Fishes Associated with Oil and Gas Platforms in Louisiana's River-Influenced Nearshore Waters

Home , Apogon maculatus, Chandeleur Sound, Halocline, Stephanolepis hispidus

Louisiana State University LSU Digital Commons

LSU Master's Theses Graduate School

2016 Fishes Associated with Oil and Gas Platforms in Louisiana's River-Influenced Nearshore Waters Ryan Thomas Munnelly Louisiana State University and Agricultural and Mechanical College, [email protected]

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Recommended Citation Munnelly, Ryan Thomas, "Fishes Associated with Oil and Gas Platforms in Louisiana's River-Influenced Nearshore Waters" (2016). LSU Master's Theses. 1070. https://digitalcommons.lsu.edu/gradschool_theses/1070

This Thesis is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Master's Theses by an authorized graduate school editor of LSU Digital Commons. For more information, please contact [email protected]. FISHES ASSOCIATED WITH OIL AND GAS PLATFORMS IN LOUISIANA’S RIVER- INFLUENCED NEARSHORE WATERS

A Thesis

Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Master of Science

The Department of Oceanography and Coastal Sciences

by Ryan Thomas Munnelly B.S., University of North Carolina Wilmington, 2011 May 2016 The Blind Men and the Elephant

It was six men of Indostan To learning much inclined, Who went to see the Elephant The Fourth reached out an eager hand, (Though all of them were blind), And felt about the knee That each by observation “What most this wondrous beast is like Might satisfy his mind Is mighty plain,” quoth he: “Tis clear enough the Elephant The First approached the Elephant Is very like a Tree!” And happening to fall Against his broad and sturdy side, The Fifth, who chanced to touch the ear, At once began to bawl: Said: “E’en the blindest man “God bless me! but the Elephant Can tell what this resembles most; Is very like a wall!” Deny the fact who can This marvel of an Elephant The Second, feeling of the tusk, Is very like a fan!” Cried, “Ho! what have we here So very round and smooth and sharp? The Sixth no sooner had begun To me ‘tis mighty clear About the beast to grope, This wonder of an Elephant Than, seizing on the swinging tail Is very like a spear!” That fell within his scope “I see,” quoth he, “the Elephant The Third approached the animal, Is very like a rope!” And happening to take The squirming trunk within his hands, And so these men of Indostan Thus boldly up and spake: Disputed loud and long, “I see,” quoth he, “the Elephant Each in his opinion Is very like a snake!” Exceeding stiff and strong, Though each was partly in the right, And all of them were wrong!

—John Godfrey Saxe

ii ACKNOWLEDGEMENTS

Ed and Don, I couldn’t ask for better mentors or a cooler project. Thank you for the opportunities, help, and guidance you have provided me with and some of your perspectives.

Thank you further for making sure I will never forget the acronym “KISS”, and bearing with me in my effort to ‘complete the loop’.

Thank you Dr. Brian Marx for your dedication to your students. You always went the extra yard to present concepts in multiple formats and took it upon yourself to make sure your students understood. Thank you Dr. Larry Rouse for help and advice that rounded out an oceanography program for a fish person. Thank you Dr. Kevin Xu, for taking the time to train me in sediment grain-size analysis and allowing me to use your lab space. Thank you Dr. Brian

Roberts for allowing me to use your auto-titrator, but more importantly for organizing Friday seminars with refreshments. Thank you Dr. Carey Gelpi for keeping us briefed on coastwide conditions throughout the years, and for donating snapper bycatch to the cause. Thank you Dr.

Angela Collins and Joe O'Hop for verifying goliath grouper identifications. Thank you Dr. Nan

Walker for the LSU Earth Scan Laboratory, and for your helpfulness. Thanks to everybody involved with the Chesney Lab, especially David and Bill.

Funding for this project was provided by the Bureau of Ocean Energy Management and supported by a match from the Louisiana Department of Wildlife and Fisheries for a companion project. I’d like to thank both of these organizations for making this research possible, as well as the Louisiana Universities Marine Consortium, where the research took place.

iii Finally, this is dedicated to my folks, Tom and Leslie, my sister Heather, my cousins

Henry and Zale, and my terrific friends (even the ones who don’t fish).

iv TABLE OF CONTENTS

ACKNOWLEDGEMENTS ...... iii

LIST OF TABLES ...... vii

LIST OF FIGURES ...... x

LIST OF EQUATIONS ...... xvi

LIST OF ABBREVIATIONS ...... xvii

ABSTRACT ...... xix

CHAPTER I: GENERAL INTRODUCTION ...... 1 References ...... 7

CHAPTER II: PHYSICOCHEMICAL FEATURES OF THE LOUISIANA NEARSHORE ZONE (≤ 25 m WATER DEPTH): A HABITAT PERSPECTIVE ...... 12 Epitome ...... 12 Introduction ...... 13 Methods ...... 17 Coastwide survey ...... 17 Comprehensive hydrographic analyses ...... 19 Results ...... 22 Coastwide survey ...... 22 Comprehensive hydrographic analyses ...... 33 Discussion ...... 40 Conclusions ...... 45 References ...... 46

CHAPTER III: COASTWIDE FISH ASSEMBLAGES AROUND SMALL OIL AND GAS PLATFORMS IN LOUISIANA’S NEARSHORE WATERS ...... 54 Epitome ...... 54 Introduction ...... 55 Methods ...... 59 Field ...... 59 Video processing ...... 61 Statistical analyses ...... 64 Results ...... 66 Observations ...... 66 Statistical analyses ...... 70 Discussion ...... 85 Conclusions ...... 92 References ...... 94

CHAPTER IV: HABITAT SUITABILITY FOR FISHES ASSOCIATED WITH OIL AND GAS PLATFORMS IN THE NEARSHORE WATERS OF LOUISIANA ...... 102 Epitome ...... 102 Introduction ...... 103 Methods ...... 108 Field ...... 108 Video processing ...... 110 Statistical analyses ...... 111 Habitat suitability analyses ...... 112 Results ...... 115 Observations ...... 115 Statistical analyses ...... 117 Habitat suitability analyses ...... 121 Discussion ...... 123 Conclusions ...... 134 References ...... 136

CHAPTER V: SUMMARY AND CONCLUSIONS ...... 144 References ...... 150

VITA ...... 152

vi LIST OF TABLES

Table 2.1. Mean, 95% confidence interval, and lowest observed−highest observed for surface (S), midwater (M), and bottom (B) physicochemical variables, reported for West, Central, and East LA, each for the initial coastwide survey (CW), 2013 and 2014...... 29

Table 2.2. Rotated factor loadings of 10 variables. 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...... 34

Table 2.3. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on Factor 3. Asterisks (*) indicate significance of interpretable variables...... 36

Table 2.4. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on extent of hypoxia. Asterisks (*) indicate significance of interpretable variables...... 38

Table 2.5. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on intensity of hypoxia. Asterisks (*) indicate significance of interpretable variables...... 38

Table 3.1. Distributions and percent occurrences of fishes identified on video. Next to the common names are the numbers of platforms where each species was present, and the fraction (of 150) those platforms represented within each nearshore Louisiana coastal region (West, Central, and East), and year (2013 and 2014). Next to the taxonomic names are the percent of the total number of fish observed (mean MAXNO of fish per platform). MAXNOs are adult fish unless noted as age 1–2 juveniles (juv.), young- of-the-year (YOY), or mixed adults (adu.), juv., and or YOY. Asterisks (*) indicate species for which YOY were detected by divers, but absent, or under-sampled by the camera array...... 67

Table 3.2. Three-way ANCOVA for type III fixed effects of region, year, and hypoxia on species richness, controlling for relative volume sampled, and % sand. Asterisks (*) indicate significance of interpretable variables...... 71

Table 3.3. 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. Tildes (~) indicate marginal significance of interpretable variables (α < 0.1)...... 71

vii

Table 3.4. Summary of the non-parametric distance-based linear model (distLM). Reported are the marginal tests on significant relationships among assemblage composition to three principal component factors, and three additional environmental variables. Asterisks (*) indicate significance. Also shown are the distance-based redundancy analysis (dbRDA) partial correlations relating coordinate axes and orthonormal X variables, and variation explained. Underlines indicate the primary contributors to each dbRDA component...... 72

Table 3.5. PERMANOVA for Type I fixed effects of region and year, controlling for sediment composition (% sand), hypoxia, and relative volume sampled. Asterisks (*) indicate significance of interpretable variables...... 74

Table 3.6. PERMANOVA pairwise comparisons of significant interregional (West, Central, and East) and interannual (2013 and 2014) assemblage shifts. Asterisks (*) indicate significance of interpretable variables (Bonferroni adjusted α = 0.0083)...... 75

Table 3.7. PERMANOVA for Type I fixed effects of dominant sediment type (Sed) and hypoxia (DO < 50% saturation), controlled for longitude (Long), year, and relative volume sampled. Asterisks (*) indicate significance of interpretable variables (α < 0.05). Tildes (~) indicate marginal significance of interpretable variables (α < 0.1)...... 76

Table 3.8. PERMANOVA pairwise comparisons of significant assemblage shifts for dominant sediment type (Sed) (sand or mud) and presence vs. absence of hypoxia (DO < 50% saturation). Asterisks (*) indicate significance of interpretable variables (Bonferroni adjusted α = 0.0125)...... 76

Table 3.9. SIMPER pairwise assemblage dissimilarity (DISS) comparing nearshore Louisiana regions (West, Central, and East), years (2013 and 2014), dominant sediment type (Sed) (sand or mud), presence or absence of hypoxia (DO < 50% saturation), and platform complexity (1–3). Results shown are species with Diss/SD ratios > 1, indicating consistent contribution to dissimilarity, and excluding species with high dissimilarity, but patchy in their distribution...... 83

Table 4.1. Three-way ANCOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on % available water column, controlling for depth. Asterisks (*) indicate significance of interpretable variables...... 118

viii Table 4.2. Mixed generalized linear model for physicochemical responses of the 11 dominant species comprising the nearshore Louisiana platform fish assemblage. 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. Asterisks (*) indicate significance of interpretable variables. Tildes (~) indicate marginal significance of interpretable variables...... 119

Table 4.3. Rotated factor loadings of 6 variables. 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...... 121

ix LIST OF FIGURES

Figure 1.2. Total number of federally-managed oil and gas platforms in the northern Gulf of Mexico outer continental shelf (OCS) (A), and net annual change in number of platforms (B) by year from 1942–2014. Shading indicates structure type (all structures vs. all small, unmanned platforms), and OCS distribution (≤ 15 m vs. > 15 m standing depth). Note: 97 structures listed without install or removal dates were excluded from the figure...... 4

Figure 2.2. Interpolated coastwide surface, midwater, and bottom salinity (A), and pairwise comparisons for salinity (B), regionally, for the nearshore coastal zone off Western LA (West), Central LA (Central), and Eastern LA (East), and by strata (surface, midwater, and bottom). Red lines mark regional designations at longitudes −92.5° and −90.4°...... 23

Figure 2.3. Interpolated coastwide surface, midwater, and bottom temperature (A), and pairwise comparisons of temperatures (B), regionally, for the nearshore coastal zone off Western LA (West), Central LA (Central), and Eastern LA (East), and by strata (surface, midwater, and bottom). Red lines mark regional designations at longitudes −92.5° and −90.4°...... 24

Figure 2.4. Interpolated coastwide surface, midwater, and bottom density (A), and pairwise comparisons of temperatures (B), regionally, for the nearshore coastal zone off Western LA (West), Central LA (Central), and Eastern LA (East), and strata (surface, midwater, and bottom). Red lines mark regional designations at longitudes −92.5° and −90.4°...... 25

Figure 2.6. Interpolated coastwide surface, midwater, and bottom dissolved oxygen (A), and pairwise comparisons for vertical extent of hypoxia (B), and intensity of hypoxia (C), each regionally, for the nearshore coastal zone off Western LA (West), Central LA (Central), and Eastern LA (East), and by dominant sediment type (sand or mud). Red lines mark regional bounds at longitudes −92.5° and −90.4°...... 32

Figure 2.7. Factor analysis showing (A) all hydrographic station (n = 343), and (B) two standard errors around the centroid means for nearshore regions off Western LA (West, n = 71), Central LA (Central, n = 162), and Eastern LA (East, n = 110)...... 35

Figure 2.8. Interpolated coastwide principal components for factors 1–3 (A), and pairwise comparisons for factor 3 (B), regionally, for Western LA (West), Central LA (Central), and Eastern LA (East), by dominant sediment type (sand or mud), and by year (2013–14). Refer to Figure 2.1 for hydrography locations (n = 343) and regional designations...... 37

Figure 2.9. Pairwise comparison of vertical extent (A), and intensity (B) of hypoxia (< 50% saturation) across nearshore Louisiana by region (West, Central, and East), and dominant sediment type (sand or mud)...... 38

Figure 2.10. Central region composite interpolations of principal component factors 1– 3 by depth. Factor scores were interpolated within 1 m depth bins from the 3–18 m isobaths, for 15 total interpolations for each factor. Refer to Figure 2.1 for hydrography locations (n = 343) and regional designations...... 39

Figure 3.1. Three categories were used to group structures based on complexity. Category 1 included single-piling jackets, caissons, or unmanned fixed platforms (A). Category 2 included caisson or unmanned fixed platforms with > 1 piling jackets without crossbeams (B). Category 3 was well protectors with ≥ 3 piling jackets connected by crossbeams (C). Large, highly complex structures and those which discharged waterborne or airborne contaminants such as produced water or sulfide gas were avoided (D)...... 60

xi Figure 3.2. All sites of hydrographic (n = 343) and video (n = 150) data used in analyses. Colored areas represent regions of distinctly different hydrography and assemblage composition of reef-associated fishes. Green circles indicate hydrographic sampling locations, orange circles indicate paired hydrographic and video sampling locations, and hollow black squares show the distribution of federally-managed oil and gas structures. Longitudes −92.5° and −90.4° mark regional boundaries. Contours are shown for the 5 m, 10 m, 15 m, 20 m, and 25 m isobaths. The red star indicates the location of East Bay...... 62

Figure 3.4. Pairwise comparison of species richness (A), and the effective number of species (ENS) based on Shannon-Weiner diversity (B) 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...... 72

Figure 3.5. 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)...... 73

Figure 3.6. Interregional (West, Central, and East) mean MAXNO pairwise assemblage dissimilarities based on the SIMPER analysis. Bold font indicates those species which together account for > 90% of interregional fish assemblage dissimilarity. Species order reflects rank order abundance...... 77

Figure 3.7. Interannual (2013, 2014) mean MAXNO pairwise assemblage dissimilarities based on the SIMPER analysis. Bold font indicates those species which together account for > 90% of interannual fish assemblage dissimilarity. Percentages above bars indicate percent dissimilarity contributions, below which are the ratio of the percent dissimilarity over the standard deviation. Species order reflects rank order abundance...... 78

xii

Figure 3.8. Dominant sediment type (sand or mud) mean MAXNO pairwise assemblage dissimilarities based on the SIMPER analysis. Bold font indicates those species which together account for > 90% of dominant sediment type fish assemblage dissimilarity. Percentages above bars indicate percent dissimilarity contributions, below which are the ratio of the percent dissimilarity over the standard deviation. Species order reflects rank order abundance...... 79

Figure 3.9. Presence vs. absence of hypoxia (DO < 50% saturation) mean MAXNO pairwise assemblage dissimilarities based on the SIMPER analysis. Bold font indicates those species which together account for > 90% of hypoxia fish assemblage dissimilarity. Percentages above bars indicate percent dissimilarity contributions, below which are the ratio of the percent dissimilarity over the standard deviation. Species order reflects rank order abundance...... 80

Figure 3.10. Platform complexity (1–3) mean MAXNO pairwise assemblage dissimilarities based on the SIMPER analysis. Bold font indicates those species which together account for > 90% of platform complexity fish assemblage dissimilarity. Species order reflects rank order abundance...... 81

Figure 4.1. Sites of all samples included in analyses. Orange circles indicate platform sites with usable video and hydrographic data (n = 150). Black squares show the distribution of all platforms standing at the onset of the study. Red lines mark regional designations at longitudes −92.5° and −90.4°. Contours are shown for the 5 m, 10 m, 15 m, 20 m, and 25 m isobaths. The red star indicates the location of the water quality profile shown in Figure 4.4...... 109

Figure 4.2. Scaled photo-collage reconstruction of the submerged structure of platform ST 21-GC, recorded August 20, 2015. Imposed continuous salinity, temperature, depth, and DO profiles show fish distribution relative to water quality. Grey circles show individual YSI readings. Red lines indicate partitioned layers of the water column within which environmental readings were assumed 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 were following the camera array...... 115

xiii

Figure 4.3. Pairwise comparisons of the vertical extent the fraction of the nearshore water column used by fishes (A) for all hypoxic sites (n = 64), and young- of-the-year red and lane snapper up in the water column at a nearshore platform in response to hypoxic conditions (B). Comparisons across nearshore Louisiana include region (West, Central, and East), year (2013 and 2014), and dominant sediment type (sand or mud). Significant differences occurred between groups not sharing a letter. The snapper were feeding in the current, and a video is posted online at: http://vimeo.com/131456255...... 117

Figure 4.4. An extreme, but common case of habitat compression. This water column is entirely supersaturated, or hypoxic. There was one layer of the water column that was mildly supersaturated, at 103.8%, which was 0.86 m in vertical extent. This may be an example of a water column which is totally avoided by fishes. The thin layer of conceivably usable habitat might serve as a corridor for nekton. The site location is indicated by the red star in Figure 4.1...... 120

Figure 4.5. Microhabitat plot describing the environmental use patterns of 26 species to three principal component factors for hypoxic (DO > 50% saturation) (red) and not hypoxic (blue) water columns. Bubbles represent two standard errors around the centroid means for each species...... 122

Figure 4.6. Standardized suitability (SS) for 11 species responses to salinity. These species consistently contributed to assemblage differences throughout the Louisiana nearshore zone. 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...... 124

Figure 4.7. Standardized suitability (SS) for 11 species responses to temperature. These species consistently contributed to assemblage differences throughout the Louisiana nearshore zone. 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...... 125

Figure 4.8. Standardized suitability (SS) for 11 species responses to DO. These species consistently contributed to assemblage differences throughout the Louisiana nearshore zone. 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...... 126

xiv Figure 4.9. Standardized suitability (SS) for 11 species responses to depth. These species consistently contributed to assemblage differences throughout the Louisiana nearshore zone. 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...... 127

Figure 4.10. Standardized suitability (SS) for 11 species responses to Secchi depth. These species consistently contributed to assemblage differences throughout the Louisiana nearshore zone. 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...... 128

Figure 5.1. Magnificent frigatebirds (Fregata magnificens) atop a well protector in the South Pass 28 block...... 149

xv LIST OF EQUATIONS

퐻′ = −∑i 푝iln푝i

ENS = exp(퐻′) = exp(−∑i 푝iln푝i)

S = P(E│F) / P(E)

xvi LIST OF ABBREVIATIONS

The following (common) abbreviations and (jargon) definitions apply throughout this document:

ANCOVA analysis of covariance ANOVA analysis of variance adu. adult Bird’s Foot the “Balize” Delta of the Mississippi River BOEM Bureau of Ocean Energy Management (Formerly the Mineral Management Service) BSEE Bureau of Safety and Environmental Enforcement dbRDA distance-based redundancy analysis 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 Fisheries and Aquaculture Organization 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 KISS “keep it simple stupid” LATEX Shelf Louisiana–Texas Shelf layer refers to a vertical portion of the water column with consistent salinity, temperature, and dissolved oxygen measurements LC Loop Current LCC Louisiana Coastal Current LCE Loop Current eddy LDWF Louisiana Department of Wildlife and Fisheries MANOVA multivariate analysis of variance MAXNO max number relative abundance estimate for a given species nGOM northern Gulf of Mexico NMFS National Marine Fisheries Service nearshore coastal zone of the outer continental shelf between 5–25 m depth NTU Nephelometric Turbidity Units

xvii

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 th pi the total proportion of the i species in the Shannon-Weiner diversity formula psu practical salinity units platforms oil and gas structures PRIMER Plymouth Routines in Multivariate Ecological Research S suitability SD standard deviation SEDAR Southeast Data Assessment and Review shallow waters < 18 m depth SAS Statistical Analysis System SLR simple linear regression SIMPER similarity percentages YOY young-of-the-year

xviii

ABSTRACT

A distinctive feature of coastal Louisiana is the unrivaled network of oil and gas installations

(platforms) extending from inshore waters to the deep Gulf of Mexico. Since 2007 there has been a 38% reduction in platform numbers with the highest removal rates occurring in shallow

(< 18 m) nearshore waters. Many fishes and invertebrates are attracted to platforms, presenting a unique opportunity to study detailed species-specific responses to the river-influenced hydrographic characteristics of Louisiana’s nearshore zone (5–25 km water depth). Prior studies of fishes around platforms focused on a few relatively large platforms in water depths ≥ 18 m.

However, about one-third of all platforms are small, unmanned and non-drilling platforms located in waters < 18 m depth. Paired video and hydrographic data were collected at 150 small platforms in < 18 m water depth during the summers of 2013–2014. Fifty-four species of fishes were associated with small platforms. The assemblage(s) included juveniles of 29 species, indicating the importance of nearshore platforms as diverse nursery habitat. The coastal zone was divided into three regions based on broad-scale interactions between freshwater input and bathymetry driving major distinctions in interregional hydrography and fish assemblages. Co- occurring within this expansive artificial reef network is the second largest hypoxic area

(dissolved oxygen (DO) < 2.0 mg l−1) on Earth. Platforms offer reef-like habitat features in the upper water column that may offer refugia for some reef-associated species during hypoxic events. Significant intraregional differences in physicochemical features were related to the presence of hypoxia (defined as DO < 50% saturation), as well as the distribution of sandy shoals, and platform complexity. Eleven species accounted for most of the assemblage dissimilarities, composing ~93% of all fishes observed. Habitat suitability indices for these 11 species provided information about habitat selection across horizontal and vertical

xix physicochemical gradients throughout the coastal zone, and within hypoxic and well-oxygenated stratified water columns. East Bay, near the outlet of the Mississippi River, exhibited less hypoxia and a distinct fauna that included four adult goliath grouper (Epinephelus itajara). This endangered fish was observed during spawning season (summer), suggesting that East Bay might support a spawning aggregation.

CHAPTER I: GENERAL INTRODUCTION

Coastal Louisiana is among the most productive regions in the United States in terms of two industries of seemingly conflicting interests: fisheries and petroleum extraction. Since the mid- twentieth century 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 site of the largest contiguous tract of wetlands in the US; inclusive of > 25% of US total wetland area (Alexander et al. 1986). Four of the five largest rivers discharging into the Gulf drain from Louisiana (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).

Subsequently, primary productivity of the Fertile Fisheries Crescent system is high due to river- based nutrient discharge (Günter 1963; Nixon et al. 1986) that has been radically elevated by agriculture (Turner and Rabalais 1991). Also throughout the Fertile Fisheries Crescent there are thousands of oil and gas structures (platforms). Collectively this extensive infrastructure creates the largest “de facto” artificial reef network on Earth (Krahl 1986), that exists within one of the highest productivity regions of the US coastal zone.

The unparalleled network of oil and gas platforms throughout coastal Louisiana’s inshore waters and extending to the deep Gulf adds another dimension to fish habitat. Many platforms support the pipeline systems stemming from larger drilling structures, but do not extract

Figure 1.1. Age 1–2 juvenile spadefish, lane snapper, and greater amberjack, as well as adult spadefish, yellow jack, cobia (lemonfish), and sheepshead around platform WC 148-1 August 01, 2013. This platform was located ~38.5 km from shore, on part of the Sabine Shoals, at ~8.5 km depth. The platform jacket is just out of view to the left of the two well heads. Note: the barnacle rubble shed from the platform. petroleum or expel contaminated wastewaters, commonly referred to as “produced waters”. As high-relief (or ‘maximum relief’) reef-like features, platforms attract dense aggregations of pelagic, demersal, and benthic fishes (Figure 1.1) 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 exploit 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 nGOM begun in the 1940’s (BOEM 2015; Figure 1.2). 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. The “peak period” was from 1992 until 2006, the first year of a net decline in platform numbers. During this time the count was 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 in 2001. This peak number represented more than one-half of the coastal platforms globally (Hamzah 2003).

During 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. Currently, platform numbers are rapidly diminishing, with disproportionate removal from the nearshore environment (Gallaway and Cole 1998). The net loss of platforms from 2007–2014 (mean −184 ± 54 (95% CI)) reduced the count from 3,900 platforms in 2006 to 2,426 platforms in 2014 (BOEM 2015). Of these removals, ~96% were small, ~42% were in shallow water, and ~41% were small and in shallow water. This change reflects an industry shift into deeper waters with less exploited hydrocarbon deposits as society approaches the peak, and ultimate decline of the oil age (Hirsch et al. 2005 and references therein).

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

(Wiseman et al. 1982; Ho and Barrett 1975). During calm summer days the eutrophic parts of the coastal zone 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 (dissolved oxygen (DO) < 2.0 mg l−1) develop and create the second largest hypoxic zone on Earth by total area coverage (Rabalais et al. 2002). 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 to unaffected depths (Caddy 1993; Chesney and

Baltz 2001). However, many species remain as hypoxia develops and move vertically in the water column to avoid exposure to low DO (Stanley and Wilson 1990).

In the northern Gulf of Mexico (nGOM), hypoxia is patchy in distribution, and ephemeral in nature (Rabalais et al. 1991), particularly in nearshore waters (Renaud 1986; Hazen et al.

2009). Variation results from bathymetric interactions with freshwater outflow from the

Mississippi-Atchafalaya river system, and the effects of wind speed and direction on plume distributions (Hetland and DiMarco 2008; DiMarco et al. 2010; Rabalais et al. 1991). 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 (Dubois et al. 2009; Chesney and Baltz 2001). 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 norther Gulf of Mexico (nGOM). Instead, shoals are primarily seen as sand resources for barrier island renourishment projects (Dubois et al. 2009 and references therein). Large-scale

5 dredging of these exhaustible features began in 2014 (Bureau of Ocean Energy Management

(BOEM) 2015).

From a habitat perspective, shoal dredging and platform removals jointly represent a dramatic environmental disturbance. Both shoals and platforms offer rare benthic habitat relative to their mud-dominated surroundings. Hard bottom substrate is particularly rare in the nGOM (Parker et al. 1983), and platforms offer a variety of ecological services which do not occur naturally (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 Kendell 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).

To date, the Rigs-to-Reefs program has placed material from 470 platforms to create artificial reefs (Bureau of Safety and Environmental Enforcement (BSEE) 2015). Of those, materials from 370 platforms have been deployed in Federal waters off Louisiana (Louisiana

Department of Wildlife and Fisheries (LDWF) 2015). Recognizing the rapid removal rates occurring in shallow, nearshore waters of the Gulf, the LDWF Artificial Reef Program released a plan (LDWF 2014) to expand into nearshore waters, defined as water depths ≤ 100 m. In 2015 the Gulf of Mexico Fishery Management Council suggested prioritizing even deeper areas along the shelf edge, leaving nothing in shallow waters except standing platforms. Current US Coast

Guard regulations require 85 ft (~ 26 m) of navigational clearance above any unmarked submerged structure. Areas frequented by shrimp trawlers are also a consideration.

Consequently an effective nearshore artificial reef program will require careful planning that

6 includes deploying materials in accessible areas of natural resiliency of fish assemblages to hypoxia, away from areas of heavy navigation, and not in areas of interest for shrimp fishermen.

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.

The presence of several large sandy shoals, and great abundance of platforms located in the nearshore coastal zone creates a dynamic landscape. The biophysical coupling of river- influenced waters subject to variable and periodic hypoxic events within the shallow nearshore zone can create a stressful environment for bottom-associated fishes. The objectives of this study were to:

1) characterize the fish assemblage(s) associated with small, nearshore platforms as de facto artificial reefs,

2) identify major regional and intraregional transitions in fish assemblages associated with physicochemical differences (e.g., salinity, temperature, depth, dominant sediment type (sand or mud), presence or absence of hypoxia (DO < 50% saturation)), and differences in platform complexity (single piling, multiple pilings without crossbeams, or multiple pilings with crossbeams),

3) evaluate annual variation between summers of 2013 and 2014, and

4) evaluate some of the unique ecosystem services that platforms provide for fishes in the nearshore zone of the outer continental shelf.

References

Alexander CE, MA Broutman, DW Field. 1986. An inventory of coastal wetlands of the USA. and Atmospheric Administration National Ocean Service, Department of Commerce, Washington DC.

Bull AS, JJ Kendall Jr. 1994. An indication of the process: offshore platforms as artificial reefs in the Gulf of Mexico. Bulletin of Marine Science 55: 186–1098.

Bureau of Ocean Energy Management (BOEM). 2015. Platform structures online query. http://www.data.boem.gov/homepg/data_center/platform/platform/master.asp. Accessed November 09, 2015.

Bureau of Safety and Environmental Enforcement (BSEE). 2015. Platform/Rig Information. http://www.data.bsee.gov/homepg/data_center/platform/platform.asp. Accessed November 09, 2015.

Caddy JF. 1993. Toward a comparative evaluation of human impacts on fishery ecosystems of enclosed and semi‐enclosed seas. Reviews in Fisheries Science 1(1): 57–95.

Chesney EJ, DM Baltz. 2001. The effects of hypoxia on fisheries in the northern Gulf of Mexico. In: Rabalais NN, RE Turner (eds.) Coastal hypoxia: consequences for living resources and ecosystems. American Geophysical Union, Coastal and Estuarine Studies, Washington D.C. 58: 321–354.

Chesney EJ, DM Baltz, RG Thomas. 2000. Louisiana estuarine and coastal fisheries and habitats: perspectives from a fish’s eye view. Ecological Applications 10(2): 350–366.

Diaz RJ, R Rosenberg. 1995. Marine benthic hypoxia: a review of its ecological effects and the behavioral responses of benthic macrofauna: 245–303.

Diaz RJ, R Rosenberg. 2008. Spreading dead zones and consequences for marine ecosystems. Science 321(5891): 926–929.

DiMarco SF, P Chapman, ND Walker, RD Hetland. 2010. Does local topography control Hypoxia on the eastern Texas-Louisiana shelf? Journal of Marine Systems 80(1-2): 25– 35.

Ditton RB, AR Graefe. 1978. Recreational fishing use of artificial reefs on the Texas coast.

Dubois S, CG Gelpi Jr, RE Condrey, MA Grippo, JW Fleeger. 2009. Diversity and composition of macrobenthic community associated with sandy shoals of the Louisiana continental shelf. Biodiversity and conservation 18(14): 3759–3784.

Gallaway BJ, JG Cole. 1998. Cumulative ecological significance of oil and gas structures in the Gulf of Mexico: A Gulf of Mexico fisheries habitat suitability model. Phase 2 model description. LGL Ecological Research Associates, Inc., Bryan, TX (United States) (No. PB--98-141443/XAB).

Gitschlag GR. 1997. Fisheries impacts of underwater explosives used to salvage oil and gas platforms in the Gulf of Mexico. International Society of Explosives Engineers, Cleveland, OH (No. CONF-970224--).

Gulf of Mexico Fishery Management Council. 2015. Evaluation of Potential Artificial Reef Siting Criteria in the Gulf of Mexico.

Günter G. 1963. The fertile fisheries crescent. Journal of the Mississippi Academy of Science 9: 286–290.

Hamzah BA. 2003. International rules on decommissioning of offshore installations: some observations. Marine Policy 27: 339–48.

Hazen EL, JK Craig, CP Good, LB Crowder. 2009. Vertical distribution of fish biomass in hypoxic waters on the Gulf of Mexico shelf. Marine Ecology Progress Series 375: 195– 207.

Hirsch RL, R Bezdek, R Wendling. 2005. Peaking of world oil production. Proceedings of the IV International Workshop on Oil and Gas Depletion 19–20.

Hetland RD, SF DiMarco. 2008. The effects of bottom oxygen demand in controlling the structure of hypoxia on the Texas-Louisiana continental shelf. Journal of Marine Systems 70: 49–62.

Ho CL, BB Barrett. 1975. Distribution of nutrients in Louisiana’s coastal waters influenced by the Mississippi River. Technical Bulletin of the Louisiana Wildlife and Fisheries Commission, Oysters, Water Bottoms and Seafoods Division, New Orleans 17: 39.

Justić D, NN Rabalais, RE Turner, WJ Wiseman. 1993. Seasonal coupling between riverborne nutrients, net productivity and hypoxia. Marine Pollution Bulletin 26: 184–189.

Krahl RB. 1986. Federal focus on platform disposition for artificial reefs. MMS Information Transfer Meeting, 1985: 112–114.

Louisiana Department of Wildlife and Fisheries (LDWF). 2015. 2013-2014 annual report.

Louisiana Department of Wildlife and Fisheries (LDWF). 2014. Louisiana Inshore and Nearshore Artificial Reef Plan.

Milliman JD, RH Meade. 1983. World-wide delivery of river sediment to the oceans. The Journal of Geology 1–21.

Nixon SW, CA Oviatt, J Fristhen, B Sullivan. 1986. Nutrients and the productivity of estuarine and coastal marine ecosystems. Journal of the Limnological Society of South Africa 12(1): 43–7.

Parker RO Jr, DR Colby, TD Willis. 1983. Estimated amount of reef habitat on a portion of the US South Atlantic and Gulf of Mexico continental shelf. Bulletin of Marine Science 33(4): 935–940.

Pokryfki L, RE Randall. 1987. Nearshore hypoxia in the bottom water of the northwestern Gulf of Mexico from 1981 to 1984. Marine Environmental Research 22(1): 75–90.

Rabalais NN, RE Turner, D Justić, Q Dortch, WJ Wiseman Jr, BK Sen Gupta. 1996. Nutrient changes in the Mississippi River and system responses on the adjacent continental shelf. Estuaries 19: 386–407.

Rabalais NN, RE Turner, WJ Wiseman Jr. 2002. Gulf of Mexico hypoxia, A.K.A. “the Dead Zone.” Annual Review of Ecology and Systematics 33: 235–263.

Rabalais NN, RE Turner, WJ Wiseman Jr, DF Boesch. 1991. A brief summary of hypoxia on the northern Gulf of Mexico continental shelf: 1985–1988. In: Tyson RV, TH Pearson (eds.). Modern and Ancient Continental Shelf Anoxia. Geological Society Special Publication 58: 35–46.

Ragan JG, AH Harris, JH Green. 1978. Temperature, salinity and oxygen measurements of surface and bottom waters on the continental shelf off Louisiana during portions of 1975 and 1976. Professional Papers Series (Biology), Nicholls State University, Thibodaux, LA 3: 1–29.

Renaud ML. 1986. Hypoxia in Louisiana coastal waters during 1983: implications for fisheries. Fisheries Bulletin 84:19–26.

Ribaudo MO, R Heimlich, R Claassen, M Peters. 2001. Least-cost management of nonpoint source pollution: source reduction versus interception strategies for controlling nitrogen loss in the Mississippi Basin. Ecological Economics 37(2): 183–197.

SEDAR 2013. SEDAR 31-Gulf of Mexico Red Snapper Stock Assessment Report. SEDAR, North Charleston SC 1103.

Stanley DR, CA Wilson. 1990. A fishery-dependent based study of fish species composition and associated catch rates around oil and gas structures off Louisiana. Fishery Bulletin 88(4).

Stanley DR, CA Wilson. 1997. Seasonal and spatial variation in the abundance and size distribution of fishes associated with a petroleum platform in the northern Gulf of Mexico. Can. J. Fish. Aquat. Sci. 54: 1166–1176.

Stanley DR, CA Wilson. 2003. Seasonal and spatial variation in the biomass and size frequency distribution of fish associated with oil and gas platforms in the northern Gulf Of Mexico. In: Stanley DR, A Scarborough-Bull (eds.). Fisheries, Reefs, and Offshore Development. American Fisheries Society, Symposium 36, Bethesda, Maryland 125–153.

Turner RE, NN Rabalais. 1991. Changes in the Mississippi River water quality this century. Bioscience 41: 140–147.

Turner RE, NN Rabalais. 2003. Linking landscape and water quality in the Mississippi River basin for 200 years. BioScience 53: 563–572.

Wiseman WJ Jr, SP Murray, JM Bane, MW Tubman. 1982. Temperature and salinity variability within the Louisiana Bight. Contributions in Marine Science 25: 109–20.

Wiseman WJ, Rabalais NN, Turner RE, Dinnel SP, A MacNaughton. 1997. Seasonal and interannual variability within the Louisiana coastal current: stratification and hypoxia. Journal of Marine Systems 12: 237–48.

Witzig J. 1986. Rig fishing in the Gulf of Mexico 1984: marine recreational fishing results. In Proceedings, Sixth Annual Gulf of Mexico Information Transfer Meeting. US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, OCS Study/MMS86–0073. New Orleans, Louisiana 103–105.

CHAPTER II: PHYSICOCHEMICAL FEATURES OF THE LOUISIANA NEARSHORE ZONE (≤ 25 m WATER DEPTH): A HABITAT PERSPECTIVE

Epitome

Louisiana’s nearshore hydrography (waters ≤ 25 m deep) is strongly influenced by the

Mississippi and Atchafalaya rivers. Freshwater outflows typically peak in summer and vary seasonally in relation to river stage, discharge, and prevailing winds. Coastal salinities, temperatures, turbidities, and nutrient loads are directly affected, and thermohaline stratification allows seasonal hypoxia (DO < 2.0 mg l−1) to develop in the presence of upwelling-favorable winds that slow shelf turnover. The result is a zone of ephemeral hypoxia which forms the second largest hypoxic area on Earth. Because fresh water is distributed via two rivers ~230 km apart, differences in the coastal landscape and shelf bathymetry effect different freshwater influences throughout the system. Analyses of regional surface, midwater, and bottom-water strata provided a snapshot of the nearshore zone based on 125 water quality profiles (salinity, temperature, depth, atmospheric pressure, pressure at depth, DO, pH, Secchi depth) collected over a 21 day period in summer of 2013. Agreement between this snapshot and comprehensive analyses of 343 profiles collected 2013–14 suggested that the nearshore zone is comprised of three functionally distinct regions. The West, Central, and East regions of Louisiana’s nearshore waters are delineated bathymetrically by the 10 m, 15 m, and 25 m isobaths, and differences in the ways the coastally-inset deltas of the Atchafalaya River distribute water to the shelf, in contrast to the deep-water discharging Bird’s Foot Delta of the Mississippi River. Bathymetry explained major differences in mixing across the nearshore zone, providing insights regarding a patchy bottom DO distribution. There was a strong relationship between regional bottom DO and the distribution of sandy shoals throughout nearshore waters, and high susceptibility to hypoxia below the 10 m isobath.

Introduction

The subtropical marsh-dominated Louisiana coastline measures 639 km (397 miles) according to the federal coastal boundary or 12,426 km (7,721 miles) including all tidally influenced coast

(National Oceanic Atmospheric Administration 1975), making it either the 5th or the 3rd longest coastline, respectively, in the United States. With > 25% of the total wetland area of the 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 in modern-day nearshore waters, which offer local bathymetric highs of coarse-grained sediments marbled throughout the mud-dominated benthic environment

(Penland et al. 1988, 1989). Since settlement of the region, the Mississippi River has become constrained within the anthropogenically manipulated infrastructure. The river is no longer allowed to wander and discharge is confined to two highly regulated primary delta complexes which have minimal and, in many ways, insufficient influence on the broader historical floodplains.

The drainage basin of the Mississippi River accounts for ~41% of the contiguous US

(Turner and Rabalais 1991), placing it third in area amongst the largest drainages on Earth

(Milliman and Meade 1983). 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 northern Gulf of Mexico (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 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 (< 18 m water depth) 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 waters at depths of

3–18 m. Throughout this estuarine-marine ecotone, salinity is the dominant driver of 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 differ according to interactions between bathymetry and freshwater source. 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

14 dynamic environment of close physical and biological coupling (Wiseman and Sturges 1999).

From a habitat standpoint, euryhaline distributions and assemblage compositions reflect 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 or life history stages of ecological and economic importance use ill-defined transition environments like this, understanding physicochemical variability 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 on Earth (Rabalais et al. 2002; 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 discharge remains high throughout the summer months, during which time high temperatures and southwest, upwelling-favorable winds intensify stratification of coastal waters (Rabalais et al. 1991; Pokryfki and Randall 1987;

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, 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 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. Therefore, the physical environment is more informative to prediction of 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 (Walker et al. 2005; Walker 2005; Pokryfki and Randall 1987), affect mixing, light penetration (Bierman et al. 1994; Quiñones-Rivera et al. 2007; Lehrter et al. 2009) and alter dominant respiration pathways (Bierman et al. 1994; Hetland and DiMarco 2008).

Therefore, site-specific physical attributes are important to local formation and dissipation of hypoxia (Wang and Justić 2009). In 1986, Renaud reported patchy hypoxic conditions in central

Louisiana waters between 9–15 m deep. In 2010, DiMarco et al. showed that mesoscale bathymetric interactions with river-influenced 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 dissolved oxygen (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 Rosenburg; 1978; Meyer 1994 and references therein),

16 particularly where winter deposition is heavy (Turner et al. 2006). Metal content also generally increases with decreasing grain size (Kristiansen et al. 2002, Kristensen et al. 2003). These characteristics can promote the positive feedback which 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. 1999;

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 benthic to water column respiration pathways.

Subsequently the Atchafalaya Shelf 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).

Methods

Coastwide survey: The initial coastwide survey, conducted July 12 - August 01 of 2013, was intended as an exploratory guide for a future study of environmental responses of the fish assemblages around small oil and gas platforms (platforms) across Louisiana. Sampling was focused in federally-managed nearshore waters < 18 m deep, during the highly variable summer

Figure 2.1. All sites of hydrographic data used in analyses are indicated by orange and green circles (n = 343). Orange circles specify hydrographic sampling locations from the initial coastwide survey (n = 125). Colored areas represent regions of distinctly different hydrography at longitudinal divides −92.5° and −90.4°. Contours are shown for the 5 m, 10 m, 15 m, 20 m, and 25 m isobaths. 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 2.1). 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 a Secchi disk was used 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 (INSTAAR 2011), 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

18 presence of sandy shoals, while a majority sediment component less than 63 µm was considered mud dominated.

Platform selection was by a modified random approach intended to characterize environmental variation in terms of physicochemical conditions as well as features 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 coastwide 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. In 2014 we collected 162 profiles over 14 days. 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 as for the initial coastwide survey, with the exception of pH. The YSI was calibrated at least every two weeks, and the DO membrane was replaced between sampling seasons. Winkler titrations (Winkler 1888) validated performance of the DO probe (slope of 1.0042, and intercept of −0.0283; F (1, 12) = 1794.43, P = 0.6538), indicating that the DO probe may have slightly underestimated DO, although Winkler titration may slightly overestimate DO (Wong and Li 2009).

Comprehensive 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

19 from the bottom. Midwater readings were selected from the literal mid-water 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 produced for 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 < 18 m depth (Figure 2.1) established based on major transitions of the 10 m, 15 m, and 25 m isobaths.

Two-way ANOVAS were used to compare water quality by region and either dominant sediment type or strata. Salinity, temperature, and density were compared with region (West,

Central, and East) and strata (surface, midwater, and bottom) 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). 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 fit with the negative binomial distribution and log link

20 function using the GLIMMIX 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 right-skewed, and while the negative binomial distribution provided an adequate fit, the gamma distribution with log link function was used by virtue of 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.

In order 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, while 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.

Results

Coastwide survey: Throughout the study area, the water column was always in part diluted below full salinity Gulf of Mexico (Gulf) water. Freshwater influence was highly spatially and temporally variable, relating not only 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 2.1) were identified based on dominant hydrographic attributes evident in the interpolated salinity, temperature, and subsequent density profiles (Figure 2.2, A; 2.3, A; 2.4, A) observed during the initial coastwide survey. With

Figure 2.5. Interpolated coastwide surface-to-bottom density difference (A), and pairwise comparisons for surface-to-bottom density difference (B), for the nearshore coastal zone off Western LA(West), Central LA (Central), and Eastern LA (East), and dominant sediment type (sand or mud) based on the INSTAAR multisource -integrated data set. Red lines mark regional designations at longitudes −92.5 ° and −90.4. relative consistency in coastwide 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 (Figure 2.4, A; 2.5, A). As expected, coastal waters were most highly stratified near the mouth of Atchafalaya Bay and around the Bird’s Foot

(Figure 2.5, A), and generally became progressively more stratified from west to east with proximity to the Mississippi River Delta (Figure 2.5, B). However, the contrasts appeared more sharply defined than a continuous transition with distance from river input alone. These abrupt transitions provided a basis for a division of the coast at fixed boundaries that reflected

26 significantly different characteristics. Further analyses 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. Sandy sediment increased with distance from shore and to the west, which 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 was defined by the notable transitions of the 10 m and 25 m isobaths. At longitude −92.5 ° there was a landward movement 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 sand-dominated 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. The dominant sources of freshwater to this region were the Atchafalaya, and far-field Mississippi rivers, and to a lesser extent, Vermilion, Atchafalaya, and Terrebonne bays. 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 (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 2.1). Regional comparison of the coastwide salinity profiles by interpolated surface, midwater, and bottom strata (Figure 2.2, A) showed that salinity in the West was nearly uniform throughout the water column, while 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 2.2, B), strata (F (2, 366) = 46.69, P < 0.0001; Figure 2.2 (B)) and the interaction

(F (4, 366) = 22.57, P < 0.0001; Figure 2.2, B) 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 2.2, B).

Temperature was highly variable, ranging from 24.39–33.38 °C, although on average it was much less variable (Table 2.1). 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 2.3, A). The overall effects of region (F (2, 176.1) =

291.14, P < 0.0001; Figure 2.3, B), strata (F (2, 177.8) = 117.05, P < 0.0001; Figure 2.3, B), and their interaction (F (2, 146.6) = 19.50, P < 0.0001; Figure 2.3, B) were significant. Pairwise comparisons of temperature showed significant variation in the water column for at least one

Table 2.1. Mean, 95% confidence interval and lowest observed−highest observed for surface (S), midwater (M), and bottom (B) physicochemical variables for West, Central, and East LA during the initial coastwide survey (CW) and all of 2013 and 2014.

Environmental West Central East variable CW 2013 2014 CW 2013 2014 CW 2013 2014 30.79 31.42 29.99 23.99 23.98 24.32 19.01 17.02 22.99 (±0.67) (±0.62) (±0.61) (±1.90) (±1.43) (±0.94) (±2.16) (±2.04) (±1.71) S 26.68– 26.19– 26.71– 0.90– 0.90– 10.11– 1.18– 1.18– 6.02– 33.30 34.22 32.79 27.84 29.30 30.08 28.04 28.04 30.66 31.02 31.63 30.53 26.38 26.23 29.09 29.41 29.43 32.76 Salinity (±0.55) (±0.55) (±0.55) (±0.38) (±0.51) (±0.45) (±0.67) (±0.54) (±1.32) M (psu) 29.45– 26.20– 26.93– 21.38– 15.24– 22.47– 19.09– 19.09– 22.95– 33.21 34.26 32.95 28.95 29.70 33.97 33.02 33.02 36.70 31.68 32.21 32.18 28.00 28.95 31.45 32.86 32.77 35.19 (±0.42) (±0.43) (±0.50) (±0.72) (±0.61) (±0.52) (±0.36) (±0.40) (±0.83) B 29.92– 28.62– 29.17– 25.26– 25.26– 25.32– 29.18– 28.85– 24.58– 33.21 34.52 33.95 34.85 34.85 35.54 35.12 35.98 36.74 30.13 30.11 30.54 30.07 29.98 30.69 29.18 29.20 28.69 (±0.17) (±0.11) (±0.13) (±0.36) (±0.26) (±0.14) (±0.32) (±0.27) (±0.42) S 29.50– 29.50– 29.93– 28.79– 28.15– 29.33– 27.83– 27.83– 22.89– 31.23 31.23 31.20 33.38 33.38 32.57 32.72 32.72 30.44 29.81 29.88 30.30 29.37 29.41 29.55 27.80 27.87 25.68 Temperature (±0.08) (±0.08) (±0.06) (±0.11) (±0.13) (±0.18) (±0.09) (±0.08) (±0.73) M (°C) 29.50– 29.50– 29.97– 28.30– 28.30– 27.50– 26.85– 26.85– 22.71– 30.19 30.65 30.62 30.66 30.69 31.14 28.79 28.79 29.34 29.35 29.57 29.79 28.57 28.59 28.20 26.28 26.45 23.47 (±0.25) (±0.18) (±0.23) (±0.31) (±0.22) (±0.43) (±0.20) (±0.21) (±0.57) B 27.84– 27.84– 27.94– 25.55– 25.55– 23.31– 24.39– 24.39– 21.65– 29.99 30.27 30.62 29.46 29.85 31.15 27.46 28.19 28.80 7.12 7.02 6.60 8.04 8.17 7.62 9.20 9.43 9.27 (±0.31) (±0.21) (±0.15) (±0.64) (±0.50) (±0.32) (±0.76) (±0.66) (±0.48) S 5.69– 5.69– 5.69– 6.08– 5.81– 6.20– 5.40– 5.40– 6.40– 9.17 9.17 7.50 20.27 20.27 13.75 19.41 19.41 12.41 7.05 6.91 6.25 7.44 7.50 6.09 7.04 6.81 6.19 Dissolved (±0.26) (±0.18) (±0.17) (±0.32) (±0.32) (±0.25) (±0.43) (±0.38) (±0.47) oxygen M 5.66– 5.66– 5.03– 3.29– 2.10– 2.77– 0.50– 0.50– 3.46– (mg l−1) 8.54 8.54 7.09 10.52 11.57 8.40 10.98 10.98 10.25 4.29 4.83 3.75 4.30 4.06 3.73 2.73 3.06 3.81 (±1.12) (±0.74) (±0.71) (±0.69) (±0.62) (±0.52) (±0.34) (±0.33) (±0.53) B 0.12– 0.12– 0.19– 0.23– 0.19– 0.08– 0.17– 0.17– 0.15– 6.76 7.84 6.56 8.16 8.73 7.50 5.51 6.44 9.49 111.95 110.61 103.86 121.25 122.94 116.15 133.08 134.97 136.64 (±5.14) (±3.37) (±2.37) (±9.13) (±7.07) (±4.39) (±10.53) (±9.25) (±6.68) S 87.70– 87.70– 88.40– 92.60– 86.70– 96.00– 72.84– 72.84– 95.60– 147.40 147.40 117.20 294.05 294.05 200.53 276.22 276.22 187.40 Dissolved 110.26 108.56 98.35 112.70 113.40 93.73 105.21 102.00 90.98 oxygen (±4.10) (±2.79) (±2.61) (±4.88) (±4.77) (±3.83) (±6.46) (±5.67) (±8.84) M (percent 87.30– 87.30– 77.80– 49.80– 32.00– 42.20– 7.40– 7.40– 7.77– saturation) 133.00 133.00 109.50 161.70 174.40 127.80 158.60 158.60 166.80 67.28 76.03 59.19 64.79 61.64 57.56 40.80 45.72 54.90 (±17.55) (±11.69) (±11.30) (±10.42) (±9.56) (±8.08) (±5.11) (±5.02) (±7.99) B 2.60– 2.60– 2.90– 3.40– 2.90– 1.20– 2.60– 2.60– 2.30– 106.40 124.30 104.80 122.70 1.32.50 130.10 83.06 97.60 149.99

(Table 2.1 continued)

Environmental West Central East variable CW 2013 2014 CW 2013 2014 CW 2013 2014 1018.40 1013.48 1010.06 (±0.42) (±1.48) (±1.68) S ------1015.55– 995.54– 996.65– 1020.20 1016.41 1017.08 1018.86 1015.50 1018.31 Density (±0.41) (±0.29) (±0.52) M ------(kg/m3) 1017.66– 1011.55– 1010.25– 1020.46 1017.41 1021.05 1019.51 1017.00 1021.39 (±0.33) (±0.62) (±0.30) B ------1018.06– 1014.68– 1018.22– 1020.58 1023.11 1023.71 8.21 8.54 8.57 (±0.06) (±0.07) (±0.06) S ------8.02– 8.19– 7.98– 8.78 9.45 9.15 8.19 8.44 8.31 (±0.03) (±0.05) (±0.03) pH M ------8.03– 7.98– 7.93– 8.35 8.70 8.72 8.00 8.24 8.07 (±0.08) (±0.08) (±0.11) B ------7.58– 7.74– 7.20– 8.22 8.61 10.77 4.10 4.13 7.19 2.54 3.24 5.16 1.88 1.71 1.90 Secchi depth (±0.89) (±0.69) (±1.16) (±0.45) (±0.46) (±0.60) (±0.46) (±0.38) (±0.30)

(m) 1.47– 1.47– 1.25– 0.47– 0.47– 0.96– 0.27– 0.27– 0.60– 9.55 10.48 12.70 7.05 8.43 11.61 7.57 7.57 4.29 10.87 10.95 12.14 8.07 8.31 9.57 12.41 12.04 11.72 Site depth (±0.92) (±0.68) (±0.85) (±0.80) (±0.57) (±0.67) (±0.84) (±0.77) (±1.10)

(m) 6.71– 6.71– 7.32– 3.66– 3.66– 4.42– 5.79– 5.49– 4.33– 15.24 15.24 16.08 15.62 15.62 16.76 17.56 17.56 17.98 22.12 24.11 28.08 19.82 18.18 20.40 9.20 9.00 8.22 Distance (±5.43) (±4.21) (±5.00) (±2.24) (±1.67) (±1.67) (±1.08) (±0.92) (±1.11) from shore 6.08– 6.08– 7.12– 9.03– 6.87– 6.54– 1.26– 1.26– 0.79– (km) 45.86 45.86 46.56 39.13 39.14 40.87 19.40 19.40 17.43 36.82 42.10 46.15 68.36 68.61 64.66 22.86 22.10 23.06 (±10.92) (±9.34) (±10.98) (±8.15) (±6.48) (±6.29) (±5.56) (±4.98) (±8.73) Percent sand 0.00– 0.00– 3.09– 1.47– 1.47– 2.85– 0.00– 0.00– 0.00– 99.73 99.73 98.27 99.96 99.96 100.00 92.04 92.04 94.95 stratum for all regions (Figure 2.3, B). This suggested that influence of temperature on density stratification 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

30 across the rest of the coast, while mid and bottom temperatures in the East were significantly cooler than the rest of the coast (Figure 2.3, B).

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

= 87.75, P < 0.0001; Figure 2.4, B), a significant strata effect (F (2, 142.7) = 108.60, P < 0.0001;

Figure 2.4, B), and a significant interaction (F (4, 98.57) = 37.28, P < 0.0001; Figure 2.4, B), 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 2.4, A and B). The three regions differed significantly in stratification and surface-to-bottom mixing. 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 2.5, B). While pairwise comparison of sand and mud were not significantly different within any region, there was an apparent trend toward higher density differences overlying mud and the overall effect was significant (F (1, 119) =

5.03, P = 0.0268; Figure 2.5, B). This indicated significant differences in stratification for major

(regional) and finer-scale (shoal) bathymetric characteristics, while the lack of an interaction between the two suggested strong, independent relationships (F (2, 119) = 0.07, P = 0.9308;

Figure 2.5, B).

Interpolation of bottom DO showed a patchy distribution of hypoxia (Figure 2.6, A).

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

B C

32 of the vertical extent of hypoxia by region (F (2, 50) = 1.64, P = 0.2047; Figure 2.6, B) and dominant sediment type (F (1, 50) = 0.70, P = 0.4059; Figure 2.6, B) were not significant, but the interaction between them was significant (F (2, 50) = 4.43, P = 0.0169; Figure 2.6, B), indicating differences in hypoxia over shoals in relation to major shelf bathymetric characteristics.

Comparisons of intensity of hypoxia showed a significant regional effect (F (2, 50) =

8.11, P = 0.0009; Figure 2.6, C), a non-significant dominant sediment type effect (F (1, 50) =

0.22, P = 0.6441 Figure 2.6, C), and a significant interaction between region and dominant sediment type (F (2, 50) = 3.45, P = 0.0395; Figure 2.6, C). However, sample size was low and pairwise comparisons offered little in relation to the extent of hypoxia (Figure 2.6, B), showing only a weak trend of decreasing intensity from west to east (Figure 2.6, C).

Patterns of interpolated pH were similar to DO (not shown). A significant SLR equation predicted pH based on DO (F (1, 373) = 881.80, P < 0.0001), with an R2 of 70.27%. Interpolated

Secchi depth (not shown) closely resembled surface salinity, and yielded a significant SLR equation (F (1, 123) = 56.64, P < 0.0001), with an R2 of 31.53%.

Comprehensive hydrographic analyses: The three orthogonal factors resulting from the ten variables explained ~73% of the variability in the hydrographic data (Table 2.2). 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 2.7).

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

Environmental variable 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

Eigenvalue 3.01 2.88 1.42 Proportion of variance explained 30.12 28.80 14.24 Cumulative variance explained 30.12 58.92 73.16

A A West

Central

East

actor 3 actor F

Factor 2

Factor 1

actor 3 actor F

Factor 2

Factor 1 Figure 2.7. Factor analysis showing (A) all hydrographic station (n = 343), and (B) two standard errors around the centroid means for nearshore regions off Western LA (West, n = 71), Central LA (Central, n = 162), and Eastern LA (East, n = 110).

coastal snapshot, confirming that regional differences in hydrography were consistent throughout

the two year study.

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 2.8, A). 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 2.8, B). All main effects and double interactions were significant, with no significant triple interaction (Table 2.3). This lent 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.

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 2.4). 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 2.5). Pairwise comparisons for extent of hypoxia showed the magnitude of the variation largely driven by annual differences and differences over sand and mud (Figure 2.9, A).

Table 2.3. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on Factor 3. Asterisks (*) indicate significance of interpretable variables.

Variable Num DF Den DF F P Region 2 66.08 7.11 0.0016 Year 1 84.21 15.61 0.0002 Sed 1 84.21 33.97 < 0.0001 Region x Year 2 66.08 29.55 < 0.0001* Region x Sed 2 66.08 11.63 < 0.0001* Year x Sed 1 84.21 5.54 0.0209* Region x Year x Sed 2 66.08 0.58 0.5631

Table 2.4. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on extent of hypoxia. Asterisks (*) indicate significance of interpretable variables.

Variable Num DF Den DF F P Year 1 120 5.38 0.0221 Region 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 Sed x Year 1 120 0.75 0.3896 Region x Sed x Year 1 120 1.13 0.2893

Table 2.5. Three-way ANOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on intensity of hypoxia. Asterisks (*) indicate significance of interpretable variables.

Variable Num DF Den DF F P Year 2 120 6.10 0.0030 Region 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 Sed x Year 1 120 7.82 0.0060* Region x Sed x Year 1 120 2.43 0.1217

A B

Pairwise comparisons for intensity of hypoxia showed decreasing intensity from west to east

(Figure 2.9, B).

Figure 2.10. Central region composite interpolations of principal component factors 1–3 by depth. Factor scores were interpolated within 1 m depth bins from the 3–18 m isobaths, for 15 total interpolations for each factor. Refer to Figure 2.1 for hydrography locations (n = 343) and regional designations.

Composite factor score interpolations for Factors 1 and 2 by depth interval for the Central region provided similar results to the previous analyses (Figure 2.10). This 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.

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 traits physically characteristic 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-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. The

Central region of the nearshore zone is most highly influenced by fresh water, and 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 waters

< 18 m depth.

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 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), imposing limitations on the extent of freshwater buildup on the coast (McHugh 1967).

This breaks down from July - 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

41 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 Mississippi, 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.

The reduced density difference over sand-dominated sediments intra-regionally (Figure

2.5, A and B) 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 2.4, A). 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,

42 and hydrography, and the complex bathymetry of the Atchafalaya Shelf generally creates greater inshore–nearshore connectivity.

Our findings lead us to agree with a case presented by Bianchi et al. 2008 and Bianchi et al. 2010, calling for a more comprehensive approach to the study of hypoxia beyond the familiar nutrient-centric perspective. 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 has followed a logical progression of relating cause and effect, and while nutrient supply from the Mississippi and Atchafalaya rivers is the most important variable influencing extent and intensity of hypoxia in the nGOM, these results lend supporting evidence to the greater role physicochemical factors may play in determining hypoxia within this system. While 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 why hypoxia is particularly developed in the immediate vicinity of its delta. The major

43 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 a similar regional boundary. 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. As an aside, it is also worth mentioning the effect of oxygen depletion on coastal acidification. Areas susceptible to hypoxia necessarily experience appreciably lower pH, lowering calcium carbonite saturation in the water column, particularly for aragonite. This effect is exacerbated in brackish waters, making the lower water column of Louisiana’s nearshore zone particularly unsuitable for exoskeleton building organisms, and it heightens the potential impact of global ocean acidification within this coastal zone (Melzner et al. 2012).

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 Rosenburg; 1978; Meyer 1994 and references therein) and higher metal contents (Kristiansen et al. 2002, Kristensen et al. 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 daily producing pure oxygen (~500% saturation)

44 within the portion of the water column most susceptible to hypoxia (Baustian et al. 2011, 2013).

The combination of these effects, and others probably led to the patchy distribution of hypoxia observed throughout the nearshore zone over the course of the study, and may provide beneficial areas of continued research, and incorporation into the broader picture of hypoxia in the nGOM.

Conclusions

Many variables affect the nearshore hydrography of Louisiana. Differences in mixing 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. This is particularly true of the Atchafalaya Shelf within the extent of the 10 m isobath. This defines the most estuary-like nearshore environment of coastal Louisiana, with features that make it less susceptible to developing and sustaining hypoxia. 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 of marine benthic organisms outside of the hypoxic season.

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

45 important roles in the way hypoxia develops. These findings suggest that major nearshore bathymetric transitions and the presence of sandy shoals significantly alter the hydrographic structure of the water column, including the capacity for stratification, in consistent ways and at biologically relevant scales. While 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 may also be host to benthic microalgae which can oxygenate bottom waters under certain conditions, all of which probably contributed to the resistance and low intensity and duration of hypoxia over shoals observed during this study.

Development of 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 candidate for future study.

There is a dynamic interplay among salinity, depth, and DO within the nearshore zone which probably drives significant shifts in biological distributions. Restricted availability of bottom-water sites due to summertime hypoxia might further alter distribution within a highly- stratified water column where environmental variation is substantial in the vertical dimension.

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.

References

Alexander CE, MA Broutman, DW Field. 1986. An inventory of coastal wetlands of the USA.

Allison MA, GC Kineke, ES Gordon, MA Goni. 2000. Development and reworking of a seasonal flood deposit on the inner continental shelf off the Atchafalaya River. Continental Shelf Research 20: 2267–2294.

Atwood DK, A Bratkovich, M Gallagher, GL Hitchcock. 1994. Introduction to the dedicated issue. Estuaries and Coasts 17: 729–731.

Baltz DM, JW Fleeger, C Rakocinski, JN McCall. 1997. Food, density, and microhabitat: factors affecting growth and recruitment potential of juvenile saltmarsh fishes. Environmental Biology of Fishes 53: 89–103.

Baltz DM, RF Jones. 2003. Temporal and spatial patterns of microhabitat use by fishes and decapod crustaceans in a Louisiana estuary. Transactions of the American Fisheries Society 132: 662–678.

Baustian MM, NN Rabalais, WL Morrison, RE Turner. 2011. Seasonal microphytobenthos on the hypoxic-northern Gulf of Mexico continental shelf. Marine Ecology Progress Series 436: 51–66.

Baustian MM, NN Rabalais, WL Morrison, REugene Turner. 2013. Microphytobenthos along the Louisiana continental shelf during mid-summer hypoxia. Continental Shelf Research 52: 108–118.

Bianchi TS, RL Cook, EM Perdue, PE Kolic, N Green, Y Zhang, RW Smith. 2011. Impacts of diverted freshwater on dissolved organic matter and microbial communities in Barataria Bay, Louisiana, USA. Marine Environmental Research 72: 248–257.

Bianchi TS, SF DiMarco, MA Allison, P Chapman, JH Cowan Jr, RD Hetland, JW Morse, G Rowe. 2008. Controls and consequences of hypoxia on the Louisiana shelf (USA): beyond the nutrient-centric view. EOS, Transactions American Geophysical Union 89: 236–237.

Bianchi TS, SF DiMarco, JH Cowan Jr, RD Hetland, P Chapman, JW Day, MA Allison. 2010. The science of hypoxia in the Northern Gulf of Mexico: a review. Science of the Total Environment 408: 1471–1484.

Bianchi TS, SF DiMarco, RW Smith, KM Schreiner. 2009. A Gradient of Dissolved Organic Carbon and Lignin from Terrebonne-Timbalier Bay Estuary to the Louisiana Shelf (USA). Marine Chemistry 117: 32–41.

Bierman VJ Jr, SC Hinz, D Zhu, WJ Wiseman Jr, NN Rabalais, RE Turner. 1994. A preliminary mass balance model of primary productivity and dissolved oxygen in the Mississippi River plume/inner Gulf Shelf region. Estuaries 17: 886–899.

Breitburg DL. 2002. Effects of hypoxia, and the balance between hypoxia and enrichment, on coastal fishes and fisheries. Estuaries 25: 767–781.

Chesney EJ, DM Baltz. 2001. The effects of hypoxia on fisheries in the northern Gulf of Mexico. In Coastal hypoxia: consequences for living resources and ecosystems, eds. Rabalais NN, RE Turner, 321–354. American Geophysical Union, Coastal and Estuarine Studies.

Chesney EJ, DM Baltz, RG Thomas. 2000. Louisiana estuarine and coastal fisheries and habitats: perspectives from a fish’s eye view. Ecological Applications 10: 350–366.

Cho K, RO Reid, WD Nowlin Jr. 1998. Objectively mapped stream-function fields on the Texas- Louisiana Shelf based on 32 months of moored current meter data. Journal of Geophysical Research 103: 10377–10390.

Cochrane JD, FJ Kelly Jr. 1986. Low-frequency circulation on the Texas-Louisiana continental shelf. Journal of Geophysical Research 91: 10645–10659.

Coleman JM, SM Gagliano. 1964. Cyclic sedimentation in the Mississippi River deltaic plain. Transactions of the Gulf Coast Association of Geological Societies 14: 67–82.

Dagg MJ, JW Ammerman, RMW Amon, WS Gardner, RE Green, SE Lohrenz. 2007. A review of water column processes influencing hypoxia in the northern Gulf of Mexico. Estuaries and Coasts 30: 735–752.

Dahm CN, RJ Edwards, FP Gelwick. 2005. Gulf Coast Rivers of the Southwestern United States. In Rivers of North America, eds. Benke AC, CE Cushing, 181–228. Burlington, Massachusetts: Elsevier Academic Press.

DiMarco SF, P Chapman, ND Walker, RD Hetland. 2010. Does local topography control hypoxia on the eastern Texas-Louisiana shelf? Journal of Marine Systems 80: 25– 35.

DiMarco SF, OR Reid. 1998. Characterization of the principal tidal current constituents on the Texas‐Louisiana shelf. Journal of Geophysical Research: Oceans 103: 3093–3109.

Dinnel SP, WJ Wiseman Jr. 1986. Fresh-water on the Louisiana and Texas shelf. Continental Shelf Research 6: 765–784.

Fofonoff NP, RC Millard Jr. 1983. Algorithms for computation of fundamental properties of seawater. UNESCO technical papers in marine science 44: 6–14.

Fry B, D Justić, P Riekenberg, EM Swenson, RE Turner, L Wang, L Pride, NN Rabalais, JC Kurtz, JC Lehrter, MC Murrell, EH Shadwick, B Boyd. (2015). Carbon dynamics on the Louisiana continental shelf and cross-shelf feeding of hypoxia. Estuaries and Coasts 38: 703–721.

Grippo M, JW Fleeger, RE Condrey, KR Carman. 2009. High benthic microalgal biomass found on Ship Shoal, north-central Gulf of Mexico. Bulletin of Marine Science 84: 237–256.

Hansen DV, M Rattray Jr. 1966. New dimensions in estuary classification. Limnology and Oceanography 11: 319–326.

Hetland RD. 2005. Relating river plume structure to vertical mixing. Journal of Physical Oceanography 35: 1667–1688.

Hetland RD, K Fennel, CK Harris, J Kaihatu, K Xu SF DiMarco. 2012. Integrated bio-physical modeling of Louisiana-Texas (LATEX) Shelf. U.S. Dept. of the Interior, Bureau of Ocean Energy Management Gulf of Mexico OCS Region, New Orleans, LA. OCS Study BOEM: 108–128.

Hetland RD, SF DiMarco. 2008. The effects of bottom oxygen demand in controlling the structure of hypoxia on the Texas-Louisiana continental shelf. Journal of Marine Systems 70: 49–62.

Hetland RD, SF DiMarco. 2012. Skill assessment of a hydrodynamic model of circulation over the Texas-Louisiana continental shelf. Ocean Modelling 43: 64–76.

INSTAAR, University of Colorado. 2011. Seafloor substrates griddings, Gulf of Mexico.

Jahnke RA, JR Nelson, RL Marinelli, JE Eckman. 2000. Benthic flux of biogenic elements on the Southeastern US continental shelf: influence of pore water adjective transport and benthic microalgae. Continental Shelf Research 20: 109–127.

Justić D, NN Rabalais, RE Turner, WJ Wiseman. 1993. Seasonal coupling between riverborne nutrients, net productivity and hypoxia. Marine Pollution Bulletin 26: 184–189.

Kristensen E, KD Kristiansen, MH Jensen. 2003. Temporal behavior of manganese and iron in a sandy coastal sediment exposed to water column anoxia. Estuaries 26: 690–699.

Kristiansen KD, E Kristensen, MH Jensen. 2002. The influence of water column hypoxia on the behavior of manganese and iron in sandy coastal marine sediment. Estuarine, Coast, and Shelf Science 55: 645–654.

Lehrter, JC, DL Beddick Jr, R Devereux, DF Yates, MC Murrell. 2012. Sediment-water fluxes of dissolved inorganic carbon, O2, nutrients, and N2 from the hypoxic region of the Louisiana continental shelf. Biogeochemistry 109: 233–252.

Lehrter JC, B Fry, MC Murrell. 2014. Microphytobenthos production potential and contribution to bottom layer oxygen dynamics on the inner Louisiana continental shelf. Bulletin of Marine Science 90: 765–780.

Lehrter, JC, DS Ko, MC Murrell, JD Hagy, BA Schaeffer, RM Greene, RW Gould, B Penta. 2013. Nutrient distributions, transports and budgets on the inner margin of a river dominated continental shelf. Journal of Geophysical Research: Oceans 188: 1–17.

Lehrter, JC, MC Murrell, and JC Kurtz. 2009. Interactions between freshwater input, light, and phytoplankton dynamics on the Louisiana continental shelf. Continental Shelf Research 29: 1861–1872.

Livingston RJ. 1988. Inadequacy of species-level designations for ecological studies of coastal migratory fishes. Environmental Biology of Fishes 22: 225–234.

Mayer LM. 1994. Surface area control of organic carbon accumulation in continental shelf sediments. Geochimica et Cosmochimica Acta 58: 1271–1284.

McHugh JL. 1967. Estuarine nekton. In Estuaries, ed. Lauff GH, 581–620. American Association for the Advancement of Science.

Melzner F, J Thomsen, W Koeve, A Oschlies, MA Gutowska, HW. Bange, HP Hansen, A Körtzinger. 2012. Future ocean acidification will be amplified by hypoxia in coastal habitats. Marine Biology 160: 1875–1888.

Milliman JD, RH Meade. 1983. World-wide delivery of river sediment to the oceans. The Journal of Geology 1–21.

National Oceanic and Atmospheric Administration, National Ocean Service. 1975. The Coastline of the United States. PA 71046

Nowlin WD Jr, AE Jochens, SF DiMarco, RO Reid, MK Howard. 2005. Low-frequency circulation over the Texas-Louisiana continental shelf. In Circulation in the Gulf of Mexico: observations and models, eds. Sturges W, A Lugo-Fernandez, 219–240. AGU Geophysics Monograph-American Geophysical Union.

Pearson TH, R Rosenberg. 1978. Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. Oceanography and Marine Biology: an Annual Review 16: 229–311.

Penland S, J Suter, R McBride, J Williams, J Kindinger, R Boyd. 1989. Holocene Sand Shoals Offshore the Mississippi River Delta Plain. Transactions-Gulf Coast Association of Geological Societies 39: 471–480.

Penland S, R Boyd, J Suter. 1988. Transgressive Depositional Systems of the Mississippi Delta Plain: A Model for Barrier Shoreline and Shelf Sand Development. Journal of Sedimentary Petrology 58: 932–949.

Pokryfki Lynn, RE Randall. 1987. Nearshore hypoxia in the bottom water of the northwestern Gulf of Mexico from 1981 to 1984. Marine Environmental Research 22: 75–90.

Pritchard DW. 1955. Estuarine circulation patterns. Proceedings from the American Society of Civil Engineering 81: 71711–717111.

Pritchard DW. 1967. What is an estuary: physical viewpoint. In Estuaries, ed. Lauff GH, 757. American Association for the Advancement of Science.

Quiñones-Rivera ZJ, B Wissel, D Justić, B Fry. 2007. Partitioning oxygen source and sinks in a stratified coastal ecosystem using stable oxygen isotopes. Marine Ecology Progress Series 342: 69–83.

Rabalais NN, RE Turner, BK Sen Gupta, DF Boesch, P Chapman, MC Murrell. 2007. Hypoxia in the northern Gulf of Mexico: Does the science support the plan to reduce, mitigate, and control hypoxia? Estuaries and Coasts 30: 753–772.

Rabalais NN, RE Turner, WJ Wiseman Jr. 2002. Gulf of Mexico hypoxia, A.K.A. “the Dead Zone.” Annual Review of Ecology and Systematics 33: 235–263.

Rabalais NN, RE Turner, WJ Wiseman Jr, DF Boesch. 1991. A brief summary of hypoxia on the northern Gulf of Mexico continental shelf: 1985–1988. In Modern and Ancient Continental Shelf Anoxia, eds.Tyson RV, TH Pearson, 35–46. Geological Society Special Publication.

Rabalais NN, WJ Wiseman Jr, RE Turner. 1994. Comparison of continuous records of near- bottom dissolved oxygen from the hypoxia zone along the Louisiana coast. Estuaries 17: 850–861.

Remmert H.1983. Studies and thoughts about the zonation along the rocky shores of the Baltic. Zoologica 22: 121–125.

Renaud ML. 1986. Hypoxia in Louisiana coastal waters during 1983: implications for fisheries. Fisheries Bulletin 84:19–26.

Rydberg L, L Edler, S Floderus, W Graneli. 1990. Interaction between supply of nutrients, primary production, sedimentation and oxygen consumption in SE Kaaegat. Ambio Stockholm 19: 134–41.

Scavia D, NN Rabalais, RE Turner, D Justić, WJ Wiseman Jr. 2003. Predicting the response of Gulf of Mexico hypoxia to variations in Mississippi River nitrogen load. Limnology and Oceanography 48: 951–956.

Schroeder WS. 1978. Riverine influence on estuaries: a case study. In Estuarine Interactions, ed. Wiley ML, 347–364. Academic Press, NY.

Shaw RF, Wiseman WJ Jr, Turner RE, Rouse LJ Jr, Condrey RE, Kelly FJ Jr. 1985. Transport of larval gulf menhaden Brevoortia patronus in continental shelf waters of wester Louisiana: a hypothesis. Transactions of the American Fisheries Society 114: 452– 460.

Switzer TS, Chesney EJ, DM Baltz. 2006. Exploring temporal and spatial variability in nekton community structure in the northern Gulf of Mexico: unravelling the potential influence of hypoxia. Proceedings of the Gulf and Caribbean Fisheries Institute 57: 699–716.

Turner RE, NN Rabalais. 1991. Changes in the Mississippi River water quality this century. Bioscience 41: 140–147.

Turner RE, NN Rabalais. 2003. Linking landscape and water quality in the Mississippi River basin for 200 years. BioScience 53: 563–572.

Valle-Levinson A, C Reyes, R Sanay. 2003. Effects of bathymetry, friction, and rotation on estuary-ocean exchange. Journal of Physical Oceanography 33: 2375–2393.

Valle‐Levinson A, K Lwiza. 1995. The effects of channels and shoals on exchange between the Chesapeake Bay and the adjacent ocean. Journal of Geophysical Research: Oceans 100: 18551–18563.

Vaquer-Sunyer R, CM Duarte. 2008. Thresholds of hypoxia for marine biodiversity. Proceedings of the National Academy of Science USA 105:15452–15457.

Walker ND. 2005. Wind and Eddy‐Related Shelf/Slope Circulation Processes and Coastal Upwelling in the Northwestern Gulf of Mexico. Circulation in the Gulf of Mexico: observations and models 295–313.

Walker ND, WJ Wiseman Jr, LJ Rouse, A Babin. 2005. Effects of river discharge, wind stress, and slope eddies on circulation and the satellite-observed structure of the Mississippi River Plume. Journal of Coastal Resources 21: 1228–1244.

Wang L, D Justić. 2009. A modeling study of the physical processes affecting the development of seasonal hypoxia over the inner Louisiana-Texas shelf: Circulation and stratification. Continental Shelf Research 29: 1464–1476.

Wilson CA, MA Allison. 2008. An equilibrium profile model for retreating marsh shorelines in southeast Louisiana. Estuarine and Coastal Shelf Science 80: 483–494.

Winkler L. 1888. The determination of dissolved oxygen in water. Berichte der Deutschen Chemischen Gesellschaft 21: 28–43.

Wiseman WJ Jr, EM Swenson, FJ Kelly. 1990. Control of estuarine salinities by coastal ocean salinity. In Residual currents and long-term transport, ed. Cheng RT, 184–193. Springer, NY.

Wiseman, WJ Jr, NN Rabalais, RE Turner, SP Dinnel, A MacNauthton. 1997. Seasonal and interannual variability within the Louisiana coastal current: stratification and hypoxia. Journal of Marine Systems 12: 237–248.

Wiseman WJ Jr, W Sturges. 1999. Physical oceanography of the Gulf of Mexico: processes that regulate its biology. In The Gulf of Mexico Large Marine Ecosystem, eds. Kumpf H, K Steidinger, K Sherman, 77–92. Maiden, Massachusetts: Blackwell Science.

Wright LD. 1970. Circulation, effluent diffusion and sediment transport, mouth of South Pass, Mississippi River delta. Technical Report 84, Coastal Studies Institute, Louisiana State University, Baton Rouge, Louisiana.

Zhang X, RD Hetland, M Marta‐Almeida, SF DiMarco. 2012. A numerical investigation of the Mississippi and Atchafalaya freshwater transport, filling and flushing times on the Texas- Louisiana shelf. Journal of Geophysical Research: Oceans 117: 1978–2012.

Zhang W, RD Hetland, SF DiMarco, K Fennel. 2015. Processes controlling mid-water column oxygen minima over the Texas‐Louisiana shelf. Journal of Geophysical Research: Oceans 120: 2800–2812.

CHAPTER III: COASTWIDE FISH ASSEMBLAGES AROUND SMALL OIL AND GAS PLATFORMS IN LOUISIANA’S NEARSHORE WATERS

Epitome

Recent years have seen a trend toward removal of the abundant oil and gas installations in the northern Gulf of Mexico (nGOM), particularly small, unmanned, non-drilling structures

(platforms) in shallow, nearshore waters (federal waters < 18 m deep). Since 2007 the platform count has decreased by184 ± 54 (95% CI) per year, a reduction of ~38%. The result has been an abrupt decline of high-relief artificial reef habitat in a region that has served for a half-century as the largest unplanned artificial reef network on Earth. Prior studies of platforms have consistently focused on a few relatively large platforms standing in depths ≥ 18 m. However, more than one-third of all federally-listed oil and gas structures that have been built in the nGOM have been small platforms in shallow water. Remotely deployed video, water quality data and diver observations documented relative abundances of fishes and environmental conditions around 150 platforms sited at depths < 18 m during the summers of 2013 and 2014. Visibility was adequate for species composition analyses in ~59% of all videos. Fifty-four fish species in one or more life history stages were documented around small platforms. Those included the endangered goliath grouper (Epinephelus itajara), the invasive red lionfish (Pterois volitans), and age 1–2 and or young-of-the-year juveniles of 29 other species. Three coastal regions were identified based upon hydrography as well as differences between dominant sediment type

(sandy shoal to mud bottom), presence or absence of hypoxia (dissolved oxygen < 50% saturation), and platform complexity. Each coastal region showed significantly different fish assemblages (by species richness, Shannon-Weiner diversity, and/or species composition). The regional differences of these “de facto” artificial reefs based on environmental variability will be useful for future artificial reef planning in Louisiana’s nearshore zone.

Introduction

A biologically relevant designation for Louisiana’s nearshore zone is defined between the 5–25 m isobaths (Chesney and Baltz 2001; Switzer et al. 2006). This coastal zone includes the federal waters of the outer continental shelf (OCS) most highly affected by riverine influence. The coastal zone off Louisiana is a broad, gently pitched shelf, strongly influenced by the outflow of the Mississippi-Atchafalaya river systems. The Mississippi River Basin is the third largest drainage on Earth (Milliman and Mead 1983), draining ~41% of the contiguous United States and some of Canada (Turner and Rabalais 1991). The long-term mean annual discharge (1817–

2002) of the Mississippi River is the largest in North America at 537 km3 yr−1 (Turner and

Rabalais 2003), and in recent decades (1966–2006) discharge has been relatively high at 580 km3 yr−1 (Mead and Moody 2010). The Atchafalaya discharges < 30% of the total volume, typically varying from 15–29% (Allison et al. 2000) and provides the second largest discharge to the Gulf

(Dahm et al. 2005). The Mississippi-Louisiana and Texas-Louisiana borders are defined by two additional smaller rivers, the Pearl and the Sabine, which discharge ~12 and 7.5 km3 yr−1, representing the fourth and fifth largest discharges to the Gulf (Dahm et al. 2005). The

Mississippi and Atchafalaya rivers dynamically influence the physical characteristics of the water column across the Louisiana-Texas (LATEX) Shelf, and contribute massive quantities of nutrients to an otherwise oligotrophic system. Nutrient availability sustains gross primary production that in turn contributes to the productive fisheries of the Fertile Fisheries Crescent, extending from Port Arthur, Texas to, Pascagoula, Mississippi (Günter 1963; Nixon et al. 1986).

Louisiana is second only to Alaska in US fisheries yields (National Marine Fisheries

Service (NMFS) 2015). The primary productivity associated with the Fertile Fisheries Crescent has enabled Louisiana to dominate Gulf landings and total dollars earned since 1950 (Chesney et

55 al. 2000; NMFS 2015). These landing are largely Gulf menhaden (Brevoortia patronus), a species that has increased in abundance despite large landings (Vaughan 1996), and presently ranks 19th among the largest global fisheries (Food and Agriculture Organization of the United

Nations (FAO) 2014). Although some species have experienced relative declines, overall landings aside from menhaden have increased for many pelagic and demersal species (Chesney et al. 2000). Additionally, the northern Gulf of Mexico (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 2015). Known as the “Sportsman’s Paradise”, Louisiana is foremost within the nGOM in total catch per trip. Florida has the highest annual recreational catch in the country, with ~54% of the catch in > 70% of the trips in the nGOM from 1981–

2014, while Louisiana is responsible for ~32% of the total catch in just 16% of those trips

(NMFS 2015).

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. This study only targeted platforms in < 18 m water depth, where platforms are consequently likely to represent a larger proportion of the overall hard bottom within the nearshore zone. 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 of any US 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.

To date, the Rigs-to-Reefs program (Reggio et al. 1987) has deployed material from 470 platforms (BSEE 2015), of which material from 370 platforms was sited in federal waters of the

OCS off the coast of Louisiana (LDWF 2015). 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

57 into nearshore waters (January, 2014). This plan defines nearshore to a depth of 100 m, and the

2015 Gulf of Mexico Fishery Management Council 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 are the effect of nutrient enrichment in nearshore Louisiana and related development of hypoxia (Rabalais et al.

2002; Switzer et. al 2006). The seasonally ephemeral low oxygen zone (dissolved oxygen (DO)

< 2.0 mg l−1) that forms along coastal Louisiana is the second largest hypoxic area on Earth, and is believed to be growing in direct relation to increased nutrient inputs from the Mississippi

River (Rabalais et al. 2002). 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 II). The distribution of sandy shoals, which offer vertical relief, can cause variable circulation patterns (DiMarco et al. 2010; Chapter II). However, most of the nearshore zone is subject to bottom-water oxygen depletion associated with eutrophication, and sand shoals periodically experience severe hypoxic episodes but it is less extensive and of shorter duration than over surrounding mud bottoms (Craig and Bosman 2013; Reeves 2015).

While some fish species can avoid the hypoxic area entirely through longitudinal movements across the coastal zone, or moving outside the affected depth range (Switzer et al.

2009; Switzer et al. 2006), 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). 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

58 more accurately ‘maximum relief’) profiles of platforms extending above the surface provide a unique resource that is undeniably important in helping to sustain occupation of the area by some reef-associated fishes when hypoxia intensifies.

The purpose of this study 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 II), and likelihood that fish assemblages associate with different sediments for other reasons. In addition, the two-year study assessed interannual variation, and evaluated local differences in assemblage composition based on platform complexity and the presence and absence of hypoxia defined as DO < 50% saturation.

Methods

Field: 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 were grouped into three categories. Category 1 platforms had single-piling “jackets” (platform legs

59 providing structural support), category 2 included platforms with two piling jackets, or > two piling jackets without crossbeams, and category 3 platforms had ≥ three piling jackets with crossbeams (Figure 3.1).

Sampling entailed 28 single day cruises aboard a 30’ vessel. Sampling dates were spread over two years, with 14 days in 2013, and 14 days in 2014, during summer months between July

12 to September 06 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.

A B

C D

Figure 3.1 Three categories were used to group structures based on complexity. Category 1 included single-piling jackets, caissons, or unmanned fixed platforms (A). Category 2 included caisson or unmanned fixed platforms with > 1 piling jackets without crossbeams (B). Category 3 was well protectors with ≥ 3 piling jackets connected by crossbeams (C). Large, highly complex structures and those which discharged waterborne or airborne contaminants such as produced water or sulfide gas were avoided. 60

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.

Hydrographic data were collected at all platforms sampled throughout the coastal zone.

A YSI model 6820 V2 sonde was used to profile salinity (psu), temperature (°C), depth (m), atmospheric pressure (mm Hg), 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, of which 322 were platforms and 21 were hydrographic stations between platforms. Of the 343 hydrographic profiles, 181 profiles were sampled in 2013, and 162 in

2014.

Video processing: Because of the high primary productivity and sediment inputs from the rivers, turbidity in the nearshore coastal zone off Louisiana was highly variable. 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 therefore 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 (Reeves et al. in review). The effect was a concentrated fish assemblage that was more amenable to video-based sampling than prior studies of larger structures had reported (Bull

Figure 3.2. All sites of hydrographic (n = 343) and video (n = 150) data used in analyses. Colored areas represent regions of distinctly different hydrography and assemblage composition of reef-associated fishes. Green circles indicate hydrographic sampling locations, orange circles indicate paired video and hydrographic sampling locations, and hollow black squares show the distribution of federally-managed oil and gas structures. Longitudes −92.5° and −90.4° mark regional boundaries. Contours are shown for the 5 m, 10 m, 15 m, 20 m, and 25 m isobaths. The red star indicates the location of East Bay.

and Kendell 1994). Of the 322 platforms, 150 were both unique (representing independent

samples) and had water quality conditions with visibility suitable for analyses. Thirty-two

videos were obtained from the West region, 70 were obtained from the Central region, and 48

were obtained from the East region (Figure 3.2). Of those, 65 videos were from 2013, and 85

from 2014. Additionally, 63 videos were recorded over sand-dominated sediments and 87 were

recorded over mud-dominated sediments. Eighty-four videos were recorded in the absence of

hypoxia while 66 were recorded in the presence of hypoxia (DO < 50% saturation). Finally, 84

62 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 3.1).

Videos were analyzed for relative abundance estimates 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, representing the lowest estimate for that species abundance for that site (Priede et al. 1994; Ellis and DiMartini 1995; Willis and Babcock 2000; Wells and Cowan 2007). This was repeated for every species visible and identifiable on video. 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 sampling was adequate to characterize the fish assemblages associated with each comparison to the potential of our methods. 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 analyses, 37 camera drops were equipped with one outward-facing, and one downward-facing synchronized cameras rather than all four. These samples were obtained during an initial survey and were only included in cases where the camera array twisted minimally in the water column and maintained a view of the submerged structure.

Disparity in total volume sampled in addition to variation caused by visibility among all

63 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. Analyses comparing species richness and Shannon-Weiner diversity between the two camera array configurations were conducted using generalized linear mixed models run with and without the effort covariate

(SAS 9.4). Species composition estimates were compared using a PERMANOVA with and without the effort covariate (PRIMER). All comparisons were based on fish counts from 31 platforms collected in 2013. Platform nested in region was included as a random effect in all models while array configuration, effort, and their interaction were included as fixed effects.

Array configuration was marginally significant for species richness without accounting for effort

(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 probability 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) by including the effort covariate. 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).

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

64 expressed in terms of the effective number of species (ENS) for more meaningful interpretation

(Jost 2006):

ENS = exp(퐻′) = exp(-∑i 푝iln푝i)

th where pi was the total proportion of the i species (Shannon 1948). Regional and annual differences were compared for platforms in hypoxic (DO < 50% saturation) and well- oxygenated waters using three-way 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 least-squares 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 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 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

65 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 the 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.

Results

Observations: During this study 54 fish species representing 28 families were observed in association with small oil and gas platforms throughout the Louisiana nearshore coastal zone

(Table 3.1). 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 3.1; Figure 3.3). 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

Table 3.1. Regional distributions and percent occurrence of fishes identified on video. Next to the common names are the numbers of platforms where each species was present, and the fraction (of 150) those platforms represented within each nearshore Louisiana coastal region (West, Central, and East), and year (2013 and 2014). Next to the taxonomic names are the percent of the total number of fish observed (mean MAXNO of fish per platform). MAXNOs are adult fish unless noted as age 1–2 juveniles (juv.), young-of-the-year (YOY), or mixed adults (adu.), juv., and or YOY. Asterisks (*) indicate species for which YOY were detected by divers, but absent, or under-sampled by the camera array.

West Central East Species 2013 2014 2013 2014 2013 2014 Sergeant major* (adu. + juv.) 4 (33%) 16 (80%) 2 (10%) 29 (56%) 0 2 (13%) Abudefduf saxatilis (4%) 47% 3% 40% 0 5% Unicorn leatherjacket 0 1 (5%) 0 0 0 0 Aluterus monoceros 0 100% 0 0 0 0 Porkfish 0 0 0 0 0 1 (7%) Anisotremus virginicus 0 0 0 0 0 100% Sheepshead 12 (100%) 14 (70%) 17 (85%) 44 (88%) 30 (91%) 14 (93%) Archosargus probatocephalus 11% 8% 10% 35% 11% 25% Gray triggerfish* (adu. + juv.) 5 (42%) 16 (80%) 11 (55%) 38 (76%) 10 (30%) 10 (67%) Balistes capriscus 11% 25% 7% 19% 5% 33% Yellow jack* 2 (17%) 4 (20%) 2 (10%) 3 (6%) 0 0 Carangoides bartholomaei 79% 14% 4% 3% 0 0 Blue runner (adu. + juv.) 7 (58%) 13 (65%) 16 (80%) 47 (94%) 9 (27%) 8 (53%) Caranx crysos 9% 22% 14% 28% 7% 20% Jack crevalle 1 (8%) 3 (15%) 6 (30%) 13 (26%) 6 (18%) 9 (60%) Caranx hippos 2% 15% 20% 16% 12% 34% Jack crevalle (juv.) 0 2 (17%) 7 (35%) 7 (14%) 1 (3%) 0 Caranx hippos 0 10% 56% 31% 3% 0 Bar jack* (juv.) 0 3 (15%) 0 0 0 0 Caranx ruber 0 100% 0 0 0 0 Blacktip shark 0 0 0 1 (2%) 0 0 Carcharhinus limbatus 0 0 0 100% 0 0 Bull shark 0 0 0 1 (2%) 0 0 Carcharhinus leucas 0 0 0 100% 0 0 Atlantic spadefish* (adu. + juv.) 12 (100%) 20 (100%) 20 (100%) 50 (100%) 32 (97%) 15 (100%) Chaetodipterus faber 12% 40% 12% 16% 4% 6% Atlantic bumper (adu. + juv.) 4 (33%) 16 (80%) 4 (20% 25 (50%) 15 (45%) 2 (13%) Chloroscombrus chrysurus 1% 30% 1% 45% 12% 10% Southern stingray 1 (8%) 0 0 4 (8%) 1 (3%) 0 Dasyatis americana 43% 0 0 41% 16% 0 Rainbow runner* 0 2 (10%) 0 8 (16%) 0 2 (13% Elagatis bipinnulata 0 16% 0 62% 0 22% Ladyfish 3 (25%) 2 (10%) 0 6 (12%) 1 (3%) 0 Elops saurus 33% 17% 0 49% 1% 0 Red hind 0 0 0 0 0 2 (13%) Epinephelus guttatus 0 0 0 0 0 100% Goliath grouper 0 0 0 0 0 1 (6.67%) Epinephelus itajara 0 0 0 0 0 100% Bluntnose jack (juv.) 0 0 0 1 (2%) 0 0 Hemicaranx amblyrhynchus 0 0 0 100% 0 0

(Table 3.1 continued)

West Central East Species 2013 2014 2013 2014 2013 2014 Queen angelfish* 0 0 0 0 1 (2%) 1 (7%) Holacanthus ciliaris 0 0 0 0 31% 69% Bermuda chub 4 (33%) 13 (65%) 6 (30%) 31 (62%) 1 (3%) 1 (7%) Kyphosus sectatrix 6% 48% 6% 37% 1% 2% Pinfish 0 4 (33%) 1 (20%) 10 (20%) 1 (3%) 0 Lagodon rhomboides 0 38% 6% 54% 1% 0 Trippletail 0 1 (5%) 0 0 1 (3%) 0 Lobotes surinamensis 0 45% 0 0 55% 0 Red snapper* 3 (25%) 4 (20%) 7 (35%) 18 (36%) 18 (55%) 12 (80%) Lutjanus campechanus 4% 3% 6% 11% 40% 36% Red snapper* (juv.) 3 (25%) 5 (25%) 0 7 (14%) 10 (30%) 1 (7%) Lutjanus campechanus 33% 13% 0 13% 34% 8% Gray snapper* (adu. + juv.) 7 (58%) 5 (25%) 19 (95%) 41 (82%) 26 (79%) 14 (93%) Lutjanus griseus 5% 2% 34% 12% 15% 31% Dog snapper* (adu. + juv.) 0 0 1 (5%) 0 0 1 (7%) Lutjanus jocu 0 0 27% 0 0 73% Lane snapper* (adu. + juv.) 2 (17%) 3 (15%) 3 (15%) 4 (8%) 1 (3%) 0 Lutjanus synagris 72% 7% 14% 4% 4% 0 Stripped mullet 0 0 0 6 (12%) 0 0 Mugil cephalus 0 0 0 100% 0 0 Pigfish 1 (8%) 2 (10%) 0 3 (6%) 1 (3%) 0 Orthopristis chrysoptera 26% 68% 0 5% 1% 0 Black drum 2 (17%) 2 (10%) 0 7 (14%) 5 (15%) 3 (20%) Pogonias cromis 13% 15% 0 41% 16% 15% Bluefish (adu. + juv.) 2 (17%) 13 (65%) 4 (20%) 20 (40%) 5 (15%) 0 Pomatomus saltatrix 8% 61% 4% 24% 3% 0 Red lionfish (adu. + juv.) 0 0 0 0 0 2 (13%) Pterois volitans 0 0 0 0 0 100% Cobia (adu. + juv. + YOY) 5 (42%) 11 (55%) 6 (30%) 13 (26%) 5 (15%) 2 (13%) Rachycentron canadum 11% 57% 9% 10% 8% 3% Red drum 4 (33%) 1 (5%) 2 (10%) 11 (22%) 9 (27%) 3 (20%) Sciaenops ocellatus 18% 3% 5% 15% 33% 25% Spanish mackerel 2 (17%) 1 (5%) 0 11 (22%) 1 (3%) 1 (7%) Scomberomorus maculatus 32% 2% 0 38% 21% 6% Atlantic lookdown 2 (17%) 3 (15%) 4 (20%) 6 (12%) 3 (9%) 4 (27%) Selene vomer 18% 4% 35% 15% 7% 20% Greater amberjack (YOY) 7 (58%) 14 (70%) 2 (10%) 13 (26%) 1 (3%) 3 (20%) Seriola dumerili 28% 40% 1% 18% 1% 12% Almaco jack (YOY) 0 10 (50%) 0 4 (8%) 0 1 (7%) Seriola rivoliana 0 76% 0 7% 0 17% Planehead filefish 1 (8%) 0 0 0 0 0 Stephanolepis hispidus 100% 0 0 0 0 0 Florida pompano 0 0 4 (20%) 17 (34%) 0 0 Trachinotus carolinus 0 0 50% 50% 0 0

A B C

D E F

Figure 3.3. 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). juvenile horse-eye jack (Caranx latus) YOY spotfin butterflyfish (Chaetodon ocellatus), adult and YOY Florida blenny (Chasmodes saburrae), feather blenny (Hypsoblennius hentz), and tessellated blenny (H. invemer), 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).

Among the most interesting findings during 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 3.2). 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 durring a dive survey in September of 2013, while a third was videoed in July of 2014. A potential fourth goliath was recorded during July of 2013,

69 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 red lionfish (Pterois volitans) and sun coral (Tubastarea coccinea).

Interestingly, 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 its most immediate proximity to the point source of eutrophication in the region (i.e., 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 the 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: intensly 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.

Statistical analyses: Species richness and Shannon-Weiner diversity (H′) varied significantly across the study area. The three-way 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

3.2). Pairwise comparison of richness showed the highest overall richness in the West region,

70 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

3.4, A). The three-way ANCOVA for Shannon-Weiner diversity indicated marginal significance for region and platform complexity (P = 0.0620, and 0.0572; Table 3.3). 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 number in the East. The ENS was

Variable Num DF Den 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

Variable Num DF Den DF F P Region 2 134 2.84 0.0620~ Year 1 134 1.49 0.2248 Hypoxia 1 134 1.53 0.2187 % Sand 1 134 0.12 0.7306 Effort 1 134 0.52 0.4714 Complexity 2 134 2.92 0.0572~ Region x Hypoxia 2 134 0.48 0.6228 Region x Year 2 134 1.40 0.2513 Year x Hypoxia 1 134 1.25 0.2655 Region x Year x Hypoxia 2 134 1.44 0.2415

A B

East region. The ENS was generally lower in the presence of hypoxia (Figure 3.4, B).

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 3.4). Distance-based redundancy analysis (dbRDA) indicated that most of the variance explained in the model was

Table 3.4. Summary of the non-parametric distance-based linear model (distLM). Reported are the marginal tests on significant relationships among assemblage compositions to three principal component factors, and three additional environmental variables. Asterisks (*) indicate significance. Also shown are the distance-based redundancy analysis (dbRDA) partial correlations relating coordinate axes and orthonormal X variables, and variation explained. Underlines indicate the primary contributors to each dbRDA component.

Variable dbRDA1 dbRDA2 dbRDA3 dbRDA4 dbRDA5 dbRDA6 dbRDA7 Pseudo-F P Year −0.620 0.196 −0.495 −0.403 −0.163 −0.021 0.378 13.374 0.001* Factor 2 0.099 0.713 −0.133 −0.168 0.576 −0.069 −0.316 4.9343 0.001* Long −0.422 0.430 0.730 0.121 −0.169 0.222 0.109 12.462 0.001* Factor 3 −0.355 −0.495 0.189 −0.275 0.633 0.333 −0.079 6.2661 0.001* % Sand −0.481 −0.103 −0.058 0.573 0.214 −0.600 −0.143 9.6884 0.001* Factor 1 −0.238 0.026 −0.337 0.292 −0.253 0.553 −0.611 5.2493 0.001* Complexity 0.118 0.113 −0.227 0.553 0.320 0.410 0.588 2.6153 0.020*

Fitted variation 59.09% 19.35% 9.64% 5.4% 3.57% 2.1% 0.85% Total variation 15.03% 4.92% 2.45% 1.37% 0.91% 0.54% 0.22% R2 = 25.44%

40 West

Central

East

Factor 2

20 Longitude S. dumerili K. sectatrix Year B. capriscus A. saxatilis C. crysosPlatform Complexity

% of total variation) total of % A. probatocephalus Factor 1 C. faber L. griseus 0 P. saltatrix % Sand C. chrysurus L. campechanus (juv.)

f fitted, f 4.9 L. campechanus (adu.)

Factor 3

-20 dbRDA2 (19.3% o (19.3% dbRDA2

-40 -40 -20 0 20 40 dbRDA1 (59.1% of fitted, 15% of total variation) Figure 3.5. 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). 73 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 3.5). 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).

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 (pseudo-F = 13.572, P = 0.001; Table 3.5), as well as three-way interactions among the main effects region and year and the bottom DO saturation covariate

Variable Degrees of freedom pseudo-F P 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 13.94 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 0.69822 0.792 999

Pairwise comparison Pseudo-t P 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

(pseudo-F = 2.3865, P = 0.008; Table 3.5). 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 3.6). 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 3.6).

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 3.7), 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 3.5). 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 3.8).

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 3.8).

Variable Degrees of freedom pseudo-F P 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 9.589 0.001 999 Sed x Hypoxia x Long 1 0.70701 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 0.72525 0.649 998

Pairwise comparison Pseudo-t P Unique perms Sed-No hypoxia 2.1706 0.001* 999 Sed-Hypoxia 0.98383 0.413 999 Hypoxia-Mud 2.2518 0.001* 998 Hypoxia-Sand 1.2532 0.110 999

SIMPER analyses (Figures 3.6–3.10) 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 3.6). Annual and intraregional comparisons of dissimilarity were also high at 64.1% between 2013 and 2014 (Figure 3.7). Fish assemblages over sand and mud were 62.7% dissimilar (Figure 3.8). Fish assemblages over hypoxic and non-hypoxic waters were 61.8% dissimilar (Figure 3.9). Finally mean assemblage dissimilarities among platform

Figure 3.8. Dominant sediment type (sand or mud) mean MAXNO pairwise assemblage dissimilarities based on the SIMPER analysis. Bold font indicates those species which together account for > 90% of dominant sediment type fish assemblage dissimilarity. Percentages above bars indicate percent dissimilarity contributions, below which is the ratio of the percent dissimilarity over the standard deviation. Species order reflects rank order abundance.

Figure 3.9. Presence vs. absence of hypoxia (DO < 50% saturation) mean MAXNO pairwise assemblage dissimilarities based on SIMPER analysis. Bold font indicates species which together account for > 90% of hypoxia fish assemblage dissimilarity. Percentages above the bars indicate percent dissimilarity contributions, below which are the ratio of the percent dissimilarity over the standard deviation. Species order reflects ranked order abundance.

81 complexity levels (1–2, 2–3, and 1–3) were 61.7%, 61.5%, and 60.1%, although there were no apparent trends (Figure 3.10). Regional dissimilarity of fish assemblages was high for all comparisons (60.3%, 64.2%, and 68.4%; Table 3.9).

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.

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 3.8) indicated that Atlantic bumper, Atlantic spadefish, bluefish, sheepshead, gray snapper, sergeant

Table 3.9. SIMPER pairwise assemblage dissimilarities (DISS) comparing nearshore Louisiana regions (West, Central, and East), years (2013 and 2014), dominant sediment type (Sed) (sand or mud), presence or absence of hypoxia (DO < 50% saturation), and platform complexity (1–3). Results shown are species with Diss/SD ratios > 1, indicating consistent contribution to dissimilarity, and excluding species with high dissimilarity, but patchy in their distribution.

Pairwise Mean Mean % Diss Species Diss/SD contrast MAXNO MAXNO contribution West Central Chloroscombrus chrysurus 98.03±30.56 161.61±46.68 1.13* 22.66 Chaetodipterus faber 59.28±14.99 43.59±4.63 1.32* 10.26 West-Central Caranx crysos 16.09±4.0 22.53±3.88 1.14* 10.00

Lutjanus griseus 1.03±0.35 5.54±0.92 1.06* 5.24 60.26% Archosargus probatocephalus 2.69±0.5 7.81±1.15 1.14* 4.72 Mean Diss Seriola dumerili 4.06±0.77 1.54±0.68 1.05* 4.49 Kyphosus sectatrix 3.13±0.93 2.71±0.58 1.04* 3.93 Balistes capriscus 2.13±0.40 1.69±0.25 1.14* 2.94 Central East Caranx crysos 1.69±0.25 10.69±4.23 1.20* 12.58 Central-East Chaetodipterus faber 43.59±4.63 9.79±1.60 1.54* 12.44

Lutjanus griseus 5.54±0.92 5.98±1.05 1.16* 5.82 64.16% Archosargus probatocephalus 7.81±1.15 4.31±0.65 1.23* 5.44 Mean Diss Lutjanus campechanus (adult) 0.93±0.26 3.67±0.85 1.01* 4.62 Balistes capriscus 1.69±0.25 1.42±0.36 1.15* 3.56 West East Chloroscombrus chrysurus 98.03±30.56 58.56±19.35 1.16* 20.47 Chaetodipterus faber 59.28±14.99 9.79±1.60 1.57* 12.53 West-East Caranx crysos 16.09±4.0 10.69±4.23 1.07* 9.91

Lutjanus griseus 1.03±0.35 5.98±1.05 1.10* 6.31 68.4% Mean Diss Seriola dumerili 4.06±0.77 0.52±0.31 1.07* 4.75 Abudefduf saxatilis 4.09±0.88 0.19±0.14 1.03* 4.43 Archosargus probatocephalus 2.69±0.50 4.31±0.65 1.18* 3.79 Balistes capriscus 2.13±0.40 1.42±0.36 1.10* 3.62 2013 2014 Chloroscombrus chrysurus 33.85±9.16 177.19±40.14 1.01* 22.71 2013-2014 Chaetodipterus faber 16.05±2.07 51.47±6.72 1.45* 11.56

Caranx crysos 9.12±1.67 23.67±3.99 1.09* 10.96 64.13% Lutjanus griseus 5.69±0.83 3.98±0.77 1.11* 5.65 Mean Diss Archosargus probatocephalus 3.05±0.35 7.55±0.99 1.16* 5.11 Balistes capriscus 0.69±0.14 2.46±0.28 1.11* 3.72 Sand Mud Chloroscombrus chrysurus 200.1±51.52 53.51±13.95 1.06* 24.12 Sand-Mud Chaetodipterus faber 57.83±8.60 20.40±2.49 1.42* 11.83

Caranx crysos 12.21±2.06 21.10±3.90 1.14* 10.01 62.66% Lutjanus griseus 5.43±1.03 4.21±0.64 1.07* 5.50 Mean Diss Archosargus probatocephalus 6.48±1.20 4.97±0.59 1.14* 4.91 Balistes capriscus 1.95±0.27 1.51±0.25 1.18* 3.30

(Table 3.9 continued)

Pairwise Mean Mean % Diss Species Diss/SD contrast MAXNO MAXNO contribution Not hypoxic Hypoxic Not Chloroscombrus chrysurus 130.91±37.69 94.92±24.90 1.01* 22.88 hypoxic- Caranx crysos 7.93±1.49 29.38±4.84 1.13* 12.14 Hypoxic Chaetodipterus faber 42.68±6.95 27.77±3.12 1.34* 10.80

Lutjanus griseus 5.76±0.90 3.39±0.57 1.06* 5.76 61.83% Archosargus probatocephalus 5.23±0.85 6.08±0.87 1.20* 5.13 Mean Diss Balistes capriscus 1.87±0.27 1.47±0.25 1.04* 3.41 1 2 Complexity Chloroscombrus chrysurus 75.91±17.74 180.74±75.19 1.05* 24.97 1-2 Chaetodipterus faber 35.58±5.98 42.72±8.81 1.31* 11.22 Caranx crysos 15.71±3.10 17.69±5.35 1.12* 10.27 61.17% Lutjanus griseus 4.89±0.71 4.74±1.36 1.00* 5.34 Mean Diss Archosargus probatocephalus 6.19±0.87 4.15±0.64 1.08* 4.88 Balistes capriscus 1.85±0.28 1.80±0.32 1.04* 3.21 1 3 Complexity Caranx crysos 15.71±3.10 22.04±5.72 1.16* 12.34 1-3 Chaetodipterus faber 35.58±5.98 28.26±5.21 1.42* 10.68

Lutjanus griseus 4.89±0.71 4.15±1.15 1.27* 7.12 61.47% Archosargus probatocephalus 6.19±0.87 5.85±1.80 1.31* 5.44 Mean Diss Balistes capriscus 1.85±0.28 1.07±0.24 1.04* 3.76 2 3 Complexity Chaetodipterus faber 42.72±8.81 28.26±5.21 1.45* 11.96 2-3 Caranx crysos 17.69±5.35 22.04±5.72 1.23* 10.73

Lutjanus griseus 4.74±1.36 4.15±1.15 1.21* 6.86 60.09% Archosargus probatocephalus 4.15±0.64 5.85±1.80 1.16* 5.47 Mean Diss Balistes capriscus 1.80±0.32 1.07±0.24 1.05* 3.33 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 3.9) 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 well-oxygenated 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.

Finally, the general trends of interannual 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.

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 observed species was the endangered 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. Sandy shoals are more

85 stable during hypoxic events, supporting the idea that these features 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 1984; Stanley and Wilson 1989, 1990). The 2013 assemblages included species that constitute most of 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 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 2015). 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 2015).

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 3.1).

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 summers, 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

86 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, three mature-sized goliath grouper were observed in East Bay during peak 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 II) and by the apparent nursery role it serves for diverse 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 restricted to 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

87 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 II). 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 IV). One effect of this is reduced access to turbid bottom-water refuge for predation-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 II). 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

88 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.

While 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.

Interannual 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 2.1).

These species 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 species observed at platforms were blue runner, sergeant major damselfish,

Bermuda chub, gray triggerfish, and YOY greater amberjack (Dooley 1972; Bortone 1977; Wells and Rooker 2004a, 2004b; Taylor 2015). In 2014 a notable influx of Sargassum was observed throughout the coastal 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.

The Gulf represents the world’s second largest concentration of Sargassum (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 2013–14 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. 2008).

Because no prior 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

91 platforms (thousands more exist in state waters) in the nGOM from 1942–2014 (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 only serve to attract fishes, then they make good monitoring stations for many species.

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 this study 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

92 submerged materials. This coastal zone is valued by a variety of stakeholders, with potential conflicts of interest, and so careful site selection is 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 coastwide. 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 example of 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

93 habitat in this area is the presence of goliath grouper and the proximity to the fishing port of

Venice.

References

Anderson M. 2001. A new method for non-parametric multivariate analysis of variance. Australian Ecology 26: 32–46.

Anderson MJ, Gorley RN, Clarke KR. 2008. PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods. Plymouth: PRIMER-E.

Army Corps of Engineers. 2015. River Gages. http://rivergages.mvr.usace.army.mil/WaterControl/new/layout.cfm. Accessed November 26, 2015.

Bacheler NM, CM Schobernd, ZH Schobernd, WA Mitchell, DJ Berrane, GT Kellison, MJM Reichert. 2013. “Comparison of trap and underwater video gears for indexing reef fish presence and abundance in the southeast United States.” Fisheries Research 143: 81–88.

Baltz DM, RF Jones. 2003. Temporal and spatial patterns of microhabitat use by fishes and decapod crustaceans in a Louisiana estuary. Transactions of the American Fisheries Society 132(4): 662–678.

Blaber SJM, TG Blaber. 1980. Factors affecting the distribution of juvenile estuarine and inshore fish. Journal of Fisheries Biology 17: 143–162.

Bortone SA., PA Hastings, SB Collard. 1977. The pelagic-Sargassum ichthyofauna of the eastern Gulf of Mexico. Northeast Gulf Science 1(2): 60–67.

Bull AS, JJ Kendall Jr. 1994. An indication of the process: offshore platforms as artificial reefs in the Gulf of Mexico. Bulletin of Marine Science 55: 186–1098.

Bullock LH, MD Murphy, MF Godcharles, ME Mitchell. 1992. Age, growth, and reproduction of jewfish, Epinephelus itajara in the Eastern Gulf of Mexico. Fisheries Bulletin. U.S. 90: 243–249.

Bureau of Ocean Energy Management (BOEM). 2015. Platform structures online query. http://www.data.boem.gov/homepg/data_center/platform/platform/master.asp. Accessed November 09, 2015.

Bureau of Safety and Environmental Enforcement (BSEE). 2015. Platform/Rig Information. http://www.data.bsee.gov/homepg/data_center/platform/platform.asp. Accessed November 09, 2015.

Chesney EJ, DM Baltz. 2001. The effects of hypoxia on fisheries in the northern Gulf of Mexico. In: Rabalais NN, RE Turner (eds.). Coastal hypoxia: consequences for living resources and ecosystems. American Geophysical Union, Coastal and Estuarine Studies 58: 321– 354.

Chesney EJ, DM Baltz, RG Thomas. 2000. Louisiana estuarine and coastal fisheries and habitats: perspectives from a fish’s eye view. Ecological Applications 10(2): 350-366.

Cho K, RO Reid, WD Nowlin. 1998. Objectively mapped stream function fields on the Texas- Louisiana shelf based on 32 months of moored current meter data. Journal of Geophysical Research: Oceans 103(C5) 10377–10390.

Clarke KR, RM Warwick. 2001. Change in marine communities: an approach to statistical analysis and interpretation, 2nd edition. Plymouth: PRIMER-E.

Clarke KR, RN Gorley. 2006. PRIMER v6: User Manual/Tutorial. Plymouth: PRIMER-E.

Cochrane JD, FJ Kelly Jr. 1986. Low-frequency circulation on the Texas-Louisiana continental shelf. Journal of Geophysical Research 91: 10645–10659.

Collins AB, RS McBride, ED McCoy, PJ Motta. 2015. Reef relief and volume are predictors of Atlantic goliath grouper presence and abundance in the eastern Gulf of Mexico. Bulletin of Marine Science 91(4): 399–418.

Colwell RK. 1997. EstiMateS: statistical estimation of species richness and shared species from samples (Software and User’s Guide), Version 5 Available: http://viceroy.eed.unconn.edu/estimates.

Craig JK, SH Bosman. 2013. Small spatial scale variation in fish assemblage structure in the vicinity of the northwestern Gulf of Mexico hypoxic zone. Estuaries and coasts 36(2): 268–285.

Dahm CN, RJ Edwards, FP Gelwick. 2005. Gulf Coast Rivers of the Southwestern United States. In: Benke AC, CE Cushing (eds.). Rivers of North America. Burlington, Massachusetts: Elsevier Academic Press.

DiMarco SF, P Chapman, ND Walker, RD Hetland. 2010. Does local topography control hypoxia on the eastern Texas-Louisiana shelf? Journal of Marine Systems 80(1-2): 25– 35.

Dinnel SP, WJ Wiseman Jr. 1986. Fresh-water on the Louisiana and Texas shelf. Continental Shelf Research 6(6): 765–784.

Ditton RB, J Auyong. 1984. Fishing offshore platforms central Gulf of Mexico: an analysis of recreational and commercial fishing use at 164 major offshore petroleum structures. Government Reports, Announcements and Index, National Technical Information Service (NTIS), US Department of Commerce 84(21).

Dooley JK 1972. Fishes associated with the pelagic Sargassum complex with a discussion of Sargassum community. Contributions in Marine Science 16(MAR) 1.

Ellis DM, ED DeMartini. 1995. Evaluation of a video camera technique for indexing abundances of juvenile pink snapper, Pristipomoides filamentosus, and other Hawaiian insular shelf fishes. Fisheries Bulletin 93: 67–77.

Fisheries and Aquaculture Organization of the United Nations (FAO). 2014. The State of World Fisheries and Aquaculture (SOPHIA).

Franks JS. 2005. First Record of Goliath Grouper, Epinephelus itajara, in Mississippi coastal waters with comments on the First Documented Occurrence of Red Grouper, Epinephelus morio, off Mississippi. In The Proceedings of the Fifty Six Annual Gulf and Caribbean Fisheries Institute, p. 295-306. Roadtown, Tortola British, Virgin Islands, November 2003.

Gallaway BJ. 1984. Assessment of platform effects on snapper populations and fisheries. In: Proceedings of the Fifth Annual Information Transfer Meeting 130–137.

Gallaway BJ, JG Cole, A Lissner, E Waddell, D Heilprin, CA Wilson, D Stanley, and RS Carney. 1997. Cumulative ecological significance of oil and gas structures in the Gulf of Mexico: information search, synthesis, and ecological modeling. Phase I final report. US Department of Interior, US Geological Survey, Biological Resources Division, USGS, BRD, CR and Mineral Management Service, Gulf of Mexico OCS Region, New Orleans, Louisiana, OCS Study MMS 97–0036.

Gallaway BJ, LR Martin, RL Howard, GS Boland, GD Dennis. 1981. Effects on artificial reef and demersal fish and macrocrustacean communities. In: Environmental Effects of Offshore Oil Production, Springer US 237–299.

Gaston KJ. 2010. Valuing common species. Science 327: 154–155.

Gledhill CT, J Lyczkowski-Shultz, K Rademacher, E Kargard, G Crist, MA Grace. 1996. Evaluation of video and acoustic index methods for assessing reef-fish populations. ICES Journal of Marine Science 53: 483–485.

Gower JFR, CM Hu, G Borstad, SA King. 2006. Ocean color satellites show extensive lines of floating Sargassum in the Gulf of Mexico. IEEE Trans. Geosci. Rem. Sens 44: 3619– 3625.

Gower JFR, SA King. 2008. Satellite images show the movement of floating Sargassum in the Gulf of Mexico and Atlantic Ocean, Nature Precedings.

Gower JFR, SA King. 2011. Distribution of floating Sargassum in the Gulf of Mexico and the Atlantic Ocean mapped using MERIS. Int. J. Remote Sens 32: 1917–1929.

Gulf of Mexico Fishery Management Council. 2015. Evaluation of Potential Artificial Reef Siting Criteria in the Gulf of Mexico.

Günter G, 1945. Studies on Marine Fishes of Texas. Publications of the Institute of Marine Science, University of Texas 1: 1–190.

Günter G. 1956. Some relations of faunal distributions to salinity in estuarine waters. Ecology 616–619.

Günter G. 1963. The fertile fisheries crescent. Journal of Mississippi Academy of Science 9: 286–290.

Hetland RD, SF DiMarco. 2008. The effects of bottom oxygen demand in controlling the structure of hypoxia on the Texas-Louisiana continental shelf. Journal of Marine Systems 70: 49–62.

Hurlbert SH. 1984. Pseudoreplication and the design of ecological field experiments. Ecological monographs 54(2): 187–211.

Jost L. 2006. Entropy and diversity. Oikos 113(2): 363–375.

Krahl RB. 1986. Federal focus on platform disposition for artificial reefs. MMS Information Transfer Meeting, 1985: 112–114.

Livingston RJ. 1988. Inadequacy of species-level designations for ecological studies of coastal migratory fishes. Environmental Biology of Fishes 22: 225–234.

Louisiana Department of Wildlife and Fisheries (LDWF). 2015. 2013-2014 annual report.

Love MS, DM Schroeder, W Lenarz, A MacCall, A Scarborough-Bull, L Thorsteinson. 2006. Potential use of offshore marine structures in rebuilding an overfished rockfish species, bocaccio (Sebastes paucispinis). Fishery Bulletin 104(3): 383–390.

Love MS, E Brothers, DM Schroeder, WH Lenarz. 2007. Ecological performance of young-of- the-year blue rockfish (Sebastes mystinus) associated with oil platforms and natural reefs in California as measured by daily growth rates. Bulletin of Marine Science 80(1): 147– 157.

McHugh JL. 1967. Estuarine nekton. In: Lauff GH (ed.). Estuaries. American Association for the Advancement of Science 83: 581–619.

Meade RH, JA Moody. 2010. Causes for the decline in suspended-sediment discharge in the Mississippi River system, 1940–2007. Hydrologic Processes 24(1): 35–49.

Milliman JD, RH Meade. 1983. World-wide delivery of river sediment to the oceans. The Journal of Geology 1–21.

National Marine Fisheries Service (NMFS). 2006. Status report on the continental United States distinct population segment of the goliath grouper (Epinephelus itajara). January 12, 2006. 49 pp.

National Marine Fisheries Service (NMFS). 2015. Office of Science and Technology. www.st.nmfs.noaa.gov/commercial-fisheries/. Accessed October 31, 2015.

Nelson RS. 1985. Growth of gray triggerfish, Balistes capriscus, on exploratory oil drilling platforms and natural reef areas in the northern Gulf of Mexico. Bulletin of Marine Science 37(1): 399– 399.

Nixon SW, CA Oviatt, J Fristhen, B Sullivan. 1986. Nutrients and the productivity of estuarine and coastal marine ecosystems. Journal of the Limnological Society of South Africa 12(1): 43–7.

Nowlin WD Jr, AE Jochens, SF DiMarco, RO Reid, MK Howard. 2005. Low-frequency circulation over the Texas-Louisiana continental shelf. In: Sturges W, A Lugo-Fernandez, (eds.). Circulation in the Gulf of Mexico: observations and models. AGU Geophysics Monograph-American Geophysical Union 161: 219–40.

Oey LY, T Ezer, HC Lee. 2005. Loop Current, rings and related circulation in the Gulf of Mexico: a review of numerical models and future challenges. Circulation in the Gulf of Mexico: Observations and models 31–56.

Parker RO Jr, DR Colby, TD Willis. 1983. Estimated amount of reef habitat on a portion of the US South Atlantic and Gulf of Mexico continental shelf. Bulletin of Marine Science 33(4): 935–940.

Porch CE, AM Eklund. 2004. Standardized visual counts of Goliath Grouper off south Florida and their possible use as indices of abundance. Gulf of Mexico Science 2: 155–163.

Priede IG, PM Bagley, A Smith, S Creasey, NR Merrett. 1994. Scavenging deep demersal fishes of the Porcupine Seabight, north-east Atlantic: observations by baited camera, trap and trawl. Journal of Marine Biology 74: 481–498.

Rabalais NN, RE Turner, WJ Wiseman Jr. 2002. Gulf of Mexico hypoxia, A.K.A. “the Dead Zone.” Annual Review of Ecology and Systematics 33: 235–263.

Reeves, DB. 2015. Oil and gas platforms on Ship Shoal, northern Gulf of Mexico, as habitat for reef-associated organisms (Master’s thesis, Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Master of Science in Department of Oceanography and Coastal Sciences by David Bradley Reeves BS, Loyola University New Orleans).

Reeves DB, SW Parker, RT Munnelly, EJ Chesney, DM Baltz. In review. Evaluation of two remotely deployed video methods for characterizing fish assemblages around small, nearshore oil and gas platforms in the northern Gulf of Mexico.

Reggio VC Jr. 1987. Rigs-to-reefs. Fisheries 12(4): 2–7.

Remmert H.1983. Studies and thoughts about the zonation along the rocky shores of the Baltic. Zoologica 22: 121–125.

Scarborough-Bull A, MS Love, DS Schroeder. 2008. Artificial reefs as fishery conservation tools: contrasting the roles of offshore structures between the Gulf of Mexico and the Sothern California Bight. AFS Symposium 49: 899–915.

Shannon CE. 2001. A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review 5(1): 3–55.

Shaw RF, DL. Drulliger. 1990. Early life history profiles, seasonal abundance and distribution of four species of carangids larvae off Louisiana. 1982 and 1983. NOAA Tech. Rep. NMFS 89, 37 p.

Sonnier F, J Teerling, HD Hoese. 1976. Observations on the offshore reef and platform fish fauna of Louisiana. Copeia 105–111.

Stanley DR, CA Wilson. 1989. Utilization of offshore platforms by recreational fishermen and scuba divers off the Louisiana coast. Bulletin of Marine Science 44(2): 767–776.

Stanley DR, CA Wilson. 1990. A fishery-dependent based study of fish species composition and associated catch rates around oil and gas structures off Louisiana. Fishery Bulletin 88(4).

Stanley DR, CA Wilson. 2004. Effect of hypoxia on the distribution of fishes associated with a petroleum platform off coastal Louisiana. North American Journal of Fisheries Management 24(2): 662–671.

Sturges W, R Leben. 2000. Frequency of ring separations from the Loop Current in the Gulf of Mexico: A revised estimate. Journal of Physical Oceanography 30(7): 1814–1819.

Switzer TS, Chesney EJ, DM Baltz. 2009. Habitat selection by flatfishes in the northern Gulf of Mexico: implications for susceptibility to hypoxia. Journal of Experimental Marine Biology and Ecology 381: 51–64.

Taylor SM. 2015. Ichthyoplankton Composition in the Loop Current and Sargassum Habitats in the Northern Gulf of Mexico. Master's Theses. Paper 134. http://aquila.usm.edu/masters_theses/134.

Turner RE, NN Rabalais. 1991. Changes in the Mississippi River water quality this century. Bioscience 41: 140–147.

100

Turner RE, NN Rabalais. 2003. Linking landscape and water quality in the Mississippi River basin for 200 years. BioScience 53: 563–572.

Vaughan DS, EJ Levi, JW Smith. 1996. Population characteristics of gulf menhaden, Brevoortia patronus. NOAA Tech. Rep. NMFS 125: 1–18.

Wells DRJ. JH Cowan Jr. 2007. Video Estimates of Red Snapper and Associated Fish Assemblages on Sand, Shell, and Natural Reef Habitats in the North-Central Gulf of Mexico. In: Patterson WF III, J Cowan Jr, GR Fitzhugh, DL Nieland (eds.). American Fisheries Society Symposium 60: 39–57.

Wells RJ, JR Rooker. 2004a. Spatial and temporal patterns of habitat use by fishes associated with Sargassum mats in the northwestern Gulf of Mexico. Bulletin of Marine Science 74(1): 81–99.

Wells RJ, JR Rooker. 2004b. Distribution, age, and growth of young-of-the year greater amberjack (Seriola dumerili) associated with pelagic Sargassum. Fishery Bulletin, 102(3): 545–554.

Willis TJ, RC Babcock. 2000. A baited underwater video system for the determination of relative density of carnivorous reef fish. Marine and Freshwater Research 51(8):755– 763.

Witzig, J. 1986. Rig fishing in the Gulf of Mexico 1984: marine recreational fishing results. In: Proceedings, Sixth Annual Gulf of Mexico Information Transfer Meeting. US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS Region, OCS Study/MMS86–0073. New Orleans, Louisiana 103–105.

Workman I, A Shah, D Foster, B Hataway. 2002. Habitat preferences and site fidelity of juvenile red snapper (Lutjanus campechanus)." ICES Journal of Marine Science: Journal du Conseil 59(suppl): S43–S50.

Zhong Y, A Bracco, TA Villareal. 2012. Pattern formation at the ocean surface: Sargassum distribution and the role of the eddy field. Limnology and Oceanography: Fluids and Environments 2(1): 12–27.

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CHAPTER IV: HABITAT SUITABILITY FOR FISHES ASSOCIATED WITH OIL AND GAS PLATFORMS IN THE NEARSHORE WATERS OF LOUISIANA

Epitome

Fish assemblages were surveyed around 150 small oil and gas platforms (platforms) off

Louisiana during summers of 2013–14. The survey covered the entire Louisiana coast in nearshore waters 3–18 m deep. Paired video and water quality (salinity temperature, dissolved oxygen (DO), water clarity, and depth) samples documented the response of reef-associated fishes to coastal hydrography. Platforms are unique artificial reefs that provide vertically- oriented substrate for fouling organisms (and nekton) throughout the water column that attracts dense assemblages of fishes and invertebrates. Platforms are abundant off Louisiana throughout the region that is commonly referred to as “the hypoxic zone”. Because of the diverse hydrography of this region, and dense aggregations of fishes around platforms, we were able to evaluate species-specific responses across large physicochemical gradients. Fish distributions were influenced by variable freshwater input from the Mississippi-Atchafalaya River system and the interactions among salinity, temperature, depth, DO and surface water clarity availabilities with the presence of hypoxia (DO < 50% saturation). The vertical extent of the water column suitable for fishes was compressed due to avoidance of hypoxic bottom water and apparent avoidance of dense surface blooms with supersaturated oxygen conditions that significantly altered habitat selection patterns. Fishes used significantly different environmental conditions in the presence of hypoxia. These shifts in patterns of use may alter metabolism, growth, reproduction, and trophic interactions although these effects were not quantified. The tradeoff between fish responses to DO and other variables is, therefore, a potentially important sub-lethal effect of hypoxia. This study provides an assessment of platforms as a valuable habitat type at a time when these structures are rapidly being removed from the nearshore coastal zone.

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Introduction

Coastal Louisiana is a deltaic system at the terminal drainage of North America’s largest watershed, and includes the largest contiguous wetland system in the United States (Alexander

1986). The Mississippi watershed drains ~41% of the contiguous US (Turner and Rabalais

1991) or about 13% of the total land area of North America, and is the third largest watershed on

Earth (Milliman and Meade 1983). Consequently, nearshore waters of coastal Louisiana receive abundant freshwater input that interacts with local bathymetry, resulting in widespread estuarine conditions. Freshwater input is highly variable and seasonal with an influence extending well beyond the bounds of the inshore estuaries (Dinnel and Wiseman 1986; Chapter II). River inputs regionally affect temperatures and salinities throughout the water column (Wiseman et al. 1982), especially during summer months when upwelling-favorable SE winds slow shelf turnover

(Cochran and Kelly 1986; Dinnel and Wiseman 1986). Local salinities, temperatures, turbidities, and nutrient distributions fluctuate due to wind and current influences on the Mississippi and

Atchafalaya river plumes and underlying marine waters (Pokryfki and Randall 1987; Rabalais et al. 1991; Wiseman et al. 1997; Walker et al. 2005; DiMarco et al. 2010). Coupled with relatively calm ocean conditions, stratification of these environmental variables adds a vertical dimension to the existing fluctuating lateral gradients (Wiseman et al. 1997). Surface-to-bottom variation in the water column can range from nearly fresh to fully marine, and several degrees temperature, following step-like halocline and thermocline transitions.

Dynamic environmental variation throughout Louisiana’s nearshore waters is further complicated by nutrient discharges from the Mississippi River Drainage. The Mississippi and

Atchafalaya rivers are the primary sources of eutrophic nutrient loading which causes intense phytoplankton blooms that die and sink depleting bottom-water dissolved oxygen (DO) (Turner

103 and Rabalais 1991; Justić et al. 1993; Rabalais et al. 2007). River flows typically peak in early

April (Turner and Rabalais 1991), and peak hypoxia (typically defined as DO > 2.0 mg l−1) ensues by June and persists through mid-September (Rabalais et al. 1991). As a result, the

Louisiana-Texas (LATEX) Shelf includes the world’s second largest seasonally recurring hypoxic zone (Rabalais et al. 2002), with DO distributions that vary horizontally and vertically.

Intense summer stratification results in a secondary major salinity-dominated pycnocline

(Cochrane and Kelly 1986). This stratification has the potential to develop additional stable and unstable layers (Wiseman et al. 1976) that maintain locally developed hypoxic conditions

(Hetland and DiMarco 2008). Over several decades the size of the hypoxic zone has grown in both area and total volume (Rabalais et al. 2002; Obenour et al. 2013). In recent years, the mean area of the hypoxic zone was 16,600 km2, with peaks > 22,000 km2, and a 27 year mean vertical extent of 3.9 m with annual means as high as 6.2 and 6.3 m in 2008 and 2009 (Obenour et al.

2013). Because coastal Louisiana supports many of the most highly productive US coastal fisheries (Chesney et al. 2000), it is important to understand the ways hypoxia impacts fishes of coastal Louisiana, particularly as coastal hypoxia increases globally (Diaz and Rosenberg 2008).

The many oil and gas platforms off coastal Louisiana are not only interesting to study in their own right, but also provide an opportunity to evaluate hypoxia and other hydrographic variables that affect the dense aggregations of fishes around them.

DO concentrations play a controlling role in the distributions of many fishes (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 are

104 rare events in open-water systems (Caddy 1993), low DO (< 50% saturation) can be stressful for finfishes. 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 than the 2.0 mg l−1 typically used to define hypoxia (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 surface blooms that cause gas supersaturation (Goreham 1899), or contain harmful algal species

(Landsberg 2002 and references therein). Supersaturation of the atmospheric gases nitrogen and oxygen can cause gas bubble disease (GBD) in fish (Marsh and Goreham 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,

105 variation in total gas pressure throughout surface waters of the northern Gulf of Mexico (nGOM) has not been documented.

Another distinctive feature of the Louisiana coastline is the network of oil and gas platforms (platforms) extending from the bays and marshes outward past the continental shelf.

In 2013 there were > 2,600 federally-listed platforms in federal waters off Louisiana (BOEM

2015), as well as many more state-managed structures in state waters (Louisiana Department of

Natural Resources 2015). Many of these federal and state-managed platforms are located in waters prone to hypoxia. As “de-facto artificial reefs”, platforms offer hard substrate to the biota of a region that is otherwise dominated by soft sediments (Parker et al. 1983; Gallaway and Cole

1998; Gallaway et al. 1981; Gallaway and Lewbel 1982). A unique ecological service that platforms provide is 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 falls below suitable concentrations.

While 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). Suitable conditions for reef-associated species can thus be maintained around platforms in areas that might be less suitable given inadequate vertical relief. Vertical movement

106 in the water column in response to one environmental variable might result in less favorable conditions of 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 (Prince and Goodyear

2006). This could result in eventual movement 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, available fouling prey, or as current breaks that allow use of favorable sites with minimal exertion. 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 dramatically lower in number within the hypoxic region.

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 portion of the study were to 1) assess species-specific responses to physicochemical drivers

107 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.

Methods

Field: Platform selection was modified random, and guided by the distribution nearshore platforms that met our sampling criteria. Platforms were clustered into fields along the coast reflecting the block-lease system for permitting 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 protective, and unmanned fixed structures in < 18 m water depth

(GeoMapApp 3.3.0). This was used in conjunction with USGS seabed data to create routes that took us through as many fields as possible. Priority was given to fields with the intention of fully characterizing environmental variation in terms of salinity, temperature, turbidity, distance from shore, depth, and dominant sediment type (sand or mud). We also considered platform complexity, date of deployment, and proximity to other platforms to sample as evenly as possible with respect to variables of potential significance.

Sampling occurred during daily cruises aboard a 30’ vessel. Sampling included 14 days at sea between July 12 - September 06 of 2013, and 14 days at sea between July 02 – September

12 of 2014. Routes ran 50 to 400 km per day along the coast from Mississippi to Texas and between three and 47 km from shore (Figure 4.1).

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Figure 4.1. Sites of all samples included in analyses. Orange circles indicate platform sites with usable video and hydrographic data (n = 150). Red lines mark regional designations at longitudes −92.5° and −90.4°. Contours are shown for the 5 m, 10 m, 15 m, 20 m, and 25 m isobaths. The red star indicates the location of the water quality profile shown in Figure 4.4. circular field of view. The fourth camera was centrally mounted among the other three and faced downward 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.

Physicochemical data, including salinity, temperature, depth, atmospheric pressure, pressure at depth, DO, pH, turbidity, and Secchi depth, were collected at small platforms across the coast. We used a YSI model 6820 V2 sonde to vertically profile the water column at a rate of one reading every two seconds, within ~0.2 m of the surface and the bottom. We sampled 343 sites, 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 were obtained 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).

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Video processing: Video recordings of the fish assemblages around small oil and gas platforms were selected for analyses based on initial visibility criteria that required the submerged platform structure (the jacket) be in view (mean distance of 3.0 m). This was an adequate threshold for the purposes of this study due to the strong reef association of the species around these platforms, and the small footprint of the platforms we targeted (Reeves et al. in review). The fish assemblages were concentrated around the small platforms and more conducive to video-based sampling than prior studies on larger structures had reported (Bull and Kendell 1994.).

Videos were analyzed to estimate the minimum number of individuals present for each species (MAXNO) and generate relative abundance estimates for the assemblages at each platform (Ellis and DiMartini 1995). This approach avoids the risk of double counting by locating a synchronized set of frames that jointly captured the peak abundance for each species present in three horizontally-facing cameras (Priede 1994; Ellis and DiMartini 1995; Willis and

Babcock 2000; Wells and Cowan 2007). A fourth downward-facing camera was reviewed, but there was potential for overlapping fields of view, and so the counts were included in place of those of the outward-facing cameras only when peak abundance was greater. The process was repeated for every species recorded in the video.

Of the 150 videos included in the analyses, 37 were equipped with a single outward- facing camera and a synchronized downward-facing camera, rather than the full array of four. In these videos the outward-facing camera maintained a view of the submerged structure for most of the recording. Disparities in water volume sampled between camera configurations and due to variation in water clarity were accounted for by a covariate accounting for sample volume

(effort). Midwater turbidity was multiplied by the number of outward-facing cameras and standardized relative to the lowest value encountered, effectively down-weighting counts at

110 platforms that sampled a larger volume of water. Analyses comparing species richness,

Shannon-Weiner diversity, and assemblage composition between the two camera array configurations indicated no significant difference between camera configurations, and reduced probability of a significant difference when effort was accounted for (see video processing methods in Chapter III for more details).

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 vs. 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

111 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.

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 III), 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 III). 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; Switzer et al. 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).

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The water-column structure around 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 avoided were eliminated from habitat use calculations. Also, because MAXNO counts could not be taken from each layer individually without potentially double counting individuals, equal use was assumed for all layers in the water column which were not clearly being avoided and hydrographic variables that occupied a larger portion of the water column were weighted according to 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. Non-overlapping error bubbles suggested

113 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 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 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 4.2). 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;

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° a Salinity (psu) TemperatureTemperature ( C) DO (% sat.) 0 50 15 20 25 30 35 40 15 20 25 30 35 40 0 50 100 150 200 0

2 24.37 30.35 126.51%

27.60 30.20 95.50%

6 32.35 29.54 69.73% 8 33.62 28.89 72.0% Depth (m) Depth 10

34.34 26.61 22.90% 12

14 34.83 26.20 3.41% 16

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.

Results

Observations: 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 3.1 for a complete list). This included the small, cryptic species we regularly observed while diving

(Table 3.1), among which were young-of-the-year red and lane snapper (Figure 4.3).

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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.

A benefit of deploying un-baited remote video systems is the opportunity to observe behaviors of organisms acting in their environment in a minimally invasive way. 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 young-of-the-year lane and red snapper displaced from their usual bottom

116

A B

habitat use, where they would feed in the current to higher in the water column (Figure 4.3, B).

Additionally, fishes were regularly observed entering waters < 50% saturation, presumably 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 stingray

(Dasyatis americana) and red and black drum, were also observed as high as 4.7, 3.7, and 3.7 m above highly turbid, low DO bottom waters into waters of ≥ 50% DO saturation.

Statistical analyses: The extent of habitat restriction from hypoxia and surface bloom-associated compression varied significantly across nearshore Louisiana. The three-way ANCOVA indicated dominant sediment type, depth, and the interaction between region and year were significant (P = 0.0174, < 0.0001, and 0.0002; Table 4.1). Pairwise comparison indicated a greater degree of compression in the East region than in the West or Central regions (see Figure

117

4.1 for regions), greater overall compression during 2014 sampling, and greater habitat restriction over muddy sediments than over sand (Figure 4.3, A).

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 documentation. 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 4.4). Figure 4.4 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 4.2). 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

Table 4.1. Three-way ANCOVA for type III fixed effects of region, year, and dominant sediment type (Sed) on the extent of habitat restriction to fishes, controlling for depth. Asterisks (*) indicate significance of interpretable variables.

Variable Num DF Den DF F P Region 2 121 6.75 0.0017 Year 1 121 10.40 0.0016 Sed 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

118

Table 4.2. Mixed generalized linear model results for the physicochemical responses of the 11 dominant species comprising the nearshore Louisiana platform fish assemblage. 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. Asterisks (*) indicate significance of interpretable variables. Tildes (~) indicate marginal significance of interpretable variables.

Environmental

Variable

ysos

n = 17,261 n = 5,418n = 2,605n = 1,240n = 840 n = 708 n = 414 n = 295 n = 263 n = 254 n = 252 n

C. chrysurusC. faberC. cr C. P. saltatrix A. probatocephalus L. griseus A. saxatilis sectatrix K. S. dumerili B. capriscus L. campechanus Salinity F 0.02 8.78 0.00 2.00 4.23 0.48 8.78 4.02 0.81 0.25 0.31 P 0.881 0.004 0.956 0.160 0.042 0.492 0.004 0.047 0.371 0.620 0.580 Temperature F 1.09 3.26 0.01 1.50 3.01 0.02 3.26 1.53 0.31 2.19 0.32 P 0.299 0.074 0.907 0.222 0.085 0.876 0.074 0.219 0.576 0.141 0.575 DO F 0.02 1.13 0.02 0.00 0.23 0.72 1.13 0.13 0.00 0.86 0.91 P 0.875 0.074 0.875 0.972 0.635 0.398 0.290 0.721 0.982 0.356 0.342 Depth F 8.43 3.88 0.26 1.73 8.39 1.13 3.88 1.64 14.85 4.01 0.00 P 0.004 0.290 0.614 0.191 0.005 0.290 0.051 0.203 <0.001 0.048 0.980 Secchi F 7.16 3.41 0.12 0.06 0.00 0.49 3.41 0.37 1.31 0.70 16.71 P 0.008 0.067 0.727 0.810 0.981 0.486 0.067 0.542 0.254 0.406 <0.001 Hypoxia F 12.42 0.00 0.55 0.13 0.92 5.67 0.00 0.82 5.60 0.24 3.87 P 0.001 0.981 0.461 0.718 0.339 0.019 0.981 0.367 0.020 0.626 0.051 Year F 33.33* 16.11* 2.98~ 1.14 27.28 25.28* 16.11* 12.07* 2.25 6.22* 3.42~ P <0.001 <0.001 0.087 0.288 <0.001 <0.001 <0.001 0.001 0.136 0.014 0.067 Effort F 0.98 0.09 1.25 0.79 3.94* 8.46* 0.09 0.03 2.08 0.09 7.49* P 0.324 0.762 0.266 0.376 0.049 0.004 0.762 0.856 0.152 0.770 0.007 Salinity x F 0.28 5.18* 0.05 1.12 1.32 0.38 5.18* 5.63* 2.28 0.17 0.36 Temperature P 0.599 0.025 0.829 0.292 0.253 0.539 0.025 0.019 0.134 0.683 0.548 Salinity x F 0.08 1.60 0.75 0.02 0.11 1.12 1.60 0.05 0.34 0.06 0.16 DO P 0.775 0.208 0.387 0.901 0.739 0.291 0.208 0.823 0.560 0.813 0.693 Salinity x F 0.58 14.50* 0.28 1.12 9.40* 0.57 14.50* 2.30 15.23* 0.04 0.23 Depth P 0.446 <0.001 0.595 0.291 0.003 0.452 <0.001 0.132 <0.001 0.837 0.635 Salinity x F 4.09* 9.81* 0.82 5.69* 4.43* 0.38 9.81* 0.05 0.05 0.74 0.03 Secchi P 0.045 0.002 0.367 0.019 0.037 0.536 0.002 0.826 0.825 0.392 0.863 Temperature x F 0.16 1.43 0.01 0.06 0.16 1.54 1.43 0.00 0.07 0.59 0.54 DO P 0.693 0.235 0.940 0.807 0.685 0.217 0.235 0.959 0.790 0.443 0.465 Temperature x F 11.25* 0.45 0.36 1.64 4.92* 0.65 0.45 0.50 9.91* 8.22* 0.42 Depth P 0.001 0.503 0.549 0.203 0.028 0.421 0.503 0.480 0.002 0.005 0.519 Temperature x F 9.41* 0.05 0.23 0.11 4.44* 0.68 0.05 1.10 2.02 7.00* 25.70* Secchi P 0.003 0.818 0.633 0.741 0.037 0.411 0.818 0.295 0.158 0.009 < 0.001 DO x F 0.06 9.59* 0.87 0.51 0.89 2.45 9.59* 2.19 0.16 0.73 0.09 Depth P 0.807 0.002 0.353 0.476 0.347 0.120 0.002 0.142 0.694 0.395 0.767 DO x F 2.42 15.93* 0.71 1.75 15.65* 0.25 15.93* 0.07 1.54 7.27* 6.78* Secchi P 0.122 <0.001 0.400 0.188 <0.001 0.615 <0.001 0.786 0.216 0.008 0.010 Depth x F 19.90* 1.66 0.96 10.16* 5.98* 3.84~ 1.66 0.27 0.13 2.80~ 3.90~ Secchi P <0.001 0.200 0.330 0.002 0.016 0.052 0.200 0.608 0.723 0.097 0.051

119

(Table 4.2. continued)

Environmental

tocephalus

Variable

n = 17,261 n = 5,418n = 2,605n = 1,240n = 840 n = 708 n = 414 n = 295 n = 263 n = 254 n = 252 n

C. chrysurusC. faberC. crysosC. P. saltatrix A. proba L. griseus A. saxatilis sectatrix K. S. dumerili B. capriscus L. campechanus Salinity x F 0.77 0.99 0.15 0.30 1.85 2.25 0.99 1.07 7.70* 3.90~ 3.43~ Hypoxia P 0.382 0.323 0.701 0.585 0.177 0.136 0.323 0.303 0.006 0.051 0.067 Temperature x F 25.89* 1.57 0.23 0.96 0.08 9.09* 1.57 0.36 3.74~ 0.76 0.80 Hypoxia P <0.001 0.212 0.635 0.328 0.779 0.003 0.212 0.550 0.055 0.385 0.373 DO x F 8.05* 4.34* 0.03 0.31 2.48 1.77 4.34* 1.77 1.92 7.70* 4.31* Hypoxia P 0.005 0.039 0.861 0.577 0.118 0.185 0.039 0.186 0.168 0.006 0.040 Depth x F 0.56 0.06 11.39* 0.36 4.70* 0.07 0.06 4.04* 2.00 2.44 3.43~ Hypoxia P 0.455 0.808 0.001 0.552 0.032 0.787 0.808 0.047 0.160 0.121 0.067 Secchi x F 9.26* 6.44* 4.35* 8.38* 0.65 25.14* 6.44* 0.17 1.05 4.15* 6.58* Hypoxia P 0.003 0.012 0.039 0.005 0.423 <0.001 0.012 0.680 0.307 0.044 0.012

Salinity (psu) Temperature (°C) TurbidityTurbidity (NTU) DO (% sat.) 15 20 25 30 35 40 15 20 25 30 35 40 0 10 20 30 40 50 0 50 100 150 200 0 23.85 32.66 4.6 146.9

1 27.43 30.68 7.7 160.8

3 27.96 29.55 4.7 156.0

Depth (m) Depth 4 28.09 29.42 4.8 136.8

5 29.43 28.75 6.4 103.8 6 30.07 28.4 35.0 8.6 7

120 constant. From this it was determined to which physicochemical variable(s) each species was responding.

Habitat suitability analyses: The factor analysis resolved six variables into four factors that together explained 90.72% of the environmental variation (Table 4.3). 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 72.72% of the total variance would be explained) (Figure 4.5).

Microhabitat use patterns for each species in the presence and absence of hypoxia were represented in three-dimensional environmental space (Figure 4.5) 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

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 31.05 23.67 18 18 Cumulative variance explained 31.05 54.72 72.72 90.72

121

No hypoxia A. saxatilis S. dumerili C. bartholomei K. sectatrix Hypoxia E. bipinnulata L. campechanus S. riviola C. crysos L. griseus C. chrysurus S. vomer P. saltatrix S. maculatus S. dumerili T. carolinus B. capriscus R. canadum A. probatocephalus C. faber P. saltatrix C. faber L. synagris L. griseus A. saxatilis R. canadum B. capriscus E. saurus O. chrysoptera C. hippos M. cephalus C. crysos C. chrysurus S. vomer S. ocellatus K. sectatrix P. cromis C. hippos

E. bipinnulata actor 3 actor

F M. cephalus L. campechanus T. carolinus L. rhomboides

L. synagris

E. saurus S. maculatus Factor 2 A. probatocephalus C. bartholomei Factor 1

122 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.

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 4.6–4.10). 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 4.8).

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

123

Availability C. chrysurus C. faber No hypoxia Hypoxia No hypoxia Hypoxia 300 All 250 1 1

200

150 SS 100 SS 50

Frequency (m) Frequency 0 0 0 18 20 24 28 32 36 18 20 24 28 32 36 18 20 24 28 32 36 Salinity (psu) Salinity (psu) Salinity (psu) C. crysos P. saltatrix A. probatocephalus

1 1 1

SS SS SS

0 0 0 18 20 24 28 32 36 18 20 24 28 32 36 18 20 24 28 32 36 Salinity (psu) Salinity (psu) Salinity (psu) L. griseus A. saxatalis K. sectatrix

1 1 1

SS SS SS

0 0 0 18 20 24 28 32 36 18 20 24 28 32 36 18 20 24 28 32 36 Salinity (psu) Salinity (psu) Salinity (psu) S. dumerili B. capriscus L. campechanus

1 1 1

SS SS SS

0 0 0 18 20 24 28 32 36 18 20 24 28 32 36 18 20 24 28 32 36 Salinity (psu) Salinity (psu) Salinity (psu)

Availability C. chrysurus C. faber No hypoxia Hypoxia

400 1 1

300

200

SS SS 100

Frequency (m) Frequency 0 0 0 20 22 24 26 28 30 32 20 22 24 26 28 30 32 20 22 24 26 28 30 32 Temperature (°C) Temperature (°C) Temperature (°C) C. crysos P. saltatrix A. probatocephalus

1 1 1

SS SS SS

0 0 0 20 22 24 26 28 30 32 20 22 24 26 28 30 32 20 22 24 26 28 30 32 Temperature (°C) Temperature (°C) Temperature (°C) L. griseus A. saxatalis K. sectatrix

1 1 1

SS SS

0 0 0 20 22 24 26 28 30 32 20 22 24 26 28 30 32 20 22 24 26 28 30 32 Temperature (°C) Temperature (°C) Temperature (°C) S. dumerili B. capriscus L. campechanus

1 1 1

SS SS SS

0 0 0 20 22 24 26 28 30 32 20 22 24 26 28 30 32 20 22 24 26 28 30 32 Temperature (°C) Temperature (°C) Temperature (°C)

125

Availability C. chrysurus C. faber No hypoxia Hypoxia

500

400 1 1

300 SS 200 SS 100

Frequency (m) Frequency 0 0 0 0 30 60 90 120 150 0 30 60 90 120 150 0 30 60 90 120 150 DO (% saturation) DO ( % saturation) DO (% saturation) C. crysos P. saltatrix A. probatocephalus

1 1 1

SS SS SS

0 0 0 0 30 60 90 120 150 0 30 60 90 120 150 0 30 60 90 120 150 DO (% saturation) DO (% saturation) DO (% saturation)

L. griseus A. saxatalis K. sectatrix

1 1 1

SS SS SS

0 0 0 0 30 60 90 120 150 0 30 60 90 120 150 0 30 60 90 120 150 DO (% saturation) DO (% saturation) DO (% saturation)

S. dumerili B. capriscus L. campechanus

1 1 1

SS SS SS

0 0 0 0 30 60 90 120 150 0 30 60 90 120 150 0 30 60 90 120 150 DO (% saturation) DO (% saturation) DO (% saturation)

126

AvailabilityAvailability C. chrysurus C. faber

NoHypoxia hypoxiaNoHypoxia hypoxia

400 1 1

300

200

SS SS

100 Frequency (m) Frequency Frequency (m) Frequency 0 0 0 5 7 9 11 13 15 17 5 7 9 11 13 15 17 5 7 9 11 13 15 17 Depth (m) Depth (m) Depth (m) C. crysos P. saltatrix A. probatocephalus

1 1 1

SS SS SS

0 0 0 5 7 9 11 13 15 17 5 7 9 11 13 15 17 5 7 9 11 13 15 17 Depth (m) Depth (m) Depth (m)

L. griseus A. saxatalis K. sectatrix

1 1 1

SS SS SS

0 0 0 5 7 9 11 13 15 17 5 7 9 11 13 15 17 5 7 9 11 13 15 17 Depth (m) Depth (m) Depth (m)

S. dumerili B. capriscus L. campechanus

1 1 1

SS SS SS

0 0 0 5 7 9 11 13 15 17 5 7 9 11 13 15 17 5 7 9 11 13 15 17 Depth (m) Depth (m) Depth (m)

127

Availability C. chrysurus C. faber No hypoxia Hypoxia No hypoxia Hypoxia 200 1 All 1

150

100

SS SS 50

Frequency (m) Frequency 0 0 0 0 3 6 9 12 0 3 6 9 12 0 3 6 9 12 Secchi depth (m) Secchi depth (m) Secchi depth (m) C. crysos P. saltatrix A. probatocephalus

1 1 1

SS SS

0 0 0 0 3 6 9 12 0 3 6 9 12 0 3 6 9 12 Secchi depth (m) Secchi depth (m) Secchi depth (m) L. griseus A. saxatalis K. sectatrix

1 1 1

SS SS

0 0 0 0 3 6 9 12 0 3 6 9 12 0 3 6 9 12 Secchi depth (m) Secchi depth (m) Secchi depth (m) S. dumerili B. capriscus L. campechanus

1 1 1

SS SS SS

0 0 0 0 3 6 9 12 0 3 6 9 12 0 3 6 9 12 Secchi depth (m) Secchi depth (m) Secchi depth (m)

128 been severe enough to limit populations (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 was an unexpected finding which we cannot attribute to any one variable. Fishes often avoided the surface bloom despite suitable salinities, temperatures, and water clarity. Both gas bubble disease (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 1941; 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%. While uncommon, we

129 observed values upward of 295% in nearshore waters of coastal Louisiana. Also, 24 harmful algal species are 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, silicone-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, and greater understanding of these responses is needed to understand the resiliency of the fish community in the nGOM.

Also, because the effects of HABs are moderate in Louisiana waters (Dortch et al. 1999) the regular avoidance behavior observed in this study is unlikely to have resulted from HABs.

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.

Here we 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

130 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 found 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 in Figure 4.2 (Case A), 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 (Case B), the assemblage was compressed within a 1.4 m layer of a 14.3 m water column constrained by < 32% saturation below and 204% 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

131 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 4.6).

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 is decreased through DO restriction (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 when bottom-water hypoxia forms, habitat selection in the absence of hypoxia might not reflect fish responses outside of the hypoxic zone. 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 working around platforms is that their fish aggregating effects 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 as Case B above were among the most common and abundant species observed throughout the Louisiana nearshore coastal zone. This platform had higher richness when bottom waters were well-mixed and well-oxygenated on another sampling occasion 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

132 environmental constraints (Coutant 1985; Schurmann and Steffensen 1992; Eby and Crowder

2002), or else that they were not as competitive in this environment as the species that remained.

In this way 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. This effect may be reflected in the overall abundances of many species within the nearshore coastal zone.

Oxygen supersaturation has a shorter temporal influence during bloom conditions than hypoxia because its affects are only manifest during daylight hours when photosynthesis is at its peak. 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 persisting for days or weeks may have a joint effect with underlying hypoxic conditions that displaces fishes that would otherwise remain in the area.

Fishes might entirely avoid areas with water quality potentially stressful during hours of peak photosynthesis, or 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

4.4).

Among the most interesting potential ecological impacts of hypoxia are on food web dynamics. Displacement in the water column can lead to considerable 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

133 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; Constantini et al. 2008; Roman et al. 2012; Elliot et al. 2012), although research has also shown evidence to the contrary (Zhang et al. 2009).

In agreement with findings by Hazen et al. (2009), and 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 1930’s, 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 greatly exceeds repercussions from the temporary disturbance (Chesney et al. 2000, Chesney and Baltz 2001).

Conclusions

Eutrophication of the Fertile Fisheries Crescent has strong influences throughout the water column and can result in habitat compression by reducing access to both the bottom and surface layers of Louisiana’s coastal waters. Habitat compression caused by surface phytoplankton

134 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 adequate DO. Observing these responses and patterns of distribution provides information about how these species cope 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. An unanswered question is 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

135 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?

References

Alexander CE, MA Broutman, DW Field. 1986. An inventory of coastal wetlands of the USA. National Ocean and Atmospheric Administration Service, Department of Commerce, Washington DC.

Baltz DM. 1990. Autecology. Methods for fish biology. American Fisheries Society, Bethesda, Maryland: 585–607.

Baltz DM, C Rakocinski, JW Fleeger. 1993. Microhabitat use by marsh-edge fishes in a Louisiana estuary. Environmental Biology of Fishes 36(2): 109–126.

Baltz DM, RF Jones. 2003. Temporal and spatial patterns of microhabitat use by fishes and decapod crustaceans in a Louisiana estuary. Transactions of the American Fisheries Society 132(4): 662–678.

Bovee KD. 1982. A guide to stream habitat analysis using the Instream Flow Incremental Methodology. IFIP No. 12 (No. 82/26). US Fish and Wildlife Service.

Breitburg DL. 2002. Effects of hypoxia, and the balance between hypoxia and enrichment, on coastal fishes and fisheries. Estuaries 25(4): 767–781.

Breitburg DL, JK Craig, RS Fulford, KA Rose, WR Boynton, DC Brady, BJ Ciotti, RJ Diaz, KD Friedland, JD Hagy III, DR Hart, AH Hined, ED Houde, SE Kolesar, SW Nixon, JA Rice, DH Secor, TE Targett. 2009. Nutrient enrichment and fisheries exploitation: interactive effects on estuarine living resources and their management. Hydrobiologia 629(1): 31–47.

Breslow NE, NE Day. 1980. Statistical Methods in Cancer Research: Volume 1: Analysis of Case Control Studies International Agency for Research in Cancer: Lyon: IARC.

136

Bull AS, JJ Kendall Jr. 1994. An indication of the process: offshore platforms as artificial reefs in the Gulf of Mexico. Bulletin of Marine Science 55: 186–1098.

Bureau of Ocean Energy Management (BOEM). 2015. Platform structures online query. http://www.data.boem.gov/homepg/data_center/platform/platform/master.asp. Accessed November 09, 2015.

Caddy JF. 1993. Toward a comparative evaluation of human impacts on fishery ecosystems of enclosed and semi‐enclosed seas. Reviews in Fisheries Science 1(1): 57–95.

Chamberlain GW, WH Neill, PA Romanowsky, K Strawn. 1980. Vertical responses of Atlantic croaker to gas supersaturation and temperature change. Transactions of the American Fisheries Society 109(6): 737–750.

Chesney EJ, DM Baltz, RG Thomas. 2000. Louisiana estuarine and coastal fisheries and habitats: perspectives from a fish’s eye view. Ecological Applications 10(2): 350–366.

Cochrane JD, FJ Kelly Jr. 1986. Low-frequency circulation on the Texas-Louisiana continental shelf. Journal of Geophysical Research 91: 10645–10659.

Colt JE. 1983. The computation and reporting of dissolved gas levels. Water Research 17(8): 841–849.

Cook DG, RM Wells, NA Herbert. 2011. Anaemia adjusts the aerobic physiology of snapper (Pagrus auratus) and modulates hypoxia avoidance behaviour during oxygen choice presentations. The Journal of experimental biology 214(17): 2927–2934.

Cornacchia JW, JE Colt. 1984. The effects of dissolved gas supersaturation on larval striped bass, Morone saxatilis (Walbaum). Journal of Fish Diseases 7(1): 15–27.

Costantini M, SA Ludsin, DM Mason, X Zhang, WC Boicourt, SB Brandt. 2008. Effect of hypoxia on habitat quality of striped bass (Morone saxatilis) in Chesapeake Bay. Canadian Journal of Fisheries and Aquatic Sciences 65(5): 989–1002.

Coutant CC. 1985. Striped bass, temperature, and dissolved oxygen: a speculative hypothesis for environmental risk. Transactions of the American Fishery Society 114: 31–61.

Craig JK, LB Crowder. 2005. Hypoxia-induced habitat shifts and energetic consequences in Atlantic croaker and brown shrimp on the Gulf of Mexico shelf. Marine Ecology Progress Series 294: 79–94.

137

Craig JK, SH Bosman. 2013. Small spatial scale variation in fish assemblage structure in the vicinity of the northwestern Gulf of Mexico hypoxic zone. Estuaries and coasts 36(2): 268–285.

Crunkilton RL, JM Czarnezki, L Trial. 1980. Severe gas bubble disease in a warmwater fishery in the Midwestern United States. Transactions of the American Fisheries Society 109(6): 725–733.

Dagg MJ,GA Breed. 2003. Biological effects of Mississippi River nitrogen on the northern Gulf of Mexico—a review and synthesis. Journal of Marine Systems 43(3): 133–152.

Diaz RJ, R Rosenberg. 2008. Spreading dead zones and consequences for marine ecosystems. Science 321(5891): 926–929.

DiMarco SF, P Chapman, ND Walker, RD Hetland. 2010. Does local topography control Hypoxia on the eastern Texas-Louisiana shelf? Journal of Marine Systems 80(1–2): 25– 35.

Dinnel SP, WJ Wiseman Jr. 1986. Fresh-water on the Louisiana and Texas shelf. Continental Shelf Research 6(6): 765–784.

Dortch Q, ML Parsons, NN Rabalais, RE Turner. 1999. What is the threat of harmful algal blooms in Louisiana coastal waters." Recent research in coastal Louisiana: Natural system function and response to human influences (1999): 1–11.

Eby LA. 2001. Response of a Fish Community to Frequent and Infrequent Disturbances in Estuarine Ecosystems.

Eby LA, LB Crowder. 2002. Hypoxia-based habitat compression in the Neuse River Estuary: context-dependent shifts in behavioral avoidance thresholds. Canadian Journal of Fisheries and Aquatic Science 59: 952–965.

Elliott DT, JJ Pierson, MR Roman. 2012. Relationship between environmental conditions and zooplankton community structure during summer hypoxia in the northern Gulf of Mexico. Journal of plankton research 34(7): 602–613.

Elliott M, V Quintino. 2007. The estuarine quality paradox, environmental homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas. Marine Pollution Bulletin 54(6): 640–645.

138

Emerson S, PD Quay, C Stump, D Wilbur, R Schudlich. 1995. Chemical tracers of productivity and respiration in the subtropical Pacific Ocean. Journal of Geophysical Research 100: 15873–15887.

Gallaway BJ, GS Lewbel. 1982. Ecology of petroleum platforms in the northwestern Gulf of Mexico: a community profile (No. FWS/OBS-82/27). LGL Ecological Research Associates, Inc., Bryan, TX (USA).

Gorham FP. 1899. Some physiological effects of reduced pressure on fish. Journal of the Boston Society of Medical Sciences 3(9): 250.

Gray RH, JM Haynes. 1977. Depth distribution of adult chinook salmon (Oncorhynchus tshawytscha) in relation to season and gas-supersaturated water. Transactions of the American Fisheries Society 106(6): 617–620.

Günter G. 1956. Some relations of faunal distributions to salinity in estuarine waters. Ecology 616–619.

Hazen EL, JK Craig, CP Good, LB Crowder. 2009. Vertical distribution of fish biomass in hypoxic waters on the Gulf of Mexico shelf. Marine Ecology Progress Series 375: 195– 207.

Hetland RD, SF DiMarco. 2008. The effects of bottom oxygen demand in controlling the structure of hypoxia on the Texas-Louisiana continental shelf. Journal of Marine Systems 70: 49–62.

Hurlbert SH. 1981. A gentle depilation of the niche: Dicean resource sets in resource hyperspace. Evolutionary Theory 5: 177–184.

Hurlbert SH. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54(2): 187–211.

Justić D, NN Rabalais, RE Turner, Q Dortch. 1995. Changes in nutrient structure of river- dominated coastal waters: stoichiometric nutrient balance and its consequences. Estuarine, Coastal and Shelf Science 40(3): 339–356.

139

Justić D, NN Rabalais, RE Turner, WJ Wiseman. 1993. Seasonal coupling between riverborne nutrients, net productivity and hypoxia. Marine Pollution Bulletin 26(4): 184–189.

Keister JE, ED Houde, DL Breitburg. 2000. Effects of bottom-layer hypoxia on abundances and depth distributions of organisms in Patuxent River, Chesapeake Bay. Marine Ecology Progress Series 205: 43–59.

Kramer DL. 1987. Dissolved oxygen and fish behavior. Environmental Biology of Fishes: 18(2): 81–92.

Landsberg JH. (2002). The effects of harmful algal blooms on aquatic organisms. Reviews in Fisheries Science 10(2): 113–390.

Livingston RJ. 1988. Inadequacy of species-level designations for ecological studies of coastal migratory fishes. Environmental Biology of Fishes 22: 225–234.

Marsh MC, FP Gorham. 1905. The gas disease in fishes.

Milliman JD, RH Meade. 1983. World-wide delivery of river sediment to the oceans. The Journal of Geology 1–21.

Nebeker AV, JD Andros, JK McCrady, DG Stevens. 1978. Survival of steelhead trout (Salmo gairdneri) eggs, embryos, and fry in air-supersaturated water. Journal of the Fisheries Board of Canada 35(2): 261–264.

Obenour DR, D Scavia, NN Rabalais, RE Turner, AM Michalak. 2013. Retrospective analysis of midsummer hypoxic area and volume in the northern Gulf of Mexico, 1985–2011. Environmental science & technology 47(17): 9808–9815.

Officer CB, JH Ryther. 1980. The possible importance of silicon in marine eutrophication. Marine Ecology Progress Series 3(1): 83–91.

Parker NC, MA Suttle, K Fitzmayer. 1984. Total gas pressure and oxygen and nitrogen saturation in warm water ponds aerated with airlift pumps. Aquacultural engineering 3(2): 91–102.

Parker RO Jr, DR Colby, TD Willis. 1983. Estimated amount of reef habitat on a portion of the US South Atlantic and Gulf of Mexico continental shelf. Bulletin of Marine Science 33(4): 935–940.

Pihl L, SP Baden, RJ Diaz. 1991. Effects of periodic hypoxia on distribution of demersal fish and crustaceans. Marine Biology 108(3): 349–360.

Pihl, L. (1994). Changes in the diet of demersal fish due to eutrophication-induced hypoxia in the Kattegat, Sweden. Canadian Journal of Fisheries and Aquatic Sciences 51(2): 321–336.

140

Pokryfki L, RE Randall. 1987. Nearshore hypoxia in the bottom water of the northwestern Gulf of Mexico from 1981 to 1984. Marine Environmental Research 22(1): 75–90.

Prince ED, CP Goodyear. 2006. Hypoxia‐based habitat compression of tropical pelagic fishes. Fisheries Oceanography 15(6): 451–464.

Rabalais NN, DE Harper, RE Turner. 2001. Responses of nekton and demersal and benthic fauna to decreasing oxygen concentrations. Coastal hypoxia: consequences for living resources and ecosystems 115–128.

Rabalais NN, RE Turner, D Justić, Q Dortch, WJ Wiseman, BKS Gupta. 1996. Nutrient changes in the Mississippi River and system responses on the adjacent continental shelf. Estuaries 19(2), 386–407.

Rabalais NN, RE Turner, WJ Wiseman Jr. 2002. Gulf of Mexico hypoxia, A.K.A. “the Dead Zone.” Annual Review of Ecology and Systematics 33: 235–263.

Redfield AC. 1958. The biological control of chemical factors in the environment. American scientist 230A–221.

Remmert H. 1983. Studies and thoughts about the zonation along the rocky shores of the Baltic. Zoologica 22: 121–125.

Renfro WC. 1963. Gas-bubble mortality of fishes in Galveston Bay, Texas. Transactions of the American Fisheries Society 92(3): 320–322.

Roman MR, JJ Pierson, DG Kimmel, WC Boicourt, X Zhang. 2012. Impacts of hypoxia on zooplankton spatial distributions in the northern Gulf of Mexico. Estuaries and coasts 35(5): 1261–1269. 141

Schurmann H, JF Steffensen. 1992. Lethal oxygen levels at different temperatures and the preferred temperature during hypoxia of the Atlantic cod, Gadus morhua L. Journal of Fish Biology 41(6): 927–934.

Switzer TS, Chesney EJ, DM Baltz. 2015. Habitat Use by Juvenile Red Snapper in the Northern Gulf of Mexico: Ontogeny, Seasonality, and the Effects of Hypoxia. Transactions of the American Fisheries Society 144(2): 300–314.

Turner RE, N Qureshi, NN Rabalais, Q Dortch, D Justić, RF Shaw, J Cope. 1998. Fluctuating silicate: nitrate ratios and coastal plankton food webs. Proceedings of the National Academy of Sciences 95(22): 13048–13051.

Turner RE, NN Rabalais. 1991. Changes in the Mississippi River water quality this century. Bioscience 41: 140–147.

Vaquer-Sunyer R, CM Duarte. 2008. Thresholds of hypoxia for marine biodiversity. Proceedings of the National Academy of Science USA 105(40):15452–15457.

Wiseman WJ, JM Bane, SP Murray, MW Tubman. 1976. Small-scale temperature and salinity structure over the inner shelf west of the Mississippi River delta. Coastal Studies Institute, Center for Wetland Resources, Louisiana State University.

Wiseman WJ, NN Rabalais, RE Turner, SP Dinnel, A MacNaughton. 1997. Seasonal and interannual variability within the Louisiana coastal current: stratification and hypoxia. Journal of Marine Systems 12: 237–48. 142

Wiseman WJ Jr, SP Murray, JM Bane, MW Tubman. 1982. Temperature and salinity variability within the Louisiana Bight. Contributions in Marine Science 25: 109–20.

Willis TJ, RC Babcock. 2000. A baited underwater video system for the determination of relative density of carnivorous reef fish. Marine and Freshwater Research 51(8): 755– 763.

Woodbury LA. 1942. A sudden mortality of fishes accompanying a supersaturation of oxygen in Lake Waubesa, Wisconsin. Transactions of the American Fisheries Society 71(1): 112– 117.

Zhang H, SA Ludsin, DM Mason, AT Adamack, SB Brandt, X Zhang, DG Kimmel, MR Roman, WC Boicourt. 2009. Hypoxia-driven changes in the behavior and spatial distribution of pelagic fish and mesozooplankton in the northern Gulf of Mexico. Journal of Experimental Marine Biology and Ecology 381: S80–S91.

Zhang H, DM Mason, CA Stow, AT Adamack, SB Brandt, Z Zhang, DG Kimmel, MR Roman, WC Boicourt, SA Ludsin. 2014. Effects of hypoxia on habitat quality of pelagic planktivorous fishes in the northern Gulf of Mexico. Marine Ecology Progress Series 505: 209226.

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CHAPTER V: SUMMARY AND CONCLUSIONS

Oil and gas platforms (platforms) are 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 study opportunity by enabling detailed 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 northern Gulf of Mexico (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 platforms are rapidly being removed, are they being evaluated. Therefore, this study has addressed a gap in understanding an important element of the world’s largest artificial reef network that will foster future management. 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 coastal zone.

Based on this study, 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

144 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 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. 2014), 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 of 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 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.

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Salinity, temperature, dissolved oxygen (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 < 50% DO saturation.

Global expansion of coastal hypoxia is occurring due to overpopulation and 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,

146 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

Kendell 1994; SEDAR 2013). The majority of fish 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 (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)—which would include all of the fishes observed throughout this study—explosive removal results in a rash loss of life that is representative of a much larger area of occupancy for some species. 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 1960’s (BOEM 2015), 18 platform removals have used explosives (US

Department of the Interior 2015). Considering the presence of goliath grouper in the area, and the strong association this species has with complex artificial structure (NMFS 2006; Porch and

147

Eklund 2004; Collins 2015) it is fortunate that this ratio is relatively low. Given the current pace of structure removal coastwide, it might not be long before the platforms of East Bay are also removed. In the case of East Bay, it is in the interest of the critically endangered (International

Union for the Conservation of Nature 1994) and currently recovering (NMFS 2006) goliath grouper that non-explosive removal methods be used when decommissioning platforms.

The untraditional approach of this study offered a new perspective on the ecosystem services provided by the oil and gas platforms 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. Eutrophic effects on DO likely drive biological interactions with every aspect of the environment, including the unexpected avoidance of surface blooms by fishes. The dynamic hydrography 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 progress the understanding of the

148 interactions among the various physical, chemical, and geological elements of this system and how they relate to the biology of the environments within it.

In addition to the fish they attract, small nearshore platforms also serve as roosts and resting sites for birds (Aumann 1981; Figure 5.1). 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 in 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.

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”.

—Gallaway and Cole (1998)

Figure 5.1. Magnificent frigatebirds (Fregata magnificens) atop a well protector in the South Pass 28 block. 149

References

Able KW. 2005. A re-examination of fish estuarine dependence: evidence for connectivity between estuarine and ocean habitats. Estuarine, Coastal and Shelf Science 64(1): 5–17.

Aumann GD. 1981. The effect of structures on migratory and local marine birds. Environmental Effects of Offshore Oil Production, Springer US 209–221.

Boswell KM, RJ Wells, JH Cowan Jr, CA Wilson. 2010. Biomass, density, and size distributions of fishes associated with a large-scale artificial reef complex in the Gulf of Mexico. Bulletin of Marine Science 86(4): 879–889.

Bureau of Ocean Energy Management (BOEM). 2015. Platform structures online query. http://www.data.boem.gov/homepg/data_center/platform/platform/master.asp. Accessed November 09, 2015.

Childs J. 1998. Avian diversity and habitat use within the Flower Garden Banks National Marine Sanctuary. Gulf of Mexico Science 16: 208–225.

Kaiser MJ, DV Mesyanzhinov, AG Pulsipher. 2002. Explosive removals of offshore structures in the Gulf of Mexico. Ocean & coastal management 45(8): 459–483.

McNair DB. 2000. The Status of magnificent frigatebirds in the interior of Florida: the influence of storms. North American Birds 54: 11–15.

National Marine Fisheries Service (NMFS). 2006. Status report on the continental United States distinct population segment of the goliath grouper (Epinephelus itajara). January 12, 2006. 49 pp

Porch CE, AM Eklund. 2004. Standardized visual counts of Goliath Grouper off south Florida and their possible use as indices of abundance. Gulf of Mexico Science 2: 155–163.

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Schofield PJ, DH Huge, TC Rezek, JA Morris Jr. 2014. Survival and growth of invasive Indo Pacific lionfish at low salinities.

SEDAR 2013. SEDAR 31-Gulf of Mexico Red Snapper Stock Assessment Report. SEDAR, North Charleston SC 1103

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VITA

Ryan Munnelly is from the island community of Nantucket, Massachusetts. There he learned how to clam and fish for bluefish, scup, squid, and sand sharks, and volunteered with the UMass

Boston field station doing harbor monitoring work with Dr. Sarah Oktay and Matt Liddle. He graduated from Nantucket High School in 2007, and earned a bachelor’s degree in marine biology from the University of North Carolina, Wilmington in 2011. In Wilmington he was involved with several projects, including: tropical fish culture with Dr. Ileana Clavijo, surf-zone work related to fish and infaunal assemblages along nourished and unnourished barrier islands with Dr. Tom Lankford, comparisons of fish and fouling assemblages and condition metrics associated with natural and created oyster reefs with Dr. Martin Posey and Troy Alphin, volunteer fish husbandry work with the Fort Fisher Aquarium, and a variety of monitoring projects with the North Carolina Division of Marine Fisheries. Post-graduation, Ryan worked as an inshore gillnet fishery observer obtaining bycatch data for the North Carolina Division of

Marine Fisheries, and continued to volunteer with the Division’s Artificial Reef Program. In

2013 Ryan was accepted into the Oceanography and Coastal Sciences program at Louisiana

State University for the work presented here, under the duel advisorship of Dr. Don Baltz and

Dr. Ed Chesney. Ryan is a candidate to receive a master’s degree in May of 2016, and is looking forward to starting a new aquarium.

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An afterthought from August

The ozone layer was fighting off the aliens and free radicals for us.

Slipping through a flip-book day fishing the rigs.

Bird rain from the cotton sky ripples my eyes as they skip across the sea.

Ten miles south of Terrebonne Bay, the navigation horns were sounding.

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