for each species approached normality when fit with a lognormal distribution 

(SAS 9.4, PROC GLIMMIX). All other assumptions were met, and there was no indication of 

multicollinearity among environmental variables.
73

4.2.3 Habitat Suitability Analyses

Microhabitat and habitat suitability analyses explored fine-scale species-specific responses of fishes 

occupying the nearshore zone of the nGOM using the video and hydrographic data around 150 

independent platforms. Analyses focused on 26 species that were reliably detected on video (Chapter 3), 

with detailed evaluation of 11 species that composed ~93% of the total number of fishes observed and 

were responsible for driving all of the consistent assemblage dissimilarities in prior analyses (Chapter 3). 

These species included: Atlantic bumper (Chloroscombrus chrysurus; ~56%), Atlantic spadefish 

(Chaetodipterus faber; ~18%), blue runner (Caranx crysos; ~9%), bluefish (Pomatomus saltatrix; ~4%), 

sheepshead (Archosargus probatocephalus; ~3%), gray snapper (Lutjanus griseus; ~2%), sergeant major 

damselfish (Abudefduf saxatilis; ~1%), Bermuda chub (Kyphosus sectatrix; < 1%), young-of-the-year 

(YOY) greater amberjack (Seriola dumerili; <1%), gray triggerfish (Balistes capriscus; <1%), and adult 

red snapper (L. campechanus; <1%). High variation along environmental gradients throughout the water 

column required partitioning of distinct layers for each hydrographic profile. Pairing video and 

hydrographic data allowed a fine-scaled resolution of water quality and fish distributions to explore 

potential shifts in patterns of habitat use in response to physicochemical variables including DO (i.e., 

hypoxia) (Switzer et al. 2009, 2015). The analyses specifically addressed differences in selection that 

occurred when fishes moved up around platforms (Rabalais et al. 2001; Chesney and Baltz 2001; Stanley 

and Wilson 2004).

The water-column structure around nearshore platforms was complex. Salinity, temperature, and DO 

were plotted by depth for all hydrographic profiles, and all major and minor haloclines, thermoclines, and 

oxyclines were identified. This approach partitioned the water column into two to eight distinct layers. 

Within each layer, environmental variation was minimal, and salinity, temperature, and DO accurately 

characterized any point within the layer, for a total of 684 layers of varying vertical extent. Due to 

variation in layering in the water columns at different platforms, distributions across gradients of 

environmental variables were described using an approach that accounted for variation in hydrographic 

variables and the vertical extent contributed by each respective layer.

Patterns of habitat use were described by weighted occurrence based on relative abundance estimates of 

fishes in each water column strata (MAXNOs). Data from layers that were completely avoided by fishes 

were eliminated from habitat use calculations. Also, because MAXNO counts could not be taken from 

each layer individually without potentially double counting individuals of each species, equal use was 

assumed for all layers in the water column which were not clearly being avoided by fishes and 

hydrographic variables that occupied a larger portion of the water column were weighted according to 

their vertical extent. Weightings were calculated by multiplying MAXNOs for each platform by the 

fraction of each water column that each layer represented.

Factor analysis was used to resolve six physicochemical variables into four factors. A varimax rotation 

was used to scale orthogonal, multivariate factors relative to one another, and create a three-dimensional 

environmental space useful for comparing trends in the species-specific distributions relative to water 

quality. Factor centroids were weighted by abundances for 26 species present throughout the water 

column, and plotted as bubbles representing two standard error radii around the centroid means. Nonoverlapping error bubbles suggested significant differences in habitat selection by each fish species 

relative to the others. Species-specific shifts in habitat selection were also shown for fishes in the 

presence of hypoxia.

Habitat suitability indices (HSI) evaluate habitat use patterns for a variable relative to the pattern of 

availability for the same variable or resource (Bovee 1982). This information can be used to characterize

patterns of habitat selection, or resource use, and species-specific environmental responses (Baltz 1990; 

Switzer et al. 2009). To describe resource availability, environmental data for each variable were 
74

partitioned by intervals chosen to create the smoothest frequency curves possible. Habitat suitability (S) 

was calculated within each interval following:

S = P(E│F) / P(E) where P(E│F) is the relative frequency of occurrence within each interval across an 

environmental gradient coinciding with the observed presence of the species of interest, and P(E) is the 

relative frequency of occurrence of each interval (along that environmental gradient) across all platform 

study sites (Baltz 1990). Raw suitability was standardized by dividing each interval value by the greatest 

suitability value for a given distribution such that the optimal suitability value became one while zero 

indicated unsuitable conditions based on this dataset.

Habitat suitability curves were constructed for the 11 most abundant species for each of five 

environmental gradients (salinity, temperature, DO, Secchi depth, and total depth). Availabilities were 

calculated based on the summed extent (m) of the water column occupied by each variable across all 

platforms. Habitat use was then calculated for each species individually based on the summed extent (m) 

of the water column occupied by each variable after excluding layers of avoidance (Figure 26). Relative 

abundances for each species were used to weigh use by multiplying the count for each species by the 

fraction of total usable habitat within each layer in the water column. This provided a conservative 

microhabitat analysis (Baltz et al. 1993; Hurlbert 1981) of species-specific habitat suitability within a 

compressed water column that reflected weighted use patterns and described species responses along each 

environmental gradient.

Figure 26. Scaled photo-collage of the fishes and the submerged structure of platform ST 21-GC plotted with 

salinity, temperature, depth, and DO profiles show fish distribution relative to water quality and 

water quality strata ranging from supersaturated to hypoxic. 

Grey dots in Figure 26 show individual YSI readings. Red lines indicate partitioned layers of the water 

column within which environmental readings were assumed to be constant in the analyses. Pink and 

green shading indicate layers of avoidance while unshaded layers were used by fishes. Note: Fishes 

present in images within the shaded layers of Figure 26 were following the camera array into low oxygen 

waters.
75

4.3 Results

Video observation confirmed DO <50% saturation is a threshold for avoidance by fishes for all species 

observed in nearshore Louisiana waters at platforms (see Table 7 and 8 for a complete list). This included 

the small, cryptic species we regularly observed while diving (Table 7, 8), among which were young-ofthe-year red and lane snapper (Figure 27). Sheepshead (Archosargus probatocephalus) and, to a lesser 

extent, gray snapper (Lutjanus griseus) were regularly observed in waters with DO <50% saturation; 

however, in these cases fish were usually alone and MAXNOs were never obtained from this portion of 

the water column.

When stratified surface blooms were present (n = 44) fishes also avoided the surface layer. This surface 

layer was characterized by supersaturated DO as well as lower salinities, higher temperatures, and higher 

turbidities relative to underlying waters. Species that typically occupied the more structurally-complex 

platform staging near the surface, such as Bermuda chub and sergeant major damselfish, also moved 

down in the water column when turbid surface blooms occurred. The mean DO within a surface bloom 

was 140.69% saturation ± 6.96 (95% CI), or ~9.67 mg l−1, and presumably DO drove the avoidance

behavior. The corresponding mean Secchi disk reading associated with bloom waters was 1.61 m ± 0.20 

(95% CI), and mean surface bloom extent was 3.53 m ± 0.34 (95% CI) below the surface. Significant 

differences in Figure 27A occurred between groups not sharing a letter.

Figure 27. Pairwise comparisons of the vertical extent the fraction of the nearshore water column is used by 

fishes (A) for all hypoxic sites (n = 64) plotted by region (West, Central, and East), year (2013 and 

2014), and dominant sediment type (sand or mud) with an example of young-of-the-year red and lane 

snapper up in the water column at a nearshore platform in response to hypoxic conditions (B). 

A benefit of deploying un-baited video arrays is that it provided the opportunity to observe the behavior 

of organisms in their environment that was not influenced by bait or a motorized ROV. In one interesting 

video, habitat compression of bloom waters supersaturated to 172% restricted Spanish mackerel 

(Scomberomorus maculatus), blue runner, Atlantic bumper, cobia (Rachycentron canadum), red and 

black drum (Sciaenops ocellatus and Pogonias cromis), and age 1–2 juvenile red snapper to within 3.5 m 

of the well-oxygenated seafloor in a 9 m water column. Predictably the pelagic species appeared to be 

working the lower edge of the bloom layer (a common behavior), presumably feeding on zooplankton, 

when a school of red drum moved through in apparent pursuit of the compressed, and exploitable Atlantic 

bumper. A more common observation was YOY lane and red snapper displaced from their usual bottom 

habitat use, where they would feed in the current to higher in the water column (Figure 27B). 

Additionally, fishes were regularly observed entering waters <50% saturation, either following the 

camera array or possibly as part of a short foraging event. Sheepshead and, to a lesser extent, gray 

snapper were frequently observed in low DO waters; however, MAXNO counts for sheepshead always 

occurred above 50% DO saturation. Vertical displacement of other benthic fishes, including Southern 
76

stingray (Dasyatis americana) and red and black drum, were also observed as high as 4.7, 3.7, and 3.7 m 

above the seabed, over highly turbid, low DO bottom waters into waters of ≥50% DO saturation.

4.3.1 Statistical Results

The extent of habitat restriction from hypoxia and surface bloom-associated compression varied across 

nearshore Louisiana. The three-way ANCOVA indicated dominant sediment type, depth, and the 

interaction between region and year were statistically significant (P = 0.0174, < 0.0001, and 0.0002; 

Table 21). Pairwise comparison indicated a greater degree of compression in the East region than in the 

West or Central regions (see Figure 25 for regions), greater overall compression during 2014 sampling, 

and greater habitat restriction over muddy sediments than over sand (Figure 27A).

There were regions of the coast where high turbidity throughout the water column consistently precluded 

effective video sampling. The mouth of Atchafalaya Bay and west across Tiger Shoal was consistently 

too turbid for video or diver observations of fish assemblages. However, review of the water-quality data 

of this area did provide an indication based on fish distributions across the rest of the coast that this area is 

probably of relatively poorer quality for many nearshore platform-associated species. Hypoxia was not 

particularly extensive in this area, but there were hypoxic patches underlying supersaturated conditions 

that jointly occupied the entire water column (Figure 28). Figure 28 shows an instance where, 

interestingly, waters with supersaturated DO were within <1 m of anoxic waters (DO <1.0 mg l−1

).

Results from the GLM analyses indicated the significant physicochemical variables fishes responded to 

within the water column while accounting for restricted use due to avoidance of surface bloom conditions 

and bottom-water DO depletion, after controlling for year and effort (Table 22). Significant interaction 

terms between hypoxia and other environmental variables indicated a significant shift in habitat use in the 

presence of hypoxia to one or more environmental variables for every species, while holding all other 

variables in the model constant. From this it was determined to which physicochemical variable(s) each 

species was responding.

Table 20. Three-way ANCOVA for type III fixed effects of region, year, and dominant sediment 

type (Sed) effects on the extent of habitat restriction to fishes, controlling for depth. 

Variable Num DF Den DF F P

Region 2 121 6.75 0.0017

Year 1 121 10.40 0.0016

Sediment type 1 121 5.81 0.0174*

Depth 1 121 26.65 < 

0.0001*

Region x Year 2 121 8.92 0.0002*

Region x Sed 2 121 1.09 0.3404

Year x Sed 1 121 3.13 0.0796

Region x Year x Sed 1 121 0.03 0.8579

Asterisks (*) indicate significance of interpretable variables.
77

Table 21. Results of a mixed generalized linear model for the physicochemical responses of the 

11 species making up the dominant fish assemblages around small nearshore platforms. 

Environmental

Variable

C. chrysurus

n = 17,261

C. faber

n = 5,418

C. crysos

n = 2,605

P. saltatrix

n = 1,240

A. probatocephalus

n = 840

L. griseus

n = 708

A. saxatilis

n = 414

K. sectatrix

n = 295

S. dumerili

n = 263

B. capriscus

n = 254

L. campechanus

n = 252

Salinity F

P

0.02

0.881

8.78

0.004

0.00

0.956

2.00

0.160

4.23

0.042

0.48

0.492

8.78

0.004

4.02

0.047

0.81

0.371

0.25

0.620

0.31

0.580

Temp F

P

1.09

0.299

3.26

0.074

0.01

0.907

1.50

0.222

3.01

0.085

0.02

0.876

3.26

0.074

1.53

0.219

0.31

0.576

2.19

0.141

0.32

0.575

DO F

P

0.02

0.875

1.13

0.074

0.02

0.875

0.00

0.972

0.23

0.635

0.72

0.398

1.13

0.290

0.13

0.721

0.00

0.982

0.86

0.356

0.91

0.342

Depth F

P

8.43

0.004

3.88

0.290

0.26

0.614

1.73

0.191

8.39

0.005

1.13

0.290

3.88

0.051

1.64

0.203

14.85

<0.001

4.01

0.048

0.00

0.980

Secchi F

P

7.16

0.008

3.41

0.067

0.12

0.727

0.06

0.810

0.00

0.981

0.49

0.486

3.41

0.067

0.37

0.542

1.31

0.254

0.70

0.406

16.71

<0.001

Hypoxia F

P

12.42

0.001

0.00

0.981

0.55

0.461

0.13

0.718

0.92

0.339

5.67

0.019

0.00

0.981

0.82

0.367

5.60

0.020

0.24

0.626

3.87

0.051

Year F

P

33.33*

<0.001

16.11*

<0.001

2.98

0.087

1.14

0.288

27.28

<0.001

25.28*

<0.001

16.11*

<0.001

12.07*

0.001

2.25

0.136

6.22*

0.014

3.42

0.067

Effort F

P

0.98

0.324

0.09

0.762

1.25

0.266

0.79

0.376

3.94*

0.049

8.46*

0.004

0.09

0.762

0.03

0.856

2.08

0.152

0.09

0.770

7.49*

0.007

Note: Analyses were based on 684 water column layers at 150 platforms. Hypoxia was defined as bottom DO < 50% 

saturation (n = 64). Degrees of freedom were fixed at 126 for all analyses. F=f values and P= p Values. Asterisks (*) 

indicate highly significant variables.
78

Table 22. Results of a mixed generalized linear model for the physicochemical responses of the 

11 species making up the dominant fish assemblages around small nearshore platforms.

Environmental

Variables

C. chrysurus

n = 17,261

C. faber

n = 5,418

C. crysos

n = 2,605

P. saltatrix

n = 1,240

A. probatocephalus

n = 840

L. griseus

n = 708

A. saxatilis

n = 414

K. sectatrix

n = 295

S. dumerili

n = 263

B. capriscus

n = 254

L. campechanus

n = 252

Salinity x F

Temp. P

0.28

0.599

5.18*

0.025

0.05

0.829

1.12

0.292

1.32

0.253

0.38

0.539

5.18*

0.025

5.63*

0.019

2.28

0.134

0.17

0.683

0.36

0.548

Salinity x F

DO P

0.08

0.775

1.60

0.208

0.75

0.387

0.02

0.901

0.11

0.739

1.12

0.291

1.60

0.208

0.05

0.823

0.34

0.560

0.06

0.813

0.16

0.693

Salinity x F

Depth P

0.58

0.446

14.50*

<0.001

0.28

0.595

1.12

0.291

9.40*

0.003

0.57

0.452

14.50*

<0.001

2.30

0.132

15.23*

<0.001

0.04

0.837

0.23

0.635

Salinity x F

Secchi P

4.09*

0.045

9.81*

0.002

0.82

0.367

5.69*

0.019

4.43*

0.037

0.38

0.536

9.81*

0.002

0.05

0.826

0.05

0.825

0.74

0.392

0.03

0.863

Temp. x F

DO P

0.16

0.693

1.43

0.235

0.01

0.940

0.06

0.807

0.16

0.685

1.54

0.217

1.43

0.235

0.00

0.959

0.07

0.790

0.59

0.443

0.54

0.465

Temp x F

Depth P

11.25*

0.001

0.45

0.503

0.36

0.549

1.64

0.203

4.92*

0.028

0.65

0.421

0.45

0.503

0.50

0.480

9.91*

0.002

8.22*

0.005

0.42

0.519

Temp. x F

Secchi P

9.41*

0.003

0.05

0.818

0.23

0.633

0.11

0.741

4.44*

0.037

0.68

0.411

0.05

0.818

1.10

0.295

2.02

0.158

7.00*

0.009

25.7*

<0.001

DO x F

Depth P

0.06

0.807

9.59*

0.002

0.87

0.353

0.51

0.476

0.89

0.347

2.45

0.120

9.59*

0.002

2.19

0.142

0.16

0.694

0.73

0.395

0.09

0.767

DO x F

Secchi P

2.42

0.122

15.93*

<0.001

0.71

0.400

1.75

0.188

15.65*

<0.001

0.25

0.615

15.93*

<0.001

0.07

0.786

1.54

0.216

7.27*

0.008

6.78*

0.010

Depth x F

Secchi P

19.90*

<0.001

1.66

0.200

0.96

0.330

10.16*

0.002

5.98*

0.016

3.848

0.052

1.66

0.200

0.27

0.608

0.13

0.723

2.80

0.097

3.90*

0.051

Salinity x F

Hypoxia P

0.77

0.382

0.99

0.323

0.15

0.701

0.30

0.585

1.85

0.177

2.25

0.136

0.99

0.323

1.07

0.303

7.70*

0.006

3.90*

0.051

3.43

0.067

Temp. x F

Hypoxia P

25.89*

<0.001

1.57

0.212

0.23

0.635

0.96

0.328

0.08

0.779

9.09*

0.003

1.57

0.212

0.36

0.550

3.74~

0.055

0.76

0.385

0.80

0.373

DO x F

Hypoxia P

8.05*

0.005

4.34*

0.039

0.03

0.861

0.31

0.577

2.48

0.118

1.77

0.185

4.34*

0.039

1.77

0.186

1.92

0.168

7.70*

0.006

4.31*

0.040

Depth x F

Hypoxia P

0.56

0.455

0.06

0.808

11.39*

0.001

0.36

0.552

4.70*

0.032

0.07

0.787

0.06

0.808

4.04*

0.047

2.00

0.160

2.44

0.121

3.43

0.067

Secchi x F

Hypoxia P

9.26*

0.003

6.44*

0.012

4.35*

0.039

8.38*

0.005

0.65

0.423

25.14*

<0.001

6.44*

0.012

0.17

0.680

1.05

0.307

4.15*

0.044

6.58*

0.012

Note: Analyses were based on 684 water column layers at 150 platforms. Hypoxia is defined as bottom DO < 50% 

saturation (n = 64). Degrees of freedom were fixed at 126 for all analyses. F=F values and P= p Values. Asterisks (*) 

indicate highly significant variables. 
79

Figure 28. An example of extreme vertical compression of suitable fish habitat around a nearshore platform 

where the entire water column is either oxygen supersaturated or hypoxic except for one small layer 

between 5 and 6 m below the surface. 

This may be an example of a water column which may be totally avoided by fishes. The thin layer of 

conceivably usable habitat might serve as a corridor for nekton. This profile was recorded on July 29, 

2013 at platform SMI 240-196. The site location is indicated by the red star in Figure 25 near the outlet 

of the Atchafalaya River. 

4.3.2 Habitat Suitability Analyses

The factor analysis resolved six variables into four factors that together explained 90.7% of the 

environmental variation (Table 24). Factor 1 included increasing DO and decreasing salinity, and was 

interpreted as the primary stratification factor. Factor 2 included increasing Secchi depth and increasing 

temperature, which was interpreted as the secondary stratification factor. Factor 3 was simply depth, and 

Factor 4 was simply the extent of habitat restriction from hypoxia and bloom avoidance. Factors 3 and 4 

had identical Eigenvalues, thus explaining the same proportion of the cumulative variance, and are 

interchangeable for interpretations when plotted against Factors 1 and 2 in three dimensions, (in which 

case a cumulative 72.7% of the total variance would be explained) (Figure 29).

Microhabitat use patterns for each species in the presence and absence of hypoxia were represented in 

three-dimensional environmental space (Figure 29) by plotting the centroid means for each species in the 

presence and absence of hypoxia. Position of the weighted centroid means indicated ways in which 

nearshore platform-associated fish distributions varied with regard to the six physicochemical variables 

included in the four factors. Most species distributions occurred in significantly different 

physicochemical conditions at platforms in waters ≥ 50% DO saturation compared to those at platforms in 

< 50% DO saturation. In many cases the separation in habitat use was greater between the presence and 

absence of hypoxia than for interspecies separation. The general trend for the fish assemblages was a 

reduced Factor 1 loading, and increased Factor 3 and 4 loadings.
80

Table 23. Results of a rotated factor loadings of 6 environmental variables measured during 

coastal surveys around small platforms throughout the nearshore zone off Louisiana.

Environmental variable Factor 1 Factor 2 Factor 3 Factor 4

DO 0.91 −0.06 0.07 −0.26

Salinity −0.87 −0.11 0.21 −0.22

Secchi −0.22 0.86 0.06 −0.34

Temperature 0.48 0.78 −0.23 0.05

Depth −0.08 −0.06 0.94 0.25

Restriction −0.04 −0.21 0.30 0.89

Eigenvalue 1.86 1.42 1.08 1.08

Proportion of variance explained 31.1 23.7 18 18

Cumulative variance explained 31.1 54.7 72.7 90.7

Note: The sign of each loading indicates whether variables are increasing or decreasing, while the magnitude 

indicates the strength of contribution to each factor. Underlines indicate the loadings used to guide interpretations 

about the system as described by these variables. 

Figure 29. Microhabitat plot of centroid means (bubbles ±2SEs) describing the environmental use patterns of 

26 species relative to three principal component factors for hypoxic (DO > 50% saturation) (red) and 

not hypoxic (blue) water columns. 
81

The HSI plots show the magnitude of change in environmental selection given the presence and absence 

of hypoxia occurring within the patchy nearshore part of the hypoxic zone without modeling other effects. 

Availability is expressed in meters, and reflects the vertical extent of all 684 layers. In many cases, 

habitat selected in the presence of hypoxia differed from that selected in the absence of hypoxia; however, 

the range of tolerance for all of these species were wide (Figures 30–34). The third line represents overall 

suitability within the hypoxic zone, and is interesting for comparison to other studies in the nGOM where 

similar species occur, but are not influenced by an 18,000 km3 region of shifting DO concentrations. For 

example, changes in habitat selection for red snapper indicated an optimal suitability shift in the presence 

of hypoxia of −8 psu salinity, +4 °C temperature, +15% DO saturation, +2 m total depth, and +3 m Secchi 

depth. Interestingly red snapper selected habitat of higher DO content at platforms in hypoxic waters than 

at platforms in non-hypoxic waters, as evidenced by both GLM and HSI results (Table 4.2; Figure 32).
82

Note: Overall suitability is described by double solid lines, while single solid lines reflect responses at non-hypoxic 

sites, and broken lines reflect responses at hypoxic sites. Availability is shown in the upper left.

Figure 30. Standardized suitability (SS) for the responses to salinity of 11 fish species observed around 

small nearshore platforms.
83

Note: Overall suitability is described by double solid lines, while single solid lines reflect responses at non-hypoxic 

sites, and broken lines reflect responses at hypoxic sites. Availability is shown in the upper left.

Figure 31. Standardized suitability (SS) for the responses to temperature of 11 fish species observed around 

small nearshore platforms.
84

Note: Overall suitability is described by double solid lines, while single solid lines reflect responses at non-hypoxic 

sites, and broken lines reflect responses at hypoxic sites. Availability is shown in the upper left.

Figure 32. Standardized suitability (SS) for the responses to DO of 11 fish species observed around small 

nearshore platforms.
85

Note: Overall suitability is described by double solid lines, while single solid lines reflect responses at non-hypoxic 

sites, and broken lines reflect responses at hypoxic sites. Availability is shown in the upper left.

Figure 33. Standardized suitability (SS) for the responses to water depth of 11 fish species observed around 

small nearshore platforms. 
86

Note: Overall suitability is described by double solid lines, while single solid lines reflect responses at non-hypoxic 

sites, and broken lines reflect responses at hypoxic sites. Availability is shown in the upper left.

Figure 34. Standardized suitability (SS) for the responses to secchi depth of 11 fish species observed 

around small nearshore platforms. 
87

4.4 Discussion

One perspective on the sustainability of fisheries within the hypoxic region of the nGOM and apparent 

absence of any negative effects on fishing is that degradation of suitable habitat has not been severe 

enough to limit populations or that the negative effects are overcome by the positive effects of high 

primary and secondary productivity (Chesney and Baltz 2001, Breitburg et al. 2009). While suitability 

varies by degree, even the most severely restricted waters sampled during this study (that had acceptable 

visibility) were being used by fishes. However, avoidance of hypoxic bottom waters and surface blooms 

significantly influenced habitat selection patterns and probably the distributions for the most common 

platform-associated fishes. If suitable habitat does not become limiting, there may be competition for the 

narrow layers of high-quality habitat conditions when habitat compression is widespread for a large part 

of the year.

Avoidance of portions of the water column <50% DO saturation showed that a higher standard for 

hypoxia is relevant to fishes rather than the widely applied 2.0 mg l−1 level. Although some fishes were 

observed in waters <50% DO saturation, MAXNO counts were never observed in such cases. This 

behavior is consistent with previously observed forays into hypoxic water for feeding (Pihl et al. 1991), 

and suggests a greater tolerance to DO depletion for species such as sheepshead and gray snapper, 

although MAXNOs for all species were always obtained in water with DO ≥50% saturation.

Avoidance of surface blooms by fishes around some platforms was an unexpected finding that we cannot 

attribute solely to the observed oxygen supersaturation of surface waters around those platforms. The 

videos revealed that fishes often avoided the surface bloom layer despite suitable salinities, temperatures, 

and water clarity. Both GBD (from photosynthetically derived oxygen supersaturated waters) and 

harmful algal blooms (HABs) have resulted in large-scale fish kills in freshwater and open estuarine 

environments (Woodbury 1942 Renfro 1963; Landsberg 2002 and references therein). Renfro (1963) 

reported a fish kill in Galveston Bay during 1959 of more than 300 adult spotted seatrout (Cynoscion 

nebulosus), many Atlantic croaker (Micropogonias undulatus), various eels, and other fishes. He 

attributed the kill to a photosynthetically-derived oxygen supersaturation level of 250%. Though 

uncommon, we observed values upward of 295% in nearshore waters of coastal Louisiana. Although we 

did not observe them, harmful algal species cannot be ruled out as well. There are 24 harmful algal 

species known to occur in Louisiana waters (Dortch et al. 1999). Dinoflagellates are one of the primary 

taxon contributing to HABs. Dinoflagellates thrive in high-nutrient, silica-limited, and stratified 

environments, such as coastal Louisiana, where the Redfield Ratio (Redfield 1958) of silicon to inorganic 

nitrogen falls below 1:1 (Officer and Ryther 1980). This is a condition that coastal Louisiana is 

approaching due to disproportionate nitrogen loading from the Mississippi River (Justić et al. 1995; 

Rabalais et al. 1996; Turner et al. 1998). Nevertheless, similarly to hypoxia, fish kills due to GBD and 

HABS are rare events in natural environments. This is due to lateral avoidance by fishes, or by sounding 

(moving down), reactions documented previously at levels of ~125% gas saturation in the case of GBD 

(Gray and Haynes 1977; Nebeker et al. 1978; Chamberlain et al. 1980; Parker et al. 1984). The sub-lethal 

direct and indirect effects of habitat displacement due to avoidance of low or high DO stress or other 

surface bloom conditions have the greater overall impact. A greater understanding of the responses of 

fishes to high and low oxygen stress is needed to understand the distribution of the fish community and 

their responses to these extremes. Although we cannot rule out HABs influencing fish distributions 

within the surface blooms, HABS are not as common in coastal waters off Louisiana as other parts of the 

Gulf (Dortch et al. 1999). Thus it seems more likely that the regular avoidance behavior observed in this 

study is related to gas supersaturation than to the presence of HABs. 
88

Elliott and Quintino (2007) described the difficulty of unraveling the influence of anthropogenic stressors 

on estuarine communities well-adapted to cope with stress, as the “estuarine quality paradox”. The 

highly-structured nature of the water column is an underappreciated hydrographic feature that can 

strongly influence the distribution of organisms. Our studies show that vertical habitat compression 

within a stratified water column can reduce suitable habitat area and quality, and ultimately drive fishes 

from an area when tolerances to other physicochemical variables are exceeded. The interaction between 

habitat availability within a stratified water column and DO depletion may, therefore, be a major driver 

for fishes living within the hypoxic zone off Louisiana. These interactions can be complex, as for red 

snapper, which selected significantly higher DO concentrations faced with the presence of hypoxia. This 

might reflect the strong benthic association of red snapper and a reluctance to move until critical oxygen 

tension is approached or exceeded, as has been observed for red bream, Pargus auratus (Cook et al. 

2011).

Hazen et al. (2009) used trawling and acoustics in Louisiana’s nearshore zone and estimated that habitat 

restriction due to hypoxia typically affected <15% of the total water column. Their estimates are 

somewhat limited and based on 1.6 km bottom trawls paired with acoustics. Physicochemical data were 

collected before and after each trawl, and backscatter above the trawl depth was unidentifiable. Because 

our sampling was based on discrete points with paired video and continuous water quality profiles with a 

mean reading every 0.08 m ± 0.0074 m (95% CI), we were able to determine what portions of the water 

column species were using more accurately. We were also able to determine species-specific selection 

patterns within a variable water column.

In the example illustrated for the platforms at ST 21-GC recorded in 2015 (Figure 26), a ten-species 

assemblage of pelagic and demersal fishes was compressed in 15.9 m of water to a narrow band between 

6.2 m above the bottom and 4.8 m below the surface. Fishes were constrained within 4.7 vertical meters 

by DO levels <23% saturation below and > 126% above. In another instance (Figure 28), the assemblage 

was compressed within a 1 m layer of a 7 m water column constrained by <9% saturation below and up to 

161% saturation in surface waters. This assemblage of four species consisted of high numbers of densely 

packed Atlantic spadefish, blue runner, gray snapper, and sheepshead. At the high-diversity platform the 

water quality used by fishes was more suitable for salinity in particular, with salinities as high as 33.6 psu 

used by fishes. At 23.1 psu salinity, the low diversity platform was unsuitable, or of poor suitability for 

many species (Figure 30).

These two examples suggest that fishes do not readily leave nearshore platforms in the face of extreme 

environmental change, and many species continue their strong association with platforms despite reduced 

habitat suitability. Use of suboptimal habitat may increase as availability of optimal habitat conditions 

decreases because of DO restrictions (Eby 2001). This idea is consistent with optimization theory 

(Kramer 1987), postulating an energetic tradeoff between optimizing conditions using the least effort 

possible, and agrees with the findings of Prince and Goodyear (2006) who noted an interplay of DO, 

temperature, depth, and predator-prey dynamics in the Pacific. Due to the large-scale disturbance that 

occurs when bottom-water hypoxia forms, habitat selection in the absence of hypoxia might not reflect 

fish responses outside of the hypoxic zone. In other words, fishes may respond differently when affected 

by widespread environmental stresses. In estuarine environments, fishes move in response to the 

continuously changing physicochemical conditions in which they live. Estuarine species are euryhaline 

(Günter 1956), and the extent of their landward distributions are driven largely by their lower salinity 

tolerances (Günter 1956; Remmert 1983). A benefit of studying fish distributions around platforms is 

that the fish aggregating effects that platforms provide facilitate study of detailed responses to extremes of 

hydrographic conditions that sometimes approach or exceed the tolerances of nearshore fishes.

The four species that remained on-site during the instance described in Figure 28 were among the most 

common and abundant species observed throughout the Louisiana nearshore coastal zone. That platform 

had higher species richness when bottom waters were well-mixed and well-oxygenated when re-sampled 
89

27 days later. The low species richness at this platform suggests that many of the less tolerant species that 

might otherwise have been present could not tolerate any portion of the water column as the result of one 

or more environmental constraints (Coutant 1985; Schurmann and Steffensen 1992; Eby and Crowder 

2002). Consequently, suitable habitat might become limiting for species that are sensitive to 

environmental fluctuation, or their prey, for which compression in the water column creates ephemeral 

habitat bottlenecks might be displaced. These effects may be reflected in the overall abundances and 

distributions of many species within the nearshore coastal zone.

The effect of DO concentration on fishes is complicated. Oxygen supersaturation has a shorter temporal 

influence during bloom conditions than hypoxia because its affects may principally manifest during 

daylight hours when photosynthesis is active. Also, the effects of gas supersaturation decrease with depth 

due to a 10% compensatory effect on total gas pressure for each meter descent below the surface (Parker 

et al. 1984). However, recurring bloom conditions that persist for days or weeks may have coincident 

effects with underlying hypoxic conditions when they displace fishes that would otherwise remain in an 

area. Fishes might entirely avoid areas with stressful water quality conditions during hours of peak 

photosynthesis, or fishes could potentially occupy the bloom waters above the hypoxic layer due to the 

compensatory effects of depth. In this case, the setting would provide a narrow corridor of usable habitat 

overlying a vacant benthic environment usable for mobile pelagic species (Figure 30).

Among the most interesting potential ecological impacts of hypoxia are those on food web dynamics. 

Displacement in the water column might lead to direct and indirect trophic interactions, by enticing fishes 

to stay in areas they might otherwise leave in order to exploit emerging benthic prey, or conversely cause 

them to leave an area they might otherwise occupy due to depletion of prey during a persistent event 

(Chesney and Baltz 2001 and references therein). In the long term, intermittently disturbed benthic 

environments become occupied by assemblages dominated by prolific, short-lived, R-selected species, as 

repeated disturbance precludes ecological succession to longer-lived organisms (Pihl 1994). Platforms 

can provide suitable conditions that strongly contrast with the surrounding environment by providing 

stability needed for succession of a higher order foraging base with a diverse fouling biota. 

Eutrophication in the nGOM produces a greater abundance of zooplankton in the water column (Dagg 

and Breed 2003 and references therein), and hypoxia may significantly alter trophic interactions (Keister 

et al. 2000). Specifically, the pelagic and planktivorous fishes within the hypoxic zone might benefit 

from increased predator-prey interactions when the two are compressed together throughout the hypoxic 

season (Prince and Goodyear 2006; Costantini et al. 2008; Roman et al. 2012; Elliot et al. 2012), although 

research has also shown evidence to the contrary (Zhang et al. 2009).

As observed by other studies off coastal Louisiana (Hazen et al. 2009; Craig and Bosman 2013), the most 

numerically abundant species encountered during this study was the Atlantic bumper, a planktivorous 

species that has increased in relative abundance since the mid-1930s, presumably as a result of 

eutrophication (Chesney et al. 2000). The enhanced primary productivity might have lasting effects on 

benthic production downstream of the impacted area, and throughout the rest of the year which might 

exceed repercussions from the temporary disturbance (Chesney et al. 2000; Chesney and Baltz 2001).

4.5 Conclusions

Eutrophication of the Fertile Fisheries Crescent has strong influences throughout the water column and 

can result in vertical habitat compression by reducing access to both the bottom and surface layers of 

Louisiana’s coastal waters. Habitat compression caused by surface phytoplankton blooms and subsequent 

hypoxia significantly alters habitat selection for some of the most common fishes living in this 

environment. The species occurring around platforms in the shallow-water nearshore zone show 

significantly different habitat selection patterns when forced into midwater strata with suitable DO. 

Observing these responses and patterns of distribution provides information about how these species cope 
90

with DO stressed environments, and demonstrates sub-lethal responses of fishes to eutrophication. 

Although we did not document these effects, fishes may experience altered metabolic rates and reduced 

growth rates, as they are forced into suboptimal environmental conditions. The scale of these habitat 

shifts can be significant. Differences in habitat selection in the presence and absence of hypoxia were in 

many cases greater than those separating species distributions given the same habitat availability. Habitat 

compression could increase interspecific and intraspecific competition when high densities of fishes 

become restricted to narrow bands of water. Ultimately, the physicochemical conditions within the 

suitably oxygenated portion of the water column below the surface bloom layer (as well as predator-prey 

interactions) influence species and life history stage distributions at platforms in shallow nearshore 

Louisiana waters. 

It is likely that optimal habitat can become rare and suitable habitat can become limiting when intense 

eutrophication and hypoxia occurs at platforms. Several questions remain: Why did the fish assemblages 

regularly avoid surface bloom waters throughout the summer? Also what is the stability of these layers in 

the water column, and how long do these smaller clines separate portions of the water column? What are 

the stoichiometric limits on the amount of space between water layers of oxygen depletion, and 

supersaturation? How do fish behave when the water column is shallow and the blooms penetrate the 

entire water column? Can a water column become fully uninhabitable with high enough eutrophication? 

Are eggs or larvae and other zooplankton affected by gas supersaturation within the bloom layer? Do 

these significant changes in environmental use result in significant metabolic alterations over relevant 

time periods to affect fish health or condition? To what extent are trophic interactions altered within the 

water column and do these changes negatively or positively affect fishes?
91

5 Cross Shelf Differences in Fishes Associated with Small Platforms 

in the Ship Shoal Area

5.1 Introduction

It is difficult to overstate the economic and ecological importance of Louisiana’s coastal zone. The 

region exports about $152 billion in goods and services annually (Barnes et al. 2015), it holds 40% of the 

nation’s wetlands (Penland et al. 1990), and its waters produce 73.8% of all Gulf fisheries landings 

(NMFS, 2015b). Louisiana’s coastal habitats have become substantially modified since the mid-twentieth 

century. Some of the most dramatic modifications are the erosion of 4876 km2 of wetlands, the 

installation of massive oil and gas infrastructure (platforms, pipelines) and the annual formation of coastal 

hypoxia (DO <2 mg l

-1

), which results in the displacement and/or mortality of some marine organisms 

(Leming and Stunz 1984; Renaud 1986; Craig and Crowder 2001, 2005; Craig et al. 2005; Switzer et al. 

2009, 2015; Craig and Bosman 2013). 

Oil and gas platforms (platforms) serve as small islands within the nGOM where fishermen tie up, birds 

roost, and marine biota attach (algae, invertebrates, fishes), grow and aggregate. Intense debate surrounds 

the value of platforms as fish habitat (Polovina 1991; Grossman et al. 1997; Gallaway et al. 2009; Shipp 

and Bortone 2009; Cowan et al. 2010; Claisse et al. 2014). However, there is no debating that platforms 

are de facto artificial reefs that attract large assemblages of fishes (Shinn 1974; Duglas et al. 1979; 

Harville 1983) and invertebrates (Gunter and Geyer 1955; Gallaway et al. 1981; Lewbel et al. 1987; 

Reeves et al. 2018b). However, it is debatable whether platforms significantly increase fisheries 

production by providing hard bottom habitat that is otherwise scarce (Stone et al. 1979) or if they 

principally alter foodchain pathways by shunting primary production to attached fouling biota rather than 

pelagic zooplankton and benthic infauna. 

There is also the question of how platforms act as FADs and whether this FAD effect increases the 

harvest of fishes that aggregate at platforms by making them more exploitable by fisherman (Samples and 

Sproul 1985; Bohnsack 1989). Past research has largely focused on characterizing platform-associated 

fish fauna, but few studies have explored the range of potential ecosystem services provided by platforms 

with the exception of some more recent studies focused on secondary production and the relative 

importance of epiphytes and macroalgae on oil platforms (Daigle et al. 2013; Claisse et al. 2014).

As of 2016 more than 900 platforms occupied Louisiana’s nearshore waters (<15 m total depth; BOEM),

which is an area that is prone to the development of the summertime hypoxia. The hypoxic zone occupies 

15,100–18,000 km2 off Louisiana’s coast (Obenour et al. 2013) and is considered the second largest 

hypoxic zone in the world (Rabalais et al. 2002a). Hypoxia is strongly associated with the bottom and is 

usually ~3 m thick (Hazen et al. 2009; Reeves 2015). Because platforms span from the bottom to the 

surface, platforms may provide benefits to reef-associated organisms by providing hard bottom habitat in 

oxygenated waters overlaying hypoxic bottoms. Hypoxia is believed to alter abundances of some reefassociated fishes and result in their vertical redistribution (Stanley and Wilson 2004), but few studies have 

focused on how the distributions of reef-associated fishes respond to hypoxia. 

In the studies described in this chapter, we evaluated some of the potential ecosystem services provided 

by nearshore oil and gas platforms: creation of benthic habitat that could act as a hypoxia refuge while 

facilitating high secondary production of benthic invertebrates. Here, we compared relative abundances 

and depth distributions of fishes at platforms experiencing varying hypoxia intensities before, during, and 

after the formation of hypoxia. We also used settling plates to document the settlement of barnacles and 

accumulation of fouling material along a 43.9 km landward-seaward transect. 
92

5.2 Methods

5.2.1 Fish Assemblages Study Design 

Fishes and hydrography were sampled at platforms on Ship Shoal (shoal platforms) and platforms 

seaward of the shoal (seaward platforms; Figure 35) before, during, and after the hypoxia season, which 

spanned mid-June to late-August (Figure 36). Platforms on Ship Shoal (shoal platforms) were subjected 

to mild hypoxia. The shoal is a submarine body of sand located ≈15 km south of the Isles Dernieres, 

Louisiana that has previously been used as a reference area for studies evaluating the effects of hypoxia 

(Baustian et al. 2009; Craig 2012; Craig and Bosman 2013). The shoal is known to be less prone to 

bottom water hypoxia because its bathymetric relief favors mixing and often precludes stratification 

(DiMarco et al. 2010; Munnelly 2016 and chapter 3) and high benthic microalgae densities on the shoal’s 

bottom can produce high oxygen levels when light penetrates to the bottom (Grippo et al. 2009, 2010). 

For purposes of this comparison we considered mild hypoxia as intermittent and thin and intense hypoxia 

as persistent and thick. Hypoxia on the shoal is intermittent, and when it occurs has a mean thickness of 

0.6 m (Reeves 2015). Platforms on the seaward side of the shoal (seaward platforms) experience intense 

hypoxia that is seasonally persistent and 3.1 m mean thick (Reeves 2015). Intense hypoxia can be broken 

up by tropical cyclones (Baustian et al. 2009), but none occurred in the study area in 2015-16.

Fishes were sampled with a video array at seven shoal and seven seaward platforms (14 total) on May 31 

(before), August 19 (during), and September 11, 2016 (after). Poor visibility precluded our use of video 

samples at shoal platforms on August 19, 2016. However, we also used the video array to sample fishes 

at six nearby platforms (three shoal and three seaward; Figure 35) on June 27, 2016. These six samples 

were included in all statistical analyses to avoid having a missing statistical cell (shoal platforms, during 

hypoxia). 

Figure 35. Chart of platform locations where fish assemblages were sampled repeatedly (open circles) and 

sampled once (black circles) during the summer of 2016. 
93

Figure 36. Bottom water DO (mgl

-1) at shoal (black circles) and seaward platforms (white circles) from May 31 

to September 11, 2016. 

Seaward platforms were located roughly 11 km southwest of shoal platforms. Seaward platforms were 

7.2±0.5 m (mean±SE) deeper than shoal platforms (14.8±0.5 vs. 7.9±0.4 m) and seaward sediment was 

sandy mud whereas shoal sediment was sand. Platforms used in these analyses were small (≤ 4 pilings) 

and 3 to 44 years old. Sampling efforts focused on small platforms because they were the dominant type 

of platforms in the study area (>90% of all platforms), they are rapidly being removed (43% reduction 

since 2006; BOEM), and they are not well studied in comparison to larger platforms further offshore. 

Fish assemblages were sampled using the same triangular prism-shaped camera array, described in 

chapter 3. The array was lowered and raised at a mean distance of 3.0±0.20 m (95% CI) from the 

platform and lowered at a rate of 0.23±0.02 m/s (95% CI). This method provided vertical video profiles 

of fishes concentrated around the small platform. Hydrographic sampling was conducted using a YSI 

6820 V2 Sonde following the same methods described in chapter 2. Video-based fish abundance 

estimates followed methods described in chapter 4, section 4.2.1.

5.2.2 Statistical Analyses: Fish Assemblages

A factor analysis was used to resolve eight correlated variables into three orthogonal factors (Proc Factor; 

SAS 9.4). The analysis was based on 70 YSI casts, and factors were rotated using the Varimax method. 

The factor analysis was performed on surface, midwater, and bottom measurements of salinity, 

temperature, DO, and turbidity. Surface and midwater salinity and turbidity were highly correlated 

(Pearson Coefficients >0.70), so means of surface and midwater measurements were calculated and 

characterized as upper salinity and turbidity. Means were also calculated for surface, midwater, and 

bottom temperature because of high correlations (Pearson Coefficients>0.57). The eight variables used in

the factor analysis were upper salinity, bottom salinity, temperature, surface DO, midwater DO, bottom 

DO, upper turbidity, and bottom turbidity. Factor scores were calculated for each variable and loadings

>|0.5| were used to characterize factors. Mean factor loadings were plotted for shoal and seaward 

platforms before, during, and after hypoxia to visualize environmental trends.
94

Principal coordinates analysis (Figure 37) was used to visualize patterns of dissimilarity of fish 

assemblages at shoal and seaward platforms before, during, and after the hypoxia season (PCO; PRIMER 

7; Gower 1966). The PCO was run on a Bray-Curtis similarity matrix that was based on the log(count+1) 

of fish species occurring more than five times in the dataset (Bacheler et al. 2013). A vector overlay was 

added to the PCO to display the associations of fish species with PCO axes. Fish species were plotted 

when Pearson correlations were greater than 0.5 and the radius of the plotted circle represents a 

correlation of 1.0. 

Repeated measures analysis of covariance (ANCOVAs) and multiple regression analyses were used to 

compare patterns of species richness, Shannon-Weiner Diversity, and counts of the five most common 

fishes (gray snapper [Lutjanus griseus], sheepshead [Archosargus probatocephalus], Atlantic spadefish 

[Chaetodipterus faber], blue runner [Caranx crysos], Atlantic bumper [Chloroscombrus chrysurus]; Proc 

GLIMMIX; SAS 9.4; Table 27). ANCOVAs included location (shoal and seaward), time (before, during, 

and after the hypoxia season), and a location-by-time interaction as explanatory variables. Multiple 

regression analyses included Factors 1–3 as explanatory variables. Both types of analyses included 

covariates to control for variable platform sizes (number of pilings) and visibility (midwater turbidity). 

Because multiple samples were collected at the same platforms, platform names were treated as repeatedmeasures subjects to account for the clustered structure of the data (Nelson 2014). Models were fitted 

with either normal, Poisson, or negative binomial distributions based on goodness of fit criteria (ShapiroWilks, Deviance/d.f.) and residual plots. Atlantic bumper were not observed during and after hypoxia at 

shoal platforms in 2015, so counts+1 were used to achieve model convergence. A significance level of 

0.05 was used for main effects and significance levels for post-hoc pairwise comparisons were corrected 

using Tukey-Kramer adjustments (Day and Quinn 1989). The reported measure of dispersion was one 

standard error unless otherwise noted.

A multinomial logit model was used to compare the depth distribution of counts before, during, and after 

the hypoxia season (Proc Logistic, SAS 9.4). The depth of counts for gray snapper, sheepshead, Atlantic 

spadefish, blue runner, and Atlantic bumper were recorded by referencing the depth gauge, pooled for all 

five species, and sorted into 3-m bins. The number of counts within each bin were then fitted to a 

multinomial distribution with a generalized logit link and compared across time (before, during, after). 

Depth distribution at shoal and seaward platforms were compared separately because of the differences in 

total depths of the two areas. Depth bins were 0–3, 3–6, and >6 m for shoal platforms and 0–3, 3–6, 6–9, 

9–12, and >12 m for seaward platforms. 

5.2.3 Fish Grazing Observations

An array of two GoPro cameras was secured to a platform and an hour of time-lapse video (one second 

intervals) recorded a 5 m2 section of submerged platform on a series of dates in 2015-16. Video frames 

were used to estimate the rates fishes grazed on fouling organisms for the one-hour deployment. A fish’s 

behavior was characterized as probably feeding when it was oriented towards platform substrate and a 

fish was observed to “peck” at the platform. A single feeding occurrence was defined as the entire interval 

an individual was pecking or hovering over platform’s substrate. 
95

5.3 Fish Assemblage Results

5.3.1 Summertime Hydrography

Results of cross shelf hydrographic analyses showed that the first three factors explained 55% of the total 

environmental variation (Table 25). Upper salinity (positive) and upper turbidity (negative) loaded on 

Factor 1. Factor 1 was characterized as a freshwater influence gradient because low salinity and high 

turbidity are indicative of freshwater influence. Bottom salinity (negative) and bottom DO (positive) 

loaded on Factor 2. Factor 2 was characterized as being a bottom water oxygen depletion gradient 

because DO had a strong negative contribution to Factor 2 and high bottom salinities are associated with 

the hypoxic waters below the pycnocline. Only temperature (positive) loaded on Factor 3, so this factor 

was characterized as a temperature gradient.

Table 24. Factor loadings for Factors 1–3, eigenvalues, variance explained by each factor and 

cumulative variance explained with bold values representing those that were used for factor 

interpretation.

Environmental

Variable Factor 1 Factor 2 Factor 3

Upper Salinity 0.89 -0.01 -0.12

Upper Turbidity -0.79 -0.30 0.20

Surface DO -0.33 0.11 -0.14

Bottom Water Salinity 0.27 -0.69 -0.44

Bottom Water DO 0.24 0.94 -0.01

Temperature -0.14 0.07 0.98

Bottom Water Turbidity -0.02 -0.13 0.04

Midwater DO 0.11 0.10 -0.01

Eigenvalue 1.68 1.50 1.22

% Variance Explained 21.00 18.75 15.25

% Cumulative Variance Explained 21.00 39.75 55.00

Table 25. Occurrence (percentage of videos where each individual species was present), mean 

counts, and minimum and maximum counts of each species identified on video around small 

platforms in summer of 2016. 

Scientific Name Common Name Percent 

Occurrence

Mean (SE) Count Min–Max 

Count

Chaetodipterus faber Atlantic spadefish 100% 65.0 (5.94) 14–144

Archosargus probatocephalus Sheepshead 93% 13.7 (1.29) 0–35

Lutjanus griseus Gray snapper 90% 7.2 (0.89) 0–17

Caranx crysos Blue runner 85% 11.8 (2.06) 0–50

Chloroscombrus chrysurus Atlantic bumper 73% 382.6 (53.30) 0–1023

Lutjanus campechanus Red snapper 65% 2.5 (0.55) 0–17

Kyphosus sectatrix Bermuda chub 63% 1.5 (0.30) 0–8

Caranx latus Horse-eye jack 43% 1.7 (0.43) 0–11

Pogonias cromis Black drum 33% 0.7 (0.19) 0–5

Pomatomus saltatrix Bluefish 30% 8.2 (2.87) 0–79

Sciaenops ocellatus Red drum 28% 0.6 (0.20) 0–7

Elagatis bipinnulata Rainbow runner 28% 0.5 (0.16) 0–5

Caranx bartholomaei Yellow jack 25% 1.3 (0.49) 0–16

Abudefduf saxatilis Sergeant major 25% 1.0 (0.38) 0–12

Caranx hippos Crevalle jack 15% 0.3 (0.15) 0–5

Balistes capriscus Gray triggerfish 13% 0.2 (0.07) 0–2

Rachycentron canadum Cobia 13% 0.2 (0.09) 0–2

Trachinotus carolinus Florida pompano 10% 0.2 (0.12) 0–3

Elops saurus Ladyfish 8% 2.3 (1.96) 0–78

Mugil cephalus Striped mullet 5% 1.0 (0.69) 0–24
96

Scientific Name Common Name Percent 

Occurrence

Mean (SE) Count Min–Max 

Count

Selene setapinnis Atlantic moonfish 5% 0.2 (0.16) 0–6

Sphyraena barracuda Great barracuda 5% 0.1 (0.03) 0–1

Orthopristis chrysoptera Pigfish 8% 0.1 (0.06) 0–2

Lagodon rhomboides Pinfish 5% 0.1 (0.06) 0–2

Aluterus monoceros Unicorn filefish 3% <0.1 0–1

Caranx ruber Bar jack 3% <0.1 0–1

Dasyatis americana Southern stingray 3% <0.1 0–1

Scomberomorus maculatus Spanish mackerel 3% <0.1 0–1

Selene vomer Lookdown 3% <0.1 0–1

There were pronounced hydrographic differences between shoal and seaward platforms before and during 

the hypoxia season, but differences were minimal after the hypoxia season (Figure 37). Seaward and 

shoal platforms exhibited similar changes along Factors 1, 2, and 3 before during and after hypoxia. 

However, seaward platforms had greater oxygen depletion than shoal platforms during the hypoxia 

season, seaward platforms experienced less freshwater influence before and during the hypoxia season 

than shoal platforms, and seaward sites were warmer before hypoxia and cooler during hypoxia than shoal 

platforms. 

Figure 37. Centroids of shoal and seaward platforms before, during and after the hypoxia season where 

Factor 1 was interpreted as a freshwater influence gradient, Factor 2 interpreted as an oxygen 

depletion gradient, and Factor 3 interpreted as a temperature gradient.

5.3.2 Comparison of Fish Assemblages 

There were 29 fish species identified on video, representing 16 different families (Table 26). Atlantic 

spadefish, sheepshead, gray snapper, blue runner, and Atlantic bumper were observed in at least 73% of 

all samples and comprised 96% of all fishes observed on video. Fish species were plotted in Figure 39 

when Pearson correlations between principal coordinates 1 and 2 were greater than 0.5, and the radius of 

the plotted circle was 1.0 (perfect correlation). The PCO explained 62.2% of total variation in fish 

assemblages and indicated that fish assemblages differed at shoal and seaward platforms before, during, 

and after the hypoxia season (Figure 39). 
97

There were more red drum (Sciaenops ocellatus), black drum (Pogonias cromis), and yellow jack 

(Caranx bartholomaei) before hypoxia at shoal platforms, and there were more Atlantic bumper and 

fewer gray triggerfish (Balistes capriscus) at seaward platforms before and after the hypoxia season. 

There was also a general pattern of decreasing red drum, black drum, and yellow jack counts and 

increasing Bermuda chub (Kyphosus sectatrix), gray snapper, rainbow runner (Elagatis bipinnulata), 

Atlantic spadefish and blue runner from May (before) to September (after) across both locations. The 

PCO shows divergence of fish assemblages during and after hypoxia, but this is mostly driven by the 

disappearance of Atlantic bumper from shoal platforms before and after the hypoxia season.

Figure 38. Number of species (species richness; A) and Shannon-Weiner Diversity (H’; B) at shoal and 

seaward platforms before, during, and after the hypoxia season. 

Table 26. Slopes, t-values, and P-values for the effects of Factors 1–3 on species richness, 

Shannon-Weiner Diversity and counts of gray snapper, sheepshead, atlantic spadefish, blue 

runner, and atlantic bumper. 

Response Factor 1 Factor 2 Factor 3

Slope t-value P-value Slope t-value P-value Slope t-value P-value

Species Richness -0.31 -2.6 0.02 -0.12 -2.1 0.05 0.20 3.3 <0.01

Shannon-Weiner H’ -0.07 -0.4 0.72 -0.13 -1.4 0.19 0.25 2.5 0.02

Gray snapper 0.75 1.4 0.17 0.10 0.4 0.67 0.32 1.4 0.17

Sheepshead -0.47 -1.4 0.17 -0.29 -1.9 0.08 0.01 0.1 0.93

Atlantic spadefish 39.68 2.1 0.05 -3.17 -0.4 0.73 2.27 0.2 0.81

Blue runner 0.05 0.1 0.95 -0.42 -1.2 0.25 0.68 1.9 0.08

Atlantic bumper -0.22 -0.4 0.71 -0.05 -0.2 0.86 -0.06 -0.2 0.84

Statistics in Table 27 were estimated using multiple regression analysis so slopes, t-values, and P-values 

are partial estimates. Species richness and H’ generally increased throughout the study period at shoal and 

seaward platforms, but H’ diverged at shoal and seaward platforms after the hypoxia season (Figure 

38A,B; Table 27). Species richness significantly increased throughout the sampling period (ANCOVA, 
98

F=9.2, P<0.01), but location and the location-by-time interaction were not significant effects (Table 27). 

H’ increased similarly before and during the hypoxia season, but a significant location-by-time interaction 

(ANCOVA, F=5.2, P=0.02) indicated that H’ diverged after the hypoxia season when it was significantly 

higher at shoal than seaward platforms (post-hoc t-test, t= -5.07, P<0.01).

Figure 39. A principal coordinates analysis showing the similarity of fish assemblages at shoal and seaward 

platforms before, during, and after the hypoxia season. 

There were differing patterns of counts for individual fish species across time and locations. Gray 

snapper counts generally increased across the study period, but a significant location-by-time interaction 

(ANCOVA, F=3.9, P=0.04; Figure 40A; Table 27) suggested that increases at shoal platforms were more 

pronounced than increases at seaward platforms; although, gray snapper counts were not significantly 

different at shoal and seaward platforms after the hypoxia season (post-hoc t-test; t= -2.2, P=0.29). 

Sheepshead counts were somewhat stable across the sampling period and the repeated measures 

ANCOVA indicated that location, time, and their interaction were not significant effects on sheepshead 

(Figure 40B; Table 27). Atlantic spadefish counts significantly varied across time (ANCOVA, F=8.1, 

P<0.01) because they were higher during and after the hypoxia season than they were before (post-hoc ttest, P-values< 0.05), but location and the location-by-time interaction were not significant effects (Figure 

40C; Table 27). Blue runner counts were significantly higher at seaward platforms (ANCOVA, F=8.7, 

P=0.01) and significantly varied across time (ANCOVA, F= 6.0, P= 0.01) because they were higher 

during and after the hypoxia season than they were before (post-hoc t-test, P-values< 0.05). However, 
99

there was no significant location-by-time interaction (Figure 40D; Table 27). Atlantic bumper counts 

were similar at shoal and seaward platforms before hypoxia, but they diverged thereafter when Atlantic 

bumper were absent at shoal platforms and numerous at seaward platforms, as suggested by the 

significant location-by-time interaction (ANCOVA, F= 144.0, P<0.01; Figure 40E; Table 27).

Figure 40. Mean MAXNO estimates (±1SE) of gray snapper (A), sheepshead (B), Atlantic spadefish (C), blue 

runner (D), and Atlantic bumper (E) at shoal and seaward platforms before, during, and after the 

hypoxia season. 
100

Figure 41. Distribution of fish counts by 3 m depth bins contrasted with DO profiles at shoal (A&B) and 

seaward (C&D) platforms before, during, and after hypoxia. 

Patterns of diversity were associated with the three composite variables produced by the hydrography 

factor analysis (Factor 1- freshwater influence, Factor 2- bottom water oxygen depletion, Factor 3-

temperature), but counts of individual fishes were mostly unassociated with these factors (Table 26). 

Species richness was negatively associated with decreasing freshwater influence (Multiple Regression, t= 

-2.6, P=0.02), negatively associated with decreasing bottom water oxygen depletion (Multiple 

Regression, t= -2.1, P=0.05), and positively associated with increasing temperature (Multiple Regression, 

t= 3.3, P<0.01). H’ was positively associated with increasing temperature (Multiple Regression, t= 2.5, 

P=0.02), but there was no significant association between H’ and the other factors (Table 27). Atlantic 

spadefish counts were positively associated with decreasing freshwater influence (Multiple Regression, 

t=2.1, P=0.05), but there was no significant association between Atlantic spadefish counts and the other

factors (Table 28). There were no significant associations between gray snapper, sheepshead, blue 

runner, and Atlantic bumper and the three factors (Table 27).
101

Black circles in Figure 43 represent 3 m depth bins, and are scaled to the proportion of fish counted 

within a 3 m bin. The horizontal bar in plot C of Figure 43 demarks the vertical extent of hypoxia (DO of 

2 mg l

-1

) at a location. Depth distribution of fishes significantly varied across time at seaward platforms 

(χ2

=20.0, P=0.01; Figure 43), but there was no significant difference at shoal platforms (χ2=3.0, P=0.55; 

Figure 43). Differences at seaward platforms were primarily driven by a sharp decrease in the number of 

counts occurring within the >12 m bin during the hypoxia season and a corresponding increase in the 

number of counts occurring within the 9–12 m bin. The odds of fish counts (video observations) 

occurring within the >12 m bin were 9.4–22.9 times higher before and after than they were during the 

hypoxia season. 

5.3.3 Fish Grazing on Fouling 

Sheepshead (Archosargus probatocephalus), gray triggerfish (Balistes capriscus), Atlantic spadefish 

(Chaetodipterus faber), gray snapper (Lutjanus griseus) and black drum were observed grazing on 

fouling organisms or platform associated epifauna during one-hour (time lapsed) camera deployments 

(Figure 42). In preliminary observation, gray triggerfish had the highest numbers of grazing behaviors 

(6.9 grazing behaviors m-2 hr-1

), and consistently grazed throughout the duration of the deployment. 

However the observations made at this platform were not typical. When we recorded and analyzed video 

from a series of nine small platforms a typical pattern emerged where grazing by sheepshead dominated 

grazing of barnacles (Figure 43). Mean grazing rates were also higher at 2 m below the surface than at 5 

m below the surface. Figure 42 shows an example of a triggerfish removing, dropping, and then chasing 

a barnacle from a small platform. Sheepshead and Atlantic spadefish also had high numbers of grazing 

behaviors, with 5.5 and 5.2 grazing behaviors m-2 hr-1

, respectively. There was one occurrence of gray 

snapper grazing on fouling organisms in this particular set of observations, but that behavior proved to be 

relatively rare. 

It is notable that the bottom water dissolved oxygen was 0.38 mg l

-1 during the deployment depicted in 

Figure 42 and hypoxia was 4.3 m thick (≈25% of the entire water column). Nevertheless, the vertical 

relief of this platform provided benthic habitat in well-oxygenated waters where benthic organisms such 

as barnacles, stone crabs (Menippe spp.), and blennies (Blenniidae) were observed in high abundances. 

These and other platform associated benthic organisms may become relatively important prey for some of 

the fish species observed to forage on platforms when bottom waters are hypoxic during the summer 

months. 
102

Figure 42. A four-second time lapse sequence of a gray triggerfish removing a barnacle from platform 

substrate and chasing the barnacle as it falls. 
103

Figure 43. Number of grazing behaviors (m-2 h-1) by sheepshead at a series of nine small platforms in the 

Ship Shoal blocks of the nearshore zone. 

5.4 Discussion of Cross Shelf Patterns of Fishes Observed at Small 

Platforms

There was no clear effect of hypoxia on the relative abundances of reef-associated fishes, and species 

richness increased with bottom oxygen depletion. It is well known that reef-associated fishes use 

platforms within the hypoxic zone (Stanley and Wilson 2004), but the lack of a relationship between reefassociated fishes and hypoxia is a new finding. Relative abundances of fishes and H’ were not associated 

with oxygen depletion, but ANCOVAs indicated that H’ and relative abundances of gray snapper and 

Atlantic bumper significantly diverged at shoal and seaward platforms during and after hypoxia.

Gray snapper occupied platforms at a higher rate on the shoal than seaward platforms after the hypoxia 

season, but no statistically significant effect of hypoxia was detected. Gray snapper abundances were 

somewhat similar at seaward platforms throughout the summer, but they increased by a factor of ten at 

shoal platforms. Hook and line sampling and diver observations indicated that gray snapper present 

during and after the hypoxia season were mostly juveniles, which were uncommon before hypoxia. Gray 

snapper exhibit ontogenetic movements to deeper waters that typically occur during mid-summer to early 

fall (Faunce and Serafy 2007; Luo et al. 2009). Gray snapper have benthic diets (Harrigan et al. 1989; 

Hettler 1989; Franks and Vanderkooy 2000; Yeager et al. 2014), and may preferentially recruit to the 

shoal because benthic invertebrates are more abundant on the shoal than the surrounding area (Dubois et 

al. 2009; Gelpi et al. 2009; Reeves et al. 2017). Less intense hypoxia likely contributes to higher 

abundances of benthic invertebrates on the shoal (Dubois et al. 2009; Gelpi et al. 2009) and may 

indirectly affect gray snapper movement to platforms. Nevertheless, the lack of a significant relationship 

between gray snapper abundances and oxygen depletion suggests there was no direct effect of hypoxia.
104

Atlantic bumper relative abundances diverged during and after hypoxia when there were no Atlantic 

bumper at shoal platforms and many at seaward platforms. The shift in the distribution of Atlantic 

bumper also drove divergences for H’ and fish assemblage similarity, as suggested by the PCO. Atlantic 

bumper are commonly found in the hypoxic zone where they vertically migrate to avoid hypoxic bottoms 

(Hazen et al. 2009; Craig 2012). The absence of Atlantic bumper at shoal platforms during and after 

hypoxia contrast with the finding that Atlantic bumper are especially common on the shoal when hypoxia 

is present in the surrounding area (Craig and Bosman 2013). It is unclear why Atlantic bumper were 

absent at shoal platforms during and after hypoxia. Although they are common around nearshore 

platforms (Reeves 2015; Munnelly 2016), they are not a typical reef-associated fish and we often 

observed schools of them well away from platforms on Ship Shoal and elsewhere. It seems likely that 

they were in the area but not at platforms or moved away from the area for reasons unrelated to the 

hydrographic conditions in the area of Ship Shoal. 

5.4.1 Depth Distributions of Fishes Near Small Platforms

Hypoxia-based habitat compression resulted in the vertical redistribution of fishes at platforms where 

bottom hypoxia occurred. Fish distributions shifted 3 m shallower when hypoxia was present at seaward 

platforms and resulted in the concentration of fishes in the 9–12 m depth strata. This finding is consistent 

with the occurrence of high fish densities in the waters just above hypoxia around platforms (Stanley and 

Wilson 2004). Changes to the depth distributions may cause fishes to inhabit less-suitable hydrographic 

environments and limits the amount of available habitat and access to the bottom (Munnelly 2016). 

Hypoxia-based habitat compression is known to be associated with the vertical redistribution of 

organisms in the nGOM (Stanley and Wilson 2004, Hazen et al. 2009; Roman et al. 2012), and it is 

commonly postulated that this phenomenon increases predator-prey encounters (Breitburg 1994; Eby and 

Crowder 2002; Eby et al. 2005; Prince and Goodyear 2006; Hazen et al. 2009; Roman et al. 2012). 

Crowding could also increase antagonistic behaviors (Aumann et al. 2006) and stress, which may have 

consequences for reproduction and growth (Bonga 1997; McCormick 2006).

5.4.2 Seasonal and Locational Differences in Fish Relative Abundances

Relative abundances of most fishes changed over the course of the summer. For instance, black drum and 

red drum were common at shoal and seaward platforms early in the summer, but were not observed after 

June 27. Because hypoxia often spans from late spring to late summer (Rabalais et al. 1991), it is 

important to account for seasonal changes in distributions of organisms by comparing areas of varying 

hypoxia intensity. This can be particularly challenging because of the ubiquity of hypoxia in coastal 

Louisiana. However, oxygenated bottom waters overlaying Louisiana’s shoals (Ship, St. Bernard, Tiger,

and Trinity) create “holes” in the hypoxic zone, and these areas can be used as reference areas for future 

studies evaluating the effects of hypoxia.

Some differences in the relative abundances of fishes at shoal and seaward platforms persisted throughout 

the summer. Blue runner and spadefish relative abundances were generally higher at seaward platforms 

than they were at shoal platforms. The primary difference between the two areas was a 7.1 m difference 

in depth (seaward: 14.8 m, shoal: 7.9 m). Depth may have played a role in shaping differences between 

the two areas because depth is known to be associated with fish abundances around platforms (Stanley 

and Wilson 1991). Nevertheless, species richness patterns and the relative abundances of many, but not 

all species were similar at shoal and seaward platforms throughout much of the study period. 
105

5.5 Chapter 5 Conclusions

This chapter summarizes studies in the Ship Shoal blocks during 2015–2016. Fishes normally associated 

with the lower parts of the water column responded to hypoxia by moving up within the water column, 

but there was no apparent effect of hypoxia on patterns of relative abundance and diversity of the reef 

associated fishes. Platforms may provide refuge for reef-associated fishes living within the nGOM’s 

hypoxic zone. Platforms span the entire water column providing hard bottom habitat that is used by small 

cryptic species and reef-associated organisms in oxygenated waters overlaying hypoxia (Stanley and 

Wilson 2004; Reeves et al. 2017, 2018b). This hard bottom habitat is settled by barnacles and other 

fouling organisms (Gunter and Geyer 1955; Gallaway et al. 1981; Lewbel et al. 1987; Reeves et al. 2017), 

and undoubtedly provides a source of prey for some species when underlying macrobenthic organisms are 

decimated by hypoxia. 

The vertical extent of energy platforms is an important characteristic that distinguishes them from other 

types of artificial reefs (Hernandez et al. 2003; Stanley and Wilson 2004). This makes energy platforms 

inherently more valuable as an artificial reef than tradition placements of hard substrate, such as those 

throughout most of the rest of the Gulf. Key elements of the added value of platforms as artificial reefs is 

1) submerged platform structures provide fouling habitat that extends primary and secondary production 

into the upper parts of the photic zone, 2) platforms provide habitat for fouling organisms that in turn 

provide shelter and a food source for epifauna and infauna in the middle to upper water column and 3) 

platforms also offer a source prey (small crabs, shrimp, and infauna) for some fishes to exploit during 

periods of low oxygen in the nearshore zone. 
106

6 Patterns of Barnacle Settlement and Growth at Oil and Gas 

Platforms in the Ship Shoal Area

6.1 Introduction

Nutrient discharge from the Mississippi and Atchafalaya rivers drive prolific primary production off 

Louisiana’s coast (Turner and Rabalais 1991, 1994; Dortch and Whitledge 1992; Rabalais et al. 1996). 

This region produces >73% of all United States fisheries landings in the Gulf of Mexico (NMFS 2015b), 

and leads in commercial landings of many reef-associated species (red snapper [Lutjanus campechanus], 

lane snapper [Lutjanus synagris], vermillion snapper [Rhomboplites aurorubens], Warsaw grouper 

[Epinephelus nigritus]; NMFS 2015b]. Naturally-occurring hard bottom habitat is rare on the continental 

shelf off Louisiana (Parker et al. 1983), and shelf edge banks provide the only source of natural hard 

bottom habitat. However, oil and gas platforms (platforms) are de facto artificial reefs that account for 

~12 km2 of hard bottom substrate on the shelf (Gallaway et al. 1998), and are renowned fishing 

destinations where reef-associated fishes are commonly landed (Stanley and Wilson 1989).

The value of platforms as artificial reef habitat has long been the subject of debate (Polovina 1991; 

Grossman et al. 1997; Gallaway et al. 2009; Shipp and Bortone 2009; Cowan et al. 2010; Claisse et al 

2014; Cresson et al 2014a; Cowan and Rose 2016), but it is critical to resolve this debate since nearshore 

platforms are rapidly being removed. The debate surrounding the ecological value of platforms falls 

within the broader attraction vs. production artificial reef debate. The attraction side argues that artificial 

reefs attract fishes and make them more susceptible to fishing (Stone et al. 1979), while the production 

side argues that artificial reefs produce additional fish biomass (Samples and Sproul 1985; Bohnsack 

1989). There is probably a continuum rather than two discrete outcomes (attraction vs. production; 

Bohnsack 1989), and the degree of attraction or production is unquestionably taxon-specific (Cowan and 

Rose 2016; Reeves et al 2017b). The number of platforms in the GOM peaked at ~4,000 in 2008 and has 

decreased to ~2,100 in 2017 (BOEM 2017). 

Most platform research in the GOM has focused on deep water platforms, but nearshore platforms (5–25 

m total depth) may be especially important because they occupy the highly productive region influenced 

by the Atchafalaya and Mississippi rivers. Nearshore platforms represent ~40% of platforms in the GOM 

(BOEM 2017). These nearshore platforms host diverse assemblages of fishes that are associated with 

varying degrees of freshwater influence (Reeves 2015; Munnelly 2016). Barnacles are the dominant 

fouling organisms on nearshore platforms (Gunter and Geyer 1955; Lewbel et al. 1987; Reeves et al. 

2018b), and they provide structural habitat (topographic relief) for stone crabs (Reeves et al. 2018b). 

Barnacles are filter feeders that prey upon zooplankton and phytoplankton (Barnes 1959), and their 

growth and settlement is positively associated with productivity (Bertness et al. 1991; Menge et al. 1997, 

2003; Sanford and Menge 2001; Leslie et al. 2005; Thiyagarajan et al. 2005). Understanding secondary 

production on artificial reefs is critical to resolving the attraction vs. production debate (Bohnsack 1989), 

and it has received increased attention in recent years. Recent studies of offshore platforms in the GOM 

have examined the importance of fouling as prey for fishes (Daigle et al. 2013; Schwartzkopf 2014; Foss 

2016) and the production of amphipods (Beaver et al. 2003). While the importance of filter feeders as 

prey and ecological engineers is well established for platforms off the California coast (Page et al. 1999; 

Claisse et al. 2014), platform-dwelling barnacles in the nGOM have been given much less attention. 

In this chapter, we present a two-year study where settlement plates were used to examine how growth 

and settlement of platform-dwelling barnacles varied with distance to shore and depth. We hypothesized 

that barnacle growth and settlement is greater closer to shore and at shallower depths due to the higher 

degree of freshwater influence and eutrophication in this part of the coastal zone (Reeves 2015; Munnelly 

2016).
107

6.1.1 Settlement Plate Construction and Deployment 

Settlement plates were constructed using 6-inch PVC schedule 40 pipe. The pipe was split lengthwise to 

make two pieces with concave and convex outer surfaces, and was cut into 10 cm long sections. 

Individual 10 cm sections were considered settlement plates (Figure 44), and were mounted to platforms 

so that concave surfaces faced outwards. The outer 254 cm2 surface area was used for all analyses.

Figure 44. An example of a settling plate before (A) and after (B) a 92-day deployment (August 21–November 

21, 2016).

Table 27. Platform names, distances to shore, settlement plate deployment and recovery dates, 

and the total time of deployment (days).

Site Name Distance to 

Shore (km)

Total

Depth (m)

Number of 

Pilings

Deployment Date Recovery Date Deployment 

Time (Days)

SS 93-44 15.7 7.6 2 Jul 29, 2015 Nov 4, 2015 98

SS 93-43 16.2 7.9 1 Jul 29, 2015 Nov 4, 2015 98

SS 93-61 16.2 7.9 1 Aug 19, 2016 Nov 21, 2016 94

SS 93-35 17.2 8.2 1 Aug 19, 2016 Nov 21, 2016 94

PL 21-1 21.4 17.3 1 Aug 28, 2015 Dec 1, 2015 95

SS 113-52 23.1 14.9 1 Aug 21, 2016 Nov 21, 2016 92

SS 112-4 23.7 14.6 2 Aug 19, 2016 Nov 21, 2016 94

ST 72-1 28.7 19.5 1 Aug 28, 2015 Dec 1, 2015 95

SS 189-C 51.6 22.6 1 Jul 29, 2015 Dec 1, 2016 125

SS 188-3 51.7 22.3 1 Aug 21, 2016 Nov 21, 2016 92

SS 209-P 54.6 29.9 4 Aug14, 2015 Dec 1, 2015 109

SS 215-C 59.6 33.5 1 Aug 21, 2016 Nov 21, 2016 92
108

Figure 45. Chart of locations of platforms where settling plates were deployed in 2015 and 2016. 

A total of seventy-two settlement plates were deployed at 12 platforms (6 settlement plates/platform) 

along a 43.9 km landward-seaward transect starting ~15 km south of the Isles Dernieres, Louisiana in 

2015 and 2016 (Figure 45, Table 28). Platforms were small (1–4 pilings) and located in depths of 7.6–

33.5 m. SCUBA divers deployed sets of three settlement plates at depths of two and seven meters. 

However, 2m plates were lost at the three most seaward platforms in both years (18 settlement plates). 

Settlement plate deployments lasted 92–125 days. Plates were retrieved by divers who sealed the plates 

in plastic bags while underwater to prevent the loss of loose materials. Settlement plates were returned to 

the laboratory and frozen at ~ –18oC. 

In conjunction with settlement plate deployment and retrieval, we collected hydrographic profiles of the 

upper 8 m with a YSI 6820 V2 Sonde. The Sonde was lowered from the vessel at a rate of 0.04±0.004 

m/s (95% CI) and recorded temperature (oC), salinity (PSU), and DO (mg l

-1

) in two-second intervals. 

The Sonde was calibrated before and after each sampling trip using the manufacturer’s specifications 

(YSI Incorporated 2012). 

6.1.2 Settlement Plate Processing

We subdivided settlement plates into six equal cells and subsampled five barnacles (>2 mm width) from 

each cell for biometrics (≥30 barnacles per plate). Barnacles were only subsampled if their bases were 

directly attached to the settlement plate (i.e. no individuals attached to other barnacles were measured). If 

empty cells were present, additional barnacles were sampled from adjacent cells so that sample size was 

as close as possible to 30 barnacles. Barnacle heights and widths were measured to 0.1 mm, total (shell + 

tissue) and tissue wet weights were measured to 0.001 g, and barnacles were identified to the species 

level. Settlement plates were then scraped of all fouling material, which was weighed to the nearest 0.1 g. 
109

Barnacles were then sorted by species and counted. Since Amphibalanus reticulatus and A. amphitrite 

were difficult to distinguish without dissections, they were grouped as Amphibalanus spp. for counts. 

Counted barnacles were classified as being spat (≤2 mm width) or post-spat (>2 mm width). Barnacles 

used for biometrics were added to estimates of fouling material weight and barnacle counts. 

After all settlement plates were sampled, we subsampled an additional five A. reticulatus per plate to 

compare wet compared to dry tissue weights. A. reticulatus tissue wet weights were measured and 

barnacles were subsequently dried at 110oC for 2 hours (Crisp and Patel 1961) and weighed again. We 

did not include these barnacles in other comparisons of biometrics since this subsampling procedure 

differed from the original. 

6.1.3 Statistical Analyses

Barnacle abundances and biometrics were converted to rates by standardizing the following variables by 

time of deployment: fouling accumulation (g m-2 day-1

), post-spat and spat Amphibalanus spp. 

abundances (number m-2 day-1

), post-spat and spat Megabalanus tintinnabulum abundances (number m-2

day-1

), and A. reticulatus height (mm day-1), width (mm day-1), total wet weight (mg day-1), and tissue wet 

weight (mg day-1

). Barnacle abundances were considered settlement rates, and A. reticulatus biometrics 

were considered proxies for growth rates. Since it is likely that barnacles on an individual plate settled 

sometime after deployment of plates, growth rates are conservative estimates. It is also likely that 

barnacles on an individual plate settled at different times, so we interpreted growth rates for the entire 

plate, not individual barnacles.

Fouling accumulation (g m-2 day-1

), post-spat and spat Amphibalanus spp. abundances (number m-2 day-1), 

post-spat and spat Megabalanus tintinnabulum abundances (number m-2 day-1

), and A. reticulatus height 

(mm day-1

), width (mm day-1), tallness (height/width), total wet weight (mg day-1), and tissue wet weight 

(mg day-1

) were compared across distance from shore (km), year (2016 vs. 2017), and depth (2 vs. 7 m) 

using generalized linear mixed models (GLMMs; Proc GLIMMIX; SAS 9.4) . We also used GLMMs to 

compare the ratio of tissue: total wet weight (percent tissue) across distance, year, and depth and included 

height as a covariate to account for size-specific differences. Backward elimination was used to eliminate 

interactions and main effects [(distance, year, depth, height (if applicable)] that did not substantially 

improve the AIC of individual models (reductions ≤2; Bolker 2008). Indicator variables were used for 

year (2015= 1; 2016=0) and depth (2 m= 1; 7 m=0). We also used simple linear regression to compare 

percent tissue vs. tallness and tissue wet weight vs. dry weight.

All statistical models were fitted with normal or lognormal distributions and goodness of fit was 

evaluated using predicted vs. residual plots. Random effects were used to designate individual platforms 

as the sampling unit for all analyses and a plate identifier was designated as a cluster for analyses of 

biometrics to control for the clustered nature of the data (Nelson 2014). 

6.1.4 Cross-Shelf Hydrography for Settlement Plate Studies

Hydrography varied with distance to shore in 2015 and 2016 on plate deployment and retrieval dates 

(Figure 46). In Figure 46 platforms were grouped into three from shore categories (15–18, 21–29, 51–60 

km). Black lines in Figure 46 denote conditions on deployment dates and grey lines denote conditions on 

retrieval dates. All hydrographic variables are plotted against a single x-axis that represents variables and 

their respective units. Salinity generally increased with distance to shore and was higher on retrieval than 

deployment dates. There was also evidence of strong salinity stratification (low salinity near the surface 

and high salinity at 8 m) at the platforms nearest to shore during the 2015 deployment. Salinity 

stratification at these platforms corresponded with high DO (>10 mg l

-1

) near the surface and extremely 

low DO (<0.5 mg l

-1

) at 8 m. Temperature also increased with distance to shore, but increases were more 

pronounced during retrieval than deployment in both years. Although this trend during the 2015 retrieval 
110

was not as clear since the settlement plates closest to shore were removed ~4 weeks earlier (November 4 

vs. December 1) than those further offshore.

Figure 46. Depth profiles of DO (mg l

-1), temperature (oC), and salinity (PPT) in 2015 and 2016 at platforms on 

days when settlement plates were deployed or retrieved. 
111

6.1.5 Cross-Shelf and Depth Dependent Patterns of Fouling

Regression lines in Figures 47 and 48 were generated by the GLMM and were plotted for relationships 

identified as being important by backward elimination. Fouling accumulation decreased with increased 

depth and distance to shore (Figure 47; Table 29). Distance (P<0.05) and depth (P<0.01) were the only 

significant variables for the GLMM testing for patterns of fouling accumulation. Fouling accumulation 

decreased at a rate of 1.7 g m-2 d-1 km-1 and fouling accumulation was generally 69.0 g m-2 greater at 2 vs. 

7m.

Figure 47. Patterns of fouling accumulation (g m-2 d-1) for each year-by-depth combination of settlement 

plates (2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 7m) with varying distance to shore. 

6.1.6 Cross-Shelf Barnacle Abundances

In total, 24,946 post-spat barnacles and 5,290 spat were found on the settlement plates (Table 30). 

Amphibalanus spp. was the most common barnacle counted. A. reticulatus and A. amphitrite were pooled 

for counts; most of these barnacles were A. reticulatus because A. reticulatus represented >99% of the 

dissected A. reticulatus + A. amphitrite. Megabalanus tintinnabulum was the second most abundant 

barnacle, representing 6.2% of all post-spat barnacles counted. 

Amphibalanus spp. spat and post-spat accumulation rates (number m-2 day-1

) varied across distance to 

shore, depth, and year, M. tintinnabulum post-spat abundance (number m-2 day-1

) varied across year and 

depth, but no factors were associated with M. tintinnabulum spat abundances (number m-2 day-1

; Figure 

48; Table 29). The distance-by-depth-by-year interactions were significant for Amphibalanus spp. postspat (P<0.05; Table 29; Figure 48A) and spat (P<0.01; Table 29; Figure 48B) indicating that four separate 

regression lines were needed for each year-by-depth combination of plates (2015 & 2m, 2015 & 7m, 2016 

& 2m, 2016 & 7m). Accumulation rates ranged from -2.01 to -86.20 post-spat and -0.01 to -0.82 spat d-1

m-2 km-1

. M. tintinnabulum post-spat accumulation rates were not significantly associated with distance 

but there were generally 1.40 more post-spat d-1 m-2 in 2015 vs. 2016 (P<0.01; Table 29; Figure 48C) and 
112

1.68 more spat d-1 m-2 at 2 vs. 7m (P<0.01; Table 29 Figure 48C). Backward elimination indicated that 

none of the variables adequately explained M. tintinnabulum spat abundances (Figure 48D). 

Figure 48. Post-spat (A) and spat Amphibalanus spp. abundances (B), post-spat (C) and spat Megabalanus 

tintinnabulum abundances (D) for each year-by-depth combination of settlement plates (2015 & 2m, 

2015 & 7m, 2016 & 2m, 2016 & 7m) with varying distance to shore. 
113

Table 28. Model intercepts (Int.), degrees of freedom error (D.F.), and t-values and slopes () for fouling community variables included 

in generalized linear mixed model of fouling accumulation, barnacle settlement rates and barnacle biometrics on settling plates located 

at different platforms, depths and deployed in different years. 

Response Distance (km) Depth (m) Year (Yr) km*m km*Yr m*Yr km*m*Yr Height km*Height

Int. D.F. (β, t) (β, t) (β, t) (β, t) (β, t) (β, t) (β, t) (β, t) (β, t)

Fouling Accum. (g m-2 d-1) 99.561 9 -1.688, -3.0* 69.005, 5.8** N.I.M. N.I.M. N.I.M. N.I.M. N.I.M. N.T. N.T.

: Amphibalanus spp. Abundance

Post-Spat (num. m-2 d-1) 269.880 4 -4.743, -3.8* 291.190, 1.5 -107.450, -1.6 -13.452, -1.3 -2.733, 1.5 1563.100, 5.4** -70.742, -4.6* N.T. N.T.

ln[Spat (num. m-2 d-1)] 1.024 4 -0.008, -0.6 0.985, 0.6 -4.335, 5.5** -0.091, -1.0 -0.022, -3.4* 12.106, 4.8** -0.649, -4.8** N.T. N.T.

: M. tintinnabulum Settlement

ln[Post-Spat (num. m-2 d-1)] 0.570 9 N.I.M. 1.682, 6.0** 1.404, 5.3** N.I.M. N.I.M. N.I.M. N.I.M. N.T. N.T.

ln[Spat (num. m-2 d-1)] 0.006 11 N.I.M. N.I.M. N.I.M. N.I.M. N.I.M. N.I.M. N.I.M. N.T. N.T.

A. reticulatus Biometrics

Height (mm d-1) 0.099 7 -0.001, -9.6** 0.044, 11.0** -0.008, -2.0 N.I.M. N.I.M. -0.035, -6.7** N.I.M. N.T. N.T.

Width (mm d-1) 0.122 9 -0.001, -3.5** N.I.M. -0.023, -4.3** N.I.M. N.I.M. N.I.M. N.I.M. N.T. N.T.

Tallness (height/width) -0.109 7 -0.015, -7.4** 0.443, 8.2** -0.135, 2.1 N.I.M. N.I.M. -0.356, -4.7** N.I.M. N.T. N.T.

ln[Total Wet Wt. (mg d-1)] 2.194 8 -0.036, -5.3** 0.362, 2.7* -0.844, -4.0** N.I.M. N.I.M. N.I.M. N.I.M. N.T. N.T.

ln[Tissue Wet Wt. (mg d-1)] 0.333 7 -0.024, -7.0** 0.625, 4.7** -0.656, -6.0** N.I.M. N.I.M. -0.925, -5.1** N.I.M. N.T. N.T.

ln[Tissue/ Total Wet Wt.] -1.967 7 0.017, -4.3** N.I.M. -0.430, -4.7** N.I.M. N.I.M. N.I.M. N.I.M. 0.077, 5.7** -0.003, -5.2**

Note: N.I.M.= Not in the model, N.T.= Not tested. 
114

6.1.7 Cross-Shelf Patterns of A. reticulatus Biometrics

Biometrics were collected for 1,468 barnacles representing five species (Table 30). Analyses were 

focused on A. reticulatus because it represented >90% of barnacles sampled for biometrics. 

Amphibalanus spp. and M. tintinnabulum counts were subdivided into post-spat (>2 mm width) and spat 

(≤2 mm width). N.A. is an abbreviation for “not applicable.” A. reticulatus and A. amphitrite were 

pooled for counts because they were difficult to distinguish without dissections, but they were treated 

separately for biometrics. Wet and dry tissue weights were significantly related (Wet= 0.02 + 10.29*Dry; 

t213=31.5, P<0.01; r2= 0.82) and percent tissue vs. tallness (height / width) was not significant (t10= -

0.1, P=0.94).

Table 29. Barnacle species and the number of barnacles for each species included in analyses of 

counts and biometrics. 

Type Counted Biometrics

Post-Spat:

Amphibalanus spp. 23,260 N.A.

Amphibalanus reticulatus N.A. 1,328

Amphibalanus amphitrite N.A. 9

Megabalanus tintinnabulum 1,538 120

Balanus trigonus 97 6

Amphibalanus improvisus 51 5

Sum 24,946 1,468

Spat:

Amphibalanus spp. 5,197 N.A.

Megabalanus tintinnabulum 93 N.A.

Sum 5,290 N.A.

Regression lines in Figures 49, 50, and 51 were generated by the GLMM and were plotted for 

relationships identified as being important by backward elimination. A. reticulatus heights (mm d-1

) and 

tallness (height/weight) were generally greater closer to shore, at 2 vs. 7m, and in 2016 vs. 2015, and 

widths (mm d-1

) were generally greater closer to shore and in 2016 vs. 2015 (Figure 49; Table 29). A. 

reticulatus heights decreased with distance to shore (P<0.01; slope= 0.0011 mm d-1 km-1

; Table 2; Figure 

6A), but the significant depth-by-year interaction (P<0.01) indicated that the effect of depth was larger in 

2016 compared to 2015. The smallest estimated mean height growth rate was 0.02 mm d-1 (60 km to 

shore, 2015 & 7m) and the greatest was 0.13 mm d-1 (15 km to shore, 2016 & 2m). A. reticulatus widths 

significantly decreased with distance (P<0.01; slope= -0.0006 mm d-1 km-1; Table 29; Figure 49B) and 

were 0.02 mm d-1 greater in 2016. vs. 2015 (P<0.01), but depth was not a significant effect. The smallest 

estimated mean width growth rate was 0.06 mm d-1 (60 km to shore, 2015) and greatest was 0.11 mm d-1

(15 km to shore, 2016). A. reticulatus tallness decreased with distance to shore (P<0.01; slope= 0.015 

km-1

; Table 29; Figure 49C), but the significant depth-by-year interaction (P<0.01) indicated that the 

effect of depth was larger in 2016 vs. 2015. The smallest estimated mean tallness was 0.36 (60 km to 

shore, 2016 & 7m) and the greatest was 1.11 (15 km to shore, 2016 & 2m). 
115

Figure 49. Amphibalanus reticulatus height (mm day-1; A), width (mm day-1; B), tallness (height/width; C) for 

each year-by-depth combination of settlement plates (2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 7m) 

with varying distance to shore. 
116

Figure 50. Amphibalanus reticulatus total wet weight (mg day-1), and tissue wet weight (mg day-1) for each 

year-by-depth combination of settlement plates (2015 & 2m, 2015 & 7m, 2016 & 2m, 2016 & 7m) with 

varying distance to shore. 

A. reticulatus total and tissue wet weights (mg d-1) decreased with increased distance to shore, were 

greater in 2016 vs. 2015, and were typically greater at 2 vs. 7m (Figure 50; Table 29). A. reticulatus total 

weight gain decreased with increased distance to shore (P<0.01; slope= -0.037 mg d-1 km-1; Table 29; 

Figure 50A). Total weight gain was 0.36 mg d-1 greater at 2 vs 7m (P<0.05) and 0.84 mg d-1 greater in 

2016 vs. 2015 (P<0.01). The smallest estimated mean total weight gain was 0.43 mg d-1 (60 km to shore, 

2015 & 7m) and greatest was 7.46 mg d-1 (15 km to shore, 2016 & 2m). A. reticulatus tissue weights 

decreased with increased distance to shore (P<0.01; slope= -0.024 mg d-1 km-1

; Table 29; Figure 50B), but 

the significant depth-by-year interaction (P<0.01) indicated that the magnitude and direction of the depth 

effect changed across years. The effect of depth was more pronounced in 2016 compared to 2015, and 

weights were greater at 2 compared to 7m in 2016 and 7 compared to 2m in 2015. 
117

Figure 51. Tissue/Total Wet Weight (percent tissue) of A. reticulus across distance from shore and height in 

2015 (A) and 2016 (B). 
118

The smallest estimated mean tissue weight growth was 0.13 mg d-1 (60 km to shore, 2015 & 2m) and the 

greatest was 1.82 mg d-1 (15 km to shore, 2016 & 2m). The response surfaces in Figure 51 were 

generated by the GLMM. Warmer colors correspond to greater percent tissue. Percent tissue varied 

across distance to shore, height, and year (Figure 51; Table 29). Percent tissue was significantly greater 

in 2016 compared to 2015 (P<0.01; Table 29; Figure 51). A significant distance-by-height interaction 

(P<0.01) suggested that percent tissue was similar at all distances for smaller barnacles, but distance had a 

strong, positive effect for large barnacles and percent tissue peaked at ~25–30%. 

6.2 Patterns of Cross Shelf Secondary Production on Platforms

Fouling accumulation, barnacle settlement, and barnacle growth were markedly higher in nearshore 

waters where there is prolific primary and secondary production. It is well established that barnacle 

growth and settlement is greater in areas with higher phytoplankton (Bertness et al. 1991; Menge et al. 

1997, 2003; Leslie et al. 2005) and zooplankton production (Sanford and Menge 2001), and patterns of 

productivity probably drove the differences in barnacle settlement and growth described here. Rate of 

primary and secondary production are generally greater closer to shore and near the surface off 

Louisiana’s coast (Chen et al. 2000). These patterns are driven by discharge from the Mississippi and 

Atchafalaya Rivers (Turner and Rabalais 1991, 1994; Dortch and Whitledge 1992; Rabalais et al. 1996), 

which initially form a low salinity layer in the surface water that gradually mixes with underlying 

seawater as distance from shore increases. Low salinity surface waters typically occur within the upper 4 

m in Louisiana’s nearshore waters (Munnelly 2015; Reeves 2017a,b), and dense phytoplankton blooms 

are common in these low salinity waters (Grimes and Finucane 1991; Dortch and Whitledge 1992).

Greater percent tissue (tissue wet weight/total wet weight) of A. reticulatus closer to shore and in 2016 

compared to 2015 reflects a higher investment in tissue, but this relationship was only apparent for larger 

barnacles. Percent tissue is often positively related to tallness and thus thinner and more brittle shells, but 

this relationship is species-specific (Wethey 1984) and was not observed here. This is an important 

consideration because brittle barnacles are prone to crushing by conspecifics (Connell 1961). Tallness 

typically increases with barnacle density (Barnes and Powell 1950; Wethey 1984; Bertness 1989), and we 

found that plates with the highest barnacle settlement and tallness all occurred in the nearshore zone. 

Higher settlement and densities of barnacles may create a positive feedback by increasing ease of 

copulation (Crisp 1976). 

Strong inter-annual-variability in the settlement and growth of barnacles may be related to later 

recruitment of A. reticulatus in 2016 than 2015. Highest Amphibalanus spp. settlement occurred for the 

plates at 2 m in 2015, but A. reticulatus growth rates were generally higher in 2016 than 2015. This could 

reflect higher recruitment of A. reticulatus in 2015, but it more likely reflects a later recruitment. 

Barnacles tend to crush and displace their neighbors as they grow outwards in a crowded environment 

(Crisp 1960; Connell 1961), so settlement may have been similar in 2016 and 2015 but masked by 

mortality of some 2016 recruits (see Bertness et al. 1991). Our strongest support for a later recruitment in 

2015 was the substantially higher number of Amphibalanus spp. spat in 2015. For example, 

Amphibalanus spp. spat settlement at the 2m plates closest to shore in 2015 exceeded 100 spat m-2 d-1

, but 

spat were nearly absent in the same area during 2016. Later recruitment in 2015 may have also caused 

lower estimates of growth rates in 2015 compared to 2016. 

6.2.1 Oceanographic Features that May Influence Barnacle Settlement and Growth

Cross-shelf patterns of temperature and salinity may have influenced barnacle settlement and growth. 

Temperature is known to be positively related to barnacle growth (Phillips 2005), but interaction between 

temperature and productivity may dampen or intensify their individual effects (Sanford and Menge 2001). 

In this study, temperature was highest offshore where there was lowest barnacle settlement and growth. 
119

Cross-shelf differences in plankton productivity may have overwhelmed the effects of temperature since 

differences between the most landward and seaward platforms were small (<2.4oC). Salinity also tended 

to increase with distance to shore. Salinity is one of the most important hydrographic features in 

determining species distributions (Gunter 1961), and it is possible that higher offshore salinity decreased 

suitability for barnacles. Barnacles are replaced by sponge and tunicate as the dominant fouling 

organisms as distance from shore increases (Lewbel et al. 1987), but sponge and tunicate were not 

typically found on settlement plates. Barnacles were found on the settlement plates furthest offshore, but 

their settlement and growth rates were minimal.

Cross-shelf patterns of total depth and turbulence (wave height) may have also influenced barnacle 

settlement and growth. Platforms 15–18 km from shore stood in waters with total depths of 7.6–8.2 m of 

total depth. Sand was found trapped between barnacles located on the 7m plates suggesting that sediment 

re-suspension had taken place. Barnacles at depth in this shoal environment may have benefited from the 

resuspension of microalgae and other organic matter accumulated at the sediment surface (Oviatt and 

Nixon 1975; Roman and Tenore 1978; Roman 1978). However, consistent declines in growth and 

settlement at 2m and at 7m further offshore suggest that the contribution of re-suspended organic matter 

was not a dominant factor for barnacles on platforms growth further offshore. Turbulence also tended to 

increase with distance to shore, and sheared off the 2m settlement plates at the six platforms furthest 

offshore (total of 18 plates). There is often a positive relationship between turbulence and barnacle 

growth (Crisp 1960; Bertness et al. 1991; Sanford and Menge 2001) and settlement (Bushek 1988; 

Bertness 1989), presumably because turbulence increases the encounter rate between barnacles and their 

prey as well as spat and settlement surfaces. However, high turbulence may decrease the ability of 

barnacles to capture prey by interfering with capture processes (Crisp 1955; Eckman and Duggins 1993), 

which may have contributed to lower barnacle growth offshore. 

6.3 Conclusions 

6.3.1 Implications of Barnacle Settlement Patterns for Artificial Reef Management

Higher barnacle settlement and growth in nearshore waters suggests that prolific nearshore primary and 

secondary production translated to increased production of fouling organisms at nearshore platforms. The 

difference between barnacle production at 2 and 7m is striking and supports the argument that the vertical 

dimension of platforms is an important aspect of their ecological value (Hernandez et al. 2003; Stanley 

and Wilson 2004; Reeves et al. 2017). Moreover, higher barnacle production at nearshore platforms 

suggest that nearshore platforms provide a different ecological function than those further offshore, and 

distance from shore should be considered as a part of artificial reef management plans. These are 

important considerations because only toppled platforms are considered for inclusion in Louisiana’s 

Artificial Reef Program (Kaiser 2006) and all platforms currently included in the program are in deeper 

waters than platforms studied here. It should also be noted that barnacle production at platforms is 

sometimes considered to be less important than primary production (see Daigle et al. 2013). However, 

without platforms, barnacles would undoubtedly be less common in Louisiana’s nearshore waters because 

there is no naturally occurring hard bottom substrate in this area (Parker et al. 1983). Thus, we consider 

the production of barnacles and other fouling organisms (stone crabs, amphipods etc.) on platforms as 

being an important characteristic of nearshore fouling communities.

Nearshore barnacle production may be an important aspect of the ecological function of platforms 

because barnacles are prey for commercially and recreationally important species, and barnacles feed on 

plankton in a region with excessive phytoplankton production and high zooplankton densities. Gray 

triggerfish (Balistes capriscus; Gallaway et al. 1981; Beaver et al. 2003; Daigle et al. 2013), sheepshead 

(Archosargus probatocephalus; Gallaway et al. 1981; Hoskin and Reed 1984; Sedberry 1987; Hernandez 

and Motta 1997), and black drum (Pogonias cromis; personal obs.) are known to feed on barnacles. 
120

Stone crabs (Menippe spp.) are also known to feed on barnacles (Powell and Gunter 1968; Gallaway et al. 

1981) and their abundances are positively associated with living barnacle densities on small platforms 

(Reeves et al. 2017). Barnacles are generalist filter feeders that prey upon a variety of organisms 

including phytoplankton and zooplankton (Barnes 1959), and may be an important trophic link between 

phytoplankton and tertiary consumers (Beaver 2002). Barnacle consumption of plankton and the 

subsequent energy transfer to fish and invertebrate biomass may be especially beneficial to the fishes that 

prey upon them in coastal Louisiana where the decomposition of plankton leads to the annual formation 

of the world’s second largest hypoxic zone (Turner and Rabalais 1991, 1994; Rabalais et al. 1996).
121

7 Sheepshead and Stone Crab Diets at Small Oil and Gas Platforms 

7.1 Introduction

Louisiana’s nearshore waters are a sea of paradox. Nutrient discharge from the Mississippi and 

Atchafalaya rivers fuels prolific primary production (Turner and Rabalais 1991, 1994; Dortch and 

Whitledge 1992; Rabalais et al. 1996), which results in high fisheries productivity (Gunter 1963). 

Louisiana accounted for 10.8% of all U.S. commercial fisheries landings by weight from 2006–2015 and 

was second only to Alaska (NMFS 2017). However, nutrient discharge from the Mississippi and 

Atchafalaya rivers also leads to the annual formation of coastal hypoxia (DO < 2 mg l-1

; Turner and 

Rabalais 1991, 1994; Turner et al. 2006b), which often spans 15,100 – 18,000 km2 (Obenour et al. 2013) 

and is considered the second largest hypoxic zone in the world (Rabalais et al. 2002). Hypoxia is known 

to decimate benthic communities (Dauer et al. 1992; Pihl 1994; Baustian and Rabalais 2009) and displace 

mobile organisms (Leming and Stuntz 1984; Renaud 1986; Craig and Crowder 2001, 2005; Craig et al. 

2005; Switzer et al. 2009, 2015; Craig and Bosman 2013). Paradoxically, this region is known both as 

“the Fertile Fisheries Crescent” (Gunter 1963) and “the Dead Zone” (Rabalais et al. 2002).

The nGOM’s hypoxic zone is often perceived as a homogenous area blanketed by hypoxia, but it is a 

dynamic area dotted with sand shoals and oil and gas platforms (platforms) that may provide refuge from 

hypoxia. Ship, Tiger, and Trinity shoals are within the area affected by hypoxia, but they tend to maintain 

oxygenated bottom waters when surrounding areas are hypoxic (Dubois et al. 2009; Gelpi et al. 2009; 

DiMarco et al. 2010; Craig and Bosman 2013; Munnelly 2016). These sand shoals may provide refuge 

from hypoxia for macrobenthic organisms (Dubois et al. 2009), blue crabs (Gelpi et al. 2009), and fishes 

(Craig and Bosman 2013; Reeves 2015; Munnelly 2016). There are also ~ 900 oil and gas platforms 

within the nearshore waters (< 15 m of water; BOEM 2015) where hypoxia occurs. Because platforms 

span from the seafloor to above the water surface, they provide hard bottom substrate in the oxygenated 

waters overlaying hypoxia. This substrate is colonized by barnacles and other organisms that develop 

diverse fouling communities (Gunter and Geyer 1955; Gallaway et al. 1981; Lewbel et al. 1987). 

Platforms in the hypoxic zone are known to support high abundances of stone crabs (Reeves et al. 2017) 

and reef-associated fishes (Stanley and Wilson 2004; Reeves et al. 2018b), but little is known about the 

consequences of hypoxia for reef-associated organisms living on and around platforms. 

Platforms on Louisiana’s continental shelf are de facto artificial reefs that attract high abundances of 

fishes (Shinn 1974; Duglas et al. 1979; Harville 1983; Stanley and Wilson 1991, 1997), but there is 

ongoing debate regarding their values as fish habitat. There is little naturally-occurring hard bottom 

habitat in the north-central GOM (2,571 km2 or 3% of substrate on the continental shelf from Pensacola, 

Florida to Pass Cavallo, Texas; Parker et al. 1983) and platforms accounted for an additional ~12 km2 of 

hard bottom substrate (Gallaway et al. 1998). The addition of artificial reefs may benefit populations that 

are limited by hard bottom substrate (Stone et al. 1979), but they may also reduce populations by 

aggregating fishes and making them more susceptible to fishing (Samples and Sproul 1985; Bohnsack 

1989). Debate over these two ideas has continued since their inception (Polovina 1991; Grossman et al. 

1997; Gallaway et al. 2009; Shipp and Bortone 2009; Cowan et al. 2011) and is often referred to as the 

attraction vs. production debate. Though the debate is often approached as only having two possible 

answers (artificial reefs attract or produce fish biomass), there is a spectrum of possibilities between 

complete attraction or production (Bohnsack 1989) and outcomes along this spectrum are undoubtedly 

species and location-specific. Understanding biological productivity and how artificial reefs function in 

different environmental conditions is key to resolving the attraction vs. production debate (Bortone 1998), 

and is receiving increased attention. 
122

In this chapter, we compare the feeding ecology of two reef-associated species–sheepshead (Archosargus 

probatocephalus) and Gulf stone crabs (Menippe adina)–during the early and late summer at platforms 

that experienced mild and intense hypoxia. We hypothesized that reef-associated organisms experiencing 

intense hypoxia would transition from bottom to platform-dwelling prey over the course of the summer, 

but those experiencing mild hypoxia would maintain consistent diets. Platforms were located on Ship 

Shoal (shoal platforms) and seaward of the shoal (seaward platforms) where they experienced mild and 

intense hypoxia, respectively. During this study the bottom surrounding seaward platforms was blanketed 

by ~3 m of hypoxia (DO < 2 mg l-1

) from June to late August/early September; whereas the bottom 

surrounding shoal platforms was typically well-oxygenated, but was briefly blanketed by ~ 1 m of 

hypoxia in late July (Reeves et al. 2018b). We compared diets of sheepshead and stone crabs during the 

early and late summer at platforms with mild (shoal platforms) and intense hypoxia (seaward platforms) 

using a combination of stable isotopes, δ13C, δ15N, and gut contents analyses. 

Sheepshead and stone crabs were studied because they are abundant at shoal and seaward platforms 

throughout the summer (Reeves et al. 2017, 2018b). Benthic invertebrates, including sessile and mobile 

organisms, are the most common prey of Sheepshead (Gallaway et al. 1981; Overstreet and Heard 1982; 

Sedberry 1987) and stone crabs (Bender 1971), and Sheepshead are known to forage on platformdwelling prey (Chapter 5). Both species support commercial fisheries in the GOM, and mean annual 

landings from 2006 – 2015 were 601 metric tons for sheepshead and 2,112 metric tons of stone crab 

claws (Menippe adina + Menippe mercenaria); however, these organisms are not fished at platforms. 

While 73% of GOM sheepshead were landed in Louisiana, only 0.04% of stone crabs were landed in 

Louisiana (99.7% landed in Florida, NMFS 2017). Sheepshead in the nGOM can live up to 20 years 

(Beckman et al. 1991) and spawn from February to April (Render and Wilson 1992). Stone crabs can live 

up to 8 years (Gerhart and Bert 2008) and spawn from April to May (Wilber 1989). Cuban stone crabs 

(Menippe nodifrons) and Gulf stone crabs are both found at shoal and seaward platforms (Reeves et al. 

2017), but this study focused on Gulf stone crabs.

7.2 Methods

7.2.1 Study Area and Field Sampling

Samples were collected for stable isotope and gut contents analyses during the early (May 31–July 20) 

and late summer of 2016 (August 19–September 11) at shoal and seaward platforms (Figure 52; Table 

30). Broad time categories were used for the early and late summer because the benthos are not 

significantly affected until roughly one month after the development of hypoxia (Baustian and Rabalais 

2009), and hypoxia formed during June in our study area (Reeves et al. 2018b). Seaward platforms were 

7.5 – 15.5 km southwest of shoal platforms, and water depths were 14.8 ± 0.52 (mean ± SE) at seaward 

and 7.9 ± 0.38 m at shoal platforms. Sampling efforts focused on small platforms (≤ 4 pilings) because 

they represent > 90% of all platforms in the study area (BOEM 2015). 

Sheepshead, stone crabs (Menippe adina), barnacles (Amphibalanus spp.), platform associated macro 

algae, and sediment were collected from 14 platforms. Sheepshead were collected at platforms adjacent 

to those where stone crabs, barnacles, algae, and sediment were collected to avoid biasing concurrent 

studies of Sheepshead abundances and grazing behaviors. Sheepshead were collected using hook and line 

sampling and spears, Stone crabs, barnacles, and macro algae were collected from the platform’s main 

piling, and divers skimmed surface sediment from the bottom ~4.0 m away from the platform. 

Sheepshead were measured [mm fork length (FL)] and weighed (g), and guts were extracted. Stone crabs 

were measured [mm carapace width (CW)] and weighed (g). Sheepshead, barnacles, stone crabs, macro 

algae, and sediment were frozen at ~ –18oC and sheepshead guts were preserved in 10% formalin. 
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Figure 52. Map of study area. 

Note: Black circles denote platforms where sheepshead were sampled and black diamonds denote platforms where 

prey (platform-associated macro algae, barnacles, sediment) and stone crabs were sampled.

7.2.2 Gut Contents Analysis

Gravimetric gut contents analysis (Carr and Adams 1972) was used to characterize sheepshead diet. Prey 

were removed from the entire digestive tract, dyed with Rose Bengal, and washed through a stack of four 

sieves (4000, 2000, 1000, 500 μm). Prey were then sorted into the following categories: macro algae, 

Amphipoda, Balanidae, Bryozoa, Menippidae, Muricidae, Nassariidae, Ostreidae, Panaeidae, Polychaeta, 

Portunidae, sediment, Squillidae, unknown, Veronidae, and Xanthidae. All prey in the 4000 and 2000 μm 

sieves were characterized, and 25% from the 1000 and 500 μm sieves were randomly subsampled and 

used to characterize the prey. Prey were dried for 12 hours at 70oC and weighed to the nearest 0.001 g. 

Dry weights were used to calculate percent composition of each prey item. 

7.2.3 Stable Isotopes Sample Preparation and Analysis

Analyses of δ13C and δ15N were performed on sheepshead liver and muscle, stone crab claw muscle, 

barnacle muscle, algae, and sediment. Slow and fast turnover tissues (liver and muscle, respectively) 

were utilized for sheepshead because they are thought to migrate offshore from inshore waters during the 

cooler months (Springer and Woodburn 1960; Jennings 1985; Tremain et al. 2004), and thus slower 

turnover tissue may not reflect offshore diets in the early summer. Three stone crabs and 5–10 barnacles 

were randomly subsampled from each collection (12 total collections). Muscle was extracted from stone 

crab claws, beneath barnacle moveable plates (retractor muscle), and from sheepshead epaxial muscle. 

The entire sheepshead liver was extracted. Stone crab and sheepshead tissues were analyzed separately, 

but barnacles were pooled from each collection to obtain sufficient material for analyses. Stone crab 

muscle, barnacle muscle, and algae were then cleaned of shell fragments and other debris under a 

dissecting microscope. All samples (sheepshead liver and muscle, stone crab muscle, barnacle muscle, 

algae, sediment) were dried in an oven at 60oC for 24 hours, and were ground into a fine powder using a 

mortar and pestle. Barnacle muscle, algae, and sediment were acid fumigated under vacuum in glass 
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dishes for 72 hours using concentrated HCl to remove carbonates (Harris et al. 2001), and were then dried 

for an additional 24 hours. We encapsulated 1.25 mg of sheepshead liver and muscle, stone crab muscle, 

and barnacle muscle; 3.0 mg of algae; and 60 mg of sediment in tin capsules. Encapsulated samples were 

sent to UCD-SIF and analyzed for δ13C and δ15N using a PDZ Europa ANCA-GSL (automated nitrogen 

carbon analyzer- gas solids and liquids) elemental analyzer (UC-SIF 2017). Stable isotope values were 

expressed as δ (‰) and calculated with the following:

δ X = {[(Rsample / Rstandard) – 1] x 1000}

where X is 13C or 15N, Rsample is 13C / 12C or 15N / 14N of the sample, and Rstandard is 13C / 12C or 15N / 14N of 

the standard. Vienna PeeDee Belemite and atmospheric N2 were the standards for δ13C and δ15N, 

respectively.

Table 30. Number of sheepshead and stone crabs, whether platform associated macro algae, 

barnacles, and sediment (sources) where collected, and number of platforms where sheepshead 

and benthos (stone crabs, platform associated algae, barnacles, sediment) were collected at shoal 

and seaward platforms (Sea) in 2016. 

Date Sheepshead

(Shoal, Sea)

Stone Crabs

(Shoal, Sea)

Sources

(Shoal, Sea)

Sheepshead 

Platforms

(Shoal, Sea)

Benthos Platforms

(Shoal, Sea)

May 31 14, 0 3, 3 Y, Y 2, 0 1, 1

Jun 27 4, 9 3, 3 Y, Y 1, 2 1, 1

Jul 20 0, 0 3, 3 Y, Y 0, 0 1, 1

Aug 19 0, 8 0, 3 N, Y 0, 2 0, 1

Aug 21 0, 0 0, 3 N, Y 0, 0 0, 1

Sep 7 0, 0 6, 0 Y, N 0, 0 2, 0

Sep 11 9, 0 3, 3 Y, Y 2, 0 1, 1

Y=Yes, N=No. Dates denote the date in 2016 when samples in individual rows were collected.

7.2.4 Statistical Analyses

A combination of frequentists and Bayesian statistical methods were used to analyze data. Frequentists 

methods were used for analyses of sheepshead and stone crab biometrics, sheepshead gut contents, and 

stable isotopes of sources. Bayesian methods were used for analyses of sheepshead and stone crab stable 

isotopes. The reported measure of error was one standard error for frequentist and the 95% credible 

interval for Bayesian analyses. A significance level of 0.05 was utilized and significance levels for posthoc comparisons following ANOVAs were corrected using Tukey-Kramer adjustments (Day and Quinn 

1989). Individual sheepshead and stone crabs were treated as the sampling unit for comparisons of their 

diets and biometrics. The absence of a relationship between sheepshead and stone crab sizes vs. δ13C and 

δ15N suggested there was no need to correct isotope data for size (e.g. Sweeting et al. 2007a, 2007b). We 

also found no relationship between C:N ratios of sheepshead and stone crabs to δ13C, which suggested 

there was no need to correct for lipids (Post et al. 2007). 

Stone crab CW and weight, sheepshead FL and weight, and number of prey types (Richness) and 

Shannon-Weiner diversity (Diversity) of sheepshead gut contents were compared across location (shoal 

compared to seaward) and time (early compared to late) with generalized linear models (GLM; Proc 

Glimmix, SAS 9.4). Location, time, and location-by-time interaction were main effects for all GLMs, 

and a size covariate was included for Richness, Diversity, and weights of sheepshead and stone crabs. 

Richness was assumed to follow a Poisson distribution with a log-link, Diversity was assumed to follow a 

gamma distribution with a log-link, and length and weight were assumed to follow normal distributions. 
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Permutational MANOVA (PERMANOVA; Anderson 2001; PRIMER 7) and distance based redundancy 

analysis (dbRDA; McArdle and Anderson 2001; PRIMER 7) were used to analyze composition of gut 

contents. The PERMANOVA and dbRDA were run on a Bray-Curtis similarity matrix based on the 

log(X+1) percent contribution. The PERMANOVA included location, time, location-by-time interaction 

and a FL covariate as main effects. Loadings for the dbRDA were then plotted in bivariate space, and a 

vector overlay was added to display the associations of individual prey types with dbRDA axes. The 

PERMANOVA and dbRDA only included prey types that occurred in >15% of all samples, and 

Menippidae and Xanthidae were pooled into their super-family Xanthoidea to meet this criterion. 

Trophic breadth analyses of sheepshead and stone crabs were performed using the SIBER procedure 

(Jackson et al. 2011; R 3.4.1). Bayesian SIBER ellipse areas were calculated for each location-by-time 

combination (Early Shoal, Early Seaward, Late Shoal, Late Seaward). SIBER ellipses were plotted in 

bivariate δ13C and δ15N space and were scaled as 95% credible ellipses, which are interpreted as 95% 

credible intervals.

Bayesian mixing-models of δ13C and δ15N were used to estimate the contribution of sources [barnacles, 

filamentous algae, sediment, sea lettuce (Ulva spp.)] to sheepshead liver, sheepshead muscle, and stone 

crab muscle using the SIMMR procedure (Parnell et al. 2010; R 3.4.1). Exploratory GLMs were 

performed on sources to compare isotopic values across location, time, and source type to determine 

groupings. Barnacles were used as a proxy for water column particulate organic matter (WPOM) because 

they are filter feeders and their isotopic signatures capture long-term isotopic variability (Nerot et al. 

2012; Lorrain et al. 2015). The SIMMR procedure was used to incorporate variability resulting from 

enrichment of δ13C and δ15N at higher trophic levels (Parnell et al. 2010). Trophic enrichment factors 

were designated as 1.3 ± 1.3 (mean ± SD) for δ13C and 2.9 ± 1.24 for δ15N (McCutchan et al. 2003). 

Mixing-models for early and late summer were run separately because of the substantial differences in 

δ15N (see results) and since early summer consumers cannot consume late sources. All early mixingmodels only considered early sources. Late mixing-models for sheepshead muscle and stone crabs 

considered all sources (early and late) because white muscle is a slow turnover tissue (Tieszen et al. 1983; 

Hesslein et al. 1993; Logan et al. 2006) that likely reflected the entire summer. However, we only 

considered late sources for Sheepshead liver because liver quickly turns over (Tieszen et al. 1983; 

Hesslein et al. 1993; Logan et al. 2006), and it was unlikely that sources from the early summer made a 

substantial contribution to liver isotope composition in the late summer.

Differences between δ13C and δ15N of sheepshead muscle and liver were visualized using a vector plot. A 

vector plot of muscle and liver was created where the muscle was treated as the start value and liver was 

the end value. Vector plots can be used to visualize the differences between past and present feeding by 

comparing tissues with fast (liver) and slow (muscle) turnover times, and can also be used to make 

inferences about migration history (Gelpi et al. 2013). Separate vector plots were created for the early 

and late summer and were overlaid with triangles connecting the three most extreme values of the 95% 

credible intervals of sources (mixing space).

7.3 Results

7.3.1 Sheepshead and Stone Crab Biometrics

There were no significant differences for either sheepshead or stone crab sizes and weights across 

location and time. Mean (± SE) sheepshead FL (341.5 ± 5.71 mm, range: 265 – 440) and weight (1018.0 

± 41.82 g, range: 425 – 1650) were not significantly related to location (FL: F1,39 = 0.7, P > 0.416; weight: 

F1,38 = 0.8, P > 0.367), time (FL: F1,39 = 0.5, P > 0.485; weight: F1,38 = 1.0, P > 0.313), or their 

interaction (FL: F = 1.3, P > 0.269; weight: F1,38 = 1.9, P > 0.173), but length was significantly associated 

with weight (F1,38 = 433.7, P < 0.001). Similarly, mean stone crab CW (46.4 ± 1.96 mm, range: 25 – 70) 
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and weight (40.4 ± 4.93 g, range: 5 – 119) were not significantly related to location (FL: F1,32 = 3.7, P > 

0.062; weight: F1,31 = 0.2, P > 0.663), time (FL: F1,32 = 0.0, P > 0.872; weight: F1,31 = 2.3, P > 0.14), or 

their interaction (FL: F1,32 = 2.0, P > 0.162; weight: F1,31 = 0.0, P > 0.868), but CW was significantly 

associated with weight (F1,31 = 404.0, P < 0.001). 

7.3.2 Sheepshead Gut Contents

Organisms from 17 taxonomic groups were identified in sheepshead guts (Table 31). The most abundant 

organisms were barnacles (Balanidae), which occurred in 96% of all samples and represented 64.1% ± 

5.49 of prey by weight in sheepshead guts. All guts contained some unidentified content, but mean 

unidentified content was only 5.8% ± 1.09. All guts contained identifiable prey. 

Diversity of sheepshead gut contents was consistent at shoal platforms and declined at seaward platforms 

from early to late summer, but Richness did not change across location or time. GLMs indicated there 

was a significant location-by-time interaction for diet Diversity (F1,39 = 6.8, P < 0.013), which suggested 

that there was divergence of sheepshead diet at shoal and seaward platforms. However, there was no 

significant effect of location (Z = 3.6, P > 0.059), time (Z = 0.3, P > 0.565), or their interaction (Z = 1.0, 

P > 0.323) on diet Richness (overall mean: 4.2 ± 0.24). Post-hoc comparisons of diet Diversity indicated

that LS means were similar at shoal and seaward platforms early in the summer (0.5 ± 0.15 vs. 0.5 ± 

0.11), but seaward platforms had significantly lower diet Diversity than shoal platforms during the late 

summer (0.1 ± 0.03 vs. 0.5 ± 0.14). There was no significant effect of FL on diet Richness (Z = 0.2, P > 

0.656) or Diversity (F1,39 = 0.1, P > 0.811).

The composition of prey in sheepshead guts changed across location and time. The PERMANOVA 

indicated that there was a significant location-by-time interaction (Pseudo-F1,39 = 2.9, P < 0.034) on prey 

composition, but there was no significant effect of size (Pseudo-F1,39 = 2.3, P > 0.063). However, 

PERMDISP (distance-based test for homogeneity of multivariate dispersions; Anderson 2006) indicated 

that the assumption of homogenous variances was violated and that differences were in-part driven by 

heteroscedasticity (location-by-time: F3,40 = 11.4, P < 0.001). The dbRDA explained 71.4% of the 

differences in diet composition (Figure 53) and corroborated the findings of the PERMANOVA and 

PERMDISP. Dispersion of diet composition was generally higher during the early summer than it was in 

late summer, and dispersion during the late summer at seaward platforms was substantially smaller than 

other location-by-time combinations. During the early summer Portunidae, Nassariidae, Bryozoa and 

Balanidae made greater contribution to diet composition at shoal platforms, whereas Squillidae and 

Xanthoidea made greater contributions at seaward platforms. During the late summer, diet composition 

in both locations was dominated by Balanidae. 
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Table 31. Mean percent composition, standard error, and percentage of guts where individual 

prey items occurred for all sampled sheepshead. 

Prey Mean Percent 

Composition

SE Percent 

Occurrence

Balanidae 64.1 5.49 96

Portunidae 9.9 3.74 27

Squillidae 7.3 3.44 18

Unknown 5.8 1.09 100

Nassariidae 2.6 1.76 32

Menippidae 2.3 1.06 25

Bryozoa 1.5 0.47 61

Sediment 1.4 0.60 39

Algae 0.8 0.26 32

Xanthidae 0.5 0.34 14

Panaeidae 0.4 – 7

Unidentified Crab 0.4 – 5

Amphipoda 0.3 0.16 25

Ostreidae 0.2 0.11 16

Muricidae 0.1 0.06 15

Veneroidae 0.1 0.05 11

Polychaeta <0.1 – 5
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Figure 53. Distance based redundancy analysis (dbRDA) showing the similarity of sheepshead prey at shoal 

and seaward platforms during the early and late summer.

Note: Prey items were plotted when Pearson correlations between dbRDA axes 1 and 2 were greater than 0.15, and 

the radii are scaled to the plotted circle of radius 1.0 (perfect correlation).

7.3.3 Dispersion of δ13C and δ15N Values for Sheepshead and Stone Crab

SIBER ellipses of consumers’ δ13C and δ15N values showed overlap across time and location, but there 

was broader dispersion of early consumers at shoal platforms than all other location-by-time groupings. 

SIBER ellipses of sheepshead muscle and stone crab showed broad overlap of δ13C and δ15N values, but 

sheepshead liver showed substantial enrichment in δ15N in the late summer relative to the early summer 

(Figure 54). Stone crab had the smallest SIBER ellipse areas, sheepshead muscle had the largest, and 

sheepshead liver ellipse areas were intermediate (Figure 55). Though overlap of 95% credible ellipses 

indicated this trend was mostly insignificant, early consumers at shoal platforms tended to have greater 

ellipse areas than all other location-by-time combinations (early seaward, late shoal, late seaward). 

Though no sheepshead sex-specific isotopic differences were observed, δ15N for stone crab females was 

more enriched than males. This difference explains the high degree of δ15N variance observed for stone 

crabs, but we lacked sufficient sample sizes to analyze the sexes separately.
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7.3.4 Patterns of Source δ13C and δ15N Values and Groupings for Mixing-Models

Mixing-model sources were grouped as filamentous algae (red algae, brown algae, green algae), sea 

lettuce, barnacles, and sediment, pooled across both locations, and means were calculated separately for 

early and late summer. Since δ13C of all filamentous algae was similar (Table 32), they were pooled as a 

single source, but it should be noted that filamentous algae consisted of unidentified red algae in the early 

summer and green and brown algae in the late summer. GLMs indicated that there was no significant 

effect of location for δ13C (F1,4 = 0.2, P > 0.652) and δ15N (F1,4 = 2.5, P > 0.191), so sources were pooled 

across location. δ13C values of individual sources were comparable during the early and late summer (F1,5

= 3.2, P > 0.133), but a significant effect of time for the δ15N (F1,5 = 7.0, P < 0.047) suggested there was 

δ15N enrichment in the late summer. Due to broad isotopic overlap of barnacles and filamentous algae, 

they were combined using the “combine_sources” function in SIMMR.

Figure 54. Sheepshead liver (A), sheepshead muscle (B), and stone crabs (C) in bivariate δ13C and δ15N with 

overlaid SIBER ellipses. 

SIBER ellipses are denoted by solid and dashed lines and represent a 95% confidence ellipse, which are interpreted 

as 95% confidence intervals (i.e. overlapping ellipses are not significantly different).
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Figure 55. Estimates of the standard ellipse areas for sheepshead liver (A), sheepshead muscle (B), and 

stone crabs (C). 

Note: Black bars denote sheepshead at seaward platforms and grey bars denote shoal platforms. Error bars 

represent the 95% credible interval.

7.3.5 Mixing Models

Mixing-models for sheepshead liver and stone crab showed that platform-associated fauna were the 

primary source of prey, but no mixing model was run for sheepshead muscle because isotope values were 

well outside the mixing space of sources (Figure 56C–D). Sheepshead liver (Figure 56A–B) and stone 

crab muscle isotope values (Figure 57A–B) were well constrained within the mixing space of their 

respective sources. Source contributions to Sheepshead liver were similar across location and time 

(Figure 58A–B), with barnacles/filamentous algae making the largest contribution (means of 79.2–

83.0%), sea lettuce making the lowest contribution (means of 5.4 – 6.5%), and sediment making an 
131

intermediate contribution (means of 9.8–16.6%). Source contributions to stone crabs were similar across 

location and time (Figure 58C–D), with barnacles/filamentous algae making the largest contribution 

(means of 67.7–76.5%), sediment making the lowest contribution (means of 2.8–4.2%), and sea lettuce 

making an intermediate contribution (means of 19.8–27.9%). For all mixing-models, the 95% credible 

intervals of barnacles/filamentous algae did not overlap with sediment and sea lettuce, but there was 

broad overlap between sediment and sea lettuce. There were no significant differences between the early 

and late summer.

Table 32. δ13C, SE (standard error) of δ13C, δ15N, SE of δ15N, and sample sizes (n) of filamentous 

algae (red algae, green algae, brown algae), sea lettuce, barnacles, and sediment collected in the 

early (May 31 – Jun 20) and late (Aug 19 – Sep 11) summer of 2016. 

Source δ13C SE δ15N SE n

Early

Red algae –19.6 1.83 8.8 0.03 3

Sea lettuce –15.4 0.89 8.4 0.04 3

Barnacles –18.5 0.15 10.9 0.42 6

Sediment –23.8 0.68 5.2 2.01 5

Late

Brown algae –20.5 0.15 10.6 0.01 4

Green algae –20.0 0.90 10.2 0.42 2

Barnacles –19.1 0.14 12.9 0.17 6

Sediment –24.7 1.10 4.8 1.75 6

Note: Brown and green algae were not collected during the early summer, and sea lettuce and red algae 

were not collected during the late summer.
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Figure 56. Sheepshead liver during the early (A) and late summer (B), and sheepshead muscle in the early 

(C) and late summer (D) plotted in bivariate δ13C and δ15N along with values of sources (sea lettuce, 

barnacles, sediment, filamentous algae). 

Note: Values of sources shown here are corrected for trophic enrichment.
133

Figure 57. Mixing-models for early (C) and late sheepshead liver (D) showing the percent contribution of 

sources to sheepshead diet. 

Black bars denote sheepshead at seaward platforms and grey bars denote shoal platforms. Error bars represent the 

95% credible intervals.

The vector plots of sheepshead muscle and liver indicated large discrepancies between the two types of 

tissue in the early summer and smaller discrepancies in the late summer (Figure 59). Mean (± SE) 

distance between δ13C and δ15N of muscle and liver decreased from 2.81 ± 0.26 ‰ in the early summer to 

2.0 ± 0.21 ‰ in the late summer. The largest differences in the early summer (Figure 59A) resulted from 

muscle that was more depleted in δ13C and enriched in δ15N than the corresponding liver. There were 

also differences between muscle and liver during the late summer but differences were variable and there 

was no clear pattern (Figure 59B). Liver δ13C and δ15N tended to fall within the mixing space, whereas 

muscle values were more variable and were often outside of the mixing space. 
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7.4 Discussion

7.4.1 Early and Late Summer Feeding Ecology

These findings indicated that hypoxia may have briefly affected the diet of sheepshead associated with 

platforms, but the effects were not detectable using stable isotopes and were not necessarily negative. 

Hypoxia is known to decimate the benthos in nearshore Louisiana (Gaston 1985; Baustian and Rabalais 

2009), and we expected that this reduction of macrobenthic biomass would result in a transition from 

bottom to platform-dwelling prey. However, we found there was no detectable effect of hypoxia on 

stable isotope composition, and there was an episodic increase in consumption of bottom-dwelling prey 

soon after the formation of hypoxia. 

Stable isotope mixing-models of sheepshead livers and stone crabs showed there were no differences 

across location (shoal compared to seaward) or time (early compared to late summer), and thus, no 

detectable effect of the presence of hypoxia on isotopic composition. Our finding is consistent with a 

previous study that found no effect of hypoxia on δ13C and δ15N values of Atlantic croaker 

Micropogonias undulatus (Mohan and Walther 2016). However, a key difference is that though Atlantic 

croaker maintained a benthic isotope signal (Mohan and Walther 2016), sheepshead livers and stone crabs 

maintained a high dependence on barnacles (proxy for WPOM)/filamentous algae throughout the 

summer. It is also possible that changes were not detected for stone crabs because claw muscle slowly 

turns over (Gelpi et al. 2013); although it is unlikely that stone crabs would have switched from platform 

to bottom-dwelling prey in the late summer since stone crabs are not typically observed on the bottom 

during the late summer in this area (Reeves et al. 2017).

Sheepshead gut contents analyses suggested that fishes at seaward platforms exploited large amounts of 

benthic prey soon after the formation of hypoxia, and that diet Diversity was stable at shoal platforms and 

declined at seaward platforms. Approximately 78% of sheepshead at seaward platforms contained mantis 

shrimp (Squillidae), which made up 35.2 ± 13.56% of their stomach contents. Sheepshead at seaward 

platforms had benthic diets primarily consisting of mantis shrimp in the early summer and barnacles 

(Balanidae) in the late summer. Sheepshead have been observed to feed on mantis shrimp (Overstreet 

and Heard 1982), but they are not reported as common prey (Overstreet and Heard 1982; Sedberry 1987). 

High consumption of mantis shrimp corresponded to the development of hypoxia at seaward platforms 

(mid - late June; Reeves et al. 2018b). Fishes are known to exploit benthic organisms that succumb to 

hypoxia (Pihl et al. 1992), but this was likely an episodic event since the change in gut contents was not 

corroborated by stable isotope analyses. A strong decline in the diet Diversity of sheepshead at seaward 

platforms could indicate that diets become restricted at seaward platforms, but consistent SIBER ellipses 

during the early and late summer at seaward platforms suggest similar relative contributions of basal 

resources. Decreases to Diversity were partly driven by decreased predation on stone crabs. Stone crabs 

suffer hypoxia-related mortality on the bottom and on platform substrate below the oxycline (Reeves et al. 

2017), so higher sheepshead consumption of stone crab in the early summer may also suggest an effect of 

hypoxia. However, because stone crabs were observed to rely mostly on barnacles/filamentous algae as 

prey, this shift would not have been apparent from stable isotopes alone. 
135

Figure 58. Stone crabs during the early (A) and late summer (B) plotted in bivariate δ13C and δ15N along with 

values of sources (sea lettuce, barnacles, sediment, filamentous algae), and mixing-models for early 

(C) and late stone crabs (D) showing the percent contribution of sources to stone crab diet. 

Note: Values of sources shown here are corrected for trophic enrichment. Black bars denote Sheepshead at seaward 

platforms and grey bars denote shoal platforms. Error bars represent the 95% credible intervals.
136

Figure 59. Vector plots showing δ15N and δ13C of sheepshead muscle and liver in the early (A) and late 

summer (B).

Note: The δ15N and δ13C of muscle is denoted by the black and grey circles and the δ15N and δ13C of the 

corresponding liver is denoted by the point of the arrow. The dashed line denotes the area of sources (sea lettuce, 

barnacles & filamentous algae, sediment) from each time period.

7.4.2 Contribution of Platform-Dwelling Prey to Sheepshead and Stone Crab Diets

Stable isotopes and gut contents analyses suggested that sheepshead and stone crabs fed upon a variety of 

prey associated with platforms. Because sheepshead liver and stone crab isotope values implied a strong 

connection to barnacles/filamentous algae and to a lesser degree, sea lettuce, we consider platform 

associated algae and filter feeders as important components of their diets. It is possible that some bottomdwelling filter feeders contributed to the strong barnacles/filamentous algae signal. However, bottom-
137

dwelling filter feeders should have different δ13C signals than barnacles/filamentous algae, because δ13C 

of bottom-dwelling filter feeders is known to differ from WPOM (Grippo et al. 2011). Because 

sheepshead and stone crab isotope values were tightly clustered around barnacles/filamentous algae and 

bottom-dwelling filter feeders were uncommon in sheepshead guts, it is likely that platform-dwelling prey 

were the dominant resource. Moreover, barnacles represented ~ 64% of all sheepshead gut contents and 

past studies indicated that barnacles are common prey of sheepshead (Hoskin 1980; Gallaway et al. 1981; 

Overstreet and Heard 1982; Hoskin and Reed 1984; Sedberry 1987; Hernandez and Motta 1997; Lenihan 

et al. 2001) and stone crabs (Powell and Gunter 1968; Gallaway et al. 1981). Recent research has begun 

to evaluate the magnitude and importance of secondary production at artificial reefs (Daigle et al. 2013; 

Claisse et al. 2014; Cresson et al. 2014a, 2014b; Champion et al. 2015; Reeves et al. 2018). Though

secondary production on artificial reefs is important to some reef associated organisms, it does not benefit 

all fishes through direct trophic links to platforms (Cowan and Rose 2016).

7.4.3 Potential for Contribution from Benthic Microalgae

Benthic microalgae (BMA) were not extracted in these analyses and while it may have contributed to 

sheepshead and stone crab diets, its contribution could have been masked by other sources included in the 

analyses. BMA are abundant on the shoal (Baustian et al. 2011) and their biomass is thought to exceed 

the overlying phytoplankton biomass (Grippo et al. 2010). BMA may contribute 53.4 – 83% and 14.5 –

47.7% to the carbon in macroinfauna on and off the shoal, respectively (Grippo et al. 2011). The δ15N 

and δ13C of BMA is indistinguishable from sediment isotopes off the shoal throughout the year and on the 

shoal during spring and summer (Gelpi et al. 2013). Due to the broad overlap of sediment and BMA, we 

interpreted contributions of sediment as a general benthic source that represents BMA, settled 

phytoplankton, and other organic materials in the surface sediment. Gelpi et al. (2013) reported 

substantial differences between BMA and sediment in the autumn when BMA was more enriched in δ13C 

than sediment. The δ13C values we observed for sea lettuce broadly overlapped with those reported for 

autumn BMA by Gelpi et al. (2013). The lack of a notable contribution of sea lettuce in the late summer 

suggests that either sediment and BMA had not diverged, or that BMA was not making a meaningful 

contribution to sheepshead liver chemistry. Sea lettuce was observed to make a substantial contribution 

to stone crabs in the late summer (19.8 – 27.9%), and it is possible that enriched BMA was contributing 

to this signal; however, it is unlikely that stone crab claw muscle had sufficiently turned over to reflect 

this signal.

7.4.4 Evidence of Sheepshead Migration

Discrepancies between the δ13C and δ15N in sheepshead livers and muscle in the early summer plus the 

convergence of values in the late summer suggests that some sheepshead migrated from outside of the 

study area before we began sampling. Mean distance between the δ15N and δ13C of liver and muscle 

modestly converged from the early to late summer. Convergence seemed to be partly driven by increased 

δ15N, which may have resulted from higher temperatures during the late summer (e.g. Goering et al. 

1990), differences in Mississippi River discharge, and/or higher nitrogen cycling in the benthos associated 

with hypoxia (e.g., Fry 2011). However, the largest discrepancies between liver and muscles for 

sheepshead in the early summer were fish that had muscle depleted in δ13C and enriched in δ15N relative 

to liver, which is suggestive of estuarine to seaward movement. Organisms in Louisiana’s inshore waters 

tend to be depleted in δ13C and enriched in δ15N (Fry 2002) relative to those in offshore waters (Fry 

2011). A similar pattern of δ15N and δ13C discrepancies and eventual convergence of fast and slow 

turnover tissues was previously observed for blue crabs on the shoal following their seaward migration 

from coastal marshes (Gelpi et al. 2013). Offshore movement of sheepshead is thought to correspond 

with seasonal movement in the early autumn for overwintering (Jennings 1985) or spawning (Springer 

and Woodburn 1960; Tremain et al. 2004), which occurs from February to April (Render and Wilson 

1992). Though it is possible that sheepshead migrated from inshore waters in the preceding winter and 
138

spring, it is likely that some were offshore residents because we previously observed sheepshead at 

nearby platforms throughout the year (D. Reeves, Unpublished Data).

7.5 Conclusions

This chapter underscores the importance of platform-dwelling primary and secondary producers as prey. 

This is a timely finding because Sheepshead and stone crabs are common on nearshore platforms where 

barnacle production is substantially higher than it is further offshore (Reeves et al. 2018), yet nearshore 

platforms are rapidly being removed as oil and gas exploration shifts further offshore (43% reduction 

since 2006; BOEM 2015). These findings suggest that barnacles and other secondary producers on 

nearshore platforms may be funneling pelagic production into sheepshead and stone crab biomass in a 

region where excessive phytoplankton production is known to fuel hypoxia (Turner and Rabalais 1991, 

1994; Rabalais et al. 1996). This process may facilitate the transfer of some of the excessive primary 

production to a select group of commercially valuable species, which represents a unique ecosystem 

service provided by the fouling communities on platforms in the Gulf. 
139

8 Notable Observations On and Around Small Energy Platforms in 

the Northern Gulf of Mexico

When placed in the marine environment, oil and gas infrastructure, such as pipelines and platforms, 

constitute a unique form of artificial reef. Oil and gas platforms (platforms) serve as de facto artificial 

reefs in the Northern Gulf of Mexico (nGOM) (Stanley and Wilson 1989) and are productive fishing sites 

where many reef-associated fishes reside and are captured (Stanley and Wilson 1990). It should be 

emphasized that platforms are a unique form of artificial reef because platforms extend from the sediment 

surface up through the entire water column into the air. Much as ecosystems provide services to human 

populations, human-made objects, such as oil platforms, can provide ecosystem services to marine biota 

and aquatic communities as substrate and shelter. When offshore structures are placed in coastal 

environments they immediately provide an object that attracts fishes (the FAD effect) and within days can 

be colonized by fouling organism such as algae, oyster and barnacle larvae. Platforms also aggregate 

large fish assemblages (Shinn 1974; Stanley and Wilson 1989, 1991). Within weeks of placement, the 

fouling can develop to the point where it can be colonized by other biota, such as amphipods, crab 

megalopae and polychaete larvae. Within months, the fouling develops sufficiently to provide structural 

habitat for blennies (Blenniidae), pistol shrimp (Alpheidae), stone crabs (Menippe spp.; Gallaway et al. 

1981) and other fauna. Both macro and micro algae (Figure 61A,B,C) can be seen growing on these 

structures within the photic zone and in the splash zone of the platform legs (Figure 61A,B), but it is 

unclear the extent of this production or at what rates it is exploited by fishes and other aquatic organisms. 

Platforms are widely regarded as important habitat for fishes (Bull and Kendall 1994; Hernandez et al. 

2003; Gallaway et al. 2009; Claisse et al. 2014; Cowan and Rose 2016; Reeves et al. 2017, 2018b) and 

other organisms (Galloway 1981; Reeves et al., 2018a). However, the influence of platforms on fishery 

production and foodchain pathways has been widely debated (Shipp and Bortone 2009; Cowan et al. 

2011; Daigle et al. 2013; Claisse et al. 2014), in part because they are a unique form of artificial reef that 

function in ways that most artificial reefs cannot. 

Fixed platforms within the northern nGOM range in size from small, single-piling caissons and well 

protectors to large, fixed platforms with production facilities and crew quarters. In this study we visited 

hundreds of small platforms and took a picture of each one (see Figure 3 for examples). Small, shallowwater (<50 ft.) platforms accounted for approximately 32% of all platforms in the nGOM during 2013 

when this study began. However, this kind of oil production structure has been under-represented in past 

scientific evaluations of platforms in the nGOM. We were compelled to evaluate these structures as fish 

habitat for a variety of reasons that included the fact that small, shallow-water platforms off Louisiana’s 

coast occupy a region of dynamic hydrography, and their relative importance as artificial reef habitat 

undoubtedly varies across substrate, depth, and the degree of freshwater influence. What we learned 

during these studies is that these structures provide habitat to a variety of organisms beyond the fishes 

attracted to them and in some cases in unusual ways. 

The principal goal of this study was to document the use of small platforms as recruitment sites and 

habitat for juvenile reef associated fishes with emphasis on snappers (Lutjanidae). This final chapter is 

focused on describing some of the unusual observations we made while conducting those studies and to 

highlight some of the other services small structures provide to biota within the nearshore coastal zone. 

Because these observations were not the principal focus of our efforts we cannot present them in a 

quantitative framework. Nevertheless they were important enough to describe these observations in a 

picture and written format and to make note of the fact that HD videos of these observations are available 

as noted below and described in this chapter. 
140

8.1 Association of Stone Crabs with Small Platforms

Figure 60. Use of platform fouling community and platform structure by stone crabs.

Although stone crabs were not readily visible on the drop cam array videos, divers observed stone crabs 

of all size and states of maturity on small platform throughout the nearshore coastal zone off Louisiana. 

Every platform we sampled within the nearshore zone had stone crabs colonizing the structure. In many 

cases the densities of stone crabs was as high as numbers reported on inshore reefs. We completed a 

focused study of their use of platforms in the Ship Shoal area and observed that they tended to be more 

abundant and matured at a larger size on platforms over sand than over mud (Reeves et al. 2017). Smaller 

stone crabs tended to be most abundant in the upper parts of the platforms where the barnacles were 

bigger and more abundant. Larger stone crabs tended to be found in the rubble piles at the base of a 

platform or in larger spaces formed by the platform’s structure (Figures 53).

8.2 Association of Juvenile Snapper with Stone Crabs Burrows

We observed the use of stone crab burrows and barnacle rubbles as refuges for newly-settled juvenile lane 

and red snapper. Figures 61a– 61d demonstrates this behavior. Figure 61 is a barnacle cluster with stone 

crab burrow underneath it. Figure 61b shows a diver about to lift the barnacle cluster and expose the 

burrow. Figure 61c and d show a stone crab (black arrows) fleeing after the barnacle cluster is moved 

exposing the burrow under the barnacle cluster. Figure 61 d shows an age 0 snapper fleeing (in blue 

circle) after the burrow is disturbed.
141

Figure 61 a, b, c, d. A composite of four video frames showing a newly settle juvenile snapper retreating, 

first into and then out of a stone crab burrow, when threatened by a diver. 

8.3 Use of Platform Shell Rubble by Stone Crabs and Newly Recruited 

Snapper 

One of the most important observations we made around small platforms is the patterns of rubble 

deposition and its use throughout the nearshore zone. As platform fouling grows thicker and is grazed by 

fishes, stone crabs and other organisms, the rubble begins to pile up (Figure 62). Both small and large 

pieces of shell rubble fall off the platforms and reach the bottom. The pattern of buildup is highly 

variable around small platforms and could be partially related to the age of the platform but other factors 

appear to be important. We speculate that the shell material sheds from the platforms due to wave action, 

gazing by fishes and other actions. We did observe fishes pulling pieces of barnacle off the platform and 

dropping grazed material. We observed that this shell rubble builds up and appears to be more stable on 

sandy bottoms such as Ship Shoal. Around platforms with mud bottom this material may be more easily 

buried as we seldom observed a buildup of shell rubble on muddy bottoms. Where this process occurs 

and is relatively stable, the pile of rubble can be quite large generating a few feet of vertical relief around 

small platforms. The rubble also increases structural complexity of the bottom around small platforms. 

This in turn provides habitat that can be used by small fishes and invertebrates such as stone crabs. 

During the peak recruitment period for juvenile snapper we observed large numbers of lane and red 

snapper associated with this rubble at sites throughout the coastal zone (Figure 62). 
142

Figure 62. Juvenile snapper utilizing rubble around the base of a small platform. 

8.4 Observations of Sea Turtles on Ship Shoal

One of the more unusual events we caught on video was a strong association of a sea turtle with a small 

platform on Ship Shoal (Figure 63). We observed this particular turtle at the water surface in Ship Shoal 

block 93, approximately 20-–0 m away form a small platform that we were about to sample. When we 

dropped the camera array, we captured video of this sea turtle within the structure at the base of the 

platform. We made several observations of sea turtles during the course of this study but most of them 

were made in the area of Ship Shoal. This was the only sea turtle we caught on video near a small 

platform.

Figure 63. Large sea turtle captured on video at the base of a small platform on Ship Shoal.
143

8.5 Unique Aspects of East Bay

In chapter 4 we point out several characteristics of the biota on and around small platforms of East Bay 

that distinguish them from small platforms located anywhere else in the nearshore zone off the Louisiana 

coast. The reasons for this are likely due to the unique circumstances of the hydrography of this 

particular bay. East Bay is situated between the south and southwest passes of the Mississippi river. 

Several characteristics of the East Bay biota are highlighted here, but by no means all of them. For 

example East Bay was the only place we observed Goliath grouper (Figure 64) in the nearshore zone off 

Louisiana. As rare as they are in the Louisiana coastal zone, we caught four Goliath grouper on video 

during three visits to East Bay during 2013–2014. It was also the only place we observed lionfish within 

the nearshore zone. Lionfish are common at platforms farther offshore but they do not occur with great 

frequency in the nearshore waters off Louisiana. The reason for this is not clear, as lionfish supposedly 

tolerate the lower salinity waters that occur near the influence of the two river outlets (Schofield et al. 

2015).

Figure 64. An example of one of 4 Goliath grouper caught on video around a small platform in East Bay.

East Bay also has a unique set of fouling organisms compared to everywhere else in the nearshore zone 

off Louisiana. Figure 65 shows an example of the fouling on a small platform within East Bay. Unlike 

the fouling community throughout most of the nearshore coastal zone, fouling in Easy Bay is not 

dominated by barnacles. In this location fouling consists of some oysters near the surface layer mixed 

with barnacles (Figure 65, top) and at depth soft corals and hydroids that are more typically observed well 

offshore (Figure 65, lower). This pattern is especially surprising given the close proximity of the river 

discharges to these platforms. What we observed was a collection of fouling organisms that is layered 

vertically with more freshwater tolerant species near the surface on the platforms in East Bay and 

transitioning to offshore marine species near the bottom. In one video, we observed a school of bay 

anchovies and red snapper at the same platform in East Bay.
144

Figure 65. An example of the unique combination of fouling communities on small platforms of Easy Bay 

near the water surface (A) and bottom (B).

8.6 Use of Small Platforms by Sea Birds

Although observation of birds was not a part of this study, we observed and photographed a wide range of 

bird species that use small platforms as roosting places (Figure 66, 67). Brown pelicans were among the 

most common species encountered but we also observed frigate birds, terns, and gulls resting on small 

platforms in large numbers. On one occasion, we observed and photographed pelicans that were getting 

caught between the guard rails of a small platform on Ship Shoal and we documented the same thing that 

happened with guard rails at the Ship Shoal lighthouse (Figure 66). Although we did not witness the 

pelicans getting caught between the rails, it is clear that the they get caught by the neck when trying to 

land on the rails and probably slip off the rails and get their head caught in the small space between the 

rails. At these two sites we saw more that had been killed and at another site we saw them piled up 

between the guard rails indicating this could be a common occurrence. 
145

Figure 66. Two examples of brown pelicans getting caught by the head between the guard rails at a Ship 

Shoal platform (left) and the Ship Shoal lighthouse (right) .

Figure 67. Examples of brown pelicans (left, right) resting on small unmanned platforms in the nearshore 

zone.

8.7 Growth of Macro- and Microalgae on Small Platforms

In many ways energy production platforms act like small islands that have subtidal and intertidal areas 

that get colonized by fouling organisms (Claisse et al. 2014; Cowan and Rose 2016; Reeves et al. 2017, 

2018b). These areas of platforms get colonized with both macro and micro algae (Figure 68A, B, C). 

The colonization by macro algae can be particularly heavy toward the upper limit of exposure to wave 

action and in parts of the upper part of submerged platform structure that is difficult to access by grazers 

(Figure 68A, B). This suggests that the macroalgae is being grazed when it is accessible. Microalgae 

also grows sub-tidally on the submerged surfaces and fouling of platforms (Figure 68C) and is probably 

limited by light penetration and grazing by snails and herbivorous fishes. As with planktonic algal 

production, growth of macrophytes on platforms varies with nutrients and light availability. The question 

becomes: What is the extent of this primary production on platforms, how fast is it turned over by grazers, 

how does it vary across the coastal zone and how important is it in sustaining fish and other biota as a part 

of the marine foodweb? These are good questions for future research.
146

Figure 68. Examples of macro and micro algae growing on the intertidal (upper left, right) and subtidal 

(lower) parts of small platforms in the nearshore coastal zone.

8.8 Sargassum-Platform Interactions in 2014

Figure 69 shows an example of the massive inundation of the nearshore coastal zone with Sargassum and 

the interaction of the Sargassum with small platforms in the summer of 2014. The massive rafts of 

Sargassum that came into the nearshore and inshore coastal zone would get caught in the upper structure 

of small platforms. With these mats of Sargassum came a large number of juvenile fishes that were 

associated with the Sargassum rafts. Many of these juvenile fishes, such as juvenile greater amberjack 

and blue runner, took up residence around small nearshore platforms. 
147

Figure 69. Sargassum caught on a small platform.

8.9 Project Summary Conclusions

Oil and gas platforms serve as unique artificial reefs in that they provide structure from the seafloor to 

above the sea surface. The fish aggregating effect that platforms provide presents a unique opportunity to 

study assemblage-level and species-specific responses to variation in water quality at a resolution that 

would be substantially more challenging to study in open water environments. The large number and 

wide distribution of platforms in the nGOM), coincident with the river-influenced hydrography of 

Louisiana’s nearshore zone (5–25 km water depth), is an ideal setting for such studies. High variation in 

river-induced turbidity results from a combination of discharge of suspended material, nutrients, and 

subsequent dense phytoplankton blooms. Turbidity and the general challenges of sampling around 

platforms have previously deterred scientists from studying nearshore platforms. Only now, as the small 

platforms are being rapidly removed, are they being evaluated. This study has addressed a gap in 

understanding an important element of the world’s largest artificial reef network that should benefit future 

management. For a camera based study, visibility was in fact the largest challenge faced during this 

study. However, video quality was adequate for 59% of the footage collected during the summer, and the 

adaptability afforded by our methods permitted the collection of an extensive video data base throughout 

the entire Louisiana nearshore zone.

We observed that platforms in shallow nearshore waters (3–18 m depth) of coastal Louisiana attract at 

least 54 fish species, of which 29 are partially or exclusively composed of young-of-the-year (YOY) or 

age 1–2 juveniles. YOY gag grouper (Mycteroperca microlepis), greater amberjack (Seriola dumerili), 

cobia, (Rachycentron canadum), gray triggerfish (Balistes capriscus), gray, lane, and red snapper 

(Lutjanus griseus, L. synagris, L. campechanus), as well as age 1–2 gray, lane, and red snapper highlight 

the economic importance of this coastal zone as a nursery area. Goliath grouper (Epinephelus itajara) 

occupy the nearshore waters of East Bay, between Southwest Pass and South Pass, which might 

represent, or be adjacent to spawning aggregation sites. The invasive red lionfish (Pterois volitans) was 

also observed in East Bay, although it was not seen anywhere else within the study area during the review 
148

of hundreds of hours of video and >100 dives. Although lab studies have shown that lionfish can 

acclimate to salinity values typical of nearshore Louisiana waters (Schofield et al. 2015), their absence 

throughout most of the coastal zone might be due to a habitat-specific effect of salinity that affects their 

habitat preference within the well-oxygenated part of the water column. One such possibility is that the 

salinity fluctuation in upper and mid-water column strata is too variable and changes too abruptly for 

lionfish. The nearshore fish assemblages contain few benthic species, but do include a diversity of 

demersal fishes. The nearshore zone off coastal Louisiana defines the extent of the second largest 

seasonally recurring hypoxic area on Earth (DO <2.0 mg l−1

), and while demersal and pelagic fishes can 

move up in the water column for extended periods of time, many benthic species probably leave or die 

within the hypoxic zone early in the season.

Eleven species dominated the assemblages that occur throughout Louisiana’s nearshore zone, 

representing 93% of all fishes identified during this study, including: Atlantic bumper (Chloroscombrus 

chrysurus; ~56%), Atlantic spadefish (Chaetodipterus faber; ~18%), blue runner (Caranx crysos; ~9%), 

bluefish (Pomatomus saltatrix; ~4%), sheepshead (Archosargus probatocephalus; ~3%), gray snapper 

(~2%), sergeant major damselfish (Abudefduf saxatilis; ~1%), Bermuda chub (Kyphosus sectatrix; < 1%), 

young-of-the-year (YOY) greater amberjack (< 1%), gray triggerfish (< 1%), and adult red snapper (< 

1%). Significant shifts in relative abundances of these species, and others reflect different freshwater 

stratification mixing regimes. Salinity, temperature, DO, and turbidity vary with depth across three 

regions separated at longitudes −92.5° and −90.4°. Also, the shallow-water nearshore zone contains 

several large, high-relief sandy shoals that further alter mixing regimes, and over which hypoxia is less 

extensive, less intense, and occurs less frequently than in surrounding waters. Shoals host more stable 

fish assemblages coast-wide than do surrounding mud bottoms. Differences in freshwater mixing over 

shoals were apparent at a 1 m depth scale, although DO depletion was irregular within the 10 m isobath. 

Below the 10 m isobath DO depleted conditions pervaded.

Significant changes in fish assemblages were observed in the presence of hypoxia < 50% DO saturation 

rather than < 2.0 mg l−1 DO (20–30% saturation). All fishes appeared sensitive to DO < 50% saturation, 

and moved up in the water column in response. In addition, fishes avoided the surface bloom layer. 

Environmental variation is considerable within stratified water columns and can lead to suitability 

conflicts among DO, salinity, temperature, and turbidity. Fish are driven from locations when their 

tolerances to one or more of these variables are exceeded. Significant shifts in habitat selection in the 

presence of hypoxia indicated the importance of DO as a controlling factor of fish distributions in the 

water column, and one of the sub-lethal effects of fishes responding to the highly variable and often 

stressful conditions caused by hypoxia of < 50% DO saturation.

The global expansion of coastal hypoxia is occurring due to population growth and the industrialization of 

developing nations. Emerging coastal oil and gas exploration in countries with unexploited deposits, as 

well as development of wind and tidal energy, mariculture, and a general growing interest in artificial reef 

deployment is underway across the globe. The nGOM is an important system to learn from, and may 

provide information applicable world-wide. Beginning in the mid-twentieth century, two high impact, 

and somewhat complementary, phenomena arose simultaneously in the nGOM. A coastal oil and gas 

infrastructure grew to create the largest artificial reef system on Earth, and the hypoxic zone off coastal 

Louisiana expanded and intensified within it to become the second largest hypoxic area on Earth. Both 

developments have undeniably influenced the fish community of the nGOM, and the coming years may 

reveal unexpected changes when the platforms are removed.

It is important to thoroughly evaluate the ecological role served by any habitat type, be it man-made or 

natural, prior to altering it. This is particularly relevant for platforms due to the high densities of fish and 

other sea life associated with them. Under federal law, oil and gas platforms are required to be removed 

within one year of ceasing production (Reggio 1987). Reportedly, 75–80% of all decommissioned 

platforms are removed using explosives (Bull and Kendall 1994; SEDAR 2013). The majority of fish 
149

biomass associated with platforms is in close proximity to the jacket. Many species occur at background 

densities >30 m from the jacket, and overall biomass tends to decline to ambient at distances ~100 m 

from the jacket at larger platforms (Stanley and Wilson 1997, 2003). These distances are probably 

reduced around small platforms in < 18 m water depth (Boswell et al. 2010). 

Because explosive removal mortally concusses or outright kills fishes within 50 m of the structure 

(Gitschlag 1997), it is likely that mortality would be close to 100% at the type of small platforms sampled 

in this study. Current precautions to avoid harming protected species are limited to surface-based sea 

turtle and marine mammal monitoring (Kaiser et al. 2002). Of the 41 federally-managed platforms that 

have been removed in East Bay since the 1960s (BOEM 2015), 18 platform removals have used 

explosives (BOEM 2015). Considering the presence of goliath grouper in the area, and the strong 

association this species has with complex artificial structures (NMFS 2006; Porch and Eklund 2004; 

Collins et al. 2015) it is fortunate that this ratio is relatively low. Given the current pace of energy 

structure removal coast wide, it might not be long before the platforms of East Bay are also removed. 

Some conservation groups view Goliath grouper as critically endangered (Mace and Stuart 1994), but in 

the US it is currently recovering (NMFS 2006). Nevertheless, it is in the interest of management of 

species like Goliath grouper that non-explosive removal methods be used whenever possible for 

decommissioning platforms, especially in East Bay.

This study offered a new perspective on the ecosystem services provided by the small oil and gas 

platforms in the nearshore zone of the nGOM and several globally applicable inner-shelf coastal 

processes. Observations from this study indicated promising areas of future research within this dynamic 

system. The nursery function this estuarine-marine ecotone serves is a defining characteristic that makes 

the shallow-water nearshore zone an important part of the coastal system to understand (Able 2005). The 

role that currents play in the temporal dynamics of fish distributions is a particularly interesting topic for 

study. The high vertical profile that platforms provide offers structure within the water column that may 

be important to juvenile and adult fishes by serving as current breaks that allow persistence in favored 

areas without excessive energy exertion. This may be particularly relevant during the hypoxic season 

when fishes become compressed within the middle of the water column. Eutrophication effects on DO 

likely drive biological interactions throughout the water column, including the unexpected avoidance of 

surface blooms by fishes. The dynamic hydrography within the nearshore zone demands finer-scale 

measurements and should be a priority for improving future studies within this and other highly variable 

systems. Pairing these methods with acoustics surveys would provide spatial information ideal for 

integration into a three-dimensional geographic information system, and ultimately modeling. 

Incorporating such an approach will advance our understanding of the interactions among the various 

physical, chemical, and geological elements of this system and how they relate to the biology of the 

environments within it.

Settling plate results showed that barnacles are a productive and dominant fouling organism in the 

nearshore region around Ship Shoal. The growth and settlement rates of barnacles are highest in the 

nearshore zone where phytoplankton production is known to be high. Nearshore barnacle production is

an important aspect of the ecological function of platforms because barnacles serve as prey for 

commercially and recreationally important species, and they feed on plankton in a region with very high 

plankton production. A number of commercially important species were observed grazing on barnacles 

and the other fouling organisms that inhabit nearshore platforms. These species included stone crabs, 

sheepshead, black drum, gray snapper and triggerfish. Diet studies corroborated these conclusions. Gut 

content and stable isotopes showed that platform dwelling barnacles and other secondary producers are 

grazed upon by sheepshead and stone crabs throughout the coastal zone and that sheepshead took 

advantage of an episodic feeding opportunity triggered by hypoxia (see Chapter 7).
150

The high rates of barnacle production in the upper portions of small platforms, and the grazing and 

shedding of that material over time, is an important characteristic of platforms that makes them a unique 

form of artificial reef. As this material sheds, it accumulates over time at the base of the platforms. As it 

builds up it provide habitat for organisms. We observed this habitat being utilized by large numbers of 

newly recruited lane and red snapper as well as stone crabs and other small reef associated species (see 

chapter 8). The buildup of this material was especially prominent on sand shoals, such as Ship Shoal, 

where it tends not to get buried by sediments over time.

In addition to attracting a diversity of fishes, small nearshore platforms also serve as roosts and resting 

sites for birds (Aumann 1981; Figure 70). Platforms may be important for a variety of birds that become 

exhausted during migration across the Gulf, and, as prominent fixtures on the horizon that may serve as 

navigational aids (Aumann 1981; Childs 1998). Some seabirds of the region, such as frigates and 

cormorants, do not produce sufficient oil to adequately coat their feathers and keep dry while at sea. 

These birds are limited in their foraging range from shore by the added water-weight of wet plumage. 

Platforms may extend the seaward foraging range of such species by providing sites where they can dry 

themselves (McNair 2000). Because fishes are attracted to platforms, foraging effort may also be reduced 

for these birds much as it is for fishermen. In summary it may be more ecologically accurate to consider 

platform reefs as a distinct type of artificial habitat rather than to assume that they are merely additions to 

bottom oriented artificial reef systems throughout the rest of the Gulf.

Figure 70. Magnificent frigate birds (Fregata magnificens) atop a well protector in the South Pass 28 block.
151

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